Low Intrusion Research Articles

Trait Anxiety and Attention: Cognitive Functioning as a Function of Attentional Demands

This study examined the relationship between trait anxiety and cognitive functioning, specifically response inhibition and conflict resolution, by comparing attention switching and sustained attention conditions in a dichotic-listening to words task. Results showed that high- as compared to low-anxiety participants had a lower hit rate in both attention conditions, a lower intrusion rate in the sustained attention condition, and greater difficulty shifting attention in the mixed condition. Furthermore, laterality-related findings revealed that high-anxiety participants had a lower hit rate when attention was directed to the left-ear (right hemisphere) and less intrusions when attention was directed right-ear (left hemisphere) than did the low-anxiety participants. The findings are interpreted based on attentional control and load theories as well as on the attentional model of hemisphere asymmetry, supporting the proposition that high anxiety is associated with an imbalance between bottom-up and top-down processes, and that anxiety may affect cognitive control under high cognitive load conditions.

Improved Interpretation of Mercury Intrusion and Soil Water Retention Percolation Characteristics by Inverse Modelling and Void Cluster Analysis

This work addresses two continuing fallacies in the interpretation of percolation characteristics of porous solids. The first is that the first derivative (slope) of the intrusion characteristic of the non-wetting fluid or drainage characteristic of the wetting fluid corresponds to the void size distribution, and the second is that the sizes of all voids can be measured. The fallacies are illustrated with the aid of the PoreXpert® inverse modelling package. A new void analysis method is then described, which is an add-on to the inverse modelling package and addresses the second fallacy. It is applied to three widely contrasting and challenging porous media. The first comprises two fine-grain graphites for use in the next-generation nuclear reactors. Their larger void sizes were measured by mercury intrusion, and the smallest by using a grand canonical Monte Carlo interpretation of surface area measurement down to nanometre scale. The second application is to the mercury intrusion of a series of mixtures of ground calcium carbonate with powdered microporous calcium carbonate known as functionalised calcium carbonate (FCC). The third is the water retention/drainage characteristic of a soil sample which undergoes naturally occurring hydrophilic/hydrophobic transitions. The first-derivative approximation is shown to be reasonable in the interpretation of the mercury intrusion porosimetry of the two graphites, which differ only at low mercury intrusion pressures, but false for FCC and the transiently hydrophobic soil. The findings are supported by other experimental characterisations, in particular electron and atomic force microscopy.

Improving the picture archiving and communication system: towards one-click clinical quantifying applications

The picture archiving and communication system (PACS) replaced the old film archiving mechanism that stored and moved the data produced by different image-acquisition devices within hospitals. Using the standard Internet transport protocol, PACS creators developed a robust digital signaling platform to optimise media use, availability and confidentiality. Currently, PACS is ubiquitous in medical facilities but lacks image-analytics capabilities. A myriad of initiatives have been launched in the hope of achieving this goal, but current solutions face issues with security and ease-of-use that have precluded their widespread adoption. Here, we present a PACS vehicle that enables the use of analytic tools in medical networks. The vehicle safeguards patient confidentiality, is user-friendly, has low intrusiveness and is easy to implement. The PACS vehicle has been thoroughly tested and, as a proof of concept, we disclose a hydrocephalus case where clinicians wanted to determine the volume of the lateral ventricles before and after placing a cerebro-spinal fluid diverting shunt. When the images were made available at a bit level using the developed vehicle, a fully automatic algorithm estimated the ventricular volumes from images before and after shunting. The image transferring took 15.74 s moving 12.54 MB of data. With a click of the mouse, the volume change was determined and incorporated in the report of the study. Three videos demonstrating the feasibility of the methods proposed here and the clinical significance of this solution are provided along with this paper.

Modeling fitness changes in wild Atlantic salmon populations faced by spawning intrusion of domesticated escapees.

Genetic interaction between domesticated escapees and wild conspecifics represents a persistent challenge to an environmentally sustainable Atlantic salmon aquaculture industry. We used a recently developed eco‐genetic model (IBSEM) to investigate potential changes in a wild salmon population subject to spawning intrusion from domesticated escapees. At low intrusion levels (5%–10% escapees), phenotypic and demographic characteristics of the recipient wild population only displayed weak changes over 50 years and only at high intrusion levels (30%–50% escapees) were clear changes visible in this period. Our modeling also revealed that genetic changes in phenotypic and demographic characteristics were greater in situations where strayers originating from a neighboring wild population were domestication‐admixed and changed in parallel with the focal wild population, as opposed to nonadmixed. While recovery in the phenotypic and demographic characteristics was observed in many instances after domesticated salmon intrusion was halted, in the most extreme intrusion scenario, the population went extinct. Based upon results from these simulations, together with existing knowledge, we suggest that a combination of reduced spawning success of domesticated escapees, natural selection purging maladapted phenotypes/genotypes from the wild population, and phenotypic plasticity, buffer the rate and magnitude of change in phenotypic and demographic characteristics of wild populations subject to spawning intrusion of domesticated escapees. The results of our simulations also suggest that under specific conditions, natural straying among wild populations may buffer genetic changes in phenotypic and demographic characteristics resulting from introgression of domesticated escapees and that variation in straying in time and space may contribute to observed differences in domestication‐driven introgression among native populations.

