Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast recovery from link failures in Ethernet networks

Fast-recovery from link failures is a well-studied topic in IP networks. Employing fast-recovery in Ethernet networks is complicated as the forwarding is based on destination MAC addresses, which do not have the hierarchical nature similar to those exhibited in Layer 3 in the form of IP-prefixes. Moreover, switches employ backward learning to populate the forwarding table entries. Thus, any fast recovery mechanism in Ethernet networks must be based on undirected spanning trees if backward learning is to be retained. In this paper, we develop three alternatives for achieving fast recovery from single link failures in Ethernet networks. All three approaches provide guaranteed recovery from single link failures. The approaches differ in the technologies required for achieving fast recovery, namely VLAN rewrite and/or mac-in-mac encapsulation. We study the performance of the approaches developed on five different networks.
Scalable queue-based spin locks with timeout

Queue-based spin locks allow programs with busy-wait synchronization to scale to very large multiprocessors, without fear of starvation or performance-destroying contention. So-called try locks, traditionally based on non-scalable test-and-set locks, allow a process to abandon its attempt to acquire a lock after a given amount of time. The process can then pursue an alternative code path, or yield the processor to some other process. We demonstrate that it is possible to obtain both scalability and bounded waiting, using variants of the queue-based locks of Craig, Landin, and Hagersten, and of Mellor-Crummey and Scott. A process that decides to stop waiting for one of these new locks can ``link itself out of line'' atomically. Single-processor experiments reveal performance penalties of 50--100\% for the CLH and MCS try locks in comparison to their standard versions; this marginal cost decreases with larger numbers of processors. We have also compared our queue-based locks to a traditional \tatas\ lock with exponential backoff and timeout. At modest (non-zero) levels of contention, the queued locks sacrifice cache locality for fairness, resulting in a worst-case 3X performance penalty. At high levels of contention, however, they display a 1.5--2X performance advantage, with significantly more regular timings and significantly higher rates of acquisition prior to timeout.
The natural compound fucoidan from New Zealand Undaria pinnatifida synergizes with the ERBB inhibitor lapatinib enhancing melanoma growth inhibition

Melanoma remains one of the most aggressive and therapy-resistant cancers. Finding new treatments to improve patient outcomes is an ongoing effort. We previously demonstrated that melanoma relies on the activation of ERBB signaling, specifically of the ERBB3/ERBB2 cascade. Here we show that melanoma tumor growth is inhibited by 60% over controls when treated with lapatinib, a clinically approved inhibitor of ERBB2/EGFR. Importantly, tumor growth is further inhibited to 85% when the natural compound fucoidan from New Zealand U. pinnatifida is integrated into the treatment regimen. Fucoidan not only enhances tumor growth inhibition, it counteracts the morbidity associated with prolonged lapatinib treatment. Fucoidan doubles the cell killing capacity of lapatinib. These effects are associated with a further decrease in AKT and NFκB signaling, two key pathways involved in melanoma cell survival. Importantly, the enhancing cell killing effects of fucoidan can be recapitulated by inhibiting ERBB3 by either a specific shRNA or a novel, selective ERBB3 neutralizing antibody, reiterating the key roles played by this receptor in melanoma. We therefore propose the use of lapatinib or specific ERBB inhibitors, in combination with fucoidan as a new treatment of melanoma that potentiates the effects of the inhibitors while protecting from their potential side effects.
Avian-to-human transmission of the PB1 gene of influenza A viruses in the 1957 and 1968 pandemics

