Miracle-dz/UniFAR-FTUs huggingface dataset:
CausalSpartanX: Causal Consistency and Non-Blocking Read-Only Transactions

Causal consistency is an intermediate consistency model that can be achieved together with high availability and performance requirements even in presence of network partitions. In the context of partitioned data stores, it has been shown that implicit dependency tracking using timestamps is more efficient than explicit dependency tracking. Existing time-based solutions depend on monotonic psychical clocks that are closely synchronized. These requirements make current protocols vulnerable to clock anomalies. In this paper, we propose a new time-based algorithm, CausalSpartanX, that instead of physical clocks, utilizes Hybrid Logical Clocks (HLCs). We show that using HLCs, without any overhead, we make the system robust on physical clock anomalies. This improvement is more significant in the context of query amplification, where a single query results in multiple GET/PUT operations. We also show that CausalSpartanX decreases the visibility latency for a given data item compared with existing time-based approaches. In turn, this reduces the completion time of collaborative applications where two clients accessing two different replicas edit same items of the data store. CausalSpartanX also provides causally consistent distributed read-only transactions. CausalSpartanX read-only transactions are non-blocking and require only one round of communication between the client and the servers. Also, the slowdowns of partitions that are unrelated to a transaction do not affect the performance of the transaction. Like previous protocols, CausalSpartanX assumes that a given client does not access more than one replica. We show that in presence of network partitions, this assumption (made in several other works) is essential if one were to provide causal consistency as well as immediate availability to local updates.
Flying-Capacitor Bottom-Plate Sampling Scheme for Low-Power High-Resolution SAR ADCs

A new sampling scheme for successive approximation register (SAR) analog-to-digital converters (ADCs) is proposed in this paper. The switching scheme eliminates two major problems of traditional SAR ADC architectures: first, the high energy demand of the input driver, because of high input capacitance; and second, the trade-off between linearity and, consequently, bottom-plate sampling, and area savings and, consequently, upper-plate sampling. The proposed sampling scheme allows reduction of the sampling capacitance to a single unit capacitor and the use of high linear bottom-plate sampling without sacrificing the double area on digital-to-analog converter (DAC). This method works with most previously published switching schemes.
On Analysis of Traffic Flow Demultiplexing Effectiveness1 The research was supported by RFBR (project No. 18-07-01255)

It is known that the demultiplexing of the individual traffic flow into several independent transport subflows can increase the speed of the one. This statement is true for a single flow but its truth for the massive case, when demultiplexing technics are applied to all traffic flows in the network of a single Internet Service Provider (ISP), is not obvious. The question arises, what impact the massive demultiplexing of traffic flows will have on the whole ISP network bandwidth. In this paper this question is considered for the static case, when each flow is demultiplexed statically, i.e. every flow before its launching is demultiplexed into the same number of subflows.
Influence of High Voltage DC Transmission on Measuring Accuracy of Current Transformers

When the high-voltage direct current (HVDC) transmission is running under the monopole-ground-circuit operation mode, slight dc will be coupled into the nearby alternating current (ac) power grids and so has some negative influences, called dc bias phenomenon, on current transformers (CT). In this paper, based on the Preisach magnetization theory, a digital simulation method of CT is established, and then, its correctness has been verified by error calibration experiments. After that, the inherent mechanism of dc bias phenomenon is analyzed and concluded by simulating the coupling relationships among the magnetic flux density of iron core, exciting current, and coupling dc. Most importantly, we have built a coupling dc monitoring network for Jingpin to the south of Jiangsu (J2SJ) HVDC Project in China’s Jiangsu Province, and based on the monitoring data and analysis results of CT’s error varying with coupling dc, the actual influence of J2SJ HVDC on CT measuring accuracy is evaluated quantitatively.
[Application of Static Characteristics of Plantar Pressure Distribution in the Assessment of Knee Joint Injury].

