Miracle-dz/UniFAR-FTUs huggingface dataset:
Isolation of a new strain of Picochlorum sp and characterization of its potential biotechnological applications

Selection of new autochthon strains is necessary, and for the moment the best strategy, to find microalgae well adapted to the local climatological conditions able to simultaneously produce several compounds of biotechnological interest and grow at high rates. We describe the isolation and characterization of a new microalgal strain isolated from the marshlands of the Odiel River in the Southwest of Spain. The new microalga belongs to the genus Picochlorum, as deduced from the analysis of its 18S rRNA encoding gene, is able to grow at a high growth rate and thrive with adverse conditions. It has an appreciable constitutive level of lutein (3.5 mg g−1 DW) and zeaxanthin (0.4 mg g−1 DW) which is increased to 1.8 mg g−1 DW at high light intensities. This strain is also characterized by a very low level of linolenic acid (3.8% of total fatty acids) and no polyunsaturated fatty acids with four or more double bonds. Although the total lipid content is not particularly high, 23% of the dry weight, its fatty acid profile makes of Picochlorum sp HM1 a promising candidate for biodiesel production, and the high content in the carotenoids lutein and zeaxanthin indicates that the microalga could also be a good source for natural eye vitamin supplements, which could be obtained as co‐products. © 2011 American Institute of Chemical Engineers Biotechnol. Prog. , 2011
Use of 3D range cameras for structural deformation measurement

A three-dimensional range camera is a state-of-the-art imaging technology that has strong potential for various closerange high-precision measurement applications. One such application is the measurement of structural deformation under external loading conditions. Deformation tests have been conducted on two concrete beams with and without steel-reinforced polymer sheets in an indoor testing facility using an SR4000 range camera. The achieved measurement precision and accuracy were both within 1 mm when compared with a terrestrial laser scanner. Further testing on the concrete beam with the steel-reinforced polymer sheets has shown that a deformation as small as 3 mm can be reliably detected with a range camera with a measurement precision of 0.3 mm and an accuracy of 0.4 mm. These results clearly indicate the high metric potential of 3D range cameras in spite of their coarse imaging resolution and low (centimeterlevel) single point accuracy. The high accuracy can be achieved thanks to the differencing scheme used to derive the deflection estimates from two sets of range camera measurements, one at no-load and one of the beam in a loaded state, which eliminates the scene-dependent range biases such as scattering and multi-path errors.
A Heuristic for the Maximum Processor Requirement for Scheduling Layered Task Graphs with Coloring

Programming models for distributed systems often construct a task graph for the program to be executed on a distributed system of processors. While the topology of the task graph can be constructed from the program structure, often the task execution times and data transfer costs between tasks depend on the input data, or more specifically, on the particular problem instance. Though this indicates that the optimal schedule of a task graph cannot be determined until the input data is available, it is possible to estimate theworst caseprocessor requirement for the optimal schedule of a program solely from the topology of its task graph. In this paper, we study the problem of estimating worst case processor requirements for scheduling (with cloning) layered task graphs based on their topology. We show that computing an accurate processor bound for layered graphs is NP hard (even for two layers) and present a polynomial time algorithm which computes an upper bound on the processor requirement. We show that the algorithm provides tight bounds for several common classes of layered task graphs.
Spatial CCK Modulation and Iterative Detection Over Frequency-Selective Fading Channels

In this letter, we present a novel spatial modulation (SM) transmission with multiple antennas by applying non-orthogonal complementary code keying (CCK). We propose a high-performance turbo receiver for this CCK-SM signaling over frequency-selective fading channels. Compared with conventional SM, our proposed CCK-SM transceiver utilizes the advantages of CCK to achieve substantial coding gain without the cost of high complexity. Our novel receiver incorporates iterative block decision feedback equalization with a CCK soft decoder to achieve clear performance gain. Simulation test shows substantial performance gain by the proposed CCK-SM transceiver over the conventional SM.
Please Scroll down for Article Journal of Neurotherapy Use of Auditory and Visual Stimulation to Improve Cognitive Abilities in Learning-disabled Children Use of Auditory and Visual Stimulation to Improve Cognitive Abilities in Learning-disabled Children

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. ABSTRACT. Introduction. Learning disabilities (LD) comprise cogni-tive deficits in executive functioning which include working memory, encoding, visual-motor coordination, planning, and information processing. This study examined the effects of auditory and visual stimulation (AVS) on four specific cognitive abilities in children diagnosed with LD who demonstrated low and below average scores on the Wechs-ler Intelligence Scale for Children, Third Edition (WISC-III) Symbol Search, Coding, Arithmetic, and Digit Span (SCAD) profile to determine if such a treatment intervention could improve these specific cog-nitive weaknesses. Methods. The WISC-III SCAD profile was administered pre-and post-12, biweekly 35-minute AVS sessions. Two index scores from the SCAD profile were also assessed: Freedom from Distractibility and Processing Speed. The study design was quasi-experimental, with repeated measures pre-and post-treatment. Results. Findings demonstrated that AVS produced significant changes in all of the specific cognitive abilities as measured by the WISC-III SCAD profile, suggesting that AVS may benefit children with LD. Discussion. AVS technology has the potential to greatly enhance cognitive abilities and quality of life for the learning-disabled individual who may be at risk for social, psychological, and a multitude of personal disappointments and lifelong failures without such intervention. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH.
Tensile Strength versus Toughness of Cement-Based Materials against High-Velocity Projectile Impact

