Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional differences in cardiovascular risk factor profile cannot fully explain differences in cardiovascular morbidity in the Netherlands: a comparison of two urban areas.

BACKGROUND Our objective was to investigate whether a region in the south of the Netherlands (Heerlen/Kerkrade) had a high burden of cardiovascular disease in comparison with a nearby region (Maastricht) and the average Dutch population, respectively. We also wanted to determine if there are interregional differences in cardiovascular risk factor profile. DESIGN Cross-sectional study. METHODS Data from a nationwide registry (CBS) were used to analyse cardiovascular mortality in the two regions and the average in the Netherlands. Data from a primary care morbidity registration network (RNH) were used to compare cardiovascular morbidity and cardiovascular risk factors in both regions. A standardisation procedure was carried out for age and sex. Data were analysed using logistic regression analyses. RESULTS The overall cardiovascular mortality rate was higher in the Heerlen/Kerkrade region (7.8 per thousand) compared with Maastricht (6.1 per thousand, OR=1.3, 95% CI 1.2-1.5) and the average in the Netherlands (5.7 per thousand). Similarly, most cardiovascular morbidity rates for Heerlen/Kerkrade were more elevated compared with the RNH overall and with Maastricht. Prevalence rates of risk factors such as diabetes mellitus (7.2%, OR=1.5, 95% CI 1.3-1.7) and overweight (10.8%, OR= 2.0, 95% CI 1.8-2.2) were significantly higher in the Heerlen/Kerkrade region compared with Maastricht. There were no differences with regard to hypertension (15.2%, OR=1.0, 95% CI 0.9-1.1). CONCLUSION Heerlen/Kerkrade is indeed a region with a high burden of cardiovascular disease. Differences in morbidity between Heerlen/Kerkrade and Maastricht cannot be fully explained by differences in cardiovascular risk factor profile.
AMD ’ s Commitment to Accelerating Energy Efficiency

The remarkable performance advances in computing since the birth of the modern microprocessor can be largely attributed to Moore’s Law—the doubling of the number of transistors on a chip about every two years as manufacturing technology advances allow for smaller and smaller transistors. Less well known is that this exponential rise in available processing power has been accompanied by corresponding improvements in energy efficiency and processor speed. A study in 2010 found that the amount of computation that could be done per unit of energy doubled about every 18 months, an observation known as Koomey’s Law.1
Symbolic and numerical software tools for LFT-based low order uncertainty modeling

One of the main difficulties in applying modern control theories for designing robust controllers for linear uncertain plants is the lack of adequate models describing structured physical model uncertainties. We present a systematic approach for the generation of uncertainty models described by linear fractional transformations (LFTs) and report on recently developed symbolic and numerical software to assist the generation of low order LFT-based uncertainty models. The kernel of the symbolic software is a Maple library for generation and manipulation of LFT models. Additional numerical tools for order reduction of LFT models are based on MATLAB and FORTRAN implementations of numerically reliable algorithms. Three examples of uncertainty modeling of aircraft dynamics illustrate the capabilities of the new software to solve high order uncertainty modeling problems.
An Energy Consumption Model for Off-The-Grid Radar Networks

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's long-range weather radars. Future distributed radar networks will involve thousands of small radars, and the design of these systems will be conducted in a trade-space that balances requirements among radar sensing, communications, networking, and distributed computation functions while addressing infras- tructure constraints (such as size, weight, space, and prime power requirements) to achieve cost-effective designs. This paper presents preliminary work on the development of "Off-The- Grid" (OTG) weather radar networks. These are envisioned as self-contained networks of small remote-sensing / commu- nication / computation nodes, each occupying a volume of 1.5 m 3 and capable of operating independent of the wired power and communication infrastructure. Operating a radar network independently of the electrical grid will require understanding the energy requirements for sensing. This paper will present the current progress in the development of the energy balancing algorithms necessary for OTG operation. Included in this paper will be an energy consumption model for OTG network analysis. The energy model includes the energy cost associated with the three main functions (sensing, computing, communicating) of each radar node in an OTG network. The energy consumption model is a fundamental component of an OTG network emulator that will allow for the testing of the energy balancing algorithms. This paper will present the OTG node energy model that has been developed and that will be used to analyze the developing energy balancing algorithms.
Using Testor Theory to Reduce the Dimension of Neural Networks Models

