Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Dioxin-Like Polychlorobiphenyls and IGF-I Serum Levels in Healthy Adults: Evidence from a Cross-Sectional Study

Objective Insulin-like growth factor I (IGF-I) and dioxin-like polychlorobiphenyls (DL-PCBs) have been associated with the pathogenesis of several diseases like cancer, diabetes and growth disorders. Because it has been suggested that organohalogenated contaminants could influence IGF-I levels in adults, the potential relationship between DL-PCBs and IGF-I serum levels was studied in 456 healthy adults from a representative sample of the general population of the Canary Islands (Spain). Design Free circulating serum levels of IGF-I and IGFBP-3 were measured through an ELISA methodology, while the serum levels of the 12 DL-PCBs congeners (IUPAC numbers # 77, 81, 105, 114, 118, 123, 126, 156, 157, 167, 169, and 189) were measured by gas chromatography/mass spectrometry (GC-MS). Results DL-PCBs 156 and 167, Total DL-PCBs body burden (∑PCBs: sum over the 12 measured DL-PCBs), and Total toxic burden (in terms of toxic equivalence to dioxins: ∑TEQs) showed a trend of inverse association with IGF-I serum levels in the whole studied population. After adjusting for potential confounders, including gender, body mass index (BMI), age, and IGF-binding protein-3 (IGFBP-3), younger (18–45 years) women with lower BMI (<27 kg/m2) and detectable levels of DL-PCB-156 showed significantly lower IGF-I levels than those in the same age and BMI subgroup with non-detectable levels of DL-PCB-156 (p<0.001). Similarly, ∑PCBs and ∑TEQs showed a tendency to an inverse association with IGF-I levels in the same group of women (p=0.017 and p=0.019 respectively). Conclusions These findings suggest that DL-PCBs could be involved in the regulation of the IGF-system in a way possibly influenced by gender, age and BMI. Although these results should be interpreted with caution, such circumstances could contribute to explain the development of diseases associated to the IGF system.
Managing the Impact of Increasing Microprocessor Power Consumption

The power dissipation of modern processors has been rapidly increasing along with increasing transistor count and clock frequencies. At the same time, there is a growing disparity between the maximum power consumption of a processor and the “typical” power consumed by that processor; i.e., power consumed while running typical applications. This trend is the result of the significant increase in transistor count required to reach the desired peak performance targets. Designing a processor with the intent of minimizing system costs, especially those arising from high power consumption, while retaining a high level of reliability requires attention at all stages of the design. In the case of the Pentium 4 processor, the design team focused from the beginning on reducing power consumption without negatively impacting either the performance or reliability of the processor in any significant way. Many techniques, both innovative and pre-existing, were applied across the entire processor in an effort to eliminate unnecessary power consumption. The mass adoption of these techniques resulted in a significant reduction in both maximum and typical processor power dissipation.
Composing Distributed Representations of Relational Patterns

Learning distributed representations for relation instances is a central technique in downstream NLP applications. In order to address semantic modeling of relational patterns, this paper constructs a new dataset that provides multiple similarity ratings for every pair of relational patterns on the existing dataset. In addition, we conduct a comparative study of different encoders including additive composition, RNN, LSTM, and GRU for composing distributed representations of relational patterns. We also present Gated Additive Composition, which is an enhancement of additive composition with the gating mechanism. Experiments show that the new dataset does not only enable detailed analyses of the different encoders, but also provides a gauge to predict successes of distributed representations of relational patterns in the relation classification task.
Quantifying Corrosion between Carbon Fibre Reinforced Polymers (CFRP) and Steel Caused by High Temperature Marine Environments

Research into carbon fibre reinforced polymers (CFRP)'s application to steel as a retrofitting technique has shown very promising results for improving mechanical properties. However, the limitation of these materials in a corrosion inducing environment has generally been overlooked. In this study, the interaction of CFRP and steel in extreme weather conditions and the material characteristics in causing localised corrosion (e.g. pitting) were investigated, with the primary aim of quantifying pit depth. Pits are known to initiate fatigue cracks in steels. Steel tiles placed in direct contact with different varieties of CFRP were exposed to 5% NaCl solutions at two temperatures for different durations. The specimens were microscopically examined to find the existence of pits, their depth and density. Steel with prior grinding suffered negligible pitting, whereas the sand-blasting created distinct isolated regions where pitting was more commonly witnessed. However, the most relevant observation was that even after 6 months of exposure to the aggressive NaCl environment, whatever pitting occurred, it was found not to be overly critical in reducing the mechanical strength of the CFRP/steel bonds.
The effects of temporal acceleration and deceleration on AV speech perception

