bluuebunny/crossref_metadata_2025 huggingface dataset:
PCF-RWKV: Product Carbon Footprint Estimation System Based on Large Language Model
Authors: Li Zhen , Tang Peihao , Wang Xuanlin , Liu Xueping , Mou Peng
Published: December 2024

As global climate change intensifies, assessing product carbon footprints has become essential for measuring greenhouse gas emissions throughout a product’s lifecycle, a key factor in achieving sustainable development and emission reduction goals. Traditional lifecycle assessment methods encounter challenges such as subjective product boundary determination and lengthy lifecycle inventory construction. Recent advancements in large language models offer new opportunities for rapid, knowledge-based content generation, yet these models often lack domain-specific training, face data security concerns, and have complex deployment requirements. This study introduces the PCF-RWKV model, which utilizes the RWKV architecture with multiple stacked residual blocks and three task-specialized Low-Rank Adaptations (LoRAs). Trained on a carbon footprint assessment-specific dataset using low-rank adaptive techniques, the model minimizes data interference and memory waste, enabling efficient deployment on consumer-grade single GPUs without relying on cloud storage.By integrating Multi-Agents technology, PCF-RWKV automates the construction of LCI for production processes, aligns production processes with emission factors to calculate carbon footprints, thereby enhancing the efficiency and security of enterprise carbon footprint evaluations and addressing the limitations of traditional methods.
Using AI and NLP for Tacit Knowledge Conversion in Knowledge Management Systems: A Comparative Analysis
Authors: Zaoui Seghroucheni Ouissale , Lazaar Mohamed , Al Achhab Mohammed
Published: December 2024

Tacit knowledge, often implicit and embedded within individuals and organizational practices, plays a crucial role in knowledge management. Converting this tacit knowledge into explicit forms is vital for organizational effectiveness. This paper conducts a comparative analysis of NLP algorithms used for document and report mining in knowledge management systems (KMS) to facilitate the conversion of tacit knowledge. The focus is on algorithms that help extract tacit knowledge from documents and reports, as this knowledge is typically represented in semi-structured and document-based forms in natural language. NLP strategies, including text mining, information extraction, sentiment analysis, clustering, classification, recommendation systems, and affective computing, are explored for their effectiveness in this context. The paper provides a comprehensive analysis of the suitability of various NLP algorithms for tacit knowledge conversion within KMS, offering valuable insights for advancing research in this area.
Penerapan Model Project-based Learning Blended Tutor Sebaya untuk Meningkatkan Hasil Belajar Mata Pelajaran Konsentrasi Keahlian Siswa Kelas XI SMK Ganesha Tama Boyolali
Authors: Syakuro Umar Abdan , Roemintoyo Roemintoyo , Sukatiman Sukatiman
Published: December 2024

Penelitian ini bertujuan untuk mengetahui (1) Capaian Nilai Siswa sebelum diterapkan PjBL Blended Tutor Sebaya di kelas XI (2) Penerapan PjBL Blended Tutor Sebaya di kelas XI. (3) Capaian Nilai Siswa Setelah Penerapan BjBL Blended Tutor Sebaya pada kelas XI (4) Perbedaan Nilai siswa sebelum dan setelah penerapan PjBL Blended Tutor Sebaya kelas XI DPIB SMK Ganesha Tama Boyolali. Penelitian menggunakan metode kuantitatif eksperimen dengan seluruh populasi sebagai sampel. Data diperoleh melalui observasi dan tes hasil belajar, mencakup tiga aspek: pengetahuan, keterampilan, dan sikap, yang dianalisis menggunakan uji Paired Sample T-Test. Hasil penelitian menunjukkan rata-rata nilai awal siswa: aspek pengetahuan 57, keterampilan 59, dan sikap 58. Setelah perlakuan, rata-rata meningkat menjadi 82 untuk pengetahuan, 77 untuk keterampilan, dan 75 untuk sikap. Model ini memiliki delapan sintak, termasuk pre-test, penentuan kelompok, pelaksanaan proyek, hingga evaluasi. Peningkatan rata-rata pada aspek pengetahuan sebesar 20%, keterampilan 17%, dan sikap 18%, dibuktikan dengan nilai signifikan (2-tailed) sebesar 0,000 (<0,05), menunjukkan adanya perbedaan signifikan antara nilai sebelum dan sesudah penerapan model PjBL Blended Tutor Sebaya.
EFFECTIVENESS OF PERICAPSULAR NERVE GROUP BLOCK IN PROXIMAL FEMORAL FRACTURES
Authors:   Republican Research Center of Emergency Medicine, Tashkent, SHARIPOVA VISOLATKHON H. , ABDULKHAMIDOV ALIBEK A. ,   Republican Research Center of Emergency Medicine, Tashkent, ALIMOV AZAMAT H. ,   Republican Research Center of Emergency Medicine, Tashkent
Published: December 2024

