Miracle-dz/UniFAR-FTUs huggingface dataset:
Constitutive behaviour of lead-free solders vs. lead-containing solders-experiments on bulk specimens and flip-chip joints

Both high Pb-Sn and eutectic 63Sn-37Pb have been the suitable materials for the interconnection of electronic components because of their low cost and appropriate physical properties. Due to environmental awareness, and the health hazards caused by the lead in the solders, large efforts have been made to develop a lead-free soldering technology. Among the large variety of lead-free solders the Sn-Ag alloys are expected to be the best candidates. Furthermore, from a reliability point of view, there has been interest in the improved thermal fatigue resistance of solder interconnects. Therefore, in this study two lead-free solder alloys (Sn96.5Ag3.5, Sn95.5Ag3.8Cu0.7) and two lead-containing solder alloys(Sn63Pb37 Sn59Pb40Agl) were investigated and compared with each other in order to give an estimation of the reliability enhancement of the new lead-free soldering technology. These investigations were focused on mechanical and physical properties (coefficient of thermal expansion, stress-strain curves at different strain-rates, ultimate strength) as well as on the microstructural appearance of the solders.
SMCQL: Secure Query Processing for Private Data Networks

People and machines are recording data at an unprecedented rate. At the same time, progress has been slow in making data available for open science and other research initiatives. Many of these efforts are stymied by privacy concerns and regulatory compliance issues. For example, numerous hospitals are interested in combining their patient records with those of other healthcare sites for clinical data research, but they cannot disclose the contents of their databases without violating patient confidentiality. We propose a novel generalization of federated database systems called a private data network (PDN), and it is designed for querying over the collective data of mutually distrustful parties. In a PDN, participants do not reveal their raw data, nor do they encrypt and upload it to the cloud. Rather, they perform secure multiparty computation (SMC) with other federation members to produce query results over the data of both parties. Here, a user submits their SQL query to an honest broker that plans and coordinates its distributed execution using SMC. Within SMC, the participating database providers compute a joint function with an output that is only revealed to the user and the honest broker. The databases computing the query learn nothing about the inputs provided by their peers, nor can they see the output of the group's computation. This capability comes at a high cost-SMC programs typically have runtimes that are orders of magnitude slower than their insecure counterparts. We address this challenge with a query planner that automatically identifies the minimal set of coordination points between parties in a given query plan. The planner translates these distributed steps into SMC as needed and feeds the secure code into our query executor. Our framework, SMCQL, plans and executes PDN queries. We are preparing SMCQL for an open-source release.
Pattern Search Optimization with a Treed Gaussian Process Oracle

This work combines pattern search optimization with a statistical emulator based on Treed Gaussian Processes (TGP) to create a new hybrid algorithm. The goal is to use the global probabilistic view provided by TGP to inform the local pattern search and form a more intelligent optimization algorithm. We also propose ways in which the emulator can be used to gain information about the objective function, inform the algorithm stopping rules and provide a probabilistic analysis of the type of convergence. We present the algorithm, a framework for statistically informed optimization, and illustrate the work with numerical results.
Study on Properties and Application of PG/CS Composite PCMs

Tris (hydroxymethyl) ethane (PG) as a phase change material, micro-porous xonotlite (CS) as matrix, PG/CS composite PCMs were prepared by melt-soaking method, and the effect of micro-porous structure of xonotlite on heat absorption capacity, bending strength and insulation performance of composites, and the exudation of PG was studied. Otherwise, for the work environment and characteristics of propulsive device of vehicle, this paper explored the feasibility that phase change materials (PCMs) worked as the insulation material in short-time insulation system of the vehicle. Experimental results show that, when the most probable pore diameters of xonotlite was not less than 63nm, the composites presented better and almost same absorption capacities of matrix (CS) to PCM (PG) in different composites; when up to 85nm, the composite exhibited the lowest leakage rate (less than 5%), the optimal mechanical property and thermal insulation performance. This Study proposed a new idea for the design of the insulation material in the thermal protection system of propulsive device of vehicle.
PAT: a postmortem object access pattern analysis and visualization tool

Applying a cache coherence protocol capable of adapting to memory access patterns is a viable approach to improving the performance of software distributed shared memory. In this paper, we present an approach of postmortem memory access pattern analysis and visualization, which has been applied to our design of a global object space for a distributed Java Virtual Machine. The tool not only can enhance our understanding of the access patterns inherent in an application but can also help us to evaluate the effectiveness of an adaptive protocol used in the design of the global object space.
Analysis of scanning force microscopy images of protein-induced DNA bending using simulations

