Miracle-dz/UniFAR-FTUs huggingface dataset:
Manipulating source code in DynamicDesign

DynamicDesign is a Computer-Aided Software Engineering environment for the C language with a layered system architecture for modularity and versatility. DynamicDesign is composed of facilities to edit hypertext objects, maneuver thorough hypertext graphs, build a hypertext graph from a set of existing C source files, and browse source code, documents and system requirements. This paper discusses the DynamicDesign facilities that deal with the source code, sourceBrowser, and source tree builder utilities. GraphBuild is a utility used to convert C source code into a hypertext source graph, based on the program's call tree. A data dictionary is constructed for the program that contains its local and global variables. The source browser allows the user to traverse, view, and edit a source code tree. Additional facilities for understanding and maintaining the source code and its auxiliary documentation are provided by the browser.
Assessment of minimum inertia requirement for system frequency stability

The reduced amount of rotational kinetic energy in power systems has significant detrimental impacts on system frequency behaviour. To ensure system security, this issue must be addressed in a systematic way. Given this, we consider three different metrics, namely i) minimum power penetration from synchronous generators, ii) minimum rated power of synchronous generators, and iii) minimum synchronous kinetic energy, as frequency control constraints in the market dispatch model, and assess frequency behaviour of the system for these metrics. The results show that each metric has a different impact on market dispatch, and, accordingly, on the system frequency behaviour. It is shown that with high penetration of converter-based generation, we need to consider a minimum kinetic energy requirement as a frequency control security constraint in the market dispatch model to guarantee the frequency stability of power systems.
Charge transport and electrode injection in polymer light-emitting diodes

We present a microscopic theory of charge transport in conjugated polymers based on polaron drift along polymer segment and on polaron hopping between segments. We show that this model is able to reproduce the current-voltage characteristics of 'good' hole-only devices based on PPV in the whole range of fields. We also present a microscopic theory of electrode injection into conjugated polymers. We show that this model is able to reproduce the current voltage characteristics of contact limited devices based on PPV.
Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm

A wavelet electrocardiogram (ECG) data codec based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm (A. Said and W.A. Pearlman, IEEE Trans. Ccts. Syst. II, vol. 6, p. 243-50, 1996) has achieved notable success in still image coding. The authors modified the algorithm for the one-dimensional case and applied it to compression of ECG data. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. The coder also attains exact bit rate control and generates a bit stream progressive in quality or rate.
Detecting Ferrite Nanobeads for Sentinel Lymph Node Mapping with a Highly Sensitive Hall Differential Magnetic Field Sensor

We fabricated a novel type of Hall differential magnetic field sensor for anti-cancer sentinel lymph node (SLN) mapping using ferrofluid as a marker. A pair of Hall devices are mounted on both end surfaces of a ferrite core (10 mm ϕ ×32 mm) of an electromagnetic coil which generates an AC exciting magnetic field at 2.5 kHz. The signals are retrieved by a digital phase sensitive detection circuit. Mapping a ferrofluid (ResovistR) sample of l00μg in Fe atomic amount (comparable to that accumulated in human SLNs) was attained when the sample was placed within 6 mm distance from the sensor head. The detectable distance is limited primarily due to the magnetic induction effect of the metal XYZ stage which held the sample.
A Multi-dimensional Distributed Array Abstraction for PGAS

DASH is a realization of the PGAS (partitioned global address space) model in the form of a C++ template library without the need for a custom PGAS (pre-)compiler. We present the DASH NArray concept, a multidimensional array abstraction designed as an underlying container for stencil-and dense numerical applications. After introducing fundamental programming concepts used in DASH, we explain how these have been extended by multidimensional capabilities in the NArray abstraction. Focusing on matrix-matrix multiplication in a case study, we then discuss an implementation of the SUMMA algorithm for dense matrix multiplication to demonstrate how the DASH NArray facilitates portable efficiency and simplifies the design of efficient algorithms due to its explicit support for locality-based operations. Finally, we evaluate the performance of the SUMMA algorithm based on the NArray abstraction against established implementations of DGEMM and PDGEMM. In combination with mechanisms for automatic optimization of logical process topology and domain decomposition, our implementation yields highly competitive results without manual tuning, significantly outperforming Intel MKL and PLASMA in node-level use cases as well as ScaLAPACK in highly distributed scenarios.
Safety and efficacy of intrathecal ziconotide in the management of severe chronic pain

