Miracle-dz/UniFAR-FTUs huggingface dataset:
[Addendum to the Dutch guideline for minor head/brain injury].

- After introduction of the Dutch guideline for 'Care for patients with minor head/brain injury' (LTH guideline) in 2010, the number of CT scans has increased. Some of these scans were for patients with only trivial trauma and may not have been necessary. - In addition, since this guideline was implemented, there have been changes in the use of anticoagulants and platelet aggregation inhibitors. Non-vitamin-K-dependent oral anticoagulants (NOACs) and platelet aggregation inhibitors, or combinations of these, are prescribed more often. - These two factors have led the Netherlands Society of Neurology to initiate a request for modification of the LTH guideline for adults in two ways: (a) identification of minimal or trivial trauma for which no CT scan is required and (b) inclusion of NOACs and platelet aggregation inhibitors, or combinations of these, in the guideline.
Analysis of Energy Efficient Protocols in WSN Network

: In this paper we have proposed different models for energy efficiency in Wireless Sensor Networks. We have analyzed and optimized the performance of the LEECH algorithm for different parameters. In this paper the proposed models have been applied on the 100 node network and the performance of the same has been calculated and shown with the help of results. Analysis of LEACH protocol is done using a 100-node network. It has been shown that cluster head drains the battery of that node. So in order to spread energy usage among multiple nodes, role of cluster head is rotated. Thus, a set of C nodes might elect themselves as cluster heads at time t, but at time 𝒕 + 𝒅 a new set C’ of nodes elect themselves as cluster.
Two‐stage liver transplantation: an effective procedure in urgent conditions

Montalti R, Busani S, Masetti M, Girardis M, Di Benedetto F, Begliomini B, Rompianesi G, Rinaldi L, Ballarin R, Pasetto A, Gerunda GE. Two‐stage liver transplantation: an effective procedure in urgent conditions. Clin Transplant 2010: 24: 122–126. © 2009 John Wiley & Sons A/S.
Crohn's disease-associated NOD2 variants share a signaling defect in response to lipopolysaccharide and peptidoglycan.

BACKGROUND & AIMS The NOD2 variants R702W, G908R, and L1007fsinsC are strongly associated with Crohn's disease (CD) in both European and American populations, but whether this susceptibility extends to all ethnic groups remains unknown. Except for the L1007fsinsC mutation, which produces a truncated NOD2 protein, the functional activity of the major CD-associated variants G908R and R702W is unknown. METHODS Individuals were genotyped for R702W, G908R, and L1007fsinsC. The ability of G908R, R702W, and L1007fsinsC variants in the presence and absence of P268S to confer responsiveness to lipopolysaccharide (LPS) and peptidoglycan (PGN) was determined in HEK293T kidney cells. RESULTS G908R and L1007fsinsC, but not R702W, were associated with disease susceptibility in Ashkenazi Jews. Ashkenazi Jews with CD had significantly higher allele frequency carriage of G908R and lower carriage of R702W compared with non-Jewish whites with CD. Functional studies revealed that the G908R, R702W, and L1007fsinsC variants in the presence and absence of P268S are defective in their ability to respond to bacterial LPS and PGN, whereas P268S alone exhibited wild-type activity. CONCLUSIONS R702W is not associated with susceptibility to CD in Ashkenazi Jews. The G908R, R702W, and L1007fsinsC variants share a common signaling defect in response to bacterial components, providing evidence for a unifying molecular mechanism whereby NOD2 mutations contribute to disease susceptibility.
Developmental Evidence for at Least Two Alcoholisms

The phenomena variously described as alcoholism or alcohol dependence do not emerge abruptly in adulthood; like most other chronic behavior disorders, they show themselves gradually, in bits and pieces over time. To put this matter another way, developmental variation is an intrinsic part of the etiologic process. In fact, the very concept of etiology implies a process of moving from a state involving the presence of risk to a state involving the emergence of the full-blown disease entity. The prospective study upon which we report here has as its focus the charting of this process from early childhood onward, with the expectation that tracking developmental variation within the context of a broadly drawn, multidomain database will provide clues to etiologic mechanisms for alcoholism that would not be likely to emerge without such breadth and without close monitoring of time-based variations in causal patterning over significant portions of the life course. The present paper provides an overview of one important strand of this research, which pursues the issue of multiple pathways into alcoholic risk in a variety of ways. We review the issues that led to our interest in this present evidence that strongly encouraged continuation of this line of inquiry, and last, report some preliminary findings among both alcoholic adults as well as their offspring which indicate that the conception of a single alcoholism is no longer a tenable etiologic hypothesis.
Cryogenic protection of oocytes with antifreeze proteins

