Miracle-dz/UniFAR-FTUs huggingface dataset:
Balancing dwell times for switching linear systems

Switching Linear Systems (SLSs) are a subclass of hybrid systems characterized by a Finite State Machine (FSM) and a set of linear dynamical systems, each corresponding to a state of the FSM. The transition between two di? erent states of the FSM is caused by external uncontrollable events that act as discrete disturbances. In the past few years structural properties of SLSs have been the topic of intensive study and in particular much work has been devoted to the attempt of characterizing their stability and/or stabilizability properties. We focus on the class of uncontrolled SLSs with a dwell time associated to each transition. Loosely, a dwell time function assigns to each transition a dwell time that serves as a minimal delay for the transitions. Notice that in our setting the dwell time is associated with transitions rather than with locations. The motivation to use the notion of dwell time function lies in the possibility to quantify the balance between long delays for some transitions and short delays for others. For instance, in a cycle of transitions, instantaneous transitions could be compensated by long delays elsewhere in the cycle. A recent result (see �Can linear stabilizability analysis be generalized to switching systems? � by E. De Santis, M.D. Di Benedetto, G. Pola), which extends Kalman decomposition to the class of controlled SLSs, shows that a controlled SLS is asymptotically stabilizable if and only if an uncontrolled SLS, appropriately associated to the controlled SLS, is asymptotically stable. Then, the stabilizability problem for the class of controlled SLSs directly translates to the stability analysis of uncontrolled SLSs. Therefore, we focus on stability problems for uncontrolled SLSs. It is well-known that if transitions are sufficiently delayed and if the dynamics in each location is asymptotically stable, then the uncontrolled SLS is asymptotically stable. The case of stability under quadratic Lyapunov function analysis is investigated. In this special case, an explicit condition on the dwell time function that ensures asymptotic stability is provided. Although this condition is based on estimates and is therefore conservative, it yields the possibility of instantaneous transitions when applied to the case where a common quadratic Lyapunov function exists. With respect to previous work in this research area, our approach gives less conservative conditions.
Handling Large Web Services Models in a Federated Governmental Information System

Experiments with large service models of a federated governmental information system are described. Large syntactic Web service models are being used for automatic composition of services in an e-government information system. A visual tool developed in software environment CoCoViLa has been used for handling syntactic service models and synthesis of compound services. For a given specification and a goal, the tool synthesizes a program that generates a service description in OWLS and BPEL.
Adaptive Fuzzy Total Sliding-Mode Control of Unknown Nonlinear Systems

This paper proposes the adaptive fuzzy total sliding-mode control systems with integral (I-AFTSMC) and proportional-integral (PI-AFTSMC) learning algorithms for the unknown nonlinear systems. These AFTSMC systems are comprised of a fuzzy total sliding-mode controller and a robust controller. The fuzzy total sliding-mode controller is utilized to approximate an ideal controller and the robust controller is designed to cover the approximation error between the fuzzy total sliding-mode controller and the ideal controller. In these designs the fuzzy rules are on-line tuned by the derived learning algorithm in the sense of Lyapunov function, so that the stability of the system can be guaranteed. The proposed AFTSMC systems are applied to the fault accommodation control of a Van der Pol oscillator and trajectory tracking control of a linear piezoelectric ceramic motor. The simulation result of Van der Pol oscillator and the experimental result of linear piezoelectric ceramic motor demonstrate that the effectiveness of the proposed AFTSMC systems for achieving favorable tracking performance. Comparing to the integral learning algorithm, the proportional-integral learning algorithm can achieve faster convergence of the tracking error; this comparison is also illustrated by the simulations and experiments.
Prevention of contrast induced nephropathy: Recommendations for the high risk patient undergoing cardiovascular procedures