Ziconotide is a conopeptide intrathecal (IT) analgesic which is approved by the US Food and Drug Administration (FDA) for the management of severe chronic pain. It is a synthetic equivalent of a naturally occurring conopeptide found in the venom of the fish-eating marine cone snail and provides analgesia via binding to N-type voltage-sensitive calcium channels in the spinal cord. As ziconotide is a peptide, it is expected to be completely degraded by endopeptidases and exopeptidases (Phase I hydrolytic enzymes) widely located throughout the body, and not by other Phase I biotransformation processes (including the cytochrome P450 system) or by Phase II conjugation reactions. Thus, IT administration, low plasma ziconotide concentrations, and metabolism by ubiquitous peptidases make metabolic interactions of other drugs with ziconotide unlikely. Side effects of ziconotide which tend to occur more commonly at higher doses may include: nausea, vomiting, confusion, postural hypotension, abnormal gait, urinary retention, nystagmus/amblyopia, drowsiness/somnolence (reduced level of consciousness), dizziness or lightheadedness, weakness, visual problems (eg, double vision), elevation of serum creatine kinase, or vestibular side effects. Initially, when ziconotide was first administered to human subjects, titration schedules were overly aggressive and led to an abundance of adverse effects. Subsequently, clinicians have gained appreciation for ziconotide’s relatively narrow therapeutic window. With appropriate usage multiple studies have shown ziconotide to be a safe and effective intrathecal analgesic alone or in combination with other intrathecal analgesics.
Semi-supervised discriminant analysis method via weighted low-rank representation and adaptive neighbor selection

Dimensionality reduction is a very important part in the field of face recognition. In view of the problem of the traditional dimensionality reduction methods are inconvenient to select neighbor parameter K and the “dense” characteristic of the low-rank representation coefficient matrix. We presented a method that semi-supervised discriminant analysis via weighted low-rank representation and adaptive neighbor selection (ANSWLR-SDA). First, we uses all the within-class samples to construct the within-class graph which can describe the within-class compactness, and then adaptively chooses the between-class samples to construct the between-class graph which can describe the between-class respectively. On this basis, we use a regularization term by weighted low-rank represented to maintain the global similarity structure of samples. Finally, we carry out the experiments on FERET and yale_faceb databases, and compare this method with the traditional dimensionality reduction methods and the results demonstrate that ANSWLR-SDA method is effectiveness and robust to different types of noise than other state-of-art face recognition method.
Universal First-Order Logic is Superfluous for NL, P, NP and coNP

In this work we continue the syntactic study of completeness that began with the works of Immerman and Medina. In particular, we take a conjecture raised by Medina in his dissertation that says if a conjunction of a second-order and a first-order sentences defines an NP-complete problems via fops, then it must be the case that the second-order conjoint alone also defines a NP-complete problem. Although this claim looks very plausible and intuitive, currently we cannot provide a definite answer for it. However, we can solve in the affirmative a weaker claim that says that all ``consistent'' universal first-order sentences can be safely eliminated without the fear of losing completeness. Our methods are quite general and can be applied to complexity classes other than NP (in this paper: to NLSPACE, PTIME, and coNP), provided the class has a complete problem satisfying a certain combinatorial property.
EFFECT OF INSULIN AND GROWTH HORMONE ON PLASMA LEPTIN IN THE PERIPARTURIENT DAIRY COW

After parturition, dairy cows suffer from an intense energy deficit due to the onset of copious milk secretion and an inadequate increase in voluntary food intake. We previously showed that this energy deficit contributes to a decline in plasma leptin. This decline mirrors that of plasma insulin, but is reciprocal to the profile of plasma growth hormone (GH), suggesting that both hormones may regulate plasma leptin in periparturient dairy cows. To study the role of insulin, hyperinsulinemic-euglycemic clamps were performed on six dairy cows in late pregnancy (LP, 31 days prepartum) and early lactation (EL, 7 days postpartum). Infusion of insulin (1μg/kg body weight per hour) caused a progressive rise in the plasma concentration of leptin that reached maximum levels at 24 h during both physiological states. At steady states, the absolute increase in plasma leptin was greater in LP than in EL cows (2.4 ng/ml vs 0.4 ng/ml). Insulin infusion increased leptin mRNA in adipose tissue during LP but not during EL. During lactation, mammary epithelial cells expressed leptin mRNA, but insulin did not increase milk leptin output. In contrast, a three day period of GH administration had no effect on plasma leptin during LP or EL. Therefore, insulin increases plasma leptin in LP by stimulating adipose tissue synthesis, but has only marginal effects in EL when cows are in negative energy balance. Other factors, such as increased response of adipose tissue to β-adrenergic signals, probably contribute to the reduction of plasma leptin in early lactating dairy cows.
Utility-Aware Social Event-Participant Planning

