Miracle-dz/UniFAR-FTUs huggingface dataset:
Analytical Solutions for Simulation of Mathematical Modelling of Liposomal Drug Release to Tumor by Adomian Decomposition Method.

In this paper, the system of partial differential equations of the thermo sensitive liposome-mediated drug delivery model is solved analytically by applied the Adomian decomposition method with the appropriate initial and boundary condition as well. Also, to determine the effectiveness of suggested models, simulated results were in comparison to the corresponding experimental information , and an important agreement was reached . So that a quantitative analysis is finally done by numerical simulation by adopting the values of all typical parameters to clarify the drug concentrations behavior with increasing time in different cases. Keywords: Local drug ; Drug delivery ; cancer stem cells ; Adomian decomposition method ; Different locations.
IoT-Based Unobtrusive Sensing for Sleep Quality Monitoring and Assessment

Aging population is a worldwide trend, which has created a societal crisis as many countries face the challenges of supporting an aging population with increasing costs of healthcare and decreasing numbers of caregivers. Sleep related disorders are common diseases, especially among the elderly. In this paper, we propose a simple and affordable unobtrusive sensing environment including a high-sensitive accelerometer on a bed and passive infrared (PIR) motion sensors in every room, following the generic framework of Internet of Health Things (IoHT) for monitoring the elderly’s sleep-wake conditions, to assess their sleep quality. The environment is nonintrusive, comfortable and can be used for long-term sleep monitoring, detecting early symptoms of sleep related disorders, and responding to caregivers. We implement and pilot test the environment under different daily living situations related to sleep quality. We develop a feature extraction algorithm and applied five popular data analytics models to assess their relative performance. Our study shows that all classifiers except Naïve Bayes can effectively detect sleep quality with the Area under ROC curve (AUC) performance higher than 90%. Among which multilayer feed-forward neural network achieved the best results, in which the detecting sensitivity is up to 96.61%, specificity is 91.81% and AUC performance is 94.21%.
Vibrational fingerprints of tungsten and cobalt based molecules adsorbed on silica surfaces

Tungsten and cobalt carbonyls adsorbed on a substrate are typical starting points for the electron beam induced deposition of tungsten or cobalt based metallic nanostructures. We employ first principles molecular dynamics simulations to investigate the dynamics and vibrational spectra of W(CO)6 and W(CO)5 as well as Co2(CO)8 and Co(CO)4 precursor molecules on fully and partially hydroxylated silica (SiO2) surfaces. Such surfaces resemble the initial conditions of electron beam induced growth processes. We find that both W(CO)6 and Co2(CO)8 are stable at room temperature and quite mobile on a silica surface saturated with hydroxyl groups (OH), moving up to half an Angstroem per picosecond. In contrast, chemisorbed W(CO)5 or Co(CO)4 ions at room temperature do not change their binding site. These results contribute to gaining fundamental insight into how the molecules behave in the simulated time window of 20 ps and our determined vibrational spectra of all species provide signatures for experimentally distinguishing the form in which precursors cover a substrate. PACS numbers: 68.43. -h,68.43. Fg,71.15. Mb,71.15. Nc ar X iv :1 30 6. 25 67 v3 [ co nd -m at . m tr lsc i] 1 9 Ju l 2 01 3 Vibrational fingerprints of tungsten and cobalt based molecules adsorbed on silica surfaces2
Comparison of Subdomain, Complex Permeance, and Relative Permeance Models for a Wide Family of Permanent-Magnet Machines

In terms of analytical models used in the initial motor design, the subdomain (SD), complex permeance (CP), and relative permeance (RP) models are among the main ones. This article presents an analysis and comparison of these three models for a wide family of permanent-magnet (PM) machines. The finite-element models are used as a reference for comparison. The fundamental harmonic of the flux-linkage generated by the PMs is selected to evaluate the precision of the analytical model in the initial design step. The number of slots, PM pole-pairs, and ratio of tooth are selected as the key parameters to generate 749 designs for the test. The error distributions and the relationships between the error and the key parameters in the different analytical models are illustrated in this article. The SD and CP models give the best and worst results, respectively. This article also explains how to select the analytical model for the high-torque-density motors.
A Method of Classifying Railway Sleepers and Surface Defects in Real Environment

