Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Swirl Flow on the Flow Field, Temperature Field and Inclusion Behavior when Using a Half Type Electromagnetic Swirl Flow Generator in a Submerged Entry and Mold

In the preceding work, the inclusion behavior in a submerged entry nozzle (SEN) and mold induced by using a swirl flow has been investigated. The results showed that a swirl flow can effectively promote the inclusions removal to the meniscus as well as reduce the inclusions entrapment at the solidified shell wall. Moreover, that the swirl flow was generated by using a full type electromagnetic swirl flow generator (EMSFG). In the present work, a kind of a half type EMSFG was investigated, since it is easier to implement in a production scale. The influence of the stirrer on the fluid flow, heat transfer, and inclusion behavior in the SEN and mold was studied. Furthermore, a comparison between these two types of EMSFG from the aspects of flow field, temperature field, and inclusion behavior was done. In addition, the effect of different magnetomotive forces, inclusion sizes, densities as well as boundary conditions on the inclusion behavior was studied. The results show that the effect of a half type EMSFG (88000 AT) on the molten steel is very close to a full type case (44000 AT). More specifically, the flow pattern, temperature distribution as well as inclusion behavior in the SEN and mold look very similar. Also, it was found that from the viewpoints of the inclusions separation to the mold meniscus and the inclusions trapping at the solidified shell wall, better results could be obtained for a “Trap” boundary condition when using half type EMSFGs.
Preparation and Characterization of a Novel Composite of Chitosan/Shell Particles

Nanometer sized (mean size: 433.9 nm) pearl shell particles (SP) were prepared with a ball mill. Thermal analysis and Fourier transform infrared (FTIR) results proved that the SP contained mainly CaCO3 (about 95%) and a small organic phase (about 5%). Novel biodegradable composites based upon chitosan (CS) and SPs were prepared using an in situ precipitation method. The organic components of SP are highly compatible with both CS and glutaraldehyde (GA). The strength and modulus of CS gel rods, prepared by coagulation of a CS/SP/GA solution in NaOH, in both the dry and wet state, were improved remarkably with addition of appropriate amounts of SP together with GA. For example, with a composition of 3% SP and 0.3% GA added, the strength and modulus were 42.9 MPa and 1.41 GPa, increasing 75 and 464% compared with CS alone, respectively. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) results showed that GA acts as not only a crosslinking agent for CS, but also a compatibilizer for CS and SP. It was found that the modified rods have smaller free volume size but nearly the same free volume fraction as pure CS rods. The good interfacial adhesion and more compact microstructure can sensitively reflect the changes in the free volume of the composites.
Design tools for reliability analysis

Recent progress in EDA tools allows IC designs to be accurately verified with consequent improvements in yield and performance through reduced guard bands. This paper present a tools perspective, including the primary effects such as HCI, NBTI and EM for which EDA tools are available, types of tools (dynamic simulation vs. static rule checking) and necessary reliability infrastructure and flows that have been working in practice. Finally, developing areas and future opportunities are addressed
Magnetic nanoparticles in tumor xenografts detected and quantified by micro-computer tomography

In this work we focus on the imaging of magnetic nanoparticles in tumor tissue. The spatial distribution of magnetic nanoparticles in tumor tissue is an essential parameter in the evaluation of the efficiency of magnetic drug targeting (MDT). We developed a volume-based imaging method for x-ray-micro tomography calibrated by magnetorelaxometry to determine the concentration of magnetic nanoparticles in a certain tissue. With this technique, the x-ray absorption information contained in a μ-CT image can be directly related to an absolute mass of magnetic nanoparticles in a certain volume element of the tumor. In contrast to other related methods reported in the literature, the procedure described here is capable of a mass resolution of 0.044 μg mm−3, making it possible to map the particle distribution in tumors with extremely low magnetic particle content, such as are usually found in mouse experiments on MDT.
Motor Recovery After Subcortical Stroke Depends on Modulation of Extant Motor Networks

