bluuebunny/crossref_metadata_2025 huggingface dataset:
English learning model based on social media
Authors:   Politeknik Negeri Malang, Indonesia, Imron Aly , Wahyuni Erly ,   Universitas Muhammadiyah Malang, Indonesia, Mandang Selvie Ratna Ivone ,   Politeknik Negeri Manado, Indonesia, Mustain Kun ,   Politeknik Negeri Malang, Indonesia, Susanto Budi ,   Politeknik Negeri Bali, Indonesia
Published: February 2024

This research endeavours to address the pressing need for a tailored English language learning model for students enrolled in Polytechnic institutions specializing in Food and Beverage studies. Recognizing the pivotal role of English proficiency in global culinary communication, we aim to design a comprehensive learning model. This model harnesses the potential of social media as an innovative pedagogical tool to enhance language skills, equipping students with the linguistic competence essential for success in their field. A mixed-methods approach was employed, combining quantitative and qualitative research methodologies. Initially, a thorough needs analysis was conducted to determine the specific language requirements of Food and Beverage students. Subsequently, an adaptive learning model was designed, incorporating social media platforms as supplementary tools for language acquisition. The model was tested within the curriculum of a Polytechnic institution, utilizing a pre-test/post-test design to assess the impact on students' language proficiency. The results of our study indicate a significant improvement in the English language proficiency of students following the implementation of the learning model. Quantitative analysis of pre-test and post-test scores revealed a statistically significant increase in language skills. Moreover, qualitative feedback from students and educators highlighted the model's efficacy in enhancing engagement and motivation, thereby fostering a more dynamic and effective learning environment. This research contributes to the intersection of language education and the Food and Beverage industry by providing a specialized English language learning model. The innovative integration of social media platforms as supplementary tools demonstrates the adaptability and effectiveness of this approach. The findings affirm the model's potential to bridge the gap between industry-specific language requirements and educational curricula, empowering students with the linguistic competence necessary for global success in the Food and Beverage sector. This study underscores the transformative potential of technology-enhanced language learning in specialized fields and lays the foundation for future research and pedagogical innovation. Ultimately, this research seeks to empower students, educators, and the industry at large, enriching the landscape of culinary education and communication on a global scale.
Benefactive declarative sentences in Indonesian: The role of the beneficiary in social behavior representation
Authors:   Faculty of Cultural Sciences, University of Jember, Indonesia, Asrumi Asrumi , Suyanto Budi ,   Faculty of Cultural Sciences, University of Jember, Indonesia, Setiari Agustina Dewi ,   Faculty of Cultural Sciences, University of Jember, Indonesia, Muji Muji ,   Faculty of Teacher Training and Education, University of Jember, Indonesia
Published: February 2024

Language shows a nation's character. Can Indonesian sentences with the predicate benefactive verbs show the character of the Indonesian nation? Benefactive sentences are sentences that have a subject argument as the beneficiaries and an object argument as the agent or vice versa. Subjects as agents and objects as beneficiaries. Beneficiaries can be oneself and can also be other people or personal things. In the Indonesian language by the beneficial declarative sentences, it can be determined the dominance of the beneficial. The problem is, what is the impact of the dominance of the beneficiary role on the behavior of Indonesian language users and what is the agent's relationship with our social beneficiaries and its social impact? The purpose of this study is to reveal the impact of dominance of the role of beneficiary in the benefactive verb on the declarative sentence of the Indonesian language, and the relationship of the agent with the beneficiary of circumstances or other people and their social impact. This research is qualitative research. The research data is in the form of declarative sentences in Indonesian which are predicated of benefactive verbs in people's speech, elementary-high school Indonesian language books, middle school economics books, and research data exploration. Research data was collected using observation and documentation methods using note-taking techniques and analyzed using distributional methods, interpretation, and analysis of meaning components. The results of this research can be concluded that beneficial declarative sentences in Indonesian show the behavior of the Indonesian people which is selfish, liberalist, and hedonistic, not socialist. The implications of these characteristics are for the nation's behavior, including corrupt public officials (only concerned with personal, family, and group profits)
Indonesian EFL students’ perceptions of TikTok utilization in EFL learning
Authors:   English for Business and Professional Communication Dept, State Polytechnic of Bali, Indonesia, Suciani Ni Ketut , Sanjaya I Nyoman Suka ,   English for Business and Professional Communication Dept, State Polytechnic of Bali, Indonesia, Sitawati Anak Agung Raka ,   English for Business and Professional Communication Dept, State Polytechnic of Bali, Indonesia, Wariyati Wariyati ,   Universitas Muslim Nusantara Al Washliyah, Indonesia
Published: February 2024

Despite its increasing popularity among young adults, TikTok has been very slow in finding its way into the English as a foreign language (EFL) teaching profession. Yet before introducing the application into the EFL classrooms, it is no doubt imperative to discern what is preferable among EFL learners. Thus, the aim of the present study was to examine the extent to which EFL learners perceive TikTok as facilitating their learning. To this end, the participants (N = 31) were asked to fill out a short, online questionnaire to gather information about (i) whether they utilized TikTok as an affordance for their EFL learning and (ii) whether they perceive its integration into the EFL classrooms as facilitative of their learning. The findings revealed that although they did not explicitly mention that they used TikTok as an affordance for their EFL learning, they held a belief that TikTok is effective in promoting their English proficiency. According to the students, there were three factors of note which contribute to the effectiveness of TikTok, namely abundant authentic input availability, easy-to-grasp information and availability of free tuition related to English language learning. Pedagogically, it implies that TikTok is worth integrating into the EFL classrooms.
Buried in the Borderlands: An Artefact Typology and Chronology for the Netherlands in the Early Medieval Period on the Basis of Funerary Archaeology
Authors: Tim van Tongeren
Published: February 2024

Buried in the Borderlands is the result of a large-scale yet detailed study of early medieval grave furnishings from the Netherlands, aiming at the creation of a comprehensive artefact typology and updated relative chronology for this under-explored period in the Low Countries.