Modern signal processing techniques make it possible to speed up or slow down the apparent speaking rate of an audio-visual (AV) speech stimulus, but little is known about the effect this processing might have on the intelligibility of AV speech signals. In this experiment, AV recordings of phrases from the Modified Rhyme Test (MRT) were accelerated or decelerated by first changing the duration of the audio signal using the PSOLA speech processing algorithm (PRAAT) and then changing the frame rate of the AVI file to maintain synchronization of the audio and visual stimuli. The original speech phrases were recorded at either a fast speaking rate (roughly 5 syllables per second (syl/s)), a normal conversational rate (3.3 syl/s), and a slow rate (1.7 syl/s). The results of a preliminary experiment showed that conversational-rate AV recordings that were shifted in speed to match the slow or fast recordings produced the same audio and audiovisual intelligibility levels as the original recordings. However, some degradation in performance occurred when the fast recordings were slowed down or the slow recordings were speeded up. In the main experiment, the phrases were processed to set their speaking rates to eight different fixed values ranging from 0.6 syl/s to 20 syl/s. The results show that AV advantages were preserved at speaking rates as fast as 12.5 syl/s, but that they disappeared when the rate was increased to 20 syl/s. Notably, the results also failed to show any improvement in AV performance for phrases presented slower than their original speaking rates.
Subthreshold analog performance of channel engineered SOI CMOS devices and circuits for ultra-low power analog/mixed-signal applications

Subthreshold analog operation of CMOS devices are very attractive in terms of both very low power dissipation and high voltage gain. In this paper, a systematic investigation, with the help of extensive process and device simulations, of the effects of halo doping [both double-halo (DH) and single-halo (SH) or lateral asymmetric channel (LAC)] on the subthreshold analog performance of 100 nm SOI CMOS devices and circuits is reported. CMOS amplifiers made with the halo implanted devices are found to have higher voltage gain over their conventional counterpart.
A dictionary learning algorithm for sparse coding by the normalized bilateral projections

Sparse coding is a method of expressing the input vector as a linear combination of a few vectors taken from a set of template vectors, often called a dictionary or codebook. A good dictionary is the one that sparse codes most vectors in a given class of possible input vectors. There are currently several proposals to learn a good dictionary from a set of input vectors. Such methods are termed under the title of dictionary learning. We propose a new dictionary learning algorithm, called K-normalized bilateral projections (K-NBP), which is a modification to a widely used dictionary learning method, i.e., K-singular value decomposition (K-SVD). The main idea behind this was to standardize and normalize the input matrix as a preprocessing stage, and to correspondingly normalize the estimated source vectors in the dictionary update stage. The experimental results revealed that our method was fast, and when the number of iterations was limited, it outperformed K-SVD. Also, if only a coarse approximation was needed, it provided results that were almost like those from K-SVD, but with fewer iterations. This indicated that our method was particularly suited to large data sets with many dimensions, where each iteration took a long time.
Review of Experimental Procedure for Determining Liquid Flow in Microchannels

Large scatter in published experimental data has been observed with respect to classical theory. Recent data have confirmed that liquid, fully-developed, laminar flow in smooth microchannels of various cross-section is governed by the Navier-Stokes equations. However, when the dimensions of the channels are comparable with the wall roughness, surface effects become significant, as shown experimentally. To better assess the effect of surface phenomena such as wall roughness, sources of systematic bias must be eliminated. Some of the observed inconsistencies in data could originate from the experimental method. This paper explores and categorizes different approaches found in literature for measuring microflow characteristics and highlights the advantages and disadvantages inherent to these experimental techniques. A discussion of system components, experimental measurement and error analyses is included in the paper, with an emphasis on important issues which may have been overlooked in previous research. This study serves as a summary of experimental procedure and is a useful guideline for research in microfluidics. Moreover, several recommendations are proposed for improvement in areas requiring further study.
Integration of Social Media News Mining and Text Mining Techniques to Determine a Corporate's Competitive Edge

Market globalization have triggered much more severe challenges for corporates than ever before. Thus, how to survive in this highly fluctuating economic atmosphere is an attractive topic for corporate managers, especially when an economy goes into a severe recession. One of the most consensus conclusions is to highly integrate a corporate’s supply chain network, as it can facilitate knowledge circulation, reduce transportation cost, increase market share, and sustain customer loyalty. However, a corporate’s supply chain relations are unapparent and opaque. To solve such an obstacle, this study integrates text mining (TM) and social network analysis (SNA) techniques to exploit the latent relation among corporates from social media news. Sequentially, this study examines its impact on corporate operating performance forecasting. The empirical result shows that the proposed mechanism is a promising alternative for performance forecasting. Public authorities and decision makers can thus consider the potential implications when forming a future policy. and assumes variable returns to scale (VRS). This study takes DEA-CCR as a performance assessing model and depicts the mathematical formulation as follows.
The resolution of neuroinflammation in neurodegeneration: leukocyte recruitment via the choroid plexus

