Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategic management for health care organizations in Azerbaijan Republic

Tel. :+436602008189 To meet persistent challenges in the health care system, an optimal development strategy for both the entire health care system and health care institutions must be adopted, based on strategic planning that takes into account all environmental changes. Health care planning should make it easier to bring rates and levels of health development in line with health promotion objectives. Organizations and individuals will be deprived of a clear way of assessing the purpose and assigning of the corporate enterprise if strategic planning is not used. Different approaches to strategic management of health care organisations in the Azerbaijan Republic were evaluated in this paper. The current situation in the health care management sector was reviewed, as well as the applicability and feasibility of business analysis tools such as Strengths, Weaknesses, Opportunities, and Threats (SWOT) and Balanced Scorecard (BSC). The use of combined SWOT-BSC methodology is a powerful tool for creating a strategic map that allows the organisation to perform a chosen strategy more effectively and serves to define the organization's strategic goals. The SWOT-BSC methodology has the advantage of being able to respond flexibly to ongoing market changes and, if necessary, adjust the management process – ensuring the health care organization's "adaptability. "
Identifying Outliers in Complex Categorical Data by Modelling the Feature Value Couplings

This paper introduces a novel unsupervised outlier detection method, namely Coupled Biased Random Walks (CBRW), for identifying outliers in categorical data with diversiﬁed frequency distributions and many noisy features. Existing pattern-based out-lier detection methods are ineffective in handling such complex scenarios, as they misﬁt such data. CBRW estimates outlier scores of feature values by modelling feature value level couplings, which carry intrinsic data characteristics, via biased random walks to handle this complex data. The outlier scores of feature values can either measure the out-lierness of an object or facilitate the existing meth-ods as a feature weighting and selection indicator. Substantial experiments show that CBRW can not only detect outliers in complex data signiﬁcantly better than the state-of-the-art methods, but also greatly improve the performance of existing meth-ods on data sets with many noisy features.
RESURRECTION OF EVOLUTIONARY PSYCHOLOGY IN GAMING: HOW CAN OLD PRINCIPLES CONTRIBUTE A NEW DOMAIN

The multidisciplinary character of game studies enables the implementation of knowledge from various study fields, and so explores games in different terms. However, not all approaches have so far gained sufficient attention. This study introduces the meaning of evolutionary psychology as well as points out its significance and certain neglect in relation to present digital games research. The exploratory study aims to contribute to the creation of a theoretical framework for the research of digital games from the perspective of evolutionary psychology. Partial goals include summarization, characteristics, and applications within the gaming discourse illustrating far-reaching ways in which evolutionary theory could potentially advance digital games research and hence enrich the game studies in general.
Anthropomorphism Affordance, Trust and Continuance Intention in Virtual Personal Assistants

With the proliferation of virtual personal assistants (VPAs) into our daily life, VPAs providers are concentrating on the anthropomorphic characteristics design to create a more human-like experience to users. While how these anthropomorphic features of VPAs affect user behavior remains an under-investigated research question. Drawing upon technology affordance perspective, this study investigates the influences of two specific anthropomorphism affordances, namely conversational human-like affordance and humor affordance, on user’s trust and continuance intention in VPAs. We conduct an empirical study and find that trust partially mediates the influences of anthropomorphism affordances on continuance intention. Additionally, usage frequency significantly moderates the effect of user trust on continuance intention. Implications and conclusions are discussed in the final section.
Genetic basis of resistance to Macrophomina phaseolina in Phaseolus vulgaris line BAT-477

Charcoal rot caused by the fungus Macrophomina phaseolina (Tassi) Goid. [synonym: Rhizoctonia bataticola (Taubenh.) E.J. Butler] causes considerable damage in bean production areas that ai"e characterized by high tcmperaturc and drought conditions. Sources of resistance to this disease have been identified within tlie bean gcrmplasm (Pastor-Corrales and Abawi, 1988; Echavez-Badel and Beaver, 1987), but little is known regarding the genetic base of this resistance. Miklas and Beaver (1994) suggested that the resistance was polygenic. The goal of our analysis was to deteiTnine the genetic basis of the resistance in line BAT-477 and develop DNA markers for use in niiuker-assisted selection.
Sustainable Approach to Teaching Embedded Systems with Hands-On Project-Based Visible Learning