During the early medieval period, the present-day Netherlands occupied a unique position as a border zone between the Frisians, Saxons and Merovingian Franks. For this large-scale research, grave goods were analysed from approximately 2500 inhumations from 21 cemeteries distributed across the country and incorporating the material culture of the aforementioned peoples. The resulting database was studied using the statistical research method Correspondence Analysis. A date was generated for individual artefact types and grave contexts. Creating the finds database confirmed that the varied Dutch material culture of the early medieval period cannot be analysed by only using a German or French typology. To simplify and locally embed future research as well as to allow for international comparison, a holistic typology has been developed which includes artefact types with roots in Germany, France and the surrounding countries as well as locally produced objects. All artefact types are provided with a revised date based on Dutch find contexts.
Dimension reduction and homogenization of composite plate with matrix pre-strain
Authors: Chakrabortty Amartya , Griso Georges , Orlik Julia
Published: February 2024

This paper focuses on the simultaneous homogenization and dimension reduction of periodic composite plates within the framework of non-linear elasticity. The composite plate in its reference (undeformed) configuration consists of a periodic perforated plate made of stiff material with holes filled by a soft matrix material. The structure is clamped on a cylindrical part. Two cases of asymptotic analysis are considered: one without pre-strain and the other with matrix pre-strain. In both cases, the total elastic energy is in the von-Kármán (vK) regime ( ε 5 ). A new splitting of the displacements is introduced to analyze the asymptotic behavior. The displacements are decomposed using the Kirchhoff–Love (KL) plate displacement decomposition. The use of a re-scaling unfolding operator allows for deriving the asymptotic behavior of the Green St. Venant’s strain tensor in terms of displacements. The limit homogenized energy is shown to be of vK type with linear elastic cell problems, established using the Γ-convergence. Additionally, it is shown that for isotropic homogenized material, our limit vK plate is orthotropic. The derived results have practical applications in the design and analysis of composite structures.
Design and development of prime herder optimization based BiLSTM congestion predictor model in live video streaming
Authors: Adhau Tejas Prashantrao , Gadicha Vijay
Published: February 2024

High-quality content for the user in video streaming services depends critically on the ability to predict the continuous user’s quality of experience (QoE). However, continuous QoE prediction has proven challenging due to the complexity imposed by the temporal dependencies in QoE data and the non-linear correlations among QoE impact elements. In this research congestion prediction model is developed using the prime herder optimization-based BiLSTM (PHO-based BiLSTM). The input database is first gathered from the NIMS and darpa99 week 1 database and, the data collection is analyzed and the packet information is extracted after that the extracted features are then fed into the optimized BiLSTM classifier to train the classifier. The classifier’s hyperparameters are successfully tuned by the recommended prime herder optimization, which is made by fusing the herding characteristics of a prime sheepdog and herder optimization. Based on the traffic congestion prediction achievements, at training percentage (TP) 90, the accuracy is 94.81%, specificity is 94.90%, and mean square error (MSE) is 4.91 respectively for D1, similarly based on D2 the accuracy is 95.62%, specificity is 95.96%, and MSE is 0.38 respectively.
Analysis of multimedia network data security based on routing algorithm
Authors: Zheng Li , Zheng Yuntian
Published: February 2024

In today’s society, the application of multimedia data is increasing, and the accompanying data security is also an important issue. This paper will analyze the data security of multimedia network based on routing algorithm. The advantages of wireless local area networks (WLAN) and ad hoc networks are combined in wireless mesh networks (WMNs), which have steadily grown to be a reliable method of wireless broadband access. The application of multi RF and multi-channel technology improves the performance of WMN. However, the limitation that includes the number of wireless network interface cards and channels in the network, results in the great challenges ofrouting and channel allocation in multi RF and multi-channel WMN. Based on AODV algorithm, this paper proposes a new cross layer routing algorithm which is JRCA-AODV algorithm. The simulation results demonstrate that the JRCA-AODValgorithm can successfully increase multiRF multi-channel WMN throughput while lowering packet loss rate and network delay. Take the packet rate of 8 Mbps as an example, the network throughput based on JRCA-AODV algorithm is 1.14 times that of MRMC-AODV algorithm, the packet loss rate based on JRCA-AODV algorithm is 14.06% lower than that of MRMC-AODV algorithm, and the network time delay based on JRCA-AODV algorithm is 14.27% lower than that of MRMC-AODV algorithm. At the same time, JRCA-AODV algorithm can effectively reduce the probability of data loss caused by the competitive and shared access mechanism of the channel, improve the success rate of data transmission, thus reduce the probability of data eavesdropping and tampering in the process of repeated transmission, and improve the security of multimedia network data.This will provide a new direction for promoting the idea of multimedia data security.
First International Conference on Unconventional Animal Models of Alzheimer’s Disease and Aging
Authors: Cogram Patricia , Garduño B. Maximiliano , Ren Bing , Xu Xiangmin
Published: February 2024

