Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutagenic activity in nipple aspirates of human breast fluid.

The Ames Salmonella mutagenesis test was applied to nipple aspirates of breast fluid from 456 women attending breast-screening clinics. Positive tests for presumptive mutagenic substances were found in 6.7% of the women tested. These findings support our hypothesis that mutagenic substances reach the breast epithelia and may have etiologic implications in the pathogenesis of benign disease and breast cancer.
Age-dependent Motor Deficits and Dopaminergic Dysfunction in DJ-1 Null Mice*

Mutations in the DJ-1 gene were recently identified in an autosomal recessive form of early-onset familial Parkinson disease. Structural biology, biochemistry, and cell biology studies have suggested potential functions of DJ-1 in oxidative stress, protein folding, and degradation pathways. However, animal models are needed to determine whether and how loss of DJ-1 function leads to Parkinson disease. We have generated DJ-1 null mice with a mutation that resembles the large deletion mutation reported in patients. Our behavioral analyses indicated that DJ-1 deficiency led to age-dependent and task-dependent motoric behavioral deficits that are detectable by 5 months of age. Unbiased stereological studies did not find obvious dopamine neuron loss in 6-month- and 11-month-old mice. Neurochemical examination revealed significant changes in striatal dopaminergic function consisting of increased dopamine reuptake rates and elevated tissue dopamine content. These data represent the in vivo evidence that loss of DJ-1 function alters nigrostriatal dopaminergic function and produces motor deficits.
CT-guided sternoclavicular joint injections: description of the procedure, reliability of imaging diagnosis, and short-term patient responses.

OBJECTIVE The purpose of this study was to evaluate pain relief 20 to 30 minutes after diagnostic or therapeutic injections into the sternoclavicular joint and to compare patient outcomes based on the CT diagnosis. MATERIALS AND METHODS Informed consent was obtained from each patient. Ethics approval was not required. Fifty patients who had CT-guided injections of corticosteroid and local anesthetic into their sternoclavicular joints were included in the study. Preinjection and 20- to 30-minute postinjection visual analog scale data were recorded and compared with the imaging findings agreed by consensus. Kappa statistics were calculated for the reliability of imaging diagnosis. The percentage of patients improving after joint injection was calculated, and the risk ratio comparing the response of patients with osteoarthritis to those without osteoarthritis was completed. The correlation between the severity of each patient's osteoarthritis and the pain response was calculated using Spearman's correlation coefficient. RESULTS Sixty-six percent of the patients reported clinically significant pain reduction at between 20 and 30 minutes after injection. The proportion of patients with osteoarthritis who had a clinically significant response was 67% compared with 64% for patients who did not have osteoarthritis. This difference was not statistically or clinically significant. There was no correlation between the severity of osteoarthritis and the amount of pain reduction (r = 0.03). The reliability of imaging diagnosis was substantial. CONCLUSION Two thirds of patients having sternoclavicular joint injections of corticosteroids and local anesthetics report clinically significant improvement regardless of the abnormalities detected on their CT images.
Sperm influences female hibernation success, survival and fitness in the bumble–bee Bombus terrestris

We present evidence that in the absence of the transfer of male gland compounds in the ejaculate as well as of behavioural male traits, such as mate guarding or harming of females, sperm itself affects female life–history traits such as hibernation success, female longevity and female fitness. Using the bumble–bee Bombus terrestris, we artificially inseminated queens (females) with sperm from one or several males and show that sire groups (groups of brother males) vary in their effects on queen hibernation survival, longevity and fitness. In addition, multiply inseminated queens always had a lower performance as compared to singly inseminated queens. Apart from these main effects, sire groups (in situations of multiple insemination) affected queen longevity and fitness not independently of each other, i.e. certain sire group combinations were more harmful to queens than others. So far, the cause(s) of these effects remain(s) elusive. Harmful male traits as detected here are not necessarily expected to evolve in social insects because males depend on females for a successful completion of a colony cycle and thus have strong convergent interests with their mates.
A Universal Top-down Fixpoint Algorithm a Universal Top-down Fixpoint Algorithm

Computing xpoints and posttxpoints of transformations has numerous applications in computer science. In this paper, we present a universal top-down xpoint algorithm based on the weak assumption that the transformation is deened by an eeective procedure. Given the procedure and a value , the universal algorithm computes the value of in the least xpoint of the transformation and has the property of focusing on the subset of elements necessary to compute the value of. The total correctness of the algorithm is proven and requires some weak (but rather technical) assumptions. These conditions can be relaxed further if posttxpoints suuce for the application. As a consequence, the algorithm generalizes and abstracts numerous algorithms and provides a versatile alternative to bottom-up algorithms. It has been used to derive speciic abstract interpretation algorithms for Prolog, which are practical both in terms of eeciency and accuracy and are, to our knowledge, the fastest algorithms available.
Extending traditional query-based integration approaches for functional characterization of post-genomic data

