bluuebunny/crossref_metadata_2025 huggingface dataset:
Pulsed Multifrequency Excitation and Spectrogram Eddy Current Testing (PMFES-ECT) for Nondestructive Evaluation of Conducting Materials
Authors: Grochowalski Jacek Michał , Chady Tomasz
Published: September 2021

This paper presents a new method for nondestructive testing—a pulsed multifrequency excitation and spectrogram eddy current testing (PMFES-ECT), which is an extension of the multifrequency excitation and spectrogram eddy current testing. The new method uses excitation in the form of pulses repeated at a specified time, containing several periods of a waveform consisting of the sum of sinusoids with a selected frequency, amplitude and phase. This solution allows the maintenance of the advantages of multifrequency excitation and, at the same time, generates high energy pulses similar to those used in pulse eddy current testing (PECT). The effectiveness of the new method was confirmed by numerical simulations and the measurement of thin Inconel plates, consisting of notches manufactured by the electric-discharge method.
Study on Adaptability of Test Methods for Workability of Fresh Self-Compacting SFRC
Authors: Ding Xinxin , Geng Haibin , Shi Kang , Song Li , Li Shangyu , Liu Guirong
Published: September 2021

To ensure the quality of concrete construction, the workability of fresh mix measured by rational test methods is critical to be controlled. With the presence of steel fibers, whether the test methods and evaluation indices of fresh self-compacting concrete (SCC) are adaptable for self-compacting steel fiber reinforced concrete (SFRC) needs to be systematically verified. In this paper, seven groups of self-compacting SFRC, referenced with one group SCC, were prepared by using the mix proportion design method based on the steel fiber-aggregates skeleton packing test. The main factors included the volume fraction and the length of hooked-end steel fiber. Tests for filling ability, passing ability, and stability of fresh self-compacting SFRC and SCC were carried out. Results indicate that the adaptability was well for the slump-flow test with indices of slump flow and flow time T500 to evaluate the filling ability, the J-ring flow test with an index of PA level to evaluate the passing ability, and the static segregation test with an index of static segregation resistance to evaluate the stability of fresh self-compacting SFRC. By the repeated tests and measurements, the slump cone should be vertically lifted off to a height of 300 mm within 3 s at a constant speed, the spacing of the rebar in the J-ring test should be adjusted to be two times the fiber length. If the table jumping test is used, the dynamic segregation percent should be increased to 35% to fit the result of the static segregation test. Good workability of the self-compacting SFRC prepared in this study is presented with the general evaluation of test results.
An Area Coverage Scheme Based on Fuzzy Logic and Shuffled Frog-Leaping Algorithm (SFLA) in Heterogeneous Wireless Sensor Networks
Authors: Rahmani Amir Masoud , Ali Saqib , Yousefpoor Mohammad Sadegh , Yousefpoor Efat , Naqvi Rizwan Ali , Siddique Kamran , Hosseinzadeh Mehdi
Published: September 2021

Coverage is a fundamental issue in wireless sensor networks (WSNs). It plays a important role in network efficiency and performance. When sensor nodes are randomly scattered in the network environment, an ON/OFF scheduling mechanism can be designed for these nodes to ensure network coverage and increase the network lifetime. In this paper, we propose an appropriate and optimal area coverage method. The proposed area coverage scheme includes four phases: (1) Calculating the overlap between the sensing ranges of sensor nodes in the network. In this phase, we present a novel, distributed, and efficient method based on the digital matrix so that each sensor node can estimate the overlap between its sensing range and other neighboring nodes. (2) Designing a fuzzy scheduling mechanism. In this phase, an ON/OFF scheduling mechanism is designed using fuzzy logic. In this fuzzy system, if a sensor node has a high energy level, a low distance to the base station, and a low overlap between its sensing range and other neighboring nodes, then this node will be in the ON state for more time. (3) Predicting the node replacement time. In this phase, we seek to provide a suitable method to estimate the death time of sensor nodes and prevent possible holes in the network, and thus the data transmission process is not disturbed. (4) Reconstructing and covering the holes created in the network. In this phase, the goal is to find the best replacement strategy of mobile nodes to maximize the coverage rate and minimize the number of mobile sensor nodes used for covering the hole. For this purpose, we apply the shuffled frog-leaping algorithm (SFLA) and propose an appropriate multi-objective fitness function. To evaluate the performance of the proposed scheme, we simulate it using NS2 simulator and compare our scheme with three methods, including CCM-RL, CCA, and PCLA. The simulation results show that our proposed scheme outperformed the other methods in terms of the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime.
Real-Time Data Assimilation in Welding Operations Using Thermal Imaging and Accelerated High-Fidelity Digital Twinning
Authors: Pereira Álvarez Pablo , Kerfriden Pierre , Ryckelynck David , Robin Vincent
Published: September 2021

Welding operations may be subjected to different types of defects when the process is not properly controlled and most defect detection is done a posteriori. The mechanical variables that are at the origin of these imperfections are often not observable in situ. We propose an offline/online data assimilation approach that allows for joint parameter and state estimations based on local probabilistic surrogate models and thermal imaging in real-time. Offline, the surrogate models are built from a high-fidelity thermomechanical Finite Element parametric study of the weld. The online estimations are obtained by conditioning the local models by the observed temperature and known operational parameters, thus fusing high-fidelity simulation data and experimental measurements.
A Model-Based Predictive Controller of the Level of Steel in the Mold with Disturbances Using a Repetitive Structure
Authors: Pereira Rogério P. do A. , Almeida Gustavo M. de , Salles José L. Felix , Cuadros Marco A. de S. L. , Valadão Carlos T. , Freitas Ricardo O. de , Bastos-Filho Teodiano
Published: September 2021

