Miracle-dz/UniFAR-FTUs huggingface dataset:
The integrating effect of homesickness, attachment and spiritual wellbeing on international students’ mental health in Malaysia

One of the numerous exciting experiences encountered by many young people nowadays is related to the transition linked to studying abroad. Many international students face various psychological and mental health problems. The objectives of this study were to identify the differences in mental health across demographic factors and to determine the relationships between homesickness, attachment and spiritual wellbeing with mental health. Besides, the mediating effects of attachment and spiritual wellbeing on the relationship between homesickness and mental health were examined. Moreover, hierarchical guidelines and a structural model of mental health were developed based on the homesickness, attachment and spiritual wellbeing constructs among international postgraduate students in Malaysia. The survey research was used as research design for this study. Through purposive and quota sampling, 442 international postgraduate students were selected from five public research universities in Malaysia. They were asked to complete a set of validated instrument which included four questionnaires of homesickness, adult attachment, spiritual wellbeing, and general health. The findings confirmed that there were significant differences in mental health according to gender, marital status, level of study and nationality. The results also showed that mental health correlated with homesickness, attachment and spiritual wellbeing. Moreover, it was found that the influence of homesickness on mental health was mediated by attachment and spiritual wellbeing constructs. Mental health guidelines were developed hierarchically based on homesickness, attachment and spiritual wellbeing in three levels to explore the importance of different factors in each construct. Finally, homesickness, attachment and spiritual wellbeing constructs were able to predict mental health by approximately 67 percent. Mental health could also be significantly predicted by the homesickness construct (β = .683, t = 42.538, p<.001), attachment construct (β = .125, t = 5.973, p<.001) and spiritual wellbeing construct (β = .139, t = 8.698, p<.001). Results of this study would be able to help counsellors raise awareness among international students who are studying in foreign countries. In addition, focusing on the guidelines can help administrators and lecturers in promoting good mental health among international students. This research would also contribute to enhancing mental health level among international students by introducing the positive roles of attachment and spiritual wellbeing to help reduce the negative effects of homesickness on mental health that may occur during their stay abroad.
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data

Sketching techniques have become popular for scaling up machine learning algorithms by reducing the sample size or dimensionality of massive data sets, while still maintaining the statistical power of big data. In this paper, we study sketching from an optimization point of view: we first show that the iterative Hessian sketch is an optimization process with preconditioning, and develop accelerated iterative Hessian sketch via the searching the conjugate direction; we then establish primal-dual connections between the Hessian sketch and dual random projection, and apply the preconditioned conjugate gradient approach on the dual problem, which leads to the accelerated iterative dual random projection methods. Finally to tackle the challenges from both large sample size and high-dimensionality, we propose the primal-dual sketch, which iteratively sketches the primal and dual formulations. We show that using a logarithmic number of calls to solvers of small scale problem, primal-dual sketch is able to recover the optimum of the original problem up to arbitrary precision. The proposed algorithms are validated via extensive experiments on synthetic and real data sets which complements our theoretical results.
IEEE 802 . 11-based Wireless LAN Achieving Small Delay Fluctuation

Real-time applications such as phone, videoconference, multimedia streaming, are typical applications which require relatively small delay and small delay fluctuation. To meet the QoS requirements of these applications, network infrastructures should have the ability to accommodate real-time traffic. Recently, IEEE802.11 wireless LANs, fundamentally based on CSMA/CA, have been widely used as parts of network infrastructures, so QoS support in wireless LANs becomes important. Several existing PCF-based centralized control mechanisms can support constant small delay of real-time traffic in a wireless LAN. However, these mechanisms require a centralized controlled coordinator, and cannot be utilized in any case. So, a decentralized control mechanism supporting real-time traffic is an important alternative solution to support real-time traffic. EDCF is a typical example of decentralized control mechanisms which provide relatively small delay for real-time traffic, but cannot achieve small delay fluctuation because of the burst feature of its backoff mechanism. We propose a decentralized control mechanism suppressing delay fluctuation in CSMA/CA networks, called DDFC (Decentralized Delay Fluctuation Control), and examine the performance of DDFC by simulation. The results of simulation confirm that we can achieve not only small delay but also small delay fluctuation in EDCF-based wireless LANs by controlling real-time traffic according to DDFC.
Description of Present State

