bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-Efficient Bone Segmentation Using Feature Pyramid- Based SegFormer
Authors: Masuda Naohiro , Ono Keiko , Tawara Daisuke , Matsuura Yusuke , Sakabe Kentaro
Published: December 2024

The semantic segmentation of bone structures demands pixel-level classification accuracy to create reliable bone models for diagnosis. While Convolutional Neural Networks (CNNs) are commonly used for segmentation, they often struggle with complex shapes due to their focus on texture features and limited ability to incorporate positional information. As orthopedic surgery increasingly requires precise automatic diagnosis, we explored SegFormer, an enhanced Vision Transformer model that better handles spatial awareness in segmentation tasks. However, SegFormer’s effectiveness is typically limited by its need for extensive training data, which is particularly challenging in medical imaging, where obtaining labeled ground truths (GTs) is a costly and resource-intensive process. In this paper, we propose two models and their combination to enable accurate feature extraction from smaller datasets by improving SegFormer. Specifically, these include the data-efficient model, which deepens the hierarchical encoder by adding convolution layers to transformer blocks and increases feature map resolution within transformer blocks, and the FPN-based model, which enhances the decoder through a Feature Pyramid Network (FPN) and attention mechanisms. Testing our model on spine images from the Cancer Imaging Archive and our own hand and wrist dataset, ablation studies confirmed that our modifications outperform the original SegFormer, U-Net, and Mask2Former. These enhancements enable better image feature extraction and more precise object contour detection, which is particularly beneficial for medical imaging applications with limited training data.
Intragroup and Intergroup Pairwise Key Predistribution for Wireless Sensor Networks
Authors: Yang Ching-Nung , Gu Ting-Song , You Jhou-Cian , Wang Chang-Ji
Published: December 2024

The major task of a wireless sensor network (WSN) is data collection. Key predistribution (KP) is to establish pairwise keys for secure communication in a WSN, such that all collected data could be securely sent to a backend database. Most research on KP-like schemes is dedicated to enhancing resiliency against node capture attack (NA) and retaining the link connectivity in the meantime. For large-scale wireless sensor networks, a more common approach is to use a multiple-sink WSN (MWSN) to support a large number of sensor nodes. In MWSNs, there are different clusters (referred to as groups). We took the lead in studying KP in the MWSN environment. Based on the new MWSN environment, we present intragroup and intergroup KP (I2KP) to fulfill both requirements of security and energy efficiency when gathering data via various sink nodes in a large-scale WSN. Three types of I2KP with respective pros and cons are proposed. Theoretical analysis and numerical simulation demonstrate their effectiveness.
Enhanced Sensor Placement Optimization and Defect Detection in Structural Health Monitoring Using Hybrid PI-DEIM Approach
Authors: Yun Minyoung , Tannous Mikhael , Ghnatios Chady , Fonn Eivind , Kvamsdal Trond , Chinesta Francisco
Published: December 2024

This work introduces a novel methodology for identifying critical sensor locations and detecting defects in structural components. Initially, a hybrid method is proposed to determine optimal sensor placements by integrating results from both the discrete empirical interpolation method (DEIM) and the random permutation features importance technique (PI). Subsequently, the identified sensors are utilized in a novel defect detection approach, leveraging a semi-intrusive reduced order modeling and genetic search algorithm for fast and reliable defect detection. The proposed algorithm has successfully located defects with low error, especially when using hybrid sensors, which combine the most critical sensors identified through both PI and DEIM. This hybrid method identifies defects with the lowest errors compared to using either the PI or DEIM methods alone.
Exploring Near- and Far-Field Effects in Photoplethysmography Signals Across Different Source–Detector Distances
Authors: Solé Morillo Ángel , Cause Joan Lambert , De Pauw Kevin , Silva Bruno da , Stiens Johan
Published: December 2024

Photoplethysmography is a widely used optical technique to extract physiological information non-invasively. Despite its large use and adoption, multiple factors influence the signal shape and quality, including the instrumentation used. This work analyzes the variability of the DC component of the PPG signal at three source–detector distances (6 mm, 9 mm, and 12 mm) using green, red, and infrared light and four photodiodes per distance. The coefficient of variation (CV) is proposed as a new signal quality index (SQI) to evaluate signal variabilities. This study first characterizes the PPG system, which is then used to acquire PPG signals in the chest of 14 healthy participants. Results show a great DC variability at 6 mm, homogenizing at 9 and 12 mm. This suggests that PPG systems are also sensitive to the near- and far-field effects commonly reported and studied in optics, which can impact the accuracy of physiological parameters dependent on the DC component, such as oxygen saturation (SpO2).
Damage Detection and Identification on Elevator Systems Using Deep Learning Algorithms and Multibody Dynamics Models
Authors: Koutsoupakis Josef , Giagopoulos Dimitrios , Seventekidis Panagiotis , Karyofyllas Georgios , Giannakoula Amalia
Published: December 2024

