bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Alternative Therapies and Physical Exercise on Neuroplasticity and Skill Acquisition in healthy volunteers: A Metaplasticity Study
Authors: Lin Jiahui , Li Jiemei , Huang Jianpeng , Li Sheng , Sun Jian , Liu Jianhua
Published: January 2024

Background To explore the effects of combining electroacupuncture (EA) with motor training (MT) on corticospinal excitability and motor learning, focusing on the concepts of homeostatic and non-homeostatic metaplasticity.
Methods The study enrolled twenty healthy volunteers who underwent four distinct interventions: EA alone, MT alone, EA-priming prior to MT, and MT-priming prior to EA. Motor evoked potentials (MEPs) and the Grooved Pegboard Test (GPT) were employed to assess changes in M1 excitability and motor performance, respectively.
Results Both EA and MT enhanced M1 excitability and motor performance. However, additional EA or MT priming did not further modulate MEPs amplitudes. EA-priming improved GPT completion times, suggesting a role in enhancing motor learning
Conclusion The study concludes that while EA and MT individually augment motor cortex excitability and performance, their combined application does not further modulate corticospinal excitability, indicating the involvement of non-homeostatic metaplasticity mechanisms. Nevertheless, EA may play a critical role in preventing M1 overstimulation, continually promoting motor learning. This underscores the need for further research into the application of EA, either independently or in conjunction with MT, in clinical settings.
Trial Registration Number This trail was registered in Chinese Clinical Trial Register (NO. ChiCTR2000039910) on November 11, 2020.
East Meets West: Evidence for Validity for the China Medical Professionalism Inventory
Authors: Li Honghe , Hirsh David , Jin Jing , Krupat Edward , Jiang Nan , Ding Ning , Ho Ming-Jung , Manning Dianne , Wen Deliang
Published: January 2024

The characteristics of medical professionalism (MP) vary across cultural contexts. Theories of professionalism and MP tools currently rely on Western cultural perspectives. The authors developed the China Medical Professionalism Inventory (CMPI) using standard processes through four steps: Phase I) systematic review and synthesis of the literature to develop an item pool; Phase II) survey of Chinese clinical and educational experts to develop evidence based on test content; Phase III) two rounds of pilot studies of practicing physicians to measure internal structure and internal consistency; and Phase IV) refinement of the instrument using an expert survey and pilot study. Systematic review of the English- and Chinese-language literature identified 1537 professionalism-specific items from 63 sources as foundation of the item pool. The authors conducted two rounds of expert review, including surveying nationally prominent Chinese healthcare leaders (n = 34, response rate 85%, and n = 76, response rate 63%). The authors conducted three pilot studies of practicing Chinese physicians (n = 360, response rate 92%; n = 3653, response rate 89%; and n = 955, response rate 95%). The results generated a 40-item CMPI and a shortened 20-item CMPI, with four domains “Respect, Compassion, and Communication; Integrity; Excellence; and Responsibility.” Applying the standards of Messick, the American Psychological Association, and Kane, the authors present the CMPI's validity evidence related to content, response process, internal structure, relationship to other variables, and consequences. This study aims to extend the conceptualization and reach of MP measurement.
ARIR: An Intent Recognition-Based Approach for API Recommendation
Authors: Cao Buqing , Wang Siyuan , Xie Xiang , Peng Qian , Yi Yating , Peng Zhenlian
Published: January 2024

With the prevalence of service composition, how to recommend API services that meet the Mashup requirements for developers has become a challenging in the field of service computing. Existing works on Web service recommendation typically conduct service recommendation based on the semantic requirements and interaction relationships of Web services, while ignoring the construction intent of Mashup creators. Moreover, they often only focus on the impact of single intent on recommendation, neglecting the diverse requirements of Mashup creators at different intent-levels. As a result, the recommendation models fail to comprehensively understand the construction intent of Mashup creators, which affects the quality and effectiveness of Web service recommendation. To address this problem, this paper proposes an intent recognition-based API recommendation method, denoted as ARIR. This method utilizes the annotation information of Mashup and API to analyse the creation intent of Mashup and the functional intent of API, thereby providing more accurate API with high-quality to Mashup creators. Firstly, it decouples the representations of Mashup and API at different intent-levels and independently initializes the node representations at each intent-level. Secondly, it trains the vector representations at each intent-level using a decoupled graph convolutional neural network module and obtains the representation vectors of Mashup/API at different intent-levels with attention weights. Then, it aggregates the intents of Mashup and API using the Mashup-API interaction relationships, resulting in the final node representations of Mashup/API. Furthermore, it constructs a similarity heterogeneous network by calculating the Mashup-to-Mashup similarity and API-to-API similarity, updating the node representations by using the Mashup and API feature matrices and adjacency matrices, and obtaining the final recommendation prediction results by using a fully connected layer. Finally, the experimental results conducted on real-world Web service datasets demonstrate that the ARIR outperforms the best-performing baseline method with Recall@20 of 3% and NDCG@20 of 5%.
HHMFO-DVFS for An Optimal Makespan-Energy-aware Workflow Scheduling in Cloud
Authors: Salehnia Taybeh , Seyfollahi Ali , Azizi Sadoon , Karami Shahreyar , Abualigah Laith
Published: January 2024

