bluuebunny/crossref_metadata_2025 huggingface dataset:
WASH and drinking water quality considerations in schools in reflection of the sustainable development goals – a review
Authors: Ngcongo Magareth Thulisile , Tekere M.
Published: August 2023

Poor drinking water quality has been linked to negative health outcomes across the world. Drinking water quality is an essential part of safe water, sanitation, and hygiene (WASH). Safe WASH in schools is linked with the achievement of sustainable development goals (SGDs), specifically, SDG 6. It is unclear whether water quality is always assessed as part of WASH in schools. This study focused on determining the consideration of water quality aspects during WASH assessment in schools by examining published studies. A systematic online review of the literature was conducted to identify studies that reported on the assessment of WASH facilities in schools. Titles, abstracts, and full text of retrieved articles were screened. Seventy-five studies were identified. Thirty-two studies considered drinking water quality analysis as part of WASH in schools. Chemical (66%), microbial (59%), and physical (38%) parameters were included in drinking water quality analysis, with lead (Pb), and Escherichia coli being mostly included. This study reveals that some studies did not include an evaluation of drinking water quality, though it reflects an important exposure pathway between WASH services and health outcomes. It is, therefore, recommended that routine water quality monitoring be included in school WASH to ensure learner's health is protected.
Application of machine learning models in assessing the hydrological changes under climate change in the transboundary 3S River Basin
Authors: Nguyen Quyen , Shrestha Sangam , Ghimire Suwas , Sundaram S. Mohana , Xue Wenchao , Virdis Salvatore G. P. , Maharjan Manisha
Published: August 2023

This paper aims to evaluate two machine learning (ML) algorithms, namely, convolutional neural network (CNN) and long short-term memories (LSTM) deep learning algorithms, to predict the hydrological regime of the 3S River Basin under various climate change scenarios. Climate models CMCC-CMS, HadGEM-AO2, and MIROC5 were used to predict future climate and streamflow for three future periods: near-future (2020–2050), mid-future (2050–2080), and far-future (2080–2100) under two Representative Concentration Pathways (RCPs) 4.5 and 8.5. The future projection shows an increase in mean annual temperature from 0.08 to 4.3 °C by CMCC-CMS, from 0.13 to 4.4 °C by HadGEM-AO2, and −0.07 to 4.2 °C MIROC5 models. Similarly, the annual precipitation is projected to fluctuate from 13.3 to 62.5% by CMCC-CMS, from −12.4 to 26.1% by HadGEM-AO2, and from 6.9 to 49% by the MIROC5 model. The 3S River Basin expects an increasing trend in streamflow in the Srepok and Sesan Rivers, while the Sekong is projected to have reduced streamflow. ML models predicted the increasing flood risk in the Sekong and Sesan catchments with the increase of the Q5 index in the future but a decrease in the Srepok.
Relationship Between Health Policies and Resilience: The Case of the Covid-19 Pandemic
Authors: Dinçer Samet
Published: August 2023

The Covid-19 pandemic has recently created an environment of chaos that modern societies have not experienced. The reactions of countries and societies to this new situation are different. The health policies implemented by countries in the fight against the outbreak during the Covid-19 pandemic process have an impact on the resilience of communities and constitute a determining factor in all kinds of losses. The concept of resilience has been increasingly used in the literature in recent years. Resilience, as a word meaning, is defined as the capacity of a system to continue its functions with the reactions it gives to the external effects it is exposed to. The purpose of this research is to explain the difficulties faced by societies during the Covid-19 pandemic process with selected country examples in the relationship of resilience. In this context, the countries of China, South Korea, Japan, Russia, India, the United States of America and Brazil were evaluated in terms of significant health policy differences and the losses suffered by the societies. Administrative or political skills of countries, existence of processes that ensure transparency, infrastructure and capacity of health systems and social capital determine the resilience capacity.
The Emerging Roles of circRNAs in Papillary Thyroid Carcinoma:
Molecular Mechanisms and Biomarker Potential
Authors: Ye Haihan , Sun Xiaoyang , Ding Qianyun , Yang Enyu , Zhao Shuo , Fan Xiaowei , Fang Meiyu , Ding Xianfeng
Published: August 2023

Papillary thyroid carcinoma (PTC) is a common endocrine malignant tumor. The incidence
of PTC has increased in the past decades and presents a younger trend. Accumulating evidence
indicates that circular RNAs (circRNAs), featured with non-linear, closed-loop structures,
play pivotal roles in tumorigenesis and regulate cell biological processes, such as proliferation, migration,
and invasion, by acting as microRNA (miRNA) sponges. Additionally, due to their unique
stability, circRNAs hold promising potential as diagnostic biomarkers and effective therapeutic targets
for PTC treatment. In this review, we systematically arrange the expression level of circRNAs,
related clinical characteristics, circRNA-miRNA-mRNA regulatory network, and molecular mechanisms.
Furthermore, related signaling pathways and their potential ability of diagnostic biomarkers
and therapeutic targets are discussed, which might provide a new strategy for PTC diagnosis,
monitoring, and prognosis.
Expression, Prognostic Value, and Immune Infiltration of MTHFD Family
in Bladder Cancer
Authors: Zheng Bai Shu , Wang Shun De , Zhang Jun Yong , Ge Cheng Guo
Published: August 2023

Background:

The Methylenetetrahydrofolate Dehydrogenase (MTHFD) family plays an
important role in the development and prognosis of a variety of tumors; however, the role of the
MTHFD family in bladder cancer is unclear.

