Miracle-dz/UniFAR-FTUs huggingface dataset:
A Controlled Clinical Comparison of Attention Performance in Children with ADHD in a Virtual Reality Classroom Compared to Standard Neuropsychological Methods

In this initial pilot study, a controlled clinical comparison was made of attention perforance in children with attention deficit-hyperactivity disorder (ADHD) in a virtual reality (VR) classroom. Ten boys diagnosed with ADHD and ten normal control boys participated in the study. Groups did not significantly differ in mean age, grade level, ethnicity, or handedness. No participants reported simulator sickness following VR exposure. Children with ADHD exhibited more omission errors, commission errors, and overall body movement than normal control children in the VR classroom. Children with ADHD were more impacted by distraction in the VR classroom. VR classroom measures were correlated with traditional ADHD assessment tools and the flatscreen CPT. Of note, the small sample size incorporated in each group and higher WISC-III scores of normal controls might have some bearing on the overall interpretation of results. These data suggested that the Virtual Classroom had good potential for controlled performance assessment within an ecologically valid environment and appeared to parse out significant effects due to the presence of distraction stimuli.
Mining human behavior for health promotion

The monitoring of human lifestyles has gained much attention in the recent years. This work presents a novel approach to combine multiple context-awareness technologies for the automatic analysis of people's conduct in a comprehensive and holistic manner. Activity recognition, emotion recognition, location detection, and social analysis techniques are integrated with ontological mechanisms as part of a framework to identify human behavior. Key architectural components, methods and evidences are described in this paper to illustrate the interest of the proposed approach.
Expanding the experience of using non-stationary waterflooding technology with changing direction of the filtration flow in the example of the Northern Buzachi field

The last few years, work has been carried out to study the effectiveness of non-stationary exposure in the highly viscous oil field Northern Buzachi (Republic of Kazakhstan). It has been proved that this technology is quite effective in the development of highly viscous oil reservoirs, however, in order to constantly maintain high technological effect, a constant modification of this technology is required, since it has a characteristic feature of rapid «aging». Further search for the conditions of effective application of nonstationary exposure on highly-viscous oil deposits can be carried out in two directions: the implementation of non-stationary exposure in new areas with other reservoir parameters and the change in the parameters of non-stationary exposure technology (including combining with other technologies) in areas where this technology is already in use. Both approaches are used on the Northern Buzachi field. Thus, the positive experience of using non-stationary waterflooding in combination with changing direction of the filtration flow in the section of the seventh block of the Northern Buzachi field allowed us to recommend new sites for the implementation of this technology. With the participation of the author of this work, a non-stationary waterflooding program was developed and implemented on the site of the sixth block (south) of the first operational facility.
Accurate and Fast Proximity Queries Between Polyhedra Using Convex Surface Decomposition

The need to perform fast and accurate proximity queries arises frequently in physically‐based modeling, simulation, animation, real‐time interaction within a virtual environment, and game dynamics. The set of proximity queries include intersection detection, tolerance verification, exact and approximate minimum distance computation, and (disjoint) contact determination. Specialized data structures and algorithms have often been designed to perform each type of query separately. We present a unified approach to perform any of these queries seamlessly for general, rigid polyhedral objects with boundary representations which are orientable 2‐manifolds. The proposed method involves a hierarchical data structure built upon a surface decomposition of the models. Furthermore, the incremental query algorithm takes advantage of coherence between successive frames. It has been applied to complex benchmarks and compares very favorably with earlier algorithms and systems.
An Acknowledgment-Based Approach for the Detection of Routing Misbehavior in MANETs

We study routing misbehavior in MANETs (mobile ad hoc networks) in this paper. In general, routing protocols for MANETs are designed based on the assumption that all participating nodes are fully cooperative. However, due to the open structure and scarcely available battery-based energy, node misbehaviors may exist. One such routing misbehavior is that some selfish nodes will participate in the route discovery and maintenance processes but refuse to forward data packets. In this paper, we propose the 2ACK scheme that serves as an add-on technique for routing schemes to detect routing misbehavior and to mitigate their adverse effect. The main idea of the 2ACK scheme is to send two-hop acknowledgment packets in the opposite direction of the routing path. In order to reduce additional routing overhead, only a fraction of the received data packets are acknowledged in the 2ACK scheme. Analytical and simulation results are presented to evaluate the performance of the proposed scheme
A novel hidden danger prediction method in cloud-based intelligent industrial production management using timeliness managing extreme learning machine

