Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Bases of Set-Shifting Deficits in Parkinson's Disease

Patients with Parkinson's disease (PD) exhibit impairments in several cognitive functions similar to those observed in patients with prefrontal cortex (PFC) lesions. The physiological origins of these cognitive deficits are not well documented. Two mechanisms have been proposed: disruptions in corticostriatal circuits or a deficiency in frontal dopamine. We previously used functional magnetic resonance imaging (fMRI) in young healthy subjects to separate patterns of PFC and striatum activity during distinct phases of performance of the Wisconsin Card Sorting Task, a set-shifting task that reveals deficits in patients with PD. Here, the same fMRI protocol was used in PD patients and matched controls. Decreased activation was observed in the PD group compared with the matched control group in the ventrolateral PFC when receiving negative feedback and the posterior PFC when matching after negative feedback. In controls, these prefrontal regions specifically coactivated with the striatum during those stages of task performance. In contrast, greater activation was found in the PD group compared with the matched control group in prefrontal regions, such as the posterior and the dorsolateral PFC when receiving positive or negative feedback, that were not coactivated with the striatum in controls. These results suggest that both nigrostriatal dopamine depletion and intracortical dopamine deficiency may play a role in cognitive deficits in PD, depending on the involvement of the striatum in the task at hand.
Biochemistry Synthesis on a Cyberphysical Digital Microfluidics Platform Under Completion-Time Uncertainties in Fluidic Operations

Cyberphysical digital microfluidics enable the integration of fluidic operations, biochemical reaction-outcome detection, and software-based control in a biochip. However, biochemistry synthesis algorithms and biochip design methods proposed in the literature are oblivious to completion-time uncertainties in fluidic operations, and they do not meet the requirements of the cyberphysical integration in digital microfluidics. We present an operation-interdependency-aware synthesis method that uses frequency scaling and is responsive to uncertainties that are inherent in the completion times of fluidic operations such as mixing and thermal cycling. Using this design approach, we can carry out dynamic online decision-making for the execution of fluidic operations and droplet-routing in response to detector feedback. We use three common laboratorial protocols to demonstrate that, compared to uncertainty-oblivious biochip design, the proposed dynamic decision-making approach is more effective in satisfying realistic physical constraints. As a result, it decreases the likelihood of erroneous reaction outcomes, and it leads to reduced time-to-results, less repetition of reaction steps, and less wastage of precious samples and reagents.
A influência do território no comportamento do mercado de trabalho: notas sobre a experiência brasileira

The Brazilian labor market indicators have improved in the decade of 2000s. The unemployment rate declined and the formalization level rose in nearly all of the Brazilian territory. However, some spatial inheritances were reinforced and new spaces were developed, which means the underdeveloped profile of the Brazilian labor market did not change. The paper presents a discussion about the relation between the spatial economic specialization and the labor market behavior. Supported by literature and empirical analysis, the paper shows how territorial features can influence the labor market. Based on the Sao Paulo State experience the work shows evidence that the spatial economic specialization can reduce job opportunities and unemployed population could be hidden under the inactivity shadow
Traffic Classification in Mobile IP Network

Traffic classification is an essential task for network management. Thus many researchers have paid attention to initial sub-flow features based classifiers for achieving online traffic classification. However, the existing classifiers cannot classify traffic effectively in mobile IP network, because they cannot always capture the initial sub-flow when a communicating node moves and its point of attachment changes. Desirable classifier should thus be capable of traffic classification based on not only initial sub-flow but also various types of sub-flow. In this paper, we propose sub-flow selection with application behaviors, and the method solves a critical problem of how to select appropriate sub-flows for achieving traffic classification in mobile IP network. Although at a very early stage of development, the proposed method shows promising preliminary results through the experiments on a reduced set of applications.
Relationship between Glycosylated Hemoglobin, Serum Nitric Oxide and Mean Arterial Blood Pressure

