bluuebunny/crossref_metadata_2025 huggingface dataset:
AI-Based Quality Control of Wood Surfaces with Autonomous Material Handling
Authors: Ericsson Mikael , Johansson Dahniel , Stjern David
Published: October 2021

The theory and applications of Smart Factories and Industry 4.0 are increasing the entry into the industry. It is common in industry to start converting exclusive parts, of their production, into this new paradigm rather than converting whole production lines all at once. In Europe and Sweden, recent political decisions are taken to reach the target of greenhouse gas emission reduction. One possible solution is to replace concrete in buildings with Cross Laminated Timber. In the last years, equipment and software that have been custom made for a certain task, are now cheaper and can be adapted to fit more processes than earlier possible. This in combination, with lessons learned from the automotive industry, makes it possible to take the necessary steps and start redesigning and building tomorrows automated and flexible production systems in the wood industry. This paper presents a proof of concept of an automated inspection system, for wood surfaces, where concepts found in Industry 4.0, such as industrial Internet of things (IIoT), smart factory, flexible automation, artificial intelligence (AI), and cyber physical systems, are utilized. The inspection system encompasses, among other things, of the shelf software and hardware, open source software, and standardized, modular, and mobile process modules. The design of the system is conducted with future expansion in mind, where new parts and functions can be added as well as removed.
Single-Shot Temporal Contrast Enhancement Measurement of a Plasma Mirror by a Chirped Pulse
Authors: Zhang Dongjun , Zhu Ping , Xie Xinglong , Liang Yan , Yang Qingwei , Sun Meizhi , Liang Xiao , Kang Jun , Zhu Haidong , Guo Ailin , Gao Qi , Yi Youjian , Li Linjun , Liu Cheng , Zhu Jianqiang
Published: October 2021

We focused on a single-shot method for directly measuring the temporal contrast enhancement of a single plasma mirror by analyzing the spectrum of a chirped pulse spatiotemporally overlapped with the igniting laser used for generating a plasma mirror. Experimentally, temporal contrast enhancement of 102 by one plasma mirror was successfully measured in a hundred picosecond timescale and was consistent with the theory. This single-shot measurement method caused no degradation on the performance of the plasma mirror, which was proved by monitoring the efficiency and far-field pattern of the igniting laser after the plasma mirror. Combined with calorimeters and CCD cameras, this method is expected to realize the single-shot online diagnosis of plasma mirrors. This method is expected to be an efficient approach for measuring the temporal contrast enhancement of the plasma mirrors.
Association of Posture, Gait, and Auditory Functioning with Cognitive Status in a Cohort of Community-Dwelling Older Adults
Authors: Kostic Emilija , Kwak Kiyoung , Kim Dongwook
Published: October 2021

Postural stability, hearing, and gait function deterioration are the risk factors associated with cognitive impairment. Although no method has been reported for treating severe cognitive impairment to date, developing an early detection model based on these risk factors could aid in slowing down or even reversing the deterioration process. In this study, the association between cognitive impairment and the combined predictive ability of sensory and gait features was assessed. Fifty-seven healthy community-dwelling men over the age of sixty-five participated in cognitive, postural stability, auditory, and level walking evaluations. They were divided into two groups: healthy control group (n = 39) and lower cognition group (n = 18), based on their Montreal cognitive assessment score. During gait, the center of mass of the cognitively impaired participants was confined to a smaller volume. Furthermore, the cognitively healthy participants were found to have better postural stability. Both groups possessed similar hearing ability; however, the cognitively impaired group made a significantly higher number of errors when repeating words or sentences. A logistic regression model utilizing each of these function quantifiers exhibited a high area under the receiver operating characteristic curve, suggesting excellent predictive ability. These models can be applied to smartphone or smart home healthcare technologies to detect the possibility of cognitive impairment, thus facilitating early detection.
Facile Synthesis of Copper Oxide-Cobalt Oxide/Nitrogen-Doped Carbon (Cu2O-Co3O4/CN) Composite for Efficient Water Splitting
Authors: Shaikh Zaffar Ahmed , Moiseev Nikita , Mikhaylov Alexey , Yüksel Serhat
Published: October 2021

Herein, we report a copper oxide-cobalt oxide/nitrogen-doped carbon hybrid (Cu2O-Co3O4/CN) composite for electrochemical water splitting. Cu2O-Co3O4/CN is synthesized by an easy two-step reaction of melamine with Cu2O-Co3O4/CN composite. The designed composite is aimed to solve energy challenges by producing hydrogen and oxygen via electrochemical catalysis. The proposed composite offers some unique advantages in water splitting. Carbon imparts superior conductivity, while the water oxidation abilities of Cu2O and Co3O4 are considered to constitute a catalyst. The synthesized composite (Cu2O-Co3O4/CN) is characterized by SEM, EDS, FTIR, TEM, and AFM in terms of the size, morphology, shape, and elemental composition of the catalyst. The designed catalyst’s electrochemical performance is evaluated via linear sweep voltammetry (LSV) and cyclic voltammetry (CV). The Cu2O-Co3O4/CN composite shows significant electrocatalytic activity, which is further improved by introducing nitrogen doped carbon (current density 10 mA cm−2, onset potential 91 mV, and overpotential 396 mV).
IoT Blockchain Data Veracity with Data Loss Tolerance
Authors: Moke Kwai Cheong , Low Tan Jung , Khan Dodo
Published: October 2021

