Miracle-dz/UniFAR-FTUs huggingface dataset:
ZnS, CdS and HgS Nanoparticles via Alkyl-Phenyl Dithiocarbamate Complexes as Single Source Precursors

The synthesis of II-VI semiconductor nanoparticles obtained by the thermolysis of certain group 12 metal complexes as precursors is reported. Thermogravimetric analysis of the single source precursors showed sharp decomposition leading to their respective metal sulfides. The structural and optical properties of the prepared nanoparticles were characterized by means of X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM) UV-Vis and photoluminescence spectroscopy. The X-ray diffraction pattern showed that the prepared ZnS nanoparticles have a cubic sphalerite structure; the CdS indicates a hexagonal phase and the HgS show the presence of metacinnabar phase. The TEM image demonstrates that the ZnS nanoparticles are dot-shaped, the CdS and the HgS clearly showed a rice and spherical morphology respectively. The UV-Vis spectra exhibited a blue-shift with respect to that of the bulk samples which is attributed to the quantum size effect. The band gap of the samples have been calculated from absorption spectra and werefound to be about 4.33 eV (286 nm), 2.91 eV (426 nm) and 4.27 eV (290 nm) for the ZnS, CdS and HgS samples respectively.
Association of mannose‐binding lectin polymorphisms and HBV outcome in a South Indian population

Mannose binding lectin (MBL) is an important innate immune system pattern recognition molecule. The MBL gene polymorphisms are reported to play a crucial role in outcome of hepatitis B virus (HBV) infection. In this study, we ascertained the association of MBL genotypes with HBV outcome in a South Indian population. The MBL gene polymorphisms at codons 52, 54 and 57 of exon I, and promoter polymorphisms at −221 were typed by polymerase chain reaction‐sequence specific primer in spontaneously recovered and in chronic HBV group. The allele frequency of codon 52 ‘C’ was significantly higher in chronic HBV group than in the recovered group (98.5% vs. 93.6%; P = 0.003) and codon 52 ‘T’ was significantly higher in recovered group than in the chronic group (6.4% vs. 1.5%; P = 0.003). In multivariate analysis, after adjusting for age, sex and state of origin, codon 52 ‘CC’ and ‘CT’ genotypes were significantly associated with chronicity and recovery respectively [odds ratio (OR), 0.25; 95% confidence interval (CI), 0.08–0.80, P = 0.02] in co‐dominant analyzing models. This was re‐affirmed in analysis performed exclusively on Tamil Nadu subjects (OR, 0.23; 95% CI, 0.06–0.93, P = 0.039). The frequency of low/none haplotype (XY/O) was significantly higher in recovered group than in chronic group (15.6% vs 7.5%) and associated with spontaneous recovery (OR, 2.28; 95% CI, 1.04–4.99, P = 0.035). Our results provide preliminary evidence that inheritance of codon 52 genotypes and XY/O haplotype associated with low MBL level substantially determine the outcome of HBV infection in a sympatrically isolated South Indian population.
Modified MicroSecure Vitrification: A Safe, Simple and Highly Effective Cryopreservation Procedure for Human Blastocysts

Clinical embryo vitrification evolved with the development of unique vitrification devices in the 21st century and with the misconception that ultra-rapid cooling in an "open" system (i.e., direct LN2 contact) was a necessity to optimize vitrification success. The dogma surrounding the importance of cooling rates led to unsafe practices subject to technical variation and to the creation of vitrification devices that disregarded important quality-control factors (e.g., ease of use, repeatability, reliability, labeling security, and storage safety). Understanding the quality-control flaws of other devices allowed for the development of a safe, secure, repeatable, and reliable µS-VTF method aimed to minimize intra- and inter-technician variation. Equally important, it combined the availability of two existing FDA-compliant devices: 1) a 0.3-mL ionomeric resin embryo straw with internalized, dual-colored, tamper-proof labeling with repeatable weld seal potential; and 2) shortened, commonly-used, 300-µm ID sterile flexipettes to directly load the embryo(s) in order to create a highly-effective global vitrification device. Like other aseptic, closed vitrification systems (e.g., High Security Vitrification (HSV), Rapid-i, and VitriSafe) effectively used in reproductive medicine, microSecure Vitrification (µS-VTF) has proven that it can achieve high post-warming survival and pregnancy outcomes with its attention to simplicity, and reduced technical variation. Although the 0.3-mL embryo straw containing an internal hydrophobic plug was commercially replaced with a standard semen straw possessing cotton-polyvinyl pyrrolidone (PVP) plugs, it maintained its ionomeric resin composition to ensure weld sealing. However, the cotton plugs can wick out the fluid-embryo contents of the flexipettes upon contact. A modified µS-VTF method was adapted to include an additional internal weld seal before the plug on the device loading side. The added technical step to the µS-VTF procedure has not affected its successful application, as high survival rates (> 95%) and pregnancy rates continue today.
Pulmonary Particle Deposition in Relation to Age, Body Weight, and Species

