bluuebunny/crossref_metadata_2025 huggingface dataset:
DNA methylation signatures in the prefrontal cortex of alcohol-naïve nonhuman primates predict risk for future ethanol drinking.
Authors: Juanes Rita Cervera , Zimmerman Kip , Wilhelm Larry , Lowe Clara , Gonzales Steve , Carlson Timothy , Ferguson Betsy , Grant Kathleen
Published: May 2024

Alcohol use disorder (AUD) is a highly prevalent, complex, multifactorial and heterogeneous disorder, with 11% and 30% of adults meeting criteria for past-year and lifetime AUD, respectively. Early and accurate identification of individuals at risk of developing an AUD would facilitate effective deployment of personalized interventions. Studies using rhesus monkeys1,2 and rats3, have demonstrated that individuals with low cognitive flexibility and a predisposition towards habitual behaviors show an increased risk for future heavy drinking. Further, low cognitive flexibility is associated with reduced dorsolateral prefrontal cortex (dlPFC) function in rhesus monkeys2. To explore the underlying unique molecular signatures that may predict risk for chronic heavy drinking, a genome-wide DNA methylation (DNAm) analysis of the alcohol-naïve dlPFC-A46 biopsy prior to chronic alcohol self-administration was conducted. The DNAm profile provides a molecular snapshot of the alcohol-naïve dlPFC, with mapped genes and associated signaling pathways that vary across individuals. The analysis identified ten DMRs that were strongly predictive of average ethanol intake consumed over 6 months of voluntary self-administration. Importantly, the same set of DMRs was able to predict drinking levels with moderate success in an independent cohort of macaques. These findings translate behavioral phenotypes into neural markers of risk for AUD, and hold promise for parallel discoveries in risk for other disorders involving impaired cognitive flexibility.
Development and testing of auxetic shoulder straps for sport backpacks
Authors: Parisi Mariafederica , Colombo Daniel , Fauci Giuseppe La , Bianca Eleonora , Dotti Francesca , Ferri Ada , Colonna Martino
Published: May 2024

Auxetic foams and lattices are a promising class of materials characterised by a negative Poisson's ratio that can be used for the development of next-generation sports equipment due to their outstanding properties (e.g., multi- impact behaviour and flexibility). We present an application of these materials in backpacks as a viable alternative to current systems with improved comfort. auxetic designs have been used to create ergonomic shoulder straps for trekking backpacks to improve their thermal comfort by exploiting the expansion of the auxetic cells under tensile load. Further optimisation of the proposed application can be achieved in the future by using the collected data in analytical models to predict the behaviour of these systems.
Magnetic response of sampling depth to heavy metal pollution in urban topsoil in China
Authors: Hao Yanfang , Liu Liang , Tong Fan , Li Chenhui , Ma Fan , Zhao Xiaofang
Published: May 2024

As urbanization accelerates, the issue of heavy metal contamination in urban topsoil has garnered significant attention. To investigate the soil layer where magnetic and heavy metal characteristics peak, this study analyzes the magnetic signatures of urban topsoil heavy metal pollution across various Chinese regions using literature data. It assesses the relationship between magnetic susceptibility (MS) and heavy metal concentrations at different sampling depths. Findings reveal diverse heavy metal pollution levels in urban topsoils, with pronounced spatial variability in contamination severity. The magnetic signatures of heavy metal pollution fluctuate with sampling depth. Specifically, the 0–5 cm layer typically reflects peak magnetic values. Heavy metal concentrations initially rise then fall with increasing depth, reaching peak levels at slightly varying depths for different metals. Pb, Zn, Cr, and Mn tend to concentrate within the top 5 cm, while Cu, Ni, and Fe show enrichment up to 10 cm. Mass magnetic susceptibility (χlf) demonstrates the strongest correlation with heavy metals at 0–5 cm, suggesting this as the optimal sampling depth for studying magnetic responses to soil heavy metal pollution, unless specific requirements dictate otherwise. Moreover, χlf is a reliable indicator of urban topsoil heavy metal pollution. These insights are crucial for determining sampling depths in related studies, thereby improving urban soil quality research and assessment methodologies.
A low-rank algorithm for computing Lyapunov operator phi-functions within matrix-valued exponential integrators
Authors: Li Dongping , Zhang Xiuying , Tian Hongjiong
Published: May 2024

In this work we introduce a low-rank algorithm designed to compute low-rank approximations of large-scale Lyapunov operator φ-functions. These computations are crucial for the implementation of matrix-valued exponential integrators tailored for large-scale stiff matrix differential equations, where the (approximate) solutions are of low rank. The method is developed using a scaling and recursive procedure, supplemented by a quasi-backward error analysis to determine the optimal parameters. The computational cost of the method primarily arises from the products of sparse matrix and block vectors.Numerical experiments confirm the effectiveness of the proposed method as a foundational tool for matrix-valued exponential integrators in addressing large-scale differential Lyapunov equations and Riccati equations.
MSC Classification: 65L05 , 65F10 , 65F30
Zingiberensis New Saponin Inhibits LncRNA TCONS-00026762/AKR1C1 Pathway, Revealing Unique Insights into Cellular Processes and Drug Response in Hepatocellular Carcinoma
Authors: Luo Liang , He Keqing , Zhou Pingsheng , Liu Xing
Published: May 2024

