bluuebunny/crossref_metadata_2025 huggingface dataset:
The Prevalence of Pathogens among Ticks Collected from Livestock in Kazakhstan
Authors: Sultankulova Kulyaisan T. , Shynybekova Gaukhar O. , Issabek Aisha U. , Mukhami Nazym N. , Melisbek Aibarys M. , Chervyakova Olga V. , Kozhabergenov Nurlan S. , Barmak Sabyrkhan M. , Bopi Arailym K. , Omarova Zamira D. , Alibekova Dana A. , Argimbayeva Takhmina U. , Namet Aidar M. , Zuban Ivan A. , Orynbayev Mukhit B.
Published: October 2022

Ticks carry and transmit a wide variety of pathogens (bacteria, viruses and protozoa) that pose a threat to humans and animals worldwide. The purpose of this work was to study ticks collected in different regions of Kazakhstan for the carriage of various pathogens. The collected ticks were examined by PCR for the carriage of various pathogens. A total of 3341 tick samples parasitizing three animal species (cattle, sheep and horses) were collected at eight regions of Kazakhstan. Eight tick species were found infesting animals: Dermacentor marginatus (28.08%), Hyalomma asiaticum (21.28%), Hyalomma anatolicum (17.18%), Dermacentor reticulatus (2.01%), Ixodes ricinus (3.35%), Ixodes persulcatus (0.33%), Hyalomma scupense (12.87%) and Hyalomma marginatum (14.90%). Ticks collected from livestock animals were examined for the pathogen spectrum of transmissible infections to determine the degree of their infection. Four pathogen DNAs (lumpy skin disease virus (LSDV), Coxiella burnetti, Teileria annulata, and Babesia caballi) were detected by PCR in Dermacentor marginatus, Hyalomma asiaticum, Hyalomma scupense, Hyalomma anatolicum. The infection of ticks Dermacentor marginatus and Hyalomma asiaticum collected on cattle in the West Kazakhstan region with LSDV was 14.28% and 5.71%, respectively. Coxiella burnetti was found in the ticks Dermacentor marginatus (31.91%) in the Turkestan region and Hyalomma anatolicum (52.63%) in the Zhambyl region. Theileria annulata was found in ticks Hyalomma scupense (7.32%) and Dermacentor marginatus (6.10%) from cattle in the Turkestan region. Babesia caballi was isolated only from the species Hyalomma scupense (17.14%) in the Turkestan region. There were no PCR-positive tick samples collected from sheep. RNA/DNAs of tick-borne encephalitis virus (TBEV), African swine fever virus (ASFV), Hantavirus hemorrhagic fever with renal syndrome (HFRS), and chlamydia pathogens were not found in ticks. The new data give a better understanding of the epidemiology of tick-borne pathogens and the possibility of the emergence of tick-borne animal diseases in Kazakhstan.
Brain Microvascular Endothelial Cell-Derived Exosomes Protect Neurons from Ischemia–Reperfusion Injury in Mice
Authors: Sun Jin , Yuan Qing , Guo Lichen , Xiao Guangxu , Zhang Tong , Liang Bing , Yao Rongmei , Zhu Yan , Li Yue , Hu Limin
Published: October 2022

Stroke often results in neurological and neuropsychiatric sequela. Exosomes derived from brain endothelial cells (EC-Exo) protect neurons from hypoxic injury. However, the biological role of exosomes in apoptosis and synaptic plasticity remains unclear. This research aimed to assess whether cerebral microvascular endothelial cells inhibit apoptosis and promote synaptic remodeling through exosome-mediated cell–cell interaction after the ischemic attack. The effects of EC-Exo on primary neuronal apoptosis and synapses in oxyglucose deprivation reoxygenation (OGD/R) injury were first assessed in vitro. Animal experiments were performed using C57BL/6J mice, divided into three groups: a sham group, a model (middle cerebral artery occlusion/reperfusion, MCAO/R) group, and an EC-Exo group (tail vein injection of EC-Exo, once/2 days for 14 days) to evaluate the neuromotor and exploratory abilities of mice after MCAO/R. Apoptosis and synaptic protein expression levels were detected. The results demonstrated that EC-Exo inhibited neuronal apoptosis and increased synaptic length after OGD/R. In vivo, EC-Exo not only improved neural motor behavior and increased regional cerebral blood flow (rCBF) in MCAO/R-injured mice but also promoted the expression of synaptic regulatory proteins and inhibited apoptosis in the brain. These results suggest that EC-Exo may provide neuroprotection against stroke by promoting synaptic remodeling and inhibiting apoptosis from protecting neurons.
Microemulsions Enhance the In Vitro Antioxidant Activity of Oleanolic Acid in RAW 264.7 Cells
Authors: De Stefani Chiara , Vasarri Marzia , Salvatici Maria Cristina , Grifoni Lucia , Quintela Jose Carlos , Bilia Anna Rita , Degl’Innocenti Donatella , Bergonzi Maria Camilla
Published: October 2022