Methods:

R software, cBioPortal, GeneMANIA, and online sites such as String-LinkedOmics were
used for bioinformatics analysis.

Results:

MTHFD1/1L/2 was significantly upregulated in bladder cancer tissues compared with normal
tissues, high expression of the MTHFD family was strongly associated with poorer clinical
grading and staging, and bladder cancer patients with upregulated expression of MTHFD1L/2 had
a significantly worse prognosis. Gene function and PPI network analysis revealed that the MTHFD
family and related genes play synergistic roles in the development of bladder cancer. 800 co-expressed
genes related to the MTHFD family were used for functional enrichment analysis, and the
results showed that many genes were associated with various oncogenic pathways such as cell cycle
and DNA replication. More importantly, the MTHFD family was closely associated with multiple
infiltrating immune lymphocytes, including Treg cells, and immune molecules such as TNFSF9,
CD274, and PDCD1.

Conclusion:

Our study shows that MTHFD family genes may be potential prognostic markers and
therapeutic targets for patients with bladder cancer.
The Pharmacological Treatment of Neuropathic Pain in Children
Authors: Einhorn Lisa M. , Hudon Jonathan , Ingelmo Pablo
Published: August 2023

The International Association for the Study of Pain (IASP) defines neuropathic pain as pain
caused by a lesion or disease of the somatosensory nervous system. It is characterized as a clinical
condition in which diagnostic studies reveal an underlying cause of an abnormality in the peripheral or
central nervous system. Many common causes of neuropathic pain in adults are rare in children. The
purpose of this focused narrative review is, to 1) provide an overview of neuropathic pain in children,
2) highlight unique considerations related to the diagnosis and mechanisms of neuropathic pain in
children, and 3) perform a comprehensive analysis of the pharmacological treatments available. We
emphasize that data for routine use of pharmacological agents in children with neuropathic pain are
largely inferred from adult literature with little research performed on pediatric populations, yet have
clear evidence of harms to pediatric patients. Based on these findings, we propose risk mitigation
strategies such as utilizing topical treatments whenever possible, assessing pain phenotyping to guide
drug class choice, and considering pharmaceuticals in the broader context of the multidisciplinary
treatment of pediatric pain. Furthermore, we highlight important directions for future research on pediatric
neuropathic pain treatment.
An Intelligent Maximum Power Point Tracking Strategy for a Wind Energy Conversion System using Machine Learning Algorithms
Authors: Bouzem Aicha , Bendaou Othmane , Yaakoubi Ali El
Published: August 2023

Background:

Machine Learning (ML) techniques have successfully replaced traditional control algorithms in recent years due to their ability to carry out complicated tasks with significant efficiency and accuracy.

Objective:

The main objective of the current work is to investigate and compare the performances of different ML models in modeling Maximum Power Point Tracking (MPPT) control for a wind turbine system. The main advantage of the designed MPPT based on ML is that it does not require any detailed mathematical model or prior knowledge of the system, such as turbine parameters or aerodynamic properties, unlike traditional MPPT techniques.

Methods:

The ML models included in this study were Support Vector Machines, Regression Trees, and Ensemble Trees. Their design was performed through a training process, and their performances were evaluated based on various metrics. During the training phase, the ML models were selected to understand the basic concept of the control strategy and extract essential hidden connections between the inputs and the output of the system.

Results:

The effectiveness of the control method was investigated using MATLAB/Simulink. The findings of this study revealed that ML models were effective in modeling the MPPT for the studied wind power system, which provides an interesting and sophisticated alternative to classical control methods for wind systems.

Conclusion:

The ML models designed allow for optimal operation of the system with a simple structure that is independent of system parameters and wind speed measurement and is adaptable for any kind of system.
Implementation of Nanocarriers for Brain-Specific Drug Delivery System
Authors: Sharma Aditya , Alam Md. Aftab , Kaur Awaneet
Published: August 2023

There are several safeguards in place to protect the brain from injury because of its vulnerability.
Two major barriers prevent harmful substances from entering the brain: the blood-brain barrier
(BBB) and the blood-cerebrospinal fluid barrier (BCSFB). Although there has been some success in
devising ways for transporting medicines to the brain, the great majority of the nanoparticles (NPs)
used in these procedures are destroyed in the process. An awareness of the whole scope of the delivery
process and the numerous obstacles it may offer is necessary for the sensible design of brain-targeted
pharmaceutical delivery systems. The blood-brain barrier (BBB) is the best-known physiological barrier
affecting both brain access and the efficacy of various pharmacological therapies. Accordingly,
the development of a promising therapy for the treatment of brain disorders requires drug targeting of
the brain, specifically damaged cells. Researchers are looking into nano-carrier systems, also called
surface-modified target-specific novel carrier systems, to determine if they can be used to boost the
effectiveness of brain drugs while minimizing their side effects. These strategies have the potential to
bypass BBB function, leading to increased drug levels in the brain. Numerous physiological parameters,
such as active efflux transport, the brain's protein corona, nanocarrier stability and toxicity, physicochemical
features, patient-related factors, and others, determine whether or not a novel carrier system
is functional.
Utilization of Herbal Components as Insecticidal and Repellent Effects
Authors: Rajput Shivam , Sharma Pramod , Malviya Rishabha
Published: August 2023