Background
Long non-coding RNAs (lncRNAs) are often involved in regulating various cellular processes during cancer progression. This study aimed to investigate the role of Zingiberensis new saponin (ZnS) in hepatocellular carcinoma (HCC) cells through the lncRNA TCONS-00026762/AKR1C1 pathway.
Methods
Bioinformatics analysis was initially used to assess the prognostic significance of AKR1C1 in TCGA liver cancer data. Huh7 and Huh7-SR cells were either transfected with sh-TCONS-0026762 and oe-AKR1C1 or treated with ZnS and oe-TCONS-00026762. The expression of TCONS-00026762 and AKR1C1 was quantified using quantitative real-time PCR. The effects of either TCONS-00026762 knockdown or ZnS treatment on autophagy, ferroptosis, and drug sensitivity were investigated using a combination of immunofluorescence staining, western blot, and CCK-8 assays.
Results
Bioinformatics analysis revealed that AKR1C1 is a prognostic marker for HCC and is association with autophagy, ferroptosis, and immune evasion. Knockdown of TCONS-00026762 suppressed autophagy, promoted ferroptosis, and enhanced sensitivity to sorafenib in HCC cells, as evidenced by the decrease in levels of the autophagy marker LC3, as well as ferroptosis markers GPX4 and SLC7A11, and an increase in Huh7-SR cell viability. However, these changes were reversed by overexpression of AKR1C1. Moreover, ZnS treatment significantly downregulated the expression of TCONS-00026762 and AKR1C1, leading to inhibition of autophagy, induction of ferroptosis, and increased susceptibility of HCC cells to sorafenib. Notably, these effects were reversible upon the overexpression of TCONS-00026762.
Conclusions
Our findings suggest that ZnS inhibits autophagy, promotes ferroptosis, and enhances sensitivity to sorafenib in HCC cells through the lncRNA TCONS-00026762/AKR1C1 pathway.
VEGFB ameliorates insulin resistance in NAFLD via the PI3K/AKT signal pathway
Authors: Li Yuqi , Li Wenhao , Zhu Xiaonan , Xu Nuo , Meng Qinyu , Jiang Wenguo , Zhang Lei , Yang Meizi , Xu Fang , Li yana
Published: May 2024

Background: Non-alcoholic fatty liver disease (NAFLD) is one of the most universal liver diseases with complicated pathogenesis throughout the world. Insulin resistance is a leading risk factor that contributes to the development of NAFLD. Vascular endothelial growth factor B (VEGFB) was described by researchers as contributing to regulating lipid metabolic disorders. Here, we investigated VEGFB as a main target to regulate insulin resistance and metabolic syndrome.
Methods: In this study, bioinformatics, transcriptomics, morphological experiments, and molecular biology were used to explore the role of VEGFB in regulating insulin resistance in NAFLD and its molecular mechanism based on human samples, animal models, and cell models. RNA-seq was performed to analyze the signal pathways associated with VEGFB and NAFLD; Palmitic acid and High-fat diet (HFD) were used to induce insulin-resistant HepG2 cells model and NAFLD animal model. Intracellular glucolipid contents, glucose uptake, hepatic and serum glucose and lipid levels were examined by Microassay and Elisa. Hematoxylin-eosin staining, Oil Red O staining, and Periodic acid-schiff staining were used to analyze the hepatic steatosis, lipid droplet, and glycogen content in the liver. Western blot and quantitative real-time fluorescent PCR were used to verify VEGFB and insulin resistance-related signaling pathway PI3K/AKT signals expression levels.
Results: We observed that VEGFB is genetically associated with NAFLD and the PI3K/AKT signal pathway. After VEGFB knockout, glucolipids levels were increased, and glucose uptake ability was decreased in insulin-resistant HepG2 cells. Meanwhile, body weight, blood glucose, blood lipids, and hepatic glucose of NAFLD mice were increased, and hepatic glycogen, glucose tolerance, and insulin sensitivity were decreased. Moreover, VEGFB overexpression reduced glucolipids and insulin resistance levels in HepG2 cells. Specifically, VEGFB/VEGFR1 activates the PI3K/AKT signals by activating p-IRS1Ser307 expression, inhibiting p-FOXO1pS256 and p-GSK3Ser9 expressions to reduce gluconeogenesis and glycogen synthesis in the liver. Moreover, VEGFB could also enhance the expression level of GLUT2 to accelerate glucose transport and reduce blood glucose levels, maintaining glucose homeostasis.
Conclusions: Our studies suggest that VEGFB could present a novel strategy for treating NAFLD as a positive factor.
High rate acidogenic fermentation in an up-flow anaerobic sludge bed reactor at extremely low pH
Authors: Zheng Mingyue , Wu Yuanyuan , Zheng Mingxia , Yu Jingwen , Wang Kaijun , Xin Xiulan , Zhang Xiaohui
Published: May 2024

Volatile fatty acid (VFA) platform has drawn much attention and it has been confirmed that VFA production by mixed-culture acidogenic fermentation at low pH has several advantages. The metabolic mechanisms and stability of acidogenic fermentation at low pH was investigated by a continuous stirred tank reactor (CSTR) fed with glucose with pH controlled at 4.0 (day 1–28), 5.0 (day 29–42) and 4.0(day 43–62). Results indicated lactate fermentation and ethanol fermentation coexist when pH was controlled at 4.0. Lactobacillus was the dominant bacteria. However, when pH in CSTR reactor was increased and controlled at 5.0, the fermentative type changed. In order to improve the efficiency of acidogenic fermentation at low pH, a up-flow anaerobic sludge bed (UASB) reactor was operated with glucose as feeding material and the organic loading rate (OLR) of UASB gradually increased and eventually was high up to 42 g/(L.d). When operated at OLR of 42 g/(L.d) and HRT of 4 h, the UASB reactor was found with a higher VFAs yields of 16.4 gCOD/(L.d), which was much higher than CSTR reactor. In addition, acidogenic granular sludge successfully appeared in UASB reactor at extremely low pH of 3.2~4.0. Lactobacillus was also predominant in the acidogenic granular sludge of UASB reactor, which was similar with CSTR reactor, however, biohydrogen-producing bacteria also took large proportion.
Comparing voids in three root canal obturation techniques: a Micro-CT study
Authors: Gharib Iad , Wong Ferranti , Davis Graham
Published: May 2024

