Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Efficiency and Total Factor Productivity of Turkey: A Comparative Analysis

Turkiye’nin enerji verimliligi ve etkinliginin, OECD ulkeleri orneklemi icinde karsilastirmali olarak olculmesi amaclanan bu calismada, Veri Zarflama Analizi cercevesinde Super Etkinlik Modeli ve Istenmeyen Cikti Modeli ile Turkiye’nin ekonomi duzeyinde teknik etkinligi olculmus, Malmquist endeksi yardimiyla Turkiye’nin toplam faktor verimliligindeki degisme analiz edilmistir. Turkiye ithal ettigi enerjiyi de diger uretim faktorleri ile birlikte etkin kullanamadigi sonucuna ulasilmistir. Turkiye’nin kullandigi enerjide agirligin fosil yakitlarda olmasi CO2 saliniminin da fazla olmasina neden olmaktadir. Model sonuclari cercevesinde Turkiye’nin ekonomisinin yapisi ile ilgili onemli bulgular ortaya cikmaktadir. Bu cercevede niteliksiz emek, nukleer eksikligi, enerji guvenligi, enerji guvenligi baglaminda da temiz enerji on plana cikmaktadir. Hizla artan enerji ihtiyaci goz onune alindiginda; yerli kaynaklarin degerlendirilmesini saglayacak, Turkiye kosullarina uygun, dunyada enerji alanindaki gelismeleri takip eden, uzun vadeli sosyal, ekonomik ve cevresel politikalari bir arada ele alan bir enerji politikasina ihtiyac duyuldugu sonucuna ulasilmistir
Exploring Macroscopic and Microscopic Fluctuations of Elicited Facial Expressions for Mood Disorder Classification

In the clinical diagnosis of mood disorder, a large proportion of patients with bipolar disorder (BD) are misdiagnosed as having unipolar depression (UD). Generally, long-term tracking is required for patients with BD to conduct an appropriate diagnosis by using traditional diagnosis tools. A one-time diagnosis system for facilitating diagnosis procedures is thus highly desirable. Accordingly, in this study, the facial expressions of patients with BD, patients with UD, and healthy controls elicited by emotional video clips were used for conducting mood disorder classification; the classification was performed by exploring the temporal fluctuation characteristics among the three groups. First, macroscopic facial expressions characterized by action units (AUs) were applied for describing the temporal transformation of muscles. Modulation spectrum analysis was applied to extract short-term intensity variations in the AUs. An interval-based multilayer perceptron (MLP) neural network was then used to classify mood disorder on the basis of the detected AU intensities. Moreover, motion vectors (MVs) were employed to describe subtle changes in facial expressions in the microscopic view. Eight basic orientations of MV change were considered for representing microfluctuation. Wavelet decomposition was then applied to extract entropy and energy features in different frequency bands. A long short-term memory model was finally used to model long-term variations for conducting mood disorder classification. A decision-level fusion approach was conducted on the combined results of macroscopic and microscopic facial expressions. For evaluating the described methods, the facial expressions elicited from the 36 subjects (12 from each of the BD, UD, and control groups) were used in 12-fold cross-validation experiments. Approaches for macroscopic and microscopic expressions achieved classification accuracies of 63.9 and 66.7 percent, respectively, and the accuracy of the fusion approach reached 72.2 percent. The results indicate that macroscopic and microscopic view descriptors are complementary to each other and helpful for conducting mood disorder classification.
Flow Kinetics of Molten Silicates through Thermal Barrier Coating: A Numerical Study

