Miracle-dz/UniFAR-FTUs huggingface dataset:
Negative Effects of Industrial Clustering on Region Social and Economic Development: System and Agglomeration Approach

The Present investigation illustrates the negative side of industrial clustering which often makes regional social and economic policy ineffective. Analyzing data from 790 papers, we identified and described 5 key negative clustering effects. Drawing from a system and agglomeration approach we propose a conceptual mechanism that illustrates cluster influence on a region, focusing on internal parameters which determine the impact nature (positive, negative or neutral). The investigation showed that the genesis of all the negative effects is connected with the tendency of industrial clusters to close in on itself in the medium term. Based on these findings, we propose recommendations on industrial cluster negative influence minimization.
Zakat and the Performance of Islamic Banks

The objective of this study is to examine the performance of Islamic banks (IBs) in Malaysia based on zakat (ZOA and ZOE) and ROA and ROE. This is to effectively understand the factors influencing the performance of IBs in Malaysia. The study employs a balanced panel of 15 IBs for the period 2009-2018 using the System-GMM. The study provides justifications why zakat is the appropriate measurement for IBs' performance. The study concludes that zakat is an appropriate performance measurement to explain the performance of IBs. This is because zakat is able to explain and truly reflects the performance of IBs, and as such, IBs should pay more zakat as they generate more profit. Zakat therefore has a role to contribute to Islamic social finance in the context of IBs. Furthermore, IBs have indispensable roles in supporting the economy of a country through their liquidity creation and risk transformation functions.
Multi-Turn Response Selection in Retrieval Based Chatbots with Hierarchical Residual Matching Network

Response selection in retrieval-based chatbot aims to find the most relevant response in a candidate repository given the conversation context. A key technique to this task lies in how to measure the matching degree between conversation context and response at rich semantic information. In this paper, we propose a hierarchical residual matching network (HRMN) to fully extract and make use of the rich semantic information in the conversation history and response for themulti-turn response selection task. We empirically verify HRMN on two benchmark data sets and compare against advanced approaches. Evaluation results demonstrate that HRMN outperforms strong baselines and has a distinct improvement in response selection.
A Study to Assess the Health Seeking Behavior and General Health Problems among Female Patients Visiting A Rural Health Center in Ambikapur, Surguja District in Chhattisgarh, India

Background: Quality of services, convenience of approach, lack of personal attention and long waitingtime have been found to be significant barriers for seeking health care in public sector, which requires tobe addressed. Objective: The present study was conducted with the objective to assess the health seekingbehavior and general health problems among female patients visiting a health center in Ambikapur. Materialsand Methods: A cross-sectional study was conducted among 101 patients visiting a rural health center inAmbikapur. Result: The present study clearly reveals there is a preference for government health facilityamong female patients in the rural area of Ambikapur. Conclusion: This government health facility wasnearest as compared to other nearby government health facilities, it was affordable and a preferable choicefor the rural patients due to trust on the doctors and staff.
Dynamic Time- and Load-Based Preference toward Optimal Appliance Scheduling in a Smart Home

In this paper, the household appliance scheduling based on the user predefined preferences is addressed. Previous works generally deal with this problem without integration of renewable energy sources (RESs) in smart home. The present paper proposes a new demand side management (DSM) technique considering time-varying appliance preferences and solar panel generation. The branch and bound (B&B) algorithm is developed based on three postulations that allow the time-varying preferences to be quantified in terms of time- and load-based features. Based on the input data including the load’s power rating, the absolute comfort derived from time- and load-preferences, the total energy available from the solar panels as well as the energy purchased from the utility grid, the (B&B) algorithm is run to generate the optimal energy consumption model that would give maximum comfort to the householder based on the mixed-integer linear programming (MILP) technique. To test the performance of the proposed mechanism, three scenarios are considered with local energy production and limited budget for purchasing the energy from the utility grid to cover the user needs. The simulation results reveal that the proposed DSM mechanism based on the MILP method offers maximum level of comfort for all the scenarios within the available energy limitation.
Education of the Patients Living with Heart Disease