The first International Conference on Unconventional Animal Models of Alzheimer’s Disease and Aging (UAMAA) took place on December 13–16, 2023, in Santiago, Chile. The Alzheimer’s disease (AD) research field is currently in search for new and unconventional models that could hold greater translational potential than transgenic mouse models. Thus this UAMAA conference is timely and significant. The event consisted of 6 sessions with talks from 28 world-class scientists from all over the world. These animal models of interest include the degu (Octodon degu), the dog (Canis familiaris), and certain species of nonhuman primates that may better recapitulate neuropathology and cognitive impairments in human AD. Our conference has provided a formal forum to discuss and highlight new research directions, alternative animal models, and innovative approaches for the AD and aging research field.
Somatic CAG Repeat Stability in a Transgenic Sheep Model of Huntington’s Disease
Authors: Handley Renee R. , Reid Suzanne J. , Burch Zoe , Jacobsen Jessie C. , Gillis Tammy , Correia Kevin , Rudiger Skye R. , McLaughlin Clive J. , Bawden C. Simon , MacDonald Marcy E. , Wheeler Vanessa C. , Snell Russell G.
Published: February 2024

Somatic instability of the huntingtin (HTT) CAG repeat mutation modifies age-at-onset of Huntington’s disease (HD). Understanding the mechanism and pathogenic consequences of instability may reveal therapeutic targets. Using small-pool PCR we analyzed CAG instability in the OVT73 sheep model which expresses a full-length human cDNA HTT transgene. Analyses of five- and ten-year old sheep revealed the transgene (CAG)69 repeat was remarkably stable in liver, striatum, and other brain tissues. As OVT73 sheep at ten years old have minimal cell death and behavioral changes, our findings support instability of the HTT expanded-CAG repeat as being required for the progression of HD.
Environment-driven evolution analysis of a product: A case study of braking system evolution
Authors: Razavi S. R. , Yang J. , Yang Y. , Akgunduz A. , Bhuiyan N. , Zeng Y.
Published: February 2024

In response to evolving societal and technical demands, this research explores the dynamic landscape of product evolution, focusing on the case study of braking systems. Acknowledging the critical role of product evolution analysis in design phases, the study introduces the Environment-Based Design (EBD) methodology. EBD emphasizes environmental analysis before delving into product specifics, employing tools like Recursive Object Model (ROM) diagrams and questioning-and-answering analyses. The paper systematically unfolds with a literature review highlighting various design methodologies, followed by the EBD application in a braking system evolution analysis. Trends in environment components are dissected, emphasizing the increasing influence of the human environment. The discussion underlines the significance of analyzing environment components in product evolution and asserts EBD’s applicability. Despite limitations, such as the exclusive focus on braking systems, the study contributes to understanding product evolution dynamics and advocates for the continued exploration of EBD across diverse products and cultural contexts.
RETRACTED: An improved constant current step-based grey wolf optimization algorithm for photovoltaic systems
Authors: Dagal Idriss , Akín Burak , Dari Yaya Dagal
Published: February 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Robust multi-frequency band joint dictionary learning with low-rank representation
Authors: Ding Huafeng , Shang Junyan , Zhou Guohua
Published: February 2024

Emotional state recognition is an important part of emotional research. Compared to non-physiological signals, the electroencephalogram (EEG) signals can truly and objectively reflect a person’s emotional state. To explore the multi-frequency band emotional information and address the noise problem of EEG signals, this paper proposes a robust multi-frequency band joint dictionary learning with low-rank representation (RMBDLL). Based on the dictionary learning, the technologies of sparse and low-rank representation are jointly integrated to reveal the intrinsic connections and discriminative information of EEG multi-frequency band. RMBDLL consists of robust dictionary learning and intra-class/inter-class local constraint learning. In robust dictionary learning part, RMBDLL separates complex noise in EEG signals and establishes clean sub-dictionaries on each frequency band to improve the robustness of the model. In this case, different frequency data obtains the same encoding coefficients according to the consistency of emotional state recognition. In intra-class/inter-class local constraint learning part, RMBDLL introduces a regularization term composed of intra-class and inter-class local constraints, which are constructed from the local structural information of dictionary atoms, resulting in intra-class similarity and inter-class difference of EEG multi-frequency bands. The effectiveness of RMBDLL is verified on the SEED dataset with different noises. The experimental results show that the RMBDLL algorithm can maintain the discriminative local structure in the training samples and achieve good recognition performance on noisy EEG emotion datasets.
A text extraction framework of financial report in traditional format with OpenCV
Authors: Wei Jiaxin , Yang Jin , Liu Xinyang
Published: February 2024

