bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Machine Learning Models Using Proposed EEG Vowel Dataset
Authors: Iqbal Asif , Bhardwaj Arpit , Suhag Ashok Kumar , Diwakar Manoj , Bijalwan Anchit 
Published: March 2024

Abstract

Electroencephalogram (EEG) signals are produced by neurons of human brain and contain frequencies and electrical properties. It is easy for a Brain to Computer Interface (BCI) system to record EEG signals by using non-invasive methods. Speech imagery (SI) can be used to convert speech imaging into text, researches done so far on SI has made use of multichannel devices. In this work, we propose EEG signal dataset for imagined a/e/i/o/u vowels collected from 5 participants using NeuroSky Mindwave Mobile2 single channel device. Decision Tree (DT), Random Forest (RF), Genetic Algorithm (GA) Machine Learning (ML) classifiers are trained with proposed dataset. For the proposed dataset, the average classification accuracy of DT is found lower in comparison to RF and GA. GA shows better performance for vowel e/o/u resulting accuracy of 80.8%, 82.36%, 81.8% for 70 − 30 data partition, 80.2%, 81.9%, 80.6% for 60 − 40 partition data and 79.8%, 81.12%, 78.36% for 50–50 data partition. Whereas RF shows improved classification accuracy for a/i which is 83.44%, 81.6% for 70 − 30 data partition, 82.2%, 81.2% for 60 − 40 data partition and 81.4%, 80.2% for 50–50 data partition. Some other performance parameters like min. value, max. value of accuracy, standard deviation, sensitivity, specificity, precision, F1 score, false positive rate and receiver operating characteristics are also evaluated and anal- ysed. Research has proven that brain functions remains normal in patients with vocal disorders. Completely disabled patients can be equipped with such technol- ogy as this may be one of the best way for them to have access over the essential day to day basic requirement.
Assessing the wastewater treatment efficiency and bioproducts accumulation potentials of co-cultures of mixotrophic microalgae
Authors: Inuwa Abdullahi Balarabe , Mahmood Qaisar , Irshad Muhammad , Faridullah Faridullah , Azeem Muhammad , Nazir Rashid 
Published: March 2024

Abstract

Utilization of microalgae for simultaneous wastewater treatment and bioproducts accumulation has been a subject of research interest for a while. However, in order to successfully turn this into reality, development of strategies to maximize the yield and performance of the deployed microalgae remains paramount. Herein, the performances and yield of different artificial microalgae consortia were evaluated in a synthetic municipal wastewater medium. The results revealed that the performance of the best monoculture (KL10) was more or less comparable to that of the best binary culture (CK). However, the general pattern of the result revealed that regardless of the species diversity in all the cultures, the average reduction of chemical oxygen demand and total phosphorus, as well as the accumulation of protein, chlorophyll a, chlorophyll b and carotenoids content remined comparable (p > 0.05). Furthermore, the average PO43--P reduction efficiency and biomass productivity of the monocultures was higher than (p < 0.05) those of the co-cultures. Conversely, average NH4-N reduction efficiency and lipid productivity of the binary cultures were superior (p < 0.05) to those of the other culture combinations. Finally, the fatty acids composition, which revealed similar fatty acids profile in all the cultures, suggests the suitability of all the cultures for utilization as feedstock for biodiesel production. In conclusion, the findings of the current study suggest that contrary to the popular notion, raising species diversity in microalgae cultures does not always guarantee increased yield and performance.
Based on Barbell 1RM: An Exploration of Load in Flywheel Resistance Training
Authors: Zhu Ziwei , Chen Jiayong , Xie Lin , Dai Jing , Huang Zijing , Zhang Wenfeng , Sun Jian , Li Duanying 
Published: March 2024

