Miracle-dz/UniFAR-FTUs huggingface dataset:
Recommendations by health organizations for pulse consumption

The present paper aims to study why and how health organizations recommend the consumption of pulses such as beans, chickpeas or lentils. Although it is recognized that frequent pulse consumption may reduce serum cholesterol levels and helps reduce risks of coronary heart disease and diabetes, these advantages are scarcely mentioned by health-promoting associations, i.e. vegetarians and organizations helping people to reduce the risks for chronic diseases. Pulses, especially common beans, are rather considered as whole grains that provide plenty of proteins, starch, dietary fibres, minerals and vitamins. Many organizations refer to the food guide pyramid to advise their members, and place beans either in the third part, together with meat, in the second one with fruits and vegetables, or in the bottom part with starchy foods. Whatever their place, they have acquired the status of staple food for anyone who wants to eat a healthy diet.
Unsupervised person re-identification via re-ranking enhanced sample-specific metric learning

Despite of the great progress of image-based person re-identification, most existing methods use supervised metric learning to build re-identification models and thus require repeated human effort to annotate sample pairs from non-overlapping cameras. In this paper, we propose an unsupervised sample-specific metric learning approach (SSML) to alleviate this problem. Specifically, using samples those are negatives (with a high probability) to the query samples, we train a local metric for each query sample following the max-margin learning theory. Moreover, a KNN intersection re-ranking (KIRR) method is used to further decrease the ambiguity of samples and aggregate the re-identification performance. With experiments on three widely used person re-identification datasets: VIPeR, CUHK01, and PRID, we demonstrate that the proposed approach is simple but effective.
Learning Multi-grid Generative ConvNets by Minimal Contrastive Divergence

This paper proposes a minimal contrastive divergence method for learning energy-based generative ConvNet models of images at multiple grids (or scales) simultaneously. For each grid, we learn an energy-based probabilistic model where the energy function is defined by a bottom-up convolutional neural network (ConvNet or CNN). Learning such a model requires generating synthesized examples from the model. Within each iteration of our learning algorithm, for each observed training image, we generate synthesized images at multiple grids by initializing the finite-step MCMC sampling from a minimal 1 x 1 version of the training image. The synthesized image at each subsequent grid is obtained by a finite-step MCMC initialized from the synthesized image generated at the previous coarser grid. After obtaining the synthesized examples, the parameters of the models at multiple grids are updated separately and simultaneously based on the differences between synthesized and observed examples. We call this learning method the multi-grid minimal contrastive divergence. We show that this method can learn realistic energy-based generative ConvNet models, and it outperforms the original contrastive divergence (CD) and persistent CD.
HEp-2 cell pattern segmentation for the support of autoimmune disease diagnosis

The Indirect Immune Fluorescence Test (iIFT) is the most commonly used screening method for the diagnosis of autoimmune diseases. The presence of certain autoimmune diseases is proven by immunologically detecting their corresponding auto-antibodies using the HEp-2 cancer cell line. For this purpose HEp-2 cells are added to the patients' blood serum containing certain auto-antibodies which will bond with the HEp-2 cells leading to a wide variety of patterns that can be observed under a fluorescence microscope. Due to the disadvantages of manual testing, automation and standardization are necessary. This paper proposes an unsupervised segmentation algorithm as part of an ongoing research to develop a CAD system to digitally support iIFT testing.
Nabiximols combined with motivational enhancement/cognitive behavioral therapy for the treatment of cannabis dependence: A pilot randomized clinical trial

Background The current lack of pharmacological treatments for cannabis use disorder (CUD) warrants novel approaches and further investigation of promising pharmacotherapy. We previously showed that nabiximols (27 mg/ml Δ9-tetrahydrocannabinol (THC)/ 25 mg/ml cannabidiol (CBD), Sativex®) can decrease cannabis withdrawal symptoms. Here, we assessed in a pilot study the tolerability and safety of self-titrated nabiximols vs. placebo among 40 treatment-seeking cannabis-dependent participants. Methods Subjects participated in a double blind randomized clinical trial, with as-needed nabiximols up to 113.4 mg THC/105 mg CBD or placebo daily for 12 weeks, concurrently with Motivational Enhancement Therapy and Cognitive Behavioral Therapy (MET/CBT). Primary outcome measures were tolerability and abstinence, secondary outcome measures were days and amount of cannabis use, withdrawal, and craving scores. Participants received up to CDN$ 855 in compensation for their time. Results Medication was well tolerated and no serious adverse events (SAEs) were observed. Rates of adverse events did not differ between treatment arms (F1,39 = 0.205, NS). There was no significant change in abstinence rates at trial end. Participants were not able to differentiate between subjective effects associated with nabiximols or placebo treatments (F1,40 = 0.585, NS). Cannabis use was reduced in the nabiximols (70.5%) and placebo groups (42.6%). Nabiximols reduced cannabis craving but no significant differences between the nabiximols and placebo groups were observed on withdrawal scores. Conclusions Nabiximols in combination with MET/CBT was well tolerated and allowed for reduction of cannabis use. Future clinical trials should explore the potential of high doses of nabiximols for cannabis dependence.
Rates of southeast Greenland ice volume loss from combined ICESat and ASTER observations

