bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Chip Formation Mechanisms in the Turning of Sintered ZnO Electro-Ceramics
Authors: Dugar Jaka , Ikram Awais , Pušavec Franci
Published: August 2021

The sintered zinc oxide (ZnO) electro-ceramics are a brittle class of hard-to-cut materials such that shaping them with the post-finishing operations necessitates careful handling and precision machining. The conventional machining approach using the grinding and lapping processes represents limited productivity, an inability to produce the required geometries and frequent uncontrolled chipping of the edges of the final products. This study thus investigates the turning performance of dense sintered ZnO varistors and chip formations to obtain the parametric range (cutting mechanism) which causes the chipping or the trans-granular/sudden failure in these brittle materials. With the analysis of the cutting tool vibration in relation to the machining parameters (f and VC), the vibration-induced chipping correlations are made and interlinked with the occurrence of grain pull-out during the turning operation. The results show that the reflected vibratory motion of the tools is directly correlated with the chip formation mechanisms in the turning of ZnO ceramics and thus provide robust measurements for quality assurance in final products.
Homophily and Social Capital in a Network of Religious Congregations
Authors: McClure Jennifer M.
Published: August 2021

This article investigates the relationship between homophily, the tendency for relationships to be more common among similar actors, and social capital in a social network of religious congregations from eight counties encompassing and surrounding a major metropolitan area in the southeastern United States. This network is inter-congregational, consisting of congregations and the relationships between them. Two types of social capital are investigated: the first involves the extent to which congregations bridge across structural holes, or bridge together otherwise disconnected congregations within the network; secondly, network closure involves the extent to which congregations are embedded in tight-knit clusters. Analyses use two types of homophily (religious and racial) to predict both outcomes, and they test linear and curvilinear relationships between both forms of homophily and the outcomes. Results indicate that congregations with moderate levels of religious homophily are more likely to bridge between otherwise disconnected congregations; however, congregations with low or high religious homophily as well as congregations with high racial homophily are more likely to be embedded in tight-knit relational clusters. This article contributes additional social network research on congregations and evidence of curvilinear relationships between homophily and social capital to the fields of social network analysis and sociology of religion.
Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors
Authors: Schackart Kenneth E. , Yoon Jeong-Yeol
Published: August 2021

Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor’s signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.
Effects of Sensor Types and Angular Velocity Computational Methods in Field Measurements of Occupational Upper Arm and Trunk Postures and Movements
Authors: Fan Xuelong , Lind Carl Mikael , Rhen Ida-Märta , Forsman Mikael
Published: August 2021

Accelerometer-based inclinometers have dominated kinematic measurements in previous field studies, while the use of inertial measurement units that additionally include gyroscopes is rapidly increasing. Recent laboratory studies suggest that these two sensor types and the two commonly used angular velocity computational methods may produce substantially different results. The aim of this study was, therefore, to evaluate the effects of sensor types and angular velocity computational methods on the measures of work postures and movements in a real occupational setting. Half-workday recordings of arm and trunk postures, and movements from 38 warehouse workers were compared using two sensor types: accelerometers versus accelerometers with gyroscopes—and using two angular velocity computational methods, i.e., inclination velocity versus generalized velocity. The results showed an overall small difference (<2° and value independent) for posture percentiles between the two sensor types, but substantial differences in movement percentiles both between the sensor types and between the angular computational methods. For example, the group mean of the 50th percentiles were for accelerometers: 71°/s (generalized velocity) and 33°/s (inclination velocity)—and for accelerometers with gyroscopes: 31°/s (generalized velocity) and 16°/s (inclination velocity). The significant effects of sensor types and angular computational methods on angular velocity measures in field work are important in inter-study comparisons and in comparisons to recommended threshold limit values.
The Ultraviolet Index Is Well Estimated by the Terrestrial Irradiance at 310 nm
Authors: Kaplan Peter D. , Dumont Emmanuel L. P.
Published: August 2021

Ultraviolet (UV) exposure significantly contributes to non-melanoma skin cancer. In the context of health, UV exposure is the product of time and the UV Index (UVI), a weighted sum of the irradiance I(λ) over all wavelengths from λ = 250 to 400 nm. In our analysis of the United States Environmental Protection Agency’s UV-Net database of over 400,000 spectral irradiance measurements taken over several years, we found that the UVI is well estimated by 77 I310. To further understand this result, we applied an optical atmospheric model to generate terrestrial irradiance spectra and found that it applies across a wide range of conditions. An accurate UVI radiometer can be built from a photodiode covered by a bandpass filter centered at 310 nm.
A WoT-Based Method for Creating Digital Sentinel Twins of IoT Devices
Authors: Lopez-Arevalo Ivan , Gonzalez-Compean Jose Luis , Hinojosa-Tijerina Mariana , Martinez-Rendon Cristhian , Montella Raffaele , Martinez-Rodriguez Jose L.
Published: August 2021