We determined the origin and evolutionary pathways of the PB1 genes of influenza A viruses responsible for the 1957 and 1968 human pandemics and obtained information on the variable or conserved region of the PB1 protein. The evolutionary tree constructed from nucleotide sequences suggested the following: (i) the PB1 gene of the 1957 human pandemic strain, A/Singapore/1/57 (H2N2), was probably introduced from avian species and was maintained in humans until 1968; (ii) in the 1968 pandemic strain, A/NT/60/68 (H3N2), the PB1 gene was not derived from the previously circulating virus in humans but probably from another avian virus; and (iii) a current human H3N2 virus inherited the PB1 gene from an A/NT/60/68-like virus. Nucleotide sequence analysis also showed that the avian PB1 gene was introduced into pigs. Hence, transmission of the PB1 gene from avian to mammalian species is a relatively frequent event. Comparative analysis of deduced amino acid sequences disclosed highly conserved regions in PB1 proteins, which may be key structures required for PB1 activities.
Emotional usability of customer interfaces: focusing on cyber banking system interfaces

Emotions play a major role in the social interaction process with electronic commerce systems. This paper describes our attempts to design customer interfaces that can induce target emotions for cyber banking systems. Four experiments were conducted to identify the important emotive factors and design factors, and to establish and verify causal relations between the factors. Results indicate that it is possible to design customer interfaces that will elicit target emotions for the systems(e.g., trustworthiness).
Block recycling schemes and their cost-based optimization in nand flash memory based storage system

Flash memory has many merits such as light weight, shock resistance, and low power consumption, but also has limitations like the erase-before-write property. To overcome such limitations and to use it efficiently as storage media in mobile systems, Flash memory based storage systems require special address mapping software called the FTL (Flash-memory Translation Layer). Like cleaning in Log-structured file system (LFS), the FTL often performs a merge operation for block recycling and its efficiency affects the performance of the storage system. To reduce the block recycling costs in NAND Flash memory based storage, we introduce another block recycling scheme that we call migration. Our cost-models and experimental results show that cost-based selection of merge or migration for each block recycling can decrease block recycling costs and, therefore, improve performance of Flash memory based storage systems. Also, we derive the macroscopic optimal migration/merge sequence minimizing block recycling costs for each migration/merge combination period. Experimental results show that the performance of Flash memory based storage can be further improved by the macroscopic optimization than the simple cost-based selection.
Operational Models of Data Mining Case Studies

This paper presents a method to publish executable models of data mining case studies in a so-called Case Base, where they can be inspected in detail by anyone using a common web browser. The Case Base serves to inspire and educate other developers of data mining applications, in particular if they are not yet experts in the field. A case study can be directly downloaded and executed on new data if it is found to provide a useful template. The approach is validated and exemplified using two data mining case studies from an Italian and a Polish telecommunications company. These case studies are interesting in their own right in that they involve complex data preparation issues. The paper studies these issues and relates them to the knowledge transfer opportunities that the Case Base offers.
Interactive 3D modeling from multiple images using scene regularities

Due to the complexity of real scenes and the fragility of fully automated vision techniques, results from many automated modeling systems are disappointing. Automated techniques often require manual clean-up and postprocessing to segment the scene into coherent objects and surfaces, or to triangulate sparse point matches. They may also be required to enforce geometric constraints such as known orientations of surfaces. For instance, building interiors and exteriors provide vertical and horizontal lines and parallel and perpendicular planes. In this paper, we attack the 3D modeling problem from the other side: we specify some geometric knowledge ahead of time (e.g., known orientations of lines, co-planarity of points, initial scene segmentations), and use these constraints to guide our matching and reconstruction algorithms. We present two interactive (semi-automated) systems for recovering 3D models of large-scale environments from multiple images.
Complexity reduced maximum likelihood detection for SDM-OFDM system

This paper proposes two complexity reduced maximum likelihood detection (MLD) methods for SDM-OFDM system to exploit the spatial diversity so as to achieve the improved transmission quality. The proposed methods enable to outperform the other suboptimal detection methods and achieve the near MLD performance with significant reduction of calculation complexity. The various computer simulation results confirm that the proposed methods could realize the above targets and might be promising solution in practical systems.
A Load-Driven Task Scheduler with Adaptive DSC for MapReduce

