Miracle-dz/UniFAR-FTUs huggingface dataset:
NuSTAR HARD X-RAY SURVEY OF THE GALACTIC CENTER REGION. I. HARD X-RAY MORPHOLOGY AND SPECTROSCOPY OF THE DIFFUSE EMISSION

We present the first sub-arcminute images of the Galactic Center above 10 keV, obtained with NuSTAR. NuSTAR resolves the hard X-ray source IGR J17456–2901 into non-thermal X-ray filaments, molecular clouds, point sources, and a previously unknown central component of hard X-ray emission (CHXE). NuSTAR detects four non-thermal X-ray filaments, extending the detection of their power-law spectra with Γ ∼ 1.3–2.3 up to ∼50 keV. A morphological and spectral study of the filaments suggests that their origin may be heterogeneous, where previous studies suggested a common origin in young pulsar wind nebulae (PWNe). NuSTAR detects non-thermal X-ray continuum emission spatially correlated with the 6.4 keV Fe Kα fluorescence line emission associated with two Sgr A molecular clouds: MC1 and the Bridge. Broadband X-ray spectral analysis with a Monte-Carlo based X-ray reflection model self-consistently determined their intrinsic column density (∼1023 cm−2), primary X-ray spectra (power-laws with Γ ∼ 2) and set a lower limit of the X-ray luminosity of Sgr A* flare illuminating the Sgr A clouds to LX ≳ 1038 erg s−1. Above ∼20 keV, hard X-ray emission in the central 10 pc region around Sgr A* consists of the candidate PWN G359.95–0.04 and the CHXE, possibly resulting from an unresolved population of massive CVs with white dwarf masses MWD ∼ 0.9 M⊙. Spectral energy distribution analysis suggests that G359.95–0.04 is likely the hard X-ray counterpart of the ultra-high gamma-ray source HESS J1745–290, strongly favoring a leptonic origin of the GC TeV emission.
On estimations for compiling software to FPGA-based systems

This paper presents recent advances in a compiler infrastructure to map algorithms described in a Java subset to FPGA-based platforms. We explain how delays and resources are estimated to guide the compiler through scheduling and temporal partitioning. The compiler supports complex analytical models to estimate resources and delays for each functional unit. The paper presents experimental results for a number of benchmarks. Those results also arise a question when performing temporal partitioning: shall we try to group as many computational structures in the same configuration or shall we have several configurations?
Enhancing topical ranking with preferences from click-through data

To overcome the training data insufficiency problem for dedicated model in topical ranking, this paper proposes to utilize click-through data to improve learning. The efficacy of click-through data is explored under the framework of preference learning. The empirical experiment on a commercial search engine shows that, the model trained with the dedicated labeled data combined with skip-next preferences could beat the baseline model and the generic model in NDCG5 for 4.9% and 2.4% respectively.
Modulation by Amino Acids: Toward Superior Control in the Synthesis of Zirconium Metal-Organic Frameworks.

The synthesis of zirconium metal-organic frameworks (Zr MOFs) modulated by various amino acids, including l-proline, glycine, and l-phenylalanine, is shown to be a straightforward approach toward functional-group incorporation and particle-size control. High yields in Zr-MOF synthesis are achieved by employing 5 equivalents of the modulator at 120 °C. At lower temperatures, the method provides a series of Zr MOFs with increased particle size, including many suitable for single-crystal X-ray diffraction studies. Furthermore, amino acid modulators can be incorporated at defect sites in Zr MOFs with an amino acid/ligand ratio of up to 1:1, depending on the ligand structure and reaction conditions. The MOFs obtained through amino acid modulation exhibit an improved CO2 -capture capacity relative to nonfunctionalized materials.
Peptide Deformylase Inhibitors as Potent Antimycobacterial Agents

