bluuebunny/crossref_metadata_2025_split huggingface dataset:
Formal Regional Delineation A case study on water availability scenario on overall Bangladesh
Authors: das Prosenjit , Anika Anika tahasin. 
Published: January 2023

Abstract
Water is an essential element for the existence of human being. A huge portion of people in the whole world is dependent on the access of water. Bangladesh is a developing country with high population and land ratio in the whole world. The availability of water varies in different administrative area due to their different geographical characteristics and topographical characteristics. In this study, the 64 administrative areas of Bangladesh is delineated into different regions on the basis of five main criteria such as rainfall, temperature, population density, no of water bodies available, total cultivable lands has been selected to identify the condition of water availability in the whole Bangladesh. The required database has been collected from Bangladesh Bureau of Statistics (BBS 2011) and has been analyzed through composite index method to categorize the whole Bangladesh according to the availability of water. The data reliability is checked through the level of skewness. Then the acquired data is classified by using the equal class interval method and the arithmetic mean method. According to the value of skewness the equal class interval method has been accepted for the study.
Identification of potential crucial genes associated with breast cancer using bioinformatics analysis and experimental verification
Authors: Ni Xiaoyu , Yang Haibing , Liu Chao 
Published: January 2023

AbstractIn this study, we identified a total of 492 DEGs, including 176 up-regulated and 316 down-regulated DEGs. GO analysis showed that the up-regulated DEGs are mainly involved in cell division, nucleus and protein binding. The down-regulated DEGs mainly involve immune response, extracellular exosome and calcium ion binding. Top five enriched pathways obtained in the KEGG pathway analysis are pathways in cancer, cytokine-cytokine receptor interaction, focal adhesion, the PI3K-akt signaling pathway and ECM-receptor interaction. Top 10 up-regulated hub genes identified from the PPI network are AURKA, CDC6, CCNA2, CDCA8, NUSAP1, CDK1, CCNB1, CCNB2, UBE2C, HMMR. The top 10 down-regulated hub genes are IGF1, JUN, FGF2, CXCL12, KIT, PTGS2, LEP, EGF, EGR1, FOS. Survival analysis showed that the expression levels of WIF1 (P = 0.019) and HMMR (P = 0.027) were correlated with the prognosis of patients with breast cancer. In addition, gene expression and methylation analysis showed that COL11A1 is highly expressed and hyper-methylation. MMP1 is highly expressed and hypo-methylation. SFRP1, WIF1 is low expressed and hyper-methylation in breast cancer. In terms of tumor purity and immune cell infiltration analysis, Interestingly, it is found that HMMR makes a strong connection with B Cell, CD8+T Cell, neutrophil, dendritic cell (P <0.05). MMP1 was negtively associated with tumor purity. The use of bioinformatics can effectively analyze the data of the gene chip, obtain the inherent information of the organism, and provide the basis for the next experiment. This study identifies key genes and pathways in breast cancer that will advance our understanding of molecular mechanisms.
Dissemination of the high-risk clone ST147 carbapenem-resistant Klebsiella pneumoniae from a local tertiary care hospital in the Republic of Korea
Authors: Park Jungsun , Shin Eunkyung , Kim Min-Kyeong , Joo Seongjae , Jeong Hyun Ju , Kim Jin Seok , Yoo Jaeil , Kim Junyoung 
Published: January 2023