Proteins belonging to a family of compounds known as “antifreeze proteins” interact with occytes and protect the oolemma from damage at cryogenic temperatures. Experiments were performed with pig oocytes rapidly cooled to cryogenic temperatures in vitrifying solutions with and without antifreeze proteins. Four different types of antifreeze polypeptides and glycoproteins were tested. The integrity of the oolemma was examined with Fluoroscein Diacetate (FDA) staining and morphological examinations. Results show that the pig oocyte oolemma is a primary site of injury during exposure to low temperatures and that all the different proteins have a similar ability to interact with and protect the oolemma. Our results may be important in developing solutions for long‐term preservation of oocytes at cryogenic temperatures (cryopreservation). © 1993 Wiley‐Liss, Inc.
Two‐step OFFGEL approach for effective peptide separation compatible with iTRAQ labeling

Shotgun proteomic analyses are increasingly becoming methods of choice for complex samples. The development of effective methods for fractionating peptides to reduce the complexity of the sample before mass analysis is a key point in this strategy. The OFFGEL technology has recently become a tool of choice in proteomic analysis at peptide level. This OFFGEL electrophoresis (OGE) approach allows the in‐solution separation of peptides from various biological sources by isoelectric focusing in highly resolved 24 fractions. It was also demonstrated that OGE technology is a filtering tool for pI‐based validation of peptide identification. As peptide OGE is compatible with iTRAQ labeling, OGE is finding valuable applications in quantitative proteomics as well. The aim of this study is to explain a new 2D‐OGE approach that improves the proteomic coverage of complex mixtures such as colorectal cell line lysates, and which is compatible with iTRAQ labeling.
ELF 4 is a phytochrome-regulated component of a negative-feedback loop involving the central oscillator components CCA 1 and LHY

Evidence has been presented that a negative transcriptional feedback loop formed by the genes CIRCADIAN CLOCK ASSOCIATED (CCA1), LATE ELONGATED HYPOCOTYL (LHY) and TIMING OF CAB (TOC1) constitutes the core of the central oscillator of the circadian clock in Arabidopsis. Here we show that these genes are expressed at constant, basal levels in dark-grown seedlings. Transfer to constant red light (Rc) rapidly induces a biphasic pattern of CCA1 and LHY expression, and a reciprocal TOC1 expression pattern over the first 24 h, consistent with initial induction of this synchronous oscillation by the light signal. We have used this assay with wild-type andmutant seedlings to examine the role of these oscillator components, and to determine the function of ELF3 and ELF4 in their light-regulated expression. The data show that whereas TOC1 is necessary for light-induced CCA1/LHY expression, the combined absence of CCA1 and LHY has little effect on the pattern of light-induced TOC1 expression, indicating that the negative regulatory arm of the proposed oscillator is not fully functional during initial seedling de-etiolation. By contrast, ELF4 is necessary for light-induced expression of both CCA1 and LHY, and conversely, CCA1 and LHY act negatively on light-induced ELF4 expression. Together with the observation that the temporal light-induced expression profile of ELF4 is counter-phased to that of CCA1 and LHY and parallels that of TOC1, these data are consistent with a previously unrecognized negative-feedback loop formed by CCA1/LHY and ELF4 in a manner analogous to the proposed CCA1/LHY/ TOC1 oscillator. ELF3 is also necessary for light-induced CCA1/LHY expression, but it is neither light-induced nor clock-regulated during de-etiolation. Taken together, the data suggest (a) that ELF3, ELF4, and TOC1 all function in the primary, phytochrome-mediated light-input pathway to the circadian oscillator in Arabidopsis; and (b) that this oscillator consists of two or more interlocking transcriptional feedback loops that may be differentially operative during initial light induction and under steady-state circadian conditions in entrained green plants.
Fast model predictive control

This thesis develops efficient optimization methods for Model Predictive Control (MPC) to enable its application to constrained systems with fast and uncertain dynamics. The key contribution is an active set method which exploits the parametric nature of the sequential optimization problem and is obtained from a dynamic programming formulation of the MPC problem. This method is first applied to the nominal linear MPC problem and is successively extended to linear systems with additive uncertainty and input constraints or state/input constraints. The thesis discusses both offline (projection-based) and online (active set) methods for the solution of controllability problems for linear systems with additive uncertainty. The active set method uses first-order necessary conditions for optimality to construct parametric programming regions for a particular given active set locally along a line of search in the space of feasible initial conditions. Along this line of search the homotopy of optimal solutions is exploited: a known solution at some given plant state is continuously deformed into the solution at the actual measured current plant state by performing the required active set changes whenever a boundary of a parametric programming region is crossed during the line search operation. The sequence of solutions for the finite horizon optimal control problem is therefore obtained locally for the given plant state. This method overcomes the main limitation of parametric programming methods that have been applied in the MPC context which usually require the offline precomputation of all possible regions. In contrast to this the proposed approach is an online method with very low computational demands which efficiently exploits the parametric nature of the solution and returns exact local DP solutions. The final chapter of this thesis discusses an application of robust tube-based MPC to the nonlinear MPC problem based on successive linearization.
Distributionally Robust Optimization Techniques in Batch Bayesian Optimization

