Miracle-dz/UniFAR-FTUs huggingface dataset:
Pre-Bond and Post-Bond Testing of TSVs and Die-to-Die Interconnects

Chip-to-chip interconnects can be traditionally tested for stuck-at faults and hard bridging faults via the boundary scan test standard. However, such a traditional test method may not be adequate for 3D-ICs, in which die-to-die interconnects could operate at a very high speed with an end-to-end delay of only a few hundred of picoseconds. Parametric defects (such as small delay faults, resistive open/bridging faults, leakage faults, etc.) have been identified as new threats to the quality, yield, and reliability of a 3D-IC. In response to this challenge, numerous test methods have been developed. In this chapter, we will first discuss common defect types occurring to die-to-die interconnects, and then review various interconnect test methods applicable during the pre-bond stage and the post-bond stage.
Electronic Health Record Patient Portal Adoption by Health Care Consumers: An Acceptance Model and Survey

Background The future of health care delivery is becoming more citizen centered, as today’s user is more active, better informed, and more demanding. Worldwide governments are promoting online health services, such as electronic health record (EHR) patient portals and, as a result, the deployment and use of these services. Overall, this makes the adoption of patient-accessible EHR portals an important field to study and understand. Objective The aim of this study is to understand the factors that drive individuals to adopt EHR portals. Methods We applied a new adoption model using, as a starting point, Ventkatesh's Unified Theory of Acceptance and Use of Technology in a consumer context (UTAUT2) by integrating a new construct specific to health care, a new moderator, and new relationships. To test the research model, we used the partial least squares (PLS) causal modelling approach. An online questionnaire was administrated. We collected 360 valid responses. Results The statistically significant drivers of behavioral intention are performance expectancy (beta=.200; t=3.619), effort expectancy (beta=.185; t=2.907), habit (beta=.388; t=7.320), and self-perception (beta=.098; t=2.285). The predictors of use behavior are habit (beta=0.206; t=2.752) and behavioral intention (beta=0.258; t=4.036). The model explained 49.7% of the variance in behavioral intention and 26.8% of the variance in use behavior. Conclusions Our research helps to understand the desired technology characteristics of EHR portals. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt EHR portals or not. The inclusion of specific constructs and relationships related to the health care consumer area also had a significant impact on understanding the adoption of EHR portals.
Location Prediction: Communities Speak Louder than Friends

Humans are social animals, they interact with different communities of friends to conduct different activities. The literature shows that human mobility is constrained by their social relations. In this paper, we investigate the social impact of a person's communities on his mobility, instead of all friends from his online social networks. This study can be particularly useful, as certain social behaviors are influenced by specific communities but not all friends. To achieve our goal, we first develop a measure to characterize a person's social diversity, which we term `community entropy'. Through analysis of two real-life datasets, we demonstrate that a person's mobility is influenced only by a small fraction of his communities and the influence depends on the social contexts of the communities. We then exploit machine learning techniques to predict users' future movement based on their communities' information. Extensive experiments demonstrate the prediction's effectiveness.
Extensions to the Visual Odometry Pipeline for the Exploration of Planetary Surfaces

Extensions to the Visual Odometry Pipeline for the Exploration of Planetary Surfaces Paul Timothy Furgale Doctor of Philosophy Graduate Department of Aerospace Science and Engineering University of Toronto 2011 Mars represents one of the most important targets for space exploration in the next 10 to 30 years, particularly because of evidence of liquid water in the planet’s past. Current environmental conditions dictate that any existing water reserves will be in the form of ice; finding and sampling these ice deposits would further the study of the planet’s climate history, further the search for evidence of life, and facilitate in-situ resource utilization during future manned exploration missions. This thesis presents a suite of algorithms to help enable a robotic ice-prospecting mission to Mars. Starting from visual odometry—the estimation of a rover’s motion using a stereo camera as the primary sensor—we develop the following extensions: (i) a coupled surface/subsurface modelling system that provides novel data products to scientists working remotely, (ii) an autonomous retrotraverse system that allows a rover to return to previously visited places along a route for sampling, or to return a sample to an ascent vehicle, and (iii) the extension of the appearance-based visual odometry pipeline to an actively illuminated light detection and ranging sensor that provides data similar to a stereo camera but is not reliant on consistent ambient lighting, thereby enabling appearance-based vision techniques to be used in environments that are not conducive to passive cameras, such as underground mines or permanently shadowed craters on the moon. All algorithms are evaluated on real data collected using our field robot at the University of Toronto Institute for Aerospace Studies, or at a planetary analogue site on Devon Island, in the Canadian High Arctic.
Medical Imaging in a Cloud Computing Environment

