bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydro-geochemistry and irrigation water quality of groundwater in Chhattisgarh plain central India
Authors: Lal Bharat , Nayak Vinod , Shukla Abhishek Kumar , Kumar Pavan
Published: October 2022

The current study was conducted with sampling of eighty-four groundwater sample which was used for analyzing various physico- chemical properties in groundwater to assess the status of irrigation water quality and their hydro-geochemistry.For this purpose, different ionic concentration pH, EC, TDS, TH, Ca2+, Mg2+, Na+, K+, Cl−, SO42−, CO32− and HCO3− were determine in groundwater and used to calculate the various irrigation water quality parameters like SAR, Na %, RSC, MHR, KR, PI%, PS and RSBC. The groundwater sample pH was ranged from 7.9 to 9.3 with having electrical conductivity of 90 µS/cm to 2000 µS/cm. Among the all-sampled groundwater 2.38%, 1.19%, 5.95%, 16.67%, and 2.38% water samples were unsuitable for irrigation water due to having high loading of PI, KR, MHR, RSC and PS value, respectively. The ionic concentration orders werefound in terms of cations Ca2+> Na+> Mg2+> K+ and anions HCO3−> Cl−> SO42−in groundwater. The piper trilinear diagram suggested Ca (Mg)- HCO3−, Ca (Mg)-Cl− and mixed type water was dominated in the study area. The Gibbs and other bivariate plot were indicated that the silicate weathering and ion exchange phenomenafrom rock water interaction was mainly responsible for the different ion’s sources in groundwater instead of evaporite and carbonate dissolutions.
Systematic literature review on nutritional habits of 0–6-year-olds with early childhood caries (ECC)
Authors: Antoniou Sophie , Antoniou Sophie , Naeem Samah
Published: October 2022

This systematic review aims to highlight potential areas of importance within a child’s diet that play a primary role in their development of early childhood caries. Caries is a multifactorial disease, influenced by a number of factors including, oral hygiene, degree of mineralisation of teeth, salivary flow rates in addition to dietary factors.
This review will specifically focus on the nutritional aspect involved in the pathogenesis of caries. Targeting the main dietary risk factors will aid in the prevention of ECC and severe early childhood caries (SECC), with an overall aim to reduce the DMFT (Decayed Missing and Filled Teeth) in children. This is of particular relevance to the secondary dentition of these children, as those with ECC are much more likely to develop caries and subsequent infections in their adolescence and adulthood also (1), further underlining the immense significance of prevention.
Background information:
There is universal recognition that consumption of free sugars and fermentable carbohydrates heavily precipitates the development of caries. However, a holistic approach to diet including all food groups needs to be investigated to devise an easy to follow and nutritionally balanced guide for caregivers to utilise when providing nourishment to children under 6. Examining the diet as such, gives a further understanding of its holistic contribution to the development of caries, rather than examining sugar intake and frequency alone.
Aims:
To construct a dietary proposal for public dissemination based on nutritional and dental recommendations for children under 6.
Objectives:
To evaluate the various dietary habits implicated in the development of ECC and how they interact with the indirect factors that also predispose children under 6 to ECC.
Management of Alternaria blight (Alternaria alternata) of tomato through novel combined formulations of fungicides
Authors: SHARMA RATAN LAL , Ahir R. R. , Sharma Astha , Ghasolia R. P. , Kumar Naresh , sharma pinki
Published: October 2022

The present investigation aimed to find the most efficient and novel combined formulation of fungicides belonging to triazole and strobilurin groups for managing Alternaria blight (Alternaria alternata) of tomato under open field conditions. Efficacy of seven fungicides like propineb, hexaconazole, propiconazole, azoxystrobin, mancozeb, tebuconazole + trifloxystrobin and carbendazim + mancozeb was evaluated in vitro and in vivo. In vitro study was carried out through poisoned food technique, while field experiment was conducted for two consecutive years (2017 and 2018) at Jobner (Jaipur), India. Two foliar sprays were applied at 45 and 60 days after transplanting (DAT), and disease intensity was recorded at 75 DAT. Hexaconazole (@ 300 and 500 ppm) completely inhibited mycelial growth, followed by tebuconazole + trifloxystrobin (@ 500 ppm). In field conditions, two foliar sprays of hexaconazole (@ 0.2%) at 15 days intervals provided maximum disease reduction (79.74%) with increased fruit yield (88.51%) over control, followed by tebuconazole + trifloxystrobin (76.33% and 82.35%, respectively). Alternaria blight is one of the significant biotic stresses that limit crop productivity and grower's prosperity. Systemic fungicides, particularly triazoles, play a substantial role in preventing infection by Alternaria sp. Thus, two foliar sprays of hexaconazole (0.2%) at 15 days intervals reduced disease intensity effectively with increased fruit yield and profitability.
U-Sleep: resilient to AASM guidelines
Authors: Fiorillo Luigi , Monachino Giuliana , Meer Julia van der , Pesce Marco , Warncke Jan , Schmidt Markus , Bassetti Claudio , Tzovara Athina , Favaro Paolo , Faraci Francesca
Published: October 2022

