Miracle-dz/UniFAR-FTUs huggingface dataset:
Descriptions of treatment effects in neurology textbooks recommended for medical students

In clinical practice there is a daily need for valid information about treatment, diagnosis, prognosis and prevention. In the early 1990s, evidence-based medicine (EBM) was developed and is now a central aspect of clinical medicine (1). Despite the growing interest in EBM in medical journals, we had the feeling that principles laid down in EBM regarding quantitative descriptions of the effects of treatments were still not represented in neurological textbooks for students. We tested this preliminary observation by systematically evaluating textbooks recommended at medical faculties in northern Europe. According to EBM principles (1), we formulated an answerable question about the treatment of five clinically important neurological diseases (Table 1). We searched for randomized controlled trials, reviews and meta-analyses, representing the top of traditional hierarchy of evidence (1), related to five diseases in MEDLINE, Cochrane library, reference handbooks and home-pages of some Swedish authorities (http://www.mpa.se and http://www.sbu.se) using the following search terms: reviews, randomized controlled trials, the name of the disease and the name of intervention. We extracted data about treatment effects from nine recommended textbooks (2–10) used during clinical training in neurology recommended at the Departments of Neurology at all Medical Faculties in Sweden and the universities in Oslo, Copenhagen and Helsinki (spring in 2002). Textbooks published before 1995 or that were written in a language other than Swedish, Danish, Norwegian or English were excluded. The main outcome of this study was the number of fully answered clinical questions divided by the total number of clinical questions (n 1⁄4 6 · 9 1⁄4 54, Table 1). A full answer consisted of any of the predefined outcomes and a qualitative measure of the outcome, such as the study outcome in both treatment and control group, absolute risk reduction (ARR) or numbers-needed-to-treat (NNT) (Table 1). ARR and NNT are important tools when comparing the effects of treatments. Relative risk differences are insufficient descriptions.
A nanoporous, ultrahydrophobic aluminum-coating process with exceptional dropwise condensation and shedding properties

Many studies have shown that dropwise condensation can enhance air-side heat transfer coefficients by at least an order of magnitude relative to filmwise condensation. However, among the hundreds of superhydrophobic surface-modification processes previously reported, there remains a lack of coating methods that enable stable dropwise condensation and can be applied to aluminum—by far the most common material for the air side of heat exchangers, e.g. in air conditioning. Here we present a bottom-up synthesis technique to grow zinc oxide-based films on to aluminum with tunable nanoporosity and strongly re-entrant surface features. These surfaces exhibit exceptional static water contact angles of up to 178° with a hysteresis less than 3° and a slide angle of 1°. We have further characterized the surfaces in the presence of six different liquids, and show that our optimal surface can repel even dipropylene glycol with a contact angle of 124°, even though its surface tension is less than half that of water. Crucially, we have also tested our films under water-condensing conditions in flowing air, characterizing the droplet-shedding behavior, and we have understood how to tune the growth process to deliver stable droplet-shedding instead of flooding. The process uses inexpensive reagents, can operate below 100 °C via immersion in an aqueous bath, and takes 1–3 h to complete, making it readily scalable to areas of many square meters and complex geometries.
Circumnuclear star-forming activities along the Hubble sequence

In order to study circumnuclear star-forming activity along the Hubble sequence, we cross-correlated the Sloan Digital Sky Survey Data Release 2 (SDSS DR2) with the Third Reference Catalog of Bright Galaxies (RC3) to derive a large sample of 1015 galaxies with both morphological and spectral information. Among these, 385 sources are classified as star-forming galaxies, and the SDSS fibre covered the circumnuclear regions (0.2-2.0 kpc). By using the spectral synthesis method to remove the contribution from the underlying old stellar population, we measured the emission lines fluxes accurately, which are then used to estimate the star-formation rates(SFRs). Our main findings are: (1) early-type spirals show much higher H α luminosities, and hence higher SFRs, and also suffer more extinctions than late-type ones. The equivalent widths ( EW s) of H α emission lines show a similar trend; however, the very late types (Sdm ~ Irr) do have large fractions of high EW s; (2) we confirm that $D_n(4000)$ shows a strong correlation with the strengths of metallic absorption lines (such as CN band, G band, and Mg Ib). Both these lines and the Balmer absorption lines show interesting variations between Sbc and Sd type galaxies; (3) the bar structure tightly relates to the enhanced star formation activity, an effect that is even more significant in the early-type spirals. But we should note that the bar structure is not a necessary or sufficient condition for galaxies to harbor circumnuclear star formations.
Improvement in Sensing Performance of H 2 O 2 Biosensor Electrodes through Modification of Anatase TiO 2 Nanorods and Pretreatment of Electrochemical Reduction

