bluuebunny/crossref_metadata_2025 huggingface dataset:
New Frontiers and Old Challenges: How to Manage Incidental Findings When Forensic Diagnosis Goes Beyond
Authors: Caenazzo Luciana , Tozzo Pamela , Dierickx Kris
Published: September 2020

Incidental findings (IFs) are well known in medical research and clinical practice as unexpected findings having potential health or reproductive importance for an individual. IFs are discovered under different contexts but do not fall within the aim of a study, and/or are unanticipated or unintentionally revealed, and/or are not the specific focus or target of the particular research or clinical query. Today, in forensic settings, we can consider as incidental findings all the information that is neither related to the cause of death nor to the dynamic of the event or the scope of the forensic investigation. The question whether and how professionals should consider traditional values as guiding notions in the reporting of IFs in the context of forensic assessments is the focus of this article. We propose a descriptive analysis, which focuses on the forensic field, describing forensic situations in which IFs may occur, and whether and to whom they may be disclosed. Some considerations will be provided regarding forensic experts concerning their moral commitment to warn relatives about IFs.
Entrepreneurship Education and Students’ Entrepreneurial Intention in Higher Education
Authors: Mei Hong , Lee Ching-Hung , Xiang Yuanyuan
Published: September 2020

Facing the challenging employment situation and the changing labor market, developing student entrepreneurial intention has attracted significant policy consideration in China. This study describes the background of entrepreneurship education in China’s higher education institutes and explores the influences of entrepreneurship education on student entrepreneurial intention. Using data from a survey on students in China, this study finds that students in different types of institutions and different major fields had a different level of engagement in entrepreneurship education. Further, the higher the level of entrepreneurship education the students received, the stronger their self-efficacy of entrepreneurial decision-making was, and the stronger their entrepreneurial intention was. Student entrepreneurial decision-making self-efficacy played a mediating role between entrepreneurship education and student entrepreneurial intention. We found that entrepreneurship education has a positive effect on entrepreneurial intention. Entrepreneurship education course-taking has a positive effect on entrepreneurial decision-making. Furthermore, the positive effect of self-efficacy of entrepreneurial decision-making on entrepreneurial intention was also confirmed. We also found that self-efficacy of entrepreneurial decision-making played the significant role of mediator between entrepreneurship education and entrepreneurial intention. The findings also showed a difference between the current China context and the western context that taking entrepreneurship-related classes had more considerable influences on student entrepreneurial intention than entrepreneurship-related practicum. We discuss the implications of the improvement of higher education in China and relevance to other contexts.
Ethics and Deontology in Spanish Public Universities
Authors: Delgado-Alemany Rafael , Blanco-González Alicia , Díez-Martín Francisco
Published: September 2020

The existence of ethical and deontological codes is a reality integrated in highly competitive sectors, such as the medical sector or the legal profession. Most studies on ethics and deontology focus on the way in which they are communicated and their effectiveness. However, no special interest has been paid to the existence, application and content of ethics and deontology in the university sector and its relationship with the transmission of ethical and deontological principles to students. Professionals, employees and managers who will play their role in society, perform their work in companies or develop strategic plans, are trained at universities, which must play an important role in the ethical and deontological training of future social actors. Therefore, it is necessary to respond to whether public universities have codes of ethics and whether the fact of having these codes implies a greater commitment to the inclusion of ethical values in their training programs. To this end, Spanish public universities are analyzed and the results, which are grouped by areas of knowledge, are presented. The results achieved provide useful insight for university managers concerned with implementing ethical and responsible policies.
5G Cellular Networks: Coverage Analysis in the Presence of Inter-Cell Interference and Intentional Jammers
Authors: Qasim Muhammad , Haroon Muhammad Sajid , Imran Muhammad , Muhammad Fazal , Kim Sunghwan
Published: September 2020

Intentional jammers (IJs) can be used by attackers for the launching of distributed denial-of-service attacks in 5G cellular networks. These adversaries are assumed to have adequate information about the network specifications, such as duration, transmit power and positions. With these assumptions, the IJs gain the ability to disrupt the legitimate communication of the network. Heterogeneous cellular networks (HetNets) can be considered a vital enabler for 5G cellular networks. Small base stations (SBSs) are deployed inside macro base station (MBS) to improve spectral efficiency and capacity. Due to orthogonal frequency division multiplexing assumption, HetNets’ performance is mainly limited by inter-cell interference (ICI). Additionally, there exist IJs-interference (IJs-I), which significantly degrades the network coverage depending on the IJs’ transmit power levels and their proximity with the target. The proposed work explores the uplink (UL) coverage performance of HetNets in the presence of both IJs-I and ICI. Moreover, to reduce the effects of ICI and IJs-I, reverse frequency allocation (RFA) is employed which is a proactive interference abating scheme. In RFA, different sub-bands of the available spectrum are used by MBS and SBS in alternate regions. The proposed setup is evaluated both analytically as well as with the help of simulation. The results demonstrate considerable UL coverage performance improvement by effectively mitigating IJs-I and ICI.
Heterogeneous Cooperative Bare-Bones Particle Swarm Optimization with Jump for High-Dimensional Problems
Authors: Lee Joonwoo , Kim Won
Published: September 2020

