Miracle-dz/UniFAR-FTUs huggingface dataset:
The Si-tag for Immobilizing Proteins on a Silicon Device

Targeting functional proteins to specific sites on a silicon device is essential for the development of new biosensors and supramolecular assemblies. Proteins have mainly been immobilized on silica surfaces by nonspecific adsorption or covalent bond formation between readily available functional groups on protein molecules (e.g., -NH2) and complimentary coupling groups on the solid surfaces. The nonspecific nature of these usual approaches inevitably contains the following difficulties; (i) it requires chemical modification of the solid surfaces, (ii) proteins may be denatured when the interaction with the surface is too strong, (iii) it is difficult to control protein orientation. Recently, we found ribosomal protein L2 as a silica-binding protein, which can be used to immobilize fused proteins on a silicon device. Indeed, a fusion of L2 and green fluorescence protein (GFP) adsorbed to the silicon/silica particles with a Kd of 0.7 nM at pH 7.5. This fusion protein was retained on the silica surface even after washing for 24 h with a buffer containing 1 M NaCl. This L2 silica-binding tag, which we call the “Si-tag“, can be used for one-step targeting of functional proteins on silica surfaces. We also constructed a Si-tagged cell wall binding (CWB) protein and demonstrated that bacteria bound to a silicon wafer through the Si-tagged CWB.
Fragile X-associated tremor/ataxia syndrome - FXTAS

It is now clearly established that the FMR1 gene is associated with two distinct pathogenic mechanisms: loss and gain of function. The "loss of function" of the FMR1 gene leads to the absence of FMRP protein (coded by FMR1). This lack of FMRP is responsible for the fragile X syndrome (FXS), which is the most common cause of inherited mental retardation. On the other hand, the toxic "gain of function" of FMR1 is responsible for two late onset disorders: premature ovarian failure and fragile X-associated tremor/ataxia syndrome (FXTAS) which was reported for the first time in 2001. The core clinical features of FXTAS are progressive cerebellar gait ataxia and intention tremor; associated features include neuropsychiatric abnormalities, parkinsonism, autonomic dysfunction and peripheral neuropathy. Cognitive changes range from mild frontal executive and memory deficits to global dementia. Neuroradiological features of FXTAS include prominent white-matter disease in the periventricular, subcortical and middle cerebellar peduncles (MCPs) on T 2 -weighted MR imaging. The principal neuropathologic characteristic of FXTAS are eosinophilic, ubiquitin-positive inclusions located in the nuclei of neurons and astrocytes in broad distribution throughout the brain and spinal column. There is prominent white-matter involvement with patchy loss of axons, myelin and associated astroglial cells. Recent studies suggest that the penetrance and severity of the neurological disorder is a function of the number of CGG repeats; namely that the penetrance among carriers of larger premutation alleles is greater than among carriers of smaller premutation alleles. Screening for the FMR1 premutation in populations of patients with movement disorders found that the frequency of premutation alleles was 13 times greater (OR = 12.4; 95% CI: 1.6, 93.5) in patients with cerebellar ataxia (16/1049) than expected based on its prevalence in the general population (2%; 16/818 for age-of-onset >50 years of age). As the FMR1- related phenotypes expand, genetic counselling for fragile X families becomes increasingly complex. Clinicians should inform their patients that their relatives are at risk for a variety of disorders including movement disorder and premature ovarian failure. In addition, women of child-bearing age are at risk of having a child with FXS and they should systematically be referred to a geneticist.
Learning robust features from underwater ship-radiated noise with mutual information group sparse DBN

Classifying Underwater Acoustic Target(UAT) based on ship-radiated noise datasets is a small-sample-size classification problem. Generalization ability of features depending on prior knowledge and traditional signal processing is seriously restricted for lack of labeled data. Deep Belief Networks (DBN) can make use of abundant unlabeled data and extract features spontaneously, but the resulting features exhibit statistical dependencies. In this paper, we propose a feature learning model called mutual information group sparse DBN (MIGS-DBN) for ship-radiated noise. Firstly, a standard RBM is pre-trained in an unsupervised learning way, then the hidden units are grouped adaptively according to mutual information and the activation level are punished. Secondly, the improved RBMs are stacked by performing a greedy layer-wise training phase, followed by the discriminative fine-tuning to achieve the sparse representation of multilayer features. Recognition experiments on real-world ship-radiated noise show that, features learned by the proposed model can reduce the redundancy and improve classification performance significantly.
Averaging and Adding in Children's Worth Judgements

