Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of synthetic speech using automatic speech recognition

The present paper presents a novel method of speech synthesis evaluation by a speech recognition system. For the experiment, 4 different speech synthesis technologies were used, including diphone concatenative, statistical parametric and two unitselection speech synthesisers. For the evaluation, the Polish speech recognition system was used. The results showed that the statistical parametric and unit-selection synthesisers produced speech which had the highest recognition accuracy. Speech synthesis based on the concatenation of diphones had the lowest recognition rate.
A tutorial on how (not) to over-interpret STRUCTURE/ADMIXTURE bar plots

Genetic clustering algorithms, implemented in popular programs such as STRUCTURE and ADMIXTURE, have been used extensively in the characterisation of individuals and populations based on genetic data. A successful example is the reconstruction of the genetic history of African Americans who are a product of recent admixture between highly differentiated populations. Histories can also be reconstructed using the same procedure for groups which do not have admixture in their recent history, where recent genetic drift is strong or that deviate in other ways from the underlying inference model. Unfortunately, such histories can be misleading. We have implemented an approach (badMIXTURE, available at github.com/danjlawson/badMIXTURE) to assess the goodness of fit of the model using the ancestry “palettes” estimated by CHROMOPAINTER and apply it to both simulated data and real case studies. Combining these complementary analyses with additional methods that are designed to test specific hypotheses allows a richer and more robust analysis of recent demographic history based on genetic data.
Optimal multicast routing in wireless ad hoc sensor networks

Multicasting in wireless ad hoc sensor networks, i.e. one terminal sends the same data to multiple receivers, is an active field of research. In this paper, the optimal energy-aware multicast routing was studied in ad hoc sensor networks. The optimal multicast routing problem was formulated as an integer linear programming. A revised particle swarm optimization (PSO) algorithm, multi-phase discrete PSO was applied to solve this NP-hard problem in a distributed computing manner. To deal with the constraints e.g. connectivity constraint and broadcast constraint, a problem-independent constraint handling technique was proposed by introducing symbiosis mechanism to PSO algorithm. The performance of the algorithm was studied with different kinds of networks. Experiment results show that the presented algorithms can effectively solve the multicast routing problem in a reasonable time, even for large scale networks with numerous receivers.
Noise assisted multivariate empirical mode decomposition applied to Doppler radar data

The operation of the noise-assisted multivariate empirical mode decomposition (NA-MEMD) algorithm, which represents a breakthrough in data-adaptive analysis, is illustrated for the time-frequency analysis of Doppler radar signals. The performance of the NA-MEMD is here compared to the continuous wavelet transform, for both synthetic and real-world data applications, showing the advantage of the noise-assisted concept in terms of sparse time-frequency localization. For the considered application, we show how the approach gives a clear and natural interpretation of Doppler radar phenomena and enables the accurate tracking of object speeds. (4 pages)
Deep Sequencing of Cell-Free Peripheral Blood DNA as a Reliable Method for Confirming the Diagnosis of Myelodysplastic Syndrome

Background: Demonstrating the presence of myelodysplastic syndrome (MDS)-specific molecular abnormalities can aid in diagnosis and patient management. We explored the potential of using peripheral blood (PB) cell-free DNA (cf-DNA) and next-generation sequencing (NGS). Materials and Methods: We performed NGS on a panel of 14 target genes using total nucleic acid extracted from the plasma of 16 patients, all of whom had confirmed diagnoses for early MDS with blasts <5%. PB cellular DNA from the same patients was sequenced using conventional Sanger sequencing and NGS. Results: Deep sequencing of the cf-DNA identified one or more mutated gene(s), confirming the diagnosis of MDS in all cases. Five samples (31%) showed abnormalities in cf-DNA by NGS that were not detected by Sanger sequencing on cellular PB DNA. NGS of PB cell DNA showed the same findings as those of cf-DNA in four of five patients, but failed to show a mutation in the RUNX1 gene that was detected in one patient's cf-DNA. Mutant allele frequenc.
Indole-acetic acid oxidase enzyme activity in three wheat cultivars under salt stress conditions at the early seedling stage

Indole-acetic acid enzyme activity in three wheat cultivars differing in their salt response was studied at the early seedling stage. It was found that the IAA oxidase enzyme activity gradually decreased with increasing EC levels in both the salt-sensitive cultivar IWP-72 and moderately salt-tolerant cultivar Sharbati sonora while in the tolerant cultivar HD-2160 the enzyme activity increased till 96 hours up to 12 EC while at 120 hours at all EC levels the activity decreased. The magnitude was, however, higher in the salt-sensitive cultivar. The IAA oxidase activity increased with advancement in seedling age but the degree of increase varied with the cultivars. Whereas in the tolerant and moderately tolerant cultivars a sharp increase was observed at 72 and 96 hours which later declined at 120 hours, on the other hand, in the sensitive cultivar it increased from 24 hours reaching a peak level at 120 hours. Also from the observations it is noticed that IAA oxidase enzyme activity was affected more in the salt-sensitive cultivar (IWP-72) as compared with the moderately salt-tolerant (Sharbati sonora) and the salt-tolerant cultivar (HD-2160).
On frequency hop synchronization in multipath Rayleigh fading