This paper proposes a novel Bare-Bones Particle Swarm Optimization (BBPSO) algorithm for solving high-dimensional problems. BBPSO is a variant of Particle Swarm Optimization (PSO) and is based on a Gaussian distribution. The BBPSO algorithm does not consider the selection of controllable parameters for PSO and is a simple but powerful optimization method. This algorithm, however, is vulnerable to high-dimensional problems, i.e., it easily becomes stuck at local optima and is subject to the “two steps forward, one step backward” phenomenon. This study improves its performance for high-dimensional problems by combining heterogeneous cooperation based on the exchange of information between particles to overcome the “two steps forward, one step backward” phenomenon and a jumping strategy to avoid local optima. The CEC 2010 Special Session on Large-Scale Global Optimization (LSGO) identified 20 benchmark problems that provide convenience and flexibility for comparing various optimization algorithms specifically designed for LSGO. Simulations are performed using these benchmark problems to verify the performance of the proposed optimizer by comparing the results of other variants of the PSO algorithm.
Monolithic Integrated High Frequency GaN DC-DC Buck Converters with High Power Density Controlled by Current Mode Logic Level Signal
Authors: Lai Longkun , Zhang Ronghua , Cheng Kui , Xia Zhiying , Wei Chun , Wei Ke , Luo Weijun , Liu Xinyu
Published: September 2020

Integration is a key way to improve the switching frequency and power density for a DC-DC converter. A monolithic integrated GaN based DC-DC buck converter is realized by using a gate driver and a half-bridge power stage. The gate driver is composed of three stages (amplitude amplifier stage, level shifting stage and resistive-load amplifier stage) to amplify and modulate the driver control signal, i.e., CML (current mode logic) level of which the swing is from 1.1 to 1.8 V meaning that there is no need for an additional buffer or preamplifier for the control signal. The gate driver can provide sufficient driving capability for the power stage and improve the power density efficiently. The proposed GaN based DC-DC buck converter is implemented in the 0.25 μm depletion mode GaN-on-SiC process with a chip area of 1.7 mm × 1.3 mm, which is capable of operating at high switching frequency up to 200 MHz and possesses high power density up to 1 W/mm2 at 15 V output voltage. To the authors’ knowledge, this is the highest power density for GaN based DC-DC converter at the hundreds of megahertz range.
A Parallel Algorithm for Matheuristics: A Comparison of Optimization Solvers
Authors: González Martín , López-Espín Jose J. , Aparicio Juan
Published: September 2020

Metaheuristic and exact methods are one of the most common tools to solve Mixed-Integer Optimization Problems (MIPs). Most of these problems are NP-hard problems, being intractable to obtain optimal solutions in a reasonable time when the size of the problem is huge. In this paper, a hybrid parallel optimization algorithm for matheuristics is studied. In this algorithm, exact and metaheuristic methods work together to solve a Mixed Integer Linear Programming (MILP) problem which is divided into two different subproblems, one of which is linear (and easier to solve by exact methods) and the other discrete (and is solved using metaheuristic methods). Even so, solving this problem has a high computational cost. The algorithm proposed follows an efficient decomposition which is based on the nature of the decision variables (continuous versus discrete). Because of the high cost of the algorithm, as this kind of problem belongs to NP-hard problems, parallelism techniques have been incorporated at different levels to reduce the computing cost. The matheuristic has been optimized both at the level of the problem division and internally. This configuration offers the opportunity to improve the computational time and the fitness function. The paper also focuses on the performance of different optimization software packages working in parallel. In particular, a comparison of two well-known optimization software packages (CPLEX and GUROBI) is performed when they work executing several simultaneous instances, solving various problems at the same time. Thus, this paper proposes and studies a two-level parallel algorithm based on message-passing (MPI) and shared memory (Open MP) schemes where the two subproblems are considered and where the linear problem is solved by using and studying optimization software packages (CPLEX and GUROBI). Experiments have also been carried out to ascertain the performance of the application using different programming paradigms (shared memory and distributed memory).
Predictive Torque Control Based on Discrete Space Vector Modulation of PMSM without Flux Error-Sign and Voltage-Vector Lookup Table
Authors: Mohd Alsofyani Ibrahim , Lee Kyo-Beum
Published: September 2020

The conventional finite set–predictive torque control of permanent magnet synchronous motors (PMSMs) suffers from large flux and torque ripples, as well as high current harmonic distortions. Introducing the discrete space vector modulation (DSVM) into the predictive torque control (PTC-DSVM) can improve its steady-state performance; however, the control complexity is further increased owing to the large voltage–vector lookup table that increases the burden of memory. A simplified PTC-DSVM with 73 synthesized voltage vectors (VVs) is proposed herein, for further improving the steady-state performance of the PMSM drives with a significantly lower complexity and without requiring a VV lookup table. The proposed scheme for reducing the computation burden is designed to select an optimal zone of space vector diagram (SVD) in the utilized DSVM based on the torque demand. Hence, only 10 out of 73 admissible VVs will be initiated online upon the optimal SVD zone selection. Additionally, with the proposed algorithm, no flux error is required to control the flux demand. The proposed PTC-DSVM exhibits high performance features, such as low complexity with less memory utilization, reduced torque and flux ripples, and less redundant VVs in the prediction process. The simulation and experimental results for the 11 kW PMSM drive are presented to prove the effectiveness of the proposed control strategy.
Comparing Video Activity Classifiers within a Novel Framework
Authors: Kwan Chiman , Budavari Bence , Ayhan Bulent
Published: September 2020

