Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Estimation of the Minimal Resistance Threshold. Case Study of Automotive Heat Exchangers

In the automotive industry, when a component undergoes a request to extend its warranty period (up to 5 or 8 years), the risk assessment needs to consider not only the failures related to non-quality, but also all possible issues originating from wear-out phenomena (durability design failures). The correct identification of a failure-free period affecting wear-out failure mechanisms, such as fatigue or corrosion, is indeed beneficial for reliability of components with a longer warranty period. The durability of the components is experimentally demonstrated by the means of accelerated life tests. Unfortunately, due to the relatively small sample size considered (4 to 8 samples), the location parameter of a three-parameter unimodal distribution (for example Weibull) leads to a failure-free period with an unacceptable level of statistical uncertainty. In this paper, we propose a new methodology for the calculation of the failure-free period defined as a “minimum resistance threshold” (MRT). This threshold is obtained as a weakly scattered deterministic value, from a small population of samples undergoing destructive durability tests. The proposed estimation method is analytically simple and robust. Both physics-of- failure and statistical criteria need to be considered to justify the applicability of the method. The suggested approach makes it possible to obtain an estimator of the location parameter in the case of an ordered sample of small size, without making any a priori hypothesis on the nature of the parent distribution. Several numerical examples will emphasize the advantages of this methodology applied to the risk assessment of design-related warranty failures.
Community‐acquired Klebsiella pneumoniae liver abscesses — an “emerging disease” in Australia

TO THE EDITOR: Further to the recent article by Anstey and colleagues on community-acquired Klebsiella pneumoniae liver abscesses, we report two similar cases at our hospital in late 2010. Case 1: A 55-year-old Indonesian-born man was referred from general practice in October 2010 with a 5-day history of fever and progressive epigastric pain. He did not have diabetes, but did have dyslipidaemia. He had migrated from Indonesia in the 1980s; his most recent visit to Indonesia was in January 2010, for 3 weeks. As he had mildly deranged liver function test results, he was investigated with abdominal ultrasound and computed tomography (CT). Both showed a large multiseptate collection in the left lobe of the liver (Box, A). The liver collection was drained under radiological guidance, yielding a pure growth of K. pneumoniae. Urine culture was also positive for an identical isolate of K. pneumoniae. This man had a rapid clinical response to percutaneous drainage and was discharged on oral ciprofloxacin therapy.
Dynein/dynactin regulate metaphase spindle length by targeting depolymerizing activities to spindle poles

During cell division metaphase spindles maintain constant length, whereas spindle microtubules continuously flux polewards, requiring addition of tubulin subunits at microtubule plus-ends, polewards translocation of the microtubule lattice, and removal of tubulin subunits from microtubule minus-ends near spindle poles. How these processes are coordinated is unknown. Here, we show that dynein/dynactin, a multi-subunit microtubule minus-end–directed motor complex, and NuMA, a microtubule cross-linker, regulate spindle length. Fluorescent speckle microscopy reveals that dynactin or NuMA inhibition suppresses microtubule disassembly at spindle poles without affecting polewards microtubule sliding. The observed uncoupling of these two components of flux indicates that microtubule depolymerization is not required for the microtubule transport associated with polewards flux. Inhibition of Kif2a, a KinI kinesin known to depolymerize microtubules in vitro, results in increased spindle microtubule length. We find that dynein/dynactin contribute to the targeting of Kif2a to spindle poles, suggesting a model in which dynein/dynactin regulate spindle length and coordinate flux by maintaining microtubule depolymerizing activities at spindle poles.
The Weak Science of Human-Computer Interaction

This article is about science and the discipline of humancomputer interaction (HCI). Science in HCI is merely one component of a wider agenda; alone science is not sufficient for ‘good’ HCI (whatever that is). We argue that science is necessary, but the way that science is undertaken—or purported to be undertaken—in HCI is inadequate. Failures are due to the sparsity of theories and risky hypotheses, the pragmatic difficulty of substantiating experiments through replication, and the over-generalization of experimental results.
Computational Modeling of Flow Rate Measurements Using an Orifice Flow Meter

