Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvement of bendability in Fusion AA3003/AA6xxx sheets with different clad thickness after artificial aging

Abstract An ingot of AA6xxx Al–Si–Mg–Cu alloy clad with AA3003 Al–Mn alloy was co-cast by Fusion technology, processed to different final gauges and artificially aged to different strengths. The influence of artificial aging and cladding thickness on the strength bendability relationship was investigated. It has been demonstrated that a cladding with better bend performance than the core material can significantly improve the bendability. For AA6xxx alloy clad with AA3003 alloy, the bendability is also improved when the material is artificially aged, before and after peak aging. While the absolute level of bendability is dependent on the cladding thickness to some extent, bend performance is significantly improved even when the thickness of cladding is less than the mean grain size.
Reproducing Field Failures for Programs with Complex Grammar-Based Input

To isolate and fix failures that occur in the field, after deployment, developers must be able to reproduce and investigate such failures in-house. In practice, however, bug reports rarely provide enough information to recreate field failures, thus making in-house debugging an arduous task. This task becomes even more challenging for programs whose input must adhere to a formal specification, such as a grammar. To help developers address this issue, we propose an approach for automatically generating inputs that recreate field failures in-house. Given a faulty program and a field failure for this program, our approach exploits the potential of grammar-guided genetic programming to iteratively find legal inputs that can trigger the observed failure using a limited amount of runtime data collected in the field. When applied to 11 failures of 5 real-world programs, our approach was able to reproduce all but one of the failures while imposing a limited amount of overhead.
Intrapreneurship employees' attitude and the appropriate working environment

Because of its positive impact on organizational growth and innovation, intrapreneurship has attracted interest in recent times. While its positive impact on organizations benefitted from extensive research over the last years, research on the willingness of employees to adopt intrapreneurial behavior remains low. This paper therefore aims to evaluate the attitudes of employees towards intrapreneurial behavior at work and what kind of working environments are suitable to encourage such behavior. Thereby, the potential risk related to such behavior is placed in the wider risk literature and then critically analyzed. The paper provides a theoretical background on intrapreneurship evincing the development of terms and definitions and identifying relevant authors in this research area. Based on previous research, the analysis of data provides new insights on employees' willingness to adopt intrapreneurial behavior and what working environments might be appropriate to support such behavior and enriches and deepens the understanding of these aspects. The findings show most respondents tended to aspire to intrapreneurial behavior and felt positively motivated towards shaping the organization's future. However, the related working environments are not always suitable and supportive for intrapreneurial behavior. Future research and the collection of further data could further enhance the understanding of employees' behavior and motivation related to intrapreneurship and a distinction of employees' and employers' thoughts might help to gain new knowledge in this field.
Identification of the midline by obese and non‐obese women during late pregnancy

During central neuraxial blockade, identifying the midline in parturients can be difficult, particularly if they are obese. We assessed the ability of women in late pregnancy, both obese and non‐obese, to identify the midline of their own back by pointing and by pinprick discrimination with reference to the true midline identified by ultrasound. Thirteen out of 25 (52%) obese women were accurate to within 5 mm in identifying the midline of their back by pointing with their fingertip, compared with 21/25 (84%) non‐obese women (p = 0.03). The median (IQR [range]) fingertip‐midline distance was greater in obese women (5 (5–10 [0–10]) mm compared with non‐obese women (2 (0–5 [0–12]) mm; p = 0.007). Identification of the midline using pinprick was poorer by obese women (median (IQR [range]) 33 (25–45 [3–85]) mm) than by non‐obese women (18 (13–25 [8–40]) mm; p < 0.0001). However, women in both groups were correct > 99% of the time in identifying that a stimulus was either to the left or to the right side.
Impact of IT Governance and IT Capability on Firm Performance

ABSTRACT Based on resource-based and strategic choice theory, this research empirically validates that IT governance is an important antecedent of IT capability, which in turn results in improved firm performance. This article contributes to the IS literature by proposing a comprehensive measure of IT governance based on secondary data, and simultaneously examining the impact of IT governance and IT capability on firm performance.
Comparison Based Learning from Weak Oracles

