Miracle-dz/UniFAR-FTUs huggingface dataset:
Biochemical and Anatomical Characteristics of Basmati And Non-basmati Rice (Oryza Sativa L.) For Resistance To Foot Rot

Fusarium fujikuroi, the causal agent of foot rot disease, infects all the parts of rice, causing serious yield losses in different parts of the world. In order to understand the basis of disease tolerance, various biochemical and anatomical traits of ten days old healthy and infected basmati and non-basmati rice seedlings were compared. Total soluble sugar content was higher in healthy seedlings, while total phenols, orthodihydroxy phenols and total soluble proteins were higher in non-basmati rice seedlings post infection indicating the initiation of defence against the pathogen. Increase in the total antioxidant activity, enzymes and α-tocopherols in basmati rice cultivars post infection indicate the oxidative stress created by pathogen. Histopathological observations revealed hyphal and conidial growth in infected tissues of basmati cultivars whereas a complete and intact tissue was observed in healthy and infected counterparts of non-basmati cultivars. Bangladesh J. Bot. 51(1): 29-36, 2022 (March)
Molecular phylogeny Of Nibung (Oncosperma tigillarium [Jack] Ridl.) inferred from trnL-F intergenic spacer sequences

Nibung (Oncosperma tigillarium [Jack] Ridl.) has a stronger wood quality and is resistant to tidal deformations. For centuries, the local people are traditionally using nibung for different purposes. However, its utilization is higher than its cultivation, causing a decrease in supply every year. Taxonomic data based on molecular markers are urgently needed in the nibung germplasm. We need to study their molecular characters to provide basic data for genetic diversity and conservation study purposes. The present study aims to analyze the phylogenetic relationship of seven accessions of nibung in Riau, Sumatra, Indonesia, based on molecular characters and to clarify the relationship among closely related infra-specific categories. The seven accessions of nibung were grouped by types of habitats i.e., lowland and highland areas. Accessions collected from the highland areas (Bukit Suligi) were very different from those collected from the lowland areas based on their genetic and evolutionary data. Based on Neighbor-Joining (NJ) analysis, it is estimated that the accession O. tigillarium from Bukit Suligi was more advanced than another accession. The present study has been able to compare more primitive and advanced accessions based on genetic distance. The studies also confirmed that the more advanced species are highly capable to survive in their in situ environment. Such type of genetic variability is very important for breeding and conservation studies and can be used in future generations of palm.
A new deep neural segmentation network for cerebral aneurysms in 2D digital subtraction angiography

Digital subtraction angiography (DSA) is routinely used for measuring the dimensions and characteristics of cerebral aneurysms as a step in planning of interventional treatments. Incorrect sizing of the aneurysm sac puts the patient at the risk of incomplete treatment due to the use of an intrasaccular implant that is too small or too large. In this work, we propose an automatic method to segment the aneurysm sac in 2D DSA images to enable fast and accurate measurements. We use a UNet-like architecture. However, we replace the encoder arm of this network with an EfficientNet architecture, pre-trained on 300 million natural images. We show that this architecture delivers very accurate segmentation of the aneurysm sac on a dataset of 144 DSA images obtained from patients prior to implantation of an intrasaccular device to treat wide-neck bifurcation aneurysms. We report a Dice coefficient of 0.9.
Response of heat-stress tolerant and susceptible wheat lines in diverse planting environments by using parametric stability models

