Digital camera 'fingerprinting' developed

April 19, 2006

Child pornographers will soon have a harder time escaping prosecution thanks to a stunning new technology in development at Binghamton University, State University of New York, that can reliably link digital images to the camera with which they were taken, in much the same way that tell-tale scratches are used by forensic examiners to link bullets to the gun that fired them.

"The defense in these kind of cases would often be that the images were not taken by this person's camera or that the images are not of real children," said Jessica Fridrich, associate professor of electrical and computer engineering. "Sometimes child pornographers will even cut and paste an image of an adult's head on the image of a child to try to avoid prosecution.

"But if it can be shown that the original images were taken by the person's cell phone or camera, it becomes a much stronger case than if you just have a bunch of digital images that we all know are notoriously easy to manipulate."

Fridrich and two members of her Binghamton University research team – Jan Lukas and Miroslav Goljan – are coinventors of the new technique, which can also be used to detect forged images.

The three have applied for two patents related to their technique, which provides the most robust strategy for digital image forgery detection to date, even as it improves significantly on the accuracy of other approaches.

Fridrich's technique is rooted in the discovery by her research group of this simple fact: Every original digital picture is overlaid by a weak noise-like pattern of pixel-to-pixel non-uniformity.

Although these patterns are invisible to the human eye, the unique reference pattern or "fingerprint" of any camera can be electronically extracted by analyzing a number of images taken by a single camera.

That means that as long as examiners have either the camera that took the image or multiple images they know were taken by the same camera, an algorithm developed by Fridrich and her co-inventors to extract and define the camera's unique pattern of pixel-to-pixel non-uniformity can be used to provide important information about the origins and authenticity of a single image.

The limitation of the technique is that it requires either the camera or multiple images taken by the same camera, and isn't informative if only a single image is available for analysis.

Like actual fingerprints, the digital "noise" in original images is stochastic in nature – that is, it contains random variables – which are inevitably created during the manufacturing process of the camera and its sensors. This virtually ensures that the noise imposed on the digital images from any particular camera will be consistent from one image to the next, even while it is distinctly different.

In preliminary tests, Fridrich's lab analyzed 2,700 pictures taken by nine digital cameras and with 100 percent accuracy linked individual images with the camera that took them.

Fridrich, who specializes in all aspects of information hiding in digital imagery, including watermarking for authentication, tamper detection, self-embedding, robust watermarking, steganography and steganalysis, as well as forensic analysis of digital images, says it is the absence of the expected digital fingerprint in any portion of an image that provides the most conclusive evidence of image tampering.

In the near future, Fridrich's technique promises to find application in the analysis of scanned and video imagery. There it can be expected to make life more difficult for forgers, or any others whose criminal pursuits rely on the misuse of digital images.

"We already know law enforcement wants to be able to use this," Fridrich said. "What we have right now is a research tool; it's a raw technology that we will continue to improve."

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The joint Task Group on clinical utility of labelled antibodies of the Society of Nuclear Medicine Europa (SNME) and the European Nuclear Medicine Society (ENMS).
In September 1985 a task group on the clinical utility of labelled antibodies was founded by the Society of Nuclear Medicine - Europe. This document was elaborated to report the aims and the programs of the group. In September 1986 the European Nuclear Medicine Society decided to participate in this initiative and a joint task group was created. INITIAL DOCUMENT: A. The aims to the Task Group are to monitor, co-ordinate and promote research and clinical application of techniques using radiolabelled antibodies in nuclear medicine. A.1. The Group should develop into a major point of reference, giving scientific and technical support to each member of the Society involved in this field. B. To pursue these purposes it will be necessary to develop the following: B.1. Criteria to evaluate the suitability of antigen-antibody systems for tumour detection and/or therapy. B.2. Criteria for quality control of radioimmunoreagents. B.3. Criteria for the prevention of adverse reactions or damage due to the reagent. B.4. Selection of suitable dosimetric methods for diagnostic or therapeutic applications. B.5. Elaboration of protocols for clinical experiments, including appropriate techniques to be applied in single cases. B.6. Organization of cooperative studies. C. The Task Group should promote: C.1. Informal meetings between the members of the Group. C.2. Workshops open to the members of the Society and other researchers. C.3. Publication of reports in appropriate journals.


FROM  ubuntu:14.04

RUN apt-get update && apt-get install -y \
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RUN   mkdir /apps
COPY  . /apps/html

RUN   mv /etc/nginx/nginx.conf /etc/nginx/nginx.conf_original && mv /apps/html/nginx.conf /etc/nginx/nginx.conf

WORKDIR /apps/html

EXPOSE 8888
CMD    ["nginx"]


About Us

Formed in 1980 by a group of residents, the Society aims to preserve and provide access to materials covering the history of Dangar Island from its earliest days through to today.

The Guringai people, also known as Eora, were custodians of the area around the Island for at least 30,000 years. The Island’s first recorded visit by Europeans was in 1788 by Captain (later Governor) Arthur Phillip when it was called Mullet Island due to the abundance of fish.

Henry Dangar purchased the Island in 1864, when it became known as Dangar’s Island. The Island served as the base for building the Hawkesbury River Railway Bridge completed in 1889. This Bridge played a key role in the movement of men and materials in the defence of Australia during World War 2.

Since then the Island has developed as a weekend destination and residential suburb with minimal vehicles and abundant peace amongst the trees.

The Society holds material covering the history of the Island, including oral history and photographs. Our work includes digitizing and archiving these materials, and proudly showing them to anyone who is interested in our unique story. We are currently working on the production of an updated historical guide to Dangar Island which will be available for purchase by residents and visitors.

Note: The Society no longer hosts walking tours of the island.

The Society was relaunched in 2013 and is registered under the Office of Fair Trading (Number INC1300153).

We are affiliated with the Royal Australian Historical Society.
For RAHS events please follow the link below:www.rahs.org.au/events


1. Introduction {#Sec1}
===============

Orexigen® Therapeutics is developing a proprietary fixed-dose combination of naltrexone sustained release (SR) and bupropion SR in a single tri-layer tablet, for the treatment of obesity. The tablet contains naltrexone SR 32 mg and bupropion SR 360 mg. The product it is awaiting approval in the US. In addition, the combination has been tested in an open-label phase II study for smoking withdrawal in overweight or obese subjects.

Naltrexone is an opioid receptor antagonist marketed in the US for the treatment of narcotic and alcohol dependency, while bupropion is a dopamine and norepinephrine reuptake inhibitor prescribed as an antidepressant and smoking cessation aid. In combination, the agents are thought to stimulate proopiomelanocortin (POMC) neuronal firing and modulate food cravings through an effect on the reward pathways. The naltrexone/bupropion formulation, known as Contrave®, is designed to initiate weight loss and sustain it over a longer period of time by switching off natural compensatory mechanisms involved in the typical weight loss plateau stage.

1.1 Company Agreements {#Sec2}
----------------------

In June 2009, Orexigen secured from GlaxoSmithKline non-exclusive rights to certain formulation patents related to bupropion in exchange for undisclosed upfront and future milestone payments.\[[@CR1]\]

1.2 Key Development Milestones {#Sec3}
------------------------------

### 1.2.1 Obesity {#Sec4}

In March 2010, Orexigen submitted an NDA for approval of naltrexone SR/bupropion SR (Contrave®) for the treatment of obesity in the US. The new drug application (NDA) comprises data from the Contrave Obesity Research (COR) clinical program in more than 4500 patients.\[[@CR2]\]

The COR program included four randomized, double-blind, placebo-controlled, phase III trials COR-I (NB-301), COR-II (NB-303), COR-Diabetes (NB-304) and COR-BMOD (NB-302).

The phase III NB-302 trial (NCT00456521) has been completed, with an enrollment of 793 obese patients. The trial assessed the safety and efficacy of naltrexone 32 /bupropion 360 mg dosed daily for 56 weeks. Patients were randomized 3 : 1 to active therapy (Contrave® plus behavior modification protocol) or behavior modification plus placebo. In January 2009, Orexigen reported that the trial had met its co-primary and key secondary endpoints, with a significant reduction in bodyweight, reductions in selected food craving measures and improvements in markers of cardiovascular risk.\[[@CR3]--[@CR5]\] Additional secondary findings were presented in June 2009.\[[@CR6]\]

All three remaining phase III trials of naltrexone SR/bupropion SR (NB-301, NB-303 and NB-304) have met their co-primary endpoints.\[[@CR7]\]

In April 2008, patient enrollment was completed in a phase III study (NB-301; NCT00532779) in 1650 patients in 34 centers in the US. This multicenter, randomized, double-blind, placebo-controlled study compared the safety and efficacy of two doses of naltrexone SR/bupropion SR (16 /360 mg and 32 /360 mg, respectively) for 56 weeks.\[[@CR4]\]

Orexigen completed a phase III study (NB-304; NCT00474630) evaluating the safety and efficacy of the product over 56 weeks in 525 patients with obesity and type 2 diabetes. The study enrolled patients at 51 centers in the US.\[[@CR5],[@CR8]\]

Patient enrollment of 1500 patients in a phase III trial (NB-303; NCT00567255) was completed in May 2008 at 36 centers in the US. This 56-week study was designed to blind re-randomization of any product recipients who have not responded at week 28 to receive either higher doses of the product or continue on the original dose.\[[@CR8],[@CR9]\]

A phase IIb trial (NB201) of bupropion SR/naltrexone immediate release (IR) in 419 patients with uncomplicated obesity was completed by Orexigen in March 2007. The multicenter, randomized, double-blind study assessed the safety, tolerability and efficacy of three different dosages of naltrexone (16, 32 or 48 mg/day) combined with a single dosage of bupropion (400 mg/day), compared with either agent alone or placebo. The protocol for this study permitted patients to continue receiving naltrexone/bupropion for an additional 24 weeks of open-label treatment. Results from the completed study were presented by Orexigen in October 2007.\[[@CR10],[@CR11]\]

