Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulating factors in the expression of radiation-induced oncogenic transformation.

Many assays for oncogenic transformation have been developed ranging from those in established rodent cell lines where morphological alteration is scored, to those in human cells growing in nude mice where tumor invasiveness is scored. In general, systems that are most quantitative are also the least relevant in terms of human carcinogenesis and human risk estimation. The development of cell culture systems has made it possible to assess at the cellular level the oncogenic potential of a variety of chemical, physical and viral agents. Cell culture systems afford the opportunity to identify factors and conditions that may prevent or enhance cellular transformation by radiation and chemicals. Permissive and protective factors in radiation-induced transformation include thyroid hormone and the tumor promoter TPA that increase the transformation incidence for a given dose of radiation, and retinoids, selenium, vitamin E, and 5-aminobenzamide that inhibit the expression of transformation. Densely ionizing alpha-particles, similar to those emitted by radon daughters, are highly effective in inducing transformations and appear to interact in a supra-additive fashion with asbestos fibers. The activation of a known dominant oncogene has not yet been demonstrated in radiation-induced oncogenic transformation. The most likely mechanism for radiation activation of an oncogene would be via the production of a chromosomal translocation. Radiation also efficiently induces deletions and may thus lead to the loss of a suppressor gene. ImagesFIGURE 4.
Lytic Activity of Recombinant Bacteriophage φ11 and φ12 Endolysins on Whole Cells and Biofilms of Staphylococcus aureus

ABSTRACT The recombinant φ11 endolysin hydrolyzed heat-killed staphylococci as well as staphylococcal biofilms. Cell wall targeting appeared to be a prerequisite for lysis of whole cells, and the combined action of the endopeptidase and amidase domains was necessary for maximum activity. In contrast, the φ12 endolysin was inactive and caused aggregation of the cells.
Clinical predictors in major depressive disorder

Remission is the goal for current depression treatment. However, the Sequenced Treatment Alternatives to Relieve Depression study has shown that the majority of patients will fail to achieve remission with a first-line antidepressant agent. Previous research has attempted to identify which depression treatments are preferred for whom by assessing baseline predictors. Of predictors, sex, age, severity of illness, depressive subtype, and comorbidity have predicted treatment response/nonresponse. However, these predictors have not always provided meaningful clinical correlation. Furthermore, based on the results of recent research, it is clear that clinicians need predictive variables to identify "next-best" preferred depression treatments for patients. This article defines these predictive variables as process predictors, in that they include factors that occur during the treatment process and are associated with outcomes.
A Study of the Issues and Security of Cloud Computing

-The paper identifies the issues and the solution to overcome these problems. Cloud computing is a subscription based service where we can obtain networked storage space and computer resources. This technology has the capacity to admittance a common collection of resources on request. It is the application provided in the form of service over the internet and system hardware in the data centers that gives these services. But having many advantages for IT organizations cloud has some issues that must be consider during its deployment. The main concern is security privacy and trust. There are various issues that need to be dealt with respect to security and privacy in a cloud computing scenario [4]. Keywords--Cloud, Issues, Security, Privacy, Resources, Technology.
State-Based Visibility for 3D Reconstruction from Multiple Views

Estimating visibility is one of the most important steps for multi-view reconstruction using volumetric scene representation. In this paper, we propose a simple approach to estimating visibility based on the current state of a scene which is implicitly represented as the zero level set of a function. Our method can determine the regions of a 3D space visible to several given viewpoints efficiently. Using this visibility method, we also present a new variational formulation for multi-view reconstruction. We cast the multi-view reconstruction problem as an op- timization of a novel energy functional amenable for minimization with an Euler-Lagrange driven evolution. The proposed algorithm has been applied to both synthetic and real datasets with promising results.
An evaluation of patient access to their electronic medical records via the World Wide Web