Humans and many other creatures depend on agriculture for survival, but it is impossible to cultivate without the use of pesticides. Different types of harmful organism or pest exists in every agricultural crop. Synthetic pesticides are widely utilised around the world as a solution to this problem, but there are drawbacks associated with their application, the most significant of which are the severe negative impacts on ecosystems and human health. Organically made pesticides should be used instead of synthetic pesticides to reduce their harmful effects. Unlike chemical pesticides, natural pesticides do not cause any harm to non-target creatures and are inexpensive. Most botanical pesticides degrade rapidly, usually in only a few days but sometimes may even take hour. One of the most promising approaches to reducing pesticide pollution and protecting crops, food, and the environment is to use botanical insecticides. Beneficial insects such as earthworms are much less likely to be killed by biopesticides. The source of herbal insecticides is herbal plants. Each plant has distinct effect since every plant have their own chemical constituent. This review explains about numerous herbs and shrubs that feature distinct insecticidal, pesticidal and repelling effect. Insecticidal activity is discovered in a broad variety of herbal plants, and this review analyses those plants in detail, defining the major active ingredient responsible for these effects.
Mathematical Model of Multispectral Data Processing for a Mobile Ecology Monitoring Platform
Authors: Spevakova S. S. , Spevakov A. G. , Chernetskaya I. V.
Published: August 2023

The purpose of research is a mathematical justification of the process of processing multispectral data in order to detect local environmental pollution zones with the possibility of classifying the pollutant.

   Methods. The fundamentals of the applied theory of stochastic systems based on equations for multidimensional characteristic functions and functionals are used as a basic mathematical apparatus. When determining a contaminant, a criterion reflecting the ability of objects obeying Lambert's law is used. To solve the problem of object classification, approaches using binary logistic regression are applied. Statistical methods of analysis were used to evaluate the results of the study.

   Results. The obtained partial mathematical models allow us to take into account many factors affecting mobile environmental monitoring platforms operating in automatic mode. Substantiate the possibility of remote analysis of local environmental pollution zones, with the possibility of determining pollutants such as hydrocarbons, phosphate ions, etc., as well as searching for unauthorized locations of construction and household garbage. They increase the accuracy characteristics by 1,3 times when determining the parameters of selected objects due to the processing of data obtained in various spectral ranges. They contribute to reducing the computational complexity of the classification algorithm by 1,1 times, taking into account the volume of input data in a limited spectral range and reducing the resolution of the reference object, while not affecting the accuracy of classification.

   Conclusion. A mathematical model has been developed for processing data and images obtained in several spectral ranges during the operation of a multispectral device for an autonomous mobile environmental monitoring platform, which makes it possible to identify objects in the field of view of the device from a mobile platform, to obtain a detailed image of working scene objects with spatial reference relative to the coordinate system used, a distinctive feature of which is to increase the accuracy of calculating the coordinates of local zones pollution, and increasing the reliability of the classification of objects based on the characteristics of diffusive reflectivity in various spectral ranges.
Prediction and Early Diagnosis of Bronchial Asthma in Workers Specializing in Argon Welding Based on Fuzzy Mathematical Models
Authors: Grigorov I. Y. , Starodubtseva L. V. , Seregin S. P. , Shulga L. V.
Published: August 2023

The purpose of research is to develop fuzzy mathematical models for predicting and early diagnosis of bronchial asthma developing under the influence of toxic substances released during argon welding providing an acceptable quality of decision-making for practical medicine

   Methods. The paper uses the method of synthesis of fuzzy mathematical models of forecasting and early diagnosis of occupational diseases provoked by the action of industrial pesticides developed in the South-Eastern Federal University on the basis of the methodology of synthesis of hybrid fuzzy decision rules allowing to take into account the multiplicative nature of the links between the risk of occurrence and development of occupational diseases with the concentration and time of exposure to harmful chemicals.

   Results. Using the chosen method, fuzzy hybrid models of forecasting and early diagnosis of industrial bronchial asthma in welding workers were obtained in which, in addition to the effects of ozone, dust and fibrogenic risk factors on the human body, unfavorable environmental and ergonomic factors combined with individual health characteristics are taken into account. In the course of modeling and expert evaluation, it was shown that the obtained mathematical model provides confidence in the correct prognosis of the occurrence of industrial bronchial asthma in welding workers at least 0.85, and early diagnosis at least 0.9.

   Conclusion. Hybrid fuzzy models of forecasting and early diagnosis of industrial bronchial asthma in welding workers caused by the presence of ozone and fibrogenic dust in combination with individual, environmental and ergonomic risk factors were obtained, the quality of which was tested on representative control samples. During the control check, it was shown that the prognostic model provides diagnostic specificity and sensitivity at the level of 0.87, and the early diagnosis model - at the level of 0.92, which is a good result for the class of tasks under consideration.
Assessment of the Effectiveness of Monitoring the Technical Condition of a Complex Technical Object, Taking Into Account Expert Assessments
Authors: Nesterovich S. A. , Brezhneva A. N.
Published: August 2023

The purpose of the research is to develop a method for evaluating the effectiveness of monitoring the technical condition of a complex technical object, taking into account expert assessments.

