bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-objective scheduling in dynamic of household paper workshop considering energy consumption in production process
Authors: Zhang Zhenya , He Xiuli , Man Yi , He Zhenglei
Published: September 2023

Aim: The uncertainty and complexity of the production process of household paper are growing sharply in modern factories. Due to the influence of rising energy costs and environmental policies, the demand for reducing production costs and energy consumption is also increasing. Therefore, it is studied that the dynamic shop scheduling problem of household paper production considering simultaneously the cost with energy consumption.

Methods: A mathematical model of the multi-objective and multi-constraint household paper scheduling problem is established first. The multi-objective scheduling process is transformed into a multi-agent Markov game process by assigning each objective to each agent. Upon which, a multi-agent game model is constructed for the household paper scheduling problem based on deep reinforcement learning; it is a proposed D3QN algorithm and Nash equilibrium strategy, and the state characteristics and action selection space are proposed according to the characteristics of the household paper production. The model performance has been verified by the actual production data.

Results: Results show that the proposed method not only achieves better performance than traditional scheduling methods but also persists in its advantages even when the configuration of the manufacturing system changes.

Conclusion: Multi-agent deep reinforcement learning in the Markov game has a good prospect in solving multi-objective dynamic scheduling problems for household paper production.
Dr Jekyll and Mr Hyde: From Two Branches of Immune Response to Three Types of Interferon Response
Authors: Brown Brent , Imarogbe Chinua , Fricke Ingo , Mensah Pascal
Published: September 2023

Interferons were the original prototype cytokine system discovered in 20th-century research. As the name implies, they were originally thought to be synthesised and secreted between cells. Thanks to technological advances, the processes involved in protein secretion can be explained comparatively more clearly at both the genetic and biochemical levels. The discovery of interferon (IFN) occurred when genetic research was still in its infancy. Franklin and Wilkins discovered the structure and function of deoxyribonucleic acid (DNA) at the same time as Crick and Watson; however, Isaacs and Lindemann, two scientists, described the first IFN in 1957. Mutations can be caused by inherent genetic protein synthesis and during infection as well as within IFN regulation pathways affecting cell proliferation. This remains central to host cell IFN synthesis and effects through IFN protein receptor subunits defined by 6 protein domains. Type II IFN is key to immune cell function secreted by a variety of immune cells, mainly natural killer (NK) as well as T cells. Single–stranded and/or double–stranded RNA/DNA viruses, as well as bacterial infections (e.g., Escherichia coli) and fungal infections (e.g., Aspergillus), also affect IFN regulation. Pathogenic proteins utilise intra/extracellular proteins that sense foreign antigens like Toll–like Receptors (TLRs), affected by mutations within the human cellular IFN transduction pathways. Since the discovery of the third IFN type in 2003, when immune cell phenotypes were further characterised, questions remain about the immunological mechanisms contributing to the regulation of the innate and adaptive host immune system. Alterations in the synthesis of type I/II/III host IFNs can differentially and beneficially alter homeostatic cellular pathways in pathological disease, with type I IFN being synthesised in cancer as well as by homeostatic cells. Therefore, considered here are the overall IFN molecular, cell regulatory mechanisms in the context of immune cell research developments.
Bacterial Products and Their Effect in the Shrubby Legume Calicotome Villosa (Poir.) Link
Authors: Pérez-Fernández María A. , De-Lara-del-Rey Irene Ariadna , Magadlela Anathi
Published: September 2023

Calicotome villosa is a eurioic legume with broad distribution in the south of Europe. It can grow in almost any type of soils as well as in humid and dry and nutrient deficient ecosystems. The broad distribution and eurioic nature of C. villosa may be attributed to its ability to establish symbiotic associations with plant growth promoting (PGP) bacteria housed in the nodules and rootless. This study examined legume-microbe symbiosis of C. villosa growing in two contrasted locations, hill top with high sun irradiance and drought; and a valley bottom, with low level or radiation and sufficient soil humidity for plant growth. Calicotome villosa adult plants established symbiotic in-teractions with bacteria in six genera, Pseudomonas, Stenotrophomonas, Bacillus, Paenibacillus, Brevicacterium and Rhizobium as well as one uncultured bacteria. Plants growing in the hill top had associated lower bacterial richness than those grown at the valley bottom. All strains were drought tolerant and produced siderophores, IAA, HCN and NH3 that stimulated plant performance in both, C. villosa plants and other four legumes commonly present in the understory of the shrubs communities The legumes’ capacity to selectively host symbiotic bacteria that enhance plant survival in harsh conditions partly accounts for the diverse partnerships between C. villosa plants and their symbionts, ultimately explaining the wide distribution of this plant species.
Analysis of Price Influencing Factors of Small-Scale Agricultural Products Based on Network Perspective
Authors: Fu Lifang , Zhang Huaxu
Published: September 2023

