Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximate modularity revisited

Set functions with convenient properties (such as submodularity) appear in application areas of current interest, such as algorithmic game theory, and allow for improved optimization algorithms. It is natural to ask (e.g., in the context of data driven optimization) how robust such properties are, and whether small deviations from them can be tolerated. We consider two such questions in the important special case of linear set functions. One question that we address is whether any set function that approximately satisfies the modularity equation (linear functions satisfy the modularity equation exactly) is close to a linear function. The answer to this is positive (in a precise formal sense) as shown by Kalton and Roberts [1983] (and further improved by Bondarenko, Prymak, and Radchenko [2013]). We revisit their proof idea that is based on expander graphs, and provide significantly stronger upper bounds by combining it with new techniques. Furthermore, we provide improved lower bounds for this problem. Another question that we address is that of how to learn a linear function h that is close to an approximately linear function f, while querying the value of f on only a small number of sets. We present a deterministic algorithm that makes only linearly many (in the number of items) nonadaptive queries, by this improving over a previous algorithm of Chierichetti, Das, Dasgupta and Kumar [2015] that is randomized and makes more than a quadratic number of queries. Our learning algorithm is based on a Hadamard transform.
A Modified Hydroxyproline Assay Based on Hydrochloric Acid in Ehrlich's Solution Accurately Measures Tissue Collagen Content.

Collagen quantification has long been relevant to biomedical research and clinical practice to characterize tissues and determine disease states. The hydroxyproline assay, while a broadly employed method of quantifying collagen, uses perchloric acid to dissolve Ehrlich's reagent. Since perchloric acid poses occupational safety hazards and high costs, in this study, a new hydroxyproline assay was developed that replaces perchloric acid with a relatively safer and cheaper alternative, hydrochloric acid (HCl). To validate this biochemical technique, first, using either acid to dissolve Ehrlich's reagent, the assays were completed for native and engineered collagenous tissues. No statistical differences were identified between the assays (p = 0.32). Subsequently, both biochemical techniques were compared to amino acid analysis, considered a proteomics gold standard. Interestingly, utilizing HCl in lieu of perchloric acid yielded greater concordance with amino acid analysis (ρc = 0.980) than did the traditional assay (ρc = 0.947); that is, the HCl-based assay more closely estimates hydroxyproline content, and, consequently, true collagen content. Thus, using Ehrlich's reagent containing HCl in the hydroxyproline assay represents an advance in both mitigating laboratory safety hazards and improving biochemical collagen quantification.
A comprehensive numerical analysis of background phase correction with V‐SHARP

Sophisticated harmonic artifact reduction for phase data (SHARP) is a method to remove background field contributions in MRI phase images, which is an essential processing step for quantitative susceptibility mapping (QSM). To perform SHARP, a spherical kernel radius and a regularization parameter need to be defined. In this study, we carried out an extensive analysis of the effect of these two parameters on the corrected phase images and on the reconstructed susceptibility maps. As a result of the dependence of the parameters on acquisition and processing characteristics, we propose a new SHARP scheme with generalized parameters. The new SHARP scheme uses a high‐pass filtering approach to define the regularization parameter. We employed the variable‐kernel SHARP (V‐SHARP) approach, using different maximum radii (Rm) between 1 and 15 mm and varying regularization parameters (f) in a numerical brain model. The local root‐mean‐square error (RMSE) between the ground‐truth, background‐corrected field map and the results from SHARP decreased towards the center of the brain. RMSE of susceptibility maps calculated with a spatial domain algorithm was smallest for Rm between 6 and 10 mm and f between 0 and 0.01 mm−1, and for maps calculated with a Fourier domain algorithm for Rm between 10 and 15 mm and f between 0 and 0.0091 mm−1. We demonstrated and confirmed the new parameter scheme in vivo. The novel regularization scheme allows the use of the same regularization parameter irrespective of other imaging parameters, such as image resolution. Copyright © 2016 John Wiley & Sons, Ltd.
Learning Image-Conditioned Dynamics Models for Control of Underactuated Legged Millirobots

