bluuebunny/crossref_metadata_2025 huggingface dataset:
Online Activity Recognition Combining Dynamic Segmentation and Emergent Modeling
Authors: Xu Zimin , Wang Guoli , Guo Xuemei
Published: March 2022

Activity recognition is fundamental to many applications envisaged in pervasive computing, especially in smart environments where the resident’s data collected from sensors will be mapped to human activities. Previous research usually focuses on scripted or pre-segmented sequences related to activities, whereas many real-world deployments require information about the ongoing activities in real time. In this paper, we propose an online activity recognition model on streaming sensor data that incorporates the spatio-temporal correlation-based dynamic segmentation method and the stigmergy-based emergent modeling method to recognize activities when new sensor events are recorded. The dynamic segmentation approach integrating sensor correlation and time correlation judges whether two consecutive sensor events belong to the same window or not, avoiding events from very different functional areas or with a long time interval in the same window, thus obtaining the segmented window for every single event. Then, the emergent paradigm with marker-based stigmergy is adopted to build activity features that are explicitly represented as a directed weighted network to define the context for the last sensor event in this window, which does not need sophisticated domain knowledge. We validate the proposed method utilizing the real-world dataset Aruba from the CASAS project and the results show the effectiveness.
High-Resolution Representations Network for Single Image Dehazing
Authors: Han Wensheng , Zhu Hong , Qi Chenghui , Li Jingsi , Zhang Dengyin
Published: March 2022

Deep learning-based image dehazing methods have made great progress, but there are still many problems such as inaccurate model parameter estimation and preserving spatial information in the U-Net-based architecture. To address these problems, we propose an image dehazing network based on the high-resolution network, called DeHRNet. The high-resolution network originally used for human pose estimation. In this paper, we make a simple yet effective modification to the network and apply it to image dehazing. We add a new stage to the original network to make it better for image dehazing. The newly added stage collects the feature map representations of all branches of the network by up-sampling to enhance the high-resolution representations instead of only taking the feature maps of the high-resolution branches, which makes the restored clean images more natural. The final experimental results show that DeHRNet achieves superior performance over existing dehazing methods in synthesized and natural hazy images.
Kinect v2-Assisted Semi-Automated Method to Assess Upper Limb Motor Performance in Children
Authors: Francisco-Martínez Celia , Padilla-Medina José A. , Prado-Olivarez Juan , Pérez-Pinal Francisco J. , Barranco-Gutiérrez Alejandro I. , Martínez-Nolasco Juan J.
Published: March 2022

The interruption of rehabilitation activities caused by the COVID-19 lockdown has significant health negative consequences for the population with physical disabilities. Thus, measuring the range of motion (ROM) using remotely taken photographs, which are then sent to specialists for formal assessment, has been recommended. Currently, low-cost Kinect motion capture sensors with a natural user interface are the most feasible implementations for upper limb motion analysis. An active range of motion (AROM) measuring system based on a Kinect v2 sensor for upper limb motion analysis using Fugl-Meyer Assessment (FMA) scoring is described in this paper. Two test groups of children, each having eighteen participants, were analyzed in the experimental stage, where upper limbs’ AROM and motor performance were assessed using FMA. Participants in the control group (mean age of 7.83 ± 2.54 years) had no cognitive impairment or upper limb musculoskeletal problems. The study test group comprised children aged 8.28 ± 2.32 years with spastic hemiparesis. A total of 30 samples of elbow flexion and 30 samples of shoulder abduction of both limbs for each participant were analyzed using the Kinect v2 sensor at 30 Hz. In both upper limbs, no significant differences (p < 0.05) in the measured angles and FMA assessments were observed between those obtained using the described Kinect v2-based system and those obtained directly using a universal goniometer. The measurement error achieved by the proposed system was less than ±1° compared to the specialist’s measurements. According to the obtained results, the developed measuring system is a good alternative and an effective tool for FMA assessment of AROM and motor performance of upper limbs, while avoiding direct contact in both healthy children and children with spastic hemiparesis.
Combination Layout of Traffic Signs and Markings of Expressway Tunnel Entrance Sections: A Driving Simulator Study
Authors: Fang Yong , Zhou Jiayi , Hu Hua , Hao Yanxi , Xiao Dianliang , Li Shaojie
Published: March 2022

To determine a better combination of signs and markings on expressway tunnel entrance sections, three types of typical signs and markings were compared and tested according to five indicators: speed, lane lateral offset, lane change behavior, fixation behavior, and operating load, using a driving simulator. The results identified that the obvious no overtaking and speed limit signs, combined with a layer of thin red pavement, had the most influence on drivers’ speed, and they led to the highest fixation frequency of static facilities, the longest average distance from the completion point of the lane change to the entrance, and the longest average lane change distance, which could help drivers to pass through tunnel entrance sections more smoothly. The location of the static facilities should be between 3 s before the tunnel entrance and 3 s after entering the tunnel, as this is the area where a driver’s relative viewpoint changes. The improper combination of warning signs and deceleration measures will affect a driver’s judgment, causing negative effects, such as premature lane changes and an increased operating load. The research results can provide a design basis and reference for the combination setting of safety signs and markings on tunnel entrance sections.
Moravian–Slovak Borderland: Possibilities for Rural Development
Authors: Vaishar Antonín , Šťastná Milada , Kramáreková Hilda
Published: March 2022