In recent years, the high-frequency abnormal price fluctuations of small-scale agricultural products have been detrimental to market stability. The traditional method based on statistical data of production factors can no longer accurately predict abnormal price fluctuations. Taking scallions as a case, the paper identifies price influencing factors from massive network information, and analyzes the causes and changing characteristics of price fluctuations from four perspectives: market supply, economic environment and market sentiment, and attention. Initially, the study employs an LDA topic model to extract factors from online sentiment data over the past four years, including market supply and demand, economic conditions, related agricultural prices, and market attention. Subsequently, using the SO-PMI algorithm to expand domain-specific lexicons and employing semantic and sentiment analysis with syntactic parsing, the study aims to improve the accuracy of sentiment quantification in text analysis. Furthermore, cointegration and Granger causality tests validate the significant impact of these factors on scallion price fluctuations, mitigating spurious regression issues. Finally, by employing a TVP-VAR model, the study compares the impulse responses and shock magnitudes of various factors in different time and spatial dimensions. It also delves into the mechanisms of heterogeneous impacts and trends in scallion prices, considering the corresponding socio-economic context and public sentiment events within specific time windows, thereby providing valuable decision-making insights for the healthy development of agricultural markets.
Deep Supervised Hashing by Fusing Multiscale Deep Features
Authors: ADIL REDAOUI , Kamel BELLOULATA , Amina BELALIA
Published: September 2023

Deep networks-based hashing has gained significant popularity in recent years, particularly in the field of image retrieval. However, most existing methods only focus on extracting semantic information from the final layer, disregarding valuable structural information that contains important semantic details crucial for effective hash learning. To address this limitation and improve image retrieval accuracy, we propose a novel deep hashing method called Deep Supervised Hashing by Fusing Multiscale Deep Features (DSHFMDF). Our approach involves extracting multiscale features from multiple convolutional layers and fusing them to generate more robust representations for efficient image retrieval. Experimental results on CIFAR10 and NUS-WIDE datasets demonstrate that our method surpasses the performance of state-of-the-art hashing techniques.
Hydrolysis Optimization of by-Products from the Potato Processing Industry and Biomethane Production from Starch Hydrolysates
Authors: Theodosi Palimeri Dimitra , Papadopoulou Konstantina , Vlyssides Apostolos G. , Vlysidis Anestis. A.
Published: September 2023

The aim of this study is to examine an efficient and environmental friendly process for hydrolyzing starch, an industrial-derived by-product of the potato processing industry, and to use the produced hydrolysates as substrates for methane production. A full factorial experiment was designed and the optimal concentrations of FeSO4·7H2O, H2O2 and temperature were determined obtaining a yield of 99.5%, with a total carbohydrates content equal to 28.65 g, when the input parameters were at their high level: FeSO4·7H2O 1.00g/L, H2O2 0.51 g/L and temperature 70.0oC. The hydrolysis kinetics were also examined revealing that temperature was the most important factor among the three optimization parameters. Furthermore, biodegradability tests were carried out to measure the methane production potential from the produced hydrolysates. The specific methanogenic activity was reached 0.669 g CODCH4/gVSS-day proving the effectiveness of the hydrolysis process and highlighting the potential of this food manufacturing by-product for bioenergy production. A preliminary cost analysis showed that a small investment for utilizing the starch in an existing wastewater treatment facility of a potato processing industry becomes profitable before the end of the 3rd year obtaining a NPV 37.5% higher than the NPV of the current utilization scenario.
Using a Non-contact Sensor to Delineate Management Zones in Vineyards and Validation with the Rasch Model
Authors: Moral Francisco J. , Rebollo Francisco J. , Serrano João
Published: September 2023

The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest to incorporate technologies and methods to determine these homogeneous zones.
A case study was conducted in a 3.3 ha vineyard located near Évora, South of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture, pH, organic matter -OM, phosphorous -P2O5, potassium -K2O, sum of the exchange bases -SEB; and cation exchange capacity -CEC) which were determined from 20 soil samples taken in the different MZs. Additionally, validation was also performed using Rasch measures, which were defined based on the formula-tion of the objective and probabilistic Rasch model, integrating the information from the afore-mentioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ.
The use of ECa constitutes an efficient technological tool for implementing site-specific man-agement in viticulture, which allows for the improvement of decision-making processes by con-sidering the inherent spatial variability of the soil.
Genotypic and Allelic Frequencies of GJB2 Variants and Features of Hearing Phenotypes in the Chinese Population of the Dongfeng-Tongji Cohort
Authors: Yuan Lanlai , Wang Xiaohui , Liu Xiaozhou , Chen Sen , Kong Weijia , He Meian , Sun Yu
Published: September 2023

