bluuebunny/crossref_metadata_2025 huggingface dataset:
A semantic segmentation scheme for night driving improved by irregular convolution
Authors: Xuantao Yang , Junying Han , Chenzhong Liu
Published: June 2023

In order to solve the poor performance of real-time semantic segmentation of night road conditions in video images due to insufficient light and motion blur, this study proposes a scheme: a fuzzy information complementation strategy based on generative models and a network that fuses different intermediate layer outputs to complement spatial semantics which also embeds irregular convolutional attention modules for fine extraction of motion target boundaries. First, DeblurGan is used to generate information to fix the lost semantics in the original image; then, the outputs of different intermediate layers are taken out, assigned different weight scaling factors, and fused; finally, the irregular convolutional attention with the best effect is selected. The scheme achieves Global Accuracy of 89.1% Mean and IOU 94.2% on the night driving dataset of this experiment, which exceeds the best performance of DeepLabv3 by 1.3 and 7.2%, and achieves an Accuracy of 83.0% on the small volume label (Moveable). The experimental results demonstrate that the solution can effectively cope with various problems faced by night driving and enhance the model's perception. It also provides a technical reference for the semantic segmentation problem of vehicles driving in the nighttime environment.
EEG and peripheral markers of viewer ratings: a study of short films
Authors: Kosonogov Vladimir , Shelepenkov Danila , Rudenkiy Nikita
Published: June 2023

Introduction

Cinema is an important part of modern culture, influencing millions of viewers. Research suggested many models for the prediction of film success, one of them being the use of neuroscientific tools. The aim of our study was to find physiological markers of viewer perception and correlate them to short film ratings given by our subjects. Short films are used as a test case for directors and screenwriters and can be created to raise funding for future projects; however, they have not been studied properly with physiological methods.

Methods

We recorded electroencephalography (18 sensors), facial electromyography (corrugator superciliiandzygomaticus major), photoplethysmography, and skin conductance in 21 participants while watching and evaluating 8 short films (4 dramas and 4 comedies). Also, we used machine learning (CatBoost, SVR) to predict the exact rating of each film (from 1 to 10), based on all physiological indicators. In addition, we classified each film as low or high rated by our subjects (with Logistic Regression, KNN, decision tree, CatBoost, and SVC).

Results

The results showed that ratings did not differ between genres.Corrugator superciliiactivity (“frowning” muscle) was larger when watching dramas; whereaszygomaticus major(“smiling” muscle) activity was larger during the watching of comedies. Of all somatic and vegetative markers, onlyzygomaticus majoractivity, PNN50, SD1/SD2 (heart rate variability parameters) positively correlated to the film ratings. The EEG engagement indices, beta/(alpha+theta) and beta/alpha correlated positively with the film ratings in the majority of sensors. Arousal (betaF3+ betaF4)/(alphaF3+ alphaF4), and valence (alphaF4/betaF4) - (alphaF3/betaF3) indices also correlated positively to film ratings. When we attempted to predict exact ratings, MAPE was 0.55. As for the binary classification, logistic regression yielded the best values (area under the ROC curve = 0.62) than other methods (0.51–0.60).

Discussion

Overall, we revealed EEG and peripheral markers, which reflect viewer ratings and can predict them to a certain extent. In general, high film ratings can reflect a fusion of high arousal and different valence, positive valence being more important. These findings broaden our knowledge about the physiological basis of viewer perception and can be potentially used at the stage of film production.
Spike-frequency adaptation inhibits the pairwise spike correlation
Authors: Wang Jixuan , Deng Bin , Gao Tianshi , Wang Jiang , Tan Hong
Published: June 2023

Introduction

The spike train output correlation with pairwise neurons determines the neural population coding, which depends on the average firing rate of individual neurons. Spike frequency adaptation (SFA), which serves as an essential cellular encoding strategy, modulates the firing rates of individual neurons. However, the mechanism by which the SFA modulates the output correlation of the spike trains remains unclear.

Methods

We introduce a pairwise neuron model that receives correlated inputs to generate spike trains, and the output correlation is qualified using Pearson correlation coefficient. The SFA is modeled using adaptation currents to examine its effect on the output correlation. Moreover, we use dynamic thresholds to explore the effect of SFA on output correlation. Furthermore, a simple phenomenological neuron model with a threshold-linear transfer function is utilized to confirm the effect of SFA on decreasing the output correlation.

Results

The results show that the adaptation currents decreased the output correlation by reducing the firing rate of a single neuron. At the onset of a correlated input, a transient process shows a decrease in interspike intervals (ISIs), resulting in a temporary increase in the correlation. When the adaptation current is sufficiently activated, the correlation reached a steady state, and the ISIs are maintained at higher values. The enhanced adaptation current achieved by increasing the adaptation conductance further reduces the pairwise correlation. While the time and slide windows influence the correlation, they make no difference in the effect of SFA on decreasing the output correlation. Moreover, SFA simulated by dynamic thresholds also decreases the output correlation. Furthermore, the simple phenomenological neuron model with a threshold-linear transfer function confirms the effect of SFA on decreasing the output correlation. The strength of the signal input and the slope of the linear component of the transfer function, the latter of which can be decreased by SFA, could together modulate the strength of the output correlation. Stronger SFA will decrease the slope and hence decrease the output correlation.

