Miracle-dz/UniFAR-FTUs huggingface dataset:
- Rivas Cells Induced Early Signaling and Apoptosis in Breast Tumor − Degradation by the Proteasome and Promotes TRAIL Flavopiridol Induces Cellular FLICE-Inhibitory Protein

The cyclin-dependent kinase inhibitor flavopiridol is undergoing clinical trials as an antitumor drug. We show here that pretreatment of different human breast cancer cell lines with flavopiridol facilitates tumor necrosis factor–related apoptosis-inducing ligand (TRAIL)–induced apoptosis. In breast tumor cells, apoptosis induction by TRAIL is blocked at the level of apical caspase-8 activation. Flavopiridol treatment enhances TRAIL-induced formation of death-inducing signaling complex and early processing of procaspase-8. Subsequently, a TRAIL-induced, mitochondria-operated pathway of apoptosis is activated in cells treated with flavopiridol. Down-regulation of cellular FLICE-inhibitory proteins (c-FLIP; c-FLIPL and c-FLIPS) is observed on flavopiridol treatment. c-FLIP loss and apoptosis sensitization by flavopiridol are both prevented in cells treated with an inhibitor of the ubiquitinproteasome system. Furthermore, targeting c-FLIP directly with small interfering RNA oligonucleotides also sensitizes various human breast tumor cell lines to TRAIL-induced apoptosis. Our results indicate that flavopiridol sensitizes breast cancer cells to TRAIL-induced apoptosis by facilitating early events in the apoptotic pathway, and this combination treatment could be regarded as a potential therapeutic tool against breast tumors. (Cancer Res 2006; 66(17): 8858-69)
affy - analysis of Affymetrix GeneChip data at the probe level

MOTIVATION The processing of the Affymetrix GeneChip data has been a recent focus for data analysts. Alternatives to the original procedure have been proposed and some of these new methods are widely used. RESULTS The affy package is an R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. The package is currently in its second release, affy provides the user with extreme flexibility when carrying out an analysis and make it possible to access and manipulate probe intensity data. In this paper, we present the main classes and functions in the package and demonstrate how they can be used to process probe-level data. We also demonstrate the importance of probe-level analysis when using the Affymetrix GeneChip platform.
The Effects of Differential Lag Reinforcement on Across Session Variability Of Leisure Activities

Variability has been shown to increase when delivery of reinforcement is made contingent upon it. A multiple baseline across participants design was used to examine the effects of an across session lag schedule on the choice of leisure activities of three elementary students diagnosed with autism. During baseline, two participants showed low levels of variability when choosing a leisure activity and one participant displayed a pattern of within session switching. Variable responding increased for all participants when the lag schedule of reinforcement was utilized and continued during fading. During follow-up, one participant continued to respond to the visual stimulus on a Lag 2 schedule without receiving a reinforcer and one participant returned to repetitive responding. This study supports research findings that lag schedules of reinforcement are effective in increasing variability in students with autism. Additionally, it addresses the limitation of frequent switching by utilizing an across session lag schedule.
Expanded abstract: Solution of Simple Assembly Line Balancing Problems with FSS

Assembly lines constitute the main production paradigm of the contemporary manufacture industry. Thus, many optimization problems have been studied aiming to improve the efficacy of its use. In this work, the Fish School Search algorithm and a variation of it that incorporates a routine to avoid stagnation of the search process were applied in order to solve the Simple Assembly Line Balancing Problem - type 1. The results were compared with an exact solution procedure named SALOME and also with the Particle Swarm Optimization algorithm. Both proposed procedures were able to achieve good results and the stagnation avoidance routine incorporated to FSS allowed more uniform distributions of tasks among workstations in the assembly line and converged faster to optimal solutions.
Simplified Neural Model for the Software Development Team Optimization