Timely damage detection on a mechanical system can prevent the appearance of catastrophic damage in it, as well as allow for better scheduling of its maintenance and repair process. For this purpose, multiple signal analysis methods have been developed to help identify anomalies in a system, through quantities such as vibrations or deformations in its critical components. In most applications, however, these data may be scarce or inexistent, hindering the overall process. For this purpose, a novel approach for damage detection and identification on elevator systems is developed in this work, where vibration data obtained through physical measurements and high-fidelity multibody dynamics models are combined with deep learning algorithms. High-quality training data are first generated through multibody dynamics simulations and are then combined with healthy state vibration measurements to train an ensemble of autoencoders and convolutional neural networks for damage detection and classification. A dedicated data acquisition system is then developed and integrated with an elevator cabin, allowing for condition monitoring through this novel methodology. The results indicate that the developed framework can accurately identify damages in the system, hinting at its potential as a powerful structural health monitoring tool for such applications, where manual damage localization would otherwise be considerably time-consuming.
Arab Culture and Organisational Context in Work-Life Balance Practice for Men and Women: A Case Study from Gaza, Palestine
Authors: Abubaker Mahmoud , Adam-Bagley Chris
Published: December 2024

This paper examines types of WLB (Work–Life Balance Policies) that have emerged in research in Western countries, and compares their applicability for male and female employees in Arab countries in general, and in Gaza, Palestine in particular. A qualitative study has been undertaken with employees of telecommunication companies, with thematic analysis to identify new kinds of WLB in an Arab culture. The WLB policies identified in the two companies were often quite different from those identified by Western researchers, and were guided by the religious principles of Islam, cultural factors, and the needs and aspirations of female employees. The international investors identified had adapted their policies to meet the cultural requirements of an Arabic society. This paper contributes to debates on the effectiveness of, and the need for culturally adapted WLB policies which try to meet the aspirations of women in developing countries. Additionally, this case study adds a new theoretical base, advocating the importance of WLB policies which are adapted to local cultural conditions in ways which also meet the aspirations of international business models. The WLB practices identified have not been described previously in any detailed study. The WLB policies and practices identified advocate for further research studies focusing on gender differences in the provision and take-up of WLB, using both qualitative and quantitative methodologies.
Seasonal Analysis and Risk Management Strategies for Credit Guarantee Funds: A Case Study from Republic of Korea
Authors: Paik Juryon , Ko Kwangho
Published: December 2024

This study investigates the prediction of small and medium-sized enterprise (SME) default rates in Republic of Korea by comparing the performance of three prominent time-series forecasting models: ARIMA, SARIMA, and Prophet. The research utilizes a comprehensive dataset provided by the Korea Credit Guarantee Fund (KODIT), which covers regional and monthly default rates from January 2012 to December 2023, spanning 12 years. By focusing on Republic of Korea’s 17 major cities, the study aims to identify regional and seasonal patterns in default rates, highlighting the critical role that regional economic conditions and seasonality play in risk management. The proposed methodology includes an exploratory analysis of default rate trends and seasonal patterns, followed by a comparative evaluation of ARIMA, SARIMA, and Prophet models. ARIMA serves as a baseline model for capturing non-seasonal trends, while SARIMA incorporates seasonal components to handle recurring patterns. Prophet is uniquely suited for dynamic datasets, offering the ability to include external factors such as holidays or economic shocks. This work distinguishes itself from others by combining these three models to provide a comprehensive approach to regional and seasonal default risk forecasting, offering insights specific to Republic of Korea’s economic landscape. Each model is evaluated based on its ability to capture trends, seasonality, and irregularities in the data. The ARIMA model shows strong performance in stable economic environments, while SARIMA proves effective in modeling seasonal patterns. The Prophet model, however, demonstrates superior flexibility in handling irregular trends and external events, making it the most accurate model for predicting default rates across varied economic regions. The study concludes that Prophet’s adaptability to irregularities and external factors positions it as the most suitable model for dynamic economic conditions. These findings emphasize the importance of region-specific and seasonal factors in tailoring risk forecasting models. Future research will validate these predictions by comparing forecasted default rates with actual data from 2024, providing actionable insights into the long-term effectiveness of the proposed methods. This comparison aims to refine the models further, ensuring robust financial stability and enhanced SME support strategies for institutions like KODIT.
The Role of Managerial Competencies in Driving Industry 4.0 Adoption: A Comparative Study of Thailand and Vietnam’s Manufacturing Sectors
Authors: Le Lan Thi Ngoc , Jeenanunta Chawalit , Ueki Yasushi , Intalar Nuchjarin , Komolavanij Somrote
Published: December 2024

This study investigates the influence of Top Management Team Competencies (TMTCs) and Middle-Tier Managers’ Competencies (MMCs) on the intention to adopt Industry 4.0 (I4.0) technologies in Thailand and Vietnam. Utilizing a quantitative approach with Partial Least Squares Structural Equation Modeling (PLS-SEM), data from 100 manufacturing firms reveal the critical roles of Industry 4.0 readiness level (RL) and perceived usefulness (PU) as mediators in these relationships. The findings highlight that while TMTC significantly enhances organizational readiness, its direct impact on adoption intention is non-significant. Conversely, MMC directly influences both PU and adoption intention, emphasizing the practical role of middle management in bridging strategic vision and operational execution. RL mediates the effects of TMTC on I4.0 adoption intention, whereas PU does not mediate the relationship between TMTC and adoption intention. These insights contribute to the literature on digital transformation, particularly in emerging economies, by identifying distinct managerial roles and the importance of readiness in driving adoption. This study underscores the need for tailored competency development among top and middle managers to foster successful I4.0 adoption and suggests further research into organizational culture, external support, and regional variations.
Landscape Design of Zones with Large-Scale Warehouse and Industrial Development Located in Peri-Urban Areas Using Sectoral Analysis of Landscape Interior (SALI)—A Case Study of Wroclaw, Poland
Authors: Niedźwiecka-Filipiak Irena , Gubański Janusz , Podolska Anna , Serafin Liliana , Rubaszek Justyna
Published: December 2024

