Miracle-dz/UniFAR-FTUs huggingface dataset:
Heart rate variability measurements and the prediction of ventricular arrhythmias.

Heart rate variability (HRV) is the temporal variation between sequences of consecutive heartbeats. On a standard electrocardiogram (ECG), the maximum upwards deflection of a normal QRS complex is at the peak of the R wave (Figure 1), and the duration between two adjacent R wave peaks is termed the R-R interval. The ECG signal requires editing before HRV analysis can be performed, a process requiring the removal of all non-sinus-node-originating beats. The resulting period between adjacent QRS complexes resulting from sinus node depolarizations is termed the N-N (normal-normal) interval.1 HRV is the measurement of the variability of the N-N intervals. Figure 1. The normal electrocardiogram with component waves labelled. Although counter-intuitive, it is possible that HRV confers a survival advantage. Any system exhibiting intrinsic variability is primed to respond rapidly and appropriately to demands placed upon it. HRV is a measure of the balance between sympathetic mediators of heart rate (HR) (i.e. the effect of epinephrine and norepinephrine, released from sympathetic nerve fibres, acting on the sino-atrial and atrio-ventricular nodes), which increase the rate of cardiac contraction and facilitate conduction at the atrio-ventricular node, and parasympathetic mediators of HR (i.e. the influence of acetylcholine, released by the parasympathetic nerve fibres, acting on the sino-atrial and atrio-ventricular nodes), leading to a decrease in the HR and a slowing of conduction at the atrio-ventricular node. Sympathetic mediators appear to exert their influence over longer time periods and are reflected in the low frequency power (LFP) of the HRV spectrum (between 0.04 Hz and 0.15 Hz.2,,3 Vagal mediators exert their influence more quickly on the heart, and principally affect the high frequency power (HFP) of the HRV spectrum (between 0.15 Hz and 0.4 Hz). 4 Thus, at any point in time, the LFP:HFP ratio is a proxy for the sympatho-vagal balance. Physiological and pathological process … Address correspondence to Dr M.J. Reed, Emergency Department, Royal Infirmary of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SA. e-mail: mattreed1{at}hotmail.com
Speeding-up test pattern generation by means of heuristic learning

Boolean Satisfiability (SAT) algorithms have seen dramatic improvements over recent years, allowing larger problem instances to be solved in application domains such as automatic test pattern generation (ATPG) that can also be viewed as solving a SAT problem. The key to a SAT-solver can be scalable is that it is able to take into account the information of high-level structure of formulas. This paper further improves to SAT-based ATPG with heuristic learning. It establishes correlations among signals by analyzing specific structure of circuit instances, finding more necessary signal line assignments, detecting conflicts earlier, and avoiding unnecessary work during test generation. Among others things, it combines strengths of binary decision graphs (BDD) and SAT techniques to improve the efficiency of test generation. Reconvergent fanout is a fundamental cause of the difficulty in testing circuits, because they introduce dependencies in the values that can be assigned to nodes. This paper exploits reconvergent fanout analysis of circuit to gather information about local signal correlation through BDD learning, and then used the learned information in the conjunctive normal form (CNF) clauses to restrict and focus the overall search space of test pattern generation. The experimental results demonstrate the effectiveness of these learning techniques.
Degenerate Peptide Recognition by Candida albicans Adhesins Als5p and Als1p

ABSTRACT Candida albicans and Saccharomyces cerevisiae expressing the adhesins Als5p or Als1p adhere to immobilized peptides and proteins that possess appropriate sequences of amino acids in addition to a sterically accessible peptide backbone. In an attempt to further define the nature of these targets, we surveyed the ability of yeast cells to adhere to 90-μm-diameter polyethylene glycol beads coated with a 7-mer peptide from a library of 197 unique peptide-beads. C. albicans bound to ca. 10% of beads from the library, whereas S. cerevisiae expressing Als5p or Als1p bound to ca. 0.1 to 1% of randomly selected peptide-beads. S. cerevisiae expressing Als1p had a distinctly different adherence phenotype than did cells expressing Als5p. The former adhered in groups or clumps of cells, whereas the latter adhered initially as single cells, an event which was followed by the build up of cell-cell aggregates. Beads with adherent cells were removed, and the peptide attached to the bead was determined by amino acid sequencing. All adhesive beads carried a three-amino-acid sequence motif (τφ+) that possessed a vast combinatorial potential. Adherence was sequence specific and was inhibited when soluble peptide identical to the immobilized peptide was added. The Als5p adhesin recognized some peptides that went unrecognized by Als1p. The sequence motif of adhesive peptides identified by this method is common in proteins and offers so many possible sequence combinations that target recognition by the Als proteins is clearly degenerate. A degenerate recognition system provides the fungi with the potential of adhering to a multitude of proteins and peptides, an advantage for any microorganism attempting to establish a commensal or pathogenic relationship with a host.
A unified ensemble of concatenated convolutional codes

