Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive mutational scanning of a kinase in vivo reveals substrate-dependent fitness landscapes

Deep mutational scanning has emerged as a promising tool for mapping sequence–activity relationships in proteins, ribonucleic acid and deoxyribonucleic acid. In this approach, diverse variants of a sequence of interest are first ranked according to their activities in a relevant assay, and this ranking is then used to infer the shape of the fitness landscape around the wild-type sequence. Little is currently known, however, about the degree to which such fitness landscapes are dependent on the specific assay conditions from which they are inferred. To explore this issue, we performed comprehensive single-substitution mutational scanning of APH(3′)II, a Tn5 transposon-derived kinase that confers resistance to aminoglycoside antibiotics, in Escherichia coli under selection with each of six structurally diverse antibiotics at a range of inhibitory concentrations. We found that the resulting local fitness landscapes showed significant dependence on both antibiotic structure and concentration, and that this dependence can be exploited to guide protein engineering. Specifically, we found that differential analysis of fitness landscapes allowed us to generate synthetic APH(3′)II variants with orthogonal substrate specificities.
Dissimilarity in patients' and spouses' representations of chronic illness: Exploration of relations to patient adaptation

Abstract In this cross-sectional study, the illness representations of patients suffering from Chronic Fatigue Syndrome (n = 49)and Addison's Disease (n = 52) and those of their spouses were compared. Couples generally held similar views with regard to the dimensions of illness identity and cause but disagreed on time-line. control/cure. and consequences of the illness. The effects of such dissimilarity in a couple's illness representations on the patient's coping behavior and adaptation were then examined. Dissimilarity was found to have a weak impact on coping and a rather strong impact on adaptive outcome. In general. minimization of the disorder's seriousness by the spouse was found to have a negative impact on adaptive outcome, although this effect differed with the dimension of illness representation and the type of illness. These results demonstrate the importance of the role of significant others and their beliefs for patient's coping and adaptation with chronic illness.
Control of Ca2+ influx by cannabinoid and metabotropic glutamate receptors in rat cerebellar cortex requires K+ channels

1 In the rodent cerebellum, both presynaptic CB1 cannabinoid receptors and presynaptic mGluR4 metabotropic glutamate receptors acutely depress excitatory synaptic transmission at parallel fibre‐Purkinje cell synapses. Using rat cerebellar slices, we have analysed the effects of selective CB1 and mGluR4 agonists on the presynaptic Ca2+ influx which controls glutamate release at this synapse. 2 Changes in presynaptic Ca2+ influx were determined with the Ca2+‐sensitive dyes fluo‐4FF AM or fluo‐3 AM. Five stimulations delivered at 100 Hz or single stimulations of parallel fibres evoked rapid and reproducible transient increases in presynaptic fluo‐4FF or fluo‐3 fluorescence, respectively, which decayed to prestimulus levels within a few hundred milliseconds. Bath application of the selective CB1 agonist WIN55,212‐2 (1 μm) markedly reduced the peak amplitude of these fluorescence transients. This effect was fully reversed by the selective CB1 antagonist SR141716‐A (1 μm). 3 Bath application of the selective mGluR4 agonist l‐AP4 (100 μm) also caused a transient decrease in the peak amplitude of the fluorescence transients evoked by parallel fibre stimulation. 4 Bath application of the potassium channel blocker 4‐AP (1 mm) totally prevented both the WIN55,212‐2‐ and the l‐AP4‐induced inhibition of peak fluorescence transients evoked by parallel fibre stimulation. 5 The present study demonstrates that activation of CB1 and mGluR4 receptors inhibits presynaptic Ca2+ influx evoked by parallel fibre stimulation via the activation of presynaptic K+ channels, suggesting that the molecular mechanisms underlying this inhibition involve an indirect inhibition of presynaptic voltage‐gated Ca2+ channels rather than their direct inhibition.
Universal Bayesian Measures and Universal Histogram Sequences