Millirobots are a promising robotic platform for many applications due to their small size and low manufacturing costs. Legged millirobots, in particular, can provide increased mobility in complex environments and improved scaling of obstacles. However, controlling these small, highly dynamic, and underactuated legged systems is difficult. Hand-engineered controllers can sometimes control these legged millirobots, but they have difficulties with dynamic maneuvers and complex terrains. We present an approach for controlling a real-world legged millirobot that is based on learned neural network models. Using less than 17 minutes of data, our method can learn a predictive model of the robot's dynamics that can enable effective gaits to be synthesized on the fly for following user-specified waypoints on a given terrain. Furthermore, by leveraging expressive, high-capacity neural network models, our approach allows for these predictions to be directly conditioned on camera images, endowing the robot with the ability to predict how different terrains might affect its dynamics. This enables sample-efficient and effective learning for locomotion of a dynamic legged millirobot on various terrains, including gravel, turf, carpet, and styrofoam. Videos and further details can be found at https://sites.google. com/view/imageconddyn
Perceived Exertion during Exercise Is Associated with Children's Energy Intake

Purpose To examine the individual-level factors that predict energy intake (EI) after imposed exercise (EX) and sedentary time (SED) in children. Methods Healthy-weight children ages 9–12 yr (n = 20) reported to the laboratory for one baseline and two experimental visits (EX and SED) each separated by 1 wk in a randomized crossover design. Percent body fat, weight (kg), and height (m) were used to calculate fat-mass index (FM index) and fat-free mass index (FFM index; kg·m−2). On the EX day, children exercised at 70% estimated V˙O2peak for 30 min on a cycle ergometer, whereas cardiovascular responses and RPE were measured. Objective EI (kcal) was measured at identical meals (breakfast, lunch, snack, and dinner) on the EX and SED days. Results Total EI was not statistically different between the EX and SED days (t = 1.8, P = 0.09). FFM index was positively associated with EI on the EX day (r = 0.54, P < 0.05). RPE was also positively associated with EI on the EX day (r = 0.82, P < 0.001). Together, FFM index and RPE explained 77% of the variability in EX day EI (F(2,17) = 26.4, P < 0.001). For each unit increase in RPE, children consumed approximately 270 more calories on the EX day. A similar pattern of associations was observed on the SED day. Conclusions FFM index was positively associated with EI on the EX day. Despite experiencing the same 70% relative exercise intensity, increased perceived difficulty predicted greater EI on both the EX and SED day. These findings demonstrate a role for both FFM and RPE in explaining EI variability in children.
Intestinal smooth muscle is required for patterning the enteric nervous system

The development of the enteric nervous system (ENS) and intestinal smooth muscle occurs in a spatially and temporally correlated manner, but how they influence each other is unknown. In the developing mid‐gut of the chick embryo, we find that α‐smooth muscle actin expression, indicating early muscle differentiation, occurs after the arrival of migrating enteric neural crest‐derived cells (ENCCs). In contrast, hindgut smooth muscle develops prior to ENCC arrival. Smooth muscle development is normal in experimentally aganglionic hindguts, suggesting that proper development and patterning of the muscle layers does not rely on the ENS. However, inhibiting early smooth muscle development severely disrupts ENS patterning without affecting ENCC proliferation or apoptosis. Our results demonstrate that early intestinal smooth muscle differentiation is required for patterning the developing ENS.
Validity of a Dietary Questionnaire Assessed by Comparison With Multiple Weighed Dietary Records or 24-Hour Recalls