Keeping the level of steel in the mold of the continuous casting process constant is fundamental for the quality of the steel produced and, consequently, its commercial value. It is challenging, considering the several disturbances that cause undesired variations in the mold level. The aim of this paper is to apply a repetitive structure composed of two controllers, a generalized predictive controller (GPC) and a repetitive GPC (R-GPC) with constraints to mitigate the bulging and clogging/unclogging disturbances and the casting speed variation in the mold level of the process. The R-GPC controller has the same characteristics as the GPC, such as performance, robustness to disturbances, and insertion of constraints, and its advantage is the elimination of periodic disturbances. The repetitive structure will be implemented with a robustness filter and tuned by a genetic algorithm (GA). The controller tests are performed by simulations of a nonlinear mathematical model of the mold level, validated using real data from the steel industry. The proposed controller reduces the bulging disturbance amplitude by 98.5% and at 25% of the frequency of reversions in the valve. Consequently, the proposed controller allows an increase in the valve life span, a reduction in maintenance costs, and quality improvement in the steel slab.
Corrosion Behavior of Copper Bearing Steels and the Derived In-Situ Coating
Authors: Li Na , Yan Ling , Wang Shaodong , Wang Changshun , Zhang Hongmei , Ai Fangfang , Jiang Zhengyi
Published: September 2021

Using a period immersion wet/dry cyclic corrosion test, in-situ copper-coated steels prepared by corroding copper-bearing steels were investigated in this study. The steel with a higher copper content (>3%) has a higher initial corrosion rate due to its obvious two-phase microstructure. The corrosion rates of all copper bearing steels tend to be stable after a certain time of corrosion. A copper-rich layer is formed between the matrix and the rust layer, which is due to the diffusion of copper from the rust layer to the metal surface. The copper’s stability under this corrosion condition led to the formation of a thin copper-rich film, which was uncovered after removing the rust by choosing appropriate descaling reagents. The copper coating was generated from the matrix itself during the corrosion process at 25 °C, which provided a new approach for producing in-situ composite materials without any bonding defect. It is found that the corrosion rate, corrosion time, and copper content in steel all affect the formation of copper-rich layer. In addition to the noble copper surface, the electrochemical corrosion test results show that the corrosion resistance of copper-coated steel has been significantly improved.
Study on Lubrication Characteristics of C4-Alkane and Nanoparticle during Boundary Friction by Molecular Dynamics Simulation
Authors: Zheng Xuan , Su Lihong , Deng Guanyu , Zhang Jie , Zhu Hongtao , Tieu Anh Kiet
Published: September 2021

Lubricant has been widely applied to reduce wear and friction between the contact surfaces when they are in relative motion. In the current study, a nonequilibrium molecular dynamics (NEMD) simulation was specifically established to conduct a comprehensive investigation on the dynamic contact between two iron surfaces in a boundary friction system considering the mixed C4-alkane and nanoparticles as lubricant. The main research objective was to explore the effects of fluid and nanoparticles addition on the surface contact and friction force. It was found that nanoparticles acted like ball bearings between the contact surfaces, leading to a change of sliding friction mode to rolling friction mode. Under normal loads, plastic deformation occurred at the top surface because nanoparticles were mainly supporting the normal load. By increasing the number of C4-alkane molecules between two contact surfaces, the contact condition has been changed from partial to full lubrication. In addition, an attractive force from the solid–liquid LJ interaction between C4-alkane and surfaces was observed at the early stage of sliding, due to the large space formed by wall surfaces and nanoparticles. The findings in this paper would be beneficial for understanding the frictional behavior of a simple lubricant with or without nanoparticles addition in a small confinement.
Multilocus Genotyping of ‘Candidatus Phytoplasma solani’ Associated with Rubbery Taproot Disease of Sugar Beet in the Pannonian Plain
Authors: Ćurčić Živko , Kosovac Andrea , Stepanović Jelena , Rekanović Emil , Kube Michael , Duduk Bojan
Published: September 2021

Rubbery taproot disease of sugar beet (RTD), associated with ‘Candidatus Phytoplasma solani’, appeared in 2020 on an epidemic scale in northern Serbia and southern Slovakia, situated at opposite edges of the Pannonian Plain. In the affected locations where the disease was assessed, symptomatic sugar beets were analysed for phytoplasma infection. Additionally, multilocus sequence analyses of ‘Ca. P. solani’ strains on epidemiologically informative marker genes (tuf, stamp and vmp1) were performed. Symptomatic sugar beets from other countries of the Pannonian Plain (Croatia, Hungary and Austria), one sample from Germany, and red beets from Serbia were included in the analyses. ‘Ca. P. solani’ was detected in sugar beet in all assessed countries, as well as in red beet. Molecular analyses revealed the high genetic variability of ‘Ca. P. solani’ with the presence of all four tuf-types (a, b1, b2 and d), 14 stamp genotypes (seven new) and five vmp1 profiles (one new). The most common multilocus genotype in Serbia, Slovakia, Croatia, and Hungary was dSTOLg (tuf-d/STOL/V2-TA). It was dominant on sites with epidemic RTD outbreaks in the Pannonian Plain and in several sugar beet fields with non-epidemic RTD occurrence suggesting the prevalence of a particular epidemiological pathway during the epidemic’s phases.
Differences in Acid Stress Response of Lacticaseibacillus paracasei Zhang Cultured from Solid-State Fermentation and Liquid-State Fermentation
Authors: Wu Pengyu , Zhu Qiuyan , Yang Rui , Mei Yuxia , Chen Zhenmin , Liang Yunxiang
Published: September 2021

