Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization based parameter identification of the Caltech ducted fan

Recent work has demonstrated the use of model predictive control (MPC) for stabilizing the Caltech ducted fan. In results published up until now, however, additional stability augmentation was required. It was felt that an inadequate model was the cause of this shortcoming. This paper details an optimization-based parameter identification scheme which was used to identify new parameters for the ducted fan model. In addition to solving a traditional least squares optimization problem over the space of parameters, we introduce the additional concept of optimizing over the space of inputs as in a typical optimal control problem. The projection operator approach to trajectory optimization described is used to perform the trajectory optimization and enables many iterations to be executed in a reasonable time span. Finally, the newly identified parameters enabled us to use pure MPC with no additional stability augmentation. We were unable to achieve the same results consistently with other techniques.
High efficient power receiver IC with load modulator for wireless resonant power transfer

The wireless power receiver with load modulator for inband communication is proposed. The MOS transistor is used for the load modulator of inband communication and the proposed wireless power receiver is implemented with 0. 35μm 2P4M BCDMOS technology. The efficiency of the wireless power receiver is obtained as high as 80% for ~3W pickup at 13.56 MHz of transfer frequency. We have verified the performance of the inband communication for the WPT system while a mobile device is in charging.
Regulation of Id1 and its association with basic helix-loop-helix proteins during nerve growth factor-induced differentiation of PC12 cells

Cell differentiation in the nervous system is dictated by specific patterns of gene expression. We have investigated the role of helix-loop-helix (HLH) proteins during differentiation of PC12 pheochromocytoma cells in response to nerve growth factor. Gel mobility shift assays using PC12 cell nuclear extracts demonstrated that active basic HLH complexes exist throughout differentiation. Addition of exogeneous Id1 protein, a negative regulator of basic HLH proteins, disrupted specific complexes formed by PC12 cell nuclear extracts on a CANNTG consensus oligonucleotide. To identify possible novel basic HLH proteins in these complexes, a glutathione S-transferase-Id1 fusion protein was used to screen a PC12 cell cDNA expression library. A single clone representing the rat E2-2 gene was identified. Sequential immunoprecipitations with antibodies to each HLH protein revealed an association between Id1 and E2-2 that could be detected in both untreated and nerve growth factor-treated PC12 cell lysates. These experiments define a new HLH interaction between Id1 and E2-2 in neuronal cells and suggest that neuronal differentiation may be regulated by HLH proteins in a distinctive manner.
Statistical and Computational Limits for Sparse Matrix Detection

This paper investigates the fundamental limits for detecting a high-dimensional sparse matrix contaminated by white Gaussian noise from both the statistical and computational perspectives. We consider $p\times p$ matrices whose rows and columns are individually $k$-sparse. We provide a tight characterization of the statistical and computational limits for sparse matrix detection, which precisely describe when achieving optimal detection is easy, hard, or impossible, respectively. Although the sparse matrices considered in this paper have no apparent submatrix structure and the corresponding estimation problem has no computational issue at all, the detection problem has a surprising computational barrier when the sparsity level $k$ exceeds the cubic root of the matrix size $p$: attaining the optimal detection boundary is computationally at least as hard as solving the planted clique problem. The same statistical and computational limits also hold in the sparse covariance matrix model, where each variable is correlated with at most $k$ others. A key step in the construction of the statistically optimal test is a structural property for sparse matrices, which can be of independent interest.
Hybrid feature selection method for autism spectrum disorder SNPs

Machine learning techniques have the potential to revolutionise medical diagnosis. Single Nucleotide Polymorphisms (SNPs) are one of the most important sources of human genome variability; thus, they have been implicated in several human diseases. To separate the affected samples from the normal ones, various techniques have been applied on SNPs. Achieving high classification accuracy in such a high-dimensional space is crucial for successful diagnosis and treatment. In this work, we propose an accurate hybrid feature selection method for detecting the most informative SNPs and selecting an optimal SNP subset. The proposed method is based on the fusion of a filter and a wrapper method, i.e. the Conditional Mutual Information Maximization (CMIM) method and the Support Vector Machine Recursive Feature Elimination (SVM-RFE) respectively. The performance of the proposed method was evaluated against three state-of-the-art feature selection methods; Minimum Redundancy Maximum Relevancy (mRMR), CMIM and ReliefF, using four classifiers, Support Vector Machine (SVM), Naive Bayes (NB), Linear Discriminant Analysis (LDA) and k Nearest Neighbors (k-NN) on Autism Spectrum Disorder(ASD) SNP dataset obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) genomics data repository. The experimental results demonstrate the efficiency of the adopted feature selection approach outperforming all of the compared feature selection algorithms and achieving up to 89% classification accuracy for the used dataset.
ULMAP: Ultralightweight NFC Mutual Authentication Protocol with Pseudonyms in the Tag for IoT in 5G

