bluuebunny/crossref_metadata_2025 huggingface dataset:
Ionic Conductivity and Dielectric Relaxation of NASICON Superionic Conductors at the Near-Cryogenic Regime
Authors: Tiliakos Athanasios , Iordache Mihaela , Marinoiu Adriana
Published: September 2021

With a crystal lattice structure first characterized in the 1970s, NASICON sodium-based superionic conductors have recently found renewed interest as solid electrolytes in sodium-ion and seawater flow batteries due to their exceptional ionic conductivity being on the same scale as liquid electrolytes. Since sodium ions in the crystal lattice move among interstitial positions through site-specific bottlenecks, the overall conductivity is strongly dependent on the NASICON composition. In this work, we report on the synthesis protocols and processing parameters of Na3Zr2Si2PO12 prepared from Na2CO3, SiO2, ZrO2, and NH4H2PO4 precursors by the conventional solid-state reaction (SSR) route. We critically evaluated important observations made in the extended literature on the topic including: (i) the importance of precursor particle size concerning the SSR synthesis, focusing on effective ball-milling protocols; and (ii) the onset of excess zirconia contamination, expanding on the effects of both thermal and pressure processing—the latter often overlooked in the available literature. In approaching the cryogenic regime, the dataset availability concerning ionic conductivity and dielectric permittivity measurements for NASICON was extended, starting from elevated temperatures at 200 °C and reaching into the very low temperature zone at −100 °C.
Valorization of Rice Straw into Cellulose Microfibers for the Reinforcement of Thermoplastic Corn Starch Films
Authors: Freitas Pedro A. V. , Arias Carla I. La Fuente , Torres-Giner Sergio , González-Martínez Chelo , Chiralt Amparo
Published: September 2021

In the present study, agro-food waste derived rice straw (RS) was valorized into cellulose microfibers (CMFs) using a green process of combined ultrasound and heating treatments and were thereafter used to improve the physical properties of thermoplastic starch films (TPS). Mechanical defibrillation of the fibers gave rise to CMFs with cumulative frequencies of length and diameters below 200 and 5–15 µm, respectively. The resultant CMFs were successfully incorporated at, 1, 3, and 5 wt% into TPS by melt mixing and also starch was subjected to dry heating (DH) modification to yield TPS modified by dry heating (TPSDH). The resultant materials were finally shaped into films by thermo-compression and characterized. It was observed that both DH modification and fiber incorporation at 3 and 5 wt% loadings interfered with the starch gelatinization, leading to non-gelatinized starch granules in the biopolymer matrix. Thermo-compressed films prepared with both types of starches and reinforced with 3 wt% CMFs were more rigid (percentage increases of ~215% for TPS and ~207% for the TPSDH), more resistant to break (~100% for TPS and ~60% for TPSDH), but also less extensible (~53% for TPS and ~78% for TPSDH). The incorporation of CMFs into the TPS matrix at the highest contents also promoted a decrease in water vapor (~15%) and oxygen permeabilities (~30%). Finally, all the TPS composite films showed low changes in terms of optical properties and equilibrium moisture, being less soluble in water than the TPSDH films.
Deep Learning-Based Ground Target Detection and Tracking for Aerial Photography from UAVs
Authors: Wang Kaipeng , Meng Zhijun , Wu Zhe
Published: September 2021

Target detection and tracking can be widely used in military and civilian scenarios. Unmanned aerial vehicles (UAVs) have high maneuverability and strong concealment, thus they are very suitable for using as a platform for ground target detection and tracking. Most of the existing target detection and tracking algorithms are aimed at conventional targets. Because of the small scale and the incomplete details of the targets in the aerial image, it is difficult to apply the conventional algorithms to aerial photography from UAVs. This paper proposes a ground target image detection and tracking algorithm applied to UAVs using a revised deep learning technology. Aiming at the characteristics of ground targets in aerial images, target detection algorithms and target tracking algorithms are improved. The target detection algorithm is improved to detect small targets on the ground. The target tracking algorithm is designed to recover the target after the target is lost. The target detection and tracking algorithm is verified on the aerial dataset.
Image Splicing Location Based on Illumination Maps and Cluster Region Proposal Network
Authors: Zhu Ye , Shen Xiaoqian , Liu Shikun , Zhang Xiaoli , Yan Gang
Published: September 2021