Liquid-state fermentation (LSF) and solid-state fermentation (SSF) are two forms of industrial production of lactic acid bacteria (LAB). The choice of two fermentations for LAB production has drawn wide concern. In this study, the tolerance of bacteria produced by the two fermentation methods to acid stress was compared, and the reasons for the tolerance differences were analyzed at the physiological and transcriptional levels. The survival rate of the bacterial agent obtained from solid-state fermentation was significantly higher than that of bacteria obtained from liquid-state fermentation after spray drying and cold air drying. However, the tolerance of bacterial cells obtained from liquid-state fermentation to acid stress was significantly higher than that from solid-state fermentation. The analysis at physiological level indicated that under acid stress, cells from liquid-state fermentation displayed a more solid and complete membrane structure, higher cell membrane saturated fatty acid, more stable intracellular pH, and more stable activity of ATPase and glutathione reductase, compared with cells from solid-state fermentation, and these physiological differences led to better tolerance to acid stress. In addition, transcriptomic analysis showed that in the cells cultured from liquid-state fermentation, the genes related to glycolysis, inositol phosphate metabolism, and carbohydrate transport were down-regulated, whereas the genes related to fatty acid synthesis and glutamate metabolism were upregulated, compared with those in cells from solid-state fermentation. In addition, some genes related to acid stress response such as cspA, rimP, rbfA, mazF, and nagB were up-regulated. These findings provide a new perspective for the study of acid stress tolerance of L. paracasei Zhang and offer a reference for the selection of fermentation methods of LAB production.
Phylogeny and Optimization of Trichoderma harzianum for Chitinase Production: Evaluation of Their Antifungal Behaviour against the Prominent Soil Borne Phyto-Pathogens of Temperate India
Authors: Mohiddin Fayaz A. , Padder Shahid A. , Bhat Arif H. , Ahanger Mohammad A. , Shikari Asif B. , Wani Shabir H. , Bhat Farooq A. , Nabi Sajad Un , Hamid Aflaq , Bhat Nazir A. , Sofi Najeebul R. , Waza Showkat A. , Hamid Burhan , Parveen Shugufta , Hussain Ashaq , Bhat Aadil N. , Ali Omar M. , Dar Mohammad S. , Abdel Latef Arafat Abdel Hamed
Published: September 2021

Trichoderma is the most commonly used fungal biocontrol agent throughout the world. In the present study, various Trichoderma isolates were isolated from different vegetable fields. In the isolated microflora, the colony edges varied from wavy to smooth. The mycelial forms were predominantly floccose with hyaline color and conidiophores among all the strains were highly branched. Based on morphological attributes, all the isolates were identified as Trichoderma harzianum. The molecular identification using multilocus sequencing ITS, rpb2 and tef1α, genes further confirmed the morphological identification. The average chitinase activity varied from 1.13 units/mL to 3.38 units/mL among the various isolates, which increased linearly with temperature from 15 to 30 °C. There was an amplified production in the chitinase production in the presence of Mg+ and Ca2+ and Na+ metal ions, but the presence of certain ions was found to cause the down-regulated chitinase activity, i.e., Zn2+, Hg2+, Fe2+, Ag+ and K+. All the chitinase producing Trichoderma isolates inhibited the growth of tested pathogens viz., Dematophora necatrix, Fusarium solani, Fusarium oxysporum and Pythium aphanidermatum at 25% culture-free filtrate concentration under in vitro conditions. Also, under in vivo conditions, the lowest wilt incidence and highest disease control on Fusarium oxysporum was observed in isolate BT4 with mean wilt incidence and disease control of 21% and 48%, respectively. The Trichoderma harzianum identified in this study will be further used in formulation development for the management of diseases under field conditions.
Fluorinated Boron-Based Anions for Higher Voltage Li Metal Battery Electrolytes
Authors: Clarke-Hannaford Jonathan , Breedon Michael , Rüther Thomas , Spencer Michelle J. S.
Published: September 2021