MOTIVATION To identify and characterize regions of functional interest in genomic sequence requires full, flexible query access to an integrated, up-to-date view of all related information, irrespective of where it is stored (within an organization or across the Internet) and its format (traditional database, flat file, web site, results of runtime analysis). Wide-ranging multi-source queries often return unmanageably large result sets, requiring non-traditional approaches to exclude extraneous data. RESULTS Target Informatics Net (TINet) is a readily extensible data integration system developed at GlaxoSmith- Kline (GSK), based on the Object-Protocol Model (OPM) multidatabase middleware system of Gene Logic Inc. Data sources currently integrated include: the Mouse Genome Database (MGD) and Gene Expression Database (GXD), GenBank, SwissProt, PubMed, GeneCards, the results of runtime BLAST and PROSITE searches, and GSK proprietary relational databases. Special-purpose class methods used to filter and augment query results include regular expression pattern-matching over BLAST HSP alignments and retrieving partial sequences derived from primary structure annotations. All data sources and methods are accessible through an SQL-like query language or a GUI, so that when new investigations arise no additional programming beyond query specification is required. The power and flexibility of this approach are illustrated in such integrated queries as: (1) 'find homologs in genomic sequence to all novel genes cloned and reported in the scientific literature within the past three months that are linked to the MeSH term 'neoplasms"; (2) 'using a neuropeptide precursor query sequence, return only HSPs where the target genomic sequences conserve the G[KR][KR] motif at the appropriate points in the HSP alignment'; and (3) 'of the human genomic sequences annotated with exon boundaries in GenBank, return only those with valid putative donor/acceptor sites and start/stop codons'.
Abscisic acid effects on activity and expression of barley (Hordeum vulgare) plastidial glucose-6-phosphate dehydrogenase

Total glucose-6-phosphate dehydrogenase (G6PDH) activity, protein abundance, and transcript levels of G6PDH isoforms were measured in response to exogenous abscisic acid (ABA) supply to barley (Hordeum vulgare cv Nure) hydroponic culture. Total G6PDH activity increased by 50% in roots treated for 12 h with exogenous 0.1 mM ABA. In roots, a considerable increase (35%) in plastidial P2-G6PDH transcript levels was observed during the first 3 h of ABA treatment. Similar protein variations were observed in immunoblotting analyses. In leaves, a 2-fold increase in total G6PDH activity was observed after ABA treatment, probably related to an increase in the mRNA level (increased by 50%) and amount of protein (increased by 85%) of P2-G6PDH. Together these results suggest that the plastidial P2-isoform plays an important role in ABA-treated barley plants.
Incremental Construction of Robust but Deep Semantic Representations for Use in Responsive Dialogue Systems

It is widely acknowledged that current dialogue systems are held back by a lack of flexibility, both in their turn-taking model (typically, allowing only a strict back-and-forth between user and system) and in their interpretation capabilities (typically, restricted to slot filling). We have developed a component for NLU that attempts to address both of these challenges, by a) constructing robust but deep meaning representations that support a range of further user intention determination techniques from inference / reasoning-based ones to ones based on more basic structures, and b) constructing these representations incrementally and hence providing semantic information on which system reactions can be based concurrently to the ongoing user utterance. The approach is based on an existing semantic representation formalism, Robust Minimal Recursion Semantics, which we have modified to suit incremental construction. We present the modifications, our implementation, and discuss applications within a dialogue system context, showing that the approach indeed promises to meet the requirements for more flexibility.
Brands and brand equity: definition and management

This article assumes that brands should be managed as valuable, long‐term corporate assets. It is proposed that for a true brand asset mindset to be achieved, the relationship between brand loyalty and brand value needs to be recognised within the management accounting system. It is also suggested that strategic brand management is achieved by having a multi‐disciplinary focus, which is facilitated by a common vocabulary. This article seeks to establish the relationships between the constructs and concepts of branding, and to provide a framework and vocabulary that aids effective communication between the functions of accounting and marketing. Performance measures for brand management are also considered, and a model for the management of brand equity is provided.
Facial Expressions with Some Mixed Expressions Recognition Using Neural Networks