Introduction: Patient education can be defined as the process of improving knowledge and skills in order to influence the attitudes and behaviour required to maintain or improve health or health style. Aim: Education of the patients living with heart disease from ambulatory nurse education for the effectiveness on awareness on life style. Methods: A quasi experimental study was conducted in Specialist Cardiology Ambulance D&D in Pristina among 100 patients. A complete clinical and laboratory measurements before and after the process of patient education (at 30, 60 and 90 days) were performed. The clinical outcome was nutrition, body mass index, blood pressure, lipid, diabetic profile and physical activity. The pre-post tested (validity, reliability and pilot testing) structured questionnaire were used for data collection. Results: All patients underwent education sessions by an experienced education nurse on 30, 60 and 90 days. At 90 days follow up, the BMI was decreased: Pre-education (29.01±5.46), Post-education (27.72±4.71), t- 5.999 p<0.0001, glycaemic level Pre-education (6.50±2.15) and Post-education (6.02±1.63), t- 4.157, p<0.0001 was decreased, HbA1c in Pre-education (6.23±2.06) and Post-education (5.72±1.44) t- 4.036 p<0.0001 respectively. The lipid profile was also changed at the 90 days follow-up: cholesterol, triglyceride and LDL-C were decreased (p<0.0001 for all), whereas HDL-C was increased (p<0.0001), by educational program at 90 days follow up. Whereas, blood pressure remains unchanged. Conclusion: Heart disease management programme where patient’s education is an important component, have been shown to be effective in increasing knowledge, self-care and self-management patients living with heart disease.
Research on FUI Style Design of Big Data Information Visualization

The purpose of the article is as follows, studying the FUI style of the interface for big data information visualization design among various styles of visualization interface in the 21st century. There are three research methods in this paper. Firstly, combing the concept of FUI and summarizing the design features of FUI style interface of big data information visualization from the perspective of design psychology. Secondly, the characteristics of government business big data information visualization and the needs of users are analyzed. Finally, the FUI design style is used in the government business big data information visualization display interface design. The FUI style presentation mode of big data information visualization and the dynamic interaction mode of FUI style interface are discussed. The conclusion is as follows, FUI is more in line with the people's psychological expectation of "future technology visual style" in big data information visualization display, highlighting the FUI data display focus on the prediction function of future events; FUI achieves visual balance through reasonable typesetting, comfortable color matching, uniform decorative shapes, etc. In terms of visual display, it not only meets the requirements of data display design, but also achieves the visual unity of partial data display design and overall data display. FUI mostly adopts flat design and simple dynamic interaction design, which conforms to users' gesture operation and people's visual browsing behavior habits in the era of mobile Internet, and meanwhile improves the utilization rate of single screen display of government departments.
Social Prediction-Based Handover in Collaborative-Edge-Computing-Enabled Vehicular Networks

Collaborative edge computing (CEC) can realize the cooperation and integration of heterogeneous resources distributed in adjacent areas, increasing the overall resource utilization efficiency. In a CEC-supported heterogeneous vehicular network composed of different access solutions, including cellular vehicle-to-everything (C-V2X) and dedicated short-range communications (DSRC), good network connections can guarantee timely access to edge resources. How to maintain stable and high-quality network connections for vehicles is a crucial issue. With traditional received signal strength (RSS)-based handover schemes, vehicles may encounter severe ping-pong effects and even direct handover failures leading to data packet loss. In this article, to overcome the frequent handover problem caused by vehicles’ high-speed motion and the ever-changing network environment, we propose a trajectory prediction-based handover scheme. In this scheme, the sojourn time of a vehicle staying in each candidate network’s coverage can be obtained through a social long short-term memory (social-LSTM)-based prediction model. Together with the signal strength, available bandwidth, and cost, the sojourn time is also taken as a handover decision attribute parameter. Simulation results show that our proposed scheme can reduce the number of handovers effectively.
A Predict Model to Evaluate the Level of HBV-DNA for the Patients With Chronic Hepatitis B Virus (CHB) in Clinic: a Cross-sectional Study

Background: The previous studies showed the correlation between HBsAg and serum HBV DNA levels were weak or missing. And the relationship of HBeAg and HBV DNA levels was lack.Objective: The study aims to investigate the correlation between HBeAg and HBV DNA levels, and to find an alternative tool to evaluate the HBV DNA levels for clinicians.Methods: We enrolled 1020 patients in this cross-sectional study. We divided the patients into four groups as: HBeAg positivity and negativity groups, high and low HBV DNA levels groups. Further, as to the levels of HBV DNA, we performed subgroups’ in HBeAg-positive and HBeAg-negative groups.Results: The levels of ALT, ALB and HBeAg were the independent factors for the serum HBV DNA in CHB patients. The predict model for the patients with HBeAg-positive was: M1 (high HBV DNA levels) = 1.412 × (1 for HBeAg-positive >16.15 S/CO or 0 for others) + 0.004 × (1 for ALT > 42.5 IU/L or 0 for others) −0.029 × (1 for ALB > 25.5 g/L or 0 for others) + 0.779, and the AUC was 0.606. And the predict model of patients with HBeAg-negative was: M2 (low levels of HBV DNA) = 0.385 − 0.005 × (1 for ALT > 36.5 IU/L or 0 for others) − 0.006 × (1 for TB > 11.15 umol/L or 0 for others), and the AUC was 0.609. Conclusion: HBeAg was an independent risk factor for the patients with HBeAg(+), and when the level of HBeAg was higher than 16.15 S/CO, the patients should have a HBV-DNA test, if not , we should combine with the level of ALT to determine the decision. For the patients with HBeAg(-), we should evaluate the patients to have a HBV-DNA test by the levels of ALT and TB.
Application of the Advanced Distillation Curve Method to Fuels for Advanced Combustion Engine Gasolines