Lithium metal batteries (LMBs) require an electrolyte with high ionic conductivity as well as high thermal and electrochemical stability that can maintain a stable solid electrolyte interphase (SEI) layer on the lithium metal anode surface. The borate anions tetrakis(trifluoromethyl)borate ([B(CF3)4]−), pentafluoroethyltrifluoroborate ([(C2F5)BF3]−), and pentafluoroethyldifluorocyanoborate ([(C2F5)BF2(CN)]−) have shown excellent physicochemical properties and electrochemical stability windows; however, the suitability of these anions as high-voltage LMB electrolytes components that can stabilise the Li anode is yet to be determined. In this work, density functional theory calculations show high reductive stability limits and low anion–cation interaction strengths for Li[B(CF3)4], Li[(C2F5)BF3], and Li[(C2F5)BF2(CN)] that surpass popular sulfonamide salts. Specifically, Li[B(CF3)4] has a calculated oxidative stability limit of 7.12 V vs. Li+/Li0 which is significantly higher than the other borate and sulfonamide salts (≤6.41 V vs. Li+/Li0). Using ab initio molecular dynamics simulations, this study is the first to show that these borate anions can form an advantageous LiF-rich SEI layer on the Li anode at room (298 K) and elevated (358 K) temperatures. The interaction of the borate anions, particularly [B(CF3)4]−, with the Li+ and Li anode, suggests they are suitable inclusions in high-voltage LMB electrolytes that can stabilise the Li anode surface and provide enhanced ionic conductivity.
Tracing Viral Transmission and Evolution of Bovine Leukemia Virus through Long Read Oxford Nanopore Sequencing of the Proviral Genome
Authors: Pavliscak Laura A. , Nirmala Jayaveeramuthu , Singh Vikash K. , Sporer Kelly R. B. , Taxis Tasia M. , Kumar Pawan , Goyal Sagar M. , Mor Sunil Kumar , Schroeder Declan C. , Wells Scott J. , Droscha Casey J.
Published: September 2021

Bovine leukemia virus (BLV) causes Enzootic Bovine Leukosis (EBL), a persistent life-long disease resulting in immune dysfunction and shortened lifespan in infected cattle, severely impacting the profitability of the US dairy industry. Our group has found that 94% of dairy farms in the United States are infected with BLV with an average in-herd prevalence of 46%. This is partly due to the lack of clinical presentation during the early stages of primary infection and the elusive nature of BLV transmission. This study sought to validate a near-complete genomic sequencing approach for reliability and accuracy before determining its efficacy in characterizing the sequence identity of BLV proviral genomes collected from a pilot study made up of 14 animals from one commercial dairy herd. These BLV-infected animals were comprised of seven adult dam/daughter pairs that tested positive by ELISA and qPCR. The results demonstrate sequence identity or divergence of the BLV genome from the same samples tested in two independent laboratories, suggesting both vertical and horizontal transmission in this dairy herd. This study supports the use of Oxford Nanopore sequencing for the identification of viral SNPs that can be used for retrospective genetic contact tracing of BLV transmission.
Nanopore Assay Reveals Cell-Type-Dependent Gene Expression of Vesicular Stomatitis Indiana Virus and Differential Host Cell Response
Authors: Kakuk Balázs , Kiss András Attila , Torma Gábor , Csabai Zsolt , Prazsák István , Mizik Máté , Megyeri Klára , Tombácz Dóra , Boldogkői Zsolt
Published: September 2021

Vesicular stomatitis Indiana virus (VSIV) of genus Vesiculovirus, species IndianaVesiculovirus (formerly as Vesicular stomatitis virus, VSV) causes a disease in livestock that is very similar to the foot and mouth disease, thereby an outbreak may lead to significant economic loss. Long-read sequencing (LRS) -based approaches already reveal a hidden complexity of the transcriptomes in several viruses. This technique has been utilized for the sequencing of the VSIV genome, but our study is the first for the application of this technique for the profiling of the VSIV transcriptome. Since LRS is able to sequence full-length RNA molecules, it thereby provides more accurate annotation of the transcriptomes than the traditional short-read sequencing methods. The objectives of this study were to assemble the complete transcriptome of using nanopore sequencing, to ascertain cell-type specificity and dynamics of viral gene expression, and to evaluate host gene expression changes induced by the viral infection. We carried out a time-course analysis of VSIV gene expression in human glioblastoma and primate fibroblast cell lines using a nanopore-based LRS approach and applied both amplified and direct cDNA sequencing (as well as cap-selection) for a fraction of samples. Our investigations revealed that, although the VSIV genome is simple, it generates a relatively complex transcriptomic architecture. In this study, we also demonstrated that VSIV transcripts vary in structure and exhibit differential gene expression patterns in the two examined cell types.
Bullying, Cyberbullying, Anxiety, and Depression in a Sample of Youth during the Coronavirus Pandemic
Authors: Englander Elizabeth
Published: September 2021

While we know that the pandemic and its social isolation, loss of school experiences, increased screen use, and financial stress have likely had a psychological impact upon children and teens, little research has been done directly with youth to assess social and emotional factors during the pandemic and in its immediate aftermath. In this study, a sample of 240 youth reported on their experiences with bullying, fighting, sexting, cyberbullying, anxiety, and depression during the period from March 2020 to April 2021. The results indicated that bullying, cyberbullying, sexting, and fighting showed only small or no increases, but anxiety and depression were dramatically increased relative to before the pandemic. Female and LGBTQ youth were particularly vulnerable during the months since March 2020. The results suggest that youth will need positive social experiences and, in some cases, psychological interventions and treatment to restore emotional equilibrium in the months ahead.
RNA Interference and CRISPR/Cas Gene Editing for Crop Improvement: Paradigm Shift towards Sustainable Agriculture
Authors: Rajput Meenakshi , Choudhary Khushboo , Kumar Manish , Vivekanand V. , Chawade Aakash , Ortiz Rodomiro , Pareek Nidhi
Published: September 2021

