bluuebunny/crossref_metadata_2025 huggingface dataset:
Inverse Problem Numerical Analysis of Forager Bee Losses in Spatial Environment without Contamination
Authors: Atanasov Atanas Z. , Koleva Miglena N. , Vulkov Lubin G.
Published: November 2023

We consider an inverse problem of recovering the mortality rate in the honey bee difference equation model, that tracks a forage honeybee leaving and entering the hive each day. We concentrate our analysis to the model without pesticide contamination in the symmetric spatial environment. Thus, the mathematical problem is formulated as a symmetric inverse problem for reaction coefficient at final time constraint. We use the overspecified information to transform the inverse coefficient problem to the forward problem with non-local terms in the differential operator and the initial condition. First, we apply semidiscretization in space to the new nonsymmetric differential operator. Then, the resulting non-local nonsymmetric system of ordinary differential equations (ODEs) is discretized by three iterative numerical schemes using different time stepping. Results of numerical experiments which compare the efficiency of the numerical schemes are discussed. Results from numerical tests with synthetic and real data are presented and discussed, as well.
Cell Intrinsic Determinants of Alpha Herpesvirus Latency and Pathogenesis in the Nervous System
Authors: Salazar Stephanie , Luong Khanh T. Y. , Koyuncu Orkide O.
Published: November 2023

Alpha herpesvirus infections (α-HVs) are widespread, affecting more than 70% of the adult human population. Typically, the infections start in the mucosal epithelia, from which the viral particles invade the axons of the peripheral nervous system. In the nuclei of the peripheral ganglia, α-HVs establish a lifelong latency and eventually undergo multiple reactivation cycles. Upon reactivation, viral progeny can move into the nerves, back out toward the periphery where they entered the organism, or they can move toward the central nervous system (CNS). This latency–reactivation cycle is remarkably well controlled by the intricate actions of the intrinsic and innate immune responses of the host, and finely counteracted by the viral proteins in an effort to co-exist in the population. If this yin-yang- or Nash-equilibrium-like balance state is broken due to immune suppression or genetic mutations in the host response factors particularly in the CNS, or the presence of other pathogenic stimuli, α-HV reactivations might lead to life-threatening pathologies. In this review, we will summarize the molecular virus–host interactions starting from mucosal epithelia infections leading to the establishment of latency in the PNS and to possible CNS invasion by α-HVs, highlighting the pathologies associated with uncontrolled virus replication in the NS.
COVID-19 Pharmacotherapy: A Summary of Key Advances and Insights from the Special Issue
Authors: Schinas Georgios , Akinosoglou Karolina
Published: November 2023

The COVID-19 pandemic has presented unprecedented challenges for healthcare systems worldwide [...]
An Avirulent Largemouth Bass Birnavirus Vaccine Candidate Protects Largemouth Bass against Birnavirus Infection
Authors: Fu Xiaozhe , Luo Mingju , Lin Qiang , Liang Hongru , Niu Yinjie , Luo Xia , Ma Baofu , Li Ningqiu
Published: November 2023

Background: Largemouth bass birnavirus (LBBV) disease outbreaks in largemouth bass fingerlings lead to high mortality in China. Therefore, the development of immersion immunization strategies is paramount. Methods: An avirulent LBBV strain was screened using a fish challenge assay. The proliferation dynamics of the avirulent strain were determined in vitro and in vivo. The efficacy of the avirulent vaccine was evaluated using immune gene expression, viral load, and a virus challenge, and the safety was also assessed using a reversion to virulence test. Results: An avirulent virus strain, designated as largemouth bass birnavirus Guangdong Sanshui (LBBV-GDSS-20180701), was selected from five fish birnavirus isolates. The proliferation peak titer was 109.01 TCID50/mL at 24 hpi in CPB cells and the peak viral load was 2.5 × 104 copies/mg at 4 dpi in the head kidneys and spleens of largemouth bass. The largemouth bass that were immersed within an avirulent vaccine or injected with an inactivated vaccine were protected from the virulent LBBV challenge with a relative percent survival (RPS) of 75% or 42.9%, respectively. The expression levels of IL-12, MHCI, MHCII, CD8, CD4, and IgM in the avirulent group were significantly upregulated at a partial time point compared to the inactivated vaccine group. Moreover, the viral load in the avirulent vaccine group was significantly lower than those in the inactivated vaccine group and control group using real-time PCR. Conclusions: LBBV-GDSS-20180701 is a potential live vaccine candidate against LBBV disease.
A 3D Numerical Study on the Tidal Asymmetry, Residual Circulation and Saline Intrusion in the Gironde Estuary (France)
Authors: Pham Van Bang Damien , Phan Ngoc Vinh , Guillou Sylvain , Nguyen Kim Dan
Published: November 2023

