bluuebunny/crossref_metadata_2025 huggingface dataset:
On Entropy of Probability Integral Transformed Time Series
Authors: Bajić Dragana , Mišić Nataša , Škorić Tamara , Japundžić-Žigon Nina , Milovanović Miloš
Published: October 2020

The goal of this paper is to investigate the changes of entropy estimates when the amplitude distribution of the time series is equalized using the probability integral transformation. The data we analyzed were with known properties—pseudo-random signals with known distributions, mutually coupled using statistical or deterministic methods that include generators of statistically dependent distributions, linear and non-linear transforms, and deterministic chaos. The signal pairs were coupled using a correlation coefficient ranging from zero to one. The dependence of the signal samples is achieved by moving average filter and non-linear equations. The applied coupling methods are checked using statistical tests for correlation. The changes in signal regularity are checked by a multifractal spectrum. The probability integral transformation is then applied to cardiovascular time series—systolic blood pressure and pulse interval—acquired from the laboratory animals and represented the results of entropy estimations. We derived an expression for the reference value of entropy in the probability integral transformed signals. We also experimentally evaluated the reliability of entropy estimates concerning the matching probabilities.
Reducing the Bias of the Smoothed Log Periodogram Regression for Financial High-Frequency Data
Authors: Reschenhofer Erhard , Mangat Manveer K.
Published: October 2020

For typical sample sizes occurring in economic and financial applications, the squared bias of estimators for the memory parameter is small relative to the variance. Smoothing is therefore a suitable way to improve the performance in terms of the mean squared error. However, in an analysis of financial high-frequency data, where the estimates are obtained separately for each day and then combined by averaging, the variance decreases with the sample size but the bias remains fixed. This paper proposes a method of smoothing that does not entail an increase in the bias. This method is based on the simultaneous examination of different partitions of the data. An extensive simulation study is carried out to compare it with conventional estimation methods. In this study, the new method outperforms its unsmoothed competitors with respect to the variance and its smoothed competitors with respect to the bias. Using the results of the simulation study for the proper interpretation of the empirical results obtained from a financial high-frequency dataset, we conclude that significant long-range dependencies are present only in the intraday volatility but not in the intraday returns. Finally, the robustness of these findings against daily and weekly periodic patterns is established.
Prediction of Factors That Affect the Knowledge and Use Higher Education Professors from Spain Make of ICT Resources to Teach, Evaluate and Research: A Study with Research Methods in Educational Technology
Authors: Guillén-Gámez Francisco D. , Mayorga-Fernández María J.
Published: October 2020

Due to the rise of new technologies, further development of digital competence by professors is necessary. The aim of this paper is to know the pedagogical digital competence of lecturers in Spain, focused on a model called PDC-TER: ICT resources to Teach, to Evaluate and to Research; as well as to predict those variables that affect the level of this competence through different regressions (Multiple Linear Regression, MLR). A study has been carried out in the Spanish territory, with a total of 867 lecturers. For it, an ex post facto non-probabilistic study based on the survey technique has been proposed. The results show that the professors have an average level of digital pedagogical competence, while in the 2.0 tools for teaching and research dimensions, it has a medium high level of competence, as well as a medium level in relation to the use of tools 2.0 for the evaluation. Furthermore, one of the variables predictive of the level of digital competence in the three dimensions of the PDC-TER model, is the number of research and innovation projects in which they have participated. These data highlight the need to improve the digital competence of professors in order to meet the demands of the qualified professions of the future, and therefore, prepare students for it.
Scaling Laws of Scheduling Gain for Uplink Massive MIMO Systems: Is User Scheduling Still Beneficial for Massive MIMO?
Authors: Kim Taehyoung , Park Sangjoon
Published: October 2020

In this paper, the scaling laws of scheduling gain and the feasibility of user scheduling for uplink massive multiple input–multiple output (MIMO) systems are investigated by analyzing the second moment of mutual information. We consider two well-known linear receivers of matched filter (MF) and zero-forcing (ZF). The exact distribution of the signal-to-interference-plus-noise ratio (SINR) and its moment-generating function are first obtained, and the approximated variance of the mutual information for a user is derived as a closed form with a function of the number of antennas. The achievable scheduling gain under the optimal user scheduler is then derived using the Gaussianity of the sum rate. From the analyses and simulation results, it is found that the scheduling gain for the MF receiver increases with the number of base station (BS) antennas, while that for the ZF receiver decreases as the number of BS antennas increases, for most cases (except some impractical scenarios). Therefore, it is verified that user scheduling is still beneficial for the MF receiver while random user selection is sufficient for the ZF receiver in massive MIMO systems.
A Novel Bidirectional DC-DC Converter for Dynamic Performance Enhancement of Hybrid AC/DC Microgrid
Authors: Keshavarzi Morteza Daviran , Ali Mohd Hasan
Published: October 2020

