bluuebunny/crossref_metadata_2025_split huggingface dataset:
One-Step Combinatorial Strategy for Optimization of Antibiotics With Plant Extract Against Drug Resistant Clinical Bacteria
Authors: Gideon Mathew , Ladan Zakari 
Published: September 2022

Abstract

Antimicrobial resistance (AMR) is one of the most worrying health problems worldwide, antimicrobial research with reference to medicinal plants is a growing domain, likewise the synergism between plant extract and antibiotics.
The present study seeks to propose and develop uses a simple, safe, less time consuming, cost-effective, and eco-friendly strategic synthetic methods to overcome antibiotic resistance in bacteria using ethnopharmacological approach with conventional antibiotics. Concentrated sulphuric acid and 10% sodium hydroxide were used in combinatorial synthesis of Calotropis procera extract with Amoxicillin and Ampicillin.to validate the positive results obtain in stage one,Piliostigma reticulatum extract was combine with 100 µg/mL of azithromycin and again with 100 µg/ml of ampicillin with 0.1 mL, 0.2 mL and 0.3 mL of the acid to validate and a different bacteria strain was also introduced.
Higher inhibitions zone were observed at 16.7 mm for salmonella spp, 16.4 mm shigella spp, 16.8 mm S. aureus, 21.3 mm E.coli and 22.4 mm streptococusat situations where antibiotics inhibitions zones was 0 mm.
The results obtained shows that acid combinatorial synthesis of antibiotic with plant extract successfully overcame the resistance threat poses by the clinical bacteria isolates as compared to earlier versions, thus shows that synergistic effects on resistant bacteria can not only be achieved in situation where the antibiotics have already shown some degree of antibacterial activity on the tested pathogens but also in little concentrations were the antibiotic does not show antimicrobial activities.
Role of “banker plants” as a sustainable integrated Pectinophora gossypiella (Saunders) and Earias insulana (Boisd.) management
Authors: Mesbah H. A. , Massoud M. A. , El-Kady M. B. , Henady Z. M. , El-Bassouiny H. M. 
Published: September 2022

Abstract
To confront global demand to reduce the use of pesticides and its risk, this study tested the effectiveness of okra and corn as banker plants with Trichogramma evanescens release as a green innovation technology for the sustainable management of cotton bollworms in comparison to conventional chemical pesticides and the release of T. evanescens alone (control). We found that okra and corn with T. evanescens release were more effective in decreasing the incidence of cotton bollworms than the conventional chemical pesticides or T. evanescens alone. We also found that okra and corn encouraged the spread of bollworm natural enemies in the treated cotton fields, which had a large impact on the number of cotton bollworm larvae, thus reducing the need for conventional pesticides. Thus, banker plants combined with T. evanescens release can support agrobiodiversity and help realize the Sustainable integrated management strategies of the cotton bollworm by reducing the use of conventional chemical pesticides, encouraging the natural enemies. Thus, contributing to global warming reduction which caused by the overuse of conventional chemical pesticides.
Seeking for the correlation between the Chemometric Indices of ATR-FTIR Spectroscopy and Multidetector CT obtained Density on Bones Exposed to Heat
Authors: Leskovar Tamara , Cavalli Fabio , Legan Lea , Innocenti Dario , Ropret Polonca , Črešnar Matija 
Published: September 2022

Abstract

Charred and burned human and animal skeletal remains are frequently found in archaeological records or can be a subject of forensic investigation. As exposure to heat causes specific changes to the physical and chemical characteristics of the remains, it presents a powerful source for a better understanding of the taphonomic history of the remains. FTIR spectroscopy is a commonly used technique when trying to understand these changes and through them the taphonomic history of the remains. Recently, density calculated from CT scans is also incorporated into this type of study. The main objective of here presented research is to establish a correlation between the chemometric indices obtained with ATR-FTIR spectroscopy and density obtained with Multidetector CT. To the best of our knowledge, the correlation between the two was never explored before. For this purpose, the midsection of defleshed bovine femur diaphyses were exposed to different temperatures for various time spans and analysed with ATR-FTIR spectroscopy and Multidetector CT. ATR-FTIR obtained results, namely the changes in the organic and mineral bone components, agree with previous studies and provide a baseline for understanding the changes in the density. The latter decreases and increases depending on the loss of organic matter, crystallization, cyanamides and hydroxyl groups incorporation into the mineral lattice, and ordering of the lattice. Additionally, significant differences were observed in the changes caused due to short- or long-term exposure to heat. With some additional work, even machine learning algorithms could be applied to the samples with an unknown taphonomic history to better understand the time and temperatures of their exposure. Furthermore, this type of research also provides important data for planning non-destructive analyses of ancient remains.
Landslide Hazard and Susceptibility Maps Derived from Satellite and Remote Sensing Data Using Limit Equilibrium Analysis and Machine Learning Model
Authors: Dashbold Batmyagmar , Bryson L. Sebastian , Crawford Matthew M. 
Published: September 2022