Abstract

Objective
This study aims to determine the optimal load for developing different abilities in flywheel resistance training (FRT) based on velocity indicators derived from the barbell one repetition maximum (1RM). The study seeks to establish the fitting relationship with flywheel load and derive the corresponding regression equation. Force-velocity profiles of the flywheel will also be used to propose load prescriptions in FRT.
Methods
39 participants underwent four tests, including a 1RM test to determine weights at different percentages (20%, 40%, 60%, 80%, 90% 1RM). Gymaware measured concentric velocities at different percentages of the 1RM. Inertial loads in FRT were explored based on the velocities. Reliability was assessed through velocity retesting. Linear and multiple linear regression were used for fitting relationships.
Results
A strong negative correlation (r = -0.88) between moment of inertia and velocity was observed (R2 = 0.78). The multiple regression model showed a high level of fit (R2 = 0.81) and a very strong correlation (r = 0.90). The regression equation is y = 0.769–0.846v + 0.002kg.
Conclusions
A multiple linear regression equation can determine personalized inertia load for FRT. FRT fosters chronic adaptations and acute capabilities but may not develop speed strength. Strength speed should be developed in the 40%-60% 1RM range, power in the 60%-80% 1RM range, and absolute strength in the 80%-100% 1RM range or beyond.
Working memory representations are spatially transferred in cortex during mental manipulations
Authors: Lundqvist Mikael , Chernik Charles , Berg Ronald van den 
Published: March 2024

Abstract

Working Memory (WM) enables us to maintain and directly manipulate mental representations, yet we know little about the neural implementation of this privileged online format. We recorded EEG data as human subjects engaged in a task requiring continuous updates to the locations of objects retained in WM. Analysis of contralateral delay activity (CDA) revealed that mental representations moved across cortex in real time as their remembered locations were updated.
Screening-enhanced effect enables poly(hexamethylene biguanide) hydrochloride to effectively overcome charge screening limitations
Authors: Wang Wenyi , Yang Chun , Liu Peng , Tao Peng , Cao Haijie , Yung Ka-Fu , Kan Chi-Wai 
Published: March 2024

Abstract
The charge screening caused by ionic strength always brings about negative effects. Poly(hexamethylene biguanide) (PHMB) was found to possess screening-enhanced effect and could effectively overcome charge screening limitations. However, the mechanism of action is unknown. We hereby combine flocculation experiments and theoretical simulations through density functional theory and molecular simulation to unravel the screening-enhanced effect. The biguanide groups of PHMB serve as primary active adsorption sites and activate the hydrogen atom in neighboring alkyl chains, which raises the binding possibility in the flocculation process. Electrolyte ions hardly affect the weak interactions but increase PHMB inter-segment stacking absorption and promote the hydrophobic effect of flocculation complexes, thereby enhancing the flocculation performance. The results suggest that the binding forces primarily arose from dispersion-dominant weak interactions, indicating a weak-interaction-dependent mechanism. This study may lay a solid foundation for developing screening-enhanced materials with the powerful capabilities of anti-charge screening limitations for specific application scenarios.
Molecular landscape of THEDES selective toxicity towards colorectal cancer
Authors: duarte Ana Rita , Oliveira Filipe , Pinto Joana , Amaro Filipa , Pereira Joana , Ferreira Inês , Diniz Mário , de Pinho Paula Guedes 
Published: March 2024

Abstract

In the relentless pursuit of overcoming modern medicine most highly demanding challenges, such as the most incident and deadliest cancers, as colon and rectum cancer (CRC), we keep on seeking innovative therapeutic solutions. Following deep eutectic systems spotlight due to their remarkable physicochemical and biological properties, versatility, and compliance with the green chemistry metrics, we sought to fill the gap between the reported promising toxicity of THEDES, combining a terpene with Ibu, towards cancer cells and the understanding of their specific impact on these cells molecular landscape. Hence, an integrated approach considering the effect of combining a terpene with Ibu as a THEDES, on permeability, cellular transport, cell viability, reactive oxygen species, cell metabolome and an in vivo systemic toxicity preliminary assessment was considered. On one hand, it was observed that exposing normal colonic cells to THEDES, at their EC50, promoted Ibu transcellular transport and cellular uptake. On the other hand, from THEDES exposure, CRC cells experience a control of ROS production, cell dead induction via apoptosis, and alteration on their metabolite landscape with deleterious effect on essential metabolic pathways, as lipid and anaerobic glycolysis energy production pathways. Furthermore, from a preliminary systemic toxicity evaluation, it was observed non-relevant systemic toxicity of these THEDES within the tested concentration range.
Digital Light Processing Printed Hydrogel Scaffolds with Adjustable Modulus
Authors: Xu Feng , Jin Hang , Wu Huiquan , Jiang Acan , Qiu Bin , Liu Lingling , Gao Qiang , Lin Bin , Kong Weiwei , Chen Songyue , Sun Daoheng 
Published: March 2024