Results from a phase II trial of naltrexone/bupropion in 206 patients with obesity were reported by Orexigen in June 2006. The multicentre study evaluated the efficacy of naltrexone IR/bupropion SR treatment in combination with a minimal diet and exercise program, compared with monotherapy or placebo. The company used a refined formulation and optimal dose ratio of naltrexone/bupropion in its ongoing phase II/III clinical program.\[[@CR12]\]

### 1.2.2 Smoking Withdrawal {#Sec5}

Results from an open-label phase II study (NB-401, NCT00563563) of the combination of naltrexone plus bupropion in 30 overweight or obese smokers have been released.\[[@CR13]\]

1.3 Patent Information {#Sec6}
----------------------

The United States Patent and Trademark Office (USPTO) issued a fourth patent on naltrexone/bupropion in January 2009. The patent (no. 7 462 626) is known as the Weber/Cowley methods patent and will provide protection for Contrave® through mid 2024. It is a companion to the Weber/Cowley composition patent.\[[@CR14]\]

In May 2008, Orexigen was granted the Weber/Cowley composition-of-matter patent (No. 7 375 111) entitled *Compositions for affecting weight loss* covering broad claims on the active constituents in Contrave® until March 2025.\[[@CR15],[@CR16]\]

The USPTO also issued a Notice of Allowance to Orexigen's patient application for what the company refers to as the "Weber/Cowley methods patent" (no. 121/356 839) providing coverage for methods of treating obesity with combinations of naltrexone and bupropion. When issued, this US patent will provide protection for Contrave® through mid 2024.\[[@CR17]\]

Previously, the USPTO issued a US patent (no. 5 817 665) entitled *Composition and method of treating depression using naloxone or naltrexone in combination with a serotonin reuptake inhibitor* covering the use of various combinations of weight-loss promoting anti-depressants with opioid antagonists including naltrexone. The patent covers any use of these combinations and not limited to weight loss. The US patent was awarded to Dr Lee Dante, and was exclusively licensed by Orexigen® Therapeutics.\[[@CR18]\]

The European Patent Office has granted Orexigen a patent covering compositions and uses of bupropion and naltrexone for affecting weight loss. The European patent once validated in individual countries will provide exclusive rights to this combination in those countries until 2024.\[[@CR19]\]

2. Scientific Summary {#Sec7}
=====================

2.1 Pharmacokinetics {#Sec8}
--------------------

In a phase I trial in 40 healthy obese volunteers, the maximum concentration (C~max~) value of naltrexone SR was reduced by approximately 25% compared with the naltrexone IR formulation, while retaining approximately 99% of the area under the concentration-time curve (AUC) value. The SR formulation also had a greater time to C~max~ (t~max~) value compared with the IR formulation (approximately 36 minutes). A reduction in C~max~ and similar AUC values were observed in an additional phase I trial. A total of 60 obese volunteers in this study were randomized to receive bupropion SR with either naltrexone SR or IR.\[[@CR20],[@CR21]\]

2.2 Adverse Events {#Sec9}
------------------

### 2.2.1 Obesity {#Sec10}

***Phase III***: In the phase III NB-302 trial, naltrexone/bupropion was generally well tolerated. A total of 793 obese patients were randomized to naltrexone/bupropion plus behavior modification or placebo plus behavior modification. The safety profile of the drug was consistent with those of the individual components. No increases in symptoms of depression or suicidality were reported, and mean blood pressure did not worsen. The overall discontinuation rate due to adverse events was 25.9% for patients receiving naltrexone/bupropion vs 13.0% for placebo. The most frequent causes of discontinuation were nausea, urticaria and anxiety. Discontinuation due to nausea was 4.6%. The most frequent adverse events occurring in mild to moderate severity were nausea (34.1% naltrexone/bupropion vs 10.5% placebo), headache (23.8% vs 17.5%) and constipation (24.1% vs 14.0%). The most frequent psychiatric adverse events reported were insomnia (8.7% NB vs 6.0% placebo), anxiety (5.1% vs 3.5%), sleep disorder (2.4% vs 3.0%) and depressed mood (1.9% vs 4.0%). Two serious adverse event cases of cholecystitis were reported in the naltrexone/bupropion arm. Naltrexone/bupropion did not worsen psychiatric symptoms, as assessed by the change in Inventory for Depressive Symptoms-Self-Rated (IDS-SR) total score. The study drug was composed of naltrexone 32 /bupropion 360 mg, and dosed daily for 56 weeks.\[[@CR3],[@CR22]\]

Preliminary analysis of a 24-week blinded data in 3934 evaluable patients showed lower rates of nausea across the four pooled phase III trials compared with pooled 24-week data from the phase IIb (NB-201) trial. The overall rate of early discontinuation due to any adverse events was lower in phase III trials compared with the phase IIB trial data (13.8% vs 16.0%, respectively). Only 7.6% of all reported adverse events led to an early discontinuation in phase III trials.\[[@CR20]\]

![Features and properties](40268_2012_10010025_Tab1){#Tab1}

![Drug development history](40268_2012_10010025_Tab2){#Tab2}

***Phase II***: There were no serious adverse events related to naltrexone/bupropion treatment in a phase IIb trial (NB-201) in 419 patients with obesity. The study assessed three different dosages of naltrexone (16, 32 or 48 mg/day) combined with a single dosage of bupropion (400 mg/day), compared with either agent alone or placebo. The naltrexone 32 /bupropion 400 mg group experienced the lowest rate of discontinuation due to adverse events, at just under 16%. The most common adverse event was nausea which typically occurred on initial drug exposure and was transient and mild. Discontinuations due to nausea through 24 weeks were substantially lower in the naltrexone 32 /bupropion 400 mg group (7.9%) than in the naltrexone 48 mg/bupropion 400 mg group (18.0%). Other adverse events included headache, dizziness and insomnia. There was also no evidence to suggest that naltrexone/bupropion treatment had an adverse effect on vital signs including blood pressure, pulse, electrocardiogram (ECG) intervals, laboratory evaluations or on a scale evaluating depression.\[[@CR10],[@CR11]\]

***Phase I***: In a phase I trial in 40 healthy obese volunteers, fewer participants receiving naltrexone SR experienced ≥1 adverse event, compared with participants receiving naltrexone IR. In another phase I study in 60 obese volunteers, naltrexone SR was associated with fewer gastrointestinal (GI), CNS and other adverse events, compared with volunteers in the naltrexone IR group (GI: 10.3% vs 16.7%, CNS: 10.3% vs 23.3%, respectively). The rate of participants experiencing ≥2 concurrently occurring adverse events was also lower in the naltrexone SR group.\[[@CR20],[@CR21]\]

### 2.2.2 Smoking Withdrawal {#Sec11}

Transient, mild to moderate nausea, insomnia, and constipation are the most the most common adverse events associated with naltrexone plus bupropion in a 24-week open-label study in overweight or obese smokers (n = 30).\[[@CR13]\]

2.3 Pharmacodynamics {#Sec12}
--------------------

### 2.3.1 Obesity {#Sec13}

***Phase III***: In the phase III NB-302 trial, patients receiving naltrexone SR/bupropion SR experienced significant improvements over placebo, in high density lipoprotein (HDL), triglycerides and high sensitivity C-reactive protein (hsCRP), markers of cardiovascular risk. A total of 793 obese patients were randomized to naltrexone SR/bupropion SR plus behavior modification (counseling, diet and exercise) or placebo plus behavior modification. The study drug was composed of naltrexone 32 /bupropion 360 mg, and dosed daily for 56 weeks.\[[@CR3]\]

***Preclinical studies***: In a preclinical study in lean mice, treatment with bupropion, naltrexone or a combination of both agents resulted in food intake reductions of 34%, 67% and 77%, respectively. In obese mice, treatment with bupropion, naltrexone or a combination of both agents resulted in food intake reductions of 27%, 49% and 94%, respectively. A separate study demonstrated that administration of naltrexone plus bupropion to the ventral tegmental area (VTA) was associated with a significant and synergistic reduction of food intake.\[[@CR23]\]

2.4 Therapeutic Trials {#Sec14}
----------------------

### 2.4.1 Drug Withdrawal {#Sec15}

In a 24-week, open-label study, combination therapy with naltrexone and bupropion plus behavioral counseling decreased nicotine use and limited nicotine withdrawal symptoms while preventing weight gain in overweight or obese smokers (n = 30). A total of 48% and 41% of subjects were continuously abstinent from smoking from week 4 through weeks 12 and 24 (primary endpoint). Nicotine withdrawal scores remained unchanged, except a significant increase on week 5. A total of 78% and 74% of subjects had 10 ppm CO at weeks 12 and 24, respectively. Tobacco use decreased from 129 to 15 and 18 cigarettes/week at weeks 12 and 24, respectively.\[[@CR13]\]

### 2.4.2 Obesity {#Sec16}

***Phase III***: Three phase III trials of 32 mg naltrexone/360 mg bupropion (NB-301, NB-303, NB-304) have met their co-primary endpoints (n = 4500). Naltrexone/bupropion produced a weight loss of 6.1%, 6.4, and 5% in these trials compared to 1.3%, 1.2% and 1.8% with placebo, respectively; 48%, 56.3% and 44.5% of patients lost ≥5% of weight with naltrexone/bupropion compared to 16.4%, 17.1% and 18.9% with placebo, respectively; naltrexone/bupropion reduced glycosylated hemoglobin (HbA~1C~) by 0.6% compared with 0.1% by placebo in NB-304; patients with a HbA~1C~ of \>8% taking naltrexone/bupropion experienced a mean reduction of 1.1%, which was significantly greater than placebo. In all cases, the difference was significant (p \< 0.001, intent-to-treat population). Naltrexone/bupropion also significantly improved cardiovascular and metabolic risk factors, such as waist circumference, visceral fat, HDL cholesterol and triglycerides. Patients receiving naltrexone/bupropion also experienced reductions in the frequency and strength of food cravings and an increased ability to control their eating compared with placebo.\[[@CR7],[@CR24]\]

