bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbiological Risks of Cheese Color Defects
Authors: Sviridenko Galina , Zakharova M. , Uskova Evgeniya
Published: October 2024

Aerobic Bacillus bacteria, yeasts, and micrococci are pigment-forming microorganisms responsible for color defects in cheese production. The article describes their environment, industry-related characteristics, types of defects they cause, and various color violations in commercial cheeses. The research featured domestic cheeses with yellow and red surface spots that appeared during industrial ripening and storage. Pigment-forming microorganisms developed on cheese surface at a low ripening temperature, high concentration of table salt, and critically low oxygen. Pigment-forming microflora proved to enter cheese from milk, brine, or production environment, e.g., water, air, and processing equipment, dry and succulent feeds being the main source of milk contamination with spore-forming aerobic bacteria, yeast, mold fungi, etc. Contamination of raw milk, milking equipment, and air environment with micrococci was primarily associated with cows’ udder and skin. Cheese production presupposes low-temperature heat treatment of raw milk, which means possible residual microflora in pasteurized milk. As a result, the total count of mesophilic aerobic and optionally anaerobic microorganisms, i.e., the potential pigment formers, was to stay below 104 CFU/cm3. Yeast and spore-forming Bacillus microorganisms demonstrated the acceptable level of ≤102 CFU/cm3 in milk intended for cheesemaking. If their total count exceeded 103 CFU/cm3, it indicated high microbiological risks of cheese appearance defects. The microflora responsible for discoloration of cheese surface was represented by yeast, micrococci, aerobic spores, or their combinations.
Emulsification in Dairy Spread Production: Technological Aspects
Authors: Starovoitova Kseniya , Tereshchuk Lyubov , Kurbanova Marina
Published: October 2024

Different emulsifiers have different effects on the consistency and heat resistance of modelled dairy spread emulsions. In this research, the best results belonged to the samples of a complex emulsifier with distilled monoglycerides and lecithin (3 to 1). The resulting consistency was hard, elastic, and solid, with the highest temperature resistance of 0.90. The emulsification time and intensity affected the average size of lipid globules. The optimal size of 10-20 μm was registered after 10-15 min of emulsification at 100 rpm. The resulting dispersion level made it possible to achieve the best structural indicators of the final product.
Dominant Strategies for Solving Sensorimotor Tasks in Students with Different Cognitive Resource Experience
Authors: Krasnoryadtseva Olga M. , Eremina Evgeniya V. , Podoinitsina Maria A.
Published: October 2024

The article introduces a new method for diagnosing the preferable cognitive resource strategy in university students. One’s personal experience of using cognitive resources defines the dominant strategies for solving sensorimotor tasks. Cognitive resource patterns can be described by using particular psychological indicators in order to select the optimal analysis method. The new method made it possible to model the situation of solving sensorimotor tasks and develop criteria for determining the strategies employed by university students to solve cognitive tasks in experimental conditions. The research involved 127 first-year students (18 y.o.) of Psychology, Tomsk State University. The strategies used by the students to solve sensorimotor tasks ranged from scarcity and heterogeneity to positive experience in cognitive resource application. Sensorimotor tasks proved to be an effective diagnostic marker of the cognitive development level during university education. The method also proved applicable as a cognitive simulator to develop optimal strategies in solving sensorimotor tasks of various levels of difficulty, as well as to reduce the existing deficiency in cognitive experience.
Metacognitive Involvement and Critical Thinking in Technical Students in Information Environment
Authors: Krylova Natalya N.
Published: October 2024

Metacognitive involvement in activities and critical thinking are the soft skills students require as a basic adaptation resource in information environment at university, in life, and at work. This research explored the correlation between metacognitive involvement and critical thinking which university students of technical specialties used to navigate information environment. The study involved 58 male and 12 female fourth-year students (21.26 ± 0.47 y.o.) of the Penza State University, Penza, Russia. The list of methods employed included scientific review, survey, testing, and Spearman’s correlation analysis. The survey involved the following questionnaires: Metacognitive Involvement in Activity (G. Schraw, R. Dennison, 1994; eight-factor version by E. I. Perikova, V. M. Byzova, 2022); Critical Thinking Test (J. Kincher, 1990); author’s own questionnaire of Students and Information Environment (N. N. Krylova, 2024). The correlation analysis revealed strong relationships between nine indicators of metacognitive involvement in activities and critical thinking (p ≤ 0.001 and p ≤ 0.01). The Structure of Error Correction factor of metacognitive involvement depended on such a parameter of information environment as the input intensity. The metacognitive involvement in activities correlated with the students’ assessment of mental and information load in the curriculum, e.g., the Metacognitive Knowledge factor correlated with the mental and information load in Physics and Mathematics while the Error Correction Structure factor was associated with the load assessment in technical disciplines. In addition, some individual parameters of information environment correlated with the students’ assessment of mental and information load. In this study, metacognitive involvement in activities correlated with critical thinking in university students as they interacted with information environment because these phenomena are not isolated psychologically from each other.
Teacher-Directed Aggression: Causes Perceived vs. Aggression Experienced
Authors: Rean Artur A. , Kuzmin Roman G.
Published: October 2024