Recent years have witnessed the advancement of the Internet of Things (IoT) and its emergence as a technology that could revolutionize many businesses. It helps considerably in creating data-driven business models with the insights it provides. IoT systems are deployed in data collection, monitor processes, provide insights and allow businesses to make data-driven productivity improvements. However, IoT systems are often experiencing data loss due to inevitable failures ranging from devices, networks, to the application layer, especially in scarce infrastructure resources environments. Data loss might be unrecoverable in many circumstances. As such, this research presents a blockchain based IoT model (framework) with the aim of circumventing data loss. We envisioned IoT blockchain technology in enhancing data veracity with data loss tolerance. That is, to have blockchain enhancing the IoT data veracity by leveraging on the features existed in its peer-to-peer network (P2P) and distributed ledger storage technology (DLT). Additionally, the edge computing of IoT blockchain technology is also conceptually workable; with intelligent small computing resources, it opens up a new era of bringing the intelligence of data collection, connectivity, computation and storage into the edge/device layer. A novel IoT blockchain strength monitoring system is also been studied to further enhance data veracity; this is achieved through a capacitance monitoring on the IoT blockchain system. The empirical results show that the proposed IoT blockchain with a strength monitoring model can alleviate data loss and thus enhance data veracity with data loss tolerance.
Response Analysis of the Tristable Energy Harvester with an Uncertain Parameter
Authors: Zhang Ying , Duan Xiaxia , Shi Yu , Yue Xiaole
Published: October 2021

In the stage of modelling, measuring, mechanical processing and manufacturing of the nonlinear energy harvesting system, deviations and errors of system parameters are inevitable. Even slight variation of key parameters may have a significant influence on the output voltages, especially for the multi-stable nonlinear case. Therefore, the investigation of dynamic behaviors for the tristable energy harvesting system with uncertain parameters is of important value both for research and application. In this paper, the uncertainty of a tristable piezoelectric vibration energy harvester with a random coefficient ahead of the nonlinear term is studied. By using the Chebyshev polynomial approximation, this tristable energy harvesting system is first reduced into an equivalent deterministic form, the ensemble mean responses of which are derived to exhibit the stochastic behaviors. The periodic and chaotic motions, bifurcations and crises under different conditions are analyzed. The results show that the output voltage is sensitive to the uncertainty of the nonlinear coefficient, which leads to unstable behavior around the bifurcation and crisis points particularly. Exploring the influence pattern of uncertain parameters on the output voltage and avoiding the unstable parameter intervals are essential for optimizing the structure. It can further improve the efficiency of the nonlinear energy harvesting system.
The Investigation of the Fracture Behavior of a Chinese 9% Cr Steel Welded Joint under Creep-Fatigue Interactive Loading
Authors: Li Yuebing , Song Yuxuan , Liu Pan , Jin Ting
Published: October 2021

To understand the premature-fracture mechanisms of long-term service damage of an advanced alloy’s (Chinese P92 steel) welded joint, the creep-fatigue (CF) experiments with holding times of 30, 120, 300, 600 and 900 s were individually performed at 923 K. The cyclic softening, inelastic-strain amplitudes and stress-relaxation behaviors were compared between welded and base-metal (BM) specimens. From the results, the failure stage of the welded specimens occupies 45% of the lifetime fraction, while it only takes up 20% of the lifetime fraction in BM specimens with short holding times (30 and 120 s). Furthermore, only two softening stages were observed for both kinds of CF specimens with long holding times. The absence of a third softening stage in longer-held specimens indicates that the processes of macroscopic-crack initiation, propagation and rupture were accelerated. Based on the observation of the fracture surfaces, the fracture mechanism shifted from fatigue-dominated damage to creep-fatigue interaction when the holding period was increased.
The Consequences of Mechanical Vibration Exposure on the Lower Back of Bus Drivers: A Systematic Review
Authors: Mendes Hyago Gabriel Oliveira , de Moraes Tomaz Bianca , Coelho-Oliveira Ana Carolina , de Freitas Juliana Pessanha , Cristina Moura-Fernandes Márcia , de Souza-Gama Marco Antônio , Salustiano da Silva Francisco José , Francisca-Santos Arlete , Ferreira-Souza Luiz Felipe , Seixas Aderito , Taiar Redha , Bernardo-Filho Mario , da Cunha de Sá-Caputo Danúbia
Published: October 2021

