gebhart/patrepeval huggingface dataset:
Genetic design of antennas and electronic circuits (1999)

This dissertation explores the use of genetic optimization for both antenna and circuit designs. Chapters 2 and 3 focus on parametric optimization of Yagi-Uda antenna arrays. In Chapter 2, Yagi-Uda arrays optimized with traditional binary genetic algorithms were found to perform better than gradient optimized arrays previously published in the literature. In Chapter 3, several different types of genetic algorithms and one gradient method were used to optimize a Yagi-Uda array for operation over a band of frequencies. The most important result from this chapter demonstrated that combining gradient and genetic optimization methods within the same process produces excellent results in an efficient manner. 
Chapters 4 and 5 introduce genetic design, which uses a formally defined design language in conjunction with genetic algorithms to optimize both the structure and the numerical parameters of a design. The design language includes a grammar that describes how building blocks are connected together to form a final design solution. This grammar can be either be very vague or very specific depending on the purpose of the designer. With a vague grammar, the genetic algorithm searches a very large design space, and occasionally finds an unexpected solution to a design problem. If the vague grammar fails to find a solution, incorporating knowledge about the problem into the grammar narrows the search to a region of the design space expected to yield good results. This results in more conventional design solutions that usually perform reasonably well. 
The antenna design example in Chapter 4 compared three different design languages for the design a 40% bandwidth antenna array composed of up to 10 array elements. Two out of three languages produced arrays that performed better than a traditional 10-element log-periodic structure optimized for the same problem. 
In Chapter 5, genetic design was applied to analog circuit design. The method outlined here was able to optimize a low-pass filter design in less than 10 minutes on a single CPU. This IS 4 orders of magnitude faster than genetic programming methods used on the same problem In the past. Design grammars are primarily responsible for this significant increase in efficiency. The simulation method, which integrated two-port network theory with the circuit chromosome and only had to recalculate small portions of a circuit as it evolved from generation to generation, also played a role.
Menin expression is regulated by transforming growth factor beta signaling in leukemia cells. (2011)

These results provided the first piece of evidence of cross-talk between menin and TGF-β signaling pathways in regulating proliferation of leukemia cells, suggesting that manipulating the cross-talk of the two pathways may lead to a novel therapy for leukemia.
Improved YOLOX’s Anchor-Free SAR Image Ship Target Detection (2022)

For the characteristics of synthetic aperture radar (SAR) images, such as the dense arrangement of ship targets on shore, which are easily affected by land, the sparse distribution of small ships in the deep sea, which are easily missing detect, and also the existence of a lot of negative sample background areas. We propose a new method based on improved YOLOX as Anchor Free target detection method, which greatly improves the training efficiency compared with the preset anchor box. In view of the problem that densely packed ship targets are easy to miss, and the ship target in the deep sea is weak and the distribution is sparse. We propose improved corner efficient intersection over union (ICEIOU) to further comprehensively consider the regression parameters, and the loss function is optimized for the network training process. We use Adaptive-NMS to adaptively adjusts the non-maximum suppression (NMS) threshold value for the dense arrangement and sparse distribution of ships, and atrous convolution is used to improve the problem of some detailed information loss. And combined with coordinate attention mechanism, high-speed and high-precision ship target detection is realized. The experimental results show that compared with the original YOLOX method, the detection precision of the method in this paper on HRSID dataset is improved from the original 88.81% to 91.48%, and the mAP index is improved from the original 87.72% to 91.76%, which is obviously better than the comparison method.
Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods (2013)