   Methods. Evaluation of the effectiveness of the application of a complex technical object is carried out with the help of appropriate performance indicators that characterize the degree of fulfillment of the tasks assigned to them. When choosing performance indicators, the following basic requirements should be taken into account: the indicator should have a quantitative expression and be calculated simply enough; the indicator should be selected taking into account the specifics of the task being solved and reflect the main characteristics of the phenomenon being evaluated; theindicator should be representative and ensure comparability of the evaluation results by the degree of preference, i. e. to prevent incomparable (indifferent) decisions.

   Results. A method for evaluating the effectiveness of monitoring the technical condition of a complex technical object is presented, taking into account an additional expanded information description with qualitative features (expert assessments).

   Conclusion. The effectiveness of the control directly depends on the accuracy and completeness of the control. The accuracy of existing control systems is quite high, but the completeness of control does not always take into account qualitative (expert) assessments about the object of control. Improving the efficiency of control systems should go not only at the expense of accuracy and speed, but also at the expense of completeness of control. As a criterion for evaluating the effectiveness of the control system, an assessment of the probability of a functional state of a controlled complex technical object is proposed. The calculation of the effectiveness of the control system is proposed, taking into account the additional expanded information description by qualitative signs (expert assessments) about the object of control. It is shown that it is possible to more accurately assess the operational state of the object of control if the completeness of control is higher, with an irreducible accuracy of control.
Information Support for Decision-Making According to the Assessment of Fire-Fighting Distances from the Borders of Open Areas for PBX Storage
Authors: Voloshenko A. A. , Shevtsov M. V. , Denisov A. N.
Published: August 2023

The purpose of research. Information support has been developed for decision-making on the assessment of fire-fighting distances from the boundaries of open storage areas for PBX to various objects of protection, taking into account the effects of heat flow.

   The object of the study is an assessment of the fire-fighting distance from the boundaries of open areas of motor vehicles.

   The subject of the study is information support for making a management decision on the compliance of the object of protection with fire safety requirements, aimed at limiting the consequences of the spread of fire in the form of a fire-fighting distance from the boundaries of open storage areas for PBX to buildings (structures) of I-V degrees of fire resistance of functional fire hazard classes F.1-F.5.

   The purpose of this work is to create and application of individual calculation formulas to determine the maximum permissible distances from the boundaries of open areas of vehicles to various buildings (structures) based on the use of a computer software product.

   Methods. Methods of system analysis, management theory and decision-making, and numerical experiment were used to solve the tasks.

   Results. The article proposes an assessment of the risk of harm to someone else's property and the determination of the value of the safe distance from the boundaries of open areas for storing PBX to various objects of protection by using the software product «Assessment of the safe distance from the boundaries of open areas of motor vehicles», aimed at improving the scientific and experimental and educational and material base of research, expert and educational organizations. The proposed calculation-based assessment of the compliance of the object of protection with fire safety requirements to prevent the spread of fire is aimed for practical application in the organization of activities and the exercise of powers by employees of the FPS of the Ministry of Emergency Situations of Russia, experts, as well as owners of protection objects.

   Conclusion. The proposed information support for decision-making on the assessment of fire-fighting distances from the boundaries of open storage areas for PBX will allow you to establish the risk of harm to someone else's property.
Insights Focused on Hybrid Graphene Modifications within the Nanoscale for Opto-Electronics Perspectives
Authors: Bracamonte Guillermo
Published: August 2023

This brief letter presents this Special Issue nominated as “Hybrid Graphene-based Materials: Synthesis, Characterization, Properties, and Applications”. This intends to show and discuss the main properties of Graphene and its derivatives; and how it could be synthesized, modified and tuned for Optics, Electro-Optics, Electronics, and Quantum characteristics. In this context, the synthesis and chemical modifications were highlighted for the design of Hybrid composites, platforms. In this context, it was afforded to varied developments within Multidisciplinary fields for high-impact Research and applications. In this manner, Graphene joined to other organic and inorganic materials showed different properties compared to free and non-modified Graphene. This fact, permitted to tune of electronic properties through materials that were transferred to applications. For example, the high electronic density could generate pseudo-electromagnetic fields and other phenomena such as luminescence, electronic conductions, and specific Quantum states that could be joined to optical active materials. Thus, it was afforded to the discussion and introduction in this other Research field as well. In this manner, it was intended to afford an overview of the high-impact Research and potential perspectives of Hybrid Graphene materials.
Predicting the Risk of Total Hip Replacement by Using A Deep Learning Algorithm on Plain Pelvic Radiographs: Diagnostic Study
Authors: Chen Chih-Chi , Wu Cheng-Ta , Chen Carl P C , Chung Chia-Ying , Chen Shann-Ching , Lee Mel S , Cheng Chi-Tung , Liao Chien-Hung
Published: August 2023

Background

Total hip replacement (THR) is considered the gold standard of treatment for refractory degenerative hip disorders. Identifying patients who should receive THR in the short term is important. Some conservative treatments, such as intra-articular injection administered a few months before THR, may result in higher odds of arthroplasty infection. Delayed THR after functional deterioration may result in poorer outcomes and longer waiting times for those who have been flagged as needing THR. Deep learning (DL) in medical imaging applications has recently obtained significant breakthroughs. However, the use of DL in practical wayfinding, such as short-term THR prediction, is still lacking.