Electrochemical biosensors are essential health monitors that aid in the detection and diagnosis of diseases. In this research, anatase titanium dioxide (TiO2) nanorods (TNR-A) were synthesized on a titanium (Ti) substrate in three stages, namely, hydrothermal, alkali, and heat treatments, and utilized as a modified electrode (TNR-A/Ti). The pretreatment of electrochemical reduction was adopted to increase the Ti3+ amount in TiO2 nanorod surfaces of the electrodes, thus improving electron transfer. The electrodes were characterized by X-ray diffractometry (XRD), fieldemission scanning electron microscopy (FESEM), and X-ray photoelectron spectroscopy (XPS). The electrodes after pretreatment (Ti3+-TNR-A/Ti) showed a better electrochemical response to hydrogen peroxide (H2O2), indicating that pretreatment improves the performance of electrodes. The assembled biosensor electrode (Nafion/HRP/Ti3+-TNR-A/Ti) exhibited a sensitivity of 6096.4 μA∙mM−1∙cm−2, a detection limit of 0.008 μM, a linearity of 0.04–700 μM, and an apparent Michaelis–Menten constant K M of 0.0027 μM, which are higher than those in previous research studies on TiO2 or similarly nanostructured modified biosensor electrodes. This research could provide a potential competent method that can be used to modify electrodes for high-performance amperometric biosensors.
Cooperation in Evolving Social Networks

We study the problem of cooperative behavior emerging in an environment where individual behaviors and interaction structures coevolve. Players not only learn which strategy to adopt by imitating the strategy of the best-performing player they observe, but also choose with whom they should interact by selectively creating and/or severing ties with other players based on a myopic cost-benefit comparison. We find that scalable cooperation---that is, high levels of cooperation in large populations---can be achieved in sparse networks, assuming that individuals are able to sever ties unilaterally and that new ties can only be created with the mutual consent of both parties. Detailed examination shows that there is an important trade-off between local reinforcement and global expansion in achieving cooperation in dynamic networks. As a result, networks in which ties are costly and local structure is largely absent tend to generate higher levels of cooperation than those in which ties are made easily and friends of friends interact with high probability, where the latter result contrasts strongly with the usual intuition.
On adaptive go-back-N ARQ protocol for variable-error rate channels

This letter presents a simple method to simultaneously optimize a multiplicity of design parameters for the adaptive automatic repeat request strategy previously reported, and subsequently provides a quantitative measurement that reflects the appropriateness of the selected parameters. An exact analytical expression that allows us to compute the throughput crossover probability between the two different protocols is derived. The results provide fundamental insights into how these key parameters interact and determine the system performance.
Image Segmentation And Reflection Analysis Through Color

In this paper, we present an approach to color image understanding that can be used to segment and analyze surfaces with color variations due to highlights and shading. We begin with a theory that relates the reflected light from dielectric materials, such as plastic, to fundamental physical reflection processes, and describes the color of the reflected light as a linear combination of the color of the light due to surface reflection (highlights) and body reflection (object color). This theory is used in an algorithm that separates a color image into two parts: an image of just the highlights, and the original image with the highlights removed. In the past, we have applied this method to hand-segmented images. The current paper shows how to perform automatic segmentation method by applying this theory in stages to identify the object and highlight colors. The result is a combination of segmentation and reflection analysis that is better than traditional heuristic segmentation methods (such as histogram thresholding), and provides important physical information about the surface geometry and material properties at the same time. We also show the importance of modeling the camera properties for this kind of quantitative analysis of color. This line of research cRn lead to physics-based image segmentation methods that are both more reliable and more useful than traditional segmentation methods.
Analog fault diagnosis and testing by inverse problem technique

This paper introduces a testing algorithm based on the inverse problem concept. This algorithm detects single and double parametric faults in analog circuits by estimating the actual parameter values of the CUT. To verify the effectiveness of the proposed algorithm, it is applied to the Sallen-Key second order band pass filter where all injected faults are detected and diagnostic correctly with max percentage estimation error of 0.7%. Moreover, an additive white Gaussian noise is added to the output of the tested filter to verify the advanced performance of the proposed algorithm.
Consistent Bounded-Asynchronous Parameter Servers for Distributed ML

