Miracle-dz/UniFAR-FTUs huggingface dataset:
Pacific Asia Conference on Information Systems ( PACIS ) 2014 A TAXONOMY OF KNOWLEDGE MANAGEMENT OUTCOMES FOR SMES

The purpose of this paper is to systematically analyze the knowledge management research within small and medium-sized companies. The study includes a systematic review of 30 peer reviewed papers on knowledge management advantages for SMEs. Balanced scorecard perspectives cover all aspects of the organization, and, consequently, the balanced scorecard approach has been applied to classify the KM benefits. The reviewed scientific studies highlight the benefits of knowledge management in the areas of economic and social perspective (increased profits, flexibility, product reputation, financial performance), commercial and customers perspective (market share, sales growth, customer satisfaction, good external relationship), internal business processes perspective (operational performance, increased productivity, product/service quality, process improvement) and organizational learning and growth perspective (employee development, innovation, organizational creativity, learning). For future studies, determining stakeholder views is recommended in order to gain sustainable competitive advantage.
Effects of the pericardium on the diastolic left coronary pressure-flow relationship in the isolated dog heart.

We studied the effects of the pericardium on diastolic left coronary pressure-flow relationships in heart-blocked and isolated canine preparations. In these preparations, the left and right coronary arteries were dilated with adenosine and perfused by means of a pressurized arterial reservoir. The diastolic left heart pressure (LHP) was controlled by the height of a reservoir connected to the left atrium and left ventricle. The right atrial and ventricular pressure i.e., coronary outflow pressure, was kept constant at 0 mm Hg. Before and after pericardiectomy, diastolic coronary pressure-flow relationships were obtained at three values of LHP (0, 15, and 30 mm Hg) with driving pressure decreasing (2 mm Hg/sec or less) from approximately 60 mm Hg to the actual zero-flow pressure (Pf = 0) during a single long diastole induced by cessation of ventricular pacing. The slopes of the coronary pressure-flow relationships were approximated by a linear regression analysis in which the correlation coefficients were greater than . 98 in all cases. Before pericardiectomy, with LHP increasing from 0 to 15 and 30 mm Hg, the value of Pf = 0 significantly increased from 7 +/- 1 to 16 +/- 1 (p less than .01) and 28 +/- 2 mm Hg (p less than .01), respectively. After pericardiectomy, it increased from 7 +/- 1 to 14 +/- 1 (p less than .01) and 17 +/- 2 mm Hg (p less than .01), respectively. When LHP was at 0 and 15 mm Hg, the pericardiectomy had no effect on the value of Pf = 0. (ABSTRACT TRUNCATED AT 250 WORDS)
Constituent Structure for Filipino: Induction through Probabilistic Approaches

The current state of Philippine linguistic resources, which includes formal grammars, electronic dictionaries and corpora are not yet significant to address industrial- strength language technologies. This paper discusses a computational approach in automatically estimating constituent structures from a corpus using unsupervised probabilistic approaches. Two models are presented and results show an F1 measure of greater than 69%. Issues and phenomena of the Filipino language are identified and discussed This paper discusses the algorithms used for the automatic induction of grammar for the Filipino language. The rationale for the study stems on the minimal work done on the development of a computational grammar for the Filipino language for the development of robust and industrial- strength natural language analysis and technologies. Existing Filipino grammars can only handle a subset of declarative type sentences. Considering the difficulty to manually construct a robust grammar capable of parsing a broad scope of sentences, automatic grammar induction is a consideration that can be used for learning language structure. Automated grammar induction systems deals with the generation of a grammar based from input corpora. Existing work for grammar induction fall under two categories based on their input constraints: Supervised and Unsupervised. Slightly supervised systems generate grammar rules from bracketed corpora or tree banks. Bracketed corpora are text documents that have been bracketed by a linguist to represent the skeletal syntactic structure of the sentences. Treebanks are large corpora that have been annotated with the part of speech tags, syntactic structure, and other functional attributes necessary. Unsupervised systems make use of non- bracketed corpora while applying searching and clustering algorithms to attempt to learn the language rules. Works on slightly supervised grammar induction, such as the works of Lari and Young(1991), Brill(1993), Sekine and Grishman(1995), and Charniak(1996), present different output formalisms to represent the grammar. However, Filipino is currently a resource-limited language and does not have the computational resources necessary for the algorithms presented. There are existing corpora available for the language, but these have not yet been bracketed.
The GAGA Factor of Drosophila Binds Triple-stranded DNA*