Teachers as victims of aggression seldom become focus of psychological research. However, teacher-directed violence has become a socially relevant phenomenon. Revealing the causes of teacher-directed aggression should at the core of antibullying programs. To identify these causes, psychologists need to study teachers’ experience and insights. The authors compared causes of teacher-directed aggression as perceived by teachers with their accounts of students’ aggression experience. The research relied on the methods of principal component analysis and Pearson’s correlation analysis. The sample consisted of 5,350 teachers from nine regions of the Russian Federation. Most respondents believed teacher-directed aggression to be caused by the dysfunctional family or parents’ disrespect of the teaching staff. The causes were divided into teacher-related, environmental, and intrapersonal. These variables correlated with teachers’ experience of student aggression. The phenomenon of teacher-directed aggression should be taken into account in violence prevention programs aimed at ensuring safety and well-being of both teachers and students.
Long-term effects of wildfires on river water quality: a comprehensive review of the variability of water quality in South Korea
Authors: Kim Changju , Han Heechan
Published: October 2024

After wildfires, the loss of the humus layer leads to increased runoff and pollutants entering rivers. This study examined the long-term effects of wildfires on water quality. We statistically analyzed the changes in the water quality of streams surrounding the wildfire area. We used eight water quality parameters provided by the National Institute of Environmental Research for the analysis. To assess the impact of the wildfires, we employed t-tests and point-biserial correlation analysis to compare the changes in water quality indicators before and after the wildfires. Additionally, an analysis of variance was conducted to evaluate the impact of three wildfires, each occurring in different periods, on the water quality in a single river basin. The results showed increasing trends in hydrogen ion concentration (pH), electrical conductivity, and dissolved oxygen after the wildfire, whereas biochemical oxygen demand, total phosphorus, and total nitrogen exhibited decreasing trends. The impact of wildfires on changes in suspended solids was relatively minimal. It is expected that the results of this study provide valuable insights into developing water quality management and restoration plans following wildfires.
Effect of integrated microbial fuel cell in a two-stage vertical flow constructed wetland for piggery wastewater treatment and resource recovery by photobioreactor
Authors: Gogoi Jayanta , N Karan , Nalwad Abhishek , Ganguly Anasuya , Mutnuri Srikanth
Published: October 2024

This study developed a nature-based pilot-scale technology for simultaneous piggery WW treatment and resource recovery potential. The technology comprised a two-stage vertical flow constructed wetland (2-VFCW) integrated with a microbial fuel cell (MFC) and microalgal photobioreactor. The first and second stage was an unsaturated and saturated type, respectively. The bioelectricity generation was optimised by investigating the suitable electrode zonation, hydraulic retention time (HRT) and WW loading rate. The 2-VFCW-MFC-treated effluent was studied to grow microalgae for biomass production. The 2-VFCW-MFC showed better treatment efficiency than the 2-VFCW, possibly due to enhanced microbial activity on the electrode surface, leading to improved organic matter degradation and electron transfer to the cathode, enhancing NO3− and PO43− reduction. The 2-VFCW-MFC with electrode zonation of 20 cm (cathode) and 60 cm (anode) and HRT of 76 h, 48 min showed the highest open-circuit voltage of 291.83+13.53 mV and WW treatment efficiency. The highest algal biomass of 21,323.34+8,316.26 mg/L (wet weight) was produced at HRT of 96 h, then entered the death phase. Comparatively, the 2-VFCW-MFC showed higher WW treatment efficiency than 2-VFCW at 2 L/day by 23.24% COD, 27.43% TOC, 33.05% PO43−, 13.51% NO3−, 8.14% TN, except TAN (22.71%).
Spatiotemporal monitoring of groundwater supply and active energy for irrigation practice in semi-arid regions of Tunisia with machine learning
Authors: Ben Mariem Sana , Kanzari Sabri , Zghibi Adel , Mouelhi Safouane , Bahrouni Hassouna , Ben Abdallah Mohamed Ali
Published: October 2024

Semiarid regions are facing overexploitation of groundwater resources to meet irrigation needs. Monitoring the water-energy nexus allows for optimal management of extracted water volumes and consumed energy. The Nabeul region of Tunisia was selected where 14 farmers, whose wells were equipped with smart electricity and water meters (SWEMs), for instant monitoring of pumped water volumes and the electrical energy required for irrigation. Monthly data over a period of eight months were used to study the variations in water volumes and active energy. The analysis of variance classified farmers into four groups based on water volumes and five groups based on active energy. Spatial variability analysis using kriging showed that the northeast zone is the most solicited in terms of water pumping and energy consumption with water volume exceeding 4,000 m3/month and active energy reaching 2,500 kWh/month. The prediction of energy based on water volume using machine learning techniques such as random forest and support vector machine was successfully conducted. The tools generated by the methodology were applied to a chosen case in the region to estimate active energy and validate the results obtained. The implemented framework allows for better management of groundwater resources for irrigation.
Towards more realistic stochastic modelling of leakage in water distribution systems
Authors: Beygi Soheila , van Zyl Jakobus E.
Published: October 2024