Due to intensified off-balance sheet disclosure by regulatory authorities, financial reports now contain a substantial amount of information beyond the financial statements. Consequently, the length of footnotes in financial reports exceeds that of the financial statements. This poses a novel challenge for regulators and users of financial reports in efficiently managing this information. Financial reports, with their clear structure, encompass abundant structured information applicable to information extraction, automatic summarization, and information retrieval. Extracting headings and paragraph content from financial reports enables the acquisition of the annual report text’s framework. This paper focuses on extracting the structural framework of annual report texts and introduces an OpenCV-based method for text framework extraction using computer vision. The proposed method employs morphological image dilation to distinguish headings from the main body of the text. Moreover, this paper combines the proposed method with a traditional, rule-based extraction method that exploits the characteristic features of numbers and symbols at the beginning of headings. This combination results in an optimized framework extraction method, producing a more concise text framework.
RETRACTED: Enhancing plant leaf disease detection: Integrating krill herd optimization-surf features and deep belief network
Authors: Bala B. Kiran , Sekhar J.C. , Al Ansari Mohammed Saleh , Rao Vuda Sreenivasa
Published: February 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Chinese-Vietnamese cross-lingual event retrieval method based on knowledge distillation
Authors: Gao Shengxiang , He Zhilei , Yu Zhengtao , Zhu Enchang , Wu Shaoyang
Published: February 2024

Cross-lingual event retrieval is an information retrieval task aimed at cross-lingual event retrieval among multiple languages to find text or documents related to a specific event. Specific to Chinese-Vietnamese cross-language event retrieval, it involves using Chinese as a query to retrieve Vietnamese documents related to the query event. The critical issue is how to efficiently align query and document representations with limited resources. Existing cross-language pre-training models are trained on large-scale multilingual corpora, but their training goals do not include explicit language alignment tasks. Due to the uneven distribution of training corpora between different languages, these models have The problem of language bias. Therefore, this linguistic bias is also inherited in cross-lingual retrieval based on these models. To solve this problem, this paper proposes a Chinese-Vietnamese cross-lingual event retrieval method based on knowledge distillation. This approach enables the model to learn good query-document matching features from monolingual retrieval by transferring knowledge from high-resource to low-resource languages. By enhancing the alignment between queries and documents in different languages in a shared semantic space, the method improves the performance of Chinese-Vietnamese cross-lingual event retrieval.
FOD-YOLO NET: Fasteners fault and object detection in railway tracks using deep yolo network1
Authors: Brintha K. , Joseph Jawhar S.
Published: February 2024

Automated railway security systems prevent train collisions with trackside obstructions that cause accidents in high-speed railways. Rail safety is being improved and accident rates reduced through continuous research. A rapid advancement in deep learning has promoted new possibilities for research in this field. In this work, a novel deep learning-based FOD-YOLO net is proposed for detecting the fasteners faults and objects in the railway tracks. There are two basic components in the deep learning-based YOLOv8: the backbone and the head. YOLOv8 utilizes an improved version of the CSPDarknet53 network for detecting objects on the railway track. The head of YOLOv8 consists of EfficientNet with various convolutional layers with squeeze and excitation blocks for detecting any defect in the track fasteners. These layers are liable for detecting the objectness scores, bounding boxes and class probabilities structured with fully connected layers for the objects and faults in tracks. Based on the results from the Yolo network, the alert message is sent to the loco pilot to avoid accidents using fuzzy logic. The experimental fallouts of proposed FOD-YOLO net achieve higher accuracy and yields better evaluation results with 98.14% accuracy, 98.84% precision and 95.94% recall. From the experimental results, the FOD-YOLO net improves the overall accuracy range by 5.44%, 4.72%, 0.73%, and 13.18% better than Fast RCNN, YOLOv5s-VF, YOLO-GD, and 2D-SSA + Deep network respectively.
Abnormal-trajectory detection method based on sub-trajectory classification and outlier-factor acquisition
Authors: Xu Dongsheng , Chen Chuanming , Jin Qi , Zheng Ming , Ni Tianjiao , Yu Qingying
Published: February 2024

Abnormal-trajectory detection can be used to detect fraudulent behavior of taxi drivers transporting passengers. Aiming at the problem that existing methods do not fully consider abnormal fragments of trajectories, this paper proposes an abnormal-trajectory detection method based on sub-trajectory classification and outlier-factor acquisition, which effectively detects abnormal sub-trajectories and further detects abnormal trajectories. First, each trajectory is reconstructed using the turning angles and is divided into multiple sub-trajectories according to the turning angle threshold and trajectory point original acceleration. The sub-trajectories are then classified according to the extracted directional features. Finally, the multivariate distances between angular adjacent segments are calculated to obtain the outlier factor, and abnormal sub-trajectories are detected. The sum of the lengths of the abnormal sub-trajectories is used to calculate the outlier score and identify abnormal trajectories. Based on experimental results using real trajectory datasets, it has been found that the proposed method performs better at detecting abnormal trajectories than other similar methods.
RETRACTED: Monitoring and analysis of physical activity and health conditions based on smart wearable devices
Authors: Yu Jie , Zhang Jubin
Published: February 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Classification of high-dimensional imbalanced biomedical data based on spectral clustering SMOTE and marine predators algorithm
Authors: Qin Xiwen , Zhang Siqi , Dong Xiaogang , Shi Hongyu , Yuan Liping
Published: February 2024

