Miracle-dz/UniFAR-FTUs huggingface dataset:
Intermittent hypoxia training in prediabetes patients: Beneficial effects on glucose homeostasis, hypoxia tolerance and gene expression

The present study aimed at examining beneficial effects of intermittent hypoxia training (IHT) under prediabetic conditions. We investigate the effects of three-week IHT on blood glucose level, tolerance to acute hypoxia, and leukocyte mRNA expression of hypoxia inducible factor 1α (HIF-1α) and its target genes, i.e. insulin receptor, facilitated glucose transporter–solute carrier family-2, and potassium voltage-gated channel subfamily J. Seven healthy and 11 prediabetic men and women (44–70 years of age) were examined before, next day and one month after three-week IHT (3 sessions per week, each session consisting 4 cycles of 5-min 12% O2 and 5-min room air breathing). We found that IHT afforded beneficial effects on glucose homeostasis in patients with prediabetes reducing fasting glucose and during standard oral glucose tolerance test. The most pronounced positive effects were observed at one month after IHT termination. IHT also significantly increased the tolerance to acute hypoxia (i.e. SaO2 level at 20th min of breathing with 12% O2) and improved functional parameters of respiratory and cardiovascular systems. IHT stimulated HIF-1α mRNA expression in blood leukocytes in healthy and prediabetic subjects, but in prediabetes patients the maximum increase was lagged. The greatest changes in mRNA expression of HIF-1α target genes occurred a month after IHT and coincided with the largest decrease in blood glucose levels. The higher expression of HIF-1α was positively associated with higher tolerance to hypoxia and better glucose homeostasis. In conclusion, our results suggest that IHT may be useful for preventing the development of type 2 diabetes. Impact statement The present study investigated the beneficial effects of intermittent hypoxia training (IHT) in humans under prediabetic conditions. We found that three-week moderate IHT induced higher HIF-1α mRNA expressions as well as its target genes, which were positively correlated with higher tolerance to acute hypoxia and better glucose homeostasis in both middle-aged healthy and prediabetic subjects. This small clinical trial has provided new data suggesting a potential utility of IHT for management of prediabetes patients.
Improving Interpretability and Regularization in Deep Learning

Deep learning approaches yield state-of-the-art performance in a range of tasks, including automatic speech recognition. However, the highly distributed representation in a deep neural network (DNN) or other network variations is difficult to analyze, making further parameter interpretation and regularization challenging. This paper presents a regularization scheme acting on the activation function output to improve the network interpretability and regularization. The proposed approach, referred to as activation regularization, encourages activation function outputs to satisfy a target pattern. By defining appropriate target patterns, different learning concepts can be imposed on the network. This method can aid network interpretability and also has the potential to reduce overfitting. The scheme is evaluated on several continuous speech recognition tasks: the Wall Street Journal continuous speech recognition task, eight conversational telephone speech tasks from the IARPA Babel program and a U.S. English broadcast news task. On all the tasks, the activation regularization achieved consistent performance gains over the standard DNN baselines.
On error distributions in ring-based LWE

Since its introduction in 2010 by Lyubashevsky, Peikert and Regev, the ring learning with errors problem (ring-LWE) has become a popular building block for cryptographic primitives, due to its great versatility and its hardness proof consisting of a (quantum) reduction from ideal lattice problems. But, for a given modulus q and degree n number field K, generating ring-LWE samples can be perceived as cumbersome, because the secret keys have to be taken from the reduction mod q of a certain fractional ideal O-K(V) subset of K called the codifferent or 'dual', rather than from the ring of integers O-K itself. This has led to various non-dual variants of ring-LWE, in which one compensates for the non-duality by scaling up the errors. We give a comparison of these versions, and revisit some unfortunate choices that have been made in the recent literature, one of which is scaling up by vertical bar Delta(K)vertical bar(1/2n) with Delta(K) the discriminant of K. As a main result, we provide, for any epsilon > 0, a family of number fields K for which this variant of ring-LWE can be broken easily as soon as the errors are scaled up by vertical bar Delta(K)vertical bar((1-epsilon)/n).
Covariance Matrix Estimation for Massive MIMO

We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.
Size-dependent avoidance of a strong magnetic anomaly in Caribbean spiny lobsters