Suburban areas are often used for large-scale developments such as hypermarkets, warehouses, and logistics zones, which lead to the fragmentation of natural areas and the visual degradation of the landscape. This study aimed to evaluate ways to reduce the negative impact of these developments by introducing green infrastructure (GI) elements. The analysis focused on warehouses in the inner ring of the planned green infrastructure system in the Wrocław Functional Area (GI WFA). This study involved three stages: (1) selecting a landscape-functional unit (LaFU) vulnerable to landscape degradation; (2) analyzing changes from the development of large-scale warehouses between 2004 and 2021; and (3) assessing the effect of new GI elements using the Sectoral Landscape Interior Analysis (SALI) method. Three models of GI implementation were proposed and evaluated both from a plan view and from a moving observer’s perspective. The results showed that large-scale developments reduce biologically active areas and disrupt landscape harmony. Model III, which includes green roofs, trees, and semi-permeable surfaces, significantly increased greenery and reduced visual degradation. It is recommended to apply the model and its variations in other similar developments for the benefit of the natural environment and landscape.
Sustainable Development Through Energy Transition: The Role of Natural Resources and Gross Fixed Capital in China
Authors: Kang Yu
Published: December 2024

Governments and politicians are very concerned about the environmental sustainability of the energy sector, particularly with regard to oil and gas. To assist in achieving global climate objectives, the clean energy transition involves moving away from a fossil-fuel-based economy and toward one that is dominated by clean, renewable energy. This reduces carbon emissions. Here, we consider the moderating effects of natural resources, urbanization, and energy consumption between 1990 and 2022 as we analyze the impact of China’s energy transition and the external balance of goods and services on the country’s environmental quality. We used ARDL econometric techniques and present a thorough empirical investigation. Overall, the findings indicate that the ecological footprint is adversely correlated with energy transition, natural resource use, the external balance of goods and services, and renewable energy usage. Urbanization and the use of non-renewable energy, however, are positively associated with that footprint. The use of renewable energy sources, richness of natural resources, and energy transition all contribute to environmental sustainability. The sustainability of the environment is weakened by urbanization and non-renewable energy usage. It is recommended that policymakers facilitate the acceleration of the energy transition by utilizing renewable energy, promoting policies that create favorable conditions for the widespread adoption of renewables, and balancing the nation’s urban structure in a way that enhances self-sufficient urban development and ensures a sustainable future. Limitations of this study and future directions for research are outlined.
Research on Assessing Comprehensive Competitiveness of Tourist Destinations Within Cities, Based on Field Theory and Competitiveness Theory
Authors: Song Zhengna
Published: December 2024

The question of how to assess the comprehensive competitiveness of tourist destinations within cities is an important aspect for determining the potential of a city’s tourism development and its ranking among peers in the field. There are four main parts to the content of this article, which consist of the analysis of competition formation motives based on “Field Theory”, the selection of influencing factors by drawing on Porter’s theory of competitiveness, the construction of an assessment model based on the multi-factors weighted comprehensive evaluation method, and an empirical analysis using Nanjing as the research area. The conclusions are as follows: Firstly, the tourist destination field within a city is composed of three interrelated elements, which are actors, rules, and competition. Under the influence of mainstream social and cultural trends, each tourist destination occupies a certain “position” by relying on the attractiveness formed by various types of capital, and then participates in peer competition within the field. Secondly, the three major influencing aspects of the competitiveness of tourist destinations are element conditions, demand characteristics, and supporting conditions. The key points involved in the three aspects can be summarized into four categories of factors, namely, quality evaluation, popularity level, spatial attractiveness, and emotional cognition, which together constitute the indicator system. Thirdly, there are thirteen tourist destinations in Nanjing that are rated above the average, accounting for about 43% of all the popular destinations. The variation coefficient of competitiveness results is about 35%, indicating a moderate to relatively weak degree of dispersion. Finally, the competitiveness of the thirty hot tourist destinations generally presents a spatial order that gradually weakens in an outward direction from the center zone of the city, forming an overall pattern of cluster groups of well-known tourist destinations in the core of the city, relatively random small clusters in the new main city area, and scattered point distribution in the suburbs.
The Impact of Financial Asset Allocation on Firms’ Total Factor Productivity: Evidence from China’s Non-Financial Companies
Authors: Song Bo , Yang Xiandong , Xu Yao
Published: December 2024

