bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effluent quality and reuse potential of wastewater treated in constructed wetlands in Southern Brazil
Authors: Sousa Arielle da Rosa , Pelissari Catiane , Laureano Andreza Thiesen , Sezerino Pablo Heleno 
Published: May 2024

ABSTRACT

The main objective of this study was to evaluate the quality and reuse potential of treated effluents by constructed wetlands (CW) systems utilized for decentralized wastewater treatment in urban and rural scenarios in southern Brazil. The assessment, based on Brazilian discharge standards and wastewater reuse guidelines, revealed a close link between treatment efficiency and technological configurations, considering diverse inlet wastewater sources. Most CW treated effluents complied with regulatory standards for disposal, prompting the exploration of reuse scenarios in urban and agricultural settings. However, the study underscores the imperative for rigorous disinfection due to the limited microbiological removal capacity of CW. Overall, the research emphasizes the adaptability and resilience of CW in treating diverse wastewater compositions, highlighting their pivotal role in advancing circular economy principles within sanitation services. Importantly, the findings suggest significant potential for treated wastewater reuse in both urban and agricultural settings. Urban applications, including toilet flushing, floor washing, and garden irrigation, prove feasible for CW systems situated in residential and commercial buildings. Meanwhile, rural CW systems demonstrate suitability for reclaimed water directed toward crop fertigation, tailored to the specific needs and irrigation methods of various crops.
Galectin-3 and Severity of Liver Fibrosis in Metabolic
Dysfunction-Associated Fatty Liver Disease
Authors: Sotoudeheian Mohammadjavad 
Published: May 2024

Abstract:
Metabolic dysfunction-associated Fatty Liver Disease (MAFLD) is a chronic liver disease
characterized by the accumulation of fat in the liver and hepatic steatosis, which can progress
to critical conditions, including Metabolic dysfunction-associated Steatohepatitis (MASH), liver fibrosis,
hepatic cirrhosis, and hepatocellular carcinoma. Galectin-3, a member of the galectin family
of proteins, has been involved in cascades that are responsible for the pathogenesis and progression
of liver fibrosis in MAFLD. This review summarizes the present understanding of the role of
galectin-3 in the severity of MAFLD and its associated liver fibrosis. The article assesses the underlying
role of galectin-3-mediated fibrogenesis, including the triggering of hepatic stellate cells,
the regulation of extracellular degradation, and the modulation of immune reactions and responses.
It also highlights the assessments of the potential diagnostic and therapeutic implications of
galectin-3 in liver fibrosis during MAFLD. Overall, this review provides insights into the multifaceted
interaction between galectin-3 and liver fibrosis in MAFLD, which could lead to the development
of novel strategies for diagnosis and treatment of this prevalent liver disease.
Regulation of Fat Content in Triticale Based on Optimization of Technological Processing Modes
Authors: Kassymbek Rabiga , Iztayev Auyelbek , Balevi Tahir , Chomanov Urishbay , Tultabayev Muhtar , Zhumaliyeva Gulzhan , Aktokalova Gulnara , Shoman Assiya 
Published: May 2024

Introduction
The aim of the study was to regulate the fat content based on the optimization of technological processing modes. A promising method of preparing grain for animal feeding is its preliminary germination. Sprouted grain is a dietary food product, as it increases the content of proteins, essential amino acids, and macro- and microelements in comparison with non-sprouted grain.

Methods
The purpose of this study was to regulate the fat content based on the optimization of technological processing modes. Regression equations describing the dependences of the quality indicators of the triticale grain germination modes on the factors tw, τ, w and tg affecting them were investigated and obtained. During the study of triticale grains, it was found that the most significant parameter affecting the germination process is the fat content. The optimization of the germination modes of triticale Leather grain was carried out by the method of nonlinear programming.

Results
During the study, it was found that the maximum fat content during germination of triticale grain was observed with the following technological parameters of germination: grain temperature = 30°C; germination time = 24 h; grain moisture = 13%; and grain temperature = 26°C. When controlling the fat content in triticale based on the optimization of technological modes, the target function was 2.83%.

Conclusion
The presented results and conclusion will allow to regulate the fat content in triticale grain during germination.
Artificial Intelligence–Based Co-Facilitator (AICF) for Detecting and Monitoring Group Cohesion Outcomes in Web-Based Cancer Support Groups: Single-Arm Trial Study
Authors: Leung Yvonne W , Wouterloot Elise , Adikari Achini , Hong Jinny , Asokan Veenaajaa , Duan Lauren , Lam Claire , Kim Carlina , Chan Kai P , De Silva Daswin , Trachtenberg Lianne , Rennie Heather , Wong Jiahui , Esplen Mary Jane 
Published: May 2024

Background
Commonly offered as supportive care, therapist-led online support groups (OSGs) are a cost-effective way to provide support to individuals affected by cancer. One important indicator of a successful OSG session is group cohesion; however, monitoring group cohesion can be challenging due to the lack of nonverbal cues and in-person interactions in text-based OSGs. The Artificial Intelligence–based Co-Facilitator (AICF) was designed to contextually identify therapeutic outcomes from conversations and produce real-time analytics.

