Miracle-dz/UniFAR-FTUs huggingface dataset:
Point-to-point Destination of Mobile Robot using Linear Odometry

The point-to-point destination (P2D) system is a robot motion system to reach the destination position by providing cartesian input coordinates for the initial and destination places. Confined areas such as airports can use this system to make it easier for users to carry goods from one point to another. This study aims to design a semi-autonomous mobile robot based on linear odometry using four E18-D80NK infrared proximity sensors. The mobile robot's initial position and destination position is initiated by providing input (initial cartesian axis) and output (end cartesian axis) values on the gadget device connected to the mobile robot wirelessly via Bluetooth communication. The results of the infrared-based heading angle reading test result in an average measurement error of 1.90%. Then, the results of the infrared-based distance test produce an average measurement error of 1.83%. The results of testing the point-to-point destination system have an average error of reading the destination coordinates as follows in quadrant I of 2.25%, in quadrant II of 1.34%, in quadrant III of 5.01 %, and quadrant IV of 4.87%.
DC Arc Flash Calculations in 110V UPS Systems

This paper describes the DC arc flash analysis, existing calculation models and arc flash methodology for networks with constant DC voltage sources. For the examined 110V DC UPS system, the main goal was to evaluate DC arc flash conditions and to determine respective PPE categories. The overview of several commercial softwares which currently cover the DC arc flash analysis is also provided.
Wearable Inertial Sensor-Based Limb Lameness Detection and Pose Estimation for Horses

Accurate objective, automated limb lameness detection and pose estimation play an important role for animal well-being and precision livestock farming. We present a wearable sensor-based limb lameness detection and pose estimation for horse walk and trot locomotion. The gait event and lameness detection are first built on a recurrent neural network (RNN) with long short-term memory (LSTM) cells. Its outcomes are used in the limb pose estimation. A learned low-dimensional motion manifold is parameterized by a phase variable with a Gaussian process dynamic model. We compare the RNN-LSTM-based lameness detection method with a feature-based multi-layer classifier (MLC) and a multi-class classifier (MCC) that are built on support vector machine/K-nearest-neighbors and deep convolutional neural network methods, respectively. Experimental results show that using only accelerometer measurements, the RNN-LSTM-based approach achieves 95% lameness detection accuracy and also outperforms the feature-based MLC or MCC in terms of several assessment criteria. The pose estimation scheme can predict the 24 limb joint angles in the sagittal plane with average errors less than 5 and 10 degs under normal and induced lameness conditions, respectively. The presented work demonstrate the successful use of machine learning techniques for high performance lameness detection and pose estimation in equine science. Note to Practitioners—Automation technologies are increasingly used for precision agriculture but few have focused on monitoring individual animals in open field for precision livestock farming. Limb lameness detection and pose estimation in open field is labor-intensive, unsafe for farmers, and inefficient. The presented machine learning-enabled, wearable inertial sensor-based design provides an effective and efficient approach for horse limb lameness detection and pose estimation applications. We present an RNN-LSTM for lameness detection and an integrated manifold learning model is used to predict the horse limb joint angles in walk and trot gaits under normal and induced lameness conditions. We also present a systematic analysis and experiments to demonstrate the impacts of the wearable sensor locations and signal information on lameness detection and pose estimation performance. Several other machine learning-based lameness detection methods are also presented and compared. The extensive multi-horse testing results are presented to demonstrate the superior accuracy and higher performance than other types of machine learning methods. One attractive feature of the proposed design lies in its high performance and fast computational capability for potential real-time applications in open field.
Compact Multi-Band Flexible Antenna for ISM, WLAN, Wi-Fi, and 5G sub-6-GHz Applications

Design and analysis of a compact multi-band flexible antenna are presented here. The antenna is designed using the flexible substrate material Rogers 5880 and has a compact size of 18mm×18mm×0.254mm. The coplanar waveguide (CPW) fed radiator consists of a rectangular-shaped patch modified using a pair of rectangular slots to achieve the required bandwidth. Another smaller slot was etched in the radiator to achieve a lower resonance. The proposed design offers a multi-band functionality covering ISM, WLAN, Wi-Fi, and upper 5G sub-6-GHz bands.
Assessing the Role of a Malonamide Linker in the Design of Potent Dual Inhibitors of Factor Xa and Cholinesterases