Bending of DNA is a feature essential to the function of many DNA-binding proteins. Bending angles can be estimated with a variety of techniques, but most directly from images obtained using scanning force microscopy (SFM). Direct measurement of the bending angle using a tangent method often produces angles that deviate significantly from values obtained using other techniques. Here, we describe the application of SFM in combination with simulations of DNA as a means to estimate protein-induced bending angles in a reliable and unbiased fashion. In this manner, we were able to obtain accurate estimates for the bending angles induced by nuclear factor I, octamer-binding transcription factor 1, the human XPC-Rad23B complex.
Characterizing Shape Using Conformal Factors

We present a new 3D shape descriptor based on conformal geometry. Our descriptor is invariant under non-rigid quasi-isometric transformations, such as pose changes of articulated models, and is both compact and efficient to compute. We demonstrate the performance of our descriptor on a database of watertight models, and show it is comparable with state-of-the-art descriptors.
Binary descriptor based SIFT and hardware implementation

Scale-Invariant Feature Transform (SIFT) [1] has lately attracted attention in computer vision as a robust feature point detection algorithm which is invariant for scale, rotation and illumination change. However, its computational complexity is too high to apply on practical real-time applications. The iterated Gaussian blurred operations on images lead to long computational latency and high memory requirement. In addition, the gradient histogram based descriptor needs lots of calculation and costs about 60% of total calculation time on generating the descriptor. We propose a binary-based descriptor that uses the intensity difference between neighboring pixels. The binary descriptor has the advantage of lower computational complexity and memory usage. For the use of the classifying the object, the binary descriptor also have the acceptable accuracy compared with the traditional histogram based descriptor. The proposed binary descriptor has 7.07x speed up than the original SIFT descriptor. In addition, it has 4.73x speed up compared with original SIFT algorithm [1]. The hardware implementation of the SIFT algorithm with the proposed binary descriptor applies parallel computing on the stage of feature location to accelerate the computing time on detecting feature points. The final implementation uses about 493-K gate count with 90-nm CMOS technology, and offers 7600 feature points/frame for 1080p images at 30 frames/s at the clock rate of 100 MHz.
A 167-ps 2.34-mW Single-Cycle 64-Bit Binary Tree Comparator With Constant-Delay Logic in 65-nm CMOS

A single-cycle tree-based 64-bit binary comparator with constant-delay (CD) logic realized in a 65-nm, 1-V CMOS process is presented in this paper. Unlike dynamic logic yet domino-compatible, CD logic predischarges the output to logic “0” and conditionally makes a transition to logic “1” through the critical-path CLK PMOS transistors for an NMOS transistor network. The constant delay (regardless of the fan-in) feature makes it up to 2× faster than a dynamic logic gate during the D-Q mode for a complex logic such as a two-bit binary comparator. The proposed comparator's architecture is divided into two stages, where the first stage adapts a novel tree comparator structure specifically designed for static logic to achieve low-power consumption and the second stage utilizes CD logic to realize high performance without sacrificing the overall energy efficiency. At 1-V supply, the proposed comparator's measured delay is 167 ps, and has an average power and a leakage power of 2.34 mW and 0.06 mW, respectively. At 0.3-pJ iso-energy or 250-ps iso-delay budget, the proposed comparator with CD logic is 20% faster or 17% more energy-efficient compared to a comparator implemented with just the static logic.
Mutational analysis of conserved positions potentially important for initiator tRNA function in Saccharomyces cerevisiae

The conserved positions of the eukaryotic cytoplasmic initiator tRNA have been suggested to be important for the initiation of protein synthesis. However, the role of these positions is not known. We describe in this report a functional analysis of the yeast initiator methionine tRNA (tRNA(iMet)), using a novel in vivo assay system which is not dependent on suppressor tRNAs. Strains of Saccharomyces cerevisiae with null alleles of the four initiator methionine tRNA (IMT) genes were constructed. Consequently, growth of these strains was dependent on tRNA(iMet) encoded from a plasmid-derived gene. We used these strains to investigate the significance of the conserved nucleosides of yeast tRNA(iMet) in vivo. Nucleotide substitutions corresponding to the nucleosides of the yeast elongator methionine tRNA (tRNA(MMet)) have been made at all conserved positions to identify the positions that are important for tRNA(iMet) to function in the initiation process. Surprisingly, nucleoside changes in base pairs 3-70, 12-23, 31-39, and 29-41, as well as expanding loop I by inserting an A at position 17 (A17) had no effect on the tester strain. Nucleotide substitutions in positions 54 and 60 to cytidines and guanosines (C54, G54, C60, and G60) did not prevent cell growth. In contrast, the double mutation U/rT54C60 blocked cell growth, and changing the A-U base pair 1-72 to a G-C base pair was deleterious to the cell, although these tRNAs were synthesized and accepted methionine in vitro. From our data, we suggest that an A-U base pair in position 1-72 is important for tRNA(iMet) function, that the hypothetical requirement for adenosines at positions 54 and 60 is invalid, and that a U/rT at position 54 is an antideterminant distinguishing an elongator from an initiator tRNA in the initiation of translation.
Bottlenecks identification in multiclass queueing networks using convex polytopes

