Miracle-dz/UniFAR-FTUs huggingface dataset:
ARTHost: Age-Optimized Receiver-Driven Transport Control Scheme in Datacenter Networks

The emergence of diversified services in the Internet of Things (IoT) poses new challenges to the datacenter, which plays an important role in data transmission. For example, urban monitoring system no longer takes delay as the only performance measure, but also needs to consider the freshness of information. Therefore, modern datacenters need to support multiple services of IoT. However, many works for datacenter networks focus on optimizing the flow completion time (FCT). The Age of Information (AoI) which is a new and promising concept in many real-time applications has not been considered in datacenter. In this paper, we apply the concept of AoI to guarantee the information freshness and propose an age-optimized receiver-driven transport control scheme, referred to as ARTHost. In ARTHost, by utilizing the receiver-driven approach, we propose a priority flow scheduling mechanism, where we classify flows into AoI flows and normal flows, representing diverse services. Then, we design a Receiver-Driven (RD) sampling pattern for AoI flows to optimize the freshness of information. Meanwhile, the optimization of FCT for normal flows is also considered. Finally, the simulation results show that the proposed ARTHost can achieve significant performance gain for AoI flows, while the performance loss of normal flows is negligible.
Wideband Endfire On-Glass Array for 5G Handset Applications

A wideband endfire array considering the glass influence at 28 GHz is proposed in this paper. The array element is a bow-tie slot antenna above a ground plane, which has the endfire radiation pattern. A glass layer, which has the same size as the ground plane, is attached on the front side of the array. A trapezoid slot is made on the edge of the ground plane to compensate the influence of the glass layer. The simulated -10-dB bandwidth is 11.3\% from 25 GHz to 28 GHz and -6-dB bandwidth is 30.3\% from 21 GHz to 28.5 GHz. The horizontal polarized endfire gain of the 4 element array ranges from 7.08 dBi to 8.36 dBi over the operating band. The array covers from $-100^{\circ}$ to $100^{\circ}$, when the realized gain is above 0 dBi on the XOY plane.
NEMESYS: near-memory graph copy enhanced system-software

Despite tackling the memory and power walls over the last decades, new challenges for manycore architectures arose due to the emergence of ever increasing memory intensiveness of applications with big, irregular and cache unfriendly data sets. As data-to-task locality is of key importance for system performance, the MEMSYS 2017 keynote speaker Peter Kogge showed evidence for the so-called "locality wall", that paved the path to near- and in-memory computing. The reduction of data movement is especially challenging on tile-based architectures with physically distributed memory as they often omit inter-tile cache coherence and thus require a different programming model (e.g. PGAS). Inter-tile communication in the PGAS paradigm is allowed via a remote procedure call (RPC)-like programming language construct. The more modern PGAS languages are object-oriented and thus the RPC mechanism requires object graphs to be copied between tiles. It is the system-software's job to provide an efficient implementation of it since the transfer of such object graphs is crucial for the performance of object-oriented applications on PGAS architectures. We therefore propose NEMESYS: NEar-Memory Graph Copy Enhanced SYstem-Software, which outsources the memory-intensive and cache unfriendly graph copy operation to near-memory hardware accelerators. As NEMESYS is an efficient implementation of the PGAS RPC, it integrates these near-memory accelerators into the system-software, opaque to the application programmer. We integrated NEMESYS into an FPGA prototype and a distributed operating system running on a 4x4-tile design with a total of 56 application cores and two memory tiles. The evaluation with the X10 IMSuite benchmarks, featuring distributed graph algorithm kernels, showed a speedup in execution time between 1.35x and 3.85x compared to a state of the art approach. The overall reduction in communication time was between 40% and 82%.
A unifying abstraction for data structure splicing