Introduction. Currently, a multimodal approach is used for adequate pain relief, which includes regional
analgesia methods in the perioperative pain relief plan, contributing to early activation and reduction of postoperative
complications. Aim. Comparison of the effectiveness of pericapsular nerve block and femoral nerve block in patients
operated under spinal anesthesia for proximal femur fractures in the perioperative period. Materials and Methods.
Depending on the regional analgesia method used, 60 adult patients were randomized into two groups: PENG (n = 30), where pericapsular nerve block was performed, and FNB (n = 30) with femoral nerve block. In the PENG group,
pericapsular nerve block was performed under ultrasound navigation with 15-20 ml of 0.5% bupivacaine solution in
combination with 4 mg of dexamethasone as an adjuvant to the local anesthetic. In the FNB group, femoral nerve
block was performed in a similar manner. The primary endpoint of the study was pain intensity according to a ten-point
numeric rating scale during the first day after surgery. Secondary endpoints included consumption of opioid analgesics
on the first postoperative day, strength of the anterior thigh muscle groups, angle of a comfortable independent patient’s
seat for performing neuraxial anesthesia in the perioperative period, and duration of the block in minutes. Data were
analyzed using SPSS software, a p value of <0.05 was taken as statistically significant. Results and Discussion.
According to a numeric rating scale, the pain intensity was, on average, 50% lower in the PENG group compared to
the FNB group (p<0.05). Blockade of the pericapsular nerve groups caused two times less weakness of the anterior
thigh muscle groups, and this made it possible to activate three times more patients in the early postoperative period
than with the femoral nerve block. Total opioid analgesic consumption was 40% lower in the PENG group (p < 0.05),
potentially reducing their side effects. When positioning patients, 27 patients in the PENG group completed it, which
was 90%, and 16 patients (53.3%) in the FNB group; this was almost 37% lower than in the PENG group. The duration
of the pericapsular nerve block action was 40% longer than that of the femoral nerve block. Conclusions. Pericapsular
nerve block significantly reduces pain, provides less need for opiates, and causes less anterior muscle weakness than
femoral nerve blocks, which promotes early mobilization of patients with proximal femoral fractures.
Circular economy practices and their effect on corporate financial performance
Authors:   Tashkent State University of Economics, Shavkatov Navruzbek , Abdurakhimova Dilora ,   Tashkent State University of Economics, Sherkuziyeva Nasiba ,   Tashkent State University of Economics, Omonov Sardor ,   Tashkent State University of Economics, Rakhmedova Madinakhon ,   Tashkent State University of Economics
Published: December 2024

In this study, we investigate the relationship between circular economy (CE) practices and financial performance in European manufacturing firms. A longitudinal analysis of 200 companies from 2018 to 2022 was conducted using a custom Circular Economy Index (CEI) and various financial metrics. Panel data regression analysis revealed a positive, statistically significant relationship between CEI and financial performance. A one-point increase in CEI was associated with increases of 0.152 percentage points in ROI, 0.087 in Gross Profit Margin, 0.063 in Net Profit Margin, and 0.203 in Total Shareholder Return. Lag analysis showed this relationship strengthened over time, with the effect on ROI increasing from 0.152 (no lag) to 0.225 (3-year lag). Slight diminishing returns were observed at very high levels of circular economy implementation. Subgroup analysis indicated stronger effects for larger firms, high-tech manufacturers, and companies in Northern Europe. Brand value and operational efficiency were identified as partial mediators. These findings provide robust evidence supporting the business case for circular economy transitions in manufacturing, with implications for managerial decision-making and policy development in sustainable manufacturing.
Integrating human resource management strategies to optimize production and operations in SMEs
Authors:   University of Samarra, Aldouri Seror Naji Mohsin
Published: December 2024

The purpose of this research is to design a human resources performance management system in order to improve the productivity of small and medium-sized enterprises (SMEs). For this purpose, a questioner has been designed to distribute among the experts of the active SMEs companies in Iraq. Based on the collected data, the statistical analysis was done. The statistical population of the study was 266 managers and experts active in the field of SMEs, of which 142 were chosen through multi-stage sample approach. Research tools for evaluating individual, group and organizational operation variables and enhancing the total efficacy are researcher-made questionnaires which were measured by using content validity and reliability determined through internal consistency within Cronbach’s alpha method.
The findings of the research show that the variable of collective management with a maximum t-value 3.92 and Cronbach's alpha 0.93 had a greater impact on developing economic status than other variables. Furthermore, the result of the research indicated that according to the fit indices of the model, the proposed model is the most appropriate one (up to 62%) for establishing the human resources management model in order to improve the productivity of SMEs.
Human-Centered AI for Discovering Student Engagement Profiles on Large-Scale Educational Assessments
Authors: Guo Hongwen , Johnson Matthew , Saldivia Luis , Worthington Michelle , Ercikan Kadriye
Published: December 2024

Large-scale assessments play a key role in education: they provide insights for educators and stakeholders about what students know and are able to do, which can inform educational policies and interventions. Besides overall performance scores and subscores, educators need to know how and why students performed at certain proficiency levels to improve learning. Process/log data contain nuanced information about how students engaged with and acted on tasks in an assessment, which hold promise of contextualizing a performance score. However, one isolated action event observed in process data may be open to multiple interpretations. To address this challenge, in the current study, we propose to integrate sequential process data with response data to create engagement profiles to better reflect students' test-taking processes. Most importantly, we propose to use AI algorithms to assist and amplify human expertise in the creation of students’ engagement profiles, so that the information extraction from the multi-source (performance and process) data can be scaled up to enhance the value of large-scale assessments in teaching and learning. We leveraged various machine learning techniques and developed a general framework of the human-centered AI approach to help human experts efficiently and effectively make sense of the multi-source data. Using a mathematics item block from the National Assessment of Educational Progress (NAEP) for illustrations, data from over 14,000 students resulted in ten preliminary profiles, more than half of which were associated with low performing students. These engagement profiles are expected to generate rich and meaningful feedback for educators and stakeholders.
Ask NAEP: A Generative AI Assistant for Querying Assessment Information
Authors: Zhang Ting , Patterson Luke , Beiting-parrish Maggie , Webb Blue , Abeysinghe Bhashithe , Bailey Paul , Sikali Emmanuel
Published: December 2024