Professional drivers are exposed to whole-body vibration while driving, which contributes to an increased risk of developing physical problems, such as pain in the lower back. This article aims to review the effects of vibration exposure on bus drivers. Searches were performed on the PubMed, Embase, Web of Science, and Scopus databases. Only full articles of observational and experimental studies that investigated the effects of vibration on bus drivers with consequences in the lumbar region published in English were included. Data on driver demographics, study design, objectives, bus model, seat model, length of exposure to vibration, and outcomes were extracted. Two studies were classified as evidence level III-2 and three studies as level III-3. The methodological quality of the publications presented one with a moderate and four with a serious risk of bias. In all the publications, pain in the lumbar spine was reported. In conclusion, the results of this systematic review suggest that bus drivers are exposed to mechanical vibration in their work routine, and this might be considered a risk factor for the development of pain in the lumbar spine, bearing in mind that the exposure is for long periods.
GAN-LSTM Joint Network Applied to Seismic Array Noise Signal Recognition
Authors: Li Jian , Hei Dongwei , Cui Gaofeng , He Mengmin , Wang Juan , Liu Zhehan , Shang Jie , Wang Xiaoming , Wang Weidong
Published: October 2021

The purpose of seismic data processing in nuclear explosion monitoring is to accurately and reliably detect seismic or explosion events from complex ambient noises. Accurate detection and identification of seismic phases are of great significance to the detection and parameter estimation of seismic events. In seismic phase identification, discriminating between noise signals and real seismic signals is essential. Accurate identification of noise signals helps reduce false detections, improves the accuracy of automatic bulletins, and relieves the workload of analysts. At the same time, in seismic exploration, the prime objective in data processing is also to enhance the signal and suppress the noises. In this study, we combined a generative adversarial network (GAN) with a long short-term memory network (LSTM) to discriminate between noise and phases in seismic waveforms recorded by the International Monitoring System (IMS) array MKAR. First, using the beamforming data of the array as the input, we obtained the signal features of seismic phases through the learning of the GAN discriminator network. Then, we input these features and trained the joint network on mixed seismic phase and noise data, and successfully classified seismic phases and noise signals with a recall of 95.28% and 97.64%, respectively. Based on this model, we established a real-time data processing method, then validated the effectiveness of this method with real 2019 data of MKAR. We also verified whether improved noise signal identification improves the quality of phase association and event detection.
Experimental Study on the Chemical Characterization of Atmospheric Aerosols in Wuhan, China
Authors: Mao Qianjun , Cheng Fangyuan , Chen Min
Published: October 2021

Air pollution has a significant impact on the use of solar energy. On the one hand, the polluted environment directly reduces the intensity of solar radiation, on the other hand, pollution of the environment will also reduce the life of the equipment. Therefore, mastering the dynamic characteristics of the atmospheric environment has certain guiding significance for the efficient utilization of solar energy. In this study, the concentrations of particulate matter, CO, SO2 and NO2 from Tianyun big data website are analyzed to obtain the general characteristics of particulate pollution in Wuhan. At the same time, a long-period sampling atmospheric particulate matter sampler in the Huangjiahu area of Wuhan has been used, and experimental analysis of the physical and chemical characteristics of the samples has been obtained. The results show that both PM2.5 and PM10 show obvious seasonal changes, and the concentration of the four anions during the sampling period is SO42− > NO3− > Cl− > F−. During the sampling period, atmospheric particulate matter is mainly composed of organic matter, inorganic anions and oxides of more than 20 elements. The results of the enrichment factor analysis show that elements such as Br, Pb, Sb and Zn are the main enriched elements during the sampling period. The enrichment factors of these elements are 246.43 ± 168.81, 133.28 ± 115.03, 403.305 ± 396.18 and 90.67 ± 67.01, respectively. The high enrichment of these elements also reflects the contribution of motor vehicle exhaust emission during the sampling period. Traffic source is the main emission source in the Huangjiahu area of Wuhan. This research has a certain guiding significance for many industries such as energy utilization, environmental monitoring, health care, transportation and so on.
Greenhouse Gas Emissions from Agriculture in EU Countries—State and Perspectives
Authors: Mielcarek-Bocheńska Paulina , Rzeźnik Wojciech
Published: October 2021

Agriculture is one of the main sources of greenhouse gas (GHG) emissions and has great potential for mitigating climate change. The aim of this study is to analyze the amount, dynamics of changes, and structure of GHG emissions from agriculture in the EU in the years 2005–2018. The research based on data about GHG collected by the European Environment Agency. The structure of GHG emissions in 2018 in the EU is as follows: enteric fermentation (45%), agricultural soils (37.8%), manure management (14.7%), liming (1.4%), urea application (1%), and field burning of agricultural residues (0.1%). Comparing 2018 with the base year, 2005, emissions from the agricultural sector decreased by about 2%, which is less than the assumed 10% reduction of GHG emissions in the non-emissions trading system (non-ETS) sector. The ambitious goals set by the EU for 2030 assume a 30% reduction in the non-ETS sector. This will require a significant reduction in GHG emissions from agriculture. Based on the analysis of the GHG emission structure and available reduction techniques, it was calculated that in this period, it should be possible to reduce emissions from agriculture by about 15%.
On the Finite Dimensionality of Closed Subspaces in Lp(M, dμ) ∩ Lq(M, dν)
Authors: Balinsky Alexander A. , Prykarpatski Anatolij K.
Published: October 2021

