Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconstructing Translucent Objects using Differentiable Rendering

Inverse rendering is a powerful approach to modeling objects from photographs, and we extend previous techniques to handle translucent materials that exhibit subsurface scattering. Representing translucency using a heterogeneous bidirectional scattering-surface reflectance distribution function (BSSRDF), we extend the framework of path-space differentiable rendering to accommodate both surface and subsurface reflection. This introduces new types of paths requiring new methods for sampling moving discontinuities in material space that arise from visibility and moving geometry. We use this differentiable rendering method in an end-to-end approach that jointly recovers heterogeneous translucent materials (represented by a BSSRDF) and detailed geometry of an object (represented by a mesh) from a sparse set of measured 2D images in a coarse-to-fine framework incorporating Laplacian preconditioning for the geometry. To efficiently optimize our models in the presence of the Monte Carlo noise introduced by the BSSRDF integral, we introduce a dual-buffer method for evaluating the L2 image loss. This efficiently avoids potential bias in gradient estimation due to the correlation of estimates for image pixels and their derivatives and enables correct convergence of the optimizer even when using low sample counts in the renderer. We validate our derivatives by comparing against finite differences and demonstrate the effectiveness of our technique by comparing inverse-rendering performance with previous methods. We show superior reconstruction quality on a set of synthetic and real-world translucent objects as compared to previous methods that model only surface reflection.
Life after autoantibody-mediated encephalitis: optimizing follow-up and management in recovering patients

Purpose of review Timely diagnosis and treatment is essential to optimize outcomes in patients with antibody-mediated encephalitis (AME); yet even with early diagnosis and treatment, long-term outcomes may still fall short of expectations. Identifying patients at greater risk of adverse outcomes is key to personalizing care, supporting accurate counseling of patients and family members, and informing therapeutic decisions in patients with AME. This review considers long-term outcomes in recovering patients, including approaches to measure and manage common sequelae that influence life after AME. Recent findings Cognitive impairment, fatigue, and sleep disturbances affect most recovering AME patients. This realization highlights the need for outcome measures that encompass more than motor function. Standardized questionnaires, surveys, and clinical assessment tools may be adapted to support comprehensive and reproducible clinical assessments and to identify patients who may benefit from additional therapies. Summary Good outcomes continue to be reported in recovering patients, emphasizing the high potential for recovery following AME. However, cognitive, behavioral, and physical sequelae may limit the potential for great outcomes following AME. Multidisciplinary follow-up is needed to recognize and treat sequelae that compromise long-term recovery and limit quality of life in recovering patients.
Fractional integration and cointegration

In this chapter we present an overview of the main ideas and methods in the fractional integration and cointegration literature. We do not attempt to give a complete survey of this enormous literature, but rather a more introductory treatment suitable for a researcher or graduate student wishing to learn about this exciting field of research. With this aim, we have surely overlooked many relevant references for which we apologize in advance. Knowledge of standard time series methods, and in particular methods related to nonstationary time series, at the level of a standard graduate course or advanced undergraduate course is assumed.
Tracking moving targets with wide depth of field behind a scattering medium using deep learning

When light propagates through a scattering medium, imaging of an object hidden behind the scattering medium is difficult due to wavefront distortion. Scattering imaging is a technique for reconstructing images by solving the problem of complex reconstruction from speckle images. Tracking moving targets behind a scattering medium is a challenge. Scattering imaging using deep learning is a robust technique that learns a huge number of pairs of ground-truth images and speckle images. Here, we demonstrate tracking of moving targets with an extended depth of field behind a scattering medium based on deep learning of speckle images acquired at different depths. We found that it was possible to track moving targets over a wide axial direction by increasing the number of trained positions.
Distributing data throughout a MANET in a communications denied environment: reinforcement learning and game theory approaches

