Research Hotspot & Journal Scope - sample\nAddictive Behaviors Featured Researches within sample\nAddictive Behaviors - DOI: 10.1016/j.addbeh.2019.06.013\nAlana Oakly · Richard Edwards · Greg Martin ·\nAddictive Behaviors - DOI: 10.1016/j.addbeh.2018.10.032\nBen Kelcey ·\nScientific Writng Examples of Treated Sample in a Sentence\nNotably, PE-GA-treated samples also had the highest sensory quality rating.\nEffect of Pectin Coating Infused with Gallic Acid on the Quality and Shelf Life of Japanese Sea Bass (Lateolabrax japonicas) Fillets [10.1007/s11947-019-02396-7]\nScientific Writng Examples of Random Sample in a Sentence\nRandom sample calculation was performed with 95% confidence, a maximum error of 2.\nScientific Writng Examples of Sample Acquisition in a Sentence\nThe outcome of this effort will result in a 10X reduction in harness mass, enabling a significant increase in science payload which then enables more capable sample acquisition, delivery and analysis systems on these missions.\nScientific Writng Examples of Semen Sample in a Sentence\nSemen samples (n = 40) were collected from normozoospermic men over 45 years old.\nIn vitro application of Ceratonia siliqua improved sperm parameters and chromatin quality after vitrifacation in normozoospermic aged men [10.1186/s43043-019-0007-9]\nScientific Writng Examples of Sperm Samples in a Sentence\nPooled sperm samples from each group were subjected to high‐throughput liquid chromatography–tandem mass spectrophotometry (LC‐MS/MS) and subsequent bioinformatic analysis that identifies key proteins to be differentially expressed (DEPs).\nQuantitative proteomics decodes clusterin as a critical regulator of paternal factors responsible for impaired compensatory metabolic reprogramming in recurrent pregnancy loss [10.1111/and.13498]\nHighly Related Keywords from sample\nTreated Sample Random Sample Sample Acquisition Semen Sample Sperm Samples National Sample Small Sample Sampled Data Systems Milk Samples Sample Size Fluid Samples Juice Samples Uk Sample Complex Samples Tumor Samples Stool Samples Representative Sample Clinical Samples Patient Samples Plasma Samples Aqueous Samples Turkish Samples Sample Sizes Language Sample Determining Sample Urine Samples Food Samples Microbiome Samples Dna Samples Blood Samples Continuous Sample Waste Samples Fna Samples Microbiological Samples Discrete Samples Cytologic Samples Validation Sample Traditional Sample Sample Data Sample Surface Core Samples Biomass Samples Blinded Sample Natural Samples Two Sample Test Military Sample Thick Samples Meat Samples Automated Sample Polycrystalline Samples Wheat Samples Powder Samples Efficient Sample Samples Produced Discretely Sampled Subgingival Samples Cohort Sample Wood Samples Alternative Sample Filter Aided Sample Samples Containing Sample Generation Sample Quality Rna Seq Samples Sample Path Animal Samples Sample Sets Sample Aged Sample Handling Sample Volume Sampled Across Single Sample Twin Sample Romanian Sample Cosmetic Samples Copper Samples Samples Coupled Sample Treatment Drink Samples Bioaerosol Sampler Quartz Samples Active Samplers Uranium Samples Sampled Time Beef Samples Soil Sample Nonsubsampled Shearlet Samples Induced Shale Samples Samples Extracted Sample Complexity Honey Samples Amplified Sample Sample Collection Varying Sample Censored Samples Sample Survey Appropriate Sample Standard Samples Set Samples Diverse Samples Samples According Sample Stability Samples Analytical Low Income Sample Disorder Sample Sample Average Hair Samples Current Sample Colombian Sample States Sample Sample Consensus Population Samples Skeletal Samples Prospective Sample Non Clinical Samples Thin Samples Chinese Sample Sampled Systems Naturalistic Sample Dna Sample Donor Samples Sample Geometry Large Volume Sample Sample Thickness Global Sample Data Sample Biological Sample Cylindrical Samples Variable Sample Non Invasive Samples Serum Sample Samples Exposed Ash Samples Semiconductor Samples Multiple Samples Paired Samples Sample Characteristics Multivariate Sample Normal Samples Cytological Samples Highly Undersampled Pork Samples Sample Design Representative Samples Virtual Sample Liquid Samples Histologic Samples Spot Samples Marrow Samples Irregularly Sampled Sample Cohort Censored Sample Portuguese Sample Large Samples Various Samples Dust Samples Fecal Sample Sample Adequacy Set Sample Sputum Samples Practical Samples Samples Stored Samples Utilizing Corn Samples Oil Samples Faecal Sample Without Sample Positive Samples Seawater Samples Reference Samples Training Sample Urine Sample Paraffin Embedded Samples Beer Samples Bereaved Sample Chilean Sample Samples Associated Tem Sample Sample Performance Psychiatric Sample Undersampled Radial Language Samples Gas Samples Sample Material Samples Irradiated Solid Sample Two Samples Rice Samples Sample Flow Protein Samples Media Samples Fuel Samples Sample Entropy Student Sample Fourier Samples Online Samples Sample 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Splitting Samples Applying Printed Sample Mucosal Samples Fault Samples Sample Learning German Speaking Sample Samples Compared Samples Derived Samples Revealed Ti6al4v Samples Cultivated Samples Vastly Undersampled Material Samples Survey Samples Hard Sample Samples Analysis Mortar Samples Collection Samples Quantized Sampled Data Nasal Samples Vinegar Samples Samples Fabricated Adequate Sample Pilot Sample Real World Sample Human Sample Sediment Sampler Sample Similarity Breath Samples Four Samples Sample Pre Treatment Sample Environments Statewide Sample Level Samples Help Seeking Sample Sample Heterogeneity Sample Median Cortex Samples Sample Efficiency Sample Comparison Lunar Sample Semolina Samples Transdiagnostic Sample Imbalanced Sample Hemolytic Samples Proteome Sample Origin Sample Flexible Sample Sample Obtained Turkey Sample Sample Mining Tablet Samples Naso Oropharyngeal Samples Artificial Samples Sample Management Biomedical Samples Cream Samples Sample Mendelian Mosquito Samples Packaging Samples Sample Delivery Membrane Samples Nasopharyngeal Samples Standard Sample Sample Statistics Sample Geometries Returned Samples Required Sample Low Cost Sample Plankton Samples Materials Samples Validation Samples Bidirectional Two Sample Bedrock Samples Fuzzy Sampled Data Adversarial Samples Sample Augmentation Sample Quantity Trial Samples Vault Samples Airborne Samples Sample Distribution Samples Suitable Pathology Sample Cement Samples Experimental Sample Sintered Sample Covid 19 Samples Public Sample Silicate Samples Samples Improves Indonesian Sample Vaginal Samples Industrial Samples Lettuce Samples Samples Manufactured Samples Treated Two Sample Summary Data Kenyan Sample Sample Classification Effluent Samples Archived Samples Seawater Sample Brain Sample Fast Sample Plastic Samples Consecutive Sample Wound Samples Sample Analyses Fermentation Samples Cm247lc Samples Salivary Samples Hungarian Sample Spanish Speaking Sample Graph Sample Mexican Sample Spherical Samples Calibration Sample Non Respiratory Samples Samples Available Manufactured Samples Samples Sourced Undersampled Mri Experimental Samples Bat Samples Sample Efficient Potato Samples Covid 19 Sample Samples Experimental Snow Samples Commercial Sample Green Sample Hard Samples Pear Samples Proteomic Sample Beam Sample Miniaturized Sample Samples Yield Sample Pooling Two Sample Multivariable Limited Sample Market Samples Cheese Samples Sample Clustering Idna Samplers Medicaid Sample Nonparametric Two Sample Service National Sample Low Sample Size Data Sample Condition Mussel Samples Sars Cov 2 Samples Sample Support Candidate Sample Split Sample Testing Adversarial Sample Statistical Sample Population Representative Sample Sample Reduction Progressive Sample Sample Cartridge Thin Film Sample Sweat Samples Samples Influence Screening Samples Bioanalytical Sample Mass Selected Sample Three Sample Small Scale Sample Museum Samples Scale Samples Volume Limited Sample Sample 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Samples Negative Sample Sample Metadata Sample Enriched Undersampled Acquisition Samples Formed Sample Damage Polyethylene Samples Extruded Samples Protein Sample Endometrial Samples Grape Samples Situ Samples Mucus Samples Scarce Samples Bacterial