Miracle-dz/UniFAR-FTUs huggingface dataset:
Polymethylmethacrylate/Polyacrylonitrile Membranes via Centrifugal Spinning as Separator in Li-Ion Batteries

Electrospun nanofiber membranes have been extensively studied as separators in Li-ion batteries due to their large porosity, unique pore structure, and high electrolyte uptake. However, the electrospinning process has some serious drawbacks, such as low spinning rate and high production cost. The centrifugal spinning technique can be used as a fast, cost-effective and safe technique to fabricate high-performance fiber-based separators. In this work, polymethylmethacrylate (PMMA)/polyacrylonitrile (PAN) membranes with different blend ratios were produced via centrifugal spinning and characterized by using different electrochemical techniques for use as separators in Li-ion batteries. Compared with commercial microporous polyolefin membrane, centrifugally-spun PMMA/PAN membranes had larger ionic conductivity, higher electrochemical oxidation limit, and lower interfacial resistance with lithium. Centrifugally-spun PMMA/PAN membrane separators were assembled into Li/LiFePO4 cells and these cells delivered high capacities and exhibited good cycling performance at room temperature. In addition, cells using centrifugally-spun PMMA/PAN membrane separators showed superior C-rate performance compared to those using microporous polypropylene (PP) membranes. It is, therefore, demonstrated that centrifugally-spun PMMA/PAN membranes are promising separator candidate for high-performance Li-ion batteries.
A New Evolutionary Algorithm Based on Simplex Crossover and PSO Mutation for Constrained Optimization Problems

A new approach is presented to handle constraints optimization using evolutionary algorithms in this paper. First, we present a specific varying fitness function technique, this technique incorporates the problem’s constraints into the fitness function in a dynamic way. The resulting varying fitness function facilitates the EA search. On one hand, The new fitness function without any parameters can properly evaluate not only feasible solution, but also infeasible one, on other hand, the information of the best solution in the current population is also concerned in fitness function, which make search more efficient. Meanwhile, a new crossover operator based on simplex crossover operator and a new PSO mutation operator is also proposed, and both the operators utilize the information of good individuals in the current populations so they can produce high quality offspring. Based on these, a new evolutionary algorithm for constrained optimization problems is proposed. The simulations are made on five widely used benchmark problems, and the results indicate the proposed algorithm is effective
Skin color detection by illumination estimation and normalization in shadow regions

Skin detection based on skin-color information has gained much attention because of its advantages in effective computation and rotation independent. An important challenge of skin color detection is how to detect skin color pixels located in shadow regions, which are corrupted by illuminant. In this paper, we propose an illuminant independent skin color detector. The detector consists of two steps: firstly it applies a novel color restoration method to enhance shadow regions; secondly, Bayesian skin color classifier is used to detect skin color pixels in color images. The proposed color restoration method applies Retinex algorithm which based on an advanced adaptive smoothing filter to normalize illumination. Firstly the input image is convolved with some adaptive smoothing mask windows, each mask weight in any window is computed via combining measures of the illumination discontinuity at each pixel; Then, Retinex theory is used to remove illumination estimation image from original image, and achieve the result image. The proposed skin-color detector present more efficiency and promising result when images under harsh illumination conditions. The experimental results prove that the new method can increase accurate hit of skin color pixel detection and maintain real-time performance.
Inflation targeting and fiscal rules in developing countries : interactions and macroeconomic consequences

