Miracle-dz/UniFAR-FTUs huggingface dataset:
Control of Demand-Driven Biosynthesis of Glutathione in Green Arabidopsis Suspension Culture Cells1

We have investigated what limits demand-driven de novo glutathione (GSH) biosynthesis in green Arabidopsis suspension culture cells. GSH is the most abundant low-molecular weight thiol in most plants and can be quantified using monochlorobimane to fluorescently label GSH in live cells. Progress curves for labeling reached a plateau as all the cytoplasmic GSH was conjugated. In the presence of excess monochlorobimane, a second, almost linear phase of labeling was observed, after a lag of 2 to 3 h, that was then maintained for an extended period. The increase in fluorescence was shown to be because of de novo GSH biosynthesis by high-performance liquid chromatography analysis and was eliminated bydl-buthionine-[S,R]-sulfoximine, a specific inhibitor of GSH biosynthesis, or reduced by inhibitors of transcription and translation. The rate of GSH biosynthesis during the linear phase was 8.9 ± 1.4 nmol g fresh weight−1min−1 and was not affected by addition of glutamate, glycine, or cysteine, the immediate precursors needed for GSH biosynthesis. Likewise, the synthesis rate was not affected by pretreatment with aminotriazole, menadione, jasmonic acid, or cadmium, all of which cause oxidative stress and up-regulate expression of GSH biosynthetic genes. The lag phase was markedly reduced by aminotriazole and menadione and marginally by jasmonic acid, suggesting the system was primed to react faster after mild stress. In contrast to the other feeding experiments, exclusion of SO4 2− from the medium abolished the second phase completely. This suggests demand-driven GSH biosynthesis is directly coupled to uptake of SO4 2− and that the linear increase in fluorescence reflects flux through the entire SO4 2− assimilation pathway.
Use of artificial neuronal networks for prediction of the control parameters in the process of anaerobic digestion with thermal pretreatment

ABSTRACT This article focuses on the analysis of the behavior patterns of the variables involved in the anaerobic digestion process. The objective is to predict the impact factor and the behavior pattern of the variables, i.e., temperature, pH, volatile solids (VS), total solids, volumetric load, and hydraulic residence time, considering that these are the control variables for the conservation of the different groups of anaerobic microorganisms. To conduct the research, samples of physicochemical sludge were taken from a water treatment plant in a poultry processing factory, and, then, the substrate was characterized, and a thermal pretreatment was used to accelerate the hydrolysis process. The anaerobic digestion process was analyzed in order to obtain experimental data of the control variables and observe their impact on the production of biogas. The results showed that the thermal pre-hydrolysis applied at 90°C for 90 min accelerated the hydrolysis phase, allowing a significant 52% increase in the volume of methane produced. An artificial neural network was developed, and it was trained with the database obtained by monitoring the anaerobic digestion process. The results obtained from the artificial neural network showed that there is an adjustment between the real values and the prediction of validation based on 60 samples with a 96.4% coefficient of determination, and it was observed that the variables with the major impact on the process were the loading rate and VS, with impact factors of 36% and 23%, respectively.
SLearn: Shared learning human activity labels across multiple datasets

The research of sensor-based human activity recognition has been attracting increasing attention over years as it is playing an important role in various human-beneficiary applications such as ambient assistive living, health monitoring, and behaviour changing. Nowadays, the advancement of sensing and communication technologies has led to the possibility of collecting a large amount of sensor data, however, to build a reliable computational model and accurately recognise human activities we still need the annotations on sensor data. Acquiring high-quality, detailed, continuous annotations is a challenging task. In this paper, we explore the solution space on sharing annotated activities across different datasets in order to enhance the recognition accuracies. We have designed and developed two approaches: sharing training data and sharing classifiers towards addressing this challenge. We have validated the approach on three datasets and demonstrated their effectiveness in recognising activities only with annotations from as little as 0.1% of each dataset.
Modesty Doesn’t Become Me Narcissism and the Big Five among Male and Female Candidates for the Big Brother TV Show

The objective of this study is to compare the Big Five of personality and the narcissism levels between candidates who auditioned for the show and control individuals, who had no intention to participate in a reality TV show. Ninety-two candidates who auditioned for the show and 94 control individuals who had no intention to do so filled in a demographic questionnaire, Costa and McCrae’s (1992) NEO-FFI-R, and Raskin and Hall’s (1981) Narcissistic Personality Inventory (NPI). The candidates were significantly less agreeable and neurotic, but more extroverted, conscientious, and narcissistic, than noncandidates. Gender personality differences between candidates and noncandidates are also presented. Reality TV shows are one of the modalities of the narcissistic culture, through which narcissistic individuals may channel their need for admiration.
Estimation of direction of attention using EEG and out-of-head sound localization