As one of the core techniques in 5G, the Internet of Things (IoT) is increasingly attracting people’s attention. Meanwhile, as an important part of IoT, the Near Field Communication (NFC) is widely used on mobile devices and makes it possible to take advantage of NFC system to complete mobile payment and merchandise information reading. But with the development of NFC, its problems are increasingly exposed, especially the security and privacy of authentication. Many NFC authentication protocols have been proposed for that, some of them only improve the function and performance without considering the security and privacy, and most of the protocols are heavyweight. In order to overcome these problems, this paper proposes an ultralightweight mutual authentication protocol, named ULMAP. ULMAP only uses Bit and XOR operations to complete the mutual authentication and prevent the denial of service (DoS) attack. In addition, it uses subkey and subindex number into its key update process to achieve the forward security. The most important thing is that the computation and storage overhead of ULMAP are few. Compared with some traditional schemes, our scheme is lightweight, economical, practical, and easy to protect against synchronization attack.
Continuous landmines scanning using legged robot with manipulator arm over rough terrain

In this paper, we introduce a new scanning technique for detecting landmines and unexploded ordnance (UXO). The manipulator arm carried by a hexapod robot is capable of scanning rough terrain using a typical mine detector. To speed up the landmine detection and marking, both scanning and moving forward will be done simultaneously. The controller will perform two tasks. The first task is to keep the sensor-head in a fixed level with respect to the ground and the second task is to keep the base of the arm within a specified range of position and orientation. A coupling between the velocity of the end-effector and the velocity of the manipulator base (robot body) is created to ensure the efficiency of the whole process. To verify the feasibility of our design, three experiments will be performed using simulation in MATLAB. The manipulator was modelled using SolidWorks.
The differential effects of pre-engineering curricula on middle School Students’ attitudes to and knowledge of engineering careers

The Middle School Students' Attitude to Mathematics, Science and Engineering Survey was developed to measure students' attitudes to engineering and knowledge about engineering careers as part of a program to enlarge the future pool of engineers because students' attitudes have been found to be an important predictor of whether students pursue careers in engineering. The program focuses on using pre-engineering curricula in middle and high schools, and informing students, teachers, parents, and school counselors about careers in engineering because most students do not know what engineering is or what engineers do and therefore do not explore engineering as a career option or prepare for it academically in the critical middle or high school years. Continued use of the survey with younger students indicated that the language used in some of the questions was too sophisticated for some middle school students and the survey has been revised. A study was conducted to examine the psychometric properties of the revised survey with a large sample of academically diverse middle school students. Comparisons among groups of students exposed to pre-engineering concepts in various different ways in their science and mathematics classes have been made to explore the extent to which the exposure may have affected students' attitudes to engineering and knowledge of engineering careers.
An Approach to Supervised Learning of Three-Valued Łukasiewicz Logic in Hölldobler's Core Method

The core method [6] provides a way of translating logic programs into a multilayer perceptron computing least models of the programs. In [7] , a variant of the core method for three valued Lukasiewicz logic and its applicability to cognitive modelling were introduced. Building on these results, the present paper provides a modified core suitable for supervised learning, implements and executes supervised learning with the backpropagation algorithm and, finally, constructs a rule extraction method in order to close the neural-symbolic cycle.
The 13C urea breath test in the diagnosis ofHelicobacter pylori infection

The urea breath test (UBT) is one of the most important non-invasive methods for detecting Helicobacter pylori infection. The test exploits the hydrolysis of orally administered urea by the enzyme urease, which H pylori produces in large quantities. Urea is hydrolysed to ammonia and carbon dioxide, which diffuses into the blood and is excreted by the lungs. Isotopically labelled CO2 can be detected in breath using various methods. Labelling urea with 13C is becoming increasingly popular because this non-radioactive isotope is innocuous and can be safely used in children and women of childbearing age. Breath samples can also be sent by post or courier to remote analysis centres. The test is easy to perform and can be repeated as often as required in the same patient. A meal must be given to increase the contact time between the tracer and the H pylori urease inside the stomach. The test has been simplified to the point that two breath samples collected before and 30 minutes after the ingestion of urea in a liquid form suffice to provide reliable diagnostic information. The cost of producing 13C-urea is high, but it may be possible to reduce the dosage further by administering it in capsule form. An isotope ratio mass spectrometer (IRMS) is generally used to measure 13C enrichment in breath samples, but this machine is expensive. In order to reduce this cost, new and cheaper equipment based on non-dispersive, isotope selective, infrared spectroscopy (NDIRS) and laser assisted ratio analysis (LARA) have recently been developed. These are valid alternatives to IRMS although they cannot process the same large number of breath samples simultaneously. These promising advances will certainly promote the wider use of the 13C-UBT, which is especially useful for epidemiological studies in children and adults, for screening patients before endoscopy, and for assessing the efficacy of eradication regimens.
Dermal Lymphatic Invasion and Inflammatory Breast Cancer Are Independent Predictors of Outcome After Postmastectomy Radiation