Introduction Stroke is the leading cause of long-term disability. Functional imaging studies report widespread changes in movement-related cortical networks after stroke. Whether these are a result of stroke-specific cognitive processes or reflect modulation of existing movement-related networks is unknown. Understanding this distinction is critical in establishing more effective restorative therapies after stroke. Using multivariate analysis (tensor-independent component analysis – TICA), we map the neural networks involved during motor imagery (MI) and executed movement (EM) in subcortical stroke patients and age-matched controls. Methods Twenty subcortical stroke patients and 17 age-matched controls were recruited. They were screened for their ability to carry out MI (Chaotic MI Assessment). The fMRI task was a right-hand finger-thumb opposition sequence (auditory-paced 1 Hz; 2, 3, 4, 5, 2…). Two separate runs were acquired (MI and rest and EM and rest; block design). There was no distinction between groups or tasks until the last stage of analysis, which allowed TICA to identify independent components (ICs) that were common or distinct to each group or task with no prior assumptions. Results TICA defined 28 ICs. ICs representing artifacts were excluded. ICs were only included if the subject scores were significant (for either EM or MI). Seven ICs remained that involved the primary and secondary motor networks. All ICs were shared between the stroke and age-matched controls. Five ICs were common to both tasks and three were exclusive to EM. Two ICs were related to motor recovery and one with time since stroke onset, but all were shared with age-matched controls. No IC was exclusive to stroke patients. Conclusion We report that the cortical networks in stroke patients that relate to recovery of motor function represent modulation of existing cortical networks present in age-matched controls. The absence of cortical networks specific to stroke patients suggests that motor adaptation and other potential confounders (e.g., effort and additional muscle use) are not responsible for the changes in the cortical networks reported after stroke. This highlights that recovery of motor function after subcortical stroke involves preexisting cortical networks that could help identify more effective restorative therapies.
Through Thickness Residual Stress Measurements by Neutron Diffraction and Hole Drilling in a Single Laser-Peened Spot on a Thin Aluminium Plate

Residual stress measurements are very challenging in thin aluminium plates. Rolling-induced crystallographic texture can lead to an S-shape fit when using the sin2ψ method for surface X-ray diffraction. Peak broadening and missing peaks can also be observed for synchrotron X-ray diffraction with conventional θ/2θ scanning due to texture. In addition, when measuring near the plate surfaces, partially-filled gauge volumes in diffraction experiments will lead to “pseudo-strains”, an apparent shift between measured and actual positions for the diffraction peak. Obtaining a meaningful value of d0 for strain calculations is another issue for diffraction experiments in thin plates. The low thickness also offers challenges for destructive methods including incremental hole drilling, i.e. there is no defined ASTM standard for measuring non-uniform residual stress profile for thin plates. In this work, 2-mm-thick Al2024-T351 plate was investigated for residual stress fields due to laser peening. Neutron diffraction measurements were carried out at POLDI (Pulse Overlap time-of-flight Diffractometer) in PSI, Switzerland and the results are compared with incremental hole drilling.
Subjective Measures of Risk Aversion and Portfolio Choice

The paper investigates risk attitudes among different types of individuals. The authors use several different measures of risk attitudes, including questions on choices between uncertain income streams suggested by Barsky et al. (1997) and a number of ad hoc measures. As in Barsky et al. (1997) and Arrondel (2002), the authors first analyse individual variation in the risk aversion measures and explain them by background characteristics (both "objective" characteristics and other subjective measures of risk preference). Next, the authors incorporate the measured risk attitudes into a household partfolio allocation model, which explains portfolio shares, while accounting for incomplete portfolios. The authors results show that the Barsky et al. (1997) measure has little explanatory power, whereas ad hoc measures do a considerably better job. The authors provide a discussion of the reasons for this finding.
Tuning electrical stimulation for thalamic visual prosthesis: An autoencoder-based approach