OBJECTIVE This paper used plantar pressure analysis equipment to discuss the plantar pressure distribution pattern and balance ability of patients with the knee joint injury under static standing. METHODS Zebris FDM-S plantar pressure analysis equipment was used to collect plantar pressure data from subjects with the knee joint injury and healthy control subjects. We compared the pressure values in each region of pelma, and then assessing the balance ability of the subjects based on the trajectory of the overall pressure center movement. RESULTS Compared with the healthy control group, patients with knee joint injury have a significantly lower pressure in the heel areas and a significantly higher pressure in the middle foot area. And the total pressure of the injured limb foot in the patient group is lower than that in the contralateral foot. In addition, there is a significant increase in the parameters of the balance ability index in the patient group. CONCLUSIONS The plantar pressure distribution pattern of patients with knee joint injury is different from that of normal people in static standing, and the balance ability is poor. Therefore, this method has a positive guiding significance in the evaluation and application of knee joint injury.
Games with Resources and Biological Effects of Radiowaves

We propose an extension of evolutionary games which enables to include time-varying external disturbances which may describe effects of environmental changes or controlled interventions. The main idea is to endow payoff tables with alterations of phenotype adjustment during the transient generations. This approach allows for modeling of biological effects of radiowaves on the cellular level.
A methodology to support the electrical network in order to promote electric vehicle charging in smart cities

Smart City design must include facilities for low emission transport, and that includes electric vehicles. Amongst other things, the installation of charging points for electric vehicles must consider the effect on the low voltage power network.A network modelling tool has been used to analyse the effect of introducing charge points into an urban environment. Real values of network topology derived from those available for the local distribution network operator have been used to populate the model.The effect of increasing penetration of EVs, changing from 3 kW to 7 kW charging are shown to cause unacceptable increases in power flow and cable thermal overload. Several strategies are then demonstrated to ameliorate the effect, including phased charging, delayed charging and cable upgrade.
Development and internal validation of a nine-lncRNA prognostic signature for prediction of overall survival in colorectal cancer patients

Background Colorectal cancer remains a serious public health problem due to the poor prognosis. In the present study, we attempted to develop and validate a prognostic signature to predict the individual mortality risk in colorectal cancer patients. Materials and Methods The original study datasets were downloaded from The Cancer Genome Atlas database. The present study finally included 424 colorectal cancer patients with wholly gene expression information and overall survival information. Results A nine-lncRNA prognostic signature was built through univariate and multivariate Cox proportional regression model. Time-dependent receiver operating characteristic curves in model cohort demonstrated that the Harrell’s concordance indexes of nine-lncRNA prognostic signature were 0.768 (95% CI [0.717–0.819]), 0.778 (95% CI [0.727–0.829]) and 0.870 (95% CI [0.819–0.921]) for 1-year, 3-year and 5-year overall survival respectively. In validation cohort, the Harrell’s concordance indexes of nine-lncRNA prognostic signature were 0.761 (95% CI [0.710–0.812]), 0.801 (95% CI [0.750–0.852]) and 0.883 (95% CI [0.832–0.934]) for 1-year, 3-year and 5-year overall survival respectively. According to the median of nine-lncRNA prognostic signature score in model cohort, 424 CRC patients could be stratified into high risk group (n = 212) and low risk group (n = 212). Kaplan–Meier survival curves showed that the overall survival rate of high risk group was significantly lower than that of low risk group (P < 0.001). Discussion The present study developed and validated a nine-lncRNA prognostic signature for individual mortality risk assessment in colorectal cancer patients. This nine-lncRNA prognostic signature is helpful to evaluate the individual mortality risk and to improve the decision making of individualized treatments in colorectal cancer patients.
Machine Learning Approaches for Intra-Prediction in HEVC

The use of machine learning techniques for encoding complexity reduction in recent video coding standards such as High Efficiency Video Coding (HEVC) has received prominent attention in the recent past. Yet, the dynamically changing nature of the video contents makes it evermore challenging to use rigid traditional inference models for predicting the encoding decisions for a given content. In this context, this paper investigates the resulting implications on the coding efficiency and the encoding complexity, when using offline trained and online trained machine-learning models for coding unit size selection in the HEVC intra-prediction. The experimental results demonstrate that the ground truth encoding statistics of the content being encoded, is crucial to the efficient encoding decision prediction when using machine learning based prediction models.
Dental erosion in gastro-esophageal reflux disease. A systematic review