The rational discovery of new peptidomimetic inhibitors of the coagulation factor Xa (fXa) could help set more effective therapeutic options (to prevent atrial fibrillation). In this respect, we explored the conformational impact on the enzyme inhibition potency of the malonamide bridge, compared to the glycinamide one, as a linker connecting the P1 benzamidine anchoring moiety to the P4 aryl group of novel selective fXa inhibitors. We carried out structure–activity relationship (SAR) studies aimed at investigating para- or meta-benzamidine as the P1 basic group as well as diversely decorated aryl moieties as P4 fragments. To this end, twenty-three malonamide derivatives were synthesized and tested as inhibitors of fXa and thrombin (thr); the molecular determinants behind potency and selectivity were also studied by employing molecular docking. The malonamide linker, compared to the glycinamide one, does significantly increase anti-fXa potency and selectivity. The meta-benzamidine (P1) derivatives bearing 2′,4′-difluoro-biphenyl as the P4 moiety proved to be highly potent reversible fXa-selective inhibitors, achieving inhibition constants (Ki) in the low nanomolar range. The most active compounds were also tested against cholinesterase (ChE) isoforms (acetyl- or butyrylcholinesterase, AChE, and BChE), and some of them returned single-digit micromolar inhibition potency against AChE and/or BChE, both being drug targets for symptomatic treatment of mild-to-moderate Alzheimer’s disease. Compounds 19h and 22b were selected as selective fXa inhibitors with potential as multimodal neuroprotective agents.
Topics in Numerical Relativity: The periodic standing-wave approximation, the stability of constraints in free evolution, and the spin of dynamical black holes

This thesis concerns numerical relativity, the attempt to study Einstein's theory of gravitation using numerical discretization. The goal of the field, the study of gravitational dynamics in cases where symmetry reduction or perturbation theory are not possible, finally seems to be coming to fruition, at least for the archetypal problem of the inspiral and coalescence of binary black hole systems. This thesis presents three episodes that each bear some relationship to this story. Chapters 2 and 3 present previously published work in collaboration with Richard Price and others on the so-called periodic standing-wave (PSW) approximation for binary inspiral. The approximation is to balance outgoing radiation with incoming radiation, stabilizing the orbit and making the problem stationary in a rotating frame. Chapters 2 and 3 apply the method to the problem of co-orbiting charges coupled to a nonlinear scalar field in three dimensions. Chapters 4, 5, and 6 concern the stability of constraint fields in conventional numerical relativity simulations. Chapter 4 (also previously published work, in collaboration with the Caltech numerical relativity group, along with Michael Holst and Lawrence Kidder) presents a method for immediately correcting violations of constraints after they have arisen. Chapters 5 and 6 present methods to ``damp' away constraint violations dynamically in two specific contexts. Chapter 5 (previously published work in collaboration with the Caltech numerical relativity group and Lawrence Kidder) presents a first-order linearly degenerate symmetric hyperbolic representation of Einstein's equations in generalized harmonic gauge. A representation is presented that stabilizes all constraints, including those that appear when the system is written in first-order form. Chapter 6 presents a generalization of the Kidder-Scheel-Teukolsky evolution systems that provides much-improved stability. This is investigated with numerical simulations of a single black hole spacetime. Finally, chapter 7 presents work in progress to implement code to calculate the spin of black holes in numerical simulations. This requires a well-defined generalization of the concept of ``rotation generators' on topological two-spheres that may not have any true Killing vectors. I present a new method for defining these fields, and results of a numerical code that computes them.
Empirical Likelihood Ratio Tests for Homogeneity of Multiple Populations in the Presence of Auxiliary Information