More than twenty years ago the pioneering paper by Lars Peter Hansen (1982) on the Generalized Method of Moments (GMM) estimation has explicitly formalized idea of many predecessors1. At those days the robust statistics had already nearly twenty years long history, nevertheless the problem of identifying regression model from extensively contaminated data (i. e. containing possibly almost50% of contamination) still waited for solution. Nowadays, the problem is solved not only on the theoretical level (see e. g. Siegel (1982), Rousseeuw (1983), (1984), Hampel et al. (1986) or Rousseeuw, Leroy (1987)) but also the algorithms, reliably and quickly evaluating the estimates, are implemented (not always in a very user-friendly form but nevertheless implemented, Vı́̌sek (1996), (2000 b), Boček, Lachout (1993), Maš́ıček (2004 a)). Nonetheless, the robust statistics haven’t yet profited from GMM approach2, although the hundreds (if not thousands) of econometric papers on GMM estimation having been written, and, vice versa, econometricis regrettably ignored the fact that one “properly” damaged observation may (completely) destroy the identification of (regression) model3. That is why the present proposal is intended as a decent attempt for “improving” the situation. Nearly inevitable consequence will be that the next text will appear trivial from the both points of view, the statistical as well as econometric one. Of course, the part explaining ideas of the GMM estimation is for econometricians simple, and the part discussing reasonability of safeguarding ourselves against data contamination is trivial for people from robust statistics. The explanation of present state will be divided into several parts to reach clarity and lucidity. We shall start, in the second part, with the story of GMM estimation attempting to explain that this approach offers (at least but in fact much more than only) a unified point of view on estimation of the regression model under various situations. The third part recalls the Cragg’s result and shows that it can be interpreted as GMM estimation. The fourth part explains why the Least Weighted Squares may be given the preference before the other (possibly highly) robust methods, recalling the points of a new paradigm of point estimation. In the next part we propose to merge both approaches in order to achieve a method being able to cope with contamination of data as well as with the presence of atypical observations and simultaneously preserving generality of point of view of GMM estimation and all its advantages. Finally, the plan of the research together with schedule on individual years is given.
COMPUTATIONALLY INEXPENSIVE SEQUENTIAL FORWARD FLOATING SELECTION FOR ACQUIRING SIGNIFICANT FEATURES FOR AUTHORSHIP INVARIANCENESS IN WRITER IDENTIFICATION

Handwriting is individualistic. The uniqueness of shape and style of handwriting can be used to identify the significant features in authenticating the author of writing. Acquiring these significant features leads to an important research in Writer Identification domain where to find the unique features of individual which also known as Individuality of Handwriting. This paper proposes an improved Sequential Forward Floating Selection method besides the exploration of significant features for invarianceness of authorship from global shape features by using various wrapper feature selection methods. The promising results show that the proposed method is worth to receive further exploration in identifying the handwritten authorship.
Models of α Centauri A and B with and without seismic constraints: time dependence of the mixing-length parameter

The a Centauri (a Cen) binary system is a well-known stellar system with very accurate observational constraints on the structure of its component stars. In addition to the classical non-seismic constraints, there are also seismic constraints for the interior models of a Cen A and B. These two types of constraint give very different values for the age of the system. While we obtain 8.9 Gyr for the age of the system from the non-seismic constraints, the seismic constraints imply that the age is about 5.6-5.9 Gyr. There may be observational or theoretical reasons for this discrepancy, which can be found by careful consideration of similar stars. The α Cen binary system, with its solar-type components, is also suitable for testing the stellar mass dependence of the mixing-length parameter for convection derived from the binaries of Hyades. The values of the mixing-length parameter for a Cen A and B are 2.10 and 1.90 for the non-seismic constraints. If we prioritize the seismic constraints, we obtain 1.64 and 1.91 for a Cen A and B, respectively. By taking into account these two contrasting cases for stellar mass dependence of the mixing-length parameter, we derive two expressions for its time dependence, which are also compatible with the mass dependence of the mixing-length parameter derived from the Hyades stars. For assessment, these expressions should be tested in other stellar systems and clusters.
Writing Narrative Literature Reviews

Narrative literature reviews serve a vital scientific function, but few resources help people learn to write them. As compared with empirical reports, literature reviews can tackle broader and more abstract questions, can engage in more post hoc theorizing without the danger of capitalizing on chance, can make a stronger case for a null-hypothesis conclusion, and can appreciate and use methodological diversity better. Also, literature reviews can draw any of 4 conclusions: The hypothesis is correct, it has not been conclusively established but is the currently best guess, it is false, or the evidence permits no conclusion. Common mistakes of authors of literature review manuscripts are described.
Memory system compression and its benefits