Conclusions

The results reveal that the SFA reduces the output correlation with pairwise neurons in the network by reducing the firing rate of individual neurons. This study provides a link between cellular non-linear mechanisms and network coding strategies.
Case report: Improvement in refractory functional seizures, depression, and quality of life with ketamine-assisted therapy
Authors: Argento Elena , Omene Egiroh , Jaeger Alexandria H. , Kertes Angela , Mitchell Kaitlyn A. , Necyk Candace , Thielking Paul , Lewis Evan Cole
Published: June 2023

Functional seizures, a primary subtype of functional neurological disorder (FND), are a known cause of serious neurological disability with an increasing awareness of their impact amongst the neuroscience community. Situated at the intersection of neurology and psychiatry, FND is characterized by a range of alterations in motor, sensory or cognitive performance, such as abnormal movements, limb weakness, and dissociative, seizure-like episodes. Functional seizures are known, in part, to have psychological underpinnings; however, the lack of effective and consistent treatment options requires research and novel approaches to better understand the etiology, diagnosis and what constitutes a successful intervention. Ketamine, a selective blocker of the N-methyl-D-aspartate receptor, has a well-established safety and efficacy profile. In recent years, ketamine-assisted therapy has shown increasing potential for treating a broad range of psychiatric conditions, building on its demonstrated rapid-acting antidepressant effects. Here we present a 51-year-old female with refractory daily functional seizures leading to significant disability and a medical history significant for major depressive disorder (MDD) and posttraumatic stress disorder (PTSD). After unsuccessful treatment attempts, the patient underwent a novel protocol with ketamine-assisted therapy. After 3 weeks of ketamine-assisted therapy followed by 20 weeks of intermittent ketamine treatment and ongoing integrative psychotherapy, the patient’s seizures were significantly reduced in frequency and severity. She experienced significant improvements in depressive symptoms and functional ability scores. To our knowledge, this is the first reported case describing improvement in functional seizures following ketamine-assisted therapy. While rigorous studies are needed, this case report encourages further investigation of ketamine-assisted therapy for functional seizures and other functional neurological symptoms.
Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival
Authors: Li Hui , Wu Zixuan , Zhang Yu , Lu Xiaohui , Miao Lili
Published: June 2023

Background

Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.

Methods

GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.

Results

GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.

Conclusion

GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.
Zika virus-like particles (VLPs) produced in insect cells
Authors: de Mello Renata Gois , Bernardino Thaissa Consoni , Guardalini Luis Giovani Oliveira , Astray Renato Mancini , Antoniazzi Marta Maria , Jared Simone Gonçalves Silva , Núñez Eutimio Gustavo Fernández , Jorge Soraia Attie Calil
Published: June 2023

Introdutcion: The Zika virus (ZIKV) infections are a healthcare concern mostly in the Americas, Africa, and Asia but have increased its endemicity area beyond these geographical regions. Due to the advances in infections by Zika virus, it is imperative to develop diagnostic and preventive tools against this viral agent. Virus-like particles (VLPs) appear as a suitable approach for use as antiviral vaccines.

Methods: In this work, a methodology was established to produce virus-like particles containing the structural proteins, C, prM, and E of Zika virus produced in insect cells using the gene expression system derived from baculovirus. The vector pFast- CprME -ZIKV was constructed containing the gene sequences of Zika virus structural proteins and it was used to generate the recombinant bacmids (Bac- CprME -ZIKV) through transformation into DH10BacTM cells. The Bac- CprME -ZIKV was transfected in Spodoptera frugiperda (Sf9) insect cells and batches of BV- CprME -ZIKV were obtained by infection assays using a multiplicity of infection of 2. The Sf9 cells were infected, and the supernatant was collected 96 h post-infection. The expression of the CprME -ZIKV protein on the cell surface could be observed by immunochemical assays. To concentrate and purify virus-like particles, the sucrose and iodixanol gradients were evaluated, and the correct CprME -ZIKV proteins’ conformation was evaluated by the Western blot assay. The virus-like particles were also analyzed and characterized by transmission electron microscopy.

Results and discussion: Spherical structures like the native Zika virus from 50 to 65 nm containing the CprME -ZIKV proteins on their surface were observed in micrographs. The results obtained can be useful in the development path for a vaccine candidate against Zika virus.
Metabolic changes in the plasma of mild Alzheimer’s disease patients treated with Hachimijiogan
Authors: Kainuma Mosaburo , Kawakatsu Shinobu , Kim Jun-Dal , Ouma Shinji , Iritani Osamu , Yamashita Ken-Ichiro , Ohara Tomoyuki , Hirano Shigeki , Suda Shiro , Hamano Tadanori , Hieda Sotaro , Yasui Masaaki , Yoshiiwa Aoi , Shiota Seiji , Hironishi Masaya , Wada-Isoe Kenji , Sasabayashi Daiki , Yamasaki Sho , Murata Masayuki , Funakoshi Kouta , Hayashi Kouji , Shirafuji Norimichi , Sasaki Hirohito , Kajimoto Yoshinori , Mori Yukiko , Suzuki Michio , Ito Hidefumi , Ono Kenjiro , Tsuboi Yoshio
Published: June 2023

