Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloning and Characterization of Three Novel Enzymes Responsible for the Detoxification of Zearalenone

Zearalenone is a common mycotoxin contaminant in cereals that causes severe economic losses and serious risks to health of human and animals. Many strategies have been devised to degrade ZEN and keep food safe. The hydrolase ZHD101 from Clonostachys rosea, which catalyzes the hydrolytic degradation of ZEN, has been studied widely. In the current research, three new enzymes that have the capacity to detoxify ZEN were identified, namely CLA, EXO, and TRI, showing 61%, 63%, and 97% amino acids identities with ZHD101, respectively. Three coding genes was expressed as heterologous in Escherichia coli BL21. Through biochemical analysis, the purified recombinant CLA, EXO, TRI, and ZHD101 exhibited high activities of degrading ZEN with the specific activity of 114.8 U/mg, 459.0 U/mg, 239.8 U/mg, and 242.8 U/mg. The optimal temperatures of CLA, EXO, TRI, and ZHD101 were 40 °C, 40 °C, 40 °C, and 45 °C, and their optimum pH were 7.0, 9.0, 9.5, and 9.0, respectively. Our study demonstrated that the novel enzymes CLA, EXO, and TRI possessed high ability to degrade ZEN from the model solutions and could be the promising candidates for ZEN detoxification in practical application.
A statistical framework for analyzing cyber attacks

v List of Tables . x List of Figures . xi Chapter 1: Introduction . 1 1.1 Research Motivation: Understanding and Characterizing Cyber Attacks . 1 1.2 Framework . 1 1.3 Data sources . 3 Chapter 2: Analyzing Long-Range Dependence Exhibited by Cyber Attacks . 5 2.
Economics and Mathematical Relationship: A Case Study in University Economics Course of Nepal

In our teaching program and methods, the mathematical approach has a major influence on economics. In this paper, I examined the aforementioned economics and mathematical relationships, taking into account their historical development as well as the experience gained over several years in the Masters in Economics Sciences' economics course. Changes in the initial practices in the classroom entering university have prompted a rethinking of a number of fundamental questions, including: What parameters should be used to determine the most suitable curriculum and teaching approach in a changing environment? What mathematical singularities does economics teaching present? This last question introduces us to the topic we'll be discussing. How much math should be taught in economics classes? Is it important for students to have a strong mathematical foundation before they study economics? For some teachers, economic issues are merely an addendum to the practical portion of the topic, while for others; economic models are the subject's main focus. As a consequence, mathematics in general is now assisting in the analysis of economics. In conclusion, as students study economics, it becomes more difficult for them to study other mathematics topics. Since not all students excel at math, economics is a more difficult subject to study. However, studying algebra, calculus, and logarithms, among other subjects, makes economics more important.
Earlier than expected introductions of the Bemisia tabaci B mitotype in Brazil reveal an unprecedented, rapid invasion history

Abstract During 1991, in Brazil, the presence of the exotic Bemisia tabaci B mitotype was reported in São Paulo state. However, the duration from the time of initial introduction to population upsurges is not known. To investigate whether the 1991 B mitotype outbreaks in Brazil originated in São Paulo or from migrating populations from neighboring introduction sites, country‐wide field samples of B. tabaci archived from 1989–2005 collections were subjected to analysis of mitochondrial cytochrome oxidase I (mtCOI) and nuclear RNA‐binding protein 15 (RP‐15) sequences. The results of mtCOI sequence analysis identified all B. tabaci as the NAFME 8 haplotype of the B mitotype. Phylogenetic analyses of RP‐15 sequences revealed that the B mitotype was likely a hybrid between a B type parent related to a haplotype Ethiopian endemism (NAFME 1–3), and an unidentified parent from the North Africa‐Middle East (NAF‐ME) region. Results provide the first evidence that this widely invasive B mitotype has evolved from a previously undocumented hybridization event. Samples from Rio de Janeiro (1989) and Ceará state (1990), respectively, are the earliest known B mitotype records in Brazil. A simulated migration for the 1989 introduction predicted a dispersal rate of 200–500 km/year, indicating that the population was unlikely to have reached Ceará by 1990. Results implicated two independent introductions of the B mitotype in Brazil in 1989 and 1990, that together were predicted to have contributed to the complete invasion of Brazil in only 30 generations.
High-Performance α-Bi2O3/CdS Heterojunction Photocatalyst: Innovative Design, Electrochemical Performance and DFT Calculation