Background: this study aimed to describe the distribution of the genotype and allele frequencies of GJB2 variants in the Chinese population of the Dongfeng Tongji cohort and to analyze the features of the hearing phenotype. Methods: we used data from 9910 participants in the Dongfeng Tongji cohort in 2013 and selected nine GJB2 variants. Pure-tone audiometry was employed to measure hearing. Differences in genotype and allele frequencies were analyzed by chi-squared test or Fisher's exact test. Results: of the 9910 participants, 5742 had hearing loss. The genotype frequency of the GJB2 variant p.V37I was statistically significantly distributed between the normal and impaired hearing groups, but not for the variant c.235delC. A higher frequency of the p.V37I homozygous genotype was found in the hearing loss group (0.5%) than in the normal hearing group (0.1%). Patients with p.V37I and c.235delC homozygous mutations exhibited varying degrees of hearing loss, mainly presenting sloping and flat audiogram shapes. Conclusions: a significant difference was found in the genotype frequency of the GJB2 variant p.V37I between the case and control groups, but not for the variant c.235delC. Different degrees of hearing loss and various audiogram shapes were observed in patients with p.V37I and c.235delC homozygous mutations.
Decoding the Digital Barnyard - Cognitive Computing in Farm Animal Emotions and Welfare
Authors: Neethirajan Suresh
Published: September 2023

In this paper, we critically examine the burgeoning role of advanced computational methodologies in deciphering the complex tapestry of farm animal behaviors and emotions. Leveraging digital imaging and artificial intelligence, we unearth nuanced behavioral patterns and micro-expressions, offering predictive insights into animal emotional states. Sound vocalization analysis, often overlooked, emerges as a pivotal tool, decoding intricate communicative nuances and emotional undertones. Cognitive tests, including mirror and bias assessments, challenge long-standing perceptions, revealing surprising depths of animal self-awareness and cognitive sophistication. However, the paper also underscores the imperative of integrating these tools with a profound understanding of animal psyche, ensuring technology serves as an enhancer, not a replacement, of traditional observational methods. This research not only highlights the transformative potential of cognitive computing in animal welfare but also calls for a judicious application, ensuring technology augments, not undermines, the intrinsic value of human-animal interactions and understanding.
Simple Sequence Repeats-Based DNA Fingerprinting and Varietal Identification of Mango Cultivars
Authors: Iqbal Javed , Ashraf Muhammad Aleem , Cai Qiuliang , Riaz Ammara , Li Yufeng , Shahid Imran , Kong Yu , Grewal Abdul Ghaffar , Kiran Sidra , Rehman Sajid , Habib Imran , Yu Naitong
Published: September 2023

Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. This study investigated the molecular evaluation of a new mango cultivar ‘Azeem Chaunsa’ using a set of the most effective 50 hyper-variable polymorphic SSR markers. Highly specific DNA fingerprints were identified in the genome of this mango cultivar, ‘Azeem Chaunsa’ compared with three standard cultivars such as Sindhri, Samar Bahisht (S.B) Chaunsa and Sufaid Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. An agglomerative hierarchical clustering method was used to construct dendrogram based on the ‘Unweighted Pair- Group Method with Arithmetic Mean’ (UPGMA). The genetic similarity coefficients were recorded between the mangos cultivars ranged from 0.49 to 0.67. Cultivar identification (CID) evaluates association among standard cultivars and Azeem Chaunsa and further concludes significant variations. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future mango breeding programmes in the context of climate change.
Rare Virulences and Great Pathotype Diversity of a Central European Blumeria hordei Population
Authors: Dreiseitl Antonín
Published: September 2023

Barley is an important crop grown on almost 49 Mha worldwide in 2021 and is particu-larly significant in Europe where powdery mildew is the most frequent disease on sus-ceptible varieties. The most suitable way for protecting crops is exploiting genetic re-sistance. However, the causal agent Blumeria hordei is an extremely adaptable pathogen. The aims of this research were to increase our knowledge of the rapidly changing path-ogen population and detect rare virulences. Random samples of the pathogen were ob-tained from the air by means of a mobile spore sampler. Spores were collected by driv-ing across the Czech Republic in 2019, 2021 and 2023 and 299 isolates were analyzed on 121 host varieties. No infection occurred on 35 differentials, rare virulence was recorded on 31 varieties and a higher virulence frequency was found on 55 differentials. A core set of differentials along with four additional varieties distinguish 295 pathotypes (Simple Index = 0.987) and virulence complexity of isolates varied from 4 to 19 with an average 10.39. The detection of new virulences, the increasing frequency of previously rare viru-lences and high pathotype diversity as well as high virulence complexity confirm that using nonspecific durable resistance is crucial for successfully breeding commercial va-rieties.
Direct Experience of Nature as a Predictor of Environmentally Responsible Behaviors
Authors: Yanniris Constantinos , Gavrilakis Costas , Hoover Michael L
Published: September 2023

