bluuebunny/crossref_metadata_2025 huggingface dataset:
A Reconstructing Model Based on Time–Space–Depth Partitioning for Global Ocean Dissolved Oxygen Concentration
Authors: Wang Zhenguo , Xue Cunjin , Ping Bo
Published: January 2024

Dissolved oxygen (DO) is essential for assessing and monitoring the health of marine ecosystems. The phenomenon of ocean deoxygenation is widely recognized. Nevertheless, the limited availability of observations poses a challenge in achieving a comprehensive understanding of global ocean DO dynamics and trends. The study addresses the challenge of unevenly distributed Argo DO data by developing time–space–depth machine learning (TSD-ML), a novel machine learning-based model designed to enhance reconstruction accuracy in data-sparse regions. TSD-ML partitions Argo data into segments based on time, depth, and spatial dimensions, and conducts model training for each segment. This research contrasts the effectiveness of partitioned and non-partitioned modeling approaches using three distinct ML regression methods. The results reveal that TSD-ML significantly enhances reconstruction accuracy in areas with uneven DO data distribution, achieving a 30% reduction in root mean square error (RMSE) and a 20% decrease in mean absolute error (MAE). In addition, a comparison with WOA18 and GLODAPv2 ship survey data confirms the high accuracy of the reconstructions. Analysis of the reconstructed global ocean DO trends over the past two decades indicates an alarming expansion of anoxic zones.
Optimizing Terrain Classification Methods for the Determination of Bedrock Depth and the Average Shear Wave Velocity of Soil
Authors: Choi Inhyeok , Kwak Dongyoup
Published: January 2024

The advancement of remote sensing has enabled the creation of high-resolution Digital Elevation Models (DEMs). Topographic features such as slope gradient (SG), local convexity (LC), and surface texture (ST), derived from DEMs, are related to subsurface geological conditions. In South Korea, bedrock depth (Dbedrock) and the average shear wave velocity of soil (VSsoil) serve as metrics for determining the site class, which represents the degree of site amplification in seismic design criteria. These metrics, typically measured through geotechnical and geophysical investigations, require predictive methods for preliminary estimation over large areas. Previous studies developed an automatic terrain classification (AC) scheme using SG, LC, and ST, and subsequent research revealed that terrain classification effectively represents subsurface conditions such as Dbedrcok and average shear wave velocity down to 30 m depth. However, AC intrinsically depends on the regional features of DEMs, dividing regions based on nested means of topographic features (SG, LC, and ST). In this study, we developed two terrain classification methods to determine the thresholds of class divisions, aiming to optimize Dbedrock and VSsoil predictions: Sequentially Optimized Classification (SOC) and Non-Sequentially Optimized Classification (NOC). Through the study of the sensitivity of terrain classification methods, smoothing levels, and threshold levels for terrain class generation, we identified the best classification method by comparing it with the geological and mountainous region distribution. Subsequently, we developed DEM-dependent regression models for each class to enhance the accuracy of predicting Dbedrock and VSsoil. The main findings of this study are: (1) the terrain class map suggested in this study represents the distribution of alluvial plane and mountainous regions well, and (2) the DEM calibration for each class provides increased accuracy of Dbedrock and VSsoil predictions in South Korea. We anticipate that the terrain class map, along with Dbedrock and VSsoil maps, will be effectively utilized in geological interpretations and land-use planning for seismic design.
Time-Series-Based Spatiotemporal Fusion Network for Improving Crop Type Mapping
Authors: Zhan Wenfang , Luo Feng , Luo Heng , Li Junli , Wu Yongchuang , Yin Zhixiang , Wu Yanlan , Wu Penghai
Published: January 2024

Crop mapping is vital in ensuring food production security and informing governmental decision-making. The satellite-normalized difference vegetation index (NDVI) obtained during periods of vigorous crop growth is important for crop species identification. Sentinel-2 images with spatial resolutions of 10, 20, and 60 m are widely used in crop mapping. However, the images obtained during periods of vigorous crop growth are often covered by clouds. In contrast, time-series moderate-resolution imaging spectrometer (MODIS) images can usually capture crop phenology but with coarse resolution. Therefore, a time-series-based spatiotemporal fusion network (TSSTFN) was designed to generate TSSTFN-NDVI during critical phenological periods for finer-scale crop mapping. This network leverages multi-temporal MODIS-Sentinel-2 NDVI pairs from previous years as a reference to enhance the precision of crop mapping. The long short-term memory module was used to acquire data about the time-series change pattern to achieve this. The UNet structure was employed to manage the spatial mapping relationship between MODIS and Sentinel-2 images. The time distribution of the image sequences in different years was inconsistent, and time alignment strategies were used to process the reference data. The results demonstrate that incorporating the predicted critical phenological period NDVI consistently yields better crop classification performance. Moreover, the predicted NDVI trained with time-consistent data achieved a higher classification accuracy than the predicted NDVI trained with the original NDVI.
Suitability Assessment of Cage Fish Farming Location in Reservoirs through Neural Networks-Based Remote Sensing Analysis
Authors: Sedighkia Mahdi , Datta Bithin
Published: January 2024