This study is concerned with understanding and improvement of mass flow rate measurement uncertainty and errors encountered at low flow rates and start-up in commercially available flow rate measurement devices, such as orifice flow meters. The flow through a typical cylindrical flange-tapped orifice flow meter is modeled computationally so the actual mass flow rate is known a-priori. Empirical predictions from the reading of “virtual” pressure sensors are compared with the actual flow rate and the measurement errors are quantified and analyzed. Commercial code ANSYS-Fluent is compared in this study to the in-house high-fidelity spectral-element solver Nek5000, so that conclusions about the applicability of a commercial code to the calculations of measurement uncertainty in the orifice flow meters can be made.
Combining Fuzzy partitions Using Fuzzy Majority Vote and KNN

this paper firstly generalizes majority vote to fuzzy majority vote, then proposes a cluster matching algorithm that is able to establish correspondence among fuzzy clusters from different fuzzy partitions over a common data set. Finally a new combination model of fuzzy partitions is build on the basis of the proposed cluster matching algorithm and fuzzy majority vote. Comparative results show that the proposed combination model is able to foster strengths and circumvent weaknesses of component fuzzy partitions and to combine the component fuzzy partitions into a better fuzzy partition than any of component fuzzy partitions and those resulted from two current combination models of fuzzy partitions.
Journal of Economic Behavior & Organization the Effects of Personality Traits on Adult Labor Market Outcomes: Evidence from Siblings

While large literatures have shown that cognitive ability and schooling increases employment and wages, an emerging literature examines the importance of so-called " non-cognitive skills " in producing labor market outcomes. However, this smaller literature has not typically used causal methods in estimating the results. One source of heterogeneity that may play an important role in producing both personality and other non-cognitive skills and labor market outcomes is family background, including genetic endowments. This paper is the first to use sibling differences to estimate the associations between personality on employment and wages and is also able to control for many other sources of heterogeneity, including attractiveness, cognitive ability, schooling, occupation, and other factors. Overall, the findings suggest that personality measures have important associations with labor market outcomes in adulthood and that the results vary considerably by demographic group. The findings also highlight the potential role of extraversion in being associated with favorable labor market outcomes, which has not been documented in many other studies.
An Improved SAC-Based Deep Reinforcement Learning Framework for Collaborative Pushing and Grasping in Underwater Environments

Autonomous grasping is a fundamental task for underwater robots, but direct grasping for tightly stacked objects will lead to collisions and grasp failures, which requires pushing actions to separate the target object and increase grasp success (GS) rates. Hence, this article proposes a novel approach by employing an improved soft actor–critic (SAC) algorithm within a deep reinforcement learning (RL) framework for achieving collaborative pushing and grasping actions. The developed scheme employs an end-to-end control strategy that maps input images to actions. Specifically, an attention mechanism is introduced in the visual perception module to extract the necessary features for pushing and grasping actions to enhance the training strategy. Moreover, a novel pushing reward function is designed, comprising a per-object distribution function around the target and a global object distribution assessment network named PA-Net. Furthermore, an enhanced experience replay strategy is introduced to address the sparsity issue of grasp action rewards. Finally, a training environment for underwater manipulators is established, in which variations in light, water flow noise, and pressure effects are incorporated to simulate underwater work conditions more realistically. The simulation and real-world experiments demonstrate that the proposed learning strategy efficiently separates target objects and avoids inefficient pushing actions, achieving a significantly higher GS rate.
Orthogonal polynomial expansions for
the Riemann xi function in the
Hermite, Meixner–Pollaczek, and continuous Hahn bases

will appear on the journal’s web site only) Pál Turán in the 1950s proposed to use the expansion of the Riemann xi function in the Hermite polynomials as a tool to gain insight into the location of the zeros of the Riemann zeta function. In this paper we follow up and expand on Turán’s ideas in several ways by considering infinite series expansions for the Riemann xi function Ξ(t) in three specific families of orthogonal polynomials: (1) the Hermite polynomials; (2) the symmetric Meixner–Pollaczek polynomials P (3/4) n (x;π/2); and (3) the continuous Hahn polynomials pn ( x; 34 , 3 4 , 3 4 , 3 4 ) . For each of the three expansions we derive asymptotic formulas for the coefficients and prove additional results. We also apply some of the same techniques to prove a new asymptotic formula for the Taylor coefficients of the Riemann xi function, and uncover a previously unnoticed connection between the Hermite expansion of Ξ(t) and the separate program of research involving the de Bruijn–Newman constant.
Tongue drive: a tongue operated magnetic sensor based wireless assistive technology for people with severe disabilities

The "tongue drive" system is a tongue-operated assistive technology developed for people with severe disability to control their environment. The tongue is considered an excellent appendage in severely disabled people for operating an assistive device. Tongue Drive consists of an array of Hall-effect magnetic sensors mounted on a dental retainer on the outer side of the teeth to measure the magnetic field generated by a small permanent magnet secured on the tongue. The sensor signals are transmitted across a wireless link and processed to control the movements of a cursor on a computer screen or to operate a powered wheelchair, a phone, or other equipments. The principal advantage of this technology is the possibility of capturing a large variety of tongue movements by processing a combination of sensor outputs. This would provide the user with a smooth proportional control as opposed to a switch based on/off control that is the basis of most existing technologies. We modeled the effects of position and orientation of the permanent magnet on the sensors in FEMLAB and experimentally measured them. We built a prototype system using off-the-shelf components and tested it successfully by developing a graphical user interface (GUI) in LabVIEW environment. A small battery powered wireless mouthpiece with no external component is under development
Cross-Project Defect Prediction Using Transfer Learning with Long Short-Term Memory Networks