In this paper we present a cloud computing environment for medical imaging which deals with the issues of scaling a traditionally single-user solution to a software-as-a-service solution. We will first introduce volume rendering for medical imaging, and the issues with volume rendering of medical images on the cloud. We will then describe our method for accelerating CPU based volume rendering on the cloud and for scaling the system to a software-as-a-service solution.
Effective device electrical parameter extraction of nanoscale FinFETs: Challenges and results

The accurate evaluation of electrical parameters like effective channel length and series resistance for 10 to 22nm FinFETs is very complex, although extremely important for the correct device modelling. Our paper reviews and applies to measured FinFETs various DC methods for the extraction of effective channel length and source/drain resistance. Experimental devices with fin thickness from 10nm to 20nm were measured and the extraction methodologies explored show consistent values of RSD in the range of 500Ω to 300Ω respectively, for five parallel fins. All methods herein discussed and applied, however, have limitations in their application to FinFET devices. Our work discusses the challenges and possible options for the Leff extraction on advanced FinFET technologies.
Correlates of Dementia and Mild Cognitive Impairment in Patients With Atrial Fibrillation: The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC‐NCS)

Background Atrial fibrillation (AF) has been associated with faster cognitive decline and increased dementia risk. Factors associated with dementia in patients with AF have been seldom studied. Methods and Results We studied 6432 individuals from the ARIC‐NCS (Atherosclerosis Risk in Communities Neurocognitive Study). In 2011 to 2013, participants underwent a physical exam, echocardiography, detailed cognitive assessments, and a subset, brain magnetic resonance imaging. Dementia and mild cognitive impairment (MCI), as well as etiology of MCI/dementia, Alzheimer's disease–related or vascular, were adjudicated by an expert panel. AF was defined by study ECGs and past hospitalizations. We used logistic regression to estimate odds ratios and 95% CI of MCI/dementia by AF status and to assess cross‐sectional correlates of MCI/dementia in patients with AF. Among 6432 participants, 611 (9.5%) had prevalent AF. AF was associated with increased odds of dementia and MCI (odds ratio, 95% CI, 2.25, 1.64–3.10, and 1.28, 1.04–1.56, respectively). Prevalence of Alzheimer's disease–related MCI/dementia and vascular MCI/dementia were higher in participants with AF than without AF (odds ratio, 95% CI, 1.29, 1.04–1.61, and 1.50, 0.99–2.25, respectively). In multivariable analyses, older age, lower body mass index, diabetes mellitus, stroke, and APOE genotype were associated with dementia prevalence in participants with AF. In models evaluating MCI/dementia subtypes, diabetes mellitus was associated with Alzheimer's disease–related MCI/dementia, whereas male sex and stroke were risk factors for vascular MCI/dementia. Conclusions In a large, community‐based study, AF was associated with higher prevalence of MCI and dementia. Controlling cardiometabolic risk factors is a potential target for prevention of adverse cognitive outcomes in AF patients.
IAF-00-B . 6 . 01 OBJECT-BASED REPRESENTATIONS OF SPATIAL IMAGES

