Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Tensegrity Locomotion on Rough Terrain via Reinforcement Learning

The dynamical properties of tensegrity robots give them appealing ruggedness and adaptability, but present major challenges with respect to locomotion control. Due to high-dimensionality and complex contact responses, data-driven approaches are apt for producing viable feedback policies. Guided Policy Search (GPS), a sample-efficient and model-free hybrid framework for optimization and reinforcement learning, has recently been used to produce periodic locomotion for a spherical 6-bar tensegrity robot on flat or slightly varied surfaces. This work provides an extension to non-periodic locomotion and achieves rough terrain traversal, which requires more broadly varied, adaptive, and non-periodic rover behavior. The contribution alters the control optimization step of GPS, which locally fits and exploits surrogate models of the dynamics, and employs the existing supervised learning step. The proposed solution incorporates new processes to ensure effective local modeling despite the disorganized nature of sample data in rough terrain locomotion. Demonstrations in simulation reveal that the resulting controller sustains the highly adaptive behavior necessary to reliably traverse rough terrain.
Learning Recurrent Binary/Ternary Weights

Recurrent neural networks (RNNs) have shown excellent performance in processing sequence data. However, they are both complex and memory intensive due to their recursive nature. These limitations make RNNs difficult to embed on mobile devices requiring real-time processes with limited hardware resources. To address the above issues, we introduce a method that can learn binary and ternary weights during the training phase to facilitate hardware implementations of RNNs. As a result, using this approach replaces all multiply-accumulate operations by simple accumulations, bringing significant benefits to custom hardware in terms of silicon area and power consumption. On the software side, we evaluate the performance (in terms of accuracy) of our method using long short-term memories (LSTMs) on various sequential models including sequence classification and language modeling. We demonstrate that our method achieves competitive results on the aforementioned tasks while using binary/ternary weights during the runtime. On the hardware side, we present custom hardware for accelerating the recurrent computations of LSTMs with binary/ternary weights. Ultimately, we show that LSTMs with binary/ternary weights can achieve up to 12x memory saving and 10x inference speedup compared to the full-precision implementation on an ASIC platform.
A 14-Bit Split-Pipeline ADC With Self-Adjusted Opamp-Sharing Duty-Cycle and Bias Current

Pipeline analog-to-digital converters (ADCs), which dominated high-speed and high-resolution applications, suffered from weak improvement in power efficiency. To address such a problem, this brief presents a 14-bit split-pipeline opamp-sharing ADC, with background calibration that optimizes duty-cycle ratio and amplifier power consumption in the shared opamp. Based on the interstage gain (that includes settling) error estimated by the split ADC calibration engine, the clock duty-cycle ratio and the bias current are adjusted to achieve better dynamic settling and resolution trade-offs. Operating at 100 MS/s with a 9-MHz input signal, the ADC achieves 46.5 dB of signal-to-noise-and-distortion ratio (SNDR) and 59.6 dB of spurious-free dynamic range (SFDR) before calibration, and after calibration, it improves to 71.7 dB of SNDR and 84.4 dB of SFDR, respectively. The ADC maintains an SNDR over 68.5 dB within the full Nyquist bandwidth consuming 32 mW of power, which yields a Walden figure-of-merit (FoM) of 147.2 fJ/conversion-step and a Schreier FoM of 160.4 dB.
Biomass consumption by surface fires across Earth's most fire prone continent

