Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Horticultural Therapy on Korean Elderly with Dementia: A Meta-analysis

Purpose: The aim of this meta-analysis was to identify the effects of horticultural therapy on Korean elderly with dementia.Methods: We searched the PubMed, EMBASE, Cochrane, CINAHL, and eight domestic databases, until February 2021. Data extraction and the risk of bias assessment were independently conducted by two authors. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated using a random-effects meta-analysis.Results: Of the 478 studies retrieved from the databases, 21 studies were included in the final analysis. A total of 93 outcome variables were analyzed in 21 literatures. The overall effect size of the horticultural treatment program was 0.91 (95% CI: 0.74~1.09, p<.001), which was statistically significant. Compared to the control group, horticultural therapy improved cognitive functions (SMD=0.71, 95% CI: 0.42~0.99, I2=79.9%), psychosocial functions (SMD=1.01, 95% CI: -0.70~1.31, I2=67.8%), and physical functions (SMD=1.05, 95% CI: 0.77~1.33, I2=72%) in Korean elderly with dementia.Conclusion: This meta-analysis found that horticultural therapy improved the cognitive, psychosocial, and physical functions of dementia patients compared to subjects in the control group.
Two-Stage Segmentation Framework Based on Distance Transformation

With the rise of deep learning, using deep learning to segment lesions and assist in diagnosis has become an effective means to promote clinical medical analysis. However, the partial volume effect of organ tissues leads to unclear and blurred edges of ROI in medical images, making it challenging to achieve high-accuracy segmentation of lesions or organs. In this paper, we assume that the distance map obtained by performing distance transformation on the ROI edge can be used as a weight map to make the network pay more attention to the learning of the ROI edge region. To this end, we design a novel framework to flexibly embed the distance map into the two-stage network to improve left atrium MRI segmentation performance. Furthermore, a series of distance map generation methods are proposed and studied to reasonably explore how to express the weight of assisting network learning. We conduct thorough experiments to verify the effectiveness of the proposed segmentation framework, and experimental results demonstrate that our hypothesis is feasible.
Developing an Efficient Business Strategy in the Era of Digital Transformation

As contemporary business is experiencing digital transformation, the role of a viable strategy is becoming crucial for any company. There are different essential aspects to be focused on when developing a digital business strategy: primarily, enhanced scope of business operations as well as application of latest IT solutions to make this strategy a “scaling-up” long-term plan intended for sustaining the company’s performance and contributing to the accomplishment of the Sustainable Development Goals (SDGs). Creating and implementing a digital business strategy that is based on the company’s specific objectives involves utilizing new approaches and designing novel business models based on the application of up-to-date IT solutions (i.e. increasing business digital capability). An efficient business strategy developed in the era of digital transformation is aimed at building a competitive advantage in the international market of products and services in the global agenda of achieving Sustainable Development Goals, the SDGs facilitating the alignment of the strategy with the needs of modern society. The purpose of the paper is to examine some original strategic initiatives defined and prioritized in the digital business strategy of a successful company. In the paper, the use of innovative (sustainability-related) strategic initiatives is demonstrated with a real-life example – Amazon’s business strategy. The research conducted in the paper is supposed to provide some insights on the development of an efficient business strategy of a multi-business company in the age of digital transformation.
Comparative Analysis of the Transcriptomes of Persisting and Abscised Fruitlets: Insights into Plant Hormone and Carbohydrate Metabolism Regulated Self-Thinning of Pecan Fruitlets during the Early Stage

