bluuebunny/crossref_metadata_2025 huggingface dataset:
NutritionDay: effective strategy for understanding nutritional risk factors and facilitating the implementation of nutritional care protocols - an analysis over the years
Authors: de Andrade Grasiela Konkolisc Pina , Rodrigues Ana Lucia Chalhoub Chediac , Suiter Erika , Yamashita Luciana Miyuki , Madeira Jessica , Carvalho Juliana Bonfleur , Yamaguti Adriana , Boilesen Sabine Nunes , Severine Ariane Nadolskis , Machado Silmara Rodrigues
Published: September 2024

Background
Hospital malnutrition is a global debilitating problem; therefore, the implementation of nutritional monitoring protocols is essential for its early diagnosis and translates into better care. NutritionDay emerged from the need to document the global malnutrition scenario to improve patient safety and the quality of nutritional care. Our objective was to analyze nutritional care data from a high-complexity hospital obtained through the NutritionDay and to compare these data between years and with the results of other institutions in order to identify areas for nutritional care improvement.
Methods
A one-day cross-sectional retrospective study was conducted at the NutritionDay global data collection date. The data were analyzed by comparing the nutritional care provided at the hospital in 2019 with national and global scenarios. Additionally, data on nutritional care in our hospital from 2017 to 2020 was compared. Quantitative variable groups were compared by the Student’s t-test. Relationships were analyzed using the Pearson’s chi-square test or the Fisher’s exact test for categorical data. The significance level was set at 10.
Results
Weighing on admission is a point of improvement for all groups. In our hospital it led to the creation of an institutional indicator for its monitoring. From 2017 to 2020, nutritional screening and assessment used the body mass index (BMI) and a non-validated tool until 2018. After 2019, we adopted nutritional risk screening (NRS2002) and a tool based on the Global Leadership Initiative on Malnutrition (GLIM) to improve nutritional care. We found a trend towards improvement in satisfaction with the diet provided, which was associated with a significant increase in meal consumption and which is due to the monthly monitoring of meal satisfaction that generate action plans. We notice an increase in dietary restrictions reported by patients associated with adhering to a healthier diet. Thus, the composition of the meals changed over the years, with a decreased use of processed products.
Conclusion
The analysis of NutritionDay data is an effective strategy for better understanding nutritional risk factors, enabling comparisons with other services and facilitating the implementation of enhanced nutritional care protocols.
Effects of multi-frequency acoustic waves on the agglomeration of fog droplets
Authors: Ibrahim M. Y. , El-Khazali Reyad , Francis Diana , Nelli Narendra
Published: September 2024

This work focuses on using multi-frequency sound waves to dissipate fog. It is a promising fog-dissipation technique due to its ease of control, flexibility, environmental friendliness, and no interference with traffic flow. This study introduces a novel approach to dissipate artificial fog generated inside an experimental setup utilizing harmonically related multi-frequency acoustic waves. Fundamental frequencies of 300 Hz, 400 Hz, and 500 Hz, along with their 9th, 11th, and 40th harmonics were tested at a maintained Sound Pressure Level (SPL) of 112 dB. Many combinations were found to increase fragmentation of large droplets, which reduces the condensation efficiency. The main mechanism for acoustic condensation seems to be the collision and merging of fog droplets. Most harmonics tested did not improve agglomeration, with the notable exception of the 400 Hz paired with its 9th-harmonic. This combination resulted in a 61.06% reduction in Liquid Water Content (LWC) for large droplets and a 90% condensation effect achieved quicker than all the other cases. These findings highlight the potential of using harmonics for acoustic fog dissipation.
Shapley Value-based Data Valuation for Machine Learning Data Markets
Authors: Baghcheband Hajar , Soares Carlos , Reis Luis Paulo
Published: September 2024

Data valuation is the act of assigning a monetary value to data based on its estimated usefulness, potential impact, and scarcity. In the current landscape of digital technology, data has emerged as a valuable resource for various entities such as organizations, governments, and individuals. Consequently, data valuation plays an increasingly important role in managing data assets, ultimately facilitating informed decision-making in relation to data acquisition, sharing, analysis, and even monetization. In the context of the Machine Learning Data Market, a platform to exchange data considering its value, data valuation has an important role in putting economic value before trading data. The Shapley Value has assumed a central role in data valuation, due to its equitable value distribution among contributors. This paper focuses on data valuation within the context of the Machine Learning Data Market (MLDM). Our primary objective is to investigate whether data valuation methods based on the Shapley Value can result in improved performance in MLDM. We introduced the Gain Data Shapley Value (GDSV) method. This paper presents an extensive empirical study of its behavior and compares GDSV with performance-based data valuation in MLDM under different configurations and learning algorithms. Our findings confirm that considering the contribution of the data set to performance scores can lead to systematic improvements in learning performance.
Effect of a 16-week Combined Supervised Exercise Program after bariatric surgery on Sarcopenia parameters based on FNIH, EWGSOP2, EASO/ESPEN criteria – The results of the EXPOBAR randomized trial program
Authors: Mendes Cláudia , Carvalho Manuel , Cabo Carolina , Bravo Jorge , Martins Sandra , Raimundo Armando
Published: September 2024