Background: Alzheimer’s disease (AD), the most prevalent form of dementia, is a debilitating, progressive neurodegeneration. Amino acids play a wide variety of physiological and pathophysiological roles in the nervous system, and their levels and disorders related to their synthesis have been related to cognitive impairment, the core feature of AD. Our previous multicenter trial showed that hachimijiogan (HJG), a traditional Japanese herbal medicine (Kampo), has an adjuvant effect for Acetylcholine estelase inhibitors (AChEIs) and that it delays the deterioration of the cognitive dysfunction of female patients with mild AD. However, there are aspects of the molecular mechanism(s) by which HJG improves cognitive dysfunction that remain unclear.

Objectives: To elucidate through metabolomic analysis the mechanism(s) of HJG for mild AD based on changes in plasma metabolites.

Methods: Sixty-seven patients with mild AD were randomly assigned to either an HJG group taking HJG extract 7.5 g/day in addition to AChEI or to a control group treated only with AChEI (HJG:33, Control:34). Blood samples were collected before, 3 months, and 6 months after the first drug administration. Comprehensive metabolomic analyses of plasma samples were done by optimized LC-MS/MS and GC-MS/MS methods. The web-based software MetaboAnalyst 5.0 was used for partial least square-discriminant analysis (PLS-DA) to visualize and compare the dynamics of changes in the concentrations of the identified metabolites.

Results: The VIP (Variable Importance in Projection) score of the PLS-DA analysis of female participants revealed a significantly higher increase in plasma metabolite levels after HJG administration for 6 months than was seen in the control group. In univariate analysis, the aspartic acid level of female participants showed a significantly higher increase from baseline after HJG administration for 6 months when compared with the control group.

Conclusion: Aspartic acid was a major contributor to the difference between the female HJG and control group participants of this study. Several metabolites were shown to be related to the mechanism of HJG effectiveness for mild AD.
Root and branch hydraulic functioning and trait coordination across organs in drought-deciduous and evergreen tree species of a subtropical highland forest
Authors: Schönauer Marian , Hietz Peter , Schuldt Bernhard , Rewald Boris
Published: June 2023

Vessel traits are key in understanding trees’ hydraulic efficiency, and related characteristics like growth performance and drought tolerance. While most plant hydraulic studies have focused on aboveground organs, our understanding of root hydraulic functioning and trait coordination across organs remains limited. Furthermore, studies from seasonally dry (sub-)tropical ecosystems and mountain forests are virtually lacking and uncertainties remain regarding potentially different hydraulic strategies of plants differing in leaf habit. Here, we compared wood anatomical traits and specific hydraulic conductivities between coarse roots and small branches of five drought-deciduous and eight evergreen angiosperm tree species in a seasonally dry subtropical Afromontane forest in Ethiopia. We hypothesized that largest vessels and highest hydraulic conductivities are found in roots, with greater vessel tapering between roots and equally-sized branches in evergreen angiosperms due to their drought-tolerating strategy. We further hypothesized that the hydraulic efficiencies of root and branches cannot be predicted from wood density, but that wood densities across organs are generally related. Root-to-branch ratios of conduit diameters varied between 0.8 and 2.8, indicating considerable differences in tapering from coarse roots to small branches. While deciduous trees showed larger branch xylem vessels compared to evergreen angiosperms, root-to-branch ratios were highly variable within both leaf habit types, and evergreen species did not show a more pronounced degree of tapering. Empirically determined hydraulic conductivity and corresponding root-to-branch ratios were similar between both leaf habit types. Wood density of angiosperm roots was negatively related to hydraulic efficiency and vessel dimensions; weaker relationships were found in branches. Wood density of small branches was neither related to stem nor coarse root wood densities. We conclude that in seasonally dry subtropical forests, similar-sized coarse roots hold larger xylem vessels than small branches, but the degree of tapering from roots to branches is highly variable. Our results indicate that leaf habit does not necessarily influence the relationship between coarse root and branch hydraulic traits. However, larger conduits in branches and a low carbon investment in less dense wood may be a prerequisite for high growth rates of drought-deciduous trees during their shortened growing season. The correlation of stem and root wood densities with root hydraulic traits but not branch wood points toward large trade-offs in branch xylem towards mechanical properties.
Defence-related metabolic changes in wheat (Triticum aestivum L.) seedlings in response to infection by Puccinia graminis f. sp. tritici
Authors: Maserumule Mercy , Rauwane Molemi , Madala Ntakadzeni E. , Ncube Efficient , Figlan Sandiswa
Published: June 2023