Infiltration of molten calcium–magnesium–alumina–silicates (CMAS) through thermal barrier coatings (TBCs) causes structural degradation of TBC layers. The infiltration kinetics can be altered by careful tailoring of the electron beam physical vapor deposition (EB-PVD) microstructure such as feather arm lengths and inter-columnar gaps, etc. Morphology of the feathery columns and their inherent porosities directly influences the infiltration kinetics of molten CMAS. To understand the influence of columnar morphology on the kinetics of the CAMS flow, a finite element based parametric model was developed for describing a variety of EB-PVD top coat microstructures. A detailed numerical study was performed considering fluid-solid interactions (FSI) between the CMAS and TBC top coat (TC). The CMAS flow characteristics through these microstructures were assessed quantitatively and qualitatively. Finally, correlations between the morphological parameters and CMAS flow kinetics were established. It was shown that the rate of longitudinal and lateral infiltration could be minimized by reducing the gap between columns and increasing the length of the feather arms. The results also show that the microstructures with long feather arms having a lower lateral inclination decrease the CMAS infiltration rate, therefore, reduce the CMAS infiltration depth. The analyses allow the identification of key morphological features that are important for mitigating the CMAS infiltration.
LISE/M - A Modernised and Unified Modular Experiment Control System for HZB Beamlines

After more than 15 years of stable operation it was time to develop a new standard experiment control and data acquisition system for HZB beamlines. The aim is to create a modular system based on commercial hardware components. Because of the convincing hardware interfacing and good experience with PXI devices we choose this as hardware platform and LabVIEW as software development system. Starting in late 2015, we developed a framework with modules for configuration, (scan) processing, device communication, logging etc. The user interface is bisected as (i) graphical and (ii) scripting version. Where the ’included’ script engine is python. The system serves both, standard commissioning tools as well as specialised instrument setups. It is integrated into the metadata catalouge system (ICAT) of the HZB in terms of collecting log and meta data and storing those according to the data policy of the institute [1]. We present an overview of the system features in general and a specific instrument view of a rather complex beamline at HZB.
Reconfiguration optimization for nonvolatile memories based field programmable gate arrays

Field Programmable Gate Arrays (FPGAs) are programmable logic blocks based circuit devices, which can be configured to different logic functions due to various demands. Compared with application-specific integrated circuits (ASICs), FPGAs are able to deliver much lower non-recurring engineering costs and much shorter time-to-market of product. As time goes by, the popularity of FPGAs increases due to the super flexibility of configurable soft logic. The recent trends toward wide appliance of the coarse-grained architectural approach that combines FPGAs with microprocessors cores and uses FPGAs as accelerators or co-processors, make FPGAs even more indispensable. Traditionally the manufacturing of FPGAs is based on static random-access memory (SRAMs) technology. As the transistor feature size goes down to the deep-nano scale (less than 20nm), the drawbacks of SRAM are exposed explicitly such as high leakage power and limited scalability. SRAMs are also unreliable since the logic information would be lost if the power supply is off. Non-volatile memories (NVMs) outperform traditional SRAMs regarding low power consumption, high capacity, near-zero power-on delay, and high error-resistance. Researchers have demonstrated the possibilities of implementing FPGA building blocks with various types of NVMs. However, using NVMs also brings several new design challenges to FPGAs: the slow and energy-hungry write operations of NVM may degrade FPGA (re) configuration speed and power efficiency, while the limited write endurance of NVM constrains the number of times that the FPGA can be (re)configured, leading to quite short device lifetime. Unfortunately, none of these NVM features is taken into consideration in current FPGA synthesis flows, which are optimized solely for SRAM-FPGAs. To qualify NVM-FPGA deployment, FPGA synthesis flow should be optimized and tuned to take NVM characteristics into consideration.
Survival disparities in patients with relapsed core-binding factor acute myeloid leukemia following allogeneic hematopoietic stem cell transplantation

