Miracle-dz/UniFAR-FTUs huggingface dataset:
Tissue oxygenation response to mild hypercapnia during cardiopulmonary bypass with constant pump output.

BACKGROUND Tissue oxygenation is the primary determinant of wound infection risk. Mild hypercapnia markedly improves cutaneous, subcutaneous (s.c.), and muscular tissue oxygenation in volunteers and patients. However, relative contributions of increased cardiac output and peripheral vasodilation to this response remains unknown. We thus tested the hypothesis that increased cardiac output is the dominant mechanism. METHODS We recruited 10 ASA III patients, aged 40-65 yr, undergoing cardiopulmonary bypass for this crossover trial. After induction of anaesthesia, a Silastic tonometer was inserted s.c. in the upper arm. S.C. tissue oxygen tension was measured with both polarographic electrode and fluorescence-based systems. Oximeter probes were placed bilaterally on the forehead to monitor cerebral oxygenation. After initiation of cardiopulmonary bypass, in random order patients were exposed to two arterial CO(2) partial pressures for 30 min each: 35 (normocapnia) or 50 mm Hg (hypercapnia). Bypass pump flow was kept constant throughout the measurement periods. RESULTS Hypercapnia during bypass had essentially no effect on Pa(CO(2)) , mean arterial pressure, or tissue temperature. Pa(CO(2)) and pH differed significantly. S.C. tissue oxygenation was virtually identical during the two Pa(CO(2)) periods [139 (50-163) vs 145 (38-158), P=0.335] [median (range)]. In contrast, cerebral oxygen saturation (our positive control measurement) was significantly less during normocapnia [57 (28-67)%] than hypercapnia [64 (37-89)%, P=0.025]. CONCLUSIONS Mild hypercapnia, which normally markedly increases tissue oxygenation, did not do so during cardiopulmonary bypass with fixed pump output. This suggests that hypercapnia normally increases tissue oxygenation by increasing cardiac output rather than direct dilation of peripheral vessels.
Statistical Reliability for Energy Efficient Data Streaming in Wireless Sensor Networks

A common application of wireless sensor networks (WSN) is streaming sensed data from multiple sensors to one or more sink nodes. Typical WSN deployments are in unattended hostile fields where link packet error rate may vary within 1-70% and path length could be up to tens of hops. Field experiments also reveal that channel error rate fluctuate within a short time scale. To cope with such harsh conditions, we propose a new notion of statistically reliable transport protocol is introduced; and the energy-efficiency of a comprehensive set of statistically reliable data delivery protocols are analyzed. Our analysis reveals that selective repeat hop-by-hop ARQ (SR) is the most efficient protocol across the board. However, for WSN where SR is infeasible due to buffer and processing constraints, a new adaptive hybrid protocol is proposed, which is the most energyefficient protocol. The hybrid protocol starts with streaming a larger than required sensed data without recovery until some threshold hop; then it switches to implicit send-and-wait hopby-hop ARQ. Detailed NS2 simulation and a field experiment confirm our theoretical findings.
MYB Transcription Factors in Chinese Pear (Pyrus bretschneideri Rehd.): Genome-Wide Identification, Classification, and Expression Profiling during Fruit Development

The MYB family is one of the largest families of transcription factors in plants. Although, some MYBs were reported to play roles in secondary metabolism, no comprehensive study of the MYB family in Chinese pear (Pyrus bretschneideri Rehd.) has been reported. In the present study, we performed genome-wide analysis of MYB genes in Chinese pear, designated as PbMYBs, including analyses of their phylogenic relationships, structures, chromosomal locations, promoter regions, GO annotations, and collinearity. A total of 129 PbMYB genes were identified in the pear genome and were divided into 31 subgroups based on phylogenetic analysis. These PbMYBs were unevenly distributed among 16 chromosomes (total of 17 chromosomes). The occurrence of gene duplication events indicated that whole-genome duplication and segmental duplication likely played key roles in expansion of the PbMYB gene family. Ka/Ks analysis suggested that the duplicated PbMYBs mainly experienced purifying selection with restrictive functional divergence after the duplication events. Interspecies microsynteny analysis revealed maximum orthology between pear and peach, followed by plum and strawberry. Subsequently, the expression patterns of 20 PbMYB genes that may be involved in lignin biosynthesis according to their phylogenetic relationships were examined throughout fruit development. Among the 20 genes examined, PbMYB25 and PbMYB52 exhibited expression patterns consistent with the typical variations in the lignin content previously reported. Moreover, sub-cellular localization analysis revealed that two proteins PbMYB25 and PbMYB52 were localized to the nucleus. All together, PbMYB25 and PbMYB52 were inferred to be candidate genes involved in the regulation of lignin biosynthesis during the development of pear fruit. This study provides useful information for further functional analysis of the MYB gene family in pear.
Brief Cognitive and Relaxation Training Increases Tolerance for a Painful Clinical Electromyographic Examination

