bluuebunny/crossref_metadata_2025_split huggingface dataset:
A methodology for creating a database to contribute to building urban resilience, the case of emergency management and response in the city of Algiers
Authors: KHOUAS Makhlouf Adel , telaidjia djamel , DJABRI Ahmed Djaber , HABIBI Yahiaoui , KERMANI Saci 
Published: December 2022

Abstract
In the context of territorial planning, cities with the capacity to limit the impact of stress and adapt to the event to return to normal functioning as quickly as possible are called resilient cities. Emergency management using new technologies is a very important task in building the urban resilience of a community. Among the necessary information requested by the rescue center (firefighters, police...) is your address; in order to navigate to an address, you must locate it and search for the best route. To facilitate this task, a set of solutions has been proposed by the development of an integrative technology called WEB GIS. With the advent of the Internet, web mapping, or the distribution of maps via the web, is an expanding field thanks to the development of genetic solutions. The integration of WEB GIS into governance seems necessary. Its integration into local governance will promote social progress. In this work, our main objective was to develop a path towards the design of a dynamic WEB GIS system for local address administrations and to serve the citizen. The WEB GIS that we have developed also allows in the management of addresses, to carry out a set of geographical queries on the study area and thematic analyses for decision support, it also allows to share this information. We believe that collaboration and the flow of information between the different actors will undoubtedly lead to a more appropriate configuration of the real-time address search operations. Our solution will help create a new mode of emergency management in Algiers. With this application, a lot of time is shortened because locating the Victim and sending them paramedics, or response teams used to take a few minutes, but using our proposed technology, it is done in seconds and in a timely manner, allowing for a quick and efficient response rescue the Victim, avoiding many complications that could lead to death.
Most reliable indicator for predicting postoperative pancreatic fistula after distal pancreatectomy: A retrospective study
Authors: Fukada Masahiro , Murase Katsutoshi , Higashi Toshiya , Yasufuku Itaru , Sato Yuta , Tajima Jesse Yu , Kiyama Shigeru , Tanaka Yoshihiro , Okumura Naoki , Takahashi Takao , Matsuhashi Nobuhisa 
Published: December 2022

Abstract
Background: Postoperative pancreatic fistula (POPF) is a major complication of pancreatic surgery. Drain fluid amylase concentration (DAC) is considered a predictive indicator of POPF. However, other indicators related to postoperative drain fluid amylase status exist, and the most reliable indicator for predicting POPF remains unclear. Thus, this study compared the accuracy of these indicators in predicting POPF development after distal pancreatectomy (DP).
Methods: This single-institution retrospective study included 122 patients who underwent DP. The study was conducted between 2010 and 2022 at Gifu University Hospital. We statistically analyzed DAC, drain fluid amylase amount (DAA) calculated by multiplying DAC and daily drainage volume, and drain and serum amylase concentration ratio (DSACR) to assess the correlation with POPF.
Results: Based on the definition and grading of the International Study Group of Pancreatic Fistula, 24.6 (%) of the 122 patients had Grades B and C POPF. The cutoff value of DAC on postoperative day [POD] 1 was 7,238 (U/L) (area under the curve [AUC] 0.65, sensitivity 56.7%, specificity 80.2%, and accuracy 74.4%). The cutoff value of DAC on POD3 was 737 (U/L) (AUC 0.73, sensitivity 73.3%, specificity 65.9%, and accuracy 67.8%). The cutoff value of DAA on POD1 was 103 (U/day) (AUC 0.64, sensitivity 80.0%, specificity 46.2%, and accuracy 54.5%). The cutoff value of DAA on POD3 was 31 (U/day) (AUC 0.72, sensitivity 70.0%, specificity 73.6%, and accuracy 72.7%). The cutoff value of DSACR on POD1 was 17 (AUC 0.69, sensitivity 80.0%, specificity 58.2%, and accuracy 63.6%). The cutoff value of DSACR on POD3 was 22 (AUC 0.77, sensitivity 77.7%, specificity 73.3%, and accuracy 73.6%). Overall, DSACR on POD3 had the highest AUC value. Furthermore, a multivariate logistic regression analysis revealed that pancreatic texture (soft; odds ratio [OR] 5.06; 95% confidence interval [CI] 1.57–19.95; p = 0.006) and DSACR on POD3 (>22; OR 15.57; 95% CI 2.41–307.76; p = 0.003) were independently associated with POPF after DP.
Conclusions: DSACR on POD3 is the most reliable indicator of drain fluid amylase status for predicting POPF after DP.
A Hybrid Deep Learning Algorithm Based Prediction Model for Sustainable Healthcare System
Authors: K Tharageswari , N Mohana Sundaram , R Santhosh 
Published: December 2022

