Miracle-dz/UniFAR-FTUs huggingface dataset:
Lack of Developmental Redundancy between Unc45 Proteins in Zebrafish Muscle Development

Since the majority of protein-coding genes in vertebrates have intra-genomic homologues, it has been difficult to eliminate the potential of functional redundancy from analyses of mutant phenotypes, whether produced by genetic lesion or transient knockdown. Further complicating these analyses, not all gene products have activities that can be assayed in vitro, where the efficiency of the various family members can be compared against constant substrates. Two vertebrate UNC-45 homologues, unc45a and unc45b, affect distinct stages of muscle differentiation when knocked down in cell culture and are functionally redundant in vitro. UNC-45 proteins are members of the UCS (UNC-45/CRO1/She4p) protein family that has been shown to regulate myosin-dependent functions from fungi to vertebrates through direct interaction with the myosin motor domain. To test whether the same functional relationship exists between these unc45 paralogs in vivo, we examined the developmental phenotypes of doubly homozygous unc45b−/−; unc45a−/− mutant zebrafish embryos. We focused specifically on the combined effects on morphology and gene expression resulting from the zygotic lack of both paralogs. We found that unc45b−/− and unc45b−/−; unc45a−/− embryos were phenotypically indistinguishable with both mutants displaying identical cardiac, skeletal muscle, and jaw defects. We also found no evidence to support a role for zygotic Unc45a function in myoblast differentiation. In contrast to previous in vitro work, this rules out a model of functional redundancy between Unc45a and Unc45b in vivo. Instead, our phylogenetic and phenotypic analyses provide evidence for the role of functional divergence in the evolution of the UCS protein family.
A Two-level Classifier for Discriminating Similar Languages

The BRUniBP team’s submission is presented for the Discriminating between Similar Languages Shared Task 2015. Our method is a two phase classiﬁer that utilizes both character and word-level features. The evaluation shows 100% accuracy on language group identiﬁcation and 93.66% accuracy on language identiﬁcation. The main contribution of the paper is a memory-efﬁcient correlation based feature selection method.
THE NON-THERMAL INTRACLUSTER MEDIUM

WMAP's detection of the Sunyaev–Zel'dovich effect at a much reduced level among several large samples of rich clusters is interpreted in terms of conventional physics. It has been suggested that the central soft X-ray and EUV excess found in some clusters cannot be of thermal origin, due to problems with rapid gas cooling and the persistent non-detection of the O vii line, but may arise from inverse Compton scattering between intracluster relativistic electrons and the cosmic microwave background (CMB). In fact, recent XMM-Newton observations of the soft X-rays from Coma and Abell 3112 are equally well fitted by a power law or a thermal virialized gas. Therefore, the missing Sunyaev–Zel'dovich flux could partly be due to an overestimate of the central density of virialized electrons which scatter the CMB. Synchrotron radiation in an intracluster magnetic field of strength of a few μG is responsible for significant additional electron energy loss. Equipartition between relativistic particle and magnetic field energy densities is a realistic possibility. GHz radiation data from a Coma cluster halo yields information on the high-energy steepening of the cluster relativistic electron spectrum. Cluster microwave emission in the WMAP passbands by higher energy cosmic-ray electrons and gamma-ray emission from an accompanying cosmic-ray proton flux are also considered. The energetic electrons could originate from active galactic nucleus jet injection, then distributed cluster wide by Alfvén wave sweeping, with accompanying in situ Fermi acceleration.
Spreading Code Assignment Strategies for MIMO-CDMA Systems Operating in Frequency-Selective Channels

Code Division Multiple Access (CDMA) and multiple input multiple output- (MIMO-) CDMA systems suffer from multiple access interference (MAI) which limits the spectral efficiency of these systems. By making these systems more power efficient, we can increase the overall spectral efficiency. This can be achieved through the use of improved modulation and coding techniques. Conventional MIMO-CDMA systems use fixed spreading code assignments. By strategically selecting the spreading codes as a function of the data to be transmitted, we can achieve coding gain and introduce additional degrees of freedom in the decision variables at the output of the matched filters. In this paper, we examine the bit error rate performance of parity bit-selected spreading and permutation spreading under different wireless channel conditions. A suboptimal detection technique based on maximum likelihood detection is proposed for these systems operating in frequency selective channels. Simulation results demonstrate that these code assignment techniques provide an improvement in performance in terms of bit error rate (BER) while providing increased spectral efficiency compared to the conventional system. Moreover, the proposed strategies are more robust to channel estimation errors as well as spatial correlation.
Stochastic scheduling of active support vector learning algorithms

Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple active learning algorithms like random learning and query learning have been proposed for the design of support vector machine (SVM) classifiers. In random learning, examples are chosen randomly, while in query learning examples closer to the current separating hyperplane are chosen at each learning step. However, it is observed that a better scheme would be to use random learning in the initial stages (more exploration) and query learning in the final stages (more exploitation) of learning. Here we present two novel active SV learning algorithms which use adaptive mixtures of random and query learning. One of the proposed algorithms is inspired by online decision problems, and involves a hard choice among the pure strategies at each step. The other extends this to soft choices using a mixture of instances recommended by the individual pure strategies. Both strategies handle the exploration-exploitation trade-off in an efficient manner. The efficacy of the algorithms is demonstrated by experiments on benchmark datasets.
Design of adaptive moving-target tracking control for vision-based mobile robot

This study constructs an adaptive moving-target tracking control (AMTC) scheme via a dynamic Petri recurrent-fuzzy-neural-network (DPRFNN) for a vision-based mobile robot with a tilt camera. First, a continuously adaptive mean shift (CAMS) algorithm is adopted for the moving-object detection, and a model-based conventional sliding-mode control (CSMC) strategy is introduced. Moreover, it further designs a model-free AMTC scheme with a DPRFNN for imitating the CSMC strategy for relaxing the control design dependent on detailed system information and alleviating chattering phenomena caused by the inappropriate selection of uncertainty bounds. In addition, a switching path-planning scheme plus the AMTC is designed without detailed environmental information, large memory size and heavy computation burden for the obstacle avoidance of a mobile robot. Furthermore, numerical simulations are given to verify the effectiveness of the proposed AMTC scheme under different target tracking, and its superiority is indiented in comparison with the CSMC System
Hepatotoxicity of alcohol‐induced polar retinol metabolites involves apoptosis via loss of mitochondrial membrane potential

Chronic alcohol consumption depletes hepatic vitamin A stores. However, vitamin A supplementation is hepatotoxic, which is further potentiated by concomitant alcohol consumption. It was suggested that polar retinol metabolites generated by alcohol‐inducible cytochrome P4502E1 aggravate liver damage. However, experimental evidence supporting this hypothesis is lacking. To elucidate the effects of polar retinol metabolites on cultured HepG2 cells and primary rat hepatocytes, polar retinol metabolites were extracted from liver tissues of rats fed either an alcoholic or isocaloric control Lieber‐DeCarli diet. Cell toxicity assays included morphology assessment, trypan blue exclusion test, and LDH/AST leakage. Staining for DAPI and acridine orange, FACS analysis, and Western blot for cleaved caspase‐9 and ‐3 were used to detect apoptosis. Polar retinol metabolites caused marked cytotoxicity in a concentration‐ and time‐dependent manner in both cell types reflected by morphological changes, a dramatic increase in trypan blue positive cells, and LDH/AST leakage. Toxicity was due to apoptosis, as demonstrated by a time‐dependent increase of sub‐G1 cellular events, a rapid loss of mitochondrial membrane potential, and a time‐dependent activation of caspase‐9 and ‐3. No toxicity was found with equivalent doses of the control extract from nonalcoholic rats. We demonstrate that polar retinol metabolites cause marked hepatocyte death through the induction of apoptosis.
Cancer in British vegetarians: updated analyses of 4998 incident cancers in a cohort of 32,491 meat eaters, 8612 fish eaters, 18,298 vegetarians, and 2246 vegans

Background: Vegetarian diets might affect the risk of cancer. Objective: The objective was to describe cancer incidence in vegetarians and nonvegetarians in a large sample in the United Kingdom. Design: This was a pooled analysis of 2 prospective studies including 61,647 British men and women comprising 32,491 meat eaters, 8612 fish eaters, and 20,544 vegetarians (including 2246 vegans). Cancer incidence was followed through nationwide cancer registries. Cancer risk by vegetarian status was estimated by using multivariate Cox proportional hazards models. Results: After an average follow-up of 14.9 y, there were 4998 incident cancers: 3275 in meat eaters (10.1%), 520 in fish eaters (6.0%), and 1203 in vegetarians (5.9%). There was significant heterogeneity between dietary groups in risks of the following cancers: stomach cancer [RRs (95% CIs) compared with meat eaters: 0.62 (0.27, 1.43) in fish eaters and 0.37 (0.19, 0.69) in vegetarians; P-heterogeneity = 0.006], colorectal cancer [RRs (95% CIs): 0.66 (0.48, 0.92) in fish eaters and 1.03 (0.84, 1.26) in vegetarians; P-heterogeneity = 0.033], cancers of the lymphatic and hematopoietic tissue [RRs (95% CIs): 0.96 (0.70, 1.32) in fish eaters and 0.64 (0.49, 0.84) in vegetarians; P-heterogeneity = 0.005], multiple myeloma [RRs (95% CIs): 0.77 (0.34, 1.76) in fish eaters and 0.23 (0.09, 0.59) in vegetarians; P-heterogeneity = 0.010], and all sites combined [RRs (95% CIs): 0.88 (0.80, 0.97) in fish eaters and 0.88 (0.82, 0.95) in vegetarians; P-heterogeneity = 0.0007]. Conclusion: In this British population, the risk of some cancers is lower in fish eaters and vegetarians than in meat eaters.
Multi Level Parallelism of Multiple Implicitly/Explicitly Restarted Arnoldi Methods for Post-petascale Computing

