Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for risk stratification when monitoring for toxicities following initiation of combination antiretroviral therapy

Objective:Laboratory monitoring is recommended during combination antiretroviral therapy (cART), but the pattern of detected abnormalities and optimal monitoring are unknown. We assessed laboratory abnormalities during initial cART in 2000–2010 across the United States. Design:Observational study in the Centers for AIDS Research Network of Integrated Clinical Systems Cohort. Methods:Among patients with normal results within a year prior to cART initiation, time to first significant abnormality was assessed by Kaplan–Meier curves stratified by event type, with censoring at first of regimen change, loss to follow-up, or 104 weeks. Incidence rates of first events were estimated using Poisson regression; multivariable analyses identified associated factors. Results were stratified by time (16 weeks) from therapy initiation. Results:A total of 3470 individuals contributed 3639 person-years. Median age, pre-cART CD4, and follow-up duration were 40 years, 206 cells/&mgr;l, and 51 weeks, respectively. Incidence rates for significant abnormalities (per 100 person-years) in the first 16 weeks post-cART initiation were as follows: lipid = 49 [95% confidence interval (CI) 41–58]; hematologic = 44 (40–49); hepatic = 24 (20–27); and renal = 9 (7–11), dropping substantially during weeks 17–104 of cART to lipid = 23 (18–29); hematologic = 5 (4–6); hepatic = 6 (5–8); and renal = 2 (1–3) (all P < 0.05). Among patients receiving initial cART with no prior abnormality (N = 1889), strongest associations for hepatic abnormalities after 16 weeks were hepatitis B and C [hazard ratio = 2.3 (95% CI 1.2–4.5) and hazard ratio = 3.0 (1.9–4.5), respectively]. The strongest association for renal abnormalities was hypertension [hazard ratio = 2.8 (1.4–5.6)]. Conclusion:New abnormalities decreased after week 16 of cART. For abnormalities not present by week 16, subsequent monitoring should be guided by comorbidities.
Intermediate state trapping of a voltage sensor

Voltage sensor domains (VSDs) regulate ion channels and enzymes by undergoing conformational changes depending on membrane electrical signals. The molecular mechanisms underlying the VSD transitions are not fully understood. Here, we show that some mutations of I241 in the S1 segment of the Shaker Kv channel positively shift the voltage dependence of the VSD movement and alter the functional coupling between VSD and pore domains. Among the I241 mutants, I241W immobilized the VSD movement during activation and deactivation, approximately halfway between the resting and active states, and drastically shifted the voltage activation of the ionic conductance. This phenotype, which is consistent with a stabilization of an intermediate VSD conformation by the I241W mutation, was diminished by the charge-conserving R2K mutation but not by the charge-neutralizing R2Q mutation. Interestingly, most of these effects were reproduced by the F244W mutation located one helical turn above I241. Electrophysiology recordings using nonnatural indole derivatives ruled out the involvement of cation-Π interactions for the effects of the Trp inserted at positions I241 and F244 on the channel’s conductance, but showed that the indole nitrogen was important for the I241W phenotype. Insight into the molecular mechanisms responsible for the stabilization of the intermediate state were investigated by creating in silico the mutations I241W, I241W/R2K, and F244W in intermediate conformations obtained from a computational VSD transition pathway determined using the string method. The experimental results and computational analysis suggest that the phenotype of I241W may originate in the formation of a hydrogen bond between the indole nitrogen atom and the backbone carbonyl of R2. This work provides new information on intermediate states in voltage-gated ion channels with an approach that produces minimum chemical perturbation.
Spatio-temporal patterns of suspended and attached bacterial communities in a hydrologically dynamic aquifer (Mittenwald, Germany)