Repeat satellite laser altimetry is critical for observing the rapidly changing mass balance of the Greenland Ice Sheet. However, sparse sampling and high surface slopes over rapidly thinning, coastal outlet glaciers may result in underestimation of mass loss. Here we supplement ICESat‐derived surface elevation changes with differenced ASTER digital elevation models of outlet glaciers in southeastern Greenland, the region with the largest concentrated change in outlet glacier mass loss. We estimate a 2002–2005 regional volume‐loss rate of 108 km3/yr. Our results are consistent with drainage‐scale GRACE and mass‐budget estimates when differences in observation periods are taken into account. The two largest glaciers, Kangerdlugssuaq and Helheim, account for only 28% of the mass loss, illustrating the combined importance of smaller glaciers and the need for complete observational coverage. Additionally, we find that rapid, concentrated thinning within the outlets represents a small contribution to the total volume change compared to dispersed inland thinning.
Simulation-Based Circuit-Activity Estimation for FPGAs Containing Hard Blocks

FPGAs are electronic devices that are programmable and can functionally perform equivalently to a number of other circuits. FPGAs are used for both rapid and cheap prototyping of new circuit designs as well as for replacing outdated chip models. Due to their complexity, circuits cannot be practically designed by hand; instead, specialized Computer Aided Design (CAD) software performs this complex task. A major concern for devices is power requirements, which can have adverse effects on both the environment and users. The power requirements of a circuit can be directly connected with its activity, which can be estimated by the CAD tools. In this work, we focus on the open source Verilog-To-Routing (VTR) CAD software and propose an improved activity estimation tool using VTR's synthesizer (Odin II) that extends beyond the capabilities of its current estimator (ACE2), such as proper black box activity propagation and support for circuits containing no clocks or more than one clock. Our results are experimentally evaluated with VTR's FPGA architectures and benchmark circuits.
Model Predictive Control for Lateral Position of Endless Metal Belts

Endless metal belts play an important role in advanced processing lines or belt machines for many production processes. In contrast to standard conveyor lines metal belts must be run over cylindrical return drums due to the high elastic modulus of the belts material and the usually high level of pre-stress. Since cylindrical return drums do not provide passive lateral guidance (self-centering) they have to be actively adjusted by swiveling drum axes. In this work a suitable control scheme is presented to guarantee a set lateral position at the return drums even in the presence of a lateral disturbance force. Since the lateral dynamics of the endless belt show strong coupling between all inputs and all outputs a multivariate control approach with inherent decoupling capabilities is needed. Moreover, a number of technological constraints must be fulfilled for all operating conditions such as limited swivel angles and the maximum allowable tensile stress in the belt. In this research work a constrained model predictive control (MPC) is therefore designed to overcome the aforementioned problems. The model is based on a description in the spatial domain (belt travel) which renders the model independent of operating speed. Using this model a multi-input multi-output (MIMO) MPC-scheme is derived also in state-space representation. Moreover, the control explicitly considers constraints on the control inputs and on the maximum allowable belt stress.
Balancing energy saving and latency in mobile collector based delay sensitive wireless sensor network

In many wireless sensor network (WSN) applications, a mobile collector(MC) traverses around the sensing field to collect sensed data from static sensor nodes. The speed of the MC is much low relative to the data transmission speed in WSN. Due to the low speed of the MC, latency may attain the maximum value if the MC collects data directly from each sensor node in the field. This may not be permissible in many delay aware WSNs. To reduce the latency, each sensor node transmits data using multi hop relay to some selected nodes. But, the number of relay hops should not be large as it would result in increased energy consumption in data transmission. Thus, a strong trade-off between energy saving and data gathering latency exists which can be realized by making an adjustment between the distance travelled by the MC and the average relay hop. In this work, we introduce a balance metric (average relay hop X tour length) which should be kept low for establishing a better trade-off between the energy saving and latency. We propose a MC based data collection method named Maximum Neighbour Polling Point (MNPP) which outperforms other existing algorithms in terms of the reduced latency and the balance metric (average relay hop X tour length).
A Permanent Magnet Brushless Doubly Fed Generator With Segmented Structure