The empirical likelihood ratio test (ELRT) statistic is constructed for testing the homogeneity of several nonparametric populations in the presence of some auxiliary information. It is shown—under some regularity conditions and under the null hypothesis that all distribution functions of the populations are equal—that the asymptotic distribution of the ELRT is a chi-squared distribution. The proposed ELRT could be more powerful than the Kruskal–Wallis test, as extra information can be efficiently employed by ELRT. The advantage of ELRT over T&P (2006) is that researchers do not need to select approximately normal statistics for inter-group comparisons, and ELRT is more suitable for the multi-population consistency test with a small sample size.
Chloroform Fraction of Cucumis melo L. ‘Gama Melon Parfum’ Cytotoxicity against Breast Cancer Cell T47D and MCF7

Nature is the source of various types of phytochemicals. Some of them are unique chemical compounds only found in certain plants. For example, Cucurbitacin is found in the family Cucurbitaceae. Cucumis melo 'Gama Melon Parfum' (GMP) is a member of the Cucurbitaceae family. Unlike melons in general, GMP melons have a bitter taste. The taste is caused by the high Cucurbitacin content. These compounds are known as anti-cancer. This study aims to identify Cucurbitacin in GMP melons and determine their effects on T47D and MCF7 breast cancer cells. GMP melon fruit medium phase (20DAA) was macerated by methanol and continued by fractionation with chloroform. Cucurbitacin B compounds in the chloroform fraction were identified using HPLC. A cell cytotoxicity test was carried out using an MTT assay with five concentration variations of the chloroform fraction. They were 7.8125, 15,625, 31.25, 62.5, and 125μg/ml. The apoptosis test was carried out using the flow cytometry method with five concentration variations of the chloroform fraction. They were 1, ½, ¼, 1/10, and 1/100 IC50. The results showed that Cucurbitacin B was found in the chloroform fraction with a concentration of 15.69 μg/mL per 1 mg of the chloroform fraction. The IC50 values of T47D and MCF7 cells, respectively, were 98 and 10 μg/ml. The apoptotic test on MCF7 cells showed that at a concentration of 1/100 IC50, the chloroform fraction was able to induce cells to undergo apoptosis.
Survey of Simulation Tools to Assess Techno-Economic Benefits of Smart Grid Technology in Integrated T&D Systems

In order to succeed in the energy transition, the power system must become more flexible in order to enable the economical hosting of more intermittent distributed energy resources (DER) and smart grid technologies. New technical solutions, generally based on the connection of various components coupled to the power system via smart power electronic converters or through ICT, can help to take up these challenges. Such innovations (e.g., decarbonization technologies and smart grids) may reduce the costs of future power systems and the environmental footprint. In this regard, the techno-economic assessment of smart grid technologies is a matter of interest, especially in the urge to develop more credible options for deep decarbonization pathways over the long term. This work presents a literature survey of existing simulation tools to assess the techno-economic benefits of smart grid technologies in integrated T&D systems. We include the state-of-the-art tools and categorize them in their multiple aspects, cover smart grid technology, approach methods, and research topics, and include (or complete) the analysis with other dimensions (smart-grid related) of key interest for future power systems analysis such as environmental considerations, techno-economic aspects (social welfare), spatial scope, time resolution (granularity), and temporal scope, among others. We surveyed more than 40 publications, and 36 approaches were identified for the analysis of integrated T&D systems. As a relatively new research area, there are various promising candidates to properly simulate integrated T&D systems. Nevertheless, there is not yet a consensus on a specific framework that should be adopted by researchers in academia and industry. Moreover, as the power system is evolving rapidly towards a smart grid system, novel technologies and flexibility solutions are still under study to be integrated on a large scale. This review aims to offer new criteria for researchers in terms of smart-grid related dimensions and the state-of-the-art trending of simulation tools that holistically evaluate techno-economic aspects of the future power systems in an integrated T&D systems environment. As an imperative research matter for future energy systems, this article seeks to contribute to the discussion of which pathway the scientific community should focus on for a successful shift towards decarbonized energy systems.
Signing up is not yet mindfulness practice: A systematic review of adherence to eHealth and mHealth mindfulness-based programs in the pre-pandemic period