![Forecasts](40268_2012_10010025_Tab3){#Tab3}

The phase III NB-302 trial met its co-primary and key secondary endpoints, with a significant reduction in bodyweight and reductions in selected food craving measures. Naltrexone/bupropion produced placebo-subtracted weight loss of up to 4.7% at 6 months in obese patients. A total of 793 obese patients were randomized to naltrexone/bupropion plus behavior modification (counseling, diet and exercise) or placebo plus behavior modification. At 56 weeks, change in bodyweight was −9.29 ± 0.40% for naltrexone/bupropion (n = 482) and −5.08 ± 0.60% for placebo (n = 193) \[p \< 0.001\]. More patients treated with naltrexone/bupropion achieved bodyweight loss of ≥5% (66.4% naltrexone/bupropion vs 42.5% placebo), ≥10% (41.5% vs 20.2%) and ≥15% (29.1% vs 10.9%); all results were significant (p \< 0.001). Waist circumference also decreased significantly from baseline in patients on active treatment, compared with placebo. Those on active treatment also demonstrated improvements in quality of life, as measured by the Impact of Weight on Quality of Life-Lite total scores (−16.65 for naltrexone/bupropion vs −12.77 for placebo, p \< 0.001). The study drug was composed of naltrexone 32 /bupropion 360 mg, and dosed daily for 56 weeks. Additional secondary data from this trial showed that patients receiving naltrexone/bupropion had significant improvements in eating control and overall quality of life compared with placebo recipients, improved physical function and self-esteem that occurred early in treatment and maintained over 1 year.\[[@CR3],[@CR25]\] Additional secondary data from this trial showed that patients receiving naltrexone SR/bupropion SR had significant improvements in eating control and overall quality of life compared with placebo recipients, improved physical function and self-esteem that occurred early in treatment and maintained over 1 year.\[[@CR6]\]

***Phase II***: In a phase IIb trial (NB-201) of naltrexone IR/bupropion SR in 419 patients with obesity, optimal treatment results were observed in the naltrexone 32 /bupropion 400 mg dose group. The study assessed three different dosages of naltrexone (16, 32 or 48 mg/day) combined with a single dosage of bupropion (400 mg/day), compared with either agent alone or placebo. Compared with the placebo and monotherapy groups, patients in the naltrexone 32 /bupropion 400 mg group demonstrated significantly greater improvements in fasting glucose and insulin resistance, as evaluated by the quantitative insulin-sensitivity check index (QUICKI) and log (HOMA) measurements. Significant improvements were also observed when compared with at least one of the control groups in waist circumference, insulin, triglycerides and homeostatic model assessment of insulin resistance (HOMA). In a subset of patients who had a DEXA scan or abdominal CAT scan at baseline and week 24, the mean reduction in visceral fat ranged from 13.7% to 16% across all naltrexone/bupropion groups, compared with a 0.1% to 4.6% mean reduction for patients receiving either of the monotherapies of placebo. At 48 weeks, weight loss from baseline bodyweight across the three naltrexone/bupropion groups ranged from 5.0% to 6.6% (last observation carried forward analysis) and from 8.0% to 10.7% (completer analysis). Additionally, patients experiencing a clinical response at 24 weeks continued to lose additional weight through 48 weeks.\[[@CR5],[@CR10],[@CR11],[@CR26]--[@CR28]\]

A review of data from a phase IIb study showed that in patients who completed 24 weeks of treatment with naltrexone IR/bupropion SR, the percentage of patients with metabolic syndrome decreased from 31% to 15% (p \< 0.05).Among patients in the placebo group, the percentage of patients with metabolic syndrome decreased from 38% to 30%. There were also evident improvements in key markers of metabolic and cardiovascular disease.\[[@CR29]\]

In an earlier phase II trial, naltrexone/bupropion treatment was associated with a greater weight loss over 6 months, compared with either monotherapy or placebo. More than 50% of patients completing the trial demonstrated 5% weight loss over 24 weeks, while 18% of patients demonstrated 10% weight loss. Additionally, the trajectory of these weight loss curves showed no evidence of a plateau.\[[@CR12]\]


A multivariable analysis of clinical factors predicting for pathological features associated with local failure after radical prostatectomy for prostate cancer.
A multivariate analysis is used to determine the predictive value of pretreatment clinical indicators on pathologic features associated with local failure after radical prostatectomy in patients with prostate cancer. A retrospective review of the pathologic findings of 235 patients with adenocarcinoma of the prostate treated between 1990 and 1993 with a radical retropubic prostatectomy was performed. The preoperative clinical data including the serum prostate specific antigen, clinical stage, Gleason sum, and endorectal magnetic resonance scan findings are used to identify patients prior to definitive treatment who would be at high risk for having pathologic features associated with local failure at radical prostatectomy. Outcome prediction curves are constructed from a logistic regression multivariate analysis displaying the probability of pathologic involvement of the seminal vesicle, extracapsular disease, or positive surgical margins as a function of the preoperative prostate specific antigen and Gleason sum for the cases when the endorectal magnetic resonance scan is positive, negative, or not included in the multivariate analysis. Factors identified on multivariate analysis as significant predictors of seminal vesicle invasion include endorectal magnetic resonance scan findings (p < 0.0001), and preoperative prostate specific antigen (p = 0.017). Endorectal magnetic resonance scan findings (p = 0.0016), preoperative prostate specific antigen (p = 0.0002), and Gleason sum (p < 0.0001) were significant predictors of extracapsular extension and preoperative prostate specific antigen (p < 0.0001) and Gleason sum (p = 0.03) were significant predictors of disease extending to the margins of resection. Clinical stage was not a significant predictor (p > 0.05) of pathologic features associated with local failure on multivariate analysis. As a single modality, endorectal surface coil magnetic resonance imaging was accurate 93%, 69%, and 72% of the time for predicting seminal vesicle invasion, transcapsular disease, and final pathologic stage, respectively. Failure to recognize microscopic penetration of the capsule found at the time of pathologic evaluation in a prostate gland with a grossly intact capsule accounts for the majority (70%) of the staging inaccuracies. The use of the endorectal surface coil magnetic resonance scan findings in conjunction with both the serum prostate specific antigen and Gleason sum improves the clinical accuracy of predicting those patients at high risk for clinically unsuspected extraprostatic disease. In particular, for the subgroup of patients with moderately elevated prostate specific antigen (> 10-20 ng/mL) and intermediate grade clinically organ confined prostate cancer [Gleason sum: 5-7] where the specificity of these tests to predict for occult extraprostatic disease is suboptimal, the additional information obtained from the endorectal coil magnetic resonance scan allows the physician to definitively subgroup these patients into low and high risk for seminal vesicle invasion or transcapsular disease.


Reynaldo Dagsa

Reynaldo Dagsa (1975 – January 1, 2011) was a Filipino politician. A member of the Barangay Peacekeeping Action Team, he served as councilman for Barangay 35 in Maypajo, Caloocan until his assassination in 2011. He was also a corporal in the Philippine Army Reserve Command.

Assassination and photo
His death achieved notoriety due to his taking of a New Year's Day family photo on Tuna Street which inadvertently captured the faces of both his killer and a lookout for the killer; the shooter, a convicted robber out on parole, pointed the gun in the photo directly at Dagsa seconds before the shot went off. Dagsa was rushed to Martinez Hospital but was immediately pronounced dead from a .45-caliber gunshot wound to the head. The photo was later turned over to Caloocan city police; the shooter in the photo was identified as Arnel Buenaflor, who was arrested on January 7, and two suspected accomplices, one Michael Gonzales (alias Fubo of Fish Pond Area I) and Rommel Oliva (alias Balong), were arrested by January 3 in connection with the murder. Buenaflor was charged with murder by Assistant City Prosecutor Darwin G. Canete after inquest. Buenaflor, a member of the Pasaway Gang, claimed to have shot Dagsa in retribution for being shot in the head by persons associated with Dagsa during a shootout months earlier, while police attributed a motive to Dagsa's peacekeeping efforts in the barangay.

References

Category:People from Caloocan
Category:1975 births
Category:2011 deaths
Category:Assassinated Filipino politicians
Category:Deaths by firearm in the Philippines
Category:Filipino military personnel
Category:Metro Manila city and municipal councilors


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<section xmlns="https://code.dccouncil.us/schemas/dc-library" xmlns:codified="https://code.dccouncil.us/schemas/codified" xmlns:codify="https://code.dccouncil.us/schemas/codify" xmlns:xi="http://www.w3.org/2001/XInclude" containing-doc="D.C. Code">
  <num>44-103.05</num>
  <heading>Changes in licensee.</heading>
  <para>
    <num>(a)</num>
    <text>The following changes occurring within an ALR shall require revision of the license:</text>
    <para>
      <num>(1)</num>
      <text>Change in the maximum number of residents for which the facility is licensed;</text>
    </para>
    <para>
      <num>(2)</num>
      <text>Name change of the ALR;</text>
    </para>
    <para>
      <num>(3)</num>
      <text>Change in ownership of the ALR;</text>
    </para>
    <para>
      <num>(4)</num>
      <text>Change in location of the ALR; or</text>
    </para>
    <para>
      <num>(5)</num>
      <text>Voluntary closure of the ALR.</text>
    </para>
  </para>
  <para>
    <num>(b)</num>
    <text>A request for changes which requires the reissuance of a license shall be made in writing to the Mayor at least 60 days in advance of the effectiveness of the changes. An application fee, as established by the Mayor, shall accompany a request for changes.</text>
  </para>
  <para>
    <num>(c)</num>
    <para>
      <num>(1)</num>
      <text>The licensee shall notify residents and their surrogates of any proposed changes set forth in its request for changes, in writing, 60 days before the effective date of the proposed changes.</text>
    </para>
    <para>
      <num>(2)</num>
      <text>A licensee shall include the following information in its request for changes:</text>
      <para>
        <num>(A)</num>
        <text>The method for informing residents and their surrogates of its intent to make the requested changes; and</text>
      </para>
      <para>
        <num>(B)</num>
        <text>The actions the licensee shall take to assist residents in securing comparable housing, if necessary.</text>
      </para>
    </para>
  </para>
  <para>
    <num>(d)</num>
    <para>
      <num>(1)</num>
      <text>Whenever there is a change of ownership, sale, assignment, or other transfer of an ALR from the person or organization named on the license to another person or organization, the transferee shall apply for a new license.</text>
    </para>
    <para>
      <num>(2)</num>
      <text>A transferee shall apply for a new license at least 60 days before the final transfer.</text>
    </para>
    <para>
      <num>(3)</num>
      <text>The licensee named under the current license shall remain responsible for the operation of the ALR until a new license is issued to the transferee.</text>
    </para>
    <para>
      <num>(4)</num>
      <text>The Mayor shall issue a new license to the transferee if the transferee meets the requirements for licensure under this chapter. Upon issuance of the new license to the transferee, the transferor shall return its license to the Mayor by certified mail.</text>
    </para>
  </para>
  <annotations>
    <annotation doc="D.C. Law 13-127" type="History" path="§305">June 24, 2000, D.C. Law 13-127, § 305, 47 DCR 2647</annotation>
  </annotations>
</section>