The research of biomedical data is crucial for disease diagnosis, health management, and medicine development. However, biomedical data are usually characterized by high dimensionality and class imbalance, which increase computational cost and affect the classification performance of minority class, making accurate classification difficult. In this paper, we propose a biomedical data classification method based on feature selection and data resampling. First, use the minimal-redundancy maximal-relevance (mRMR) method to select biomedical data features, reduce the feature dimension, reduce the computational cost, and improve the generalization ability; then, a new SMOTE oversampling method (Spectral-SMOTE) is proposed, which solves the noise sensitivity problem of SMOTE by an improved spectral clustering method; finally, the marine predators algorithm is improved using piecewise linear chaotic maps and random opposition-based learning strategy to improve the algorithm’s optimization seeking ability and convergence speed, and the key parameters of the spectral-SMOTE are optimized using the improved marine predators algorithm, which effectively improves the performance of the over-sampling approach. In this paper, five real biomedical datasets are selected to test and evaluate the proposed method using four classifiers, and three evaluation metrics are used to compare with seven data resampling methods. The experimental results show that the method effectively improves the classification performance of biomedical data. Statistical test results also show that the proposed PRMPA-Spectral-SMOTE method outperforms other data resampling methods.
Intelligent control for solar-electric vehicles: integrating gannet optimization algorithm and quantum neural network for power tracking and high gain conversion
Authors: Arunagirinathan Sumithara , Subramanian Chitra
Published: February 2024

This paper presents a hybrid approach for optimizing the maximum power point tracking of photovoltaic (PV) systems in electric vehicles. The hybrid technique involves the simultaneous utilization of the Gannet Optimization Algorithm (GOA) and Quantum Neural Network (QNN), collectively referred to as the GOA-QNN technique. The primary aim is to enhance the efficiency and maximize the power output of PV systems. The proposed hybrid methodology boosts the performance of the photovoltaic system by managing the power interface. A high step-up DC/DC converter is employed to adjust the photovoltaic source power and load, ensuring optimal power transfer under various operating conditions. The proposed method optimally determines the duty cycle of the converter. Subsequently, the model is implemented in the MATLAB/Simulink platform, and its execution is evaluated using established procedures. The results clearly demonstrate the superiority of the proposed method over existing approaches in terms of power quality, settling time, and controller stability. The proposed technique achieves an impressive efficiency level of 95%, exceeding the efficiency of other existing techniques.
Process control of chemical dynamic system based on multi-strategy mayfly optimization algorithm
Authors: Li Jingyan , Mo Yuanbin , Hong Lila , Gong Rong
Published: February 2024

Dynamic optimization problems exist widely in chemical industry, and its operational variables change with the evolution of both space and time. Therefore, dynamic optimization problems have important research significance and challenges. To solve this problem, a multi-strategy mayfly optimization algorithm (MMOA) combined with control variable parameterization method(CVP) is proposed in this paper. MMOA introduces three improvements on the basis of the original algorithm, namely, circle chaos crossover strategy, center wandering strategy and boundary correction strategy. The hybrid strategy can better balance the exploration and exploitation ability of the algorithm. Based on MATLAB simulation environment, MMOA was evaluated. The experimental results show that MMOA has excellent performance in solving precision, convergence speed and stability for the benchmark function. For the six classical chemical dynamic optimization problems, MMOA obtained the performance indexes of 0.61071, 0.4776, 0.57486, 0.73768, 0.11861 and 0.13307, respectively. Compared with the data in the previous literature, MMOA can obtain more accurate control trajectory and better performance indicators. It provides an effective way to solve the dynamic optimization problem.
Enhancing Data Use Ontology (DUO) for health-data sharing by extending it with ODRL and DPV
Authors: Pandit Harshvardhan J. , Esteves Beatriz
Published: February 2024

The Global Alliance for Genomics and Health is an international consortium that is developing the Data Use Ontology (DUO) as a standard providing machine-readable codes for automation in data discovery and responsible sharing of genomics data. DUO concepts, which are encoded using OWL, only contain the textual descriptions of the conditions for data use they represent, and do not specify the intended permissions, prohibitions, and obligations explicitly – which limits their usefulness. We present an exploration of how the Open Digital Rights Language (ODRL) can be used to explicitly represent the information inherent in DUO concepts to create policies that are then used to represent conditions under which datasets are available for use, conditions in requests to use them, and to generate agreements based on a compatibility matching between the two. We also address a current limitation of DUO regarding specifying information relevant to privacy and data protection law by using the Data Privacy Vocabulary (DPV) which supports expressing legal concepts in a jurisdiction-agnostic manner as well as for specific laws like the GDPR. Our work supports the existing socio-technical governance processes involving use of DUO by providing a complementary rather than replacement approach. To support this and improve DUO, we provide a description of how our system can be deployed with a proof of concept demonstration that uses ODRL rules for all DUO concepts, and uses them to generate agreements through matching of requests to data offers. All resources described in this article are available at: https://w3id.org/duodrl/repo.
Lossless compression-based detection of osteoporosis using bone X-ray imaging
Authors: Alshamrani Khalaf , Alshamrani Hassan A.
Published: February 2024

BACKGROUND:

Digital X-ray imaging is essential for diagnosing osteoporosis, but distinguishing affected patients from healthy individuals using these images remains challenging.

