bluuebunny/crossref_metadata_2025 huggingface dataset:
Whole-Exome Sequencing to Identify Potential Genetic Risk in Substance Use Disorders: A Pilot Feasibility Study
Authors: AshaRani P. V. , Amron Syidda , Zainuldin Noor Azizah Bte , Tohari Sumanty , Ng Alvin Y. J. , Song Guo , Venkatesh Byrappa , Mathuru Ajay S.
Published: June 2021

Genetics intersects with environmental, cultural, and social factors in the development of addictive disorders. This study reports the feasibility of whole-exome sequencing of trios (subject and two family members) to discover potential genetic variants in the development of substance use disorders (SUD). Family trios were recruited from the National Addictions Management Service in Singapore during the 2016–2018 period. Recruited subjects had severe alcohol use disorder (AUD) or opioid use disorder (OUD), with nicotine dependence (ND) and a family history of addictive disorders. Demographic characteristics and severity of addiction were captured. Whole-exome sequencing (WES) and analysis were performed on salivary samples collected from the trios. WES revealed variants in several genes in each individual and disruptive protein mutations in most. Variants were identified in genes previously associated with SUDs, such as Pleckstrin homology domain-containing family M member 3 (PLEKHM3), coiled-coil serine-rich protein 1 (CCSER1), LIM and calponin homology domains-containing protein 1 (LIMCH1), dynein axonemal heavy chain 8 (DNAH8), and the taste receptor type 2 member 38 (TAS2R38) involved in the perception of bitterness. The feasibility study suggests that subjects with a severe addiction profile, polysubstance use, and family history of addiction may often harbor gene variants that may predispose them to SUDs. This study could serve as a model for future precision medicine-based personalized interventional strategies for behavioral addictions and SUDs and for the discovery of potentially pathogenic genetic variants.
Serum Metabolomics in PCOS Women with Different Body Mass Index
Authors: Ożegowska Katarzyna , Plewa Szymon , Mantaj Urszula , Pawelczyk Leszek , Matysiak Jan
Published: June 2021

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine and metabolic disorder, affecting 5–10% of women of reproductive age. It results from complex environmental factors, genetic predisposition, hyperinsulinemia, hormonal imbalance, neuroendocrine abnormalities, chronic inflammation, and autoimmune disorders. PCOS impacts menstrual regularities, fertility, and dermatological complications, and may induce metabolic disturbances, diabetes, and coronary heart disease. Comprehensive metabolic profiling of patients with PCOS may be a big step in understanding and treating the disease. The study aimed to search for potential differences in metabolites concentrations among women with PCOS according to different body mass index (BMI) in comparison to healthy controls. We used broad-spectrum targeted metabolomics to evaluate metabolites’ serum concentrations in PCOS patients and compared them with healthy controls. The measurements were performed using high-performance liquid chromatography coupled with the triple quadrupole tandem mass spectrometry technique, which has highly selective multiple reaction monitoring modes. The main differences were found in glycerophospholipid concentrations, with no specific tendency to up-or down-regulation. Insulin resistance and elevated body weight influence acylcarnitine C2 levels more than PCOS itself. Sphingomyelin (SM) C18:1 should be more intensively observed and examined in future studies and maybe serve as one of the PCOS biomarkers. No significant correlations were observed between anthropometric and hormonal parameters and metabolome results.
Association of Serum Bilirubin Level with Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease: A Cross-Sectional Study of 1672 Obese Children
Authors: Bellarosa Cristina , Bedogni Giorgio , Bianco Annalisa , Cicolini Sabrina , Caroli Diana , Tiribelli Claudio , Sartorio Alessandro
Published: June 2021

As in adults, obesity also plays a central role in the development of metabolic syndrome (MS) in children. Non-alcoholic fatty liver disease (NAFLD) is considered a manifestation of MS. Not only MS but also NAFLD seem to be inversely associated with serum bilirubin concentrations, an important endogenous tissue protector when only mild elevated. The aim of the study was to evaluate the association between serum bilirubin levels and the prevalence of MS and NAFLD in Italian obese children and adolescents. A retrospective cross-sectional study was performed in 1672 patients aged from 5 to 18 years. Clinical and laboratory parameters were assessed. NAFLD was measured by liver ultrasonography. The study was approved by the Ethical Committee of the Istituto Auxologico Italiano (research project code 1C021_2020, acronym BILOB). MS was present in 24% and fatty liver (FL) in 38% of this population. Bilirubin was not associated with FL and MS as a whole, but it was inversely associated only with selected components of MS, i.e., large WC, high blood pressure and high triglycerides. Our data suggest that bilirubin is not protective against MS and NAFLD in the presence of severe obesity.
Vaccine Effects on Susceptibility and Symptomatology Can Change the Optimal Allocation of COVID-19 Vaccines: South Korea as an Example
Authors: Choi Wongyeong , Shim Eunha
Published: June 2021