Background: Hypertension is about twice as frequent in individuals with diabetes as in those without diabetes. Formation of glycosylated conjugates like HbA1c is implicated to have many effects on the vascular endothelium which leads to the development of hypertension in diabetes. Nitric oxide (NO)-dependent vasodilatation has been shown to be an important factor in the maintenance and regulation of peripheral vascular tone. Studies correlating these parameters give conflicting results. Hence the present study was designed to correlate HbA1c, Serum NO & mean arterial blood pressure. Aims: To study the relationship between glycosylated hemoglobin, serum nitric oxide & mean arterial blood pressure. Settings and Design: It is a case control study with 28 type 2 diabetic hypertensives, 32 type 2 diabetic normotensives and 51 controls (non diabetic normotensives). Materials & Methods: The study subjects included 28 type 2 diabetic hypertensives, 32 type 2 diabetic normotensives and 51 controls (non diabetic normotensives) [ADA 2010 and JNC7]. FBS, PPBS, PCV, Hb, HbA1c & serum NO estimation and BP recording was done in all the study subjects. Normalised mean arterial blood pressure (MAPn) and calculated glycosylated hemoglobin (cHbA1c) were calculated from mean arterial BP (MAP) and HbA1c respectively. Statistical Analysis: was done using R commander software. The difference in the distribution of cHbA1c, MAPn & NO levels between all 3 groups was measured using ANOVA and Kruskal-Wallis test. Correlation between the parameters was measured by Correlation coefficient and logistic regression (Spearman linear regression) analysis (univariate and multivariate). Results: There was a significant difference in the distribution of cHbA1c, MAPn & NO levels (p<0.001) between all 3 groups, whether measured by ANOVA or Kruskal-Wallis test. On univariate analysis, there was a positive correlation between cHbA1c & MAPn (ρ= +0.26), a negative correlation between NO & MAPn (ρ = -0.54) and cHbA1c & NO (ρ= -0.66) . On multivariate analysis, not only NO, but contrary to univariate analysis, cHbA1c also showed a negative association with MAPn. Conclusion: As the severity of diabetes increases, there is increase in BP, which is mainly due to the marked decrease in NO level which masks the negative correlation between HbA1c on MAPn.
False Positive (fp) and False Negative (fn)

We estimated f p and f n with the similar equation in Deng et al. [1]. The difference is the calculation of P r(O ij = 1, P ij = 1). Lee et al. [2] assessed the reliability of DIP protein interactions for yeast as 0.6, which represents P r(P ij = 1|O ij = 1). We modified the equations for f p and f n in Deng et al. [1] by using P (O ij = 1) * 0.6 for P r(O ij = 1, P ij = 1). The average numbers of interaction partners in the experimental protein-protein interaction sets are 5. If we consider that the protein interaction sets are incomplete, especially for worm, and protein interactions are relatively well studied in yeast, we can assume that each protein has on average of at least five interaction partners. Hazbun and Fields [3] estimated that each protein interacts with about t = 5 to 50 proteins. We assume that each protein interacts with other proteins about t=5 times and we use it to estimate the total number of real interaction pairs. In addition, we also showed the results using t=50 in Figure S1. For example of yeast, f n = P r(O ij = 0|P ij = 1) = 1.0 − P r(O ij = 1, P ij = 1) P r(P ij = 1) = 1.0 − P r(O ij = 1)P r(P ij = 1|O ij = 1) P r(P ij = 1) = 1.0 − number of observed interaction pairs number of real interaction pairs * 0.6 = 1.0 − 7, 985 t * N/2 * 0.6 = 1.0 − 7, 985 5 * 2, 568/2 * 0.6 = 0.25 f p = P r(O ij = 1|P ij = 0) = P r(O ij = 1, P ij = 0) P r(P ij = 0) = P r(O ij = 1)P r(P ij = 0|O ij = 1) P r(P ij = 0) = number of observed interaction pairs total protein pairs − number of observed interaction pairs * 0.4 = 7, 985 N * (N + 1)/2 − t * N/2 * 0.4 = 7, 985 2, 568 * (2, 568 + 1)/2 − 5 * 2, 568/2 * 0.4 = 0.0009 where N is number of proteins in the DIP database with PFAM-A domain information. To assess the reliability of observed protein …
The Management of Data, Events, and Information Presentation for Network Management