Groundwater ecosystems are perceived as energy-poor systems very stable in environmental conditions and consequently harboring stable microbial communities of low diversity. In a hydrologically transient porous aquifer (Mittenwald, Germany), pronounced seasonal patterns of bacterial communities suspended in groundwater, exhibiting a dramatic drop in Shannon diversity at time of snow melting water impact, were found while the attached communities were found comparably stable year-round. The succession of dominant taxa within the bacteria during colonization of sterile sediments exposed to groundwater in situ indicated the presence of r- and K-strategists within the bacteria. A first estimation of carbon flux through the suspended microbial food web hinted at bacterial mortality induced by protozoan grazing and viral lysis.
Differentiation of Bifidobacterium longum subspecies longum and infantis by quantitative PCR using functional gene targets

Background Members of the genus Bifidobacterium are abundant in the feces of babies during the exclusively-milk-diet period of life. Bifidobacterium longum is reported to be a common member of the infant fecal microbiota. However, B. longum is composed of three subspecies, two of which are represented in the bowel microbiota (B. longum subsp. longum; B. longum subsp. infantis). B. longum subspecies are not differentiated in many studies, so that their prevalence and relative abundances are not accurately known. This may largely be due to difficulty in assigning subspecies identity using DNA sequences of 16S rRNA or tuf genes that are commonly used in bacterial taxonomy. Methods We developed a qPCR method targeting the sialidase gene (subsp. infantis) and sugar kinase gene (subsp. longum) to differentiate the subspecies using specific primers and probes. Specificity of the primers/probes was tested by in silico, pangenomic search, and using DNA from standard cultures of bifidobacterial species. The utility of the method was further examined using DNA from feces that had been collected from infants inhabiting various geographical regions. Results A pangenomic search of the NCBI genomic database showed that the PCR primers/probes targeted only the respective genes of the two subspecies. The primers/probes showed total specificity when tested against DNA extracted from the gold standard strains (type cultures) of bifidobacterial species detected in infant feces. Use of the qPCR method with DNA extracted from the feces of infants of different ages, delivery method and nutrition, showed that subsp. infantis was detectable (0–32.4% prevalence) in the feces of Australian (n = 90), South-East Asian (n = 24), and Chinese babies (n = 91), but in all cases at low abundance (<0.01–4.6%) compared to subsp. longum (0.1–33.7% abundance; 21.4–100% prevalence). Discussion Our qPCR method differentiates B. longum subspecies longum and infantis using characteristic functional genes. It can be used as an identification aid for isolates of bifidobacteria, as well as in determining prevalence and abundance of the subspecies in feces. The method should thus be useful in ecological studies of the infant gut microbiota during early life where an understanding of the ecology of bifidobacterial species may be important in developing interventions to promote infant health.
Higher Motor Activity in Schizophrenia Patients Treated With Olanzapine Versus Risperidone

There are indications that atypical antipsychotics differ in the probability of causing motor retardation. Whereas olanzapine seems to exert sedation, risperidone might slow patients because of parkinsonism or increased negative symptoms. Objective data on gross motor activity are not available. We present actigraphic data of 16 schizophrenia patients treated with olanzapine (mean dose, 21.1 mg/d) and 23 with risperidone (mean dose, 4.7 mg/d) to investigate possible differences in their effects on motor activity. Participants wore actigraphs continuously for 24 hours at the nondominant arm. Groups did not differ in age, Positive and Negative Syndrome Scale scores, duration of illness, and number of episodes. Patients treated with olanzapine had higher activity levels than those treated with risperidone (P = 0.024); this effect was robust and also present after covarying for chlorpromazine equivalents and Positive and Negative Syndrome Scale scores. Movement index (proportion of active episodes) and the average duration of immobility, however, failed to show any difference between groups. The results indicate that patients on olanzapine are more active during the day than patients on risperidone. It remains unclear whether this difference is due to subthreshold parkinsonism with risperidone or stronger beneficial effects of olanzapine on psychomotor slowing. Because the average duration of immobility remained unaffected, sedation is not likely to be the cause for the observed differences.
Cloud top height estimation from the Meteosat water vapor imagery using computational intelligence techniques: Preliminary results