ABSTRACT On a global scale, the geomagnetic field varies predictably across the Earth's surface, providing animals that migrate long distances with a reliable source of directional and positional information that can be used to guide their movements. In some locations, however, magnetic minerals in the Earth's crust generate an additional field that enhances or diminishes the overall field, resulting in unusually steep gradients of field intensity within a limited area. How animals respond to such magnetic anomalies is unclear. The Caribbean spiny lobster, Panulirus argus, is a benthic marine invertebrate that possesses a magnetic sense and is likely to encounter magnetic anomalies during migratory movements and homing. As a first step toward investigating whether such anomalies affect the behavior of lobsters, a two-choice preference experiment was conducted in which lobsters were allowed to select one of two artificial dens, one beneath a neodymium magnet and the other beneath a non-magnetic weight of similar size and mass (control). Significantly more lobsters selected the control den, demonstrating avoidance of the magnetic anomaly. In addition, lobster size was found to be a significant predictor of den choice: lobsters that selected the anomaly den were significantly smaller as a group than those that chose the control den. Taken together, these findings provide additional evidence for magnetoreception in spiny lobsters, raise the possibility of an ontogenetic shift in how lobsters respond to magnetic fields, and suggest that magnetic anomalies might influence lobster movement in the natural environment. Summary: Lobsters avoid artificial dens below strong magnets, suggesting that magnetic anomalies might affect lobster orientation and movement.
Inhibition of IKKβ Reduces Ethanol Consumption in C57BL/6J Mice

Abstract Proinflammatory pathways in neuronal and non-neuronal cells are implicated in the acute and chronic effects of alcohol exposure in animal models and humans. The nuclear factor-κB (NF-κB) family of DNA transcription factors plays important roles in inflammatory diseases. The kinase IKKβ mediates the phosphorylation and subsequent proteasomal degradation of cytosolic protein inhibitors of NF-κB, leading to activation of NF-κB. The role of IKKβ as a potential regulator of excessive alcohol drinking had not previously been investigated. Based on previous findings that the overactivation of innate immune/inflammatory signaling promotes ethanol consumption, we hypothesized that inhibiting IKKβ would limit/decrease drinking by preventing the activation of NF-κB. We studied the systemic effects of two pharmacological inhibitors of IKKβ, TPCA-1 and sulfasalazine, on ethanol intake using continuous- and limited-access, two-bottle choice drinking tests in C57BL/6J mice. In both tests, TPCA-1 and sulfasalazine reduced ethanol intake and preference without changing total fluid intake or sweet taste preference. A virus expressing Cre recombinase was injected into the nucleus accumbens and central amygdala to selectively knock down IKKβ in mice genetically engineered with a conditional Ikkb deletion (IkkbF/F). Although IKKβ was inhibited to some extent in astrocytes and microglia, neurons were a primary cellular target. Deletion of IKKβ in either brain region reduced ethanol intake and preference in the continuous access two-bottle choice test without altering the preference for sucrose. Pharmacological and genetic inhibition of IKKβ decreased voluntary ethanol consumption, providing initial support for IKKβ as a potential therapeutic target for alcohol abuse.
Effects of protein or amino-acid supplementation on the physical growth of young children in low-income countries

Abstract Child growth stunting is common in low-income countries, possibly due to insufficient protein intakes. Most previous studies have concluded that children’s protein intakes are adequate in relation to estimated requirements, but these studies did not consider issues of protein digestibility and effects of infection on dietary protein utilization. Using an alternative approach to assess the possible role of protein inadequacy in children’s growth restriction, the results of 18 intervention trials in which supplementary protein or amino acids were provided to children ages 6–35 months and growth outcomes were reviewed. Eight studies conducted in hospitalized children recovering from acute malnutrition found that the recommended protein intake levels for healthy children supported normal growth rates, but higher intakes were needed for accelerated rates of “catch-up” growth. Ten community-based studies did not demonstrate a consistent benefit of supplemental protein on children’s growth. However, weaknesses in the study designs limit the conclusions that can be drawn from these studies, and additional appropriately designed trials are needed to answer this question definitively. Recommendations for optimizing future study designs are provided herein.
MIMO with Energy Recycling

In this paper, multiple-input-single-output (MISO) point-to-point communication system is considered, in which a multiple-input-multiple-output (MIMO) energy recycling (ER) transmitter is designed such that, each antenna can transmit information (multi-input) or recycle energy (multi-output) at any given point in time. The rate by such an ER-MISO communication system under an average transmission power constraint is shown to be achievable. Moreover, the optimal power allocation and the dynamic antenna selection policies that achieve the maximum communication rate are derived. The optimal dynamic antenna selection policy carefully switches the mode of the antennas between active-antennas (transmitting) and ER-antennas, where most of the harvested energy occurs from the neighboring antennas' transmissions, i.e., recycling. In addition, it is shown that, with ER, the achievable rate exceeds the capacity of the classical non-recycling counterpart. Since the complexity of the optimal dynamic antenna selection is exponential with the number of antennas, a linearithmic algorithm that has a minimal degradation in the achievable rate is proposed. Numerical results show that notable gain can be obtained by enabling ER. To address the major questions on the capability of ER and the impact of antenna coupling, hardware setup and experimental results for a four-antenna ER-transmitter are developed, based on a uniform linear array (ULA). As a result, hardware measurements indicate that the loss in the rate due to antenna coupling can be eliminated with sufficient antenna spacing and therefore, ER can achieve a significant gain.
Shear Strength Model for Reinforced Concrete Columns with Low Transverse Reinforcement Ratios