Object based representations of image data enable new contentrelated functionalities while facilitating management of large image databases. Developing such representations for multidate and multi-spectral images is one of the objectives of the second phase of the Alexandria Digital Library (ADL) project at UCSB. Image segmentation and image registration are two of the main issues that are to be addressed in creating localized image representations. We present in this paper some of the recent and current work by the ADL’s image processing group on robust image segmentation, registration, and the use of image texture for content representation. Built upon these technologies are techniques for managing large repositories of data. A texture thesaurus assists in creating a semantic classification of image regions. An object-based representation is proposed to facilitate data storage, retrieval, analysis, and navigation.
MATHEMATICAL ENGINEERING TECHNICAL REPORTS Feedback Control through Networks with Packet Loss: Mixed H2/H∞ Approach and Application to a Teleoperating System

We consider a networked control system that utilizes unreliable channels where packets may be lost. Assuming that such losses can be modeled as stochastic processes, we propose a mixed H2/H∞ control approach for controller synthesis. The designed controller exploits the information regarding the losses and is hence called mode dependant. The approach is applied to a bilateral teleoperating system. In the numerical results, the proposed control shows desired performance in the achievable norms and time responses.
Birds see the true colours of fruits to live off the fat of the land

Communication is a characteristic of life, but its reliability and basic definition are hotly debated. Theory predicts that trade among mutualists requires high reliability. Here, we show that moderate reliability already allows mutualists to optimize their rewards. The colours of Mediterranean fleshy-fruits indicate lipid rewards (but not other nutrients) to avian seed dispersers on regional and local scales. On the regional scale, fruits with high lipid content were significantly darker and less chromatic than congeners with lower lipid content. On the local scale, two warbler species (Sylvia atricapilla and Sylvia borin) selected fruit colours that were less chromatic, and thereby maximized their intake of lipids—a critical resource during migration and wintering. Crucially, birds were able to maximize lipid rewards with moderate reliability from visual fruit colours (r2 = 0.44–0.60). We suggest that mutualisms require only that any association between the quality and sensory aspects of signallers is learned through multiple, repeated interactions. Because these conditions are often fulfilled, also in social communication systems, we contend that selection on reliability is less intense than hitherto assumed. This may contribute to explaining the extraordinary diversity of signals, including that of plant reproductive displays.
Imaging of human differentiated 3D neural aggregates using light sheet fluorescence microscopy

The development of three dimensional (3D) cell cultures represents a big step for the better understanding of cell behavior and disease in a more natural like environment, providing not only single but multiple cell type interactions in a complex 3D matrix, highly resembling physiological conditions. Light sheet fluorescence microscopy (LSFM) is becoming an excellent tool for fast imaging of such 3D biological structures. We demonstrate the potential of this technique for the imaging of human differentiated 3D neural aggregates in fixed and live samples, namely calcium imaging and cell death processes, showing the power of imaging modality compared with traditional microscopy. The combination of light sheet microscopy and 3D neural cultures will open the door to more challenging experiments involving drug testing at large scale as well as a better understanding of relevant biological processes in a more realistic environment.
Purposeful Mobility in Tactical Sensor Networks

Adding mobility to sensor networks can significantly increase the capability of the sensor network by making it resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors. Mobility in sensor networks may be controllable, and hence be used to help achieve the network’s missions. That is, mobility may be “purposeful” instead of being treated as an uncontrollable external stimulus to which the ad-hoc networks must respond. To make use of the purposeful mobility, we propose techniques for mobility assisted sensing and routing considering the computation complexity, network connectivity, energy consumption of both communications and movement, and the network lifetime. We also define utility functions that can capture the benefits of the movement from the perspective of all missions, and maximize the capability of the network.
Knowledge Base Completion using Compositional Vector Space Models

Traditional approaches to knowledge base completion have been based on symbolic representations. Low-dimensional vector embedding models proposed recently for this task are attractive since they generalize to possibly unlimited sets of relations. A significant drawback of previous embedding models for KB completion is that they merely support reasoning on individual relations (e.g., bornIn(X,Y ) ⇒ nationality(X,Y )). In this work, we develop models for KB completion that support chains of reasoning on paths of any length using compositional vector space models. We construct compositional vector representations for the paths in the KB graph from the semantic vector representations of the binary relations in that path and perform inference directly in the vector space. Unlike previous methods, our approach can generalize to paths that are unseen in training and, in a zero-shot setting, predict target relations without supervised training data for that relation.
Structure of LacY with an α-substituted galactoside: Connecting the binding site to the protonation site

