Miracle-dz/UniFAR-FTUs huggingface dataset:
Sam68/KHDRBS1 is critical for colon tumorigenesis by regulating genotoxic stress-induced NF-κB activation

Nuclear factor kappa B (NF-κB)-mediated transcription is an important mediator for cellular responses to DNA damage. Genotoxic agents trigger a 'nuclear-to-cytoplasmic' NF-κB activation signaling pathway; however, the early nuclear signaling cascade linking DNA damage and NF-κB activation is poorly understood. Here we report that Src-associated-substrate-during-mitosis-of-68kDa/KH domain containing, RNA binding, signal transduction associated 1 (Sam68/KHDRBS1) is a key NF-κB regulator in genotoxic stress-initiated signaling pathway. Sam68 deficiency abolishes DNA damage-stimulated polymers of ADP-ribose (PAR) production and the PAR-dependent NF-κB transactivation of anti-apoptotic genes. Sam68 deleted cells are hypersensitive to genotoxicity caused by DNA damaging agents. Upregulated Sam68 coincides with elevated PAR production and NF-κB-mediated anti-apoptotic transcription in human and mouse colon cancer. Knockdown of Sam68 sensitizes human colon cancer cells to genotoxic stress-induced apoptosis and genetic deletion of Sam68 dampens colon tumor burden in mice. Together our data reveal a novel function of Sam68 in the genotoxic stress-initiated nuclear signaling, which is crucial for colon tumorigenesis. DOI: http://dx.doi. org/10.7554/eLife.15018. 001
Psychometric properties of the Temporal Satisfaction with Life Scale among Turkish people

ABSTRACT OBJECTIVES: The determinants of subjective well-being have been largely investigated in recent years. According to Pavot and Diener who have developed TSWL (Temporal Satisfaction with Life Scale), to assess the life satisfaction level of an individual according to temporal factors, subjective well-being is composed of two constructs: an emotional or affective component (i.e. positive and negative affects) and a conceptual or cognitive component (i.e. satisfaction with life, marriage, work, and leisure). The aim of this study was to adapt the Temporal Satisfaction with Life Scale into Turkish (TSWLS-T) and examine the reliability and validity of this new Turkish version. METHODS: The study was conducted in four phases with randomly chosen 236 participants (113 females, 123 males) and the mean age of sample was 38.6 ± 12.5 years. Cultural adaptation was implemented according to the internationally suggested method and a pre-test was administered to examine the language equivalence. Since the scale had high levels of language equivalence, validity and reliability studies were conducted. For construct validity, confirmatory factor analysis was employed. The Satisfaction with Life Scale (SWLS) was used in order to evaluate the validity of TSWLS-T, since internal consistency (Cronbach’s alpha and intra-class coefficients) and test–retest analysis were employed to estimate instrument reliability. RESULTS: The TSWLS-T demonstrated acceptable internal consistency, with a Cronbach’s alpha of 0.87 for the total scale and ranging between 0.76 and 0.88 for the subscales. The test–retest reliability was also satisfactory, with intra-class correlation coefficients of 0.81 for the total scale and ranging between 0.61 and 0.74 for the subscales (p < 0.01). Fit indices of the model supported the factor structure. However, the 1st, 5th, and 11th items in scale (past, present, and future) showed a series of problems. With these items excluded, the 12-item model provided a better fit to the data than the 15-item model while the factor structure remained almost unchanged. The author recommends that the 12-item TSWLS be used to measure temporal life satisfaction. CONCLUSIONS: The TSWLS-T is a valid and reliable measure to assess life satisfaction in Turkish.
A Systematic Review of PCA and Its Different Form for Face Recognition

