Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear dimensionality reduction by curvature minimization

In this paper, we introduce a nonlinear dimensionality reduction (NLDR) technique that can construct a low-dimensional embedding efficiently and accurately with low embedding distortions. The key idea is to divide NLDR into nonlinearity reduction and linear dimensionality reduction, which simplifies the overall NLDR process. Nonlinearity reduction is based on the elastic shell model that measures the in-plane stretching and bending energy. With this model, we minimize the curvature of the data, which is the source of nonlinearity, while preserving the original intrinsic property (i.e., local lengths) as-much-as possible. We discretize and linearize our nonlinearity reduction model such that it leads to an iterative deformation technique that alternates between two steps in order to flatten a manifold: the curvature minimization step that solves a bi-Laplace system and the local length restoration step that solves a Poisson system. We propose an efficient optimization technique for the both steps using a direct solver based on Cholesky decomposition, which exploits the fact that the system matrices stay constant; during iterations, we reuse the factorizations that are obtained once at the beginning and perform back substitutions only. Since our algorithm relies only on local geometric properties, it can accurately embed the data with complicated topology. Experimental results show that our algorithm is faster than the most of other state-of-the-art algorithms and preserves local areas and angles better than previous approaches.
Study Protocol: Validation and Adaptation of community-worker-administered stroke symptom questionnaire in a periurban Pakistani community to determine disease burden.

BACKGROUND Stroke is the second leading cause of mortality and the leading cause of disability in the world today. The disease burden is on the rise in developing nations, but there is scarcity of data from these regions to inform policy decisions. Stroke burden can be determined by clinical diagnosis alone in the public health context and is a far more feasible way to assess disease status in low- to middle-income countries like Pakistan. We aim to translate and adapt a validated stroke symptom questionnaire, train community health workers in its administration, and verify it against assessment by two trained neurologists. METHODS/DESIGN This is a prospective study, which we aim to carry out in Ibrahim Hyderi, a periurban slum of Karachi. We translated into Urdu the questionnaire for verifying stroke free status (QVSFS), which is an internationally validated tool to assess the same. Two community health workers (CHW) will be identified and will receive training by neurologists, which will include teaching regarding stroke pathophysiology, symptomatology, and detection. They will be familiarized with the QVSFS, and their questionnaire administration will be assessed through roleplay. We intend to recruit 322 subjects from the same community and the CHWs will gather data on them. The same subjects will later be assessed by two trained neurologists, and the findings collaborated to validate those obtained by the CHWs. Sensitivity, specificity, positive and negative predictive values, and Cohen's kappa will be determined for the CHW-administered questionnaire tested against assessment by two neurologists together and separately for the two CHWs. Data analysis will be done using SPSS version 19.0. DISCUSSION The results of this study will determine if and how well CHW-administered questionnaires are at assessing stroke status in a community. This will facilitate use of the same as a practical alternative for stroke surveillance in the country. TRIAL REGISTRATION NCT02073955.
Empirical Proof of the CAPM with Higher Order Co-moments in Nigerian Stock Market: The Conditional and Unconditional Based Tests

This study examines the significance of the risk factors in the CAPM with higher order co-moments using a two-pass methodological technique of Fama and Macbeth. Stock prices of 53 companies out of the 207 listed in Nigerian Stock Exchange (NSE) for a sample period January 2003 to December 2011 are analyzed. The study particularly augments the model using unconditional and conditional information. The unconditional test reveals that only the co-skewness risk is priced while the covariance and co-skewness demonstrate weak relationship with asset returns; while the conditional test shows that all the risk factors in the up-market are not priced but the covariance and co-skewness risk play significant role in explaining asset returns in the down-market phase. However, the conditional information has improved the descriptive ability of the model.
Estimation of structure and physical relations among multi-modal sensor variables for musculoskeletal robotic arm

