Miracle-dz/UniFAR-FTUs huggingface dataset:
Technopreneurship-Based Competitiveness and Innovation at Small Business in Gorontalo City

Business today has been globalized. This has made business even more competitive. Companies, regardless of their size, have to improve their competitiveness. Sustainable competitiveness is the core need for innovation. This study aims at exploring the correlation between IT-based innovation or technopreneurship and business competitiveness. This was a quantitative study with survey method. The respondents in this study were small business owners in handicraft and creative content production in Gorontalo city. The data were collected by online form and after three month collecting data, data were collected were 163 respondents. Product, process and organizational innovation and business competitiveness instruments use instruments from previous research. All instruments use a Likert scale with points 1 to 5 which indicate a scale of disagreement to agreement from the respondents. The data were analyzed using PLS-SEM. The Results show that information technology-based product innovation, IT based process innovation, and IT organizational innovation significantly and positively influence the growth of business competitiveness. Product innovation of business owners in Gorontalo city, Indonesia is actively producing new products. Also, innovation is not only limited to product innovation but also production process innovation, which uses information technology. Utilization of technopreneurship is significantly able to increase business competitiveness, especially for small businesses in Gorontalo city. Utilization of innovation in information technology assumed to strongly develop business competitiveness. The business competitiveness of small businesses in the high-tech field is influenced by products, processes and organizational innovation. SMEs must be able to create products, or product segments, and services that exceed the performance limitations of traditional products by utilizing everything possible through digital models.
Adult-onset Leukoencephalopathy with Axonal Spheroids and Pigmented Glia (ALSP) Masquerading Primary Progressive Aphasia

Adult‐onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) is a rare autosomal dominant neurodegenerative disease resulting from heterozygous mutations in the colony‐stimulating factor 1 receptor gene. [1] ALSP is a challenging diagnosis in the absence of pathological or genetic confirmation because of its varied clinical presentation and imaging features. We report a case of ALSP in a 54‐year‐old lady presenting with predominant language disturbance in the form of logopenic variant of primary progressive aphasia (LvPPA) with no similar family history. Magnetic resonance imaging (MRI) brain showed frontoparietal predominant periventricular and corpus callosum signal changes with diffusion restrictions suggestive of leukodystrophy where eventually genetic testing aided in the final diagnosis.
Novel Approach to Fault-Tolerant Control of Inter-Turn Short Circuits in Permanent Magnet Synchronous Motors for UAV Propellers

This paper deals with the development of a novel fault-tolerant control technique aiming at the diagnosis and accommodation of inter-turn short circuit faults in permanent magnet synchronous motors for lightweight UAV propulsion. The reference motor is driven by a four-leg converter, which can be reconfigured in case of a phase fault by enabling the control of the central point of the motor Y-connection. A crucial design point entails the development of fault detection and isolation (FDI) algorithms capable of minimizing the failure transients and avoiding the short circuit extension. The proposed fault-tolerant control is composed of two sections: the first one applies a novel FDI algorithm for short circuit faults based on the trajectory tracking of the motor current phasor in the Clarke plane; the second one implements the fault accommodation, by applying a reference frame transformation technique to the post-fault commands. The control effectiveness is assessed via nonlinear simulations by characterizing the FDI latency and the post-fault performances. The proposed technique demonstrates excellent potentialities: the FDI algorithm simultaneously detects and isolates the considered faults, even with very limited extensions, during both stationary and unsteady operating conditions. In addition, the proposed accommodation technique is very effective in minimizing the post-fault torque ripples.
Dietary Habits, Physical Activity and Sleep Pattern Among In-School Adolescents in Lagos, Nigeria

Background: Overnutrition has been documented at epidemic levels in children and adults. The associated risk factors may include poor dietary habits, sedentary behaviour, inadequate sleep and low parental education. Objective: To describe dietary habits, physical activity and sleep patterns among secondary school adolescents. Methods: A cross-sectional study of 1,120 adolescents recruited from public and private secondary schools in Lagos, Nigeria, was carried out to study the dietary habits, sleep patterns and physical activity in relation to nutritional status. Results: Ten per cent of the adolescents skipped breakfast, while 28% had fruits on up to five days of the week. Eleven per cent had a sweetened drink every day, while 20 % had a sweetened drink on most days of the week. One out of four (26%) adolescents had more than two hours of screen time daily, and only 5% engaged in sporting activities up to five times weekly. One-third of the students slept for less than six hours daily and experienced sleeping difficulties. Multivariate analysis showed that females were twice as likely not to participate in sports (OR = 2.38, CI = 1.3-4.37, p = 0.002 and to have a higher intake of confectionaries (OR = 1.47, CI = 1.07-2.04, p = 0.01. Conclusion: Poor dietary habits, inadequate physical activity and insufficient sleep were observed among secondary school adolescents. A multi-pronged approach to improve these behaviours is recommended.
Utilization Strategy of User Engagements in Korean Fake News Detection

