Miracle-dz/UniFAR-FTUs huggingface dataset:
Harnessing RNAi-based nanomedicines for therapeutic gene silencing in B-cell malignancies

Significance RNA interference (RNAi) holds great promise as a novel therapeutic approach. Small interfering RNAs (siRNAs) that manipulate gene expression in leukocytes could be used to treat blood cancers. However, the lack of strategies for delivering siRNAs to leukocytes systemically has hampered the development of RNAi-based therapeutics. Here, we show that lipid-based nanoparticles coated with anti-CD38 monoclonal antibodies specifically target mantle cell lymphoma (MCL) cells and induce cell-specific therapeutic gene silencing in vivo. CD38-targeted nanoparticles that contain cyclin D1 siRNAs prolong survival of mice bearing MCL lymphomas in the bone marrow. This strategy opens a new avenue for treating MCL that might be applied to other hematological malignancies. Despite progress in systemic small interfering RNA (siRNA) delivery to the liver and to solid tumors, systemic siRNA delivery to leukocytes remains challenging. The ability to silence gene expression in leukocytes has great potential for identifying drug targets and for RNAi-based therapy for leukocyte diseases. However, both normal and malignant leukocytes are among the most difficult targets for siRNA delivery as they are resistant to conventional transfection reagents and are dispersed in the body. We used mantle cell lymphoma (MCL) as a prototypic blood cancer for validating a novel siRNA delivery strategy. MCL is an aggressive B-cell lymphoma that overexpresses cyclin D1 with relatively poor prognosis. Down-regulation of cyclin D1 using RNA interference (RNAi) is a potential therapeutic approach to this malignancy. Here, we designed lipid-based nanoparticles (LNPs) coated with anti-CD38 monoclonal antibodies that are specifically taken up by human MCL cells in the bone marrow of xenografted mice. When loaded with siRNAs against cyclin D1, CD38-targeted LNPs induced gene silencing in MCL cells and prolonged survival of tumor-bearing mice with no observed adverse effects. These results highlight the therapeutic potential of cyclin D1 therapy in MCL and present a novel RNAi delivery system that opens new therapeutic opportunities for treating MCL and other B-cell malignancies.
Executive Exercise Explained : Patterns for Stock Options †

It is well documented that executives granted stock options tend to exercise early and in a few large transactions or “blocks”. Standard risk-neutral valuation models cannot explain these patterns, and attempts to capture the exercise behavior of risk averse executives have been limited to the special case of one option. This paper solves for the optimal exercise behavior for a risk averse executive who is granted multiple stock options. We show that traditional utility-based models do not predict block exercise behavior. Rather, the risk averse executive exercises stock options individually at a sequence of increasing price thresholds. We give these thresholds in closed form. When, in addition, the executive exerts costly effort to exercise options, he faces a trade-off between exercising little and often to maximize return, and exercising larger quantities on fewer occasions to minimize effort. We find that as costs increase, options are exercised on fewer dates. The costly exercise utility-based model generates block exercise behavior and yields new predictions. In particular, executives should begin by exercising large blocks of options, but the block sizes should become smaller over time.
Universal HSPICE model for chalcogenide based phase change memory elements

We present a two terminal HSpice model for chalcogenide based phase change memory (CRAM) element. By including physical models of CRAM programming, this model can simulate not only the resistance change by different electrical pulses, but also temperature profile and crystalline fraction during the operation. Furthermore, it was successfully integrated with standard W/R circuit in memory technology. Output of sense amplifier vs writing current amplitude figure corresponded well with the typical R-I curve of CRAM elements.
Capturing implicit user influence in online social sharing

