Miracle-dz/UniFAR-FTUs huggingface dataset:
CounterMap: Towards generic traffic statistics collection and query in Software Defined Network

Traffic statistics are fundamental for many network measurement tasks like heavy hitter identification, traffic matrix estimator, anomaly detection, etc. However, traditional techniques like NetFlow and sFlow only provide coarse-grained statistics due to packet or flow sampling. Even Software Defined Networking (SDN) offers fine-grained traffic statistics collection, most of existing methods focus on specific applications and thus lack generality. To this end, we propose CounterMap, a generic traffic statistics collection and query platform. CounterMap maintains a full map of flow counters by actively polling switches and passively monitoring flow timeouts. For efficient storage and query, CounterMap stores the counters in fast off-the-shelf in-memory data store, and offers a generic SQL-like query language. With the CounterMap language, applications can gain visibility into both existing and historical flows, without querying the dataplane devices themselves. We show how network applications benefit from CounterMap, with higher measurement accuracy and lower dataplane overhead.
Fault tolerant nanoelectronic processor architectures

In this paper we propose a fault-tolerant processor architecture and an associated fault-tolerant computation model capable of fault tolerance in the nanoelectronic environment that is characterized by high and time varying fault rates. The proposed fault tolerant processor architecture not only guarantees the correctness of computation but also is flexible in that it dynamically trades-off computation resources and performance. The core of the architecture is a decentralized instruction control unit called the voter that achieves both fault tolerance and the maximum parallel execution of instructions by exploiting the abundant computational resources provided by nanotechnologies. Although the result of each instruction needs to be confirmed by executing it on multiple computation units, multiple unconfirmed instructions can proceed as speculative branches. The voter implements a hardware-frugal computation unit allocation algorithm to organize the redundant computations and to dynamically control the growth of speculative branches.
Review article Tourette syndrome and obsessive-compulsive disorder q

Tourette syndrome and obsessive–compulsive disorder are neuropsychiatric disorders that have sparked considerable interest over the decades. They are the focus of research for a remarkable diversity of disciplines, ranging from neuroimagers and prenatal epidemiologists to experts in the neural circuits that connect the cortex with the basal ganglia, as well as neuroimmunologists focusing on brain-based autoimmune phenomena. Several hypotheses have been put forward to explain the onset and exacerbation of these illnesses. Here, we discuss the clinical phenomenology and treatment options that are currently available. New psychopharmacological agents are being used that are based on a greater understanding of the neurobiology and are being used in combination with behavioral interventions. Longitudinal clinical investigations into clinical symptoms and the natural course are providing additional clues on the underlying pathophysiology. Recent advances in research models are also reviewed in an attempt to clarify some of the molecular etiologies that lead to these disorders. Published by Elsevier B.V.
Motion-tracking adaptive persistence and adaptive-size median filter for color Doppler processing in ultrasound systems on multicore platform

Color Doppler processing in the ultrasound imaging systems is mainly used to observe the blood flow in the region of interest. The desired blood signal will be greatly affected by the speckle noises, and the major design issues are to eliminate these kinds of noises effectively. In this work, we propose the time-domain (1) motion-tracking adaptive persistence and spatial-domain (2) adaptive-size median filter for effectively eliminating the speckle noises, respectively. The proposed two filters have individually 2~3 dB better performance than the referenced algorithms, and the proposed adaptive de-speckle filters can also work together in the same system to obtain even better performances. At last, the proposed signal-processing algorithms are implemented on the multi-core platform, and the property of parallel processing significantly accelerates the computation.
The Intergenerational Consequences of Mass Incarceration: Implications for Children's Contact with Grandparents

In response to the rapid growth in mass incarceration, a burgeoning literature documents the mostly deleterious consequences of mass incarceration for individuals and families. But mass incarceration, which has profoundly altered the American kinship system, may also have implications for relationships that span across generations. In this paper, I use data from the Fragile Families and Child Wellbeing Study to examine how paternal incarceration has altered one important aspect of intergenerational relationships, children's contact with grandparents. Results from both ordinary least squares (OLS) and fixed-effects regression models show that incarceration decreases the frequency of children? s contact with paternal, but not maternal, grandparents. More than one-quarter of this negative relationship is explained by separation between parents that occurs after paternal incarceration, highlighting the kinkeeping role of mothers. Additionally, consequences are concentrated among children living with both parents prior to paternal incarceration and among children of previously incarcerated fathers. Taken together, results provide some of the first evidence that the collateral consequences of incarceration may extend to intergenerational relationships.
Brain Computer Interface Boulevard of Smarter Thoughts