The conventional bidirectional DC-DC converter (BDC), which employs a half-bridge configuration, has some major disadvantages, including a controller designed for one direction with poor performance in the other direction, a bidirectional operation which does not have symmetrical voltage gain resulting in asymmetrical operation, and step-up and step-down switches that are simultaneously modulated, thereby increasing switching losses. To overcome these drawbacks, this paper proposes a new, nonisolated, DC-DC converter for the bidirectional power flow of battery energy storage applications in DC and hybrid microgrids (HMGs). The proposed converter uses two back-to-back Boost converters with two battery voltage levels, which eliminates step-down operation to obtain symmetric gains and dynamics in both directions. In discharge mode, two battery sections are in parallel connection at a voltage level lower than the grid voltage. In charge mode, two battery sections are in series connection at a voltage level higher than the grid voltage. Simulations demonstrate the efficacy of the proposed converter in the MATALB\Simulink environment. The results show that the proposed converter has promising performance compared to that of the conventional type. Moreover, the novel converter adds no complexity to the control system and does not incur considerable power loss or capital cost.
A Wideband Slotted Spherical Waveguide Antenna Based on Multi-Mode Concept
Authors: Bi Xiaokun , Guo Shaohua , Zhu Yujian , Yuan Tao
Published: October 2020

A wideband slotted spherical waveguide antenna based on the multi-mode concept is presented. The proposed design starts from a metallized spherical cavity fed by a rectangular waveguide. Then, two groups of slots are symmetrically cut on the shell. By suitably choosing the slot dimensions and locations, four radiation modes can be excited in a single radiator and merged with each other, resulting in a wideband radiation characteristic. To verify this, a prototype is designed and fabricated using stereolithography apparatus to achieve a light weight. As the measured fractional bandwidth (FBW) of the proposed antenna can be increased to 70.1% while maintaining stable radiation patterns and high gain, a simple and effective design of wideband slotted waveguide antennas with good radiation characteristics can be validated.
HyperLedger Fabric-Based Proactive Defense against Inside Attackers in the WSN With Trust Mechanism
Authors: Cho Kyeongsun , Cho Youngho
Published: October 2020

In Wireless Sensor Networks (WSNs), the Trust Mechanism (TM) is used to defend against insider attacks by measuring the trustworthiness of all inside sensor nodes in the network. Thus, each sensor node with TM observes its neighbor nodes’ behaviors, evaluates their trustworthiness as numeric trust values, and captures untrustworthy nodes as inside attackers. Although the defense performance of trust mechanisms can be further improved by sharing the information about inside attackers detected by TM with all sensor nodes, the detected inside attacker list must be securely shared with and stored in all sensor nodes in the WSN. However, according to our survey, we observed that most existing studies simply assume that the communication channel for sharing the attacker detection list is reliable and trusted even in the presence of inside attackers in the WSN. In this paper, we propose and implement a proactive defense model that integrates the HyperLedger Fabric and trust mechanism to defend against inside attackers by securely sharing the detected inside attacker list with all sensor nodes in the WSN. In addition, we conduct comparative experiments to show that our proposed model can better defend against inside attackers than an existing trust mechanism. According to our experimental results, our proposed model could lower the attack damage (the number of packet drops) caused by an inside packet drop attacker by 59 to 67% compared to an existing trust mechanism.
Is Promotion of Mobility in Older Patients Hospitalized for Medical Illness a Physician’s Job?—An Interview Study with Physicians in Denmark
Authors: Pedersen Mette Merete , Brødsgaard Rasmus , Nilsen Per , Kirk Jeanette Wassar
Published: October 2020

The aim of this study was to identify the most common barriers and facilitators physicians perceive regarding their role in the promotion of mobility in older adults hospitalized for medical illness as part of on an intervention to promote mobility. Twelve physicians at two medical departments were interviewed face-to-face using semi-structed interviews based on the Theoretical Domains Framework. The physicians’ perceived barriers to promoting mobility were: the patients being too ill, the department’s interior does not fit with mobility, a culture of bedrest, mobility not being part their job, lack of time and resources and unwillingness to accept an extra workload. The facilitators for encouraging mobility were enhanced cross-professional cooperation focusing on mobility, physician encouragement of mobility and patient independence in e.g., picking up beverages and clothes. The identified barriers and facilitators reflected both individual and social influences on physicians’ behaviors to achieve increased mobility in hospitalized older medical patients and suggest that targeting multiple levels is necessary to influence physicians’ propensity to promote mobility.
Systematic Dysphagia Screening of Elderly Persons in the Emergency Department—A Feasibility Study
Authors: Melgaard Dorte , Sørensen Line R. , Lund Diana , Leutscher Peter , Ludwig Marc
Published: October 2020