Consider universal data compression: the length $l(x^n)$ of sequence $x^n\in A^n$ with finite alphabet $A$ and length $n$ satisfies Kraft's inequality over $A^n$, and $-\frac{1}{n}\log \frac{P^n(x^n)}{Q^n(x^n)}$ almost surely converges to zero as $n$ grows for the $Q^n(x^n)=2^{-l(x^n)}$ and any stationary ergodic source $P$. In this paper, we say such a $Q$ is a universal Bayesian measure. We generalize the notion to the sources in which the random variables may be either discrete, continuous, or none of them. The basic idea is due to Boris Ryabko who utilized model weighting over histograms that approximate $P$, assuming that a density function of $P$ exists. However, the range of $P$ depends on the choice of the histogram sequence. The universal Bayesian measure constructed in this paper overcomes the drawbacks and has many applications to infer relation among random variables, and extends the application area of the minimum description length principle.
A new multilevel DC-DC boost converter for fuel cell based power system

This paper presents a system model of fuel cell based distributed generation systems (DGS) in a standalone AC power supply system. Non-isolated high step-up DC-DC converters are required widely in the industrial applications. Many of these conventional DC-DC converters have the disadvantages of operating at high duty-cycle, high switch voltage stress and high diode peak current. A three-level step-up converter is implemented to boost the fuel cell stack voltage of 90V to 340V. This high DC link voltage is fed to the voltage source inverter and interfaced with the load. Two feedback control loops are designed to make the system operate in stable conditions. This system configuration is suitable for low-power applications. The Performance of the developed system is analyzed in MATLAB/Simulink environment under steady state and transient conditions.
Combining machine readable lexical resources and bilingual corpora for broad word sense disambiguation

This paper describes a new approach to word sense disambiguation (WSD) based on automatically acquired "word sense division. The semantically related sense entries in a bilingual dictionary are arranged in clusters using a heuristic labeling algorithm to provide a more complete and appropriate sense division for WSD. Multiple translations of senses serve as outside information for automatic tagging of bilingual corpora and acquisition of WSD rules. We describe and implement a WSD method using the English-Chinese bilingual version (LecDOCE) of the Longman Dictionary of Contemporary English (LDOCE). For this purpose, we draw on information about topics and topical sets in the Longman Lexicon of Contemporary English (LLOCE) to represent and disambiguate LecDOCE senses. Example sentences and their translations from LecDOCE are employed as training materials for WSD, while further examples from the Brown corpus are used for testing. Quantitative results of disambiguating 12 words are also presented.
O blood group as an indicator for abdominal aortic aneurysm.

OBJECTIVE An aortic aneurysm is a general term for an enlargement (dilation) of the aorta to greater than 1.5 times normal size. Abdominal aortic aneurysm (AAA) primarily affects the population older than 50 years, with a prevalence of approximately 5%. There are a few theories about AAA etiology. Interest in the relationship between blood type and vascular disease has been established. The aim of our study is to evaluate distribution of blood-groups among the patients with abdominal aortic aneurysm (AAA) as well as to identify any kind of relationship between blood type and AAA. MATERIALS AND METHODS The design of our research is combination of retrospective and prospective case-control study in a sample of population of Montenegro. Statistical analysis was performed in SPPS v 20.0, using the chi-square test for independent samples, with the probability level at p < 0.05 as significant, and p < 0.01 as highly significant. RESULTS O blood group was the most frequent among the examination group (53.11%), and A blood group was the most frequent among group without AAA (43.22%). Presence of AAA in individuals with O blood type was 1.46 higher than for the other blood types. CONCLUSIONS This finding leads us to suspect that O blood type can be indicator for AAA.
Frankenstein Classiiers: Some Experiments