Significance Substituted d-galactopyranosides, particularly those in the α configuration and/or with hydrophobic constituents at the anomeric position, bind to LacY with higher affinity than the physiological substrate lactose that has a β configuration. The structure of a conformationally restricted LacY mutant with bound p-nitrophenyl-α-d-galactopyranoside (α-NPG), a high-affinity lactose analog, is described. Higher affinity, gained by nonspecific hydrophobic interaction of the nitrophenyl group, shows identical interaction at the key galactosyl moiety as in thio-digalactoside and so validates the highly specific, oriented set of hydrogen bonds with the key galactosyl moiety of substrates. Confirmation of galactose-specific binding interactions delineates a directional hydrogen-bonding network that couples the binding site to sites that are sensitive to protonation in the mechanism. The X-ray crystal structure of a conformationally constrained mutant of the Escherichia coli lactose permease (the LacY double-Trp mutant Gly-46→Trp/Gly-262→Trp) with bound p-nitrophenyl-α-d-galactopyranoside (α-NPG), a high-affinity lactose analog, is described. With the exception of Glu-126 (helix IV), side chains Trp-151 (helix V), Glu-269 (helix VIII), Arg-144 (helix V), His-322 (helix X), and Asn-272 (helix VIII) interact directly with the galactopyranosyl ring of α-NPG to provide specificity, as indicated by biochemical studies and shown directly by X-ray crystallography. In contrast, Phe-20, Met-23, and Phe-27 (helix I) are within van der Waals distance of the benzyl moiety of the analog and thereby increase binding affinity nonspecifically. Thus, the specificity of LacY for sugar is determined solely by side-chain interactions with the galactopyranosyl ring, whereas affinity is increased by nonspecific hydrophobic interactions with the anomeric substituent.
Air-Interface Slice Based Dynamic Resource Reservation for Ultra-Low-Latency IoT Transmissions

The ultra-low latency transmission for emergency services needs an effective resources management scheme to deliver content in few milliseconds. The traditional solutions can't guarantee the ultra-low latency performance required by such traffic. In this paper, we propose an air-interface slice based dynamic resource reservation schema for a massive number of sensors with emergency flows in the context of the next generation cellular networks. The proposed schema allows ultra-low latency flows to be transported by guaranteed-rate radio link connection with a content name as identifier and it achieves air-interface latency in few milliseconds. The dynamic bit-map update, silence probability and window-based re-transmission are introduced based on the Frame Slotted Aloha, which can schedules the delay-sensitive flows immediately from one or many groups of connected terminals. Furthermore, a probability theory based analytic model is provided and evaluated with Monte-Carlo simulation results.
Implementation and evaluation of deep neural networks (DNN) on mainstream heterogeneous systems

Deep Neural Networks (DNN), with deep layers and very high dimension of parameters, have demonstrated break-through learning capability in machine learning area. These days DNN with Big Data input are leading a new direction in large scale object recognition. DNN training requires vast amount of computing power, which poses great challenge to system design. DNN training embraces massive thread and data parallelism, which matches naturally with GPU. There are various heterogeneous systems including discrete CPU armed with GPUs and chip level integrated CPU+GPU heterogeneous processors-named APUs. In this paper, we explore the implementation of DNN models on different heterogenous platforms to provide systematic evaluation and comparison. Specifically we implement two well-known DNN kernels Multi-Layer Perceptron (MLP) and Autoencoder on various GPUs and APUs from mainstream processor manufacturers. Evaluations results show GPUs are faster than APUs but at the cost of burning much more power. APUs achieve upto 2x higher performance per watt efficiency, which indicates that APU server can be an energy efficient and high density solution to accelerate DNN applications. This paper also conducts bottleneck analysis and presents the optimized techniques on various platforms.
The effect of IVX‐0142, a heparin‐derived hypersulfated disaccharide, on the allergic airway responses in asthma