Under the normative Expected Value (EV) model, multiple outcomes are additive, but in everyday worth judgement intuitive averaging prevails. Young children also use averaging in EV judgements, leading to a disordinal, crossover violation of utility when children average the part worths of simple gambles involving independent events (Schlottmann, 2000). This study explored the origins of this averaging bias in children‘s worth judgements, assessing whether averaging also appears for riskless judgements and for other types of risky judgements. In Experiment 1, 8year-olds judged the worth of having either one or two squares of chocolates in two formally equivalent tasks: Children made additive worth judgements when chocolates varied in size, but used averaging when they varied in winning probability. Performance on the EV task was slightly more advanced when risky followed riskless judgements, with some evidence of transfer. In Experiment 2, 5-year-olds gave additive worth judgements when judging variable fractions of chocolate pies, with displays closely parallel to the spinner discs used for the gambles in Experiment 1. In Experiment 3, 5-yearolds gave additive worth judgements of gambles in which to win either one or two prizes, with alternative rather than independent probabilities of winning. Thus the overgeneralisation of averaging processes to EV judgement, while persistent, neither reflects a general difficulty with additive value judgement, nor with displays showing positive and negative information, nor with risky judgement per se. It may come into play because children have difficulty appreciating the implications of independence, apparent also in other domains. Despite such difficulty, children realize that risky game outcomes go beyond what they can see, and so may apply averaging, as default strategy for population judgement, whereas addition might be the default for judging the sample itself.
The Structure of Turbulence in Fully Developed Pipe Flow

Measurements, principally with a hot-wire anemometer, were made in fully developed turbulent flow in a 10-inch pipe at speeds of approximately 10 and 100 feet per second. Emphasis was placed on turbulence and conditions near the wall. The results include relevant mean and statistical quantities, such as Reynolds stresses, triple correlations, turbulent dissipation, and energy spectra. It is shown that rates of turbulent-energy production, dissipation, and diffusion have sharp maximums near the edge of the laminar sublayer and that there exist a strong movement of kinetic energy away from this point and an equally strong movement of pressure energy toward it.
CONFERENCE ( NRSC 2013 ) April 16 ‐ 18 , 2013 , National Telecommunication Institute , Egypt E-spline in Image Denoising Applications

B-splines caught interest of many engineering applications due to their merits of being flexible and provide a large degree of differentiability and cost/quality trade off relationship. However they have less impact with continuous time applications as they are constructed from piecewise polynomials. On the other hand, Exponential spline polynomials (E-splines) represent the best smooth transition between continuous and discrete domains as they are made of exponential segments. In this paper we present a technique for utilizing E-splines in image de-noising applications. This technique is based upon sub-band decomposition of the image through an E-spline based perfect reconstruction (PR) system. Different thresholdings are applied on the decomposition layers for de-noising purposes. Due to the selective nature of E-spline based decomposition, the performance of our E-spline based de-noising technique outperforms all other literature techniques.
TIS11 Family Proteins and Their Roles in Posttranscriptional Gene Regulation

Posttranscriptional regulation of gene expression of mRNAs containing adenine-uridine rich elements (AREs) in their 3′ untranslated regions is mediated by a number of different proteins that interact with these elements to either stabilise or destabilise them. The present review concerns the TPA-inducible sequence 11 (TIS11) protein family, a small family of proteins, that appears to interact with ARE-containing mRNAs and promote their degradation. This family of proteins has been extensively studied in the past decade. Studies have focussed on determining their biochemical functions, identifying their target mRNAs, and determining their roles in cell functions and diseases.
University of Birmingham Unfolding Kernel embeddings of graphs

In this paper, we investigate the use of manifold learning techniques to enhance the separation properties of standard graph kernels. The idea stems from the observation that when we perform multidimensional scaling on the distance matrices extracted from the kernels, the resulting data tends to be clustered along a curve that wraps around the embedding space, a behaviour that suggests that long range distances are not estimated accurately, resulting in an increased curvature of the embedding space. Hence, we propose to use a number of manifold learning techniques to compute a low-dimensional embedding of the graphs in an attempt to unfold the embedding manifold, and increase the class separation. We perform an extensive experimental evaluation on a number of standard graph datasets using the shortest-path [1], graphlet [2], random walk [3] and Weisfeiler-Lehman [4] kernels. We observe the most signiﬁcant improvement in the case of the graphlet kernel, which ﬁts with the observation that neglecting the locational information of the substructures leads to a stronger curvature of the embedding manifold. On the other hand, the Weisfeiler-Lehman kernel partially mitigates the locality problem by using the node labels information, and thus does not clearly beneﬁt from the manifold learning. Interestingly, our experiments also show that the unfolding of the space seems to reduce the performance gap between the examined kernels.
Continuous monitoring of Folsomia candida (Insecta: Collembola) in a metal exposure test.