Objectives:
Micro-computed tomography (micro-CT) is an invaluable tool in measuring residual voids after filling root canals as an indicator of the quality of root canal treatment. This study compares void volumes in root canals filled using the cold lateral condensation (CLC) continuous wave (CWC), or single cone (SC) techniques.
METHODS:
99 maxillary premolars allocated according to internal anatomy into three matching groups. The root canals were shaped and cleaned and filled with Gutta‑percha and TubliSeal® EWT sealer using cold lateral condensation (CLC), continuous wave condensation (CWC) or single cone (SC) technique. Void volumes were calculated using a novel software at 30 µm isotropic voxel size resolution. The total void volumes (TVVs) for each technique were statistically compared using Mann-Whitney non-parametric test.
RESULTS:
The mean percentage of the TVVs (%TVVs) found in SC (1.86±1.64%) group was statistically higher than that in CLC (0.75±0.45%) group, which in turn had statistically significantly more %TVVs than CWC (0.55±0.52%) group.
CONCLUSION:
The results of this study show that, in maxillary premolars, the SC obturation method resulted in significantly larger %TVVs than both CLC and CWC. The CWC technique resulted in significantly less %TVVs compared to CLC and SC methods.
Reconstruction and enhancement techniques for overcoming occlusion in face recognition
Authors: Pleško Filip , Goldmann Tomáš , Malinka Kamil
Published: May 2024

Face occlusions on CCTV cameras obscure important key facial features, preventing face recognition (FR) systems from recognizing people. This work mainly focuses on reconstructing these missing facial parts using Generative Adversarial Neural Networks (GANs) to improve FR accuracy while maintaining a low False Acceptance Rate (FAR). In addition, we are trying to improve the generated images further by using different image enhancement methods to test whether they can be used to improve the FR accuracy. To test the results, we perform experiments using state-of-the-art FR methods such as QMagFace and ArcFace to see whether image reconstruction and image enhancement help to improve FR accuracy.
Fatty acid synthesis promoted by PA1895-1897 operon delays quorum sensing activation in Pseudomonas aeruginosa
Authors: Han Lei , Ren Jie , Xue Yishu , Gao Jianwei , Fu Qiang , Shao Ping , Zhu Hui , Zhang Min , Ding Fengming
Published: May 2024

PA1895-1897 is a quorum sensing (QS) operon regulated by the anti-activator LuxR homologue QscR in Pseudomonas aeruginosa. We aimed to investigate its impact on bacterial metabolism, and whether it contributes to the delayed QS activation. We performed liquid chromatograph-mass spectrometer–based metabolomics using wildtype PAO1, PA1895-1897-knockout mutant, and mutant with pJN105.PA1895-1897 overexpression vector at the OD600nm of 1.8. The impact of metabolites on QS signal molecule (3OC12-HSL and C4-HSL) concentrations, pyocyanin production, and QS gene (lasR, lasI, rhlR, and rhlI) expression was examined. Metabolomics analysis found that fatty acid biosynthesis had the highest fold enrichment among all metabolic pathways. Medium- and long-chain fatty acids including palmitoleic acid, 2,2-Dimethyladipic acid, undecanoic acid, methylglutaric acid, myristoleic acid, myristic acid, pentadecanoic acid, and some short-chain fatty acids (butyric acid, acetic acid, and caproic acid) were down-regulated by PA1895-1897 knockout, and up-regulated by PA1895-1897 overexpression. Among these fatty acids, palmitoleic acid and acetic acid were the predominantly abundant fatty acids affected by PA1895-1897 operon. When different doses of exogenous palmitoleic acid or acetic acid were added to the cultures of PA1895-1897 knockout mutants, their levels of 3OC12-HSL, C4-HSL, and pyocyanin were decreased in a dose-dependent manner. High doses of palmitoleic acid and acetic acid suppressed the mRNA expression of lasR, rhlR, and rhlI. Inhibition of fatty acid biosynthesis increased the production of 3OC12-HSL, C4-HSL, and pyocyanin in PA1895-1897-overexpressed culture. Our data suggest that fatty acid synthesis is promoted by PA1895-1897 operon, and contributes the delayed expression of QS phenotypes, furthering the understanding about the regulation of bacterial QS activation.
Artificial Neural Network Modeling on Heat Transfer Performance of Finned Heat Pipe
Authors: Seo Young Min , Choi Ho Yeon , Ko Rock Kil , Kim Seokho , Park Yong Gap
Published: May 2024

