Query: Examination of the Correlation Between Internet Addiction and Social Phobia in Adolescents.

Relevant passages:
Relations Among Loneliness, Social Anxiety, and Problematic Internet Use <=SEP=> The model of problematic Internet use advanced and tested in the current study proposes that individuals' psychosocial well-being, along with their beliefs about interpersonal communication (both face-to-face and online) are important cognitive predictors of negative outcomes arising from Internet use. The study examined the extent to which social anxiety explains results previously attributed to loneliness as a predictor of preference for online social interaction and problematic Internet use. The results support the hypothesis that the relationship between loneliness and preference for online social interaction is spurious, and that social anxiety is the confounding variable.

The comorbid psychiatric symptoms of Internet addiction: attention deficit and hyperactivity disorder (ADHD), depression, social phobia, and hostility. <=SEP=> PURPOSE
To: (1) determine the association between Internet addiction and depression, self-reported symptoms of attention deficit and hyperactivity disorder (ADHD), social phobia, and hostility for adolescents; and (2) evaluate the sex differences of association between Internet addiction and the above-mentioned psychiatric symptoms among adolescents.


METHODS
A total of 2114 students (1204 male and 910 female) were recruited for the study. Internet addiction, symptoms of ADHD, depression, social phobia, and hostility were evaluated by the self-report questionnaire.


RESULTS
The results demonstrated that adolescents with Internet addiction had higher ADHD symptoms, depression, social phobia, and hostility. Higher ADHD symptoms, depression, and hostility are associated with Internet addiction in male adolescents, and only higher ADHD symptoms and depression are associated with Internet addiction in female students.


CONCLUSION
These results suggest that Internet addiction is associated with symptoms of ADHD and depressive disorders. However, hostility was associated with Internet addiction only in males. Effective evaluation of, and treatment for ADHD and depressive disorders are required for adolescents with Internet addiction. More attention should be paid to male adolescents with high hostility in intervention of Internet addiction.

Internet Addiction: The Emergence of a New Clinical Disorder <=SEP=> Anecdotal reports indicated that some on-line users were becoming addicted to the Internet in much that same way that others became addicted to drugs or alcohol which resulted in academic, social, and occupational impairment. However, research among sociologists, psychologists, or psychiatrists has not formally identified addictive use of the Internet as a problematic behavior. This study investigated the existence of Internet addiction and the extent of problems caused by such potential misuse. This study utilized an adapted version of the criteria for pathological gambling defined by the DSM-IV (APA, 1994). On the basis of this criteria, case studies of 396 dependent Internet users (Dependents) and a control group of 100 non-dependent Internet users (Non-Dependents) were classified. Qualitative analyses suggests significant behavioral and functional usage differences between the two groups. Clinical and social implications of pathological Internet use and future directions for research are discussed.

Internet addiction in Korean adolescents and its relation to depression and suicidal ideation: a questionnaire survey. <=SEP=> This study examined the relationship of Internet addiction to depression and suicidal ideation in Korean adolescents. The participants were 1573 high-school students living in a city who completed the self-reported measures of the Internet Addiction Scale, the Korean version of the Diagnostic Interview Schedule for Children-Major Depression Disorder-Simple Questionnaire, and the Suicidal Ideation Questionnaire-Junior. A correlational survey design was employed. Among the samples, 1.6% was diagnosed as Internet addicts, while 38.0% was classified as possible Internet addicts. The prevalence of Internet addiction did not vary with gender. The levels of depression and suicide ideation were highest in the Internet-addicts group. Future studies should investigate the direct relationship between psychological health problems and Internet dependency.

Internet addiction among Chinese adolescents: prevalence and psychological features. <=SEP=> BACKGROUND
To investigate the prevalence of Internet addiction among Chinese adolescents and to explore the psychological features associated with Internet addiction.