AASM guidelines are the results of decades of efforts aiming at standardizing sleep scoring procedure, in order to have a commonly used methodology. The guidelines cover several aspects from the technical/digital specifications, e.g., recommended EEG derivations, to detailed sleep scoring rules accordingly to age. In the context of sleep scoring automation, deep learning has demonstrated better performance compared to many other techniques. Usually, clinical expertise and official guidelines are fundamental to support automated sleep scoring algorithms in solving the task. In this paper we show that a deep learning based sleep scoring algorithm may not need to fully exploit the clinical knowledge or to strictly follow the AASM guidelines. Specifically, we demonstrate that U-Sleep, a state-of-the-art sleep scoring algorithm, can be strong enough to solve the scoring task even using clinically non-recommended or non-conventional derivations, and with no need to exploit information about the chronological age of the subjects. We finally strengthen a well-known finding that using data from multiple data centers always results in a better performing model compared with training on a single cohort. Indeed, we show that this latter statement is still valid even by increasing the size and the heterogeneity of the single data cohort. In all our experiments we used 28528 polysomnography studies from 13 different clinical studies.
Software Fault Prediction Using Deep Learning Techniques
Authors: Batool Iqra , Khan Tamim Ahmed
Published: October 2022

Software fault prediction (SFP) techniques are used to identify faults at the early stages of the software development life cycle (SDLC). We find machine learning techniques as commonly used techniques for SFP as compared to deep learning methods which can produce more accurate results. Deep learning offers exceptional results in a variety of domains such as computer vision, natural language processing, speech recognition, etc. In this study, we use three deep learning methods, namely, Long Short Term Memory (LSTM), Bidirectional LSTM (BILSTM), and Radial Basis Function Network (RBFN) to predict software faults and compare our results with existing models to show how our results are more accurate. In our study, we use Chidamber and Kemerer (C&K) metrics-based datasets to conduct experiments and test our proposed algorithm. We conclude that LSTM and BILSTM perform better whereas RBFN is faster in producing the required results. We use k-fold cross validation to do the model evaluation. Our proposed models provide a more accurate and efficient SFP mechanism to software developers.
Identification of an Autophagy-Related Signature for Predicting Prognoses and Immune Activity in Pancreatic Cancer metastasis
Authors: Deng Qianxi , Wu Linju , He Jin , Wu Fan , Jiang Zheng
Published: October 2022

Background
Although autophagy is crucial in cancer metastasis, the role of genes in the autophagy process in pancreatic cancer metastasis and prognosis remains uncertain. The study intended to identify ARGs associated with cancer metastasis and construct an ARGs prognostic model for pancreatic cancer patients.
Methods
Differentially expressed ARGs (DEARGs) were identified in GEO (the Gene Expression Omnibus) database and HADb (the Human Autophagy Database). TCGA (The Cancer Genome Atlas) database and real time-PCR was applied to validate the expression of these genes. Univariate and LASSO Cox regression analyses were applied to screen OS (overall survival) related DEARGs (p < 0.05) as hub genes. A 5-ARGs prognostic model was constructed. Five ARGs were further analyzed to recognize underlying small-molecule drugs in the L1000FWD database and performed by GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses. Moreover, CIBERSORT and ESTIMATE were performed to match immune-infiltrating cells between the primary and metastasis groups. Correlation analysis demonstrated potential regulatory pathways between 5 ARGs and significant immune cell subsets.
Result
We filtrated twenty-two DEARGs and screened five OS-related ARGs (CASP1, RHEB, CHMP2B, MYC, HDAC6) as hub genes. A 5-ARGs prognostic model was built, calculating risk scores and dividing the low- and high-risk groups by the median. The low-risk group was markedly longer OS than the high-risk group in TCGA-PAAD cohort. Moreover, the 5-ARGs prognostic model was more precise than the clinicopathological characteristics. Function enrichment analysis showed that 5 ARGs were involved in the autophagy-related pathway. We identified several potential small-molecule compounds targeting ARGs. The ESTIMATE analysis showed the metastasis group was a significantly lower ESTIMATE score than the primary group. CIBERSORT analysis showed a higher percentage of Treg cells in the metastasis group. In the PCA analysis, immune cell subsets were signally diverse between the two groups. In addition, Treg cell was statistically associated with RHEB (r = -0.67, p = 0.049), CHMP2B (r = -0.7, p = 0.035), MYC (r = -0.75, p = 0.019).
Conclusion
Our results demonstrated that ARGs might participate in the metastasis process of pancreatic cancer by regulating autophagy and immune infiltration, further identifying potential drugs for pancreatic cancer. Simultaneously, the 5-ARGs prognostic model might be a promising prognostic model for pancreatic cancer patients.
Antibiotic Resistance Profile of Common Uropathogens during COVID-19 Pandemic: Hospital based Epidemiologic Study
Authors: Gawad Ahmed M. Abdel , Ashry Walaa Mohamed Omar , El-Ghannam Sherief , Hussein Mahmoud , Yousef Ahmed
Published: October 2022

