Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of the novel tumour suppressor p33ING1 is independent of p53

A recently cloned tumour suppressor candidate, p33ING1, has been shown in vitro to collaborate with p53 to execute growth arrest and apoptosis. However, it is unclear as to how the expression of ING1 is regulated in normal and stress conditions. Using a p53-knockout mouse model, we investigated if the expression of ING1 was dependent on p53. We found that there was no difference in ING1 mRNA and protein levels between p53+/+ and p53–/– murine organs. In addition, when normal human epithelial keratinocytes (NHEK) and a keratinocyte cell line, HaCaT, which lacks wild-type p53 function, were exposed to UVB irradiation, the expression levels of ING1 were elevated in both NHEK and HaCaT cells. It is interesting, however, that UVB irradiation did not induce ING1 expression in dermal fibroblasts isolated from p53+/+ and p53–/– mice. Based on our findings, we therefore conclude that the expression of ING1 is independent of p53 status. UV induction of ING1 in keratinocytes suggests that ING1 may play a role in cellular stress response and skin carcinogenesis. © 2000 Cancer Research Campaign http://www.bjcancer. com
Inheritance of Mid and High Oleic Acid Content in Ethiopian Mustard

Zero erucic acid Ethiopian mustard (Brassica carinata A. Braun) seed oil has a low oleic acid content (330 g kg -1 ). The mid oleic acid line AB3 (650 g kg -1 ) and the high oleic acid line AB1 (830 g kg -1 ) have been developed. The objective of this research was to study the inheritance of both traits in Ethiopian mustard. Plants of AB1 were reciprocally crossed with plants of the standard line 25X-1, the low linolenic acid line AB4, and AB3. Plants of AB3 were also reciprocally crossed with plants of 25X-1. A genetic study was conducted through the analysis of the fatty acid profile of F 1 , F 2 , BC 1 F 1 , and F 3 seed generations. The results revealed that mid oleic acid content in AB3 was determined by partially recessive alleles at a single locus O1, whereas high oleic acid content in AB1 was the result of partially recessive alleles at two loci, O1 and 012. Both loci produced an increment of oleic acid content of similar magnitude, although ol2 alleles had phenotypic expression only in presence of ol alleles in homozygous condition. Segregation patterns for oleic acid content were similar in crosses of AB1 with 25X-1 and AB4, which indicated that loci for high oleic acid content were not related to loci for low linolenic acid content. Recombination of genes controlling high oleic acid and low linolenic acid content resulted in phenotypes with >850 g kg -1 oleic acid and <25 g kg -1 linolenic acid. Reduction of linolenic acid content resulted in an increase of linoleic rather than oleic acid content.
Multigene Family for Bowman–Birk Type Proteinase Inhibitors of Wild Soja and Soybean: The Presence of Two BBI-A Genes and Pseudogenes

Genes for Bowman–Birk type protease inhibitors (BBIs) of wild soja (Glycine soja) and soybean (Glycine max) comprise a multigene family. The organization of the genes for wild soja BBIs (wBBIs) was elucidated by an analysis of their cDNAs and the corresponding genomic sequences, and compared with the counterparts in the soybean. The cDNAs encoding three types of wild soja BBIs (wBBI-A, -C, and -D) were cloned. Two subtypes of cDNAs for wBBI-A, designated wBBI-A1 and -A2, were further identified. Similar subtypes (sBBI-A1 and -A2) were also found in the soybean genome. cDNA sequences for wBBIs were highly homologous to those for the respective soybean homologs. Phylogenetic analysis of these cDNAs demonstrated the evolutional proximity between these two leguminae strains.
Consistent estimation of discrete-choice models for panel data with multiplicative effects

This paper presents an extension to the fixed-effect Logit for panel-data discrete-choice models, where the error component structure is multiplicative (individual effects multiplied by time effects). In linear models with such an error-component structure as investigated by Ahn, Lee and Schmidt (2001), usual fixed-effect estimators are generally inconsistent. We propose a conditional Logit estimator based on a different sufficient statistic, for the case where multiplicative time effects are known. When not the case, we discuss the implementation of the Modified Profile Likelihood based on a transformation of incidental parameters. The last estimator is an extension of Honore and Lewbel (2000) semiparametric estimator. We investigate small sample properties of these estimators with a Monte Carlo experiment.
CoWME: a general framework to evaluate cognitive workload during multimodal interaction

