bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative
Authors: Zang Chengxi , Hou Yu , Schenck Edward , Xu Zhenxing , Zhang Yongkang , Xu Jie , Bian Jiang , Morozyuk Dmitry , Khullar Dhruv , Nordvig Anna , Shenkman Elizabeth , Rothman Russel , Block Jason , Lyman Kristin , Zhang Yiye , Varma Jay , Weiner Mark , Carton Thomas , Wang Fei , Kaushal Rainu , Consortium the RECOVER
Published: March 2023

Background Patients who were SARS-CoV-2 infected could suffer from newly incidental conditions in their post-acute infection period. These conditions, denoted as the post-acute sequelae of SARS-CoV-2 infection (PASC), are highly heterogeneous and involve a diverse set of organ systems. Limited studies have investigated the predictability of these conditions and their associated risk factors.
Method In this retrospective cohort study, we investigated two large-scale PCORnet clinical research networks, INSIGHT and OneFlorida+, including 11 million patients in the New York City area and 16.8 million patients from Florida, to develop machine learning prediction models for those who are at risk for newly incident PASC and to identify factors associated with newly incident PASC conditions. Adult patients aged 20 with SARS-CoV-2 infection and without recorded infection between March 1st, 2020, and November 30th, 2021, were used for identifying associated factors with incident PASC after removing background associations. The predictive models were developed on infected adults.
Results We find several incident PASC, e.g., malnutrition, COPD, dementia, and acute kidney failure, were associated with severe acute SARS-CoV-2 infection, defined by hospitalization and ICU stay. Older age and extremes of weight were also associated with these incident conditions. These conditions were better predicted (C-index >0.8). Moderately predictable conditions included diabetes and thromboembolic disease (C-index 0.7-0.8). These were associated with a wider variety of baseline conditions. Less predictable conditions included fatigue, anxiety, sleep disorders, and depression (C-index around 0.6).
Conclusions This observational study suggests that a set of likely risk factors for different PASC conditions were identifiable from EHRs, predictability of different PASC conditions was heterogeneous, and using machine learning-based predictive models might help in identifying patients who were at risk of developing incident PASC.
Identification of Hub Genes Associated with Diabetic Cardiomyopathy Using Integrated Bioinformatics Analysis
Authors: Cui Hailong , Hu Die , Xu Jing , Zhao Shuiying , Song Yi , Qin Guijun , Liu Yanling
Published: March 2023

Diabetic cardiomyopathy (DCM) is a common cardiovascular complication of diabetes, which may threaten the quality of life and shorten life expectancy in diabetic population. However, the molecular mechanisms underlying the diabetes cardiomyopathy are not fully elucidated. We analyzed two datasets from Gene Expression Omnibus (GEO). Differentially expression analysis and weighted gene correlation network analysis (WGCNA) were used to screen key genes and molecules. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network analysis were constructed to identify hub genes. The diagnostic value of hub gene was evaluated using the receiver operating characteristic (ROC). Quantitative real-time PCR (RT-qPCR) was used to validate the hub genes. A total of 13 differentially co-expressed modules were selected by WGCNA and differential expression analysis. KEGG and GO analysis showed these DEGs were mainly enriched in lipid metabolism and myocardial hypertrophy pathway, cytomembrane and mitochondrion. As a result, six genes were identified as hub genes. Finally, five genes (Pdk4, Lipe, Serpine1, Igf1r, and Bcl2l1) were found significantly changed in both the validation dataset and experimental mice with DCM. In conclusion, the present study identified five genes which may help to provide novel targets for the diagnosis and treatment of DCM.
Changes in seed quality parameters of American cotton due to seed treatment with metal oxide nanoparticles during storage
Authors: Singh Nirmal , Bhuker Axay
Published: March 2023

Purpose
An experiment was conducted to check out effect of seed treatment with nanoparticles on storability of American cotton seeds in laboratory of Department of Seed Science and Technology, CCS HAU Hisar.
Methods
Delinted and fuzzy Seeds of two American cotton varieties (H 1300 and H 1098-i) were nanoprimed for 10 hours with zinc oxide nanoparticles (ZnONPs) @400 ppm and titanium dioxide nanoparticles (TiO2NPs) @100 ppm. Observed parameters at different interval (0 month, 3 months, 6 months, 9 months and 12 months) during storage were moisture content, germination percentage, seedling length, seedling dry weight, SVI-I, SVI-II, electrical conductivity and dehydrogenase activity.
Results
Size of ZnONPs and TiO2NPs were 36.25 nm and 39.40 nm, respectively. Results of experiment revealed that different storage periods and nanopriming treatments had significant effect on all seed quality parameters except effect of nanopriming treatments on germination percentage (excluding delinted seeds of H 1098-i). It is also revealed that interaction effect of nanopriming treatment and storage period was non-significant on all parameters except EC. Maximum value of seed quality parameters except EC was observed at 0 month and minimum was found after 12 months of storage. Maximum reduction in seed quality parameters were observed in control treatment and minimum was found when seeds were nanoprimed with ZnONPs @ 400 ppm.
Conclusion
Results of experiment came to a conclusion that ZnONPs and TiO2NPs had capacity to hold seed quality and vigour during storage of cotton seeds of American varieties (H 1300 and H 1098-i).
Novel MRI-guided Focussed Ultrasound Stimulated Microbubble Radiation Enhancement Treatment for Breast Cancer
Authors: Dasgupta Archya , Saifuddin Murtuza , McNabb Evan , Ho Ling , Lu Lin , Vesprini Danny , Karam Irene , Soliman Hany , Chow Edward , Gandhi Sonal , Trudeau Maureen , Tran William , Curpen Belinda , Stanisz Greg , Sahgal Arjun , Kolios Michael , Czarnota Gregory J.
Published: March 2023