Pecan is one of the most popular nut species in the world. The fruit drop rate of the pecan ‘Pawnee’ is more than 57%, with four fruit drop stages, which is very serious. In this study, we conducted transcriptomic profiling of persisting and abscised fruitlets in early fruit development by RNA-seq. A total of 11,976 differentially expressed genes (DEGs) were identified, 3012 upregulated and 8964 downregulated, in a comparison of abscised vs. persisting fruitlets at 35 days after anthesis (DAA). Our transcriptomic data suggest that gene subsets encoding elements involving the biosynthesis, metabolism, perception, signal transduction, and crosstalk of the plant hormones abscisic acid (ABA), auxin, cytokinin, ethylene, and gibberellin (GA) and plant growth regulators jasmonates, salicylic acid, and brassinosteroids were differentially expressed. In addition, the majority of transcriptionally activated genes involved in hormone signaling (except for ethylene and salicylic acid signaling) were downregulated in abscised fruitlets. The differential expression of transcripts coding for enzymes involved in sucrose, glucose, trehalose, starch, galactose, and galactinol metabolism shows that sucrose, galactinol, and glucose synthesis and starch content were reduced as starch biosynthesis was blocked, and retrogradation and degradation intensified. These results suggest that the abscised pecan fruitlets stopped growing and developing for some time before dropping, further indicating that their sugar supply was reduced or stopped. The transcriptome characterization described in this paper contributes to unravelling the molecular mechanisms and pathways involved in the physiological abscission of pecan fruits.
Design and Analysis of a Novel Double-Stator Double-Rotor Motor Drive System for In-Wheel Direct Drive of Electric Vehicles

In-wheel direct drive (IWDD) of electric vehicles (EVs), which simplifies the transmission system and facilitates flexible control of vehicle dynamics, has evolved considerably in the EV sector. This paper proposes a novel double-stator double-rotor motor (DSDRM) with a bidirectional flux modulation effect for in-wheel direct drive of EVs. With the proposed special design, a synthetic-slot structure with synthetic materials containing copper and permanent magnets (PMs) in the slots of the motor is ingeniously employed, and the outer and inner rotors are mechanically connected together as a single rotor, making its mechanical structure less complicated than those of two-rotor machines. The main work of this paper involves the design, analysis, construction, and testing of the proposed machine. The DSDRM with a synthetic-slot structure was demonstrated to be feasible by finite element analysis (FEA), prototype fabrication, and experimental results. In addition, vehicle layout with DSDRM is presented and verified by the vehicle road test experiment. Thus, the DSDRM with the synthetic-slot structure can be used as a hub motor for in-wheel direct drive of EVs.
Research on current decoupling control of six‐phase permanent magnet linear synchronous motor for electromagnetic launch

Six‐phase permanent magnet linear synchronous motor (PMLSM) for electromagnetic launch (EML) system presents the characteristics of a high order, nonlinearity, multivariable, strong coupling, and nonperiodic transient operation in the synchronous rotating coordinate system, posing a great challenge to the dynamic response ability of the current loop. Existing research on current decoupling control (CDC) mainly focuses on cross decoupling within a three‐phase system, even though there are neither decoupling methods for multiphase systems nor effective evaluation criteria for the decoupling and dynamic response performances. From this perspective, this paper first presents an equivalent reduced‐order complex‐matrix dynamic mathematical model of six‐phase PMLSM and analyze its transient coupling characteristics during the process of EML. Then, the CDC methods of six‐phase PMLSM based on direct compensation and matrix diagonalization principles are realized, respectively, to accomplish the cross decoupling and back electromotive force decoupling within and between different three‐phase windings. Finally, an all‐round method is proposed, for the first time, to evaluate the decoupling performances and dynamic response performances of different CDC strategies for six‐phase PMLSM. Significant superiority of deviation decoupling regulator in decoupling performance and robustness are verified based on high‐speed EML experimental platform of six‐phase PMLSM.
A Multiple Degree of Freedom Actuator using a single vibrating transducer

