Miracle-dz/UniFAR-FTUs huggingface dataset:
“Chinese don’t walk?” – The emergence of domestic walking tourism on China’s Ancient Tea Horse Road

Abstract Walking is a potential key growth area for a diversifying domestic leisure and tourism demand in China. This research discusses the emergence of walking as a touristic activity among Chinese domestic tourists on the Ancient Tea Horse Road (ATHR) in Yunnan, using mobile ethnography. Constellations of sought practices, experiences, and expressed beliefs concerning walking are discussed for four emerging communities of touristic walkers on theses trails: the hiker, the sightseer, the donkey friend and the ATHR pilgrim. The findings presented here reflect various influences from within and outside China, converging to create unique discourses around walking as a leisure pursuit. These findings have implications for the development of recreational walking opportunities in China, where officially designated destinations frequently only cater to the sightseers among walking tourists.
Local Dynamics of an SVIR Epidemic Model with Logistic Growth

Discussion of local stability analysis of SVIR models in this article is included in the scope of applied mathematics. The purpose of this discussion was to provide results of local stability analysis that had not been discussed in some articles related to the SVIR model. The SVIR models discussed in this article involve logistics growth in the vaccinated compartment. The results obtained, i.e. if the basic reproduction number less than one and m is positive, then there is one equilibrium point i.e. E0 is locally asymptotically stable. In the field of epidemiology, this means that the disease will disappear from the population. However, if the basic reproduction number more than one and b1 more than b, then there are two equilibrium points i.e. disease-free equilibrium point denoted by E0 and the endemic equilibrium point denoted by E1*. In this case the endemic equilibrium point E1* is locally asymptotically stable. In the field of epidemiology, this means that the disease will remain in the population. The numerical simulation supports these results.
Effect of Excluded Volume on Phase Transitions in Biopolymers

The effects of excluded volume on the existence and nature of a phase transition in an infinitely long double‐stranded helical polymer are discussed in relation to the recent treatment of Poland and Scheraga, which showed that, if the entropy of a closed polymer loop of 2l links (corresponding to a diassociated length of l polymer units) varies as S2l/kB=al−clnl+b (l→∞), then a genuine phase transition should occur if c>1 but that θ, the fraction of ordered units, would be continuous at the transition unless c>2. The standard Markoffian models of a polymer chain neglect the excluded volume and yield c=½d for a general d‐dimensional system. Numerical data on self‐avoiding lattice chains and rings are reviewed and it is concluded that c≃1.46 and 1.75 are better estimates for d=2 and 3, respectively.The transition should thus remain continuous but it becomes sharper since it is shown that θ varies as (Tt—T)(2−c)/(c−1) when the transition temperature Tt is approached from below (and 1
Real Time Sleep Onset Detection from Single Channel EEG Signal Using Block Sample Entropy

In recent years, driver’s temporary state has been one in each of the foremost causes of road accidents and would possibly lead to severe physical damaging, mortality and necessary and noticeable economic losses. Maximum road accidents possible to avoided, if possible, to properly monitored driver’s drowsiness and a system are given warnings. In this work, a simple and inexpensive method has been offered to detect driver’s drowsiness or sleep onset detection with single channel EEG signal analysis. The key novelty of this work is to identify the sleep onset detection from a publicly available graph signal dataset by exploitation only one feature, simply implementable filter in any microcontroller device or smartphone and a threshold based mostly classification. Since, threshold-based classification techniques don’t need to train the classifier, hence, new subject adaptation is comparatively easier and real time implementation is more feasible. This novel approach can be easily implemented in smartphone to design and expand a drowsiness detection and alarming system for vehicle’s driver. On a variety of subjects, the experimental results show 95.68% accuracy.
Design and Manufacture of an Innovative Vertebral Dilator with Ni-Ti Shape Memory Alloy

The knitted gridding vertebral dilator with Ni-Ti shape memory alloy is designed which is to be used in the treatment of osteoporosis vertebral compressed fracture. The knitted gridding vertebral dilators with different parameters are knitted and their radial force and elastic modulus are tested; then the best knitted parameter is obtained. Taking into consideration the practical application of the vertebral dilator, the structure of both ends of the dilator is improved and an innovative vertebral dilator is obtained which can meet the clinical application needs.
Linking Soil Hydrology and Creep: A Northern Andes Case