Data structure splicing (DSS) refers to reorganizing data structures by merging or splitting them, reordering fields, inlining pointers, etc. DSS has been used, with demonstrated benefits, to improve spatial locality. When data fields that are accessed together are also collocated in the address space, the utilization of hardware caches improves and cache misses decline. A number of approaches to DSS have been proposed, but each addressed only one or two splicing optimizations (e.g., only splitting or only field reordering) and used an underlying abstraction that could not be extended to include others. Our work proposes a single abstraction, called Data Structure Access Graph (D-SAG), that (a) covers all data-splicing optimizations proposed previously and (b) unlocks new ones. Having a common abstraction has two benefits: (1) It enables us to build a single tool that hosts all DSS optimizations under one roof, eliminating the need to adopt multiple tools. (2) It avoids conflicts: e.g., where one tool suggests to split a data structure in a way that would conflict with another tool's suggestion to reorder fields. Based on the D-SAG abstraction, we build a toolchain that uses static and dynamic analysis to recommend DSS optimizations to developers. Using this tool, we identify ten benchmarks from the SPEC CPU2017 and PARSEC suites that are amenable to DSS, as well as a workload on RocksDB that stresses its memory table. Restructuring data structures following the tool's suggestion improves performance by an average of 11% (geomean) and reduces cache misses by an average of 28% (geomean) for seven of these workloads.
Are genes destiny? Exploring the role of intrauterine environment in moderating genetic influences on body mass

Genes influence every aspect of human behavior, physiology, and health. Obesity, a major global public health concern, is no exception. However, relatively little is known about whether environmental factors moderate the effects of genetic influences on body mass. By incorporating molecular genetics and the fetal origins of obesity hypothesis into a gene‐environment interaction framework, this study investigates how the effect of the obesity‐associated gene (FTO) interacts with the effect of intrauterine environment to influence body mass during adulthood.
The ambient obstruction tensor and the conformal deformation complex

We construct here a conformally invariant differential operator on algebraic Weyl tensors that gives special curved analogues of certain operators related to the deformation complex and that, upon application to the Weyl curvature, yields the (Fefferman? Graham) ambient obstruction tensor. This new definition of the obstruction tensor leads to simple direct proofs that the obstruction tensor is divergence-free and vanishes identically for conformally Einstein metrics. Our main constructions are based on the ambient metric of Fefferman? Graham and its relation to the conformal tractor connection. We prove that the obstruction tensor is an obstruction to finding an ambient metric with curvature harmonic for a certain (ambient) form Laplacian. This leads to a new ambient formula for the obstruction in terms of a power of this form Laplacian acting on the ambient curvature. This result leads us to construct Laplacian-type operators that generalise the conformal Laplacians of Graham? Jenne? Mason? Sparling. We give an algorithm for calculating explicit formulae for these operators, and this is applied to give formulae for the obstruction tensor in dimensions 6 and 8. As background to these issues, we give an explicit construction of the deformation complex in dimensions n = 4, construct two related (detour) complexes, and establish essential properties of the operators in these.
Heavy-Tailed Distributions Generated by Randomly Sampled Gaussian, Exponential and Power-Law Functions

A simple stochastic mechanism that produces exact and approximate power-law distributions is presented. The model considers radially symmetric Gaussian, exponential and power-law functions inn= 1, 2, 3 dimensions. Randomly sampling these functions with a radially uniform sampling scheme produces heavy-tailed distributions. For two-dimensional Gaussians and one-dimensional exponential functions, exact power-laws with exponent –1 are obtained. In other cases, densities with an approximate power-law behaviour close to the origin arise. These densities are analyzed using Pade approximants in order to show the approximate power-law behaviour. If the sampled function itself follows a power-law with exponent –α, random sampling leads to densities that also follow an exact power-law, with exponent -n/a – 1. The presented mechanism shows that power-laws can arise in generic situations different from previously considered specialized systems such as multi-particle systems close to phase transitions, dynamical systems at bifurcation points or systems displaying self-organized criticality. Thus, the presented mechanism may serve as an alternative hypothesis in system identification problems.
Random Partitioning and Distribution-based Thresholding for Iterative Variable Screening in High Dimensions

