Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Numerical Computation Method Based on Particle Swarm Optimization Algorithm

In this paper, a novel numerical computation method based on particle swarm optimization ( PSO ) was presented, including numerical integral, eigenvalues and eigenvectors of matrix, interpolation polynomial. Simulation results show that the algorithms are validated methods with high precision and powerful self-adapting. These algorithms have value in numerical calculation and engineering practice.
The organizational stratification of opportunities for work–life balance

As organizational scholars, we offer an ‘organizational stratification’ approach useful for revealing inequalities in the distribution of work–life ‘opportunities’ within and across jobs and workplaces. In doing so, we discuss the implications of historically narrow conceptualizations of workplace opportunity — typically focused on promotion only — and suggest a more expansive approach to theorizing, and in turn operationalizing, workplace opportunities essential to worker and family well‐being. We illustrate how researchers might employ an organizational stratification approach by describing an ongoing research project in which we differentiate opportunities ‘on paper’ from opportunities ‘in practice’ and examine variations in how US employers distribute work–life opportunities among lower‐skilled jobs. We demonstrate how an organizational stratification perspective can be useful for developing knowledge on the nature of inequality in the distribution of opportunities for work–life balance, and thus, for suggesting new avenues that enhance social justice in the workplace.
An efficient switching threshold-based scheduling protocol for multiuser cognitive AF relay networks

The multiuser switched diversity (MUSwiD) selection scheme is useful in reducing the required amount of channel estimations and system complexity in wireless networks. In this paper, we propose and evaluate the performance of cognitive amplify-and-forward (AF) MUSwiD relay networks where a cognitive user is selected among a set of users for data reception. The selection process is performed such that the end-to-end (e2e) signal-to-noise ratio (SNR) of the selected user satisfies a predetermined switching threshold. An upper bound on the e2e SNR of a user is used in deriving closed-form approximations for the outage probability and average symbol error probability (ASEP) of the studied system. To get more insights about the system performance, the behavior is studied in the high SNR regime. The derived analytical and asymptotic expressions are verified by Monte-Carlo simulations. Main results illustrate that the diversity order of the studied cognitive AF multiuser switched diversity relaying network is the same as its non cognitive counterpart. Also, findings show that the asymptotic results tightly converge to the derived bounds and the analytical bounds are indeed very tight, validating the accuracy of our methodology. Finally, results show the effectiveness of the proposed MUSwiD scheduling scheme in reducing the channel estimation load compared to the opportunistic scheduling where the best user is always assigned the system resources.
Scalable parallel architecture for singular value decomposition of large matrices

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications, many of them involving high dimensionality datasets and real-time response. In this paper we describe a scalable parallel processing architecture for accelerating the SVD of large m × n matrices. Based on a linear array of simple processing-units (PUs), the proposed architecture follows a double data-flow paradigm (FIFO memories and a shared-bus) for optimizing the time spent in data transferences. The PUs, which perform elemental column-pair evaluations and rotations, have been designed for an efficient utilization of available FPGA resources and to achieve maximum algorithm speed-ups. The architecture is fully scalable from a two-PU scheme to an arrangement with as many as n/2 PUs. This allows for a trade-off between occupied area and processing acceleration in the final implementation, and permits the SVD processor to be implemented both on low-cost and high-end FPGAs. The system has been prototyped on Spartan-6 and Kintex-7 devices for performance comparison.
Learning resistance mutation pathways of HIV

We propose a novel machine learning algorithm for learning mutation pathways of viruses from a population of viral DNA strands. More specifically, given a number of sequences, the algorithm constructs a phylogenetic tree that expresses the ancestry of the sequences, and at the same time builds a model describing dependencies between mutations that is consistent with the data as well as the phylogenetic tree. Our approach extends existing approaches for phylogenetic tree construction by not assuming mutations to be independent, and extends existing approaches for detecting dependencies between different positions of a sequence by not assuming the sequences to be independent.
Plasma current ramp-up experiments in QUEST

The Ohmic heating (OH) plasma currents up to 48 kA with a discharge duration of 65 ms are obtained in the Kyushu University Spherical Tokamak (QUEST) with the help of the electron cyclotron wave (ECW) and cancellation coils. In the first experimental campaign, some results were observed in the plasma current ramp-up phase which initially appeared contradictory. A smaller plasma current is obtained using an larger OH coil bias current of 8 kA while slightly larger and smoother plasma current is obtained using an lower OH coil bias current of 5 kA. We have found that the relatively short plasma current ramp-up time of 15~20 ms employed in these experiments provides the opposite vertical field to the equilibrium field due to the current induced in the vacuum chamber. The vertical field penetration time is ~5 ms, which is comparable to the current ramp-up time. Using the slower OH coil current variation in the initial OH coil current rise-up phase but with the reversed connection, a plasma current of 48 kA is obtained in 65 ms.
Growth and associations between auxology, caregiving environment, and cognition in socially deprived Romanian children randomized to foster vs ongoing institutional care.

