Miracle-dz/UniFAR-FTUs huggingface dataset:
Sonderforschungsbereich 438 Mathematische Modellierung, Simulation Und Veriikation in Materialorientierten Prozessen Und Intelligenten Systemen Hierarchical Concepts for Improved Interfaces between Modelling, Simulation, and Visualization Hierarchical Concepts for Improved Interfaces between Modelli

Figure 8: Image compression: octree cells and sparse grid points tion. Of course, there are several issues future work has to focus on. First, numerical experiments will have to show how a voxel-based FEM code, which is developed at the moment, can compete with standard nite element programs. Furthermore, on the visual-ization side, the use of z-buuer information for the combination of surface-and voxel-based visualizations in the sense of an augmented reality, for example for integrating a free form surface CAD model of a car into the computed velocity eld of its exterior, is presently studied. Three-dimensional adaptive mesh reenement for hyperbolic conservation laws.time exploration of regular volume data by adap-tive reconstruction of iso-surfaces. Abstract Appropriate and eecient representations of domains, objects, and scenes are an important issue in the elds of geometric modelling , numerical simulation, and visualiza-tion. Though various techniques have been developed and are successfully used as single-purpose solutions, there is still some lack of comprehensive approaches that allow to base modelling, simulation, and visualization on the same representation of the underlying geometry or that ooer, at least, eecient interfaces between the diierent descriptions. In this paper, we want to discuss how hierarchical schemes can close this gap and, thus, allow a straightforward embedding of numerical simulations into a more general context.
Generating Cubic Splines on Level Sets

This report looks at employing optimization techniques to generate cubic splines restricted to lie on the surfaces. We implement a recent algorithm designed for exactly this problem, and attempt to understand its motivation and examine its effectiveness. We also pose the problem in AMPL and apply a standard nonlinear solver to verify our results, and to compare the relative benefits of using this new algorithm over more traditional approaches.
Moving object tracking research based on active vision

In an active vision condition both camera and object may move simultaneously and common motion detection methods could not deal with such situation. To overcome the shortcoming of common motion detection, a background-matching algorithm was proposed to solve such problem. When motion was detected, a Kalman predictor was used to estimate the object's position in the image. Combining increment PID controlling approach with dead zone, the camera can track the moving object steadily and reliably. The experiments proved the effectiveness of the algorithm.
Zigbee Technology and its Application in Wireless Home Automation Systems: A Survey

Wireless home automation systems have drawn considerable attentions of the researchers for more than a decade. The major technologies used to implement these systems include Z-Wave, Insteon, Wavenis, Bluetooth, WiFi, and ZigBee. Among these technologies the ZigBee based systems have become very popular because of its low cost and low power consumption. In this paper ZigBee based wireless home automation systems have been addressed. There are two main parts of this paper. In the first part a brief introduction of the ZigBee technology has been presented and in the second part a survey work on the ZigBee based wireless home automation system has been presented. The performances of the ZigBee based systems have also been compared with those of other competing technologies based systems. In addition some future opportunities and challenges of the ZigBee based systems have been listed in this paper.
Two hits are better than one: targeting both phosphatidylinositol 3-kinase and mammalian target of rapamycin as a therapeutic strategy for acute leukemia treatment

Phosphatidylinositol 3-kinase (PI3K) and mammalian target of rapamycin (mTOR) are two key components of the PI3K/Akt/mTOR signaling pathway. This signal transduction cascade regulates a wide range of physiological cell processes, that include differentiation, proliferation, apoptosis, autophagy, metabolism, motility, and exocytosis. However, constitutively active PI3K/Akt/mTOR signaling characterizes many types of tumors where it negatively influences response to therapeutic treatments. Hence, targeting PI3K/Akt/mTOR signaling with small molecule inhibitors may improve cancer patient outcome. The PI3K/Akt/mTOR signaling cascade is overactive in acute leukemias, where it correlates with enhanced drug-resistance and poor prognosis. The catalytic sites of PI3K and mTOR share a high degree of sequence homology. This feature has allowed the synthesis of ATP-competitive compounds targeting the catalytic site of both kinases. In preclinical models, dual PI3K/mTOR inhibitors displayed a much stronger cytotoxicity against acute leukemia cells than either PI3K inhibitors or allosteric mTOR inhibitors, such as rapamycin. At variance with rapamycin, dual PI3K/mTOR inhibitors targeted both mTOR complex 1 and mTOR complex 2, and inhibited the rapamycin-resistant phosphorylation of eukaryotic initiation factor 4E-binding protein 1, resulting in a marked inhibition of oncogenic protein translation. Therefore, they strongly reduced cell proliferation and induced an important apoptotic response. Here, we reviewed the evidence documenting that dual PI3K/mTOR inhibitors may represent a promising option for future targeted therapies of acute leukemia patients.
Measurement of Sharpness and Its Application in ISAR Imaging

