Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Validation of Network-Intensive Workloads on a Full-System Simulator

Performance accuracy is a critical but often neglected aspect of architectural performance simulators. One approach to evaluating performance accuracy is to attempt to reproduce observed performance results from a real machine. In this paper, we attempt to model the performance of a Compaq Alpha XP1000 workstation using the M5 full-system simulator. There are two novel aspects to this work. First, we simulate complex TCP/IP networking workloads and use network bandwidth as our primary performance metric. Unlike conventional CPU-intensive applications, these workloads spend most of their time in the operating system kernel and include significant interactions with platform hardware such as the interrupt controller and network interface device. Second, we attempt to achieve performance accuracy without extremely precise modeling of the reference hardware. Instead, we use simple generic component models and tune them to achieve appropriate bandwidths and latencies. Overall, we were able to achieve reasonable accuracy even with our relatively imprecise model, matching the bandwidth of the real system within 15% in most cases. We also used profiling to break CPU time down into categories, and found that the simulation results correlated well with the real machine.
Comparison of discrete-time approximations for continuous-time nonlinear systems

This work addresses the problem of approximating the sampled input-output (i/o) behavior of continuous-time nonlinear systems using discrete-time Volterra models. For an exactly band-limited nonlinear system for which a Volterra representation exists, the discrete-time Volterra model exactly corresponds to the sampled continuous-time Volterra kernels. Physical systems, as they are causal, are never exactly band-limited. Thus, a modeling error is introduced. By relaxing the causality condition and allowing a small processing delay, it is shown through simulation that more accurate discrete-time Volterra models, compared to sampled continuous-time Volterra models, can be generated.
Ieee Transactions on Visualization and Computer Graphics Topological Fisheye Views for Visualizing Large Graphs

— Graph drawing is a basic visualization tool. For graphs of up to hundreds of nodes and edges, there are many effective techniques available. At greater scale, data density and occlusion problems often negate its effectiveness. Conventional pan-and-zoom, and multiscale and geometric fisheye views are not fully satisfactory solutions to this problem. As an alternative, we describe a topological zooming method. It is based on the precomputation of a hierarchy of coarsened graphs, which are combined on-the-fly into renderings with the level of detail dependent on the distance from one or more foci. We also discuss a related distortion method that allows our technique to achieve constant information density displays.
Retrieving near‐global aerosol loading over land and ocean from AVHRR

The spaceborne advanced very high resolution radiometer (AVHRR) sensor data record is approaching 40 years, providing a crucial asset for studying long‐term trends of aerosol properties regionally and globally. However, due to limitations of its channels' information content, aerosol optical depth (AOD) data from AVHRR over land are still largely lacking. In this paper, we describe a new physics‐based algorithm to retrieve aerosol loading over both land and ocean from AVHRR for the first time. The over‐land algorithm is an extension of our Sea‐viewing Wide Field‐of‐view Sensor and Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue algorithm, while a simplified version of our Satellite Ocean Aerosol Retrieval algorithm is used over ocean. We compare retrieved AVHRR AOD with that from MODIS on a daily and seasonal basis and find, in general, good agreement between the two. For the satellites with equatorial crossing times within 2 h of solar noon, the spatial coverage of the AVHRR aerosol product is comparable to that of MODIS, except over very bright arid regions (such as the Sahara), where the underlying surface reflectance at 630 nm reaches the critical surface reflectance. Based upon comparisons of the AVHRR AOD against Aerosol Robotic Network data, preliminary results indicate that the expected error confidence interval envelope is around ±(0.03 + 15%) over ocean and ±(0.05 + 25%) over land for this first version of the AVHRR aerosol products. Consequently, these new AVHRR aerosol products can contribute important building blocks for constructing a consistent long‐term data record for climate studies.
A biosensor for detection of DNA sequences based on a 50MHz QCM electronic oscillator circuit