To prevent possible accidents, the study of data-driven analytics to predict hidden dangers in cloud service-based intelligent industrial production management has been the subject of increasing interest recently. A machine learning algorithm that uses timeliness managing extreme learning machine is utilized in this article to achieve the above prediction. Compared with traditional learning algorithms, extreme learning machine (ELM) exhibits high performance because of its unique feature of a high generalization capability at a fast learning speed. Timeliness managing ELM is proposed by incorporating timeliness management scheme into ELM. When using the timeliness managing ELM scheme to predict hidden dangers, newly incremental data could be added prior to the historical data to maximize the contribution of the newly incremental training data, because the incremental data may be able to contribute reasonable weights to represent the current production situation according to practical analysis of accidents in some industrial productions. Experimental results from a coal mine show that the use of timeliness managing ELM can improve the prediction accuracy of hidden dangers with better stability compared with other similar machine learning methods.
Do ‘Auditory Processing’ Tests Measure Auditory Processing in the Elderly?

Objective: To examine the associations between measures of auditory processing and measures of auditory or cognitive function in elderly listeners with impaired hearing. Design: Multiple measures of auditory processing, auditory function, and cognitive function were obtained and linear, multiple-regression analyses were conducted to examine the relations between these sets of variables. In particular, four measures of auditory processing were obtained from each of 213 elderly participants. Measures of auditory processing included duration discrimination for a 1000-Hz pure tone, temporal-order discrimination for mid-frequency pure tones, dichotic syllable identification, and recognition of 45% time-compressed monosyllables. Each participant also completed additional measures of auditory function, including pure-tone thresholds, auditory brain stem responses for each ear and at two presentation rates (11.1 and 71.1 clicks per second), and performance-intensity functions for monosyllabic words (PI-PB rollover). Finally, three measures of cognitive function, all from the Wechsler Adult Intelligence Scale-Revised, were obtained from the 213 participants. Results: For three of the four measures of auditory processing examined in this study (duration discrimination, temporal-order discrimination, and dichotic CV identification), a measure of cognitive function (IQ) and age were the two primary predictors of individual differences in performance. For these three measures of auditory processing, 11 to 14% of the total variance could be accounted for by the predictor variables. For the remaining measure of auditory processing (recognition of time-compressed monosyllables), 56% of the total variance could be accounted for by a set of four predictor variables, but most of this variance (54% of the total variance) was associated with individual differences in hearing loss. When hearing loss was removed as a predictor for this measure of auditory processing, 14% of the total variance was explained by four variables: age, IQ, and two measures derived from auditory brain stem response wave-V latency. Conclusions: Performance on the battery of auditory processing measures by elderly hearing-impaired listeners was systematically related to individual differences in cognitive function rather than auditory function, especially for stimuli not affected by peripheral hearing loss. However, much of the variance in auditory processing performance remained unaccounted for by any of the predictor variables examined in this study.
TB2F: Tree-bitmap and bloom-filter for a scalable and efficient name lookup in Content-Centric Networking

Content-Centric Networking (CCN) is an entirely novel networking paradigm, in which packet forwarding relies upon lookup operations on content names directly instead of fixed-length host addresses. The unique features of CCN names, i.e., variable length, huge cardinality, and hierarchical structure, introduce new challenges that could hinder the deployment of such a new architecture at the Internet scale. In this paper, we make an in-depth study of characteristics of large-scale CCN names, and propose a simple yet efficient CCN-customized name lookup engine (named by TB2F), which capitalizes the strengths of Tree-Bitmap (TB) and Bloom-Filter (BF) mechanisms, while counteracts their main limitations. To this end, TB2F splits CCN prefix into a constant size T-segment and a variable length B-segment with a relative short length, which are treated using TB and BF, respectively. Furthermore, an optimal length of the T-segment is found to improve the lookup efficiency. Experimental comparisons with respect to the reference Name Prefix-Trie and Bloom-Hash have been also carried out. The results show that TB2 F properly configured has good scalability and efficiency by (i) speeding up lookup operations and reducing the false positive rate with respect to Bloom-Hash; (ii) requiring less memory than Name Prefix-Trie; (iii) achieving a low overhead in updating operations in the large scale case.
Dealing with family relationships in linked data

Many web resources require an accurate representation of family relationships. However, available ontologies describing this kind of relationships provide only simple and rudimentary representations. In addition, the transition from one culture/language to another cannot be solved with simple translation solutions, specifically when concepts do not intersect in different cultures. In this paper, we propose a new ontology, called PersonLink, that defines rigorously and precisely different family relationships, and takes into account the differences that may exist between cultures and new relationships emerging in our societies nowadays. It provides a solution based on multicultural meta-ontology of concepts and associated mechanisms. Moreover, rules are provided to infer new links and/or check inconsistencies in the inputs. The PersonLink ontology has been applied, first, in the context of the CAPTAIN MEMO memory prosthesis (for modeling, storing, and reasoning on “family relationships” links), and then, in the context of the two large scale real-world datasets, Freebase and DBpedia.
Early detection of radiation-induced structural changes in rat trabecular bone.

