Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-assembly of modular robots from finite number of modules using graph grammars

We wish to design decentralized algorithms for self-assembly of robotic modules that have 100% yield even if the number of available building blocks is limited, and specifically when the number of available building blocks is identical to the number of blocks required by the structure. In contrast to self-assembly at the nano and micro scales where abundant building blocks are available, modular robotic systems need to self-assemble from a limited number of modules. In particular, when self-assembly is used for reconfiguration, it is desirable that the new conformation includes all of the available modules. We propose a suite of algorithms that (1) generate a reversible graph grammar, i.e., generates rules for a desired structure that allow the structure not only to assemble, but also to disassemble, and (2) have a set of structures that are growing in parallel converge to a single structure using broadcast communication. We show that by omitting a reversal rule for the last attached module, self-assembly eventually completes, and that communication can drastically speed up this process.
An Optimized GD2-Targeting Retroviral Cassette for More Potent and Safer Cellular Therapy of Neuroblastoma and Other Cancers

Neuroblastoma is the commonest extra cranial solid cancer of childhood. Despite escalation of treatment regimens, a significant minority of patients die of their disease. Disialoganglioside (GD2) is consistently expressed at high-levels in neuroblastoma tumors, which have been targeted with some success using therapeutic monoclonal antibodies. GD2 is also expressed in a range of other cancer but with the exception of some peripheral nerves is largely absent from non-transformed tissues. Chimeric Antigen Receptors (CARs) are artificial type I proteins which graft the specificity of a monoclonal antibody onto a T-cell. Clinical data with early CAR designs directed against GD2 have shown some promise in Neuroblastoma. Here, we describe a GD2-targeting CAR retroviral cassette, which has been optimized for CAR T-cell persistence, efficacy and safety.
Employer–employee relationships at Lonmin Platinum: A developing South African perspective

Abstract More than ever, companies are confronted with the importance of developing and maintaining relationships with their strategic stakeholders, such as employees. These relationships should be aimed at balancing the interests of the company with the interests of said stakeholders. Managing relationships with stakeholders is difficult in itself and even more so within the complex context of the South African mining industry. The aim of this article is to determine guidelines that could be used to ascertain employer–employee relationship type and relationship quality in the mining sector. In 2004, a quantitative questionnaire survey was conducted with a stratified quota sample of 508 company employees as part of a commissioned stakeholder perception survey. In addition, qualitative focus-group sessions were conducted to contextualise and clarify the quantitative results. The research indicated that the employer–employee relationship at Lonmin Platinum could be classified as an exchange, rather than a communal relationship. Employees generally perceived the quality of their relationship with the company in a negative way. Employees from all job levels had low levels of trust in the company. This study contributes to a growing body of research aimed at trying to understand the nature of employer–employee relations within large companies in a developing society, where companies are faced with the challenge of communicating to and managing diverse workforces.
Formation control of autonomous robots to track a moving target in an unknown environment

This paper presents a novel approach to path planning for the formation of a swarm of autonomous robots to track a moving target in an unknown environment. This approach is based on the traditional potential fields combined with the rotational vector field. The potential field is used to repel the robots away from obstacles while the rotational vector field is added to drive robots to avoid obstacles in the direction of the target's trajectory. Under the effect of the blended vector field, autonomous robots can easily escape obstacles in order to quickly reach the target. In this approach, the neighboring robots in a swarm will be linked to each other by the attractive and the repulsive vector field between them in order to generate a stable formation. Moreover, information about obstacles, which each member robot detects from the environment, will be sent to all other member robots in the swarm. Hence, the formation of the swarm is maintained while tracking a moving target. The effectiveness of this proposed approach has been verified in simulations.
Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review

More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a simulation model. Existing approaches can be used to simultaneously update several model states and model parameters if applicable. In other words, the basic principles for multivariate data assimilation are already available. We argue that a better understanding of the measurement errors for different observation types, improved estimates of observation bias and improved multiscale assimilation methods for data which scale nonlinearly is important to properly weight them in multiscale multivariate data assimilation. In this context, improved cross-validation of different data types, and increased ground truth verification of remote sensing products are required.
Cellular microenvironments reveal defective mechanosensing responses and elevated YAP signaling in LMNA-mutated muscle precursors

