Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image

We present Deep Shape-from-Template (DeepSfT), a novel Deep Neural Network (DNN) method for solving real-time automatic registration and 3D reconstruction of a deformable object viewed in a single monocular image.DeepSfT advances the state-of-the-art in various aspects. Compared to existing DNN SfT methods, it is the first fully convolutional real-time approach that handles an arbitrary object geometry, topology and surface representation. It also does not require ground truth registration with real data and scales well to very complex object models with large numbers of elements. Compared to previous non-DNN SfT methods, it does not involve numerical optimization at run-time, and is a dense, wide-baseline solution that does not demand, and does not suffer from, feature-based matching. It is able to process a single image with significant deformation and viewpoint changes, and handles well the core challenges of occlusions, weak texture and blur. DeepSfT is based on residual encoder-decoder structures and refining blocks. It is trained end-to-end with a novel combination of supervised learning from simulated renderings of the object model and semi-supervised automatic fine-tuning using real data captured with a standard RGB-D camera. The cameras used for fine-tuning and run-time can be different, making DeepSfT practical for real-world use. We show that DeepSfT significantly outperforms state-of-the-art wide-baseline approaches for non-trivial templates, with quantitative and qualitative evaluation.
Systematic Review of Physical Activity Interventions in Hispanic Adults

Introduction: Physical activity (PA) has demonstrated substantial physical and psychological benefits. However, Hispanics engage in less leisure-time PA when compared with other groups, putting them at higher risk for diseases associated with obesity, such as diabetes mellitus type 2. This literature review was conducted to identify best practices with regard to interventions designed to increase PA among Hispanic adults. Methods: Extensive searching located 21 randomized controlled studies conducted in the United States. Results: Common conceptual frameworks were the transtheoretical model and social cognitive theory. Most interventions used educational sessions with a variety of topics and many used promotoras to increase PA. Outcomes were predominantly examined using self-report PA measures. Walking was the most commonly reported PA behavior. Studies with significant results were those that measured moderate-to-vigorous PA and used theory to guide interventions. Male and older participants were underrepresented. Conclusions: Effective culturally appropriate PA interventions for Hispanics adults are needed. Particular attention to intervention tailoring based on country of origin could enhance intervention effectiveness.
Similarity-preserving Image-image Domain Adaptation for Person Re-identification

This article studies the domain adaptation problem in person re-identification (re-ID) under a "learning via translation" framework, consisting of two components, 1) translating the labeled images from the source to the target domain in an unsupervised manner, 2) learning a re-ID model using the translated images. The objective is to preserve the underlying human identity information after image translation, so that translated images with labels are effective for feature learning on the target domain. To this end, we propose a similarity preserving generative adversarial network (SPGAN) and its end-to-end trainable version, eSPGAN. Both aiming at similarity preserving, SPGAN enforces this property by heuristic constraints, while eSPGAN does so by optimally facilitating the re-ID model learning. More specifically, SPGAN separately undertakes the two components in the "learning via translation" framework. It first preserves two types of unsupervised similarity, namely, self-similarity of an image before and after translation, and domain-dissimilarity of a translated source image and a target image. It then learns a re-ID model using existing networks. In comparison, eSPGAN seamlessly integrates image translation and re-ID model learning. During the end-to-end training of eSPGAN, re-ID learning guides image translation to preserve the underlying identity information of an image. Meanwhile, image translation improves re-ID learning by providing identity-preserving training samples of the target domain style. In the experiment, we show that identities of the fake images generated by SPGAN and eSPGAN are well preserved. Based on this, we report the new state-of-the-art domain adaptation results on two large-scale person re-ID datasets.
Religious beliefs and climate change adaptation: A study of three rural South African communities