In distributed ML applications, shared parameters are usually replicated among computing nodes to minimize network overhead. Therefore, proper consistency model must be carefully chosen to ensure algorithm's correctness and provide high throughput. Existing consistency models used in general-purpose databases and modern distributed ML systems are either too loose to guarantee correctness of the ML algorithms or too strict and thus fail to fully exploit the computing power of the underlying distributed system. Many ML algorithms fall into the category of \emph{iterative convergent algorithms} which start from a randomly chosen initial point and converge to optima by repeating iteratively a set of procedures. We've found that many such algorithms are to a bounded amount of inconsistency and still converge correctly. This property allows distributed ML to relax strict consistency models to improve system performance while theoretically guarantees algorithmic correctness. In this paper, we present several relaxed consistency models for asynchronous parallel computation and theoretically prove their algorithmic correctness. The proposed consistency models are implemented in a distributed parameter server and evaluated in the context of a popular ML application: topic modeling.
Coinduction up-to in a fibrational setting

Bisimulation up-to enhances the coinductive proof method for bisimilarity, providing efficient proof techniques for checking properties of different kinds of systems. We prove the soundness of such techniques in a fibrational setting, building on the seminal work of Hermida and Jacobs. This allows us to systematically obtain up-to techniques not only for bisimilarity but for a large class of coinductive predicates modelled as coalgebras. By tuning the parameters of our framework, we obtain novel techniques for unary predicates and nominal automata, a variant of the GSOS rule format for similarity, and a new categorical treatment of weak bisimilarity.
Volumetric MRI data correlate to disease severity in metachromatic leukodystrophy

Metachromatic leukodystrophy (MLD) is an inherited lysosomal disorder due to a deficiency in arylsulfatase A with progressive demyelination and neurological decline. This retrospective MRI study investigated the extent of cortical involvement at time of diagnosis, and clinical correlates to both conventional and regional volumetric measures of brain involvement.
An overview of conventional and surface free energy methods used to determine asphalt aggregate adhesion

Asphalt aggregate adhesion strength is the fundamental property that determines the moisture damage of asphalt pavement. Moisture damage is related to loss of stiffness or strength as a result of cohesive and adhesive failure of the pavement material. The conventional test for asphalt aggregate adhesion is only comparative and does not provide a quantitative value. Currently research is being carried out to introduce surface free energy measurements as fundamental means to quantify asphalt aggregate adhesion and cohesion. Some of the methods developed to measure surface free energy are Sessile Drop Method, Wilhelmy Plate Method, Adsorption Method, Inverse Gas Chromatography, and Micro-calorimeter. This could eventually lead to the development of a cost effective, accurate and reliable surface free energy measurement instrument which can be used by field engineers.
An improved MPPT method for quasi-Z-source inverter based grid-connected photovoltaic power system

The main objective for a grid-connected photovoltaic (PV) inverter is to feed the harvested energy from PV panels to the grid with high efficiency and high electrical power quality. In this paper, an improved maximum power point tracking method applied for a quasi-Z-source PV inverter is proposed to track the maximum power of the PV power system. Furthermore, the DC-link stable voltage control and AC-side power control of the entire system are designed. The simulated results illustrate the validity and correctness of the proposed approach, and an efficient method for PV power generation.
Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments.
Appraisal Expression Recognition with Syntactic Path for Sentence Sentiment Classification

An appraisal expression is described as a collocation of the polarity word and its modified target, which can be considered as an atomic unit expressing an evaluative stance towards a target. Recognizing appraisal expressions is essential for sentence sentiment classification. However, the relevant research is far from enough. This paper proposes a novel method that uses syntactic paths to recognize appraisal expressions. Compared with the previous work, the proposed syntactic path based method has two advantages: 1) it automatically explores syntactic knowledge, and 2) it covers more syntactic relationships between polarity words and targets. Based on these, this paper applies appraisal expressions to sentence sentiment classification. Some novel features based on appraisal expressions, including semantic features, syntactic features, lexical features and polarity features, are designed to classify sentiment sentences as positive or negative. Experimental results on the camera and MP3 player domains show that the proposed appraisal expression based method outperforms other sentence sentiment classification methods. Moreover, we present a composite classifier to integrate our appraisal expression based feature set and the common-used feature set. Experimental results show that our composite classifier can get a better performance than each of them.
Differential effects of maternal obesity and weight loss in the periconceptional period on the epigenetic regulation of hepatic insulin‐signaling pathways in the offspring

