Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of artificial intelligence on consumer buying behaviors

Artificial Intelligence (AI) is an area that is fast growing in the business world. It has already been applied in many areas for instance commerce and everyday life. With AI in business, the industry will rely on faster cheaper, and more accurate marketing techniques. The present investigation is undertaken to find the relation between AI and consumer buying behavior and secondly to know the difference between customer buying behavior based on their demographics. To achieve these objectives, the researcher has collected data from 314 respondents from Nagpur. The researcher has employed Descriptive statistics, Correlation, Cronbach alpha, Anova, Mann-Whitney Test, and Kruskal-Wallis Test and has utilized SPSS for these tests. Results concluded to have a significant relationship between AI and consumer buying behavior. It was also concluded that there is a difference between consumer buying behavior and gender & monthly income. These were supported with hypothesis testing.
Spectra dependent photonic structure design for energy harvesting by indoor photovoltaic devices

In this work, we report spectra-dependent energy harvesting by optimizing the photon management of an indoor photovoltaic device while taking into consideration the degradation of electrical transport characteristics caused by the nano-photonic structures. For the test case of a CdTe-based photovoltaic device, it has been shown that although the incorporation of dielectric-filled nanoholes in the absorber layer can enhance light absorption by about 40%, the optical-to-electrical conversion efficiency of the device is significantly diminished because of the degradation of the electrical transport characteristics. Instead, the best performance metrics are obtained when the nanostructures are incorporated in the window layer of the device alone. A finite difference time domain based numerical analysis, coupled with Poisson’s equation and continuity equation, shows that by controlling the areal density of the optimized structure in direct correlation with spectral characteristics of the illuminating light source, it is possible to maximize the overall power conversion efficiency of the indoor photovoltaic device. In the case of commercial white light-emitting diodes (LEDs), large arealdensities of holes are found to be more conducive for harvesting energy from cool-white LEDs, whereas smaller areal densities of holes provide better performances for illumination under warm-glow white LEDs.
Probiotics Intervention for Mitigation of Uterine Infection in Dairy Animals -An Update

Probiotic bacteria are an important subject to explore when it comes to inhibiting infectious bacteria, also commercially available for its usage in a variety of sectors including animals and humans. Postpartum uterine infections including metritis and endometritis are common in buffaloes and cow a major problem dairy industry, as it is associated with reduced fertility and decreased milk yield. To address this issue, the present review discusses the role of probiotics in the treatment of infectious uterus and its implications in the reproductive efficiency of dairy animals. Probiotic administration in the host has proven to improve health status by competing for the nutrient utilization of infectious microbes. The antibiotic activity of probiotic bacteria is also known to reduce stress on the host. Application of the probiotic strains has been proposed as an alternative to prevent uterine infection and inflammation. Hence, this review article summarizes the effects of probiotics on metritis and endometritis in bovines. And the current studies on probiotics with their effects on the uterus include their immunomodulatory effects on the animal host.
Modelling the Effect of COVID-19 Lockdown on Air Pollution in Makkah Saudi Arabia with a Supervised Machine Learning Approach

To reduce the spread of COVID-19, lockdowns were implemented in almost every single country in the world including Saudi Arabia. In this paper, the effect of COVID-19 lockdown on O3, NO2, and PM10 in Makkah was analysed using air quality and meteorology data from five sites. Two approaches were employed: (a) comparing raw measured concentrations for the lockdown period in 2019 and 2020; and (b) comparing weather-corrected concentrations estimated by the machine learning approach with observed concentrations during the lockdown period. According to the first approach, the average levels of PM10 and NO2 decreased by 12% and 58.66%, respectively, whereas the levels of O3 increased by 68.67%. According to the second approach, O3 levels increased by 21.96%, while the levels of NO2 and PM10 decreased by 13.40% and 9.66%, respectively. The machine learning approach after removing the effect of changes in weather conditions demonstrated relatively less reductions in the levels of NO2 and PM10 and a smaller increase in the levels of O3. This showed the importance of adjusting air pollutant levels for meteorological conditions. O3 levels increased due to its inverse correlation with NO2, which decreased during the lockdown period.
OpenCMP: An Open-Source Computational Multiphysics Package