OBJECTIVE:

This study introduces a novel method using deep learning to improve osteoporosis diagnosis from bone X-ray images.

METHODS:

A dataset of bone X-ray images was analyzed using a newly proposed procedure. This procedure involves segregating the images into regions of interest (ROI) and non-ROI, thereby reducing data redundancy. The images were then processed to enhance both spatial and statistical features. For classification, a Support Vector Machine (SVM) classifier was employed to distinguish between osteoporotic and non-osteoporotic cases.

RESULTS:

The proposed method demonstrated a promising Area under the Curve (AUC) of 90.8% in diagnosing osteoporosis, benchmarking favorably against existing techniques. This signifies a high level of accuracy in distinguishing osteoporosis patients from healthy controls.

CONCLUSIONS:

The proposed method effectively distinguishes between osteoporotic and non-osteoporotic cases using bone X-ray images. By enhancing image features and employing SVM classification, the technique offers a promising tool for efficient and accurate osteoporosis diagnosis.
A Comprehensive Overview on Pharmacological and Therapeutic Insights of Solanum nigrum Linn
Authors: Ahmed Md Sohel , Akter Irin
Published: February 2024

_Solanum nigrum _is a traditional Chinese bush renowned for its dynamic therapeutic activities in the Indian and Chinese systems of medicine. It is a typical, palatable herbal remedy that belongs to the family Solanaceae. This overview assembles the prospective pharmacological and medicinal significance of the last three decades' accomplishments of scholarly reports from internet sources and publications. According to several literature reviews, _Solanum nigrum_ encompasses a variety of phytochemical compounds that could be isolated and identified using various extraction techniques. The major chemical components of this herb are alkaloids, glycoproteins, polysaccharides, and phenolic compounds with a broad spectrum of pharmacological outcomes such as anticancer, immunostimulant, antibacterial, antidiabetic, antiviral, antiinflammatory, antioxidant, antipyretic, antidiarrheal, cardioprotective, anti-hyperlipidemic, anti-ulcerogenic, hepatoprotective, anti-seizure, anti-larvicidal, anti-allergic, anti-asthmatic, and neuropharmacological efficacy. Recently, scientists and researchers have been searching for potentially biologically active plants due to the increasing toxicity and adverse effects of modern synthetic drugs. As every part of _Solanum nigrum _contains a variety of therapeutically active phytochemicals, it could be a significant source for scientists to conduct further research and discover the proper mechanism for preventing diseases. In conclusion, _Solanum nigrum_ emerges as a valuable resource in the pursuit of alternative therapeutic options. Its multifaceted pharmacological properties and traditional usage underscore its potential significance in modern healthcare.
Probabilistic Assessment of the Heavy Metal Pollution in Debrecen’s Topsoil
Authors: Fehér Zsolt Zoltán , Nagy Péter Tamás
Published: February 2024

Understanding better the spatial and subsurface infiltration patterns of heavy metal distribution in urban soils can help in environmental and health risk assessment and the development of effective environmental policy. The present paper investigates the overall environmental quality of the Debrecen area in terms of heavy metal pollution and describes a simulation procedure for the spatial and statistical patterns of heavy metals in atmospheric deposited dust samples and the spatial diversity of health vulnerability. The research is based on the evaluation of 300 soil samples from Debrecen and its surroundings. Maps of topsoil major heavy metal distributions, including As, Cd, Cr, Co, Cu, Mo, Ni, Pb, and Zn, were obtained using sequential Gaussian simulation. Then, the pollution levels were determined from the stochastic maps, thus obtaining a comprehensive quantitative pollution characterization of the nine elements in the city. According to the results, the potential risk of pollutants to the environment is in the order of Cd > Mo > As > Cu > Ni > Cr > Pb > Co > Zn, with a pollution load of 0.66. Cd, Mo, and Cu are the main toxic pollutants in Debrecen topsoils, with mean concentrations of 1.9 mg/kg, 77.3 mg/kg, and 1.4 mg/kg, exceeding the threshold values by 0.9 mg/kg, 2.3 mg/kg, and 0.4 mg/kg, respectively. The stochastic models assessed the uncertainties and risks related to the spatial distribution of heavy metals in soil within the contaminated areas, and a positive correlation can be found between the increase in pollution values above the predetermined threshold limits and the corresponding increase in threshold levels. Additionally, there is a consistent decrease in the relative area of excess contamination, although the ecological pollution index (96.9) revealed the Debrecen region as a hotspot area for considerable risk of contamination that needs continuous monitoring and remediation.
IMPROVING SCIENCE LEARNING OUTCOMES USING SNAKES AND LADDERS GAME MEDIA IN PRIMARY SCHOOLS / PENINGKATAN HASIL BELAJAR IPA MENGGUNAKAN MEDIA PERMAINAN ULAR TANGGA DI MADRASAH IBTIDAIYAH
Authors: Ulfa Mariya , Nadhif Moh. , Salamah Umi
Published: February 2024

