Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximum power transfer tracking for a photovoltaic-supercapacitor energy system

It is important to maintain high efficiency when charging electrical energy storage elements so as to achieve holistic optimization from an energy generation source (e.g., a solar cell array) to an energy storage element (e.g., a supercapacitor bank). Previous maximum power point tracking (MPPT) methods do not consider the fact that efficiency of the charger varies depending on the power output level of the energy generation source and the state of charge of the storage element. This paper is the first paper to optimize the efficiency of a supercapacitor charging process by utilizing the MPPT technique and simultaneously considering the variable charger efficiency. More precisely, previous MPPT methods only maximize the power output of the energy generation source, but they do not guarantee the maximum energy is stored in the energy storage element. Note that the load device takes its energy from the storage element so it is important to maximize energy transfer from the source into the storage element. We present a rigorous framework to determine the optimal capacitance of a supercapacitor and optimal configuration of a solar cell array so as to maximize the efficiency of energy transfer from the solar cells into a bank of supercapacitors. Experimental results show the efficacy of the proposed technique and design optimization framework.
A Direct Phenotypic Comparison of siRNA Pools and Multiple Individual Duplexes in a Functional Assay

Background RNAi is a prominent tool for the identification of novel regulatory elements within complex cellular pathways. In invertebrates, RNAi is a relatively straightforward process, where large double-stranded RNA molecules initiate sequence-specific transcript destruction in target cells. In contrast, RNAi in mammalian cell culture assays requires the delivery of short interfering RNA duplexes to target cells. Due to concerns over off-target phenotypes and extreme variability in duplex efficiency, investigators typically deliver and analyze multiple duplexes per target. Currently, duplexes are delivered and analyzed either individually or as a pool of several independent duplexes. A choice between experiments based on siRNA pools or multiple individual duplexes has considerable implications for throughput, reagent requirements and data analysis in genome-wide surveys, yet there are relatively few data that directly compare the efficiency of the two approaches. Methodology/Principal Findings To address this critical issue, we conducted a direct comparison of siRNA pools and multiple single siRNAs that target all human phosphatases in a robust functional assay. We determined the frequency with which both approaches uncover loss-of-function phenotypes and compared the phenotypic severity for siRNA pools and the constituent individual duplexes. Conclusions/Significance Our survey indicates that screens with siRNA pools have several significant advantages over identical screens with the corresponding individual siRNA duplexes. Of note, we frequently observed greater phenotypic penetrance for siRNA pools than for the parental individual duplexes. Thus, our data indicate that experiments with siRNA pools have a greater likelihood of generating loss-of-function phenotypes than individual siRNA duplexes.
HUMAN HEALTH RISK OF HEAVY METALS THROUGH FISH AND SHELLFISH INGESTION: A CASE STUDY FOR THE ARABIAN GULF

ABSTRACT Human exposure to heavy metals through ingestion of fish and shellfish from the Arabian Gulf was predicted. Risks associated with such exposures were assessed. Concentrations of ten heavy metals: cadmium (Cd), arsenic (As), chromium (Cr), copper (Cu), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), vanadium (V) and zinc (Zn) were characterized for 35 marine fish and shellfish species from the Arabian Gulf region for the period of 1988-2010. Ingestion patterns of seafood were developed. Cancer risks were estimated from arsenic (As) exposure through the oral route, while other metals were not reported to be human carcinogen through oral route. Hazard indices from these metals through fish ingestion were predicted. Chronic daily intakes (CDI) of these metals were estimated to be in the range of 1.55×10 -06 – 5.72×10 -04 mg/kg/day. This study estimated cancer risks in the range of 6.7×10 -11 – 1.1×10 -04 with an average of 2.1×10 -06 . Cumulative hazard index was estimated to be 0.159 (range: 0.01–1.59). Approximately 0.18% of the exposed populations had higher hazard index than the U.S. Environmental Protection Agency regulatory limit of unity. The probability of one cancer incident in 1 million populations from lifetime exposure to arsenic through fish ingestion was predicted to be 0.49. Presence of other metals and inorganic/organic chemicals and complexes in fish and shellfish may impose additional risks to human. Through comprehensive understanding of cumulative exposures and risks from all contaminants, appropriate measures can be adopted to better protect human health in the Arabian Gulf region.
Universal Semi-local Election Protocol Using Forward Links