Sparse learning has recently received increasing attention in many areas including machine learning, statistics, and applied mathematics. The mixed-norm regularization based on the l1q norm with q>1 is attractive in many applications of regression and classification in that it facilitates group sparsity in the model. The resulting optimization problem is, however, challenging to solve due to the inherent structure of the mixed-norm regularization. Existing work deals with special cases with q=1, 2, infinity, and they cannot be easily extended to the general case. In this paper, we propose an efficient algorithm based on the accelerated gradient method for solving the general l1q-regularized problem. One key building block of the proposed algorithm is the l1q-regularized Euclidean projection (EP_1q). Our theoretical analysis reveals the key properties of EP_1q and illustrates why EP_1q for the general q is significantly more challenging to solve than the special cases. Based on our theoretical analysis, we develop an efficient algorithm for EP_1q by solving two zero finding problems. To further improve the efficiency of solving large dimensional mixed-norm regularized problems, we propose a screening method which is able to quickly identify the inactive groups, i.e., groups that have 0 components in the solution. This may lead to substantial reduction in the number of groups to be entered to the optimization. An appealing feature of our screening method is that the data set needs to be scanned only once to run the screening. Compared to that of solving the mixed-norm regularized problems, the computational cost of our screening test is negligible. The key of the proposed screening method is an accurate sensitivity analysis of the dual optimal solution when the regularization parameter varies. Experimental results demonstrate the efficiency of the proposed algorithm.
How I treat autoimmune lymphoproliferative syndrome (2011)

Autoimmune lymphoproliferative syndrome (ALPS) represents a failure of apoptotic mechanisms to maintain lymphocyte homeostasis, permitting accumulation of lymphoid mass and persistence of autoreactive cells that often manifest in childhood with chronic nonmalignant lymphadenopathy, hepatosplenomegaly, and recurring multilineage cytopenias. Cytopenias in these patients can be the result of splenic sequestration as well as autoimmune complications manifesting as autoimmune hemolytic anemia, immune-mediated thrombocytopenia, and autoimmune neutropenia. More than 300 families with hereditary ALPS have now been described; nearly 500 patients from these families have been studied and followed worldwide over the last 20 years by our colleagues and ourselves. Some of these patients with FAS mutations affecting the intracellular portion of the FAS protein also have an increased risk of B-cell lymphoma. The best approaches to diagnosis, follow-up, and management of ALPS, its associated cytopenias, and other complications resulting from infiltrative lymphoproliferation and autoimmunity are presented.
Acid-Sensitive Sheddable PEGylated PLGA Nanoparticles Increase the Delivery of TNF-α siRNA in Chronic Inflammation Sites (2016)

There has been growing interest in utilizing small interfering RNA (siRNA) specific to pro-inflammatory cytokines, such as tumor necrosis factor-α ( TNF-α), in chronic inflammation therapy. However, delivery systems that can increase the distribution of the siRNA in chronic inflammation sites after intravenous administration are needed. Herein we report that innovative functionalization of the surface of siRNA-incorporated poly (lactic-co-glycolic) acid (PLGA) nanoparticles significantly increases the delivery of the siRNA in the chronic inflammation sites in a mouse model. The TNF-α siRNA incorporated PLGA nanoparticles were prepared by the standard double emulsion method, but using stearoyl-hydrazone-polyethylene glycol 2000, a unique acid-sensitive surface active agent, as the emulsifying agent, which renders (i) the nanoparticles PEGylated and (ii) the PEGylation sheddable in low pH environment such as that in chronic inflammation sites. In a mouse model of lipopolysaccharide-induced chronic inflammation, the acid-sensitive sheddable PEGylated PLGA nanoparticles showed significantly higher accumulation or distribution in chronic inflammation sites than PLGA nanoparticles prepared with an acid-insensitive emulsifying agent (i.e., stearoyl-amide-polyethylene glycol 2000) and significantly increased the distribution of the TNF-α siRNA incorporated into the nanoparticles in inflamed mouse foot.
Quantification of citrullinated histones: Development of an improved assay to reliably quantify nucleosomal H3Cit in human plasma (2020)

Our novel approach using defined nucleosome controls enables reliable quantification of H3Cit in human plasma. This assay will be broadly applicable to study the role of histone citrullination in disease and its utility as a biomarker.
Monoclonal antibodies to rat sarcomata. I. Immunization procedures and source of lymphoid cells for hybridoma production. (1982)

