Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerator and Target Technology for Accelerator Driven Transmutation and Energy Production

1.1 History of Accelerator Driven System Activities Since the early 1990’s, accelerator driven systems (ADS) – subcritical assemblies driven by high power proton accelerators through a spallation target which is neutronically coupled to the core – have been proposed for addressing certain missions in advanced nuclear fuel cycles. Institutes throughout the world have conducted numerous programs evaluating the role of ADS in nuclear waste transmutation and energy production. In 1995, the National Research Council (NRC) issued a report on transmutation technologies [1], which included an evaluation of one ADS concept that was under study at that time: a large-scale system that proposed using a ~100-MW accelerator to drive a thermal, molten salt subcritical core. The NRC recognized the numerous complexities associated with the system, including the fact that, at that time, much of the high-power accelerator technology required for that ADS system had yet to be demonstrated. Consequently, the NRC report did not look favorably upon ADS.
Long-Term Follow-Up of Attentional and Executive Functions of PTSD Patients

Scientific evidence showed significant correlations between symptoms of posttraumatic stress disorder (PTSD) and deficits in cognitive processing. Understanding how these deficits correlate with symptoms of PTSD in prospective studies can provide arguments to improve explanatory models of pathological mechanisms of this disorder. Our objective was to prospectively evaluate adult victims of urban violence suffering from PTSD, considering its impact on attention, executive functions, and the factors associated with these changes. We reapplied a battery of neuropsychological tests on a cohort of 43 patients with PTSD due to urban violence. We also reapplied the Clinician Administered PTSD Scale (CAPS) and the Beck Depression Inventory (BDI-I) scales. We administered a battery of neuropsychological tests: Wechsler Adult Intelligence Scale (WAIS-III) Digit Span, Wechsler’s Memory Scale—Revised (WMS-III), Spatial Span, Stroop, and Wisconsin Card Sort Test (WCST). Patients showed a clinical improvement evidenced by a statistically significant decrease in CAPS and BDI scores at follow-up. Regarding neuropsychological testing, significant differences were found at follow ups such as a reduced number of perseverative errors in WCST (p = .004) and an increase in the span of the backward digit subtest (p = .007). These changes are directly associated with education level (p = .030), and PTSD symptoms (p = .005). Patients on average showed an improvement in PTSD and depression symptoms at reevaluation. The data showed an improvement in cognitive performance of executive functions such as working memory and cognitive flexibility over the years. These enhancements are significant for patients with more years of study, and for those that have recovered clinically, showing fewer symptoms of depression PTSD.
Improved time series prediction using evolutionary algorithms for the generation of feedback connections in neural networks

Some results from a method for generating recurrent neural networks (RNN) for prediction of financial and macroeconomic time series are presented. In the presented method, a feedforward neural network (FFNN) is first obtained using backpropagation. While backpropagation is usually able to find a fairly good predictor, all FFNN are limited by their lack of short-term dynamic memory. RNNs, by contrast, may exhibit short-term memory due to feedback connections in the network. In the method presented here, the RNNs are generated by an evolutionary algorithm (EA). The preliminary results indicate that the evolved RNN indeed outperform, by a few per cent, the FFNN obtained through backpropagation on several time series. However, it is noted that, regardless of the predictor used, the prediction error cannot be much improved over that obtained from a very simple predictor. Finally, another approach is tested as well, in which the evolved RNN generate not only a prediction but also a measure of confidence in the prediction.
Reliability in the Identification of Midbrain Dopamine Neurons

Brain regions typically contain intermixed subpopulations of neurons with different connectivity and neurotransmitters. This complicates identification of neuronal phenotypes in electrophysiological experiments without using direct detection of unique molecular markers. A prime example of this difficulty is the identification of dopamine (DA) neurons in the midbrain ventral tegmental area (VTA). Although immunocytochemistry (ICC) against tyrosine hydroxylase (TH) is widely used to identify DA neurons, a high false negative rate for TH ICC following ex vivo electrophysiology experiments was recently reported, calling into question the validity of comparing DA and non-DA VTA neurons based on post-hoc ICC. However, in whole cell recordings from randomly selected rat VTA neurons we have found that TH labeling is consistently detected in ∼55% of neurons even after long recording durations (range: 2.5–150 min). This is consistent with our prior anatomical finding that 55% of VTA neurons are TH(+). To directly estimate a false negative rate for our ICC method we recorded VTA neurons from mice in which EGFP production is driven by the TH promoter. All 12 EGFP(+) neurons recorded with a K-gluconate internal solution (as used in our rat recordings) were strongly labeled by TH ICC (recording duration 16.6±1.8 min). However, using recording electrodes with an internal solution with high Cl− concentration reduced the intensity of TH co-labeling, in some cases to background (recording duration 16.7±0.9 min; n = 10). Thus TH is a highly reliable molecular marker for DA neurons in VTA patch clamp recordings provided compatible microelectrode solutions are used.
Discovering Conservation Rules