The data produced by sensors of IoT devices are becoming keystones for organizations to conduct critical decision-making processes. However, delivering information to these processes in real-time represents two challenges for the organizations: the first one is achieving a constant dataflow from IoT to the cloud and the second one is enabling decision-making processes to retrieve data from dataflows in real-time. This paper presents a cloud-based Web of Things method for creating digital twins of IoT devices (named sentinels).The novelty of the proposed approach is that sentinels create an abstract window for decision-making processes to: (a) find data (e.g., properties, events, and data from sensors of IoT devices) or (b) invoke functions (e.g., actions and tasks) from physical devices (PD), as well as from virtual devices (VD). In this approach, the applications and services of decision-making processes deal with sentinels instead of managing complex details associated with the PDs, VDs, and cloud computing infrastructures. A prototype based on the proposed method was implemented to conduct a case study based on a blockchain system for verifying contract violation in sensors used in product transportation logistics. The evaluation showed the effectiveness of sentinels enabling organizations to attain data from IoT sensors and the dataflows used by decision-making processes to convert these data into useful information.
Robust Multi-Frame Super-Resolution Based on Adaptive Half-Quadratic Function and Local Structure Tensor Weighted BTV
Authors: Liu Shanshan , Wang Minghui , Huang Qingbin , Liu Xia
Published: August 2021

It is difficult to improve image resolution in hardware due to the limitations of technology and too high costs, but most application fields need high resolution images, so super-resolution technology has been produced. This paper mainly uses information redundancy to realize multi-frame super-resolution. In recent years, many researchers have proposed a variety of multi-frame super-resolution methods, but it is very difficult to preserve the image edge and texture details and remove the influence of noise effectively in practical applications. In this paper, a minimum variance method is proposed to select the low resolution images with appropriate quality quickly for super-resolution. The half-quadratic function is used as the loss function to minimize the observation error between the estimated high resolution image and low-resolution images. The function parameter is determined adaptively according to observation errors of each low-resolution image. The combination of a local structure tensor and Bilateral Total Variation (BTV) as image prior knowledge preserves the details of the image and suppresses the noise simultaneously. The experimental results on synthetic data and real data show that our proposed method can better preserve the details of the image than the existing methods.
Low Spatial Peak-to-Average Power Ratio Transmission for Improved Energy Efficiency in Massive MIMO Systems
Authors: Rezaei Aghdam Sina , Eriksson Thomas
Published: August 2021

A significant portion of the operating power of a base station is consumed by power amplifiers (PAs). Much of this power is dissipated in the form of heat, as the overall efficiency of currently deployed PAs is typically very low. This is because the structure of conventional precoding techniques typically results in a relatively high variation in output power at different antennas in the array, and many PAs are operated well below saturation to avoid distortion of the transmitted signals. In this work, we use a realistic model for power consumption in PAs and study the impact of power variation across antennas in the array on the energy efficiency of a massive MIMO downlink system. We introduce a family of linear precoding matrices that allow us to control the spatial peak-to-average power ratio by projecting a fraction of the transmitted power onto the null space of the channel. These precoding matrices preserve the structure of conventional precoders; e.g., they suppress multiuser interference when used together with zeroforcing precoding and bring advantages over these precoders by operating PAs in a more power-efficient region and reducing the total radiated distortion. Our numerical results show that by controlling the power variations between antennas in the array and incorporating the nonlinearity properties of PA into the precoder optimization, significant gains in energy efficiency can be achieved over conventional precoding techniques.
Differential Inductive Sensing System for Truly Contactless Measuring of Liquids′ Electromagnetic Properties in Tubing
Authors: Berger Marc , Zygmanowski Anne , Zimmermann Stefan
Published: August 2021

Certain applications require a contactless measurement to eliminate the risk of sensor-induced sample contamination. Examples can be found in chemical process control, biotechnology or medical technology. For instance, in critically ill patients requiring renal replacement therapy, continuous in-line monitoring of blood conductivity as a measure for sodium should be considered. A differential inductive sensing system based on a differential transformer using a specific flow chamber has already proven suitable for this application. However, since the blood in renal replacement therapy is carried in plastic tubing, a direct measurement through the tubing offers a contactless method. Therefore, in this work we present a differential transformer for measuring directly through electrically non-conductive tubing by winding the tube around the ferrite core of the transformer. Here, the dependence of the winding type and the number of turns of the tubing on the sensitivity has been analyzed by using a mathematical model, simulations and experimental validation. A maximum sensitivity of 364.9 mV/mol/L is measured for radial winding around the core. A longitudinal winding turns out to be less effective with 92.8 mV/mol/L. However, the findings prove the ability to use the differential transformer as a truly contactless sensing system.
Copper (II) Ion-Modified Gold Nanoclusters as Peroxidase Mimetics for the Colorimetric Detection of Pyrophosphate
Authors: Shi Yunjing , Wang Jinjie , Mu Kun , Liu Suqin , Yang Guang , Zhang Min , Yang Jingxia
Published: August 2021

