bluuebunny/crossref_metadata_2025 huggingface dataset:
Existence of Solutions for Nonlinear Fractional Differential Equations and Inclusions Depending on Lower-Order Fractional Derivatives
Authors: Muthaiah Subramanian , Baleanu Dumitru
Published: April 2020

This article deals with the solutions of the existence and uniqueness for a new class of boundary value problems (BVPs) involving nonlinear fractional differential equations (FDEs), inclusions, and boundary conditions involving the generalized fractional integral. The nonlinearity relies on the unknown function and its fractional derivatives in the lower order. We use fixed-point theorems with single-valued and multi-valued maps to obtain the desired results, through the support of illustrations, the main results are well explained. We also address some variants of the problem.
Footprints of a Singular 22-Nucleotide RNA Ring at the Origin of Life
Authors: Demongeot Jacques , Henrion-Caude Alexandra
Published: April 2020

(1) Background: Previous experimental observations and theoretical hypotheses have been providing insight into a hypothetical world where an RNA hairpin or ring may have debuted as the primary informational and functional molecule. We propose a model revisiting the architecture of RNA-peptide interactions at the origin of life through the evolutionary dynamics of RNA populations. (2) Methods: By performing a step-by-step computation of the smallest possible hairpin/ring RNA sequences compatible with building up a variety of peptides of the primitive network, we inferred the sequence of a singular docosameric RNA molecule, we call the ALPHA sequence. Then, we searched for any relics of the peptides made from ALPHA in sequences deposited in the different public databases. (3) Results: Sequence matching between ALPHA and sequences from organisms among the earliest forms of life on Earth were found at high statistical relevance. We hypothesize that the frequency of appearance of relics from ALPHA sequence in present genomes has a functional necessity. (4) Conclusions: Given the fitness of ALPHA as a supportive sequence of the framework of all existing theories, and the evolution of Archaea and giant viruses, it is anticipated that the unique properties of this singular archetypal ALPHA sequence should prove useful as a model matrix for future applications, ranging from synthetic biology to DNA computing.
Does Medication-Related Osteonecrosis of the Jaw Influence the Quality of Life of Cancer Patients?
Authors: Tenore Gianluca , Mohsen Ahmed , Rossi Antonella Francesca , Palaia Gaspare , Rocchetti Federica , Cassoni Andrea , Valentini Valentino , Ottolenghi Livia , Polimeni Antonella , Romeo Umberto
Published: April 2020

The aim of this study is to observe the influence of Medication-Related Osteonecrosis of the Jaw (MRONJ) on the physical and mental conditions of cancer patients using a Quality of Life (QoL) questionnaire during regular dental practice measures. Twenty cancer patients (8 males and 12 females) with established MRONJ were enrolled in the “MoMax” (Oral Medicine and Maxillofacial) project of the Department of Oral Sciences and Maxillofacial Surgery at “Sapienza” University of Rome, and were included in the study. The 12-item Short Form Survey was used to evaluate the QoL. Statistical analysis revealed a significant difference for Mental Component Summary (MCS) scores based on age (p = 0.018). The regression analysis revealed that the Physical Component Summary (PCS) scores were negatively influenced by the anti-resorptive medication duration (p = 0.031 and β = −1.137). No significant differences were observed with the other variables considered. The QoL of cancer patients is generally deteriorated and MRONJ may cause a further negative impact. This study highlights the possible need to include psychosocial and physical evaluations in the management process of MRONJ in cancer patients.
The Minimal Effect of Linker Length for Fatty Acid Conjugation to a Small Protein on the Serum Half-Life Extension
Authors: Cho Jinhwan , Park Junyong , Tae Giyoong , Jin Mi Sun , Kwon Inchan
Published: April 2020

Conjugation of serum albumin or one of its ligands (such as fatty acid) has been an effective strategy to prolong the serum half-lives of drugs via neonatal Fc receptor (FcRn)–mediated recycling of albumin. So far, fatty acid (FA) has been effective in prolonging the serum half-lives for therapeutic peptides and small proteins, but not for large therapeutic proteins. Very recently, it was reported a large protein conjugated to FA competes with the binding of FcRn with serum albumin, leading to limited serum half-life extension, because primary FA binding sites in serum albumin partially overlap with FcRn binding sites. In order to prevent such competition, longer linkers between FA and the large proteins were required. Herein, we hypothesized that small proteins do not cause substantial competition for FcRn binding to albumin, resulting in the extended serum half-life. Using a small protein (28 kDa), we investigated whether the intramolecular distance in FA-protein conjugate affects the FcRn binding with albumin and serum half-life using linkers with varying lengths. Unlike with the FA-conjugated large protein, all FA-conjugated small proteins with different linkers exhibited comparable the FcRn binding to albumin and extended serum half-life.
A Novel Method to Identify Autoantibodies against Putative Target Proteins in Serum from beta-Thalassemia Major: A Pilot Study
Authors: Sumera Afshan , Anuar Nur Diana , Radhakrishnan Ammu Kutty , Ibrahim Hishamshah , Rutt Nurul H. , Ismail Nur Hafiza , Tan Ti-Myen , Baba Abdul Aziz
Published: April 2020