Samples Carlo Sampler Sample Balance Robust Sample Saffron Samples Sauce Samples Fake Samples Memory Sampled Data Stainless Steel Samples Worldwide Sample Anisotropic Samples Extrapulmonary Samples Sampled Data Asynchronous Combined Sample Sampled Data Dynamic Sample Smeariness Sample Autocorrelation Samples Part Multi Sample Reduce Sample Sample Preconcentration Nonclinical Sample Mixed Samples Finite Sample Limited Samples Pus Samples Surface Samples Samples Prepared Nonsubsampled Contourlet Sample Distributions Sample Surveys Normative Sample Sampled Along Multinational Sample Department Sample Student Samples Effective Sample Groundwater Samples Glass Samples Turkish Sample Multi Ethnic Sample Australian Sample Multiethnic Sample Critical Samples Samples Followed Reference Sample Ancient Samples Flour Samples Feed Samples Sample Space Samples Reveal Cancer Samples Tumour Samples Biopsy Sample Drug Samples Field Samples Cytology Samples Elderly Sample American Sample Pharmaceutical Samples Complete Sample Pain Sample Chinese Samples Sample Area Improved Sample Cross Sectional Sample Microfluidic Sample Sample Rate Bone Samples Test Samples Female Sample Culture Samples Sample Contamination Plasma Sample Sample Population Sample Types Degraded Samples Samples Made Canadian Sample Galaxy Sample Samples Analyzed Sample Spinning Finnish Sample Treated Samples Three Samples Epidemiological Sample Sample Exchange Samples Around Random Samples Mars Sample 2 Sample Mendelian Pm10 Samples Improving Sample Realistic Samples Egyptian Sample Multi Sample Analysis Samples Correlation Safe Sample Nonuniformly Sampled Egg Samples Aquaculture Samples Bread Samples Biased Samples Volume Samples Sample Disturbance Cluster Sample Apple Samples Cigarette Samples Sample Sites Ice Samples Seafood Samples Tear Samples Physiological Samples Containing Samples Internet Sample Simplified Sample Melanoma Samples Mixed Sample Rapid Sample Sample Set Related Samples Pharmaceutical Sample Dependent Samples European Sample Samples Synthesized Particle Samples Labeled Samples Feedstuff Samples Bone Sample Spot Sample Non Fragile Sampled Data Hydroxyapatite Samples Sampled Position Randomly Sampled Sample Magnetometer Sample Inference Adolescent Samples Survey Sample Samples Across Sample Environment Analysis Sample Vivo Samples Sample Identification Challenging Samples Biodiesel Samples Granite Samples Autopsy Samples Selected Sample Organ Samples Sandstone Samples Carlo Samplers Sample Correlation Mixture Samples Nonclinical Samples Casework Samples Guano Samples Sample Preservation Research Samples Environmental Sample Collected Samples Short Samples Polymer Samples Sample Information Lesion Samples Petroleum Samples Tissue Sample Permanent Sample Postmortem Samples Meteorite Samples Healthy Sample Treatment Samples Printed Samples Sample Means Pediatric Sample Sample Dissolution Sample Prevalence Proteomics Sample Sample Treatments Samples Selection Water Sampler Carbonate Samples Sputum Sample Psychiatric Samples Rubber Samples Self Collected Samples Aperiodic Sampled Data Humor Samples Graphene Samples Lung Samples Model Samples Acid Samples Lignin Samples Per Sample Bayesian Sample Minimum Sample Sample Buffer Trial Sample Bulk Sample Minimal Sample Pressure Sample Sample Digestion Greek Sample Cryopreserved Samples Lunar Samples Freshwater Samples Sample Recruited Sample Application Undergraduate Samples Lichen Samples Aspirate Samples Samples Measured Undergraduate Sample College Sample Point Samples Multiscale Sample Sample Reactivity Longitudinal Samples Sampled Blood Tract Samples Mud Samples Final Sample Sample Problem Sample Tubes Discrete Sample On Sample Serial Samples Danish Sample Calibration Samples Microdialysis Samples Plant Sample Fluids Samples Undersampled Mr Diet Samples Manure Samples Adult Samples Noninvasive Samples Samples Undergoing Mushroom Samples Lifespan Sample Sample Representativeness Sampled Data Controller Trauma Exposed Sample Tomato Samples Limestone Samples Leaf Samples Undersampled Data Sample Integrity Sample Positioning Treatment Sample Moss Samples Aerosol Samplers Sample Bias Speech Samples Veteran Sample Mineral Samples Effusion Samples Silicon Samples Multi Site Sample Sample Variance Thin Sample Directional Sampled Outputs Whole Blood Samples Local Sample Paint Samples Sample Drying Asphalt Samples Chicken Samples Synthetic Samples Non Clinical Sample German Samples Sample Multiplexing Volume Sample Sample Load Sediment Samples Sample Selection Geological Samples Clinical Sample Sample Stacking Diverse Sample Community Sample Rock Samples Sample Face Samples Collected Population Sample Single Sample Face Large Sample Sample 2006 Samples Within Surveillance Samples Quechers Sample Small Samples Ore Samples On Line Sample Two Sample Tests French Sample Gibbs Samplers Injury Sample Undersampled Dynamic Cocaine Samples Sampled Data Output Coffee Samples Hemolyzed Samples Quasar Sample Selected Samples Samples Comparison Grain Samples Sample Drop Sample Reanalysis Carcinoma Samples German Sample Sample Per Crystalline Samples Increasing Sample Sample Cleanup Nonlinear Sampled Data Stool Sample Beverage Samples Fruit Samples Direct Sample Stratified Samples Tobacco Samples Rainwater Samples Tungsten Samples Real Sample Air Sampler Sample Quantiles Adolescent Sample Faecal Samples Cereal Samples Wastewater Samples Longitudinal Sample Water Sample Semen Samples Japanese Sample Convenience Sample Concrete Samples Embedded Samples Sample Properties Sample Cell Composite Samples Adult Sample Samples Taken Sample Injection Csf Samples Aqueous Sample Air Samplers Contaminated Samples Integrative Sampler Test Sample Sediment Sample Italian Sample Rock Sample Sample Temperature Wine Samples Marine Samples Matter Samples Sludge Samples Sample Transfer Complicated Samples Sample Introduction University Sample Sampled Data Stabilization Skeletal Sample Core Sample Passive Samplers Respiratory Samples Complex Sample Steel Samples Sample Covariance Forensic Samples Ceramic Samples One Sample Field Amplified Sample Propolis Samples Nationwide Sample Seed Samples Air Samples Food Sample Metagenomic Samples Tea Samples Tio2 Samples Pooled Samples Incurred Sample Nationally Representative Sample Sewage Samples Sparsely Sampled Sample Allocation Probability Sample Sample Storage Malaysian Sample Ffpe Samples Cell Samples Turbid Samples Cervical Samples Sample Holder Aquatic Samples Swedish Sample Novel Sample Two Sample Mendelian Two Sample Problem Species Sampled Control Samples Human Samples Sample Enrichment Sample Nis Sample Testing Samples Processed Control Sample Heterogeneous Sample Samples Used Sample Plot Probability Samples Agricultural Samples International Sample Norwegian Sample Alloy Samples Sample Rotation Sample Results Muscle Samples Data Samples Integrative Samplers Surgical Samples African Sample Milk Sample Sample Test Robust Sampled Data Clinic Sample Coal Samples Commercial Samples Matched Samples National Samples Spanish Sample Samples Application Independent Sample Forensic Sample Sampled Data Samples Submitted Filter Samples Aerosol Samples Passive Sampler Street Samples Vegetable Samples Samples Obtained Liquid Sample Rna Samples Sampled Grating Blood Sample Fecal Samples Biota Samples Sample Type Vibrating Sample Sample Return Samples Without Swab Samples Sample Volumes Non Uniformly Sampled Care Sample Sampled Data Synchronization Sample Evidence Lavage Samples Sand Samples Sample Mean Brazilian Sample Coal Sample Sample Matrix Samples Prior Aspiration Samples Metallic Samples Matched Sample Clay Samples Non Subsampled Shearlet Brain Samples Two Sample Samples Consumed Plaque Samples Samples Reveals Patient Sample Samples Employing Offender Sample Fish Samples Biopsy Samples Sample Database School Sample Simple Sample Sample Matrices Sample Dilution Sampled Data Control Skin Samples Archaeological Samples Tissue Samples Solid Samples Film Samples Real Samples Training Samples Serum Samples Soil Samples Iranian Sample Health Sample Water Samples Silica Samples Sample Preparation Sample Loading Diagnostic Samples Sample Pretreatment Environmental Samples Sample Analysis Robotic Sample Sampled Data State Saliva Samples Biological Samples Inpatient Sample