This paper presents an overall analysis of the redundancy in the information (addresses, instructions, and data) stored and exchanged between the processor and the memory system and evaluates the potential of compression in improving performance, power consumption, and cost of the memory system. Analysis of traces obtained with Sun Microsystems' Shade simulator simulating SPARC executables of nine integer and six floating-point programs in the SPEC CPU2000 benchmark suite yielded impressive results. Well-designed compression schemes may provide benefits in performance, power, and cost that far outweigh their overheads constituting extra time, logic, and power for compression and decompression. This will be more so in the future since the speed, size, and power consumption of logic (which will be used to perform compression/decompression) are improving and are projected to improve at a much higher rate compared to those of interconnect (which will be used to communicate the information), both on-chip and off-chip.
Global patterns in oceanic planktonic metabolism

Rates of gross primary production (GPP) and respiration (CR) of plankton communities in the upper ocean were evaluated on the basis of a data set comprising 3149 paired light and dark bottle measurements of volumetric GPP‐CR of euphotic zone plankton communities. The data were from 72 published and unpublished reports of measurements made between 1981 and 2011 from the open ocean and the Mediterranean Sea. The data set is dominated by measurements in chlorophyll a (Chl a)‐rich oceans and North Atlantic waters, with a paucity of measurements in the Indian Ocean and South Pacific Ocean. CR scaled as the 3/4 power of GPP with a power slope of 0.79 ± 0.01, implying that the threshold GPP separating heterotrophic from autotrophic plankton communities is 1.26 mmol O2 m−3 d−1. Plankton communities with Chl a < 0.35 mg m−3 tend to be heterotrophic. Both GPP and CR declined exponentially with depth, but the GPP declined faster, at 42% ± 7% m−1, than CR (29% ± 8% m−1), so that CR increases relative to GPP with depth.
Inter-Transaction Association Rules Mining for Rare Events Prediction

Rare events prediction is a very interesting and critical issue that has been approached within various contexts by research areas, such as statistics and machine learning. Data mining has provided a set of tools to treat this problem when the size as well as the inherent features of the data, such as noise, randomness and special data types, become an issue for the traditional methods. Transaction databases that contain sets of events require special approaches in order to extract valuable temporal knowledge. Sequential analysis aims to discover patterns or rules describing the temporal structure of data. In this paper we propose an approach that extends sequential analysis to predict rare events in transaction databases. We utilize the framework of inter-transaction association rules, which associate events across a window of transactions. The proposed algorithm produces rules for the accurate and timely prediction of a user-specified rare event, such as a network intrusion or an engine failure.
The Gender Wage Gap: Does a Gender Gap in Reservation Wages Play a Part?

This paper focuses on re-examining the gender wage gap and the potential role that reservation wages play. Based on two waves of rich data from the IZA Evaluation Dataset Survey we examine the importance of gender differences in reservation wages to explain the gender gap in realized wages for a sample of newly unemployed individuals actively searching for a full-time job in Germany. The dataset includes measures for education, socio-demographics, labor market history, psychological factors and job search characteristics allowing us to perform a decomposition analysis including these potentially influential factors. Our results suggest that the gender wage gap disappears once we control for reservation wages. We also find a close correspondence between the two gaps for certain subgroups. For example, those with low labor market experience show no gender gap in reservation wages and also no corresponding gap in observed wages. In an attempt to better understand how the initial gender gap in reservation wages arises, we also decompose the gender gap in reservation wages and draw some preliminary conclusions on the nature of the unobservable traits that reservation wages might be capturing.
A 3D visual analysis tool in support of the SANDF's growing ground based air defence simulation capability

A 3D visual analysis tool has been developed to add value to the SANDF's growing Ground Based Air Defence (GBAD) System of Systems simulation capability. A time based XML interface between the simulation and analysis tool, via a TCP connection or a log file, allows individual simulation objects to be wholly updated or partially modified. Live pause and review of the simulation action is supported by employing data key frames and compressed XML for enhanced performance. An innovative configurable filter tree allows visual clutter to be reduced as required and an open source scene graph (OpenSceneGraph) manages the 3D scene representation and rendering. A visualisation capability is developed for the effective presentation of the dynamic air defence system behaviour, system state transitions and inter-system communication. The visual analysis tool has successfully been applied in support of system performance experiments, tactical doctrine development and simulation support during training and live field exercises. The 3D visualisation resulted in improved situational awareness during experiment analysis, in increased involvement of the SANDF in experiment analysis and in improved credibility of analysis results presented during live or after action visual feedback sessions.
Amino Acid Starvation Has Opposite Effects on Mitochondrial and Cytosolic Protein Synthesis