ABSTRACT Peptide deformylase (PDF) catalyzes the hydrolytic removal of the N-terminal formyl group from nascent proteins. This is an essential step in bacterial protein synthesis, making PDF an attractive target for antibacterial drug development. Essentiality of the def gene, encoding PDF from Mycobacterium tuberculosis, was demonstrated through genetic knockout experiments with Mycobacterium bovis BCG. PDF from M. tuberculosis strain H37Rv was cloned, expressed, and purified as an N-terminal histidine-tagged recombinant protein in Escherichia coli. A novel class of PDF inhibitors (PDF-I), the N-alkyl urea hydroxamic acids, were synthesized and evaluated for their activities against the M. tuberculosis PDF enzyme as well as their antimycobacterial effects. Several compounds from the new class had 50% inhibitory concentration (IC50) values of <100 nM. Some of the PDF-I displayed antibacterial activity against M. tuberculosis, including MDR strains with MIC90 values of <1 μM. Pharmacokinetic studies of potential leads showed that the compounds were orally bioavailable. Spontaneous resistance towards these inhibitors arose at a frequency of ≤5 × 10−7 in M. bovis BCG. DNA sequence analysis of several spontaneous PDF-I-resistant mutants revealed that half of the mutants had acquired point mutations in their formyl methyltransferase gene (fmt), which formylated Met-tRNA. The results from this study validate M. tuberculosis PDF as a drug target and suggest that this class of compounds have the potential to be developed as novel antimycobacterial agents.
λ group: Using Optics to Take Group Data Delivery in the Datacenter to the Next Degree

The increasing number of datacenter applications with heavy one-to-many communications has raised the need for an efficient group data delivery solution. This paper presents an unconventional clean-slate architecture called λ that uses optical networking technologies to enable ultra-fast, energy-efficient, low cost, and highly reliable group data delivery in the datacenter. By replicating data purely optically, λ enables reliable one-to-many communication independent of modulated data rate, while simultaneously being energy-efficient. λ makes use of software defined network switches to facilitate direct interactions between applications and the network, eliminating the need for conventional multicast routing and group management protocols without sacrificing link-stress or latency performance. From an end-to-end perspective, λ provides predictable latency and near-zero packet loss between application end points, allowing even simple end-to-end flow control and packet loss recovery mechanisms to work well. We implement a λ prototype to measure its physical layer characteristics and end-to-end performance benefits to applications. Extensive simulations using synthetic traffic show λ provides an order of magnitude performance improvement relative to a number of existing alternative group data delivery approaches.
Intrusion Detection Systems: A Survey and Taxonomy

This paper presents a taxonomy of intrusion detection systems that is then used to survey and classify a number of research prototypes. The taxonomy consists of a classification first of the detection principle, and second of certain operational aspects of the intrusion detection system as such. The systems are also grouped according to the increasing difficulty of the problem they attempt to address. These classifications are used predictively, pointing towards a number of areas of future research in the field of intrusion detection.
A statistically robust variance‐components approach for quantitative trait linkage analysis

Previously we showed (Wang, Guerra & Cohen 1998) that a statistically robust version of the Haseman & Elston (1972) sib‐pair method greatly increased power to detect linkage in the presence of outliers. In this paper we report on M‐estimation to accommodate outliers in the variance‐components approach to linkage analysis developed by Amos (1994). Simulations show that in the presence of outliers the robust variance‐components approach provides substantially greater power, more precise estimation of heritabilities, and better false–positive rates than the original Gaussian based approach. In the absence of outliers the performance of the robust variance‐components approach is similar to that of the Gaussian based approach. For illustration we apply the method to two well characterized lipoprotein systems.
A multi-engine approach to answer-set programming*