In big data analysis, a simple task such as linear regression can become very challenging as the variable dimension $p$ grows. As a result, variable screening is inevitable in many scientific studies. In recent years, randomized algorithms have become a new trend and are playing an increasingly important role for large scale data analysis. In this article, we combine the ideas of variable screening and random partitioning to propose a new iterative variable screening method. For moderate sized $p$ of order $O(n^{2-\delta})$, we propose a basic algorithm that adopts a distribution-based thresholding rule. For very large $p$, we further propose a two-stage procedure. This two-stage procedure first performs a random partitioning to divide predictors into subsets of manageable size of order $O(n^{2-\delta})$ for variable screening, where $\delta>0$ can be an arbitrarily small positive number. Random partitioning is repeated a few times. Next, the final estimate of variable subset is obtained by integrating results obtained from multiple random partitions. Simulation studies show that our method works well and outperforms some renowned competitors. Real data applications are presented. Our algorithms are able to handle predictors in the size of millions.
Effect of cycling and functional electrical stimulation with linear and interval patterns of timing on gait parameters in patients after stroke: a randomized clinical trial

Abstract Objective Patients in the chronic phase after a stroke are an underrepresented group in the literature. Therefore, the aim of this study was to compare the effects of cycling and functional electrical stimulation with linear versus interval patterns of timing on gait parameters in patients after stroke. Design A double blinded, parallel, randomized clinical trial. Setting Neuroscience Institute. Participants Patients with lower limb disability due to stroke (N = 30) with a stroke onset >6 months and <18 months. Interventions Twenty-eight minutes of leg cycling with functional electrical stimulation with linear or interval patterns of timing applied to the peroneal and biceps femoris muscles, 3 times/week for 4 weeks. Main measures Timed 10-Meter Walk Test and Functional Ambulation Classification were the primary outcome measures. The Modified Modified Ashworth scale, active range of motion, Timed Up and Go Test, and Single Leg Stance Test were the secondary outcome measures. Evaluation was performed at baseline, after 4, and after 8 weeks. Results Thirty participants completed the 4-week intervention (interval group, n = 16; linear group, n = 14). The Functional Ambulation Classification, Timed 10-Meter Walk Test, and the Timed Up and Go Test improved significantly in both groups. The Modified Modified Ashworth scale scores for quadriceps and plantar flexion statistically decreased after 4-weeks in the interval group. Significant group-by-time interaction was shown for Timed Up and Go Test (p = 0.003, np2=0.228), knee flexion active range of motion (p < 0.001, np2=0.256) and dorsiflexion active range of motion (p < 0.001, np2=0.359). Modified Modified Ashworth scale and active range of motion in both the ankle and knee improved significantly in the interval group. Conclusions The functional electrical stimulation with cycling protocols improved the Functional Ambulation Classification, Timed 10-Meter Walk Test, active range of motion, Timed Up and Go Test, and Modified Modified Ashworth scale. An interval protocol of timing was more effective than the linear protocol in terms of spasticity and active range of motion. Implications for rehabilitation Cycling + functional electrical stimulation training with an interval pattern of timing seems superior to cycling + functional electrical stimulation training with a linear pattern. Interval protocol has positive effects on spasticity and range of motion after 12 sessions in patients post stroke. Cycling + functional electrical stimulation improves functional mobility and speed in stroke survivors and the effects of this intervention lasted in follow-up assessment after one month.
Mathematical Model of an Autoclave

This paper presents the mathematical modelling of the following autoclave processes: heating, cooling and pressure changes. An autoclave is a pressure vessel of a cylindrical form where the composite semi-products are placed on a metal plate above electrical heaters and heated at selected temperatures and under a higher pressure. The purpose of the modelling is to build a mathematical model with which the behaviour of the processes can be simulated and the temperature and pressure control in the autoclave can be improved. Furthermore, using this mathematical model we intend to test advanced uni- and multi-variable control algorithms. The mathematical model is built on the basis of the heat-transfer and pressure-changing theories. While the pressure-changing process is not very complex, the heating and cooling processes involve complex phenomena of heat conduction and convection. In the mathematical model some simplifications were considered and so the heat-transfer correlations past flat plates were used. Most of the data are real and obtained from the autoclave manufacturer, but where not possible, the method of the model’s response fitting to the measured data with the criterion function of the sum of squared errors was used. In this way, to a great extent simulated similarly to the real process responses were obtained. It can be concluded that the obtained mathematical model is usable for the design of a
Tropical Pacific Decadal Variability and the Subtropical–Tropical Cells