Relapse rate of core-binding factor (CBF) acute myeloid leukemia (AML) is higher than expected. In attempts to investigate the role of hematopoietic stem cell transplantation (HSCT) as post-remission therapy for relapsed CBF-AML patients in second remission (CR2), we have conducted this study. This was a single-center retrospective study of relapsed de novo CBF-AML patients over 18 years old undergoing HSCT at CR2 between January 2000 and December 2015. Forty-two patients were divided into 2 groups according to their cytogenetics: 24 in t(8;21) group and 18 in inv(16)/t(16;16) group. When cytogenetic profiles at relapse were compared to those at diagnosis, changes in chromosomal/karyotype abnormalities were observed in 66.7% and 25% of patients with t(8;21) and inv(16)/t(16;16) (P = 0.002). t(8;21) patient relapsed more often compared to inv(16)/t(16;16) patients (P = 0.007) and this translated into shorter overall survival for t(8;21) patients with 30.6% 3-year survival rate after HSCT, compared to inv(16)/t(16;16) patients with 3-year survival rate at 64.5% (P = 0.041). The initial cytogenetics and first remission duration were identified as prognostic factors affecting survival. Among relapsed CBF-AML patients undergoing HSCT, those with t(8;21) are associated with worse prognosis compared to those with inv(16)/t(16;16) and this has to do with failure to achieve durable response with HSCT.
Performance of CDMA system using Antenna Arrays with Power Control Error in a Rayleigh Fading

Antenna arrays have been recognized by most fourth generation CDMA systems proposals as a way to enhance the capacity and system coverage by effectively combating multipath fading and mitigating co-channel interference. The multiple access interference (MAI) problems can be overcome by power control by the process so that the average received power at base station is same for each user. The paper introduces a new approach to outage probability analysis of prediction maximal ratio combining (MRC) diversity reception in Rayleigh fading channels. The analysis joins several of the most important factors affecting the performance of CDMA systems; including path loss, large-scale fading (shadowing), small-scale fading (Rayleigh fading), and co-channel interference (CCI) as well as for correcting mechanisms such as power control error (compensates for path loss and shadowing), spatial diversity (mitigates against Rayleigh fading), and voice activity gating (reduces CCI). We show that by controlling the power level of a user at the output of the diversity combiner (MRC) and imposing the condition that a user does not transmit when in a deep fade; the average inter-cell interference level of the system is significantly reduced. As a result of this reduction, we demonstrate analytically that the outage capacity of the system is improved more than linearly with increasing number of antenna elements.
a new enterprise scale software system for the analysis of the biological data

-In this paper, we propose a new software system design for the analysis and processing of the biological data, namely the sequence data and the microarray gene expression profiles. The efficiency and reliability requirements of the biological signal processing environment along with the interoperability and portability of the components constitute the system have imposed a limitation on the selection of the software tools and the underlying architecture of the system. We have also employed a number of state-of-the-art statistical signal processing algorithms to rather discover the underlying biological processes in the microarray gene expression experiments. On the other hand, due to the overwhelming nature of the biological signals it was also required to build a grid of loosely coupled software services to carry out the most computationally intensive bioinformatics algorithms. Moreover, we have also implemented a web interface to facilitate the use of our system.
COMPARISON OF DIFFERENT GRANULATION TECHNIQUES FOR LACTOSE MONOHYDRATE

The objective of this study was directed to improve the physical and technical properties of poorly flowing and highly cohesive Lactose monohydrate to solve the most important problem that affects tablet manufacture. To overcome all the problems related to lactose granulation is required. Granulation is one of the most important unit operations in the production of pharmaceutical oral dosage forms. Granulation process will improve flow and compression characteristics, reduce segregation, improve content uniformity, and eliminate excessive amounts of fine particles. The results will be improved yields, reduced tablet defects, increased productivity. Pharmaceutical products are processed all over the world using the direct-compressing, wet-granulation, or dry granulation methods. Which method is chosen depends on the ingredients individual characteristics and ability to properly flow, compresses, eject, and disintegrate. Then the proper granulation process can be applied. The objective of present article was to focus on the best possible granulation technology that gives good results based on evaluation of different granule properties, namely the Carr’s index, Hausner’s index, Angle of repose, were evaluated for granule prepared by different binders and different techniques. Finally, the tabletting process showed low values of ejection forces, good tablet properties (weight uniformity, hardness, friability, and disintegration) indicating good compressibility of the prepared granules using Fluidized Bed Processor (HPMC 2.5% as binder) and Coprocessing of Lactose.
Dynamic modeling and experimental validation of skid-steered wheeled vehicles with low-pressure pneumatic tires on soft terrain

