Miracle-dz/UniFAR-FTUs huggingface dataset:
A comprehensive platform for thermal studies in TSV-based 3D integrated circuits

We present an advanced and comprehensive platform for thermal dissipation studies in TSV-based 3D ICs. A 2-tier 3D test chip with through silicon via (TSV) and μ-bump is used for thermal characterization with unprecedented precision and design exploration capabilities. A comprehensive calibrated 3D finite element model is associated to provide a predictive tool that is able to simulate the thermal mapping in any given 3D interconnect configuration with minimal error. Guidelines are finally provided for thermal optimization of 3D designs with a precision far beyond the prior art.
Incidentally detected carcinoma in situ in a fibroadenoma of breast in a postmenopausal woman: A case report

Fibroadenomas are the most common benign tumor of the br but the peak incidence seen in young adolescent women during the second and third decades of life. Fibroadenoma is a biphasic tumor, composed of an epithelial and a stromal component. Even though they are solitary le sions, multiple fibroadenomas can also occur especially in the older age group. Breast fibroadenomas seemed to display a wide spectrum of proliferative and non proliferative histologic changes. Of all these changes, carcinoma arising from fibroadenoma is a occurrence. Here, we have present standing multiple fibroadenoma in a postmenopausal women. Clinical and radiological features are not helpful in identifying carcinoma arising from fibroad the excised specimen should be done for the confirmation of the diagnosis.
Synchronization of Complex Dynamical Networks with Switching Topology: a Switched System Point of View

Abstract In this paper, we study the synchronization problem for complex dynamical networks with switching topology. The synchronization problem is transformed into the stability problem for a time-varying switched system. We address two basic problems: synchronization under arbitrary switching topology, and synchronization via design of switching within a pre-given collection of topologies when synchronization can not be achieved by using any topology alone in this collection. For the both problems, we first establish synchronization criteria for general connection topology. Then, under the condition of simultaneous triangularization of the connection matrices, a common Lyapunov function and a single Lyapunov function are systematically constructed respectively by those of several lower-dimensional dynamic systems.
Case Library Construction Technology of Energy Loss in Distribution Networks Considering Regional Differentiation Theory

The grid structures, load levels, and running states of distribution networks in different supply regions are known as the influencing factors of energy loss. In this paper, the case library of energy loss is constructed to differentiate the crucial factors of energy loss in the different supply regions. First of all, the characteristic state values are selected as the representation of the cases based on the analysis of energy loss under various voltage classes and in different types of regions. Then, the methods of Grey Relational Analysis and the K-Nearest Neighbor are utilized to implement the critical technologies of case library construction, including case representation, processing, analysis, and retrieval. Moreover, the analysis software of the case library is designed based on the case library construction technology. Some case studies show that there are many differences and similarities concerning the factors that influence the energy loss in different types of regions. In addition, the most relevant sample case can be retrieved from the case library. Compared with the traditional techniques, constructing a case library provides a new way to find out the characteristics of energy loss in different supply regions and constitutes differentiated loss-reducing programs.
A comparison between MODWT-SVM-DE hybrid model and ARIMA model in forecasting primary energy consumptions

The future demand of primary energy plays an important role in a reliable supply system, which is used as a guideline for a proper policy. The useful information of demand can be obtained from suitable forecasting models. In this paper, the forecasting performances of ARIMA model and hybrid model of MODWT-SVM-DE model are investigated and compared based on three criteria; MAE, MAPE, and sMAPE. The empirical results indicated that the MODWT-SVM-DE model provides more accurate forecasts than ARIMA model at significance level α = 0.10. However, the ARIMA model as a simplified model is capable to provide the accurate result that is not relatively different than that of the MODWT-SVM-DE model in given data sets.
Edgeworth expansion for functionals of continuous diffusion processes

This paper presents new results on the Edgeworth expansion for high frequency functionals of continuous diffusion processes. We derive asymptotic expansions for weighted functionals of the Brownian motion and apply them to provide the Edgeworth expansion for power variation of diffusion processes. Our methodology relies on martingale embedding, Malliavin calculus and stable central limit theorems for semimartingales. Finally, we demonstrate the density expansion for studentized statistics of power variations.
Analyst vs. Market Forecasts of Earnings Management to Avoid Small Losses

