Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel apparatus for light touch threshold measurement

All the people have their own individual force ranges to feel the sense of touch and its minimum value is called light touch threshold (in short LTT). For instance, if a touching force is very weak, people do not know whether the object is contacted to their skin, even though it is pushing the skin already. This paper presents a novel apparatus to measure the LTT felt by each subject, which is referred to as Active von Frey (AvF) in this paper. As far as the authors know, the LTT measurement device is for the first time proposed in this paper. It is possible for the AvF to provide the touching force ranges from 1[mgf] to 400[mgf]. In order to provide an accurate touching force for the subject, D'Arsonval movement is chosen as an actuator to rotate a touching AvF pin. Both an electric current applied to the D'Arsonval movement and a rotational angle of AvF pin are utilized to calculate the touching force by the electro-mechanical statics. In addition, the image processing technique is used to measure the rotational angle of AvF pin. Finally we show that the LTTs are very different from individual to individual through the experimental results of 10 participants. We hope that the personalized parameters is used to design or control haptic or tele-operation devices for various applications.
Bmc Medical Research Methodology Open Access Use of Hierarchical Models to Evaluate Performance of Cardiac Surgery Centres in the Italian Cabg Outcome Study

Background: Hierarchical modelling represents a statistical method used to analyze nested data, as those concerning patients afferent to different hospitals. Aim of this paper is to build a hierarchical regression model using data from the "Italian CABG outcome study" in order to evaluate the amount of differences in adjusted mortality rates attributable to differences between centres.
Dengue Virus Type 3 Adaptive Changes during Epidemics in São Jose de Rio Preto, Brazil, 2006–2007

Global dengue virus spread in tropical and sub-tropical regions has become a major international public health concern. It is evident that DENV genetic diversity plays a significant role in the immunopathology of the disease and that the identification of polymorphisms associated with adaptive responses is important for vaccine development. The investigation of naturally occurring genomic variants may play an important role in the comprehension of different adaptive strategies used by these mutants to evade the human immune system. In order to elucidate this role we sequenced the complete polyprotein-coding region of thirty-three DENV-3 isolates to characterize variants circulating under high endemicity in the city of São José de Rio Preto, Brazil, during the onset of the 2006-07 epidemic. By inferring the evolutionary history on a local-scale and estimating rates of synonymous (dS) and nonsynonimous (dN) substitutions, we have documented at least two different introductions of DENV-3 into the city and detected 10 polymorphic codon sites under significant positive selection (dN/dS > 1) and 8 under significant purifying selection (dN/dS < 1). We found several polymorphic amino acid coding sites in the envelope (15), NS1 (17), NS2A (11), and NS5 (24) genes, which suggests that these genes may be experiencing relatively recent adaptive changes. Furthermore, some polymorphisms correlated with changes in the immunogenicity of several epitopes. Our study highlights the existence of significant and informative DENV variability at the spatio-temporal scale of an urban outbreak.
Incremental Information Flow Analysis of Role Based Access Control

Role-Based Access Control (RBAC) has been widely used for expressing access control policies. Although RBAC provides flexible mechanisms to control the access to information, it does not control how the information propagates after it is obtained. Formally analyzing information flows resulting from an RBAC policy helps administrators understand the policy and detect potential flaws in the policy. Further, RBAC policies tend to evolve incrementally over time and it would be inefficient to perform analysis from scratch upon every change to the policies. Incremental analysis is useful in situations where small changes to the policy lead to small or no changes to the analysis result. In this paper, we present the first algorithms for incrementally analyzing information flows whenever a change is made to an RBAC policy. The performance results show that our incremental algorithms significantly outperform our nonincremental algorithm in terms of execution time while requiring only moderately larger disk space.
Intakes and sources of isoflavones, lignans, enterolignans, coumestrol and soya-containing foods in the Norfolk arm of the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk), from 7 d food diaries, using a newly updated database