Tommy Emmanuel - All I Want for Christmas (Guitar Recorded Versions) by Tommy Emmanuel: Hal Leonard 9781495026157 Paperback - Books Express\nHome Tommy Emmanuel Tommy Emmanuel - All I Want for Christmas (Guitar Recorded ...\nTommy Emmanuel - All I Want for Christmas (Guitar Recorded Versions)\nISBN 10: 1495026159 / ISBN 13: 9781495026157\nShips with Tracking Number! INTERNATIONAL WORLDWIDE Shipping available. May not contain Access Codes or Supplements. May be ex-library. Shipping & Handling by region. Buy with confidence, excellent customer service!. Bookseller Inventory # 1495026159q\nTitle: Tommy Emmanuel - All I Want for Christmas (...


2 Korin 3 | Baebol Long Intenet | Niu Wol Translesen\nSeken leta i go long Korin 3:1-18\nLeta blong talemaot se mifala i hu (1-3)\nMan blong wok long niufala kontrak (4-6)\nLaet blong niufala kontrak i saenaot bigwan moa (7-18)\n3 ?Olsem wanem? ?Mifala i mas talemaot long yufala bakegen se mifala i hu? ?Yufala i ting se ol narafala oli mas raetem wan leta long yufala blong talemaot se mifala i hu, olsem sam man oli stap mekem? ?No mifala i nidim blong yufala nao i raetem wan leta olsem, blong givim i go long ol narafala? 2 Yufala nao i olsem leta blong mifala+ we oli raetem long hat blong mifala, mo olgeta man oli save leta ya mo oli ridim. 3 Yufala ya, yufala i leta we i kam long Kraes, we mifala ol minista blong hem,+ mifala i raetem. Leta ya, oli no yusum ink blong raetem, be oli yusum spirit blong God ya we i laef. Mo oli no raetem long ol flat ston,+ be long hat blong man.+ 4 Mifala i save tok olsem, from we mifala i joen long Kraes, nao mifala i stap bilif strong long God. 5 Mifala i no stap talem se mifala i naf blong mekem wok ya long prapa paoa blong mifala nomo, be God nao i mekem se mifala i naf blong mekem wok ya.+ 6 Hem i mekem mifala i naf blong kam ol minista blong wan niufala kontrak.+ Mifala i no folem Loa we oli raetem,+ be mifala i folem spirit, from we Loa we oli raetem i blong jajem man blong i ded,+ be spirit i mekem man i laef.+ 7 Loa ya we i mekem man i ded mo we oli raetem long ol ston,+ i kamtru wetem wan glori we i mekem se ol man Isrel oli no save lukluk fes blong Moses, from we glori i stap long fes blong hem,+ wan glori we i blong smoltaem nomo. 8 !Sipos i olsem, ol samting we spirit i karem i kam+ oli mas kam wetem glori we i bigwan moa!+ 9 Sipos Loa we i jajem man se i mas ded,+ i gat glori long hem,+ wok we i blong mekem man i kam stret man, glori blong hem i bigwan moa.+ 10 Samting we fastaem i gat glori long hem, naoia i no moa gat glori long hem from i gat wan glori we i gud moa i bitim hem.+ 11 !Sipos samting we i blong smoltaem nomo i kamtru wetem glori,+ samting we i blong stap oltaem nomo bambae i gat moa glori i bitim hem!+ 12 From we yumi gat hop olsem,+ tingting blong yumi i strong we yumi no fraet blong toktok. 13 Mo yumi no mekem olsem Moses taem hem i kavremap fes blong hem long wan kaliko,+ blong ol man Isrel oli no stap lukluk nomo long samting ya we i blong smoltaem nomo. 14 Be tingting blong olgeta i fas,+ from we kam kasem tede, i olsem we wan kaliko i blokem tingting blong olgeta, nao oli no kasem save taem oli harem tok blong olfala kontrak.+ Kaliko ya, Kraes nomo i save tekemaot.+ 15 Yes kam kasem tede, wan samting olsem kaliko i stap blokem hat blong olgeta,+ nao oli no naf blong kasem save ol samting we Moses i raetem.+ 16 Be taem man i kambak long Jehova,* kaliko ya i kamaot.+ 17 Jehova* i Spirit,+ mo long ples we spirit blong Jehova* i stap, man i save fri.+ 18 Mo yumi evriwan yumi no gat kaliko we i blokem fes blong yumi mo yumi olsem mira we i stap soemaot glori blong Jehova.* Taem yumi mekem olsem, yumi stap jenis blong kam olsem pija blong hem, yumi soemaot moa glori,* stret olsem we Spirit ya Jehova* i stap mekem long yumi.*+\n^ PT: “soemaot wan glori afta narafala glori.”\n^ MNT: “stret olsem spirit blong Jehova i stap mekem long yumi.”