We propose a novel, theoretically-grounded, acquisition function for batch Bayesian optimisation informed by insights from distributionally robust optimization. Our acquisition function is a lower bound on the well-known Expected Improvement function – which requires a multi-dimensional Gaussian Expectation over a piece-wise afﬁne function – and is computed by evaluating instead the best-case expectation over all probability distributions consistent with the same mean and variance as the original Gaussian distribution. We show that, unlike alternative approaches including Expected Improvement, our proposed acquisition function avoids multi-dimensional integrations entirely, and can be calculated exactly as the solution of a convex optimization problem in the form of a tractable semideﬁnite program (SDP). Moreover, we prove that the solution of this SDP also yields exact numerical derivatives, which enable efﬁcient optimisation of the acquisition function. Numerical results suggest that our acquisition function performs very similar to the computationally intractable exact Expected Improvement and considerably better than other heuristics.
Conditional Sampling Distributions for Coalescent Models Incorporating Recombination

With the volume of available genomic data increasing at an exponential rate, we have unprecedented ability to address key questions in molecular evolution, historical demography, and epidemiology. Central to such investigations is population genetic inference, which seeks to quantify the genetic relationship of two or more individuals provided a stochastic model of evolution. A natural and widely-used model of evolution is Kingman's coalescent (Kingman, 1982), which explicitly describes the genealogical relationship of the individuals, with various extensions to account for complex biological phenomena. Statistical inference under the coalescent, however, remains a challenging computational problem. Modern population genetic methods must therefore realize a balance between computational efficiency and fidelity to the underlying model. A promising class of such methods employ the conditional sampling distribution (CSD). The CSD describes the probability of sampling an individual with a particular genomic sequence, provided that a collection of individuals from the population, and their corresponding sequences, has already been observed. Critically, the true CSD is generally inaccessible, and it is therefore necessary to use an approximate CSD in its place; such an approximate CSD is ideally both accurate and computationally efficient. In this thesis, we undertake a theoretical and algorithmic investigation of the CSD for coalescent models incorporating mutation, homologous (crossover) recombination, and population structure with migration.Motivated by the work of De Iorio and Griffiths (2004), we propose a general technique for algebraically deriving an approximate CSD directly from the underlying population genetic model. The resulting CSD admits an intuitive coalescent-like genealogical interpretation, explicitly describing the genealogical relationship of the conditionally sampled individual to the previously sampled individuals. We make use of the genealogical interpretation to introduce additional approximations, culminating in the sequentially Markov CSD (SMCSD), which models the conditional genealogical relationship site-by-site across the genomic sequence. Critically, the SMCSD can be cast as a hidden Markov model (HMM), for which efficient algorithms exist; by further specializing the general HMM methods to the SMCSD, we obtain optimized algorithms with substantial practical benefit. Finally, we empirically validate both the accuracy and computational efficiency of our proposed CSDs, and demonstrate their utility in several applied contexts.
Classification of High-Dimensional Data with Ensemble of Logistic Regression Models

A classification method is developed based on ensembles of logistic regression models, with each model fitted from a different set of predictors determined by a random partition of the feature space. The proposed method enables class prediction by an ensemble of logistic regression models for a high-dimensional data set, which is impossible by a single logistic regression model due to the restriction that the sample size needs to be larger than the number of predictors. The proposed classification method is applied to gene expression data on pediatric acute myeloid leukemia (AML) patients to predict each patient's risk for treatment failure or relapse at the time of diagnosis. Hence, specific prognostic biomarkers can be used to predict outcomes in pediatric AML and formulate individual risk-adjusted treatment. Our study shows that the proposed method is comparable to other widely used models in generalized accuracy and is significantly improved in balance between sensitivity and specificity. The proposed ensemble algorithm enables the standard classification model to be used for classification of high-dimensional data.
Optimal frequency of administration of pamidronate in patients with hypercalcaemia of malignancy

OBJECTIVE Hypercaicaemia of malignancy (HM) is a common metabolic complication associated with cancer. The hypocaicaemic effects of medications used to reduce serum calcium levels in HM are short lived and relapse in hypercaicaemia is not uncommon. Pamidronate is one of the most commonly used bisphosphonates in the treatment of HIM but there are no specific guidelines for the frequency of use of this drug in recurrent hypercalcaemia. This study was conducted to assess the optimum frequency of pamidronate therapy necessary to maintain normocalcaemia in patients with HM.
Piezoelectric vs. Capacitive Based Force Sensing in Capacitive Touch Panels