Abstract Objective A diet rich in phyto-oestrogens has been suggested to protect against a variety of common diseases but UK intake data on phyto-oestrogens or their food sources are sparse. The present study estimates the average intakes of isoflavones, lignans, enterolignans and coumestrol from 7 d food diaries and provides data on total isoflavone, lignan and phyto-oestrogen consumption by food group. Design Development of a food composition database for twelve phyto-oestrogens and analysis of soya food and phyto-oestrogen consumption in a population-based study. Setting Men and women, aged 40–79 years, from the general population participating in the Norfolk arm of the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk) between 1993 and 1997, with nutrient and food data from 7 d food diaries. Subjects A subset of 20 437 participants. Results The median daily phyto-oestrogen intake for all men was 1199 μg (interquartile range 934–1537 μg; mean 1504 μg, sd 1502 μg) and 888 μg for all women (interquartile range 710–1135 μg; mean 1205 μg, sd 1701 μg). In soya consumers, median daily intakes were higher: 2861 μg in men (interquartile range 1304–7269 μg; mean 5051 μg, sd 5031 μg) and 3142 μg in women (interquartile range 1089–7327 μg; mean 5396 μg, sd 6092 μg). In both men and women, bread made the greatest contribution to phyto-oestrogen intake – 40·8 % and 35·6 %, respectively. In soya consumers, vegetable dishes and soya/goat's/sheep's milks were the main contributors – 45·7 % and 21·3 % in men and 38·4 % and 33·7 % in women, respectively. Conclusions The ability to estimate phyto-oestrogen intake in Western populations more accurately will aid investigations into their suggested effects on health.
GALEX Ultraviolet Observations of Stellar Variability in the Hyades and Pleiades Clusters

We present GALEX near-ultraviolet (NUV: 1750–2750 Å) and far-ultraviolet (FUV: 1350–1750 Å) imaging observations of two 1.2° diameter fields in the Hyades and Pleiades open clusters in order to detect possible UV variability of the member stars. We have performed a detailed software search for short-term UV flux variability during these observations of the ∼400 sources detected in each of the Hyades and Pleiades fields to identify flarelike (dMe) stellar objects. This search resulted in the detection of 16 UV variable sources, of which 13 can be directly associated with probable M-type stars. The other UV sources are G-type stars and one newly discovered RR Lyrae star, USNOB1.0 1069–0046050, of period 0.624 day and distance ∼4.5 to 7 kpc. Light curves of photon flux versus time are shown for seven flare events recorded on six probable dMe stars. UV energies for these flares span the range 2 × 1027 to 5 × 1029 erg, with a corresponding variability change of ΔNUV = 1.82 mag. Only one of these flare events (on the star Cl* Melotte 25 LH129) can definitely be associated with an origin on a member of the Hyades cluster itself. Finally, many of our M-type candidates show long periods of enhanced UV activity but without the associated rapid increase in flux that is normally associated with a flare event. However, the total UV energy output during such periods of increased activity is greater than that of many short-term UV flares. These intervals of enhanced low-level UV activity concur with the idea that, even in quiescence, the UV emission from dMe stars may be related to a superposition of many small flare events possessing a wide range of energies.
Improving Initial Estimations for Structure from Motion Methods

In Computer Graphics as well as in Computer Vision and Autonomous Navigation, Structure from Motion is a common method to register cameras. Usually several steps are involved with bundle-adjustment as the final one. A good initial estimation of camera positions is of crucial importance for the success of the bundle-adjustment and is the core component of any Structure from Motion system. Yet there are some limitations to current Structure from Motion tools regarding the quality of the initial estimation. With our proposed method of merging different connected components resulting from a lack of good input images, we aim to overcome the fact that at first glance no global initial estimation could be found. We will show that in many of these situations our method is applicable and may even be used to speed up the Structure from Motion process and limit its memory consumption in general.
Use of a novel multipart controller for the parametric study of a trotting quadruped robot