fevrier 2008 - EUTERPE - Le Portail des Concerts\n3 articles avec fevrier 2008\nLa salle de concert du Foyer Européen fut presque trop petite mardi dernier (09/02/2008) pour contenir le public, venu nombreux au concert du "Quatuor de Saxophones du Luxembourg". Nous y avons découvert quatre instrumentistes (Guy Goethals, Leana Sealy,...\nQuand la musique devient visible......\nNous ne pouvons que qualifier de magnifique et d'extraordinaire le concert donné le 12 février 2008 à la Philharmonie, dans le cadre de l'abonnement "Grands Orchestres" désignation qui ce soir là fut d'une éclatante justesse. Le "Philharmonia Orchestra...\nHommage à la Musique luxembourgeoise\nHier soir 14 février 2008, l'hommage rendu à René Hemmer et Jeannot Heinen fut en fait un hommage à la composition luxembourgeoise. Comme toujours Marcel Wengler et le Luxembourg SInfonietta ne furent pas étranger au succès d'une soirée enrichissante...


Delhi air quality 'severe', trucks barred from entering Delhi - Weekly Voice\nHome India Delhi Delhi air quality ‘severe’, trucks barred from entering Delhi\nHomeless people sit around a bonfire to keep themselves warm as they wait for free food distribution on a morning with thick smog in New Delhi, India, Tuesday, Jan. 1, 2019. Air quality in the capital region, already the worst in the world, is hovering between 'severe' to 'poor' category. An ongoing cold wave is worsening the air quality in parts of north India where road, rail and air traffic is also being hit by a dense fog. (AP Photo/Manish Swarup)\nNew Delhi: As Delhi continued to breathe toxic air for over 30 hours, the Supreme Court-appointed EPCA on Thursday issued directions to take urgent measures under the Graded Response Action Plan (GRAP) from Friday and stop the entry of trucks in the city for a day.\nPrevious articleKatrina Kaif opts out of Varun Dhawan’s dance film\nNext articleINFINITI reveals the new QX Inspiration concept ahead of 2019 NAIAS


WoRMS - World Register of Marine Species - Periamma Perrier R., 1896\nSpecies Periamma kumai Mitsukuri, 1912 accepted as Ellipinion kumai (Mitsukuri, 1912)\nSpecies Periamma ludwigi (von Marenzeller, 1893) accepted as Penilpidia ludwigi (von Marenzeller, 1893)\nSpecies Periamma naresi (Thiel, 1882) accepted as Amperima naresi (Théel, 1882)\nSpecies Periamma tetramerum Clark, 1920 accepted as Amperima naresi (Théel, 1882)\nWoRMS (2021). Periamma Perrier R., 1896. Accessed at: http://www.marinespecies.org/aphia.php?p=taxdetails&id=123517 on 2021-06-16


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03.12.2018 - 20.02.2019\n1. Mo 03.12.2018 20:00 - 21:50\n2. Mi 05.12.2018 20:00 - 21:50\n4. Mi 12.12.2018 20:00 - 21:50\n5. Mo 17.12.2018 20:00 - 21:50\n6. Mi 19.12.2018 20:00 - 21:50\n11. Mo 21.01.2019 20:00 - 21:50\n12. Mi 23.01.2019 20:00 - 21:50\n13. Mo 28.01.2019 20:00 - 21:50\n14. Mi 30.01.2019 20:00 - 21:50\n15. Mo 04.02.2019 20:00 - 21:50\n17. Mo 11.02.2019 20:00 - 21:50\n18. Mi 13.02.2019 20:00 - 21:50\nDatum 03.12.2018 - 20.02.2019