It is necessary to measure the sharpness of distributions in many situations. A class of functions is investigated in this paper. First, the relation between this class and sharpness is clarified, and this justifies this class as sharpness measures. Then, we analyze the performance of different sharpness measures and present a guide to select the sharpness measure. In addition, the relation of this class to the sparsity measure is addressed, which leads to a deeper understanding about sparsity. Finally, we show and discuss the application of this class in inverse synthetic aperture radar imaging.
How Latina/O Family Values Impact Student Persistence To College Graduation: A Multi-Case Study

The purpose of this multi-case study is to discover the common family values of Latino families living in Chicago that were passed down from the parent to the child and how those values may have enabled the child to complete a four-year college degree. This study employed a multi-case qualitative study design. The participants were 12 Latina/o parents in Chicago who had at least one child who had graduated from a four-year college. Data were collected from interviews, field notes, and documents. A pattern-finding approach was used for data analysis. In this study, all participants shared family values that they believed were important to teach their children. Half of the participants each said that faith and respect were important family values. Threefourths of the participants reported that their method of teaching their children these values was by modeling the behavior or by setting an example. Half of the participants reported that their children faced discrimination at some point during school. Of the 12 participants, 10 reported how they believed the family values they taught their children helped them overcome discrimination and other hardships.
2 Policy Brief Science , Technology and Innovation in the New Economy

Scientific advances and technological change are important drivers of recent economic performance. The ability to create, distribute and exploit knowledge has become a major source of competitive advantage , wealth creation and improvements in the quality of life. Some of the main features of this transformation are the growing impact of information and communications technologies (ICT) on the economy and on society; the rapid application of recent scientific advances in new products and processes; a high rate of innovation across OECD countries; a shift to more knowledge-intensive industries and services ; and rising skill requirements. These changes imply that science, technology and innovation are now key to improving economic performance and social well-being. However , if governments want to obtain the benefits from this transformation they will have to put the right policies in place. Limits on public spending, increased competition and globalisation, changes in the drivers of the innovation process, and a better understanding of the role played by science and technology in economic performance and societal change, have led governments to sharpen their policy tools. Increasingly, government must become a facilitator, enabling business and consumers to adapt to the demands and opportunities of the new economy. But there are other areas, such as investment in fundamental research and ensuring stakeholders' involvement in policy design and implementation, where an active role of government is indispensable. This Policy Brief explores the role of science, technology and innovation in the new economy and discusses the role of government in fostering scientific and technological progress for economic growth and greater social well-being. s What is the role of science, technology and innovation in the new economy? Is there other evidence that innovation is stronger? What about innovation in the services sector? What is the role of science in innovation? What role do innovation networks play? Has the environment for innovation changed? How can governments improve the environment for innovation? What is the role of government in funding science? Is government support to private R&D effective? Is government policy adjusting to innovation in the new economy? What next?
Personal possessions as cues for autobiographical remembering

An encounter with personal possessions in everyday life, such as souvenirs, jewellery, or digital photos, may bring the past back to mind. Sometimes this is a brief and fleeting memory, other times it brings back vivid memories and emotional responses. Through three qualitative studies, this PhD research investigated personal possessions as cues: The responses personal possessions evoke (called cued responses), how the item-memories relationship evolves, and what characteristics of possessions facilitate cued remembering. An understanding of this process could facilitate the design of personal possessions or systems for cuing memories, for example in the field of human-computer interaction. The findings in this thesis showed the dynamic nature of the item-memories relationship, and the ways in which cuing can be facilitated or hampered.
Identification of amino acids related to catalytic function of Sulfolobus solfataricus P1 carboxylesterase by site-directed mutagenesis and molecular modeling