This paper describes initial experience with the Web-based Patient Clinical Information System (PatCIS). The system was designed to serve as a framework for the integration of applications that help patients access their electronic medical record, add data to their record, review on-line health information, and apply their own clinical data (automatically) to guideline programs that offer health advice. The architecture supports security functions and records user activities, relieving application developers from concerns about safe information practices and the evaluation process. PatCIS is being used to study the social and cognitive impact of allowing patients to have access to their health records via the Web. To date, PatCIS has grown to include 15 clinical functions and 4 dynamic links to literature (called infobuttons). Eleven patients have been enrolled since April, 1999; five have been active users. Experience shows that the PatCIS architecture supports application integration while providing adequate security and evaluation functions. Initial caution with the patient enrollment process has limited recruitment and, consequently, usage. However, experience thus far suggests that PatCIS has good usability and utility. No adverse events, including undesirable impact on doctor-patient interactions, have been reported. There do not appear to be any technical impediments to scaling up the enrollment to continue to observe patient usage.
Non-Gaussian effects in the cage dynamics of polymers

The correlation between the fast cage dynamics and structural relaxation is investigated in a model polymer system. It is shown that the cage vibration amplitude, as expressed by the Debye–Waller factor, and the relaxation time τα collapse on a single universal curve with a simple analytic form when the temperature, the density, the chain length and the monomer–monomer interaction potential are changed. For the physical states with the same τα the coincidence of the mean-square displacement, the intermediate scattering function and the non-Gaussian parameter is observed in a wide time window spanning from the ballistic regime to the onset of the Rouse dynamics driven by the chain connectivity. The role of the non-Gaussian effects is discussed.
Le Roman de Flamenca : An Annotated Corpus of Old Occitan

This paper describes an ongoing effort to digitize and annotate the corpus of Le Roman de Flamenca, a 13th-century romance written in Old Occitan. The goal of this project is twofold: The first objective is to digitize one of the earliest editions of the text and to create an interactive online database that will allow parallel access to a glossary, to translations of verses, and to comments from Paul Meyer’s edition. The second objective is to lemmatize and syntactically annotate the corpus and make it accessible using the ANNIS online-search engine.
The Role of Construal Level in Attentional Bias Toward Temptation

Inducing a mindset of abstraction, i.e. high-level construal, increases people’s performance in various measures of self-control (Fujita & Han, 2009; Fujita & Roberts, 2010; Kentaro Fujita et al., 2006). This has been found with both explicit attitudes towards tempting stimuli and evaluative associations with tempting stimuli. The current research seeks to extend this effect further, investigating whether construal level may affect automatic deployment of attention. Following work in the realm of addiction, which linked temptation strength with attentional bias, we tested whether construal manipulation may affect which objects attention is directed to. To induce high-level or low-level construal, we used the previously validated “Category – Exemplar” task (Fujita et al., 2006). To measure the effect of abstraction on attentional bias, we used Change Blindness, a paradigm in which participants spot a change made to a flickering picture. We conducted our test in the domain of food temptations. For half of the participants, the changed object was tempting (cupcake), and for the others it was neutral (mug). The aim of our research was to see if construal manipulation, changed object, and self-reported dieting status would interact to predict the attentional bias in the Change Blindness task. Results supported our prediction, as we found a three-way interaction in which dieters engaged in a high-level construal saw tempting stimuli slower than dieters in a low-level construal (t(132)=2.29, p=. 0238). A limitation to these promising results, however, is that the bulk of the interaction was found in the neutral change condition. The Role of Construal Level in Attentional Bias Toward Temptation 3
ROSSI X-RAY TIMING EXPLORER AND BeppoSAX OBSERVATIONS OF THE TRANSIENT X-RAY PULSAR XTE J1859+083