We introduce a unified ensemble for turbo-like codes (TCs) that contains the four main classes of TCs: parallel concatenated codes, serially concatenated codes, hybrid concatenated codes, and braided convolutional codes. We show that for each of the original classes of TCs, it is possible to find an equivalent ensemble by proper selection of the design parameters in the unified ensemble. We also derive the density evolution (DE) equations for this ensemble over the binary erasure channel. The thresholds obtained from the DE indicate that the TC ensembles from the unified ensemble have similar asymptotic behavior to the original TC ensembles.
Efficient graph management based on bitmap indices

The increasing amount of graph like data from social networks, science and the web has grown an interest in analyzing the relationships between different entities. New specialized solutions in the form of graph databases, which are generic and able to adapt to any schema as an alternative to RDBMS, have appeared to manage attributed multigraphs efficiently. In this paper, we describe the internals of DEX graph database, which is based on a representation of the graph and its attributes as maps and bitmap structures that can be loaded and unloaded efficiently from memory. We also present the internal operations used in DEX to manipulate these structures. We show that by using these structures, DEX scales to graphs with billions of vertices and edges with very limited memory requirements. Finally, we compare our graph-oriented approach to other approaches showing that our system is better suited for out-of-core typical graph-like operations.
PreCisIon: PREdiction of CIS-regulatory elements improved by gene’s positION

Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.
A Comparative Study of MAC Layer Protocols for Mobile Ad-Hoc Networks

In today’s world of mobility, Mobile Ad-Hoc Network (MANET) is of utmost importance because it provides connectivity to users while on move. The main issue in Mobile Ad-Hoc Network (MANET) is of accessing the wireless channel, where too many users try to get access simultaneously. Traditionally, IEEE 802.11 Standards provide two protocols at MAC layer i.e. Distributed Coordination Function (DCF) and Point Coordination Function (PCF). In this paper a comparative study of PCF and DCF with Distributed Queuing Mobile Ad-Hoc Network (DQMAN) and Distributed Point Coordination Function (DPCF) protocols is presented. After a comprehensive computer based simulation, DPCF out performs the traditional protocols by a huge margin.
A Quantitative Analysis of Olive Oil Market in the North-West Italy

The problem of the competitiveness of the agricultural products has always animated the analyses of the agricultural economists. At the present, them competitive context is influenced from two phenomena of bottom: the progressive increase of the markets segmentation process, fed from the productive differentiation of the enterprises, and the crescent communicative weight of the products in the shelves of the GDO, exalted from the policies of merchandising feeding. Such phenomena feed complex competitive interdependences between the various trade categories and between the various brands inside of the category. The extravirgin olive oil, in virtue of the maturity level of its market, shows several peculiarities: it is introduced as a system burdened from secular problems of structural type that need of able participations to give back to force and competitiveness, in this moment that the consumption, is assumed, could increase. In so far as, a provisional support on which is the levers in order to render own market the best regarding the competitors, finds a remarkable interest, especially with the parallel use of a recent source of information (scanner date).
Aging effects on regional brain structural changes in schizophrenia.

BACKGROUND Although mostly conceptualized as a neurodevelopmental disorder, there is an increasing interest in progressive changes of cognitive deficits and brain structure and function in schizophrenia across the life span. METHODS In this study, we investigated age-related changes in regional gray matter using voxel-based morphometry in a sample of 99 patients (age range 18-65 years) with Diagnostic and Statistical Manual of Mental Disorders-IV schizophrenia and 113 healthy controls (age range 19-59 years) using a cross-sectional design. RESULTS We found steeper age-related decline in gray matter in patients in a cluster comprising the left superior temporal cortex and adjacent inferior parietal lobule. We then divided the schizophrenia sample in 3 subgroups based on a 3-factor model of psychopathology ratings. Age-related changes were markedly different in each of the 3 subgroups (compared with healthy controls). While patients with predominantly paranoid symptoms showed stronger age-related progression in the left superior temporal cortex and right inferior frontal gyrus, those of the disorganized subgroup had stronger gray matter loss in the left lateral cerebellum, while the predominantly negative subgroup showed minor effects in the left superior temporal gyrus. CONCLUSIONS Our findings show that differences in brain structural changes associated with aging diverge between schizophrenia patients and healthy subjects and that different subgroups within a patient sample might be at higher risk of age-related regional gray matter loss.
Vehicle Speed Estimation from Single Still Images Based on Motion Blur Analysis