With the rapid population growth, there is an urgent need for innovative crop improvement approaches to meet the increasing demand for food. Classical crop improvement approaches involve, however, a backbreaking process that cannot equipoise with increasing crop demand. RNA-based approaches i.e., RNAi-mediated gene regulation and the site-specific nuclease-based CRISPR/Cas9 system for gene editing has made advances in the efficient targeted modification in many crops for the higher yield and resistance to diseases and different stresses. In functional genomics, RNA interference (RNAi) is a propitious gene regulatory approach that plays a significant role in crop improvement by permitting the downregulation of gene expression by small molecules of interfering RNA without affecting the expression of other genes. Gene editing technologies viz. the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (CRISPR/Cas) have appeared prominently as a powerful tool for precise targeted modification of nearly all crops’ genome sequences to generate variation and accelerate breeding efforts. In this regard, the review highlights the diverse roles and applications of RNAi and CRISPR/Cas9 system as powerful technologies to improve agronomically important plants to enhance crop yields and increase tolerance to environmental stress (biotic or abiotic). Ultimately, these technologies can prove to be important in view of global food security and sustainable agriculture.
Effects on Capsicum annuum Plants Colonized with Trichoderma atroviride P. Karst Strains Genetically Modified in Taswo1, a Gene Coding for a Protein with Expansin-like Activity
Authors: Sánchez-Cruz Ricardo , Mehta Richa , Atriztán-Hernández Karina , Martínez-Villamil Olivia , del Rayo Sánchez-Carbente María , Sánchez-Reyes Ayixon , Lira-Ruan Verónica , González-Chávez Carlos Alberto , Tabche-Barrera María Luisa , Bárcenas-Rodríguez Roberto Carlos , Batista-García Ramón Alberto , Herrera-Estrella Alfredo , Balcázar-López Edgar , Folch-Mallol Jorge Luis
Published: September 2021

Here, we analyzed the effects on Capsicum annuum plants of Trichoderma atroviride P. Karst strains altered in the expression of SWOLLENIN (SWO1), a protein with amorphogenic activity on plant cell wall components. Strains of T. atroviride that overexpressed the Taswo1 gene were constructed as well as deletion mutants. A novel, cheap and accurate method for assessing root colonization was developed. Colonization assays showed that the Taswo1 overexpressing strains invaded the host root better than the WT, resulting in a stronger plant growth-promoting effect. The expression of plant defense marker genes for both the systemic acquired resistance and induced systemic resistance pathways was enhanced in plants inoculated with Taswo1 overexpressing strains, while inoculation with deletion mutant strains resulted in a similar level of expression to that observed upon inoculation with the wild-type strain. Response to pathogen infection was also enhanced in the plants inoculated with the Taswo1 overexpressing strains, and surprisingly, an intermediate level of protection was achieved with the mutant strains. Tolerance to abiotic stresses was also higher in plants inoculated with the Taswo1 overexpressing strains but was similar in plants inoculated with the wild-type or the mutant strains. Compatible osmolyte production in drought conditions was studied. This study may contribute to improving Trichoderma biocontrol and biofertilization abilities.
Evaluation of Frost Damage and Pod Set in Faba Bean (Vicia faba L.) under Field Conditions
Authors: Alharbi Najeeb H. , Alghamdi Salem S. , Migdadi Hussein M. , El-Harty Ehab H. , Adhikari Kedar N.
Published: September 2021

Frost is one factor that causes extensive yield losses globally. A study was conducted to evaluate frost damage under field conditions and assess the genetic variation of flowers converting into pods. Diverse faba bean genotypes were evaluated under four growing seasons in a randomized complete block design: three at the University of Sydney, Narrabri, Australia (2014–2016) with three sowing dates, and one at the Agricultural Research Station, Dirab, Riyadh, Saudi Arabia (2016/2017) in one sowing. Visual methods were used to estimate frost damage and record the development of pods. Radiation frost in 2014 (Narrabri) damaged lower pods, while advection frost in 2016/2017 (Dirab) damaged upper pods. The radiation frost formed immediately above the ground; therefore, flowers and pods of taller plants minimized the damage because of their long distance from the ground. The earliest (mid-April) and middle sowing (7 May) suffered more by frost, while a delay in sowing (last week in May) led to frost escape or minor damage. The genotypes IX474/4-3 and 11NF010a-2 showed low sensitivity to frost at the vegetative and reproductive stages. Flowers developed at the beginning of flowering had a faster and higher pod formation rate (41–43%) than those formed later and contributed more to yields. Therefore, a severe frost at the beginning of flowering can cause a significant yield loss as these flowers are the most productive. The frost-tolerant genotypes, and faster and higher pod forming rates, identified in this study can be exploited to breed better varieties in the future.
Kinetics of Cometabolic Transformation of 4-chlorophenol and Phenol Degradation by Pseudomonas putida Cells in Batch and Biofilm Reactors
Authors: Lin Yen-Hui
Published: September 2021