Objectives:Inflammatory breast cancer (IBC) is a clinical staging based on history and physical findings. Dermal lymphatic invasion (DLI) can occur with or without IBC. We examine how these independently affect outcome in women treated with postmastectomy radiation. Methods:Four hundred thirty-two patients treated with postmastectomy radiation for invasive mammary cancer were assessed. Kaplan-Meier methodology was used to calculate rates of locoregional recurrence (LRR), distant metastases (DM) and overall survival (OS). Variables entered into univariate and multivariate analysis included T stage, IBC, DLI, estrogen receptor/progesterone receptor status, HER-2/neu status, N stage, extracapsular node extension (ECE), and use of chemotherapy (CT). Median follow-up is 58 months. Results:For all 432 patients, the rate of LRR was 3% and DM 28%. Seven percent are alive with disease (AWD) and 26% are dead of disease (DOD). Thirty-one patients had IBC without DLI, 21 had DLI without IBC, and 18 had both IBC and DLI. For DLI 10% developed LRR, 45% DM, 7.5% are AWD and 50% are DOD. Of patients with IBC, 8% developed LRR, 44% DM, 8% are AWD and 48% DOD. DLI was the only significant independent predictor for LRR (HR 4.8, P < 0.05). Predictors of DM and OS were IBC, ≥4 positive nodes, and CT. Conclusions:DLI and IBC are independent predictors of poor outcome after postmastectomy radiation. DLI is associated with an increased risk for LRR, and IBC with worse rates of DM and OS. Patients with both features have worse outcome than those with either alone.
A Review on Selective Catalytic Reduction of NOx by NH3 over Mn–Based Catalysts at Low Temperatures: Catalysts, Mechanisms, Kinetics and DFT Calculations

It is a major challenge to develop the low–temperature catalysts (LTC, <250 °C) with excellent efficiency and stability for selective catalytic reduction (SCR) of NOx by NH3 from stationary sources. Mn-based LTC have been widely investigated due to its various valence states and excellent redox performance, while the poisoning by H2O or/and SO2 is one of the severe weaknesses. This paper reviews the latest research progress on Mn-based catalysts that are expected to break through the resistance, such as modified MnOx–CeO2, multi-metal oxides with special crystal or/and shape structures, modified TiO2 supporter, and novel carbon supporter (ACF, CNTs, GE), etc. The SCR mechanisms and promoting effects of redox cycle are described in detail. The reaction kinetics will be a benefit for the quantitative study of Eley–Rideal (ER) and Langmuir–Hinshelwood (LH) mechanisms. This paper also introduces the applications of quantum-chemical calculation using density functional theory to analyze the physic-chemical properties, explicates the reaction and poisoning mechanisms, and directs the design of functional catalysts on molecule levels. The intensive study of H2O/SO2 inhibition effects is by means of the combination analysis of in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and density functional theory (DFT), and the amplification of tolerance mechanisms will be helpful to design an excellent SCR catalyst.
The Gulf of Riga as a resource for wind energy — a project description