Landscape fire is a key but poorly understood component of the global carbon cycle. Predicting biomass consumption by fire at large spatial scales is essential to understanding carbon dynamics and hence how fire management can reduce greenhouse gas emissions and increase ecosystem carbon storage. An Australia‐wide field‐based survey (at 113 locations) across large‐scale macroecological gradients (climate, productivity and fire regimes) enabled estimation of how biomass combustion by surface fire directly affects continental‐scale carbon budgets. In terms of biomass consumption, we found clear trade‐offs between the frequency and severity of surface fires. In temperate southern Australia, characterised by less frequent and more severe fires, biomass consumed per fire was typically very high. In contrast, surface fires in the tropical savannas of northern Australia were very frequent but less severe, with much lower consumption of biomass per fire (about a quarter of that in the far south). When biomass consumption was expressed on an annual basis, biomass consumed was far greater in the tropical savannas (>20 times that of the far south). This trade‐off is also apparent in the ratio of annual carbon consumption to net primary production (NPP). Across Australia's naturally vegetated land area, annual carbon consumption by surface fire is equivalent to about 11% of NPP, with a sharp contrast between temperate southern Australia (6%) and tropical northern Australia (46%). Our results emphasise that fire management to reduce greenhouse gas emissions should focus on fire prone tropical savanna landscapes, where the vast bulk of biomass consumption occurs globally. In these landscapes, grass biomass is a key driver of frequency, intensity and combustion completeness of surface fires, and management actions that increase grass biomass are likely to lead to increases in greenhouse gas emissions from savanna fires.
Efficient Linear Bandits through Matrix Sketching

We prove that two popular linear contextual bandit algorithms, OFUL and Thompson Sampling, can be made efficient using Frequent Directions, a deterministic online sketching technique. More precisely, we show that a sketch of size $m$ allows a $\mathcal{O}(md)$ update time for both algorithms, as opposed to $\Omega(d^2)$ required by their non-sketched versions in general (where $d$ is the dimension of context vectors). This computational speedup is accompanied by regret bounds of order $(1+\varepsilon_m)^{3/2}d\sqrt{T}$ for OFUL and of order $\big((1+\varepsilon_m)d\big)^{3/2}\sqrt{T}$ for Thompson Sampling, where $\varepsilon_m$ is bounded by the sum of the tail eigenvalues not covered by the sketch. In particular, when the selected contexts span a subspace of dimension at most $m$, our algorithms have a regret bound matching that of their slower, non-sketched counterparts. Experiments on real-world datasets corroborate our theoretical results.
A 0.6-V, 74.2-dB DR Continuous-Time Sigma–Delta Modulator With Inverter-Based Amplifiers

This brief presents a 0.6 V third-order continuous-time sigma-delta modulator (CT-SDM) based on single-stage inverter-based amplifiers. The designed amplifier uses an on-chip bulk-bias technique to control the common mode output voltage and to mitigate process, voltage and temperature variations. Also, a negative resistance is used at the output of the amplifier to enhance dc gain. To increase power efficiency, a single-amplifier resonator is used in the loop filter. To enable this implementation a compensation technique to mitigate the effects of amplifier’s finite dc gain in the resonator transfer function is presented. The proposed CT-SDM was fabricated in a 130-nm CMOS process with an active area of 0.232 <inline-formula> <tex-math notation="LaTeX">$\mathrm {mm^{2}}$ </tex-math></inline-formula>. The modulator achieves a 74.2 dB DR and peak SNDR/SNR of 59.43/69.04 dB for a 100 kHz signal bandwidth while consuming 89.50 <inline-formula> <tex-math notation="LaTeX">$\mathrm {\boldsymbol \mu W}$ </tex-math></inline-formula> from a 0.6-V power supply.
How biological attention mechanisms improve task performance in a large-scale visual system model

How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.
Impact of bariatric surgery on neural food processing and cognition: an fMRI study

Introduction The Roux-en-Y gastric bypass (RYGB) is one of the most widely used techniques for bariatric surgery. After RYGB, weight loss up to 50%–70% of excess body weight, improvement of insulin-resistance, changes in food preferences and improvements in cognitive performance have been reported. This protocol describes a longitudinal study of the neural correlates associated with food-processing and cognitive performance in patients with morbid obesity before and after RYGB relative to lean controls. Methods and analysis This study is a pre–post case–control experiment. Using functional MRI, the neural responses to food stimuli and a working memory task will be compared between 25 patients with obesity, pre and post RYGB, and a matched, lean control group. Resting state fMRI will be measured to investigate functional brain connectivity. Baseline measurements for both groups will take place 4 weeks prior to RYGB and 12 months after RYGB. The effects of RYGB on peptide tyrosine tyrosine and glucagon-like polypeptide-1 will also be determined. Ethics and dissemination The project has received ethical approval by the local medical ethics committee of the Carl-von-Ossietzky University of Oldenburg, Germany (registration: 2017-073). Results will be published in a peer-reviewed journal as original research and on international conferences. Trial registration number DRKS00012495; Pre-results.
A Study of Magnitude and Psychological Correlates of Smartphone Use in Medical Students: A Pilot Study with A Novel Telemetric Approach