Heterojunction semiconductor photocatalysis is an auspicious technique for clear up organic pollutants from water, and have been of valuable strategy in the area of photocatalysis. Herein, electrophoretic deposition procedure was used to prepare α-Bi2O3/CdS type-Ⅱ heterojunction photocatalysts. The results of PL, Raman, and EIS show that there is a heterojunction effect in α-Bi2O3/CdS, which is propitious to improve the separation efficiency of photogenerated electron-hole pairs. The DFT calculation reveals that the work function of CdS (4.57 eV) is higher than that of α-Bi2O3 (3.37 eV), which facilitates the migrating of e- from the CB of α-Bi2O3 to the CB of CdS, and the migrating of h+ from the VB of CdS to the VB of α-Bi2O3, thus the e--h+ pairs with high redox ability are retained. The performances were assessed by degrading methyl orange (MO), acid magenta under simulated visible light irradiation. Under simulated visible light irradiation, BC45 composite exhibited the highest degradation efficiency of 87% (MO) and 81% (acid fuchsin) for 4 h, which was about 2 times higher than that of CdS (MO) and (acid fuchsin). It is believed that the dual characteristics of H2O wettability and dye adsorption performance in α-Bi2O3/CdS composites promote photocatalytic process compared with single CdS and α-Bi2O3. The study could provide new insights to develop efficiently capable photocatalysts of the α-Bi2O3/CdS composites.
Integration and Testing of Novel MOX Gas Sensors for IoT-based Indoor Air Quality Monitoring

The occurrence of hazardous gases and toxic or harmful vapors in laboratories, factories, and chemical warehouses requires a fast detection of leakage accidents to avoid health impairments. In this paper, the integration and validation of two novel metal oxide gas sensors (MOX) for the application in an IoT-based air quality monitoring and the alarming system is proposed. The sensors are combined with WeMos D1 Mini IoT-based microcontroller for data processing and transmitting via Wi-Fi communication protocol. The system design takes into consideration the low-cost, light-weight, small-size, and low power consumption concepts to enable a portable compact system that can be operated stand-alone or easily be adapted to any stationary or mobile robotic platform. The system was tested with several volatile organic materials (VOCs). The acquired air quality data are transferred to an IoT cloud, where the data are stored in a database for further analysis and research. Further, the data can be directly monitored on a PC, tablet, and smartphone. The system testing results confirm that the system can be used efficiently in laboratory environments.
The Synthesis and Anti-Cytomegalovirus Activity of Piperidine-4-Carboxamides

Treatment options for human cytomegalovirus (CMV) remain limited and are associated with significant adverse effects and the selection of resistant CMV strains in transplant recipients and congenitally infected infants. Although most approved drugs target and inhibit the CMV DNA polymerase, additional agents with distinct mechanisms of action are needed for the treatment and prevention of CMV. In a large high throughput screen using our CMV-luciferase reporter Towne, we identified several unique inhibitors of CMV replication. Here, we synthesize and test in vitro 13 analogs of the original NCGC2955 hit (1). Analogs with no activity against the CMV-luciferase at 10 µM and 30 µM (2–6, 10–14) were removed from further analysis. Three analogs (7–9) inhibited CMV replication in infected human foreskin fibroblasts. The EC50 of (1) was 1.7 ± 0.6 µM and 1.99 ± 0.15 µM, based on luciferase and plaque assay, respectively. Compounds 7, 8, and 9 showed similar activities: the EC50 values of 7 were 0.21 ± 0.06 µM (luciferase) and 0.55 ± 0.06 (plaque), of 8: 0.28 ± 0.06 µM and 0.42 ± 0.07, and of 9: 0.30 ± 0.05 µM (luciferase) and 0.35 ± 0.07 (plaque). The CC50 for 7, 8, and 9 in non-infected human foreskin fibroblasts was > 500µM, yielding a selectivity index of >1500. Compounds 1, 7, and 8 were also tested in CMV-infected primary human hepatocytes and showed a dose–response against CMV by luciferase activity and viral protein expression. None of the active compounds inhibited herpes simplex virus 1 or 2. Compounds 7 and 8 inhibited mouse CMV replication in vitro. Both inhibited CMV at late stages of replication; 7 reduced virus yield at all late time points, although not to the same degree as letermovir. Finally, the activity of analog 8 was additive with newly identified CMV inhibitors (MLS8969, NFU1827, MSL8554, and MSL8091) and with ganciclovir. Further structural activity development should provide promising anti-CMV agents for use in clinical studies.
Beyond Prior Belief and Volatility: The Distinct Iterative Prior Updating Process in ASD

