bluuebunny/crossref_metadata_2025 huggingface dataset:
Eco-Innovative Construction: Integrating Green Roofs within the BIM Framework
Authors: Cascone Stefano
Published: December 2023

This research delves into the integration of green roofs with Building Information Modeling (BIM), a pivotal advancement in sustainable urban construction. Aligning with the United Nations Sustainable Development Goals, particularly Goal 11, the study explores how this integration can address global challenges like climate change and resource depletion. Using the Dynamo Visual Programming Language within Autodesk Revit, the research develops a computational modeling approach for green roofs, focusing on their thermal and structural characteristics under varied environmental conditions. Key findings demonstrate the significant influence of substrate and drainage material combinations on green roofs’ thermal performance, highlighting the need for tailored designs based on climatic conditions. The study also emphasizes the importance of considering structural performance in both dry and saturated conditions for overall building integrity. The research identifies gaps in current practices, such as limited focus on specific green roof materials and reliance on certain software tools, suggesting the need for broader material selection and software adaptability. Future research directions include expanding material selections, exploring diverse environmental conditions, and integrating green roofs with various BIM software platforms. The study's implications extend to stakeholders in the construction industry, offering a framework for architects, urban planners, and policymakers to design and implement green roofs aligned with environmental goals. This work contributes to the field by proposing a novel approach to sustainable construction, integrating ecological design with digital technology, and setting a new benchmark in the integration of green roofs with BIM. By addressing these aspects, the research paves the way for future developments in sustainable urban construction, enhancing the efficiency, sustainability, and resilience of urban communities in line with global sustainability objectives.
DNA Barcoding as a Plant Identification Method
Authors: Letsiou Stavroula , Madesis Panagiotis , Vasdekis Efstathios , Montemurro Cinzia , Grigoriou Maria E. , Skavdis George , Moussis Vasillios , Koutelidakis Antonios E. , Tzakos Andreas G.
Published: December 2023

In the last two decades, plant taxonomy has bloomed, following the development of a novel technique, namely DNA Barcoding. DNA barcodes are standardized sequences, ideally unique, coding or non-coding, either from the genome of the organism or from its organelles, that are used to identify/classify an organismal group; in short the method includes amplification of the DNA barcode, sequencing and comparison with a reference database containing the relevant sequences from different species. In plants, the use a universal DNA barcode, such as COI which is used in animals, has not been achieved so far. Several DNA barcodes from single loci as well as combinations of barcodes have been successfully used in various settings; additionally, as next generation sequencing becomes affordable, very long sequences- super barcodes, such as the chloroplast genome are being used successfully especially to distinguish between close species. In this review we summarize the work done on DNA barcoding in plants and discuss different approaches used so far.
A Study on Automated Problem Troubleshooting in Cloud Environments with Rule Induction and Verification
Authors: Poghosyan Arnak , Harutyunyan Ashot , Davtyan Edgar , Petrosyan Karen , Baloian Nelson
Published: December 2023

Remediation of IT issues encoded into domain-specific or user-defined alerts occurring in cloud environments and customer ecosystems in a vast majority of cases suffers from accurate recommendations which could be timely supplied for recovery of performance degradations. That, of course, is hard to realize through furnishing those abnormality definitions with an appropriate expert knowledge which varies from one environment to another. At the same time, in a large proportion of support cases, the reported problems under Global Support Services (GSS) or Site Reliability Engineering (SRE) treatment ultimately go down to the product teams making them waste costly development hours on investigating self-monitoring metrics of our solutions. Therefore, the mean-time-to-resolution (MTTR) rates of problems/alerts are significantly impacted from lack of a systematic approach towards adopting AI Ops. That would imply building, maintaining, and continuously improving/annotating a data store of insights that ML models are trained and generalized across the whole customer base and corporate cloud services. Our ongoing study is in line with such a vision and validates an approach that learns the alert resolution patterns in such a global setting and explains them using interpretable AI methodologies. The knowledge store of causative rules is then applied in predicting potential sources of the application degradation reflected in an active alert instance. In this communication, we share our experiences with a prototype solution and up to date analysis demonstrating how root conditions are discovered with a high accuracy for a specific type of problem. It is validated against the historical data of resolutions performed by heavy manual development efforts. We also offer a Dempster-Shafer theory-based rule verification framework for experts as a what-if analysis tool to test their hypotheses about underlying environment.
Cross-layer Methods for Ad Hoc Networks Review and Classification
Authors: Ivanov Valeriy , Tereshonok Maxim
Published: December 2023