The approved coronavirus disease (COVID-19) vaccines reduce the risk of disease by 70–95%; however, their efficacy in preventing COVID-19 is unclear. Moreover, the limited vaccine supply raises questions on how they can be used effectively. To examine the optimal allocation of COVID-19 vaccines in South Korea, we constructed an age-structured mathematical model, calibrated using country-specific demographic and epidemiological data. The optimal control problem was formulated with the aim of finding time-dependent age-specific optimal vaccination strategies to minimize costs related to COVID-19 infections and vaccination, considering a limited vaccine supply and various vaccine effects on susceptibility and symptomatology. Our results suggest that “susceptibility-reducing” vaccines should be relatively evenly distributed among all age groups, resulting in more than 40% of eligible age groups being vaccinated. In contrast, “symptom-reducing” vaccines should be administered mainly to individuals aged 20–29 and ≥60 years. Thus, our study suggests that the vaccine profile should determine the optimal vaccination strategy. Our findings highlight the importance of understanding vaccine’s effects on susceptibility and symptomatology for effective public health interventions.
Vertigo as One of the Symptoms of Lyme Disease
Authors: Sowula Klaudia , Szaleniec Joanna , Dworak Mateusz , Przeklasa Maria , Maraj Małgorzata , Ceranowicz Piotr , Tomik Jerzy
Published: June 2021

Objectives: The aim of the study was to evaluate the frequency of vertigo symptoms and potential labyrinth damage in patients with diagnosed Lyme disease (LD). LD can affect the vestibulocochlear nerve, leading to hearing loss and vertigo/dizziness. Material and Methods: The study included a group of 38 patients between the ages of 20 and 77, who were hospitalized due to vertigo/dizziness between 2018 and 2019. All of the patients underwent a detailed medical interview and an otolaryngological and neurological examination, including video electronystagmography (VENG), in addition to audiological and diagnostic tests. Additionally, ELISA and Western blot tests were performed to confirm the diagnosis of LD. Results: In 20 patients (53%), the Romberg trial was positive (p < 0.001). The degree of vestibular dysfunction as shown by the VENG test was associated with the rate of hearing loss as confirmed by the Auditory Brainstem Response (ABR) test (p = 0.011), and it mainly concerned high-frequency sounds (p = 0.014). Conclusion: Vertigo can be a symptom of LD. It is often associated with labyrinth and hearing-organ damage, which can imply that the inner ear or nerve VIII is dysfunctional in the course of this disease. Antibiotic therapy is effective in reducing otoneurological symptoms.
Differences in Clinical Features among Different Onset Patterns in Moyamoya Disease
Authors: Hirano Yudai , Miyawaki Satoru , Imai Hideaki , Hongo Hiroki , Teranishi Yu , Dofuku Shogo , Ishigami Daiichiro , Ohara Kenta , Koizumi Satoshi , Ono Hideaki , Nakatomi Hirofumi , Saito Nobuhito
Published: June 2021

Moyamoya disease is characterized by severe stenosis at the ends of the bilateral internal carotid arteries and the development of collateral circulation. The disease is very diverse in terms of age at onset, onset patterns, radiological findings, and genetic phenotypes. The pattern of onset is mainly divided into ischemic and hemorrhagic onsets. Recently, the opportunity to identify asymptomatic moyamoya disease, which sometimes manifests as nonspecific symptoms such as headache and dizziness, through screening with magnetic resonance imaging has been increasing. Various recent reports have investigated the associations between the clinical features of different onset patterns of moyamoya disease and the corresponding imaging characteristics. In this article, we have reviewed the natural history, clinical features, and imaging features of each onset pattern of moyamoya disease.
Persistent Spinal Pain Syndrome Type 2 (PSPS-T2), a Social Pain? Advocacy for a Social Gradient of Health Approach to Chronic Pain
Authors: Naiditch Nicolas , Billot Maxime , Moens Maarten , Goudman Lisa , Cornet Philippe , Le Breton David , Roulaud Manuel , Ounajim Amine , Page Philippe , Lorgeoux Bertille , Nivole Kevin , Pries Pierre , Swennen Cecile , Teyssedou Simon , Charrier Elodie , de Montgazon Géraldine Brumauld , Descoins Pierre François , Roy-Moreau Brigitte , Grimaud Nelly , David Romain , Vendeuvre Tanguy , Rigoard Philippe
Published: June 2021

The Social Gradient of Health (SGH), or position in the social hierarchy, is one of the major determinants of health. It influences the development and evolution of many chronic diseases. Chronic pain dramatically affects individual and social condition. Its medico-economic impact is significant and worldwide. Failed Back Surgery Syndrome or Persistent Spinal Pain Syndrome type 2 (PSPS-T2) represents one of its most fascinating and disabling conditions. However, the influence of SGH on PSPS-T2 has been poorly explored. We designed a prospective multicentric study (PREDIBACK study) to assess the SGH prevalence, and to examine its association with medical and psychological variables, in PSPS-T2 patients. This study included 200 patients to determine the SGH association with pain (NPRS), Quality of life (EQ-5D-5L), kinesiophobia (FABQ-Work), catastrophism (CSQ), and functional capacity (ODI). Around 85.3% of PSPS-T2 patients in our study had low SGH. Low SGH patients had a higher FABQ-Work and CSQ-Catastrophizing score than high SGH patients (p < 0.05). High SGH patients have a higher ODI score than low SGH patients (p < 0.10). Our results suggest that SGH is a relevant factor to guide prevention, research, and ultimately intervention in PSPS-T2 patients and could be more widely transposed to chronic pain.
Unsupervised Foreign Object Detection Based on Dual-Energy Absorptiometry in the Food Industry
Authors: Andriiashen Vladyslav , van Liere Robert , van Leeuwen Tristan , Batenburg Kees Joost
Published: June 2021

