Miracle-dz/UniFAR-FTUs huggingface dataset:
E-LSTM: An Efficient Hardware Architecture for Long Short-Term Memory

Long Short-Term Memory (LSTM) and its variants have been widely adopted in many sequential learning tasks, such as speech recognition and machine translation. Significant accuracy improvements can be achieved using complex LSTM model with a large memory requirement and high computational complexity, which is time-consuming and energy demanding. The low-latency and energy-efficiency requirements of the real-world applications make model compression and hardware acceleration for LSTM an urgent need. In this paper, several hardware-efficient network compression schemes are introduced first, including structured top-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> pruning, clipped gating, and multiplication-free quantization, to reduce the model size and the number of matrix operations by 32 <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> and 21.6 <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula>, respectively, with negligible accuracy loss. Furthermore, efficient hardware architectures for accelerating the compressed LSTM are proposed, which support the inference of multi-layer and multiple time steps. The computation process is judiciously reorganized and the memory access pattern is well optimized, which alleviate the limited memory bandwidth bottleneck and enable higher throughput. Moreover, the parallel processing strategy is carefully designed to make full use of the sparsity introduced by pruning and clipped gating with high hardware utilization efficiency. Implemented on Intel Arria10 S<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula>660 FPGA running at 200MHz, the proposed design is able to achieve 1.4–2.2 <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> energy efficiency and requires significantly less hardware resources compared with the state-of-the-art LSTM implementations.
Selective Growth of α-Sexithiophene by Using Silicon Oxides Patterns

A process for fabricating ordered organic films on large area is presented. The process allows growing sexithiophene ultra-thin films at precise locations on patterned Si/SiOx substrates by driving the orientation of growth. This process combines the parallel local anodic oxidation of Si/SiOx substrates with the selective arrangement of molecular ultra-thin film. The former is used to fabricate silicon oxide arrays of parallel lines of 400 nm in width over an area of 1 cm2. Selective growth arises from the interplay between kinetic growth parameters and preferential interactions with the patterned surface. The result is an ultra-thin film of organic molecules that is conformal to the features of the fabricated motives.
Flexible CoScheduling : Dealing with Load Imbalance and Heterogeneous Resources

Fine-grained parallel applications require all their proc esses to run simultaneously on distinct processors to make g ood progress. This is typically achieved by space slicing with v ariable partitioning, in which nodes are dedicated for the d uration of the run, or by gang scheduling, in which time slicing is coo rdinated across processors. The problem is that both scheme s suffer from fragmentation, where processors are left idle b ecause jobs cannot be packed with 100% efficiency. Naturally , this leads to reduced utilization and sub-optimal performance. Flexible coscheduling (FCS) solves this problem by monitor i g each job’s granularity and communication activity, and usi ng gang scheduling only for those jobs that really need it. Pr ocesses from other jobs, which can be scheduled without any constrai nts, are used as filler to reduce fragmentation. In addition, inefficiencies due to load imbalance and hardware heterogen eity are also reduced, because the classification is done on a per-process basis. FCS has been fully implemented as part of the STORM resource manager, and shown to be competitive with gang scheduling and implicit coscheduling.
Inferring Business Similarity from Topic Modeling [ Latent Dirichlet Allocation and Jaccard Similarity applied to Yelp reviews ]

In this paper, we apply the discovery of subtopics in Yelp reviews towards determining the level of similarity between Yelp businesses. Specifically, we apply an online Latent Dirichlet Allocation (LDA) algorithm to extract the latent subtopics within all reviews for a given business. We then aggregate the most frequently occurring subtopics per business, and utilize them to calculate the Jaccard Similarity between the topics of other businesses. Utilizing this combination of latent topics and similarity measurement allows us to uncover both subtle and obvious relationships between the reviews of two establishments. In addition, we describe other discoveries including the variance in topics found by rating distribution, as well other insights gained by an inspection of latent topics in review text.
New Culture Medium Containing Ionic Concentrations of Nutrients Similar to Concentrations Found in the Soil Solution

A new growth medium which closely approximates the composition of the soil solution is presented. This soil solution equivalent (SSE) medium contains the following components (millimolar): NO3, 2.5; NH4, 2.5; HPO4, 0.005; Na, 2.5; Ca, 4.0; Mg, 2.0; K, 0.503; Cl, 4.0; SO4, 5.0; ethylenediamine-di(o-hydroxyphenylacetic acid), 0.02; and MES [2-(N-morpholino)ethanesulfonic acid] (to maintain the pH at 6.0), 10, plus 0.1% arabinose. The advantages of the SSE medium are discussed.
New Image Steganography Method Based on K-means Clustering