Wind is one of the main renewable energy resources. The planning of offshore wind farms is an ongoing process and the Gulf of Riga region is no exception. Accurate information on marine wind field with high spatial and temporal resolution is therefore needed. Rough ice conditions in the Gulf of Riga could impose a threat to the construction and operation of offshore wind parks. The Gulf of Riga is an important habitat area for marine mammals and birds. They could suffer the most from the operational activity of wind parks. People are afraid that their living standards may decrease. In several cases it remains uncertain how the planned wind parks contribute to the energy needs of adjacent counties. The project aims directly at producing policy-relevant and scientifically based information on wind energy fields, the most affected key natural species populations and social reactions of and economic benefits for the entire Gulf of Riga region. A decision-making tool based on spatial planning methods of the GIS environment will be developed to facilitate common planning for the exploitation of wind energy in the Gulf of Riga region. Dynamic maps of wind energy, ice conditions, migrating and wintering bird populations, and seals dating back to 2001 and having the projection to future climate will be produced. The indicators for spatial planning with regard to public attitude towards the development of wind parks and for the quantification of local plans concerning renewal energy consumption will be developed and integrated into the decision-making tool. The outputs of the project contribute to the elaboration of policy-relevant, environmental and socio-economic issues related to the exploitation of renewable energy. The project objectives are to provide the decision-makers and potential developers of wind parks in the Gulf of Riga with reliable marine wind information derived from high-resolution remote sensing data, coastal wind measurements and an ensemble of regional climate models. Wind fields will be complemented with the information on habitat areas for seals and wintering, migrating and breeding birds. Local people and authorities will be involved in the active process of the selection of suitable areas for wind parks through mapping their attitude and considering the requirements for the areas of renewable energy. The project partners are research institutes and funds for nature from Estonia and Latvia and the project period is from July 2010 until June 2012. This project is financed by the Estonia-Latvia Programme. Estonia-Latvia Programme is implemented according to the principles of the European Territorial Cooperation and it supports cross-border cooperation between Estonia and Latvia. It is funded by the European Regional Development Fund (ERDF), the Republic of Estonia and the Republic of Latvia.
Gleason grading of prostate cancer. Contemporary approach.

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Design and Development of a Bangla Semantic Lexicon and Semantic Similarity Measure

In this paper, we have proposed a hierarchically organized semantic lexicon in Bangla and also a graph based edgeweighting approach to measure semantic similarity between two Bangla words. We have also developed a graphical user interface to represent the lexical organization. Our proposed lexical structure contains only relations based on semantic association. We have included the frequency of each word over five Bangla corpuses in our lexical structure and also associated more details to words such as, whether the words are mythological or not, whether it can be used as verb or not, in order to use the word as a verb which word should be appended to it etc. As we have earlier discussed, this lexicon can be used in various applications like categorization, semantic web, and natural language processing applications like, document clustering, word sense disambiguation, machine translation, information retrieval, text comprehension and question-answering systems.
Increased leakage of sarcoplasmic reticulum Ca2+ contributes to abnormal myocyte Ca2+ handling and shortening in sepsis*

Objective:Changes in cardiac function due to sepsis have been widely reported. However, the underlying mechanisms remain poorly understood. In the mammalian heart, myocyte function and intracellular calcium homeostasis are closely coupled. In this study we tested the hypothesis that alterations in cardiac calcium homeostasis due to sepsis underlie the observed myocyte dysfunction. Design:Randomized prospective animal study. Setting:Research laboratory. Subjects:Male Sprague-Dawley rats weighing 250–275 g. Interventions:We induced sepsis by cecal ligation and puncture in the rat, which mimics the type of infection caused by perforation of the intestine in humans. Measurements and Results:Forty-eight hours after cecal ligation and puncture, isolated cardiac ventricular cardiomyocytes demonstrated a 57% decreased peak systolic [Ca2+]. The time constant of the Ca2+ transient increased 71% and 57% in myocytes obtained 24 hrs and 48 hrs after cecal ligation and puncture, respectively. The average shortening of cardiomyocytes 48 hrs after cecal ligation and puncture was significantly decreased. To investigate the cellular mechanisms of altered Ca2+ transients and myocyte shortening, we measured Ca2+ sparks, the spontaneous local Ca2+ release events in cardiomyocytes at resting states. The Ca2+ spark frequency progressively increased in myocytes 24 hrs and 48 hrs after cecal ligation and puncture. The total activity of sparks also increased compared with sham-operated animals. The overall leakage of sarcoplasmic reticulum Ca2+ in resting states was increased in sepsis and resulted in reduced sarcoplasmic reticulum Ca2+ content. Conclusions:Abnormal Ca2+ leakage from the sarcoplasmic reticulum contributes significantly to the depressed myocyte shortening in sepsis. In the future, modalities that prevent this Ca2+ leakage may prove beneficial in the treatment of sepsis-induced myocyte shortening.
ErbB2 expression is correlated with increased survival of patients with osteosarcoma

Elevated ErbB2 expression and gene amplification have been shown to be associated with poor prognosis in many cancers. Recently, it has been demonstrated that overexpression of ErbB2 protein in osteosarcoma is associated with the presence of pulmonary metastasis and decreased survival. By contrast, a previous study showed that the expression of ErbB2 declines in individual osteosarcomas as they become metastatic. In the current study, the authors determined the relation between ErbB2 status and outcome in a large number of selected patients with high‐grade osteosarcoma.