Research has shown individuals with autism spectrum disorder (ASD) display atypical patterns in predictive processing, yet it remains controversial regarding what causes these atypical behaviors because findings have been inconsistent. Our study employed a two-state Bayesian model to decide between two suggested factors: an aberrant long-term prior and atypical short-term iterative belief updating. Both ASD individuals and typically developing (TD) counterparts participated in a task where they reproduced time durations over two sessions, one characterized by high volatility and the other by predictable sequences. Both sessions involved the same time durations, but the sequences differed in volatility. While both groups adjusted their prior belief to the level of volatility in a similar manner, they diverged in their short-term iterative updating of beliefs. Individuals with ASD iteratively adjusted their beliefs with each new stimulus as if it were less connected to previous ones compared to TD individuals, thereby assigning greater weight to incoming sensory information. Our findings highlight that the distinctive signature of cognitive processing in ASD lies in a mechanism of overreliance on sensory input specific to short-term iterative belief updating. This unique characteristic may mirror an experience among individuals with ASD of temporal discontinuity rendering the world overly unpredictable.
The Association of Underlying Diseases and Age-Related Cataracts in Iranian Patients

Background: Age-Related Cataracts (ARC) is a multifactorial ocular dysfunction resulting inblurred lens, visual reduction, and blindness. Various underlying diseases are involved in increasing the risk of ARC. The purpose of this study was to investigate the association of underlying diseases and related medications with ARC in Iranian patients. Methods: In this case-control study, 353 patients (age between 40 to 70 years) with ARC were referred to Rouhani Hospital, Babol, Iran, and 343 control individuals (age between 40 to 70 years) participated. The history of underlying diseases of participants was collected by history-taking and self-expression. The cataract intensity and type determination was based on the Lens Opacities Classification System III (LOCS Ш). Results: Our results show that obesity (p <0.001), diabetes mellitus (OR = 0.422, 95% CI [0.285, 0.625], p<0.001) ,and hypertension (OR = 0.518, 95% CI [0.378, 0.712], p<0.001) are associated with prevalence of ARC (more prevalent in ARC patients compared to controls). The posterior subcapsular ARC is more prevalent in asthmatic ARC patients compared to non-asthmatic ARC patients (p=0.019). The prevalence of cortical ARC is higher in anemic ARC patients compared to non-anemic ARC patients (p=0.031). Cortical and posterior subcapsular ARC prevalence is higher in rheumatic ARC patients than non-rheumatic ARC patients (p=0.006). Also, atorvastatin use plays a preventive role in ARC (p=0.031). Conclusion: Our results established that obesity, diabetes mellitus, hypertension, and asthma are associated with the prevalence of ARC. Also, atorvastatin, as a routine medication, plays a preventive role in ARC. Furthermore, asthma, anemia, and rheumatism are involved in prevalence of certain types of ARC.
Wearable Physical Activity and Sleep Tracker Based Healthy Lifestyle Intervention in Early Intervention Psychosis (EIP) Service: Patient Experiences

