Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing Neuromorphic Solutions in Action: Implementing a Bio-Inspired Solution to a Benchmark Classification Task on Three Parallel-Computing Platforms

Neuromorphic computing employs models of neuronal circuits to solve computing problems. Neuromorphic hardware systems are now becoming more widely available and “neuromorphic algorithms” are being developed. As they are maturing toward deployment in general research environments, it becomes important to assess and compare them in the context of the applications they are meant to solve. This should encompass not just task performance, but also ease of implementation, speed of processing, scalability, and power efficiency. Here, we report our practical experience of implementing a bio-inspired, spiking network for multivariate classification on three different platforms: the hybrid digital/analog Spikey system, the digital spike-based SpiNNaker system, and GeNN, a meta-compiler for parallel GPU hardware. We assess performance using a standard hand-written digit classification task. We found that whilst a different implementation approach was required for each platform, classification performances remained in line. This suggests that all three implementations were able to exercise the model's ability to solve the task rather than exposing inherent platform limits, although differences emerged when capacity was approached. With respect to execution speed and power consumption, we found that for each platform a large fraction of the computing time was spent outside of the neuromorphic device, on the host machine. Time was spent in a range of combinations of preparing the model, encoding suitable input spiking data, shifting data, and decoding spike-encoded results. This is also where a large proportion of the total power was consumed, most markedly for the SpiNNaker and Spikey systems. We conclude that the simulation efficiency advantage of the assessed specialized hardware systems is easily lost in excessive host-device communication, or non-neuronal parts of the computation. These results emphasize the need to optimize the host-device communication architecture for scalability, maximum throughput, and minimum latency. Moreover, our results indicate that special attention should be paid to minimize host-device communication when designing and implementing networks for efficient neuromorphic computing.
DynamicCloudSim: simulating heterogeneity in computational clouds

Simulation has become a commonly employed first step in evaluating novel approaches towards resource allocation and task scheduling on distributed architectures. However, existing simulators fall short in their modeling of the instability common to shared computational infrastructure, such as public clouds. In this work, we present DynamicCloudSim which extends the popular simulation toolkit CloudSim with several factors of instability, including inhomogeneity and dynamic changes of performance at runtime as well as failures during task execution. As a use case and validation of the introduced functionality, we simulate the impact of instability on scientific workflow scheduling by assessing and comparing the performance of four schedulers in the course of several experiments. Results indicate that our model seems to adequately capture the most important aspects of cloud performance instability, though a validation on real hardware is still pending. The source code of DynamicCloudSim and the examined schedulers is available at https://code.google. com/p/dynamiccloudsim/.
Quarter-micron lithography using a deep-UV stepper with modified illumination

We have investigated the use of annular illumination on a KrF excimer laser stepper ((lambda) equals 248 nm) working near the resolution limit of the lens. The numerical aperture of the lens was 0.48 and the illuminator-lens combination produced a partial coherence of 0.44. With a central obscuration equal to 75% of the diameter of the illuminator aperture in place and using a surface-imaging resist process, we have increased the depth of focus for 0.25 micrometers dense lines and spaces from 0.9 micrometers at one point in the imaging field to 1.5 micrometers . Performance for dense contacts was also improved. These improvements demonstrate the feasibility of 0.25 micrometers technology with deep-UV lithography.
Improving Automated Patent Claim Parsing: Dataset, System, and Experiments

Off-the-shelf natural language processing software performs poorly when parsing patent claims owing to their use of irregular language relative to the corpora built from news articles and the web typically utilized to train this software. Stopping short of the extensive and expensive process of accumulating a large enough dataset to completely retrain parsers for patent claims, a method of adapting existing natural language processing software towards patent claims via forced part of speech tag correction is proposed. An Amazon Mechanical Turk collection campaign organized to generate a public corpus to train such an improved claim parsing system is discussed, identifying lessons learned during the campaign that can be of use in future NLP dataset collection campaigns with AMT. Experiments utilizing this corpus and other patent claim sets measure the parsing performance improvement garnered via the claim parsing system. Finally, the utility of the improved claim parsing system within other patent processing applications is demonstrated via experiments showing improved automated patent subject classification when the new claim parsing system is utilized to generate the features.
Route Bazaar: Automatic Interdomain Contract Negotiation

While it is widely acknowledged that the Border Gateway Protocol (BGP) has many flaws, most of the proposed fixes focus solely on improving the stability and security of its path computation. However, because interdomain routing involves contracts between Autonomous Systems (ASes), this paper argues that contractual and routing issues should be tackled jointly. We propose Route Bazaar, a backward-compatible system for flexible Internet connectivity. Inspired by the decentralized construction of trust in cryptocurrencies, Route Bazaar uses a decentralized public ledger and cryptography to provide ASes with automatic means to form, establish, and verify end-to-end connectivity agreements.
Endogenous Oils Derived From Human Adipocytes Are Potent Adjuvants That Promote IL-1α–Dependent Inflammation

