Miracle-dz/UniFAR-FTUs huggingface dataset:
Are There Imaging Characteristics Associated with Epidermal Growth Factor Receptor and KRAS Mutations in Patients with Adenocarcinoma of the Lung with Bronchioloalveolar Features?

Purpose: To identify any particular imaging features on computed tomography (CT) in patients with confirmed adenocarcinoma with bronchioloalveolar (ABAC) features and known epidermal growth factor receptor (EGFR) and KRAS mutations. Materials and Methods: Institutional review board approval was obtained for this retrospective study. Seventy-seven pulmonary nodules in 64 patients with a histologic diagnosis of ABAC and known EGFR or KRAS mutation status were assessed. Of these, 23 patients who were negative for both EGFR and KRAS mutations were used as a control group. Lesion size, margins, and density (ground glass versus solid) were assessed. Statistical analysis using the two-tailed Fisher's exact test t test was performed with multiple different variables. Results: Twenty-one (33%) of 64 patients had EGFR mutations, 20 (31%) of 64 patients had a KRAS mutation, and 23 (36%) had neither. In nine patients with an EGFR mutation, there were 10 nodules with some ground glass opacity (GGO) and in nine patients with a KRAS mutation, there were nine nodules with some GGO. Twenty-six (34%) of the 77 nodules had some GGO, and 12 (46%) of these 26 nodules were entirely GGO. Sixty-two (81%) of the 77 nodules had some solid component, which also included some that were mixed with GGO. Thirty-five (45%) of 77 nodules had air bronchograms. All five nodules (100%) with a high percentage of bronchioloalveolar carcinoma (>75%) had the appearance of GGO only. The presence of GGO on CT was not significantly associated with the presence of an EGFR mutation (p = 0.44) or with the presence of a KRAS mutation (p = 0.77). Conclusions: In our sample of patients with ABAC, there was no specific CT appearance, which would correlate with either an EGFR mutation or a KRAS mutation, when compared with a control group of patients who did not have these mutations.
Determination of Body Composition of Children from Skinfold Measurements

Total body water was measured in 23 children aged 1 to 11 years and correlated with estimates of lean body mass derived from measurements of skinfold thickness. The correlation coefficient was 0·98. Skinfold thickness can, therefore, be used to estimate lean body mass, and thus total body fat, in young children for whom other techniques for the measurement of body composition cannot easily be used.
Acquired Nasopharyngeal Stenosis in a Patient with Sarcoidosis

Abstract Introduction: Acquired nasopharyngeal stenosis typically occurs as a result of surgery or irradiation of the nasopharynx. Sarcoidosis has numerous manifestations in the head and neck region, although an association with nasopharyngeal stenosis has not previously been reported. Case report: A 40-year-old man with sarcoidosis developed severe acquired nasopharyngeal stenosis. This was successfully managed with balloon dilatation, followed by pharyngoplasty with local pharyngeal flap reconstruction. Conclusion: This report is intended to prompt consideration of nasopharyngeal stenosis as a potential cause of nasal obstruction in patients with sarcoidosis, and to draw attention to the need to consider sarcoidosis in the differential diagnosis of patients with acquired nasopharyngeal stenosis. We also demonstrate the viability of pharyngoplasty in the management of nasopharyngeal stenosis in the setting of sarcoidosis.
Automobile Fuel Economy Standards: Impacts, Efficiency, and Alternatives

This article discusses automobile fuel economy standards in the United States and other countries. We first describe how these programs affect the automobile market, including impacts on fuel consumption and other dimensions of the vehicle fleet. We then review two different methodologies for assessing the costs of fuel economy programs—engineering and market-based approaches—and discuss what the results of these assessments imply for policy. Next we compare the welfare effects of fuel economy standards and fuel taxes and discuss whether these two types of policies can be complementary. Finally, we review arguments for transitioning away from fuel economy regulations and toward a “feebate” system, a policy approach that imposes fees on vehicles that are fuel inefficient and provides rebates to those that are fuel efficient.
ISAR imaging of targets with moving parts using micro-doppler detection on the range profile image

In ISAR imaging, most works have assumed the target to be a rigid body, a body without any rotating, vibrating or moving parts. The rotation of structures in a target, such as the rotor of a helicopter or the turret of a tank target, may induce frequency modulation on the returned signals and generate sidebands about the center frequency of the target's body Doppler frequency, known as the micro-Doppler phenomenon. In this paper we present a new method based on range grouping of the target's range profile for the separation of the rotating or moving parts from the target's body. The method is carried out on the Range Profile Image, different from other methods that do the separation at the signal level.
Membrane localization of all class I PI 3‐kinase isoforms suppresses c‐Myc‐induced apoptosis in Rat1 fibroblasts via Akt

