Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep, Consistent Behavioral Decision Making with Planning Features for Autonomous Vehicles

Autonomous driving promises to be the main trend in the future intelligent transportation systems due to its potentiality for energy saving, and traffic and safety improvements. However, traditional autonomous vehicles’ behavioral decisions face consistency issues between behavioral decision and trajectory planning and shows a strong dependence on the human experience. In this paper, we present a planning-feature-based deep behavior decision method (PFBD) for autonomous driving in complex, dynamic traffic. We used a deep reinforcement learning (DRL) learning framework with the twin delayed deep deterministic policy gradient algorithm (TD3) to exploit the optimal policy. We took into account the features of topological routes in the decision making of autonomous vehicles, through which consistency between decision making and path planning layers can be guaranteed. Specifically, the features of a route extracted from path planning space are shared as the input states for the behavioral decision. The actor-network learns a near-optimal policy from the feasible and safe candidate emulated routes. Simulation tests on three typical scenarios have been performed to demonstrate the performance of the learning policy, including the comparison with a traditional rule-based expert algorithm and the comparison with the policy considering partial information of a contour. The results show that the proposed approach can achieve better decisions. Real-time test on an HQ3 (HongQi the third ) autonomous vehicle also validated the effectiveness of PFBD.
How Should an Agent Practice?

We present a method for learning intrinsic reward functions to drive the learning of an agent during periods of practice in which extrinsic task rewards are not available. During practice, the environment may differ from the one available for training and evaluation with extrinsic rewards. We refer to this setup of alternating periods of practice and objective evaluation as practice-match, drawing an analogy to regimes of skill acquisition common for humans in sports and games. The agent must effectively use periods in the practice environment so that performance improves during matches. In the proposed method the intrinsic practice reward is learned through a meta-gradient approach that adapts the practice reward parameters to reduce the extrinsic match reward loss computed from matches. We illustrate the method on a simple grid world, and evaluate it in two games in which the practice environment differs from match: Pong with practice against a wall without an opponent, and PacMan with practice in a maze without ghosts. The results show gains from learning in practice in addition to match periods over learning in matches only.
Privacy Awareness of Web Users

In this project we examine Internet users’ Web browsing habits and their level of awareness about privacy on the Web. We created a Web site that describes common ways used online in order to gather information about users without their knowledge. Besides just providing general information to users about this issue, we also show them their own available personal information. Our hope is that this personalized approach will raise their awareness of this important issue.
Removing the i’s from i.i.d : Testing generalization on hard datasets

The last few years have seen widespread success of over-parameterized deep learning models on various applications with massive datasets. However, these models are often critiqued for assuming access to perfect data, that is, a large amount of clean, i.i. d sampled data. In real-world scenarios, neither of these assumptions is entirely true. We consider four arbitrary domains as examples of some of these scenarios, namely, point cloud completion (with distribution shift), visual dialog (dataset size/bias issues), meta-rl for control (noisy, high variance and sparse training signal) and poaching prediction task (unstructured dataset with skew, noise and distribution shift). Using these datasets, we show that data and priors are meant to complement each other in machine learning models and it’s important to think of them jointly on a task to task basis for better generalization.
1-Embryology of the Kidney

The kidney is a sophisticated, highly vascularized organ that plays a central role in overall body homeostasis. In humans, the kidneys filter as much as 180 liters of blood per day, receiving as much as ~20% of the total cardiac output. Renal filtration of blood removes metabolic waste products (e.g., urea, ammonia, and by-products of bile from the liver) as urine while concomitantly adjusting the levels of water, electrolytes, and pH of tissue fluids. Additionally, the kidneys regulate blood pressure via the renin-angiotensin-aldosterone system, secrete erythropoietin that stimulates erythrocyte production, and contribute to the activation of vitamin D to control calcium and phosphate balance. The filtration function of the kidneys is accomplished by basic units called nephrons (Fig. 1.1). Humans on average have 1 million nephrons per adult kidney but the range of total nephrons is highly variable across human populations. Each mouse kidney may contain up to 12,000–16,000 nephrons depending on the strain. This wide range in nephron number is influenced by genetic background, fetal nutrition and environment, and maturity at birth. Nephron endowment can be clinically important as markedly reduced nephron numbers raises the susceptibility risk to hypertension and chronic kidney disease. At the core of the nephron is the renal corpuscle or glomerulus (see Fig. 1.1). The glomerulus consists of a porous and highly convoluted capillary bed composed of highly fenestrated glomerular endothelial cells. These glomerular capillaries are circumscribed by morphologically elaborate and interdigitating cells called podocytes. These capillaries are further structurally supported by pericytes CHAPTER OUTLINE
Engineering the genome of Escherichia coli BL21 for improved secretory production of recombinant proteins