The purpose of a network management (NM) system is to monitor and control a network. Monitoring and control functions entail dealing with large volumes of data, events, and the presentation of relevant information on a management station. In this thesis we focus on data and events management and information presentation issues of an NM system. Existing NM systems either use traditional database systems which are not well suited for an NM system or they lack intelligent event and information presentation management frameworks. None of the systems provides a unified framework for managing data, events and information presentation tasks on an NM station. We believe that the complexities of network management can be reduced substantially by exploiting, enhancing and combining the features of new generation database systems such as active temporal and database visualization systems. In this thesis we show that an active database system where active behaviors are specified as Event-Condition-Action (ECA) rules is a suitable framework for NM data and events management. The Hy database visualization system with its sophisticated abstraction and visualization capabilities is well-suited to meet the requirements of NM information presentation. We also show that by viewing the network as a conceptual global database the network management functions can be specified as declarative database manipulation operations and Event-Condition-Action (ECA) rules. But the facilities provided by existing active database systems are not enough for an NM system. A number of existing active temporal database systems provide support for a composite event specification language (CESL) (used in the E part of an ECA rule) that allows one to relate events in the temporal dimension. But these languages lack features that otherwise are required by certain applications. We propose a CESL called CEDAR that extends the power of existing languages. CEDAR allows a user to specify various event management functionalities in the NM domain, which are difficult or impossible to specify in existing languages. An implementation model of the language operators using Colored Petri Nets is proposed. We also propose a model of a network management database system that incorporates CEDAR into an active database system, and various features required by an NM system. The resulting system (the Hy-CEDAR system) is integrated with the Hy database visualization system.
Working at the Nexus of Generic and Content-Specific Teaching Practices: An Exploratory Study Based on TIMSS Secondary Analyses

For years scholars have attended to either generic or content-specific teaching practices attempting to understand instructional quality and its effects on student learning. Drawing on the TIMSS 2007 and 2011 databases, this exploratory study empirically tests the hypothesis that attending to both types of practices can help better explain student performance. Capitalizing on one generic and one content-specific framework, we tested this hypothesis for grade 8 mathematics. The analyses for the entire sample showed that more variance was explained when considering both types of practices in tandem than that explained when considering each type in isolation. Important insights were also gleaned when testing this hypothesis for each individual country, since notable differences were observed across participating countries. In discussing the study findings, which were relatively consistent across the two TIMSS cycles, we draw implications for the development of theoretical frameworks capturing instructional quality and the design of international comparative studies.
11. ‘He walked up the pole with arms and legs’

The present chapter, based on Vidakovic (2006), investigates the frequency with which Manner and Path of motion are expressed in speech in English and Serbian and explores language-specific and universal factors influencing L2 acquisition in this domain. It reveals that Manner information is omitted by Serbian native speakers in certain contexts in their L1, which places Serbian closer to the verb-framed end of the typological continuum. English learners of Serbian and Serbian learners of English are influenced by their L1 in terms of Manner mention, but the interplay of L1 and L2 influences is also attested. The universal tendencies in reference to Path are discussed, as well as implications for L2 acquisition, teaching and research on language and cognition.
Improved Interpretability of the Unified Distance Matrix with Connected Components To Appear Proceedings of DMIN ’ 11