Abstract

In the present era, maintaining a healthy and disease-free life is complex due to multiple personal and environmental impacts. Early identification and diagnosis will help human beings lead a sustainable life. However, to achieve this, health care data has to be processed in an efficient manner with more accuracy. Thus, the impacts of diseases or future impacts can be predicted or detected and proper medication can be provided by the physicians. Efficient feature extraction techniques must be employed with minimum computation cost so that the extracted features can be classified in a better way. However, the performance can be improved if deep learning models replace machine learning models. In this research work, a hybrid deep learning approach is proposed using convolutional neural networks (CNN) and the random forest algorithm. The final classifier block in the CNN architecture is replaced with a random forest classifier to enhance the prediction accuracy and overall performance. Standard benchmark healthcare datasets are employed in the proposed model simulation analysis and the performances are compared to existing techniques such as MNN (Multi Neural Network), CNN-Multilayer Perceptron (CNN-MLP), CNN-Long Short-Term Memory (CNN-LSTM), and Support Vector Machines (SVM), KNN to validate the superior performance.
Biochemical and microbiological characterization of a thermotolerant bacterial consortium involved in the corrosion of Aluminum Alloy 7075
Authors: Atalah Joaquin , Blamey Lotsé , Amenabar Maximiliano J. , Kelley-Loughnane Nancy , Blamey Jenny M. 
Published: December 2022

Abstract
Microorganisms can play a significant role in material corrosion, with bacterial biofilms as major participants in microbially influenced corrosion (MIC). The exact mechanisms by which this takes place are poorly understood, resulting in a scarcity of information regarding MIC detection and prevention. In this work, a consortium of moderately thermophilic bacteria isolated from a biofilm growing over aluminum alloy 7075 was characterized. Its effect over the alloy was evaluated on a 40-day period using Electron Microscopy, demonstrating acceleration of corrosion in comparison to the abiotic control. The bacterial consortium was biochemically and microbiologically characterized as an as an attempt to elucidate factors contributing to corrosion. Molecular analysis revealed that the consortium consisted mainly of members of the Bacillusgenus, with lower abundance of other genera such as Thermoanaerobacterium, Anoxybacillus and Paenibacillus. The EPS polysaccharide presented mainly mannose, galactose, rhamnose and ribose. Our observations suggest that the acidification of the culture media resulting from bacterial metabolism acted as the main contributor to corrosion, hinting at an unspecific mechanism. The consortium was not sulfate-reducing, but it was found to produce hydrogen, which could also be a compounding factor for corrosion.
Factors and practices: farmers' adaptation to climate change in Bangladesh
Authors: Ahmed Shabbir , Fatema Nuzhat 
Published: December 2022

Abstract
Climate literature is highly pronounced about the impending threat to agriculture taking into account the climate change scenario and suggesting adaptation as a possible option to opt for. Considering this, the study seeks to comprehend the factors influencing farmers’ adaptation strategies to cope with climate change in coastal Bangladesh (Koyra Upazila, Khulna). In order to achieve the objectives descriptive, multivariate, and binary logistic regressions were used to analyze the data. Findings demonstrate that the most often used adaptation strategies were crop, water, and infrastructure management. Regression result shows that factors such as gender, labor in the family, farming experience, and the damaged sector are important factors in determining how well adaption methods are implemented. Binary logistic regression analysis explains that age (p = ≤0.041), income (p = ≤0.037), and farm size (p = ≤0.005) are significant factors in deciding on a new adaption option. The outcomes of this research can be used to reevaluate current frameworks and strategies for coping with climate change and to identify the factors that influence policy formulation. In order to improve the water management system for agriculture, policies such as Cash-for-Work (CFW) and Employment Generation Programme for the Poorest (EGPP) may be used to boost local agriculture.
A new method for modelling precipitation variability in relation to climate change
Authors: Qamar Sadia , Ali Zulfiqar , Sammen Saad Shauket 
Published: December 2022