Ask NAEP, a chatbot built with the Retrieval-Augmented Generation (RAG) technique, aims to provide accurate and comprehensive responses to queries about publicly available information of the National Assessment of Educational Progress (NAEP). This study presents an evaluation of this chatbot’s performance in generating high-quality responses. We conducted a series of experiments to explore the impact of incorporating a retrieval component into GPT-3.5 and GPT-4o large language models and evaluated the combined retrieval and generative processes. This work presents a multidimensional evaluation framework using an ordinal scale to assess three dimensions of chatbot performance: correctness, completeness, and communication. Human evaluators assessed the quality of responses across various NAEP subjects. The findings revealed that GPT-4o consistently outperformed GPT-3.5, with statistically significant improvements across all dimensions. Incorporating retrieval into the pipeline further enhanced performance. The RAG approach resulted in high-quality responses. Ask NAEP reduced the occurrence of hallucinations by increasing the correctness measure from 85.5% of questions to 92.7%, a 50% reduction in non-passing responses. The study demonstrates that leveraging large language models (LLMs) like GPT-4o, along with a robust RAG technique, significantly improves the quality of responses generated by the Ask NAEP chatbot. These enhancements can help users to better navigate the extensive NAEP documentation more effectively by providing accurate responses to their queries.
On the issue of quality of medical care for patients with diabetic retinopathy.
Authors:   Peoples’ Friendship University of Russia named after Patrice Lumumba, Biryukov V. V. , Breusov V. V. ,   Peoples’ Friendship University of Russia named after Patrice Lumumba
Published: December 2024

Relevance. One of the most important modern medical and social problems is diabetes mellitus. Against its background, many complications develop, mainly as a result of damage to the vessels of the microcirculatory bed. Diabetic retinopathy is one of the most common and formidable complications of diabetes, leading to irreversible blindness. Early diagnosis and timely initiation of treatment of retinopathy is an effective prevention of disability in patients with diabetes mellitus. Thus, the aim of the study was to assess the quality of medical care provided to patients with diabetic retinopathy with the identification of further possible ways to modernize medical and organizational measures to prevent its complications. The methods used in the study were: analytical, statistical (calculation of extensive indicators), sociological (anonymous survey of ophthalmologists). The study found that there is a clear problem with low adherence of patients with
diabetes to regular monitoring by ophthalmologists. In addition, ophthalmology offices are underequipped, as well as low availability of necessary drugs used as therapy for retinopathy. The data obtained during the study allow us to conclude that it is necessary to improve the organization of medical care and algorithms for managing patients with diabetes mellitus in order to reduce the risk of their disability.
IT Giants vs. states in human rights regulation in digital space: a comparative review
Authors: Vinogradov Vadim , Chambas Estelle
Published: December 2024

The extensive power of IT Giants in the digital domain requires national governments to strengthen regulatory measures. This article addresses the critical debate on the parallelism between IT Giants and sovereign states, with an emphasis on the governance of human rights in digital space. The analysis engages with the regulatory landscapes within the European Union, with a specific look at France's legal mechanisms, and contrasts these with the regulatory environment in Russia. The research evaluates the effectiveness of both nation-states and IT Giants in upholding human rights in digital space, scrutinizing statutory norms alongside corporate governance policies. The objective is to determine if IT Giants are comparable to nation-states in their role in human rights protection.
Morar e resistir: a insurgência popular pelo direito à moradia na cidade de Fortaleza/CE
Authors: Almeida Lara Cruz de , Casimiro Lígia Maria Silva Melo de , Bezerra Samuel Monteiro
Published: December 2024

This text aims to identify the relevance of the insurgent action of the population that finds itself excluded from access to its social right to decent housing, especially based on relevant experiences in the city of Fortaleza/CE, from the 2010s onwards. Initially, the possibility of popular insurgency in the search for the realization of the right to housing is discussed and, then, the local scenario is analyzed, in search of significant experiences on the topic. The research has a qualitative approach methodology, as it seeks to understand knowledge about the concepts of insurgent planning, the right to decent housing and urban public policy. It is essentially explanatory and exploratory, considering that it seeks to understand the relationship between the themes described. Bibliographical research is used, focusing on articles and books on the topic, in addition to relevant Brazilian legislation. In the end, it is noted that the experiences of popular insurgency in the city of Fortaleza/CE appear to be an alternative path in the search for the realization of the social right to decent housing. Non-exclusive alternative to the state's duty to prepare, implement and review urban policy.
PERANCANGAN DAN PEMBUATAN ALAT PEMOTONG SERAT NANAS MENGGUNAKAN SISTEM PNEUMATIK
Authors: Eka Putra Ismet , Hendra Boy
Published: December 2024