Abstract
Hydrogels are extensively explored as biomaterials for tissue scaffolds, and their controlled fabrication has been the subject of wide investigation. However, the tedious mechanical property adjusting process through formula control hindered their application for diverse tissue scaffolds. To overcome this limitation, we proposed a two-step process to realize simple adjustment of mechanical modulus over a broad range, by combining digital light processing (DLP) and post-processing steps. UV-curable hydrogels are 3D printed via DLP, with the ability to create complex 3D patterns. Subsequent post-processing with Fe3+ ions bath induces secondary crosslinking of hydrogel scaffolds, tuning the modulus as required through soaking in solutions with different Fe3+ concentrations. This innovative two-step process offers high-precision (10 µm) and broad modulus adjusting capability (15.8–345 kPa), covering a broad range of tissues in the human body. As a practical demonstration, hydrogel scaffolds with tissue-mimicking patterns were printed for cultivating cardiac tissue and vascular scaffolds, which can effectively support tissue growth and induce tissue morphologies.
CSPDNet:A New Lightweight Network for Efficient UAV Object Detection
Authors: Hua Wei , Chen Qili , Chen Wenbai 
Published: March 2024

Abstract
Optimizing the structure of deep neural networks is essential in many applications. Especially in the object detection tasks of Unmanned Aerial Vehicles (UAVs). Due to the constraints of the onboard platform, a more efficient network is required to meet practical demands. Nevertheless, existing lightweight detection networks exhibit excessive redundant computations and may yield in a certain level of accuracy loss. To address these issues, this paper proposes a new lightweight network structure named Cross-Stage Partially Deformable Network (CSPDNet). The initial proposal consists of a Deformable Separable Convolution Block (DSCBlock), separating feature channels, greatly reducing the computational load of convolution, and applying adaptive sampling to the separated feature map. Subsequently, to establish information interaction between feature layers, a channel weighting module is proposed. This module calculates weights for the separated feature map, facilitating information exchange across channels and resolutions. Moreover, it compensates for the effect of pointwise (1 × 1) convolutions, filtering out more important feature information. Furthermore, a new CSPDBlock is designed, primarily composed of DSCBlock, establishing multidimensional feature correlations for each separated feature layer. This approach improves the ability to capture critical feature information and reconstruct gradient paths, thereby preserving detection accuracy. The proposed technology achieves a balance between model parameter size and detection accuracy. Furthermore, experimental results on object detection datasets demonstrate that our designed network, using fewer parameters, achieves competitive detection performance results compared to existing lightweight networks YOLOv5n, YOLOv6n, YOLOv8n, NanoDet and PP-PicoDet. The optimization effect of the designed CSPDBlock, using the VisDrone dataset, is validated when incorporated into advanced detection algorithms YOLOv5m, PPYOLOEm, YOLOv7, RTMDetm and YOLOv8m. In more detail, by incorporating the designed modules it was achieved that the parameters were reduced by 10%-20% while almost maintaining detection accuracy.
Domestic Violence and Its Predictors Among Pregnant Women in Durame Town, Central Ethiopia, 2023. A Community Based Cross-Sectional Study
Authors: Lonsako Arega Abebe , Yonas Fekadu , Ermias Dejene , Gizachew Addisalem 
Published: March 2024

