Miracle-dz/UniFAR-FTUs huggingface dataset:
Domains of employability skills as predictors of quality of worklife: Basis for a training and development program

This study aimed to determine the most significant predictor of the quality of worklife of business graduates from among the domains of the employability skills of business graduates of Government Owned and Controlled Corporations as basis for a training and development program. The descriptive-correlational method of research was used involving 278 samples chosen through purposive sampling. To arrive at an accurate interpretation of the data, statistical tests such as the mean and multiple regressions were employed. The study revealed that the level of employability skills in terms of self management is practiced all the time by the GOCCs business graduates in Region XII. Their quality of worklife is satisfactory. The eight employability skills significantly predicts the domains of quality of worklife of business graduate. Planning and organizing and lifelong learning are the two most significant predictors of quality of worklife. Further, a training and development program is made a part of this study for possible adoption of interested agencies. It is therefore recommended that there must be proper documentation of the employability skills that maybe significant to business employees to address the problem of mismatch. There must be proper evaluation of the quality of worklife practices to better meet the needs of dual-career families. Curriculum of different universities and colleges must be equipped with the knowledge and skills so required by companies so that graduates would certainly become valuable assets who will bring the establishments they will serve to high level of performance.
EdgeVib: Effective Alphanumeric Character Output Using a Wrist-Worn Tactile Display

This paper presents EdgeVib, a system of spatiotemporal vibration patterns for delivering alphanumeric characters on wrist-worn vibrotactile displays. We first investigated spatiotemporal pattern delivery through a watch-back tactile display by performing a series of user studies. The results reveal that employing a 2×2 vibrotactile array is more effective than employing a 3×3 one, because the lower-resolution array creates clearer tactile sensations in less time consumption. We then deployed EdgeWrite patterns on a 2×2 vibrotactile array to determine any difficulties of delivering alphanumerical characters, and then modified the unistroke patterns into multistroke EdgeVib ones on the basis of the findings. The results of a 24-participant user study reveal that the recognition rates of the modified multistroke patterns were significantly higher than the original unistroke ones in both alphabet (85.9% vs. 70.7%) and digits (88.6% vs. 78.5%) delivery, and a further study indicated that the techniques can be generalized to deliver two-character compound messages with recognition rates higher than 83.3%. The guidelines derived from our study can be used for designing watch-back tactile displays for alphanumeric character output.
Properties of Stochastic Perceptual Auditory-event-based Models for Automatic Speech Recognition

Recently, physiological and psychoacoustic studies have uncovered new evidence supporting the idea that human auditory processes focus on the transitions between spoken sounds rather than on the steady-state portions of spoken sounds for speech recognition. Stochastic Perceptual Auditory-event-based Models (SPAMs) were developed by Morgan, Bourlard, Hermansky and Greenberg to take this new evidence into account for word models in speech recognition by machines. This paper details our efforts to build a speech recognition system based on some of the properties of SPAMs. Although not all aspects of the complete SPAM theory have been implemented, we did find that fairly good recognition is possible with a system that concentrates almost exclusively on the transitions between speech sounds. Additionally, we found that such a system enhanced the more conventional phoneme-based system, which emphasized recognition of steady-state sounds. This blended system performed better than either system alone, especially in the case of noise-obscured speech.
Modeling and Evaluating a Bayesian Network of Culture-specific Non-verbal Behaviors for Virtual Character Dialogues

Human behavior is, amongst others, influenced by cultural background. Thus research on virtual characters that should imitate human behavior, considers cultural background to influence the behavior of agents as well. This paper presents a hybrid approach of modeling culture-specific non-verbal behaviors for virtual character dialogues based on both: theoretical knowledge and empirical data. A Bayesian network model has been established that augments the causal relations between culture, dialog behavior, and non-verbal behavior with empirical data. Therefore, the structure and variables of the network are designed based on models and theories from the social sciences, while its parameters are learned from a video corpus of German and Japanese conversations. A 10-fold-cross-validation has been conducted to validate the model. Having such a model at hand allows further investigation of behavioral dependencies as well as the automatic generation of non-verbal behaviors for virtual character dialogs that reflect prototypical differences based on culture.
Spatial language abilities and cognition across the adult-lifespan and in early Alzheimer's disease

