bluuebunny/crossref_metadata_2025 huggingface dataset:
Chromone-embedded Peptidomimetics and Furopyrimidines as Highly Potent SARS-CoV-2 Infection Inhibitors: A Molecular Docking Study
Authors: Senobari Zahra Shakibay , Hosseini Mohsen Masoumian , Teimouri Mohammad Bagher , Rezayan Ali Hossein , Samarghandian Saeed , Hekmat Azadeh
Published: February 2023

Background: Coronavirus disease 2019 (COVID-19) is a respiratory illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Controlling the spread of viruses is one of the main concerns of pharmaceutical companies. Looking at the viral infection cycle can lead to the development of effective drugs. Since cell entry and replication of SARS-CoV-2 play a crucial role in the life cycle of CoV, this study investigated how derivatives of chromone compounds inhibit viral entry and prevent viral replication.
Method: In this study, the inhibitory effect of chromone-embedded peptidomimetics and furopyrimidines on 7BZ5 (spike receptor binding domain) from Severe acute respiratory syndrome CoV 2, Homo sapiens, and 6LU7 (main protease domain) from Bat SARS-like CoV were investigated via molecular docking. The crystal structure of these proteins was taken from the Protein Data Bank (PDB). The ligand binding interaction option was used to determine the inhibition site. For structure preparation, unwanted molecules were removed, and the 3D structure was protonated and energetically minimized using Molecular Environment Operation (MOE) software. The chromone derivatives were first designed in three dimensions, and their energy was minimized using MOE 2019. Then, the online software SwissADME was used to calculate the molecular drug likeness. Lipinski and Benigni-Bossa's rule evaluated chromone derivatives, and toxicity was calculated using Toxtree v3.1.0 software. Then the compounds with pharmacological properties were selected for molecular docking. Interactions were assessed by molecular docking with MOE 2019, and the S score was calculated.
Result: The pharmacokinetic tests showed that the chromone derivatives of the peptidomimetic family had acceptable pharmacokinetic activity in the human body. Some compounds exhibited pronounced medicinal properties, including Ch-p1, Ch-p2, Ch-p6, Ch-p7, Ch-p12, and Ch-p13. Molecular docking also showed that these compounds bound with high affinity to the main protease of SARS-CoV-2. Ch-p7 had the highest binding energy, with an S-score of -8.7370. This compound was bound to Gln189 via a benzene ring and Asn142 via three bonds. Therefore, it is likely that the inhibitory property of this compound is more effective than the other compounds in this study.
Conclusions: For the virus to replicate in the host cell, SARS-CoV-2 must bind to the receptor via the receptor-binding domains of the S1 subunit and then be proteolytically processed by the main protease. In the present study, the inhibition of viral replication was investigated, and the results showed that chromone derivatives were effective. Compared to other studies on this subject, chromone derivatives from the peptidomimetic family had a high inhibitory effect.
Evaluation of the antidermatophytic activity of potassium salts of N-acylhydrazinecarbodithioates and their aminotriazole-thione derivatives
Authors: Ciesielska Anita , Kowalczyk Aleksandra , Paneth Agata , Stączek Paweł
Published: February 2023

Nowadays, dermatophyte infections are relatively easy to cure, especially since the introduction of orally administered antifungals such as terbinafine and itraconazole. However, these drugs may cause side effects due to liver damage or their interactions with other therapeutics. Hence, the search for new effective chemotherapeutics showing antidermatophyte activity seems to be the urge of the moment. Potassium salts of N-acylhydrazinecarbodithioates are used commonly as precursors for the synthesis of biologically active compounds. They were also found to act as antimicrobials, including activity against Candida spp. strains. Keeping that in mind, the activity of a series of five potassium N-acylhydrazinecarbodithioates (1a-e) and their aminotriazole-thione derivatives (2a-e) was evaluated against a set of pathogenic, keratinolytic fungi, but also against some Gram-positive and Gram-negative bacteria. All tested compounds were found non-toxic for L-929 and HeLa cells, with the IC30 and IC50 values assessed in the MTT assay above 128 µg/mL. The compound 5-amino-3-(naphtalen-1-yl)-4,5-dihydro-1H-1,2,4-triazole-5-thione (2d) was found active against all fungal strains tested. Scanning Electron Microscopy (SEM) revealed inhibition of mycelium development of T. rubrum cultivated on nail fragments and treated with 2d 24 h after infection with fungal spores. TEM (Transmission Electron Microscopy) observation of mycelium treated with 2d showed ultrastructural changes in the morphology of hyphae. Finally, the RNA-seq analysis indicated that a broad spectrum of genes responded to stress induced by the 2d compound. In conclusion, the results obtained confirm the potential of N-acylhydrazinecarbodithioate derivatives for future use as promising leads for the development of new antidermatophyte agents.
Expression of a deep-sea bacterial laccase from Halomonas alkaliantarctica and its application in dyes decolorization
Authors: Wang Jingjing , Zhang Ran , Zhu Guilan , Wang Lingling , Bai Han , Qian Yong , Zhou Xiazhen , Yin Qiang , Zhang Yan
Published: February 2023