This thesis is concerned with the role of Inflation Targeting (IT) and Fiscal Rules (FRs), as well as of their interactions, on macroeconomic environment. After laying the conceptual and empirical backgrounds of both these rules-Based policy frameworks (Chapter 1), the dissertation highlights new evidence on their macroeconomic consequences. First, IT adoption does help attracting more Foreign Direct Investment into Developing Countries (Chapter 2). Second, inthese countries, IT adoption provides strong incentives for governments to undertake reforms designed to improve the quality of institutions (Chapter 3). Third, the introduction of national-Level numerical FRs does stand as a credible remedy against fiscal indiscipline in these countries, all the more in politically stable economies and where the numberof FRs in place is important. But this discipline-Enhancing effect of FRs decreases with the time length since their adoption, and is weakened in the presence of supranational rules and in countries with more fragmented government. Interestingly, this effect varies with the type of rules: while Budget Balance Rules and Expenditure Rules have significant disciplineenhancing effects, the effect of Debt Rules proved not significantly different from zero (Chapter 4). The last three chapters of the thesis focus on the role of the interaction between IT and FRs, and to a broader extent, on the interplay between monetary and fiscal authorities. The first result that emerges is that IT, which is a framework for conducting monetary policy, proves also sufficiently binding for fiscal authorities to providing them with strong incentives for improving fiscal discipline, notably in developing countries (Chapter 5). In addition, on the one hand, IT and FRs act complementarily, as adopting both IT and FRs leads to better results in terms of running fiscal surpluses and in terms of bringing down average inflation than adopting only one of these two frameworks. On the other hand, the sequence which consists of introducing FRs first before adopting IT yields better inflationary and fiscal performances than the opposite sequence (Chapter 6). Finally, better Policy Mix coherence, that is, better coordination between monetary and fiscal policies, is conducive to higher economic growth in the Economic Community of West African States (ECOWAS) (Chapter 7).
Forget the battery, let's play games!

Today, the battery life of mobile devices like smart-phones stand as a major obstacle between us and our favorite games. Our goal is to solve this problem using customized power management policies tailored for interactive workloads like game applications. In contrast to video processing, power management for gaming applications is a new field of study and has to account for workload changes based on the users input. We have for the first time studied the stability properties of PID controller-based workload prediction schemes - that have been widely used for video applications - and shown that they do not work for games. Instead, new workload models based on time series modeling are better suited for gaming applications. Using them we have developed power management schemes for modern closed-source games using a DLL injection scheme; all previous techniques required instrumenting the game source code to collect execution times of game frames at runtime. Finally, in this paper we also summarize a number of open problems in this area and outline the potential for new research opportunities.
Structural Mechanisms Underlying Benzodiazepine Modulation of the GABAA Receptor

Many clinically important drugs target ligand-gated ion channels; however, the mechanisms by which these drugs modulate channel function remain elusive. Benzodiazepines (BZDs), anesthetics, and barbiturates exert their CNS actions by binding to GABAA receptors and modulating their function. The structural mechanisms by which BZD binding is transduced to potentiation or inhibition of GABA-induced current (IGABA) are essentially unknown. Here, we explored the role of the γ2Q182-R197 region (Loop F/9) in the modulation of IGABA by positive (flurazepam, zolpidem) and negative [3-carbomethoxy-4-ethyl-6,7-dimethoxy-β-carboline (DMCM)] BZD ligands. Each residue was individually mutated to cysteine, coexpressed with wild-type α1 and β2 subunits in Xenopus oocytes, and analyzed using two-electrode voltage clamp. Individual mutations differentially affected BZD modulation of IGABA. Mutations affecting positive modulation span the length of this region, whereas γ2W183C at the beginning of Loop F was the only mutation that adversely affected DMCM inhibition. Radioligand binding experiments demonstrate that mutations in this region do not alter BZD binding, indicating that the observed changes in modulation result from changes in BZD efficacy. Flurazepam and zolpidem significantly slowed covalent modification of γ2R197C, whereas DMCM, GABA, and the allosteric modulator pentobarbital had no effects, demonstrating that γ2Loop F is a specific transducer of positive BZD modulator binding. Therefore, γ2Loop F plays a key role in defining BZD efficacy and is part of the allosteric pathway allowing positive BZD modulator-induced structural changes at the BZD binding site to propagate through the protein to the channel domain.
Learning features on robotic surgical tools