A full 3D numerical model is used for studying tidal asymmetry, estuarine circulation, and saline intrusion in the Gironde estuary. The model is calibrated and verified using the data measured during two field surveys in the Gironde estuary. Harmonic analysis of numerical results is proposed to understand how the superposition of M2, M4 and M6 components generate a complex estuarine circulation and salinity intrusion in the Gironde estuary. The numerical results show that the M6 component plays a significant role as important as the M4 one in modifying the nature of tidal asymmetry, especially in the Gironde upper estuary. In this case, the use of the phase lag between M2 and M4, neglecting M6, to predict the tidal asymmetry nature could produce errors. The effect of asymmetrical tides on saline intrusion and residual circulation is specifically discussed here.
Impact of Phytoplankton Community Structure Changes in the South Sea of Korea on Marine Ecosystems Due to Climate Change
Authors: Park Kyung-Woo , Chung Mi-Hee , Yoo Man-Ho , O Kwang-Seok , Kim Kyoung-Yeon , Park Tae-Gyu , Youn Seok-Hyun
Published: November 2023

Herein, we conducted surveys during the 2018–2022 summers to investigate the impact of climate change-related changes in the phytoplankton community structure on the marine ecosystem in the South Sea of Korea. The average surface water temperature increased by ~1.07 °C at 0.0195 °C·yr−1 between 1968 and 2022. During the summers, the rate was 0.0211 °C·yr−1, with a total increase of ~1.16 °C, indicating a stronger increase in summer surface water temperature. Over the last 30 years, nutrient levels in the South Sea have decreased, particularly at the surface. Moreover, 29.3–90.0% of the phytoplankton community structure was dominated by nanoflagellates (≤20 μm). Based on the size of the phytoplankton chl-a, the average contribution rate of picophytoplankton was the highest (60.1%). Redundancy analysis revealed negative correlations between nutrients and water depth, excluding NH4. Increased stratification due to climate change is causing reduced nutrient availability at the surface mixed layer, and the size of the phytoplankton structure is progressively reducing. These changes are expected to manifest in a complex microbial food web centered on smaller phytoplankton with low primary productivity. This can reduce the efficiency of carbon transfer to higher consumer levels, suggesting a potential decrease in marine productivity.
Habitat Quality Assessment and Driving Factor Analysis of Xiangyu in Feng River Basin Based on InVEST Model
Authors: Huo Aidi , Liu Qi , Zhao Zhixin , Elbeltagi Ahmed , Abuarab Mohamed EL-Sayed , Ganjidoust Hossein
Published: November 2023

Analyzing the evolution of regional habitat quality is an important means to assess the impact of engineering activities on ecosystems. Taking Xiangyu in the Feng River Basin as the study area, the land use change in 1985 and 2022 was analyzed, and the habitat quality and degradation degree were evaluated by using the Integrated Assessment and Tradeoff of Ecosystem Services (InVEST) model. The results showed that from 1985 to 2022, the transfer of land use types in Xiangyu mainly occurred on dry land, bare land, forest land, and industrial land. The area of dry land and bare land converted into industrial land is 10,825.15 m2 and 249,123.09 m2, respectively, and affected by the measures of returning farmland to forest and grassland in Shaanxi Province, the area transferred to forest land reached 371,471.87 m2, mainly from dry land and bare land. The continuous expansion of industrial land led to a significant decline in habitat quality, and the areas with high habitat degradation were concentrated in forest land in a large range, which indicated that forest land was vulnerable to industrial land expansion. Land use change and human engineering activities are the main factors affecting the ecological environment, and limiting the expansion rate of industrial land is the key to protecting the ecological environment.
Stormwater Treatment Using Natural and Engineered Options in an Urban Growth Area: A Case Study in the West of Melbourne
Authors: Sanciolo Peter , Sharma Ashok K. , Navaratna Dimuth , Muthukumaran Shobha
Published: November 2023

The expected increase in urbanization and population in coming years is going to increase the impervious land area, leading to substantial increases in stormwater runoff and hydrological challenges, and presents significant challenges for urban potable water supply. These are worldwide challenges that can potentially be ameliorated by harvesting stormwater for potable use or for other uses that can reduce the pressure on potable water supply. This study sought to assist the local water authority in planning for future potable water supply through a review of the scientific literature to determine the likely chemical and microbial characteristics of stormwater, the treatment train (TT) requirements, and the likely costs of treatment to achieve potable standards for the high-growth metropolitan region of Melbourne, Australia. Literature stormwater quality statistical data and treatment process performance data were used to model the expected product water microbial and chemical quality after treatment using a number of advanced TT options. The results of the modelling were compared with literature microbial log reduction targets (LRTs) for the potable use of stormwater and with the Australian Drinking Water Guidelines (ADWG). It was found that a reverse osmosis (RO)-based TT with microfiltration pre-treatment and post-RO advanced oxidation and chlorination in storage reservoirs is a conservative stormwater potable use treatment option. A less conservative and less expensive ozone-and-biologically active filtration (O3/BAF)-based TT option is also proposed if RO concentrate disposal is deemed to be too challenging. These results could be useful in climate change adaptation involving the evaluation of options for the mitigation of future population-growth- and climate-change-driven water supply challenges, as well as urbanization-driven stormwater hydrology and receiving water pollution challenges.
The Lag Effect of Riverine Flow-Discharge and Sediment-Load Response to Antecedent Rainfall with Different Cumulative Durations in Red Hilly Area in China
Authors: Zhao Lixiang , Nie Xiaofei , Zheng Haijin , Liao Kaitao , Zhang Jinjuan
Published: November 2023