Pembuatan sebuah alat yang dapat membantu memotong bahan baku material komposit serat alam (serat nenas) secara otomatis, dapat meningkatkan efesiensi dan mempermudah dalam pemotongan, baik dari segi kecepatan, tenaga, jumlah produksi, hingga faktor keamanan mesin pemotong tersebut. Hasil dari pengujian menunjukkan bahwa menggunakan alat pemotong serat nenas sistem pneumatik dapat memotong serat dengan cepat untuk memenuhi kebutuhan akan serat nenas sebagai bahan baku material komposit dan juga menghindari keadaan dimana ketika memotong serat secara manual akan terasa lelah karena kinerja yang semakin menurun dan itu sangat mempengaruhi tingkat keamanan yang dapat membahayakan dalam proses pemotongan. Perbedaan tekanan yang diberikan pada sistem bervariasi 2, 3, 4, 5 bar dengan hasil pemotongan yang bervariasi yaitu 61, 100, 113, dan 150 pemotongan setiap 60 detiknya. Alat pemotong serat nanas sistem pneumatik ini mampu memotong dalam waktu 0.41 detik dengan tekanan udara 5 bar.
EVALUASI KINERJA SISTEM PENDINGIN KOMPRESI UAP VRF DENGAN SIKLUS INJEKSI
Authors: Rachman Arfidian , Yuana Dewi Arfita , Effendi Asnal , Nesti Lisa
Published: December 2024

Akibat dari penurunan laju aliran massa pada bahagian hisap pada sistem pendinginan variable refrigerant flow (VRF), sistem aliran pendingin berkinerja buruk. Untuk meningkatkan efisiensi metode siklus injeksi uap digunakan. Dampak injeksi uap secara teoritis dieksplorasi dalam kajian ini pada berbagai tekanan menengah dan suhu lingkungan luar, dan temuan didukung oleh data eksperimen. Kapasitas pemanasan kompresor, daya input, koefisien kinerja (COP), dan efisiensi isentropik semuanya dipengaruhi oleh tekanan. Pada suhu sekitar yang rendah, peningkatan COP dengan injeksi uap sangat luar biasa. Dalam kajian ini, kinerja sistem pendingin dengan siklus injeksi dievaluasi, sistem dengan siklus injeksi ini menghasilkan peningkatan kapasitas pendinginan sebesar 3,26% dan rasio efisiensi energi (EER) sebesar 2,32%.
PERBANDINGAN METODE COILED TUBING DAN PUMP PADA APLIKASI SOLVENT TREATMENT BERDASARKAN PARAMETER SUCCESS RATIO DAN CUT OFF DI LAPANGAN FASH
Authors: Melysa Richa , Anwar Irwan , Sulistya Jehan , Afdal Afdal
Published: December 2024

ABSTRAK
Fash field merupakan lapangan dengan kategori heavy oil yang dikelola oleh PT. Chevron Pacific Indonesia dengan jenis batuan batu pasir. Sehingga seiring dengan produksi minyak ke permukaan maka akan timbul masalah produksi seperti asphaltene. Untuk mengatasi masalah asphaltene digunakan pelarut untuk melarutkan asphaltene dalam bentuk pelarut. Ada 2 cara yang digunakan untuk melakukan injeksi solvent yaitu dengan menggunakan coiled tubing dan dengan menggunakan pompa. Pada penelitian ini akan dibahas tingkat keberhasilan masing-masing metode dalam aplikasi perlakuan pelarut dan penentuan nilai ambang batas guna menentukan calon sumur yang tepat untuk setiap metode yang digunakan. Dalam menentukan tingkat keberhasilannya, Minimum oil recovery untuk masing-masing metode yaitu coiled tubing dan pump adalah 8 bopd dan 4 bopd serta untuk menentukan nilai threshold digunakan parameter yang memiliki nilai tertentu sebagai acuan untuk memaksimalkan penggunaan existing metode dalam aplikasi perawatan pelarut. Parameter yang digunakan adalah kadar aspal (%), water cut (%), suhu kepala sumur (°F), dan suhu reservoir (°F).
Machine Translation and Tourism Discourse
Authors: Moreno-Romero Carmen , Hermán-Carvajal Antonio
Published: December 2024

In the last few decades, tourism has consistently played a significant role in the Spanish economy. Spain, one of the world's most popular tourist destinations, received 9.6 million international tourists in September 2024, according to the Spanish National Institute of Statistics (INE, 2024a). Due to the significance of the tourism sector, it is particularly important that Spain’s most visited tourist attractions offer high-quality information in multiple languages on their websites to ensure that as many people as possible look up the information contained therein, as businesses and other stakeholders in the tourism sector can benefit significantly from website localisation. For this study, the linguistic adequacy of the websites of Spain’s top 20 tourist attractions as well as their official localised versions in English and French were analysed by taking into account a series of parameters related to best practices in web localisation (Olvera-Lobo and Castillo-Rodríguez, 2019; Tercedor Sánchez, 2005). Furthermore, the official localised websites in English and French were compared with the translation proposals of DeepL and Google Translate to assess the quality of the machine-translated tourism-themed content. The results obtained show poor quality in terms of localisation and linguistic adequacy for the official Spanish, English and French versions of the analysed websites. Regarding the overall assessment of the machine-translated content, DeepL performed better than Google Translate and outperformed the official websites localised into English in terms of linguistic quality.
Association of lipids in lipoprotein subfractions with liver fibrosis in a mouse model of metabolic dysfunction–associated steatohepatitis
Authors: Nakahara Honoka , Ichimura-Shimizu Mayuko , Tachibana Shotaro , Jargalsaikhan Orgil , Qinyi Cai , Yuko Miyakami , Ogawa Hirohisa , Matsuda Satoru , Tsuneyama Koichi
Published: December 2024