The biodegradation kinetics of 4-chlorophenol (4-CP) and phenol and microbial growth of Pseudomonas putida (P. putida) cells were estimated in batch and biofilm reactors. The kinetic parameters of cells on phenol were determined using the Haldane formula. The maximum specific growth rate of P. putida on phenol, the half-saturation constant of phenol and the self-inhibition constant of phenol were 0.512 h−1, 78.38 mg/L and 228.5 mg/L, respectively. The yield growth of cells on phenol (YP) was 0.618 mg phenol/mg cell. The batch experimental results for the specific transformation rate of 4-CP by resting P. putida cells were fitted with Haldane kinetics to evaluate the maximum specific utilization rate of 4-CP, half-saturation constant of 4-CP, and self-inhibition constant of 4-CP, which were 0.246 h−1, 1.048 mg/L and 53.40 mg/L, respectively. The negative specific growth rates of cells on 4-CP obtained were fitted using a kinetic equation to investigate the true transformation capacity and first-order endogenous decay coefficient, which were 4.34 mg 4-CP/mg cell and 5.99 × 10−3 h−1, respectively. The competitive inhibition coefficients of phenol to 4-CP transformation and 4-CP to phenol degradation were 6.75 and 9.27 mg/L, respectively; therefore, phenol had a higher competitive inhibition of 4-CP transformation than the converse. The predicted model examining cometabolic transformation of 4-CP and phenol degradation showed good agreement with the experimental observations. The removal efficiencies for phenol and 4-CP were 94.56–98.45% and 96.09–98.85%, respectively, for steady-state performance.
Divine Foreknowledge and Human Freedom: Exploring a Glut-Theoretic Account
Authors: DeVito Michael
Published: September 2021

This essay marks the first steps towards a viable glut-theoretic (contradictory) solution to the longstanding foreknowledge and free will dilemma. Specifically, I offer a solution to the dilemma that accommodates omniscience (foreknowledge) and human freedom (as the ability to do otherwise) in a simple, flat-footed way. This goal is accomplished via viewing the theological fatalist argument not as a problem, but as a sound argument: omniscience and human free will are contradictory and by dropping to a weaker underlying account of logical consequence, we can embrace them in their full-throated, robust (though contradictory) interpretations. That said, the primary aim of this paper is one of exploration: how does a subclassical solution to the foreknowledge and free will dilemma stack up in comparison to the traditional solutions on offer in the literature. This essay represents the beginning of such an exploration.
Modifications in Prefrontal Cortex Oxygenation in Linear and Curvilinear Dual Task Walking: A Combined fNIRS and IMUs Study
Authors: Belluscio Valeria , Casti Gabriele , Ferrari Marco , Quaresima Valentina , Sappia Maria Sofia , Horschig Jörn M. , Vannozzi Giuseppe
Published: September 2021

Increased oxygenated hemoglobin concentration of the prefrontal cortex (PFC) has been observed during linear walking, particularly when there is a high attention demand on the task, like in dual-task (DT) paradigms. Despite the knowledge that cognitive and motor demands depend on the complexity of the motor task, most studies have only focused on usual walking, while little is known for more challenging tasks, such as curved paths. To explore the relationship between cortical activation and gait biomechanics, 20 healthy young adults were asked to perform linear and curvilinear walking trajectories in single-task and DT conditions. PFC activation was assessed using functional near-infrared spectroscopy, while gait quality with four inertial measurement units. The Figure-of-8-Walk-Test was adopted as the curvilinear trajectory, with the “Serial 7s” test as concurrent cognitive task. Results show that walking along curvilinear trajectories in DT led to increased PFC activation and decreased motor performance. Under DT walking, the neural correlates of executive function and gait control tend to be modified in response to the cognitive resources imposed by the motor task. Being more representative of real-life situations, this approach to curved walking has the potential to reveal crucial information and to improve people’ s balance, safety, and life’s quality.
Identification of Specific Substances in the FAIMS Spectra of Complex Mixtures Using Deep Learning
Authors: Li Hua , Pan Jiakai , Zeng Hongda , Chen Zhencheng , Du Xiaoxia , Xiao Wenxiang
Published: September 2021

High-field asymmetric ion mobility spectrometry (FAIMS) spectra of single chemicals are easy to interpret but identifying specific chemicals within complex mixtures is difficult. This paper demonstrates that the FAIMS system can detect specific chemicals in complex mixtures. A homemade FAIMS system is used to analyze pure ethanol, ethyl acetate, acetone, 4-methyl-2-pentanone, butanone, and their mixtures in order to create datasets. An EfficientNetV2 discriminant model was constructed, and a blind test set was used to verify whether the deep-learning model is capable of the required task. The results show that the pre-trained EfficientNetV2 model completed convergence at a learning rate of 0.1 as well as 200 iterations. Specific substances in complex mixtures can be effectively identified using the trained model and the homemade FAIMS system. Accuracies of 100%, 96.7%, and 86.7% are obtained for ethanol, ethyl acetate, and acetone in the blind test set, which are much higher than conventional methods. The deep learning network provides higher accuracy than traditional FAIMS spectral analysis methods. This simplifies the FAIMS spectral analysis process and contributes to further development of FAIMS systems.
Boosting Intelligent Data Analysis in Smart Sensors by Integrating Knowledge and Machine Learning
Authors: Łuczak Piotr , Kucharski Przemysław , Jaworski Tomasz , Perenc Izabela , Ślot Krzysztof , Kucharski Jacek
Published: September 2021