Rainfall is an important factor that causes riverine flow and sediment transport, and extreme rainfall has a particularly significant effect on the fluctuations of riverine flow and sediment load. Based on the daily rainfall from 1990 to 2020, in the upper watershed of the Lianjiang River, which is one of the source tributaries of China’s largest freshwater lake (Poyang Lake), the 95th percentile method and minimum event interval time were employed to identify extreme rainfall events. Mann–Kendall test was used to check for abrupt changes in annual rainfall, riverine flow discharge, and riverine sediment loads, and to identify abrupt-change years; thus, different periods were divided via the abrupt change years. Multiple linear regression was applied to explore the lag effect of riverine flow-discharge and sediment-load response to antecedent rainfall, with different cumulative durations for each period. The results of the study indicated that (1) the expansion of garden land in 1995 caused a significant and abrupt change in sediment load. (2) Extreme rainfall events had a greater impact on riverine flow and sediment load as compared to ordinary rainfall. These events were found to explain more variations in riverine flow and sediment load, which led to longer lag times for both riverine flow and sediment transport. (3) The expansion of garden land under extreme rainfall conditions resulted in longer lag times for riverine flow and sediment transport, and reduced the need for antecedent rainfall with a longer pre-event time. Therefore, the analysis of antecedent rainfall and the lag response of riverine flow discharge and sediment load can help in understanding the response mechanism of riverine flow discharge and sediment load for the current era of increasing extreme rainfall. This analysis is crucial for improving the accuracy of simulating riverine flow and sediment under extreme rainfall conditions. Ultimately, it can contribute to effective watershed management during extreme rainfall events.
Threats to the Lower Section of the River after Fish Mortality in the Ecological Environment of the Oder River
Authors: Siwek Hanna , Podlasińska Joanna
Published: November 2023

This work presents a case study accompanied by an analysis of potential reasons for fish mortality in the lower Oder River during an ecological disaster in August 2022. Changes in physicochemical water quality indicators indicate that fish and benthic organism death was likely due to the creation of hypoxia. The research also highlighted the trophic threats to the studied Oder River section linked to the disaster. The disaster occurred in the upper and middle Oder River, extending to the lower stretch. A physicochemical analysis of water samples revealed that the fish and organism death in the estuarine section was mainly due to reduced dissolved oxygen, caused by the decomposition of organic matter from the upper river sections. This was reinforced by high temperatures and low water levels. The negative trophic consequences of the described ecological disaster for the lower section of the Oder River may be long-term. Over thirty years of monitoring showed threats of excess biogenic compounds, organic matter, and bacterial contamination. Despite decreasing nitrogen and phosphorus, significant phytoplankton blooms implied internal nutrient sources. Considering climate change and the poor trophic status, recurrent disasters and deteriorating conditions are anticipated. Mitigation requires continuous monitoring, limiting the nutrient input (especially phosphorus), and preparing for extreme events. Geotechnical methods in the lower river can improve oxygen levels and fish survival.
Operational Characteristics Assessment of a Wind–Solar–Hydro Hybrid Power System with Regulating Hydropower
Authors: Li Yulong , Tong Zhoubo , Zhang Jingjing , Liu Dong , Yue Xuhui , Mahmud Md Apel
Published: November 2023

Renewable energy generation technology, as an alternative to traditional coal-fired power generation, is receiving increasing attention. However, the intermittent characteristics of wind and solar energy pose certain challenges to the stable operation of power grids. This requires a better understanding of the operational characteristics of renewable energy to improve the comprehensive efficiency. To achieve this, firstly, four indicators (i.e., average fluctuation magnitude, Richards–Baker flashiness, average climbing rate, and change in the time-averaged value) within a single-evaluation-indicator framework are proposed to quantitatively evaluate the fluctuation characteristics of wind, solar, and hydropower and a wind–solar–hydro hybrid power system. Secondly, a comprehensive evaluation indicator is developed by scientifically assigning and recombining the four indicators using entropy weight theory. Furthermore, the comprehensive evaluation index is applied to the wind–solar–hydro hybrid power system to determine the operational characteristics of subsystems and a complementary system at different time scales. Finally, the load tracking coefficient and coupling degree are used to quantify the complementarity degree of the hybrid power system. It is found that the fluctuation degree of the hybrid power system is smaller than that of the individual power system. Meanwhile, both fluctuation and complementary characteristics are strengthened with the increase in time scale. The proposed methods and results shift the volatility from an abstract concept to concrete representation, providing a new perspective and reference for evaluating the operational characteristics of the hybrid power system to achieve power system planning and scheduling.
General practice service use at the end-of-life before and during the COVID-19 pandemic: a population-based cohort study using primary care electronic health records
Authors: Chukwusa Emeka , Barclay Stephen , Gulliford Martin , Harding Richard , Higginson Irene , Verne Julia
Published: November 2023

Background

Globally, the COVID-19 pandemic has caused unprecedented strain in healthcare systems, but little is known about how it affected patients requiring palliative and end-of-life care from GPs.

Aim

To evaluate the impact of the pandemic on primary care service use in the last 3 months of life, including consultations and prescribing, and to identify associated factors.

Design and setting

A retrospective cohort study in UK, using data from the Clinical Practice Research Datalink.