A small but growing body of literature suggests that outdoor experiences during childhood affect environment-related behaviors in adulthood. However, research on the magnitude of the effect (effect size) of outdoor experience on learners’ behaviors remains scarce. In this study, we explore the extent to which outdoor experiences associate with environmentally responsible behaviors. Our sample consisted of 143 ninth- and tenth-grade students living on a Greek island. The data were collected using a properly adjusted environmental literacy instrument. Two different methodological pathways, i.e., a quasi-experimental approach and correlation analysis, were used to analyse the data. A tentative variable representing the frequency and intensity of students’ experiential contact with nature was found to be the strongest available predictor of their self-reported pro-environmental behaviors. The findings of this study support the significance of outdoor, experiential learning during childhood in shaping individuals’ environmental behaviors.
A Smart Framework to Detect Threats and Protect Data of IoT based on Machine Learning
Authors: M. Almasabi Ahmad , Khemakhem Maher , Harbaoui Ahmed , Eassa Fathy , B. Alkodre Ahmad. , Jambi Kamel , Abi Sen Adnan Ahmed
Published: September 2023

Abstract: The Internet of Things (IoT) has witnessed rapid and widespread adoption across various domains, including transportation, healthcare, education, agriculture, urban planning, smart homes, and more. Despite its transformative potential, this pervasive deployment of IoT devices has introduced new challenges, particularly concerning security and privacy threats such as unauthorized data access and device breaches. The excessive usage of these technological devices, coupled with the absence of robust security and privacy systems for user data, calls for a comprehensive approach to address these issues. In this study, we propose a novel framework designed to analyze, audit, test, and detect potential vulnerabilities within IoT environments and applications. The central components of the proposed framework include a machine learning algorithm for data classification and attack detection, along with the integration of Blockchain technology to enhance security measures. Specifically, the framework performs an in-depth analysis of user data to identify potential security or privacy vulnerabilities. Additionally, it conducts rigorous testing of smart services and automated data-collecting devices. To evaluate the effectiveness of our classification algorithm, we conducted a comprehensive implementation on a real-world IoT dataset. The results showcased the efficiency and accuracy of our approach in detecting and mitigating potential threats. Furthermore, based on our research findings, we provide valuable recommendations for enhancing security and privacy in IoT ecosystems. We also highlight emerging trends in the security and privacy domains, which can serve as valuable insights for researchers and practitioners. In conclusion, our proposed framework offers a robust and proactive approach to address the security and privacy challenges, such as unauthorized data access and device breaches posed by the widespread adoption of IoT devices. By combining machine learning algorithms and Blockchain technology, we contribute to safeguarding user data and fostering a secure environment for IoT applications. This study lays the groundwork for further advancements in the realm of IoT security and privacy, ensuring a safer and more resilient IoT landscape for the future.
Induction of Autophagy and Its Role in Facial Nerve Regeneration after Facial Nerve Injury
Authors: Yon Dong Keon , Kim Yong Jun , Park Dong Choon , Jung Su Young , Kim Sung Soo , Yeo Joon Hyung , Lee Jeongmin , Lee Jae Min , Yeo Seung Geun
Published: September 2023

Objective: There are currently no known treatment methods for ensuring complete recovery from facial nerve damage. Thus, various basic and clinical studies continue to be conducted to achieve this end. As part of this research, autophagy is being investigated for its role in nerve regeneration. Here, we review the existing literature regarding the involvement and signifi-cance of autophagy in facial nerve injury and regeneration. Methods: A comprehensive litera-ture review was conducted to assess the induction and role of autophagy in facial nerve injury and subsequent regeneration. Results: Studies conducted on rats and mice have demonstrated activation of autophagy and expression of related factors in facial and sciatic nerves. Among the most studied of these factors in relation to degeneration and regeneration of facial and sciatic nerves are LC3II/I, PI3K, mTOR, Beclin-1, ATG3, ATG5, ATG7, ATG9, and ATG12. Conclusion: This analysis indicates that autophagy is involved in the process of nerve regeneration follow-ing facial and sciatic nerve damage. Inadequate autophagy induction or failure of autophagy re-sponses can result in regeneration issues after facial or sciatic nerve damage. Animal studies suggest that autophagy plays an important role in facial and sciatic nerve degeneration and re-generation.
Machine Learning Methods in Climate Prediction: A Survey
Authors: Chen Liuyi , Han Bocheng , Wang Xuesong , Zhao Jiazhen , Yang Wenke , Yang Zhengyi
Published: September 2023

Weather and climate prediction have been crucial in human history for enabling effective agricultural planning, safeguarding against natural disasters, and facilitating strategic decision-making in various sectors. In this context, the need for accurate and timely forecasting is highly significant. Machine learning has the potential to improve the accuracy and speed of weather and climate prediction. This comprehensive survey assesses the efficacy of Machine Learning (ML) and Machine Learning-Enhanced (ML-Enhanced) methodologies in short-term weather forecasting and medium-to-long-term climate prediction. Acknowledging the historical importance of weather and climate prediction as crucial tools affecting human life and societal functions, the paper scrutinizes over 20 methods, highlighting six that appear to be at the forefront of ML applications in meteorological forecasting. While ML shows promising results in short-term weather prediction, its role remains supplementary in medium-to-long-term climate forecasting due to the complexity of climate conditions and limited data samples. The study finds ML to be fast, scalable, and relatively accurate; however, traditional methods remain indispensable, particularly for medium-to-long-term forecasts, where understanding the mechanisms of meteorological changes is pivotal.
An Adaptive Mixup Hard Negative Sampling for Zero-Shot Entity Linking
Authors: Cai Shisen , Wu Xi , Maimaiti Maihemuti , Chen Yichang , Wang Zhixiang , Zheng Jiong
Published: September 2023

