Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate Information Metallogenic Prognosis Model

Metallogenic circumstances spatial of the same category mineral deposit structure had defined commonality in a certain region. The important was that studied mineral deposit informations and determine the nature or a segment quantitative investigation, integrated experts’ experience to make sure the weight of dominate mineral factors, and constructed metallogenic prognosis model, and then proceed metallogenic prognosis and mineral resource evaluation use in other regions. To overcome geologic investigation problem which not unity and manifold explanation about geology、geophysics、geochemistry、remote geology at present.
Point of Contact Location and Normal Force Estimation Using Biomimetical Tactile Sensors

One of the most important human capabilities is the tactile sensing that allows advanced in hand manipulation for several objects or tasks. In the robot world, object manipulation without tactile sensing is relying only on visual detection, thus introducing large error margins. This paper presents several solutions for point of contact detection and normal force estimation by using a biomimetical tactile sensor mounted on a robot hand. Even if this paper focuses on the data generated by using a specific sensor, the results and implemented methods can be applied to a wide range of tactile sensors.
Performance Analysis of Single Cell IEEE 802.16e Wireless MAN

We analyze IEEE 802.16e medium access control (MAC) sublayer and provides a simple analytical model to compute the 802.16e MAC throughput. Our approach is to begin with a key approximation made in IEEE 802.11. This study leads to a fixed point equation, which characterizes the operating point of system. It allows us to compute the attempt rate of a mobile in saturated case as well as the throughput formulas for the overall network. Moreover, our performance model deals with a recently released IEEE802.16 criterium : the tr parameter, which have a main impact on the MAC performance.
T-Rex : A Flexible Relation Extraction Framework

In the wake of the explosive growth in the use of the computer as a communication device, has come a need for systems that help people cope with the sheer volume of information available. It is universally known that the Internet contains vast amounts of unstructured documents, but the same is also true for large organizations like publishing companies, government departments, airplane manufacturers, car manufacturers, and so forth. In many application domains, there is the potential to significantly increase the utility of available textual information by using automated methods for mapping parts of the unstructured text into a structured representation. This process is called Information Extraction (IE). Within IE, the task of Entity Extraction is essentially a classification problem: given a piece of text in a document, the task consists in deciding whether it fits into some entity class. The task of Relation Extraction (REX), also known as event extraction or template filling, additionally aims to establish relations between the classified entities. The top performer in the 2002 DARPA ACE evaluation got entity extraction precision and recall scores of about 80%, but binary relation extraction scores of only roughly 60%. Using a system that makes nearly one mistake out of two suggestions is hardly acceptable in real-world applications. Relation extraction is therefore a difficult open research problem, with important applications in diverse fields, such as Knowledge Management and Web Mining.
A Clustering Algorithm based on Internal Constrained Multi-view K-means

As more and more multi-view data are collected, how to apply the traditional clustering algorithm to multi-view data has been studied widely. Among them, the K-means clustering algorithm is extended because of its efficiency on large-scale datasets. Based on the K-means clustering algorithm and the multi-view data without domain knowledge, this paper presents a clustering algorithm based on internal constrained multi-view K-means (ICMK). This paper also evaluates the proposed method on three standard datasets (digits dataset, IS dataset, WTP dataset), and compares with some baseline methods. The experiment results show that ICMK can produce a good view interaction structure automatically and higher quality clustering results.
Predicting Future Conflict under REDD+ Implementation

With the current complexity of issues facing forest and land management, the implementation of the REDD+ initiative comes with significant risks, including conflict. While the exact nature and shape of conflict in REDD+ implementation is difficult to pinpoint, this study aims to build a preliminary predictive framework to identify possible sources of impairment that may result in conflict over management of forests and natural resources. The framework was developed from an extensive literature review and was tested in three REDD+ pilot project sites in Nepal. The results indicate that most of the sources of impairment are present in all study sites, particularly issues relating to benefit sharing, which have been main drivers of conflict prior to REDD+. While we found that the application of the framework has been useful in the Nepalese context, there are some limitations in its scope and precision. Nonetheless, this study points to important implications with regards to REDD+ implementation and conflict management that can be useful for policy makers and practitioners involved in REDD+ strategy designs, as well as other areas of forest management involving outsiders and communities.
Differential Effects of Motor Efference Copies and Proprioceptive Information on Response Evaluation Processes

