Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of SSP Based on Lab Work toward Science Process Skills of Students

This research aimed to find the influence of Science Process Skills between a subject spesific pedagogy (SSP) based on elaborative lab work group with the one, a SSP based on conventional lab work in the IX grade of SMPN 2 Tolitoli. It was quasi-experimental study using non equivalent control group design. Two classes were chosen by random sampling techniques, and each class consists of 31 students. The data of science process skills (SPS) that obtained through observation sheets were analyzed by descriptive analysis techniques on significance of 5%. The result showed that the significance was less than 0,005. It can conclude that the application of SSP during teaching and learning process of Science based on the elaborative lab work has significant influence on SPS of the students, compared with the conventional ones. It reinforced by the criteria of SPS improvement, for the experimental class in 0,5 (medium category) and 0,1 (low category) for the control class. Kata Kunci: Subject spesific pedagogy, Lab work, Science process skills How to Cite: Djufri, E. , & Wilujeng, I. (2017). The influence of science subject spesific pedagogy (SSP) of lab work-based toward science process skills of students at SMPN 2 Tolitoli. Jurnal Pendidikan Matematika dan Sains, IV(2), 27-35. doi:http://dx.doi. org/10.21831/jpms.v4i1. 10111 Permalink/DOI: DOI: http://dx.doi. org/10.21831/jpms.v4i1. 1011
Market Reaction to Regulatory Merger Announcements : Operating Synergies and Certification Value

We analyze the post-merger operating performance of FDIC-assisted bank mergers (regulatory mergers). We find that regulatory merger combinations experience significant improvements in both profitability and cost efficiency up to two years following the merger transaction. In contrast, over the equivalent 2-year period, the post-merger performance of acquirers in non-regulatory mergers is not significantly different from the performance of their non-merger peer group. In addition, we examine the reaction of the market to regulatory merger announcements. We find that the common shares of regulatory acquirers experienced significant positive abnormal returns (average of 3.53%) on the day of the merger announcement and the following day (Days 0 and 1). Measuring the abnormal returns separately for first-time auction participants and repeat participants produces 4.33% and 2.44% abnormal returns respectively. Further, we examine the market reaction to the announcement of the list of unsuccessful bidders and find that first time failed bank auction bidders, without actually winning the bid, still experienced on average 1.41% abnormal return during the 2-day event window (Days 0 and 1). These results suggest that an invitation by the FDIC to a bank to participate in the auction creates “Certification Value” for the participant. Overall, we find that regulatory merger announcements are followed by significant positive market reactions and these reactions are the results of operating synergies and certification effects.
Capital asset pricing model with fuzzy returns and hypothesis testing

Over the last four decades, several estimation issues of the beta have been discussed extensively in many articles. An emerging consensus is that the betas are time-dependant and their estimates are impacted by the return interval and the length of the estimation period. These findings lead to the prominence of the practical implementation of the Capital Asset Pricing Model. Our goal in this paper is two-fold: After studying the impact of the return interval on the beta estimates, we analyze the sample size effects on the preceding estimation. Working in the framework of fuzzy set theory, we first associate the returns based on closing prices with the intraperiod volatility for the representation by the means of a fuzzy random variable in order to incorporate the effect of the interval period over which the returns are measured in the analysis. Next, we use these fuzzy returns to estimate the beta via fuzzy least square method in order to deal efficiently with outliers in returns, often caused by structural breaks and regime switches in the asset prices. A bootstrap test is carried out to investigate whether there is a linear relationship between the market portfolio fuzzy return and the given asset fuzzy return. Finally, the empirical results on French stocks suggest that our beta estimates seem to be more stable than the ordinary least square (OLS) estimates when the return intervals and the sample size change. Key-words: CAPM ; Beta; Fuzzy least squares; Bootstrap hypothesis testing; Intraperiod volatility. ∗Corresponding author. LAMETA Université de Montpellier I, UFR d’Economie Avenue Raymond DUGRAND Site de Richter C.S. 79606 34960 MONTPELLIER CEDEX 2 France, Courriel: sadefo@lameta.univmontp1.fr, jules.sadefo-kamdem@univ-montp1.fr
Virtual reality for pain and anxiety management in children.