This paper determines optimal strategies for transmitting messages in a mobile ad-hoc network (MANET) in a communications-limited and lossy communications environment. When an agent generates or receives a message it must decide to which neighbors, and how many times, that message is to be passed. The opposing goals are to (1) propagate all messages throughout the MANET quickly and (2) to minimize the total number of messages sent. We compare two optimized decision strategies for the agents, reinforcement learning (RL) and game theory (GT) methods. For the RL framework, each node in the MANET acts as a reinforcement learning agent who must learn optimal decisions for when to send messages to whom. For the GT framework, we create a game tree where the nodes encompass message knowledge and connectivity information, and the decision branches represent sending messages to neighbors. We solve the game using a Monte-Carlo Tree Search (MCTS) variation to determine the probability that a message is sent to a neighbor. Performance is assessed in terms of the total number of messages sent, and the length of time for a given percentage of messages to reach a given percentage of nodes. Experiments with MANETs of varying size and connectivity are considered, and the RL and GT performance and training speed are compared. The decision strategies are domain agnostic and may be applied to ground, air, surface, sub-surface, or satellite networks.
Circulating Levels of MiRNAs From 320 Family in Subjects With Lipodystrophy: Disclosing Novel Signatures of the Disease

Lipodystrophy (LD) indicates a group of rare disorders, with generalized or partial loss of white adipose tissue (WAT) often associated with metabolic derangements. Heterogeneity/wide spectrum of the disease and lack of biomarkers make diagnosis often difficult. MicroRNAs are important to maintain a correct WAT function and WAT is a source of circulating miRNAs (cmiRs). miRNAs from 320 family were previously detected in the WAT and variably associated to the metabolic syndrome. Our aim was then to investigate if LD can result in altered abundance of cmiRs-320. We collected samples from a cohort of LD subjects of various subtypes and from age matched controls. Use of quantitative PCR determined that cmiRs- 320a-3p, 320b, 320c, 320e are upregulated, while 320d is downregulated in LD. CmiRs-320 power as classifiers was more powerful in the most extreme and defined forms of LD, including the generalized and the Dunnigan subtypes. cmiR-320a-3p showed significant inverse relationships with plasma leptin (P < 0.0001), typically low in LD. The hepatic enzymes gamma-glutamyl transferase (GGT), aspartate aminotransferase (AST), alanine aminotransferase (ALT) and the marker of inflammation C-reactive protein (CRP) were inversely related to cmiR 320d (P < 0.05, for CRP and GGT; P < 0.01, for AST and ALT). Gene ontology analysis revealed cell-cell adhesion as a process regulated by 320 miRNAs targets, thus disclosing a novel route to investigate origin of WAT loss/dysfunction. In conclusion, cmiRs-320 constitute novel biomarkers of LD, abundance of miR320a-3p is inversely associated to indicators related to WAT function, while downregulation of cmiR-320d predicts an altered hepatic profile and higher inflammation.
American Thoracic Society Documents American Thoracic Society/European Respiratory Society Statement on Pulmonary Rehabilitation

Linda Nici, Claudio Donner, Emiel Wouters, Richard Zuwallack, Nicolino Ambrosino, Jean Bourbeau, Mauro Carone, Bartolome Celli, Marielle Engelen, Bonnie Fahy, Chris Garvey, Roger Goldstein, Rik Gosselink, Suzanne Lareau, Neil MacIntyre, Francois Maltais, Mike Morgan, Denis O’Donnell, Christian Prefault, Jane Reardon, Carolyn Rochester, Annemie Schols, Sally Singh, and Thierry Troosters, on behalf of the ATS/ERS Pulmonary Rehabilitation Writing Committee
Network Pharmacology-Based Prediction and Verification of the Potential Mechanisms of He's Yangchao Formula against Diminished Ovarian Reserve