Face recognition is an important part of our daily life. Face recognition is used either for verification (one-to-one matching) or for identification (one-to-many). Mainly face recognition consists of two categories feature based and appearance based. Feature-based method first process the input image to identify and measure distinctive facial features such as the eyes, mouth, nose, etc., as well as other fiducial marks and then compute the geometric relationships among those facial points, thus reducing the input facial image to a vector of geometric features. Appearance based method used holistic features of 2D image attempt to identify faces using global representations, i.e., descriptions based on the entire image rather than on local features of the face. In this paper holistic method is discussed using Principle Component Analysis. This paper presents a systematic review of different forms of Principle Component Analysis (PCA) for face recognition. Based on the brief review of different forms of PCA, comparison table of recognition rate for ORL and FERET database are prepared. Face is an important biometric trait used in many applications such as General identity verification, Criminal justice system, Image database investigation, Smart card etc. The human ability to recognize faces is awesome. A human can recognize thousands of faces learned throughout the lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses, beards or changes in hair style. Developing a computational model for face recognition is difficult. Over the last few decades, a lot of researchers have been working in this area. Principal component analysis (PCA) is holistic method. Holistic method tries to identify face using global representation. It describes the entire face rather than on local features such as eyes, nose, lip etc of the face. One of the simplest and most effective PCA approaches used in face recognition systems is the eigenface approach. This approach transforms faces into a small set of essential characteristics.
Enabling Domain-Awareness for a Generic Natural Language Interface

In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge from user Interactions and Incorporates the knowledge learned to improve the generic system. We have embedded our approach in a generic natural language interface and evaluated the extended system against two benchmark datasets. We found that the performance of the original generic system can be substantially improved through automatic domain knowledge extraction and incorporation. We also show that the generic system with domain-awareness enabled by our approach can achieve performance similar to that of previous learning-based domain-specific systems.
Growing a language environment with editor libraries

Large software projects consist of code written in a multitude of different (possibly domain-specific) languages, which are often deeply interspersed even in single files. While many proposals exist on how to integrate languages semantically and syntactically, the question of how to support this scenario in integrated development environments (IDEs) remains open: How can standard IDE services, such as syntax highlighting, outlining, or reference resolving, be provided in an extensible and compositional way, such that an open mix of languages is supported in a single file? Based on our library-based syntactic extension language for Java, SugarJ, we propose to make IDEs extensible by organizing editor services in editor libraries. Editor libraries are libraries written in the object language, SugarJ, and hence activated and composed through regular import statements on a file-by-file basis. We have implemented an IDE for editor libraries on top of SugarJ and the Eclipse-based Spoofax language workbench. We have validated editor libraries by evolving this IDE into a fully-fledged and schema-aware XML editor as well as an extensible Latex editor, which we used for writing this paper.
Target Components Discrimination using Adaptive Time-Delay Neural Network

The feasibility of distinguishing multiple type components of exo-atmospheric targets is demonstrated by applying the Time Delay Neural Network (TDNN) and the Adaptive Time-Delay Neural Network (ATNN). Exo-atmospheric targets are especially difficult to distinguish using currently available techniques because all target parts follow the same spatial trajectory. Thus, classification must be based on light sensors that record signal over time. Results have demonstrated that the trained neural networks are able to successfully identify warheads from other missile parts on a variety of simulated scenarios, including differing angles, fragmented pieces and tumbling. The network with adaptive time delays (the ATNN) performs highly complex mapping on a limited set of training data and achieves better generalization to overall trends of situations compared to the TDNN. We also apply the theorem of Funahashi, Hornik et al and Stone-Weierstrass to state the general function approximation ability of the ATNN. The network is trained on additive noisy data and shows that it possesses robustness to environment variations.
Whole-Body Control of a Mobile Manipulator Using Feedback Linearization Based on Dual Quaternions

This paper presents a whole-body pose control of a mobile manipulator using a cascade scheme with two control loops. In the outer loop there is a nonlinear controller based on dual-quaternion feedback linearization-whose reference is a unit dual quaternion representing the desired end effector's pose-that acts as a dynamic trajectory generator and generates input signals for both nonholonomic mobile base and manipulator arm, the inner loop uses the input signals generated by the outer-loop as reference for an input-output linearizing controller that explicitly takes into account the nonholonomic constraints of the mobile base. Experimental results on a real platform are performed in order to compare the proposed scheme to a traditional whole-body kinematic controller using the pseudoinverse of the Jacobian matrix. The results show that the abrupt initial movement that is a characteristic of the classic approach, when the initial error is too large, is mitigated by the use of the nonlinear control.
Road Markers Recognition Based on Shape Information