Copper (II) ions have been shown to greatly improve the chemical stability and peroxidase-like activity of gold nanoclusters (AuNCs). Since the affinity between Cu2+ and pyrophosphate (PPi) is higher than that between Cu2+ and AuNCs, the catalytic activity of AuNCs-Cu2+ decreases with the introduction of PPi. Based on this principle, a new colorimetric detection method of PPi with high sensitivity and selectivity was developed by using AuNCs-Cu2+ as a probe. Under optimized conditions, the detection limit of PPi was 0.49 nM with a linear range of 0.51 to 30,000 nM. The sensitivity of the method was three orders of magnitude higher than that of a fluorescence method using AuNCs-Cu2+ as the probe. Finally, the AuNCs-Cu2+ system was successfully applied to directly determine the concentration of PPi in human urine samples.
Hamiltonian Monte Carlo with Random Effect for Analyzing Cyclist Crash Severity
Authors: Rezapour Mahdi , Ksaibati Khaled
Published: August 2021

Vulnerable traffic users, such as bikers and pedestrians, account for a significant number of fatalities on the roadways. Extensive research has been conducted in the literature review to identify factors to those crashes. Studying factors to those crashes is especially important in the Western state in the US, due to one of the highest fatality rates in the nation and its unique geographic conditions. The first step in identifying factors to the severity of cyclist crashes is to find the underlying factors to that type of crash, while accounting for the heterogeneity in the dataset. Various techniques such as mixed parameter or mixed effect models have been employed in the literature to account for the heterogeneity of the dataset. In the mixed effect model, often the random effect parameter has been assigned subjectively, and based on some attributes and engineering intuitions. Those assignments are expected to account for the heterogeneity in the dataset and enhancement of the model fit. However, a question might arise whether those factors could account for an optimum amount of the heterogeneity in the dataset. A more reasonable way might be to let the algorithm such as the finite mixture model (FMM) to identify those clusters based on parameters of the Gaussian model, means and covariance matrices of the dataset, and allocate each observation to the related clusters. Thus, in this study, to capture optimum amount of heterogeneity, first we implemented the finite mixture model in the context of maximum likelihood, due the label switching issue of the method in the context of the Bayesian method. After assignment of the parameters to the observation, the main method of Hamiltonian Monte Carlo (HMC) with random effect was implemented. The results highlighted a significant improvement in the model fit, in terms of Widely Applicable Information Criterion (WAIC). The results of this study highlighted factors such as older biker age, increased number of lanes, nighttime travelling, increased posted speed limit and driving while under emotional conditions are some factors contributing to an increased severity of bikers’ crash severity. Extensive discussion has been made regarding the methodological algorithms and model parameters estimations.
Substitution of Building Components in Historic Buildings
Authors: Sobotka Anna , Linczowski Kazimierz , Radziejowska Aleksandra
Published: August 2021

Historic buildings that have survived to the present day have been subject to maintenance, repair, and overhaul. Repair work is being carried out so that it can be enjoyed by future generations. However, there have been changes in the construction technology: some construction products have been discontinued and replaced with others of different quality parameters, lower prices, etc. It is necessary to use substitute products during construction work—that is, replacement products that are shaped after the original. Therefore, there is a problem of selecting the best possible substitute material, taking into account many important factors, including the recommendations and requirements of the conservator. This paper presents a methodology for the process of material substitution planning and selection of a substitute with the use of multicriteria analysis, by implementing it in the refurbishment of a historic building façade.
A Novel Taxonomy for Risks in Agribusiness Supply Chains: A Systematic Literature Review
Authors: Imbiri Soleman , Rameezdeen Raufdeen , Chileshe Nicholas , Statsenko Larissa
Published: August 2021

Agribusiness supply chain (ASC) risk is currently a major business problem throughout the world. The current trend of globalisation has affected every business, and supply chain risks have become a concern in logistics and other business processes. Current risk management strategies must address a variety of global and local challenges. To tackle this issue, existing research has analysed risks in agrifood supply chains, ASC risk management, disruption in ASCs, risk assessments of agriculture supply chains and sources of risk facing an agricultural supply chain. However, the existing research has not defined and categorised risks as a basis for managing risks in ASCs. Therefore, the definition and categorisation of risks in the ASC has been overlooked. To address this gap, this paper undertakes a systematic literature review, offering constructs to define and categorise risks in ASCs, and develops a novel taxonomy in ASC risks to enrich future research on ASC risk management. Sixty-one articles from six databases published between 2000 and 2020 underwent descriptive and thematic analysis.
Identifying and Selecting Key Sustainable Parameters for the Monitoring of e-Powered Micro Personal Mobility Vehicles. Evidence from Italy
Authors: Carrara Elena , Ciavarella Rebecca , Boglietti Stefania , Carra Martina , Maternini Giulio , Barabino Benedetto
Published: August 2021