The present study evaluates the application of different artificial intelligence methods associated with remote sensing data processing for assessing water quality parameters, with a focus on fish cage farming in the reservoirs. Three AI methods were utilized including 1—optimal artificial neural network (ONN), 2—adaptive neuro fuzzy inference system in which a hybrid algorithm was used for the training process (ANFIS) and 3—coupled evolutionary algorithm-adaptive neuro fuzzy inference system in which particle swarm optimization was utilized in the training process (EA-ANFIS). Three critical water quality parameters for cage fish farming were selected consisting of water temperature, dissolved oxygen (DO) and total dissolved solids (TDS). Moreover, two measurement indices, the Nash–Sutcliffe model efficiency coefficient (NSE) and root mean square error (RMSE), were utilized to assess the predictive skills of the data driven models. Based on the results in the case study, EA-ANFIS is the best method to simulate water temperature and DO in the reservoir by the remote sensing technique. Furthermore, the ANFIS-based model is the best method to simulate TDS. According to the results in the case study, utilizing the spectral images might not be reliable to simulate DO concentration in the reservoirs. However, the images are robust to simulate water temperature as well as TDS concentration.
Editorial on Hydrology and Water Resources in Agriculture and Ecology
Authors: Shang Songhao , Gabriel Hamza Farooq , Zhang Qianqian
Published: January 2024

The agricultural sector uses the largest share of freshwater, accounting for over 70% of the global freshwater withdrawals, and this proportion can be up to 90% in arid and semiarid regions [...]
Sensing and Deep CNN-Assisted Semi-Blind Detection for Multi-User Massive MIMO Communications
Authors: Han Fengxia , Zeng Jin , Zheng Le , Zhang Hongming , Wang Jianhui
Published: January 2024

Attaining precise target detection and channel measurements are critical for guiding beamforming optimization and data demodulation in massive multiple-input multiple-output (MIMO) communication systems with hybrid structures, which requires large pilot overhead as well as substantial computational complexity. With benefits from the powerful detection characteristics of MIMO radar, we aim for designing a novel sensing-assisted semi-blind detection scheme in this paper, where both the inherent low-rankness of signal matrix and the essential knowledge about geometric environments are fully exploited under a designated cooperative manner. Specifically, to efficiently recover the channel factorizations via the formulated low-rank matrix completion problem, a low-complexity iterative algorithm stemming from the alternating steepest descent (ASD) method is adopted to obtain the solutions in case of unknown noise statistics. Moreover, we take one step forward by employing the denoising convolutional neural network (DnCNN) to preprocess the received signals due to its favorable performance of handling Gaussian denoising. The overall paradigm of our proposed scheme consists of three stages, namely (1) target parameter sensing, (2) communication signal denoising and (3) semi-blind detection refinement. Simulation results show that significant estimation gains can be achieved by the proposed scheme with reduced training overhead in a variety of system settings.
The Media and Information in the Content Diet of Colombian Social Media Users
Authors: Barrios-Rubio Andrés
Published: January 2024

The mass media are central to everyday life, a meeting point for citizens with the facts of the current social situation, and a space for the meaning, perception, interpretation, and construction of the notion of reality in the collective imagination. The impact of technology and communication platforms on the social fabric has opened up access to information and atomized trust and credibility in the face of the journalistic brand, an instance of crisis on the smartphone screen in which the media are relegated to the background and influencers, opinion leaders, and the protagonists of the facts themselves, in direct contact with the followers, gain relevance. The transformation configured in the users’ content diet aims to review the industry’s behavior on social networks to interpret why it is losing its place in the citizens’ consumption agenda. This research, which relied on a mixed methodology, downloaded messages from Facebook, X/Twitter, Instagram, YouTube, and TikTok profiles of two written, five audio, and two audiovisual media in a period of 91 days, and added them to what was carried out in the same period in 2019 and 2021. The corpus of the study made it possible to prove the composition of the communication, the operational tactics, and the thematic axis. The research concluded that the Colombian mass media need to innovate to establish productive routines that bet on digital native products, corresponding to the dynamics of networked consumption by an audience that concentrates all actions on screen devices.
Suggesting Context Differences Influence the Impact of Nurses’ Psychological Contracts
Authors: Rodwell John , Ellershaw Julia
Published: January 2024

Inconsistent findings regarding psychological contracts may be due to the variety of contexts studied. Sensemaking processes inform the psychological contract and may explain contextual differences. This study examines the psychological contract components of promises, fulfillment and breach, with negative affectivity, in relation to employee-level outcomes in two related but different contexts. Surveys were completed by 162 hospital nurses and 218 aged care nurses, in a situation where many potential contextual moderators were held relatively constant. Both fulfillment and breach were significant and predicted multiple outcomes in each context. Similar patterns of results for fulfillment and breach suggests there may simultaneously be two forms of discrepancy mechanism underpinning the impacts of the psychological contract: assessment of continuous discrepancy (fulfillment) and assessment of discontinuous discrepancy (breach). Negative affectivity appears to have prevented relationships, particularly between breach and stress, and should be included in future psychological contract research. The consistent relationships of fulfillment and breach with organizational and occupational commitment highlights the importance of career management. The main differences by context were the negative effects of breach and the lack of an effect for promises for aged care nurses, possibly due to prestige and other differences to be investigated in future research.
Mapping Corporate Social Responsibility in Family Firms: A Bibliometric Review across Countries
Authors: Citterio Alberto , Locatelli Rossella , Uselli Andrea
Published: January 2024