Road information understanding is a necessary task for intelligent vehicles and driver assistance systems. Previous research mostly focused on the detection and estimation of lane position. Other information provided by road markers was scarcely mentioned. We propose a shape-based road marker detection and recognition method in this paper. The 8-neighbor chain codes of close regions are abstracted from the plane image. Selected moment features and an improved minimal-error-rate classifier are utilized to recognized different lane markers and other road markers. The lengths and slopes of lane markers are fast calculated also using the moment features. The results show that the method can detect and recognize road markers effectively.
Factors influencing citizen intention to adopt egovernment in Saudi Arabia

This paper discusses E-government, in particular the challenges that face adoption in Saudi Arabia. E-government can be defined based on an existing set of requirements. In this research we define E-government as a matrix of stakeholders: governments to governments, governments to business and governments to citizens, using information and communications technology to deliver and consume services. E-government has been implemented for a considerable time in developed countries. However, E-government services still face many challenges in their implementation and general adoption in many countries including Saudi Arabia. It has been noted that the introduction of E-government is a major challenge facing the government of Saudi Arabia, due to possible concerns raised by its citizens. In addition, the literature review and the discussion identify the influential factors that affect the citizens' intention to adopt E-government services in Saudi Arabia. Consequently, these factors have been defined and categorized followed by an exploratory study to examine the importance of these factors. Therefore, this research has identified factors that determine if the citizen will adopt E-government services and thereby aiding governments in accessing what is required to increase adoption.
Building Managers’ Views on Accessibility and UD Implementation in Public Buildings: Putrajaya

This paper discusses the interview data collection of an on-going research on accessibility of public buildings in Putrajaya. Main issues include the public awareness of PWD rights and the true concepts of Universal Design (UD). Main purposes are to investigate the building managers’ level of awareness and perception regarding the accessibility of their buildings and to study their knowledge on UD theory. Semi-structured interview was carried out with building managers from three public buildings in Putrajaya. Findings show that UD knowledge needs to be enhanced among building managers in order to increase awareness on inclusive environment in public buildings. Keywords: Public awareness; accessibility; Universal Design; semi-structured interview eISSN 2514-7528 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia
A SVM-based method for abnormity detection of log curves

Rapid and accurate abnormity detection of log curves is critical in the quality control for logging industry. Traditional methods based on manual detection have been proven to be ineffective and unreliable. A machine learning method based on Support Vector Machine (SVM) is proposed in this paper to address this problem. The SVM classifiers are established according to the suspicious sections selected from log curves and the detected results given by experts. A genetic algorithm (GA) is introduced for optimization of parameters. With GA and SVM fusions, the optimal models for classifiers are determined to detect abnormity sections. Experimental results of China XiangJiang Oilfield show that an accuracy of 95% is achieved for suspicious straight sections and 96% is achieved for suspicious bouncing sections, which has proven the feasibility of this method.
Incorporating Contextual Cues in Trainable Models for Coreference Resolution

We propose a method that incorporates various novel contextual cues into a machine learning for resolving coreference. Distinct characteristics of our model are (i) incorporating more linguistic features capturing contextual information that is more sophisticated than what is offered in Centering Theory, and (ii) a tournament model for selecting a referent. Our experiments show that this model significantly outperforms earlier machine learning approaches, such as Soon et al. (2001).
High-Energy Emission from Magnetars

The recently discovered soft gamma-ray emission from the anomalous X-ray pulsar 1E 1841-045 has a luminosity Lγ ~ 1036 ergs s-1. This luminosity exceeds the spin-down power by 3 orders of magnitude and must be fed by an alternative source of energy such as an ultrastrong magnetic field. A gradual release of energy in the stellar magnetosphere is expected if it is twisted and a strong electric current is induced on the closed field lines. We examine two mechanisms of gamma-ray emission associated with the gradual dissipation of this current. (1) A thin surface layer of the star is heated by the downward beam of current-carrying charges, which excite Langmuir turbulence in this layer. As a result, it can reach a temperature kBT ~ 100 keV and emit bremsstrahlung photons up to this characteristic energy. (2) The magnetosphere is also a source of soft gamma rays at a distance of ~100 km from the star, where the electron cyclotron energy is in the kilo-electron volt range. A large electric field develops in this region in response to the outward drag force felt by the current-carrying electrons from the flux of kilo-electron volt photons leaving the star. A seed positron injected in this region undergoes runaway acceleration and upscatters X-ray photons above the threshold for pair creation. The created pairs emit a synchrotron spectrum consistent with the observed 20-100 keV emission. This spectrum is predicted to extend to higher energies and reach a peak at ~1 MeV.
On approximating arbitrary metrices by tree metrics

