Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and Characterization of Genes Related to Resistance of Autographa californica Nucleopolyhedrovirus Infection in Bombyx mori

Simple Summary Autographa californica nucleopolyhedrovirus (AcMNPV) is a kind of baculovirus that was initially found and named for its host, but the previous study reveals several silkworm strains are preferentially susceptible to AcMNPV through intrahemocelical injection method. In the following study, genetics analysis showed that a set of potential genes which controlled resistance of AcMNPV was located on chromosome 3. In the present research, we performed Genome-Wide Association Studies to identify the gene that controls the resistance of AcMNPV, results show that the Niemann-Pick C1 (NPC-1) gene is strongly associated with this resistance. Then we found that there are several amino acid mutations in the protein sequence of BmNPC1 between two different resistance strains of Bombyx mori. RNAi results showed that BmNPC1 successfully suppressed virus infection ability and changed the expression pattern of viral genes. Abstract In Bombyx mori, as an important economic insect, it was first found that some strains were completely refractory to infection with Autographa californica nucleopolyhedrovirus (AcMNPV) through intrahemocelical injection; whereas almost all natural strains had difficulty resisting Bombyx mori nucleopolyhedrovirus (BmNPV), which is also a member of the family Baculoviridae. Previous genetics analysis research found that this trait was controlled by a potentially corresponding locus on chromosome 3, but the specific gene and mechanism was still unknown. With the help of the massive silkworm strain re-sequencing dataset, we performed the Genome-Wide Association Studies (GWAS) to identify the gene related to the resistance of AcMNPV in this study. The GWAS results showed that the Niemann-Pick type C1 (NPC-1) gene was the most associated with the trait. The knockdown experiments in BmN cells showed that BmNPC1 has a successful virus suppression infection ability. We found a small number of amino acid mutations among different resistant silkworms, which indicates that these mutations contributed to the resistance of AcMNPV. Furthermore, inhibition of the BmNPC1 gene also changed the viral gene expression of the AcMNPV, which is similar to the expression profile in the transcriptome data of p50 and C108 strains.
Microstrip switchable filtering power divider with three operating modes

A switchable filtering power divider (FPD) with three operating modes is presented, i.e. dual-band FPD centring at 2.1 and 2.5 GHz, low-band FPD working at 2.1 GHz, high-band FPD operating at 2.5 GHz. The bandpass filtering responses are achieved by embedding four dual-mode resonators. The simulated and measured results are in good agreement.
Cross Validating a Rubric for Automatic Classification of Cognitive Presence in MOOC Discussions

As large-scale, sophisticated open and distance learning environments expand in higher education globally, so does the need to support learning at scale in real time. Valid, reliable rubrics of critical discourse are an essential foundation for developing artificial intelligence tools that automatically analyse learning in educator-student dialogue. This article reports on a validation study where discussion transcripts from a target massive open online course (MOOC) were categorised into phases of cognitive presence to cross validate the use of an adapted rubric with a larger dataset and with more coders involved. Our results indicate that the adapted rubric remains stable for categorising the target MOOC discussion transcripts to some extent. However, the proportion of disagreements between the coders increased compared to the previous experimental study with fewer data and coders. The informal writing styles in MOOC discussions, which are not as prevalent in for-credit courses, caused ambiguities for the coders. We also found most of the disagreements appeared at adjacent phases of cognitive presence, especially in the middle phases. The results suggest additional phases may exist adjacent to current categories of cognitive presence when the educational context changes from traditional, smaller-scale courses to MOOCs. Other researchers can use these findings to build automatic analysis applications to support online teaching and learning for broader educational contexts in open and distance learning. We propose refinements to methods of cognitive presence and suggest adaptations to certain elements of the Community of Inquiry (CoI) framework when it is used in the context of MOOCs.
Modified-Kansei engineering for the quality of logistics services during the Covid-19 pandemic: Evidence from Indonesia

Abstract This study modifies Kansei engineering by measuring the effect of customer emotional satisfaction from the services provided by logistics service providers on customer loyalty during the Covid-19 pandemic. Kansei engineering modification in this study uses EFA (exploratory factor analysis) analysis in the ServQual dimensions, then CFA (Confirmatory Factor Analysis) is taken to examine the relationship between variables. The object of distributing the questionnaire is 298 respondents who have experience using the services of Indonesian logistics providers. The EFA results on the ServQual dimensions show three new variables besides Kansei’s words: customer satisfaction, commitment, and loyalty. The CFA findings also show that during the Covid-19 pandemic, customer commitment affects customer loyalty. In addition, customer commitment mediates customer satisfaction and customer loyalty. Lastly, customer satisfaction significantly affects customer loyalty.
Enhanced multi-stage network for defocus deblurring using dual-pixel images