Burgstahler and Eames (2003) present evidence that analysts commonly anticipate earnings management to avoid small losses, but often incorrectly predict its occurrence. Here we consider whether the market’s behavior mimics that of analysts. Our results suggest that analysts exhibit more forecast optimism in their zero earnings forecasts than in their other small earnings forecast levels, and markets exhibit less relative optimism at this point. At the 271-360 day forecast horizon, we find a reduction in the earnings response coefficient at analysts’ zero earnings forecasts and interpret this as reflecting less optimism in market earnings forecasts than in analyst forecasts when analysts forecast zero earnings. This evidence is consistent with the market not following analysts in erroneously predicting earnings management to avoid small losses. We do not find similar evidence for shorter forecast horizons, suggesting that market and analyst forecasts converge towards the end of the year. Finding differences in market and analyst earnings forecasts in this loss avoidance environment raises the possibility of differences in a variety of earnings management and other environments, and sends a general note of caution in using analyst forecasts issued early in the year to proxy market expectations.
General IIR optical filter design for WDM applications using all-pass filters

A general design algorithm is presented for infinite impulse response (IIR) bandpass and arbitrary magnitude response filters that use optical all-pass filters as building blocks. Examples are given for an IIR multichannel frequency selector, an amplifier gain equalizer, a linear square-magnitude response, and a multi-level response. Major advantages are the efficiency of the IIR filter compared to finite impulse response (FIR) filters, the simplicity of the optical architecture, and its tolerance for loss. A reduced set of unique operating states is discussed for implementing a reconfigurable multichannel selection filter.
Liquidity and the Dynamic Pattern of Asset Price Adjustment: A Global View

Global liquidity expansion has been very dynamic since 2001. Contrary to conventional wisdom, high money growth rates have not coincided with a concurrent rise in goods prices. At the same time, however, asset prices have increased sharply, significantly outpacing the subdued development in consumer prices. We investigate the interactions between money and goods and asset prices at the global level. Using aggregated data for major OECD countries, our VAR results support the view that different price elasticities on asset and goods markets explain the observed relative price change between asset classes and consumer goods.
LOW LEVEL LASER THERAPY ( LLLT ) IMPROVES HEALTH STATUS AND QUADRICEPS MUSCLE ACTIVATION IN ELDERLY WITH KNEE OSTEOARTHRITIS

The quadriceps weakness associated with knee osteoarthritis (OA) has been partially attributed to the inability of the central nervous system of activating all quadriceps motor units, also known as muscle inhibition (MI). The analgesic effect of low-level laser therapy (LLLT) may reduce the afferent input from pain receptors increasing efferent output from quadriceps α motor neurons, restoring the ability to fully activating the muscle. This study aimed at determining the effects of LLLT on MI and health status in elderly with knee OA. Ten elderly women (mean age 64.5±6.2 yr) with knee OA performed an 8-week period of LLLT treatment (wavelength 830nm, continuous wave, output power 200W, 4J per point) using a single probe in contact with the skin at 6 different points at the knee joint. MI was assessed using the twitch-interpolation technique. Superimposed electrical shock (maximal voltage = 240 V) was applied to the femoral nerve during maximal isometric voluntary contractions at 90 of knee flexion (0 = full extension). MI was estimated by the amount of extra torque evoked by the superimposed twitch in relation to the voluntary maximal torque. The health status was assessed with the WOMAC questionnaire. Results revealed that LLLT reduced MI by 50% (effect size = 0.64, p<0.05). Pain, stiffness and functional limitation decreased by 40%, 44% and 33%, respectively (effect size = from 0.9 to 1.3, p<0.001). In conclusion, LLLT treatment appears to have a relevant potential to minimize MI as well as to improve the health status of OA patients.
hep-th / 0001206 SLAC-PUB-8337 SU-ITP-00 / 02 IASSNS-HEP-00 / 05 Self-tuning flat domain walls in 5 d gravity and string theory

We present Poincare invariant domain wall (“3-brane”) solutions to some 5-dimensional effective theories which can arise naturally in string theory. In particular, we find theories where Poincare invariant solutions exist for arbitrary values of the brane tension, for certain restricted forms of the bulk interactions. We describe examples in string theory where it would be natural for the quantum corrections to the tension of the brane (arising from quantum fluctuations of modes with support on the brane) to maintain the required form of the action. In such cases, the Poincare invariant solutions persist in the presence of these quantum corrections to the brane tension, so that no 4d cosmological constant is generated by these modes.
Analysing the Impact of Renewable Energy Regulation on Retail Electricity Prices

Retail electricity prices have substantially increased in the last decade in the European Union (EU) as a result of different regulations, raising the concern of policy makers. The growth in the support costs for electricity from renewable energy sources (RES-E) has often been singled out as a main driver of these prices. The aim of this paper is to analyse the degree of influence of RES-E promotion costs on the evolution of the retail price of electricity in the EU Member States. The analysis is carried out for households as well as for industry, with the help of a panel data econometric model. Our results show that the impact of renewable energy promotion costs on the retail electricity prices is positive and statistically significant, although relatively small. Differences across consumer types can be observed. An increase of 1% in those costs induces an average increase of only 0.023% in industrial retail prices and 0.008% in the residential retail prices. This impact on retail prices is mediated by the type of support scheme being adopted, with price-based support instruments showing a greater effect than quantity-based ones.
Climate Reconstruction Using Tree-Ring Data