In this paper, a new image steganography method based on k-means clustering for embedding secret messages into a gray image is proposed. The proposed methodology is a combination of two techniques, image clustering and Least Significant Bits replacement. In the embedding process, a cover image is segmented into clusters using the K-means clustering algorithm. Each cluster is partitioned into two regions, smooth and complex, only smooth regions may contain the secret data. In this manner, degradation of the Stego image quality is imperceptible to the human eye. For better protection of secret message, a pseudo-random key mechanism is coupled to the implementation of the LSB method. The secret data can be recovered directly from the image Stego without reference to cover-image. The experimental results show that the proposed method has a high image quality and a good embedding capacity.
The Port of Trieste (Northern Adriatic Sea)—A Case Study of the “Ecosystem Approach to Management”

This study is a rare example of “the ecosystem approach to management” that has been carried out for the purpose of providing practical support to decision-makers in managing a Site of National Interest (SIN) where activities such as fishing, aquaculture and swimming are restricted. Benthic ecosystem functioning was assessed to verify whether it would be possible to exclude the less contaminated part from the SIN and its legislative constraints. At five macrosites subjected to diversified industrialization and anthropization, we evaluated the structural characteristics of the sediments, both heterotrophic and phototrophic communities, and the main processes of production, transformation and consumption of organic matter at seven stations, plus a reference site. Along the north-eastern boundary of the bay, the port, shipbuilding and iron foundry areas, characterised by high levels of contaminants, low macrozoobenthic diversity, major organic contents (up to 51.1 mgC g-1) and higher numbers of hydrocarbon degrading bacteria (up to 5,464 MPN gdry-1), differed significantly (RANOSIM = 0.463, p = 2.9%) from the other areas (stations). Oxygen consumption (-15.221.59 mgC m-2) prevailed over primary production and the trophic state was net heterotrophic. In contrast, on the other side of the harbour (residential area/centre bay), contamination levels were below the legal limits and both the microalgal and macrobenthic communities displayed higher biodiversity. Higher macrofaunal abundances (up to 753174.7 ind.m-2), primary production rates (up to 58.608.41 mgC m-2) and exoenzymatic activities were estimated. nMDS and SIMPROF analyses performed on benthic communities significantly separated the most contaminated stations from the other ones. Overall, by applying this holistic approach, a better environmental situation was highlighted along the southern boundary of the bay and according to these results this part of the bay could be excluded from the SIN. However, further sampling is required along a finer sampling grid in the less contaminated side of the port in order to confirm these first results. Our work is one of the first case studies where such an ecosystem approach has been applied to a port area, in order to provide practical support to decision-makers involved in the spatial planning of harbour zones.
On time series classification with dictionary-based classifiers

A family of algorithms for time series classification (TSC) involve running a sliding window across each series, discretising the window to form a word, forming a histogram of word counts over the dictionary, then constructing a classifier on the histograms. A recent evaluation of two of this type of algorithm, Bag of Patterns (BOP) and Bag of Symbolic Fourier Approximation Symbols (BOSS) found a significant difference in accuracy between these seemingly similar algorithms. We investigate this phenomenon by deconstructing the classifiers and measuring the relative importance of the four key components between BOP and BOSS. We find that whilst ensembling is a key component for both algorithms, the effect of the other components is mixed and more complex. We conclude that BOSS represents the state of the art for dictionary-based TSC. Both BOP and BOSS can be classed as bag of words approaches. These are particularly popular in Computer Vision for tasks such as image classification. We adapt three techniques used in Computer Vision for TSC: Scale Invariant Feature Transform; Spatial Pyramids; and Histogram Intersection. We find that using Spatial Pyramids in conjunction with BOSS (SP) produces a significantly more accurate classifier. SP is significantly more accurate than standard benchmarks and the original BOSS algorithm. It is not significantly worse than the best shapelet-based or deep learning approaches, and is only outperformed by an ensemble that includes BOSS as a constituent module.
Decontamination of Chlorella sp. culture using antibiotics and antifungal cocktail treatment

Direct sampling of microalgae from nature inevitably brings together the problem of massive growth of bacteria and fungi. In this study, bacterial and fungal contamination level was evaluated from the Chlorella sp. isolated from two different locations of local freshwater area. Attempts to obtain axenic Chlorella sp. culture by combinations of antibiotic and antifungal at different range of concentration treatment were investigated. It is evident that there were three different bacteria and two different fungi present in the culture, but apparently sterility can be achieved when ampicillin, cefotaxime and carbendazim cocktail were employed at concentrations of 700 µg/mL, 200 µg/mL and 0. 1µg/mL, respectively. These concentrations are also proven harmless toward Chlorella sp. as higher concentrations inhibit the growth of microalgae. It was found that by streaking the contaminated microalgae twice onto the TAP agar containing the previously described cocktail, completely removed the contaminating fungi and bacteria from the culture. In conclusion, this study suggested that axenic Chlorella sp. can be attained with this method and cocktail recipe.
Towards Real-Time Magnetic Resonance Teleradiology Over The Internet