Abstract The decadal-scale variability in the tropical Pacific has been analyzed herein by means of observations and numerical model simulations. The two leading modes of the sea surface temperature (SST) variability in the central western Pacific are a decadal mode with a period of about 10 yr and the ENSO mode with a dominant period of about 4 yr. The SST anomaly pattern of the decadal mode is ENSO like. The decadal mode, however, explains most variance in the western equatorial Pacific and off the equator. A simulation with an ocean general circulation model (OGCM) forced by reanalysis data is used to explore the origin of the decadal mode. It is found that the variability of the shallow subtropical–tropical overturning cells is an important factor in driving the decadal mode. This is supported by results from a multicentury integration with a coupled ocean–atmosphere general circulation model (CGCM) that realistically simulates tropical Pacific decadal variability. Finally, the sensitivity of the shal.
MiR‐6838‐5p suppresses cell metastasis and the EMT process in triple‐negative breast cancer by targeting WNT3A to inhibit the Wnt pathway

Triple‐negative breast cancer (TNBC) has become a common tumor that harms women's physical and mental health, as characterized by a relatively rapid recurrence and a high incidence of brain metastasis. Research increasingly suggests that microRNAs play key roles in the progress of TNBC. However, the function of miR‐6838‐5p in TNBC has not yet been reported, and requires additional exploration.
An optical fibre dynamic instrumented palpation sensor for the characterisation of biological tissue

The diagnosis of prostate cancer using invasive techniques (such as biopsy and blood tests for prostate- speciﬁc antigen) and non-invasive techniques (such as digital rectal examination and trans-rectal ultrasonography) may be enhanced by using an additional dynamic instrumented palpation approach to prostate tissue classiﬁcation. A dynamically actuated membrane sensor/actuator has been developed that incorporates an optical ﬁbre Fabry–Pérot interferometer to record the displacement of the mem- brane when it is pressed on to different tissue samples. The membrane sensor was tested on a silicon elastomer prostate model with enlarged and stiffer material on one side to simulate early stage prostate cancer. The interferometer measurement was found to have high dynamic range and accuracy, with a minimum displacement resolution of ± 0.4 (cid:2) m over a 721 (cid:2) m measurement range. The dynamic response of the membrane sensor when applied to different tissue types changed depending on the stiffness of the tissue being measured. This demonstrates the feasibility of an optically tracked dynamic palpation technique for classifying tissue type based on the dynamic response of the sensor/actuator.
PHONETIC CUES IDENTIFYING ENGLISH COMPOUNDS

This study investigates the acoustic correlates of stress in English compounds by measuring the interaction of stress cues with different intonational environments. Effects on vowel duration, intensity, and pitch changes are compared in contrasting compounds and phrases. The results of an experiment in which participants pronounced compounds and phrases in controlled prosodic and intonational environments provide new evidence that the phonetic indicators of stress interact with these environments in a systematic way.
Testing the no-hair theorem with observations of black holes in the electromagnetic spectrum

According to the general-relativistic no-hair theorem, astrophysical black holes depend only on their masses and spins and are uniquely described by the Kerr metric. Mass and spin are the first two multipole moments of the Kerr spacetime and completely determine all other moments. The no-hair theorem can be tested by measuring potential deviations from the Kerr metric which alter such higher-order moments. In this review, I discuss tests of the no-hair theorem with current and future observations of such black holes across the electromagnetic spectrum, focusing on near-infrared observations of the supermassive black hole at the Galactic center, pulsar-timing and very-long baseline interferometric observations, as well as x-ray observations of fluorescent iron lines, thermal continuum spectra, variability, and polarization.
Economic Evaluation of Extending Medicare Immunosuppressive Drug Coverage for Kidney Transplant Recipients in the Current Era.