Recently, the focus of entity linking research has centered on the zero-shot scenario, where the entity mention to be labeled at the time of testing was never observed during the training phase or may belong to a different domain than the source domain. Current studies have used BERT as the base encoder as it effectively establishes distributional links between source and target domains. The currently available negative sampling methods all use an extractive approach, which makes it difficult for the models to learn diverse and more challenging negative samples. To address this problem, we propose a generative negative sampling method, Adaptive_mixup_hard, which generates more difficult negative entities by fusing the features of both positive and negative samples on top of hard negative sampling and introduces a transformable adaptive parameter W to increase the diversity of negative samples. Next, we fuse our method with the Biencoder architecture and evaluate its performance under three different score functions. Ultimately, experimental results on the standard benchmark dataset Zeshel demonstrate the effectiveness of our method.
Targeting Oxidative Stress May Contribute to Improving the Inflammatory State and Glycemic Index of Glucose Control in Type 2 Diabetes
Authors: Arabshomali Arman , Bazzazzadehgan Shadi , Mahdi Fakhri , Shariat-Madar Zia
Published: September 2023

The clinical relationship between diabetes and inflammation is well-established. Various branches of science independently have confirmed that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with Type 2 diabetes mellitus (T2DM). Under diabetic condition, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress and tissue damage are believed to have a role in the development of diabetes. Although the exact mechanism underlying the oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in onset and progression of vascular disease, kidney disease, hepatic injury, pancreas damage and, therefore holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications therapy fails to achieve the normal range for glycated hemoglobin target, signifying treatment resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical in vivo and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision of the future diabetes clinical trials.
THE IMPLEMENTATION OF CLASSPOINT IN LEARNING ENGLISH: A CASE STUDY AT SMK MUHAMMADIYAH 3 KARANGANYAR ON ELEVENTH GRADE IN ACADEMIC YEAR 2021/2022
Authors: Hidayat Ikhwan Mahfud , Siregar Epi Supriyani , Hasibuan Siti Aminah , Ika Purnama Sari  , Anggraini Yanti
Published: September 2023

The application of Information and Communication Technology (ICT) in teaching and learning activities has a major influence in improving the quality of education, especially in the era of the industrial revolution 4.0 as it is today. Classpoint is a learning platform that supports IT-based learning activities. This study aims to determine the application of Classpoints in learning English at SMK Muhammadiyah 3 Karanganyar on elevent grade in the academic year 2021/2022. The research approach is qualitative research, case study research. The method that used to collect data is observation, interviews, and documentation. The methods used to analyze the data are data reduction, data presentation, and drawing conclusions. To test the validity of the data used data triangulation, method triangulation, and source triangulation. The results of research on the three subjects can be seen that the application of classpoint is very effective for learning English
EDUCATION AND EVALUATION IN A BUDDHISM PERSPECTIVE
Authors: Sapardi Sapardi
Published: September 2023

In today's modern era, advances in technology and knowledge have changed the civilization of people's lives with a new global culture that cannot be stopped anymore. In creating harmony, society is faced with the challenge of self-control of passions, emotions, and others which often lead to crime. This is the reason for the profanity of problems in society. Education developed in Buddhism (based on Buddhism) teaches us to see problems, see root causes, analyze problems and at the same time provide problem-solving solutions, which aim to achieve a more enlightened life. Buddhist education is defined as the process of getting rid of the main sources of human mental depravity, namely ignorance, greed, and hatred. Education in Buddhism is the transmission of values, knowledge, abilities, attitudes, and behaviors which are life itself. The method used in this research is descriptive qualitative. To interpret text data in this study using a hermeneutic approach. Based on the study that Buddhist education is pragmatic based on love and compassion, it is one of the ways to build a harmonious social life in society. Therefore, education also aims to get rid of suffering caused by ignorance, greed, and hatred and change human behavior. The success of education can be evaluated by how far each person can lead to better and more useful thoughts, words, and actions for life.
ANALYSIS OF STUDENT LEARNING CHARACTERISTICS AT LOW-CLASS ELEMENTARY SCHOOL LEVEL AT MI MUHAMMADIYAH 1 UJUNGPANGKAH
Authors: GILANG SURYANI PUTRI AL FITRI  , Ismail Marzuki, S.Ag., M.Pd
Published: September 2023

