Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-negative dynamical system with application to speech and audio

Non-negative data arise in a variety of important signal processing domains, such as power spectra of signals, pixels in images, and count data. This paper introduces a novel non-negative dynamical system (NDS) for sequences of such data, and describes its application to modeling speech and audio power spectra. The NDS model can be interpreted both as an adaptation of linear dynamical systems (LDS) to non-negative data, and as an extension of non-negative matrix factorization (NMF) to support Markovian dynamics. Learning and inference algorithms were derived and experiments on speech enhancement were conducted by training sparse non-negative dynamical systems on speech data and adapting a noise model to the unknown noise condition. Results show that the model can capture the dynamics of speech in a useful way.
Achievable Bisimilar Behaviour of Abstract State Systems

Given a plant system and a desired system, we study conditions for which there exists a controller that interconnected with the plant, yields a system that is bisimilar to the desired system. Some sufficient and some necessary conditions are provided in the general case of (non-deterministic) abstract state systems and stronger results are obtained for the special classes of autonomous abstract state systems, finite abstract state systems, and non-deterministic linear dynamical systems.
Probabilistic Regularized Extreme Learning Machine for Robust Modeling of Noise Data

The extreme learning machine (ELM) has been extensively studied in the machine learning field and has been widely implemented due to its simplified algorithm and reduced computational costs. However, it is less effective for modeling data with non-Gaussian noise or data containing outliers. Here, a probabilistic regularized ELM is proposed to improve modeling performance with data containing non-Gaussian noise and/or outliers. While traditional ELM minimizes modeling error by using a worst-case scenario principle, the proposed method constructs a new objective function to minimize both mean and variance of this modeling error. Thus, the proposed method considers the modeling error distribution. A solution method is then developed for this new objective function and the proposed method is further proved to be more robust when compared with traditional ELM, even when subject to noise or outliers. Several experimental cases demonstrate that the proposed method has better modeling performance for problems with non-Gaussian noise or outliers.
Design of Classifier Using Artificial Neural Network for Patients Survival Analysis

The aim of this paper is to develop the design of classifier using Artificial Neural Network for patients survival analysis based on echocardiography dataset. Survival analysis can be considered a classification problem in which the application of machine learning methods is appropriate. Survival analysis plays an important role not only for health care policy markers, but also for the clinician. Echocardiography is used for diagnosis of cardiac diseases and to arrive at precise diagnosis experienced cardiologists need complementary assistance from intelligent decision system. Artificial Neural Networks have emerged as an important tool for classification. The advantage of Artificial Neural Network helps for efficient classification of given data. In this research paper, design the classifiers Back Propagation Neural Network (BPNN) and Radial Basis Function Neural Network (RBFNN) for patient's survival analysis. The performance of classifiers is measured in terms of classification accuracy. Experimental result showed that the good design of classifier for patients survival analysis based on Echocardiogram database is Back propagation neural network (BPNN) with training set classification accuracy 93% and testing set classification accuracy 84% and design of Radial Basis function neural network (RBFNN) classifier training set classification accuracy 88% and testing set classification accuracy 69%.
Social and Environmental Disclosure by Parastatals and Companies Listed on the Botswana Stock Exchange

The need to communicate social and environmental effects of business operations to society has been with us forover four decades now. However, due to diverse factors the pace of introducing social and environmentalreporting in developing countries has been slow. The purposes of this study are: to determine whether companieslisted on the Botswana Stock Exchange and Parastatals in Botswana report on social and environmental issues intheir annual reports and to what extent they disclose such information; to establish whether there is a differencein the level of reporting between listed companies and parastatals; and to determine whether size, type ofindustry and ownership influence the extent of disclosure. All listed companies and parastatals operating inBotswana formed the population of this study. Secondary data obtained from annual reports was reviewed andcontent analysis was employed to determine the extent of social and environment reporting. The extent ofdisclosure was measured using number of sentences describing the key themes such as human resources,environmental issues and community involvement. Regression analysis was used to find the association betweendependent variable (extent of disclosure) and three independent variables namely size of the company,ownership and type of industry. The results suggest that social and environment reporting exists in Botswanaentities and listed companies tend to disclose more than parastatals. The findings also show that size, type ofindustry and ownership are not good predictors of the level of social and environmental disclosure in Botswanaentities.
Specific Gene bciD for C7-Methyl Oxidation in Bacteriochlorophyll e Biosynthesis of Brown-Colored Green Sulfur Bacteria