In this paper a novel multipart control is developed for a trotting quadruped robot. The control is designed to drive the quadruped to a steady-state motion with desired forward speed and apex height, using only one actuator per leg. The body pitching motion is controlled to be small. The controller is applied to the robot and the complete system is used to develop a parametric study for the robot. The study examines the behavior of the actuator effort and the leg touchdown angles, over a parametric region of both the robot physical parameters and the gait parameters. Interesting results appear, not previously reported, that may contribute to enhanced robot design and better gait selection for a given robot. Typical findings are that a robot should be lighter- weight when running on more slippery terrain, as well as that certain higher forward speeds require less actuator effort than other slower speeds.
An Automatic Irrigation Control System for Soilless Culture of Lettuce

To achieve precise measurement of moisture content in the substrate and intelligent water-saving irrigation, a simple and low cost automatic irrigation control system based on ZigBee wireless network has been developed. A software with irrigation strategy was proposed based on the models of substrate wetting pattern, lettuce root zone and the evapotranspiration. The system could detect substrate moisture in real-time and irrigate automatically according to the threshold of substrate and the irrigation strategy. The average fresh weight per plant under intelligent irrigation are 16.60% and 11.37% higher than manual control irrigation at least in different growth stages in spring and summer, the average drainage rate of intelligent irrigation is 16.08% and 17.06% smaller than manual control irrigation in spring and summer, and the irrigation water use efficiency of intelligent irrigation is 68.03% and 98.61% higher than manual control irrigation in spring and summer. The results show that the system is a promising tool for scientific and rational irrigation decision.
A Survey of Key Pre Distribution Schemes in Wireless Sensor Networks

Wireless Sensor Network (WSN) is an area of research that has various applications both for mass public and military. A wireless sensor network is composed of many sensors which can be used to monitor physical or environmental conditions, such as temperature, sound, pressure. After collecting these data they should pass this data through the network to a main location. A Sensor Node in Wireless Sensor Network lacks resources such as processing capability, memory capacity, battery power, and communication capability. Because of the limited resources on sensor nodes, the use of conventional key management techniques in wireless sensor networks is limited. Key establishment is the most important cryptographic primitive in all kinds of applications where security is a concern. Authentication and pair wise key establishment are critical in sensor networks. In this paper, we provide a survey of key management schemes in wireless sensor networks.
CDSMs for Semantic Relatedness and Entailment

Distributional Semantics Models (DSMs) have become widely accepted as successful models for lexical semantics. However their extension to handling larger structural units such as entire sentences remains challenging. Compositional DSMs (CDSMs) aim to successfully model sentence semantics by taking into account grammatical structure and logical words, which are ignored by simpler models. We explore a recursive matrix-vector space model, where each word or phrase has associated with it a vector capturing its semantics, as well as a matrix capturing how it alters the meanings of other words or phrases in its vicinity. We proceed to test this proposed CDSM on the tasks of semantic relatedness score prediction and semantic entailment classification, over the SICK data set of approximately 10,000 sentence pairs.
An effective unsupervised network anomaly detection method

In this paper, we present an effective tree based subspace clustering technique (TreeCLUS) for finding clusters in network intrusion data and for detecting unknown attacks without using any labelled traffic or signatures or training. To establish its effectiveness in finding all possible clusters, we perform a cluster stability analysis. We also introduce an effective cluster labelling technique (CLUSLab) to generate labelled dataset based on the stable cluster set generated by TreeCLUS. CLUSLab is a multi-objective technique that exploits an ensemble approach for stability analysis of the clusters generated by TreeCLUS. We evaluate the performance of both TreeCLUS and CLUSLab in terms of several real world intrusion datasets to identify unknown attacks and find that both outperform the competing algorithms.
Interannual variability of the rainfall regime and strong ENSO events along the Peruvian Pacific Basin: large-scale control mechanisms

