Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Nutrition and Metabolism Calcium Intake Is Associated with Adiposity in Black and White Men and White Women of the HERITAGE Family Study 1 , 2

Calcium (Ca ) intake may play a role in the regulation of body weight. Increased Ca intake has been associated with lower body weight, BMI, and adiposity measures in cross-sectional studies. We examined the association between Ca intake, derived from the Willett FFQ, and overall and abdominal adiposity in Black and White men and women of the HERITAGE Family Study. BMI, the percentage of body fat (%FAT), the sum of 8 skinfold thicknesses, computerized tomography total abdominal fat (TAF), abdominal visceral (AVF) and abdominal subcutaneous (ASF) fat, and waist circumference were measured in 362 men (109 Blacks, 253 Whites) and 462 women (201 Blacks, 261 Whites). Subjects were divided into tertiles of energy-adjusted Ca intake. Adiposity measures across tertiles were compared by ANOVA and also regressed against the energy-adjusted Ca intake to test for a linear trend. The strongest inverse associations appeared in Black men and White women. Black men in the high Ca intake group were leaner than those in the low Ca intake group: BMI 23.4 0.9 vs. 26.7 1.1 kg/m (P 0.01); for all other adiposity measures, P 0.05. In White women, regression analyses showed significant inverse associations between Ca intake and BMI (P 0.02), %FAT (P 0.001), TAF (P 0.006), AVF (P 0.03), and ASF (P 0.01). The percentage of fat of White men in the highest Ca intake group was significantly lower than in the lowest Ca group (P 0.04). No significant associations were found in Black women. Low Ca intake may be associated with higher adiposity, particularly in men and White women. J. Nutr. 134: 1772–1778, 2004.
Phytic acid Ameliorates Mitochondrial Lipid Peroxides , Antioxidants and Lipids in Isoproterenol-Induced Myocardial Infarction in Wistar Rats

Copyright  2015 irjpbs. Aim of the present study is to evaluate the preventive role of phytic acid on mitochondrial lipid peroxides, antioxidants and lipids in isoproterenol (ISO)-induced myocardial infarction (MI) in male Wistar rats. Rats subcutaneously injected with ISO (85 mg/kg) at an interval of 24 h for 2 days resulted in a significant increase in the levels of mitochondrial lipid peroxides with a significant decrease in the activities of mitochondrial antioxidants (SOD, catalase, glutathione peroxidase, glutathione-Stransferase and reduced glutathione). Induction of ISO also showed a significant increase in the levels of mitochondrial cholesterol, triglycerides and free fatty acids with a subsequent decrease in the levels of phospholipids. Oral pretreatment with phytic acid (25 and 50 mg/kg) to ISO-induced rats daily for a period of 56 days significantly decreased the levels of mitochondrial lipid peroxides with a significant increase in the activities of mitochondrial antioxidants and significantly minimized the alterations in the mitochondrial lipid levels in ISO-induced rats. Thus, the findings demonstrate that phytic acid prevents alterations in mitochondrial lipid peroxides, antioxidants and lipids in ISO-induced MI in rats.
Model Checking with Edge-valued Decision Diagrams

Abstract We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic func-tions and its implementation in a model checking library along with state-of-the-art algorithms forbuilding the transition relation and the state space of discrete state systems.We provide efﬁcient algorithms for manipulating EVMDDs and give upper bounds of the the-oretical time complexity of these algorithms for all basic arithmetic and relational operators. Wealso demonstrate that the time complexity of the generic recursive algorithm for applying a binaryoperator on EVMDDs is no worse than that of Multi-Terminal Decision Diagrams.We have implemented a new symbolic model checker with the intention to represent in one for-malism the best techniques available at the moment across a spectrum of existing tools: EVMDDsfor encoding arithmetic expressions, identity-reduced MDDs for representing the transition relation,and the saturation algorithm for reachability analysis. We compare our new symbolic model check-ing EVMDD library with the widely used CUDD package and show that, in many cases, our tool isseveral orders of magnitude faster than CUDD.
Association between the level of circulating bioactive tumor necrosis factor alpha and the tumor necrosis factor alpha gene polymorphism at -308 in patients with rheumatoid arthritis treated with a tumor necrosis factor alpha inhibitor.