OSI model used to be common network model for years. In the case of ad hoc networks with dynamic topology and difficult radio communications conditions, gradual departure is happening from the classical kind of OSI network model with a clear delineation of layers (physical, channel, network, transport, application) to the cross-layer approach. The layers of the network model in ad hoc networks strongly influence each other. Thus, the cross-layer approach can improve the performance of an ad hoc network by jointly developing protocols using interaction and collaborative optimisation of multiple layers. The existing cross-layer methods classification is too complicated, because it’s based on the whole manifold of network model layers combinations, regardless their importance. In this work, we review ad hoc networks cross-layer methods, propose the new useful classification of cross-layer methods, and show future research directions in ad hoc networks cross-layer methods development. The proposed classification can help to simplify the goal-oriented cross-layer protocol development.
Anterior Tarsal Tunnel Syndrome: Entrapment of the Articular Branch of Deep Peroneal Nerve
Authors: Moonot Pradeep , Karwande Nikhil , Dakhode Shubham , Thorat Tushar
Published: December 2023

Case:

A 28-year-old male patient who injured his ankle 2 years ago presented with unilateral ankle pain, tingling, and numbness for 1 year. Clinically, tenderness and positive Tinel sign were localized on anterior aspect of ankle. On exploration, deep peroneal nerve and mainly its articular branch were encased in fibrotic tissue. Decompression of both nerves resulted in symptomatic relief after surgery.

Conclusion:

High index of suspicion, a thorough medical history, meticulous clinical examination, complete knowledge of nerve anatomy, proper radiological studies, and careful surgical decompression are all necessary for the diagnosis and management of such atypical cases.
Redefining Bankruptcy Law: Incorporating the Principle of Business Continuity for Fair Debt Resolution
Authors: Kiemas Andre , Matheus Juan , Gunadi Ariawan
Published: December 2023

This study critically examines the inadequacies of the current Indonesian Bankruptcy Law, highlighting the conflicting nature of its debtors' insolvency declaration mandate, as stated in Article 2, verse (1). The research explores the philosophical basis of incorporating the principle of business continuity into future bankruptcy regulations to ensure fair, rapid, transparent, and efficient debt resolution for both debtors and creditors. Employing a normative legal research methodology, the paper investigates the inherent values of justice, legal certainty, and interests, along with general and bankruptcy principles. The study posits that the essence of bankruptcy law is not merely to protect creditors but also to ensure the survival and continuity of debtor businesses. The findings reveal that existing bankruptcy procedures, including insolvency examinations and financial report analysis, could be refined to better safeguard debtor businesses. This paper argues that an explicit elaboration of the business continuity principle in bankruptcy legislation could promote balanced legal protection in insolvency proceedings. The implications of this research can guide legislative reforms, ensuring a more equitable and efficient debt resolution process in the Indonesian bankruptcy system.Highlights:

The current Indonesian Bankruptcy Law struggles with issues of fairness and efficiency in resolving debt problems.
The principle of business continuity should be explicitly incorporated into bankruptcy legislation to ensure balanced protection for both debtors and creditors.
Legal examination mechanisms, such as insolvency examinations and financial report analysis, could be further refined to safeguard debtor businesses more effectively.

Keywords: Indonesian Bankruptcy Law, Debt Resolution, Business Continuity, Normative Legal Research, Legal Protection.
Alleviation of social injustices in STEM education: Harnessing pedagogical affordances of virtual and augmented reality applications through open learning
Authors: Dhurumraj Thasmai , Ramaila Sam
Published: December 2023

This paper explores the extent to which pedagogical affordances of virtual and augmented reality (VAR) applications can be harnessed as a means to alleviate social injustices in science, technology, engineering and mathematics (STEM) education through open learning. The enhancement of epistemic and epistemological access in STEM education requires coherent implementation of appropriate strategic interventions which are essentially geared towards the promotion of pedagogic innovation in its broadest sense. The empirical investigation adopted a qualitative research design located within the interpretivist paradigm. Qualitative data was collected through semi-structured interviews. The study is underpinned by the theory of social justice framework as a theoretical lens. Key findings emanating from the study demonstrated that sustainable integration of VAR applications in STEM education can essentially be harnessed as a catalytic tool to address the articulation gap between school and higher education through parity of participation within the broader South African context. The realisation of this key strategic imperative hinges to a large degree on the critical interrogation of enablers and constraints about sustainable utilisation of VAR applications in STEM teaching and learning.
Boosting Solar-Driven Water Evaporation through Selective Water Gating Enabled by Thermo-Responsive Sporopollenin
Authors: Tam Kam , Wang Yi , Zhao Weinan , Lee Yebin , Li Yuning
Published: December 2023

Solar-driven evaporation has emerged as a sustainable approach for water generation and purification. However, the undesirable heat loss leads to low energy conversion efficiency that limits water generation and impedes the scalability of this technology. Here, we developed a bilayer-structured solar evaporator (SDWEs) by engineering the fluidic flow within two water transport channels. A porous polydopamine (PDA) coating layer served as photothermal section and water supply microchannels, while the thermo-responsive sporopollenin layer on the bottom skeleton of the foam acted as a switchable water gating layer. Through confocal laser microscopy and micro-CT characterization, we demonstrated that this structural design enabled the selective and directional water transport. Noteworthy, this unique fluidic flow could facilitate the continuous supply of thin water layers and reduce the latent heat required for water evaporation. Therefore, the optimized p-SDWE sample achieved a high-water evaporation rate of 3.58 kg m−2 h−1 using 93.9% solar energy from 1 sun irradiation, and successfully delivered 18–22 liters of purified water per square meter of SDWE per day when treating brine water. This work elucidated the functions of water transport at the interface within the solar evaporator and presented a novel strategy for high-performance solar-driven water generation.
Evaluation of Geometric Errors in a Horizontal Lathe using the Indirect Calibration Method
Authors: Baldan Juliana Santiago , Rocha Guilherme Castilho Encinas da , Bertolini Marília da Silva , de Morais César Augusto Galvão
Published: December 2023