Question Pain and anxiety are common in children who need procedures such as administering vaccines or drawing blood. Recent reports have described the use of virtual reality (VR) as a method of distraction during such procedures. How does VR work in reducing pain and anxiety in pediatric patients and what are the potential uses for it? Answer Recent studies explored using VR with pediatric patients undergoing procedures ranging from vaccinations and intravenous injections to laceration repair and dressing changes for burn wounds. Interacting with immersive VR might divert attention, leading to a slower response to incoming pain signals. Preliminary results have shown that VR is effective, either alone or in combination with standard care, in reducing the pain and anxiety patients experience compared with standard care or other distraction methods.
An empiriCAl AnAlysis of tHe Annuity rAte

Empirical analyses of annuities markets have been limited to a few developed countries and restricted by data limitations. Chile provides excellent conditions for research on annuities due to the depth of its market and the availability of data. The paper utilizes a panel of life insurance company data to examine econometrically the main determinants of the annuity rate, defined as the internal rate of return on annuities. The results indicate that the annuity rate is determined by the risk-free interest rate, the share of privately-issued higher yield securities in the portfolio of providers, as a proxy for the spread over the risk-free rate, the leverage of providers, the level of broker’s commissions, the market share of individual providers, the level of the premium, and the degree of market competition. The results also show that efforts to improve market transparency produced structural shifts in the parameters of the annuity rate equation. The results are consistent with separate research on money’s worth ratios, and indicate the need to develop appropriate financial instruments, allowing providers to hedge their risks while extracting higher returns, and also to ensure competition and transparency in annuities markets, in order to ensure good outcomes for annuitants.
Methylation-sensitive enrichment of minor DNA alleles using a double-strand DNA-specific nuclease

Abstract Aberrant methylation changes, often present in a minor allelic fraction in clinical samples such as plasma-circulating DNA (cfDNA), are potentially powerful prognostic and predictive biomarkers in human disease including cancer. We report on a novel, highly-multiplexed approach to facilitate analysis of clinically useful methylation changes in minor DNA populations. Methylation Specific Nuclease-assisted Minor-allele Enrichment (MS-NaME) employs a double-strand-specific DNA nuclease (DSN) to remove excess DNA with normal methylation patterns. The technique utilizes oligonucleotide-probes that direct DSN activity to multiple targets in bisulfite-treated DNA, simultaneously. Oligonucleotide probes targeting unmethylated sequences generate local double stranded regions resulting to digestion of unmethylated targets, and leaving methylated targets intact; and vice versa. Subsequent amplification of the targeted regions results in enrichment of the targeted methylated or unmethylated minority-epigenetic-alleles. We validate MS-NaME by demonstrating enrichment of RARb2, ATM, MGMT and GSTP1 promoters in multiplexed MS-NaME reactions (177-plex) using dilutions of methylated/unmethylated DNA and in DNA from clinical lung cancer samples and matched normal tissue. MS-NaME is a highly scalable single-step approach performed at the genomic DNA level in solution that combines with most downstream detection technologies including Sanger sequencing, methylation-sensitive-high-resolution melting (MS-HRM) and methylation-specific-Taqman-based-digital-PCR (digital Methylight) to boost detection of low-level aberrant methylation-changes.
Impact of Different Factors in Creation of Word of Mouth at Hospitality Industry

Few empirical studies have been conducted to explore what motivates and demotivates customers to engage in word of mouth (WOM) activities in the restaurant industry. This research paper inspects the connection between different attributes of hospitality industry which lead to the creation of word of mouth. A self-administered questionnaire was used to collect. 200 respondents from one of the leading and famous university of Pakistan is used as a sample to study on. To test the proposed model, we use structural equation modelling. The research ended with two major findings. First, food quality and service quality have great impact on creation of WOM. Second, price and atmosphere does not have any impact in creation of word of mouth.
The Study on the Effect of University Faculties' Job Stress on Organizational Commitment

In recent years, the role of university faculty is more and more important, and multiple job responsibilities made faculty’s job more demanding and stressful. Under high performance pressure, faculty turnover rate is always high, and it has detrimental effects on the development of university. However, research on the effect of university faculty’s job stress on organization commitment is rarely, this study takes job burnout and job engagement, in to the research framework, constructs job stress-organizational commitment conceptual model, and takes university faculties from Ningbo as an example to examine this model. The results show that: (1) job stress has significant negative effect on organizational commitment; (2) job stress has significant negative effect on job engagement; (3)job engagement has significant positive effect on organizational commitment, and job burnout has significant negative effect on organizational commitment. Keywords—Job Stress; Job Engagement; Job Burnout; Organizational Commitment
Monetary Policy under Bounded Rationality