Introduction:
Bariatric surgery is a recognized treatment option for severe obesity, and its effectiveness in reducing weight and controlling obesity-related conditions has been demonstrated. However, it can also lead to decreased skeletal muscle mass and strength, increasing the risk of sarcopenia after surgery. This randomized clinical trial studied the effects of a 16-week supervised combined exercise program on sarcopenia in bariatric surgery patients.
Methods
Thirty-seven surgery candidates participated in the EXPOBAR (EXercise POst BARiatric) program and were randomized into experimental or control groups. The intervention lasted 16 weeks, starting one month after surgery, and included a supervised combined aerobic and resistance exercise intervention. The outcomes, including body composition and physical fitness parameters, were assessed at four time points. All participants underwent gastric bypass surgery (RYGB).
Results
The EXPOBAR trial revealed significant and meaningful effects of the exercise intervention on anthropometric indices, such as weight (p = 0.039) and waist circumference (p = 0.010). The EXPOBAR trial also showed that after bariatric surgery, there was a clear decrease in muscle mass, and this loss continued through the duration of follow-up, despite the exercise protocol. The most substantial improvements were observed in physical function and strength metrics (p = 0.005 and p < 0.001, respectively), along with a reduction in fat mass (p = 0.006), indicating the intervention’s effectiveness in enhancing both physical fitness and body composition.
Discussion
Current findings indicate that following an initial decrease due to bariatric surgery, a combined exercise intervention significantly improves functional physical capacity and strength. The exercise program in this study effectively reversed the surgery-induced loss in function and strength, reducing the number of patients at risk of sarcopenia. Physical and functional capacity are crucial noninvasive indicators for diagnosing muscle quality and sarcopenia.
Conclusion
Long-term management of sarcopenia and sarcopenic obesity in bariatric surgery patients requires frequent monitoring of body composition and muscle function. This approach is essential for tracking progress and optimizing treatment strategies over time. This study highlights the importance of integrating structured exercise programs into after bariatric surgery care to mitigate the risk of sarcopenia. Future options include nutritional protein supplementation and changes in the exercise protocol.
Trial registration
: The trial was registered at Clinicaltrials.gov (NCT03497546).
Environmental role of modified zeolite minerals in mercury removal in water and wastewater : Recoverability with maximum removal of mercury ions
Authors: jahani farahnaz
Published: September 2024

The natural clinoptilolite zeolite was treated with NaOH and heat. The modified zeolite was then investigated by Field-emission Scanning Electron Microscope (FESEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and BET techniques. The modified zeolite managed to remove mercury ions up to 95%; while raw zeolite showed the maximum Hg removal ability of 35%. Also, the modified zeolite was reused seven times with stable adsorption of mercury ions. Based on the kinetic studies, the adsorption of mercury ion by modified zeolite follows the pseudo-second order model. Moreover, the experimental data were better fitted with Langmuir isothermal model than Freundlich. The removal of toxic mercury ions could serve as a useful solution for today's environmental issues.
Direct collaboration between hospitals and NGOs, an essential tool to reinforce linkage to care in People living with HIV
Authors: Aldámiz-Echevarria Teresa , Fanciulli Chiara , Lopez Monica , Perez Leire , Tejerina Francisco , Sanchez David , Lodeiros Blanca , Lopez Juan Carlos , Berenguer Juan , Bellon Jose Maria , Ferris Maria , Blazquez Mario , Calvo Almudena , Domene Mario , Vegas Oswaldo , Rodriguez Carmen , Muñoz Patricia , Gijon Paloma , Montilla Pedro , Bermudez Elena , Valerio Maricela , Alonso Roberto , Padilla Belen , Ventimilla Cristina , Diez Cristina
Published: September 2024

With the aim of improving access and engagement to healthcare in people living with HIV (PLHIV), in 2022 Gregorio Marañón Hospital and the NGO COGAM developed a circuit for recruitment and referral to hospital. Program targeted PLHIV who were neither receiving antiretroviral treatment (ART) nor on medical follow-up (FU); but also, individuals at risk who underwent screening tests at the NGO and, if positive, were referred for confirmation. The result was an increase in annual new PLHIV seen in hospital by reaching a population who were, essentially, young men (94% male, median age 30 years), migrants (95%) with recent diagnosis of HIV (median 5 years) and who were recently arrived in Spain (median 5 months). Most of them hadn´t healthcare coverage (78%). In multivariate analysis, that included all PLHIV seen for the first time in the ID Unit between 2019 and 2022, lack of healthcare coverage was the only independent predictor of lost to FU that reached statistical significance (HR 5.19, CI 2.76–9.47). Furthermore, time from HIV diagnosis to ART initiating was shortened from 14 to 6 days without affecting linkage to care. Our conclusion is that collaboration with NGOs reinforce diagnosis, FU, and adherence to ART for PLHIV.
Enhancing Reproductive Health Among Adolescent Girls in India: Results of An Individualized RCT to study the efficacy of the Go Nisha Go Mobile Game
Authors: Raj Aparna , Shankar Lalita , Dixit Anvita , Saha Ananya , Battala Madhusudana , Khan Nizamuddin , Ayyagari Kavita , Saggurti Niranjan , Howard Susan
Published: September 2024