The presented paper proposes a hybrid neural architecture that enables intelligent data analysis efficacy to be boosted in smart sensor devices, which are typically resource-constrained and application-specific. The postulated concept integrates prior knowledge with learning from examples, thus allowing sensor devices to be used for the successful execution of machine learning even when the volume of training data is highly limited, using compact underlying hardware. The proposed architecture comprises two interacting functional modules arranged in a homogeneous, multiple-layer architecture. The first module, referred to as the knowledge sub-network, implements knowledge in the Conjunctive Normal Form through a three-layer structure composed of novel types of learnable units, called L-neurons. In contrast, the second module is a fully-connected conventional three-layer, feed-forward neural network, and it is referred to as a conventional neural sub-network. We show that the proposed hybrid structure successfully combines knowledge and learning, providing high recognition performance even for very limited training datasets, while also benefiting from an abundance of data, as it occurs for purely neural structures. In addition, since the proposed L-neurons can learn (through classical backpropagation), we show that the architecture is also capable of repairing its knowledge.
Deep Reinforcement Learning with Explicit Spatio-Sequential Encoding Network for Coronary Ostia Identification in CT Images
Authors: Jang Yeonggul , Jeon Byunghwan
Published: September 2021

Accurate identification of the coronary ostia from 3D coronary computed tomography angiography (CCTA) is a essential prerequisite step for automatically tracking and segmenting three main coronary arteries. In this paper, we propose a novel deep reinforcement learning (DRL) framework to localize the two coronary ostia from 3D CCTA. An optimal action policy is determined using a fully explicit spatial-sequential encoding policy network applying 2.5D Markovian states with three past histories. The proposed network is trained using a dueling DRL framework on the CAT08 dataset. The experiment results show that our method is more efficient and accurate than the other methods. blueFloating-point operations (FLOPs) are calculated to measure computational efficiency. The result shows that there are 2.5M FLOPs on the proposed method, which is about 10 times smaller value than 3D box-based methods. In terms of accuracy, the proposed method shows that 2.22 ± 1.12 mm and 1.94 ± 0.83 errors on the left and right coronary ostia, respectively. The proposed method can be applied to the tasks to identify other target objects by changing the target locations in the ground truth data. Further, the proposed method can be utilized as a pre-processing method for coronary artery tracking methods.
Highly Dense FBG Temperature Sensor Assisted with Deep Learning Algorithms
Authors: Kokhanovskiy Alexey , Shabalov Nikita , Dostovalov Alexandr , Wolf Alexey
Published: September 2021

In this paper, we demonstrate the application of deep neural networks (DNNs) for processing the reflectance spectrum from a fiberoptic temperature sensor composed of densely inscribed fiber bragg gratings (FBG). Such sensors are commonly avoided in practice since close arrangement of short FBGs results in distortion of the spectrum caused by mutual interference between gratings. In our work the temperature sensor contained 50 FBGs with the length of 0.95 mm, edge-to-edge distance of 0.05 mm and arranged in the 1500–1600 nm spectral range. Instead of solving the direct peak detection problem for distorted signal, we applied DNNs to predict temperature distribution from entire reflectance spectrum registered by the sensor. We propose an experimental calibration setup where the dense FBG sensor is located close to an array of sparse FBG sensors. The goal of DNNs is to predict the positions of the reflectance peaks of the reference sparse FBG sensors from the reflectance spectrum of the dense FBG sensor. We show that a convolution neural network is able to predict the positions of FBG reflectance peaks of sparse sensors with mean absolute error of 7.8 pm that is slightly higher than the hardware reused interrogator equal to 5 pm. We believe that dense FBG sensors assisted with DNNs have a high potential to increase spatial resolution and also extend the length of a fiber optical sensors.
Experiences and Lessons Learnt from the Evaluation of ICT Tools for and with Migrants
Authors: Leligou Helen C. , Anastasopoulos Despina , Vretos Nicholas , Solachidis Vassilis , Kantor Eszter , Plašilová Iva , Girardet Elodie , Montagna Anita , Vlahaki Fotini , Tountopoulou Maria
Published: September 2021

As the number of migrants arriving in Europe increases, host societies face the challenge of supporting their smooth integration, respecting their needs and recognizing their competencies. A key element for their new life is their integration in the labour market. This paper presents a platform which offers a set of tools that has been developed to support migrants to find their way into the labour market in EU countries. This set includes tools for skill assessment, artificial intelligence tools providing recommendations for jobs that match their personal skills and needs, tools for suggesting training paths and options to empower their candidacy, and easy-to-use tools for creating their CV/portfolio. We focus on the evaluation of this platform in real life settings in two countries (Greece and Spain), which is part of our co-creation approach. The results are very promising and show the satisfaction of the migrants. Additionally, they provide valuable insights for both those that develop such tools and those that can use them in their work/activities with the migrants (such as the non-governmental organisations and host authorities).
Punch Incision versus Elliptical Excision for Epidermal Inclusion Cysts: Systematic Review and Meta-Analysis
Authors: Mukuda Kengo , Watanabe Jun
Published: September 2021