The Brain Computer Interface is a major breakthrough for the technical industry, medical world, military and the society on a whole. It is concerned with the control of devices around us such as computing gears & even automobiles in the near future without really the physical intervention of the user. It helps bridge the communication gap between the society and the disabled. This mainly lays its focus on people suffering from brainstem stroke, going through a spinal cord injury or even blindness. BCI helps such patients to retain or restore communication with the outside world through intelligent signals from the brain due to the high risk of paralysis under such circumstances. This is achieved by a signal acquisition technique and converting these signals available from the sensors placed on the scalp into real-time computer commands that can be visually operated and understood. It has nothing to do with the natural neural transmission of brain signals but extracts them with the help of sensors to be processed and direct the outputs to an external device. This may also prove to be a major military gadget where troops may communicate their thoughts in highly stressed situations without breaking the hush. But, as every technology have some merits and demerits, so does BCI.
A Mutation in the Carbohydrate Recognition Domain Drives a Phenotypic Switch in the Role of Galectin-7 in Prostate Cancer

The observation that galectin-7 (gal-7) is specifically expressed in mammary myoepithelial (basal) cells prompted us to investigate whether this protein is expressed in the basal cells of other tissues. Given that breast and prostate cancer have remarkable underlying biological similarities and given the important roles of basal cells in prostate cancer, we examined the expression patterns and role of gal-7 in human prostate cancer. Using tissue microarray, we found that although gal-7 is readily expressed in basal cells in normal prostate tissue, it is downregulated in prostate cancer (PCa) cells. De novo expression of gal-7 in prostate cancer cells increases their sensitivity to apoptosis in response to etoposide and cisplatin. The assessment of a carbohydrate-recognition domain (CRD)-defective mutant form of gal-7 (R7S) showed that the ability of this protein to modulate apoptosis was independent of its CRD activity. This activity was also independent of its ability to translocate to the mitochondrial and nuclear compartments. However, CRD activity was necessary to inhibit the invasive behaviors of prostate cancer cells. In vivo, gal-7 overexpression in PCa cells led to a modest yet significant reduction in tumor size, while its CRD-defective mutant form significantly increased tumor growth compared to controls. Taken together, these results suggest that although de novo expression of gal-7 may be an interesting means of increasing the tumorigenic phenotypes of PCa cells, alterations in the CRD activity of this protein drive a phenotypic switch in its role in PCa cells. This CRD-independent activity represents a paradigm shift in our understanding of the functions of galectin. The R74S model will be useful to distinguish CRD-dependent and CRD-independent functions of gal-7 in cancer progression.
Assessing alliance ruptures and resolutions: Reliability and validity of the Collaborative Interactions Scale-revised version

Abstract Objective: This study presents the revised version of the Collaborative Interactions Scale (CIS) [Colli, A. , & Lingiardi, V. (2009). The Collaborative Interactions Scale: A new transcript-based method for the assessment of therapeutic alliance ruptures and resolutions in psychotherapy. Psychotherapy Research, 19(6), 718–734. ], an observer-rated measure for the assessment of therapeutic-alliance ruptures and resolutions. Intensive use of the previous scale resulted in three criticisms: (i) excessive time required to perform evaluations, (ii) the low occurrence of some items, and (iii) the scale’s low capacity to capture some patient–therapist interactions in fine detail. In this study, we aimed to describe the scale revision process and evaluate interrater reliability and scale validity by comparing sessions of patients with and without personality disorders (PDs). Method: Three raters conducted a blind evaluation of a sample of 60 sessions (180 segments; 3607 narrative units) with 30 patients (15 had a PD diagnosis and 15 had a DSM-5 clinical syndrome diagnosis without a PD). Results: Interrater reliability results ranged from acceptable to excellent and were comparable to those of the former version. Patients with PDs showed a greater number of alliance ruptures and a smaller number of collaborative processes than patients without PDs. Moreover, therapists presented more negative interventions with the PD sample than with the non-PD sample. Conclusions: The results indicate that the revised CIS is a reliable rating system that is useful for both empirical research and clinical assessments. Clinical or methodological significance of this article: The CIS-R is a reliable rating system that is suitable for both empirical research and clinical assessment. It is useful for recognizing rupture and resolution processes, both in clinical everyday practice and in psychotherapists’ training. Application of the CIS-R promotes clinical reflection on the therapeutic action used to manage ruptures in a session.
Childhood obesity and dental caries among paediatric dental clinic attenders.