Teleradiology involves transmitting high-resolution medical images from one remote site to another and displaying the images effectively so that radiologists can perform the proper diagnosis. Recent advances in medicine combined with those in technology have resulted in a vast array of medical imaging techniques, but due to the characteristics of these images, there are challenges to overcome in order to transmit these images efficiently. We describe in this thesis a prototype system that implements three image retrieval algorithms (Full-resolution, Scaled, and Pre-compressed) for retrieving magnetic resonance (MR) images that are stored on a web server. The MR images are displayed on a computer monitor instead of a traditional light screen. Our prototype system consists of a Java-based Image Viewer, and a web server extension component called, Image Servlet. The latter is responsible for transmitting the MR images to the Image Viewer. This thesis also investigates the feasibility of achieving real-time performance in retrieving and viewing MR images over the Internet using HTTP/1.0 protocol. We have conducted experiments to measure the round trip time of retrieving the MR images. Based on the findings from the experiments, the three image retrieval algorithms are compared and a discussion of their appropriateness for teleradiology is presented. iv Dedication To my wife Rita for her continuous encouragement and support.
Real time high spatial-temporal resolution flow imaging with spiral MRI using auto-calibrated SENSE

A novel spiral phase contrast technique was developed for high temporal and spatial resolution imaging of blood flow without cardiac gating. Spiral sampling of k-space has excellent flow properties and acquisition speed. Parallel imaging using the coil sensitivity maps can be used to reduce the imaging duration at the cost of SNR. An auto-calibrated spiral sensitivity encoding method is introduced and used for reconstruction of phase contrast images. Phase estimation for a simulated phantom using data from various acceleration rates was compared to the true phase map. To study the accuracy of the flow estimate with parallel image reconstruction, a high resolution cardiac gated experiment was performed and a subset of under-sampled data were reconstructed. The real-time experiments were performed to measure blood velocity in the ascending aorta and through the aortic valve with high spatial and temporal resolution. Temporal resolution of the flow images was improved by a factor of at least three with no cardiac gating signal with preserved spatial resolution. The results demonstrate the potential of using the technique for real-time flow imaging with improved spatial and temporal resolution.
Proteomics of bovine endometrium, oocytes and early embryos

Embryo-maternal communication, as well as recognition and establishment of pregnancy, is predominantly controlled by secretion of hormones and proteins. Furthermore, uterine fluid serves as a histotroph and contains factors essential for embryo development and elongation, making it a meaningful source for proteomic approaches of early embryonic development. The studies included in this review address the analysis of uterine fluid and endometrium during the oestrous cycle, early pregnancy, maternal effects on embryo development and embryo-induced alterations to the maternal environment. Clear differences between the proteome of uterine fluid and blood plasma unravelled the active contribution of the endometrium to the composition of uterine luminal fluid. Proteins were identified which may contribute either to growth enhancement of blastocysts or influence secretion of “Interferon tau”. Several studies suggested important roles of intrauterine factors including “Tissue inhibitor of metalloproteinases 2” for pregnancy establishment and “Acyl-CoA-binding protein” for the embryo prior to implantation. A meta-analysis of quantitative proteome studies revealed functional clusters including the terms “degradation of extracellular matrix”, “platelet degranulation” and “MHC class II antigen presentation”. Proteomic studies targeting oocytes and early embryos provided evidence for the function of “Cyclin B” in mitotic resumption, for “14-3-3 epsilon” to activate “maturation promotion factor” for promotion of mitosis during in vitro maturation, or for the inhibition of proteasomes during the late phase of maturation. Analysis of blastocyst derived trophectoderm cell lines suggested effects of annexin down-regulation on the failure rate of nuclear transfer pregnancies. Finally, absolute quantification of “Y-box-binding protein 2” and “Insulin-like growth factor 2 mRNA-binding protein 3” during early embryogenesis by “selected reaction monitoring” demonstrated the dynamism of proteome alterations during the first embryonic cell divisions.
Zeeker: A topic-based search engine

The rapid growth and massive quantities of data on the Internet have increased the importance and complexity of Information Retrieval. The amount and diversity of data introduce shortcomings in the way search engines rank their results. As a result, Search Engine Optimization companies flourish by exploiting the search engine weaknesses in order to manipulate the search results. Furthermore, many search engines present several million results to queries and more often or not these results are biased toward blogs and on-line stores. This bias is due to the link analysis used to rank the search results. Internet link structure is the strength but at the same time the Achilles’ heel of these ranking algorithms. In this work it is proposed to push search engine behavior in a new direction, away from link analysis and toward actual content and topic analysis of web pages. With the use of clustering algorithms and the vast amount of information in Wikipedia the idea is to create categories that are good enough to be used to filter search results. The prospect of letting the user filter the search results by the push of a button would improve the relevance of the search results for a particular query. Categories will give the user fewer yet more relevant results. The well-defined categories and articles of Wikipedia are shown to be valuable as a training set when clustering Internet data. The implemented Zeeker Search Engine has precise categories which can become even better by taking advantage of additional information available in Wikipedia. A user-survey conducted has revealed that Zeeker Search Engine has good relevance when retrieving information, is easy to use and has great potential as a search engine. This work has suggested innovative ideas and ways of using the information in Wikipedia to produce good categories and retrieve more relevant search results.
Fine-Grained Communication-Aware Task Scheduling Approach for Acyclic and Cyclic Applications on MPSoCs