Introduction Laccase is a copper-containing polyphenolic oxidase widely found in bacteria, archaea, fungi, animals, and plants. As a green biocatalyst with considerable potential for numerous environmental and industrial applications, the enzyme production efficiency of laccase in nature is low, and the cost is high.
Purpose To examine the characterization and potential applications of laccase in this study, a novel laccase from Halomonas alkaliantarctica (LacHa) was cloned and heterologously expressed in Escherichia coli.
Results To achieve heterologous and efficient laccase expression, a bacterial laccase gene designed as LacHa from Halomonas alkaliantarctica of deep sea was cloned and expressed in E. coli. The results showed that the optimum temperature and pH of the enzyme reaction were 45°C and 7.5. The 100 μM Cu2+ and Fe2+ ions had the strongest stimulatory effect on laccase activity, the surface-active agent SDS and organic solvent 5% ethanol had opposite effect. EDTA, and 5% DMSO have no effect on LacHa activity. The activity of LacHa was enhanced 1.5 fold by chloride at concentrations lower than 500 mM, and 57.6% of its initial activity remained in the reaction system containing 1000 mM NaCl. Furthermore, LacHa showed decolorization rates ranging from 90.28% to 100% for indigo carmine and two azo dyes without mediators, with wide pH (5.0-9.0) and temperature (25-65°C) ranges.
Conclusions In the present study, LacHa was expressed and showed unusual properties, suggesting its great application potential in the treatment of textile industries or environmental applications.
VANET Security Enhancement in Cloud Navigation with Internet of Things Based Trust Model in Deep Learning Architecture
Authors: Gnanajeyaraman Gnanajeyaraman , U Arul , G Miichael , A Selvakumar , S Ramesh , T Manikandan
Published: February 2023

Many intelligent services are available for developing sensor-based vehicle-to-vehicle communication systems through vehicular ad hoc network (VANET). Although neighbour locating and interconnected vehicle sensor processes have been improved by geographic routing methods. However, reliability and data continuity among data routing are crucial for developing transportation systems due to the high level of mobility and realistic environment.The vehicles' wireless communication is also unrestricted and open, making them more vulnerable to security threats and compromising data for improper uses.This research propose novel technique in security improvement in VANET with vehicle cloud based navigation and trust model using deep learning techniques. the vehicle network navigation is carried out using cloud network integrated with IoT and its data transmission to the base station is analysed. then the navigated vehicle security is enhanced using trust based federated transfer quadratic authentication system. the experimental analysis is carried out based on number of vehicles in network as well as its security enhancement. the parameters analysed are throughput, data transmission rate, latency, network traffic analysis, scalability. the proposed technique attained throughput of 95%, data transmission rate of 67%, latency of 56%, network traffic analysis of 76%, scalability of 75%
Effects of Transcranial Electrical Stimulation to the Right Posterior Parietal Cortex on Physical Control Responses
Authors: Mitsutake Tsubasa , Nakazono Hisato , Taniguchi Takanori , Yoshizuka Hisayoshi , Sakamoto Maiko
Published: February 2023

The posterior parietal cortex (PPC) plays an important role in postural stability by adapting to changes in input from the visual, vestibular, and proprioceptive systems. However, it is little known whether transcranial electrical stimulation (tES) of the PPC affects reactive postural responses. The purpose of this study was to investigate changes in physical control responses to anodal and cathodal transcranial direct current stimulation (tDCS) and transcranial random noise stimulation (tRNS) of the right PPC using a simultaneous inertial measurement unit. The joint movements of the lower limb of 33 healthy volunteers were measured while standing on a soft-foam surface with eyes closed, during various stimulation modalities. These modalities included anodal, cathodal tDCS, and sham stimulation in Experiment 1 and tRNS and sham stimulation in Experiment 2. The results showed that cathodal stimulation significantly decreased the joint angular velocity in the hip rotation, ankle inversion-eversion, and abduction-adduction directions compared to anodal or sham stimulation in Experiment 1. In contrast, there were no significant differences in physical control responses with tRNS stimulation in Experiment 2. These findings suggest that tES of the right PPC may modulate physical control responses; however, the effect depends on the stimulus modality.
Semi-Harmonic Maps from Tori and Sphere into Sphere
Authors: Aminian Mehran
Published: February 2023

The aim of this paper is considering semi-harmonic maps from a flat and non flat torus into a sphere, and between 2-spheres. At first we introduce semi-harmonic maps and then we consider these maps between tori and sphere.
MSC2010: 58E20; 53C43
Numerical analysis of thorax injury caused by the blunt impact of SIR-X sponge grenade
Authors: Chen Chaoming , Zhao Fadong , Ma Zongmin
Published: February 2023