OpenCMP is a computational multiphysics software package based on the finite element method (Ferziger & Perić, 2002). It is primarily intended for physicochemical processes in which fluid convection plays a significant role. OpenCMP uses the NGSolve finite element library (Schöberl, n.d.) for spatial discretization and provides a configuration file-based interface for pre-implemented models and time discretization schemes. It also integrates with Netgen (Schöberl, n.d.) and Gmsh (Geuzaine & Remacle, 2009) for geometry construction and meshing. Additionally, it provides users with built-in functionality for post-processing, error analysis, and data export for visualisation using Netgen (Schöberl, n.d.) or ParaView (Ahrens et al., 2005).
Wool/polyester blends with UV protection and disperse printing

: A novel method for improving disperse print quality and UV-protecting efficiency of blended fabric wool/polyester was developed by combining UV-SUN ® CEL LIQ as a UV-absorber or TiO 2 -NPs as a blocker of UV into the disperse printing paste [βCD (10g/Kg), PEG-600 (20g/Kg), DMDHEU (10g/Kg), Citric acid (10g/Kg), Na-alginate (500g/Kg), and Disperse dye (20g/Kg)]. The achieved results reveal that when other parameters remain constant, the improvement in UV-protective capability follows the decreasing order TiO 2 NP's > UV-SUN ® CEL. The depth of dispersed printings, on the other hand, is the polar opposite. The amount of UV-protective agent put into the fabric surface, as well as the positive impact of the utilized disperse dye on blocking and/or absorbing damaging UV-B radiation, influence UV-protection ability. Even after 15 washing cycles, the UV-protection characteristic imparted is still effective. UV-protecting, Nanosized material, UV-absorber, or UV-blocker.
Time-Constrained Ensemble Sensing With Heterogeneous IoT Devices in Intelligent Transportation Systems

Recently we have witnessed the rise of Artificial Intelligence of Things (AIoT) and the shift of sensing paradigm from cloud-centric to the edge-centric, which effectively improves the sensing capability of intelligence transportation systems. To improve the real-time sensing performance, in this work we propose an ensemble sensing based scheme to solve the time-constraint synchronized inference problem and achieve robust inference with heterogeneous IoT devices in intelligence transportation systems. We design and implement Ensen, which incorporates various novel techniques such as customized DNN model design, KD-based model training, and dynamic deep ensemble management, etc., to achieve improved accuracy and maximize the computational resource usage of the whole sensing group. Extensive evaluations on different types of common IoT devices have shown that Ensen achieves a robust performance and can be easily extended to different types of convolutional neural networks.
Damage and Progressive Failure Analysis for Aeronautic Composite Structures with Curvature (Analyse van de propagatie van schade in gekromde composietonderdelen voor vliegtuigconstructies)

RIBEIRO, M. L. (2013) Damage and progressive failure analysis for aeronautic composite structures with curvature. 234p . PhD Thesis São Carlos School of Engineering, University of São Paulo, São Carlos. Recent improvements in manufacturing processes and materials properties associated with excellent mechanical characteristics and low weight have became composite materials very attractive for application on civil aircraft structures. However, even new designs are still very conservative, because the composite structure failure phenomena are very complex. Several failure criteria and theories have been developed to describe the damage process and how it evolves, but the solution of the problem is still open. Moreover, modern manufacturing processes, e.g. filament winding, have been used to produce a wide variety of structural shapes. Therefore, this work presents the development of a damage model and its application to simulate the progressive failure of flat composite laminates as well as for composite cylinders made by filament winding process. The proposed damage model has been implemented as a UMAT (User Material Subroutine) and VUMAT (User Material Subroutine for explicit simulations), which were linked to ABAQUS Finite Element (FE) commercial package. Progressive failure analyses have been carried out using FE Method in order to simulate the failure of filament wound composite structures under different quasi-static and impact loading conditions. In addition, experiments have been performed not only to identify parameters related to the material model but also to evaluate both the potentialities and the limitations of the proposed model. Key-Words: curved structures, composite materials, material model, progressive failure analysis, Finite Element Method.
Feedback of reaction force in haptics