Motion blur arises when the object motion is fast relative to the shutter time of the camera. In this work, we p ropose a method to estimate the speed of moving vehicles from sing le still images based on motion blur analy sis for the p urpose of traffi c law enforcement. T he blur parameters are estimated from a sing le motion blurred image and then used to calculate the speed of the moving vehicle in a scene. F irst, the motion d irection of the vehicle is estimated using image grad ient information and the orientation of the motion blur is simp lifi ed to a one-d imensional case by image rotation and rectifi cation. T he length of the motion blur is then estimated by ed ge d etection and blurred ed ge analy sis. F inally , the speed of the moving vehicle is calculated accord ing to the imaging geometry , camera parameters, and the estimated blur parameters. E xperimental results are p resented for both synthetic and real images.
Practically Realizing Random Access Scan Practically Realizing Random Access Scan Practically Realizing Random Access Scan Practically Realizing Random Access Scan

Except where reference is made to the work of others, the work described in this thesis is my own or was done in collaboration with my advisory committee. This thesis does not include proprietary or classified information. Permission is granted to Auburn University to make copies of this thesis at its discretion, upon the request of individuals or institutions and at their expense. The author reserves all publication rights. The number of clock cycles in a serial scan (SS) test is often prohibitive as the number of flip-flops (FF) increases. Besides, scan-in and scan-out sequences result in unwanted circuit activity. This increases the test power enormously. The scan process activates all flip-flops in the scan chain, although very few flip-flops need to be set for a targeted fault and only a subset of all the flip-flops needs to be observed. A technique known as Random Access Scan (RAS) can solve these problems. Here every flip-flop is addressed uniquely. In RAS, only the required number of flip-flops is set or reset for a given test and this reduces the set up time of flip-flops significantly. Due to the flexibility of setting the required flip-flops randomly, the test power drastically reduces to a bare minimum. Thus two complementary problems are addressed using the single technique of RAS. These advantages come at a cost of increased area overhead and that is often unacceptable. In this work, we have addressed the problem in such a way that the implementation is practical and the additional area overhead is justified. We have developed a new RAS cell, which minimizes the number of signals otherwise routed to it compared to earlier designs. This improvement saves silicon area. v Another contribution of this work is a new RAS cell without a scan-in signal and an added toggle feature. This flip-flop toggles its state when addressed and hence any desired state can be achieved by just addressing it if the current state is known. The scan out structure is also designed in such a way that when a flip-flop is addressed or toggled, the existing value of the flip-flop is read out. This is done using a hierarchical bus structure that drives the data from the addressed flip-flops to a primary output. Considering the limited drive capability of the flip-flops, the hierarchical bus restricts the load that the addressed flip-flop must drive. The flip-flops are addressed using a grid …
Process-based modelling of biogenic monoterpene emissions combining production and release from storage

Monoterpenes, primarily emitted by terrestrial vegetation, can influence atmospheric ozone chemistry, and can form precursors for secondary organic aerosol. The short-term emissions of monoterpenes have been well stud- ied and understood, but their long-term variability, which is particularly important for atmospheric chemistry, has not. This understanding is crucial for the understanding of future changes. In this study, two algorithms of terrestrial biogenic monoterpene emissions, the first one based on the short- term volatilization of monoterpenes, as commonly used for temperature-dependent emissions, and the second one based on long-term production of monoterpenes (linked to pho- tosynthesis) combined with emissions from storage, were compared and evaluated with measurements from a Pon- derosa pine plantation (Blodgett Forest, California). The measurements were used to parameterize the long-term stor- age of monoterpenes, which takes place in specific stor- age organs and which determines the temporal distribution of the emissions over the year. The difference in assump- tions between the first (emission-based) method and the sec- ond (production-based) method, which causes a difference in upscaling from instantaneous to daily emissions, requires roughly a doubling of emission capacities to bridge the gap to production capacities. The sensitivities to changes in temper- ature and light were tested for the new methods, the tempera- ture sensitivity was slightly higher than that of the short-term temperature dependent algorithm.
Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap

This paper presents a class of NK landscapes with nearest-neighbor interactions and tunable overlap. The considered class of NK landscapes is solvable in polynomial time using dynamic programming; this allows us to generate a large number of random problem instances with known optima. Several genetic and evolutionary algorithms are then applied to the generated problem instances. The results are analyzed and related to scalability theory for genetic algorithms and estimation of distribution algorithms.
Timing diagrams and correlations in gamma-ray bursts signal jets from accretion into black holes

The temporal properties of a sample of 498 bright gamma-ray bursts (GRBs) with durations between 0.05 s and 674 s were analysed. The large range in duration (T90) is accompanied by a similarly large range in the median values of the pulse timing properties including rise time, fall time, FWHM and separation between the pulses. Four timing diagrams relating these pulse properties to T90 are presented and show the power law relationships between the median values of the 4 pulse timing properties and T90, but also that the power laws depend in a consistent manner on the number of pulses per GRB. The timing diagrams are caused by the correlated properties of the pulses in the burst and can be explained by a combination of factors including the Doppler boost factor Gamma, a viewing effect caused by a jet and different progenitors. GRBs with similar values of T90 have a wide range in the number of pulses. GRBs with the large number of short and spectrally hard pulses may occur either from a homogeneous jet with a higher average value of Gamma or close to the axis of an inhomogeneous jet with higher values of Gamma near the rotation axis. The less luminous GRBs with fewer pulses may originate further from the axis of the inhomogeneous jet. The pulses in GRBs have six distinctive statistical properties including correlations between time intervals, correlations between pulse amplitudes, an anticorrelation between pulse amplitudes and time intervals, and a link to intermittency in GRS 1915+105. The timing diagrams and correlated pulses suggest that GRBs are powered by accretion processes signalling jets from the formation of black holes.
A Software Project Perspective on the Fitness and Evolvability of Personal Learning Environments

This position paper deals with the exploration of fitness and evolvability of personal learning environments (PLEs). Taking a software engineer’s perspective, PLE evolution is a software project. Software quality characteristics like Functionality and Usability map to the PLE’s fitness, while Maintainability is important for evolvability. Only adaptation can secure future fitness. But for this, the software project has to be a good PLE for its developers in its on right.
Timed Hierarchical Object-Oriented Petri Net

Petri nets (Murata, 1989) (Peterson, 1991) have been widely used to model various discrete event systems (Moody & Antsaklis, 1998). Characterized as concurrent, asynchronous, distributed, parallel, nondeterministic, and/or stochastic (Murata, 1989), Petri nets have gained more and more applications. However, when they are used to analyze and model systems of different domains, the shortages of this kind of formal method still exist. Basic Petri nets lack temporal knowledge description, so they have failed to describe the temporal constraints in time critical or time dependent systems. The introduction of temporal knowledge into Petri nets has increased not only the modeling power but also the model complexity (Wang et al. 2000). The improved models of Petri nets (Wang, 1998) include Timed Petri Net (Ramchandi, 1974), Stochastic Timed Petri Net (Florin etc al., 1991) and Time Petri Net (TPNs) (Merlin & Farber, 1976). In TPNs (Merlin & Farber, 1976), each bar has two times specified. The first time denotes the minimal time that must elapse from the time that all the input conditions of a bar are enabled until this bar can fire. The other time denotes the maximum time that the input conditions can be enabled and the bar does not fire. After this time, the bar must fire. In general, these two times give some measures of minimal and maximal execution times of the bars. The reachability (coverability) analysis is one of the main analysis methods for Petri nets (Murata, 1989), in which the coverability tree is always used. It permits the automatic translation of behavioral specification models into a state transition graph made up of a set of states, a set of actions, and a succession relation associating states through actions (Bucci & Vivario, 1995). That is to say, it involves essentially the enumeration of all reachable markings or their coverable markings. This representation makes such properties as deadlock and reachability (Zhou, 1995) explicit, and allows the automatic verification of ordering relationships among task execution times (Tsai et al., 1995). Although the reachability analysis method can be used for all nets, it is only limited to “small” nets due to the complexity of the state-space explosion. The same thing also happens in the analysis of TPN models. Sloan et al. (Sloan & Buy, 1996) developed several reduction rules for TPN analysis that work at an individual transition level. These reduction rules help to reduce the complexity of TPN analysis to some extent. However, it is not a trivial work to automatically search the preconditions of applying these reduction rules for a