Identification of elderly patients in risk of dysphagia as early as possible upon hospital admission seems warranted due to the risk of aspiration pneumonia, dehydration, length of stay, and increased mortality. This study aimed to evaluate the feasibility and outcome of dysphagia screening of elderly persons admitted to the emergency department (ED). Inclusion criteria were age ≥ 60 years. A nurse applied the Simple Water Swallow test within one hour of admission. Subsequent assessment was performed by an occupational therapist (OT) using Volume Viscosity Swallow Test and Minimal Eating Observation Form. Of 113 eligible participants (median age 78 years), 75 (66%) were screened in the ED by the nurse, and among those, 12 (16%) were detected with dysphagia. Twenty of the patients not screened in the ED due to critical illness were tested by the OT in the ward after clinical stabilization and 15 patients (75%) were identified with dysphagia. This study demonstrated that it is feasible to perform dysphagia screening of elderly persons by a nurse in the ED, but there are severe limitations according to screening patients with critical illness and patients fasting before surgery in the ED. These patients have a high prevalence of dysphagia and should be screened as early as possible after hospitalization, as it will rarely be possible in the ED.
Sexuality of Women after Gynecological Surgeries
Authors: Kozłowski Mateusz , Gargulińska Paula , Ustianowski Łukasz , Lewandowska Roksana , Kwiatkowski Sebastian , Cymbaluk-Płoska Aneta
Published: October 2020

(1) Background: Disorders of sexual life negatively impact self-esteem and social relationships. This problem affects patients after gynecological surgery. Providing access to specialist sexologist care constitutes an important aspect of support for this patient group. (2) Objective: The aim of the study was to assess the sexual life of women depending on the time since surgery, extent of gynecological surgery and postoperative chemotherapy and/or radiotherapy. (3) Methods: The study included 136 patients from gynecological outpatient clinics in Szczecin, Poland. The women answered questions from a special three-part questionnaire. Participation was anonymous and voluntary. The data obtained in the survey were subject to statistical analysis. (4) Results: Among patients with a sparing of the cervix, most have never or almost never experienced discomfort or pain during intercourse, and believe that the quality of their sex life has not deteriorated after surgery. It was found that cervical removal, despite the existence of other conditions, increases the chance of pain during sexual activity 11 times. We found that the removal of adnexa did not increase the risk of changing sexual activity. In patients who had not undergone postoperative chemo- and/or radiotherapy, sexual activity did not change after surgery, and they never or almost never experienced discomfort or pain during intercourse. On the other hand, it was shown, despite the smaller study group, that patients treated with postoperative chemo- and/or radiotherapy did not initiate sexual intercourse. (5) Conclusion: The more extended the gynecological surgery of the uterus, the greater the limitation of sexual life.
Reductions in Cerebral Blood Flow Can Be Provoked by Sitting in Severe Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Patients
Authors: Campen C (Linda) MC van , Rowe Peter C. , Visser Frans C
Published: October 2020

Introduction: In a large study with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients, we showed that 86% had symptoms of orthostatic intolerance in daily life and that 90% had an abnormal reduction in cerebral blood flow (CBF) during a standard tilt test. A standard head-up tilt test might not be tolerated by the most severely affected bed-ridden ME/CFS patients. Sitting upright is a milder orthostatic stress. The present study examined whether a sitting test, measuring cerebral blood flow by extracranial Doppler, would be sufficient to provoke abnormal reductions in cerebral blood flow in severe ME/CFS patients. Methods and results: 100 severe ME/CFS patients were studied, (88 females) and were compared with 15 healthy controls (HC) (13 females). CBF was measured first while seated for at least one hour, followed by a CBF measurement in the supine position. Fibromyalgia was present in 37 patients. Demographic data as well as supine heart rate and blood pressures were not different between ME/CFS patients and HC. Heart rate and blood pressure did not change significantly between supine and sitting both in patients and HC. Supine CBF was not different between patients and HC. In contrast, absolute CBF during sitting was lower in patients compared to HC: 474 (96) mL/min in patients and 627 (89) mL/min in HC; p < 0.0001. As a result, percent CBF reduction while seated was −24.5 (9.4)% in severe ME/CFS patients and −0.4 (1.2)% in HC (p < 0.0001). In the ten patients who had no orthostatic intolerance complaints in daily life, the CBF reduction was −2.7 (2.1)%, which was not significantly different from HC (p = 0.58). The remaining 90 patients with orthostatic intolerance complaints had a −26.9 (6.2)% CBF reduction. No difference in CBF parameters was found in patients with and without fibromyalgia. Patients with a previous diagnosis of postural orthostatic tachycardia syndrome (POTS) had a significantly larger CBF reduction compared with those without POTS: 28.8 (7.2)% vs. 22.3 (9.7)% (p = 0.0008). Conclusions: A sitting test in severe ME/CFS patients was sufficient to provoke a clinically and statistically significant mean CBF decline of 24.5%. Patients with a previous diagnosis of POTS had a larger CBF reduction while seated, compared to patients without POTS. The magnitude of these CBF reductions is similar to the results in less severely affected ME/CFS patients during head-up tilt, suggesting that a sitting test is adequate for the diagnosis of orthostatic intolerance in severely affected patients.
Candlestick—The Main Mistake of Economy Research in High Frequency Markets
Authors: Stasiak Michał Dominik
Published: October 2020

