Miracle-dz/UniFAR-FTUs huggingface dataset:
Common Blood Flow Changes across Visual Tasks: I. Increases in Subcortical Structures and Cerebellum but Not in Nonvisual Cortex

Nine positron emission tomography (PET) studies of human visual information processing were reanalyzed to determine the consistency across experiments of blood flow increases during active tasks relative to passive viewing of the same stimulus array. No consistent blood flow increases were found in cerebral cortex outside of the visual system, but increases were seen in the thalamus and cerebellum. Although most tasks involve increases in arousal, establishing an intention or behavioral goal, setting up control structures for sequencing task operations, detecting targets, etc., these operations do not produce blood flow increases, detectable with the present methods, in localized cortical regions that are common across tasks. Common subcortical regions, however, may be involved. A left cerebellar and a medial cerebellar focus reflected motor-related processes. Blood flow increases in these regions only occurred in experiments in which the subject made an overt response and were largest when the response was made in the active but not passive condition. These motor-related processes were more complex than simple motor execution, however, since increases were still present when the response was made in both the active and passive conditions. These cerebellar increases may reflect processes related to response selection.Blood flow increases in a right cerebellar region were not motor-related. Increases were not modulated by the presence or absence of motor responses during either the active or passive conditions, and increases were sensitive to within-experiment variables that held the motor response constant. Increases occurred in both language and nonlanguage tasks and appeared to involve a general nonmotor process, but the nature of that process was difficult to specify. A right thalamic focus was sensitive to variables related to focal attention, suggesting that this region was involved in attentional engagement. Right thalamic increases were also correlated over conditions with increases in the left and medial cerebellum, perhaps reflecting additional contributions from motor-related nuclei receiving cerebellar projections. Blood flow increases in a left thalamic focus were completely uncorrelated over conditions with increases in the right thalamus, indicating that it was involved in different functions. Both the left thalamus and right cerebellum yielded larger blood flow increases when subjects performed a complex rather than simple language task, possibly reflecting a language-related pathway. Blood flow increases in the left thalamus were also observed, however, during nonlanguage tasks.
Quality Assurance of FRP Retrofit Using Infrared Thermography

Fiber Reinforced Polymer (FRP) plates and wrapping are increasingly becoming very popular retrofit material. These FRP materials have the advantages of being corrosion resistant and having a high strength to weight ratio. The performance of the FRP retrofit is highly dependent on the quality of the bond between the plate or fabric and the surface of the member been retrofitted. The current installation procedures are mainly hand rolling the FRP fabric or plate. Ideally, the rolling should squeeze any air that may have been trapped in the epoxy bond layer. In practical applications, this approach lends itself to the potential of having varying bond thickness and even voids between the FRP and the surface of the structural element. Meanwhile Infrared (IR) imaging technology developments have allowed rapid evaluation of large areas to determine skin temperature variations. These temperature variations are influenced by the presence of anomalies in the bond between the FRP and the member to be retrofitted. In this paper, a case study of such evaluation is presented.
Rethinking learning analytics adoption through complexity leadership theory

Despite strong interest in learning analytics (LA), adoption at a large-scale organizational level continues to be problematic. This may in part be due to the lack of acknowledgement of existing conceptual LA models to operationalize how key adoption dimensions interact to inform the realities of the implementation process. This paper proposes the framing of LA adoption in complexity leadership theory (CLT) to study the overarching system dynamics. The framing is empirically validated in a study analysing interviews with senior staff in Australian universities (n=32). The results were coded for several adoption dimensions including leadership, governance, staff development, and culture. The coded data were then analysed with latent class analysis. The results identified two classes of universities that either i) followed an instrumental approach to adoption - typically top-down leadership, large scale project with high technology focus yet demonstrating limited staff uptake; or ii) were characterized as emergent innovators - bottom up, strong consultation process, but with subsequent challenges in communicating and scaling up innovations. The results suggest there is a need to broaden the focus of research in LA adoption models to move on from small-scale course/program levels to a more holistic and complex organizational level.
One and Two Locus Likelihoods Under Complex Demography