Motion control for haptics is essential to realize various applications where the contact motion plays a major role. Particularly the feedback of contact to an operator on surgery is one of the important issues. The R&D team successfully realized a vivid sensation of touch for medical forceps in endoscopic surgery. This paper discusses how a bilateral motion is realized. Also the position and force control are analyzed for multilateral system. The paper also mentions the quarry process of environmental information.
A Catalog-Based AIG-Rewriting Approach to the Design of Approximate Components

As computational demand and energy efficiency of computer systems are becoming increasingly relevant requirements, traditional design paradigms are bound to become no longer appropriate, as they cannot guarantee significant improvements. The approximate-computing design paradigm has been introduced as a potential candidate to achieve better performances, by relaxing non-critical functional specifications. Anyway, several challenges need to be addressed in order to exploit its potential. In this paper, we propose a systematic and application-independent approximate design approach suitable to combinational logic circuits. Our approach is based on non-trivial local rewriting of and-inverter graphs (AIG), reducing the number of AIG-nodes and possibly resulting in lower hardware resources requirements. We adopt multi-objective optimization to carefully introduce approximation while aiming at optimal trade-offs between error and hardware-requirements. We evaluate our approach using different benchmarks, and, in order to measure actual gains, we perform actual synthesis of Pareto-optimal approximate configurations. Experimental results show that the proposed approach allows achieving significant savings, since resulting approximate circuits exhibit lower requirements and restrained error w.r. t. their exact couterparts.
Evaluation of Wrist Accelerometer Cut-Points for Classifying Physical Activity Intensity in Youth

Background Wrist worn accelerometers are convenient to wear and provide greater compliance. However, methods to transform the resultant output into predictions of physical activity (PA) intensity have been slow to evolve, with most investigators continuing the practice of applying intensity-based thresholds or cut-points. The current study evaluated the classification accuracy of seven sets of previously published youth-specific cut-points for wrist worn ActiGraph accelerometer data. Methods Eighteen children and adolescents [mean age (± SD) 14.6 ± 2.4 years, 10 boys, 8 girls] completed 12 standardized activity trials. During each trial, participants wore an ActiGraph GT3X+ tri-axial accelerometer on the wrist and energy expenditure (Youth METs) was measured directly using the Oxycon Mobile portable calorimetry system. Seven previously published sets of ActiGraph cut-points were evaluated: Crouter regression vertical axis, Crouter regression vector magnitude, Crouter ROC curve vertical axis, Crouter ROC curve vector magnitude, Chandler ROC curve vertical axis, Chandler ROC curve vector magnitude, and Hildebrand ENMO. Classification accuracy was evaluated via weighted Kappa. Confusion matrices were generated to summarize classification accuracy and identify patterns of misclassification. Results The cut-points exhibited only moderate agreement with directly measured PA intensity, with Kappa ranging from 0.45 to 0.58. Although the cut-points classified sedentary behavior accurately (> 95%), classification accuracy for the light (3–51%), moderate (12–45%), and vigorous-intensity trials (30–88%) was generally poor. All cut-points underestimated the true intensity of the walking trials, with error rates ranging from 35 to 100%, while the intensity of activity trials requiring significant upper body and/or arm movements was consistently overestimated. The Hildebrand cut-points which serve as the default option in the popular GGIR software package misclassified 30% of the light intensity trials as sedentary and underestimated the intensity of moderate and vigorous intensity trials 75% of the time. Conclusion Published ActiGraph cut-points for the wrist, developed specifically for school-aged youth, do not provide acceptable classification accuracy for estimating daily time spent in light, moderate, and vigorous intensity physical activity. The development and deployment of more robust accelerometer data reduction methods such as functional data analysis and machine learning approaches continues to be a research priority.
Flavivirus Capsid Proteins Inhibit the Interferon Response