Inflammation is an integral part of the body's physiological repair mechanism, unless it remains unresolved and becomes pathological, as evident in the progressive nature of neurodegeneration. Based on studies from outside the central nervous system (CNS), it is now understood that the resolution of inflammation is an active process, which is dependent on well‐orchestrated innate and adaptive immune responses. Due to the immunologically privileged status of the CNS, such resolution mechanism has been mostly ignored. Here, we discuss resolution of neuroinflammation as a process that depends on a network of immune cells operating in a tightly regulated sequence, involving the brain's choroid plexus (CP), a unique neuro‐immunological interface, positioned to integrate signals it receives from the CNS parenchyma with signals coming from circulating immune cells, and to function as an on‐alert gate for selective recruitment of inflammation‐resolving leukocytes to the inflamed CNS parenchyma. Finally, we propose that functional dysregulation of the CP reflects a common underlying mechanism in the pathophysiology of neurodegenerative diseases, and can thus serve as a potential novel target for therapy.
Therapeutic Effects of Xanthine Oxidase Inhibitors: Renaissance Half a Century after the Discovery of Allopurinol

The prototypical xanthine oxidase (XO) inhibitor allopurinol, has been the cornerstone of the clinical management of gout and conditions associated with hyperuricemia for several decades. More recent data indicate that XO also plays an important role in various forms of ischemic and other types of tissue and vascular injuries, inflammatory diseases, and chronic heart failure. Allopurinol and its active metabolite oxypurinol showed considerable promise in the treatment of these conditions both in experimental animals and in small-scale human clinical trials. Although some of the beneficial effects of these compounds may be unrelated to the inhibition of the XO, the encouraging findings rekindled significant interest in the development of additional, novel series of XO inhibitors for various therapeutic indications. Here we present a critical overview of the effects of XO inhibitors in various pathophysiological conditions and also review the various emerging therapeutic strategies offered by this approach.
Standing on the Shoulders of Ants: Towards More Efficient XML-to-Relational Mapping Strategies

As XML has become a standard for data representation, it is inevitable to propose and implement techniques for efficient managing of XML data. A natural alternative is to exploit features and functions of (O)RDBMSs, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an appropriate XML-to-relational mapping strategy. In this paper we propose an enhancing of so-called adaptive mapping methods which evaluate several mapping possibilities and choose the one which suits the current application the most. We optimize the process of searching the optimal strategy using a heuristic called ant colony optimization and we enhance the adaptivity using similarity of XML data and ideas of user-driven techniques.
Adaptive learning by a target-tracking system

Purpose – The purpose of this paper is to report upon research into developing a biologically inspired target‐tracking system (TTS) capable of acquiring quality images of a known target type for a robotic inspection application.Design/methodology/approach – The approach used in the design of the TTS hearkens back to the work on adaptive learning by Oliver Selfridge and Chris J.C. H. Watkins and the work on the classification of objects by Zdzislaw Pawlak during the 1980s in an approximation space‐based form of feedback during learning. Also, during the 1980s, it was Ewa Orlowska who called attention to the importance of approximation spaces as a formal counterpart of perception. This insight by Orlowska has been important in working toward a new form of adaptive learning useful in controlling the behaviour of machines to accomplish system goals. The adaptive learning algorithms presented in this paper are strictly temporal difference methods, including Q‐learning, sarsa, and the actor‐critic method. Learni.
On the partial recovery of residual strain accumulated during an interrupted cyclic loading of NiTi shape memory alloys

It is well known that the behaviour of shape memory alloys (SMAs) evolves when subjected to cyclic loading. For instance, during superelastic cycling of an SMA, an increasing residual strain is observed, mainly during the first cycles. This paper first reports that (i) this residual strain, believed to be irreversible, can be partially recovered and (ii) a stress increase is observed after a pause during cyclic loading. Also, it suggests an explanation of these experimental observations based on the endo and exothermic phase transformations of the alloy, the heat exchange by convection around the sample and the Clausius–Clapeyron relation characterizing the SMA.
Controllable liquid spread speed in the groove using femtosecond laser