Iraqi forces have managed to find and liberate 500 Iraqis held hostage by the ISIS terrorists in a hospital in western Mosul, north of Iraq.

Media sources say Iraqi popular forces have released 500 Iraqis held captive by the ISIS terrorists in a basement in al-Jomhouri hospital in the west of the northern Iraqi city of Mosul.

Most of the prisoners have caught scabies due to the Takfiri terrorists’ deliberate negligence in providing them with the very basic living necessities and facilities.

Previously known as the seven-year itch, scabies is a contagious skin infestation transmitted by the mite Sarcoptes scabiei (also known as the itch mite).

The itch mite is a parasitic arthropod that burrows into skin and causes scabies. It looks like the tick but a lot smaller and can be seen only under a microscope.

Scabies is the most common skin diseases in the world. The most common symptoms of the disease are severe itchiness and a pimple-like rash. The itch is caused by the secretions from the parasite’s body.

Occasionally, tiny burrows may be seen in the skin. When first infected, usually two to six weeks are required before symptoms occur. If a person develops a second infection later in life, symptoms may begin within a day.

Al-Jomhouri hospital was among the medical centres seized by the ISIS. Prior to the Iraqi forces’ recapture of the hospital, the terrorists used to keep the injured in it.


Puffy-esque Story Planned for Law & Order

May 3

Television crime drama Law & Order is well-known for drawing inspiration from the headlines of New York papers — but the show's writers didn't dig too deeply in the archive for their latest idea.

According to Foxnews, a new episode will feature a "black hip-hop star with his own clothing line, who has a Park Avenue townhouse and a place in the Hamptons." What's more, the show will be about a shooting at a nightclub where the star — whose name is Darryl "G-Trane" Collins — is partying with his girlfriend, named Allie Tejada, described as a "20s, Latina, rising star."

Of course, any resemblance to the recent legal drama of rap mogul Sean "Puff Daddy/P. Diddy" Combs and his former girlfriend Jennifer Lopez is purely coincidental.

The episode, titled "3 Dawg Night," is set to begin filming the week of May 7, though it's not scheduled to air until this fall, according to Foxnews. Casting for the episode is underway.

Combs' reps told the New York Post that the story was "pure entertainment" that "doesn't affect him."

Of course, Combs and Co. must be pleased that in the episode — just as in the March court finding — the rap star in question has nothing to do with the shooting.

The show may be more galling to Lopez — the Latina character in the episode reportedly pulls the trigger at the nightclub.


A Critical Look at Prebiotics Within the Dietary Fiber Concept.
This article reviews the current knowledge of the health effects of dietary fiber and prebiotics and establishes the position of prebiotics within the broader context of dietary fiber. Although the positive health effects of specific fibers on defecation, reduction of postprandial glycemic response, and maintenance of normal blood cholesterol levels are generally accepted, other presumed health benefits of dietary fibers are still debated. There is evidence that specific dietary fibers improve the integrity of the epithelial layer of the intestines, increase the resistance against pathogenic colonization, reduce the risk of developing colorectal cancer, increase mineral absorption, and have a positive impact on the immune system, but these effects are neither generally acknowledged nor completely understood. Many of the latter effects are thought to be particularly elicited by prebiotics. Although the prebiotic concept evolved significantly during the past two decades, the line between prebiotics and nonprebiotic dietary fiber remains vague. Nevertheless, scientific evidence demonstrating the health-promoting potential of prebiotics continues to accumulate and suggests that prebiotic fibers have their rightful place in a healthy diet.


1. Field of the Invention
The present invention relates generally to an apparatus and method for power control in a mobile communication system, and more particularly, to an apparatus and method for flexibly changing a fixed target Signal-to-Interference Ratio (SIR), a fixed target SIR step, and a time to perform a transmission (TX) power control request, in order to prevent a receiver apparatus from performing an excessive TX power control request in the event of a sudden reception (RX) channel environment change.
2. Description of the Related Art
In a mobile communication system, when an output power of a Mobile Station (MS) is high, this often causes interference with an adjacent MS. The adjacent MS detects a noise of the interference, and increases its output power in order to increase an SIR (or a Signal-to-Noise Ratio (SNR)). Consequently, the mobile communication system maintains the same output power level of adjacent MSs to control the data TX power of a transmitter.
Directly controlling the TX power of a mobile communication system as described above is referred to as an inner loop power control, and setting the range of the inner loop power control is referred to as an outer loop power control.
The above-described TX power control method is applicable to a Base Station (BS) controlling the output power of an MS, and to an MS controlling the output power of a BS.
In Wideband Code Division Multiple Access (CDMA), for TX power control, a receiver apparatus uses a BLock Error Rate (BLER) satisfying a Quality of Service (QoS). This ensures that data of an RX transport block is received at a certain level. The receiver apparatus measures the BLER of the current channel, determines whether to control the TX power of a transmitter, and requests the transmitter apparatus to increase/decrease its TX power accordingly.
The receiver apparatus uses the SIR of an RX channel to detect a channel BLER. More specifically, the receiver apparatus measures the SIR of an RX channel and sets a target SIR satisfying a desired BLER of the receiver apparatus.
Thereafter, if the SIR of the current RX channel is smaller than the target SIR, the receiver apparatus transmits a Transmission Power Control (TPC) Up request to the transmitter apparatus. However, if the SIR of the current RX channel is greater than the target SIR, the receiver apparatus transmits a TPC Down request to the transmitter apparatus, thereby adjusting the BLER of a RX Dedicated Channel (DCH).
The receiver apparatus may detect the occurrence or nonoccurrence of a transport block error at every Transmission Time Interval (TTI) to set the target SIR.
For example, after detecting the occurrence of a transport block error, the receiver apparatus adds an SIR Step Up size to the current target SIR to set the next target SIR (Next_Target_SIR=Current_Target_SIR+SIR_Step_Up). After detecting the nonoccurrence of a transport block error, the receiver apparatus subtracts an SIR Step Down size from the current target SIR to set the next target SIR (Next_Target_SIR=Current_Target_SIR−SIR_Step_Down). Herein, the SIR Step Down size is the product of the SIR Step Up size and the BLER (SIR_Step_Down=SIR_Step_Up×BLER).
As described above, the target SIR is not fixed, but varies depending on the channel environment. However, in the event of a sudden channel environment change, a sudden Additive White Gaussian Noise (AWGN) decrease, a sudden channel fading change, or a BS output power decrease or increase, a receiver apparatus will request an excessive output power of a transmitter apparatus in order to satisfy the BLER.


---
abstract: 'We use the method of Press, Rybicki & Hewitt (1992) to search for time lags and time leads between different energy bands of the RXTE data for MCG–6-30-15. We tailor our search in order to probe any reverberation signatures of the fluorescent iron K$\alpha$ line that is thought to arise from the inner regions of the black hole accretion disk. In essence, an optimal reconstruction algorithm is applied to the continuum band (2–4keV) light curve which smoothes out noise and interpolates across the data gaps. The reconstructed continuum band light curve can then be folded through trial transfer functions in an attempt to find lags or leads between the continuum band and the iron line band (5–7keV). We find reduced fractional variability in the line band. The spectral analysis of Lee et al. (1999) reveals this to be due to a combination of an apparently constant iron line flux (at least on timescales of ${\rm few}\times 10^4\s$), and flux correlated changes in the photon index. We also find no evidence for iron line reverberation and exclude reverberation delays in the range 0.5–50ksec. This extends the conclusions of Lee et al. and suggests that the iron line flux remains constant on timescales as short as 0.5ksec. The large black hole mass ($>10^8\Msun$) naively suggested by the constancy of the iron line flux is rejected on other grounds. We suggest that the black hole in MCG–6-30-15 has a mass of $M_{\rm BH}\sim 10^6-10^7\Msun$ and that changes in the ionization state of the disk may produce the puzzling spectral variability. Finally, it is found that the 8–15keV band lags the 2–4keV band by 50–100s. This result is used to place constraints on the size and geometry of the Comptonizing medium responsible for the hard X-ray power-law in this AGN.'
author:
- 'Christopher S. Reynolds'
title: |
    On the lack of X-ray iron line reverberation in MCG–6-30-15:\
    Implications for the black hole mass and accretion disk structure
---

\#1[to 0pt[\#1]{}]{} \#1 \#1

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\#1 =cmr10 scaled2 =cmbx10 scaled2 =cmti10 scaled2 PS.