One of the key problems of researching the high-frequency financial markets is the proper data format. Application of the candlestick representation (or its derivatives such as daily prices, etc.), which is vastly used in economic research, can lead to faulty research results. Yet, this fact is consistently ignored in most economic studies. The following article gives examples of possible consequences of using candlestick representation in modelling and statistical analysis of the financial markets. Emphasis should be placed on the problem of research results being detached from the investing practice, which makes most of the results inapplicable from the investor’s point of view. The article also presents the concept of a binary-temporal representation, which is an alternative to the candlestick representation. Using binary-temporal representation allows for more precise and credible research and for the results to be applied in investment practice.
Spatio-Temporal Relationship between Land Cover and Land Surface Temperature in Urban Areas: A Case Study in Geneva and Paris
Authors: Ge Xu , Mauree Dasaraden , Castello Roberto , Scartezzini Jean-Louis
Published: October 2020

Currently, more than half of the world’s population lives in cities, which leads to major changes in land use and land surface temperature (LST). The associated urban heat island (UHI) effects have multiple impacts on energy consumption and human health. A better understanding of how different land covers affect LST is necessary for mitigating adverse impacts, and supporting urban planning and public health management. This study explores a distance-based, a grid-based and a point-based analysis to investigate the influence of impervious surfaces, green area and waterbodies on LST, from large (distance and grid based analysis with 400 m grids) to smaller (point based analysis with 30 m grids) scale in the two mid-latitude cities of Paris and Geneva. The results at large scale confirm that the highest LST was observed in the city centers. A significantly positive correlation was observed between LST and impervious surface density. An anticorrelation between LST and green area density was observed in Paris. The spatial lag model was used to explore the spatial correlation among LST, NDBI, NDVI and MNDWI on a smaller scale. Inverse correlations between LST and NDVI and MNDWI, respectively, were observed. We conclude that waterbodies display the greatest mitigation on LST and UHI effects both on the large and smaller scale. Green areas play an important role in cooling effects on the smaller scale. An increase of evenly distributed green area and waterbodies in urban areas is suggested to lower LST and mitigate UHI effects.
PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy
Authors: Ma Ding , Zhao Zhigang , Zheng Ye , Guo Renzhong , Zhu Wei
Published: October 2020

Map generalization is a process of reducing the contents of a map or data to properly show a geographic feature(s) at a smaller extent. Over the past few years, the fractal way of thinking has emerged as a new paradigm for map generalization. A geographic feature can be deemed as a fractal given the perspective of scaling, as its rough, irregular, and unsmooth shape inherently holds a striking scaling hierarchy of far more small elements than large ones. The pattern of far more small things than large ones is a de facto heavy tailed distribution. In this paper, we apply the scaling hierarchy for map generalization to polygonal features. To do this, we firstly revisit the scaling hierarchy of a classic fractal: the Koch Snowflake. We then review previous work that used the Douglas–Peuker algorithm, which identifies characteristic points on a line to derive three types of measures that are long-tailed distributed: the baseline length (d), the perpendicular distance to the baseline (x), and the area formed by x and d (area). More importantly, we extend the usage of the three measures to other most popular cartographical generalization methods; i.e., the bend simplify method, Visvalingam–Whyatt method, and hierarchical decomposition method, each of which decomposes any polygon into a set of bends, triangles, or convex hulls as basic geometric units for simplification. The different levels of details of the polygon can then be derived by recursively selecting the head part of geometric units and omitting the tail part using head/tail breaks, which is a new classification scheme for data with a heavy-tailed distribution. Since there are currently few tools with which to readily conduct the polygon simplification from such a fractal perspective, we have developed PolySimp, a tool that integrates the mentioned four algorithms for polygon simplification based on its underlying scaling hierarchy. The British coastline was selected to demonstrate the tool’s usefulness. The developed tool can be expected to showcase the applicability of fractal way of thinking and contribute to the development of map generalization.
Hierarchical Instance Recognition of Individual Roadside Trees in Environmentally Complex Urban Areas from UAV Laser Scanning Point Clouds
Authors: Wang Yongjun , Jiang Tengping , Liu Jing , Li Xiaorui , Liang Chong
Published: October 2020