The field of CSR has witnessed considerable growth and established itself as a significant subject in family business studies. However, despite previous reviews exploring this topic from various angles, there remains a crucial gap in understanding the influence of diverse regulatory frameworks and social, environmental, and managerial values on the development of literature production and research streams across different regions. This gap holds particular significance for comprehending the latest advancements in this dynamic research field, particularly in emerging economies, where cultural and regulatory environments play a substantial role in shaping the attitude of family firms toward CSR. To bridge this gap, this paper conducts a comprehensive review of empirical studies focusing on sustainability in family firms. These studies are organized based on the country of study, and our review, based on a conjunct database derived from the Scopus and World of Science, encompasses 308 articles published between 1996 and 2023. Utilizing bibliometric software and adhering strictly to our inclusion criteria, we systematically grouped these articles into three distinct clusters: North American studies, European studies, and Asian studies. We found significant differences among areas regarding the main objectives, methodologies, and results of the research. This study comprehensively maps key themes and findings in family business sustainability, aiding researchers in organizing knowledge and guiding future investigations. Recognizing regional influences is crucial to ensuring representative and applicable research outcomes.
The Impact of Using Different Types of Compost on the Growth and Yield of Corn
Authors: Zapałowska Anita , Jarecki Wacław
Published: January 2024

The cultivation of corn holds immense importance as a foundational global grain crop, catering to human sustenance and serving as vital animal feed. Moreover, corn plays a substantial role in biofuel production. Additionally, cultivating corn can have a positive effect on crop rotation by improving soil quality and reducing erosion. In a pot trial using six distinct compost variations derived from different organic wastes as fertilizers for GS210 corn, specific indices, such as Fv/Fm (0.80, 0.80, 0.81), Fv/F0 (4.07, 3.99, 4.03), PI (4.62, 4.22, 5.21), and RC/ABS (1.71, 1.68, 2.01), exhibited the highest values. Interestingly, mineral fertilization with NPK displayed significant benefits on various growth parameters like plant height (188.9 cm), cob length (17.50 cm), grains per cob (324.0), and thousand-grain weight (MTZ) (285.2). The difference in the cob grain count between NPK mineral fertilization and the control reached 168.5 grains, which was statistically confirmed. Furthermore, the grain’s protein content notably increased with mineral fertilization (9.5) compared to the control (8.5). While organic fertilizers showed lower outcomes (9.1–9.3) than NPK mineral fertilization, they generally outperformed the control (8.5). This prompts the need for future studies to assess the effectiveness of individual organic fertilizers in combination with mineral nitrogen fertilization.
Model-Driven Bayesian Network Learning for Factory-Level Fault Diagnostics and Resilience
Authors: Ademujimi Toyosi , Prabhu Vittaldas
Published: January 2024

We propose to use engineering models for Bayesian Network (BN) learning for fault diagnostics at the factory-level using key performance indicators (KPIs) such as overall equipment effectiveness (OEE). OEE is widely used in industry and it measures sustainability by capturing product quality (e.g., less scrap) and measures resilience by capturing availability. A major advantage of the proposed approach is that the engineering models are likely to be available long before the corresponding digitalized smart factory becomes fully operational. Specifically, for BN structure learning, we propose to use analytical queueing theory models of the factory to elicit the structure, and to carry out intervention we propose to use designed experiments based on discrete-event simulation models of the factory. For parameter learning, we apply a qualitative maximum a posteriori (QMAP) method and propose additional expert constraints based on the law of propagation of uncertainty from queueing theory. Furthermore, the proposed approach overcomes the challenge of obtaining balanced-class data in BN learning for fault diagnostics. We apply the proposed BN learning approach to (i) a 4-robot cell in our laboratory and (ii) a robotic machining cell in a commercial vehicle factory. In both cases, the proposed method is found to be efficacious in accurately learning the BN structure and parameter, as measured using structural-hamming distance and Kullback–Leibler divergence score, respectively. The proposed approach can pave the way for a new class of resilient and sustainable smart manufacturing systems.
Sustainable Urban Mobility Planning in the Port Areas: A Case Study
Authors: Maslaric Marinko , Bojic Sanja , Mircetic Dejan , Nikolicic Svetlana , Medenica Todorovic Ranka
Published: January 2024

Sustainable development, urban planning, mobility, and transport planning, integrated within the context of sustainable urban mobility, have been central themes in both scientific and applied spheres over the past few decades. In port cities, it becomes particularly essential to tackle sustainability issues given the pollution and noise emanating from ships and other port-related activities. To meet mobility and transportation sustainability needs in the port area, a port should implement measures aligned with a sustainable urban mobility planning (SUMP) approach. However, many ports have thus far achieved limited results in this direction due to the absence of an approach to defining sustainable mobility solutions based on the SUMP approach for an urban area associated with the given port. The overall aim of this paper is to support the development of territorial SUMP for port areas by proposing a methodology that identifies and prioritizes sustainable mobility solutions tailored to a specific port area. The proposed methodology is applied in the Port of Bar (Montenegro) through an appropriate case study. In this case study, the methodological steps are systematically followed, resulting in the practical implementation of the selected mobility solution: the use of a hybrid bus for internal employee transportation within the port area. The undertaken case study underscores the simplicity, practical applicability, and adaptability of the proposed methodology.
Machine Learning Insights on Driving Behaviour Dynamics among Germany, Belgium, and UK Drivers
Authors: Roussou Stella , Garefalakis Thodoris , Michelaraki Eva , Brijs Tom , Yannis George
Published: January 2024