OBJECTIVE The tumor necrosis factor alpha (TNFalpha) -308A polymorphism has been associated with high production of TNFalpha and poor response to anti-TNFalpha therapy, but these associations remain controversial. The aim of this study was to explore the association between circulating TNFalpha bioactivity, the TNFalpha -308 polymorphism, and the clinical response to infliximab in patients with rheumatoid arthritis (RA). METHODS One hundred ninety-eight patients with RA were treated with infliximab and methotrexate. Responses at 6 months according to the American College of Rheumatology (ACR) preliminary criteria for improvement in RA were recorded. Genotyping for the TNFalpha -308 polymorphism was performed by enzyme-linked oligosorbent assay. Circulating TNFalpha bioactivity was evaluated in 50 patients with RA by assessing the production of interleukin-6 (IL-6) in synoviocytes induced by a small amount of TNFalpha plus plasma. IL-6 production in 48-hour supernatants and the levels of TNFalpha protein and IL-6 were measured by enzyme-linked immunosorbent assay. RESULTS The TNFalpha -308 polymorphism was not associated with the ACR response to infliximab. The level of circulating TNFalpha bioactivity was higher in patients with the TNFalpha -308 A/A or A/G genotype than that in patients with the G/G genotype (median 50.0 ng/ml [interquartile range (IQR) 31.5-62.0] versus 33.0 ng/ml [IQR 16.5-47.5]; P < 0.02). However, no difference was observed for the TNFalpha protein level according to genotype (median 0.62 pg/ml [IQR 0.00-8.85] for G/G versus 3.35 pg/ml [IQR 1.55-4.63] for A/A or A/G; P not significant). The level of circulating TNFalpha bioactivity was higher in good responders (> or =50% improvement) than in poor responders (< or =20% improvement) (median 45.0 ng/ml [IQR 21.0-59.0] versus 28.0 ng/ml [IQR 14.0-39.0]; P = 0.05). However, the level of TNFalpha protein was similar in both groups. CONCLUSION The level of functional circulating TNFalpha is partially genetically determined and is predictive of the clinical response to infliximab. Nonresponders to anti-TNFalpha therapy are likely to have a disease that is not primarily driven by TNFalpha.
Exploiting scene cues for dropped object detection

This paper presents a method for the automated detection of dropped objects in surveillance scenarios, which is a very important task for abandoned object detection. Our method works in single views and exploits prior information of the scene, such as geometry or the fact that a number of false alarms are caused by known objects, such as humans. The proposed approach builds dropped object candidates by analyzing blobs obtained with a multi-layer background subtraction approach. The created dropped object candidates are then characterized both by appearance and by temporal aspects such as the estimated drop time. Next, we incorporate prior knowledge about the possible sizes and positions of dropped objects through an efficient filtering approach. Finally, the output of a human detector is exploited over in order to filter out static objects that are likely to be humans that remain still. Experimental results on the publicly available PETS2006 datasets and on several long sequences recorded in metro stations show the effectiveness of the proposed approach. Furthermore, our approach can operate in real-time.
Ideal gas behavior of rotamerically defined conformers in native globular proteins

Protein conformational transitions, which are essential for function, may be driven either by entropy or enthalpy when molecular systems comprising solute and solvent molecules are the focus. Revealing thermodynamic origin of a given molecular process is an important but difficult task, and general principles governing protein conformational distributions remain elusive. Here we demonstrate that when protein molecules are taken as thermodynamic systems and solvents being treated as the environment, conformational entropy is an excellent proxy for free energy and is sufficient to explain protein conformational distributions. Specifically, by defining each unique combination of side chain torsional state as a conformer, the population distribution (or free energy) on an arbitrarily given order parameter is approximately a linear function of conformational entropy. Additionally, span of various microscopic potential energy terms is observed to be highly correlated with both conformational entropy and free energy. Presently widely utilized free energy proxies, including minimum potential energy, average potential energy terms by themselves or in combination with vibrational entropy\cite, are found to correlate with free energy rather poorly. Therefore, our findings provide a fundamentally new theoretical base for development of significantly more reliable and efficient next generation computational tools, where the number of available conformers,rather than poential energy of microscopic configurations, is the central focus. We anticipate that many related research fields, including structure based drug design and discovery, protein design, docking and prediction of general intermolecular interactions involving proteins, are expected to benefit greatly.
Probabilistic Joint Feature Selection for Multi-task Learning

We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypothesis classes associated with each of the tasks and regularizing the variance of the hypothesis parameters, similar feature patterns across different tasks are encouraged and features that are relevant to all (or most) of the tasks are identified. Our analysis shows that the proposed probabilistic framework can be seen as a generalization of previous result from adaptive ridge regression to the multi-task learning setting. We provide a detailed description of the proposed algorithms for simultaneous model construction and justify the proposed algorithms in several aspects. Our experimental results show that this approach outperforms a regularized multi-task learning approach and the traditional methods where individual tasks are solved independently on synthetic data and the real-world data sets for lung cancer prognosis.
Security Analysis of MAC Protocol for Mobile Device Identification Based on PARADIS