Hybridomas secreting monoclonal antibodies with specificity for Hooded rat fibrosarcomata have been obtained by fusion of the rat myeloma Y3 Ag 1.2.3. (Galfre, Milstein & Wright, 1979) with cells taken from spleens or lymph nodes of immunized syngeneic and allogeneic donors. Two of the monoclonal antibodies, both derived from he spleens of tumour bearers, showed specificity for individual tumours one for MC24 (M10/76) and the other for HSNTC (11/160). These two antibodies had a long half-life in the blood when injected intravenously showing that they had a low affinity for normal tissue antigens. Monoclonal antibodies exhibiting broad tumour specificity or extensive cross-reactivity with normal cells were secreted by many of the hybridomas derived from both syngeneic and allogeneic rats that had been hyperimmunized with tumour cells. These results are discussed in relation to the production of monoclonal anti-tumour antibodies for use in experimental therapy.
Interactive breast cancer segmentation based on relevance feedback: from user-centered design to evaluation (2009)

Computer systems play an important role in medical imaging industry since radiologists depend on it for visualization, interpretation, communication and archiving. In particular, computer-aided diagnosis (CAD) systems help in lesion detection tasks. This paper presents the design and the development of an interactive segmentation tool for breast cancer screening and diagnosis. The tool conception is based upon a user-centered approach in order to ensure that the application is of real benefit to radiologists. The analysis of user expectations, workflow and decision-making practices give rise to the need for an interactive reporting system based on the BIRADS, that would not only include the numerical features extracted from the segmentation of the findings in a structured manner, but also support human relevance feedback as well. This way, the numerical results from segmentation can be either validated by end-users or enhanced thanks to domain-experts subjective interpretation. Such a domain-expert centered system requires the segmentation to be sufficiently accurate and locally adapted, and the features to be carefully selected in order to best suit user's knowledge and to be of use in enhancing segmentation. Improving segmentation accuracy with relevance feedback and providing radiologists with a user-friendly interface to support image analysis are the contributions of this work. The preliminary result is first the tool conception, and second the improvement of the segmentation precision.
Hepatoma-derived growth factor is a pulmonary endothelial cell-expressed angiogenic factor (2004)

Hepatoma-derived growth factor (HDGF) was previously identified as a developmentally regulated cardiovascular and renal gene that is mitogenic for vascular smooth muscle and aortic endothelial cells. As reciprocal interactions of smooth muscle and endothelial cells are necessary for vascular formation, we examined whether HDGF plays a role in angiogenesis. According to immunohistochemistry, HDGF was highly expressed in endothelial cells of nonmuscularized, forming blood vessels of the fetal lung. HDGF was also expressed in endothelial cells of small (20 microm) mature arteries and veins. By Western immunoblotting, HDGF was highly expressed by human pulmonary microvascular endothelial cells in vitro. Adenoviral overexpression of HDGF was mitogenic for human pulmonary microvascular endothelial cells in serum-free medium, stimulating a 1.75-fold increase in bromodeoxyuridine (BrdU) uptake and a twofold increase in cell migration. With the chick chorioallantoic membrane (CAM), a biologic assay for angiogenesis, exogenous recombinant HDGF significantly stimulated blood vessel formation and a dose-dependent reorganization of cells within the CAM into a more compact, linear alignment reminiscent of tube formation. According to double immunostaining for endothelial cells with a transforming growth factor-betaII receptor antibody and BrdU as a marker of cell proliferation, exogenous HDGF selectively stimulated endothelial cell BrdU uptake. HDGF also activated specific ERK1/2 signaling and did not overlap with VEGF SAPK/JNK, Akt-mediated pathways. We conclude that HDGF is a highly expressed vascular endothelial cell protein in vivo and is a potent endothelial mitogen and regulator of endothelial cell migration by mechanisms distinct from VEGF.
Investigation on the short-circuit capability of 1200 V trench gate field-stop IGBTs (2003)