The i-DREAMS project has a core objective: to establish a comprehensive framework that defines, develops, and validates a context-aware ‘Safety Tolerance Zone’ (STZ). This zone is crucial for maintaining drivers within safe operational boundaries. The primary focus of this research is to conduct a detailed comparison between two machine learning approaches: long short-term memory networks and shallow neural networks. The goal is to evaluate the safety levels of participants as they engage in natural driving experiences within the i-DREAMS on-road field trials. To accomplish this objective, the study gathered a series of trips from a sample group consisting of 30 German drivers, 43 Belgian drivers, and 26 drivers from the United Kingdom. These trips were then input into the aforementioned machine learning methods to reveal the factors contributing to unsafe driving behaviour across various experiment stages. The results obtained highlight the significant positive impact of i-DREAMS’ real-time interventions and post-trip assessments on enhancing driving behaviour. Furthermore, it is worth noting that neural networks demonstrated superior performance compared to other algorithms considered within this research context.
Effect of Interlayer Composition on the Properties of Laser-Directed-Energy-Deposition-Based Additively Manufactured Copper-Stainless Steel Wall Structures
Authors: Yadav Sunil , Paul C. P. , Rai A. K. , Jinoop A. N. , Dixit S. K.
Published: January 2024

Laser-directed energy deposition (LDED) is one of the advanced techniques used for the sustainable manufacturing of engineering components with minimal material wastage and higher performance. This paper reports an investigation on LDED-based additive manufacturing of compositionally graded Copper (Cu)-stainless steel (SS) wall structures for improved performance of tooling components. Three different approaches, such as Cu-SS direct joint, 20% graded Cu-SS, and 50% graded Cu-SS, are used to build the wall structures. Optical microscopy of LDED-built graded samples reveals defect-free deposition of Cu-SS direct joint and 50% graded Cu-SS wall structures at identified process parameters, whereas the 20%-graded wall yields micro-cracks in the lower Cu region. The elemental distribution shows gradual traditions in the weight percentages of Cu and Fe along the built wall. Furthermore, the ultimate tensile strengths of the direct Cu-SS joint wall structure and the 50%-graded Cu-SS wall structure are higher than the strength of LDED-deposited Cu, while the 20%-graded Cu-SS wall structure has lower ultimate tensile strength than the strength of LDED-deposited Cu. Lower ultimate strength and failure in the lower-Cu zone of 20% graded Cu-SS wall structure can be attributed to the presence of micro-cracks in the Cu20SS80 zone of 20%-graded Cu-SS wall structures. The study establishes LDED as a technique for building multi-material components promoting sustainability in terms of manufacturing and component performance.
Suggestions and Solutions for Enhancing Active Commuting to the University of Maribor and Advancing CO2 Emission Reduction
Authors: Mesarec Beno , Trček Branka
Published: January 2024

This study investigated commuting behavior at four technical faculties (BCTF) in Maribor. The main aim was to provide suggestions and solutions for challenges related to active commuting to the BCTF, while promoting advancements in CO2 emission reduction. The research methodology was based on analyses of a questionnaire survey and calculations of CO2 emissions. The results indicate that implementing measures to promote walking, bicycling and the use of city and regional public transport, in conjunction with supportive housing and parking policies, has the potential to eliminate car trips within 0–1 km of the BCTF and reduce car trips from other zones in favor of active commuting by 30% to 50%. These proposed transport scenarios could lead to an annual reduction in CO2 emissions ranging from 17% to 29%. The greatest potential for CO2 savings is observed within 0–5 km of the BCTF, where a shift to walking and bicycling could reduce emissions by up to 44%. The results also highlighted a notable disparity, indicating that students with term-time accommodations emitted 3.5 times and 4.1 times less annual CO2 within 0–5 km of the BCTF compared to students and staff commuting daily from their permanent residences in the city.
Sustainable Development of Urban Mobility through Active Travel and Public Transport
Authors: Lättman Katrin , Otsuka Noriko
Published: January 2024

A sustainable development of urban transportation relies on our ability to offer citizens reliant and attractive alternatives to car travel, such as efficient and appealing public transport (PT) services, alongside an urban environment that is stimulating for active travel alternatives, such as walking and cycling [...]
Viruses of Apple Are Seedborne but Likely Not Vertically Transmitted
Authors: Wunsch Anna , Hoff Bailey , Sazo Mario Miranda , van Zoeren Janet , Lamour Kurt H. , Hurtado-Gonzales Oscar P. , Fuchs Marc
Published: January 2024