Background: Antimicrobial resistance has a direct impact on the ability to treat common infections, and this was worsened during the COVID-19 pandemic. Worldwide surveillance studies are lacking and resistance rates vary spatially, so frequent local surveillance reports are required to guide antimicrobial stewardship efforts.
This study aims to report our common local uropathogens and their antibiogram profiles in our community during the COVID era.
Methods: A retrospective study included patients referred to our urology units with urine culture and sensitivity. All bacterial strains were identified, and their antibiotic susceptibilities were tested.
Results: Out of 2581 urine culture results recruited, 30% showed microbiological proof of infection. The majority, 486 (63.4%), were isolated from females. The most frequent isolates were Escherichia coli (44.4%) and S. aureus (17.8%). The resistance rates ranged from 26.9 to 76.9%. Piperacillin-tazobactam antibiotic had the lowest resistance rate. The multi-drug resistance pattern was recorded in 181 (23.9%) of the isolates; 159/597 (26.6%) Gram-negative and 22/160 (13.8%) Gram-positive isolates.
Conclusions: Alarming rates of antimicrobial resistance were detected, which stresses the significance of following infection control policies and establishing national antimicrobial stewardship standards.
Flash flood susceptibility mapping in Alipurduar district using multi-criteria decision analysis approach
Authors: BISWAS SANJAY , MITRA RAJIB , ROY DIPESH , MANDAL DEEPAK KUMAR
Published: October 2022

One of the worst climate-related natural disasters in the world is flash flooding. The present study has integrated the Geographic information system (GIS) and Analytical hierarchy process (AHP) method for mapping the flash flood susceptibility zones of the Sub-Himalayan Alipurduar district of West Bengal, India. The study applied eleven flood conditioning factors, and weights have been assigned for them based on the expert's opinion to compute the AHP. The flash flood susceptibility map depicted four zones, viz., (a) flash flood free zone, (b) low flash flood susceptibility zone, (c) moderate flash flood susceptibility zone, and (d) high flash flood susceptibility zone. The research found that 7.98% area of the district was highly susceptible to flash floods, and only 3.93% area into a flash flood free zone. Out of six community development blocks of the district, three blocks were highly susceptible to flash floods disaster, i.e., Madarihat, Kalchini, and Kumargram. The produced map was also validated with the field photographs and flash flood inventory map of the district. This kind of study is always helpful in mitigating the intensity of such a kind of disaster and can play a precious role in achieving sustainable development goals.
Enhanced Adsorption and Photocatalytic Degradation of Methylene Blue Using S-TiO 2 Composites Pillared Clay under Visible Light
Authors: Natsir Muh. , Irwan Irwan , Azis Thamrin , Wati Irma , Maulidiyah Maulidiyah , Salim La Ode Agus , Arham Zul , Bijang Catherina M. , Nurdin Muhammad
Published: October 2022

We investigated methylene blue adsorption capacity and photodegradation removal efficiency using an S-TiO2@clay composite by irradiating a commercial Tungsten halogen lamp in a reactor. The same experimental conditions were applied to clay and pristine TiO2 as a reference. Morphology surface area, chemical bonding, and optical properties of those samples were characterized by using FESEM, FTIR and UV-Vis DRS tehcniques. The S-TiO2@clay composites showed a high surface area and an even pore distribution compared to natural clays and pristine TiO2. The results indicate that the composite was successfully pillared on natural clay. These results exhibit that S-TiO2 composite pillared natural clay (S-TiO2@clay) presented better results in the methylene blue dye adsorption-photodegradation process, with an adsorption efficiency of 93.87% and degradation efficiency of 94.94%. In tests performed in the absence of natural clay, the degradation efficiency of 88.46%, while tests performed in the natural clay only obtained an adsorption efficiency of 86.41%. These results evidence that the combination methods of adsorption-photodegradation are very efficient in removing methylene blue dye.
A volatile producing Bacillus subtilis strain from the rhizosphere of Haloxylon ammodendron promotes plant root development
Authors: He Ao-Lei , Ren Wei , Zhao Ling-Yu , Li Hui-Ru , Paré Paul W. , Zhao Qi , Zhang Jin-Lin
Published: October 2022

Aims
The colonization of plant growth-promoting rhizobacteria (PGPR) along plant roots in turn facilitates their ability to promote plant growth and health. In this study, we found that Bacillus subtilis strain WM13-24 from the rhizosphere of Haloxylon ammodendron was able to promote the growth of both Arabidopsis and its host plant. Furthermore, we found that volatile compounds (VCs) from strain WM13-24 could promote plant growth by stimulating lateral root formation and root hair growth. However, the molecular mechanism underlying WM13-24-stimulated root development is still unknown.
Methods
In this study, a series of Arabidopsis mutants defective in specific plant hormone signaling pathways were used as materials to preliminarily study the effect of volatile compounds (VCs) released by strain WM13-24 on plant root development through genetic and pharmacological methods. The volatile compounds of strain WM13-24 were identified by solid-phase microextraction gas chromatography-mass spectrometry (SPME-GC-MS).
Results
The results showed that auxin signaling and transport played a crucial role in WM13-24-stimulated changes of root architectures in Arabidopsis. SPME-GC-MS analysis revealed that WM13-24 produces 2, 3-butanediol and benzyl alcohol and the growth responses of plants to the two VCs were concentration dependent.
Conclusions
All these results suggested that VCs emitted from Bacillus subtilis strain WM13-24 from the rhizosphere of Haloxylon ammodendron improves root development depending on auxin signaling.
Prevalence of high-risk Human papillomavirus infections and associated factors among women living with HIV in Shashemene town public health facility, Southern Ethiopia
Authors: Megersa Tariku , Lencha Bikila , Kumsa Kebede , Lemma Kebebaw , Dengo Sisay
Published: October 2022