Zika virus (ZIKV) establishes persistent infections in multiple human tissues, a phenomenon that likely plays a role in its ability to cause congenital birth defects and neurological disease. Multiple nonstructural proteins encoded by ZIKV, in particular NS5, are known to suppress the interferon (IFN) response by attacking different steps in this critical antiviral pathway. Less well known are the potential roles of structural proteins in affecting the host immune response during ZIKV infection. Capsid proteins of flaviviruses are of particular interest because a pool of these viral proteins is targeted to the nuclei during infection and, as such, they have the potential to affect host cell gene expression. In this study, RNA-seq analyses revealed that capsid proteins from six different flaviviruses suppress expression of type I IFN and IFN-stimulated genes. Subsequent interactome and in vitro ubiquitination assays showed that ZIKV capsid protein binds to and prevents activating ubiquitination of RIG-I CARD domains by TRIM25, a host factor that is important for the induction arm of the IFN response. The other flavivirus capsid proteins also interacted with TRIM25, suggesting that these viral proteins may attenuate antiviral signaling pathways at very early stages of infection, potentially even before nonstructural proteins are produced.
Cover successions on early Paleozoic basement in Marie Byrd Land, West Antarctica – evidence for Cretaceous plant-bearing rocks at South Polar latitudes

ABSTRACT Detrital zircon ages from sandstones in isolated plant-bearing, probably fluviatile sedimentary successions at Milan Rock and Mount Murphy, Marie Byrd Land, West Antarctica indicate probable mid-Cretaceous (95--105 Ma) depositional ages. Rocks of similar age reported from the Amundsen Sea have indicated warm, humid environments and the new data reported here for plant-bearing rocks would now place such conditions close (>80°S) to the contemporary mid-Cretaceous South Pole
Comparison of standard miniplates and locked miniplates in post-traumatic fracture stabilization

ABSTRACT BACKGROUND: Bicortical screws (lag and positional) or miniplates with monocortical screws are generally used for the rigid fixation of the sagittal split ramus osteotomy (SSRO) in maxillofacial surgery. However, in this osteosynthesis method, the plate must be perfectly adapted to the bone to prevent misalignment of the bone segment and occlusal changes. In addition, it is necessary to prevent the position of the condyle in the mandibular fossa from changing after fixation. In recent years, locked miniplate systems have been used to overcome these complications. METHODS: The aim of this study is to compare the commonly used 2.0 mm standard miniplate/screw systems and 2.0 mm locking miniplate/screw systems in fresh sheep jaws with Obwegeser-Dal Pont (OD) and Hunsuck-Epker (HE) modifications, by evaluating standard parameters. RESULTS: Our study consists of two main groups and two subgroups. 40 sheep hemimandibulae were randomly divided into two main groups. Each group was randomly divided into two subgroups. There are ten hemimandibulae (n=10) in each subgroup. Linear force test was applied using 4-hole standard miniplate and 4-hole locking miniplate systems on sheep jaws with 5 mm advancement by applying OD and HE techniques, which are two frequently preferred modifications in SSRO. For statistical analysis SPSS® 16.0 (Statistical Package for the Social Sciences, SPSS Inc. Chicago, Illinois, USA) package program was used. It was statistically compared with the 95% confidence interval using the Pearson coefficient, and p<0.05 was interpreted as significant. The values of the loading forces applied to the samples in the groups were subjected to analysis of variance (ANOVA) to confirm the normality of the sample. Multiple comparisons were made between groups using the Tukey test. The mean loadings in the groups were analyzed by one-way ANOVA. CONCLUSION: In general, as the strength of the force increases, the displacement values increase in all groups, but although it was observed that the locked miniplate/screw system was more stable than the standard miniplate/screw system, no statistically significant difference was found.
Power Quality Enhancement of the Distribution Network by Multilevel STATCOM-Compensated Based on Improved One-Cycle Controller