Individual tree segmentation is essential for many applications in city management and urban ecology. Light Detection and Ranging (LiDAR) system acquires accurate point clouds in a fast and environmentally-friendly manner, which enables single tree detection. However, the large number of object categories and occlusion from nearby objects in complex environment pose great challenges in urban tree inventory, resulting in omission or commission errors. Therefore, this paper addresses these challenges and increases the accuracy of individual tree segmentation by proposing an automated method for instance recognition urban roadside trees. The proposed algorithm was implemented of unmanned aerial vehicles laser scanning (UAV-LS) data. First, an improved filtering algorithm was developed to identify ground and non-ground points. Second, we extracted tree-like objects via labeling on non-ground points using a deep learning model with a few smaller modifications. Unlike only concentrating on the global features in previous method, the proposed method revises a pointwise semantic learning network to capture both the global and local information at multiple scales, significantly avoiding the information loss in local neighborhoods and reducing useless convolutional computations. Afterwards, the semantic representation is fed into a graph-structured optimization model, which obtains globally optimal classification results by constructing a weighted indirect graph and solving the optimization problem with graph-cuts. The segmented tree points were extracted and consolidated through a series of operations, and they were finally recognized by combining graph embedding learning with a structure-aware loss function and a supervoxel-based normalized cut segmentation method. Experimental results on two public datasets demonstrated that our framework achieved better performance in terms of classification accuracy and recognition ratio of tree.
Investigation into Recycled Rubber Aggregates and Steel Wire Fiber for Use in Concrete Subjected to Impact Loading
Authors: Tate Steven M. , Hamid Hiwa F. , Durham Stephan A. , Chorzepa Mi G.
Published: October 2020

This study investigated the potential use of tire derived rubber aggregates, particularly powdered rubber, and recycled steel-wire fibers in concrete subjected to impact loading. The fibers are approximately 0.4 mm in average diameter and 25 mm in length on average. There are two main portions to this study. The first phase of this study involved small-scale batching to investigate the fresh and hardened properties of concrete mixtures with powdered rubber up to 50% replacement of sand volume and recycled steel fibers up to 0.25% by mixture volume. Additional mixtures containing powdered rubber, crumb rubber, and tire chips were evaluated for their mechanical performance. Based on fresh concrete properties, compressive strength, modulus of rigidity, and impact resilience, mixtures were selected for a second investigative phase. In this phase, static and impact testing were performed on two sets of scaled beams. One beam set was produced with concrete containing 40% powdered rubber as a sand replacement and another beam set with a combination mixture incorporating rubber products of varying sizes (10% powdered rubber, 10% crumb rubber, and 10% tire chip) and 0.25% recycled steel fiber. Flexural performance improved initially with the inclusion of powdered rubber but decreased with increasing concentrations. Mixtures including recycled steel fibers at 0.25% outperformed industrial steel fiber mixtures in both flexural strength and impact resistance. For both the static and impact beams with the recycled powdered rubber and steel fibers in the combination demonstrated improved load distribution and load-carrying capacity, acting as a sufficient replacement for industrial steel fiber reinforcement.
Synthesis, Crystal Structures and Thermal Properties of Ammine Barium Borohydrides
Authors: Grinderslev Jakob B. , Amdisen Mads B. , Jensen Torben R.
Published: October 2020

Ammine metal borohydrides show large compositional and structural diversity, and have been proposed as candidates for solid-state ammonia and hydrogen storage as well as fast cationic conductors. Here, we report the synthesis method of ammine barium borohydrides, Ba(BH4)2·xNH3 (x = 1, 2). The two new compounds were investigated with time-resolved temperature-varied in situ synchrotron radiation powder X-ray diffraction, thermal analysis, infrared spectroscopy and photographic analysis. The compound Ba(BH4)2·2NH3 crystallizes in an orthorhombic unit cell with space group symmetry Pnc2, and is isostructural to Sr(BH4)2·2NH3, forming octahedral [Ba(NH3)2(BH4)4] complexes, which are connected into a two-dimensional layered structure, where the layers are interconnected by dihydrogen bonds, N–Hδ+⋯−δH–B. A new structure type is observed for Ba(BH4)2·NH3, which crystallizes in an orthorhombic unit cell with space group symmetry P212121, forming a three-dimensional framework structure of [Ba(NH3)(BH4)6] complexes. The structure is built from distorted hexagonal chains, where NH3 groups form dihydrogen bonds to the nearby BH4−-groups within the chain. Ba(BH4)2·2NH3 is unstable at room temperature and releases NH3 in two subsequent endothermic reactions with maxima at 49 and 117 °C, eventually reforming Ba(BH4)2. We demonstrate that the thermal stability and composition of the gas release for the ammine alkaline earth metal borohydrides can be correlated to the charge density of the metal cation, but are also influenced by other effects.
A Unique Population in a Unique Area: The Alcon Blue Butterfly and Its Specific Parasitoid in the Białowieża Forest
Authors: Dziekańska Izabela , Nowicki Piotr , Pirożnikow Ewa , Sielezniew Marcin
Published: October 2020