Four strong El Nino events took place within the last five decades (1972/1973, 1982/1983, 1997/1998 and 2015/2016) recorded as strong in the Nino 3.4 region. They can exhibit significant differences in their evolution associated with a distinct rainfall anomaly evolution along the PPB (Peruvian Pacific Basin), which illustrates the strong nonlinearity of the ENSO teleconnection on the rainfall in this area. These extreme rainfalls have harmful impacts on the population and productive sectors due to floods and landslides which are trigged by them. Yet the key climatic circulation pattern for their different evolution and magnitude are still unknown. Here we show that different rainfall patterns during these events are associated with moisture transport originated from different large-scale moisture sources. For example, in the 1983 -1998 (2016) events appear as related with strong (weak to moderate) moisture coming from the Pacific warming (also coming from Atlantic Ocean through the Amazon basin). Characteristic of these moisture transports is due to an atmospheric response opposite between the 1983-1998 events (that are similar) and 2016 event experiencing out-of-phase moisture transport patterns. Although these rainfalls are linked to the moisture arrival from those sources, the moisture amount entering the PPB can be also influenced by regional atmospheric circulation of upper level winds (100 to 300 hPa) leading to different enhanced moisture transport associated with different rainfall anomalies in the North-Centre PPB. The interplay of large-scale and regional circulation and Pacific moisture transport explains the Ep mode associated with rainfall in the north-Centre PPB. The high dispersion of rainfall in highlands (Cp mode) during the moderate (extremes) El Nino appears as linked to low-middle (high level) moisture transport from the Amazon (Pacific) reaching highlands.
Dynamic security policy learning

Recent research [12] has suggested that traditional top down security policy models are too rigid to cope with changes in dynamic operational environments. There is a need for greater flexibility in security policies to protect information appropriately and yet still satisfy operational needs. Previous work has shown that security policies can be learnt from examples using machine learning techniques. Given a set of criteria of concern, one can apply these techniques to learn the policy that best fits the criteria. These criteria can be expressed in terms of high level objectives, or characterised by the set of previously seen decision examples. We argue here that even if an optimal policy could be learnt automatically, it will eventually become sub-optimal over time as the operational requirements change. The policy needs to be updated continually to maintain its optimality. This paper proposes two dynamic security policy learning frameworks
Evaluating physiological strain during cold exposure using a new cold strain index.

A cold strain index (CSI) based on core (Tcore) and mean skin temperatures (T sk) and capable of indicating cold strain in real time and analyzing existing databases has been developed. This index rates cold strain on a universal scale of 0-10 and is as follows: CSI = 6.67(Tcoret - Tcore 0) ⋅ (35 - Tcore 0)-1 + 3.33(T sk t -T sk 0) ⋅ (20 -T sk 0)-1, where Tcore 0 andT sk 0are initial measurements and Tcoret andT skt are simultaneous measurements taken at any time t; when Tcoret > Tcore 0, then Tcoret - Tcore 0 = 0. CSI was applied to three databases. The first database was obtained from nine men exposed to cold air (7°C, 40% relative humidity) for 120 min during euhydration and two hypohydration conditions achieved by exercise-heat stress-induced sweating or by ingestion of furosemide 12 h before cold exposure. The second database was from eight men exposed to cold air (10°C) immediately on completion of 61 days of strenuous outdoor military training, 48 h later, and after 109 days. The third database was from eight men repeatedly immersed in 20°C water three times in 1 day and during control immersions. CSI significantly differentiated ( P < 0.01) between the trials and individually categorized the strain of the subject for two of these three databases. This index has the potential to be widely accepted and used universally.
Acoustical performance of complex-shaped earth berms