OBJECTIVES To determine effects of improved nurturing compared with institutional care on physical growth and to investigate the association between growth and cognitive development. DESIGN A randomized controlled trial beginning in infants (mean age, 21.0 months; range, 5-32 months), with follow-up at 30, 42, and 54 months of age. SETTING Institutionalized and community children in Bucharest, Romania. PARTICIPANTS One hundred thirty-six healthy institutionalized children from 6 orphanages and 72 typically developing, never-institutionalized children. INTERVENTION Institutionalized children were randomly assigned to receive foster care or institutional care as usual. OUTCOME MEASURES Auxology and measures of intelligence over time. RESULTS Growth in institutionalized children was compromised, particularly in infants weighing less than 2500 g at birth. Mean height and weight, though not head size, increased to near normal within 12 months in foster care. Significant independent predictors for greater catch-up in height and weight included age younger than 12 months at randomization, lower baseline z scores, and higher caregiving quality, particularly caregiver sensitivity and positive regard. Baseline developmental quotient, birth weight, and height catch-up were significant independent predictors of cognitive abilities at follow-up. Each incremental increase of 1 in standardized height scores between baseline and 42 months was associated with a mean increase of 12.6 points (SD, 4.7 points) in verbal IQ (P < .05). CONCLUSIONS Foster care had a significant effect on growth, particularly with early placement and high-quality care. Growth and IQ in low-birth-weight children are particularly vulnerable to social deprivation. Catch-up growth in height under more nurturing conditions is a useful indicator of caregiving quality and cognitive improvement.
AnCora: Multilevel Annotated Corpora for Catalan and Spanish

This paper presents AnCora, a multilingual corpus annotated at different linguistic levels consisting of 500,000 words in Catalan (AnCora-Ca) and in Spanish (AnCora-Es). At present AnCora is the largest multilayer annotated corpus of these languages freely available from http://clic.ub. edu/ancora. The two corpora consist mainly of newspaper texts annotated at different levels of linguistic description: morphological (PoS and lemmas), syntactic (constituents and functions), and semantic (argument structures, thematic roles, semantic verb classes, named entities, and WordNet nominal senses). All resulting layers are independent of each other, thus making easier the data management. The annotation was performed manually, semiautomatically, or fully automatically, depending on the encoded linguistic information. The development of these basic resources constituted a primary objective, since there was a lack of such resources for these languages. A second goal was the definition of a consistent methodology that can be followed in further annotations. The current versions of AnCora have been used in several international evaluation competitions
OUTLIER DETECTION OVER DATA STREAMS

We study discovering outliers under the data stream model. The data stream model is relevant to new classes of applications involving massive datasets, such as web click stream analysis and detection of network intrusions. The frequent pattern based outlier detection method [31] is modified in the data stream environment. Instead of finding the exact frequent patterns with multiple passes, we approximate them with single pass and the error of estimated support of each frequent itemset is guaranteed not to exceed a user-specified parameter. For each coming data point, its outlier factor is computed using the frequent patterns seen so far, and the top k outliers are output to the user.
Cohort profile: The biopsychosocial religion and health study (BRHS).

How did the study come about? In The Secrets of Long Life in the National Geographic Buettner explored longevity among three communities in Sardinia Italy, Okinawa Japan, and Loma Linda California. Loma Linda is largely a community of 7th-day Adventists. In 1969 initial research found that among individuals surviving past age 35 Adventist women in California lived 3.7 years longer than their counterparts and Adventist men 6.2 years longer. In a later, larger California sample the differences were even stronger—4.4 years for women and 7.3 years for men. Exercise, vegetarian diet, not smoking, eating nuts and social support have been found to predict longevity in Adventists. Yet even when these and several psychological variables are controlled church attendance still predicts greater longevity. Interest has been increasing regarding the association of both mental and physical health with religion or spirituality. There have been a number of literature reviews that have concluded that the associations of religion and health are largely positive. In fact, Hall concluded religious attendance was more cost-effective in increasing longevity than statin-type medications. While some have questioned the quality of these research conclusions and others have pointed out that the benefits or costs of religion may vary depending on the indicator of religious involvement, there is general agreement regarding the need for more and better research on the subject. Nonetheless, Hummer and his colleagues concluded there was consistent evidence that religious attendance was associated with lower mortality risk in cross-sectional and prospective studies. They also concluded there was a need for more diverse measures of religious involvement, comparison among specific subpopulations, and a better understanding of the pathways by which religion might influence health (p. 1226). It was with this goal in mind that this Biopsychosocial Religion and Health Study was developed.
unCUT: bridging the gap from paper diary cards towards mobile electronic monitoring solutions in borderline and self-injury