Context: Smartphone use is being investigated as a potential behavioral addiction. Most of the studies opt for a subjective questionnaire-based method. This study evaluates the psychological correlates of excessive smartphone use. It uses a telemetric approach to quantitatively and objectively measure participants' smartphone use. Methodology: One hundred forty consenting undergraduate and postgraduate students using an Android smartphone at a tertiary care teaching hospital were recruited by serial sampling. They were pre-tested with the Smartphone Addiction Scale-Short Version, Big five inventory, Levenson's Locus of Control Scale, Ego Resiliency Scale, Perceived Stress Scale, and Materialism Values Scale. Participants' smartphones were installed with tracker apps, which kept track of total smartphone usage and time spent on individual apps, number of lock–unlock cycles, and total screen time. Data from tracker apps were recorded after 7 days. Results: About 36 % of participants fulfilled smartphone addiction criteria. Smartphone Addiction Scale score significantly predicted time spent on a smartphone in the 7-day period (β = 0.234, t = 2.086, P = 0.039). Predictors for time spent on social networking sites were ego resiliency (β = 0.256, t = 2.278, P = 0.008), conscientiousness (β = −0.220, t = −2.307, P = 0.023), neuroticism (β = −0.196, t = −2.037, P = 0.044), and openness (β = −0.225, t = −2.349, P = 0.020). Time spent gaming was predicted by success domain of materialism (β =0.265, t = 2.723, P = 0.007) and shopping by ego resiliency and happiness domain of materialism. Conclusions: Telemetric approach is a sound, objective method for evaluating smartphone use. Psychological factors predict overall smartphone usage as well as usage of individual apps. Smartphone Addiction Scale scores correlate with and predict overall smartphone usage.
Method of Non-contacted Electric Field Measurement on HV Generator Stator Bar Based SiC Grading Coating Electroluminescence

In order to study the performances of electric field (or electric potential gradient) distribution along the stator end-winding stress grading system of the high voltage (HV) machines, a newly setup was firstly designed to measure the electroluminescent performances of silicon carbide (SiC) based stress grading coating (SGT) normally used in HV electric machine in this paper. Two kinds of test specimens were prepared, which consisted of simulated stator bars and standard correcting bars. The simulated stator bar was made to simulate the end-winding insulation system of actual large generator stator bar, and the standard correcting bar was used to obtain the relationship between the electroluminescent performance and electric stress on SiC grading coating or tape as a correcting reference. The fitting curve between the electroluminescent intensity per unit length (or area) of each SGT with the applied voltage gradient was measured by using a photomultiplier (PMT) probe (or sensor). Under the applied AC voltage, the non-contact scanning measurements of electroluminescent intensities along the SGT of simulated stator bar were carried out. This newly proposed non-contact method of electric field measurement in paper should be adequate to optimize end-winding stress grading system of the HV machines.
Cardiac Biomarker Release After Exercise in Healthy Children and Adolescents: A Systematic Review and Meta-Analysis.