We consider finite connected undirected graphs as a model for anonymous computer networks. In this framework we show a general purpose distributed election protocol, which uses forward links over the standard communication channels between processors. The forward links are represented in the form of structured labels, so the algorithm is in fact a graph relabelling system. However, its transformations are not local in the classical sense. For this particular algorithm we define a new notion of semi-locality. We claim that semi-local computations are as powerful as global ones, while still conforming to the intuitive meaning of the locality term.
Reduced Affinity for Isoniazid in the S315T Mutant ofMycobacterium tuberculosis KatG Is a Key Factor in Antibiotic Resistance*

Catalase-peroxidase (KatG) fromMycobacterium tuberculosis is responsible for the activation of the antitubercular drug isonicotinic acid hydrazide (INH) and is important for survival of M. tuberculosis in macrophages. Characterization of the structure and catalytic mechanism of KatG is being pursued to provide insights into drug (INH) resistance in M. tuberculosis. Site-directed mutagenesis was used to prepare the INH-resistant mutant KatG[S315T], and the overexpressed enzyme was characterized and compared with wild-type KatG. KatG[S315T] exhibits a reduced tendency to form six-coordinate heme, because of coordination of water to iron during purification and storage, and also forms a highly unstable Compound III (oxyferrous enzyme). Catalase activity and peroxidase activity measured usingt-butylhydroperoxide and o-dianisidine were moderately reduced in the mutant compared with wild-type KatG. Stopped-flow spectrophotometric experiments revealed a rate of Compound I formation similar to wild-type KatG using peroxyacetic acid to initiate the catalytic cycle, but no Compound I was detected when bulkier peroxides (chloroperoxybenzoic acid,t-butylhydroperoxide) were used. The affinity of resting (ferric) KatG[S315T] for INH, measured using isothermal titration calorimetry, was greatly reduced compared with wild-type KatG, as were rates of reaction of Compound I with the drug. These observations reveal that although KatG[S315T] maintains reasonably good steady state catalytic rates, poor binding of the drug to the enzyme limits drug activation and brings about INH resistance.
Comparing the Efficacy of Two Internet-Based, Computer-Tailored Smoking Cessation Programs: A Randomized Trial

Background Online computer-tailored smoking cessation programs have not yet been compared directly. Objective To compare the efficacy of two Internet-based, computer-tailored smoking cessation programs. Methods Randomized controlled trial conducted in 2003-2004. Visitors to a smoking cessation website were randomly assigned to either an original online, interactive smoking cessation program or to a modified program. Both programs consisted of tailored, personalized counseling letters based on participants' characteristics, followed by monthly email reminders. The original program was based on psychological and addiction theory, and on preliminary research conducted in the same population. The modified program was shorter and contained more information on nicotine replacement therapy and nicotine dependence, and less information on health risks and coping strategies. In both programs, 1 month and 2 months after entering the study, participants were invited by email to answer the same tailoring questionnaire again in order to receive a second counseling letter. Participants in both programs obtained, on average, 1.2 feedback counseling letters over 2.5 months, and 84% received only 1 feedback letter. The outcome was self-reported smoking abstinence (no puff of tobacco in the previous 7 days), assessed 2.5 months after entry in the program. We report results from intention-to-treat (ITT) analyses, where all non-respondents at follow-up were counted as smokers. Results The baseline questionnaire was answered by a total of 11969 current (74%) and former (26%) smokers, and the follow-up survey by 4237 people (35%). In an ITT analysis, abstinence rates in baseline current smokers were respectively 10.9% and 8.9% (odds ratio [OR]=1.24, 95% confidence interval [CI]1.08-1.43, P=.003) in the original and modified programs, and 25.2% and 15.7% (OR=1.81, CI 1.51-2.16, P<.001) in baseline former smokers. While we found statistically significant differences in quit rates in smokers in the contemplation stage favoring the original program (OR=1.54, CI 1.18-2.02, P=.002), no between-group differences in quit rates were observed in smokers in the precontemplation (OR=1.07, CI 0.36-3.14, P=.91) and preparation (OR=1.15, CI 0.97-1.37, P=.10) stages of change. Conclusions In smokers in the contemplation stage of change and in former smokers, the original program produced higher smoking abstinence rates than the modified program.
Inclusion of genetic relationship information in the pedigree selection method using mixed models

We used a mixed model approach and computer simulation to evaluate the inclusion of parentage information as determined by the genealogy established in the pedigree method. The simulations were based on a purely additive genetic model for one quantitative trait of 20 unlinked segregating loci with equal effects and an allelic frequency of 0.5 for heritability values of 10%, 25%, 50% and 75% for selection based on an F4:5 progeny mean. We simulated 1000 experiments for each heritability value, corresponding to the evaluation of 256 F4:5 progenies. The phenotypic values of the progenies were analyzed according to two models, one ignoring and one considering the additive genetic parentage among the progenies. The additive relationship coefficients among F4:5 progenies ranged from 0.0 to 1.75. The evaluated selection procedures were the phenotypic progeny mean (M) and the best linear unbiased predictor including parentage (BLUPA). The inclusion of parentage among progenies using the BLUPA procedure resulted in higher selection gains than when the relationship information was ignored, which possibly recompenses the additional work invested to obtain these records, above all in the case of low - heritability traits.
PIRATTE: Proxy-based Immediate Revocation of ATTribute-based Encryption