Background

Preclinical studies have demonstrated focused ultrasound (FUS) stimulated microbubble (MB) rupture leads to the activation of acid sphingomyelinase-ceramide pathway in the endothelial cells. When radiotherapy (RT) is delivered concurrently with FUS-MB, apoptotic pathway leads to increased cell death resulting in potent radiosensitization. Here we report the first human trial of using magnetic resonance imaging (MRI) guided FUS-MB treatment in the treatment of breast malignancies.

Methods

In the phase 1 prospective interventional study, patients with breast cancer were treated with fractionated RT (5 or 10 fractions) to the disease involving breast or chest wall. FUS-MB treatment was delivered before 1st and 5th fractions of RT (within 1 hour).

Results

8 patients with 9 tumours were treated. All 7 evaluable patients with at least 3 months follow-up treated for 8 tumours had a complete response in the treated site. The maximum acute toxicity observed was grade 2 dermatitis in 1 site, and grade 1 in 8 treated sites, at one month post RT, which recovered at 3 months. No RT-related late effect or FUS-MB related toxicity was noted.

Conclusions

This study demonstrated safety of combined FUS-MB and RT treatment. Promising response rates suggest potential strong radiosensitization effects of the investigational modality.
Trial registration: clinicaltrials.gov, identifier NCT04431674
Effect of different Hb concentrations on the risk of gestational diabetes mellitus in women with thalassemia minor
Authors: Wang Xiaoju , Xiao Shuang , Li Lingou , Yang Mei
Published: March 2023

Backgrounds

A few studies have focused on the effect of thalassemia and different Hb levels on pregnancy outcomes recently. However, to our knowledge, there are no studies on the effects of different levels of hemoglobin(Hb) on pregnancy outcomes in Chinese women with thalassemia minor. In the present research, we aimed to clarify the effect of different Hb levels on pregnancy outcomes and to further explore the association of different Hb levels and gestational diabetes mellitus (GDM) in pregnant women with thalassemia minor in Chinese populations.

Methods

A retrospective controlled study was conducted on 723 pregnant women who were followed up for delivery in our hospital from 2017 to 2021. They were grouped into thalassemia minor and control group. The two groups were further divided into three subgroups, including anmia, normal and high Hb subgroups. Pregnant complications were studied in two main groups and their three subgroups. All statistical analyses were performed using R version 4.1.0 and contributed packages.

Results

There were no significant differences regarding neonatal and maternal pregnancy outcomes in women with and without thalassemia except for postpartum anemia. Furthermore, in the thalassemia group, the prevalence of GDM in the high Hb subgroup was significantly higher than the other two subgroups. However, in the control group, no significant statistical differences were found among the three subgroups. Moreover, in the high Hb subgroup, the fetuses of women with thalassemia were more likely to develop jaundice after birth. In the normal Hb subgroup, the proportion of macrosomia in the thalassemia group was significantly higher than the control group, while the proportion of low birth weight infants was on the contrary. Lastly, in anemia subgroups, we found less pregnant women with thalassemia suffered from cesarean compared to pregnant women without thalassemia.

Conclusion

We concluded that high Hb concentration might be a trigger for GDM in Chinese pregnant women with thalassemia minor. Maternal iron and Hb levels should be monitored during antenatal care and pregnancy management, as iron supplementation may lead to adverse pregnancy outcomes in women with thalassemia minor with normal or particularly high Hb concentrations.
Revealing the Materials Genome of Superhard High-Entropy Diborides via the Hybrid Data-driven and Knowledge-enabled Model
Authors: Wang William Yi , Lu Jiaqi , Zhang Fengpei , Yao Gang , Gao Xingyu , Liu Ya , Zhang Zhi , Wang Jun , Wang Yiguang , Liang Xiubing , Song Haifeng , LI Jinshan , Zhang Pingxiang
Published: March 2023