Splicing is the most common operation in image forgery, where the tampered background regions are imported from different images. Illumination maps are inherent attribute of images and provide significant clues when searching for splicing locations. This paper proposes an end-to-end dual-stream network for splicing location, where the illumination stream, which includes Grey-Edge (GE) and Inverse-Intensity Chromaticity (IIC), extract the inconsistent features, and the image stream extracts the global unnatural tampered features. The dual-stream feature in our network is fused through Multiple Feature Pyramid Network (MFPN), which contains richer context information. Finally, a Cluster Region Proposal Network (C-RPN) with spatial attention and an adaptive cluster anchor are proposed to generate potential tampered regions with greater retention of location information. Extensive experiments, which were evaluated on the NIST16 and CASIA standard datasets, show that our proposed algorithm is superior to some state-of-the-art algorithms, because it achieves accurate tampered locations at the pixel level, and has great robustness in post-processing operations, such as noise, blur and JPEG recompression.
Aerosol–Cloud Interaction at the Summit of Mt. Fuji, Japan: Factors Influencing Cloud Droplet Number Concentrations
Authors: Iwamoto Yoko , Watanabe Ayami , Kataoka Ryota , Uematsu Mitsuo , Miura Kazuhiko
Published: September 2021

To investigate interactions between aerosols and clouds, the size and number concentrations of the cloud condensation nuclei (CCN) and the cloud droplets (CDs) were measured at the summit of Mt. Fuji (altitude 3776 m), Japan. The CCN number concentrations (NCCN) are significantly higher in continental air masses than in air masses from the Pacific Ocean. The hygroscopicity parameter κ did not change much for different air mass origins, indicating that aerosol particles in the free troposphere are well mixed. Based on the CD number concentrations (NCD), the degree of supersaturation in the ambient air during the cloud-shrouded period was estimated to be 0.15% (25th percentile) to 0.44% (75th percentile). To evaluate factors influencing the NCD, measured NCD were compared to ones calculated based on the Köhler theory using aerosol number size distributions, κ, and the degree of supersaturation. The results showed that NCD could not be reproduced satisfyingly when the mean number size distribution or the mean effective supersaturation were used for the calculation. This study highlights the importance of obtaining information about the degree of supersaturation to predict NCD in the atmosphere.
Dispersion of Carbon Nanotubes with Different Types of Superplasticizer as a Dispersing Agent for Self-Sensing Cementitious Materials
Authors: de Almeida Carísio Pedro , dos Santos Mendonça Yasmim Gabriela , Soares Carlos Fernando Teodósio , Reales Oscar Aurelio Mendoza , de Moraes Rego Fairbairn Eduardo , Filho Romildo Dias Toledo
Published: September 2021

Due to their exceptional electrical properties, carbon nanotubes (CNTs) can be applied as conductive fillers to develop self-sensing cement-based matrices. In order to obtain an adequate self-sensing response, CNTs must be evenly dispersed through the cement matrix in a volume sufficient enough to create an electric percolation network. This is challenged by the difficulty of dispersing CNTs; therefore, there is a demand for an efficient dispersing agent that can be filled by superplasticiezers, which are products of known compatibility with cement and high availability. This research explores the use of four commercial superplasticizers available in Brazil, both naphthalene and ether polycarboxylate-based, as dispersing agents for CNTs in water. Ultrasonic energy was applied to aqueous solutions containing CNTs and superplasticizers. UV–Vis spectroscopy and ξ-potential measurements were used to investigate which superplasticizer was more effective to disperse the CNTs. Cement pastes were produced with the CNT dispersions and their electrical resistivity was measured. It was found that only superplasticizers without aliphatic groups in their structure were capable of dispersing CNTs in water. It was concluded that second-generation naphthalene-based superplasticizers were more efficient dispersing agents for CNTs than third-generation ether polycarboxylate-based ones for self-sensing applications.
Medical Robotic Bed to Prevent Pressure Sores
Authors: Seon Minju , Lee Youngdae , Moon Chanwoo
Published: September 2021

Patients who stay in bed for long periods are prone to pressure sores. Pressure sores cause multiple complications and prolong hospitalization. To prevent pressure sores, the patient’s lying position must be changed continuously so that excessive pressure on any body part does not last long. In this paper, we propose a novel robotic bed to prevent the formation of pressure sores. This robotic bed is composed of multiple segments that are driven independently by brushless direct current motors and that use body pressure information for feedback control. By controlling the movement of the segments on the top of the bed with a fuzzy controller, the patient’s body pressure is kept below the reference value. Moreover, a belt-type body pressure sensor is developed herein by using force-sensing resistor technology to measure the patient’s body pressure. A bed control system composed of the main controller, a teach pendant, motor controllers, and sensors was implemented. Through real experiments, the validity of the proposed robot bed was verified, and it was confirmed that the fuzzy closed-loop controller followed the reference body pressure commands well.
Equal Baseline Camera Array—Calibration, Testbed and Applications
Authors: Kaczmarek Adam L. , Blaschitz Bernhard
Published: September 2021