The brushless doubly fed machine (BDFM) has been one of the key topics in the research of wind power generation. To improve the performances of the BDFM, a new permanent magnet (PM) brushless doubly fed generator (BDFG) with complementary structure is proposed in this paper. Compared with the traditional BDFM, there is an additional PM rotor providing excitation magnetic field for power and control windings. Benefiting from the absence of the exciting current and the excitation loss, the efficiency, and the power density may be increased. In order to solve a series of problems due to the introduction of PM rotor and the field modulation ring, the segmented structure is adopted. The improvement schemes are introduced in detail. Finally, the performances of the proposed BDFG are analyzed by the finite-element analysis and the results verify the effectiveness of the proposed methods.
All in focus camera vision system for robot navigation and manipulation based on the DFF criteria

A method to improve the resolution in depth by applying the depth from focus (DFF) criteria is proposed. The depth from focus is a criteria used to get simultaneously both the all-in-focus image and three-dimensional information with a single camera. But in these criteria there is a well-known drawback; the resolution is good only at short distances. Here, the optical characteristic that describes the limitation of the measurement range is analyzed. Then, a better criterion to improve the resolution in the depth is proposed by considering the "best focal distance". In order to use this new method, it is necessary to modify the focal distance (zoom) in the camera. Then, an accurate control of the camera should be done to acquire a good view of the desired target and later by, applying the depth from focus criteria together with the best focal distance, being able to obtain good depth (three-dimensional) information.
Formation of tungsten oxide nanowires by ion irradiation and vacuum annealing

Here we reported the fabrication of tungsten oxide (WO3−x) nanowires by Ar+ ion irradiation of WO3 thin films followed by annealing in vacuum. The nanowire length increases with increasing irradiation fluence and with decreasing ion energy. We propose that the stress-driven diffusion of the irradiation-induced W interstitial atoms is responsible for the formation of the nanowires. Comparing to the pristine film, the fabricated nanowire film shows a 106-fold enhancement in electrical conductivity, resulting from the high-density irradiation-induced vacancies on the oxygen sublattice. The nanostructure exhibits largely enhanced surface-enhanced Raman scattering effect due to the oxygen vacancy. Thus, ion irradiation provides a powerful approach for fabricating and tailoring the surface nanostructures of semiconductors.
Differences among six woody perennials native to Northern Europe in their level of genetic differentiation and adaptive potential at fine local scale

Abstract The ability of perennial species to adapt their phenology to present and future temperature conditions is important for their ability to retain high fitness compared to other competing plant species, pests, and pathogens. Many transplanting studies with forest tree species have previously reported substantial genetic differentiation among populations within their native range. However, the question of “how local is local” is still highly debated in conservation biology because studies on genetic patterns of variation within and among populations at the local scale are limited and scattered. In this study, we compare the level of genetic differentiation among populations of six different perennial plant species based on their variation in spring flushing. We assess the level of additive genetic variation present within the local population. For all six species, we find significant differentiation among populations from sites with mean annual temperature ranging between 7.4°C and 8.4°C. The observed variation can only be partly explained by the climate at the site of origin. Most clear relationship between early flushing and higher average spring temperature is observed for the three wind‐pollinated species in the study, while the relations are much less clear for the three insect‐pollinated species. This supports that pollination system can influence the balance between genetic drift and natural selection and thereby influence the level of local adaptation in long‐lived species. On the positive side, we find that the native populations of woody plant species have maintained high levels of additive genetic variation in spring phenology, although this also differs substantially among the six studied species.
Un-preprocessing: Extended CPP that works with your tools

Many tools directly change programs, such as bug-fixing tools, program migration tools, etc. We call them program-modification tools. On the other hand, many programming languages use the C preprocessor, such as C, C++, and Objective-C. Because of the complexity of preprocessors, many program-modification tools either fail to produce sound results under the presence of preprocessor directives, or give up completely and deal only with preprocessed code. In this paper we propose a lightweight approach that enables program-modification tools to work with the C preprocessor for free. The idea is that program-modification tools now simply target the preprocessed code, and our system, acting as a bidirectional C preprocessor, automatically propagates the changes on the preprocessed code back to the un-preprocessed code. The resulting source code is guaranteed to be correct and is kept similar to the original source as much as possible. We have evaluated our approach on Linux kernel with a set of generated changes. The evaluation results show the feasibility and effectiveness of our approach.
In vitro differential sensitivity of melanomas to phenothiazines is based on the presence of codon 600 BRAF mutation