Background
Adolescent girls in India face significant barriers to accessing sexual and reproductive health (SRH) information and services. Digital interventions, particularly mobile-based ones, promise to deliver SRH education in a fun and engaging manner. These can be offered privately directly to the adolescent, allowing players to ‘experience’ the outcomes of their choices, receive tailored feedback, and the option to ‘try again’.
Methods
This study evaluated the efficacy of "Go Nisha Go®" (GNG), a low-end smartphone-based digital game for adolescent girls in India, using a two-armed, encouragement-led, randomized controlled trial (RCT). The study involved 1,950 participants from Patna, Jaipur, and Delhi NCR. The intervention group received encouragement to play GNG, while the control group did not. Key constructs measured included menstrual health management (MHM), contraception knowledge, and agency. Data were collected at baseline and a ten-week follow-up.
Results
The intervention group showed significant improvements in various MHM parameters, contraception knowledge, and agency outcomes compared to the control group. Overall, 1,697 out of 1,993 participants completed the study after ten weeks (85%). The intervention group's awareness of menstrual hygiene products increased from 33–92%, while comprehensive knowledge of oral contraceptive pills (OCPs) rose from 2–17%. Confidence in negotiating contraception use increased from 60–85%, and the attitude of refusing sex when not ready improved from 61–85%.The subjects in the game group showed high levels of satisfaction with the app, with 74% discussing the game with others and 66% recommending it. The belief in negotiating marriage decisions with parents also improved more in the intervention group than in the control group.
Conclusion
The findings of the first-ever RCT outcome evaluation for a digital mobile game app for enhancing SRH education among adolescent girls in low-resource settings support the efficacy of digital games for health like GNG. The game's engaging and interactive format effectively communicated complex and sensitive SRH information, empowered participants, and encouraged critical health behaviors through informed decision-making. Future studies could explore the long-term sustainability of behavior changes induced by such interventions and their effectiveness across different settings and populations.
Trial Registration: CTRI/2023/03/050447
Registration date: March, 2023
Quality priorities related to the management of type 2 diabetes in primary care: Results from the COMPAS+ quality improvement collaborative
Authors: Gaid Dina , Giasson Guylaine , Gaboury Isabelle , Houle Lise , Layani Géraldine , Menear Matthew , Tilly Véronique Noël , Pomey Marie-Pascale , Vachon Brigitte
Published: September 2024

Structured Abstract
Background: This study aims to describe the main type 2 diabetes mellitus (T2DM) quality improvement (QI) challenges identified by primary care teams in the province of Quebec who participated in the COMPAS+ QI collaborative.
Methods: A qualitative descriptive design was used to analyse the results of 8 COMPAS+ workshops conducted in 4 regions of the province between 2016 to 2020. Deductive content analysis was performed to classify the reported QI priorities under the Consolidated Framework for Implementation Research domains; and proposed change strategies under the Behavior Change Wheel (BCW) intervention functions.
Results: A total of 177 participants attended the T2DM COMPAS+ workshops. Three QI priorities were identified: 1) lack of coordination and integration of T2DM care and services; 2) lack of preventive services for pre-diabetes and T2DM; and 3) lack of integration of the patient-as-partner approach to support T2DM self-management. The proposed QI strategies to address those priorities were classified under the education, training, persuasion, habilitation and restructuring BCW intervention functions.
Conclusion: This study provides insights on how QI collaboratives can support the identification of QI priorities and strategies to improve T2DM management in primary care.
Exploration of the use of machine learning and natural language processing techniques to identify patients who are medically cleared for psychiatric placement among hospitalized patients
Authors: Verma Ritchie , Lipten Samuel D. , Jernigan Michael
Published: September 2024

Purpose
Psychiatric patients who are hospitalized generally require medical clearance before they can be transferred to a psychiatric facility to receive care. Their hospitalization typically ends up being prolonged beyond medical clearance, resulting in significant costs and length of stay burdens on the hospital and delays in receiving psychiatric care. In this study, we explored how different open-source natural language processing (NLP), and machine learning (ML) techniques might assist in identifying patients who are medically cleared to be discharged to inpatient psychiatry wards among hospitalized patients.
Methods
We retrospectively examined patients hospitalized on the medical floors of a 1,063-bed academic medical center during 2020. The Internal Medicine provider notes were classified into “Cleared” vs “Not Cleared” to train a supervised machine learning model. Logistic regression (LR) and support vector machine (SVM) models, among other classifiers, were used. The accuracy results were compared with those of the rule-based approach.
Results
LR and SVM achieved very high accuracy scores on unseen data, with accuracies of 93.6% (95% CI 89–98%) and 91.2% (95% CI 86–96%), respectively. Comparatively, the rule-based approach using regular expression yielded 86.8% (95% CI of 81–93%) accuracy. AUC/ROC score for machine learning approach was 0.96.
Conclusion
Open-source NLP and ML techniques are quite sophisticated in providing high accuracy in text-based classification tasks. These approaches can be replicated to automate the chart review process for both research and clinical decision support, saving countless hours of manpower.
Changes of vertical dimension and alveolar bone remodeling in patients with second molar scissors bite during orthodontic correction
Authors: Guo Feng , Wang Chenxu , Hu Hengyu , Lei Lang
Published: September 2024

