Miracle-dz/UniFAR-FTUs huggingface dataset:
TWIST1 Is Expressed in Colorectal Carcinomas and Predicts Patient Survival

TWIST1 is a transcription factor that belongs to the family of basic helix-loop-helix proteins involved in epithelial-to-mesenchymal transition and invasion processes. The TWIST1 protein possesses oncogenic, drug-resistant, angiogenic and invasive properties, and has been related with several human tumors and other pathologies. Colorectal cancer is one of the tumors in which TWIST1 is over-expressed, but its involvement in the clinical outcome of the disease is still unclear. We tested, by RT-PCR, the expression levels of TWIST1 in normal and tumor paired-sample tissues from a series of 151 colorectal cancer patients, in order to investigate its prognostic value as a tumor marker. TWIST1 expression was restricted to tumor tissues (86.1%) and correlated with lymph node metastasis (LNM). Adjusted analysis showed that the expression levels of TWIST1 correlated with overall survival (OS) and disease-free survival (DFS). Importantly, TWIST1 expression levels predicted OS specifically at stages I and II. Moreover, patients with stage II tumors and high TWIST1 levels showed even shorter survival than patients with stage III tumors. These results suggest that TWIST1 expression levels could be a tumor indicator in stage II patients and help select patients at greater risk of poor prognosis who might benefit from adjuvant chemotherapy.
On the scalability of centralized control

Scalability of clusters and MPPs is typically discussed in terms of limits on growth: something which grows at a rate of O(logp) (where p is the number of processors) is said to be more scalable than something whose growth rate is O(p). But in practice p does not grow without limits. We therefore suggest that discussions of scalability should take time into account. System sizes grow with time, so larger systems need to be supported - but only after some time. And in particular, there is no real need to support arbitrarily large systems right now. Surprisingly, when time is thus put into the picture, we find that centralized control is actually quite scalable. The reason is that the capabilities of a centralized control node grow at a fast pace due to Moore's law. This seems to be more than enough in order to manage current growth patterns displayed by parallel systems.
Augmented Active Surface Model for the Recovery of Small Structures in CT

This paper devises an augmented active surface model for the recovery of small structures in a low resolution and high noise setting, where the role of regularization is especially important. The emphasis here is on evaluating performance using real clinical computed tomography (CT) data with comparisons made to an objective ground truth acquired using micro-CT. In this paper, we show that the application of conventional active contour methods to small objects leads to non-optimal results because of the inherent properties of the energy terms and their interactions with one another. We show that the blind use of a gradient magnitude based energy performs poorly at these object scales and that the point spread function (PSF) is a critical factor that needs to be accounted for. We propose a new model that augments the external energy with prior knowledge by incorporating the PSF and the assumption of reasonably constant underlying CT numbers.
Influencing factors on professional commitment in Iranian nurses: A qualitative study

Background: Dissatisfaction and tending to leave are some of the major nursing problems around the world. Professional commitment is a key factor in attracting and keeping the nurses in their profession. Commitment is a cultural dependent variable. Some organizational and socio-cultural factors are counted as the drivers of professional commitment. This study aimed to explore factors influencing the professional commitment in Iranian nurses. Materials and Methods: A qualitative content analysis was used to obtain rich data. We performed 21 in-depth face-to-face semi-structured interviews. The sampling was based on the maximum variation with the staff nurses and managers in 5 university affiliated hospitals. Constant comparative method used for data analysis Results: Two main categories were emerged: “Challenging with different feelings” and “Managers’ role”. Challenging with different feelings had two subcategories: “Burnout” and “sense of valuing”. The other theme was composed of three subcategories: “Gratitude or punishment climate”, “manager's view of caring” and “knowledge-based vs. routine-based nursing”. Conclusions: Findings revealed the burnout as a common sense in nurses. They also sensed being valued because of having a chance to help others. Impediments in the health care system such as work overload and having more concern in the benefits of organization rather than patient's care and wellbeing lead to a sense of humiliation and frustration. Congruence between the managers and nurses’ perceived values of the profession would be a main driver to the professional commitment. Making a sense of support and gratitude, valuing the care and promoting the knowledge-based practice were among the other important factors for making the professional commitment.
An Evolutionary Algorithm for Inversion of ANNsHenrik Jacobsson and Bj orn OlssonDept