Abstract Answer-set programming (ASP) is a truly declarative programming paradigm proposed in the area of non-monotonic reasoning and logic programming, which has been recently employed in many applications. The development of efficient ASP systems is, thus, crucial. Having in mind the task of improving the solving methods for ASP, there are two usual ways to reach this goal: (i) extending state-of-the-art techniques and ASP solvers or (ii) designing a new ASP solver from scratch. An alternative to these trends is to build on top of state-of-the-art solvers, and to apply machine learning techniques for choosing automatically the “best” available solver on a per-instance basis. In this paper, we pursue this latter direction. We first define a set of cheap-to-compute syntactic features that characterize several aspects of ASP programs. Then, we apply classification methods that, given the features of the instances in a training set and the solvers' performance on these instances, inductively learn algorithm selection strategies to be applied to a test set. We report the results of a number of experiments considering solvers and different training and test sets of instances taken from the ones submitted to the “System Track” of the Third ASP Competition. Our analysis shows that by applying machine learning techniques to ASP solving, it is possible to obtain very robust performance: our approach can solve more instances compared with any solver that entered the Third ASP Competition.
Optimizing Irregular Data Accesses for Cluster and Multicore Architectures

Applications with irregular accesses to shared state are one of the most challenging computational patterns in parallel computing. Accesses can involve both read or write operations, with writes having the additional complexity of requiring some form of synchronization. Irregular accesses perform poorly in local cached-based memory systems and across networks in global distributed memory settings, because they have poor spatial and temporal locality. Irregular accesses arises in transaction processing, in various system level programs, in computing histograms, performing sparse matrix operations, updating meshes in particle-mesh methods, and building adaptive unstructured meshes. Writing codes with asynchronous parallel updates on clusters and multicore processors presents different sets of challenges. On clusters, the goal is to minimize the number of messages and the volume of messages between nodes. While on multicore machines, the goal is to minimize off-chip accesses since there is significant performance difference between on chip and off chip memory access. In this dissertation, we explore various analyses, optimizations, and tools for shared accesses on both multicore and distributed memory cluster architectures. On cluster architectures, we consider both irregular reads and writes, demonstrate how Partitioned Global Address Space languages support programming irregular problems, and develop optimizations to minimize communication traffic, both in volume and number of distinct events. On multicore processors, we consider the lower level code generation and tuning problem, independent of any particular source language. We explore performance tradeoffs between various shared update implementations, such as locking, replication of state to avoid collisions, and hybrid versions. We develop an adaptive implementation that adjusts the shared update strategy based on densities that yields significant speedups. In addition, we develop a performance debugging tool to find scalability problems in large scientific applications early in the development cycle. Throughout the thesis we perform experiments demonstrating the value of our optimizations and tools in both architectural settings, use a set of benchmarks and applications that include histogram making, sparse matrix computations, and two scientific simulations involving particle-mesh methods. Our results show substantial speeds of up to 4.8X for multicore platforms and 120X for clusters. The results are a comprehensive set of techniques for improving the performance of irregular applications using advanced languages, compilers, analyses, optimizations and tools.
CMP Memory Modeling : How Much Does Accuracy Matter ?

As Chip-multiprocessor (CMP) become the ubiquitous architecture, especially for commercial servers targeting throughput-oriented applications, processor manufacturers are likely to integrate increasing number of cores on-die. Designing and developing these CMP architectures involves studying a number of options for on-die interconnect, cache and memory system while optimizing for both power and performance. Simulation-based study is widely adopted for the design space exploration for these systems. Although most existing CMP simulators have detailed cache and interconnect models, they use simplistic memory models that use either a fixed latency to the memory sub-system or a simple queuing model which adds bandwidth constraints to the fixed latency approach. In this paper, we demonstrate the necessity for a cycle-accurate memory model for CMP architecture. We study three types of memory models: (1) Fixed latency model, (2) simple queuing model and (3) detailed cycle-accurate model. We show that the performance difference among them is increased as the number of cores is increased on-chip. We also find that optimization studies done using simplistic models can lead to erroneous conclusions. Our studies show that the performance difference between simplistic models and accurate memory controller can be as high as 65% for memory optimization studies.
Biofilm formation with mixed cultures of Pseudomonas aeruginosa/Escherichia coli on silicone using artificial urine to mimic urinary catheters