The aims of this retrospective study were to assess changes of vertical dimension and alveolar bone remodeling in cases with second molar scissors bite (SB) before and after intermaxillary cross-elastics (ICE) treatment. 36 patients with unilateral SB (SB group) and 36 subjects with normal occlusion (Control group) were included. CBCT records were taken before (SB-T0) and after orthodontic treatment (SB-T1). Alveolar bone height (ABH) and thickness (ABT), tooth and alveolar bone inclination, molar and facial height were measured. No changes on the vertical dimension were observed during treatment. Surrounding alveolar bone displayed synchronous changes in the inclination with molars for both arches. After ICE, the maxillary alveolar bone was found thinner at buccal side (P < 0.05), while no difference was found at the palatal side. The mandibular alveolar bone was found thicker at buccal side and thinner at lingual side (P < 0.05). Nevertheless, no difference in the alveolar bone thickness was observed between SB-T1 group and Control group. ICE is a safe method to correct SB with stability of vertical dimension and safety of periodontal bone. Buccolingual inclination of the alveolar bone changes with the molar tooth movement, showing a bone bending tendency during SB correction.
Concurrent Estimation of Pregabalin and Etoricoxib by New Stability Indicating Rp-uplc Approach- Application in Assay of Commercial Tablets
Authors: Ponnekanti Krishnaphanisri , Godela Ramreddy
Published: September 2024

The present research aims to establish new stability indicating RP-UPLC method for concurrently estimating Pregabalin and Etoricoxib in blended powder and their combined tablet formulation. The effective separation of Pregabalin and Etoricoxib achieved with HSS column C18 (150x2.1mm,1.8µm), 0.1% orthophosphoric acid: acetonitrile in 65:35 v/v) at a flow rate of 0.3mL/min, and isocratic elution at 228nm. The elution of PRB and ETB was noticed at 1.56 and 2.01 minutes, with good resolution and system suitability with the developed approach. PRB and ETB have shown linear responses from 18.75 to 112.5µg/mL and 15 to 90µg/mL, respectively. The range of the % RSD for intraday and inter-day precision was 0.33 to 0.81. The LOD and LOQ of Pregabalin and Etoricoxib were computed to be 0.07 µg/mL, 0.21 µg/mL, and 0.01µg/mL, 0.04 µg/mL, respectively, by standard deviation method. The validation method was carried out using ICH standards. The stability- indicating the feature of the method was confirmed by the forced degradation studies where degradants generated by stress testing were clearly distinguished from the peaks of analytes. The shorter elution period and superior sensitivity of both analytes with this method are appropriate for regular analysis of Pregabalin and Etoricoxib.
A novel electromagnetic forming actuator for curved sheet forming: analytical optimization, simulation, and experimental validation
Authors: Hu Yang , Lai Zhipeng , Li Changxing , Gong Mengyuan , Xu Wei , Zhang Zixuan , Jiang Yuze , Cao Quanliang , Han Xiaotao , Li Liang
Published: September 2024

A newly-designed electromagnetic forming actuator has been proposed to enable curved-geometry sheet metal forming, cannot be efficiently realized by conventional electromagnetic forming. In the pursuit of fast designing the actuator, an analytical model was derived to obtain the relationship between the produced magnetic pressure and the system geometric parameters of the actuator. Based on this analytical formulation, we explored the regulatory behavior and impact mechanism of various parameters of the actuator on the magnetic field, magnetic pressure, and efficiency of the forming system, which has been validated by the results from finite element simulations. A design criterion is proposed for optimization of the actuator. And accordingly, a series of experiments have been performed to validated the feasibility of the proposed actuator for electromagnetic calibration.
The impact of performing arts on mental health, social connection, and creativity in university students: A Randomized Controlled Trial
Authors: Agres Kathleen Rose , Chen Yifan
Published: September 2024

Background: University students often face mental health challenges, exacerbated by stigmas that hinder seeking support and treatment. We introduce a participatory arts programme, Movin' and Groovin' for Wellness (MGW), that features facilitated drumming and dancing sessions. This study aimed to investigate the impact of the MGW programme on students' mental health, social connections, and creativity.
Methods: A 10-week pilot parallel Randomised Controlled Trial (RCT) was conducted with 76 participants randomly assigned into an Experimental (MGW) group (N=38) or a Control group (N=38). Data were collected at baseline, midway, and post-intervention. Mental health was evaluated using the Depression, Anxiety, and Stress Scale-21 (DASS-21), and quality of life via the WHO Quality of Life-BREF (WHOQOL-BREF) scale. The Brief Resilient Coping Scale, Lubben Social Networking scale, Experience of Creation scale, Brief Resilient Coping scale, and Brief Music in Mood Regulation scale (B-MMR) were also administered. Qualitative feedback was gathered through a bespoke survey and focus group discussion (FGD), focusing on participants' subjective experiences of the programme, mood/emotion states, social connections, and creative expression.
Results: The MGW programme led to significant improvements in mental health, quality of life, and creativity, while the Control group experienced significant declines in mental health and quality of life during the term. The Experimental group showed significant reductions in Stress scores (DASS-21) at Week 10, whereas the Control group had significantly worse anxiety, depression, and stress at Week 5, with stress scores remaining elevated at Week 10. Improvements in the Experimental group were also observed in the Psychological (at Week 5) and Physical (at Week 10) domains of the WHOQOL-BREF. In comparison, the Control group showed a significant decrease in WHOQOL-BREF Physical scores at Week 10. The Experimental group also showed enhanced creativity (Experience of Creation scale) at Week 5 and Week 10, although no significant changes were observed in the social networking or resilient coping scales. Qualitative findings highlighted the programme's positive impacts on participants' mental health, social connections, and creativity.
Conclusions: The MGW programme effectively improved mental health, quality of life, social connection and creative expression among university students. These findings suggest that arts-based interventions such as MGW can support student health and well-being in a stigma-free and culturally appropriate manner.
Trial registration: The trial was retrospectively registered at ClinicalTrials.gov under ID: NCT06542003.
Reliability, Availability and Maintainability Analysis of Machining Line at Engine Manufacturing Plant
Authors: Mahajan Tushar , Gargama Heeralal , Sonawane Lokesh
Published: September 2024