Current recommended ecotoxicological tests with the parthenogenetic springtail Folsomia candida using standard OECD soil do not allow for continuous monitoring during the exposure period. Effects of chemicals cannot be determined until the end of the experiment (typically after 4 weeks), since the animals stay below the soil surface. In this study, F. candida were maintained on a plaster of Paris/graphite substrate for 7 weeks and were supplied with an aqueous suspension of yeast contaminated with Cd, Cu, Pb, and Zn as nitrate salts. Growth rate, time to first batch of eggs, quantity of food consumed, and the presence of graphite in the gut (a sign of avoidance of yeast) were all affected by metal contaminated diets. The relative toxicities of Cd:Cu:Pb:Zn in the yeast were 1.0:1.07:12.0:4.3, respectively (on a weight basis) with Cd being the most toxic. Internal body concentrations increased, and the concentration factor (metal concentration in F. candida/metal concentration in yeast) decreased with increasing metal exposure. In general, metals are much less toxic when added to the food of F. candida than when incorporated into soil in standard tests. It is suggested that Collembola have a greater tolerance of metals in the diet since they avoid contaminated food, and are able to excrete assimilated metals at moulting via exfoliation of the midgut epithelium where the elements are retained as part of a storage--detoxification system. The methodology described in this article allows effects on growth to be observed as early as 7 days after the beginning of the experiment.
The effects of low molecular weight dicarboxylic acids on cloud formation

The ubiquitous presence of organic compounds in tropospheric particles requires that their role in aerosol/cloud interactions be accounted for in climate models. In this paper, we present studies that investigate the hygroscopic behavior of organic compounds and their efficiency as ice nuclei. Specifically, results for soluble and partially soluble dicarboxylic acids that have been observed in atmospheric aerosol are discussed. At room temperature, we use a humidified tandem differential mobility analyzer (HTDMA) and a condensation particle counter interfaced with a cloud condensation nuclei counter to characterize the water uptake behavior of these acids. The HTDMA data agree quite well with modeled hygroscopic behavior. However, we find that some of the compounds retain water to very low humidities, never exhibiting efflorescence. The studies are extended to lower temperatures using a continuous flow ice thermal diffusion chamber to investigate the role of these species in ice nucleation at cirrus condi.
Semi-supervised CLPsych 2016 Shared Task System Submission

The 2016 CLPsych Shared Task is centered on the automatic triage of posts from a mental health forum, au.reachout. com. In this paper, we describe our method for this shared task. We used four different groups of features. These features are designed to capture stylistic and word patterns, together with psychological insights based on the Linguistic Inquiry and Word Count (LIWC) word list. We used a multinomial naive Bayes classiﬁer as our base system. We were able to boost the accuracy of our approach by extending the number of training samples using a semi-supervised approach, labeling some of the unlabeled data and extending the number training samples.
Exploring the Impact of Dynamic Mutual Influence on Social Event Participation

Nowadays, it is commonly seen that an offline social event is organized through online social network services (SNS), in this way cyber strangers can be connected in physical world. While there are some preliminary studies on social event participation through SNS, they usually have more focus on the mining of event profiles and have less focus on the social relationships among target users. In particular, the importance of dynamic mutual influence among potential event participants has been largely ignored. In this paper, we develop a novel discriminant framework, which allows to integrate the dynamic mutual dependence of potential event participants into the discrimination process. Specifically, we formulate the group-oriented event participation problem as a variant two-stage discriminant framework to capture the users’ preferences as well as their latent social connections. The experimental results on real-world data show that our method can effectively predict the event participation with a significant margin compared with several state-of-the-art baselines, which validates the hypothesis that dynamic mutual influence could play an important role in the decisionmaking process of social event participation.
Information classification using fuzzy knowledge based agents

It is possible to find any kind of useful information in the Web. However, there are serious problems in retrieving, managing and using this information, due to its vastness. Different approaches have been developed to avoid those problems (search engines, metasearch engines, spiders, softbots, intelligent agents or Web agents). This paper is based on one of these systems which uses a set of heterogeneous intelligent software agents to achieve these previous tasks. Two different agents compose the system: Web agents developed to retrieve information from a specific Web source and meta Web agents developed to select the appropriated Web agent to search the necessary information. Each Web agent retrieves, filters and stores the information from the Web to improve system performance. The meta Web agents need to represent and classify the behavior of different Web agents. In this work a fuzzy system that helps to classify the behavior of the Web agents is presented. The meta Web agent calculates the appropriateness of existing agent behavior, using different distances that are analyzed in the paper. The behavior classification is used to decide which Web agent is requested for information by the meta Web agent.
MiR-27 a-3 p promotes esophageal cancer cell proliferation via F-box and WD repeat domain-containing 7 ( FBXW 7 ) suppression