Contrast induced nephropathy (CIN) is the third leading cause of hospital aquired renal failure and is associated with significant morbidity and mortality. Chronic kidney disease is the primary predisposing factor for CIN. As estimated glomerular filtration rate <60 ml/1.73 m2 represents significant renal dysfunction and defines patients at high risk. Modifiable risk factors for CIN include hydration status, the type and amount of contrast, use of concomitant nephrotoxic agents and recent contrast administration. The cornerstone of CIN prevention, in both the high and low risk patients, is adequate parenteral volume repletion. In the patient at increased risk for CIN it is often appropriate to withhold potentially nephrotoxic medications, and consider the use of n‐acetylcysteine. In patients at increased risk for CIN the use of low or iso‐osomolar contrast agents should be utilized and strategies employed to minimize contrast volume. In these patients serum creatinine should be obtained forty‐eight hours post procedure and it is often appropriate to continue withholding medications such as metformin or non steroidal anti‐inflammatories until renal function returns to normal. © 2006 Wiley‐Liss, Inc.
Trigger Extraction in Biological Text for Question Answering [ CS 224 N ] Fall 2012 : 12-7-12

When confronted with a large amount of text, it is difficult to manually extract important and relevant information from it. Having a way to extract that information is a highly interesting research problem that has the potential to improve question answering capabilities. Specifically, identifying sections of text that describe a term, phenomenon, or abstract idea and transforming them into structured formats is useful for returning answers based on knowledge and understanding of the text or document rather than answers based on similarity metrics like those used by search engines.
Bee Venom Acupuncture Augments Anti-Inflammation in the Peripheral Organs of hSOD1G93A Transgenic Mice

Amyotrophic lateral sclerosis (ALS) includes progressively degenerated motor neurons in the brainstem, motor cortex, and spinal cord. Recent reports demonstrate the dysfunction of multiple organs, including the lungs, spleen, and liver, in ALS animals and patients. Bee venom acupuncture (BVA) has been used for treating inflammatory diseases in Oriental Medicine. In a previous study, we demonstrated that BV prevented motor neuron death and increased anti-inflammation in the spinal cord of symptomatic hSOD1G93A transgenic mice. In this study, we examined whether BVA’s effects depend on acupuncture point (ST36) in the organs, including the liver, spleen and kidney, of hSOD1G93A transgenic mice. We found that BV treatment at ST36 reduces inflammation in the liver, spleen, and kidney compared with saline-treatment at ST36 and BV injected intraperitoneally in symptomatic hSOD1G93A transgenic mice. Those findings suggest that BV treatment combined with acupuncture stimulation is more effective at reducing inflammation and increasing immune responses compared with only BV treatment, at least in an ALS animal model.
Correlates of Depressive and Anxiety Symptoms in Young Adults with Spina Bifida *

Objective Based on social ecological theory, this study was designed to examine the unique relationships between multi-level ecological factors and psychological symptoms in young adults with spina bifida (SB). Method A sample of 61 individuals with SB, 18–25 years of age, completed standardized self-report measures of attitude toward SB, satisfaction with family functioning, Chronic Care Model (CCM) services, and depressive and anxiety symptoms. A chart review yielded SB clinical data. Results High rates of depressive and anxiety symptoms were found. Hierarchical regression analysis identified the proximal individual (attitude toward SB) and family (satisfaction with family functioning) factors as more strongly related to depressive symptoms than the distal healthcare system factor (CCM services). Self-reported pain was the only ecological factor associated with anxiety symptoms. Conclusions Study findings provide a potential foundation for multi-factor screening of young adults with SB at risk for psychological symptoms.
Quality Based Software Project Staffing and Scheduling with Cost Bound