Video activity classification has many applications. It is challenging because of the diverse characteristics of different events. In this paper, we examined different approaches to event classification within a general framework for video activity detection and classification. In our experiments, we focused on event classification in which we explored a deep learning-based approach, a rule-based approach, and a hybrid combination of the previous two approaches. Experimental results using the well-known Video Image Retrieval and Analysis Tool (VIRAT) database showed that the proposed classification approaches within the framework are promising and more research is needed in this area
State of Charge Estimation in Lithium-Ion Batteries: A Neural Network Optimization Approach
Authors: Hossain Lipu M. S. , Hannan M. A. , Hussain Aini , Ayob Afida , Saad Mohamad H. M. , Muttaqi Kashem M.
Published: September 2020

The development of an accurate and robust state-of-charge (SOC) estimation is crucial for the battery lifetime, efficiency, charge control, and safe driving of electric vehicles (EV). This paper proposes an enhanced data-driven method based on a time-delay neural network (TDNN) algorithm for state of charge (SOC) estimation in lithium-ion batteries. Nevertheless, SOC accuracy is subject to the suitable value of the hyperparameters selection of the TDNN algorithm. Hence, the TDNN algorithm is optimized by the improved firefly algorithm (iFA) to determine the optimal number of input time delay (UTD) and hidden neurons (HNs). This work investigates the performance of lithium nickel manganese cobalt oxide (LiNiMnCoO2) and lithium nickel cobalt aluminum oxide (LiNiCoAlO2) toward SOC estimation under two experimental test conditions: the static discharge test (SDT) and hybrid pulse power characterization (HPPC) test. Also, the accuracy of the proposed method is evaluated under different EV drive cycles and temperature settings. The results show that iFA-based TDNN achieves precise SOC estimation results with a root mean square error (RMSE) below 1%. Besides, the effectiveness and robustness of the proposed approach are validated against uncertainties including noise impacts and aging influences.
Designing a CHAM Block Cipher on Low-End Microcontrollers for Internet of Things
Authors: Kwon Hyeokdong , An SangWoo , Kim YoungBeom , Kim Hyunji , Choi Seung Ju , Jang Kyoungbae , Park Jaehoon , Kim Hyunjun , Seo Seog Chung , Seo Hwajeong
Published: September 2020

As the technology of Internet of Things (IoT) evolves, abundant data is generated from sensor nodes and exchanged between them. For this reason, efficient encryption is required to keep data in secret. Since low-end IoT devices have limited computation power, it is difficult to operate expensive ciphers on them. Lightweight block ciphers reduce computation overheads, which are suitable for low-end IoT platforms. In this paper, we implemented the optimized CHAM block cipher in the counter mode of operation, on 8-bit AVR microcontrollers (i.e., representative sensor nodes). There are four new techniques applied. First, the execution time is drastically reduced, by skipping eight rounds through pre-calculation and look-up table access. Second, the encryption with a variable-key scenario is optimized with the on-the-fly table calculation. Third, the encryption in a parallel way makes multiple blocks computed in online for CHAM-64/128 case. Fourth, the state-of-art engineering technique is fully utilized in terms of the instruction level and register level. With these optimization methods, proposed optimized CHAM implementations for counter mode of operation outperformed the state-of-art implementations by 12.8%, 8.9%, and 9.6% for CHAM-64/128, CHAM-128/128, and CHAM-128/256, respectively.
Development of a Multi-Purpose Autonomous Differential Drive Mobile Robot for Plant Phenotyping and Soil Sensing
Authors: Iqbal Jawad , Xu Rui , Halloran Hunter , Li Changying
Published: September 2020

To help address the global growing demand for food and fiber, selective breeding programs aim to cultivate crops with higher yields and more resistance to stress. Measuring phenotypic traits needed for breeding programs is usually done manually and is labor-intensive, subjective, and lacks adequate temporal resolution. This paper presents a Multipurpose Autonomous Robot of Intelligent Agriculture (MARIA), an open source differential drive robot that is able to navigate autonomously indoors and outdoors while conducting plant morphological trait phenotyping and soil sensing. For the design of the rover, a drive system was developed using the Robot Operating System (ROS), which allows for autonomous navigation using Global Navigation Satellite Systems (GNSS). For phenotyping, the robot was fitted with an actuated LiDAR unit and a depth camera that can estimate morphological traits of plants such as volume and height. A three degree-of-freedom manipulator mounted on the mobile platform was designed using Dynamixel servos that can perform soil sensing and sampling using off-the-shelf and 3D printed components. MARIA was able to navigate both indoors and outdoors with an RMSE of 0.0156 m and 0.2692 m, respectively. Additionally, the onboard actuated LiDAR sensor was able to estimate plant volume and height with an average error of 1.76% and 3.2%, respectively. The manipulator performance tests on soil sensing was also satisfactory. This paper presents a design for a differential drive mobile robot built from off-the-shelf components that makes it replicable and available for implementation by other researchers. The validation of this system suggests that it may be a valuable solution to address the phenotyping bottleneck by providing a system capable of navigating through crop rows or a greenhouse while conducting phenotyping and soil measurements.
Sensing-HH: A Deep Hybrid Attention Model for Footwear Recognition
Authors: Yao Yumin , Wen Ya , Wang Jianxin
Published: September 2020