Abstract
Background
Domestic violence is one of the major public health problems throughout the world. Poor and middle-income countries experience more severe domestic violence against pregnant women. It has a negative effect on both mothers and their offspring. However, there was limited evidence on the domestic violence among pregnant women in central Ethiopia. Thus, this study aimed to assess the prevalence of domestic violence and its predictors among pregnant women in Durame Town, Central Ethiopia.
Methods
A community-based cross-sectional study was conducted among 300 pregnant women in Durame Town. A systematic random sampling technique was used to select the participants. Data were collected through an interviewer-administered questionnaire, entered into EpiData version 4.6 and exported to statistical package for the social sciences (SPSS) version 26 for analysis. Descriptive and multivariate logistic regression analyses were performed and statistical significance is declared at p < 0.05.
Results
The prevalence of domestic violence among pregnant women was 49.0% with 95% CI: (43.3 to 54.7), Mothers who have no formal education [AOR = 3.26; 95% CI: (1.33, 7.98)], Husbands alcohol consumption [AOR = 2.96; 95% CI: (1.68, 5.24)], Housewives [AOR = 2.25; 95% CI: (1.19, 4.22)], and Husbands no formal education [AOR = 3.64; 95% CI: (1.35, 9.84)] were significant factors associated with domestic violence among pregnant women.
Conclusions
In this study the prevalence of domestic violence among pregnant women was high. Mothers who have no formal education, housewives, husband’s alcohol consumption and husbands no formal education were factors associated with domestic violence.
Psychological distress mediates the association between COVID-19-related discrimination and subsequent PTSD symptom severity in healthcare workers: a two-year follow-up study
Authors: Narita Zui , Okubo Ryo , Sasaki Yohei , Takeda Kazuyoshi , Takao Masaki , Komaki Hirofumi , Oi Hideki , Miyama Takeshi , Kim Yoshiharu 
Published: March 2024

Abstract
Background
Past research has suggested a cross-sectional association between COVID-19-related discrimination and PTSD symptom severity. However, no cohort study has examined the longitudinal association that allows causal interpretation. Also, even if such an association genuinely exists, the mechanism remains unclear.
Methods
We conducted a two-year follow-up study, obtaining data from healthcare workers in a hospital setting. We first evaluated how COVID-19-related discrimination in 2021 was associated with subsequent PTSD symptom severity in 2023. Thereafter, we conducted causal mediation analysis to examine how this association was mediated by psychological distress in 2022, accounting for exposure-mediator interaction. Missing data were handled using random forest imputation.
Results
A total of 660 hospital staff were included. The fully adjusted model showed greater PTSD symptom severity in individuals who experienced any COVID-19-related discrimination compared with those without such experiences (β, 0.44; 95% CI, 0.04–0.90). Regarding each type of discrimination, perceived discrimination was associated with greater PTSD symptom severity (β, 0.52; 95% CI, 0.08–0.96), whereas verbal discrimination did not reach statistical significance. Psychological distress consistently mediated 28.1–38.8% of the observed associations.
Conclusions
COVID-19-related discrimination is associated with subsequent PTSD symptom severity in healthcare workers. Psychological distress may serve as an important mediator, underscoring the potential need for interventions targeting this factor.
Synthesis of carbon dots from biogas-plant-derived carbon residue by solvothermal method
Authors: Otomo Takato , Tsukuda Satoshi 
Published: March 2024

Abstract
To effectively utilize waste biomass, such as food waste and kitchen waste, conversion to renewable energy, such as biogas using methane fermentation has been put into practical use. However, only a portion of the waste is converted into biogas, and most of the waste remains as a residue, the main component of which is carbon. We focused on biogas-plant-derived carbon residues (BPC) as precursors for carbon dots (CDs). CDs were successfully synthesized from BPC using a solvothermal method and high-quality blue-emitting CDs were extracted using column chromatography. In addition, the emission wavelength was tuned by modifying the CD surface. This communication shows that BPC has high potential as an environmentally friendly precursor for CD synthesis.
Prompt-driven Healthy/Diseased Image Pairs Enabling Pixel-level Chest X-ray Pathology Localization
Authors: Suo Jinli , Dong Kaiming , Cheng Yuxiao , He Kunlun , Dai Qionghai 
Published: March 2024