Materials descriptors with multivariate, multiphase and multiscale of a complex system have been treated as the remarkable materials genome, addressing the composition-processing-structure-property-performance (CPSPP) relationships during the development of advanced materials. With the aid of high-performance computations, big data and artificial intelligent technologies, it is still a challenge to derive the explainable machine learned model to reveal the underlaying CPSPP relationship, especially, under the extreme conditions. Here, we propose a hybrid data-driven and knowledge-enabled model with two key descriptors to design the superhard high entropy boride ceramics (HEBs), which is not only in line with the common features from various machine learning algorithms but also integrate the solid-solution strengthening mechanisms. While five dominate features in terms of load, valence differences, electronegativity, electron work functions, and the differences among solutes in various column of periodical elementary table were screened out from 149 ones, the best optimal machine learning (ML) algorithm was addressed among decision tree, support vector regression, K-Nearest Neighbor, random forest, Adaboost, gradient enhanced regression tree, Bagging, ExtraTree, and XGBoost. The Shapley additive explanation the key influence trend for material hardness with the change of HEBs electronic properties. Correspondingly, the predicted 14 potential best superhard HEB candidates via ML are further validated by first-principles calculations via the aforementioned knowledge-based model. This work supports a smart strategy to derive the hybrid data-driven and knowledge-enable explainable model predicting the target properties of advanced HEBs and paves a path accelerating their development at cost-effective approach.
Is resting state fMRI better than individual characteristics at predicting cognition?
Authors: Omidvarnia Amir , Sasse Leonard , Larabi Daouia , Raimondo Federico , Hoffstaedter Felix , Kasper Jan , Dukart Jurgen , Petersen Marvin , Cheng Bastian , Thomalla Götz , Eickhoff Simon , Patil Kaustubh
Published: March 2023

Changes in spontaneous brain activity at rest provide rich information about behavior and cognition. The mathematical properties of resting-state functional magnetic resonance imaging (rsfMRI) are a depiction of brain function and are frequently used to predict cognitive phenotypes. Individual characteristics such as age, gender, and total intracranial volume (TIV) play an important role in predictive modeling of rsfMRI (for example, as “confounders” in many cases). It is unclear, however, to what extent rsfMRI carries independent information from the individual characteristics that is able to predict cognitive phenotypes. Here, we used kernel ridge regression modeling to thoroughly examine the predictability of four cognitive phenotypes in 20,000 healthy UK Biobank subjects. We extracted common rsfMRI features of functional brain connectivity (FC) and temporal complexity (TC). We assessed the ability of these features to predict outcomes in the presence and absence of age, gender, and TIV. Additionally, we assessed the predictiveness of age, gender, and TIV only. We find TC and FC features to perform comparably with regard to predicting cognitive phenotypes. As compared to rsfMRI features, individual characteristics provide systematically better predictions with smaller sample sizes and, to some extent, in larger cohorts. It is also consistent across different levels of inherent temporal noise in rsfMRI. Our results suggest that when the objective is to perform cognitive predictions as opposed to understanding the relationship between brain and behavior, individual characteristics outperform rsfMRI features.
sEMG signal-based portable hand and wrist integrated rehabilitation robot for hand dysfunction
Authors: Wang Hui , Liang Hui , Chen Long , Jiao Hengan , Sheng Weihang , Zhang Guangxing , Deng Fang , Wang Chuansheng
Published: March 2023

For patients with hand movement dysfunction caused by diseases such as stroke and hemiplegia, a portable hand and wrist integrated rehabilitation robot is presented based on the human factor engineering. The rehabilitation robot can achieve rehabilitation training of 14 DOFs of fingers and 2 DOFs of wrist. The four-channel sEMG signals of finger and wrist movements are collected by DELSYS equipment, and the pre-processing operations such as denoising and segmentation are carried out by MATLAB. Three kinds of time domain signal features are extracted and combined. The classification training model is obtained by LDA, CNN and LSTM classification method, respectively for different hand movements. Comparisons of the accuracy and learning speed of the three methods show that the CNN method has the highest accuracy and the fastest learning speed. The prototype model of the rehabilitation robot is generated by 3D printing, then the CPM rehabilitation and sEMG control experiments are carried out. Experiment results verify the effectiveness and efficiency of the proposed multi-function rehabilitation robot.
Genome-wide analyses of the Tubby-like proteins in Brassica napus revealed their potential roles in the abiotic stress response
Authors: Xu Hongru , Huang Lintao , Qian Fang , Zhang Xiaojun , Li Hao , Zhai Yungu , Wei Wenliang
Published: March 2023

Rapeseed (Brassica napus) is the third-largest source of edible vegetable oil in the world. One of the most crucial techniques to increase rapeseed oil production is to develop and utilize saline-alkali soil. Rapeseed biochemical underpinnings for tolerance to abiotic stress, particularly salt stress, are not entirely established. The tubby-like protein(TLP) gene family is a class of transcription factors originally discovered in obese mice. It plays several roles in the growth and development of plants, particularly in responseto biotic and abiotic stresses. Twenty-nine BnaTLPs members were identified in the B. napus cultivar Zhongshuang 11, which were unevenly distributed on 16 chromosomes of B. napus. Phylogenetic analysis showed that TLPproteins were separated into six groups based on protein homology in 9 plant species. Gene structure analysis showed that the majority of the BnaTLPs members have similar intron/exon and motif structures. Conserved domain analysis showed that BnaTLP8A, BnaTLP8C, and AtTLP8 lacked the N-terminal F-box protein, which may have an impact on how well they function. Collinearity analysis revealed that most BnaTLPsare the products of heterologous polyploidization and segmental duplication events. RNA-seq data showed that the majority of BnaTLPs members are expressed in significant tissues and organs at various developmental stages. Real-time qPCR results showed that BnaTLP9A, BnaTLP3C, BnaTLP2C, and BnaTLP10C.2 are upregulated in response to drought and salt stress in B. napus, while BnaTLP8A is downregulated. This study provides new insight into how TLPs react to drought and salt stresses, in addition to identifying candidate genes for abiotic stress improvement in B. napus.
Bioactivity of Cinnamomum verum powder and extract against Cryptolestes ferrugineus S., Rhyzopertha dominica F. and Sitophilus granarius L. (Coleoptera)
Authors: Mahmoud Hend A. , Azab Mohamed M. , Sleem Fatma Mohamed Amin
Published: March 2023