The authors have requested that this preprint be removed from Research Square.
SGCNet: Multi-task Self-Gated Convolution based UNet with Multi Scale Convolution and Global Attention Module
Authors: Zhang Xiaohu , Huang Haifeng
Published: January 2024

Concrete cracks pose significant safety hazards to concrete buildings, and semantic segmentation models based on deep learning has achieved the state-of-arts results in concrete crack detection. However, there are some limitations in these models. Firstly, stains in crack images would inter-fere the extraction of crack features. Secondly, current crack detection models usually use convo-lutional kernels of uniform size, which could not adapt cracks with varying scales. Thirdly, due to the diversity and irregularity of cracks' edges, existing semantic segmentation models could not effectively segment these edges. Finally, current mainstream model only use serial stacked convo-lution operation, which is limited to extract global features. To solve these problems above, a Self-Gated Convolution (SGC) based U-Net model with Multi Scale Convolution Module (MSCM) and Global Attention Module (GAM) named as SGCNet is proposed by us. In this model, SGC is used to remove interference features and MSCM is used for extract features of different scales with dilated convolutions. Additionally, edge detection of cracks is used as the second task to en-hance the edge feature extraction ability of the model. Finally, GAM is used to extract global con-textual information. Experimental results show that the SGCNet proposed by us could achieve the accuracy of 0.942, 0.836 and 0.991 on the Cracktree200, CRACK500 and CFD datasets respectively, which is higher than that of the traditional models.
Electrochemical self-signal identification of circulating tumor DNA based on poly-xanthurenic acid assembled on black phosphorus nanosheets
Authors: Yan Xinyu , Zhang Wei , Yang Jimin
Published: January 2024

A self-signal electrochemical identification interface was prepared for the determination of circulating tumor DNA (ctDNA) in peripheral blood based on poly-xanthurenic acid (PXTA) assembled on black phosphorus nanosheets (BPNSs) acquired through simple ultrasonication method. The electropolymerization efficiency was promoted due to the physical adsorption between the xanthurenic acid (XTA) monomers and BPNSs, which was beneficial to the enlargement of the signal response of PXTA. The assembled PXTA/BPNSs nanocomposite with attractive electrochemical activity was adopted as a platform for the recognition of DNA immobilization and hybridization. The probe ssDNA was covalently fixed onto the PXTA/BPNSs nanocomposite with plentiful carboxyl groups through the terminate free amines of DNA probes by use of the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydrosulfosuccinimide cross-linking reaction, accompanied with the decline of the self-signal response. When the hybridization between the probe ssDNA and the target DNA was accomplished, the self-signal response of the nanocomposite interface reproduced by virtue of the shaping of helix construction. The determination limit of the assembled DNA identification interface was 2.1×10− 19 mol/L, and the complementary target DNA concentrations varied from 1.0×10− 18 mol/L to 1.0×10− 12 mol/L. The DNA identification platform displayed magnificent sensitivity, specificity and stability, and was efficaciously implemented to the mensuration of ctDNA derived from colorectal cancer.
Climate Change Trend Analysis and Future Projection in Guguf Watershed, Northern Ethiopia
Authors: Mohammed Mekin , Bezabeh Seyoum
Published: January 2024

According to Intergovernmental panel on Climate Change (IPCC) Climate change is the weather characteristic condition such as precipitation, air temperature, humidity, wind, sunshine, cloud cover and atmospheric pressure at a specific location determined over a long period of at least 30 years. The main objective of this study was to analyse the climate trend and future projection in Guguf watershed of Southern Tigray, Ethiopia. 32 years (1987–2018) Meteorological data were collected from Ethiopia National Meteorological Agency (NMA). Download canESM2 (Canadian Second Generation Earth System Model) which was freely available at the Canadian climate change scenario group website. The Mann-Kendal trend test was used to test for the presence of trends using XLSTAT. SDSM 4.2.9 decision support tool was used to downscale large scale predictors and project future climate change. The period from 1987–2018 were considered as a base period whereas the period from 2019–2100 were considered as future periods. Historically, slight decrease in rainfall, and an overall increase in the mean annual minimum and maximum temperatures in the study area for the last 32 years. The highest increment of maximum temperature recorded in October month up to + 2.7°C in RCP8.5 scenarios. The precipitation increases up to a maximum of 49% (2073–2100) for RCP4.5 scenario and 66% (2073–2100) for RCP4.5 scenario in the Belg. Precipitation decreases in Kiremt (Jun–September) season by 8% (2019–2045) and 23% (2073–2100) for RCP4.5 scenarios. Future work needs to consider studying the effects of different climate change adaptation strategie.
Exploring BIM-based queries for retrieving cultural heritage semantic data
Authors: Suhari Ketut Tomy , Saptari Asep Yusup , Abidin Hasanuddin Z. , Gunawan Putu Harry , Meilano Irwan , Hernandi Andri , Widyastuti Ratri
Published: January 2024