Autonomous robots that work in the same environment as humans must operate safely and adapt to handle various tools and deal with partial malfunctions. We propose an approach for estimating the robot structure and apply this approach for building a controller of dynamic motions. The robot structure is estimated by evaluating the mutual information (MI) among the sensor variables. Variables with high values of MI are edge-connected and the controller is automatically constructed based on the estimated structure. The proposed approach can accommodate changes in the robot parameters and dynamic motions. We verify the proposed method by using a simulator of a musculoskeletal arm driven that is driven by artificial muscle for mechanical safety.
The dose-dependent toxicological effects and potential perturbation on the neurotransmitter secretion in brain following intranasal instillation of copper nanoparticles

Abstract Increasing production and application of metallic nanomaterials are likely to result in the release of these particles into the environment. These released nanoparticles may enter into the lungs and the central nervous system (CNS) directly through inhalation, which therefore poses a potential risk to human health. Herein, we focus on the systemic toxicity and potential influence on the neurotransmitter secretion of intranasally instilled copper nanoparticles (23.5 nm) at three different doses. Copper nanoparticle-exposed mice exhibit pathological lesions at different degrees in certain tissues and especially in lung tissue as revealed by histopathology and transmission electron microscopy (TEM) observations. Inductively-coupled plasma mass spectrometry (ICP-MS) results show that the liver, lung and olfactory bulb are the main tissues in which the copper concentrations increased significantly after exposure to a higher level of Cu nanoparticles (40 mg/kg of body weight). The secretion levels of various neurotransmitters changed as well in some brain regions, especially in the olfactory bulb. Our results indicate that the intranasally instilled copper nanoparticles not only cause the lesions where the copper accumulates, but also affect the neurotransmitter levels in the brain.
Deficits in recognition of emotional facial expression are still present in alcoholics after mid- to long-term abstinence.

OBJECTIVE Emotional facial expression (EFE) decoding skills play a key role in interpersonal relationships. Decoding errors have been described in several pathological conditions, including alcoholism. The aim of this study was to investigate whether EFE decoding skill deficits persist after abstention from alcohol of at least 2 months. METHOD Alcoholic patients abstinent for at least 2 months (n = 25) were compared with 25 recently detoxified patients and with 25 normal controls matched for age, gender and educational level. Subjects were presented with 40 photographs of facial expressions portraying happiness, anger, sadness, disgust and fear. Each emotion was displayed with neutral, mild, moderate and strong emotional intensity. Each facial expression was judged successively on eight scales labeled happiness, sadness, fear, anger, disgust, surprise, shame and contempt. For each scale, subjects rated the estimated intensity level. A complementary scale assessed the self-estimated difficulty in performing the task. RESULTS Recently detoxified alcoholics were significantly less accurate than controls, making more EFE labeling errors and overestimating the intensity of the portrayed emotions. Deficits in decoding accuracy for anger and disgust were present in mid- to long-term abstinent patients; intensity overestimation was present in the former and absent in the latter. CONCLUSIONS Deficits in decoding accuracy for anger and disgust, and to a lesser degree sadness, persist with an abstinence of 2 months and beyond. Right frontotemporal regions and cingulate could be implicated. These deficits may contribute to the social skills deficits frequently encountered in alcoholic patients.
Tweaking Association Rules to Optimize Software Change Recommendations

Past researchs have been trying to recommend artifacts that are likely to change together in a task to assist developers in making changes to a software system, often using techniques like association rules. Association rules learning is a data mining technique that has been frequently used to discover evolutionary couplings. These couplings constitute a fundamental piece of modern change prediction techniques. However, using association rules to detect evolutionary coupling requires a number of configuration parameters, such as measures of interest (e.g. support and confidence), their cut-off values, and the portion of the commit history from which co-change relationships will be extracted. To accomplish this set up, researchers have to carry out empirical studies for each project, testing a few variations of the parameters before choosing a configuration. This makes it difficult to use association rules in practice, since developers would need to perform experiments before applying the technique and would end up choosing non-optimal solutions that lead to wrong predictions. In this paper, we propose a fitness function for a Genetic Algorithm that optimizes the co-change recommendations and evaluate it on five open source projects (CPython, Django, Laravel, Shiny and Gson). The results indicate that our genetic algorithm is able to find optimized cut-off values for support and confidence, as well as to determine which length of commit history yields the best recommendations. We also find that, for projects with less commit history (5k commits), our approach produced better results than the regression function proposed in the literature. This result is particularly encouraging, because repositories such as GitHub host many young projects. Our results can be used by researchers when conducting co-change prediction studies and by tool developers to produce automated support to be used by practitioners.
Involvement of Intracellular Calcium Stores during Oxygen/Glucose Deprivation in Striatal Large Aspiny Interneurons