Abstract
Background : The emergence of carbapenem-resistant Enterobacterales (CRE) infections is rapidly increasing and represents a serious public threat. In 2020, a total of 16,883 carbapenemase-producing Enterobacterales strains were collected; among these isolates, 21 strains were repeatedly isolated in a local tertiary care hospital.
Methods : Antimicrobial susceptibility testing was performed using the broth microdilution method. All 21 strains of CRKP were analyzed by PFGE after XbaI digestion. The 21 CRKP strains were sequenced on the Illumina Miseq and Oxford Nanopore GridION platforms.
Results : These 21 CRKP isolates showed an identical antimicrobial resistance profile, such as resistance to ampicillin, carbapenems, cephems, chloramphenicol, fluoroquinolone, macrolides and trimethoprim/sulfamethoxazole. Based on whole-genome analysis, these 21 CRKP isolates shared a common genetic structure (ISAba125-IS630-blaNDM-1-bleMBL) and harbored additional resistance determinants (blaOXA-1, blaCTX-M-15, blaSHV-11, blaSHV-67, aac(6')-Ib-cr, qnrS1, OqxA, OqxB, catB3, mph(A), sul1, and dfrA12) and mutations in the quinolone resistance-determining regions of gyrA (S83I) and parC (S80I). These isolates belonged to the ST147 and KL64 capsular types, which were carried on IncFIB replicon plasmids. The 21 CRKP strains collected from one hospital were divided into five PFGE patterns, and they were closely related with a minimum similarity value of 95.2%. These isolates were found to be highly related based on the presence of between 2 and 27 SNPs.
Conclusions : These findings indicate that NDM-1-producing K. pneumoniae ST147 may have been introduced via a common source, implying nosocomial transmission; furthermore, continuous monitoring is necessary to prevent endemic transmission.
Classification of FLT3 Inhibitors and SAR Analysis by Machine Learning Methods
Authors: Zhao Yunyang , Tian Yujia , Pang Xiaoyang , Li Guo , Yan Aixia , Shi Shenghui 
Published: January 2023

Abstract
FMS-like tyrosine kinase 3 (FLT3) is a type III receptor tyrosine kinase, which is an important target for anti-cancer therapy. In this work, we conducted a structure-activity relationship (SAR) study on 3867 FLT3 inhibitors we collected. MACCS fingerprints, ECFP4 fingerprints, and TT fingerprints were used to represent the inhibitors in the dataset. A total of 36 classification models were built based on support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGBoost), and deep neural networks (DNN) algorithms. Model 3D_3 built by deep neural networks (DNN) and TT fingerprints performed best on the test set with the highest prediction accuracy of 85.83% and Matthews correlation coefficient (MCC) of 0.72 and also performed well on the external test set.
In addition, we clustered 3867 inhibitors into 11 subsets by K-Means algorithm to figure out the structural characteristics of the reported FLT3 inhibitors. Finally, we analyzed the SAR of FLT3 inhibitors by RF algorithm based on ECFP4 fingerprints. The results showed that 2-aminopyrimidine, 1-ethylpiperidine, 2,4-bis(methylamino)pyrimidine, amino-aromatic heterocycle, [(2E)-but-2-enyl]dimethylamine, but-2-enyl, and alkynyl were typical fragments among highly active inhibitors. Besides, three scaffolds in Subset_A (Subset 4), Subset_B, and Subset_C showed a significant relationship to inhibition activity targeting FLT3.
Natural Amenities and Neo-Hobbesian Local Public Finance
Authors: Petach Luke 
Published: January 2023

Abstract
A revenue maximizing local government must obey a migration constraint when levying taxes. Using this insight, I develop a simple theory of taxation that suggests natural amenities are a key factor influencing local tax rates. Natural amenities confer rents to residents which governments and interest groups compete to extract. Revenue maximizing local tax rates are increasing in the level of natural amenities, increasing in moving costs, and decreasing in households’ reservation utility. Using data on natural amenities and taxation for US counties, I find that local tax rates are in-fact increasing the level of natural amenities. Finally, I suggest an alternative interpretation of the “tax revolts” of the late 1970’s. Rather than an attempt to constrain Leviathan, local property tax reform (such as California’s Proposition 13) and restrictions on housing supply are the outcome of competition over amenity rents in which property owners successfully capture a monopoly position at the expense of other social groups including renters and local government.
JEL Codes: H21, H71, D72
A SLR on Deep Learning Models Based on Textual Information For Effort Estimation in Scrum
Authors: Sembhoo Avinash , Gobin-Rahimbux Baby 
Published: January 2023