We present observations of the 9.8 s X-ray pulsar XTE J1859+083 made with the All Sky Monitor (ASM) and Proportional Counter Array (PCA) on board the Rossi X-ray Timing Explorer, and the Wide Field Camera (WFC) on board BeppoSAX. The ASM data cover a 12 year time interval and show that an extended outburst occurred between approximately MJD 50,250 and 50,460 (1996 June 16 to 1997 January 12). The ASM data excluding this outburst interval suggest a possible modulation with a period of 60.65 ± 0.08 days. Eighteen sets of PCA observations were obtained over an approximately one month interval in 1999. The flux variability measured with the PCA appears consistent with the possible period found with the ASM. The PCA measurements of the pulse period showed it to decrease nonmonotonically and then to increase significantly. Doppler shifts due to orbital motion rather than accretion torques appear to be better able to explain the pulse period changes. Observations with the WFC during the extended outburst give a position that is consistent with a previously determined PCA error box, but which has a significantly smaller error. The transient nature of XTE J1859+083 and the length of its pulse period are consistent with it being a Be/neutron star binary. The possible 60.65 day orbital period would be of the expected length for a Be star system with a 9.8 s pulse period.
A Speech Endpoint Detection Algorithm Based on Entropy and RBF Neural Network

Speech endpoint detection is an important step in the field of speech analysis, speech synthesis and speech recognition. This paper proposed an endpoint detection algorithm, which used amplitude entropy, spectral entropy and frame energy as feature parameters and utilized RBF neural network as a feature classification system. 170 sentences are used as testing data to detect speech endpoint, which length is from 4 second to 7 second. The experiments show that the testing results using RBF neural network are better than that using entropy alone or BP neural network based on entropy.
Exchange Rates and Inflation Rates: Exploring Nonlinear Relationships

This paper investigates the Purchasing Power Parity Theory (PPP) in the context of possible nonlinear relationships between prices and exchange rates of three key currencies. The main contribution of this paper is testing for nonlinearities and nonlinear relationships in a framework of information arrival. Three issues motivated the paper. First, research interest in exchange rate fluctuations, PPP, and exchange rate pass through. Second, market volatilities have triggered curiosity in nonlineraities in various economic and financial time series and nonlinear relationships and chaos in financial markets. For instance, the study of chaotic behavior may shed some light on the nature of latent nonlinearities. Third, developments in the econometrics of nonlinearity in the last three decades offer researchers new tools for detecting relationships that are inherently nonlinear and may not be conducive to various methodologies that are seeking to impose linear modeling on nonlinear relationships. Our findings show strong evidence that the exchange series exhibit nonlinear dependencies that may be inconsistent with chaotic structure. We identify GARCH(1,1) process as the model that best explains the nonlinearities in the monthly exchange rates and inflation rates. Therefore, we propose and estimate bivariate GARCH(1,1) models of the variances to ascertain the flow of information between exchange rates and prices. Bivariate GARCH models show that, the volatility spillover and information arrival between exchange rates and price levels occur simultaneously. Thus, we find support for the PPP theory and exchange rate pass through in the economies under consideration. We conclude that two theories, i.e., the exchange rate pass through and PPP may simultaneously hold the key to exchange rate analysis.
Hormonal changes in relation to biomass partitioning and shoot growth impairment in salinized tomato (Solanum lycopersicum L.) plants