Most of the Neural Network models proposed during the last few years are capable of solving several complex problems such as recognition, forecast or reconstruction of different phenomena. A crucial feature of these models is that they tackle a wide variety of classification problems, and although these models work accurately within a limited particular context, they require numerous resources; this makes its efficient hardware implementation nearly impossible. In this paper we propose a novel alternative which uses Testor Theory, which is a useful tool in pattern recognition within the logical-combinatorial approach, to reduce the dimension of neural network models. We test the accuracy of the proposed method by recognizing real-world objects in images. We show that, under some circumstances, it is possible to reduce the dimension of a neural network without affecting its capability to solve classification problems or modifying its effectiveness.
Functional Analysis of the Caenorhabditis elegans UNC-73B PH Domain Demonstrates a Role in Activation of the Rac GTPase In Vitro and Axon Guidance In Vivo

ABSTRACT The Caenorhabditis elegans UNC-73B protein regulates axon guidance through its ability to act as a guanine nucleotide exchange factor (GEF) for the CeRAC/MIG-2 GTPases. Like other GEFs for Rho family GTPases, UNC-73B has a Dbl homology (DH) catalytic domain, followed by a C-terminal pleckstrin homology (PH) domain. We have explored whether the PH domain cooperates with the adjacent DH domain to promote UNC-73B GEF activity and axonal pathfinding. We show that the UNC-73B PH domain binds preferentially to monophosphorylated phosphatidylinositides in vitro. Replacement of residues Lys1420 and Arg1422 with Glu residues within the PH domain impaired this phospholipid binding but did not affect the in vitro catalytic activity of the DH domain. In contrast, a mutant UNC-73B protein with a Trp1502-to-Ala substitution in the PH domain still interacted with phosphorylated phosphatidylinositides but had lost its GEF activity. UNC-73B minigenes containing these mutations were microinjected into C. elegans and transferred to unc-73(e936) mutant worms. Unlike the wild-type protein, neither PH domain mutant was able to rescue the unc-73 axon guidance defect. These results suggest that the UNC-73B PH domain plays distinct roles in targeting and promoting GEF activity towards the Rac GTPase, both of which are important for the directed movements of motorneurons in vivo.
Role of superoxide–nitric oxide interactions in the accelerated age-related loss of muscle mass in mice lacking Cu,Zn superoxide dismutase

Mice lacking Cu,Zn superoxide dismutase (SOD1) show accelerated, age‐related loss of muscle mass. Lack of SOD1 may lead to increased superoxide, reduced nitric oxide (NO), and increased peroxynitrite, each of which could initiate muscle fiber loss. Single muscle fibers from flexor digitorum brevis of wild‐type (WT) and Sod1−/− mice were loaded with NO‐sensitive (4‐amino‐5‐methylamino‐2′,7′‐difluorofluorescein diacetate, DAF‐FM) and superoxide‐sensitive (dihydroethidium, DHE) probes. Gastrocnemius muscles were analyzed for SOD enzymes, nitric oxide synthases (NOS), and 3‐nitrotyrosine (3‐NT) content. A lack of SOD1 did not increase superoxide availability at rest because no increase in ethidium or 2‐hydroxyethidium (2‐HE) formation from DHE was seen in fibers from Sod1−/− mice compared with those from WT mice. Fibers from Sod1−/− mice had decreased NO availability (decreased DAF‐FM fluorescence), increased 3‐NT in muscle proteins indicating increased peroxynitrite formation and increased content of peroxiredoxin V (a peroxynitrite reductase), compared with WT mice. Muscle fibers from Sod1−/− mice showed substantially reduced generation of superoxide in response to contractions compared with fibers from WT mice. Inhibition of NOS did not affect DHE oxidation in fibers from WT or Sod1−/− mice at rest or during contractions, but transgenic mice overexpressing nNOS showed increased DAF‐FM fluorescence and reduced DHE oxidation in resting muscle fibers. It is concluded that formation of peroxynitrite in muscle fibers is a major effect of lack of SOD1 in Sod1−/− mice and may contribute to fiber loss in this model, and that NO regulates superoxide availability and peroxynitrite formation in muscle.
Autonomous clustering for wireless sensor networks