We present some empirical results on the use of two methods for integrating diierent classiiers into a hybrid classiier that should perform better than each of its constituent classiiers. The main point of these methods is that instead of combining full classiiers, they combine pieces of them. One of the methods is based on ROC analysis; the other is based on augmenting the data with features derived from earlier learned classiiers. Experimental results are presented that suggest that these approaches can yield improvements over combining full classiiers.
Selection Into Mental Health Court

How defendants are selected into mental health courts (MHC) is central to issues of fairness, efficacy, and successful program replication. Only recently has empirical research started to examine MHC selection, revealing a multi-stage process with multiple decision makers and multiple variables. In this study, we use classification and regression tree analysis (CART) to examine the variables suggested in recent research to predict selection into MHC. The analysis includes legal and diagnostic variables, treatment history, measures of treatability, motivation to change, violence risk, and symptom severity. We find that the MHC is more likely to accept defendants who did not have warrants issued for their arrest, who had diagnoses other than depression, and who did not report using illegal drugs around the time of their admission. Symptom severity and motivation to treatment also predict MHC admission, with their effects contingent on defendants’ statuses on other variables.
Maximum-Likelihood Digital Data Sequence Estimation Over the Gaussian Channel with Unknown Carrier Phase

We consider the problem of simultaneous ML estimation of data and carrier phase from a linear suppressed-carrier modulated signal received in the presence of additive white Gaussian noise. The ML detector of the data sequence is derived, and its error probability performance is analyzed. The result shows that the performance loss due to the unknown carrier phase can be reduced by increasing the sequence length. A suboptimum decision-aided subsequence-by-subsequence detector whose complexity does not increase exponentially with sequence length is proposed, and its performance is analyzed.
Genetic susceptibility to lead poisoning.

Major strides have been taken in the regulation of lead intoxication in the general population, but studies using genetic markers of susceptibility to environmental toxicants raise the question of whether genes can make certain individuals more vulnerable to environmental toxins such as lead. At least three polymorphic genes have been identified that potentially can influence the bioaccumulation and toxicokinetics of lead in humans. The first gene to be discussed in this review is the gene coding for delta-aminolevulinic acid dehydratase (ALAD), an enzyme of heme biosynthesis, that exists in two polymorphic forms. The resulting isozymes have been shown to affect the blood and bone lead levels in human populations. The effects of ALAD in lead intoxication have also been studied in laboratory mice that differ in the genetic dose for this enzyme. The second gene reviewed here is the vitamin D receptor (VDR) gene. The VDR is involved in calcium absorption through the gut and into calcium-rich tissues such as bone. Recent findings suggest that VDR polymorphism may influence the accumulation of lead in bone. Finally, the third gene to be discussed here that may influence the absorption of lead is the hemochromatosis gene coding for the HFE protein. The presence of mutations in the HFE gene leads to hemochromatosis in homozygotic individuals. Because of the associations between iron and lead transport, it is possible that polymorphisms in the HFE gene may also influence the absorption of lead, but this has not yet been studied. More studies will be needed to define the role of these genes in lead intoxication. ImagesFigure 2Figure 4
Sound Source Separation Using Shifted Non-Negative Tensor Factorisation

Recently, shifted non-negative matrix factorisation was developed as a means of separating harmonic instruments from single channel mixtures. However, in many cases two or more channels are available, in which case it would be advantageous to have a multichannel version of the algorithm. To this end, a shifted non-negative tensor factorisation algorithm is derived, which extends shifted non-negative matrix factorisation to the multi-channel case. The use of this algorithm for multi-channel sound source separation of harmonic instruments is demonstrated. Further, it is shown that the algorithm can be used to perform non-negative tensor deconvolution, a multi-channel version of non-negative matrix deconvolution, to separate sound sources which have time evolving spectra from multi-channel signals
in Wireless Sensor Networks