Ikki Tousen Western Wolves Anime Ships on Home Video in Japan on February 27 - News - Anime News Network\nThe official website for Ikki Tousen: Western Wolves , the newest anime entry in the Ikki Tousen franchise, revealed on Friday that the anime will ship on Blu-ray Disc and DVD on February 27. The anime will have three episodes.\nSource: Ikki Tousen: Western Wolves anime's website via Ota-Suke


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Yu wang cheng shi : Sex and the city (Work) - Nicholson Memorial Library System\nThe work Yu wang cheng shi : Sex and the city represents a distinct intellectual or artistic creation found in Nicholson Memorial Library System. This resource is a combination of several types including: Work, Language Material, Books.\nThe Resource Yu wang cheng shi : Sex and the city\nContext of Yu wang cheng shi : Sex and the city\n
 Data from Yu wang cheng shi : Sex and the city - Nicholson Memorial Library System
\nData Citation of the Work Yu wang cheng shi : Sex and the city


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WoRMS - World Register of Marine Species - Henryalphonsia Števčić, 2005\nHenryalphonsia Števčić, 2005\nunaccepted (not validly published name)\nPilumnoplax elata Boone, 1927 accepted as Machaerus elata (Boone, 1927) accepted as Eucratoplax elata A. Milne-Edwards, 1880 accepted as Panoplax elata (A. Milne-Edwards, 1880) (type by original designation)\nWoRMS (2022). Henryalphonsia Števcic, 2005. Accessed at: https://www.marinespecies.org/aphia.php?p=taxdetails&id=881723 on 2022-01-28


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Lail Blueprint Cabernet Sauvignon Merlot 2008 - Natalie MacLean\nLail Blueprint Cabernet Sauvignon Merlot 2008\nLCBO: 219 bottles\nProduct #: 60251\nMore Vintages: 2010 Lail Blueprint Cabernet Sauvignon Merlot 2008 Wine ReviewNatalie has not yet reviewed this wine. It's listed here for your convenience so that you can find it easily in your local liquor store.\nIf you liked the Lail Blueprint Cabernet Sauvignon Merlot 2008, you might also like these wines:Top Rated Red WinesBest California Red WineBest California CabernetBest California ChardonnayGamble Family Vineyards Paramount Cabernet Sauvignon Merlot 2005Ridge Santa Cruz Mountains Cabernet Sauvignon Merlot 2005\nServe Lail Blueprint Cabernet Sauvignon Merlot 2008 between 60-65 degrees Farenheit or 15-18 degrees Celsius.\nRecipes for Lail Blueprint Cabernet Sauvignon Merlot 2008Asian Chicken Salad on Endive SpearsAsian Pork Tenderloin, Noodle and Vegetable Salad with Lime-Peanut Dre...Asparagus and Sugar Snap Pea SoupAvocado and Papaya SaladBalsamic Grilled Radicchio with Shaved PecorinoMore recipes...


Usagi Yojimbo, book 3, the wanderer's road - Forsyth County Public Library\nThe Resource Usagi Yojimbo, book 3, the wanderer's road, by Stan Sakai\nThe item Usagi Yojimbo, book 3, the wanderer's road, by Stan Sakai represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Forsyth County Public Library.\n"The stories in this volume originally appeared in Usagi Yojimbo #7-12 and Turtle Soup"--T.p. verso\nAppeal Terms of Usagi Yojimbo, book 3, the wanderer's road\n
 Data from Usagi Yojimbo, book 3, the wanderer's road, by Stan Sakai - Forsyth County Public Library
\nData Citation of the Item Usagi Yojimbo, book 3, the wanderer's road, by Stan Sakai


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Allen Wiggins - Stats\nLong Jump 4.88m\nShot Put 17.34m\n300 Meter Dash 35.38\nShot Put 16.63m\nShot Put 15.41m\nShot Put 15.8m\nAllen Wiggins (First Academy) - Feb 27\nTrack & Field Top 50: Boys Shot Put: Carter, Wiggins He...\nThree of the four state champions from 2015 return for their senior seasons. Eron Carter (2A), Allen Wiggins (1A), and Macon Rodier (4A) come in with the top three marks as well. Palatka's Carter and ...


wrong wrong save for pasting 2020 'ASTORS' CHAMPIONS | Joomag在线报刊亭\nwrong save for pasting 2020 'ASTORS' CHAMPIONS\n出版日期 8 February 2021 / “商业, 综合” / 语言—English / 301页\nThe Annual 'ASTORS' CHAMPIONS Edition includes 'the Best Products of 2020 'A Year in Review', with a review of the ‘ASTORS’ Award Winning products and programs, highlighting key details on many of the winning firms products and services, includes video interviews and more. It also includes featured guest editorial pieces from some of the security industry’s most respected leaders, and recognized firms in the 2020 ‘ASTORS’ Awards Program. 更多\nThe 2020 'ASTORS' CHAMPIONS Edition Fully Interactive Magazine - the Best Products of 2020 'A Year in Review' is your Go To Guide from Physical Security (Access Control, Critical Infrastructure, Perimeter Protection and Video Surveillance Cameras and Video Management Systems), to IT Security (Cybersecurity, Encryption, Data Storage, Anti-Malware and Networking Security – Just to name a few), to Detect, Delay, Respond to, and Mitgate today’s real-time threats in our evolving security landscape. 更多\n标签: education · reviews · military · communications · cloud computing · cyber security · homeland security · law enforcement · public safety · encryption · first responders · it security · biometrics · aerospace · emergency response · data storage · facial recognition · video analytics · government security · ports of entry · video surveillance · physical security · perimeter protection · critical infrastructure · cbrne detection · security services · federal agencies · campus security · disaster prevention · border security · maritime security · corporate facilities · networking security · 'astors' homeland security awards program · crisis responders · municipal agencies · state agencies