Background
Metabolic dysfunction–associated steatohepatitis (MASH) exhibits inflammation and fibrosis in addition to lipid accumulation in the liver, which may progress to cirrhosis and liver failure. Liver biopsy is the only method currently available to differentiate between MASH and simple steatosis.
Aims
This study investigated whether the serum lipoprotein subfraction reflects fibrosis severity in a MASH mouse model.
Methods
Nine-week-old male A/J and C57BL6/J mice were fed a high-fat/cholesterol/cholate-based (iHFC) diet to induce fibrotic MASH. To generate fibrosis of varying severity, mice were fed two diets with different cholesterol concentrations (1.25% and 2.5%). After 9 weeks of feeding, serum cholesterol and triglyceride levels of each lipoprotein were comprehensively analyzed, including chylomicron, very-large low-density lipoprotein, low-density lipoprotein (LDL), and high-density lipoprotein (HDL), with 20 subclasses according to particle size.
Results
Among 20 lipoprotein subfractions, serum levels of very-large HDL-cholesterol, very-small HDL-cholesterol, very-small HDL-triglycerides, and very-small LDL-cholesterol were significantly higher in the stage 2 fibrosis group than the stage 1 fibrosis group. Serum very-small LDL-cholesterol levels were correlated with histological severity of MASH, which reportedly increases with the progression of MASH in humans.
Conclusion
The serum lipoprotein subfraction reflects liver fibrosis severity even in early phase, independent of the severity of other MASH lesions in MASH model mice. Fractionating HDL, which have been measured in clinical practice, may help establish noninvasive markers of liver fibrosis.
Origins of the fastest stars from merger-disruption of He-CO white dwarfs
Authors: Perets Hagai , Glanz Hila , Bhat Aakash , Pakmor Rüdiger
Published: December 2024

Hypervelocity white dwarfs (HVWDs) are stellar remnants moving at speeds exceeding the Milky Way's escape velocity1-6. The origins of the fastest HVWDs are enigmatic, with proposed formation scenarios facing challenges explaining both their extreme velocities and observed properties7-8. Here we report a three-dimensional hydrodynamic simulation of a merger between two hybrid helium-carbon-oxygen white dwarfs (HeCO WDs with masses of 0.68 and 0.62 M_sun). We find that the merger leads to a partial disruption of the secondary WD, coupled with a double-detonation explosion of the primary WD. This launches the remnant core of the secondary WD at a speed of ~2000 km s-1, consistent with observed HVWDs. The low mass of the ejected remnant and its heating from the primary WD's ejecta explain the observed luminosities and temperatures of hot HVWDs, which are otherwise difficult to reconcile with previous models. This discovery establishes a new formation channel for HVWDs and points to a previously unrecognized pathway for producing peculiar Type Ia supernovae and faint explosive transients.
WITHDRAWN: Unveiling the continuum of acute-on-chronic liver failure: phenotypic insights into severity and outcomes
Authors: Zhang Qian , Hu Jiaxuan , Qiu Shaotian , Bian Jiale , Gao Aimin , Liu Fang , Zhao Caiyan , Zhang Liaoyun , Ren Wanhua , Xin Shaojie , Chen Yu , Duan Zhongping , Han Tao
Published: December 2024

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
parenting concerns in cancer patients with minor children: a scoping review
Authors: Gu Sai-nan , ZHU Ai-yong , Sun Shan-shan , Shen Ling-ling , Zhao Fang
Published: December 2024

Background: Parenting problems are prevalent in cancer patients, and breast cancer patients themselves are more prone to depression, anxiety, fear of illness and other negative emotions, and the role of motherhood requires female cancer patients to be treated while raising their children, and patients must balance managing their illness with caring for their minor children. Therefore, the group of young and middle-aged cancer deserves more attention from society, medical treatment, and nursing.
Objectives：to summarise the influencing factors of rearing anxiety of young and middle-aged cancer patients with minor children.
Design:Scoping review
Data sources:the scope review report framework of Arksey and O'Malley was used to search China Knowledge Network (CNKI),China Biomedical Literature Database (CBM),Wanfang database,PubMed,Web of Science, Embase and Cochrane Library From the establishment of the database to July 20,2024,the included literatures were screened and analysed.
Results: A total of 13 articles were included. the results showed that the level of parenting anxiety of cancer patients at home and abroad was higher, which was mostly affected by personal characteristics, disease characteristics and psychosocial characteristics.
Conclusion: Cancer patients are affected by many factors in the process of disease and parenting,and face the challenge of parenting,which leads to a high level of parenting anxiety. Therefore,future medical workers should pay close attention to the parenting concerns of cancer patients and regard them as the core part of psychological care.
Joint Optimization of Collaborative Delivery Routes and Charging Station Locations for Electric Vehicles and Drones
Authors: Guan Tian , Gao Mingren , Wang Shu , Han Yi , Jiang JiaXin
Published: December 2024