Phosphoinositide 3′‐kinases (PI3Ks) constitute a family of lipid kinases implicated in signal transduction through tyrosine kinase receptors and heterotrimeric G protein‐linked receptors. PI3Ks are heterodimers made up of four different 110‐kDa catalytic subunits (p110α, p110β, p110γ, and p110δ) and a smaller regulatory subunit. Despite a clear implication of PI3Ks in survival signaling, the contribution of the individual PI3K isoforms has not been elucidated. To address this issue, we generated Rat1 fibroblasts that co‐express c‐Myc and membrane targeted derivates of the different p110 isoforms. Here we present data for the first time showing that activation of PI3‐kinase signaling through membrane localization of p110β, p110γ, and p110δ protects c‐Myc overexpressing Rat1 fibroblasts from apoptosis caused by serum deprivation like it has been described for p110α. Expression of each p110 isoform reduces significantly caspase‐3 like activity in this apoptosis model. Decreased caspase‐3 activity correlates with the increase in Akt phosphorylation in cells that contain one of the myristoylated p110 isoforms. p110 isoform‐mediated protection from cell death was abrogated upon expression of a kinase‐negative version of Akt. © 2005 Wiley‐Liss, Inc.
Conversion of Biomass into Bioplastics and Their Potential Environmental Impacts

To build our economy on a sustainable basis, we need to find a replacement for fossil carbon as chemical industry feedstocks (Andrady and Neal, 2009). There are growing concerns about current petroleum based production, accumulation of waste in landfills and in natural habitats including the sea, physical problems for wildlife resulting from ingestion or entanglement in plastic, the leaching of chemicals from plastic products and the potential for plastics to transfer chemicals to wildlife and humans (Thompson et al., 2009). Bioplastics, derived from bio-based polymers, may provide a solution. Unlike the chemically synthesized polymers, the bio-based polymers are produced by living organisms, such as plants, fungi or bacteria. Some microorganisms are particularly capable in converting biomass into biopolymers while employing a set of catalytic enzymes. Attempts to transfer biomass to produce industrially useful polymers by traditional biotechnological approaches have obtained only very limited success, suggesting that an effective biomass-conversion requires the synergistic action of complex networks. As an interdisciplinary research field which is a unique combination of life science and engineering, synthetic biology can provide new approaches to redesign biosynthesis pathways for the synergistic actions of biomassconversion and may ultimately lead to cheap and effective processes for conversion of biomass into useful products such as biopolymers. In the following sections of this review, we will give first an introduction on bioplastics and synthetic biology (section 2). The properties of bio-based polymers for bioplastics equal to or better than their chemical synthetic counter parts will be compared. The subfields of synthetic biology related to polymer biosynthesis will be reviewed. In the Section 3, we will focus on synthetic biological approaches to improve the biological system to produce polymers for bioplastics, such as polyhydroxyalkanoates (PHAs). The fourth section then goes on to evaluate the environmental impacts of the synthetic biology derived bioplastics. In this section, we will review the current methods to measure the environmental impacts on bioplastics on greenhouse gases (GHGs) emission, direct or indiret land usage, energy consumptions and waste management, as well as the current regulation guidelines on bioplastics in Europe. And in the last section, we will summarize the perspectives of synthetic biology and bioplastics.
A novel framework for the identification of drug target proteins: Combining stacked auto-encoders with a biased support vector machine

The identification of drug target proteins (IDTP) plays a critical role in biometrics. The aim of this study was to retrieve potential drug target proteins (DTPs) from a collected protein dataset, which represents an overwhelming task of great significance. Previously reported methodologies for this task generally employ protein-protein interactive networks but neglect informative biochemical attributes. We formulated a novel framework utilizing biochemical attributes to address this problem. In the framework, a biased support vector machine (BSVM) was combined with the deep embedded representation extracted using a deep learning model, stacked auto-encoders (SAEs). In cases of non-drug target proteins (NDTPs) contaminated by DTPs, the framework is beneficial due to the efficient representation of the SAE and relief of the imbalance effect by the BSVM. The experimental results demonstrated the effectiveness of our framework, and the generalization capability was confirmed via comparisons to other models. This study is the first to exploit a deep learning model for IDTP. In summary, nearly 23% of the NDTPs were predicted as likely DTPs, which are awaiting further verification based on biomedical experiments.
A 460MHz Doherty power amplifier for IMT-Advanced systems

