Miracle-dz/UniFAR-FTUs huggingface dataset:
Reachability testing of concurrent programs

One approach to testing concurrent programs, called reachability testing, generates synchronization sequences automatically and on-the-fly, without constructing any static models. In this paper, we present a general execution model for concurrent programs that allows reachability testing to be applied to several commonly used synchronization constructs. We also present a new method for performing reachability testing. This new method guarantees that every partially ordered synchronization sequence will be exercised exactly once without having to save any sequences that have already been exercised. We describe a prototype reachability testing tool called RichTest and report some empirical results, including a comparison between RichTest and a partial order reduction-based tool called VeriSoft. RichTest performed significantly better for the programs in our study
Standardization of antifungal susceptibility testing.

The application of in-vitro antifungal susceptibility testing to clinical research and to the guidance of antifungal therapy has been limited by a lack of reproducibili ty and uncertain clinical relevance. As a result of studies of the identified variables impacting on in-vitro susceptibility results, the National Committee for Clinical Laboratory Standards have proposed a standardized antifungal susceptibility test method M27-P. The degree of intra- and inter-laboratory reproducibility which can be achieved with this method have been defined in multi-laborat ory collaborative studies. More convenient methods (microdilution broth and stable gradient technology) have been evaluated relative to the proposed standard method and the potential for a similar process with a disc diffusion method is apparent. A modification of this standard method for susceptibility testing of filamentous fungi appears promising. The existence of a standardized method and of alternative methods with a defined relationship to the proposed standard, facilitates meaningful analysis of published studies addressing the issue of clinical relevance of antifungal susceptibility testing. As a result of this process, correlation of MICs determined in vitro with clinical response to therapy is beginning to emerge, most notably in relation to fluconazole therapy for oropharyngeal candidosis associated with infection with the human immunodeficiency virus
Scalable routing for networked sensors and actuators

The design of efficient routing protocols for ad hoc and sensor networks is challenging for several reasons: Physical network topology is random. Nodes have limited computation and memory capabilities. Energy and bisection bandwidth are scarce. Furthermore, in most settings, the lack of centralized components leaves all network control tasks to the nodes acting as decentralized peers. In this paper, we present a novel routing algorithm, scalable source routing (SSR), which is capable of memory and message efficient routing in large random networks. A guiding example is a community of 'digital homes' where smart sensors and actuators are installed by laypersons. Such networks combine wireless ad-hoc and infrastruc- ture networks, and lack a well-crafted network topology. Typically, the nodes do not have sufficient processing and memory resources to perform sophisticated routing algorithms. Flooding on the other hand is too bandwidth- consuming in the envisaged large-scale networks. SSR is a fully self-organizing routing protocol for such scenarios. It creates a virtual ring that links all nodes via predecessor/successor source routes. Additionally, each node possesses O(logN) short-cut source routes to nodes in exponentially increasing virtual ring distance. Like with the Chord overlay network, this ensures full connectivity within the network. Moreover, it provides a routing se- mantic which can efficiently support indirection schemes like i3. Memory and message efficiency are achieved by the introduction of a route cache together with a set of path manipulation rules that allow to produce near-to-optimal paths.
Localization of Active Pathways in Peripheral Nerves: A Simulation Study

A methodology is investigated for determining the location of active pathways in a peripheral nerve using measurements from a multicontact cuff electrode. The problem is treated as an inverse problem of source localization and solved using the sLORETA algorithm, developed for the electroencephalogram/magnetoencephalogram source localization problem. Simulated measurements are generated corresponding to action potentials traveling along either one or three pathways in a rat sciatic nerve. The performance of the proposed methodology using these measurements is evaluated in terms of localization error, missed pathways, and spurious pathways. The source localization performance when assuming an idealized nerve anatomy is compared to that when the correct anatomy is known. The effect of a spatio-temporal constraint based on the nerve anatomy and electrophysiology is also investigated. The approach in its present form was not found to be sufficiently reliable for subfascicular localization in practice, due to mean localization errors in the 140-180 mum range, high numbers of spurious pathways, and low resolution. Nonetheless, the constraints were shown to produce a marked reduction in the number of spurious pathways. Conditions under which the source localization approach may be useful for peripheral nerves are discussed.
Load balancing techniques for distributed stream processing applications in overlay environments

Service overlays that support distributed stream processing applications are increasingly being deployed in wide-area environments. The inherent heterogeneous, dynamic and large-scale nature of these systems makes it difficult to meet the quality of service (QoS) requirements of the distributed stream processing applications. In this paper we address the load balancing problem for distributed stream processing applications and present a decentralized and adaptive algorithm that allows the composition of distributed stream processing applications on the fly across a large-scale system, while satisfying their QoS demands. The algorithm fairly distributes the load on the resources and adapts dynamically to changes in the resource utilization or the QoS requirements of the applications. Our experimental results demonstrate the scalability, efficiency and performance of our approach
A Hausdorff-type distance, a directional derivative of a set-valued map and applications in set optimization