With the rapid development of internet applications, more and more network service and commercial applications are deployed to cloud computing environment, with petabytes of data to be processed. MapReduce is one of the most famous solutions for large-scale data processing. This paper focuses on optimizing the scheduler of MapReduce framework in task level. We care about the hardware configuration and real-time workload of the nodes in a hadoop cluster and aim at shortening time cost of MapReduce jobs and improving hardware resource utilization rate. We put forward a load-driven task scheduler which assigns tasks to Task Trackers according to the workload of slave nodes. It is based on a Dynamic Slot Controller (DSC) that can adjust Map task Slot (MS) and Reduce task Slot (RS) of Task Trackers running on slave nodes adaptively. Our load-driven task scheduler can shorten time consumption of MapReduce job by 14% and improve the CPU utilization rate of hadoop cluster by 34% when processing 10GB data.
Poor Predictive Validity of the Bayley Scales of Infant Development for Cognitive Function of Extremely Low Birth Weight Children at School Age

Objective. The Bayley Scales of Infant Development, Second Edition (BSID II) are commonly used to assess outcomes of extremely low birth weight (ELBW) infants. We sought to assess the predictive validity of the BSID II Mental Developmental Index (MDI) for cognitive function at school age. Design/Methods. Of 330 ELBW infants admitted in 1992–1995, 238 (72%) survived to the age of 8 years, of whom 200 (84%) were tested at both 20 months’ corrected age (CA) and 8 years. Mean birth weight was 811 g, mean gestational age was 26.4 weeks, 41% were boys, and 60% were black. Measures included the BSID II at 20 months’ CA and the Kaufman Assessment Battery for Children (KABC) Mental Processing Composite (MPC) at 8 years’ postnatal age. BSID II MDI and MPC scores were compared and the predictive validity calculated for all 200 ELBW children and for the 154 ELBW neurosensory-intact subgroup. Predictors of stability or change in cognitive scores were examined via logistic regression adjusting for gender and sociodemographic status. Results. For all ELBW children, the mean MDI was 75.6 ± 16 versus a mean KABC of 87.8 ± 19. For the neurosensory-intact subgroup, the mean MDI was 79.3 ± 16 and the mean KABC was 92.3 ± 15. Rates of cognitive impairment, defined as an MDI or KABC of <70, dropped from 39% at 20 months’ CA to 16% at 8 years for the total ELBW population and from 29% to 7% for the neurosensory-intact subgroup. The positive predictive value of having an MPC of <70 given an MDI of <70 was 0.37 (95% confidence interval [CI]: 0.27, 0.49) for all ELBW infants, 0.20 (95% CI: 0.10, 0.35) for the neurosensory-intact subgroup, and 0.61 (95% CI: 0.42, 0.77) for the neurosensory-impaired subgroup. The negative predictive values were 0.98, 0.99, and 0.85 for the 3 groups, respectively. Neurosensory impairment at 20 months’ CA predicted lack of improvement of cognitive function (odds ratio: 6.9; 95% CI: 2.4, 20.2). Children whose cognitive scores improved between 20 months and 8 years had significantly better school performance than those whose scores stayed at <70, but they did less well than those whose scores were persistently >70. Conclusions. The predictive validity of a subnormal MDI for cognitive function at school age is poor but better for ELBW children who have neurosensory impairments. We are concerned that decisions to provide intensive care for ELBW infants in the delivery room might be biased by reported high rates of cognitive impairments based on the use and presumptive validity of the BSID II MDI.
Removing Gaussian Noise from Color Images by Varying the Size of Fuzzy Filters