Stem rust caused by the pathogen Puccinia graminis f. sp. tritici is a destructive fungal disease-causing major grain yield losses in wheat. Therefore, understanding the plant defence regulation and function in response to the pathogen attack is required. As such, an untargeted LC-MS-based metabolomics approach was employed as a tool to dissect and understand the biochemical responses of Koonap (resistant) and Morocco (susceptible) wheat varieties infected with two different races of P. graminis (2SA88 [TTKSF] and 2SA107 [PTKST]). Data was generated from the infected and non-infected control plants harvested at 14- and 21- days post-inoculation (dpi), with 3 biological replicates per sample under a controlled environment. Chemo-metric tools such as principal component analysis (PCA), orthogonal projection to latent structures-discriminant analysis (OPLS-DA) were used to highlight the metabolic changes using LC-MS data of the methanolic extracts generated from the two wheat varieties. Molecular networking in Global Natural Product Social (GNPS) was further used to analyse biological networks between the perturbed metabolites. PCA and OPLS-DA analysis showed cluster separations between the varieties, infection races and the time-points. Distinct biochemical changes were also observed between the races and time-points. Metabolites were identified and classified using base peak intensities (BPI) and single ion extracted chromatograms from samples, and the most affected metabolites included flavonoids, carboxylic acids and alkaloids. Network analysis also showed high expression of metabolites from thiamine and glyoxylate, such as flavonoid glycosides, suggesting multi-faceted defence response strategy by understudied wheat varieties towards P. graminis pathogen infection. Overall, the study provided the insights of the biochemical changes in the expression of wheat metabolites in response to stem rust infection.
Involvement of CBF in the fine-tuning of litchi flowering time and cold and drought stresses
Authors: Shan Xiaozhen , Yang Yun , Wei Shuoqi , Wang Chao , Shen Weishi , Chen Hou-bin , Shen Ji-yuan
Published: June 2023

Litchi (Litchi chinensis) is an economically important fruit tree in southern China and is widely cultivated in subtropical regions. However, irregular flowering attributed to inadequate floral induction leads to a seriously fluctuating bearing. Litchi floral initiation is largely determined by cold temperatures, whereas the underlying molecular mechanisms have yet to be identified. In this study, we identified fourCRT/DRE BINDING FACTORS(CBF) homologs in litchi, of whichLcCBF1,LcCBF2andLcCBF3showed a decrease in response to the floral inductive cold. A similar expression pattern was observed for theMOTHER OF FT AND TFL1homolog (LcMFT) in litchi. Furthermore, both LcCBF2 and LcCBF3 were found to bind to the promoter ofLcMFTto activate its expression, as indicated by the analysis of yeast-one-hybrid (Y1H), electrophoretic mobility shift assays (EMSA), and dual luciferase complementation assays. Ectopic overexpression ofLcCBF2andLcCBF3inArabidopsiscaused delayed flowering and increased freezing and drought tolerance, whereas overexpression ofLcMFTinArabidopsishad no significant effect on flowering time. Taken together, we identified LcCBF2 and LcCBF3 as upstream activators ofLcMFTand proposed the contribution of the cold-responsive CBF to the fine-tuning of flowering time.
Recent progress on the microbial mitigation of heavy metal stress in soybean: overview and implications
Authors: Shaffique Shifa , Hussain Saddam , Kang Sang-Mo , Imran Muhammad , Kwon Eun-Hae , Khan Muhammad Aaqil , Lee In-Jung
Published: June 2023

Plants are adapted to defend themselves through programming, reprogramming, and stress tolerance against numerous environmental stresses, including heavy metal toxicity. Heavy metal stress is a kind of abiotic stress that continuously reduces various crops’ productivity, including soybeans. Beneficial microbes play an essential role in improving plant productivity as well as mitigating abiotic stress. The simultaneous effect of abiotic stress from heavy metals on soybeans is rarely explored. Moreover, reducing metal contamination in soybean seeds through a sustainable approach is extremely needed. The present article describes the initiation of heavy metal tolerance mediated by plant inoculation with endophytes and plant growth-promoting rhizobacteria, the identification of plant transduction pathways via sensing annotation, and contemporary changes from molecular to genomics. The results suggest that the inoculation of beneficial microbes plays a significant role in rescuing soybeans under heavy metal stress. They create a dynamic, complex interaction with plants via a cascade called plant–microbial interaction. It enhances stress metal tolerance via the production of phytohormones, gene expression, and secondary metabolites. Overall, microbial inoculation is essential in mediating plant protection responses to heavy metal stress produced by a fluctuating climate.
Genetic dissection of protein and starch during wheat grain development using QTL mapping and GWAS
Authors: Guo Yingxin , Wang Guanying , Guo Xin , Chi Songqi , Yu Hui , Jin Kaituo , Huang Heting , Wang Dehua , Wu Chongning , Tian Jichun , Chen Jiansheng , Bao Yinguang , Zhang Weidong , Deng Zhiying
Published: June 2023