The Drosophila GAGA factor binds specifically to simple repeating d(GA·TC) n DNA sequences. These sequences are known to be capable of forming triple-stranded DNA as well as other non-B-DNA conformations. Here, it is shown that GAGA binds to a d[CT(GA·TC)]22intermolecular triplex with similar specificity and affinity as to a regular double-stranded B-form d(GA·TC)22 sequence. The interaction of GAGA with triplex DNA cannot, however, stimulate transcription in vitro. The affinity of GAGA for triplexes of the purine motif, such as a d[AG(GA·TC)]22intermolecular triplex, is significantly lower. The DNA binding domain of GAGA is sufficient for efficient binding to triplex DNA. Based on the reported solution structure of the complex of GAGA-DNA binding domain with double-stranded DNA, a model for its interaction with triplex DNA is proposed in which most of the protein-DNA contacts observed in duplex DNA are maintained, especially those occurring through the minor groove. The higher negative charge of the triplex is likely to have also an important contribution to both the specificity and affinity of the interaction.
Editorial: Psychological Test and Assessment Modeling

, in 2008. However, in the last two years the journal has altered its scope due to the topics of submitted papers and due to (invited) special issues. As a matter of fact, the scope has changed towards the primary subjects of psychology-specific statistical methods and problems, general psychometrics, and psychological assessment in theory and practice. First of all, the special issue 2008/2 “High Ability Assessment” (cf. Stoger & Ziegler, 2008) should be mentioned. In this issue for instance, Holocher-Ertl, Kubinger, and Hohensinn (2008) dealt with the gap between practical demands and scientific supply when identifying children who may be cognitively gifted. Holling and Kuhn (2008) investigated the factor structure of divergent thinking in gifted children. Phillipson (2008) calibrated underachievers’ achievements using the Rasch model. And Ziegler and Stoger (2008) suggested some content model of learning. There was then a special issue in 2008/3 “The Use of LLTM (Linear Logistic Test Model): Cognitive Modelling and Item-Technology Analysis”. In this issue for instance, Kubinger (2008) brought up a revival of the Rasch model-based LLTM. Embretson and Daniel (2008) used the LLTM for analysing the complexity in mathematical problem solving items; Sonnleitner (2008) and Holling et al. (2008) applied the LLTM for the evaluation of item generating rules (the former for reading comprehension, the latter for statistical wording); Xie and Wilson (2008) used the LLTM for DIF-analyses, and Hohensinn et al. (2008) used this model for
Spatio-angular resolution tradeoffs in integral photography

An integral camera samples the 4D light field of a scene within a single photograph. This paper explores the fundamental tradeoff between spatial resolution and angular resolution that is inherent to integral photography. Based on our analysis we divide previous integral camera designs into two classes depending on how the 4D light field is distributed (multiplexed) over the 2D sensor. Our optical treatment is mathematically rigorous and extensible to the broader area of light field research. We argue that for many real-world scenes it is beneficial to sacrifice angular resolution for higher spatial resolution. The missing angular resolution is then interpolated using techniques from computer vision. We have developed a prototype integral camera that uses a system of lenses and prisms as an external attachment to a conventional camera. We have used this prototype to capture the light fields of a variety of scenes. We show examples of novel view synthesis and refocusing where the spatial resolution is significantly higher than is possible with previous designs.
Multi-dimensional subspace based feature selection for face recognition

