Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of Brain MR Images with ITK Toolkit

: Segmentation of nontrivial images is one of the most difficult tasks in image processing. Segmentation accuracy determines the success or failure of computerized analysis procedures. Medical image segmentation has become an important diagnostic tool in the practice of modern medicine. Segmentation of MRI Brain images is the delineation of neuro-anatomical structures such as the Cerebrum, Cerebellum, Hippocampus, etc. as well as abnormalities such as tumors. Although numerous methods have been proposed during the past two decades for brain MRI segmentation, it remains a challenging task. In this paper brain MRI segmentation is demonstrated for delineation of a tumor, ventricles and other anatomical structures using Insight Segmentation and Registration Toolkit (ITK) routines as the foundation. This public software provides callable routines only. It does not provide graphics, visualization, or other interactive tools specific to a given task, such as segmentation. Segmentation of medical images is an important step in forming realistic tissue models. To assist in classifying the relevant literature, three generations of development are identified where each generation adds an additional level of algorithmic complexity. The first generation is composed of the simplest forms of image analysis, the second is characterized by the application of uncertainty models and optimization methods, and the third incorporates knowledge into the segmentation process. The progress toward fully automatic segmentation is discussed and sources of segmentation software from industry and academia are identified, along with databases for segmentation validation. We have implemented a variety of semiautomatic and automatic segmentation routines as well as preprocessing algorithms provided by ITK. This implementation facilitates interactive adjustments of algorithm parameters and their consequences on the segmentation results via an intuitive GUI incorporating the ITK segmentation routines.
Definitive Radiation Therapy for Early Glottic Carcinoma

Background: Definitive radiation therapy (RT) for early laryngeal glottic carcinoma offers an excellent probability of cure and it is associated with persistent disease or tumor recurrence in a minority of patients. The objective of treatment controlling the malignant tumor and preserving a functionally useful voice is best optimized by the use of radiotherapy in early stages. Although surgery can offer equal good results, it is best reserved in the event of radiation failure. Aim of the work: The aim of the present retrospective study is to identify the treatment outcomes and different prognostic variables affecting early (T1N0M0 and T2N0M0) laryngeal glottic squamous cell carcinoma (SCC) treated with definitive radiation therapy. Methods: The medical records of 81 patients with T1N0M0 and T2N0M0 glottic invasive SCC treated with definitive radiation therapy throughout the period from January, 2002 to September, 2010, at Clinical Oncology Department, Tanta University Hospital, were reviewed. All patients had at least 12 months of follow-up. These patients were evaluated for response to RT, local control, disease specific survival (DSS) rates and treatment toxicity. The different prognostic factors affected the local control and DSS rates were also statistically analyzed. Results: The median follow-up period was 45.9 months. Eleven patients (13.58%) received <65 Gy as a total irradiation dose and 86.42% received > 65 Gy. Complete disappearance of the laryngeal glottic lesion (CR) was achieved in 91.36% of patients. Five-year local control rates were 89.1% in T1 and 64.96% in T2 tumor stage. Multivariate analysis revealed that anterior commissure involvement (P=0.048) and overall treatment time (P=0.002) are adversely affected local control rates with statistical significance. Seven (9.46%) patients failed locally and 2 (2.7%) had developed distant failure. Five-year DSS rates were as follows: T1, 89.81% and T2, 70.76%. Sever early radiation reaction involving skin, larynx & pharynx were rare (1.2%, 3.7% and 6.2%, respectively), and severe late reactions was recorded in 1.2% of patients. Conclusion: Definitive RT cures a high proportion of patients with T1N0M0 and T2N0M0 glottic SCC and has a low rate of severe complications. The anterior commissure involvement and overall treatment time were adversely affected local control rate. [Alaa Maria; Mohamed El-Shebiney and Omnia Abd El-Fattah. Definitive Radiation Therapy for Early Glottic Carcinoma. Life Science Journal 2012; 9(2):146-153]. (ISSN: 1097-8135). http://www.lifesciencesite. com. 25
NURBS hyper-surfaces for 3D topology optimization problems

Abstract A general topology optimization strategy is presented in this study for three-dimensional applications. The approach is based on the combination of a well-established density-based method and the Non-uniform rational basis spline (NURBS) hyper-surfaces formalism. The topology of the structure to be optimized can be embedded in a reference domain and it is opportunely described by means of a suitable NURBS hyper-surface. This choice implies several advantages. On the one hand, the number of design variables (control points and weights of the NURBS hyper-surface) is drastically reduced, when compared to classical density-based approaches, and it is unrelated to the mesh of the finite element model. On the other hand, the topology is described through a purely geometrical entity, while the mesh is utilized only to perform the computation of the relevant physical quantities for the problem at hand. A sensitivity analysis with respect to the new variables set is carried out. The effectiveness of the method as well as the effects of some discrete parameters tuning the NURBS hyper-surface shape are investigated on meaningful benchmarks and results are compared with those provided by the classical Solid Isotropic Material with Penalization approach.
Does the bilingual advantage extend to trilingualism?