X-ray imaging is a widely used technique for non-destructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of foreign objects in food samples. Examples of such inclusions are bone fragments in meat products, plastic and metal debris in fish, and fruit infestations. This article presents a processing methodology for unsupervised foreign object detection based on dual-energy X-ray absorptiometry (DEXA). A novel thickness correction model is introduced as a pre-processing technique for DEXA data. The aim of the model is to homogenize regions in the image that belong to the food product and to enhance contrast where the foreign object is present. In this way, the segmentation of the foreign object is more robust to noise and lack of contrast. The proposed methodology was applied to a dataset of 488 samples of meat products acquired from a conveyor belt. Approximately 60% of the samples contain foreign objects of different types and sizes, while the rest of the samples are void of foreign objects. The results show that samples without foreign objects are correctly identified in 97% of cases and that the overall accuracy of foreign object detection reaches 95%.
Influence of Combined Motion of Pitch and Surge with Phase Difference on Aerodynamic Performance of Floating Offshore Wind Turbine
Authors: Feng Xiangheng , Lin Yonggang , Zhang Guohao , Li Danyang , Liu Hongwei , Wang Bin
Published: June 2021

Platform motions induced by waves pose a challenge to accurately predict the aerodynamic performance of floating offshore wind turbines (FOWTs). In view of this, the power performance and wake structure of FOWTs under platform pitch, surge, and their combined motions were investigated in this paper, using the computational fluid dynamics software, STAR-CCM+, with overset meshing and rigid body motion techniques. First, the simulation cases in single and same-phase combined motions with different amplitudes and frequencies were performed. Afterward, the approach of calculating the phase difference between pitch and surge motions was proposed to investigate the influence of the combined motion with phase difference on the aerodynamic performance. Results show that the increment of amplitude and frequency augments the mean power output and aggravates the power fluctuation in single and same-phase combined motions. The intensity of power variation under combined motion with a phase difference is weakened at 0.1 Hz compared to the single motion, while enhanced at 0.2 Hz, showing a different influence law on the aerodynamic performance. In addition, this paper established the power fluctuation table based on real sea states of Shidao in China, providing a certain reference for the controller design in this sea area.
A Potential Fungal Probiotic Aureobasidium melanogenum CK-CsC for the Western Honey Bee, Apis mellifera
Authors: Hsu Chih-Kuan , Wang Dun-Yan , Wu Ming-Cheng
Published: June 2021

Aureobasidium melanogenum has been used as an animal feed additive for improving thehealth of pets, however, it has not yet been applied in honey bees. Here, a fungal strain CK-CsC isolated from bee bread pollen, was identified as A. melanogenum. Following characterizing CK-CsC fermentation broth, the 4-days fermentation broth (SYM medium or bee pollen) of the CK-CsC was used to feed newly emerged adult honey bees in cages under laboratory-controlled conditions for analysis of survival, gene expression of nutrient and antibacterial peptide, and gut microbiota of honey bees. It was found that the CK–CsC fermentation broth (SYM medium or bee pollen) is nontoxic to honey bees, and can regularly increase nutrient gene expression of honey bees. However, significant mortality of bees was observed after bees were fed on the supernatant liquid of the fermentation broth. Notably, this mortality can be lowered by the simultaneous consumption of bee pollen. The honey bees that were fed bee pollen exhibited more γ-Proteobacteria, Bacteriodetes, and Actinobacteria in their gut flora than did the honey bees fed only crude supernatant liquid extract. These findings indicate that A. melanogenum CK–CsC has high potential as a bee probiotic when it was fermented with bee pollen.
Public Sphere and Misinformation in the U.S. Election: Trump’s Audience and Populism Indicators in the COVID-19 Context
Authors: Pérez-Curiel Concha , Domínguez-García Ricardo , Jiménez-Marín Gloria
Published: June 2021

(1) In a context of an unprecedented global pandemic, an analysis of the effects of political disinformation on audiences is needed. The U.S. election process culminating in the official proclamation of Joe Biden as president has led to an increase in the public’s distrust of politics and its leaders, as public opinion polls show. In this context, the change in the electorate’s attitude towards Donald Trump, throughout the legislature and especially after the elections, stands out. So, the objective of this research was to determine, through the measurement of surveys, the views of the electorate on the behavior of the Republican candidate and the possible causes that determine the loss of confidence in his speeches and comments. (2) The methodology, a comparative quantitative-qualitative approach, analyzed the responses collected by Pew Research waves 78 and 80 (2020 and 2021). Specifically, the surveys analyzed were 11,818 U.S. adults in the case of the American Trends Panel 2020 and 5360 in the case of the same panel for 2021. (3) Results showed the change of position of the electorate, especially Republicans, in the face of the policy of delegitimization of the process and Trump’s populist messages on Twitter. (4) Conclusions pointed in two directions: society has decided not to trust Trump, while at the same time showing distrust about the correct management of the electoral ballot.
Radiomics in Lung Diseases Imaging: State-of-the-Art for Clinicians
Authors: Frix Anne-Noëlle , Cousin François , Refaee Turkey , Bottari Fabio , Vaidyanathan Akshayaa , Desir Colin , Vos Wim , Walsh Sean , Occhipinti Mariaelena , Lovinfosse Pierre , Leijenaar Ralph , Hustinx Roland , Meunier Paul , Louis Renaud , Lambin Philippe , Guiot Julien
Published: June 2021

Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50 years. As modern medicine is evolving towards precision medicine, offering personalized patient care and treatment, the requirement for robust imaging biomarkers has gradually increased. Radiomics, a specific method generating high-throughput extraction of a tremendous amount of quantitative imaging data using data-characterization algorithms, has shown great potential in individuating imaging biomarkers. Radiomic analysis can be implemented through the following two methods: hand-crafted radiomic features extraction or deep learning algorithm. Its application in lung diseases can be used in clinical decision support systems, regarding its ability to develop descriptive and predictive models in many respiratory pathologies. The aim of this article is to review the recent literature on the topic, and briefly summarize the interest of radiomics in chest Computed Tomography (CT) and its pertinence in the field of pulmonary diseases, from a clinician’s perspective.
OPriv: Optimizing Privacy Protection for Network Traffic
Authors: Chaddad Louma , Chehab Ali , Kayssi Ayman
Published: June 2021

Statistical traffic analysis has absolutely exposed the privacy of supposedly secure network traffic, proving that encryption is not effective anymore. In this work, we present an optimal countermeasure to prevent an adversary from inferring users’ online activities, using traffic analysis. First, we formulate analytically a constrained optimization problem to maximize network traffic obfuscation while minimizing overhead costs. Then, we provide OPriv, a practical and efficient algorithm to solve dynamically the non-linear programming (NLP) problem, using Cplex optimization. Our heuristic algorithm selects target applications to mutate to and the corresponding packet length, and subsequently decreases the security risks of statistical traffic analysis attacks. Furthermore, we develop an analytical model to measure the obfuscation system’s resilience to traffic analysis attacks. We suggest information theoretic metrics for quantitative privacy measurement, using entropy. The full privacy protection of OPriv is assessed through our new metrics, and then through extensive simulations on real-world data traces. We show that our algorithm achieves strong privacy protection in terms of traffic flow information without impacting the network performance. We are able to reduce the accuracy of a classifier from 91.1% to 1.42% with only 0.17% padding overhead.
A Study of Fall Detection in Assisted Living: Identifying and Improving the Optimal Machine Learning Method
Authors: Thakur Nirmalya , Han Chia Y.
Published: June 2021

This paper makes four scientific contributions to the field of fall detection in the elderly to contribute to their assisted living in the future of Internet of Things (IoT)-based pervasive living environments, such as smart homes. First, it presents and discusses a comprehensive comparative study, where 19 different machine learning methods were used to develop fall detection systems, to deduce the optimal machine learning method for the development of such systems. This study was conducted on two different datasets, and the results show that out of all the machine learning methods, the k-NN classifier is best suited for the development of fall detection systems in terms of performance accuracy. Second, it presents a framework that overcomes the limitations of binary classifier-based fall detection systems by being able to detect falls and fall-like motions. Third, to increase the trust and reliance on fall detection systems, it introduces a novel methodology based on the usage of k-folds cross-validation and the AdaBoost algorithm that improves the performance accuracy of the k-NN classifier-based fall detection system to the extent that it outperforms all similar works in this field. This approach achieved performance accuracies of 99.87% and 99.66%, respectively, when evaluated on the two datasets. Finally, the proposed approach is also highly accurate in detecting the activity of standing up from a lying position to infer whether a fall was followed by a long lie, which can cause minor to major health-related concerns. The above contributions address multiple research challenges in the field of fall detection, that we identified after conducting a comprehensive review of related works, which is also presented in this paper.
Hyperoxia Inhibits Proliferation of Retinal Endothelial Cells in a Myc-Dependent Manner
Authors: Singh Charandeep , Benos Andrew , Grenell Allison , Rao Sujata , Anand-Apte Bela , Sears Jonathan E.
Published: June 2021

Oxygen supplementation is necessary to prevent mortality in severely premature infants. However, the supraphysiological concentration of oxygen utilized in these infants simultaneously creates retinovascular growth attenuation and vasoobliteration that induces the retinopathy of prematurity. Here, we report that hyperoxia regulates the cell cycle and retinal endothelial cell proliferation in a previously unknown Myc-dependent manner, which contributes to oxygen-induced retinopathy.
Oxidation State and Local Structure of Chromium Ions in LaOCl
Authors: Antuzevics Andris , Krieke Guna , Ozols Haralds , Fedotovs Andris , Sarakovskis Anatolijs , Kuzmin Alexei
Published: June 2021