The surface induced flow in micro groove has attracted much attention because it can be used as a passive power source in microfluidic devices. In recent years, some researchers have used the surface induced force to deliver liquids in micro groove. The flow speed should be controlled accurately in order to displace liquids with desirable volumes. In this paper, we investigated the feasibility to control the flow speed by constructing microstructure on surface groove using femtosecond laser. Firstly, we used femtosecond laser to fabricate different microstructures on alumina surfaces with different laser scanning speed. It was found that the flow speed in groove increased when the femtosecond laser scanning speed decreased. And the liquid spread distance was linear to the square of spread time. Then we investigated the dynamics of the liquid flow which was influenced by the surface chemical composition property. Some metal materials with different surface energies were sputtered on the irradiated surface. The coated metal film can also change the liquid spread speed in groove. This work provides a method to obtain the expected controllable spread speed by constructing the microstructure using femtosecond laser.
Chopper stabilized analog front-end IC with improved ripple reduction loop

This paper presents a chopper stabilized analog front-end (AFE) IC with enhanced ripple reduction loop for resistive sensor application. The chopper stabilization is effective solution to reduce the low frequency noise, however, suffers from severe output ripple due to the modulated amplifier offset. We proposed a chopper stabilized resistive AFE with improved ripple reduction loop (RRL). The proposed RRL can achieve low noise and low power characteristics while maintaining small circuit area consumption.
Damping in Finemet films capped by platinum

Evolution of the Gilbert damping enhancement in Al-doped Finemet (Al-F) films due to wedge-shaped Pt (0 - 7 nm) capping layer was observed using a broadband ferromagnetic resonance technique. The Pt wedge-shaped layer evolves from clusters to a continuous layer when its nominal thickness dPt > 1.5 nm. The damping for the discontinuous layer changes with dPt in a different way than expected from backflow of spin currents and is accompanied with a shift in ferromagnetic resonance field for Al-F covered by Pt clusters. The data are analyzed in terms of spin mixing conductance and spin-orbit coupling.
Phylogenetic Analysis of the Species Theilovirus: Emerging Murine and Human Pathogens

ABSTRACT The Cardiovirus genus of the family Picornaviridae includes two distinct species, Encephalomyocarditis virus and Theilovirus. We now report the complete nucleotide sequences of three Theiler's murine encephalomyelitis virus (TMEV) strains (TO Yale, TOB15, and Vie 415HTR) and of Vilyuisk human encephalomyelitis virus (VHEV). This information, together with the recently reported sequences of divergent theiloviruses (Theiler's-like rat virus [TRV] and Saffold viruses 1 and 2 [SAFV-1 and SAFV-2]), enables an updated phylogenetic analysis as well as a reexamination of several gene products important in the pathogenesis of this emerging group of viruses. In the light of the known neurotropism of TMEV and the new human SAFV-1 and SAFV-2, the resulting data suggest the existence of theiloviruses that cause human central nervous system infections. Our phylogenetic analyses point to the classification of presently known theiloviruses into five types: TMEV, VHEV, TRV, SAFV-1, and SAFV-2.
Towards a Framework for Rhetorical Argumentation

This paper presents an approach towards the definition of a formal framework for rhetorical argumentation. Before describing the competence theory behind the framework, we introduce the notion of rhetorical argument, and describe the New Rhetoric, a well known theory in the philosophy of argumentation, upon which our work is based. 1 Motivation The study of argumentation has undergone periods of decadence alternate with periods of renaissance. Currently, we are witnessing one of the latter, as proved by research flowering in many issues and aspects, both in Philosophy and in Artificial Intelligence. The work presented in this paper is concerned in particular with rhetorical argumentation, which on the other hand has enjoyed consideration to a somewhat lesser extent. By rhetorical argument we want to denote arguments which are both heavily based on the audience’s perception of the world, and concerned more with evaluative judgments than with establishing the truth or otherwise of a proposition, like those in the following dialogue 1 :
Comparison between the products of four RPM systems for metals

Purpose – To compare the capabilities and product quality of four state‐of‐the‐art metal rapid prototyping and manufacturing (RPM) systems. This comparison could help industrial companies to know the advantages and disadvantages of each system and decide which system is the most appropriate for their application field.Design/methodology/approach – This work evaluates and compares the quality of four identical benchmarks fabricated from different metallic powders by using four recently developed RPM systems for metals. The evaluation considers benchmark geometry, dimensional precision, material type, product strength and hardness, surface quality, building speed, materials, operation and running cost.Findings – Results show that using RPM technology for the production of metallic products proved to be successful and promising technology to fabricate high strength products such as dies and molds parts which have complicated geometry and fine features. The best quality and strength was developed by the techn.
Regenerative converter for PWM AC drives

A description is presented of a regenerative converter which allows the SCR power structure to operate as a synchronous line commutator, while a 2 transistor series/shunt chopper, with a power resistor, controls the regenerative power flow, and offers an emergency braking capability. In addition, SCR commutation is accomplished by the line voltage and diversion of bus current. Both simulation and experimental results are given. <<ETX>>