Multiple degree of freedom actuation typically requires one actuator for each degree of freedom, where each actuator requires its own heavy and expensive transducer to transform an electrical input signal into a useful mechanical output. Mechanisms can be used to split the output of a single motor, but the resulting systems are often complex, large, heavy, and noisy. Some also lack true independence of outputs. This thesis develops and demonstrates a novel system for multiple degree of freedom actuation using a single transducer to achieve independent, bi-directional control of multiple degrees of freedom. The resulting system is mechanically simple, compact, lightweight, easy to control, and potentially inexpensive. The Multiple Degree of freedom Actuator (MDA) comprises i) a single vibrating transducer and ii) a parallel network of resonators. Each resonator is tuned to its own unique resonant frequency and drives its own degree of freedom. First, it is shown that the MDA can actuate independently multiple degrees of freedom with a single transducer by selectively exciting the resonant frequencies of one or more resonators, which then drive their respective degrees of freedom. Both numerical simulation and physical prototypes are used to verify the results. Second, a simple, compact resonator/rectifier mechanism is developed and fabricated using flexures that convert oscillating motion of a resonator to useful, continuous, bi-directional rotation of an output rotor without crosstalk between outputs. Third, the theoretical efficiency of the MDA, driven by an electromagnetic transducer, is derived. An efficient, low-moving-mass moving magnet transducer is developed and shown to greatly improve theoretical system efficiency. Finally, a hypocycloid speed reducer mechanism is developed and fabricated to achieve a very high reduction ratio in a compact package with greater simplicity and improved performance. Thesis Supervisor: David R. Wallace Title: Professor
Research on the Influencing Factors of the Willingness to Use Information Systems at universities

Based on the theory and model of information technology adoption, this paper proposes a model of influencing factors on the willingness to use information systems at universities. Researchers use a questionnaire to test the model by analyzing the data of questionnaire results. From these results, influencing factors of success for university management information systems in the application process is summarized. The researchers offer suggestions for implementing such a system based on the findings.
Modeling HMM Map Matching Using Multi-label Classification

Map matching deals with matching GPS coordinates to corresponding points or segments on a road network map. The work has various applications in both vehicle navigating and tracking domains. Traditional rule-based approach for solving the Map matching problem yielded great matching results. However, its performance depends on the underlying algorithm and Mathematical/Statistical models employed in the approach. For example, HMM Map Matching yielded O(N2) time complexity, where N is the number of states in the underlying Hidden Markov Model. Map matching techniques with large order of time complexity are impractical for providing services, especially within time-sensitive applications. This is due to their slow responsiveness and the critical amount of computing power required to obtain the results. This paper proposed a novel data-driven approach for projecting GPS trajectory onto a road network. We constructed a supervised-learning classifier using the Multi-Label Classification (MLC) technique and HMM Map Matching results. Analytically, our approach yields O(N) time complexity, suggesting that the approach has a better running performance when applied to the Map matching-based applications in which the response time is the major concern. In addition, our experimental results indicated that we could achieve Jaccard Similarity index of 0.30 and Overlap Coefficient of 0.70.
Identification of rare coding variants associated with Kawasaki disease by whole exome sequencing

Kawasaki disease (KD) is an acute pediatric vasculitis that affects genetically susceptible infants and children. To identify coding variants that influence susceptibility to KD, we conducted whole exome sequencing of 159 patients with KD and 902 controls, and performed a replication study in an independent 586 cases and 732 controls. We identified five rare coding variants in five genes (FCRLA, PTGER4, IL17F, CARD11, and SIGLEC10) associated with KD (odds ratio [OR], 1.18 to 4.41; p = 0.0027–0.031). We also performed association analysis in 26 KD patients with coronary artery aneurysms (CAAs; diameter > 5 mm) and 124 patients without CAAs (diameter < 3 mm), and identified another five rare coding variants in five genes (FGFR4, IL31RA, FNDC1, MMP8, and FOXN1), which may be associated with CAA (OR, 3.89 to 37.3; p = 0.0058–0.0261). These results provide insights into new candidate genes and genetic variants potentially involved in the development of KD and CAA.
A Mortality Case Caused by Thrombotic Microangiopathy after Successful Bloodless Living Donor Liver Transplantation