PURPOSE The authors evaluated the impact of acute exercise and 24-hour recovery on serum concentration of cardiac troponins T and I (cTnT and cTnI) and N-terminal fragment of the prohormone brain natriuretic peptide (NT-proBNP) in healthy children and adolescents. The authors also determined the proportion of participants exceeding the upper reference limits and acute myocardial infarction cutoff for each assay. METHOD Web of Science, SPORTDiscus, MEDLINE, ScienceDirect, and Scopus databases were systematically searched up to November 2017. Studies were screened and quality-assessed; the data was systematically extracted and analyzed. RESULTS From 751 studies initially identified, 14 met the inclusion criteria for data extraction. All 3 biomarkers were increased significantly after exercise. A decrease from postexercise to 24 hours was noted in cTnT and cTnI, although this decrease was only statistically significant for cTnT. The upper reference limit was exceeded by 76% of participants for cTnT, a 51% for cTnI, and a 13% for NT-proBNP. Furthermore, the cutoff value for acute myocardial infarction was exceeded by 39% for cTnT and a 11% for cTnI. Postexercise peak values of cTnT were associated with duration and intensity (Q(3) = 28.3, P < . 001) while NT-proBNP peak values were associated with duration (Q(2) = 11.9, P = . 003). CONCLUSION Exercise results in the appearance of elevated levels of cTnT, cTnI, and NT-proBNP in children and adolescents. Postexercise elevations of cTnT and NT-proBNP are associated with exercise duration and intensity.
Across‐the‐World Automated Optimization and Continuous‐Flow Synthesis of Pharmaceutical Agents Operating Through a Cloud‐Based Server

Abstract The power of the Cloud has been harnessed for pharmaceutical compound production with remote servers based in Tokyo, Japan being left to autonomously find optimal synthesis conditions for three active pharmaceutical ingredients (APIs) in laboratories in Cambridge, UK. A researcher located in Los Angeles, USA controlled the entire process via an internet connection. The constituent synthetic steps for Tramadol, Lidocaine, and Bupropion were thus optimized with minimal intervention from operators within hours, yielding conditions satisfying customizable evaluation functions for all examples.
The Origin of a New Sex Chromosome by Introgression between Two Stickleback Fishes

Abstract Introgression is increasingly recognized as a source of genetic diversity that fuels adaptation. Its role in the evolution of sex chromosomes, however, is not well known. Here, we confirm the hypothesis that the Y chromosome in the ninespine stickleback, Pungitius pungitius, was established by introgression from the Amur stickleback, P. sinensis. Using whole genome resequencing, we identified a large region of Chr 12 in P. pungitius that is diverged between males and females. Within but not outside of this region, several lines of evidence show that the Y chromosome of P. pungitius shares a most recent common ancestor not with the X chromosome, but with the homologous chromosome in P. sinensis. Accumulation of repetitive elements and gene expression changes on the new Y are consistent with a young sex chromosome in early stages of degeneration, but other hallmarks of Y chromosomes have not yet appeared. Our findings indicate that porous species boundaries can trigger rapid sex chromosome evolution.
Research on Bot-Net Prevention and Control Technology Based on P2P

Aiming at the problem that the traditional DDoS defense method can only perform passive defense attack and can not eradicate the attack traffic, a solution of IP MAN cleaning is proposed. Based on the research of architecture, propagation and guidance strategy, dithering method, interaction and control strategy and parameter selection of typical P2P botnet SuperNet. , the deficiency of traditional defense methods is given. At last, aiming at the existing botnet, IP MAN cleaning program is designed. At the same time, the realization methods of attack traffic identification scheme, drainage scheme, DDoS traffic cleaning scheme and normal traffic reinjection technology are given.
Longitudinal Hydration Assessment in Collegiate Basketball Players Over Various Training Phases.

Heishman, AD, Daub, BD, Miller, RM, Freitas, EDS, and Bemben, MG. Longitudinal hydration assessment in collegiate basketball players over various training phases. J Strength Cond Res XX(X): 000-000, 2018-To the best of our knowledge, previous literature has not longitudinally examined hydration status in collegiate basketball players. Therefore, the purpose of this investigation was to examine the prepractice hydration status of collegiate basketball players across various training phases for 2 consecutive years. Retrospective analyses examined prepractice urine-specific gravity (USG) assessments obtained from National Collegiate Athletic Association (NCAA) Division I male basketball players during the preseason and competitive season, for 2 consecutive years. The first year (year 1 = Y1) of analysis consisted of 15 athletes and the second year (year 2 = Y2) consisted of 16 athletes, with 8 athletes in both seasons. Hydration status was classified based on the National Athletic Trainers' criteria: (a) euhydrated, USG < 1.020; (b) hypohydrated, USG = 1.020-1.030; and (c) significantly hypohydrated, USG > 1.030. Additional comparisons examined the association of minutes played with hydration status and changes in hydration status for athletes returning from Y1 to Y2. The results indicated 55-65.7% of cases showed levels of significant hypohydration during the preseason and competitive seasons for both years. Preseason hydration status was significantly better than the competitive season (Y1, p = 0.008; Y2, p = 0.005). Despite significant differences in minutes played (p < 0.001), no differences in hydration status were observed. Returning athletes displayed no differences in hydration status between Y1 and Y2. Collegiate basketball players show levels of hypohydration when longitudinally examined across various training phases. Although hydration may be improved in the preseason, alternative factors such as average game minutes played and length in program may not influence hydration status.
A CMOS Time-of-Flight Depth Image Sensor With In-Pixel Background Light Cancellation and Phase Shifting Readout Technique