Wheeled skid-steered technology has an increasing interest in its use for off-road unmanned ground vehicles, because of its great mobility and compact mechanical structure. By integrating multibody dynamics model and semi-empirical tire-terrain model, this paper presents a dynamic modeling approach for skid-steered wheeled vehicles with low-pressure pneumatic tires on soft terrain to predict and investigate its steering performance. The forward dynamics equations are built by spatial vector algebra. The tire–terrain model estimates flexible deformation and sinkage of the tire, and calculates forces and torques exerted on the tire according to relative motions of tire–terrain contact. The combined longitudinal slip and lateral skid of tires, and the vertical coupled deformations of tires and terrain are also considered in tire-terrain model. This approach optimizes the solution procedure and improves the computing efficiency. The simulation results show that the proposed tire–terrain model can predict the effects of rigid and flexible operation modes of tires on mechanical properties of tires and steering performances of the vehicle. The proposed dynamic model is validated on a six-wheeled skid-steered vehicle. The comparisons between experimental results and simulations show that the proposed dynamic model provides a better accuracy of steering performance simulation for skid-steered vehicles.
Translation of Sentence Lampung-Indonesian Languages with Neural Machine Translation Attention Based Approach

In this research, automatically Lampung language translation into the Indonesian language was using neural machine translation (NMT) attention based approach. NMT, a new approach method in machine translation technology, that has worked by combining the encoder and decoder. The encoder in NMT is a recurrent neural network component that encrypts the source language to several length-stable vectors and the decoder is a recurrent neural networks component that generates translation result comprehensive. NMT Research has begun with creating a pair of 3000 parallel sentences of Lampung language (api dialect) and Indonesian language. Then it continues to decide the NMT parameter model for the data training process. The next step is building NMT model and evaluate it. The testing of this approach has used 25 single sentences without out-of-vocabulary (OOV), 25 single sentences with OOV, 25 plural sentences without OOV, and 25 plural sentences with OOV. The testing translation result using NMT attention shows the bilingual evaluation understudy (BLEU) an average value is 51, 96 %.
A Coupled Insulin and Meal Effect Neuro-Fuzzy Model for The Prediction of Blood Glucose Level in Type 1 Diabetes Mellitus Patients.

Abstract Diabetes Mellitus is a metabolic disorder that affects the ability of the human body to properly utilize and regulate glucose. It is pervasive world-wide yet tenuous and costly to manage. Diabetes Mellitus is also difficult to model because it is nonlinear, dynamic and laden with mostly patient specific uncertainties. A neuro-fuzzy model for the prediction of blood glucose level in Type 1 diabetic patients using coupled insulin and meal effects is developed. This study establishes that the necessary and sufficient conditions to predict blood glucose level in a Type 1 diabetes mellitus patient are: knowledge of the patient’s insulin effects and meal effects under diverse metabolic scenarios and the transparent coupling of the insulin and meal effects. The neuro-fuzzy models were trained with data collected from a single Type 1 diabetic patient covering a period of two months. Clarke’s Error Grid Analysis (CEGA) of the model shows that 87.5% of the predictions fall into region A, while the remaining 12.5% of the predictions fall into region B within a four (4) hour prediction window. The model reveals significant variation in insulin and glucose responses as the Body Mass Index (BMI) of the patient changes.
Framing Effect and Financial Wellbeing: Role of Investment Behaviors as Mediator

Based on the premise that human beings are not rational agents and are frame dependent while making investment decisions, this study has found a significant impact of framing effect on investment behaviors and financial wellbeing. Structural Equation Modelling is employed in Stata, on the data collected from 344 respondents from Pakistan (299 salaried persons and 45 businessmen), having more than three years’ experience. We supported the view of behavioral finance that framing effect could influence the financial wellbeing negatively. We extended the analysis further by validating the mediating role of investment behaviors between framing effect and financial wellbeing, which is a contribution to the body of knowledge in the field of behavioral finance.
Small volume asymptotics for anisotropic elastic inclusions