Finding effective finite-dimensional criteria for closed subspaces in Lp, endowed with some additional functional constraints, is a well-known and interesting problem. In this work, we are interested in some sufficient constraints on closed functional subspaces, Sp⊂Lp, whose finite dimensionality is not fixed a priori and can not be checked directly. This is often the case in diverse applications, when a closed subspace Sp⊂Lp is constructed by means of some additional conditions and constraints on Lp with no direct exemplification of the functional structure of its elements. We consider a closed topological subspace, Sp(q), of the functional Banach space, Lp(M,dμ), and, moreover, one assumes that additionally, Sp(q)⊂Lq(M,dν) is subject to a probability measure ν on M. Then, we show that closed subspaces of Lp(M,dμ)∩Lq(M,dν) for q>max{1,p},p>0 are finite dimensional. The finite dimensionality result concerning the case when q>p>0 is open and needs more sophisticated techniques, mainly based on analysis of the complementary subspaces to Lp(M,dμ)∩Lq(M,dν).
Effect of the Elemental Content of Shells of the Bivalve Mollusks (Mytilus galloprovincialis) from Saldanha Bay (South Africa) on Their Crystallographic Texture
Authors: Nekhoroshkov Pavel , Zinicovscaia Inga , Nikolayev Dmitry , Lychagina Tatiana , Pakhnevich Alexey , Yushin Nikita , Bezuidenhout Jacques
Published: October 2021

A both wild and farmed mussels in natural conditions, anthropogenic inputs are usually reflected in the increase of the content of specific elements. To determine the possible effect of the elemental patterns of farmed and wild mussels (Mytilus galloprovincialis) collected in the Saldanha Bay area (South Africa) on the crystallographic texture of the shells, the content of 20 elements in shells and 24 in the soft tissue of mussels was determined by neutron activation analysis. The crystallographic texture of mussel shells was analyzed using time-of-flight neutron diffraction. The wild mussels from open ocean site live in stressful natural conditions and contain higher amounts of the majority of determined elements in comparison with mussels farmed in closed water areas with anthropogenic loadings. The changes between the maximums of the same pole figures of the three samples are in the range of variability identified for the genus Mytilus. The content of Cl, Sr, and I was the highest in mussels from the open ocean site, which is reflected by the lowest mass/length ratio. The determined crystallographic textures of mussels are relatively stable as shown in the analyzed pole figures despite the concentrations of Na, Mg, Cl, Br, Sr, and I in shells, which significantly differ for wild and farmed mussels. The stability of the crystallographic texture that we observed suggests that it can be used as a reference model, where if a very different texture is determined, increased attention to the ecological situation should be paid.
Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements
Authors: Bandopadhyay Ritam , Singh Tanveer , Ghoneim Mohammed M. , Alshehri Sultan , Angelopoulou Efthalia , Paudel Yam Nath , Piperi Christina , Ahmad Javed , Alhakamy Nabil A. , Alfaleh Mohamed A. , Mishra Awanish
Published: October 2021

Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60–70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.
Extensive GJD2 Expression in the Song Motor Pathway Reveals the Extent of Electrical Synapses in the Songbird Brain
Authors: Alcami Pepe , Totagera Santhosh , Sohnius-Wilhelmi Nina , Leitner Stefan , Grothe Benedikt , Frankl-Vilches Carolina , Gahr Manfred
Published: October 2021

Birdsong is a precisely timed animal behavior. The connectivity of song premotor neural networks has been proposed to underlie the temporal patterns of neuronal activity that control vocal muscle movements during singing. Although the connectivity of premotor nuclei via chemical synapses has been characterized, electrical synapses and their molecular identity remain unexplored. We show with in situ hybridizations that GJD2 mRNA, coding for the major channel-forming electrical synapse protein in mammals, connexin 36, is expressed in the two nuclei that control song production, HVC and RA from canaries and zebra finches. In canaries’ HVC, GJD2 mRNA is extensively expressed in GABAergic and only a fraction of glutamatergic cells. By contrast, in RA, GJD2 mRNA expression is widespread in glutamatergic and GABAergic neurons. Remarkably, GJD2 expression is similar in song nuclei and their respective embedding brain regions, revealing the widespread expression of GJD2 in the avian brain. Inspection of a single-cell sequencing database from zebra and Bengalese finches generalizes the distributions of electrical synapses across cell types and song nuclei that we found in HVC and RA from canaries, reveals a differential GJD2 mRNA expression in HVC glutamatergic subtypes and its transient increase along the neurogenic lineage. We propose that songbirds are a suitable model to investigate the contribution of electrical synapses to motor skill learning and production.
Headache Attributed to SARS-CoV-2 Infection or COVID-19 Related Headache—Not Migraine-like Problem-Original Research
Authors: Kacprzak Aleksandra , Malczewski Daniel , Domitrz Izabela
Published: October 2021