This article argues that religious beliefs significantly influence a community’s understanding and experience of climate change adaptation, indicating the need for an inclusion of such information in climate change adaptation education. Data were collected using the Q-method, whereby recurring statements were identified from semi-structured interviews with participants from three rural communities in the North-West province of South Africa: Ikageng, Ventersdorp and Jouberton. The research found that community members who regard themselves as religious (overall of the Christian faith) fall under two groups: the religious determinists or fatalists, who see climate as a natural process that is governed by God, and religious participants who deny this ‘naturalness’ and acknowledge humans’ impact on the climate.
Is Empathy for Pain Unique in Its Neural Correlates? A Meta-Analysis of Neuroimaging Studies of Empathy

Empathy is an essential component of our social lives, allowing us to understand and share other people's affective and sensory states, including pain. Evidence suggests a core neural network—including anterior insula (AI) and mid-cingulate cortex (MCC)—is involved in empathy for pain. However, a similar network is associated to empathy for non-pain affective states, raising the question whether empathy for pain is unique in its neural correlates. Furthermore, it is yet unclear whether neural correlates converge across different stimuli and paradigms that evoke pain-empathy. We performed a coordinate-based activation likelihood estimation (ALE) meta-analysis to identify neural correlates of empathy, assess commonalities and differences between empathy for pain and for non-pain negative affective states, and differences between pain-empathy evoking stimuli (i.e., facial pain expressions vs. acute pain inflictions) and paradigms (i.e., perceptual/affective vs. cognitive/evaluative paradigms). Following a systematic search, data from 128 functional brain imaging studies presenting whole-brain results of an empathy condition vs. baseline/neutral condition were extracted. Synthesizing neural correlates of empathy confirmed a core network comprising AI, MCC, postcentral gyrus, inferior parietal lobe, thalamus, amygdala, and brainstem. There was considerable overlap in networks for empathy for pain and empathy for non-pain negative affective states. Important differences also arose: empathy for pain uniquely activated bilateral mid-insula and more extensive MCC. Regarding stimuli, painful faces and acute pain inflictions both evoked the core empathy regions, although acute pain inflictions activated additional regions including medial frontal and parietal cortex. Regarding paradigms, both perceptual/affective and cognitive/evaluative paradigms recruited similar neural circuitry, although cognitive/evaluative paradigms activated more left MCC regions while perceptual/affective paradigms activated more right AI. Taken together, our findings reveal that empathy for pain and empathy for non-pain negative affective states share considerable neural correlates, particularly in core empathy regions AI and MCC. Beyond these regions, important differences emerged, limiting generalizability of findings across different affective/sensory states. Within pain-empathy studies, the core regions were recruited robustly irrespective of stimuli or instructions, allowing one to tailor designs according to specific needs to some extent, while ensuring activation of core regions.
Proteus: network-aware web browsing on heterogeneous mobile systems

We present Proteus, a novel network-aware approach for optimizing web browsing on heterogeneous multi-core mobile systems. It employs machine learning techniques to predict which of the heterogeneous cores to use to render a given webpage and the operating frequencies of the processors. It achieves this by first learning offline a set of predictive models for a range of typical networking environments. A learnt model is then chosen at runtime to predict the optimal processor configuration, based on the web content, the network status and the optimization goal. We evaluate Proteus by implementing it into the open-source Chromium browser and testing it on two representative ARM big.LITTLE mobile multi-core platforms. We apply Proteus to the top 1,000 popular websites across seven typical network environments. Proteus achieves over 80% of best available performance. It obtains, on average, over 17% (up to 63%), 31% (up to 88%), and 30% (up to 91%) improvement respectively for load time, energy consumption and the energy delay product, when compared to two state-of-the-art approaches.
Automating Motion Correction in Multishot MRI Using Generative Adversarial Networks

Multishot Magnetic Resonance Imaging (MRI) has recently gained popularity as it accelerates the MRI data acquisition process without compromising the quality of final MR image. However, it suffers from motion artifacts caused by patient movements which may lead to misdiagnosis. Modern state-of-the-art motion correction techniques are able to counter small degree motion, however, their adoption is hindered by their time complexity. This paper proposes a Generative Adversarial Network (GAN) for reconstructing motion free high-fidelity images while reducing the image reconstruction time by an impressive two orders of magnitude.
Disentanglement Cost of Quantum States.