The defocus deblurring raised from the finite aperture size and exposure time is an essential problem in the shooting process, which seriously affects the quality of the images. However, studies based on defocus deblurring in monocular images yielded good results, while those on binocular images are rare. The current methods directly merge the left and right views regardless of their unique features. Objects within the camera’s DoF will not have a difference in phase, while light rays from outside the DoF will have a relative shift that is directly correlated with the amount of defocus blur. In this paper, we firstly proposed an enhanced multi-stage network for defocus deblurring using dual-pixel Images. Taking into account the parallax between the left and right views, the first two stages learn the information of them, respectively, and correct the deviation of the images under the supervision of the ground truth. The third stage consists of EERG and ERGS. It merges with the feature map of the previous stage, so that the left and right views are mutually enhanced, and a good restored image is obtained. ERGS uses the residual block as the basic unit to restore the details of the blurred area while maintaining the clear. Experimental results show that our proposed network can achieve better accuracy than state-of-the-art approaches on the public DPD dataset.
Sensitivity analysis of prefiltering in identification of two‐time scaled systems

System identification is an important field of modeling that allows obtaining mathematical models capable of reproducing the experimental behavior of dynamical systems accurately. When dealing with complex systems that involve more than one time and/or space scale, the identification task is not so trivial. In this context, this works focuses on the study of two‐time scaled systems (TTSSs), comprising a theoretical sensitivity analysis of prefiltered estimators for system identification purposes. It is worth mentioning that prefiltered estimators are a very important class of estimators when frequency‐domain identification is required rather than its time‐domain counterpart. Thus, the sensitivity analysis is performed for the identification of a Lockheed F104G aircraft model, which corresponds to a TTSS. Numerical simulations are also performed to validate the theoretical analysis.
MotionLab@Home: Complementary Measurement of Gait Characteristics Using Wearable Technology and Markerless Video Tracking - A Study Protocol

Background: While treatment monitoring of healthcare interventions is mainly conducted at the hospital, most information on a patient’s health status could be obtained from his everyday life activities. Therefore, there is a great interest in methods for long term (home) monitoring applications. However, there is still a lack of quantitative methods allowing everyday life activities monitoring such as gait analysis at home. While video-based systems have been employed given their high accuracy, they remain expensive and obtrusive with the range of motion of a patient limited to the set up measurement volume. Body worn sensors on the other hand present as an excellent opportunity to remotely and unobtrusively monitor gait characteristics not only at home, but during activities of everyday life. Technical limitations as well as changes in the patient’s gait patterns challenge the extraction of specific gait parameters. Methods: We propose a hybrid system comprising of a markerless video-based motion capturing system and a wearable sensor system with foot worn sensors. A study protocol is presented that will be used to validate the systems against each other. Discussion: This study will evaluate whether a markerless motion capturing system is feasible as a complementary tool for everyday gait analysis. Further, we will validate the accuracy of the sensor system using the video-based system as a gold standard. In the future, the combination might allow a recalibration of algorithmic sensor parameters based on deviations from the reference video-based system, and the combination of both modalities may enhance gait analysis in home monitoring.
Flavonoids as Potential Anti-Inflammatory Molecules: A Review

Hydroxylated polyphenols, also called flavonoids, are richly present in vegetables, fruits, cereals, nuts, herbs, seeds, stems, and flowers of numerous plants. They possess numerous medicinal properties such as antioxidant, anti-cancer, anti-microbial, neuroprotective, and anti-inflammation. Studies show that flavonoids activate antioxidant pathways that render an anti-inflammatory effect. They inhibit the secretions of enzymes such as lysozymes and β-glucuronidase and inhibit the secretion of arachidonic acid, which reduces inflammatory reactions. Flavonoids such as quercetin, genistein, apigenin, kaempferol, and epigallocatechin 3-gallate modulate the expression and activation of a cytokine such as interleukin-1beta (IL-1β), Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-8 (IL-8); regulate the gene expression of many pro-inflammatory molecules such s nuclear factor kappa-light chain enhancer of activated B cells (NF-κB), activator protein-1 (AP-1), intercellular adhesion molecule-1 (ICAM), vascular cell adhesion molecule-1 (VCAM), and E-selectins; and also inhibits inducible nitric oxide (NO) synthase, cyclooxygenase-2, and lipoxygenase, which are pro-inflammatory enzymes. Understanding the anti-inflammatory action of flavonoids provides better treatment options, including coronavirus disease 2019 (COVID-19)-induced inflammation, inflammatory bowel disease, obstructive pulmonary disorder, arthritis, Alzheimer’s disease, cardiovascular disease, atherosclerosis, and cancer. This review highlights the sources, biochemical activities, and role of flavonoids in enhancing human health.
A A picturebook reveals the nature of bias