Most algorithms treat Wireless Sensor Networks (WSNs) only as a generator of data without any autonomy. In contrast to this approach, we propose the ACIDE framework: A completely decentralized, bottom-up clustering process and information exchange that does not depend on given infrastructure such as fixed root nodes. While it has slightly higher requirements for the nodes, its dynamic and independent nature has many advantages, such as the user beeing able to initiate queries from any point in the network rather than being limited to query the network through an a priori fixed sink node. The framework can deal with changing environments and energy depletion. Through careful abstraction, we also support customization and adaption to different environments.
Effective Error Concealment Algorithm by Boundary Information for H.264 Video Decoder

H.264 is a new video coding standard which contains some novel coding functions and provides more coding efficiency than previous standards. However, video streams are sensitive to channel errors that often degrade the visual quality of the decoded sequence, not only corrupt the current frame but also propagate to subsequent frames. In order to solve this problem, the error concealment in the decoder is very important and useful, neither bit rate nor delay will increase during the transmission. In this paper, we propose an error concealment method by utilizing the temporal correlation of the lost macroblock and its neighboring macroblocks to reconstruct the damaged data. Simulation results show that both of the subjective and objective performances of the proposed techniques are superior to conventional temporal concealment methods for H.264 standard
Universal Approximation Using Shuffled Linear Models

This paper proposes a specific type of Local Linear Model, the Shuffled Linear Model (SLM), that can be used as a universal approximator. Local operating points are chosen randomly and linear models are used to approximate a function or system around these points. The model can also be interpreted as an extension to Extreme Learning Machines with Radial Basis Function nodes, or as a specific way of using Takagi-Sugeno fuzzy models. Using the available theory of Extreme Learning Machines, universal approximation of the SLM and an upper bound on the number of models are proved mathematically, and an efficient algorithm is proposed.
Using a Genetic Algorithm for Detecting Repetitions in Biological Sequences

One of the most important goals in computational molecular biology is allocating repeated patterns in nucleic or protein sequences, and identifying structural or functional motifs that are common to a set of such sequences. In this paper we describe a new approach to detect the repetitions of fixed length in Biological Sequences using a Genetic Algorithm. The method involves evolving a population of patterns in an evolutionary manner and gradually improving the fitness of the population as measured by an objective function, which measures the approximate repetitions of the patterns in the given sequence. The general attraction of the approach is the ability to detect repeated schemas, thus inferring motifs of fixed length from biological sequences. Key-Words: Genetic Algorithms, Evolutionary Programming, Repetitions, Motifs, Biological Sequences, Pattern Matching
Optimal link path queries in a simple polygon

We develop a data structure for answering link distance queries between two arbitrary points in a simple polygon. The data structure requires <italic>O</italic>(<italic>n</italic><supscrpt>3</supscrpt>) time and space for its construction and answers link distance queries in <italic>O</italic>(log <italic>n</italic>) time. Our result extends to link distance queries between pairs of segments or polygons. We also propose a simpler data structure for computing a link distance approximately, where the error is bounded by a small additive constant. Finally, we also present a scheme for approximating the link and the shortest path distance simultaneously.
The Association of ACE Genotypes on Cardiorespiratory Variables Related to Physical Fitness in Healthy Men

Aerobic power (VO2max), aerobic capacity (RCP), and running efficiency (RE) are important markers of aerobic fitness. However, the influence of the angiotensin converting enzyme (ACE) polymorphism on these markers has not been investigated in healthy individuals. One hundred and fifty physically active young men (age 25 ± 3 years; height 1.77 ± 0.06 m; body mass 76.6 ± 0.9 kg; VO2max 47.7 ± 5.5 ml·kg-1·min-1) visited the laboratory on two separate occasions, and performed the following tests: a) a maximal incremental treadmill test to determine VO2max and RCP, and b) two constant-speed running tests (10 km·h-1 and 12 km·h-1) to determine RE. The genotype frequency was II = 21%; ID = 52%; and DD = 27%. There was a tendency for higher VO2max with the ACE II genotype (p = 0.08) compared to DD and ID genotypes. Magnitude based inferences suggested a likely beneficial effect on VO2max with the ACE II genotype. There was no association between genotypes for other variable. These findings suggest that individuals with the ACE II genotype have a tendency towards better values in aerobic power, but not with aerobic capacity or running economy.
Differentially driven symmetric microstrip inductors