Method

The study cohort included those who died between 2019 and 2020. Poisson regression models using generalised estimation equations were used to examine the association between primary care use and patient characteristics. Adjusted rate ratios (aRRs) and 95% confidence intervals (95% CIs) were estimated.

Results

A total of 44 534 patients died during the study period. The pandemic period was associated with an 8.9% increase in the rate of consultations from 966.4 to 1052.9 per 1000 person-months, and 14.3% longer telephone consultation duration (from 10.1 to 11.5 minutes), with a switch from face-to-face to telephone or video consultations. The prescription of end-of-life care medications increased by 6.3%, from 1313.7 to 1396.3 per 1000 person-months. The adjusted rate ratios for consultations (aRR = 1.08, 95% CI = 1.06 to 1.10,P<0.001) and prescriptions (aRR 1.05: 95% CI = 1.03 to 1.07,P<0.001) also increased during the pandemic.

Conclusion

The pandemic had a major impact on GP service use, leading to longer consultations, shifts from face-to-face to telephone or video consultations, and increased prescriptions. GP workload-related issues must be addressed urgently to ease the pressure on GPs.
Do território ao ciberespaço: uma busca do capital simbólico do indígena Misak
Authors: Concha Jennifer Paola Pisso , Leite Mário Cezar Silva
Published: November 2023

Neste artigo discute-se como as representações sobre o capital simbólico da comunidade indígena Misak de Guambía, Cauca, Colômbia, transcende o seu território, na cultura digital (cibercultura). Já se afirmou que esse trânsito se dá sob a perspectiva de olhares não indígenas (produtores culturais).  Nesse sentido, o trabalho tem como objetivo analisar a cultura indígena contemporânea Misak, ela mesma, quando se depara com o ciberespaço e as novas tecnologias. Os objetos de análise são textos digitais, produções audiovisuais, fotografias, blogs, mídias digitais, redes sociais, projetos comunitários indígenas desde as TICs e/ou comunicação, permitindo observar quais são os desdobramentos da elaboração do campo simbólico dos Misak, interligados em uma realidade física/virtual. A metodologia é de abordagem qualitativa, netnográfica e a construção teórico-metodológica é semiodiscursivo. Portanto, analisar os imaginários, rasgos identitários, elaborações de si e sua cultura do povo guambiano contemporâneo, no ciberambiente, pode permitir uma visão mais aproximada da percepção desses povos no âmbito da diversidade cultural.
Analisis Pengaruh Geometrik Jalan Terhadap Kecelakaan Lalu Lintas
Authors: Ellytrina Dinda Fauziah Nur , Zhafirah Athaya
Published: November 2023

The geometric design of the road must comply with the requirements. Otherwise, it will affect the increasing traffic accidents. Traffic accidents are an indicator of road safety. This study aimed to determine the location of accident-prone areas (black spots) and the relationship between geometric road conditions and traffic accidents on the Garut – Tasikmalaya road section via Cilawu. The method used in this research is polynomial linear regression analysis with variable X relationship, consisting of stopping sight distance, overtaking sight distance, bend radius, and degree of curvature. The Y variable is the EAN (Equivalent Accident Number) value. The geometric road data used in this study is primary data directly taken in the field, while traffic accident data is secondary data. The analysis results by calculating the EANc value show that bends one and bends two are the locations of accident-prone areas (black spots). Except for overtaking sight distance, the relationship between road geometry for bend radii, stopping visibility, and degree of curvature to traffic accidents are closely correlated, which means it has quite an effect on accidents. Overtaking sight distance has little effect on accidents.
La liberalizzazione del commercio nei mercati internazionali. L´importanza dell´esportazione (La liberalización del comercio en los mercados internacionales. La importancia de exportar).
Authors: D´Auria Anna , Sánchez-Rivas García Javier , Tregua Marco , Pablo-Romero Gil-Delgado María del Pópulo
Published: November 2023

El recurso se enfoca en el tema del comercio internacional y en los diferentes métodos de entrada a mercados internacionales, o sea: la exportación directa o indirecta, la inversión en sitios de producción extranjeros, la inversión comercial en el extranjero, o a través la colaboración con socios locales.

El recurso está destinado para el alumnado con el objetivo de comprender las estrategias utilizadas por parte de las empresas a la hora de elegir el método de entrada a mercados internacionales.

La liberalización del comercio internacional ha brindado a las empresas acceso a mercados adicionales más allá de sus propios mercados internos para vender y exportar sus bienes y servicios, un cambio económico que ha llevado a un crecimiento sustancial del comercio internacional. Por esto, es importante por cada empresa, comprender los métodos de entrada más adecuados.
La fissazione del prezzo per i mercati esteri. Un complesso equilibrio tra fattori interni ed esterni all impressa e le reazioni di mercato (La elección del precio en los mercados extranjeros. Un equilibrio complejo entre factores interiores y exteriores a la empresa y las reacciones del mercado).
Authors: Tregua Marco , Pablo-Romero Gil-Delgado María del Pópulo , D´Auria Anna , Sánchez-Rivas García Javier
Published: November 2023

La elección de los precios en los mercados internacionales es un asunto complejo ya que hay que tener en cuenta los gastos de la empresa, los gastos de la distribución al extranjero, la competencia y el nivel de gastos que los consumidores pueden aguantar. Además, la elección de los precios en los mercados extranjeros conlleva diferencias entre consumidores, aunque los productos sean los mismos, entonces las reacciones de los consumidores juegan un papel importante. Hoy en día la oportunidad de comparar precios es grande ya que los nuevos medios brindan informaciones de manera inmediata, entonces elegir los precios es un asunto importante y complejo.