Computer-aided surgical interventions in both manual and robotic procedures have been shown to improve patient outcomes and enhance the skills of the human physician. Tool tracking is one such example that has various applications. In this paper, we show how to learn fine-scaled features on surgical tools for the purpose of pose estimation. Our experiments analyze different state-of-the-art feature descriptors coupled with various learning algorithms on in-vivo data from a surgical robot. We propose that it is important to be able to detect naturally-occurring features robustly in order to achieve long-term, marker-less tool tracking. We also contribute a new improvement on feature classification based on Randomized Trees.
Using microbial desalination cells to reduce water salinity prior to reverse osmosis

A microbial desalination cell (MDC) is a new method to reduce the salinity of one solution while generating electrical power from organic matter and bacteria in another (anode) solution. Substantial reductions in the salinity can require much larger volumes of the anode solution than the saline water, but any reduction of salinity will benefit the energy efficiency of a downstream reverse osmosis (RO) desalination system. We investigated here the use of an MDC as an RO pre-treatment method using a new type of air-cathode MDC containing three equally sized chambers. A single cycle of operation using a 1 g L−1 acetate solution reduced the conductivity of salt water (5 g L−1 NaCl) by 43 ± 6%, and produced a maximum power density of 480 mW m−2 with a coulombic efficiency of 68 ± 11%. A higher concentration of acetate (2 g L−1) reduced solution conductivity by 60 ± 7%, and a higher salt concentration (20 g L−1 NaCl) reduced solution conductivity by 50 ± 7%. The use of membranes with increased ion exchange capacities further decreased the solution conductivity by 63 ± 2% (20 g L−1 NaCl). These results demonstrate substantial (43–67%) desalination of water is possible using equal volumes of anode solution and salt water. These results show that MDC treatment could be used to substantially reduce salt concentrations and thus energy demands for downstream RO processing, while at the same time producing electrical power.
Combined analysis of probability of missed detection and positioning accuracy for receiver selection in SFN based passive radar systems

Multistatic passive radar systems provide higher positioning accuracy comparing with the bistatic ones. However, the positioning performance of the multistatic passive radar systems is largely dependent on the geometry. Especially, it is difficult to designate transmitters from the given ones in a single frequency network (SFN) based passive radar system. Therefore the receiver location is of crucial importance. In this paper, the influence of different receiver positions for the probability of missed detection and the target positioning accuracy are analyzed. Then a performance function for selecting the optimal receiver is proposed. Finally, a simulation with three transmitters and one receiver is presented.
The X-Ray Binary GRS 1741.9–2853 in Outburst and Quiescence

We report Chandra and XMM-Newton observations of the transient neutron star low-mass X-ray binary GRS 1741.9-2853. Chandra detected the source in outburst on 2000 October 26 at an X-ray luminosity of ~1036 ergs s-1 (2-8 keV; 8 kpc), and in quiescence on 2001 July 18 at ~1032 ergs s-1. The latter observation is the first detection of GRS 1741.9-2853 in quiescence. We obtain an accurate position for the source of 17h45m2. ˢ33, -28°54'49. ″7 (J2000), with an uncertainty of 0. ″7. GRS 1741.9-2853 was not detected significantly in three other Chandra observations, nor in three XMM-Newton observations, indicating that the luminosity of the source in quiescence varies by at least a factor of 5 from (<0.9-5.0) × 1032 ergs s-1 (2-8 keV). A weak X-ray burst with a peak luminosity of 5 × 1036 ergs s-1 above the persistent level was observed with Chandra during the outburst on 2000 October 26. The energy of this burst, 1038 ergs, is unexpectedly low and may suggest that the accreted material is confined to the polar caps of the neutron star. A search of the literature reveals that GRS 1741.9-2853 was observed in outburst with ASCA in the fall of 1996 as well, when the BeppoSAX WFC detected the three previous X-ray bursts from this source. The lack of X-ray bursts from GRS 1741.9-2853 at other epochs suggests that it produces bursts only during transient outbursts when the accretion rate onto the surface of the neutron star is about 10-10 M☉ yr-1. A similar situation may hold for other low-luminosity bursters recently identified from WFC data.
Phosphorus decrease and climate variability : mediators of synchrony in phytoplankton changes among European peri-alpine lakes