Online social sharing sites are becoming very popular nowadays among Web users, who use these sites to share their favourite items and to discover interesting and useful items from other users. While an explicit social network is not necessarily present in these sites, it is still possible that users influence one another in the process of item adoption through various implicit mechanisms. In this paper, we study how we can capture the implicit influences among the users in a social sharing site. We propose a probabilistic model for user adoption behaviour, where we assume that when user adopts an item, he would pick a user and choose from the set of items that this user has adopted. By using the model, we estimate the probability that one user influences another user in the course of item adoption, based on the temporal adoption pattern of the users. We carry out empirical studies of the model on Delicious, a popular social bookmarking site. Experiments show that our model can be used to predict item adoption more accurately than using collaborative filtering techniques. We find that the strength of implicit influence various across different topics. We also show that our method is able to identify the influential users who are more likely to possess items interested by other users. Our model can be used to study the dynamics in a social sharing site and to complement collaborative filtering in recommendation systems.
Robot navigation using a pressure generated mechanical stress field: "the biharmonic potential approach"

This paper suggests a new approach for navigation in a known environment. The approach is based on the biharmonic potential fields which govern mechanical stress fields in homogeneous solids. It is observed that a path generated by such a technique is free of sharp turns that may appear in its counterpart that is generated from an underlying harmonic potential. This in turns makes a path from the former more dynamically suitable for traversal. Also, the navigation field is extracted from the biharmonic potential in a manner that bypass the rapidly vanishing field problem which is encountered in the harmonic potential approach. Development of the biharmonic approach, simulation results, as well as comparison with the Neumann and Dirichlet setting of the harmonic approach are provided. <<ETX>>
Adaptively merging large-scale range data with reflectance properties

In this paper, we tackle the problem of geometric and photometric modeling of large intricately shaped objects. Typical target objects we consider are cultural heritage objects. When constructing models of such objects, we are faced with several important issues that have not been addressed in the past-issues that mainly arise due to the large amount of data that has to be handled. We propose two novel approaches to efficiently handle such large amounts of data: A highly adaptive algorithm for merging range images and an adaptive nearest-neighbor search to be used with the algorithm. We construct an integrated mesh model of the target object in adaptive resolution, taking into account the geometric and/or photometric attributes associated with the range images. We use surface curvature for the geometric attributes and (laser) reflectance values for the photometric attributes. This adaptive merging framework leads to a significant reduction in the necessary amount of computational resources. Furthermore, the resulting adaptive mesh models can be of great use for applications such as texture mapping, as we will briefly demonstrate. Additionally, we propose an additional test for the k-d tree nearest-neighbor search algorithm. Our approach successfully omits back-tracking, which is controlled adaptively depending on the distance to the nearest neighbor. Since the main consumption of computational cost lies in the nearest-neighbor search, the proposed algorithm leads to a significant speed-up of the whole merging process. In this paper, we present the theories and algorithms of our approaches with pseudo code and apply them to several real objects, including large-scale cultural assets.
Air Pollution and School Absenteeism: Results from a Natural Experiment

2 Abstract In this paper we examine the effect of air pollution on absenteeism among elementary school children in Utah Valley. We take advantage of a " natural " experiment that occurred when a large local steel mill closed for about 13 months in 1986 and 1987. Because the mill had a very large impact on particulate pollution but little or no effect on carbon monoxide, we are able to disentangle the effect of these two pollutants, using the mill closure and various measures of atmospheric stagnation as instruments. We find that particulate pollution had a strong impact on school absences, but that carbon monoxide did not. Our findings also suggest that OLS estimates significantly underestimate the effect of particulates on school absenteeism. However, our IV estimates of the effect of carbon monoxide are negative and implausible in our preferred IV specifications.
Decoupled control of the high mobility robot Hylos based on a dynamic stability margin

This paper concerns the control of an autonomous high mobility wheel-legged rover crossing uneven terrains. A new control strategy, using active redundancies of the robot, leads to elaborate a posture control based on the potential field approach of the stability measurement. Then a decoupled posture and trajectory control algorithm based on the velocity model of the robot is proposed. Last, simulation results showing performance of the control algorithm are presented.
Effect of early cold stress on the maturation of rice anthers