The growing interest reflected in the studies on dental erosion is justified by the severe health problems it entails, i.e. esthetic, phonetic, masticatory disturbances and pulp complications. Most studies investigate the prevalence of dental erosion in adults and children, the severity of lesions and etiopathogenetic factors. Background and aim Dental erosions (DE) are one of the extraesophageal complications of gastroesophageal reflux disease (GERD). An increasing amount of papers shed light on this topic. We carried out a systematic review on the association between GERD and DE. Methods We studied the association between DE and GERD in adults and children. The search for published studies was performed in PubMed using search terms “dental erosion” and “gastro-esophageal reflux disease”. References published since 2007 were included and a systematic review was carried out. Articles not assessing DE in GERD patients were excluded, and also case presentations and articles in languages of limited circulation. The prevalence of DE in patients with GERD, extrinsic and intrinsic etiological factors of DE and the severity of dental erosion lesions were analyzed. Results A total of 273 articles were found, 10 studies being retained for analysis. Correlations between DE and GERD, namely the prevalence and severity of dental erosion in GERD patients, were investigated. DE prevalence was between 10.6% – 42%, median 25.5%. Mean values of DE prevalence were 48.81% in GERD patients, compared to 20.48% in non-GERD controls. Comparative values of DE frequency in adults with GERD was 38.96%, compared to 98.1% in children with GERD. Conclusions DE is a condition associated with GERD. DE prevalence is higher in GERD patients. Intrinsic pathogenetic factors with direct action on the hard dental tissues are GERD, while extrinsic factors are represented by diet. Among the patients diagnosed with GERD, youth under the age of 18 had a higher frequency compared to adults.
On Path Length Estimation for Wireless Capsule Endoscopy

Wireless capsule endoscopy (WCE) is a non-invasive technology used for inspection of the gastrointestinal tract. Localization of the capsule is a vital part of the system enabling physicians to identify the position of anomalies. Due to intestinal motility, the positions of the intestines will change significantly within the abdominal cavity over time. However, the distance from one position to another within the intestines changes much less. In this paper a method for calculating the pathlength travelled by a WCE is proposed. The method is based on Kalman-and particle filters and is simulated using a model that approximately replicates the movement through the small intestine. The travelled distance was estimated to an accuracy within a few millimeters.
Diurnal variation of metabolites in three individual participants

ABSTRACT The circadian system influences virtually all biological functions. Understanding the impact of circadian variation on metabolism may provide insight into mechanisms of circadian-associated disorders and guide the implementation of chrono-therapy. Previous research has reported circadian variation in 7–20% of metabolites in human blood. In this study, untargeted metabolomics profiles were measured using blood of two healthy men and one healthy woman, collected every 2 h for up to 48 h under carefully controlled conditions. The pattern of variation of each metabolite over time was examined on each participant separately, using both one- and two-order harmonic models. A total of 100 of 663 metabolites, representing all metabolite categories, showed diurnal rhythmic concentrations that exceeded the Bonferroni threshold (P < 2.5 × 10−5). Overall, peak times of many metabolites were clustered during the afternoon-midnight, including the majority of amino acids, all peptides, all lysolipids and all phospholipids, whereas the majority of steroids peaked in the morning. We observed substantial inter-individual variation for both peak times and amplitudes in these three subjects. In conclusion, at least 15% of blood metabolites, representing a broad group of biological pathways, exhibit diurnal variation in three participants. The average peak times of most of these metabolites are clustered in morning or afternoon-midnight. Further work is needed to validate and extend this work in more individuals.
Comprehensive Evaluation of Supply Voltage Underscaling in FPGA on-Chip Memories