This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative to other 3D imaging equipment such as Structured-light 3D scanners or Light Detection and Ranging (LIDAR). The considered kinds of arrays are called Equal Baseline Camera Array (EBCA). This paper presents a novel approach to calibrating the array based on the use of self-calibration methods. This paper also introduces a testbed which makes it possible to develop new algorithms for obtaining 3D data from images taken by the array. The testbed was released under open-source. Moreover, this paper shows new results of using these arrays with different stereo matching algorithms including an algorithm based on a convolutional neural network and deep learning technology.
Metal Binding and Sources of Humic Substances in Recent Sediments from the Cananéia-Iguape Estuarine-Lagoon Complex (South-Eastern Brazil)
Authors: Millo Christian , Bravo Carlo , Covelli Stefano , Pavoni Elena , Petranich Elisa , Contin Marco , De Nobili Maria , Crosera Matteo , Otero Sutti Bruno , das Mercês Silva Camila , de Santis Braga Elisabete
Published: September 2021

The Cananéia-Iguape estuarine–lagoon complex (São Paulo state, Brazil) is a natural laboratory to study metal binding by humic substances (HS) in subtropical settings. This transitional environment is evolving into a freshwater environment due to water input from the Ribeira River, funneled through the Valo Grande Canal (Iguape). Past mining activities in the Ribeira River basin and maritime traffic are suspected to be potential sources of trace metals in the system. In this study, the trace metal contents of Free Humic Acids (FHA), Bound Humic Acids (BHA), and Fulvic Acids (FA) extracted from sedimentary organic matter were investigated. Moreover, the sources of HS were traced using their stable carbon isotope compositions and C/N ratios. The results suggested a mixed marine–terrestrial source of FHA, BHA, and FA. Copper and Cr were the most abundant trace metals bound to HS. On average, Cu showed concentrations of 176, 115, and 37.9 μg g−1 in FHA, BHA, and FA, respectively, whereas Cr showed average concentrations of 47.4, 86.3, and 43.9 μg g−1 in FHA, BHA, and FA, respectively. Marine FHA showed the highest binding capacity for trace metals, whereas terrestrial FA derived from the decay of mangrove organic matter showed the lowest binding capacity.
Incorporation of Shipping Activity Data in Recurrent Neural Networks and Long Short-Term Memory Models to Improve Air Quality Predictions around Busan Port
Authors: Hong Hyunsu , Jeon Hyungjin , Youn Cheong , Kim Hyeonsoo
Published: September 2021

Air pollution sources and the hazards of high particulate matter 2.5 (PM2.5) concentrations among air pollutants have been well documented. Shipping emissions have been identified as a source of air pollution; therefore, it is necessary to predict air pollutant concentrations to manage seaport air quality. However, air pollution prediction models rarely consider shipping emissions. Here, the PM2.5 concentrations of the Busan North and Busan New Ports were predicted using a recurrent neural network and long short-term memory model by employing the shipping activity data of Busan Port. In contrast to previous studies that employed only air quality and meteorological data as input data, our model considered shipping activity data as an emission source. The model was trained from 1 January 2019 to 31 January 2020 and predictions and verifications were performed from 1–28 February 2020. Verifications revealed an index of agreements (IOA) of 0.975 and 0.970 and root mean square errors of 4.88 and 5.87 µg/m3 for Busan North Port and Busan New Port, respectively. Regarding the results based on the activity data, a previous study reported an IOA of 0.62–0.84, with a higher predictive power of 0.970–0.975. Thus, the extended approach offers a useful strategy to prevent PM2.5 air pollutant-induced damage in seaports.
A Systematic Review of Unexplained Early Regression in Adolescents and Adults with Down Syndrome
Authors: Walpert Madeleine , Zaman Shahid , Holland Anthony
Published: September 2021

A proportion of young people with Down syndrome (DS) experience unexplained regression that severely impacts on their daily lives. While this condition has been recognised by clinicians, there is a limited understanding of causation and an inconsistent approach to diagnosis and treatment. Varied symptomology and little knowledge of the cause of this regression have impacted on clinician’s ability to prevent or manage this condition. The purpose of this review was to examine the current evidence surrounding unexplained regression in adolescents and young adults, and to establish patterns that may be of use to clinicians, as well as raising awareness of this condition. Four areas were specifically reviewed, (1) terminology used to refer to this condition, (2) the symptoms reported, (3) potential trigger events and, (4) treatments and prognosis. A variety of terminology is used for this condition, which has constrained past attempts to identify patterns. An extensive number of symptoms were reported, however sleep impairment, loss of language and distinct changes in personality and behaviour, such as disinterest and withdrawal, were among the most frequently seen. Life events that were tentatively associated with the onset of a regressive period included a significant change in environmental circumstances or a transition, such as moving home or leaving school. Prognosis for this condition is relatively positive with the majority of individuals making at least a partial recovery. However, few patients were found to make a full recovery to their previous level of functioning and serious adverse effects could persist in those who have made a partial recovery. This is an under-researched condition with significant impacts on people with DS and their families. There are no established treatments for this condition and there is relatively little recognition in the research community. Further studies that focus on the prevention and treatment of this condition with controlled treatment trials are needed.
The Effect of Waste Plant Oil on the Composition and Micro-Morphological Properties of Old Asphalt Composition
Authors: Suo Zhi , Nie Lei , Xiang Fanrong , Bao Xu
Published: September 2021