Obesity is characterized by chronic inflammation associated with neutrophil and M1 macrophage infiltration into white adipose tissue. However, the mechanisms underlying this process remain largely unknown. Based on the ability of oil-based adjuvants to induce immune responses, we hypothesized that endogenous oils derived from necrotic adipocytes may function as an immunological “danger signal. ” Here we show that endogenous oils of human origin are potent adjuvants, enhancing antibody responses to a level comparable to Freund’s incomplete adjuvant. The endogenous oils were capable of promoting interleukin (IL)-1α–dependent recruitment of neutrophils and M1-like macrophages, while simultaneously diminishing M2-like macrophages. We found that endogenous oils from subcutaneous and omental adipocytes, and from healthy and unhealthy obese individuals, promoted comparable inflammatory responses. Furthermore, we also confirmed that white adipocytes in visceral fat of metabolically unhealthy obese (MUO) individuals are significantly larger than those in metabolically healthy obese individuals. Since adipocyte size is positively correlated with adipocyte death, we propose that endogenous oils have a higher propensity to be released from hypertrophied visceral fat in MUO individuals and that this is the key factor in driving inflammation. In summary, this study shows that adipocytes contain a potent oil adjuvant which drives IL-1α–dependent proinflammatory responses in vivo.
Pole-based localization for autonomous vehicles in urban scenarios

Localization is a key capability for autonomous vehicles especially in urban scenarios. We propose the use of pole-like landmarks as primary features in these environments, as they are distinct, long-term stable and can be detected reliably with a stereo camera system. Furthermore, the resulting map representation is memory efficient, allowing for easy storage and on-line updates. The localization is performed in real-time by a stereo camera system as a main sensor, using vehicle odometry and an off-the-shelf GPS as secondary information sources. Localization is performed by a particle filter approach, coupled with an Kalman filter for robustness and sensor fusion. This leads to a lateral accuracy below 20 cm in various urban test areas. The system has been included in our autonomous test vehicle and successfully demonstrated the full loop from mapping to autonomous driving.
Surveying the landscape: an in-depth analysis of spatial database workloads

Spatial databases are increasingly important for a wide variety of real-world applications, such as land surveying, urban planning, cartography and location-based services. However, spatial database workload properties are not well-understood. For example, it is unknown to what degree one spatial application resembles another in terms of resource demand, or how the demand will change as more concurrent queries (i.e., more users) are added. We show that spatial workloads have a different CPU execution profile than well-studied decision support workloads, as represented by TPC-H. We present a framework to automatically classify spatial queries and characterize spatial workload mixes. We first analyze the resource consumption (i.e., computation and I/O) of a representative set of spatial queries, which are then classified into five distinct categories. Next, we create five homogeneous spatial workloads, each composed of queries from one of these classes. We then vary database-specific parameters (e.g., the buffer pool size) and workload specific parameters (e.g., the query mix), to characterize a workload in terms of CPU utilization and I/O activity trends. We study workloads simulating real-world spatial database applications and show how our framework can classify them and predict resource utilization trends under various settings. This can provide clues to the database administrator regarding which resources are heavily contended and can guide resource upgrades. We further validate our approach by applying it to a much larger dataset, and to a second DBMS.
First-principles simulations of iron with nitrogen: from surface adsorption to bulk diffusion

Adsorption, absorption and diffusion pathways of nitrogen are studied for ferromagnetic body-centered cubic iron via spin-polarized density functional theory in combination with the climbing image nudged elastic band method. The computed data suggest that, depending on the coverage of N atoms, N prefers to stay on particular surface sites. Once pinned down well below the surface, N prefers to move into octahedral interstices rather than tetrahedral interstices. However, the tetrahedral interstices are crucial because they act as transition states and yield the saddle point energies of the corresponding minimum energy pathways. In comparison with carbon, we found that nitrogen prefers a different pathway from the (1 0 0) surface to the subsurface due to its strong repulsive interaction with Fe ions.
A Tree System Approach for Fingerprint Pattern Recognition

The purpose of this paper is to demonstrate how a syntactic approach and, in particular, a tree system may be used to represent and classify fingerprint patterns. The fingerprint impressions are subdivided into sampling squares which are preprocessed and postprocessed for feature extraction. A set of regular tree languages is used to describe the fingerprint patterns and a set of tree automata is used to recognize the coded patterns. In order to infer the structural configuration of the encoded fingerprints, a grammatical inference system is developed. This system utilizes a simple procedure to infer the numerous substructures and relies on a reachability matrix and a man-machine interactive technique for the inference of complex structures. The 92 fingerprint impressions were used to test the proposed approach. A set of 193 tree grammars was inferred from each sampling square of the 4 × 4 sampling matrix which is capable of generating about 2 × 1034 classes for the fingerprint patterns.
Cool-Fetch: a compiler-enabled IPC estimation based framework for energy reduction

