bluuebunny/crossref_metadata_2025 huggingface dataset:
The promise of carrier screening: noninvasive prenatal diagnoses without proband for spinal muscular atrophy in early gestation age
Authors: Li Huanyun , Li Shaojun , Zhao Zhenhua , Fu Xinyu , Zhu Jingqi , Feng Jun , Tang Weiqin , Wu Di , Kong Xiangdong
Published: March 2024

The feasibility of traditional noninvasive prenatal diagnosis (NIPD) relying on proband-based relative haplotype dose analysis has been demonstrated. However, the prognosis of type I spinal muscular atrophy (SMA) is poor, and the proband sample is hard to collect during the second pregnancy. We investigate the feasibility of NIPD for SMA via haplotype construction without the need for a proband. Six samples were collected from both the paternal and maternal families in 36 families at risk of SMA. By enriching the SMN1/2 gene and its upstream and downstream informative SNPs, the family haplotype was constructed, and the Bayes factor was used to infer the fetal genotype by the dose changes of informational SNPs in cell-free DNA. All samples underwent MLPA testing after chorion villus sampling or amniocentesis. The MLPA results showed 100% consistency with NIPD. The earliest gestational week for successful NIPD was 7+ 3 weeks, with a minimum fetal fraction of 1.9%. Haplotype construction based on both paternal and maternal families demonstrated significant reliability and feasibility for families without a proband. Additionally, this approach provides a safer, and earlier prenatal diagnosis option for couples identified as at-risk through SMA carrier screening.
Question asking practice fosters curiosity in young children
Authors: Bonawitz Elizabeth , Park Anne , Colantonio Joseph , Reyes Lourdes Delgado , Sharp Sophie , Mackey Allyson
Published: March 2024

Children who are more curious learn more in school, but little is known about how to promote curiosity-driven behaviors. In a preregistered experiment, 103 children (54 boys, 49 girls, ages 5-7-years) were randomly assigned to a condition in which they were encouraged to ask questions, or to listen carefully, during eight one-on-one science lessons over two weeks. Children in the question-asking condition valued new science information significantly more than children in the listening condition (Wilcoxon r = .23). Children with less background knowledge benefited more from question-asking. These results suggest that practice with question-asking can boost some aspects of curiosity and learning.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Value shift in response to aging: A longitudinal study based on healthy aging
Authors: Shen Yiran , Cheng Xinjiao , Sang Xue , Cao Ruoyun , Yan Chaoyang
Published: March 2024

Objective
Healthy aging is considered an effective way to deal with the challenges of aging. Intrinsic capacity(IC) and functional ability (FA) are the key elements of this concept. However, the relationship between the two has not been explored in detail.
Methods
A theoretical model was constructed by analyzing the concept of “health aging quantification.” A national database (China Health and Retirement Longitudinal Study, CHARLS) was used as the data source for the study. A range of physical and mental measures were employed to construct intrinsic abilities using factor analysis, and a measure of disability was used as a proxy for FA. Descriptive and regression analyses were also conducted to preliminarily assess the distribution of the variables on the IC). This study used cross-lagged models to examine structural and effect differences between IC and FA in the longitudinal manner, along with mediation analysis to analyze the mechanism of the two.
Results
IC showed normal distribution and an increasing trend in education and income. In the structural analysis, IC and FA indicate significant cross-lagged effects in the longitudinal direction. The effect of IC on FA is also greater than that of FA on IC; such an effect also tends to intensify over time. Furthermore, multimorbidity mediates the effect of IC on FA, but the mediating effect is not very large. Finally, social participation did not significantly mediate the effect of FA on IC.
Conclusion
The study provides novel insights into the evolution of disability, in which the discovery of the disease is only a process of the outcome of disability. This suggests that policymakers should not only focus on identifying a disease, but also on assessing, maintaining, and providing intervention before the disease. The authorities should also promote the implementation of people-centered rather than disease-centered measures in the health delivery system to achieve value transformation.
Nugget and corona bond size measurement through active thermography and transfer learning model
Authors: Santoro Luca , Razza Valentino , De Maddis Manuela
Published: March 2024

