Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Adaptation and Energy Minimization for Hardware Recurrent Spiking Neural Networks

The Liquid State Machine (LSM) is a promising model of recurrent spiking neural networks that provides an appealing brain-inspired computing paradigm for machine-learning applications such as pattern recognition. Moreover, processing information directly on spiking events makes the LSM well suited for cost- and energy-efficient hardware implementation. In this article, we systematically present three techniques for optimizing energy efficiency while maintaining good performance of the proposed LSM neural processors from both an algorithmic and hardware implementation point of view. First, to realize adaptive LSM neural processors, thus boost learning performance, we propose a hardware-friendly Spike-Timing Dependent Plastic (STDP) mechanism for on-chip tuning. Then, the LSM processor incorporates a novel runtime correlation-based neuron gating scheme to minimize the power dissipated by reservoir neurons. Furthermore, an activity-dependent clock gating approach is presented to address the energy inefficiency due to the memory-intensive nature of the proposed neural processors. Using two different real-world tasks of speech and image recognition to benchmark, we demonstrate that the proposed architecture boosts the average learning performance by up to 2.0% while reducing energy dissipation by up to 29% compared to a baseline LSM with little extra hardware overhead on a Xilinx Virtex-6 FPGA.
Design of A Transformer-Based Reconfigurable Digital Polar Doherty Power Amplifier Fully Integrated in Bulk CMOS

This paper presents a digital polar Doherty power amplifier (PA) fully integrated in a 65 nm bulk CMOS process. It achieves +27.3 dBm peak output power and 32.5% peak PA drain efficiency at 3.82 GHz and 3.60 GHz, respectively. The proposed digital Doherty PA architecture optimizes the cooperation of the main and auxiliary amplifiers and achieves superior back-off efficiency enhancement (a maximum 47.9% improvement versus the corresponding Class-B operation). This digital intensive architecture also allows in-field PA reconfigurability which both provides robust PA operation against antenna mismatches and allows flexible trade-off optimization on PA efficiency and linearity. Transformer-based passives are employed as the Doherty input and output networks. The input 90 ° signal splitter is realized by a 6-port folded differential transformer structure. The active Doherty load modulation and power combining at the PA output are achieved by two transformers in a parallel configuration. These transformer-based passives ensure an ultra-compact PA design (2.1 mm 2) and broad bandwidth (24.9% for -1 dB P out bandwidth). Measurement with 1 MSym/s QPSK signal shows 3.5% rms EVM with +23.5 dBm average output power and 26.8% PA drain efficiency. Measurement with 16-QAM signal exhibits the PA's flexibility on optimizing efficiency and linearity.
Near and medium infrared optical fiber lasers and emerging applications

Laser cavities emitting in the near and medium infrared wavelength range, made of rare earth doped optical fibers and suitable pairs of integrated mirrors, are used in a large number of applications. Nowadays, the efficient employment of near and medium infrared laser beams is largely widespread in the field of m*aterial processing, surgery, directed energy, remote sensing, spectroscopy, imaging, and so on. In a lot of cases, the high conversion efficiency, the excellent beam quality, the compactness and, the good heat dissipation capability make fiber lasers competitive and attractive with respect to other light sources, such as ion-doped crystal and bulk glass lasers, optical parametric oscillators, semiconductor and gas lasers. The paper aims to recall and/or briefly illustrate a few among the numerous strategies recently followed by research laboratories and industries to obtain laser sources based on rare earth doped optical fibres. A recall on the host materials and the dopants employed for their construction, and the corresponding applications is given, too. Moreover, an example of near infrared (NIR) fiber optic laser development, by employing available on market components is illustrated by underlining the possibility to easily obtain high beam quality.
Leberkrankung Established therapies and new therapeutic strategies in alcoholic liver disease