Background: Every year, large number of women are suffering from cervical cancer. Particularly women living with HIV are at high-risk of being suffered with it. Early testing of high-risk HPV infection can significantly reduce the incidence of cervical cancer. However, lack of early and regular testing has been identified as one of the major problems among risky populations.
Methods: Institutional-based cross-sectional study design was conducted among women living with HIV in Shashemene town public health facilities with a total sample size of 406 from February 1–March 30. Systematic random sampling technique was employed to select the study subjects. A structured questionnaire and checklist was used to collect data. The collected data were cleaned, coded, and entered into Epi-info version 7.2.5 and exported to statistical package for social science version 24 for analysis. Finally, bi-variable and multivariable logistic regression analyses were performed to identify determinants of high-risk human HPV. Odds ratio with 95% confidence interval was used to test association between exposure and outcome under study and p-value< 0.05 was considered significant.
Results: The prevalence of high-risk HPV infections among study participant was 173(35.2%) with 95% CI (30.5%-40.1%). Prevalence of high-risk HPV type 16, 18 and other high-risk HPV types were 62(15.3%), 23(5.7%) and 58(14.3%), respectively. Having history of sexually transmitted infections [AOR=3.120; 95% CI (1.977-4.923)], Endline CD4 count <200 cells/mm3 [AOR=3.072; 95% CI(1.009-9.350)], Endline HIV viral-load >50 copies/ml [AOR=3.446; 95% CI(1.368-8.683)] and more than one-lifetime sexual partner [AOR=2.112; 95% CI(1.297-3.441)] were significantly associated with high-risk HPV infections.
Conclusion: More than one third of women living with HIV had high-risk HPV. Having history of STI, low CD4 count, high viral load and multiple sexual partners were associated with high risk HPV. HIV positive women with these risk factors should be given special consideration in clinical and public health intervention
WITHDRAWN: Developmental Trends in Academic Emergency Medicine Journals, 2000 to 2019
Authors: Cheng Wen-Mei , Cheng Chien-Wei , Lee Ching-Hsing
Published: October 2022

Background
We investigated academic developmental trends in emergency medicine (EM) by analyzing the performance of EM journals.
Methods
This was a literature review study. We collected data from the Journal Citation Reports (JCR) database for EM category journals, including journal titles, language, numbers, and impact factors (IFs) from 2000 to 2019. The aggregate IFs of EM and 11 other categories (cardiac and cardiovascular systems, clinical neurology, critical care medicine, gastroenterology and hepatology, infectious diseases, general and internal medicine, pediatrics, respiratory system, surgery, toxicology, and urology and nephrology) were collected from 2003 to 2019. The slope of the linear regression was used to evaluate the trend in EM journal IFs and the aggregate IFs of all categories. Pearson’s correlation coefficient was used to evaluate the correlation between EM journals’ IF in 2000 and their IF trend from 2000 to 2019.
Results
The EM journal number increased from 8 (all in English) in 2000 to 31 (26 in English) in 2019. In total, 28 EM journals had a positive IF trend since their initial enrollment into the JCR database, and the trend was significant for 18 journals. The correlation of the EM journals’ IF in 2000 and IF trends from 2000 to 2019 was 0.75. The increasing trend of aggregate IF for the EM category was significant and ranked 8th of 12 categories.
Conclusions
The increased number, language diversity, and IF trend for EM journals indicates that the development of academic EM is a continuous international trend. In the past 20 years, the IF trend increased faster for EM journals with a higher initial IF. The overall performance of EM journals was non-inferior to other medical specialties.
Oceanic Carbon in Seagrass Ecosystems in Freshwaters of Northern Brazil
Authors: Ogbuka Josiah
Published: October 2022

Seagrass ecosystems can sequester and retain considerable amount of oceanic carbon. However, few studies and limited data constrain seagrass carbon stocks on regional and global scales, especially in underreported seagrass region of South America. This study measured and predicted carbon stocks in seagrass beds of the Macapa River and the Barra Grande lagoon, northern Brazil. Aboveground and belowground biomass components were sampled from Halodule wrightii seagrass beds of the Macapa River only, while sediment cores were sampled at 50cm depth in the Halodule wrightii seagrass beds of the Macapa River. In Barra Grande lagoon, three sediment cores were sampled at 8-30cm depth in Halodule wrightii and mixed stands of Halodule sp. seagrass beds. The carbon (C) stocks of the seagrass aboveground and belowground biomass of Halodule wrightii seagrass beds of the Macapa River were 0.005MgC/ha− 1 and 0.018MgC/ha− 1 respectively. The C stock of sediment from seagrass beds in Macapa River averaged 41.8MgC/ha− 1, while the C stock of sediment from seagrass beds of Barra Grande lagoon averaged 12.3MgC/ha− 1, These findings add to the limited global database on seagrass carbon stocks to support optimization of carbon capture and storage through sustainable global carbon financing regime for vegetated marine ecosystems. The results also contributes to realizing SDG 13 indicator 13.2.2 on reducing the total annual greenhouse gas (GHG) emissions, SDG 14.2 target, namely, “By 2020, sustainably manage and protect marine and coastal ecosystems to avoid significant adverse impacts, including by strengthening their resilience, and take action for their restoration in order to achieve healthy and productive oceans.”
Role of Galectin-3 in diagnosis and severity assessment of epicardial artery lesions in patients with suspected coronary artery disease
Authors: Bošnjak Ivica , Bedeković Dražen , Selthofer-Relatić Kristina , Roguljić Hrvoje , Mihaljević Ivica , Bilić-Ćurčić Ines
Published: October 2022