In this study, single and dual species biofilms of Pseudomonas aeruginosa and Escherichia coli, two common bacteria associated with urinary tract infections, were formed in silicon coupons immersed in artificial urine medium. In single species experiments, E. coli appeared to form biofilms more easily than P. aeruginosa. In mixed biofilms, both species apparently benefited from the presence of the other, as the average Log total cells cm−2 of mixed biofilms (7.29 cells cm−2) was higher than obtained for single cultures (6.99 cells cm−2). However, the use of selective media seemed to indicate that P. aeruginosa was the only microorganism to benefit in mixed biofilms (Log 7 CFU of P. aeruginosa cm−2, compared to Log 6 CFU cm−2 obtained in pure cultures). Peptide nucleic acid-fluorescence in situ hybridization combined with confocal laser scanning microscopy confirmed that E. coli was indeed being outnumbered by P. aeruginosa at 48 h. Whereas E. coli is the main causative agent of catheter-associated urinary tract infections, the results from this study indicate that the reason for the higher prevalence of this microorganism is not related to an enhanced ability to form biofilm and outcompete other species that may also be present, but rather to a better ability to form single-species biofilms possibly due to a more frequent access to the catheter surface.
Extending recommendation systems with software maps

In practice, recommendation systems have evolved as helpful tools to facilitate and optimize software engineering processes. Serving both developers and managers, specific recommendation systems address their individual problems. Yet, in a number of cases complementing them with other techniques can enhance their use and extend their scope. In this paper, we first discuss different perspectives on software-engineering processes and examples of recommendation systems that support representatives of these perspectives. We then identify how select software-map techniques can extend recommendation systems to facilitate decision making by addressing the perspectives' information and communication needs.
Towards efficient packet switching metro WDM networks

In this article, we first give a brief overview of the current state-of-the-art of optical WDM networking. In this overview we point out that the ubiquitous SONET/SDHWDM metro rings are likely to become a serious bottleneck between high-speed local area networks/broadband access technologies and WDM backbone networks. Next, we discuss innovative metro WDM network architectures and formulate the requirements of future packet switching metro WDM networks. After reviewing previous work on single-hop WDM networks, several resulting guidelines for the design of Medium Access Control (MAC) protocols are provided. Following these guidelines leads us to a future-proof Arrayed-Waveguide Grating (AWG) based metro WDM network and a novel reservation based MAC protocol, which supports Qualityof-Service (QoS). Each node at the periphery of this passive single-hop WDM network is equipped with a single tunable transceiver for data and a broadband light source, which is spectrally sliced in order to broadcast reservation requests. Each node has global knowledge and schedules variable-size data packets in a distributed fashion by executing the same greedy first-come-firstserved and first-fit arbitration algorithm. The network is reliable, scalable, and allows for optical multicasting. All wavelengths are used for data transmission. The protocol supports both packet and circuit switching. The network efficiency is significantly increased by using multiple Free Spectral Ranges (FSRs) of the underlying AWG, spatially reusing wavelengths, and transmitting data and control simultaneously by means of spreading techniques.
Using Holistic Queue Scheduling to Optimize the Real-Time Performanceof AFDX

AFDX, Avionics Full Duplex Switched Ethernet Network, is an aircraft data network using the FIFO schedul- ing strategy to transmit data. In this circumstance, the delay of the critical data is large, while congestion is uncertain. To cope with this problem, this paper presents a Holistic Queue Scheduling policy to optimize the real-time performance of AFDX, and estimate the latency bounds based on Network Calculus. Simulation results show that this policy not only en- sures real-time critical data, but also ensures the fairness of scheduling non-critical data. And this policy can reduce the impact of malicious data in some extent.
An Evaluation of the Stress Non-Uniformity due to the Heterogeneity of AC in the Indirect Tensile Test