To effectively assess the injury risk of the blunt impact of the SIR-X sponge grenade on the human thorax, In this paper, we used a numerical simulation technique to test the non-lethal kinetic energy projectiles that blunt impact on the Hybrid Ⅲ 50th dummy model. By simulating the effect of the L5 projectile on the thorax of the Hybrid Ⅲ 50th dummy model, about NATO standard AEP-99 (2021 edition), the thoracic displacement curves of the dummy model in three testing conditions were obtained in the validation corridors. The idea of replacing the finite element model of the human body with the Hybrid Ⅲ 50th dummy finite element model was proposed. We considered the difficulty in obtaining data due to the large deformation of the contact position when the SIR-X sponge grenade impacts the dummy's thorax. We proposed a mathematical model to predict the impact injury of the human thorax using the rib displacement measured by the rib displacement sensor of the Hybrid III 50th dummy. We simulated the SIR-X sponge grenade blunt impacting the dummy model's thorax. The measured rib displacement was used to predict and analyze the injury risk of the human thorax, providing a specific data reference for practical application.
Energy optimization in additive manufacturing based on cluster-aware enhanced spider monkey optimization
Authors: Bhuvaneswari R.Bhuvaneswari , N. Nagabhooshanam , M Chandralekha , D Sendil Kumar , Babu Gadde.Raghu , A.K. Chakravarthy , Praveen Neti , P. Ganeshan , Kannan Sathish
Published: February 2023

Additive manufacturing (AM) is a leading technology used in many fields, such as medicine and aerospace, to make prototypes and functional part fabrication. The energy requirements of the AM process are considerable and have serious consequences for environmental health and long-term viability. Research in both the private and public sectors has shifted its attention to the problem of predicting and optimising the amount of energy that AMs use.Material state, process operation, part and process design, working environment, and other factors all play a role in this problem. Existing research shows that the design-relevant aspects have a significant role in AM energy consumption (EC) modelling in reality, although this topic has not received enough attention. As a result, this research starts by analysing the design relevant features (DRFs) from the perspective of energy modelling.Before production, these features are normally decided by part designer (PD)and process operator (PO).An ANN driven cluster-aware enhanced spider monkey optimization algorithm (CAESMOA) is suggested to improve the energy utility relying on the novel modelling methodology. Deep learning is used to improve the global best of CAESMOA and solve a number of concerns, including speeding up search times. In order to verify the accuracy of the suggested modelling technique, DRFsare obtained from a functioning AM system in the production line. In our research, we use a normalisation strategy to filter out extraneous information. At the same time, optimization has been performed to direct PD and PO towards design and decision modifications that lessen the energy requirements of the specified AM system under investigation.The effectiveness of the suggested approach is examined, and the efficiency is also contrasted with that of other current methods. These statistics showed that our approach to energy optimization in AM delivered the most trustworthy outcomes.
Sound and rhythm impact on soil biofilm-forming ability
Authors: Fičko Karlo , Palijan Goran
Published: February 2023

Modern civilization is producing alarming levels of noise which often is developed in soil proximity having an opportunity to influence soil organisms. Yet, its effects on soil microbial communities are unexplored. To investigate the effects of different sound types we tested classical music of Mozart and Beethoven, construction, and road works noise and rhythm played on drums at the environmentally relevant sound levels and time intervals. All tested sounds impacted soil biofilm forming ability but differently between soil and land use types. Agricultural fields were less impacted by noise. Interestingly only regular rhythm stimulated all tested samples. Such results are the first evidence that noise can change the functional properties of soil microbial communities and that its effects are dependent on the type of sound.
Selective concurrence of the long non-coding RNA MALAT1 and the Polycomb Repressive Complex 2 to promoter regions of active genes in MCF7 breast cancer cells
Authors: Arratia Felipe , Fierro Cristopher , Blanco Alejandro , Fuentes Sebastian , Nahuelquen Daniela , Montecino Martin , Rojas Adriana , Aguilar Rodrigo
Published: February 2023

Background:The collaboration between the Polycomb Repressive Complex 2 (PRC2, an epigenetic modifier) and long non-coding RNAs (lncRNAs) has become a paradigm for gene regulation studies. In cancer cells, the MALAT1 lncRNA has arisen as a key partner for PRC2. However, it is unknown whether this partnership occurs genome-wide at the chromatin level, as most of the studies focus on single -usually repressed- genes. Due to the genomic binding properties of both macromolecules, we wondered whether there are binding sites shared by PRC2 and MALAT1.
Results: Using public genome-binding datasets for PRC2 and MALAT1 derived from independent ChIP- and CHART-seq experiments performed in the breast cancer cell line MCF7, we searched for regions containing PRC2 and MALAT1 overlapping peaks. Peak calls for each molecule were performed using MACS2 and then overlapping peaks were identified by bedtools intersect. Using this approach, we identified 1,293 genomic sites where PRC2 and MALAT1 concur. Interestingly, 54,75% of those sites are within gene promoter regions (<3000 bases from the TSS). These analyses were also linked with transcription profiles of MCF7 cells, obtained from public RNA-seq data. Hence, it was determined that MALAT1 and PRC2 can concomitantly bind to promoters of genes that are actively transcribed in MCF7 cells. Gene ontology analyses revealed an enrichment of genes related to categories including cancer malignancy and epigenetic regulation.
Conclusions: By re-visiting occupancy and transcriptomic data we identified a novel subset of genes, including key cancer-related genes, where MALAT1 and PRC2 may collaborate to control transcription.
Recommendations for an Early Safety Assessment in General Practice Training
Authors: Woods Amelia , Pitot Michelle , Elliot Taryn , Benson Jill
Published: February 2023