Oleanolic acid (OA) is the main triterpenic acid of olive leaves known for numerous pharmacological properties, including antioxidant activity. However, it is poorly soluble in water and consequently with low bioavailability, which limits its pharmacological application. Microemulsions (MEs) are dispersed systems consisting of two immiscible phases that promote rapid solubilization and absorption in the gastrointestinal tract. To improve both solubility and intestinal permeability of this molecule, OA has been formulated in two different microemulsions (ME-1 and ME-2). A solubility screening was carried out to select the ME components, and pseudoternary phase diagrams were constructed to evaluate the region of existence and select the appropriate amount of the constituents. ME-1 was prepared using Capmul PG-8/NF as the oily phase, and Transcutol and Tween 20 (7:3) as surfactants, while ME-2 contained Nigella oil and Isopropil myristate as the oily phase, and Transcutol HP and Cremophor EL (2:1) as surfactants. The OA solubility was increased by 1000-fold and 3000-fold in ME-1-OA and ME-2-OA, respectively. The MEs’ droplet size and the PdI were evaluated, and the stability was assessed for 8 weeks by monitoring chemical and physical parameters. The parallel artificial membrane permeability assay (PAMPA) also demonstrated an enhanced intestinal permeability of both OA formulations compared with free OA. The potential ability of both MEs to enhance the bioactivity of OA against LPS-induced oxidative stress in RAW 264.7 murine macrophages was also investigated. Overall, this study suggests that both MEs promote a bio-enhancement of the protective action of OA against the LPS-induced pro-oxidant stress in macrophages. Overall, this study suggests that MEs could be an interesting formulation to improve OA oral bioavailability with potential clinical applications.
UV-Induced Gold Nanoparticle Growth in Polystyrene Matrix with Soluble Precursor
Authors: Kudryashov Andrey , Baryshnikova Svetlana , Gusev Sergey , Tatarskiy Dmitry , Lukichev Ivan , Agareva Nadezhda , Poddel’sky Andrey , Bityurin Nikita
Published: October 2022

It is demonstrated that UV (LED at 365 nm) irradiation with subsequent heating (90–110 °C) of the polystyrene matrix containing a soluble Au(I) compound ((Ph3P)Au(n-Bu)) results in the growth of gold nanoparticles within the sample bulk, as confirmed by UV-vis spectroscopy and TEM electron microscopy. Pure heating of the samples without previous UV irradiation does not provide gold nanoparticles, thereby facilitating optical image printing. Comparing the nanoparticles’ growth kinetics in samples with different precursor content suggests the nanoparticle growth mechanism through Au(I) autocatalytic reduction at the surface of a gold nanoparticle. Within the polymer matrix, this mechanism is suggested for the first time.
Sensing Performance of Triple-Band Terahertz Metamaterial Absorber Based on Snowflake-Shaped Resonators
Authors: Ma Limin , Liu Yuhuang , Zhu Yongkai , Gu Wenhua
Published: October 2022

Terahertz metamaterial absorbers are important functional devices for liquid analyte detection. In contrast to general metamaterial absorbers with single-layer metasurfaces that possess only one resonant mode, a triple-band terahertz metamaterial absorber formed by a single layer of symmetrically arrayed snowflake-shaped resonators was proposed in this study. The simulation results showed that the absorption of the metamaterial absorber reached 97.43% at 0.550 THz, 79.22% at 1.249 THz, and 99.02% at 1.867 THz with narrow resonant peaks. The resonant frequencies were sensitive to the refractive index of the surrounding medium at a fixed analyte thickness, which would play an important role in the performance of the sensor for detecting changes in the surrounding refractive index. The maximum value of the refractive index sensitivity was 137.70 GHz/RIU, 306.25 GHz/RIU, and 473.86 GHz/RIU, with a figure of merit (FoM) of 3.14, 2.33, and 6.46, respectively, for refractive index values ranging from 1.0 to 2.2 under three resonant modes. It is worth noting that most of the liquid samples showed a refractive index ranging from 1.0 to 2.0. Furthermore, the identification of peanut oil, carbon disulfide, and turpentine was considered to verify that the proposed terahertz sensor could be used for high-sensitivity liquid detection and has broad development prospects in the field of detecting and sensing.
All-Fiber Wavelength-Tunable Narrow-Linewidth Polarization-Maintaining Tm-Doped Fiber MOPA System
Authors: Sun Tianran , Su Xinyang , Zhang Yunhong , Zhang Huaiwei , Xu Tianjia , Zheng Yi
Published: October 2022

An all-fiber wavelength-tunable narrow-linewidth polarization-maintaining (PM) Tm-doped fiber master oscillator power amplifier (MOPA) system is presented. We demonstrate an all-fiber ring cavity Tm-doped fiber master-oscillator (MO) with a tuning range of 110 nm (from 1925 to 2034 nm). The maximum output power of 459 mW is obtained at 1992.9 nm for 16 W of launched pump power at 793 nm, corresponding to a slope efficiency of 5.6% concerning launched pump power. By using a one-stage Tm-doped fiber amplifier combined with a high gain of >10 dB, the maximum slope efficiency is 12.6% and the output power is 5.65 W at 1993 nm. The 3 dB linewidth is less than 0.5 nm, M2 ≈ 1.25, and the polarization extinction ratio (PER) reaches 21.4 dB. The influence of different active fiber lengths on laser amplification is also studied.
Production and Biological Assessment of VNIISPK Cultivars of Various Ploidy for the Zone of Temperate Continental Climate
Authors: Krasova Nina , Ozherelieva Zoya , Galasheva Anna , Lupin Maksim
Published: October 2022