In this work, a Doherty power amplifier is presented for IMT-Advanced system at 450-470MHz frequency band. An imperfect Quarter-wave transmission line, which consisted of two shunt capacitors and a series microstrip line, is adopted to replace the bulky impedance inverter quarter-wave transmission line for designing the Doherty power amplifier (PA). Both the traditional and proposed structures for the Doherty power amplifiers were implemented. Comparing with the traditional Doherty amplifier, the size of the circuit and the manufacturing costs are decreased obviously. The measurement results of the proposed Doherty PA exhibit good performance as well as the traditional Doherty power amplifier. For a input signal with a 7.8dB Peak to Average Power Ratio (PAPR), the measured drain efficiency of the proposed Doherty power amplifier is 48.5% at an average output power of 43.0 dBm, which is a 7.8dB backed - off the peak output power. Moreover, in order to improve the linearity of the proposed Doherty power amplifier, the augmented Hammerstein and polynomial predistorter are used to linearize the proposed Doherty power amplifier. After digital predistortion, the adjacent channel leakage ratio (ACLR) reaches -45.5dBc at an average output power of 43.0 dBm, which can satisfy the requirements of the IMT-Advanced systems.
A Novel Clustering Approach Based on the Manifold Structure of Gene Expression Data

Clustering is an effective approach for computing analysis of gene expression data. Various of clustering algorithms have been developed to give reasonable interpretations of biological data and discover biological meaningful patterns of cellular functions. Based on the manifold structure of gene expression data analyzed under the framework of geometric representation, a novel clustering approach is presented to reveal the nonlinear expression patterns. The novel clustering approach can be divided into the following computing steps. The first step is to construct a neighborhood graph for gene expression points through which the approximate geodesic distances between each two points can be obtained. Then, instead of Euclidean distance, approximate geodesic distance is exploited to reveal the similarity between gene profiles. Finally, via defining the geodesic distance between a cluster and a gene expression point, new clusters can be generated after essential iterative processes. Application of the approach to the yeast cell-cycle dataset validates its rationality and efficiency.
Quenched Light, or Seeing Through a Glass Darkly - A Collocation-Based View of Larkin’s Atheism and Depression

This paper uses computational collocation-based analysis to examine Philip Larkin’s reputation as a depressive atheist. After a brief discussion of the term ‘collocation’, a complete corpus of Larkin’s poetry will be analysed for key symbols. This will be compared with a passage from 1 Corinthians 13 describing the transition from an incomplete human state to that of maturity, self-knowledge and perfection. Both will be checked against a reference corpus in the form of a newspaper corpus of 44.5 million words. The nature of transitions in Larkin’s poems (whether from day to night, from dissatisfaction to inability or from love to disappointment) will shed light on several questions surrounding his verse, finally showing his persona as a rebellious, doubting and immature Christian.
A new hardware design and FPGA implementation for Internet routing towards IP over WDM and terabit routers

With the advent of the World Wide Web and the services on it, there is a strong demand for the nodes that make Internet routing with guaranteed speed and throughput. Current 40-channel WDM (Wavelength Division Multiplexing) has boosted a single 2.5 Gbps OC-48 link to 100 Gbps, so the requirement to make IPv4 (Internet Protocol version 4) routing table lookup is 100 MLPS (million lookups per second.) The emerging 96-channel WDM and 10 Gbps OC-192 fibers certainly demand much more. Previous works on fast IPv4 routing table lookup used indirect RAM indexing to CPU caching or CAM (Content Addressable Memory) to achieve a few or tens MLPS. Their theoretical best performances depend on the memory access speed and some of them are not extensible to accommodate the forthcoming IPv6. In this paper we describe a novel way to do this work with only a FPGA, and this approach, which utilizes the logic modeling and minimization techniques, promises a capability to make IPv4 and (IPv6) routing decisions in a pipelined fashion within only a FPGA CLB delay time.
Stabilité de la sélection de variables pour la régression et la classification de données corrélées en grande dimension