This study was conducted in the third grade of MI Muhammadiyah 1 Ujungpangkah to determine students' learning styles and how they affect the learning process. The research methods used were observation, interviews with grade 3 teachers, and a learning style questionnaire filled out by 15 students. The analysis revealed that the visual learning style was dominant at 53%, followed by kinesthetic at 13% and auditory at 33%. This highlights the importance of providing diverse learning materials that cater to students' preferred learning styles. The learning process should encourage active participation and inclusivity to explore student's potential.
REGULATORY CONSTITUTIONAL COMPETENCES IN TAXATION: THE CANARY ISLANDS’ECONOMIC AND FISCAL REGIME IN SPAIN
Authors: Martínez Cristóbal Daniel
Published: September 2023

This research work is based on the study of the transition process of the integration of the Canary Islands in the European Economic Community, also including the historical principles of the Economic and Fiscal Regime and its evolution, with the main objective of analyzing and identifying the modifications in the main law that regulates it and check its evolution and identify the areas that have been most affected, determining the effectiveness and contribution of current tax incentives in achieving the objectives for which they were designed within the powers regulated by the Spanish Constitution . The consolidation of its special economic situation within the Spanish internal order facilitated by community recognition in the evolution of the special economic situation of the Canary Islands will be highlighted, and that for its development it is necessary to study the economic situation of the Canary archipelago and to know the essential needs of trade with other regions. Additionally, indirect taxes such as the IGIC and the AIEM, subject to imports of goods in the Canary archipelago, will be analyzed.
Comparison of microalgal hydrochar and pyrochar: production, physicochemical properties, and environmental application
Authors: Park Chaerin , Kim Eun Jung
Published: September 2023

Microalgal biomass has been considered the third-generation biofuel production feedstock, but microalgae-derived biochar still needs to be thoroughly understood. This study aims to evaluate the production and physicochemical properties of microalgae-derived hydrochar by comparison with pyrochar for environmental applications. Microalgal biochar was produced with commercially available Chlorella Vulgaris microalgae using hydrothermal carbonization (HTC) and dry thermal carbonization (DTC) processes under various temperature conditions. Pyrochar presented higher pH, ash contents, porosity, and surface area than hydrochar. Hydrochar gave more oxygen-containing functional groups on the surface and higher lead adsorption than pyrochar, making the microalgal hydrochar applicable in soil amendment and various environmental remediation. HTC could be an economically feasible thermochemical process for microalgal biochar production. It can produce hydrochar with high production yield from wet microalgae at low temperatures without a drying process.
Direct and indirect association of domestic violence against women and severe maternal morbidity: a case control study
Authors: Sahebi Mahdieh , Abdollahpour Sedigheh , Sadeghi Masoumeh , Miri Hamid Heidarian
Published: September 2023

Introduction
Along with the reduction in maternal mortality, severe maternal morbidity (SMM) is getting more popular for the evaluation of maternal health programs. To prevent severe maternal morbidity we should know the risk factors which are similar to maternal mortality. the goal of this study is the investigation of direct association of domestic violence and indirect association of this exposure through pregnancy, delivery and neonatal risk factors with severe maternal morbidity as outcome.
Method
The target population of this case-control study is all women who gave birth in the hospitals of Torbat Heidarieh university of medical science in 2017(1397).
123 mothers with severe maternal morbidity (SMM) according to WHO criteria were selected as cases and 127 mothers who did not have WHO criteria were selected as a control group. Data were analyzed by STATA14 and mediation packages with the counterfactual approach.
Result
The odds ratio of pure direct effect for physical violence through pregnancy and neonatal risk factor are 2.26 and 2.29, respectively. The odds ratio of social violence through pregnancy, delivery and neonatal risk factors are 2.54, 267, and 2.57 and for economicalal violence through neonatal risk factors is 1.99. also the interaction between physical and social violence and pregnancy risk factors increase the risk of severe maternal morbidity by 394.6% and 360%, respectively.
conclusion
Domestic violence against women has direct association with SMM which has a significant effect on outcome as exposure. Physical and social violence have significant interaction with SMM. It is recommended to consider domestic violence screening as one of the effective interventions to prevent SMM and to improve the health of mothers by applying control strategies.
On the Time-Frequency Dynamics of Growth Cycles in Brazil
Authors: Matos Paulo , Alves Douglas , Monteiro Valdeir
Published: September 2023

We add to the empirical literature on growth, by addressing instrumentalized co-movements between the quarterly variation of real GDP per capita versus fiscal, monetary, and credit variables in Brazil. We use partial wavelet coherency to analyze time-frequency growth dependency on macro variables: net debt to GDP, primary balance to GDP, inflation, SELIC rate, household, and enterprise credit to GDP. We also use partial phase difference and partial gain to identify and measure the lead-lag relationship between growth and these macro variables. We provide a set of new stylized facts about the recent history of growth in Brazil over the period from 2004 and 2022, a period marked by three recessions. To summarize, in periods of expansion, primary balance cycles lead in-phase growth cycles, while inflationary and household credit cycles use to lead out-of-phase growth cycles. During recessions, we find a relevant positive role played by the enterprise credit, and a negative leadership of SELIC on economic growth cycle.
JEL classification: C02, O42, H60
Dual blockade of BRD4 and ATR/WEE1 pathways exploits ARID1A loss in clear cell ovarian cancer
Authors: Simpkins Fiona , Kinose Yasuto , Xu Haineng , Kim Hyoung , Kumar Sushil , Shan Xiaoyin , Geroge Erin , Wang Xiaolei , Medvedev Sergey , Ferman Benjamin , Gitto Sarah , Whicker Margaret , D.Andrea Kurt , Wubbenhorst Bradley , Hallberg Dorothy , O'Connor Mark , Schwartz Lauren , Hwang Wei-Ting , Nathanson Katherine , Mills Gordon , Velculescu Victor , Wang Tian-Li , Brown Eric , Drapkin Ronny
Published: September 2023