Abstract
Deep Learning (DL) is a branch of Machine Learning where models are developed using neural networks made of several layers for prediction. DL models have been developed to predict effort estimation in software development. This paper presents a review of works which discuss the use of DL models for effort estimation for Scrum. The various textual information, the different DL techniques used. The methodology used for the review is snowballing. It was found that Deep-SE, a model which combines LSTM and RHN has been developed specifically for effort estimation. Also, a number of other DL techniques which have been experimented are discussed. A number of performance metrics were identified and also the perfomance of the various models were compared.
Identification and analysis of lipid metabolism-related genes in allergic rhinitis
Authors: Tao Qilei , Zhu Yajing , Wang Tianyu , Deng Yue , Liu Huanhai , Wu Jian 
Published: January 2023

Abstract
Background:Studies have shown that the lipid metabolism mediator leukotriene is associated with the pathogenesis of allergic rhinitis (AR). The aim of this study was to identify key lipid metabolism-related genes (LMRGs) related to the diagnosis and treatment of AR.
Material and methods: AR-related expression datasets (GSE75011, GSE46171) were downloaded through the Gene Expression Omnibus (GEO) database. First, weighted gene coexpression network analysis (WGCNA) was used to get AR-related genes (ARRGs). Next, between control and AR guoups in GSE75011, differentially expressed genes (DEGs) were screened, and DEGs were intersected with LMRGs to obtain lipid metabolism-related differentially expressed genes (LMR DEGs). Protein‒protein interaction (PPI) networks were constructed for these LMR DEGs. Hub genes were then identified through stress, radiality, closeness and edge percolated component (EPC) analysis and intersected with the ARRGs to obtain candidate genes. Biomarkers with diagnostic value were screened via receiver operating characteristic (ROC) curves.Differential immune cells screened between control and AR groups were then assessed for correlation with the diagnostic genes, and clinical correlation analysis and enrichment analysis were performed. Finally, reverse transcription-polymerase chain reaction(RT‒qPCR) was made on blood samples from control and AR patients to validate these identified diagnostic genes.
Results: 73 LMR DEGs were obtained, which were involved in biological processes such as metabolism of lipids and lipid biosynthetic processes. Sixty-six ARRGs and 22 hub genes were intersected to obtain four candidate genes. Three diagnostic genes (LPCAT1, SGPP1, SMARCD3) with diagnostic value were screened according to the AUC > 0.7, with markedly variant between control and AR groups. In addition, two immune cells, regulatory T cells (TReg) and T follicular helper cells (TFH), were marked variations between control and AR groups, and SMARCD3 was significantly associated with TFH. Moreover, SMARCD3 was relevant to immue-related pathways, and correlated significantly with clinical characteristics (age and sex). Finally, RT‒qPCR results indicated that changes in the expression of LPCAT1 and SMARCD3 between control and AR groups were consistent with the GSE75011 and GSE46171.
Conclusion: LPCAT1, SGPP1 and SMARCD3 might be used as biomarkers for AR.
Making Impact on Common Financial Factors Affecting Liquidity Ratio Based on Greedy Approach Through Price Movement in Stock Market
Authors: Prakash P. , Krishnaprabha S. , Sundararajan S. 
Published: January 2023

Abstract
This research article focused on discovering appropriate liquidity risk concerns in the financial Sector. Primarily, it deals with the appropriate liquidity factors that affect financial performance services pertained to several liquidity crises and the respective liquidity measures. Liquidity is considered the primary constraint. The Liquidity Ratios are the defective condition of calculating the financial performance services and their respective status. For fulfilling this performance service status prediction, this research use calculation for consistency index procedure. Liquidity index-based predictions have collaborated concerning the price movement in the stock market. The Liquidity will affect the trading and market transparency whenever the price moment varies. To control this trading and not market transparency of liquidity index be employed the greedy approach for estimating the most factor affected by the liquid index. Hence, this research elaborates on the greedy approach today with 25 essential financial factors. Each Panther will have combined with the tractor-confirmed liquidity crisis whenever the factors of liquidity crisis are combined with the actual financial factor, the minimum and maximum Degree of matching are calculated. This calculation determines the factors that affected the Liquidity concerning their exact, Plugin, subsume, and fail condition. Eventually, the search concludes the determination of factors affecting Liquidity concerning the actual finance factor and liquidity crisis. Finally, the result was concluded with the Degree of matching and their efficiency of finding liquidity factors with a successful reasonable result. Based on the Degree of matching result, this research found the actual reason for Liquidity with the help of various financial factors.
A comparison of the diagnostic ability of magnified narrow band imaging and blue laser/light imaging for sessile serrated lesions
Authors: Kobayashi Reo , Yoshida Naohisa , Morinaga Yukiko , Hashimoto Hikaru , Tomita Yuri , Inoue Ken , Hirose Ryohei , Dohi Osamu , Murakami Takaaki , Inada Yutaka , Morimoto Yasutaka , Itoh Yoshito 
Published: January 2023