LaOCl doped with 0–10 mol% Cr was synthesized by thermal decomposition of chlorides. X-ray diffraction (XRD) analysis revealed that incorporation of chromium results in a decrease of the lattice parameter a and a simultaneous increase of the lattice parameter c. The local structure of chromium ions was studied with X-ray photoelectron (XPS), X-ray absorption (XANES), multifrequency electron paramagnetic resonance (EPR) and electron-nuclear double resonance (ENDOR) spectroscopy techniques. It was determined that synthesis in oxidizing atmosphere promotes the incorporation of chromium ions predominantly in the 5+ oxidation state. Changes of chromium oxidation state and local environment occur after a subsequent treatment in reducing atmosphere. Spin-Hamiltonian (SH) parameters for a Cr5+ and two types of Cr3+ centers in LaOCl were determined from the EPR spectra simulations.
Effects of the Replacement Length of Concrete with ECC on the Cyclic Behavior of Reinforced Concrete Columns
Authors: Hyun Jung-Hwan , Bang Jin-Wook , Lee Bang-Yeon , Kim Yun-Yong
Published: June 2021

This paper presents an experimental investigation on the effects of the replacement length of concrete with engineered cementitious composites (ECC) on the cyclic behavior of a reinforced concrete (RC) column. A conventional RC column specimen and two RC composite columns designed with ECC were fabricated. To investigate the cyclic behavior of each specimen, a series of cyclic loading tests was performed under a reversed cyclic loading condition with a constant axial load. Test results showed that ECC columns exhibited higher cyclic behavior in terms of load carrying capacity, ductility, and energy dissipation capacity compared to the RC column. It was also found that when applying ECC to the column specimen with a length of 3.6d or more, the energy dissipation capacity was greatly increased.
Creation of AlSi12 Alloy Coating by Centrifugal Induction Surfacing with the Addition of Low-Melting Metals
Authors: Komarov Aleksander I. , Kyzioł Lesław , Orda Dmitry V. , Iskandarova Donata O. , Sosnovskiy Igor A. , Kurilyonok Artem A. , Żuk Daria
Published: June 2021

This paper investigates the structure and mechanical characteristics of a coating based on an AlSi12 alloy, obtained by centrifugal induction surfacing as an alternative to a bronze sliding bearing. To provide for the adhesion of an aluminum layer to the inner surface of a steel bearing housing, a sublayer of low-melting metals was formed, while the formation of the main layer and the sublayer was done in a single processing cycle. The low-melting metals had higher density, which ensured that the sublayer was created at the interface with the steel bearing housing under the action of centrifugal forces. It is shown that the low-melting sublayer forms a strong bond both with the aluminum alloy and with the steel base. Lead and tin are used as low-melting additives. It has been established that lead or tin used in a sublayer are indirectly involved in the structural formation of boundary layers of steel and aluminum claddings, acting as a medium for diffuse mass transfer. Thus, lead is not included in the composition of the main coating and does not change the chemical composition of the aluminum layer. After the addition of tin, the aluminum develops a dendritic structure, with tin captured in the interdendritic space. In this case, the deposited layer is saturated with iron with the formation of intermetallic (Fe, Al, Si) compounds, both at the interface and in the coating volume. This paper offers an explanation of the mechanism through which Pb and Sn act on the structure formation of the coating, and on the boundary layer of the steel bearing housing. Tribological tests have shown that the resulting materials are a promising option for plain bearings and highly competitive with the CuSn10P bronze.
Analysis and Assessment of the Usefulness of Recycled Plastic Materials for the Production of Airfield Geocell
Authors: Wesołowski Mariusz , Włodarski Piotr , Iwanowski Paweł , Kowalewska Agata
Published: June 2021

The load-bearing capacity of natural airfield pavement has a direct impact on the safety of air operations. Unfortunately, the field tests often indicate that the load-bearing capacity of natural airfield pavements is not sufficient. In this case, it is necessary to reinforce them in order to meet the requirements set out in international documents. It is important that the method of reinforcing the subsoil is fast and as noninvasively as possible. There are many methods of reinforcing the subsoil, however, they are expensive and time-demanding, which involves turning off the airport for a long time. Airfield geocells made of recycled plastics discussed in the article seem to be the optimal solution due to the quick implementation of their application by pressing into the existing natural pavement. The article presents the results of laboratory tests demonstrating that material in question is load-resistant and chemical-resistant, while field studies have confirmed that the airfield geocell made of the plastic in question improves the load carrying capacity of natural airfield pavement.
The Extrusion and SPS of Zirconium–Copper Powders and Studies of Selected Mechanical Properties
Authors: Skrzekut Tomasz , Boczkal Grzegorz , Zwoliński Adam , Noga Piotr , Jaworska Lucyna , Pałka Paweł , Podsiadło Marcin
Published: June 2021

Zr-2.5Cu and Zr-10Cu powder mixtures were consolidated in the extrusion process and using the spark plasma sintering technique. In these studies, material tests were carried out in the fields of phase composition, microstructure, hardness and tensile strength for Zr-Cu materials at room temperature (RT) and 400 °C. Fractography analysis of materials at room temperature and 400 °C was carried out. The research took into account the anisotropy of the materials obtained in the extrusion process. For the nonequilibrium SPS process, ZrCu2 and Cu10Zr7 intermetallic compounds formed in the material at sintering temperature. Extruded materials were composed mainly of α-Zr and ZrCu2. The presence of intermetallic compounds affected the reduction in the strength properties of the tested materials. The highest strength value of 205 MPa was obtained for the extruded Zr-2.5Cu, for which the samples were cut in the direction of extrusion. For materials with 10 wt.% copper, more participation of the intermetallic phase was formed, which lowered the mechanical properties of the obtained materials. In addition to brittle intermetallic phases, the materials were characterized by residual porosity, which also reduced the strength properties.
A Comparative Study of Thermal Aging Effect on the Properties of Silicone-Based and Silicone-Free Thermal Gap Filler Materials
Authors: Chowdhury A S M Raufur , Rabby Monjur Morshed , Kabir Mehzabeen , Das Partha Pratim , Bhandari Rabin , Raihan Rassel , Agonafer Dereje
Published: June 2021