Amino acids are essential for cell growth and proliferation for they can serve as precursors of protein synthesis, be remodelled for nucleotide and fat biosynthesis, or be burnt as fuel. Mitochondria are energy producing organelles that additionally play a central role in amino acid homeostasis. One might expect mitochondrial metabolism to be geared towards the production and preservation of amino acids when cells are deprived of an exogenous supply. On the contrary, we find that human cells respond to amino acid starvation by upregulating the amino acid-consuming processes of respiration, protein synthesis, and amino acid catabolism in the mitochondria. The increased utilization of these nutrients in the organelle is not driven primarily by energy demand, as it occurs when glucose is plentiful. Instead it is proposed that the changes in the mitochondrial metabolism complement the repression of cytosolic protein synthesis to restrict cell growth and proliferation when amino acids are limiting. Therefore, stimulating mitochondrial function might offer a means of inhibiting nutrient-demanding anabolism that drives cellular proliferation.
Using HMM to sign language video retrieval

This paper presents a system called DCMR. Content-based video searching is a challenging field, and most research focus on the low level features such as color histogram, texture and etc. In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands' dynamic features. Consequently, we segment the video frames by motion features. As for each segment, we generate a HMM. When a clip of hand language inputs, we also get the feature serials, and then we compare the possibility of the input serials in each HMM. Experiment results on a large of hand language videos show that our searching system performs much better than existing methods on hand language video searching systems. Compared with the traditional methods, our system reduces the average searching time by half and the searching precision has doubled.
Head Turning-Induced Hypotension in Elderly People

Carotid sinus hypersensitivity has a high prevalence in the elderly and is a possible cause of falls. In carotid sinus hypersensitivity, external triggers cause sudden reductions in blood pressure, leading to dizziness or syncope, resulting in falls. Turning of the head is considered an important example of such an external trigger in everyday life, wherein rotation of the neck is thought to manipulate the hypersensitive carotid sinus. However, direct evidence for this is lacking. The aim of this study was to investigate the effects of head turning in elderly with carotid sinus hypersensitivity. We performed a prospective, observational study in 105 elderly patients who visited a geriatric falls clinic in a university teaching hospital and in 25 community dwelling healthy elderly subjects. Continuous measurements of blood pressure and heart rate (Finapres) were performed before, during, and after head turning. Head turning-induced hypotension was defined as a drop in systolic blood pressure of at least 20 mmHg during head turning. Carotid sinus hypersensitivity was examined with carotid sinus massage. We also tested for two other common geriatric hypotensive syndromes, orthostatic hypotension and post prandial hypotension, using active standing and a meal test. All three hypotensive syndromes were defined using consensus definitions. Head turning resulted in hypotension in 39% of patients (mean systolic blood pressure drop 36 mm Hg) and in 44% of the healthy elderly, irrespective of the direction of the head movement. Carotid sinus hypersensitivity was associated with head-turning induced hypotension (OR= 3.5, 95% CI= 1.48 to 8.35). We conclude that head turning is indeed an important cause of sudden drops in blood pressure in elderly with carotid sinus hypersensitivity.
Asynchronized Concurrency: The Secret to Scaling Concurrent Search Data Structures

We introduce "asynchronized concurrency (ASCY)," a paradigm consisting of four complementary programming patterns. ASCY calls for the design of concurrent search data structures (CSDSs) to resemble that of their sequential counterparts. We argue that ASCY leads to implementations which are portably scalable: they scale across different types of hardware platforms, including single and multi-socket ones, for various classes of workloads, such as read-only and read-write, and according to different performance metrics, including throughput, latency, and energy. We substantiate our thesis through the most exhaustive evaluation of CSDSs to date, involving 6 platforms, 22 state-of-the-art CSDS algorithms, 10 re-engineered state-of-the-art CSDS algorithms following the ASCY patterns, and 2 new CSDS algorithms designed with ASCY in mind. We observe up to 30% improvements in throughput in the re-engineered algorithms, while our new algorithms out-perform the state-of-the-art alternatives.
Achieving Continuous Manufacturing : Technologies and Approaches for Synthesis , Work-Up and Isolation of Drug Substance

Introduction the Future for Continuous Drug Substance Manufacture Successful innovation in manufacturing and adoption of continuous manufacturing (CM) has an important role to play in the industry’s future (ref Badman and Trout, 2014). The vision for CM in the pharmaceutical industry is to exploit integrated end-to-end processing to convert raw materials into safe, effective and high quality medicinal products. This vision is driven by the potential to improve control over quality, reduce costs, enhance process safety and significantly reduce the timelines currently involved across the medicines’ supply chain. As new continuous systems and technologies become fully established, so the industry’s ability to continue to meet the demands for existing as well as new, safer and increasingly personalized dosage forms will be enhanced.