Male reproductive development in rice (Oryza sativa Linnaeus is very sensitive to various forms of environmental stresses including low temperature. Here, we present our findings on the proteomic analysis of the later developmental consequences of low temperature treatment on rice anthers. Anther proteins at the trinucleate stage, with or without cold treatment for four days at 12°C at the young microspore stage, were extracted, separated by two‐dimensional gel electrophoresis (2‐DE) and compared. More than 3000 rice anther proteins of cold‐sensitive cultivar Doongara plants at the trinucleate stage were resolved on 2‐DE gels over a pH range of 4–7 and detected by silver‐staining. Seventy protein spots were differentially displayed after four days of cold treatment at the young microspore stage. Of these, 12 protein spots were newly‐induced, 47 were up‐regulated, and 11 were down‐regulated by cold treatment at the early microspore stage. We identified 18 by matrix‐assisted laser desorption/ionization mass spectrometry time of flight (MALDI‐TOF) analysis. Of the identified proteins, seven were observed as breakdown (cleavage) products by a combination of 2‐DE and MALDI‐TOF analysis, thus demonstrating for the first time that cold temperature stress at the young microspore stage enhances and induces partial degradation of proteins in the rice anthers at the trinucleate stage.
Joint fault detection, identification, and state estimation based on conditional joint decision and estimation

This paper presents an approach to fault detection, identification, and state estimation (FDISE) for a dynamic system with abrupt total or partial failures. FDISE includes both decision and estimation and they are highly coupled. Decision includes fault detection and identification (FDI), while estimation is for failure magnitude and system state. Correct FDI benefits estimation and accurate estimation can facilitate FDI. Moreover, detection is binary with only two possibilities, but identification involves multiple hypotheses each for a specific fault. Thus, FDISE is a challenging joint decision and estimation (JDE) problem. Our recently proposed JDE approach provides a general and flexible framework to solve such a problem. In this paper, a joint FDISE (JFDISE) is proposed based on the conditional JDE method. In JFDISE, an interacting multiple-model estimator is used to obtain the hypothesis probabilities and the state estimates. Furthermore, the difficulty caused by the incompatibility of the decision set and the hypothesis set is handled. Simulation results for JFDISE of a flight control system with sequential actuator failures show that the JFDISE outperforms the decision then estimation and the separate estimation and decision methods in terms of a joint performance measure.
Systematic Brain Data Analysis: A Review

The Brain Data Analysis and evaluation is a challenging task. Focusing towards the human-thinking-centric studies characteristics, brain informatics (BI) emphasizes a systematic methodology with key issue of systematic brain data analysis. The brain data analytical methods are very rare and thus brain data research and implementation is more challenging. This paper reviews the existing research and methodologies developed so far, in the area of Brain Informatics, Web Intelligence, Learning Schemes, Analytical methods and relevant aspects of these along with their limitations. More data and analytical methods need to be added in the existing BI approaches. Also, there is high need to embed these into a mature computing environment.
Energy-aware complex network model with compensation

In this paper, we use complex network theory to analyze the evolving topology of wireless sensor networks (WSNs). Based on the BA model, we propose a novel complex network model, i.e., Neighborhood Log-on and Log-off model with energy awareness (NLL-E). NLL-E assumes locally preferential attachment, which exists in many complex networks. We further consider node addition and invalidation in topology evolvement, and add compensation mechanism for network robustness. The statistical properties and dynamics of NLL-E are analytically studied. Numerical simulations indicate that, comparing with BA, NLL-E has decreased average path length and increased network connectivity.
Adaptive algorithm of itarative inverse filter relaxation to acoustic fluctuation in sound reproduction system