Although purchasing state-of-the-art teaching equipment may be financially demanding, substantial efforts are being made at the Norwegian University of Science and Technology (NTNU) in Trondheim to provide students with an enhanced hands-on embedded system design experience in a sustainable manner. In particular, an approach that consists of adopting low-cost commercial off-the-shelf (COTS) components and tools for learning purposes is proposed in this work. This strategy effectively combines both industry standard highly-reliable automation controllers, such as Programmable Logic Controller (PLC) technology, as well as novel microcontrollers (i.e., the micro:bit microcontroller based on the nRF51822 system-on-chip (SoC)) explicitly designed for use in embedded systems education. This contributes towards a hands-on sustainable learning experience based on the applicability of Visible Learning (VL). The objective of this paper is to propose a novel organisation of the embedded systems module for the engineering cybernetics education curriculum. The intended outcome is to promote a novel teaching approach. This is achieved by engaging students in both a series of organised theoretical lectures as well as practical and highly involving laboratory group projects. Surface learning sections and deep learning sections are thoroughly alternated to stimulate understanding, making relations, and extending the students’ knowledge. The course organisation and main topics, as well as result analysis of student surveys are discussed. The survey results and feedback from the reference group indicate that the course organisation and topics are effective and helpful for the students.
Statistica Sinica Preprint

Nonparametric Bayesian Two-Level Clustering for Subject-Level Single-Cell Expression Data Abstract: The advent of single-cell sequencing opens new avenues for personalized treatment. In this paper, we address a two-level clustering problem of simultaneous subject subgroup discovery ( subject level ) and cell type detection ( cell level ) for single-cell expression data from multiple subjects. However, cur-rent statistical approaches either cluster cells without considering the subject heterogeneity or group subjects without using the single-cell information. To bridge the gap between cell clustering and subject grouping, we develop a nonparametric Bayesian model, Subject and Cell clustering for Single-Cell expression data (SCSC) model, to achieve subject and cell grouping simultaneously. SCSC does not need to prespecify the subject subgroup number or the cell type number. It automatically induces subject subgroup structures and matches cell types across subjects. Moreover, it directly models the single-cell raw count data by deliberately considering the data’s dropouts, library sizes, and over-dispersion. A blocked Gibbs sampler is proposed for the posterior inference. Simulation studies and the application to a multi-subject iPSC scRNA-seq dataset validate the ability of SCSC to simultaneously cluster subjects and cells.
Research on the Influencing Factors of Bond Default: Literature Review

Since the default of "super-day debt" in 2014, more and more bonds of listed companies in China have defaulted, and bond default has gradually become the norm. In this paper, the influencing factors of bond default are summarized as the research object, and it is found that bond default has certain rules from multiple angles, which can provide reference for theoretical circles, practical circles, government and investors.
THE MICROBIAL COMPONENT IN SPANISH AQUATIC ECOSYSTEMS

Spain has a wide variety of aquatic ecosystems with peculiar chemical composition and hydrological regimes. Microorganisms are the sole inhabitants of many of these sytems and a very important component in most. Studies of microbial ecology in Spanish ecosystems, therefore, provide examples of both "conventional" and "peculiar" environments, where hypotheses about the role of microorganisms can be tested. This paper provides an overview of the studies of microorganisms carried out in Spanish aquatic ecosystems and summarizes their contributions to the current paradigm of the bacterioplankton.
Microspheres for bone regeneration and localised delivery of enzymes