The archaeon Sulfolobus solfataricus P1 carboxylesterase is a thermostable enzyme with a molecular mass of 33.5 kDa belonging to the mammalian hormone-sensitive lipase (HSL) family. In our previous study, we purified the enzyme and suggested the expected amino acids related to its catalysis by chemical modification and a sequence homology search. For further validating these amino acids in this study, we modified them using site-directed mutagenesis and examined the activity of the mutant enzymes using spectrophotometric analysis and then estimated by homology modeling and fluorescence analysis. As a result, it was identified that Ser151, Asp244, and His274 consist of a catalytic triad, and Gly80, Gly81, and Ala152 compose an oxyanion hole of the enzyme. In addition, it was also determined that the cysteine residues are located near the active site or at the positions inducing any conformational changes of the enzyme by their replacement with serine residues. [BMB Reports 2016; 49(6): 349-354]
Development of RF Energy Harvesting and Charging Circuits for Low Power Mobile Devices (信号処理)

The electrical power generated by RF energy harvesting techniques is small, depending on techniques it is enough to drive low power consumption devices. Therefore, it is possible to increase the battery life and to reduce the environmental pollution. In this paper, we focus on the RF energy harvesting and design the rectenna with a 4×4 patch antenna of 2.13 GHz for low power mobile devices. The rectenna element is a microstrip patch antenna with PTFT board of 10 dielectric constant and 1.6 mm thick that has a gain of 5.8dBi. A step-up converter is adopted the Texas Instruments TPS61220. The step-up converter is operated with load at 0.7V to 5.5V. If the output current is 1.7mA, the conversion efficiency shows 80.9%. From the evaluated results of RF energy harvesting system, the low power mobile devices such as Zigbee when we set the distance of 12m can be operated
Parallel Workload Modeling with Realistic Characteristics

Workload modeling and performance evaluation play crucial roles in the study of scheduling algorithms on large-scale parallel and distributed systems. An effective design of a scheduling algorithm for these systems requires experiments with hundreds of simulations to evaluate its performance. Since each simulation needs one workload as input, only real workloads with usually a limited availability are not sufficient, and so representative workload models are needed. Several studies have shown that realistic workload characteristics such as burstiness, bag-of-tasks, etc., cause significant performance impacts on scheduling. Therefore, we argue that realistic workload models should contain as many characteristics of real workloads as possible. In practice, researchers use unrealistic workloads in their scheduling evaluations because they lack models that can help generate realistic workloads. In this article, we analyze real parallel workloads to show the presence of important characteristics including long range dependence, periodicity and temporal burstiness of job arrivals, bag-of-tasks behavior, and correlation of runtime and number of processors. Then, we present a systematic approach to create a complete model that contains all of these characteristics. Validation of our model with real world data shows that it does not only capture the above characteristics, but also can fit marginal distributions well.
Feature leaning with deep Convolutional Neural Networks for screening patients with paroxysmal atrial fibrillation

In this paper, a novel electrocardiogram (ECG) signal classification and patient screening method is developed. The focus is on identifying patients with paroxysmal atrial fibrillation (PAF) which is a life threatening cardiac arrhythmia. The proposed approach uses the raw ECG signal as the input and automatically learns the representative features for PAF to be used by a classification mechanism. The features are learned directly from the time domain ECG signals by using a Convolutional Neural Network (CNN) with one fully connected layer. The learned features can replace the hand-crafted features and our experimental results indicate the effectiveness of the learned features in patient screening. The experimental results indicate that combining the learned features with other classifiers will improve the performance of the patient screening system as compared to an End-to-End convolutional neural network classifier. The major characteristics of the proposed approach are to simplify the process of feature extraction for different cardiac arrhythmias and to remove the need for using a human expert to specify the appropriate features. The effectiveness of the proposed ECG classification method is demonstrated through performing extensive simulation studies.
An adaptive speckle suppression filter for medical ultrasonic imaging

An adaptive smoothing technique for speckle suppression in medical B-scan ultrasonic imaging is presented. The technique is based on filtering with appropriately shaped and sized local kernels. For each image pixel, a filtering kernel, which fits to the local homogeneous region containing the processed pixel, is obtained through a local statistics based region growing technique. The performance of the proposed filter has been tested on the phantom and tissue images. The results show that the filter effectively reduces the speckle while preserving the resolvable details. The simulation results are presented in a comparative way with two existing speckle suppression methods.
Examining the Relationship between Organizational Justice and Job Performance