We show that the minimal rate of noise needed to catalytically erase the entanglement in a bipartite quantum state is given by the regularized relative entropy of entanglement. This offers a solution to the central open question raised in [Groisman et al., Phys. Rev. A 72, 032317 (2005)PLRAAN1050-294710.1103/PhysRevA.72. 032317] and complements their main result that the minimal rate of noise needed to erase all correlations is given by the quantum mutual information. We extend our discussion to the tripartite setting where we show that an asymptotic rate of noise given by the regularized relative entropy of recovery is sufficient to catalytically transform the state to a locally recoverable version of the state.
The Impacts of Tumor and Tumor Associated Epilepsy on Subcortical Brain Structures and Long Distance Connectivity in Patients With Low Grade Glioma

Low grade gliomas in cerebral cortex often cause symptoms related to higher cerebral functions such as attention, memory and executive function before treatment is initiated. Interestingly, focal tumors residing in one cortical region can lead to a diverse range of symptoms, indicating that the impact of a tumor is extended to multiple brain regions. We hypothesize that the presence of focal glioma in the cerebral cortex leads to alterations of distant subcortical areas and essential white matter tracts. In this study, we analyzed diffusion tensor imaging scans in glioma patients to study the effect of glioma on subcortical gray matter nuclei and long-distance connectivity. We found that the caudate nucleus, putamen and thalamus were affected by cortical glioma, displaying both volumetric and diffusion alterations. The cerebellar cortex contralateral to the tumor side also showed significant volume decrease. Additionally, tractography of the cortico-striatal and cortico-thalamic projections shows similar diffusion alterations. Tumor associated epilepsy might be an important contributing factor to the found alterations. Our findings indeed confirm concurrent structural and connectivity abrasions of brain areas distant from brain tumor, and provide insights into the pathogenesis of diverse neurological symptoms in glioma patients.
The Relation Between Open‐Circuit Voltage and the Onset of Photocurrent Generation by Charge‐Transfer Absorption in Polymer : Fullerene Bulk Heterojunction Solar Cells

Photocurrent generation by charge‐transfer (CT) absorption is detected in a range of conjugated polymer–[6,6]‐phenyl C61 butyric acid methyl ester (PCBM) based solar cells. The low intensity CT absorption bands are observed using a highly sensitive measurement of the external quantum efficiency (EQE) spectrum by means of Fourier‐transform photocurrent spectroscopy (FTPS). The presence of these CT bands implies the formation of weak ground‐state charge‐transfer complexes in the studied polymer–fullerene blends. The effective band gap (Eg) of the material blends used in these photovoltaic devices is determined from the energetic onset of the photocurrent generated by CT absorption. It is shown that for all devices, under various preparation conditions, the open‐circuit voltage (Voc) scales linearly with Eg. The redshift of the CT band upon thermal annealing of regioregular poly(3‐hexylthiophene):PCBM and thermal aging of poly(phenylenevinylene)(PPV):PCBM photovoltaic devices correlates with the observed drop in open‐circuit voltage of high‐temperature treated versus untreated devices. Increasing the weight fraction of PCBM also results in a redshift of Eg, proportional with the observed changes in Voc for different PPV:PCBM ratios. As Eg corresponds with the effective bandgap of the material blends, a measurement of the EQE spectrum by FTPS allows us to measure this energy directly on photovoltaic devices, and makes it a valuable technique in the study of organic bulk heterojunction solar cells.
Diabetes and the brain: More information needed