The gene named bciD, which encodes the enzyme involved in C7-formylation in bacteriochlorophyll e biosynthesis, was found and investigated by insertional inactivation in the brown-colored green sulfur bacterium Chlorobaculum limnaeum (previously called Chlorobium phaeobacteroides). The bciD mutant cells were green in color, and accumulated bacteriochlorophyll c homologs bearing the 7-methyl group, compared to C7-formylated BChl e homologs in the wild type. BChl-c homolog compositions in the mutant were further different from those in Chlorobaculum tepidum which originally produced BChl c: (31 S)-8-isobutyl-12-ethyl-BChl c was unusually predominant.
Identification of Novel Host Interactors of Effectors Secreted by Salmonella and Citrobacter

During infection, pathogenic bacteria face an adverse environment of factors driven by both cellular and humoral defense mechanisms. To help evade the immune response and ultimately proliferate inside the host, many bacteria evolved specialized secretion systems to deliver effector proteins directly into host cells. Translocated effector proteins function to subvert host defense mechanisms. Numerous pathogenic bacteria use a specialized secretion system called type III secretion to deliver effectors into the host cell cytosol. Here, we identified 75 new host targets of Salmonella and Citrobacter effectors, which will help elucidate their mechanisms of action. ABSTRACT Many pathogenic bacteria of the family Enterobacteriaceae use type III secretion systems to inject virulence proteins, termed “effectors,” into the host cell cytosol. Although host-cellular activities of several effectors have been demonstrated, the function and host-targeted pathways of most of the effectors identified to date are largely undetermined. To gain insight into host proteins targeted by bacterial effectors, we performed coaffinity purification of host proteins from cell lysates using recombinant effectors from the Enterobacteriaceae intracellular pathogens Salmonella enterica serovar Typhimurium and Citrobacter rodentium. We identified 54 high-confidence host interactors for the Salmonella effectors GogA, GtgA, GtgE, SpvC, SrfH, SseL, SspH1, and SssB collectively and 21 interactors for the Citrobacter effectors EspT, NleA, NleG1, and NleK. We biochemically validated the interaction between the SrfH Salmonella protein and the extracellular signal-regulated kinase 2 (ERK2) host protein kinase, which revealed a role for this effector in regulating phosphorylation levels of this enzyme, which plays a central role in signal transduction. IMPORTANCE During infection, pathogenic bacteria face an adverse environment of factors driven by both cellular and humoral defense mechanisms. To help evade the immune response and ultimately proliferate inside the host, many bacteria evolved specialized secretion systems to deliver effector proteins directly into host cells. Translocated effector proteins function to subvert host defense mechanisms. Numerous pathogenic bacteria use a specialized secretion system called type III secretion to deliver effectors into the host cell cytosol. Here, we identified 75 new host targets of Salmonella and Citrobacter effectors, which will help elucidate their mechanisms of action.
Prenatal VPA Exposure and Changes in Sensory Processing by the Superior Colliculus