Software project planning is becoming more complicated and important as the size of software project grows. Many approaches have been proposed to help project managers by providing optimal staffing and scheduling in terms of minimizing the cost (i.e., necessary expanse) or time (i.e., time span or duration) required for the software project. Unfortunately, the software quality, another critical factor in software project planning, is largely overlooked in previous work. In this paper, we propose the quality based software project staffing and scheduling approach using a genetic algorithm (GA). We define a quality score by considering practical issues in software project planning in addition to task severity and defect amplification model. Further, the cost is utilized as a cost-bound in the GA to consider not only quality but also cost. Case study shows that the proposed approach improves the quality while the cost is optimized as the same as the cost-based approach. In other words, we provide better software project plans considering both cost and quality for software project managers. Also, we show the relationship between the quality and the cost in terms of software project planning.
Unravelling the environmental drivers of deep-sea nematode biodiversity and its relation with carbon mineralisation along a longitudinal primary productivity gradient

Alongside a primary productivity gradient between the Galicia Bank region in the Northeast Atlantic and the more oligotrophic eastern Mediterranean Basin, we investigated the bathymetric (1200–3000 m) and longitudinal variation in several measures for nematode taxon (Shannon–Wiener genus diversity, expected genus richness and generic evenness) and functional diversity (trophic diversity, diversity of life history strategies, biomass diversity and phylogenetic diversity). Our goals were to establish the form of the relation between diversity and productivity (measured as seafloor particulate organic carbon or POC flux), and to verify the positive and negative effect of sediment particle size diversity (SED) and the seasonality in POC flux (SVI), respectively, on diversity, as observed for other oceanographic regions and taxa. In addition, we hypothesised that higher taxon diversity is associated with higher functional diversity, which in turn stimulates nematode carbon mineralisation rates (determined from biomass-dependent respiration estimates). Taxon diversity related positively to seafloor POC flux. Phylogenetic diversity (measured as average taxonomic distinctness) was affected negatively by the magnitude and variability in POC flux, and positively by SED. The latter also showed an inverse relation with trophic diversity. Accounting for differences in total biomass between samples, we observed a positive linear relation between taxon diversity and carbon mineralisation in nematode communities. We could, however, not identify the potential mechanism through which taxon diversity may promote this ecosystem function since none of the functional diversity indices related to both diversity and nematode respiration. The present results suggest potential effects of climate change on deep-sea ecosystem functioning, but further also emphasise the need for a better understanding of nematode functions and their response to evolutionary processes.
Robust Stabilization of linear stochastic differential models with additive and multiplicative diffusion via attractive ellipsoid techniques

Linear controlled stochastic differential equations (LCSDE) subject to both multiplicative and additive stochastic noises are considered. We study a robust “practical” stabilization for this class of LCSDE meaning that almost all trajectories of this stochastic model converges in a “mean-square sense” to a bounded zone located in an ellipsoidal set. Also, we present a result related to convergence in probability one sense to a zero zone. The considered stabilizing feedback is supposed to be linear. This problem is shown to be converted into the corresponding attractive averaged ellipsoid “minimization” under some constraints of BMI's (Bilinear Matrix Inequalities) type. The application of an adequate coordinate changing transforms these BMI's into a set of LMI's (Linear Matrix Inequalities) that permits to use directly the standard MATLAB - toolbox. A numerical example is used to illustrate the effectiveness of this methodology.
A very-high impedance current mirror for bio-medical applications

In many biomedical applications operating at low voltage require very high output impedance current mirror. In this paper, “A Very high impedance current mirror, with less number of transistors which can operate at low voltage without any additional biasing circuitry” is proposed. The proposed current mirror uses MOS current dividers to sample the output current to achieve very high impedance with a large output and voltage range. A feedback action is used to force the input and output currents to be equal. The proposed circuit is also insensitive to the biasing current. This implementation yields an increase in the output impedance by a factor of about gmrout compared with that of the super-Wilson current mirror, thus offering a potential solution to mitigate the effect of the low output impedance of deep submicron CMOS transistors used in low voltage current mirrors and current sources. An NMOS version of the proposed current mirror circuit was implemented using an UMC-180nm CMOS process and simulated using Spectre to validate its performance. The output current is mirrored with a transfer error lower than 1% when the input current is increased from 5 to 40 µA.
Detailed passive cable models of whole-cell recorded CA3 pyramidal neurons in rat hippocampal slices