Chronical alcohol abuse causes more than 200 diseases and/or symptoms and among these alcoholic liver disease (ALD) is of special importance since it occurs frequently and may be life-threatening. In Europe alcohol consumption as well as ALD increased as compared to the rest of the world. It has been estimated that in Europe approximately 500 000 people die every year due to ALD. ALD consists of alcoholic fatty liver, alcoholic steatohepatitis (ASH), alcoholic cirrhosis and hepatocellar cancer (HCC ). Alcohol hepatitis (AH) is a clinical feature with jaundice and liver failure and a high mortality. The course of ALD is variable and depends among others, on genetics, gender, the presence of other liver diseases as well as exposure towards toxic substances and drugs. The treatment of ALD mainly consists of alcohol abstinence which may be difficult to achieve in the alcoholic. The results of the therapy improve by cognitive psychotherapy as well as antigraving medication.The treatment of AH with poor prognosis is limited. Although a number of therapeutic approaches in AH have been tried, the present therapy consists of intensive care in association with the administration of steroids, hyperalimentation and possibly the administration of N-acetylcystein. Presently it is discussed whether liver transplantation is an option for these patients. New therapeutic approaches focuses on pathopyhsiologically identified targets in ALD. This includes elimination of endotoxines, cytokines, and chemokines as well as an inhibition oxidative stress.Antigraving substances, such as Nalmafen also may improve liver function since their administration degreases alcohol consumption. In addition, betain to stimulate methyltransfer as well the inhibition of apoptosis have been investigated. Übersicht Seitz HelmutKarl, Mueller Sebastian. Etablierte Therapien und Z Gastroenterol H er un te rg el ad en v on : I ca hn S ch oo l o f M ed ic in e at M ou nt S in ai . U rh eb er re ch tli ch g es ch üt zt . Stimulation of liver regeneration by granulozytecolony stimulating factor as well as mesenchymalcell and bone marrow transplantation have shown some positive results. Nevertheless new therapeutic strategies are urgently needed. Especially in AH with its high mortality.
State of the art review: Chemotherapy‐induced cardiotoxicity in children

Chemotherapy-induced cardiotoxicity in adults and children is a topic with a growing interest in the cardiology literature. The ability to detect cardiac dysfunction in a timely manner is essential in order to begin adequate treatment and prevent further deterioration. This article aims to provide a review on the myocardial injury process, chemotherapeutic agents that lead to cardiotoxicity, the definition of cardiotoxicity, and the methods of timely detection and treatment.
Mid-pregnancy cervical length as a risk factor for cesarean section in women with twin pregnancies

Abstract Objective: It is well known that a short cervix at mid-pregnancy is a risk factor for spontaneous preterm birth in both singleton and twin gestations. Recent evidence also suggests that a long cervix at mid-pregnancy is a predictor of the risk of cesarean section (C/S) in singleton gestation. The purpose of this study was to determine whether a long cervix at mid-pregnancy was associated with an increased risk of C/S in women with twin pregnancies. Methods: We enrolled 746 women pregnant with twins whose cervical length was measured by trans-vaginal ultrasonography at a mean of 22 weeks of gestation and who delivered in our institution. Cases with a short cervix [cervical length (CL) <15 mm] were excluded. Cases were divided into four groups according to the quartile of CL. Results: The rate of C/S increased according to the quartile of CL (47% in the 1st quartile, 51% in the 2nd quartile, 56% in the 3rd quartile and 62% in the 4th quartile, P<0.005, χ2 for trend). CL was an independent risk factor for C/S even after adjustment for confounding variables. When confining analysis to women who delivered after a trial of labor (n=418), to nulliparous women (n=633) or to those who delivered at late preterm or full term (n=666), the rate of C/S also increased according to the quartile of CL, and the relationship between CL and the risk of C/S remained significant after adjustment in each group. Conclusion: In women pregnant with twins, long CL at mid-pregnancy was a risk factor for C/S.
Analysis on solder ball shear testing conditions with a simple computational model

This paper introduces a simple computational model for the analysis on the solder ball shear testing conditions. Both two‐dimensional (2‐D) and three‐dimensional (3‐D) finite element models are used to investigate the effect of shear ram speed on the solder ball shear strength of plastic ball grid array (PBGA) packages. An effective thickness is identified for the 2‐D finite element analysis. By using this effective thickness as a scale factor, it is shown that the 2D model is feasible for the study of 3‐D problems. The computational model is validated by experimental data in terms of load‐displacement curves. The results from both testing and modeling indicate that the shear ram speed has a substantial effect on the solder ball shear strength. In general, faster ram speed can result in higher ball shear strength. Therefore, the characterization of solder ball shear strength is loading rate‐dependent.
Deep Textual Searching for Visual Semantics of Personal Photo Collections with a Hybrid Similarity Measure

In recent years, personal photos on the internet have become important parts of people’s lives. There is much automatic application software to search for photos, but searching still suffers from problems of semantic accuracy. Research has been conducted to satisfy user demands for a semantic model using a set of features or keyword annotation techniques. Keywords in photos give the best evidence to identify what photos are about. However, it does not always relate to the actual meaning of photos.For this reason, we propose a textual description with a hierarchical concept and comparison of the feature set with a hybrid similarity measure. The experimental results indicate that our proposed approach offers significant performance improvements in the interpretation of semantic meanings with a maximum success rate of 80.4%.
Background initialisation by spatio-temporal motion estimation