Increasing the reliability of fruit crops in unstable weather conditions of a temperate continental climate has become particularly relevant. This research was carried out based on a bioresource collection from the Russian Research Institute of Fruit Crop Breeding (VNIISPK BRC). Apple cultivars (diploids and triploids) of different maturation periods were studied. Triploid cultivars (3×) of summer maturation were developed using diploid gametes of the ‘Papirovka tetraploid’ cultivar as a donor (2-4-4-4×), triploids of winter maturation were developed using 13-6-106 (Suvorovetz: open pollination), and ‘Wealthy tetraploid’ (2-4-4-4×) or ‘Giant Spy’ (2-4-4-4×) were used as donors of diploid gametes. ‘Antonovka’ and ‘Melba’ were taken as control cultivars. The aim of this work was to evaluate the apple breeding cultivars according to the main economic and biological indicators and to determine the threshold of resistance to unfavorable conditions of the winter period for possible cultivation in specific conditions of a temperate continental climate. As a result of using the method of modeling damaging factors, apple cultivars that withstood not only the critical temperatures of January, but also especially dangerous frosts after thaws at the end of winter were identified, with the stability of vital tissues at the level of ‘Antonovka’ (a control cultivar), scab immune cultivars (RVi6) ‘Ivanovskoye’, ‘Zdorovie’ and ‘Pamyati Hitrovo’, and immune triploids (3×) ‘Vavilovskoye’, ‘Aleksandr Boyko’, Rozhdestvenskoye’ and ‘Academic Saveliev’. During the whole winter, the winter resistance of summer scab immune triploids, ‘Zhilinskoye’, ‘Maslovskoye’, ‘Yablochny Spas’ and ‘Spasskoye’, was at the level of ‘Antonovka’, but was higher than ‘Melba’. The high precocity of scab-immune cultivars, ’Afrodita’, ‘Ivanovskoye’, ‘Veniaminovskoye’, and ‘Yubiley Moskvy’, and triploids ‘Patriot’ and ‘Rozhdestvenskoye’, have been identified. Triploid cultivars are superior to diploid cultivars and control ‘Antonovka’ in fruit size. According to the complex of characteristics, promising apple cultivars were identified for planting in intensive orchards of the temperate continental climate zones, namely ‘Avgusta’ and ‘Solnyshko’ (summer cultivars), and ‘Aleksandr Boyko’, ‘Vavilovskoye’, ‘Venyaminovskoye’, ‘Ivanovskoye’ and ‘Rozhdestvenskoye’ (winter cultivars).
Drought-Induced Responses in Maize under Different Vapor Pressure Deficit Conditions
Authors: Devi Mura Jyostna , Reddy Vangimalla R. , Timlin Dennis
Published: October 2022

Water stress in plants depends on the soil water level and the evaporative demand. In this study, the physiological, biochemical, and molecular response of maize were examined under three evaporative demand conditions (low—1.00 kPa, medium—2.2 kPa, and high—4.00 kPa Vapor pressure deficit (VPD)) at three different soil water content (SWC); well-watered, 45%, and 35% SWC. Plants grown at 35% SWC under high VPD had significant (p < 0.01) lower leaf weight, leaf area, and leaf number than low VPD. Plants under low, medium, and high VPD with drought stress (45% and 35% SWC) showed a 30 to 60% reduction in their leaf area compared to well-watered plants. Gas exchange parameters including photosynthesis, stomatal conductance, and water use efficiency exhibited significant differences (p < 0.01) between treatments, with the highest reduction occuring at 35% SWC and high VPD. Both drought and VPD significantly (p < 0.01) increased C4 enzyme levels and some transcription factors with increased stress levels. Transcription factors primarily related to Abssisic Acid (ABA) synthesis were upregulated under drought, which might be related to high ABA levels. In summary, severe drought levels coupled with high VPD had shown a significant decrease in plant development by modifying enzymes, ABA, and transcription factors.
Rheological, Surface Tension and Conductivity Insights on the Electrospinnability of Poly(lactic-co-glycolic acid)-hyaluronic Acid Solutions and Their Correlations with the Nanofiber Morphological Characteristics
Authors: Liu Ziqian , Ramakrishna Seeram , Ahmed Ifty , Rudd Chris , Liu Xiaoling
Published: October 2022

In this study, solutions were prepared with fixed concentrations of hyaluronic acid (HA) but varied concentrations of poly (lactic-co-glycolic acid) (PLGA) to emphasize the effects of PLGA concentration and HA addition on solution properties and to further evaluate their electrospinning performance. The dependence of specific viscosity on PLGA concentration was studied to determine the concentration regimes and evaluate the critical concentration (Ce) for successful fiber generation. The Ce of PLGA solutions is 12.07% compared to 10.09% for PLGA-HA solutions. Blending with HA results in a lower concentration dependence and better consistency to the theoretical scaling mechanisms due to the additional topological constrains, which thus result in more chain entanglements. Solutions in semi-dilute entangled regimes show the crossover of complex moduli, verifying the stable and reliable entanglement network. Higher concentrations and HA addition both led to lower crossover frequencies and, thus, a longer relaxation time. The effects of a higher PLGA concentration and HA addition on the surface tension were not evident. However, the HA addition significantly improved the solution conductivity up to three times in the pure PLGA solutions due to its polyelectrolyte nature. Defect-free and uniform nanofibers were generated from 35% to 40% of the PLGA-HA solutions, yet fibers with bead-on-string structures were produced from all studied pure PLGA solutions. Such solution characteristics and parametric correlations can provide predictive insights on tailoring the morphological characteristics of nanofibers for specific applications.
Capillary Thinning of Viscoelastic Threads of Unentangled Polymer Solutions
Authors: Semenov Alexander , Nyrkova Irina
Published: October 2022