With power consumption becoming an increasingly important factor, it is necessary to reevaluate traditional, power-intensive, architectural techniques and their relative performance benefits. We believe that combined architecture-compiler efforts open up new and efficient ways to retain the performance benefits of modern architectures while addressing their power impact. In this paper, we present Cool-Fetch, an architecture compiler based approach to reduce energy consumption in the processor. While we mainly target the fetch unit, an important side-effect of our approach is that we obtain energy savings in many other parts of the processor. The explanation is that the fetch unit often runs substantially ahead of execution, bringing in instructions to different stages in the processor that may never be executed. We have found that although the degree of instruction level parallelism (ILP) of a program tends to vary over time, it can be statically estimated by the compiler. Our instructions per clock (IPC) estimation scheme uses monotonic dataflow analysis and simple heuristics, to guide a fetch-throttling mechanism. We develop the necessary architecture support and include its power overhead. Using Mediabench and SPEC2000 applications, we obtain up to 15% total energy savings in the processor with generally little performance degradation. We also provide a comparison of Cool-Fetch with previously proposed hardware-only dynamic fetch-throttling schemes.
Efficient expression of gene variants that harbour AGA codons next to the initiation codon

In an effort to improve the knowledge about the rules which direct the effect of the early ORF sequences on translation efficiency, we have analyzed the effect of pairs of the six arginine codons at the second and third positions on the expression of lacZ variants. Whereas the pairs of identical AGA or AGG codons were favorable for the gene expression, identical pairs of each of the four CGN codons were very inefficient. This result was unexpected because tandems of AGA or AGG codons located in more internal gene positions provoke deficient expression whilst internally located CGU and CGC are the most abundant and efficiently translated arginine codons. The mixed combinations of AGA and each of the CGN codons usually resulted in efficient rates of lacZ expression independently of the peptidyl-tRNA propensity to dissociate from the ribosome. Thus, the variant harboring the pair of AGA codons was expressed as efficiently as the variant carrying a pair of AAA codons in the same positions, a configuration reported as one of the most common and efficient for gene expression. We explain these results assuming that the presence of adenines in these early positions enhance gene expression. As expected, specific mRNA levels correlated with the intensity of lacZ expression for each variant. However, the induction of lacZ AGA AGA gene in pth cells accumulated peptidyl-tRNAArg4 as well as a short 5′-proximal lacZ mRNA fragment suggesting ribosome stalling due to depletion of aminoacylated-tRNAArg4.
Network loss tomography using striped unicast probes

In this paper, we explore the use of end-to-end unicast traffic as measurement probes to infer link-level loss rates. We leverage off of earlier work that produced efficient estimates for link-level loss rates based on end-to-end multicast traffic measurements. We design experiments based on the notion of transmitting stripes of packets (with no delay between transmission of successive packets within a stripe) to two or more receivers. The purpose of these stripes is to ensure that the correlation in receiver observations matches as closely as possible what would have been observed if a multicast probe followed the same path to the receivers. Measurements provide good evidence that a packet pair to distinct receivers introduces considerable correlation which can be further increased by simply considering longer stripes. Using an M/M/1/K model for a link, we theoretically confirm this benefit for stripes. We also use simulation to explore how well these stripes translate into accurate link-level loss estimates. We observe good accuracy with packet pairs, with a typical error of about 1%, which significantly decreases as stripe length is increased
Mechanical Properties of Composite Material Using Coal Ash and Clay

Coal ash is industry waste exhausted lots of amount by electric power plant. The particle sizes of coal ash, especially coal fly ash are very fine, and the chemical component are extremely resemble with Okinawa-Kucha clay. From the point of view that clay is composed of particles of micro meter size in diameter, we should try the application for fabrication of composite material using coal fly ash and clay. The comparison of the mechanical properties of composite material using coal fly ash and clay were performed during electric furnace burning and spark plasma sintering. As a result, the bending strength of composite material containing the coal ash 10% and fired at 1423K using the electric furnace after press forming at 30 MPa showed the highest value of 47 MPa. This phenomenon suggests a reinforcement role of coal ash particles to clay base material. In spark plasma sintering process, the bending strength of the composite material containing the clay 5-10% to fly ash base material fired at 1473K and pressured at 20 MPa showed the highest value of 88 MPa. This result indicates a binder effect of clay according to the liquid phase sintering of melted clay surrounding around coal fly ash particles surface.
Compiling Dynamic Mappings with Array Copies Report Emp Cri A-292