Background.This study aimed to investigate a possible role of serum galectin-3 (Gal-3) levels in diagnosis and assessment of significant epicardial artery lesions in patients with suspected coronary artery disease (CAD).
Methods. This was a single center retrospective cohort study including 168 subjects with suspected CAD and indications for coronary angiography divided into three groups: percutaneous coronary intervention (PCI) group (N 64), coronary artery bypass graft surgery (CABG) group (N 57), and group with no coronary stenosis (N 47). Gal-3 levels were measured and the syntax score (Ss) was calculated.
Results: The mean value of Gal-3 in the PCI and CABG group was 19.98 ng/ml, while in the control group it was 9.51 ng/ml (t=9.075, p < 0.001). The highest value of Gal-3 was found in the group of subjects with three-vessel disease (t=-3.652b, p<0.001). When subgroups were analyzed by Gal-3 levels (< 17.8 ng/ml low, 18.8-25.9 ng/ml intermediate, > 25 ng/ml high risk) there was a significant difference between at least two Gal-3 groups for the arithmetic mean of Syntax score (IF=13,898, p<0.001). The syntax I’s arithmetic mean at low and intermediate risk Gal-3 levels was significantly lower than at high-risk Gal-3 levels (p<0.001).
Conclusion. Gal-3 could be used as an additional tool for diagnosis and severity assessment of atherosclerotic disease in patients with suspected CAD. Furthermore, it could help identify high risk subjects in patients with stable CAD.
Automated classification of polyps using deep learning architectures and few-shot learning
Authors: Krenzer Adrian , Heil Stefan , Fitting Daniel , Matti Safa , Zoller Wolfram G. , Hann Alexander , Puppe Frank
Published: October 2022

Background: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous. Therefore, polyps are classified using different classification systems. After the classification, further treatment and procedures are based on the classification of the polyp. Nevertheless, classification is not easy. Therefore, we suggest two novel automated classifications system assisting gastroenterologists in classifying polyps based on the NICE and Paris classification.
Methods: We build two classification systems. One is classifying polyps based on their shape (Paris). The other classifies polyps based on their texture and surface patterns (NICE). A two-step process for the Paris classification is introduced: First, detecting and cropping the polyp on the image, and secondly, classifying the polyp based on the cropped area with a transformer network. For the NICE classification, we design a few-shot learning algorithm based on the Deep Metric Learning approach. The algorithm creates an embedding space for polyps, which allows classification from a few examples to account for the data scarcity of NICE annotated images in our database.
Results: For the Paris classification, we achieve an accuracy of 89.35 %, surpassing all papers in the literature and establishing a new state-of-the-art and baseline accuracy for other publications on a public data set. For the NICE classification, we achieve a competitive accuracy of 81.13 % and demonstrate thereby the viability of the few-shot learning paradigm in polyp classification in data-scarce environments. Additionally, we show different ablations of the algorithms. Finally, we further elaborate on the explainability of the system by showing heat maps of the neural network explaining neural activations.
Conclusion: Overall we introduce two polyp classification systems to assist gastroenterologists. We achieve state-of-the-art performance in the Paris classification and demonstrate the viability of the few-shot learning paradigm in the NICE classification, addressing the prevalent data scarcity issues faced in medical machine learning.
Prediction model based on radiomics and clinical features for preoperative lymphovascular invasion in patients with gastric cancer with Lauren classification
Authors: Wang Ping , Chen Kaige , Han Ying , Zhao Min , Abiyasi Nanding , Shang Jiming , Yan Shaolei , Peng Haiyong , Shang Naijian , Meng Wei
Published: October 2022

Objective
Lymphovascular invasion (LVI) is an independent risk factor of gastric cancer (GC) prognosis; however, LVI cannot be determined preoperatively. We explored whether a model based on contrast-enhanced computed tomography (CECT) radiomics features combined with clinicopathological factors can evaluate preoperative LVI in patients with GC with a clear Lauren classification.
Methods
We retrospectively analyzed 495 patients with GC, including 288 with LVI. The extracted CECT features were standardized, followed by consistency testing, correlation analysis, univariate analysis, and multivariate least absolute shrinkage and selection operator (LASSO) regression analysis. The radiomics score (Radcore) was calculated for each patient. Univariate (p < 0.10) and multivariate (p < 0.050) analyses were used to identify the clinical risk factors associated with LVI. Accordingly, three prediction models were established: Clinical + Arterial phase_Radcore, Clinical + Venous phase_Radcore, and a combined model. The prediction performances of the models were verified using receiver operating characteristics, decision curve analysis, and calibration curves in the testing dataset. The relationship between Lauren classification and LVI was analyzed using a histogram.
Results
The areas under the curve of the combined model were 0.8629 (95% confidence interval [CI], 0.8247–0.9011) and 0.8343 (95% CI, 0.7673–0.9012) in the training and testing datasets, respectively. The combined model had superior performance compared with the other models. Diffuse-type GC according to the Lauren classification accounted for 43.4% of LVI cases.
Conclusions
CECT-based radiomics models can effectively predict the preoperative LVI status in patients with GC with Lauren classification. The prediction ability of the models was effectively improved by incorporating clinicopathological factors.
Characterization of the life cycle of Dermacentor nuttalli in the Qinghai-Tibetan Plateau under laboratory conditions and identification of spotted fever group Rickettsia
Authors: Ma Hejia , Ai Jingkai , Kang Ming , Li Jixu , Sun Yali
Published: October 2022