The recent invasion of electric-powered personal mobility vehicles (e-PMVs) in many cities worldwide has disputed the transport sector and captured the attention of academics, practitioners, and public administrators. Indeed, these vehicles are believed to be sustainable transport alternatives. Therefore, understanding how to evaluate and monitor the related performance is crucial and may be addressed by suitable key sustainable parameters (KSPs) to inform on the excellences and criticalities of e-PMVs. Previous research has focused largely on “how to measure and manage” KSPs rather than “what to measure”. Conversely, as far as the authors know, no study investigated objective methods for identifying and selecting top KSPs. This paper covers this gap by proposing a cohesive approach, which identifies a long list of KSPs, defines their properties, involves experts to elicit judgments for each KSP, evaluates the long list, and returns the most promising set. This approach is demonstrated with an application based on an Italian survey. A circumscribed and relevant set of six overlapping KSPs is derived by merging two different approaches. These results may support the opportunity to assess the performance of e-PMVs among cities according to a common set of KSPs.
What Causes the Virtual Agglomeration of Creative Industries?
Authors: Chen Xu , Liu Chunhong , Jiang Yao , Gao Changchun
Published: August 2021

The agglomeration paradigm for creative industries has fundamentally changed under the digital economy, giving rise to a new form of virtual agglomeration within these industries. This study explores the causes of this virtual agglomeration. We collected online Chinese news texts related to the virtual agglomeration of the creative industry, used text mining to identify nine factors affecting its formation, and refined the internal and external factors for an analytical framework based on the PEST (political, economic, social, technological) and value-chain models. We then combined the relevant literature and the creative industry’s development practices, analyzed the mechanism of each driving factor, and constructed a driving-force model for the creative industry’s virtual agglomeration. The external driving factors were government policy planning, the digital economic environment, emerging consumer demand, and the application of innovative technology; the internal factors were the digitalization of cultural resources, flexible manufacturing, digital marketing and promotion, online interactive services, and virtual platform facilities. Each factor was found to contribute to virtual agglomeration through different internal mechanisms. This study’s findings have theoretical and practical value for cultivating the modes of virtual agglomeration within creative industries.
Effect of the Milking Frequency on the Concentrations of Ammonia and Greenhouse Gases within an Open Dairy Barn in Hot Climate Conditions
Authors: D’Urso Provvidenza Rita , Arcidiacono Claudia
Published: August 2021

Knowledge of how different management strategies affect gas production from livestock buildings can be helpful for emission predicting purposes and for defining mitigation strategies. The objective of this study was to statistically assess whether and how measured concentrations of ammonia (NH3), methane (CH4) and carbon dioxide (CO2) were influenced by milking frequency. Concentrations of gases were measured continuously by using infrared photoacoustic spectroscopy in the breeding environment of an open dairy barn located in Sicily in hot climate conditions. Data were acquired by specific in-field experiments carried out in 2016 and 2018, when milking sessions occurred twice a day (2MSs) and three times a day (3MSs), respectively. The number of the milking cows was 64 in both 2MSs and 3MSs. The results showed that concentrations of NH3, CH4 and CO2 were statistically influenced by the number of milking sessions. From 2MSs to 3MSs, NH3 concentrations were enhanced (p < 0.001) due to the higher cow’s activity. Conversely, gas concentrations of CH4 and CO2 were lower for 3MSs compared to those for 2MSs due to the effect of the different feeding frequency. Overall, the milking frequency influenced barn management and cow behaviour by modifying the level of gas concentrations in the barn environment.
A Secure, Lightweight, and Anonymous User Authentication Protocol for IoT Environments
Authors: Son Seunghwan , Park Yohan , Park Youngho
Published: August 2021

The Internet of Things (IoT) is being applied to various environments such as telecare systems, smart homes, and intelligent transportation systems. The information generated from IoT devices is stored at remote servers, and external users authenticate to the server for requesting access to the stored data. In IoT environments, the authentication process is required to be conducted efficiently, and should be secure against various attacks and ensure user anonymity and untraceability to ensure sustainability of the network. However, many existing protocols proposed in IoT environments do not meet these requirements. Recently, Rajaram et al. proposed a paring-based user authentication scheme. We found that the Rajaram et al. scheme is vulnerable to various attacks such as offline password guessing, impersonation, privileged insider, and known session-specific temporary information attacks. Additionally, as their scheme uses bilinear pairing, it requires high computation and communication costs. In this study, we propose a novel authentication scheme that resolves these security problems. The proposed scheme uses only hash and exclusive-or operations to be applicable in IoT environments. We analyze the proposed protocol using informal analysis and formal analysis methods such as the BAN logic, real-or-random (ROR) model, and the AVISPA simulation, and we show that the proposed protocol has better security and performance compared with existing authentication protocols. Consequently, the proposed protocol is sustainable and suitable for real IoT environments.
Method for Diagnosing the Uneven Settlement of a Rail Transit Tunnel Based on the Spatial Correlation of High-Density Strain Measurement Points
Authors: Li Hu , Xu Qianen , Liu Yang
Published: August 2021