Many viruses occur in apple (Malus domestica (Borkh.)), but no information is available on their seed transmissibility. Here, we report that six viruses infecting apple trees, namely, apple chlorotic leaf spot virus (ACLSV), apple green crinkle-associated virus (AGCaV), apple rubbery wood virus 2 (ARWV2), apple stem grooving virus (ASGV), apple stem pitting virus (ASPV), and citrus concave gum-associated virus (CCGaV) occur in seeds extracted from apple fruits produced by infected maternal trees. Reverse transcription polymerase chain reaction (RT-PCR) and quantitative RT-PCR (RT-qPCR) assays revealed the presence of these six viruses in untreated apple seeds with incidence rates ranging from 20% to 96%. Furthermore, ASPV was detected by RT-PCR in the flesh and peel of fruits produced by infected maternal trees, as well as from seeds extracted from apple fruits sold for fresh consumption. Finally, a large-scale seedling grow-out experiment failed to detect ACLSV, ASGV, or ASPV in over 1000 progeny derived from sodium hypochlorite surface sterilized seeds extracted from fruits produced by infected maternal trees, suggesting no detectable transmission via embryonic tissue. This is the first report on the seedborne nature of apple-infecting viruses.
MicroRNA750-3p Targets Processing of Precursor 7 to Suppress Rice Black-Streaked Dwarf Virus Propagation in Vector Laodelphax striatellus
Authors: Wang Haitao , Dong Yan , Xu Qiufang , Wang Man , Li Shuo , Ji Yinghua
Published: January 2024

MicroRNAs (miRNAs) are non-coding RNAs, which, as members of the RNA interference pathway, play a pivotal role in antiviral infection. Almost 80% of plant viruses are transmitted by insect vectors; however, little is known about the interaction of the miRNAs of insect vectors with plant viruses. Here, we took rice black-streaked dwarf virus (RBSDV), a devastating virus to rice production in eastern Asia, and the small brown planthopper, (SBPH, Laodelphax striatellus) as a model to investigate the role of microRNA750-3p (miR750-3p) in regulating viral transmission. Our results showed that Ls-miR750-3p was downregulated in RBSDV-infected SBPH and predominately expressed in the midgut of SBPH. Injection with miR750-3p agomir significantly reduced viral accumulation, and the injection with the miR750-3p inhibitor, antagomir-750-3p, dramatically promoted the viral accumulation in SBPH, as detected using RT-qPCR and Western blotting. The processing of precursor 7 (POP7), a subunit of RNase P and RNase MRP, was screened, identified, and verified using a dual luciferase reporter assay as one target of miR750-3p. Knockdown of POP7 notably increased RBSDV viral propagation in SBPH and then increased the viral transmission rate by SBPH. Taken together, our data indicate that miR750-3p targets POP7 to suppress RBSDV infection in its insect vector. These results enriched the role of POP7 in modulating virus infection in host insects and shared new insight into the function of miRNAs in plant virus and insect vector interaction.
Grout Ground Leakage Caused by the Development of Separation Layer in a Case Study of Muduchaideng Coal Mine
Authors: Xie Baolei , Meng Xiangdong , Sui Wanghua , Hang Yuan , Yuan Shichong
Published: January 2024

A lot of grout ground leakage occurred during Muduchaideng coal mine separation layer grout work, resulting in serious pollution. To find the mechanism of grout leakage, this paper carried out indoor experiments and on-site measurements. Through the indoor scale model test, the deformation of overburden stratum was captured, which reflected that the horizontal shear band developed at the depths of 289.67–322.48 m, 386.42–431.18 m, and 474.95–524.07 m. Then, these positions were verified through on-site drilling. It was found that the mud slurry consumption increased, the water level dropped, and the borehole wall was seriously deformed in these disturbed positions. Therefore, the reason for this grout leakage was that the overlying separation layer continued to develop upwards, and the borehole was destroyed in the location where the separation layer developed. Then, the grout pipeline was destroyed, and some grout flew towards the ground surface along the pipeline and the borehole wall. This article reveals a kind of grout ground leakage phenomenon in a case study of Muduchaideng coal mine, which can provide a warning for engineering projects.
Telemedicina durante la pandemia del COVID-19 en una ciudad altoandina: Estudio en línea a pacientes
Authors: Padilla-Cáceres Tania Carola , Mamani-Cori Vilma , Caballero-Apaza Luz Marina , Cervantes-Alagón Sheyla Lenna , Acero-Condori Lizbeth , Sucari Wilson
Published: January 2024

Con la llegada de la pandemia del COVID-19, el gobierno peruano realizó modificaciones en el sistema de salud, dando paso al decreto legislativo N° 117-2020, para el servicio de telemedicina dentro del sector de la salud pública y privada, entendiéndose como la comunicación entre el paciente y el profesional médico a través de un dispositivo como computadora o teléfono. Objetivo. Identificar los niveles de satisfacción en la atención del servicio por telemedicina de los pacientes de una clínica privada de especialidades médicas en la ciudad de Puno durante la pandemia por COVID-19. Materiales y métodos. El diseño del estudio fue observacional, prospectivo; previo consentimiento informado, se aplicó el cuestionario The Patient Satisfaction Questionnaire Short Form [PSQ-18] de manera virtual a 56 pacientes mayores de 18 años seleccionados de manera no probabilística durante la pandemia mediante la telemedicina en una clínica de Puno durante el 2020 y 2021. Resultados. El 55,4% de los pacientes se mostraron parcialmente satisfechos y el 39,3% indicaron estar satisfechos; encontrándose asociación estadística significativa entre la satisfacción de la atención de salud mediante telemedicina con la edad del paciente (p<0,01*); las dimensiones del cuestionario mostraron medias ligeramente altas, destacando las dimensiones Accesibilidad y comodidad (12,93±3,13); Calidad técnica (12,34±3,56); Trato interpersonal (6,45±1,32); aspectos financieros (6,32±1,52) y satisfacción general (6,11±1,88). Conclusiones. Las dimensiones referidas a la calidad técnica, comodidad y accesibilidad fueron reportadas con mayores niveles de satisfacción, estos hallazgos contribuyen a la evidencia sobre la aceptación de la telemedicina como una alternativa viable para brindar atención de calidad.
Contenido de arsénico, conocimiento y actitud en el consumo del agua de pozo familiar
Authors: Málaga Apaza Julio
Published: January 2024