-Facial feature extraction is the essential step of facial expression recognition. The automatic facial impression evaluation applies for wide area use. The important facial feature vectors for expression analysis are analyzed. The extracted feature vector loads all known feature vectors and trains the NN using as input training vectors while PCA is used for dimensionality reduction. The method is effective for both dimension reduction and good recognition performance in comparison with other proposed methods as shown in experiment results.
Scalability in Ext2 File System

Scalability is an important performance issue in modern File System. In this paper, we present our case study where we designed a simple benchmark and measured the performance of create and open operations on ext2. In order to explain an interesting result from the case study, we traced into the code and explained what actually leads to that result. Finally we added a new create mode that accelerates the create process a lot.
A nonlinear efficient layerwise finite element model for smart piezolaminated composites under strong applied electric field

In this work, we present an electromechanically coupled efficient layerwise finite element model for the static response of piezoelectric laminated composite and sandwich plates, considering the nonlinear behavior of piezoelectric materials under strong electric field. The nonlinear model is developed consistently using a variational principle, considering a rotationally invariant second order nonlinear constitutive relationship, and full electromechanical coupling. In the piezoelectric layer, the electric potential is approximated to have a quadratic variation across the thickness, as observed from exact three dimensional solutions, and the equipotential condition of electroded piezoelectric surfaces is modeled using the novel concept of an electric node. The results predicted by the nonlinear model compare very well with the experimental data available in the literature. The effect of the piezoelectric nonlinearity on the static response and deflection/stress control is studied for piezoelectric bimorph as well as hybrid laminated plates with isotropic, angle-ply composite and sandwich substrates. For high electric fields, the difference between the nonlinear and linear predictions is large, and cannot be neglected. The error in the prediction of the smeared counterpart of the present theory with the same number of primary displacement unknowns is also examined.
Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex

The development of stimulus selectivity in the primary sensory cortex of higher vertebrates is considered in a general mathematical framework. A synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete. The change in the efficacy of a given synapse depends not only on instantaneous pre- and postsynaptic activities but also on a slowly varying time-averaged value of the postsynaptic activity. Assuming an appropriate nonlinear form for this dependence, development of selectivity is obtained under quite general conditions on the sensory environment. One does not require nonlinearity of the neuron's integrative power nor does one need to assume any particular form for intracortical circuitry. This is first illustrated in simple cases, e.g., when the environment consists of only two different stimuli presented alternately in a random manner. The following formal statement then holds: the state of the system converges with probability 1 to points of maximum selectivity in the state space. We next consider the problem of early development of orientation selectivity and binocular interaction in primary visual cortex. Giving the environment an appropriate form, we obtain orientation tuning curves and ocular dominance comparable to what is observed in normally reared adult cats or monkeys. Simulations with binocular input and various types of normal or altered environments show good agreement with the relevant experimental data. Experiments are suggested that could test our theory further.
QoS Monitoring and Troubleshooting of a Large Scale IPTV Deployment

Several network segments are involved in a large scale IPTV deployment, from the original video content server to the set-top-box (STB). Each network segment could be error-prone. QoS monitoring and troubleshooting are critical to guarantee satisfying user experience. In this paper, we discuss QoS monitoring and troubleshooting in AT&T U-Verse, one of the largest IPTV deployments in the world.We present the overall architecture of U-Verse, with a focus on QoS. Furthermore, we review the current efforts in U-Verse on QoS monitoring and troubleshooting, as well as their challenges and opportunities. Moreover, we provide a case study on how to troubleshoot the U-Verse IPTV system with the data collected by current QoS monitoring and troubleshooting infrastructure.
Symmetric Multimodality Revisited: Unveiling Users' Physiological Activity

In this paper, we describe our own stance on a research area called "Humatronics", which aims at establishing a (more) symmetric interaction relationship between humans and computer systems. In particular, we will advocate a novel approach to understanding humans that is based on largely involuntary and unconscious physiological information and gaze behavior rather than purposeful and conscious actions or behaviors. "Understanding humans" here refers to users' states related to emotion and affect, attention and interest, and possibly even to their intentions. A key feature of our approach is that it provides insight into a person's cognitive-motivational state without relying on cognitive judgements, such as answers to dedicated queries. Lifelike interface agents are endowed with synthetic bodies and faces and can be considered as prime candidates for outbalancing the asymmetric relationship in current human-computer interaction. As example applications, we will report on two recent studies that utilized lifelike agents as presenters or interaction partners of users. The resulting interactions can be conceived as implementing initial steps toward symmetric multimodality in user interfaces
Enhancing and identifying cloning attacks in online social networks