Soil creep is common along the hillslopes of the tropical Andes of Colombia, where very heterogeneous soils develop on old debris flow deposits and are subjected to abundant rainfall with a bimodal annual regime. In particular, the western hillside of the city of Medellín, Colombia, is comprised of a series of debris and earth flow deposits in which landslides and soil creep are common. To explore linkages between soil creep and hydrology, we selected an experimental site in the western hillslope of the Medellín valley to assess the behavior of water within the soil mass, its relationship with rainfall, and its connection with soil displacement. In experimental plots, we systematically measured runoff, percolation, water table levels, and volumetric water content, for a period of almost 2 years; we also conducted several alti-planimetric positioning surveys to estimate relative displacements of the soil surface. Moisture content of the soil remained above field capacity for most of the year (~68% of the time) and active and quasi-permanent lateral subsurface flow occurred within the upper 80 cm of the profile. The shallow flow likely facilitates the downslope movement. Additionally, our results suggest that displacement magnitudes are largest during the wet season of September–October–November, when a highly humid soil experiences changes in water content, so it is during this time that the effects of expansion / contraction of the soil particles (associated to wetting / drying cycles) contribute the most to the movement. This observational study represents a contribution to the understanding of soil creep in tropical hillslopes, where it responds to the wetting / drying cycles, with the particularities of a rainy weather (>1500 mm/year), warm temperatures (~22 °C on average), and a bimodal precipitation seasonality.
Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of 5182 cases from long QT syndrome and Brugada syndrome consortia cohorts and gnomAD population controls

Guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false positive rate over test sensitivity and diagnostic yield, and require customisation for the specific genetic characteristics of gene-disease dyads. Inherited arrhythmias like long QT syndrome (LQTS) and Brugada syndrome (BrS) are genetically heterogeneous, with missense variants constituting the preponderance of disease-causing variants. Evidence from family segregation or functional assays to confirm pathogenicity are often unavailable or impractical in clinical genetic testing, leading to high rates of variants of uncertain significance and false negative test results. We compared rare variant frequencies from 1847 LQTS (KCNQ1, KCNH2, SCN5A) and 3335 BrS (SCN5A) cases from the International LQTS/BrS Genetics Consortia to population-specific gnomAD data. We propose disease-specific criteria for ACMG/AMP evidence classes – rarity (PM2/BS1 rules) and enrichment of individual (PS4) and domain-specific (PM1) variants in cases over controls. Rare SCN5A variant prevalence differed between BrS cases with spontaneous (28.7%) versus induced (15.8%) type 1 Brugada ECG (p=1.3x10–13) and between European (20.8%) and Japanese (8.9%) patients (p=8.8x10–18). Transmembrane regions and specific N-terminus (KCNH2) and C-terminus (KCNQ1/KCNH2) domains were characterised by high enrichment of case variants and >95% probability of pathogenicity. Applying the customised rules, 17.5% of European BrS cases and 73.7% of European LQTS cases had variants classified as (likely) pathogenic, compared to estimated diagnostic yields (case excess over gnomAD) of 19.3%/82.6%. Large case/control datasets enable quantitative implementation of ACMG/AMP guidelines and increased sensitivity for inherited arrhythmia genetic testing. Classification of Brugada/LQTS variants Type of funding source: Foundation. Main funding source(s): Dutch Heart Foundation, Netherlands Organisation for Scientific Research
OH- Effect on the Growth and Structural Properties of Chemical Bath Deposited ZnS Quantum Thin Films

Zinc sulfide (ZnS) quantum thin films have been deposited from precursors with a variety of OH- concentration onto microscope glass substrates by chemical bath deposition method. The growth and structural properties have been investigated. XRD patterns of ZnS films obtained from acidic solution showed a favorable wurtzite structure, while for those obtained from alkaline solution, showed a sphalerite structure. The growth studied of the deposited films has also shown that the OH- played a vital role in nucleation and the film growth.
The Limited Role of Surface Defects as Nucleation Sites for Cu2 O on Cu(001)

The authors have observed the initial oxidation stages of Cu(001) thin films by in situ ultrahigh vacuum-transmission electron microscopy, examining the role of surface defects, such as surface steps, as possible nucleation sites for the Cu{sub 2}O on Cu(001) due to oxidation. Weak beam techniques were used to image surface steps. In contrast to previous speculations, the authors did not observe evidence that surface steps are preferential nucleation sites.
Compact Scheduling for Task Graph Oriented Mobile Crowdsourcing

With the proliferation of increasingly powerful mobile devices and wireless networks, mobile crowdsourcing has emerged as a novel service paradigm. It enables crowd workers to take over outsourced location-dependent tasks, and has attracted much attention from both research communities and industries. In this paper, we consider a mobile crowdsourcing scenario, where a mobile crowdsourcing task is too complex (e.g., post-earthquake recovery, citywide package delivery) but can be divided into a number of easier subtasks, which have interdependency between them. Under this scenario, we investigate an important problem, namely task graph scheduling in mobile crowdsourcing (TGS-MC), which seeks to optimize a compact scheduling, such that the task completion time (i.e., makespan) and overall idle time are simultaneously minimized with the consideration of worker reliability. We analyze the complexity and NP-complete of the TGS-MC problem, and propose two heuristic approaches, including BFS-based dynamic priority scheduling BFSPriD algorithm, and an evolutionary multitasking-based EMTTSch algorithm, to solve our problem from local and global optimization perspective, respectively. We conduct extensive evaluation using two real-world data sets, and demonstrate superiority of our proposed approaches.
Spin-dependent tunneling in modulated structures of (Ga,Mn)As