Building Information Modeling (BIM) technology has been widely adopted in the construction industry for managing building information. However, its application in cultural heritage conservation has yet to be fully explored. This study aims to demonstrate the potential of using BIM technology in managing cultural heritage tourism assets through a case study of the traditional village of Penglipuran in Bali, Indonesia. Four queries were developed using Industry Foundation Classes (IFC) data model to retrieve information on cultural, legal spaces, physical boundaries, and traditional house elements. The results show that BIM technology can effectively assist in managing cultural heritage tourism assets by providing detailed IFC information. Moreover, results also highlight the potential of BIM technology in preserving and promoting cultural heritage tourism assets. This research provides a comprehensive understanding of BIM technology's potential in cultural heritage conservation and its application in tourism.
Automated offset detection approaches: Case study in IGS Repro2 and 3
Authors: Zhang Jin , Lian LiZhen , Huang ChengLi , Xu CanCan , Zhang SiMeng
Published: January 2024

Due to their high false positive detection rates, traditional automated offset detections on GNSS station coordinate time series still cannot fully replace manual detections in practical applications and need to be improved. This work proposes preliminary and enhanced automated offset detection approaches for IGS Repro2 and Repro3 datasets. Their manually detected offset recordings in ITRF2014 and ITRF2020 are used as evaluation criteria. In the preliminary approaches, stochastic models based on covariance matrix, white noise model, and white noise plus flicker noise model of both univariate and multivariate are studied. Although a somewhat “good” performance is achieved, the preliminary automated detections still lead to many false positive detections. Thus, based on the preliminary approaches, and ancillary data, an enhanced detection approach is proposed. Enhanced detections significantly reduce 56%~80% false positive detections compared to preliminary approaches. As a result, for Repro3, the optimal overall performance is attained with true positive, false positive, and false negative rates (TP, FP, FN) of (0.57, 0.25, 0.18), along with a detection rate of 75%; for Repro2, the rates are (0.58, 0.20, 0.22), accompanied by a 73% detection rate. According to its “good” performance mentioned above, the current enhanced approach may serve as a supplementary or reference to manual detection, although still not being perfect. Furthermore, twenty manually detected unknown offsets in ITRF2020 are found to correspond to some known events (thirteen earthquakes and seven equipment changes); thirty-four automated detections that correspond to known events but are not collected in ITRF2020 are manually checked as offsets (fourteen earthquakes and twenty equipment changes).
Cytokine Expression Profiles in Children and Adolescents with Tic Disorders.
Authors: Kutuk Ozgur , Kutuk Meryem Ozlem , Tufan Ali Evren , Kilicaslan Fethiye , Gokcen Cem , Aksu Gulen Guler , Yektas Cigdem , Kandemir Hasan , Celik Fatma , Mutluer Tuba , Buber Ahmet , Karadag Mehmet , Coban Nurdan , Coskun Seyma , Hangul Zehra , Altintas Ebru , Acikbas Ufuk , Giray Asli , Aka Yeliz , Basturk Bilkay
Published: January 2024

The etiology of tic disorders (TDs) is not precisely known, although several lines of evidence suggest involvement of the immune system in pathogenesis. Here, we aimed to determine the expression levels of pro-inflammatory and anti-inflammatory cytokines in children with TD and compare them with those of healthy controls. Furthermore, we also evaluated their association with clinical variables in the TD group. Within the study period, 88 children with tic disorders and 111 healthy control children were enrolled. Most children with tic disorders were diagnosed with Tourette’s disorder (n = 47, 53.4%) or persistent motor tic disorder (n = 39, 44.3%), while the remainder (n = 2, 2.3%) were diagnosed with persistent vocal tic disorder. We found that children with tic disorders had significantly elevated levels of IL-1β, TNF-α, IL-6 and IL-4 expression, while healthy control cases presented with increased levels of IL-17. Our findings provide a molecular landscape of cytokine expression in children with TD, which may suggest a proinflammatory state not affected by the presence of comorbidity and symptom severity. Delineating the contribution of alterations in the immune system to the pathogenesis of tic disorders will have critical implications for diagnosis and therapeutic interventions.
A fixed-stress type splitting method for nonlinear poroelasticity
Authors: Kraus Johannes , Kumar Kundan , Lymberly Maria , Radu Florin Adrian
Published: January 2024

In this paper we consider a nonlinear poroelasticity model that describes the quasi-static mechanical behaviour of a fluid-saturated porous medium whose permeability depends on the divergence of the displacement. Such nonlinear models are typically used to study biological structures like tissues, organs, cartilage and bones, which are known for a nonlinear dependence of their permeability/hydraulic conductivity on solid dilation.
We formulate (extend to the present situation) one of the most popular split- ting scheme, namely the fixed-stress split method for the iterative solution of the coupled problem. The method is proven to converge linearly for sufficiently small time steps under standard assumptions. The error contraction factor then is strictly less than one, independent of the Lam ́e parameters, Biot and stor- age coefficients if the hydraulic conductivity is a strictly positive, bounded and Lipschitz-continuous function.
Obtaining cashew bark extract and its application for removal of metallic species in aqueous matrix
Authors: Borges Thaíse da Silva , Queiroz Luciano Matos , Ferreira Sérgio Luís Costa , José Nádia Mamede
Published: January 2024