Abstract In this paper, we follow Kuroiwa’s set approach in set optimization, which proposes to compare values of a set-valued objective map F with respect to various set order relations. We introduce a Hausdorff-type distance relative to an ordering cone between two sets in a Banach space and use it to define a directional derivative for F. We show that the distance has nice properties regarding set order relations and the directional derivative enjoys most properties of the one of a scalar single-valued function. These properties allow us to derive necessary and/or sufficient conditions for various types of maximizers and minimizers of F.
Experimentally Verified Parameter Sets for Modelling Heterogeneous Neocortical Pyramidal-Cell Populations

Models of neocortical networks are increasingly including the diversity of excitatory and inhibitory neuronal classes. Significant variability in cellular properties are also seen within a nominal neuronal class and this heterogeneity can be expected to influence the population response and information processing in networks. Recent studies have examined the population and network effects of variability in a particular neuronal parameter with some plausibly chosen distribution. However, the empirical variability and covariance seen across multiple parameters are rarely included, partly due to the lack of data on parameter correlations in forms convenient for model construction. To addess this we quantify the heterogeneity within and between the neocortical pyramidal-cell classes in layers 2/3, 4, and the slender-tufted and thick-tufted pyramidal cells of layer 5 using a combination of intracellular recordings, single-neuron modelling and statistical analyses. From the response to both square-pulse and naturalistic fluctuating stimuli, we examined the class-dependent variance and covariance of electrophysiological parameters and identify the role of the h current in generating parameter correlations. A byproduct of the dynamic I-V method we employed is the straightforward extraction of reduced neuron models from experiment. Empirically these models took the refractory exponential integrate-and-fire form and provide an accurate fit to the perisomatic voltage responses of the diverse pyramidal-cell populations when the class-dependent statistics of the model parameters were respected. By quantifying the parameter statistics we obtained an algorithm which generates populations of model neurons, for each of the four pyramidal-cell classes, that adhere to experimentally observed marginal distributions and parameter correlations. As well as providing this tool, which we hope will be of use for exploring the effects of heterogeneity in neocortical networks, we also provide the code for the dynamic I-V method and make the full electrophysiological data set available.
A mathematical model of pH, based on the total stoichiometric concentration of acids, bases and ampholytes dissolved in water*

In chemistry and in acid-base physiology, the Henderson-Hasselbalch equation plays a pivotal role in studying the behaviour of the buffer solutions. However, it seems that the general function to calculate the valence of acids, bases and ampholytes, N = f(pH), at any pH, has only been provided by Kildeberg. This equation can be applied to strong acids and bases, pluriprotic weak acids, bases and ampholytes, with an arbitrary number of acid strength constants, pKA, including water. By differentiating this function with respect to pH, we obtain the general equation for the buffer value. In addition, by integrating the titration curve, TA, proposed by Kildeberg, and calculating its Legendre transform, we obtain the Gibbs free energy of pH (or pOH)-dependent titratable acid. Starting from the law of electroneutrality and applying suitable simplifications, it is possible to calculate the pH of the buffer solutions by numerical methods, available in software packages such as Excel. The concept of buffer capacity has also been clarified by Urbansky, but, at variance with our approach, not in an organic manner. In fact, for each set of monobasic, dibasic, tribasic acids, etc., various equations are presented which independently fit each individual acid-base category. Consequently, with the increase in acid groups (pKA), the equations become more and more difficult, both in practice and in theory. Some examples are proposed to highlight the boundary that exists between acid-base physiology and the thermodynamic concepts of energy, chemical potential, amount of substance and acid resistance.
The Participation of Activated Peritoneal Macrophages in Treponema pallidum Subspecies pertenue Infection in Syrian Hamsters