In the current context of achieving carbon neutrality, energy transition has become imperative. For the automotive sector, replacing traditional fuel-powered vehicles with electric vehicles (EVs) offers the most effective solution. In logistics, deploying EVs for delivery can significantly reduce costs. This paper proposes a novel model to address the problem of collaborative delivery using drones and electric vehicles based on a genetic algorithm (GA). Furthermore, it incorporates the siting of charging stations as part of the model. A new logic for the deployment and retrieval of drones is developed and implemented in the algorithm. Unlike previous models constrained by fixed charging requirements, this model enables EVs to proactively decide whether to recharge at charging stations when visiting specific customer nodes, ensuring that the remaining range of EVs never falls below zero within the mathematical framework.
Enhancing Security Operations Center Efficiency throughMulti-Model Integration of Large Language Models and SIEMSystems
Authors: Singh Yuvraj , Patel ND , Shandilya Shishir Kumar
Published: December 2024

The rising rates of cyberattacks necessitate advanced solutions within Security Operations Centers (SOCs). This research explores the integration of Large Language Models (LLMs) with Security Information and Event Management (SIEM) systems to enhance the triage processes of Tier 1 SOC analysts. We evaluate five LLMs—GPT-4, GPT-3.5, LLaMA 3, Mixtral 8x22B, and OpenHermes 2.5 Mistral 7B—on their ability to classify alerts as 'interesting' or 'not interesting'. Our proposed framework, consisting of an alert generation module, an LLM agent, and a reporting module, was tested using Wazuh SIEM integrated with CALDERA for adversary emulation. The results demonstrate that GPT-4 achieved the highest accuracy with a precision of 94\%, recall of 92\%, and an F1-score of 93\%, significantly outperforming the other models. The integration of LLMs accelerated preliminary triage by reducing the average processing time per alert by 40\% and decreased the cognitive load on analysts by automating up to 60\% repetitive tasks. However, challenges such as hallucinations—occurring in approximately 5\% of cases—integration complexities and privacy risks associated with handling sensitive data were observed. To address these issues, we propose a hybrid approach where LLMs act as co-pilots alongside analysts, incorporating strategies for model transparency, bias detection, and compliance with data privacy regulations. These findings offer practical insights for enhancing SOC efficiency and resilience against evolving cyber threats, emphasizing the importance of prompt optimization, continuous learning, and industry collaboration for large-scale alert training in future studies.
An Artificial Intelligence Approach to Predicting Processing Parameters for Liquid Composite Molded (LCM) Carbon Fibre-Reinforced Plastics (CFRPs)
Authors: Sears Jennifer L , Johrendt Jennifer
Published: December 2024

This study developed a comparative machine learning (ML) framework to predict optimal processing parameters and mechanical properties for automotive-grade carbon fibre-reinforced plastics (CFRPs) produced via Liquid Composite Molding (LCM). Multi-linear- (MLR), support vector- (SVR), random forest- (RFR), and gradient boosting regression (GBR) algorithms were coupled with artificial neural network (ANNs) using multi-layer perceptron (MLP), and single and dual-path functional application programming interface (FAPIs) models to increase the prediction outcomes. The models developed herein can be tailored to the case-specific needs of the application. The results demonstrated that the RFR model, enhanced with hyperparameter tuning, achieved the highest predictive accuracy, explaining 45% of the variability in the data for the linear regression case. The FAPI model using Keras® and Tensorflow® exhibited superior performance for the non-linear case, with test predictions of 78.20% for flexural strength, 73.8% for flexural modulus and 99.97% for binder use. Additionally, thermal and demolding analysis expanded the complexity of the predictions by enhancing the correlation to part quality, ultimately accelerating product development and providing industry with accurate predictive modelling tools.
Active Grade Estimator on Short Answer Assessment
Authors: Iqbal Mohammad , Nugraha Tsamara Rana , Pao Hsing-Kuo
Published: December 2024

When introducing machine learning to automated grading systems, active learning is advantageous by helping teachers provide as little guidance as possible to offer proper automatic grading results in the end. However, given a high variety of Q/A nature, one has to pay attention to a diverse set ofpossible correct answers to offer suitable grading. Moreover, students who lack self-confidence in replying to exam questionsusually put long-winded or formless answers which jeopardizes the automatic gradingto reach its reliable performance. All aforementioned factors prohibit applying the conventional keyword-matching approaches to solve the problem. To deal with the difficulty, we propose a novel two-stage query strategy based on large language models (LLMs).In the first stage, we match a student's answer to a key answer from a prepared answer set. Afterward, the student's answer shall be summarized through LLMs to a well-structured answer. The proposed LLM-based approach is considered a prototype-based learning method. We also attempt to reduce the possibility of bias labeling by having multiple graders as oracles to join the proposed active learning framework. The proposed approach has been demonstrated on two publicly automated short answer grading datasets with different grading tasks. Overall, the proposed model exhibits outstanding performance compared to state-of-the-art methods focusing on similar topics in terms of effectiveness and efficiency.
Accelerated Sky Region Segmentation Using Hybrid Deep CNNs and Lattice Boltzmann Level-Set Model
Authors: Albalooshi Fatema A. , Qader M. R. , Ismail Yasser , Elmedany Wael , Al-Ammal Hesham , Rajarajan Muttukrishnan , Asari Vijayan k.
Published: December 2024