—This study investigates the cloud top height estimation using nonlinear methods to Meteosat imagery. The suggested approach aims to develop an integrated statistical methodology to estimate the cloud top height on a pixel basis using Meteosat Second Generation water vapor imagery. Radiosonde measurements are used as reference dataset and a spatio-temporal correlation with Meteosat images is performed in order to collect a representative sample for the statistical analysis. Here, we apply Multi Layer Perceptron (MLP) and Support Vector Machines (SVM) and we compare the results to the Linear Regression model. The best results are achieved using SVM for regression. The proposed approach is very promising as it can be used for future in-depth analysis so as to develop a robust approach for geometrical height estimation on a pixel basis of the operational data of Meteosat imagery. It is noted that an accurate estimation of cloud top height can help to eliminate geometric restrictions (e.g. Parallax phenomenon) of the Meteosat satellite imagery, improving its usefulness in a wide area of applications and especially in satellite-based weather forecast.
Using Simulation, Fault Injection and Property-Based Testing to Evaluate Collision Avoidance of a Quadcopter System

In this work we use our testing platform based on FaultCheck and QuickCheck that we apply on a quad copter simulator. We have used a hardware platform as the basis for the simulator and for deriving realistic fault models for our simulations. The quad copters have a collision-avoidance mechanism that shall take over control when the situation becomes hazardous, steer away from the potential danger and then give control back to the pilot, thereby preventing collisions regardless of what the pilot does. We use our testing platform to randomly generate thousands of simulations with different input stimuli (using QuickCheck) for hundreds of quad copters, while injecting faults simultaneously (using FaultCheck). This way, we can effectively adjust system parameters and enhance the collision-avoidance mechanism.
Calibration, Validation, and Hardware-Software Modifications to the Carstens EMMA System

Ce rapport d'experience decrit les modifications apportees aux calibration, validation, materiel et programmes informatiques d'un articulometre electromagnetique mi-sagittal (Castens EMMA, version 1990). Ces modifications repondent au besoin de stabilite des mesures de la coordination spatiale et temporelle des structures articulatoires chez les sujets normaux et chez des sujets adultes souffrant de begaiement
A Triple Helix of University—Industry—Government Relations

1. Introduction: Universities in the Global Knowledge Economy. Part I: The Construction of the Knowledge-based Regime. 2. The New Role of the University in the Productive Sector, Judith Sutz. 3. Innovation Networks in Australia and China, Tim Tupin and Sam Garrett-Jones. 4. Technological Programs in the European Union, Philippe Laredo. Part II: The Co-evolution of Technologies and Institutions. 5. When Worlds Collide: Patents in Public-Sector Research, Andrew Webster and Kathryn Packer. 6. Emerging Environments in Biotechnology, Maureen D. McKelvey. 7. The Desktop Model of Innovation in Digital Media, William N. Kaghan and Gerald B. Barnett. Part III: The Operation of the Triple Helix. 8. Crossing Boundaries: The Emergence of Research-Technology Communities, Terry Shinn. 9. Negotiating a New Science: Artificial Intelligence, Petra Ahrweiler. 10. The New Communication Regime of University-Industry-Government Relations, Loet Leydesdorff. Part IV: Universities in Knowledge-based Economies. 11. Universities and Industrial Competitive Advantage, Magnus Gulbrandsen. 12. Japan: From Technology to Science Policy, Morris Low. 13. The Entrepreneurial University and the Emergence of Democratic Corporatism, Henry Etzkovitz. Epilogue 14. A Triple Helix of University-Industry-Government Relations, Loet Leydesdorff and Henry Etzkowitz.
Exploring the Use of Word Relation Features for Sentiment Classification

Word relation features, which encode relation information between words, are supposed to be effective features for sentiment classification. However, the use of word relation features suffers from two issues. One is the sparse-data problem and the lack of generalization performance; the other is the limitation of using word relations as additional features to unigrams. To address the two issues, we propose a generalized word relation feature extraction method and an ensemble model to efficiently integrate unigrams and different type of word relation features. Furthermore, aimed at reducing the computation complexity, we propose two fast feature selection methods that are specially designed for word relation features. A range of experiments are conducted to evaluate the effectiveness and efficiency of our approaches.
Vaginismus in peri- and postmenopausal women: a pragmatic approach for general practitioners and gynaecologists