Abstract

Landslide susceptibility mapping and landslide hazard mapping are approaches used to assess the potential for landslides and predict the occurrence of landslides, respectively. We evaluated and tested a limit equilibrium approach to produce a local-scale, multi-temporal Geographic Information System (GIS)-based landslide hazard map that utilized satellite soil moisture data, soil strength and hydrologic data, and a high-resolution (1.5 m) LiDAR-derived digital elevation map (DEM). The final multi-temporal landslide hazard map was validated temporally and spatially using four study sites at known landslide locations and failure dates. The resulting product correctly indicated low factor of safety values at the study sites on the dates the landslide occurred. Also, we produced a regional-scale landslide susceptibility map using a logistic regression machine learning model using 15 variables derived from the geomorphology, soil properties, and land cover data. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was used for the accuracy of the model, which yielded a success rate of 0.84. We show that using publicly available data, a multi-temporal landslide hazard map can be created that will produce a close-to-real time landslide predictive map. The landslide hazard map provides an understanding into the evolution of landslide development temporally and spatially, whereas the landslide susceptibility map indicates the probability of landslides occurring at specific locations. When used in tandem, the two mapping models are complementary to each other. Specifically, the landslide susceptibility mapping identifies the areas most susceptible to landslides while the landslide hazard mapping predicts when landslide may occur within the identified susceptible area.
Security Enhancements in M-Health Using Distributed Ledger Technology based Digital Locker System
Authors: Ray Soumya , Mishra Kamta Nath , Dutta Sandip 
Published: September 2022

Abstract

Electronic Medical Records (E.M.Rs) comprise sensitive and private information of the patients in m-healthcare, and the passing of data across different medical institutions poses severe challenges. Leakage of information could destroy the privacy of the data, and the availability of the data at runtime may be disrupted by the DDoS (Distributed Denial of Service) attack. Distributed Ledger Technology (DLT) helps overcome the challenges of the trusted decentralized database. It is possible to validate all the stakeholders by a single-step authentication process using distributed ledger technology. In this research paper, the authors have proposed a distributed ledger technology architecture (DLTA) using an m-health digital locker (DL) system and presented the interaction of the different m-healthcare entities with the anticipated model. The authors have designed the mathematical model to enhance the security re-assurance of the DLTA-based m-health DL system. The security analysis of the proposed model is highlighted and compared the same with the non-distributed system architecture. The key factors considered for evaluating the proposed model are network congestion, throughput, average turnaround time, average response time, average waiting time, and network consumption.
Early diagnosis by mNGS could improve the prognosis for severe leptospirosis patients
Authors: Jiang# Xuqin , Jiang# Hui , Xiong# Yingying , Fang# Ming , Geng Bei , Wu* Huimei , Mei* Xiaodong 
Published: September 2022

Abstract

PurposesTo evaluate the diagnostic efficiency of metagenomics next generation sequencing (mNGS) assay in severe leptospirosis and its role on prognosis.
Methods We retrospectively reviewed the medical records of patients with confirmed leptospirosis from Jan. 1, 2019 to Dec. 31, 2021 from three hospitals. Detailed data including socio-demographic data, clinical manifestations, laboratory examination results, CT images etc. were collected and analyzed.
Results Six severe cases were included in this study. All were diagnosed by positive mNGS results. Three of the patients were also polymerase chain reaction examined and presented negative results. Five patients were diagnosed by mNGS assay within two or three days and antibiotics were down-graded to ceftriaxone in them. All of them were cured finally. One case, who was diagnosed by mNGS late on day 5, died.
Conclusions mNGS is highly efficient in diagnosing leptospirosis and could possibly reduce the mortality rate if used at an early stage.
COPRAO: A Rule-Based Capability-Aware Query Optimizer for an FPGA-Based Reconfigurable Near-Data Processor
Authors: B.G. Lekshmi , Meyer-Wegener Klaus 
Published: September 2022