Rail transport is an efficient and safe way to move large quantities of goods and people over long distances but it still suffers from maintenance issues, mainly due to assets of great extent, quantity, weight, and geographic dispersion. Because of this, some initiatives in automatic inspection of railway assets have been developed in recent years/in the last decade. In particular, the automatic inspection of railway sleepers still needs improvement and consolidation. This work presents a method for sleepers inventorying, identification of the type and defects based on image processing, heuristics and feature fusion in an unsupervised way. The Haar transform and integral images are used, as well as other image processing techniques such as edge detection, and entropy computation along with aspects of railroad topology. The algorithm was developed using real images of daily railway, previously unclassified, and that were subject to various noises and variations of a real railway operation. The method was validated through experiments with an image set comprising 32,917 sleepers in 10,116 images. The results are promising in which 97% accuracy is reached, for the identification of the type of sleepers, and 93% accuracy for the identification of visible defects in sleepers.
Roadmapping for Data: Concept and Typology of Data-Integrated Smart-Service Roadmaps

Data become critical in the recent business environment, especially in the smart service where value is generation via data analytics to support self-reconfigured, instrumented, interconnected, and intelligent characteristics. Thus, data have been recognized as important assets for planning to ensure a firm's competitiveness. However, the literature is surprisingly sparse in integrating data for the technology roadmap (TRM) which has been widely used to support strategic planning. In response, this article suggests a concept of the data-integrated TRM and proposes relevant structure, typology, and roadmapping process to show how to integrate data into the technology roadmapping. First, types of data integration are defined based on the literature review and practical business cases. Second, the concept and structure of data-integrated TRM are suggested, adding a data layer as an intermediate and functional link for planning corresponding smart services. Third, the typology of data-integrated TRM is also suggested considering types of data integration. Based on the typology, this article also illustrates roadmapping processes for practical examples. An in-depth discussion of the suggested data-integrated TRM is expected to be of high value in terms of practicality in the near future.
An Analysis of Smartphone Security Practices among Undergraduate Business Students at a Regional Public University

In 2019, the number of smartphone users in the United States was estimated to be over 266 million, or 81% of the population. While smartphones, combined with a plethora of apps that are readily available, have become wholly integrated into our daily lives, they embody a multitude of risks for consumers. The purpose of this study is to assess smartphone security practices among undergraduate business students at a regional public university. In December 2019, a survey focusing on security-related practices was administered to students in multiple business classes at the university. The results of the survey show that students exhibit a high degree of care on some measures of security, but they are rather lax in other areas. Males exhibit evidence of some more risky behaviors than their female counterparts. Those who have lost their phones in the past are more likely to be familiar with some disaster preparedness phone features and they are more likely to insure their smartphones.
Price Setting Frequency and the Phillips Curve

We develop a New Keynesian (NK) model with endogenous price setting frequency. Whether a firm updates its price in a given period depends on an analysis of expected cost and benefits modelled by a discrete choice process. A firm decides to update the price when expected benefits outweigh expected cost and then resets the price optimally. As markups are countercyclical, the model predicts that prices are more flexible during expansions and less flexible during recessions. Our quantitative analysis shows that contrary to the standard NK model, the assumed price setting behaviour: is consistent with micro data on price setting frequency; gives rise to an accelerating Phillips curve that is steeper during expansions and flatter during recessions; explains shifts in the Phillips curve associated with different historical episodes without relying on implausible high cost-push shocks and nominal rigidities.
Stable and Accurate Marching-on-in-Time Solvers of Time Domain EFIE, MFIE, and CFIE Based on Quasi-Exact Integration Technique