In this work, we evaluate aggressive undervolting, i.e., voltage scaling below the nominal level to reduce the energy consumption of Field Programmable Gate Arrays (FPGAs). Usually, voltage guardbands are added by chip vendors to ensure the worst-case process and environmental scenarios. Through experimenting on several FPGA architectures, we measure this voltage guardband to be on average 39% of the nominal level, which in turn, delivers more than an order of magnitude power savings. However, further undervolting below the voltage guardband may cause reliability issues as the result of the circuit delay increase, i.e., start to appear faults. We extensively characterize the behavior of these faults in terms of the rate, location, type, as well as sensitivity to environmental temperature, with a concentration of on-chip memories, or Block RAMs (BRAMs). Finally, we evaluate a typical FPGA-based Neural Network (NN) accelerator under low-voltage BRAM operations. In consequence, the substantial NN energy savings come with the cost of NN accuracy loss. To attain power savings without NN accuracy loss, we propose a novel technique that relies on the deterministic behavior of undervolting faults and can limit the accuracy loss to 0.1% without any timing-slack overhead.
A Formally Verified Validator for Classical Planning Problems and Solutions

In this paper we present a formally verified validator for planning problems and their solutions. We formalise the semantics of a fragment of PDDL (V, ¬, →, = in the preconditions, typing and constants) in the Higher-Order Logic theorem prover Isabelle/HOL. We then construct an efficient plan validator and mechanically prove it correct w.r. t. our semantics. We argue that our approach provides a superior compromise in constructing validators where one can have the best of two worlds: (i) clear and concise semantics w.r. t. which the validator is built thus helping to avoid bugs (unlike existing validators, which we show have bugs) and (ii) an optimised implementation whose performance is competitive with mainstream unverified validators.
Stabilization of Systems Under Stochastic Clock Offsets

This paper is concerned with the stabilization of networked control systems under clock offsets between sensors and controllers where the clock offsets are assumed to be stochastic variables following a certain probability distribution. A linear time-invariant controller is designed to deal with the effects of the stochastic offsets between sensors and controllers clocks, which can guarantee the stochastic stability of the linear systems. Finally, the validity of our results is illustrated using a numerical simulation.
Developing a Modular Unmanned Aerial Vehicle (UAV) Platform for Air Pollution Profiling

The unmanned aerial vehicle (UAV) offers great potential for collecting air quality data with high spatial and temporal resolutions. The objective of this study is to design and develop a modular UAV-based platform capable of real-time monitoring of multiple air pollutants. The system comprises five modules: the UAV, the ground station, the sensors, the data acquisition (DA) module, and the data fusion (DF) module. The hardware was constructed with off-the-shelf consumer parts and the open source software Ardupilot was used for flight control and data fusion. The prototype UAV system was tested in representative settings. Results show that this UAV platform can fly on pre-determined pathways with adequate flight time for various data collection missions. The system simultaneously collects air quality and high precision X-Y-Z data and integrates and visualizes them in a real-time manner. While the system can accommodate multiple gas sensors, UAV operations may electronically interfere with the performance of chemical-resistant sensors. Our prototype and experiments prove the feasibility of the system and show that it features a stable and high precision spatial-temporal platform for air sample collection. Future work should be focused on gas sensor development, plug-and-play interfaces, impacts of rotor wash, and all-weather designs.
Differentiation of Aneugens and Clastogens in the In Vitro Micronucleus Test by Kinetochore Scoring Using Automated Image Analysis