Space constitutes one of the core framing structures of experience in the natural environment. Therefore, communicating spatial information with verbal means, such as locative relations between objects, is vital for numerous everyday activities and constitutes a core part of human linguistic communication. The present project aimed to 1) develop psychometrically sound measures assessing spatial language abilities, including naming static and dynamic spatial relations, memory for route- and survey-based descriptions, and comprehension of descriptions of locative relations under different spatial reference frames; 2) identify the trajectories of these spatial language abilities across the adult-lifespan and contrast them against trajectories of various (non-verbal) visuospatial and (non-spatial) verbal abilities; and 3) investigate spatial language abilities in individuals who are at an early stage of Alzheimer’s disease (AD), for the first time. Across a series of studies involving 160 adults aged between 18 and 85, we found comparable age-related declines in spatial language and visuospatial abilities, although their onset and magnitude depended on the type of subability examined. By contrast, verbal abilities remained well-preserved with increasing age. Moreover, performance in spatial language measures was found to discriminate mild AD patients and age-, education-, and gender-matched controls to a very high degree. The results of the present work have several theoretical and practical implications, as they 1) establish the test-retest reliability, and the concurrent, construct and discriminative validity of the newly-developed spatial language measures; 2) reveal a number of divergent and convergent domain-specific cognitive changes across the adult-lifespan; 3) extend the large existing literature on the detrimental (a)typical ageing effects on visuospatial cognition by demonstrating that spatial processing is also compromised when assessed through language; and 4) suggest that language- and perception-based representations of space are underpinned by comparable cognitive operations and supported by overlapping neural networks that are particularly sensitive to ageing effects.
A Fast Power Optimization Algorithm for Non-regenerative Dual Hop Relay Network

In this paper, we considers a dual-hop relay network which operates under amplify and forward (AF) communication mode. The power allocation at the source terminal (ST) as well as at the relay node (RN) is considered to enhance the end to end throughput of the system. A power optimization problem for orthogonal frequency division multiplexing (OFDM) based transmission over two hops is formulated. A novel joint solution from the dual decomposition is proposed which results in enhanced performance subject to individual power constraints at the two transmitters. The proposed schemes exhibits much faster convergence as compared to the existing techniques while yielding the same performance. Simulation results are presented to validate the performance of the proposed algorithm.
The Anesthesiologist’s Impact on Bleeding Control During Liver Surgery

Liver surgery is often associated with increased likelihood of massive bleeding. The blood loss is one of major intraoperative issue the surgical team must deal with. Bleeding is usually present in cirrhotic patients but can be faced even in the patients with normal liver function undergoing liver surgery. Correction of preoperative abnormal coagulation’s tests, strong interaction between the surgeon and the anesthesiologist, and finally the anesthesia technique, may successfully reduce the bleeding intensity and blood transfusions requirements. This review will be focused only in the anesthesiologist’s role in minimizing the blood loss during major liver surgery.
Diffraction Ring Technique and Nonlinear Optical Properties of 5-Aminoindazole

The nonlinear optical properties of 5-Aminoindazole in Dimethyl sulfoxide (DMSO) solvent was studied using single beam Z-scan technique with a continuous-wave radiation at 473 nm of an output power of 4.6 mW. All the solution samples showed large nonlinear refractive indexice and absorption coefficient of the order of 10 -8 cm 2 /W and 10 -3 cm/W, respectively. The concentration-dependent nonlinear refractive index was also investigated. We presents experimental evidences of observing diffraction pattern in 5-Aminoindazole: DMSO solvent with the calculation of the refractive index change, ∆n , the relative phase shift,  , and effective nonlinear refractive index ,n2. The solvent of spectroscopic grade and was used without further purification. All the solutions used for the study were freshly prepared.
Hybrid Modulation Strategies for Eliminating Low-Frequency Neutral-Point Voltage Oscillations in the Neutral-Point-Clamped Converter

Nearest vector (NV) modulation strategies for the neutral-point-clamped converter are known to generate low-frequency neutral point (NP) voltage oscillations. Non-NV strategies can eliminate these oscillations, but at the expense of higher switching losses and output voltage harmonic distortion. This letter proposes a simple way of creating hybrid strategies, as combinations of NV and non-NV strategies, which are also able to eliminate NP voltage oscillations. The approach minimizes the participation of non-NV strategies and hence their drawbacks, while it can be applied to any type of load (nonlinear and/or unbalanced). Simulations in MATLAB-Simulink are used to illustrate its operation.
Exploiting ERP Systems in Enterprise Search

Enterprise resource planning (ERP) systems are the core of many companies: they contain entities which are the focus of enterprise searches [5]. In this paper, a model which exploits those entities to improve the search experience of enterprise users is proposed. Specifically, a graph knowledge base called entity graph is defined. It is used both to offer a novel data exploration experience that reflects the business processes and to improve the search accuracy contributing to the score of a search result into a weighted linear model. The applicability of the model is demonstrated by implementing an enterprise search prototype called SeNSE (Skyline eNterprise Search Engine).
The activity status of cofilin is directly related to invasion, intravasation, and metastasis of mammary tumors