This work deals with the development of a high sensibility DNA biosensor based on a 50MHz Quartz Crystal Microbalance (QCM) Oscillator Electronic Circuit. The designed QCM oscillator sensor is able to detect the presence of complementary DNAs in a solution that match the sequence on a given strand in function of the changes in the output frequency of the oscillator. The design is adapted so that the Barkhausen condition is satisfied even when the quartz is immerged in liquid media. Also a comparative study of the developed 50MHz biosensor in front of a QCM oscillator with smaller frequency is carried out, with object of checking if the sensibility of the oscillator increases, allowing to detect smaller concentrations of the complementary DNA.
Rf-pilot phase noise compensation for long-haul coherent optical OFDM systems

Long-haul optical transmission systems employing coherent optical orthogonal frequency division multiplexing (CO-OFDM) are sensitive to laser phase noise. This causes a common phase rotation and inter-carrier interference. An effective method to compensate for the phase noise is to insert an RF-pilot tone in the middle of the OFDM signal. This RF-pilot is used to reverse the phase distortion at the receiver. This paper presents a performance analysis of the RF-pilot phase noise compensation scheme in a simulated 64 Gb/s CO-OFDM system. The effects of various parameters including laser linewidth, Mach-Zehnder modulator drive power, pilot-to-signal ratio, and fiber launch power are investigated. A comparison with the pilot-aided common phase error compensation method is provided to show the differences in the BER performance with respect to the required overhead.
Colorful PDR: Colorizing PDR with shopping context in walking

The technology for detection of indoor location information has been attracting much attention in the recent past, since such information can be utilized for navigation and marketing research. The commonly used indoor location detection methods are Wi-Fi positioning, Bluetooth Low Energy (BLE) beacons and Pedestrian Dead-reckoning (PDR). PDR can provide location information relative to the original position by analyzing acceleration and angular velocity using sensors in smartphones without needing any positioning equipment in the environment. Meanwhile, to know the user's context in the indoor environment, PDR, RFID and surveillance cameras are investigated. Although PDR results can provide the atomic physical behavior such as the direction of walking (forward/backward or right/left), it is difficult to detect the user's shopping behaviors to determine if he/she is approaching, searching or just browsing in the shopping venues. Our research objective is to estimate the user's walking context appropriate for shopping venues with the same sensor information as used for conventional PDR. We propose a new method for walking context recognition that uses machine learning with a feature vector of accelerometers and gyroscopes. Based on the experiments conducted, we found that this model was able to recognize the intuitive walking context. We also established the utility of our proposal in the experiment at the actual shopping venue and verified that it can be applied to improve PDR positioning precision by 8%.
A Sequence Similarity Search Algorithm Based on a Probabilistic Interpretation of an Alignment Scoring System

We present a probabilistic interpretation of local sequence alignment methods where the alignment scoring system (ASS) plays the role of a stochastic process defining a probability distribution over all sequence pairs. An explicit algorithms is given to compute the probability of two sequences given and ASS. Based on this definition, a modified version of the Smith-Waterman local similarity search algorithm has been devised, which assesses sequence relationships by log likelihood ratios. When tested on classical examples such as globins or G-protein-coupled receptors, the new method proved to be up to an order of magnitude more sensitive than the native Smith-Waterman algorithm.
The formation and control of emerging disinfection by-products of health concern

When drinking water treatment plants disinfect water, a wide range of disinfection by-products (DBPs) of health and regulatory concern are formed. Recent studies have identified emerging DBPs (e.g. iodinated trihalomethanes (THMs) and acids, haloacetonitriles, halonitromethanes (HNMs), haloacetaldehydes, nitrosamines) that may be more toxic than some of the regulated ones (e.g. chlorine- and bromine-containing THMs and haloacetic acids). Some of these emerging DBPs are associated with impaired drinking water supplies (e.g. impacted by treated wastewater, algae, iodide). In some cases, alternative primary or secondary disinfectants to chlorine (e.g. chloramines, chlorine dioxide, ozone, ultraviolet) that minimize the formation of some of the regulated DBPs may increase the formation of some of the emerging by-products. However, optimization of the various treatment processes and disinfection scenarios can allow plants to control to varying degrees the formation of regulated and emerging DBPs. For example, pre-disinfection with chlorine, chlorine dioxide or ozone can destroy precursors for N-nitrosodimethylamine, which is a chloramine by-product, whereas pre-oxidation with chlorine or ozone can oxidize iodide to iodate and minimize iodinated DBP formation during post-chloramination. Although pre-ozonation may increase the formation of trihaloacetaldehydes or selected HNMs during post-chlorination or chloramination, biofiltration may reduce the formation potential of these by-products.
Long-range cooperative binding of kinesin to a microtubule in the presence of ATP