ABSTRACT This study examined whether the proposed bilingual advantage in inhibitory control and working memory can be extended to a trilingual advantage, and assessed any age-related effects on a continuum in young adults to older adults. Trilinguals, bilinguals and monolinguals’ performance on the Simon task and a numerical version of the N-back task was compared. On the Simon task, there was no language group difference observed, although the data show an age-related decline in inhibitory control only in trilinguals, but not in bilinguals or monolinguals. No clear language group differences were observed between trilinguals and bilinguals on the N-back task, however an overall trilingual and bilingual disadvantage, compared to monolinguals, was observed. Together the results suggest that managing two or three languages, compared to just one, may have a negative impact on inhibitory control and working memory performance. Importantly, they highlight the need to control for a possible confounding effect of including trilinguals/multilinguals in bilingual cohorts and to ensure that participants in monolingual cohorts speak only one language.
Soil resource information for simulation – providing inputs for APSIM , and the role of APsoil

The views expressed in this publication are the personal opinions of the authors. CSIRO, AFFA, their officers and employees are not liable, without limitation, for any consequences incurred, or any loss or damage suffered, by any person as a result of their reliance on the information contained in this publication, and to the maximum extent permitted by law exclude all liability (including in negligence) in respect of this publication.
Suppression technique of vertical leakage current in GaN-on-Si power transistors

This paper analyzes the possible physical mechanisms responsible of high vertical leakage in GaN-on-Si power transistors. Vertical leakage and back bias measurement are presented and compared against TCAD simulations with the aim of identifying the physical phenomena and parameters that impact the vertical leakage. An easy-to-implement TCAD approach for simulating the non-ideality of the AlN nucleation layer and AlN/Si interface is introduced. Finally, a method to largely suppress the vertical leakage via implantation of highly doped p++ wells at the AlN/Si interface is proposed and investigated via TCAD simulations. The suggested technique allows for a reduction of five orders of magnitude in the leakage current when a p++ surface doping in excess of 5 × 1019 cm−3 is implanted at the Si-substrate surface. In this work, a normally-on HEMT is investigated but the analysis can be extended to any GaN-on-Si power device.
Conflict detection and social perception: bringing meta-reasoning and social cognition together

Abstract Research on implicit conflict detection suggests that people are sensitive to violations of logical principles. When they make reasoning errors, their epistemic radar presumably detects an anomaly. This study tested conflict detection using novel measures: self-report measures of how much reasoners struggled when solving a problem and whether they considered an alternative response, and social inferences of what they believe other people would respond. Moreover, this study tested whether these social inferences are informed by how much conflict people feel when trying to decide on an answer themselves. Results show 1) that reasoners in general are conflict-sensitive, even when they are incorrect; but 2) this sensitivity is greater for correct vs. incorrect responders; and 3) the experience of conflict influences social inferences, such that reasoners are less likely to believe that other people share their response when they themselves considered an alternative response when trying to solve a problem.
Where to invest in BRICS? An analysis from the point of view of the industrial organization

The objective of this study is to identify the most interesting industries for investing in Brazil, Russia, India e China (BRICs), according to risk-return and value premises, based in the theory of Industrial Organization (IO) tradition. This work analyzed 2770 firms in the BRICs from 1995 until 2008. With this purpose were compared rates of performance as ROA (return on assets), ROE (return on shares), average price earnings, market value over book value and Tobin’s Q of the companies. The results support studies from Fama and French (1992), Mohanram (2005) and Goldszmidt, Brito and Vasconcelos (2007), although deviates from World Bank (2008) as to risk-return enhancing in China. Results show that the most attractive sectors for investment using the risk-return approach, filtering by value indicators, would be oil & gas in Russia and mining in Brazil,India and China, while the least interesting industries would be textile, motor vehicle parts, tools & accessories and telecommunications in Brazil. ABSTRACT
Verbal Working Memory

Working memory refers to the temporary retention of information that has just arrived to the senses or has been retrieved from long-term memory. While internal representations of external stimuli have a natural tendency to decay over time or with interference, they can be kept “in mind” through the action of memory rehearsal strategies, and can be subjected to various operations that manipulate information in the service of ongoing behavior. A fundamental debate about the neural basis of working memory for linguistic information is whether it is supported by a dedicated brain system in its own right, or whether it emerges from the same neural circuitry that underpins basic online language processing. While the answer to this question remains a matter of debate, recent cognitive neuroscience research suggests that verbal working memory can be viewed as a functional adaptation of core neural substrates that enable the perception, comprehension, and production of speech.
Detecting objects using Rolling Convolution and Recurrent Neural Network

