Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic Significance of Serum Tumor Markers in Patients with Advanced-stage NSCLC Treated with Pemetrexed-based Chemotherapy.

BACKGROUND Tumor biomarkers represent effective tools for diagnostics and follow-up monitoring of patients with non-small cell lung cancer (NSCLC). We focused on evaluating the predictive and prognostic role of the seven following tumor biomarkers: carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA 21-1), fragments of cytokeratin 8, 18 and 19 (MonoTotal), neuron-specific enolase (NSE), chromogranin A, thymidine kinase (TK) and squamous cell carcinoma antigen (SCCA) in patients with advanced-stage NSCLC treated with pemetrexed-based chemotherapy. PATIENTS AND METHODS In total, 114 patients with advanced-stage (IIIB or IV) non-squamous NSCLC treated with pemetrexed-based chemotherapy (monotherapy or combination with a platinum derivative) were included. Comparison of progression-free (PFS) and overall survival (OS) according to the level of assessed tumor markers was performed using the log-rank test. RESULTS We recorded significantly shorter OS for patients with high pretreatment levels of CYFRA 21-1 (10.3 vs. 23.4 months; p<0.001), NSE (1.6 vs. 13.5 months; p=0.003) and TK (11.3 vs. 23.4 months; p=0.003). CONCLUSION CYFRA 21-1, NSE and TK are feasible biomarkers for estimation of a patient's overall prognosis, however, none of the measured serum tumor markers were able to predict the efficacy of pemetrexed-based chemotherapy.
A methodology of Collaborative Requirements Validation in a cooperative environment

The increasing complexity of systems and the interdisciplinary necessary to their realization push the organizations to be resorted in teams and thus they must cooperate, because it seems to constitute a means to improve the quality and the time of realizing the products. In this paper, we are interested to the validation phase in the process of requirements engineering in a cooperative context. The cooperation is not a recent practice because people cooperate since always. However, the cooperation, such as it reappears nowadays, is not simply a team work, it wants to be structured and organized in order to produce better results. To this purpose we propose a methodology which presents a collaborative approach of the requirements validation process based on the concepts of competences and multi-viewpoints. The objective of this methodology is twofold; first it increases the quality of the software product (i.e. it leads to better match users' needs) and it reduces the complexity of the validation task.
A mental disorder early warning approach by observing depression symptom in social diary

With the advances of information technology, there are increasing researches aiming at assisting depression diagnosis and treatment. In most of them the user is necessarily actively joining the diagnosis and treatment program while he has perceived mental disorder himself. In order to early prevent the mental disorder, in this paper we propose an early warning mechanism that observes and mines user diary published on social network platform, and generates a score of getting mental disordered or depressed. If the score is large than a threshold, the system can notify the user and his friends on the social network to take care about the friend. We have conducted experiments to evaluate the proposed approach, and the results show that the proposed approach is effective.
Protein structure quality assessment based on the distance profiles of consecutive backbone Cα atoms

Predicting the three dimensional native state structure of a protein from its primary sequence is an unsolved grand challenge in molecular biology. Two main computational approaches have evolved to obtain the structure from the protein sequence - ab initio/de novo methods and template-based modeling - both of which typically generate multiple possible native state structures. Model quality assessment programs (MQAP) validate these predicted structures in order to identify the correct native state structure. Here, we propose a MQAP for assessing the quality of protein structures based on the distances of consecutive Cα atoms. We hypothesize that the root-mean-square deviation of the distance of consecutive Cα (RDCC) atoms from the ideal value of 3.8 Å, derived from a statistical analysis of high quality protein structures (top100H database), is minimized in native structures. Based on tests with the top100H set, we propose a RDCC cutoff value of 0.012 Å, above which a structure can be filtered out as a non-native structure. We applied the RDCC discriminator on decoy sets from the Decoys 'R' Us database to show that the native structures in all decoy sets tested have RDCC below the 0.012 Å cutoff. While most decoy sets were either indistinguishable using this discriminator or had very few violations, all the decoy structures in the fisa decoy set were discriminated by applying the RDCC criterion. This highlights the physical non-viability of the fisa decoy set, and possible issues in benchmarking other methods using this set. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.
Multiscale Modeling Study on the Nanometric Cutting Process of CaF2

The hierarchical approach of multi-scale modelling was adopted to study the nanometric cutting process of calcium fluoride. Then fly cutting experiments of CaF2 were performed to analyze the influence of cutting speed upon the surface roughness of CaF2. The results of FEM simulations show that larger negative rake angle and larger cutting edge radius lead to lower tensile stress in the cutting region. Tangential cutting force will first increase with an increase of negative rake angle and cutting edge radius, and then start to decrease with them. The tensile stress in the cutting region will increase with cutting depth at first, and then become stable when it reaches a certain extent. The specific cutting force increases rapidly with decrease of cutting depth, showing an obvious size effect. Within the range of cutting speeds adopted in the simulations, cutting speed has little influence on the tensile stress in the cutting region. And the results of fly cutting experiments show that cutting speed has little influence on the surface roughness of a machined surface under the cutting speeds adopted. This verifies the validity of the simulation result to some extent.
Fault tolerant framework and techniques for component-based autonomous robot systems