Gaucher disease (GD) is caused by the decreased activity and/or stability of the lysosomal enzyme glucocerebrosidase (GCR). The available treatment consists in the intravenous administration of exogenous GCR, and is effective in reverting most of the symptoms. However, in terms of bone pathology, which is among the most disabling manifestations, a slow and incomplete response is observed, indicating that adjuvant therapies are necessary to consistently restore GCR activity in bone and accelerate regeneration. In this study, calcium alginate microspheres were analysed as a vehicle for localised GCR delivery to bone. Results demonstrated that the entrapped enzyme retained full activity and exhibited a broader pH-dependent activity profile, compared to that of free-GCR, with improved stability at physiological pH. GCR release profile was established, and it was demonstrated that GCR could be released in a sustained manner. The biological behaviour of the system was evaluated by analyzing the uptake of released GCR by GCR-deficient cells from a GD patient, using different techniques: GCR activity measurements, radiolabelling and
Exploring the Black Box: Technology, Economics, and History

List of figures Preface Introduction Part I. Dealing With an Uncertain Future: 1. Path-dependent aspects of technological change 2. Charles Babbage: pioneer economist 3. Joseph Schumpeter: radical economist 4. Technological innovation and long waves Part II. Technology in Context: 5. Economic experiments 6. Why in America? 7. Can Americans learn to become better imitators? 8. Critical issues in science policy research Part III. Sectoral Studies in Technological Change: 9. Energy-efficient technologies: past and future perspectives 10. Innovation in the chemical processing industries 11. Telecommunications: complex, uncertain, and path-dependent 12. Understanding the adoption of new technology in the forest products industry 13. Scientific instrumentation and university research Index.
Vitamins and Cancer Immunotherapy

Vitamins are essential for cellular growth and nutrition. The bioavailability of vitamins may affect the immune system’s ability to fight cancer. Research efforts investigate the complex interplay of vitamins, immune cells, and cancer cells to improve treatment outcomes. This review explores managing the intake of vitamin A, B, C, D, E, and K to enhance the efficacy of forced-atopy cancer immunotherapy.
Status of cholesterol in our diets: A review

Cardiovascular disease (CVD) is the leading cause of death in the world. Hypercholesterolemia, characterized by elevated blood low-density lipoprotein cholesterol (LDL-C) concentrations, is a risk factor for CVD. A growing body of research suggests that LDL-C levels and CV risk are linked. Despite the fact that the majority of current epidemiologic studies show no substantial link between eating one egg per day and blood cholesterol levels or cardiovascular risk, proponents of a positive link remain. The goal was to look at intervention trials that looked at the impact of cholesterol on LDL levels in people. In addition, eggs and dietary cholesterol affect serum cholesterol in many ways. The importance of decreasing cholesterol levels with probiotics, dietary fiber, plant sterols, and nutraceuticals was also discussed.
Fake News Detection on news articles using Machine and Deep Learning Techniques

In the recent years a widespread proliferation of fake and fabricated content has been witnessed among various online web platforms, leading to the formation of a distorted and most of the times manipulated public opinion towards political, social or other everyday issues. Therefore, there have been many efforts to develop fake news detection systems to contribute in the unveiling and debunking of deceptive news. In this thesis we will be working on three different fake news datasets, trying to spot the linguistic differences between fake and truthful articles providing a visualization of the results. The aim of the project is to compare five different machine learning classifiers as well as to develop an ensemble method of different combinations of classification models to investigate which gives best universal results for all three data sources. Afterwards, a simple long short-term memory neural network was developed to examine the results of a deep learning method in comparison to statistical machine learning models. The methodology followed in this project starts with applying natural language processing and feature extraction techniques which aim to prepare the data to be “fed” into each classification model for training and tuning parameters for each classifier. The results are then presented and compared using barplots, confusion matrices and precision–recall curves. SUBJECT AREA: Machine Learning, Deep Learning, Data Mining, Data Visualization
Agricultural Biotechnology in International Development