Abstract
Purpose
The diagnosis of sessile serrated lesions (SSL) and SSL with dysplasia (SSLD) using blue laser/light imaging (BLI) has not been well evaluated. We analyzed the diagnostic ability and specific endoscopic findings of BLI for SSL and SSLD compared to those of narrow band imaging (NBI).
Methods
We retrospectively reviewed 476 resected lesions from the cecum to the descending colon, which showing Type1 of the Japan NBI Expert Team (JNET) classification completely or partially with magnified NBI or BLI between 2014 and 2021 in our institution. The comparison of the NBI and BLI groups after matching was performed regarding the diagnostic ability of SSL and SSLD. The endoscopic findings of SSL on NBI and BLI were defined as expanded crypt opening (ECO) or thick and branched vessels (TBV) based on previous reports. Additionally, those of SSLD originally defined as network vessels (NV) and white dendritic change (WDC) were analyzed.
Results
After matching, the sensitivity of lesions with either ECO or TBV for diagnosing SSL and with those with either WDC or NV for diagnosing SSLD in the NBI/BLI were 97.5%/98.5% (p = 0.668) and 81.0%/88.9% (p = 0.667). Regarding the comparison of specific endoscopic findings between the SSLD and SSL, there were significant differences in WDC (66.4% vs. 8.6%, p < 0.001), NV (55.3% vs. 1.4%, p < 0.001), and either WDC or NV (86.8% vs. 9.0%, p < 0.001).
Conclusions
There was no difference in the diagnostic ability of NBI and BLI for SSL and SSLD. NV and WDC might be useful for diagnosing SSLD.
Primary adenoid cystic carcinoma in the lung: reporting a recurrent case at an advanced stage and mini-literature review.
Authors: Bendari Ahmed 
Published: January 2023

Abstract
Introduction: Primary adenoid cystic carcinoma (ACC) of the lung only account for less than 0.2% of all primary lung tumors. ACC in lung usually arises from the peribronchial glands and they are usually proximally located which makes it often challenging for surgical resection
Case presentation: A 65-year-old woman who was diagnosed with adenoid cystic carcinoma in 2017 at another institution and treated with lobectomy. In 2021, she presented at our hospital with frequent cough and dyspnea at rest and on exertion. Chest radiography showed bronchial obstruction and lung atelectasis, for stent placement for symptomatic relief. Repeated chest CT in 2022 showed progression of the tumor involving beyond the lung parenchyma into pleura and diaphragm Finally, the patient had left posterolateral thoracotomy, extra pleural pneumonectomy, En bloc pericardiectomy and En bloc resection of left diaphragm. Now she is on lung cancer surveillance with chest CT every 6 months. Last chest CT did not show any residual tumor or recurrence.
Conclusion: Despite its rarity, primary ACC of the lung should be well recognized by the pathologist and clinicians to make accurate diagnosis. . Although ACC of the lung usually has an indolent clinical course and behavior, recurrences are relatively frequent. The prognosis depends on the most dominant histological pattern, tumor staging and surgical margin status.
A core-shell electrospun scaffold including extracellular matrix and chitosan to promote articular cartilage tissue regeneration
Authors: Movahedi Mehdi , Karbasi Saeed 
Published: January 2023