In this paper, we theoretically consider the process of the capillary thinning of a polymer fluid thread bridging two large immobile droplets in the regime of highly stretched polymer chains. We first derive a new relation between the pressure p and the flow velocity v in unentangled polymer solutions, which is called the anti-Bernoulli law: it shows that p is higher where v is faster. Using this equation, it is shown that the flow field is asymptotically irrotational, in particular, in the thread/droplet transition zones (in the case, the negligible solvent viscosity and inertial effects). On this basis, we predict the free surface profile and the thread thinning law for the FENE-P model of polymer dynamics. The predictions are compared with recent theoretical results and some experimental data on capillary thinning.
Bacillus coagulans BACO-17 Alone or in Combination with Galacto-Oligosaccharide Ameliorates Salmonella-Induced Diarrhea and Intestinal Inflammation
Authors: Wu Min-Zi , Sun Tsai-Chien , Huang Yu-Wen , Wu Yi-Ching , Chen Wei-Jen , Chu Hui-Fang , Liu Cheng-Yen , Chau Chi-Fai
Published: October 2022

In this study, a diarrhea model was established by exposing rats to appropriate antibiotics and Salmonella. After an in vitro screening of prebiotics, fructo-oligosaccharide and galacto-oligosaccharide (GOS) were selected; their synbiotic potential and ability to ameliorate diarrhea symptoms and intestinal inflammation with Bacillus coagulans BACO-17 were evaluated in vivo. After a 27-day feeding experiment including antibiotic intervention and Salmonella infection, it was found that using B. coagulans BACO-17 alone and in combination with GOS as a synbiotic could render a better recovery by lowering diarrhea indexes by 26.9% and 18.7%, respectively. Compared with the negative control, the administration of this synbiotic mixture resulted in the most significant increase in fecal concentrations of total short-chain fatty acids (about 2-fold higher), with a promising improvement in disrupted gut microbial balance. It was worth noting that the administration of B. coagulans BACO-17 alone or in combination with GOS effectively reduced intestinal inflammation (27–31%) and mucosal necrosis (82%) over the negative control. These results suggested that B. coagulans BACO-17 and GOS could be exploited as a promising synbiotic mixture to relieve intestinal inflammatory diseases and improve gut health.
Solid Oxide Fuel Cell-Based Polygeneration Systems in Residential Applications: A Review of Technology, Energy Planning and Guidelines for Optimizing the Design
Authors: Ramadhani Farah , Hussain M. A. , Mokhlis Hazlie , Erixno Oon
Published: October 2022

Solid oxide fuel cells are an emerging energy conversion technology suitable for high-temperature power generation with proper auxiliary heat. Combining SOFCs and polygeneration has produced practical applications for modern energy system designs. Even though many researchers have reviewed these systems’ technologies, opportunities and challenges, reviews regarding the optimal strategy for designing and operating the systems are limited. Polygeneration is more complicated than any other energy generation type due to its ability to generate many types of energy from various prime movers. Moreover, integration with other applications, such as vehicle charging and fueling stations, increases the complication in making the system optimally serve the loads. This study elaborates on the energy planning and guidelines for designing a polygeneration system, especially for residential applications. The review of polygeneration technologies also aligns with the current research trend of developing green technology for modern and smart homes in residential areas. The proposed guideline is expected to solve the complication in other applications and technologies and design the polygeneration system optimally.
Distribution Network Fault-Line Selection Method Based on MICEEMDAN–Recurrence Plot–Yolov5
Authors: Hou Sizu , Xu Yan , Guo Wei
Published: October 2022

Distribution system fault signals contain severe noise components. In order to solve the problem of distribution network fault-line selection, a fault-line selection method based on modifying the Improved Complete Ensemble Empirical Mode Decomposition Adaptive Noise (MICEEMDAN) algorithm, Recurrence Plot, and Yolov5 network is proposed. First, ICEEMDAN is optimized using multi-scale weighted permutation entropy (MWPE). MICEEMDAN can decompose an electrical signal into a series of intrinsic mode functions (IMFs). Recurrence Plot transformation of all IMFs, obtained from decomposition and stitching from top to bottom, realizes the conversion of 1D time series to 2D images. Then, the recurrence maps obtained from all lines in the distribution network are stitched to obtain the distribution network recurrence map, realizing the mining of the fault-signal features of the whole distribution network. Finally, the Yolov5 network is used to mine the fault features of the recurrence map of the distribution network autonomously to realize the fault-line selection. The experiments show that the method has a good noise immunity and 99.98% fault-selection accuracy, which can effectively complete the distribution network fault selection.
Finite Rate Reaction Mechanism Adapted for Modelling Pseudo-Equilibrium Pyrolysis of Cellulose
Authors: Chandía Tomás Mora
Published: October 2022