A numerical analysis has been conducted to examine the heat transfer characteristics of a finned heat pipe based on thermal resistance networks. The present numerical analysis also reports the enhancement of heat transport of heat pipe using the fins. The key simulation parameters considered were three types of fins with circular, square, and hexagonal shapes, the fin length in the range from 19.05mm to 38.1mm, the number of fins in the range from 5 to 20, and the fin thickness in the range from 0.25mm to 1mm. The heat transfer rate shoots up by 62.58% in the case of finned heat pipe when compared with the baseline model with respect to the variation in the simulation parameters. An artificial neural network, which is one of the machine learning methods, was used to predict the heat transfer performance obtained from thermal resistance analysis of the finned heat pipe. The optimized ANN model could predict the heat transfer performance of the finned heat pipe with reasonable accuracy. In addition, the heat transfer rate of the finned heat pipe could be predicted accurately from extrapolated and interpolated data using the optimized ANN model.
RETRACTED: Droplet Breakup and Evaporation in Liquid-Fueled Detonations
Authors: Young Calvin , Duke-Walker Vasco , McFarland Jacob
Published: May 2024

The authors have requested that this preprint be removed from Research Square.
Absolute and age-relative suicide-rates for women and men age 60 years and older, at the global, region, and nation level, 1990-2019: a systematic analysis of the Global Burden of Disease Study 2019 data
Authors: Sha Feng , Chang Qingsong , Zhao Ziyi , Cai Ziyi , Li Bingyu , Wu Donghui , Yu Xin , Yip Paul S.F. , Canetto Silvia
Published: May 2024

Suicide-rates are highest among older adults. Yet, older-adult suicide has been under-studied, particularly in relation to suicide in other age-groups, and by sex and location. Age-standardized suicide-rates (ASSR) of older-adults (OA) (ages 60-years-and-older) and non-older-adults (NOA) (ages 10-59 years), and the ratio of OA-to-NOA ASSR, for the 1990-2019 period, were calculated based on 2019 Global-Burden-of-Disease (GBD) data. OA absolute and age-relative ASSR were examined by country/nation/territory Socio-Demographic Index (SDI). There was a significant negative-correlation between OA-to-NOA ASSR and SDI. OA-to-NOA ASSR-ratios were larger in women in many regions, though OA ASSR were lower among women. The finding that OA had higher age-relative suicide-rates in lower socioeconomic-position regions challenges the belief that OA-suicide is a problem of higher socioeconomic-position regions. The fact that in many regions OA age-relative suicide-rates were higher in women than in men challenge the belief that OA women are protected from suicide.
Examining the Physiological Traits of Callus Tissues from Endosperm- Supported Mature Embryos in Common Wheat (Triticum aestivum L.) under In Vitro Salt Stress Conditions
Authors: Mouhssine Fatine , Elyacoubi Houda , Imtara Hamada , Ez-zriouli Rabab , Elgoumi Younes , AlZain Mashail N. , Shahat Abdelaaty A. , Alzamel Nurah M. , Rochdi Atmane
Published: May 2024

Salt tolerance is a much-needed potential in cereal crops. To date, numerous research protocols have focused on establishing selection programs to increase tolerance and productivity of crops in salt-stressed areas. In this study, we aimed to induce callus from endosperm-supported mature embryos of five common wheat varieties (Nassim, Wissam, Wafia, Rajae, and Tigre) subject directly to various increasing NaCl concentrations (0–9 g/L) under in vitro culture process. We chose callus growth, organic solutes accumulation, and ion content as main traits to evaluate the impact of salinity on stressed calli. Our findings indicate that the accentuated salinity pressure leads to a substantial elevation of Cl−, Na+, proline and soluble carbohydrates content, along with a reduction in callus growth, potassium accumulation, and K+/Na+ ratio. Yet, the performance under salt stress was significantly dependent on the varietal effect. At the highest concentration, the marked values of these solutes (12.06 µmol/g FM of proline; 43 µmol/g FM of Total soluble sugar; 31.15 mg/ g DM Na+; 12.82 mg/g DM of Cl−, 12.61 mg/g DM of K+ and 0.40 K+/Na+) were respectively recorded by Rajae. Principal component analysis (PCA) first classified Rajae as the most tolerant followed by wafia as tolerant, while Wissam and Tigre were ranked as sensitive. Whereas, the variety Nassim showed a moderate tolerance. Besides the K+/Na + Ratio and salinity tolerance index (STI), the PCA analysis has shown that all the studied physiological criteria seem worthwhile for better discrimination of the varieties tested according to their reaction to salinity.
New Method for Transient Signal Analysis using the Continuous Wavelet Transform
Authors: Gomez-Luna Eduardo , Cuadros Dixon , Candelo-Becerra John E.
Published: May 2024

This paper presents a new method for transient signal analysis in the frequency domain based on the continuous wavelet transform (CWT). The study involved testing signals obtained from an electronic switch that considers opening and closing operations. The source is connected to inductive, resistive, and capacitive loads. The resonance behaviors were analyzed, obtaining the result that the signal processing performed by CWT is better for spectrum analysis than the Fourier Transform (FT). The results show that the CWT achieves greater reliability, repeatability, high noise attenuation, and softness of the analyzed spectrum. This study shows the potential of WT for analyzing transient signals, specifically in the connection and disconnection of loads.
Nanoparticle uptake by a semi-permeable, spherical cell from an external planar diffusive field. III. Analysis of an experimental system
Authors: Miklavcic Stanley Joseph
Published: May 2024