It is known that the resources that limit the overall performance of a system are the congested ones, referred to as bottlenecks. From knowledge of bottleneck stations, it is possible, with limited computational effort, to derive asymptotic values of several performance indices. While identifying the bottleneck stations is a well-established practice under a single-class workload, no simple methodology for multiclass models exists. We present new algorithms for identifying the bottlenecks in multiclass queueing networks with constant-rate servers. We show how the application of assessed techniques, such as the ones related to convex polytopes, can provide insights on the performance of a queueing network. The application of our techniques to the asymptotic analysis of closed product-form networks is also investigated.
EMF modeling in traffic surveillance experiments

We use a wireless sensor network equipped with acceleration sensors to measure seismic waves caused by rolling traffic. In this paper, we report on our experiences in applying an EMF-based data infrastructure to these experiments. We built an experimentation infrastructure that replaces unstructured text-file based management of data with a model-based approach. We use EMF to represent sensor data and corresponding analysis results; we use an extension of EMF's resource API to persist data in a database; and we use model transformations to describe data analysis. We conclude that a model based approach leads to safer, better documented, and more reproducible experiments.
An Evaluation and Possible Improvement Path for Current SMT Behavior on Ambiguous Nouns

Mistranslation of an ambiguous word can have a large impact on the understandability of a given sentence. In this article, we describe a thorough evaluation of the translation quality of ambiguous nouns in three different setups. We compared two statistical Machine Translation systems and one dedicated Word Sense Disambiguation (WSD) system. Our WSD system incorporates multilingual information and is independent from external lexical resources. Word senses are derived automatically from word alignments on a parallel corpus. We show that the two WSD classifiers that were built for these experiments (English--French and English--Dutch) outperform the SMT system that was trained on the same corpus. This opens perspectives for the integration of our multilingual WSD module in a statistical Machine Translation framework, in order to improve the automated translation of ambiguous words, and by consequence make the translation output more understandable.
Fundamental limits and improved algorithms for linear least-squares wireless position estimation

In this paper, theoretical lower bounds on performance of linear least-squares (LLS) position estimators are obtained, and performance differences between LLS and nonlinear least-squares (NLS) position estimators are quantified. In addition, two techniques are proposed in order to improve the performance of the LLS approach. First, a reference selection algorithm is proposed to optimally select the measurement that is used for linearizing the other measurements in an LLS estimator. Then, a maximum likelihood approach is proposed, which takes correlations between different measurements into account in order to reduce average position estimation errors. Simulations are performed to evaluate the theoretical limits and to compare performance of various LLS estimators. Copyright © 2010 John Wiley & Sons, Ltd. (Part of this work was presented at the IEEE Wireless Communications and Networking Conference (WCNC) 2008 and at the IEEE International Conference on Communications (ICC) 2008. )
Computing Semantic Similarities Based on Machine-Readable Dictionaries

The measurement of semantic similarity is a foundation work in semantic computing. In this paper the authors study the similarity measure between two words. Different from previous works, this paper suggests a novel method that relies on machine-readable dictionaries for measuring similarities. Machine-readable dictionaries are more widely available than other kinds of lexical resources. If two words have similar definitions, they are semantically similar. A definition is represented by a definition vector. Each dimension represents a word in the dictionary. The score of each dimension in the vector is calculated by a variation of tf*idf. Evaluations show that this method achieves competitive results in both Chinese and English.
CA 125 in Biological Fluids