At present, the regeneration agent with mineral oil as the main component is widely used. However, its strong volatility, nonrenewability, and other shortcomings restrict the development of regeneration technology. In this study, waste vegetable oil was used as the main component of the regeneration agent to prepare regenerated aging asphalt. The change in microstructure of aging asphalt was explored with the change in waste vegetable oil content and regeneration time. The results showed that the addition of waste vegetable oil could effectively supplement the contents of saturates and aromatics, and inhibit the oxidation of saturates and aromatics into asphaltene and resin. When the regeneration time was 60 min and the regeneration content was 7.0%, the effect was best. The correlation between the component composition of regenerated aging asphalt and the micro-morphological characteristics was in the order of saturates, asphaltene, resin, and aromatics.
Incorporation of Bi2O3 Residuals with Metallic Bi as High Performance Electrocatalyst toward Hydrogen Evolution Reaction
Authors: Syah Rahmad , Ahmad Awais , Davarpanah Afshin , Elveny Marischa , Ramdan Dadan , Albaqami Munirah D. , Ouladsmane Mohamed
Published: September 2021

Nanostructured Bismuth-based materials are promising electrodes for highly efficient electrochemical reduction processes such as hydrogen evolution reaction (HER). In this work, a novel sort of nanocomposite made up of partially reduced Bi2O3 into metallic Bi anchored on a 3D network of Ni-foam as a high-performance catalyst for electrochemical hydrogen reduction. The application of the hybrid material for HER is shown. The high catalytic activity of the fabricated electrocatalyst arises from the co-operative effect of Bi/Bi2O3 and Ni-foam which provides a highly effective surface area combined with the highly porous structure of Ni-foam for efficient charge and mass transport. The advantages of the electrode for the electrochemical reduction processes such as high current density, low overpotential, and high stability of the electrode are revealed. An overall comparison of our as-prepared electrocatalyst with recently reported works on related work is done.
Drosophila Accessory Gland: A Complementary In Vivo Model to Bring New Insight to Prostate Cancer
Authors: Rambur Amandine , Vialat Marine , Beaudoin Claude , Lours-Calet Corinne , Lobaccaro Jean-Marc , Baron Silvère , Morel Laurent , de Joussineau Cyrille
Published: September 2021

Prostate cancer is the most common cancer in aging men. Despite recent progress, there are still few effective treatments to cure its aggressive and metastatic stages. A better understanding of the molecular mechanisms driving disease initiation and progression appears essential to support the development of more efficient therapies and improve patient care. To do so, multiple research models, such as cell culture and mouse models, have been developed over the years and have improved our comprehension of the biology of the disease. Recently, a new model has been added with the use of the Drosophila accessory gland. With a high level of conservation of major signaling pathways implicated in human disease, this functional equivalent of the prostate represents a powerful, inexpensive, and rapid in vivo model to study epithelial carcinogenesis. The purpose of this review is to quickly overview the existing prostate cancer models, including their strengths and limitations. In particular, we discuss how the Drosophila accessory gland can be integrated as a convenient complementary model by bringing new understanding in the mechanisms driving prostate epithelial tumorigenesis, from initiation to metastatic formation.
Dendritic Spine Initiation in Brain Development, Learning and Diseases and Impact of BAR-Domain Proteins
Authors: Khanal Pushpa , Hotulainen Pirta
Published: September 2021

Dendritic spines are small, bulbous protrusions along neuronal dendrites where most of the excitatory synapses are located. Dendritic spine density in normal human brain increases rapidly before and after birth achieving the highest density around 2–8 years. Density decreases during adolescence, reaching a stable level in adulthood. The changes in dendritic spines are considered structural correlates for synaptic plasticity as well as the basis of experience-dependent remodeling of neuronal circuits. Alterations in spine density correspond to aberrant brain function observed in various neurodevelopmental and neuropsychiatric disorders. Dendritic spine initiation affects spine density. In this review, we discuss the importance of spine initiation in brain development, learning, and potential complications resulting from altered spine initiation in neurological diseases. Current literature shows that two Bin Amphiphysin Rvs (BAR) domain-containing proteins, MIM/Mtss1 and SrGAP3, are involved in spine initiation. We review existing literature and open databases to discuss whether other BAR-domain proteins could also take part in spine initiation. Finally, we discuss the potential molecular mechanisms on how BAR-domain proteins could regulate spine initiation.
Application of ALD Thin Films on the Surface of the Surgical Scalpel Blade
Authors: Szindler Magdalena , Szindler Marek , Basiaga Marcin , Łoński Wojciech , Kaim Paulina
Published: September 2021