The iterative methods are widely used to solve eigen problems in scientific computation. We focus on multiple restarted Arnoldi methods (MRAM) [4] which manage iterative co-methods to accelerate their convergence. These methods are considered as good candidate for emerging large scale computational systems thanks to their asynchronous communication schema, their potential load balancing and their multi-level parallelism. Both coarse grain parallelism between co-methods and fine grain parallelism inside each co-method need to be flexibly mapped to large scale distributed memory systems like hierarchical supercomputer, the cloud or P2P platforms. In this paper, we investigate such possibility in MRAMs by developing and executing them with a development and execution environment called FP2C (Framework for Post-Petascale Computing) [11]. The FP2C is a user-friendly and hierarchical-system-oriented development and execution environment based on workflow and distributed parallel methodologies. Our first goal is to show the feasibility of the approach FP2C to realize complex applications such as MRAMs. The next objective of the paper is to point out the adaptability of MRAMs to new generation of supercomputers (Petascale and futur Exascale). In addition, we show by our experiments that, collaboration of multiple iterative methods based on coarse grain parallelism accelerates convergence, and co-working processors within each iterative method based on fine grain parallelism accelerates the time per iteration.
Partitioning Data on Features or Samples in Communication-Efficient Distributed Optimization?

In this paper we study the effect of the way that the data is partitioned in distributed optimization. The original DiSCO algorithm [Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss, Yuchen Zhang and Lin Xiao, 2015] partitions the input data based on samples. We describe how the original algorithm has to be modified to allow partitioning on features and show its efficiency both in theory and also in practice.
Current Density-Voltage and Capacitance-Voltage Characteristics of Pulsed Laser Deposited Nitrogen-Doped n-Carbon/p-Silicon Diode

The current density-voltage (J-V) and capacitance-voltage (C-V) characteristics of a p-n heterojunction device are studied. The device was fabricated by depositing nitrogen (N) doped carbon (C) thin film on/p-type silicon substrate by pulsed laser deposition (PLD) technique at room temperature. Camphor (C10H16O), a natural source, was used as the starting precursor for the carbon layer of the heterostructure. In order to dope the carbon thin films with different doping concentrations, gaseous N was incorporated in the PLD chamber with different partial pressure. Both the J-V and C-V characteristics reveal that the device behaves as a successful p-n junction device up to a certain nitrogen partial pressure (NPP) in the PLD chamber, and this is near about 30 mTorr. At higher NPP, the material properties of the grown carbon layer of the device change and the device performance deteriorates. The built-in potential of the device with varying NPP is also estimated and found them to agree well with the device characteristics.
School Culture and Ecology

The environmental degradation caused by the high volume of vehicles, industrial activity, population growth and conversion of green open space. It is therefore necessary for human-based efforts to reduce the degradation of the environment. One of them can be done through the growth of ecological intelligence. The most effective growth of ecological intelligence at the age of 12 to 18 years. It is an age where humans are in secondary school. The growth of ecological intelligence can be done through school culture with environmental content in it. This research uses survey method based on quantitative approach and correlational research design. The technique of determining the number of samples using stratified random sampling, obtained 36 schools and 260 students. Data were collected by observation techniques, interviews, questionnaires, literature studies and documentation studies. The results showed that school culture has correlation with environmental condition. Thus, the exemplary aspect of teachers, principals, and educators have efforts to preserve the environment on school culture. The habitualization of school residents in preserving the environment in the school culture should be a centralized standard rule.
Extending Value Reuse to Basic Blocks with Compiler Support