In today's competitive manufacturing landscape, operational excellence is vital. Continuous production depends on optimal machine performance to meet high demand. Unplanned downtime threatens revenue. This paper presents a case study of Reliability, Availability, and Maintainability (RAM) analysis of a machining line with 14 machines at an engine manufacturing plant. The analysis aims to address frequent machine failures and improve reliability and availability, enhancing overall plant efficiency. To perform the RAM analysis, comprehensive failure and maintenance time data for all machines were collected over the past year. After data collection, thorough cleaning and analysis techniques were applied to evaluate various statistical parameters of the reliability and maintainability models. Given the non-exponential failure and repair distributions, Semi-Markov Process (SMP) modelling was employed for availability assessment. The analysis computes RAM indices for all machines, offering insights into their current operating status. It includes a comparative study of machine failure frequencies and examines availability, maintainability, and reliability features for different machines in the production facility. It also presents reliability versus time plots for individual machines and the entire machining line. These results guide identifying critical machines, optimizing maintenance practices to minimize downtime, and provide insights for exploring Reliability-Centered Maintenance (RCM) strategies.
Modeling Body Part Interactions for Skeleton-Text Contrastive Learning in Action Recognition
Authors: Liang Shuang , Qian Ruihao , Zhuang Zikun , Xie Chi
Published: September 2024

Skeleton-based action recognition has garnered significant attention due to its efficiency and robustness. Recent advances in skeleton-text contrastive learning show promise but overlook interactions between skeleton parts. This paper proposes a part interaction module that models these interactions to align skeleton features with descriptive texts. Experiments demonstrate that incorporating this module leads to notable improvements, establishing a new state-of-the-art on popular benchmarks. Our work underscores the importance of part interactions for action recognition.Code is released at https://github.com/ReskyQian/Body-Part-Interactions.
Integrated Attention Network for Handwritten Mongolian Historical Archive Text Detection with Swin Transformer
Authors: Liuxu Ding , Yuefeng Liu
Published: September 2024

Text detection is a vital step towards the intelligent management of historical archives. With the development of CNNs, numerous effective methods for archive text detection have been proposed. However, text detection networks and publicly available data for Mongolian historical archives are still limited. Moreover, historical archives often feature blurred text and complicated writing backgrounds, which pose significant challenges for text detection. To address these issues, this paper introduces a text detection network, ESFCENet, specifically designed for Mongolian historical archives, integrating attention and Swin Transformer. Specifically, we propose an improved Swin Transformer (SWT) module that optimizes multi-scale archive text detection by fusing global text feature information, enhancing text feature extraction in the presence of blurred fonts and complex backgrounds. In addition, we introduce an Efficient Channel and Self-Attention Integration Module (ECASI), which suppresses redundant background information while enhancing feature extraction of foreground information. Finally, to facilitate research in this field, we have compiled a Mongolian dataset. Experimental results demonstrate that our proposed network achieves accurate text detection on Mongolian historical archives, with an F-measure reaching 99.0%. It also shows promising ability on multiple related benchmarks, e.g., an F-measure of 87.9% on ICDAR 2015, 85.7% on CTW1500, and 86.6% on Total-Text.
Dual-guided Multi-modal Bias Removal Strategy for Temporal Sentence Grounding in Video
Authors: Ruan Xiaowen , Qi Zhaobo , Xu Yuanrong , Zhang Weigang
Published: September 2024

Temporal Sentence Grounding in Video aims to locate target video segments related to the input textual query within a given video, which is severely affected by the biases, leading to a significant decrease in the generalization performance. However, existing debias methods only remove a limited amount of bias and do not consider the more significant multimodal bias. In this work, we verify the existence of multimodal bias through comparative experiments, and further propose a Dual-guided Multi-modal Bias Removal Strategy (DMBR) to address this issue. Based on the span-based natural language video localization paradigm, DMBR extracts salient text concepts, such as verbs, nouns, and numerals, and visual concepts, such as actions contained in the input video, to guide the generation of multimodal biases, which can simulate all potential multimodal biases in a dual and complementary manner through Language Guided Multi-modal Bias Generator and Video Guided Multi-modal Bias Generator. Meanwhile, we produce the adversarial training paradigm. The bias generators is expected to generate multi-modal bias samples that can deceive the discriminator and the backbone network, while the backbone network aims to produce correct predictions even in the presence of biased features and the discriminator aims to accurately predict whether the sample contains bias. This strategy forces the backbone model to accurately identify and effectively remove the influence of multimodal biases, thus improving the robustness of the model. We implement our DMBR on multiple existing backbones under widely used benchmarks Charades-CD and ActivityNet-CD datasets, which demonstrate the effectiveness of our debias strategy.
Leveraging Metaheuristics with Deep Learning for DDoS Attack Detection in SDN based IoT Networks
Authors: Alkanhel Reem , Rafiq Ahsan , Saleh Mohammed , Muthanna Ali , Singh Daljeet , Muthanna Ammar , Aziz Ahmed
Published: September 2024