Abstract
Electrospinning is known as a versatile technique for articular cartilage tissue regeneration (ACTR) due to its excellent potential to produce a fibrous scaffold that mimics the extracellular matrix (ECM) of native tissue. However, there is a need to promote the biological performance of scaffolds maintaining their mechanical strength. In this study, a core-shell polyhydroxybutyrate (PHB)-starch/halloysite nanotubes (HNTs) @ ECM-chitosan (Cs) scaffold was prepared via the coaxial electrospinning method. The results exhibited a narrower fiber diameter of up to 164 ± 24 nm with an appropriate pore size and porosity after incorporating Cs and ECM. Moreover, the core-shell scaffold showed an enhanced Young’s modulus up to 4.45 ± 0.1 MPa that could support chondrocyte cell growth. After that, the wettability and in vitro degradability of the core-shell scaffold were induced due to the hydrophilic nature of shell components. Also, chondrocyte cells had more viability and attachment on the core-shell structure proving the potential of core-shell fibers for biomedical applications. In conclusion, the results showed that the core-shell structured PHB-starch/HNTs @ ECM-Cs could be a suitable candidate for further trial towards ACTR.
WITHDRAWN: The bridge between the neurological and psychological visual response interpretations using Rorschach's test
Authors: Khalifa Samar 
Published: January 2023

Abstract
This paper is an application of Rorschach’s test case diagnosis. A case study interview from resources for clinicians for the treatment of depression in adults was included in the clinical evaluation. Diagnostic steps were taken through coding the interview sentences from the patient’s response to investigate the neuropsychological factors in verbal-visual behavior diagnosis.
Utilization of Jengkol Peel (Pithecellobium jiringa) as an Adsorbent of Iron Metal
Authors: Fildza Mutiara , Rohmatullaili Rohmatullaili , Oktasari Ade 
Published: January 2023

Cellulose, which has the active group OH, is found in Jengkol peel. Jengkol peel has the potential to be utilized as an adsorbent for Iron (Fe) metal because it contains these active groups. The FT-IR spectrophotometer instrument was used to confirm the presence of the -OH group in the Jengkol peel adsorbent, which was observed at the peak of the OH vibration at wave number 3293 cm1. Utilizing NaOH (0.1 M), the active group was activated. With an adsorption percentage of 96.24%, pH 7 was the optimum adsorption pH. With an adsorption percentage of 99.20%, 25 minutes was indeed the optimum contact time. With an adsorption capacity value of 8.581 mg/g, the binding of Fe metal by the adsorbent active group occurs in the complex formation mechanism, it was indicating a relatively high adsorption efficiency.
Effect of Driver Response on Efficiency of Vehicular Communication using Penalty Cost Function (EVCPCF)
Authors: Iskandarani Mahmoud Zaki 
Published: January 2023

Background and Objective:
This study examines and takes into account three key timing factors that have an impact on the effectiveness of human-machine interfaces (HVI). A threshold-based mechanism is created to account for both cooperative driving and advanced vehicle control system (AVCS) scenarios. For AVCS and cooperative driving, the developed model takes into account on-board machine interface time, human interface time, and transmission time.

Methods:
A threshold function that represents the penalty cost of a slow driver reaction is presented in order to enable adaptive intelligence, enhance HVI design, and increase vehicle safety. The Penalty Cost Function (PCF) is used to make vehicle control systems intervene and take control in situations where the driver responds slowly to safety and warning messages. Additionally, this study demonstrates that AVCS-based vehicular systems are more responsive overall and are less impacted by the PCF function than cooperative systems.

Results:
The mathematical models created through this work allowed for a limiting efficiency value and capping for each driving scenario, according to comparative plots. This will improve the creation of more reliable control systems as part of a vehicle's mechatronics, impacting how vehicles communicate with one another in a cooperative setting. MATLAB simulation was used to verify the mathematical model. The simulation covered two limiting cases of 0.33 and 0.5 and used incrementing numbers of vehicles (10, 20, 30, 40, 50) to check the impact of increasing vehicle numbers on communication efficiency and examine whether both AVCS and AVCS with cooperative will have close levels and converge at limiting values.

Conclusion:
The successfully completed simulation demonstrated that throughput decreased as the number of vehicles increased, although in the limiting case, both scenarios and the driving system changed virtually by the same percentage.