Before using a trained artiicial neural network (ANN) in an application it is important to identify inputs which cause incorrect behaviours. We therefore propose the use of an evolutionary algorithm (EA) to invert the mappings of ANNs. The EA is used to search for input patterns which produce strong (distinct) classiications into one of the classes. Since the input space is typically very large, multimodal, and poorly understood, EAs are likely to be more robust than gradient methods , with a lower probability of getting stuck on local optima. Analysis of our results supports this hypothesis. Our evolutionary algorithm also involves the use of niching, which allows it to simultaneously explore multiple regions of the search space. The resulting population of input patterns therefore typically represents a set of distinctly diierent instances. This property is important, since the aim is to identify inputs which are erroneously classiied. We show how analysis of the set of inputs found by inversion can lead to detection of aws in the ANN, and we discuss the possibilities of using this inversion method as a tool for validation and retraining .
Discordant Autophagy Response in Fasting Obese Mice Discordant Signaling and Autophagy Response to Fasting in Hearts of Obese Mice : 1 Implications for Ischemia Tolerance

24 Autophagy is regulated by nutrient and energy status and plays an adaptive role during nutrient 25 deprivation and ischemic stress. Metabolic syndrome (MetS) is a hypernutritive state characterized by 26 obesity, dyslipidemia, elevated fasting blood glucose levels and insulin resistance. It has also been 27 associated with impaired autophagic flux and larger sized infarcts. We hypothesized that diet-induced 28 obesity (DIO) affects nutrient sensing, explaining the observed cardiac impaired autophagy. We 29 subjected male FVBN mice to a high fat diet, which resulted in increased weight gain, fat deposition, 30 hyperglycemia, insulin resistance and sustained larger infarcts after myocardial I/R. Autophagic flux 31 was impaired after 4wks on a high fat diet. To interrogate nutrient-sensing pathways, DIO mice were 32 subjected to overnight fasting, and hearts were processed for biochemical and proteomic analysis. 33 Obese mice failed to upregulate LC3-II or to clear p62/SQSTM1 after fasting, although mRNA for LC3B 34 and p62/SQSTM1 were appropriately upregulated in both groups, demonstrating an intact 35 transcriptional response to fasting. Energy and nutrient sensing signal transduction pathways (AMPK 36 and mTOR) also responded appropriately to fasting, although mTOR was more profoundly suppressed 37 in obese mice. Proteomic quantitative analysis of the hearts under fed and fasted conditions revealed 38 broad changes in protein networks involved in oxidative phosphorylation, autophagy, oxidative stress, 39 protein homeostasis, and contractile machinery. In many instances, the fasting response was quite 40 discordant between lean and DIO mice. Network analysis implicated the PPAR and mTOR regulatory 41 nodes. Hearts of obese mice exhibited impaired autophagy, altered proteome and discordant response 42 to nutrient deprivation. 43
Relation between volume, number of faces and three-dimensional growth laws in coarsening cellular patterns

Abstract The recently established linear growth law for three-dimensional diffusive coarsening shows zero average growth for grains with 15·8 faces, while the average number of faces per grain in the pattern is 13·7 ± 0·1. In the better-known two-dimensional case, grains with six sides (the average number) show zero growth. We show that the three-dimensional zero growth value is a consequence only of the linear form of the law and the cubic dependence of average area per grain on the number of faces.
Computing Surface-Based Photo-Consistency on Graphics Hardware

This paper describes a novel approach to the problem of recovering information from an image set by comparing the radiance of hypothesised point correspondences. Our algorithm is applicable to a number of problems in computer vision, but is explained particularly in terms of recovering geometry from an image set. It uses the idea of photo-consistency to measure the confidence that a hypothesised scene description generated the reference images. Photo-consistency has been used in volumetric scene reconstruction where a hypothesised surface is evolved by considering one voxel at a time. Our approach is different: it represents the scene as a parameterised surface so decisions can be made about its photo-consistency simultaneously over the entire surface rather than a series of independent decisions. Our approach is further characterised by its ability to execute on graphics hardware. Experiments demonstrate that our cost function minimises at the solution and is not adversely affected by occlusion.
PERFORMANCE ANALYSIS OF PILOT BASED CHANNEL ESTIMATION TECHNIQUES IN MB OFDM SYSTEMS

Ultra wideband (UWB) communication is mainly used for short range of communication in wireless personal area networks. Orthogonal Frequency Division Multiplexing (OFDM) is being used as a key physical layer technology for Fourth Generation (4G) wireless communication. OFDM based communication gives high spectral efficiency and mitigates Inter-symbol Interference (ISI) in a wireless medium. In this paper the IEEE 802.15. 3a based Multiband OFDM (MB OFDM) system is considered. The pilot based channel estimation techniques are considered to analyze the performance of MB OFDM systems over Liner Time Invariant (LTI) Channel models. In this paper, pilot based Least Square (LS) and Least Minimum Mean Square Error (LMMSE) channel estimation technique has been considered for UWB OFDM system. In the proposed method, the estimated Channel Impulse Responses (CIRs) are filtered in the time domain for the consideration of the channel delay spread. Also the performance of proposed system has been analyzed for different modulation techniques for various pilot density patterns.
Adaptive Biharmonic In-Painting for Sparse Acquisition Using Variance Frames