This work presents the preparation and characterization of the powder from the bark of the cashew tree Anacardium occidentale L. and the aqueous extract obtained from the bark of the cashew tree and studies the use of this extract for removing metals in acid solution. The experiments were carried out on a laboratory scale using contaminated water with a concentration of 4.0 mol/L of the metals Ba, Cd, Cr, Cu, Mn, Pb, Sn, Zn and different volumes of the extract obtained from the bark of the cashew tree. The coagulation process between the extract and the metal species led to a decrease in the metal concentration in solution due to precipitation. Removal of up to 25% was obtained for all analyzed metals. Using the principles of green chemistry, the process was evaluated with a very good green approach.
A Low-Cost, Open-Source-based Optical Surgical Navigation System Using Stereoscopic Vision
Authors: Tsui Darin , Ramos Kirsten , Melentyev Capalina , Rajan Ananya , Tam Matthew , Jo Mitsuhiro , Ahadian Farshad , Talke Frank E.
Published: January 2024

Computer-assisted surgical navigation systems have gained popularity in surgical procedures that demand high amounts of precision. These systems aim to track the real-time positioning of surgical instruments in relation to anatomical structures. Typically, state-of-the-art methods involve tracking reflective 3D marker spheres affixed to both surgical instruments and patient anatomies with infrared cameras. However, these setups are expensive and financially impractical for small healthcare facilities. This study suggests that a fully optical navigation approach utilizing low-cost, off-the-shelf parts may become a viable alternative. We develop a stereoscopic camera setup, costing around $120, to track and monitor the translational movement of open-source based fiducial markers on a positioning platform. We evaluate the camera setup based on its reliability and accuracy. Using the optimal set of parameters, we were able to produce a root mean square error of 2 mm. These results demonstrate the feasibility of real-time, cost-effective surgical navigation using off-the-shelf optical cameras.
A Levitated Control Attention for Named Entity Recognition
Authors: Huang Rong , Chen YanPing , Huang Ruizhang
Published: January 2024

Controlled attention is a mechanism developed in cognitive neuroscience. It has been successfully applied to support named entity recognition, where the start and end boundaries of a possible named entity are marked by two specific tokens to indicate its position in a sentence. Then, it is fed into a deep network for classification. The entity boundary markers enable a deep neural network to be aware of entity boundaries and to build the contextual dependency of a sentence relevant to a possible named entity. The problem is that every possible named entity should be evaluated independently. This leads to very high computational complexity and cannot construct the semantic dependency between different named entities. In this paper, a levitated control attention mechanism is presented for named entity recognition. The levitated control attention is composed of a separable matrix, which enables the weighting of discriminative contextual features relevant to each specific entity. All possible named entities are together fed into a deep network for one-pass classification, which can establish the semantic dependency between contextual features and possible named entities. The levitated control attention is evaluated on four public datasets. Experiments show that it not only considerably reduces the computational complexity but also improves performance.
Aerobic exercise-induced up-regulation of HIF-1α ameliorates heart failure by regulating MCT1 and MPC1 expression
Authors: Xu Longfei , Yang Miaomiao , Wei Aili , Wei Zilin , Qin Yingkai , Wang Kun , Li Bin , Chen Kang , Liu Chen , Li Chao , Wang Tianhui
Published: January 2024

Background
The terminal stage of ischemic heart disease develops into heart failure (HF), which is characterized by hypoxia and metabolic disturbances in cardiomyocytes. Based on high sensitivity to hypoxia, the failing heart activates cellular metabolic adaptation to balance energy demand by accumulating hypoxia-inducible factor-1α (HIF-1α). Furthermore, monocarboxylic acid transporter protein 1 (MCT1) and mitochondrial pyruvate carrier 1 (MPC1), as key nodes of metabolic adaptation, affect metabolic homeostasis in the failing rat heart. Aerobic exercise training has been demonstrated to be beneficial in slowing the progression of HF by elevating HIF-1α and MCT1 levels, whereas the modulatory effects of exercise on MCT1 and MPC1 in HF (hypoxia) remain elusive. This research aimed to investigate the effects of exercise associated with MCT1 and MPC1 on HF under hypoxia.
Methods
Rats were randomly divided into four groups: sham sedentary (SHAM), HF sedentary (HF), HF short-term exercise trained (HF-E1) and HF long-term exercise trained (HF-E2). The left anterior descending branch of the coronary artery was ligated to induce HF in rats, and the delaying effect of exercise on HF in rats was evaluated by ventricular ultrasound (ejection fraction, short-axis shortening rate), HE, and Masson staining, etc. The effects of HIF-1α on metabolism, MCT1 and MPC1 proteins expression in hypoxic H9c2 cells were examined using HIF-1α agonist/inhibitor and lentiviral transfection.
Results
Our results indicate the presence of severe pathological remodelling (as evidenced by deep myocardial fibrosis, increased infarct size and abnormal hypertrophy of the myocardium, etc.) and reduced cardiac function in the failing hearts of rats in the HF group compared to the SHAM group. Treadmill exercise training ameliorated myocardial infarction (MI)-induced cardiac pathological remodelling and improved cardiac function in HF exercise group rats, and significantly increased the expression of HIF-1α (p < 0.01), MCT1 (p < 0.05) and MPC1 (p < 0.05) proteins compared to HF group rats. In addition, pharmacological overexpression of HIF-1α significantly up-regulated the expression of MCT1 (p < 0.001) and MPC1 (p < 0.001) proteins in hypoxic H9c2 cells.
Conclusion
The data gathered in this study suggest that long-term aerobic exercise training as a non-pharmacological treatment may be effective in slowing down the disease process, improving the pathological phenotype and enhancing cardiac function by activating myocardial HIF-1α and up-regulating the expression of key proteins (MCT1 and MPC1) in HF rats.
Design and Development of robust OCR system for hand filled form in Office Automation
Authors: Agrawal Akanksha , Roy Pranab Singha , Rakesh Vineet Kumar , Samanta Tapas , Pal Sarbajit
Published: January 2024