Background
Dermacentor nuttalli has been a focus of study because tick-borne pathogens have been widely identified in D. nuttalli in the northern and southwestern China. The salivary glands and midgut of ticks are specific and major barriers to efficient pathogen transmission. The spotted fever group Rickettsia causes tick-borne rickettsiosis, which poses serious threats to the health of humans and animals. Identification of the species of Rickettsia in the midgut and salivary glands of D. nuttalli is essential for understanding the colonization of the pathogens in ticks and for developing effective control strategies for Rickettsia.
Methods
This study collected D. nuttalli in the field on the Qinghai-Tibetan Plateau from March to April 2021 to characterize the D. nuttalli life-cycle under laboratory conditions, and identified SFG Rickettsia in the D. nuttalli midgut and salivary glands of males and females in both original and next-generational adults.
Results
D. nuttalli ticks collected in this area were molecularly confirmed, and exhibited one life cycle of an average of 67.4 days under laboratory conditions. The average weight of engorged females was 656.0 mg, which was 74.5 times the weight of unfed females. Moreover, high colonization rates of Rickettsia spp. were found in both the midgut and salivary glands of both male (92.0%) and female (93.0%) D. nuttalli ticks, anf no positivity being found in single tissue colonization. However, low rates of 4.0–6.0% of Rickettsia spp. colonization in the D. nuttalli midgut and salivary glands were detected. Furthermore, the sequencing analysis showed that the Rickettsia sequences obtained in this study shared 98.6 to 100% nucleotide identity to R. slovaca and R. raoultii isolated from Dermacentor spp. in China. The phylogenetic analysis of Rickettsia spp. based on the gltA, ompA, ompB and sca4 genes revealed that the Rickettsia sequences obtained could be classified into these two groups, R. slovaca and R. raoultii.
Conclusions
This study is the first to identify the life-cycle of collected D. nuttalli in the field in the Qinghai-Tibetan Plateau under laboratory conditions, and to detect the two species of SFG Rickettsia in the midgut and salivary glands of males and females in both original and next-generational D. nuttalli adults. Our study provides new insights into the pathogen colonization in ticks in the Qinghai-Tibet Plateau, and the relationship among hosts, ticks and pathogens.
Fortification of Wheat Bread with Edible Chrysanthemum (Chrysanthemum morifolium Ramat.): Unraveling the Mechanisms of Dough Rheology and Bread Quality Changes
Authors: Xu Huihuang , Wu Min , Shang Nan , Wei Wenguang , Gao Fei
Published: October 2022

The inclusion of plant material in bread formulations is a global trend, but research on the mechanisms of its effect on the structural and baking performance of the dough is lacking. Herein, edible chrysanthemum (Chrysanthemum morifolium Ramat.) powder (CP) was substituted for wheat flour at 3–15 wt% and its effects on dough structure and rheology, bread physicochemical properties, and aroma profile were investigated. The inclusion of CP reduced the relative crystallinity and structure orderliness of starch in terms of X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy analysis. Steady-state shear and oscillation tests showed that the inclusion of CP resulted in an enhanced viscoelastic behavior of dough, implying an increase in the resistance of the dough system to flow and deformation, which caused a decrease in specific volume and softness of bread compared to the control (bread without CP). The large oscillatory amplitude oscillation shear tests (LAOS) indicated that doughs exhibited Ⅰ behavior (strain thinning). The scanning electron microscopy (SEM) observation further confirmed these findings. Significantly, formulations with 3 and 6 wt% CP not only improved the rheological and structural properties of doughs but also enriched the aroma profile of bread compared to the control. Furthermore, sensory evaluators reported that bread enriched with 6% CP scored highest in appearance, texture, and overall acceptability, meaning a product with a high sensory appeal to consumers. This work provides valuable information for an in-depth study of the relationship between bread quality and the rheological behavior and structural properties of the dough.
Public Alert and Warning System Literature Review in the USA: Identifying Research Gaps and Lessons for Practice
Authors: Sadiq Abdul-Akeem , Okhai Ratna , Tyler Jenna , Entress Rebecca
Published: October 2022

As emergencies continue to impact communities in the United States on an unprecedented scale, it is imperative for communities to look for effective ways to keep people safe and reduce future impacts. Public alert and warning systems are an effective means of accomplishing these goals. As such, researchers have studied public alert and warning systems extensively in the United States. Due to the plethora of studies on public alert and warning systems, a systematic and comprehensive synthesize is needed to understand what has been studied and their major findings and identify practical lessons that can be used to further improve public alert and warning systems. Hence, the goal of this study is to answer the following two questions: (1) What are the major findings from public alert and warning system research? (2) What policy and practical lessons can be gleaned from public alert and warning system research to improve public alert and warning system research and practice? We answer these questions by conducting a systematic and comprehensive review of the public alert and warning system literature, starting with a keyword search. The search produced 1,737 studies, and we applied six criteria (e.g., the study has to be a peer-reviewed article, dissertation, or conference paper), which narrowed the number of studies to 100. After analyzing the 100 studies, the results reveal 12 emergent themes regarding the major findings from public alert and warning system research. The results also reveal eight emergent themes related to the policy and practical lessons. We then offer recommended topics for future research as well as outline some policy and practical recommendations. We conclude by summarizing the findings and discussing the limitations of the study.
Design a mobile sensor system based on bee colony optimization: modeling and simulation
Authors: Al-Mousawi Ali
Published: October 2022