Many applications process data in which there exists a ``conservation law'' between related quantities. For example, in traffic monitoring, every incoming event, such as a packet's entering a router or a car's entering an intersection, should ideally have an immediate outgoing counterpart. We propose a new class of constraints -- Conservation Rules -- that express the semantics and characterize the data quality of such applications. We give confidence metrics that quantify how strongly a conservation rule holds and present approximation algorithms (with error guarantees) for the problem of discovering a concise summary of subsets of the data that satisfy a given conservation rule. Using real data, we demonstrate the utility of conservation rules and we show order-of-magnitude performance improvements of our discovery algorithms over naive approaches.
Generalized stochastic subdivision

Stochastic techniques have assumed a prominent role in computer graphics because of their success in modeling a variety of complex and natural phenomena. This paper describes the basis for techniques such as stochastic subdivision in the theory of random processes and estimation theory. The popular stochastic subdivision construction is then generalized to provide control of the autocorrelation and spectral properties of the synthesized random functions. The generalized construction is suitable for generating a variety of perceptually distinct high-quality random functions, including those with non-fractal spectra and directional or oscillatory characteristics. It is argued that a spectral modeling approach provides a more powerful and somewhat more intuitive perceptual characterization of random processes than does the fractal model. Synthetic textures and terrains are presented as a means of visually evaluating the generalized subdivision technique.
Mosaic Paths to New Knowledge: Conceptualizing Cultural Wealth from Women of Colour as They Experience the Process of becoming Doctoral Recipients

The aim of this study is to identify the positive contributions women of colour (WOC) bring to higher education as they experience the process of becoming doctoral recipients. Their experiences are presented as a new epistemology—a theory of knowledge—as part of the larger area of cultural capital theory. The experiences of WOC in Canadian doctoral programs are conceptualized as ‘cultural wealth’ and new knowledge because evidence reveals that the intrinsic value of their contributions has evolved from unique cultural and historical resources. The discursive theoretical frameworks of Womanist theory, critical race theory (CRT) and cultural capital theory are utilized to guide the analysis of the findings. This study establishes the experiences of the participants as valuable and distinctive knowledge by emphasizing the intersectionality of race, class, gender, culture, and spirituality. The research suggests that the experiences of women of colour are informed by an inner wisdom woven from the mosaic, or uniquely diverse paths, which these women have taken toward earning their doctorate degree. The existing interpretation of cultural capital theory originally established by Bourdieu and Passeron (1977) is considered the only social marker of wealth in socio-economical and educational research. Although previous studies have challenged this dominant perspective, this current study presents a unique interpretation of cultural capital theory by expanding the notion of cultural wealth from a Canadian perspective. This study highlights the importance of the racial/cultural context that is highly visible in Canadian culture but seldom addressed in higher education research. In addition, the aim of my study is to establish the wealth of “Mosaic Paths”
PHYSICAL ACTIVITY PROFILE OF THE PROFESSORS OF PADJADJARAN UNIVERSITY BASED ON GLOBAL PHYSICAL ACTIVITY QUESTIONNAIRE

Physical activity is one of the factors which determines one’s health and fitness, including the professors of Padjadjaran University, as it might support their academic performances. Global Physical Activity Questionnaire (GPAQ) may describe physical activity. The purpose of this study was to describe physical activity profile of the professors of Padjadjaran University based on GPAQ. Physical activity profile which was classified as gender, age group, recommendation fulfillment, and intensity variables by present-ing quantity (n) and percentage (%) was obtained from 141 professors who fulfilled the inclusion criteria. The result of this des-criptive-quantitative study showed that 109 of the respondents were male, and 32 were female. According to WHO age group cate-gories, 35 respondents were middle aged, 78 were elderly, and 28 were late elderly. Fifty-eight respondents (41.1%) did not fulfill minimal recommendation for physical activity, 114 respondents (80.8%) underwent moderate activity and 29 respondents (20.6%) underwent vigorous activity. Therefore, it can be concluded that professors of Padjadjaran University, which were mostly middle-aged men, did not fulfill minimal recommendation for physical activities, although many of them underwent moderate activities in their daily routines.
The governance of agro- and pharmaceutical biotechnology innovation: Public policy and industrial strategy