Whether its for expediting targeted drug delivery or more generally for the potential risk posed to health through exposure to contaminated environments, the internalization of nanoparticles by biological cells has been the subject of much experimental research. One particular experimental system involving a 2D cell culture exposed to a nanoparticle solution is here modelled mathematically with the goal of identifying both cell-specific and environment-specific properties that govern the rate of nanoparticle uptake and the capacity for internalization by cells. Three models are presented and compared with experimental data. The first model considered, previously used in the literature to analyze experimental measurements, is discounted for its unrealistic behaviour and lack of adequate representation of the cells. The predictions of the second and third models, not previously considered, compare favorably with experimental measurements. We find generally that the experimentally measured rates of uptake are foremost dictated by the manner of exposure: unidirectional diffusion toward the 2D cell culture. This rate is then modulated by cell-specific properties. The latter are here represented by cell size and two phenomenological parameters. We find that for 2D cultures of close-packed cells, the finite domain (per unit area) 1D model presented here is appropriate. For cells free in solution or 2D cell cultures distributed at low surface density, the 3D, isolated cell model is more appropriate.
Uncertainty Characterization in Contaminated Groundwater system Using Fuzzy Vertex Alpha-cut Technique
Authors: Srivast Divya , Singh Raj Mohan , verma Pushpanjali
Published: May 2024

Groundwater is a vital natural resource. Water from this source is used practically worldwide because of its economical price, easy access, reliability, and excellent quality. However, groundwater contamination might make it unsafe to use for agriculture, household, and drinking needs. To solve groundwater management issues, groundwater system modelling is a fundamental requirement. Adopting any cleanup technique requires the identification of undiscovered sources of pollution. The data required for the processes involved in developing Artificial Neural Networks (ANN) models is produced by a groundwater flow and transport simulation model. The concentration breakthrough curves are described by the suggested approach using statistical parameters such as skewness, kurtosis, maximum value, average value, and standard deviation. To identify the sources in terms of their location, magnitudes, and duration of activity, a feed-forward multilayer artificial neural network (ANN) is employed with the defined parameters. Test and training patterns are used in varying numbers during experiments. To determine the source fluxes of groundwater pollution, a developed methodology is illustrated using example problems. To solve the groundwater flow and transport simulation model, specific boundary conditions and input parameters may be needed. Uncertainty in one is understanding of the given data, or epistemic uncertainty, can result in imprecise input parameters via indirect measurements and subjective interpretation. Using the Fuzzy Vertex Method, the epistemic uncertainty in the flow parameters is characterized as a result of imperfect measurement of source flux and one of the flow parameters.
Stretchable, Transparent and Multifunctional PVC-gel Heater: A Novel Approach to Skin-Mountable, Wearable Thermal Devices.
Authors: Kyung Ki-Uk , Kim Minki , Cho Minjae , Chung Chongyoung
Published: May 2024

The electric heaters based on functional material and design have been developed to realize the various multifunctional applications. In this work, the functional heater consisting of polyvinyl chloride (PVC)-gel heater and hydrogel electrode, for the first time, is proposed, which exhibits high stretchability, transparency and capacity to generate diverse thermal patterns through spatially localized heating. The proposed heater is capable of generating the uniform temperature distribution at the heated area under extreme strains up to 400%. Besides, its transparency over 86% transmittance across the visible range renders it highly suitable for wearable or skin-mountable applications in an aesthetic viewpoint. Thanks to its localized heating ability, the proposed heater is capable of being extended to pixelated heater array which is row/column addressable and transfers diverse thermal pattern, while it is still stretchable and transparent, demonstrating 5 x 5 heater array. Various applications are demonstrated such as the skin-mountable thermo-haptic devices, wearable thermotherapy, and controlled thermal pattern generations, all of which show its superior mechanical, optical and thermal advantages. This innovative functional heater can expand the possibilities for transferring the thermal information and sensation integrated with visual cues in the next-generation skin-mountable and wearable electric heating devices.
From Pixels to Titles: Video Game Identification by Screenshots using Convolutional Neural Networks
Authors: Breve Fabricio
Published: May 2024

This paper investigates video game identification through single screenshots, utilizing five convolutional neural network (CNN) architectures (MobileNet, DenseNet, EfficientNetB0, EfficientNetB2, and EfficientNetB3) across 22 home console systems, spanning from Atari 2600 to PlayStation 5, totalling 8,796 games and 170,881 screenshots. Confirming the hypothesis, CNNs autonomously extract image features, enabling the identification of game titles from screenshots without additional features. Using ImageNet pre-trained weights as initial weights, EfficientNetB3 achieves the highest average accuracy (74.51\%), while DenseNet169 excels in 14 of the 22 systems. Employing alternative initial weights trained in an arcade screenshots dataset boosts accuracy for EfficientNetB2 and EfficientNetB3, with the latter reaching a peak accuracy of 76.36\% and demonstrating reduced convergence epochs from 23.7 to 20.5 on average. Overall, the combination of optimal architecture and weights attains 77.67\% accuracy, primarily led by EfficientNetB3 in 19 systems. These findings underscore the efficacy of CNNs in video game identification through screenshots.
Examination of the Impact of Curiosity and Fatigue on Brain Condition
Authors: YAN NI , Kokubun Keisuke , Nemoto Kiyotaka , Yamakawa Yoshinori
Published: May 2024