A new stochastic model is developed to predict leak types and sizes in water distribution systems. By linking records of actual failures in water networks with new tools for stochastic modelling, the study provides more accurate estimates of network leakage behaviour. District metered areas (DMAs) have been adopted internationally as best practice for monitoring and controlling leakage, with the infrastructure leakage index (ILI) as the main performance indicator. The leakage exponent (N1), which quantifies the relationship between leakage rate and pressure, is a key parameter in describing DMA leakage behaviour. After analysing thousands of stochastic networks for different combinations of pipe material and ILI, the study found that different pipe materials have distinct leakage exponent distributions. Iron and asbestos cement (AC) pipes display N1 values close to 0.5, polyvinyl chloride (PVC) pipes have the highest N1 values, and polyethylene (PE) lies between PVC and iron/AC. The study further showed that current guidelines linking ILI to N1 for different pipe materials depart substantially from the observed results, indicating that these guidelines may need to be updated. The study provides a tool for more realistic modelling of leakage that offers valuable insights into the behaviour of leakage in different pipe materials.
Membrane technology as a strategy for microplastics removal from landfill leachate: a review
Authors: Brito Fabio , Santos Carolina , Carpanez Thais , Moreira Victor Rezende , Amaral Míriam
Published: October 2024

This study offers a comprehensive review of global microplastic (MP) contamination in landfill leachate (LL) and examines remediation strategies using membrane technologies such as ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), and membrane bioreactors (MBRs). Research investigations and full-scale applications of these technologies for treating LL demonstrate their efficacy as viable solutions for on-site leachate treatment, providing promise in mitigating LL toxicity and reducing the environmental and human health risks associated with MP pollution. While the size of MPs in LL may raise questions about the necessity of using NF and RO membranes for MP removal, these processes are commonly employed in many landfills to serve as barriers for MP retention. Despite the high efficacy of MBR systems in removing MPs, the accumulation of MPs in the biological sludge can adversely affect biological performance and membrane fouling, necessitating further exploration. In general, membrane technologies face challenges such as membrane fouling and the release of MPs. Therefore, further research is needed to address MP removal, understand membrane–MP interactions, explore cleaning strategies in LL treatment and their impact on MP release from membranes, and study the integrity of membranes after continuous exposure to LL under varied operating conditions.
Relation of chemical characteristics and sensory profile of catfish (Pangasius sp.) belly processed by various smoking methods
Authors: Wijaya Fransisca , Tri Kumala Dewi Rike , Prathama Sebastian , Purnomo Wibisono Agus
Published: October 2024

Catfish (Pangasius sp.) belly, a by-product of the frozen fish fillet industry, has certain processing limitations, thereby reducing product utilization and selling value. It is a potential process for producing products with highl market acceptance. The study aimed to investigate the relationship between the chemical characteristics of a catfish belly in various smoking methods and its sensory profile. Various smoking methods in this research include smoking cabinets, vertical offset smokers, traditional smoking houses, and liquid smoke, which had different parameters of time, temperature, and distance to the smoke source. The chemical characteristics of smoked catfish belly were determined in terms of proximates, total phenols, and total acid. The sensory profiles in the form of intensity of 8 attributes of smoked catfish belly were obtained using the Rate-All-That-Apply method accompanied by a hedonic test (n = 80). Different smoking parameters in each method greatly influence the chemical characteristics and sensory profiles produced. Methods with longer smoking times will produce lower water content, increasing the fat content and a strong smoky aroma and taste. The correlation between chemical characteristics, sensory profile, and hedonic was also analyzed using Partial Least Square Regression (PLS regression) to determine the relationship with the stomach of smoked catfish belly using various methods. Of all the methods, the smoking cabinet was the optimal method for processing smoked catfish belly.
The effect of sago starch (Metroxylon sp.) and chitosan as edible coating on physical and chemical characteristics of red chili (Capsicum annuum L.)
Authors: Fahira Islami Iasha , Nurindra Rahmadhia Safinta
Published: October 2024

The reduced quality of red chili can be attributed to moisture loss. To inhibit water vapor transfer, one effective method is using an edible coating. This study aims to determine the effects of sago starch and chitosan as coating materials in reducing chili deterioration during storage at room temperature. A one-factorial, completely randomized design was used, with variations in the ratios of sago starch to chitosan (76.19%:23.81%, 71.43%:28.57% and 66.67%:33.33%). The parameters tested included weight loss, hardness, color, and moisture content. Red chili storage was conducted at room temperature, with observations on days 1, 3, 6, 9, 12, and 15. The results indicated that the edible coating made from sago starch and chitosan significantly impacted the weight loss, hardness, color, and moisture content of the red chili. The best treatment for maintaining the physical and chemical properties of red chili during room temperature storage was the 66.67% sago starch and 33.33% chitosan formulation, which resulted in a weight loss of 46.99%, hardness of 35.01 N, color a* value of 30.60%, color b* value of 20.90%, brightness L* value of 26.11%, and moisture content of 67.92%.
OBJECT DETECTION IN HOCKEY SPORT VIDEO VIA PRETRAINED YOLOV3 BASED DEEP LEARNING MODEL
Authors:   Gujarat Technological University, India, H. Patel Suhas , Kamdar Dipesh ,   V.V.P. Engineering College, India
Published: October 2024