In this paper, we present a novel hybrid method for accelerated sky region segmentation that integrates Convolutional Neural Networks (CNNs) with the Lattice Boltzmann Level-Set (LBLS) model. By leveraging DeepLabV3+, Fully Convolutional Network (FCN), and SegNet, our approach guides the active contour and extracts regions of interest. We employ a local image fitting level-set function to characterize the region-based active contour model and utilize the Lattice Boltzmann Method (LBM) to achieve rapid convergence. This deep LBLS segmentation method not only preserves precise details of the sky region but also demonstrates improved robustness and computational efficiency. Experimental results on the CamVid dataset show that our proposed method outperforms state-of-the-art techniques, achieving a mean recall value improvement of up to 14.45%. Our method contributes to advancements in sky region segmentation, essential for applications such as object detection, augmented reality, and virtual reality.
Model breeding and ecotoxicity study of Eprinomectin on the reproductive performance of Onthophagus hircus (Coleoptera: Scarabaeidae)
Authors: Bianchinotti Vernadet , González-Vainer Patricia , Suárez Gonzalo
Published: December 2024

This study developed a laboratory rearing model for the dung beetle Onthophagus hircus to evaluate the ecotoxicological effects of eprinomectin (EPM) on its survival and reproductive performance. Adult O. hircus were exposed to increasing EPM concentrations (0-50 ppm) in bovine feces. Survival was significantly reduced at 50 ppm EPM. A reproductive per-formance experiment compared control and 0.05 ppm EPM treatment groups. While adult fecundity was not significantly affected, the EPM treatment resulted in complete failure of progeny development, with no adult emergence. The study demonstrates that environmentally relevant EPM concentrations can negatively impact O. hircus populations through larvi-cidal effects, even when adult survival and reproduction appear unaffected. This highlights the importance of considering long-term impacts when assessing the environmental risks of antiparasitic drugs on beneficial dung fauna. The laboratory rearing model developed provides a valuable tool for further ecotoxicological research on dung beetles.
Regulatory effects of Poria cocos polysaccharides on gut microbiota and metabolites: Evaluation of prebiotic potential
Authors: Zhou Xu , Li Yangyou , Yang Yuhan , Wei Li , Wang Chen , Xu Jiahui , Song Jiajia , Liu Shijian , Bai Junying , Suo Huayi
Published: December 2024

Dietary polysaccharides have the function of regulating gut microbiota and metabolites, and can serve as an important source of functional foods. This study aimed to analyze the regulation of poria cocos polysaccharides on the structure and metabolism of human gut microbiota through an in vitro fecal fermentation model. The results showed that Poria cocos polysaccharides can be utilized by gut microbiota, resulting in a significant decrease in pH and a significant increase in the concentration of short-chain fatty acids. Additionally, the relative abundance of beneficial bacteria such as Lactobacillus, Bifidobacterium increased, while the relative abundance of harmful bacteria such as Escherichia-Shigella, Bilophila decreased. Furthermore, Poria cocos polysaccharides had a positive effect on microbial metabolites, significantly up-regulating metabolites such as L-cystine, and etelcalcetide. These results highlight the beneficial role of Poria cocos polysaccharides in maintaining intestinal health and indicate their potential prebiotics in the functional food industry.
Blocking copper transporter protein-dependent drug efflux with albumin-encapsulated Pt(IV) for synergistically enhanced chemo-immunotherapy
Authors: Fang Man , Cao Lei , Zhang Zhao , Yu Zhen , Shen Yue , Chen Jieqi , Chen Juan , Liu Zhaoqian , Meng Yingcai , Xiao Haihua , Qu Qiang , Yin Ji-Ye , Li Xiang-Ping
Published: December 2024

Non-small cell lung cancer (NSCLC) represents the most prevalent form of lung cancer, exerting a substantial impact on global health. Cisplatin-based chemotherapy is the standard treatment for NSCLC, but resistance and severe side effects present significant clinical challenges. Recently, novel tetravalent platinum compounds have attracted significant interest. While numerous studies concentrate on their functional modifications and targeted delivery, tumor-induced platinum resistance is frequently overlooked. Previous tetravalent platinum compound demonstrated antitumor activity, yet proved ineffective against cells exhibiting resistance to cisplatin. In order to enhance the efficacy and potential applications of tetravalent platinum in NSCLC, a glutathione (GSH)-responsive albumin nanoquadrivalent platinum (HSA@Pt) have been constructed. In light of previous research into drug conjugation, this study was to develop a combined chemo-immunotherapy approach. The HSA@Pt demonstrated high efficacy and low toxicity, with targeted tumor accumulation. Furthermore, tetrathiomolybdate (TM) has been demonstrated to exert a synergistic inhibitory effect on Cu2+ Transporting Beta Polypeptide (ATP7B) and Programmed Death Ligand 1 (PD-L1), impede platinum efflux, induce cellular stress, and activate antitumor immunity. The findings suggest HSA@Pt's potential for clinical use and a novel chemo-immunotherapy strategy for NSCLC, enhancing the utility of established drugs through synergistic sensitization.
Linguodidactic Principles and Content of Linguistic Disciplines of the Diachronic Cycle in the University Training of Philologists and Teachers of Literature
Authors:   Transbaikal State University, Ignatovich Tatiana Yu. , Biktimirova Yulia V. ,   Transbaikal State University
Published: December 2024