While the size and heterogeneity of wireless sensor networks conﬁrm the need and beneﬁt of group communication, an intelligent approach that exploits the interaction pattern and network context is still missing. This paper introduces sensor middleware to dynamically select the most eﬃcient alternative from a set of group communication mechanisms. The proposed solution leverages on an empirical analysis of the ODMRP multicast protocol and was evaluated by a proof-of-concept prototype running on the SunSPOT platform. Results show that network overhead is considerably reduced when using the sensor middleware for software deployment
The impact of group pseudo-guessing parameter differences on the detection of uniform and nonuniform DIF

Differential item functioning (DIF) is an important aspect of item development and validity assessment. Traditionally DIF is divided into two broad types, focusing on conditional group differences of the item difficulty (uniform DIF) and discrimination (nonuniform DIF) parameters. Relatively little attention has been given to group differences on the probability of answering an item correctly due to chance. The goal of this study was to investigate the influence of such group differences on the detection of uniform and nonuniform DIF, and on the accuracy of the estimation of item difficulty and discrimination parameters. Results demonstrate that when groups differed on the pseudo-guessing parameter in a 3 parameter item response theory model, Type I error rates for both uniform and nonuniform DIF were elevated, and that these differences appear to be due to parameter estimation bias for both item difficulty and discrimination. Implications of these results are discussed.
The Construct of Webflow for Capturing the Web UserExperience

In his visionary book, Mihaly Csikszentmihalyi [2] describes the construct of flow as the holistic sensation that people feel when they act with total involvement. Hoffman and Novak [6] take a more serene approach and suggest flow for studying consumer behavior in the context of electronic commerce. More recently, there has been a growing interest towards using the flow concept for understanding user experience in information systems [see, e.g., 9, 8, 7]. Flow is a state which occurs when navigating in an information space and which is intrinsically enjoyable, selfreinforcing and accompanied by a loss of self-consciousness; it can exist in both experimental and goal-oriented types of behavior [5]. As a measurable concept, flow can be inferred from its antecedents and consequences. A primary antecedent condition that is necessary for the flow state to be experienced is that skills and challenges are perceived to be congruent and above a critical threshold. If the skills of the users are high, but the challenges are low, (s)he may fall into boredom, while if their challenges are high, but the skills are low, they may fall into anxiety. If both the challenges and skills are too low, users may fall into apathy. Oinas-Kukkonen [11] has modified the general flow concept into a Web-specific construct: Webflow is an optimal perceived user experience which improves a web user’s orientation and navigational use, as well as vice versa, and which is predicted by balanced user skills and the feeling of the web to be enjoyably challenging, the feeling of being in control of web use, and the perceived ease of use and usefulness of the web.
Load balancing techniques for extending smart metering system lifetime

In smart metering systems, when the density of node is high or distance of communication range is large, the adjacent node number becomes large. If routing based on the number of hop from the sink node is used in such a network, the deviation of load will become large and it will shorten the network lifetime, also degrades other network performance. In this paper, we proposed the techniques solving the above-mentioned problem as routing technique and intermittent interval control technique. The sender node control reduces differences in load and throughput resulting from topology by bypassing to sideward nodes. In the receiver node control, data reception probability is controlled by adjusting the intermittent interval. Simulation results show that proposal technique prolonged the network lifetime by about 53%, and reduced the average delay time by about 21%, comparing with existing method.
Sophisticated Offline Analysis of Teams of Autonomous Mobile Robots

Debugging control software for an autonomous mobile robot is a dif? cult and time consuming task. But it gets even harder, when analyzing a whole team of robots and their team behavior. The quality of the robots" decisions based on their current knowledge cannot be judged anymore by merely looking at their actions from the outside. In this paper an approach for collecting intrinsic and extrinsic data of a team of robots during full operation and analyzing this data of? ine is described. Since the amount of data to be collected is quite large a method for automated and semi-automated analysis is shown - making it possible to detect known problems in an automated process and mark potentially interesting events for manual review. Furthermore a solution to reuse existing single robot debugging tools on teams of robots, without rewriting each tool, is presented.
Leaf identification using morphology and structural decomposition