Due to the benefits of its reusability and productivity, the component-based approach has become the primary technology in service robot software frameworks, such as MRDS (Microsoft Robotics Developer Studio), RTC (Robot Technology Component), ROS (Robot Operating System) and OPRoS (Open Platform for Robotic Services). However, all the existing frameworks are very limited in fault tolerance support, even though the fault tolerance function is crucial for the commercial success of service robots. In this paper, we present a rule-based fault tolerant framework together with widely-used, representative fault tolerance measures. With our observation that most faults in components and applications in service robot systems have common patterns, we equip the framework with the required fault tolerant functions. The system integrators construct fault tolerance applications from non-fault-aware components by declaring fault handling rules in configuration descriptors or/and adding simple helper components, considering the constraints of the components and the operating environment. Much more consistency in system reliability can be obtained with less effort of system developer. Various fault scenarios with a test robot system on the proposed OPRoS fault tolerant framework demonstrate the benefits and effectiveness of the proposed approach.
Sum capacity of Gaussian vector broadcast channels

This paper characterizes the sum capacity of a class of potentially nondegraded Gaussian vector broadcast channels where a single transmitter with multiple transmit terminals sends independent information to multiple receivers. Coordination is allowed among the transmit terminals, but not among the receive terminals. The sum capacity is shown to be a saddle-point of a Gaussian mutual information game, where a signal player chooses a transmit covariance matrix to maximize the mutual information and a fictitious noise player chooses a noise correlation to minimize the mutual information. The sum capacity is achieved using a precoding strategy for Gaussian channels with additive side information noncausally known at the transmitter. The optimal precoding structure is shown to correspond to a decision-feedback equalizer that decomposes the broadcast channel into a series of single-user channels with interference pre-subtracted at the transmitter.
Generating Multilingual Descriptions from Linguistically Annotated OWL Ontologies: the NaturalOWL System

We introduce NaturalOWL, an open-source multilingual natural language generator that produces descriptions of instances and classes, starting from a linguistically annotated ontology. The generator is heavily based on ideas from ILEX and M-PIRO, but it is in many ways simpler and it provides full support for OWL DL ontologies with RDF linguistic annotations. NaturalOWL is written in Java, and it is supported by M-PIRO's authoring tool, as well as an alternative plug-in for the Protege ontology editor.
SQNR: A System for Querying Nodes and relations in multi-relational social networks

Social networks are usually modeled by graphs, where the nodes represent actors, and edges indicate interactions amongst actors. In the real world, social networks are mostly multi-relational, i.e., actors are related through different relationship types, such as friendship, kinship and co-authorship. A multi-relational social network can be represented by multiple single-relational graphs, each reflecting one kind of relation. Acquiring information contained in a multi-relational social network, such as which actors interact frequently in which relationships, can help us to understand the network comprehensively and then offer better services. This paper develops a system (SQNR: A System for Querying Nodes and Relations) to query nodes that interact frequently in the specified relationships and to query relationships in which the specified community patterns (limitations of the community memberships of some actors, such as belong to the same community) can be satisfied. Twelve community patterns can be specified in this paper. The queried results provide new insights about relationships amongst actors.
On the Influence of Velocity and Acceleration Estimators on a Servopneumatic System Behaviour

Pneumatic systems are clean and reliable actuators, presenting very high force to weight ratios. They further present some advantages, such as inherent compliance and suitability for fire hazard environments. However, their intrinsic nonlinearities have hindered a more wide range of applications, leading to the use of complex control laws that typically require the knowledge of velocity and acceleration. This means that the velocity and acceleration estimators might play a crucial role in servopneumatic systems control, since a difficult to achieve balance between differentiation noise and phase lag must be inferred by the control engineer. This paper experimentally compares the performance of several velocity and acceleration estimators, relying upon a digital encoder position signal. The comparison is performed not only regarding the quality of the actual estimates per se but also on their effect on the control error and control action obtained when using a nonlinear sliding mode-based controller.
Pattern generators with sensory feedback for the control of quadruped locomotion