Hyperglycemia is clearly associated with the longterm risk of diabetes-related microvascular and macrovascular complications. Treatment to reduce hyperglycemia, as determined by hemoglobin A1c (HbA1c), reduces the occurrence and slows the progression of retinopathy, nephropathy, and neuropathy in adults [1] and adolescents [2,3] as well as the macrovascular complications [4]. Despite overall improved glycemic control from newer diabetes management technologies that have developed during the last three decades (insulin analogs, self-blood glucose monitoring, insulin pumps, and continuous glucose monitoring [CGM] sensors), hypoglycemia continues to be a limiting factor in achieving a euglycemic state in insulin-treated (type 1 and insulin-requiring type 2) diabetes mellitus [5]. Even today, with the best of technologies available, persons with type 1 diabetes mellitus (T1DM) spend a significant portion of each day hyperglycemic and/or hypoglycemic. This is clear from many studies, most notably from the JDRF CGM Study [6] in which an average of 395 min (6.5 hr) of the day were spent with blood glucoses (BG) >180 mg/dL, 101 min (1.7 hr) with BG >250 mg/dL and 60 min (1 hr) of the day with BGs 180 mg/dL, 268 min (4.5 hr) with BG >250 mg/dL and 47 min (0.8 hr) with BG <70 mg/dL. Nearly half the day, on average, was spent either hypoor hyperglycemic. In years past, when hypoglycemia was considered to be the major contributor to cognitive deficits in children with diabetes, we were satisfied with allowing a higher glycemic target in children so as to avoid hypoglycemia. Coupling the observations from the JDRF CGM study with the associated cognitive impairment in either hypoglycemic or hyperglycemic state leaves caregivers of patients with T1DM with an important challenge: What is the best range to target blood glucose to maximize the benefits of glycemic control for the prevention of the long-term vascular complications while minimizing the potential for cognitive and CNS complications associated with both hypoglycemia and hyperglycemia? In this issue of the Journal of Pediatric Neuroradiology, Kaufmann et al. report their findings from a crosssectional study using cognitive testing and brain MRI in 30 “pediatric patients” (6 20 years old) with T1DM and 19 similarly-aged non-diabetic controls. The T1DM subjects were analyzed in two groups, one (n = 15) with HbA1c < 8.0% (“low HbA1c group”) and the other with *Address for correspondence: Neil H. White, Division of Endocrinology & Diabetes, Co-Unit Leader, Patient-Oriented Research Unit (PORU), Director, Pediatric Clinical Research Unit (PCRU), Department of Pediatrics, 660 South Euclid Avenue, Box 8116, St. Louis, MO 63110, USA. Tel. : +1 314 286 1157; Fax: +1 314 286 1187; E-mail: white_n@kids.wustl. edu. Journal of Pediatric Neuroradiology 1 (2012) 3–5 DOI 10.3233/PNR-2012-002 IOS Press 3
Lying, Negligence, or Lack of Knowledge? Children’s Intention-Based Moral Reasoning About Resource Claims

In a hidden inequality context, resource allocators and resource recipients are unaware that an unknowingly advantaged recipient possesses resources. The present study presented children aged 3–13 years (N = 121) with a hidden inequality vignette involving an accidental transgression in which one resource claimant, who unknowingly possessed more resources than another claimant, made an “unintentional false claim” to resources. This unintentional false claim resulted in depriving another recipient of needed resources. Results revealed that children’s ability to accurately identify the claimant’s intentions was related to how they evaluated and reasoned about resource claims, a previously understudied aspect of resource allocation contexts. Children’s attributions of intentions to the accidental transgressor mediated the relationship between age and evaluations of the accidental transgression and the relationship between age and assignment of punishment to the accidental transgressor. With age, children who negatively evaluated the unintentional false claim shifted from reasoning about lying to a focus on negligence on the part of the unintentional false claimant. This shift reflects an increasing understanding of the accidental transgressor’s benign intentions. These findings highlight how mental state knowledge and moral reasoning inform children’s comprehension of resource allocation contexts.
Improving engineering physics teaching learning from physics education research

Students come to our courses with a personal theory of physics. Most students do not change theirpersonal theories during a traditionally taught physics course. In this paper I will give some reasons forthis and also highlight some successful active-engagement curricula who help students to modify theirpersonal theories of physics and thus help them acquiring a good functional understanding of physics.
Description and use of LSODE, the Livermore Solver for Ordinary Differential Equations