Protein, starch, and their components are important for wheat grain yield and end-products, which are affected by wheat grain development. Therefore, QTL mapping and a genome-wide association study (GWAS) of grain protein content (GPC), glutenin macropolymer content (GMP), amylopectin content (GApC), and amylose content (GAsC) were performed on wheat grain development at 7, 14, 21, and 28 days after anthesis (DAA) in two environments using a recombinant inbred line (RIL) population of 256 stable lines and a panel of 205 wheat accessions. A total of 29 unconditional QTLs, 13 conditional QTLs, 99 unconditional marker−trait associations (MTAs), and 14 conditional MTAs significantly associated (p < 10−4) with four quality traits were found to be distributed on 15 chromosomes, with the phenotypic variation explained (PVE) ranging from 5.35% to 39.86%. Among these genomic variations, three major QTLs [QGPC3B, QGPC2A, and QGPC(S3|S2)3B] and SNP clusters on the 3A and 6B chromosomes were detected for GPC, and the SNP TA005876-0602 was stably expressed during the three periods in the natural population. The QGMP3B locus was detected five times in three developmental stages in two environments with 5.89%–33.62% PVE, and SNP clusters for GMP content were found on the 3A and 3B chromosomes. For GApC, the QGApC3B.1 locus had the highest PVE of 25.69%, and SNP clusters were found on chromosomes 4A, 4B, 5B, 6B, and 7B. Four major QTLs of GAsC were detected at 21 and 28 DAA. Most interestingly, both QTL mapping and GWAS analysis indicated that four chromosomes (3B, 4A, 6B, and 7A) were mainly involved in the development of protein, GMP, amylopectin, and amylose synthesis. Of these, the wPt-5870–wPt-3620 marker interval on chromosome 3B seemed to be most important because it played an important role in the synthesis of GMP and amylopectin before 7 DAA, in the synthesis of protein and GMP from 14 to 21 DAA, and in the development of GApC and GAsC from 21 to 28 DAA. Using the annotation information of IWGSC Chinese Spring RefSeq v1.1 genome assembly, we predicted 28 and 69 candidate genes for major loci from QTL mapping and GWAS, respectively. Most of them have multiple effects on protein and starch synthesis during grain development. These results provide new insights and information for the potential regulatory network between grain protein and starch synthesis.
Tobamovirus infection aggravates gray mold disease caused by Botrytis cinerea by manipulating the salicylic acid pathway in tomato
Authors: Gupta Rupali , Leibman-Markus Meirav , Weiss Daniela , Spiegelman Ziv , Bar Maya
Published: June 2023

Botrytis cinerea is the causative agent of gray mold disease, and infects more than 1400 plant species, including important crop plants. In tomato, B. cinerea causes severe damage in greenhouses and post-harvest storage and transport. Plant viruses of the Tobamovirus genus cause significant damage to various crop species. In recent years, the tobamovirus tomato brown rugose fruit virus (ToBRFV) has significantly affected the global tomato industry. Most studies of plant-microbe interactions focus on the interaction between the plant host and a single pathogen, however, in agricultural or natural environments, plants are routinely exposed to multiple pathogens. Here, we examined how preceding tobamovirus infection affects the response of tomato to subsequent infection by B. cinerea. We found that infection with the tobamoviruses tomato mosaic virus (ToMV) or ToBRFV resulted in increased susceptibility to B. cinerea. Analysis of the immune response of tobamovirus-infected plants revealed hyper-accumulation of endogenous salicylic acid (SA), upregulation of SA-responsive transcripts, and activation of SA-mediated immunity. Deficiency in SA biosynthesis decreased tobamovirus-mediated susceptibility to B. cinerea, while exogenous application of SA enhanced B. cinerea symptoms. These results suggest that tobamovirus-mediated accumulation of SA increases the plants’ susceptibility to B. cinerea, and provide evidence for a new risk caused by tobamovirus infection in agriculture.
Functional near-infrared spectroscopy of medical students answering various item types
Authors: Husain Syeda Fabeha , Wang Nixi , McIntyre Roger S. , Tran Bach X. , Nguyen Thao Phuong , Vu Linh Gia , Vu Giang Thu , Ho Roger C. , Ho Cyrus S.
Published: June 2023

Background

Traditionally, the effect of assessment item types including true/false questions (TFQs), multiple-choice questions (MCQs), short answer questions (SAQs), and case scenario questions (CSQs) is examined through psychometric qualities or student interviews. However, brain activity while answering such questions or items remains unknown. Functional near-infrared spectroscopy (fNIRS) can be used to safely measure cerebral cortex hemodynamic response during various tasks. Hence, this fNIRS study aimed to determine differences in frontotemporal cortex activity as medical students answered TFQs, MCQs, SAQs, and CSQs.

Methods

In total, 24 medical students (13 males and 11 females) were recruited in this study during their mid-psychiatry posting. Oxy-hemoglobin and deoxy-hemoglobin levels in the frontal and temporal regions were measured with a 52-channel fNIRS system. Participants answered 9–18 trials under each of the four types of tasks that were based on their psychiatry curriculum during fNIRS measurements. The area under the oxy-hemoglobin curve (AUC) for each participant and each item type was derived. Repeated measures ANOVA with post-hoc Bonferroni-corrected pairwise comparisons were used to determine differences in oxy-hemoglobin AUC between TFQs, MCQs, SAQs, and CSQs.