There are several ways to reduce and compensate for voltage disturbances. One of the methods is to use a Multilevel STATCOM. Multilevel inverters are widely used in various parts of the power system and industry due to advantages, such as appropriate output waveform (voltage and current). There are numerous controllers for multilevel STATCOM control. One of the simple and economy controllers is the one-cycle controller, which is usually used in DC / DC and DC / AC converters. In this paper, a new structure is proposed to improve the performance of the one-cycle controller. Improvements include voltage sag and swell, voltage disturbances, harmonics, and short-term outages. To demonstrate the performance of the proposed controller, the multilevel STATCOM is also tested and compared with conventional PWM control. The simulation results show that multilevel STATCOM will correct the disturbances. Among the advantages of the proposed method are its simplicity, robustness, and flexibility, so that with one adjustment, the parameters of the control system can compensate for all the defects.
An attention-based transformer model for dental caries detection

Dental caries is one of the most common diseases suffered by modern people. If early diagnosis and treatment are not carried out in time, dental caries may greatly affect the quality of life. However, the doctor’s diagnosis often misses tooth decay that is not obvious. In our research, we propose a caries detection model that combines attention mechanism and transformer. A new attention mechanism is introduced to represent features in different channels better. The AP50 of the model reached 63.81%, and even unlabeled caries in the X-ray image could be found.
ACE2 and TMPRSS2 Immunolocalization and COVID-19-Related Thyroid Disorder

Simple Summary We analyzed the underlying mechanism of thyroidal manifestations in patients with COVID-19 using ACE2 and TMPRSS2 immunostaining. Prior to our work, few studies had investigated the mRNA expression of ACE2 in the thyroid gland. However, there has been no tissue-level study based on histological staining of ACE2 and TMPRSS2. Here, we found for the first time that ACE2 and TMPRSS2 proteins were not expressed in thyroid follicular cells and that ACE2 was exclusively expressed in thyroidal pericytes by immunolocalization of ACE2 and TMPRSS2 in the human thyroid tissue. The results of the present study demonstrate that SARS-CoV-2 does not directly invade thyroid follicular cells, but microcirculatory damage caused by pericyte infection may affect surrounding follicles in the thyroid gland. Abstract Thyroid dysfunction has been reported to be an extrapulmonary symptom of COVID-19. It is important to identify the tissue subset that expresses angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2), which are essential for host infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in order to understand the viral pathogenesis of COVID-19-related thyroid dysfunction. We investigated the expression and distribution of ACE2- and TMPRSS2-expressing cells in the thyroid gland. RT-PCR and Western blotting were performed on human thyroid follicular cells (Nthy-ori3-1) and rat thyroid tissues to detect the expression levels of ACE and TMPRSS2 mRNA and proteins. We also analyzed the expression patterns of ACE2 and TMPRSS2 in 9 Sprague-Dawley rats and 15 human thyroid tissues, including 5 normal, 5 with Hashimoto’s thyroiditis, and 5 with Graves’ disease, by immunohistochemistry (IHC) and immunofluorescence. Both ACE2 and TMPRSS2 mRNAs and proteins were detected in the thyroid tissue. However, ACE2 and TMPRSS2 proteins were not expressed in thyroid follicular cells. In IHC, ACE2 and TMPRSS2 were not stained in the follicular cells. No cells co-expressed ACE2 and TMPRSS2. ACE2 was expressed in pericytes between follicles, and TMPRSS2 was mainly stained in the colloid inside the follicle. There was no difference in expression between the normal thyroid, Hashimoto’s thyroiditis, and Graves’ disease. SARS-CoV-2 does not directly invade the thyroid follicular cells. Whether SARS-CoV-2 infection of pericytes can affect COVID-19-related thyroid dysfunction warrants further study.