Access control to data in traditional enterprises is typically enforced through reference monitors. However, as more and more enterprise data is outsourced, trusting third party storage servers is getting challenging. As a result, cryptography, specifically Attribute-based encryption (ABE) is getting popular for its expressiveness. The challenge of ABE is revocation. To address this challenge, we propose PIRATTE, an architecture that supports fine-grained access control policies and dynamic group membership. PIRATTE is built using attribute-based encryption; a key and novel feature of our architecture, however, is that it is possible to remove access from a user without issuing new keys to other users or re-encrypting existing ciphertexts. We achieve this by introducing a proxy that participates in the decryption process and enforces revocation constraints. The proxy is minimally trusted and cannot decrypt ciphertexts or provide access to previously revoked users. We describe the PIRATTE construction and provide a security analysis along with performance evaluation.We also describe an architecture for online social network that can use PIRATTE, and prototype application of PIRATTE on Facebook.
Semi-Supervised Linear Discriminant Clustering

This paper devises a semi-supervised learning method called semi-supervised linear discriminant clustering (Semi-LDC). The proposed algorithm considers clustering and dimensionality reduction simultaneously by connecting K-means and linear discriminant analysis (LDA). The goal is to find a feature space where the K-means can perform well in the new space. To exploit the information brought by unlabeled examples, this paper proposes to use soft labels to denote the labels of unlabeled examples. The Semi-LDC uses the proposed algorithm, called constrained-PLSA, to estimate the soft labels of unlabeled examples. We use soft LDA with hard labels of labeled examples and soft labels of unlabeled examples to find a projection matrix. The clustering is then performed in the new feature space. We conduct experiments on three data sets. The experimental results indicate that the proposed method can generally outperform other semi-supervised methods. We further discuss and analyze the influence of soft labels on classification performance by conducting experiments with different percentages of labeled examples. The finding shows that using soft labels can improve performance particularly when the number of available labeled examples is insufficient to train a robust and accurate model. Additionally, the proposed method can be viewed as a framework, since different soft label estimation methods can be used in the proposed method according to application requirements.
Role of perturbing ocean initial condition in simulated regional sea level change

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensembles with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. Thus, in order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are necessary.
The GDP-bound form of Arf6 is located at the plasma membrane

The function of Arf6 has been investigated largely by using the T27N and the Q67L mutants, which are thought to be blocked in GDP- and GTP-bound states, respectively. However, these mutants have been poorly characterized biochemically. Here, we found that Arf6(T27N) is not an appropriate marker of the inactive GDP-bound form because it has a high tendency to lose its nucleotide in vitro and to denature. As a consequence, most of the protein is aggregated in vivo and localizes to detergent-insoluble structures. However, a small proportion of Arf6(T27N) is able to form a stable complex with its exchange factor EFA6 at the plasma membrane, accounting for its dominant-negative phenotype. To define the cellular localization of Arf6-GDP, we designed a new mutant, Arf6(T44N). In vitro, this mutant has a 30-fold decreased affinity for GTP. In vivo, it is mostly GDP bound and, in contrast to the wild type, does not switch to the active conformation when expressed with EFA6. This GDP-locked mutant is found at the plasma membrane, where it localizes with EFA6 and Ezrin in actin- and phosphatidylinositol (4,5)-bisphosphate-enriched domains. From these results, we conclude that the Arf6 GDP-GTP cycle takes place at the plasma membrane.
Essential Thrombocythemia.

Abnormal blood clotting (thrombosis) is common in people with essential thrombocythemia and causes many signs and symptoms of this condition. Clots that block blood flow to the brain can cause strokes or temporary stroke-like episodes known as transient ischemic attacks. Thrombosis in the legs can cause leg pain, swelling, or both. In addition, clots can travel to the lungs (pulmonary embolism), blocking blood flow in the lungs and causing chest pain and difficulty breathing (dyspnea).
A simple high-performance matrix-free biomass molten carbonate fuel cell without CO2 recirculation