This manuscript is related to a formulation for modelling cellulose pyrolysis with a pseudo-equilibrium approach. The objective is to model the kinetics of the cellulose pyrolysis with a semi-global mechanism obtained from the literature in order to obtain the yield and the rate of formation, mainly that of char. The pseudo-equilibrium approach consists of the assumption that the solid phase devolatilisation can be described kinetically—at a finite rate—thus preserving the competitive characteristic between the production of char and tar, while the gas phase can be described directly by means of chemical equilibrium. The aforementioned approach gives a set of ordinary, linear, and nonlinear differential equations that are solved numerically with a consistent numerical scheme (i.e., the Totally Implicit Euler method). Chemical equilibrium was solved using CANTERA coupled with a code written in MATLAB. The results showed that the scheme preserved the tar-gas competitive characteristic for cellulose pyrolysis. The gas phase was defined as a mixture of CO2, CO, H2O, CH4, H2, and N2, showing a similar composition compared to models from the literature. Finally, the extension of the model to biomass in general is straightforward for including hemicellulose and lignin. The formulation is described in detail throughout the document in order to be replicated and evaluated for other biological components.
Religious Education in Transition: From Content-Centred to Student-Centred
Authors: Sultana Carl-Mario
Published: October 2022

Catholic Religious Education as a subject in school curricula is an area in which the need for change is constantly felt. This change is driven by the paradigm shift in anthropology brought about by Vatican Council II, which sought to put the human being at the centre. Notwithstanding this shift proposed more than 50 years ago, we are still struggling to handle and implement this change. In practice, this calls for a re-evaluation of the traditional doctrinal methods, which have been associated with teaching Religious Education in the past and seeking to adopt new methods which are more anthropological and depart from where the human being actually stands and seek to answer the existential questions which contemporary human beings pose. The point of departure for such a vision is the etymological meaning of the term ‘education’ from the Latin root educere. In practical terms, such a shift from a content-centred to a more student-centred approach entails adopting a constructivist approach and putting into practice the principles of what is referred to as ‘Adaptive Religious Education’, which seeks to educate children in all the six dimensions of the human being simultaneously in a holistic way.
Re-Evaluating the Notion of Isrâ and Mi’râj in Ibadi Tradition: With Special References to the Modern Sirah Readings
Authors: Albayrak Ismail , Shueily Sulaiman Al
Published: October 2022

The notion of mi’râj (the heavenly journey of Prophet Muhammad) is an important non-homogenic topic, although it is not often handled in Ibadi intellectual, sīrah (biography of the Prophet) and exegetical traditions. In this article, we analyse the treatment of the subject chronologically in the Ibadi tradition. We discuss the Ibadis’ main concerns on the subject, how they differ, what inferences they make from the related verses, sīrah, hadith and exegetical (tafsir) reports, and most importantly whether they accept the notion of mi’râj. This article analyses the notion of isrâ because of its close relationship to mi’râj. In summary, there are variations on the issue of mi’râj among the North African and Omani Ibadis. Even more interesting is the existence of significant nuances among the Omani Ibadis. In short, while all North African Ibadis accept mi’raj as an event, it is observed that some Omani Ibadis accept it, while others sometimes reject it for religious and sometimes rational grounds.
Quantitative Analysis of Tectonic Geomorphology Research Based on Web of Science from 1981 to 2021
Authors: Liu Zhiheng , Zhou Suiping , Yu Hang , Zhang Wenjie , Guo Fengcheng , Chen Xuemei , Guo Jianhua
Published: October 2022

Tectonic geomorphology is an important research area that uses multisource data to quantify the landscape response induced by the interaction between the tectonic uplift and climate changes. In this study, a comprehensive and quantitative analysis using bibliometric and scientometrics based on the research areas, countries, institutions, journals, authors, keywords, and citations is carried out, which provides an exhaustive history of tectonic geomorphology, and points out the hopspots and trends in the research area. A total of 2796 papers and 110,111 references from 1981 to 2021 are collected from Science Citation Index-Expanded (SCI-E) as the main data source. The results show that with the development of remote sensing, tectonic geomorphology, and the improvement of instruments and equipment, the amount of tectonic geomorphology analysis has been increasing. The journal Geomorphology is one of the most popular journals in this field. Through the co-occurrence network analysis, 12 clusters are identified in which the most popular research hotspot in tectonic geomorphology research is how to constrain the rates of active faulting using geomorphic indices. Through literature co-citation analysis, 13 research directions are extracted in which an important trend is to investigate the response of drainage divide migration to the fault slip rates. With the help of remote sensing data, physical attributes, and contextual knowledge, the reliability of measuring uplift rates under tectonic and climate changes has been increased. A future suggestion is to use multi-source heterogeneous data fusion to conduct quantitative analysis for tectonic geomorphology research.
Accurate Estimation of Chlorophyll-a Concentration in the Coastal Areas of the Ebro Delta (NW Mediterranean) Using Sentinel-2 and Its Application in the Selection of Areas for Mussel Aquaculture
Authors: Fernández-Tejedor Margarita , Velasco Jorge Enrique , Angelats Eduard
Published: October 2022