Fine-grained task models can exploit parallelism to achieve high performance for multiprocessor system-on-chip (MPSoC). However, fine-grained models face the issues of high-communication overhead and difficult scheduling decisions, and the two challenges are inter-dependent. To address the issues, this paper gives a full analysis of the fine-grained communication optimization technique and communication pipeline, from both time and topology perspectives, and proposes a static fine-grained communication-aware task scheduling (FCATS) approach, which integrates scheduling with communication pipeline for acyclic and cyclic applications based on the fine-grained Simulink model. The approach contains search-based scheduling with high-quality solutions utilizing genetic algorithm-integer linear programming (GA-ILP) and hybrid GA-heuristic scheduling with short solving time to meet different demands for users. The experimental results with both synthetic and real-life benchmarks on the 4/8/16-CPU platform demonstrate the efficiency of the approach on performance improvements compared to previous works.
Throughput Delay Tradeoff for Wireless Multicast Using Hybrid-ARQ Protocols

In this paper, we present a hybrid automatic repeat request (ARQ) scheme for wireless multicast with incremental redundancy channel coding and packet retransmission. With this scheme, we can reliably deliver the same copy of information to different users with mild delay. In addition, the design of the feedback channel for this scheme can be greatly simplified as no effort must be expended to combat cross user interference. We assume that there is always a packet for the transmitter to send whenever the channel is available. The transmitter is assumed to have a buffer of infinite length so that there is no packet-dropping. Three specific schemes are studied, including generalized slotted ALOHA (GSA), repetition time diversity (RTD), and general incremental redundancy (IR). The scaling laws of the average delay and average throughput with respect of the number of users are derived. In addition, we also derive a condition to obtain a linear scaling for both the throughput and the delay with respect to the number of users. Since every user can achieve no more than the ergodic capacity, we actually achieve the optimal scaling law in this case. Simulation results confirm our findings.
Distributed Object Store Principles of Operation The Case for Intelligent Storage

In this paper we look at the growth of distributed object stores (DOS) and examine the underlying mechanisms that guide their use and development. Our focus is on the fundamental principles of operation that define this class of system, how it has evolved, and where it is heading as new markets expand beyond the use originally presented. We conclude by speculating about how object stores as a class must evolve to meet the more demanding requirements of future applications.
GABAA receptor drugs and neuronal plasticity in reward and aversion: focus on the ventral tegmental area

GABAA receptors are the main fast inhibitory neurotransmitter receptors in the mammalian brain, and targets for many clinically important drugs widely used in the treatment of anxiety disorders, insomnia and in anesthesia. Nonetheless, there are significant risks associated with the long-term use of these drugs particularly related to development of tolerance and addiction. Addictive mechanisms of GABAA receptor drugs are poorly known, but recent findings suggest that those drugs may induce aberrant neuroadaptations in the brain reward circuitry. Recently, benzodiazepines, acting on synaptic GABAA receptors, and modulators of extrasynaptic GABAA receptors (THIP and neurosteroids) have been found to induce plasticity in the ventral tegmental area (VTA) dopamine neurons and their main target projections. Furthermore, depending whether synaptic or extrasynaptic GABAA receptor populations are activated, the behavioral outcome of repeated administration seems to correlate with rewarding or aversive behavioral responses, respectively. The VTA dopamine neurons project to forebrain centers such as the nucleus accumbens and medial prefrontal cortex, and receive afferent projections from these brain regions and especially from the extended amygdala and lateral habenula, forming the major part of the reward and aversion circuitry. Both synaptic and extrasynaptic GABAA drugs inhibit the VTA GABAergic interneurons, thus activating the VTA DA neurons by disinhibition and this way inducing glutamatergic synaptic plasticity. However, the GABAA drugs failed to alter synaptic spine numbers as studied from Golgi-Cox-stained VTA dendrites. Since the GABAergic drugs are known to depress the brain metabolism and gene expression, their likely way of inducing neuroplasticity in mature neurons is by disinhibiting the principal neurons, which remains to be rigorously tested for a number of clinically important anxiolytics, sedatives and anesthetics in different parts of the circuitry.