The human gait pattern is an emerging biometric trait for user identification of smart devices. However, one of the challenges in this biometric domain is the gait pattern change caused by footwear, especially if the users are wearing high heels (HH). Wearing HH puts extra stress and pressure on various parts of the human body and it alters the wearer’s common gait pattern, which may cause difficulties in gait recognition. In this paper, we propose the Sensing-HH, a deep hybrid attention model for recognizing the subject’s shoes, flat or different types of HH, using smartphone’s motion sensors. In this model, two streams of convolutional and bidirectional long short-term memory (LSTM) networks are designed as the backbone, which extract the hierarchical spatial and temporal representations of accelerometer and gyroscope individually. We also introduce a spatio attention mechanism into the stacked convolutional layers to scan the crucial structure of the data. This mechanism enables the hybrid neural networks to capture extra information from the signal and thus it is able to significantly improve the discriminative power of the classifier for the footwear recognition task. To evaluate Sensing-HH, we built a dataset with 35 young females, each of whom walked for 4 min wearing shoes with varied heights of the heels. We conducted extensive experiments and the results demonstrated that the Sensing-HH outperformed the baseline models on leave-one-subject-out cross-validation (LOSO-CV). The Sensing-HH achieved the best Fm score, which was 0.827 when the smartphone was attached to the waist. This outperformed all the baseline methods at least by more than 14%. Meanwhile, the F1 Score of the Ultra HH was as high as 0.91. The results suggest the proposed model has made the footwear recognition more efficient and automated. We hope the findings from this study paves the way for a more sophisticated application using data from motion sensors, as well as lead to a path to a more robust biometric system based on gait pattern.
Integrating LCA with Process Modeling for the Energetic and Environmental Assessment of a CHP Biomass Gasification Plant: A Case Study in Thessaly, Greece
Authors: Voultsos Ioannis , Katsourinis Dimitrios , Giannopoulos Dimitrios , Founti Maria
Published: September 2020

The energetic and environmental performance of a cogeneration biomass gasification plant, situated in Thessaly, Greece is evaluated via a methodology combining process simulation and Life Cycle Assessment (LCA). Initially, the gasification process of the most common agricultural residues found in the Thessaly region is simulated to establish the effect of technical parameters such as gasification temperature, equivalence ratio and raw biomass moisture content. It is shown that a maximum gasification efficiency of approximately 70% can be reached for all feedstock types. Lower efficiency values are associated with increased raw biomass moisture content. Next, the gasifier model is up-scaled, achieving the operation of a 1 MWel and 2.25 MWth cogeneration plant. The Life Cycle Assessment of the operation of the cogeneration unit is conducted using as input the performance data from the process simulation. Global Warming Potential and the Cumulative Demand of Non-Renewable Fossil Energy results suggest that the component which had the major share in both impact categories is the self-consumption of electricity of the plant. Finally, the key conclusion of the present study is the quantification of carbon dioxide mitigation and non-renewable energy savings by comparing the biomass cogeneration unit operation with conventional reference cases.
Comparison of the Scaling Relationships of Leaf Biomass versus Surface Area between Spring and Summer for Two Deciduous Tree Species
Authors: Liu Mengdi , Niklas Karl J. , Niinemets Ülo , Hölscher Dirk , Chen Long , Shi Peijian
Published: September 2020

The scaling relationship between either leaf dry or fresh mass (M) and surface area (A) can reflect the photosynthetic potential and efficiency of light harvesting in different broad-leaved plants. In growing leaves, lamina area expansion is typically finished before the completion of leaf biomass accumulation, thereby affecting the M vs. A scaling relationship at different developmental stages of leaves (e.g., young vs. adult leaves). In addition, growing plants can have different-sized leaves at different plant ages, potentially also changing M vs. A scaling. Furthermore, leaf shape can also change during the course of ontogeny and modify the M vs. A scaling relationship. Indeed, the effect of seasonal changes in leaf shape on M vs. A scaling has not been examined in any previous studies known to us. The study presented here was conducted using two deciduous tree species: Alangium chinense (saplings forming leaves through the growing season) and Liquidambar formosana (adult trees producing only one leaf flush in spring) that both have complex but nearly bilaterally symmetrical leaf shapes. We determined (i) whether leaf shapes differed in spring versus summer; (ii) whether the M vs. A scaling relationship varied over time; and (iii) whether there is a link between leaf shape and the scaling exponent governing the M vs. A scaling relationship. The data indicated that (i) the leaf dissection index in spring was higher than that in summer for both species (i.e., leaf-shape complexity decreased from young to adult leaves); (ii) there was a significant difference in the numerical value of the scaling exponent of leaf perimeter vs. area between leaves sampled at the two dates; (iii) spring leaves had a higher water content than summer leaves, and the scaling exponents of dry mass vs. area and fresh mass vs. area were all greater than unity; (iv) the scaling relationship between fresh mass and area was statistically more robust than that between leaf dry mass and area; (v) the scaling exponents of leaf dry and fresh mass vs. area of A. chinense leaves in spring were greater than those in summer (i.e., leaves in younger plants tend to be larger than leaves in older plants), whereas, for the adult trees of L. formosana, the scaling exponent in spring was smaller than that in summer, indicating increases in leaf dry mass per unit area with increasing leaf age; and (vi) leaf shape appears not to be related to the scaling relationship between either leaf dry or fresh mass and area, but is correlated with the scaling exponent of leaf perimeter vs. area (which tends to be a ½ power function). These trends indicate that studies of leaf morphometrics and scaling relationships must consider the influence of seasonality and plant age in sampling of leaves and the interpretation of data.
A Novel Method of Spectra Processing for Brillouin Optical Time Domain Reflectometry
Authors: Barkov Fedor L. , Konstantinov Yuri A. , Krivosheev Anton I.
Published: September 2020