Vaginismus is generally described as an involuntary contraction of the vaginal musculature, which usually results in the failure of penetration. Despite a lack of consensus as to the exact definition, prevalence rates vary between 4.2% and 42%. It is commonly diagnosed at both gynaecological and psychosexual clinics. The majority of studies and treatment options concentrate on the premenopausal age group. It is accepted that even within this age group, the diagnosis is often incorrect as symptoms can be confused with dyspareunia and other sexual pain disorders. There is no literature discussing vaginismus in the postmenopausal patient, despite evidence that an active sex life is important to the majority of women, irrespective of age. It is known that the majority of women do not report difficulties in their sex life and it may be that the older patient is more embarrassed at disclosing any such difficulties. This review aims to highlight the possible causes of vaginismus in this older age group and to aid the clinician in asking the appropriate questions, performing the appropriate examination and suggesting possible treatment options.
Using Learning Techniques to Generate System Models for Online Testing

Today’s software systems are mostly modular and have to be changeable. However, the testing of such systems becomes difficult, especially when changes are applied after deployment. One way to passively test such a system is to check whether the observed traces are accepted by a system model. In this paper, we present a method to generate a model of the System Under Test from its test cases. We adapt Angluin’s algorithm for learning finite automata to the special case of learning from traces obtained from test cases and provide the promising results of our experiment.
Multi-class multi-instance boosting for part-based human detection

With the purpose of designing a general learning framework for detecting human parts, we formulate this task as a classification problem over non-aligned training examples of multiple classes. We propose a new multi-class multi-instance boosting method, named MCMIBoost, for effective human parts detection in static images. MCMIBoost has two benefits. First, training examples are represented as a set of non-aligned instances, so that the alignment problem caused by human appearance variation can be handled. Second, instead of learning part detectors individually, MCMIBoost learns a unified detector for efficient detection, and uses the feature-sharing concept to design an efficient multi-class classifier. Experiment results on MIT and INRIA datasets demonstrate the superior performance of the proposed method.
Dynamic system simulator for the modeling of CDMA systems

As wireless systems progressed from first generation to second generation, and now 3G systems, system design tools have progressively become more sophisticated. Static system simulators have found widespread use in CDMA system design. In this article it is argued that static simulators are inadequate to capture the details of 3G systems, and study the performance of complex algorithms, and the case is made for dynamic system simulators. A detailed description of the structure of a wireless system simulator is given, with emphasis on a dynamic simulator. Some advantages of dynamic vs. static simulators are discussed.
Analysis of TCP under Wireless Circumstances: A Performance Evaluation

With the emergence of wireless technology, and increase of mobile computing devices, the demand for the better network connectivity is the major interest of the users. Transmission Control Protocol (TCP) is the standard network protocol for communication in the Internet, but its performance drastically degrades over wireless networks, as TCP takes packet drop or collision as a sign of congestion. In this paper, we analyze TCP's performance over wireless networks using NS-2 Simulator. Unlike traditional performance evaluation methods for TCP over wireless networks, we consider different versions of TCP over different routing protocols. Moreover, we also consider the effectiveness of TCP both over infrastructure-based and infrastructure-less wireless networks. Simulation results show that TCP's performance varies from scenario to scenario both in infrastructure-based and ad-hoc wireless networks.
Ownership Changes and Investment in Transition Countries