The pharmaceutical industry is currently seeing an increasing focus on recombinant pharmaceuticals. Most of the recombinant pharmaceutical proteins have eukaryotic origin that require posttranslational modifications such as disulfide bond formation. To facilitate better folding of such proteins in microbial host cells, they are often translocated to the periplasm. As the periplasmic production yields still remain low in comparison with the cytoplasmic production, the process requires optimization. Current approaches for optimization of recombinant protein production and secretion are to a great extent based on the co-expression of chaperons and factors enhancing folding and stability of a target protein, or knock-out mutations of proteases. In this study, a novel approach for regulating the expression of native genes in the genome is used as an approach to facilitate better folding and stability of recombinant proteins in the periplasm. Seven strains of Escherichia coli were constructed by introducing mutations of three genes encoding periplasmic proteins, and combinations of these mutations. Up-regulation of the signal peptide peptidase SppA and the periplasmic chaperone Skp, and down-regulation of the periplasmic protease DegP was obtained by changing the respective RBS sequences in the genome of E. coli BL21 by CRMAGE recombineering. A reporter plasmid expressing alkaline phosphatase fused to the industrially relevant single-chain antibody scFv173 was used to compare the created mutants strains. The periplasmic recombinant protein production was measured by colorimetric assay after release of protein by osmotic shock. The degP down-regulation resulted in a significant decrease in production of alkaline phosphatase compared to the wildtype BL21 strain. The mutation of sppA gave significantly higher expression rates compared to the other constructed strains, but not high enough to state a significance compared to the wildtype BL21 strain. No other significant differences were observed between the units of phosphatase activity among studied strains and the wildtype BL21 strain. The potential of the upregulation of sppA should be further investigated.
A 28 Day Clinical Assessment of a Lactic Acid-containing Antimicrobial Intimate Gel Wash Formulation on Skin Tolerance and Impact on the Vulvar Microbiome

While intimate feminine hygiene products are widely used as part of daily cleansing routines, little is known about how these products impact the vulvovaginal area and its microbiome stability. This 4 week clinical study assessed tolerance of a novel gel wash containing lactic acid (pH 4.2) for external daily use when used on the external genital area and its effects on skin moisturization, vulvar skin pH, and the vulvar microbiome. After a 7 day pre-study conditioning period, 36 healthy females in three balanced age groups (18–29, 30–44, and 45–55 years) used the gel wash to cleanse their external genital area (mons pubis and vulva) and entire body at least once per day for 28 days. Skin tolerance of the gel wash was assessed by the gynecologist. Effects of the gel wash on vulvar skin microbiota were studied by performing bacterial 16S rRNA and fungal internal transcribed spacer (ITS) microbial richness and diversity analysis. Based on gynecologic assessment after 28 days of use, the gel wash showed acceptable tolerance, with no signs of increased dryness, redness, edema, itching, stinging, or burning. Use of the gel wash was associated with a significant increase in both short-term (single application) and longer-term (daily use for 28 days) skin moisturization. There was no significant change in vulvar skin pH over time with daily product use, and the gel wash did not significantly affect the natural vulvar microbiome species richness or diversity for bacteria or fungi. Results showed that this gel wash is a mild, moisturizing cleanser that maintains the natural pH and microbial diversity of vulvar skin. To our knowledge, this was the first study to assess the effect of an antimicrobial feminine gel wash on the natural pH and vulvar microbiome habitat of the skin using bacterial 16S rRNA and fungal ITS genetic sequencing techniques.
Реабилитация детей с патологией коленного сустава после артроскопических операций в условиях санатория

We examined 88 children aged between 7 and 15 years who had undergone various operations on the knee joint. The main group consisted of 44 patients whose rehabilitation was based at a rehabilitative health centre with the application of silt peloids and mineral baths. The rehabilitation of the patients of the control group (44 children) was carried out in local clinics at the place of residence with the use of physiotherapeutic modalities and massage. The rehabilitative procedures were applied at intervals of 1-3 months following arthroscopic operations. The analysis of the outcomes of therapy showed that the use of the natural physical factors for the rehabilitation of patients who underwent operations on the knee joint is more effective than the traditional outpatient treatment. Specifically, the frequency of positive results increased by 1.5 times whereas that of unsatisfactory results was reduced in comparison with the control group.
Scalable Gradients and Variational Inference for Stochastic Differential Equations

We derive reverse-mode (or adjoint) automatic differentiation for solutions of stochastic differential equations (SDEs), allowing time-efficient and constant-memory computation of pathwise gradients, a continuous-time analogue of the reparameterization trick. Specifically, we construct a backward SDE whose solution is the gradient and provide conditions under which numerical solutions converge. We also combine our stochastic adjoint approach with a stochastic variational inference scheme for continuous-time SDE models, allowing us to learn distributions over functions using stochastic gradient descent. Our latent SDE model achieves competitive performance compared to existing approaches on time series modeling.
Project Management’s Triple Constraints Mapping on Augmented Reality based Learning System for Improved Quality