The aim of this study is to assess the geometric errors in a horizontal lathe, specifically focusing on the Indirect Calibration method. The research aims to provide insights into the quality and performance of the lathe's metrological processes. The application of the Indirect Calibration method to assess geometric errors in a mechanical lathe contributes to the field of metrology by offering a unique approach to error evaluation. The research involves the setup of an experimental structure according to the Indirect Calibration method. Data collection, storage of a linear variable differential transformer displacement (LVDT), application of the Least Squares Method, and statistical analysis with analysis of variance (ANOVA) are key research methods. The study reveals significant geometric errors in the mechanical lathe, with variations in error magnitude across different transverse positions. The position of the lathe's carriage significantly influences the errors. These findings provide valuable insights for the quality and precision of machined parts. The Indirect Calibration method can help manufacturers identify optimal machining positions, contributing to improved product quality.
GENESO a framework for pan-cancer classification and marker gene discovery by symmetrical occlusion method using deep learning
Authors: Zhao Xing , Wang Huating , Sun Hao
Published: December 2023

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results.
In this paper, we introduce "GENESO," a novel framework for pan-cancer classification and marker gene discovery using the symmetrical occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called "Symmetrical Occlusion". It collaborates with the baseline LSTM network, mimicking the "gain of function" and "loss of function" of genes to quantitatively evaluate their importance in pan-cancer classification.
By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. Through the integration of SO and selecting the top 33% of genes ranked by importance, the accuracy of the second network reaches an accuracy of 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNASeq data, employing known marker genes as a validation test.
Stress distributions around the interference fit between a round pin and a perforated finite plate
Authors: CASTAGNETTI Davide , Dragoni Eugenio
Published: December 2023

Interference fit couplings between a perforated finite plate and a round pin are widely used mechanical systems in several industrial applications. Only a few works in the literature investigate the coupling contact pressure due to interference in the absence of an external load, and these works are limited to a few specific configurations. To overcome this limitation, this work performs a numerical systematic investigation of the pin-plate coupling for a wide range of configurations that can be encountered in practice. Three are the variables investigated: the pin diameter, the plate length, and the pin offset in the longitudinal direction, all of them normalized over plate width, for a total of 18 configurations. The work provides a detailed prediction of the contact pressure and equivalent von Mises stress along the contact surface and compares the results with photoelastic investigations retrieved from the literature. For design purposes, the results are synthesized through two stress concentration factors, one referring to the peak contact pressure, and the second one to the peak von Mises stress.
The prevalence and influencing factors of COVID-19 in pregnant women in Hunan Province, China, immediately following the relaxation of epidemic control measures
Authors: Wang Yingxia , Liu yixu , Zou Kehan , Yang Min , Wu Yinglan , xie Donghua
Published: December 2023

Objective: To investigate the prevalence and influencing factors of COVID-19 in pregnant women in Hunan Province immediately following the relaxation of epidemic control measures.
Methods: This was a cross-sectional study with a multistage stratified sampling method. The questionnaire collected basic maternal information, data on COVID-19 infection status, and pregnancy-related information. The survey was conducted by trained investigators, and data quality checks were carried out twice per week.
Results: Among the 7761 included pregnant women, 5191 (66.9%) had a positive SARS-CoV-2 test result or related symptoms. The majority of maternal infections were mild (90.0%), and very few were severe and critical (0.4% and 0.1%), and headache and body aches (65.3%) were the most common symptoms. A total of 2711 (52.2%) women gave birth, and 449 (16.6%) newborns had infections. Logistic multivariable regression analysis showedthatpregnant women with an education level of junior college and above (OR=1.392, 95% CI: 1.182, 1.639), those with a monthly household income ≥3000 yuan and above (OR=1.175, 95% CI: 1.027, 1.344), those who lived with their family during family member infection (OR=1.476, 95% CI: 1.316, 1.655), and those with pulmonary (OR=1.408, 95% CI: 1.070, 1.854) or other (OR=1.398, 95% CI: 1.188, 1.645) underlying diseases were more likely to have COVID-19. A farmer/worker occupation type (OR=0.617, 95% CI: 0.484, 0.786) was a protective factor.
Conclusions: Many pregnantwomen had COVID-19 immediately following the relaxation of epidemic control measures, but most had mild cases, and few effects on newborns were observed. Mobility is the most critical factor influencing infection. The continued utilization of masks and adherence to social distancing measures remain crucial in mitigating COVID-19 transmission.
Normative values of motor performance and their relationship with BMI status in Hong Kong preschoolers
Authors: Yip Ka-Man , So Hung-Kwan , Tung Keith , Wong Rosa , Tso Winnie , Wong Ian , Yam Jason , Kwan Mike , Louie Lobo , Lee Albert , Wong Wilfred , Hui Lai-Ling , Nelson E.A.S. , Ip Patrick
Published: December 2023