Objective

In this study, we will propose a DL-based assistant system for patients with pelvic radiographs to identify the need for THR within 3 months.

Methods

We developed a convolutional neural network–based DL algorithm to analyze pelvic radiographs, predict the hip region of interest (ROI), and determine whether or not THR is required. The data set was collected from August 2008 to December 2017. The images included 3013 surgical hip ROIs that had undergone THR and 1630 nonsurgical hip ROIs. The images were split, using split-sample validation, into training (n=3903, 80%), validation (n=476, 10%), and testing (n=475, 10%) sets to evaluate the algorithm performance.

Results

The algorithm, called SurgHipNet, yielded an area under the receiver operating characteristic curve of 0.994 (95% CI 0.990-0.998). The accuracy, sensitivity, specificity, and F1-score of the model were 0.977, 0.920, 0932, and 0.944, respectively.

Conclusions

The proposed approach has demonstrated that SurgHipNet shows the ability and potential to provide efficient support in clinical decision-making; it can assist physicians in promptly determining the optimal timing for THR.
Retention in an mHealth App Aiming to Promote the Use of HIV Pre-Exposure Prophylaxis Among Female Sex Workers in Dar es Salaam, Tanzania: Prospective Cohort Study
Authors: Mbotwa Christopher H , Kazaura Method R , Moen Kåre , Leshabari Melkizedeck T , Metta Emmy , Mmbaga Elia J
Published: August 2023

Background

Increasing access to smartphones in sub-Saharan Africa offers an opportunity to leverage mobile health (mHealth) technology to improve access to health care in underserved populations. In the domain of HIV prevention, mHealth interventions can potentially contribute to solving the challenges of suboptimal adherence to pre-exposure prophylaxis (PrEP) and low retention in PrEP services among populations most vulnerable to HIV acquisition. However, there is a gap in the knowledge about the use of such interventions in sub-Saharan Africa.

Objective

This study aims to evaluate the extent and predictors of retention in an mHealth app (Jichunge) that aims to promote adherence to PrEP and retention in PrEP care among female sex workers in Dar es Salaam, Tanzania.

Methods

A prospective cohort of female sex workers residing in Dar es Salaam were recruited, using respondent-driven sampling. All participants were provided with the Jichunge app as they started PrEP. A questionnaire was used to collect data on sociodemographics and other structural factors, while app use data for the 60-day period following the first 150 days of being in the intervention arm were extracted from the app’s back end. A multivariable log-binomial model was used to determine predictors of 6-month retention in the Jichunge app.

Results

A total of 470 female sex workers were recruited. Nearly three-quarters of participants (206/284, 72.5%) who came to the 6-month follow-up interview no longer had the Jichunge app on their phones. The majority of these participants (193/206, 93.7%) no longer had access to the app because of issues related to their phones. Data extracted from the back end of the app showed that the use of the app declined over time, and only 13.4% (63/470) of the participants were retained (continued to use the app) after 6 months of intervention. At 6 months, women aged ≥35 years were >2 times more likely to use the app than women aged 18 to 24 years (adjusted risk ratio [aRR] 2.2, 95% CI 1.2-4.1; P=.01). Furthermore, retention in the app was higher among participants who demonstrated high PrEP awareness at baseline (aRR 1.8, 95% CI 1.1-3; P=.01) and among those who had experienced financial difficulties due to health care spending (aRR 1.9, 95% CI 1.2-3.2; P=.01).

Conclusions

Most female sex workers (206/284, 72.5%) who were enrolled in PrEP care in Tanzania no longer used the Jichunge app after 6 months. Retention in the app at 6 months was predicted by older age, high PrEP awareness, and financial difficulties due to health care spending. Strategies for the long-term retention of participants in mHealth apps, such as systems for reinstallations of apps, should be considered during the design phase.
The Shifting of Regional Regime: Study Case of Renegotiation NAFTA to USMCA
Authors: Ardhana Putri Febrianty , Daniah Rahmah
Published: August 2023

This study was designed using descriptive writing techniques using secondary data with library research techniques and qualitative analysis. The results of this study indicate that the factors behind the renegotiation of NAFTA to the USMCA come from internal and external factors. From internal factors, there are considerations from each NAFTA member country in the form of profit and loss considerations from an economic perspective, such as gains from Foreign Direct Investment (FDI) and losses in the form of trade deficits. Meanwhile, from external factors, there were considerations related to the existence of economic threats from third parties, several NAFTA rules that are considered detrimental and irrelevant, as well as considerations of the potential for modernizing NAFTA rules from a digital trade perspective. In addition, the renegotiation of NAFTA to the USMCA also brings those international agreements to a deeper stage of economic integration, where the USMCA is between the Free Trade Agreement (FTA) and Customs Union stages because the USMCA has deeper rules than the FTA stage. However, on the other hand, it still does not fully comply with the rules at the stage of the Customs Union.
Research Paper Design Analysis & Development of Fixture for Engine Block
Authors: Zade Nagesh P. , Bankar Vaibhav
Published: August 2023