ARID1A, an epigenetic tumor suppressor, is the most common gene mutation in clear-cell ovarian cancers (CCOCs). CCOCs are often resistant to standard chemotherapy and lack effective therapies. We hypothesized that ARID1A loss would increase CCOC cell dependency on chromatin remodeling and DNA repair pathways for survival. We demonstrate that combining BRD4 inhibitor (BRD4i) with DNA damage response inhibitors (ATR or WEE1 inhibitors; e.g. BRD4i-ATRi) was synergistic at low doses leading to decreased survival, and colony formation in CCOC in an ARID1A dependent manner. BRD4i-ATRi caused significant tumor regression and increased overall survival in ARID1AMUT but not ARID1AWT patient-derived xenografts. Combination BRD4i-ATRi significantly increased γH2AX, and decreased RAD51 foci and BRCA1 expression, suggesting decreased ability to repair DNA double-strand-breaks (DSBs) by homologous-recombination in ARID1AMUT cells, and these effects were greater than monotherapies. These studies demonstrate BRD4i-ATRi is an effective treatment strategy that capitalizes on synthetic lethality with ARID1A loss in CCOC.
Lymphatic drainage patterns of malignant skin tumors in the head and neck region: a single-center retrospective study
Authors: Nishio Takuya , Maeda Taku , Ishikawa Kosuke , Murao Naoki , Fuyama Kanako , Yamamoto Yuhei , Hayashi Toshihiko
Published: September 2023

Background
This study aimed to clarify the relationship between primary site and lymphatic drainage pattern for malignant skin tumors in the head and neck region. Malignant melanoma and squamous cell carcinoma in the head and neck region are known to have poor prognosis because of lymph node metastasis. Nevertheless, numerous aspects of lymphatic drainage patterns remain elusive.
Methods
We statistically analyzed data of 47 patients with malignant skin tumors in the head and neck region. Information was collected on the patients' clinical characteristics, primary tumor site, and lymphatic drainage patterns.
Results
The parotid lymph nodes drained the greatest amount of lymph from skin tumors of the head and neck. Important lymphatic drainage pathways were the superficial cervical nodes for primary tumors in the buccal/nasal region, level IA and level IB nodes for primary tumors in the lip region, the occipital nodes, posterior auricular nodes, and level VA nodes in the parietal/occipital region, and the preauricular nodes in the auricular region.
Conclusion
These findings have considerable significance in terms of understanding lymphatic drainage patterns for malignant skin tumors in the head and neck and may be useful for clinical decision-making and when planning treatment. Further research and clinical applications are expected to contribute to an improved prognosis in patients with cutaneous head and neck malignancies.
Jordanian Population Knowledge, Attitude and Practices on the Uses of Antidiabetics for Weight Loss Purposes: A Cross Sectional Study
Authors: Abutaima Rana , Barakat Muna , Sawan Hana Abu , ALomari Shatha , Mhaidat Nizar
Published: September 2023

Background Obesity became a recent pandemic, especially, during the Corona Virus Pandemic of 2019 (COVID-19) lockdown. Therefore, people started to adopt effortless methods to lose weight such as certain antidiabetic medications.Objectives To evaluate Jordanian population knowledge, attitude and practices towards the use of antidiabetic medications such as (Ozempic®), (Saxenda®), (Mounjaro®) and (Glucophage®) for weight loss.Method A self-administered validated online questionnaire was developed and disseminated to public. Data were extracted to examine descriptive statistics. Linear regression was performed to evaluate predictors of knowledge and attitude. A P-value ≤ 0.05 was chosen to indicate statistical significance.Results Total of 389 responses were analyzed, 65.6% females, 54.2% married, 78.1% living in the center of Jordan, 35.5% overweight and 26.5% have > 1000 Jordanian Dinars (JOD) monthly income. 57% think that antidiabetics could be used for weight loss. 47.27%, 44.55%, 68.18% recognized (Ozempic®), (Saxenda®), (Mounjaro®) and (Glucophage®) use for weight loss, respectively and 12.3% of participants used medications to lose weight. Neutral attitude was observed. Gender and body mass index (BMI) were significant predictors of knowledge (P < 0.001, P = 0.002, respectively).Conclusion Use of (Ozempic®), (Saxenda®) and other antidiabetics to lose weight become a common practice. The results of this study suggests supervising prescription and dispensing to avoid misuse, especially, in people who are contraindicated to use them.
A method to enhance the nonlinear magnetic plucking for vibration energy harvesters
Authors: Rosso Michele , Cuccurullo Simone , Perli Filippo Pietro , Maspero Federico , Corigliano Alberto , Ardito Raffaele
Published: September 2023