This publication describes the analysis and development of an application for Borderline Personality Disorder patients, which was conducted with the assistance of 18 psychological experts from three different countries and resulted in a functional prototype containing those requirements. Nonsuicidal self-injury means deliberately harming one's own body tissue without suicidal intent and is associated with Borderline Personality Disorder. The research objective was to identify basic requirements to help those people with the support of a mobile device. Due to the lack of available mobile applications to support both patients and therapists, the novel prototype unCUT was developed and evaluated with those psychological experts throughout different iterations which ended up in 14 identified basic requirements for such an application.
Cooperative Action of Cdk1/cyclin B and SIRT1 Is Required for Mitotic Repression of rRNA Synthesis

Mitotic repression of rRNA synthesis requires inactivation of the RNA polymerase I (Pol I)-specific transcription factor SL1 by Cdk1/cyclin B-dependent phosphorylation of TAFI110 (TBP-associated factor 110) at a single threonine residue (T852). Upon exit from mitosis, T852 is dephosphorylated by Cdc14B, which is sequestered in nucleoli during interphase and is activated upon release from nucleoli at prometaphase. Mitotic repression of Pol I transcription correlates with transient nucleolar enrichment of the NAD+-dependent deacetylase SIRT1, which deacetylates another subunit of SL1, TAFI68. Hypoacetylation of TAFI68 destabilizes SL1 binding to the rDNA promoter, thereby impairing transcription complex assembly. Inhibition of SIRT1 activity alleviates mitotic repression of Pol I transcription if phosphorylation of TAFI110 is prevented. The results demonstrate that reversible phosphorylation of TAFI110 and acetylation of TAFI68 are key modifications that regulate SL1 activity and mediate fluctuations of pre-rRNA synthesis during cell cycle progression.
Computer-assisted patch clamping

Patch clamping is an electrophysiological technique that permits the measurement of ion channel activity in many different kinds of cells. Placement of the patch clamp electrodes using micromanipulators is a time consuming and complicated task due to the lack of depth perception of microscope optics and the constrained physical environment. In order to simplify this process, a software platform has been created that permits the user to easily perform not only single electrode recordings but multiple ones. The software platform provides capabilities for automatic positioning of micropipettes in specified locations on the image plane, autofocusing on selected objects, detecting visible micropipettes using image processing techniques, haptic-enabled master slave control of micromanipulators for accurate positioning of electrodes while generating virtual forces to prevent collision between micropipettes, as well as several other novel features which help the user to perform patch clamping more efficiently. The system does not require any changes in the hardware, and uses a fully software-based approach.
Dark states in electromagnetically induced transparency controlled by a microwave field

The rigorous dark-state conditions, i.e. two-photon resonance, for a Λ-type electromagnetically induced transparency (EIT) are extended with the system controlled by a microwave field. The extended dark states are extremely sensitive to the phase of the microwave field in a narrow interval. However, the dark state is no longer required for EIT in this scheme and EIT without dark states is present.
Technological Knowledge and Offshore Outsourcing: Evidence from Japanese firm-level data

This paper empirically examines the effects of knowledge capital on offshore outsourcing choices based on original survey data of Japanese firms. The results of a multinomial logit model demonstrate that firms' offshoring is positively correlated with knowledge capital measured by their R&D activities or patenting, even after controlling for other firm characteristics including productivity, capital intensity, firm age, and export status. Further, knowledge-intensive firms are more inclined to choose foreign insourcing rather than outsourcing, suggesting that firms tend to internalize their technological knowledge in offshore sourcing.
Climate change policies and endogenous technical change in a general equilibrium modelling framework : trade spillovers, knowledge stocks and rebound effects

This work is structured into three chapters, each one exploring the effectiveness of climate policies considering the formulation of endogenous technical change (ETC) from different perspectives. Including ETC in a computable general equilibrium model allows combining important feedback mechanisms that may affect the final outcome of a climate policy. The first chapter considers ETC specifically as biased-technical change in the form of trade-embodied international technology spillovers, restricted to imports of machinery and equipment. The second chapter improves the representation of ETC by building sectorspecific stocks of knowledge, which accumulate thanks to investments in R&D. The third chapter focuses on the rebound effect by means of the improved ETC model described in the previous chapter. Estratto: Diviso in tre capitoli, questo lavoro esplora l‟effettività delle politiche climatiche in relazione al tema del progresso tecnico endogeno (ETC), sotto varie prospettive. L‟inclusione dell‟ETC in un modello di equilibrio economico generale consente la combinazione di importanti meccanismi di feedback in grado di incidere sul risultato finale di una politica climatica. Il primo capitolo elabora il progresso tecnico nella forma di spillovers tecnologici derivanti dal commercio internazionale di macchinari e di capitale. Il secondo capitolo presenta una più completa rappresentazione dell‟ETC introducendo nel modello degli stock di conoscenza specifici per ogni settore, accumulabili tramite investimenti in ricerca e sviluppo. Il terzo capitolo, partendo dal modello ETC sviluppato nel capitolo precedente, si concentra sui cosiddetti effetti di rebound.
Bipartite grammar-based representations of large sparse binary matrices: Framework and transforms