The world is heading to increase the productivity, quantity and quality, of basic crops, but the stored grain pests destroy all these efforts and reduce its quality. This study aims to assess activity of Cinnamomum verum powder and extract against Cryptolestes ferrugineus, Rhyzopertha dominica, and Sitophilus granarius. Residual film of cinnamon was tested with and without grains (as contact toxicity). Repellent activity was estimated by using choice chamber method and waved filter paper for powder and extract, respectively. There were significant differences among all tested insects. S. granarius was more affected with cinnamon extract than C. ferrugineus followed by R. dominica. LC50 values were 1.01, 1.37 and 3.13% at 24 h. While, C. ferrugineus was more affected with powder than S. granarius followed by R. dominica. For repellent activity, C. ferrugineus was the most affected with the powder and extract followed by R. dominica and S. granarius, where, the mean repellent percentages were 100, 98 and 82% for the powder and 86.94, 62.78 and 29.44% for the extract, respectively. The repellent percentage increased with increasing the concentration and the time of exposure. Cinnamon powder and extract can be used as insecticide against stored grain pests by easy way and safety to human and the environment.
Spidroin-Inspired Hierarchical Structure Binder Achieves Highly Integrated Silicon-Based Electrodes
Authors: Mu Pengzhou , Zhang Shu , Zhang Huanrui , Li Jiedong , Liu Zhi , Dong Shanmu , Cui Guanglei
Published: March 2023

As a promising component for next-generation high energy lithium-ion batteries, silicon based electrode has attracted increasing attention by virtue of ultrahigh theoretical specific capacities. Nevertheless, fast capacity fade posed by tremendous volume changes during the lithiation and delithiation process remains a huge challenge before large-scale applications. Inspired by spidroin, we herein develop a tenacious hierarchical structure binder for tolerating huge volume change of silicon-based anode, which is prepared through simply mixing aqueous poly(acrylic acid) solution, and oily N-methyl pyrrolidone solution containing a tetrazole groups based copolymer (PPB) of polyacrylonitrile and poly(ethylene glycol) bisazide. Such an aqueous-oil binary solution based blend (AOB) binder exhibits a spidroin-like hierarchical structure. In the AOB binder, hydrophobic PPB polymer condensates in the mixture solution to form crystalline region within submicron-sized irregular spherical domains as the rigid node of the molecular chain segment similar to β-sheet of spidroin; while water-souble, amorphous poly(acrylic acid) mimicks the α-helix structure of spidroin, and builds up a network structure by linking with PPB via ionic bonding similar to the interactions between repetitive amino acid sequence segment in the primary structure of spidroin. Benefited by these, AOB binder enables both high tensile strength and elasticity, and superior adhesion of electrodes, therefore apparently stabilizing silicon-based anode structure and rendering prolonged electrode cycle life. This work marks a milestone in developing state-of-the-art silicon-based electrodes towards high energy density lithium battery applications.
Efficacy of cerebellar transcranial magnetic stimulation in spinocerebellar ataxia type 3: A randomized controlled trial
Authors: Shi Yuting , Zou Guangdong , Chen Zhao , Wan Linlin , Peng Linliu , Peng Huirong , Shen Lu , Xia Kun , Qiu Rong , Tang Beisha , Jiang Hong
Published: March 2023

Spinocerebellar ataxia type 3 (SCA3) is the most common subtype of SCA without effective treatment. This study aimed to evaluate the comparative efficacy of low-frequency repetitive transcranial magnetic stimulation (rTMS) and intermittent Theta Burst Stimulation (iTBS) in a larger cohort of SCA3 patients. One hundred and twenty patients with SCA3 were randomly selected to receive 1Hz rTMS, iTBS or sham. All patients were assessed at baseline and after all sessions. Primary outcomes included the Scale for the Assessment and Rating of Ataxia (SARA) and the International Cooperative Ataxia Rating Scale (ICARS). Secondary outcomes included 10-meter walking test (10MWT), nine-hole peg test (9-HPT), and PATA Rate Test (PRT). This study revealed that 1Hz rTMS and iTBS outperformed sham in reducing the SARA and ICARS scores in SCA3 patients, but with no difference between 1Hz rTMS and iTBS. Furthermore, iTBS decreased 9-HPT scores when using a non-dominant hand. Additionally, we found that symptom severity variance of patients did not influence the effect of rTMS on the clinical impression. No severe adverse events were recorded in this study. The study concluded that 1Hz rTMS and iTBS interventions targeting the cerebellum are effective and safe in patients with SCA3.
Postprandial Sodium Sensor in the Drosophila Gut
Authors: Suh Greg (Seong Bae) , Kim Byoungsoo , Hwang Gayoung , Yoon Sung-Eun , Kuang Meihua , Wang Jing W. , Kim Young Joon
Published: March 2023