Abstract
Climate change is one of the main consequences of anthropogenic activities. Since the 1950s, gradual changes and an increase in climate warming have been observed. Previous research has been indicating potential associations between climate warming and spatiotemporal changes in precipitation. Moreover, the regional patterns of precipitation have a key role in the continuous monitoring of climate characteristics and natural hazards such as floods and droughts. Therefore, precise and accurate measurements of precipitation concentration and spatiotemporal variability in their patterns are very crucial. In this study, a new method for measuring precipitation concentration is developed and applied to 54 meteorological stations in Pakistan. Furthermore, to assess the precipitation patterns, the proposed method provides solid evidence for considering the effect of temperatures under climate warming. Furthermore, using the spatial correlation between the proposed method and its competitor, a comparative analysis is made to evaluate the performance of the proposed method. Moreover, the spatial variability structure in various precipitation patterns is assessed and compared using spatial predictive maps. Outcomes associated with this research show significant deviations between the proposed method and the existing one. In this paper, regression analysis revealed that the additional input can potentially improve the precipitation estimates under the appropriate sampling estimator. This is the first study that has documented the impact of climate warming on measuring precipitation concentration. These findings can contribute to a better understanding of precipitation concentration in relation to climate warming.
Application of the PSO–neural network in rainfall–runoff modeling
Authors: Kumar Keshav , Singh Vivekanand , Roshni Thendiyath 
Published: December 2022

Abstract
In this study, rainfall–runoff (R–R) models were developed by assembling Particle Swarm Optimization (PSO) with the Feed Forward Neural Network (FFNN) and the Wavelet Neural Network (WNN). Performances of the model were compared with the wavelet ensembled neural network (WNN) and the conventional FFNN. The data from 1981 to 2005 were used for calibration and from 2006 to 2014 for validation of the models. Different combinations of rainfall and runoff were considered as inputs to the PSO–FFNN model. The fitness value and computational time of all the combinations were computed. Input combination was selected based on the lowest fitness value and lowest computational time. Four R–R models (FFNN, WNN, PSO–FFNN and PSO–WNN) were developed with the best input combination. The performance of the models was evaluated using statistical parameters (Nash–Sutcliffe Efficiency (NSE), D and root mean square error (RMSE)) and parameters vary in the range of (0.86–0.90), (0.95–0.97) and (68.87–84.37), respectively. After comparing the performance parameters and computational time of all four models, it was found that the PSO–FFNN model gave better values of NSE (0.89), D (0.97), RMSE (68.87) and less computational time (125.42 s) than other models. Thus, the PSO–FFNN model was better than the other three models (FFNN, WNN and PSO–WNN).
Preparation of IgE Antibody and Distribution of IgE+ Secretory Cells in
the Palatine Tonsil of Bactrian Camel
Authors: Wang Wen-Hui , Liu Li-Ping , Li Min , Zhang Wang-Dong 
Published: December 2022

Background:
Allergic diseases induced by dust have seriously threatened human health,
while Bactrian camels can live in a sandy environment for a long time.

Objective:
To prepare rabbit anti-Bactrian camel IgE antibody and explore the distribution
characteristics of IgE+ secretory cells in the palatine tonsils, which lays a theoretical foundation for the
distribution of local antibodies in the palatal tonsils of Bactrian camel and the study of immune
function.

Methods:
In this study, the amino acid sequences of Bactrian camel IgE, IgA, IgM and IgG heavy
chain constant regions were compared, and a specific IgE gene fragment were selected (447 bp). The
recombinant plasmid pET-28a-IgE was induced in Escherichia coli BL21(DE3) by IPTG and its
expression conditions were optimized. The antibody was prepared by immunizing rabbits with purified
IgE recombinant protein, its titer and specificity were detected by indirect ELISA and Western
blotting. Immunohistochemical and statistical methods investigated the distribution of IgE+ secretory
cells in the palatine tonsils.