Abstract — At present, most of the existing target detection algorithms use the method of region proposal to search for the target in the image. The most effective regional proposal method usually requires thousands of target prediction areas to achieve high recall rate. This lowers the detection efficiency. Even though recent region proposal network approach have yielded good results by using hundreds of proposals, it still faces the challenge when applied to small objects and precise locations. This is mainly because these approaches use coarse feature. Therefore, we propose a new method for extracting more efficient global features and multi-scale features to provide target detection performance. Given that feature maps under continuous convolution lose the resolution required to detect small objects when obtaining deeper semantic information; hence, we use rolling convolution (RC) to maintain the high resolution of low-level feature maps to explore objects in greater detail, even if there is no structure dedicated to combining the features of multiple convolutional layers. Furthermore, we use a recurrent neural network of multiple gated recurrent units (GRUs) at the top of the convolutional layer to highlight useful global context locations for assisting in the detection of objects. Through experiments in the benchmark data set, our proposed method achieved 78.2% mAP in P ASCAL VOC 2007 and 72.3% mAP in PASCAL VOC 2012 dataset. It has been verified through many experiments that this method has reached a more advanced level of detection.
Concepts for a Product Line Knowledge Base & Variability

Federated Information Systems are based on gathering information from different heterogeneous data sources. The Internet a Meta FIS in one sense demands for the ability to query many different information sources. Obviously, most of them are structured very differently. Considering databases, XML files, other structured text files or Web Services as information supplier the complexity of integrating the information with their various describing models is not easy to handle. Even companies that only want to setup a global information system (e.g. a Data Warehouse) are faced with integration problems. As a lot of departments were able to develop their own local information pools there can be a variety of different sometimes redundant data sources even inside one company. In this paper an new approach of building such a global information system is described. Besides the theoretical aspects it is mainly shown that the system is really working and can easily be adapted to the special needs, a certain Federated Information System has to fulfill.
Broadleaf Signalgrass (Brachiaria platyphylla) Duration of Interference in Rice (Oryza sativa)

Interference from broadleaf signalgrass at a density of 180 plants/m2 reduced rough rice yields of ‘Bond’ a maximum of 48% at 95 days after rice emergence and reduced yields of ‘Mars' a maximum of 21% from season-long interference. Interference durations of 40 days or longer reduced the panicles/m2, culms/m2, and plant height of rice. Straw dry weight of Bond and Mars was reduced 41 and 26%, respectively, from season-long interference. Increased durations of weed interference did not affect the number of spikelets/panicle, percent filled spikelets, rough kernel weight, or head rice yield of either cultivar. Broadleaf signalgrass produced less dry weight and fewer panicles/m2 when grown with Mars than with Bond.
Derivation and Evaluation of a New Extinction Coefficient for Use With the n-HUT Snow Emission Model

In this study, snow slab data collected from the Arctic Snow Microstructure Experiment were used in conjunction with a six-directional flux coefficient model to calculate individual slab absorption and scattering coefficients. These coefficients formed the basis for a new semiempirical extinction coefficient model, using both frequency and optical diameter as input parameters, along with the complex dielectric constant of snow. Radiometric observations, at 18.7, 21.0, and 36.5 GHz at both horizontal polarization (H-Pol) and vertical polarization (V-Pol), and snowpit data collected as part of the Sodankylä Radiometer Experiment were used to compare and contrast the simulated brightness temperatures produced by the multi-layer Helsinki University of Technology snow emission model, utilizing both the original empirical model and the new semiempirical extinction coefficient model described here. The results show that the V-Pol RMSE and bias values decreased when using the semiempirical extinction coefficient; however, the H-Pol RMSE and bias values increased on two of the lower microwave bands tested. The unbiased RMSE was shown to decrease across all frequencies and polarizations when using the semiempirical extinction coefficient.
On the Realism of the Rain Microphysics Representation of a Squall Line in the WRF Model. Part I: Evaluation with Multifrequency Cloud Radar Doppler Spectra Observations

This study investigates how multifrequency cloud radar observations can be used to evaluate the representation of rain microphysics in the WRF Model using two bulk microphysics schemes. A squall line observed over Oklahoma on 12 June 2011 is used as a case study. A recently developed retrieval technique combining observations of two vertically pointing cloud radars provides quantitative description of the drop size distribution (DSD) properties of the transition and stratiform regions of the squall-line system. For the first time, the results of this multifrequency cloud radar retrieval are compared to more conventional retrievals from a nearby polarimetric radar, and a supplementary result of this work is that this new methodology provides a much more detailed description of the DSD vertical and temporal variations. While the extent and evolution of the squall line is well reproduced by the model, the 1-h low-reflectivity transition region is not. In the stratiform region, simulations with both schemes are able to reproduce the observed downdraft and the associated significative subsaturation below the melting level, but with a slight overestimation of the relative humidity. Under this subsaturated air, the simulated rain mixing ratio continuously decreases toward the ground, in agreement with the observations. Conversely, the profiles of the mean volume diameter and the concentration parameter of the DSDs are not well reproduced. These discrepancies pinpoint at an issue in the representation of rain microphysics. The companion paper, investigates the sources of the biases in the microphysics processes in the rain layer by performing numerical sensitivity studies.
Peringkasan Review Produk Berbasis Fitur Menggunakan Semantic Similarity Scoring Dan Sentence Clustering