Multispectral satellite remote sensing imagery, together with appropriate modeling, have been proven to provide chlorophyll-a maps that are useful to evaluate the suitability of coastal areas for carrying out shellfish aquaculture. However, current approaches used for chlorophyll-a estimation in very shallow coastal areas often fail in their accuracy. To overcome this limitation, an algorithm that provides an accurate estimation of chlorophyll-a concentration in the coastal areas of the Ebro delta (North Western Mediterranean) using atmospherically corrected Sentinel 2 (S2) remote sensing reflectances (Rrs) has been calibrated and validated. The derived chlorophyll-a maps created have been used in a dynamic carrying capacity model that covers areas from very rich waters inside the embayment to the more oligotrophic waters in the open sea. The use of carrying capacity models is recommended to evaluate the potential of marine coastal areas for bivalve mollusk aquaculture. In this context, the depletion of chlorophyll-a is an indicator of negative environmental impact and thus a continuous monitoring of chlorophyll-a is key. The proposed methodology allows estimation of chlorophyll-a concentration from Sentinel-2 with an accuracy higher than 70% in most cases. The carrying capacity and the suitability of the external areas of the Ebro delta have been determined. The results show that these areas can hold a significant mussel production. The methodology presented in this study aims to provide a tool to the shellfish aquaculture industry.
Real-Time Detection and Classification of Power Quality Disturbances
Authors: Mozaffari Mahsa , Doshi Keval , Yilmaz Yasin
Published: October 2022

This paper considers the problem of real-time detection and classification of power quality disturbances in power delivery systems. We propose a sequential and multivariate disturbance detection method (aiming for quick and accurate detection). Our proposed detector follows a non-parametric and supervised approach, i.e., it learns nominal and anomalous patterns from training data involving clean and disturbance signals. The multivariate nature of the method enables joint processing of data from multiple meters, facilitating quicker detection as a result of the cooperative analysis. We further extend our supervised sequential detection method to a multi-hypothesis setting, which aims to classify the disturbance events as quickly and accurately as possible in a real-time manner. The multi-hypothesis method requires a training dataset per hypothesis, i.e., per each disturbance type as well as the ’no disturbance’ case. The proposed classification method is demonstrated to quickly and accurately detect and classify power disturbances.
CeRA-eSP: Code-Expanded Random Access to Enhance Success Probability of Massive MTC
Authors: Youn Jiseung , Park Joohan , Oh Joohyun , Kim Soohyeong , Ahn Seyoung , Cho Sunghyun , Park Sangwoo , You Cheolwoo
Published: October 2022

With the growing interest in the Internet of Things (IoT), research on massive machine-type communication (mMTC) services is being actively promoted. Because mMTC services are required to serve a large number of devices simultaneously, a lack of resources during initial access can be a significant problem when providing mMTC services in cellular networks. Various studies on efficient preamble transmission have been conducted to solve the random access problem of mMTC services. However, supporting a large number of devices simultaneously with limited resources is a challenging problem. In this study, we investigate code-expanded random access (CeRA), which extends the limited preamble resources to the code domain to decrease the high collision rate. To solve the existing CeRA phantom codeword and physical uplink shared channel (PUSCH) resource shortage problems, we propose an optimal preamble codeword set selection algorithm based on mathematical analysis. The simulation results indicate that the proposed code-expanded random access scheme to enhance success probability (CeRA-eSP) achieves a higher random access success rate with a lower access delay compared to the existing random access schemes.
A Robust Faster R-CNN Model with Feature Enhancement for Rust Detection of Transmission Line Fitting
Authors: Guo Zhimin , Tian Yangyang , Mao Wandeng
Published: October 2022

Rust of transmission line fittings is a major hidden risk to transmission safety. Since the fittings located at high altitude are inconvenient to detect and maintain, machine vision techniques have been introduced to realize the intelligent rust detection with the help of unmanned aerial vehicles (UAV). Due to the small size of fittings and disturbance of complex environmental background, however, there are often cases of missing detection and false detection. To improve the detection reliability and robustness, this paper proposes a new robust Faster R-CNN model with feature enhancement mechanism for the rust detection of transmission line fitting. Different from current methods that improve feature representation in front end, this paper adopts an idea of back-end feature enhancement. First, the residual network ResNet-101 is introduced as the backbone network to extract rich discriminative information from the UAV images. Second, a new feature enhancement mechanism is added after the region of interest (ROI) pooling layer. Through calculating the similarity between each region proposal and the others, the feature weights of the region proposals containing target object can be enhanced via the overlaying of the object’s representation. The weight of the disturbance terms can then be relatively reduced. Empirical evaluation is conducted on some real-world UAV monitoring images. The comparative results demonstrate the effectiveness of the proposed model in terms of detection precision and recall rate, with the average precision of rust detection 97.07%, indicating that the proposed method can provide an reliable and robust solution for the rust detection.
Determining Exception Context in Assembly Operations from Multimodal Data
Authors: Simonič Mihael , Majcen Hrovat Matevž , Džeroski Sašo , Ude Aleš , Nemec Bojan
Published: October 2022

Robot assembly tasks can fail due to unpredictable errors and can only continue with the manual intervention of a human operator. Recently, we proposed an exception strategy learning framework based on statistical learning and context determination, which can successfully resolve such situations. This paper deals with context determination from multimodal data, which is the key component of our framework. We propose a novel approach to generate unified low-dimensional context descriptions based on image and force-torque data. For this purpose, we combine a state-of-the-art neural network model for image segmentation and contact point estimation using force-torque measurements. An ensemble of decision trees is used to combine features from the two modalities. To validate the proposed approach, we have collected datasets of deliberately induced insertion failures both for the classic peg-in-hole insertion task and for an industrially relevant task of car starter assembly. We demonstrate that the proposed approach generates reliable low-dimensional descriptors, suitable as queries necessary in statistical learning.
Deep Learning in Controlled Environment Agriculture: A Review of Recent Advancements, Challenges and Prospects
Authors: Ojo Mike O. , Zahid Azlan
Published: October 2022