SUMMARY 1. In an attempt to discern long-term regional patterns in phytoplankton community composition we analysed data from five deep peri-alpine lake basins that have been included in long-term monitoring programmes since the beginning of the 1970s. Local management measures have led to synchronous declines in phosphorus concentrations by more than 50% in all four lakes. Their trophic state now ranges from mesotrophic to oligotrophic. 2. No coherence in phytoplankton biomass was observed among lakes, or any significant decrease in response to phosphorus (P)-reduction (oligotrophication), except in Lakes Constance and Walen. 3. Multivariate analyses identified long-term changes in phytoplankton composition, which occurred coherently in all lakes despite the differing absolute phosphorus concentrations. 4. In all lakes, the phytoplankton species benefiting from oligotrophication included mixotrophic species and/or species indicative of oligo-mesotrophic conditions. 5. A major change in community composition occurred in all lakes at the end of the 1980s. During this period there was also a major shift in climatic conditions during winter and early spring, suggesting an impact of climatic factors. 6. Our results provide evidence that synchronous long-term changes in geographically separated phytoplankton communities may occur even when overall biomass changes are not synchronous.
Fragmented aperture imaging for motion and defocus deblurring

In this paper we present a space-varying deblurring algorithm from a single defocused and motion-blurred image obtained with a fragmented aperture. We show that, for the same overall incoming light, a fragmented aperture leads to better motion and defocus deblurring than a (compact) conventional circular aperture. We demonstrate that not only fragmented apertures preserve more spectrum of an image of the scene than traditional circular apertures, but they also allow a better identification of blur scale. Our algorithm estimates both motion blur magnitude and direction as well as defocus blur scale at each pixel. The estimation of the blur parameters is addressed by using local projections on subspaces and L1 regularization, while deblurring is posed as a variational minimization problem and solved via linearization of the Euler-Lagrange equations. The technique produces convincing results on real scenario.
Interaction control of a programmable footpad-type gait rehabilitation robot for active walking on various terrains

This paper discusses interaction control of a programmable footpad-type gait rehabilitation robot which allows walking velocity updates on various terrains for patients' active walking. In human, there exists a neuronal coordination of arm and leg. When humans walk, both the upper and lower limb are moving together synchronized at one to one frequency. Additionally it has been known that providing arm swing could be beneficial during locomotor training. Thus, the suggested rehabilitation robot is composed of an upper limb device, a sliding device, two footpad devices, and a partial body support system. The footpad device on the slide device can generate various trajectories such as planar, stairs and slope walking. The upper-limb device allows users to swing their arms naturally through the use of a simple pendulum link with a passive prismatic joint. The upper and lower limbs of the robot are connected by a synchronized gait pattern. By analyzing the interaction torque between the upper limb of the human and the robot, the walking velocity on various terrains can be updated. Experimental results with a healthy subject show that the user can update the walking velocity on level ground, slopes, and stairs through upper and lower limb connections. Hence, the training might give more effective result since the robot allows the patient to walk according to his intentions on various terrains.
Feed additives for swine: Fact sheets – prebiotics and probiotics, and phytogenics

This is the last in a series of fipeer-reviewed Practice tip articles, each including two or three fact sheets. Previous practice tips included fact sheets on acidifi ers and antibiotics in the September-October issue ( J Swine Health Prod. 2009;17:270–275); on carcass modifi ers, carbohydrate-degrading enzymes, and proteases, and anthelmintics in the November-December issue (J Swine Health Prod. 2009;17:325–332); on fland mold inhibitors, mycotoxin binders, and antioxidants in the January-February issue (J Swine Health Prod. 2010;18:27–32); and on high dietary levels of copper and zinc for growing pigs and phytase in the March-April issue (J Swine Health Prod. 2010;18:87-91).
ROBUS 2011 Proceedings of Workshop on Robust Unsupervised and Semisupervised Methods in Natural Language Processing (at RANLP 2011)