Recently Online Social Networks (OSNs) are enjoying a continuous boom, while suffering from omnifarious malicious attacks. Cloning attack is one of the attack patterns towards online social networks, where typically the attacker disguises fake accounts as real users by thieving and copying their profiles, and sends friend requests to the friends of the cloned victim. It is difficult for ordinary users to detect these fake identities because of the identical names and similar profile information. In this paper, we raise two possible improvements, namely snowball sampling and iteration attack, to the regular attack pattern upgrading its efficiency and power, so that the attackers can more easily engage into the community. An experiment has been conducted on Renren, the largest OSN in China, to fully compare and substantiate the effectiveness of the enhanced strategy with traditional attacks and different levels of cloning attacks. Then we discuss approaches to detect cloning attacks and put forward a detector named CloneSpotter, which can be deployed into OSN servers. The detector takes advantage of the detailed login IP records and provides solid evidence of locations, in order to judge whether the suspicious accounts are manipulated by real users or attackers. Besides, we discuss a content-based approach to protect users from cloning attacks, which can be easily implemented into distributed clients. Our contribution lies in two aspects. First, we improve a threatening attack pattern towards OSNs, and test its effectiveness in real systems. Second, we provide an effective defense method to detect cloning attacks, which is real-time and lightweight. By deploying the detectors, OSN systems can assist users to accurately distinguish cloning accounts, and safeguard their privacy.
Quantifying SBS Content in Modified Asphalt Using Fourier Transform Infrared Spectroscopy

Styrene-Butadiene-Styrene (SBS) has been widely used in the modified asphalt engineering around the world due to its excellent contribution to both high and low temperature performance of asphalt. The content of SBS plays a critical role in the performance of modified asphalt. Therefore, an accurate and effective method to quantify the SBS content in modified asphalt was proposed based on the Fourier-Transform Infrared (FTIR) spectroscopy method. Two Infrared (IR) indices were provided to quantify the content of SBS. In addition, the practicability and accuracy of this method was verified by testing the prepared sample in laboratory.
Error-bounds for balanced model-reduction of linear time-varying systems

Error-bounds are developed for balanced truncation of linear time-varying systems, leading to an extension of the "twice the sum of the tail" formulas, well known in the time-invariant case. The approach relies on an operator-theoretic framework for analysis of linear time-varying systems. This provides a multivariable notion of frequency for such systems, which are thus characterized by rational functions of many complex variables, allowing the problem to be formulated in the linear-fractional framework. Using a time-varying version of standard necessary conditions for reduced-order modeling, based on convex operator inequalities, we show that these error-bounds for balanced truncation are related to the closest possible reduced-order modeling error in a sense which parallels the time-invariant case.
A Multi-Hop Dynamic Path-Selection (MHDP) Algorithm for the Augmented Lifetime of Wireless Sensor Networks

In Wireless Sensor Networks (WSN), the lifetime of sensors is the crucial issue. Numerous schemes are proposed to augment the life time of sensors based on the wide range of parameters. In majority of the cases, the center of attraction will be the nodes’ lifetime enhancement and routing. In the scenario of cluster based WSN, multi-hop mode of communication reduces the communication cast by increasing average delay and also increases the routing overhead. In this proposed scheme, two ideas are introduced to overcome the delay and routing overhead. To achieve the higher degree in the lifetime of the nodes, the residual energy (remaining energy) of the nodes for multi-hop node choice is taken into consideration first. Then the modification in the routing protocol is evolved (Multi-Hop Dynamic Path-Selection Algorithm—MHDP). A dynamic path updating is initiated in frequent interval based on nodes residual energy to avoid the data loss due to path extrication and also to avoid the early dying of nodes due to elevation of data forwarding. The proposed method improves network’s lifetime significantly. The diminution in the average delay and increment in the lifetime of network are also accomplished. The MHDP offers 50% delay lesser than clustering. The average residual energy is 20% higher than clustering and 10% higher than multi-hop clustering. The proposed method improves network lifetime by 40% than clustering and 30% than multi-hop clustering which is considerably much better than the preceding methods.
Integrating Document Structure into a Multi-Document Summarizer

In this paper, we present a novel approach for automatic summarization. CBSEAS, the system implementing this approach, integrates a method to detect redundancy at its very core, in order to produce more expressive summaries than previous approaches. The evaluation of our system during TAC 2008 —the Text Analysis Conference— revealed that, even if our system performed well on blogs, it had some failings on news stories. A post-mortem analysis of the weaknesses of our original system showed the importance of text structure for automatic summarization, even in the case of short texts like news stories. We describe some ongoing work dealing with these issues and show that first experiments provide a significant improvement of the results.