Self-organizing maps have been adopted in many fields as the data visualization method of choice. The unified distance matrix is the de facto standard for evaluating and interpreting self-organizing maps. In large, high-dimensional problems clusters can be difficult to identify in the plain unified distance matrix. Here we introduce an enhanced version of the unified distance matrix in which clusters are easier to see and interpret. In this enhanced version we view the self-organizing map as a planar graph where the clusters are connected components of this graph. Using the transitive properties of connectedness and exploiting the fact that each component has a minimal node where the gradient on the unified distance matrix is equal to zero we can transform these connected components into stars with the minimal node as the internal node. In order to avoid unnecessary fragmentation of the components we apply a kernel based smoothing algorithm to the unified distance matrix. Our enhanced unified distance matrix is then the smoothed original unified distance matrix with the star components overlaid. The result is an easily interpretable selforganizing map. We perform a number of experiments on synthetic as well as real-world data that highlight the increased visual power of this enhanced unified distance matrix. Fig. 1. A unified distance matrix.
Enhanced IP protocol for handover modular architecture and measurement phase information exchange

The handover metering infrastructure is one of the most important factors for the heterogeneous mobile networks. This is because these parameters are very important when handover decision is taken. There are two methods to collect these parameters, one method using centralized node which is responsible for collecting this information whereas the second method is based on the distributed strategy. In this paper we propose a simple distributed scheme among different wireless nodes. Putting extra bits in the IP option header paved the way to exchange the handover metrics among different wireless networks. This method enhances the contributing of the IP protocol in the handover process. We also will propose a modular structure for the handover mechanism using the IP protocol. The choice of the IP protocol comes from its dominant use in the next generation wireless network which is based on all IP networks. Moreover, in this paper we introduce some new metrics that enhances the overall handover decision using prove of concept.
Sharing trajectories of autonomous driving vehicles to achieve time-efficient path navigation

Traffic congestion arises to be a very serious problem especially in metropolitan cities nowadays. Drivers need to spend more time to their destinations. In this paper, a dynamic navigation protocol, called STN, is proposed to search for time-efficient paths for autonomous driving vehicles toward their given destinations. The trajectory information of vehicles is maintained in a server to assist the planning of navigation path. With STN, a vehicle sending a request message toward the nearest access point (AP) to acquire the driving path. By comparing the trajectories and time information in the system, the future traffic load can be predicted. The traffic load information enables the server to estimate driving speed within different paths toward the destination and then determines a time-efficient path. In addition, adjustment, update, and replan mechanisms are developed to reduce the deviation of prediction. To evaluate the performance of STN, the real road map of Shalu, Taiwan, including 20 road segments, is used. The simulator Estinet, formerly known as NCTUns (National Chiao Tung University Network Simulation) has been used for the validation of STN. The simulator integrates some traffic simulation capabilities, such as road network construction and vehicles mobility control, in the recent version. The simulation results demonstrate that STN saves around 14% driving time as compared with Vehicle-Assisted Shortest-Time Path Navigation (VAN).
Ambient air pollution: a cause of COPD?

The role of ambient air pollution in the development of chronic obstructive pulmonary disease (COPD) is considered to be uncertain. We review the evidence in the light of recent studies. Eight morbidity and six mortality studies were identified. These were heterogeneous in design, characterisation of exposure to air pollution and methods of outcome definition. Six morbidity studies with objectively defined COPD (forced expiratory volume in 1 s/forced vital capacity ratio) were cross-sectional analyses. One longitudinal study defined incidence of COPD as the first hospitalisation due to COPD. However, neither mortality nor hospitalisation studies can unambiguously distinguish acute from long-term effects on the development of the underlying pathophysiological changes. Most studies were based on within-community exposure contrasts, which mainly assess traffic-related air pollution. Overall, evidence of chronic effects of air pollution on the prevalence and incidence of COPD among adults was suggestive but not conclusive, despite plausible biological mechanisms and good evidence that air pollution affects lung development in childhood and triggers exacerbations in COPD patients. To fully integrate this evidence in the assessment, the life-time course of COPD should be better defined. Larger studies with longer follow-up periods, specific definitions of COPD phenotypes, and more refined and source-specific exposure assessments are needed. Evidence of chronic effects of air pollution on the prevalence and incidence of COPD is suggestive but not conclusive http://ow.ly/pCfjy
Unusual Legionnaires' outbreak in cool, dry Western Canada: an investigation using genomic epidemiology