There is increasing interest in learning algorithms that involve interaction between human and machine. Comparison-based queries are among the most natural ways to get feedback from humans. A challenge in designing comparison-based interactive learning algorithms is coping with noisy answers. The most common fix is to submit a query several times, but this is not applicable in many situations due to its prohibitive cost and due to the unrealistic assumption of independent noise in different repetitions of the same query. In this paper, we introduce a new weak oracle model, where a non-malicious user responds to a pairwise comparison query only when she is quite sure about the answer. This model is able to mimic the behavior of a human in noise-prone regions. We also consider the application of this weak oracle model to the problem of content search (a variant of the nearest neighbor search problem) through comparisons. More specifically, we aim at devising efficient algorithms to locate a target object in a database equipped with a dissimilarity metric via invocation of the weak comparison oracle. We propose two algorithms termed WORCS-I and WORCS-II (Weak-Oracle Comparison-based Search), which provably locate the target object in a number of comparisons close to the entropy of the target distribution. While WORCS-I provides better theoretical guarantees, WORCS-II is applicable to more technically challenging scenarios where the algorithm has limited access to the ranking dissimilarity between objects. A series of experiments validate the performance of our proposed algorithms.
Determination of the dynamics of micromachined lateral suspensions in the scanning electron microscope

A lateral suspension, suitable for a microseismometer application, has been fabricated using deep reactive-ion etching. The critical dynamic parameters of the suspension, namely the normal modes along the compliant axis and the damping, have been determined from slow-scan imaging in an environmental scanning electron microscope. The results show the presence of an unwanted spurious mode which can be attributed to the finite mass of the suspension. An analytical solution yields good agreement with observations. Damping is shown to be dominated by viscous effects, with the suspension material only limiting performance at high vacuum.
Diabetes and fractures: an overshadowed association

Purpose of reviewTo review recent literature on fracture risk in patients with type 1 and type 2 diabetes. Recent findingsObservational and population studies have reported a higher risk of fractures in patients with type 1 and type 2 diabetes, especially at the hip. Type 2 diabetic patients have a higher bone mineral density compared with the general population, and yet, remain unprotected from fractures. Type 1 diabetic patients have a greater risk of fractures and a lower bone mineral density compared with the general population. Their lower bone mineral density, however, does not fully account for the raised fracture risk. Therefore, impaired bone quality rather than lower bone density appears to mediate the increased fracture risk in patients with type 1 and 2 diabetes.Recently, studies have shown an association between advanced glycation end products with increased fracture risk in diabetic patients. These studies support the hypothesis of poor glycemic control and chronic hyperglycemia having a direct detrimental effect on bone quality. In addition, increased fracture risk has been reported in patients with peripheral and autonomic neuropathy, recurrent hypoglycemic events, vitamin D deficiency, and those receiving thiazolidinedione therapy. SummaryDiabetes is associated with an increased risk of fractures in patients with type 1 and type 2 diabetes. Appropriate measures aimed at fracture prevention should be considered in the complex care of the diabetic patient.
Resistive switching memories based on metal oxides: mechanisms, reliability and scaling

With the explosive growth of digital data in the era of the Internet of Things (IoT), fast and scalable memory technologies are being researched for data storage and data-driven computation. Among the emerging memories, resistive switching memory (RRAM) raises strong interest due to its high speed, high density as a result of its simple two-terminal structure, and low cost of fabrication. The scaling projection of RRAM, however, requires a detailed understanding of switching mechanisms and there are potential reliability concerns regarding small device sizes. This work provides an overview of the current understanding of bipolar-switching RRAM operation, reliability and scaling. After reviewing the phenomenological and microscopic descriptions of the switching processes, the stability of the low- and high-resistance states will be discussed in terms of conductance fluctuations and evolution in 1D filaments containing only a few atoms. The scaling potential of RRAM will finally be addressed by reviewing the recent breakthroughs in multilevel operation and 3D architecture, making RRAM a strong competitor among future high-density memory solutions.
Exploring the Metabolism of (+)-[18F]Flubatine In Vitro and In Vivo: LC-MS/MS Aided Identification of Radiometabolites in a Clinical PET Study †

Both (+)-[18F]flubatine and its enantiomer (−)-[18F]flubatine are radioligands for the neuroimaging of α4β2 nicotinic acetylcholine receptors (nAChRs) by positron emission tomography (PET). In a clinical study in patients with early Alzheimer’s disease, (+)-[18F]flubatine ((+)-[18F]1) was examined regarding its metabolic fate, in particular by identification of degradation products detected in plasma and urine. The investigations included an in vivo study of (+)-flubatine ((+)-1) in pigs and structural elucidation of formed metabolites by LC-MS/MS. Incubations of (+)-1 and (+)-[18F]1 with human liver microsomes were performed to generate in vitro metabolites, as well as radiometabolites, which enabled an assignment of their structures by comparison of LC-MS/MS and radio-HPLC data. Plasma and urine samples taken after administration of (+)-[18F]1 in humans were examined by radio-HPLC and, on the basis of results obtained in vitro and in vivo, formed radiometabolites were identified. In pigs, (+)-1 was monohydroxylated at different sites of the azabicyclic ring system of the molecule. Additionally, one intermediate metabolite underwent glucuronidation, as also demonstrated in vitro. In humans, a fraction of 95.9 ± 1.9% (n = 10) of unchanged tracer remained in plasma, 30 min after injection. However, despite the low metabolic degradation, both radiometabolites formed in humans could be characterized as (i) a product of C-hydroxylation at the azabicyclic ring system, and (ii) a glucuronide conjugate of the precedingly-formed N8-hydroxylated (+)-[18F]1.
Possible Transitions Between Types of Pseudoknots of RNA Structure