It is well-kown that sensory information influences the way we execute motor responses. However, less is known about if and how sensory and motor information are integrated in the subsequent process of response evaluation. We used a modified Simon Task to investigate how these streams of information are integrated in response evaluation processes, applying an in-depth neurophysiological analysis of event-related potentials (ERPs), time-frequency decomposition and sLORETA. The results show that response evaluation processes are differentially modulated by afferent proprioceptive information and efference copies. While the influence of proprioceptive information is mediated via oscillations in different frequency bands, efference copy based information about the motor execution is specifically mediated via oscillations in the theta frequency band. Stages of visual perception and attention were not modulated by the interaction of proprioception and motor efference copies. Brain areas modulated by the interactive effects of proprioceptive and efference copy based information included the middle frontal gyrus and the supplementary motor area (SMA), suggesting that these areas integrate sensory information for the purpose of response evaluation. The results show how motor response evaluation processes are modulated by information about both the execution and the location of a response.
Design of experiments in BDD variable ordering: lessons learned

Applying the design of experiments methodology to the evaluation of BDD variable ordering algorithms has yielded a number of conclusive results. The methodology relies on the equivalence classes of functionally perturbed circuits that maintain logic invariance, or are within (1, 2, .)-minterms of the original reference circuit function, also maintaining entropy-invariance. For some of the current variable ordering algorithms and tools, the negative results include: statistically significant sensitivity to naming of variables; confirmation that a number of variable ordering algorithms are statistically equivalent to a random variable order assignment; and observation of a statistically anomalous variable ordering behavior of a well known benchmark circuit isomorphic class when analyzed under single and multiple outputs. On the positive side, the methodology supports a statistically significant merit evaluation of any newly introduced variable ordering algorithm, including the one briefly introduced in this paper.
The longitudinal impact of cognitive speed of processing training on driving mobility.

PURPOSE To examine how cognitive speed of processing training affects driving mobility across a 3-year period among older drivers. DESIGN AND METHODS Older drivers with poor Useful Field of View (UFOV) test performance (indicating greater risk for subsequent at-fault crashes and mobility declines) were randomly assigned to either a speed of processing training or a social and computer contact control group. Driving mobility of these 2 groups was compared with a group of older adults who did not score poorly on the UFOV test (reference group) across a 3-year period. RESULTS Older drivers with poor UFOV test scores who did not receive training experienced greater mobility declines as evidenced by decreased driving exposure and space and increased driving difficulty at 3 years. Those at risk for mobility decline who received training did not differ across the 3-year period from older adults in the reference group with regard to driving exposure, space, and most aspects of driving difficulty. IMPLICATIONS Cognitive speed of processing training can not only improve cognitive performance but also protect against mobility declines among older drivers. Scientifically proven cognitive training regimens have the potential to enhance the everyday lives of older adults.
Motor cortex changes in spinal cord injury: a TMS study

Abstract Using paired pulse transcranial magnetic stimulation (TMS) paradigms, we studied cortical excitability in a patient with spinal cord lesion. During posterior tibial nerve stimulation, the contextual flexion of hand fingers contralateral to the stimulated lower limb had suggested a change in motor cortex excitability. Results showed a decrease in the activity of motor cortex inhibitory circuits. This could suggest that in spinal cord injury, just as in stroke and peripheral deafferentation, a disinhibition of latent synapses within the motor cortex and the rewriting of a new motor map can occur.
Online Coded Caching

We consider a basic content distribution scenario consisting of a single origin server connected through a shared bottleneck link to a number of users each equipped with a cache of finite memory. The users issue a sequence of content requests from a set of popular files, and the goal is to operate the caches as well as the server such that these requests are satisfied with the minimum number of bits sent over the shared link. Assuming a basic Markov model for renewing the set of popular files, we characterize approximately the optimal long-term average rate of the shared link. We further prove that the optimal online scheme has approximately the same performance as the optimal offline scheme, in which the cache contents can be updated based on the entire set of popular files before each new request. To support these theoretical results, we propose an online coded caching scheme termed coded least-recently sent (LRS) and simulate it for a demand time series derived from the dataset made available by Netflix for the Netflix Prize. For this time series, we show that the proposed coded LRS algorithm significantly outperforms the popular least-recently used caching algorithm.
NEURAL NETS AS SYSTEMS MODELS AND CONTROLLERS

Repr. from Proc. Seventh Yale Workshop on Adaptive and Learning Systems , pp. 73-79, May 1992. This paper briefly surveys some recent results relevant to the suitability of “neural nets” as models for dynamical systems as well as controllers for nonlinear plants. In particular, it touches upon questions of approximation, identifiability, construction of feedback laws, classification and interpolation, and computational capabilities of nets. No discussion is included of “learning” algorithms, concentrating instead on representational issues.
Searching for the right outcome? A systematic review and meta‐analysis of controlled trials using carotid intima‐media thickness or pulse wave velocity to infer antiatherogenic properties of thiazolidinediones