Interaction of kinesin-coated latex beads with a single microtubule (MT) was directly observed by fluorescence microscopy. In the presence of ATP, binding of a kinesin bead to the MT facilitated the subsequent binding of other kinesin beads to an adjacent region on the MT that extended for micrometers in length. This cooperative binding was not observed in the presence of ADP or 5′-adenylylimidodiphosphate (AMP-PNP), where binding along the MT was random. Cooperative binding also was induced by an engineered, heterodimeric kinesin, WT/E236A, that could hydrolyze ATP, yet remained fixed on the MT in the presence of ATP. Relative to the stationary WT/E236A kinesin on a MT, wild-type kinesin bound preferentially in close proximity, but was biased to the plus-end direction. These results suggest that kinesin binding and ATP hydrolysis may cause a long-range state transition in the MT, increasing its affinity for kinesin toward its plus end. Thus, our study highlights the active involvement of MTs in kinesin motility.
Maximum likelihood based noise covariance matrix estimation for multi-microphone speech enhancement

Multi-microphone speech enhancement systems can often be decomposed into a concatenation of a beamformer, which provides spatial filtering of the noisy signal, and a singlechannel (SC) noise reduction filter, which reduces the noise remaining in the beamformer output. Here, we propose a maximum likelihood based method for estimating the intermicrophone covariance matrix of the noise impinging on the microphone array. The method allows prediction of this co-variance matrix for non-stationary noise sources even in signal regions where the target speech signal is present. Although the noise covariance matrix may have several purposes, we use it in this paper for estimating the power spectral density (psd) of the noise entering the SC filter, as this is important for optimal operation of the SC filter. In simulation experiments with a binaural hearing aid setup in a realistic acoustical scenario, the proposed method performs better than existing methods for estimating this noise psd.
Efficient computation of delay-sensitive routes from one source to all destinations

In this paper we describe an efficient algorithm for the constrained shortest path problem which is defined as follows. Given a directed graph with two weights on each link e, a cost l/sub e/, and a delay t/sub e/, find the cheapest path from a source to all destinations such that the delay of each path is no more than a given threshold. The constrained shortest path problem arises in quality-of-service-sensitive routing in data networks and is of particular importance in real time services. The problem formulation and the algorithmic framework presented are quite general; they apply to IP, ATM, and optical networks. Unlike previous algorithms, our algorithm generates paths from one source to all destinations. Our algorithm is strongly polynomial, and is asymptotically faster than earlier algorithms. We corroborate our analysis by a preliminary simulation study.
Subcellular Changes in Bridging Integrator 1 Protein Expression in the Cerebral Cortex During the Progression of Alzheimer Disease Pathology