This paper studies effects of monetary policy under bounded rationality when agents confront uncertainty in model parameters. The model we use in this paper is a version of the New Keynesian model with an IS-Phillips curve as was used in Christiano, Tranbandt, and Walentin (2011). We consider two additional elements of the model that characterize the environment of uncertainty: (i) private agents form forward looking expectations via adaptive learning in the presence of parameter uncertainty, and (ii) the central bank that conducts monetary policy confronts uncertainty about working capital channel. In the presence of parameter uncertainty the central bank adopts two approaches for conducting monetary policy: robust control and feedback control (Bayesian updating algorithm). We study how these two approaches are implemented in an environment of bounded rationality. Also, we evaluate three different policy schemes, policy under rational expectation (perfect information), policy based on the robust control, and policy based on the feedback (Bayesian) control, by examining which policy achieves better outcome for economic stability. Our quantitative analysis shows that the robust control policy achieves the best result under discretion. However, the robust control policy shows the worst performance under commitment. Also, for policies based on perfect information and the feedback control under commitment outperform those under discretion.
A Study on Theoretical Nano Forces in AFM Based Nanonmanipulation

As it is important to understand the basic mechanics principle in nanofabrication process, much research has been done about nano mechanics with different tools in different nano enviroments, and various kinds of nano force formula have been proposed. However, as the special case of AFM based nanomanipulation is considered, little about its mechanics principle under the micro probe's operation is known, such as what kinds of nano forces are the decisive factors and how they work, which are important to perform accurate control in nanomanipulation. To explore this subject, nano forces among tip, substrate and particle are analyzed, and simulation & experiments are performed to verify the rationality of the analysis.
Spillovers through Imports and Absorptive Capacity in Turkey

In R&D based endogenous growth framework, due to the increase of technological capacity by reverse engineering, learning by doing and imitation effects, the interaction of developing countries with outside world will lead economic growth together with productivity increases through observing and utilizing new and more variety of intermediate and capital goods. The aim of this study is to examine the technological knowledge spillovers through imports within the frame of absorptive capacity for Turkish Manufacturing Industry. Departing from the assumption that the relation between technology spillovers and absorptive capacity is non-linear, threshold regression techniques are employed. The results provide evidence on the existence of international technology spillovers in Turkish Manufacturing Industry. The main finding of threshold regression analyses is that the efficiency of spillovers is differentiated with respect to the industry specific absorptive capacities.
SUBLIMATION-DRIVEN ACTIVITY IN MAIN-BELT COMET 313P/GIBBS

We present an observational and dynamical study of newly discovered main-belt comet 313P/Gibbs. We find that the object is clearly active both in observations obtained in 2014 and in precovery observations obtained in 2003 by the Sloan Digital Sky Survey, strongly suggesting that its activity is sublimation-driven. This conclusion is supported by a photometric analysis showing an increase in the total brightness of the comet over the 2014 observing period, and dust modeling results showing that the dust emission persists over at least three months during both active periods, where we find start dates for emission no later than 2003 July 24 ± 10 for the 2003 active period and 2014 July 28 ± 10 for the 2014 active period. From serendipitous observations by the Subaru Telescope in 2004 when the object was apparently inactive, we estimate that the nucleus has an absolute R-band magnitude of HR = 17.1 ± 0.3, corresponding to an effective nucleus radius of re ∼ 1.00 ± 0.15 km. The object’s faintness at that time means we cannot rule out the presence of activity, and so this computed radius should be considered an upper limit. We find that 313P’s orbit is intrinsically chaotic, having a Lyapunov time of Tl = 12,000 yr and being located near two three-body mean-motion resonances with Jupiter and Saturn, 11J-1S-5A and 10J+12S-7A, yet appears stable over >50 Myr in an apparent example of stable chaos. We furthermore find that 313P is the second main-belt comet, after P/2012 T1 (PANSTARRS), to belong to the ∼155 Myr old Lixiaohua asteroid family.
Exploration of cuing methods for localization of spatial cues using thermal haptic feedback on the forehead

Haptic feedback systems for spatial awareness are widely used in navigational and obstacle detection tasks and mostly used in combination with vibrotactile modules. As such, this work explores using thermal haptic feedback on the forehead for spatial awareness. As an initial step in this direction, our goal is to investigate the performance of different cueing methods for a minimal number of thermal elements. As such, the system uses three equally distributed peltier modules on the forehead to provide the thermal feedback. We investigated three different cuing methods with 30, 150 and 450 effective haptic feedback ranges. The results indicate that the 30 method to be the most precise (lowest error) while the 450 method to be the fastest for detecting the target.
Reforming Employment Protection in Egypt: An Evaluation Based on Transition Models with Measurement Errors