Fake News (disinformation with malicious intent) has emerged as a major social problem. To address this issue, previous studies mainly utilized single information, the news content, to detect fake news. However, using only news content in training is insufficient. Moreover, most studies did not consider the propagation aspect of fake news as a training feature. Thus, in an attempt to incorporate the ability to learn representation based on textual information and social context, this study proposed a fake news detection algorithm that thoroughly utilizes user graph in Korean fake news and dataset construction methods. In addition, a training strategy was proposed for utilizing user graph in Korean fake news detection through comparative and ablation studies. The experimental results showed that K-FANG outperformed the baseline in detecting fake news. Moreover, user engagements were found to be useful for detecting fake news even if the data contained hate speech. Finally, the validity of using stance information by expanding its class and controlling the class imbalance issues was also verified. This study provided useful implications for utilizing user information in fake news detection.
First report of canine morbillivirus infection of adipose tissue-derived stem cells from dogs with distemper

Background and Aim: Ribonucleic acid viruses remain latent in different cell types, including mesenchymal stem cells; however, the distemper virus remains undetected in these cells. This study aimed to determine whether adipose stem cells (ASCs) from dogs with distemper disease are infected with the canine morbillivirus (CM). Materials and Methods: Twelve dogs with the neurological phase of the disease and who were positive for CM by reverse transcription polymerase chain reaction (RT-PCR), were studied. ASCs from adipose tissue of the lesser omentum of these infected dogs were isolated and characterized. Direct fluorescence was used to detect the viral antigen in cell cultures. Flow cytometry and RT-PCR identified detectable quantities of the virus in two cultures, while electron microscopy confirmed the CM particles within ASCs. Results: This study revealed that ASCs of the omentum of dogs with distemper disease can be infected with CM, indicating their possible involvement in this virus latency and persistence. This suggests that its detection should be considered within the quality control process of stem cells intended for regenerative medicine. Conclusion: To the best of our knowledge, this is the first study that demonstrates that omentum ASCs from dogs with distemper disease can be infected with CM and may be involved in viral latency or persistence. Our study also suggests that the detection of CM should be considered within the quality control process of stem cells intended for regenerative medicine.
A search for signatures of dark matter in the AMS-01 electron and antiproton spectrum

If dark matter consists of Weakly Interacting Massive Particles (WIMPs), such as the supersymmetric neutralino, various theories predict that their annihilation in the galaxy can give rise to anomalous features in the otherwise smooth spectra of charged cosmic rays. Up to now searches for these spectral anomalies have focused largely on antiparticles (p, e+ ) due to their lower astrophysical backgrounds. In this thesis we present results of a search for dark matter annihilation in the charge Z = -1 spectrum of AMS01 (essentially electrons and antiprotons). To avoid model dependent complications we assume that the primary annihilation channel is through W+W production. We use the galactic propagation software GALPROP to determine the dark matter spectra at Earth from a smooth isothermal source. Fits to the data did not reveal any contribution from dark matter and limits were placed on the rate of W+Wproduction in the galaxy and on the corresponding cross-section for WIMP annihilation through the W+W channel (given a smooth isothermal distribution). Thesis Supervisor: Peter Fisher Title: Professor Thesis Supervisor: Kate Scholberg Title: Assistant Professor
The Effect of Long-Term Menstrual Pain on Large-Scale Brain Network in Primary Dysmenorrhea Patients

Purpose Primary dysmenorrhea (PD) is a common gynecological disease, characterized by crampy and suprapubic pain occurring with menses. Growing evidences demonstrated that PD patients were associated with abnormalities in brain function and structure. However, little is known regarding whether the large-scale brain network changes in PD patients. The purpose of this study was to investigate the effect of long-term menstrual pain on large-scale brain network in PD patients using independent component analysis (ICA) method. Methods Twenty-eight PD patients (female, mean age, 24.25±1.00 years) and twenty-eight healthy controls (HCs) (mean age, 24.46±1.31 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the resting-state networks (RSNs) in two groups. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within RSNs and interactions among RSNs between two groups. Results Compared to the HC group, PD patients showed significant increased intra-network FCs within the auditory network (AN), sensorimotor network (SMN), right executive control network (RECN). However, PD patients showed significant decreased intra-network FCs within ventral default mode network (vDMN) and salience network (SN). Moreover, FNC analysis showed increased VN-AN and decreased VN-SMN functional connectivity between two groups. Conclusion Our study highlighted that PD patients had abnormal brain networks related to auditory, sensorimotor and higher cognitive network. Our results offer important insights into the altered large-scale brain network neural mechanisms of pain in PD patients.
Estimating Long Memory Causality Relationships by a Wavelet Method