Resistance Spot Welding (RSW) is considered a preferred technique for joining metal parts in various industries, mainly for its efficiency and cost-effectiveness. The mechanical properties of spot welds are pivotal in ensuring structural integrity and overall assembly performance. In this work, the quality attributes of resistance spot welding, such as nugget and corona bond sizes, are assessed by analyzing the thermal behavior of the joint using a physical information neural network (PINN). The investigation starts by examining the phase and amplitude gradient of the thermal signal. A convolutional neural network (CNN) is employed to estimate the size of the nuggets and corona bonds. The CNN architecture is based on the Inception V3 architecture, a state-of-the-art neural network that excels in image recognition tasks. This study presents a suggestion to adopt a new methodology for automatic RSW quality control based on thermal signal analysis.
High Sensitivity of Targeted Next-Generation Sequencing on Patients with Suspected Mycobacteria Infectious Diseases: A Prospective Matched Cohort Study
Authors: Hang Tian-Xing , Chen Yu , Ren Yun-Yao , Liu Xu-Hui , Hu Chun-Mei
Published: March 2024

Objectives
To evaluate the diagnostic accuracy of Mycobacterium-targeted next-generation sequencing (M-tNGS)technique forpatients with suspected Mycobacterium infectious diseases.
Methods
We consecutively enrolled patients with suspected Mycobacterium infectious diseases, collected samples (respiratory tract sample and tissue biopsy), and tested them using M-tNGS and GeneXpert MTB RIF (Xpert) assays. The results of these tests were compared with the clinical diagnosis and Mycobacterium culture results.
Results
Overall,244 patients were enrolled, from whom 206 respiratory samples and 38 tissue samples were obtained. The sensitivity of M-tNGS was superior to that of Xpert in both respiratory and biopsy samples (92.2% vs. 43.6% and 90.0% vs. 46.0%, respectively). Conversely, M-tNGS was less specific than Xpert in respiratory and biopsy samples (79.7% vs. 100% and 87.5% vs. 100% , respectively). Meanwhile, M-tNGS more frequently detected drug resistance and nontubercular mycobacteria (NTM), with sensitivity of 70.91% and 13.11%, respectively. Based on comparison with a composite reference standard, M-tNGS was more accurate than the Xpert assay and Mycobacteriumtuberculosis(MTB) culture, with areas under the curve of 0.86, 0.72, and 0.6, respectively.
Conclusion
M-tNGS is suitable for the early screening of Mycobacterium infectious diseases. Notably, M-tNGS can provide more information on drug resistance and Mycobacterium species identification, facilitating accurate treatment.
A Pilot Study: Deep Multi-Instance Learning for Origin Tracing of Brain Metastases
Authors: Yu Hui , Zhang Zhongzhou , Yang Ziyuan , Wang Tao , Wang Zhiwen , Wang Zhongxian , Liu Lunxin , Liu Yan , Zhang Yi
Published: March 2024

Treatment decisions for brain metastasis heavily rely on identifying the primary site, which is typically accomplished through biomarker-based techniques such as genomics and histopathology. However, limited healthcare resources sometimes can hinder their availability. Therefore, we innovatively transform origin tracing into an image classification task. Based on T1ce-MRI, we develop a non-invasive and cost-effective pipeline, called deep multi-instance learning (DMIL). The DMIL-based pipeline includes three steps: pre-processing, training and testing. Particularly, in pre-processing, mix-modal data decoration is proposed to learn multiple modal knowledge. For DMIL training, center-point-based lesion identification is employed to automatically crop ROIs, eliminating the need for manual intervention. Additionally, self-adaptive lesion classification aims to achieve slice-wise origin tracing. During the inference stage, to address the uncertainty stemming from heterogeneity within a patient's volume, we design a voting majority mechanism to make final patient-wise predictions. Evaluated on the clinical dataset, our DMIL-based pipeline demonstrated promising results. The best patient-wise results achieved at 87.27% (accuracy), 85.00% (PPV) and 83.33% (sensitivity).
A Phase I Study using Bortezomib (Velcade), Cladribine, and Rituximab (VCR) in Treating Elderly Patients with Mantle Cell Lymphoma
Authors: Pu Jeffrey J. , Berger Kristin N. , Zheng Chunlei , Do Nhan , Brophy Mary T. , Claxton David F. , Ehmann W Christopher , Drabick Joseph J. , Li Haiquan , Loughran Thomas P. , Epner Elliot M.
Published: March 2024