With a growing emphasis on cognitive well-being, this study investigates factors influencing brain health, measured by Fractional Anisotropy Brain Healthcare Quotient (FA-BHQ). We find a positive correlation between curiosity, assessed by the Curiosity and Exploration Inventory-II (CEI-II), and brain health as indicated by FA-BHQ. Conversely, fatigue, evaluated using the Chalder Fatigue Scale (CFS), demonstrates a negative correlation with brain health. Furthermore, curiosity and fatigue serve as significant mediators in the relationship between these factors and FA-BHQ, respectively. Specific brain regions, including the corpus callosum, internal capsule, fornix, and posterior thalamic radiation, show significant negative correlations with fatigue, while the corpus callosum, fornix, internal capsule, corona radiata, external capsule, cingulum, and posterior thalamic radiation exhibit significant positive correlations with curiosity. Notably, this study highlights that more brain regions exhibit significant correlations with curiosity compared to fatigue, shedding light on the growing recognition of curiosity's role in influencing brain health and emphasizing the importance of considering curiosity in the research on cognitive well-being.
Subtype-specific HERV-K102 envelope is a novel serum immunosuppressive biomarker and therapeutic target of cancer
Authors: Xu Rongzhen , Gong Qinyuan , Li Mengyuan , Zheng Shuwen , Wu Zhaoxing , Wang Ping , Zhang Xuzhao , Liang Yun , Qian Wenbin
Published: May 2024

Background: Immune dysfunction is a hallmark of cancer and plays critical roles in immunotherapy resistance, but there is no serum biomarker that can be used to evaluate immune-dysfunction status of cancer patients. Here, we identified subtype-specific HERV-K102 envelope (K102-Env) with immunosuppressive activity in circulating blood as a novel serum immunosuppressive biomarker of cancer.
Methods: We first generated monoclonal antibodies against K102-Env with high sensitivity and specificity, and we developed an ELISA assay for serum K102-Env. We then investigated whether K102-Env and K108-Env proteins are present in circulating blood of cancer patients.
Results: We detected K108-Env in 63.33% of patients with pancreatic duct adenocarcinoma (PDAC) (n = 30) and 63% of healthy sera (n = 30). In contrast, K102-Env markedly increased in patients with PDAC, hepatocellular carcinoma (HCC), and non-small cell lung cancer (NSCLC) compared with healthy controls (p < 0.01). The positive rates of K102-Env were 34.00%, 39%, and 28.0% in PDAC, HCC, and NSCLC, respectively, whereas only 5.0% of healthy individuals had marginally increased K102-Env. In patients with PDAC, K102-Env was 36.63-fold higher than in sera of healthy controls. K102-Env significantly upregulated PD-1/PD-L1 and c-Myc expression levels of T cells. Importantly, serum K102-Env levels correlated well with advanced cancers and tumor biomarkers CA19-9 and AFP.
Conclusion: These findings indicate that circulating K102-Env is a novel serum biomarker for evaluating immunosuppressive status and disease stage of patients with cancer, and it also provides a potential target for cancer immunotherapy.
Therapeutic Efficacy of Moxifloxacin and Marbofloxacin against Mastitis in Buffalo
Authors: Shelke AA , Siddiqui MFMF , Sakhare MP , Suryawanshi PR , Shaikh SR
Published: May 2024

The present research work was carried out to evaluate efficacy of moxifloxacin and marbofloxacin in clinical mastitis in buffaloes. Total 20 clinical mastitis positive buffaloes were selected after screening of 129 lactating buffaloes by strip cup test and clinical signs, in and around Parbhani area. The selected buffaloes were divided into 2 groups, 10 animals in each. Group I was treated with Inj. Moxifloxacin @ 5 mg/kg BW IM for 5 days and group II received Inj. Marbofloxacin @ 2 mg/kg BW IM for 5 days. Supportive treatment was given in both groups as antihistaminic, multivitamins and NSAIDs. The clinical parameters like rectal temperature, heart rate and respiratory rate showed significant improvement in both the treatment groups. Haematolgical studies showed significant improvement in TLC, neutrophil and lymphocyte count while apparent but non-significant improvement observed in Hb, PCV, basophil, eosinophil and monocyte count. On bacterial isolation, most frequent bacteria observed were Staphylococcus aureus (48.14%), followed by E. coli (25.92%), Klesiella spp. (14.81%) and mixed bacterial infection (11.11%). Results of antibiotic sensitivity test of samples showed sensitive to, in descending order, Marbofloxacin (70%), Moxifloxacin (50%), Enrofloxacin (60%) and Ciprofloxacin (50%). Efficacy of marbofloxacin @ 2 mg/kg BW IM for 5 days was more (70%) compared to moxifloxacin @ 5 mg/kg BW IM for 5 days (50%). Hence, marbofloxacin was found more effective than moxifloxacin for treatment and control of mastitis in buffalo.
Continuous-Transition-Mediated Deformation Twinning in Cubic Boron Nitride
Authors: Nie Anmin , Bu Yeqiang , Su Zhengping , Huang Junquan , Tong Ke , Li Penghui , Wang Chong , Jin Tianye , Zhao Song , Zhao Zhisheng , Soldatov Alexander , Wang Yanbin , Xu Bo , Liu Zhongyuan , Wang Hongtao , Yang Wei , Tian Yongjun
Published: May 2024

Deformation twinning, a phenomenon primarily documented within metallic systems, has remained essentially unexplored in covalent materials due to the formidable challenges posed by their inherent extreme hardness and brittleness. Utilizing our loading-specific twinning criterion, we have successfully activated extensive deformation twinning and quantified the consequent significant improvements in mechanical properties in < 100>-oriented cBN submicron pillars at room temperature, employing a five-degree-of-freedom nanomanipulation stage inside a transmission electron microscope. Extending beyond cBN, this criterion has also proven widely applicable across a spectrum of covalent materials, underscoring its broad potential. Building on the successful implementation of twinning, our investigations have unveiled the twinning dynamics at the atomic level in cBN. In contrast to metallic systems, the twinning observed in cBN is governed by a novel mechanism of continuous transitions involving the collective displacement of atoms beneath the (111) slip planes within the lattice. These findings substantially advance our comprehension of twinning mechanisms in covalent face-centered cubic materials, and herald a promising avenue for microstructural engineering aimed at enhancing the strength and toughness of these materials.
The Politics of Emotional Empathy: Partisanship, Trait Empathy, and Social Justice Concerns in a Representative Sample of Californians
Authors: Martinez Andres
Published: May 2024