Earth berms have been used for many years along railways and motorways as noise abatement systems. On one hand their construction is often cheaper than traditional barriers with less negative environmental impacts and better visual integration. On the other hand they need more space to be built and are always proposed with the same global symmetrical, smooth shape. In this work we propose to assess the efficiency of various complex-shaped earth berms dedicated to ground transportation using a 2D Boundary Element Method. For urban roads and tramways innovative low-height berms - no more than 1 m high - are proposed and study. For railways and motorways taller complex-shaped systems up to 6 m high are assessed. The analysis is carried out for 1.5 m high receivers areas (pedestrians, cyclists) as well as 4 m high ones (buildings). Results are expressed in terms of acoustic gain obtained with the complex-shaped earth berm solution referred to a straight rigid barrier located at the infrastructures edge.
Physiological and molecular adaptations to drought in Andean potato genotypes

The drought stress tolerance of two Solanum tuberosum subsp. andigena landraces, one hybrid (adg×tbr) and Atlantic (S. tuberosum subsp. tuberosum) has been evaluated. Photosynthesis in the Andigena landraces during prolonged drought was maintained significantly longer than in the Tuberosum (Atlantic) line. Among the Andigena landraces, ‘Sullu’ (SUL) was more drought resistant than ‘Negra Ojosa’ (NOJ). Microarray analysis and metabolite data from leaf samples taken at the point of maximum stress suggested higher mitochondrial metabolic activity in SUL than in NOJ. A greater induction of chloroplast-localized antioxidant and chaperone genes in SUL compared with NOJ was evident. ABA-responsive TFs were more induced in NOJ compared with SUL, including WRKY1, mediating a response in SA signalling that may give rise to increased ROS. NOJ may be experiencing higher ROS levels than SUL. Metabolite profiles of NOJ were characterized by compounds indicative of stress, for example, proline, trehalose, and GABA, which accumulated to a higher degree than in SUL. The differences between the Andigena lines were not explained by protective roles of compatible solutes; hexoses and complex sugars were similar in both landraces. Instead, lower levels of ROS accumulation, greater mitochondrial activity and active chloroplast defences contributed to a lower stress load in SUL than in NOJ during drought.
Textureless object recognition and arm planning for a mobile manipulator

Manipulator robots require of comprehensible perception systems that permit them to interact with the environment, localize target objects and perform complex manipulation tasks. To do that, a full-step manipulation process has to be performed involving recognition of supporting planes, object clustering, its recognition and finally smooth arm trajectory planning with obstacle avoidance. The goal of this paper is to propose a general and practical strategy for designing a 3D perception system architecture that can robustly plan for the location of texture and untextured objects for the purpose of grasping. Our proposed system includes RGB-D calibrated system to acquire 3D color scenario data, a 7-DOF arm controlled with a PMAC 2-PCI and a precise arm-end grasp. A validation of the overall proposed idea with some experimental results and a comparison of the benefits with similar initiatives is presented.
The development of a fire vulnerability index for the mediterranean region

The SIGRI (Sistema Integrato per la Gestione del Rischio Incendi) pilot project, funded by ASI (the Italian Space Agency), aims at developing an Integrated System for the Management of the Wild Fire Events. The system should provide satellite based products capable to help fire contrasting activities during all the phases: prevision, detection, and damage assessment/recovering. In particular, the paper concerns the development of a Fire Risk Index to be produced daily with the objective of showing the total level of risk for the area of interest and the zones of major concern within such area. In the European Community the member countries interested by forest fires are at least six: Portugal, Spain, France, Germany, Italy, and Greece. The higher number of wild fires occurs in the western part of Spain and Portugal, in southern Italy and in the Mediterranean islands The idea to develop maps able to show the fire risk is based on the observation that there is a tight relationship between the fire and the characteristics of the fuel (vegetation type, density, humidity content), of the topography (slope, altitude, solar aspect angle) and the meteorological conditions (rainfall, wind direction and speed, air humidity, surface and air temperature). These parameters directly impact the proneness of a given area to the fire ignition and propagation. Since these quantities can be measured, notwithstanding the cause of the fire ignition, mainly due, in Italy, to human actions (more than 90% of the ignitions is intentional or accidental), could be unpredictable the behaviour of the fire can be considered strictly dependent from those and then it can be foreseen when such parameters are known.