Cladribine indirectly downregulates methylations of DNA, RNA and histone by blocking transferring methyl groups from S-adenosyl-methionine. Cladribine and Rituximab combination showed a synergetic effect in treating B cell lymphomas. Bortezomib (Velcade) is a FDA approved proteasome inhibitor for treating mantle cell lymphoma (MCL).
In this single arm phase I study, we evaluated the safety, dose limiting toxicity, and efficiency of Bortezomib, Cladribine, and Rituximab (VCR) combination treatment in elderly MCL patients. We also proposed potential DNA methylation biomarkers for VCR treatment. A standard 3+3 dose escalation scheme was designed to determine the maximum tolerable cladribine dose. The therapy consisted of 6 28-day cycles.
Most patients tolerated this regimen well. The overall responding (OR) rate was 84.6% and complete remission (CR) rate was 84.6%. In newly diagnosed subject cohort, the OR and CR was 100% respectively, 1 year overall survival rate was 90%, and progression free survival rate was 80%. Low grade hematological toxicity and mild fatigue were observed. No severe systemic toxicity was observed. Five hypermethylated regions located at gene promoters were identified as potential biomarkers for an effective treatment response.
In conclusion, VCR combination is a well-tolerated, low toxicity and effective regimen for elderly untreated MCL.
Clinicaltrials.gov #: NCT01439750.
Affordances, aesthetics, and sustainability: on the relationship between materials, language and space in everyday object perception
Authors: Grasso Eduardo Naddei , Strappini Francesca , Borghi Anna M. , Scorolli Claudia
Published: March 2024

Everyday objects offer invitations to act (affordances). Most empirical work on affordances has focused on the shape and size of objects, neglecting the analysis of other visual properties, such as texture, investigated instead by designers. Texture perception depends on the type of material, which changes the familiarity, aesthetics, and action(s) an object offers. Here, we investigated the influence of aesthetics and material sustainability on affordance activation. We thus employed objects in materials. We re-adapted a well-established paradigm in literature, showing objects with the same shape, made from sustainable and non-sustainable materials (namely, plastic vs. wood) with varying degrees of familiarity and pleasantness. The objects were positioned at a near or far distance, and followed by different kinds of verbs (observation, manipulation, function, interaction). Participants also completed the Pro-Environmental Behaviors Scale (PEBS) and rated the objects according to seven dimensions: pleasantness, familiarity, sustainability, hardness, heaviness, ownership, and sociality. Results showed greater facilitation with plastic objects compared to the wooden ones when presented in the near space and followed by function verbs. However, we also found a main effect of the material, with response times (RTs) shorter for wooden objects, especially when followed by interaction verbs. We found no correlation between RTs and PEBS, though several significant interactions occurred, and we argue that the material component affected affordances within the specific interplay between object location and linguistic elaboration, hypothesizing that beauty might have transversely modulated the responses.
The Quality and Reliability of Short Videos about Thyroid Nodules on Bilibili and Tiktok: Cross-sectional Study
Authors: Chen YuYing , Wang Qianyu , Huang Xuanwei , Zhang Yu , Li Yuanhui , Ni Tianyu , Pan Gang , Luo Dingcun , Ni Yeqin
Published: March 2024

Purpose
The detection rate of thyroid nodules has witnessed a significant surge recently. Short video platforms such as Tiktok and Bilibili show tremendous potential in the dissemination of health information. There is a plethora of videos about thyroid nodules on Tiktok and bilibili with uncertain quality and reliability. garnering widespread popularity among users. The aim of study is to investigate the quality and reliability of these videos.
Methods
On December 3rd 2023, the top 100 short videos related to thyroid nodules on Bilibili and Tiktok were collected respectively. After extracting the basic information, the quality and reliability of each video was assessed by using the Global Quality Score (GQS) and DISCERN score. Further, Spearman correlation analyses were applied to examine the correlation among video variables, GQS and DISCERN score.
Results
Compared to Bilibili, Tiktok exhibits greater popularity, as evidenced by higher counts of likes, comments and shares. The median (interquartile range) scores of GQS and DISCERN score were 3 (2–3) on Tiktok while 2 (2–3) on Bilibili. Moreover, it was observed that the videos shared by thyroid specialists demonstrated higher scores both in GQS and DISCERN score than others on Tiktok. Spearman correlation analysis revealed no significant correlation between video variables and scores.
Conclusion
This study revealed that the quality and reliability of thyroid nodules videos on Bilibili and Tiktok were unsatisfactory. Notably, videos shared by thyroid specialists are more likely to exhibit superior quality and reliability, holding greater informative value. Consequently, people should be caution when perusing short videos.
Stability Assessment for Improved Mustard Production in Ecologically Diverse Regions of Jharkhand: Insights from AMMI and GGE
Authors: Kumar Vankadari Akhil , Kumar Niraj , Jagadeesh Kommineni , Kumar Arun , Mahto Chandrasekhar , Lal Hemchandra , Kumar Binay , Ahmed Ekhalaque , Kumar Sunil , Prasad Pradeep , Dubey Himanshu
Published: March 2024