Visual prosthesis holds hope of vision restoration for millions with retinal degenerative diseases. Machine learning techniques such as artificial neural networks could help in improving prosthetic devices as they could learn how the brain encodes information and imitate that code. This paper introduces an autoencoder-based approach for tuning thalamic visual prostheses. The objective of the proposed approach is to estimate electrical stimuli that are equivalent to a given natural visual stimulus, in a way such that they both elicit responses that are as similar as possible when introduced to a Lateral Geniculate Nucleus (LGN) population. Applying the proposed method to a probabilistic model of LGN neurons, results demonstrate a significant similarity between both responses with a mean correlation of 0.672 for optimal electrodes placement and 0.354 for random electrodes placement. The results indicate the efficacy of the proposed approach in estimating an electrical stimulus equivalent to a specific visual stimulus.
Brain registration and subtraction - improved localization for SPECT analysis (B.R.A.S.I.L.): a computer-aided diagnosis in epilepsy tool kit

Surgery is an important option in the treatment of patients with medically intractable epilepsy. Traditional techniques for the localization of the epileptogenic zone (EZ), e.g. surface electroencephalography (EEG) and magnetic resonance (MR) imaging, allow accurate localization in a significant number of epileptic patients. Besides, in many situations, the single photon emission computed tomography (SPECT) images have played a very important role in EZ localization. However, the identification of the EZ based on the visual interpretation side-by-side of the ictal and periictal images is in general a difficult task. To improve SPECT analysis, computational techniques have been developed focusing on the registration and fusion of ictal and periictal SPECT images. The combination of image registration and subtraction of SPECT images can improve the selective detection of brain regions with functional activation during epileptic seizures. The proposed methodology shown high sensitivity to detect hyperperfusion higher than 10%, in this article we apresents the techniques implemented, the methodology used to test and some initial results obtained with our own developed software B.R. A.S. I.L. ("Brain Registration And Subtraction: Improved Localization for SPECT Analysis").
Extending UML to Visualize Design Patterns In Class Diagrams

A design pattern describes a general solution to a design problem that recurs repeatedly in many projects. Software designers adapt the pattern solution to their specific project. Design patterns are usually modeled using UML. However, UML does not keep track of pattern-related information when a design pattern is applied or composed with other patterns. Thus, it is hard for a designer to identify design patterns in software system designs. The benefits of design patterns are compromised because the designers cannot communicate with each other in terms of the design patterns they use and their design decisions and tradeoffs. In this paper, we present the essential features of a new member of the UML language family that supports working with object-oriented design patterns. This UML extension allows the explicit representation of design patterns in software designs. We also discuss some of the relevant aspects of the UML profile which is based on standard UML extension mechanisms. A case study shows how it can be used to assist pattern-based software development.
Stable and efficient lattice algorithms for adaptive IIR filtering

Previous attempts at applying lattice structures to adaptive infinite-impulse-response (IIR) filtering have met with gradient computations of O(N/sup 2/) complexity. To overcome this computational burden, two new lattice-based algorithms are proposed for adaptive IIR filtering and system identification, with both algorithms of O(N) complexity. The first algorithm is a reinterpretation of the Steiglitz-McBride method (1965), while the second is a variation on the output error method. State space models are employed to make the derivations transparent, and the methods can be extended to other parameterizations if desired. The set of possible stationary points of the algorithms is shown to be consistent with the convergent points obtained from the direct-form versions of the Steiglitz-McBride and output error methods, whose properties are well studied. The derived algorithms are as computationally efficient as existing direct-form based algorithms, while overcoming the stability problems associated with time-varying direct-form filters. >
B Cell Repertoire Analysis Identifies New Antigenic Domains on Glycoprotein B of Human Cytomegalovirus which Are Target of Neutralizing Antibodies

