bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transforming Philippine Agriculture Through Data-driven Innovation: A Quantitative Landscape Assessment to Prioritize Technological Solutions
Authors: Taer Albino Namoc , Taer Erma Catipan 
Published: February 2024

Abstract
This systematic review analyzed agricultural innovations in the Philippines over 2018–2023 to provide comprehensive categorization, adoption trend analysis, and recommendations for optimizing research priorities. Methodical literature search, screening, and quantitative analysis facilitated organized investigation across innovation types, contributors, applications, and geographical contexts. Results revealed image analysis followed by the sustainable farming system had the highest segment (26% and 23%, respectively) of the innovation categories displaying cutting-edge techniques as well as environmental stewardship. Rice-centric innovations dominate (33.33%) showcasing the underrepresentation of high-value crops, livestock, and remote farming sectors. However, innovations have skewed geographical representation with 69.23% of studies concentrating only on Luzon regions, chiefly central and northern areas. Agricultural potential also exists across Visayas and Mindanao warranting increased emphasis. Additionally, most research contributors represent less than 5% share each, indicating a fragmentation in efforts lacking cross-institutional partnerships. Findings exposed critical gaps in innovation prioritization and adoption levels directed at sustainable practices, precision technologies, non-cereal commodities, and geographically disadvantaged communities. Significant institutional support is imperative to address disparities through modernization policies and localized capacity-building programs aided by industry-academia partnerships. Unified innovation transfer conduits can accelerate the transition of solutions from proofs-of-concept to farmer-ready tools catering to regional needs.
Uncovering the Truth: A Deep Learning Ensemble Model for Identifying Fake News
Authors: Namatullah Arooba , Khurshid Syed Khaldoon , Jaleel Abdul , Khan Maryam , Rashid Sania 
Published: February 2024

Abstract
The rapid outspread of misinformation and its continuous spreading on digital platforms have raised a serious concern due to its ability to create harmful effects. Over the past ten years, fake news has become increasingly popular in Pakistan. Now it’s a challenging task to identify or differentiate among fake news and real news. Several researchers have made tremendous advancements to detect misleading information in previous years, but due to the nature of the problem, there are still several unresolved problems. The main goal of this research is to create the detection dataset for Pakistani news by semantically extracting news data from various sources and through social media platforms. We have categorized the textual properties of news article. To evaluate our proposed dataset, we used various learning algorithms namely Naive Bayes, Support Vector Machine (SVM), Random Forrest, Logistic Regression, Recurrent neural network (RNN), Long short-term memory (LSTM) and Bidirectional Long short-term memory (Bi-LSTM). By merging them, we built an Ensemble Learning classifier (Meta Model) to achieve higher accuracy. Our findings proved that our proposed Deep Ensemble Learning model outperformed others with an accuracy of 89 percent. The outcomes also demonstrated that an ensemble model outperformed the individual Base model. The findings suggested that an ensemble model can maximize not only accuracy but it can also be used on small datasets. The metrics like accuracy, Precision, F1-score and recall are used to measure an effectiveness of each applied model.
Reducing PAPR for the FBMC-OQAM System Using Gaussian and Laplace Based Linear Companding Transform
Authors: Ramavath Srinivas , Samal Umesh Chandra 
Published: February 2024

Abstract
In this paper, two new companders are designed to reduce the ratio of peak to average power (PAPR) experienced by filter bank multicarrier (FBMC) signals. Specifically, the compander basic model is generalized, which alter the distributed FBMC signal amplitude peak. The proposed companders design approach provides better performance in terms of reducing the PAPR, Bit Error Rate (BER) and phase error degradation over the previously existing compander schemes. Many PAPR reduction approaches, such as the µ-law companding technique, are also available. It results in the formation of spectrum side lobes, although the proposed techniques result in a spectrum with fewer side lobes. The theoretical analysis of linear compander and expander transform for a few specific parameters are derived and analyzed. The suggested linear companding technique is analytically analysed using simulations to show that it efficiently decreases the high peaks in the FBMC system.
Cutting-edge Technology and Systems for Water Treatment and Reuse
Authors: Jin Peng-Kang 
Published: February 2024