Results

Oxy-hemoglobin AUC was highest during the CSQs, followed by SAQs, MCQs, and TFQs in both the frontal and temporal regions. Statistically significant differences between different types of items were observed in oxy-hemoglobin AUC of the frontal region (p ≤ 0.001). Oxy-hemoglobin AUC in the frontal region was significantly higher during the CSQs than TFQ (p = 0.005) and during the SAQ than TFQ (p = 0.025). Although the percentage of correct responses was significantly lower in MCQ than in the other item types, there was no correlation between the percentage of correct response and oxy-hemoglobin AUC in both regions for all four item types (p > 0.05).

Conclusion

CSQs and SAQs elicited greater hemodynamic response than MCQs and TFQs in the prefrontal cortex of medical students. This suggests that more cognitive skills may be required to answer CSQs and SAQs.
Direct and indirect effects of self-directed learning on creativity in healthcare undergraduates: a chain mediation model of openness to challenge and diversity and creative self-efficacy
Authors: Qian Jiazhen , Li Xiang , Liu Ting , Zhang Mengfan , Li Kaiyan
Published: June 2023

Background

Creativity and self-directed learning (SDL) are prominent for undergraduate healthcare students to provide quality patient care in an increasingly complex healthcare environment. Research suggested that SDL is linked with creativity, yet the mechanism underlying the relationship between SDL and creativity has not been fully understood.

Objective

This study examined the relationship between SDL and creativity and constructed a chain mediation model to identify the mediating effect of openness to diversity and challenge (ODC) and creative self-efficacy (CSE).

Methods

Through convenience sampling, 575 healthcare undergraduates (average age = 19.28 years, SD = 1.124 years) were surveyed from Shandong Province in China. Creativity, SDL, ODC, and CSE were assessed using corresponding scales. Pearson’s correlation analysis, hierarchical multiple linear regression analysis, a serial multiple mediation analysis, and bias-corrected percentile Bootstrap method were conducted by using structural equation modeling by AMOS 26.0.

Results

The direct path between SDL and creativity was significant. SDL can positively predict both ODC and CSE, and the latter two variables can significantly and positively predict creativity. ODC and CSE played a significant partial mediating role in the relationship between SDL and creativity. The mediating effect consists of three indirect effects: SDL → ODC → creativity (the mediating effect value is 0.193, p = 0.012), SDL → CSE → creativity (the mediating effect value is 0.096，p = 0.001), and SDL → ODC → CSE → creativity (the mediating effect value is 0.035, p = 0.031).

Conclusion

SDL can positively predict creativity. ODC and CSE had significant mediating effects between SDL and creativity, including single partial mediating effects of ODC and CSE and chain mediating effects of ODC-CSE.
Teachers’ views on the effect of STEM education on the labor market
Authors: Akcan Ahmet Tayfur , Yıldırım Bekir , Karataş Ali Rauf , Yılmaz Mustafa
Published: June 2023

Introduction

This paper explores teachers’ views on the impact of STEM education on the labor market. This study focused on teachers’ views to investigate STEM education and the labor market and the relationship between the two.

Methods

The sample consisted of 32 teachers from different branches. Participants were recruited using purposive convenience sampling. This paper adopted a qualitative case study research design. Qualitative data were collected using a semi-structured interview form. The qualitative data were analyzed using inductive content and descriptive analysis.

Results

Participants stated that STEM education offered new fields of work, promoted entrepreneurship, and increased job opportunities. They also noted that STEM education helped reduce social costs. They emphasized that STEM education made participants happy, prevented brain drain, and reduced social problems. On the other hand, they also noted that STEM education could lead to technological unemployment. The descriptive analyses showed that STEM education had a positive impact on employment, a reduction in social costs, and a positive impact on underemployment. In light of the results, we made recommendations for future research.
Virtually screening adults for depression, anxiety, and suicide risk using machine learning and language from an open-ended interview
Authors: Wright-Berryman Jennifer , Cohen Joshua , Haq Allie , Black David P. , Pease James L.
Published: June 2023

Background

Current depression, anxiety, and suicide screening techniques rely on retrospective patient reported symptoms to standardized scales. A qualitative approach to screening combined with the innovation of natural language processing (NLP) and machine learning (ML) methods have shown promise to enhance person-centeredness while detecting depression, anxiety, and suicide risk from in-the-moment patient language derived from an open-ended brief interview.

Objective

To evaluate the performance of NLP/ML models to identify depression, anxiety, and suicide risk from a single 5–10-min semi-structured interview with a large, national sample.

Method

Two thousand four hundred sixteen interviews were conducted with 1,433 participants over a teleconference platform, with 861 (35.6%), 863 (35.7%), and 838 (34.7%) sessions screening positive for depression, anxiety, and suicide risk, respectively. Participants completed an interview over a teleconference platform to collect language about the participants’ feelings and emotional state. Logistic regression (LR), support vector machine (SVM), and extreme gradient boosting (XGB) models were trained for each condition using term frequency-inverse document frequency features from the participants’ language. Models were primarily evaluated with the area under the receiver operating characteristic curve (AUC).