Authenticating wireless devices based on PARADIS technique draws increasing research interest recently, providing security access services in wireless networks. This paper provides an overview of various schemes for PARADIS identification using physical layer characteristics. Firstly, this work systematizes the existing knowledge on this topic for a better understanding of PARADIS device identification, its implications on the analysis and design of security solutions in wireless mobile networks, and possible applications. Secondly, we review the development progress of PARADIS identification techniques, discuss the merits and demerits of existing PARADIS identification schemes and provide a summary of the current state of the art. Moreover, we propose a new authentication scheme based on PRARDIS and discuss its security and feasibility in the SAE/LTE application. We also highlight the open problems of PRARDIS and motivate future works.
An energy-efficient heterogeneous dual-core processor for Internet of Things

With the fast development of Internet of Things (IoTs) in recent years, many IoT applications, such as structure health monitoring, surveillance camera and etc, require both extensive computation for burst-mode signal processing as well as ultra low power continuous operations. However, most of conventional IoT processors focus on ultra low power consumption and cannot satisfy those demands. This paper proposes a novel energy-efficient heterogenous dual-core processor, which includes both an ultra low power near-threshold CoreL and a fast CoreH to meet those emerging requirements. Furthermore, an optimal framework is proposed to realize energy efficient task mapping and scheduling. The processor is fabricated and its energy consumption in low power mode is as low as 7.7pJ/cycle and outperforms related work. Detailed analysis under several real applications shows that up to 2.62× energy efficiency improvements can be achieved without deadline miss compared with the high-performance-only signle core architecture.
Metaphors of Human Thinking: A New Tool in User Interface Design and Evaluation

Understanding human thinking is crucial in the design and evaluation of human-computer interaction. Inspired by introspective psychology, we present five metaphors of human thinking. The aim of the metaphors is to help designers consider important traits of human thinking. We illustrate how to use the metaphors for usability evaluation and how good and poor user interfaces can be appreciated in terms of the metaphors. An experiment with 87 subjects show that usability evaluation by metaphors of human thinking compared to heuristic evaluation uncovers usability problems that are assessed as more severe on users and more complex to repair.
The eccentric short-period orbit of the supergiant fast X-ray transient HD 74194 (=LM Vel)

Aims. We present the first orbital solution for the O-type supergiant star HD 74194, which is the optical counterpart of the supergiant fast X-ray transient IGR J08408-4503. Methods. We measured the radial velocities in the optical spectrum of HD 74194, and we determined the orbital solution for the first time. We also analysed the complex Hα profile. Results. HD 74194 is a binary system composed of an O-type supergiant and a compact object in a short-period (P = 9.5436 ± 0.0002 d) and high-eccentricity (e = 0.63 ± 0.03) orbit. The equivalent width of the Hα line is not modulated entirely with the orbital period, but seems to vary in a superorbital period (P = 285 ± 10 d) nearly 30 times longer than the orbital one.
Suspended load motion control using multicopters

This paper presents a distributed kinematic control law for group coordination for several multicopters and a payload suspended with wires from each multicopter. The complete system with constraints on the wires are modeled in 6 degrees of freedom (DOF), using the Udwadia-Kalaba equation. Velocity controllers for the multicopters are developed to realize the desired motion set by the kinematic controller. This results in a system where the group of multicopters are able to maneuver the payload to a desired position while keeping a desired formation. The results are verified by simulations.
Road Detection Based on Illuminant Invariance

By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms.
Splenectomy inhibits non-small cell lung cancer growth by modulating anti-tumor adaptive and innate immune response

It has been shown that inhibitors of the immune system reside in the spleen and inhibit the endogenous antitumor effects of the immune system. We hypothesized that splenectomy would inhibit the growth of relatively large non-small lung cancer (NSCLC) tumors by modulating the systemic inhibition of the immune system, and in particular Myeloid Derived Suppressor Cells (MDSC). The effect of splenectomy was evaluated in several murine lung cancer models. We found that splenectomy reduces tumor growth and the development of lung metastases, but only in advanced tumors. In immune-deficient NOD-SCID mice the effect of splenectomy on tumor growth and metastatic spread disappeared. Splenectomy significantly reduced the presence of MDSC, and especially monocytic-MDSC in the circulation and inside the tumor. Specific reduction of the CCR2+ subset of monocytic MDSC was demonstrated, and the importance of the CCL2-CCR2 axis was further shown by a marked reduction in CCL2 following splenectomy. These changes were followed by changes in the macrophages contents of the tumors to become more antitumorigenic, and by increased activation of CD8+ Cytotoxic T-cells (CTL). By MDSC depletion, and adoptive transfer of MDSCs, we demonstrated that the effect of splenectomy on tumor growth was substantially mediated by MDSC cells. We conclude that the spleen is an important contributor to tumor growth and metastases, and that splenectomy can blunt this effect by depletion of MDSC, changing the amount and characteristics of myeloid cells and enhancing activation of CTL.
Software improvements in an international company