The article describes biomaterials and surgical instruments, in particular surgical cutting tools. In addition, the functions of coatings and the layer vapor deposition methods are described. In the experimental component of the study, zinc oxide thin film was deposited on the surgical knife blades by the atomic layer deposition (ALD) method with a varying number of cycles. The structures of the deposited thin films were investigated using a Raman spectrometer and the surface topography of the samples was examined using atomic force microscopy and scanning electron microscopy. The adhesion of the thin films was tested using the micro-scratch method. The corrosion resistance was also tested. Surgical instruments coated with non-allergenic metal oxide coatings, containing metal structures that reduce the growth of bacteria, could significantly decrease the risk of undesirable reactions of the body during and after surgery.
Nature Has No Elementary Particles and Makes No Measurements or Predictions: Quantum Measurement and Quantum Theory, from Bohr to Bell and from Bell to Bohr
Authors: Plotnitsky Arkady
Published: September 2021

This article reconsiders the concept of physical reality in quantum theory and the concept of quantum measurement, following Bohr, whose analysis of quantum measurement led him to his concept of a (quantum) “phenomenon,” referring to “the observations obtained under the specified circumstances,” in the interaction between quantum objects and measuring instruments. This situation makes the terms “observation” and “measurement,” as conventionally understood, inapplicable. These terms are remnants of classical physics or still earlier history, from which classical physics inherited it. As defined here, a quantum measurement does not measure any preexisting property of the ultimate constitution of the reality responsible for quantum phenomena. An act of measurement establishes a quantum phenomenon by an interaction between the instrument and the quantum object or in the present view the ultimate constitution of the reality responsible for quantum phenomena and, at the time of measurement, also quantum objects. In the view advanced in this article, in contrast to that of Bohr, quantum objects, such as electrons or photons, are assumed to exist only at the time of measurement and not independently, a view that redefines the concept of quantum object as well. This redefinition becomes especially important in high-energy quantum regimes and quantum field theory and allows this article to define a new concept of quantum field. The article also considers, now following Bohr, the quantum measurement as the entanglement between quantum objects and measurement instruments. The argument of the article is grounded in the concept “reality without realism” (RWR), as underlying quantum measurement thus understood, and the view, the RWR view, of quantum theory defined by this concept. The RWR view places a stratum of physical reality thus designated, here the reality ultimately responsible for quantum phenomena, beyond representation or knowledge, or even conception, and defines the corresponding set of interpretations quantum mechanics or quantum field theory, such as the one assumed in this article, in which, again, not only quantum phenomena but also quantum objects are (idealizations) defined by measurement. As such, the article also offers a broadly conceived response to J. Bell’s argument “against ‘measurement’”.
Estimating SDG Indicators in Data-Scarce Areas: The Transition to the Use of New Technologies and Multidisciplinary Studies
Authors: Alamanos Angelos , Linnane Suzanne
Published: September 2021

The Sustainable Development Goals (SDGs) and their indicators provide opportunities to best combine the available knowledge and data to monitor and estimate different metrics and track their progress. The overall picture can be complex as some indicators are often interconnected (e.g., rural and/or urban development with a water body’s status). Two factors can play a crucial role in achieving the SDGs: the use of new technologies for database building and multidisciplinary studies and understanding. This study aims to explore these factors, highlight their importance and provide an example as guidance of their proper and combinative use. Ireland is used as an example of a data-scarce case with poor–slow progress, especially on the environmental SDGs. Two “non-reported” SDG indicators (lack of data) are selected and estimated in this work using freely available data (remote sensing, satellite imagery) and geospatial software for the first time in the country. The results show improvements in rural and urban development; however, this is accompanied by negative environmental consequences. A more holistic approach is needed and a broader conceptual model is presented to avoid any misleading interpretations of the study of SDGs. The transition to the modern technological and multidisciplinary evolution requires respective knowledge and understanding, strongly based on complex systems analysis.
Electrodeposition of Cu-Mn Films as Precursor Alloys for the Synthesis of Nanoporous Cu
Authors: Castillo Ezer , Dimitrov Nikolay
Published: September 2021

Cu-Mn alloy films are electrodeposited on Au substrates as precursor alloys for the synthesis of fine-structured nanoporous Cu structures. The alloys are deposited galvanostatically in a solution containing ammonium sulfate, (NH4)2SO4, which serves as a source of the ammine ligand that complexes with Cu, thereby decreasing the inherent standard reduction potential difference between Cu and Mn. The formation of the [Cu(NH3)n]2+ complex was confirmed by UV-Vis spectroscopic and voltammetric studies. Galvanostatic deposition at current densities ranging from 100 to 200 mA⋅cm−2 generally resulted in the formation of type I, crystalline coatings as revealed by scanning electron microscopy. Although the deposition current efficiency is (<30%) generally low, the atomic composition (determined by energy dispersive X-ray spectroscopy) of the deposited alloys range from 70–85 at% Mn, which is controlled by simply adjusting the ratio of the metal ion concentrations in the deposition bath. Anodic stripping characterization revealed a three-stage dissolution of the deposited alloys, which suggests control over the selective removal of Mn. The composition of the alloys obtained in the studies are ideal for electrochemical dealloying to form nanoporous Cu.
On the General Solutions of Some Non-Homogeneous Div-Curl Systems with Riemann–Liouville and Caputo Fractional Derivatives
Authors: Delgado Briceyda B. , Macías-Díaz Jorge E.
Published: September 2021