This study aimed to establish sex- and age-specific reference values for motor performance (MP) in Hong Kong preschoolers aged 3–5 years old and examine the relationship between MP and BMI status. A cross-sectional study was conducted among 5,579 preschoolers in Hong Kong. Three MP tests were administered, and height and weight information were collected. GAMLSS was used to compute the normative values of the motor tests. Boys outperformed girls in activities requiring muscle strength and power, while girls outperformed boys in activities requiring balance and coordination. The MP scores increased with age for both overarm beanbag throw and standing long jump for both sexes, while the one-leg balance scores showed larger differences between P50 and P95 in older preschoolers. Children with excessive weight performed worse in standing long jump and one-leg balance compared to their healthy weight peers. This study provides valuable information on the MP of preschoolers in Hong Kong, including sex- and age-specific reference values and the association between BMI status and MP scores. These findings can serve as a reference for future studies and clinical practice and highlight the importance of promoting motor skill development in preschoolers, particularly those who are overweight or obese.
Urbanization Trends and Challenges: A Case Study in the Asan Watershed of Uttarakhand on Urban Growth Patterns and Sustainable Land Use Planning
Authors: Sharma Ankita , Nikam Bhaskar , Bagri Dhirendra Singh
Published: December 2023

Historical evidence suggests that urbanization is an inevitable and universal process, all over the world. Notably, urbanization has outpaced the average population growth rate, indicating the rapid pace of urban expansion. The case study focuses on the Asan watershed of Uttarakhand, one of India's highly urbanized states, where urban population growth is remarkable. The paper discusses the significance of raising urban diameter within the region based on specific criteria like decadal Census statistics and Land cover dynamics. It highlights the importance of accurate urban mapping and monitoring, using advanced technologies like remote sensing and GIS, to assess urban growth patterns and inform effective urban planning. Through the use of statistical techniques, remote sensing, and GIS, the study enables cost-effective and comprehensive urban studies to enhance decision-making. It also includes a comparative analysis of population statistics for India and its selective regions. The LULC changes exert substantial impacts on natural resources, socioeconomic factors, and environmental hydrological processes. The associate study requires the creation of decadal Land Use/Land Cover maps, areal analysis, validation through accuracy assessment, and the generation of urban growth pattern maps along with the direction of growth expansion. The analysis revealed a concerning trend of rapid urban expansion in the study area, which increased nearly four times over almost four decades, while the percentage of forest, plantations, cropland, and water bodies decreased significantly. The findings also highlighted the dominant directions of urban expansion over time. The study predicts that the eastern portion of the area is likely to continue dominating urban expansion in the future. Overall, the study provides valuable insights into the changing landscape and urbanization patterns within the region, emphasizing the importance of sustainable land use planning and environmental conservation efforts to address the challenges posed by rapid urban growth and its impact on natural resources.
Comprehensive Insights into Health Services Accessibility and Quality of Life of Families with Individuals with 22q11.2 Deletion Syndrome in Brazil
Authors: Silva Isabela Mayá Wayhs , Gil-da-Silva-Lopes Vera Lúcia
Published: December 2023

Background
The 22q11.2 Deletion Syndrome (22q11.2 DS) presents unique healthcare challenges for affected individuals, families, and healthcare systems. Despite its rarity, 22q11.2 DS is the most common microdeletion syndrome in humans, emphasizing the need to understand and address the distinctive healthcare requirements of those affected. This paper examines the multifaceted issue of health service access and caregivers’ quality of life in the context of 22q11.2 DS in Brazil, a condition with diverse signs and symptoms demanding multidisciplinary care. This study employs a comprehensive approach to evaluate health service accessibility and the quality of life of caregivers of individuals with 22q11.2 DS. It utilizes a structured Survey and the WHOQOL-bref questionnaire for data collection.
Results
Individuals with 22q11.2 DS continue to receive incomplete clinical management after obtaining the diagnosis, even in the face of conditions that enabled an average age of diagnosis that precedes that found in sample groups that are more representative of the Brazilian population (mean of 3.2 versus 10, respectively). In turn, caring for individuals with 22q11.2 DS who face difficulty accessing health services impacts the perception of quality of life associated with the caregivers' environment of residence.
Conclusions
Results obtained help bridge the research gap in understanding how caring for individuals with multisystem clinical conditions such as 22q11.2 DS and difficulties in accessing health are intertwined with aspects of quality of life in Brazil. This research paves the way for more inclusive healthcare policies and interventions to enhance the quality of life for families affected by this syndrome.
The Administrative Data Cystectomy Model and its Impact on Misclassification Bias
Authors: Ross James , Lavallee Luke T. , Hickling Duane , Walraven Carl van
Published: December 2023