Dynamical adaption of sparse image acquisition processes in (scanning) transmission electron [(S)TEM] microscopes remains an important avenue for developing improved performance at reduced dose rates and acquisition times. Though more advanced algorithms, such as Bayesian dictionary in-painting or compressed sensing [1], produce high-fidelity reconstructions, they suffer from long reconstruction times unsuitable user feedback expected during on-line image acquisition. Demonstrated here is an easy-to-implement method for adaptive sparse sampling of images, aimed at providing sub-Nyquist sampling.
Hippocampal place cells construct reward related sequences through unexplored space

Dominant theories of hippocampal function propose that place cell representations are formed during an animal's first encounter with a novel environment and are subsequently replayed during off-line states to support consolidation and future behaviour. Here we report that viewing the delivery of food to an unvisited portion of an environment leads to off-line pre-activation of place cells sequences corresponding to that space. Such ‘preplay’ was not observed for an unrewarded but otherwise similar portion of the environment. These results suggest that a hippocampal representation of a visible, yet unexplored environment can be formed if the environment is of motivational relevance to the animal. We hypothesise such goal-biased preplay may support preparation for future experiences in novel environments. DOI: http://dx.doi. org/10.7554/eLife.06063. 001
Distribution Statement A: " Approved for Public Release; Distribution Is Unlimited. " Distributed Rule-based Inference in the Presence of Redundant Information

The problem of processing redundant information (also known as " double counting ") has been addressed in distributed Level 1 Fusion systems over the past decade. Some approaches for avoiding the ill-effects of processing redundant data include: tagging all data items with a unique identifier, controlling the flow of data throughout the network or tracking pedigree information for each data item. Recently, Covariance Intersection provides an alternative solution to Level 1 Fusion in the presence of redundant information. This technique allows fusion processes to combine redundant information without the results becoming inconsistent and overconfident. As the fusion community attacks the higher levels of information fusion, we are still faced with processing data items in the presence of redundant information. Lockheed Martin Advanced Technology Laboratories has developed a technique analogous to Covariance Intersection for combining information using propositional logic. As a result, if a propositional inference engine consumes data from distributed sources that have redundant inputs, the output of that inference engine will still be consistent and will not overestimate the confidence. This approach simplifies propositional inference in the presence of redundant information, allowing for inference over a distributed network of fusion nodes. One of the biggest difficulties in the development of distribution fusion systems is the potential for redundant information to corrupt fusion computations. Avoiding redundant information processing has led to designs involving: elaborate data tagging schemes, control over network topology, and pedigree tracking. With the development of Covariance Intersection [1], distributed Level 1 Fusion could be performed within an arbitrary network topology without pedigree tracking. Realizing that the risk of processing redundant information will drive the development of higher-level fusion architectures, Lockheed Martin Advanced Technology Laboratories (ATL) has developed an algorithm analogous to Covariance Intersection for propositional logic. Since propositional logic is being
SIEGE: Smoking Induced Epithelial Gene Expression Database

The SIEGE (Smoking Induced Epithelial Gene Expression) database is a clinical resource for compiling and analyzing gene expression data from epithelial cells of the human intra-thoracic airway. This database supports a translational research study whose goal is to profile the changes in airway gene expression that are induced by cigarette smoke. RNA is isolated from airway epithelium obtained at bronchoscopy from current-, former- and never-smoker subjects, and hybridized to Affymetrix HG-U133A Genechips, which measure the level of expression of ∼22 500 human transcripts. The microarray data generated along with relevant patient information is uploaded to SIEGE by study administrators using the database's web interface, found at http://pulm.bumc. bu.edu/siegeDB. PERL-coded scripts integrated with SIEGE perform various quality control functions including the processing, filtering and formatting of stored data. The R statistical package is used to import database expression values and execute a number of statistical analyses including t-tests, correlation coefficients and hierarchical clustering. Values from all statistical analyses can be queried through CGI-based tools and web forms found on the ‘Search’ section of the database website. Query results are embedded with graphical capabilities as well as with links to other databases containing valuable gene resources, including Entrez Gene, GO, Biocarta, GeneCards, dbSNP and the NCBI Map Viewer.
Angular momentum transport in a multicomponent solar wind with differentially flowing, thermally anisotropic ions

