**Improving Fertilizer Use Efficiency–Methods and Strategies for the Future**

Editors

**Przemysław Barłóg Jim Moir Lukáš Hlisnikovský Xinhua He**

Basel • Beijing • Wuhan • Barcelona • Belgrade • Novi Sad • Cluj • Manchester

*Editors* Przemysław Barłóg Poznan University of Life Sciences Poznan, Poland

Xinhua He University of Western Australia Perth, Australia

Jim Moir Lincoln University Christchurch, New Zealand Lukáš Hlisnikovský Crop Research Institute Prague, Czech Republic

*Editorial Office* MDPI St. Alban-Anlage 66 4052 Basel, Switzerland

This is a reprint of articles from the Special Issue published online in the open access journal *Plants* (ISSN 2223-7747) (available at: https://www.mdpi.com/journal/plants/special\_issues/Fertilizer\_ Use\_Efficiency).

For citation purposes, cite each article independently as indicated on the article page online and as indicated below:

Lastname, A.A.; Lastname, B.B. Article Title. *Journal Name* **Year**, *Volume Number*, Page Range.

**ISBN 978-3-0365-9582-5 (Hbk) ISBN 978-3-0365-9583-2 (PDF) doi.org/10.3390/books978-3-0365-9583-2**

© 2023 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) license.


**4.1 High-speed AND gate beyond 160 Gb/s**

The simulation results of the AND gate at 160 Gb/s will be given in Section 4.1.1, while the corresponding experimental results (i.e., wavelength conversion) at 170 Gb/s will be presented in Section 4.1.2.


**Author details**

**Figure 6.** Sensitivity of congestion delay weighting using WSM

**Figure 5.** The WSM and TOPSIS scores for the non- real-time application

98 Selected Topics in WiMAX

Mohammed A. Ben-Mubarak, Borhanuddin Mohd. Ali, Nor Kamariah Noordin, Alyani Ismail and Chee Kyun Ng

Department of Computer and Communication Systems Engineering, Faculty of Engineer‐ ing, Universiti Putra Malaysia, Selangor, Malaysia


**6. Wearable devices in future**

*Wearable Devices - The Big Wave of Innovation*

English paper exam results Between

Computer paper exam results Between

**Table 4.**

**Table 5.**

*One-way ANOVA results.*

groups

groups

This research was significant in its own ways of research and its findings; and it aims to compare the success of students in English paper exams and English mobile

**Sum of squares**

Within groups 14077.36 72 195.52

Within groups 8681.68 72 120.58

Total 14350.08 74

Total 9459.52 74

**Sum of squares**

Computer mobile exams Between groups 60.67 2 30.33 0.24 0.784 Within groups 8939.00 72 124.15

Total 8999.67 74 English mobile exams Between groups 40.67 2 20.33 0.053 0.948 Within groups 27478.00 72 381.64

Total 27518.67 74

**Df Mean square**

272.72 2 136.36 0.70 0.50

777.84 2 388.92 3.23 0.046

**Df Mean square** **F Sig.**

**F Sig.**

exams, as well as discussing smartphone pros and cons as assessment tools.

*One-way ANOVA results for computer mobile and English mobile exams.*

From the previous experiences, it was observed that there were Internet accessibility problems when all the students tried to access the exam at the same time. Therefore, students are divided into groups and entered the exam. Even with smaller groups, it was observed that the questions were emerging slowly. By

Mostly, students had tried to find a way to cheat or to disobey the given rules; and they tested the programs by their own ways. They tried to take screenshots of the program, and this was prevented successfully. The students who tried to do this were warned by the course teacher. One student tried to shade the questions and cheat; this was also successfully prevented by displaying him a warning message.

The exam started when the teacher had made an active link on the Internet. Since the students used translation programs in their daily lives, their smartphones

increasing the speed of Internet access, this problem was elevated.

**5.1 Internet access problems**

**5.2 Print screen and copy problems**

**5.3 Translation problems**

**106**

We are residing in a planet where technology is contemporary in our life routines. The more that you know, the more that you want to know! Knowledgeable people are generally more keen on learning new technological devices. People's relatively high rates of prior experience with computers and smartphones may partially explain the sample's high willingness to accept smart wearable devices [4]. Today, smartphones are one of the vastest revolutions in individuals' life spans. Smartphones are becoming increasingly popular, both in formal and informal educational environments. Although benefits and obstacles in using smartphones as assessment tools can be discussed, "70 percent of students and teachers agree that they prefer to write work and notes on their computers rather than writing on paper" [52], and recent studies shows that students are as successful in smartphone exams as they are in written exams.

There are different students with different social needs: some are keen on being virtually social, and some are keen on being physically social (see **Figure 3**). Some research studies show that the younger physically social students are more successful than the younger virtually social ones [53, 54]; a solution to these would be improving wearable technologies in a way that students can both be physically and virtually social!

**Figure 3.** *Physically virtual and virtually social [53, 54].*

*Wearable Devices - The Big Wave of Innovation*


*2.2. Statistical Analysis*

The percentage of sex, four categories of monthly income, four categories of PECs, and mortality rates were compared to understand the differences between all patients with head injuries and the patients with moderate-to-severe head injuries. Means, medians, and standard deviations of continuous variables, such as age, monthly income, Charlson comorbidity index, and ICD/ISS were analyzed using analysis of variance (ANOVA). The relative odds of death in the admission course were estimated by using binary logistic regression with the backward conditional stepwise method. Statistical significance was set at *p* < 0.05. All the data analyses were generated by using SPSS software, version 20.0 (IBM Corporation, New York, NY, USA). Institutional board review was waived because this study involved secondary data analysis of a well-encrypted database.