Genome-wide association studies have established BIN1 (Bridging Integrator 1) as the most significant late-onset Alzheimer disease (AD) susceptibility locus after APOE. We analyzed BIN1 protein expression using automated immunohistochemistry on the hippocampal CA1 region in 19 patients with either no, mild, or moderate-to-marked AD pathology, who had been assessed by Clinical Dementia Rating and CERAD scores. We also examined the amygdala, prefrontal, temporal, and occipital regions in a subset of these patients. In non-demented controls without AD pathology, BIN1 protein was expressed in white matter, glia, particularly oligodendrocytes, and in the neuropil in which the BIN1 signal decorated axons. With increasing severity of AD, BIN1 in the CA1 region showed: 1) sustained expression in glial cells, 2) decreased areas of neuropil expression, and 3) increased cytoplasmic neuronal expression that did not correlate with neurofibrillary tangle load. In patients with AD, both the prefrontal cortex and CA1 showed a decrease in BIN1-immunoreactive (BIN1-ir) neuropil areas and increases in numbers of BIN1-ir neurons. The numbers of CA1 BIN1-ir pyramidal neurons correlated with hippocampal CERAD neuritic plaque scores; BIN1 neuropil signal was absent in neuritic plaques. Our data provide novel insight into the relationship between BIN1 protein expression and the progression of AD-associated pathology and its diagnostic hallmarks.
Executable Modeling with UML. A Vision or a Nightmare?

Extreme Programming is the most prominent new, light-weight (or agile) methods, defined to contrast the current heavy-weight and partially overloaded object-oriented methods. It focuses on the core issues of software technology. One of its principles is not to rely on diagrams to document a system. In this paper, we examine what properties a modeling language like UML must have in order to support the Extreme Programming approach effectively. In particular, we discuss how such a diagrammatic programming language must look like to replace a textual programming language and what benefits and problems such an approach may bring.
The sea cucumber genome provides insights into morphological evolution and visceral regeneration

Apart from sharing common ancestry with chordates, sea cucumbers exhibit a unique morphology and exceptional regenerative capacity. Here we present the complete genome sequence of an economically important sea cucumber, A. japonicus, generated using Illumina and PacBio platforms, to achieve an assembly of approximately 805 Mb (contig N50 of 190 Kb and scaffold N50 of 486 Kb), with 30,350 protein-coding genes and high continuity. We used this resource to explore key genetic mechanisms behind the unique biological characters of sea cucumbers. Phylogenetic and comparative genomic analyses revealed the presence of marker genes associated with notochord and gill slits, suggesting that these chordate features were present in ancestral echinoderms. The unique shape and weak mineralization of the sea cucumber adult body were also preliminarily explained by the contraction of biomineralization genes. Genome, transcriptome, and proteome analyses of organ regrowth after induced evisceration provided insight into the molecular underpinnings of visceral regeneration, including a specific tandem-duplicated prostatic secretory protein of 94 amino acids (PSP94)-like gene family and a significantly expanded fibrinogen-related protein (FREP) gene family. This high-quality genome resource will provide a useful framework for future research into biological processes and evolution in deuterostomes, including remarkable regenerative abilities that could have medical applications. Moreover, the multiomics data will be of prime value for commercial sea cucumber breeding programs.
Higher-order test generation

Symbolic reasoning about large programs is bound to be imprecise. How to deal with this imprecision is a fundamental problem in program analysis. Imprecision forces approximation. Traditional static program verification builds "may" over-approximations of the program behaviors to check universal "for-all-paths" properties, while automatic test generation requires "must" under-approximations to check existential "for-some-path" properties. In this paper, we introduce a new approach to test generation where tests are derived from validity proofs of first-order logic formulas, rather than satisfying assignments of quantifier-free first-order logic formulas as usual. Two key ingredients of this higher-order test generation are to (1) represent complex/unknown program functions/instructions causing imprecision in symbolic execution by uninterpreted functions, and (2) record uninterpreted function samples capturing input-output pairs observed at execution time for those functions. We show that higher-order test generation generalizes and is more precise than simplifying complex symbolic expressions using their concrete runtime values. We present several program examples where our approach can exercise program paths and find bugs missed by previous techniques. We discuss the implementability and applications of this approach. We also explain in what sense dynamic test generation is more powerful than static test generation.
Novel signaling pathways that control ovarian follicular development, ovulation, and luteinization.