Background: Many studies have confirmed headache as one of the most common COVID-19-related neurological symptoms. There are some reports concerning migraine attacks during SARS-CoV-2 infection with an unusual course of migraine attack. Our aim was to recognize and characterize accurately the features of headaches accompanying this disease. Methods: Research based on questionnaire study gathered 100 randomly chosen medical healthcare employees who experienced symptoms associated with COVID-19 disease, 96 with confirmed COVID-19 (positive SARS-CoV-2 PCR laboratory test or positive rapid COVID-19 antigen test). Conclusion: Headaches reported in the study did not fulfill criteria for migraine with/without aura, tension-type headache according to ICHD-3.
The Mental Health Outcomes of Food Insecurity and Insufficiency in West Africa: A Systematic Narrative Review
Authors: Ae-Ngibise Kenneth Ayuurebobi , Asare-Doku Winifred , Peprah Jennifer , Mujtaba Mohammed Nuhu , Nifasha Diane , Donnir Gordon Maanianu
Published: October 2021

(1) Background: Food insufficiency is a global pandemic affecting many people, especially those residing in developing countries. African countries have been affected by food insufficiency, which is mostly caused by drought or wars. Famine or food insufficiency has been reported to have an impact on the psychological health and quality of life of people affected. This review assessed the mental health outcomes of famine and food insufficiency in West Africa. (2) Methods: A search of the published literature was conducted using PubMed, PsycExtra, Medline, and PsycINFO databases. The search was limited to papers published in English between the years 2010 and 2020. Two reviewers independently screened the titles and abstracts of the retrieved papers using pre-defined inclusion and exclusion criteria and a third reviewer resolved conflicts. Data were extracted and appraised using a data extraction form and an appraisal checklist. (3) Results: A total of 81 papers were identified through the journal databases search. Out of the seven papers that met the inclusion criteria, six papers used cross-sectional designs and one paper used an experimental design. The six papers used quantitative approach for data collection, while the one paper used a qualitative technique. The evidence synthesized from this review indicated that exposure to food insecurity or insufficiency is associated with increased psychological distress including anxiety, sleeplessness, intellectual disability, general mental, and emotional instability. (4) Conclusions: This review strongly highlights the need for further research across the sub-region. It further suggests that famine and food insufficiency are associated with significant mental health problems in adults and impacts the cognitive and intellectual development of children. Although there is paucity of literature about famine and its impact on mental health in West Africa, these findings are important for developing social policy initiatives for increasing food supply and mental health interventions for all ages.
openVFIFE: An Object-Oriented Structure Analysis Platform Based on Vector Form Intrinsic Finite Element Method
Authors: Tan Biao , Cao Shuyang , Fang Genshen , Cao Jinxin , Ge Yaojun
Published: October 2021

The vector form intrinsic finite (VFIFE) method is a new and promising structural analysis technique that has many advantages as compared with the conventional finite element method (FEM) in analyzing the complex behaviors of a structure. However, despite the popularization of its application in civil and infrastructure engineering, there is no available unified general analysis framework for it, which limits the applications and developments of VFIFE. This work develops and implements a platform (termed openVFIFE) based on a new proposed object-oriented framework to facilitate the development and application of the vector form intrinsic finite method as well as the efficient and accurate analyses of complex behaviors for civil structures. To validate the platform, a series of numerical examples are conducted. Furthermore, to extend the applications of VFIFE, the nonlinear dynamic and collapse processes of a transmission tower under earthquake load are studied using openVFIFE. The results of these numerical examples simulated by the developed truss or beam elements are consistent with theoretical solutions, previous research or conventional finite element models. The failure modes of the transmission tower under earthquake load simulated by the platform is consistent with those observed in real cases. In addition, the results of nonlinear dynamic analyses of the transmission tower show that the computational efficiency of the proposed platform is 6-10 times higher than that of the conventional finite element method. The results provide sufficient evidence to prove the accuracy and efficiency of the proposed platform in the static, dynamic and elastoplastic analyses of truss and frame structures, especially in the structure analysis characterized by strong geometry nonlinearity. It is noteworthy that in addition to the link and beam elements, further work is undergoing on implementing more elements, such as shell and solid elements. The openVFIFE also allows researchers who are interested in this topic to put their creative ideas into this platform and continuously improve the completeness and applicability of the VFIFE method.
Tomato Yellow Leaf Curl Virus (TYLCV) Promotes Plant Tolerance to Drought
Authors: Shteinberg Moshik , Mishra Ritesh , Anfoka Ghandi , Altaleb Miassar , Brotman Yariv , Moshelion Menachem , Gorovits Rena , Czosnek Henryk
Published: October 2021

A growing body of research points to a positive interplay between viruses and plants. Tomato yellow curl virus (TYLCV) is able to protect tomato host plants against extreme drought. To envisage the use of virus protective capacity in agriculture, TYLCV-resistant tomato lines have to be infected first with the virus before planting. Such virus-resistant tomato plants contain virus amounts that do not cause disease symptoms, growth inhibition, or yield loss, but are sufficient to modify the metabolism of the plant, resulting in improved tolerance to drought. This phenomenon is based on the TYLCV-dependent stabilization of amounts of key osmoprotectants induced by drought (soluble sugars, amino acids, and proteins). Although in infected TYLCV-susceptible tomatoes, stress markers also show an enhanced stability, in infected TYLCV-resistant plants, water balance and osmolyte homeostasis reach particularly high levels. These tomato plants survive long periods of time during water withholding. However, after recovery to normal irrigation, they produce fruits which are not exposed to drought, similarly to the control plants. Using these features, it might be possible to cultivate TYLCV-resistant plants during seasons characterized by water scarcity.
Synthesis of Ceramic Reinforcements in Metallic Matrices during Spark Plasma Sintering: Consideration of Reactant/Matrix Mutual Chemistry
Authors: Dudina Dina V. , Vidyuk Tomila M. , Korchagin Michail A.
Published: October 2021