Thermal conductive gap filler materials are used as thermal interface materials (TIMs) in electronic devices due their numerous advantages, such as higher thermal conductivity, ease of use, and conformity. Silicone is a class of synthetic materials based on a polymeric siloxane backbone which is widely used in thermal gap filler materials. In electronic packages, silicone-based thermal gap filler materials are widely used in industries, whereas silicone-free thermal gap filler materials are emerging as new alternatives for numerous electronics applications. Certainly, characterization of these TIMs is of immense importance since it plays a critical role in heat dissipation and long-term reliability of the electronic packages. Insubstantial studies on the effects of various chemical compounds on the properties of silicone-based and silicone-free TIMs has led to this study, which focuses on the effect of thermal aging on the mechanical, thermal, and dielectric properties of silicone-based and silicone-free TIMs and the chemical compounds that cause the changes in properties of these materials. Characterization techniques such as dynamic mechanical analysis (DMA), thermomechanical analysis (TMA), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), and broadband dielectric spectroscopy (BbDS) are used to study the mechanical, thermal, and dielectric characteristics of these TIMs, which will guide towards a better understanding of the applicability and reliability of these TIMs. The experiments demonstrate that upon thermal aging at 125 °C, the silicone-free TIM becomes hard, while silicone-based TIM remains viscoelastic, which indicates its wide applicability to higher temperature applications for a long time. Though silicone-based TIM displays better mechanical and thermal properties at elevated temperatures, dielectric properties indicate low conductivity for silicone-free TIM, which makes it a better candidate for silicone-sensitive applications where higher electric insulation is desired.
Innovative Investment Models with Frequent Payments of Tax on Income and of Interest on Debt
Authors: Brusov Peter , Filatova Tatiana , Chang She-I , Lin George
Published: June 2021

New modern investment models are created to be as close as possible to real investment conditions. We consider long-term as well as arbitrary duration models with payments of interest on debt and of tax on income a few times per year (semi-annually, quarterly and monthly), which could be applied in real economic practice. Their verification will lead to the creation of a comprehensive system of adequate and correct assessment of the effectiveness of the company’s investment program and its investment strategy. One of the most important elements of calculating the effectiveness of investment projects is the assessment of the discount rate, the calculation methods of which are generalized for the real conditions of the implementation of investment projects. We consider the effectiveness of the investment project from two points of view: the equity owners and the owners of equity and debt. NPV for each of these cases is calculated by two different methods: with the separation of credit and investment flows (and thus discounting the flows using two different rates) and without such separation (with discounting of both flows using the same rate, and WACC can be chosen as the rate). Numerical calculations, conducted for four investment models (without flow separation) show that: (1) in the case of considering the effectiveness of an investment project for owners of equity capital, the increase in the number of payments of tax on income and of interest on debt p leads to a decrease in NPV: this means that the effectiveness of an investment project decreases with p; (2) in the case of considering the effectiveness of an investment project for owners of equity and debt capital, the increase in the number of payments of tax on income and of interest on debt p leads to an increase in NPV: this means that the effectiveness of an investment project increases with p. In the former case, companies should pay tax on profit and interest on debt once per year, while in the latter case, more frequent payments are profitable for the effectiveness of investment. Eight innovative investment models created in this paper can assist decision-makers in the optimal design, planning and control of company investments and the development of a company’s investment strategy.
Alternative Dirichlet Priors for Estimating Entropy via a Power Sum Functional
Authors: Botha Tanita , Ferreira Johannes , Bekker Andriette
Published: June 2021

Entropy is a functional of probability and is a measurement of information contained in a system; however, the practical problem of estimating entropy in applied settings remains a challenging and relevant problem. The Dirichlet prior is a popular choice in the Bayesian framework for estimation of entropy when considering a multinomial likelihood. In this work, previously unconsidered Dirichlet type priors are introduced and studied. These priors include a class of Dirichlet generators as well as a noncentral Dirichlet construction, and in both cases includes the usual Dirichlet as a special case. These considerations allow for flexible behaviour and can account for negative and positive correlation. Resultant estimators for a particular functional, the power sum, under these priors and assuming squared error loss, are derived and represented in terms of the product moments of the posterior. This representation facilitates closed-form estimators for the Tsallis entropy, and thus expedite computations of this generalised Shannon form. Select cases of these proposed priors are considered to investigate the impact and effect on the estimation of Tsallis entropy subject to different parameter scenarios.
Open Markov Type Population Models: From Discrete to Continuous Time
Authors: Esquível Manuel L. , Krasii Nadezhda P. , Guerreiro Gracinda R.
Published: June 2021