In this work, we investigate analytically the solutions of a nonlinear div-curl system with fractional derivatives of the Riemann–Liouville or Caputo types. To this end, the fractional-order vector operators of divergence, curl and gradient are identified as components of the fractional Dirac operator in quaternionic form. As one of the most important results of this manuscript, we derive general solutions of some non-homogeneous div-curl systems that consider the presence of fractional-order derivatives of the Riemann–Liouville or Caputo types. A fractional analogous to the Teodorescu transform is presented in this work, and we employ some properties of its component operators, developed in this work to establish a generalization of the Helmholtz decomposition theorem in fractional space. Additionally, right inverses of the fractional-order curl, divergence and gradient vector operators are obtained using Riemann–Liouville and Caputo fractional operators. Finally, some consequences of these results are provided as applications at the end of this work.
Factors Associated with Volunteer Activities and Sleep Efficiency in Older Adults with Hypertension: A Sequential Model Study
Authors: Aonuma Ryoko , Mayers Thomas , Mizukami Katsuyoshi , Aonuma Kazutaka , Matsuda Hitomi
Published: September 2021

The purpose of this study was to examine, using a sequential model, factors associated with volunteer participation and sleep efficiency in Japanese older adults receiving treatment for hypertensive disease. A questionnaire survey was conducted to collect data on participant demographics, lifestyle, health status, and depression, and sleep activity monitors were used to objectively measure sleep status and sleep efficacy. Of the 167 respondents, the 59 being treated for hypertension were divided into two groups based on their participation in volunteering. Comparison between the groups showed significant differences in nocturnal awakening, sleep efficiency, and nap frequency. Volunteers had less nocturnal awakening, increased sleep efficiency, fewer naps, and decreased depression. Covariance structure analysis of the survey data and sleep measurements for hypertensive older adults in the volunteer group was performed by modeling the relationships between variables with a path diagram. Our model showed strong goodness of fit (χ2 test = 15.636, p = 0.111, GFI = 0.925, AGFI = 0.842, CFI = 0.925, RMSEA = 0.099). The findings of this study suggest that older adults with hypertension who participate in volunteer activities have less nocturnal awakening, improved sleep quality, and reduced risk of depression, and provides evidence to promote social participation in volunteering among older adults with hypertension.
Theoretical Prediction of the Efficiency of Hydrogen Production via Alkane Dehydrogenation in Catalytic Membrane Reactor
Authors: Shelepova Ekaterina V. , Vedyagin Aleksey A.
Published: September 2021

The hydrogen economy is expected to dominate in the nearest future. Therefore, the most hydrogen-containing compounds are considered as potential pure hydrogen sources in order to achieve climate neutrality. On the other hand, alkanes are widely used to produce industrially important monomers via various routes, including dehydrogenation processes. Hydrogen is being produced as a by-product of these processes, so the application of efficient separation of hydrogen from the reaction mixture can give double benefits. Implementation of the dehydrogenation processes in the catalytic membrane reactor is that case. Since the use of dense metal membranes, which possess the highest perm-selectivity towards hydrogen, is complicated in practice, the present research is aimed at the optimization of the porous membrane characteristics. By means of a mathematical modeling approach, the effects of pore diameter on the hydrogen productivity and purity for the cases of ethane and propane dehydrogenation processes were analyzed. The pore size value of 0.45 nm was found to be crucial as far as the diffusion of both the alkane and alkene molecules through the membrane takes place.
The Influence of Government Shareholding on Dividend Policy in Malaysia
Authors: Sinnadurai Philip , Subramaniam Ravichandran , Devi Susela
Published: September 2021

We investigate the association between dividend policy and government shareholding, using Malaysian data. We hypothesize a positive association. We contribute to the literature about dividend policy. Unique features of our study include adaptations to the Malaysian institutional setting, with respect to usage of dividend relevance theory, research methodology, and data collection. The methodology entails two-stage least squares regressions. Dividend payout and dividend yield are the dependent variables in tests of the research hypothesis. The independent variable of interest measures ownership by government-related institutional investors. The sample comprises 1190 company-years, over the investigation period 2006–2013. The results support our hypothesis. The evidence suggests that this support principally emanates from companies with low-quality corporate governance.
Geospatial Analysis and Mapping Strategies for Fine-Grained and Detailed COVID-19 Data with GIS
Authors: Carballada Angel Miramontes , Balsa-Barreiro Jose
Published: September 2021