Object detection is the most common task in Sports Video Analysis. This task requires accurate object detection that can handle a variety of objects of different sizes that are partially occluded, have poor lighting, or are presented in complicated surroundings. Object in field sports includes player’s team and ball detection; this is a difficult task resulting from the rapid movement of the player and speed of the object of concern. This paper proposes a pre-trained YOLOv3, deep learning-based object detection model. We have prepared a hockey dataset consisting of four main entities: Team 1 (AUS), Team 2 (BEL), Hockey Ball, and Umpire. We constructed own dataset because there are no existing field hockey datasets available. Experimental results indicate that the pre-trained YOLOV3 deep learning model generates comparative results on this dataset by modifying the hyperparameters of this pre-trained model.
AN ENHANCED ENSEMBLE HYBRID DEEP LEARNING ALGORITHM FOR IMPROVING THE ACCURACY IN IRIS SEGMENTATION
Authors:   Karpagam Institute of Technology, India, M Sathiya , K Karunambiga ,   Karpagam Institute of Technology, India, Kumar G. Sai Chaitanya ,   DVR and Dr. HS MIC College of Technology, India, Sekaran S. Chandra ,   PSV College of Engineering and Technology, India
Published: October 2024

In recent years, there has been a meteoric rise in the application of deep neural networks for the purpose of iris segmentation. This can be attributed to the extraordinary capacity for learning possessed by the convolution kernels that are utilised by CNNs. Conventional methods have several drawbacks, some of which can be partially compensated for by using CNN-based algorithms, which increase the segmentation precision. On the other hand, the CNN-based iris segmentation approaches that are currently in use typically require a more complex network, which results in an increase in the number of parameters. This is essential to realise a higher degree of precision in the results. CNN-based techniques are effective, they can only be used for a specific application. This makes them inappropriate for general iris segmentation goals, even though they are effective.
AN IMPROVED SEGMENTATION METHOD FOR BRAIN CANCER USING CAPSULE NEURAL NETWORKS
Authors:   Chettinad College of Engineering and Technology, India, M Kumar , Ramasamy Jayaraj ,   Botho University, Botswana, Kumar M. Praveen ,   Vellore Institute of Technology, Vellore, India, B.K. Harsha ,   CMR Institute of Technology, India
Published: October 2024

Brain cancer is a life-threatening disease that requires accurate and efficient segmentation methods for effective diagnosis and treatment planning. In this study, we propose an improved segmentation method for brain cancer using Capsule Neural Networks (CapsNets). CapsNets are a promising alternative to traditional convolutional neural networks (CNNs) as they capture spatial relationships between features more effectively. However, existing CapsNet-based segmentation methods suffer from limitations such as low segmentation accuracy and high computational complexity. To address these limitations, we introduce an improved CapsNet architecture that incorporates dynamic routing and attention mechanisms. The dynamic routing algorithm enhances the routing process between capsules, allowing for better feature representation and improved segmentation accuracy. Additionally, the attention mechanism focuses the network’s attention on important regions, reducing the computational complexity without sacrificing segmentation quality. We evaluate the proposed method on a publicly available brain cancer dataset and compare its performance against state-of-the-art segmentation approaches. The experimental results demonstrate that our method achieves superior segmentation accuracy and outperforms existing methods in terms of Dice coefficient and Hausdorff distance. Furthermore, our method demonstrates faster convergence and reduced computational complexity compared to previous CapsNet-based approaches. In conclusion, this study presents an improved segmentation method for brain cancer using Capsule Neural Networks. The proposed method addresses the limitations of existing CapsNet-based approaches by incorporating dynamic routing and attention mechanisms. The experimental results validate the effectiveness of our method, showcasing superior segmentation accuracy and reduced computational complexity. The improved segmentation method has the potential to enhance the diagnosis and treatment planning of brain cancer, ultimately contributing to improved patient outcomes.
DEEP REINFORCEMENT LEARNING-BASED OPTIMIZATION AND ENHANCEMENT OF MULTIMEDIA DATA: AN INNOVATIVE APPROACH
Authors:   Indian Institute of Information Technology Kalyani, India, Ponnusamy Muruganantham , T Prabakaran ,   Joginpally B. R. Engineering College, India, Thouti Swapna ,   CVR College of Engineering, India, Ravichandran Saivarshini ,   University of Rochester - Simon Business School, United States
Published: October 2024

The rapid growth of multimedia data in various domains has necessitated the development of efficient techniques to enhance and optimize its quality. Traditional approaches often struggle to address the complexity and diversity of multimedia data, leading to suboptimal results. This paper presents a novel approach to tackle this challenge by leveraging the power of deep reinforcement learning (DRL). The proposed method utilizes DRL to learn and optimize multimedia data in an improvised manner. By employing a combination of convolutional neural networks and deep Q-networks, the model can effectively extract high-level features and make informed decisions to enhance the quality of multimedia data. The reinforcement learning framework enables the system to learn from its actions, continuously improving its performance through an iterative process. To evaluate the effectiveness of the proposed method, extensive experiments were conducted using a diverse set of multimedia datasets. The results demonstrate significant improvements in various quality metrics, including image resolution, video frame rate, and audio clarity. Additionally, the proposed approach exhibits robustness across different types of multimedia data, ensuring consistent enhancement performance across various domains. Furthermore, the computational efficiency of the proposed method is also highlighted, as it demonstrates faster convergence and lower computational overhead compared to traditional optimization methods. This makes the approach practical for real-time applications where multimedia data needs to be processed efficiently. Overall, this paper introduces an innovative framework that combines deep reinforcement learning with multimedia data optimization. The results indicate its potential for enhancing multimedia data quality, offering a promising solution to the challenges associated with traditional approaches. The proposed method not only improves the visual and auditory aspects of multimedia content but also provides a scalable and efficient solution for real-world applications in domains such as image processing, video streaming, and audio analysis.
LINEAR REGRESSION-BASED ANALYSIS OF MULTIMEDIA DATA FOR AI-DRIVEN PATTERN RECOGNITION
Authors:   Abhijit Kadam Institute of Management and Social Sciences, India, Nadaf Akabarsaheb Babulal , Adivarekar Pravin Prakash ,   A.P. Shah Institute of Technology, India, Dwivedi Vijay Kumar ,   Vishwavidyalaya Engineering College, India, Yadav Dharmendra Kumar ,   Lalit Narayan Mithila University, India
Published: October 2024