The primary issue involved in image and signal processing is to efficiently remove noise from a digital color image while preserving its features. A fuzzy filter is presented for the reduction of additive noise for digital color images. The filter consists of two sub filters. The first sub filter computes fuzzy distances among the color components of the central pixel and its neighborhood. These distances decide in what extent each component should be corrected. The objective of the second sub filter is to calculate the color components differences to retain the fine details of the image. One distance measure as the Minkowski's distance and other as the Absolute distance are selected and compared their performances using Peak Signal to Noise Ratio
Cancer Genetic Counseling in Public Health Care Hospitals: The Experience of Three Brazilian Services

In Brazil, genetic counseling is usually available in university-affiliated medical genetics services located in tertiary centers that provide cancer diagnosis and treatment. The present study aims to describe the structure and characteristics of three cancer genetic services in Brazilian public health care hospitals and discuss alternatives for the identification and prevention of hereditary cancer syndromes in developing countries. The three services presented here are similar in their structure, routine procedures for cancer risk estimation and criteria for the indication of genetic testing. They all demand that genetic counseling be an essential part of the cancer risk evaluation process, before and after cancer predisposition testing. However, when high-risk patients are identified, all services describe difficulties in the access and continuity of genetic and medical services to the patient and his/her at-risk relatives. The services differ in the type of population served, reflecting distinct referral guidelines. This study emphasizes the importance of the creation of new cancer genetic services in other Brazilian regions and the necessity for establishing a collaborative network to facilitate the diagnosis and research of cancer genetic syndromes.
Antiimmunoglobulin-treated B cells respond to a B cell differentiation factor for IgG1

We have determined whether B cells previously activated by anti-Ig (anti-Ig blasts) are responsive to lymphokines that induce isotype switching. Culture of anti-Ig blasts with a mixture of lymphokines, including BSF-1, resulted in marked secretion of IgM and IgG1, but not other IgG isotypes. The IgG1 response of anti-Ig blasts to lymphokines was 13-fold greater than was observed with splenic B cells. B cell blasts induced by 8-mercaptoguanosine or dextran sulfate did not secrete high levels of any IgG isotype in response to lymphokines alone. An mAb against BSF-1 suppressed the IgG1 response of anti-Ig blasts, but not the IgM response to lymphokines. These data suggest that anti-Ig-treated B cells respond to at least one of the effects of BSF-1.
Real-World Multitasking from a Cognitive Neuroscience Perspective

This chapter examines the demands made by multitasking situations in the real world, and argues that the human brain systems critical in dealing with them may be surprisingly circumscribed. Four kinds of evidence are considered: single-case studies of patients with selective multitasking problems; group studies of the relationship between multitasking failures and other cognitive control problems; the neuroanatomical locus of multitasking deficits according to group lesion studies, and evidence from functional imaging. These studies suggest three distinct brain systems are involved in supporting the retrospective memory, prospective memory and planning demands of multitasking, and tentative suggestions for the neuroanatomical correlates of these systems are proposed. In a recent television program, the U.S. astronaut Jerry Linenger described his experiences aboard the Mir space station: “We had many system failures and they were in need of your constant attention. Many days I’d start an experiment in the morning and then I’d run over and help hacksaw through a pipe and plug the ends and then run back to my experiments. I’d have three or four watches on with alarms set to different things that I’d have to run back to. So I was multitasking in order to try to get everything accomplished. ’’ Although, at first sight, Jerry Linenger’s use of the term multitasking accords well with the Compact Oxford English Dictionary definition: the “ability to perform concurrent tasks or jobs by interleaving,’’ his account suggests something more complex than interleaving tasks in a multipletask sense. The situation he faced also required further mental activities, such as prioritization, planning, and prospective memory (i.e., the realization of a delayed intention; Ellis 1996). The ability to deal with such complex situations is clearly important to effectiveness in everyday life. Neurological patients who have lost this ability are severely handicapped, especially in work situations. However, although the present volume is testament to recent advances in understanding many situations which have some relevance to aspects of multitasking (e.g. dualor multiple-task paradigms, task switching etc), more complex situations akin to those faced by Jerry Linenger have been rarely studied within an experimental psychology or cognitive neuroscience framework. Indeed, the complexity of such situations would seem to 20
The robustness of a new CAPTCHA