Abstract Multinational companies in the life science sector are heavily influenced by government policies and regulations and in turn attempt to influence these actors nationally and internationally. This paper focuses on recent and on-going research, principally on the agro-biotechnology and, to a lesser extent, on the pharmaceutical industries, covering the evolution of policy and regulation in Europe, how policies are influenced by stakeholder pressures and how policy in turn influences company strategies for product development. We focus particularly on new ‘governance’ agendas in Europe and consider the relative impacts of enabling, constraining, discriminating and indiscriminate policies on company strategies as part of our development of an integrated approach to policy and governance. We also consider changes in external operating environments for multinational companies and compare past histories and present pressures on agro-biotechnology and pharmaceutical companies. The paper argues, with evidence, that a more enabling and discriminating policy and regulatory environment can achieve public goals more efficiently and effectively, taking account of impacts on innovation, than more blunt policy instruments. This type of environment takes into account the resources and capabilities available to firms and research laboratories rather than relying on broad brush carrot and stick approaches.
Social identity shapes social perception and evaluation: Using neuroimaging to look inside the social brain

On February 26, 2012, 17-year-old Trayvon Martin was shot and killed by neighborhood watch captain George Zimmerman—who thought the teenager looked suspicious—sparking a national outrage and discussion about race in the United States. Why had an innocent, unarmed African American teenager died on his way home? In the aftermath, some sought answers not in explicit racism and prejudice, but rather in the domain of implicit racism—arguing, as two social psychologists wrote in an op-ed (newspaper opinion piece), that “our minds are colored by race” (Goff & Richardson, 2012, n.p.). According to a standard dual process account developed over the last 25 years, the implicit effects of race that colored George Zimmerman’s mind that night were sadly predictable. Seeing a Black face would likely trigger automatic negative evaluations and associations for Mr. Zimmerman, regardless of his explicit beliefs about race (see Devine, 1989). Moreover, due to his inexperience with Black faces, he may have failed to see Mr. Martin as an individual, but rather merely as an interchangeable member of the social category “African American. ” According to the standard dual process account, these events took place automatically and inevitably, triggered in a reflex-like manner by the salient visual cue of race. However, in this chapter, we provide evidence that the psychological and neural processes underlying person perception are context-dependent, dynamic, and shaped by motivational states, rather than inevitable, reflexive, and predictable. Specifically, we review research showing that self-categorization and social identity structure social perception and evaluation. Self-categorization involves the activation of psychological connections between the self and some class of stimuli at the personal (i.e., defining oneself as unique from others) or collective (i.e., defining oneself in terms of similar characteristics to one’s social group) level (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987; Turner, Oakes, Haslam, & McGarty, 1994). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
A unified description of cerebellar inter-spike interval distributions and variabilities using summation of Gaussians

Neuronal inter-spike intervals (ISIs) have previously been described as Poisson, Gamma, inverse Gaussian or other unimodal distributions. We analyzed ISIs of rhythmic and arrhythmic neuronal spike trains in cerebellum recorded from freely behaving rats, and found that their distributions can be described as the summation or integration of multiple Gaussian distributions. The ISIs of rhythmic cerebellar Purkinje cells have a main Gaussian peak at a basic firing interval and exponentially reduced peaks at multiples of this firing period. ISIs of arrhythmic Purkinje cells can be modeled as the integration of multiple Gaussian distributions centered at continuous intervals with exponentially reduced peak amplitudes. The sources of variability are directly related to the relative timing of action potentials between neighboring cells since we show that irregularities of discharge in one cell are associated with the previous history of its discharge in time relative to another cell. Through relative phase analyses, we demonstrate that the shape and the mathematical form of the ISI distributions in cerebellum are direct result of dynamic interactions in the nearby neuronal network, in addition to intrinsic firing properties. The analysis in this paper provides a unified description of cerebellar inter-spike interval distributions which deviate from the usual Poisson assumptions. Our results suggest the existence of an intrinsic rhythmicity in cells exhibiting arrhythmic spike trains in cerebellum, and may identify an important source of variability in neuronal firing patterns that is relevant to the mechanism of neural computation in cerebellum.
Source Term Model for an Array of Vortex Generator Vanes