The authors evaluated the validity of a 152-item semiquantitative food frequency questionnaire (SFFQ) by comparing it with two 7-day dietary records (7DDRs) or up to 4 automated self-administered 24-hour recalls (ASA24s) over a 1-year period in the women's Lifestyle Validation Study (2010-2012), conducted among subgroups of the Nurses' Health Studies. Intakes of energy and 44 nutrients were assessed using the 3 methods among 632 US women. Compared with the 7DDRs, SFFQ responses tended to underestimate sodium intake but overestimate intakes of energy, macronutrients, and several nutrients in fruits and vegetables, such as carotenoids. Spearman correlation coefficients between energy-adjusted intakes from 7DDRs and the SFFQ completed at the end of the data-collection period ranged from 0.36 for lauric acid to 0.77 for alcohol (mean r = 0.53). Correlations of the end-period SFFQ were weaker when ASA24s were used as the comparison method (mean r = 0.43). After adjustment for within-person variation in the comparison method, the correlations of the final SFFQ were similar with 7DDRs (mean r = 0.63) and ASA24s (mean r = 0.62). These data indicate that this SFFQ provided reasonably valid estimates for intakes of a wide variety of dietary variables and that use of multiple 24-hour recalls or 7DDRs as a comparison method provided similar conclusions if day-to-day variation was taken into account.
Discordance between Circulating Atherogenic Cholesterol Mass and Lipoprotein Particle Concentration in Relation to Future Coronary Events in Women.

BACKGROUND It is uncertain whether measurement of circulating total atherogenic lipoprotein particle cholesterol mass [non-HDL cholesterol (nonHDLc)] or particle concentration [apolipoprotein B (apo B) and LDL particle concentration (LDLp)] more accurately reflects risk of incident coronary heart disease (CHD). We evaluated CHD risk among women in whom these markers where discordant. METHODS Among 27533 initially healthy women in the Women's Health Study (NCT00000479), using residuals from linear regression models, we compared risk among women with higher or lower observed particle concentration relative to nonHDLc (highest and lowest residual quartiles, respectively) to individuals with agreement between markers (middle quartiles) using Cox proportional hazards models. RESULTS Although all 3 biomarkers were correlated (r ≥ 0.77), discordance occurred in up to 20.2% of women. Women with discordant high particle concentration were more likely to have metabolic syndrome (MetS) and diabetes (both P < 0.001). Over a median follow-up of 20.4 years, 1246 CHD events occurred (514725 person-years). Women with high particle concentration relative to nonHDLc had increased CHD risk: age-adjusted hazard ratio (95% CI) = 1.77 (1.56-2.00) for apo B and 1.70 (1.50-1.92) for LDLp. After adjustment for clinical risk factors including MetS, these risks attenuated to 1.22 (1.07-1.39) for apo B and 1.13 (0.99-1.29) for LDLp. Discordant low apo B or LDLp relative to nonHDLc was not associated with lower risk. CONCLUSIONS Discordance between atherogenic particle cholesterol mass and particle concentration occurs in a sizeable proportion of apparently healthy women and should be suspected clinically among women with cardiometabolic traits. In such women, direct measurement of lipoprotein particle concentration might better inform CHD risk assessment.
HerpRap: A Hybrid Array Architecture Providing Any Point-in-Time Data Tracking for Datacenter

Both physical disk failure and logical errors such as software error, user abuse and virus attacks may cause data lose. The risk of logical errors is far greater than physical disk failure. Moreover, existing RAID solution cannot satisfy the reliability requirement in face of the logical errors in data centers. It is therefore becoming increasingly important for RAID-based storage systems to be able to recover data to any point-in-time when logical errors occur. We proposed a novel storage array architecture, Herp Rap, which is able to recover data from both physical disk failure and logical errors. We have implemented a prototype of Herp Rap and carried out extensive performance measurements using DBT-2 and file system benchmarks. Our experiments demonstrated that the proposed Herp Rap is able to track or recover data to any point-in-time quickly by tracing back the history of block logs. Moreover, Herp Rap outperforms existing HDD-based or SSD-based RAID5 with copy-on-write (COW) snapshot in terms of performance, energy efficiency, failure recovery ability and reliability.
Co-calibration of two self-reported measures of adherence to antiretroviral therapy