Disorders involving dysfunctional sensory processing are characterized by an inability to filter sensory information, particularly simultaneously arriving multimodal inputs. We examined the effects of prenatal exposure to valproic acid (VPA), a teratogen linked to sensory dysfunction, on the behavior of juvenile and adult rats, and on the anatomy of the superior colliculus, a critical multisensory integration center in the brain. VPA-exposed rats showed deficits in colliculus-dependent behaviors including startle response, prepulse inhibition, and nociceptive responses. Some deficits reversed with age. Stereological analyses revealed that colliculi of VPA-treated rats had significantly fewer parvalbumin-positive neurons, a subset of GABAergic cells. These results suggest that prenatal VPA treatment affects the development of the superior colliculus and leads to persistent anatomical changes evidenced by aberrant behavior in tasks that require sensory processing.
Convergence of visual and whisker responses in the primary somatosensory thalamus (ventral posterior medial region) of the mouse

Using in vivo electrophysiology, we find that a subset of whisker‐responsive neurons in the ventral posterior medial region (VPM) respond to visual stimuli. These light‐responsive neurons in the VPM are particularly sensitive to optic flow. Presentation of optic flow stimuli modulates the amplitude of concurrent whisker responses. Visual information reaches the VPM via a circuit encompassing the visual cortex. These data represent a new example of cross‐modal integration in the primary sensory thalamus.
Phil . trans . R . Soc Universal Turing Machine

Many electrical engineers would agree that, had it not been for evolutionary programming, the natural unification of replication and 802.11b might never have occurred. In fact, few cyberneti-cists would disagree with the construction of hash tables. In this work, we propose an application for agents (VelarTirwit), disproving that the producer-consumer problem can be made atomic, pseudorandom, and knowledge-base.
Stereo line matching based on the combination of geometric and intensity data

This paper presents a line matching method for the reconstruction of 3D line segment, based on geometric and intensity information. Line matching is a difficult task in the area of stereo vision, since it relies on incomplete line data. A set of line attributes is used to match a pair of 2D lines. Line attributes consist of intensity information and geometric information including length, orientation, and endpoint position. For the implementation of the proposed matching method, we employ multi-threshold technique, which provides flexible and efficient matching capability. The experimental results show that the rate of the correct match comes up with 96.12%, which is very hard to be achieved in the complex scene used in the experiment.
Goal-Directed Abstraction

A critical component of an abstract interpretation algorithm is the abstract domain, and traditionally, it is manually defined. Recently, automatic abstract interpretation techniques have emerged. A prominent technique, called Counter Example Guided Abstraction Refinement (CEGAR), and is based on an iterative process given a target property. Beginning with an abstract domain with a low level of detail, failure to prove the property gives rise a process of abstraction refinement so that the next iteration can use a new abstract domain with a higher level of detail. The idea is to build the final abstract domain with just the right amount of detail. In this paper, we present a complementary approach: we abstract on demand, as opposed to refine on demand. Starting with no abstraction at all, our algorithm iteratively builds, if needed, abstract domains with lesser detail. We demonstrate advantages of our algorithm over CEGAR.
Diffusion Tensor Imaging on Teenagers, Born at Term With Moderate Hypoxic-ischemic Encephalopathy

Hypoxic-ischemic encephalopathy (HIE) is graded with three levels of severity—mild, moderate and severe. The outcome of individuals with mild and severe grades can be reliably predicted from this scheme. Individuals with moderate degree are divided in outcome between those who suffer major neurologic problems (e.g., cerebral palsy) and those who are assumed to recover from the incident. It is however not clear if the recovery is complete and unquestionable.A group of adolescents who had been born at term, diagnosed with moderate HIE but had not developed cerebral palsy, were investigated with diffusion tensor imaging. Fractional anisotropy maps were used as a basis of comparison to a group of controls of the same age and gender distribution.In several white matter areas fractional anisotrophy was lower in the group of individuals with a history of moderate HIE. These areas include the internal capsules (bilaterally in the posterior limb and on the right in the anterior limb), the posterior and anterior corpus callosum as well as frontal inferior white matter areas.These results indicate that even in the absence of such major neurologic impairments as cerebral palsy, moderate HIE causes long term white matter disturbances which are not repaired by adolescence.
REVIEW - What Best Constrains Galaxy Evolution in the Local Universe