Metal–ceramic composites are obtained via ex-situ or in-situ routes. The in-situ route implies the synthesis of reinforcement in the presence of a matrix and is often regarded as providing more flexibility to the microstructure design of composites than the ex-situ route. Spark plasma sintering (SPS) is an advanced sintering method that allows fast consolidation of various powder materials up to full or nearly full density. In reactive SPS, the synthesis and consolidation are combined in a single processing step, which corresponds to the in-situ route. In this article, we discuss the peculiarities of synthesis of ceramic reinforcements in metallic matrices during SPS with a particular consideration of reactant/matrix mutual chemistry. The formation of carbide reinforcements in Cu, Al, and Ni matrices is given attention with examples elaborated in the authors’ own research. Factors determining the suitability of reactive SPS for manufacturing of composites from a matrix/reactants system and features of the structural evolution of the reaction mixture during sintering are discussed.
An Experimental Study of the Effects of Low-Calcium Fly Ash on Type II Concrete
Authors: Tee Kong Fah , Mostofizadeh Sayedali
Published: October 2021

In this study, the compressive strength and the permeation properties of fly ash-based Geopolymer were experimentally investigated. Type 2 Portland cement (T2PC) was partially or entirely replaced with 0, 10, 20, 30, 50, 70, and 100% of fly ash (FA). The laboratory tests were conducted for compressive strength at 7, 28, and 90 days, and permeation properties such as water absorption at 7 and 28 days. The main goal was to produce eco-friendly concrete with high strength and low permeability through blending cementitious materials including low Calcium (Ca) (T2PC and FA) for protecting concrete against sulphate attacks and other chemically destructive compounds in the environment. This study focused on the effectiveness of the curing period, combinations of chemical activators by varying the molarity of alkaline solutions between 4.16 and 12.96 M and keeping the sodium silicate (SS) to sodium hydroxide (SH) by the weight ratio of 2.5. Lab observations from this study demonstrated that the compressive strength was enhanced with the increment in fly ash content at all ages, with optimum being at 20% as the replacement of T2PC.
Highly Fluorescent Carbon Dots as a Potential Fluorescence Probe for Selective Sensing of Ferric Ions in Aqueous Solution
Authors: Atchudan Raji , Kishore Somasundaram Chandra , Edison Thomas Nesakumar Jebakumar Immanuel , Perumal Suguna , Vinodh Rajangam , Sundramoorthy Ashok K. , Babu Rajendran Suresh , Alagan Muthulakshmi , Lee Yong Rok
Published: October 2021

This paper’s emphasis is on the development of a fluorescent chemosensor for Fe3+ ions in an aqueous solution, using hydrophilic carbon dots (O-CDs). A simple, cost-effective, and environmentally friendly one-step hydrothermal synthesis method was used to synthesize fluorescent hydrophilic O-CDs from Oxalis corniculata (Family; Oxalidaceae). The graphitic structure and size distribution of the O-CDs was verified by X-ray diffraction, Raman spectroscopy, and high-resolution transmission electron microscopy studies. The resulting O-CDs had a near-spherical shape and an adequate degree of graphitization at the core, with an average diameter of 4.5 nm. X-ray photoelectron and Fourier transform infrared spectroscopy methods revealed the presence of several hydrophilic groups (carbonyl, amine, carboxyl, and hydroxyl, along with nitrogen and oxygen-rich molecules) on the surface of O-CDs. The synthesized hydrophilic O-CDs with excitation wavelength-dependent emission fluorescence characteristics showed a high quantum yield of about 20%. Besides this, the hydrophilic O-CDs exhibited a bright and controllable fluorescence with prolonged stability and photo-stability. These fluorescent hydrophilic O-CDs were used as a nanoprobe for the fluorometric identification of Fe3+ ions in an aqueous solution, with high sensitivity and selectivity. By quenching the blue emission fluorescence of this nanosensor, a highly sensitive Fe3+ ion in the range of 10–50 µM with a minimum detection limit of 0.73 µM was achieved. In addition, the developed nanosensor can be used to sense intracellular Fe3+ ions with high biocompatibility and cellular imaging capacity, and it has a lot of potential in biomedical applications.
Exploring Emerging Technologies with Analysis of Bibliographic Data Focused on Plasma Surface Treatment
Authors: Kim Youbean
Published: October 2021