Context. The Helios measurements of the angular momentum flux L of the fast solar wind lead to a tendency for the fluxes associated with individual ion angular momenta of protons and alpha particles, Lp and Lα, to be negative (i.e., in the sense of counter-rotation with the Sun). However, the opposite holds for the slow wind, and the overall particle contribution LP = Lp + Lα tends to exceed the magnetic contribution LM. These two aspects are at variance with previous models. Aims. We examine whether introducing realistic ion temperature anisotropies can resolve this discrepancy. Methods. From a general set of multifluid transport equations with gyrotropic species pressure tensors, we derive the equations governing both the meridional and azimuthal dynamics of outflows from magnetized, rotating stars. The equations are not restricted to radial flows in the equatorial plane but valid for general axisymmetric winds that include two major ion species. The azimuthal dynamics are examined in detail, using the empirical meridional flow profiles for the solar wind, constructed mainly according to measurements made in situ. Results. The angular momentum flux L is determined by the requirement that the solution to the total angular momentum conservation law is unique and smooth in the vicinity of the Alfven point, defined as where the combined Alfvenic Mach number MT = 1. MT has to consider the contributions from both protons and alpha particles. Introducing realistic ion temperature anisotropies may introduce a change of up to 10% in L and up to ∼1. 8k m s −1 in azimuthal speeds of individual ions between 0.3 and 1 AU, compared with the isotropic case. The latter has strong consequences on the relative importance of LP and LM in the angular momentum budget. Conclusions. However, introducing ion temperature anisotropies cannot resolve the discrepancy between in situ measurements and model computations. For the fast-wind solutions, while in extreme cases LP may become negative, Lp never does. On the other hand, for the slow solar wind solutions examined, LP never exceeds LM, even though LM may be less than the individual ion contribution, since Lp and Lα always have opposite signs for the slow and fast wind alike.
Generating perceptually-correct shadows for mixed reality

When human cannot perceive the inconsistency of artificial shadows which are not physically correct, they are acceptable as ldquoperceptually-correctrdquo shadows. This paper focuses on the simplification of light-source models for generating the perceptually-correct artificial shadows. First, we conducted subjective evaluations to obtain knowledge about the human perception of the shadows. Then the knowledge was applied to control the resolution of the light-source map to generate perceptually-correct artificial shadows. Comparative studies among artificial and real shadows justified perceptually correctness. All experiments were done using still images, not videos. Our research becomes a reference to determine the resolution of light-source map in an MR scene.
Fractal Antennas: Design, Characteristics and Application

This report will describe the theories and techniques for shrinking the size of an antenna through the use of fractals. Fractal antennas can obtain radiation pattern and input impedance similar to a longer antenna, yet take less area due to the many contours of the shape. Fractal antennas are a fairly new research area and are likely to have a promising future in many applications.
Transmission Dynamics and Prospects for the Elimination of Canine Rabies

Rabies has been eliminated from domestic dog populations in Western Europe and North America, but continues to kill many thousands of people throughout Africa and Asia every year. A quantitative understanding of transmission dynamics in domestic dog populations provides critical information to assess whether global elimination of canine rabies is possible. We report extensive observations of individual rabid animals in Tanzania and generate a uniquely detailed analysis of transmission biology, which explains important epidemiological features, including the level of variation in epidemic trajectories. We found that the basic reproductive number for rabies, R0, is very low in our study area in rural Africa (∼1.2) and throughout its historic global range (<2). This finding provides strong support for the feasibility of controlling endemic canine rabies by vaccination, even near wildlife areas with large wild carnivore populations. However, we show that rapid turnover of domestic dog populations has been a major obstacle to successful control in developing countries, thus regular pulse vaccinations will be required to maintain population-level immunity between campaigns. Nonetheless our analyses suggest that with sustained, international commitment, global elimination of rabies from domestic dog populations, the most dangerous vector to humans, is a realistic goal.
New Preprocessing approach for Images in Diabetic Retinopathy Screening

The development of an automatic telemedicine system for diabetic retinopathy depends on detection of red lesion in color images. This paper presents image preprocessing and optic disc removal methods for detection of microaneurysms and hemorrhages. Microaneurysms and hemorrhages occurs at the first stage of Diabetic Retinopathy. Lesions are hardly visible, proposed method improves the ability to distinguish between lesions and non-lesions.
On surface modification of austenitic stainless steel using microwave processed Ni/Cr3C2 composite cladding

In the present work Ni-based + 20% Cr3C2 composite clads were developed on SS-304 austenitic stainless steel through microwave hybrid heating technique. Experimental trials were conducted inside a domestic microwave applicator at 2.45 GHz and 900 W. The developed microwave composite clads were characterised through SEM/EDS, XRD and Vicker's micro-hardness tests. Further tribological wear behavior of the so developed clad was investigated using pin-on-disc type tribometer under dry sliding wear conditions. Microstructural analysis revealed the uniform dispersion of Cr3C2 particles inside the Ni matrix in the form of cellular-like structure. The presence of FeNi3, NiSi, Cr3Ni2 and chromium carbide (Cr3C2) was confirmed from the XRD analysis, which contributes to the increase in micro-hardness of the composite clad. The average value of micro-hardness of the developed clads was found to be 450 ± 55 HV. The microwave-processed clad exhibits three times more wear resistance than SS-304 substrate.