This paper introduces an equation developed based on the strut-and-tie analogy to predict the shear strength of reinforced concrete columns with low transverse reinforcement ratios. The validity and applicability of the proposed equation are evaluated by comparison with available experimental data. The proposed equation includes the contributions from concrete and transverse reinforcement through the truss action, and axial load through the strut action. A reinforced concrete column with a low transverse reinforcement ratio, commonly found in existing structures in Singapore and other parts of the world was tested to validate the assumptions made during the development of the proposed equation. The column specimen was tested to failure under the combination of a constant axial load of 0.30 f' c A g and quasi-static cyclic loadings to simulate earthquake actions. The analytical results revealed that the proposed equation is capable of predicting the shear strength of reinforced concrete columns with low transverse reinforcement ratios subjected to reversed cyclic loadings to a satisfactory level of accuracy
Matching Natural Language Sentences with Hierarchical Sentence Factorization

Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks. Depending on whether training data is available, prior research has proposed both unsupervised distance-based schemes and supervised deep learning schemes for sentence matching. However, previous approaches either omit or fail to fully utilize the ordered, hierarchical, and flexible structures of language objects, as well as the interactions between them. In this paper, we propose Hierarchical Sentence Factorization---a technique to factorize a sentence into a hierarchical representation, with the components at each different scale reordered into a "predicate-argument" form. The proposed sentence factorization technique leads to the invention of: 1) a new unsupervised distance metric which calculates the semantic distance between a pair of text snippets by solving a penalized optimal transport problem while preserving the logical relationship of words in the reordered sentences, and 2) new multi-scale deep learning models for supervised semantic training, based on factorized sentence hierarchies. We apply our techniques to text-pair similarity estimation and text-pair relationship classification tasks, based on multiple datasets such as STSbenchmark, the Microsoft Research paraphrase identification (MSRP) dataset, the SICK dataset, etc. Extensive experiments show that the proposed hierarchical sentence factorization can be used to significantly improve the performance of existing unsupervised distance-based metrics as well as multiple supervised deep learning models based on the convolutional neural network (CNN) and long short-term memory (LSTM).
Biological Synthesis of Silver Nanoparticles and Its Antibacterial Activity.

The ability of prokaryotic microorganisms to reduce the inorganic metals has opened up an exciting ecofriendly approach towards the development of green nanotechnology. Thus synthesis of metal nanoparticles through biological approach is an important aspect of current nanotechnology. In this study, silver nanoparticles have been successfully synthesized by Escherichia coli, in which exposure of supernatant to silver ions resulted in the extracellular reduction of the metal ions and formation of silver nanoparticles. Antimicrobial activity of silver nanoparticles was evaluated for their combined effects with antibiotics against microbes. The antibacterial activities increased in the presence of biologically synthesized silver nanoparticles. The enhancing effect was observed for Bacitracin against Escherichia coli and Salmonella paratyphi B. , for Ampicillin against Corynebacterium diphtheriae, for Kanamycin against Klebsiella pneumonia, for gentamycin against Pseudomonas aeruginosa and for Bacitracin, Gentamycin, Erythromycin, Ciprofloxacin against Staphylococcus aureus.
Detecting Semantic Method Clones In Java Code Using Method Ioe-behavior

The determination of semantic equivalence is an undecidable problem; however, this dissertation shows that a reasonable approximation can be obtained using a combination of static and dynamic analysis. This study investigates the detection of functional duplicates, referred to as semantic method clones (SMCs), in Java code. My algorithm extends the input-output notion of observable behavior, used in related work [1, 2], to include the effects of the method. The latter property refers to the persistent changes to the heap, brought about by the execution of the method. To differentiate this from the typical input-output behavior used by other researchers, I have coined the term method IOE-Behaviorwhich means its input-output and effects behavior. Two methods are defined as semantic method clones, if they have identical IOE-Behaviorthat is, for the same inputs (actual parameters and initial heap state), they produce the same output (that is resultfor non-void methods, and final heap state).
The Landscape Epidemiology of Seasonal Clustering of Highly Pathogenic Avian Influenza (H5N1) in Domestic Poultry in Africa, Europe and Asia