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.
Defining the Thermal Features of Sub-Surface Reinforcing Fibres in Non-Polluting Thermo–Acoustic Insulating Panels: A Numerical–Thermographic–Segmentation Approach
Authors: Liu Kaixin , Perilli Stefano , Chulkov Arsenii O. , Yao Yuan , Omar Mohammed , Vavilov Vladimir , Liu Yi , Sfarra Stefano
Published: September 2021

Natural fibres present ozone-friendly solutions in the field of construction. The attenuation of the sound and heat losses is an important feature in such type of materials above all, when used in non-woven fabrics and fibre-reinforced composites. Hemp fibres show robust insulation performance; this research work should be considered beneficial to the development of a non-destructive thermographic methodology, which can address the thermal barrier (typically applied on multi-layer panel) effects. The intent is to assess the integrity of the sub-surface reinforcing glass fibres; such integrity state will help confer the rigidity and the resistance to mechanical stresses. The testing proposed in this study can be further developed in a laboratory right after the manufacturing process of similar type of components. The testing needs preliminary numerical simulations to help guide the selection of the appropriate pre- and post-processing algorithms combined with or without segmentation operators. A set of numerical and experimental tests were performed through controlled thermal stimulation while recording the thermal responses. The study also highlights the advantages, disadvantages, and future development of the presented technique and methodologies.
Aedes Mosquito Distribution along a Transect from Rural to Urban Settings in Yaoundé, Cameroon
Authors: Djiappi-Tchamen Borel , Nana-Ndjangwo Mariette Stella , Tchuinkam Timoléon , Makoudjou Idene , Nchoutpouen Elysée , Kopya Edmond , Talipouo Abdou , Bamou Roland , Mayi Marie Paul Audrey , Awono-Ambene Parfait , Wondji Charles , Antonio-Nkondjio Christophe
Published: September 2021

Introduction: The surveillance of mosquito vectors is important for the control of arboviruses diseases worldwide. Detailed information on the bionomics and distribution of their main vectors, Aedes aegypti and Aedes albopictus, is essential for assessing disease transmission risk and for better planning of control interventions. Methods: Entomological surveys were carried out from November 2019 to November 2020 in six localities of Yaoundé city following a transect from urban to rural settings: two urban (Obili, Mvan), two peri-urban (Simbock, Ahala) and two rural areas (Lendom, Elig-essomballa)—during rainy and dry seasons. All water containers were inspected. Aedes mosquito abundance, species distribution and seasonal distribution patterns were compared using generalized linear models. Stegomyia indexes were estimated to determine the risk of arbovirus transmission. Results: A total of 6332 mosquitoes larvae were collected (2342 in urban areas, 1694 in peri-urban areas and 2296 in rural sites). Aedes species recorded included Ae. albopictus, Ae. aegytpi, Ae. simpsoni and Aedes spp. High mosquito abundance was registered in the rainy season (4706) compared to the dry season (1626) (p < 0.0001). Ae. albopictus was the most abundant Aedes species in urban (96.89%) and peri-urban (95.09%) sites whereas Ae. aegypti was more prevalent in rural sites (68.56%) (p < 0.0001). Both species were found together in 71 larval habitats. Ae. albopictus was mostly found in discarded tires (42.51%), whereas Ae. aegypti was more prevalent in plastic containers used for storing water (65.87%). The majority of Aedes mosquitoes’ breeding places were situated close to human dwellings (0–10 m). Conclusion: Uncontrolled urbanization seems to greatly favour the presence of Aedes mosquito species around human dwellings in Yaoundé. Controlling Aedes mosquito distribution is becoming urgent to reduce the risk of arbovirus outbreaks in the city of Yaoundé.
On the Electrochemical Migration Mechanism of Gold in Electronics—Less Reliable Than Expected?
Authors: Medgyes Bálint , Gharaibeh Ali , Rigler Dániel , Harsányi Gábor
Published: September 2021

Electrochemical migration (ECM) forming dendritic short circuits is a major reliability limiting factor in microcircuits. Gold, which is a noble metal, has been regarded as a metallization that can withstand corrosion and also ECM, therefore its application in high-reliability metallization and surface finishing systems became widespread although it has a relatively high and fluctuating price. Gold electrochemical short circuits have been found only in the case of halogen (e.g., chloride containing) contaminants that can initiate the anodic dissolution of gold via complex ion formation. The experimental results of the study demonstrate that gold can form dendritic shorts even without the presence of halogen contaminants, therefore the direct anodic dissolution of gold must also be supposed. This could also be a serious reliability influencing factor even when applying gold metallization systems and must be taken into consideration. The theoretical background of the classical (contaminant-free) model of gold is also discussed in the paper.
Theory of Functional Connections Applied to Linear ODEs Subject to Integral Constraints and Linear Ordinary Integro-Differential Equations
Authors: De Florio Mario , Schiassi Enrico , D’Ambrosio Andrea , Mortari Daniele , Furfaro Roberto
Published: September 2021