Sodium is essential for all living organisms. Animals including insects and mammals detect sodium primarily through peripheral taste cells. It is not known, however, whether animals can detect this essential micronutrient independently of the taste system. Here, we report that Drosophila IR76b mutants that were unable to detect sodium1 became capable of responding to sodium after a period of dietary salt deprivation. From a screen for cells required for the deprivation-induced sodium preference, we identified a population of anterior enteric neurons that we named INSO (Internal Sodium Sensing) neurons, that are necessary and sufficient for directing a behavioral preference for sodium. Enteric INSO neurons innervate the gut epithelia mainly through their dendritic processes and send their axonal projections along the esophagus to the brain and to the crop duct. Through calcium imaging and CaLexA experiments, we found that INSO neurons are amiloride-insensitive and respond immediately and specifically to sodium ions. Taken together, we have identified a previously unknown taste-independent sodium sensor that is essential for the maintenance of sodium homeostasis.
Efficacy and safety of rituximab in connective tissue disease-associated thrombotic thrombocytopenic purpura/thrombotic microangiopathy
Authors: Ohkubo Naoaki , Nakayamada Shingo , Hanami Kentaro , Fukuyo Shunsuke , Miyazaki Yusuke , Inoue Yoshino , Tanaka Hiroaki , Todoroki Yasuyuki , Miyata Hiroko , Tanaka Yoshiya
Published: March 2023

Background
This study examined the efficacy and safety of Rituximab (RTX) treatment in connective tissue disease (CTD)-associated thrombocytopenic purpura (TTP) and thrombotic microangiopathy (TMA), using historical controls as comparators.
Methods
Patients who were admitted to our department from March 1, 2013, to March 31, 2021, and diagnosed with CTD-associated TTP/TMA refractory to plasma exchange were included in the retrospective study. A patient with treatment-resistant disease was treated with RTX in addition to high-dose glucocorticoid (GC) therapy (GC + RTX). As historical controls, we selected patients with CTD-associated TTP/TMA who were admitted to our center and treated with GC and immunosuppressants (IS) such as cyclophosphamide. The primary endpoint was the survival rate at 52 weeks after initiation of treatment.
Results
Fifteen patients were enrolled in the study (GC + RTX). As a control group, 11 patients were enrolled in the same manner (GC + IS). There were no significant differences in age or sex or laboratory tests between the two groups. The primary endpoint of survival rate was higher in the GC + RTX group than in the GC + IS group. In the immunophenotyping analysis before treatment, among all subsets of immune cells, only plasmocytes were elevated in TTP patients compared to healthy controls. The proportion ofplasmocytes correlated with serum markers, suggesting increased B cell differentiation, which was markedly decreased after RTX treatment.
Conclusion
In CTD-associated TTP/TMA, the addition of RTX to plasma exchange and GC therapy may improve B cell-based pathology and survival.
Chebyshev Chaotic Map with Attribute Based Encryption on Session Based Data Sharing in Fog Environment
Authors: A THUSHARA G , Bhanu S. Mary Saira
Published: March 2023

Fog computing is a feasible approach that can alleviate the tremendous pressure on cloud-based medical data processing. Despite the benefits of low latency, storage, and computational power that service IoT applications and devices, fog computing has few privacy and security concerns. Attribute Based Encryption is a powerful cryptographic technique for ensuring the secure sharing of medical data. Unfortunately, the problem of collusion induced by compromised users, trusted third party attack, bottleneck of key generation center, ineffective key distribution, and poor data-sharing remains unsettled in the research in attribute based encryption systems. This work proposes a user-specific and file-specific attribute-based encryption that combines Chebyshev chaotic maps for generating hash function to provide efficient session-based key setup in fog-based data-sharing. The computational cost spent by fog nodes to carry out session management is extremely minimum in the proposed work. Furthermore, the work can minimize third-party processing overheads and protect data-sharing from a number of cryptographic assaults. According to experimental and theoretical analysis, the proposed work is secure and extremely effective for sharing data in a fog environment.
The relationship between fear of negative evaluation, family function, and adolescents’ aggression: the mediating role of mobile phone addiction and rumination
Authors: Chang Hongjuan , YAN Jixia , Shen Lijun
Published: March 2023

Aggressive behaviour has caused significant damage to the body and mind of teenagers. It is imperative to understand the cause of aggressive behaviour. Therefore, we explored the relationship between family function and fear of negative evaluations and aggression. A total of 2929 college students aged 16–29 years who completed the questionnaires were included in the analysis. Structural equation modelling (SEM) was used to evaluate the associations between family function and fear of negative evaluations and aggression. Correlational analyses revealed that aggressive behaviours were associated with the family function, fear of negative evaluations, rumination, and mobile phone addiction (P < 0.01). The Family APGAR index was negatively associated with aggressive behaviour (β = -0.15, P < 0.01). The relationship between family APGAR index and aggressive behaviour could be explained by the mediating effects of rumination (indirect effect: β = -0.09, P < 0.01) and mobile phone addiction (indirect effect: β = -0.06, P < 0.01). Fear of negative evaluation could significantly predict aggressive behaviour. Fear of negative evaluation was positively associated with aggressive behaviour (β = 0.07, P < 0.01). The relationship between fear of negative evaluation and aggressive behaviour could be explained by the mediating effect of rumination (indirect effect: β = 0.10, P < 0.01) and mobile phone addiction (indirect effect: β = 0.10, P < 0.01). The findings of this study suggested that there was a significant association between family function and fear of negative evaluation and aggression, and these associations were mediated by cell phone addiction and rumination.
Low Power FPGA Implementation of an Efficient AES- SBOX Realization for Health Care Applications
Authors: Priya E. S. Selva , Suganthi L.
Published: March 2023