Abstract
Water treatment and reuse is the key strategy to address the problems of water shortages. This book deals with various problems and investigates different treatment technologies concerning water reuse. In response to the challenges of severe water shortages and the deterioration of water quality, the focus on cutting-edge technology and systems for water treatment and reuse is fast-growing worldwide. Progress is needed to provide high quality reclaimed water, minimize the risks to environment and human health, and support use of non-conventional water resources.
In Focus–a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.
Iron-based autotrophic denitrification driven by sponge iron for nitrite removal in an anaerobic bioreactor: Effect of iron and carbon source
Authors: Ren Shuang , Wang Peng , Li Wenxuan , Zhu Hongjuan , Hu Kaiyao , Mu Hao , Gao Xiaoyi , Wang Wei 
Published: February 2024

Abstract

The study investigated the denitrification effect of the iron autotrophic denitrification process for removing nitrite under anaerobic conditions, utilizing sponge iron as the electron donor. When the C/N ratio equaled 1, defined as the ratio of chemical oxygen demand to total nitrogen (TN), and the influent nitrite nitrogen (NO2−-N) was at 80 mg/L, the average steady-state TN effluent concentration of this system was 41.94 mg/L during the 79-day experiment. The TN value exhibited a significant decrease compared to both the sponge iron system (68.69 mg/L) and the carbon source system (56.50 mg/L). Sponge iron is beneficial for providing an electron donor and ensuring an anaerobic system, fostering an environment that promotes microorganism growth while effectively inhibiting the conversion of nitrite to nitrate. In addition, carbon sources play a vital role in ensuring microorganism growth and reproduction, thereby aiding in TN removal. The optimal parameters based on the effectiveness of TN removal in the iron autotrophic denitrification system were determined to be s-Fe0 dosage of 30 g/L and C/N = 1.5. These results suggest that the iron autotrophic denitrification process, driven by sponge iron, can effectively remove nitrite under anaerobic conditions.
Targeting Lysosomes: A Strategy Against Chemoresistance in Cancer
Authors: Shirbhate Ekta , Singh Vaibhav , Mishra Aditya , Jahoriya Varsha , Veerasamy Ravichandran , Tiwari Amit K , Rajak Harish 
Published: February 2024

Abstract:
Chemotherapy is still the major method of treatment for many types of cancer. Curative
cancer therapy is hampered significantly by medication resistance. Acidic organelles like lysosomes
serve as protagonists in cellular digestion. Lysosomes, however, are gaining popularity due to their
speeding involvement in cancer progression and resistance. For instance, weak chemotherapeutic
drugs of basic nature permeate through the lysosomal membrane and are retained in lysosomes in
their cationic state, while extracellular release of lysosomal enzymes induces cancer, cytosolic escape
of lysosomal hydrolases causes apoptosis, and so on. Drug availability at the sites of action is
decreased due to lysosomal drug sequestration, which also enhances cancer resistance. This review
looks at lysosomal drug sequestration mechanisms and how they affect cancer treatment resistance.
Using lysosomes as subcellular targets to combat drug resistance and reverse drug sequestration is
another method for overcoming drug resistance that is covered in this article. The present review has
identified lysosomal drug sequestration as one of the reasons behind chemoresistance. The article
delves deeper into specific aspects of lysosomal sequestration, providing nuanced insights, critical
evaluations, or novel interpretations of different approaches that target lysosomes to defect cancer.
SegEIR-Net: A Robust Histopathology Image Analysis Framework for Accurate
Breast Cancer Classification
Authors: Singh Pritpal , Kumar Rakesh , Gupta Meenu , Al-Turjman Fadi 
Published: February 2024

Background::
Breast Cancer (BC) is a significant threat affecting women globally. An accurate and reliable disease classification method is required to get an
early diagnosis. However, existing approaches lack accurate and robust classification.