Mobile Wireless Sensor Networks (MWSN) plays a central role in modern artificial intelligence-based systems, as they corresponds to the part that senses data and equal human senses in their work. The parts responsible for converting the environmental signal into a digital signal are the sensors. The higher the quality of the sensors, the greater the readability. Because of this fame, the wireless sensor network has become a research field for a lot of research that has worked to develop both the work and performance of wireless sensor networks through the use of artificial intelligence algorithms. This research paper discusses the effect of using beehive algorithms, which is one of the swarm intelligence algorithms within natural computing. This paper discusses the process of creating a three-dimensional simulation model to simulate the MWSN system based on BCO, as well as a simulation model for the network itself. The simulation was tested for the new system and the communication performance of MWSN was improved by adding AI to the working principle of each component of the system. The simulation results were compared with similar protocols to show the extent of the impact of the BCO algorithm on the overall performance of the network. It was found that the use of the BCO algorithm gives MWSN more efficiency in many ways, depending on the indicators of the efficiency of wireless networks. The model was named IAANET for short, which means Intelligent Aerial Ad-hoc Network because the aerial components within MWSN is the optimization target.
Exploring the Effects of Potentization by Electron Microscopy, Raman Spectroscopy and AI Algorithms
Authors: Berghian-Grosan Camelia , Kourounis Drosos , Porav Alin Sebastian , Dag Ilknur , Ay Kursad Osman , Vithoulkas George
Published: October 2022

Potentization is a process of successive dilutions and vigorous succussions of a substance or initial tincture. Transmission electron microscopy is adopted for the investigation of potentized ethanol- and water-based solutions of gold and reveals nanoparticles and various assemblies formed in accordance with the level of potentization. Raman spectroscopy is further applied in combination with artificial intelligence algorithms for the analysis of potentized purified water, unpurified water, and purified water-based gold solutions. The proposed methodology is promising and sound in distinguishing potentized and non-potentized spectra or spectra obtained at different levels of potentization.
Land use land cover Dynamics using CA-Markov Chain A case of Belete Gera Forest Priority Area South Western Ethiopia
Authors: Gemmechis Wendafiraw Abdisa
Published: October 2022

Arrogant practices of land use including expansion of agricultural land and infrastructural development are resulting in deforestation that goes to climate change. Cellular Automata (CA)-Markov chain combines the advantages of cellular and Markov chain analysis to simulate and predict future land use/cover trends depending on the Land Use Land Cover (LULC) changes in the past. First, spatial distribution of LULC and area changed were calculated using IDRISI software and GIS technology, and then the forest land cover conversion to other LULC was evaluated to obtain rate of deforestation during a period of 1980–2018. Second, using transition potential matrices of 1999–2018, CA-Markov chain was executed to simulate spatial distribution of land use/cover in 2018. Based on the simulated LULC map for 2018 and the actual LULC map of 2018 CA-Markov Model was validated with a kappa index of 1. Finally, future land use/cover transformed during the periods of 2018–2037 and 2037–2056 were predicted using CA-Markov Chain Model. The results revealed that decreasing of forest land and increasing of agricultural land in the study period. Forest land was decreased by 52,156.71 hectares from 1980 to 2018, while agricultural land increased by 78,021.35 hectares during 1980–2018. Rate of deforestation between 1980 and 2018 was 1,372.54 hectares per year. Therefore, the predicted results of 2037 year suggests that forest cover would decreases by 30,204.65 hectares within 19 years and also agricultural land would be increases by 30,693.91 hectares between 2018 and 2037. It approved helping concerned bodies that work on the forest better understand and address a tough land use system, and develop.
The Effect of Heart Disease, Diabetes, and Hypertention in COVID 19 Patients
Authors: Alfares Farah , Alshihabi Farah , Abozraa Abdalrhman , Abobaker Hussam , Nabulsi Ahmad
Published: October 2022

Background
Patients with preexisting diabetes and cardiovascular metabolic illnesses who have coronavirus disease-2019 (COVID-19) have a higher mortality risk. More research is needed to correctly concentrate the influence of previous health issues on COVID-19 results due to the spread of novel variants with evolving clinical features.
Aim
The primary goal of this study was to look at the effects of diabetes and cardiovascular disease (CVD) on disease prognosis and severe health consequences in individuals with COVID-19.
Methods
A retrospective analysis was conducted at Damascus hospital on 202 patients with COVID-19 from February 10, 2022, to May 10, 2022. The chi-square test was used to explore the relationship between sickness results and research parameters. The statistical significance level was chosen at P 0.05.
Results
Men made up 51% of the patients, while women made up 49%. The average age of the patients was 66.5 years. Cough (20%) was the most prevalent clinical complaint among 202 COVID-19 patients, followed by weariness and dyspnea (18%) and fever (17%). 28% of these patients had diabetes, 45% had hypertension, and 16% had heart failure or myocardial infarction. Multiple organ failure occurred in 7% of patients, and patient mortality occurred in 49% of instances. We identified a statistically significant association between the existence of cardiac disease in the patient and the development of problems as a result of COVID-19 infection, with 69% of patients developing difficulties during their infection compared to 64% who did not develop any symptoms.
Conclusion
In this study, 82 COVID-19 patients passed away. Diabetes, CVD, and COVID-19 patients had the greatest mortality rates. Diabetes and CVD patients were at a much higher risk.
A study of blood sugar changes in non-diabetic patients admitted to the Cardiac Care Department, Damascus Hospital.
Authors: Hammoud Taghrid , Aldeen Redan Zhr , Saleem ‏Majd , Al-Fawaris Ma'moun
Published: October 2022