Brain-Machine Interfaces (BMIs) are being researched controlling external devices such as robots and computers by measuring the cranial nerve activity of the operator. The brain activities evoked by visual stimuli have been studied intensively. However, few studies have considered a BMI that uses the brain activities evoked by auditory stimuli. This study investigated whether a person's direction of attention can be estimated using an event-related potential (ERP) generated by selective attention to an auditory stimulus. An auditory stimulus and an out-of-head sound localization system that can create an audio image outside the head that is presented through an earphone were used instead of a loudspeaker system. This system was experimentally evaluated by presenting the subject auditory cues from one of six directions while the subject directed his attention in one direction. An EEG response similar to an ERP was observed. The direction of attention was estimated using support vector machine with an accuracy of 89.2[%] on average for the three subjects. This suggests that a BMI system based on the estimated direction of attention can be developed by using out-of-head sound localization.
Rules for Biologically Inspired Adaptive Network Design

Miniature Transport Engineers In its vegetative phase, the slime mold Physarum polycephalum “slimes” its way through the world seeking food. As it explores, it links previously found food sources with tubular structures. Tero et al. (p. 439) report that if food sources are deposited on a plate in a pattern corresponding in miniature to the positions of the cities that surround Tokyo, the resulting network of Physarum tubules that develops is rather similar in structure to the railroad network that connects the Japanese cities. A model was produced that describes the adaptive network development displayed by the slime mold. This biologically inspired model might provide insight into how to implement properties like resistance of transport systems to local failures into similar human-designed systems. Human municipal transportation engineers might learn design strategies from the lowly slime mold. Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks—in this case, the Tokyo rail system. The core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical model that may be useful to guide network construction in other domains.
The mediating role of integration of safety by activity versus operator between organizational culture and safety climate

ABSTRACT In this study, we analyse the impact of the organizational culture and introduce a new variable, the integration of safety, which relates to the modalities for the implementation and adoption of safety in the work process, either through the activity or by the operator. One hundred and eighty employees replied to a questionnaire measuring the organizational climate, the safety climate and the integration of safety. We expected that implementation centred on the activity or on the operator would mediate the relationship between the organizational culture and the safety climate. The results support our assumptions. A regression analysis highlights the positive impact on the safety climate of organizational values of the ‘rule’ and ‘support’ type, as well as of integration by the operator and activity. Moreover, integration mediates the relation between these variables. The results suggest to take into account organizational culture and to introduce different implementation modalities to improve the safety climate.
Humanoid robot task recognition from movement analysis

In this paper, we present a method to perform tasks identification on a humanoid robot. The observed motion is compared to a set of candidate controllers that the robot might be executing. The more relevant candidate controllers are selected, and can be used as a description of the motion, or as a basis to replicate a similar motion on another robot. The analysis of the movements is based on the task-function approach and is applied in the context of humanoid robot motions. A pool of tasks is defined in order to cover the range of possible motion of the robot and the demonstration movement is projected in each candidate task of that pool. The reduced trajectory is then compared with the characteristic task trajectory using a numerical optimization process. The movement is then projected into the null space of the best task candidate. As a consequence, the motion due to the task candidate is subtracted from the original movement. This process is iterated until the result of a projection becomes null. The approach is applied to recognize the tasks performed by a HRP-2 robot in simulation, in order to disambiguate very similar-looking motions. Preliminary directions are given for possible application for human motion recognition.
A new architecture for a single-chip multi-channel beamformer based on a standard FPGA

A new architecture for a compact medical ultrasound beamformer has been developed. Combination of novel and known principles has been utilized, leading to low processing power requirements and simple analog circuitry. Usage of a field programmable gate array (FPGA) for the digital signal processing provides programming flexibility. First, sparse sample processing is performed by generating the in-phase and quadrature beamformed signals. Hereby only 512 samples are beamformed for each line in an image. That leads to a 15-fold decrease in the number of operations and enables the use of Delta-Sigma (/spl Delta//spl Sigma/) modulation analog-to-digital converters (ADC). Second, simple second-order /spl Delta//spl Sigma/ modulation ADC with classic topology is used. This allows for simple analog circuitry and a very compact design. Several tens of these together with the corresponding preamplifiers can be fitted together onto a single analog integrated circuit. Third, parameter driven delay generation is used, using 3 input parameters per line per channel for either linear array imaging or phased array imaging. The delays are generated on the fly. The delay generation logic also determines the digital apodization by using 2 additional parameters. The control logic consists of few adders and counters and requires very limited resources. Fourth, the beamformer is fully programmable. Any channel can be set to use an arbitrary delay curve, and any number of these channels can be used together in an extendable modular multi-channel system. A prototype of the digital logic is implemented using a Xilinx Virtex-E series FPGA. A 5 MHz center frequency is used along with an oversampling ratio of 14. The sampling clock frequency used is 140 MHz and the number of channels in a single Xilinx 1 million gate FPGA XCV600E is 32. The beamformer utilizes all of the BlockRAM of the device and 33% of its Core Logic Block (CLB) resources. Both simulation results and processed echo data from a phantom are presented.
Consumer price knowledge in the market for apparel