Evaluating human machine interaction in the case of multimodal systems is often a difficult task involving the monitoring of multiple sources, data fusion and results interpretation. While subtasks are highly dependent on the specific goal of the application and on the available interaction modalities, it is possible to formalize this workflow into a standard process and to consider a generic measure to estimate the ease of use of a specific application. In this work, we present CoWME, a modular software architecture describing multimodal human machine interaction evaluation, from data collection to final evaluation, in a formal way, in terms of cognitive workload. Communication protocols between modules are described in XML while data fusion is delegated to a configurable rule engine. An interface module is introduced between the monitoring modules and the rule engine to collect and summarize data streams for cognitive workload evaluation. We present a deployment example showing how this architecture is deployed by monitoring an interactive session with an Android application taking into account stressed speech detection, mydriasis and touch analysis.
Affordance based Part Recognition for Grasping and Manipulation

Affordances (unit utility, functional and topological relationships) and semantic scene understanding are key to building a generic, scalable and cognitive architecture for visual perception. ‘Affordance based object recognition’ or recognition based on affordance features is an important step in this regard. In this paper, we extend the scope of affordance features to define ‘Conceptual Equivalence Classes’ and to recognize these classes leading to a Visual Cognitive Engine. This schema is analogous to building a scalable unit (part/ part assembly/ object) recognition system. This system has been built with the target of enabling a robotic arm to grasp a-priori unseen objects in a cluttered scene using global knowledge. The Visual Cognitive Engine uses inputs from multiple ontology bases – ConceptNet (for unit concept definitions), WordNet/WebKB (for textual unit definitions), Otto Bock Human Grasping database (for grasp affordances), together with the Part Functional Affordance Schema, developed in this paper, to establish semantic unit affordances. Recognition of parts or part assemblies based on affordances, using the Visual Cognitive Engine enables knowledge of affordance and interaction modes for the entire object. This leads to a goaldirected object recognition and manipulation system that can perform implicit cognitive tasks such as substitute a cup for a mug, bottle, jug, pitcher, pilsner, beaker, chalice, goblet or any other unlabeled object, but with a physical part affording the ability to hold liquid and a part affording grasping, given the goal of ‘bringing an empty cup’ and no cups are available in the work environment. The performance of such a system is superior to traditional view-point based object recognition and manipulation systems. Keywords-Affordance, Recognition by Components, Part affordances, Grasping, Symbol binding
Ubi-Pen: Development of a Compact Tactile Display Module and Its Application to a Haptic Stylus

The objective of this research is to propose and design a compact tactile display module and verify its performance in a pen-like haptic interface. A small, safe, silent and light tactile display module with a low power dissipation has been built. Based on this module, we present the Ubi-Pen, a system providing texture and vibration stimuli. Preliminary evaluations indicate it can satisfactorily represent tactile patterns. We also investigate the optimal frequencies at which to present stimuli, and evaluate its capacity to support GUI operations by producing a simple click-like feedback when buttons are pressed
Adequate reconstruction of transparent objects on a shoestring budget

Reconstructing transparent objects is a challenging problem. While producing reasonable results for quite complex objects, existing approaches require custom calibration or somewhat expensive labor to achieve high precision. On the other hand, when an overall shape preserving salient and fine details is sufficient, we show in this paper a significant step toward solving the problem on a shoestring budget, by using only a video camera, a moving spotlight, and a small chrome sphere. Specifically, the problem we address is to estimate the normal map of the exterior surface of a given solid transparent object, from which the surface depth can be integrated. Our technical contribution lies in relating this normal reconstruction problem to one of graph-cut segmentation. Unlike conventional formulations, however, our graph is dual-layered, since we can see a transparent object's foreground as well as the background behind it. Quantitative and qualitative evaluation are performed to verify the efficacy of this practical solution.
Quantitative findings from a mixed methods evaluation of once-weekly therapeutic community day services for people with personality disorder

Background: Quantitative findings are presented from a mixed methods study of four one-day-a-week therapeutic communities for people with personality disorder (qualitative findings from the same study are reported in a separate paper). The evaluation assessed both the clinical efficacy of the model and its acceptability to service users, service employees and those who refer clients to the services. Aims: The study aimed to clarify whether one-day therapeutic communities can be effective for people with personality disorder. Method: Changes in the functioning of service users who attended the day services were assessed every 12 weeks for up to 1 year. Results: We found significant improvements in both the mental health and social functioning of service users. Changes in patterns of self-harm and service use were suggestive of possible underlying improvements but failed to reach significance levels. We also found evidence of the possible offset of costs within 16 months of an individual leaving one of the services. Conclusions: This study suggests one-day therapeutic communities may be both clinically- and cost-effective for people with personality disorder.
Assessment of the increase in variability when combining volumetric data from different scanners