In order to disrupt hegemonic thinking, the foundation of biases on which this thinking is built must first be confronted. I became increasingly aware of the detrimental impact of implicit bias during a research project I conducted in a children’s literature course with preservice teachers. In this research project, I analysed the responses of the preservice teachers to a cosmopolitan approach to reading children’s literature. A cosmopolitan approach in literacy invites a reflexive consideration of personal perspectives and an opening towards learning from the perspectives of others (Hansen, 2017). In encouraging the ideals of a cosmopolitan approach to literacy, I encountered areas of resistance from the preservice teachers. These instances of resistance were often rooted in implicit bias. During the final stages of completing my research, the picturebook Milo Imagines the World by Matt de la Peña (2021) was released. Milo Imagines the World reveals how deeply held ideologies and biases impact perceptions of reality. An awareness of how biases impact one’s perception of reality is an important factor in developing greater self-awareness and combating hegemonic thinking. In this article, I provide a critical analysis of the various forms of bias encountered during my research along with a reflective exploration of the picturebook Milo Imagines the World. This picturebook and analysis provide a context for better understanding the subtle pervasiveness of biases that often contribute to the maintenance of hegemonic thinking.
Stratification of Patients with Diabetes Using Continuous Glucose Monitoring Profiles and Machine Learning

Background. Continuous glucose monitoring (CGM) offers an opportunity for patients with diabetes to modify their lifestyle to better manage their condition and for clinicians to provide personalized healthcare and lifestyle advice. However, analytic tools are needed to standardize and analyze the rich data that emerge from CGM devices. This would allow glucotypes of patients to be identified to aid clinical decision-making.Methods. In this paper, we develop an analysis pipeline for CGM data and apply it to 148 diabetic patients with a total of 8632 days of follow up. The pipeline projects CGM data to a lower-dimensional space of features representing centrality, spread, size, and duration of glycemic excursions and the circadian cycle. We then use principal components analysis and k-means to cluster patients’ records into one of four glucotypes and analyze cluster membership using multinomial logistic regression.Results. Glucotypes differ in the degree of control, amount of time spent in range, and on the presence and timing of hyper- and hypoglycemia. Patients on the program had statistically significant improvements in their glucose levels.Conclusions. This pipeline provides a fast automatic function to label raw CGM data without manual input.
An Empirical Research on the Relationship between Quality of Work Life and Leadership Styles in SMEs

Literature on Quality of Work Life (QWL) is limited and several studies commonly correlate with some variables but no study on QWL has associated with Leadership styles. This research investigates the relationship between QWL of employees and Leadership styles in SMEs. The objectives of the study are a) To find the status of QWL of employees in SMEs, b) To investigate and determine the relationships between QWL and Leadership styles and c) To compare the QWL under Transformational Leadership style and Transactional leadership style. In this context, study conducted in mechanical manufacturing SMEs in and around Bangalore. Results showed that there is a significant relationship between QWL and Leadership styles. Under Transformational leadership style employees enjoys high level of Quality of Work Life.
Optimizing the Focusing Performance of Non-ideal Cell-Free mMIMO Using Genetic Algorithm for Indoor Scenario

This paper proposes a genetic algorithm (GA) combined with ray tracer to generate a cell-free topology of massive MIMO (mMIMO) for the optimal focusing performance serving multiple users. The realistic hardware impairment, for instance the non-ideal power amplifier, is taken into account of the system modeling and topology optimization. To the best of our knowledge, this is the first attempt to apply GA in optimizing the hardware-impaired multi-user cell-free mMIMO. Although the demonstrated numerical analysis is for indoor scenario, the proposed approach is transferable for generic scenarios. In GA, the base station (BS) antennas’ placement is encoded with an adjusted binary matrix representation, which is straightforward for the subsequent genetic operations. The explored candidates by GA can evolve beyond the parents, where the fitness of individuals is evaluated dynamically via a ray tracer radio channel simulator. Compared to the traditional GA, our proposed GA can find better solutions with a faster convergence speed. The algorithm provides near-optimal results in experiments, applicable to generic environment with multiple mobile users and different signal-to-interference-plus-noise ratios.
Malware Detection using LightGBM with a Custom Logistic Loss Function