With the increasing number of software projects, within-project defect prediction (WPDP) has already been unable to meet the demand, and cross-project defect prediction (CPDP) is playing an increasingly significant role in the area of software engineering. The classic CPDP methods mainly concentrated on applying metric features to predict defects. However, these approaches failed to consider the rich semantic information, which usually contains the relationship between software defects and context. Since traditional methods are unable to exploit this characteristic, their performance is often unsatisfactory. In this paper, a transfer long short-term memory (TLSTM) network model is first proposed. Transfer semantic features are extracted by adding a transfer learning algorithm to the long short-term memory (LSTM) network. Then, the traditional metric features and semantic features are combined for CPDP. First, the abstract syntax trees (AST) are generated based on the source codes. Second, the AST node contents are converted into integer vectors as inputs to the TLSTM model. Then, the semantic features of the program can be extracted by TLSTM. On the other hand, transferable metric features are extracted by transfer component analysis (TCA). Finally, the semantic features and metric features are combined and input into the logical regression (LR) classifier for training. The presented TLSTM model performs better on the f-measure indicator than other machine and deep learning models, according to the outcomes of several open-source projects of the PROMISE repository. The TLSTM model built with a single feature achieves 0.7% and 2.1% improvement on Log4j-1.2 and Xalan-2.7, respectively. When using combined features to train the prediction model, we call this model a transfer long short-term memory for defect prediction (DPTLSTM). DPTLSTM achieves a 2.9% and 5% improvement on Synapse-1.2 and Xerces-1.4. 4, respectively. Both prove the superiority of the proposed model on the CPDP task. This is because LSTM capture long-term dependencies in sequence data and extract features that contain source code structure and context information. It can be concluded that: (1) the TLSTM model has the advantage of preserving information, which can better retain the semantic features related to software defects; (2) compared with the CPDP model trained with traditional metric features, the performance of the model can validly enhance by combining semantic features and metric features.
An empirical study on the estimation of software development effort with use case points

Empirical studies are important in software engineering to evaluate new tools, techniques, methods and technologies in a structured way before they are introduced in the industrial (real) software process. Perform empirical studies in a real context is very difficult due to various obstacles, so, we intend to create a stable environment that allows us to perform reliably empirical studies with students. This paper describes a case study with 104 students grouped in seven teams that developed a software system (Web application) for a real costumer. In this study we used a model based on Use Case Points (UCP) to estimate the resources needed to develop a software system.
Effect of kinesio taping on standing balance in subjects with multiple sclerosis: A pilot study\m{1}.

OBJECTIVE The aim of this study was to assess the effect of Kinesio Taping on body stability in subjects with MS. STUDY DESIGN Non controlled intervention study in a Rehabilitation Unit. INTERVENTION A consecutive convenience sample of 15 individuals with multiple sclerosis was assessed. Kinesio Tex Tape was applied directly to the skin of both calves and kept for the next two days. MAIN OUTCOME MEASURES Clinical and stabilometric assessments were performed at baseline, immediately after application of the tape and the day after its removal. To control for learning effect 10 subject with multiple sclerosis were tested repeatedly under the same conditions without tape. RESULTS No statistically or clinically relevant differences were observed among conditions in the mediolateral plane. In the AP plane Friedman's ANOVA showed statistically significant differences between baseline and taping condition with respect to length of sway. A trend towards statistically relevant differences were found also with respect to mean sway and velocity of sway. No learning effect was found for repeated testing within the no treated group. CONCLUSIONS These preliminary results suggest that the use of ankle taping may be useful in immediately stabilising body posture.
Flexural Properties and Failure Mechanisms of Short-Carbon-Fiber-Reinforced Polylactic Acid Composite Modified with MXene and GO

Recently, short-fiber-reinforced thermoplastic composites (SFRTPCs) have been playing a more and more crucial role in the application of automotive interior materials due to their advantages of low density and environmental resistance properties. However, their relevant mechanical properties need to be optimized. Previous investigations revealed that the surface modification of fibers is useful to improve their mechanical properties. In this work, carbon fiber (CF)-reinforced polylactic acid (PLA) composites modified with MXene and graphene oxide (GO) were prepared by twin-screw extrusion and injection molding methods. Short CF was firstly modified with polyetherimide (PEI), then different weight ratios of MXene-GO (1:1) were subsequently modified on PEI-CF. Finally, the flexural properties and failure mechanisms were analyzed. The results showed that MXene-GO was successfully coated on CF surface, and the flexural strength and modulus of CF-PEI-MXene-GO-reinforced PLA (CF-PEI-MG/PLA) composite were improved compared to that of CF/PLA composite. In addition, the fracture sections of the composites were flat and white, and the fibers bonded well with PLA for CF-PEI-0.1MG/PLA composite compared to CF/PLA composite. The present study could provide a reference for further improving the mechanical performance of PLA-related composites.
A Framework for A Framework for A Framework for A Framework for SSSSeeeeccccure Cloud ure Cloud ure Cloud ure Cloud ComputingComputingComputingComputing