Estimating the initial background of a scene is a key prerequisite for several applications in video analytics. In this paper, we present a simple approach that takes into account spatio-temporal motion intensities while estimating the true background. We tested the algorithm on real video sequences from the Scene Background Initialization (SBI) benchmark dataset, and the results show that the algorithm is competitive compared to the state of the art.
The generalized matrix chain algorithm

In this paper, we present a generalized version of the matrix chain algorithm to generate efficient code for linear algebra problems, a task for which human experts often invest days or even weeks of works. The standard matrix chain problem consists in finding the parenthesization of a matrix product M := A1 A2 ⋯ An that minimizes the number of scalar operations. In practical applications, however, one frequently encounters more complicated expressions, involving transposition, inversion, and matrix properties. Indeed, the computation of such expressions relies on a set of computational kernels that offer functionality well beyond the simple matrix product. The challenge then shifts from finding an optimal parenthesization to finding an optimal mapping of the input expression to the available kernels. Furthermore, it is often the case that a solution based on the minimization of scalar operations does not result in the optimal solution in terms of execution time. In our experiments, the generated code outperforms other libraries and languages on average by a factor of about 9. The motivation for this work comes from the fact that—despite great advances in the development of compilers—the task of mapping linear algebra problems to optimized kernels is still to be done manually. In order to relieve the user from this complex task, new techniques for the compilation of linear algebra expressions have to be developed.
A cross-protocol attack on the TLS protocol

This paper describes a cross-protocol attack on all versions of TLS; it can be seen as an extension of the Wagner and Schneier attack on SSL 3.0. The attack presents valid explicit elliptic curve Diffie-Hellman parameters signed by a server to a client that incorrectly interprets these parameters as valid plain Diffie-Hellman parameters. Our attack enables an adversary to successfully impersonate a server to a random client after obtaining 240 signed elliptic curve keys from the original server. While attacking a specific client is improbable due to the high number of signed keys required during the lifetime of one TLS handshake, it is not completely unrealistic for a setting where the server has high computational power and the attacker contents itself with recovering one out of many session keys. We remark that popular open-source server implementations are not susceptible to this attack, since they typically do not support the explicit curve option. Finally we propose a fix that renders the protocol immune to this family of cross-protocol attacks.
Dual-Side Optimization for Cost-Delay Tradeoff in Mobile Edge Computing

Mobile code offloading (MCO) is a technology that offloads computing tasks from mobile devices to remote servers managed by code offload service providers (CSPs). Nowadays, it is recommended that the remote servers be placed on the edge of the network to support modern applications, e.g., augmented reality, which demand stringent and ultralow latency or high bandwidth. To date, previous studies have independently addressed code offloading policy in mobile devices and pricing/server provisioning policies in the CSP; moreover, the system models for both user side and CSP side have not adequately reflected their practical aspects. This paper designs a practical model for the both sides and takes account of them in an integrated MCO framework simultaneously. By leveraging Lyapunov drift-plus-penalty technique, we propose code offloading, local CPU clock frequency, and network interface selection policies for mobile users, and propose MCO service pricing and server provisioning policies for the CSP in each of a competition scenario and a cooperation scenario. In the competition scenario, we propose a Com-UC algorithm for mobile users and a Com-PC algorithm for the CSP with the aim to minimize each cost for each queue stability constraint. In the cooperation scenario, we propose a Coo-JC algorithm with the aim to minimize their sum cost for both mobile users and CSP. Via trace-driven simulations, we demonstrate that Com-UC saves at most 71% of its cost and Com-PC attains 82% profit gain for the same delay compared to existing algorithms; moreover, the cooperation between mobile users and CSP additionally reduces costs and delays.
The Determinants of Consumers’ Purchase Intention to Online Group-Buying

This paper contributes to examine the determinants of consumers’ post-adoption purchase intention with an integrated theoretical model proposed by our study. Data collected from a questionnaire survey of group buying consumers provides empirical support for that model. The results indicate that consumers’ satisfaction with prior use and perceived usefulness significantly influence consumers’ continuance intention. Consumers’ satisfaction is determined primarily by consumers' confirmation of expectation and secondarily by perceived e-recovery service quality. Further, confirmation also has a significant influence on post-adoption perceived usefulness
A Clustering Method for Web Service Discovery

With the development of web service applications, how to improve the efficiency of service discovery is an important research work in modern times. From the aspect of service function, this paper clusters web services to form service clusters based on service ontology which is generated by domain modeling. It can significantly reduce the overhead and enhance the service discovery efficiency. The corresponding service clustering algorithm and experiments are given to verify the feasibility of the proposed method.
Effect of resistivity of ITO thin film when used in transparent checkerboard surfaces for RCS reduction

