Miracle-dz/UniFAR-FTUs huggingface dataset:
Restricted q-Isometry Properties Adapted to Frames for Nonconvex lq-Analysis

This paper discusses reconstruction of signals from few measurements in the situation that signals are sparse or approximately sparse in terms of a general frame via the $l_q$-analysis optimization with $0<q\leq 1$. We first introduce a notion of restricted $q$-isometry property ($q$-RIP) adapted to a dictionary, which is a natural extension of the standard $q$-RIP, and establish a generalized $q$-RIP condition for approximate reconstruction of signals via the $l_q$-analysis optimization. We then determine how many random, Gaussian measurements are needed for the condition to hold with high probability. The resulting sufficient condition is met by fewer measurements for smaller $q$ than when $q=1$. The introduced generalized $q$-RIP is also useful in compressed data separation. In compressed data separation, one considers the problem of reconstruction of signals' distinct subcomponents, which are (approximately) sparse in morphologically different dictionaries, from few measurements. With the notion of generalized $q$-RIP, we show that under an usual assumption that the dictionaries satisfy a mutual coherence condition, the $l_q$ split analysis with $0<q\leq1 $ can approximately reconstruct the distinct components from fewer random Gaussian measurements with small $q$ than when $q=1$
Elastin-like-recombinamers multilayered nanofibrous scaffolds for cardiovascular applications

Coronary angioplasty is the most widely used technique for removing atherosclerotic plaques in blood vessels. The regeneration of the damaged intima layer after this treatment is still one of the major challenges in the field of cardiovascular tissue engineering. Different polymers have been used in scaffold manufacturing in order to improve tissue regeneration. Elastin-mimetic polymers are a new class of molecules that have been synthesized and used to obtain small diameter fibers with specific morphological characteristics. Elastin-like polymers produced by recombinant techniques and called elastin-like recombinamers (ELRs) are particularly promising due to their high degree of functionalization. Generally speaking, ELRs can show more complex molecular designs and a tighter control of their sequence than other chemically synthetized polymers Rodriguez Cabello et al (2009 Polymer 50 5159–69, 2011 Nanomedicine 6 111–22). For the fabrication of small diameter fibers, different ELRs were dissolved in 2,2,2-fluoroethanol (TFE). Dynamic light scattering was used to identify the transition temperature and get a deep characterization of the transition behavior of the recombinamers. In this work, we describe the use of electrospinning technique for the manufacturing of an elastic fibrous scaffold; the obtained fibers were characterized and their cytocompatibility was tested in vitro. A thorough study of the influence of voltage, flow rate and distance was carried out in order to determine the appropriate parameters to obtain fibrous mats without beads and defects. Moreover, using a rotating mandrel, we fabricated a tubular scaffold in which ELRs containing different cell adhesion sequences (mainly REDV and RGD) were collected. The stability of the scaffold was improved by using genipin as a crosslinking agent. Genipin-ELRs crosslinked scaffolds show a good stability and fiber morphology. Human umbilical vein endothelial cells were used to assess the in vitro bioactivity of the cell adhesion domains within the backbone of the ELRs.
Three-dimensional bioprinting and tissue fabrication: prospects for drug discovery and regenerative medicine

Bioprinting technology has emerged as a powerful tool for building tissue and organ structures for drug discovery and regenerative medicine applications. In general, bioprint- ing uses a computer-controlled three-dimensional (3D) printing device to accurately deposit cells and biomaterials into precise geometries with the goal of creating anatomically correct biological structures. While traditional 3D printing uses metals, plastics, and polymers as printing materials or "ink", bioprinting deals with living cells and biological matrix. Hence, there are significant challenges to make a transition from traditional 3D printing to bioprint - ing, and ultimately achieve functional outcomes in bioprinted tissues. Therefore, it is critical that there is new technology development and in-depth basic research in bioprinted tissues, such as developing novel biomaterials specifically for use in bioprinting and biofabrication techniques, understanding the cell-matrix remodeling for the desired mechanical properties, and functional outcomes, establishing proper vascular perfusion, etc. Currently, there is active research going on bioprinting technology and its potential as a future source for tissue implants. This review paper overviews the current state of the art in bioprinting technology and focuses on the outcomes of the bioprinted tissues and their potential applications in drug discovery and regenerative medicine. Current challenges and limitations are highlighted, and future directions for next-generation bioprinting technology are also presented.
Interactive Visualization for Topic Model Curation