Caterpillars of the Alcon blue butterfly Phengaris alcon are initially endophytic and feed inside the flowerheads of Gentiana plants, but complete their development as social parasites in the nests of Myrmica ants, where they are fed by workers. Its specific and complicated ecological requirements make P. alcon a very local, threatened species, sensitive to environmental changes. We investigated an isolated and previously unknown population in an area of high nature value—the Białowieża Forest (NE Poland). Using the mark–release–recapture method we estimated the seasonal number of adults at 1460 individuals, and their density (850/ha) was the highest among all populations using G. pneumonanthe studied so far. The site is also unique due to the presence of the specific parasitoid Ichneumon cf. eumerus, and parasitoids are considered the ultimate indicators of the biodiversity of Phengaris systems. Since 75.5% of P. alcon pupae were infested we could estimate the seasonal population of adult wasps at about 4500 individuals. The high abundance of both P. alcon and its parasitoid may be explained by favorable habitat characteristics, i.e., the strong presence of host plants and the high density of nests of Myrmica scabrinodis, which is the only local host ant of the butterfly.
Comparative Transcriptome Analysis of Two Root-Feeding Grape Phylloxera (D. vitifoliae) Lineages Feeding on a Rootstock and V. vinifera
Authors: Savoi Stefania , Eitle Markus W. , Berger Harald , Curto Manuel , Meimberg Harald , Griesser Michaela , Forneck Astrid
Published: October 2020

Grape phylloxera is one of the most dangerous insect pests for worldwide viticulture. The leaf- and root-galling phylloxerid has been managed by grafting European grapevines onto American rootstock hybrids. Recent reports pinpoint the appearance of host-adapted biotypes, but information about the biomolecular characteristics underlying grape phylloxera biotypisation and its role in host performance is scarce. Using RNA-sequencing, we sequenced the transcriptome of two larval stages: L1 (probing) and L2-3 (feeding) larvae of two root-feeding grape phylloxera lineages feeding on the rootstock Teleki 5C (biotype C) and V. vinifera Riesling (biotype A). In total, 7501 differentially expressed genes (DEGs) were commonly modulated by the two biotypes. For the probing larvae, we found an increased number of DEGs functionally associated with insect chemoreception traits, such as odorant-binding proteins, chemosensory proteins, ionotropic, odorant, and gustatory receptors. The transcriptomic profile of feeding larvae was enriched with DEGs associated with the primary metabolism. Larvae feeding on the tolerant rootstock Teleki 5C exhibited higher numbers of plant defense suppression-associated DEGs than larvae feeding on the susceptible host. Based on the identified DEGs, we discuss their potential role for the compatible grape phylloxera–Vitis interaction belowground. This study was the first to compare the transcriptomes of two grape phylloxera lineages feeding on a tolerant and susceptible host, respectively, and to identify DEGs involved in the molecular interaction with these hosts. Our data provide a source for future studies on host adaptation mechanisms of grape phylloxera and help to elucidate grape phylloxera resistance further.
A User Study of a Wearable System to Enhance Bystanders’ Facial Privacy
Authors: Perez Alfredo J. , Zeadally Sherali , Griffith Scott , Garcia Luis Y. Matos , Mouloud Jaouad A.
Published: October 2020

The privacy of users and information are becoming increasingly important with the growth and pervasive use of mobile devices such as wearables, mobile phones, drones, and Internet of Things (IoT) devices. Today many of these mobile devices are equipped with cameras which enable users to take pictures and record videos anytime they need to do so. In many such cases, bystanders’ privacy is not a concern, and as a result, audio and video of bystanders are often captured without their consent. We present results from a user study in which 21 participants were asked to use a wearable system called FacePET developed to enhance bystanders’ facial privacy by providing a way for bystanders to protect their own privacy rather than relying on external systems for protection. While past works in the literature focused on privacy perceptions of bystanders when photographed in public/shared spaces, there has not been research with a focus on user perceptions of bystander-based wearable devices to enhance privacy. Thus, in this work, we focus on user perceptions of the FacePET device and/or similar wearables to enhance bystanders’ facial privacy. In our study, we found that 16 participants would use FacePET or similar devices to enhance their facial privacy, and 17 participants agreed that if smart glasses had features to conceal users’ identities, it would allow them to become more popular.
Sentiment Analysis on Twitter Data of World Cup Soccer Tournament Using Machine Learning
Authors: Patel Ravikumar , Passi Kalpdrum
Published: October 2020

In the derived approach, an analysis is performed on Twitter data for World Cup soccer 2014 held in Brazil to detect the sentiment of the people throughout the world using machine learning techniques. By filtering and analyzing the data using natural language processing techniques, sentiment polarity was calculated based on the emotion words detected in the user tweets. The dataset is normalized to be used by machine learning algorithms and prepared using natural language processing techniques like word tokenization, stemming and lemmatization, part-of-speech (POS) tagger, name entity recognition (NER), and parser to extract emotions for the textual data from each tweet. This approach is implemented using Python programming language and Natural Language Toolkit (NLTK). A derived algorithm extracts emotional words using WordNet with its POS (part-of-speech) for the word in a sentence that has a meaning in the current context, and is assigned sentiment polarity using the SentiWordNet dictionary or using a lexicon-based method. The resultant polarity assigned is further analyzed using naïve Bayes, support vector machine (SVM), K-nearest neighbor (KNN), and random forest machine learning algorithms and visualized on the Weka platform. Naïve Bayes gives the best accuracy of 88.17% whereas random forest gives the best area under the receiver operating characteristics curve (AUC) of 0.97.
Two-Stage Alignment of FIB-SEM Images of Rock Samples
Authors: Reimers Iryna , Safonov Ilia , Kornilov Anton , Yakimchuk Ivan
Published: October 2020