An apparatus and method for obtaining an electrical signal indicative of the degree of extension of a fluid cylinder, the signal being transmitted to a remote location for use in providing a remote readout of the cylinder position. The displacement of the piston is translated into a rotational movement of a threaded rod coupled to the piston. The rod is, in turn, coupled to a potentiometer or other device that provides an electrical signal indicative of the cylinder extension.
A new framework for recognition of Mandarin syllables with tones using sub-syllabic units

Three classes of subsyllabic units for Mandarin syllables are defined, i.e., the initials, the finals, and the transitions. A new structure for Mandarin syllable recognition is developed, in which the tones and base syllables are recognized jointly and a total of 574 subsyllabic unit models will be enough to provide improved recognition performance. This approach has the potential to be extended to continuous Mandarin speech recognition, although the preliminary experiments demonstrated here are based on isolated syllables only. <<ETX>>
Context-Sensitive Medical Information Retrieval

Substantial medical data such as pathology reports, operative reports, discharge summaries, and radiology reports are stored in textual form. Databases containing free-text medical narratives often need to be searched to find relevant information for clinical and research purposes. Terms that appear in these documents tend to appear in different contexts. The con-text of negation, a negative finding, is of special importance, since many of the most frequently described findings are those denied by the patient or subsequently "ruled out. " Hence, when searching free-text narratives for patients with a certain medical condition, if negation is not taken into account, many of the retrieved documents will be irrelevant. The purpose of this work is to develop a methodology for automated learning of negative context patterns in medical narratives and test the effect of context identification on the performance of medical information retrieval. The algorithm presented significantly improves the performance of information retrieval done on medical narratives. The precision im-proves from about 60%, when using context-insensitive retrieval, to nearly 100%. The impact on recall is only minor. In addition, context-sensitive queries enable the user to search for terms in ways not otherwise available
Understanding the effect of adaptive preference elicitation methods on user satisfaction of a recommender system

In a recommender system that suggests options based on user attribute weights, the method of preference elicitation (PE) employed by a recommender system can influence users' satisfaction with the system, as well as the perceived usefulness and the understandability of the system. Specifically, we hypothesize that users with different levels of domain knowledge prefer different types of PE. While domain experts reported higher satisfaction and perceived usefulness with attribute-based PE (i.e., indicating preference levels for the domain-related attributes), novices preferred case-based PE (i.e., indicating the preference for specific examples, from which attribute-preferences can then be implicitly calculated). The paper discusses the decision-theoretical principles that are believed to lead to this distinction, as well as an experiment that provides substantial evidence for the hypothesis. Consequently, we introduce the idea of adapting the method of PE to users' domain knowledge on the fly using click stream data.
Cross-View Projective Dictionary Learning for Person Re-Identification

Person re-identification plays an important role in many safety-critical applications. Existing works mainly focus on extracting patch-level features or learning distance metrics. However, the representation power of extracted features might be limited, due to the various viewing conditions of pedestrian images in reality. To improve the representation power of features, we learn discriminative and robust representations via dictionary learning in this paper. First, we propose a cross-view projective dictionary learning (CPDL) approach, which learns effective features for persons across different views. CPDL is a general framework for multiview dictionary learning. Secondly, by utilizing the CPDL framework, we design two objectives to learn low-dimensional representations for each pedestrian in the patch-level and the image-level, respectively. The proposed objectives can capture the intrinsic relationships of different representation coefficients in various settings. We devise efficient optimization algorithms to solve the objectives. Finally, a fusion strategy is utilized to generate the similarity scores. Experiments on the public VIPeR and CUHK Campus datasets show that our approach achieves the state-of-the-art performance.
Apolipoprotein E gene and age-related macular degeneration in a Chinese population