We design a generation algorithm for a problem which a&es in computational chemistry: the random generation of models of amorphous strutures. Such structures can be modeled as graphs which see embedded in d-space. The algorithm uses the well known approach of simulating a rapidly-mixing Markov chain. Gur analysis of the Mixing rate is based on Dobrushin uniqueness. The structure of the problem forces us to extend the basic method and find an alternative to Dobrushin’s condition which is more appropriate for our problem. This extension appears to be of more general interest.
Visceral fat is a major contributor for multiple risk factor clustering in Japanese men with impaired glucose tolerance.

OBJECTIVE The significance of abdominal visceral fat accumulation was evaluated in Japanese men with impaired glucose tolerance (IGT). RESEARCH DESIGN AND METHODS The IGT subjects (n = 123) were aged 55 +/- 9 years with a BMI of 24 +/- 3 kg/m(2). The 148 control subjects with normal glucose tolerance (NGT) were matched for age and BMI. IGT and NGT were classified according to the 1985 World Health Organization criteria. Abdominal fat distribution was analyzed by computed tomography at umbilical level. Plasma lipid, glucose, and insulin concentrations and blood pressure (BP) were measured. RESULTS In subjects with IGT, the average visceral fat area (VFA) was significantly greater than in subjects with NGT. Fasting insulin, the sum of insulin concentrations during an oral glucose tolerance test, insulin resistance according to a homeostasis model assessment for insulin resistance (HOMA-IR), systolic BP, and serum triglyceride were significantly higher, whereas the DeltaI(30-0)/DeltaG(30-0) was significantly lower, in subjects with IGT. Subjects with IGT and NGT were then divided into three subgroups according to the number of risk factors they possessed (dyslipidemia, hypertension, neither, or both). In both IGT and NGT subjects, BMI, VFA, subcutaneous fat area, fasting insulin, HOMA-IR, and insulin secretion of the homeostasis model assessment were significantly higher in the double-risk factor subgroup than in the no-risk factor subgroup, and VFA was a potent and independent variable in association with the presence of a double risk factor. CONCLUSIONS Visceral fat accumulation is a major contributor for multiple risk factor clustering in Japanese men with IGT and NGT.
Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems

Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection.
High-Throughput Sequencing Shows High Fungal Diversity and Community Segregation in the Rhizospheres of Container-Grown Conifer Seedlings

Forest nurseries in Sweden produce ca. 360 million seedlings of Pinus sylvestris L. and Picea abies (L.) Karst. annually. Fungi represent the largest microbial component in rhizospheres and may significantly affect health and, consequently, quality of the seedlings. The aim of this study was to assess fungi focusing on pathogens in roots and the sphagnum peat growth substrate of healthy-looking P. sylvestris and P. abies seedlings from nine forest nurseries situated in northern, central and southern regions of Sweden. We hypothesized that nursery stock and the growth substrate can provide a venue for dissemination of fungal diseases. In each nursery and for each tree species, 100 seedlings with the growth substrate were collected during the dormant period. DNA was isolated from parts of root systems and from samples of the growth substrate, amplified using internal transcribed spacer of rDNA as a marker and 454-sequenced. Clustering at 98.5% similarity of 169,844 high-quality sequences resulted in 619 non-singleton fungal taxa. Although results showed that management practices in forest nurseries generally give a healthy stock, latent establishment of pathogenic fungi in both roots and the growth substrate supported the hypothesis. Furthermore, seedling roots and the growth substrate were inhabited by distinct communities of fungi, and lifestyles of these fungi largely determined community segregation into particular ecological niche.