A new method of Brillouin spectra post-processing, which could be applied in modern distributed optical sensors: Brillouin optical time domain analyzers/reflectometers (BOTDA/BOTDR), has been demonstrated. It operates by means of the correlation analysis performed with special technique («backward-correlation»). It does not need any additional data for time or space averaging and operates with the single spectrum only. We have simulated the method accuracy dependence on signal-to-noise ratio (SNR) and other parameters. It is shown that the new method produces better results at low SNRs than conventional technique, based on finding of Brillouin spectrum maximum, do. These results are in a good agreement with the experiment. Finally, we have estimated the performance of the new method for its application in polarization-BOTDA set-up for a polarization maintaining (PM) fiber modal birefringence distributed study.
Consumer Attitudes towards Local and Organic Food with Upcycled Ingredients: An Italian Case Study for Olive Leaves
Authors: Perito Maria Angela , Coderoni Silvia , Russo Carlo
Published: September 2020

Food made with upcycled ingredients has received considerable attention in very recent years as a result of the need to both reduce waste and increase food nutritional properties. However, consumer acceptance of these novel foods is fundamental to their market uptake. This paper aims to assess the likelihood of the acceptance of food obtained from upcycled ingredients of olive oil productions and its association with some relevant recent consumption trends, such as organic food consumption and attention to food origin. In addition, particular attention is given to age group behaviors to appraise the differences between generations. Results suggest that, despite the negative influence of food technophobia, a core of sustainability-minded consumers seems to emerge that is interested in organic or local products, that could also favor the uptake of these novel food made with upcycled ingredients in the market. Results suggest that developing organic or “local” food products with upcycled ingredients can increase the probability of consumer acceptance.
UHPLC–MS/MS-Based Nontargeted Metabolomics Analysis Reveals Biomarkers Related to the Freshness of Chilled Chicken
Authors: Zhang Tao , Zhang Shanshan , Chen Lan , Ding Hao , Wu Pengfei , Zhang Genxi , Xie Kaizhou , Dai Guojun , Wang Jinyu
Published: September 2020

To identify metabolic biomarkers related to the freshness of chilled chicken, ultra-high-performance liquid chromatography–mass spectrometry (UHPLC–MS/MS) was used to obtain profiles of the metabolites present in chilled chicken stored for different lengths of time. Random forest regression analysis and stepwise multiple linear regression were used to identify key metabolic biomarkers related to the freshness of chilled chicken. A total of 265 differential metabolites were identified during storage of chilled chicken. Of these various metabolites, 37 were selected as potential biomarkers by random forest regression analysis. Receiver operating characteristic (ROC) curve analysis indicated that the biomarkers identified using random forest regression analysis showed a strong correlation with the freshness of chilled chicken. Subsequently, stepwise multiple linear regression analysis based on the biomarkers identified by using random forest regression analysis identified indole-3-carboxaldehyde, uridine monophosphate, s-phenylmercapturic acid, gluconic acid, tyramine, and Serylphenylalanine as key metabolic biomarkers. In conclusion, our study characterized the metabolic profiles of chilled chicken stored for different lengths of time and identified six key metabolic biomarkers related to the freshness of chilled chicken. These findings can contribute to a better understanding of the changes in the metabolic profiles of chilled chicken during storage and provide a basis for the further development of novel detection methods for the freshness of chilled chicken.
Effect of Roasting and Brewing on the Antioxidant and Antiproliferative Activities of Tartary Buckwheat
Authors: Ryu Ji-yeon , Choi Yoonseong , Hong Kun-Hwa , Chung Yong Suk , Cho Somi Kim
Published: September 2020