Purpose To examine the association between apolipoprotein E (APOE) polymorphisms and age-related macular degeneration (AMD) in a Chinese population. Methods The study consisted of 712 subjects, including 201 controls, 363 cases with early AMD, and 148 cases with exudative AMD. Genomic DNA was extracted from venous blood leukocytes. Common allelic variants of APOE (ε2, ε3, and ε4) were analyzed by PCR and direct sequencing. Results APOE ε3ε3 was the most frequent genotype, with a frequency of 72.6% in controls, 72.5% in early AMD, and 70.3% in exudative AMD. Frequency of the ε2 allele was 6.7% in controls, 7.4% in early AMD, and 8.8% in exudative AMD. Frequency of the ε4 allele was 8.7% in controls, 7.7% in early AMD, and 7.8% in exudative AMD. No statistically significant difference in APOE genotype and allele frequency distribution was observed among controls, cases with early AMD, and cases with exudative AMD. For ε2 allele carriers, the odds ratio was 1.12 (95% confidence interval [CI], 0.65–1.93) for early AMD and 1.06 (95% CI, 0.53–2.10) for exudative AMD. For ε4 allele carriers, the odds ratio was 1.04 (95% CI, 0.61–1.75) for early AMD and 0.83 (95% CI, 0.42–1.62) for exudative AMD. Conclusions Our data provide no evidence to support an association of APOE polymorphisms with early or exudative AMD, suggesting that APOE is less likely to be a major AMD susceptibility gene in the Chinese population.
Devanagari offline handwritten numeral and character recognition using multiple features and neural network classifier

This paper presents an attempt to solve the challenging problem of Devanagari numeral and character recognition. It uses structural and geometric features to represent the Devanagari numerals and characters. Each image is zoned in 9 blocks and 8 structural features are extracted from each block. Similarly 9 global geometric features are extracted. These 81 features are used for representing the image. Multilayer perceptron neural network (MLP-NN) is used for classification. 3000 handwritten samples of Devanagari numerals and 5375 handwritten samples of Devanagari alphabetic characters are used for training and testing. Experimental results show 93.17% recognition accuracy using 40 hidden neurons for numerals and 82.7% recognition accuracy using 60 hidden neurons for characters. Fivefold cross validation is used for verifying the results.
Architecture of an interoperable IoT platform based on microservices

The vision of the Internet of Things enabled the development of a wide spectrum of services, applications and ecosystems, deemed infeasible not long ago. However, lack of standardization poses a number of questions still requiring proper addressing. Due to the need of supporting large number of users and significant data processing throughput, Internet of Things requires a specific approach towards the problem of providing sufficient scalability and performance, clearly pointing towards the distribution of effort among a large number of small and specialized services. Reflecting on the importance of coexistence of heterogeneous systems supporting the Internet of Things, this paper presents an overview of the specific problems inherent to the IoT and the proposal of an architecture of a microservice based middleware aimed at connecting heterogeneous IoT devices. The middleware functionality is achieved irrespective of the size and complexity of a given device network, both from the data model aspect and from the aspect of connecting existing and newly created middleware components.
Multilingual hierarchical MRASTA features for ASR

Recently, a multilingual Multi Layer Perceptron (MLP) training method was introduced without having to explicitly map the phonetic units of multiple languages to a common set. This paper further investigates this method using bottleneck (BN) tandem connectionist acoustic modeling for four high-resourced languages — English, French, German, and Polish. Aiming at the improvement of already existing high performing automatic speech recognition (ASR) systems, the multilingual training of the BN-MLP is extended from short-term to hierarchical longterm (multi-resolutional RASTA) feature extraction. Furthermore, deeper structures and context-dependent target labels are also examined. We experimentally demonstrate that a single state-of-the-art BN feature set can be trained for multiple languages, which is superior to the monolingual feature set, and results in significant gains in all the four languages. Studying the scalability of the multilingual BN features, a similar gain is observed in small (50 hours) and in larger scale (300 hours) ASR experiments regardless of the distribution of the data amount between the languages. Using deeper structures, context-dependent targets, and speaker adaptation, the multilingual BN reduces the word error rates by 3‐7% relative over the target language BN features and 25‐30% over the conventional MFCC system. Index Terms: deep MLP, bottleneck, multilingual, hierarchical, MRASTA, LVCSR
Nonclinical analysis of the safety, pharmacodynamics, and pharmacokinetics of plasma‐derived human FXIII concentrate in animals