Objective::
This study aims to design a model to classify BC Histopathology images accurately by leveraging segmentation techniques.

Methods::
This work proposes a combined segmentation and classification approach for classifying BC using histopathology images to address these issues.
Chan-Vese algorithm is used for segmentation to accurately delineate regions of interest within the histopathology images, followed by the
proposed SegEIR-Net (Segmentation using EfficientNet, InceptionNet, and ResNet) for classification. Bilateral Filtering is also employed for noise
reduction. The proposed model uses three significant networks, ResNet, InceptionNet, and EfficientNet, concatenates the outputs from each block
followed by Dense and Dropout layers. The model is trained on the breakHis dataset for four different magnifications and tested on BACH (BreAst
Cancer Histology) and UCSB (University of California, Santa Barbara) datasets.

Results::
SegEIR-Net performs better than the existing State-of-the-Art (SOTA) methods in terms of accuracy on all three datasets, proving the robustness
of the proposed model. The accuracy achieved on breakHis dataset are 98.66%, 98.39%, 97.52%, 95.22% on different magnifications, and 93.33%
and 96.55% on BACH and UCSB datasets.

Conclusion::
These performance results indicate the robustness of the proposed SegEIR-Net framework in accurately classifying BC from histopathology
images.
Association between the Nurses` Productivity and Quality of Work Life in Covid-19 Referral Hospital: Evidence from Iran
Authors: Bastani Peivand , Yusefi Ali Reza , Ahmadidarrehsima Sudabeh , Mashayekhi Mahsa 
Published: February 2024

Introduction:
Nurses' productivity is assumed as a determinant factor affecting patients` health promotion. The productivity of the nurses can be influenced by many factors.

Objectives:
This study aims to determine the association between the nurses` productivity and their quality of work life (QWL) in the south of Iran.

Methods & Materials:
This was a cross-sectional study conducted in 2021. 312 nurses by census were included. A researcher-made questionnaire was used to collect the data. Data were analysed by descriptive and analytical statistics, including Independent T-test, ANOVA, Pearson correlation, and multiple linear regression applying SPSS23 at the significant level of 0.05.

Results:
According to the results, the mean score of productivity and QWL were 89.32±9.24 out of 125 and 91.63±7.01 out of 160, respectively. There was a positive significant statistical correlation between the nurses` productivity and QWL (r=0.621, p<0.0001). Based on the results of linear regression, the following dimensions of QWL were identified as the predictor of nurses` productivity respectively: problem-solving, willingness and motivation to work, engagement in decision making (p<0.0001), employment promotion, communication, job security (p=0.001), salary and payments, and employment proud and honour (p=0.002).

Conclusion:
As the present results show, the studied nurses` productivity was evaluated at a good level. There was a positive correlation between the nurses` productivity and QWL and the dimensions of QWL were identified as the predictors of productivity. Planning for improvement and promotion of each of these dimensions according to the contextual determinants are recommended to improve the nurses` productivity to an excellent level.
Attitudes Toward and Use of eHealth Technologies Among German Dermatologists: Repeated Cross-Sectional Survey in 2019 and 2021
Authors: Augustin Matthias , Reinders Patrick , Janke Toni Maria , Strömer Klaus , von Kiedrowski Ralph , Kirsten Natalia , Zink Alexander , Otten Marina 
Published: February 2024

Background
In recent years, legal and infrastructural conditions have been set to improve the adoption of digital applications in health care in Germany. The impact of these actions was amplified by the COVID-19 pandemic. So far, no studies have confirmed this progress in dermatology.

Objective
The aim of this study was to measure changes in knowledge, interest, expectation, and use of digital applications in health care among dermatologists in Germany in 2019 and 2021.

Methods
We administered a repeated cross-sectional survey among dermatologists in medical practices and clinics in Germany at 2 time points: t1 (2019; before the COVID-19 pandemic) and t2 (2021; during the COVID-19 pandemic). We used a standardized questionnaire, including items on respondents’ knowledge, interest, expectation, and use of digital applications, as well as their demographics. The survey was distributed by post and email. The data were analyzed descriptively as well as with multiple logistic regressions.