Background He's Yangchao formula (HSYC) has been clinically proven to be effective in treating diminished ovarian reserve (DOR). However, the underlying molecular mechanisms of HSYC in DOR are unclear. Objective This study aims to predict the underlying mechanisms of He's Yangchao formula (HSYC) against DOR through network pharmacology strategies and verify in vivo. Methods Systematic network pharmacology was used to speculate the bioactive components, potential targets, and the underlying mechanism of HSYC in the treatment of DOR. Then, the CTX-induced DOR mouse model was established to verify the effect of HSYC against DOR and the possible molecular mechanisms as predicted in the network pharmacology approach. Results A total of 44 active components and 423 potential targets were obtained in HSYC. In addition, 91 targets of DOR were also screened. The identified hub genes were AKT1, ESR1, IL6, and P53. Further molecular docking showed that the four hub targets were well-bound with their corresponding compounds. In vivo experiments showed that HSYC could promote the recovery of the estrous cycle and increase the number of primordial, growing follicles and corpora lutea. Besides, The results of qRT-PCR showed HSYC could regulate the expression of AKT1, ESR1, P53, and IL6 in DOR mice. Conclusion It was demonstrated that HSYC could increase ovarian reserves, and AKT1, ESR1, IL6, and P53 may play an essential role in this effect, which provided a new reference for the current lack of active interventions of DOR.
Psychometric Properties of the Mental Health and Social Inadaptation Assessment in Iranian Adolescents

Objective: The study was an attempt to investigate the psychometric properties of the mental health and social inadaptation measurement on Iranian adolescents. Materials and Methods: The study was a cross-sectional study conducted in two separate phases. The sample of the first phase of the study included 604 students of Islamshahr city (academic year 1398-1399) who were selected by cluster sampling method.The second phase of the study was conducted on 44 adolescents who referred to medical centers in Tehran and were selected by convinent sampling method. Data collection questionnaires were the Mental health and social Inadaptation Assessment (MIA) and the Strengths and Dissiculties Questionnaire (SDQ). The data was analysed using confirmatory factor analysis, Cronbach's alpha coefficient and Pearson correlation coefficient. Results: Results of the study supported one and two factor structures for all of the psychopatology scales. Cronbach's alpha coefficient of scales ranged from 0.73 to 0.94 except for eating disorder and psychopathy scales (α = 0.57). The test-retest reliabiity of the majoritty of the scales were moderate to high (0.51< <0.81). However, the the psychopathy, eating disorder, and dysfunction related to eating scales showed low reliability (0.38< <0.48). Moreover, the correlation coefficient between the scales of the MIA and the scales of SDQ supported the the concurrent validity of the instrument (P <0.05). Conclusion: The MIA is promising to give valid and reliable results in screening adolescents' problems. However, the psychometric properties of the three scales of psychopathy (such as the original version), eating disorder, and eating-related dysfunction were not supported in this study.
Do Buffer Zone Programs Improve Local Livelihoods and Support Biodiversity Conservation? The Case of Sagarmatha National Park, Nepal

Background and Research Aims: Buffer zone programs aim to reduce park-people conflicts by improving local livelihoods through integrated conservation and development activities. A case study was conducted at Sagarmatha National Park, Nepal from 2002–2016 to examine some buffer zone initiatives. Methods: Focus group discussions (n = 7), key informant interviews (n = 14), and field observations were performed in accordance with the IUCN Framework for Assessing Management Effectiveness of Protected Areas 2006 and WWF´s Rapid Assessment and Prioritization of Protected Area Management 2006. Results: A total of 99 buffer zone activities were identified, including a variety of construction activities such as hydroelectric projects, trails, schools, and monasteries. Park funds were allocated mainly for community development and social welfare (42%), and less on conservation and conflict management (22%). For example, traditional “Nawa” animal rearing practices, feral dog control, and mitigation of wildlife damages to crops and livestock were overlooked. Conclusion: Support gained from the buffer zone program to address livelihoods of needy households who suffer from wildlife damages was lacking, despite legal provisions for compensation (e.g. crop damages caused by jharal). This should not occur at the expense of wildlife conservation and if it does, it will diminish the original intent of buffer zones. Implications for Conservation: Although most of the local communities were positive about buffer zone programs and activities, there was a dire need to incorporate “Nawa” practices, wildlife damage compensation schemes, and feral dog controls. This study suggests to update policies that focus on conflict management.
Hypolipidemic effect of [6]-Gingerol-loaded Eudragit polymeric nanoparticles in high-fat diet-induced rats and Gamma scintigraphy evaluation of gastric-retention time