Factor XIII (FXIII) is a coagulation protein which plays a major role in hemostasis by covalently cross‐linking fibrin molecules, thereby stabilizing the blood clot and increasing resistance to fibrinolysis. FXIII deficiency, either congenital or acquired, is associated with spontaneous bleeding, increased bleeding time, and poor wound healing. Purified plasma‐derived human FXIII concentrate (pd hFXIII) has been available since 1993 for therapeutic use in congenital FXIII deficiency. This set of nonclinical investigations aimed to evaluate the pharmacodynamic effects and assess the safety profile of pd hFXIII. The efficacy and safety of pd hFXIII were evaluated by pharmacodynamic, pharmacokinetic, and toxicity studies in mice and rats, safety pharmacology studies in dogs, neoantigenicity study, local tolerance, and thrombogenicity tests in rabbits. Administration of pd hFXIII resulted in the correction of deficits in clot formation kinetics and strength as measured by thromboelastometry, and was not associated with thrombus formation up to 350 IU/kg in FXIII knockout mice. There was no production of neoantigens resulting from the viral elimination manufacturing steps detected, and no adverse reactions were observed in toxicity studies with single doses up to 3550 IU/kg in mice and 1420 IU/kg in rats; nor from repeat doses of 350 IU/kg in rats. In addition, local tolerance tests revealed a good tolerability profile in rabbits. Overall, this data showed that pd hFXIII was well tolerated and pharmacodynamically active in preclinical animal models, supporting pd hFXIII as a therapy for FXIII deficiency.
Noise robustness and stochastic tolerance of OT error-driven ranking algorithms

Recent counterexamples show that Harmonic Grammar (HG) error-driven learning (with the classical Perceptron reweighing rule) is not robust to noise and does not tolerate the stochastic implementation (Magri 2014, MS). This article guarantees that no analogous counterexamples are possible for proper Optimality Theory (OT) error-driven learners. In fact, a simple extension of the OT convergence analysis developed in the literature (Tesar and Smolensky 1998, Linguist. Inq., 29, 229–268; Boersma 2009, Linguist. Inq., 40, 667–686; Magri 2012, Phonology, 29, 213–269) is shown to ensure stochastic tolerance and noise robustness of the OT learner. Implications for the comparison between the HG and OT implementations of constraint-based phonology are discussed.
Docetaxel-loaded liposomes: preparation, pH sensitivity, Pharmacokinetics, and tissue distribution

Docetaxel (DTX), as a member of taxoid family, has been widely used in the treatment of cancers. The present study prepared pH-sensitive DTX-loaded liposomes (DTX-Lips) by thin-film dispersion method and various physico-chemical and morphological properties were examined. The pH sensitivity of in vitro DTX release and the in vivo pharmacokinetics and tissue distribution using Kunming mice were also investigated. The mean particle size and zeta potential of DTX liposomes were (277±2) nm and (−32.60±0.26) mV, respectively. Additionally, in vitro drug release study showed that the cumulative release rate was 1.3 times more at pH 5.0 than at pH 7.4, suggesting a pH-dependent release ability of DTX-Lips. Pharmacokinetic and pharmaceutical studies in comparison with Duopafei® showed that the half-time period (t1/2) and area under the curve (AUC) of DTX-Lips in mouse plasma were 1.8 times longer and 2.6 times higher, respectively, and that DTX-Lips selectively accumulated in macrophage-rich organs such as liver and spleen. These results together suggest that the DTX-Lips could be a promising formulation for the clinical administration of DTX.
Panel Discussion on Building and Maintaining Trust in the ABSELesque Classroom

The purpose of this panel is to clarify the benefits of a climate of trust in the classroom. In particular, the panel focuses on building studentsâ€™ trust in teachers who use experiential methods such as exercises or simulations. We contrast a trusting climate to a mistrusting climate, discuss ways to build and maintain trust, and suggest possible consequences of trust. We address expectations and perceptions held by students. Two specific models for building trust are discussed. The first is a content model that identifies ten conditions (antecedent factors) that can lead to trust. The second is a process model that proposes cause-effect relationships for causes and consequences of trust in the classroom.
Does Multispectral Texture Features Really Improve Cervical Cancer Detection