A matrix-free molten carbonate fuel cell without CO2 recirculation for efficient power generation from carbon-containing fuels. In previous reports, flowing CO2 at the cathode is essential for either conventional molten carbonate fuel cells (MCFCs) based on molten carbonate/LiAlO2 electrolytes or matrix-free MCFCs. For the first time, we demonstrate a high-performance matrix-free MCFC without CO2 recirculation. At 800°C, power densities of 430 and 410 mW/cm2 are achieved when biomass—bamboo charcoal and wood, respectively–is used as fuel. At 600°C, a stable performance is observed during the measured 90 hours after the initial degradation. In this MCFC, CO2 is produced at the anode when carbon-containing fuels are used. The produced CO2 then dissolves and diffuses to the cathode to react with oxygen in open air, forming the required CO32− or CO42− ions for continuous operation. The dissolved O2− ions may also take part in the cell reactions. This provides a simple new fuel cell technology to directly convert carbon-containing fuels such as carbon and biomass into electricity with high efficiency.
Improved SMC implementation of the PHD filter

The paper makes two contributions. First, a new formulation of the PHD filter which distinguishes between persistent and newborn objects is presented. This formulation results in an efficient sequential Monte Carlo (SMC) implementation of the PHD filter, where the placement of newborn object particles is determined by the measurements. The second contribution is a novel method for the state and error estimation from an SMC implementation of the PHD filter. Instead of clustering the particles in an ad-hoc manner after the update step (which is the current approach), we perform state estimation and, if required, particle clustering, within the update step in an exact and principled manner. Numerical simulations indicate a significant improvement in the estimation accuracy of the proposed SMC-PHD filter.
CrowdFusion: A Crowdsourced Approach on Data Fusion Refinement

Data fusion has played an important role in data mining because high quality data is required in a lot of applications. As on-line data may be out-of-date and errors in the data may propagate with copying and referring between sources, it is hard to achieve satisfying results with merely applying existing data fusion methods to fuse Web data. In this paper, we make use of the crowd to achieve high quality data fusion result. We design a framework selecting a set of tasks to ask crowds in order to improve the confidence of data. Since data are correlated and crowds may provide incorrect answers, how to select a proper set of tasks to ask the crowd is a very challenging problem. In this paper, we design an approximation solution to address this challenge since we prove that the problem is at NP-hard. To further improve the efficiency, we design a pruning strategy and a preprocessing method, which effectively improve the performance of the proposed approximation solution. We verify the solutions with extensive experiments on a real crowdsourcing platform.
Providing Support for Safe Software Architecture Transformations

Software architecture is a key concept in the design of a complex system. An architecture models the structure and behavior of the system, including the software elements and the relationships between them. While architectures were originally specified informally, recent years have seen the creation of a number of Architecture Description Languages (ADLs) [4]. ADLs are designed around the dimensions of composition and interaction, allowing the architect to introduce new concerns by constructing and combining increasingly complex elements
Analysis of Relationship between limb length and joint load in quadruped walking on the slope

An animal has a characteristic ratio of forefoot and rear legs so that its morphology can adapt to the living environment. Likewise, the structure of robot should be better fitted the locomotion in the working environment. This paper derives an optimal structure of the quadruped robot, which minimizes the sum of joint torques of the robot. Minimization of the joint torque allows to reduce the joint acceleration in walking motion, and hence to reduce energy consumption. Numerical simulation analyzed joint torques in each limb length and slope angle under walking on a slope. The optimal rate of rear leg length (RRL) is derived by the simulation as the physical structure. Our analysis suggests that the joint torque will increase as the slope angle becomes steeper in the case that the rear legs are shorter than forelegs. On the other hand, the joint torque will decrease as the slope angle is declined in the case that the forelegs are shorter than the rear legs. Experimental results validated the simulation analysis.
Functional Annotations of Paralogs: A Blessing and a Curse

Gene duplication followed by mutation is a classic mechanism of neofunctionalization, producing gene families with functional diversity. In some cases, a single point mutation is sufficient to change the substrate specificity and/or the chemistry performed by an enzyme, making it difficult to accurately separate enzymes with identical functions from homologs with different functions. Because sequence similarity is often used as a basis for assigning functional annotations to genes, non-isofunctional gene families pose a great challenge for genome annotation pipelines. Here we describe how integrating evolutionary and functional information such as genome context, phylogeny, metabolic reconstruction and signature motifs may be required to correctly annotate multifunctional families. These integrative analyses can also lead to the discovery of novel gene functions, as hints from specific subgroups can guide the functional characterization of other members of the family. We demonstrate how careful manual curation processes using comparative genomics can disambiguate subgroups within large multifunctional families and discover their functions. We present the COG0720 protein family as a case study. We also discuss strategies to automate this process to improve the accuracy of genome functional annotation pipelines.