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography provides a stack of images that represent serial slices of the sample. These images are displaced relatively to each other, and an alignment procedure is required. Traditional methods for alignment of a 3D image are based on a comparison of two adjacent slices. However, such algorithms are easily confused by anisotropy in the sample structure or even experiment geometry in the case of porous media. This may lead to significant distortions in the pore space geometry, if there are no stable fiducial marks in the frame. In this paper, we propose a new method, which meaningfully extends existing alignment procedures. Our technique allows the correction of random misalignments between slices and, at the same time, preserves the overall geometrical structure of the specimen. We consider displacements produced by existing alignment algorithms as a signal and decompose it into low and high-frequency components. Final transformations exclude slow variations and contain only high frequency variations that represent random shifts that need to be corrected. The proposed algorithm can operate with not only translations but also with arbitrary affine transformations. We demonstrate the performance of our approach on a synthetic dataset and two real FIB-SEM images of natural rock.
Convergent and Concurrent Validity between Clinical Recovery and Personal-Civic Recovery in Mental Health
Authors: Pelletier Jean-François , Davidson Larry , Giguère Charles-Édouard , Franck Nicolas , Bordet Jonathan , Rowe Michael
Published: October 2020

Several instruments have been developed by clinicians and academics to assess clinical recovery. Based on their life narratives, measurement tools have also been developed and validated through participatory research programs by persons living with mental health problems or illnesses to assess personal recovery. The main objective of this project is to explore possible correlations between clinical recovery, personal recovery, and citizenship by using patient-reported outcome measures. All study participants are currently being treated and monitored after having been diagnosed either with (a) psychotic disorders or (b) anxiety and mood disorders. They have completed questionnaires for clinical evaluation purposes (clinical recovery) will further complete the Recovery Assessment Scale and Citizenship Measure (personal-civic recovery composite index). Descriptive and statistical analyses will be performed to determine internal consistency for each of the subscales, and assess convergent-concurrent validity between clinical recovery, citizenship and personal recovery. Recovery-oriented mental health care and services are particularly recognizable by the presence of Peer Support Workers, who are persons with lived experience of recovery. Upon training, they can personify personalized mental health care and services, that is to say services that are centered on the person’s recovery project and not only on their symptoms. Data from our overall research strategy will lay the ground for the evaluation of the effects of the intervention of Peer Support Workers on clinical recovery, citizenship and personal recovery.
Tools of Information and Communication Technologies in Ecological Marketing under Conditions of Sustainable Development in Industrial Regions (Through Examples of Poland and Ukraine)
Authors: Kuzior Aleksandra , Lobanova Alla
Published: October 2020

This scientific work analyzes the current state and problems of implementing the concept of sustainable development in industrial regions, in particular, in Poland and Ukraine. Emphasis is placed on slowing down the implementation of the main provisions of this doctrine, in particular, the violation of environmental requirements and non-compliance with ecological standards by industrial enterprises. The aim of the article is to find effective innovative tools for intensifying the process of implementing the strategy of sustainable development in industrial regions. The paper uses theoretical methods—analysis and synthesis, formalization, hypothetical-deductive modeling, mental modeling, systematization and generalization—as well as empirical: observation, description and comparison. The main result of the work is the substantiation of the scientific idea that the implementation of a sustainable development strategy in industrial regions is possible by intensifying the process of ecological marketing through the use of new information and communication technologies (ICT) and their innovative tools—methodologies, digital systems, the Internet, cloud technologies, and systems of product design, manufacture and sale—due to accelerated communication links. The authors’ approach to the development of the mechanism of creation and functioning of the single information space (field) of the ecological marketing of the industrial region is offered in this work, and also, the classification of modern ICT and their tools, which it is expedient to use in this mechanism, is carried out. Their purpose and the expected results from the introduction of ecological products for market research, the development of ecological technologies for the life cycles of ecological products and, thus, the impact on the acceleration of sustainable development in industrial regions are determined.
Urban Planning and Design for Building Neighborhood Resilience to Climate Change
Authors: Rędzińska Katarzyna , Piotrkowska Monika
Published: October 2020