As a result of dissimilarity in lung morphometry and physiological conditions, therapeutic aerosol particles deposit differently in humans of various ages and body weights. These particles also deposit differently in non-human species that are often utilized in inhalation and dosing studies. The focus of this work is to determine the optimal particle size and deposition (traditional efficiency and volume-weighted) of therapeutic particles in humans of both genders ranging in age from 3 months old to 21 years old and three nonhuman species (B6C3F1 mouse, Long-Evans hooded rat, and Beagle dog). This study finds that in humans, both optimal particle size and volume-weighted deposition are age and weight dependent; as age and weight increase, optimal particle size and deposition increase. Also, for all ages, breathing rates that are lower than normal enhance volume-weighted deposition and shift optimal particle size. Additionally, a rigorous sensitivity analysis of breathing rate and particles diameter on deposition shows that at normal breathing rates, sensitivity to breathing rate is greater than sensitivity to particle diameter for young children, but sensitivities to both become similar as age/body weight increase. At optimal breathing rates, the sensitivity to both breathing rate and particle diameter are lowest at the optimal breathing rates for children; for healthy adults, however, there is no apparent difference in sensitivity at normal and optimal breathing rates. This study also found that the mouse represents infants and young children relatively well, the rat represents older children
Annual Conference of the Prognostics and Health Management Society , 2011 Deriving Bayesian Classifiers from Flight Data to Enhance Aircraft Diagnosis

Online fault diagnosis is critical for detecting the onset and hence the mitigation of adverse events that arise in complex systems, such as aircraft and industrial processes. A typical fault diagnosis system consists of: (1) a reference model that provides a mathematical representation for various diagnostic monitors that provide partial evidence towards active failure modes, and (2) a reasoning algorithm that combines set-covering and probabilistic computation to establish fault candidates and their rankings. However, for complex systems reference models are typically incomplete, and simplifying assumptions are made to make the reasoning algorithms tractable. Incompleteness in the reference models can take several forms, such as absence of discriminating evidence, and errors and incompleteness in the mapping between evidence and failure modes. Inaccuracies in the reasoning algorithm arise from the use of simplified noise models and independence assumptions about the evidence and the faults. Recently, data mining approaches have been proposed to help mitigate some of the problems with the reference models and reasoning schemes. This paper describes a Tree Augmented Naı̈ve Bayesian Classifier (TAN) that forms the basis for systematically extending aircraft diagnosis reference models using flight data from systems operating with and without faults. The performance of the TAN models is investigated by comparing them against an expert supplied reference model. The results demonstrate that the generated TAN structures can be used by human experts to identify improvements to the reference model, by adding (1) new causal links that relate evidence to faults, and different pieces of evidence, and (2) updated thresholds and new monitors that facilitate the derivation of more precise evidence from the sensor data. A case study shows that this improves overall reasoner performance. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Acute Synaptic Activity Causes Differential miRNA Expression in the Drosophila melanogaster Larval Central Nervous System

The primary goal of this thesis was to determine if spaced synaptic stimulation induced the differential expression of microRNAs (miRNAs) in the Drosophila melanogaster central nervous system (CNS). Prior to attaining this goal, we needed to identify and validate a spaced stimulation paradigm that could induce the formation of new synaptic growth at a model synapse, the larval neuromuscular junction (NMJ). Both Channelrhodopsinand high potassium-based stimulation paradigms adapted from (Ataman, et al. 2008) were tested. Once validation of these paradigms was complete, we sought to characterize the miRNA expression profile of the larval CNS by miRNA array. Following attainment of these data, we used quantitative real-time PCR (RT-qPCR) to determine if acute synaptic stimulation caused the differential expression of neuronal miRNAs. We found that upon high potassium spaced training in a wild type (Canton S) genotype, 5 miRNAs showed significant differential expression when normalized to a validated reference gene, the U1 snRNA. Moreover, absolute quantification of our RTqPCR study implicated one miRNA: miR-958 as being significantly regulated by activity. Investigation into potential targets for miR-958 revealed it to be a potential regular of Dlar, a protein tyrosine phosphatase implicated in synapse development. This investigation provides the foundation to directly test our underlying hypothesis that, following spaced training, differential expression of miRNAs alters the translation of proteins required to induce and maintain these structural changes at the synapse.
Detecting Convoys Using License Plate Recognition Data