Controlled environment agriculture (CEA) is an unconventional production system that is resource efficient, uses less space, and produces higher yields. Deep learning (DL) has recently been introduced in CEA for different applications including crop monitoring, detecting biotic and abiotic stresses, irrigation, microclimate prediction, energy efficient controls, and crop growth prediction. However, no review study assess DL’s state of the art to solve diverse problems in CEA. To fill this gap, we systematically reviewed DL methods applied to CEA. The review framework was established by following a series of inclusion and exclusion criteria. After extensive screening, we reviewed a total of 72 studies to extract the useful information. The key contributions of this article are the following: an overview of DL applications in different CEA facilities, including greenhouse, plant factory, and vertical farm, is presented. We found that majority of the studies are focused on DL applications in greenhouses (82%), with the primary application as yield estimation (31%) and growth monitoring (21%). We also analyzed commonly used DL models, evaluation parameters, and optimizers in CEA production. From the analysis, we found that convolutional neural network (CNN) is the most widely used DL model (79%), Adaptive Moment Estimation (Adam) is the widely used optimizer (53%), and accuracy is the widely used evaluation parameter (21%). Interestingly, all studies focused on DL for the microclimate of CEA used RMSE as a model evaluation parameter. In the end, we also discussed the current challenges and future research directions in this domain.
Analysis of Structural Health Monitoring Data with Correlated Measurement Error by Bayesian System Identification: Theory and Application
Authors: Mu He-Qing , Liang Xin-Xiong , Shen Ji-Hui , Zhang Feng-Liang
Published: October 2022

Measurement error is non-negligible and crucial in SHM data analysis. In many applications of SHM, measurement errors are statistically correlated in space and/or in time for data from sensor networks. Existing works solely consider spatial correlation for measurement error. When both spatial and temporal correlation are considered simultaneously, the existing works collapse, as they do not possess a suitable form describing spatially and temporally correlated measurement error. In order to tackle this burden, this paper generalizes the form of correlated measurement error from spatial correlation only or temporal correlation only to spatial-temporal correlation. A new form of spatial-temporal correlation and the corresponding likelihood function are proposed, and multiple candidate model classes for the measurement error are constructed, including no correlation, spatial correlation, temporal correlation, and the proposed spatial-temporal correlation. Bayesian system identification is conducted to achieve not only the posterior probability density function (PDF) for the model parameters, but also the posterior probability of each candidate model class for selecting the most suitable/plausible model class for the measurement error. Examples are presented with applications to model updating and modal frequency prediction under varying environmental conditions, ensuring the necessity of considering correlated measurement error and the capability of the proposed Bayesian system identification in the uncertainty quantification at the parameter and model levels.
Adaptive Data Selection-Based Machine Learning Algorithm for Prediction of Component Obsolescence
Authors: Moon Kyoung-Sook , Lee Hee Won , Kim Hongjoong
Published: October 2022

Product obsolescence occurs in the manufacturing industry as new products with better performance or improved cost-effectiveness are developed. A proactive strategy for predicting component obsolescence can reduce manufacturing losses and lead to customer satisfaction. In this study, we propose a machine learning algorithm for a proactive strategy based on an adaptive data selection method to forecast the obsolescence of electronic diodes. Typical machine learning algorithms construct a single model for a dataset. By contrast, the proposed algorithm first determines a mathematical cover of the dataset via unsupervised clustering and subsequently constructs multiple models, each of which is trained with the data in one cover. For each data point in the test dataset, an optimal model is selected for regression. Results of empirical experiments show that the proposed method improves the obsolescence prediction accuracy and accelerates the training procedure. A novelty of this study is that it demonstrates the effectiveness of unsupervised clustering methods for improving supervised regression algorithms.
Review of Fundamental Active Current Extraction Techniques for SAPF
Authors: Baros Jan , Sotola Vojtech , Bilik Petr , Martinek Radek , Jaros Rene , Danys Lukas , Simonik Petr
Published: October 2022

The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods. Shunt active power filters are highly desirable to minimize losses due to the increase in the number of nonlinear loads (deformed power). Currently, there is rapid development in new adaptive, non-adaptive, and especially hybrid methods of digital signal processing. Nowadays, modern methods of digital signal processing maintain a key role in research and industrial applications. Many of the best practices that have been used to control shunt active power in industrial practice for decades are now being surpassed in favor of new progressive approaches. This systematic research review classifies the importance of using advanced signal processing methods in the field of shunt active power filter control methods and summarizes the extant harmonic extraction methods, from the conventional approach to new progressive methods using genetic algorithms, artificial intelligence, and machine learning. Synchronization techniques are described and compared as well.
A Cooperative Routing Scheme Using Inter-Satellite Links to Assist Data Downloading for LEO Satellite Networks
Authors: Yang Zijian , Liu Huijie , Jin Jifeng , Tian Feng
Published: October 2022