METHODS
A total of 2620 high school students from four high schools in Changsha City were surveyed using Diagnostic Questionnaire for Internet Addiction (YDQ), Eysenck Personality Questionnaire (the edition for children, EPQ), Time Management Disposition Scale (TMDS) and Strengths and Difficulties Questionnaire (SDQ). The mean age of whole sample was 15.19 years (ranging from 12 years to 18 years). According to the modified YDQ criteria by Beard, 64 students who were diagnosed as Internet addiction (the mean age: 14.59 years) and 64 who were diagnosed as being normal in Internet usage (the mean age: 14.81 years) were included in a case-control study.


RESULTS
The rate of Internet use among the surveyed adolescents was 88%, among which the incidence rate of Internet addiction was 2.4%. The Internet addiction group had significantly higher scores on the EPQ subscales of neuroticism, psychoticism, and lie than the control group (P < 0.05). The Internet addiction group scored lower than the control group on the TMDS subscales of sense of control over time, sense of value of time, and sense of time efficacy (P < 0.05). Compared with the control group, the Internet addiction group had also significantly higher scores on the SDQ subscales of emotional symptoms, conduct problems, hyperactivity, total difficulties and lower scores on the subscale of prosocial behaviours (P < 0.05).


CONCLUSIONS
The present study suggests that Internet addiction is not rare among Chinese adolescents. In addition, adolescents with Internet addiction possess different psychological features when compared with those who use the Internet less frequently.

Hardware resource estimation for heterogeneous FPGA-based SoCs <=SEP=> The increasing complexity of recent System-on-Chip (SoC) designs introduces new challenges for design space exploration tools. In addition to the time-to-market challenge, designers need to estimate rapidly and accurately both performance and area occupation of complex and diverse applications. High-Level Synthesis (HLS) has been emerged as an attractive solution for designers to address these challenges in order to explore a large number of SoC configurations. In this paper, we target hybrid CPU-FPGA based SoCs. We propose a high-level area estimation tool based on an analytic model without requiring register-transfer level (RTL) implementations. This technique allows to estimate the required FPGA resources at the source code level to map an application to a hybrid CPU-FPGA system. The proposed model also enables a fast design exploration with different trade-offs through HLS optimization pragmas. Experimental results show that the proposed area analytic model provides an accurate estimation with a negligible error (less than 5+) compared to RTL implementations.

No double-dissociation between optic ataxia and visual agnosia: Multiple sub-streams for multiple visuo-manual integrations <=SEP=> The current dominant view of the visual system is marked by the functional and anatomical dissociation between a ventral stream specialised for perception and a dorsal stream specialised for action. The "double-dissociation" between visual agnosia (VA), a deficit of visual recognition, and optic ataxia (OA), a deficit of visuo-manual guidance, considered as consecutive to ventral and dorsal damage, respectively, has provided the main argument for this dichotomic view. In the first part of this paper, we show that the currently available empirical data do not suffice to support a double-dissociation between OA and VA. In the second part, we review evidence coming from human neuropsychology and monkey data, which cast further doubts on the validity of a simple double-dissociation between perception and action because they argue for a far more complex organisation with multiple parallel visual-to-motor connections: 1. A dorso-dorsal pathway (involving the most dorsal part of the parietal and pre-motor cortices): for immediate visuo-motor control--with OA as typical disturbance. The latest research about OA is reviewed, showing how these patients exhibit deficits restricted to the most direct and fast visuo-motor transformations. We also propose that mild mirror ataxia, consisting of misreaching errors when the controlesional hand is guided to a visual goal though a mirror, could correspond to OA with an isolated "hand effect". 2. A ventral stream-prefrontal pathway (connections from the ventral visual stream to pre-frontal areas, by-passing the parietal areas): for "mediate" control (involving spatial or temporal transpositions [Rossetti, Y., & Pisella, L. (2003). Mediate responses as direct evidence for intention: Neuropsychology of Not to-, Not now- and Not there-tasks. In S. Johnson (Ed.), Cognitive Neuroscience perspectives on the problem of intentional action (pp. 67-105). MIT Press.])--with VA as typical disturbance. Preserved visuo-manual guidance in patients with VA is restricted to immediate goal-directed guidance, they exhibit deficits for delayed or pantomimed actions. 3. A ventro-dorsal pathway (involving the more ventral part of the parietal lobe and the pre-motor and pre-frontal areas): for complex planning and programming relying on high representational levels with a more bilateral organisation or an hemispheric lateralisation--with mirror apraxia, limb apraxia and spatial neglect as representatives. Mirror apraxia is a deficit that affects both hands after unilateral inferior parietal lesion with the patients reaching systematically and repeatedly toward the virtual image in the mirror. Limb apraxia is localized on a more advanced conceptual level of object-related actions and results from deficient integrative, computational and "working memory" capacities of the left inferior parietal lobule. A component of spatial working memory has recently been revealed also in spatial neglect consecutive to lesion involving the network of the right inferior parietal lobule and the right frontal areas. We conclude by pointing to the differential temporal constraints and integrative capabilities of these parallel visuo-motor pathways as keys to interpret the neuropsychological deficits.