Background: Physical activity, sleep, mental health, physical health, wellbeing, quality of life, cognition, and functioning in people who experience psychosis are interconnected factors. People experiencing psychosis are more likely to have low levels of physical activity, high levels of sedation, and sleep problems. Intervention: An eight-week intervention; including the provision of a Fitbit and its software apps, sleep hygiene and physical activity guidance information, as well as three discussion and feedback sessions with a clini-cian. Participants: Out of a sample of 31 using an early intervention psychosis (EIP) service who took part in the intervention, fifteen participants con-sented to be interviewed—9 (60%) males and 6 (40%) females, age range: 19 51 years, average age: 29 years. Method: In-depth interviews investigating patient experience of the intervention and its impact on sleep, exercise, and wellbeing were undertaken. Thematic analysis was applied to analyse the qualitative data and content analysis was used to analyse questions with a yes/no response. Results: Most of the participants actively used the Fitbit and its software apps to gain information, feedback, and set goals to make changes to their lifestyle and daily routines to improve quality of sleep, level of physical activity, and exercise. Conclusion: The intervention was reported to be bene-ficial, and it is relatively easy and low cost to implement and therefore could be offered by all EIP services. Furthermore, there is potential value for application in services for other psychiatric disorders, where there is often a need to promote healthy lifestyle, physical activity, and effective sleep.
SPARCL1 Is a Novel Prognostic Biomarker and Correlates with Tumor Microenvironment in Colorectal Cancer

Background Secreted protein acidic and rich in cysteine-like 1 (SPARCL1) plays an important role in tumor pathogenesis. We aim to evaluate the clinical significance and potential biological roles of SPARCL1 in colorectal cancer (CRC). Methods Datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were downloaded to evaluate the expression levels of SPARCL1 in CRC. Receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of SPARCL1. Then, comprehensive database search was conducted for published clinical studies to explore clinical significance of SPARCL1. In addition, coexpression genes of SPARCL1 were identified through the cBioPortal database and enrichment analysis of SPARCL1 and its coexpression genes were performed by the “clusterProfiler” R package. Finally, the correlations between SPARCL1 and tumor microenvironment scores, tumor-infiltrating immune cells in CRC were determined by “ESTIMATE” and “GSVA” R packages. Results SPARCL1 was significantly downregulated in CRC tissues, and SPARCL1 showed high accuracy for diagnosis of primary CRC in both GEO and TCGA datasets. Pooled results from published clinical studies showed SPARCL1 expression was associated with differentiation (OR = 1.89, 95% CI: 1.38-2.59), tumor stage (OR = 0.47, 95% CI: 0.29-0.77), distant metastasis (OR = 0.53, 95% CI: 0.33-0.84), and overall survival (HR = 0.56, 95% CI: 0.43-0.74). SPARCL1 and its top 300 coexpression genes were involved in several KEGG pathways, such as focal adhesion, cell adhesion molecules, PI3K-Akt signaling pathway, cGMP-PKG signaling pathway, and ECM-receptor interaction. Besides, the SPARCL1 expression was significantly correlated with stromal score, immune score, ESTIMATE score, and diverse immune cells. Conclusion SPARCL1 significantly correlated with clinicopathological features and tumor microenvironment in CRC.
Cashew Apple Extract: A Novel, Potential Green Reducing Agent for the Synthesis of Reduced Graphene Oxide

Abstract Reduced graphene oxide (rGO) is one of the promising materials which are used in energy storage devices, field effect resistors and as an additive in polymer composites for functional and structural applications. The reduction of graphene oxide (GO) to rGO is popular and attractive. Chemical reduction of GO is considered as one of the promising methods for the large-scale production of rGO. Herein, we report for the first time a sustainable, eco-friendly and facile approach for synthesizing rGO using cashew apple extract as a reducing agent. Reduction of GO by cashew apple extract was confirmed by the bathochromic shift in the UV-Visible spectrum. The extent of reduction by cashew apple extract at temperatures (80°C, 120°C, and 180°C) was determined by making use of X-ray Photoelectron Spectroscopy (XPS), X-ray Diffraction (XRD), Raman Spectroscopy and Fourier Transform Infrared Spectroscopy (FTIR) and were morphologically confirmed using Transmission Electron Microscopy (TEM). Through this research work, we propose an environment friendly approach for the production of rGO.
Pick And Place Robotic Arm With Training Kit