Para que las empresas puedan gestionar el proceso de elección de los precios de manera correcta es necesario que tanto los objetivos de rentabilidad como los de accesibilidad a la compra tengan su papel en el trabajo de los administradores de la empresa y sobre todo de los expertos de marketing. Además, el control a lo largo del tiempo es otro asunto imprescindible para que la empresa pueda seguiré en un mercado.

El recurso complementa el conocimiento básico de economía y de marketing ya que describe la manera en la cual los precios pueden afectar tanto la empresa y su competencia como los consumidores, entonces los efectos se desarrollan en todo el mercado, al ser internacionales los flujos de productos y los canales de distribución, incluso más los mercados digitales.
Barriere tariffarie per l´equilibrio della bilancia commerciale. Mercati internazionali tra aperture e chiusure (Aranceles por el equilibrio de la balanza comercial. Mercados internacionales entre aperturas y clausuras).
Authors: Tregua Marco , Sánchez-Rivas García Javier , D´Auria Anna , Pablo-Romero Gil-Delgado María del Pópulo
Published: November 2023

La balanza comercial es un dato bajo el control de los gobiernos y hay varias maneras para gestionar de forma correcta la diferencia entre exportaciones e importaciones. Con el propósito de limitar la dependencia de otros mercados, un país puede elegir aranceles para ralentizar el flujo de importaciones, pero esta intervención es posible siempre que la Organización Mundial del Comercio lo permita y si los consumidores en un país pueden encontrar formas alternativas de satisfacer sus necesidades.

El recurso está destinado para el alumnado con el objetivo de comprender el papel de los aranceles en el control de la balanza comercial y las características más importantes de los aranceles, como sus tipologías, valores y finalidades. El enfoque en los principios de la Organización Mundial del Comercio permite entender cómo se gestionan los flujos de comercio internacionales de manera correcta.

El recurso complementa de manera digital el material de las clases impartidas en las asignaturas de Economía y Administración de Empresa para que los estudiantes puedan comprender de forma concreta el papel de los gobiernos en la normalización de los mercados internacionales frente a condiciones de desequilibrio.
Doenças crônicas não transmissíveis e seus fatores de risco na população beneficiária do Programa Bolsa Família
Authors: Carvalho Quéren Hapuque de , Silva Alanna Gomes da , Santos Douglas Paschoal dos , Malta Deborah Carvalho
Published: November 2023

Objetivo: sintetizar as evidências científicas sobre a ocorrência de doenças crônicas não transmissíveis (DCNT) e seus fatores de risco (FR) na população beneficiária do Programa Bolsa Família (PBF). Métodos: trata-se de uma revisão integrativa da literatura, cuja busca por publicações de 2004 a 2020 foi feita nas seguintes bases de dados: Literatura Latino-americana e do Caribe em Ciências da Saúde (LILACS) e Indice Bibliográico Español en Ciencias de la Salud (IBECS), via Biblioteca Virtual da Saúde (BVS); Medline, via Pubmed, SCOPUS (via Portal CAPES); e Scientific Electronic Library Online - SciELO. Resultados: foram selecionados 23 artigos, os quais foram agrupados em três categorias: 1) Prevalência dos fatores de risco para DCNT em mulheres beneficiárias do PBF: as mulheres beneficiárias apresentaram piores desfechos no consumo de tabaco, menor prática de atividade física, maior prevalência de diabetes, hipertensão e obesidade; 2) Estado nutricional e insegurança alimentar em crianças, adolescentes e famílias beneficiárias do PBF: os estudos apontaram para uma elevada prevalência de obesidade e coexistência de déficit estatural em crianças beneficiárias; e 3) Consumo alimentar de beneficiários do PBF: foi identificado um padrão não saudável de alimentação. Conclusão: usuários do PBF apresentam elevadas prevalências de fatores de risco para doenças crônicas não transmissíveis e pior padrão alimentar. Esses dados reforçam a importância de o PBF estar sendo direcionado às populações mais vulneráveis, visando mitigar as imensas desigualdades sociais. No entanto, é necessário avançar em outras políticas públicas de proteção social que impactem os determinantes sociais e melhorem a qualidade de vida de extensa camada da população brasileira.
Increasing Learning Achievement in Islamic Religious Education Through a Contextual Learning Approach of Students
Authors: Daabi Muhammad Kholif Ikhda , Inayati Nurul Latifatul
Published: November 2023

