Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantification of stochastic noise of splicing and polyadenylation in Entamoeba histolytica

Alternative splicing and polyadenylation were observed pervasively in eukaryotic messenger RNAs. These alternative isoforms could either be consequences of physiological regulation or stochastic noise of RNA processing. To quantify the extent of stochastic noise in splicing and polyadenylation, we analyzed the alternative usage of splicing and polyadenylation sites in Entamoeba histolytica using RNA-Seq. First, we identified a large number of rarely spliced alternative junctions and then showed that the occurrence of these alternative splicing events is correlated with splicing site sequence, occurrence of constitutive splicing events and messenger RNA abundance. Our results implied the majority of these alternative splicing events are likely to be stochastic error of splicing machineries, and we estimated the corresponding error rates. Second, we observed extensive microheterogeneity of polyadenylation cleavage sites, and the extent of such microheterogeneity is correlated with the occurrence of constitutive cleavage events, suggesting most of such microheterogeneity is likely to be stochastic. Overall, we only observed a small fraction of alternative splicing and polyadenylation isoforms that are unlikely to be solely stochastic, implying the functional relevance of alternative splicing and polyadenylation in E. histolytica is limited. Lastly, we revised the gene models and annotated their 3′UTR in AmoebaDB, providing valuable resources to the community.
Finding and Containing Enemies Within the Walls with Self-securing Network Interfaces (CMU-CS-03-109)

Self-securing network interfaces (NIs) examine the packets that they move between network links and host software, looking for and potentially blocking malicious network activity. This paper describes how self-securing network interfaces can help administrators to identify and contain compromised machines within their intranet. By shadowing host state, self-securing NIs can better identify suspicious traffic originating from that host, including many explicitly designed to defeat network intrusion detection systems. With normalization and detection-triggered throttling, selfsecuring NIs can reduce the ability of compromised hosts to launch attacks on other systems inside (or outside) the intranet. We describe a prototype self-securing NI and example scanners for detecting such things as TTL abuse, fragmentation abuse, “SYN bomb” attacks, and random-propagation worms like Code-Red. We thank the members and companies of the PDL Consortium (including EMC, Hewlett-Packard, Hitachi, IBM, Intel, Network Appliance, Panasas, Seagate, Sun, and Veritas) for their interest, insights, feedback, and support. We thank IBM and Intel for hardware grants supporting our research efforts. This material is based on research sponsored by the Air Force Research Laboratory, under agreement number F49620-01-1-0433. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory or the U.S. Government.
Quantification of the Frequency and Multiplicity of Infection of Respiratory- and Lymph Node–Resident Dendritic Cells During Influenza Virus Infection

Background Previous studies have demonstrated that DC differentially regulate influenza A virus (IAV)–specific CD8 T cell responses in vivo during high and low dose IAV infections. Furthermore, in vitro infection of DC with IAV at low versus high multiplicities of infection (MOI) results in altered cytokine production and a reduced ability to prime naïve CD8 T cell responses. Flow cytometric detection of IAV proteins within DC, a commonly used method for detection of cellular IAV infection, does not distinguish between the direct infection of these cells or their uptake of viral proteins from dying epithelial cells. Methods/Principal Findings We have developed a novel, sensitive, single-cell RT-PCR–based approach to assess the infection of respiratory DC (rDC) and lymph node (LN)-resident DC (LNDC) following high and low dose IAV infections. Our results show that, while a fraction of both rDC and LNDC contain viral mRNA following IAV infection, there is little correlation between the percentage of rDC containing viral mRNA and the initial IAV inoculum dose. Instead, increasing IAV inoculums correlate with augmented rDC MOI. Conclusion/Significance Together, our results demonstrate a novel and sensitive method for the detection of direct IAV infection at the single-cell level and suggest that the previously described ability of DC to differentially regulate IAV-specific T cell responses during high and low dose IAV infections could relate to the MOI of rDC within the LN rather than the percentage of rDC infected.
SYNCHRONOUS CMC, WORKING MEMORY, AND L2 ORAL PROFICIENCY DEVELOPMENT