The coalescent is a random process that describes the genealogy relating a sample of individuals, and provides a probability model that can be used for likelihood-based inference on genetics data. For example, coalescent models may include recombination, natural selection, population size crashes and growth, and migrations, and thus can be used to learn the strength of these biological and demographic forces. Unfortunately, computing the likelihood of data remains a challenging problem in many of these coalescent models.In this dissertation, I develop new equations and algorithms for computing coalescent likelihoods at one or two loci, and apply them to inference problems in a composite likelihood framework. I begin by developing an algorithm for the one-locus case, computing the site frequency spectrum (the distribution of mutant allele counts) under complex demographic histories with population size changes (including exponential growth), population splits, population mergers, and admixture events. This method improves on the runtime and numerical stability of previous approaches, and can successfully infer demographic histories that would otherwise be too computationally challenging to consider. I then consider the two- locus case, and derive a formula for the likelihood at a pair of sites under a variable population size history; this formula scales to tens of individuals. In addition to this exact formula, I also develop a highly efficient importance sampler to compute the same likelihood. I apply these results to the problem of inferring recombination rates under variable population size.
The Impact of Frailty on Patient-Centered Outcomes Following Aortic Valve Replacement

Background Frailty confers risk for surgical morbidity and mortality. Whether patient-reported measures of health, well-being, or quality of life respond differently to surgery in non-frail and frail individuals is unknown. Methods Older adults with severe aortic stenosis presenting for surgery were assessed for frailty using Cardiovascular Health Study Criteria. Patient-reported measures of functional capacity (Duke Activity Status Index [DASI]), physical and mental health (Medical Outcomes Study Short Form-Physical and Mental Component Scales [SF-12 PCS and SF-12 MCS, respectively]), well-being (linear analogue self-assessment [LASA]), and quality of life (LASA) were administered before and 3 months after surgery. Results Of 103 participants (mean age of 80.6 years), 54 were frail. Frail participants had lower baseline DASI, SF-12 PCS, SF-12 MCS, physical well-being, and quality of life scores than non-frail participants. At follow-up, frail participants showed significant improvement in physical function, with DASI and SF-12 PCS scores improving by 50% and 14%, respectively. Non-frail subjects did not significantly improve in these measures. SF-12 MCS scores also improved to a greater extent in frail compared to non-frail participants (3.6 vs < 1 point). Furthermore, the frail participants improved to a greater extent than non-frail participants in physical well-being (21.6 vs 7.1 points) and quality of life measures (25.1 vs 8.7 points). Conclusions Frailty is prevalent in older adults with severe aortic stenosis and is associated with poor physical and mental function, physical well-being, and quality of life. In response to surgery, frail participants exhibited greater improvement in these patient-centered outcomes than non-frail peers.
Compositional Quality and Potential Gastrointestinal Behavior of Probiotic Products Commercialized in Italy

Recent guidelines indicate that oral probiotics, living microorganisms able to confer a health benefit on the host, should be safe for human consumption, when administered in a sufficient amount, and resist acid and bile to exert their beneficial effects (e.g., metabolic, immunomodulatory, anti-inflammatory, competitive). This study evaluated quantitative and qualitative aspects and the viability in simulated gastric and intestinal juices of commercial probiotic formulations available in Italy. Plate counting and MALDI-TOF mass spectrometry were used to enumerate and identify the contained organisms. In vitro studies with two artificial gastric juices and pancreatin–bile salt solution were performed to gain information on the gastric tolerance and bile resistance of the probiotic formulations. Most preparations satisfied the requirements for probiotics and no contaminants were found. Acid resistance and viability in bile were extremely variable depending on the composition of the formulations in terms of contained species and strains. In conclusion, this study indicates good microbiological quality but striking differences in the behavior in the presence of acids and bile for probiotic formulations marketed in Italy.
Effect of a Smartphone Application Incorporating Personalized Health-Related Imagery on Adherence to Antiretroviral Therapy : A Randomized Clinical Trial

Poor adherence to combination antiretroviral therapy (ART) is a major global challenge. In this study we examined the efficacy of a smartphone application incorporating personalized health-related visual imagery that provided real-time information about the level of medication and the patient’s level of immunoprotection, in order to improve adherence to ART. We randomized 28 people on ART to either a standard or augmented version of the smartphone application. The augmented version contained components that illustrated participants’ current estimated plasma concentrations of antiretroviral drugs and the immune protection provided by ART. Adherence to ART was assessed at baseline and at 3 months using self-reported adherence, pharmacy dispensing records, and HIV viral load. Information was also collected on illness and medication beliefs and use of the application. Participants who received the augmented application showed a significantly higher level of self-reported adherence to ART at three months ( p = 0.03) and decreased viral load ( p = 0.023) as compared to individuals using the standard version. Greater usage of the extra components of the augmented application was associated with greater perceived understanding of HIV infection and increased perceived necessity for ART. Smartphone applications that incorporate personalized health-related visual imagery may have potential to improve adherence to ART.
Spin-imbalance in a 2D Fermi-Hubbard system