ABSTRACT The mechanisms underlying the cell response to mechanical forces are crucial for muscle development and functionality. We aim to determine whether mutations of the LMNA gene (which encodes lamin A/C) causing congenital muscular dystrophy impair the ability of muscle precursors to sense tissue stiffness and to respond to mechanical challenge. We found that LMNA-mutated myoblasts embedded in soft matrix did not align along the gel axis, whereas control myoblasts did. LMNA-mutated myoblasts were unable to tune their cytoskeletal tension to the tissue stiffness as attested by inappropriate cell-matrix adhesion sites and cytoskeletal tension in soft versus rigid substrates or after mechanical challenge. Importantly, in soft two-dimensional (2D) and/or static three-dimensional (3D) conditions, LMNA-mutated myoblasts showed enhanced activation of the yes-associated protein (YAP) signaling pathway that was paradoxically reduced after cyclic stretch. siRNA-mediated downregulation of YAP reduced adhesion and actin stress fibers in LMNA myoblasts. This is the first demonstration that human myoblasts with LMNA mutations have mechanosensing defects through a YAP-dependent pathway. In addition, our data emphasize the crucial role of biophysical attributes of cellular microenvironment to the response of mechanosensing pathways in LMNA-mutated myoblasts.
i-ADHoRe 3.0—fast and sensitive detection of genomic homology in extremely large data sets

Comparative genomics is a powerful means to gain insight into the evolutionary processes that shape the genomes of related species. As the number of sequenced genomes increases, the development of software to perform accurate cross-species analyses becomes indispensable. However, many implementations that have the ability to compare multiple genomes exhibit unfavorable computational and memory requirements, limiting the number of genomes that can be analyzed in one run. Here, we present a software package to unveil genomic homology based on the identification of conservation of gene content and gene order (collinearity), i-ADHoRe 3.0, and its application to eukaryotic genomes. The use of efficient algorithms and support for parallel computing enable the analysis of large-scale data sets. Unlike other tools, i-ADHoRe can process the Ensembl data set, containing 49 species, in 1 h. Furthermore, the profile search is more sensitive to detect degenerate genomic homology than chaining pairwise collinearity information based on transitive homology. From ultra-conserved collinear regions between mammals and birds, by integrating coexpression information and protein–protein interactions, we identified more than 400 regions in the human genome showing significant functional coherence. The different algorithmical improvements ensure that i-ADHoRe 3.0 will remain a powerful tool to study genome evolution.
Sex education, homosexuality, and social contestation in 1970s New Zealand

This essay examines the relationships between homosexuality and sex education in New Zealand during the 1970s. It argues that reading sex education debates and resources provides a useful way of exploring connections between the ontologies and politics of sexuality at that time. In particular, the advent of social movements concerned with sexual issues marked a turning point in homosexuality's appearance within formal and informal modes of sex education. During the 1970s, sex education and related debates became a key site at which various conceptualisations of homosexuality were constructed and contested. By analysing the struggles between radical and conservative perspectives, we can see how same‐sex desire came to symbolise changing sexual mores, as well as broader ideas about social order and social change.
A new 3D image segmentation method for parallel architectures

This paper presents a novel model for 3D image segmentation and reconstruction. It has been designed with the aim to be implemented over a computer cluster or a multi-core platform. The required features include a nearly absolute independence between the processes participating in the segmentation task and providing amount of work as equal as possible for all the participants. As a result, it is avoid many drawbacks often encountered when performing a parallelization of an algorithm that was constructed to operate in a sequential manner. Furthermore, the proposed algorithm based on the new segmentation model is efficient and shows a very good, nearly linear performance growth along with the growing number of processing units.
Non-stationary noise responses of some fully differential on-chip readout circuits suitable for CMOS image sensors