The development of time-domain integral equation solvers with robust late-time stability properties has been a long-standing quest. Among the many methods that have been investigated, those leveraging quasi-exact integration techniques appear to be most successful. This article presents stable and accurate marching-on-in-time (MOT) solvers for time-domain electric, magnetic, and combined field integral equations (EFIE, MFIE, and CFIE) based on quasi-exact integration techniques. The novel MOT solvers exhibit excellent stability while yielding highly accurate results, as demonstrated by various numerical examples. In addition, the solvers’ excellent stability and accuracy properties are used to examine spurious modes encountered when time-domain integral equations are applied to closed surfaces. It is demonstrated that MOT solutions to the time domain EFIE and MFIE often are polluted by spurious modes at the cavity’s resonant frequencies whereas those of the CFIE solver are devoid of such contamination.
RESPONSABILIDADE SOCIAL: A EXPERIÊNCIA DAS FIRMAS BRASILEIRAS DE ALIMENTOS E BEBIDAS

The objective of this article is to identify the way of understanding social responsibility by the main companies in the food and beverage sector in Brazil, as well as the link between social responsibility and business strategy. As for the research methodology, it is qualitative and descriptive, with bibliographic and documental surveys in corporate websites, with the purpose of knowing the projects and the results of social responsibility actions, which are communicated and made publicly available by the selected companies. The selection criteria of these companies is their positioning in the ranking of the net revenue of the sector. The results indicate that investments in social responsibility are linked to the competitive strategy. However, there are possibilities for improvement, through greater detail of responsible practices and the results of social responsibility projects, making it possible to meet the demand of stakeholders, strengthening reputation and increasing sales and profits in the long term.
LogStore: A Workload-aware, Adaptable Key-Value Store on Hybrid Storage Systems (Extended abstract)

Due to the recent explosion of data volume and velocity, a new array of lightweight key-value stores have emerged to serve as alternatives to traditional databases. The majority of these storage engines, however, sacrifice their read performance in order to cope with write throughput by avoiding random disk access when writing a record in favor of fast sequential accesses. But, the boundary between sequential vs. random access is becoming blurred with the advent of solid-state drives (SSDs). In this work, we propose our new key-value store, Log-Store, optimized for hybrid storage architectures. Additionally, introduce a novel cost-based data staging model based on log-structured storage, in which recent changes are first stored on SSDs, and pushed to HDD as it ages while minimizing the read/write amplification for merging data from SSDs and HDDs. Furthermore, we take a holistic approach in improving both the read and write performance by dynamically optimizing the data layout, such as deferring and reversing the compaction process and developing an access strategy to leverage the strengths of each available medium in our storage hierarchy. Lastly, in our extensive evaluation, we demonstrate that LogStore achieves up to 6x improvement in throughput/latency over LevelDB, a state-of-the-art key-value store.
Prevalence of vitamin D deficiency in HIV/AIDS patients

Objective: To find prevalence of Vitamin D deficiency in HIV/AIDS patients presenting to Jinnah Hospital Lahore. Methodology: This observational cross-sectional study was conducted in Department of Medicine, Jinnah Hospital Lahore for duration of 6 months from November 1, 2016 to April 30, 2017. After taking informed consent, 171 patients aged 20 to 60 years, of both genders, diagnosed as HIV/AIDS for more than 6 months were included in the study. Basic demographic information was recorded, after which 5 ml of blood sample taken and vitamin D levels performed. Data were analyzed using SPSS 20. Vitamin D level was stratified using Chi-Square Test. Results: Out of 171 patients, 78.9% were male and 21.1% were female. Mean age was 30.7+9.2 years. Mean duration of disease was 14.5+8.6 months. Patients belonging to low socioeconomic status constituted 53.8%, middle socioeconomic status 28.1% and 18.1% came from high socioeconomic status. Mean Vitamin D level was 38.6+12.4 nmol/l. Vitamin D deficiency was present in 76.0% while severe Vitamin D deficiency was seen in 9.4%. Age, gender, socioeconomic status and duration of disease were associated significantly with Vitamin D deficiency. Conclusion: Vitamin D deficiency was highly prevalent in patients with HIV/AIDS in our population. We recommend that HIV/AIDS patients should be given Vitamin D supplements in conjunction with antiviral therapy to improve their over-all health and quality of life.
Optimal regenerative braking torque of permanent-magnet synchronous motor in electric vehicles