In this paper, we introduce a new concept called context-free bipartite grammar (CFBG) and present a framework wherein large sparse binary matrices can be compactly represented by CFBGs. Similar to the traditional concept of context-free grammar (CFG), a CFBG consists of a set of production rules. Unlike CFGs, however, the right member of each production rule in a CFBG is a labeled bipartite graph with each edge labeled either as a variable or terminal symbol. Given a CFBG, start with its initial variable and repeatedly expand each variable labeled edge by first deleting that edge and then inserting in some manner all edges contained in the right member of that variable. The CFBG is admissible if the edge expansion process leads to a unique bipartite graph containing only terminal symbol labeled edges, in which case the CFBG is said to represent the matrix equal to the biadjacency matrix of the unique graph. Two bipartite grammar transforms, a sequential D-neighborhood pairing transform and an iterative pairing transform (IPT), are further presented to convert any binary matrix into a CFBG representing it. Experiments show that compared with popular sparse matrix storage methods such as compressed row storage and quadtree, CFBGs obtained by IPT can reduce the storage of sparse matrices significantly (by a factor of as much as 68).
Topological approximation by small simplicial complexes

Given a point-cloud dataset sampled from an underlying geometric space X, it is often desirable to build a simplicial complex S approximating the geometric or topological structure of X. For example, recent techniques in automatic feature location depend on the ability to estimate topological invariants of X. These calculations can be prohibitively expensive if the number of cells in the approximating complex S is large. Unfortunately, most existing simplicial approximation algorithms either give too many cells, or involve calculations which are tractable or valid only in low dimensional Euclidean geometry. In this paper we introduce the combinatorial Delaunay triangulation, a simplicial complex construction which can be eciently computed in arbitrary metric spaces, and which gives reliable topological approximations using comparatively few cells.
Bilinear functional equations in 2-D quantum gravity

The microscopic theories of quantum gravity related to integrable lattice models can be constructed as special deformations of pure gravity. Each such deformation is defined by a second order differential operator acting on the coupling constants. As a consequence, the theories with matter fields satisfy a set of constraints inherited from the integrable structure of pure gravity. In particular, a set of bilinear functional equations for each theory with matter fields follows from the Hirota equations defining the KP (KdV) structure of pure gravity.
Task-dependent distribution and constrained optimization of via-points for smooth robot motions

This paper presents an effective method for planning and optimizing robot motions in joint space using via-points. The via-point formulation allows for a sparse movement representation which is inherently smooth according to a minimum jerk criterion. In this research we focus on two aspects. First, we present an initialization method to find a feasible number of via-points and their distribution in time. This initialization takes the difficulty of the planning problem into account and finds a tradeoff between representation complexity (number of via-points) and optimization time. Second, we propose a two-step optimization approach to improve the via-point parameters to satisfy constraints over the whole motion duration. We show that our methods generate feasible and smooth robot motions with a high success rate for tasks of varying complexity. The methods are evaluated in simulation using four different scenarios with two different robots, a 7-DOF robot arm and a 16-DOF humanoid upper body. Additionally, the experiments with the robot arm are shown in a real-world experiment.
An Examination: Using Participatory Action Research in a Marginalized Coastal Community at Risk to Natural Hazards

This extended case study examines the appropriateness of using Participatory Action Research (PAR) in a small, marginalized coastal community at risk to natural hazards. PAR is a method of conducting high-quality research to support the social change goals of diverse cultural and ethnic communities, especially as they relate to community involvement, democracy, emancipation, and liberation (Lindsey and McGuinness (1998). PAR is not the typical research methodology for hazards research. The community’s goal was to ‘Save our heritage and our land’. They consisted of 75-80 members who primarily make their living by seafood extraction. This community has experienced social oppression and environmental events associated with living in a coastal Louisiana community. Findings suggest that PAR has its limitations, however, it does appear to be a useful research method for residents, researchers and those who want a more respectful, empowering, ground up approach to multi-user learning and social change.