&NA; We examined the effect of cognitive and/or relaxation training on the tolerance for a painful one and one‐half hour clinical electromyographic (EMG) examination, which includes multiple electric shocks to nerves and multiple insertions of needle electrodes into muscles. Four groups of 10 males each received training as follows: (i) cognitive only, (ii) relaxation only, (iii) cognitive plus relaxation, and (iv) neither cognitive nor relaxation (control). The three trained groups tolerated the EMG study better than the control group as judged by assessments by “blind” observers, self‐ratings, and measurements of heart rate. However, none of the training sessions was clearly superior to the other two types of training. We recommend cognitive relaxation training be used in the clinical setting to increase tolerance for painful medical procedures.
Reading liminal and temporal dimensionality in the Baxter family ‘public-narrative’

This article draws upon inductive research to explore the complex liminal and temporal dimensionality of storytelling in a family-business context, uncovering alternative social constructions of family-business stories as ‘Public-Narrative’ and ‘Business-Romance’. It develops theoretical insights, advancing our understanding of how narrative devices influence theories of family business. Developing a more nuanced understanding of where such stories sit within the overarching rubric of organisational-stories is central to expanding the theoretical knowledge base. Understanding such stories as generative scripts helps us author new entrepreneurial identities across generations. An analysis of the ‘Baxter Public-Narrative’ revealed viable, alternative themes and storylines, particularly romance and adventure, expanding available storied repertoires. The findings suggest that generational and inter-generational storylines change over time in a morphological manner with each successive generation.
Adverse Selection in Electronic Markets: Evidence from Online Stamp Auctions

We analyze adverse selection costs in online stamp auctions, based on a comparison of prices on eBay with those of matched stamps at a specialty stamps auction site in the U.S., Michael Rogers, Inc. (MR), which we know a priori has low quality uncertainty. We find that buyer prices are 10-15% lower on eBay as compared to MR, and the price difference, increases with the value of the stamps. Consistent with this adverse selection discount we find that the seller reputation mechanism on eBay has an economically modest, although statistically significant, effect on auction price and probability of sale. Copyright Blackwell Publishing Ltd. 2004.
GABAB Receptor Modulation of Serotonin Neurons in the Dorsal Raphé Nucleus and Escalation of Aggression in Mice

The serotonin (5-HT) system in the brain has been studied more than any other neurotransmitter for its role in the neurobiological basis of aggression. However, which mechanisms modulate the 5-HT system to promote escalated aggression is not clear. We here explore the role of GABAergic modulation in the raphé nuclei, from which most 5-HT in the forebrain originates, on escalated aggression in male mice. Pharmacological activation of GABAB, but not GABAA, receptors in the dorsal raphé nucleus (DRN) escalated aggressive behaviors. In contrast, GABA agonists did not escalate aggressive behaviors after microinjection into the median raphé nucleus. The aggression-heightening effect of the GABAB agonist baclofen depended on the activation of 5-HT neurons in the DRN because it was blocked by coadministration of the 5-HT1A agonist 8-OH-DPAT [((±)-8-hydroxy-2-(di-n-propylamino)tetralin) hydrobromide] (DPAT), which acts on autoreceptors and inhibits 5-HT neural activity. In vivo microdialysis showed that GABAB activation in the DRN increased extracellular 5-HT level in the medial prefrontal cortex. This may be attributable to an indirect action via presynaptic GABAB receptors. The presynaptic GABAB receptors suppress Ca2+ channel activity and inhibit neurotransmission, and the coadministration of N-type Ca2+ channel blocker facilitated the effect of baclofen. These findings suggest that the indirect disinhibition of 5-HT neuron activity by presynaptic GABAB receptors on non-5-HT neurons in the DRN is one of the neurobiological mechanisms of escalated aggression.
MORE: An Intelligent Knowledge Acquisition Tool