Following exposure to salinity, the root/shoot ratio is increased (an important adaptive response) due to the rapid inhibition of shoot growth (which limits plant productivity) while root growth is maintained. Both processes may be regulated by changes in plant hormone concentrations. Tomato plants (Solanum lycopersicum L. cv Moneymaker) were cultivated hydroponically for 3 weeks under high salinity (100 mM NaCl) and five major plant hormones (abscisic acid, ABA; the cytokinins zeatin, Z, and zeatin-riboside, ZR; the auxin indole-3-acetic acid, IAA; and the ethylene precursor 1-aminocyclopropane-1-carboxylic acid, ACC) were determined weekly in roots, xylem sap, and leaves. Salinity reduced shoot biomass by 50–60% and photosynthetic area by 20–25% both by decreasing leaf expansion and delaying leaf appearance, while root growth was less affected, thus increasing the root/shoot ratio. ABA and ACC concentrations strongly increased in roots, xylem sap, and leaves after 1 d (ABA) and 15 d (ACC) of salinization. By contrast, cytokinins and IAA were differentially affected in roots and shoots. Salinity dramatically decreased the Z+ZR content of the plant, and induced the conversion of ZR into Z, especially in the roots, which accounted for the relative increase of cytokinins in the roots compared to the leaf. IAA concentration was also strongly decreased in the leaves while it accumulated in the roots. Decreased cytokinin content and its transport from the root to the shoot were probably induced by the basipetal transport of auxin from the shoot to the root. The auxin/cytokinin ratio in the leaves and roots may explain both the salinity-induced decrease in shoot vigour (leaf growth and leaf number) and the shift in biomass allocation to the roots, in agreement with changes in the activity of the sink-related enzyme cell wall invertase.
Semi-Markovian User State Estimation and Policy Optimization for Energy Efficient Mobile Sensing

User context monitoring using sensors on mobile devices benefits end-users unobtrusively and in real-time by providing information support to various kinds of mobile applications and services. A pervasive question, however, is how the sensors on a mobile device could be scheduled more efficiently such that they can detect more user information with as little energy usage as possible. In this paper, we model the user state sensing problem as the intermittent sampling of a semi-Markov process. Assuming sensors make perfect detections, we propose (a) a semi-Markovian state estimation mechanism that selects the most likely user state while observations are missing, and (b) a tractable approximation to a semi-Markov optimal sensing policy. The approximate semi-Markov optimal sensing policy us determines the duration the sensor should stay idle based on its current state detection before making the next observation, such that the expected state estimation error is minimized while maintaining a given energy budget. Both the semi-Markov estimation mechanism and the novel sensing policy us we develop are evaluated on simulated two-state processes and real user state traces, and their performances are shown to outperform Markov estimation and the Markov-optimal policy (studied in [25]), where the gain depends on the particular state distributions. Finally, we implement an energy efficient human activity recognition system on Nokia N95 smart phones, where the accelerometer is operated according to us . We demonstrate by a set of real experiments that the battery lifetime could be increased to at least three times as compared to continuous sensing, while producing only less than 3% estimation error.
Legitimation durch Massenmedien? Die öffentliche Thematisierung der Humangenomforschung im Ländervergleich

Empfohlene Zitierung / Suggested Citation: Gerhards, J., & Schäfer, M. S. (2008). Legitimation durch Massenmedien? Die öffentliche Thematisierung der Humangenomforschung im Ländervergleich. In K. -S. Rehberg (Hrsg.), Die Natur der Gesellschaft: Verhandlungen des 33. Kongresses der Deutschen Gesellschaft für Soziologie in Kassel 2006. Teilbd. 1 u. 2 (S. 1078-1094). Frankfurt am Main: Campus Verl. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-152909
Artemether-Lumefantrine versus Dihydroartemisinin-Piperaquine for Treating Uncomplicated Malaria: A Randomized Trial to Guide Policy in Uganda

Background Uganda recently adopted artemether-lumefantrine (AL) as the recommended first-line treatment for uncomplicated malaria. However, AL has several limitations, including a twice-daily dosing regimen, recommendation for administration with fatty food, and a high risk of reinfection soon after therapy in high transmission areas. Dihydroartemisinin-piperaquine (DP) is a new alternative artemisinin-based combination therapy that is dosed once daily and has a long post-treatment prophylactic effect. We compared the efficacy and safety of AL with DP in Kanungu, an area of moderate malaria transmission. Methodology/Principal Findings Patients aged 6 months to 10 years with uncomplicated falciparum malaria were randomized to therapy and followed for 42 days. Genotyping was used to distinguish recrudescence from new infection. Of 414 patients enrolled, 408 completed follow-up. Compared to patients treated with artemether-lumefantrine, patients treated with dihydroartemisinin-piperaquine had a significantly lower risk of recurrent parasitaemia (33.2% vs. 12.2%; risk difference = 20.9%, 95% CI 13.0–28.8%) but no statistically significant difference in the risk of treatment failure due to recrudescence (5.8% vs. 2.0%; risk difference = 3.8%, 95% CI −0.2–7.8%). Patients treated with dihydroartemisinin-piperaquine also had a lower risk of developing gametocytaemia after therapy (4.2% vs. 10.6%, p = 0.01). Both drugs were safe and well tolerated. Conclusions/Significance DP is highly efficacious, and operationally preferable to AL because of a less intensive dosing schedule and requirements. Dihydroartemisinin-piperaquine should be considered for a role in the antimalarial treatment policy of Uganda. Trial Registration Controlled-Trials.com ISRCTN75606663
Clerodendrum colebrookianum Walp.: A potential folk medicinal plant of North