La contaminación por arsénico del agua de consumo humano, es un problema de salud pública, porque produce diversas enfermedades cancerígenas y de piel. Objetivo. Determinar niveles de arsénico en el agua de pozos, y evaluar el grado de conocimiento y actitud sobre el consumo del agua familiar. Materiales y métodos. Se utilizaron 96 muestras del agua de pozos del distrito de Juliaca. Las cuales se analizaron en laboratorio de Unidad de Servicios de Análisis Químicos de la Facultad de Química - Universidad Nacional Mayor de San Marcos-Lima, mediante la técnica Espectrofotometría de Absorción Atómica con Horno de Grafito. Los datos de arsénico fueron procesados estadísticamente mediante el diseño completamente al azar. Asimismo, la descripción del conocimiento y actitud del consumo de agua familiar se realizó aplicando la técnica de la encuesta y el instrumento fue un cuestionario de 11 ítems para la variable conocimiento y 7 para la variable actitud, con respuestas de alto, medio y bajo para conocimiento y buena, regular y mala calificadas con escala de Likert. Resultados. La concentración promedio fue 0.031 mg de As/L de agua y entre zonas hubo semejanza (p>0.05). En el grado de conocimiento sobre contaminación con arsénico en el agua de consumo humano respondieron el 40.81 % con calificación alta y el 59.19% están entre medio y bajo; en actitud, la calificación buena obtuvo menos del 50 % de encuestados y el resto están entre regular y mala. Conclusiones. El contenido arsenical en el agua de pozos supera los límites máximos permisibles según Organización Mundial de Salud y más del 50% se exponen al agua contaminada.
Presupuesto público en salud y sus efectos en la desnutrición crónica infantil. El caso peruano
Authors: Paucar Jurado Juan Cirilo
Published: January 2024

En la actualidad, aunque las tasas de malnutrición que afectan a los pueblos indígenas y a las zonas de bajos ingresos han disminuido en un 33,8%, América Latina sigue registrando niveles alarmantes de malnutrición, especialmente a nivel infantil. En el caso de Perú en particular, urge estudiar el impacto del presupuesto sanitario en la dinámica de la desnutrición infantil. Objetivo. Analizar la incidencia del presupuesto de salud pública en la reducción de la desnutrición infantil en Perú durante las dos últimas décadas. Metodología. Revisión narrativa acerca del impacto de los presupuestos de salud pública en la desnutrición. Dentro de busqueda se consideraron bases de datos como Scopus, Web of Science, Scielo, Redalyc, Latindex y Google Scholar desde el 2019 a 2023. Considerando con ecuación health budget" OR "chronic child malnutrition", "government spending" con la función booleana AND como parámetros de búsqueda para el campo "topic" para encontrar documentos que también trataran sobre "malnutrition" OR "chronic child malnutrition" OR "child malnutrition". Resultados. Se identificaron 57 fuente, se excluyeron 4 artículos por duplicidad y 37 por falta de información, dando como resultando un total de 16 artículos a considerar en este análisis. Conclusión. Se puede concluir que existe una relación significativa entre el aumento del presupuesto público en salud y la disminución de la desnutrición infantil a nivel nacional. La literatura existente destaca que a medida que se incrementa la asignación presupuestaria en el ámbito de la salud, se observa una reducción correspondiente en las tasas de desnutrición.
Valoración inicial de enfermería en emergencias psiquiátricas: revisión sistemátic
Authors: Arone Mallqui Pánfilo
Published: January 2024

Un porcentaje significativo de las emergencias hospitalarias son psiquiátricas; por lo que, durante la práctica clínica diaria, el personal de enfermería debe atender a pacientes con síntomas mentales y signos conductuales. Para tomar decisiones que permitan afrontar dichas urgencias, el profesional de enfermería requiere realizar una adecuada valoración para establecer las necesidades reales del paciente. Objetivo. Identificar los instrumentos utilizados por el servicio de enfermería para una valoración inicial efectiva en emergencias psiquiátricas. Metodología. Se realizó una revisión sistemática cuya búsqueda se realizó en las bases de datos Scopus y PubMed. La ecuación empleada fue la base de datos Scopus se utilizaron (mental AND health AND diagnosis AND psychiatric AND emergency) OR (instruments AND diagnosis AND psychiatric AND emergencies); en PubMed se usaron (initial AND assessment AND psychiatric AND patients AND emergency AND diagnosis), a partir de metodo de busqyeda empleado se obtuvo un total de 802 fuentes que pasaron por un proceso de selección quedando para el análisis de 22 publicaciones. Conclusión. Las entrevistas y cuestionarios se erigen como una herramienta indispensable. Permiten establecer un vínculo directo con el paciente, identificar sus preocupaciones, síntomas y necesidades específicas, garantizando así su bienestar físico y emocional desde el inicio de la atención. El uso de las escalas de medición varía de acuerdo a la enfermedad del paciente, el sistema de clasificación más utilizada es la CIE-10 y que los registros clínicos sobre antecedentes familiares y de sustancias, además de los aspectos sociodemográficos, son los más usados y permiten visualizar el perfil general del paciente de emergencias psiquiátricas.
Pembuatan Alat Monitoring Daya Pada Baterai Panel Surya 50 Wp Berbasis Internet Of Things
Authors: Malik Fajar , Mursid Sri  Paryanto , Utami Sri
Published: January 2024