In present digital world, the data transmitted over network has become worldwide. The information compiled, processed and communicated in Bits and bytes of digital format over communication channels. For secure communication an advanced encryption Standard (AES) cryptographic algorithm is employed to avoid the risk of secret information tampering. This Research article predominantly focuses on low power and low area hardware architecture designed using Field Programmable Gate array. The novel architecture is derived by employing composite field arithmetic for substitute byte and inverse substitute bytes operation. By this approach the unwanted delay occurs during the Look up table (LUT) method has been averted. Optimized Positive polarity reed Muller (OPPRM) architecture is introduced in order to minimize the hardware utilization, eventually subpipeling technique has brought in, to enhance the speed of the architecture. The Performance metrics of OPPRM-AES is evaluated with respect to Bonded IPADS, Slice, LUTS, Number of slices, Static as well as Dynamic Power. The performance of a proposed architecture is compared with AES-PPRM, AES-CFA and AES-ECG.The architecture is implemented onto Zynq ZC702 Evaluation Board and the simulation is performed through the vivado 2019.1 software.
Applying Neural Style Transfer to Transform Images into a Different Style Domain by the NST Method
Authors: Vishnukumar A , E Kamalanaban , Gugan S , A Abdul Gafoor , T Mukesh
Published: March 2023

A group of software algorithms known as neural style transfer (NST) alter digital pictures or videos to take on the look or visual style of another image. It is a machine learning-based optimization approach. In this study, we employ software that translates a picture's style onto a second image, referred to as the content image. Images may be encrypted, and the data can then be transferred to the recipient as an encrypted picture. The purpose of picture alteration is served through the usage of deep neural networks. The NST method may be used with this paper to modify two photos in photo-editing software. The created image can be outputted in whatever size the user desires. Hence The neural style transfer.
Ecology and behavioral patterns of Luciola cruciate in a restored forest in a chemical plant
Authors: Sano Kazuhiko , Yokoyama Tadashi , Kato Jinichiro
Published: March 2023

There is a current initiative to bring back fireflies. The first step was the development of a breeding system. The system can accommodate approximately 5,000 hatched larvae of Luciola cruciate, an aquatic firefly species, until they reach the last instar larval stage. The bred larvae are released into a river in the forest restored in a chemical plant, where they can breed naturally. Firefly festivals are events in which the public can share the pleasure of watching fireflies. The key to successful firefly-viewing events is to predict the peak flight season of fireflies. There is scope to improve the methods used for flight season prediction, which have impaired prediction accuracy owing to the variability of regional characteristics. In this study, data on fireflies and meteorological data accumulated for the restored forest over 11 years have been analyzed and the peak flight days of L. cruciate adults and climbing by L. cruciate larvae were discussed. The new regression equation-based method proposed in this study, which used the breeding temperature and the minimum humidity, could estimate the peak flight date of adult fireflies better than the conventional method based on the effective cumulative temperature. As part of the ecology of fireflies, a statistical analysis on climbing by larvae was conducted and revealed that the minimum temperature and cumulative precipitation were significant predictors of climbing, and that climbing occurred on a rainy night with a minimum temperature of 10°C or higher.
Classification codes:
25.02 : Animal Biochemistry
101.03 : Statistics and Computing/Statistics Programs
Some elliptic equations with unbounded coefficients and singular gradient term
Authors: MARAH AMINE , REDWANE HICHAM
Published: March 2023

We are interseted in a class of nonlinear elliptic equations involving a blowing-up coefficient and a singular term whose prototype is
\[\begin{aligned} \left\{ \begin{aligned}&-\mathrm{div}\Big (b(u) (1+|u|)^q \nabla u\Big )= b_1\frac{|\nabla u|^2}{|u|^\theta }+f\ \ \mathrm{in}\ \Omega, \\&u=0\ \ \mathrm{on}\ {\partial \Omega },\\ \end{aligned} \right.
\end{aligned}\]
where $\Omega$ is a bounded open subset of $\Real^N (N\geq 2)$, $b(s)$ is a positive continuous function which blows up for a finite value of the unknown, $b_1>0$, $q>0$, $\theta>0 $ and the nonnegative source $f$ belongs to $L^{t}(\Omega)$, $t\geq 1$.
Corrosion and catalytic properties of electrodeposited nanocrystalline molybdenum
Authors: Hasan Siti Nur , Asselin Edouard
Published: March 2023

Molybdenum (Mo) is a less toxic alternative to chromium for protective coatings. Mo possesses similar properties to Cr, although its electrochemical properties, particularly its passive behavior, have been less studied. We compare the passive behavior of electrodeposited Mo coatings to that of bulk metallic Mo in 3.5% sodium chloride (NaCl) solution. The results demonstrate a strong correlation between the microstructure and passive properties of the coating. Electrodeposited Mo has a higher tendency to passivate, a higher passive current density, and a larger passivation window compared to bulk Mo in 3.5% NaCl. The enhanced electrochemical behavior of the Mo coating is attributed to its nanometric structure and increased electrochemically active surface area. This study highlights the potential for the use of electrodeposited Mo as a safer and more environmentally friendly alternative to Cr coatings.
SL4U: A Scenario Description Language forUnmanned Swarm
Authors: Zhao Yue , Yao Yuan , He Tong , Zhou Xingshe , Shen Bo
Published: March 2023