The short circuit failure mechanism of newly developed 1200 V/150 A trench gate field-stop IGBT has been investigated. The devices mainly fail after a few hundred microseconds of the short-circuit turn-off. It has been found that the leakage current due to extreme temperature rise in the backside layers results in thermal runaway during off-state. The device with improved backside layer achieved more than 15 /spl mu/s of short circuit capability while keeping the low on-state voltage drop of 1.55 V.
Two-component regulatory systems responsive to environmental stimuli share strongly conserved domains with the nitrogen assimilation regulatory genes ntrB and ntrC. (1986)

We report that the ntrB and ntrC proteins of Bradyrhizobium sp. [Parasponia] strain RP501 share homology with other regulatory proteins. There is extensive conservation of C-terminal regions between products of RP501 ntrB; Klebsiella pneumoniae ntrB; Escherichia coli envZ, cpxA, and phoR; Agrobacterium tumefaciens virA; and, to a lesser extent, E. coli cheA. There is also extensive conservation of N-terminal regions between products of RP501 ntrC; K. pneumoniae ntrC; E. coli ompR, sfrA, phoB, cheY and cheB; Salmonella typhimurium cheB and cheY; Bacillus subtilis spoOA and spoOF; and A. tumefaciens virG. We propose that these regulatory genes comprise two-component regulatory systems that evolved from a common ancestral system that involved transduction of information about the status of the environment by one protein domain (the C-terminal regions conserved among ntrB, envZ, etc.) to a second one (the N-terminal region conserved among ntrC, ompR, etc.). The ntrC-set protein then acts upon a specific responding mechanism, typically as a transcriptional activator but also as an effector of the maturation of outer membrane proteins or as a modulator of the direction of flagella rotation.
Towards Kernel Density Estimation over Streaming Data (2006)

A variety of real-world applications heavily relies on the analysis of transient data streams. Due to the rigid processing requirements of data streams, common analysis techniques as known from data mining are not applicable. A fundamental building block of many data mining and analysis approaches is density estimation. It provides a well-defined estimation of a continuous data distribution, a fact which makes its adaptation to data streams desirable. A convenient method for density estimation utilizes kernels. However, its computational complexity collides with the processing requirements of data streams. In this work, we present a new approach to this problem that combines linear processing cost with a constant amount of allocated memory. We even support a dynamic memory adaptation to changing system resources. Our kernel density estimators over streaming data are related to M-Kernels, a previously proposed technique, but substantially improve them in terms of accuracy as well as processing time. The results of an experimental study with synthetic and real-world data streams substantiate the efficiency and effectiveness of our approach as well as its superiority to M-Kernels with respect to estimation quality and processing time.
Semantic representation (2004)

Semantic understanding of multimedia content is critical in enabling effective access to all forms of digital media data. By making large media repositories searchable, semantic content descriptions greatly enhance the value of such data. Automatic semantic understanding is a very challenging problem and most media databases resort to describing content in terms of low-level features or using manually ascribed annotations. Recent techniques focus on detecting semantic concepts in video, such as indoor, outdoor, face, people, nature, etc. This approach works for a fixed lexicon for which annotated training examples exist. In this paper we consider the problem of using such semantic concept detection to map the video clips into semantic spaces. This is done by constructing a model vector that acts as a compact semantic representation of the underlying content. We then present experiments in the semantic spaces leveraging such information for enhanced semantic retrieval, classification, visualization, and data mining purposes. We evaluate these ideas using a large video corpus and demonstrate significant performance gains in retrieval effectiveness.
Design of Frequency Selective Windows for Improved Indoor Outdoor Communication (2006)