Rail transit tunnels span long distances, are large-scale structures and pass through complicated geological conditions; thus, the risk of uneven settlement cannot be ignored. To address this issue, a method for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed in this study. First, with the distributed optical fiber sensing technology, a method for determining the intervals of strain measurement points with strong spatial correlations is proposed based on a support vector machine. Second, combined with the statistical analysis of the influence range of the uneven settlement of a tunnel, an algorithm for diagnosing the uneven settlement of regional railway tunnels based on the spatial correlation of high-density strain measurement points is proposed. Finally, the effectiveness of the proposed method is verified by numerical simulation and actual tunnel data.
Group Structure and Geometric Interpretation of the Embedded Scator Space
Authors: Cieśliński Jan L. , Kobus Artur
Published: August 2021

The set of scators was introduced by Fernández-Guasti and Zaldívar in the context of special relativity and the deformed Lorentz metric. In this paper, the scator space of dimension 1+n (for n=2 and n=3) is interpreted as an intersection of some quadrics in the pseudo-Euclidean space of dimension 2n with zero signature. The scator product, nondistributive and rather counterintuitive in its original formulation, is represented as a natural commutative product in this extended space. What is more, the set of invertible embedded scators is a commutative group. This group is isomorphic to the group of all symmetries of the embedded scator space, i.e., isometries (in the space of dimension 2n) preserving the scator quadrics.
Thermodynamic Assessment of the AF–CrF3 (A = Li, Na, K) and CrF2–CrF3 Systems
Authors: Dumaire Thomas , Konings Rudy J. M. , Smith Anna Louise
Published: August 2021

Understanding the corrosion mechanisms and the effect of corrosion products on the basic properties of the salt (e.g., melting point, heat capacity) is fundamental for the safety assessment and durability of molten salt reactor technology. This work focused on the thermodynamic assessment of the CrF2−CrF3 system and the binary systems of chromium trifluoride CrF3 with alkali fluorides (LiF, NaF, KF) using the CALPHAD (computer coupling of phase diagrams and thermochemistry) method. In this work, the modified quasi-chemical model in the quadruplet approximation was used to develop new thermodynamic modelling assessments of the binary solutions, which are highly relevant in assessing the corrosion process in molten salt reactors. The agreement between these assessments and the phase equilibrium data available in the literature is generally good. The excess properties (mixing enthalpies, entropies and Gibbs energies) calculated in this work are consistent with the expected behaviour of decreasing enthalpy and Gibbs energy of mixing with the increasing ionic radius of the alkali cations.
Characterization and Application of a Lytic Phage D10 against Multidrug-Resistant Salmonella
Authors: Li Zhiwei , Li Wanning , Ma Wenjuan , Ding Yifeng , Zhang Yu , Yang Qile , Wang Jia , Wang Xiaohong
Published: August 2021

Salmonella is a widely distributed foodborne pathogen that is a serious threat to human health. The accelerated development of drug resistance and the increased demand for natural foods invoke new biocontrol agents to limit contamination by multidrug-resistant (MDR) Salmonella strains. In this study, a lytic Salmonella phage named D10 was characterized at the biological and genomic levels. D10 possesses a short latent period (10 min) and a large burst size (163 PFU/cell), as well as adequate stability under a range of pH conditions and moderate thermal tolerance. D10 effectively lysed different MDR Salmonella serovars and repressed their dynamic growth in the medium. Genomic analysis disclosed that D10 is a new member of the Siphoviridae family and lacks the genes implicated in lysogeny, pathogenicity, or antibiotic resistance. A three-ingredient phage cocktail was then developed by mixing D10 with previously identified myovirus D1-2 and podovirus Pu20. The cocktail significantly reduced the count of MDR strains in liquid eggs, regardless of the temperature applied (4 and 25 °C). These results suggest that phage D10 is a promising tool to prevent food contamination by MDR Salmonella.
On the Use of Phylogeographic Inference to Infer the Dispersal History of Rabies Virus: A Review Study
Authors: Nahata Kanika D. , Bollen Nena , Gill Mandev S. , Layan Maylis , Bourhy Hervé , Dellicour Simon , Baele Guy
Published: August 2021