A differentially excited symmetric inductor that enhances inductor quality (Q) factor on silicon RFICs is presented. Compared with an equivalent single-ended configuration, experimental data demonstrate that the differential inductor offers a 50% greater Q factor and a broader range of operating frequencies. Predictions from full-wave simulations and a physics-based SPICE-compatible model are validated by experimental measurements on an inductor fabricated in a triple-level metal silicon technology. Application of the symmetric inductor to a cross-coupled oscillator improves output voltage swing and phase noise by 75% and 1.8 dB, respectively (for a given power consumption), while chip area is reduced by 35% compared to conventional inductor equivalents.
Transforming Third World Cities through Good Urban Governance: Fresh Evidence

Many Ghanaians believe that introducing multi-party elections at the metropolitan, municipal and district levels would ensure the election of competent people to manage the urban or local economy. This belief is premised on the assumption that electorates are informed and would vote for competent politicians. Using the 2008 elections in Ghana, it is argued that only a minority of electorates vote on issues; the majority vote along tribal and party lines; and based on how “humble” a politician is or simply based on monetocracy. This means that introducing elections into the local government system would not necessarily lead to a transformation of the local or urban economy; greater local democracy is not the answer to the housing problem, sanitation crisis, unemployment burden and the poverty challenge. There may be the need for a new form of local democracy.
Real-time environment map interpolation

Environment mapping, or reflection mapping, has been widely used in the game and movie industries to give objects a realistic illumination atmosphere. For moving objects, direct frame-by-frame calculation of environment maps and correspondence-based interpolation are both impractical for real-time applications due to the large computational costs. To deal with this problem, "fake" environment mapping with a fixed, pre-generated environment image has been commonly used, but clearly such an approximation is inadequate for a highly reflective object whose environment is constantly changing as it moves. In this paper, we present an approach that sparsely samples environment maps of a moving object and rapidly interpolates them for high performance. Two techniques are introduced for fast environment map interpolation without computation of scene shading. The first method utilizes scene geometry to facilitate interpolation, and the second involves geometry reconstruction from depth buffer values to reduce inefficiencies caused by complex scene geometry. These two techniques can easily be implemented in graphics hardware, and test results show that they achieve significant boosts in performance over frame-by-frame environment map computation with little loss in visual quality.
Identity elements for the aminoacylation of metazoan mitochondrial tRNAArg have been widely conserved throughout evolution and ensure the fidelity of the AGR codon reassignment

Eumetazoan mitochondrial tRNAs possess structures (identity elements) that require the specific recognition by their cognate nuclear-encoded aminoacyl-tRNA synthetases. The AGA (arginine) codon of the standard genetic code has been reassigned to serine/glycine/termination in eumetazoan organelles and is translated in some organisms by a mitochondrially encoded tRNASerUCU. One mechanism to prevent mistranslation of the AGA codon as arginine would require a set of tRNA identity elements distinct from those possessed by the cytoplasmic tRNAArg in which the major identity elements permit the arginylation of all 5 encoded isoacceptors. We have performed comparative in vitro aminoacylation using an insect mitochondrial arginyl-tRNA synthetase and tRNAArgUCG structural variants. The established identity elements are sufficient to maintain the fidelity of tRNASerUCU reassignment. tRNAs having a UCU anticodon cannot be arginylated but can be converted to arginine acceptance by identity element transplantation. We have examined the evolutionary distribution and functionality of these tRNA elements within metazoan taxa. We conclude that the identity elements that have evolved for the recognition of mitochondrial tRNAArgUCG by the nuclear encoded mitochondrial arginyl-tRNA synthetases of eumetazoans have been extensively, but not universally conserved, throughout this clade. They ensure that the AGR codon reassignment in eumetazoan mitochondria is not compromised by misaminoacylation. In contrast, in other metazoans, such as Porifera, whose mitochondrial translation is dictated by the universal genetic code, recognition of the 2 encoded tRNAArgUCG/UCU isoacceptors is achieved through structural features that resemble those employed by the yeast cytoplasmic system.
Ayurvedic management of Pravahika – A case report