Imaging a microscopic power struggle Strongly interacting fermions in a two-dimensional lattice form a checkerboard pattern, with spins of opposite directions occupying neighboring sites of the lattice. When an external magnetic field is applied, the situation becomes more complicated—should the spins align with the field, or try to preserve the checkerboard order? Brown et al. studied this problem using 6Li atoms in an optical lattice with unequal numbers of two spin components; the imbalance between the two played the role of an effective magnetic field. With the field applied, the checkerboard pattern correlations of the spin component perpendicular to the field became stronger than those of the spin component parallel to the field, indicating that the system was approaching the so-called canted antiferromagnetic state. Science, this issue p. 1385 The interplay of strong interactions and magnetic fields gives rise to unusual forms of superconductivity and magnetism in quantum many-body systems. Here, we present an experimental study of the two-dimensional Fermi-Hubbard model—a paradigm for strongly correlated fermions on a lattice—in the presence of a Zeeman field and varying doping. Using site-resolved measurements, we revealed anisotropic antiferromagnetic correlations, a precursor to long-range canted order. We observed nonmonotonic behavior of the local polarization with doping for strong interactions, which we attribute to the evolution from an antiferromagnetic insulator to a metallic phase. Our results pave the way to experimentally mapping the low-temperature phase diagram of the Fermi-Hubbard model as a function of both doping and spin polarization, for which many open questions remain.
Hyperspectral classification with adaptively weighted li-norm regularization

Sparse regression methods have been proven effective in a wide range of signal processing problems such as image compression, speech coding, channel equalization, linear regression and classification. In this paper we develop a new method of hyperspectral image classification based on the sparse unmixing algorithm SUnSAL for which a pixel adaptive L1-norm regularization term is introduced. Our algorithm manages to preserve the benefits of convexity in all experiments of interest (i.e. it does not get caught in unfavorable local minima for one or more classes at a time), while achieving comparable overall accuracies (OA's) and kappa coefficients of agreement as the non-convex state of the art algorithms KSOMP and KSSP.
Prey from the eyes of predators: Color discriminability of aposematic and mimetic butterflies from an avian visual perspective

Predation exerts strong selection on mimetic butterfly wing color patterns, which also serve other functions such as sexual selection. Therefore, specific selection pressures may affect the sexes and signal components differentially. We tested three predictions about the evolution of mimetic resemblance by comparing wing coloration of aposematic butterflies and their Batesian mimics: (a) females gain greater mimetic advantage than males and therefore are better mimics, (b) due to intersexual genetic correlations, sexually monomorphic mimics are better mimics than female‐limited mimics, and (c) mimetic resemblance is better on the dorsal wing surface that is visible to predators in flight. Using a physiological model of avian color vision, we quantified mimetic resemblance from predators’ perspective, which showed that female butterflies were better mimics than males. Mimetic resemblance in female‐limited mimics was comparable to that in sexually monomorphic mimics, suggesting that intersexual genetic correlations did not constrain adaptive response to selection for female‐limited mimicry. Mimetic resemblance on the ventral wing surface was better than that on the dorsal wing surface, implying stronger natural and sexual selection on ventral and dorsal surfaces, respectively. These results suggest that mimetic resemblance in butterfly mimicry rings has evolved under various selective pressures acting in a sex‐ and wing surface‐specific manner.
Frontline Science: Multiple cathepsins promote inflammasome‐independent, particle‐induced cell death during NLRP3‐dependent IL‐1β activation

Sterile particles cause several chronic, inflammatory diseases, characterized by repeating cycles of particle phagocytosis and inflammatory cell death. Recent studies have proposed that these processes are driven by the NLRP3 inflammasome, a platform activated by phagocytosed particles, which controls both caspase‐1–dependent cell death (pyroptosis) and mature IL‐1β secretion. After phagocytosis, particles can disrupt lysosomes, and inhibitor studies have suggested that the resulting release of a lysosomal protease—cathepsin B—into the cytosol somehow activates NLRP3. However, using primary murine macrophages, we found that particle‐induced cell death occurs independent of NLRP3/caspase‐1 and depends instead on multiple, redundant cathepsins. In contrast, nigericin, a soluble activator of NLRP3 inflammasomes, induced cell death that was dependent on the NLRP3. Interestingly, nigericin‐induced cell death depended partly on a single cathepsin, cathepsin X. By inhibiting or silencing multiple cathepsins in macrophages, several key proinflammatory events induced by sterile particles are blocked, including cell death, pro–IL‐1β production, and IL‐1β secretion. These data suggest that cathepsins might be potential therapeutic targets in particulate‐mediated inflammatory disease. In support of this concept, we find that a broad‐spectrum cathepsin inhibitor can suppress particle‐induced IL‐1–dependent peritonitis.
Static stress triggering explains the empirical aftershock distance decay