Multimedia data, encompassing images, videos, and audio, has become a cornerstone in various AI-driven applications, particularly in pattern recognition tasks. The increasing complexity and volume of multimedia data necessitate robust and scalable analytical approaches. Traditional pattern recognition techniques often struggle to effectively manage the high-dimensional and multimodal nature of multimedia data. This study addresses the challenge by leveraging linear regression for analyzing multimedia data to enhance AI-driven pattern recognition. The proposed method integrates linear regression models with feature extraction techniques to identify and map underlying patterns within the multimedia data. The process begins with preprocessing steps, including normalization and dimensionality reduction, to ensure data consistency and manage computational complexity. Subsequently, linear regression models are applied to establish relationships between the extracted features and predefined classes or labels. The model’s performance is evaluated using precision, recall, and F1-score metrics. Experimental results on a benchmark multimedia dataset reveal that the proposed approach achieves an average accuracy of 92.4%, with a precision of 91.8% and a recall of 93.1%. These results outperform several state-of-the-art methods, demonstrating the model’s efficacy in accurately recognizing patterns within diverse multimedia data. Furthermore, the model exhibits scalability, maintaining high performance even when applied to large-scale datasets, thus validating its potential for real-world AI applications. The study concludes that linear regression, when integrated with appropriate feature extraction and preprocessing techniques, offers a viable solution for enhancing AI-driven pattern recognition in multimedia data.
Behavior Change Techniques Used in Self-Management Interventions Based on mHealth Apps for Adults With Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Zhou You , Li Si-Jia , Huang Ren-Qian , Ma Hao-Ming , Wang Ao-Qi , Tang Xing-Yi , Pei Run-Yuan , Piao Mei-Hua
Published: October 2024

Background

Hypertension has become an important global public health challenge. Mobile health (mHealth) intervention is a viable strategy to improve outcomes for patients with hypertension. However, evidence on the effect of mHealth app interventions on self-management in patients with hypertension is yet to be updated, and the active ingredients promoting behavior change in interventions remain unclear.

Objective

We aimed to evaluate the effect of mHealth app self-management interventions on blood pressure (BP) management and investigate the use of behavior change techniques (BCTs) in mHealth app interventions.

Methods

We conducted a literature search in 6 electronic databases from January 2009 to October 2023 for studies reporting the application of mHealth apps in self-management interventions. The Cochrane Risk of Bias (version 2) tool for randomized controlled trials was used to assess the quality of the studies. BCTs were coded according to the Taxonomy of BCTs (version 1). The extracted data were analyzed using RevMan5.4 software (Cochrane Collaboration).

Results

We reviewed 20 studies, of which 16 were included in the meta-analysis. In total, 21 different BCTs (mean 8.7, SD 3.8 BCTs) from 12 BCT categories were reported in mHealth app interventions. The most common BCTs were self-monitoring of outcomes of behavior, feedback on outcomes of behavior, instruction on how to perform the behavior, and pharmacological support. The mHealth app interventions resulted in a –5.78 mm Hg (95% CI –7.97 mm Hg to –3.59 mm Hg; P<.001) reduction in systolic BP and a –3.28 mm Hg (95% CI –4.39 mm Hg to –2.17 mm Hg; P<.001) reduction in diastolic BP. The effect of interventions on BP reduction was associated with risk factors, such as hypertension, that were addressed by the mHealth app intervention (multiple risk factors vs a single risk factor: –6.50 mm Hg, 95% CI –9.00 mm Hg to –3.99 mm Hg vs –1.54 mm Hg, 95% CI –4.15 mm Hg to 1.06 mm Hg; P=.007); the presence of a theoretical foundation (with vs without behavior change theory: –10.06 mm Hg, 95% CI –16.42 mm Hg to –3.70 mm Hg vs –4.13 mm Hg, 95% CI –5.50 to –2.75 mm Hg; P=.07); intervention duration (3 vs ≥6 months: –8.87 mm Hg, 95% CI –10.90 mm Hg to –6.83 mm Hg vs –5.76 mm Hg, 95% CI –8.74 mm Hg to –2.77 mm Hg; P=.09); and the number of BCTs (≥11 vs <11 BCTs: –9.68 mm Hg, 95% CI –13.49 mm Hg to –5.87 mm Hg vs –2.88 mm Hg, 95% CI –3.90 mm Hg to –1.86 mm Hg; P<.001).