We evaluated the effect of the roasting and brewing conditions of Tartary buckwheat (TB), which is widely used in infusion teas, on its antioxidant and antiproliferative activities in vitro. TB was roasted at 210 °C for 10 min and brewed at a high temperature for a short time (HTST; 85–90 °C, 3 min) or at room temperature for a long time (RTLT; 25–30 °C, 24 h). Roasted TB (RTB) tea brewed at RTLT had the highest total polyphenol content (TPC) and total flavonoid content (TFC) among the four TB teas for different roasting and brewing conditions. Moreover, RTB brewed at RTLT showed the greatest 2,2-diphenyl-1-picrylhydrazyl-, 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)-, and alkyl-scavenging activities. The TB tea brewed at RTLT had higher Fe2+-chelating activity than that brewed at HTST, irrespective of roasting. Moreover, RTB tea brewed at RTLT inhibited the proliferation of human pancreatic and breast cancer cells. Overall, RTB-RTLT displayed the largest effect on antioxidant and antiproliferative effects. Finally, rutin was found to possess the most pronounced effect on the antioxidant and antiproliferative activities of the TB teas. These results indicate that the antioxidant and antiproliferative activities of RTB are enhanced by RTLT brewing.
Building towards Precision Oncology for Pancreatic Cancer: Real-World Challenges and Opportunities
Authors: Wang Yifan , Lakoma Anna , Zogopoulos George
Published: September 2020

The advent of next-generation sequencing (NGS) has provided unprecedented insight into the molecular complexity of pancreatic ductal adenocarcinoma (PDAC). This has led to the emergence of biomarker-driven treatment paradigms that challenge empiric treatment approaches. However, the growth of sequencing technologies is outpacing the development of the infrastructure required to implement precision oncology as routine clinical practice. Addressing these logistical barriers is imperative to maximize the clinical impact of molecular profiling initiatives. In this review, we examine the evolution of precision oncology in PDAC, spanning from germline testing for cancer susceptibility genes to multi-omic tumor profiling. Furthermore, we highlight real-world challenges to delivering precision oncology for PDAC, and propose strategies to improve the generation, interpretation, and clinical translation of molecular profiling data.
Exploring Eimeria Genomes to Understand Population Biology: Recent Progress and Future Opportunities
Authors: Blake Damer P. , Worthing Kate , Jenkins Mark C.
Published: September 2020

Eimeria, protozoan parasites from the phylum Apicomplexa, can cause the enteric disease coccidiosis in all farmed animals. Coccidiosis is commonly considered to be most significant in poultry; due in part to the vast number of chickens produced in the World each year, their short generation time, and the narrow profit margins associated with their production. Control of Eimeria has long been dominated by routine chemoprophylaxis, but has been supplemented or replaced by live parasite vaccination in a minority of production sectors. However, public and legislative demands for reduced drug use in food production is now driving dramatic change, replacing reliance on relatively indiscriminate anticoccidial drugs with vaccines that are Eimeria species-, and in some examples, strain-specific. Unfortunately, the consequences of deleterious selection on Eimeria population structure and genome evolution incurred by exposure to anticoccidial drugs or vaccines are unclear. Genome sequence assemblies were published in 2014 for all seven Eimeria species that infect chickens, stimulating the first population genetics studies for these economically important parasites. Here, we review current knowledge of eimerian genomes and highlight challenges posed by the discovery of new, genetically cryptic Eimeria operational taxonomic units (OTUs) circulating in chicken populations. As sequencing technologies evolve understanding of eimerian genomes will improve, with notable utility for studies of Eimeria biology, diversity and opportunities for control.
Aliarcobacter butzleri from Water Poultry: Insights into Antimicrobial Resistance, Virulence and Heavy Metal Resistance
Authors: Müller Eva , Abdel-Glil Mostafa Y. , Hotzel Helmut , Hänel Ingrid , Tomaso Herbert
Published: September 2020

Aliarcobacter butzleri is the most prevalent Aliarcobacter species and has been isolated from a wide variety of sources. This species is an emerging foodborne and zoonotic pathogen because the bacteria can be transmitted by contaminated food or water and can cause acute enteritis in humans. Currently, there is no database to identify antimicrobial/heavy metal resistance and virulence-associated genes specific for A. butzleri. The aim of this study was to investigate the antimicrobial susceptibility and resistance profile of two A. butzleri isolates from Muscovy ducks (Cairina moschata) reared on a water poultry farm in Thuringia, Germany, and to create a database to fill this capability gap. The taxonomic classification revealed that the isolates belong to the Aliarcobacter gen. nov. as A. butzleri comb. nov. The antibiotic susceptibility was determined using the gradient strip method. While one of the isolates was resistant to five antibiotics, the other isolate was resistant to only two antibiotics. The presence of antimicrobial/heavy metal resistance genes and virulence determinants was determined using two custom-made databases. The custom-made databases identified a large repertoire of potential resistance and virulence-associated genes. This study provides the first resistance and virulence determinants database for A. butzleri.
Risk Factors Associated with Recurrent Clostridioides difficile Infection
Authors: Negrut Nicoleta , Bungau Simona , Behl Tapan , Khan Shamim Ahmad , Vesa Cosmin Mihai , Bustea Cristiana , Nistor-Cseppento Delia Carmen , Rus Marius , Pavel Flavia-Maria , Tit Delia Mirela
Published: September 2020