There are several dynamic programming methods for predicting RNA secondary structures with pseudoknots, but reasonable and efficient ways which are constructed by some kinds of structures is difficult, the structure can be equipped with prescribed and expected energies in RNAlocmin. In this paper. According to the BHG and MFE principle, we present the algorithms to improve theγ1-structure in Boltzmann sampling. The experiments by the software package called gfold indicates that improving γ1-structure as an instance is very efficient, and we also implement the transitions between different types of pseudoknots.
Artificial Neural Network Learning Enhancement using Bacterial Foraging Optimization Algorithm

The artificial neural network (ANN) is a mathematical model capable of representing any non-linear relationship between input and output data. ANN is an abstract representation of the biological nervous system which has the ability to solve many complex problems. It has been successfully applied to a wide variety of classification and function approximation problems. The information processing capability of artificial neural networks (ANNs) is related to its architecture and weights. To have a high efficiency in ANN, selection of an appropriate architecture and learning algorithm is very important. In this study, the adaption of neural network connection weights using Bacterial Foraging Optimization Algorithm (BFO) is proposed as a mechanism to improve the performance of Artificial Neural Network in classification of Software Defect Dataset. The problem concerns the classification of software as defective or non defective on the basis of software metrics data. The results show that BFOANNs have better accuracy than traditional ANNs. The experimental results showed that BFOA-ANN has an improvement of 2.55 % in software defect prediction accuracy than the original feed forward artificial neural network and 2.80 % in case of cascade forward neural network. General Terms Learning enhancement, Optimization
Production management systems - a CIM perspective

Find the secret to improve the quality of life by reading this production management systems a cim perspective. This is a kind of book that you need now. Besides, it can be your favorite book to read after having this book. Do you ask why? Well, this is a book that has different characteristic with others. You may not need to know who the author is, how well-known the work is. As wise word, never judge the words from who speaks, but make the words as your good value to your life.
Scientific Workflow Clustering and Recommendation Leveraging Layer Hierarchical Analysis

This article proposes an approach for identifying and recommending scientific workflows for reuse and repurposing. Specifically, a scientific workflow is represented as a layer hierarchy, which specifies hierarchical relations between this workflow, its sub-workflows, and activities. Semantic similarity is calculated between layer hierarchies of workflows. A graph-skeleton based clustering technique is adopted for grouping layer hierarchies into clusters. Barycenters in each cluster are identified, which refer to core workflows in this cluster, for facilitating cluster identification and workflow ranking and recommendation. Experimental evaluation shows that our technique is efficient and accurate on ranking and recommending appropriate clusters and scientific workflows with respect to specific requirements of scientific experiments.
Role of Social Environmental Protective Factors on Anxiety and Depressive Symptoms Among Midwestern Homeless Youth

We employ a social stress framework, which examines the influence of multiple stressors (e.g., physical abuse, foster care placement) on an individual's ability to function (e.g., mental well-being), to longitudinally examine the effects of stressful life events on mental health and the role of the social environment in this process among 150 homeless youth. Results revealed that numerous stressors, such as physical abuse and running away from home more frequently, were associated with greater depressive symptoms and elevated anxiety. Having mentors and family and friends from home that youth can rely on resulted in more positive social support, which subsequently lowered the risk for depressive symptoms and anxiety at wave 2.
CFD Investigation of Flow Structures in Rotor-Stator Disc Cavity Systems

Ingestion of hot gas from the main annulus to the rotor-stator disc cavity is a major concern related to industrial turbines. Fluctuating pressure structures which are previously shown to form inside the disc cavity can influence the gas ingestion from the main flow stream. These rotating low pressure regions can reduce the lifetime of the turbine by overheating the components, induced by ingestion of hot gas, and influencing the mechanical integrity of the device. The hot gas ingestion is usually reduced by supplying a cooling air stream to the cavity and a proper rim seal design. The amount of the cooling air however needs to be minimized so as not to adversely affect the turbine performance and efficiency. A preliminary numerical study was conducted using computational fluid dynamics (CFD) on a one-stage test turbine in order to investigate the flow structure and pressure distribution in the turbine disc cavity. The test turbine consists of a newly designed blisk which is soon to be installed at Energy department, Royal Institute of Technology (KTH). The cavity model was simplified including the front cavity and only a section of the main annulus with no blades. The geometry of the rim seal was modified in the model by using a larger clearance in order to increase the probability of capturing the unsteady pressure structures. In order to obtain the boundary conditions to the cavity model, the main annulus was simulated separately using a sector model. The influence of the purge air mass flow rate on the flow structure and gas ingestion was further investigated. The results showed recirculation of the flow inside the cavity. Alternating ingress and egress through the rim seal was observed for the low purge case, while the cavity was totally sealed at high purge flow. No unsteady pressure structures were detected by the results of this study. The model needs however to be improved in order to obtain more reliable results.
Behavior of wood in transverse compression