Human cytomegalovirus (HCMV), a herpesvirus, is a ubiquitously distributed pathogen that causes severe disease in immunosuppressed patients and infected newborns. Efforts are underway to prepare effective subunit vaccines and therapies including antiviral antibodies. However, current vaccine efforts are hampered by the lack of information on protective immune responses against HCMV. Characterizing the B-cell response in healthy infected individuals could aid in the design of optimal vaccines and therapeutic antibodies. To address this problem, we determined, for the first time, the B-cell repertoire against glycoprotein B (gB) of HCMV in different healthy HCMV seropositive individuals in an unbiased fashion. HCMV gB represents a dominant viral antigenic determinant for induction of neutralizing antibodies during infection and is also a component in several experimental HCMV vaccines currently being tested in humans. Our findings have revealed that the vast majority (>90%) of gB-specific antibodies secreted from B-cell clones do not have virus neutralizing activity. Most neutralizing antibodies were found to bind to epitopes not located within the previously characterized antigenic domains (AD) of gB. To map the target structures of these neutralizing antibodies, we generated a 3D model of HCMV gB and used it to identify surface exposed protein domains. Two protein domains were found to be targeted by the majority of neutralizing antibodies. Domain I, located between amino acids (aa) 133–343 of gB and domain II, a discontinuous domain, built from residues 121–132 and 344–438. Analysis of a larger panel of human sera from HCMV seropositive individuals revealed positivity rates of >50% against domain I and >90% against domain II, respectively. In accordance with previous nomenclature the domains were designated AD-4 (Dom II) and AD-5 (Dom I), respectively. Collectively, these data will contribute to optimal vaccine design and development of antibodies effective in passive immunization.
Effect of probabilistic inputs on neural network-based electric load forecasting

This paper presents a novel method to include the uncertainties or the weather-related input variables in neural network-based electric load forecasting models. The new method consists of traditionally trained neural networks and a set of equations to calculate the mean value and confidence intervals of the forecasted load. This method was tested for daily peak load forecasts for one year by using modified data from a large power system. The tests indicate that in addition to the confidence interval, the new method provides a more accurate mean forecast than a multilayer perceptron networks alone.
Nano-Hydroxyapatite Improves the Properties of β-tricalcium Phosphate Bone Scaffolds

β-Tricalcium phosphates have been widely used as biomaterials for bone substitutes; however, the poor mechanical properties limit the application in bearing loading bones. In this study, nano-hydroxyapatite has been introduced to improve the mechanical properties for porous bioceramic scaffolds. Nanocomposites containing 0–10 wt% needle-like nano-hydroxyapatite were prepared for investigation. It has been found that needle-like nano-hydroxyapatite improves the toughness, hardness, and compressive strength of the porous β-tricalcium phosphates scaffolds, as well as the microstructure properties. The study provides a reference for the development of safe, excellent bone scaffolds for bone tissue engineering.
Marshalling Evidence Through Data Mining in Support of Counter Terrorism

In this paper we present an architecture to manage a large, distributed volume of evidence for counterterrorism applications. This approach facilitates the intelligence analyst’s train of thought by enabling hypotheses to be postulated and evaluated against the available evidence. The hypothesis creation is left to the human (as we believe only humans possess the flexibility to adapt hypothesis to the dynamic nature of the problem), but the system automates the gathering and linking of evidence that supports or negates the hypothesis. We do this by extensive use of data mining techniques in support of the process of query answering. The approach is incorporated into a distributed agent system that allows users to discover and compose agents for hypothesis processing.
A head tracking method using bird's-eye view camera and gyroscope

This paper describes a new head tracking method utilizing a gyroscope mounted on a head-mounted display (HMD) and a bird's-eye view camera that observes the HMD from a fixed third-person viewpoint. Furthermore, we propose an extension of this method to hybrid registration, combining it with user's view cameras. The HMD is equipped with a gyroscope and a marker. The gyroscope measures the orientation of the user s view camera so that the number of pose parameters to be solved can be reduced. The other parameters are to be estimated by the bird's-eye view camera that observes the marker. This method is an improvement over the conventional outside-in-style vision-based tracker method, which only uses visual information. Hence, it can be thought of as an alternative to a physical head tracker such as a magnetic sensor and to an inside-out-style vision-based tracker. In addition to theoretical discussions, this paper demonstrates the effectiveness of our methods by experiments. We also propose methods for calibrating the gyroscope and the marker on HMD, which are essential in implementing the tracking method.
Application mapping to a hardware platform through automated code generation targeting a RTOS: a design case study