Rabies is a neglected zoonotic disease which is caused by negative strand RNA-viruses belonging to the genus Lyssavirus. Within this genus, rabies viruses circulate in a diverse set of mammalian reservoir hosts, is present worldwide, and is almost always fatal in non-vaccinated humans. Approximately 59,000 people are still estimated to die from rabies each year, leading to a global initiative to work towards the goal of zero human deaths from dog-mediated rabies by 2030, requiring scientific efforts from different research fields. The past decade has seen a much increased use of phylogeographic and phylodynamic analyses to study the evolution and spread of rabies virus. We here review published studies in these research areas, making a distinction between the geographic resolution associated with the available sequence data. We pay special attention to environmental factors that these studies found to be relevant to the spread of rabies virus. Importantly, we highlight a knowledge gap in terms of applying these methods when all required data were available but not fully exploited. We conclude with an overview of recent methodological developments that have yet to be applied in phylogeographic and phylodynamic analyses of rabies virus.
A Modeling Study on Vaccination and Spread of SARS-CoV-2 Variants in Italy
Authors: Antonini Chiara , Calandrini Sara , Bianconi Fortunato
Published: August 2021

From the end of 2020, different vaccines against COVID-19 have been approved, offering a glimmer of hope and relief worldwide. However, in late 2020, new cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started to re-surge, worsened by the emergence of highly infectious variants. To study this scenario, we extend the Susceptible-Exposed-Infectious-Removed model with lockdown measures used in our previous work with the inclusion of new lineages and mass vaccination campaign. We estimate model parameters using the Bayesian method Conditional Robust Calibration in two case studies: Italy and the Umbria region, the Italian region being worse affected by the emergence of variants. We then use the model to explore the dynamics of COVID-19, given different vaccination paces and a policy of gradual reopening. Our findings confirm the higher reproduction number of Umbria and the increase of transmission parameters due to the presence of new variants. The results illustrate the importance of preserving population-wide interventions, especially during the beginning of vaccination. Finally, under the hypothesis of waning immunity, the predictions show that a seasonal vaccination with a constant rate would probably be necessary to control the epidemic.
Spatiotemporal Analysis of Meteorological and Hydrological Droughts and Their Propagations
Authors: Abbas Adnan , Waseem Muhammad , Ullah Waheed , Zhao Chengyi , Zhu Jianting
Published: August 2021

The quantitative description of relationships and propagation between different forms of drought at multiple spatiotemporal scales in various geographical locations is informative for early drought warning systems. This study intends to evaluate the historical hydrometeorological drought from 1984–2015 in the Soan River Basin, which is a critical water source for the Pothwar region of Pakistan. The reconnaissance drought index (RDI) and standardized runoff index (SRI) are used to characterize meteorological and hydrological droughts, respectively. The spatiotemporal variations of the RDI and SRI demonstrated that 2000 and 2010 were extremely dry and wet years, respectively. The results further reveal that the frequency of hydrometeorological drought events was higher in a shorter time scale (3 and 6 months), while durations featured longer timescales (9 and 12 months). The RDI and SRI time series showed a significant decreasing trend in terms of the Mann–Kendal and Sen slope estimator (SSE) results. Cross-correlation analysis for RDI and SRI with a time lag acknowledged the existence of a sequence between the RDI and SRI and a positive relationship between the two indices. The findings of this study could be helpful for better understanding drought variability and water resource management.
Reclaimed Water for Vineyard Irrigation in a Mediterranean Context: Life Cycle Environmental Impacts, Life Cycle Costs, and Eco-Efficiency
Authors: Canaj Kledja , Morrone Domenico , Roma Rocco , Boari Francesca , Cantore Vito , Todorovic Mladen
Published: August 2021

The agricultural sector in the Mediterranean region, is increasingly using reclaimed water as an additional source for irrigation. However, there is a limited number of case studies about product-based life cycle analysis to ensure that the overall benefits of reclaimed water do indeed outweigh the impacts. The Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) methods are used in this study to investigate the environmental impacts and costs of vineyard cropping systems when tertiary reclaimed water is used as a supplementary source of irrigation water (integrated system). The conventional production system utilizing 100% groundwater was used as a reference system. As a proxy for sustainability, eco-efficiency, which combines economic and environmental performance, was assessed. The LCA revealed that the integrated system could reduce the net environmental impact by 23.8% due to lower consumption of irrigation water (−50%), electricity (−27.7%), and chemical fertilizers (−22.6%). Nevertheless, trade-offs between economics and the environment occurred as an integrated system is associated with higher life cycle costs and lower economic returns due to lower crop yield (−9.1%). The combined eco-efficiency assessment (ratio of economic value added to total environmental impact) revealed that the integrated system outperformed in terms of eco-efficiency by 12.6% due to lower environmental impacts. These results confirmed that reclaimed water could help to ensure an economically profitable yield with net environmental benefits. Our results provided an up-to-date and consistent life cycle analysis contributing to the creation of a valuable knowledge base for the associated costs and benefits of vineyard cultivation with treated wastewater.
Online Parameters Identification and State of Charge Estimation for Lithium-Ion Battery Using Adaptive Cubature Kalman Filter
Authors: Li Wei , Luo Maji , Tan Yaqian , Cui Xiangyu
Published: August 2021