Results:
The IgE recombinant protein was expressed in the form of inclusion bodies with a size of 16
kDa. The optimal IPTG induction concentration was 0.7 mmol/L and the induction time was 8 h. The
titer of the antibody was 1:16000 by ELISA, and the antibody could specifically bind to the
recombinant protein by Western blotting. IgE+ secretory cells were mainly distributed in the
subepithelial compartments of reticulated crypt epithelium of the palatine tonsil of the Bactrian camel,
followed by the subepithelial compartments of stratified squamous epithelium and occasionally in the
extrafollicular region.

Conclusion:
The rabbit anti-Bactrian camel IgE polyclonal antibody was successfully prepared. It is
confirmed that IgE exists in the palatine tonsils of Bactrian camels under normal living conditions. In
addition, IgE+ secretory cells are mainly distributed in the subepithelial compartments of reticulated
crypt epithelium of the palatine tonsil, which is consistent with the distribution characteristics of IgG+
and sIgA+ secretory cells in the palatal tonsils of the Bactrian camel.
NorA, Tet(K), MepA, and MsrA Efflux Pumps in Staphylococcus aureus, their Inhibitors
and 1,8-Naphthyridine Sulfonamides
Authors: Melo Coutinho Henrique Douglas , de Morais Oliveira-Tintino Cícera Datiane , Muniz Débora Feitosa , dos Santos Barbosa Cristina Rodrigues , Silva Pereira Raimundo Luiz , Begnini Iêda Maria , Rebelo Ricardo Andrade , da Silva Luiz Everson , Mireski Sandro Lucio , Nasato Michele Caroline , Lacowicz Krautler Maria Isabel , Barros Oliveira Carlos Vinicius , Pereira Pedro Silvino , Rodrigues Teixeira Alexandre Magno , Tintino Saulo Relison , de Menezes Irwin Rose Alencar , da Silva Teresinha Gonçalves 
Published: December 2022

Abstract:
Antibiotic resistance can be characterized, in biochemical terms, as an antibiotic’s inability to reach
its bacterial target at a concentration that was previously effective. Microbial resistance to different agents can
be intrinsic or acquired. Intrinsic resistance occurs due to inherent functional or structural characteristics of the
bacteria, such as antibiotic-inactivating enzymes, nonspecific efflux pumps, and permeability barriers. On the
other hand, bacteria can acquire resistance mechanisms via horizontal gene transfer in mobile genetic elements
such as plasmids. Acquired resistance mechanisms include another category of efflux pumps with more specific
substrates, which are plasmid-encoded. Efflux pumps are considered one of the main mechanisms of bacterial
resistance to antibiotics and biocides, presenting themselves as integral membrane transporters. They are essential
in both bacterial physiology and defense and are responsible for exporting structurally diverse substrates,
falling into the following main families: ATP-binding cassette (ABC), multidrug and toxic compound extrusion
(MATE), major facilitator superfamily (MFS), small multidrug resistance (SMR) and resistance-nodulation-cell
division (RND). The Efflux pumps NorA and Tet(K) of the MFS family, MepA of the MATE family, and
MsrA of the ABC family are some examples of specific efflux pumps that act in the extrusion of antibiotics. In
this review, we address bacterial efflux pump inhibitors (EPIs), including 1,8-naphthyridine sulfonamide derivatives,
given the pre-existing knowledge about the chemical characteristics that favor their biological activity.
The modification and emergence of resistance to new EPIs justify further research on this theme, aiming to develop
efficient compounds for clinical use.
Renal Stem Cells, Renal Resistive Index, and Neutrophil Gelatinase Associated
Lipocalin Changes After Revascularization in Patients With Renovascular Hypertension
and Ischemic Nephropathy
Authors: Simeoni Mariadelina , Cianci Rosario , Gigante Antonietta , Marco Perrotta Adolfo , Ronchey Sonia , Mangialardi Nicola , Schioppa Annalisa , De Marco Oriana , Cianci Eleonora , Barbati Cristiana , Lai Silvia , Ferri Claudio 
Published: December 2022

Background:
Percutaneous transluminal renal angioplasty (PTRA) with or without stenting is the
gold standard therapy in patients with atherosclerotic renal artery stenosis (aRAS). However, therapeutic success
depends on the correct timing of revascularization and the reversibility of the renal damage.