CA 125 is not a specific tumor marker, and is synthesized by normal and malignant cells of different origin (mainly in tissues derived from the müllerian epithelia) in a similar proportion. Abnormal CA 125 levels may be found in fluids of different origin (ascites, pleura, pericardium, amniotic fluid, cyst fluid, bronchoalveolar fluid, etc.) and in serum from patients with these fluids. Differences in serum CA 125 found in malignant or benign diseases may be related to the number of cells that synthesize the marker, and are highly dependent on the access to serum, where the marker is normally determined. Moreover, CA 125 is a very good tumor marker in ovarian and lung cancer. The sensitivity of CA 125 in ovarian cancer is related to stage (40–95%), histological type (lower levels in mucinous adenocarcinoma), and the marker is useful in the early detection of recurrence (sensitivity 80%) and in therapy monitoring. It's sensitivity in lung cancer is lower than in ovarian cancer, 39% in locoregional malignancies and 69% in metastastatic disease, but clearly related to stage and histology (mainly in adenocarcinomas and large cell lung cancer) and it is useful in prognosis and disease monitoring.
Robust Minimum Variance Adaptive Beamformers and Multiuser MIMO Receivers: From the Worst-Case to Probabilistically Constrained Designs

Two related problems of the design of robust adaptive beamformers and multiuser multiple-input multiple-output (MIMO) receivers are considered. A popular recent solution to these problems is based on the worst-case performance optimization. Unfortunately, in practical applications the actual worst case occurs with a very low probability and, as a result, the worst-case based designs may be overly conservative. As a less conservative alternative to the worst-case designs, the so-called probabilistically constrained designs are introduced. The latter approach guarantees that the distortionless response constraint is satisfied for a mismatched array response with a certain selected probability. Improved flexibility and performance of the robust probabilistically constrained designs with respect to the worst-case designs are illustrated via simulations
Evolutionally dynamic L1 regulation in embryonic stem cells

Mobile elements are important evolutionary forces that challenge genomic integrity. Long interspersed element-1 (L1/LINE-1) is the only autonomous transposon still active in the human genome. Here, Castro-Diaz et al. show that early embryonic control of L1 is an evolutionarily dynamic process. The data indicate that two transcriptional repression systems are engaged in repressing L1 in human embryonic stem cells. A model is proposed in which newly emerged L1 lineages are first suppressed by DNA methylation-inducing small RNA-based mechanisms before sequence-specific protein repressors are selected.
Semantic Agent-Based Service Middleware and Simulation for Smart Cities

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.
The Conjugate Gradient Method and Trust Regions in Large Scale Optimization

Algorithms based on trust regions have been shown to be robust methods for unconstrained optimization problems. All existing methods, either based on the dogleg strategy or Hebden-More iterations, require solution of system of linear equations. In large scale optimization this may be prohibitively expensive. It is shown in this paper that an approximate solution of the trust region problem may be found by the preconditioned conjugate gradient method. This may be regarded as a generalized dogleg technique where we asymptotically take the inexact quasi-Newton step. We also show that we have the same convergence properties as existing methods based on the dogleg strategy using an approximate Hessian.
Fluctuations in Frequency Composition of Neural Activity Observed by Portable Brain Intention Detection Device

As part of the goal of developing wearable sensor technologies, we have continued the development of a headset system for monitoring activity across the primary motor cortex of the brain. Through the combination of electroencephalography (EEG) and near-infrared spectroscopy (NIRS), the headsets are capable of monitoring event-related potentials and hemodynamic activity, which are wirelessly transmitted to a computer for real-time processing to generate control signals for a motorized prosthetic limb or a virtual embodiment of one or more limbs. This paper focuses on recent observations that have been made regarding the frequency content of EEG data, which we believe is responsible for the high performance we have previously reported using artificial neural networks to infer user’s intentions. While the inference engine takes advantage of frequency content from 0-128 Hertz (Hz), distinct fluctuations in alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-100 Hz) frequency bands are human-observable across varying upper limb motor exercises when observed at the group level. In addition to prosthetic limbs, this technology is continuing to be investigated for application in areas including pain treatment, robotic arm control, lie detection, and more general brain-computer interfaces.
Vispubdata.org: A Metadata Collection About IEEE Visualization (VIS) Publications

We have created and made available to all a dataset with information about every paper that has appeared at the IEEE Visualization (VIS) set of conferences: InfoVis, SciVis, VAST, and Vis. The information about each paper includes its title, abstract, authors, and citations to other papers in the conference series, among many other attributes. This article describes the motivation for creating the dataset, as well as our process of coalescing and cleaning the data, and a set of three visualizations we created to facilitate exploration of the data. This data is meant to be useful to the broad data visualization community to help understand the evolution of the field and as an example document collection for text data visualization research.