This paper presents a laboratory experimental study on the effect of tensile strength and toughness on the resistance of cement-based materials to high-velocity projectile impact. Three types of cement-based materials with similar compressive strength but different tensile strengths and toughnesses were examined in terms of the penetration depth, crater diameter, and crack propagation in specimens subjected to impact of ogive-nosed projectile with a diameter of 13.35 mm and a mass of 19 grams traveling at velocities of about 650 m/s. The materials evaluated include: (i) a plain high-strength concrete (HSC) with low tensile strength and toughness, (ii) a fiber-reinforced concrete (FRHSC) with high toughness but similar flexural tensile strength as the HSC, and (iii) a polymer cement composite (PCC) with high flexural tensile strength but low toughness. The PCC was developed from a combination of inorganic cements with water-soluble polymers, and it had a 28-day flexural tensile strength of 25 MPa. Results suggest that the toughness was a more important parameter that contributes to the impact resistance of the cement-based materials. Increasing the tensile strength alone, however, did not seem to contribute to the impact resistance of the cement-based materials.
Lead-Lag Relationship using a Stop-and-Reverse-MinMax Process

The intermarket analysis, in particular the lead–lag relationship, plays an important role within financial markets. Therefore, a mathematical approach to be able to find interrelations between the price development of two different financial instruments is developed in this paper. Computing the differences of the relative positions of relevant local extrema of two charts, i.e., the local phase shifts of these price developments, gives us an empirical distribution on the unit circle. With the aid of directional statistics, such angular distributions are studied for many pairs of markets. It is shown that there are several very strongly correlated financial instruments in the field of foreign exchange, commodities and indexes. In some cases, one of the two markets is significantly ahead with respect to the relevant local extrema, i.e., there is a phase shift unequal to zero between them.
Fully Integrated Inductor-Less Flipping-Capacitor Rectifier for Piezoelectric Energy Harvesting

This paper presents a fully integrated piezoelectric energy harvesting interface without external components. Instead of relying on bulky external inductors with high quality factor as in the conventional parallel-synchronized-switch harvesting-on-inductor (P-SSHI) approach, we propose a flipping-capacitor rectifier (FCR) topology to achieve voltage inversion of the piezoelectric energy harvester through a reconfigurable capacitor array. This fundamentally preserves a fully integrated solution without inductors while achieving a high-energy extraction capability. Measurement results from FCR<sub>1</sub> using discrete components shows an output power enhancement of up to 3.4<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula>, which is close to the theoretical prediction. We also fabricated a seven-phase FCR<sub>3</sub> with four MIM capacitors and 21 switches using a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> 1.8/3.3/6 V CMOS process, occupying an active area of ~1.7 mm<sup>2</sup>. Additionally, we implemented an active rectifier based on a common-gate comparator with phase alignment to ensure high-speed operation while minimizing the diode voltage drop. A phase generate-and-combine circuit eliminates redundant switching activities. Systematic optimization of the three main energy loss mechanisms during the finite flip time: 1) phase offset; 2) incomplete charge transfer; and 3) reduced conduction time, is also introduced. Measurement results show that the output power enhancement can reach up to 4.83<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> at an excitation frequency of 110 kHz.
Constructing a Temporal Relation Tagged Corpus of Chinese Based on Dependency Structure Analysis

This paper describes an annotation guideline for a temporal relation tagged corpus. Our goal is to construct a machine learnable model that automatically analyzes temporal events and relations between events. Since analyzing all combinations of events is inefficient, we examine use of dependency structure analysis to efficiently recognize meaningful temporal relations. We survey a small tagged data set to investigate the coverage of our method. Although the coverage of our methods is about 49%, we find that the dependency structure appears useful for reducing manual efforts in constructing a tagged corpus with temporal relations.
Recognition by Variance: Learning Rules for Spatiotemporal Patterns

Abstract Recognizing specific spatiotemporal patterns of activity, which take place at timescales much larger than the synaptic transmission and membrane time constants, is a demand from the nervous system exemplified, for instance, by auditory processing. We consider the total synaptic input that a single readout neuron receives on presentation of spatiotemporal spiking input patterns. Relying on the monotonic relation between the mean and the variance of a neuron's input current and its spiking output, we derive learning rules that increase the variance of the input current evoked by learned patterns relative to that obtained from random background patterns. We demonstrate that the model can successfully recognize a large number of patterns and exhibits a slow deterioration in performance with increasing number of learned patterns. In addition, robustness to time warping of the input patterns is revealed to be an emergent property of the model. Using a leaky integrate-and-fire realization of the readout neuron, we demonstrate that the above results also apply when considering spiking output.
Please Scroll down for Article Journal of Freshwater Ecology Modeling Phytoplankton Dynamics in the River Darling (australia) Using the Radial Basis Function Neural Network Modeling Phytoplankton Dynamics in the River Darling (australia) Using the Radial Basis Function Neural Network