Simple Performance Tests (SPT) including Indirect Tensile (IDT) Test and Dynamic Modulus Test have been widely used in the evaluation of the performance of asphalt concrete. The so-called SPT tests typically apply uniform stresses on the boundary and therefore obtain the stress-strain relation with convenience. Nevertheless, asphalt concrete is a heterogeneous material composed of asphalt binder, aggregates and air voids. The three constituents have drastically different stiffness. Even under a uniform boundary stress, the internal stress and strain distributions are not uniform. This paper presents a comparison between the stress distribution based on heterogeneous material properties and that based on homogeneous material properties using X-ray Computed Tomography (XCT) and Finite Element (FE) simulation. The comparison indicates that material heterogeneity is an important factor that must be considered in the characterization of asphalt concrete.
Double-field inflation.

We present an inflationary universe model which utilizes two coupled real scalar fields. The inflation field $\phi$ experiences a first order phase transition and its potential dominates the energy density of the Universe during the inflationary epoch. This field $\phi$ is initially trapped in its metastable minimum and must tunnel through a potential barrier to reach the true vacuum. The second auxiliary field $\psi$ couples to the inflaton field and serves as a catalyst to provide an abrupt end to the inflationary epoch: i.e., the $\psi$ field produces a time-dependent nucleation rate for bubbles of true $\phi$ vacuum. In this model, we find that bubbles of true vacuum can indeed percolate and we argue that thermalization of the interiors can more easily take place. The required degree of flatness (i.e., the fine tuning) in the potential of the $\psi$ field is comparable to that of other models which invoke slowly rolling fields. Pseudo Nambu-Goldstone bosons may naturally provide the flat potential for the rolling field.
Compositional Verification of a Network of CSP Processes: Using FDR2 to Verify Refinement in the Event of Interface Difference

The paper [5] presented an implementation relation formalising what it means for one process to “implement” another in the CSP (Communicating Sequential Processes, [15]) framework in the event that the two processes have different interfaces. An improved version of the relation appears in [6] and allows for compositional verification of a network of CSP processes. The model checker FDR2([15]) may be used to check CSP refinement in the event that specification and implementation processes have the same interface. In this paper, we show how to transform the problem of checking the conditions from [6], where the specification and implementation processes have different interfaces, into one where the specification and implementation processes have the same interface. This allows us to take advantage of the existing tool FDR2 and allows automatic, compositional verification using the relation developed.
Temporal Validation of the UKPDS Outcomes Model Using 10-Year Posttrial Monitoring Data

OBJECTIVE To evaluate the accuracy of the UK Prospective Diabetes Study Outcomes Model (UKPDS-OM) in predicting clinical outcomes during the UKPDS posttrial monitoring (PTM) period. RESEARCH DESIGN AND METHODS At trial end in 1997, the 4,031 surviving UKPDS patients, of the 5,102 originally enrolled in the study, returned to their usual care providers, with no attempts made to maintain them in their randomized therapy groups. PTM risk factor data were collected for 5 years and clinical outcome data for 10 years. The UKPDS-OM was used firstly to forecast likely progression of HbA1c, systolic blood pressure, total-to-HDL cholesterol ratio, and smoking status and secondly to estimate the likely first occurrence of seven major diabetes-related complications or death from any cause. Model predictions were compared against observed PTM data for risk factor time paths and survival probabilities for major diabetes complications. RESULTS UKPDS-OM–forecasted risk factor time paths were similar to those observed for HbA1c (up to 3 years) and total-to-HDL cholesterol ratio but underestimated for systolic blood pressure and smoking status. Predicted 10-year event probabilities were similar to those observed for blindness, ischemic heart disease, myocardial infarction, and renal failure but were higher for heart failure and death from any cause and lower for stroke and amputation. CONCLUSIONS The UKPDS-OM has good predictive accuracy for two of four risk factor time paths and for 10-year clinical outcome probabilities with the exception of stroke, amputation, heart failure, and death from any cause. An updated version of the model incorporating PTM data is being developed.