A model of coherent tunneling, which combines multiorbital tight-binding approximation with Landauer-B\"uttiker formalism, is developed and applied to all-semiconductor heterostructures containing (Ga,Mn)As ferromagnetic layers. A comparison of theoretical predictions and experimental results on spin-dependent Zener tunneling, tunneling magnetoresistance, and anisotropic magnetoresistance is presented. The dependence of spin current on carrier density, magnetization orientation, strain, voltage bias, and spacer thickness is examined theoretically in order to optimize device design and performance.
The TRAINing Technique: An Experiential Process Fostering Growth of Counselors in Training

ABSTRACT Students in counseling programs tend to learn better by being active participants in the classroom. Using a relational-cultural pedagogical approach, the authors share an experiential learning practice, the TRAINing technique, where an entire class of counseling students can relate to one another through a shared experience that builds connection and fosters professional growth and skill development. The TRAINing technique provides the opportunity for adult learners to understand, observe, and practice their counseling skills while receiving immediate feedback/supervision. This technique helps counselors in training to gain a deeper appreciation and understanding of the counseling process through authentic connections. The authors give a detailed description of the three phases of the TRAINing technique and its application in different settings. In addition, the authors discuss the counselor training implications.
Implementation of Data Mining in Grouping Percentage of Blind Letters Age 15+ By Province Using K-Means Algorithm

Data Mining is a method that is often needed in large-scale data processing, so data mining has important access to the fields of life including industry, finance, weather, science and technology. In data mining techniques there are methods that can be used, namely classification, clustering, regression, variable selection, and market basket analysis. Illiteracy is one of the factors that hinder the quality of human resources. One of the fundamental things that must be fulfilled to improve the quality of human resources is the eradication of illiteracy among the community. The purpose of this research is to determine the clustering of illiterate communities. The results of the study are illiterate data clustering according to the age proportion of 15+, namely 1 node of the high group, the low group has 23 nodes, and the medium group of 10 nodes. The results of this study become input for the government to determine illiteracy eradication policies in Indonesia based on provinces
Practical finite‐time sampled‐data output consensus for a class of nonlinear multiagent systems via output feedback

This article devotes a practical finite‐time sampled‐data output consensus investigation for a class of nonlinear multiagent systems with unavailable velocities and undirected topology via output feedback. Noticing that the focused multiagent system features nonlinearities with non‐Lipschitz restriction, and the outputs of the agents are detectable only at the sampling instants, a reduced‐order observer with the sampled output measurement is established for each follower to evaluate the unavailable velocity, and the distributed finite‐time sampled‐data consensus protocols, which are constructed by the established reduced‐order observer as well as the sampled output measurement of the agents, are developed by combining the techniques of adding a power integral and backstepping. By selecting a suitable Lyapunov function candidate, we can verify that the developed sampled‐data consensus protocols which work under the allowable sampling period and the appropriate design parameters can solve the considered practical finite‐time output consensus problem. Finally, two simulation examples, include a numerical and an engineering simulations, are provided to reveal the effectiveness and availability of the proposed consensus scheme.
THE PREDICTORS OF POTENTIAL DRUG-DRUG INTERACTIONS AMONG DIABETIC HYPERTENSIVE ADULT OUTPATIENTS IN A KENYAN REFERRAL HOSPITAL

Objective: To characterize the predictors of potential drug-drug interactions among adult diabetic hypertensive outpatients at Kenyatta National Hospital. Methods: This cross-sectional study collected and analyzed data on potential drug interactions from 104 diabetic hypertensive outpatients (aged ≥18 y) at the Department of Endocrinology Outpatient Clinic of Kenyatta National Hospital from 1st May 2019 to 31st August 2019. The main outcome measure was the prevalence of potential drug-drug interactions and their predictors among the study population. Results: There was a female preponderance (70.2%). The mean age of the study participants was 61.6 y (SD±10.8). The prevalence of potential drug interactions was high at 57.7%. The average number of drug interactions was one interacting pair per patient, with a majority of the prescriptions (81.0%) having moderate drug-drug interactions. Patients receiving>2 drugs were almost three times more likely to have drug-drug interaction compared to those prescribed ≤ 2 drugs (AOR=2.79; 95% CI: 1.11-7.28); p=0.029). Participants who were at stage 4 of hypertension were 2.5 times more likely to have a drug-drug interaction compared to the other stages of hypertension (AOR=2.52; 95% CI 1.31-4.89; p=0.007). Conclusion: Polypharmacy and stage 4 hypertension are independently associated with drug-drug interactions among patients with both diabetes and hypertension. Future studies should characterize the specific type of drug interactions and possible targets of minimization of drug-drug interactions.
Circle detection and location based on binocular stereo vision