Internet of Things (IoT) and Software-Defined Networking (SDN) are essential technology that enhances network administrations’ performance. Conveniently, SDN offers a simple and centralized system for administering a huge count of IoT devices and significantly decreases the capacity of network administrators. SDN mostly concentrates on upper-level control and network management, but IoT purposes are carrying devices collected to enable share and monitoring real-time performances with network connectivity. However, there is still a requirement for improving security performance in SDN depending on IoT networks to mitigate attacks containing IoT devices like Distributed Denial of Service (DDoS). With this stimulus, this study designs metaheuristics with deep learning-based DDoS attack detection model (MDL-DDoSAM) in the SDN-IoT environment. The presented MDL-DDoSAM technique mainly aims to identify the occurrence of DDoS attacks in the SDN-IoT environment. To accomplish this, the presented MDL-DDoSAM technique initially preprocesses the networking data. In addition, the presented MDL-DDoSAM technique designs the jellyfish search optimizer-based feature selection (JFSO-FS) technique to elect feature subsets. For DDoS attack detection and classification, the Bidirectional CUDA Deep Neural Network Long Short-Term Memory (BiCD-LSTM) model was used. Its hyperparameters are optimally adjusted by an improved whale optimization algorithm (IWOA). The significant DDoS attack detection performance of the MDL-DDoSAM system was tested utilizing a benchmark database, and the results indicate improved performance over other existing models.
U2BIL:A Two-phase Class Separation Method for Unbalanced Tunnel Defects via Class Incremental Learning
Authors: Yiwei Cai , Xinwen Gao , Yumeng Yang , Xinyang Feng
Published: September 2024

With more and more tunnel excavation projects, tunnel defects occur frequently. To reduce the cost of manual overhaul and maintenance, machine vision inspection methods are gradually emerging, but the traditional machine learning inspection methods cannot satisfy the continuous learning to update the knowledge of the prototype class without repeated access to the defect data. Incremental learning, as a continuous learning paradigm, can accomplish this task and alleviate the catastrophic forgetting phenomenon, but traditional incremental learning is difficult to fit the extremely unbalanced data distribution of the generalized realistic distribution. In this paper, based on the extremely unbalanced data distribution of tunnels, we propose a two-phase learning paradigm applicable to incremental learning to mitigate the overfitting of header data when the classes are unbalanced and incorporate the DR loss under the ETF classifier to ensure the maximum symmetric separation of the interclass prototypes under the classifier space. The proposed method in this paper obtains better performance under tunnel data compared to other incremental SOTAS.
A red fluorescent genetically encoded biosensor for in vivo imaging of extracellular L-lactate dynamics
Authors: Nasu Yusuke , Kamijo Yuki , Mächler Philipp , Ness Natalie , Vu Cong , Kusakizako Tsukasa , Ku Zaneta , Boisvert Marc , Grebenik Ekaterina , Miyazaki Ikumi , Hashizume Rina , Sato Haruaki , Liu Rui , Hori Yukiko , Tomita Taisuke , Katayama Tetsuro , Furube Akihiro , Caraveo Gabriela , Paquet Marie-Ève , Drobizhev Mikhail , Nureki Osamu , Arai Satoshi , Brancaccio Marco , Campbell Robert , Kleinfeld David
Published: September 2024

The transient build-up of L-lactate in tissue is associated with acidosis, as occurs during hypoxia, and traditionally viewed as deleterious1–3. However, recent studies contradict this view by demonstrating L-lactate's vital role as an intercellular and interorgan exchangeable fuel4. As one example, the astrocyte-to-neuron lactate shuttle (ANLS) hypothesis proposes that neurons import L-lactate from astrocytes via the extracellular space to produce adenosine triphosphate (ATP) and sustain heightened neuronal activity5,6. To address the validity of this and related hypotheses on the emerging roles of L-lactate in brain energetics6,7,8, we introduce R-eLACCO2.1, a red fluorescent extracellular L-lactate biosensor. R-eLACCO2.1 enables two-color imaging, is superior to a contemporary green fluorescent biosensor in terms of sensitivity as measured in in vivo images from mouse neocortex, and is an effective fluorescence lifetime-based biosensor. To highlight the potential insights gained from in vivo measurements with R-eLACCO2.1, we performed dual-color imaging from somatosensory cortex of actively locomoting mice. This enabled us to observe the interplay between neural activity, reported by intracellular GCaMP expression, and extracellular L-lactate. As the highest-performance tool in the suite of extracellular L-lactate biosensors, R-eLACCO2.1 is ideally suited to delimit the emerging roles of L-lactate in mammalian metabolism.
Risk factors of sarcopenia in patients with esophageal squamous cell carcinoma
Authors: Qie Peng , Nie Xiaodong , Cui Hongshang , Zhang Lixiao , Yin Qifan , Zhang Guibin , Wang Huien
Published: September 2024