The main purpose of this study is to examine the role of organizational justice on job performance of employees in a selected private manufacturing company in Malaysia. This study which empirically examined the direct effect of perceived distributive, procedural and interactional justice on job performance employed a quantitative research method and involved a total of 142 respondents. Prior to actual study, a pilot study was conducted in order to assess the reliability and appropriateness of the measurements used. The data gathered was analysed by using SPSS Version 23. The research finding showed a positive association between distributive, procedural and interactional justice on employees’ job performance. The findings also showed that distributive justice tend to be the strongest contributor of employees’ job performance compared to procedural justice and interactional justice. Theoretical discussion, practical implications, limitations of the study and suggestions for future research were also being discussed.
Utility of Health Facility-based Malaria Data for Malaria Surveillance

Background Currently, intensive malaria control programs are being implemented in Africa to reduce the malaria burden. Clinical malaria data from hospitals are valuable for monitoring trends in malaria morbidity and for evaluating the impacts of these interventions. However, the reliability of hospital-based data for true malaria incidence is often questioned because of diagnosis accuracy issues and variation in access to healthcare facilities among sub-groups of the population. This study investigated how diagnosis and treatment practices of malaria cases in hospitals affect reliability of hospital malaria data. Methodology/Principal Findings The study was undertaken in health facilities in western Kenya. A total of 3,569 blood smears were analyzed after being collected from patients who were requested by clinicians to go to the hospital’s laboratory for malaria testing. We applied several quality control measures for clinical malaria diagnosis. We compared our slide reading results with those from the hospital technicians. Among the 3,390 patients whose diagnoses were analyzed, only 36% had clinical malaria defined as presence of any level of parasitaemia and fever. Sensitivity and specificity of clinicians’ diagnoses were 60.1% (95% CI: 61.1−67.5) and 75.0% (95% CI: 30.8−35.7), respectively. Among the 980 patients presumptively treated with an anti-malarial by the clinicians without laboratory diagnosis, only 47% had clinical malaria. Conclusions/Significance These findings revealed substantial over-prescription of anti-malarials and misdiagnosis of clinical malaria. More than half of the febrile cases were not truly clinical malaria, but were wrongly diagnosed and treated as such. Deficiency in malaria diagnosis makes health facility data unreliable for monitoring trends in malaria morbidity and for evaluating impacts of malaria interventions. Improving malaria diagnosis should be a top priority in rural African health centers.
Different Lines of Rats Selectively-Bred for High Alcohol-Drinking Demonstrate Disparate Preferences for Nicotine Self-administration

Background. Alcohol and nicotine are commonly co- abused. The search for a common core of neural, behavioral, and genetic factors underlying addiction has been the goal of addiction research. Purpose. Genetic predisposition to high alcohol intake has been studied in rats by selectively breeding rats that have high preference for alcohol. The current experiments were conducted to determine if the level of intravenous nicotine administration for the various lines of alcohol-preferring rats differs from that for nonalcohol-preferring controls. Study design. Adult alcohol-na¨ selectively-bred alcohol-preferring male rats from four lines (P, AA, HAD-1, sP) and their control nonalcohol-preferring rats (NP, ANA, LAD-1, sNP) were trained and given access to self-administer nicotine (0.03 mg/kg/infusion). Results. The results show that the P rats self- administered significantly more nicotine than NP rats. In contrast, there were no significant differences in nicotine self-administration between the sP and sNP or the AA and ANA rats. Unexpectedly, high alcohol-drinking HAD-1 rats self-administered significantly less nicotine than low alcohol-drinking LAD-1 rats. Conclusion. This suggests that some genetic factors that underlie high-alcohol intake have more general effects in promoting high nicotine intake tendencies, while other genetic factors are more specific to only heavy drinking.
Pushdown Automata in Statistical Machine Translation

This article describes the use of pushdown automata (PDA) in the context of statistical machine translation and alignment under a synchronous context-free grammar. We use PDAs to compactly represent the space of candidate translations generated by the grammar when applied to an input sentence. General-purpose PDA algorithms for replacement, composition, shortest path, and expansion are presented. We describe HiPDT, a hierarchical phrase-based decoder using the PDA representation and these algorithms. We contrast the complexity of this decoder with a decoder based on a finite state automata representation, showing that PDAs provide a more suitable framework to achieve exact decoding for larger synchronous context-free grammars and smaller language models. We assess this experimentally on a large-scale Chinese-to-English alignment and translation task. In translation, we propose a two-pass decoding strategy involving a weaker language model in the first-pass to address the results of PDA complexity analysis. We study in depth the experimental conditions and tradeoffs in which HiPDT can achieve state-of-the-art performance for large-scale SMT.