Assessing the safety of new GP registrars is critical for the safety of patients, the registrar themselves and for their practice. The aim of an Early Safety Assessment (ESA) is to assess safety in independent practice, competency in self-assessment, appropriate help-seeking, knowledge and practice. The aim was to explore what should be included in an ESA, and the acceptability and feasibility of recommendations. A literature review, environmental scan, review of documents and ESA data from participating Australian GP Regional Training Organisations (RTOs), interviews with Directors of Training from participating RTOs, and a Delphi consensus were conducted. The study found that ESAs vary, both in content and timing. Recommendations were developed for their utility and feasibility. The ESA should end when the registrar is either flagged or found to be ‘safe to practice with the supervisor available most of the time’. There are barriers that can be addressed and facilitators to be encouraged so an ESA can be successfully implemented.
Integrative network pharmacology and molecular docking to reveal the mechanism of Jinqiaomai tablet on asthma
Authors: Liu Zhen , Qiu Shi , Liu Wen
Published: February 2023

Background:Jinqiaomai tabletis widely used to treat asthma in China. Despite this, it is less certain how Jinqiaomai tablet worked.Objective:To explore the active components and molecular mechanism of Jinqiaomai tablet treating asthma via network pharmacology and molecular docking.Methods:Through searching the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), we identified the active components and targets of Jinqiaomai tablet (JQM). Pathogenic genes related to asthma were retrieved from DisGeNET and GeneCards database.In turn, the common target genes between JQM and asthma were obtained.Also, GO and KEGG enrichment analysis were conducted on the online platform PANTHER for the common target genes. By utilizing the STRING database, an interaction network for the JQM-asthma common target protein was established. Based on the Cytohubba package, hub genes were calculated. In addition, molecular docking was conducted to confirm whether the targeted compounds bind to potential therapeutic targets.Results:In total, 15 active components and 208 targets of Jinqiaomai tablet were identified. 3701 pathogenic genes related to asthma were obtained, including 3697 from GeneCards database and 110 from DisGeNET database accompanying 106 repetitions. Then, 128 common target genes between JQM and asthma were obtained. GO and KEGG enrichment analysis of the common target genes were performed. An interaction network for the JQM-asthma common target protein was established and the top ten hub genes were AKT1, VEGFA, PTGS2, MMP9, CASP3, TNF, IL6, EGF, IL1B and NFKBIA. The affinity of the molecular docking between the targeted compound and the potential therapeutic target was analyzed, and the ligands and the overall pictures of partial results of molecular docking above were showed.Conclusion:The active components and molecular mechanism of Jinqiaomai tablet treating asthma were revealed via network pharmacology and molecular docking.
Synthesis and Characterization of Some Transition Complexes with 4- [2-(2-chlorobenzylidene)hydrazinyl]-7H-pyrrolo[2, 3-d]pyrimidine: Antimicrobial and Cytotoxic Activity
Authors: Bagul Abhay , Gaikwad Digamber , Patil Yogesh
Published: February 2023

Ten new transition metal complexes (1–10) with 4-[2-(2-chlorobenzy-lidene)hydrazinyl]-7H-pyrrolo[2,3-d]pyrimidine (HPPHoCB) was prepared. 4-[2-(2-Chlorobenzylidene)hydrazinyl]-7H-pyrrolo[2,3-d]pyrimidine of general formula [C13H10ClN5], was prepared through the condensation reaction of 2-chlorobenzaldehyde with pyrrolopyrimidinehydrazide. The characterization of the new formed compounds was done by physico-chemical studies, conductance measurement, magnetic susceptibility data, 1H-NMR, UV-Visible, ESR, FT(IR) spectroscopy and elemental analysis. In addition, the structure of the complexes Cr(III), Fe(II), Co(II), Ni(II) and Cu(II) has been determined by X-ray diffraction method. The prepared HPPHoCB ligand act as bidentate ligand and coordinate with central metal ions through nitrogen of azomethine and pyrrolo groups. The low molar conductance values in nitrobenzene indicate that the metal complexes are non-electrolytes in nature. The magnetic moments and electronic spectral data suggest octahedral geometry for the Cr(III), Mn(II), Co(II), Ni(II), and Fe(II) complexes, tetrahedral geometry for Zn(II), Cd(II), Hg(II) complexes and square planar for Pd(II) and Cu(II) complexes. The HPPHoCB ligand and its metal complexes were screened for antimicrobial activities against two Gram-positive bacteria (Staphylococcus aureus MTCC 96 and Bacillus subtilis MTCC 121), two Gram-negative bacteria (Escherichia coli MTCC 1652 and Pseudomonas aeruginosa MTCC 741), and Fungus (Aspergillus niger, Aspergillus flavous and Fusarium species) as well as for cytotoxic studies against Artemia salina . The synthesised metal complexes were found more active against both bacterial as well as fungi in antimicrobial and cytotoxic screening test than that of HPPHoCB ligand.
Autologous Platelet Gel Healing Effects on Cutaneous Leishmaniasis Wounds
Authors: Shadmand Enayatollah , Solhjoo Kavous , Taghipour Ali , Tayer Akbar Hashemi , Sadeghi Fatemeh , Meshkin Ahmad
Published: February 2023

Background and Objectives

Autologous platelet gel (APG) has healing growth factors and is used in most surgeries to treat a variety of tissue defects. This study was conducted to investigate the healing effects of APG on cutaneous leishmaniasis (CL) wounds.