Abnormal immune reactivity in patients with beta-thalassemia (beta-thal) major can be associated with poor prognosis. Immunome protein-array analysis represents a powerful approach to identify novel biomarkers. The Sengenics Immunome Protein Array platform was used for high-throughput quantification of autoantibodies in 12 serum samples collected from nine beta-thal major patients and three non-thalassemia controls, which were run together with two pooled normal sera (Sengenics Internal QC samples). To obtain more accurate and reliable results, the evaluation of the biological relevance of the shortlisted biomarkers was analyzed using an Open Target Platform online database. Elevated autoantibodies directed against 23 autoantigens on the immunome array were identified and analyzed using a penetrance fold change-based bioinformatics method. Understanding the autoantibody profile of beta-thal major patients would help to further understand the pathogenesis of the disease. The identified autoantigens may serve as potential biomarkers for the prognosis of beta-thal major.
Chitosan Extraction from Goliathus orientalis Moser, 1909: Characterization and Comparison with Commercially Available Chitosan
Authors: Fournier Pauline , Szczepanski Caroline R. , Godeau René-Paul , Godeau Guilhem
Published: April 2020

Chitosan is a polymer obtained by deacetylation of chitin, and chitin is one of the major components of the arthropod cuticle. Chitin and chitosan are both polysaccharides and are considered to be an interesting class of biosourced materials. This is evident as chitosan has already demonstrated utility in various applications in both industrial and biomedical domains. In the present work, we study the possibility to extract chitin and prepare chitosan from the Goliath beetle Goliathus orientalis Moser. The presented work includes description of this process and observation of the macroscopic and microscopic variations that occur in the specimen during the treatment. The prepared chitosan is characterized and compared with commercially available chitosan using infrared and thermogravimetric analysis. The deacetylation degree of prepared chitosan is also evaluated and compared with commercially available shrimp chitosan.
Early-Stage Temperature Gradients in Glazed Spandrels Due to Aesthetical Features to Support Design for Thermal Shock
Authors: Montali Jacopo , Laffranchini Luciano , Micono Carlo
Published: April 2020

Investigating thermal breakage of glass panes requires careful analysis of the environmental boundary conditions to determine the expected thermal gradient between the sunlit and shaded parts of the glass. This is particularly critical for glazed spandrels, where an opaque posterior insulation layer normally increases the system’s temperatures. The choice of the spandrel system should also be evaluated against the aesthetical impression that it conveys. The aim of this study is to understand how early design factors, such as aesthetical features like color, are driving temperature gradients in the glazed pane to design for thermal shock. Multiple finite-differences analyses in a quasi-static regime for non-ventilated, single glazed spandrels were conducted in three locations (London, New York and Mumbai). Results were then analyzed via a general linear model in SAS 9.4 and Tuckey post hoc analysis. It was shown that a low absorptance of the back insulation (e.g., light color) can lead to a wide range of possible temperature gradients depending on the glass transparency, with higher values of the thermally induced temperature gradients for more opaque glasses. Conversely, a high absorptance of the insulation layer leads to moderate values of glass temperature gradients, which are not substantially sensitive to the effect of the glass transparency.
Power Cycling and Reliability Testing of Epoxy-Based Graphene Thermal Interface Materials
Authors: Lewis Jacob S. , Perrier Timothy , Mohammadzadeh Amirmahdi , Kargar Fariborz , Balandin Alexander A.
Published: April 2020

We report on the lifespan evolution of thermal diffusivity and thermal conductivity in curing epoxy-based thermal interface materials with graphene fillers. The performance and reliability of graphene composites have been investigated in up to 500 power cycling measurements. The tested composites were prepared with an epoxy resin base and randomly oriented fillers consisting of a mixture of few-layer and single-layer graphene. The power cycling treatment procedure was conducted with a custom-built setup, while the thermal characteristics were determined using the “laser flash” method. The thermal conductivity and thermal diffusivity of these composites do not degrade but instead improve with power cycling. Among all tested filled samples with different graphene loading fractions, an enhancement in the thermal conductivity values of 15% to 25% has been observed. The obtained results suggest that epoxy-based thermal interface materials with graphene fillers undergo an interesting and little-studied intrinsic performance enhancement, which can have important implications for the development of next-generation thermal interface materials.
Overview of Recent Advances in Immobilisation Techniques for Phenol Oxidases in Solution
Authors: Ndlovu Thandanani , Ba Sidy , Malinga Soraya P
Published: April 2020