[galaxies:Seyfert, galaxies:individual:MCG–6-30-15, line:formation, methods:statistical, X-ray:galaxies]{}

Introduction
============

The X-rays from active galactic nuclei (AGN) are thought to originate from the innermost regions of an accretion disk around a central supermassive black hole. Thus, in principle, the study of these X-rays should allow one to probe the immediate environment of the accreting black hole as well as the exotic physics, including strong-field general relativity, that operates in this environment.

In the past decade X-ray astronomy has begun to fulfill that promise. Both [*EXOSAT*]{} and [*Ginga*]{} discovered iron K-shell features (including the K$\alpha$ fluorescent line of cold iron at 6.4keV) in the X-ray spectra of Seyfert galaxies which were interpreted as ‘reflection’ of the primary X-ray continuum by cold, optically-thick material in the immediate vicinity of the black hole (Guilbert & Rees 1988; Lightman & White 1988; Nandra et al. 1989; Nandra, Pounds & Stewart 1990; Matsuoka et al. 1990). It was suggested that this cold reflecting material was the putative accretion disk of AGN models. With the launch of [*ASCA*]{} and the advent of medium resolution spectroscopy, the iron line in several objects was shown to be broad ($\sim 80\,000\kmps$ FWZI) and skewed (Tanaka et al. 1995; Nandra et al. 1997). The overall line profiles are in good agreement with models for fluorescent line emission from the innermost regions of geometrically-thin black hole accretion disks (Fabian et al. 1989). Such data allow us to address issues such as the location of the radius of marginal stability, the spin of the black hole, and the inclination distribution of various classes of AGN (see Reynolds 1999 and references therein for a review of these studies). In the current, [*RXTE*]{} era, we can now probe the iron line and Compton reflection hump in individual objects in some detail (e.g., MCG-5-23-16, Weaver et al. 1998; MCG–6-30-15, Lee et al. 1998, 1999a; NGC 5548, Chiang et al. 1999).

While these spectral studies have been successful, a complete picture of the AGN phenomenon is not possible without addressing the timing properties. Timing studies are important for two intertwined reasons. Firstly, AGN are [*inherently*]{} variable systems. In general, the variability timescale in a given object is seen to shorten as one considers higher frequency radiation. In the X-ray and $\gamma$-ray bands, dramatic variability has been seen in many Seyfert galaxies with doubling timescales of only a few minutes (e.g. see Reynolds et al. 1995). Although it is poorly understood to date, the nature of this violent variability is a vital component of any final AGN model. Careful characterization of the timing properties, as well as determining the observed spectral evolution during dramatic temporal events, is required if we are to understand this phenomenon.

Secondly, timing studies are needed to break certain degeneracies that exist in models which, to date, have only been constrained by purely spectral data. The spin of the black hole in MCG–6-30-15 provides an excellent example of such a degeneracy — by fitting the ‘very-broad’ state (Iwasawa et al. 1996) of the iron line in this object with models consisting of a thin, disk-hugging corona, Dabrowski et al. (1997) inferred that the black hole in this AGN must be almost maximally rotating, with a dimensionless spin parameter of $a>0.94$. However, by including line emission from within the radius of marginal stability, Reynolds & Begelman (1997) showed that a geometry in which the X-ray source is at some height above the disk plane can produce the same line profile even if the black hole is completely non-rotating. While there are subtle spectral differences between the two scenarios (Young, Ross & Fabian 1998) the most obvious way of distinguishing these scenarios is through their timing properties. The Reynolds & Begelman (1997) geometry predicts substantial time delays between fluctuations in the primary power-law continuum and the responding fluctuations in the iron line. More generally, the reverberation characteristics of the iron line contain tremendous information on the mass and spin of the black hole as well as the geometry of the X-ray source (Stella 1990; Reynolds et al. 1999).

The observational situation is more complex. Lee et al. (1999b) and Chiang et al. (1999) have analyzed extensive [*RXTE*]{} datasets for MCG–6-30-15 and NGC 5548, respectively, in order to study the timing properties and spectral variability. In both of these objects, the same pattern of spectral variability is seen. Firstly, the X-ray photon index displays flux-correlated changes in the sense that the source is softer when it is brighter. Secondly, and more surprisingly, the iron line flux was found to be constant over the timescales probed by these direct spectral studies ($\sim 50-500$ksec). As discussed by both sets of authors, these results are difficult to interpret in the framework of standard X-ray reflection models since the breadth of these lines indicate that they originate from a small region. It appears that some feedback mechanism regulates the amount of iron line emission in order to produce approximately constant iron line flux. Flux-correlated changes in the ionization state of the disk represent one such mechanism (we discuss this in more detail in Section 5 of this paper). Unless this feedback mechanism operates instantaneously, we might still expect variability of the iron line flux on short timescales.

Driven by these motivations, this paper addresses the problem of determining causal relationships between light curves in different X-ray bands, with particular emphasis on timescales shorter than those that can be probed by direct spectroscopy. In particular, we use the long [*RXTE*]{} observation of the bright Seyfert 1 galaxy MCG–6-30-15 reported by Lee et al. (1999a,b) and consider the relationship between the 2–4keV band (hereafter called the continuum band) and the 5–7keV band which contains most of the iron line photons (and hereafter called the line band). An important special case is one in which there is a linear transfer function relating one band to the other: $$b(t)=\int_{-\infty}^{\infty}d\tau\, \Psi(\tau) a(t-\tau),$$ where $a(t)$ and $b(t)$ are continuum and line band fluxes respectively, and $\Psi$ is the transfer function. Such relationships between bands contain much of the important physical information, such as the reverberation characteristics of the iron line.

Mathematically, the linear transfer equation can be easily inverted using Fourier methods to obtain, $$\Psi(t)=\frac{1}{2\pi}\int^{\infty}_{-\infty}d\omega\,e^{-i\omega t}\frac{\tilde
{a}(\omega)}{\tilde{b}(\omega)},$$ where $\tilde{a}(\omega)$ represents the Fourier transform of $a(t)$. However, in real situations, a large number of regularly sampled measurements are required to obtain an accurate deconvolution using this simple method. More often, deconvolution is achieved using maximum entropy techniques or some other regularization method (Horne et al. 1991; Krolik et al. 1991).

Another common approach (and one that is often used with less well sampled data) is to compute cross-correlation functions (CCFs), or some variant thereof which accounts for the finite and irregular sampling often encountered in real data. The discrete correlation function (DCF; Edelson & Krolik 1988) is one example of such a variant. Lee et al. (1999b) apply such methods to the observation of MCG–6-30-15 considered in this paper and detect both phase and time lags between [*RXTE*]{} bands (also see Nowak & Chiang 1999). While these methods are powerful, it can be difficult to separate subtle time leads/lags from the autocorrelation properties of the data.

Here, we take an alternative approach which is heavily based on the method of Press, Rybicki & Hewitt (1992; hereafter PRH92). In essence, we use the correlation properties of the continuum band data to reconstruct an optimal continuum light curve in which the data gaps have been interpolated. Most importantly, we also compute the expected deviation of the continuum flux from the interpolated curve. The reconstructed continuum band light curve is convolved with a trial transfer function and compared with the line band light curve in a $\chi^2$ sense. We then examine changes in the $\chi^2$ statistic as a function of the parameters that define the trial transfer function.

Section 2 recaps the PRH92 method. This is then applied to the [*RXTE*]{} data for MCG–6-30-15 in Section 3. The robustness and validity of our approach is demonstrated by applying this method to simulated data (Section 4). Section 5 draws together our results and discusses their implications for the nature of this source. In particular, we argue that the black hole in this AGN has a mass of only $10^6-10^7\Msun$. In order to explain the spectral variability, it is suggested that there are flux correlated changes in the ionization state of the surface layers of the accretion disk. Section 6 presents a short summary of the results and relevant astrophysical implications.

The problem and method of solution
==================================

The optimal reconstruction
--------------------------

The continuum band light curve is reconstructed from the data using the technique of PRH92. For completeness, this section summarizes their method. The reader who is primarily interested in the application of this method may skip to Section 3.

Suppose that the true flux of the source at time $t$ is $s(t)$, but we measure $y(t)=s(t)+n(t)$, where $n(t)$ is the noise in the measurement. In our case, the noise is Poisson in nature. Our knowledge of $s(t)$ is further impeded by the fact that the measurement is only made at a finite number of times $t_i$, where $i=1,...,N$. We denote $y(t_i)$ as $y_i$ and refer to this as the continuum data vector.

We seek an optimal reconstruction of $s(t)$ which is continuous in time, $\hat{s}(t)$, such that $$\langle e^2(t)\rangle\equiv \langle[\hat{s}(t)-s(t)]^2\rangle$$ is minimized for all $t$. As usual, angle brackets denote the expectation value. We impose that $\hat{s}(t)$ is linear in the data vector in the sense that $$\hat{s}(t)=\sum^{N}_{i=1}q_i(t)y_i,$$ where $q_i(t)$ are a set of inverse response functions that are also continuous in time.

Assuming that the noise is uncorrelated with both $s(t)$ and itself, PRH92 showed that eqn (3) can be minimized to yield, $$\hat{s}(t)=\sum^{N}_{i,j=1}\langle s(t_i)s(t)\rangle(B^{-1})_{ij}\,y_j.$$ Here, $$B_{ij}=\langle s(t_i)s(t_j)\rangle+\langle n_i^2\rangle \delta_{ij}$$ is the total covariance matrix. To keep the notation concise, PRH92 define the correlation statistics: $$\begin{aligned}
c_i&\equiv &\langle s(t_i)s(t)\rangle\\
C_{ij}&\equiv & \langle s(t_i)s(t_j)\rangle\\
{\cal C}(t)&\equiv & \langle s(t)s(t)\rangle\end{aligned}$$ These functions define what PRH92 call the ‘covariance model’. The expected variance of the real signal from the optimal reconstruct in eqn (5) is then given by $$\langle e^2(t)\rangle={\cal C}(t)-\sum^{N}_{i,j=1}c_i(t)(B^{-1})_{ij}c_j(t).$$

Once the covariance model is known, eqns (5) and (10) define the optimal reconstruction of the continuum light curve together with a statistic measuring the expected deviation of the real signal from the reconstruction.