Employment of optical fibers for RC bond-slip characterization

Some features as workability, high durability and low cost of production have contributed for reinforced concrete (RC) be largely used worldwide. However, environmental actions and the natural material decaying are the most common processes that contribute for the loss of the physical-mechanical properties of the RC structures. When the bond between the concrete and the reinforcing rebar are affected, the results can be extremely dramatic and unpredicted. In this work, an optical fiber device for the monitoring of the bond-slip of old RC structures, where less intrusive techniques need to be considered, is proposed and tested. The sensor developed is based on the fiber Bragg grating (FBG) technology, inscribed in silica optical fiber. A pull-out test was carried out in a RC specimen, following the recommendations of the Annex D of the EN 10080. The results showed that the bond-slip optical sensors are capable to measure micro-displacements, with lower intrusiveness. Therefore, they can be used for monitoring the bond-slip of old RC structures as way of to collect information, essential to assist the owners to adopt cost effective, efficient and safer maintenance measures.

Acute Intermittent Porphyria in the North of China: The Acute Attack Effect on Quality of Life and Psychological Condition.

Background Acute intermittent porphyria (AIP) is an autosomal recessive disorder with intermittent attacks. Patients with AIP are susceptible to impaired quality of life and psychological distress. Objectives To document the clinical features of AIP and its impact on SF-36 and IES scores of AIP patients in China and to explore the variables associated with SF-36 and IES scores. Methods A single investigator collated data related to treatments and outcomes in 27 patients with AIP of PUMCH. A cross-sectional questionnaire survey including the SF-36, the IES-R, and demographic questions was conducted in the north of China. Differences in the QoL scale/summary scores and proportions in the QoL dimensions between patients and the general population were analyzed. Independent effects of chronic conditions and demographic variables on the SF-36 and IES-R were analyzed. Results AIP patients had considerably lower SF-36 scores than the general population (the PF score and MH were lower than normal, P < 0.05). Working had higher RP than staying at home (P = 0.02); “without acute attack” had higher PF and BP scores and PCS composite score (P = 0.001). The mean IES-R score of AIP was higher than normal (36.7 ± 11.8 points, P < 0.001), “without acute attack” had lower intrusion score than “with acute attack” (P = 0.03). Conclusion AIP patients in China had impaired quality of life, especially in terms of physical health. The acute attacks coursed the posttraumatic stress disorder-related symptoms.

Serotonin transporter 5-HTTLPR genotype is associated with intrusion and avoidance symptoms of DSM-5 posttraumatic stress disorder (PTSD) in Chinese earthquake survivors

ABSTRACTBackground and Objectives: Prior studies have found that the serotonin transporter gene-linked polymorphic region (5-HTTLPR) interacts with trauma exposure to increase general risk for Posttraumatic Stress Disorder (PTSD). However, there is little knowledge about the effects of the interaction on distinct symptom clusters of PTSD. This study aimed to investigate the relation between the interaction of 5-HTTLPR and earthquake-related exposures and a contemporary phenotypic model of DSM-5 PTSD symptoms in a traumatised adult sample from China.Design: A cross-sectional design with gene-environment interaction (G × E) approach was adopted. Methods: Participants were 1131 survivors who experienced 2008 Wenchuan earthquake. PTSD symptoms were assessed with the PTSD Checklist for DSM-5 (PCL-5). The 5-HTTLPR polymorphism was genotyped with capillary electrophoresis (CE) in ABI 3730xl genetic Analyzer.Results: Although there was no significant interaction between 5-HTTLPR and traumatic exposure on total PTSD symptoms, respondents with the LL genotype of 5-HTTLPR who were highly exposed to the earthquake experienced lower intrusion and avoidance symptoms than those with the S-allele carriers.Conclusions: The findings suggest that the 5-HTTLPR may have an important impact on the development of PTSD and add to the extant knowledge on understanding and treating of posttraumatic psychopathology.