Abstract
Placing the processing power near the data, rather than shipping the data to the processor is inevitable and demanding in the era of Big Data. With a given near-data processor, it is important to use it properly to reduce the massive data transfer between data sources and computing nodes. In database query processing, as many operations as possible should be sent to the near-data processor, because it can process them at line-rate and thus can eliminate massive data transfer across the network. Unfortunately, there is still not enough support for effective utilization of hardware capabilities to solve the issues of data processing in query processors. In this paper, we propose a new approach to the query optimization in a relational DBMS, which considers the specialized computing capabilities of the attached FPGA-based near-data processor. We use extended rules to achieve hardware-conscious optimization and refine the optimization strategies according to changes in the hardware state. Our evaluations demonstrate that the proposed query-optimization approach can improvethe processing of queries.
A realist evaluation of the feasibility of a digital music and movement intervention for older people living in care homes
Authors: Ofosu Esther Frema , De Nys Len , Connelly Jenni , Ryde Gemma. C. , Whittaker Anna. C. 
Published: September 2022

Abstract

Background
Low physical activity in care home residents brings about negative mental health consequences, such as higher levels of depression and loneliness. With advancements in communication technology, particularly during the COVID-19 pandemic, the feasibility and effectiveness of digital Physical Activity (PA) resources in care homes deserve more research attention. A realist evaluation was used to uncover influencing factors of a feasibility study implementation to inform how a digital music and movement programme would work and under what circumstances this would be most effective.
Methods
Participants were 49 older adults (aged 65 years+) recruited across ten care homes in Scotland. Surveys were administered at baseline and post-intervention comprising psychometric questionnaires on multidimensional health markers validated in older adults with possible cognitive impairment. The intervention comprised 12 weeks of four prescribed digitally delivered movement (n = 3) and music-only (n = 1) sessions per week. An activity coordinator delivered these online resources in the care home. Post-intervention focus groups with staff and interviews with a sub-sample of participants were conducted to gain qualitative data on the acceptability of the intervention.
Results
33 care home residents started the intervention, but only 18 residents (84% female) completed both pre- and post-intervention assessments. Activity coordinators (AC) offered 57% of the prescribed sessions, with an average residents’ adherence of 60%. ACs and residents mentioned improved mood, physical health, job satisfaction and social support. Improvements with large effect sizes were found for anxiety, depression, loneliness, perceived stress and sleep satisfaction, but no changes in fear of falling, domains of general health or appetite. Delivery challenges were (1) motivation and engagement, (2) changes in cognitive impairment and disabilities of the participants, (3) death or hospitalisation of the participants and (4) limited staffing and technology resources to deliver the programme as intended.
Conclusion
This realist evaluation suggested that this digitally delivered movement and music intervention is feasible. From the findings, the initial programme theory was refined for future implementation of an RCT in other care homes.
Trial registration:
retrospectively registered at ClinicalTrials.gov NCT05559203
Resistensi Masyarakat terhadap Kebijakan Penanganan COVID-19: Studi di Desa Jawisari Kabupaten Kendal
Authors: Wijayanti Tiara Candra , Mahsun Muhammad 
Published: October 2022