This article analyzes the question of how the change of geopolitical position in the rural region of Eastern Moravia, which was shifted from the center of the state on its border, is reflected. The paper shows how the originally marginal region transformed from an area with shepherd agriculture to an industrial area with a skilled workforce during the existence of Czechoslovakia and questions how to cope with the consequences of the reverse change into a marginal geopolitical position on the eastern border of Czechia. The paper considers the balance of migration, supplemented by the construction of new dwellings, to be a relatively complex indicator. It states that the region of Eastern Moravia is problematic in terms of further development, except for the northern part, which is affected by the suburbanization of Ostrava. As a result, it proposes to supplement the current orientation toward the manufacturing industry by creating conditions for the development of cultural tourism.
A Comprehensive Analysis of the Power Demand–Supply Situation, Electricity Usage Patterns, and the Recent Development of Renewable Energy in China
Authors: Mastoi Muhammad Shahid , Munir Hafiz Mudassir , Zhuang Shenxian , Hassan Mannan , Usman Muhammad , Alahmadi Ahmad , Alamri Basem
Published: March 2022

Renewable energy is now the world’s most reliable and sustainable solution to environmental pollution, the energy crisis, and social sustainability. In order to regulate renewable energies and ensure the sustainable development of renewable energy in China, a regulatory framework is imperative. Electricity demand and supply forecasting have become one of the most important topics for research on sustainable solutions to energy issues. This article analyzes the Chinese electric power industry structure by looking at historical electricity demand and supply data. This study shows how a divergent set of energy policies can facilitate the application of renewable energy to China’s electric power sector. The analysis shows that in 2020, China’s electricity generation and consumption increased by 0.9 and 1.3 percent annually, respectively, producing capacity of power plants increased by 5.6 GW, coal consumption of power supply decreased by 4.3 g/kWh, power generation projects investment increased by 51.6 billion RMB, power grid projects investment decreased by 1.8 billion RMB, and newly installed generation capacity increased by 769 GW year on year (YOY). During the first three quarters of 2021, the generation, consumption and coal consumption of electricity increased respectively by 10.7 and 12.9%, the generating capacity of power plants increased by 9.4 GW, the average coal consumption of power supply decreased by 0.9 g/kWh, power generation projects investment increased by 1.8 billion RMB, while power grid projects investment decreased by 0.3 billion RMB and new generation capacity added around 20.16 GW compared to the same period last year. Furthermore, domestic power consumption grew by 6.0% and 7%, respectively, in 2020–2021. The paper examines China’s current climate, developments, and renewable energy targets between 2020 and 2021. This research aims to identify the main risks associated with China’s renewable energy development and propose a few policy measures for risk management.
A Study on Temperature Distribution within HVDC Bushing Influenced by Accelerator Content during the Curing Process
Authors: Zhou Yuanxiang , Wang Xuewei , Teng Chenyuan , Zhang Yunxiao , Huang Xin , Chen Jianning
Published: March 2022

Power transmission technology plays an important role in energy sustainability. Bushing is an indispensable type of equipment in power transmission. In production, the accelerator changes the temperature distribution during the curing process, influencing the formation of defects and thus the safety output of renewable energy. In this study, uncured epoxy resin samples with different accelerator contents were prepared and measured by differential scanning calorimetry (DSC). The obtained heat flow curves were analyzed for curing kinetics. Then, the curing process of large length–diameter ratio bushings was simulated by using the finite element method combined with a curing kinetics model, transient Fourier heat transfer model, and stress–strain model. The study reveals that the curing system can be established by the Sestak–Berggren autocatalytic model with different accelerator contents. The overall curing degree and the maximum radial temperature difference of the capacitor core tend to increase and then decrease with the accelerator content. This is mainly attributable to the rapid exotherm excluding the participation of some molecular chains in the reaction, resulting in permanent under-curing. As the accelerator content increases, the strain peak decreases and then increases. This paper provides guidance for the comprehensive evaluation and manufacturing of the low-defect capacitor cores of large-size high voltage direct current (HVDC) bushings.
Measuring the Sustainability of the Orange Economy
Authors: Ferreiro-Seoane Francisco J. , Llorca-Ponce Alicia , Rius-Sorolla Gregorio
Published: March 2022

1. Background. The Orange economy includes creative and cultural activities; and it has aroused great interest, both for research on growth and for public agencies and institutions, which have highlighted its capacity as an economic engine and a generator of sustainable growth. Despite this widely disseminated argument, empirical evidence is scarce. 2. Methods. This paper aims to resolve that, based on an analysis of Orange economy companies in two Spanish regions—the Valencian and Galician Autonomous Communities—for the period between 2000 and 2019. Based on the SABI® database, which contains data from the annual accounts that companies must submit to Mercantile Registry, company’s data have been grouped into three large subgroups and within activity branches. 3. Results. The Orange economy revenues and earnings have contributed at a higher growth rate than of the economy as a whole. It has achieved higher profitability ratios on a lasting basis over time. Although, there are differences between the various activities included in this sector 4. Conclusions. The Orange economy can be considered as an engine and a generator of sustained growth over time. Furthermore, results obtained show that the Orange economy is a sector that is resilient against crisis.
Sustainable Development in Local Culture Industries: A Case Study of Taiwan Aboriginal Communities
Authors: Yang Cheng-Hsiang , Sun Yikang , Lin Po-Hsien , Lin Rungtai
Published: March 2022