Thrombotic microangiopathy (TMA) after solid organ transplantation is infrequent and its etiology remains still unclear. Nevertheless, if early diagnosis and early therapies are not performed, it can lead to severe life-threatening complications and even death. A 54-year-old female (a Jehovah’s Witness) was diagnosed with drug-induced toxic hepatitis and was decided to undergo bloodless living donor liver transplantation (LDLT). After the successful LDLT, the patient’s condition deteriorated, and she was diagnosed with TMA during further evaluation. We tried to proceed with plasma exchange-based treatment, but she and her family declined according to their religious beliefs. The patient expired 4 days after the diagnosis. Physicians should maintain a high level of suspicion for TMA after liver transplantation when clinical manifestations are observed.
A Statistical Loom to Upgrading Dynamic Packet Failure Determination

Determination and inference of packet failure features are exigent due to the moderately unusual occurrence and typically short duration of packet failure episodes. The intention of our study is to understand how to determine packet failure episodes accurately with endto-end probes. We start by taxing the ability of standard Poisson-modulated end-to-end determinations of failure in a prohibited laboratory environment using IP routers and service end hosts. Our tests show that failure characteristics reported from such Poissonmodulated probe tools can be pretty erroneous over a series of traffic conditions. Aggravated by these annotations Specifically, our method entails probe tests that follow a statistical allocation to 1) permit a precise trade-off between accuracy and force on the network, and 2) permit more accurate determinations than normal Poisson probing at the same rate. We appraise the capabilities of our slant testually by mounting and implementing a prototype tool, called VOILA. The tests express the trade-offs between force on the network and determination accuracy. We show that VOILA hearsay failure characteristics far more accurately than conventional failure determination tools. Key Terms--Dynamic Determination, VOILA, network congestion, network probes, packet failure.
A Novel Active Power Line Conditioners using PLL Synchronization and PI controller

this paper presents Shunt Active Power Line Conditioners (APLC) for compensating reactive power and harmonic currents drawn by the loads besides power factor correction. The shunt APLC is implemented with three phase PWM current controlled voltage source inverter and is connected to the point of common coupling for compensating the current harmonics. The compensation process is based on phase locked loop (PLL) synchronization and proportional integral (PI) controller. These control strategy for shunt APLC makes certain that source current is sinusoidal even when the load is non- sinusoidal and unbalanced. The PWM-VSI inverter switching is done according to gating signals derived from hysteresis current controller and the capacitor voltage is maintained constant using PI controller. The proposed shunt APLC is investigated using extensive simulation and is found to be effective in terms of THD, active filtering, reactive power compensation and VDC settling time under both transient and steady state conditions.
Formulation Development, Characterization and Antifungal Evaluation of Chitosan NPs for Topical Delivery of Voriconazole In Vitro and Ex Vivo

This study aims to develop chitosan-based voriconazole nanoparticles (NPs) using spray-drying technique. The effect of surfactants and polymers on the physicochemical properties, in vitro release, and permeation of NPs was investigated. The prepared NPs containing various surfactants and polymers (e.g., Tween 20 (T20), Tween 80 (T80), sodium lauryl sulfate (SLS), propylene glycol (PG), and Polyethylene glycol-4000 (PEG-4000)) were physiochemically evaluated for size, zeta potential, drug content, percent entrapment efficiency, in vitro release, and permeation across rats’ skin. A Franz diffusion cell was used for evaluating the in vitro release and permeation profile. The voriconazole-loaded NPs were investigated for antifungal activity against Candida albicans (C. albicans). The prepared NPs were in the nano range (i.e., 160–500 nm) and positively charged. Images taken by a scanning electron microscope showed that all prepared NPs were spherical and smooth. The drug content of NPs ranged from 75% to 90%. Nanoparticle formulations exhibited a good in vitro release profile and transport voriconazole across the rat’s skin in a slow control release manner. The NPs containing SLS, T80, and PG exhibited the best penetration and skin retention profile. In addition, the formulation exhibited a potential antifungal effect against C. albicans. It was concluded that the development of chitosan NPs has a great potential for the topical delivery of voriconazole against fungal infection.
Synthetic Aircraft Trajectories Generated with Multivariate Density Models