Over the last few decades there has been an exponential growth in IT, motivating IT professionals and scientists to explore new dimensions resulting in the advancement of artificial intelligence and its subcategories like computer vision, deep learning and augmented reality. AR is comparatively a new area which was initially explored for gaming but recently a lot of work has been done in education using AR. Most of this focuses on improving students understanding and motivation. Like any other project, the performance of an AR based project is determined by the customer satisfaction which is usually affected by the theory of triple constraints; cost, time and scope. many studies have shown that most of the projects are under development because they are unable to overcome these constraints and meet project objectives. We were unable to find any notable work done regarding project management for augmented reality systems and application. Therefore, in this paper, we propose a system for management of AR applications which mainly focuses on catering triple constraints to meet desired objectives. Each variable is further divided into subprocesses and by following these processes successful completion of the project can be achieved.
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks

Variational Bayesian Inference is a popular methodology for approximating posterior distributions over Bayesian neural network weights. Recent work developing this class of methods has explored ever richer parameterizations of the approximate posterior in the hope of improving performance. In contrast, here we share a curious experimental finding that suggests instead restricting the variational distribution to a more compact parameterization. For a variety of deep Bayesian neural networks trained using Gaussian mean-field variational inference, we find that the posterior standard deviations consistently exhibit strong low-rank structure after convergence. This means that by decomposing these variational parameters into a low-rank factorization, we can make our variational approximation more compact without decreasing the models' performance. Furthermore, we find that such factorized parameterizations improve the signal-to-noise ratio of stochastic gradient estimates of the variational lower bound, resulting in faster convergence.
Which Traits Make Weeds More Successful in Maize Crops? Insights from a Three-Decade Monitoring in France

A major aim in invasion biology is identifying traits distinguishing alien invasive and alien non-invasive plants. Surprisingly, this approach has been, so far, poorly used to understand why some arable weeds are abundant and widespread while others are rare and narrowly distributed. In the present study, we focused on the characteristics of successful weeds occurring in maize fields, one of the most important crops worldwide. Two national weed surveys conducted in France were used to identify increasing and decreasing species based on 175 and 484 surveyed fields in the 1970s and the 2000s, respectively. Weed trait values related to regional frequency, local abundance, and specialization to maize were identified with phylogenetic generalized least-squares (PGLS). We found a positive relationship between regional frequency and local abundance, i.e., the most widespread weeds were also locally more abundant. We highlighted that weeds with the C4 photosynthetic pathway and summer emergence were more abundant, more frequent, and more specialized to maize crops. More generally, we highlighted two successful strategies: On the one hand, traits related to a general weediness syndrome with rapid resource acquisition (high SLA and Ellenberg-N) and high colonization capacity (seed longevity, fecundity, and wind dispersal); on the other hand, traits related to specific adaptation to spring cultivation (thermophilous species with summer emergence, late flowering, and C4 photosynthetic pathway). Deviations from the abundancy–frequency relationships also indicated that species of the Panicoideae sub-family, species with Triazine-resistant populations, and neophyte species were more abundant than expected by their regional frequency. To some extent, it is therefore possible to predict which species can be troublesome in maize crops and use this information in weed risk assessment tools to prevent new introductions or favor early detection and eradication. This study showed how tools developed in functional and macro-ecology can be used to improve our understanding of weed ecology and to develop more preventive management strategies.
The Moderating Role of Best Friendships on the Longitudinal Relationship Between Parental Psychological Control and Internalizing Problems, Externalizing Problems, and Identity Exploration in Emerging Adulthood

The Moderating Role of Best Friendships on the Longitudinal Relationship Between Parental Psychological Control and Internalizing Problems, Externalizing Problems, and Identity Exploration in Emerging Adulthood Lauren Elizabeth Cook School of Family Life, BYU Master of Science Parental psychological control has been linked to numerous negative outcomes among emerging-adult children. Given that emerging adulthood is a time for young people to become autonomous, explore their identities, and begin to feel like an adult, controlling parenting that limits these necessary developmental experiences can be particularly harmful to emerging adults. Given this vulnerability, the current study aimed to understand how parental psychological control affects emerging adults’ adjustment (i.e., internalizing problems, externalizing problems, identity exploration), explore a moderating factor (i.e., best friendships) that could help these struggling emerging adults, and examine how these relations could differ by parent and child gender. Participants came from four universities across the United States and completed the READY questionnaire online at two time points, one year apart (N = 273, Mage = 20.95). Results revealed that maternal psychological control positively predicted identity exploration for males and best friendships moderated the relationship between parental psychological control and identity exploration for females. No significant results were found for internalizing and externalizing problems. I then discuss conceptual factors that may play a role in understanding the relation between parental psychological control, best friendships, emerging adult adjustment (i.e., internalizing problems, externalizing problems, identity exploration), and gender.
Measuring Displacement: Assessing Proxies for Involuntary Residential Mobility