BACKGROUND Kidney transplant recipients must take immunosuppressant drugs to prevent rejection and maintain transplant function. Medicare coverage of immunosuppressant drugs for kidney transplant recipients ceases 36 months after transplantation, potentially increasing the risk of transplant failure. A contemporary economic analysis of extending Medicare coverage for the duration of transplant survival using current costs of immunosuppressant medications in the era of generic equivalents may inform immunosuppressant drug policy. METHODS A Markov model was used to determine the incremental cost and effectiveness of extending Medicare coverage for immunosuppressive drugs over the duration of transplant survival, compared with the current policy of 36-month coverage, from the perspective of the Medicare payer. The expected improvement in transplant survival by extending immunosuppressive drug coverage was estimated from a cohort of privately insured transplant recipients who receive lifelong immunosuppressant drug coverage compared with a cohort of Medicare-insured transplant recipients, using multivariable survival analysis. RESULTS Extension of immunosuppression Medicare coverage for kidney transplant recipients led to lower costs of -$3077 and 0.37 additional quality-adjusted life years (QALYs) per patient. When the improvement in transplant survival associated with extending immunosuppressant coverage was reduced to 50% of that observed in privately insured patients, the strategy of extending drug coverage had an incremental cost-utility ratio of $51,694 per QALY gained. In a threshold analysis, the extension of immunosuppression coverage was cost-effective at a willingness-to-pay threshold of $100,000, $50,000, and $0 per QALY if it results in a decrease in risk of transplant failure of 5.5%, 7.8%, and 13.3%, respectively. CONCLUSIONS Extending immunosuppressive drug coverage under Medicare from the current 36 months to the duration of transplant survival will result in better patient outcomes and cost-savings, and remains cost-effective if only a fraction of anticipated benefit is realized.
Planck Scale Physics, Gravi-Weak Unification and the Higgs Inflation

Starting with a theory of the discrete space-time at the Planck scale, we developed a Gravi-Weak Unification (GWU) - a $Spin(4,4)$-invariant model unified gravity with weak $SU(2)$ gauge and Higgs fields in the visible and invisible sectors of the Universe. Considering the Gravi-Weak symmetry breaking, we showed that the obtained sub-algebras contain the self-dual left-handed gravity in the OW, and the anti-self-dual right-handed gravity in the MW. Finally, at the low energy limit, we have only the Standard Model (SM) and the Einstein-Hilbert's gravity. The Froggatt-Nielsen's prediction of the top-quark and Higgs masses was given in the assumption that there exist two degenerate vacua in the SM. This prediction was improved by the next order calculations. We have developed a model of the Higgs Inflation using the GWU action. According to this inflationary model, a scalar field (inflaton) starts trapped from the "false vacuum" of the Universe at the Higgs field's VEV $v_2 \sim 10^{18}$ GeV. The interaction between the ordinary and mirror Higgs fields $\phi$ and $\widetilde{\phi}$ generates a Hybrid model by A. ~Linde of the Higgs Inflation in our Universe.
Quality Costing Technique: An Appropriate Financial Indicator for Reducing Costs and Improving Quality in the Organizations

Quality costing method is one of the total quality management (TQM) tools. This technique is also the most significant financial performance indicator, which can assist the companies to monitor and control their expenses related the quality of products and services during production process, in order to ensure that the firm is able to satisfy the requirements of the customers. Accordingly, the adoption of this method can cause that the companies save money and being more competitive in the market. However, the main purpose of this paper was to explore and discuss regarding the aspects of this TQM tool, and how it can detect unnecessary costs and maintain good quality for products and services with an aim to attain highest level of customer satisfaction in the organizations.