Background:
Misclassification bias (MB) is the deviation of measured from true values due to incorrect case assignment. This study compared MB when cystectomy status was determined using administrative database codes vs. predicted cystectomy probability.
Methods:
We identified every primary cystectomy-diversion type at a single hospital 2009-2019. We linked to claims data to measure true association of cystectomy with 30 patient-hospitalization factors. Associations were also measured when cystectomy status was assigned using billing codes and cystectomy probability from multivariate logistic regression model with covariates from administrative data. MB was the difference between measured and true associations.
Results:
500 people underwent cystectomy (0.12% of 428 677 hospitalizations). Sensitivity and positive predictive values for cystectomy codes were 97.1% and 58.6% for incontinent diversions and 100.0% and 48.4% for continent diversions, respectively. The model accurately predicted cystectomy-incontinent diversion (c-statistic [C] 0.999, Integrated Calibration Index [ICI] 0.000) and cystectomy-continent diversion (C:1.000, ICI 0.000) probabilities. MB was significantly lower with imputed cystectomy-diversion type status using model-based predictions for both incontinent cystectomy (F=12.75; p<.0001) and continent cystectomy (F=11.25; p<.0001).
Conclusions:
A model using administrative data accurately returned the probability that cystectomy by diversion type occurred during a hospitalization. Using this model to impute cystectomy status minimized MB. Accuracy of administrative database research can be increased by using probabilistic imputation to determine case status instead of individual codes.
Long COVID and recovery from Long COVID: Quality of life impairments and subjective cognitive decline at a median of 2 years after initial infection
Authors: Szewczyk Warren , Fitzpatrick Annette L , Fossou Herve , Gentile Nicole L , Sotoodehnia Nona , Vora Surabhi , West T Eoin , Bertolli Jeanne , Cope Jennifer R , Lin Jin-Mann , Unger Elizabeth , Vu Quan M
Published: December 2023

Background:Quality of life (QoL) and cognition for those with Long COVID is not well-characterized, but existing research suggests impairments in both persist beyond 12 months after initial illness.
Methods:In this cross-sectional study, 435 participants with SARS-CoV-2 infection, confirmed with laboratory test or physician diagnosis, between March 2020 and December 2021 completed self-report surveys between March 2022 and September 2022 (n=7305 sent surveys; response rate=6.0%). Multi-domain QoL and cognitive concerns were evaluated using PROMIS-29 and the Cognitive Change Index-12. Those not recovered from COVID-19 at time of survey (“Current Long COVID”; n=181) and those who recovered from COVID-19 in >3 months (“Recovered Long COVID”; n=34), were combined to form a Long COVID group (n=215) and were compared with those who recovered from COVID in ≤3 months (“Without Long COVID”; n=220).
Results: Nearly half the participants (47.7%) were surveyed more than 2 years from initial infection (median=23.3 months; IQR=18.6, 26.7). The Long COVID group showed significantly greater proportion of moderate-to-severe impairment in all health domains assessed compared to those Without Long COVID (all p<0.05). The Recovered Long COVID group showed significantly lower prevalence of fatigue, pain, depression, and physical and social function impairment compared to those with Current Long COVID (all p<0.05). However, compared to patients Without Long COVID, the Recovered Long COVID group had greater prevalences of fatigue, pain (P≤0.06) and subjective cognitive decline (61.8% vs 29.1%; p<0.01).
Multivariate relative risk (RR) regression indicated Long COVID risk was greater for older age groups (RR range 1.46-1.52; all p≤0.05), those without a bachelor’s degree (RR=1.33; 95% CI=1.03-1.71; p=0.03), and those with 3 or more comorbidities prior to SARS-CoV-2 infection (RR=1.45; 95% CI=1.11-1.90; p<0.01). Each additional symptom experienced during acute COVID-19 was associated with a 14% greater Long COVID risk (RR=1.14, 95% CI=1.10-1.18; p<0.01).
Conclusions: Long COVID is associated with long-term cognitive complaints and diminished quality of life. Older age, not having a bachelor’s degree, and pre-existing comorbidities are risk factors for prolonged or non-recovery from COVID-19. Recovery from Long COVID was reported by a subset of those with Long COVID, though clinically significant cognitive complaints, fatigue, and pain persisted.
Methylene Blue (MB) removal from Aqueous Solution by Alum; Catalytic Ozonation Process
Authors: Ikhlaq Amir , Parveen Sehrish , Masood Zafar , Rizvi Osama Shaheen , Johani Eng. Thamer Abdulhameed Al , Ahsan Muffakir , Amjad Hadeeqa , Qi Fei
Published: December 2023