For cervical cancer detection, the performance of multispectral texture (MST) features extracted from multispectral Pap smear images is evaluated. In this study we carried out pairwise comparisons between different image features, including MST versus average spectral texture features (AST, without spectral information), and MST versus multispectral intensity features (MSI, without texture information). We demonstrate, experimentally, that well-selected MST features combining both multispectral and texture information can achieve better classification results (ROC curves) for cervical cancer detection from multispectral Pap smear images. Furthermore, we investigate which type of wavelet texture features (orthogonal, bi-orthogonal or non-orthogonal) individually or in combination is most effective.
Intention to visit Malaysia for medical tourism using the antecedents of Theory of Planned Behaviour: A predictive model

The aim of this study is to examine the extended model of Theory of Planned Behaviour in predicting tourists' intention in seeking medical tourism in Malaysia. The additional variables in this model are perceived risks, perceived benefits and resource availability whereby it is predicted to have influences to the model of Theory of Planned Behaviour. Sample is drawn using a quota sampling technique. A total of 380 completed questionnaires are collected. The partial least square approach is employed so as to conduct a comprehensive and vigorous structural equation modelling analysis. The results show that perceived benefits and perceived costs are significantly related to attitude; resource availability is significantly related to perceived behavioural control; and attitude and subjective norm are significantly related to intention for medical tourism in Malaysia; however, the perceived behavioural control is found to be insignificant to intention. Attitude and subjective norm are also significantly related to intention for medical tourism in Malaysia. However, the perceived behavioural control is found to be not insignificant related to intention. The findings of this study can serve as the blueprint for future research in the similar area with reasonable modification on the model construction in order to enhance and improve the theoretical extension model of Theory of Planned Behaviour.
The relationship between acculturation and the effects of caregiving of the elderly among Cuban-Americans

OF THE THESIS THE RELATIONSHIP BETWEEN ACCULTURATION AND THE EFFECTS OF CAREGIVING OF THE ELDERLY AMONG CUBAN-AMERICANS by Georgia de las Pozas Florida International University, 1999 Miami, Florida Professor Gail Ann Hills, Major Professor The purpose of this study was to establish the perceived caregiving effects among thirty Cuban-born individuals caring for elderly relatives and the relationship of these effects with acculturation. Most common difficulties were lack of private time, or social life, and decreased emotional and physical health. Satisfactions were mostly derived from fostering the elders' welfare. A strong positive relationship was found between caregivers' difficulties and stability of the caregiving dyad (r= 0.642, p< .001). Caregivers involved in more unstable caregiver-care receiver dyads had more stress associated with caregiving difficulties. The acculturation factors of language, electronic media, and social relations, and the stability of the caregiving dyad accounted for 54 percent of the variation in caregivers' difficulties (p< .001) but only 21 percent of the variation of caregivers' satisfaction (p<.2 2 1), These findings provided preliminary data of caregiving characteristics among Cuban-Americans and the importance of including acculturation in studies involving
Locating the Wood Defects with Damped Newton Approaches based Non-negative Matrix Factorization

Non-negative matrix factorization (NMF) is an unsupervised method whose aim is to find an approximate factorization Vn*m=Wn*r*Hr*m into non-negative matrices Wn*r and Hr*m. This paper presents an extension to NMF and discusses the development and the use of damped Newton based the non-negative matrix factorization called DNNMF with good convergence property for wood defects detection. We also provide algorithms for computing these new factorizations and the supporting theoretical analysis. DNNMF can make sure the convergence of the cost function and has been tested with color wood images based on the statistical features extracted by local binary pattern (LBP). Finally, we present experimental results that explore the properties of DNNMF. Comparative experiments show DNNMF is effectual and practical with good research values and potential applications.