ABSTRACT Adherence to antiretroviral therapy (ART) is an important determinant of clinical success assessed in many HIV studies. Harmonizing adherence data from studies that use different measures is difficult without a co-calibration equation to convert between validated instruments. Our purpose was to co-calibrate two commonly used adherence measures: the AIDS Clinical Trials Group (ACTG) questionnaire and the Visual Analog Scale (VAS). We used robust linear regression to develop a co-calibration equation in a clinical care cohort. The outcome was the 30-day VAS percentage of ART taken and the predictors were ACTG questions. We evaluated the equation’s goodness of fit in five STTR (Seek, Test, Treat, Retain) consortium studies where individuals completed both measures: 2 criminal justice; 2 international; and 1 other high-risk vulnerable population. We developed a three-phase decision rule to convert ACTG to VAS in 1045 participants. First, when the last missed dose on the ACTG was reported as >30 days ago, the VAS was set to 100% (N = 582). Second, if “doses missed” was zero for all items, VAS was 100% (N = 104). Third, among remaining participants (N = 359), VAS was estimated as 96.8% minus 2.9% times the number of missed doses (“doses per day” was non-significant). Correlation between predicted and reported VAS was r = 0.80 in the criminal justice group (N = 446), r = 0.46 in the international group (N = 311), r = 0.32 in the other vulnerable population (N = 63), and r = 0.66 overall. When outliers due to inversion of the VAS scale were excluded (n = 25), these correlations were 0.88, 0.78, 0.80, and 0.86, respectively. We concluded that a simple decision rule and equation allowed us to co-calibrate between two widely used adherence measures thus combining data from studies with different instruments. This study highlighted issues with VAS inversions and its limitations as a single item. Combining studies using different instrument facilitates larger pooled datasets to address key research questions.
An improved RGB-D SLAM algorithm based on Kinect sensor

This paper presents an improved frontend algorithm of RGB-D SLAM, that is, Extend-RGBD-ICP algorithm. After introducing the existing frontend algorithm and analyzing its drawbacks, we present three improvement aspects: point cloud data down-sampling, matching points' selection and elimination of cumulative error of consecutive frames splicing. From the experiments on different complexities scenarios and the evaluation on benchmark dataset, it can be seen that the Extend-RGBD-ICP algorithm can achieve both accuracy and efficiency.
Simulated Autonomous Driving on Realistic Road Networks using Deep Reinforcement Learning

Using Deep Reinforcement Learning (DRL) can be a promising approach to handle various tasks in the field of (simulated) autonomous driving. However, recent publications mainly consider learning in unusual driving environments. This paper presents Driving School for Autonomous Agents (DSA^2), a software for validating DRL algorithms in more usual driving environments based on artificial and realistic road networks. We also present the results of applying DSA^2 for handling the task of driving on a straight road while regulating the velocity of one vehicle according to different speed limits.
Effect of sodium selenate on photosynthetic efficiency, antioxidative defence system and micronutrients in maize (Zea mays)

Oxidative stress or formation of faulty proteins due to non-specific replacement of sulphur by selenium(Se)/mineral imbalance can be one of the reasons for Se phytotoxicity. Present investigation reports the effect of Se on photosynthetic efficiency, anti-oxidative status and micronutrients in maize. Selenate-Se application (1–32 mg kg−1 soil) showed significant growth reduction after 30 days of sowing and all the plants died with concentration higher than 4 mg kg−1 soil. Lower Se doses increased dry matter, chlorophyll, proline and activities of defence enzymes viz. peroxidase, catalase and superoxide dismutase and decreased malondialdehyde, glutathione and glutathione reductase activity as compared to control. All the parameters showed the reverse trend with Se treatment of 4 mg kg−1 soil. Concentration of nutrients (K, P, S, Mn, Mg and Ca) in leaves decreased with application of increasing Se doses. Shoot and root weight decreased (8.5–31.9% and 12–24%, respectively) in response to varying Se doses and highest Se accumulation in these tissues was observed with Se @ 4 mg kg−1 soil. The phyto-toxic effects of higher Se doses may be due to its prooxidant effects and disturbances in nutrients level.
Convergent gustatory and viscerosensory processing in the human dorsal mid‐insula