Unmanned swarm systems are now employed in a wide range of applications. Agriculture, commerce, and the military will all benefit from the advancement of unmanned swarm technology. To support multiple applications, the scenarios should have a standardized description and definition as the system input, allowing for more precise and specific processing and resource planning. In this paper, the Scenario description Language for Unmanned swarm (SL4U) is introduced in order to implement the unmanned swarm scenario. The scenario is divided into environment and task. We describe the environment, including the task space, target and home locations, and the initial settings of the unmanned swarm. In terms of tasks, we have identified four categories of tasks, four temporal relationship constraints, the event handler, as well as other elements.The dual engines of parsing and micro-embedded collaboration we developed will handle the SL4U. We employ a search and rescue scenario in both simulation and physics to test SL4U. Through the processing of the dual engines, the unmanned swarm's search and rescue operations in a predefined environment are accomplished successfully. As scenarios are developed, the benefits of SL4U will become more apparent, as it will drastically reduce personnel costs and experimentation time.
Multistability Analysis and Adaptive Feedback Control on a New Financial Risk System
Authors: Johansyah Muhammad Deni , Sambas Aceng , Vaidyanathan Sundarapandian , Benkouider Khaled , Sulaiman Ibrahim Mohammed
Published: March 2023

This study presents the findings of a new financial risk system (FRS) with one absolute function and two quadratic nonlinearities. The rich dynamic behaviors of the new financial risk system are discussed analytically and numerically through stability analysis, phase portrait, bifurcation diagram, Lyapunov exponent, multistability and coexisting attractors. In addition, a new financial risk system with two quadratic nonlinear-ities and one absolute function shows multistability and coexistence of chaotic attractors. Using adaptive feedback control, we established a new control law for fully synchronising the proposed chaotic financial systems with itself. To conclude, some numerical simulation was presented using MATLAB to illustrate the efficiency of the designed method.
Decision trees as feature selection methods to characterize the novice panel’s perception of Pinot noir wines
Authors: An Jingxian , Kilmartin Paul A. , Young Brent R. , Deed Rebecca C. , Yu Wei
Published: March 2023

Consumer perceptions and purchase behaviours are typically determined by phenolic influenced sensory attributes such as astringency, bitterness, and sourness. Marketing strategies would be more effective if machine learning methods assisted winemakers in understanding the chemical parameters that influence panellists' sensory evaluations of Pinot noir wines. Nowadays, feature selection methods such as random forest classifier and neighbourhood component analysis are utilised to select important factors. In the meantime, decision trees are utilised in regression or classification models as opposed to feature selection methods. In this study, decision trees were able to identify the relationships between sensory attributes and important chemical parameters in Pinot noir wines from diverse product extrinsic cues (regions of origin, vintages and price points) and novice panels. Decision trees not only could be utilised to build soft sensors but also work as effective feature selection methods, which could inspire winemakers to make proper Pinot noir wines. With the help of principal component analysis and scatter plots, it was discovered, for instance, that total phenolics, total flavanols, total flavan-3-ols, and total tannins in wines could considerably contribute to astringency, bitterness, and sourness and that total anthocyanin could contribute to clarity regardless of diverse Pinot noir wine or novice panels.
Antioxidant dihydrolipolic acid protects against aluminum-induced toxicity in Alzheimer's model
Authors: SANAJOU Sonia , Yirün Anil , Demirel Göksun , Cakir Deniz Arca , Sahin Gönül , Erkekoglu Pinar , Baydar Terken
Published: March 2023

Dihydrolipoic acid (DHLA) is a natural antioxidant that is recognized as being useful in combating metal toxicity and oxidative stress. It can protect cells from environmental contaminants and may be beneficial in treating neurodegenerative diseases by protecting against oxidative damage and chronic inflammation. Therefore, this study aimed to investigate the possible neuroprotective effects of DHLA against aluminum-induced toxicity in an in vitro Alzheimer’s disease (AD) model. The study focused on the glycogen synthase kinase3 (GSK3) pathway, and the Wnt signaling. A differentiated SH-SY5Y cell line model of AD was developed, and the study groups were as follows: control, Al, DHLA, Al-DHLA, AD, AD-Al, AD-DHLA, and AD-Al-DHLA. The impact of DHLA on oxidative stress parameters was evaluated, and GSK3 pathway was evaluated by measuring GSK3-β, human serine/threonine-protein phosphatase PP1-alpha catalytic subunit (PPP1CA), protein phosphatase 2A (PP2A) levels, and human RAC-alpha serine/threonine-protein kinase (AKT1). The Wnt signaling pathway was evaluated by measuring canonical Wingless and Int-1/β-catenin (Wnt/β-catenin) on different study groups. Exposure to DHLA reduced oxidative stress by dramatically lowering reactive oxygen species levels, protecting against protein oxidation, and limiting malonaldehyde production. Additionally, the total antioxidant capacity of DHLA-treated groups increased drastically. Furthermore, upregulation of Wnt signaling and downregulation of GSK3 pathways were observed in the groups treated by DHLA. Overall, the neuroprotective effects of DHLA, especially by reducing oxidative stress and regulating key imbalanced pathways in AD disease, make it a good candidate to be added to AD patients' treatment regimens.
Robust Sliding Mode Control for Two-Wheel Robot Without Kinematic Equations
Authors: Mousaei Arash , Gheisarnejad Meysam , Khooban Mohammad Hasan
Published: March 2023