In this project, we propose a novel kernel named Adaptive Data-dependent Matrix Norm Based Gaussian Kernel (ADM-Gaussian kernel) for facial feature extraction. As a popular facial feature extraction method for face recognition, the current kernel method endures some problems. Firstly, the face image must be transformed to the vector, which leads to the large storage requirements and the large computational effort, and secondly since the different geometrical structures lead to the different class discrimination of the data in the feature space, the performance of the kernel method is influenced when kernels are inappropriately selected. In order to solve these problems, firstly we create a novel matrix norm based Gaussian kernel which views images as matrices for facial feature extraction, which is the basic kernel for the data-dependent kernel. Secondly we apply a novel maximum margin criterion to seek the adaptive expansion coefficients of the data-dependent kernel, which leads to the largest class discrimination of the data in the feature space. Experiments on ORL and Yale databases demonstrate the effectiveness of the proposed algorithm.
Development of an antagonistic bionic joint controller for a musculoskeletal quadruped

In this paper, a joint control algorism was proposed to implement on our musculoskeletal robot. The joints are all actuated by pneumatic muscles and have antagonistic structure. In order to gain a better performance, we first modeled the pneumatic muscle, and then considering the dynamics two control method was discussed and compared. As a tradeoff of rapidity and accuracy, the combined joint control algorism was implemented on the robot system. The algorism could tune the stiffness of the joint automatically to fit the compliance need for joint control. The experiments on our robot showed that the joint control algorism could operate the robot with a fast and accurate response. There is nearly not lagging behind, and with a small overshot during the step testing, and a complex leg's trajectory was also achieved through our joint controller.
Integrating Type Theory and Distributional Semantics: A Case Study on Adjective–Noun Compositions

In this article, we explore an integration of a formal semantic approach to lexical meaning and an approach based on distributional methods. First, we outline a formal semantic theory that aims to combine the virtues of both formal and distributional frameworks. We then proceed to develop an algebraic interpretation of that formal semantic theory and show how at least two kinds of distributional models make this interpretation concrete. Focusing on the case of adjective–noun composition, we compare several distributional models with respect to the semantic information that a formal semantic theory would need, and we show how to integrate the information provided by distributional models back into the formal semantic framework.
A subject-specific multiscale model of transcranial magnetic stimulation

A SUBJECT-SPECIFIC MULTISCALE MODEL OF TRANSCRANIAL MAGNETIC STIMULATION Brian D. Goodwin, B.S. Marquette University, 2014 Transcranial magnetic stimulation (TMS) is a neuromodulation technique used to treat a variety of neurological disorders. While many types of neuromodulation therapy are invasive, TMS is an attractive alternative because it is noninvasive and has a very strong safety record. However, clinical use of TMS has preceded a thorough scientific understanding: its mechanisms of action remain elusive, and the spatial extent of modulation is not well understood. We created a subject-specific, multiscale computational model to gain insights into the physiological response during motor cortex TMS. Specifically, we developed an approach that integrates three main components: 1) a high-resolution anatomical MR image of the whole head with diffusion weighted MRI data; 2) a subject-specific, electromagnetic, non-homogeneous, anisotropic, finite element model of the whole head with a novel time-dependent solver; 3) a population of multicompartmental pyramidal cell neuron models. We validated the model predictions by comparing them to motor evoked potentials (MEPs) immediately following single-pulse TMS of the human motor cortex. This modeling approach contains several novel components, which in turn allowed us to gain greater insights into the interactions of TMS with the brain. Using this approach we found that electric field magnitudes within gray matter and white matter vary substantially with coil orientation. Our results suggest that 1) without a time-dependent, subject-specific, non-homogeneous, anisotropic model, loci of stimulation cannot be accurately predicted; 2) loci of stimulation depend upon biophysical properties and morphologies of pyramidal cells in both gray and white matter relative to the induced electric field. These results indicate that the extent of neuromodulation is more widespread than originally thought. Through medical imaging and computational modeling, we provide insights into the effects of TMS at a multiscale level, which would be unachievable by either method alone. Finally, our approach is amenable to clinical implementation. As a result, it could provide the means by which TMS parameters can be prescribed for treatment and a foundation for improving coil design.
Zebrafish larvae evade predators by sensing water flow