This article presents a novel method of classification of plants using their leaves. Major plant species have unique leaves which are different from each other by features as shape and texture. The primary step for the identification is detection of the edges of plant leaves which is done by Otsu's algorithm, texture features from Gray Level Cooccurrence Matrix and binary morphology. We propose a method of structural decomposition of the edges which extracts the structural signatures and quantifies the features which are independent of leaf size and orientation. This algorithm has been tested for the images of 40 plant leaves of 10 different species and it gives an accuracy rate of 67.5%.
Video Conferences through the Internet: How to Survive in a Hostile Environment

This paper analyzes and compares two different video conference solutions, widely used in corporate and home environments, with a special focus on the mechanisms used for adapting the traffic to the network status. The results show how these mechanisms are able to provide a good quality in the hostile environment of the public Internet, a best effort network without delay or delivery guarantees. Both solutions are evaluated in a laboratory, where different network impairments (bandwidth limit, delay, and packet loss) are set, in both the uplink and the downlink, and the reaction of the applications is measured. The tests show how these solutions modify their packet size and interpacket time, in order to increase or reduce the sent data. One of the solutions also uses a scalable video codec, able to adapt the traffic to the network status and to the end devices.
Net bundles over posets and K-theory

We continue studying net bundles over partially ordered sets (posets), defined as the analogues of ordinary fibre bundles. To this end, we analyze the connection between homotopy, net homology and net cohomology of a poset, giving versions of classical Hurewicz theorems. Focusing our attention on Hilbert net bundles, we define the K-theory of a poset and introduce functions over the homotopy groupoid satisfying the same formal properties as Chern classes. As when the given poset is a base for the topology of a space, our results apply to the category of locally constant bundles.
Answering Reading Comprehension Items without Passages on the SAT

Performance of college undergraduates on the Reading Comprehension task of the SAT was well above chance when the passages were deleted. Moreover, examinees and test items performed similarly with or without the passages: individual performance correlated with verbal SAT score, and the difficulty of items belonging to a passage correlated with a normative measure based on equated delta. The findings demonstrate that the Reading Comprehension task substantially measures factors unrelated to reading comprehension.
A (slightly) faster algorithm for klee's measure problem

Given <i>n</i> axis-parallel boxes in a fixed dimension <i>d</i> ≥ 3, how efficiently can we compute the volume of the union? This standard problem in computational geometry, commonly referred to as <i>Klee's measure problem</i>, can be solved in time <i>O</i>(<i>n<sup>d/2</sup></i> log <i>n</i>) by an algorithm of Overmars and Yap (FOCS 1988). We give the first (albeit small) improvement: our new algorithm runs in time <i>n<sup>d/2</sup></i>2<sup><i>O</i></sup>(log<sup>*</sup><i>n</i>), where log<sup>*</sup> denotes the iterated logarithm. For the related problem of computing the <i>depth</i> in an arrangement of <i>n</i> boxes, we further improve the time bound to near <i>O</i>(<i>n<sup>d/2</sup></i> log<i><sup>d/2-1</sup></i> <i>n</i>), ignoring log\log <i>n</i> factors. Other applications and lower-bound possibilities are discussed. The ideas behind the improved algorithms are simple.
Hierarchical information visualization using enccon model

This paper describes a new efficient approach for visualizing large hierarchical information. Our technique is based on the connection + enclosure visualization model [1] from which the area division is used for the recursive positioning of nodes, while a node-link diagram is still drawn to present the entire hierarchical structure. We inherit the advantages of Space-Optimized (SO) Tree technique [1] that can enhance the usability of display space by using area division. However, we replace a set of polygons used in SO Tree by a set of rectangles for the area division. This not only decreases the computation cost in calculating geometrical polygons, but also greatly reduces the human perceptual and cognitive loads spent on understanding the underlying hierarchical structure. We use semantic zooming technique to enlarge a particular viewing area and filter out the rest of structure that is less interested. The navigation is accommodated by animation in order to preserve the mental map [2].