This article proposes solutions to control the balance of a two-wheel robotic system in the presence of uncertainties in the dynamic equations and without the need for kinematic equations. To do this, the dynamic equations of this system are first transferred to the error area and then these equations are divided into two completely independent subsystems, under excitation, and full excitation. In the following, two completely different sliding mode controllers are presented to control the under-excitation subsystem, which can make this subsystem asymptotically stable in the presence of structural and non-structural uncertainties. After that, a sliding mode control is proposed to control the entire excitation subsystem, making this subsystem asymptotically stable in the presence of existing uncertainties. Since these two subsystems are completely independent of each other, proving their global asymptotic stability provides proof of the global asymptotic stability of the closed-loop system. The isolation of two-wheel balancing robot subsystems eliminates the need to use kinematic equations, resulting in structural uncertainties not affecting the tracking accuracy of closed-loop system state variables. Finally, to verify the performance of the proposed controllers and compare their performance results, three-stage simulations are implemented on the two-wheel Balance robotic system. Mathematical proofs and simulation results show the optimal performance of the proposed solutions.
Nitrate removal from aqueous solutions with sodium alginate/quaternary branched polyethylenimine/carboxylated multi-wall carbon nanotube
Authors: khademian Maryam , Sarrafi Yaghoub , Tajbakhsh Mahmood , Hasantabar Vahid
Published: March 2023

One concern in recent years is increasing the amount of nitrate in drinking water. This study investigated nitrate adsorption using sodium alginate/quaternary branched polyethylenimine /carboxylated multi-wall carbon nanotube nanocomposite beads. The structure of nanocomposite beads was characterized with Field emission scanning electron microscopy images (FE-SEM), Energy dispersive X-ray mapping (EDX), X-ray diffraction spectroscopy (XRD), Fourier transform-infrared spectroscopy (FT-IR), and Thermogravimetric analysis (TGA). Several experiments were performed to optimize adsorption conditions, adsorption isotherms, kinetics, and reusability of the synthesized nanocomposite beads. Temkin and Freundlich isotherms, and the pseudo-first-order kinetic model, provided the best fit for the experimental adsorption data. Under optimal conditions, the nitrate removal efficiency was 72%. The results demonstrated that the introduced nanocomposite beads are pH-stable, have low-cost preparation, are recyclable at least for twelve adsorption-desorption cycles, and are safe.
A study on the model of robust fractional order extended Kalman filtering with gross error
Authors: Zhao Jiaxing , Wang Jian , Han Houzeng , Jiang Tao
Published: March 2023

Based on the Huber function, this paper constructs a model of the robust fractional order extended system (RFEKF), which effectively reduces the influence of the gross error. Firstly, by analyzing the abnormal observation characteristics of gross error in fractional order system, the RFEKF is constructed by an equivalence weight matrix of introducing redundancy and the statistical characteristics of predicted residuals, and thus it adjusts the gain matrix and obtains the optimal solution through iteration. Secondly, combined with the RFEKF, the robust estimation of the observed values with gross error is carried out, which further improves the real-time operational efficiency of the model. Finally, simulation experiment and practical implementation are carried out to verify the proposed RFEKF model in GNSS positioning and navigation field, the results show that the RFEKF can still navigate correctly in the case of gross error, compared with EKF, the accuracy of navigation positioning can be significantly improved.
Text Sentiment Analysis with Event Information
Authors: Zhang Xue , Zhao Hui , Chang Jingjing , Ying Di
Published: March 2023

In recent years, the research of text sentiment analysis has recognized the importance of associating events with sentiment polarity, that is, the sentiment triggered by events can be detected through direct or indirect modeling of events. However, there are two problems with the current study: (1) There is no publicly available dataset; (2) Existing models fail to better model event information. To address these issues, we created an event-based sentiment analysis dataset (ESCO), where each sentence is labeled with event triplet representation and sentiment polarity labels. Based on this dataset, we propose a sentiment analysis model Event-GCN-Attention (EGA) based on event-enhanced semantics. We use Bi-directional Long-Short Term Memory (Bi-LSTM) and Graph Convolutional Network (GCN) to model event information. At the same time, Bi-LSTM is used to model the context information of sentences, and multi-polarity orthogonal attention is used to capture the difference attention weight under different polarities, which can be used as a significant discriminant feature. Finally, we assign different weights according to the importance of event information and sentence context information and combine them to get the final sentence representation. These representations can be used to guide downstream sentiment analysis tasks. Studies show that our proposed model outperforms existing baseline models in our constructed dataset. The dataset (ESCO) is publicly available on https://github.com/cjj-sunshine/event-based-implicit-sentiment-analysis.