Taiwan’s indigenous communities have an abundance of unique cultures. Their service industries with local and foreign cultures have opened up distinct opportunities for sustainable development. Despite the enormous potential of aboriginal communities, particular attention should be given to ecology and sustainability. The traditional emphasis on craftsmanship and design is shifting to a new focus on the service industries and experimental design, which is not limited to the design of tangible products. Design concepts are now being applied to service industries that span several fields and are also being used to come up with systematic solutions for real-life problems. However, in the service industry, design experience must be used when introducing design concepts. The problem is how to shift from “High-tech” to “High-touch”, for the aborigines are used to designing products at the usability level. This research proposes a model of experience design for use in aboriginal culture revitalization. Three different cases show how to apply the framework from experience design to local revitalization. Results show that the model can integrate the principles of sustainability into service industries and that it needs to be verified in future studies.
National Culture and Financial Inclusion: Evidence from Belt and Road Economies
Authors: Liaqat Idrees , Gao Yongqiang , Rehman Faheem Ur , Lakner Zoltán , Oláh Judit
Published: March 2022

Financial Inclusion is a key factor in achieving the sustainable development goals of the United Nations. The research in the area of financial inclusion is becoming more critical for scholars and policymakers. In previous studies, effects of formal institutions on financial inclusion have been explored. However, influence of informal institutions (culture) on financial inclusion remained untapped. To fill this gap, we investigate how national culture affects the financial inclusion of 81 Belt and Road economies using 17 years of data from 2004 to 2020. The empirical findings of the two-stage least square (2SLS) show that Hofstede’s cultural dimensions are significantly associated with financial inclusion with different signs and levels of magnitude. We find that financial inclusion is lower in countries where uncertainty avoidance and power distance is high and that the opposite is true for individualism and masculinity. The overall results are reliable to a series of robustness checks and provide a useful basis for policymakers, regulatory agencies, and other stakeholders in achieving the sustainable development goal of financial inclusion in Belt and Road countries.
A Systematic Review on the Local Wisdom of Indigenous People in Nature Conservation
Authors: Abas Azlan , Aziz Azmi , Awang Azahan
Published: March 2022

The local wisdom of indigenous people in nature conservation plays a critical part in protecting the planet’s biodiversity and the overall health of the ecosystems. However, at the same time, indigenous people and their lands are facing immense threats through modernization and globalization. This study aims to systematically review and analyze the local wisdom of the indigenous people in nature conservation. The present study integrated multiple research designs, and the review was based on the published standard, namely the PRISMA statement (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). This study used Web of Science (WoS) and Scopus as the main databases in searching for the required articles. Through content analysis, this study can be divided into seven main categories: (a) forest management, (b) flora and fauna conservation, (c) food security, (d) water management, (e) land management, (f) weather forecasting, and (g) others. The findings offer some basics on how academics can adopt and adapt the existing local wisdom of indigenous people in nature conservation into the scientific framework and design to answer the Sustainable Development 2030 Agenda.
The Effect of the Built Environment on the COVID-19 Pandemic at the Initial Stage: A County-Level Study of the USA
Authors: Guan Chenghe , Tan Junjie , Hall Brian , Liu Chao , Li Ying , Cai Zhichang
Published: March 2022

The COVID-19 pandemic affected how people interact with the built environment and ways of human habitation are facing significant challenges. However, the existing literature has not adequately addressed how the built environment affected the early prevalence of the pandemic. This research aims to extend the existing literature by relating the initial stage pandemic conditions with more comprehensive measures of the built environment including density, diversity, road network, and accessibility at the county level across the United States and conducting bi-weekly comparisons. We collected infection, death, and mortality data in 3141 counties between 1 March to 8 June 2020 and collected seventeen built environment attributes. Our results show that: (1) Road density and street intersection density were significantly associated with the infection rate; (2) Population density only maintained a positive correlation to the prevalence of COVID-19 during the first two weeks, after which the relationship became negative; and (3) Transit accessibility also contributed significantly to the pandemic and the accessibility of transit-oriented jobs was highly correlated to the infection rate in the first two weeks. The study provides valuable insights for policymakers and stakeholders to adopt resource allocation strategies for context-specific conditions.
LPI Radar Signal Recognition Based on Dual-Channel CNN and Feature Fusion
Authors: Quan Daying , Tang Zeyu , Wang Xiaofeng , Zhai Wenchao , Qu Chongxiao
Published: March 2022