Over the past two decades, phenol oxidases, particularly laccases and tyrosinases, have been extensively used for the removal of numerous pollutants in wastewaters due to their broad substrate specificity and their ability to use readily accessible molecular oxygen as the essential cofactor. As for other enzymes, immobilisation of laccases and tyrosinases has been shown to improve the performance and efficiency of the biocatalysts in solution. Several reviews have addressed the enzyme immobilisation techniques and the application of phenol oxidases to decontaminate wastewaters. This paper offers an overview of the recent publications, mainly from 2012 onwards, on the various immobilisation techniques applied to laccases and tyrosinases to induce and/or increase the performance of the biocatalysts. In this paper, the emphasis is on the efficiencies achieved, in terms of structural modifications, stability and resistance to extreme conditions (pH, temperature, inhibitors, etc.), reactivity, reusability, and broad substrate specificity, particularly for application in bioremediation processes. The advantages and disadvantages of several enzyme immobilisation techniques are also discussed. The relevance and effectiveness of the immobilisation techniques with respect to wastewater decontamination are critically assessed. A perspective on the future directions for large-scale application of the phenol oxidases in immobilised forms is provided.
How Complexity and Uncertainty Grew with Algorithmic Trading
Authors: Hilbert Martin , Darmon David
Published: April 2020

The machine-learning paradigm promises traders to reduce uncertainty through better predictions done by ever more complex algorithms. We ask about detectable results of both uncertainty and complexity at the aggregated market level. We analyzed almost one billion trades of eight currency pairs (2007–2017) and show that increased algorithmic trading is associated with more complex subsequences and more predictable structures in bid-ask spreads. However, algorithmic involvement is also associated with more future uncertainty, which seems contradictory, at first sight. On the micro-level, traders employ algorithms to reduce their local uncertainty by creating more complex algorithmic patterns. This entails more predictable structure and more complexity. On the macro-level, the increased overall complexity implies more combinatorial possibilities, and therefore, more uncertainty about the future. The chain rule of entropy reveals that uncertainty has been reduced when trading on the level of the fourth digit behind the dollar, while new uncertainty started to arise at the fifth digit behind the dollar (aka ‘pip-trading’). In short, our information theoretic analysis helps us to clarify that the seeming contradiction between decreased uncertainty on the micro-level and increased uncertainty on the macro-level is the result of the inherent relationship between complexity and uncertainty.
Knudsen Number Effects on Two-Dimensional Rayleigh–Taylor Instability in Compressible Fluid: Based on a Discrete Boltzmann Method
Authors: Ye Haiyan , Lai Huilin , Li Demei , Gan Yanbiao , Lin Chuandong , Chen Lu , Xu Aiguo
Published: April 2020

Based on the framework of our previous work [H.L. Lai et al., Phys. Rev. E, 94, 023106 (2016)], we continue to study the effects of Knudsen number on two-dimensional Rayleigh–Taylor (RT) instability in compressible fluid via the discrete Boltzmann method. It is found that the Knudsen number effects strongly inhibit the RT instability but always enormously strengthen both the global hydrodynamic non-equilibrium (HNE) and thermodynamic non-equilibrium (TNE) effects. Moreover, when Knudsen number increases, the Kelvin–Helmholtz instability induced by the development of the RT instability is difficult to sufficiently develop in the later stage. Different from the traditional computational fluid dynamics, the discrete Boltzmann method further presents a wealth of non-equilibrium information. Specifically, the two-dimensional TNE quantities demonstrate that, far from the disturbance interface, the value of TNE strength is basically zero; the TNE effects are mainly concentrated on both sides of the interface, which is closely related to the gradient of macroscopic quantities. The global TNE first decreases then increases with evolution. The relevant physical mechanisms are analyzed and discussed.
Assessing Gender Gaps in Educational Provision, Research and Employment Opportunities in the Transport Sector at the European Level
Authors: Pirra Miriam , Carboni Angela , Diana Marco
Published: April 2020

Serious gaps are found when evaluating the recognition and inclusion of gender aspects in transport strategies, research and innovation. Similar issues can be spotted in the transport labor market, where only 22% of workers are women at the European level. The roots of these limitations are in the low participation of women in Science, Technology, Engineering and Maths (STEM) studies and, therefore, in the traditionally male-dominated transport field occupations. Stemming from the European project TInnGO, the current paper proposes a descriptive analysis to evaluate the gender gaps in educational provision and research in ten European countries. Specific indicators, such as percentages in the gender composition or the presence of university courses dealing with mobility and transport, have been defined and their availability in different countries is verified. In addition, a desktop review of practices for encouraging and supporting women in STEM studies is operated, underling characteristics such as the kind of initiative, the methods and tools used, the target group or the type of promoter. The results of this activity show that a wide network of associations and mentoring operates in various European nations, mostly targeting secondary school students, trying to make females aware of their potentialities in a deeply gender-biased field like the STEM one.
Measuring Traffic Volumes Using an Autoencoder with No Need to Tag Images with Labels
Authors: Roh Seungbin , Shin Johyun , Sohn Keemin
Published: April 2020