Abstract: The Design, Analysis & Development of the Fixture described in this project is to convert Three fixtures for three different components into One fixture for three components, that is Three in one fixture. The three-in-one fixture will be a milling fixture used for the secondary operation of three different casted engine blocks. It will reduce the cycle time, and cost of manufacturing, also the cost of fixtures will be reduced as compared to the manufacturing cost of three fixtures.
Bienestar animal en la cadena cárnica bovina colombiana
Authors: León Betancur Andres Felipe
Published: August 2023

Contextualización: Según la Organización Mundial de Sanidad Ani[1]mal (OIE), el bienestar animal es una ciencia multifactorial, que comprende aspectos científicos, culturales, éticos, económicos y políticos. Desde 1995, la OIE apoya a los países miembros en la adopción de directrices para la aplicación del BA, es así que los países latinoamericanos han ido desarrollando sus propias leyes y lineamientos con el fin de integrar los conceptos tanto de estudios internaciones como de aquellos realizados en condiciones propias de cada territorio. Vacío de investigación: Se hace necesario conocer el impacto del bienestar animal en la cadena cárnica bovina en Colombia, en indagar lo que la investigación en el área ha logrado en nuestro país. Propósito del estudio: El siguiente documento tiene como objetivo hacer una contextualización sobre los eslabones de la cadena cárnica bovina en Colombia, donde se realizará una discusión sobre los aspectos más importantes en cada una de las etapas que los comprende, de esta manera se busca visualizar lo que ha logrado la investigación en el campo del bienestar animal, con el fin de mostrar la importancia de la implementación de este concepto. Metodología: Exploración de fuentes secundarias de información, con referencia a actualizaciones relevantes en el área de bienestar animal y su impacto en la cadena cárnica bovina en Colombia. Resultados y conclusiones: la investigación científica en el área, ha venido dando información acerca de las problemáticas que actualmente se presentan, junto a soluciones claras de las mismas, con el fin de lograr una producción óptima. Por lo que es fundamental seguir indagando sobre el impacto de aplicaciones de buenas prácticas de bienestar animal en la cadena logística.
Exploring consumer attitudes and purchase intentions: Unraveling key influencers in China’s green agricultural products market
Authors: Fahlevi Mochammad , Hasan Fakhrul , Islam Mohammad Raijul
Published: August 2023

This study explores the factors influencing consumer attitudes and purchasing intentions towards green agricultural products in China, as consumers have shown increased awareness due to heightened health and wellness consciousness. A random sampling method generated a sample for a questionnaire survey, yielding a response rate of 88.7 percent. Both descriptive and inferential statistics were used to analyze the data, including Pearson Correlation and regression analysis. The research found that Chinese consumers exhibit a weakly positive attitude and neutral purchasing intention for green agricultural products. Furthermore, it identified a strong correlation and significant relationships between factors such as awareness, consumption values, social influence, and health consciousness and both attitude and purchase intention. The study also confirmed that attitude positively and significantly impacts purchase intention. This research enriches the understanding of consumer behavior in the green agricultural product market and aids marketers in making informed decisions.
D-Limonene decreases depression-like behavior and improves memory via an anti-neuroinflammatory mechanism under chronic restraint stress in rats
Authors: ALKANAT MEHMET , Alkanat Hafize
Published: August 2023

D-Limonene is a monoterpene compound with anticancer, gastroprotective,
anti-inflammatory, antioxidant, anti-nociceptive, and anxiolytic
features. In this study, we aimed to investigate the effects of
D-limonene under chronic restraint stress in rats. Forty rats were
included in the study and randomly divided into 5 groups: i) control,
ii) limonene, iii) restraint stress, iv) restraint stress+limonene, and
v) restraint stress+fluoxetine, respectively. D-limonene at a dose of 10
mg/kg was administered orally by gavage along with 21 days. At the end
of the saline or drug administration, sucrose preference tests, open
field tests, novel object recognition tests, and forced swimming test
were performed. BDNF, IL-1β, IL-6, and caspase-1 levels were measured
from hippocampus tissue. In the sucrose preference test, the consumption
rate decreased in the stress group, whereas it increased in the
stress+limonene group. In the open field test, traveled distance, mean
speed decreased in the restraint stress group, but these values
increased in the stress+limonene administered group. In addition, the
administration of D-limonene to the restraint stress group were
abolished the increased defensive behavior in the stress group in the
open field test. In the novel object recognition test, the
discrimination index percentage of the restraint stress+limonene group
was elevated compared to the stress group. While BDNF levels decreased
in the restraint stress group, IL-1β and caspase-1 levels increased
compared to the stress +limonene administered group. D-limonene reduces
the detrimental effect of stress on learning and memory tests. Also,
D-limonene reduces anhedonic and defensive behavior, these effects
appear to have antidepressant-like properties.
Research on an improved time scale algorithm of hydrogen masers and cesium atomic clocks
Authors: jiang meng , zhang yu
Published: August 2023