Understanding the mechanisms controlling cancer cell invasion and metastasis constitutes a fundamental step in setting new strategies for diagnosis, prognosis, and therapy of metastatic cancers. LIM kinase1 (LIMK1) is a member of a novel class of serine–threonine protein kinases. Cofilin, a LIMK1 substrate, is essential for the regulation of actin polymerization and depolymerization during cell migration. Previous studies have made opposite conclusions as to the role of LIMK1 in tumor cell motility and metastasis, claiming either an increase or decrease in cell motility and metastasis as a result of LIMK1 over expression (Zebda, N., O. Bernard, M. Bailly, S. Welti, D.S. Lawrence, and J.S. Condeelis. 2000. J. Cell Biol. 151:1119–1128; Davila, M., A.R. Frost, W.E. Grizzle, and R. Chakrabarti. 2003. J. Biol. Chem. 278:36868–36875; Yoshioka, K., V. Foletta, O. Bernard, and K. Itoh. 2003. Proc. Natl. Acad. Sci. USA. 100:7247–7252; Nishita, M., C. Tomizawa, M. Yamamoto, Y. Horita, K. Ohashi, and K. Mizuno. 2005. J. Cell Biol. 171:349–359). We resolve this paradox by showing that the effects of LIMK1 expression on migration, intravasation, and metastasis of cancer cells can be most simply explained by its regulation of the output of the cofilin pathway. LIMK1-mediated decreases or increases in the activity of the cofilin pathway are shown to cause proportional decreases or increases in motility, intravasation, and metastasis of tumor cells.
Identification of novel centromere/kinetochore-associated proteins using monoclonal antibodies generated against human mitotic chromosome scaffolds

We describe the generation of 11 monoclonal antibodies that bind to the centromere/kinetochore region of human mitotic chromosomes. These antibodies were raised against mitotic chromosome scaffolds and screened for centromere/kinetochore binding by indirect immunofluorescence against purified chromosomes. Immunoblot analyses with these antibodies revealed that all of the antigens are greater than 200 kD and are components of nuclei, chromosomes, and/or chromosome scaffolds. Comparison of the immunolocalization of the antigens with that observed for the centromere-associated protein CENP- B revealed that each of these centromere/kinetochore proteins lies more peripherally to the DNA than does CENP-B. In cells normally progressing through the cell cycle, these antigens displayed four distinct patterns of centromere/kinetochore association, corresponding to a minimum of four novel centromere/kinetochore-associated proteins.
Interlanguage Segmental Mapping as Evidence for the Nature of Lexical Representation

The traditional view of phonological representation assumes that lexical representation is economical and free of redundancy and that a phoneme is represented as a combination of contrastive phonetic features. The traditional view, however, is challenged by the recent developments in phonological theories. In Optimality Theory, the distinction between contrastive vs. non-contrastive aspects of pronun- ciation is made not by the lexical representation but by the constraint ranking and the commonly adopted principle of Lexicon Optimization requires lexical representation to be as close to the surface representation as possible. An exemplar model of phonology also assumes that predictable and redundant phonetic properties are also specified in the lexical representation and that each contextual variant of a phoneme forms a separate phonetic category. The current paper reviews recent studies on segmental mapping in interlanguage phonology, examines the nature of the L1 phonological representation that the mapping crucially refers to, and discusses how the interlanguage data bear on the debate on the nature of the lexical representation.
A NOVEL FEATURE EXTRACTION TECHNIQUE FOR FACIAL EXPRESSION RECOGNITION

This paper presents a new technique to extract the light invariant local feature for facial expression recognition. It is not only robust to monotonic gray-scale changes caused by light variations but also very simple to perform which makes it possible for analyzing images in challenging real-time settings. The local feature for a pixel is computed by finding the direction of the neighboring of the pixel with the particular rank in term of its gray scale value among all the neighboring pixels. When eight neighboring pixels are considered, the direction of the neighboring pixel with the second minima of the gray scale intensity can yield the best performance for the facial expression recognition in our experiment. The facial expression classification in the experiment was performed using a support vector machine on CK+ dataset The average recognition rate achieved is 90.1 ± 3.8%, which is better than other previous local feature based methods for facial expression analysis. The experimental results do show that the proposed feature extraction technique is fast, accurate and efficient for facial expression recognition.
Ultrafast Water Dynamics at the Interface of the Polymerase–DNA Binding Complex

DNA polymerases slide on DNA during replication, and the interface must be mobile for various conformational changes. The role of lubricant interfacial water is not understood. In this report, we systematically characterize the water dynamics at the interface and in the active site of a tight binding polymerase (pol β) in its binary complex and ternary state using tryptophan as a local optical probe. Using femtosecond spectroscopy, we observed that upon DNA recognition the surface hydration water is significantly confined and becomes bound water at the interface, but the dynamics are still ultrafast and occur on the picosecond time scale. These interfacial water molecules are not trapped but are mobile in the heterogeneous binding nanospace. Combining our findings with our previous observation of ultrafast water motions at the interface of a loose binding polymerase (Dpo4), we conclude that the binding interface is dynamic and the water molecules in various binding clefts, channels, and caves are mobile and even fluid with different levels of mobility for loose or tight binding polymerases. Such a dynamic interface should be general to all DNA polymerase complexes to ensure the biological function of DNA synthesis.
Spontaneous Usage of Different Shortcuts Based on the Commutativity Principle