In multicenter MRI studies, pooling of volumetric data requires a prior evaluation of compatibility between the different machines used. We tested the compatibility of five different scanners (2 General Electric Signa, 2 Siemens Symphony, and a Philips Gyroscan) at five different sites by repeating the scans of five volunteers at each of the sites. Using a semiautomatic method based on the Talairach atlas, and SPM algorithms for tissue segmentation (multimodal T1 and T2, or T1‐only), we obtained volume measurements of the main brain lobes (frontal, parietal, occipital, temporal) and for each tissue type. Our results suggest that pooling of multisite data adds small error for whole brain measurements, intersite coefficient of variation (CV) ranging from 1.8 to 5.2%, respectively, for GM and CSF. However, in the occipital lobe, intersite CV can be as high as 11.7% for WM and 17.3% for CSF. Compared with the intersite, intrasite CV values were always much lower. Whenever possible, T1 and T2 tissue segmentation methods should be used because they yield more consistent volume measurements between sites than T1‐only, especially when some of the scans were obtained with different sequence parameters and pixel size from those of the other sites. Our study shows that highest compatibility among scanners would be obtained using equipments of the same manufacturer and also image acquisition parameters as similar as possible. After validation, data from a specific ROI or scanner showing values markedly different from the other sites might be excluded from the analysis. Hum Brain Mapp, 2009. © 2007 Wiley‐Liss, Inc.
Economic evaluation of human papillomavirus vaccination in the United Kingdom

Objective To assess the cost effectiveness of routine vaccination of 12 year old schoolgirls against human papillomavirus infection in the United Kingdom. Design Economic evaluation. Setting UK. Population Schoolgirls aged 12 or older. Main outcome measures Costs, quality adjusted life years (QALYs), and incremental cost effectiveness ratios for a range of vaccination options. Results Vaccinating 12 year old schoolgirls with a quadrivalent vaccine at 80% coverage is likely to be cost effective at a willingness to pay threshold of £30 000 (€37 700; $59 163) per QALY gained, if the average duration of protection from the vaccine is more than 10 years. Implementing a catch-up campaign of girls up to age 18 is likely to be cost effective. Vaccination of boys is unlikely to be cost effective. A bivalent vaccine with the same efficacy against human papillomavirus types 16 and 18 costing £13-£21 less per dose (depending on the duration of vaccine protection) may be as cost effective as the quadrivalent vaccine although less effective as it does not prevent anogenital warts. Conclusions Routine vaccination of 12 year old schoolgirls combined with an initial catch-up campaign up to age 18 is likely to be cost effective in the UK. The results are robust to uncertainty in many parameters and processes. A key influential variable is the duration of vaccine protection.
Prevention of Exponential Equivalence in Simple Password Exponential Key Exchange (SPEKE)

Simple Password Exponential Key Exchange (SPEKE) and Dragonfly are simple password-based authenticated key exchange protocols that use a value derived from a shared password as a generator for modular exponentiation, as opposed to Diffie–Hellman key exchange, which uses a fixed value. However, it has been shown that in SPEKE, an active attacker, can examine multiple passwords in a single attempt because the passwords have an exponential correlation.We show that Dragonfly can also suffer from the same problem, and we propose a simple countermeasure to prevent the exponential equivalence in SPEKE.
Development and Validation of a Risk Score for Prediction of Acute Kidney Injury in Patients With Acute Decompensated Heart Failure: A Prospective Cohort Study in China

Background Although several risk factors for acute kidney injury (AKI) have been identified, early detection of AKI in acute decompensated heart failure patients remains a challenge. The aim of this study was to develop and validate a risk score for early prediction of AKI in acute decompensated heart failure patients. Methods and Results A total of 676 consecutive acute decompensated heart failure participants were prospectively enrolled from 6 regional central hospitals. Data from 507 participants were analyzed. Participants from 4 of the 6 hospitals (n=321) were used to develop a risk score and conduct internal validation. External validation of the developed risk score was conducted in participants from the other 2 hospitals (n=186). Sequential logistic regression was used to develop and validate the risk score. The c statistic and calibration plot were used to assess the discrimination and calibration of the proposed risk score. The overall occurrence of AKI was 33.1% (168/507). The risk score, ranging from 0 to 55, demonstrated good discriminative power with an optimism‐corrected c statistic of 0.859. Similar results were obtained from external validation with c statistic of 0.847 (95% CI 0.819‐0.927). The risk score had good calibration with no apparent over‐ or under‐prediction observed from calibration plots. Conclusions The novel risk score is a simple and accurate tool that can help clinicians assess the risk of AKI in acute decompensated heart failure patients, which in turn helps them plan and initiate the most appropriate disease management for patients in time.
A Yellow Page Information Retrieval System Based on Sorted Duality Interrelevant Successive Tree and Industry Ontology