In this letter, the author presents a time scale fusion method based on
improved exponential filtering and V-C filtering. Firstly, the minimum
error theory is used to dynamically estimate the frequency drift
parameters of the hydrogen maser, and the exponential filtering method
is used to generate the full hydrogen clock time scale. Secondly, an
improved weighted average algorithm is used to generate the cesium
species time scale. Finally, based on the principle of least squares,
the V-C filter is designed to improve the short-term performance of the
time scale of cesium clock ensemble by utilizing the rate information of
the hydrogen masers, and the comprehensive time scale of hydrogen masers
and cesium atomic clocks is obtained. The experimental results show that
the time scale has a stability of 1.60e-15 for one hour and 3e-15 for
one day, which are superior to the performance of all hydrogen masers or
cesium atomic clocks on the same average time scale.
Unsupervised probabilistic machine learning applied to seismicity declustering: a new approach to represent earthquake catalogues with fewer assumptions
Authors: Septier Antoine , Renouard Alexandra , Déverchère Jacques , Perrot Julie
Published: August 2023

Many applications in seismology require to isolate earthquake clusters
from a background activity. Relative declustering methods essentially
find a 2D representation of an earthquake catalogue that distinguishes
between two classes of events: crisis and non-crisis events. However,
the number of statistical and/or physical parameters to be used is often
limited due to the difficulty of concatenating the information onto a
physically meaningful 2D grid. In this study, we propose to alleviate
the declustering task by using the ability of unsupervised artificial
intelligence to model complex spatio-temporal relationships directly
from data. Through a data-driven approach, we define an easily
transferable declustering model that provides declustering results with
fewer assumptions and no prior selection of thresholds. We first obtain
this model by training a self-organising neural network (SOM) that
learns to cluster data points according to their feature similarity on a
2D map. We then assign each SOM cluster a label (crisis or non-crisis
class) using an agglomerative clustering procedure. We quantify the
classification uncertainty by developing a probabilistic function based
on the projection learned by SOM. Our method is applied to a synthetic
dataset and to real catalogues from the Gulf of Corinth, Central Italy
and Taiwan. We discuss the validity of the method by estimating its
classification accuracy. For real data, we qualitatively compare our
results to previous declustering attempts. We show that our approach is
easy to handle, provides a fairly new representation of earthquake
catalogues and has the potential to reduce classification ambiguities
between nearby events.
An Alternative Explanation for the Great Oxygenation Event (GOE): Weathering of Rocks Containing Minerals with Peroxy Bonds
Authors: Liu Victor , Stolc Viktor , Freund Friedemann
Published: August 2023

During the Great Oxygenation Event (GOE) 2.4 - 2.35 Gyrs ago, Earth
experienced a notable shift in its oxidation state. This has been widely
attributed to cyanobacteria having “invented” oxygenic
photosynthesis.  We present a very different view based on the fact that
oxygen is released from rocks during weathering. If so, the GOE must
have been caused by an influx of abiogenic O into
Earth’s surface environment. Minerals forming Earth’s crust contain
impurity hydroxyls such as OSiOH. Pairs of those are
known to undergo a common redox conversion, ubiquitously forming peroxy
defects plus H:

OSiOH-HOSiO
⇌
OSi/\SiO
+ H

Being diffusively mobile, most H2 will be lost, leaving behind bound O
as peroxy. The peroxy defects release O during
weathering:

OSi/\SiO
+ H2O → OSiOH-HOSiO +
12 O

We suggest that this abiogenically generated O was
responsible for the progressive oxidation of the early Earth and that
this abiotic process drove the Great Oxygenation Event (GOE).
Global predicted bathymetry using neural networks
Authors: Harper Hugh , Sandwell David T.
Published: August 2023

Sparse distribution of depth soundings in the ocean make it necessary to
infer depth in the gaps using alternate information such as
satellite-derived gravity and a mapping from gravity to depth. We design
and train a neural network on a collection of 50 million depth soundings
to predict bathymetry globally using gravity anomalies. We find the best
result is achieved by pre-filtering depth and gravity in accordance with
isostatic admittance theory described in previous predicted depth
studies. When training the model, if the training and testing split is a
random partition at the same resolution as the data, the training and
testing sets will not be independent, and model misfit results will be
too optimistic. We solve this problem by partitioning the training and
testing set with geographic bins. Our final predicted depth model
improves on old predicted depth model rms by 16%, from 165 m to 138 m.
Among constrained grid cells, 80% of the predicted values are within
128 m of the true value. Improvements to this model will continue with
additional depth measurements, but higher resolution predictions, being
limited by upward continuation of gravity, shouldn’t be attempted with
this method.
On c-sober spaces and ω*-well-filtered spaces
Authors: Yang Jinbo , Luo Yun , Ye Zixuan
Published: August 2023

Based on countably irreducible version of Topological Rudin?s Lemma, we give
some characterizations of c-sober spaces and ?*-well-filtered spaces. In
particular, we prove that a topological space is c-sober iff its Smyth power
space is c-sober and a c-sober space is an ?*-well-filtered space. We also
show that a locally compact ?+-well-filtered P-space is c-sober and a T0
space X is c-sober iff the one-point compactification of X is c-sober.
Activity concentrations of 238U, 232Th, and 40K radionuclides in some south African medicinal herbs and their effective ingestion doses
Authors: Adeleye Bamise , Chetty Naven
Published: August 2023