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. ABSTRACT A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp. , in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp. , sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms. INTRODUCTION Many etlorts have been undertaken to model and explain the population dynamics of phytoplankton by heuristic and deterministic approaches (Okada and Aiba1983, Reynolds 1984, Sommer et al. 1986, Kromcamp and Walsby 1990). While much has been achieved in understanding the ecology of phytoplankton blooms, the predictive accuracy of these deterministic models is not so promising because of the complexity of aquatic ecosystems. However, recent research has demonstrated that artificial neural network based models of phytoplankton population dynamics could give promising predictive results by exploring the information content contained in long-term historical data of environmental parameters and algal population Although algal blooms frequently are observed in lowland rivers throughout the world and phytoplankton can exhibit very different population and community aspects in rivers compared to lakes (Reynolds 1992), much less research effort has been put into studies of the …
The mobileak project: Forensics methodology for mobile application privacy assessment

When talking about privacy, we talk about information, about data. There are several aspects that have to be considered when aiming to assess the privacy level of an application. These aspects are the states in which data can exist: data at rest, data in use and data in transit. Each of these require different methodologies and technologies in order to be properly addressed. This paper focuses on the state where data are at rest. It will be shown how common mobile forensics methodologies and tools can be used to assess the privacy level of mobile applications, and therefore how mobile applications store and manage personal information.
Testosterone and Dihydrotestosterone Tissue Levels in Recurrent Prostate Cancer

Purpose: Prostate cancer eventually recurs during androgen deprivation therapy despite castrate levels of serum androgens. Expression of androgen receptor and androgen receptor–regulated proteins suggests androgen receptor activation in recurrent prostate cancer. Many groups have pursued mechanisms of ligand-independent androgen receptor activation but we found high levels of testicular androgens in recurrent prostate cancer tissue using RIA. Experimental Designs: Prostate specimens from 36 men were procured preserving blood flow to prevent ischemia and cyropreserved immediately. Recurrent prostate cancer specimens from 18 men whose cancer recurred locally during androgen deprivation therapy and androgen-stimulated benign prostate specimens from 18 men receiving no hormonal treatments were studied. Tissue levels of testosterone and dihydrotestosterone were measured in each specimen using liquid chromatography/electrospray tandem mass spectrometry. Testosterone and dihydrotestosterone levels were compared with clinical variables and treatment received. Results: Testosterone levels were similar in recurrent prostate cancer (3.75 pmol/g tissue) and androgen-stimulated benign prostate (2.75 pmol/g tissue, Wilcoxon two-sided, P = 0.30). Dihydrotestosterone levels decreased 91% in recurrent prostate cancer (1.25 pmol/g tissue) compared with androgen-stimulated benign prostate (13.7 pmol/g tissue; Wilcoxon two-sided, P < 0.0001) although dihydrotestosterone levels in most specimens of recurrent prostate cancer were sufficient for androgen receptor activation. Testosterone or dihydrotestosterone levels were not related to metastatic status, antiandrogen treatment, or survival (Wilcoxon rank sum, all P > 0.2). Conclusions: Recurrent prostate cancer may develop the capacity to biosynthesize testicular androgens from adrenal androgens or cholesterol. This surprising finding suggests intracrine production of dihydrotestosterone and should be exploited for novel treatment of recurrent prostate cancer.
Solving Molecular Docking Problems with Multi-Objective Metaheuristics

Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II), speed modulation multi-objective particle swarm optimization (SMPSO), third evolution step of generalized differential evolution (GDE3), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and S-metric evolutionary multi-objective optimization (SMS-EMOA). We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA) provided by the AutoDock tool). Furthermore, the ligand binding site and molecular interactions of computed solutions are analyzed, showing promising results for the multi-objective approaches. In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery.
Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Asymmetric Distances for Binary Embeddings

—In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH), PCA Embedding (PCAE), PCA Embedding with random rotations (PCAE-RR), and PCA Embedding with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques.
Factors Determining Final Height in Congenital Adrenal Hyperplasia

Abstract Congenital adrenal hyperplasia (CAH) is a family of adrenal disorders whereby cortisol biosynthesis is impaired or abolished. In most cases, CAH is caused by a deficiency of the enzyme 21-hydroxylase causing a massive build up of adrenal precursors. In addition to prenatal virilisation of genetic females and postnatal virilisation of both males and females, short adult stature is characteristic of the disorder. The inadequate final height in CAH patients is often attributed to overtreatment with glucocorticoid replacement and poor control of adrenal androgen levels. In a recent study, the use of growth hormone alone and in combination with gonadotropin releasing hormone analogue in children with CAH and poor predicted final height was found to decrease height deficit after one and two years of treatment.