As a core business strategy, sustainability has become increasingly important in today’s rapidly evolving world. The improvement of a firm’s total factor productivity (TFP) is necessary for the realization of sustainable development. The wide variation in the types and sizes of China’s firms can reflect the differences in financial capital allocation among firms. In addition, as the second largest economy in the world, China has a large number of firm data to be examined. Based on this, this paper selects China’s A-share non-financial listed companies from 2010 to 2023 as research samples to empirically test the impact of financial asset allocation on the TFP of firms. It is found that excessive financialization negatively affects both TFP and innovation, but that innovation can increase TFP, thus weakening the negative impact of financialization on TFP. Therefore, to enhance the productivity of firms and reach the sustainability of development, firms should invest more in innovation and reduce the level of financialization. By emphasizing innovation, firms can promote the application of green technologies and the production of green products, and achieve win–win economic and social benefits while protecting the environment, and sustainability can be realized.
A Systematic Informetric Analysis and Literature Review of Food Waste Quantification Studies in the Food Service Industry
Authors: Vardopoulos Ioannis , Abeliotis Konstadinos , Lasaridi Katia
Published: December 2024

Incorporating findings from 74 meticulously selected studies, this analysis delves into the complex challenge of measuring food waste (FW) in the food service industry (FSI). The objectives are to aggregate findings on FW quantities, scrutinize quantification methods, identify research gaps, and outline key areas for future exploration. The analysis uncovers an average FW of 167.2 g (min 4.7 g, max 1100 g, standard deviation 202) per meal (26.1%), with studies focusing on plate waste indicating an average of 125.0 g (min 4.7 g, max 292 g, standard deviation 97.3) per meal (29.0%). Variability stems from FW quantification from diverse terminology, inconsistent methodologies, and contextual factors, revealing a lack of standardized concepts. Geographic and sub-sector differences further contribute to the variation in reported FW quantities, affecting the generalizability and comparability of quantities across different FSI establishments and studies. Notably, the majority of the articles offer case-specific insights, limiting their relevance to broader FW generation estimates at the local, national, or sectoral level. Beyond the need for precise quantification, the study acknowledges that the primary challenge lies in addressing wasteful behavioral drivers and actions. Within this perspective, this study underscores the influential role of sociocultural factors and behavioral tendencies and advocates for the need for a deeper understanding of FW generation to formulate practical, sustainable FW prevention strategies. This study provides essential groundwork for harmonizing quantification techniques and guides policymakers and industry stakeholders for the development of practical policies and targeted measures and interventions to effectively reduce FW in the FSI.
Water Quality by Spectral Proper Orthogonal Decomposition and Deep Learning Algorithms
Authors: Zhang Shaogeng , Lin Junqiang , Li Youkun , Zhu Boran , Zhang Di , Peng Qidong , Jin Tiantian
Published: December 2024

Water quality plays a pivotal role in human health and environmental sustainability. However, traditional water quality prediction models are limited by high model complexity and long computation time, whereas AI models often struggle with high-dimensional time series and lack physical interpretability. This paper proposes a two-dimensional water quality surrogate model that couples physical numerical models and AI. The model employs physical simulation results as input, applies spectral proper orthogonal decomposition to reduce the dimensionality of the simulation results, utilizes a long short-term memory neural network for matrix forecasting, and reconstructs the two-dimensional concentration field. The simulation and predictive performance of the surrogate model were systematically evaluated through four design scenarios and three sampling dataset lengths, with a particular focus on the convection–diffusion zone and high-concentration zone. The results indicated that the model achieves high prediction accuracy for up to 7 h into the future, with sampling dataset lengths ranging from 20 to 80 h. Specifically, the model achieved an average R2 of 0.92, a MAE of 0.38, and a MAPE of 1.77%, demonstrating its suitability for short-term water quality predictions. The methodology and findings of this study demonstrate the significant potential of integrating spectral proper orthogonal decomposition and deep learning for water quality prediction. By overcoming the limitations of traditional models, the proposed surrogate model provides high-accuracy predictions with enhanced physical interpretability, even in complex, dynamic environments. This work offers a practical tool for rapid responses to water pollution incidents and supports improved watershed water quality management by effectively capturing pollutant diffusion dynamics. Furthermore, the model’s scalability and adaptability make it a valuable resource for addressing intelligent management in environmental science.
Assessment of Sustainable Waste Management: A Case Study in Lithuania
Authors: Činčikaitė Renata
Published: December 2024

Sustainable waste management is a very important issue that has received increasing attention in recent years due to its significant impact on the environment and human health. As the population and urbanization increase, more and more waste is generated, leading to problems such as pollution, resource depletion, climate change, etc. Therefore, it is necessary to develop effective waste management strategies that are sustainable and do not harm the environment. The EU is making progress in sustainable waste management within the wider context of a circular economy, but challenges remain, particularly in reducing material consumption and effectively managing specific waste streams. The EU’s approach involves setting clear targets, monitoring progress in a comprehensive framework, and supporting Member States in achieving these targets. In 2019, Lithuanian companies invested about 40% more in environmental protection than in 2018. Notably, 15% of them are invested in waste management. An inhabitant throws out an average of 278 kilograms of mixed municipal waste per year. According to the global waste index in 2022, Lithuania ranked 16th (up from 23rd place), Latvia 37th (down from 35th place), and Estonia 32nd (down from 30th place). The purpose of this article is to identify the factors that determine sustainable waste management in cities and to predict the changes that will occur. Research methods: synthesis and comparison of concepts and methods in scientific literature, secondary data analysis, statistical data processing, and expert interview methods. Research results: It has been determined which factors and how they determine sustainable waste management in the country. The experts evaluated the alternatives—waste prevention, reuse, recycling, and optimization of landfills—according to the following criteria: economic, social, environmental protection, and technology. The most important criterion was determined to be the environmental protection criterion.
Existence and Multiplicity of Solutions for Fractional p-Laplacian Systems Involving Critical Homogeneous Nonlinearities
Authors: Zhang Shulin
Published: December 2024