In view of extensive ethno-medicinal importance and utilization in various forms of ethnomedicinal applications of Clerodendrum colebrookianum in the north eastern region, the present paper is an effort to compile the existing information on folklore medicine uses by different communities of north eastern India. The paper also encompasses to analyze the potential aspects in scientific identification of principle compounds and formulation of druglike leads based on basic and applied research activities and for development of sustainable exploitation and conservation strategies in the near future. The present work is an extensive review and analysis of published literature supplemented by actual field surveys conducted and consultation with local healers and peoples familiar with ethnobotanical and ethnomedicinal uses of Clerodendrum colebrookianum in different parts of the north eastern India. C. colebrookianum is known by more than thirty vernacular names among 20 different tribes and communities of north eastern region. The plant is used for treatment and cure of more than 16 different diseases and ailments. The use of young and tender leaves as decoction for antihypertensive purpose was the most common form of ethnomedicinal application for the species of C . colebrookianum among all ethnic tribes and communities in the region. A detailed investigation on the phytochemical, pharmacological properties of C. colebrookianum may lead to discover the potential lead compounds or molecules against life threatening diseases of human life such as hypertension, diabetes, etc.
Online setpoint optimisation cooperating with predictive control of a yeast fermentation process : A neural network approach

Online set-point optimisation which cooperates with model predictive control (MPC) and its application to a yeast fermentation process are described. A computationally efficient multilayer control system structure with adaptive steady-state target optimisation (ASSTO) and a suboptimal MPC algorithm are presented in which two neural models of the process are used. For set-point optimisation, a steady-state neural model is linearised online and the set-point is calculated from a linear programming problem. For MPC, a dynamic neural model is linearised online and the control policy is calculated from a quadratic programming problem. In consequence of linearisation of neural models, the necessity of online nonlinear optimisation is eliminated. Results obtained in the proposed structure are comparable with those achieved in a computationally demanding structure with nonlinear optimisation used for set-point optimisation and MPC. & 2011 Elsevier Ltd. All rights reserved.
A Graphene-Based Biosensing Platform Based on Regulated Release of an Aptameric DNA Biosensor

A novel biosensing platform was developed by integrating an aptamer-based DNA biosensor with graphene oxide (GO) for rapid and facile detection of adenosine triphosphate (ATP, as a model target). The DNA biosensor, which is locked by GO, is designed to contain two sensing modules that include recognition site for ATP and self-replication track that yields the nicking domain for Nt.BbvCI. By taking advantage of the different binding affinity of single-stranded DNA, double-stranded DNA and aptamer-target complex toward GO, the DNA biosensor could be efficiently released from GO in the presence of target with the help of a complementary DNA strand (CPDNA) that partially hybridizes to the DNA biosensor. Then, the polymerization/nicking enzyme synergetic isothermal amplification could be triggered, leading to the synthesis of massive DNA amplicons, thus achieving an enhanced sensitivity with a wide linear dynamic response range of four orders of magnitude and good selectivity. This biosensing strategy expands the applications of GO-DNA nanobiointerfaces in biological sensing, showing great potential in fundamental research and biomedical diagnosis.