SUMMARY The ability of fish to evade predators is central to the ecology and evolution of a diversity of species. However, it is largely unclear how prey fish detect predators in order to initiate their escape. We tested whether larval zebrafish (Danio rerio) sense the flow created by adult predators of the same species. When placed together in a cylindrical arena, we found that larvae were able to escape 70% of predator strikes (mean escape probability Pescape=0.7, N=13). However, when we pharmacologically ablated the flow-sensitive lateral line system, larvae were rarely capable of escape (mean Pescape=0.05, N=11). In order to explore the rapid events that facilitate a successful escape, we recorded freely swimming predators and prey using a custom-built camera dolly. This device permitted two-dimensional camera motion to manually track prey and record their escape response with high temporal and spatial resolution. These recordings demonstrated that prey were more than 3 times more likely to evade a suction-feeding predator if they responded before (Pescape=0.53, N=43), rather than after (Pescape=0.15, N=13), a predator's mouth opened, which is a highly significant difference. Therefore, flow sensing plays an essential role in predator evasion by facilitating a response prior to a predator's strike.
Where's the Money? The Social Behavior of Investors in Facebook's Small World

Are investing activities dependent on social relationships? In our research, we apply social network analysis to the field of investing behaviors and discover that investors have a tendency to invest in companies that are socially similar to them. While traditional studies on investing behavior tend to focus on factors like psychology, opinions, investing experience etc, they fail to consider social relationship as an important factor. In this paper we provide general rules of thumb that are useful for companies seeking funding from investor. These rules of thumb are generated by analyzing the social relationships between investors and companies found within the small world of Facebook.
Mir-184 Post-Transcriptionally Regulates SOX7 Expression and Promotes Cell Proliferation in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common human malignancies and the third leading cause of cancer mortality worldwide. The development and progression of HCC is a complicated process, involving the deregulation of multiple genes that are essential to cell biological processes. Recently, microRNAs (miRNAs) have been suggested to be closely associated with tumorigenesis. Our study showed that miR-184 is upregulated in HCC cell lines and tissues. Overexpression of miR-184 in HCC cells increased cell proliferation, tumorigenicity, and cell cycle progression, whereas inhibition of miR-184 reduced cell proliferation, tumorigenicity, and cell cycle progression. Additionally, we identified SOX7 as a direct target of miR-184. Ectopic expression of miR-184 led to downregulation of the SOX7 protein, resulting in upregulation of c-Myc, Cyclin D1, and phosphorylation of Rb. Our findings suggested that miR-184 represents a potential onco-miR and plays an important role in HCC progression by suppressing SOX7 expression.
Sharp Sides to the African Superplume

Beneath southern Africa is a large structure about 1200 kilometers across and extending obliquely 1500 kilometers upward from the core-mantle boundary with a shear velocity reduction of about 3%. Using a fortuitous set of SKS phases that travel along its eastern side, we show that the boundary of the anomaly appears to be sharp, with a width less than 50 kilometers, and is tilted outward from its center. Dynamic models that fit the seismic constraints have a dense chemical layer within an upwardly flowing thermal structure. The tilt suggests that the layer is dynamically unstable on geological time scales.
Optimizing Multipliers for the CPU : A ROM based approach