This paper analyses the theory of information retrieval relativity and proposes establishing a content-based industry information retrieval system based on ontology. The system can accomplish the mapping between retrieval results and pragmatics relativity in some degree and bring more convenience to users when querying, which embodies the user- oriented principle. This retrieval system uses a novel retrieval model called sorted duality inter-relevant successive tree to index the contents of yellow page data to improve the retrieval efficiency. The experiment shows that this system is successful and has a better precision and recall of retrieval.
Cooperation of congestion control based on energy-aware in heterogeneous networks

To increase the energy efficiency of the whole heterogeneous network, a scheme of cooperation in congestion control based on energy-aware is proposed in this paper. In congestion avoidance, the scheme for the first time modeled on Markov chain, will work out the amount of unacknowledged data packages on each path of heterogeneous networks, to figure out the maximum amount of data that each link can carry. Cooperation will start when the congestion window size is larger than twice of the minimal value of the maximal amount of data that each path can carry in heterogeneous networks. In cooperation, based on the Linked Increases algorithm, end-to-end energy consumption model is implemented to work out the overall energy consumption indexes; as congestion window increment is inversely proportional to the square root of the energy cost on each path, the congestion window size will be adjusted simultaneously. Simulation results demonstrate load balancing kept and fairness between single TCP flow and MPTCP flow guaranteed. The results also reveal improvement of energy utilization, and increase of the amount of data packages successfully transmitted in heterogeneous network with the throughput unchanged.
On the connectivity of dynamic random geometric graphs

We provide the first analytical results for the connectivity of dynamic random geometric graphs --- a model of mobile wireless networks in which vertices move in random directions, and an edge exists between two vertices if their Euclidean distance is below a given value. We provide precise asymptotic results for the expected length of the connectivity and disconnectivity periods of the network. We believe the formal tools developed in this work could be of use in more concrete settings, in the same manner as the development of connectivity threshold for static random geometric graphs has affected a lot of research done on ad hoc networks. In the process of proving results for the dynamic case we also obtain new asymptotically precise bounds for the probability of the existence of a component of fixed size l, l ≥ 2, for the static case.
Fixed-point trigonometric functions on FPGAs

Three approaches for computing sines and cosines on FPGAs are studied in this paper, with a focus of highthroughput pipelined architecture, and state-of-the-art implementation techniques. The first approach is the classical CORDIC iteration, for which we suggest a reduced iteration technique and fine optimizations in datapath width and latency. The second is an ad-hoc architecture specifically designed around trigonometric identities. The third uses a generic table- and DSP-based polynomial approximator. These three architectures are implemented and compared in the FloPoCo framework.
The Society of the Muslim Brothers.

Since its first publication in 1969, this book continues to be routinely cited as the standard source for the history of the revivalist Egyptian movement, the Muslim Brethren, up to the time of Nasser. This classic work is now accessible to a new generation of scholars and students interested in the Muslim revival. Professor John Voll of the University of New Hampshire, a leading scholar of Islam in the English speaking world, contributes a Foreword to the paperback edition.
Non-linear short-term prediction in speech coding

Addresses the question of how to extract the nonlinearities in speech with the prime purpose of facilitating coding of the residual signal in residual excited coders. The short-term prediction of speech in speech coders is extensively based on linear models, e.g. the linear predictive coding technique (LPC), which is one of the most basic elements in modern speech coders. This technique does not allow extraction of nonlinear dependencies. If nonlinearities are absent from speech the technique is sufficient, but if the speech contains nonlinearities the technique is inadequate. The authors give evidence for nonlinearities in speech and propose nonlinear short-term predictors that can substitute the LPC technique. The technique, called nonlinear predictive coding, is shown to be superior to the LPC technique. Two different nonlinear predictors are presented. The first is based on a second-order Volterra filter, and the second is based on a time delay neural network. The latter is shown to be the more suitable for speech coding applications. <<ETX>>
MINING USING DECISION TREE BASED FEATURE SELECTION THROUGH MANHATTAN HIERARCHICAL CLUSTER MEASURE

Opinion mining plays a major role in text mining applications in consumer attitude detection, brand and product positioning, customer relationship management, and market research. These applications led to a new generation of companies and products meant for online market perception, reputation management and online content monitoring. Subjectivity and sentiment analysis focus on private states automatic identification like beliefs, opinions, sentiments, evaluations, emotions and natural language speculations. Subjectivity classification labels data as either subjective or objective, whereas sentiment classification adds additional granularity through further classification of subjective data as positive/negative or neutral. Features are extracted from the data for classifying the sentiment. Feature selection has gained importance due to its contribution to save classification cost with regard to time and computation load. In this paper, the main focus is on feature selection for Opinion mining using decision tree based feature selection. The proposed method is evaluated using IMDb data set, and is compared with Principal Component Analysis (PCA). The experimental results show that the proposed feature selection method is promising.