The state of charge (SOC) of a lithium-ion battery plays a key role in ensuring the charge and discharge energy control strategy, and SOC estimation is the core part of the battery management system for safe and efficient driving of electric vehicles. In this paper, a model-based SOC estimation strategy based on the Adaptive Cubature Kalman filter (ACKF) is studied for lithium-ion batteries. In the present study, the dual polarization (DP) model is employed for SOC estimation and the vector forgetting factor recursive least squares (VRLS) method is utilized for model parameter online identification. The ACKF is then designed to estimate the battery’s SOC. Finally, the Urban Dynamometer Driving Schedule and Dynamic Stress Test are utilized to evaluate the performance of the proposed method by comparing with results obtained using the extended Kalman filter (EKF) and the cubature Kalman filter (CKF) algorithms. The simulation and experimental results show that the proposed ACKF algorithm combined with VRLS-based model identification is a promising SOC estimation approach. The proposed algorithm is found to provide more accurate SOC estimation with satisfying stability than the extended EKF and CKF algorithms.
Constructing Supports–Network with N–TiO2 Nanofibres for Highly Efficient Hydrogen–Production of PEM Electrolyzer
Authors: Wang Sen , Lv Hong , Sun Yongwen , Ji Wenxuan , Shen Xiaojun , Zhang Cunman
Published: August 2021

Hydrogen production with a proton exchange membrane (PEM)electrolyzer utilized with renewable energy power is considered to be an efficient and clean green technique, but the poor oxygen evolution performance results in high energy consumption and low efficiency. In this work, a strategy is reported for the construction of a support network of the anodic catalyst layer to simultaneously ameliorate its sluggish reaction kinetics and mass transport in order to realize highly efficient hydrogen production of the PEM electrolyzer. After in situ synthesis of IrO2 nanoparticles on N–doped TiO2 nanofibers, the as–prepared IrO2/N–TiO2 electrode shows substantially enhanced Ir utilization and accelerated mass transport, consequently decreasing the corresponding cell potential of 107 mV relative to pure IrO2 at 2 A cm−2. The enhanced activity of IrO2/N–TiO2 could be due to the fact that the N–TiO2 nanofiber support can form a porous network, endowing IrO2/N–TiO2 with a large reactive contact interface and favorable mass transfer characters. The strategy in this work supplies a pathway to develop high–efficiency interfacial reaction materials for diverse applications.
Creation, promotion and classification of private labels
Authors: Nikolaeva M.A. , Bas D.D.
Published: August 2021

The purpose of this article is to consider the advantages of private labels, the process of their creation and promotion, as well as the classification of private labels. The article discusses the benefits of private labels for their owners and consumers. The classification of private labels is presented and the definition of their types and varieties is given. The process of creating and promoting private labels, as well as the features of their creation in retail trade networks, is considered. It has been established that successful private labels are beneficial for all participants in the distribution channel: manufacturers who receive large orders for the production of goods and their guaranteed sale; retailers whose private labels provide competitive advantages, customer loyalty and high profits. Meanwhile, end consumers have the opportunity to buy goods of proper quality at reduced prices, as well as the confidence that they will not be deceived.
The main directions of the state policy in the field of ensuring food security in Russia
Authors: Nikolaeva M.A. , Chizhikova A.R.
Published: August 2021

The purpose of this article is a comparative analysis of the most important provisions regulated in the Doctrines of 2010 and 2020, as well as the identification of the main directions of state policy necessary to solve the issue of ensuring food security. The article presents the results of the comparative analysis of the main provisions, tasks and directions in the field of ensuring food security established in the Doctrines of 2010 and 2020. The existence of continuity of the Doctrine 2020 on long-term planning issues is revealed, new tasks and directions in the field of ensuring food security for the period up to 2030 are established. The results of the implementation of the provisions of the Doctrine 2020 have been summed up.
Conversion rate and risk factors of conversion to open in laparoscopic appendicectomy
Authors: Pushpanathan Nelson Rao , Hashim Mohd Nizam Md , Zahari Zalina , Aziz Syed Hassan Syed Abd. , Zain Wan Zainira Wan , Ramely Rosnelifaizur , Wong Michael Pak-Kai , Mohamad Ikhwan Sani , Mokhter Wan Mokhzani Wan , Yahya Maya Mazuwin , Merican Siti Rahmah Hashim Isa , Zakaria Zaidi , Zakaria Andee Dzulkarnaen
Published: August 2021