Hand-filled forms are a ubiquitous means of information collection, yet their manual processing remains labor-intensive and error-prone. In this paper we proposed a novel approach to completely automate the processing of template based hand filled form and store the recognized data in central database. The proposed framework combines image processing techniques for form segmentation and a convolution neural network model, for accurate character recognition. By seamlessly integrating these components, the proposed approach streamlines the transition from handwritten content to digital data, reducing manual effort and potential errors.
Individual tree diameter growth models for natural secondary forest in Changbai Mountains
Authors: Zhang Hao , Lu Jun
Published: January 2024

In this paper we develop a serial distance-depended individual tree model for some species in natural forest which would provide prediction and characteristics for natural species. The data used to develop individual model for natural mixed forests were collected from 712 remeasured 10-year periodic permanent sample plots of in Baihe Forest Bureau of Changbai mountains, northeast China. Based on analysing relationship between diameter increment of individual trees with tree size, competitive status, and site condition and finding out the major independent variables, the growth models for individual trees of 15 species in the natural mixed forests were developed using stepwise regression method. The individual growth model developed in this study can reflect the tree increment of 15 species and be generally well suited for simulating tree and stand growth for natural mixed forests in Changbai Mountains. The research results showed that the natural logarithm of DBH (lnD) and square diameter (D2) were included in the predicting models of diameter increment for all 15 species. The diameter increment was directly proportional to tree diameter for each species. For the competitive indexes in growth model, the relative diameter (RD), canopy closure (P), and the ratio of diameter of subject tree with maximum diameter (DDM) were related to diameter increment and the stand density measures were not significantly influenced on diameter increment. As canopy closure (P) increase, tree increment decreases. The site conditions were performance less of factors in increment predictions in the model.
Investigation of the Effect of Calcitriol on Radiofrequency Radiation Exposed Breast Cancer Cell Lines
Authors: ELÇİ Mualla Pınar , FATSA Tuğba , ÖREN Sema , MİSER-SALİHOĞLU Ece , EŞMEKAYA Meriç Arda , AKAYDIN Sevgi
Published: January 2024

Radiofrequency (RF) fields have been classified as probable human carcinogens and non-thermal RF-radiation (RFR) can cause an increase in oxidative stress and inflammation in tissues. Vitamin D has been researched for many years for its anti-cancer and suppressive effects on cancer cell growth. In this study, we aimed to examine the effects of exposure to RF signals on cell viability, free radical formation, and related inflammation, and the restorative effect of vitamin D against this. For this purpose, MCF-7 and MDA-MB-231 cells were exposed to 2.1GHz W-CDMA-modulated RFR. The viability of cells was determined by MTT assay, and the percentage of apoptotic cells was determined by FITC-conjugated Annexin-V/PI assay. The expression levels of VDR, NF- κB, COX-2, and p53 genes were studied using Real-Time-PCR. ROS analysis was performed by flow cytometry. A statistically significant decrease in MCF-7 cell viability (p < 0.001) was observed with increasing doses of calcitriol compared to the control group, while no significant difference was observed in MDA-MB-231 cells (p > 0.05). As a result of ROS analysis, significant decreases in life values were observed for both cells due to calcitriol. A statistically significant increase in p53 expression was observed with increasing calcitriol dose in both cell lines. An increase in VDR, NF-kappa B, and COX2 expressions was also observed in MCF-7 cells. We observed that calcitriol administered after RF exposure caused an increase in apoptosis and mRNA expression of inflammation markers, a decrease in ROS levels, and an increase, and this can be evaluated in cancer treatment or prevention.
Fast Implementation of Extreme Learning Machine-based DirectRanker for Surrogate-assisted Evolutionary Algorithms
Authors: Harada Tomohiro
Published: January 2024

Surrogate-assisted evolutionary algorithms (SAEAs) have been widely used to solve computationally expensive optimization problems. The extreme learning machine-based DirectRanker (ELDR) is a single-layer feed-forward neural network surrogate model designed for SAEAs. ELDR estimates the superiority of two solutions with a high estimation accuracy, even in high-dimensional problems. However, ELDR requires a long computation time as the problem dimensionality and the number of hidden neurons increase, thus making it difficult to apply it to high-dimensional problems. A surrogate model should be computationally efficient and enable rapid fitness estimations. Therefore, this paper proposes a fast implementation technique, i.e., fast version ELDR (fELDR) that achieves mathematically equivalent learning results with low computational complexity. Additionally, this paper proposes a pointwise score function to render the prediction results reusable. The experimental results confirmed the effectiveness of fELDR when compared with the original ELDR. The learning results of the proposed fELDR were equivalent to those of the original ELDR while reducing the training time by up to 97\%, especially when using a large hidden layer on a high dimensionality problem. Moreover, due to the reusable prediction results, the computation time of the fELDR-assisted SAEA can be further decreased by 79.5\% when compared with that of the original ELDR-assisted SAEA. The reduced training time and reusable prediction results of fELDR render it feasible to apply ELDR to high-dimensional optimization problems and realize a high prediction accuracy with a large number of hidden neurons.
Multipath Effects Mitigation in Offshore Construction Platform GNSS-RTK Displacement Monitoring Using Parallel Temporal Convolution Network
Authors: Jiang Yiyang , Guo Cheng , Wang Jinfeng , Xu Rongqiao
Published: January 2024