Research trends and emerging technologies were explored through the Web of Science (WoS) literature of the last decade in relation to plasma technology, especially plasma surface treatment, widely used in all industries. For this, a network analysis using country and author keywords and emerging technology search algorithms, with regard to novelty, fast growth and impact, were used. As a result, we derived 40 keywords in terms of novelty and fast growth. Additionally, with these keywords, we traced the impact based on the citation relationships. Finally, nine keywords which were analyzed to contain many new technological issues were identified by deriving the author keywords included in the relevant documents. It is expected that the new technology fields derived from this paper can contribute to establishing a preemptive R&D strategy.
B-MFO: A Binary Moth-Flame Optimization for Feature Selection from Medical Datasets
Authors: Nadimi-Shahraki Mohammad H. , Banaie-Dezfouli Mahdis , Zamani Hoda , Taghian Shokooh , Mirjalili Seyedali
Published: October 2021

Advancements in medical technology have created numerous large datasets including many features. Usually, all captured features are not necessary, and there are redundant and irrelevant features, which reduce the performance of algorithms. To tackle this challenge, many metaheuristic algorithms are used to select effective features. However, most of them are not effective and scalable enough to select effective features from large medical datasets as well as small ones. Therefore, in this paper, a binary moth-flame optimization (B-MFO) is proposed to select effective features from small and large medical datasets. Three categories of B-MFO were developed using S-shaped, V-shaped, and U-shaped transfer functions to convert the canonical MFO from continuous to binary. These categories of B-MFO were evaluated on seven medical datasets and the results were compared with four well-known binary metaheuristic optimization algorithms: BPSO, bGWO, BDA, and BSSA. In addition, the convergence behavior of the B-MFO and comparative algorithms were assessed, and the results were statistically analyzed using the Friedman test. The experimental results demonstrate a superior performance of B-MFO in solving the feature selection problem for different medical datasets compared to other comparative algorithms.
UAV-Assisted Data Collection in Wireless Sensor Networks: A Comprehensive Survey
Authors: Nguyen Minh T. , Nguyen Cuong V. , Do Hai T. , Hua Hoang T. , Tran Thang A. , Nguyen An D. , Ala Guido , Viola Fabio
Published: October 2021

Wireless sensor networks (WSNs) are usually deployed to different areas of interest to sense phenomena, process sensed data, and take actions accordingly. The networks are integrated with many advanced technologies to be able to fulfill their tasks that is becoming more and more complicated. These networks tend to connect to multimedia networks and to process huge data over long distances. Due to the limited resources of static sensor nodes, WSNs need to cooperate with mobile robots such as unmanned ground vehicles (UGVs), or unmanned aerial vehicles (UAVs) in their developments. The mobile devices show their maneuverability, computational and energy-storage abilities to support WSNs in multimedia networks. This paper addresses a comprehensive survey of almost scenarios utilizing UAVs and UGVs with strogly emphasising on UAVs for data collection in WSNs. Either UGVs or UAVs can collect data from static sensor nodes in the monitoring fields. UAVs can either work alone to collect data or can cooperate with other UAVs to increase their coverage in their working fields. Different techniques to support the UAVs are addressed in this survey. Communication links, control algorithms, network structures and different mechanisms are provided and compared. Energy consumption or transportation cost for such scenarios are considered. Opening issues and challenges are provided and suggested for the future developments.
Rollover Index for Rollover Mitigation Function of Intelligent Commercial Vehicle’s Electronic Stability Control
Authors: Shin Donghoon , Woo Seunghoon , Park Manbok
Published: October 2021

This paper describes a rollover index for detection or prediction of impending rollover in different driving situations using minimum sensor signals which can be easily obtained from an electronic stability control (ESC) system. The estimated lateral load transfer ratio (LTR) was used as a rollover index with only limited information such as the roll state of the vehicle and some constant parameters. A commercial vehicle has parameter uncertainties because of its load variation. This is likely to affect the driving performance and the estimation of the dynamic state of the vehicle. The main purpose of this paper is to determine the rollover index based on reliable measurements and the parameters of the vehicle. For this purpose, a simplified lateral and vertical vehicle dynamic model was used with some assumptions. The index is appropriate for various situations although the vehicle parameters may change. As part of the index, the road bank angle was investigated in this study, using limited information. Since the vehicle roll dynamics are affected by the road bank angle, the road bank angle should be incorporated, although previous studies ignore this factor in order to simplify the problem. Because it increases or reduces the chances of rollover, consideration of the road bank angle is indispensable in the rollover detection and mitigation function of the ESC system. The performance of the proposed algorithm was investigated via computer simulation studies. The simulation studies showed that the proposed estimation method of the LTR and road bank angle with limited sensor information followed the actual LTR value, reducing the parameter uncertainties. The simulation model was constructed based on a heavy bus (12 tons).
Cluster-Based Memetic Approach of Image Alignment
Authors: Cocianu Catalina-Lucia , Uscatu Cristian Răzvan
Published: October 2021