Pandemi Covid-19 membawa dampak yang signifikan utamanya pada sektor kesehatan dan ekonomi. Hal ini mendorong pemerintah untuk segera mengambil kebijakan pembatasan kegiatan sosial yang dirumuskan dalam kebijakan PSBB dan PPKM dari level 1-4. Kebijakan tersebut banyak mendapatkan perlawanan hampir di seluruh wilayah di Indonesia, sehingga banyak sarjana yang tertarik untuk menemukan penyebab dari resistensi yang dilakukan masyarakat guna optimalisasi kebijakan yang diambil pemerintah terkait penanganan Covid-19. Dengan mengkaji kasus resistensi masyarakat Desa Jawisari terhadap kebijakan penanganan Covid-19. Kajian ini berusaha untuk menjawab dua pertanyaan penelitian. Pertama Bagaimana Bentuk Resistensi Masyarakat Desa Jawisari Terhadap Himbauan Pemerintah dalam Penanganan Penyebaran Covid-19 ? Kedua Mengapa Masyarakat Desa Jawisari Resisten Terhadap Himbauan Pemerintah dalam Penanganan Penyebaran Covid-19?. Studi ini menggunakan teori resistensi James Scott yang menjelaskan mengenai perlawanan kaum tani akibat dominasi dari kaum proletar. Penelitian ini menggunakan metode penelitian kualitatif dengan pendekatan studi kasus untuk memperoleh data mengenai resistensi masyarakat terkait kebijakan penanganan Covid-19 di Desa Jawisari. Data primer diperoleh dari hasil wawancara, observasi dan studi literatur penelitian terdahulu. Kajian ini menemukan bentuk-bentuk resistensi yang dilakukan oleh masyarakat Desa Jawisari terbagi menjadi tiga bentuk yaitu resistensi terbuka, resistensi tertutup dan resistensi defensif . Studi ini juga menemukan ada beberapa faktor yang melatarbelakangi perlawanan tersebut diantaranya tidak mendapatkan BLT-DD, kepedulian terhadap pendidikan, pemenuhan kehidupan sehari-hari, desakan jama’ah, sosialisasi yang kurang efektif serta tenaga kesehatan yang kurang maksimal dalam menangani pandemi Covid-19.
Simultaneous identification of the number, location and release intensity of groundwater contamination sources based on simulation optimization and ensemble surrogate model
Authors: Li Jiuhui , Wu Zhengfang , Lu Wenxi , He Hongshi 
Published: September 2022

Abstract
In most instances, the number, location and release intensity of groundwater contamination sources (GCSs) are all unknown. The 0-1 mixed integer nonlinear programming optimization model (0-1 MINPOM) used previously could only identify the location and release intensity for GCSs. Thus a 0-1 MINPOM was improved and applied to simultaneously identify the number, location and release history of GCSs. In addition, to reduce the time of calling the simulation model for iterative calculation, the deep belief neural network (DBNN), long short-term memory network (LSTM) and Kriging method were applied to establish an ensemble surrogate model of the simulation model to replace the simulation model for iterative calculation. The results show that compared with the three single surrogate models, the ensemble surrogate model has the highest approximation accuracy to the simulation model, and could save 99% of the calculation time when iterative calculation was performed in place of the simulation model. The improved 0-1 MINPOM could identify the number, location, and release history of GCSs simultaneously. The accuracy of identifying the number of GCSs was 100%, and the accuracies of identifying the locations and release history were above 95.12% and 83.51%, respectively.
Development of seismic vulnerability index for water distribution network (SVI-WDN) in the province of Special Region of Yogyakarta, Indonesia: A conceptual framework
Authors: Marleni Ni Nyoman Nepi , Devi Elsa Febriana , Kamulyan Budi 
Published: September 2022

Abstract
The Special Region of Yogyakarta is one of the areas impacted by the 2006 earthquake which damaged vital infrastructures, including water distribution networks (WDN). The vulnerability of these networks increases because the design process does not consider the mitigation strategy of natural disasters. This region does not have any tools to estimate the infrastructure vulnerability for underground lifeline facilities, including WDN. Therefore, this study aimed to develop a framework to generate a Seismic Vulnerability Index for Water Distribution Network (SVI-WDN) for the Special Region of Yogyakarta which has been known to be exposed to many earthquake incidences. The framework presents a process to develop a SVI-WDN which consist of three steps. First step, to obtain the criteria, sub-criteria, their value range and the corresponding score for each value. Second step, to normalize the sub-criteria score. The third step, to obtain the criteria and sub-criteria weight by using the analytical hierarchy process (AHP). Lastly, the calculation of a vulnerability index for water distribution. Additional steps for visualizing the index are by generating a geographical information system map representing index value. Thus, this study presents a reproducible framework that can assist water authorities to prioritize the water distribution pipe segment which requires more intensive handling and maintenance.
Pumping schedule assignment using chromatic graphs to reduce groundwater pumping energy consumption
Authors: Nagkoulis Nikolaos , Kontos Yiannis N. , Katsifarakis Konstantinos L. 
Published: September 2022