Central pattern generators (CPGs) are becoming a popular model for the control of locomotion of legged robots. Biological CPGs are neural networks responsible for the generation of rhythmic movements, especially locomotion. In robotics, a systematic way of designing such CPGs as artificial neural networks or systems of coupled oscillators with sensory feedback inclusion is still missing. In this contribution, we present a way of designing CPGs with coupled oscillators in which we can independently control the ascending and descending phases of the oscillations (i.e. the swing and stance phases of the limbs). Using insights from dynamical system theory, we construct generic networks of oscillators able to generate several gaits under simple parameter changes. Then we introduce a systematic way of adding sensory feedback from touch sensors in the CPG such that the controller is strongly coupled with the mechanical system it controls. Finally we control three different simulated robots (iCub, Aibo and Ghostdog) using the same controller to show the effectiveness of the approach. Our simulations prove the importance of independent control of swing and stance duration. The strong mutual coupling between the CPG and the robot allows for more robust locomotion, even under non precise parameters and non-flat environment.
Locus of Control and Self-Reported Depression among College Students

The Internal-External Control, Guilford Depression, and Marlowe-Crowne Social Desirability Scales were administered to 69 university undergraduates to test the hypothesis that depression is associated with belief in external control. The results supported the hypothesis. Implications of the results for notions which link I-E to maladjustment in a U-shaped fashion and for some psychodynamic notions regarding correlates of depression were discussed.
Statistical analysis of glycosylation profiles to compare tissue type and inflammatory disease state

MOTIVATION Glycosylation is one of the most important post-translational modifications of proteins and explains some aspects of the diversification of higher organisms not explained by template-driven synthesis. For glycomics to mature as much as genomics and proteomics, the necessary tools need to be developed and tested. Liquid chromatography-mass spectrometry is one of the gold standards for oligosaccharide analysis and leads to large amounts of data, not easily interpreted manually. We present a study on the testing and validation of statistical analysis tools to aid the structural elucidation of these analyses as well as using the results to answer biologically relevant questions. RESULTS We show the usefulness of data reduction and statistical analysis in the interpretation of complex glycosylation data. The reduction does not result in the loss of importance of the glycosylation information as shown by comparison of control and disease samples in two tissue types.
The Internet of Things: The Role of Reconfigurable Platforms

The Internet of Things (IoT) paradigm has quickly gone past various technological domains to become part of everyday life across the globe. Ubiquitous devices (things) with a certain amount of intelligence, capable of connecting to the Internet and sharing information collaboratively are now a widespread reality [1]-[3]. The general perception today indicates that the IoT may become a technological milestone, with an impact similar to that caused by the advent of the Internet itself. It will transform the Internet from a humancentric platform, where most applications are focused on humanto-human interaction and where most of the data are provided by humans, to a machine-intensive platform.
Cellular Phenotype Recognition for High-Content RNA Interference Genome-Wide Screening

Genome-wide, cell-based screens using high-content screening (HCS) techniques and automated fluorescence microscopy generate thousands of high-content images that contain an enormous wealth of cell biological information. Such screens are key to the analysis of basic cell biological principles, such as control of cell cycle and cell morphology. However, these screens will ultimately only shed light on human disease mechanisms and potential cures if the analysis can keep up with the generation of data. A fundamental step toward automated analysis of high-content screening is to construct a robust platform for automatic cellular phenotype identification. The authors present a framework, consisting of microscopic image segmentation and analysis components, for automatic recognition of cellular phenotypes in the context of the Rho family of small GTPases. To implicate genes involved in Rac signaling, RNA interference (RNAi) was used to perturb gene functions, and the corresponding cellular phenotypes were analyzed for changes. The data used in the experiments are high-content, 3-channel, fluorescence microscopy images of Drosophila Kc167 cultured cells stained with markers that allow visualization of DNA, polymerized actin filaments, and the constitutively activated Rho protein RacV12. The performance of this approach was tested using a cellular database that contained more than 1000 samples of 3 predefined cellular phenotypes, and the generalization error was estimated using a cross-validation technique. Moreover, the authors applied this approach to analyze the whole high-content fluorescence images of Drosophila cells for further HCS-based gene function analysis. (Journal of Biomolecular Screening 2008:29-39)
Reliable CORBA Event Channels

This paper presents a pragmatic way to build a Reliable CORBA Event Service. Our approach is pragmatic in the sense that, rather than building the service from scratch, we show how to obtain it, through a simple transformation, from any standard (unreliable) CORBA 2.0 Event Service. Our extension does not introduce any modification to the CORBA specification, nor any communication overhead. The Reliable CORBA Event Service provides the adequate semantics for building reliable notification-based applications, and an interesting light-weight and open alternative to existing group oriented systems.
Top-k closest pairs join query: an approximate algorithm for large high dimensional data