Low earth orbit (LEO) satellite networks can provide Internet service to users in areas where cellular networks are difficult to deploy. One critical function of satellites is to transfer data from satellite networks to ground core network through earth stations (ESs). The Ka-band multiple-input multiple-output (MIMO) can be used to establish feeder links with larger bandwidth between satellites and ESs. However, propagation at the Ka band is subjected to rain attenuation and various atmospheric fading mechanisms, which severely reduce the maximum link capacity. As a result, the insufficient capacity of feed link becomes the throughput bottleneck of satellite networks. In order to increase network throughput, it is important to fully use feeder link resources. In this paper, we propose a cooperation scheme to route packets to ESs through a well-resourced feeder link, such that the bandwidth of the feeder links can be fully utilized and the throughput of data downloading at the ESs is maximized. Firstly, we model the satellite network system and the feeder link based on MIMO technology. Then, a Maximum-Flow-Minimum-Cost (MCMF) routing algorithm consisting of two Linear Programs (LPs) is presented to compute maximum-flow routings for data download. Eventually, a variety of simulations are conducted to assess the proposed scheme, which shows that the cooperative routing scheme outperforms the existing SiRRS method in terms of throughput and delay.
Parents’ and Teachers’ Expectations of School Social Workers
Authors: Csók Cintia , Pusztai Gabriella
Published: October 2022

In parallel with research focusing on the effectiveness of students and teachers, the content and impact of school social work have come to the forefront of international research discourses. In the Hungarian public education system, teachers had previously carried out social assistance tasks, but in September 2018, an external model of kindergarten and school social assistance activities was introduced, giving structure to the already existing work. No empirical studies have been performed on the results of implementation so far. Regarding this topic, our research question is, in what areas do parents and teachers expect the most from school social workers? To get answers, we conducted semi-structured interviews with 20 school social workers. During the analyses, we focused on the relationships established between parents and teachers, and also analysed partners’ expectations. One of the most important results of the research is that, with social workers in mind, we created systematised parent and pedagogical types. We compared the services required by parents and teachers with the social assistance reform concept. We point out that while the Social Assistance Regulation empowers these professionals primarily for preventive, group and community activities, parents and teachers alike expect individual-focused assistance.
Texas in Transition: Considering the Production of Grapes, Wine, and Place
Authors: Myles Colleen C. , Townsend Christi G. , Collins Kourtney
Published: October 2022

Given the state’s growing prominence in the United States wine industry, paired with its relative obscurity, we explore the cultural and environmental transformation of the state of Texas from the perspective of the b(l)ooming wine industry. Using a qualitative, narrative approach, focused on the two largest and most productive appellations in the state, we form a framework for understanding the historical and contemporary context for wine in Texas. Through participant observation and targeted interviews with growers, winemakers, and other wine industry insiders, we uncover how wine has become a major part of the regional identity of the Texas Hill Country and High Plains. We find that, even though the best wines made in Texas are made from lesser known and harder to market varietals, Texans have embraced the wine (culture) produced in their state. Though, as elsewhere, the industry in Texas is complex and multifaceted, it is still evolving, and industry actors are focusing on making a high quality, tasty product in order to compete with other wine industry giants. Although growers in the Hill Country and High Plains face various challenges, these circumstances demand creativity. However, the challenging circumstances and accompanying creativity are precisely what drive the unique tastes of Texas wines, a reality the Texas wine industry has begun to embrace.
Arbuscular Mycorrhizal Fungi Improve Growth and Phosphate Nutrition of Acacia seyal (Delile) under Saline Conditions
Authors: Manga Anicet Georges Bruno , Ndiaye Malick , Ndiaye Mame Arama Fall , Sané Seyni , Diop Tahir Abdoulaye , Diatta André Amakobo , Bassene César , Min Doohong , Battaglia Martin , Harrison Matthew Tom
Published: October 2022

Many plant species adapted to semi-arid environments are grown in the Sahelian region in northern Africa. One such species is Acacia seyal (Delile), a multipurpose leguminous tree grown in various agroecological zones, including saline soils. These challenging arid and semi-arid environments harbor a diversity of arbuscular mycorrhizal fungi (AMF) communities that can develop symbiotic associations with plants to improve their hydromineral nutrition. This study compared the effects of native AMF communities isolated from semi-arid sites (high, moderate, and low salinity zones Ndiafate, Ngane, and Bambey, respectively) and the AMF Rhizoglomus aggregatum on the development and phosphate nutrition of A. seyal seedlings subject to three salinity treatments (0, 340, and 680 mM). Plant height, dry matter weight of the shoots and roots, and phosphorus uptake from the soil were measured. Plants inoculated with AMF native species from each site that were provided with up to 340 mM of NaCl had greater shoot height than plants grown under 680 mM salinity. At NaCl concentrations above 340 mM, shoot and root development of A. seyal seedlings diminished. However, dry matter production of shoots (7%) and roots (15%) improved following AMF inoculation compared with the control (respectively 0.020 and 0.07 g for shoots and roots). When inoculated with AMF isolates from the high salinity zone (Ndiafate), phosphate content/nutrition was increased by 10% around 30 days after inoculation compared with non-inoculated seedlings (2.84 mg/kg of substrate). These results demonstrate that native AMF inoculants are capable of helping plants withstand environmental constraints, especially those exposing plants to harsh climatic conditions. We discuss insights on how AMF influences the interplay between soil phosphorus and perceived salinity that may have implications for broader relationships between plants and symbiotic fungi.