Do reforms introducing more flexibility in developing countries’ labor markets reduce unemployment? This paper proposes to evaluate the new Egyptian labor market law, which was introduced in 2003, aiming to enhance the flexibility of the hiring and the firing processes. The Egypt labor market panel surveys (ELMPS 2006 and ELMPS 2012) are used to measure the impact of this reform on the dynamics of separation and job finding rates, and to quantify their contributions to overall unemployment variability. Using synthetic panel data created from the retrospective accounts of the 2006 and 2012 cross-sections, and by overlapping the two surveys, we estimate annual and semi-annual transition probabilities of workers among employment, unemployment and inactivity labor market states. A unique and novel model is built to correct for the recall and design bias observed in the retrospective data. Using our “corrected” data, we show that the reform significantly increases the separation rates in Egypt, but leads to non-significant effects on the job finding rates. The combined net effect is therefore an increase in the levels of the Egyptian unemployment rate. By performing counterfactuals analysis, we show evidence of the increasingly dominant role of the job separation rate in accounting for Egyptian unemployment fluctuations.
AN EFFICIENT APPROACH TO DETECT FOREST FIRE USING K-MEDIODS ALGORITHM

Problem Statement: : Clustering high dimensional spatial data for Forest fire risk analysis has been major issue due to sparsity of data points. Most of the clustering algorithm becomes inefficient if the required distance similarity measure is computed for low dimensional spatial space of high dimensional data with sparsity of data point along different dimensions and also considering the obstacles. Objective of this study were to contribute the complexity of projecting clusters for traffic risk analysis, (i) lack of support for reducing the number of dimensions on spatial space to reduce the searching time (ii) the lack of support for obstacles in the spatial data space. (iii) Compare computation time of HARP, Proclus, Doc, FastDoc, SSPC algorithms. Approach: During the first phase the satellite captured still images for different dimensions such as time and location of the forest fire network are enhanced and this images are given as input to red color image separation, During this phase the input images groped based on red color using K-Means algorithm and during the second phase the red color images are converted to gray scale images . The third phase mainly focuses on spatial attribute relevance analysis for detecting dense and sparse forest fire regions after detecting dense and sparse fire regions the algorithm employees pruning technique to reduce the search space by taking only dense fire regions and eliminating sparse fire regions and during fourth phase K-mediods algorithm is employed to project the clusters on different spatial dimensions and also it solves the problem of obstacles Results: First we showed that various projecting clustering algorithm on spatial space becomes inefficient if the number of dimensions increases . The new scheme proposed reduces the spatial dimension space so that it reduces the computation time and also it solves the problem of obstacles using K-mediods algorithim and finally the result is compared with HARP ,Proclus,Doc,FastDoc,SSPC The algorithms produces acceptable results when the average cluster dimensionality is greater than 10%. Conclusion: Hence the findings suggested the overhead reasonably minimized and using simulations, we investigated the efficiency of our schemes in supporting high dimensional spatial clustering for forest fire risk analysis.
Low computational complexity design over sparse channel estimator in underwater acoustic OFDM communication system

The computational complexity required in the channel estimation plays an important role in underwater acoustic communications (UAC) with orthogonal frequency duplex access (OFDM), especially when the channel is sparse. The authors develop an algorithm to carry out the orthogonal matching pursuit (OMP) for the sparse channel estimation based on the compressive sensing, where the goal is to obtain the minimum computational complexity. It is discovered that the inter-carrier interference (ICI) mainly depends on the adjacent subcarriers since the ICI interferences become more and more marginable with the increase of the distance from the other subcarriers to the current desired subcarrier in the frequency domain, which can be utilised to reduce the complexity of the design over the sparse channel estimator. By exploiting this property, the authors propose that the diagonal band of the ICI channel matrix is employed in the calculation of the objective function to minimise the required computational complexity, which develops an adaptive algorithm that is theoretically proved to be a faster algorithm. Numerical simulations are demonstrated for the typical UAC system that the proposed algorithm achieves the remarkable gain of the computational complexity compared to the existing algorithm.
Aalborg Universitet Datasheet-based modeling of Li-Ion batteries

Researchers and developers use battery models in order to predict the performance of batteries depending on external and internal conditions, such as temperature, C-rate, Depth-of-Discharge (DoD) or State-of-Health (SoH). Most battery models proposed in the literature require specific laboratory test for parameterization, therefore a great majority do not represent an appropriate and feasible solution. In this paper three easy-to-follow equivalent circuit modeling methods based only on information contained in a commercial Li-Ion cell manufacturer’s datasheet are presented and validated at steady state, comparing simulation results and manufacturer’s curves. Laboratory results are included in order to demonstrate the accuracy of parameters estimation. Results of each method are presented, compared and discussed for a Kokam SLPB 120216216 53Ah Li-Ion cell.