Samsung Dryer Filter Check Flow Sense Lg Dryer Beautiful Lg Dryer Takes Too Long Model Dlex2650w Repair Parts Of Flow Flow Sense Lg Dryer Elegant Samsung Dryer Filter Check Samsung Dryer Filter Check Reset – candidmagnet.info\nsamsung dryer filter check flow sense lg dryer beautiful lg dryer takes too long model dlex2650w repair parts of flow flow sense lg dryer elegant samsung dryer filter check samsung dryer filter check reset.\nsamsung dryer filter check icon in bootstrap,samsung dryer filter check icon in excel,samsung dryer filter check light is on but filter is clean,samsung dryer filter check blinks 5 times table song,samsung dryer filter check light how to fix it,samsung dryer filter check blinks 5 times 5,samsung dryer filter check light reset,samsung dryer filter check blinks 5 times 15,samsung dryer filter check light,samsung dryer filter check problems,samsung dryer filter check light came on.\nPosted on 11/22/2019 08:03:15 am Full size samsung-dryer-filter-check-flow-sense-lg-dryer-beautiful-lg-dryer-takes-too-long-model-dlex2650w-repair-parts-of-flow-flow-sense-lg-dryer-elegant-samsung-dryer-filter-check-samsung.jpg


view - Picture of Fatumaru Lodge, Port Vila - TripAdvisor\nview - Picture of Fatumaru Lodge, Port Vila\n"Boutique beach resort...\n1 helpful vote “"Boutique beach resort in Paradise"”\nI stayed with Fatumaru Lodge for 1 week because i need a break from busy life in Auckland and I can't be more happy that i have selected the right place to relax, with no noise and air pollution. Front desk have amazing friendly people who are ready to help you to select the best choice of tour that suit...\nMore Review collected in partnership with this hotel This business uses tools provided by TripAdvisor (or one of its official Review Collection Partners) to encourage and collect guest reviews, including this one. Helpful? Thank Neel04 Report Been to Fatumaru Lodge? Share your experience!\nAdd Photo See all 386 reviews of Fatumaru Lodge Explore similar hotels Warwick Le Lagon - Vanuatu 1,414 ReviewsShow Prices 2.9 miles Holiday Inn Resort Vanuatu 631 ReviewsShow Prices 0.9 miles Poppy's on the Lagoon 381 ReviewsShow Prices 1.6 miles See all Port Vila hotels About Us


WTO International Symposium|中華經濟研究院\nWTO International Symposium\nSupported by: Office of Trade Negotiations, Executive Yuan\nDate: 09:00-16:30, Dec. 16, 2019 (Monday)\nVenue: Tsai Lecture Hall, College of Law, National Taiwan University\n致歡迎詞暨開場演講 Opening Remarks & Keynote\nKeynote Speaker: Mr. Chen Chung DENG, Minister without Portfolio & Chief Negotiator, Executive Yuan\nSession 1: The Challenges Facing the WTO in 2020 and Beyond\n講 者：瑞士伯恩大學世界貿易研究所Peter Van den Bossche教授\nModerator: Prof. Guang-Hwa YANG, Dept. of International Business, National Cheng-Chi University, Taiwan\nSpeaker: Prof. Peter VAN DEN BOSSCHE, World Trade Institute, Switzerland\nDiscussant: Prof. Wen-Chen SHIH, Dept. of International Business, National Cheng-Chi University, Taiwan\nSession2 : The National Security Exception in an Era of Growing Geopolitical Rivalry\n講 者：美國哈佛大學法學院Henry L. Stimson講座教授伍人英教授\nModerator: Prof. Tsai-Yu LIN, College of Law, National Taiwan University, Taiwan\nSpeaker: Prof. Mark WU, the Henry L. Stimson Professor, Harvard Law School\nDiscussant: Dr. Huai-Shing YEN, Taiwan WTO and RTA Center, Chung-Hua Institution for Economic Research, Taiwan\nSession 3: Future Imperfect: Mapping Digital Trade in the Data-Driven Economy\n講 者：加拿大國際治理創新中心Dan Ciuriak資深研究員\nModerator: Prof. Shin-Yi PENG, Institute of Law for Science and Technology, National Tsing Hua University, Taiwan\nSpeaker: Mr. Dan CIURIAK, Centre for International Governance Innovation, Canada\nDiscussant: Dr. Roy Chun LEE, Taiwan WTO and RTA Center, Chung-Hua Institution for Economic Research, Taiwan\nModerator: Former Constitutional Court Justice Chang-Fa LO\nDiscussants: All the speakers, moderator and discussants above\nThe conference is conduct in English. Simultaneous interpretation is available.\n若有任何疑問，歡迎來電詢問：02-2735 6006 轉3346 施小姐、3343 楊小姐。


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Risultati GFL 2 2021 in diretta, Football Americano Germania - Diretta.it\nRisultati in diretta GFL 2 2021, Risultati, Classifiche\nSA÷5¬~ZA÷GERMANIA: GFL 2¬ZEE÷jodOP8aP¬ZB÷81¬ZY÷Germania¬ZC÷tz38z3Yi¬ZD÷p¬ZE÷42KPAsr0¬ZF÷2¬ZO÷0¬ZG÷1¬ZH÷81_jodOP8aP¬ZJ÷2¬ZL÷/football-americano/germania/gfl-2/¬OAJ÷ATkIliYI-SMsn1kKD.png¬ZX÷08Germania 008rmania0450000000001000GFL 2 005......000¬ZCC÷0¬ZAF÷Germania¬~AA÷82XhHBSk¬AD÷1627826400¬ADE÷1627826400¬AB÷3¬CR÷3¬AC÷3¬CX÷Fursty Razorbacks¬RW÷0¬AX÷0¬BX÷-1¬WQ÷¬WN÷KIR¬AF÷Kirchdorf Wildcats¬JB÷4CtFBHd2¬GRB÷0¬AH÷14¬BB÷7¬BD÷7¬BF÷0¬BH÷0¬OB÷4Q8gcRhT-KS4ayuvs.png¬WM÷FUR¬AE÷Fursty Razorbacks¬JA÷QLsBCcsd¬AS÷1¬AZ÷1¬GRA÷0¬AG÷52¬BA÷14¬BC÷7¬BE÷12¬BG÷19¬OA÷Y9jlX2U0-x0yHV83r.png¬~AA÷4zxNMX4S¬AD÷1627822800¬ADE÷1627822800¬AB÷3¬CR÷3¬AC÷3¬CX÷Straubing Spiders¬RW÷0¬AX÷0¬BX÷-1¬WQ÷¬WN÷FRA¬AF÷Frankfurt Pirates¬JB÷0GiyJa4S¬GRB÷0¬AH÷8¬BB÷8¬BD÷0¬BF÷0¬BH÷0¬OB÷QVK1aSjT-63TwIILj.png¬WM÷STR¬AE÷Straubing 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Ol Sam 6 | Baebol Long Intenet | Niu Wol Translesen\nOl Sam 6:1-10\nWan prea we man i askem God blong i sore long hem\nDedman i no save presem God (5)\nGod i harem taem man i askem hem blong i sore long hem (9)\nLong daerekta. Blong sing wetem ol instramen we i gat string, long tiun blong Seminit.* Singsing blong Deved. 6 O Jehova, yu no tok blong stretem mi long taem we yu kros,Mo yu no stretem mi long taem we yu no glad.+ 2 O Jehova, yu kaen* long mi, from we mi stap kam slak. O Jehova, yu hilim mi,+ from we ol bun blong mi oli stap seksek. 3 Yes, tingting blong mi* i trabol tumas,+Nao mi askem long yu Jehova se, ?bambae i gohed kasem wetaem?+ 4 O Jehova, yu kambak, mo yu sevem mi,*+From fasin blong yu blong lavem man oltaem, plis yu sevem mi.+ 5 From we long ded, i no gat man i tokbaot* yu. Mo long Gref,* ?hu bambae i presem yu?+ 6 Mi mi stap pulum nogud win blong mi mo mi kam taed.+ Mi stap krae fulnaet, we wota blong ae blong mi i mekem bed blong mi i wetwet gud.*Longfala jea blong mi i fulap gud long wota from we mi stap krae.+ 7 Ae blong mi i kam slak olgeta from mi harem nogud tumas,+Mo i no moa klia* from we ol man oli stap mekem nogud long mi. 8 Yufala we i stap mekem rabis fasin, yufala i gowe long mi,From Jehova bambae i harem saon blong krae blong mi.+ 9 Jehova bambae i harem mi taem mi askem hem blong i sore long mi.+ Jehova bambae i akseptem prea blong mi. 10 Olgeta enemi blong mi bambae oli sem mo oli harem nogud. Mo wantaem nomo bambae oli ron i gobak we oli sem bitim mak.+\n^ PT: “mekem bed blong mi i swim.”\n^ NT: “Mo i kam olfala.”\nOl Sam 6