We address the problem of finding a natural continuous time Markov type process—in open populations—that best captures the information provided by an open Markov chain in discrete time which is usually the sole possible observation from data. Given the open discrete time Markov chain, we single out two main approaches: In the first one, we consider a calibration procedure of a continuous time Markov process using a transition matrix of a discrete time Markov chain and we show that, when the discrete time transition matrix is embeddable in a continuous time one, the calibration problem has optimal solutions. In the second approach, we consider semi-Markov processes—and open Markov schemes—and we propose a direct extension from the discrete time theory to the continuous time one by using a known structure representation result for semi-Markov processes that decomposes the process as a sum of terms given by the products of the random variables of a discrete time Markov chain by time functions built from an adequate increasing sequence of stopping times.
Potency- and Selectivity-Enhancing Mutations of Conotoxins for Nicotinic Acetylcholine Receptors Can Be Predicted Using Accurate Free-Energy Calculations
Authors: Katz Dana , DiMattia Michael A. , Sindhikara Dan , Li Hubert , Abraham Nikita , Leffler Abba E.
Published: June 2021

Nicotinic acetylcholine receptor (nAChR) subtypes are key drug targets, but it is challenging to pharmacologically differentiate between them because of their highly similar sequence identities. Furthermore, α-conotoxins (α-CTXs) are naturally selective and competitive antagonists for nAChRs and hold great potential for treating nAChR disorders. Identifying selectivity-enhancing mutations is the chief aim of most α-CTX mutagenesis studies, although doing so with traditional docking methods is difficult due to the lack of α-CTX/nAChR crystal structures. Here, we use homology modeling to predict the structures of α-CTXs bound to two nearly identical nAChR subtypes, α3β2 and α3β4, and use free-energy perturbation (FEP) to re-predict the relative potency and selectivity of α-CTX mutants at these subtypes. First, we use three available crystal structures of the nAChR homologue, acetylcholine-binding protein (AChBP), and re-predict the relative affinities of twenty point mutations made to the α-CTXs LvIA, LsIA, and GIC, with an overall root mean square error (RMSE) of 1.08 ± 0.15 kcal/mol and an R2 of 0.62, equivalent to experimental uncertainty. We then use AChBP as a template for α3β2 and α3β4 nAChR homology models bound to the α-CTX LvIA and re-predict the potencies of eleven point mutations at both subtypes, with an overall RMSE of 0.85 ± 0.08 kcal/mol and an R2 of 0.49. This is significantly better than the widely used molecular mechanics—generalized born/surface area (MM-GB/SA) method, which gives an RMSE of 1.96 ± 0.24 kcal/mol and an R2 of 0.06 on the same test set. Next, we demonstrate that FEP accurately classifies α3β2 nAChR selective LvIA mutants while MM-GB/SA does not. Finally, we use FEP to perform an exhaustive amino acid mutational scan of LvIA and predict fifty-two mutations of LvIA to have greater than 100X selectivity for the α3β2 nAChR. Our results demonstrate the FEP is well-suited to accurately predict potency- and selectivity-enhancing mutations of α-CTXs for nAChRs and to identify alternative strategies for developing selective α-CTXs.
A Thermo-Mechanical Analysis of Laser Hot Wire Additive Manufacturing of NAB
Authors: Hatala Glenn W. , Wang Qian , Reutzel Edward W. , Fisher Charles R. , Semple Jennifer K.
Published: June 2021

There is increased interest in using nickel aluminum bronze (NAB) alloys in large-scale directed energy deposition additive manufacturing (DEDAM) processes for maritime applications, but one challenge lies in the component distortion that results from residual stress generated during fabrication. This paper describes the development and evaluation of thermo-mechanical simulations for laser hot wire (LHW) DEDAM of NAB to predict part distortion. To account for the dearth of temperature-dependent properties for NAB C95800 in open literature and public databases, temperature-dependent material and mechanical properties for NAB C95800 were experimentally measured using test specimens fabricated with a variety of DEDAM processes. Autodesk’s Netfabb Local Simulation software, a commercial finite-element based AM solver, was employed but with its heat source model modified to accommodate LHW DEDAM’s oscillating laser path and additional energy input supplied by the preheated wire feedstock. Thermo-mechanical simulations were conducted using both the acquired temperature-dependent material and mechanical properties and the constant room-temperature properties to assess the impact on simulation accuracy. The usage of constant properties in the thermo-mechanical analysis resulted in significantly different predicted distortion compared to those using the temperature-dependent properties, at times even predicting substrate displacement in an opposite direction.
Metabolomics: A Scoping Review of Its Role as a Tool for Disease Biomarker Discovery in Selected Non-Communicable Diseases
Authors: Aderemi Adewale Victor , Ayeleso Ademola Olabode , Oyedapo Oluboade Oluokun , Mukwevho Emmanuel
Published: June 2021