Results
At t1, 585 (272/571, 47.6% female; mean age 52.4, SD 8.9 years) dermatologists and at t2, 792 (360/736, 48.9% female; mean age 54.3, SD 8.6 years) dermatologists participated in this survey. Interest in digital medicine was higher at t1 than at t2 (381/585, 65.1% vs 458/792, 57.8%; P≤.001). Nevertheless, 38.6% (306/792) had used digital applications more often since the beginning of the pandemic. For example, real-time telemedicine with patients (12/585, 2.1% vs 160/792, 7.6%; P≤.001) and other specialists did increase (33/385, 5.7% vs 181/792, 22.8%; P≤.001). Almost one-third expressed great concerns about digitalization (272/792, 34.3% vs 294/792, 37.1%; P=.21). Spatial analysis revealed higher interest in, more positive expectations toward, and higher use of digital applications in urban areas in comparison to rural areas. For instance, dermatologists from urban areas assessed future applications as having less risk (adjusted odds ratio [aOR] 0.51, 95% CI 0.35-0.76) than did dermatologists from rural areas. The situation was similar with the age groups, as, for example, dermatologists aged <50 years also expected lower risks (aOR 0.51, 95% CI 0.34-0.77) than those aged ≥50 years. There were no differences between sexes in use, but there were differences in knowledge and expectation; for example, male participants assessed their confidence in using digital applications as higher (aOR 1.44, 95% CI 1.01-2.04) than did female participants.

Conclusions
During the pandemic, the use of digital applications in dermatology increased but still remained at a moderate level. The regional and age-related disparities identified indicate the need for further action to ensure equal access to digital care.
Preventive Pharmacological Therapy and Risk of Recurrent Urinary Stone Disease
Authors: Arivoli Kumaran , Valicevic Autumn N. , Oerline Mary K. , Hsi Ryan S. , Patel Sanjeevkumar R. , Hollingsworth John M. , Shahinian Vahakn B. 
Published: February 2024

Background
Urinary stone disease is a prevalent condition associated with a high recurrence risk. Preventive pharmacological therapy has been proposed to reduce recurrent stone episodes. However, limited evidence exists regarding its effectiveness, contributing to its underutilization by physicians. This study aimed to evaluate the association between preventive pharmacological therapy (thiazide diuretics, alkali therapy, and uric acid–lowering medications) and clinically significant urinary stone disease recurrence.

Methods
Using data from the Veterans Health Administration, adults with an index episode of urinary stone disease from 2012 through 2019 and at least one urinary abnormality (hypercalciuria, hypocitraturia, or hyperuricosuria) on 24-hour urine collection were included. The primary outcome was a composite variable representing recurrent stone events that resulted in emergency department visits, hospitalizations, or surgery for urinary stone disease. Cox proportional hazards regression was performed to estimate the association between preventive pharmacological therapy use and recurrent urinary stone disease while adjusting for relevant baseline patient characteristics.

Results
Among the cohort of patients with urinary abnormalities (n=5637), treatment with preventive pharmacological therapy was associated with a significant 19% lower risk of recurrent urinary stone disease during the 12–36-month period after the initial urine collection (hazard ratio, 0.81; 95% confidence interval, 0.65 to 1.00; P = 0.0496). However, the effectiveness of preventive pharmacological therapy diminished over longer follow-up periods (12–48 and 12–60 months after the urine collection) and did not reach statistical significance. When examining specific urinary abnormalities, only alkali therapy for hypocitraturia was associated with a significant 26% lower recurrence risk within the 12–36-month timeframe (hazard ratio, 0.74; 95% confidence interval, 0.56 to 0.97; P = 0.03).