A source term model was developed for numerical simulations of an array of vortex generators. The source term models the side force created by a vortex generator being modeled. The model is obtained by introducing a side force to the momentum and energy equations that can adjust its strength automatically based on a local flow. The model was tested and calibrated by comparing data from numerical simulations and experiments of a single low-profile vortex generator vane, which is only a fraction of the boundary layer thickness, over a flat plate. The source term model allowed a grid reduction of about seventy percent when compared with the numerical simulations performed on a fully gridded vortex generator without adversely affecting the development and capture of the vortex created. The source term model was able to predict the shape and size of the stream wise vorticity and velocity contours very well when compared with both numerical simulations and experimental data.
Improvement in the exciton and EHP generation rate of P3HT:PC60BM based BHJ OSCs with the incorporation of SWCNTs

In this paper the impact of SWCNTs content on the optical performance and EHP generation rate of P3HT:PC60BM based BHJ OSC is presented using the Optical transfer matrix theory and Onsager-Braun formulism. The results from our optical simulation show that the presence of SWCNTs in the active layer composite of P3HT:PC60BM based BHJ OSC improves the exciton generation rate by broadening the absorption spectra towards the NIR region. The exciton generation rate and intensity of absorption was seen to improve as the added content of SWCNT increased. Furthermore the active layer thickness dependent exciton dissociation probability and EHP generation rate was found to be optimal when the added content of SWCNT was at 1%.
SISO MAP decoding of rate-1 recursive convolutional codes: A revisit

In this paper, we revisit the BCJR soft-input soft-output (SISO) maximum a posteriori probability (MAP) decoding process of rate-1 recursive convolutional (RC) codes. From this we establish some interesting duality properties between encoding and decoding of RC codes. We observe that the forward and backward BCJR decoders can be simply represented by their dual SISO channel encoders using shift registers in the complex field. Similarly, the bidirectional MAP decoding can be implemented by linearly combining the outputs of the dual SISO encoders of the respective forward and backward decoders.
Efficient setup for multicast connections using tree-caching

The problem of finding a minimum-cast multicast tree (Steiner tree) is known as NP-complete. Heuristic-based algorithms for this problem to achieve good performance are usually time-consuming. In this paper, we propose a new strategy called tree-caching for efficient setup of multicast connections in connection-oriented networks. In this scheme, the tree topologies that have been computed are cached in a database of the source nodes and can be used for setup of subsequent connection requests which have some common multicast members. This can reduce the connection establishment time by an efficient reuse of cached trees without having to rerun a multicast routing algorithm for the whole group. This gain is obtained by eliminating, whenever possible, the expensive tree computation algorithm that has to be performed in setting up a multicast connection. We first formulate the problem of tree-caching. We then propose a tree-caching algorithm to reduce the complexity of the tree computations when a new connection is to be established. Through simulations, we find that the proposed tree-caching strategy perform well and can significantly reduce the computation complexity for setting up multicast connections.
Arabic-English Semantic Word Class Alignment to Improve Statistical Machine Translation

Clustering words is a widely used technique in statistical natural language processing. It requires syntactic, semantic, and contextual features. Especially, semantic clustering is gaining a lot of interest. It consists in grouping a set of words expressing the same idea or sharing the same semantic properties. In this paper, we present a new method to integrate semantic classes in a Statistical Machine Translation (SMT) context to improve the Arabic-English translation quality. In our method, we first apply a semantic word clustering algorithm for English. We then project the obtained semantic word classes from the English side to the Arabic side. This projection is based on available word alignments provided by the alignment step using GIZA++ tool. Finally, we apply a new process to incorporate semantic classes in order to improve the SMT quality. The experimental results show that introducing semantic word classes achieves 4 % of relative improvement on the BLEU score for the Arabic → English translation task.
Awaiting Explanation in the Field of Enterprise Architecture Management

Over the past few years, enterprise architecture management (EAM) has become increasingly popular in academia and in practice. One reason for this is that organizations seek to make use of various benefits that have been associated with EAM. However, researchers have stressed that EAM research has mainly focused on prescriptive frameworks and methodologies, whereas these concepts and associated impacts and outcomes have seen little generalization and verification to date. In this paper we explore this claim. Based on a comprehensive literature analysis, we found that prescriptive research does indeed dominate the field. However, we also found that few researchers have analyzed and generalized EAM phenomena, whereas the share of contributions to explanation and prediction is negligibly small. We summarize common EAM processes as well as impact and outcome factors that have emerged from this research and show to what extent the relationship between these components has thus far been explained.
Sparse recovery and Kronecker products

In this note will consider sufficient conditions for sparse recovery such as Spark, coherence, restricted isometry property (RIP) and null space property (NSP). Then we will discuss the solution of underdetermined linear equations when the matrix is the Kronecker product of matrices. Specially we will explain how NSP behave in the case where the matrix is the Kronecker product of matrices.