Metabolomics is a branch of ‘omics’ sciences that utilises a couple of analytical tools for the identification of small molecules (metabolites) in a given sample. The overarching goal of metabolomics is to assess these metabolites quantitatively and qualitatively for their diagnostic, therapeutic, and prognostic potentials. Its use in various aspects of life has been documented. We have also published, howbeit in animal models, a few papers where metabolomic approaches were used in the study of metabolic disorders, such as metabolic syndrome, diabetes, and obesity. As the goal of every research is to benefit humankind, the purpose of this review is to provide insights into the applicability of metabolomics in medicine vis-à-vis its role in biomarker discovery for disease diagnosis and management. Here, important biomarkers with proven diagnostic and therapeutic relevance in the management of disease conditions, such as Alzheimer’s disease, dementia, Parkinson’s disease, inborn errors of metabolism (IEM), diabetic retinopathy, and cardiovascular disease, are noted. The paper also discusses a few reasons why most metabolomics-based laboratory discoveries are not readily translated to the clinic and how these could be addressed going forward.
An SVM-Based NAND Flash Endurance Prediction Method
Authors: Zhang Haichun , Wang Jie , Chen Zhuo , Pan Yuqian , Lu Zhaojun , Liu Zhenglin
Published: June 2021

NAND flash memory is widely used in communications, commercial servers, and cloud storage devices with a series of advantages such as high density, low cost, high speed, anti-magnetic, and anti-vibration. However, the reliability is increasingly getting worse while process improvements and technological advancements have brought higher storage densities to NAND flash memory. The degradation of reliability not only reduces the lifetime of the NAND flash memory but also causes the devices to be replaced prematurely based on the nominal value far below the minimum actual value, resulting in a great waste of lifetime. Using machine learning algorithms to accurately predict endurance levels can optimize wear-leveling strategies and warn bad memory blocks, which is of great significance for effectively extending the lifetime of NAND flash memory devices and avoiding serious losses caused by sudden failures. In this work, a multi-class endurance prediction scheme based on the SVM algorithm is proposed, which can predict the remaining P-E cycle level and the raw bit error level after various P-E cycles. Feature analysis based on endurance data is used to determine the basic elements of the model. Based on the error features, we present a variety of targeted optimization strategies, such as extracting the numerical features closely related to the endurance, and reducing the noise interference of transient faults through short-term repeated operations. Besides a high-parallel flash test platform supporting multiple protocols, a feature preprocessing module is constructed based on the ZYNQ-7030 chip. The pipelined module of SVM decision model can complete a single prediction within 37 us.
The Chemical Ecology Approach to Reveal Fungal Metabolites for Arthropod Pest Management
Authors: Berestetskiy Alexander , Hu Qiongbo
Published: June 2021

Biorational insecticides (for instance, avermectins, spinosins, azadirachtin, and afidopyropen) of natural origin are increasingly being used in agriculture. The review considers the chemical ecology approach for the search for new compounds with insecticidal properties (entomotoxic, antifeedant, and hormonal) produced by fungi of various ecological groups (entomopathogens, soil saprotrophs, endophytes, phytopathogens, and mushrooms). The literature survey revealed that insecticidal metabolites of entomopathogenic fungi have not been sufficiently studied, and most of the well-characterized compounds show moderate insecticidal activity. The greatest number of substances with insecticidal properties was found to be produced by soil fungi, mainly from the genera Aspergillus and Penicillium. Metabolites with insecticidal and antifeedant properties were also found in endophytic and phytopathogenic fungi. It was noted that insect pests of stored products are mostly low sensitive to mycotoxins. Mushrooms were found to be promising producers of antifeedant compounds as well as insecticidal proteins. The expansion of the number of substances with insecticidal properties detected in prospective fungal species is possible by mining fungal genomes for secondary metabolite gene clusters and secreted proteins with their subsequent activation by various methods. The efficacy of these studies can be increased with high-throughput techniques of extraction of fungal metabolites and their analysis by various methods of chromatography and mass spectrometry.
Land-Use Type Drives Soil Population Structures of the Entomopathogenic Fungal Genus Metarhizium
Authors: Fernández-Bravo María , Gschwend Florian , Mayerhofer Johanna , Hug Anna , Widmer Franco , Enkerli Jürg
Published: June 2021

Species of the fungal genus Metarhizium are globally distributed pathogens of arthropods, and a number of biological control products based on these fungi have been commercialized to control a variety of pest arthropods. In this study, we investigate the abundance and population structure of Metarhizium spp. in three land-use types—arable land, grassland, and forest—to provide detailed information on habitat selection and the factors that drive the occurrence and abundance of Metarhizium spp. in soil. At 10 sites of each land-use type, which are all part of the Swiss national soil-monitoring network (NABO), Metarhizium spp. were present at 8, 10, and 4 sites, respectively. On average, Metarhizium spp. were most abundant in grassland, followed by forest and then arable land; 349 Metarhizium isolates were collected from the 30 sites, and sequence analyses of the nuclear translation elongation factor 1α gene, as well as microsatellite-based genotyping, revealed the presence of 13 Metarhizium brunneum, 6 Metarhizium robertsii, and 3 Metarhizium guizhouense multilocus genotypes (MLGs). With 259 isolates, M. brunneum was the most abundant species, and significant differences were detected in population structures between forested and unforested sites. Among 15 environmental factors assessed, C:N ratio, basal respiration, total carbon, organic carbon, and bulk density significantly explained the variation among the M. brunneum populations. The information gained in this study will support the selection of best-adapted isolates as biological control agents and will provide additional criteria for the adaptation or development of new pest control strategies.