Purpose: Laparoscopic appendicectomy (LA) has several advantages over conventional open appendicectomy (OA). However, about 5% to 10% of LA patients still need to be converted to open surgery. Identifying risk factors that contribute to conversion to OA allows for early identification of patients who may benefit from primary OA. This study aimed to determine the conversion rate of LA to OA and to identify its associated risk factors among patients with acute or perforated appendicitis.Methods: A retrospective review of medical records was performed among patients with acute or perforated appendicitis who underwent LA between December 2015 and January 2017. With the use of multivariable logistic regression analyses, the predictors of conversion from laparoscopic to OA were investigated.Results: Out of 120 patients, 33 cases were converted to OA which gives a conversion rate of 27.5%. Among 33 patients who were converted to OA, 27 patients (81.8%) had perforated appendix, while in the LA group, perforated appendix cases consisted of 34.5% (P<0.001). Histopathology of the appendix was the predictor of conversion from LA to OA (adjusted odds ratio, 8.82; 95% confidence interval, 3.13–24.91; P<0.001).Conclusion: The result from our study shows that the overall conversion rate for the study period was high. Patients with perforated appendicitis had a higher risk of conversion to OA. Therefore, preoperative diagnosis of perforated appendicitis may be paramount in predicting conversion to OA.
Radiofrequency ablation (Rafaelo Procedure) for the treatment of hemorrhoids: a case series in the United Kingdom
Authors: Hassan Sarah , McGrath Daniel , Barnes Richard , Middleton Simon
Published: August 2021

Purpose: Hemorrhoidal disease remains a common condition that can have a significant effect on a patient’s quality of life. Various methods have been introduced over the years; however, their overall success rates remain low. Although the traditional Milligan Morgan technique is effective, the associated pain level prevents it from being an attractive form of treatment. This study was devised to assess the safety and efficacy associated with a novel minimally invasive approach, radiofrequency ablation (RFA).Methods: Forty-two patients underwent RFA at a single center, by 1 of 2 surgeons. This was performed under local anesthetic and sedation. Outcomes including postoperative pain levels, recurrence rates, and patient satisfaction scores were recorded and analyzed using medians and interquartile rangesResults: The median postoperative pain score was 2.5/10 (interquartile range [IQR], 0–4.5) and the overall patient satisfaction score was 9 out of 10 (IQR, 6.5–10). Recurrence rates (6–12 months following the procedure) were low at 12% and all patients reported milder symptoms at recurrence. There were no serious adverse complicationsConclusion: The results from this case series supports other limited data in concluding that RFA is a safe and effective method in the treatment of hemorrhoids and patients report a high level of satisfaction following
Long-term nitrofurantoin: an analysis of complication awareness, monitoring, and pulmonary injury cases
Authors: Speirs Toby Peter , Tuffin Nicole , Mundy-Baird Finlay , Sakota Helena , Mulholland Sarah , Westlake Michelle , Lyon Max , Medford Andrew R , Sharp Charles , Darby Michael , Albur Mahableshwar , Keeley Francis , Burden Helena , Kenward Charlie , Jonas Elizabeth , Barratt Shaney , Adamali Huzaifa I
Published: August 2021

Background

Long-term nitrofurantoin (NF) treatment can result in pulmonary and hepatic injury. Current guidelines do not outline the type or frequency of monitoring required for detection of these injuries.

Aim

To assess 1) awareness of NF complications among prescribers; 2) monitoring practice; and 3) to describe the pulmonary sequelae of NF-related complications.

Design & setting

Evaluation of prescribing habits by questionnaires and review of GP databases, and case-note review in secondary care.

Method

The following study procedures were undertaken: 1) an electronic questionnaire was distributed to prescribers, interrogating prescribing and monitoring practices, and awareness of complications; 2) an analysis was undertaken (June–July 2020) of NF monitoring among GPs in the local clinical commissioning group (CCG); and 3) a case review was carried out of patients diagnosed with NF-induced interstitial lung disease (NFILD) at the interstitial lung disease (ILD) centre (2014–2020).

Results

A total of 125 prescribers of long-term NF responded to the questionnaire (82.4% GPs; 12.0% urologists). Many were unaware of the potential for liver (42.4%) and lung (28.0%) complications; 40.8% and 52.8% never monitored for these, respectively. Only 53.3% of urologists believed themselves responsible for arranging monitoring, while nearly all GPs believed this to be the prescriber’s responsibility (94.2%). One-third of all responders considered current British National Formulary (BNF) guidelines 'not at all sufficient/clear', with mean clarity scoring of 2.2/5. Among patients with NFILD (n = 46), NF had been prescribed most often (69.6%) for treatment of recurrent UTI and 58.6% (n = 27) were prescribed for >6 months. On withdrawal of the medication 61.4% displayed resolution (completely or minimal fibrosis), while 15.9% of patients had progressive lung fibrosis.

Conclusion

NF can cause marked or irreversible lung complications and there is currently a shortfall in awareness and monitoring. Existing monitoring guidelines should be augmented.