The accuracy of low probability of intercept (LPI) radar waveform recognition is an important and challenging problem in electronic warfare. Aiming at the problem of the difficulty in feature extraction and the low recognition rates of the LPI radar signal under a low signal-to-noise ratio, and inspired by the symmetry theory, we propose a new approach for the LPI radar signal recognition method based on a dual-channel convolutional neural network (CNN) and feature fusion. Our new approach contains three main modules: the preprocessing module that converts the LPI radar waveforms into two-dimensional time-frequency images using the Choi–Williams distribution (CWD) transformation and performs image binarization, the feature extraction module that extracts different features obtained from the images, and the recognition module that utilizes a multi-layer perceptron (MLP) network to fuse these features and distinguish the type of LPI radar signals. In the feature extraction module, a two-channel CNN model is proposed that extracts Histogram of Oriented Gradients (HOG) features and deep features from time-frequency images, respectively. Finally, the recognition module recognizes the radar signals using a Softmax classifier based on the fused features from two channels. The experimental results from 12 types of LPI radar signals prove the superiority and robustness of the proposed model. Its overall recognition rate reaches 97% when the signal-to-noise ratio is −6 dB.
Automated Detection of Sudden Cardiac Death by Discrete Wavelet Transform of Electrocardiogram Signal
Authors: Shi Manhong , Yu Hongjie , Wang Hongjie
Published: March 2022

Sudden cardiac death (SCD) results in millions of deaths annually; as it is a fatal heart abnormality, early prediction of SCD could save peoples’ lives to the greatest extent. Symmetry and asymmetry play an important role in many fields. Electrocardiograms (ECG) as a noninvasive process for acquiring the electrical activity of the heart, has both asymmetric and non-stationary characteristics; it is frequently employed to diagnose and evaluate the heart’s condition. In this work, we have detected SCD 14 min (separately for each one-minute interval) prior to its occurrence by analyzing ECG signals using discrete wavelet transform (DWT) and locality preserving projection (LPP). In the experiment, we have performed DWT on ECG signals to obtain coefficients, then LPP as a reduction methodology was used to cut down these obtained coefficients. Then, the acquired LPP features were ranked using various methods, including the T-test, Bhattacharyya, Wilcoxon, and entropy. At last, the highly ranked LPP features were subjected to decision tree, k-nearest neighbor (KNN), and support vector machine classifiers for distinguishing normal from SCD ECG signals. Our proposed technique has achieved a highest accuracy of 97.6% for the detection of SCD 14 min prior using the KNN classifier, compared to the existing works. Our proposed method is capable of predicting the people at risk of developing SCD 14 min before its onset, and, hence, clinicians would have enough time to provide treatment in intensive care units (ICU) for a subject at risk of SCD. Thus, this proposed technique as a useful tool can increase the survival rate of many cardiac patients.
Computational Optimization of the 3D Least-Squares Matching Algorithm by Direct Calculation of Normal Equations
Authors: Liebold Frank , Maas Hans-Gerd
Published: March 2022

3D least-squares matching is an algorithm that allows to measure subvoxel-precise displacements between two data sets of computed tomography voxel data. The determination of precise displacement vector fields is an important tool for deformation analyses in in-situ X-ray micro-tomography time series. The goal of the work presented in this publication is the development and validation of an optimized algorithm for 3D least-squares matching saving computation time and memory. 3D least-squares matching is a gradient-based method to determine geometric (and optionally also radiometric) transformation parameters between consecutive cuboids in voxel data. These parameters are obtained by an iterative Gauss-Markov process. Herein, the most crucial point concerning computation time is the calculation of the normal equations using matrix multiplications. In the paper at hand, a direct normal equation computation approach is proposed, minimizing the number of computation steps. A theoretical comparison shows, that the number of multiplications is reduced by 28% and the number of additions by 17%. In a practical test, the computation time of the 3D least-squares matching algorithm was proven to be reduced by 27%.
Incidence, Disease Severity, and Follow-Up of Influenza A/A, A/B, and B/B Virus Dual Infections in Children: A Hospital-Based Digital Surveillance Program
Authors: Obermeier Patrick E. , Seeber Lea D. , Alchikh Maren , Schweiger Brunhilde , Rath Barbara A.
Published: March 2022

Influenza virus (IV) coinfection, i.e., simultaneous infection with IV and other viruses, is a common occurrence in humans. However, little is known about the incidence and clinical impact of coinfection with two different IV subtypes or lineages (“dual infections”). We report the incidence, standardized disease severity, and follow-up of IV dual infections from a hospital-based digital surveillance cohort, comprising 6073 pediatric patients fulfilling pre-defined criteria of influenza-like illness in Berlin, Germany. All patients were tested for IV A/B by PCR, including subtypes/lineages. We assessed all patients at the bedside using the mobile ViVI ScoreApp, providing a validated disease severity score in real-time. IV-positive patients underwent follow-up assessments until resolution of symptoms. Overall, IV dual infections were rare (4/6073 cases; 0.07%, incidence 12/100,000 per year) but showed unusual and/or prolonged clinical presentations with slightly above-average disease severity. We observed viral rebound, serial infection, and B/Yamagata-B/Victoria dual infection. Digital tools, used for instant clinical assessments at the bedside, combined with baseline/follow-up virologic investigation, help identify coinfections in cases of prolonged and/or complicated course of illness. Infection with one IV does not necessarily prevent consecutive or simultaneous (co-/dual) infection, highlighting the importance of multivalent influenza vaccination and enhanced digital clinical and virological surveillance.
Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2
Authors: Ferrari Gianlupi Juliano , Mapder Tarunendu , Sego T. J. , Sluka James P. , Quinney Sara K. , Craig Morgan , Stratford Robert E. , Glazier James A.
Published: March 2022