Research has repeatedly found that displacement is not more likely in gentrifying neighborhoods. Since the dependent variable—displacement—is difficult to measure, researchers resort to a variety of proxy measures for it. I classify three types of proxies: a population approach that measures compositional changes in neighborhoods over time, an individual approach that measures individual housing mobility, and a motivational approach that traces both individual mobility as well as the reasons why a household moved to determine whether that move was involuntary. I examine the prevalence of these approaches across a sample of the literature. I then test the commensurability of the proxy measures with data from New York City by comparing the rank orderings of neighborhoods with the most and least displacement. I find widely different results across the approaches. I explain these results by examining the underlying mechanisms of displacement that are masked by the other approaches.
Methyl- b -Cyclodextrins Preferentially Remove Cholesterol from the Liquid Disordered Phase in Giant Unilamellar Vesicles

Methyl- b -cyclodextrins (M b CDs) are molecules that are extensively used to remove and to load cholesterol (Chol) from artiﬁcial and natural membranes; however, the mechanism of Chol extraction by M b CD from pure lipids or from complex mixtures is not fully understood. One of the outstanding questions in this ﬁeld is the capability of M b CD to remove Chol from lipid domains having different packing. Here, we investigated the speciﬁcity of M b CD to remove Chol from coexisting macrodomains with different lipid packing. We used giant unilamellar vesicles (GUVs) made of 1,2-dioleoylpho-sphatidylcholine:1,2-dipalmitoylphatidylcholine:free cholesterol, 1:1:1 molar ratio at 27 (cid:3) C. Under these conditions, individual GUVs present Chol distributed into l o and l d phases. The two phases can be distinguished and visualized using Laurdan generalized polarization and two-photon excitation ﬂuorescence microscopy. Our data indicate that M b CD removes Chol preferentially from the more disordered phase. The process of selective Chol removal is dependent on the M b CD concentration. At high concentrations, M b CD also removes phospholipids.
CORRELATIVE STUDY BETWEEN MALOCCLUSION SEVERITY LEVEL AND ORAL HYGIENE STATUS AMONG STUDENTS AT SMP LPP WAKAF FOUNDATION UNIVERSITAS MUSLIM INDONESIA IN 2017 (Research report)

Background: Malocclusion is a dentofacial growth deviation that interferes with mastication, deglutination, speech and facial harmony. In Indonesia, the prevalence of malocclusion is constantly high (around 80%) which reached 90% among school-age adolescents in 1983 and 89% in 2006. Malocclusion condition, especially crowding, can generate plaque accumulation and calculus formation because of toothbrush inability to outreach interdental areas in crowded teeth. Aims: To determine the correlation between malocclusion severity level and oral hygiene status among class VII and VIII students at SMP LPP YW Universitas Muslim Indonesia Makassar in 2017. Methods: This study is an observational analytic study using cross-sectional design. Target population is class VII and VIII students at SMP LPP YW Universitas Muslim Indonesia Makassar. The data was collected using ICON and OHI-S assessment method. Statistical analysis was performed using Spearman test. Results: The results showed p value = 0.01 which means that there was a significant correlation between malocclusion severity level and oral hygiene status with r = 0.314. Conclusion: There is a significant correlation between malocclusion severity level and oral hygiene status among class VII and VIII students at SMP LPP YW Universitas Muslim Indonesia Makassar in 2017.
Proceedings of Meetings on Acoustics

Acoustic signature of a rigid wing, equipped with a movable downstream flap and interacting with a line vortex, is studied in a twodimensional low-Mach number flow. The flap is attached to the airfoil via a torsion spring, and the coupled fluid-structure interaction problem is analysed using thin-airfoil methodology and application of the Brown and Michael equation. It is found that incident vortex passage above the airfoil excites flap motion at the system natural frequency, amplified above all other frequencies contained in the forcing vortex. Far-field radiation is analysed using Powell-Howe analogy, yielding the leading order dipole-type signature of the system. It is shown that direct flap motion has a negligible effect on total sound radiation. The characteristic acoustic signature of the system is dominated by vortex sound, consisting of relatively strong leading and trailing edge interactions of the airfoil with the incident vortex, together with late-time wake sound resulting from induced flap motion. In comparison with the counterpart rigid (non-flapped) configuration, it is found that the flap may act as sound amplifier or absorber, depending on the value of flap-fluid natural frequency. The study complements existing analyses examining sound radiation in staticand detached-flap configurations.