CAPTCHA is a standard security technology that presents tests to tell computers and humans apart. In this paper, we examine the security of a new CAPTCHA that was deployed until very recently by Megaupload, a leading online storage and delivery website. The security of this scheme relies on a novel segmentation resistance mechanism. However, we show that this CAPTCHA can be segmented using a simple but new automated attack with a success rate of 78%. It takes about 120 ms on average to segment each challenge on a standard desktop computer.
Intimate partner violence and group therapy: The voices of Latino men

xiv INTRODUCTION. 1 Review of Relevant Literature. 3 Group Treatment of IPV. 3 Male Identity Development. 6 Latino Males. 10 Cultural Considerations in IPV Group Treatment. 14 METHODS. 18 Participants . 18 Sample Characteristics. 20 Study Goals. 20 Research Approach. 21 Instruments. 23 Procedures. 25 Data Analysis. 27 RESULTS. 31 Group Treatment for IPV Makes a Positive Impact. 31 Importance of male support. 32 Importance of education in group. 34 Gender Role Stress Influences IPV. 35 Work related stressors. 35 Financial and economic stressors. 38 IPV is a Spectrum of Abusive Behaviors. 41 Intentional IPV behaviors. 41 IPV behaviors as evasive tactics. 44 The Macho vs. the Man. 45 The macho. 46 The man. 48 Marital Dynamics Influence IPV. 51 Communication within intimate relationships. 51
Study on identification of nonlinear systems using Quasi-ARX models

System identification can be used to construct a model to represent a given system, and it plays an important role in system analysis, control and prediction. From the view of application, conventional nonlinear black-box models are not good since an easy-to-use model is to interpret properties of the nonlinear process, rather than treated as vehicles for adjusting the fit to the data. Therefore, some careful modeling is needed for certain applications, and prior knowledge from system is inspired to be combined with formal properties of the model. Quasi-linear autoregressive with exogenous inputs (quasi-ARX) modeling scheme provides an effective approach to extend well-studied and user-friendly linear techniques to nonlinear applications. It constructs models consisting of two parts: a macro-part and a core-part. The macro-part owns a useful interface to introduce some properties favorable to specific applications, and the corepart is a flexible nonlinear model to parameterize complicated coefficients of the macro-part. To this end, an ARX-like linear structure is constructed as the macro-part by using Taylor expansion; while the coefficients are parameterized by a multi-input-multi-output (MIMO) nonlinear model in the core-part. Nevertheless, it is no easy solution to identify nonlinear systems using the quasi-ARX models, though it is equipped with a useful structure. Followed by requirements of real applications, the identification is expected to interpret properties of the nonlinear system and hold the principle of simplicity. One effective approach to this challenge is to divide the model parameters into two parts: the nonlinear parameters and the linear parameters. The nonlinear parameters mean those interpretable ones, such as translation and dilation parameters of wavelet basis function, which can be determined by using prior knowledge. When the nonlinear parameters are fixed, the quasi-ARX model can be transformed linear in parameters. These linear parameters are the ones to fit the data, which can be estimated by linear regression methods. Furthermore, the quasi-ARX model is meaningful to nonlinear polynomial system identification, which often contains a big number of candidate monomial terms. The identified quasi-ARX model inspires a pre-processing approach to evaluate significance of each monomial term, which is helpful to reduce the candidate pool efficiently. In this thesis, investigations are firstly made on nonlinear parameter estimation with clustering partition and grid partition method, where wavelet network (WN) and neurofuzzy network (NFN) are included as the core-part of the model, respectively. Then the linear parameter is estimated by means of kernel method, where radial basis function network (RBFN) is incorporated. Finally, neural network (NN) is embedded in the quasi-ARX model, which is identified and provides a pre-screening scheme for polynomial system identification. i