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Wajtaoa | Oktoba 2013\nLANWIS Afrikaans Albanian Amharic Arabic Armenian Armenian (West) Aymara Azerbaijani Azerbaijani (Cyrillic) Bislama Brazilian Sign Language Bulgarian Catalan Cebuano Chichewa Chinese Cantonese (Simplified) Chinese Cantonese (Traditional) Chinese Mandarin (Simplified) Chinese Mandarin (Traditional) Colombian Sign Language Croatian Czech Danish Dutch Efik English Estonian Ewe Fijian Finnish French Ga Georgian German Greek Guarani Haitian Creole Hiligaynon Hungarian Icelandic Igbo Iloko Indonesian Italian Italian Sign Language Japanese Japanese Sign Language Kazakh Kikongo Kikuyu Kiluba Kinyarwanda Kirghiz Korean Kwangali Latvian Lingala Lithuanian Luo Malagasy Mexican Sign Language Myanmar Ngabere Norwegian Nzema Papiamento (Aruba) Papiamento (Curaçao) Peruvian Sign Language Polish Portuguese Punjabi Quechua (Bolivia) Rarotongan Romanian Russian Russian Sign Language Sango Sepedi Serbian Serbian (Roman) Sesotho (Lesotho) Setswana Shona Silozi Silozi Silozi Slovenian Spanish Spanish Sign Language Sranantongo Swahili Swedish Tagalog Tahitian Tatar Thai Tigrinya Tsonga Turkish Twi Ukrainian Vietnamese Wayuunaiki Xhosa Yoruba Zulu\nHaf ya i tokbaot wan Witnes we i stap storian wetem narafala. Yu traem tingbaot se, wan Witnes we nem blong hem Maria i kam long haos blong wan woman nem blong hem Sofia, nao tufala i stap storian.\n?FROM WANEM GOD I LETEM OL SAMTING YA OLI HAPEN?\nMaria: Mi mi kam long haos blong yu tede blong givim wan samting long yu. Hemia smol pepa ya se, ?Yu Yu Wantem Save Trutok?\nSofia: ?Hemia blong wanem ya, blong skul?\nMaria: Yes. Yu luk se long fored blong pepa ya i gat sikis kwestin, hemia se—\nSofia: !Eh! Yu no westem taem blong toktok wetem mi.\nMaria: ?From wanem yu talem olsem?\nSofia: From we mi mi no bilif long God.\nMaria: Mi glad we yu talemaot tingting blong yu long mi. ?Be longtaem finis yu yu no bilif long God?\nSofia: No, fastaem mi mi stap go long jos. Be longtaem nao mi mi no moa go.\nMaria: !A yes! Sore mi no talem nem blong mi long yu. Nem blong mi Maria.\nSofia: Mi Sofia.\nMaria: Mi glad blong mitim yu.\nSofia: I Gud blong luk yu tu.\nMaria: Yu luk Sofia, mi mi no kam blong fosem yu blong yu bilif olsem mi. Mi wantem askem wan kwestin long yu. ?I gat wan samting we i mekem se yu yu no bilif long God?\nSofia: Yes. Mama blong mi i bin aksiden long wan trak, 17 yia i pas finis.\nMaria: Oh, mi sore blong harem samting ya. ?Afta wanem i hapen long hem?\nSofia: Aksiden ya i mekem se, kam kasem naoia, hem i no moa save wokbaot.\nMaria: Oh man sore tumas. Mi save se hemia i mekem yu yu harem nogud tumas.\nSofia: Yes, hemia nao i mekem se tingting blong mi i fasfas. Mi stap tingbaot se, ?sipos God i stap, from wanem hem i letem samting ya i hapen? ?From wanem hem i letem yumi harem nogud olsem?\n?I RONG BLONG ASKEM OL KWESTIN OLSEM?\nMaria: I no rong blong gat tingting olsem, mo i stret nomo we yu askem ol kwestin ya. Taem yumi harem nogud, oltaem yumi wantem save se from wanem samting olsem i hapen. ?Yu yu save se Baebol i tokbaot sam man blong God we olgeta tu oli stap askem ol kwestin olsem?\nMaria: ?Yu yu glad sipos mi soem wan eksampol blong wan man we Baebol i tokbaot?\nSofia: Yes i oraet.\nMaria: Yu traem luk wanem we profet Habakuk i askem long God. Bambae yumitu ridim long Habakuk 1:2, 3, we i talem se: “Hae God. Naoia, long ples blong mifala, ol man oli stap faet, oli stap kilkilim olgeta oli ded. Oltaem, mi stap krae i kam long yu blong yu givhan long mifala. ?Be wetaem bambae yu harem mi, yu tekemaot mifala long ol trabol ya? ?From wanem yu letem mi mi stap luk ol trabol ya olsem?” ?Olsem wanem? ?Yu luk se ol kwestin ya oli sem mak long ol kwestin we yu yu stap askem?\nMaria: ?Yu ting se God i kros long Habakuk from we hem i askem ol kwestin olsem? ?Yu ting se God i talem long hem se hem i nidim moa bilif? !Nogat!\nSofia: !Man i tru ya!\nJEHOVA I NO LAEKEM NATING BLONG LUK WE MAN I SAFA\nMaria: Baebol i talem se God stap luk ol samting we i mekem yumi harem nogud, mo hem i stap tingbaot yumi.\nSofia: ?Yu minim wanem?\nMaria: Bambae mi soem wan eksampol we i stap long Eksodas 3:7. ?Yu yu glad blong ridim vas ya?