In this work, a technique to improve the magnetic plucking phenomenon for frequency up-converting piezoelectric energy harvesters is presented. The technique involves using shielded magnets with Neodymium-iron-boron alloy polarized in the opposite direction on a main magnet. The phenomenon is investigated both at the computational and the experimental level. Subsequently, simulations on a mesoscale piezoelectric energy harvester are presented which demonstrate a gain of 17 times if the magnets are shielded in comparison with the classical plucking (i.e. without shielding). The technique finds useful applications and benefits in the field of low-speed and low-frequency vibration energy harvesting, such as in actuation and sensing.
Effect of Gravity Orientation on Flickering Characteristics of Premixed Conical Flame
Authors: Qian Chenghao , Yang Yao , Wang Gaofeng , Kirkunova Anastasia , Hu Keqi
Published: September 2023

Experimental and numerical simulation methods were employed to investigate the effect of gravity orientation on the dynamics of premixed conical flames. The study focused on a typical propane-air flame established on a Bunsen burner. Experiments and simulations were conducted under normal gravity (+ g), reverse gravity (-g), and transverse gravity (⊥g). In the initial phase of the research, the time-averaged shape of the flame under these gravity orientations was examined using flame chemiluminescence imaging. Particle Image Velocimetry (PIV) experiments and Direct Numerical Simulation (DNS) were performed to capture transient information, allowing for the visualization of the flame's flickering motion. The Dynamic Mode Decomposition (DMD) method was applied to analyze the velocity results, providing further insights into the mode and phase characteristics of flame dynamics. Additionally, the frequencies of flame flickering were determined through heat release signal experiments, revealing the relationship between gravity direction and flickering frequency. The study also validated a well-known empirical correlation for the + g case and attempted to adopt a formula for the ⊥g case.
Clinical features analysis of 75 deceased donors maintained in ICU
Authors: YAO Zhiyuan , LIU Yu , ZHAN Liying , QIU Tao , LI Guang , CHEN Zhongbao , FANG Xiaoyu , LIU Zhou , WU Wei , LIAO Zhaomin , XIA Wenfang
Published: September 2023

Objective
To summarize and analyze the integrated management program of 75 deceased donors maintained in ICU of our hospital, so as to promote the development of organ transplantation.
Methods
The data deceased donors maintained in ICU of our hospital from June 2020 to January 2022 were collected. The basic data, laboratory examination results, disease distribution and maintenance measures were retrospectively studied.
Results
75 patients were included, with a sex ratio (M/F) of 90.67% vs 9.33%, a median age of 55, a median ICU length of 4 days. Donors with higher APACHE II scores tended to enter the donation process faster (P=0.001). The primary disease of donors was mainly cerebral hemorrhage (53, 70.67%). 53 pathogens were detected in 58 patients (infection rate: 77.33%), mainly bacteria (42, 79.25%, Gram-negative mainly), Klebsiella pneumoniae, Acinetobacter baumannii and Escherichia coli were the most detected. 96.00% (72/75) donors successfully completed donation, mainly donation after cardiac death (65, 86.67%). 229 large organs and tissues were obtained from 72 donors, with an acquisition ratio of 1:3.14. The acquisition ratio of donors of different ages was statistically different (P<0.001). The overall organ utilization rate was 96.51% (221/229), and the kidney utilization rate in our hospital was 95.14% (137/144).
Conclusion
ICU plays an irreplaceable role in organ transplantation. ICU staffs familiarize the integrated management program of deceased donors, which is helpful to promote the development of organ transplantation.
A rare case of acute respiratory distress syndrome driven by parathyroid storm: a case report
Authors: Wu Changde , Chang Wei , Huang Minmin , Guo Lanqi , Fan Xiang , Yang Yi , Liu Ling
Published: September 2023

Background: Acute respiratory distress syndrome (ARDS) driven by parathyroid storm-associated hypercalcemiahas rarely been documented in the literature. This underreported complication leads to inappropriate management, resulting in uncertain outcomes.
Case presentation: We report a case of a 41-year-old female who presented with parathyroid storm and hypercalcemia-induced ARDS. Infection screens were negative. After receiving medical treatment with invasive ventilation and extracorporealmembrane oxygenation, her respiratory condition improved gradually. Her bronchoscopic lung biopsy pathology showed alveolar calcium deposition. A chestcomputed tomography scan also demonstrated improvement in pulmonary calcification, although it did not completely disappear even 2 months after blood calcium decreased to normal after radiofrequency ablation of parathyroid adenoma.
Conclusion: Although rare, unexplained respiratory failure in patients with parathyroid crisis-associated hypercalcemia should be considered for the possibility of ARDS due to hypercalcemia.