Almost all vision technologies that are used to measure traffic volume use a two-step procedure that involves tracking and detecting. Object detection algorithms such as YOLO and Fast-RCNN have been successfully applied to detecting vehicles. The tracking of vehicles requires an additional algorithm that can trace the vehicles that appear in a previous video frame to their appearance in a subsequent frame. This two-step algorithm prevails in the field but requires substantial computation resources for training, testing, and evaluation. The present study devised a simpler algorithm based on an autoencoder that requires no labeled data for training. An autoencoder was trained on the pixel intensities of a virtual line placed on images in an unsupervised manner. The last hidden node of the former encoding portion of the autoencoder generates a scalar signal that can be used to judge whether a vehicle is passing. A cycle-consistent generative adversarial network (CycleGAN) was used to transform an original input photo of complex vehicle images and backgrounds into a simple illustration input image that enhances the performance of the autoencoder in judging the presence of a vehicle. The proposed model is much lighter and faster than a YOLO-based model, and accuracy of the proposed model is equivalent to, or better than, a YOLO-based model. In measuring traffic volumes, the proposed approach turned out to be robust in terms of both accuracy and efficiency.
Characterization Circuit, Gate Driver and Fixture for Wide-Bandgap Power Semiconductor Device Testing
Authors: Saadeh Osama , Al-Hmoud Ahmad , Dalala Zakariya
Published: April 2020

The world is currently experiencing major advancement in the electrification of both the industrial and commercial sectors. This is part of an effort to reduce reliance on combustible fuels, reduce emissions, integrate renewable energy systems and increase efficiency. Due to the complexity of modern circuits and systems, any circuit’s design should start with proper simulation and device selection, to reduce overall cost and time of prototyping, both of which require accurate and thorough device characterization. Wide bandgap (WBG) power semiconductor devices offer superior characteristics over conventional devices, including faster switching speeds, higher breakdown voltage, lower losses, and higher operating temperature. These properties call for special test circuits and procedures for accurate characterization. In this work, custom characterization circuits and fixtures, suitable for WBG devices are designed, tested, and described. The circuits measure several of the main characteristics of voltage controlled WBG power switches. Different technology devices were tested and characterized.
Understanding of Polarization-Induced Threshold Voltage Shift in Ferroelectric-Gated Field Effect Transistor for Neuromorphic Applications
Authors: Moon Seungjun , Shin Jaemin , Shin Changhwan
Published: April 2020

A ferroelectric-gated fin-shaped field effect transistor (Fe-FinFET) is fabricated by connecting a Pb(Zr0.2Ti0.8)O3-based ferroelectric capacitor into the gate electrode of FinFET. The ferroelectric capacitor shows coercive voltages of approximately −1.5 V and 2.25 V. The polarization-induced threshold voltage shift in the Fe-FinFET is investigated by regulating the gate voltage sweep range. When the maximum positive gate to source voltage is varied from 4 V to 2 V with a fixed starting negative gate to source voltage, the threshold voltage during the backward sweep is increased from approximately −0.60 V to 1.04 V. In the case of starting negative gate to source voltage variation from −4 V to −0.5 V with a fixed maximum positive gate to source voltage of 4 V, the threshold voltage during the forward sweep is decreased from 1.66 V to 0.87 V. Those results can be elucidated with polarization domain states. Lastly, it is observed that the threshold voltage is mostly increased/decreased when the positive/negative gate voltage sweep range is smaller/larger than the positive/negative coercive voltage, respectively.
An Efficient Resource Allocation for Massive MTC in NOMA-OFDMA Based Cellular Networks
Authors: Wu Yali , Zhang Shuang , Liu Zhengxuan , Liu Xiaoshuang , Li Jianfeng
Published: April 2020

To alleviate random access congestion and support massive-connections with less energy consumption for machine-type communications (MTC) in the 5G cellular network, we propose an efficient resource allocation for massive MTC (mMTC) with hybrid non-orthogonal multiple access (NOMA)-orthogonal frequency division multiple access (OFDMA). First, a hybrid multiple access scheme, including the NOMA-based congestion-alleviating access scheme (NCAS) and OFDMA-based congestion-alleviating access scheme (OCAS), is proposed, in which the NOMA based devices coexist with OFDMA based ones. Then, aiming at maximizing the system access capacity, a traffic-aware resource blocks (RBs) allocation is investigated to optimize RBs allocation for preamble transmission and data packets transmission, as well as to optimize the RBs allocation between NCAS and OCAS for the RBs usage efficiency improvement. Next, aiming at the problem of high computational complexity and improving energy efficiency in hybrid NOMA-OFDMA based cellular M2M communications, this paper proposes an improved low complexity power allocation algorithm. The feasibility conditions of power allocation solution under the maximum transmit power constraints and quality of service (QoS) requirements of the devices is investigated. The original non-convex optimization problem is solved under the feasibility conditions by two iterative algorithms. Finally, a device clustering scheme is proposed based on the channel gain difference and feasible condition of power allocation solution, by which NOMA based devices and OFDMA based devices can be determined. Simulation results show that compared with non-orthogonal random access and transmission (NORA-DT), the proposed resource allocation scheme for hybrid NOMA-OFDMA systems can efficiently improve the performance of access capacity and energy efficiency.
Millimeter Wave Propagation in Long Corridors and Tunnels—Theoretical Model and Experimental Verification
Authors: Rapaport Liat , Pinhasi Gad A. , Pinhasi Yosef
Published: April 2020