License plate recognition (LPR) sensors are embedded camera systems that monitor road traffic. When a vehicle passes by a sensor, the vehicle's license plate, the location, and the time of observation are recorded. Given a stream of such observations from a collection of sensors spread around the road network, our goal is to detect convoys: groups of two or more vehicles traveling with highly correlated trajectories. Some of the main challenges with modeling and processing data from LPR sensors include that the data-gathering process is event-driven, thus data are not regularly sampled in time or space. Also, an appropriate definition of convoy should be relative to background traffic patterns, which are temporally and spatially varying. This paper proposes novel models for LPR observations of traffic which are well suited for online convoy detection. Baseline traffic is modeled as following a mixture of semi-Markov processes, and specific models for temporal and spatial correlation of observations of vehicles traveling in a convoy are introduced. These models are used within a sequential hypothesis testing framework to obtain a system for real-time convoy detection. The model of baseline traffic may be of independent interest for forecasting road traffic patterns. Experiments with an extensive simulated dataset illustrate the performance of the scheme and offer insights into the tradeoffs between detection rate, false alarm rate, and the expected number of observations required to detect a convoy.
Assessing Agreement between miRNA Microarray Platforms

Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland–Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland–Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland–Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.
Carbon – nitrogen coupling under three schemes of model representation : a traceability analysis

The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C–N coupling differs greatly among models, and how these diverse representations of C–N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C–N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C–N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, downregulation of photosynthesis, and the pathways of N import. We incorporated the three C–N coupling schemes into the Conly version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C–N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of − 23 %, −30 %, and −54 % for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; −29 %, −15 %, and −45 %) and changes in mean C residence time (MRT; 9 %, −17 %, and −17 %) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C :N ratio, downregulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible C :N ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C–N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.
Stable Matrix Approximation for Top-N Recommendation on Implicit Feedback Data

Matrix approximation (MA) methods are popular in recommendation tasks on explicit feedback data. However, in many real-world applications, only positive feedbacks are explicitly given whereas negative feedbacks are missing or unknown, i.e., implicit feedback data, and standard MA methods will be unstable due to incomplete positive feedbacks and inaccurate negative feedbacks. This paper proposes a stable matrix approximation method, namely StaMA, which can improve the recommendation accuracy of matrix approximation methods on implicit feedback data through dynamic weighting during model learning. We theoretically prove that StaMA can achieve sharper uniform stability bound, i.e., better generalization performance, on implicit feedback data than MA methods without weighting. Meanwhile, experimental study on real-world datasets demonstrate that StaMA can achieve better recommendation accuracy compared with five baseline MA methods in top-N recommendation task.
Gait Measurement for the Audience-Participant Digital Entertainment

This paper presents a method to measure online the gait features from the gait silhouette images and reflect the gait features to CG characters for an audience-participation digital entertainment. First, both static and dynamic gait features are extracted from the silhouette images captured by the online gait measurement system with two cameras and a chroma-key background. Then, Standard Gait Models (SGMs) with various types of gait features are constructed and stored, which are composed of a pair of CG characters’ rendering parameters and synthesized silhouette images. Finally, blend ratios of the SGMs are estimated to minimize gait feature errors between the blended model and the online measurement. In an experiment, a gait database with 100 subjects is used for gait feature analysis and it is confirmed that the measured gait features are reflected to the CG character effectually.
FE Analysis of the Dynamic Characteristics of the Human Finger Pad in Contact With Objects With/Without Surface Roughness

We calculate the transient dynamic response of human finger skin and the distribution of the strain energy density at the tactile receptors focusing on the effect of epidermal ridges on tactile sensation. Using a FE (finite element) model which we create from geometric and material properties measured from an actual human index finger, we introduce a method of dynamic contact analysis which we use to analyze the dynamic contact between a finger with/without epidermal ridges and an object with/without surface roughness. It is found that the epidermal ridges increase the sensitivity of the tactile receptors. The presence of epidermal ridges change either the distribution pattern or the amplitude of the strain energy density at the tactile receptors. It is also found that the Meissner’s corpuscles are relatively sensitive for detecting the surface roughness, whereas Merkel’s discs are relatively sensitive for detecting indentations in objects.
Learning Pose Specific Representations by Predicting Different Views