Emerging evidence has suggested that dysregulation of microRNA-27a-3p (miR-27a-3p) may contribute to tumor development and progression in various types of cancers. However, its role in esophageal cancer is still unknown. In the present study, miR-27a-3p was significantly increased in esophageal squamous cell carcinoma (ESCC) tissues and cell lines. In esophageal cancer Eca109 cells, ectopic overexpression of miR-27a-3p promoted cell proliferation, meanwhile, cell proliferation was reduced by miR-27a-3p inhibition. Further studies showed that down-regulated miR-27a-3p expression could induced cell cycle arrest at the G1/S transition. In exploring mechanisms underlying the promotive role, our results revealed that miR-27a-3p markedly inhibited the expression of F-box and WD repeat domain-containing 7 (FBXW7). FBXW7, a tumor suppressor, exhibited significantly inhibitory effect on Eca109 cell proliferation. Thus our observations suggested that miR-27a-3p functioned as a tumor suppressor by targeting FBXW7. These findings indicated that miR-27a-3p could be considered as a potential therapeutic strategy for ESCC therapy.
Molecular mechanisms of the cardiovascular protective effects of polyphenols

Epidemiological studies have reported a greater reduction in cardiovascular risk and metabolic disorders associated with diets rich in polyphenols. The antioxidant effects of polyphenols are attributed to the regulation of redox enzymes by reducing reactive oxygen species production from mitochondria, NADPH oxidases and uncoupled endothelial NO synthase in addition to also up-regulating multiple antioxidant enzymes. Although data supporting the effects of polyphenols in reducing oxidative stress are promising, several studies have suggested additional mechanisms in the health benefits of polyphenols. Polyphenols from red wine increase endothelial NO production leading to endothelium-dependent relaxation in conditions such as hypertension, stroke or the metabolic syndrome. Numerous molecules contained in fruits and vegetables can activate sirtuins to increase lifespan and silence metabolic and physiological disturbances associated with endothelial NO dysfunction. Although intracellular pathways involved in the endothelial effects of polyphenols are partially described, the molecular targets of these polyphenols are not completely elucidated. We review the novel aspects of polyphenols on several targets that could trigger the health benefits of polyphenols in conditions such as metabolic and cardiovascular disturbances.
Felt senses of self and no-self in therapy

The thesis develops Gendlin's concept of the felt sense in two directions, and introduces parallel concepts of self. It starts by examining western and eastern cultural contexts, neuroscientific conceptualisations and linguistic issues as they relate to self, using the lens of Gendlin's two ways of relating to the world interpreting according to the unit model and thinking beyond patterns, to point out conceptual confusions. Buddhist philosophy and practice are discussed as methods of undoing such conceptual confusions in order to relieve suffering, with self as an independent, stable, substantial entity being the primary example of such a confusion. Dualism is identified as the basic misconception from which suffering ensues. Non-duality is investigated as a spiritual endstate, an integral part of the goals of humanistic therapies and an intrinsic element in 'carrying forward', then compared with Gendlin's implicit intricacy, Sartre's Being-in-itself and intersubjective theories. A small qualitative study investigates what happens when felt senses of self are intentionally produced or accessed by focusing. A continuum of experiences is described, ranging from self to no-self, with trauma proving a major block to both self and no-self experiencings. The felt sense is re-defined in two ways, as an extending boundary and as a direct referent. A sense of self is also considered both as a boundary drawing exercise, and a direct referent. Self may function in either of these forms on a relative level, constructively or destructively, according to circumstances and conditions, while on an ontological level no such single entity may be proven to exist. The conclusion is drawn that self and no-self form a kind of twisting human thread, which shows, at any one moment, just one side of a duality. These sides are conceptually, rather than actually, distinct.
A new approach for high efficiency buck-boost DC/DC converters using series compensation

This paper proposes a new buck-boost DC/DC converters, which is connected in series to the power supply. The proposed circuit provides only differential voltage between the input voltage and the output voltage command. The power rating of a conventional circuit is dominated by the input voltage or the output voltage. In contrast, the voltage rating of the proposed circuit requires only the differential voltage between the input and output voltage. In addition, the series converter generates a positive and negative voltage to realize boost mode and buck mode, respectively. As a result, the power rating of the DC/DC converter can be drastically reduced. A new approach for series compensation converters is introduced in order to realize high efficiency and a reduction of power rating. Two new buck-boost converters and their control methods are proposed based on a new concept in which the proposed circuits consist of an Hbridge circuit and a power assist circuit. The H-bridge circuit is used in order to determine the polarity of the differential voltage. The power assist circuit controls the DC voltage of the H-bridge circuit depending on the output voltage command. In the proposed circuit, a flyback converter and inverting chopper are used as the power assist circuit. Simulation and experimental results are shown in order to demonstrate the advantages of the proposed converters in comparison with a conventional buck-boost converter. A maximum efficiency of 98% was obtained with the proposed circuit. The proposed circuits can decrease losses by 2/3 in comparison with a conventional buck-boost converter. Therefore, the proposed converter can realize high efficiency and down-sizing in applications that require the output voltage to be closed to the input voltage.