In America’s hyper-polarized political landscape, is the fundamental problem an empathy gap (or deficit) across party categories? An analysis of a representative sample of Californians (N = 875) suggests that the answer is “no.” Although Democrats, Republicans, and Independents differed somewhat in average trait emotional empathy levels, the magnitudes of these differences were not large. Interestingly, analysis showed that (on average) all political affiliations are characterized by high levels of trait emotional empathy. However, the target of emotional empathy varied by party. Democrats’ and Independents’ empathic tendencies were linked to social justice concerns. In contrast, Republicans’ empathic tendencies were untethered from this domain. These findings provide evidence that—in California and perhaps beyond—emotional empathy is pronounced across the political spectrum. However, the targets of empathy differ by political affiliation. Discussion explores the implications of these findings for political polarization and cooperation across partisan categories.
Insights on Earthquake Nucleation Revealed by Numerical Simulation and Unsupervised Machine Learning of Laboratory-Scale Earthquake Nucleation
Authors: Ye William (Sheng Hua) , Lui Semechah , Young R. Paul
Published: May 2024

Understanding earthquake nucleation is vital for predicting and mitigating seismic events, saving lives, and enhancing construction practices in earthquake-prone areas. Cascade triggering and preslip triggering are prevalent theories, posing challenges in differentiation based on field observations. Our study employs a novel unsupervised machine learning pipeline, integrating macroscopic- and grain-scale data from stick-slip experiments in a discrete element method (DEM) framework. Running 27 simulations, we cluster foreshocks and mainshocks separately and assess their correlation. The study supports the cascade triggering model on the macro-scale, as we did not observe any scaling between nucleation parameters and the mainshock size. On the other hand, further grain-scale analysis identifies that, separate from Coulomb stress transfer, there is an additional mechanism related to shear stress accumulation on the fault, which is likely the preslip triggering. Overall, while foreshocks may not directly influence the trend at which contact force evolves, they could prime the fault for dynamic rupture by increasing the proportion of contacts accumulating shear stresses. Our findings infer the possible coexistence of the two theorized mechanisms.
Plant peptide hormone phytosulfokine promotes embryogenic development of calli in Pinus massoniana
Authors: Luo Qunfeng , Hu Shan , Deng Zhaolei , Gu Zhenjun , Liu Qian , zhou Guang , Du Qiang , Yang Chunxia
Published: May 2024

Pinus massoniana is a critical afforestation and ecological tree species in China. However, the continued existence of this pine is severely threatened by pine wilt disease. Somatic embryogenesis serves as a highly efficient clonal propagation approach. Although significant progress has been made in somatic embryogensis research on P.massoniana, resulting in the successful regeneration of plants, the limited embryogenic potential of improved cell lines and the loss of embryogenic properties resulting from prolonged proliferation have posed obstacles to the industrialization of SE production. Here, we investigated the effect of phytosulfokine on embryogenic development of cell lines from P. massoniana, and then leading to a cascade of physicochemical changes. Eight embryogenic cell lines of P. massoniana were used as research materials to observe phenotype and cytological changes. Physiological factors and the contents of nutrients and endogenous hormones were measured before and after phytosulfokine addition. We found that PSK promoted the embryogenic suspensor mass structure of embryogenic cell lines of P. massoniana. In addition, PSK accumulated soluble sugar, protein, and starch, and maintained redox homeostasis during the cell line proliferation process by reducing H2O2 levels. Further, endogenous hormone indole-3-acetic acid may be the main driver of the embryonic changes of cell lines. Our findings increase our understanding of how PSK affects somatic embryogensis in P. massoniana, thereby providing a valuable tool for establishing efficient somatic embryogensis systems in conifer species.
Discriminative Frontal Face Synthesis by Using Attention and Metric Learning
Authors: Cevikalp Hakan , Turgut Kaya , Topal Cihan
Published: May 2024

This paper introduces a novel approach for obtaining distinctive frontal facial representations from
collections of multiple facial images. The primary objective is to ensure that the profound features extracted
through a deep Convolutional Neural Network (CNN) from these learned facial representations exhibit notable separability
within the feature space. The acquisition of frontal facial representations capable of effectively representing entire
sets of images holds significant value as it considerably reduces the number of image samples requiring processing.
This acceleration proves especially advantageous during the classification testing phase.
The proposed method combines three fundamental components: attention mechanisms, adversarial methodologies, and metric learning strategies.
We adopt a U-Net architecture enhanced by attention modules for the facial aggregation network that generates frontal faces
that approximate multiple face images within image sets. Furthermore, we employ both a discriminator network and a pre-trained
facial classification network to successfully achieve the goals of adversarial and metric learning.
The experimental studies on different face recognition datasets demonstrate that using only attention mechanisms
and metric learning strategy is sufficient to synthesize discriminative frontal face images yielding high classification accuracies.
Bayesian Prediction of Afghanistan Annual Population Growth Using ARIMA and BSTS Models
Authors: Haqbin Sayed Rahmi Khuda , Khan Athar Ali
Published: May 2024