In this paper, we newly propose an adaptive relaxation algorithm for inverse filter design of the multichannel sound reproduction system. The inverse filter of the conventional method often amplifies the background noise and line noise when the room transfer function changes. In order to resolve the problem, the adaptive relaxation algorithm based on the truncated singular value decomposition (TSVD) method is introduced, in which only one microphone to observe the noise condition is placed apart from listener’s ears. First, desired signals are reproduced at all control points for listening and control point for noise observation. Next, the number of truncated singular values of matrix composed of room transfer functions is determined based on the observed noise. The experimental result of the computer simulation using real environmental data reveals that the proposal method can prevent the noise amplification. The subjective evaluation in the real sound reproduction system also indicates the trade-off relation between the sound quality and the localization.
Enhanced Performance Consistency in Nanoparticle/TIPS Pentacene‐Based Organic Thin Film Transistors

In this study, inorganic silica nanoparticles are used to manipulate the morphology of 6,13‐bis(triisopropylsilylethynyl)‐pentacene (TIPS pentacene) thin films and the performance of solution‐processed organic thin‐film transistors (OTFTs). This approach is taken to control crystal anisotropy, which is the origin of poor consistency in TIPS pentacene based OTFT devices. Thin film active layers are produced by drop‐casting mixtures of SiO2 nanoparticles and TIPS pentacene. The resultant drop‐cast films yield improved morphological uniformity at ∼10% SiO2 loading, which also leads to a 3‐fold increase in average mobility and nearly 4 times reduction in the ratio of measured mobility standard deviation (μStdev) to average mobility (μAvg). Grazing‐incidence X‐ray diffraction, scanning and transmission electron microscopy as well as polarized optical microscopy are used to investigate the nanoparticle‐mediated TIPS pentacene crystallization. The experimental results suggest that the SiO2 nanoparticles mostly aggregate at TIPS pentacene grain boundaries, and 10% nanoparticle concentration effectively reduces the undesirable crystal misorientation without considerably compromising TIPS pentacene crystallinity.
Antigenotoxic Studies of Different Substances to Reduce the DNA Damage Induced by Aflatoxin B1 and Ochratoxin A

Mycotoxins are produced mainly by the mycelial structure of filamentous fungi, or more specifically, molds. These secondary metabolites are synthesized during the end of the exponential growth phase and appear to have no biochemical significance in fungal growth and development. The contamination of foods and feeds with mycotoxins is a significant problem for the adverse effects on humans, animals, and crops that result in illnesses and economic losses. The toxic effect of the ingestion of mycotoxins in humans and animals depends on a number of factors including intake levels, duration of exposure, toxin species, mechanisms of action, metabolism, and defense mechanisms. In general, the consumption of contaminated food and feed with mycotoxin induces to neurotoxic, immunosuppressive, teratogenic, mutagenic, and carcinogenic effect in humans and/or animals. The most significant mycotoxins in terms of public health and agronomic perspective include the aflatoxins, ochratoxin A (OTA), trichothecenes, fumonisins, patulin, and the ergot alkaloids. Due to the detrimental effects of these mycotoxins, several strategies have been developed in order to reduce the risk of exposure. These include the degradation, destruction, inactivation or removal of mycotoxins through chemical, physical and biological methods. However, the results obtained with these methods have not been optimal, because they may change the organoleptic characteristics and nutritional values of food. Another alternative strategy to prevent or reduce the toxic effects of mycotoxins is by applying antimutagenic agents. These substances act according to several extra- or intracellular mechanisms, their main goal being to avoid the interaction of mycotoxins with DNA; as a consequence of their action, these agents would inhibit mutagenesis and carcinogenesis. This article reviews the main strategies used to control AFB1 and ochratoxin A and contains an analysis of some antigenotoxic substances that reduce the DNA damage caused by these mycotoxins.
EEQuest: An Event Extraction and Query System