Background: Esophageal squamous cell carcinoma（ESCC） is a common malignant tumor of the digestive tract, which seriously threatens human life and health. This study aimed to explore the correlation between sarcopenia in patients with ESCC and tumor clinical stage, characteristics, adverse reactions after chemotherapy and peripheral blood inflammatory indexes. Moreover, the correlation between appendicular skeletal mass index (ASMI) and the patient-generated subjective global assessment (PG-SGA) for the assessment of patient nutritional status were also be analyzed.
Methods: The clinical data of 225 patients with advanced ESCC in Hebei General Hospital from January 2019 to February 2022 were collected. Pearson analysis was carried out to analyze the correlation between ASMI and PG-SGA score.
Results: Among the 225 patients, the incidence of sarcopenia was 43.11% ( 97 of 225 patients) . The sarcopenia group was significantly older and the incidence of grade Ⅲ / Ⅳ adverse reactions after chemotherapy was higher; In addition, the sarcopenia group showed lower BMI, but higher PG - SGA score and NLR (neutrophil-to-lymphocyte ratio, NLR) (P<0.05). Univariate analysis and multivariate analysis showed that age, PG-SGA score, grade Ⅲ / Ⅳ adverse reaction after chemotherapy, and NLR were independent risk factors for sarcopenia (P< 0.05). There was a significant negative correlation between ASMI and PG - SGA score (r=-0.27,P<0.001) .
Conclusion: Advanced age, the occurrence of adverse reactions after chemotherapy and the systemic inflammatory state of patients are closely related to the occurrence of sarcopenia in advanced ESCC. ASMI and PG-SGA, have a significant correlation in the evaluation of nutritional status of patients.
A Broad Spectrum Lasso Peptide Antibiotic Targeting the Bacterial Ribosome
Authors: Wright Gerard , Jangra Manoj , Travin Dmitrii , Aleksandrova Elena , Kaur Manpreet , Darwish Lena , Koteva Kalinka , Klepacki Dorota , Wang Wenliang , Tiffany Maya , Sokaribo Akosiererem , Coombes Brian , Vázquez-Laslop Nora , Polikanov Yury , Mankin Alexander
Published: September 2024

Lasso peptides, biologically active molecules with a distinct structurally constrained knotted fold, are natural products belonging to the class of ribosomally-synthesized and posttranslationally modified peptides (RiPPs). Lasso peptides act upon several bacterial targets, but none have been reported to inhibit the ribosome, one of the main antibiotic targets in the bacterial cell. Here, we report the identification and characterization of the lasso peptide antibiotic, lariocidin (LAR), and its internally cyclized derivative, lariocidin B (LAR-B), produced by Paenabacillussp. M2, with broad-spectrum activity against many bacterial pathogens. We show that lariocidins inhibit bacterial growth by binding to the ribosome and interfering with protein synthesis. Structural, genetic, and biochemical data show that lariocidins bind at a unique site in the small ribosomal subunit, where they interact with the 16S rRNA and aminoacyl-tRNA, inhibiting translocation and inducing miscoding. LAR is unaffected by common resistance mechanisms, has a low propensity for generating spontaneous resistance, shows no human cell toxicity, and has potent in vivo activity in a mouse model of Acinetobacter baumannii infection. Our finding of the first ribosome-targeting lasso peptides uncovers new routes toward discovering alternative protein synthesis inhibitors and offers a new chemical scaffold for developing much-needed antibacterial drugs.
Effect of the membership in the World Trade Organization on Income Inequality
Authors: GNANGNON Sena Kimm
Published: September 2024

This paper has investigated empirically the effect of the membership in the GATT/WTO on trade policy and income inequality. The analysis has revealed that the GATT/WTO membership has been associated with trade policy liberalization and lower income inequality, although the magnitudes of these effects vary across groups of countries.
JEL Classification: F13; F14; O15.
Knowledge, Perceptions and Behaviors among Women with Late Stage Cervical Cancer Attended at Bugando Medical Centre in Tanzania: Explorative Qualitative Study.
Authors: Mvandal Samson Peter
Published: September 2024

Background: Worldwide cervical cancer ranks the fourth most common cancer in women. In Tanzania, cervical cancer is the leading female malignancy, and a major cause of cancer related mortality and morbidity in women. More than 80% of women with cervical cancer, are diagnosed with late stage, in which curative treatment options are not available. Objective: To explore the knowledge, perceptions and behaviors among women with late-stage cervical cancer who attended Bugando Medical Centre (BMC) from November to December 2021.
Methodology: Explorative qualitative study was conducted from November to December 2021 at BMC, involving 11 participants who had late-stage cervical cancer. Purposive sampling was used to recruit information-rich participants. Data collection was done by using open ended In-depth interview guide. The guide contained information on social demographic characteristics, knowledge on cervical disease, perceptions towards cervical cancer symptoms, health care seeking behaviors. Data was transcribed and analysed manually by using thematic approach.
Results: The coded texts generated three themes and nine subthemes. The results showed that Participants had poor knowledge about cervical cancer disease, causes, risk factors, prevention measures and treatment options which had impact on the perceptions and health care seeking behaviors. Participants misinterpreted the symptoms with other urogenital conditions like fungus and urinary tract infection. Misconception about the symptoms and disease, long distance to health facilities and financial challenges hindered involvement in seeking biomedical intervention and witch doctors were given a priority.
Conclusion: Findings from this study suggest a strong need of intensive health promotion efforts and education through mass media and outreaches to improve adequate and correct knowledge and awareness about cervical cancer disease, causes, symptoms, risk factors, prevention and treatment options. Health care providers and policy makers should include cervical cancer disease as a topic of everyday health education in the health facilities.
Assessment Of Self - Management For Patients With Type 2 Diabetes During The Syrian Crisis
Authors: Saba Fadi , Arbaji Emilio , Hammoud Taghrid
Published: September 2024