Recently a number of quasi-experimental studies have investigated the potential of a crossmodality transfer of second language competency between real-time, conversational exchange via text and speech (Abrams, 2003; Beauvious, 1998; Kost, 2004; Payne & Whitney, 2002). Payne and Whitney employed Levelt's (1989) model of language production and concepts from working memory as a rationale for a hypothesized connection between synchronous computer-mediated communication (SCMC) and second language (L2) speech and as a basis for predicting the differential contributions of SCMC to the L2 oral proficiency development. This study extends the psycholinguistic framework reported in Payne and Whitney (2002) with discourse and corpus analytic techniques to explore how individual differences in working memory capacity may affect the frequency of repetition and other patterns of language use in chatroom discourse. Working memory capacity was measured by a reading span and nonword repetition test. Oral proficiency was measured with a speaking task that solicited a 5-minute speech sample and was scored based on a holistic scale. The data collected from 20 chat sessions were analyzed for occurrences of repetition and relexicalization, as well as language output measures. Findings suggest a connection between working memory and language output as measured in this study.
Systematic review of controlled trials of interventions to promote smoke alarms

AIMS To evaluate the effects of promotion of residential smoke alarms. METHODS Electronic databases, conference proceedings, and bibliographies were systematically searched, and investigators and organisations were contacted, in order to identify controlled trials evaluating interventions designed to promote residential smoke alarms. The following were assessed: smoke alarm acquisition, ownership, and function; fires; burns; and fire related injuries. Odds ratios (OR) were estimated by meta analysis of randomised trials. RESULTS A total of 26 trials were identified, of which 13 were randomised. Overall, counselling and educational interventions had only a modest effect on the likelihood of owning an alarm (OR = 1.26; 95% confidence interval (CI): 0.87 to 1.81) or having a functional alarm (OR = 1.19; 95% CI: 0.85 to 1.66). Counselling as part of primary care child health surveillance had greater effects on ownership (OR = 1.93; 95% CI: 1.04 to 3.58) and function (OR = 1.72; 95% CI: 0.78 to 3.78). Results were sensitive to trial quality, however, and effects on fire related injuries were not reported. In two non-randomised trials, direct provision of free alarms significantly increased functioning alarms and reduced fire related injuries. Media and community education showed little benefit in non-randomised trials. CONCLUSION Counselling as part of child health surveillance may increase smoke alarm ownership and function, but its effects on injuries are unevaluated. Community smoke alarm give away programmes apparently reduce fire related injuries, but these trials were not randomised and results must be interpreted cautiously. Further efforts to promote smoke alarms in primary care or through give away programmes should be evaluated by adequately designed randomised controlled trials measuring injury outcomes.
Oxygen-Dependent Cell-to-Cell Variability in the Output of the Escherichia coli Tor Phosphorelay

ABSTRACT Escherichia coli senses and responds to trimethylamine-N-oxide (TMAO) in the environment through the TorT-TorS-TorR signal transduction system. The periplasmic protein TorT binds TMAO and stimulates the hybrid kinase TorS to phosphorylate the response regulator TorR through a phosphorelay. Phosphorylated TorR, in turn, activates transcription of the torCAD operon, which encodes the proteins required for anaerobic respiration via reduction of TMAO to trimethylamine. Interestingly, E. coli respires TMAO in both the presence and absence of oxygen, a behavior that is markedly different from the utilization of other alternative electron acceptors by this bacterium. Here we describe an unusual form of regulation by oxygen for this system. While the average level of torCAD transcription is the same for aerobic and anaerobic cultures containing TMAO, the behavior across the population of cells is strikingly different under the two growth conditions. Cellular levels of torCAD transcription in aerobic cultures are highly heterogeneous, in contrast to the relatively homogeneous distribution in anaerobic cultures. Thus, oxygen regulates the variance of the output but not the mean for the Tor system. We further show that this oxygen-dependent variability stems from the phosphorelay. IMPORTANCE Trimethylamine-N-oxide (TMAO) is utilized by numerous bacteria as an electron acceptor for anaerobic respiration. In E. coli, expression of the proteins required for TMAO respiration is tightly regulated by a signal transduction system that is activated by TMAO. Curiously, although oxygen is the energetically preferred electron acceptor, TMAO is respired even in the presence of oxygen. Here we describe an interesting and unexpected form of regulation for this system in which oxygen produces highly variable expression of the TMAO utilization proteins across a population of cells without affecting the mean expression of these proteins. To our knowledge, this is the first reported example of a stimulus regulating the variance but not the mean output of a signaling system.
BitNet: Bit-Regularized Deep Neural Networks