Introduction: Recent meta‐analyses cast doubt over purported beneficial effects of Peroxisome Proliferator Activated Receptor‐Gamma (PPAR‐γ) receptor agonists. Thiazolidinedione (TZD) trials using surrogate outcomes to postulate an antiatherogenic paradigm have been criticised as misinformative. We conducted an independent systematic review and meta‐analysis of controlled TZD studies incorporating carotid intima‐media thickness (CIMT) or pulse wave velocity (PWV) as primary outcome measures. The aim was to provide an evidence‐based overview of TZD intervention studies using markers prospectively linked to vascular outcome in type 2 diabetes.
XML-based data integration

Today’s fast and continuous growth of large business organizations enforces an increasing need in integrating and sharing large amounts of data, coming from a number of heterogeneous and distributed data sources. Thus, during the last decade, research and business community interest has migrated from DataBase Management Systems (DBMS) to data integration systems. Whereas the former make a unique local data source accessible through a schema, the latter offer the necessary framework to combine the data from a set of heterogeneous and autonomous sources through a socalledglobal schema . We call such a system a hierarchicaldata integration system. Today, one more step is being achieved towards so-called Peer-to-Peer(P2P) data integration systems, which are characterized by an architecture constituted by various autonomous nodes which hold information, and are linked to each other by means of mappings. Another technical progress, somehow orthogonal to the aforementioned one, is the one that concerns with the impressive growth of Internet and the consequent proposal of the XML standard for the exchange of data on the Web. Our goal is to develop a formal framework that captures all the issues related to hierarchical data integration systems, whose global schema is expressed by means of an XML schema language. In particular, we will start by considering the case of a global schema specification given by means of a DTD and a set of XML integrity constraints. Moreover, we plan to investigate issues related to XML-based P2P data integration systems. Our research will be done in joint supervision of the department of Computer Science of the University of Rome ”La Sapienza” and the GEMO Project, born from the merging of INRIA-Rocquencourt Verso Project and the IASI group of the University of Paris-Sud.
Can the Error-Monitoring System Differentiate ADHD From ADHD With Reading Disability? Reading and Executive Dysfunction as Reflected in Error Monitoring

Objectives: ADHD and reading disability (RD) are distinct disorders that often appear together. Individuals with both disorders are currently diagnosed based on questionnaires/behavioral performance. The present study aimed to determine whether ADHD alone differs from ADHD with RD in error monitoring, which is part of the executive system, as measured while reading. Method: Event-related potentials were recorded during a lexical decision task performed by children with comorbid ADHD and RD and children with ADHD. Results: Lower executive function and reading abilities were accompanied by decreased event-related potential components in participants with ADHD and RD, compared with participants with ADHD. Conclusion: Results suggest that the error monitoring activation can be used as a possible biomarker to objectively differentiate ADHD with RD from ADHD alone.
Modelling conduction through the Purkinje ventricular junction and the short-QT syndrome associated with HERG mutation in the rabbit ventricles

Remarkable differences in action potential properties between the Purkinje fibre and ventricular cells may lead to abnormalities in excitation conduction through the Purkinje-ventricular junction (PVJ) and arrhythmogenic behaviour. We develop a family of electrophysiologically detailed computer models for rabbit epicardial, midmyocardial and endocardial ventricular myocytes, as well as the rabbit Purkinje fibre cells, in order to simulate a realistic APD dispersion during conduction through the PVJ under normal conditions and under pathological conditions of the short QT syndrome associated with HERG N588K mutation.
Consumption of predefined ‘Nordic’ dietary items in ten European countries – an investigation in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort

Abstract Objective Health-beneficial effects of adhering to a healthy Nordic diet index have been suggested. However, it has not been examined to what extent the included dietary components are exclusively related to the Nordic countries or if they are part of other European diets as well, suggesting a broader preventive potential. The present study describes the intake of seven a priori defined healthy food items (apples/pears, berries, cabbages, dark bread, shellfish, fish and root vegetables) across ten countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) and examines their consumption across Europe. Design Cross-sectional study. A 24 h dietary recall was administered through a software program containing country-specific recipes. Sex-specific mean food intake was calculated for each centre/country, as well as percentage of overall food groups consumed as healthy Nordic food items. All analyses were weighted by day and season of data collection. Setting Multi-centre, European study. Subjects Persons (n 36 970) aged 35–74 years, constituting a random sample of 519 978 EPIC participants. Results The highest intakes of the included diet components were: cabbages and berries in Central Europe; apples/pears in Southern Europe; dark bread in Norway, Denmark and Greece; fish in Southern and Northern countries; shellfish in Spain; and root vegetables in Northern and Central Europe. Large inter-centre variation, however, existed in some countries. Conclusions Dark bread, root vegetables and fish are strongly related to a Nordic dietary tradition. Apples/pears, berries, cabbages, fish, shellfish and root vegetables are broadly consumed in Europe, and may thus be included in regional public health campaigns.
Simulation and design of a nitric oxide sensor array for cell cultures