Introduction: The ABSP the release of transgenic varieties in centres of origin - effect on biotechnology R&D priorities in developing countries current status of research on agricultural biotechnology in Indonesia agricultural needs in sub-Saharan Africa the role of biotechnology the application of biotechnology to potato development of virus resistant sweetpotato the application of biotechnology to rice current advances in the biotechnology of banana the application of biotechnology to date palm the use of coat protein technology to develop virus-resistant cucurbits the biotechnology of oil palm rice biotechnology capacity building in Asia international biosafety regulations - benefits and costs fundation Peru - a case study in capacity building Cassava biotechnology research - beyond the toolbox developing and accessing agricultural biotechnologies - international, US and developing country perspectives and experiences international intellectual property and genetic resource issues affecting agricultural biotechnology SIRDC as a scientific and technology centre for sustainable agricultural, industrial and technical development role in technology transfer technology transfer system in Thailand trade in conventional and biotechnology agricultural products wild biodiversity - the last frontier? developing an agricultural biotechnology business - perspectives from the front lines.
A Hybrid Unequal Error Protection / Unequal Error Resilience Scheme for JPEG Image Transmission using OFDM

This paper combines two major error control coding techniques alongside the highly efficient Orthogonal Frequency Division Multiplexing scheme to provide a sophisticated and reliable framework for JPEG image transmission. The image to be transmitted is first spilt into different quality layers of unequal importance by the use of the progressive JPEG encoding technique. The quality layers are then assigned an Unequal Error Resilience to synchronization loss by unequally allocating the number of headers available for synchronization to them. Following that Unequal Error Protection against channel noise is provided to the layers by the use of Rate Compatible Punctured Convolutional Coding. Finally to provide greater bandwidth efficiency and protection against intersymbol interference, the Orthogonal Frequency Division Multiplexing scheme has been used. The proposed scheme provides a significant gain in image quality over a scheme that uses Equal Error Protection and Equal Error Resilience. The image quality has been evaluated in terms of the Peak to Peak Signal to Noise power Ratio (PSNR) and the Mean Structural Similarity Index (MSSIM) metric. Keywords: UEP, UER, JPEG Image Transmission, OFDM.
FACIAL LANDMARK DETECTION: A REVIEW

: Face landmarking, characterized as the detection and confinement of certain keypoints focuses on the face, assumes ostensibly the significant job as a middle person step for some, consequent face handling tasks that extents from biometric recognition to the comprehension of mental states This paper reviews the concept of the Facial Landmark detection , its methods and applications.
Evaluation of Risk Factors for Preterm Birth Outcome in Gujarat, India

Background: Preterm birth (PTB) is a leading cause of neonatal survival complications, mortality, and morbidity worldwide. In India 35% of all neonatal deaths are due to PTB with 36th global ranking, hence, India's healthcare sector has been working towards reducing the rate of PTB effectively. Objective: This study aimed to assess the risk factors such as environmental and pathophysiological causes associated with preterm birth in the population of Gujarat, India. Materials and Methods: In this study, multivariate random sampling was performed and systematically 200 pregnant mothers [PTB <37 weeks (N=100), Full-term >37 weeks (N=100)] were chosen after excluding mothers with vaginal infection, multiple gestations, fetal anomalies, non-cephalic presentation, cesarean delivery, and pregnancy with Mullerian anomalies. Statistical analysis was performed by Chi-square test, and variables with p-value <0.05 were considered statistically significant. Results: Out of all the variables, maternal age below 20 years, extreme BMI, high blood pressure during pregnancy, maternal health complications, medication and doctor's consultation were highly significant (p < 0.0001). Furthermore, variables like type of area, diet, education, Hb levels below 9 g/dL and above 13 g/dL and blood-group of the mother were also significantly associated with PTB outcome (p < 0.05). Among the sub-categories of PTB (extreme-, very-, moderate/late- PTB), maternal age, Hb level and the past obstetric outcome showed very high significance (p < 0.0001). Conclusion: For the prediction of birth outcome, mother's internal physiological and lifestyle factors need to be taken into consideration, and mothers at risk priorly can be screen out, followed by proper healthcare assistance to decrease the preterm birth rate and its consequences. Key words: Preterm birth, maternal age, blood pressure, past obstetric outcome, risk factors
ANALISIS KINERJA SISTEM KOMUNIKASI CAHAYA TAMPAK DIBAWAH AIR DENGAN OPTICAL CONCENTRATOR PERFORMANCE ANALYSIS OPTICAL CONCENTRATOR ON UNDERWATER VISIBLE LIGHT COMMUNICATION