Clostridioides difficile (CD) is responsible for nosocomial diarrhea syndrome with possible severe progression. Recurrence of the disease induces higher health system costs, as well as exposes patients to additional health risks. Patients with recurrence of this disease are difficult to identify, so the purpose of this study is to quantify various demographic, clinical, and treatment factors that could prevent further progression to recurrence of the disease. In the period 2018–2019, about 195 patients were diagnosed with more than one episode of CDI in the three months following the first episode. The recurrence rate for CDI was 53.84% (60.95% for one episode and 39.05% for multiple episodes). Most commonly afflicted were 60–69-year-old patients, or those with higher Charlson Comorbidity Index (CCI). Multiple analyses associated cardiovascular (odds ratios (OR) = 3.02, 95% confidence intervals (CI) = 1.23–7.39, p = 0.015), digestive (OR = 3.58, 95% CI = 1.01–12.63, p = 0.047), dementia (OR = 3.26, 95% CI = 1.26–8.41, p = 0.014), immunosuppressive (OR = 3.88, 95% CI = 1.34–11.21, p = 0.012) comorbidities with recurrences. Risk factor identification in the first episode of CDI could lead to the implementation of treatment strategies to improve the patients’ quality of life affected by this disease.
Factors that Influence the Decision to Seek Help in a Police Population
Authors: Burns Carolyn , Buchanan Marla
Published: September 2020

Police officers face many competing pressures and demands. Exposure to potentially traumatic incidents and significant job-related stressors can place many at higher risk of developing physical and mental health problems. The police culture exerts a pronounced influence on officers, preventing some from asking for or receiving assistance. The stigma of being perceived as weak or incompetent, concerns about being labelled unfit for duty, and worry that accessing psychological support will impact future career advancement can affect the decision to seek help. The Enhanced Critical Incident Technique was utilized to investigate the following research question: What helps or hinders the decision to access psychological services in a police population? Qualitative interviews were conducted with 20 serving Royal Canadian Mounted Police officers in the lower mainland of British Columbia, Canada. The findings encompass five main themes: the importance of systemic factors, access to information and education, quality and influence of relationships, individual characteristics, and organizational processes that will increase the likelihood of accessing mental health services. The results contribute to the empirical literature by enhancing what is known about elements that influence an officers’ decision to seek psychological services, and factors that can enable officers to overcome barriers.
Beyond the Decline of Wild Bees: Optimizing Conservation Measures and Bringing Together the Actors
Authors: Drossart Maxime , Gérard Maxence
Published: September 2020

Wild bees are facing a global decline mostly induced by numerous human factors for the last decades. In parallel, public interest for their conservation increased considerably, namely through numerous scientific studies relayed in the media. In spite of this broad interest, a lack of knowledge and understanding of the subject is blatant and reveals a gap between awareness and understanding. While their decline is extensively studied, information on conservation measures is often scattered in the literature. We are now beyond the precautionary principle and experts are calling for effective actions to promote wild bee diversity and the enhancement of environment quality. In this review, we draw a general and up-to-date assessment of the conservation methods, as well as their efficiency and the current projects that try to fill the gaps and optimize the conservation measures. Targeting bees, we focused our attention on (i) the protection and restoration of wild bee habitats, (ii) the conservation measures in anthropogenic habitats, (iii) the implementation of human made tools, (iv) how to deal with invasive alien species, and finally (v) how to communicate efficiently and accurately. This review can be considered as a needed catalyst to implement concrete and qualitative conversation actions for bees.
IoT: A New Open Access Journal for Internet of Things
Authors: Picone Marco
Published: September 2020

During the last decade, the Information Technology ecosystem has been significantly revolutionized by the advent of the Internet of Things (IoT) and its pervasive and quick evolution [...]
Identification of Acupoint Indication from Reverse Inference: Data Mining of Randomized Controlled Clinical Trials
Authors: Hwang Ye-Chae , Lee In-Seon , Ryu Yeonhee , Lee Ye-Seul , Chae Younbyoung
Published: September 2020

The specificity of acupoint indication (i.e., reverse inference—diseases for which an acupoint could be used) might differ from the specificity of acupoint selection (i.e., forward inference—acupoints used for a disease). In this study, we explore acupoint specificity through reverse inferences from the dataset of prescribed acupoints for a certain disease in clinical trials. We searched acupuncture treatment regimens in randomized controlled trials included in the Cochrane Database of Systematic Reviews. For forward inference, the acupoints prescribed for each disease were quantified. For reverse inference, diseases for each acupoint were quantified. Data were normalized using Z-scores. Bayes factor correction was performed to adjust for the prior probability of diseases. The specificities of acupoint selections in 30 diseases were determined using forward inference. The specificities of acupoint indications regarding 49 acupoints were identified using reverse inference and then subjected to Bayes factor correction. Two types of acupoint indications were identified for 24 acupoints: regional and distal. Our approach suggests that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Acupoint indication will improve our understanding of acupoint specificity and will lead to the establishment of a new model of analysis and educational resources for acupoint characteristics.
CT Findings in Pulmonary and Abdominal Sarcoidosis. Implications for Diagnosis and Classification
Authors: Tana Claudio , Donatiello Iginio , Coppola Maria Gabriella , Ricci Fabrizio , Maccarone Marica Tina , Ciarambino Tiziana , Cipollone Francesco , Giamberardino Maria Adele
Published: September 2020