The background in this study is the low achievement of learning Islamic religious education. This research is intended to improve the learning achievement of Islamic religious education through a contextual learning approach. This exploration uses classroom action research (PTK) which consists of two cycles with four stages, namely, planning, action, observation, and reflection. The subjects of this study were grade XI students of SMA 5 Surakarta consisting of 11 boys and 19 girls. The conclusion of this study is that there is an increase in each cycle. In the first cycle, the average score of the test was 65.17 out of 30 students who took the test, with 37% (11 students) in the complete category and 63% (19 students) in the incomplete category. Furthermore, in cycle II there was an increase in tests with an average of 77.47 out of 30 students who took the test. With many 87% (26 students) completed and 13% (4 students) incomplete. The increase in Islamic Religious Education learning achievement from cycle I to cycle II by 50%. With the contextual learning approach, it can improve the learning achievement of Islamic Religious Education in students.
Digital Twins and Its Security Issues and Implications
Authors:   Department of Information Technology, Vellore Institute of Technology, Vellore (Tamil Nadu), India., C Nikhil
Published: November 2023

A digital twin is a digital or virtual copy of physical assets or products. It has the virtual and real world by collecting real-time data from the sensors which are installed in the devices. The collected data is either locally decentralized or centrally stored in cloud. Then the data is evaluated and simulated in virtual copy of the assets. After revising the information from stimulation the parameters are applied to real assets and we can predict current and future conditions in both design and operational environment. Also these are the next big thing in fourth industrial revolution for the development of new products and process. Because of vast amount of data used and the risk this poses to sensitive system data. To overcome these. The key enabling technology for digital twins data analytics and IoT must follow the updated security policies, and data sharing based on Distributed Ledger Technology can help to overcome the challenges in sharing data.
Performance Analysis of MIMO Heterogeneous Wireless Sensor Networks
Authors:   Assistant Professor, Department of EECE, DIT University, Dehradun (Uttarakhand), India., Mishra Saurabh , Ranjan Prof. Rakesh ,   Professor & Vice Chancellor, Sushant University Gurgaon (Haryana), India., Singh Dr. Sonika ,   Associate Professor, Department of EECE, DIT University, Dehradun (Uttarakhand), India., Singh Dr. Gagan ,   Professor, Department of EECE, DIT University, Dehradun (Uttarakhand), India.
Published: November 2023

Wireless Sensor Networks (WSN) are widely used in remote applications related to defence and healthcare. A network with nodes having different capabilities like sensing, various computational capabilities, power-efficient communication, and a varied sensing range is called a heterogeneous wireless sensor network. Heterogeneous wireless sensor networks using MIMO wireless channels are more useful for energy-efficient multi-channel communication. MIMO applications in wireless sensor networks have the potential to enhance throughput, reduce End-to-End Delay, improve packet delivery ratios, and conserve energy in wireless sensor networks. Its implementation needs to be carefully considered in light of the specific deployment conditions and resource constraints of the network, considering proper antenna design, synchronisation mechanisms, and energy-efficient algorithms. This paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO for various Quality of Service parameters like Packet Delivery Ratio, End to End Delay, Throughput and Residual energy. The research work shows that the application of MIMO in Wireless Sensor Networks enables sensor nodes to collaborate effectively, leading to improved reliability and coverage, and also increases the network's lifetime by conserving energy in resource-constrained sensor nodes through the preservation of Residual Energy.
KAJIAN ARSITEKTUR KONTEKSTUAL PADA ELEMEN FASAD HOTEL DI KAWASAN KOTA LAMA SEMARANG
Authors: Aryanto Tiara Nisa , Kridarso Etty R. , Wijayanto Punto
Published: November 2023

Konsep arsitektur kontekstual pada umumnya diaplikasikan pada kawasan-kawasan bersejarah. Kawasan bersejarah di Provinsi Jawa Tengah yaitu Kawasan Kota Lama Semarang memiliki potensi yang besar dalam segi pariwisata lokal. Sehingga saat ini telah hadir fasilitas penunjang berupa bangunan hotel. Penelitian ini bertujuan untuk menjelaskan penerapan konsep arsitektur kontekstual pada elemen fasad bangunan hotel di Kawasan Kota Lama Semarang, dan memperlihatkan keselarasan antara bangunan baru dengan bangunan disekitarnya. Penelitian ini menggunakan metode kualitatif dengan menggunakan pendekatan deskriptif dan evaluatif. Hasil dari analisis telah menunjukkan bahwa fasad dari kedua bangunan hotel memiliki penerapan arsitektur kontekstual yang kuat dari segi harmoni, sedangkan dari segi kontras hanya ditemukan di beberapa elemen.
Deep Clustering with Self-supervision using Pairwise Data Similarities
Authors: Sadeghi Mohammadreza , Armanfard Narges
Published: November 2023

Deep clustering incorporates embedding into clustering to find a lower dimensional space appropriate for clustering. In this paper, we propose a novel deep clustering framework with self-supervision using pairwise data similarities (DCSS). The proposed method consists of two successive phases. In the first phase, we propose to form hypersphere-like groups of similar data points, i.e. one hypersphere per cluster, employing an autoencoder that is trained using cluster-specific losses. The hyper-spheres are formed in the autoencoder’s latent space. In the second phase, we propose to employ pairwise data similarities to create a K-dimensional space that is capable of accommodating more complex cluster distributions, hence providing more accurate clustering performance. K is the number of clusters. The autoencoder’s latent space obtained in the first phase is used as the input of the second phase. The effectiveness of both phases is demonstrated on seven benchmark datasets by conducting a rigorous set of experiments. The DCSS code is available: https://github.com/Armanfard-Lab/DCSS
Intuitive Understanding of Observing Reality: With Extension of the Game Theory
Authors: Yoon Jihyeon
Published: November 2023