Purpose – The aim of this study is to analyze consumers' price knowledge in the market for apparels. Design/methodology/approach – After reviewing earlier attempts at assessing the construct, the price estimation error “PEE” was used, a measure based on explicit price knowledge stored in long-term memory, as a valid indicator of price knowledge. Findings – The results, including data from about 1,527 consumers on 66 products from the German apparel market, indicate that price knowledge is relatively low. Originality/value – Although, in the literature, there are several studies on price knowledge in the food industry, little is known about price knowledge in other industry sectors. This is quite surprising since pricing strategy is a concept which is vitally important to all retailers. Therefore, this study is a first contribution to extending the concept of behavioral pricing to the apparel market.
Dissecting the oligonucleotide binding properties of a disordered chaperone protein using surface plasmon resonance

We have used surface plasmon resonance to investigate the nucleic acid binding properties of the core protein of hepatitis C virus, a disordered protein believed to chaperone the genomic RNA. It was previously shown that a peptide (peptide E) corresponding to the association of two basic clusters of core enhances the annealing and the dimerization of nucleic acid fragments derived from a stem loop (SL2) in the 3′ untranslated region of the hepatitis C virus genome. However, strong aggregation of nucleic acids by core or peptide E in the excess of the latter precluded the characterization of their binding parameters up to now. By careful design of surface plasmon resonance experiments, we obtained accurate binding parameters for the interaction of peptide E with SL2-derived oligonucleotides of different lengths and sequences, in form of stem-loop, duplex or strand. Peptide E was found to bind in a salt dependent manner to all oligonucleotides assayed. Affinity data identify at least two binding modes, of which one is independent of sequence/structure, and the other is specific to the SL2 stem-loop fold. Stoichiometry data support a multi-motif binding model allowing formation of higher-order complexes. We propose that the modular binding mode demonstrated for structured RNA-binding proteins also applies to this disordered chaperone and is relevant to its activity.
Antifibrotic effects of CXCR 4 antagonist in bleomycin-induced pulmonary fibrosis in mice

Circulating fibrocytes had been reported to migrate into the injured lungs, and contribute to fibrogenesis via chemokine-chemokine receptor systems including CXCL12-CXCR4 axis. Here we hypothesized that blockade of CXCR4 might inhibit the migration of fibrocytes to the injured lungs and the subsequent pulmonary fibrosis. To explore the antifibrotic effects of blockade of CXCR4, we used a specific antagonist for CXCR4, AMD3100, in bleomycin-induced pulmonary fibrosis model in mice. Administration of AMD3100 significantly improved the loss of body weight of mice treated with bleomycin, and inhibited the fibrotic lesion in subpleural areas of the lungs. The quantitative analysis demonstrated that treatment with AMD3100 reduced the collagen content and fibrotic score (Aschcroft score) in the lungs. Although AMD3100 did not affect cell classification in bronchoalveolar lavage fluid on day 7, the percentage of lymphocytes was reduced by AMD3100 on day 14. AMD3100 directly inhibited the migration of human fibrocytes in response to CXCL12 in vitro, and reduced the trafficking of fibrocytes into the lungs treated with bleocmycin in vivo. These results suggest that the blockade of CXCR4 might be useful strategy for therapy of patients with pulmonary fibrosis via inhibiting the migration of circulating fibrocytes. J. Med. Invest. 60 : 127-137, February,
The VLA-COSMOS 3 GHz Large Project: Multiwavelength counterparts and the composition of the faint radio population