MORE is a tool that assists in eliciting knowledge from domain experts. Acquired information is added to a domain model of qualitative causal relations that may hold among hypotheses, symptoms, and background conditions. After generating diagnostic rules from the domain model, MORE prompts for additional information that would allow a stronger set of diagnostic rules to be generated, MORE'S primary value lies in its understanding of what kinds of knowledge are likely to be diagnostically significant. By formulating its questions in a way that focuses on such knowledge, it makes the most effective use of the domain experts' time.
Narcissism in the Rorschach Revisited: Some Reflections on Empirical Data

This study investigates the extent to which the Rorschach was able to identify accurately pathological expressions of narcissism according to the methodological recommendations offered by T. Nezworski and J. Wood (1995). Ninety-one patients who were found to meet DSM-IV criteria for an Axis II disorder (Cluster A personality disorders = 10; antisocial = 20, borderline = 25, histrionic = 5, narcissistic [NPD] =15; Cluster C personality disorders = 16) and 50 nonclinical participants were compared on 5 Rorschach variables: reflection, pair, personalization, idealization, and the egocentricity index. The results of this study indicate that selected Rorschach variables can be used effectively to differentiate NPD patients from a nonclinical sample and from Cluster A, Cluster C, and other Cluster B personality disorders. Also, the reflection and idealization variables were found to be empirically related to DSM-IV diagnostic criteria for NPD and a self-report measure of NPD. Finally, these two variables could be used for classification purposes in ways that were clinically meaningful in the diagnosis of NPD. Narcissistic personality disorder (NPD) was included as a diagnostic category in the Diagnostic and Statistical Manual of Mental Disorders (3rd ed.; DSM-III; American Psychiatric Association, 1980) in large part because of widespread interest in the theoretical and clinical concept of narcissism by psychodynamic psychotherapists (Kernberg, 1970, 1975, 1984; Kohut, 1971, 1977; Pulver, 1970; Stolorow, 1975; Teicholz, 1978). However, the justification for regarding NPD as an independent diagnostic entity having distinguishable features from other personality disorders has been the matter of some controversy
Sex Specific Incidence Rates of Type 2 Diabetes and Its Risk Factors over 9 Years of Follow-Up: Tehran Lipid and Glucose Study

Objective To investigate the population-based incidence of type 2 diabetes and its potential risk factors in a sex-split cohort of Iranian population. Materials and Methods A total of 8400 non-diabetic participants, aged ≥20 years (3620 men and 4780 women) entered the study. Crude and age standardized incidence rates per 1000 person-years were calculated for whole population and each sex separately. Cox proportional hazard models were used to evaluate hazard ratios (HR) and 95% confidence intervals for all potential risk factors in both uni-variable and multivariable models. Results During a median follow-up of 9.5 years, 736 new cases of diabetes were identified, including 433 women and 303 men. The annual crude and age-standardized incidence rates (95% CI) of diabetes in the total population were 10.6 (9.92–11.4) and 9.94 (7.39–13.6) per 1000 person-years of follow-up and the corresponding sex specific rates were 10.2 (9.13–11.4) and 9.36 (5.84–14.92) in men and 11.0 (9.99–12.0) and 10.1 (7.24–13.9) in women, respectively. In the multivariable model, the risk for incident diabetes was significantly associated with fasting and 2 hour post challenge plasma glucose as well as family history of diabetes in both men and women. However, among women, only the contribution of wrist circumference to incident diabetes achieved statistical significance [HR: 1.16 (1.03–1.31)] with waist/height ratio being marginally significant [HR: 1.02 (0.99–1.04)]; while among men, only body mass index was a significant predictor [HR: 1.12 (1.02–1.22)]. Additionally, low education level conferred a higher risk for incident diabetes only among men [HR: 1.80 (1.23–2.36); P for interaction with sex = 0.003]. Conclusion Overall, sex did not significantly modify the impact of risk factors associated with diabetes among Iranian adults; however, among modifiable risk factors, the independent role of lower education and general adiposity in men and central adiposity in women might require different preventive strategies.
An Asymmetric and DCC Analysis of Two Stock Markets Return: An Evidence Study of the U.S. and the Canada's Stock Markets