[6]-Gingerol is the potent pharmacological active phytocompound of ginger. The essential role of [6]-gingerol in drug therapy is limited due to its poor water solubility and low bioavailability. Hence, [6]-gingerol-loaded Eudragit nanoparticles were prepared by using a single emulsification solvent evaporation method to overcome hepatic first-pass metabolism and to increase oral bioavailability. The study was designed to investigate the anti-hyperlipidemic potential of [6]-gingerol in rats fed a high-fat diet (HFD). The hypolipidemic potential of [6]-gingerol at a dose of 25 and 50 mg/kg was evaluated in HFD-induced hyperlipidemic rats. The results of the study were surprisingly intriguing with [6]-gingerol significantly ( p ≤ 0.005), altering the serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol levels to near-normal in HFD-induced hyperlipidemic rats. The TC and TG were also significantly reduced after treatment with 25 and 50 mg/kg of [6]-gingerol as compared to standard atorvastatin treatment. Gamma scintigraphy results were promising with 24-hour gastric-retention time. The novel formulation [6]-gingerol-loaded Eudragit polymeric nanoparticle has a significant potential to be used as a green antihyperlipidemic agent.
Blockchain Framework for Cognitive Sensor Network Using Non-Cooperative Game Theory

The incorporation of technology in healthcare and hospital management has given a new perception to the medical procedures, and drug management for patient-centric care. Emerging technologies like blockchain, Internet of Things, and cognitive computing are most adaptable for designing smart healthcare systems. However, due to the diversified tasks involved, a design approach with broader understanding involving multiple factors that represent each area of the healthcare is the need of the hour. Game theory has gained prominence in modeling multi-player problems designated by strategic interdependency. This paper proposes a non-cooperative game strategy between players (stakeholders) to inspect how rationality is exhibited among the players who seamlessly try to get benefitted from the actions of other players. To evaluate the feasibility of the proposed model, a prototype was designed based on Ethereum permissioned blockchain employing Raspberry pi IoT devices and sensor-based cognition. Use of blockchain brings in trust, security and transparency to the system. The simulation results show that the proposed model provides better outcomes in terms of latency ( $\approx 15~\text {min}$ ), throughput and scalability with an increased number of transactions. The comparative analysis elucidates the fact that the proposed method outperforms the existing healthcare systems with a significant improvement of 10-15% in terms of resource utilization and provides faster and accurate patient-centric services.
Weight Gain after Hormone Receptor-Positive Breast Cancer

Obesity following breast cancer diagnosis is associated with poor overall survival. Understanding weight trajectories will help inform breast cancer survivors at greater risk of weight gain, and those who would benefit from earlier anti-obesity interventions. We performed a retrospective chart review of women from the Breast Cancer Program Longitudinal Repository (BCPLR) at Johns Hopkins diagnosed with hormone receptor-positive Stage I-III breast cancer from 2010 to 2020. We investigated obesity (measured by body mass index [BMI]) over time, patient and tumor characteristics, as well as treatment and recurrence. We observed a significant ≥5% increase in BMI from diagnosis to most recent follow-up (p = 0.009), particularly among those who were overweight at diagnosis (p = 0.003). Additionally, among those up to 5 years since diagnosis, there was a significant association between experiencing a ≥0.1 kg/m2 increase per year since diagnosis and baseline BMI status (p = 0.009). A ≥0.6 kg/m2 decrease in BMI was observed for participants with obesity at diagnosis (p = 0.006). Our study highlights (i) the significant burden of obesity in women with a history of breast cancer and (ii) higher risks for increases in BMI and shifts in class of obesity among women who are overweight at diagnosis.
Process modeling with multi-level categorical inputs via variable selection and level aggregation