In Pakistan, wheat planting is delayed because of dawn sowing, which reduces yield due to terminal heat stress. This effect can be alleviated by changing sowing times. Therefore, parametric stability analysis was carried out with eight different sowing dates (environments), namely, early, normal, late, and very late, with 10-day intervals in 2019–2020 and 2020–2021 at the Wheat Research Institute, Faisalabad, Pakistan. Significant heat stress responses were observed at the latter two sowing dates. The genetic and phenotypic relationship among the traits revealed that the normalized vegetation index (NI) had a positive correlation with grain yield (kg ha−1) (Yi) and 1000-grain weight (g) (GrWt). However, canopy temperature (CaTe) had a negative correlation with Yi, GrWt, and NI. For Yi and GrWt, the linear environmental response (α) and deviation from linear response (λ) were observed as transformed forms of regression coefficient (bi) and deviation from regression (S2d). Planting dates, i.e., E1, E6, and E7, had slight effects on Yi, and E6, E7, E2, and E8 had slight effects on GrWt. Meanwhile, E3, E4, E5, E1, E3, and E4 exerted a strong effect on the genotype by environment interactions for Yi and GrWt. For Yi, lines G23, G20, and G21 were adapted to E8; G9 and G19 were adapted to E1; and G15, G17, and G22 were adapted to E5. For GrWt, G13, G20, G3, G11, G21, and G15 were adapted to E8 and E4; G10, G7, G8, and G5 were adapted to E5; G4, G22, and G17 were adapted to E6 and E4; and G24 and G2 were adapted to E2 and E3. The candidate wheat lines with enhanced GrWt and Yi were found in E5 and E6 (late sowing) and E7 and E8 (very late) and presented tolerance to terminal heat stress.
An instruction detection system with Support Vector Machine, Cuckoo-Genetic algorithm and principal component analysis

Nowadays, with the abundant growth of internet users, attacks on computer systems have dramatically increased. This condition might increase the risk of security for Internet users or networks systems. Thus, Intrusion Detection Systems (IDS) is used for detection, identification and diagnosis of security issues on computer networks . As a data mining technique, Support Vector Machine (SVM) is considered in the design and implementation of IDS.SVM’s performance is influenced by its parameters and its input feature space respectively. So, in order to reach and achieve a reasonable efficiency of SVM, two values should be optimized: values of parameters for better accuracy, and set of input feature for shorter training time. In this paper, we used Principal Component Analysis (PCA) for feature extraction and dimension reduction of input data and the Cuckoo-Genetic algorithm, as a meta-heuristic optimization technique, to determine the optimum parameters of SVM for classification of normal and malicious data. The practical results, by using proposed method on NSL-KDD dataset, indicates that the proposed method reached a better detection rate Compared to genetic and cuckoo.
Development of a new armor unit against high waves

Coastal hazards such as high waves are expected to increase due to global climate change. Therefore, we investigated new armor unit structures for disaster prevention. Recently, a concrete caisson has been used in many breakwaters against high waves in South Korea, but the demand for concrete armor unit has increased due to the high cost and many installation requirements. Though many new armor units have been developed over the world since Tetrapod in 1950, few have been used due to lack of systematical development. The representative armor units in current use have many advantages, but they cannot be applied to waves higher than 8 m. One of the new armor units developed by the design guide based on recent trend and hydraulic model experiments were conducted. The new armor unit was developed as a single layer due to cost effectiveness. However, the thickness is close to 1.5 times by overlapping the alphabet A and V. It showed higher overtopping compared to a double layer because of the thickness and the high packing density. It has a high interlocking vertically but low horizontally. It shows good stability at 9 m in model testing.
Alkali-Activated Materials with Pre-Treated Municipal Solid Waste Incinerator Bottom Ash

This study presents the results of an experimental campaign on the use of municipal solid waste incinerator bottom ash (MIBA) and fly ash (FA) as precursors for the production of alkali-activated materials. MIBA was subjected to a pre-treatment stage in response to two issues: high metallic aluminum content, which reacts in a high pH solution, releasing hydrogen; and low amorphous content of silica-, aluminum- and calcium-bearing phases, which translates into a limited formation of reaction products. The proposed pre-treatment stage oxidizes most of the metallic aluminum fraction and compensates for the low reactivity of the material via the formation of additional reactants. Different combinations of MIBA and FA were tried—mass-based ratios of 0/100, 25/75, 50/50, 75/25, and 100/0 for MIBA/FA. Two mix designs of the alkaline activator with sodium hydroxide and sodium silicate were evaluated by varying the Na2O/binder and SiO2/Na2O ratios. These mortars were tested in the fresh and hardened state. The results showed that the pre-treatment stage was effective at stabilizing the dimensional variation of MIBA. Despite the lower reactivity of MIBA, mortars with 50/50 of MIBA/FA presented a maximum 28-day compressive strength of 25.2 MPa, higher than the 5.7 MPa of mortars made with MIBA only.
Formaldehyde Deodorization Effect and Far-Infrared Emission Characteristics of Ceramics Prepared with Sawdust, Risk Husk, and Charcoal: Effect of Material Mixing Ratio