Informační a komunikační technologie představují nové a slibné kanály, jak lze k uživatelům doručit intervence založené na Mindfulness přístupu. Běžným problémem v této oblasti aplikovaného výzkumu je nedostatek evidence o adherenci ke zmíněným programům. Aktuální článek ve formě systematické review podle PRISMA protokolu shrnuje informace o tom, jaká je adherence k intervencím ve studiích zabývajících se eHealth Mindfulness programy, jak je adherence měřena a co jsou její možné prediktory. V databázích PubMed, Web of Science, Medline, Scopus a PsychlNFO bylo do konce roku 2019 identifikováno 3104 potenciálně relevantních článků. Vzhledem k očekávanému nárůstu implementace eHealth programů na podporu duševního zdraví pro zdravou i klinickou populaci v důsledku pandemie SARS-CoV-2, se stávající review zabývala jen studiemi před začátkem pandemie. 69 z nich splnilo všechna vstupní kritéria pro systematickou review. 61 % studií ve svých výsledcích prezentovalo různé parametry adherence, 36 % pak prezentovalo základní tzv. adherence rate. Míra adherence v klinických populacích se pohybovala od 41 % do 92 %;v neklinických populacích se pohybovala od 1 % do 85 %. Prediktory adherence byly zkoumány ve 48 % studií, většina hodnocených proměnných však přinesla značně heterogenní výsledky. Velká heterogenita byla pozorována také v samotné definici adherence a ve způsobech a nástrojích jejího měření. Aktuální systematická review jednoznačně dokládá potřebu standardizovaného systému měření adherence a dalšího výzkumu v oblasti jejích prediktorů. Alternate :Information and communication technology are promising channels in delivering the mindfulness-based intervention. A common problem in these interventions is the lack of study of treatment adherence. The current article summarizes the state of measuring and reporting adherence, the rate of adherence, and possible predictors of adherence in the form of a systematic review following the PRISMA statement. A database search of PubMed, Web of Science, Medline, Scopus, and PsychINFO identified 3104 potentially relevant articles published up to the end of December 2019. The review focuses only on the SARS-CoV-2 pre-pandemic time because the accelerated development of the eHealth Mindfulness-based interventions and a vast amount of newly published interventions in the following years was expected. A total of 69 studies met all the eligibility criteria. Out of these studies, 61% reported some measure of adherence and 36% reported the adherence rate. The adherence rate in clinical populations ranged from 41% to 92%;in non-clinical populations, it ranged from 1% to 85%. Predictors of adherence were investigated in 48% of the studies;however, the majority of assessed variables had mixed findings about predicting adherence. There was a huge variety in the definitions and measurements of adherence. A standardized system of measuring and reporting adherence and further investigation of its predictors is needed.
Special Issue on Advanced Mechanical Modeling of Nanomaterials and Nanostructures

The increased requirements in design and manufacturing nanotechnology have favored the development of enhanced composite materials with tailored properties, such as functionally graded (FG) and carbon-based materials, primarily carbon nanotubes (CNTs), and graphene sheets or nanoplatelets, because of their remarkable mechanical properties, electrical conductivity, and high permeability [. ].
Deciphering of Pod Borer [Helicoverpa armigera (Hübner)] Resistance in Cajanus platycarpus (Benth.) Offers Novel Insights on the Reprogramming and Role of Flavonoid Biosynthesis Pathway