The present study investigates the genetic variability and stability of 15 mustard (Brassica juncea) genotypes across four diverse locations in Jharkhand, employing a randomized block design with three replications. Significant differences among the genotypes are observed, with environmental factors and their interactions exerting a considerable influence. Utilizing the AMMI and GGE biplot methods, the study delves into the intricate interactions affecting economically vital traits such as seed yield per plant and oil percentage. The combined effect of environment and interaction explains a substantial portion of the observed variation of 79.6 and 58.9% on seed yield per plant and oil % respectively. The first two principal components together explained larger portion of 85.2% and 89.5% of the GXE variation of seed yield per plant and oil % respectively. The AMMI analysis had identified that, the genotypes Kranthi, PA-5232 and BAUM-09-12-1 for seed yield per plant and BAUM-08-18, Shivani, DRMRCI-70 and Pusa Bold for oil % are stable performers. The GGE biplot analysis and AMMI have commonly identified BAUM-09-12-1 and Pusa Bold as high yielding and most stable for seed yield per plant and oil % respectively. The results of AMMI identified ranchi as most ideal environment for selection of genotypes for both seed yield per plant and oil%, but GGE differs in-terms with Ranchi as ideal only for oil% and dumka for seed yield per plant. The availability of the above information of genetic variability and stability of genotypes for seed yield per plant and oil % can aid improving mustard production levels and self-sufficiency in edible oils.
Risk and predictive factors of rate of lymph node invasion in breast cancer with axillary involvement
Authors: RICHARD Maxime , HOTTON Judicaël , RAUCH Philippe , MARCHAL Frédéric , GOMES-DAVID Manuel , HEJL Lorraine , Pierret Marion , Abel-Decollogne Fabienne , Routiot Thierry
Published: March 2024

Perpose
Breast cancer is the most common cancer among women in France. Axillary lymph node invasion has a major prognostic impact. The aim of this study was to evaluate the risk and predictive factors of the rate of lymph node invasion in breast cancer with axillary involvement.
Methods
A retrospective study was conducted at the Lorraine Cancer Institute between 1 January 2014 and 31 December 2015. It included patients with breast cancer who underwent breast surgery associated with ALND (either immediately in case of positive FNAC, or secondarily in case of positive SLNB).
Results
In total, 194 patients were included. 99 underwent SLNB and ALND after (Group 1), 95 had a positive node in the FNAC and underwent ALND (Group 2). Multivariate analysis shown that only age at diagnosis (RR 2.79 [1.27; 5.74]), ultrasound tumor size (RR 2.97 [1.20; 7.64]), LVSI (RR 1.88 [1.07; 2.74]), multifocality (RR 2.27[1.35; 5.41]) and high histological grade (RR 3.38 [1.45; 9.74]) were significantly associated with a high axillary involvement. There was a 1.28% recurrence rate at 5 years in Group 1, compared with 28.21% recurrence rate at 5 years in Group 2 (p<0.001).
Conclusions
Age, tumor size (on ultrasound), lymphovascular invasion, multifocality and histological grade are risk and predictors factors of the rate of lymph node invasion. Preoperative positive FNB have a greater degree of lymph node involvement and a worse overall and progression-free survival than patients whose lymph node involvement was discovered at the time of the SLNB.
Development of a local binary pattern descriptor for texture analysis using deep convolutional neural network
Authors: SINGH HARDEEP SINGH , GAGAN GAGANDEEP
Published: March 2024

The machine learning is an important branch of artificial intelligence. In machine learning, the facial expression recognition continued a difficult and interesting topic. The majority of extant techniques are based on traditional features descriptors such as local binary patterns and its extended variants. This research paper expresses the strength of deep learning techniques that is the deep convolutional neural networks for classification of faces in selected dataset. We applied proposed Deep CNN architecture with local binary patterns and histogram of oriented gradient method. Viola Jones algorithm is applied for detection of faces from Face Recognition dataset. The features of faces are extracted by Binary Phase Component Analysis and information correlation factor gain. Then the classification of images is performed by our proposed deep convolutional neural network (Deep CNN). The performance of the model is evaluated by accuracy, precision, recall, f1-score and confusion matrix. The architecture of CNN constitutes convolutional layer, max-pooling, dense and flatten layers with dropout. The proposed architecture is validated on the Face Recognition dataset. We obtained 0.98 as accuracy which is the very high accuracy of deep CNN model for classification.
TINN: Time-step integration neural network for dynamic analysis of nonlinear structure systems subjected to seismic excitation
Authors: Li Changqing , Li Shuang , Chen Yicheng , Zhai Changhai
Published: March 2024