Materials and Methods

In this clinical trial, 15 patients with CL were recruited and followed for two months. The patients had more than one cutaneous wound, one of which was examined as the control and the other one as the intervention wound. APG was applied to the intervention wounds once a week, up to eight times. The response to treatment was evaluated base on the histopathology analyses.

Results

The use of APG on the wounds in the intervention group was associated with complete and faster healing in 66% of the cases and partial healing in 34% of the wounds. During study, none of the control wounds were completely healed. Following eight weeks treatment of CL lesions with APG, the inflammatory process in the epidermis, and dermis were decreased significantly.

Conclusion

This study demonstrated for the first time that APG can be effective in wound healing and removal of scars caused by CL.
Trial registration
IRCT, IRCT20190212042694N1. Registered 20 February 2019, https://en.irct.ir/trial/37522
Some results on maximum likelihood from incomplete data: finite sample properties and an improved M-estimator for resampling method
Authors: Surya Budhi
Published: February 2023

This paper presents some results on the classical maximum likelihood (ML) parameter estimation from incomplete data. Finite sample properties of incomplete-data conditional observed information matrices are established. They possess positive def-initeness and the same Loewner partial ordering as the expected information matrices do. An explicit form of the observed Fisher information (OFI) is derived for the calculation of standard errors of the ML estimates. It simplifies Louis (1982) general formula for the OFI matrix. To prevent from getting an incorrect inverse of the OFI matrix, which may be attributed by the lack of sparsity and large size of the matrix, a monotone convergent recursive equation for the inverse of OFI matrix is developed which in turn generalizes the algorithm of Hero and Fessler (1994) for the Cramér-Rao lower bound. To improve the estimation, in particular when applying repeated sampling to incomplete data, a robust M-estimator is introduced. A closed form sandwich estimator of covariance matrix is proposed to provide the standard errors of the M-estimator. By the resulting loss of information presented in finite-sample incomplete data, the sandwich estimator produces smaller standard errors for the M-estimator than the ML estimates. In the case of complete information or absence of re-sampling, the M-estimator coincides with the ML estimates. Application to parameter estimation of a finite-mixture of Markov jump processes is discussed to verify the results. The simulation study confirms the accuracy and asymptotic properties of both the ML estimates and M-estimator.
2020 MSC: 60J20, 60J27, 62M09, 62H30
Population structure and phylogeographic history of wild soybean (Glycine soja) have implications for its conservation
Authors: Meng Jing , Li Xue-Jiao , Zhao Yan , He Shuilian
Published: February 2023

Glycine soja Sieb. & Zucc., the wild ancestor from which the important crop plant soybean was bred. G. soja provides important germplasm resources for the breeding and improvement of cultivated soybean crops, however the species is threatened by habitat loss and fragmentation, and is experiencing population declines across its natural range. Understanding the patterns of genetic diversity in G. soja populations can help to inform conservation practices. Additionally, wild soybean has a wide distribution across the Sino-Japanese Floristic Region, and therefore provides an opportunity to investigate the effects of fluctuations in the Quaternary climate on the current genetic structure of plant species in this region. In this study, we analyzed the genetic diversity and differentiation of G. soja populations and investigated the phylogeographic history of the species. We obtained 147 wild soybean accessions collected from 16 locations across the natural range of the species from China, Korea and Japan. Samples were analyzed using SLAF-seq (Specific-Locus Amplified Fragment Sequencing), and we obtained a total of 56,489 highly consistent population SNPs. Our results suggested that wild soybean harbored relatively high diversity and that populations of the species were highly differentiated. The 147 wild soybean individuals clustered into two groups: lineage I comprised five populations from Northern and Central China as well as a population from Japan. Lineage II comprised the other 11 populations, which had Northeast Chinese, Korean and Yangtze River origins. Analysis of gene flow suggested that historical migrations of wild soybean may have occurred, from south to north across the East-Asia land-bridge. The phylogeographic history of wild soybean provides us with new insights into the migration patterns of herbaceous plants across the Sino-Japanese Floristic Region.
Deep Learning Neural Network (DLNN) based classification and optimization algorithm for Organ Inflammation Disease diagnosis
Authors: Basha Alavudeen , Ali Azath Mubarak , P Parthasarathy , Tayfour Omer Elsier , Changalasetty Suresh Babu , Shuja Muhammed
Published: February 2023

Diagnostic image volume and complexity in healthcare system increases in rapid pace where available human proficiency may not sufficient for interpreting this much capacity of image data. Machine learning approaches exposed excessive potential to knob huge amount of two-dimensional annotated images of common illnesses from large databases. Deep learning imitates human for extracting knowledge from dataset and favourable to data scientists for accumulating, analysing, interpreting and predictive modelling. In this paper organ inflammation disease is addressed with Deep Learning Neural Network (DLNN) based classification scheme is incorporated to diagnose or prognoses the patient from severity, based on their historical database. In pandemic environment collecting histopathology tissue score is time consuming process due to a smaller number of physician availability, by implementing proposed DLNN algorithm suits for collecting organ inflammation score and categorizing its brutality by classification of pancreatitis, duodenum and appendix. In order to achieve accuracy and sensitivity of various stages soreness DLNN based algorithm is developed and it supports by classifying the datasets.
Eulertigs: minimum plain text representation of k-mer sets without repetitions in linear time
Authors: Schmidt Sebastian , Alanko Jarno N.
Published: February 2023