This paper is concerned with a class of fractional p-Laplacian systems with critical homogeneous nonlinearities. Under proper conditions, the existence and multiplicity results of nontrivial solutions are obtained by variational methods. To some extent, our results improve and supplement some existing relevant results.
Towards a Unitary Formulation of Quantum Field Theory in Curved Spacetime: The Case of de Sitter Spacetime
Authors: Kumar K. Sravan , Marto João
Published: December 2024

Before we ask what the quantum gravity theory is, there is a legitimate quest to formulate a robust quantum field theory in curved spacetime (QFTCS). Several conceptual problems, especially unitarity loss (pure states evolving into mixed states), have raised concerns over several decades. In this paper, acknowledging the fact that time is a parameter in quantum theory, which is different from its status in the context of General Relativity (GR), we start with a “quantum first approach” and propose a new formulation for QFTCS based on the discrete spacetime transformations which offer a way to achieve unitarity. We rewrite the QFT in Minkowski spacetime with a direct-sum Fock space structure based on the discrete spacetime transformations and geometric superselection rules. Applying this framework to QFTCS, in the context of de Sitter (dS) spacetime, we elucidate how this approach to quantization complies with unitarity and the observer complementarity principle. We then comment on understanding the scattering of states in de Sitter spacetime. Furthermore, we discuss briefly the implications of our QFTCS approach to future research in quantum gravity.
Next Generation Self-Sanitising Face Coverings: Nanomaterials and Smart Thermo-Regulation Systems
Authors: Pattanaik Priyabrata , Venkatraman Prabhuraj D. , Tripathy Hara Prasada , Butler Jonathan A. , Mishra Dilip Kumar , Holderbaum William
Published: December 2024

Face masks are essential pieces of personal protective equipment for preventing inhalation of airborne pathogens and aerosols. Various face masks are used to prevent the spread of virus contamination, including blue surgical and N95 filtering masks intended for single use. Traditional face masks with self-sanitisation features have an average filtration efficiency of 50% against airborne viruses. Incorporating nanomaterials in face masks can enhance their filtration efficiency; however, using nanomaterials combined with thermal heaters can offer up to 99% efficiency. Bacterial contamination is reduced through a self-sterilisation method that employs nanomaterials with antimicrobial properties and thermoregulation as a sanitisation process. By combining functional nanomaterials with conductive and functional polymeric materials, smart textiles can sense and act on airborne viruses. This research evaluates the evidence behind the effectiveness of nanomaterials and thermoregulation-based smart textiles used in self-sanitising face masks, as well as their potential, as they overcome the shortcomings of conventional face masks. It also highlights the challenges associated with embedding textiles within nanomaterials. Finally, it makes recommendations regarding safety, reusability, and enhancing the protection of the wearer from the environment and underscores the benefits of reusable masks, which would otherwise pollute the environment. These self-sanitising face masks are environmentally sustainable and ideal for healthcare, the food industry, packaging, and manufacturing.
Organophosphorus Pesticides Management Strategies: Prohibition and Restriction Multi-Category Multi-Class Models, Environmental Transformation Risks, and Special Attention List
Authors: Wang Yingwei , Wang Lu , Li Yufei
Published: December 2024

Organophosphorus pesticides (OPs) have become one of the most widely used pesticides in Chinese agriculture; however, methods to identify potential restrictions on OPs molecules are lacking. Therefore, this study retrieved the OPs restriction list and constructed eight multi-class, multi-category machine learning models for OPs restrictions. Among these, the random forest (RF) model demonstrated excellent predictive performance, as it was successfully validated and applied. Potential environmental transformation products of OPs were obtained using EAWAG-BBD software, while toxicity indicators for the parent OPs and their transformation products were predicted with ADMETlab 3.0 software. This study found that unrestricted OPs, such as phorate, parathion, and chlorpyrifos, exhibited a high probability of toxicity. Additionally, the environmental transformation products of OPs posed similar comprehensive toxicity risks as the parent compounds. A special attention list for OPs was created based on the toxicity risks of unrestricted parent OPs and their transformation products, using standard deviation classification. Phorate and parathion were identified as OPs requiring special attention. This paper aims to provide an effective method for identifying the potential restriction levels of OPs and to propose an evaluation system that comprehensively considers the health risk, thereby supporting the improvement and optimization of management and usage strategies for OPs.
Proteotranscriptomic Profiling of the Toxic Mucus of Kulikovia alborostrata (Pilidiophora, Nemertea)
Authors: Kuznetsov Vasiliy G. , Melnikova Daria I. , Shabelnikov Sergey V. , Magarlamov Timur Yu.
Published: December 2024