PLTS merupakan salah satu jenis pembangkit yang dapat dimanfaatkanpotensinya di Indonesia. PLTS dapat menghasilkan energi alternatif denganmemanfaatkan cahaya matahari. Energi yang diterima dari panel surya tersimpanpada baterai dan energi yang akan disalurkan dari baterai membutuhkanpemantauan agar kondisi dari baterai dapat terjaga dengan baik. Pemantauan padabeterai juga diperlukan untuk mengetahui nilai parameter seperti tegangan dan arusyang masuk agar tidak terjadi overcharge. Penelitian ini bertujuan untuk membuatalat monitoring daya baterai berbasis IoT agar dapat mempermudah memantaukondisi baterai dengan automatic system. Sensor yang digunakan dalam penelitianini adalah sensor INA 219 dengan mikrokontroler ESP 8266. Hasil pengujian datakalibrasi tegangan dan arus sensor INA 219 memiliki nilai dengan rata-rata errortegangan 0,43% hasil persamaan 𝑦 = 0,09987x − 0.0065. Untuk nilai error arusrata-rata 5,67% hasil persamaan 𝑦 = 1,0101x + 24.95. Hasil pengujian relayterhadap beban diinisiasi terhadap nilai State of Charge. Untuk relay terhadapbeban memiliki jangkauan nilai SoC sebesar 31% dengan kondisi di bawah 31%relay akan open, saat SoC di atas 31% relay akan dalam kondisi close. Relayterhadap baterai diinisiasi saat SoC bernilai 90% dengan nilai SoC diatas 90% relaybaterai akan terputus (open). Hasil data penelitian melalui web server thinger.iomemiliki kenaikan baterai sebesar 69% dengan kondisi awal persentase bateraisebesar 27% dan kondisi akhir sebesar 95% rata-rata arus sebesar 565 mA yangdilakukan selama total 8 jam pengujian, parameter dalam monitoring baterai dapatditampilkan melalui web server berupa arus, tegangan, dan State of Charge baterai.Fungsi utama alat ini dengan sistem Internet of Things mampu memantau kondisibaterai yang dapat diakses kapanpun.
Suggestions to Improve Treatment·Rehabilitation Systems for Drug Abusers in Korea
Authors:   The Correction Welfare Society of Korea, Koh Yun-Soon
Published: January 2024

Drug-related problems have become very serious social problems in Korea which used to boast as drug-free society. Korean government proclaimed ‘War on Drugs’ and has fortified supply-prevention strategies. However, for ‘War on Drugs’ we should intervene not only on supply side but also on treatment·rehabilitation(TR) for drug abusers. Currently the infrastructure for TR for drug abuse is very poor in Korea. This study analyzed the TR system in Korea and made suggestions for improvement. Specific contents of this paper are as follows. First, the nature of the problems in Korea was analyzed. They are availability of diverse drugs, sharp increase of abusers and young users, and high relapse rate, etc. Second, the ineffective court-ordered treatment policy was analyzed. It was recommended that treatment facilities should be improved and the collaboration system between legal system and treatment system should be developed. Third, the TR systems in public sector such as hospitals, Addiction Rehabilitation Centers(ARCs), Addiction Management Integrative Support Centers(AMISC) were analyzed. Public support to hospital treatment expense, nation-wide expansion of ARCs, and the development of referral system using AMISC were suggested. Fourth, the private sector systems such as DARC, Sonasa, NA were analyzed. It was suggested that government should financially support DARC and Sonasa. Also, it was recommended that NA meetings should be set up across the country. Finally, it was suggested that government should strengthen NIMS, drug-testing kits, prevention education, and develop the control tower to effectively deal with drug addiction issues.
Prediction of Tropospheric Ducting for UHF Signals In Plateau State Using Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
Authors: Moses Bako , O.U Okereke , J.D Jiya
Published: January 2024

A study on the occurrence of tropospheric ducting for UHF signal in Plateau State using ANFIS had been investigated using the variation of the meteorological data; temperature, pressure, and relative humidity collected from NIMET for Jos, Plateau State Nigeria. The refractivity gradient was calculated using MATLAB as computational software. The conditions of occurrence of path clearance and tropospheric ducting were utilized to checkmate the occurrence of ducting over the period. The data gotten is used to train an ANFIS model, taking 70% of the data for model training, 20% for testing and 10% for validation. The integrity of the ANFIS model was tested using root mean square error (RMSE) and maximum absolute percentage error (MAPE) which confirmed that the model is accurate to 99% considered fit for forecasting. The developed model was able to mimic the tropospheric ducting trend up to a period of 7 years (2019- 2025) after successful simulation with an assertion that the rainy months are more prevailed to chances of tropospheric ducting occurrence as higher humidity prevails during this time which has more significance on refractivity gradient. An investigation was carried out on the effect of variation of tropospheric parameters; temperature, pressure and humidity on refractivity gradient using linear regression and Spearman correlation to ascertained the degree of dependence of each parameter and the result showed that refractivity gradient is strongly influenced by relative humidity with a correlation coefficient of -0.9772 as against temperature and pressure having correlation coefficients of -0.2587 and 0.2866 respectively.
A NEED ANALYSIS FOR THE TRAINING CURRICULUM MODEL
Authors: Md Ghazali Nor Hasnida , Abdullah Norazilawati , Md Zabit Mohd Nazir , Shuib Tajul Rosli , Hamzah Mahizer
Published: January 2024