We extend our established agent-based multiscale computational model of infection of lung tissue by SARS-CoV-2 to include pharmacokinetic and pharmacodynamic models of remdesivir. We model remdesivir treatment for COVID-19; however, our methods are general to other viral infections and antiviral therapies. We investigate the effects of drug potency, drug dosing frequency, treatment initiation delay, antiviral half-life, and variability in cellular uptake and metabolism of remdesivir and its active metabolite on treatment outcomes in a simulated patch of infected epithelial tissue. Non-spatial deterministic population models which treat all cells of a given class as identical can clarify how treatment dosage and timing influence treatment efficacy. However, they do not reveal how cell-to-cell variability affects treatment outcomes. Our simulations suggest that for a given treatment regime, including cell-to-cell variation in drug uptake, permeability and metabolism increase the likelihood of uncontrolled infection as the cells with the lowest internal levels of antiviral act as super-spreaders within the tissue. The model predicts substantial variability in infection outcomes between similar tissue patches for different treatment options. In models with cellular metabolic variability, antiviral doses have to be increased significantly (>50% depending on simulation parameters) to achieve the same treatment results as with the homogeneous cellular metabolism.
Assessment of Satisfaction with Pharmacist-Administered COVID-19 Vaccinations in France: PharmaCoVax
Authors: Piraux Arthur , Cavillon Marie , Ramond-Roquin Aline , Faure Sébastien
Published: March 2022

Background: COVID-19 vaccines are among the most effective measures to reduce serious illness and death from infection with the highly contagious SARS-CoV-2 virus. To improve vaccine accessibility, pharmacists in France have been authorized to administer COVID-19 vaccinations since March 2021. This study aims to assess satisfaction among French people receiving their COVID-19 vaccination from a community pharmacist. Methodology: The PharmaCoVax study was conducted in French community pharmacies from 16 March to 30 June 2021. Interested pharmacists completed an online participation form, giving them access to the self-administered questionnaire. People receiving a pharmacist-administered COVID-19 vaccination completed this questionnaire in the pharmacy. Results: Among the 442 pharmacists involved, 123 actively participated in the study. Overall, 5733 completed questionnaires were analyzed. A proportion of 59% (n = 3388) of those who received a pharmacist-administered COVID-19 vaccination had previously received their influenza vaccination, most often in the same pharmacy (n = 1744). Only 24% (n = 1370) of people visiting a pharmacy had tried to obtain their COVID-19 vaccination elsewhere. Satisfaction was excellent with a rating of 4.92 out of 5.00, and the net promoter score was 93. Conclusions: The pharmacist-administered COVID-19 vaccination service was overwhelmingly appreciated by users. The trust placed in pharmacists may explain the desire to have them perform additional vaccinations.
SARS-CoV-2 T-Cell Responses in Allogeneic Hematopoietic Stem Cell Recipients following Two Doses of BNT162b2 mRNA Vaccine
Authors: Clémenceau Béatrice , Guillaume Thierry , Coste-Burel Marianne , Peterlin Pierre , Garnier Alice , Le Bourgeois Amandine , Jullien Maxime , Ollier Jocelyn , Grain Audrey , Béné Marie C. , Vié Henri , Chevallier Patrice
Published: March 2022

Background: At variance to humoral responses, cellular immunity after anti-SARS-CoV-2 vaccines has been poorly explored in recipients of allogeneic hematopoietic stem-cell transplantation (Allo-HSCT), especially within the first post-transplant years where immunosuppression is more profound and harmful. Methods: SARS-CoV-2 Spike protein-specific T-cell responses were explored after two doses of BNT162b2 mRNA vaccine in 45 Allo-HSCT recipients with a median time from transplant of less than 2 years by using INF-γ ELISPOT assay and flow-cytometry enumeration of CD4+ and CD8+ T lymphocytes with intracellular cytokine production of IFN-γ and TNF-α. Results: A strong TNF-α+ response from SARS-CoV-2-specific CD4+ T-cells was detected in a majority of humoral responders (89%) as well as in a consistent population of non-humoral responders (40%). Conclusions: T-cells are likely to participate in protection against COVID-19 viral infection, even in the absence of detectable antibody response, especially in the first years post-transplant in Allo-HSCT recipients.
Blood Inflammatory, Hydro-Electrolytes and Acid-Base Changes in Belgian Blue Cows Developing Parietal Fibrinous Peritonitis or Generalised Peritonitis after Caesarean Section
Authors: Coenen Marie-Charlotte , Gille Linde , Eppe Justine , Casalta Hélène , Bayrou Calixte , Dubreucq Pierre , Frisée Vincent , Moula Nassim , Evrard Julien , Martinelle Ludovic , Sartelet Arnaud , Bossaert Philippe , Djebala Salem
Published: March 2022