Nemertea is a phylum of bilaterally symmetrical, coelomate, unsegmented worms, also known as ribbon worms. Most species of the phylum Nemertea are marine predators that contain toxins in the single-celled glands of the proboscis and/or integument. Recent transcriptomic studies have shown that nemerteans from all taxonomic groups possess a wide range of putative protein and peptide toxins, while the proteomic data for these animals are highly limited. In this study, proteotranscriptomic analysis was used to investigate the major protein components of the poison of the nemertean Kulikovia alborostrata. We identified 146 transcripts of putative toxins in the transcriptome of K. alborostrata and five putative toxins among the secreted proteins and peptides of the mucus of the animal. The expression levels of cysteine-rich peptides found in the mucus with similarity to known toxins were evaluated in different parts of the body of the worm by quantitative real-time PCR. The high level of expression of investigated peptides in the integument indicate the protective function of these toxins. Overall, this supports the idea that the mucus of nemerteans is a valuable source of peptide and protein toxins.
Intra-Individual Comparisons of [18F]fluorodeoxyglucose and Prostate-Specific Membrane Antigen Positron Emission Tomography in Prostate Cancer Patients Across Different Disease States: New Insights into Disease Heterogeneity
Authors: McGeorge Stephen , Pattison David A. , Dhiantravan Nattakorn , Thomas Paul A. , Yaxley John W. , Roberts Matthew J.
Published: December 2024

Background/Objectives: Prostate-specific membrane antigen (PSMA) PET/CT is more accurate than CT and bone scans for staging intermediate and high-risk prostate cancer (PCa). Fluorodeoxyglucose (FDG) PET has improved disease characterisation in metastatic castrate-resistant PCa (mCRPCa) and indicates patients with a particularly poor prognosis. The aim of this study was to assess the benefits of both PSMA and FDG PET in PCa staging by the direct intra-individual comparison of PSMA and FDG uptake patterns. Methods: Patients who underwent both PSMA and FDG PET/CT from 2015 to 2020 at our institution were identified and included if they had a histological or clinical diagnosis of PCa. Medical records were reviewed for demographic information and clinical details (including PSA, previous treatment, and disease status). Imaging interpretation was based on reporting by experienced nuclear medicine physicians. Results: Sixteen patients were identified. In 11 men with localised or hormone-sensitive PCa, PSMA-avid and FDG-avid disease was seen in 64% (n = 7) and 9% (n = 1) of patients, respectively. FDG-avid disease was present in 60% of patients with mCRPCa (n = 3/5), all of whom showed PSMA uptake. Of note, one patient showed higher initial FDG uptake that progressed in size and uptake on PSMA PET over 12 months. Conclusions: FDG PET might be useful in the assessment of patients with high clinical suspicion of metastases (e.g., high PSA, symptoms) with negative PSMA PET, particularly in castrate-resistant PCa.
Microsurgical treatment of cerebral aneurysms after endovascular treatment (systematic review of the literature). Part 2
Authors:   Moscow Regional Research and Clinical Institute (MONIKI), Dzhindzhikhadze R. S. ,   Moscow, Russian Federation, Gadzhiagaev V. S. ,   Moscow Regional Research and Clinical Institute (MONIKI); Moscow, Russian Federation, Polyakov A. V. ,   Moscow Regional Research and Clinical Institute (MONIKI); Moscow, Russian Federation, Zaytsev A. D. ,   Moscow Regional Research and Clinical Institute (MONIKI); Moscow, Russian Federation, Sultanov R. A. ,   Moscow Regional Research and Clinical Institute (MONIKI); Moscow, Russian Federation, Salyamova E. I. ,   Moscow Regional Research and Clinical Institute (MONIKI); Moscow, Russian Federation
Published: December 2024

To conduct a systematic review of the literature on microsurgical treatment of recurrent and residual
aneurysms after unsuccessful endovascular treatment, determine the surgical technique features depending
on the cause of aneurysm recurrence, localization, size, and shape of the aneurysm, and analyze treatment outcomes, including radical exclusion, complication rates, and clinical outcomes. Despite technical difficulties, microsurgical treatment of residual and recurrent aneurysms is a safe and effective method in most cases, with only a small number of patients requiring unconventional techniques such as coil removal, thrombectomy, or deconstructive procedures combined with revascularization. Aggressive treatment is recommended in all cases where long-term angiographic follow-up shows an increasing residual or recurrent aneurysm.
Computer Vision Syndrome and Cerebral Venous Circulation
Authors:   Samarkand State Medical University, Dzhurabekova A.T. ,   Bashkir State Medical University, Eshimova Sh. , Akhmadeeva L.R.
Published: December 2024