Tight-seal whole-cell recordings were made from cleaned somata of CA3 pyramidal cells deep in hippocampal slices from 19–21-d-old rats. The cells were filled with biocytin, and their voltage responses to short current pulses were recorded. After washout of initial sag, responses scaled linearly with injected current and were stable over time. The dendritic and axonal arbors of four cells were reconstructed and measured using light microscopy. Dendritic spines and axonal boutons were counted and the additional membrane area was incorporated into the relevant segments. The morphology of each neuron was converted into a detailed branching cable model by assuming values for specific membrane capacitance Cm and resistance Rm, and cytoplasmic resistivity Ri. These parameters were optimized for each cell by directly matching the model's response to that of the real cell by means of a modified weighted least-squares fitting procedure. By comparing the deviations between model and experimental responses to control noise recordings, approximate 95% confidence intervals were established for each parameter. If a somatic shunt was allowed, a wide range of possible Rm values produced acceptable fits. With zero shunt, Cm was 0.7–0.8 microFcm-2, Ri was 170–340 omega cm, and Rm ranged between 120 and 200 k omega cm2. The electrotonic lengths of the basal and oblique dendrites were 0.2–0.3 space constants, and those of the apical tufts were 0.4–0.7 space constants. The steady-state electrical geometry of these cells was therefore compact; average dendritic tip/soma relative synaptic efficacies were > 93% for the basal and oblique dendrites, and > 81% for the tufts. With fast transient synaptic inputs, however, the models produced a wide range of postsynaptic potential shapes and marked filtering of voltage-clamp currents.
TDVMP: Improved Virtual Machine-Based Software Protection with Time Diversity

The VM (Virtual effective solution to protect software, making it extremely a Machine)-based software protection technique provides difficulty to analyze and crack. In this paper, we improve it from two aspects. Firstly, the time diversity is to fight against cumulative attack by making software executing along variant paths in different running time. Secondly, transform instructions in an execution path with reducing performance penalty through controlling deformation strategy. At last, we design and develop a VM-based protection with time diversity system, named TDVMP, and carry out some experiments with it. The results show that the improvements are effective.
On the Root Causes of Cross-Application I/O Interference in HPC Storage Systems

As we move toward the exascale era, performance variability in HPC systems remains a challenge. I/O interference, a major cause of this variability, is becoming more important every day with the growing number of concurrent applications that share larger machines. Earlier research efforts on mitigating I/O interference focus on a single potential cause of interference (e.g., the network). Yet the root causes of I/O interference can be diverse. In this work, we conduct an extensive experimental campaign to explore the various root causes of I/O interference in HPC storage systems. We use microbenchmarks on the Grid'5000 testbed to evaluate how the applications' access pattern, the network components, the file system's configuration, and the backend storage devices influence I/O interference. Our studies reveal that in many situations interference is a result of bad flow control in the I/O path, rather than being caused by some single bottleneck in one of its components. We further show that interference-free behavior is not necessarily a sign of optimal performance. To the best of our knowledge, our work provides the first deep insight into the role of each of the potential root causes of interference and their interplay. Our findings can help developers and platform owners improve I/O performance and motivate further research addressing the problem across all components of the I/O stack.
Active Information Retrieval for Linking Twitter Posts with Political Debates

Users of microblogging social networks produce millions of short messages every day. Retrieving relevant information to a particular event from this sheer volume of data is not a trivial task. In this paper, we present a framework for the retrieval of Twitter posts that are relevant to a set of political debates. Our main contribution is the proposal of a set of strategies for involving the user in the retrieval process, so that by presenting to her meaningful posts to be labeled, the method achieves a noticeably higher accuracy. The correct retrieval or labeling could be provided by an external information source such as a domain expert, or simulated with an oracle. A key aspect of active retrieval methods is to request the labels of the instances that help improve the retrieval accuracy the most, while keeping the number of labeling requests to a minimum. The proposed strategies for selecting labeling requests make use of the textual content of tweets and their structural information. The experimental results show the advantages of the proposed methods and the effectiveness of the selection strategies for involving the user in the retrieval process.
Does Competition Destroy Ethical Behavior?