The increased spread of malicious software (malware) through the internet remains a serious threat. Malware authors use obfuscation and deformation techniques to generate new types than can evade traditional detection methods. Hence, it is widely expected that machine learning methods can classify malware and cleanware based on the characteristics of malware samples. This paper investigates malware classification accuracy using static methods for malware detection based on LightGBM by a custom log loss function, which controls learning by installing coefficient α to a loss function of the false-negative side and coefficient β to a loss function of the false-positive side. By installing coefficients, we can create a lopsided classifier. We used two malware datasets, non-public and public, to construct a malware baseline model to verify the effectiveness of the proposed method. We extracted the dataset features from PE-file surface analysis and PE-header dumps and customized a binary log loss function to improve all the classification evaluation metrics to a certain extent. We obtained a better result (AUC = 0.979) at α = 430 and β = 339 than the normal log loss function (AUC = 0.978) on the EMBER dataset. In addition, to maintain malware detection coverage and quick countermeasures to true positive results, we propose a hybrid usage of different custom models to prioritize positive results.
Automatic Number Plate Recognition System for Indian Number Plates using Machine Learning Techniques

India being a country where the population is above 1.3 billion where each person has at least one car of his/her use. Considering this, the number of cars driven on the roads of India must be greater than the population of the people in the country. India being a diverse country, diversity is not only seen in the language of the number plates but also in size, spacing between the letters on the number plate and the font of the number plate. Diversity differs from state to state. Even though most of the people are using English Number plates, there is no certain law as to how a number plate should be, so some people tend to have number plates according to their preferences. To withstand these problems, we have created a system using You Only Look Once version 5 (YOLOv5) for number plate detection and Google Tesseract for Character Recognition.
Promoting Voluntariness on Technology Usage in Organisations: A Mobile Technology Perspective

Voluntariness in technology adoption and use is vital in promoting technology diffusion and use in organisations. Various technology adoption models have been proposed to explain the adoption of technologies in different settings, such as organizational and individual, as well as in the voluntary and mandatory contexts. Recently, uptake of mobile phones in achieving organisational targets has been increased in developing countries and Tanzania in particular. This is due to the notable improvements in both hardware performance and sophistications. In organisation context, not all users are willing to use technology as required. In such circumstances, they are mandated to use it in order to fulfil their working duties. This leads to poor uptake of technology and results to unclear understanding regarding to their attitudes towards using it. While some studies have discussed the impact of voluntariness in using traditional desktop computer systems and thin client computing, mobile phone technology has not received the deserved attention. Discussing voluntariness in using mobile phone technology in organisations in relation to other technologies is essential especially due to its usage in both working and private purposes. This paper describes the voluntary aspects of using mobile phones in performing activities of the firms in Tanzania and compares it with desktop and thin client technologies. Also, it proposes possible ways of handling such situation in order to improve its use. Among others, the paper has analysed mandotoriness on usage of mobile technology. Further, it highlights key areas which should be addressed in order to improve the usage of mobiletechnology in organisations and eventually cover the gap caused by such mandatory situations.
Model-Based Study of Creep and Recovery of a Glassy Polymer

Polyvinyl chloride specimens were subjected to three different constant loads at ambient temperature, and the creep is monitored as a function of time. After a certain time, the load was withdrawn and the strain recovery was followed with time. Although the deformational behavior of such material is conventionally described by the Burger model consisting of elastic, viscoelastic, and viscous components, in the present work, it is shown that the whole creep recovery process is reversible and is described by three viscoelastic components connected in series. Depending on the relative value of the observation and the relaxation times, the viscoelastic components appear pseudo- elastic or viscous. It is found that the model parameters evaluated from the creep data fail to predict the recovery data in both the initial and the end phases, while those from the recovery data can partially reproduce the creep data (satisfactorily in the late phase and with high deviation in the initial phase). The model parameters vary with stress values, but with a good approximation, they could be averaged for a certain stress range to describe creep processes for a specified time period. The proposed model describes creep data better than the Finley and the Weibull models.
Progress in piezoelectric quartz crystal sensors

The fundamental principle of the piezoelectric sensors and the analytical methods based on mass, viscosity, electric conductivity in solution are briefly introduced. a review on electrochemical quartz crystal microbalance (eqcm) and piezoelectric biosensors is presented in detail. new progress in series piezoelectric sensor (spqc), series surface acoustic wave sensor ( saw) and electric-separated piezoelectric sensor (esps), which have a great potential in further development both in theory and application, is also described concisely.
Control Strategies for Active Suspension with Pneumatic Actuators

Skogsindustrin ar en stor del av Sveriges ekonomi. Med hjalp av den sa kallade kapa till langd metoden, vilket betyder att traden forst kapas till lamplig langd och sen forslas de till sidan av en .