Instrument records from the past 200 years support a scientific consensus that climate is changing Trenberth et al. (2007). What is less clear is how to interpret these changes in an historical context spanning many hundreds, or thousands, or tens of thousands of years. The statistical question is this: how do we quantify and model historical climate without having direct observations beyond the most recent one or two centuries? The most common solution is to build an index of historical climate change using long-scale proxy observations that are constructed from data such as tree ring measurements, lake sediments, bore-hole observations, coral records and ice cores (see Jones and Mann (2004) for a review as well as Jansen et al. (2007)). Reconstructions based on these sources feature prominently in the 2007 Intergovernmental Panel on Climate Change report (Jansen et al. 2007). There are two steps necessary to reconstruct climate from proxy data. Step one involves filtering out any non-climate features so that only climatic features remain in the proxy. Step two involves using the filtered proxy data, either alone, or combined with other proxy measurements, to reconstruct climate at either the local or global scale. While some studies have not paid enough attention to the first ∗E-mail: matthew.schofield@uky.edu
AHP_HeGES: Tools to evaluate usability of educational computer game (UsaECG)

Development of computer game for teaching and learning become popular nowadays. In order to develop a game that able to contribute to the teaching and learning process and at the same time, fun to be played by the users, a comprehensive evaluation technique is needed. Experts' involvement in the evaluation process able to help developers detect usability problem before the game can be used by users. Gathering experts to conduct an evaluation process is not an easy task. This is because experts have their own commitments. To overcome this problem, a tool known as AHP_HeGES was developed to assist in evaluation process. This tool is an online system that can be used by experts to conduct the evaluation process. Evaluation technique used are based on heuristic evaluation, known as Playability Heuristic Evaluation for Educational Computer Game (PHEG) that consists of five heuristics; interface, educational element, content, playability, and multimedia. This research is important to facilitate game developers in identifying elements that need to be improved before the final version is ready to be released.
Performance of Rayleigh-Product MIMO Channels with Linear Receivers

This paper presents an analytical investigation on the performance of Rayleigh-product MIMO channels with linear minimum mean-square-error (MMSE) or zero-forcing (ZF) receivers. For MMSE receivers, exact closed-form expressions for the ergodic sum-rate of the system are derived. In addition, simplified expressions are obtained for the key parameters dictating the sum-rate performance of the system in the high signal-to-noise ratio (SNR) regime (i.e., high SNR slope and power offset) and low SNR regime (i.e., minimum energy per information bit required to convey any positive rate and the wideband slope). While for ZF receivers, tight closed-form upper and lower bounds for the ergodic sum-rate of the system are derived. It is analytically proven that the ZF and MMSE receivers achieve the same sum rate performance in the high SNR regime. Moreover, for both MMSE and ZF receivers, the achievable diversity-multiplexing tradeoff (DMT) of Rayleigh-product MIMO channels is characterized. The findings suggest that a larger number of scatterers will improve the the performance of Rayleigh-product MIMO channels with linear receivers, and the ZF receivers achieve the same performance as the MMSE receivers in Rayleigh-product MIMO channels in the high SNR regime. Moreover, it is demonstrated that as long as the number of the scatterers is greater than the number of receive antennas, linear receivers achieve the optimal DMT.
Pleural effusion with pleural thickening in a patient exposed to zinc chromate paints: a rare case report.

A 35-year-old male painter presented with left sided pleuritic chest pain and exertional dyspnea. A chest radiograph revealed left pleural effusion with pleural thickening. This condition is suspected to be caused by chronic exposure to zinc dichromate and history of exposure was >13 years. Pleural effusion with pleural thickening can be both benign and malignant. Biopsy remains gold standard investigation for exclusion. Pleural fluid cytology and pleural biopsy revealed lymphocytic pleural effusion with few macrophages in proteinaceous fluid background and negative for malignant cells, which was suggestive of benign chronic inflammatory reaction and exclude any malignant changes. Pleural fluid drained and symptomatic treatment provided and patient counseled. Further follow-up needed to diagnosis early malignant changes.
Data management and visualization for cluster-based grid operations

The concept of smart grids has been widely introduced to cope with energy transition towards sustainable energy, which results in decentralization of the energy supply. Among various solutions to accomplish the smart grids, clustering power systems approach (CPSA) is proposed. This approach creates active decentralized areas in the form of interconnected cluster areas equipped with their own controller. The CPSA can be flexibly applied at any grid level in a manner that enables consistency in both grid structure and control. In this paper, to facilitate implementation of the CPSA, a data management infrastructure is proposed for the controller. It enables scalability, interoperability, and flexibility to the cluster area applications. In addition, to support users in monitoring of the cluster areas, data visualization on the web-based graphical user interface of the controller is presented. Lastly, a demonstration of applying the data management and data visualization is delivered.
Electro-thermal simulation of bond wires in power modules for realistic mission profiles