Global Navigation Satellite System (GNSS), renowned for its high precision and automation, has shone brightly in deformation monitoring of offshore facilities and sea-cross bridges. However, GNSS antennas placed in these locations are often subject to signal interference from various reflective surfaces such as water, which significantly compromises observation accuracy and reliability. Synthesizing previous research, firstly we propose a method for constructing a multipath dataset. This involves detailed mapping of the boundaries of reflective areas in the airspace map, using three types of linear combinations of satellite observations within this area as the multipath dataset, and employing static solution residuals as multipath reference values. Subsequently, we have constructed and trained a corresponding parallel temporal convolution network to enable real-time prediction of multipath, thereby mitigating the impact of multipath on this observation. Through time-frequency domain analysis and correlation analysis, it has been demonstrated that the trained network can capture the main characteristics of multipath and suppress those components within the frequency band corresponding to the multipath, effectively mitigating the interference of multipath errors in observations.
Effect of Urea-High-Temperature Combined Treatment on the Dimensional Stability of Densified Fast-Growing Wood
Authors: Wang Zhichuang , Wei Rongjun , Wang Xuechun , Gao Jingjing , Wang Tinghuan , Yang Chen , Guo Jin , Wang Zhenyu , He Zhengbin , Yi Songlin
Published: January 2024

Due to the continuous depletion of timber resources and the increasing ecological awareness among people, large-scale fast-growing artificial forests have become a key solution to address the imbalance between timber supply and demand. In recent years, the problem of low density and mechanical strength of fast-growing timber has been addressed through timber densification. However, densified timber still faces issues such as high moisture absorption and poor dimensional stability. Urea molecules can expand the volume of the non-crystalline region of cellulose to protect the cell wall structure of timber from damage during the densification process. In this paper, an effective modification strategy was proposed to prepare lightweight high-strength wood through the synergistic effect of urea vacuum impregnation treatment and high temperature densification, which solved the problem of poor dimensional stability of densified wood. Research results indicate that when the concentration of urea solution is at 50%, the maximum weight gain of the timber samples reaches 17.76%. After densification treatment, the absolute dry density of the test samples increased by more than 0.031g/cm3. Timber treated with a 50% urea solution and processed at 170°C demonstrates good dimensional stability, with a radial swelling rate of only 0.79% under a relative humidity of 65%. Therefore, the joint modification of wood using urea and high-temperature treatment is an effective and environmentally friendly method, presenting broad prospects for development.
Thermodynamic formalism and anomalous transport in 1D semiclassical Bose-Hubbard chain
Authors: Marković Dragan , Čubrović Mihailo
Published: January 2024

We analyze the time-dependent free energy functionals of the semiclassical one-dimensional Bose-Hubbard chain. We first review the weakly chaotic dynamics and the consequent early-time anomalous diffusion in the system. The anomalous diffusion is robust, appears with strictly quantized coefficients, and persists even for very long chains (more than hundred sites), crossing over to normal diffusion at late times. We identify fast (angle) and slow (action) variables and thus consider annealed and quenched partition functions, corresponding to fixing the actions and integrating over the actions, respectively. We observe the leading quantum effects in the annealed free energy, whereas the quenched energy is undefined in the thermodynamic limit, signaling the absence of thermodynamic equilibrium in the quenched regime. But already the leading correction away from the quenched regime reproduces the annealed partition function exactly. This encapsulates the fact that in both slow- and fast-chaos regime both the anomalous and the normal diffusion can be seen (though at different times).
Professionalism-training in undergraduate medical education in a multi-cultural, multi-ethnic setting in the Gulf Region: an exploration of reflective essays
Authors: Buhumaid Rasha , Otaki Farah , Czabanowska Katarzyna , Stanley Adrian , Ezimokhai Mutairu , Jackson Lisa , Ho Samuel B.
Published: January 2024