Incremental but fundamental changes are currently being made to fuel composition and combustion strategies to diversify energy feedstocks, decrease pollution, and increase engine efficiency. The increase in parameter space (by having many variables in play simultaneously) makes it difficult at best to propose strategic changes to engine and fuel design by use of conventional build-and-test methodology. To make changes in the most time- and cost-effective manner, it is imperative that new computational tools and surrogate fuels are developed. Currently, sets of fuels are being characterized by industry groups, such as the Coordinating Research Council (CRC) and other entities, so that researchers in different laboratories have access to fuels with consistent properties. In this work, six gasolines (FACE A, C, F, G, I, and J) are characterized by the advanced distillation curve (ADC) method to determine the composition and enthalpy of combustion in various distillate volume fractions. Tracking the compositi.
Development of a technique to measure local scattering in turbid media using backscattered light at the surface for noninvasive turbidity evaluation of blood in subcutaneous blood vessels

For noninvasive skin-surface evaluation of turbidity in subcutaneous blood vessels we have developed a technique to estimate the reduced scattering coefficient from spatially resolved backscattered light. The solution of the diffusion approximation was used to derive an analytical solution for the effective attenuation coefficient as a function of the spatially resolved reflectance with respect to the source–detector distance. The reduced scattering coefficient can be calculated from the effective attenuation coefficient. This represents the blood turbidity or serum triglyceride concentration. An exact solution for the reduced scattering coefficient was newly obtained as a function of the effective attenuation coefficient using the special diffusion coefficient, which expands the applicability of the diffusion approximation to the case of human blood. To eliminate the effects of strong scattering in the surrounding tissue we introduced a differential principle using spatially resolved reflectance measured at positions on and off the blood vessel. The results of Monte Carlo simulation demonstrate the validity of the proposed technique even in the case of blood, which does not necessarily satisfy the conditions of the diffusion approximation. The small dependence on absorption variation in the practical range and robustness against the measurement error were verified. With the differential principle we can estimate blood turbidity by suppressing the effect of the surrounding tissue. With this technique, one can expect more than 50 times higher sensitivity for blood turbidity than that obtained without using this principle. The validity of the simulation and the applicability of the proposed technique were verified with measurements using a model phantom of subcutaneous blood vessels in a tissue-simulating turbid medium.
Nutritional comparison of the pallid emperor moth, Cirina forda and the Atlantic mackerel, Scombrus scomber

Lack of adequate animal proteins in human diets and its malnutrition consequences has led to advocacy for entomophagy. However, many edible insects are yet to be proven comparable to meat or fish. This study compared the nutritional quality of Pallid Emperor moth, Cirina forda and Atlantic mackerel, Scomber scombrus. Proximate and anti-nutrients quantities of the samples were determined using standard AOAC methods, mineral elements were measured using flame photometry and Atomic Absorption Spectroscopy, while amino acid were determined by HPLC method. The data obtained were analyzed using t-test at P
Networks as Drivers of National Innovative System Development in the Conditions of Globalization

Research background: The modern social, political and economic challenges of the Fourth Industrial revolution and development of the Network Society actualized the problem of maximizing of effectiveness of innovative policy analysis as one of the key factors of economic and political competitiveness of national states, regions, cities and urban agglomerations in Global World. Purpose of the article: The study focuses on the impact of networking on the effectiveness of national innovative development in the context of globalization. In this vein, the main ways of network interaction are considered and the network model of innovation policy is analyzed. Methods: Modern innovation policy is a synthesis of scientific, economic, industrial, and partly regional policy of the state, aimed at the formation and maintenance of an adequate institutional environment for the process of creating, disseminating and introducing innovations. Thus the key feature of the research methodology is the combination of the New Institutional Approach and the Network Theory. Findings & Value added: The study provides a detailed analysis of international experience in the field of open innovation and innovative development based on network interaction. Moreover, the authors present the classification of countries that are leaders in the process of building information (communicative) and network infrastructure. Particular attention is paid to issues of network interaction at the global level and the case of Russian innovation system in this context.
Study on User Experience of Live Streaming Sales Based on ISM and Kano Quality Model