The labeled data required to learn pose estimation for articulated objects is difficult to provide in the desired quantity, realism, density, and accuracy. To address this issue, we develop a method to learn representations, which are very specific for articulated poses, without the need for labeled training data. We exploit the observation that the object pose of a known object is predictive for the appearance in any known view. That is, given only the pose and shape parameters of a hand, the hand's appearance from any viewpoint can be approximated. To exploit this observation, we train a model that - given input from one view - estimates a latent representation, which is trained to be predictive for the appearance of the object when captured from another viewpoint. Thus, the only necessary supervision is the second view. The training process of this model reveals an implicit pose representation in the latent space. Importantly, at test time the pose representation can be inferred using only a single view. In qualitative and quantitative experiments we show that the learned representations capture detailed pose information. Moreover, when training the proposed method jointly with labeled and unlabeled data, it consistently surpasses the performance of its fully supervised counterpart, while reducing the amount of needed labeled samples by at least one order of magnitude.
Original β 1-Adrenoceptor-mediated relaxation with isoprenaline and the role of MaxiK channels in guinea-pig esophageal smooth muscle

The possible functional coupling between β1-adrenoceptor and MaxiK channels which results in smooth muscle relaxation was examined in the guinea-pig esophageal muscularis mucosae. Isoprenaline-elicited relaxation of esophageal smooth muscle was confirmed to be mediated through β1-adrenoceptors as the response was competitively antagonized by a β1-selective antagonist atenolol with a pA2 value of 7.01. Iberiotoxin (IbTx, 10–7 M), a selective MaxiK channel inhibitor, substantially diminished the relaxant response to isoprenaline. The extent of the MaxiK channel contribution to the relaxant response was 15–40% of the control response when estimated as the E50%–Emax responses to isoprenaline. The relaxation to isoprenaline was also attenuated by high-KCl (80 mM) to the same degree as the relaxant response generated in the presence of IbTx, and thus the estimated extent of the K+ channel contribution was 10–40%. These findings indicate that β1-adrenoceptors are substantially coupled with MaxiK channels to produce relaxation of esophageal smooth muscle in the guinea-pig. Although MaxiK channels account for the contribution of K+ channels to the β1-adrenoceptor-mediated relaxation in this smooth muscle preparation, their contribution seems to be less when compared to the β2-adrenoceptor-mediated relaxation of tracheal smooth muscle.
Reply to Interactive comment on “ The influence of deep convection on HCHO and H 2 O 2 in the upper troposphere over Europe ” by Heiko

Deep convection is an efficient mechanism for vertical trace gas transport from Earth’s surface to the upper troposphere (UT). The convective redistribution of short-lived trace gases emitted at the surface typically results in a C-shaped profile. This redistribution mechanism can impact photochemical processes, e.g. ozone and radical production in the UT on a 10 large scale due to the generally longer lifetimes of species like formaldehyde (HCHO) and hydrogen peroxide (H2O2), which are important HOx precursors (HOx = OH+HO2 radicals). Due to the solubility of HCHO and H2O2 their transport may be suppressed as they are efficiently removed by wet deposition. Here we present a case study of deep convection over Germany in the summer of 2007 within the framework of the HOOVER II project. Airborne in-situ measurements within the inand outflow regions of an isolated thunderstorm provide a unique data set to study the influence of deep convection on the transport 15 efficiency of soluble and insoluble trace gases. Comparing the inand outflow indicates almost undiluted transport of insoluble trace gases from the boundary layer to the UT. The ratios of out/inflow of CO and CH4 are 0.94 ± 0.04 and 0.99 ± 0.01, respectively. For the soluble species HCHO and H2O2 these ratios are 0.55 ± 0.09 and 0.61 ± 0.08, respectively, indicating partial scavenging and washout. Chemical box model simulations show that post-convection secondary formation of HCHO and H2O2 cannot explain their enhancement in the UT. A plausible explanation, in particular for the enhancement of the highly 20 soluble H2O2, is degassing from cloud droplets during freezing, which reduces the retention coefficient.