The development of the Fifth-Generation (5G) of cellular communications considers bands in millimeter waves (MMW) for indoor, short-range links. The propagation of MMW is affected by atmospheric and weather conditions, specular reflections from surfaces, and the directivity of the antennas. The short wavelength enables utilization of a quasi-optical propagation model for the description of indoor multi-path scenarios. A study of MMW propagation in tunnels, long corridors, or canyons is carried out using ray-tracing to evaluate the link budget and group delay. The analysis considers radiation patterns of both transmitting and receiving antennas, deriving a criterion for the number of dominating rays. Error analysis demonstrates the convergence of the method, while using a finite number of reflected rays. Experiments in a small-scale tunnel model demonstrate the accuracy of the analysis.
A Single Error Correcting Code with One-Step Group Partitioned Decoding Based on Shared Majority-Vote
Authors: Das Abhishek , Touba Nur A.
Published: April 2020

Technology scaling has led to an increase in density and capacity of on-chip caches. This has enabled higher throughput by enabling more low latency memory transfers. With the reduction in size of SRAMs and development of emerging technologies, e.g., STT-MRAM, for on-chip cache memories, reliability of such memories becomes a major concern. Traditional error correcting codes, e.g., Hamming codes and orthogonal Latin square codes, either suffer from high decoding latency, which leads to lower overall throughput, or high memory overhead. In this paper, a new single error correcting code based on a shared majority voting logic is presented. The proposed codes trade off decoding latency in order to improve the memory overhead posed by orthogonal Latin square codes. A latency optimization technique is also proposed which lowers the decoding latency by incurring a slight memory overhead. It is shown that the proposed codes achieve better redundancy compared to orthogonal Latin square codes. The proposed codes are also shown to achieve lower decoding latency compared to Hamming codes. Thus, the proposed codes achieve a balanced trade-off between memory overhead and decoding latency, which makes them highly suitable for on-chip cache memories which have stringent throughput and memory overhead constraints.
Potential of Pressure Sensor Based Mass Estimation Methods for Electric Buses
Authors: Spaeth Utz , Fechtner Heiko , Weisbach Michele , Schmuelling Benedikt
Published: April 2020

One approach to improve the economic efficiency of trolleybuses in the so-called BOB Project in the German town of Solingen is to use them as mobile energy storages in a smart grid. To achieve this, reliable information on available energy is essential, which in turn needs to be derived from a precise range calculator. As shown in this article, vehicle mass is a strong influencing factor, especially in urban traffic. Depending on passenger volume, the total mass and range of the bus varies by about 30 percent. The currently available mass on the bus fluctuates by more than 2 tons for constant payloads, and there is no proven solution for a more accurate mass estimation for buses in public passenger transportation. Therefore, this article presents a viable methodology to detect changes in payload, using high precision pressure sensors on the bus’s tires and air suspensions. These mass inducted pressure changes are extracted from the measurement data, using a filter to be later converted back into the corresponding masses. As the article will show, both approaches have their respective advantages and disadvantages, but have high potential and should therefore be investigated further.
A Compact Dual-Mode Bandpass Filter with High Out-of-Band Suppression Using a Stub-Loaded Resonator Based on the GaAs IPD Process
Authors: Zhang Wei , Yao Zhao , Zhang Jie , Kim Eun Seong , Kim Nam Young
Published: April 2020

In this letter, a compact dual-mode bandpass filter (BPF) with an ultra-wide stopband that employs two folded open-loop resonators (FOLRs) and stub-loaded resonators (SLRs) is proposed. The dual-mode resonators are optimized by loading two SLRs onto the folded open-loop resonators, and this process is analyzed using the dual-mode theory. To miniaturize the device size and increase chip performance, the proposed BPF is fabricated by a III–V compound semiconductor-fabrication process using a high-performance GaAs substrate based on the integration passivation device (IPD) fabrication process. A compact dual-mode BPF with low insertion loss and high return loss is designed and fabricated. Two extra transmission zeros (TZs) located in the high-frequency range increase the wide stopband, and the two TZs near the passband result in a higher selectivity. A resonant frequency centered at 7.45 GHz with an insertion loss of −1.21 dB and a measured return loss of higher than −23.53 dB and 3 dB fractional bandwidths of 5.8% are achieved. The stopband can be suppressed up to 20 GHz owing to the two tunable TZs resulting in higher selectivity and wideband rejection. The size of the filter was drastically optimized using a simplified architecture of two FOLRs and SLRs.
Attention-LSTM-Attention Model for Speech Emotion Recognition and Analysis of IEMOCAP Database
Authors: Yu Yeonguk , Kim Yoon-Joong
Published: April 2020