The in vitro micronucleus test according to OECD Test Guideline 487 (TG 487) is widely used to investigate the genotoxic potential of drugs. Besides the identification of in vitro genotoxicants, the assay can be complemented with kinetochore staining for the differentiation between clastogens and aneugens. This differentiation constitutes a major contribution to risk assessment as especially aneugens show a threshold response. Thus, a novel method for automated MN plus kinetochore (k+) scoring by image analysis was developed based on the OECD TG 487. Compound‐induced increases in MN frequency can be detected using the cytokinesis‐block (cytochalasin B) method in V79 cells after 24 h in a 96‐well format. Nuclei, MN, and kinetochores were labeled with nuclear counterstain and anti‐kinetochore antibodies, respectively, to score MN in binuclear or multinuclear cells and to differentiate compound‐induced MN by the presence of kinetochores. First, a reference data set was created by manual scoring using two clastogens and aneugens. After developing the automated scoring process, a set of 14 reference genotoxicants were studied. The automated image analysis yielded the expected results: 5/5 clastogens and 6/6 aneugens (sensitivity: 100%) as well as 3/3 non‐genotoxicants (specificity: 100%) were correctly identified. Further, a threshold was determined for identifying aneugens. Based on the data for our internally characterized reference compounds, unknown compounds that induce ≥53.8% k+ MN are classified as aneugens. The current data demonstrate excellent specificity and sensitivity and the methodology is superior to manual microscopic analysis in terms of speed and throughput as well as the absence of human bias. Environ. Mol. Mutagen. 60:227–242, 2019. © 2018 Wiley Periodicals, Inc.
An End-to-End Approach to Self-Folding Origami Structures

This paper presents an end-to-end approach to automate the design and fabrication process for self-folding origami structures. Self-folding origami structures are robotic sheets composed of rigid tiles and joint actuators. When they are exposed to heat, each joint folds into a preprogrammed angle. Those folding motions transform themselves into a structure, which can be used as body of 3-D origami robots, including walkers, analog circuits, rotational actuators, and microcell grippers. Given a 3-D model, the design algorithm automatically generates a layout printing design of the sheet form of the structure. The geometric information, such as the fold angles and the folding sequences, is embedded in the sheet design. When the sheet is printed and baked in an oven, the sheet self-folds into the given 3-D model. We discuss, first, the design algorithm generating multiple-step self-folding sheet designs, second, verification of the algorithm running in <inline-formula><tex-math notation="LaTeX">$O(n^2)$</tex-math> </inline-formula> time, where <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is the number of the vertices, third, implementation of the algorithm, and finally, experimental results, several self-folded 3-D structures with up to 55 faces and two sequential folding steps.
Effect of Endurance Training on Hemoglobin Mass and V˙O2max in Male Adolescent Athletes

Purpose It is unknown, whether endurance training stimulates hemoglobin mass (Hbmass) and maximal oxygen uptake (V˙O2max) increases during late adolescence. Therefore, this study assessed the influence of endurance training on Hbmass, blood volume parameters, and V˙O2max in endurance athletes and control subjects from age 16 to 19 yr. Methods Hemoglobin mass, blood volume parameters, V˙O2max and anthropometric parameters were measured in male elite endurance athletes from age 16 to 19 yr in 6-month intervals (n = 10), as well as in age-matched male controls (n = 12). Results Neither the level of Hbmass per lean body mass (LBM) (P = 0.80) nor the development of Hbmass during the 3 yr (P = 0.97) differed between athletes and controls. Hbmass at age 16 yr was 13.24 ± 0.89 g·kg−1 LBM and increased by 0.74 ± 0.58 g·kg−1 LBM (P < 0.01) from age 16 to 19 yr. There was a high correlation between Hbmass at age 16 and 19 yr (r = 0.77; P < 0.001). Plasma volume, blood volume, and V˙O2max were higher in athletes compared to controls (P < 0.05). Blood volume and V˙O2max increased with age (P < 0.01, similarly in both groups). Conclusions Endurance training volumes do not explain individual differences in Hbmass levels nor Hbmass and V˙O2max development in the age period from 16 to 19 yr. The higher V˙O2max levels of athletes may be partially explained by training-induced higher plasma and blood volumes, as well as other training adaptations. Since Hbmass at age 16 yr varies substantially and the development of Hbmass in late adolescence is comparably small and not influenced by endurance training, Hbmass at age 16 yr is an important predictor for Hbmass at adult age and possibly for the aptitude for high-level endurance performance.