We present a novel optimization strategy for training neural networks which we call "BitNet". The parameters of neural networks are usually unconstrained and have a dynamic range dispersed over all real values. Our key idea is to limit the expressive power of the network by dynamically controlling the range and set of values that the parameters can take. We formulate this idea using a novel end-to-end approach that circumvents the discrete parameter space by optimizing a relaxed continuous and differentiable upper bound of the typical classification loss function. The approach can be interpreted as a regularization inspired by the Minimum Description Length (MDL) principle. For each layer of the network, our approach optimizes real-valued translation and scaling factors and arbitrary precision integer-valued parameters (weights). We empirically compare BitNet to an equivalent unregularized model on the MNIST and CIFAR-10 datasets. We show that BitNet converges faster to a superior quality solution. Additionally, the resulting model has significant savings in memory due to the use of integer-valued parameters.
Metabolic Analysis of Adaptation to Short-Term Changes in Culture Conditions of the Marine Diatom Thalassiosira pseudonana

This report describes the metabolic and lipidomic profiling of 97 low-molecular weight compounds from the primary metabolism and 124 lipid compounds of the diatom Thalassiosira pseudonana. The metabolic profiles were created for diatoms perturbed for 24 hours with four different treatments: (I) removal of nitrogen, (II) lower iron concentration, (III) addition of sea salt, (IV) addition of carbonate to their growth media. Our results show that as early as 24 hours after nitrogen depletion significant qualitative and quantitative change in lipid composition as well as in the primary metabolism of Thalassiosira pseudonana occurs. So we can observe the accumulation of several storage lipids, namely triacylglycerides, and TCA cycle intermediates, of which citric acid increases more than 10-fold. These changes are positively correlated with expression of TCA enzymes genes. Next to the TCA cycle intermediates and storage lipid changes, we have observed decrease in N-containing lipids and primary metabolites such as amino acids. As a measure of counteracting nitrogen starvation, we have observed elevated expression levels of nitrogen uptake and amino acid biosynthetic genes. This indicates that diatoms can fast and efficiently adapt to changing environment by altering the metabolic fluxes and metabolite abundances. Especially, the accumulation of proline and the decrease of dimethylsulfoniopropionate suggest that the proline is the main osmoprotectant for the diatom in nitrogen rich conditions.
Curved dielectric optical waveguides with reduced transition losses

At a junction between two monomode dielectric optical waveguides with different curvatures power is lost by radiation. To reduce this transition loss, it is proposed to offset each waveguide section towards its centre of curvature by a distance which equals the corresponding shift between the wave-beam axis and the waveguide axis.
Comparing Fully and Partially Synthetic Datasets for Statistical Disclosure Control in the German IAB Establishment Panel

For datasets considered for public release, statistical agencies have to face the dilemma of guaranteeing the confidentiality of survey respondents on the one hand and offering sufficiently detailed data for scientific use on the other hand. For that reason a variety of methods that address this problem can be found in the literature. In this paper we discuss the advantages and disadvantages of two approaches that pro-vide disclosure control by generating synthetic datasets: The first, proposed by Rubin [1], generates fully synthetic datasets while the second suggested by Little [2] imputes values only for selected variables that bear a high risk of disclosure. Changing only some variables in general will lead to higher analytical validity. However, the disclosure risk will also increase for partially synthetic data, since true values remain in the data-sets. Thus, agencies willing to release synthetic datasets will have to decide, which of the two methods balances best the trade-off between data utility and disclosure risk for their data. We offer some guidelines to help making this decision. To our knowledge, the two approaches never haven been empirically compared in the literature so far. We apply the two methods to a set of variables from the 1997 wave of the German IAB Establishment Panel and evaluate their quality by comparing results from the original data with results we achieve for the same analyses run on the datasets after the imputation procedures. The results are as expected: In both cases the analytical validity of the synthetic data is high with partially synthetic datasets outperforming fully synthetic datasets in terms of data utility. But this advantage comes at the price of a higher disclosure risk for the partially synthetic data.
Optimized post-operative surveillance of permanent pacemakers by home monitoring: the OEDIPE trial

Aims The ŒDIPE trial examined the safety and efficacy of an abbreviated hospitalization after implantation or replacement of dual-chamber pacemakers (PM) using a telecardiology-based ambulatory surveillance programme. Methods and results Patients were randomly assigned to (i) an active group, discharged from the hospital 24 h after a first PM implant or 4–6 h after replacement, and followed for 4 weeks with Home-Monitoring (HM), or (ii) a control group followed for 4 weeks according to usual medical practices. The primary objective was to confirm that the proportion of patients who experienced one or more major adverse events (MAE) was not higher in the active than in the control group. The study included 379 patients. At least one treatment-related MAE was observed in 9.2% of patients (n = 17) assigned to the active group vs. 13.3% of patients (n = 26) in the control group (P = 0.21), a 4.1% absolute risk reduction (95% CI −2.2 to 10.4; P = 0.98). By study design, the mean hospitalization duration was 34% shorter in the active than in the control group (P < 0.001), and HM facilitated the early detection of technical issues and detectable clinical anomalies. Conclusion Early discharge with HM after PM implantation or replacement was safe and facilitated the monitoring of patients in the month following the procedure.
Numerical Characterization of Quasi-Static Ultrasound Elastography for the Detection of Deep Tissue Injuries