We propose a speech-emotion recognition (SER) model with an “attention-long Long Short-Term Memory (LSTM)-attention” component to combine IS09, a commonly used feature for SER, and mel spectrogram, and we analyze the reliability problem of the interactive emotional dyadic motion capture (IEMOCAP) database. The attention mechanism of the model focuses on emotion-related elements of the IS09 and mel spectrogram feature and the emotion-related duration from the time of the feature. Thus, the model extracts emotion information from a given speech signal. The proposed model for the baseline study achieved a weighted accuracy (WA) of 68% for the improvised dataset of IEMOCAP. However, the WA of the proposed model of the main study and modified models could not achieve more than 68% in the improvised dataset. This is because of the reliability limit of the IEMOCAP dataset. A more reliable dataset is required for a more accurate evaluation of the model’s performance. Therefore, in this study, we reconstructed a more reliable dataset based on the labeling results provided by IEMOCAP. The experimental results of the model for the more reliable dataset confirmed a WA of 73%.
θ-Sensitive k-Anonymity: An Anonymization Model for IoT based Electronic Health Records
Authors: Khan Razaullah , Tao Xiaofeng , Anjum Adeel , Kanwal Tehsin , Malik Saif , Khan Abid , Rehman Waheed , Maple Carsten
Published: April 2020

The Internet of Things (IoT) is an exponentially growing emerging technology, which is implemented in the digitization of Electronic Health Records (EHR). The application of IoT is used to collect the patient’s data and the data holders and then to publish these data. However, the data collected through the IoT-based devices are vulnerable to information leakage and are a potential privacy threat. Therefore, there is a need to implement privacy protection methods to prevent individual record identification in EHR. Significant research contributions exist e.g., p+-sensitive k-anonymity and balanced p+-sensitive k-anonymity for implementing privacy protection in EHR. However, these models have certain privacy vulnerabilities, which are identified in this paper with two new types of attack: the sensitive variance attack and categorical similarity attack. A mitigation solution, the θ -sensitive k-anonymity privacy model, is proposed to prevent the mentioned attacks. The proposed model works effectively for all k-anonymous size groups and can prevent sensitive variance, categorical similarity, and homogeneity attacks by creating more diverse k-anonymous groups. Furthermore, we formally modeled and analyzed the base and the proposed privacy models to show the invalidation of the base and applicability of the proposed work. Experiments show that our proposed model outperforms the others in terms of privacy security (14.64%).
Bark Stripping by Deer Was More Intensive on New Recruits than on Advanced Regenerants in a Subalpine Forest
Authors: Nagaike Takuo
Published: April 2020

Research Highlights: To ensure sustainable forest regeneration, it is important to clarify whether new recruits or advanced regenerants are more likely to be stripped. Therefore, the effects of bark stripping on saplings in subalpine forests with abundant saplings should be analyzed by regeneration mode, but there have been no such studies until now. Background and Objectives: I investigated the effects of bark stripping by Cervus nippon on saplings in a subalpine coniferous forest in central Japan to (1) reveal differences in bark stripping between new recruits and advanced regenerants and (2) clarify the factors affecting survivorship. Materials and Methods: A 50 m × 140 m (0.7 ha) plot was set in the old-growth subalpine coniferous forest. All trees in the plot that were ≥2 m in height were tagged, identified to species, measured diameter at breast height and recorded bark stripping by deer. These trees and new recruits were counted and measured in 2005, 2007, 2012, and 2017. I compared saplings recruited in 2007, 2012, and 2017 (“new recruits”) with existing saplings of the same size (“advanced regenerants”). Results: The density of new recruits of Abies mariesii and Tsuga diversifolia increased, whereas that of Abies veitchii decreased. The proportion of stripped saplings was greater in new recruits than in advanced regenerants, significantly so in A. veitchii, which also had the highest maximum bark stripping ratio. Factors affecting the survivorships applied by the regression tree analysis were the maximum stripping ratio of stems for the two Abies species and the initial size for the T. diversifolia. Conclusions: Bark stripping by deer was more intensive on new recruits than on advanced regenerants in a subalpine forest, and regeneration in canopy gaps might fail because of intensive bark stripping in areas overabundant in deer.
Selenastrum Capricornutum a New Strain of Algae for Biodiesel Production
Authors: Pugliese Annarita , Biondi Lorenzo , Bartocci Pietro , Fantozzi Francesco
Published: April 2020

The increasing global demand for biofuels for energy security and to reduce the effects of climate change has created an opportunity to explore new sources of biomass, of which, microalgae is the most promising one. The Laboratory of the Biomass Research Centre (CRB, University of Perugia) is equipped with a photobioreactor that is used to cultivate microalgae under batch conditions. Tests were carried out a temperature of 22 °C and a Photosynthetic Photon Flux Density of 140 µE·m−2·s−1. Cultures were characterized in terms of biomass produced and lipid fraction distribution. The novelty of this paper is the measure of the fuel properties of Selenastrum capricornutum, a new strain for biodiesel production. In particular, after the microalgae have been collected and oil has been extracted, this has been transesterified using a methanol/NaOH solution. The resulting biodiesel has been analyzed with a high-resolution gas chromatograph to determine the concentration of the different methylesters.
A Comparative Analysis of Breast Cancer Detection and Diagnosis Using Data Visualization and Machine Learning Applications
Authors: Ak Muhammet Fatih
Published: April 2020