The covariance model
--------------------

Here, again, we follow the method of PRH92 to determine the covariance model for our continuum data. At this stage, we make the assumption that the underlying process is statistically stationary so that $$\langle s(t_1)s(t_2)\rangle=\langle s(0)s(t_2-t_1)\rangle=C(t_2-t_1),$$ where $C(\tau)$ is the autocorrelation function that we have to determine. This function is related to the first order structure function $V(\tau)$ by $$C(\tau)=\langle s^2 \rangle - V(\tau),$$ and $V(\tau)$ can be approximated by forming pair-wise estimates for all distinct pairs of data points in the continuum light curve, and then binning by the time lag of the pairs. We find that the analytic form $$V_{\rm anal}(\tau)=A\left(\frac{(\tau/\tau_0)^{\alpha_1}}{1+(\tau/\tau_0)^{\alpha_1}}\right)^{\alpha_2}$$ fits the structure functions of this paper well. In fact, the reconstruction is fairly insensitive to the exact analytic form used to approximate the structure function.

Making the reasonable assumption that $C(\tau)\rightarrow \langle
s\rangle^2$ as $\tau\rightarrow\infty$, our final expression for the autocorrelation function is $$C(\tau)=\langle s\rangle^2 + V_{\rm anal}(\infty)-V_{\rm anal}(\tau).$$

Application to MCG–6-30-15
==========================

In this Section, we apply the method outlined above to a long [*RXTE*]{} observation of the bright Seyfert 1 galaxy MCG–6-30-15.

The RXTE data
-------------

[*RXTE*]{} observed MCG–6-30-15 for approximately $7\times 10^5\s$ starting on 4-Aug-1997. We retrieved these data from the NASA-[heasarc]{} public archive situated at the Goddard Space Flight Center. Our data reduction closely parallels that of Lee et al. (1999a) who has studied the spectral characteristics of this observation. Since, as mentioned in the introduction, we are interested in the soft X-ray continuum and the iron line band, the Proportional Counter Array (PCA) is the appropriate instrument for us to consider. Examining the housekeeping files for this observation reveals that Proportional Counter Units (PCUs) 3 and 4 suffer occasional breakdown and shut off. Hence, we do not consider data from these units and, instead, extracted [standard-2]{} data from PCUs 0–2. We applied fairly standard faint-source screening criteria to these data: the source must be at least $10\degmark$ above the Earth’s limb ([elv]{}$>$10), the source must be located within $0.02\degmark$ of the nominal pointing position ([offset]{}$<$0.02), there must be at least three PCUs on ([num\_pcu\_on]{}$>$2), it has been at least 30 minutes since a passage of the South Atlantic Anomaly ([time\_since\_saa]{}$>$30), and the electron background is not too high ([electron0]{}$<$0.1). After application of these screening criteria, approximately $3.5\times 10^5\s$ of ‘good’ data remain. From these data, 2–4keV and 5–7keV light curves were extracted using 64s bins. We also extracted the 8–15keV light curve which we will use in Section 3.3.

The background was estimated using the L7-240 background models which are appropriate for faint sources such as AGN. Background light curves were computed and subtracted from the measured light curves in order to form the final background subtracted light curves that we shall use in our study. Figure 1 shows the continuum band (2–4keV) light curves that results from this procedure. For clarity, the light curve shown in this figure has been binned with 256s bins.

Searching for lags and leads
----------------------------

We now apply the procedure outlined in Section 2 to these lightcurves. To begin with, we must estimate the structure function for these data. Figure 2a shows a pair-wise estimate of the continuum band structure function obtained following the method of PRH92. This figure also shows our analytic approximation which is given by eqns (13) and (14) with $$\begin{aligned}
A&=&1.757\,{\rm cps}\\
\tau_0&=&2.117\times 10^3\s\\
\alpha_1&=&3.805\\
\alpha_2&=&0.195\\
\langle s\rangle&=&3.91\,{\rm cps}\end{aligned}$$ Using this covariance model, the PRH92 reconstruction was applied to the continuum light curve using $N=5000$ data points. A portion of the resulting reconstructed light curve is shown in Fig. 2b.

The next stage in the procedure is to convolve the reconstructed continuum band light curve with a trial transfer function and compare the result with the line band light curve in a $\chi^2$ sense. We can then minimize the $\chi^2$ statistic in order to constrain free parameters in the trial transfer function. We also minimize $\chi^2$ over multiplicative and additive offsets between the continuum and line band light curves, i.e. we set $$b(t)=B\int_{-\infty}^{+\infty}\psi(\tau) a(t-\tau)\,d\tau + K,$$ and minimize over $B$ and $K$ as well as the parameters describing the trial transfer function $\psi$.

In this work, we choose two trial transfer functions. The first represents the case where some fraction $f_{\rm tr}$ of the line band flux is a delayed copy of the continuum band with a time delay $t_{\rm
tr}$: $$\psi_1(t)= (1-f_{\rm tr})\delta(t)+f_{\rm tr}\delta(t-t_{\rm tr}).$$ The second represents the case where some fraction $f_{\rm tr}$ of the line band flux is a delayed and smeared copy of the continuum band flux, where a Gaussian kernel is used: $$\psi_2(t)= (1-f_{\rm tr})\delta(t)+\frac{f_{\rm tr}}{\sigma_{\rm tr}}\sqrt{\frac{2}{\pi}}\exp\left( -\frac{(t-t_{\rm tr})^2}{2\sigma_{\rm tr}^2}\right),$$

No extrapolations were performed during this procedure. In order to avoid extrapolating, the $\chi^2$ statistic was calculated using a subset of data points. For the trial transfer function $\psi_1$, only data during times $t_{\rm start}+t_{\rm tr,max}<t<t_{\rm end}-t_{\rm
tr,max}$ were used to compute $\chi^2$, where $t_{\rm start}$ and $t_{\rm end}$ are the times of the start and end of the reconstructed continuum light curve. For $\psi_2$, $\chi^2$ is computed based upon data from times $t_{\rm start}+t_{\rm tr,max}+2\sigma_{\rm
tr,max}<t<t_{\rm end}-t_{\rm tr,max}-2\sigma_{\rm tr,max}$.

Figure 3 shows the $\chi^2$ surfaces and confidence contours once this procedure has been performed. When displaying the $\chi^2$ surfaces, we plot $\log_{10}(\chi^2-\chi^2_{\rm min}+1)$ in order to highlight the topography of the surface near the global minimum in the surface. It can be seen that the minimum of the $\chi$2 surface corresponds to the two lines $f_{\rm tr}=0$ and $t_{\rm tr}=0$, i.e. no time delayed component of the line band light curve is detected. Here we only show the results for $\psi_1$ — the $\psi_2$ results are trivial (i.e. $\chi^2$ surface is completely flat) since the preferred solution always have $f_{\rm tr}=0$. The best fit values of the multiplicative and additive constants are $B=0.78$ and $K=0.90$.

The overall time delays between bands
-------------------------------------

By considering the $f_{\rm tr}=1$ slice through the $\chi^2$ surface produced with trial transfer function $\psi_1$, we can examine [*overall*]{} lags and leads between energy bands. Examining the 2–4keV and 5–7keV light curves for MCG–6-30-15 in this way, we find that the $\chi^2$ slice possesses a minimum at zero lag — i.e. we find no evidence for overall time lags or leads between the continuum and line bands down to 64s, the bin size of the data. Performing the same procedure for the 2–4keV and 8–15keV light curves reveals a one bin offset in the position of the minimum (Fig. 4), indicating that the 8–15keV light curve is delayed by $\sim $50–100s as compared with the 2–4keV light curve.

Lee et al. (1999b) have applied CCF methods to this [*RXTE*]{} dataset. By carefully comparing with simulations, they find evidence that the 7.5–10keV band lags the lower energy bands with a [*phase delay*]{} of $\phi\sim 0.6$. They also find evidence that the hard band (10–20keV) lags the softer bands with a [*time delay*]{} similar to that found in this work. Figure 5 shows the DCF for our 2–4keV and 8–15keV lightcurves (this is very similar to Fig. 17 of Lee et al. 1999b). A small time lag of 50–100s between these two bands is evident. Thus, CCF methods and the optimal reconstruction method both suggest a time lag of 50–100s between the 2–4keV and 8–15keV bands.

The meaning of an additive offset
---------------------------------

Our fitting in Section 3.2 clearly reveals the need for an additive offset (i.e. non-zero $K$ value) between the line and continuum band light curves. In other words, the fractional variability about the mean level is less in the line band that it is in the continuum band.

The spectral analysis of Lee et al. (1999b) allows this behaviour to be understood in terms of the spectral phenomenology. Firstly, Lee et al. found that on timescales of ${\rm few}\times 10$ksec, the iron line flux does not track the continuum flux and, instead, remains approximately constant. Secondly, it was found that there are flux correlated changes in the photon index by as much as $\Delta
\Gamma\approx 0.2$ in the sense that higher flux states are softer. Both of these spectral changes will tend to reduce variability in the line band as compared with the (softer) continuum band.

Applications to simulations
===========================

Constructing the simulated light curves
---------------------------------------

In order to assess the significance and robustness of the above results, this section describes the application of this method to simulations. We tailor our simulation to match the [*RXTE*]{} observation MCG–6-30-15 as much as possible. [*EXOSAT*]{} showed that the high frequency fluctuations of MCG–6-30-15 possess a power spectrum of the form $f^{-1.36}$. We use this power spectrum with an additional low-frequency cutoff at $f_c=10^{-6}\Hz$: $$P(f)=\left(\frac{1}{1+(f/f_c)}\right)^\alpha.$$ We then make a (noiseless) simulated continuum light curve, $F(t)$, by summing Fourier components of random phase between $f_{\rm min}=10^{-7}\Hz$ and $f_{\rm max}=1\Hz$, i.e. $$F(t)=\int^{f_{\rm max}}_{f_{\rm min}}df\,P(f)\sin[2\pi\,f\,t-\phi(f)]$$ where $\phi(f)$ is a uniformly randomly distributed in the range $0$ to $2\pi$ for each distinct value of $f$.