Ulasan produk dari konsumen merupakan salah satu faktor yang penting dalam penjualan suatu produk. Menganalisis klasifikasi sentimen dan peringkasan suatu review produk memiliki tiga tahap yang harus dilakukan. Tahap pertama yaitu ekstraksi fitur menggunakan frequent itemset mining dengan algoritma apriori. Kemudian, dilakukan klasifikasi opini menggunakan SentiWordnet untuk penentuan polaritas kata opini. Tahap terkahir yaitu dilakukan peringkasan menggunakan semantic similarity scoring dan sentence clustering. Hasil dari penelitian ini didapat bahwa filtering kata yang sesuai juga mempengaruhi performansi dari ekstraksi pada penelitian ini. Filtering kata digunakan yaitu Noun, Noun Phrase, irisan serta gabungan keduanya, keempat filtering kata yang digunakan memiliki hasil yang cukup seimbang, gabungan dan irisan yang diharapkan dapat meningkatkan performansi juga masih didapat hasil yang tidak terlalu jauh dengan hanya Noun dan Noun Phrase. Hasil performansi ekstraksi pada penelitian ini adalah sekitar 20-40% pada dataset yang digunakan. Klasifikasi menggunakan SentiWordNet menunjukkan hasil performansi yang cukup baik namun pada beberapa dataset yang memiliki kompleksitas kalimat yang cukup tinggi juga terjadi penurunan walaupun tidak terlalu berbeda jauh dan masih pada sekitaran 40-90%. Peringkasan dokumen dapat dilakukan dengan baik pada dataset yang disediakan karena dataset memiliki jumlah kalimat ulasan produk yang memadai dan peringkasan dengan metode yang digunakan memperlihatkan beberapa representasi kalimat dari clustering dengan baik. Kata kunci: analisis sentimen, ulasan produk, frequent pattern generation, association mining, semantic smimilarity scoring, sentence clustering.
FPGA-Based Device-Level Electro-Thermal Modeling of Floating Interleaved Boost Converter for Fuel Cell Hardware-in-the-Loop Applications

Floating interleaved boost converter (FIBC) is a promising topology of the dc/dc converters to interface the fuel cell with dc bus in a hybrid powertrain. For the efficient control development of power converters, the hardware-in-the-loop (HIL) simulation plays an important role. The accuracy of the real-time model determines the credibility of the HIL simulation. In order to take the power losses and thermal stress into account in the control development, the device-level real-time model is becoming popular in recent years, which can effectively produce device transient voltage and current waveforms, switching power dissipations, and thermal behaviors. In this paper, a device-level electro-thermal model of FIBC is proposed and developed using the field programmable gate array based real-time simulation technology. The FIBC network model can effectively be simulated with a 500-ns time step while producing the insulated-gate bipolar transistor transient switching waveforms authentically with a 5-ns resolution. The switching power losses can thus be estimated in real time and then used for the computation of the IGBT thermal behavior. Therefore, the device junction temperature can be evaluated in the real-time simulation. The accuracy of the proposed FIBC device-level model is validated by the reference model in the Saber offline simulation tool. At last, an embedded PI controller of FIBC is employed in the real-time experiments to verify the effectiveness of the developed model.
Homework Practices of Elementary School Teachers in 4th Grade Turkish Course

This study aims to investigate the forms and frequency of homework given as part of a 4th grade Turkish course assessment in the state elementary schools in the Turkish Republic of Northern Cyprus. Data were collected using a questionnaire, a homework scale and structured interviews in this mixed methods research. The study sample consisted of 61 primary school teachers who were teaching 4th grade during the 2014-2015 academic year and 51 teachers who had taught 4th grade prior to the date of the study, making a total sample of 112 teachers. Structured interviews were conducted with nine voluntary teachers who participated in the study. Results revealed that homework assignments related to reading comprehension were given significantly more frequently than homework related to speaking or presentation of materials. The teachers’ awareness on the benefits of the kinds of homework given in low frequency was determined in findings. Numerous reasons as to why homework with certain structures could not be given were discussed through structured interviews. Based on specific suggestions made by the teachers on improving the efficiency of homework, a re-evaluation of syllabus materials and a consideration for teacher training on the way homework assignments are formulated in the constructivist approach are highlighted.