The relevance of considering modern approaches to teaching the history of the Russian language in
the training of philologists and teachers of literature and at the university is unconditional, since the achievements of recent decades in linguistics and linguodidactics require the addition and updating of the traditional
methodological platform in order for teaching to be effective. There is also no doubt that diachronic linguistic
knowledge is in demand, because without it philological education will be flawed, will not give an understanding of the historical variability of the language and will not allow you to see the continuity of historical and modern linguistic transformations, to understand the causes and essence of modern linguistic processes and predict
trends of future changes in the Russian language. The purpose of the article is to consider the linguodidactic
methodology and the content of linguistic disciplines of the diachronic cycle in the context of modern philological
education (using the example of the undergraduate and graduate curricula of the Transbaikal State University,
which train teachers of literature and philology). The method of linguodidactic analysis of methodology is used,
theoretical and practical content of disciplines on the history of the Russian language are discussed. Russian
methodological and didactic principles, such as dialectical, historical-chronological, linguistic-cultural, continuity
and argumentation, based on them, the content and practical tasks on the history of the Russian language,
including tasks with individual examples and texts of different chronological sections of the language, including
modern Russian, requiring historical and linguistic analysis and commentary contribute to effective formation
of linguistic competence among students and undergraduates studying linguistic disciplines of the diachronic
cycle. Russian history course programs are developed and implemented by future philologists and teachers
of literature at the Transbaikal State University. The authors have showed the manifestation of the formulated
methodological principles of teaching the history of the Russian language and revealed the features of linguodidactic methodology in the context of modern requirements of the educational standard and using examples
of thematic planning of the content of linguistic disciplines of the diachronic cycle, various tasks and exercises.
Two Lines Enable FasTrack Breeding in Blueberry
Authors: Song Guo-qing
Published: December 2024

The juvenile period of blueberry seedlings typically lasts ≈3 to 4 years. To shorten this period and facilitate FasTrack breeding, we developed transgenic ‘Aurora’ blueberry plants with constitutive expression of the blueberry FLOWERING LOCUS T gene, enabling flowering of T0 transformants within just 1 year. To evaluate the potential of these transgenic lines in accelerating breeding cycles, we crossed transgenic ‘Aurora’ with transgenic southern highbush blueberry ‘Legacy’, referred to as Mu-Legacy. Mu-Legacy also exhibited early flowering mainly as a result of a transgene insertion, making it suitable for FasTrack breeding. Over 2 years of phenotyping, we observed that transgenic seedlings flowered consistently each year, whereas nontransgenic seedlings did not produce any flowers. These results suggest that either the constitutive expression of the blueberry FLOWERING LOCUS T gene or the specific transgene insertion site in transgenic ‘Legacy’ can effectively shorten the juvenile phase of blueberry plants. Given the significance of ‘Aurora’ and ‘Legacy’ in blueberry production, these transgenic lines emerge as a valuable tool for accelerating blueberry breeding programs.
Youth Everyday Culture: communication in the digital environment
Authors: Barinova S. G. , Barinova S. G.
Published: December 2024

The culture of everyday life forms the basis of values and meanings of human life from day to day. In order to obtain data on the place and role of the digital environment in the lives of modern students, a survey was conducted. The survey covered the components of students’ lives that are related to studies, relationships, daily activities, interests and hobbies, etc. Theoretical and methodological approaches to the consideration of the culture of everyday life of youth and communication in the digital environment are systemic and integrated. The specifics of the study revealed the need to apply a causal analysis of the phenomena under study. By changing the formats of interaction with family, official structures, and educational organizations, the digital environment is shaping a new culture of everyday life. At the same time, it is obvious that following the change in the forms of communication, the content and values of this interaction will also change. The results of the research can be applied in philosophy, cultural studies, and pedagogy.
Confiance et biais d’automatisation : différences entre novices et experts dans un contexte militaire
Authors: Marchand Anne-Lise , Maille Nicolas , Munoz Pauline , Chaudron Laurent
Published: December 2024

L’étude vise à examiner si le biais d’automatisation dans des situations d’arbitrage entre une aide humaine et une aide basée sur l’IA varie en fonction des caractéristiques psychosociales des individus. La littérature met en évidence la robustesse du biais d’automatisation dans les situations de prise de décision avec une seule aide, mais quelques études récentes mobilisant le paradigme de la double aide à la décision identifient des résultats plus nuancés, notamment en fonction des caractéristiques des participants. 2 groupes de participants (37 élèves pilotes militaires vs 37 pilotes opérationnels) sont engagés dans une simulation de mission aérienne d’attaque au sol, où ils doivent choisir entre les informations fournies par une aide humaine et celles fournies par une aide automatisée basée sur l’IA. La confiance en ces aides est induite a priori par des niveaux de fiabilité prédéfinis (20%, 50%, 70% 90%). A fiabilité égale, lorsque les jeunes participants et les experts sont confrontés à une aide humaine et une aide basée sur l’IA, ils ont une préférence pour l’aide humaine. Toutefois cette préférence est plus importante pour les experts. L’étude remet en question l’invariabilité du biais d’automatisation, soulignant l’impact des caractéristiques psychosociales de l’opérateur sur la prise de décision. Il semble nécessaire de reconsidérer le biais d’automatisation dans des contextes modernes au travers des représentations individuelles des technologies pour optimiser la conception des systèmes d’aide à la décision.