Indoor air quality is a very important environmental factor in modern society. However, air pollutants generated from various interior construction materials significantly affect the human body, including formaldehyde (HCHO) and volatile organic compounds that threaten public health by deteriorating indoor air quality. Effective in removing these harmful substances are porous materials, such as woodceramics. In this study, charcoal, a porous material, was added to rice husk, an agricultural by-product, and sawdust generated during the sawing process to prepare boards and ceramics at different mixing ratios, and the HCHO deodorization performance and far-infrared emission characteristics were measured. As the mixing ratio of charcoal increased, the deodorization rate of the boards and ceramics tended to increase. Overall, the deodorization rate was measured to be 80% to 90%, indicating that the boards and ceramics prepared with charcoal are suitable to be used for the purpose of deodorization. The effect of the material mixing ratio on far-infrared emissivity and emission power was insignificant.
Analysis of Organizational Resilience Capacity in Accommodation Service Business in Semarang

This study aims to comprehensively analyze how to develop human resource management (HRM) practices that create organizational resilience and investigate factors influencing it. This study was done in a qualitative-descriptive manner. Key informants participated in this study – selected based on positions at work and their length of work relevant to the research problems – included HR Manager, HR Coordinator, and Training Manager Assistant of Hotel Ciputra Semarang. The data was collected through in-depth interviews. To examine the data credibility, a triangulation process to the key informants was done. The data was analyzed using a technique proposed by Miles and Hubberman consisting of data reduction, data presentation and conclusion drawing. This study finds that there are 4 HRM practices that can support the organizational resilience, including selective and measurable recruitment, employee compensation, employee training and development, and employee engagement. Further, there are also 4 factors influencing the organizational resilience, namely healthy finance (reserve fund), good employee performance, leadership, and organizational experience.
UPF1 Inhibits Hepatocellular Carcinoma Growth through DUSP1/p53 Signal Pathway

Human hepatocellular carcinoma (HCC) has a high mortality rate because of the dearth of effective treatments. Multiple studies have shown that overexpression of UPF1, a key nonsense-mediated mRNA decay (NMD) factor, reduces HCC growth through various cell signaling pathways. However, the mechanism by which UPF1 expression retards HCC proliferation through the regulation of RNA stability remains unclear. By employing various UPF1 variants and transcriptome analysis, we revealed that overexpression of UPF1 variants, not UPF1-mediated NMD, reduces HCC tumorigenesis. Additionally, UPF1 variant overexpression reduced tumorigenesis in xenografted mice. Transcriptome analysis indicated that the level of dual specificity phosphatase 1 (DUSP1) was increased by UPF1 variants via posttranscriptional regulation. The UPF1 overexpression-mediated increase of DUSP1 activated tumor suppressor signaling, ultimately inhibiting cell growth. In this study, we highlighted the function of UPF1 as a tumor suppressor in HCC growth.
The Separation in Rreal-time of the Doppler Blood Flow and Moving Wall Signals Using EMD Algorithm