By extending the context of the Game Theory to the understanding of P vs NP Problem, fundamental principles of observation can be explained to the very limit of existence.
Generating Views Using Atmospheric Correction for Contrastive Self-supervised Learning of Multi-spectral Images
Authors: Patnala Ankit , Stadtler Scarlet , Schultz Martin G , Gall Juergen
Published: November 2023

In remote sensing, plenty of multi-spectral images are publicly available from various landcover satellite missions. Contrastive self-supervised learning is commonly applied to unlabeled data but relies on domain-specific transformations used for learning. When focusing on vegetation, standard transformations from image processing cannot be applied to the NIR channel, which carries valuable information about the vegetation state. Therefore, we use contrastive learning, relying on different views of unlabelled, multi-spectral images to obtain a pre-trained model to improve the accuracy scores on small-sized remote sensing datasets. This study presents the generation of additional views tailored to remote sensing images using atmospheric correction as an alternative transformation to color jittering. The purpose of the atmospheric transformation is to provide a physically consistent transformation. The proposed transformation can be easily integrated with multiple channels to exploit spectral signatures of objects. Our approach can be applied to other remote sensing tasks. Using this transformation leads to improved classification accuracy of up to 6%.
Chance-Constrained Rollover-Free Manipulation Planning with Uncertain Payload Mass
Authors: Song Jiazhi , Petraki Antoine , DeHart Brandon , Sharf Inna
Published: November 2023

This paper presents a chance-constrained rollover-free manipulation planning method for robotic arms under payload mass uncertainty. The corresponding motion planning problem is stated as a chance-constrained nonlinear optimal control problem (NOCP) subject to kinematics and rollover stability constraints. The latter takes the form of a chance constraint that ensures a certain probability of the robot maintaining dynamic rollover stability in the presence of payload mass uncertainty. To achieve efficient solutions to the NOCP, a novel geometric bound for the stability region is derived. The novel bound is then utilized to modify the rollover-stability constraint. To showcase its benefit, comparisons between the proposed bound of probabilistic rollover stability measure and the naive noise model are provided through statistical analysis. The formulation's practicality is demonstrated through experiments with a Kinova Jaco 2 arm mounted on a free-to-roll platform. Results demonstrate greater robustness of the robot's motion plan to mass uncertainty and computational efficiency of the trajectory generation. 
Programming Computational Electromagnetic Applications Assisted by Large Language Models
Authors: Carísio Fernandes Leandro
Published: November 2023

This article discusses the possibilities and limitations of using large language models (LLMs) in software development with applications in computational electromagnetics. Three tasks are discussed: code translation, code generation, and code description. The tests showed that LLMs are generally very useful. Even when errors occurred, they can provide useful hints to find a solution.
A NEW MOBILE RF DRIVE TEST APPLICATION
Authors: Samani Siewe Darix
Published: November 2023

To enhance the quality of service (QoS) provided to users, network operators are compelled to continually refine their network infrastructure through the iterative process of drive testing. Drive testing is a method used to measure and assess the coverage, capacity, and QoS in a mobile radio network. However, the conventional paradigm governing drive testing, which entails the deployment of either radio frequency equipment or software solutions such as TEMS Investigation accompanied by GPS and an MS (Mobile Station), is marred by inherent limitations that hinder precision in data collection spatiality and necessitate a cumbersome use of multiple tools. In our work, we embark on a novel trajectory, anchoring our non-invasive drive test methodology  on the potency of a wearable device such as smart phones. Inspired by this, we design  an Android-based drive test platform that stands as a fulcrum of innovation. This platform consists primarily of a mobile application that acts as a measuring instrument, and an API to relay the data collected by the mobile application. This Android-based approach provides operators with heightened precision in both location determination and parameter measurements. Moreover, it streamlines service provisioning, eliminating the need for a range of complex tools, and instead offering a simple application-based solution. By adopting our mobile application, the drive testing process becomes adaptable to a variety of scenarios, including roads with high traffic density or narrow pathways. Our methodology signifies a significant step forward in improving resources-efficient drive testing process for operators.
Exploiting the Quantum Advantage for Satellite Image Processing: Review and Assessment
Authors: Otgonbaatar Soronzonbold , Kranzlmüller Dieter
Published: November 2023

This article examines the current status of quantum computing in Earth observation (EO) and satellite imagery. We analyze the potential limitations and applications of quantum learning models when dealing with satellite data, considering the persistent challenges of profiting from quantum advantage and finding the optimal sharing between high-performance computing (HPC) and quantum computing (QC). We then assess some parameterized quantum circuit models transpiled into a Clifford+T universal gate set. The T-gates shed light on the quantum resources required to deploy quantum models, either on an HPC system or several QC systems. In particular, if the T-gates cannot be simulated efficiently on an HPC system, we can apply a quantum computer and its computational power over conventional techniques. Our quantum resource estimation showed that quantum machine learning (QML) models, with a sufficient number of T-gates, provide the quantum advantage if and only if they generalize on unseen data points better than their classical counterparts deployed on the HPC system and they break the symmetry in their weights at each learning iteration like in conventional deep neural networks. We also estimated the quantum resources required for some QML models as an initial innovation. Lastly, we defined the optimal sharing between an HPC+QC system for executing QML models for hyperspectral satellite images. These are a unique dataset compared to other satellite images since they have a limited number of input qubits and a small number of labeled benchmark images, making them less challenging to deploy on quantum computers.
Pars-HaO: Hate and Offensive Language Detection on Persian Tweets Using Machine Learning and Deep Learning
Authors: Karami Sheykhlan Mohammad , Abdoljabbar Saleh Kheiri
Published: November 2023