This study aimed to describe the inflammation, hydro-electrolyte and acid-base imbalances caused by generalised peritonitis (GP) and parietal fibrinous peritonitis (PFP) after caesarean section. After clinical examination, blood was sampled from 11 cows with PFP, 30 with GP and 14 healthy cows. Serum and plasma refractometry and glutaraldehyde tests were used to evaluate the inflammation level, while hydro-electrolytes and acid-base parameters were assessed using an EPOC® device. In addition to clinical signs of dehydration (>10%), blood analysis showed a high fibrinogen concentration (PFP: 8.64 ± 8.82 g/L; GP: 7.83 ± 2.45 g/L) and fast glutaraldehyde coagulation (<3 min) indicative of severe inflammation in both diseases compared to the control group (p < 0.05). Moreover, a severe decrease in electrolytes concentration (Na+: 126.93 ± 5.79 mmol/L; K+: 3.7 ± 1.3 mmol/L; Ca++: 0.89 ± 0.12 mmol/L; Cl−: 82.38 ± 6.45 mmol/L) and a significant increase in bicarbonate (30.87 ± 8.16 mmol/L), base excess (5.71 ± 7.42 mmol/l), L-lactate (8.1 ± 4.85 mmol/L) and creatinine (3.53 ± 2.30 mg/dL) were observed in cows with GP compared to the control group (p < 0.05). In contrast, few major perturbations were noticed in PFP, where only K+ (3.64 ± 0.25 mmol/L) and Ca++ (1.06 ± 0.09 mmol/L) were significantly modified (p < 0.05). In conclusion, a high dehydration and severe inflammation are induced by PFP and GP. Nevertheless, GP causes more electrolytes and acid-base disturbances than PFP.
Spatial Variation in Risk for Highly Pathogenic Avian Influenza Subtype H5N6 Viral Infections in South Korea: Poultry Population-Based Case–Control Study
Authors: Ahmad Saleem , Koh Kye-Young , Yoo Dae-Sung , Lee Jae-Il
Published: March 2022

Given the substantial economic damage caused by the continual circulation of highly pathogenic avian influenza (HPAI) outbreaks since 2003, identifying high-risk locations associated with HPAI infections is essential. In this study, using affected and unaffected poultry farms’ locations during an HPAI H5N6 epidemic in South Korea, we identified places where clusters of HPAI cases were found. Hotspots were defined as regions having clusters of HPAI cases. With the help of the statistical computer program R, a kernel density estimate and a spatial scan statistic were employed for this purpose. A kernel density estimate and detection of significant clusters through a spatial scan statistic both showed that districts in the Chungcheongbuk-do, Jeollabuk-do, and Jeollanam-do provinces are more vulnerable to HPAI outbreaks. Prior to the migration season, high-risk districts should implement particular biosecurity measures. High biosecurity measures, as well as improving the cleanliness of the poultry environment, would undoubtedly aid in the prevention of HPAIV transmission to poultry farms in these high-risk regions of South Korea.
A Socio-Economic and Environmental Analysis of the Implementation of Sustainable Urban Drainage Systems in Vega Baja—Alicante (Spain)
Authors: Ortuño Armando , Casares Jairo , Calero Paloma , Flor María , Iborra Vicente
Published: March 2022

One of the territories most affected by flooding in Spain is the district of Vega Baja del Segura, located in the southernmost point of the province of Alicante. The objective of this article is to estimate the socio-economic and environmental efficiency of implementing sustainable urban drainage systems (SUDS) as part of the Vega Baja Nature Plan. This plan seeks to optimise rainfall management by reproducing and restoring the natural hydrological processes altered by the urban development of cities through integrated actions that generate new natural areas to be used and enjoyed by the residents. To this end, a cost–benefit analysis was carried out in accordance with the methodology established by the European Commission, and a social profitability of 4.3% (IRR) was obtained for the project, which shows the social benefit to be gained from its execution.
On Hypsometric Curve and Morphological Analysis of the Collapsed Irrigation Reservoirs
Authors: Kim Donghyun , Kim Jongsung , Wang Wonjoon , Lee Haneul , Kim Hung Soo
Published: March 2022

The impact of irrigation reservoirs requires investigation through hydrological analysis to identify the flood control functions of these reservoirs. However, there is insufficient information concerning important geographical, morphological, and topographic characteristics, such as the reservoir cross-section. Therefore, this study aimed to identify the morphological and topographic characteristics of reservoirs using geographical information instead of measurement data. Ten reservoirs, including the Ga-Gog reservoir located in Miryang City, South Korea, were selected. The topographic information of the reservoirs was obtained using topographic maps and GIS techniques. Based on this information, the volume (V)-area (A)-depth (H) relationship and the hypsometric curve (HC) according to the relative area (a/A) and relative height (h/H) were created. A comparison of the reservoir volume, estimated using topographic information, with the measured volume revealed an error rate between 0.23% and 14.27%. In addition, two collapsed reservoirs located near Miryang City were investigated by creating V-A-H relationships and HCs using topographic information. The morphological characteristics of the reservoirs were identified by analyzing the (1) morphology index, (2) full water storage area-levee height relationship, and (3) full water storage area relationship. The analysis results showed that the collapsed reservoirs had high water depth and a large area relative to other reservoirs. Similar types of reservoirs were grouped by conducting a cluster analysis using basic properties such as the basin area, storage, and levee height. The cluster analysis results, based on HC analysis, grouped the reservoirs into three shapes: convex upward (youthful stage), relatively flat (mature stage), and convex downward (old stage). The HCs of the collapsed reservoirs exhibited a convex downward shape, indicating that they were subjected to considerable erosion due to aging. Moreover, this considerable erosion caused a large quantity of sediment to accumulate in the reservoirs, resulting in an insufficient allowable storage capacity of the reservoir because the flood control capacity was reduced, which may have led to their collapse during heavy rainfalls. Therefore, the identification of potential causes of reservoir collapse through the morphological characteristics and HCs of reservoirs are expected to support the operation and management of reservoirs to reduce flood damage.
BLP3-SP: A Bayesian Log-Pearson Type III Model with Spatial Priors for Reducing Uncertainty in Flood Frequency Analyses
Authors: Tian Dan , Wang Lei
Published: March 2022