Highly pathogenic avian influenza subtype H5N1 (H5N1) has contributed to substantial economic loss for backyard and large-scale poultry farmers each year since 1997. While the distribution of domestic H5N1 outbreaks across Africa, Europe and Asia is extensive, those features of the landscape conferring greatest risk remain uncertain. Furthermore, the extent to which influential landscape features may vary by season has been inadequately described. The current investigation used World Organization for Animal Health surveillance data to (i) delineate areas at greatest risk of H5N1 epizootics among domestic poultry, (ii) identify those abiotic and biotic features of the landscape associated with outbreak risk and (iii) examine patterns of epizootic clustering by season. Inhomogeneous point process models were used to predict the intensity of H5N1 outbreaks and describe the spatial dependencies between them. During October through March, decreasing precipitation, increasing isothermality and the presence of H5N1 in wild birds were significantly associated with the increased risk of domestic H5N1 epizootics. Conversely, increasing precipitation and decreasing isothermality were associated with the increased risk during April through September. Increasing temperature during the coldest quarter, domestic poultry density and proximity to surface water were associated with the increased risk of domestic outbreaks throughout the year. Spatial dependencies between outbreaks appeared to vary seasonally, with substantial clustering at small and large scales identified during October through March even after accounting for inhomogeneity due to landscape factors. In contrast, during April to September, H5N1 outbreaks exhibited no clustering at small scale once accounting for landscape factors. This investigation has identified seasonal differences in risk and clustering patterns of H5N1 outbreaks in domestic poultry and may suggest strategies in high-risk areas with features amenable to intervention such as controlling domestic bird movement in areas of high poultry density or preventing contact between poultry and wild birds and/or surface water features.
Guidelines for the Management of Severe Traumatic Brain Injury, Fourth Edition

The scope and purpose of this work is 2-fold: to synthesize the available evidence and to translate it into recommendations. This document provides recommendations only when there is evidence to support them. As such, they do not constitute a complete protocol for clinical use. Our intention is that these recommendations be used by others to develop treatment protocols, which necessarily need to incorporate consensus and clinical judgment in areas where current evidence is lacking or insufficient. We think it is important to have evidence-based recommendations to clarify what aspects of practice currently can and cannot be supported by evidence, to encourage use of evidence-based treatments that exist, and to encourage creativity in treatment and research in areas where evidence does not exist. The communities of neurosurgery and neuro-intensive care have been early pioneers and supporters of evidence-based medicine and plan to continue in this endeavor. The complete guideline document, which summarizes and evaluates the literature for each topic, and supplemental appendices (A-I) are available online at https://www.braintrauma. org/coma/guidelines.
Aryl-Diazonium Functionalized Polycrystalline Silicon Nanoribbons Based Device for Lead Detection

Development of sensors enabling lead traces detection is a burning issue as heavy metals ions are responsible of brain diseases. In this paper, we present a simple electronic resistor based on polycrystalline silicon nanoribbons and functionalized with aryl-diazonium salts in view of using this type of structures for heavy metal detection. The preconcentration of lead at the surface of the functionalized nanostructures has been checked. Finally, electrical characterization of the resistors showed that the sensor sensitivity to these species is improved thanks to functionalization in the range 10−7 to 10−5 mol·L−1.
A texture display using vibrotactile and electrostatic friction stimuli surpasses one based on either type of stimulus

This study demonstrates that the simultaneous use of two types of representative principles for tactile texture displays, vibrotactile and electrostatic friction stimulation surpasses either type of stimulation. We used a set of sinusoidal grating scales with different surface spatial periods as simulated textured surfaces for testing the quality of texture displays. Experimental participants judged the best stimulus condition among the vibrotactile, electrostatic friction, and the conjunctive stimuli in terms of the reality perceived from the simulated texture stimuli. The use of vibrotactile and electrostatic stimuli in conjunction was judged to be the most realistic for the spatial periods of 1 and 2 mm, whereas noticeable differences among the three stimuli conditions were not reported for small spatial periods of 0.2 and 0.5 mm. The simultaneous use is effective for simulating the surfaces with middle-level asperity.
Use of patterned magnetic films to retain and orient micro-components during fluidic assembly

Patterned magnetic thin films have for the first time been used to orient and retain micron-sized III-V elements on silicon substrates during fluidic hybrid assembly. Modeling of the forces between Ni thin films patterned on one surface of 5–6 μm target areas on Si substrates predicts that the strength and fall-off characteristics of the attractive forces can be engineered to orient and securely retain only pills that are right side up. Verification of this behavior has been obtained by assembling 50×100 μm2 micropills in recesses with patterns of Sm-Co rectangles.