Background:
Diabetes, as it is called (the disease of the age), has taken up large demographic areas, so it is better to treat it than to prevent it. Since measuring blood sugar periodically is one of the easiest methods available that makes us vigilant about the initial changes in blood sugar, especially when there are risk factors; Based on the foregoing, the importance of the research is based on studying the changes in blood sugar values ​​in non-diabetic patients and their predisposition to high blood sugar in the presence of the cardiac factor as a risk factor, as current studies indicate that there are several metabolic and hormonal changes that occur in patients with important heart diseases, and that high blood sugar values Blood in patients with heart disease is significantly associated with higher morbidity and mortality. This study aims to study the relationship between blood sugar values ​​upon discharge from the hospital and the patient's pathological history, serum creatinine values, systolic pressure and pulse of the patient, family history, smoking amount, LDL and CKmb values ​​upon discharge. And studying the relationship between the patient's antecedents and CKmb upon discharge.
Methods and materials:
Samples were collected in Damascus Hospital (Cardiac Care Department) in Damascus, affiliated to the Syrian Ministry of Health, in the period between (1/1/2020 to 1/1/2022), and the information required for the study was extracted from patients’ files and samples were analyzed by the two students, Redan Zhr Aldine. And Majd Seleem on a daily basis during official working hours, as 260 cases were collected.
Results:
The sample included 260 patient's male (68.2%) females (30.8%), and the age group (51–60) was the most common in the study, and the percentage of patients with infarction and angina pectoris was 38.5%. The percentage of patients with atrial fibrillation was 23.1%. When studying the relationship between blood glucose values at the moment of hospital discharge and the patient's medical history, blood creatinine values, systolic pressure, pulse, family history, smoking amount, LDL and CKMB values at the moment of discharge and histological history, the p-value was < 0.05.
Conclusion:
There is a statistically significant relationship between blood glucose values at the moment of discharge from the hospital and the patient's medical history, blood creatinine values, systolic pressure, pulse, patient history, smoking amount, LDL and CKMB values at the moment of discharge and pathological history, and there is no statistically significant relationship between Medical history and CKMB values at the moment of hospital discharge.
Comparison of State-of-the-Art Neural Network Survival Models with the Pooled Cohort Equations for Cardiovascular Disease Risk Prediction
Authors: Deng Yu , Liu Lei , Jiang Hongmei , Peng Yifan , Wei Yishu , Zhou Zhiyang , Zhong Yizhen , Zhao Yun , Yang Xiaoyun , Yu Jingzhi , Lu Zhiyong , Kho Abel , Ning Hongyan , Allen Norrina B. , Wilkins John , Liu Kiang , Lloyd-Jones Donald , Zhao Lihui
Published: October 2022

Background: The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox PH-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their success in image recognition and text classification. Various survival neural network models have been proposed by combining survival analysis and neural network architecture to take advantage of the strengths from both. However, the performance of these survival neural network models compared to each other and to PCEs in ASCVD prediction is unknown.
Methods: In this study, we used 6 cohorts from the Lifetime Risk Pooling Project (with 5 cohorts as training/internal validation and one cohort as external validation) and compared the performance of the PCEs in 10-year ASCVD risk prediction with an all two-way interactions Cox PH model (Cox PH-TWI) and three state-of-the-art neural network survival models including Nnet-survival, Deepsurv, and Cox-nnet. For all the models, we used the same 7 covariates as used in the PCEs. We fitted each of the aforementioned models in white females, white males, black females, and black males, respectively. We evaluated models’ internal and external discrimination power and calibration.
Results: The training/internal validation sample comprised 23216 individuals. The average age at baseline was 57.8 years old (SD = 9.6); 16% developed ASCVD during average follow-up of 10.50 (SD = 3.02) years. Based on 10x10 cross-validation, the method that had the highest C-statistics was Deepsurv (0.7371) for white males, Deepsurv and Cox PH-TWI (0.7972) for white females, PCE (0.6981) for black males, and Deepsurv (0.7886) for black females. In the external validation dataset, Deepsurv (0.7032), Cox-nnet (0.7282), PCE (0.6811), and Deepsurv (0.7316) had the highest C-statistics for white male, white female, black male, and black female population, respectively. Calibration plots showed that in 10x10 validation, all models had good calibration in all race and sex groups. In external validation, all models overestimated the risk for 10-year ASCVD.
Conclusions: We demonstrated the use of the state-of-the-art neural network survival models in ASCVD risk prediction. Neural network survival models had similar if not superior discrimination and calibration compared to PCEs.