Aircraft trajectory generation is a high stakes problem with a wide scope of applications, including collision risk estimation, capacity management and airspace design. Most generation methods focus on optimizing a criterion under constraints to find an optimal path, or on predicting aircraft trajectories. Nevertheless, little in the way of contribution has been made in the field of the artificial generation of random sets of trajectories. This work proposes a new approach to model two-dimensional flows in order to build realistic artificial flight paths. The method has the advantage of being highly intuitive and explainable. Experiments were conducted on go-arounds at Zurich Airport, and the quality of the generated trajectories was evaluated with respect their shape and statistical distribution. The last part of the study explores strategies to extend the work to non-regularly shaped trajectories.
Gain Enhancement of Double-Slot Vivaldi Antenna using Corrugated Edges and Semicircle Director for Microwave Imaging Application

Microwave imaging, such as images for radiological inspection in the medical profession, is one of the applications utilized in ultra-wideband (UWB) frequency ranges. The Vivaldi antenna is one of the most popular antennas for this purpose. The antenna is utilized because of its simple, lightweight, and compact design, as well as its excellent efficiency and gain capabilities. In this work, we present a high-gain Vivaldi antenna for microwave imaging applications. The proposed Vivaldi antenna is designed using a double-slot structure method with the addition of corrugated edges and a semicircle director aimed at improving the gain. The antenna is designed to operate at frequencies ranging from 3.1 to 10.6 GHz. Based on the modeling findings, the suggested antenna attain a bandwidth of 7.5 GHz with operating frequencies from 3.1 GHz to 10.6 GHz for a VSWR of less than two. In comparison to a typical single slot antenna, the suggested antenna provides a substantial boost in gain performance. The increase in gain is proportional to the frequency of operation. The constructed antenna has a lower bandwidth than the simulated one, with operating frequencies of 3.5 GHz – 3.75 GHz and 4.25 – 10.89 GHz, respectively, and useable bandwidths of 250 MHz and 6.64 GHz. All these results suggest that the antenna is suitable for microwave imaging applications.
Simulation and Genetic Algorithms for Optimizing Comminution Circuit at Gol-e-Gohar Iron Plant (RESEARCH NOTE)

simulation optimization is a scientific tool that is widely used to design and optimize comminution circuits in mineral processing plants. In this research, first of all, in order to determine the suitable d80 for cicuit hydrocyclone underflow, the requiremed parameters of simulator (residence time distribution, breakage function, selection function and Plitt’s model calibration) were determined. Then simulation of comminution circuit by presentation of BMCS software under MATLAB environment was performed. In the end, the GA toolbox of MATLAB software was used for optimization of the comminution circuit, by determining the simulator as fitness function. The results from this research showed that, by determining the optimum value of input parameters (solid perecent, fresh feed and water rate to the input streams), the genetic algorithm is able to achieve a suitable d80 for circuit cuf (cyclon underflow).
PENGARUH KUALITAS PELAYANAN, E-SYSTEM PERPAJAKAN, DAN SOSIALISASI PERPAJAKAN TERHADAP KEPUASAN WAJIB PAJAK

Taxes are the main source of state revenue, tax revenues are collected from the people and for the benefit of the people. The Directorate General of Taxes has made various efforts to increase tax revenue through services provided to taxpayers. This study aims to analyze the effect of service quality, taxation esystem, and tax socialization on taxpayer satisfaction at the West Sidoarjo Primary Tax Service Office. This type of research is quantitative research. The sampling technique in this study was calculated based on accidental sampling technique with a sample size of 40 respondents. The results of this study indicate that simultaneously and partially service quality, taxation e-system, and tax socialization have an effect the taxpayer satisfaction at the West Sidoarjo Primary Tax Service Office.Keywords: Service Quality, Taxation E-System, Taxpayer Satisfaction, Tax Socialization