LSODE, the Livermore Solver for Ordinary Differential Equations, is a package of FORTRAN subroutines designed for the numerical solution of the initial value problem for a system of ordinary differential equations. It is particularly well suited for 'stiff' differential systems, for which the backward differentiation formula method of orders 1 to 5 is provided. The code includes the Adams-Moulton method of orders 1 to 12, so it can be used for nonstiff problems as well. In addition, the user can easily switch methods to increase computational efficiency for problems that change character. For both methods a variety of corrector iteration techniques is included in the code. Also, to minimize computational work, both the step size and method order are varied dynamically. This report presents complete descriptions of the code and integration methods, including their implementation. It also provides a detailed guide to the use of the code, as well as an illustrative example problem.
Skin Biopsy in the Diagnosis of Peripheral Neuropathies

In the last decade, skin biopsy has enhanced the diagnostic armamentarium in peripheral neuropathies with the opportunity to easily investigate small diameter sensory nerves, in particular somatic unmyelinated fibres. There is no neurophysiological test for the routine examination of this class of nerve fibres. Moreover, although quantitative sensory testing – psychophysical thresholds for warm, cold, and heat pain that are functions of unmyelinated C and small myelinated Aσ fibres – may be useful in population studies, they are of no help diagnosing neuropathy in individual patients (Shy et al. 2003). The presence of axons within the human epidermis was denied for more than a century by most investigators, despite Paul Langerhans’s first description in 1868 and further studies confirming his original work. This was due to the relative insensitivity of the staining methods, and to the lack of techniques to prevent derangement of skin nerve fibres which are so easily damaged during
Oxidative Stress as Cause, Consequence, or Biomarker of Altered Female Reproduction and Development in the Space Environment

Oxidative stress has been implicated in the pathophysiology of numerous terrestrial disease processes and associated with morbidity following spaceflight. Furthermore, oxidative stress has long been considered a causative agent in adverse reproductive outcomes. The purpose of this review is to summarize the pathogenesis of oxidative stress caused by cosmic radiation and microgravity, review the relationship between oxidative stress and reproductive outcomes in females, and explore what role spaceflight-induced oxidative damage may have on female reproductive and developmental outcomes.
Dexmedetomidine Attenuates Acute Lung Injury Induced by Heatstroke and Improve Outcome.

INTRODUCTION Dexmedetomidine (DEX) has been demonstrated to inhibit inflammatory response and protect against multiorgan injury in various scenarios. The objectives of the present study was to ascertain whether DEX is able to attenuate acute lung injury (ALI) under heatstroke (HS), and to explore the underlying mechanism. METHODS Male C57BL/6 mice were exposed to ambient temperature of 39.5 ± 0.2°C until core temperature (Tc) reach 43°C. DEX or 0.9% saline was injected intraperitoneally immediately. At the end of the experiment, Bronchoalveolar lavage fluid (BALF) and lung tissue was harvested. RESULTS HS induce acute lung injury and pulmonary dysfunction, while DEX treatment could significantly inhibit lung injury and improve respiratory dysfunction under HS. The overall effect was beneficial and improved the 72 h cumulative survival rate of mice with HS. Furthermore, HS significantly elevated the levels of cytokines in bronchoalveolar lavage fluid (BALF), as well as increased the activity of Toll-like receptor 4 (TLR4)/MyD88/nuclear factor-κB (NFκB) signaling pathway in lung tissue, while DEX treatment could inhibit such effects. Finally, DEX could upregulate the expression of caveolin 1 downregulated by HS, which may contribute to the inhibition of TLR4/MyD88/NFκB signaling pathway. DISCUSSION In conclusion, the present results indicated that DEX may protect against lung inflammatory response and injury under HS via TLR4/MyD88/NFκB signaling pathway, and caveolin-1 may participate in the effects.