Background: IVX‐0142 is a heparin‐derived hypersulfated disaccharide devoid of anticoagulant activity while possessing anti‐allergic and anti‐inflammatory activity in preclinical studies. In a proof‐of‐concept study, the allergen inhalation challenge model was used to investigate the effect of IVX‐0142 in mild atopic asthma.
Design and Evaluation of a Lactobacillus manihotivorans Species-Specific rRNA-Targeted Hybridization Probe and Its Application to the Study of Sour Cassava Fermentation

ABSTRACT Based on 16S rRNA sequence comparison, we have designed a 20-mer oligonucleotide that targets a region specific to the speciesLactobacillus manihotivorans recently isolated from sour cassava fermentation. The probe recognized the rRNA obtained from all the L. manihotivorans strains tested but did not recognize 56 strains of microorganisms from culture collections or directly isolated from sour cassava, including 29 species of lactic acid bacteria. This probe was then successfully used in quantitative RNA blots and demonstrated the importance of L. manihotivoransin the fermentation of sour cassava starch, which could represent up to 20% of total lactic acid bacteria.
Urban climate in Central European cities and global climate change

Jagiellonian University, Institute of Geography and Spatial Management, Gronostajowa St. 7, 30-387 Kraków, Poland Global Change Research Centre AS CR, Belidla St. 986/4a, 603 00 Brno, Czech Republic Department of Climatology and Landscape Ecology, University of Szeged, Egyetem u. 2. , 6720 Szeged, Hungary Institute of Meteorology and Water Management National Research Institute, Piotra Borowego St. 14, 30-215 Kraków, Poland 5 Zentralanstalt für Meteorologie und Geodynamik, Hohe Warte St. 38, 1190 Vienna, Austria Palacký University Olomouc, Krizkovskeho St. 511/8, 77147 Olomouc, Czech Republic Slovak Hydrometeorological Institute, Jeseniova St. 17, 83315 Bratislava, Slovakia E-mail: anita.bokwa@uj.edu. pl
Temporal variation in African American English: The Distinctive Use of Vowel Duration

Introduction: African American English (AAE) is a unique dialect of American English that differs systematically from the variety spoken by the White population. Acoustic-phonetic explorations of segmental structure of AAE including vowel and consonant productions are still rare and the current state and developmental direction of AAE in the United States relative to dialects of White American English (WAE) are largely undetermined. Particularly little is known about timing patterns in AAE such as segmental durations, speech rate and rhythm. Objective: The purpose of this study was to better understand temporal variation in AAE by analyzing vowel duration. Methods: The experiment was conducted in a historically well-established southern speech community of African Americans in Pitt County in North Carolina. Sixteen male speakers, eight AAE and eight WAE, read a randomized set of words containing 11 vowels followed by either a voiced stop /d/ or a voiceless stop /t/ for a total 896 tokens. Two measures were used, the absolute duration and the proportional duration (ratio). Results: Compared with WAE speakers, AAE speakers significantly prolonged vowels preceding voiced consonants but the shorter durations of vowels before voiceless consonants did not differ significantly from those of WAE speakers. The proportional measure further established that the temporal contrast between vowels preceding voiced versus voiceless consonants was significantly enhanced in AAE relative to WAE. Furthermore, the tense-lax vowel distinction was reduced in AAE relative to WAE in both voicing contexts. Conclusions: These findings indicate that both the extensive vowel lengthening before voiced stops and the smaller temporal contrast between tense and lax vowels are distinctive features of AAE, signaling a differential use of vowel duration in AAE. The vowel lengthening before voiced stops may serve as the most salient cue with respect to the voicing status of the word final consonant. It may enhance the temporal contrast between vowels, and this contrast may serve as the primary marker of the consonant voicing distinction even if the consonant itself is devoiced or deleted altogether.