Two periodic structures with particular reflection phase properties, when used in a checkerboard patterned arrangement, can lead to wideband reduction in radar cross-section. The individual periodic structures are to be designed such that the difference in the reflection phase of the two structures is around 180° in the frequency band of interest. Phase cancellation results in the reduction in the backscattered RCS. For effective phase cancellation, it is necessary that the individual periodic structure is a high impedance surface (HIS). HIS can be realized using low loss substrates with highly conductive coating. Typical PCB substrates with copper layer can be used to realize such HIS. In this work, we investigate the use of indium titanium oxide (ITO) thin film for realizing transparent checkerboard patterned surfaces with RCS reduction capabilities. ITO is a transparent conducting oxide, having a trade-off between transparency and conductivity. Glass with dielectric constant εr = 7.4 is used as the substrate. The effect on the reflection phase characteristics due to the resistivity of ITO thin film, patterned over glass substrate is investigated. A checkerboard patterned surface with copper coating, leading to 6 dB reduction in RCS in the X-band is used as the base design to demonstrate the effect of the resistivity of the ITO thin film. The transparent checkerboard patterned surface is fabricated using ITO coated glass and a suitable etching process to realize the patterned surface. Measurement of reduction in backscatter RCS in the X-band is carried out. Both measurement and simulation results demonstrate the transition of the periodic structure from an HIS to a resistive radar absorbing material, depending on the resistivity of the ITO thin film. Results confirm that the conductivity of the ITO thin film is a critical parameter, when used to realize checkerboard patterned surfaces for RCS reduction.
Active learning and inference method for within network classification

In relational learning tasks such as within network classification the main problem arises from the inference of nodes' labels based on the the ground true labels of remaining nodes. The problem becomes even harder if the nodes from initial network do not have any labels assigned and they have to be acquired. However, labels of which nodes should be obtained in order to provide fair classification results? Active learning and inference is a practical framework to study this problem. The method for active learning and inference in within network classification based on node selection is proposed in the paper. Based on the structure of the network it is calculated the utility score for each node, the ranking is formulated and for selected nodes the labels are acquired. The paper examines several distinct proposals for utility scores and selection methods reporting their impact on collective classification results performed on various real-world networks.
Accounting for genetic differences among unknown parents in microevolutionary studies: how to include genetic groups in quantitative genetic animal models

Summary Quantifying and predicting microevolutionary responses to environmental change requires unbiased estimation of quantitative genetic parameters in wild populations. ‘Animal models’, which utilize pedigree data to separate genetic and environmental effects on phenotypes, provide powerful means to estimate key parameters and have revolutionized quantitative genetic analyses of wild populations. However, pedigrees collected in wild populations commonly contain many individuals with unknown parents. When unknown parents are non‐randomly associated with genetic values for focal traits, animal model parameter estimates can be severely biased. Yet, such bias has not previously been highlighted and statistical methods designed to minimize such biases have not been implemented in evolutionary ecology. We first illustrate how the occurrence of non‐random unknown parents in population pedigrees can substantially bias animal model predictions of breeding values and estimates of additive genetic variance, and create spurious temporal trends in predicted breeding values in the absence of local selection. We then introduce ‘genetic group’ methods, which were developed in agricultural science, and explain how these methods can minimize bias in quantitative genetic parameter estimates stemming from genetic heterogeneity among individuals with unknown parents. We summarize the conceptual foundations of genetic group animal models and provide extensive, step‐by‐step tutorials that demonstrate how to fit such models in a variety of software programs. Furthermore, we provide new functions in r that extend current software capabilities and provide a standardized approach across software programs to implement genetic group methods. Beyond simply alleviating bias, genetic group animal models can directly estimate new parameters pertaining to key biological processes. We discuss one such example, where genetic group methods potentially allow the microevolutionary consequences of local selection to be distinguished from effects of immigration and resulting gene flow. We highlight some remaining limitations of genetic group models and discuss opportunities for further development and application in evolutionary ecology. We suggest that genetic group methods should no longer be overlooked by evolutionary ecologists, but should become standard components of the toolkit for animal model analyses of wild population data sets.
Conduction in non-crystalline systems IX. the minimum metallic conductivity

Abstract The minimum metallic conductivity in disordered materials, proposed by the author in previous papers, is evaluated in the light of the revised criterion for Anderson localization given by Edwards and Thouless (1972). The experimental evidence resulting from the recent work of Allen and Adkins (1972) is reviewed, as is also the discussion by Cohen (1971) and Eggarter (1972) based on percolation theory. This and other evidence suggests strongly that a minimum metallic conductivity does exist having approximately the calculated value.