Management of pod borer, Helicoverpa armigera in pigeonpea (Cajanus cajan L.), an important legume crop, has been a pertinent endeavor globally. As with other crops, wild relatives of pigeonpea are bestowed with various resistance traits that include the ability to deter the H. armigera. Understanding the molecular basis of pod borer resistance could provide useful leads for the management of this notorious herbivore. Earlier studies by our group in deciphering the resistance response to herbivory through multiomics approaches in the pigeonpea wild relative, Cajanus platycarpus, divulged the involvement of the flavonoid biosynthesis pathway, speculating an active chemical response of the wild relative to herbivory. The present study is a deeper understanding of the chemical basis of pod borer (H. armigera) resistance in, C. platycarpus, with focus on the flavonoid biosynthesis pathway. To substantiate, quantification of transcripts in H. armigera-challenged C. platycarpus (8 h, 24 h, 48 h, 96 h) showed dynamic upregulation (up to 11-fold) of pivotal pathway genes such as chalcone synthase, dihydroflavonol-4-reductase, flavonoid-3′5′-hydroxylase, flavonol synthase, leucoanthocyanidin reductase, and anthocyanidin synthase. Targeted LC-MS analyses demonstrated a concomitant increase (up to 4-fold) in naringenin, kaempferol, quercetin, delphinidin, cyanidin, epigallocatechin, and epicatechin-3-gallate. Interestingly, H. armigera diet overlaid with the over-produced flavonoids (100 ppm) showed deleterious effects on growth leading to a prolonged larval period demonstrating noteworthy coherence between over-accumulation of pathway transcripts/metabolites. The study depicts novel evidence for the directed metabolic reprogramming of the flavonoid biosynthesis pathway in the wild relative to pod borer; plant metabolic potential is worth exploiting for pest management.
Chinese Herbal Formula Huayu-Qiangshen-Tongbi Decoction Attenuates Rheumatoid Arthritis through Upregulating miR-125b to Suppress NF-κB-Induced Inflammation by Targeting CK2

The Huayu-Qiangshen-Tongbi (HQT) decoction, a Chinese medical formula, has been identified to show a potent therapeutic effect on rheumatoid arthritis (RA). However, the specific molecular mechanism of HQT in RA has not been well studied. In the present study, LPS-treated human rheumatoid fibroblast-like synoviocyte (FLS) MH7A cells and collagen-induced arthritis (CIA) mice were utilized as in vitro and in vivo models. Our results demonstrated that HQT could efficiently inhibit RA-induced inflammation by reducing the production of cytokines including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6). Moreover, HQT significantly upregulated the expression of miR-125b. Besides, analysis of bioinformatics suggested casein kinase 2 (CK2) was a potential target of miR-125b. Luciferase reporter assay was performed and revealed that miR-125b suppressed CK2 expression in MH7A cells. Furthermore, miR-125b inhibited LPS-induced NF-kappa-B (NF-κB) activation, which is a downstream target of CK2. In addition, the NF-κB inhibitor ammonium pyrrolidinedithiocarbamate (PDTC) and NF-kappa-B inhibitor alpha (IkB-α) enhanced the inhibitory effect of miR-125b on the expression of TNF-α, IL-1β, and IL-6. Taken together, our study revealed that HQT could attenuate RA through upregulating miR-125b to suppress NF-κB-induced inflammation by targeting CK2. The findings of this study should facilitate investigating the mechanism of HQT on RA and discovering novel therapeutic targets for RA.
Diagnosis and Management of Acanthamoeba Keratitis: A Continental Approach

Acanthamoeba keratitis (AK) is a potentially blinding infection caused by protozoa found worldwide. The topical application of biguanides and diamidines is the most common anti-amoebic treatment for AK. In this study, we hypothesized that geographical location and socioeconomic status influence the management and treatment of AK. To test this hypothesis, we analyzed case reports and series of Acanthamoeba eye infections from different geographic regions to evaluate the association between diagnosis, treatment, and outcome worldwide. This study looked specifically at case reports of patients with diagnosed AK using bibliographic databases such as PubMed, BioMed Central, and Google Scholar, which were searched between 30 April 1990 and 1 May 2022. The search identified 38 eligible studies that provided data for 60 clinical cases of AK. The results indicated that current standard treatments are effective if the infection is identified early and that delays can lead to clinical symptoms, including permanent visual opacities. There was evidence suggesting an association between the treatment regimen practiced in certain geographic regions and treatment outcome. Patient access to medical facilities and economic background also had an influence on the treatment and outcome of AK. Further analysis of more case reports can expand our understanding of the influence of specific demographic and individual patient characteristics on the effectiveness and accessibility of AK medicines. Additionally, using a living systematic review approach to incorporate emerging evidence will reveal the relative merits of different treatment regimens for AK and outcomes.