This paper is concerned with the effect of multipath fading on the performance of frequency hop (FH) time synchronization and the resultant bit-error rate (BER) performance. The expressions of the mean value and the variance of the estimated FH timing error and BER are derived for the case of multipath Rayleigh fading, which is characterized by a path-delay vector and a path-strength distribution vector. Somewhat surprisingly, our results show that in comparison with single-path fading, multipath fading does not degrade the mean and variance of the estimated timing error and BER performance, but rather improves them owing to multipath diversity. The significance of our results is to demonstrate quantitatively the robustness of FH in the presence of multipath fading as far as the establishment of hop timing is concerned. Furthermore, we identify the spectral estimator as a robust method for establishing FH timing.
Study of strategies used in on‐line searching

The paper reports a study of the behaviour of on‐line searchers in looking for the answers to set questions. The work was carried out with a view to learning more about the way actual searches are conducted, so that instructions to users can be given to optimize the generation of references. The study suggests that developments in user education would be made considerably easier by some rationalization among file producers and systems, especially in spelling, vocabulary, basic commands and indexing philosophy.
[Role of micro-organisms in adapting plants to environmental stress conditions].

Due to their sessile nature, plants have always been confronted to various abiotic and biotic stresses in their immediate environment. As a consequence, the survival of plants depended on their ability to adjust rapidly their physiology, development and growth to escape or mitigate the impacts of stress. All plants are known to perceive and respond to stress signals such as drought, heat, salinity, attacks by herbivores and pathogens. Some biochemical processes are common to all plant stress responses including the production of certain stress proteins and metabolites, as well as the modification of the reactive oxygen species (ROS) metabolism. Although there has been extensive research in the plant stress response field, it is not yet known which factors are responsible for conferring to some plant species the capacity to colonize extreme habitats. Although considerable progress has been made in our understanding of plant stress physiology, the contribution of the plant-associated microbial community in the soil, commonly called the rhizosphere, has only recently received enhanced attention. Recent studies showed that some plant species in natural habitats require microbial associations for stress tolerance and survival. Since plants have colonized land, they have evolved mechanisms to respond to changing environmental conditions and settle in extreme habitats. Although many plants lack the adaptive capability to adapt to stress conditions, the ability of a variety of plants to adapt to stress conditions appears to depend on the association with microbes, raising a number of questions: can all plants improve stress tolerance when associated with their appropriate microbial partners? Did we miss identifying the right partners for a given plant species or variety? What distinguishes the microbes and plants that are adapted to extreme environmental conditions from those living in temperate zones? Answers to these questions are likely to revolutionize plant biology and could lead to new methods for a sustainable agriculture.
Effective Skill Assessment Using Expectation Maximization in a Multi Network Temporal Bayesian Network

We propose a temporal multi network single skill model for effective assessment and prediction of student skills that is more accurate than multi skill conjunctive models while requiring only a fraction of the computational resources to run. Using the Expectation Maximization algorithm we define steps for effective learning of model parameters over 150,000 responses of real student data that reveal important skill knowledge and learning trends. This skill report is exhibited in the paper. Lastly we focus on how to harness the power of the learned parameters to accurately predict an end of year standardized state math test. Our results of prediction using the multiple single skill network model beat out previous best prediction errors using a single multi skilled model. We believe these results could encourage wider use of these machine learning techniques that can now be effectively run on standard computing machines such as PCs found in school computer labs.
Distributed estimation and control of multi-agent systems in uncertain environment

Due to the wide applications in wireless sensor networks, multi-robot cooperative control and satellite formation flying, etc., distributed control and estimation of multi-agent systems (MASs) are now a hot topic in the system control community. In practice, when carrying out distributed tasks, MASs are often subject to various uncertainties, which can make significant macro-influence to the whole systems via affecting each agents microscopic decisions. The interaction among uncertainties and distributed information pattern may bring essential difficulty to the design and analysis of MASs. This paper is aimed at seeking more robust and more effective distributed estimation and control protocols to achieve global estimation and control tasks under various uncertainties including stochastic noises, signal loses, quantization errors and unknown system structures, etc. Specifically, distributed estimation, distributed control and distributed adaptive control are investigated.
Multivalued SRAM cell using resonant tunneling diodes