The traditional causality relationship proposed by Granger (1969) assumes the relationships between variables are short range dependent with the same integrated order. Chen (2006) proposed a bi-variate model which can catch the long-range dependent among the two variables and the series do not need to be fractionally co-integrated. A long memory fractional transfer function is introduced to catch the long-range dependent in this model and a pseudo spectrum based method is proposed to estimate the long memory parameter in the bi-variate causality model. In recent years, a wavelet domain-based method has gained popularity in estimations of long memory parameter in unit series. No extension to bi-series or multi-series has been made and this paper aims to fill this gap. We will construct an estimator for the long memory parameter in the bi-variable causality model in the wavelet domain. The theoretical background is derived and Monte Carlo simulation is used to investigate the performance of the estimator.
Analysis and Visualization of New Energy Vehicle Battery Data

In order to safely and efficiently use their power as well as to extend the life of Li-ion batteries, it is important to accurately analyze original battery data and quickly predict SOC. However, today, most of them are analyzed directly for SOC, and the analysis of the original battery data and how to obtain the factors affecting SOC are still lacking. Based on this, this paper uses the visualization method to preprocess, clean, and parse collected original battery data (hexadecimal), followed by visualization and analysis of the parsed data, and finally the K-Nearest Neighbor (KNN) algorithm is used to predict the SOC. Through experiments, the method can completely analyze the hexadecimal battery data based on the GB/T32960 standard, including three different types of messages: vehicle login, real-time information reporting, and vehicle logout. At the same time, the visualization method is used to intuitively and concisely analyze the factors affecting SOC. Additionally, the KNN algorithm is utilized to identify the K value and P value using dynamic parameters, and the resulting mean square error (MSE) and test score are 0.625 and 0.998, respectively. Through the overall experimental process, this method can well analyze the battery data from the source, visually analyze various factors and predict SOC.
CR-submanifolds in a complex hyperbolic space satisfy-ing an equality of Chen

Recently, Bang-Yen Chen has introduced new type of Riemannian curvature invariants and obtained sharp inequalitiesinvolving these invariants for arbitrary submanifolds in Riemannian and Kaehlerian space forms. It is natural and interesting to investigate and understand submanifolds which satisfythe equality case of this type of inequalities,and such submanifolds have been investigated by many geometers (cf. for instance, [2-6, 8-10, 12-16]). In this paper, we investigate Ci? -submanifolds of complex hyperbolic spaces which satisfy the equality case of one of Chen's inequalities. Let M be an ^-dimensional Riemannian manifold. Denote by K(n) the sectional curvature of M associated with a plane section n a TpM, p e M. For any orthonormal basis e\,. ,en of the tangent space TPM, the scalar curvature r at p is defined to be
Robust, self-consistent, closed-form tomography of quantum logic gates on a trapped ion qubit

We introduce and demonstrate experimentally: (1) a framework called "gate set tomography" (GST) for self-consistently characterizing an entire set of quantum logic gates on a black-box quantum device; (2) an explicit closed-form protocol for linear-inversion gate set tomography (LGST), whose reliability is independent of pathologies such as local maxima of the likelihood; and (3) a simple protocol for objectively scoring the accuracy of a tomographic estimate without reference to target gates, based on how well it predicts a set of testing experiments. We use gate set tomography to characterize a set of Clifford-generating gates on a single trapped-ion qubit, and compare the performance of (i) standard process tomography; (ii) linear gate set tomography; and (iii) maximum likelihood gate set tomography.
Correlation of Body Mass index with Disease Activity in Rheumatoid Arthritis

Objective: To evaluate correlation between body mass index and disease activity in rheumatoid arthritis patients. Methodology: This comparative case-control observational study was conducted at Pakistan Institute of Medical Sciences, on rheumatoid arthritis patients visiting the (Out Patient Departments) OPDs between July, 2021 and December, 2021.The study subjects were selected by non-probability convenient sampling from outpatient department. Body mass index and disease activity score were calculated for rheumatoid arthritis patients in OPD. Statistical Package for Social Sciences (SPSS) version 26 was used for data analysis. Mean ± S.D was calculated for age, body mass index and disease activity. Pearson’s correlation coefficient was used for establishing an association between variables. P value less than 0.05 was considered significant. Simple scatter with fit line was plotted to show graphical association between body mass index and disease activity. Results: A total 60 patients with 35 (58.3%) female and 25(41.7%) were male. The mean age was 47.21 years. The mean DAS-28 for normal weight group was 2.74 and for overweight group was 4.17. There was positive correlation between body mass index and DAS-28 with r was 0.584 (p<0.05). When correlation on gender basis was calculated, for female patients r was 0.653 and for males 0.529, respectively. Conclusion: In Rheumatoid Arthritis patients, body mass index is positively correlated with disease activity. Evaluation of this requires trial on large scale, thus, helping in tailoring new management plan, including, weight reduction rather than escalating drug treatment for disease control and improving quality of life in rheumatoid arthritis patients.
An Advanced Echo Separation Scheme for Space-Time Waveform-Encoding SAR Based on Digital Beamforming and Blind Source Separation