This study investigated a method to determine the optimal regenerative braking torque with maximum energy recovery at given speed, which is essential for the regenerative braking control of electric vehicles. The method is based on the loss modelling of a permanent-magnet synchronous motor (PMSM) system, which consists of electric motor and inverter. The system-loss model is established based on a PMSM mathematical model including iron loss and is used to derive the optimal regenerative braking torque symbolic formula. In addition, the parameter sensitivity of the optimal regenerative braking torque is analysed and a method for online parameter identification is used to obtain the actual parameter values in real time. Thus, the accuracy and adaptability of the optimal regenerative braking torque during the motor-operation process is improved. The analysis results are validated through simulation and bench tests.
App Popularity Prediction by Incorporating Time-Varying Hierarchical Interactions

App popularity prediction is a significant task in mobile service development, which predicts an app's future popularity based on its current behaviors. It provides benefits from app development to targeted investment. Popularity is affected by two factors, i.e., internal ones like reviews and external ones like interaction among apps. However, most related studies only explore internal factors but neglect external ones. In fact, external factor plays an important role in popularity prediction modelling since it is the promoting and/or inhibiting influence resulted by app interaction. The app interaction has two major characteristics, i.e., interactivity and dynamicity, which brings challenges to app popularity prediction due to two reasons: 1) interactivity—it is hard to evaluate the existence and influence intensity of interactions; 2) dynamicity—the nature of interaction influence, e.g., promoting or inhibiting, and its intensity on popularity change with time. In this paper, we propose DeePOP, a popularity prediction model that innovatively leverages time-varying hierarchical interactions. First, we propose Hierarchical Interaction Graph, which is first studied in this work, to organically characterize the relationship and influence among apps. Second, DeePOP integrates internal factors and time-varying hierarchical interactions as inputs to build the prediction model. It develops multi-level modules based on Recurrent Neural Network with attention mechanism and generates multi-step time series predictions by fusing the outputs of modules. Experiments on a real-world dataset show that DeePOP outperforms state-of-the-art methods in prediction accuracy, effectively reducing the Root Mean Square Error (RMSE) to 0.088.
Assessing The Employees’ Performance In The Hotel Industry

Purpose – The main objective of this paper is to try to evaluate the employees’ work performance and to give an answer to the research question: how good the people, who work in the hotel industry in Croatia, are at what they do. The purpose of this paper is to maintain and improve the hotel industry competitiveness in the context of human capital. Design – The research relies on the primary data as well as on the quantitative methods. Methodology – In order to achieve both the aim and the purpose of the research, numerous scientific methods have been applied, among which the method of questioning while the method of descriptive statistics forms the basis. The employees’ survey (N=452) was carried out along the Adriatic coast in the summer season of 2018. Approach – In order to gain more insight into the work performance of every worker, the self-assessment method has been used. This method measures the employees’ work performance and is based on the data about how the workers assess their work performance themselves and also what they think how their guests, their co-workers and their supervisors would assess their work performance. Findings – Research results show that 87.39% of the employees in the hotel industry believe that they know their job well, while 12.61% of the employees or even every eighth worker is not good enough at what he does. From the total number of people who are good at what they do, 220 of them or 48.67% are confident enough at what they do while 175 of them mostly agree with the statement that they are good at their work. Therefore, the fact that 49.43% of the work force is much less productive is not surprising. 17.03% of the employees have shown to be highly productive and 33.63% have shown average work force productivity. The originality of the research – The results obtained may be very important for managers in both the hospitality industry and the hotel sector, so they could stay focused on the employees’ performance in order to improve the employees’ productivity.
Improving and Controlling Organic Field Effect Transistor Performance through Dual Solvent Processing and Molecular Doping