Online event-based social network (EBSN) platforms are becoming popular these days. An important task of managing EBSNs is to arrange proper social events to interested users. Existing approaches usually assume that each user only attends one event or ignore location information. The overall utility of such strategy is limited in real world: 1) each user may attend multiple events; 2) attending multiple events will incur spatio-temporal conflicts and travel expenses. Thus, a more intelligent EBSN platform that provides personalized event planning for each participant is desired. In this paper, we first formally define the problem of Utility-aware Social Event-participant Planning (USEP), which is proven to be NP-hard. To solve the USEP problem, we first devise a greedy-based heuristic algorithm, which performs fast under certain circumstances but has no approximation guarantee. We then present a two-step approximation framework, which not only guarantees a 1/2-approximation ratio but also includes a series of optimization techniques to improve its space/time efficiency. Finally, we verify the efficiency and effectiveness of the proposed methods through extensive experiments on real and synthetic datasets.
Preferring Properly: Increasing Coverage while Maintaining Quality in Anytime Temporal Planning

Temporal Fast Downward (TFD) is a successful temporal planning system that is capable of dealing with numerical values. Rather than decoupling action selection from scheduling, it searches directly in the space of time-stamped states, an approach that has shown to produce plans of high quality at the price of coverage. To increase coverage, TFD incorporates deferred evaluation and preferred operators, two search techniques that usually decrease the number of heuristic calculations by a large amount. However, the current definition of preferred operators offers only limited guidance in problems where heuristic estimates are weak or where subgoals require the execution of mutex operators. In this paper, we present novel methods for refinement of this definition and show how to combine the diverse strengths of different sets of preferred operators using a restarting procedure incorporated into a multi-queue best-first search. These techniques improve TFD's coverage drastically and preserve the average solution quality, leading to a system that solves more problems than each of the competitors of the temporal satisficing track of IPC 2011 and clearly outperforms all of them in terms of IPC score.
A Primer on Alzheimer ' s Disease and the Brain-National Institute on Aging

The healthy human brain contains tens of billions of neurons, specialized cells that process and transmit information via electrical and chemical signals. Most neurons have three basic components: a cell body, multiple dendrites, and an axon. The cell body contains the nucleus, which houses the genetic blueprint that directs and regulates the cell’s activities. Dendrites are branch-like structures that radiate from the cell body and collect information from other neurons. The axon is a cable-like structure that extends from the other end of the cell body and transmits messages to other neurons.
An Industrial Augmented Reality Solution For Discrepancy Check

Construction companies employ CAD software during the planning phase, but what is finally built often does not match the original plan. The procedure of validating the model is called "discrepancy check". The system proposed here allows the user to easily obtain an augmentation in order to find differences between the planned 3D model and the built items. The main difference to previous body of work in this field is the emphasis on usability and acceptance of the solution. While standard image-based solutions use markers or rely on a "perfect" 3D model to find the pose of the camera, our software uses anchor-plates. Anchor-Plates are rectangular structures installed on walls and ceiling in the majority of industrial edifices. We are using them as landmarks because they are the most reliable components often used as reference coordinates by constructors. Furthermore, for real industrial applications, they are the most suitable solutions in terms of general applicability. Unfortunately, they have not been designed with computer vision applications in mind. On the contrary, they are often made or painted in such way that they are not easily popping out. They are therefore difficult targets to segment and to track. This paper proposes a solution to extract and match them to their 3D counterparts. We created a software that uses the detected structures for pose estimation and image augmentation. The software has been successfully employed to find discrepancies in several rooms of two industrial plants.
Large scale networks security strategy

The article deals with optimum two-phase planning of secure routs in large scale computer networks. Uncertainty of future needs is covered by extensive statistical modeling, which resulted in identification of statistical dependences and phenomena allowing for optimization of creation. To describe secure paths in random matrices the author uses programmable percolation apparatus. Tolerance of the created secure routes to failures in certain secure paths is demonstrated here.
Human Leukocyte Antigen Class I and II Alleles and Cervical Adenocarcinoma