In the developing world, cancer death is one of the major problems for humankind. Even though there are many ways to prevent it before happening, some cancer types still do not have any treatment. One of the most common cancer types is breast cancer, and early diagnosis is the most important thing in its treatment. Accurate diagnosis is one of the most important processes in breast cancer treatment. In the literature, there are many studies about predicting the type of breast tumors. In this research paper, data about breast cancer tumors from Dr. William H. Walberg of the University of Wisconsin Hospital were used for making predictions on breast tumor types. Data visualization and machine learning techniques including logistic regression, k-nearest neighbors, support vector machine, naïve Bayes, decision tree, random forest, and rotation forest were applied to this dataset. R, Minitab, and Python were chosen to be applied to these machine learning techniques and visualization. The paper aimed to make a comparative analysis using data visualization and machine learning applications for breast cancer detection and diagnosis. Diagnostic performances of applications were comparable for detecting breast cancers. Data visualization and machine learning techniques can provide significant benefits and impact cancer detection in the decision-making process. In this paper, different machine learning and data mining techniques for the detection of breast cancer were proposed. Results obtained with the logistic regression model with all features included showed the highest classification accuracy (98.1%), and the proposed approach revealed the enhancement in accuracy performances. These results indicated the potential to open new opportunities in the detection of breast cancer.
Barriers and Mitigating Strategies to Healthcare Access in Indigenous Communities of Canada: A Narrative Review
Authors: Nguyen Nam Hoang , Subhan Fatheema B. , Williams Kienan , Chan Catherine B.
Published: April 2020

The objective of this review is to document contemporary barriers to accessing healthcare faced by Indigenous people of Canada and approaches taken to mitigate these concerns. A narrative review of the literature was conducted. Barriers to healthcare access and mitigating strategies were aligned into three categories: proximal, intermediate, and distal barriers. Proximal barriers include geography, education attainment, and negative bias among healthcare professionals resulting in a lack of or inadequate immediate care in Indigenous communities. Intermediate barriers comprise of employment and income inequities and health education systems that are not accessible to Indigenous people. Distal barriers include colonialism, racism and social exclusion, resulting in limited involvement of Indigenous people in policy making and planning to address community healthcare needs. Several mitigation strategies initiated across Canada to address the inequitable health concerns include allocation of financial support for infrastructure development in Indigenous communities, increases in Indigenous education and employment, development of culturally sensitive education and medical systems and involvement of Indigenous communities and elders in the policy-making system. Indigenous people in Canada face systemic/policy barriers to equitable healthcare access. Addressing these barriers by strengthening services and building capacity within communities while integrating input from Indigenous communities is essential to improve accessibility.
Visualizing the USA’s Maritime Freight Flows Using DM, LP, and AON in GIS
Authors: Shen Guoqiang , Yan Xiaoyi , Zhou Long , Wang Zhangye
Published: April 2020

In this research, we developed a novel model framework consisting of data mining (DM), linear programming (LP), and an all-or-nothing (AON) flow assignment to estimate maritime freight flows between the United States and the rest of the world. We first built DM and LP models to select and combine various country-level data sources on import and export freight into a complete geographic information system (GIS)-based origin and destination (OD) database with targeted locations, networks, and attributes on ocean routes connecting foreign and U.S. maritime ports. Then, we performed freight assignments and estimated total or commodity-specific import and export freight flows. Additionally, we visualized major sea ports with various handling capacities and optimal maritime freight flows in 2D in GIS and in 3D in Google Earth with highlights for selected total and most imported or exported goods on maritime networks and for major trading partners, such as the U.S. and China. Finally, a visual validation of model results on optimal maritime routes with respect to real-time vessel density network links and routes was provided as well.
Techno-Economic Assessment of Destabilized Li Hydride Systems for High Temperature Thermal Energy Storage
Authors: Corgnale Claudio
Published: April 2020

A comprehensive techno-economic analysis of destabilized Li hydrides, used as thermal energy storage systems in concentrating solar power plants, is presented and discussed. Two systems, operating at temperatures on the order of 550–650 °C, are selected as thermal energy storage units for steam power plants, namely the Si-destabilized Li hydride (LiSi) and the Al-destabilized Li hydride (LiAl). Two thermal energy storage systems, operating at temperatures on the order of 700–750 °C, are selected for integration in supercritical CO2 power plants, namely the Si-destabilized Li hydride (LiSi) and the Sn-destabilized Li hydride (LiSn). Each storage system demonstrates excellent volumetric capacity, achieving values between 100 and 250 kWhth/m3. The LiSi-based thermal energy storage systems can be integrated with steam and supercritical CO2 plants at a specific cost between 107 US$/kWhth and 109 US$/kWhth, with potential to achieve costs on the order of 74 US$/kWhth under enhanced configurations and scenarios. The LiAl-based storage system has the highest potential for large scale applications. The specific cost of the LiAl system, integrated in solar steam power plants, is equal to approximately 74 US$/kWhth, with potential to reach values on the order of 51 US$/kWhth under enhanced performance configurations and scenarios.
Monitoring Dermacentor reticulatus Host-Seeking Activity in Natural Conditions
Authors: Zając Zbigniew , Bartosik Katarzyna , Woźniak Aneta
Published: April 2020