A fundamental operation in computational genomics is to reduce the input sequences to their constituent k-mers. For maximum performance of downstream applications it is important to store the k-mers in small space, while keeping the representation easy and efficient to use (i.e. without k-mer repetitions and in plain text). Recently, heuristics were presented to compute a near-minimum such representation. We present an algorithm to compute a minimum representation in optimal (linear) time and use it to evaluate the existing heuristics. Our algorithm first constructs the de Bruijn graph in linear time and then uses a Eulerian-cycle-based algorithm to compute the minimum representation, in time linear in the size of the output.
Development and validation of a deacetylation regulators-related prognostic signature in gastric cancer
Authors: Lei Chunyu , Xu Juan , Zhang Chengli , Liang Xiaolong
Published: February 2023

Mounting evidences have indicated the effects of the tumor micro-environment (TME) on gastric cancer (GC) prognosis, tumorigenesis and metastasis. However, there is no reliable biomarker that could effectively predict the prognosis and estimate the immune feature of GC patients. Herein, we obtained the expression data from The Cancer Genome Atlas (TCGA) and the National Center for Biotechnology Information (NCBI) databases to construct a deacetylation regulator associated risk signature that could be used as a predictor of survival outcome and immune feature of GC patients. A total of 13 genes were screened out from the univariate-LASSO-multivariate analyses to generate the risk signature based on the regression coefficients. The risk signature exhibited robust prognostic abilities in both training set and testing set, and this association remained significant in the multivariate analysis after controlling for age, gender, T, N, M or Stage. Functional analyses indicated that the risk signature showed a correlation with immune feature of GC patients. Further analyses indicated the risk signature could be used to estimate the infiltration immune cells and predict the immunotherapy response of GC. Taken together, our risk signature could predict prognosis and immune feature of CC, which might provide crucial clues to formulate individualized treatment and provides promising novel biomarkers for immunotherapy.
Real-Time Text Extraction from Malaysian Road Direction Signs Using Dashboard Camera
Authors: Lim Wan Chin , Shah Noraisyah Mohamed , Mahiyiddin Wan Amirul Wan Mohd
Published: February 2023

The road direction sign, which serves as a navigation tool, aids the driver in travelling on the road. A real-time text extraction from road direction signs is investigated, using input video images acquired from a dashboard camera while driving on Malaysian roads. This paper proposed a three-stage approach for real-time text extraction: (i) traffic direction signboard detection; (ii) text detection; and (iii) text recognition. In the direction signboard detection, the YOLOv5s model was applied and achieved a precision of 97%and a recall of 96%. In the text detection stage, three text detection models, EAST, DB and PAN, were investigated to select the best text detection model. The DB model is chosen with the highest IoU of 0.8238 and the shortest inference time of 0.1938s. In the text recognition stage, four models (Pytesseract, CRNN, RobustScanner and ABINet) are employed to perform evaluation and pick the best model. The CRNN is selected with the lowest character error rate of 5.85%, the highest accuracy of 97.84%, and a fast inference time of 0.324s. The proposed models, YOLOv5s, DB, and CRNN are combined to run sequentially in the real-time system during daytime conditions. It is performed by using a laptop that is equipped with a GPU and programmed in Python. The real-time text extraction system can run at an adaptive frame rate of 6.5 frames per second with an accuracy of 97%.
Multi-label emotion classification of Tweets with transformer models
Authors: Hettikankanamge T. L. , Pinidiyaarachchi A. J.
Published: February 2023

Analysis and classification of emotions expressed in social media content such as tweets have been useful for numerous commercial and social purposes for tasks like hate speech detection. Emotion classification of social media content has been performed using traditional techniques such as Recurrent Neural Networks (RNN) and Multivariate Long Short Term Memory (LSTM) in the past, which can be outperformed by the new transformer models. The ‘SemEval-2018 Task 1: Affect in Tweets’ (Mohommad et al. 2018) presents a challenge on multi-label classification of emotions expressed in tweets into 11 sentiment classes. The datasets given for this challenge are used in this work to explore the accuracy of the transformer models against other techniques used by the competitors of the particular challenge. Additionally the transformer models (BERT, RoBERTa and XLM RoBERTa) were compared with each other on their performance based on accuracy and speed. The best performing BERT-large model which is trained using bert-large-uncased tokenizer has shown a multi-label accuracy (Jaccard Index) which is higher than the sixth recorded score in the SemEval-2018 Task 1 competition, F1-micro which is higher than the best F1 score recorded.
Informality: Family Ties and Retirement Income
Authors: Göktuna Bilge Öztürk , Dayangaç Renginar
Published: February 2023

This paper suggests a demand side analysis of informal employmentcharacterised by incompliances with labour tax regulation, using a general equilibrium model with overlapping generations. A public social insurance provide benefits to formal employees in retirement, while we allow for an informal insurance mechanism for informal employees through a social norm of mutual support. The objective of the paper is to evaluate impact of auditing policy and social norms on growth and social welfare. We define the private transfer rate to the informal population and provide an analysis on the impact of social norms to wage levels, growth and welfare.
Real-Time Detection of Large Scale Stealthy DDoS Attacks Targeting Financial Institutions
Authors: Duan Qi Duan Qi , Al-Shaer Ehab Al-Shaer Ehab
Published: February 2023