In This work we present a novel approximate algorithm to calculate the top k closest pairs join query of two large and high dimensional data sets. The algorithm has worst case time complexity O(d/sup 2/nk) and space complexity O(nd) and guarantees a solution within a O(d/sup 1+ 1/2 /) factor of the exact one, where t /spl isin/ {1,2,. , /spl infin/} denotes the Minkowski metrics L/sub t/ of interest and d the dimensionality. It makes use of the concept of space filling curve to establish an order between the points of the space and performs at most d + 1 sorts and scans of the two data sets. During a scan, each point from one data set is compared with its closest points, according to the space filling curve order, in the other data set and points whose contribution to the solution has already been analyzed are detected and eliminated. Experimental results on real and synthetic data sets show that our algorithm (i) behaves as an exact algorithm in low dimensional spaces; (ii) it is able to prune the entire (or a considerable fraction of the) data set even for high dimensions if certain separation conditions are satisfied; (iii) in any case it returns a solution within a small error to the exact one.
Effects of luteolin on regulatory proteins and enzymes for myocyte calcium circulation in hypothermic preserved rat heart

Heart transplantation has been applied in the clinic as an optimal solution for patients with end stage cardiac failure for a number of years. However, hypothermic preservation of the heart remains limited to 4–6 h and calcium accumulation over time is an important factor resulting in cell death. To provide longer and safer storage for donor hearts, it was demonstrated in our previous study that luteolin, a traditional Chinese medicine used to treat cardiovascular diseases, inhibits cell death and L-type calcium currents during hypothermic preservation. In the current study, the protective role of luteolin in modulating cardiomyocyte calcium cycling was further investigated. Intracellular calcium overload has already been implicated in hypothermia-induced dysfunction of cardiomyocytes. University of Wisconsin (UW) solution supplemented with 7.5, 15 or 30 µmol/l luteolin was used to preserve fresh isolated cardiomyocytes at 4°C. The results demonstrated that all three doses of luteolin supplementation attenuated calcium overload over a 6 h preservation period. Luteolin also suppressed the accumulation of important regulatory proteins and enzymes for cardiomyocyte calcium circulation, mitochondria Ca2+ uniporter and calmodulin, which are normally induced by cold storage in UW solution. Protein Kinase A activity was also suppressed in cardiomyocytes preserved in luteolin supplemented UW solution, while Ca2+-Mg2+-ATPase activity was increased. The results demonstrated that luteolin confers a cardioprotective effect through inhibiting the changes of calcium regulators during cold storage and therefore ameliorates Ca2+ overload in rat cardiomyocytes.
Data reduction strategy of the Effelsberg-Bonn HI Survey (EBHIS)

Since autumn 2008 a new L-band 7-Feed-Array receiver is used for an HI 21-cm line survey performed with the 100-m Effelsberg telescope. The survey will cover the whole northern hemisphere comprising both, the galactic and extragalactic sky in parallel. Using state-of-the-art FPGA based digital Fast Fourier Transform spectrometers, superior in dynamic range and temporal resolution, allows to apply sophisticated radio frequency interferences (RFI) mitigation schemes to the survey data. The EBHIS data reduction software includes the RFI mitigation, gain-curve correction, intensity calibration, stray-radiation correction, gridding, and source detection. We discuss the severe degradation of radio astronomical HI data by RFI signals and the gain in scientific yield when applying modern RFI mitigation schemes. For this aim simulations of the galaxy distribution within the local volume (z<0.07) with and without RFI degradation were performed. These simulations, allow us to investigate potential biases and selection effects introduced by the data reduction software and the applied source parametrization methods.
Interventions to Slow Aging in Humans: Are We Ready?

The workshop entitled ‘Interventions to Slow Aging in Humans: Are We Ready? ’ was held in Erice, Italy, on October 8–13, 2013, to bring together leading experts in the biology and genetics of aging and obtain a consensus related to the discovery and development of safe interventions to slow aging and increase healthy lifespan in humans. There was consensus that there is sufficient evidence that aging interventions will delay and prevent disease onset for many chronic conditions of adult and old age. Essential pathways have been identified, and behavioral, dietary, and pharmacologic approaches have emerged. Although many gene targets and drugs were discussed and there was not complete consensus about all interventions, the participants selected a subset of the most promising strategies that could be tested in humans for their effects on healthspan. These were: (i) dietary interventions mimicking chronic dietary restriction (periodic fasting mimicking diets, protein restriction, etc.); (ii) drugs that inhibit the growth hormone/IGF‐I axis; (iii) drugs that inhibit the mTOR–S6K pathway; or (iv) drugs that activate AMPK or specific sirtuins. These choices were based in part on consistent evidence for the pro‐longevity effects and ability of these interventions to prevent or delay multiple age‐related diseases and improve healthspan in simple model organisms and rodents and their potential to be safe and effective in extending human healthspan. The authors of this manuscript were speakers and discussants invited to the workshop. The following summary highlights the major points addressed and the conclusions of the meeting.