Striatal large aspiny interneurons were recorded from a slice preparation using a combined electrophysiologic and microfluorometric approach. The role of intracellular Ca2+ stores was analyzed during combined oxygen/glucose deprivation (OGD). Before addressing the role of the stores during energy deprivation, the authors investigated their function under physiologic conditions. Trains of depolarizing current pulses caused bursts of action potentials coupled to transient increases in intracellular calcium concentration ([Ca2+]i). In the presence of cyclopiazonic acid (30 μmol/L), a selective inhibitor of the sarcoendoplasmic reticulum Ca2+ pumps, or when ryanodine receptors were directly blocked with ryanodine (20 μmol/L), the [Ca2+]i transients were progressively smaller in amplitude, suggesting that [Ca2+]i released from intracellular stores helps to maintain a critical level of [Ca2+]i during physiologic firing activity. As the authors have recently reported, brief exposure to combined OGD induced a membrane hyperpolarization coupled to an increase in [Ca2+]i. In the presence of cyclopiazonic acid or ryanodine, the hyperpolarization and the rise in [Ca2+]i induced by OGD were consistently reduced. These data support the hypothesis that Ca2+ release from ryanodine-sensitive Ca2+ pools is involved not only in the potentiation of the Ca2+ signals resulting from cell depolarization, but also in the amplification of the [Ca2+]i rise and of the concurrent membrane hyperpolarization observed in course of OGD in striatal large aspiny interneurons.
Performance of Standard Phenotypic Assays for TonB Activity, as Evaluated by Varying the Level of Functional, Wild-Type TonB

ABSTRACT The ability of gram-negative bacterial cells to transport cobalamin and iron-siderophore complexes and their susceptibility to killing by some bacteriophages and colicins are characteristics routinely used to assay mutations of proteins in the TonB-dependent energy transduction system. These assays vary greatly in sensitivity and are subject to perturbation by overexpression of TonB and, perhaps, other proteins that contribute to the process. Thus, the choice of assay and the means by which a potential mutant is expressed can greatly influence the interpretation and recognition of a given mutant. In the present study, we expressed TonB at several different quantified levels in cells that were then subjected to a panel of assays. Our results suggest that it is reasonable to regard the assays as having windows of sensitivity. Thus, while no single assay satisfactorily spans the potential range of TonB activity, it is evident that certain assays are better suited for resolving small deviations from wild-type levels of activity, with others most useful when activity levels are very low. It is apparent from the results that the application of all possible assays to the characterization of new mutants will yield the most meaningful results.
Youth suicide attempts and the dose–response relationship to parental risk factors: a population-based study

Background There is a lack of specific knowledge about the dose–response effect of multiple parental risk factors for suicide attempts among children and adolescents. The aim of this study was to determine the dose–response effect of multiple parental risk factors on an offspring's risk for suicide attempt. Method We designed a population-based two-generation nested case–control study and used Danish register data. A population of 403 431 individuals born between 1983 and 1989 was sampled. Among these, 3465 (0.8%) were registered as having had a suicide attempt. Twenty controls were matched to each case and a link to the offspring's biological parents was established. Results There was a dose–response relationship between the number of exposures and the risk of suicide attempts, with the increased risk seeming to be a multiplicative effect. Parental suicide, suicide attempt, psychiatric illness and low level of income were all significant independent risk factors for offspring's suicide attempts. Conclusions Knowledge of the effect of multiple risk factors on the likelihood of suicide attempts in children and adolescents is important for risk assessment. Dose–response effects of multiple parental risk factors are multiplicative, but it is rare for children and adolescents to be exposed to multiple parental risk factors simultaneously. Nevertheless, they should be considered along with the offspring's own multiple risk factors in determining the overall risk of a suicide attempt. Further research incorporating both parental and offspring's risk factors is indicated to determine the overall dose–response effect of multiple risk factors.
A miniaturized microstrip common resonator triplexer without extra matching network