BackgroundDespite the established need to prioritize professionalism-training in developing future physicians, very few medical programs in the Gulf Region embed in their curricula discrete contextualized courses aimed at developing the corresponding competencies, while fostering self-directed learning. This study aims at exploring the perception of undergraduate medical students in a multi-cultural and multi-ethnic setting regarding their understanding of, and personal experience with professionalism through their engagement with the content of an innovative curriculum-based professionalism course, offered at a Medical School in Dubai, United Arab Emirates.MethodsThe study used a qualitative phenomenological research design. Out of 33 students, 29 students had submitted reflective essays. The content of these essays was inductively analyzed following a six-step framework for conducting thematic analysis. The framework’s steps include familiarizing oneself with the data, generating initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the report.FindingsThe inductive qualitative analysis generated theProfessionalism Learning Journeymodel. This conceptual model includes four interconnected themes:Awareness, Acknowledgement, Realization, and Application.The generated model depicts the trajectory that the learners appear to experience while they are engaging with the content of the course.ConclusionIntegrating a professionalism-training course into undergraduate medical curriculum is likely to be positively appraised by the learners. It raises their awareness, enables them to value the subject matter and the sophistication of its application, and empowers them to put into practice the taught principles, on an individual basis and collectively. This is especially true when the course is entrenched in constructivism experiential learning theory and designed to foster self-directed learning. The introduced conceptual model, in conjunction with the innovative professionalism-training course curriculum, can serve as a template for other competencies and other schools.
Electro-magneto-mechanical co-simulation in strongly coupled dynamic applications
Authors: Reato Federico Maria , Ricci Claudio , Cinquemani Simone , Misfatto Jan , Calzaferri Matteo
Published: January 2024

Multibody-based design methodologies are techniques that have seen an increasing use, both in industry and science, in the last few decades. This boost was made possible by the more and more performing computers and the increasingly reliable simulation software. Normally the analysis of large and complex mechanical systems tends to be decoupled to isolate the main macro phenomena and thus allow the models to be simulated by different techniques, tools, and algorithms. All these aspects highlight the difficulties of analysis of coupled heterogeneous systems. The strict interdependence between the different physical domains or different scales of analysis has clearly increased the difficulties in multibody prediction capabilities. An interesting new approach is represented by the multi-physics co-simulations technique where the global model of a coupled system is solved through the inter-exchange of effort and flows variables coming from events of different natures. The paper intends to propose a novel co-simulation architecture for the integration of the magnetic and analog electronic domains into the mechanic one through the implementation among the others of a Matlab-Python based bi-directional communication routine for the interexchange of effort and flow independent variables between the master model (multibody-based) and the equivalent circuit model developed through Spice® as well as the possibility to integrate the dynamic analysis of the 3D electro-magnetic field through the open package ESRF Radia®. To highlight the potentiality of the multi-domain architecture and to validate the results obtained from the co-simulation a comparison with the experimental results of a micro electro-magnetic actuated drive [1] are proposed.
The Impact of Corporate Social Responsibility on the Financial Performance of European Banks: A Simultaneous Equations Model
Authors: SLAMA Mehrez BEN , HAMOUDA Sinda BEN
Published: January 2024

This study examines the effect of Corporate Social Responsibility (CSR) on the financial performance of 27 European banks during the period of 2011 to 2018. Using panel data and the simultaneous equation model, our research has shown that the implementation of corporate social responsibility practices has a negative impact on the financial performance of banks. This finding is significant as it highlights the potential trade-offs that banks may face when implementing CSR initiatives. However, it is important to note that this does not mean that banks should abandon these practices altogether. CSR practices can have important benefits for society and the environment, and it is crucial for banks to find a balance between financial goals and social and environmental responsibilities.
Ransomware Detection with Opcode Analysis and GAN-Based Unsupervised Learning
Authors: Zhong Qinian , Kang Qian
Published: January 2024

This study introduces an innovative approach to ransomware detection utilizing opcode analysis combined with Generative Adversarial Networks (GANs). Focusing on the dynamic nature of modern ransomware threats, the research develops a method that leverages unsupervised learning to detect both known and novel ransomware variants. The study begins by examining the evolution of ransomware, from its initial focus on Windows-based systems to the current sophisticated attacks on various platforms. It then explores the implementation of a GAN-based model, capable of discerning ransomware through complex opcode patterns. Experimental results demonstrate the model's effectiveness across several ransomware families, with high accuracy, precision, recall, and F1-scores. The research further delves into the implications of advanced ransomware detection techniques, challenges in adapting to evolving ransomware strategies, the integration of AI in cybersecurity, and future directions in ransomware mitigation. This paper contributes significantly to the field of cybersecurity by providing an advanced, adaptable, and efficient tool for ransomware detection, marking a step forward in combating the increasing ransomware threat.
Performance Degradation Caused by Ionization of the Released Gas Molecules in W-band Gyrotron Traveling Wave Tube Based on A Simplified Ionization Model
Authors: Wang Yu , Liu Guo , Jiang Wei , Yao Yelei , Wang Jianxun , Luo Yong
Published: January 2024

Analysis of the performance degradation for W-band lossy ceramic-loaded gyrotron traveling wave tubes (gyro-TWTs) caused by ionization of the released gas molecules is presented in this paper. The gas is released from the lossy ceramics during high average or continuous wave operation and ionized by colliding with the high-energy gyrating electrons. A potential well will be formed by the diffusion and accumulation of the ionization particles after the collision and then degrade the gyro-TWT performance. This process has been simulated based on a simplified model by introducing an equivalent ionization source combining ions and electrons. With a vacuum of 2.1*10-6 Pa, the theoretically calculated initial energy and equivalent ionization current are 0.01 eV and 0.5 A, respectively. It leads to a deterioration in the output power stability of the gyro-TWT. The performance degradation including spectrum, and field pattern caused by gas ionization is also given and analyzed. One of the primary causes is the quality (pitch factor and velocity spread) degradation of the electron beam. According to the simulation and hot test experiments, the vacuum should be maintained below 2.1*10-6 Pa for stabilizing the amplified operation.
Identification of culturable bacteria associated with the rhizosphere of Lablab purpureus growing in Namibia
Authors: Kavishe Faith Fransisca , Uzabakiriho Jean Damascène , Kennedy Jeya , Chimwamurombe Percy
Published: January 2024