Objective
The aim of this study was to develop a method to train and evaluate AICF’s capacity to monitor group cohesion.

Methods
AICF used a text classification approach to extract the mentions of group cohesion within conversations. A sample of data was annotated by human scorers, which was used as the training data to build the classification model. The annotations were further supported by finding contextually similar group cohesion expressions using word embedding models as well. AICF performance was also compared against the natural language processing software Linguistic Inquiry Word Count (LIWC).

Results
AICF was trained on 80,000 messages obtained from Cancer Chat Canada. We tested AICF on 34,048 messages. Human experts scored 6797 (20%) of the messages to evaluate the ability of AICF to classify group cohesion. Results showed that machine learning algorithms combined with human input could detect group cohesion, a clinically meaningful indicator of effective OSGs. After retraining with human input, AICF reached an F1-score of 0.82. AICF performed slightly better at identifying group cohesion compared to LIWC.

Conclusions
AICF has the potential to assist therapists by detecting discord in the group amenable to real-time intervention. Overall, AICF presents a unique opportunity to strengthen patient-centered care in web-based settings by attending to individual needs.

International Registered Report Identifier (IRRID)
RR2-10.2196/21453
Just-in-Time Adaptive Intervention for Stabilizing Sleep Hours of Japanese Workers: Microrandomized Trial
Authors: Takeuchi Hiroki , Ishizawa Tetsuro , Kishi Akifumi , Nakamura Toru , Yoshiuchi Kazuhiro , Yamamoto Yoshiharu 
Published: May 2024

Background
Sleep disturbance is a major contributor to future health and occupational issues. Mobile health can provide interventions that address adverse health behaviors for individuals in a vulnerable health state in real-world settings (just-in-time adaptive intervention).

Objective
This study aims to identify a subpopulation with vulnerable sleep state in daily life (study 1) and, immediately afterward, to test whether providing mobile health intervention improved habitual sleep behaviors and psychological wellness in real-world settings by conducting a microrandomized trial (study 2).

Methods
Japanese workers (n=182) were instructed to collect data on their habitual sleep behaviors and momentary symptoms (including depressive mood, anxiety, and subjective sleep quality) using digital devices in a real-world setting. In study 1, we calculated intraindividual mean and variability of sleep hours, midpoint of sleep, and sleep efficiency to characterize their habitual sleep behaviors. In study 2, we designed and conducted a sleep just-in-time adaptive intervention, which delivered objective push-type sleep feedback messages to improve their sleep hours for a subset of participants in study 1 (n=81). The feedback messages were generated based on their sleep data measured on previous nights and were randomly sent to participants with a 50% chance for each day (microrandomization).

Results
In study 1, we applied hierarchical clustering to dichotomize the population into 2 clusters (group A and group B) and found that group B was characterized by unstable habitual sleep behaviors (large intraindividual variabilities). In addition, linear mixed-effect models showed that the interindividual variability of sleep hours was significantly associated with depressive mood (β=3.83; P=.004), anxiety (β=5.70; P=.03), and subjective sleep quality (β=−3.37; P=.03). In study 2, we found that providing sleep feedback prolonged subsequent sleep hours (increasing up to 40 min; P=.01), and this effect lasted for up to 7 days. Overall, the stability of sleep hours in study 2 was significantly improved among participants in group B compared with the participants in study 1 (P=.001).

Conclusions
This is the first study to demonstrate that providing sleep feedback can benefit the modification of habitual sleep behaviors in a microrandomized trial. The findings of this study encourage the use of digitalized health intervention that uses real-time health monitoring and personalized feedback.
Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study
Authors: Akiya Ippei , Ishihara Takuma , Yamamoto Keiichi 
Published: May 2024

Abstract

Background
Synthetic patient data (SPD) generation for survival analysis in oncology trials holds significant potential for accelerating clinical development. Various machine learning methods, including classification and regression trees (CART), random forest (RF), Bayesian network (BN), and conditional tabular generative adversarial network (CTGAN), have been used for this purpose, but their performance in reflecting actual patient survival data remains under investigation.

Objective
The aim of this study was to determine the most suitable SPD generation method for oncology trials, specifically focusing on both progression-free survival (PFS) and overall survival (OS), which are the primary evaluation end points in oncology trials. To achieve this goal, we conducted a comparative simulation of 4 generation methods, including CART, RF, BN, and the CTGAN, and the performance of each method was evaluated.