\nSofia: Oke, i talem se: “Nao Hae God i talem long hem se, ‘Yufala ol laen blong Isrel, yufala i man blong mi, mo mi mi luk finis ol rabis fasin ya we ol man Ijip oli stap mekem long yufala. Mi harem krae blong olgeta ya we oli stap long Ijip, we oli wantem mi mi tekemaot olgeta long han blong ol man ya we oli stap fosem olgeta blong oli wok slef blong olgeta. Mi mi save finis we oli harem nogud tumas, mo oltaem mi stap tingting long olgeta.’”\nMaria: Tangkiu. Folem vas ya we yu ridim, ?yu ting se God i luk ol trabol we ol man blong hem oli stap kasem?\nSofia: Yes, hem i luk trabol blong olgeta.\nMaria: God i no lukluk nomo trabol we i kasem olgeta. Yu traem luk samting we las haf blong vas ya i talem. God i talem se: “Mi mi save finis we oli harem nogud tumas, mo oltaem mi stap tingting long olgeta.” ?Ol tok ya oli soemaot se God i tingbaot yumi?\nSofia: Yes, hem i tingbaot yumi.\nMaria: Yes. God i no stap lukluk ol trabol blong yumi nomo, be hem i harem nogud tu, taem yumi kasem trabol.\nSofia: !Man tru ya!\nMaria: Yu tingbaot fas eksampol ya, mo naoia bambae yumitu luk wan narafala eksampol bakegen. Bambae yumitu ridim long Sekaraea 2:8. Long fas haf blong vas ya i talem se: “Taem wan man i kilim yufala, i olsem we man ya i kilim ae blong mi stret.” ?Yu ting se taem ol man blong God oli harem nogud, hemia i mekem God i harem nogud tu?\nSofia: Yes i luk olsem se hem tu i harem nogud.\nMaria: I tru Sofia, God i tingbaot yumi, mo hem i no laekem nating blong luk yumi harem nogud. Taem yumi harem nogud, hem tu i harem nogud wetem yumi.\n?FROM WANEM JEHOVA I NO MEKEM WAN SAMTING?\nMaria: Bifo mi go, mi wantem talem wan samting long yu.\nSofia: I stret nomo.\nMaria: Yu traem tingbaot samting we Baebol i talem long saed blong paoa blong God. Mi stap tingbaot wan vas, hemia long Jeremaea 10:12. ?Yu glad blong ridim vas ya plis?\nSofia: Yes. “Nao Profet Jeremaea i leftemap nem blong Hae God, i talem se, ‘Hae God i mekem wol ya long paoa blong hem nomo. Long waes blong hem, hem i putum wol ya i stap gud, mo long save blong hem, hem i putum skae long ples blong hem.’”\nMaria: Tangkiu. Yu traem tingbaot. ?Yu ting se God i gat bigfala paoa blong wokem heven mo wol wetem olgeta samting we oli stap long tufala?\nMaria: Sipos God i gat paoa blong wokem evri samting we yumi luk raonabaot long yumi, ?yu ting se hem i gat paoa tu blong finisim ol trabol we oli stap mekem yumi harem nogud?\nMaria: Tingbaot mama blong yu. ?From wanem yu yu wari taem yu luk se mama blong yu i harem nogud?\nSofia: Hemia from we hem i mama blong mi, mo mi lavem hem.\nMaria: I tru mo sipos yu gat paoa blong mekem hem i kamgud bakegen, ?bambae yu yu mekem?\nSofia: Yes, bambae mi mekem ya.\nMaria: Baebol i talem se God i gat bigfala paoa, hem i luk we yumi stap harem nogud, mo hem i sore long yumi. Yu traem tingbaot. God i save tekem aksen kwiktaem nomo blong finisim ol trabol we i mekem yumi harem nogud. Be hem i no mekem olsem. ?From wanem? From we hem i bos gud long tingting blong hem.\nSofia: Man, mi neva tingbaot samting ya.\nMaria: ?From wanem God i tekem longtaem tumas blong finisim ol trabol we yumi kasem? ?Yu ting se hem i gat wan gudfala risen blong mekem olsem? *\nSofia: Ating yes.\nMaria: Mi harem se mobaelfon blong yu i ring, ?i oraet sipos mi kambak long wan narafala taem blong yumitu save storian moa long samting ya?\nSofia: Yes i oraet nomo, mi glad. Tangkiu tumas. *\nI gat sam kwestin we yu yu wantem save ansa blong olgeta? ?Yu yu wantem save moa long bilif mo wok we ol Witnes blong Jehova oli stap mekem? Sipos i olsem, yu no fraet blong toktok wetem ol Witnes. Olgeta bambae oli glad nomo blong tokbaot ol samting ya wetem yu.\n^ par. 61 Sipos yu wantem save moa, yu luk japta 11 blong buk ya ?Wanem Samting We Baebol i Rili Tijim? we ol Witnes blong Jehova oli wokem.\n^ par. 64 Nekis Wajtaoa bambae i tokbaot from wanem God i letem man i safa.\nSTORI BLONG FRAN PEJ Ol Rabis Pija—?Oli Save Spolem Yu No Nogat?\nKEYS TO FAMILY HAPPINESS ?Yu yu mared bakegen?\n?Olgeta Lanwis Oli Kamaot Long Taoa Blong Babel?\nSTORIAN WETEM WAN NEBA Does God Care About Our Suffering?\n?From Wanem Yufala i Stap Go Long Haos Blong Ol Man?\nText Ol defren wei blong daonlodem ol buk long intenet WAJTAOA Ol Rabis Pija, ?Oli Save Spolem Yu?\nOl Rabis Pija, ?Oli Save Spolem Yu?\nWAJTAOA Ol Rabis Pija, ?Oli Save Spolem Yu?


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