Dolichos lablab (Lablab purpureus (L.) Sweet)) is a multipurpose drought tolerant protein-rich legume crop native to Africa and grown in warm temperate to tropical climates for its edible seeds and manure. Lablab purpureus holds significant benefits to subsistence farmers and offers a great promise for sustainable crop productivity, especially in marginalised areas. Its uses range from human consumption as a vegetable to improving soil fertility, and as forage. Notwithstanding Lablab purpureus crucial potential functions in Namibia, there is currently limited information regarding the plant’s rhizosphere bacteria. The study aimed at identifying Lablab purpureus’ natural rhizosphere bacteria. Isolation of rhizosphere bacteria involved the use of general media (Luria Bertani agar and tryptic soy agar); selective media such as Rhizobium and Yeast Extract Mannitol (YEM) Congo red from soil sample extracts. Eighty-five strains of bacteria were isolated and were subsequently identified by 16S rRNA gene sequencing analysis. The results showed that they belonged to the following genera, Bacillus, Streptomyces, Exiguobacterium, Stutzerimonas, Rhizobium, Acidovorax, Agrobacterium, Psychrobacter, Priestia, Planococcus, Bhargavaea, Stenotrophomonas, Caulobacter, Peribacillus, Niallia, Athrobacter, Sphingobium, Enterobacter, Sphingobacterium, Sinorhizobium, Flavobacterium, Microbacterium, Metabacillus, Neobacillus, and Pseudomonas which are reported to have growth promoting substances. The study highlighted the potential use of these plant growth promoting rhizobacteria for inocula production or biofertilisers for enhancing growth and nutrient content of beans and other crops under field conditions. The study was the first report of Lablab purpureus’s rhizosphere associated bacteria in Namibia.
Testing measurement invariance in a conditional likelihood framework by considering multiple covariates simultaneously
Authors: Draxler Clemens , Kurz Andreas
Published: January 2024

This article addresses the problem of measurement invariance in psychometrics. In particular, its focus is on the invariance assumption of item parameters in a class of models known as Rasch models. It suggests a mixed effects or random intercept model for binary data together with a conditional likelihood approach of both estimating and testing the effects of multiple covariates simultaneously. The procedure can also be viewed as a multivariate multiple regression analysis which can be applied in longitudinal designs to investigate effects of covariates over time or different experimental conditions. This work also derives four statistical tests based on asymptotic theory and a parameter-free test suitable in small sample size scenarios. Finally, it outlines generalizations for categorical data in more than two categories. All procedures are illustrated on real-data examples from behavioral research and on a hypothetical data example related to clinical research in a longitudinal design.
Contribution of genomic surveillance to the detection and monitoring of SARS-CoV-2 variants during the 6 pandemic waves in the Central African Republic from 2020 to 2023
Authors: Rafaï Clotaire Donatien , Lango-Yaya Ernest , Belizaire Marie Roseline Darnicka , Adonis Ouoko Fa-Ti-Gbia Maurel Annicet , Roungou Jean- Baptiste , SENZONGO Oscar , KOFFI Prof Boniface
Published: January 2024

Objective: The COVID-19 pandemic has highlighted the need to strengthen diagnostic and genomic surveillance capacities. The Central African Republic was able to manage 5 waves of disease during health monitoring and integrated genomic surveillance as a surveillance tool in 2021.
The aim of this study was to report surveillance data from the National Laboratory of Clinical Biology and Public Health and describe the landscape of circulation of SARS-CoV-2 variants.
Materials and methods: This retrospective, descriptive observational study over a period of 3 years (ranging from April 2020 to November 2023) was carried out on a population of consenting volunteers from throughout the CAR and tested by RT‒PCR on nasopharyngeal samples with sufficient information in the LNBCSP database. Sequencing is largely carried out at the INRB in KINSHASA and from May 2023 at the LNBCSP.
Results and discussion: Out of 97,864 RT‒PCR tests carried out, 9,764 were positive, which corresponds to a prevalence of 9.98%. The average age of the patients was 39.97 ± 13.76 years, and the sex ratio (M/F) was 2.12. RT‒PCR positivity was significantly associated with age (p=0.001), sex (p=0.013) and clinical manifestations. Ten variants circulated during the 5 waves recorded. The landscape of circulating variants was dominated by the Omicron (B.1.1.529) and Delta (B.1.617.2) variants and especially by B.1.620 and B.640, which marked the second wave in CAR-T cells.
Conclusion: This retrospective series provides key information for understanding the history of the COVID-19 pandemic in the CAR. Risk factors were identified, and the variant circulation landscape was described. Strengthening national genomic surveillance capacities would help the country adopt a better response against this pandemic.