The aim of the paper was to present the procedure of building neighborhood resilience to climate threats, embedded in planning (from the strategic to local level) and design process and focused on usage of natural adaptive potential. The presented approach encompasses: (1) the strategic identification of focal areas in terms of climate adaptation needs, (2) comprehensive diagnosis of local ecological vulnerability and natural adaptive potential to build adaptive capacity, and (3) incorporation of natural adaptive potential through an identified set of planning and design tools. For diagnosis and strategic environmental impact assessment, the multicriteria analysis has been elaborated. The described procedure is applied to the City of Warsaw on the strategic level, by elaboration of the ranking of districts in terms of priority to take adaptation actions based on climatic threats, demographic vulnerability, and assessment of Warsaw Green Infrastructure potential. For further analysis at the planning and design stage, the district with the most urgent adaptation needs has been chosen, and within its borders, two neighborhoods (existing and planned one) with diagnosed ecological sensitivity were selected. Both case studies were analyzed in terms of environmental conditions, urban structure, and planning provisions. It enabled identification of existing natural adaptive potential and assessment of its use. As a result, propositions for enhancing neighborhood resilience to climate change were suggested.
The Status Quo of the Criminal Accountability for Marine Illegal Fishing in China: From the Perspective of Judgment Analysis
Authors: Feng Li , He Peipei , Zheng Chenghui , Chen Pei
Published: October 2020

Over the past few years, China’s marine economy has been vigorously booming, while strong measures have been equally undertaken to ensure superior quality of the marine environment. However, the country is still suffering illegal fishing problems, which hinder the marine ecological environment and fishery resources from reaching sustainable development both internally and globally. To this end, the Chinese government has ratified a series of legal documents to provide the basis for judicial departments to hold individuals and groups responsible for practicing illegal fishing at sea. Although the measures have indeed performed well in some instances, a number of legal obstacles remain to be fixed. In this article, to realize the status quo of the control of maritime illegal fishing in China, all the criminal judgments relevant to illegal fishing at sea from 2014 were collected and analyzed not only qualitatively but also quantitatively, through which the existing problems of accountability for illegal fishing at sea in China were summarized. In addition, a number of related studies were examined and in-depth interviews were organized to clarify the main reasons for these problems and propose some necessary solutions. It is believed that our findings would not only help to improve the control of maritime illegal fishing and boost the marine ecological environment protection in China, but also to establish a possible reference for other countries in the world.
Novel Integration of CAPP in a G-Code Generation Module Using Macro Programming for CNC Application
Authors: Nguyen Trung Kien , Phung Lan Xuan , Bui Ngoc-Tam
Published: October 2020

In the modern manufacturing industry, the role of computer-aided process planning (CAPP) is becoming increasingly crucial. Through the application of new technologies, experience, and intelligence, CAPP is contributing to the automation of manufacturing processes. In this article, the integration of a proposed CAPP system that is named as BKCAPP and G-code generation module provides a completed CAD–CAPP–CNC system that does not involve any manual processing in the CAM modules. The BKCAPP system is capable of automatically performing machining feature and operation recognition processes from design features in three-dimensional (3D) solid models, incorporating technical requirements such as the surface roughness, geometric dimensions, and tolerance in order to provide process planning for machining processes, including information on the machine tools, cutting tools, machining conditions, and operation sequences. G-code programs based on macro programming are automatically generated by the G-code generation module on the basis of the basic information for the machining features, such as the contour shape, basic dimensions, and cutting information obtained from BKCAPP. The G-code generation module can be applied to standard machining features, such as faces, pockets, bosses, slots, holes, and contours. This novel integration approach produces a practical CAPP method enabling end users to generate operation consequences and G-code files and to customize specific cutting tools and machine tool data. In this paper, a machining part consisting of basic machining features was used in order to describe the method and verify its implementation.
TOPSIS Method Based on Complex Spherical Fuzzy Sets with Bonferroni Mean Operators
Authors: Ali Zeeshan , Mahmood Tahir , Yang Miin-Shen
Published: October 2020

The theory of complex spherical fuzzy sets (CSFSs) is a mixture of two theories, i.e., complex fuzzy sets (CFSs) and spherical fuzzy sets (SFSs), to cope with uncertain and unreliable information in realistic decision-making situations. CSFSs contain three grades in the form of polar coordinates, e.g., truth, abstinence, and falsity, belonging to a unit disc in a complex plane, with a condition that the sum of squares of the real part of the truth, abstinence, and falsity grades is not exceeded by a unit interval. In this paper, we first consider some properties and their operational laws of CSFSs. Additionally, based on CSFSs, the complex spherical fuzzy Bonferroni mean (CSFBM) and complex spherical fuzzy weighted Bonferroni mean (CSFWBM) operators are proposed. The special cases of the proposed operators are also discussed. A multi-attribute decision making (MADM) problem was chosen to be resolved based on the proposed CSFBM and CSFWBM operators. We then propose the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on CSFSs (CSFS-TOPSIS). An application example is given to delineate the proposed methods and a close examination is undertaken. The advantages and comparative analysis of the proposed approaches are also presented.