Ulcerative colitis (UC) is a form of inflammatory bowel disease (IBD) that causes inflammation and ulcers in the colon. The disease is a type of colitis, which is a group of diseases that cause inflammation of the colon, the largest section of the large intestine, either in segments or completely. The main symptom of this active disease is diarrhea mixed with blood. In Ayurveda, it can be compared with a disease Pravahika characterized by Atidrava Mala Pravrutti with Rakta. A 30 year old female patient reported to the out patient Department of Panchakarma, NIA, Jaipur, with the complaints of frequent loose, watery, frothy, and foul-smelling stool stained with mucous and blood. Other associated complaints were reduced appetite, distension and pain in the abdomen, weakness, heat intolerance, reduced sleep, and headache. The patient was diagnosed as IBD consistent with UC. A combination of Nagarmotha(Cyperus rotundus L.) 2 g, Indrayava(Holarrhena antidysenterica (L.) Wall. ) 1 g, Nagakeshara(Mesua ferrea L.) 1 g, Madhuyashti(Glycyrrhiza glabra L.) 1 g, and Amalaki(Emblica officinalis Gaertn.) 1 g powders three times a day, along with Dadimashtaka Choorna 3 g with Shankha Bhasma 500mg three times a day, Mustarista 2 tsp three times a day after food, and Dhanyapanchaka Kvatha 20ml two times a day before food was administered for 2months. After the 2-month treatment, a significant response in various symptoms such as frequent defecation, abdomen distension, headache, heat intolerance, and reduced sleep was found.
Harmonic/percussive separation using Kernel Additive Modelling

Recently, Kernel Additive Modelling was proposed as a new framework for performing sound source separation. Kernel Additive Modelling assumes that a source at some location can be estimated using its values at nearby locations where nearness is defined through a source-specific proximity kernel. Different proximity kernels can be used for different sources, which are then separated using an iterative kernel backfitting algorithm. These kernels can efficiently account for features such as continuity, stability in time or frequency and self-similarity. Here, we show that Kernel Additive Modelling can be used to generalise, extend and improve on a widely-used harmonic/percussive separation algorithm which attempts to separate pitched from percussive instruments.
The Timing of Facial Motion in posed and Spontaneous Smiles

Almost all work in automatic facial expression analysis has focused on recognition of prototypic expressions rather than dynamic changes in appearance over time. To investigate the relative contribution of dynamic features to expression recognition, we used automatic feature tracking to measure the relation between amplitude and duration of smile onsets in spontaneous and deliberate smiles of 81 young adults of Euro- and African-American background. Spontaneous smiles were of smaller amplitude and had a larger and more consistent relation between amplitude and duration than deliberate smiles. A linear discriminant classifier using timing and amplitude measures of smile onsets achieved a 93% recognition rate. Using timing measures alone, recognition rate declined only marginally to 89%. These findings suggest that by extracting and representing dynamic as well as morphological features, automatic facial expression analysis can begin to discriminate among the message values of morphologically similar expressions.
Is Union Job Dissatisfaction Real

The Characteristics of Business Owners (CBO) data base was created in 1987 by the U.S. Bureau of the Census. It was based upon a 1986 survey of 125,000 self-employed persons; it includes five self-contained samples of 25,000 each: 1) Hispanics, 2) blacks, 3) all other minorities, 4) females, and 5) nonminority males. Two versions of the CBO data files focus, respectively, upon 1) self-employed persons, and 2) small firms. For each observation, data were collected upon owner human capital, demographic traits, and financial capital investment in one's firm. Firm specific data are extensive, including sales, profits, employment, payroll, etc.