Computer vision syndrome (CVS) is a prevalent condition in the world. It develops after long hours with computers or mobile electronic devices. The main signs of CVS include optical, pain and fatigue. Limited data are published describing pathophysiological links between the blood circulation and CVS with no obvious correlations. The number of such studies is not enough. Evidence for effective methods of pharmacotherapy for CVS is lacking.
Purpose to analyze the cerebral blood circulation in young patients with CVS and its dynamics after using Gingko biloba extract in Uzbekistan Republic.
Material and methods. Eighty five patients with CVS were the participants of our open pilot study. They were divided into two groups: the main group (45 patients, 42% men, mean age 27,7 ± 7,1 year) and comparison group (40 patients, 50% men, mean age 31,6 ± 4,8 year). All study participants got standard therapy, but those in the main group also got 120 mg of Ginkgo biloba extract (40 mg 3 times a day) during 60 consecutive days. Three visits were assigned for each patient: before the start of treatment, on Day 30 and Day 60. The symptoms and ultrasound duplex-triplex scanning data were analyzed for venous hemodynamics assessment.
Results. The results show that 78,8% of our patients had abnormal venous circulation with increase linear blood flow velocity in vertebral veins and basal vein of Rosenthal. The statistically significant decrease of initially abnormally high parameters was observed beginning with visit 2 in the main group and beginning with visit 3 in the comparison group.
Conclusion. The results of the study can let us think about the possible influence of Ginkgo biloba extract to a better normalization of cerebral venous circulation in patients with CVS. More prospective studies with a bigger number of patients and more detailed clinical-and-instrumental data are needed
Spinal Cord Injury: New Concepts in Understanding the Work of Epidural Stimulants and Other Modern Treatment Methods
Authors:   N.A. Semashko Institute of Clinical Medicine of the Russian University of Medicine, Seleznev F.A. , Petrovskiy M.Yu. , Belov M.D. , Kotenev A.V. , Lisin A.V. , Rustamov A.T. ,   Russian University of Medicine,   I.M. Sechenov First Moscow State Medical University
Published: December 2024

Spinal cord injury is a serious condition that hundreds of thousands of people around the world face every year. Currently, there are many approaches to the treatment of patients with spinal cord injury, one of which is the method of epidural stimulation of the spinal cord. Many clinical and preclinical studies have shown encouraging results when using an epidural stimulator as a means of restoring locomotion after spinal cord injury. In addition, in recent years, the positive effect of epidural stimulation has been noted on other organ systems whose functions are impaired as a result of spinal cord injury. Other modern methods of treating patients with spinal cord injury based on the principles of optogenetics, neuronal stem cell transplantation, pharmacotherapy and the use of magnetic stimulation are also considered.
THE EFFECT OF TEMPERATURE AND STORAGE DURATION OF WASHED RED CELLS ON THE NUMBER OF ERYTHOCYTES
Authors: Andina Chika Alivia , Noviar Ganjar , Marliana Nina , Hayati Eem
Published: December 2024

Background: Blood services in Indonesia, including processing and storing donor blood, aim to ensure blood quality remains optimal. Washed Red Cell blood components are used for patients with severe allergies due to repeated transfusions, have a limited shelf life and are susceptible to secondary infections. Aims: Blood services in Indonesia, including processing and storing donor blood, aim to ensure blood quality remains optimal. Washed Red Cell blood components are used for patients with severe allergies due to repeated transfusions, have a limited shelf life and are susceptible to secondary infections. Methods: This research design uses a quasi-experiment with serial time measurements. Samples were taken from one bag of WRC donor blood from the Bandung City PMI Blood Transfusion Unit. Specimens were stored at room temperature (20-25°C) and refrigerator temperature (4-6°C) for 0, 3, 6, and 9 hours, and the number of erythrocytes was measured using a Haematology Analyzer. The results of the study showed that the average number of erythrocytes stored at room temperature was 7.54×10⁶/µL at the 0 hour examination, 6.37×10⁶/µL at the 3 hour examination, 5.40×10⁶/µL at the 6 hour examination. and at the 9 hour examination 4.56×10⁶/µL. Meanwhile, the average number of erythrocytes stored at refrigerator temperature was at the 0 hour examination 7.65×10⁶/µL, at the 3 hour examination 7.43×10⁶/µL, at the 6 hour examination 7.25×10⁶/µL, and at 9 hour examination 7.02×10⁶/µL. The results of the General Linear Model (GLM) statistical test show a sig value = 0.000 0.05. Conclusions: temperature and storage time have a significant influence on the number of erythrocytes.
ENERGI, KARBOHIDRAT, SERAT, DAN AKTIVITAS FISIK: KONTRIBUTOR KEGEMUKAN PADA SISWA SMA
Authors: Sholihah Siti Nurbayani , Judiono Judiono , Saleky Yohannes Willihelm , Rahmat Mamat , Pusparini Pusparini , Suprihartono Fred Agung , Fauziyah Raden Roro Nur
Published: December 2024