A CMOS time-of-flight (TOF) image sensor with in-pixel background light (BGL) cancellation and demodulation lock-in pixel is developed for both indoor and outdoor depth imaging applications. The proposed polarity switching integration technique using p+/n-well diode realizes the in-pixel BGL cancellation up to 180 klx. In addition, the developed phase-shift readout (PSR) effectively reduces the inherent correlated noise and column fixed-pattern noise (FPN) as well with sensitivity improvement. A prototyped pulse-modulation-based TOF sensing chip with a <inline-formula> <tex-math notation="LaTeX">$64 \times 64$ </tex-math></inline-formula> pixel array, <inline-formula> <tex-math notation="LaTeX">$20\mu \text {m} \times 20\mu \text{m}$ </tex-math></inline-formula> pixel pitch, and 33% fill factor has been fabricated in TSMC standard 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process and verified. The achieved depth sensing capability ranges from 0.75 to 7.5 m with a linearity error below 1.1%, and the measured relative precision is 4.2% at a 7.5-m target distance.
TLR4/NF-κB signaling activation in plantar tissue and dorsal root ganglion involves in the development of postoperative pain

Background Severe postoperative pain remains a clinical problem that impacts patient’s rehabilitation. The present work aims to investigate the role of Toll-like receptor-4 (TLR4) activation in wounded plantar tissue and dorsal root ganglion (DRG) in the genesis of postoperative pain and its underlying mechanisms. Results Postoperative pain was induced by plantar incision in rat hind paw. Plantar incision led to increased expression of TLR4 in ipsilateral lumbar 4–5 (L4/L5) DRGs, which occurred at 2 h and was persistent to the third day after surgery. Similar to the change in TLR4 expression, there was also significant increase in phosphorylated nuclear factor-kappa B p65 (p-p65) in DRGs after surgery. Immunofluorescence staining revealed that the increased expressions of TLR4 and p-p65 not only in neuronal cells but also in satellite glial cells in DRG. Furthermore, the enhanced expressions of TLR4 and p-p65 were also detected in plantar tissues around the incision, which was observed starting at 2 h and lasting until the third day after surgery. Prior intrathecal (i.t.) injections of TAK-242 (a TLR4-specific antagonist) or 4',6-diamidino-2-phenylindole-dihydrochloride (PDTC, a nuclear factor-kappa B activation inhibitor) dose dependently alleviated plantar incision-induced mechanical allodynia and thermal hyperalgesia and inhibited the increased expressions of p-p65, tumor necrosis factor-alpha, and interleukin-1 beta in DRG. Prior subcutaneous (s.c.) plantar injection of TAK-242 or PDTC also ameliorated pain-related hypersensitivity following plantar incision. Moreover, the plantar s.c. injection of TAK-242 or PDTC inhibited the increased expressions of p-p65, tumor necrosis factor-alpha, and interleukin-1 beta not only in local wounded plantar tissue but also dramatically in ipsilateral lumbar 4–5 DRGs. Conclusion TLR4/ nuclear factor-kappa B signaling activation in local injured tissue and DRG contribute to the development of postoperative pain via regulating pro-inflammatory cytokines release. Targeting TLR4/ nuclear factor-kappa B signaling in local tissue at early stage of surgery may be an effective strategy for the treatment of postoperative pain.