The paper presents a new memetic, cluster-based methodology for image registration in case of geometric perturbation model involving translation, rotation and scaling. The methodology consists of two stages. First, using the sets of the object pixels belonging to the target image and to the sensed image respectively, the boundaries of the search space are computed. Next, the registration mechanism residing in a hybridization between a version of firefly population-based search procedure and the two membered evolutionary strategy computed on clustered data is applied. In addition, a procedure designed to deal with the premature convergence problem is embedded. The fitness to be maximized by the memetic algorithm is defined by the Dice coefficient, a function implemented to evaluate the similarity between pairs of binary images. The proposed methodology is applied on both binary and monochrome images. In case of monochrome images, a preprocessing step aiming the binarization of the inputs is considered before the registration. The quality of the proposed approach is measured in terms of accuracy and efficiency. The success rate based on Dice coefficient, normalized mutual information measures, and signal-to-noise ratio are used to establish the accuracy of the obtained algorithm, while the efficiency is evaluated by the run time function.
Increasing the Performance of a Fiber-Reinforced Concrete for Protective Facilities
Authors: Fediuk Roman , Amran Mugahed , Klyuev Sergey , Klyuev Aleksandr
Published: October 2021

The use of fiber in cement materials is a promising and effective replacement for bar reinforcement. A wide range of fiber-reinforced concretes based on composite binders with increased impact strength characteristics have been developed. The synthesized composites included the composite binder made of Portland cement, silica, and carbonate additives. Basalt and steel were used as fibers. The nature of the influence of the composition and manufacturing technology of cement composites on the dynamic hardening coefficient has been established, while the growth of these indicators is achieved by creating a denser interfacial transition zone between the cement paste, aggregate, and fiber as a result of improving the homogeneity of the concrete mixture and controlling the consistency. Workability indicators (slump flow up to 730 mm; spreading time up to a diameter of 50 cm is up to 3 s) allow them to be classified as self-compacting concrete mixtures. An increase in the values of the impact strength coefficient by a factor of 5.5, the dynamic hardening coefficient by almost 70% as a result of interfacial interaction between fibers and binder matrix in the concrete composite, as well as absorption of impact energy by fiber, was revealed. The formula describing the effect of the loading rate on the coefficient of dynamic hardening of fiber-reinforced concrete has been refined. The fracture processes of the obtained materials have been established: after the initiation of primary cracks, the structure of the composite absorbs impact energy for a long time, while in the inelastic range (the onset of cracking and peak loads), a large number of secondary cracks appear.
A Novel Colorimetric Nano Aptasensor for Ultrasensitive Detection of Aflatoxin B1 Based on the Exonuclease III-Assisted Signal Amplification Approach
Authors: Chen Yu , Zhang Fuyuan , Liu Ruobing , Liu Minxuan , Sang Yaxin , Wang Shuo , Wang Xianghong
Published: October 2021

The detection of aflatoxin B1 (AFB1) has recently garnered much attention on the issue of food safety. In this study, a novel and sensitive aptasensor towards AFB1 is proposed using an Exonuclease III (Exo III)-integrated signal amplification strategy. This reported sensing strategy is regulated by aptamer-functionalized nanobeads that can target AFB1; furthermore, complementary DNA (cDNA) strands can lock the immobilized aptamer strands, preventing the signal amplification function of Exo III in the absence of AFB1. The presence of AFB1 triggers the displacement of cDNA, which will then activate the Exo III-integrated signal amplification procedure, resulting in the generation of a guanine (G)-rich sequence to form a G-4/hemin DNAzyme, which can catalyze the substrate of ABTS to produce a green color. Using this method, a practical detection limit of 0.0032 ng/mL and a dynamic range of detection from 0.0032 to 50 ng/mL were obtained. Additionally, the practical application of the established sensing method for AFB1 in complex matrices was demonstrated through recovery experiments. The recovery rate and relative standard deviations (RSD) in three kinds of cereal samples ranged from 93.83% to 111.58%, and 0.82% to 7.20%, respectively, which were comparable with or better than previously reported methods.
Highly Effective Covalently Crosslinked Composite Alginate Cryogels for Cationic Dye Removal
Authors: Sezen Serap , Thakur Vijay Kumar , Ozmen Mehmet Murat
Published: October 2021

Currently, macroporous hydrogels have been receiving attention in wastewater treatment due to their unique structures. As a natural polymer, alginate is used to remove cationic dyes due to its sustainable features such as abundance, low cost, processability, and being environmentally friendly. Herein, alginate/montmorillonite composite macroporous hydrogels (cryogels) with high porosity, mechanical elasticity, and high adsorption yield for methylene blue (MB) were generated by the one-step cryogelation technique. These cryogels were synthesized by adding montmorillonite into gel precursor, followed by chemical cross-linking employing carbodiimide chemistry in a frozen state. The as-prepared adsorbents were analyzed by FT-IR, SEM, gel fraction, swelling, uniaxial compression, and MB adsorption tests. The results indicated that alginate/montmorillonite cryogels exhibited high gelation yield (up to 80%), colossal water uptake capacity, elasticity, and effective dye adsorption capacity (93.7%). Maximum adsorption capacity against MB was 559.94 mg g−1 by linear regression of Langmuir model onto experimental data. The Pseudo-Second-Order model was fitted better onto kinetic data compared to the Pseudo-First-Order model. Improved porosity and mechanical elasticity yielding enhanced dye removal capacity make them highly potential alternative adsorbents compared to available alginate/montmorillonite materials for MB removal.