In a modern day CPU, the multiplier has become an important part of an ALU in terms of both power and performance. Modern day multiplier designs provide some enhancements in power and performance over traditional multiplier designs. However, this enhancement, especially from a power perspective, may prove to be inadequate for a low-power application. Using lookup-based tables for multiplication is an attractive alternative to other modern day multiplier applications in order to greatly reduce the amount of power required. Because so much research has been done on reducing the power usage of Read Only Memories (ROMs), lookupbased tables for multiplication can be implemented with a much lower power than traditional designs. While using lookup tables for multiplication has been researched, most approaches still require tables too large for realistic implementation. Both Vinnakota[1] and Ling[4] introduce approaches to reduce the size of their multiplication tables, but neither approach can be used with modern, 32-bit, multipliers feasibly. To achieve multiplication using smaller tables, we introduce a hybrid approach using Vinnakota's method and the Karatsuba algorithm. This hybrid approach is then compared to some of the modern day multiplier architectures. The comparison will be done assuming standard CMOS technology.
Mapping of season length anomalies in Mexico

Parameters describing the cyclic patterns of vegetation phenology can be derived from satellite image time series. The length of the annual vegetation period is a useful summary parameter, important for analyzing broad-scale ecological differences of vegetation and seasonal gains in biomass. Anomalies in season length can be linked to principal seasonal drivers of vegetation growth, namely temperature, precipitation and radiation. This study employs a record of satellite images for Mexico over 17 years. The 16-day composite of MODIS vegetation index at 250m spatial resolution was processed and season length was extracted. The long-term normal depicts longer seasons in southern Mexico and forested areas. Seasonal anomalies show spatial-temporal patterns with major variations in semi-arid northern Mexico, which were linked to climatic drivers.
Probabilistic Model Checking of Regenerative Concurrent Systems

We consider the problem of verifying quantitative reachability properties in stochastic models of concurrent activities with generally distributed durations. Models are specified as stochastic time Petri nets and checked against Boolean combinations of interval until operators imposing bounds on the probability that the marking process will satisfy a goal condition at some time in the interval [α, β] after an execution that never violates a safety property. The proposed solution is based on the analysis of regeneration points in model executions: a regeneration is encountered after a discrete event if the future evolution depends only on the current marking and not on its previous history, thus satisfying the Markov property. We analyze systems in which multiple generally distributed timers can be started or stopped independently, but regeneration points are always encountered with probability 1 after a bounded number of discrete events. Leveraging the properties of regeneration points in probability spaces of execution paths, we show that the problem can be reduced to a set of Volterra integral equations, and we provide algorithms to compute their parameters through the enumeration of finite sequences of stochastic state classes encoding the joint probability density function (PDF) of generally distributed timers after each discrete event. The computation of symbolic PDFs is limited to discrete events before the first regeneration, and the repetitive structure of the stochastic process is exploited also before the lower bound α, providing crucial benefits for large time bounds. A case study is presented through the probabilistic formulation of Fischer's mutual exclusion protocol, a well-known real-time verification benchmark.
Effect on seroprevalence of anti-poliovirus antibodies and on vaccination coverage of the implementation of a DTwP-IPV-Hib vaccination programme in a South American city

SUMMARY Vaccination coverage and seroprevalence of poliovirus antibodies were assessed in Argentinean children (aged 8–12 and 19–21 months) living in Cordoba City pre-/post-implementation of a DTwP-IPV-Hib vaccination programme, and compared to those of controls from neighbouring populations receiving a full oral poliovirus vaccine schedule. Vaccination coverage was higher in control areas pre-intervention; this increased post-intervention in Cordoba (>90%) but not in control areas. Poliovirus types 1 and 2 seroprotection rates were >97% in all groups pre-/post-intervention. Type 3 seroprotection rates were generally lower, but increased post-intervention in Cordoba becoming significantly higher than control rates. Anti-type 1 and 3 antibody titres increased twofold and sevenfold, respectively, post-intervention, whereas anti-type 2 antibody titres decreased ~40% in the 8–12 months group. All titres increased in the 19–21 months post-intervention group. The introduction of a three-dose primary DTwP-IPV-Hib schedule maintained protection against poliovirus types 1 and 2, and increased protection against type 3, while vaccine coverage in the study area increased.