The empirical results show that the dynamic conditional correlation (DCC) and the bivariate asymmetric-IGARCH (1, 1) model is appropriate in evaluating the relationship of the U.S. and the Canada’s stock markets. The empirical result also indicates that the U.S. and the Canada’s stock markets is a positive relation. The average estimation value of correlation coefficient equals to 0.669, which implies that the two stock markets is synchronized influence. Besides, the empirical result also shows that the U.S. and the Canada’s stock markets have an asymmetrical effect, and the variation risks of the U.S. and the Canada’s stock market returns also receives the influence of the positive and negative of the itself return rate’ volatility.
Privacy preserving processing of data decision tree based on sample selection and Singular Value Decomposition

Data mining is a set of automated techniques used to extract hidden or buried information from large databases. With the development of data mining technologies, privacy protection has become a challenge for data mining applications in many fields. To solve this problem, many privacy-preserving data mining methods have been proposed. One important type of such methods is based on Singular Value Decomposition (SVD). In the proposed algorithm, attributes are grouped according to their distance difference similarity by clustering the data set using decision tree classification. Secondly, the algorithm packetizes the attributes according to their SA value in each group. Thirdly, for each group it selects attributes from the smallest bucket and searches for a similar attributes in the attributes-1 largest buckets from the same group to create an equivalence class following the unique attribute-distinct diversity anonymization model. The proposed algorithm satisfies the “utility based anonymization principle that crucial information is protected from being suppressed. Also, weights given to attributes improve clustering and give the ability to control the generalization's depth. In prototype decision tree is combination of clustering and classification technique such methods are called ensemble classifier, this new proposed method is more efficient in balancing data privacy and data utility.
Estimating the Security of Lattice-based Cryptosystems

Encryption and signature schemes based on worst-case lattice problems are promising candidates for the post-quantum era, where classic number-theoretic assumptions are rendered false. Although there have been many important results and breakthroughs in lattice cryptography, the questions of how to systematically evaluate their security in practice and how to choose secure parameters are still open. This is mainly due to the fact that most security proofs are essentially asymptotic statements. In addition, the hardness of the underlying complexity assumption is controlled by several interdependent parameters rather than just a simple bit length as in many classic schemes. With our work, we close this gap by providing a framework that (1) distills a hardness estimate out of a given parameter set and (2) relates the complexity of practical lattice-based attacks to symmetric “bit security” for the first time. Our approach takes various security levels, or attacker types, into account. Moreover, we use it to predict long-term security in a similar fashion as the results that are collected on www.keylength. com. In contrast to the experiments by Gama and Nguyen (Eurocrypt 2008), our estimates are based on precisely the family of lattices that is relevant in modern lattice-based cryptography. Our framework can be applied in two ways: Firstly, to assess the hardness of the (few) proposed parameter sets so far and secondly, to propose secure parameters in the first place. Our methodology is applicable to essentially all lattice-based schemes that are based on the learning with errors problem (LWE) or the small integer solution problem (SIS) and it allows us to compare efficiency and security across different schemes and even across different types of cryptographic primitives.
Almost periodic currents, chains and divisors in tube domains