Speculative execution and instruction reuse are two important strategies that have been investigated for improving processor performance. Value prediction at the instruction level has been introduced to allow even more aggressive speculation and reuse than previous techniques. This study suggests that using compiler support to extend value reuse to a coarser granularity than a single instruction, such as a basic block, may have substantial performance benefits. We investigate the input and output values of basic blocks and find that these values can be quite regular and predictable. For the SPEC benchmark programs evaluated, 90 percent of the basic blocks have fewer than four register inputs, five live register outputs, four memory inputs, and two memory outputs. About 16 to 41 percent of all the basic blocks are simply repeating earlier calculations when the programs are compiled with the -O2 optimization level in the GCC compiler. Compiler optimizations, such as loop-unrolling and function inlining, affect the sizes of basic blocks, but have no significant or consistent impact on their value locality, nor the resulting performance. Based on these results, we evaluate the potential benefit of basic block reuse using a novel mechanism called the block history buffer. This mechanism records input and live output values of basic blocks to provide value reuse at the basic block level. Simulation results show that using a reasonably sized block history buffer to provide basic block reuse in a 4-way issue superscalar processor can improve execution time for the tested SPEC programs by 1 to 14 percent, with an overall average of 9 percent when using reasonable hardware assumptions.
Towards Natural Acoustic Interfaces for Automatic Speech Recognition

Aiming at ’natural’ hands-free acoustic human/machine int rfaces, the need for according distant-talking automatic sp eech recognition (ASR) systems increases and presents us with ma jor signal processing challenges at the acoustic front-end . Considering interactive TV as a challenging exemplary applica tion scenario, we investigate the structural problems presente d by noisy and reverberant multi-source environments with unpr edictable interference and acoustic echoes of loudspeaker s ignals, and discuss current acoustic signal processing techn iques to enhance the input to the actual ASR system. For illustrati on, the scenario of an EU-funded project on distant-talking int erfaces for interactive TV (DICIT) is considered as a challeng ing example.
TransOS: a transparent computing-based operating system for the cloud

Cloud computing has become a hot topic recently. Among these research issues, cloud operating systems have attracted extensive attention. However, to date, there is no answer to such issues as what a cloud operating system is and how to develop one. This paper proposes a cloud operating system, TransOS, from the viewpoint of transparent computing, in which all traditional operating system codes and applications are centrally stored on network servers, and an almost bare terminal dynamically schedules the necessary codes selected by users from the network server, and runs them mostly with the terminal’s local resources. The TransOS manages all the resources to provide integrated services for users, including traditional operating systems. This paper first introduces the concept of transparent computing as a background and presents TransOS and its main characteristics. It then gives a layered structure-based designation of TransOS and finally illustrates one example of its implementation.
Nanoenergetic Gas-Generators: principles and applications

Metastable Intermolecular Composites or so-called Nanoenergetic Materials have been widely touted for their potential to fulfill dreams in high density energetic materials and nanotechnology. They are likely to become the next-generation explosives, propellants and primes as they enable flexibility in energy density and power release through control of particle size, tunable stoichiometry and choice of fuel and oxidizer. Despite intense examination by scientists and engineers worldwide the temperature progress and velocity of the thermal front propagation on the nanostructured formulations, however, gas pressure evolution and rate of gas release are not well investigated and understood. This issue has seriously impeded realization of various potential emerging applications envisioned in rocket solid fuels and explosives, which require a high pressure discharge in a short period of time as well as in bio-defeat systems. This highlight describes principles and development of Nanoenergetic Gas-Generators (NGG) systems comprising high PV (pressure × volume) values and energy densities (up to 25.7 kJ cm−3) that may have several potential civil and military applications. Our recent study revealed that Al/Bi2O3 and Al/I2O5 nanocomposites can generate a transient pressure pulse more than three times larger than that during the explosion of traditional thermite reactive mixtures.
Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis

In many current dynamic global vegetation mod- els (DGVMs), including those incorporated into Earth sys- tem models (ESMs), terrestrial vegetation is represented by a small number of plant functional types (PFTs), each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmen- tal gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA), maximum carboxylation rate at 25 C (Vcmax25) and maxi- mum electron transport rate at 25 C (Jmax25)) to vary within PFTs via trait-climate relationships based on a large trait database. The R 2 of these relationships were up to 0.83 and 0.71 for Vcmax25 and Jmax25, respectively. For SLA, more variance remained unexplained, with a maximum R 2 adjusted of 0.40. Compared to the default simulation, allow- ing trait variation within PFTs resulted in gross primary pro- ductivity differences of up to 50 % in the tropics, in > 35 % different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, to- gether emphasize that incorporating climate-driven trait vari- ation, calibrated on observational data and based on ecolog- ical concepts, allows more variation in vegetation responses in DGVMs and as such is likely to enable more reliable pro- jections in unknown climates.