Sarcoidosis is a granulomatous disorder of unknown etiology characterized by noncaseating granulomas virtually in every organ and tissue. This finding represents the most important diagnostic clue to reach a correct definition of sarcoidosis, although the biopsy is invasive and has several risk procedures. Several efforts are made to suspect the diagnosis of sarcoidosis by combining noninvasive elements, in particular from imaging, though these findings are often nonspecific and reflect the wide multifactorial pathogenesis. Every effort should be made to obtain a detailed radiological picture that, if associated with a suggestive clinical picture, could avoid the need of biopsy in some specific cases. In this narrative review, we aim to describe main computed tomography (CT) features of pulmonary and abdominal sarcoidosis, by reporting strengths and limits of this technique, in particular for the identification of extrapulmonary, isolated disease.
Revision Arthroplasty Through the Direct Anterior Approach Using an Asymmetric Acetabular Component
Authors: Prodinger Peter Michael , Lazic Igor , Horas Konstantin , Burgkart Rainer , von Eisenhart-Rothe Rüdiger , Weissenberger Manuel , Rudert Maximilian , Holzapfel Boris Michael
Published: September 2020

Despite increasing numbers of primary hip arthroplasties performed through the direct anterior approach (DAA), there is a lack of literature on DAA revision arthroplasty. The present study was performed in order to evaluate outcomes and revision rates after revision through the DAA using an asymmetric acetabular component with optional intra- and extramedullary fixation. In a retrospective cohort study, we analyzed prospectively collected data of 57 patients (61 hips, 43 female, 18 male) who underwent aseptic acetabular component revision through the DAA with the abovementioned implant system between January 2015 and December 2017. The mean follow-up was 40 months (12–56). Survival rates were estimated using the Kaplan–Meier method. All complications were documented and functional outcomes were assessed pre- and postoperatively. Kaplan–Meier analysis revealed an estimated five-year implant survival of 97% (confidence interval CI 87–99%). The estimated five-year survival with revision for any cause was 93% (CI 83–98%). The overall revision rate was 6.6% (n = 4). Two patients had to undergo revision due to periprosthetic infection (3.3%). In one patient, the acetabular component was revised due to aseptic loosening four months postoperatively. Another patient suffered from postoperative iliopsoas impingement and was treated successfully by arthroscopic iliopsoas tenotomy. Two (3.3%) of the revised hips dislocated postoperatively. The mean Harris Hip Score improved from 35 (2–66) preoperatively to 86 (38–100) postoperatively (p < 0.001). The hip joint’s anatomical center of rotation was restored at a high degree of accuracy. Our findings demonstrate that acetabular revision arthroplasty through the DAA using an asymmetric acetabular component with optional intra- and extramedullary fixation is safe and practicable, resulting in good radiographic and clinical midterm results.
Computational Analysis of Clinical and Molecular Markers and New Theranostic Possibilities in Primary Open-Angle Glaucoma
Authors: Pinazo-Durán María D. , García-Medina José J. , Bolarín José M. , Sanz-González Silvia M. , Valero-Vello Mar , Abellán-Abenza Javier , Zanón-Moreno Vicente , Moreno-Montañés Javier
Published: September 2020

Primary open-angle glaucoma (POAG) is a paramount cause of irreversible visual disability worldwide. We focus on identifying clinical and molecular facts that may help elucidating the pathogenic mechanisms of the disease. By using ophthalmological approaches (biomicroscopy, ocular fundus, optical coherence tomography, and perimetry) and experimental tests (enzyme-linked immunosorbent assay (ELISA), high performance liquid chromatography (HPLC), and Western blot/immunoblotting) directed to evaluate the oxidative stress, inflammation, apoptosis, and neurodegeneration processes, we gather information to build a network of data to perform a computational bioinformatics analysis. Our results showed strong interaction of the above players and its downstream effectors in POAG pathogenesis. In conclusion, specific risk factors were identified, and molecules involved in multiple pathways were found in relation to anterior and posterior eye segment glaucoma changes, pointing to new theranostic challenges for better managing POAG progression.
Risk Assessment Using Risk Scores in Patients with Acute Coronary Syndrome
Authors: Chan Pin Yin Dean , Azzahhafi Jaouad , James Stefan
Published: September 2020

Risk scores are widely used in patients with acute coronary syndrome (ACS) prior to treatment decision-making at different points in time. At initial hospital presentation, risk scores are used to assess the risk for developing major adverse cardiac events (MACE) and can guide clinicians in either discharging the patients at low risk or swiftly admitting and treating the patients at high risk for MACE. During hospital admission, risk assessment is performed to estimate mortality, residual ischemic and bleeding risk to guide further in-hospital management (e.g., timing of coronary angiography) and post-discharge management (e.g., duration of dual antiplatelet therapy). In the months and years following ACS, long term risk can also be assessed to evaluate current treatment strategies (e.g., intensify or reduce pharmaceutical treatment options). As multiple risk scores have been developed over the last decades, this review summarizes the most relevant risk scores used in ACS patients.