Results

The best discriminative ability was found when identifying depression with an SVM model (AUC = 0.77; 95% CI = 0.75–0.79), followed by anxiety with an LR model (AUC = 0.74; 95% CI = 0.72–0.76), and an SVM for suicide risk (AUC = 0.70; 95% CI = 0.68–0.72). Model performance was generally best with more severe depression, anxiety, or suicide risk. Performance improved when individuals with lifetime but no suicide risk in the past 3 months were considered controls.

Conclusion

It is feasible to use a virtual platform to simultaneously screen for depression, anxiety, and suicide risk using a 5-to-10-min interview. The NLP/ML models performed with good discrimination in the identification of depression, anxiety, and suicide risk. Although the utility of suicide risk classification in clinical settings is still undetermined and suicide risk classification had the lowest performance, the result taken together with the qualitative responses from the interview can better inform clinical decision-making by providing additional drivers associated with suicide risk.
Hard work, long hours, and Singaporean young adults' health—A qualitative study
Authors: Leu Jodie , Rebello Salome A. , Sargent Ginny M. , Kelly Matthew , Banwell Cathy
Published: June 2023

Background

As young adults in their 20s to 30s transitioning toward new careers and independence, their dietary and physical activity practices often change, increasing their risk of weight gain. This study explored the ways that Singaporean young adults perceived and experienced the interaction between their working hours, work, and health practices.

Methods

This research used semi-structured interviews to explore the perspectives and experiences of participants. Purposive and snowball sampling was used to recruit 15 men and 18 women, aged 23 to 36, who had worked full-time at their respective jobs in Singapore for at least 1 year. An inductive and deductive thematic analysis approach was employed.

Results

Young working adults' commitment to work was driven by a hard-working culture, a desire to attain better jobs and remuneration, and to fulfill cultural expectations to support their multi-generation families. Their non-work time was largely spent recuperating from work by socializing over food and in sedentary activities.

Conclusion

For young working adults, long work hours are normalized, even though they are a barrier to healthy diets and physical activity. Existing social and institutional norms support a culture that values commitment to work and encourages young adults to devote long hours to building a sound financial future and achieving personal and cultural aspirations. These findings have implications for long-term population health and should be considered in health promotion activities targeting young adults and barriers.
Effects of Varying Levels of Background Noise on Room Acoustic Parameters, Measured with ESS and MLS Methods
Authors: Papadakis Nikolaos M. , Antoniadou Smaro , Stavroulakis Georgios E.
Published: June 2023

Typically, background noise of different types and levels is present during the measurement of the impulse response in spaces. The two methods that are, in practice, most frequently used in the measurement of the impulse response, are the exponential sine sweep (ESS), and the maximum length sequence (MLS). This study’s objective was to estimate the impact of background noise (white noise, tonal noise) on the acoustic parameters (T30, EDT, C80, and D50) for ESS and MLS measurements, by introducing artificial background noise, employing an external sound source. For this purpose, measurements were performed with varying levels of external noise (in steps of 2 dB), and the effect was assessed, using the relative error compared to measurements without artificial background noise. According to the findings for white noise (as background noise), in the case of T30 and EDT, the difference between the two methods, as well as the relative error, for the initial levels of added background noise, was small. However, for higher levels of added background noise, there was a sharp increase in the relative error, which was greater for the ESS method, both for T30 and EDT. Regarding C80 and D50, while initially the differences between the ESS and MLS methods were small, cumulatively, as the background noise increased, the relative error increased for both methods, with the ESS method showing the largest error. In the case of tonal noise (as background noise), the results were consistent with those observed in the case of white noise. The study’s findings contribute to a better understanding of the ESS and MLS methods, and suggest the expected relative error of acoustic parameters when various types and levels of background noise are present. Additionally, the study suggests, based on background noise and level, the optimum method to conduct impulse response measurements.
Research on Fault Diagnosis of HVAC Systems Based on the ReliefF-RFECV-SVM Combined Model
Authors: Nie Lei , Wu Rouhui , Ren Yizhu , Tan Mengying
Published: June 2023

A fault diagnosis method of heating, ventilation, and air conditioning (HVAC) systems based on the ReliefF-recursive feature elimination based on cross validation-support vector machine (ReliefF-RFECV-SVM) combined model is proposed to enhance the diagnosis accuracy and efficiency. The method initially uses ReliefF to screen the original features, selecting those that account for 95% of the total weight. The recursive feature elimination based on cross validation (RFECV), based on a random forest classifier, is then applied to select the optimal feature subset according to diagnostic accuracy. Finally, a support vector machine (SVM) model is constructed for fault classification. The method is tested on seven typical faults of the ASHRAE 1043-RP water chiller dataset and three typical faults of an air-cooled self-built air conditioner simulation dataset. The results show that the ReliefF-RFECV-SVM method significantly reduces diagnosis time compared to SVM, shortening it by about 50% based on the ASHRAE 1043-RP dataset, while achieving an overall accuracy of 99.98%. Moreover, the proposed method achieves a comprehensive diagnosis accuracy of 99.97% on the self-built simulation dataset, with diagnosis time the reduced by about 65% compared to single SVM.
Robust Adaptive Composite Learning Integrated Guidance and Control for Skid-to-Turn Interceptors Subjected to Multiple Uncertainties and Constraints
Authors: Bai Yu , Yan Tian , Fu Wenxing , Li Tong , Huang Junhua
Published: June 2023