A method for real-time wireless monitoring of the efficiency and conditions of three-phase induction motor operation

Concerning the primary aim of attending to the requirements used in the monitoring of induction motor efficiency, along with prioritizing a low intrusion level, the Literature presents various methods that need only the voltages, currents and some rotor speed cases. In a general sense, these methods estimate the torque on the machine shaft, along with calculate the output power and efficiency, through the use of a variety of different techniques. In this context, the present study proposes a real time wireless monitoring method over the operation conditions and efficiency of the three-phase induction motors. The method proposed herein estimates through the values measured on the three-phase voltages and currents and the equivalent circuit of the machine, the torque and speed of the shaft. Based on these estimates, both output power and efficiency can be calculated. The equivalent circuit of the machine is estimated through an iterative algorithm that uses only the data from the machine plate and the resistance of the stator, as will be shown in this study.

Low-impact cable system adopted for the Awa Shirasagi Ohashi Bridge, Japan

The Awa Shirasagi Ohashi Bridge is located at the tidal estuary of the River Yoshino in Japan, adjacent to wetlands where migratory birds such as snipe and plover congregate. As the wetlands form a unique and invaluable ecosystem, an environmental conservation group expressed serious concerns over the construction of the bridge. A long-span bridge with low visual intrusiveness to avoid any negative impacts on the ecosystem associated with the wetland was required. To satisfy the requirements, a unique type of cable trussed system termed a ‘cable egret’ structure was designed. The proposed structural form enabled a 260 m long span with pylons only extending 29·6 m above the deck and a minimum number of cables, minimising impacts on the ecosystem associated with the wetland. In the span between the two pylons, the main girders made composite with the sandwich slabs are propped by intermediate under-slung supports, which are in turn suspended by a cable truss system. This paper describes details of the cable egret system and the construction method adopted for the bridge, which allowed the environmental impact to be minimised.

Detection and modelling of incipient failures in internal combustion engine driven generators using Electrical Signature Analysis

Condition-based maintenance of electric generators have been gaining increasing importance due to the electricity demand and the criticality that this equipment represents to electrical power systems. In this context, this paper proposes a methodology and a system for detection and modeling of incipient failures in the components of internal combustion engine-driven generators based on Electrical Signature Analysis (ESA). The proposed methodology enables the detection of incipient faults both in the prime mover and in the coupled synchronous generator, only relying on measurements of the generator stator voltages and currents. The proposed ESA failure patterns are based on defined frequencies and the structural features of the machine, so they can be reproduced in a wide range of engine-generators sets. The main advantages of the proposed system are its low intrusiveness, feasible installation and cost efficiency. A scale model laboratory has been designed to simulate faults in a small diesel generator and apply the ESA methodology to detect these faults and obtain the failure patterns. Experimental results are presented to prove the effectiveness of the proposed methodology. The main results include the findings that exciter generator unbalance induces electrical unbalance components, exciter diode short circuit induces even harmonics, intake valve failure and piston ring failure induce multiples of rotation frequency components, and mechanical misalignment of the engine generator set induces multiples of half order speed frequency components on ESA. Moreover, the proposed prototype is installed at two large in-service internal combustion engine-driven generators and examples of signal analysis are provided.

Fathering moderates the effects of maternal depression on the family process.

Maternal depression negatively impacts children's development, yet few studies have focused on fathering and the family process in cases of maternal depression. A community cohort of married/cohabitating women was recruited on the second postbirth day (N = 1,983) and maternal depression repeatedly assessed across the first year and again at 6 years to form two cohorts: mothers chronically depressed from birth to 6 (N = 46) and nondepressed controls (N = 103). At 6 years, mother-child, father-child, and family interactions were observed. In families of depressed mothers, both mother and father exhibited lower sensitivity and higher intrusiveness, and children displayed lower social engagement during interactions with mother and father. Fathering moderated the effects of maternal depression on the family process. When fathers showed low sensitivity, high intrusiveness, and provided little opportunities for child social engagement, the family process was less cohesive, implying a decrease in the family's harmonious, warm, and collaborative style. However, in cases of high father sensitivity, low intrusiveness, and increased child engagement, the family process was unaffected by maternal depression. Findings describe both comparability and compensatory mechanisms in the effects of fathering on family life when maternal care is deficient, highlight the buffering role of fathers, and underscore the importance of father-focused interventions when mothers are depressed.