A miniaturized microstrip triplexer with a common resonator has been proposed in this paper. By exploiting the variable frequency response of stepped-impedance resonator, the common resonator can be shared by three filter channels of a triplexer if its fundamental and higher-order spurious resonant frequencies are properly assigned. The proposed triplexer with a third-order Chebyshev frequency response at each channel is composed of only seven resonators. Moreover, extra matching network placed on the input port is needed for the conventional triplexer, but it is not needed for the proposed one. Experimental triplexer is fabricated and measured to verify the usefulness of the proposed concept. The measured results are in a good agreement with the simulated predictions. The size of the triplexer is only approximately 0.48 lambdag x 0.32 lambdag, showing a very small size.
Chromatin configurations and meiotic competence of oocytes are related to follicular diameter in nonstimulated rhesus monkeys.

Specific aims of this study were to compare relationships between size of intact antral follicles and meiotic competence, diameters, and chromatin configurations of germinal vesicle (GV) oocytes in non-gonadotropin-stimulated rhesus monkeys. Intact antral follicles were dissected from excised ovaries of nine normally cycling monkeys in the follicular phase of the menstrual cycle and of two acyclic monkeys. Follicles were classified according to diameter: I (200-450 microns), II (451-700 microns), III (701-1000 microns) and IV (> 1000 microns). Cumulus-enclosed oocytes were released from follicles and either measured (diameter) and fixed immediately or cultured for 48 h in modified CMRL medium containing 0.5 micrograms/ml ovine FSH, 10 micrograms/ml ovine LH, and 10% bovine calf serum. Following Hoechst staining, three distinct patterns of chromatin organization (GV1-3) were identified in GV oocytes according to the degree of association with the nucleolar periphery (encapsulation or "rimming"). In antral follicles > 450 microns in diameter, perinucleolar encapsulation (GV3) of oocytes before culture and meiotic maturation (metaphase II) of oocytes after culture increased (p < 0.01) with antral follicle growth in a graded fashion. While 56.3% of oocytes from large (> 1000 microns) follicles completed maturation, few (9.3%) oocytes from small (200-450 microns) follicles were competent to mature in vitro. At 0 h of culture, class IV follicles contained a greater (p < 0.01) proportion of GV3 oocytes and a smaller (p < 0.01) proportion of GV1 oocytes than classes I, II, and III follicles. (ABSTRACT TRUNCATED AT 250 WORDS)
Semantic mapping and semantics-boosted navigation with path creation on a mobile robot

Movable obstacles are challenges for robotic navigation in human living environments because they lead to frequent changes in pre-built maps. Such changes cause navigation failures and high costs in path replanning. In this paper, we focus on the problem of semantic mapping and semantics-boosted navigation, introducing our intelligent robotic system that is capable of real-time belief-based scene understanding, object detection and recognition, as well as path creation strategy based on the semantic information. With deeper understanding of the environments, robotic navigation in cluttered environments filled with movable obstacles is improved. Scene understanding and object detection are achieved by our state-of-the-art Convolu-tional Neural Network (CNN) with multi-functions and then transformed into robotic beliefs using Bayes filtering to ensure temporal coherence. Object beliefs are further extended from 2D to 3D space with geometric feature detection and used for semantic mapping together with scene beliefs. Planning algorithm is designed to utilize semantic beliefs to create path through cluttered environments by manipulating movable obstacles at minimal costs. We evaluate the system on our robots with real human-living office scenarios.
The impacts of network configuration and node mobility on path dynamics in mobile ad hoc networks