We study the composition of the faint radio population selected from the Karl G. Jansky Very Large Array Cosmic Evolution Survey (VLA-COSMOS) 3 GHz Large Project, which is a radio continuum survey performed at 10 cm wavelength. The survey covers a 2.6 square degree area with a mean rms of ~ 2.3 μJy/beam, cataloging 10 830 sources above 5σ, and enclosing the full 2 square degree COSMOS field. By combining these radio data with optical, near-infrared (UltraVISTA), and mid-infrared (Spitzer/IRAC) data, as well as X-ray data (Chandra), we find counterparts to radio sources for ~93% of the total radio sample reaching out to z ≲ 6; these sources are found in the unmasked areas of the COSMOS field, i.e., those not affected by saturated or bright sources in the optical to near-infrared (NIR) bands. We further classify the sources as star-forming galaxies or AGN based on various criteria, such as X-ray luminosity; observed mid-infrared color; UV–far-infrared spectral energy distribution; rest-frame, near-UV optical color that is corrected for dust extinction; and radio excess relative to that expected from the star formation rate of the hosts. We separate the AGN into subsamples dominated by low-to-moderate and moderate-to-high radiative luminosity AGN, i.e., candidates for high-redshift analogs to local low- and high-excitation emission line AGN, respectively. We study the fractional contributions of these subpopulations down to radio flux levels of ~11 μJy at 3 GHz (or ~20 μJy at 1.4 GHz assuming a spectral index of –0.7). We find that the dominant fraction at 1.4 GHz flux densities above ~200 μJy is constituted of low-to-moderate radiative luminosity AGN. Below densities of ~100 μJy the fraction of star-forming galaxies increases to ~ 60%, followed by the moderate-to-high radiative luminosity AGN (~ 20%) and low-to-moderate radiative luminosity AGN (~ 20%). Based on this observational evidence, we extrapolate the fractions down to sensitivities of the Square Kilometer Array (SKA). Our estimates suggest that at the faint flux limits to be reached by the (Wide, Deep, and UltraDeep) SKA1 surveys, a selection based only on radio flux limits can provide a simple tool to efficiently identify samples highly (>75%) dominated by star-forming galaxies.
GABAA receptors can initiate the formation of functional inhibitory GABAergic synapses

The mechanisms that underlie the selection of an inhibitory GABAergic axon's postsynaptic targets and the formation of the first contacts are currently unknown. To determine whether expression of GABAA receptors (GABAARs) themselves – the essential functional postsynaptic components of GABAergic synapses – can be sufficient to initiate formation of synaptic contacts, a novel co‐culture system was devised. In this system, the presynaptic GABAergic axons originated from embryonic rat basal ganglia medium spiny neurones, whereas their most prevalent postsynaptic targets, i.e. α1/β2/γ2‐GABAARs, were expressed constitutively in a stably transfected human embryonic kidney 293 (HEK293) cell line. The first synapse‐like contacts in these co‐cultures were detected by colocalization of presynaptic and postsynaptic markers within 2 h. The number of contacts reached a plateau at 24 h. These contacts were stable, as assessed by live cell imaging; they were active, as determined by uptake of a fluorescently labelled synaptotagmin vesicle‐luminal domain‐specific antibody; and they supported spontaneous and action potential‐driven postsynaptic GABAergic currents. Ultrastructural analysis confirmed the presence of characteristics typical of active synapses. Synapse formation was not observed with control or N‐methyl‐d‐aspartate receptor‐expressing HEK293 cells. A prominent increase in synapse formation and strength was observed when neuroligin‐2 was co‐expressed with GABAARs, suggesting a cooperative relationship between these proteins. Thus, in addition to fulfilling an essential functional role, postsynaptic GABAARs can promote the adhesion of inhibitory axons and the development of functional synapses.
Faraday cage angled-etching of nanostructures in bulk dielectrics

For many emerging optoelectronic materials, heteroepitaxial growth techniques do not offer the same high material quality afforded by bulk, single-crystal growth. However, the need for optical, electrical, or mechanical isolation at the nanoscale level often necessitates the use of a dissimilar substrate, upon which the active device layer stands. Faraday cage angled-etching (FCAE) obviates the need for these planar, thin-film technologies by enabling in situ device release and isolation through an angled-etching process. By placing a Faraday cage around the sample during inductively coupled plasma reactive ion etching, the etching plasma develops an equipotential at the cage surface, directing ions normal to its face. In this article, the effects that Faraday cage angle, mesh size, and sample placement have on etch angle, uniformity, and mask selectivity are investigated within a siliconetching platform. Simulation results qualitatively confirm experiments and help to clarify the physical mechanisms at work. These results will help guide FCAE process design across a wide range of material platforms.
Optimization of Insuring Critical Path Problem with Uncertain Activity Duration Times

In fuzzy decision systems, we model insuring critical path problem by two-stage risk-aversion fuzzy programming. For the proposed two-stage insuring critical path problem, we rst dene three solution concepts, expected value solution, wait-and-see solution and here-and-now solution, then introduce the value of perfect information of value-at-risk (VaRVPI) and the value of the fuzzy solution of value-at-risk (VaRVFS). When activity duration times are continuous fuzzy variables, we adopt fuzzy simulation to turn the original insuring critical path problem into its approximate optimization problem. After that, we solve the approximate insuring critical path problem by hybrid algorithm, which combines dynamic programming method and genetic algorithm (GA). Finally, we report some computational results to illustrate the credibility of the developed modeling idea and the eectiveness of the designed algorithm. c