Materials and Methods:
We report a case series of patients treated with PTRA for renovascular hypertension
and ischemic nephropathy. We measured bilateral renal resistive index (RRI), circulating renal stem cells
(RSC), and Neutrophil Gelatinase Associated Lipocalin (NGAL) at baseline and after PTRA at different time
points to understand their changes in post-revascularization.

Results:
At baseline, the studied patients (n = 5) had different RSC levels. After PTRAs, all patients showed an
improvement in blood pressure, while renal function varied differently within the studied subjects. RRI > 0.75
at baseline and the absence of NGAL decrease after PTRAs were associated with post-PTRA renal function
worsening, despite an increase of RSC in all patients.

Conclusions:
Although limited to a few patients, our observation allowed the exploration of the behaviour of the
studied parameters in different degrees of renal ischemia. This revealed different disease models suggesting the
importance of further investigations in larger and homogeneous cohorts to confirm that a greater basal RSC percentage,
low RRI values before PTRA, and a post-revascularization NGAL reduction could be related to better
renal outcomes in aRAS patients.
Liposome Based Drug Delivery for the Management of Psoriasis -
A Comprehensive Review
Authors: Bahadur Shiv , Sharma Manisha 
Published: December 2022

Abstract:
Psoriasis has been considered as a chronic inflammatory skin disease which leads to the
dysfunction of immune systems. According to the World Psoriasis Day consortium, psoriasis affects
around 125 million individuals globally or about 2% to 3% of the overall population. Most of the
conventional drug delivery systems primarily attempt to relieve symptoms of psoriasis and are ineffective
in providing targeted action and higher bioavailability because of the drug's short half-life
and instability, as well as they lack safety and efficacy. The shortcomings of conventional drug
delivery systems give rise to the development of novel drug delivery systems which includes
liposomes, transferosomes, ethosomes, niosomes, emulsomes, dendrimers, hydrogel, nanoparticles,
etc. These novel formulations may enhance the therapeutic effects by changing physiological and
pharmacokinetic parameters. Several research reports suggest that these novel drug delivery systems
may enhance therapeutic effects which can be used as a promising approach for the treatment of
psoriasis. The liposomes based drug delivery system have been considered as most promising vehicles
for enhancing therapeutic potentials of drugs into or through the skin upon topical application.
Liposomes have small unilamellar vesicles which may enhance the penetration ability through stratum
corneum layer of skin. Therefore, present review article highlights on the different aspects of
the liposomes as potential drug delivery system for the treatment of psoriasis.
The Characteristics of Green-synthesized Magnesium Oxide Nanoparticles
(MgONPs) and their Biomedical Applications
Authors: Chandrasekaran Rajkuberan , Kuca Kamil , Patil Sunita , Krishnan Muthukumar 
Published: December 2022

Abstract:
In the current epoch, noble metals/metal oxides with precise structures are needed to develop sustainable products to improve the welfare of human beings and the environment. Nanomaterials in the regime 1 -100 nm scale are a promising material for the research fraternities owing to their stupendous properties. The metallic/metal oxide nanoparticles ( silver, gold, copper oxide, iron oxide, magnesium oxide) are gaining significant momentum and need to be extensively studied. Magnesium oxide nanoparticles (MgONPs) are a periclase, white hygroscopic material consisting of Mg2+ ions and O-2 ions in lattice arranged. These nanoparticles can be fabricated through physical, chemical and biological methods. The development of green synthesized MgONPs needs to be ascertained and explored its ultimate in medicine, health, cosmetics, environmental protection, chemical industries, and energy. Therefore, the present review manifests the green synthetic approaches of MgONPs and their impact on crystalline structure and shape. Further, we have provided the antibacterial and anticancer activities of MgONPs thoroughly reported in various kinds of literature. Overall, the unique MgONPs can be plausibly used as safe biomaterials in biomedical applications.