High sensitivity force sensing is a desirable function of capacitance touch screen panels. In this paper, we report on a dynamic force detection technique by utilizing piezoelectric materials. The force-voltage responsivities are investigated for four widely used stack-ups, with various panel thicknesses and touch locations. Based on the theoretical analysis and simulation results, the maximum responsivity and the signal-to-noise ratio are achieved at 0.42 V/N and 59.1 dB, respectively. The proposed technique implements force sensing successfully, enhancing the human-machine interactivity experience.
Characterization of the dual start motif of a class II holin gene

Holins are small membrane proteins that, at a genetically programmed time in a bacteriophage infective cycle, allow bacteriolytic enzymes, or endolysins, to escape to the periplasm and to attack the cell wall. Most holins fall into two sequence classes, I and II, based on the number of potential transmembrane domains (three for class I and two for class II). The prototype class I holin gene, S λ, has a dual start motif and encodes not only the effector holin, Sλ105, but also an inhibitor, Sλ107, with a Met–Lys … extension at the terminus. The prototype class II holin gene of phage 21, S 21, begins with the motif Met–Lys–Ser–Met … , and a potential RNA secondary structure overlaps the Shine–Dalgarno sequence. Here, we demonstrate that (i) two protein products are elaborated from S 21, S2171 and S2168; (ii) the shorter product is required for lysis; (iii) the longer product, S2171, inhibits S 21 function; and (iv) the Lys‐2 residue is important for the inhibitor function. Moreover, the RNA stem–loop structure is involved in the downregulation of S2171 synthesis. However, our results suggest that, in S 21, different segments of the single consensus Shine–Dalgarno sequence serve the two translational starts. These results show that the dual start motifs of class II holin genes are functionally homologous to those of class I holin genes.
Towards efficient statistical parsing using lexicalized grammatical information

For a long time, the goal of wide-coverage natural language parsers had remained elusive. Much progress has been made recently, however, with the development of lexicalized statistical models of natural language parsing. Although lexicalized tree adjoining grammar (TAG) is a lexicalized grammatical formalism whose development predates these recent advances, its application in lexicalized statistical parsing models remains relatively unstudied. This is despite the fact that TAG offers tangible benefits for such an application, most notably that certain efficient (linear-time) statistical parsing disambiguation models—supertagging—can be easily implemented given that a TAG is available. The central aim of this thesis is to develop strategies and resources in order to make supertagging more effective. While all of these strategies and resources can be used by supertagging models, many can also be used for any statistical processing model of TAG, including models of full parsing and also natural language generation. The first part of the thesis concerns methods for improving the accuracy of supertagging in order to enhance its viability for full parsing. Previous supertagging models have achieved about 90% supertagging accuracy. While this is sufficient for some applications, it is inadequate for full parsing. One possible solution is to first determine what inadequately-explored features might be useful in supertagging and to then develop frameworks that use these features effectively. This approach leads me to develop supertagging models which achieve a significant improvement in accuracy over previous models. Despite these advances, results indicate that it may prove difficult to increase accuracy even further to the point where supertagging is
Viral aggregation: quantitation and kinetics of the aggregation of poliovirus and reovirus

The aggregation of poliovirus and reovirus was followed in buffers at various pH values by means of a single particle analysis (SPA) test. The SPA test used here was modified from the original test reported earlier to prevent disaggregation of virus clumps from invalidating the results. The modified SPA test demonstrated that the efficiency of aggregation, which is a measure of the percentage of collisions which are effective in producing an aggregate, may vary widely depending on the conditions in which the virus is placed. The modified SPA test was also used to demonstrate that the kinetic features of viral aggregation follow the classical laws of colloid particle aggregation, which in turn are solely dependent upon diffusion of the particles as caused by brownian motion.
Apathy in Parkinson's disease: Diagnostic and etiological dilemmas

About one‐third of patients with Parkinson's disease (PD) are diagnosed with apathy in cross‐sectional studies. However, once patients with concomitant depression and dementia are excluded, the frequency of apathy drops to 5% to 10%. Several scales have been recommended to rate apathy in PD, but specific psychiatric interviews have not been developed, and recently proposed standardized diagnostic criteria are still in the validation process. Most studies assessing the association between subthalamic deep brain stimulation (STN‐DBS) and apathy have reported a relative increase in the frequency and severity of apathy, although discrepant findings have also been reported. Several mechanisms to explain apathy in PD have been proposed, from dopaminergic imbalances in frontal‐basal ganglia circuits to dysfunction of nondopaminergic circuits and the cingulate gyrus. Future studies should provide reliable and valid instruments to diagnose apathy in PD, and should examine the mechanism of apathy accounting for relevant confounders, such as depression and cognitive deficits, and important contextual factors. Finally, treatment for apathy in PD should not be restricted to psychoactive drugs, but should also include nonpharmacological techniques such as psychotherapy and occupational therapy. © 2012 Movement Disorder Society