The shape of the spatial aftershock decay is sensitive to the triggering mechanism and thus particularly useful for discriminating between static and dynamic stress triggering. For California seismicity, it has been recently recognized that its form is more complicated than typically assumed consisting of three different regimes with transitions at the scale of the rupture length and the thickness of the crust. The intermediate distance range is characterized by a relative small decay exponent of 1.35 previously declared to relate to dynamic stress triggering. We perform comprehensive simulations of a simple clock‐advance model, in which the number of aftershocks is just proportional to the Coulomb‐stress change, to test whether the empirical result can be explained by static stress triggering. Similarly to the observations, the results show three scaling regimes. For simulations adapted to the depths and focal mechanisms observed in California, we find a remarkable agreement with the observation over the whole distance range for a fault distribution with fractal dimension of 1.8, which is shown to be in good agreement with an independent analysis of California seismicity.
An improved region-based model with local statistical feature

In this paper, a new region-based active contour model is proposed for image segmentation. Different from the general region-based active contour models, this model partitions the regions of interests in images depending on the local statistics of the intensity and the magnitude of gradient in the neighborhood of the contour. Inspired by the structure tensor method, an improved regularization term is defined through the duality formulation to penalize the length of region boundaries. Experiments on medical images demonstrate the proposed model outperforms the classical segmentation models in terms of efficiency and accuracy.
Exploiting IMU Sensors for IOT Enabled Health Monitoring

Inertial Measurement Units (IMUs) embedded in commercial mobile devices are a good choice for continuous monitoring in healthcare domain due to their attractive form factor and low power consumption. We present improved and accurate sensing algorithms using a single IMU to sense basic events like step count, stride length, fall, immobility etc. Our algorithms have been shown to perform better than the state of the art algorithms, and are implemented in such a way that IMU is not bound to any specific position or orientation with respect to the user. We propose a 3-layer based framework for a complete end-to-end system architecture for IoT enabled health monitoring, useful for application in areas like individual fitness monitoring and elderly care.
Complex Field Fault Modeling-Based Optimal Frequency Selection in Linear Analog Circuit Fault Diagnosis

Owing to the lack of feasible fault modeling method, hard (open and short) faults, and discretized parametric faults are still the mostly used fault models. These models cannot characterize all soft (parameter shifting) faults because that the parameter of analog element be of continuity character. To address this concern, a complex field fault modeling method is presented first. If fault happens to passive element xi in linear analog circuit, the real (Ur) and imaginary (Uj) parts of faulty voltage phasor U°(U°=Ur+j Uj) must satisfy binary quadratic function Fi(Ur,Uj)=0, which is independent from the value of element xi and uniquely determined by its location and the nominal circuit under test. Hence, the binary quadratic function can model any continuous parameter shifting (soft) or hard fault. Second, to avoid calculating the explicit expression of binary quadratic function, a simulation-based method is given to obtain the locus of the change in the function Fz in the complex plane. Besides, the nominal (fault-free) point, the loci determined by the binary quadratic functions might intersect with each other. It is referred to as aliasing problem in this paper. This problem can be solved by adjusting the frequency of the input signal. Therefore, a constraint optimization method is proposed to select optimal test frequencies. The proposed test generation and compression methods, when combined with the complex field modeling method, can pinpoint much more fault components with less test points and frequencies when compared with the other methods.
Design and Fabrication of a Miniaturized GMI Magnetic Sensor Based on Amorphous Wire by MEMS Technology

A miniaturized Co-based amorphous wire GMI (Giant magneto-impedance) magnetic sensor was designed and fabricated in this paper. The Co-based amorphous wire was used as the sense element due to its high sensitivity to the magnetic field. A three-dimensional micro coil surrounding the Co-based amorphous wire was fabricated by MEMS (Micro-Electro-Mechanical System) technology, which was used to extract the electrical signal. The three-dimensional micro pick-up coil was designed and simulated with HFSS (High Frequency Structure Simulator) software to determine the key parameters. Surface micro machining MEMS (Micro-Electro-Mechanical System) technology was employed to fabricate the three-dimensional coil. The size of the developed amorphous wire magnetic sensor is 5.6 × 1.5 × 1.1 mm3. Helmholtz coil was used to characterize the performance of the device. The test results of the sensor sample show that the voltage change is 130 mV/Oe and the linearity error is 4.83% in the range of 0~45,000 nT. The results indicate that the developed miniaturized magnetic sensor has high sensitivity. By testing the electrical resistance of the samples, the results also showed high uniformity of each device.