A multivalued SRAM cell using a vertically integrated multipeak resonant tunneling diode (RTD) pair is described. Two RTDs in series can have 2N+1 stable states. With this concept, a five-stable-state memory cell has been implemented with two 2-peak RTDs. Several designs are presented for a high-speed static random access multivalued memory using the folding characteristics of RTDs. The different designs are described and studied by comparing their power consumption under different conditions of device parameters and switching speed. The authors show that the proposed memory cell using a pair of multipeak RTDs yields the best result from the standpoint of size, power dissipation, and speed among the RTD memory cells discussed. >
Direct and Surrogate-Based Optimization of Dual-Rotor Wind Turbines

Dual-rotor wind turbines (DRWT) may offer better energy efficiency over their singlerotor counterparts. The design and analysis of DRWT requires, among other, the use of computational fluid dynamics models. These models can be, depending on their formulation, computationally heavy. Numerous simulations are then required during the design process, and this may render the overall computational cost to be prohibitive. This paper investigates and compares several optimization techniques for the design of DRWTs. In particular, we solve the DRWT fluid flow using the Reynolds-Averaged Navier-Stokes equations with a two-equation turbulence model on an axisymmetric mesh, and consider three design approaches: the traditional parametric sweep where the design variables are varied and the responses examined, direct optimization with a derivative-free algorithm, and surrogate-based optimization (SBO) using data-driven surrogates. The approaches are applied to test cases involving two and three design variables. The results show that the same optimized designs are obtained with all the approaches. However, going from the two parameter case to the three parameter one, the effort of setting up, running, and analyzing the results increases significantly with the parametric sweep approach. The optimization techniques are much easier to use and deliver the results with lower computational cost, where the SBO algorithm outperforms the direct approach.
An analytical model for predicting the remaining battery capacity of lithium-ion batteries

Predicting the residual energy of the battery source that powers a portable electronic device is quite important in designing and employing an effective dynamic power management policy in the device. This paper presents a closed-form analytical model for predicting the remaining capacity of a lithium-ion battery. The proposed high-level model relies on online current and voltage measurements and, at the same time, correctly accounts for the temperature and cycle aging effects. The accuracy of the high-level model is validated by comparing our analytical model with the Dualfoil simulation results (under some simplifying assumptions), demonstrating 5% error between simulated and predicted data.
Rice Seed Germination Analysis

This research aimed to develop the computer software called “Rice Seed Germination Analysis (RiSGA)” which could predict rice seed image for rice germination by using an image processing technique. The RiSGA consisted of five main process modules: 1) image acquisition, 2) image pre-processing, 3) feature extraction, 4) quality control analysis and 5) quality results. Six variations of Thai rice seed species (CP111, RD41, Chiang Phattalung, Sang Yod Phattalung, Phitsanulok 2 and Chai Nat 1) were used for the experiment. The RiSGA extracted three main features: 1) color, 2) morphological and 3) texture feature. The RiSGA applied four well-known techniques: 1) Euclidean Distance (ED), 2) Rule Based System (RBS), 3) Fuzzy Logic (FL) and 4) Artificial Neural Network (ANN). The RiSGA precision of ED, RBS, FL, and ANN was 87.50%, 100%, 100%, and 100%, respectively. The average access time was 4.35 seconds per image, 5.29 seconds per image, 7.04 seconds per image, and 159.65 seconds per image, respectively.
Electrophysiological evaluation of central and peripheral neural effects of lead exposure.

: Lead encephalopathy is more usual in children and has rarely been observed in adults. Peripheral neuropathy on the other hand is of more common occurrence among adults with occupational lead exposure, and has been extensively studied with electrophysiological methods. Although encephalopathy often manifests itself with generalized seizures, usual electroencephalographic (EEG) findings have been diffuse slow wave abnormalities. Paroxysmal abnormalities either focal or generalized spikes and/or sharp waves have been detected in some patients. Evoked potential studies have lately been applied to children or adults with a relatively low level of lead exposure, and minor dose-dependent differences have appeared in comparison to control groups. Subclinical signs of peripheral neuropathy have been detected among human subjects with various levels of lead exposure. Nerve conduction velocities of lead workers have been generally lower, although the means have been within normal limits. Some authors have shown clear correlations between measures of lead exposure and nerve conduction velocities indicating an exposure--effect relationship.
Effect of baculovirus P35 protein on apoptosis in brain tissue of rats with acute cerebral infarction.