Gauge stations have uneven lengths of discharge records owing to the historical hydrologic data collection efforts. For watersheds with limited water data length, the flood frequency model, such as the Log-Pearson Type III, will have large uncertainties. To improve the flood frequency prediction for these watersheds, we propose a Bayesian Log-Pearson Type III model with spatial priors (BLP3-SP), which uses a spatial regression model to estimate the prior distribution of the parameters from nearby stations with longer data records and environmental factors. A Markov chain Monte Carlo (MCMC) algorithm is used to estimate the posterior distribution and associated flood quantiles. The method is validated using a case study watershed with 15 streamflow gauge stations located in the San Jacinto River Basin in Texas, US. The result shows that the BLP3-SP outperforms other choices of the priors for the Bayesian Log-Pearson Type III model by significantly reducing the uncertainty in the flood frequency estimation for the station with short data length. The results have confirmed that the spatial prior knowledge can improve the Bayesian inference of the Log-Pearson Type III flood frequency model for watersheds with short gauge period.
Wastewater Treatment by Adsorption and/or Ion-Exchange Processes for Resource Recovery
Authors: Vecino Xanel , Reig Mònica
Published: March 2022

Nowadays, resource recovery is a trending topic following the circular economy schemes proposed by the European Union [...]
A field study on the profile of veterinary students in Türkiye: example of Ankara University Faculty of Veterinary Medicine
Authors: YERLİKAYA Nigar
Published: March 2022

This research was carried out to determine the general profile of the students enrolled in Turkish and English programs of Ankara University, Faculty of Veterinary Medicine (AUFVM). Determination of the demographic characteristics, socioeconomic statuses, pre-university education levels, foreign language levels of students are aimed. Additionally, reasons for choosing the veterinary profession, career expectations, views on post-graduate education, leisure time preferences, and participation in sportive and artistic activities are evaluated. A survey consisting of questions prepared for the purpose of the study was conducted with 545 students studying in the 1st, 2nd, 3rd, 4th, and 5th grades enrolled in Ankara University Faculty of Veterinary Medicine, 2019-2020 Spring Semester of Turkish and English programs. After the data analysis, it has been determined that the students are generally of urban origin and come from families with low income of the Central Anatolian Region. Accordingly, more than half of the students chose the veterinary faculty program as their first choice. They are satisfied with being a veterinary faculty student and a candidate for the profession. In addition, it has been highlighted that more than half of the students want to continue their post-graduate education, “sometimes” have the chance to participate in sportive and cultural activities, and have a low rate of reading books. As a result, it is thought that presenting a general overview of the student profile will be beneficial for both university and faculty administration and academicians in order to provide the opportunity to know the students better.
Dose-dependent effects of simvastatin, atorvastatin and rosuvastatin on apoptosis and inflammation pathways on cancerous lung cells
Authors: DİKMEN Nursel , ÖZKAN Hüseyin , ÇİMEN Funda , ÇAMDEVİREN Baran , AY Emrah , AMBARCIOĞLU Pınar , DURAN Nizami , YAKIN Akın
Published: March 2022

The aim of study was to investigate the anti-proliferative and inflammatory effects of atorvastatin, rosuvastatin, and simvastatin in lung cancer. The effects of statins were investigated in Vero, BEAS-2B, and A549 cell lines. In addition to expressions of BAX, BCL-2, TNFα, IL-10, IL-6, protein levels of TNFα, IL-10, IL-6 were determined. Cell viability and MDA were also measured. While the cell numbers in groups with low doses of statins were found to be approximately 1x106/mL, proliferation was inhibited at higher rates containing high doses. Simvastatin, rosuvastatin, and high dose atorvastatin upregulated the BAX, while high dose of atorvastatin and both doses of rosuvastatin caused downregulation in BCL-2. All statin groups had higher MDA. Simvastatin and high dose rosuvastatin upregulated TNFα. While low dose simvastatin and atorvastatin and high dose atorvastatin and rosuvastatin upregulated IL-10, IL-6 was upregulated with a low dose of rosuvastatin. TNFα was higher in simvastatin and rosuvastatin groups. IL-10 was highest in rosuvastatin groups. Atorvastatin groups had lower IL-6. Although cell numbers have been reduced by all statins, rosuvastatin is more effective on studied genes.
Newer long-acting insulin prescriptions for patients with type 2 diabetes: prevalence and practice variation in a retrospective cohort study
Authors: Dankers Marloes , Hek Karin , Nelissen-Vrancken Marjorie , Houweling Sebastiaan T , Mantel-Teeuwisse Aukje , van Dijk Liset
Published: March 2022

Background

Little is known about prescription patterns of expensive non-recommended newer long-acting insulins (glargine 300 U/mL and degludec) for patients with type 2 diabetes mellitus (T2DM).