The homeostatic regulation of feeding behavior requires an organism to be able to integrate information from its internal environment, including peripheral visceral signals about the body's current energy needs, with information from its external environment, such as the palatability of energy‐rich food stimuli. The insula, which serves as the brain's primary sensory cortex for representing both visceral signals from the body and taste signals from the mouth and tongue, is a likely candidate region in which this integration might occur. However, to date it has been unclear whether information from these two homeostatically critical faculties is merely co‐represented in the human insula, or actually integrated there. Recent functional neuroimaging evidence of a common substrate for visceral interoception and taste perception within the human dorsal mid‐insula suggests a model whereby a single population of neurons may integrate viscerosensory and gustatory signals. To test this model, we used fMRI‐Adaptation to identify whether insula regions that exhibit repetition suppression following repeated interoception trials would then also exhibit adapted responses to subsequent gustatory stimuli. Multiple mid and anterior regions of the insula exhibited adaptation to interoceptive trials specifically, but only the dorsal mid‐insula regions exhibited an adapted gustatory response following interoception. The discovery of this gustatory‐interoceptive convergence within the neurons of the human insula supports the existence of a heretofore‐undocumented neural pathway by which visceral signals from the periphery modulate the activity of brain regions involved in feeding behavior. Hum Brain Mapp 38:2150–2164, 2017. © 2017 Wiley Periodicals, Inc.
Clinical consequences of changing the sliding window IMRT dose rate

Changing pulse repetition frequency or dose rate used for IMRT treatments can alter the number of monitor units (MUs) and the time required to deliver a plan. This work was done to develop a practical picture of the magnitude of these changes. We used Varian's Eclipse Treatment Planning System to calculate the number of MUs and beam‐on times for a total of 40 different treatment plans across an array of common IMRT sites including prostate/pelvis, prostate bed, head and neck, and central nervous system cancers using dose rates of 300, 400 and 600 MU/min. In general, we observed a 4%–7% increase in the number of MUs delivered and a 10–40 second decrease in the beam‐on time for each 100 MU/min of dose rate increase. The increase in the number of MUs resulted in a reduction of the “beam‐on time saved”. The exact magnitude of the changes depended on treatment site and planning target volume. These changes can lead to minor, but not negligible, concerns with respect to radiation protection and treatment planning. Although the number of MUs increased more rapidly for more complex treatment plans, the absolute beam‐on time savings was greater for these plans because of the higher total number of MUs required to deliver them. We estimate that increasing the IMRT dose rate from 300 to 600 MU/min has the potential to add up to two treatment slots per day for each IMRT linear accelerator. These results will be of value to anyone considering general changes to IMRT dose rates within their clinic. PACS number: 87.55. N
Evaluation of the Evidence Base for the Alcohol Industry's Actions to Reduce Drink Driving Globally.

OBJECTIVES To evaluate the evidence base for the content of initiatives that the alcohol industry implemented to reduce drink driving from 1982 to May 2015. METHODS We systematically analyzed the content of 266 global initiatives that the alcohol industry has categorized as actions to reduce drink driving. RESULTS Social aspects public relations organizations (i.e., organizations funded by the alcohol industry to handle issues that may be damaging to the business) sponsored the greatest proportion of the actions. Only 0.8% (n = 2) of the sampled industry actions were consistent with public health evidence of effectiveness for reducing drink driving. CONCLUSIONS The vast majority of the alcohol industry's actions to reduce drink driving does not reflect public health evidenced-based recommendations, even though effective drink-driving countermeasures exist, such as a maximum blood alcohol concentration limit of 0.05 grams per deciliter for drivers and widespread use of sobriety checkpoints.
Quantifying the bending of bilayer temperature-sensitive hydrogels

Stimuli-responsive hydrogels can serve as manipulators, including grippers, sensors, etc., where structures can undergo significant bending. Here, a finite-deformation theory is developed to quantify the evolution of the curvature of bilayer temperature-sensitive hydrogels when subjected to a temperature change. Analysis of the theory indicates that there is an optimal thickness ratio to acquire the largest curvature in the bilayer and also suggests that the sign or the magnitude of the curvature can be significantly affected by pre-stretches or small pores in the bilayer. This study may provide important guidelines in fabricating temperature-responsive bilayers with desirable mechanical performance.