A finite element analysis program exists to evaluate the stress distribution in wood members subjected to perpendicular-to-grain (transverse) compression. In this study, the program was used to perform parameter studies to evaluate the effects of key variables on the distribution of stresses and the maximum stress concentrations in wood subjected to transverse compression. These variables included: specimen geometry (length/depth), loading geometry (loaded length/specimen length), and material properties (ratio of moduli of elasticity of the wood in the direction of loading/perpendicular to loading). The results showed that a complex state of stress exists in members even when the load is distributed over the entire specimen surface. In particular, numerically-determined stresses nearly 3.5 times the nominal stress were found for certain combinations of input parameters. In addition, an empirically-derived equation is presented that estimates the magnitude of maximum stress concentration as a function of the three parameters investigated. The equation was developed with the use of multiple regression techniques and had a correlation coefficient of 0.958.
Learning-based human detection applied to RGB-D images

Accurate human detection is still a challenging topic due to complicated environments in the real world. In addition, the RGB-D cameras are becoming popular at reasonable price, such as Microsoft Kinect sensor, which provides both RGB and depth data. The depth information often helpful for detection. We adopt the R-CNN method in this paper, which combines the Selective Search technique to generate region proposals and the CNNs (Convolutional Neural Networks) to learn features. A depth map encoding technique (HHA) is adopted to match the CNNs format for learning features. The HHA and RGB images are our inputs. We propose several algorithms to combine their information in constructing various human detectors. Our information fusion structures include CNN, SVM together with PCA for features reduction. More accurate human detection results are shown with the aid of depth information.
Ultrasensitive hot-electron kinetic-inductance detectors

While experimental studies of kinetic-inductance sensors have been limited so far by the temperature range near the superconducting transition, these detectors can be very sensitive at temperatures well below the transition, where the number of equilibrium quasiparticles is exponentially small. In this regime, a shift of the quasiparticle chemical potential under radiation results in the change of the kinetic inductance, which can be measured by a sensitive SQUID readout. We modeled the kinetic inductance response of detectors made from disordered superconducting Nb, NbC, and MoRe films. Low phonon transparency of the interface between the superconductor and the substrate causes substantial re-trapping of phonons providing high quantum efficiency and the operating time of ∼1 ms at ≈1 K. Due to the small number of quasiparticles, the noise equivalent power of the detector determined by the quasiparticle generation-recombination noise can be as small as ∼10−19 W/√Hz at He4 temperatures.
EGF induces epithelial-mesenchymal transition through phospho-Smad2/3-Snail signaling pathway in breast cancer cells

Epithelial-mesenchymal transition (EMT) can contribute to tumor invasion, metastasis, and resistance to chemotherapy or hormone therapy. EMT may be induced by a variety of growth factors, such as epidermal growth factor (EGF). Most studies regarding EMT have focused on TGF-β-Smads signaling. The mechanism of EGF-induced EMT via activation of the Smad2/3 in breast cancer cells, MCF-7 and MDA-MB-231, remains unclear. The expression levels of Snail, vimentin, and fibronectin were increased by EGF treatment in a time-dependent manner, while the expression level of E-cadherin was decreased. EGF-induced nuclear co-localization of phospho-Smad2/3 and Snail and cancer cell migration were inhibited by pretreatment with an ERK1/2 inhibitor, PD98059 and a phospho-Smad2 inhibitor, SB203580. Knockdown of Smad2/3 expression suppressed EGF-induced expressions of Snail, vimentin, fibronectin, and cancer cell invasion, suggesting an acquisition of the mesenchymal and migratory phenotype in less aggressive MCF-7 cells. Moreover, MDA-MB-231 cells were shown that EGF-induced EMT, and cell invasion through ERK1/2-phospho-Smad2/3-Snail signaling pathway. We have discovered that EGF-stimulated activation of Smad2/3 upregulated several key EMT markers, inhibited E-cadherin expression, promoted EMT, enhanced migration and invasion in MCF-7 and MDA-MB-231 breast cancer cells. Identification of this molecular mechanism may provide new molecular targets for the development of therapies for metastatic breast cancer.