Deep tissue injuries are subcutaneous regions of tissue breakdown associated with excessive mechanical pressure for extended period of time. These wounds are currently clinically undetectable in their early stages and result in severe burdens on not only the patients who suffer from them, but the health care system as well. The goal of this work was to numerically characterize the use of quasi-static ultrasound elastography for detecting formative and progressive deep tissue injuries. In order to numerically characterize the technique, finite-element models of sonographic B-mode imaging and tissue deformation were created. These models were fed into a local strain-estimation algorithm to determine the detection sensitivity of the technique on various parameters. Our work showed that quasi-static ultrasound elastography was able to detect and characterize deep tissue injuries over a range of lesion parameters. Simulations were validated using a physical phantom model. This work represents a step along the path to developing a clinically relevant technique for detecting and diagnosing early deep tissue injuries.
Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.
Globalisation , Productivity and Technology Research Paper 2004 / 08 Outsourcing , foreign ownership , exporting and productivity : An empirical investigation with plant level data

We investigate the impact of international outsourcing on productivity using plant level data for Irish manufacturing. Specifically, we distinguish the effect of outsourcing of materials from services inputs. Moreover, we examine whether the impact on productivity is different for plants being more embedded in international markets through exporting or being part of a multinational. Our results demonstrate that these distinctions can in general be important and are line with implications from the recent theoretical literature. JEL classification: F14, F23, L23
Performance Analysis of Proactive and Reactive MANET Routing Protocols using TCP Traffic for Freeway and Random Waypoint Mobility Model

Mobile ad-hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any stand-alone infrastructure or centralized administration. Mobile ad-hoc network have the attribute such as wireless connection, continuously changing topology, distributed operation and ease of deployment. In this paper we have investigated the performance of two MANET routing protocol (Proactive and Reactive) by using Freeway and Random Waypoint mobility model for mobility of nodes using TCP traffic. Freeway Mobility model has been generated by IMPORTANT (Impact of Mobility Patterns on Routing in Ad-hoc NeTwork) tool, whereas Random Waypoint by inbuilt setdest tool in NS2. A detailed simulation has been carried out in NS2 with TCP traffic sources and AODV as reactive and DSDV as proactive routing protocols. The metrics used for performance analysis are Packet Delivery Fraction, Average end-to-end Delay, Packet Loss, Routing Overhead, Normalized Routing Load and throughput. It has been observed that (proactive routing protocol) DSDV performance is better than (reactive routing protocol) AODV but at the cost of higher average end-end delay in both mobility models. Both routing protocols give optimized result in Random Waypoint mobility model as compared to Freeway Mobility Model.
Prevalence of Cigarette Smoking in Schizophrenic Patients Compared to Other Hospital Admitted Psychiatric Patients

Background: This study aimed to estimate the prevalence of cigarette smoking and some of the related factors among schizophrenic and other hospitalized psychiatric patients. Methods: This was a cross-sectional study on 120 patients hospitalized in Shahid Beheshti hospital in Kerman in 2005. Patients were equally devided in two groups of schizophrenia and other psychiatric disorders. Sampling was based on statistical census and data were collected using a questionnaire including 27 questions on demographic data, psychiatric disorder, smoking cigarettes and other substances, and Fagerstrom test. Data were analyzed by Chi-square and ANOVA tests using SPSS software. Findings: Prevalence and severity of cigarette smoking was 71.6% and 6.47% among schizophrenic and 51.6% and 6.40% among other psychiatric patients, respectively and the difference was not significant. History of withdrawal was 25.6% and 58.1% in the schizophrenia and other disorders respectively and the difference was significant (P < 0.05). Addiction to other substances was 51.6% in schizophrenic and 45% in the other patients and the most prevalent substances in both groups were opium and alcohol. The severity of smoking cigarettes was 6.9 along with other drug abuses and 5.1 in cases with just smoking based on Fagerstrom test and the difference was significant (P < 0.05). Conclusion: The prevalence of cigarette smoking in both schizophrenia and other psychiatric patients is higher than normal population, but there is no significant difference between these two groups. Schizophrenic patients need persistent supportive and supervising programs for cigarette smoking abuse treatment because of their cognitive, motivate and social problems.