In this paper,the empirical mode decomposition(EMD) was proposed to decompose mixed Doppler signals for separating the Doppler blood flow and the wall signals.The EMD was firstly to be used to decompose a mixed Doppler signal into a finite and usually small number of individual components named intrinsic mode functions(IMFs). Then a strategy based on the curve of the wall-to-blood signal energy ratio(WBSR) was developed to automatically identify and remove low frequency components which contributed to the wall pulsation.In the simulation study,this method was applied to process the simulated Doppler signals.Compared with the estimated low blood flow signal in frequency and time domain with relative error of 95% based on the tradition high-pass filter,the new approach obtained improved accuracy with the errors of 50% and 45%,respectively.This method was implemented based on a personal computer using C language,and could process the Doppler ultrasound signals recorded from carotid arteries in real-time.From the simulation and clinical results,it could be concluded that the proposed method improved the performance for wall components removal from the mixed signals effectively and objectively.
A Multi-Methodological Approach to Study Systems Development in a Software Organization

Large-scale systems development is a complex activity involving number of dependencies that people working together face. Only a few studies concentrate on the coordination of development activities in their organizational context. This research study tries to fill at least part of this gap by studying how systems development process is coordinated in practice. The study uses a multimethodological approach to interpret coordination of systems development process in a contemporary software organization in Finland. The methodology is based on the empirical casestudy approach in which the actions, conceptions, and artefacts of practitioners are analyzed using within-case and cross-case principles. In all the three phases of the study, namely multi-\site coordination, requirement understanding, and working with systems development methods, both the qualitative and quantitative methods were used to an understanding of coordination in systems development. The main contribution of this study is to demonstrate that contemporary systems development is much more complex and more driven by opportunity than is currently acknowledged by researchers. The most challenging part of the research process was the combination of qualitative and quantitative methods, because of the lack of multimethodological work done in IS discipline.
An Overview on Fault Management for Electric Vehicle Onboard Chargers

Onboard charging systems (OBCs) convert AC power from an external charging source into a DC voltage used to charge the battery pack of an electric vehicle (EV). OBCs are versatile since they can convert energy from almost every AC source, including standard household electrical receptacles, without needing wall chargers or charging stations. Since the same motor-drive electronics are reconfigured for onboard charging, weight and cost barely increase. However, the power quality and reliability of the OBCs are essential elements for proper grid interconnection. This article reviews the failures of power electronic converters that can be used for onboard charging and their most prominent fault-tolerance techniques. The various fault-tolerance methods are evaluated and compared in terms of complexity, cost, and performance to provide insights for future developments and research directions.
A study of odor reproduction using multi‐component olfactory display

A sensory test experiment (triangle difference test) was conducted using the 20‐component olfactory display to confirm odor reproduction based on odor components. The essential oils used were lemon, palmarosa, carrot seed, elemi, lavender, cypress and mentha arvensis. Each one was selected from seven essential oil categories. The sensory test reveals that it was difficult to distinguish between the reproduced odor and the target one. Thus, the odor reproduction by olfactory display based on odor components was generally possible. Furthermore, we found that the participants used its features or intensities as clues to distinguish between the blended odor and the target one from a survey of the free comments on the questionnaire sheets.
Psychosocial factors associated with adolescent depressive and anxiety symptoms during the COVID-19 pandemic

The COVID-19 pandemic has created many challenges for adolescents across the world. The current study aimed to investigate the prevalence of depressive and anxiety symptoms and suicidal ideation in adolescents living in Melbourne, Australia, during the state of Victoria’s second lockdown. The study also sought to identify pre-existing and current psychosocial stressors associated with adolescent’s depressive and anxiety symptoms, and to identify the extent to which adolescents experiencing mental health difficulties sought professional help during the pandemic. A COVID-19 sub-study of the Mothers’ and Young People’s Study—an 18-year longitudinal cohort study—was conducted between July and September 2020, an online survey completed by 257 adolescents aged 14–17 years and their mothers, which asked about pandemic-related stressors, remote learning, family life, and mental health. Descriptive statistics and hierarchical multiple regression analysis were conducted. Mental health difficulties were common with 38% and 20% of adolescents reporting clinically significant depressive and anxiety symptoms, respectively, and 21% reporting frequent suicidal or self-harm ideation. Factors associated with depressive and anxiety symptoms included being female, exposure to current maternal depressive symptoms, lower levels of resilience, experiences of loneliness, stressful life events, and school- and family-related stressors. Two-thirds of adolescents who were experiencing clinically significant depressive or anxiety symptoms had not sought professional help. Our findings highlight the urgent mental health need among adolescents and the importance of reducing barriers to accessing support.
Channel Modeling for Orbital Angular Momentum Based Underwater Wireless Optical Systems