Mechanisms of decompensation and organ failure in cirrhosis: From peripheral arterial vasodilation to systemic inflammation hypothesis. <=SEP=> The peripheral arterial vasodilation hypothesis has been most influential in the field of cirrhosis and its complications. It has given rise to hundreds of pathophysiological studies in experimental and human cirrhosis and is the theoretical basis of life-saving treatments. It is undisputed that splanchnic arterial vasodilation contributes to portal hypertension and is the basis for manifestations such as ascites and hepatorenal syndrome, but the body of research generated by the hypothesis has revealed gaps in the original pathophysiological interpretation of these complications. The expansion of our knowledge on the mechanisms regulating vascular tone, inflammation and the host-microbiota interaction require a broader approach to advanced cirrhosis encompassing the whole spectrum of its manifestations. Indeed, multiorgan dysfunction and failure likely result from a complex interplay where the systemic spread of bacterial products represents the primary event. The consequent activation of the host innate immune response triggers endothelial molecular mechanisms responsible for arterial vasodilation, and also jeopardizes organ integrity with a storm of pro-inflammatory cytokines and reactive oxygen and nitrogen species. Thus, the picture of advanced cirrhosis could be seen as the result of an inflammatory syndrome in contradiction with a simple hemodynamic disturbance.

Single Image Shadow Removal via Neighbor-Based Region Relighting <=SEP=> In this paper we present a novel method for shadow removal in single images. For each shadow region we use a trained classifier to identify a neighboring lit region of the same material. Given a pair of lit-shadow regions we perform a region relighting transformation based on histogram matching of luminance values between the shadow region and the lit region. Then, we adjust the CIELAB a and b channels of the shadow region by adding constant offsets based on the difference of the median shadow and lit pixel values. We demonstrate that our approach produces results that outperform the state of the art by evaluating our method using a publicly available benchmark dataset.

Electric grid state estimators for distribution systems with microgrids <=SEP=> In the development of smart grid, state estimation in distribution systems will likely face more challenges than that at the transmission level. This paper addresses one of such challenges, namely, the absence of topology information, by developing a forecast-aided topology change detection method and an event-triggered recursive Bayesian estimator to identify the correct topology. Simulation studies with microgrid induced changes are presented to illustrate the effectiveness of the proposed algorithm.

Thumb Motor Performance Varies by Movement Orientation, Direction, and Device Size During Single-Handed Mobile Phone Use <=SEP=> OBJECTIVE
The aim of this study was to determine if thumb motor performance metrics varied by movement orientation, direction, and device size during single-handed use of a mobile phone device.


BACKGROUND
With the increased use of mobile phones, understanding how design factors affect and improve performance can provide better design guidelines.