The Textile wastewater is among the most polluted types of industrial waste. Wastewater treatment in the textile industries is notoriously difficult because of the use of complex chemicals, Dyes in the textile production steps and conventional methods are not enough to treat these chemicals. Textile wastewater, known for its high pollution levels, poses challenges for treatment due to complex chemicals and dyes. A comparative study was conducted on simple ozonation and catalytic ozonation using alum as a catalyst for degrading methylene blue. Various factors like time, pH, catalyic and ozone dosage were analyzed. Results showed that catalytic activity in ozonation is pH and ozone flow dependent. pH 6.6 and 200V ozone flow achieved maximum methylene blue elimination. Scanning electron microscopy (SEM) was used to characterize surface morphology of catalyst, (FTIR) Fourier transform infrared spectroscopy was used to identify the important functional groups, and energy dispersive X-ray spectroscopy (EDS) was used to characterize the catalyst's elemental composition. Compared to simple ozonation, catalytic ozonation showed higher removal in the initial phase. Real textile wastewater analysis confirmed the effectiveness of alum catalyst in achieving significant removal of methylene blue (87%) through this novel cost-efficient process.
Development of new microplastic reference particles for usage in pre-defined numbers
Authors: Oster Simon D.J. , Bräumer Paul E. , Wagner Daniel , Rösch Max , Fried Martina , Narayana Vinay K.B. , Hausinger Eva , Metko Helena , Vizsolyi Eva C. , Schott Matthias , Laforsch Christian , Löder Martin G.J.
Published: December 2023

For almost two decades now, scientists have increasingly focused on the occurrence of microplastics in the environment and their impact on environmental and human health. Currently, the variety of analytical methods used in microplastic research result in data of different quality and resolution. This largely hampers comparability between data sets and consequently prevents a reliable risk assessment. In this context, the lack of suitable reference microplastic particles that can be added as internal standard in an exactly known number further prevents quality assessment of, and harmonization in terms of comparability between different analytical methods. Although this lack has widely been recognized, currently only reference microplastic particles in form of micro-beads or -fragments (powders) are commercially available. Manual addition of such reference microplastic particles to samples in a precisely defined number as an internal standard is inefficient and the alternative use of microplastic particle suspensions does not allow for the addition of an exactly defined particle number. The optimum solution to solve this issue would be reference microplastic particles embedded in an easy-to-use soluble matrix in exact numbers. This would allow for evaluating analytical quality during microplastic analysis as well as establishing harmonization in terms of comparability between different methods. In the present study we focused on the development of such reference microplastic particles. We used CNC milling for the production of small diameter plastic columns followed by gelatine embedment and subsequent cryosectioning. This results in gelatin slices containing an exactly defined number of reference microplastic particles with well-defined size, shape and polymer type / chemical composition that can be added to a sample easily with the dissolution of the gelatine. We successfully produced square shaped reference microplastic particles in a size range of 125–1000 µm of five different polymers. The overall size-deviation of the reference microplastic particles never exceeded ± 11.2% from the mean value of a set of particles. The highest percentage weight-deviation was 25.5% from the mean value of a set of 125 x 125 x 20 µm PS reference microplastic particles. Our approach allows for the production of reference microplastic particles tailored to specific needs of all different analytical methods used in current microplastic research. Beyond analytical method validation, these reference microplastic particles furthermore open possibilities for experiments on microplastics ranging from organismic uptake to environmental distribution.
Changes in physical properties with varying impregnation temperatures and compression times during fabrication of carbon blocks using needle cokes and pitch
Authors: Youn U-Sang , Lee Sang-Hye , Kim Jong-Bok , Roh Jae-Seung
Published: December 2023

Impregnation was conducted to decrease the pores formed during the carbonization process after manufacturing carbon blocks using needle cokes and coal tar pitch. This was carried out in the order of heating, subjecting to vacuum, and compression, and changes in mechanical and electrical properties before and after impregnation were analyzed with impregnation temperature and compression time as variables. The impregnation temperatures were 150, 200, and 250°C, and compression times were 30, 60, and 90 min. The optimal impregnation temperature was 200°C, resulting in a 12.5% increase in bulk density and a 26.0% decrease in porosity after impregnation of the carbon blocks. The optimal compression time was 60 min, leading to a 14.3% increase in bulk density and a 24.0% decrease in porosity after impregnation. Under the selected optimal conditions, after three impregnation cycles, the bulk density increased by 33.8% compared to the initial state (0 cycles 1.259 g/cm³ → 3 cycles 1.685 g/cm³), and porosity decreased by 56.8% (0 cycles 39.1% → 3 cycles 16.9%). According to the performance evaluation of carbon blocks, electrical resistivity decreased by 52.0% (72.5 µΩm → 34.8 µΩm) and flexural strength increased by 368.3% (6.0 MPa → 28.1 MPa). The substantial increase in flexural strength was attributed to the reduction in porosity.
Technological Vanguard: The Outstanding Performance of the LTY-CNN Model for the Early Prediction of Epileptic Seizures
Authors: yang yang , Luan Tianyun , Yu Zhangjun , Zhang Min , Li Fengtian , Chen Xing , Gao Fei , Zhang Zhijun
Published: December 2023