The underwater turbulence channel is modelled and a unified statistical distribution is applied for characterizing orbital angular momentum (OAM) propagation in underwater wireless optical communication (UWOC) systems. Based on Monte-Carlo simulations, the effects of turbulences are characterized by the multiple phase screens model considering both the coherence width and scintillation index. The phase screen samples are processed by the randomized spectral sampling discrete Fourier transform (DFT) technique. To validate the propagated field distribution, both the phase structure function and optical transfer function are derived and evaluated with the aid of ensemble-averaged results. The Generalized Gamma Distribution (GGD) enriched by an additional independent parameter is applied for modelling the probability density function (PDF) of both the reference-channels, fluctuating irradiance as well as the intermodal crosstalk irradiance between different OAM modes. Furthermore, based on the PDF, the performance metrics of both single input multiple output (SISO) and multiple input multiple output (MIMO) systems are analyzed, based on the average capacity, the bit-error rate and the outage probability.
Fusion-Learning-Based Optimization: A Modified Metaheuristic Method for Lightweight High-Performance Concrete Design

In order to build high-quality concrete, it is imperative to know the raw materials in advance. It is possible to accurately predict the quality of concrete and the amount of raw materials used using machine learning-enhanced methods. An automated process based on machine learning strategies is proposed in this paper for predicting the compressive strength of concrete. Fusion-learning-based optimization is used in the proposed approach to generate a strong learner by pooling support vector regression models. The SVR technique proposes an optimization method for finding the kernel radial basis function (RBF) parameters based on improving the innovative gunner algorithm (AIG). As a result of AIG's diverse solutions, local optima are effectively avoided. Therefore, the novelty of our research is that, in solving the uncertainty of predicted outputs based on integrated models, we use fusion-learning-based optimization to improve regression discrimination. We also collected a standard dataset to analyze the proposed algorithm, and subsequently, the dataset was designed from concrete laboratory tests on 244 samples, seven features, and three outputs. Different regression intensities are determined by correlation analysis of responses. Regression fusion is sufficiently accurate to estimate the number of desired outcomes examined based on the appropriate input data sample. The best quality concrete can be achieved with an error rate of less than 5%.
The Influence of Repetitive UIS on Electrical Properties of Advanced Automotive Power Transistors

This paper investigates a degradation of three types of automotive power MOSFETs through repetitive Unclamped Inductive Switching (UIS) test typically used to evaluate the avalanche robustness of power devices. It is not uncommon in switching applications that greater than the planned voltage for voltage spikes can occur, so even the best electronic designs may encounter frequent avalanche events. Hence, there is a need to analyse the impact of repetitive avalanching on the electrical performance of power transistors. This article focused on the shift of main electrical parameters: on-resistance RON , breakdown voltage VBR, threshold voltage VTH , and corresponding characteristics, as well as capacitances. Analysis proved that DMOS transistors are less vulnerable to repetitive avalanching. The most impacted parameter was on-resistance RDSon, where a 14 % increase was observed after 6 · 10 stress pulses. The parameters shift is attributed to hot carrier injection in the space charge region of blocking PN junction and involves mainly defects generation/activation in the drain side region of the gate oxide. For the TrenchMOS transistor, a significant shift of I − V curves was observed with considerable impact on the RON where an increase of 22 % was observed. The trench corner is verified to be the mainly degraded region by Synopsys Technology Computer Aided Design (TCAD) simulations. Degradation of drain-gate capacitance CDG and input capacitance Cin was observed in all three types of analysed structures. DLTS was used to verify the generation/activation of defects invoked by stress. An increase of DLTS signal corresponding to energy levels of oxygen vacancies and impurities in SiO2 and on interfaces were detected on stressed samples.