In this paper, a binocular stereo vision system is developed for recognition and localization of a spherical object. The system uses two cameras to acquire images of object, shows and processes the images from two cameras simultaneously. It then applies point Hough transform to recognize the object and get real-time coordinates through the two images. Experiments with the proposed method yielded good results, as the system can detect and position a spherical object successfully.
Identification of Grape Leaf Diseases Using Convolutional Neural Network

The presence of leaf diseases in grapes can reduce the productivity of grapes and result in losses for farmers. Leaf diseases are mainly caused by bacteria, fungi, virus etc. A proper diagnosis of disease in plants is needed in order to take appropriate control measures. This paper aims to assist in the identification and classification of grape leaf diseases Convolutional Neural Network (CNN). CNN is basically an artificial neural network architecture that requires repeated training processes to get good accuracy. CNN consists of 3 stages, namely Data Input, Feature Learning, and Classification. The implementation of CNN in this study uses Keras libraries that use the python programming language. Keras is a framework created to facilitate learning of computers. The CNN training process using 0.0001 learning rate obtained results with an accuracy rate of 91,37%
Experience of a Portuguese radiation therapy department in the treatment of synchronous and metachronous head, neck, and oesophageal cancers

Abstract Background: Multiple primary cancers in patients with head and neck squamous cell carcinoma (HNSCC) and oesophageal squamous cell carcinoma (ESCC) share common features. Their treatment approach can be a challenge. This retrospective study aims to estimate the cumulative incidence and to describe the outcome of patients with multiple primary cancers, treated in a Tertiary Centre in Portugal. Methods: The study includes patients with HNSCC, ESCC, and multiple tumours (synchronous or metachronous), treated with curative intent in a Centre, between 2004 and 2019. The analysis is focused on the clinical baseline characteristics, the treatment approach, and the outcomes. Patients with distant metastasis at tumour diagnosis were excluded. Results: Of a total of 820 cases, 31 had multiple tumours. In 15.8 years, the cumulative incidence of multiple tumours was 6.45%. Twenty-seven patients were treated with curative intent (n = 7 synchronous, n = 20 metachronous). The most frequent HNSCC cancers in synchronous tumours were oropharynx and hypopharynx tumours (n = 4); oral cavity was the most frequent HNSCC cancer (n = 12) in metachronous tumours. The primary treatment included surgery, adjuvant or definitive radiation therapy or chemoradiation. With a median follow-up time of 73 months, the median overall survival was 51.8 months for synchronous and 102 months for metachronous tumours. Conclusions: Multiple tumours of HNSCC and ESCC are uncommon. In the small group of Portuguese patients analysed, there is a potential pattern of occurrence and treatment outcome. Due to the limited number of patients this study has included, the authors have considered that additional prospective studies with large samples are needed.
Low-Power Wide Area Network Construction Method Based on LoRa Technology for Agricultural Science and Technology Parks

The Internet of Things (IoT) requires different but complementary types of wireless network technologies, having their own merits from distance, power consumption, capacity and cost perspectives. This paper introduces a comparative study of LoRa wireless communication network technology for the long-distance and low-power wide-area network scenario deployment. In this paper, we propose a low-power wide-area network construction method based on LoRa technology for an agricultural science and technology park in Ningxia, Western China. Specifically, we design the optimal placement of LoRa sensors in the facility greenhouse by measuring the LoRa signal quality on the spot in the traditional brick wall sunlight greenhouse. In the traditional brick wall solar greenhouse, the success rate of data communication between LoRa terminal and LoRa gateway reaches 100%. Experiment shows that the coverage distance of the LoRa network reaches 3km in the most common conditions in agricultural science and technology park, i.e., the height of the LoRa gateway is 10 meters, and the maximum transmission power is 27dbm.
Earnings Management in Light of the Shift to International Financial Reporting Standards (IFRS): An Exploratory Study on Saudi Corporations

This study aims to study the Earnings management in light of the shift to International Financial Reporting Standards (IFRS) through a field study, which has occurred in Saudi jointstock companies. Through research, I achieved several results, such as: That there is change expected to happen in Earnings management in light of the shift to International Financial Reporting Standards (IFRS) via: Manipulating both the expenditure and revenue in the income statement, The manipulation of the accounts of Balance Sheet Statement, The manipulation of cash flows statement, as well as through the manipulation of reports of the changes in equity statement. The accountants in Saudi Corporations are concerned to shift to IFRS, expecting that the Earnings management is going on; thus, the IFRS had implemented.