We present EEQuest, an application that extracts events from text using natural language processing (NLP) and supervised machine-learning techniques, and provides a system to query events extracted from a text corpus. We provide a use case for the application wherein we extract business-related events from news articles. The extracted events are then categorized based on the business organization/company that they are related to. Finally, the events are added to a knowledge base using which a query system is built. The system can be used to display events related to a particular organization or a group of organizations. Although we are using the system to extract business-related events, the event extraction mechanism can be used in a more general sense with any available textual data, to extract any kind of events that have a structure that can answer the question: Who did what, when and where?
Effect of Treatment for CHC on Liver Disease Progression and Hepatocellular Carcinoma Development in African Americans

Background and Aims: African Americans (AA) historically have a low response rate to hepatitis C therapies, and there is limited information available for this patient population regarding the development and treatment of chronic hepatitis C (CHC). The aim of this study was to evaluate liver disease progression and hepatocellular carcinoma (HCC) development in AA with CHC. Methods: Between 1995 and 2008, 246 AA patients with CHC were identified from a database of patients and followed until 2012-2013 (average 8 years) or the development of HCC after 2008. Results: Viral clearance (intent to treat; sustained virus response (SVR)) was achieved in 15% of patients with interferon based therapies with or without ribavirin. AA patients who achieved an SVR (n=22) did not develop HCC or new onset cirrhosis, whereas the HCC incidence in untreated AA patients was 23% (51/203). Patients who achieved an SVR also had improved fibrosis, as defined by the AST Platelet Ratio Index (APRI) and Fibrosis-4 (FIB-4) score, relative to nonresponders and untreated patients. Conclusions: The severity of liver disease at the first visit (except for cirrhosis) correlated with the development of HCC, but because of the overlap in values between patients, these measurements were not useful for predicting individual risk. Since cirrhosis at the first visit was not a predictive factor, treatment with newer antiviral therapies is the best option for reducing the incidence of advanced liver disease and its harmful outcomes in the AA population.
Block-Structured Adaptive Mesh Refinement on Curvilinear-Orthogonal Grids

An adaptive mesh refinement scheme for the equations of magnetohydrodynamics on curvilinear-orthogonal grids is presented. A block-structured refinement approach is used sharing important properties with the hybrid central-upwind/constrained-transport single grid solver like angular momentum conservation on cylindrical and spherical grids and the preservation of magnetic field solenoidality. The adaptive mesh framework is part of the astrophysical fluid dynamics code NIRVANA which is continuously developed and maintained by the author. The code is parallelized on the basis of the MPI library, and dynamic load balancing in adaptive mesh simulations is achieved by space-filling curve domain decomposition techniques. For various two- and three-dimensional magnetohydrodynamic problems adaptive mesh functionality and efficiency are demonstrated.
Einbürgerung: Rahmenbedingungen, Motive und Perspektiven des Erwerbs der deutschen Staatsangehörigkeit

Deutschland im Jahr 2020: Eine freie, solidari sche und kinderfreundliche Gesellschaft mit gleichen Chancen der wirtschaftlichen, sozialen und kulturellen Teilhabe unabhangig von Geschlecht und Herkunft; eine lebendige Demokratie mit enga gierten Burgerin nen und Burgern; eine nachhaltig wachsen de Wirtschaft mit guter Arbeit fur alle; ein vorsorgender Sozialstaat, der mehr Bildung und Gesundheit ermoglicht; ein Land, das in Euro pa und der Welt Verantwortung fur Frieden und sozialen Fortschritt ubernimmt.
Extending Process Improvement into a New Organizational Unit

The importance of software process improvement (SPI) is gaining increasing acknowledgement in software companies. Many companies have started SPI and try to extend it in all the functional units. However, some units may have problems initiating SPI. In this paper an initial level requirements and design practice assessment is presented. The assessment was conducted with a method that was specifically developed to pay attention to the organizational readiness for SPI and trying to obtain organizational support for it. The study summarizes the findings that establish a solid understanding of the current practices in the company, and identify concrete improvement areas. Even if the assessment method needs to be customized for each company, the case study suggests that it can help to establish a positive attitude towards SPI.