With the development of the Internet economy, live streaming sales have become a new marketing method, which is popular among users. This paper explores quality attributes of live streaming sales based on the experience of their users. In this study, 56 factors, including the original and abstract reasons for and the specific item of user experience of live streaming sales, were first obtained with the evaluation grid method according to the semi-structured interview of highly involved people. Then, 5 experts formed a focus group for discussion and determined 11 key factors influencing user experience as analysis factors of the ISM theoretical model. Results are obtained through the statistical analysis of the ISM theoretical model, and four major dimensions are defined, namely the first-level demand dimension, the second-level interaction dimension, the third-level good quality dimension and the fourth-level extension dimension. Finally, the relationship between attractive quality attributes in different dimensions and the Kano two-dimensional quality classification and user satisfaction is analyzed based on the Kano two-dimensional quality questionnaire. A satisfaction coefficient matrix diagram is drawn to analyze the key quality attributes. Research conclusions and suggestions are made according to the results of data analysis so as to provide reference value for subsequent improvement of related designs and help designers improve user experience.
Feeding habits and trophic interactions of four sympatric hammerhead shark species reveal trophic niche partitioning

Knowledge of the ecological roles of species within food webs and how their trophic interactions affect food web structure is critical to model management and conservation scenarios for species that are suffering high levels of anthropogenic pressure, such as hammerhead sharks. In this paper, we analyze the diet and trophic relationships of 4 sympatric hammerhead shark species using a combination of stomach content and stable isotope analyses. These species showed trophic similarities by sex and trophic dissimilarities by maturity stage. We found that the trophic niche of hammerhead species tends to be more similar within species than among them. This suggests that competitive interactions are more likely to occur between conspecifics than between congeneric individuals and highlights the potential different roles that these species can play within the food web structure. The intermediate to high trophic positions observed in Sphyrna corona, S. media, S. tiburo and S. lewini juveniles indicate mesopredator roles, whereas S. lewini subadults could be considered top predators. Our findings revealed multiple trophic interactions between hammerhead sharks and prey from different trophic levels, which could be critical for the structure and function of marine food webs.
Distributed Beams: Concept of Operations for Polarimetric Rotating Phased Array Radar

Important requirements for a future generation of weather surveillance radars include improvements in data quality and more rapid update of volumetric data. Phased array radar (PAR) is a candidate technology capable of providing the required functionality. The rotating PAR (RPAR) is a potential architecture that could improve the capabilities of the current parabolic-reflector-based US Weather Surveillance Radar—1988 Doppler (WSR-88D) operational network and is more affordable than other candidate PAR architectures. However, RPAR concept of operations that support observational needs has to be developed. The Distributed Beams (DB) technique introduced in this article provides a way to either reduce the scan times or to reduce the variance of radar-variable estimates by azimuthally spoiling the transmit beam while receiving multiple digital beams as the radar rotates in azimuth. Specifically, the rotation speed of the pedestal is derived from the duration of the coherent processing interval (CPI) to produce the desired spatial sampling. This results in beams from subsequent CPIs in approximately the same directions, which increases the number of available data samples for processing. The increased number of available samples can be coherently processed to reduce the variance of estimates. Alternatively, by reducing the number of samples per CPI and increasing the RPAR’s rotation rate, the scan time can be reduced without increasing the variance of estimates. Results presented demonstrate both applications of the DB technique for dual-polarization observations. Given that this technique makes use of spoiled transmit beams, its benefits come at the expense of degraded angular resolution (beamwidth and sidelobe levels), and reduced sensitivity compared with the use of pencil beams. The technique could be implemented as part of an RPAR concept of operations to meet requirements for the future weather surveillance network if certain tradeoffs are accounted for in the radar design process.
A Structure Landmark-Based Radio Signal Mapping Approach for Sustainable Indoor Localization

Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection and construction of signal radio map (a basis for Wi-Fi fingerprinting-based localization) is a labor-intensive and time-cost work, which limit their practical and sustainable use. In this study, an indoor signal mapping approach is proposed, which extracts fingerprints from unknown signal mapping routes to construct the radio map. This approach employs special indoor spatial structures (termed as structure landmarks) to estimate the location of fingerprints extracted from mapping routes. A learning-based classification model is designed to recognize the structure landmarks along a mapping route based on visual and inertial data. A landmark-based map matching algorithm is also developed to attach the recognized landmarks to a map and to recover the location of the mapping route without knowing its initial location. Experiment results showed that the accuracy of landmark recognition model is higher than 90%. The average matching accuracy and location error of signal mapping routes is 96% and 1.2 m, respectively. By using the constructed signal radio map, the indoor localization error of two algorithms can reach an accuracy of 1.6 m.