Background: Epilepsy is a common neurological disorder that affects approximately 60 million people worldwide. Characterized by unpredictable neural electrical activity abnormalities, it results in seizures with varying intensity levels. Electroencephalography (EEG), as a crucial technology for monitoring and predicting epileptic seizures, plays an essential role in improving the quality of life for people with epilepsy.
Method: This study introduces an innovative deep learning model, a lightweight triscale yielding convolutional neural network” (LTY-CNN), that is specifically designed for EEG signal analysis. The model integrates a parallel convolutional structure with a multihead attention mechanism to capture complex EEG signal features across multiple scales and enhance the efficiency achieved when processing time series data. The lightweight design of the LTY-CNN enables it to maintain high performance in environments with limited computational resources while preserving the interpretability and maintainability of the model.
Results: In tests conducted on the SWEC-ETHZ and CHB-MIT datasets, the LTY-CNN demonstrated outstanding performance. On the SWEC-ETHZ dataset, the LTY-CNN achieved an accuracy of 99.9%, an area under the receiver operating characteristic curve (AUROC) of 0.99, a sensitivity of 99.9%, and a specificity of 99.8%. Furthermore, on the CHB-MIT dataset, it recorded an accuracy of 99%, an AUROC of 0.932, a sensitivity of 99.1%, and a specificity of 93.2%. These results signify the remarkable ability of the LTY-CNN to distinguish between epileptic seizures and nonseizure events. Compared to other existing epilepsy detection classifiers, the LTY-CNN attained higher accuracy and sensitivity.
Conclusion: The high accuracy and sensitivity of the LTY-CNN model demonstrate its significant potential for epilepsy management, particularly in terms of predicting and mitigating epileptic seizures. Its value in personalized treatments and widespread clinical applications reflects the broad prospects of deep learning in the health care sector. This also highlights the crucial role of technological innovation in enhancing the quality of life experienced by patients.
RETRACTED: Total tithriiodothyronine level associated with disease severity for patients with emergent status
Authors: Wang Shuxia , Ge Gaoxia , Chen Mingxia , Wang Lei , Xu Shuhang , Yao Xiaoming
Published: December 2023

The authors have requested that this preprint be removed from Research Square.
Development of Respiratory Motion-Resolved Hepatobiliary Phase Cine-Magnetic Resonance Imaging for Stereotactic Body Radiotherapy in Liver Tumor
Authors: Shimada Ryuji , Sofue Keitaro , Tianyuan Wang , Ishihara Takeaki , Ueshima Eisuke , Ueno Yoshiko , Kusaka Akiko , Murakami Takamichi
Published: December 2023

Cine-magnetic resonance imaging (MRI) has been used to track respiratory-induced motion of the liver and tumor and assist in the accurate delineation of tumor volume. Recent developments in compressed sensitivity encoding (SENSE;CS) have accelerated temporal resolution while maintaining contrast resolution. This study aimed to develop and assess hepatobiliary phase (HBP) cine-MRI scans using CS. Phantom was imaged using cine-MRI and signal intensity (SI) and contrast ratio (CR) measured to determine the optimal flip-angle turbo field echo (TFE) prepulse delay. Twenty patients underwent HBP cine MRI after injecting gadoxetic acid every 0.5 s for 1 min. Acquired images had three different acceleration factors (SENSE, CS without denoising [CS-no], and CS with strong denoising [CS-strong]). The image quality of the HBP cine MRI was quantitatively and qualitatively analyzed. In the phantom study, a flip angle of 30 °and TFE prepulse delay of 150 ms were optimal for clinical imaging. In a clinical study, CS-strong showed the highest signal-to-noise ratio and comparable contrast ratio among the three sequences. The CS-strong group showed a significantly higher image quality (P < 0.01), except for motion smoothness (P = 0.11). CS with denoising improved the tumor-to-liver contrast and image quality in high-temporal-resolution HBP cine MRI.
Participants in a tourism city's environmental protection behavior: a game analysis
Authors: Zhu Linlin
Published: December 2023

The way that tourists behave when making decisions has a big impact on both the growth of tourism and the preservation of the environment. This paper builds a tripartite dynamic game analysis model of tourism development and environmental protection behavior from the perspectives of tourism city government, community, and tourism enterprises. It then computes the equilibrium solution of tripartite benefit maximization based on the dynamic game model. Based on this, the action plan for environmental protection during the development of tourism is presented in accordance with the three parties' best decision.The governments of tourist cities can increase the punishment for some behaviors that may damage the environment by establishing environmental protection regulations. At the same time, the role of the community in the development of the tourism city is played, and the participation of the community is helped in innovative ways. Tourism enterprises can actively introduce tourism professionals to enhance the overall service awareness of the tourism industry.
Synthesis of NaAlSiO4 Hollow Microspheres as Absorbents for the Removal of Heavy Metal ions in Environmental Remediation
Authors: Ouyang Zhiyuan , Meng Lihui , Hu Yanru , Li Wenchao , Zhu Fang , Xie Bin , Zhou Zilin , Cui Shuojie , Wang Meng , Wu Qingzhi
Published: December 2023