Understanding the content of a large text corpus can be assisted by topic modeling methods, but the discovered topics often do not make clear sense to human analysts. Interactive topic modeling addresses such problems by allowing a human to steer the topic model curation process (generate, interpret, diagnose, and refine). However, human have limited ability to work with the artifacts of computational topic models since they are difficult to interpret and harvest. This paper explores the nature of such challenges and provides a visual analytic solution in the context of supporting political scientists to understand the thematic content of online petition data. We use interactive topic modeling of the White House online petition data as a lens to bring up key points of discussions and to highlight the unsolved problems as well as potentials utilities of visual analytics methods. ACM Classification
Optimal Hyper-Parameter Tuning of SVM Classifiers With Application to Medical Diagnosis

Proper tuning of hyper-parameters is essential to the successful application of SVM-classifiers. Several methods have been used for this problem: grid search, random search, estimation of distribution Algorithms (EDAs), bio-inspired metaheuristics, among others. The objective of this paper is to determine the optimal method among those that recently reported good results: Bat algorithm, Firefly algorithm, Fruit-fly optimization algorithm, particle Swarm optimization, Univariate Marginal Distribution Algorithm (UMDA), and Boltzmann-UMDA. The criteria for optimality include measures of effectiveness, generalization, efficiency, and complexity. Experimental results on 15 medical diagnosis problems reveal that EDAs are the optimal strategy under such criteria. Finally, a novel performance index to guide the optimization process, that improves the generalization of the solutions while maintaining their effectiveness, is presented.
[Factors Influencing Post Traumatic Stress Disorder in Crime Scene Investigators].

PURPOSE The purpose of this study was to verify the relationships among social support, resilience and post traumatic stress disorder (PTSD), and especially to identify factors influencing PTSD in police crime scene investigators. METHODS A cross-sectional design was used, with a convenience sample of 226 police crime scene investigators from 7 Metropolitan Police Agencies. Data were collected through self-report questionnaires during July and August, 2015. Data were analyzed using t-test, χ²-test, Fisher's exact test, and binary logistic regression analysis with SPSS/WIN 21.0 program. RESULTS The mean score for PTSD in police crime scene investigators was 13.69. 11 points. Of the crime scene investigators 181 (80.1%) were in the low-risk group and 45 (19.9%) in high-risk group. Social support (t=5.68, p<.001) and resilience (t=5.47, p<.001) were higher in the low-risk group compared to the high-risk group. Logistic regression analysis showed that resilience (OR=4.74, 95% CI: 1.57~14.35), and social support (OR=2.13, 95% CI: 1.23~3.69) are effect factors for PTSD low group. CONCLUSION For effective improvement of PTSD in police crime scene investigators, intervention programs including social support and strategies to increase should be established.
A novel method to visualise the three‐dimensional organisation of the human cerebral cortical vasculature

Current tissue‐clearing protocols for imaging in three dimensions (3D) are typically applied to optimally fixed, small‐volume rodent brain tissue – which is not representative of the tissue found in diagnostic neuropathology laboratories. We present a method to visualise the cerebral cortical vasculature in 3D in human post‐mortem brain tissue which had been preserved in formalin for many years. Tissue blocks of cerebral cortex from two control cases, two Alzheimer's brains and two cases from Alzheimer's patients immunised against Aβ42 were stained with fluorescent Lycopersicon esculentum agglutinin (Tomato lectin), dehydrated and cleared using an adapted three‐dimensional imaging of solvent cleared organs (3DISCO) protocol to visualise the vascular endothelium. Tissue was imaged using light sheet and confocal microscopy and reconstructed in 3D using amira software. The method permits visualisation of the arrangement of the parallel penetrating cortical vasculature in the human brain. The presence of four vascular features including anastomosis, U‐shaped vessels, spiralling and loops were revealed. In summary, we present a low cost and simple method to visualise the human cerebral vasculature in 3D compatible with prolonged fixation times (years), allowing study of vascular involvement in a range of normative and pathological states.
Low-Cost Wireless Temperature Measurement: Design, Manufacture, and Testing of a PCB-Based Wireless Passive Temperature Sensor

Low-cost wireless temperature measurement has significant value in the food industry, logistics, agriculture, portable medical equipment, intelligent wireless health monitoring, and many areas in everyday life. A wireless passive temperature sensor based on PCB (Printed Circuit Board) materials is reported in this paper. The advantages of the sensor include simple mechanical structure, convenient processing, low-cost, and easiness in integration. The temperature-sensitive structure of the sensor is a dielectric-loaded resonant cavity, consisting of the PCB substrate. The sensitive structure also integrates a patch antenna for the transmission of temperature signals. The temperature sensing mechanism of the sensor is the dielectric constant of the PCB substrate changes with temperature, which causes the resonant frequency variation of the resonator. Then the temperature can be measured by detecting the changes in the sensor’s working frequency. The PCB-based wireless passive temperature sensor prototype is prepared through theoretical design, parameter analysis, software simulation, and experimental testing. The high- and low-temperature sensing performance of the sensor is tested, respectively. The resonant frequency decreases from 2.434 GHz to 2.379 GHz as the temperature increases from −40 °C to 125 °C. The fitting curve proves that the experimental data have good linearity. Three repetitive tests proved that the sensor possess well repeatability. The average sensitivity is 347.45 KHz/°C℃ from repetitive measurements conducted three times. This study demonstrates the feasibility of the PCB-based wireless passive sensor, which provides a low-cost temperature sensing solution for everyday life, modern agriculture, thriving intelligent health devices, and so on, and also enriches PCB product lines and applications.
A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing

Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis. The submodels were each trained with face or non-face object images, which resulted in separate representations of facial parts and object parts. Importantly, evoked neural activities were modeled by Bayesian inference, which had a top-down explaining-away effect that enabled recognition of an individual part to depend strongly on the category of the whole input. We show that this explaining-away effect was indeed crucial for the units in the face submodel to exhibit significant selectivity to face images over object images in a similar way to actual face-selective neurons in the macaque IT cortex. Furthermore, the model explained, qualitatively and quantitatively, several tuning properties to facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, and Livingstone (2009). These included, in particular, tuning to only a small number of facial features that were often related to geometrically large parts like face outline and hair, preference and anti-preference of extreme facial features (e.g., very large/small inter-eye distance), and reduction of the gain of feature tuning for partial face stimuli compared to whole face stimuli. Thus, we hypothesize that the coding principle of facial features in the middle patch of face processing in the macaque IT cortex may be closely related to mixture of sparse coding models.
Structural basis for coupling protein transport and N-glycosylation at the mammalian endoplasmic reticulum

A close-up view of oligosaccharyltransferase Many secretory and membrane proteins are modified through the attachment of sugar chains by N-glycosylation. Such modification is required for correct protein folding, targeting, and functionality. In mammalian cells, N-glycosylation is catalyzed by the oligosaccharyltransferase (OST) complex via its STT3 subunit. OST forms a complex with the ribosome and the Sec61 protein translocation channel. Braunger et al. combined cryo–electron microscopy approaches to visualize mammalian ribosome-Sec61-OST complexes in order to build an initial molecular model for mammalian OST. Science, this issue p. 215 Cryo–electron microscopy reveals how cotranslational protein transport and N-glycosylation are coupled in mammals. Protein synthesis, transport, and N-glycosylation are coupled at the mammalian endoplasmic reticulum by complex formation of a ribosome, the Sec61 protein-conducting channel, and oligosaccharyltransferase (OST). Here we used different cryo–electron microscopy approaches to determine structures of native and solubilized ribosome-Sec61-OST complexes. A molecular model for the catalytic OST subunit STT3A (staurosporine and temperature sensitive 3A) revealed how it is integrated into the OST and how STT3-paralog specificity for translocon-associated OST is achieved. The OST subunit DC2 was placed at the interface between Sec61 and STT3A, where it acts as a versatile module for recruitment of STT3A-containing OST to the ribosome-Sec61 complex. This detailed structural view on the molecular architecture of the cotranslational machinery for N-glycosylation provides the basis for a mechanistic understanding of glycoprotein biogenesis at the endoplasmic reticulum.
Precise performance analysis of the LASSO under matrix uncertainties

In this paper, we consider the problem of recovering an unknown sparse signal x0 G Rn from noisy linear measurements y = Hx0 +z G Rm. A popular approach is to solve the ¿4-norm regularized least squares problem which is known as the LASSO. In many practical situations, the measurement matrix H is not perfectely known and we only have a noisy version of it. We assume that the entries of the measurement matrix H and of the noise vector z are iid Gaussian with zero mean and variances 1 /n and σ2z. In this work, an imperfect measurement matrix is considered under which we precisely characterize the limilting behavior of the mean squared error and the probability of support recovery of the LASSO. The analysis is performed when the problem dimensions grow simultaneously to infinity at fixed rates. Numerical simulations validate the theoretical predictions derived in this paper.
Afadin controls p120‐catenin–ZO‐1 interactions leading to endothelial barrier enhancement by oxidized phospholipids

Afadin is a novel regulator of epithelial cell junctions assembly. However, its role in the formation of endothelial cell junctions and the regulation of vascular permeability remains obscure. We previously described protective effects of oxidized 1‐palmitoyl‐2‐arachidonoyl‐sn‐glycero‐3‐phosphorylcholine (OxPAPC) in the in vitro and in vivo models of lung endothelial barrier dysfunction and acute lung injury, which were mediated by Rac GTPase. This study examined a role of afadin in the OxPAPC‐induced enhancement of interactions between adherens junctions and tight junctions as a novel mechanism of endothelial cell (EC) barrier preservation. OxPAPC induced Rap1‐dependent afadin accumulation at the cell periphery and Rap1‐dependent afadin interaction with adherens junction and tight junction proteins p120‐catenin and ZO‐1, respectively. Afadin knockdown using siRNA or ectopic expression of afadin mutant lacking Rap1 GTPase binding domain suppressed OxPAPC‐induced EC barrier enhancement and abolished barrier protective effects of OxPAPC against thrombin‐induced EC permeability. Afadin knockdown also abolished protective effects of OxPAPC against ventilator‐induced lung injury in vivo. These results demonstrate for the first time a critical role of afadin in the regulation of vascular barrier function in vitro and in vivo via coordination of adherens junction–tight junction interactions. J. Cell. Physiol. 227: 1883–1890, 2012. © 2011 Wiley Periodicals, Inc.
Evaluating the psychometric properties of the Jacelon Attributed Dignity Scale.