Solution processed organic electronic devices such as organic field effect transistors (OFETs) show the potential for low cost manufacturing due to their low temperature processing and possible fabrication via inkjet or roll-to-roll processing. However, while OFETs have made strides in performance, they currently remain an emergent technology, and fully organic devices command high consumer prices. Further technological developments that easily and effectively enhance device performance are still needed. This work focuses on processes and techniques that are demonstrated to improve OFET performance and actively control device characteristics. This thesis investigates the improvement of small-molecule/polymer blend OFETs, realized by mixing 6,13-bis(triisopropylsilylethynyl) pentacene (TIPSpentacene) and amorphous polystyrene in solution and fabricating bottom gate/bottom contact devices via a spin coating process. Precise manipulation of substrate conditions, processing parameters, and solvent combinations of these OFETs was undertaken in an effort to improve device performance, specifically transistor mobility. The use of pentafluorobenzenthiol (PFBT) as a self-assembled monolayer (SAM) to modify the source and drain electrodes was also investigated as a way to decrease contact resistance and improve semiconductor crystallinity. It was found that mobility could be increased by almost an order of magnitude via application of a dual-solvent solution that combines a solvent more suited to TIPS-pentacene with another more suited to the polystyrene. This result is examined via the use of atomic force microscopy (AFM) and polarized microscopy, which reveal considerable morphological differences between device films from different solvents. A technique for manipulating the threshold voltage characteristics of OFETs through the use of ultra-low doping of the organic semiconductor solution is also demonstrated. This technique is applied to the dual-solvent transistors and poly[N,N’-bis(4-butylphenyl)-N,N’-bis(phenyl-benzidine)] (poly-TPD) polymer traniii sistors via the addition of very small amounts (less than 0.3% by weight) of the soluble p-dopant molybdenum tris-[1-(trifluoroethanoyl)-2-(trifluoromethyl)ethane1,2-dithiolene] [Mo(tfd-COCF3)3]. Controlled threshold voltage shifting is attained by varying doping concentrations. Further investigation of dopant effects on film characteristics are undertaken on doped TIPS-pentacene using variable temperature current-voltage (VTIV) measurements, where extremely small doping concentrations are found to induce a large increase in conductivity of the organic semiconducting film.
Thermal–oxidative Stability of Commercial Rice Bran Oil

The thermal–oxidative stability of commercially available rice bran oil (RBO) was evaluated at 180 ℃ . Commercial RBO exhibited much higher thermal–oxidative stability than commercial high oleic canola oil in terms of polar components and polymer contents. Moreover, significant prolongation of antioxidants such as tocopherol (Toc) and γ -oryzanol (Ory) was observed for the commercial system during heating compared with the modeled RBO systems, in which Toc and/or Ory were added to physically refined RBO. Excellent thermal–oxidative stability of the commercial RBO system was proved and validated by the combined effect of Toc and Ory and the obvious prolongation of antioxidant activities.
Attitude towards Online Advergame: An Empirical Study among Saudi Consumers

As a result of the increase of computer games and high speed internet connections,in-gameadvertising playsasignificant role in this domain.Advertisers’anticipatethat in-gameadvertisingwill be an important marketing methodthat may enable themto reachtargetedconsumers.Consumers’ attitudes toward in-game advertising, how consumers think about online advertising and the impact of these attitudes on brand image will be investigated in this study. In order to test the attitudes, several factors such as entertainment, customer engagement, andattitude toward advergames in general are included. The outcomesand results will be discussed at the end of this study. Discussion, implications, conclusion, limitations and future studies areto be provided.