OBJECTIVE Early detection of bone changes following radiotherapy is very important. The aim of this study is to establish a radiographic image analysis method for early detection of radiation-induced trabecular bone changes. METHODS Thirty-five Wistar rats were used for the experimental model of trabecular bone changes, which were induced by X-ray irradiation with 30 Gy to develop simulated osteomyelitis. Standardized 2.2 x direct magnification radiography was performed immediately prior to X-ray irradiation and once a week for 4 weeks following irradiation. The latent X-ray images were scanned using a computed radiography (CR) system. Mathematical morphological processing was then applied to the CR image data, which allowed the bone trabecular pattern features to be extracted as skeletal binary images. The sensitivity and specificity for detecting early trabecular bone changes in CR images and in skeletal binary images were evaluated. Quantitative analyses with quantum level value (QL value), skeletal pixel percentage (SKP) and star volume analysis (skeletal volume (Vsk), skeletal space volume (Vsp)) were performed. Histopathological examination was also conducted for confirmation of physical changes in the bone. RESULTS Visual observation of the skeletal binary images provided a higher sensitivity than the CR images. In the quantitative analysis, SKP, Vsk and Vsp values provided higher sensitivity than QL values. CONCLUSION The results of the present study suggest that a combined radiographic image analysis method using CR, mathematical morphological processing, SKP, Vsk and Vsp can be useful for the early detection of radiation-induced trabecular bone changes.
Method For Dynamic Monitoring Processing Machine

We developed a method for dynamic detection methods used in the machining process to assess the status of machine tool spindles by using Smart Tool Holder. The prevailing sensor systems were installed on processing machines. Using the mobility of intelligent cutting tools and their data-gathering capabilities, we created a predictive model to identify spindle abnormalities, thereby establishing a set of models for the machine.
Systematic MDS erasure codes based on Vandermonde matrices

An increasing number of applications in computer communications uses erasure codes to cope with packet losses. Systematic maximum-distance separable (MDS) codes are often the best adapted codes. This letter introduces new systematic MDS erasure codes constructed from two Vandermonde matrices. These codes have lower coding and decoding complexities than the others systematic MDS erasure codes.
How to stop under-utilization and love multicores

Hardware trends oblige software to overcome three major challenges against systems scalability: (1) taking advantage of the implicit/vertical parallelism within a core that is enabled through the aggressive micro-architectural features, (2) exploiting the explicit/horizontal parallelism provided by multicores, and (3) achieving predictively efficient execution despite the variability in communication latencies among cores on multisocket multicores. In this three hour tutorial, we shed light on the above three challenges and survey recent proposals to alleviate them. The first part of the tutorial describes the instruction- and data-level parallelism opportunities in a core coming from the hardware and software side. In addition, it examines the sources of under-utilization in a modern processor and presents insights and hardware/software techniques to better exploit the micro-architectural resources of a processor by improving cache locality at the right level of the memory hierarchy. The second part focuses on the scalability bottlenecks of database applications at the level of multicore and multisocket multicore architectures. It first presents a systematic way of eliminating such bottlenecks in online transaction processing workloads, which is based on minimizing unbounded communication, and shows several techniques that minimize bottlenecks in major components of database management systems. Then, it demonstrates the data and work sharing opportunities for analytical workloads, and reviews advanced scheduling mechanisms that are aware of non-uniform memory accesses and alleviate bandwidth saturation.
Safety and Immunogenicity of an Oral Inactivated Whole-Cell Pseudomonas aeruginosa Vaccine Administered to Healthy Human Subjects