The use of low emissivity windows degrades radio communication. This Communication presents design, manufacturing, and test measurements for an energy saving window that is transparent to GSM, GPS, and 3G radio wave frequencies. A frequency selective structure (FSS) is used in the metallic coating of the window to provide the desirable transparency in the frequency range from 900 MHz to 2 GHz. The periodic pattern used for the FSS is of the aperture type and the elements are hexagon loops. The FSS simulations are performed using the mode matching technique as well as the finite-difference time domain method. A frequency selective window was manufactured from a commercially available low emissivity glass. Measurements indicate that the frequency selective window has approximately 10 dB better transmission in the 900 MHz-2 GHz band than the original window.
Heme Oxygenase-1 Protects Pancreatic β Cells from Apoptosis Caused by Various Stimuli (2001)

Profound cell stress that occurs in islets after transplantation, as well as at the onset of diabetes, results in beta-cell loss through apoptosis. Protection of beta cells by HO-1 improves their survival in vitro after various proapoptotic stimuli, suggesting that HO-1 suppresses one or several signaling pathways leading to apoptosis. We hypothesize that our in vitro findings can be extrapolated to the in vivo situation, and we propose that expression of HO-1 in islets may illuminate a valuable new approach to improving diabetes treatment.
Repairing the basic defect in cystic fibrosis – one approach is not enough (2015)

Cystic fibrosis has attracted much attention in recent years due to significant advances in the pharmacological targeting of the basic defect underlying this recessive disorder: the deficient functional expression of mutant cystic fibrosis transmembrane conductance regulator (CFTR) chloride channels at the apical membrane of epithelial cells. However, increasing evidence points to the reduced efficacy of single treatments, thus reinforcing the need to combine several therapeutic strategies to effectively target the multiple basic defect(s). Protein-repair therapies that use potentiators (activating membrane-located CFTR) or correctors (promoting the relocation of intracellular-retained trafficking mutants of CFTR) in frequent mutations such as F508del and G551D have been put forward and made their way to the clinic with moderate to good efficiency. However, alternative (or additional) approaches targeting the membrane stability of mutant proteins, or correcting the cellular phenotype through a direct effect upon other ion channels (affecting the overall electrolyte transport or simply promoting alternative chloride transport) or targeting less frequent mutations (splicing variants, for example), have been proposed and tested in the field of cystic fibrosis (CF). Here, we cover the different strategies that rely on novel findings concerning the CFTR interactome and signalosome through which it might be possible to further influence the cellular trafficking and post-translational modification machinery (to increase rescued CFTR abundance and membrane stability). We also highlight the new data on strategies aiming at the regulation of sodium absorption or to increase chloride transport through alternative channels. The development and implementation of these complementary approaches will pave the way to combinatorial therapeutic strategies with increased benefit to CF patients.
Applying Multidimensional Framework in Agile Software Development (MDFA) (2021)

Software development is a complex and expensive job. As software systems become more complex day by day because of several aspects e.g. innovation, business Automation, data privacy, and security issues. To develop a quality product and construct software that satisfies customer needs, we are required to develop a system that fulfills the needs of users. For developing a perfect system we also need a perfect framework or architecture. The proposed framework is just not a framework, but it provides us a complete pattern and flows to develop a software system. It includes initial steps from requirements gathering till its final steps like implementation and testing. This research is based on such a multidimensional framework for software development which covers six dimensions that are used implicitly or explicitly. There are four viewpoints that represent different stakeholders. These dimensions and viewpoints are integrated with the scrum process to increase the quality of software systems. The suggested framework is evaluated by a case study.
Circuit reliability of memory cells with SEU protection (for space application) (1992)

The use of high value polysilicon resistors to provide SEU (single event upset) hardening introduces a latent failure mechanism when not properly tested. This failure mechanism is only present in parts with SEU resistors. The resistance prevents detection of gate oxide defects using normal test techniques. As the circuit ages, the defect becomes more conductive, resulting in a functional failure. A detailed description of the failure mechanism and a set of distinguishing characteristics to aid in failure analysis are provided. Screening the defect population requires a simple high-voltage data retention test. The use of this screen reduced the failure rate in the subject circuit by over 30*.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>