Abstract
Medical artificial intelligence (AI) offers great potential for automatic pathology interpretation, but the performance is far behind providing a practical tool in clinical settings, which demands both pixel-level accuracy and high interpretability for diagnosis. The main challenges lie in that the construction of such AI models relies on substantial training data with fine-grained labeling that is impractical in real applications. To circumvent this barrier, we propose a prompt-driven constrained generative model to produce anatomically aligned healthy/diseased image pairs and then learn a superb pathology localization model in a supervised manner.
The new paradigm effectively addresses the lack of high-fidelity chest X-ray images with pathology labeling at fine scales. Benefiting from the emerging text-driven generative foundation model and the newly incorporated constraint, our model presents promising localization accuracy of the subtle pathologies, high interpretability for clinical decisions, and good transfer ability to many unseen pathological categories (e.g., new prompts and mixed pathologies). These advantageous features establish our model as a promising solution to assist chest X-ray analysis. Besides, the proposed approach is also inspiring for other tasks lacking massive training data and time-consuming manual labeling.
A Novel Environmental pressure Compensation Approach of IR Gas Sensors in Industrial environment
Authors: Su Jiahao , Zhang Hailong , Wang Chunguang , Tan Bo , Tian Fuchao 
Published: March 2024

Abstract
In order to improve the analytical accuracy and applicability of infrared gas sensors, this paper examines the need to integrate a pressure compensation algorithm into the infrared gas analyzer, identifying appropriate compensation methods and optimizing test data accuracy. First, a test platform was constructed to evaluate the accuracy of three types of infrared sensors for trace gases in industrial environments. The sensors were tested in the following order: CO2 at concentrations of 0.5%-4.5%; CH4 at concentrations of 2%-18%; and CO at 100-900ppm standard gas concentrations, found that the maximum value of the test error were 48%, 44.5%, 45%, respectively, do not meet the error range specified in the standard. Secondly, the constant-pressure accuracy test was carried out by selecting the same concentration of CO2, CH4 and CO standard gases and substituting them into the optimized least squares compensation model, and it was found that the maximum errors of the three gas tests were 16%, 9% and 24%, which were superior to the standard error ranges. Thirdly, the pressure compensation was verified for the three infrared gas analyzers after algorithmic compensation within the pressure compensation device. Based on this, the optimized least squares-wavelet transform soft threshold coupling model were established to integrate the ambient pressure, the test concentration and the standard gas concentration with the optimization model, and it was found that the maximum measurement errors after optimization with the optimized least squares-wavelet transform soft thresholding coupling method were 0.2%, 0.05% and 1%. In summary, this paper develops an error optimization model for various environmental pressure conditions, and provides a theoretical framework for the research and development of infrared gas analyzers and other spectroscopic gas detecting instruments. Additionally, it establishes a technical foundation for constructing in-situ on-line monitoring systems for trace gases in industrial environments.
A green method of preparation of porous melamine formaldehyde resin without template in aqueous solution
Authors: Cui Huapeng , Li Shengnan 
Published: March 2024

Abstract
Porous melamine formaldehyde resin was synthesized by a green method without using template in aqueous solution, the chemical property and pore structure of porous melamine formaldehyde resin were characterized by infrared, SEM and BET. SEM images showed that the pore structure of the as-synthesized samples was formed by nanoparticles accumulation. The surface area and pore structure of melamine formaldehyde resin could be adjusted by changing the prepolymer concentration. The adsorption capability of the as-synthesized melamine formaldehyde resin for Congo Red (CR) is examined. The results show that melamine formaldehyde resin exhibits a large adsorption capacity. This investigation reveals that the -NH2 and pore structure have great effects on the adsorption capacity of Congo Red dye of the as-synthesized melamine formaldehyde resin samples.