On the complex domain deep machine learning for face recognition

Biometric based verification and recognition has become the center of attention for many significant applications for security conscious societies, as it is believed that biometrics can provide accurate and reliable identification. The face biometrics are one that possesses the merits of both high accuracy and low intrusiveness. An efficient machine recognition of human faces in big dataset is both important and challenging tasks. This paper addresses an intelligent face recognition system that is pose invariant and can recognize multi-expression, occluded and blurred faces through efficient but compact deep learning. Superior functionality of neural network in a complex domain has been observed in recent researches. My work presents a new approach, which is the fusion of higher-order novel neuron models with multivariate statistical techniques in a complex domain with a sole goal of improving performance of biometric systems. This also aims at reducing the computational cost and providing a faster recognition system. This paper presents the formal algorithms for feature extraction with multivariate statistical techniques in complex domain and compare them their real domain counterpart. This paper also presents a classifier structure (OCON : One-Class-in-One-Neuron) which contains an ensemble of novel higher order neurons, which drastically reduces the complexity of proposed learning machine because only single neuron is sufficient to recognize a subject in the database. This novel fusion in the proposed deep learning machine has thoroughly presented its superiority over a wide spectrum of experiments. Advanced deep learning capabilities, and complex domain implementation in particular, are significantly advancing state-of-art in computer vision and pattern recognition.

Some thoughts on the monitoring and preservation of waterlogged archeological sites in eastern England

This study reviews five hydrological monitoring projects used on archeological sites in the waterlogged landscapes of fenland East Anglia and east Yorkshire in England. The project design, recorded variables, and implications of each are discussed. In particular, the importance of understanding the landscape context is paramount, and retrieving an appropriate dataset over a sufficiently lengthy period of time to obtain reliable results and predictability. Some of the lessons learnt and outstanding problems are explored. As former wetlands are fast disappearing around the world through dewatering and a host of wider development threats such as urbanization and gravel extraction, the low intrusion suite of methods described here for measuring the degree and certainty of organic preservation is doubly important for establishing the viability of preservation in situ schemes for waterlogged archeological sites. This is crucial to get right, as wetland archeological records are an irreplaceable resource which offer extraordinarily full and diverse datasets of human lifeways which are all too often either poorly preserved or erroneously interpreted because of the skewed datasets recovered from dryland sites. WIREs Water 2017, 4:e1204. doi: 10.1002/wat2.1204This article is categorized under: Science of Water &gt; Methods Science of Water &gt; Water and Environmental Change Human Water &gt; Water as Imagined and Represented

RT-WABest: A novel end-to-end bandwidth estimation tool in IEEE 802.11 wireless network

In 802.11 wireless network, a large number of multimedia applications are emerging. Accurate end-to-end bandwidth estimation techniques can help these applications adjust their behavior accordingly, such as stream’s bitrate adaptation, to improve quality of service. However, most current bandwidth estimation techniques are designed for wired networks that have high intrusiveness and consume long convergence time, which cannot be applied in resource-limited wireless network. In this article, we present a novel bandwidth estimation tool for IEEE 802.11 wireless network, which only needs to be deployed in one end of the end-to-end path and estimate available bandwidth based on round-trip-time measurements with low intrusiveness and short convergence time. We compare our tool with another state-of-the-art tool on an IEEE 802.11 wireless testbed, and the experimental results show that our tool has higher accuracy.

Validation of a low intrusiveness heart rate sensor for stress assessment

Heart rate variability (HRV) analysis has been used as a quantitative marker of the autonomous nervous system activity to measure mental stress. Wearable sensors have been emerging as a solution to collect HRV data for stress assessment in a real context, however such studies raise additional requirements. The wearable system must be minimally obtrusive to allow the subjects to perform their tasks without interference, and inconspicuous to avoid the anxiety associated with wearing medical devices in public. The purpose of this study was to quantify the accuracy trade-off in the use of a chest band heart rate sensor that is less intrusive and less costly than a wearable electrocardiogram (ECG). The HRV metrics extracted from a chest band heart rate monitor, Zephyr HxMTM (ZphTM), were compared with those extracted from an ECG certified medical device, Vital JacketTM (VJTM). The two systems were worn simultaneously under laboratory conditions by a population of 14 young and healthy subjects, aged 20 to 26 years, under the stress induced by the Trier Social Stress Test (TSST) procedure. The results showed a mean difference between RR intervals of 9 ms; a root-mean square error (RMSE) of less than 8% and a Pearson’s correlation higher than 0.946, considering all TSST phases. In the HRV analysis, the average of all normal intervals (AVNN) showed errors less than 2% between the two systems with a correlation higher than 0.99 for all TSST phases. We thus conclude that the used chest band sensor represents an alternative to the current wearable medical devices to monitor RR intervals, and could be used for mental stress monitoring similar to the TSST protocol.