The role of cell‐mediated immunity in hamsters during treponemal infection appears to involve the activated macrophage. To date, studies have been hindered by the inability to confirm that macrophages exhibit enhanced treponemicidal activity at the infection site. We show that lipopolysaccharide and thioglycollate‐treated animals, when inoculated with Treponema pallidum subsp. pertenue, exhibit enhanced clearance of these organisms compared with controls. Macrophages from these infected groups display an enhanced respiratory burst, as detected by NBT reduction, as well as a marked increase in C3b receptor‐mediated ingestion activity. Signficiant changes in these parameters indicate that alterations in macrophage activation are occurring in the infected compartment. Thus the stimulatory agents apparently modify the host's immune responses to promote subsequent reduction of treponemal infection. In addition, hamster peritoneal macrophages demonstrate enhanced activation behavior as a result of exposure to at least two signals, which may be prerequisite for processing this organism efficiently.
Storytelling strategies for leading change in university prestige

xv Chapter 1: Introduction of the Problem . 1 Organization of the Chapter . 1 Purpose of the Study . 4 Statement of Problem and Background . 2 Research Questions . 4 Design of the Study and Conceptual Framework . 5 The Study’s Significance . 6 Limitations . 9 Operational Definitions . 10 Summary . 12 Chapter 2: Literature Review . 14 Organization of the Chapter . 14 Governance and structure . 15 An Overview of the American University System . 14 University finance . 17 Academic curriculum and instruction . 18 University students. 21 University Prestige . 22 The search for prestige . 22 Prestige and reputation . 23 Value and cost of seeking prestige . 25 Elements of University Prestige. 27 Students . 27 Faculty. 29 Rankings . 30 Financial stability . 33 Resource distribution . 34 Organizational Change . 35 The challenges of change . 36
Topographic distribution of brain activities corresponding to psychological structures underlying affective meanings: An fMRI study

Affective meanings aroused by various objects, such as paintings, melodies, or words, can be quantified by the semantic differential (SD) technique (Osgood, Suci, & Tannenbaum, 1957). In this technique, three main factors (“Evaluation,”“Activity,” and “Potency”) have been consistently extracted from factor analyses of participants' subjective ratings of various objects using bipolar scales of adjective pairs. In the present study, we investigated brain activity during SD ratings of line-drawing stimuli using functional magnetic resonance imaging (fMRI). We compared brain activity among the three main factors underlying affective meanings. The overall results showed that Evaluation, Activity, and Potency produced brain activities in the inferior frontal gyrus, the superior temporal gyrus, and the superior frontal gyrus, respectively. These findings suggest that the psychological structures underlying affective meanings are distributed in specific areas of the brain.
An Algorithm Based on the Standard Deviation of Passive Microwave Brightness Temperatures for Monitoring Soil Surface Freeze/Thaw State on the Tibetan Plateau

The land surface on the Tibetan Plateau (TP) experiences diurnal and seasonal freeze/thaw processes that play important roles in the regional water and energy exchanges, and passive microwave satellites provide opportunities to detect the soil state for this region. With the support of three soil moisture and temperature networks on the TP, a dual-index microwave algorithm with Advanced Microwave Scanning Radiometer-Earth Observing System data is developed for the detection of soil surface freeze/thaw state. One index is the standard deviation index (SDI) of brightness temperature (TB), which is defined as the standard deviation of horizontally polarized brightness temperatures at 6.9, 10.7, 18.7, 23.8, 36.5, and 89.0 GHz. It is the major index and is used to reflect the reduction of liquid water content after soils get frozen. The other index is the 36.5-GHz vertically polarized brightness temperature (TB36.5V), which islinearly correlated with ground temperature. The threshold values of the two indices (SDI and TB36.5V) are determined with one grid from the network located in a semiarid climate, and the algorithm is validated with other grids from the same network. Further validations are conducted based on the other two networks located in different climates (semihumid and arid, respectively). Results show that the classification accuracy using this algorithm is more than 90% for the semihumid and semiarid regions, and misclassifications mainly occur at the transition period between unfrozen and frozen seasons. Nevertheless, the algorithm has limited capability in identifying the soil surface freeze/thaw state in the arid region because the microwave signals can penetrate deep dry soils and thus embody the bulk information beyond the surface layer.
Effects of a Tier 2 Supplemental Reading Intervention for At-Risk Fourth-Grade Students

This study investigated a Tier 2 intervention in the context of a response-to-intervention (RTI) model for 123 fourth-grade students identified as having a high probability of reading failure. A randomized control trial was used to evaluate the effects of a 24-session multicomponent supplemental intervention targeting fluency and expository comprehension of science texts. Intervention students performed significantly higher on science knowledge and comprehension strategy knowledge and use, but not on word reading, fluency, or other measures of reading comprehension. Moderators of intervention effects were also examined; children at higher risk in the intervention condition appeared to benefit more in comparison to lower probability children in intervention and compared to higher probability children in the control condition.
The effectiveness of two novel techniques in establishing the mechanical and contractile responses of biceps femoris