BACKGROUND More than one-quarter of New Zealand children are overweight or obese. Research on the causes of obesity has found associations with high consumption of sweetened foods and beverages, which have also been shown to be risk factors for dental caries, but studies investigating a possible association between dental caries and obesity have had conflicting findings. AIM The aim of this study was to determine whether deciduous dental caries experience was associated with BMI among paediatric dental clinic attenders. DESIGN This was a cross-sectional study of clinical records of 200 children aged eight and under (70% European) treated in the University of Otago undergraduate paediatric dentistry clinic between 2004 and 2006. Height and weight were measured and used to calculate BMI. Deciduous dental caries experience was recorded. RESULTS The overall mean BMI was 16.0 (SD = 2.0). Pacific Island children had a higher mean BMI (at 17.0) than NZ European, Maori, and Asian/Other children (15.7, 16.8, and 15.9 respectively; P < 0.05). The dmft ranged from 0 to 15, with a mean of 6.1 (SD = 3.8); 24% had dmft <3, and 38% had dmft >8. No significant association was found between the BMI and caries experience (P-value = 0.932). CONCLUSIONS There was no association between BMI and dental caries experience in this convenient sample.
Social Identity and Close Relationships: What is the Connection?

Social Identity and Close Relationships p. 2 Despite the centrality of intrapersonal processes of social cognition and affect, social psychology is ultimately the study of the connections between people. Even social cognition has become more interpersonal in recent years as topics such as shared cognition, transactional memory, and distributed cognition have become fruitful areas of social psychological research. Apart from shared cognition, there are two large bodies of research literature in social psychology that deal directly with the interconnectedness between and among individuals. One is the study of close relationships, personalized bonds between individuals and members of small groups such as family, teams, and peer friendship groups. The other is the study of social identity, the more depersonalized bonds among individuals who share membership in large social groups or categories, such as organizations, nations, or ethnic and religious identity. Together these two areas of research account for the lion's share of articles published in the IRGP section of the Journal of Personality and Social Psychology, as well as in specialty journals devoted to those topics specifically. Yet, despite the fact that both close relationships and group membership underscore the fundamentally social nature of human beings, there is very little connection between research in these two domains. Close relationship researchers rarely cite or refer to social identity or embeddedness in social groups, and social identity theorists draw a sharp distinction between intergroup and interpersonal processes, relegating the latter to " personal " rather than " social " identity (cf Hogg, 2001). A few years ago, Wendi Gardner and I tried to juxtapose the literatures on close relationships and social identity by postulating that relational ties and group Social Identity and Close Relationships p. 3 identities constitute two different levels of the " social self " (Brewer & Gardner, 1996). In place of existing dichotomies that contrasted individual/independent versus interpersonal/interdependent self-construals (Markus & Kitayama; Cross & Madsen) on the one hand, or personal versus social/group identities (Turner; Hogg & Abrams, 1988) on the other, we proposed a tripartite model, distinguishing among individual, relational, and collective self representations. Further, we suggested that these are not simply three aspects of a single self system, but rather three separate systems with different identity properties, locus of agency, and motivational concerns (see also Sedikides & Brewer, 2001). The relational and collective levels of self postulated by Brewer and Gardner (1996) represent two different forms of social …
Krivine nets

We define a new approach to compilation to distributed architectures based on networks of abstract machines. Using it we can implement a generalised and fully transparent form of Remote Procedure Call that supports calling higher-order functions across node boundaries, without sending actual code. Our starting point is the classic Krivine machine, which implements reduction for untyped call-by-name PCF. We successively add the features that we need for distributed execution and show the correctness of each addition. Then we construct a two-level operational semantics, where the high level is a network of communicating machines, and the low level is given by local machine transitions. Using these networks, we arrive at our final system, the Krivine Net. We show that Krivine Nets give a correct distributed implementation of the Krivine machine, which preserves both termination and non-termination properties. All the technical results have been formalised and proved correct in Agda. We also implement a prototype compiler which we compare with previous distributing compilers based on Girard's Geometry of Interaction and on Game Semantics.
An extended neuro-fuzzy approach for efficiently predicting review ratings in E-markets

Internet has opened new interesting scenarios in the fields of commerce and marketing. In particular, the idea of e-commerce has enabled customers to perform their transactions in a faster and cheaper way than conventional markets, and it has allowed companies to increase their sales volume thanks to a world-wide visibility. However, one of the problems that can strongly affect the performance of any e-commerce portal is related to the quality and validity of ratings provided by customers in their past transactions. Indeed, these reviews are used to determine the extent of customers acceptance and satisfaction of a product or service and they can affect the future selling performance and market share of a company. As a consequence, an efficient analysis of customer feedback could allow e-commerce portals to improve their selling capabilities and revenue. This paper introduces an innovative computational intelligence framework for efficiently learning review ratings in e-commerce by addressing different issues involved in this significant task: the dimension and imprecision of ratings data. In particular, we integrate the techniques of Singular Value Decomposition (SVD), Fuzzy C-Means (FCM) and ANFIS and, as shown in experimental results, this synergetic approach yields better learning performance than other rating predictors based on a conventional artificial neural network and FCM algorithm.
Visualising and systematizing a per-poor ICT intervention for Rural and Semi-urban Mothers in India