Conclusions

The self-management interventions based on mHealth apps were effective strategies for lowering BP in patients with hypertension. The effect of interventions was influenced by factors related to the study’s intervention design and BCT.
Social Media Usage for Medical Education and Smartphone Addiction Among Medical Students: National Web-Based Survey
Authors: Clavier Thomas , Chevalier Emma , Demailly Zoé , Veber Benoit , Messaadi Imad-Abdelkader , Popoff Benjamin
Published: October 2024

Background

Social media (SoMe) have taken a major place in the medical field, and younger generations are increasingly using them as their primary source to find information.

Objective

This study aimed to describe the use of SoMe for medical education among French medical students and assess the prevalence of smartphone addiction in this population.

Methods

A cross-sectional web-based survey was conducted among French medical students (second to sixth year of study). The questionnaire collected information on SoMe use for medical education and professional behavior. Smartphone addiction was assessed using the Smartphone Addiction Scale Short-Version (SAS-SV) score.

Results

A total of 762 medical students responded to the survey. Of these, 762 (100%) were SoMe users, spending a median of 120 (IQR 60‐150) minutes per day on SoMe; 656 (86.1%) used SoMe for medical education, with YouTube, Instagram, and Facebook being the most popular platforms. The misuse of SoMe in a professional context was also identified; 27.2% (207/762) of students posted hospital internship content, and 10.8% (82/762) searched for a patient’s name on SoMe. Smartphone addiction was prevalent among 29.1% (222/762) of respondents, with a significant correlation between increased SoMe use and SAS-SV score (r=0.39, 95% CI 0.33‐0.45; P<.001). Smartphone-addicted students reported a higher impact on study time (211/222, 95% vs 344/540, 63.6%; P<.001) and a greater tendency to share hospital internship content on social networks (78/222, 35.1% vs 129/540, 23.8%; P=.002).

Conclusions

Our findings reveal the extensive use of SoMe for medical education among French medical students, alongside a notable prevalence of smartphone addiction. These results highlight the need for medical schools and educators to address the responsible use of SoMe and develop strategies to mitigate the risks associated with excessive use and addiction.
Video Abstracts in Research
Authors: Nachman Sophie , Ortiz-Prado Esteban , Tucker Joseph D
Published: October 2024

Video abstracts can be useful in health research. A video abstract provides key messages about a research article and can increase public engagement, spark conversations, and may increase academic attention. A growing number of open source software programs make it easier to develop a video abstract. This viewpoint provides practical tips for creating a video abstract for health research.
Konfiks Derivasi Per-/-an dalam Debat Capres-Cawapres Tahun 2024: Metode Linguistik Korpus
Authors: Dhika JR Vicno Triwira
Published: October 2024

This research aimed to discuss the “per-/-an” confix which has undergone derivation in Indonesian. This research used the presidential and vice presidential candidate debate script number 01 as the research object studied. This research used a qualitative corpus linguistics approach. The corpus linguistic approach used in this research utilized the KORTARA (Korpus Nusantara) corpus linguistic application. The KORTARA corpus linguistic application (Korpus Nusantara) is an application that can help to collect, process and analyze linguistic data digitally. Data collection in this research utilized the affix word search feature to find specific data containing affixes. The affix word search feature was lasted by accessing the corpus menu in the KORTARA (Korpus Nusantara) application, then selecting the 2024 presidential-cawapres debate script as the object for research. Based on the research that has been carried out, 56 data were obtained on the use of the derivation confix per-/-an in the corpus of the 01 Presidential-Cawapres debate texts in 2024. The results of this research can have implications in the scientific field of morphology related to the principles of derivational development in Indonesian.
Aspirasi Pemuda di Kabupaten Klaten untuk Pendidikan Tinggi sebagai Kerja Generasi dan Konstruksi Identitas
Authors: Warda Yusnita Silsilia
Published: October 2024

This article qualitatively explores the production processes of higher education aspirations among students and recent graduates of upper-secondary schools in Klaten Regency. Considering the socio-spatial and temporal context, this study examines the dynamics of aspirations in the ‘desakota’ region during the digital era, an area that has been relatively underresearched. Data generation in this study primarily relies on in-depth interviews with eleven participants. Employing the concepts of identity and generations, this study reveals that higher education aspirations are refinements of individual narratives constructed through interactions with adults and peers in educational, familial, and digital settings. Situated in an in-between area, the production process of aspirations among Klaten’s youth reflects an ambiguity as traditional factors collide with values brought by modernity. I propose that aspirations for higher education in this context are both social and individual projects, encompassing not only future, but also present matters through which youth fashion themselves. This mirrors the critics towards developmental approach that frames educational aspirations predominantly as rational decision aimed at achieving upward social mobility.
Contribution of Green Supply Chain Management Practices towards a Sustainable Development—Applied Study in the Food Industry in Lebanon
Authors: Ayoubi Mohamad Saad El
Published: October 2024