This paper investigates a novel robust adaptive dynamic surface control scheme based on the barrier Lyapunov function (BLF), online composite learning, disturbance observer, and improved saturation function. It is mainly designed for a class of skid-to-turn (STT) interceptor integrated guidance and control (IGC) design problems under multi-source uncertainties, state constraints, and input saturation. The serial-parallel estimation model used in this study estimates the system states and provides “critic” information for the neural network and disturbance observer; then, these three are combined to realize online composite learning of the multiple uncertainties of the system and improve the interception accuracy. In addition, the state and input constraints are resolved by adopting the BLF and the improved saturation function, while the design of the auxiliary system ensures stability. Finally, a series of simulation results show that the proposed IGC scheme with a direct-hit intercept strategy achieves a satisfactory effect, demonstrating the validity and robustness of the scheme.
Experimental Implementation of a Magnetic Levitation System for Laser-Directed Energy Deposition via Powder Feeding Additive Manufacturing Applications
Authors: Kumar Parichit , Ansari Mazyar , Toyserkani Ehsan , Khamesee Mir Behrad
Published: June 2023

Magnetic levitation and additive manufacturing (AM) are two fields of significant interest in academic research. The use of non-contact forces for magnetic levitation techniques provides opportunities for adoption within the AM environment. The key goal of this article is to experimentally validate the implementation of a magnetic levitation system for Laser-Directed Energy Deposition via Powder Feeding (LDED-PF) Additive Manufacturing applications. Through simulations (conducted in ANSYS Maxwell) and experimental implementation, the levitation system’s stability is tested under a variety of different conditions. The experimental implementation highlights the feasibility of a magnetic levitation system for LDED-PF applications. The levitation system developed is capable of the suspension of non-magnetic materials. The system is also able to maintain stable levitation for extended periods of time. The incorporation of the levitation system into the AM environment may result in an increased maneuverability of non-clamped structures for AM deposition operations.
Optimized Nitrogen Fertilizer Rate Can Increase Yield and Nitrogen Use Efficiency for Open-Field Chinese Cabbage in Southwest China
Authors: Cao Hailin , Zhang Fen , Fu Jian , Ma Xiao , Wang Junjie , Liu Fabo , Guo Guangzheng , Tian Yiming , Liang Tao , Zhou Na , Wang Yan , Chen Xinping , Wang Xiaozhong
Published: June 2023

Intensive vegetable production has been characterized by high nitrogen (N) fertilizer input in southwest China. Optimizing the N fertilizer rate is the basis for the optimal management of regional N fertilizer. A two-year field experiment with five N fertilizer rates was conducted during 2019–2021 in southwest China, and the aim of this study was to identify the effects of different N application rates on yield, dry matter biomass (DMB), N uptake, N use efficiency (NUE) and soil mineral N (Nmin) residues for Chinese cabbage (Brassica chinensis L.) and further determine the critical plant N concentration and root-zone soil Nmin residues required to reach the maximum DMB of Chinese cabbage. Five N treatments were established: control without N input (CK); optimal N fertilizer rate decreased by 30% (70% OPT, 175 kg N ha−1), optimized N fertilizer rate (OPT, 250 kg N ha−1), optimal N fertilizer rate increased by 30% (130% OPT, 325 kg N ha−1) and farmers’ N fertilizer practice (FP, 450 kg N ha−1). The N source in all treatments was conventional urea (N ≥ 46.2%). The results showed that the total yield of Chinese cabbage followed a “linear-plateau” trend with an increasing N fertilizer rate. There was no significant difference in yield between the OPT, 130% OPT and FP treatments. The aboveground plant DMB and N uptake showed a ‘slow-fast-slow’ pattern with the growth period. There was no significant difference in aboveground plant DMB and N uptake between the OPT, 130% OPT and FP treatments. Moreover, the OPT treatment significantly increased the aboveground plant DMB and N accumulation by 29.6% and 40.5%, respectively, compared with the 70% OPT treatment. The OPT treatment significantly increased the NUE by 23.8%, 31.2% and 43.1% compared with that in the 70% OPT, 130% OPT and FP treatments, respectively. The linear-plateau model provided the best fit for the relationship among aboveground DMB of Chinese cabbage, plant N concentration and root-zone soil Nmin content. The critical root-zone soil Nmin and plant N concentrations were 94.1, 63.4 and 68.3 kg ha−1 and 34.4, 33.5 and 32.9 g kg−1 during the rosette, heading and harvest periods, respectively. In summary, compared to the FP treatment, the optimized N fertilizer rate (250 kg N ha−1) could significantly reduce the N application rate, maintain yield, increase aboveground plant DMB and N uptake, and improve NUE. Moreover, the study has great significance for guiding the green utilization of vegetable N fertilizer in southwest China.