Obesity is a condition resulting from an imbalance between energy intake and expenditure, leading to excess energy stored as fat tissue. Factor contributing to obesity in adolescents primary stem from dietary patterns. This study aims to determine the relationship between energy intake, carbohydrate intake, fiber intake, physical activity, and obesity among 11th-grade students at SMA Negeri 1 Ngamprah, West Bandung Regency. A cross-sectional research design was employed, with a sample size of 48 students with random sampling. The sampling technique used was random sampling. Data collection involved interviews, questionnaires, and measurements of weight and height. The data was analyzed using Chi-square and logistic regression tests. The findings revealed that 26 students (54,2%) were obese, while only 2,1% met the daily fiber requirements. Significant relationships were found between energy intake (p=0,000), carbohydrate intake (p=0,000), and physical activity (p=0,003) with obesity. However, no significant association was found between fiber intake and obesity (p = 1,000). The variable that significantly influenced obesity was energy intake (p = 0,008; OR = 24,227; CI: 2,339-250,902), while carbohydrate intake (p = 0,076; OR = 4,837; CI: 0,848-27,597) and physical activity (p = 0,367; OR = 2,274; CI: 0,381-13,556) do not directly influenced obesity. Enhancing students’ understanding and behaviors regarding balanced nutrition, along with boosting physical activity through extracurricular activities, is necessary to reduce obesity among adolescents.
EDUKASI GIZI MENGGUNAKAN KALENDER EDUKASI STUNTING (KALSITING) MENINGKATKAN PENGETAHUAN IBU BALITA UNTUK PENCEGAHAN STUNTING
Authors: Rahmat Mamat , Isdiany Nitta
Published: December 2024

The stunting prevalence stunting in Cimahi as a result of the 2022 Indonesian Nutrition Status Survey  was 16.4. The prevalence of stunting is expected to 14% by 2024. The education level  and nutritional knowledge of toddler mothers is significantly related to the incidence of stunting. However, the education level and nutritional knowledge of toddler mothers in Cimahi are still low. Therefore, nutrition education is needed to increase the knowledge of toddler mothers regarding stunting. The study aimed to determine the influence of nutrition education using the stunting prevention education calendar (kalsiting) on the knowledge of toddler mothers for stunting prevention. This study used quasi experiment design, two groups with control group. The research location in Pasirkaliki Village, Kota Cimahi, West Java. The research sample was 30 mothers who had children aged 0-59 months. Statistical analysis used the Willcoxon test, independent t-test, Paired t-test, Mann Whitney U test. The results showed that the average score of knowledge increase in the treatment group was higher than that of the control group (p=0.031<0.05), there was a significant difference in the average increase in knowledge between the treatment group and the control group. However, there was no difference in the average increase in Z-Score height by age (HAZ)and weight by age (WAZ) before and after three months of nutrition education using leaflet media (p>0.05). Providing nutrition education using the media of the stunting prevention nutrition education calendar (Kalsiting) and by using leaflet media has been proven to significantly increase maternal nutrition knowledge.
Yeni Uygurcada Kanıtsallık Sistemi
Authors: Türkyılmaz Bahar
Published: December 2024

Kanıt kategorisi ya da kanıtsallık; alıcıya bilginin kaynağına hangi şekilde, ne ya da kimin aracılığıyla ulaşıldığına dair veriler sunan bir dil bilim kategorisidir. Kanıtsallık pek çok dilde dil bilgisel ayırt ediciliğe sahip olup aynı zamanda sözcüksel biçimlerle de elde edilebilmektedir. Bu çalışmada, Yeni Uygurcanın kanıtsal sistemi hem dil bilgisel hem de sözcüksel yönleriyle incelenmiştir. Çalışmanın yönteminde Johanson’un Türk dilleri temelinde oluşturduğu dolaylılık sistemi esas alınmış olup sözcüksel araçlar da bu çalışmada sistem içerisine dâhil edilmiştir. İnceleme için Yeni Uygurcada roman, destan, masal, efsane-rivayet, hikâye ve uzun hikâye (povest) gibi edebî türler arasından on iki eser seçilmiş ve tarama bu eserler üzerinde yapılmıştır. İnceleme üç basamaktan oluşmaktadır. Kanıt sisteminin ilk basamağı çekim ekleri olup bu kısımda görünüşsel açıdan sınır sonrasılık bildiren yapılar dolaylılık işlevinde karşıtlık ilişkisi temelinde değerlendirilmiştir. İkinci basamak ek fiil parçacıkları olup buradaki yapılar da karşıtlık ilişkisine göre irdelenmiştir. Üçüncü basamak olan sözcüksel biçimler ise her iki basamağın içerisinde kimi zaman kanıtsal anlamı tek başına barındıran kimi zaman da güçlendiren kullanımlarıyla değerlendirilmiştir. Yapılan incelemede, aynı alanın çekim ekleri olan -Iptu’nun -GAn’a nazaran dolaylılık kullanımlarının daha fazla olduğu görülmüş, -GAn’ın ise özellikle algısal kanıt türünde çalıştığı, bununla birlikte raporlayıcı kanıt türünü de kolaylıkla işaretleyebildiği tespit edilmiştir. Hem durum hem olay kodlaması yapabilen ek fiil parçacıklarından iken’in algısal, çıkarımsal ve raporlayıcı olmak üzere tüm kanıt türlerini işaretleyebilirken imiş’in ise yalnızca raporlayıcı kanıt türünde işlek olduğu saptanmıştır. Bununla birlikte hem çekim eklerinin hem de ek fiil parçacıklarının kanıt türlerini işaretlerken sözcüksel biçimlerle de desteklendiği görülmüştür.