After a polemical introduction about the proper activity of an astrophysicist facing a dominant theoretical model and many Tb of highly informative data, I review a few recent results on the properties of galaxies in the nearby (redshift one-tenth) Universe that directly bear on physical cosmology. In one example, I show that there are a number of ways of measuring, or strongly constraining, massive galaxy-galaxy major merger rates, which are predicted with limited uncertainties in the current generation of models. In another, I show that we can go beyond "correlations" between individual galaxy properties and "environment". Our results show that it is galaxy star-formation histories--not their morphologies--that are sensitive to environmental density. I look forward to a future, perhaps not that far away, in which these results guide a fundamental modification to our theoretical assumptions, though I fear that the dominant paradigm may not require subversion.
Development of the sales locus of control scale

The sales locus of control scale (SLCS), composed of 12 items, was developed to measure the constructs of internal, chance and powerful others. A total of 1153 Taiwan insurance and industrial salespeople were used for development and evaluation of the scale. Construct validity, validities related to 29 criteria and reliabilities were all evaluated. Results indicated that reliabilities, the construct validity and most criterion-related validities are supported. Results also indicated that the criterion validities of the SLCS are generally better than those of locus of control scales developed by Rotter, Levenson and Spector. Moreover, situation-specific and multi-dimensional SLCS contains fewer items, and its validity is less attenuated by social desirability. The usefulness of the scale is also discussed.
Repetitive Analyses of P-Glycoprotein in Chronic Myeloid Leukaemia

Abstract P-glycoprotein, a pump located in the plasma cell membrane, extrudes several clinically important drugs from the cell, and hence causes multidrug resistance. Reversing clinical drug resistance is possible by using agents that inhibit the activity of P-glycoprotein. We describe the results of sequential flow cytometric determinations of P-glycoprotein expression and activity in two patients suffering from acute lymphoblastic transformation of chronic myeloid leukaemia. Neither P-glycoprotein expression, nor its activity could be detected in the initial sample of the first patient. In the second patient, no P-glycoprotein expression was found at diagnosis. However, after chemotherapy containing P-glycoprotein substrates, a significant expression was found in both patients and the functional flow cytometric test was positive. In order to achieve an accurate selection of patients that might benefit from the clinical use of Pgp inhibitors, repeated analyses are indicated in each patient suffering from acute leukaemia, during the course of the illness.
Attitudes Toward People Living With HIV/AIDS: A Model of Attitudes to Illness 1

This study examined attitudes toward people living with HIV/AIDS within a sample of 220 young men and women. As predicted, a multiple regression analysis revealed that the fear of contracting HIV/AIDS through casual contact was a significant predictor of both men's and women's willingness to interact with people living with HIV/AIDS. Attitudes toward homosexuality were also a significant predictor of attitudes toward people living with HIV/AIDS among women, who generally have a low risk of contracting the disease in Western societies. These results indicate that attitudes toward people with a serious illness may be strongly related to the perceived risk of contracting the disease.
Efficient Routing Using Node Pull Out Estimation

Recently, when the disaster occurred, the lifesaving emergency method that was called triage are being introduced. Purpose of triage is to decide the lifesaving order from patient’s condition and to save more preventable deaths. The sensor network is constructed by using the computerized tag, and the research of the emergency lifesaving support system that observes and collects information on patient is active. We state this network as triage network. When the data of patient is collected through the sensor network, it is necessary to consider battery power of the sensor node. If the battery ran out, not only the patient data measured with the node is not obtained but also the relaid data is lost. In this paper, we propose N2LE, combining delayedRREP by estimated lifetime and triggeredRREQ. The purpose of N2LE is to reduce the difference between node lifetime and network lifetime that is caused by battery problem. Battery that can be used in delayedRREP by estimated lifetime for the network is quantified and reflects it in the route. When the change takes place in the battery environment, the route is restructured in triggeredRREQ. We evaluate our proposal using simulations, and results show that our proposal achieves longer network lifetime while node lifetime kept similar.
Examination of the Mechanisms Underlying Effectiveness of the Turtle Technique