Les donnees a haut-debit, par leur grande dimension et leur heterogeneite, ont motive le developpement de methodes statistiques pour la selection de variables. En effet, le signal est souvent observe simultanement a plusieurs facteurs de confusion. Les approches de selection habituelles, construites sous l'hypothese d'independance des variables, sont alors remises en question car elles peuvent conduire a des decisions erronees. L'objectif de cette these est de contribuer a l'amelioration des methodes de selection de variables pour la regression et la classification supervisee, par une meilleure prise en compte de la dependance entre les statistiques de selection. L'ensemble des methodes proposees s'appuie sur la description de la dependance entre covariables par un petit nombre de variables latentes. Ce modele a facteurs suppose que les covariables sont independantes conditionnellement a un vecteur de facteurs latents. Une partie de ce travail de these porte sur l'analyse de donnees de potentiels evoques (ERP). Les ERP sont utilises pour decrire par electro-encephalographie l'evolution temporelle de l'activite cerebrale. Sur les courts intervalles de temps durant lesquels les variations d'ERPs peuvent etre liees a des conditions experimentales, le signal psychologique est faible, au regard de la forte variabilite inter-individuelle des courbes ERP. En effet, ces donnees sont caracterisees par une structure de dependance temporelle forte et complexe. L'analyse statistique de ces donnees revient a tester pour chaque instant un lien entre l'activite cerebrale et des conditions experimentales. Une methode de decorrelation des statistiques de test est proposee, basee sur la modelisation jointe du signal et de la dependance a partir d'une connaissance prealable d'instants ou le signal est nul. Ensuite, l'apport du modele a facteurs dans le cadre general de l'Analyse Discriminante Lineaire est etudie. On demontre que la regle lineaire de classification optimale conditionnelle aux facteurs latents est plus performante que la regle non-conditionnelle. Un algorithme de type EM pour l'estimation des parametres du modele est propose. La methode de decorrelation des donnees ainsi definie est compatible avec un objectif de prediction. Enfin, on aborde de maniere plus formelle les problematiques de detection et d'identification de signal en situation de dependance. On s'interesse plus particulierement au Higher Criticism (HC), defini sous l'hypothese d'un signal rare de faible amplitude et sous l'independance. Il est montre dans la litterature que cette methode atteint des bornes theoriques de detection. Les proprietes du HC en situation de dependance sont etudiees et les bornes de detectabilite et d'estimabilite sont etendues a des situations arbitrairement complexes de dependance. Dans le cadre de l'identification de signal, une adaptation de la methode Higher Criticism Thresholding par decorrelation par les innovations est proposee.
Mediating Role of HRM in Organizational Conflict and Impact on Organizational Effectiveness : Empirical Evidence of Pakistan Public Universities

This paper aims to investigate the role of HRM in managing the organizational conflict in public sector universities. Hence, a questionnaire survey and interview with 371 respondents in the education sector in Pakistan was conducted to examine the respondents’ general perception about conflict to assess the role of HRM in conflict in education sector i.e., transforming of dysfunctional conflict into functional conflict. Therefore based on the qualitative data, it is found that functional conflict has a positive relationship with organizational effectiveness. Further, it is also found that HRM practices can transform dysfunctional conflict into functional conflict and have significant relationship with the organizational effectiveness. Keywords—Functional Conflict, Dysfunctional Conflict, Organizational Effectiveness, Organizational Conflict, HRM
The Clinical Course and Chronic Sequelae of Hepatitis B Virus Infection

Much has been learned about infection due to hepatitis B virus (HBV) in the more than 15 years since Blumberg and his colleagues [11] described the hepatitis B surface antigen (HBsAg). The development of sensitive serologic tests for detecting the antigens and antibodies specific for HBV has enabled the study of this infection at a remarkable pace during the past decade. The reader is referred to recent reviews [8,49] which chronologically trace the origin of these advances. The present paper will primarily emphasize current concepts of the clinical course of acute hepatitis B infection and its sequelae.
Novel techniques for Montgomery modular multiplication algorithms for public key cryptosystems

Extension of Montgomery multiplication algorithms in GF(p) are studied and analyzed. The time and space requirements of various state-of-the-art algorithms are presented. We propose Modified Montgomery Modular Multiplication Algorithms that reduces the number of computational operations such as number of additions, memory reads and writes involved in the existing algorithms, thereby, saving considerable time and area for execution. Many design examples has been solved to prove the theoretical correctness of the proposed algorithms. Complexity analysis shows that Modified Coarsely Integrated Scanning (MCIOS) consume less space and time compared to other modified Montgomery Algorithms. To verify the logical correctness, the proposed MCIOS algorithm was implemented in Xilinx Spartan3E FPGA. The total memory for execution of 64-bit operand is 135484 KB for MCIOS and 140496 KB for existing Coarsely Integrated Scanning (CIOS) method. The proposed algorithm can be changed to be suitable for any arbitrary Galois field size with little modifications. Also the proposed algorithm can be developed as architecture suitable for System on Chip (SoC) implementations of Elliptic curve cryptosystem. Subsequently, the system can be developed as a 3D chip.
Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.
Structural Basis of Oligosaccharide Receptor Recognition by Human Papillomavirus*

High risk human papillomavirus types 16 (HPV16) and 18 (HPV18) can cause cervical cancer. Efficient infection by HPV16 and HPV18 pseudovirions requires interactions of particles with cell-surface receptor heparan sulfate oligosaccharide. To understand the virus-receptor interactions for HPV infection, we determined the crystal structures of HPV16 and HPV18 capsids bound to the oligosaccharide receptor fragment using oligomeric heparin. The HPV-heparin structures revealed multiple binding sites for the highly negatively charged oligosaccharide fragment on the capsid surface, which is different from previously reported virus-receptor interactions in which a single type of binding pocket is present for a particular receptor. We performed structure-guided mutagenesis to generate mutant viruses, and cell binding and infectivity assays demonstrated the functional role of viral residues involved in heparin binding. These results provide a basis for understanding virus-heparan sulfate receptor interactions critical for HPV infection and for the potential development of inhibitors against HPV infection.