In this report, we detailed the design and fabrication of a nitric oxide (NO) sensor for cell culture measurements. As an example, we considered NO sensor design for hypoxic cell culture applications (cells which can proliferate at less than 4% oxygen concentration). Primarily, a set of 2D, steady state, reaction coupled diffusion simulation is performed. The simulation results suggest the optimal design of NO sensor array for NO hypoxic cell culture applications. It also deduces the current corresponding to pericellular NO concentration. From the design interpretations, we fabricated thin-film, planar, nitric oxide sensor array (electrode dia. 50 µm) for hypoxic cell cultures which is integrated at the bottom of the cell culture flask to form sensing cell culture flask (SCCF) for NO. We also presented the long-term measurement (upto 18 hrs) of MCF-7 hypoxic breast cancer cells which shows a linear increase in current with respect to time.
Query by Image Content using Color-Texture Features Extracted from Haar Wavelet Pyramid

The paper presents the Wavelet Pyramid based image retrieval techniques [1] using Haar transform. Here content based image retrieval (CBIR) is done using the image feature set extracted from Haar Wavelets applied on the image at various levels of decomposition. Here the database image features are extracted by applying Haar Wavelets on gray plane (average of red, green and blue) and color planes (red, green and blue components). The techniques Gray-Haar Wavelets and Color-Haar Wavelets are tested on image database having 11 categories with total 1000 images. Total 55 queries are fired on the database. The results show that precision and recall of Haar Wavelets are better than complete Haar transform based CBIR, which proves that Haar Wavelets gives better discrimination capability in image retrieval at higher query execution speed, per higher level Haar Wavelets. Color-Haar Wavelets based CBIR have greater precision and recall than Gray-Haar Wavelets based CBIR. The Haar Wavelets level-5 outperforms other Haar Wavelets, because the higher level Haar Wavelets are giving very coarse color-texture features while the lower level are representing very fine color-texture features which are less useful to differentiate the images in image retrieval.
Infoticles: information modeling in immersive environments

This paper introduces an immersive virtual reality application that allows users to browse and explore the contents of database systems. We have implemented a visualization metaphor that is based upon the intrinsic characteristics of particles, coined 'infolicles', which are used as representations of data objects. Users are able to interact with the dynamic, three-dimensional visualization by manipulating forces and surfaces. These tools, representing respectively user interests and data filters, influence the collection of infolicles according to the rules of Newtonian mechanics. Informational values are expressed through the presence of both dynamic and static characteristics such as motion, directionality, and form. We demonstrate these principles through a prototype that uses our university's financial budget data.
Microwave-Assisted Extraction of Oleanolic Acid and Ursolic Acid from Ligustrum lucidum Ait

Oleanolic acid and ursolic acid are the main active components in fruit of Ligustrum lucidum Ait, and possess anticancer, antimutagenic, anti-inflammatory, antioxidative and antiprotozoal activities. In this study, microwave-assisted extraction of oleanolic acid and ursolic acid from Ligustrum lucidum was investigated with HPLC-photodiode array detection. Effects of several experimental parameters, such as type and concentration of extraction solvent, ratio of liquid to material, microwave power, extraction temperature and microwave time, on the extraction efficiencies of oleanolic acid and ursolic acid from Ligustrum lucidum were evaluated. The influence of experimental parameters on the extraction efficiency of ursolic acid was more significant than that of oleanolic acid (p < 0.05). The optimal extraction conditions were 80% ethanol aqueous solution, the ratio of material to liquid was 1:15, and extraction for 30 min at 70 °C under microwave irradiation of 500 W. Under optimal conditions, the yields of oleanolic acid and ursolic acid were 4.4 ± 0.20 mg/g and 5.8 ± 0.15 mg/g, respectively. The results obtained are helpful for the full utilization of Ligustrum lucidum, which also indicated that microwave-assisted extraction is a very useful method for extraction of oleanolic acid and ursolic acid from plant materials.
A fusion ANFIS model for forecasting EPS of leading industries in Taiwan

Earnings per share (EPS) is often regarded as a major indicator for investors to purchase stocks. The traditional approach is to use a conventional linear time series model for EPS prediction. However, the results would be in doubt when the forecasting problems are nonlinear. For this reason, this paper proposes a fusion forecasting model that incorporates an autoregressive model into an adaptive network-based fuzzy inference system (ANFIS) To illustrate the proposed model, 15-quarter EPS data are employed. The experimental results indicate that the proposed model outperforms the listing models