METHOD
A repeated measures laboratory experiment of 20 right-handed participants measured the thumb tip's 3-D position relative to a phone during reciprocal tapping tasks across four phone designs and four thumb tip movement orientations. Each movement orientation included two movement directions: an "outward" direction consisting in CMC (carpometacarpal) joint flexion or abduction movements and an "inward" direction consisting in CMC joint extension or adduction movements. Calculated metrics of the thumb's motor performance were Fitts' effective width and index of performance.


RESULTS
Index of performance varied significantly across phones, with performance being generally better for the smaller devices. Performance was also significantly higher for adduction-abduction movement orientations compared to flexion-extension, and for "outward" compared to "inward" movement directions.


CONCLUSION
For single-handed device use, adduction-abduction-type movements on smaller phones lead to better thumb performance.


APPLICATION
The results from this study can be used to design new mobile phone devices and keypad interfaces that optimize specific thumb motions to improve the user-interface experience during single-handed use.

Elliptic Curve Cryptosystems <=SEP=> The application of elliptic curves to the field of cryptography has been relatively recent. It has opened up a wealth of possibilities in terms of security, encryption, and real-world applications. In particular, we are interested in public-key cryptosystems that use the elliptic curve discrete logarithm problem to establish security. The objective of this thesis is to assemble the most important facts and findings into a broad, unified overview of this field. To illustrate certain points, we also discuss a sample implementation of the elliptic curve analogue of the El

Electronic Payments of Small Amounts <=SEP=> This note considers the application of electronic cash to transactions in which many small amounts must be paid to the same payee and in which it is not possible to just pay the total amount afterwards. The most notable example of such a transaction is payment for phone calls. If currently published electronic cash systems are used and a full payment protocol is executed for each of the small amounts, the overall complexity of the system will be prohibitively large (time, storage and communication). This note describes how such payments can be handled in a wide class of payment systems. The solution is very easy to adapt as it only in uences the payment and deposit transactions involving such payments. Furthermore, making and verifying each small payment requires very little computation and communication, and the total complexity of both transactions is comparable to that of a payment of a xed amount.

A 25-kHz 3rd-order continuous-time Delta-Sigma modulator using tri-level quantizer <=SEP=> This paper presents a 3rd order continuous-time Delta-Sigma modulator with a tri-level quantizer, which provides 3-dB reduction of quantization noise without dynamic element matching (DEM). The tri-level DAC linearity is analyzed and it shows that a highly linear tri-level DAC can be realized in fully-differential active-RC Delta-Sigma modulator. The performance of the tri-level continuous-time Delta-Sigma modulator has been verified through simulations using a standard 0.18-μm CMOS process. It achieves 81-dB SNDR at 3.2-MS/s sampling rate and consumes 1.14-μW power with ideal amplifier.

Finding a Maximum Clique using Ant Colony Optimization and Particle Swarm Optimization in Social Networks <=SEP=> Interaction between users in online social networks plays a key role in social network analysis. One on important types of social group is full connected relation between some users, which known as clique structure. Therefore finding a maximum clique is essential for some analysis. In this paper, we proposed a new method using ant colony optimization algorithm and particle swarm optimization algorithm. In the proposed method, in order to attain better results, it is improved process of pheromone update by particle swarm optimization. Simulation results on popular standard social network benchmarks in comparison standard ant colony optimization algorithm are shown a relative enhancement of proposed algorithm. Keywordssocial network analysis; clique problem; ACO; PSO.

Surgical Management of Hidradenitis Suppurativa: Outcomes of 590 Consecutive Patients. <=SEP=> BACKGROUND
Hidradenitis suppurativa is a progressive, recurrent inflammatory disease. Surgical management is potentially curative with limited efficacy data.


OBJECTIVE
To evaluate hidradenitis surgical patients.


METHODS
Retrospective review of outcomes of 590 consecutive surgically treated patients.