For the successful electrification of global transportation, the reliability of power electronic modules is of major importance. Today, one of the main reasons for module failure is the thermo-mechanically induced fatigue of bond wires as a result of strong load variations. A multitude of studies have been conducted to analyze the operational stress of bond wires based on thermal simulations using simple repetitive load patterns. This paper proposes a compact electro-thermal model for detailed time-efficient simulations of the thermal stress within bond wires. It incorporates the impact of parasitic electromagnetic coupling effects for an accurate loss determination over a wide frequency range. Finally, the bond wire model is embedded into a system simulation of the drive train of an electric vehicle. This allows to determine the realistic temperature distribution along the bond wires over time for specific mission profiles.
Laminate fibre structure characterisation by orientation-selective X-ray grating interferometry

Scatter dark field imaging with an X-ray grating interferometer has been implemented to probe the micro-structure of polymers, fibre-reinforced composites or light metals. The method has now been developed further to enable the characterisation of the fibre laminate structure. Experimental results obtained by scatter dark field computed tomography illustrate how information on the microstructure such as micro-cracks density and weave pattern can be gained. Future developments of the technology aim at increasing the size of the field of view and improving the robustness.
MGr 1-Ag promotes invasion and bone metastasis of small-cell lung cancer in vitro and in vivo

Bone metastasis of small-cell lung cancer (SCLC) usually occurs early in the progression of the disease. However, the molecular mechanism underlying bone metastasis is largely unknown. MGr1-Ag, a multifunction protein, has been suggested to play important roles in cell growth, differentiation and migration. In our present study, MGr1-Ag was found to be highly expressed in bone-metastatic SCLC cells (SBC-5 cell line) as compared with the expression in cells without bonemetastatic ability (SBC-3 cell line). Therefore, we hypothesized that MGr1-Ag is involved in bone metastasis of SCLC. Using a sense vector to upregulate MGr1-Ag expression in SBC-3 cells, we found that forced overexpression of MGr1-Ag enhanced cell invasion and migration in vitro and promoted bone metastases in vivo. Furthermore, specific siRNA-induced knockdown of MGr1-Ag expression in SBC-5 cells suppressed the potential of cell invasion and migration in vitro and dramatically decreased the number and sites of bone metastasis in vivo. We also found that MGr1-Ag induced SCLC cells to undergo epithelial-mesenchymal transition (EMT), as demonstrated by cell morphological changes, decreased expression of epithelial markers and increased expression of mesenchymal markers. Taken together, we conclude that MGr1-Ag promotes SCLC cell invasion and bone metastasis in vitro and in vivo, and that this is partially mediated via the EMT pathway.
An empirical study for hypertext categorization

As the Web expands exponentially, the need to put some order to its content becomes apparent. Hypertext categorization, that is the automatic classification of web documents into predefined classes, came to elevate humans from that task. The extra information available in a hypertext document poses new challenges for automatic categorization. HTML tags and metadata provide rich information for hypertext categorization that is not available in traditional text classification. This paper looks at (i) what representation to use for documents and which extra information hidden in HTML pages to take into consideration to improve the classification task, and (ii) how to deal with the very high number of features of texts. A hypertext dataset and four well-known learning algorithms (Naive Bayes, K-nearest neighbor, support vector machines and C4.5) were used to exploit the enriched text representation along with feature reduction. The results showed that enhancing the basic text content with HTML page keywords, title and anchor links improved the accuracy of the classification algorithms.
Distributed Semi-supervised Learning with Kernel Ridge Regression

This paper provides error analysis for distributed semi-supervised learning with kernel ridge regression (DSKRR) based on a divide-and-conquer strategy. DSKRR applies kernel ridge regression (KRR) to data subsets that are distributively stored on multiple servers to produce individual output functions, and then takes a weighted average of the individual output functions as a final estimator. Using a novel error decomposition which divides the generalization error of DSKRR into the approximation error, sample error and distributed error, we find that the sample error and distributed error reect the power and limitation of DSKRR, compared with KRR processing the whole data. Thus a small distributed error provides a large range of the number of data subsets to guarantee a small generalization error. Our results show that unlabeled data play important roles in reducing the distributed error and enlarging the number of data subsets in DSKRR. Our analysis also applies to the case when the regression function is out of the reproducing kernel Hilbert space. Numerical experiments including toy simulations and a music-prediction task are employed to demonstrate our theoretical statements and show the power of unlabeled data in distributed learning.