The panel of 60 human cancer cell lines (the NCI-60) assembled by the National Cancer Institute for anticancer drug discovery is a widely used resource. We previously sequenced 24 cancer genes in those cell lines. Eleven of the genes were found to be mutated in three or more of the lines. Using a pharmacogenomic approach, we analyzed the relationship between drug activity and mutations in those 11 genes (APC, RB1, KRAS, NRAS, BRAF, PIK3CA, PTEN, STK11, MADH4, TP53, and CDKN2A). That analysis identified an association between mutation in BRAF and the antiproliferative potential of phenothiazine compounds. Phenothiazines have been used as antipsychotics and as adjunct antiemetics during cancer chemotherapy and more recently have been reported to have anticancer properties. However, to date, the anticancer mechanism of action of phenothiazines has not been elucidated. To follow up on the initial pharmacologic observations in the NCI-60 screen, we did pharmacologic experiments on 11 of the NCI-60 cell lines and, prospectively, on an additional 24 lines. The studies provide evidence that BRAF mutation (codon 600) in melanoma as opposed to RAS mutation is predictive of an increase in sensitivity to phenothiazines as determined by 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt assay (Wilcoxon P = 0.007). That pattern of increased sensitivity to phenothiazines based on the presence of codon 600 BRAF mutation may be unique to melanomas, as we do not observe it in a panel of colorectal cancers. The findings reported here have potential implications for the use of phenothiazines in the treatment of V600E BRAF mutant melanoma. [Mol Cancer Ther 2008;7(6):1337–46]
Tag refinement based on multilingual tag hierarchies extracted from image folksonomy

This paper presents a novel method for tag refinement using multilingual sources of tagged images in an image folksonomy. The proposed method enables accurate tag refinement by effectively leveraging multilingual sources of tags and considering the hierarchical structure of tags in the following way. First, synonymous tags across different languages are detected based on similarities between tagged images. In this stage, the proposed method utilizes visual similarities to effectively detect synonymous tags since the visual features extracted from images should be similar if they are assigned tags with the same meaning in different languages. Then hierarchical structure of the tags are extracted based on the similarity between the detected synonymous tags. The hierarchical structure provides hypernymous and hyponymous tags of the target tags, which are important for considering the relevance between tags and images. Consulting the hierarchical structure enables removal of irrelevant tags from the images and assignment of relevant tags to the images. The proposed method effectively utilizes tags in various languages in an image folksonomy. Experimental results show the effectiveness of introducing multilingual sources of tagged images for accuracy improvement in tag refinement.
Sustained Release of Immunosuppressant by Nanoparticle-anchoring Hydrogel Scaffold Improved the Survival of Transplanted Stem Cells and Tissue Regeneration

The outcome of scaffold-based stem cell transplantation remains unsatisfied due to the poor survival of transplanted cells. One of the major hurdles associated with the stem cell survival is the immune rejection, which can be effectively reduced by the use of immunosuppressant. However, ideal localized and sustained release of immunosuppressant is difficult to be realized, because it is arduous to hold the drug delivery system within scaffold for a long period of time. In the present study, the sustained release of immunosuppressant for the purpose of improving the survival of stem cells was successfully realized by a nanoparticle-anchoring hydrogel scaffold we developed. Methods: Poly (lactic-co-glycolic acid) (PLGA) nanoparticles were modified with RADA16 (RNPs), a self-assembling peptide, and then anchored to a RADA16 hydrogel (RNPs + Gel). The immobilization of RNPs in hydrogel was measured in vitro and in vivo, including the Brownian motion and cumulative leakage of RNPs and the in vivo retention of injected RNPs with hydrogel. Tacrolimus, as a typical immunosuppressant, was encapsulated in RNPs (T-RNPs) that were anchored to the hydrogel and its release behavior were studied. Endothelial progenitor cells (EPCs), as model stem cells, were cultured in the T-RNPs-anchoring hydrogel to test the immune-suppressing effect. The cytotoxicity of the scaffold against EPCs was also measured compared with free tacrolimus-loaded hydrogel. The therapeutic efficacy of the scaffold laden with EPCs on the hind limb ischemia was further evaluated in mice. Results: The Brownian motion and cumulative leakage of RNPs were significantly decreased compared with the un-modified nanoparticles (NPs). The in vivo retention of injected RNPs with hydrogel was obviously longer than that of NPs with hydrogel. The release of tacrolimus from T-RNPs + Gel could be sustained for 28 days. Compared with free tacrolimus-loaded hydrogel, the immune responses were significantly reduced and the survival of EPCs was greatly improved both in vitro and in vivo. The results of histological evaluation, including accumulation of immune cells and deposition of anti-graft antibodies, further revealed significantly lessened immune rejection in T-RNPs-anchoring hydrogel group compared with other groups. In pharmacodynamics study, the scaffold laden with EPCs was applied to treat hind limb ischemia in mice and significantly promoted the blood perfusion (~91 % versus ~36 % in control group). Conclusion: The nanoparticle-anchoring hydrogel scaffold is promising for localized immunosuppressant release, thereby can enhance the survival of transplanted cells and finally lead to successful tissue regeneration.