RESULTS
Most patients were white (91.0% [435/478]), men (337 [57.1%]), smokers (57.7% [297/515]) with Hurley Stage III disease (476 [80.7%]). Procedure types were excision (405 [68.6%]), unroofing (168 [28.5%]), and drainage (17 [2.9%]) treating disease of perianal/perineum (294 [49.8%]), axilla (124 [21.0%]), gluteal cleft (76 [12.9%]), inframammary (12 [2.0%]), and multiple surgical sites (84 [14.2%]). Postoperative complications occurred in 15 patients (2.5%) and one-fourth (144 [24.4%]) suffered postoperative recurrence, which necessitated reoperation in one-tenth (69 [11.7%]) of patients. Recurrence risk was increased by younger age (hazard ratio [HR], 0.8; 95% confidence interval [CI], 0.7-0.9), multiple surgical sites (HR, 1.6; 95% CI, 1.1-2.5), and drainage-type procedures (HR, 3.5; 95% CI, 1.2-10.7). Operative location, disease severity, gender, and operative extent did not influence recurrence rate.


CONCLUSION
Excision and unroofing procedures were effective treatments with infrequent complications and low recurrence rates. Well-planned surgical treatment aiming to remove or unroof the area of intractable hidradenitis suppurativa was highly effective in the management of this challenging disease.

Analysis of Massive MIMO-Enabled Downlink Wireless Backhauling for Full-Duplex Small Cells <=SEP=> Recent advancements in self-interference (SI) cancellation capability of low-power wireless devices motivate in-band full-duplex (FD) wireless backhauling in small cell networks (SCNs). In-band FD wireless backhauling concurrently allows the use of the same frequency spectrum for the backhaul as well as access links of the small cells. In this paper, using tools from stochastic geometry, we develop a framework to model the downlink rate coverage probability of a user in a given SCN with massive multiple-input-multiple-output (MIMO)-enabled wireless backhauls. The considered SCN is composed of a mixture of small cells that are configured in either in-band or out-of-band backhaul modes with a certain probability. The performance of the user in the considered hierarchical network is limited by several sources of interference, such as the backhaul interference, small cell base station (SBS)-to-SBS interference, and the SI. Moreover, due to the channel hardening effect in massive MIMO, the backhaul links only experience long term channel effects, whereas the access links experience both the long term and the short term channel effects. Consequently, the developed framework is flexible to characterize different sources of interference while capturing the heterogeneity of the access and backhaul channels. In specific scenarios, the framework enables deriving closed-form coverage probability expressions. Under perfect backhaul coverage, the simplified expressions are utilized to optimize the proportion of in-band and out-of-band small cells in the SCN in the closed form. Finally, a few remedial solutions are proposed that can potentially mitigate the backhaul interference and in turn improve the performance of in-band FD wireless backhauling. Numerical results investigate the scenarios in which in-band wireless backhauling is useful and demonstrate that maintaining a correct proportion of in-band and out-of-band FD small cells is crucial in wireless backhauled SCNs.

Applications of Trajectory Data in Transportation: Literature Review and Maryland Case Study <=SEP=> This paper considers applications of trajectory data in transportation, and makes two primary contributions. First, it provides a comprehensive literature review detailing ways in which trajectory data has been used for transportation systems analysis, distilling existing research into the following six areas: demand estimation, modeling human behavior, designing public transit, measuring and predicting traffic performance, quantifying environmental impact, and safety analysis. Additionally, it presents innovative applications of trajectory data for the state of Maryland, employing visualization and machine learning techniques to extract value from 20 million GPS traces. These visual analytics will be implemented in the Regional Integrated Transportation Information System (RITIS), which provides free data sharing and visual analytics tools to help transportation agencies attain situational awareness, evaluate performance, and share insights with the public.