Without loss of generality, we assume that the line band flux possesses the same mean normalization as the continuum band light curve. However, in order to mimic the situation found in Section 3 as closely as possible, we assume that there is an additive offset between the continuum band and line band light curves as well as the convolution a transfer function. In other words we compute a (noiseless) line-band light curve using the expression: $$b(t)=(1-f)\Lambda\,a(t)+f\int_{-\infty}^{+\infty}d\tau\Psi_{1,nzl}(\tau)a(t-\tau)+K.$$ Here, $\Psi_{1,nzl}$ is the non-zero-lag component of our imposed simulated transfer function for which we use a Gaussian: $$\Psi_{1,nzl}={\sigma}\sqrt{\frac{2}{\pi}}\exp \left( -
\frac{(t-t_0)^2}{2\sigma^2}\right)$$ where $f$ is the fraction of the continuum flux that is delayed, $t_0$ is the mean time delay, and $\sigma$ is the temporal standard-width of the smearing. For concreteness, we set $$\begin{aligned}
\Lambda&=&0.75\\
f&=&0.15\\
K&=&0.85\\
t_0&=&1.0\times 10^4\s\\
\sigma&=&2.0\times 10^3\s.\end{aligned}$$ This value of $f$ is approximately the fraction of the line-band flux which originates from the iron line, and hence this simulation crudely mimics the effect of iron line reverberation with a $10^4\s$ time delay. Our value of $K$ is set to be similar that found for MCG–6-30-15 above.

From these ‘perfect’ noiseless light curves, we formed Possion sampled noisy light curves assuming a mean count rate of 4cps in both the continuum and line bands, and using 64s bins. The datagap structure of the real MCG–6-30-15 dataset was then imposed on the simulated light curves.

We now examine our realistic, simulated, data in order to assess how well we can detect the existence of the imposed lag and recover the properties of $\Psi_{1,nzl}$ using our method.

Extracting the lag from the simulations
---------------------------------------

We use the method of Section 2.1 and 2.2 to form an optimally reconstructed, evenly-sampled continuum lightcurve. The covariance model used is given by eqn (13) and (14) with $$\begin{aligned}
A&=&2.5\,{\rm cps}\\
\tau_0&=&6.23\times 10^3\s\\
\alpha_1&=&0.855\\
\alpha_2&=&1\\
\langle s\rangle&=&3.63\,{\rm cps}\end{aligned}$$ A total of $N=3000$ simulated data points were used to form the reconstruction which spans a simulated observation time of 400000s. A portion of the simulated dataset and its reconstruction are presented in Fig. 6. Note how well the reconstruction algorithm recovers the real signal during the times with data, and brackets the real signal during other times.

Figure 7 presents the $\chi^2$ surfaces and confidence contours that result from passing the simulated light curves through the trial transfer functions $\psi_1$ and $\psi_2$, including minimization over any additive offset between the continuum and line band light curves. Both trial transfer functions clearly detect the imposed lag in so far as a a deep and isolated hole is present in the $\chi^2$ surface at approximately the right time delay, delay fraction and delay width. Note that the $f_{\rm tr}$ dimension, which has been suppressed in the $\psi_2$ plots, has a value of $f_{\rm tr}=0.16$ at the global minimum. This demonstrates the power of this technique for finding and characterizing subtle time lags or leads that are present in such data.

Discussion
==========

In order to bring structure to the discussion that follows, we will summarize the pertinent results from this paper.

1.  We clearly see reduced fractional variability in the iron line band (5–7keV) as compared with the continuum band (2–4keV). This is the origin of the additive offset, $K$, that was introduced in Section 3. The spectral fitting results of Lee et al. (1999b) suggests that this is due to a combination of a constant iron line flux and flux correlated changes in the photon index.

2.  Our analysis finds no evidence for iron line reverberation effects. By running a number of simulations, we find that any reverberation time delays must be less than $\sim 500\s$ or greater than $\sim 50$ks. Together with the above result, this suggests an approximately constant iron line flux over these timescales. Thus, we can extend the work of Lee et al. (1999b) and infer a constant iron line on timescales down to $0.5$ksec.

3.  Any overall time lag between the 2–4keV and 5–7keV band is less than $\sim 50$s. However, we do find that the 8–15keV band is delayed with respect to the 2–4keV band by 50–100s. We can use this time delay to obtain a rough size scale for the Comptonizing cloud that is producing the hard X-rays. Assuming a coronal temperature of $\sim
    100\keV$, it takes approximately 3 inverse Compton scatterings for a photon to be boosted between the 2–4keV and 8–15keV bands. Thus, the mean free path of a photon is approximately 15–30 light seconds. This is a lower limit on the size of the Comptonizing region.

As we will see, this combination of facts presents problems for current models.

Simple reflection models
------------------------

Initially, let us discuss these results in the light of simple X-ray reflection models (e.g. George & Fabian 1991). Assuming that variations in the primary flux are not accompanied by gross changes in geometry, we expect to observe one of two cases. Firstly, if the light crossing time of the fluorescing part of the disk is shorter than the timescale being probed by the observation, an iron line with constant [*equivalent width*]{} will result (i.e. the iron line flux will track the flux of the illuminating primary X-ray source). On the other hand, if the light crossing time of the fluorescing disk is greater than the timescale being probed, a constant [*flux*]{} line will result.

Within the context of these simple reflection models, we are forced to conclude that the light crossing time of the fluorescing region is larger than $\sim 50$ks. Since the line is relativistically broad, most of the fluorescence occurs in the central $r\sim 20GM/c^2$ of the disk. Setting the light crossing time of this region to be greater than 50ks gives a black hole mass of $M_{\rm BH}\sim 2\times 10^8\Msun$. Given such a large black hole mass, the accretion rate must be less than 1% of the Eddington rate in order to produce the observed luminosity of $L_{\rm bol}\sim
10^{44}\ergps$ (Reynolds et al. 1997). Furthermore, the size of the X-ray emitting blobs must be small, $r_{\rm blob}/r_{\rm disk}\sim 10^{-3}$, in order to produce the very small time delays seen between different bands. Despite being so small, these blobs must be at large distances above and below the accretion disk plane, or else one would still see iron line variability as a flaring blob illuminated the patch of disk directly beneath.

To date, there are no dynamical measurements of the black hole mass in MCG–6-30-15, and hence such a model does not explicitly contradict any data. However, there are several indirect arguments that lead us to reject the inference of a large black hole mass in MCG–6-30-15. An independent indicator of the black hole mass is possible by estimating the bulge mass of the host galaxy and then applying the bulge/hole mass relationship of Magorrian et al. (1998). The B-band luminosity of the S0-galaxy which hosts this Seyfert nucleus is approximately $m_{\rm B}=13.7$ (RC3 catalogue), and this is likely to be completely dominated by the bulge since the nucleus is heavily reddened in the B-band and the galactic disk is very weak. Using a Hubble constant of $H_0=65\kmpspMpc$, the absolute B-band magnitude of the bulge is then $M_{\rm B}-19$. Using the standard relations (Faber et al. 1997), the bulge mass is then $M_{bulge}\sim
3\times 10^9\Msun$. Finally, applying the Magorrian et al. (1998) scaling factor between bulge mass and black hole mass gives $M_{\rm BH}\sim
1-2\times 10^7\Msun$, an order of magnitude smaller than the black hole mass estimate in the previous paragraph.

There are also X-ray constraints that suggest a black hole mass significantly smaller than $10^8\Msun$. MCG–6-30-15 has exhibited large amplitude X-ray variability on timescales as short as 100s. However, the dynamical timescale of the accretion disk where the bulk of the energy is released is $t_{\rm dyn}\sim 10^5(M/10^8\Msun)\s$. Thus, if the black hole really is as massive as $M_{\rm BH}\sim 2\times
10^8\Msun$, large amplitude variability would be occurring on timescales as short as $10^{-2}t_{\rm dyn}$. It is difficult to conceive of processes which would give such variability. The final X-ray argument against a $2\times 10^8\Msun$ black hole in MCG–6-30-15 comes from the power spectrum derived by Lee at al. (1999b) and Nowak & Chiang (1999). By comparing the power spectral density (PSD) of MCG–6-30-15 with that of NGC 5548 and Cygnus X-1, they estimate that the black hole in MCG–6-30-15 has a mass of $M_{\rm BH}\sim 10^6\Msun$.

More complex scenarios
----------------------

Since the application of simple X-ray reflection arguments led us to deduce an unacceptably large black hole mass, we must examine alternative avenues. Indeed, the spectral fitting of Lee et al. (1999b) forces us to consider complications beyond the simple reflection picture — In their spectral fitting, they found that the Compton reflection continuum fails to show the expected correlation with the iron line equivalent width (in fact, they are anti-correlated; Lee et al. 1999b). Very similar behaviour is also seen in NGC 5548 (Chiang et al. 1999)

Ionization of the disk surface is one of the few physical phenomenon that can (partially) decouple the strength of the Compton reflection continuum from the strength of the iron line. Matt, Fabian & Ross (1993) demonstrated that the iron emission line is more sensitive to ionization effects than the general form of the Compton reflection continuum. In other words, patches of the disk with certain (surface) ionization parameters can produce a Compton reflection continuum without producing appreciable iron fluorescence.