The Schlumberger Laboratory for Computer Science (SLCS) was formed in 1989 as a corporate-wide resource to enhance the quality and creativity of software products within Schlumberger and to improve the productivity of software development. Because of a wide range of needs, it was necessary to decide which techniques SLCS's small software improvement team could use most effectively. The authors describe the choices made and the effectiveness of those choices in work with Schlumberger's engineering organizations. Through the motivation efforts of a small group, productive changes have occurred across the company. Improvements were made in many development areas, including project planning and requirements management. The catalysts behind these advances included capability assessments, training, and collaboration. <<ETX>>
Modelling the hydrodynamic sway force exerted on the bare-hull of an axi-symmetric underwater vehicle in lateral acceleration manoeuvres

Experimental data from pure sway tests on a series of five axi-symmetric bare-hulls for a slender underwater vehicle were used to study and model the sway force in lateral-plane sway manoeuvres. The sway force is represented with two components, one in phase with the sway acceleration and the other in phase with the sway velocity. The test data reveal that there is a variation in the apparent mass with both the sway frequency and amplitude. Although the present study provides some insight into this phenomenon, further experimental and analytical work will be required to acquire an improved understanding of the phenomena.
Chemical and Functional Properties of Hard-to-Cook Bean (Phaseolus vulgaris) Protein Concentrate

The objective of this research was to evaluate the chemical and functional properties of hard-to-cook (HTC) bean (Phaseolus vulgaris) protein concentrate to determine their potential practical applications. The respective protein concentrate was obtained from the flour using isoelectric precipitation and the protein content was 73.03%. Proximate composition and in vitro digestibility were measured to evaluate the chemical properties, and nitrogen solubility, emulsifying capacity, emulsion stability, foaming capacity, foam stability and viscosity were measured to evaluate its functional properties. The proximate composition of the HTC bean (P. vulgaris) flour and protein concentrate registered values of moisture, ash, protein, fat, fiber and NFE of 8.92, 4.52, 21.71%, 4.41%, 4.11% and 65.25% for flour and of 2.68%, 2.54%, 73.03%, 2.77%, 1.31% and 20.35% for protein concentrate. The in vitro digestibility was of 76.7%. The hard-to-cook bean protein concentrate exhibited good functional properties suggesting its use as additive. This concentrate registered solubility values that are ranging from 2.5% to 71.81%. The emulsifying (EC) and foaming capacity (FC) registered values of 89% - 97% and of 7% - 53% at different pH levels, respectively as well as an emulsion (ES) and foaming stability (FS) pH- and time-dependent. The HTC bean (P. vulgaris) protein concentrate registered a viscosity profile dependent of shear rate. The results suggest that HTC bean (P. vulgaris) protein concentrate is a valuable food ingredient or additive.
Balanced Oscillatory Coupling Improves Information Flow

All animals are able to rapidly change their behavior. The neural basis of such flexibility requires that groups of distant neural ensembles rapidly alter communications with selectivity and fidelity. Low frequency oscillations are a strong candidate for how neurons coordinate communication via the dynamic instantiation of functional networks. These dynamic networks are argued to rapidly guide the flow of information, with the presumption that stronger oscillations more strongly influence information flow. Surprisingly, there is scant evidence or theoretical support for how oscillatory activity might enhance information flow. Here we introduce a novel computational model for oscillatory neural communication and show that, rather than the strength of the oscillation, it is the balance between excitatory and inhibitory neuronal activity that has the largest effect on information flow. When coupling between an oscillation and spiking has balanced excitatory-inhibitory inputs, information flow is enhanced via improved discriminability between signal and noise. In contrast, when coupling is unbalanced, driven either by excessive excitation or inhibition, information flow is obstructed, regardless of the strength of the oscillation. A multitude of neuropathologies, including Parkinson’s disease, schizophrenia, and autism, are associated with oscillatory disruptions and excitation-inhibition imbalances. Our results show that understanding the distinction between balanced and unbalanced oscillatory coupling offers a unifying mechanistic framework for understanding effective neural communication and its disruption in neuropathology.