Cloud computing is one of the most discussed topics today in the field of information technology. It introduces a new Internet-based environment for on-demand, dynamic provision of reconfigurable computing resources. The biggest challenge in cloud computing is the security and privacy problems caused by its multi-tenancy nature and the outsourcing of infrastructure, sensitive data and critical applications. In this paper, we propose a framework that identifies security and privacy challenges in cloud computing. It highlights cloud-specific attacks and risks and clearly illustrates their mitigations and countermeasures. We also propose a generic cloud computing security model that helps satisfy security and privacy requirements in the clouds and protect them against various vulnerabilities. The purpose of this work is to advise on security and privacy considerations that should be taken and solutions that might be considered when using the cloud environment by individuals and organizations.
A performance-weighted mixture of LMS filters

In this paper, we explore the use of a particular multistage adaptation algorithm for a variety of adaptive filtering applications where the structure of the underlying process to be estimated is unknown. The proposed algorithm uses a performance-weighted mixture of LMS filters of various orders to construct its final output. The algorithm is analyzed in a stochastic context with respect to its convergence and mean-square error (MSE) behaviors and is shown to achieve the best MSE performance of the constituent algorithms in the mixture. Through simulations, it has been observed that the mixture structure can offer considerable performance improvement for both stationary and time varying observation sequences.
Impacts of warming and elevated CO2 on a semi-arid grassland are non-additive, shift with precipitation, and reverse over time.

It is unclear how elevated CO2 (eCO2 ) and the corresponding shifts in temperature and precipitation will interact to impact ecosystems over time. During a 7-year experiment in a semi-arid grassland, the response of plant biomass to eCO2 and warming was largely regulated by interannual precipitation, while the response of plant community composition was more sensitive to experiment duration. The combined effects of eCO2 and warming on aboveground plant biomass were less positive in 'wet' growing seasons, but total plant biomass was consistently stimulated by ~ 25% due to unique, supra-additive responses of roots. Independent of precipitation, the combined effects of eCO2 and warming on C3 graminoids became increasingly positive and supra-additive over time, reversing an initial shift toward C4 grasses. Soil resources also responded dynamically and non-additively to eCO2 and warming, shaping the plant responses. Our results suggest grasslands are poised for drastic changes in function and highlight the need for long-term, factorial experiments.
On the origin of the broad, relativistic iron line of MCG{6-30-15 observed by XMM-Newton

The relativistic iron line prole recently observed by XMM-Newton in the spectrum of the Seyfert 1 galaxy MCG{6-30-15 (Wilms et al. 2001) is discussed in the framework of the lamp-post model. It is shown that the steep disc emissivity, the large line equivalent width and the amount of Compton reflection can be self-consistently reproduced in this scenario.
Decline of T3 and Elevation in Reverse T3 Induced by Hyperglucagonemia: Changes in Thyroid Hormone Metabolism, Not Altered Release of Thyroid Hormone

Recently we reported that hyperglucagonemia induced by glucagon infusion causes a decline in serum Triiodothyronine (T3) and a rise in reverse T3 (rT3) in euthyroid healthy volunteers. These changes in T3 and rT3 levels were attributed to altered T4 metabolism in peripheral tissues. However, the contribution of altered release of thyroid hormones by the thyroid gland could not be excluded. Since the release of thyroid hormones is suppressed by exogenous administration of L-thyroxine (L-T4) in appropriate dosage, we studied thyroid hormone levels for up to 6 hours after intravenous administration of glucagon in euthyroid healthy subjects after administration of L-T4 for 12 weeks. A control study was conducted using normal saline infusion. Plasma glucose rose promptly following glucagon administration demonstrating its physiologic effect. Serum T4, Free T4 and T3 resin uptake were not altered during both studies. Glucagon infusion induced a significant decline in serum T3 (P less than 0.01) and a marked rise in rT3 (P less than 0.01) whereas saline administration caused no alterations in T3 or rT3 levels. Thus the changes in T3 and rT3 were significantly different during glucagon study when compared to saline infusion. (P less than 0.01 for both comparisons). Therefore, this study demonstrates that changes in serum T3 and rT3 caused by hyperglucagonemia may be secondary to altered thyroid hormone metabolism in peripheral tissues and not due to altered release by the thyroid gland, since the release of thyroid hormones is suppressed by exogenous L-T4 administration.