AIM To develop and psychometrically test the Jacelon Attributed Dignity Scale (JADS). BACKGROUND The JADS was designed to measure self-perceived attributed dignity in community-dwelling older adults. Attributed dignity was conceived of as a state characteristic of the self. The JADS is a short, positively scored, norm-referenced, evaluation index designed to measure self-perceived attributed dignity during the last week. DESIGN Instrument development and testing including psychometric properties, internal consistency, factor structure, temporal stability and construct validity. METHOD Using a quota sample, 289 older adults (65-99 years old) were recruited from senior centres in western New England to complete the JADS, demographic information, the Self-Esteem Scale and the Social Desirability Scale during 2010-2011. Descriptive statistics, exploratory factor analysis, construct validity and temporal stability were evaluated. RESULTS The resulting positively scored 18-item scale has four factors with high internal consistency for each factor and the entire scale. Construct validity was established by examining correlations with instruments that measured self-esteem and social desirability. Attributed dignity is a unique concept that is stable over time. CONCLUSION The JADS is an 18-item Likert-scaled instrument designed to measure attributed dignity. Attributed dignity is a concept with four factors and is defined as a cognitive component of the self-connoting self-value, perceived value from others, self in relation to others and behaving with respect. The importance of attributed dignity for older adults in relation to health, function, independence, quality of life and successful ageing can now be evaluated.
Double integrator consensus in fixed time: A novel distributed algorithm for generalised networks

A novel fixed-time consensus algorithm is presented for a multi-agent system comprising of double-integrator based agents. The proposed consensus algorithm ensures that agents' states converge to that of a maneuvering target in fixed-time. Each state of the agents (position, velocity, and acceleration) is exchanged over separate communication network which are assumed to be undirected. It is assumed that there exist one agent receiving target's information (position, velocity, and acceleration). It is not necessary that agent having target's position be the same which gets target's velocity and/or acceleration. However, the target cannot access the information of the agents. Lyapunov stability theory is used to establish the global stability of the proposed algorithm. Fixed time convergence of the proposed algorithm is established by using the concept of bi-limit homogeneity of a vector field. We also show that the proposed fixed-time algorithm can be extended directly to design a multi-agent formation control law. Effectiveness of the proposed consensus algorithm is presented by numerical results.
Neuroimage: Clinical Sex Differences in the Interacting Roles of Impulsivity and Positive Alcohol Expectancy in Problem Drinking: a Structural Brain Imaging Study a R T I C L E I N F O

Keywords: Cerebral morphometry VBM Thalamus Insula Gender difference Disinhibition Alcohol expectancy Social drinking A B S T R A C T Alcohol expectancy and impulsivity are implicated in alcohol misuse. However, how these two risk factors interact to determine problem drinking and whether men and women differ in these risk processes remain unclear. In 158 social drinkers (86 women) assessed for Alcohol Use Disorder Identification Test (AUDIT), positive alcohol expectancy, and Barratt impulsivity, we examined sex differences in these risk processes. Further, with structural brain imaging, we examined the neural bases underlying the relationship between these risk factors and problem drinking. The results of general linear modeling showed that alcohol expectancy best predicted problem drinking in women, whereas in men as well as in the combined group alcohol expectancy and impulsivity interacted to best predict problem drinking. Alcohol expectancy was associated with decreased gray matter volume (GMV) of the right posterior insula in women and the interaction of alcohol expectancy and impulsivity was associated with decreased GMV of the left thalamus in women and men combined and in men alone, albeit less significantly. These risk factors mediated the correlation between GMV and problem drinking. Conversely, models where GMV resulted from problem drinking were not supported. These new findings reveal distinct psychological factors that dispose men and women to problem drinking. Although mediation analyses did not determine a causal link, GMV reduction in the insula and thalamus may represent neural phenotype of these risk processes rather than the consequence of alcohol consumption in non-dependent social drinkers. The results add to the alcohol imaging literature which has largely focused on dependent individuals and help elucidate alterations in brain structures that may contribute to the transition from social to habitual drinking.