Work-based learning is a learning process carried out in most of a real work environment. It requires students to have the ability to apply those skills in their work environment. Developing a training curriculum model for a course is normally preceded by a need analysis. So, there is a need to do needs analysis. The aim of this study is to determine the generic skills and values required to fulfil the need of the community and the needs for the development of a training curriculum model which is trained based on the work-based learning approach. The study is using a quantitative approach which uses survey method. The samples involved are 43 trainers which are chosen through purposive sampling. Questionnaires are distributed to all the samples. Questionnaires are developed by the researcher. Data is analysed using the Statistical Package for Social Science (SPSS) version 25.0 for frequency, percentage, mean and standard deviation. The overall findings of the study show that there is no educational training either scheduled or application in the course, and there are no direct resources which focuses on generic skills and values elements. They also agree to be trained with all the seven generic skills and five values skills before they join the industry. The implication of the study is that all the elements such as the generic skills and values should be included in the training curriculum module. In conclusion, they need few generic skills and values which contributes to a training curriculum model that can facilitate a better teaching and learning process. Further researchers proposed are to gain data from various educational sector like community colleges and to go for in-depth research such as qualitative approach.
EXPRESSIVE ART THERAPY APPROACH IN REDUCING SELF-HARM AMONG ADOLESCENT
Authors: Zakaria Wan Puteri Nurul Izzah , Ahmad Noorlila
Published: January 2024

Adolescent self-harming behavior is a complex and concerning issue which require a comprehensive and holistic understanding. Expressive art therapy serves as a therapeutic approach to address self-harm among adolescents in which they can express and explore their emotions, thoughts, and experiences in a non-verbal manner by utilizing various art forms. This research aims to explore in-depth self-harming behaviour among adolescents and the implementation of expressive art therapy approach to reduce self-harming behaviour among adolescent. This research employed an action research approach whereby the entire cycle process starting from planning stage to the reflecting stage were completed using one sample as participant engaged in expressive art therapy. Referral volunteered adolescents participated after claiming to involve in self-harm activities. The action research cycle involved nine sessions in a six weeks period. The results found that the adolescents developed self-resilience and could regulate through a suitable personal coping skill thus reducing self-harm behavior. The results also showed that expressive art therapy approach is effective in helping adolescents from relapsing into self-harm behavior. Moreover, the creative process in expressive art therapy approach provided a safe and supportive environment for the adolescents to externalize their distress and develop alternative coping mechanisms.
THE IMPACT OF FLIPPED CLASSROOM ON EFL STUDENTS’ GRAMMATICAL COMPETENCE AND ATTITUDE IN CHINA
Authors: Liao Juan , Yasak Zurina
Published: January 2024

This study aims to examine how flipped an English Grammar classroom would affect students’ English grammatical competence and attitude. The study was conducted for 6 weeks in two Business English classes of a vocational college in China. There are 50 students in the flipped classroom and 52 students in the traditional classroom. Achievement tests and a survey on learners’ attitudes of the model were used for collecting data. It was revealed the flipped classroom model exerted moderate impact on learners’ academic achievements compared to the traditional teaching methodology. Besides, students mostly had positive attitude towards applying the flipped classroom model in instructing English grammar.
THE IMPORTANCE OF SELF-EMOTIONAL COMPETENCY MODEL FOR MIDDLE SCHOOL LEADERS IN THE ERA OF SOCIETY 5.0: A PILOT STUDY
Authors: Samad Norliza , Mohd Noor Mohd Asri , Mansor Mahaliza
Published: January 2024

The self-emotional competency model can be used as a measurement tool to increase the emotional qualities of school leadership in facing the change in the education era of Society 5.0. However, validation of the self-emotional competency model using exploratory factor analysis (EFA) is still scarce. Therefore, this pilot study is conducted to identify the applicability of the emotional competency model of middle leaders in primary schools through exploratory factor analysis (EFA). This study employed a quantitative approach using a survey method. A questionnaire was used as a research instrument. The instrument contained 18 items. A total of 179 respondents participated in this pilot study. The validity and reliability of the instrument were obtained through descriptive analysis of Cronbach's Alpha reliability and exploratory factor analysis (EFA) using SPSS version 27 software. The overall analysis shows that 13 items meet the EFA fit requirements with Kaiser-Meyer-Olkin (KMO) values of more than 0.6. Bartlett's test values were significant, with item communalities values exceeding 0.3 and Eigen values exceeding 1.0 at a percentages of variance exceeding 60 percent. The Cronbach's Alpha coefficient was above 0.70 for all items. A total of five items were removed. The findings of the study show that the instrument of self-emotional competency instrument has very high validity and reliability and has the potential to be used as a guide in the development of self-emotional competence of middle leaders in Malaysia. A positive impact is essential in generating emotionally intelligent leaders who are competitive and capable to lead the school community towards the era of Society 5.0 especially in primary school in Malaysia.