Methods
Using multiple clinical trial data sets, 1000 data sets were generated by using each method for each clinical trial data set and evaluated as follows: (1) median survival time (MST) of PFS and OS; (2) hazard ratio distance (HRD), which indicates the similarity between the actual survival function and a synthetic survival function; and (3) visual analysis of Kaplan-Meier (KM) plots. Each method’s ability to mimic the statistical properties of real patient data was evaluated from these multiple angles.

Results
In most simulation cases, CART demonstrated the high percentages of MSTs for synthetic data falling within the 95% CI range of the MST of the actual data. These percentages ranged from 88.8% to 98.0% for PFS and from 60.8% to 96.1% for OS. In the evaluation of HRD, CART revealed that HRD values were concentrated at approximately 0.9. Conversely, for the other methods, no consistent trend was observed for either PFS or OS. CART demonstrated better similarity than RF, in that CART caused overfitting and RF (a kind of ensemble learning approach) prevented it. In SPD generation, the statistical properties close to the actual data should be the focus, not a well-generalized prediction model. Both the BN and CTGAN methods cannot accurately reflect the statistical properties of the actual data because small data sets are not suitable.

Conclusions
As a method for generating SPD for survival data from small data sets, such as clinical trial data, CART demonstrated to be the most effective method compared to RF, BN, and CTGAN. Additionally, it is possible to improve CART-based generation methods by incorporating feature engineering and other methods in future work.
Effect of Flavored on! Nicotine Pouch Products on Smoking Behaviors: Protocol for a Sequential, Multiple Assignment, Randomized Controlled Trial
Authors: Cheng Hui G , Rose Jed E , Karelitz Joshua L , Botts David R , Botts Tanaia L , Willette Perry N , Cohen Gal 
Published: May 2024

Background
Cigarette smoking is a leading cause of morbidity and mortality. For adults who smoke cigarettes and cannot or will not quit smoking, smoke-free products, such as nicotine pouches, have been recognized as a potential alternative to smoking combusted cigarettes to reduce harm due to cigarette smoking. The role of flavors in these smoke-free products in tobacco harm reduction has not been fully understood.

Objective
This study evaluates the effect of flavors in on! nicotine pouch products (research products) in the reduction of cigarette smoking among adults who smoke cigarettes in their natural environment.

Methods
This study uses a sequential, multiple assignment, randomized trial design. Approximately 400 eligible adults who smoke cigarettes will be enrolled and randomized to have access to either the Original (unflavored) on! nicotine pouch product only or a complete flavor profile (ie, Berry, Cinnamon, Citrus, Coffee, Mint, Original, and Wintergreen) of on! nicotine pouch products. After 3 weeks, participants in the Original-only arm will be randomized again, with half remaining in the Original-only arm and half having access to the complete flavor profile for another 3 weeks. Primary outcomes are expired-air carbon monoxide (CO) levels. Secondary outcomes are self-reported cigarette consumption and CO-verified cigarette abstinence.

Results
Recruitment and data collection started in September 2023 and is projected to last until March 2025. We anticipate completing the data analysis in 2025. As of May 2024, we have enrolled 314 participants.

Conclusions
This study will provide empirical evidence about the effect that flavor availability in smoke-free products may have in reducing cigarette smoking.

Trial Registration
ClinicalTrials.gov NCT06072547; https://clinicaltrials.gov/study/NCT06072547

International Registered Report Identifier (IRRID)
DERR1-10.2196/56565
ANALYSIS AND IDENTIFICATION OF DAMAGE TO AMC 36-800/MA AN SHAN LATHES USING FAILURE MODE AND EFFECT ANALYSIS AND FAULT TREE ANALYSIS METHODS
Authors: Fuad Achmad Nur , Hidayat Hidayat , Rizqi Akhmad Wasiur 
Published: May 2024

Maintenance emerges as a crucial intervention to ensure the sustained reliability of machinery. The AMC 36-800/MA AN SHAN lathe, a piece of equipment subject to extensive operational demands, frequently encounters breakdowns, thereby obstructing the seamless execution of maintenance activities for facilities. This investigation seeks to pinpoint the components responsible for the failures and malfunctions afflicting the lathe above. Employing the methodologies of Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA), this study successfully identifies the components at the epicentre of the machine's vulnerabilities. The analysis culminates in delineating critical components by calculating Risk Priority Numbers (RPN), unveiling a pivotal RPN value of 309.57. Moreover, it isolates two components whose failure modes surpass the critical RPN threshold: the Drive Motor and the Fixed Head. The genesis of these failures can be attributed to the escalating operational intensity, elevated engine temperatures, and a maintenance regimen that is both sporadically scheduled and suboptimal. Keywords: Lathe AMC 36-800/Ma AN Shan, Failure mode, FMEA, FTA, RPN
Enhancing Efficiency in Industrial Metal Roof Replacement: Utilizing Goal Programming for Cost Optimization
Authors: Sutanto Wilson , Prajitna Stefanus Hanifa , Harito Christian 
Published: May 2024