A notion of almost periodic current is introduced, as well as a notion of almost periodic holomorphic chain proceeded from that definition. Such a chain can be defined either as a special case of almost periodic currents or as a holomorphic chain whose trace measure is an almost periodic distribution. It is shown that in general situation almost periodicity of the trace of a current does not imply that for the current itself, even if it is closed and positive. The zero set (regarded as a holomorphic chain) of a holomorphic mapping can be represented as a Monge-Ampere type current, and one could expect that the zero set of an almost periodic holomorphic mapping should be almost periodic; however we construct an example of an almost periodic holomorphic mapping whose zero set is not almost periodic. Nevertheless, we prove almost periodicity of the Monge-Ampere currents corresponding to almost periodic holomorphic mappings with certain additional properties. Then we construct functions that play the same role for almost periodic divisors as the so-called Jessen functions for almost periodic holomorphic functions. In terms of Jessen function we give a sufficient condition for realizability of an almost periodic divisor as the divisor of a holomorphic almost periodic function; some necessary condition is obtained, too.
Finding stable local optimal RNA secondary structures

MOTIVATION Many RNAs, such as riboswitches, can fold into multiple alternate structures and perform different biological functions. These biologically functional structures usually have low free energies in their local energy landscapes and are very stable such that they cannot easily jump out of the current states and fold into other stable conformations. The conformational space of feasible RNA secondary structures is prohibitively large, and accurate prediction of functional structure conformations is challenging. Because the stability of an RNA secondary structure is determined predominantly by energetically favorable helical regions (stacks), we propose to use configurations of putative stacks to represent RNA secondary structures. By considering a reduced conformational space of local optimal stack configurations instead of all feasible RNA structures, we first present an algorithm for enumerating all possible local optimal stack configurations. In addition, we present a fast heuristic algorithm for approximating energy barriers encountered during folding pathways between each pair of local optimal stack configurations and finding all the stable local optimal structures. RESULTS Benchmark tests have been conducted on several RNA riboswitches, whose alternate secondary structures have been experimentally verified. The benchmark results show that our method can successfully predict the native 'on' and 'off' secondary structures, and better rank them compared with other state-of-art approaches. AVAILABILITY The software is freely available and can be downloaded at http://genome.ucf. edu/RNASLOpt. CONTACT shzhang@eecs.ucf. edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Final Report : Improved Discrimination of Asperger Patients using fMRI and Machine Learning

Asperger Syndrome is an autism spectrum disorder that reduces a patient’s ability to interact socially, and restricts their interests and abilities. Using functional magnetic resonance imaging (fMRI), it has been shown that Asperger patients exhibit reduced activity between the nodes of a resting-state neuronal network comprised of the posterior cingulate cortex (PCC), the medial prefrontal cortex (MPFC), and the lateral parietal cortex, compared to healthy controls [1]. The study of Ref. [1] proposed a technique to discriminate Asperger patients and healthy controls using the self-organizing map (SOM) algorithm [2] to automatically generate a cluster representing this resting-state network from restingstate fMRI data. If robust, such a method could have important applications in screening for this disorder, both in clinical and research settings. However, this method has a few potential weaknesses. First, it performs discrimination using a single statistic. Second, the SOM algorithm clusters voxel timecourses based on Euclidean distances, and therefore may not robustly cluster voxels that are functionally connected but possess inter-voxel delays. Third, the original method required user interaction to choose the cluster that best represents the resting-state network, which may bias the results. Therefore, we are proposing three innovations to this algorithm. To address the first and last issues, we will apply filter and wrapper methods directly to the fMRI images, bypassing SOM and the need for user interaction. We have also implemented several different discrimination methods to compare to the simple z-score threshold test implemented in
Transport properties of RTILs from classical molecular dynamics

Room Temperature Ionic Liquids (RTILs) have attracted much attention in the scientific community in the past decade due the their novel and highly customizable properties. Nonetheless their high viscosities pose serious limitations to the use of RTILs in practical applications. To elucidate some of the physical aspects behind transport properties of RTILs, extensive classical molecular dynamics (MD) calculations are reported. Bulk viscosities and ionic conductivities of butyl-methyl-imidazole based RTILs are presented over a wide range of temperatures. The dependence of the properties of the liquids on simulation parameters, e.g. system size effects and choice of the interaction potential, is analyzed. ∗ oliviero.andreussi@epfl.ch † nicola.marzari@epfl.ch