Based on research on expertise a person can be said to possess integrated conceptual knowledge when she/he is able to spontaneously identify task relevant information in order to solve a problem efficiently. Despite the lack of instruction or explicit cueing, the person should be able to recognize which shortcut strategy can be applied – even when the task context differs from the one in which procedural knowledge about the shortcut was originally acquired. For mental arithmetic, first signs of such adaptive flexibility should develop already in primary school. The current study introduces a paper-and-pencil-based as well as an eyetracking-based approach to unobtrusively measure how students spot and apply (known) shortcut options in mental arithmetic. We investigated the development and the relation of the spontaneous use of two strategies derived from the mathematical concept of commutativity. Children from grade 2 to grade 7 and university students solved three-addends addition problems, which are rarely used in class. Some problems allowed the use of either of two commutativity-based shortcut strategies. Results suggest that from grade three onwards both of the shortcuts were used spontaneously and application of one shortcut correlated positively with application of the other. Rate of spontaneous usage was substantial but smaller than in an instructed variant. Eyetracking data suggested similar fixation patterns for spontaneous an instructed shortcut application. The data are consistent with the development of an integrated concept of the mathematical principle so that it can be spontaneously applied in different contexts and strategies.
Evolutionary reinforcement learning of spoken dialogue strategies

From a system developer’s perspective, designing a spoken dialogue system can be a time-consuming and difficult process. A developer may spend a lot of time anticipating how a potential user might interact with the system and then deciding on the most appropriate system response. These decisions are encoded in a dialogue strategy, essentially a mapping between anticipated user inputs and appropriate system outputs. To reduce the time and effort associated with developing a dialogue strategy, recent work has concentrated on modelling the development of a dialogue strategy as a sequential decision problem. Using this model, reinforcement learning algorithms have been employed to generate dialogue strategies automatically. These algorithms learn strategies by interacting with simulated users. Some progress has been made with this method but a number of important challenges remain. For instance, relatively little success has been achieved with the large state representations that are typical of reallife systems. Another crucial issue is the time and effort associated with the creation of simulated users. In this thesis, I propose an alternative to existing reinforcement learning methods of dialogue strategy development. More specifically, I explore how XCS, an evolutionary reinforcement learning algorithm, can be used to find dialogue strategies that cover large state spaces. Furthermore, I suggest that hand-coded simulated users are sufficient for the learning of useful dialogue strategies. I argue that the use of evolutionary reinforcement learning and hand-coded simulated users is an effective approach to the rapid development of spoken dialogue strategies. Finally, I substantiate this claim by evaluating a learned strategy with real users. Both the learned strategy and a state-of-the-art hand-coded strategy were integrated into an end-to-end spoken dialogue system. The dialogue system allowed real users to make flight enquiries using a live database for an Edinburgh-based airline. The performance of the learned and hand-coded strategies were compared. The evaluation results show that the learned strategy performs as well as the hand-coded one (81% and 77% task completion respectively) but takes much less time to design (two days instead of two weeks). Moreover, the learned strategy compares favourably with previous user evaluations of learned strategies.
Community Energy Storage impacts on smart grid adaptive Volt-VAR Optimization of distribution networks

This paper aims to investigate Community Energy Storage (CES) impacts on AMI-based Volt-VAR Optimization (VVO) solutions for advanced distribution networks. CES is one of the technologies employed to improve system stability, reliability and quality. As such, it could have considerable impacts on voltage control, reactive power optimization and energy conservation. Conservation Voltage Reduction (CVR) is one of the main tasks of advanced VVO engines in distribution networks. Moreover, in order to check the performance of the discussed VVO engine in the presence of CES during peak time intervals, 33-node distribution feeder is employed. The results of this paper show significant improvement in the performance of the VVO engine when CES is forced to discharge in peak times. Moreover, the results present how CES could affect Volt-VAR Control Component (VVCC) switching and how it affects the energy conservation efficiency.
An ANN verifying approach to equipment campaign model

To any simulating system, only its credibility being confirmed can it take on practical worthiness. When economical and feasibility were concerned, the verifying and validating tactic was put forward to equipment compaign simulation prototype system. Then damage parameter experiment was done under typical condition. Neural network was used to verify error between experiment data and experiential value of damage parameters, the trained neural network was embedded into model. At last system simulating result was validated through real war data and experiment data of real equipment. So a fresh approach on complexity theory was explored to equipment simulating model or analogous problem.