Measurements of 238U, 232Th, and 40K activity concentrations in some commonly
used medicinal plant parts have been performed for radiation hazard
assessment and as baseline data for health risk monitoring in South Africa
and other countries. The mean activity of 238U, 232Th, and 40K was found to
be 43.3 Bqkg-1, 33.7 Bqkg-1, and 180 Bqkg-1 in Sclerocarya birrea; 85.0
Bqkg-1, 75.3 Bqkg-1, and 316.7 Bqkg-1 in Cymbopogon citratus; 47.3 Bqkg-1,
37.0 Bqkg-1, and 773.3 Bqkg-1 in Neorautanenia ficifolia; 25.7 Bqkg-1,
30.0 Bqkg-1, and 510 Bqkg-1 in Kigelia africana, respectively. The estimated
annual effective dose due to ingestion ranged from 0.013 mSv (Kigelia
africana) to 0.032 mSv (Cymbopogon citratus), well within recommended limits
for the members of the public. Although the values revealed no hazards from
a radiological point of view, it represents a valuable database for
regulatory functions.
Website E-Learning Menggunakan Web Responsive PHP dan Database MYSQL
Authors: Sukardi Sukardi , Putra Teguh Ikhsani
Published: August 2023

Penelitian ini dilatar belakangi oleh permasalahan keterbatasan sumber belajar yang ada sehingga menyebabkan banyak aspek dalam bidang pendidikan tidak berjalan sesuai dengan yang diharapkan. Tujuan penelitian ini adala Penelitian dan pengembangan ini bertujuan untuk mengetahui Validitas, Praktikalitas dan Efektifitas Website E-Learning menggunakan Web Responsive PHP dan DataBase MYSQL. Penelitian ini menggunakan metode penelitian dan pengembangan (R&D). Metode penelitian ini menggunakan analisis Model pengembangan 4-D tahap utama yaitu Define (pendefinisian), Design (perancangan), Develop (pengembanagan), dan Disseminate (Penyebaran) langkah utama dalam penelitian tidak hanya merunut versi asli tetapi disesuaikan dengan karakteristik subjek dan tempat asal examinee. Uji coba dilakukan pada 6 orang guru dan 30 orang siswa. Hasil uji validitas oleh para ahli Secara keseluruhan penilaian uji validator terhadap Media Pembelajaran Website E-Learning 86,5%, sehingga tingkat validitas dapat di interpretasikan sangat valid digunakan. Hasil penilaian uji praktikalitas secara keseluruhan penilaian praktikalitas terhadap media pembelajaran Website E-Learning sebesar 88,07%, sehingga tingkat praktikalitasnya dapat di interpretasikan sangat praktis digunakan. Hasil penilaian uji efektivitas Secara keseluruhan penilaian efektivitas media pembelajaran Website E-Learning sebesar 91,7%, sehingga tingkat efektivitasnya dapat di interpretasikan efektif digunakan. Berdasarkan penilaian beserta masukan ahli serta hasil dari uji coba lapangan media pembelajaran Website E-Learning sudah teruji kelayakan, keunggulan, dan dapat digunakan pada proses pembelajaran.
Media Audio Visual Berbasis Kontekstual pada Muatan IPA Meningkatkan Hasil Belajar Siswa
Authors: Sukmadewi Luh Putu Maylin , Suniasih Ni Wayan
Published: August 2023

Keterbatasan penggunaan media pembelajaran yang variatif dan berbasis teknologi pada proses pembelajaran khususnya muatan pembelajaran IPA menjadi salah satu alasan penelitian pengembangan ini dilakukan. Penelitian ini bertujuan untuk mengembangkan media pembelajaran audio visual berbasis kontekstual muatan IPA kelas VI SD. Jenis penelitian ini merupakan penelitian pengembangan dengan menggunakan model ADDIE (Analyze, Design, Development, Implementation, Evaluation). Subjek pada penelitian ini yaitu para ahli dan siswa kelas VI yang terdiri dari 1 orang ahli materi pembelajaran, 1 orang ahli desain pembelajaran, 1 orang ahli media pembelajaran, 3 orang siswa uji coba perorangan, dan 9 orang siswa uji coba kelompok kecil. Metode pengumpulan data yang digunakan yaitu wawancara, observasi, dan angket. Teknik analisis data menggunakan analisis deskriptif kuantitatif dan deskriptif kualitatif. Hasil dari penelitian ini yaitu media pembelajaran audio visual berbasis kontekstual dinyatakan layak berdasarkan hasil penilaian ahli materi pembelajaran sebesar 91,66% dengan kualifikasi sangat baik, hasil penilaian ahli desain pembelajaran sebesar 93,75% dengan kualifikasi sangat baik, hasil penilaian ahli media pembelajaran sebesar 93,33% dengan kualifikasi sangat baik, hasil penilaian siswa melalui uji coba perorangan sebesar 96,52%, dan hasil penilaian siswa melalui uji coba kelompok kecil sebesar 97,90% dengan kualifikasi sangat baik. Berdasarkan hasil penelitian dapat disimpulkan bahwa media pembelajaran audio visual berbasis kontekstual pada muatan IPA kelas VI sekolah dasar layak digunakan pada proses pembelajaran.