The interactions of peptide and steroid hormone signaling cascades in the ovary are critical for follicular growth, ovulation, and luteinization. Although the pituitary gonadotropins follicle-stimulating hormone (FSH) and luteinizing hormone (LH) play key regulatory roles, their actions are also dependent on other peptide signaling pathways, including those stimulated by insulin-like growth factor-1 (IGF-1), transforming growth factor-beta (TGF-beta) family members (e.g., inhibin, activin, growth differentiation factor-9, bone morphogenic proteins), fibroblast growth factor, and Wnts (via Frizzled receptors). Each of these factors is expressed and acts in a cell-specific manner at defined stages of follicular growth. IGF-1, estrogen, and FSH comprise one major regulatory system. The Wnt/Frizzled pathways define other aspects relating to ovarian embryogenesis and possibly ovulation and luteinization. Likewise, the steroid receptors as well as orphan nuclear receptors and their ligands impact ovarian cell function. The importance of these multiple signaling cascades has been documented by targeted deletion of specific genes. For example, mice null for the LH-induced genes progesterone receptor (PR) and cyclo-oxygenase-2 (COX-2) fail to ovulate. Whereas PR appears to regulate the induction of novel proteases, COX-2 appears to regulate cumulus expansion. This review summarizes some new aspects of peptide and steroid hormone signaling in the rodent ovary.
Estimating Saturated Hydraulic Conductivity using Green-Ampt Equation

The potential of groundwater recharge and the transport of agricultural contaminants from recharge structures in Badakhera watershed were evaluated using the one-dimensional Green-Ampt infiltration equation and soil leachability model. The saturated hydraulic conductivity k s , a parameter of the Green-Ampt equation, is normally calculated using empirical equations. The in-situ measurement of k s for the recharge structures in the Badakhera watershed is lacking. For this purpose, a field experiment was conducted to evaluate the performance of an in-situ measurement of the k s from infiltration rate and three other k s estimation methods namely; soil texture (ST), percent clay content (PCC), and relative effective porosity (REP) based method. Most effective and the reliable k s estimation method was selected based upon four evaluation criteria, as; coefficient of determination (R 2 ), index of agreement (D), root mean square error (RMSE) and relative bias (RB). The optimised k s values from field-measured infiltration data using Marquardt algorithm were adjudged as the most promising method for simulating the infiltration rate from the recharge structures. The responses of the PCC and the ST based k s estimate methods were comparable to each other, while the response of the REP based method registered higher deviation. The optimised k s value from field infiltration data can successfully be used for estimating potential recharge and transport of agricultural contaminants from the recharge structures in the Badakhera watershed.
Cancer-related fatigue, depressive symptoms, and functional status: a mediation model.

BACKGROUND Patients with cancer grapple with a confusing array of disease- and treatment-related symptoms while trying to maintain functioning in usual roles and daily activities. Research is needed to sort out and identify symptom clusters as a basis for a rational approach to symptom management. OBJECTIVE The aim of this study was to test, through secondary analysis, a mediation hypothesis about the direct and indirect relationships between fatigue and depressive symptoms through a pathway involving functional status. METHODS Data from the experimental and control groups of a randomized clinical intervention trial for fatigue management, collected after the second chemotherapy treatment or during the last week of radiotherapy, were analyzed. The mediation pathway from fatigue to depressive symptoms through functional status was tested separately for groups receiving either an energy conservation intervention or a control intervention, equating for time and attention. RESULTS For the control group, the results indicate support for partial mediation. The previously significant relationship between fatigue and depressive symptoms was reduced after functional status was controlled, accounting for 43% of the total mediated effect. The mediation hypothesis was not supported in the energy conservation group, indicating that the intervention may have changed the role of functional status in mediating the effect of fatigue on depressive symptoms. DISCUSSION In the control group, when routine activities became more difficult because of fatigue, individuals had more depressive symptoms. The results suggest that functional status is an important factor to consider in symptom management for fatigue. An appropriate intervention for fatigue would have two targets: the fatigue and strategies to reduce the likelihood of impaired functioning that could result in elevated depressive symptoms.