As social networks continue to gain widespread popularity, an urgent requirement arises to automatically identify and detect offensive language and hate speech. While there is a wealth of research and datasets available for English in this domain, there is currently a scarcity of research and datasets focused on identifying hate speech and offensive language in Persian text. This article introduces a 3-class dataset named Pars-HaO, consisting of 8013 tweets, to fill the gap in existing research. We collected the dataset by combining comments from pages that are more exposed to hate speech and using a keyword-based approach. Three annotators then labeled the tweets. In this study, we employed a combination of the Convolutional Neural Network (CNN) model and four widely recognized machine learning models, namely Support Vector Machine (SVM) and Logistic Regression (LR), Random Forest (RF), and Decision Tree (DT) as a baseline. Then, we compared the base models with Long Short-Term Memory(LSTM), Bidirectional LSTM (BiLSTM), and CNN models, each trained using the output of the last hidden state of Bidirectional Encoder Representations from Transformers (BERT). Experimental results on the Pars HaO dataset demonstrated that the BERT with BiLSTM technique yielded the best outcome, achieving a macro F1-score of 70%.

 
Augmented Reality (AR) Technology on Student Engagement: An Experimental Research Study
Authors: SWARGIARY KHRITISH
Published: November 2023

This experimental research aims to investigate the potential benefits of integrating augmented reality (AR) technology into the classroom setting. The study hypothesizes that the use of AR technology will enhance student engagement and lead to improved learning outcomes. A sample of participants from a local high school will be involved in this research. The research employs a pre-test/post-test design to assess the impact of AR technology on student engagement and learning outcomes. Data will be collected and analysed to determine the effectiveness of AR technology in enhancing classroom education.
The potential of SDNs and multihoming in VANETs: A Comprehensive Survey
Authors: Sarpong Richmond , Sousa Bruno , Araújo Filipe
Published: November 2023

The escalating growth of vehicles has amplified the complexity of Vehicle Ad-hoc Networks (VANETs), necessitating innovative strategies to combat communication delays and disruptions. In this study, we covered a literature review from 2009 to 2023 where we present a comprehensive exploration of solutions by integrating Software-Defined Networking (SDN), Programming Protocol-independent Packet Processors (P4), and Service Function Chaining (SFC). Our research addresses the core challenges of VANETs, emphasizing the specific problem of communication delays.

We conducted an in-depth analysis of SDN’s application in VANETs, showcasing its potential to enhance network efficiency and adaptability. Additionally, we delve into the practical implementation of P4 architecture in traffic management and multihoming environments, elucidating its pivotal role in improving VANET performance. Simultaneously, we explore the intricacies of SFC and its support for services and policies in VANETs.

Our study reveals novel approaches to mitigate delays in VANETs, presenting valuable insights for both researchers and practitioners. By integrating SDN, P4 architecture, and SFC in a multihoming environment, our research not only advances the understanding of VANET challenges but also provides practical and implementable solutions for achieving efficient and low-latency vehicular communication networks. This work do not only contributes to the academic discourse but also holds significant promise for real-world applications, marking a pivotal step towards the future of seamless vehicular communications.
Robot Evolution for Autonomous Behavior in Dynamic Environments
Authors: Zaman Budee U
Published: November 2023

 This paper introduces a novel robot parallel evolution design algorithm , leveraging the concept of a module network, to optimize the learning process of collision avoidance, approach, and wall switching behaviors in evolutionary robots. The proposed algorithm is validated and tested, demonstrating its efficacy in enabling evolutionary robots to autonomously exhibit behaviors such as collision avoidance, movement, repli-cation, and attack. The learning methodology focuses on refining the neural network-based strategies for collision avoidance, approach, and wall switching behaviors. The evolutionary robots, operating in a simulated environment, show-case the ability to adapt and enhance their performance over time. The simulation environment includes randomly generated rectangular obstacles with varying side lengths, strategically placed to represent real-world challenges. Additionally, the environment features randomly scattered approach targets, serving as goals for the robots. The modular design of the neural network allows for the integration of fundamental behaviors such as collision avoidance and approach, enabling a progressive enhancement of the robot's capabilities. As the neural network evolves, the robots demonstrate an increasingly sophisticated ability to navigate their surroundings, avoid obstacles, approach targets, and adapt to dynamic scenarios. Through extensive simulations, the proposed algorithm proves effective in training evolutionary robots to navigate complex environments autonomously. The study contributes to the field of evolutionary robotics by presenting a modular neural network approach that enables the gradual acquisition and integration of diverse behaviors, showcasing the potential for autonomous and adaptive robotic systems in dynamic and challenging environments. 