DDoS attackers targeting the financial services firms can cause chaos by disrupting key public services including payment processing and intra-bank links, manipulating markets to influence stock prices, and exposing firms to extremely large losses in earnings, capital, productivity, consumer confidence, etc. State-of-the-art DDoS detectors are mostly based on black listing and rate limiting which are not effective against large scale stealthy (low and slow) attacks. The objectives of this paper is to detect large scale stealthy DDoS attacks targeting financial institutions using data-driven security analytics which can (1) protect application-level services by detecting large scale stealthy DDoS attacks as early as possible, (2) automate the traffic/log analysis process, and (3) provide the guidance for real-time mitigation. The major results of the paper include (1) the data-driven approach to identify features for DDoS detection based on real-life dataset and the methodology to identify the cross-correlation between features, (2) the information theoretical and statistic analysis to develop a model of the normal behavior of users, and (3) the summary of experimental results based on the data from real bank web log and the comparison with a real DDoS attack dataset. We believe that these technical approaches can provide the defense-in-depth against large scale stealthy DDoS attacks targeting financial institutions.
ChatGPT Performs on the Chinese National Medical Licensing Examination
Authors: Wang Xinyi , Gong Zhenye , Wang Guoxin , Jia Jingdan , Xu Ying , Zhao Jialu , Fan Qingye , Wu Shaun , Hu Weiguo , Li Xiaoyang
Published: February 2023

INTRODUCTION:
ChatGPT, a language model developed by OpenAI, uses a 175 billion parameter Transformer architecture for natural language processing tasks. This study aimed to compare the knowledge and interpretation ability of ChatGPT with those of medical students in China by administering the Chinese National Medical Licensing Examination (NMLE) to both ChatGPT and medical students.
METHODS
We evaluated the performance of ChatGPT in two years' worth of the NMLE, which consists of four units. At the same time, the exam results were compared to those of medical students who had studied for five years at medical colleges.
RESULTS
ChatGPT’s performance was lower than that of the medical students, and ChatGPT’s correct answer rate was related to the year in which the exam questions were released.
CONCLUSION
ChatGPT’s knowledge and interpretation ability for the NMLE were not yet comparable to those of medical students in China. It is probable that these abilities will improve through deep learning.
The impact of patient factors and tumor characteristics on language neuroplasticity in left hemispheric diffuse gliomas prior to surgical resection
Authors: Chang Wei-Han , Wei Kuo-Chen , Chen Pin-Yuan , Chen Yi-Chun , Wu Yah-Yuan , Tsai Hong-Chieh , Chen Mei-Hui , Chao Yi-Ping , Chen Ko-Ting
Published: February 2023

Purpose
Language networks are reorganized during glioma growth, leading to varying language performance in patients with gliomas located in language-eloquent areas. Therefore, pre-treated language performance reflects the neuroplasticity potential. Different domains of language processing, such as speech expression, repetition, and comprehension, involving different neural networks. We analyzed the effects of patient factors and tumor characteristics on the pre-treated performance to investigate neuroplastic potential of different language domains.
Methods
Patient age, sex, education level, tumor grade, language pathway involvement, T1 contrast enhanced (C+), and FLAIR (T2) volume were selected as variables. The correlation with abnormal language performance was verified using univariate and multivariate logistic regression.
Results
In total, 104 patients were enrolled in this study. 44% of patients had repetitive abnormalities, 34.9% had comprehension abnormalities, and 32.1% had expression abnormalities. The proportion of language pathway involvement and normal language performance was 60% in grade 2 and 3 gliomas and 16% in grade 4 gliomas. Tumor grade (p = 0.006) and T2 volume (p = 0.008) were associated with abnormal performance in the expressive domain, education level (p = 0.004) and T1 C + volume (p = 0.049) in the repetitive domain, and education level (p = 0.013), T2 volume (p = 0.011), and tumor grade (p = 0.089) in the comprehensive domain.
Conclusion
Different clinical and radiological factors affected the abnormal performance of the three language domains, indicating their functional connectivity and neuroplastic potential are inherently varied. The dynamic interactions between patient factors, tumor characteristics, and language processing should be considered when resecting left hemispheric gliomas.
Effectiveness of Indocyanine Green Flourescence Imaging in Resection of Hepatoblastoma
Authors: Shen Qiyang , Liu Xingyu , Pan Sirui , Li Tao , Zhou Jianfeng
Published: February 2023