Consistency, accuracy and efficiency are key aspects for practical usability of a system design flow featuring automatic code generation. Consistency is the property of maintaining the same behaviour at different levels of abstraction through synthesis and refinement, leading to functionally correct implementation. Accuracy is the property of having a good estimation of system performances while evaluating a high-level representation of the system. Efficiency is the property of introducing low overheads and preserving performances at the implementation level. The RTOS is a key element of the link to implementation flow. In this paper, we capture relevant high-level RTOS parameters that allow consistency, accuracy and efficiency to be verified in a top-down approach. Results from performance estimation are compared against measurements on the actual implementation. Experimental results on automatically generated code show design flow consistency, an accuracy error of about 0.66% and an overhead of about 11.8% in term of speed.
Spatial Heterogeneity, Source‐Sink Dynamics, and the Local Coexistence of Competing Species

Patch occupancy theory predicts that a trade‐off between competition and dispersal should lead to regional coexistence of competing species. Empirical investigations, however, find local coexistence of superior and inferior competitors, an outcome that cannot be explained within the patch occupancy framework because of the decoupling of local and spatial dynamics. We develop two‐patch metapopulation models that explicitly consider the interaction between competition and dispersal. We show that a dispersal‐competition trade‐off can lead to local coexistence provided the inferior competitor is superior at colonizing empty patches as well as immigrating among occupied patches. Immigration from patches that the superior competitor cannot colonize rescues the inferior competitor from extinction in patches that both species colonize. Too much immigration, however, can be detrimental to coexistence. When competitive asymmetry between species is high, local coexistence is possible only if the dispersal rate of the inferior competitor occurs below a critical threshold. If competing species have comparable colonization abilities and the environment is otherwise spatially homogeneous, a superior ability to immigrate among occupied patches cannot prevent exclusion of the inferior competitor. If, however, biotic or abiotic factors create spatial heterogeneity in competitive rankings across the landscape, local coexistence can occur even in the absence of a dispersal‐competition trade‐off. In fact, coexistence requires that the dispersal rate of the overall inferior competitor not exceed a critical threshold. Explicit consideration of how dispersal modifies local competitive interactions shifts the focus from the patch occupancy approach with its emphasis on extinction‐colonization dynamics to the realm of source‐sink dynamics. The key to coexistence in this framework is spatial variance in fitness. Unlike in the patch occupancy framework, high rates of dispersal can undermine coexistence, and hence diversity, by reducing spatial variance in fitness.
Influence of body fat distribution on free fatty acid metabolism in obesity.

UNLABELLED In order to determine whether differences in body fat distribution result in specific abnormalities of free fatty acid (FFA) metabolism, palmitate turnover, a measure of systemic adipose tissue lipolysis, was measured in 10 women with upper body obesity, 9 women with lower body obesity, and 8 nonobese women under overnight postabsorptive (basal), epinephrine stimulated and insulin suppressed conditions. RESULTS Upper body obese women had greater (P less than 0.005) basal palmitate turnover than lower body obese or nonobese women (2.8 +/- 0.2 vs. 2.1 +/- 0.2 vs. 1.8 +/- 0.2 mumol.kg lean body mass (LBM)-1.min-1, respectively), but a reduced (P less than 0.05) net lipolytic response to epinephrine (59 +/- 7 vs. 79 +/- 5 vs. 81 +/- 7 mumol palmitate/kg LBM, respectively). Both types of obesity were associated with impaired suppression of FFA turnover in response to euglycemic hyperinsulinemia compared to nonobese women (P less than 0.005). These specific differences in FFA metabolism may reflect adipocyte heterogeneity, which may in turn affect the metabolic aberrations associated with different types of obesity. These findings emphasize the need to characterize obese subjects before studies.