Ticks are hematophagous ectoparasites of humans and animals. These arthropods employ different strategies in their host-seeking activity; most often, it is the “nest”- and “pasture-questing” behaviour. Some species, e.g., Dermacentor reticulatus, exhibit both types of activity depending on their developmental stage. The aim of the present study was to investigate the host-seeking activity of adult D. reticulatus ticks in the eastern part of Poland. To this end, ticks were collected with the flagging method during their seasonal activity in three different types of habitat. Active specimens were marked with a permanent marker and then released. This was repeated consistently at 7-day intervals using a different colour of the marker each time, which allowed tracking the questing activity of the specimens. Most frequently, repetitive tick activity (repeated up to seven times) was noted in a locality surrounded by urban developments. In an agriculturally unused open meadow habitat, 69.9% of D. reticulatus ticks were found to undertake questing activity only once. D. reticulatus females proved to be more aggressive and determined to find a host than the males of this species. Adult D. reticulatus ticks are able to stay in the habitat for a long time and undertake multiple host-seeking activities. The greatest threat of attacks on animals, including domestic animals, and sporadically humans, by these ticks occurs in meadow habitats, which are preferred by this species.
Physiological, Psychological and Performance-Related Changes Following Physique Competition: A Case-Series
Authors: Longstrom Jaymes M. , Colenso-Semple Lauren M. , Waddell Brian J. , Mastrofini Gianna , Trexler Eric T. , Campbell Bill I.
Published: April 2020

The purpose of this case-series was to evaluate the physiological, psychological and performance-related changes that occur during the postcompetition period. Participants included three male (34.3 ± 6.8 years, 181.6 ± 8.9 cm) and four female (29.3 ± 4.9 years, 161.4 ± 6.0 cm) natural physique athletes. Body composition (fat mass (FM) and fat-free mass (FFM); Skinfold), resting metabolic rate (RMR; indirect calorimetry), total body water (TBW; bioelectrical impedance analysis), sleep quality (PSQI; Pittsburgh Sleep Quality Index), quality of life measures (RAND SF36), menstrual irregularities, and knee extension performance were assessed 1–2 weeks prior to competition, and 4 weeks and 8–10 weeks postcompetition. Blood hormones (free triiodothyronine; T3, free thyroxine; T4, and leptin) were assessed at 1–2 weeks prior to competition and 8–10 weeks postcompetition. Participants tracked daily macronutrient intake daily for the duration of the study. Group-level data were analyzed using exploratory, one-tailed, nonparametric statistical tests. Bodyweight, FM, bodyfat%, RMR, and blood hormones (T3, T4, and leptin) increased significantly (p < 0.05) at the group level. Relative (%Δ) increases in fat mass were associated with △RMR (τ = 0.90; p = 0.001) and △leptin (τ = 0.68; p = 0.02), and △leptin was associated with △RMR (τ = 0.59; p = 0.03). The time course for recovery appears to vary substantially between individuals potentially due to strategies implemented postcompetition.
Artificial Intelligence Techniques for Cognitive Sensing in Future IoT: State-of-the-Art, Potentials, and Challenges
Authors: Osifeko Martins O. , Hancke Gerhard P. , Abu-Mahfouz Adnan M.
Published: April 2020

Smart, secure and energy-efficient data collection (DC) processes are key to the realization of the full potentials of future Internet of Things (FIoT)-based systems. Currently, challenges in this domain have motivated research efforts towards providing cognitive solutions for IoT usage. One such solution, termed cognitive sensing (CS) describes the use of smart sensors to intelligently perceive inputs from the environment. Further, CS has been proposed for use in FIoT in order to facilitate smart, secure and energy-efficient data collection processes. In this article, we provide a survey of different Artificial Intelligence (AI)-based techniques used over the last decade to provide cognitive sensing solutions for different FIoT applications. We present some state-of-the-art approaches, potentials, and challenges of AI techniques for the identified solutions. This survey contributes to a better understanding of AI techniques deployed for cognitive sensing in FIoT as well as future research directions in this regard.
A Review on IEEE 802.11p for Intelligent Transportation Systems
Authors: Arena Fabio , Pau Giovanni , Severino Alessandro
Published: April 2020

Road safety is an active area of research for the automotive industry, and certainly one of ongoing interest to governments around the world. The intelligent transportation system (ITS) is one of several viable solutions with which to improve road safety, where the communication medium (e.g., among vehicles and between vehicles and the other components in an ITS environment, such as roadside infrastructure) is typically wireless. A typical communication standard adopted by car manufacturers is IEEE 802.11p for communications. Thus, this paper presents an overview of IEEE 802.11p, with a particular focus on its adoption in an ITS setting. Specifically, we analyze both MAC and PHY layers in a dedicated short-range communication (DSRC) environment.