We estimate accelerator-cash flow models for 25,000 firms in 15 transition economies over the period 1993-2003, and find that (1) investment-cash flow sensitivities decline over transition years, which we attribute to a decreasing of asymmetric information and managerial discretion as capital markets and corporate governance standards develop. (2) After an ownership change, the investment-cash flow sensitivity declines, indicating that new owners reduce either cash constraints or managerial discretion or both. (3) For state owned firms, in early transition the investment-cash-flow sensitivity is negative, but in late transition the coefficient becomes positive. We interpret the first fact as being consistent with soft budget constraints, and the second with managerial discretion. (4) Privatised firms invest efficiently in the long run. (5) Foreign- and financially-controlled firms are less financially constrained than other firms.
Identification and isolation of the main component (gp350-gp220) of Epstein-Barr virus responsible for generating neutralizing antibodies in vivo

The majority of hybridomas we have characterized against Epstein-Barr virions react with the major glycoproteins gp350 and gp220 (gp350/220). One of these antibodies, ID4C-1, neutralizes virus infection in vitro. The presence of gp350/220 on the viral envelope could be confirmed directly by immunoelectron microscopy. We used lectin affinity (ricin) and immunoaffinity (ID4C-1) to purify gp350/220 and show that this material is able to induce potent virus-neutralizing antibodies. Absorption of four human and one rabbit anti-Epstein-Barr virus sera with purified gp350/220 suggests that this is the primary component responsible for generating neutralizing antibodies in vivo.
Adaptive neural network Dynamic Surface Control: An evaluation on the musculoskeletal robot Anthrob

The soft robotics approach is widely considered to enable robots in the near future to leave their cages and move freely in our modern homes and manufacturing sites. Musculoskeletal robots are such soft robots which feature passively compliant actuation, while leveraging the advantages of tendon-driven systems. Even though these robots have been intensively researched within the last decade, high-performance feedback control laws have only very recently been developed. In [1], a controller was developed utilizing Dynamic Surface Control (DSC), an extension to backstepping, with an adaptive neural network compensator for joint as well as muscle friction. We compare these novel control strategies to Computed Force Control (CFC), an existing technique from the field of tendon-driven control, yielding highly improved trajectory tracking. The musculoskeletal robot Anthrob [2] serves as a benchmark.
SLM : Synchronized Live Migration of Virtual Clusters across Data Centers

Cluster platforms, deployed in data centers worldwide, are the backbone of the popular cloud computing services. For scalability, manageability and resource utilization, one physical machine in the cloud platform can be virtualized into a bundle of virtual machines (VMs). Each VM works as an independent node. To solve a time consuming task, several VMs are grouped as a virtual cluster and collaborate on the task. It’s essential for a cloud computing platform to support live migration of virtual clusters. First, virtual cluster migration enables load-management in data centers [1, 5, 3]. Second, live migration of virtual cluster provides transparent infrastructure maintenance [3]. Third, virtual cluster migration can be used to support enterprise IT consolidation [5]. Finally, flexible deployment of virtual clusters across data centers is also a key enabler of federated clouds [1]. Co-migration of a group of VMs and migration of virtual clusters have attracted considerable interest for data center management [1, 5, 3] and HPC cluster computing [2]. VCT [2] focuses on devising mechanisms to manage a tightly coupled HPC virtual cluster as a single entity, making cluster level operation such as suspending, migrating or resuming a synchronous process across all nodes. However, VCT requires the cluster to be offline for as long as tens of minutes. Many time sensitive applications and services cannot afford this extended downtime. VMFlock, CloudNet and Shrinker [1, 5, 3] employ the same technique, data deduplication, to reduce the network traffic during migration. Besides eliminating redundant data, VMFlock also accelerates instantiation of the applications at the target data center through transferring the essential set of data blocks first. CloudNet employs dynamic VPN connectivity to migrate networks and “smart stop and copy”to intelligently pick when to halt the iterative transfer of dirty pages to decrease downtime and latency. VMFlock, CloudNet and Shrinker have succeeded in eliminating the migration of redundant data blocks so as to reduce network traffic and total migration time. However, VMFlock adapts an offline migration mode. CloudNet and Shrinker, though they support live migration, both fail to consider that VMs in a cluster still need to collaborate on tasks during live migration.