This paper presents a work in progress on the task of unsupervised parsing, following the main stream approach of optimizing the overall probability of the corpus. We evaluate a sequence of experiments for Czech with various modifications of corpus initiation, of dependency edge probability model and of sampling procedure, stressing especially the treeness constraint. The best configuration is then applied to 19 languages from CoNLL-2006 and CoNLL-2007 shared tasks. Our best achieved results are comparable to the state of the art in dependency parsing and outperform the previously published results for many languages.
Performance enhancement of flow control in 10GbE WANs

This paper presents a new method of improving the flow control mechanism in 10 Gigabit Ethernet (10GbE) WANs. The ON/OFF control method prescribed by the standard leads to fluctuations of flow rates and the queue levels of the switches. Apart from the ON/OFF control, there are a few recent flow control mechanisms developed for the 10GbE networks in the literature. However, they do not comply with the present 10GbE standard as they require other quantities such as queue level to be included in the control frame. Our approach converts the fair share calculated by the switch to an equivalent pause time. As a result, our algorithm complies with the standard. Performance of this scheme has been studied via simulations and compared with the performance of the ON/OFF control method.
Metasearch information fusion using linear programming

For a specific query merging the returned results from multiple search engines, in the form of a metasearch aggregation, can provide significant improvement in the quality of relevant documents. This paper suggests a minimax linear programming (LP) formulation for fusion of multiple search engines results. The paper proposes a weighting method to include the importance weights of the underlying search engines. This is a two-phase approach which in the first phase a new method for computing the importance weights of the search engines is introduced and in the second stage a minimax LP model for finding relevant search engines results is formulated. To evaluate the retrieval effectiveness of the suggested method, the 50 queries of the 2002 TREC Web track were utilized and submitted to three popular Web search engines called Ask, Bing and Google. The returned results were aggregated using two exiting approaches, three high-performance commercial Web metasearch engines and our proposed technique. The efficiency of the generated lists was measured using TREC-Style Average Precision (TSAP). The new findings demonstrate that the suggested model improved the quality of merging considerably
Multiple Sclerosis Affects Skeletal Muscle Characteristics

Background The impact of multiple sclerosis (MS) on skeletal muscle characteristics, such as muscle fiber cross sectional area (CSA), fiber type proportion, muscle strength and whole muscle mass, remains conflicting. Methods In this cross sectional study, body composition and muscle strength of the quadriceps were assessed in 34 MS (EDSS: 2.5±0.19) patients and 18 matched healthy controls (HC). Hereafter a muscle biopsy (m.vastus lateralis) was taken. Results Compared to HC, mean muscle fiber CSA of all fibers, as well as CSA of type I, II and IIa fibers were smaller and muscle strength of the quadriceps was lower in MS patients. Whole body composition was comparable between groups. However, compared to HC, the biopsied leg tended to have a higher fat percentage (p = 0.1) and a lower lean mass (p = 0.06) in MS patients. Conclusion MS seems to negatively influence skeletal muscle fiber CSA, muscle strength and muscle mass of the lower limbs of mildly affected MS patients. This emphasises the need for rehabilitation programs focusing on muscle preservation of the lower limb. Trial Registration ClinicalTrials.gov NCT01845896
Mathematical Model of Cancer Treatments Using Immunotherapy, Chemotherapy and Biochemotherapy

In this paper, mathematical model of cancer treatments have been presented and analyzed using coupled ordinary differential equations (ODEs). This model describes cancer growth on a cell population level with combination immunotherapy and chemotherapy treatments are often called biochemotherapy. This model also describes the effect of tumor infiltrating lymphocytes (TIL), interleukin-2 (IL-2) and interferon alpha (INF-α) on dynamics of tumor cells under the influence of immunotherapy, chemotherapy and biochemotherapy. Through this mathematical model, numerical simulations of immunotherapy, chemotherapy and biochemotherapy for some cases such as variation of tumor size and variation of parameter among patient 9 and patient 10 were presented. Our result shown that for parameter set patient 9 and patient 10, the biochemotherapy more effective than the immunotherapy and chemotherapy.