Smart Health Care: An Edge-Side Computing Perspective <=SEP=> Increasing health awareness and rapid technological advancements have resulted in significant growth in an emerging sector: smart health care. By the end of 2020, the total number of smart health-care devices is expected to reach 808.9 million (646 million devices without wearables and the remaining with wearables) [1], [2]. This proliferation of devices is expected to revolutionize health care by speeding up treatment and diagnostic processes, decreasing physician visit costs, and enhancing patient care quality.

Hand segmentation for hand-object interaction from depth map <=SEP=> Hand segmentation for hand-object interaction is a necessary preprocessing step in many applications such as augmented reality, medical application, and human-robot interaction. However, typical methods are based on color information which is not robust to objects with skin color, skin pigment difference, and light condition variations. Thus, we propose hand segmentation method for hand-object interaction using only a depth map. It is challenging because of the small depth difference between a hand and objects during an interaction. To overcome this challenge, we propose the two-stage random decision forest (RDF) method consisting of detecting hands and segmenting hands. To validate the proposed method, we demonstrate results on the publicly available dataset of hand segmentation for hand-object interaction. The proposed method achieves high accuracy in short processing time comparing to the other state-of-the-art methods.

Finding News Citations for Wikipedia <=SEP=> An important editing policy in Wikipedia is to provide citations for added statements in Wikipedia pages, where statements can be arbitrary pieces of text, ranging from a sentence to a paragraph. In many cases citations are either outdated or missing altogether.
 In this work we address the problem of finding and updating news citations for statements in entity pages. We propose a two-stage supervised approach for this problem. In the first step, we construct a classifier to find out whether statements need a news citation or other kinds of citations (web, book, journal, etc.). In the second step, we develop a news citation algorithm for Wikipedia statements, which recommends appropriate citations from a given news collection. Apart from IR techniques that use the statement to query the news collection, we also formalize three properties of an appropriate citation, namely: (i) the citation should entail the Wikipedia statement, (ii) the statement should be central to the citation, and (iii) the citation should be from an authoritative source.
 We perform an extensive evaluation of both steps, using 20 million articles from a real-world news collection. Our results are quite promising, and show that we can perform this task with high precision and at scale.

A Modular Framework for Versatile Conversational Agent Building <=SEP=> This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible.

ERP integration in a healthcare environment: a case study <=SEP=> 

Evaluating the influence of YouTube advertising for attraction of young customers <=SEP=> Nowadays, we have been faced with an increasing number of people who are spending tremendous amounts of time all around the world on YouTube. To date, the factors that persuade customers to accept YouTube advertising as an advertising medium are not yet fully understood. The present paper identified four dimensions towards YouTube advertising (i.e., entertainment, Informativeness, Customization and irritation) which may be affected on advertising value as well as brand awareness, and accordingly on purchase intention of consumers. The conceptual model hypothesizes that ad value strategies are positively associated with brand awareness, which in turn influence perceived usefulness of You Tube and continued purchase behavior. For this study, data were collected from students studying at the Sapienza University of Rome. In total, 315 usable questionnaires were chosen in order to analysis of data for the variables. The results show that entertainment, informativeness and customization are the strongest positive drivers, while irritation is negatively related to YouTube advertising. On the other hand, advertising value through YouTube affects both brand awareness and purchase intention of con-

Embedding new data points for manifold learning via coordinate propagation <=SEP=> In recent years, a series of manifold learning algorithms have been proposed for nonlinear dimensionality reduction. Most of them can run in a batch mode for a set of given data points, but lack a mechanism to deal with new data points. Here we propose an extension approach, i.e., mapping new data points into the previously learned manifold. The core idea of our approach is to propagate the known coordinates to each of the new data points. We first formulate this task as a quadratic programming, and then develop an iterative algorithm for coordinate propagation. Tangent space projection and smooth splines are used to yield an initial coordinate for each new data point, according to their local geometrical relations. Experimental results and applications to camera direction estimation and face pose estimation illustrate the validity of our approach.

Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approach <=SEP=> We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using “convolution” and “deconvolution” networks to achieve the conventional “coarse recognition” and “fine extraction” functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.

Preserving the Archival Bond in Distributed Ledgers: A Data Model and Syntax <=SEP=> Distributed cryptographic ledgers, such as the blockchain, are now being used in recordkeeping. However, they lack a key feature of more traditional recordkeeping systems needed to establish the authenticity of records and enable reliance on them for trustworthy recordkeeping. The missing feature is known in archival science as the archival bond – the mutual relationship that exists among documents by virtue of the actions in which they participate. In this paper, we propose a novel data model and syntax using core web principles that can be used to address this shortcoming in distributed ledgers as recordkeeping systems.

Fast and accurate scan registration through minimization of the distance between compact 3D NDT representations <=SEP=> Registration of range sensor measurements is an important task in mobile robotics and has received a lot of attention. Several iterative optimization schemes have been proposed in order to align three-dimensional (3D) point scans. With the more widespread use of high-frame-rate 3D sensors and increasingly more challenging application scenarios for mobile robots, there is a need for fast and accurate registration methods that current state-of-the-art algorithms cannot always meet. This work proposes a novel algorithm that achieves accurate point cloud registration an order of a magnitude faster than the current state of the art. The speedup is achieved through the use of a compact spatial representation: the Three-Dimensional Normal Distributions Transform (3D-NDT). In addition, a fast, global-descriptor based on the 3D-NDT is defined and used to achieve reliable initial poses for the iterative algorithm. Finally, a closed-form expression for the covariance of the proposed method is also derived. The proposed algorithms are evaluated on two standard point cloud data sets, resulting in stable performance on a par with or better than the state of the art. The implementation is available as an open-source package for the Robot Operating System (ROS).

Optimized Spatial Hashing for Collision Detection of Deformable Objects <=SEP=> We propose a new approach to collision and self– collision detection of dynamically deforming objects that consist of tetrahedrons. Tetrahedral meshes are commonly used to represent volumetric deformable models and the presented algorithm is integrated in a physically–based environment, which can be used in game engines and surgical simulators. The proposed algorithm employs a hash function for compressing a potentially infinite regular spatial grid. Although the hash function does not always provide a unique mapping of grid cells, it can be generated very efficiently and does not require complex data structures, such as octrees or BSPs. We have investigated and optimized the parameters of the collision detection algorithm, such as hash function, hash table size and spatial cell size. The algorithm can detect collisions and self– collisions in environments of up to 20k tetrahedrons in real–time. Although the algorithm works with tetrahedral meshes, it can be easily adapted to other object primitives, such as triangles. Figure 1: Environment with dynamically deforming objects, that consist of tetrahedrons.

Effects of cognitive-behavioral therapy on brain activation in specific phobia <=SEP=> Little is known about the effects of successful psychotherapy on brain function in subjects with anxiety disorders. The present study aimed to identify changes in brain activation following cognitive-behavioral therapy (CBT) in subjects suffering from specific phobia. Using functional magnetic resonance imaging (fMRI), brain activation to spider videos was measured in 28 spider phobic and 14 healthy control subjects. Phobics were randomly assigned to a therapy-group (TG) and a waiting-list control group (WG). Both groups of phobics were scanned twice. Between scanning sessions, CBT was given to the TG. Before therapy, brain activation did not differ between both groups of phobics. As compared to control subjects, phobics showed greater responses to spider vs. control videos in the insula and anterior cingulate cortex (ACC). CBT strongly reduced phobic symptoms in the TG while the WG remained behaviorally unchanged. In the second scanning session, a significant reduction of hyperactivity in the insula and ACC was found in the TG compared to the WG. These results propose that increased activation in the insula and ACC is associated with specific phobia, whereas an attenuation of these brain responses correlates with successful therapeutic intervention.