SUMMARY An outbreak of Legionnaires' disease occurred in an inner city district in Calgary, Canada. This outbreak spanned a 3-week period in November–December 2012, and a total of eight cases were identified. Four of these cases were critically ill requiring intensive care admission but there was no associated mortality. All cases tested positive for Legionella pneumophila serogroup 1 (LP1) by urinary antigen testing. Five of the eight patients were culture positive for LP1 from respiratory specimens. These isolates were further identified as Knoxville monoclonal subtype and sequence subtype ST222. Whole-genome sequencing revealed that the isolates differed by no more than a single vertically acquired single nucleotide variant, supporting a single point-source outbreak. Hypothesis-based environmental investigation and sampling was conducted; however, a definitive source was not identified. Geomapping of case movements within the affected urban sector revealed a 1·0 km common area of potential exposure, which coincided with multiple active construction sites that used water spray to minimize transient dust. This community point-source Legionnaires' disease outbreak is unique due to its ST222 subtype and occurrence in a relatively dry and cold weather setting in Western Canada. This report suggests community outbreaks of Legionella should not be overlooked as a possibility during late autumn and winter months in the Northern Hemisphere.
Using Geometric Constraints to Support Virtual Electrical Installation Design

This paper presents an extension of the geometric constraint-based paradigm to support the design of electrical installation. A system has been developed, using graph-based algorithms, to facilitate the construction of an electrical installation design and to allow the calculation, visualization and interaction in real time with a 3D model. Virtual engineering is a usercentered process that provides a collaborative framework to integrate all of the models, data and decision-support tools needed for good engineering design. The ceiling conduit mesh, in electrical design, is automatically constructed and also routes to define the shortest path are generated. Furthermore, the system automatically detects obstacles in the architectonic design and provides a new avoiding path for the electric conduit.
CRRA: A collaborative approach to re-ranking search results

Web search is not only an individual activity, but also a collaborative activity. By analyzing users' search activities at a community level, effectively refining the ranking of search results has received wide attention in information retrieval in recent years. Previous research has proposed approaches that predefined communities to search collaboratively. However, these approaches usually neglected correlation between users. In this study, we propose a novel collaborative approach (CRRA) for re-ranking search results based on user search activities recorded in query logs. The central idea is to establish correlations among three factors: user, query and document terms, by analyzing user logs. These correlations are then employed to determine community dynamically based on probability theory and collaborative filtering technique and calculate re-ranking score of search results. Evaluation results show that CRRA is more effective than other collaborative ranking approaches.
Analyzing the war–media nexus in the conflict-ridden, semi-democratic milieu of Pakistan

This study combined the key findings of a dozen empirical studies with an original qualitative investigation aimed at understanding the dynamics of conflict journalism in Pakistan. The author devised an original contextual model and tested its applicability in five different conflicts of varying intensity. The study found that conflict journalism is dependent on the interaction between two key factors: the journalistic assessment of a conflict in terms of its seriousness of threat to national security and the resultant flak that stems from various sources that significantly influence professional reporting. The article concludes that journalists working in the semi-democratic, conflict-marred settings of Pakistan adopt a more vigilant and independent stance if they perceive a conflict to be posing an enormous threat to national security, for example the Taliban conflict, and that their critical stance erodes to a more compromising position in the case of a medium-level threat in conflicts such as the one in Balochistan and the ethno-political conflict in Karachi; their reporting further diminishes to a more sensational stance in the case of a low-level threat conflict due to the preponderance of the commercial interests of media industries.