Objective
The present research aimed to analyze the application of indocyanine green (ICG) fluorescence contrast technique in the resection of hepatoblastoma (HB) in children, and to discuss the use of ICG in the surgery of HB and the value of guidance.
Methods
We retrospectively analyzed the data of 23 children with HB resected by using ICG fluorescence contrast technique at the Children’s Hospital of Nanjing Medical University from June 2020 to September 2022, including 16 boys and 7 girls, aged 5 days to 80 months. The patients were administered with an ICG injection of 0.1mg/kg around 24 hours before surgery. The surgical margin was detected by real-time fluorescence imaging and confirmed by postoperative pathology.
Results
All primary lesions showed bright fluorescence in 23 HB cases. 22 had clear borders with normal liver tissue, while one neonatal case showed no difference between tumor and background. 13 anatomic resection and 10 non-anatomic resection were performed with ICG fluorescence navigation. The surface of the residual liver was scattered with multiple tumor fluorescence, which was then locally enucleated according to the fluorescence. 22 isolated specimens were dissected and fluorescently visualized. Pathology identified deformed, vacuolated and densely arranged hepatocytes resembling pseudo-envelope changes without tumor residual, due to the compression of the tissue at the site of circumferential imaging.
Conclusion
The ring ICG fluorescence imaging of HB indicates the tumor resection boundary effectively, especially in multiple lesions cases.
A potential Entomological and epidemiological drivers for Reemergence of Human African Trypanosomiasis in Ethiopia after 55 Years
Authors: Waldetensai Abate , Abose Ebise , Getachew Abebe , Tadesse Henok , Meharenet Behabilom , Hidoto Moges , Difabachew Hailemariam , Eukubay Araya , Kassahun Alemayehu , Gonfa Geremew , Wakgari Tesfa , Manaye Nigus , Hailemichael Tsegalem , Kore Kokeb , Asfaw Netsanet , Hassen Jemal , Mengesha Wondu , Tsega Daniel , Abera Adugna , Bokicho Belachew , Lemango Fiseha , Mamecha Tihitina , Teka Frezer , Achamyeleh Kelelaw , Melese Tariku , Mulugeta Yimer , Wossen Mesfin , Regassa Feyisa , Tasew Geremew , Ali Abraham
Published: February 2023

Background: Sleeping Sickness, Human African Trypanosomiasis (HAT) is a vector- borne disease caused by Trypanosoma brucei (T.b). Sleeping sickness in Ethiopia was reported in 1967 for the first time. Recently in Southern parts of Ethiopia, in August 2022, five (5) cases of sleeping sickness (T. b. rhodesiense) were confirmed. Following this outbreak, the current investigation was aimed to identify the entomological and epidemiological drivers for the reemergence of HAT outbreak and recommend appropriate interventions. Methods: A cross sectional study design with descriptive data analysis was used. Tsetse fly collection and blood samples from cattle Animal were taken. NGU and bio-conical traps were used to determine the distribution (density and abundance) of the vector. About 10μl of blood was collected from the marginal ear vein of 301 cattle animals using the heparinized microhematocrit capillary. The parasite detection was carried out through vector dissection under binocular stereo-microscope (magnification of 60X) and microscopic examination from serum of Animals using the Buffy coat method. Results: A total of 329 tsetse flies were captured and identified to Glosina (G.) palidipes 259 (60.4%) and Glossina fuscipes 70 (16.3%). 188 (51.1%) of tsetse flies were collected from Dembagofa with 94 apparent density. Among all captured Tsetse fly, 39 (11.8%) of Tsetse were fed with high female apparent density in eachecological variation: wood land (51), Bush land (20) and grass land (11). Overall, the apparent density of tsetse fly was high in Wood land (93): G. pallidipes (76.5) and Bush land (36.5). Among all examine cattles for the presence of parasite, 9 cattles were detected positive with an overall prevalence of 3%. T. congolense 6 (2%) and T. vivax 1 (0.3%) with 2 (0.7%) suspected brucei. The parasite prevalence Trypanosoma was 4 (4.6%) in poor body a condition (Bcs) cattle. The animals in age range 5 - 9 years were infected high with 7 (5.3%) prevalence. Conclusion: The current study revealed that there are high-risk factors that predispose the community to Human African Trypanosomiasis (HAT) due to the presence of two different species of Tsetse flies and many animal reservoirs. The transmissions of Human African trypanosomiasis (HAT) are related to environmental, Vector, and human factors. Further geographically expanded investigation should be conducted throughout the country.
Vegetation responses to pathogen-induced tree loss – Swedish elm and ash forests revisited after 32 years
Authors: Brunet Jörg , Felton Adam , Hedwall Per-Ola
Published: February 2023

Invasive fungal pathogens are an increasing problem globally and can cause devastating effects on forest ecosystems. In this study we contrast vegetation surveys in eutrophic elm (Ulmus glabra) and ash (Fraxinus excelsior) forests in southern Sweden, conducted just prior to the arrival of Dutch elm disease (DED) in 1989, and then again in 2021, several years after ash dieback (ADB) began. Mean cover and species richness (α-diversity) of the upper tree layer strongly decreased from 1989 to 2021. In the lower tree layer, loss of elm and ash was compensated by an increase in other tree species. The cover and richness of the shrub layer increased in previously elm-dominated stands but not in ash-dominated stands. Canopy recovery was mainly dominated by shade-tolerant tree species which, especially in the previously ash-dominated stands, implies a successional shift. The extensive loss of canopy cover in elm stands caused a larger change in species composition and increased compositional variability (β-diversity) between plots when compared to the ash stands. The direction of the changes in tree layer composition between the surveys varied with soil moisture and nutrient availability. While beech increased in less eutrophic plots, more nutrient rich plots changed towards hornbeam or small-leaved lime, and wetter plots turned towards alder and bird cherry. Hence, our results indicate increased compositional diversity and alternative successional pathways for community reorganization following DED and ADB. Future research will reveal if these pathways will later merge or further split.