The performance of mobile ad hoc networks (MANETs) is influenced by many factors including node mobility, node density, and wireless transmission range. The dynamics induced by these factors along the paths between MANET nodes affect node connectivity. Research efforts aiming at quantifying such path dynamics are limited (1) considering only the impact of a small number of factors, mostly node mobility; (2) quantifying only some path metrics, mainly the distribution of path lifetime and the expected path lifetime; and (3) relying mainly on simulation rather than analysis. In this paper, we provide closed form equations relating node mobility, node density, and wireless transmission range to path dynamics in MANETs as expressed by the path lifetime, the path churn rate and the path frequency. The closed form equations reveal interesting aspects of MANET performance and can be used in optimizing MANET routing protocols and applications.
Survey on Probabilistic Models of Low-Rank Matrix Factorizations

Low-rank matrix factorizations such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD) and Non-negative Matrix Factorization (NMF) are a large class of methods for pursuing the low-rank approximation of a given data matrix. The conventional factorization models are based on the assumption that the data matrices are contaminated stochastically by some type of noise. Thus the point estimations of low-rank components can be obtained by Maximum Likelihood (ML) estimation or Maximum a posteriori (MAP). In the past decade, a variety of probabilistic models of low-rank matrix factorizations have emerged. The most significant difference between low-rank matrix factorizations and their corresponding probabilistic models is that the latter treat the low-rank components as random variables. This paper makes a survey of the probabilistic models of low-rank matrix factorizations. Firstly, we review some probability distributions commonly-used in probabilistic models of low-rank matrix factorizations and introduce the conjugate priors of some probability distributions to simplify the Bayesian inference. Then we provide two main inference methods for probabilistic low-rank matrix factorizations, i.e., Gibbs sampling and variational Bayesian inference. Next, we classify roughly the important probabilistic models of low-rank matrix factorizations into several categories and review them respectively. The categories are performed via different matrix factorizations formulations, which mainly include PCA, matrix factorizations, robust PCA, NMF and tensor factorizations. Finally, we discuss the research issues needed to be studied in the future.
Neoadjuvant Chemotherapy Versus Primary Cytoreductive Surgery for Stage IV Uterine Serous Carcinoma

Objective This study compares surgical and survival outcomes of women with stage IV uterine serous carcinoma (USC) treated with neoadjuvant chemotherapy (NAC) and interval cytoreduction to women treated with primary cytoreductive surgery (PCS) followed by adjuvant chemotherapy. Methods This retrospective dual cohort study included women diagnosed with stage IV USC at a single academic institution. Kruskal-Wallis and Fisher exact tests were used to compare demographics and surgical outcomes. Progression-free survival (PFS) and overall survival (OS) were estimated by using Kaplan-Meier methods. Comparison between study groups was tested by log-rank statistics. Results Ten women with stage IV USC who received NAC and 34 who underwent PCS met inclusion criteria. Neoadjuvant chemotherapy patients had a lower mean body mass index and were more often African American. Compared with PCS, the NAC cohort had shorter mean operative times (137 ± 66 vs 203 ± 80 minutes, P = 0.025) and were discharged from the hospital earlier (median length of stay, 3 vs 5 days; P = 0.002). Rates of debulking to no gross residual disease (70% NAC vs 32.3% PCS) or less than 1 cm of disease (30% NAC vs 50% PCS) did not differ (P = 0.10). Median follow-up time was 17.5 months. There was no difference in median PFS (10.4 vs 12 months, P = 0.29) or OS (17.3 vs 20.7 months, P = 0.23) for NAC and PCS cohorts. Conclusions Women receiving NAC for stage IV USC had shorter surgeries and hospital stays than did those receiving PCS. There was no difference in PFS or OS, although our sample size was small. Neoadjuvant chemotherapy may be an appropriate therapy for select patients with advanced-stage USC.