We use this fact to construct the following simple model. Let the X-ray flux illuminating the surface layers of the accretion disk be $$F(r)\propto F_{\rm X}r^{-\beta}.$$ A variety of X-ray source geometries give $\beta\approx 3$ at large radii, and $\beta<3$ as one approaches the innermost parts of the disk. Now, the ionization parameter of at the surface of the disk is given by $$\xi=\frac{4\pi F(r)}{n(r)},$$ where $n(r)$ is the density of the surface layers of the disk. We suppose that $n(r)\propto r^{-\gamma}$. Hence, we have $$\xi\propto F_{\rm X}r^{\gamma-\beta}$$ Standard disk models (Shakura & Sunyeav 1973) give $\gamma\approx 2$ at large radii, and $\gamma<2$ near the inner part of the disk. Now, suppose that there exists a critical ionization parameter $\xi_{\rm crit}$ above which there is no iron line produced. For reasonable values of $\beta$ and $\gamma$, this gives a critical radius $r_{\rm crit}$ within which no iron line is produced. The total iron line flux expected from the object is then given by $$F_{\rm line}\propto \int^{\infty}_{r_{\rm crit}}F(r)dr,$$ which is readily manipulated to give $$F_{\rm line}\propto F_{\rm X}^{(1-\gamma)/(\beta-\gamma)}.$$ For our canonical values of $\beta$ and $\gamma$, this gives $F_{\rm
line}\propto F_{\rm X}^{-1}$. Thus, this simple model produces an iron line flux which is anti-correlated with the flux of the illuminating source. Provided a strong Compton reflection continuum can still originate from the ionized portions of the disk, this type of picture may explain the spectral behavior that we observe.

One simple prediction of this model is that the velocity width of the line profile gets smaller as the continuum flux increases (due to an outward migration in the inner radius of the line emitting region). Of course, the toy model presented above only captures the crudest aspects of the problem. Fully self-consistent ionized reflection models must be calculated (taking into account the vertical structure of the disk; e.g. see Nayakshin, Kazanas & Kallman 1999) and compared with the data in order to test whether the picture sketched here is reasonable or not.

Even if global, flux-correlated changes in the ionization of the disk surface are responsible for the observed spectral changes, we would still expect reverberation signatures on short timescales. We have set upper limits of $\sim 500$s on the timescale of any reverberation delay. If the black hole mass is $M_{\rm BH}\sim 1\times 10^7\Msun$, the light crossing time of the iron line producing region is $\sim 2000$s, and hence we need to infer a disk-hugging corona (with $h/r\sim 0.3$) in order to be compatible with the reverberation limits. If, instead, the black hole is $M_{\rm BH}\sim 1\times 10^6\Msun$, the light crossing time of the entire line producing region is only $200\s$ and so the X-ray source geometry is unconstrained by our reverberation limits. The corresponding Eddington ratios are $\sim 10\%$ and $\sim 100\%$ for black hole masses of $10^7\Msun$ and $10^6\Msun$ respectively.

Conclusions
===========

In this paper, we have used an interpolation method based upon that of PRH92 to search for temporal lags and leads between the 2–4keV, 5–7keV and 8–15keV bands in a long [*RXTE*]{} observation of the bright Seyfert 1 galaxy MCG–6-30-15. In essence, we use the PRH92 method to compute an optimal reconstruction of the 2–4keV light curve in which the datagaps are interpolated across. We then fold this reconstructed light curve through trial transfer functions and compare with data from the other bands in a $\chi^2$ sense.

Our search for lags and leads was tailored to find reverberation effects in the iron line which is thought to originate from the innermost regions of the black hole accretion disk. We find no evidence for any reverberation, and rule out reverberation delays in the range $0.5-50$ksec. We can extend the conclusions of Lee et al. (1999b), and infer that the iron line possesses a constant flux on timescales on timescales as short as 500s. We also find that the hard band (8–15keV) is delayed by 50–100s relative to the 2–4keV band.

We attempt to put these various results together into a coherent picture for this object. The constancy of the iron line flux leads one to consider large black hole masses (in excess of $10^8\Msun$). However, such a large mass is found to be unacceptable from the standpoint of both X-ray variability constraints, and constraints based on the mass of the galactic bulge. Indeed, using the bulge/hole scaling factor of Magorrian et al. (1998), we estimate that the hole has a mass of $M_{\rm BH}\sim
1-2\times 10^7\Msun$. Given that this is a more reasonable mass estimate, some mechanism beyond the simple X-ray reflection model must be invoked to explain the temporal variability of the iron line and Compton reflection continuum. We suggest that flux correlated changes in the average ionization state of the surface layers of the accretion disk may be such a mechanism. While we support this suggestion with a toy model, the plausibility if this suggestion can only be assessed once detailed modeling has been performed.

Acknowledgments {#acknowledgments .unnumbered}
===============

I thank James Chiang, Rick Edelson, Andrew Hamilton, Julia Lee and Mike Nowak for insightful discussions throughout the course of this work. CSR thanks support from Hubble Fellowship grant HF-01113.01-98A. This grant was awarded by the Space Telescope Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA under contract NAS 5-26555. CSR also thanks partial support from NASA under LTSA grant NAG5-6337. This work has made use of data obtained through the High Energy Astrophysics Science Archive Research Center (HEASARC) Online Service, provided by the NASA Goddard Space Flight Center.

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The financial services industry is dangerously complacent in its approach to digital money. Some of the major banks almost look like they fear technological change that promises greater transparency, efficiency and security at a lower cost.

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Openness to academic collaboration is also crucial. This week, Citi and Imperial College London are holding their fourth annual symposium on digital money. We’ll be bringing together academic, industry and regulatory experts at Canary Wharf to ensure that these advances bring tangible benefits.

In 2016, we should not accept a financial system where it can take banks days to settle stock trades. Retailers should not be subject to a privatised transaction tax through high credit card fees. Poor migrant workers should not have to forfeit large chunks of their income in fees when they pay remittances.

If we don’t act to unpick regulatory obstacles or undo big business inertia, economic growth will falter.

We in universities must lead the change too, or risk falling behind. At Imperial College Business School, digital money has become the new normal. Our students are fintech-savvy. Many take classes on digital money and experiment with blockchain. Our graduates are helping to build digital money startups like mobile payment firm Yoyo, which is providing a glimpse of a cash-free future. Business scholars collaborate with data scientists at Imperial’s Centre for Cryptocurrency Research and Engineering, where we are already looking beyond money and what we previously thought of as the digital realm; cryptocurrencies could change the way we deal with contracts, identity, medical prescriptions, patents and copyright.

No city in the world is as well placed as London to lead this revolution. We have the world’s most important financial services industry, more first-class universities than any other city, and a thriving startup culture that has fintech in its sights. But too few industry, government and academic leaders recognise this change. No industry is immune from disruption. With digital money, we have a simple choice: disrupt or be disrupted.


Q:

PHPEXCel Read only one sheet to Array

I am using PHPExcel to only read values from  excel sheets
if i use this code , it works fine without no problem:
  function ReadUploadedFile($Uploadedfile,$fileExtension)
    {
            class MyReadFilter implements PHPExcel_Reader_IReadFilter
            {
                public function readCell($column, $row, $worksheetName = '')
                 {
                    // Read rows 1 to 7 and columns A to E only
                    if ($row>=1 && $row<=100) {
                        if (in_array($column,range('A','Z'))) {
                            return true;
                        }
                    }
                    return false;
                }
            }
}

        $filterSubset = new MyReadFilter();
        $inputFileType="";

        $inputFileType = 'Excel5';
        $objReader = PHPExcel_IOFactory::createReader($inputFileType);
        $objReader->setReadFilter($filterSubset);
        $objReader->setReadDataOnly(true);
        $objPHPExcel = $objReader->load('myExcelsheet.xls');
        $sheetData = $objPHPExcel->getActiveSheet()->toArray(null,true,true,true);

$sheetData now is an array and i can use it with no problem.

what if i have many worksheets ,and i need to specify only one , as per documentation from PHPEXCEL , they say to use setLoadSheetsOnly()
i try the code blow but it doesn't work.
$inputFileType = 'Excel2007';
$objReader = PHPExcel_IOFactory::createReader($inputFileType);
$objReader->setReadFilter($filterSubset);
$objReader->setReadDataOnly(true);
$objReader->setLoadSheetsOnly("Summary"); //my worksheet name is Summary
$objPHPExcel = $objReader->load('myExcelsheet.xlsx');

so what should i write after the above line to convert this object to Array
i try this
$sheetData = $objPHPExcel->getActiveSheet()->toArray(null,true,true,true);

but it gives this error

Call to a member function cellExists() on a non-object

and when i try this
$sheetData = $objPHPExcel->toArray(null,true,true,true);

Call to undefined method PHPExcel::toArray()

A:

/** Here is my code work: */
ini_set('display_errors', TRUE);
ini_set('display_startup_errors', TRUE);
define('EOL', (PHP_SAPI == 'cli') ? PHP_EOL : '
');

/** PHPExcel_IOFactory */
require_once dirname(__FILE__) . '/../Classes/PHPExcel/IOFactory.php';

$objReader = PHPExcel_IOFactory::createReader('Excel2007');
$inputFileType = 'Excel2007';
$inputFileName = 'file.xlsx';
$sheetname = 'mysheey'; // I DON'T WANT TO USE SHEET NAME HERE

$objReader = PHPExcel_IOFactory::createReader($inputFileType);
$objReader->setLoadSheetsOnly($sheetname);
$objPHPExcel = $objReader->load($inputFileName);
$sheetData = $objPHPExcel->getActiveSheet()->toArray(null, true, true, true);
echo ' Highest Column ' . $getHighestColumn = $objPHPExcel->setActiveSheetIndex()->getHighestColumn(); // Get Highest Column
echo ' Get Highest Row ' . $getHighestRow = $objPHPExcel->setActiveSheetIndex()->getHighestRow(); // Get Highest Row

echo "
";
print_r($sheetData);
echo "
";