Dynamic analysis is an essential method for evaluating the seismic response of structures and predicting their seismic damage. The traditional time-step integration methods are computationally time-consuming and sensitive to structural complexity. This study proposes a novel time-step integration neural network (TINN) to perform dynamic analysis for nonlinear structures. TINN is composed of a fully connected feed-forward network and a residual network (ResNet) to simulate the calculation procedure of a single time step in the time-step integration method, and the recursive mechanism is applied to calculate the time history of structural responses. In addition, several techniques are applied to reduce the cumulative error due to the recursive mechanism to improve the accuracy and stability of TINN. TINN could accurately predict the seismic responses of all degrees of freedom (DOF) of the structures, including displacement, velocity, acceleration, and internal force. In particular, the efficiency of TINN doesn't decrease with the increase of structural DOF and the degree of nonlinearity, and it has no restrictions on the amplitude and duration time of the ground motion records. The results on three numerical cases show that TINN performs well in predicting the structural seismic responses with very limited training data available.
High throughput rapid amplicon sequencing for multilocus sequence typing of M. ovipneumoniae using DNA obtained from clinical samples
Authors: Framst Isaac , Wolking Rebecca M. , Schonfeld Justin , Ricker Nicole , Beeler-Marfisi Janet , Chalmers Gabhan , Kamath Pauline L. , Maboni Grazieli
Published: March 2024

Background
Spillover events of Mycoplasma ovipneumoniae have devastating effects on wild bighorn sheep populations. Multilocus sequence typing (MLST), a common method for tracking bacterial lineages, is used to monitor spillover events and the spread of M. ovipneumoniae between populations. Most work involving M. ovipneumoniae typing has used Sanger sequencing, however, this technology is time consuming, expensive, and is not well suited to efficient batch sample processing. Our study aimed to develop and validate a workflow for multilocus sequence typing of M. ovipneumoniae using Nanopore Rapid Barcoding sequencing and multiplex PCR. We compare the workflow with Nanopore Native Barcoding library preparation and Illumina MiSeq amplicon protocols to determine the most accurate and cost-effective method for sequencing multiplex amplicons.
Results
A multiplex PCR was optimized for four housekeeping genes of M. ovipneumoniae using archived DNA samples from wild sheep. Sequences recovered from Nanopore Rapid Barcoding correctly identified all MLST types with the shortest total workflow time, and lowest cost per sample when compared to Nanopore Native Barcoding, and Illumina MiSeq methods.
Conclusion
Our proposed workflow serves as a convenient and effective diagnostic method for strain typing of M. ovipneumoniae, and could be applied to other bacterial MLST schemes. The workflow is suitable for diagnostic settings where reduced hands-on time, cost and multiplexing capabilities are important.
Robust multivariate regression for high-dimensional data
Authors: Santana Juan Fernando Herrera , González Rubén Darío Guevara
Published: March 2024

Multivariate multiple linear regression is a widely used statistical technique for modelling relationships between some response variables and several predictor variables. Traditional likelihood-based methods can produce very misleading results in the presence of outliers. In this work, we propose two robust multivariate regression methods designed to handle high-dimensional data: one based on the minimum regularized covariance determinant estimator, a robust estimator of location and scatter for high-dimensional data; and another based on dimensionality reduction using robust sparse principal component analysis. Through a study simulation, we evaluate the robustness and efficiency of the estimators obtained, the ability of the methodologies to correctly classify observations in contaminated datasets, and the computational cost. A real data application illustrates the use of the proposed methodologies.
Prognostication of mechanical properties of Banana and Jute fiber reinforced concrete using AI
Authors: B.T Ashwini , Y.M Vijaya kumar , B.S Keerthi Gowda , D.T Naveen Kumar
Published: March 2024

In the present study, using data from experiments, an artificial neural network (ANN) model has been created to predict the strengths of concrete with banana and jute fibers at concrete ages of 7 and 28 days. The parameters considered for the ANN inputs are Grade of Concrete, FA, CA, W/C, Super Plasticizer, length, diameter and Density of fiber, curing in days, NaOH Concentration, Fiber treatment in hours, percentage of fiber added. The results from training and testing models have shown the great potential of ANN in predicting the compressive and flexural strengths of banana and jute fiber reinforced concrete.