A significant number of young children exhibit challenging behaviors in preschool settings. A tiered framework of intervention has documented effectiveness in elementary and secondary schools, and recently has been extended to preschool settings. Although there is emerging research to support the effectiveness of Tier 1 (universal) and Tier 3 (intensive) interventions with young children, few studies have evaluated Tier 2 interventions. In this investigation, we examined the effects of the Turtle Technique, a Tier 2 self-control intervention, with three children ages 3 to 4 using a multiple baseline across participants design. In addition, we examined operational components of the intervention. Results showed reductions in behavior following intervention implementation; however, direct observations indicated that the children did not utilize overt techniques as taught. The findings imply that additional research is needed to determine the mechanisms responsible for behavior change as a result of the Turtle Technique.
Structure of spaces of rhombus tilings in the lexicograhic case

Rhombus tilings are tilings of zonotopes with rhombohedra. We study a class of \emphlexicographic rhombus tilings of zonotopes, which are deduced from higher Bruhat orders relaxing the unitarity condition. Precisely, we fix a sequence $(v_1, v_2,\dots, v_D)$ of vectors of $ℝ^d$ and a sequence $(m_1, m_2,\dots, m_D)$ of positive integers. We assume (lexicographic hypothesis) that for each subsequence $(v_{i1}, v_{i2},\dots, v_{id})$ of length $d$, we have $det(v_{i1}, v_{i2},\dots, v_{id}) > 0$. The zonotope $Z$ is the set $\{ Σα _iv_i 0 ≤α _i ≤m_i \}$. Each prototile used in a tiling of $Z$ is a rhombohedron constructed from a subsequence of d vectors. We prove that the space of tilings of $Z$ is a graded poset, with minimal and maximal element.
Employment Sector Choice in a Developing Labor Market

I develop a model of endogenous choice of employment sector in an intertemporal context for a two-sector economy. I show how unemployment duration while awaiting employment in the high-wage sector is an increasing function of the wage differential between sectors, a decreasing function of the expected differential in unemployment duration and a decreasing function of the individual discount rate. I test and find empirical support for this argument using data from the 1998 Moroccan labor force survey, with the high wage sector being the public sector, and the low-wage sector being the private sector. I use data from a sample of 1,609 university graduates and consider a structural model estimating (1) the decision to work (or to seek employment) in the public versus private sector, (2) the wage equation in each sector, and (3) the unemployment duration equation in each sector. Structural estimates indicate that earnings and unemployment durations significantly influence the choice of employment sector. The other main empirical results of this study are that the individual intertemporal discount rate is 2.3%, and that the "wage premium" of the public sector measured by the starting hourly wages gap is over 42.5%. JEL Classification: J24, J31, J42, J45, J64
Query Optimization in Multidatabase Systems Considering Schema Conflicts

In a multidatabase system, the participating databases are autonomous. The schemas of these databases may be different in various ways, while the same information is represented. A global query issued against the global database needs to be translated to a proper form before it can be executed in a local database. Since data requested by a query (or a part of a query) is sometimes available in multiple sites, the site (database) that processes the query with the least cost is the desired query processing site. The authors study the effect of differences in schemas on the cost of query processing in a multidatabase environment. They first classify schema conflicts to different types. For each type of conflict, they show how much more or less complex a translated query can become in comparison with the originally user-issued global query. Based on this observation, they propose an analytical method that considers the conflicts between local databases and finds the database(s) that renders the least execution cost in processing a global query. This research introduces a new level of query optimization (termed the schema-level optimization) in multidatabase environments. The results provide a new dimension of enhancement for the capability of a query optimizer in multidatabase systems.