We derive asymptotic expansions for the displacement at the boundary of a smooth, elastic body in the presence of small inhomogeneities. Both the body and the inclusions are allowed to be anisotropic. This work extends prior work of Capdeboscq and Vogelius (Math. Modeling Num. Anal. 37, 2003) for the conductivity case. In particular, we obtain an asymptotic expansion of the difference between the displacements at the boundary with and without inclusions, under Neumann boundary conditions, to first order in the measure of the inclusions. We impose no geometric conditions on the inclusions, which need only be measurable sets. The first-order correction contains a moment or polarization tensor $\mathbb{M}$ that encodes the effect of the inclusions. We also derive some basic properties of this tensor $\mathbb{M}$. In the case of thin, strip-like, planar inhomogeneities we obtain a formula for $\mathbb{M}$ only in terms of the elasticity tensors, which we assume strongly convex, their inverses, and a frame on the curve that supports the inclusion. We prove uniqueness of $\mathbb{M}$ in this setting and recover the formula previously obtained by Beretta and Francini (SIAM J. Math. Anal., 38, 2006).
The relationship between tourism involvement, organizational commitment and organizational citizenship behaviors in the hotel industry

Purpose – Due to the important role of hotel frontline employees in the service encounter, hotel firms strive to understand factors influencing frontline employees’ working attitudes and behaviors. The main purpose of the current study is to enrich this understanding by examining the interrelationships among tourism involvement, organizational commitment and organizational citizenship behaviors (OCBs). Design –Based on the recovery theory, tourism involvement was hypothesized to influence both organizational commitment and OCBs. Committed employees were hypothesized to be more likely to perform OCBs. The current study further hypothesized a mediating role of organizational commitment in the relationship between tourism involvement and the OCBs. Methodology –Measurements of tourism involvement, organizational commitment, and the OCBs were developed. A total of 336 frontline employees from 20 international hotels in Taiwan voluntarily participated in the current study. Their responses were examined by using independent t -tests, confirmatory factor analyses, and structural equation modelling. Findings –The outcomes demonstrate that tourism involvement positively influenced organizational commitment. Both tourism involvement and organizational commitment positively influenced the OCBs. The organizational commitment was found to be a mediator between tourism involvement and the OCBs. Originality of the research –The most extant studies examined factors influencing the development of organizational commitment and the OCBs by using work-related variables. However, they ignored contributions made by tourism to employees’ work life. The originality of the current study is the link of the non-work variable to work-related attitude and behavior. As such it provides a new insight to managing tourism human resources.
RDF triple processing methodology for the recommendation system using personal information

In this paper, we design and implement the personalized recommend system that provides more semantic information to users using the RDF triples and personal information. The system consists of the data storage, information search module, document collection module, data merge module and recommend module. These new modules are different from the existing modules that have been using in the current Web. These new modules are suitable for the semantic Web environment. Especially, in this paper, we focus on the RDF that is one of the ontology languages. And all modules are newly designed for processing the RDF triple. Finally, we have the test to give the necessity of our study in the virtual semantic Web environment.
A Bibliometric Study on Learning Analytics

s, titles, and keywords of the learning analytics published documents to create the clustering analysis. The document citations and word frequently give meaning to the analysis of the data (Chu 1991). The MDS twodimensional map and the Kruskal’s S-Stress value was used to interpret the stress. Citation analysis was used to classify the knowledge structures and create a taxonomy of the 2730 research documents identified in the dataset (Figure 19).
Environmental Sustainability and Social Responsibility as new corporate strategic drivers: a proposal for an accounting evaluation by the Polied(ro) research project

: Aim and topic of the paper is to formulate a theoretical model for an accounting evaluation applied to environmental sustainability and social responsibility, that the present international crisis shows as two new corporate strategic drivers. To achieve this goal the paper presents an approach that follows an Italian research project entitled POLIED(RO): the study tries to accommodate the main suggestions of the International Accounting Standards and the final result tries to propose a model oriented towards the overcoming of the neutrality between the traditional accounting values and those derivable from social and environmental reports realised by the corporate system.