Conclusions
When considering all urinary abnormalities together, this study demonstrates that the use of preventive pharmacological therapy is associated with a lower risk of clinically significant recurrent episodes of urinary stone disease in the 12–36 month timeframe after urine collection, although only the association with the use of alkali therapy for hypocitraturia was significant when individual abnormalities were examined.
REDUCING STUDENTS’ COMMUNICATION APPREHENSION THROUGH GROUP WORK AS THE INTERACTIVE LEARNING ACTIVITY AT UNIVERSITAS PGRI SUMATERA BARAT
Authors: Siska Siska , Ikhsan M Khairi , Yelliza Yelliza 
Published: February 2024

The high level of communication apprehension is one of the most frequent problems for the students as the English foreign language learners, somehow giving the appropriate interactive learning activities could be good solution for these problems. Therefore, this research was aimed at finding out the students’ responses on the using of group work as the learning activities to reduce their communication apprehension. The research was conducted on the second year students of English Department at Universitas PGRI Sumatera Barat. The total number of respondents in this research was 21 students from 2022 B class selected purposively based on the subject matter; speech that use group work as the learning activities. This research was qualitative in nature since it used observation and an interview to collect the data. Students’ positive responses on using group work as the interactive learning activities to reduce their communication apprehension while speaking reached 90 % based on the interview, while data from the observation showed most of the students had positive engagement, good motivation and eager to practice their speech in their own group bravely with high self-confidence. This, the conclusion can be stated that group work as interactive learning activities can help the students to reduce their communication apprehension
Outdoor Learning Model by Utilizing Mount Penanggungan Cultural Heritage to Realize Education for Sustainable Development
Authors: Segara Nuansa Bayu , Suprijono Agus , Marzuqi Muhammad Ilyas 
Published: February 2024

The cultural heritage of Gunung Penanggungan has the potential to become a space for education for sustainable development. But it has not been optimally utilized by formal schools. This study aims to construct a learning model that can contribute to realizing the SDGs through education for sustainable development by utilizing the potential that exists in Mount Penanggungan. Design-based research is used in the development of this outdoor learning model. There are three stages of development: 1) analysis and exploration; 2) design and construction; and 3) evaluation and reflection. The subject of this study was the development of a one-day outdoor learning model involving two experts for qualitative product validation. Research data collection methods are adjusted to the research objectives, including: 1) literature studies, journals, proceedings, and relevant research books; 2) expert review; and 3) a validation sheet of the learning model draft.The data analysis used in this study is a qualitative-verifiable data analysis strategy. The results of this study show the components of the outdoor learning model, which consist of: 1) impact; 2) syntax; 3) the role of the teacher; 4) a support system; and 5) the principles of learning, have been worth testing. The outdoor learning model developed is considered to be in conformity with the objectives of ESD. School support, teacher competence and technical preparation are key to successful learning. The advantage of this model lies in the process of exploration, collaboration and reflection carried out directly in an outdoor class.
PENGARUH UKURAN PERUSAHAAN, SENSITIVITAS INDUSTRI, DAN SERTIFIKASI ISO 14001 TERHADAP NILAI PERUSAHAAN PADA PERUSAHAAN MANUFAKTUR DI INDONESIA
Authors: Darmayanti Kadek Indah , Dewi Luh Gede Kusuma 
Published: February 2024

Penelitian ini bertujuan untuk menganalisis pengaruh ukuran perusahaan, sensitivitas industri, dan sertifikasi ISO 14001 terhadap nilai perusahaan. Populasi dalam penelitian ini adalah perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia tahun 2019-2021. Pengambilan sampel menggunakan metode purposive sampling dengan meggunakan kriteria tertentu. Metode analisis data menggunakan regresi linier berganda. Variabel dependen penelitian ini adalah nilai perusahaan yang diukur dengan menggunakan Tobins’Q. Varibel independen dalam penelitian ini adalah ukuran perusahaan, sensitivitas industri, dan sertifikasi ISO 14001.
Hasil penelitian menunjukkan (a) ukuran perusahaan berpengaruh positif terhadap nilai perusahaan, (b) sensitivitas industri tidak berpengaruh terhadap nilai perusahaan, dan (c) sertifikasi ISO 14001 tidak berpengaruh terhadap nilai perusahaan