ABSTRACT This study examines the safety and immunogenicity of an oral, whole-cell Pseudomonas aeruginosa vaccine administered to healthy volunteers. Thirty subjects received an oral dose of Pseudostat in two timed, measured doses with serological follow-up to 56 days postvaccination. Following vaccination, several individuals were identified as antibody responders for all three immunoglobulin (Ig) isotypes tested, specifically against whole-cell P. aeruginosa extract and outer membrane proteins F and I. The mean pooled lipopolysaccharide antigen-specific IgA showed the most significant and constant increases in titer postdose, with a similar increase in titer for whole-cell P. aeruginosa extract-specific IgA. The results demonstrated an increased phagocytic ability of the selected macrophage cell line in post vaccination sera. Furthermore a significant increase in intracellular macrophage killing of opsonized P. aeruginosa was also demonstrated (82% on day 14 postdose) in the presence of the postvaccination sera. The safety component of the study did not show any vaccine-attributable adverse effects in any of the subjects, as documented by clinical evidence, hematology, and biochemistry profiles. We conclude that Pseudostat is safe and immunogenic in humans at this dose and that further studies to determine the appropriate dosage and efficacy are needed. In our study, we have shown that the most significant and sustained responses to oral vaccination in human adult volunteers were serum IgA levels and that pooled sera collected postimmunization have an increased capacity to promote opsonophagocytotic killing of P. aeruginosa.
Clinical Evaluation of Effects of Chronic Resveratrol Supplementation on Cerebrovascular Function, Cognition, Mood, Physical Function and General Well-Being in Postmenopausal Women—Rationale and Study Design

Background: This methodological paper presents both a scientific rationale and a methodological approach for investigating the effects of resveratrol supplementation on mood and cognitive performance in postmenopausal women. Postmenopausal women have an increased risk of cognitive decline and dementia, which may be at least partly due to loss of beneficial effects of estrogen on the cerebrovasculature. We hypothesise that resveratrol, a phytoestrogen, may counteract this risk by enhancing cerebrovascular function and improving regional blood flow in response to cognitive demands. A clinical trial was designed to test this hypothesis. Method: Healthy postmenopausal women were recruited to participate in a randomised, double-blind, placebo-controlled (parallel comparison) dietary intervention trial to evaluate the effects of resveratrol supplementation (75 mg twice daily) on cognition, cerebrovascular responsiveness to cognitive tasks and overall well-being. They performed the following tests at baseline and after 14 weeks of supplementation: Rey Auditory Verbal Learning Test, Cambridge Semantic Memory Battery, the Double Span and the Trail Making Task. Cerebrovascular function was assessed simultaneously by monitoring blood flow velocity in the middle cerebral arteries using transcranial Doppler ultrasound. Conclusion: This trial provides a model approach to demonstrate that, by optimising circulatory function in the brain, resveratrol and other vasoactive nutrients may enhance mood and cognition and ameliorate the risk of developing dementia in postmenopausal women and other at-risk populations.
On the causes of lung hyperinflation during bronchoconstriction.

Airway obstruction in asthma and chronic obstructive pulmonary disease (COPD) is often associated with lung hyperinflation. In this review, we examine the mechanisms that may cause functional residual capacity (FRC), residual volume (RV) and total lung capacity (TLC) to increase during acute and chronic airway obstruction. Normally, FRC at rest is determined by the static characteristics of the lung and chest wall. When airways narrow, FRC may be also be determined by dynamic factors. There are data suggesting that expiratory flow limitation during tidal breathing represents the starting trigger for FRC to increase, in order to allow breathing at higher flows. Indeed, the increase in FRC during induced bronchoconstriction in asthma is closely associated with the occurrence of flow limitation, i.e. the achievement of maximum flow during tidal breathing. Conversely, the decrease in FRC following bronchodilatation in COPD is closely associated with flow limitation disappearing or occurring at lower lung volumes. In normal young people, RV is determined by the static characteristics of the chest wall. During bronchoconstriction RV may also be determined by dynamic factors; therefore, changes in flow or airway calibre at low lung volumes may modulate RV during bronchoconstriction. During acutely induced bronchoconstriction, RV achieved with an expiration from TLC is less than with an expiration from tidal breathing, and this effect appears to be linked to the bronchodilator effect of the deep inhalation. The reasons for the increase in TLC during airway narrowing are not clear, but the duration of the bronchoconstriction by itself may play a role.
Robust spoken dialogue systems for consumer products: a concrete application

In this paper, we report the significant results of a fully-imple-mented voice operated dialogue system, and particularly its main component: the Dialogue Manager (DM). Just like for other interfaces, spoken interfaces require a well-conducted design, implying a good analysis of the users’ needs throughout the dialogue. The VODIS project 1 has led to the design and development of a spoken interface for the control of car equipment. Due to the workload caused by the task of driving the vehicle, spoken communication provides a potentially safe and efficient mode of operating the car equipment. To achieve this, we present the main characteristics of the task model specified during the design stage, and show how its specific features related to the spoken communication allowed to implement a robust dialogue.