Aim

To identify practice variation in, and practice- and patient-related characteristics associated with, the prescription of newer long-acting insulins to patients with T2DM in primary care.

Design and setting

A retrospective cohort study in Dutch general practices (Nivel Primary Care Database).

Method

A first prescription for intermediate or long-acting insulins in 2018 was identified in patients aged ≥40 years using other T2DM drugs. Per practice, the median percentage and interquartile range (IQR) of patients with newer insulin prescriptions were calculated. Multilevel logistic regression models were constructed to calculate intraclass correlation coefficients (ICCs) and quantify the association of patient and practice characteristics with prescriptions for newer insulins (odds ratios [ORs] and 95% confidence intervals [CIs]).

Results

In total, 7757 patients with prescriptions for intermediate or long-acting insulins from 282 general practices were identified. A median percentage of 21.2% (IQR 12.5–36.4%) of all patients prescribed intermediate or long-acting insulins per practice received a prescription for newer insulins. After multilevel modelling, the ICC decreased from 20% to 19%. Female sex (OR 0.77, 95% CI = 0.69 to 0.87), age ≥86 years compared with 40–55 years (OR 0.22, 95% CI = 0.15 to 0.34), prescriptions for metformin (OR 0.66, 95% CI = 0.53 to 0.82), sulfonylurea (OR 0.58, 95% CI = 0.51 to 0.66), or other newer T2DM drugs (OR 3.10, 95% CI = 2.63 to 3.66), and dispensing practices (OR 1.78, 95% CI = 1.03 to 3.10) were associated with the prescription of newer insulins.

Conclusion

The inter-practice variation in the prescription of newer insulins is large and could only be partially explained by patient- and practice-related differences. This indicates substantial opportunities for improvement.
Non-antibiotic treatment of acute urinary tract infection in primary care: a qualitative study
Authors: Gbinigie Oghenekome A , Tonkin-Crine Sarah , Butler Christoper C , Heneghan Carl J , Boylan Anne-Marie
Published: March 2022

Background

The views of women with acute, uncomplicated urinary tract infection (auUTI) on the acceptability of non-antibiotic treatment options are poorly understood.

Aim

To establish women’s thoughts on and experience of non-antibiotic treatment for auUTIs.

Design and setting

Qualitative interview study with primary care patients in Oxfordshire, UK, embedded within the Cranberry for Urinary Tract Infection (CUTI) feasibility trial.

Method

One-to-one, semi-structured interviews were conducted between August 2019 and January 2020 with some CUTI trial participants and some patients who were not part of the CUTI trial who had experienced at least one urinary tract infection (UTI) in the preceding 12 months in Oxfordshire, UK. Interviews were analysed using thematic analysis.

Results

In total, 26 interviews were conducted and analysed. Women expected to receive an immediate antibiotic for their UTI but were aware of the potential harms of this approach. They were keen to find a non-antibiotic, ‘natural’ alternative that could effectively manage their symptoms. In certain situations (early illness, milder illness, and with no important upcoming engagements), women indicated they would be prepared to postpone antibiotic treatment by up to 3 days, especially if offered an interim non-antibiotic option with perceived therapeutic potential.

Conclusion

Many women with auUTIs are open to trying non-antibiotic treatments first in certain situations. There is scope for more dialogue between primary care clinicians and patients with auUTI around delaying antibiotic treatment and using non-antibiotic options initially, which could reduce antibiotic consumption for this common infection.
Microcontroller Based Parking Lot Monitoring System Prototype
Authors:   Department of Informatics, Faculty of Information Technology and Digital, Digital Economic Institute LPKIA Bandung, Indonesia, Purwanto Heri , Prasetio Budi
Published: March 2022

Parking area is one of the facilities that must be available in specific or public places such as parks, recreation areas, malls, offices, business areas and agencies, and other places. Currently, the existing parking facilities generally do not provide information on the presence or absence of vacant parking spaces. This often causes problems in finding parking spaces, where vehicle users, especially four-wheeled vehicles (cars) will look for empty parking spaces by walking around so they can spend a lot of time. This study aims to create a parking lot monitoring system that is equipped with a microcontroller-based monitoring system so that vehicle users can find out how many parking spaces are available and where the parking lot is located. This parking monitoring system was developed using the prototyping method so that determining the need for the actual system is easier to realize. The test results of this device show that this prototype can provide information regarding the number of vacant parking lots and their locations. The impact of this research is that it can eliminate the accumulation of vehicles in front of the parking lot entrance, because vehicle users can easily and quickly find a parking location.