To achieve high-resolution and wide-swath (HRWS) imaging, a space-time waveform-encoding (STWE) spaceborne synthetic aperture radar (SAR) system is adopted. In rugged terrain, the beam-pointing mismatch problem will appear when the traditional digital beamforming (DBF) technique is used to separate the received echoes. This problem leads to decreasing the received echo’s gain, deteriorating the quality of the image product and making the interpretation of SAR image difficult. To address this problem, an advanced echo separation scheme for STWE spaceborne SAR based on the DBF and blind source separation (BSS) is put forward in this paper. In the scheme, the echoes are transmitted within the adjacent pulse repetition intervals to simulate multiple beams, and the scattered echoes are received by the sixteen-channel antennas in elevation simultaneously. In post-processing, a detailed flow is adopted. In the method, the DBF is firstly performed on received echoes. Due to the error caused by terrain undulation, the degree of echo separation is not enough. Then, the BSS is performed on the multiple echoes obtained after the DBF processing. Finally, the highly separated echo signal can be obtained. In this scheme, there is no need to perform the direction of arrival (DOA) estimation before the DBF processing, which saves valuable computing resources. In addition, to verify the proposed scheme, point target and distributed target simulations based on the 16-channel data of an elevation X-band DBF-SAR system are carried out. The results of point targets indicate that the residual echo caused by rough terrain can be reduced by more than 14 dB using the proposed scheme. The proposed scheme can be directly implemented into existing SAR systems; thus, it does not increase the complexity of the system design. The scheme has the potential to be applied to future spaceborne SAR missions.
Analysis of Competence Development of the 21st Century in Islamic Religious Education Subject

In this 21st century Islamic Religious Education (PAI) subject need to develop learning models that are able to develop 21st century competencies. There is a relationship between information technology and Islam in which the Quran contains various instructions on the universal principles of science which is the main domain of information technology. This means that the use of information technology such as the internet in learning Islamic Religious Education is in accordance with Islamic principles. This research is descriptive research and uses survey method. The data collection techniques used closed and open questionnaires. The development of 21st century competencies in PAI is still not optimal. There are three ways to develop 21st century competencies in PAI subject. First, connecting between PAI materials with 21st century life so that PAI material becomes more contextual. Second, developing innovative and creative PAI learning methods and strategies. Third, utilizing the advances in information technology (IT), especially the internet in PAI learning.
Impact of camphor on the in vitro mixed ruminal microorganism fermentation from goats selected for consumption of low and high levels of Juniperus spp. 1

Abstract Encroaching plant species in West Texas continues to significantly reduce livestock production capacity and cause an imbalance between plant and livestock ecology. Juniperus ashei and Juniperus pinchotii are encroaching species rarely used by browsing animals, mainly due to phytochemical defenses. Juniperus spp. contain large concentrations of monoterpenes in their essential oil profiles to deter herbivory. Since 2003, two divergent bloodlines of meat goats have been selected to consume low or high (LJC or HJC) amounts of juniper foliage, through screening fecal samples with near-infrared reflectance spectroscopy. However, it remains unclear whether HJC goats expressed a physiological ability to consume a greater amount of juniper or if they were colonized by a ruminal microbial population that could detoxify juniper phytochemicals. Therefore, this study aimed to investigate the impact of 0.00 and 1.97 mM of camphor on the mixed ruminal microorganism fermentation after 0, 1, 2, 4, 12, and 24 h of incubation. Five LJC and five HJC goats were fed a juniper-free diet (n = 10) and five LJC and five HJC goats (n = 10), were fed a diet containing 30% fresh J. ashei leaves for 21 days prior to ruminal fluid collection. In vitro fermentations used LJC and HJC, ruminal fluid inoculum was added (33% v/v) to anoxic media in sealed Balch tubes. Total short-chain fatty acid (SCFA) production and acetate to propionate ratio were increased (P < 0.05), but there was no effect on pH (6.56 ± 0.09). Goats that received the juniper-free diet had higher (P < 0.05) SCFA production than juniper-containing diets. There was no consistent difference in LJC and HJC microbial fermentation end products caused by the addition of 1.97 mM of camphor, and goats receiving a juniper-free diet consistently generated more SCFAs in the presence of 1.97 mM of camphor. Furthermore, bloodline differences in juniper consumption were likely related to physiological adaption capacities within the animal and not a ruminal microbial detoxification advantage.