Abstract
In this paper, groundwater pumping schedules are examined, in terms of pumping energy consumption minimization. Chromatic graphs are used for the first time to assign groundwater pumping schedules. Assuming that a finite number of users pumps from a common aquifer, we examine the following three pumping scenarios: (a) all users pump simultaneously, (b) users pump during one out of two different periods, (c) users pump during one out four different periods. A computational code, based on Theis equation, is constructed to calculate the drawdowns and, subsequently, the energy consumption, for various well locations, numbers of wells, flow rates, pumping period durations and aquifers' characteristics. We use nearest neighbor graphs and chromatic graphs to represent the interactions of the well users. We compare the results obtained when chromatic graphs are used, to the optimum, which is obtained using genetic algorithms (GAs). Our results indicate that: (a) performance of chromatic graphs is good, (b) when two pumping periods are used, it is sufficient for each player to cooperate with their nearest neighbor and pump alternately. In typical cases, the energy consumption reduction can be around 10–40%. The benefit is even higher if four pumping periods are used.
Analysis on competition strategy and regulatory strategy of international river water resources system – with the participation of co-operational agencies
Authors: Xu Hao , Chen Liuxin , Li Qiongfang 
Published: September 2022

Abstract
In order to reasonably allocate water resources, meet the water demand of water users, and solve the frequent conflicts of water resources in international rivers, this paper explores the optimal regulation strategy of water resources with the participation of co-operational agency based on game model. Our results show that: for water users, the regulatory strategy of co-operational agencies affects the competition of water users, and the competition strategies among water users also affect each other. The economic benefits of water resources, water withdrawal costs, fine and honor value all affect the water resources competition strategy of water users. For co-operational agencies, the competition strategy of water users affects the regulatory strategy of co-operational agencies. The intensity of penalization and the regulatory cost have an impact on the regulatory strategy of co-operational agencies, but the amount of operation funds of co-operational agencies does not affect its regulatory strategy. The research shows the water resources game process of international rivers with the participation of co-operational agencies, and provides some insights for the water resources regulation of international rivers.
The LL-37 Antimicrobial Peptide as a Treatment for Systematic Infection
of Acinetobacter baumannii in a Mouse Model
Authors: Abtahi Hamid , Zarei-Mehrvarz Ehsan , Fahimirad Shohreh , Ghaznavi-rad Ehsanollah , Abbasian Shabnam Sadoogh 
Published: September 2022

Background:
The antimicrobial peptides (AMPs) played a critical role in the innate immunity of host and considered natural sources illustrating a broad-spectrum antimicrobial activity with high specificity and low cytotoxicity. AMPs generally possess a net positive charge and have amphipathic structures. Thus, AMPs can bind and interact with negatively charged bacterial cell membranes, leading to destructive defects in biomembranes and ending in cell death. LL37 is only human cathelicidin-derived antimicrobial peptide which show a broad spectrum of antimicrobial activity.

Materials and Methods:
To determine the antibacterial efficiency of LL37 in a mouse model of systemic A. baumannii infection, LL37 corresponding gene was expressed in E.coli, purification and refolding situations were optimized. The antimicrobial performance of produced LL-37 against A. baumannii was evaluated in vitro via MIC and Time Kill assays, and its destructive effects on the bacterial cell were confirmed by SEM image.

Results:
The recombinant LL37 showed strong antibacterial function against A. baumannii at 1.5 μg/mL concentration. Time kill assay showed a sharp reduction of cell viability during the first period of exposure, and complete cell death was recorded after 40 min exposure.

Conclusion:
Furthermore, in vivo results represented a significant ability of LL37 in the treatment of systematic infected mouse models, and all infected mice receiving LL37 protein survived without no trace of bacteria in their blood samples.