Madrasah Ibtidaiyah merupakan awal perjalanan bagi peserta didik untuk memanfaatkan ilmu yang di dapat agar bermakna bagi kehidupannya. Pada kurikulum 2013 materi IPA hanya diberikan kepada jenjang kelas tinggi saja. IPA singkatan dari Ilmu Pengetahuan Alam merupakan kumpulan pengetahuan tentang gejala alam. IPA sering dianggap sebagai mata pelajaran paling sulit. Hal ini terlihat pada peserta didik kelas IV MI Al Fattah Malang. Dari hasil belajar IPA pada akhir semester I masih banyak yang belum mencapai nilai kriteria ketuntasan minimal (KKM). Penelitian ini bertujuan untuk mengetahui hasil belajar awal peserta didik, pelaksanaan pembelajaran IPA menggunakan media permainan ular tangga dan hasil belajar akhir peserta didik setelah menggunakan media permainan ular tangga. Penelitian ini menggunakan rancangan penelitian tindakan kelas yang terdiri dari 2 siklus. Setiap siklus terdiri dari 2 pertemuan. Setiap siklus terdiri dari perencanaan, tindakan, pengamatan, refleksi, perbaikan rencana. Berdasarkan hasil penelitian diperoleh tiga simpulan berikut: hasil belajar awal peserta didik banyak mengalami ketidak tuntasan, penggunaan media permainan ular tangga dapat meningkatkan hasil belajar IPA, dan hasil belajar peserta didik dapat meningkat melalui penggunaan media permainan ular tangga. Hal ini dibuktikan dengan prosentase ketuntasan hasil belajar peserta didik  sebelum dan sesudah menggunakan media permainan ular tangga yaitu dari 9,1% meningkat menjadi 81,82%.
Электрохимическое поведение серебра при поляризации промышленным переменным током в растворе нитрата натрия
Authors: Баешов А , Тулешова Э , Айболова Г
Published: February 2024

В работе показаны отличительные особенности электрохимических процессов,протекающих на серебряном электроде при электролизе промышленным переменным током врастворе нитрата натрия методом рационального математического планирования. Определеныоптимальные условия растворения серебра при исследовании влияния плотности тока наэлектродах, концентрации и температуры электролита, продолжительности электролиза ичастоты переменного тока. Показано, что при поляризации переменным током серебра в парес титановым электродом, устраняется процесс пассивации серебряного электрода, и скоростьрастворения металла возрастает
Атмосферное выпадение тяжелых металлов на территории Республики Казахстан
Authors: Нургалиева Д , Омарова Н , Ташенов А , Нуркасимова М , Махамбет А , Фронтасьева М , Чепурченко О , Глущенко В , Солодухин В , Кабдулкаримова К
Published: February 2024

Метод мхов-биомониторов был применен для оценки атмосферного выпадениятяжелых металлов и других микроэлементов в Юго-Восточной, Северо-Восточной, Северной иЦентральной частях Казахстана Воздуху Европы (UNECE ICP Vegetation). Семьдесят восемьобразцов летом и осенью 2015 года, а тридцать пять образцов летом 2016 года. 46 элементовопределили методом нейтронного активационного анализа на реакторе ИБР-2 ЛабораторииНейтронной Физики Объединенного Института Ядерных Исследований.Тема актуальна, поскольку оценка загрязнения атмосферного воздуха является важнойзадачей охраны окружающей среды. Для прогноза и оценки состояния окружающей средыв последние десятилетия все большее распространение получают методы, основанные набиоиндикации.Основной целью работы являлос определение степени загрязнения токсичными элементамис помощью мхов-биоиндикаторов некоторых районов Казахстана. Для достижения этой цели,поставлены следующие задачи:- изучение видового состава и определение видов мхов;- анализ научных данных об индикационных способностях мхов;- определение степени загрязнения атмосферного воздуха с помощью количественногоанализа- подведение итогов исследований и выводы об уровне загрязнения исследуемой территории.Результаты, представленные в данной работе, получены впервые и могут служить основойдля дальнейших исследований атмосферных загрязнений в других районах Казахстана.
Модельдiк алкандар мен мұнай өнiмiнiң каталитикалық өзгерiске ұшырауы
Authors: Орынбасар Р , Тастанова Л , Апендина А , Закумбаева Г , Туктин Б
Published: February 2024

Гексан, тетрадекан және мұнайдың дизельдiк фракциясының ПФК - 6катализаторда (РН2=2МПа, Vкөл = 3 сағ-1, Н2: шикiзат - 200:1) температураның 300-ден 4000С-те өзгерiске ұшырауы зерттелдi. ПФК - 6 катализаторының гидроизомерлеужәне гидрокүкiртсiздендiру белсендiлiгi жоғары болатыны көрсетiлдi. Қолайлы жағдайлардахалықаралық EN-590 стандартқа сай қату температурасы минус 500С, қалдық күкiрт мөлшерi0,002% қыстық дизель отыны алынды.
Сабинол негiзiнде жаңа триазол мен несепнәр туындылары және олардың биологиялық белсендiлiгi
Authors: Ташенов Е , Сүлеймен Е , Искакова Ж
Published: February 2024