Portable tensiomyography (TMG) and myotonometry (MMT) devices have been developed to measure mechanical and contractile properties of skeletal muscle. The aim of this study was to explore the sensitivity of the aforementioned techniques in detecting a change in passive mechanical properties of the biceps femoris (BF) muscle as a result of change in knee joint angle (i.e. muscle length). BF responses were assessed in 16 young participants (23.4 ± 4.9 years), at three knee joint angles (0°, 45° and 90°), for maximal isometric torque (MIT) along with myo-electrical activity. Contractile and mechanical properties were measured in a relaxed state. Inter-day reliability of the TMG and MMT was also assessed. MIT changed significantly (p < 0.01) across the three angles, so did stiffness and other parameters measured with MMT (p < 0.01). Conversely, TMG could detect changes only at two knee angles (0° and 45°, p < 0.01), when there is enough tension in the muscle. Reliability was overall insufficient for TMG whilst absolute reliability was excellent (coefficient of variation < 5%) for MMT. The ability of MMT more than TMG to detect an inherent change in stiffness can be conceivably exploited in a number of clinical/therapeutic applications that have to do with unnatural changes in passive muscle stiffness.
Towards understanding TCP performance on LTE/EPC mobile networks

The popularity of smartphones and smartphone applications means that data is the dominant traffic type in current mobile networks. In this paper we present our work on a systematic investigation into facets of the LTE/EPC architecture that impact the performance of TCP as the predominant transport layer protocol used by applications on mobile networks. We found that (1) load increase in a cell causes dramatic bandwidth reduction on UEs and significantly degrades TCP performance, (2) seamless handover causes significant TCP losses while lossless handover increases TCP segments' delay.
Entity identification in database integration

The objective of entity identification is to determine the correspondence between object instances from more than one database. Entity identification at the instance level, assuming that schema level heterogeneity has been resolved a priori, is examined. Soundness and completeness are defined as the desired properties of any entity identification technique. To achieve soundness, a set of identity and distinctness rules are established for entities in the integrated world. The use of extended key, which is the union of keys, and possibly other attributes, from the relations to be matched, and its corresponding identify rule are proposed to determine the equivalence between tuples from relations which may not share any common key. Instance level functional dependencies (ILFD), a form of semantic constraint information about the real-world entities, are used to derive the missing extended key attribute values of a tuple. <<ETX>>
Auditory temporal resolution in children assessed by magnetoencephalography

By means of magnetoencephalography we investigated the auditory-evoked fields (AEFs) elicited by broadband noise bursts in a gap-detection paradigm in children. AEFs of 16 healthy children (mean age 8.7 years) were recorded while they passively listened to 100-ms white-noise bursts with temporal gaps of 3, 6, 10 and 30 ms inserted after 5 or 50 ms. The peak of the earliest and largest positivity occurred at 97 ms and was evaluated by spatiotemporal source analysis. Psychophysical gap-detection thresholds were obtained for the same children. We found that the neuromagnetic gap responses corresponded to the psychoacoustic thresholds. AEFs thus provide an objective tool to assess auditory temporal resolution in children. Children's neuromagnetic response patterns differed significantly from the adult responses under the same experimental conditions.
Asymptotic performance of hybrid-selection/maximal-ratio combining over fading channels

In this letter, we study the asymptotic performance of hybrid-selection/maximal-ratio combining (HS/MRC) and postdetection HS/equal-gain combining (HS/EGC) over generalized fading channels for large average signal-to-noise ratios (ASNRs). By evaluating the asymptotic moment generating function of the HS/MRC output SNR at high ASNR, we derive the diversity and coding gains for HS/MRC for a large class of modulation formats and versatile fading conditions, including different types of fading channels and nonidentical SNR statistics across diversity branches. Our analytical results reveal that the diversity gains of HS/MRC and HS/EGC are equivalent to that of MRC, and the difference in the coding gains for different modulation formats is manifested in terms of a modulation factor defined in this letter. Some new analytical results about effects of the number of combined branches for HS/MRC and noncoherent combining loss of HS/EGC are also provided.
Classification of COPD with Multiple Instance Learning

Chronic obstructive pulmonary disease (COPD) is a lung disease where early detection benefits the survival rate. COPD can be quantified by classifying patches of computed tomography images, and combining patch labels into an overall diagnosis for the image. As labeled patches are often not available, image labels are propagated to the patches, incorrectly labeling healthy patches in COPD patients as being affected by the disease. We approach quantification of COPD from lung images as a multiple instance learning (MIL) problem, which is more suitable for such weakly labeled data. We investigate various MIL assumptions in the context of COPD and show that although a concept region with COPD-related disease patterns is present, considering the whole distribution of lung tissue patches improves the performance. The best method is based on averaging instances and obtains an AUC of 0.742, which is higher than the previously reported best of 0.713 on the same dataset. Using the full training set further increases performance to 0.776, which is significantly higher (DeLong test) than previous results.