This paper explores the effect of Green Supply Chain Management (GSCM) practices on the dimensions of Sustainable Development (SD) in the context of the Lebanese food industry. It aimed to examine to what extent GSCM practices and SD schemes are perceived in the food industry. As there is a growing concern and raising awareness of traceability among consumers in the food supply, researches can have a contribution to develop sustainability in food industry.  As such, six GSCM practices, namely Eco-design (ED), Internal Environmental Management (IEM), Investment Recovery (IR), Green Purchasing (GP), Environmental Cooperation (EC) and Reverse Logistics (RL) were employed. These six GSCM variables were used to analyze structural relationships with the three dimensions of the SD, that is to say economic, environmental and social performances. The proposed model was tested using a questionnaire based survey via two modes of face to face and emails using a plant survey, senior managers of 88 food companies in Lebanon. The data were analyzed in SPSS and AMOS statistical programs. An Exploratory (Unrestricted) Factor Analysis (EFA), Confirmatory (Restricted) Factor Analysis (CFA) and multiple regressions were applied. The Structural Equation Modeling (SEM) revealed that the GSCM practices IR, GP, ED and IEM had significant relationships with one or more of the SD dimensions.On the basis of the findings, implications that may ameliorate the effect of GSCM practices on the SD dimensions can be taken into consideration. For instance, the enhance of the environmental cooperation with the suppliers and customers, improving the image of the company in the mind of their customers, reinforcing the commitment of GSCM from managers, utilization of cleaner technology, activation of internal performance evaluation system, enhancing the labor conditions and performing special training for workers on environmental issues.
Impacto de la violencia en el Índice de Desarrollo Humano
Authors: Jiménez-López Eduardo , Cadena-Vargas Edel
Published: October 2024

La violencia limita el desarrollo humano y reduce la probabilidad de que una persona alcance su máximo potencial. En este trabajo identificamos el efecto que tiene la violencia sobre el desempeño de las personas medidas por tres variables que componen el índice de desarrollo humano (IDH), con la ayuda de una técnica estandarizada matemático-espacial es aplicada a datos obtenidos para municipios del Estado de México. Que identifica la relación causal, se utiliza la regresión geográficamente ponderada, aprovechando la existencia de una ventana temporal que encuentran las relaciones entre las diferentes variables que proponemos en este trabajo. En la medida en que la violencia afecta los factores del IDH se tiene impactos persistentes sobre el bienestar, discutimos las implicaciones de la violencia sobre la educación, salud y nivel de vida en los municipios en estudio.
El efecto de la fecundidad adolescente en resultados educativos: el caso de Chile
Authors: Barahona-Chiappe Pía Carolina , Salinas-Ulloa Viviana
Published: October 2024

Esta investigación estima los efectos diferenciales de la fecundidad adolescente en la acumulación de capital humano de mujeres y hombres en Chile y pregunta por cambios en dichos efectos entre tres cohortes. Se toma en consideración el problema de la selectividad de origen, es decir, el hecho de que quienes experimentan fecundidad adolescente habitualmente tienen un background socioeconómico que los predispone a resultados educacionales desfavorables. Se utiliza la Encuesta de Caracterización Socioeconómica Nacional 2017 y se realiza un análisis en base a ponderación de propensity scores y ajuste con modelos de regresión. Nuestros resultados indican que el efecto negativo de la fecundidad adolescente en la probabilidad de concluir la enseñanza secundaria o acceder a educación superior es más grande para las mujeres que los hombres, pero la brecha de género ha disminuido a través del tiempo, a tal punto que en la cohorte más joven no hay diferencias significativas.
A prática de escrita em uma perspectiva dialógica de linguagem: interações entre ensino fundamental e superior
Authors: Nascimento Débora Ventura Klayn
Published: October 2024

Este artigo apresenta uma experiência discursiva estabelecida entre alunos da educação básica e superior. De um lado, estudantes do ensino fundamental II (6° ao 9° ano) escrevem com o objetivo de passar orientações pedagógicas a futuros professores de Português. De outro, licenciandos prestes a concluir o curso de Letras Português/Literaturas recebem, analisam e respondem as cartas dos referidos alunos. Transitando e servindo de correio em meio a essa linha enunciativa, uma professora atuante na educação básica e estreante como docente substituta no ensino superior busca estabelecer uma ponte entre educação básica e superior. Para isso, com base em estudos que mostram a importância de contextualização discursiva nas atividades de produção textual, bem como em discussões a respeito de concepções de educação, este artigo discute sobre expectativas e reflexões dos aprendizes transeuntes da ponte e do evento discursivo estabelecido (aprendizes transeuntes entre os quais a professora correio se inclui). Como procedimento metodológico e fundamentação teórica, usa-se a Análise Dialógica do Discurso, a fim de problematizar a experiência didática, bem como as percepções sobre a prática docente. Os resultados apontam para concepções de educação cristalizadas na educação básica e percepções as quais levam a (re)pensar práticas de formação inicial.
A centralidade do texto no ensino de lí­ngua materna: uma perspectiva da Filosofia da Linguagem do Cí­rculo de Bakhtin
Authors: Oliveira Antonio Flávio Ferreira de
Published: October 2024