This study shows how the Theory of Functional Connections (TFC) allows us to obtain fast and highly accurate solutions to linear ODEs involving integrals. Integrals can be constraints and/or terms of the differential equations (e.g., ordinary integro-differential equations). This study first summarizes TFC, a mathematical procedure to obtain constrained expressions. These are functionals representing all functions satisfying a set of linear constraints. These functionals contain a free function, g(x), representing the unknown function to optimize. Two numerical approaches are shown to numerically estimate g(x). The first models g(x) as a linear combination of a set of basis functions, such as Chebyshev or Legendre orthogonal polynomials, while the second models g(x) as a neural network. Meaningful problems are provided. In all numerical problems, the proposed method produces very fast and accurate solutions.
Relation between Alpha-Synuclein and Core CSF Biomarkers of Alzheimer’s Disease
Authors: Monge-García Victoria , García-Ayllón María-Salud , Sáez-Valero Javier , Sánchez-Payá José , Navarrete-Rueda Francisco , Manzanares-Robles Jorge , Gasparini-Berenguer Ruth , Romero-Lorenzo Raquel , Cortés-Gómez María Angeles , Monge-Argilés José-Antonio
Published: September 2021

Background: Alzheimer’s disease (AD) is characterized by the presence of β-amyloid plaques and neurofibrillary tangles, while Lewy body dementia (LBD) is characterized by α-synuclein (α-syn) inclusions. Some authors examine α-syn protein in the neurodegeneration process of AD and propose to consider cerebrospinal fluid (CSF) α-syn as a possible additional biomarker to the so-called “core” of AD. Objective: To determine whether there is a correlation between α-syn levels and “core” AD biomarkers in patients with mild cognitive impairment (MCI). Materials and methods: In total, 81 patients in the early stages of MCI were selected from the outpatient dementia consultation in Alicante General Hospital. Using a cross-sectional case–control design, patients were analyzed in four groups: stable MCI (MCIs; n = 25), MCI due to AD (MCI-AD; n = 32), MCI due to LBD (MCI-LBD; n = 24) and a control group of patients with acute or chronic headache (Ctrl; n = 18). Correlation between CSF protein levels in the different groups was assessed by the Rho Spearman test. Results: We found positive correlations between T-tau protein and α-syn (ρ = 0.418; p value < 0.05) and p-tau181p and α-syn (ρ = 0.571; p value < 0.05) exclusively in the MCI-AD group. Conclusion: The correlation found between α-syn and tau proteins in the first stages of AD support the involvement of α-syn in the pathogenesis of AD. This result may have clinical and diagnostic implications, as well as help to apply the new concept of “precision medicine” in patients with MCI.
Assessment of the Impact of Alcohol Consumption Patterns on Heart Rate Variability by Machine Learning in Healthy Young Adults
Authors: Pop Gheorghe Nicusor , Christodorescu Ruxandra , Velimirovici Dana Emilia , Sosdean Raluca , Corbu Miruna , Bodea Olivia , Valcovici Mihaela , Dragan Simona
Published: September 2021

Background and Objectives: Autonomic nervous system (ANS) dysfunction is present in early stages of alcohol abuse and increases the likelihood of cardiovascular events. Given the nonlinear pattern of dynamic interaction between sympathetic nervous system (SNS) and para sympathetic nervous system (PNS) and the complex relationship with lifestyle factors, machine learning (ML) algorithms are best suited for analyzing alcohol impact over heart rate variability (HRV), because they allow the analysis of complex interactions between multiple variables. This study aimed to characterize autonomic nervous system dysfunction by analysis of HRV correlated with cardiovascular risk factors in young individuals by using machine learning. Materials and Methods: Total of 142 young adults (28.4 ± 4.34 years) agreed to participate in the study. Alcohol intake and drinking patterns were assessed by the AUDIT (Alcohol Use Disorders Identification Test) questionnaire and the YAI (Yearly Alcohol Intake) index. A short 5-min HRV evaluation was performed. Post-hoc analysis and machine learning algorithms were used to assess the impact of alcohol intake on HRV. Results: Binge drinkers presented slight modification in the frequency domain. Heavy drinkers had significantly lower time-domain values: standard deviation of RR intervals (SDNN) and root mean square of the successive differences (RMSSD), compared to casual and binge drinkers. High frequency (HF) values were significantly lower in heavy drinkers (p = 0.002). The higher low-to-high frequency ratio (LF/HF) that we found in heavy drinkers was interpreted as parasympathetic inhibition. Gradient boosting machine learner regression showed that age and alcohol consumption had the biggest scaled impact on the analyzed HRV parameters, followed by smoking, anxiety, depression, and body mass index. Gender and physical activity had the lowest impact on HRV. Conclusions: In healthy young adults, high alcohol intake has a negative impact on HRV in both time and frequency-domains. In parameters like HRV, where a multitude of risk factors can influence measurements, artificial intelligence algorithms seem to be a viable alternative for correct assessment.