Abstract An Industrial IoT-enabled manufacturing system often involves multiple categorical variables, denoting the process configurations and product customizations. These categorical variables lead to a flexible relationship between the input process variables and output quality measurements, as there are many potential configurations of the manufacturing process. This causes significant challenges for data-driven process modeling and root cause diagnosis. This article proposes a data-driven additive model to address the effects of different categorical variables on the relationship between process variables and quality measurements. The estimation algorithm automatically identifies the variables that have significant effects on the product quality, aggregates the levels of each categorical variable based on a priori knowledge of level similarity, and provides an accurate model that describes the relationship between the process variables and quality measurements. The simulation study validates the accuracy and effectiveness of the proposed method, and a case study on a hot rolling process shows that the method provides useful guidance on the understanding of the production system.
Differential Changes in Circulating Steroid Hormones in Hibernating Brown Bears: Preliminary Conclusions and Caveats

Brown bears are obese when they enter the den, and after 6 mo of hibernation and physical inactivity, bears show none of the adverse consequences of a sedentary lifestyle in humans, such as cardiovascular disease, type 2 diabetes, and kidney failure. The metabolic mechanisms that drive hibernation physiology in bears are poorly defined, but systemic endocrine regulators are likely involved. To investigate the potential role of steroid hormones, we quantified the total levels of 12 steroid hormones, the precursor cholesterol, sex hormone–binding globulin (SHBG), and corticosterone-binding globulin (CBG) in paired serum samples from subadult free-ranging Scandinavian brown bears during the active and hibernation states. During hibernation, androstenedione and testosterone were significantly decreased in subadult female bears (n=13), whereas they increased in all males but one (n=6) and therefore did not reach a significant difference. Despite this difference, SHBG increased more than 20-fold during hibernation for all bears. Compared with SHBG concentrations in humans, bear levels were very low in the active state, but during hibernation, levels equaled high levels in humans. The increased SHBG levels likely maintain a state of relative quiescence of the reproductive hormones in hibernating bears. Interestingly, the combination of SHBG and testosterone levels results in similar free bioavailable testosterone levels of 70–80 pM in both subadult and adult sexually active male bears, suggesting a role for SHBG in controlling androgen action during hibernation in males. Dehydroepiandrosterone sulfate, dihydrotestosterone, and estradiol levels were below the detection limit in all but one animal. The metabolically active glucocorticoids were significantly higher in both sexes during hibernation, whereas the inactive metabolite cortisone was reduced and CBG was low approaching the detection limit. A potential caveat is that the glucocorticoid levels might be affected by the ketamine applied in the anesthetic mixture for hibernating bears. However, increased hibernating cortisol levels have consistently been reported in both black bears and brown bears. Thus, we suggest that high glucocorticoid activity may support the hibernation state, likely serving to promote lipolysis and gluconeogenesis while limiting tissue glucose uptake to maintain a continuous glucose supply to the brain.
Regularity of CR maps into uniformly pseudo convex hyper surfaces and applications to proper holomorphic maps

We study regularity properties of CR maps in positive codimension valued in pseudoconvex manifolds which carry a nontrivial Levi foliation. We introduce an invariant which can be used to deduce that any sufficiently regular CR map from a minimal manifold into such a foliated target is either generically smooth or geometrically highly constrained, and to show generic smoothness of sufficiently regular CR transversal CR maps between pseudoconvex hypersurfaces. As an application, we discuss boundary regularity of proper holomorphic maps into bounded symmetric domains.
An E-Commerce Control Unit for Addressing Online Transactions in Developing Countries: Saudi Arabia—Case Study

Online transactions play an increasingly important role in our daily lives. Recently, online shopping has dramatically expanded not only in small and medium enterprises, but also among individual internet users who use social media as online trading platforms. While there are several online-shopping platforms in Saudi Arabia, they are still facing critical obstacles that challenge customers, businessmen, and organizations. This paper presents a smart control unit that could help address current challenges facing e-commerce and suggest recent government legislation dedicated to governing and simplifying online transactions to make them more reliable, faster, secure, and competitive.