UVLC has several challenges, i.e. the exponential value of the water attenuation coefficient and the limited bandwidth of the light source. This thesis considered used of optical concentrator on photodetector to focus and collect light entering the receiver, therefore the received power is increasing within the communication range. This thesis uses two scenarios to evaluate the performance evalluation. Scenario I analyzes the performance of the UVLC system without the optical concentratror on two types of On Off Keying (OOK) modulation, namely OOK - Non Return to Zero (OOK-NRZ) and OOK-Return to Zero (OOK-RZ), without the addition of an optical concentrator. Scenario II compares system performance UVLC with the addition of an optical concentrator. Both scenarios will be tested based on distance, Received Power, Signal to Noise Ratio (SNR) and Bit Error Rate (BER) parameters. The result confirmed the addition of optical concentrator has better performance by proving that Received Power and SNR value that obtained in scenario II greater than in the scenario I. This is proven when using an optical concentrator on the photodetector gives an increase in received power of 165% and gives an increase in the value of the SNR of 59%. It can be concluded that the addition of optical concentrator results in better performance.
Vehicle Parameter Identification and its Use in Control for Safe Path Following

This thesis develops vehicle parameter identification algorithms, and applies identified parameters to a controller designed for safe path following.A tire-road friction coefficient is estimated using an in-tire accelerometer to measure acceleration signals directly from the tires. The proposed algorithm first determines a tire-road contact patch with a radial acceleration profile.The estimation algorithm is based on tire lateral deflections obtained from lateral acceleration measurements only inside the contact patch. A new model is derived for the lateral deflection profiles, which provides robustness to orientation-variation of the accelerometer body frame during tire rotation.A novel algorithm is developed to identify three inertial parameters: sprung mass, yaw moment of inertia, and longitudinal position of the center of gravity. A correlation of inertial parameters is derived and is used for the identification algorithm.Inertial parameters and vehicle states are simultaneously estimated with a dual unscented Kalman filter based on a nonlinear vehicle model.In order to activate and de-activate different modes of the proposedalgorithm, a local observability analysis is performed with the nonlinear vehicle model.The performance and robustness of the proposed approach are demonstrated with extensive CarSim simulations and experimental tests on a flat road with a constant tire-road friction coefficient.Following a curved road can be dangerous if autonomous vehicles do not take roll motion into consideration.A control algorithm is designed to prevent a dangerous vehicle state induced by roll motion while following a curved road.Roll motion is suppressed throughout cornering with model predictive control.A four-wheel nonlinear vehicle model with roll dynamics and a tire brush model are utilized for the prediction of the vehicle state. An optimal balance in the trade-off between vehicle speed androll motion is achieved with full braking as a control actuator. Identified vehicle inertial parameters are incorporated into the designed controller.CarSim simulations illustrate the performance of the proposed controller and the effect of the vehicle parameter estimator.
Plasmonic sensor with self-reference capability based on functional layer film composed of Au/Si gratings

We propose a simple one-dimensional grating coupling system that can excite multiple surface plasmon resonances for refractive index (RI) sensing with self-reference characteristics in the near-infrared band. Using theoretical analysis and the finite-difference time-domain method, the plasmonic mechanism of the structure is discussed in detail. The results show that the excited resonances are independent of each other and have different fields of action. The mode involving extensive interaction with the analyte environment achieves a high sensitivity of 1236 nm/RIU, and the figure of merit (FOM) can reach 145 RIU−1. Importantly, the mode that is insensitive to the analyte environment exhibits good self-reference characteristics. Moreover, we discuss the case of exchanging the substrate material with the analyte environment. Promising simulation results show that this RIsensor can be widely deployed in unstable and complicated environments