Explanations of unethical behavior often neglect the role of competition, as opposed to greed, in assuring its spread. Using the examples of child labor, corruption, excessive' executive pay, corporate earnings manipulation, and commercial activities by universities, this paper clarifies the role of competition in promoting censured conduct. When unethical behavior cuts costs, competition drives down prices and entrepreneurs' incomes, and thereby reduces their willingness to pay for ethical conduct. Nonetheless, I suggest that competition might be good for ethical behavior in the long run, because it promotes growth and raises incomes. Higher incomes raise the willingness to pay for ethical behavior, but may also change what people believe to be ethical for the better.
Severity at baseline and onset of improvement in depression. Meta-analysis of imipramine and moclobemide versus placebo

Summary Meta-analysis of several double-blind, placebo-controlled studies, including 1277 patients, has been performed in order to compare the efficacy of moclobemide, a new reversible and selective MAO-A inhibitor (RIMA) and imipramine. The main interest of the analysis was to test the time course of improvement and the impact of the pre-defined outcome criteria (50% reduction of total HAMD score) on the response to treatment, if initial severity of depression and drop-outs due to inefficacy are taken into consideration. In order to analyze the interdependence of the severity of the disease and outcome, patient sample was subdivided into three HAMD (17 items) baseline score groups: low- (score ≤ 21), medium- (22-27) and high (≥ 28) scorers. We found that reliable assessment of the point in time at which a drug begins to show therapeutic effect in each individual is a critical factor in the determination of the time course of improvement. We defined therefore the onset of improvement as the time point of a significant decrease (20%) of HAMD baseline score without subsequent deterioration. The threshold for the distinction between a significant change and spontaneous fluctuations, or error variations due to instrument or observer, was the natural variability of the HAMD score during the first two observation days. The results of the analysis replicated our earlier findings and confirmed that in treatment responders the time course of improvement is identical under placebo and antidepressants. Neither the time-points of the onset of effect, nor the time-points at which a 50% decrease of HAMD was reached, differed between the groups. In particular, no treatment- Specific time lag showed up in the onset of action. The difference in efficacy between antidepressants and placebo was evident only in the total number of responders and non-responders. Moreover, onset of improvement within the first 10 days of treatment, which was observed in 40-50% of patients, was highly predictive of the final response to treatment. The rate of correctly predicted responders in our sample was 70% for all three treatment modalities. With respect to the severity of the disease, a slight shift towards earlier onset of improvement was found for more severe cases. This finding was true for placebo and drug responders hut there was no clear-cut other interdependence with the treatment outcome. Drop-out rales due to inefficacy were in this study similar under all treatments (20-24%) anil occurred mostly during the first two weeks of the trial (64-71%.).
Dynamic scheduler for multi-core systems

Many dynamic scheduling algorithms have been proposed in the past. With the advent of multi core processors, there is a need to schedule multiple tasks on multiple cores. The scheduling algorithm needs to utilize all the available cores efficiently. The multicore processors may be SMPs or AMPs with shared memory architecture. In this paper, we propose a dynamic scheduling algorithm in which the scheduler resides on all cores of a multi-core processor and accesses a shared Task Data Structure (TDS) to pick up ready-to-execute tasks. This method is unique in the sense that the processor has the onus of picking up tasks whenever it is idle. We have discussed the proposed scheduling algorithm using a set of tasks as an example. The paper concludes with the discussion of advantages and limitations of the proposed scheduling algorithm.