The harm of heavy metal ions to the environment has attracted increasing attention. Adsorption has been proven to be one of the best choices for controlling water pollution. Hollow microspheres with a high surface area and large internal space have been considered ideal adsorbents. In this work, NaAlSiO4 hollow microspheres were synthesized through a solvothermal method combined with calcination treatment. The removal ability of the hollow microspheres to heavy metal ions was evaluated using Ni(II) and Cd(II) as the models under different conditions, including different pH values, metal ion concentrations, and adsorption times. SEM and TEM images show that the average diameter of the hollow microspheres was approximately 2 ± 0.5 µm, and the average pore size was approximately 20 ~ 60 nm. The peak near 707°C in the DSC curve indicates the crystal transformation from an amorphous state to a well-crystallized state, and well-crystallized NaAlSiO4 microspheres can be obtained after calcination at 850℃. The maximum adsorption capacity of the hollow microspheres was 115.15 ± 1.68 mg·g− 1 for Ni(II) and 106.03 ± 0.97 mg·g− 1 for Cd(II). The adsorption of the NaAlSiO4 hollow microspheres depends on the surface area and content of CTAB for Ni(II) and Cd(II), respectively. The Ni(II) adsorption efficiency of the NaAlSiO4 hollow microspheres was still more than 95% after 4 cycles. This study provides an effective absorbent for removing heavy metal ions in wastewater treatment and environmental remediation.
The Effectiveness of an Educational Nursing Intervention on the Adherence to Therapeutic Regimen in Patients with Diabetes: an Interventional Study
Authors: Correia Luciana Isabel , Sa-Couto Pedro , Marques Sandra , Raínho Maria Conceição , Simões João Lindo
Published: December 2023

This study aims to assess the effect of an educational intervention performed by nurses on adherence to the therapeutic regimen (drug and non-drug) in patients with diabetes mellitus (DM) type 2. This is an analytical and interventional prospective quantitative study. A convenience sample was studied, composed of 102 participants with DM type 2, followed in a primary health care unit in the central region of Portugal. Data collection was carried out by applying the Summary of Diabetes Self-Care Activities Measure (SDSCAM) and the Psychometric Measure of Adherence to Treatments scale (PMAT) before and one month after the educational nursing intervention. Statistically significant differences were found between the first assessment and the assessment after the nursing educational intervention, in dimensions D1: General Food, D2: Specific Food, D4: Foot Care, and D5: Medications of the SDSCAM, and in the total value of the PMAT, revealing that, in general, the participants in the study improved in their self-care and in adherence to treatments after the educational session. So, an educational nursing intervention focused on adherence to the drug and non-drug therapeutic regimen, which involved the perspectives of the person with DM and family, will be effective in reaching the best potential in health, producing positive effects in changing diabetic patients’ behaviours and habits.
Analysis of Future Drought Characterization Under Multiple Drought Indices and Climate Change Impact Conditions for Developing Best Strategic Measures with CMIP-6 Climate Model in Mille Watershed, Lower Awash Basin, Ethiopia
Authors: Amognehegn Asnake , Nigussie Asmare , Assega Mihiretie , Adamu Anteneh , Adamu Gerawerk , Assefa Natnael
Published: December 2023

The agricultural sector is vulnerable to extreme phenomena such as droughts, particularly in arid and semi-arid environments and in regions where water infrastructure is limited. The objective of this study is to analyze future drought characteristics in meteorological, hydrology, and agricultural droughts under climate change in Mille watershed using three drought indices; Reconnaissance Drought Index (RDI), Streamflow Drought Index (SDI) and Agricultural Standardized Precipitation Index (aSPI). The study used baseline data (1985–2014) and future (2041–2100) downscaled from Coupled Model Intercomparison Project 6 (CMIP-6) based on the three Global Climate Models; (MIROC-6, CMCC and MRI) under two scenarios of the Shared Socioeconomic Pathways (SSP2-4.5, SSP5-8.5) with Soil and Water Assessment Tool (SWAT) model to simulate future streamflow for two future time horizons 2050s (2041–2070) and 2080s (2071–2100). as a result, in the future most hazardous Reconnaissance Drought Index (RDI) event occurred at Kombolcha, Mille, Batie and Sirinka with magnitude and frequency of 2050s (-1.51, 4.76%), 2058 (-1.49, 6.16%), 2063s (-1.52, 5.65%) and 2066 (-1.5, 4.48%) respectively, but in the annual time scale (SDI-12) extreme and severe hydrological drought events occurred 2088 (-2.00) and 2091 (-1.51) in SSP2-4.5 for study area, and also compared to other Mille and Batie stations experienced more frequently agricultural drought in terms of location. Generally, the RDI confirmed a significant drought trend in the past, while the frequency and severity of drought will increase in the future, however relatively less frequent hydrological drought events are observed in the study area and in the watershed both precipitation and streamflow will decline in the wet seasons and increase in the dry seasons. These findings may be useful for preparedness plans, including means for efficient monitoring and timely identification of drought events, is essential for informed decision making on drought mitigation and water management, especially for the water-dependent agricultural sector.