The purpose of this project is to developed Pick and Place Robotic Arm with Training Kit. The function of this robot is to pick and place material and equipped with hardware and software. This robot can be controlled by using the remote controller and also using computer program. The main objective of this project is to develop a prototype pick and place robot that can be used as a teaching method to deliver a better understanding of basic function, operation and programming of a robot. The application ofthis project is also can be used in other related field such as industry, military, medical and so on. This project was successfully developed and tested and the hardware and the software could be integrated and working well without error.
Flatfish: A Reinforcement Learning Approach for Application-Aware Address Mapping

The DRAM performance has become a critical bottleneck of modern computing systems. Prior studies have proposed various optimization techniques on address mapping to bridge the gap between real performance and the peak performance. Nevertheless, these techniques have some common limitations. First, most of them focus on an indirect metric (e.g., bitwise flip ratio) and fail to address the effects of complicated organization hierarchy and timing constraints of DRAM. Second, these approaches do not leverage application-specific information and may not generate the proper address mapping schemes for modern applications. In this article, we propose Flatfish as a comprehensive solution to address these challenges. Flatfish is a self-adaptive memory controller that is able to generate address mapping schemes according to the memory access pattern. Different from prior approaches, Flatfish considers complicated memory hierarchy, including channel, rank, and bank group and addressed critical timing constraints. By mining the characteristics from the memory access traces, Flatfish integrates a reinforcement learning model to generate a binary invertible matrix (BIM) as the address mapping scheme. Flatfish can work in either offline mode or online mode to meet various requirements in different scenarios. The experimental results show that Flatfish can achieve $1.91\times $ speedup in the offline mode on GPU, and $1.63\times $ speedup in the online mode on CPU, over the commonly used Hynix address mapping scheme.
Clinical subtyping using community detection: Limited utility?

To discover psychiatric subtypes, researchers are adopting a method called community detection. This method was not subjected to the same scrutiny in the psychiatric literature as traditional clustering methods. Furthermore, many community detection algorithms have been developed without psychiatric sample sizes and variable numbers in mind. We aim to provide clarity to researchers on the utility of this method.
A Computer Vision-Based Approach for Tick Identification Using Deep Learning Models

Simple Summary Ticks are ectoparasites of humans, livestock, and wild animals and, as such, they are a nuisance, as well as vectors for disease transmission. Since the risk of tick-borne disease varies with the tick species, tick identification is vitally important in assessing threats. Standard taxonomic approaches are time-consuming and require skilled microscopy. Computer vision may provide a tenable solution to this problem. The emerging field of computer vision has many practical applications already, such as medical image analyses, facial recognition, and object detection. This tool may also help with the identification of ticks. To train a computer vision model, a substantial number of images are required. In the present study, tick images were obtained from a tick passive surveillance program that receives ticks from public individuals, partnering agencies, or veterinary clinics. We developed a computer vision method to identify common tick species and our results indicate that this tool could provide accurate, affordable, and real-time solutions for discriminating tick species. It provides an alternative to the present tick identification strategies. Abstract A wide range of pathogens, such as bacteria, viruses, and parasites can be transmitted by ticks and can cause diseases, such as Lyme disease, anaplasmosis, or Rocky Mountain spotted fever. Landscape and climate changes are driving the geographic range expansion of important tick species. The morphological identification of ticks is critical for the assessment of disease risk; however, this process is time-consuming, costly, and requires qualified taxonomic specialists. To address this issue, we constructed a tick identification tool that can differentiate the most encountered human-biting ticks, Amblyomma americanum, Dermacentor variabilis, and Ixodes scapularis, by implementing artificial intelligence methods with deep learning algorithms. Many convolutional neural network (CNN) models (such as VGG, ResNet, or Inception) have been used for image recognition purposes but it is still a very limited application in the use of tick identification. Here, we describe the modified CNN-based models which were trained using a large-scale molecularly verified dataset to identify tick species. The best CNN model achieved a 99.5% accuracy on the test set. These results demonstrate that a computer vision system is a potential alternative tool to help in prescreening ticks for identification, an earlier diagnosis of disease risk, and, as such, could be a valuable resource for health professionals.