Background: Associations between human leukocyte antigens (HLA) alleles and cervical cancer are largely representative of squamous cell carcinoma (SCC), the major histologic subtype. We evaluated the association between HLA class I (A, B, and C) and class II (DRB1 and DQB1) loci and risk of cervical adenocarcinoma (ADC), a less common but aggressive histologic subtype. Methods: We pooled data from the Eastern and Western US Cervical Cancer studies, and evaluated the association between individual alleles and allele combinations and ADC (n = 630 ADC; n = 775 controls). Risk estimates were calculated for 11 a priori (based on known associations with cervical cancer regardless of histologic type) and 38 non a priori common alleles, as odds ratios (OR) and 95% confidence intervals (CI), adjusted for age and study. In exploratory analysis, we compared the risk associations between subgroups with HPV16 or HPV18 DNA in ADC tumor tissues in the Western US study cases and controls. Results: Three of the a priori alleles were significantly associated with decreased risk of ADC [DRB1*13:01 (OR = 0.61; 95% CI: 0.41–0.93), DRB1*13:02 (OR = 0.49; 95% CI: 0.31–0.77), and DQB1*06:03 (OR = 0.64; 95% CI: 0.42–0.95)]; one was associated with increased risk [B*07:02 (OR = 1.39; 95% CI: 1.07–1.79)]. Among alleles not previously reported, DQB1*06:04 (OR = 0.46; 95% CI: 0.27–0.78) was associated with decreased risk of ADC and remained significant after correction for multiple comparisons, and C*07:02 (OR = 1.41; 95% CI: 1.09–1.81) was associated with increased risk. We did not observe a difference by histologic subtype. ADC was most strongly associated with increased risk with B*07:02/C*07:02 alleles (OR = 1.33; 95% CI: 1.01–1.76) and decreased risk with DRB1*13:02/DQB1*06:04 (OR = 0.41; 95% CI: 0.21–0.80). Conclusion: Results suggest that HLA allele associations with cervical ADC are similar to those for cervical SCC. An intriguing finding was the difference in risk associated with several alleles restricted to HPV16 or HPV18-related tumors, consistent with the hypothesis that HLA recognition is HPV type-specific.
Neuromantic – from Semi-Manual to Semi-Automatic Reconstruction of Neuron Morphology

The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.
Input-Output-to-State Stability

This work explores Lyapunov characterizations of the input-output-to-state stability (IOSS) property for nonlinear systems. The notion of IOSS is a natural generalization of the standard zero-detectability property used in the linear case. The main contribution of this work is to establish a complete equivalence between the IOSS property and the existence of a certain type of smooth Lyapunov function. As corollaries, one shows the existence of "norm-estimators," and obtains characterizations of nonlinear detectability in terms of relative stability and of finite-energy estimates.
IDE (rs6583817) polymorphism and pulse pressure are independently and interactively associated with level and change in executive function in older adults.

OBJECTIVE We report a gene × environment (health) study focusing on concurrent performance and longitudinal change in a latent-variable executive function (EF) phenotype. Specifically, we tested the independent and interactive effects of a recently identified insulin degrading enzyme genetic polymorphism (IDE rs6583817) and pulse pressure (PP; one prominent aging-related vascular health indicator) across up to 9 years of EF data in a sample of older adults from the Victoria Longitudinal Study. Both factors vary across a continuum of risk-elevating to risk-reducing and have been recently linked to normal and impaired cognitive aging. METHOD We assembled a genotyped and typically aging group of older adults (n = 599, M age = 66 years at baseline), following them for up to 3 longitudinal waves (M interval = 4.4 years). We used confirmatory factor analyses, latent growth modeling, and path analyses to pursue 3 main research goals. RESULTS First, the EF single factor model was confirmed comprising 4 executive function tasks and it demonstrated measurement invariance across the waves. Second, older adults with the major IDE G allele exhibited better EF outcomes than homozygotes for the minor A allele at the centering age of 75 years. Adults with higher PP performed more poorly on EF tasks at age 75 years and exhibited greater EF longitudinal decline. Third, gene × health interaction analyses showed that worsening vascular health (higher PP) differentially affected EF performance in older adults with the IDE G allele. CONCLUSION Genetic interaction analyses can reveal differential and magnifying effects on cognitive phenotypes in aging. In the present case, pulse pressure is confirmed as a risk factor for concurrent and changing cognitive health in aging, but the effects operate differently across the risk and protective allelic distribution of this IDE gene.
Programming by demonstration: removing sub-optimal actions in a partially known configuration space

Programming by demonstration is a promising approach to automatic robot programming, however, methods are required to remove suboptimal actions that can be demonstrated by end users. In this paper we use the partial knowledge of configuration space (C-space) derived in the previous work by Chen et al. (2000) to remove suboptimal actions from a demonstration. Our idea is to use demonstrated paths to predict what regions in C-space are obstacle free. Suboptimal actions in a demonstration are then avoided by planning alternative actions that pass through the obstacle free regions. Experimental results show the validity of the approach. A demonstrated path containing significant sub-optimality was converted by the approach into a short, efficient path suitable for execution by the robot.
A Rigorous, Operational Formalization of Recursive Modeling

We present a formalization of the Recursive Modeling Method, which we have previously, somewhat informally, proposed as a method that autonomous artificial agents can use for intelligent coordination and communication with other agents. Our formalism is closely related to models proposed in the area of game theory, but contains new elements that lead to a difregent solution concept. The advantage of our solution method is that always yields the optimal solution, which is the rational action of the agent in a multi-agent environment, given the agent’s state of knowledge and its preferences, and that it works in realistic cases when agents have only a finite amount of information about the agents they interact with.