Our aim was to determine the effect of exposure to maternal obesity or to maternal weight loss around conception on the programming of hepatic insulin signaling in the offspring. We used an embryo transfer model in sheep to investigate the effects of exposure to either maternal obesity or to weight loss in normal and obese mothers preceding and for 1 wk after conception on the expression of hepatic insulin‐signaling and gluconeogenic factors and key miRNAs involved in insulin signaling in the offspring. We found that exposure to maternal obesity resulted in increased hepatic miR‐29b (P<0.05), miR‐103 (P<0.01), and miR‐107 (P<0.05) expression, a decrease in IR (P<0.05), phopsho‐Akt (P<0.01), and phospho‐FoxO1 (P<0.01) abundance, and a paradoxical decrease in 11βHSD1 (P<0.05), PEPCK‐C (P<0.01), and PEPCK‐M (P<0.05) expression in lambs. These changes were ablated by a period of moderate dietary restriction imposed during the periconceptional period. Maternal dietary restriction alone also resulted in decreased abundance of a separate subset of hepatic insulin‐signaling molecules, namely, IRS1 (P<0.05), PDK1 (P<0.01), phospho‐PDK1 (P<0.05), and aPKCξ (P<0.05) and in decreased PEPCK‐C (P<0.01) and G6Pase (P<0.01) expression in the lamb. Our findings highlight the sensitivity of the epigenome to maternal nutrition around conception and the need for dietary interventions that maximize metabolic benefits and minimize metabolic costs for the next generation. —Nicholas, L. M. , Rattanatray, L. , MacLaughlin, S. M. , Ozanne, S. E. , Kleemann, D. O. , Walker, S. K. , Morrison, J. L. , Zhang, S. , Muhlhausler, B. S. , Martin‐Gronert, M. S. , McMillen, I. C. , Differential effects of maternal obesity and weight loss in the periconceptional period on the epigenetic regulation of hepatic insulin‐signaling pathways in the offspring. FASEB J. 27, 3786–3796 (2013). www.fasebj. org
Small and large anemonefishes can coexist using the same patchy resources on a coral reef, before habitat destruction

Summary 1 According to meta-population models, a superior competitor and a superior disperser can coexist in a patchy environment. The two anemonefishes, a large aggressive Amphiprion clarkii Bennett and a small less-aggressive A. perideraion Bleeker, use the same host anemone Heteractis crispa Ehrenberg on a coral reef, Okinawa, Japan, where most of the hosts disappeared after the coral bleaching in 1998. Their microhabitat (host) use and coexistence, and the quality and quantity of microhabitats were investigated in 1988, 1989, 1999 and 2000 on the coral reef. Their interspecific interaction was also examined. 2 Before the habitat destruction, the two species coexisted. Although A. clarkii was behaviourally dominant over A. perideraion in a cohabiting group, A. perideraion was a superior competitor in terms of site displacement, because A. perideraion could displace a microhabitat. Adult A. clarkii emigrated from a cohabiting group probably due to the high cost of interactions with adult A. perideraion . Although it is easier to defend a small area for a larger species, sharing a host with adult A. perideraion may not pay for A. clarkii because A. clarkii needs a larger area. 3 A. clarkii was not only a superior disperser, which was able to find a vacated host, but also a pioneer species that was able to use newly settled small hosts. Larval A. clarkii settled on such a small host because they were able to move to larger hosts for future reproduction, while A. perideraion did not settle on a small host because of low mobility after settlement. Microhabitat (host) with various sizes might have promoted their coexistence. 4 After the habitat destruction, the superior competitor A. perideraion went extinct locally due probably to lack of small host utilization ability. The present study implies that the difference in body size between the two competitors plays an important role in their coexistence, because species with different body sizes can have different mobility and require different amounts of resources.
Fast shared-memory algorithms for computing the minimum spanning forest of sparse graphs

Summary form only given. Minimum spanning tree (MST) is one of the most studied combinatorial problems with practical applications in VLSI layout, wireless communication, and distributed networks, recent problems in biology and medicine such as cancer detection, medical imaging, and proteomics, and national security and bioterrorism such as detecting the spread of toxins through populations in the case of biological/chemical warfare. Most of the previous attempts for improving the speed of MST using parallel computing are too complicated to implement or perform well only on special graphs with regular structure. We design and implement four parallel MST algorithms (three variations of Boruvka plus our new approach) for arbitrary sparse graphs that for the first time give speedup when compared with the best sequential algorithm. In fact, our algorithms also solve the minimum spanning forest problem. We provide an experimental study of our algorithms on symmetric multiprocessors such as IBM's p690/Regatta and Sun's Enterprise servers. Our new implementation achieves good speedups over a wide range of input graphs with regular and irregular structures, including the graphs used by previous parallel MST studies. For example, on an arbitrary random graph with IM vertices and 20M edges, our new approach achieves a speedup of 5 using 8 processors. The source code for these algorithms is freely-available from our Web site hpc.ece. unm.edu. This work was supported in part by NSF Grants CAREER ACI-00-93039, ITR ACI-00-81404, DEB-99-10123, ITR EIA-01-21377, Biocomplexity DEB-01-20709, and ITR EF/BIO 03-31654.