Punch incision is an alternative to elliptical excision for treating epidermal inclusion cysts, but its efficacy has not been systematically reviewed. This study assessed the efficacy and safety of punch incision versus elliptical excision for epidermal inclusion cysts. Randomized controlled trials published through January 2021 that evaluated the performance of punch incision versus elliptical excision on epidermal inclusion cysts were identified through electronic databases and clinical registries. Version 2 of the Cochrane risk-of-bias tool for randomized trials tool was used. Review Manager software was used for the meta-analysis. Two trials (100 participants) were identified. The primary outcomes were recurrence rate (risk ratio, 2.40; 95% confidence interval [CI], 0.37–15.60 [favoring elliptical excision]), mean operative time (mean difference [MD], −5.28; 95% CI, −12.72 to 2.16 [favoring punch incision]), and mean postoperative wound length (MD, −11.67; 95% CI, −20.59 to −2.76 [favoring punch incision]). The evidence was low to moderate due to the small sample size and its considerable heterogeneity. The use of punch incision shortened the mean postoperative wound length and had comparable safety to that of elliptical excision.
Challenges Perceived by Health Care Providers for Implementation of Contact Screening and Isoniazid Chemoprophylaxis in Karnataka, India
Authors: Chawla Kiran , Burugina Nagaraja Sharath , Siddalingaiah Nayana , Sanju Chidananda , Shenoy Vishnu Prasad , Kumar Uday , Das Arundathi , Hazra Druti , Shastri Suresh , Singarajipur Anil , Reddy Ramesh Chandra
Published: September 2021

Background: In India, challenges in pediatric TB contact screening and chemoprophylaxis initiation are still underexplored. Elucidating these challenges will help in better implementation of the programme at the grass-roots level thereby helping in early detection of pediatric cases and timely initiation of preventive therapy. This study aimed at exploring the challenges faced by the health care provider in contact screening and chemoprophylaxis initiation implementation of the pediatric household contacts. Methods: A qualitative study was conducted in the districts of Bengaluru and Udupi and in-depth interviews of key participants were adopted to explore the challenges. Qualitative data analysis was done after developing transcripts by generating themes and codes. Results: The key challenges were identified as stigma towards the disease, migrant patients with changing address, difficulty in sample collection, anxiety among parents due to long duration of the prophylactic treatment and adherence to IPT is not well documented, inadequate transportation from rural areas, and the ongoing COVID-19 pandemic. Conclusions: It is important for the National TB programme to address these challenges efficiently and effectively. Innovative solutions, feasible engagements, and massive efforts are to be taken by the programme to improve contact screening and isoniazid chemoprophylaxis implementation.
Machine Learning Algorithms for Urban Land Use Planning: A Review
Authors: Chaturvedi Vineet , de Vries Walter T.
Published: September 2021

Urbanization is persistent globally and has increasingly significant spatial and environmental consequences. It is especially challenging in developing countries due to the increasing pressure on the limited resources, and damage to the bio-physical environment. Traditional analytical methods of studying the urban land use dynamics associated with urbanization are static and tend to rely on top-down approaches, such as linear and mathematical modeling. These traditional approaches do not capture the nonlinear properties of land use change. New technologies, such as artificial intelligence (AI) and machine learning (ML) have made it possible to model and predict the nonlinear aspects of urban land dynamics. AI and ML are programmed to recognize patterns and carry out predictions, decision making and perform operations with speed and accuracy. Classification, analysis and modeling using earth observation-based data forms the basis for the geospatial support for land use planning. In the process of achieving higher accuracies in the classification of spatial data, ML algorithms are being developed and being improved to enhance the decision-making process. The purpose of the research is to bring out the various ML algorithms and statistical models that have been applied to study aspects of land use planning using earth observation-based data (EO). It intends to review their performance, functional requirements, interoperability requirements and for which research problems can they be applied best. The literature review revealed that random forest (RF), deep learning like convolutional neural network (CNN) and support vector machine (SVM) algorithms are best suited for classification and pattern analysis of earth observation-based data. GANs (generative adversarial networks) have been used to simulate urban patterns. Algorithms like cellular automata, spatial logistic regression and agent-based modeling have been used for studying urban growth, land use change and settlement pattern analysis. Most of the papers reviewed applied ML algorithms for classification of EO data and to study urban growth and land use change. It is observed that hybrid approaches have better performance in terms of accuracies, efficiency and computational cost.
The Effectiveness of Online Coaching through Social Networking Site
Authors: Mahdaria Siti , Restuaji Titus Angga
Published: September 2021

In the more globalized world, social networking sites are used to connect people and popular as a learning platform. More people use webinars to talk about specific topics through a social network. The number of online courses raise and change the way people learn. People used to study in a classroom with a tutor in front of them, but now people only need to sit in front of a screen to learn new things. However, the effectiveness of this process is still questioned. Therefore, this study aims to analyse the effectiveness of online coaching through a social networking site and the critical challenge in online coaching and approach to tackle it. This study is qualitative research. The data is collected from online interviews with a semi-structured  interview guide. The sample of the study is 12 mentees and 5 mentors who had been involved in 12 weeks of online scholarship coaching held by Coach Potato Indonesia. The data is analyzed using a thematic content method, and the effectiveness of online coaching is measured by using the Kirkpatrick Model. The result of the study is that online mentoring through social networking sites is effective and efficient, especially in particular related to geographical and financial issues. The authors found the critical challenges in online mentoring are internet connection and timing. Therefore, online mentoring should use multiple platforms to adjust with the technical issue that might occur.