Мақалада Juniperus sabina L. эфир майынан бөлiнiп алынған монотерпеноидсабинолдың Оверманұң қайта топтастыру реакциясымен аллил амин туындысын алу жолыкелтiрiлген. Триазол және несепнәр қосылыстарын дайындау үшiн бастапқы қосылыс ретiндепайдаланған сабинол негiзiндегi аллил аминнiң толық спектрлiк мәлiметтерi ( 1 H және 13 CЯМР, екi өлшемдi 1 H - 1 H COSY, HSQC, HMBC) сипатталған. Бастапқы амин, кетон және 4-нитрофенил азид сияқты қол жетiмдi құрылыс блоктарынан үш компоненттi реакция арқылытриазолдар синтезi орындалды. Несепнәр синтезi амин мен гексил изоцианаты әрекеттесуарқылы жүзеге асырылды. Реакция өнiмдерi 50% -дан астам шығуымен оқшауланып,олардың құрылымы заманауи физика-химиялық талдау әдiстерiнiң көмегiмен дәлелдендi.Алынған жаңа триазолдар мен уреид қосылыстарының цитоуттық, қатерлi iсiкке қарсы,ангидраза, тирозиназа, бутирилхолинестераза және дипептил пептидаза ингибирлеу сияқтыбелсендiлiктерi анықталды.
Влияние нефти на численность различных групп микроорганизмов, участвующих в круговороте азота
Authors: Рысбаева Г , Саттарова А , Исаева А
Published: February 2024

В нефтезагрязненных экосистемах азот является одним из основныхбиогенных элементов. Поддержание его уровня в окружающей среде обеспечивается активнойдеятельностью различных микроорганизмов, принимающих участие в его круговороте. Всвязи с этим представляет интерес проблема влияния нефтяного загрязнения на превращенияазота в почве, что тесно связано с практическими вопросами биодеградации. Во всепериоды исследования численность азофиксирующих микроорганизмов и олигонитрофиловв загрязненной почве оказалась выше, чем незагрязненной. Увеличение интенсивностиазотфиксациии в загрязненной почве может быть обусловлено увеличением в ней содержаниялегкодоступного органического вещества - спиртов, органических кислот, аминокислоти других соединений. Оно коррелирует с увеличением численности групп анаэробныхазотфиксаторов рода Clostridium. Возможно, что азотфиксирующие микроорганизмы могутиспользовать продукты метаболизма углеводородокисляющих микроорганизмов
Синтез и исследование углеродных наноструктурированных добавок для литий ионных аккумуляторов
Authors: Абдрахманова А , Кривченко В , Омарова Н
Published: February 2024

: Высокие показатели удельной емкости являются ключевой характеристикойлитий-ионных аккумуляторов по сравнению с обычными никель – кадмиевыми, никель –металлгидридными исвинцово – кислотными аккумуляторными системами. В настоящеевремя литий-ионные аккумуляторы являются одними из наиболее широко используемыхисточников питания в военных, медицинских, бытовых и промышленных электронныхустройствах. Несмотря на высокие удельные показатели, ряд приложений требует достиженияеще более высоких характеристик, т.к. недостаток энергоемкости приводит к уменьшениюпериода работы устройств между моментами подзарядки батареи. Решение проблемысвязано как с разработкой новых материалов, так и с оптимизацией микроструктурыэлектродов.В связи с этим, данная работа была посвящена изучению влияния синтезированныхи модифицированных наноструктурированных углеродных добавок на функциональныехарактеристики положительного электрода на основе литий железа фосфата для литий-ионныхаккумуляторов. Исследования показали, что использование модифицированных углеродныхнанотрубокметодом Хаммерсавместо коммерческих углеродных нанотрубокзначительноповышает удельные характеристики литий ионных аккумуляторов.
Effects of Injury Prevention Programs on Muscle Flexibility in Children and Adolescents: A Systematic Review
Authors:   Department of Sports Injuries and Corrective Exercises, Faculty of Sports Sciences, Shahid Bahonar University of Kerman, Kerman, Iran., Mahmoudi Foad , Daneshjoo Abdolhamid ,   Department of Sports Injuries and Corrective Exercises, Faculty of Sports Sciences, Shahid Bahonar University of Kerman, Kerman, Iran., Bahiraei Saeid ,   Department of Sports Injuries and Corrective Exercises, Faculty of Sports Sciences, Shahid Bahonar University of Kerman, Kerman, Iran., Sahebozamani Mansour ,   Department of Sports Injuries and Corrective Exercises, Faculty of Sports Sciences, Shahid Bahonar University of Kerman, Kerman, Iran.
Published: February 2024

Purpose: This study aims to conduct a systematic review of injury prevention programs on muscle flexibility in children and adolescents. Methods: Relevant articles were searched in two electronic databases, PubMed and Scopus. An electronic search was conducted on December 1, 2022, without applying any year constraints. Studies that investigated the effect of injury prevention programs on muscle flexibility in subjects under 17 years of age were included. The study method was evaluated using the PEDro scale. Results: A total of 3563 studies were initially retrieved from databases, and data from 5 randomized controlled trials (RCTs) were used in this systematic review. Injury prevention programs (three out of five articles) can improve the muscle flexibility of children and adolescents (before and after the intervention). Conclusion: Injury prevention programs can improve the muscle flexibility of children and adolescents in the intervention group (before and after the intervention); although no improvement was observed in the control group. Therefore, factors, such as duration, frequency and intensity of the program, gender, activity level, type of sport, and sample size are decisive in muscle flexibility.