This study explores the use of Goal Programming (GP) to optimise project management decisions in the construction industry, focusing on a case study of a roof replacement project. The construction industry is crucial to a country's development, contributing significantly to economic growth and employment rates. However, construction projects are often complex and resource-intensive. Project management is essential in ensuring the successful completion of construction projects. The study uses GP to address the time-cost trade-off in project management, aiming to minimise project costs while meeting project deadlines and quality requirements. The GP model considers various constraints, such as the availability of workers and equipment, project duration, and budget limitations. The study presents two optimisation options: a time-focused option and a cost-focused ed option. The time-focused option prioritises timely project completion, while the cost-focused option aims to minimise project costs. In the case study, the time-focused option is the most suitable choice. This approach allows the project to be completed in time as the alternative option delay delays the project far too unacceptable. Overall, the study demonstrates the effectiveness of GP in optimising project management decisions in the construction industry. By carefully evaluating project constraints and objectives, GP can help construction companies achieve the best possible outcomes in terms of cost, time, and quality. Keywords: Goal Programming, Construction Industry, Project Management, Time-Cost Trade-off, Optimization
The Shift to the 5.0 Revolution: The Challenges of Public Education in Costa Rica
Authors: Atencio Gabriel Silva , Acuña Edwin Gerardo Acuña 
Published: May 2024

Objective: The objective of this qualitative, exploratory, and descriptive study was to understand the causes and effects contributing to a specific phenomenon. Theoretical Framework: The study is contextualized within the realm of virtual education and digital transformation, emphasizing the need for a more active and dynamic approach in state support for students. Method: In-depth interviews and a bibliometric review were employed to identify key factors and comprehend the phenomenon under investigation. Result: It was found that students demand more active and dynamic state support, with measurable objectives, in line with the online teaching model and digital transformation goals. Discussion: It was concluded that the success of virtual education requires an agile, flexible, and dynamic teaching model that aligns with national objectives. Research Implications: This study suggests the need for reforms in virtual education to align with national digital transformation goals. Additionally, it underscores the importance of a more dynamic and measurable approach in state support for students. Originality/Value: The combination of qualitative methods and bibliometric review provides a unique perspective on the challenges and opportunities in virtual education, representing a significant contribution to both academia and educational policies.
Value-motivational sphere of students with different levels of self-esteem
Authors: Tolstykh Liliya Raisovna 
Published: May 2024

The relevance of the study is due to the following factors: research is needed that would allow us to understand the origins of changes in values and motives, their psychological nature. Despite the fact that in psychological science there is a large number of studies studying the values, motives, and self-esteem of students, there are not enough studies devoted to the study of differences in the value-motivational sphere of students with different levels of self-esteem. The object of the research is the value-motivational sphere and self-assessment of the personality of students. The subject of the research is the peculiarities of the value-motivational sphere of students with different levels of self-esteem. Research hypothesis: there are differences in the indicators of the value-motivational sphere of students with different levels of self-esteem. Special attention is paid to the analysis of differences in the value-motivational sphere of students with different levels of self-esteem. Research methods: theoretical: analysis and generalization of theoretical sources on the research problem; empirical, methods of mathematical data processing H – Kraskel-Wallis criterion. Research methods: "Diagnosis of self-esteem" Dembo-Rubinstein; "Value questionnaire" Sh. Schwartz; "Diagnosis of components of the motivational structure of personality" V.K. Gerbachevsky. The main conclusions of the study are: the value of "Achievement" among students with an adequate level of self-esteem is higher than in groups of students with an underestimated and overestimated level of self-esteem. Students with a low level of self-esteem are less focused on achieving results, and poorly demonstrate social competence in terms of public standards. The value of "Conformity" and "Hedonism" among students with low self-esteem is higher than among students with adequate and overestimated self-esteem, i.e. students are focused on personal pleasure and comfort. The value of "Independence" is higher for students with an adequate level of self-esteem. The motive of "Avoiding failure" of students with low self-esteem is higher than of students with adequate and overestimated self-esteem. The motive of "Evaluation of achieved results" is higher among students with an adequate level of self-esteem than among students with an underestimated and overestimated level of self-esteem. The motive of "Evaluating one's potential" is lower for students with an underestimated level of self-esteem than for students with an adequate and overestimated level of self-esteem.