This study analyzes Afghanistan’s annual population growth using historical time series data from 1950 to 2022. The objectives are modeling, comparison, and prediction. Two models are employed: the auto-regressive integrated moving average (ARIMA) and the Bayesian Structural Time Series (BSTS). These models are fitted to the data, and their accuracy is evaluated using the Leave-One-Out Information Criteria (LOOIC), a Bayesian model selection criterion. The ARIMA(2,1,2) model is identified as suitable based on its minimum LOOIC value. The analysis is conducted using R statistical software and Stan proba-bilistic programming language for Bayesian modeling. The model comparison indicates the ARIMA model outperforms the BSTS model for this population growth data, exhibiting lower LOOIC values, suggesting better model fit and pre-dictive ability. The key result is a next-decade prediction of annual population growth from 2023 to 2032, generated using the preferred ARIMA(2,1,2) model. This model is deemed most appropriate for forecasting Afghanistan’s population growth, as evidenced by its superior performance on the LOOIC evaluation metric. The study demonstrates the effectiveness of the ARIMA model in capturing population growth dynamics and providing accurate forecasts for the upcoming decade.
Printing of Fine, Continuous, and Soft Fibers in Complex 3D Trajectories via Embedded Solvent Exchange
Authors: Tawfick Sameh , Eom Wonsiik , Hossain Mohammad Tanver , Parasramka Vidush , Kim Jeongmin , Siu Ryan , Sanders Kate , Piorkowski Dakota , Lowe Andrew , Koh Hyun Gi , De Volder Michael , Fudge Douglas , Ewoldt Randy
Published: May 2024

Nature uses hairy and fibrous structures for sensing and structural functions as observed in beetle hairs, mammalian whiskers, ear stereocilia, spider silks, and hagfish slime thread skeins. However, replicating these intricate, thin, high aspect ratio geometries has been a longstanding manufacturing challenge. It is currently not possible to fabricate 3D fibrous structures with microscale diameters and centimeter lengths. Here, we demonstrate 3D printing of fine hair having freeform trajectories and substrate fixation, with fiber diameters as fine as 1.5 µm and continuous length. This is realized via 3D printing by solvent exchange (3DPX), where the nozzle is embedded in a bath of microgranular gel. The yield stress rheology of the bath material allows the free-form placement of the fibers with bioinspired trajectories. The solvent exchange induces rapid radial solidification of the extruded polymer solutions at a rate of 2.33 µm/s, resulting in an elastic plateau modulus increase by four orders of magnitude, which prevents capillarity-induced fiber breakage. Furthermore, 3DPX offers unparalleled versatility in material selection, including the ability to print with commercially available thermoplastic polymers and nanocomposite materials. This study introduces and demonstrates the potential of 3DPX in replicating natural fibrous structures and paving the way for applications in biomimetic functions.
Numerical model of N-level cascade systems for atomic RF sensing applications
Authors: Bussey Liam , Kale Yogeshwar , Winter Samuel , Burton Fraser , Lien Yu-Hung , Bongs Kai , Costantinou Costas
Published: May 2024

The numerical model has been developed for atomic ladder (cascade) systems, which proves to be suitable for Rydberg RF sensors.This model is designed with the capability to be extended to N-level non-thermal atomic systems with ease. The adaptability of this model to Rydberg RF sensors is validated by comparing its results with those of earlier reported experiments. The numerical model here provides a good approximation to the experimental results. Thus, such a dynamic model can be useful for quantum technologists in designing, optimising, and developing the Rydberg RF-based sensors in a user-friendly manner.
Optimal Decentralized PI Control Design for a TimeDelay Benchmark Process Control System : AModified Whale Optimization Algorithm Approach
Authors: Mahapatro Soumya ranjan , Khadanga Rajendra Kumar , Das Mangal
Published: May 2024

This paper presents a new optimal decentralized PIcontroller design based on a modified hybrid whale optimization approach that is addressed for a typical industrial benchmark process control device. This research work determines the gain parameters of the PID controllers using the modified whale optimization algorithm (mWOA), aiming to achieve efficient performance by taking into account the integral time absolute error (ITAE) cost function. Further, the stability and performance of the proposed controller are verified by considering multiplicative input and output uncertainty. A comparison has beenmade between the performance of the proposed decentralized control method and a traditional decentralized PID controllerarchitecture. The obtained results highlight that the proposedcontroller exhibits superior control performance in inevitablepractical scenarios, such as in the face of additive stochasticuncertainties and load perturbation.
Rapid trajectory planning under multiple constraints in unknown environment
Authors: Xu Chenghong , Qi Wenjie , Zhang Zhigang , Ge Shuaishuai , Cheng Junjie , Zhang Xiangkui , Wang Guojian , Peng Fei
Published: May 2024

In this work, we propose a rapid trajectory planning method based on robotic kinematic constraints, specifically applied to ground-based robot navigation in unknown environments. We address this by formulating a Quadratically Constrained Quadratic Program problem, integrating third-order polynomials and multiple motion states to generate trajectories while considering kinematic constraints. The solutions derived from this method are utilized in initial path point generation. Leveraging the geometric properties of convex decomposition enables path point corrections, while employing Bézier curves enhances trajectory smoothness. We introduce a novel replanning framework encompassing local waypoint generation, trajectory collision detection, and replanning strategies. The viability and effectiveness of our method are demonstrated through simulations and real-world experiments.