This paper presents an Information Communication Technology for Development (ICT4D) intervention through a novel audio assisted mobile application, designed for low literate mothers in rural and sub-urban parts of Assam in India. It explores new methods to enhance the usability of ICTs by adopting the per-poor or grassroots level innovation model which facilitates the poor to innovate for themselves through their interpretation of existing technologies. Systematically harvesting grassroots innovation is gaining momentum and attracting ICT interventions due to the increasing availability of low cost personalized mobile phones. Following a user centred design approach, we designed an audio-visual based application for the Nokia 6303. This would impart maternal health care information to low literate mothers and provide them with easier access to government health care facilities. Our research and field work involved 24 participants and investigated new modes of disseminating maternal health care information without disrupting the existing government health care system. We explored usage of Interactive Genetic Algorithms (IGAs) to redefine our layout from scratch and compared two methods of representing graphics- metaphorical icons and realistic visuals, observing significant preference for the latter. We found that grid based menu icons in small screen interfaces were more adaptable than a list based menu. To consolidate and validate the design proposed by us, we qualitatively tested a high fidelity prototype with 8 fresh participants. Our findings provide a possible systematic set of considerations that can be taken prior to realizing per-poor innovation in future ICT4Ds.
Long-term neurobehavioral outcomes in children with neuroblastoma and opsoclonus-myoclonus-ataxia syndrome: relationship to MRI findings and anti-neuronal antibodies.

OBJECTIVES Opsoclonus-myoclonus-ataxia (OMA) syndrome affects 2% to 3% of patients with neuroblastoma. This study examined relationships between long-term neurobehavioral outcomes and potential biologic markers of OMA, including chronic changes on magnetic resonance imaging (MRI) brain scanning and prevalence of late antineuronal antibodies. STUDY DESIGN Children with neuroblastoma and OMA were identified through medical record review of patients treated at the University of California at San Francisco Medical Center from 1979 to 1999. Eleven patients with a mean follow-up time of 7.6 years underwent standard neurologic, neurocognitive, developmental/behavioral, and academic assessments. Consenting patients underwent MRI brain scanning and a blood draw. Sera were analyzed for the presence of antineuronal immunoreactivity. RESULTS Two (18%) patients had no observed neurologic abnormalities, 7 (64%) demonstrated mild deficits, and 2 (18%) had severe neurologic deficits. However, on neurocognitive, behavioral, and academic assessments, 6 (55%) children performed within the average range, 1 (9%) was moderately below average and 4 (36%) had severe cognitive and behavioral deficiencies. Brain MRI in 5 of 5 patients was notable for cerebellar atrophy without supratentorial involvement. Antineuronal activity was detected in sera of 0 of 10 children at follow-up. CONCLUSIONS Certain patients with neuroblastoma associated OMA may achieve average-range neurobehavioral function in spite of residual neurologic abnormalities, with suggestion of continued improvement over time. Late cerebellar atrophy appears to be a common finding regardless of neurologic outcome, whereas antineuronal immune reactivity does not appear to be a long-term feature of OMA.
Simultaneously Sparse and Low-Rank Abundance Matrix Estimation for Hyperspectral Image Unmixing

In a plethora of applications dealing with inverse problems, e.g., image processing, social networks, compressive sensing, and biological data processing, the signal of interest is known to be structured in several ways at the same time. This premise has recently guided research into the innovative and meaningful idea of imposing multiple constraints on the unknown parameters involved in the problem under study. For instance, when dealing with problems whose unknown parameters form sparse and low-rank matrices, the adoption of suitably combined constraints imposing sparsity and low rankness is expected to yield substantially enhanced estimation results. In this paper, we address the spectral unmixing problem in hyperspectral images. Specifically, two novel unmixing algorithms are introduced in an attempt to exploit both spatial correlation and sparse representation of pixels lying in the homogeneous regions of hyperspectral images. To this end, a novel mixed penalty term is first defined consisting of the sum of the weighted ℓ1 and the weighted nuclear norm of the abundance matrix corresponding to a small area of the image determined by a sliding square window. This penalty term is then used to regularize a conventional quadratic cost function and impose simultaneous sparsity and low rankness on the abundance matrix. The resulting regularized cost function is minimized by: 1) an incremental proximal sparse and low-rank unmixing algorithm; and 2) an algorithm based on the alternating direction method of multipliers. The effectiveness of the proposed algorithms is illustrated in experiments conducted both on simulated and real data.