: We explored the effect of baculovirus P35 protein on apoptosis in the brain tissue of rats with acute cerebral infarction (ACI). A rat model of middle cerebral artery infarction was created. The rats were randomly divided into sham, model, and treatment groups. Baculovirus P35 protein was injected into the intracranial arteries of the treatment group rats. The rats in the model group were given an equal volume of phosphate-buffered saline. The rats were sacrificed after 72 h and the brain tissue was separated. The levels of caspase-3, Bcl-2, and Bax mRNA, the brain cell apoptosis index, and the infarct size were determined. After 72 h, the levels of caspase-3 and Bax mRNA in the model and treatment groups were significantly greater than in the sham group, and the levels of Bcl-2 mRNA were significantly smaller (P < 0.05). The levels of caspase-3 and Bax mRNA were significantly lower in the treatment group than in the model group, and the level of Bcl-2 mRNA was significantly greater (P < 0.05). Compared with the sham group, the brain tissue apoptosis index and the cerebral infarction area increased significantly in the model and treatment groups (P < 0.05). The brain tissue apoptosis index and cerebral infarction area in the treatment group were significantly lower than in the model group (P < 0.05). Baculovirus P35 protein can effectively inhibit brain cell apoptosis in rats with ACI. It delayed apoptosis and necrosis in subjects with ACI tissue and had a protective effect on brain tissue.
Portfolio Selection of Interdependent R&D Projects

Worldwide competition of markets has forced organizations to invest in targeted R&D projects so that resources can be focussed on successful outcomes. A number of alternatives are encountered to select the most appropriate projects in R&D project selection model. In order to maintain technical/risk/resource/benefit competitiveness, the decision-maker assigns limited amount of assets to a set of competing projects. Interdependencies between applicant projects have great impact on the project outcome. But very little effects are noticed to involve them while modelling the problem. In this paper, we have considered outcome, technical, resource and risk interdependencies to develop a bi-objective non-linear R&D project portfolio selection model under the constraints on resources, budget, interdependencies and outcome, and discuss how our methodology can be used to make decision support tools for optimal R&D project selection in a corporate environment. The objectives are minimization of risk and maximization of benefit. Suitable numerical results are provided to illustrate our method. The solution is done by using fuzzy additive goal programming technique.
A secure data outsourcing scheme based on Asmuth–Bloom secret sharing

ABSTRACT Data outsourcing is an emerging paradigm for data management in which a database is provided as a service by third-party service providers. One of the major benefits of offering database as a service is to provide organisations, which are unable to purchase expensive hardware and software to host their databases, with efficient data storage accessible online at a cheap rate. Despite that, several issues of data confidentiality, integrity, availability and efficient indexing of users’ queries at the server side have to be addressed in the data outsourcing paradigm. Service providers have to guarantee that their clients’ data are secured against internal (insider) and external attacks. This paper briefly analyses the existing indexing schemes in data outsourcing and highlights their advantages and disadvantages. Then, this paper proposes a secure data outsourcing scheme based on Asmuth–Bloom secret sharing which tries to address the issues in data outsourcing such as data confidentiality, availability and order preservation for efficient indexing.
Digital Signal Processing Techniques: Calculating Biological Functionalities

Calculating Biological functionalities of proteins and presenting them numerically is an approach that will benefit the designing of drugs and vaccines. For example, potency of vaccines is known to be measured in terms of specificity, which is determined by bio-recognition (affinity), and sensitivity. Calculating the bio-recognition of peptides employed in the design of vaccines by means of procedures like the Digital Signal Processing (DSP) techniques rather than clinical experimentations not only gives room for the manipulation of the amino acids sequences of the peptides but also helps determine the degree of specificity of the antibody generated, hence the potency of the vaccine produced. This also provides opportunity for optimatization of the peptides for the desired biological characteristics. Also comparing the potency of peptide-based drugs through calculation of their biological functions is a faster, easier and resource-saving approach to pharmacotherapeutic investigations. In this study, two DSP techniques are fully explained and demonstrated. They are Resonant Recognition Model and Informational Spectrum Method. They are employed in the calculation of some physiological characteristics of Plasmodial peptides (P18 and P32), which are still being study for possible use as materials for the designing of anti-Malaria vaccines. Furthermore, the approaches are utilised to assess the pharmacological activities of two Fusion inhibitors (Enfuvirtide and Sifuvirtide). Enfuvirtide is currently in use for the management of anti-HIV/AIDS while Sifuvirtide is still being studied. Our calculated results demonstrate strong correlation with the preliminary clinical findings. They also seem to suggest that presenting biological characteristics in numerical terms is an easier and more rational approach to designing drugs and vaccines as it save resources and time unlike clinical experimentations. The methods also appear to help simplify the manoeuvring of the protein residues, which are employed in the designing and development of drugs and vaccines in order to obtain maximal biological characteristics.
Role of T Follicular Helper (Tfh) Cells Plasticity in Autoimmune Thyroiditis among Hepatitis C Virus Infection

The term T follicular helper (Tfh) cells were first used in 2000, it describes anew subset of CD4+ T cells located in tonsils. Tfh cells are subsets of CD4+ T helper cells that are required for maintenance of the germinal center reactions and generation of long-lived humoral immunity. They induce differentiation of B-cells into plasma cells. Tfh cells provide a help to cognate B cells via their expression of many molecules as CD40 ligand, IL-21, IL4, and others [1].