Este trabalho discute a influência da filosofia do Cí­rculo de Bakhtin nas metodologias hodiernas de ensino de lí­ngua portuguesa no Brasil. Nesse sentido, tem o objetivo de investigar a atuação do princí­pio dialógico como fator primordial para a implementação de metodologias que fomentem uma prática de ensino que priorize a construção de competências para o multiletramento social. Para tanto, foram mobilizados conceitos de autores do Cí­rculo, mais precisamente de Volochí­nov (2013), Volóchinov (2017), Bakhtin (2010, 2011 e 2015), e de autores que interpretam essas teorias, como Geraldi (2006, 2007), Antunes (2003), Rojo e Cordeiro (2004), Soares (2010), Rojo e Moura (2012, 2019). Metodologicamente, a pesquisa é bibliográfica em diálogo com a qualitativa-interpretativista. Como resultado, foi constatado que o princí­pio dialógico orienta as metodologias hodiernas do ensino de lí­ngua materna fomentando práticas pedagógicas caracterizadas e alinhadas ao processo de construção de competências linguí­stico-discursivas no aluno para escrever e ler as diversas realidades da vida.
Processos mentais e construção de sentidos na fundamentação teórica da tese de doutorado
Authors: Frutuoso Anikele
Published: October 2024

A tese de doutorado é um texto que requer dos autores rigor nas escolhas linguí­sticas, posicionamento e maior processamento mental. Cada unidade retórica que compõe o texto da tese de doutorado carrega em si funções que lhes são inerentes. Nesse sentido, a Fundamentação Teórica da tese de doutorado tem como função maior apresentar uma discussão pertinente acerca da teoria a qual embasa a tese. Os processos mentais configuram como grupos verbais responsáveis por sentidos relacionados à consciência, à emoção, ao desejo, a percepção. Assim sendo, este artigo propõe analisar ouso dos processos mentais na construção de sentido da unidade retórica Fundamentação Teórica da tese de doutorado. Desse modo, elencamos como aporte teórico a Linguí­stica Sistêmico-Funcional (HALLIDAY E MATHIESSEN, 2004, 2014) entre outros estudiosos dessa vertente teórica, como Fuzer e Cabral (2014), no Brasil. Utilizamos o corpus TACTESE, de Figueiredo-Gomes e Bertuleza (no prelo). Para recenseamento dos processos mentais utilizamos a ferramenta concord para visualização das listas de orações mentais presentes no corpus. Os resultados mostram que os processos cognitivos predominam em maior frequência (82,3 %), são usados para construir argumentação, apresentar objetos teóricos na unidade retórica Fundamentação Teórica. Em sequência, aparecem os processos desiderativos que representam 9%  das ocorrências e realizam significados relacionados a entidos inerentes a vontades, asseveração em relação a pontuações teóricas, os perceptivos, com menor frequência 4,7% são usados para representar percepções, os emotivos com 4% que inferem sentidos relacionados a graus de emoção. O alto uso de processos mentais no corpus revela como o sistema de transitividade se configura como recurso léxicogramatical para construir sentidos na da unidade retórica Fundamentação Teórica.
Ressignificações: sobre o tempo em Walter Benjamin e em Émile Benveniste
Authors: Garcia dos Anjos Aroldo
Published: October 2024

Este trabalho filia-se ao campo das investigações acerca de uma antropologia histórica da linguagem, especialmente no que toca à busca de uma interface entre a linguí­stica e a literatura. Presente nas reflexões de Walter Benjamin e de Émile Benveniste, a crí­tica à instrumentalidade da linguagem traz consigo desdobramentos para a forma como os autores concebem o tempo e a história. A partir da problematização da relação entre linguagem e experiência, proposta por Agamben, objetiva-se observar a expressão da temporalidade nas obras de ambos autores. Para tanto, serão discutidas e aproximadas noções fundamentais como as de tempo-agora e de tempo linguí­stico.
Investigando os tipos de processos no resumo acadêmico: um estudo sistêmico-funcional
Authors: Silva Débora Brenda Teixeira , Oliveira Natalyany Nunes , Barbosa José Roberto Alves
Published: October 2024

Considerando os estudos Funcionalistas da linguagem, destacamos a Linguí­stica Sistêmico-Funcional (LSF) enquanto uma teoria voltada à investigação do uso e da forma da lí­ngua. Diante disso, este trabalho tem por objetivo analisar o sistema de transitividade, especificamente os processos, na construção de resumos acadêmicos, conforme suas unidades retóricas. De forma mais especí­fica, intentamos identificar a ordem de frequência dos processos presentes no corpus e comparar o número de ocorrências dos tipos de processos em cada unidade retórica. Sendo a LSF uma abordagem importante ao Funcionalismo Linguí­stico, para tratar desse assunto, tomamos especialmente as contribuições teóricas de Fuzer e Cabral (2014), Halliday e Matthiessen (2014) e Santos (2014); ao passo que, para tratar do resumo acadêmico, baseamo-nos principalmente em Biasi-Rodrigues (1998, 1999) e Motta-Roth e Hendges (2010). Nesse contexto, analisamos resumos de oito monografias do curso de Letras Lí­ngua Inglesa e suas respectivas Literaturas, da Universidade do Estado do Rio Grande do Norte, produzidas no ano de 2019. A partir dos resultados obtidos, constatamos que, dentre os processos, o único não identificado foi o comportamental, enquanto que os processos materiais apresentaram maior frequência, seguidos dos relacionais, mentais, verbais e existenciais. No tocante à frequência por unidade retórica, verificamos que os processos materiais também são os mais recorrentes, variando apenas na ordem de frequência dos demais. Isto posto, concluí­mos que os resumos investigados são constituí­dos com maior frequência de processos materiais, o que relaciona sua natureza do "˜fazer"™ com a finalidade caracterí­stica do gênero resumo, que é apresentar concisamente um estudo realizado.