Array remappings are useful to many applications on distributed memory parallel machines. They are integrated into High Performance For-tran, a Fortran 90-based data-parallel language. This paper describes techniques for handling dynamic mappings through simple array copies: array remappings are translated into copies between statically mapped distinct versions of the array. It discusses the language restrictions required to do so. The remapping graph which captures all remapping and liveness information is presented, as well as additional data-ow optimizations that can be performed on this graph, so as to avoid useless remappings at runtime. Such useless remappings appear for arrays that are not used after a remapping. Live array copies are also kept to avoid other ow-dependent useless remappings. Finally the code generation and runtime management issues needed by our scheme are discussed. These techniques are implemented in our prototype HPF compiler.
Novel Document Detection using Online L 1-Dictionary Learning

Given their pervasive use, social media, such as Twitter, have become a leading source of breaking news. A key task in the automated identification of such news is the detection of novel documents from a voluminous stream of text documents in a robust and scalable manner. In this paper, we introduce an approach for novel document detection based on online dictionary learning. Unlike traditional dictionary learning, which uses squared loss, the proposed formulation uses `1-loss for the reconstruction error. The online `1-dictionary learning problem is efficiently solved using the alternating directions method, and we establish a O( √ T ) regret bound under suitable assumptions. Empirical results on newsstream and Twitter data, show more than an order of magnitude speedup, without much loss in quality of results.
Advancing human circadian rhythms with afternoon melatonin and morning intermittent bright light.

CONTEXT Both light and melatonin can be used to phase shift the human circadian clock, but the phase-advancing effect of the combination has not been extensively investigated. OBJECTIVE The objective of the study was to determine whether phase advances induced by morning intermittent bright light and a gradually advancing sleep schedule could be increased with afternoon melatonin. PARTICIPANTS Healthy adults (25 males, 19 females, between the ages of 19 and 45 yr) participated in the study. DESIGN There were 3 d of a gradually advancing sleep/dark period (wake time 1 h earlier each morning), bright light on awakening [four 30-min bright-light pulses (approximately 5000 lux) alternating with 30 min room light < 60 lux] and afternoon melatonin, either 0.5 or 3.0 mg melatonin timed to induce maximal phase advances, or matching placebo. The dim light melatonin onset was measured before and after the treatment to determine the phase advance. RESULTS There were significantly larger phase advances with 0.5 mg (2.5 h, n = 16) and 3.0 mg melatonin (2.6 h, n = 13), compared with placebo (1.7 h, n = 15), but there was no difference between the two melatonin doses. Subjects did not experience jet lag-type symptoms during the 3-d treatment CONCLUSIONS Afternoon melatonin, morning intermittent bright light, and a gradually advancing sleep schedule advanced circadian rhythms almost 1 h/d and thus produced very little circadian misalignment. This treatment could be used in any situation in which people need to phase advance their circadian clock, such as before eastward jet travel or for delayed sleep phase syndrome.
Residual layer-free detachment-based nanolithography

We present a simple method to generate nanostructures without residual layer using detachment-based nanolithography. Spin coated organic thin film and patterned stamp such as ultraviolet (UV) curable mold were prepared. The mold and organic thin film were contacted by slight pressure (1~2 bar). While conformal contact between mold and organic thin film, the sample was heated under the glass transient temperature. After cooling to room temperature, the mold was removed from substrate, rendering a pattern organic layer without residual layer. This method can form as small as 70 nm lines.
Neuroanatomical abnormalities before onset of delusions in patients with Alzheimer’s disease: a voxel-based morphometry study

Background Structural brain abnormalities associated with delusions in Alzheimer’s disease are poorly understood. In addition, whether the neural substrate underlying the delusions develops before the onset of the delusions is unclear. In this study, we used a voxel-based morphometry approach to examine the existence of regional structural abnormalities at baseline in patients with Alzheimer’s disease who did and who did not develop delusions. Methods Using the Neuropsychiatric Inventory, we identified patients with Alzheimer’s disease who exhibited delusions during a 2-year period. All the patients had undergone a magnetic resonance imaging examination at the start of the study period (baseline). We conducted a voxel-based morphometry analysis using statistical parametric mapping (SPM5) software and compared the results of patients with Alzheimer’s disease who did and did not develop delusions. Results Compared with the patients who did not develop delusions (n = 35), the patients who did develop delusions (n = 18) had significantly smaller gray matter volumes on both sides of the parahippocampal gyrus, the right posterior cingulate gyrus, the right orbitofrontal cortex, both sides of the inferior frontal cortex, the right anterior cingulate, and the left insula. Conclusion Structural brain abnormalities involving both the frontal and medial temporal lobes may be crucial to the expression of delusions in patients with Alzheimer’s disease.