A Hybrid Fault-Tolerant LEON3 Soft Core Processor Implemented in Low-End SRAM FPGA

In this work we implemented a hybrid fault-tolerant LEON3 soft-core processor in a low-end FPGA (Artix-7) and evaluated its error detection capabilities through neutron irradiation and fault injection in an incremental manner. The error mitigation approach combines the use of SEC/DED codes for memories, a hardware monitor to detect control-flow errors, software-based techniques to detect data errors and configuration memory scrubbing with repair to avoid error accumulation. The proposed solution can significantly improve fault tolerance and can be fully embedded in a low-end FPGA, with reduced overhead and low intrusiveness.

Fitting processor architectures for measurement-based probabilistic timing analysis

The pressing market demand for competitive performance/cost ratios compels Critical Real-Time Embedded Systems industry to employ feature-rich hardware. The ensuing rise in hardware complexity however makes worst-case execution time (WCET) analysis of software programs – which is often required, especially for programs at the highest levels of integrity – an even harder challenge. State-of-the-art WCET analysis techniques are hampered by the soaring cost and complexity of obtaining accurate knowledge of the internal operation of advanced processors and the difficulty of relating data obtained from measurement observations with reliable worst-case behaviour. This frustrating conundrum calls for novel solutions, with low intrusiveness on development practice. Measurement-Based Probabilistic Timing Analysis (MBPTA) techniques offer the opportunity to simultaneously reduce the cost of acquiring the knowledge needed for computing reliable WCET bounds and gain increased confidence in the representativeness of measurement observations. This paper describes the changes required in the design of several high-performance features – massively used in modern processors – to meet MBPTA requirements.

Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning

This paper argues that the research field of Artificial Intelligence in Education (AIED) can benefit from integrating recent technological advances (e.g., wearable devices, big data processing, 3D modelling, 3D printing, ambient intelligence) and design methodologies, such as TORMES, when developing systems that address the psychomotor learning domain. In particular, the acquisition of motor skills could benefit from individualized instruction and support just as cognitive skills learning has over the last decades. To this point, procedural learning has been considered since the earliest days of AIED (dating back to the 1980’s). However, AIED developments in motor skills learning have lagged significantly behind. As technology has evolved, and supported by the do-it-yourself and quantified-self movements, it is now possible to integrate emerging interactive technologies in order to provide personal awareness and reflection for behavioural change at low cost and with low intrusion. Many activities exist that would benefit from personalizing motor skills learning, such as playing a musical instrument, handwriting, drawing, training for surgery, improving the technique in sports and martial arts, learning sign language, dancing, etc. In this context, my suggestions for AIED research in the coming 25 years focus on addressing challenges regarding 1) modelling the psychomotor interaction, and 2) providing appropriate personalized psychomotor support.

Modeling the Perceptual Response from Effects Oriented Web Components Towards Lower Intrusiveness

The design of web applications includes the use of components that attempt to increase influence on target audience to achieve expected results in the form of interactions. In this area, conflicts between user experience and business goals are observed, especially when primary tasks within a website are negatively affected by intrusive marketing messages. The proposed in this paper approach based on perceptual experiments is related to modeling the structure of interactive objects and building an inference model, with the main purpose being to determine the response from web users using different levels of influence. The obtained results, compared with online responses from an actual campaign, provide the possibility to adopt compromise solutions through designing Internet applications with an expected outcome and minimizing negative responses without interfering with user experience.

AutoElastic: Automatic Resource Elasticity for High Performance Applications in the Cloud

Elasticity is undoubtedly one of the most striking characteristics of cloud computing. Especially in the area of high performance computing (HPC), elasticity can be used to execute irregular and CPU-intensive applications. However, the on- the-fly increase/decrease in resources is more widespread in Web systems, which have their own IaaS-level load balancer. Considering the HPC area, current approaches usually focus on batch jobs or assumptions such as previous knowledge of application phases, source code rewriting or the stop-reconfigure-and-go approach for elasticity. In this context, this article presents AutoElastic, a PaaS-level elasticity model for HPC in the cloud. Its differential approach consists of providing elasticity for high performance applications without user intervention or source code modification. The scientific contributions of AutoElastic are twofold: (i) an Aging-based approach to resource allocation and deallocation actions to avoid unnecessary virtual machine (VM) reconfigurations (thrashing) and (ii) asynchronism in creating and terminating VMs in such a way that the application does not need to wait for completing these procedures. The prototype evaluation using OpenNebula middleware showed performance gains of up to 26 percent in the execution time of an application with the AutoElastic manager. Moreover, we obtained low intrusiveness for AutoElastic when reconfigurations do not occur.