Diabetes mellitus (DM) is a long-term metabolic disease in which blood glucose levels are elevated due to the complete absence or incomplete absence of the insulin hormone. The requirements for people with diabetes are not controlling blood glucose levels only; there is also an urge to prevent complications and side effects of the disease. Studies show that good self-care for individuals with this disease has led to good outcomes. Diabetics who do self-care have shown positive results by reducing diabetes complications and its development, which leads to a significant reduction in the burden of diabetes. Despite these positive changes, people who adhere to these self-care practices are very few, especially when we see broad and chronic changes. There are many factors that play a major role in adherence to self-care practices, such as social factors, demographic factors, and various economic factors. While the role of doctors plays an important role in increasing self-care practices for diabetic patients to achieve the desired result. Materials and methods used in this study A sample of 200 diabetic patients was assembled with electronic questionnaire that included a number of questions controlled to achieve the study objective, in Damascus; Syria, within specific inclusion and exclusion criteria mentioned later. The data were processed using SPSS version 26, a general descriptive study of the sample's answers was conducted, followed by appropriate statistical tests to reach scientific results documented by previous medical literature. Results By presenting the results of the descriptive study on the degree of availability of an organized community response that provides the greatest amount of assistance to enhance self-care for diabetes, and help patients to live with their disease and avoid its complications as much as possible. In addition to surveying the degree of patients' awareness and knowledge of the steps of self-care and their ability to manage the disease. An analytical study was conducted on some axes related to developing self-care from attending educational workshops and others; where the effect of some demographic indicators was studied from the effect of the patient's gender on his attending training workshops. The results of the study we conducted, indicated that there is no significant difference between males and females and patient's social status in their commitment to attending educational workshops. In the study we conducted, the impact of community response and promoting the concept of self-care for diabetes among patients (as one axis) on their level of awareness and dealing with the complications of the disease and their ability to manage the symptoms of the disease was studied. A one-way Anova test was conducted and its results indicated the existence of a significant impact of promoting the concept of self-care on patients’ lives and helping them avoid complications of the disease.
The Kataev Memorial Readings – X. Dendrobiotic Invertebrates and Fungi and their Role in Forest Ecosystems. Vol. 1. Insects and Other Invertebrates
Authors: Мусолин Д.Л. , Селиховкин А.В.
Published: September 2024

Конференция проводится кафедрой защиты леса, древесиноведения и охотоведения при поддержке Санкт-Петербургского государственного лесотехнического университета имени С. М. Кирова.
The Kataev Memorial Readings – X. Dendrobiotic Invertebrates and Fungi and their Role in Forest Ecosystems. Vol. 2. Phytopathogenic Fungi, Problems of Forest Pathology and Forest Protection
Authors: Мусолин Д.Л. , Селиховкин А.В.
Published: September 2024

Конференция проводится кафедрой защиты леса, древесиноведения и охотоведения при поддержке Санкт-Петербургского государственного лесотехнического университета имени С. М. Кирова.
THE INFLUENCE OF ISLAMIC BANKS, ISSI AND SBSN FINANCING ON INDONESIA'S GROSS DOMESTIC PRODUCT
Authors: Putri Rafika Ananda , Nasution Muhammad Lathief Ilhamy , Atika Atika
Published: September 2024

Abstract: The purpose of this study is to find out how financing, ISSI and SBSN affect gross domestic product. The results of this study are expected to be useful for the government and industry players in Indonesia in knowing the picture of the state of the financial sector and formulating policy strategies in the future so as to create high and stable real sector growth to be able to encourage economic growth in Indonesia. The results of the study show that: 1) The influence of Islamic Banking Financing has no effect on GDP. 2) ISSI has no influence on GDP. 3) SBSN has no significant influence on GDP. 4) Sharia, ISSI, and SBSN banking financing simultaneously have an influence on GDP.
Keywords: Influence of Financing, ISSI, SBSN, PDB, Sharia Banking
 
Abstrak: Tujuan penelitian ini adalah untuk mengetahui bagaimana pembiayaan ISSI dan SBSN terhadap produk domestik bruto. Hasil penelitian ini diharapkan dapat berguna bagi pemerintah dan pelaku industri di Indonesia dalam mengetahui gambaran keadaan sektor keuangan serta merumuskan strategi kebijakan pada masa yang akan datang sehingga menciptakan pertumbuhan sektor riil yang tinggi dan stabil untuk dapat mendorong pertumbuhan ekonomi di Indonesia. Hasil  penelitian menunjukkan bahwa: 1) Pengaruh Pembiayaan Perbankan Syariah tidak memiliki pengaruh terhadap PDB. 2) ISSI tidak memiliki pengaruh  terhadap PDB. 3) SBSN tidak memiliki pengaruh signifikan terhadap PDB. 4) Pembiayaan perbankan Syariah, ISSI, dan SBSN secara simultan memiliki pengaruh Terhadap PDB.
Kata Kunci: Pengaruh Pembiayaan, ISSI, SBSN, PDB, Perbankan Syariah