CMOS active-pixel image sensors, as well as charge-coupled devices, generate both white noise and 1/f/sup /spl alpha//-noise over several decades depending on biasing current, operating temperature, and the characteristics of the process used, limiting the detector dynamic range. Three readout circuits, based on a fully differential cascode operational transconductance amplifier, designed and realized on a standard CMOS 0.7-/spl mu/m single polysilicon/double metal process, are proposed for CMOS active-pixel imagers. The first is an uncompensated switched capacitor (SC) voltage amplifier; the second, an offset compensated SC amplifier; and the third, a commutable bandpass filter. All three amplifiers allow correlated double sampling and double delta sampling for pixel and column fixed pattern noise suppression, respectively. The amplifiers offer up to 10-Mpixels/s readout rates. A detailed theoretical analysis of the amplifiers response to white noise and low-frequency excess noise is given, considering nonstationary nature of the output signals. An original method based on diffusive Markovian representation of 1/f/sup /spl alpha//-noise is used. The theoretical results are compared with experimental data.
Text-independent compressed domain speaker verification for digital communication networks call monitoring

In this paper we present a text-independent automatic speaker verification system that works in the compressed domain using GSM AMR coded speech. While traditional approaches process LPC-based cepstral coefficients extracted from LPC related bitstream coefficients, our objective is to study the feasibility of a system that directly processes the raw bitstream transmitted over a digital communication network. In a textindependent closet-set task, with a database of 100 speakers, the proposed system achieves an EER equal to 5.93%, 4.41% and 3.80% for 10, 20 and 30 second long test speech segments respectively.
Gender similarities in work and well‐being outcomes among managers and professionals in Egypt

Purpose – This paper aims to investigate gender similarities and differences among managers and professionals working in a variety of organizations and industries in Egypt. It seeks to replicate and extend previous work by employing a different sample working in a large Muslim country.Design/methodology/approach – Data were collected from 242 respondents, 146 males and 96 females, using anonymously completed questionnaires, a 48 percent response rate. Measures included personal demographic and work situation characteristics, stable individual difference personality factors, job behaviors, work outcomes, after‐work recovery experiences, indicators of quality of life (e.g. work‐family conflict and life satisfaction) and psychological well being.Findings – There were considerable differences in personal demographic and work situation characteristics, consistent with previous findings. Females were younger, less likely to be married, worked at lower organizational levels, were less likely to supervise others,.
The Anatomy of ‘Free Choice’ Prostitution

This paper draws on an ethnographic study of a self-employed prostitute, her receptionists and her clients. It describes the prostitute's business and her working life, and considers the dynamics of power and control within the prostitute-client exchange. The paper argues that issues of control and consent in prostitution are more complex than many current feminist analyses suggest.
Where To Begin? Mapping Transcription Start Sites Genome-Wide in Escherichia coli

ABSTRACT Recent genome-wide studies of bacterial transcription have revealed large numbers of promoters located inside genes. In this issue of the Journal of Bacteriology, Thomason and colleagues (J. Bacteriol. 197:18–28, 2015, doi:10.1128/JB.02096-14) map transcription start sites in Escherichia coli on an unprecedented scale. This work provides important insights into the regulation of transcripts that initiate inside genes and sources of variability between studies aimed at identifying these RNAs.
Sport injuries as the main cause of sport career termination among Finnish top-level athletes

Abstract Injuries are common among athletes, and are sometimes so severe that they affect an athlete's career in sport. As studies on sport career termination are few, we conducted a study to investigate the role of injuries as a reason for ending a sport career. The study group consisted of 574 male and female top-level cross-country skiers, swimmers, long-distance runners and soccer players who responded to a retrospective postal questionnaire in 2006. Twenty-seven athletes (4.9%, 27/548) reported ending their sport career because of injury. A follow-up interview was conducted by telephone in 2007 (n=20 volunteered to be interviewed) to confirm sport career termination and the reasons for this. Fifteen of the interviewed athletes terminated and five continued their sport on the same level as earlier. Female athletes (12/15) terminated their sport career more frequently than male athletes (3/15). Athletes who reported terminating their sport career because of injury were on average two and a half years older (24.1 years vs. 21.6 years, P=0.006) than athletes who continued the sport. All the swimmers (n=5) who were interviewed terminated their career because of a shoulder injury. All the soccer players who ended their career (n=4) were female and had a severe knee injury, such as anterior cruciate ligament injury. Most of the athletes who terminated their sport career (70.4%, 19/27) reported that the injury caused them mild or moderate permanent disability. We found that sports injuries play a significant role in terminating a career in sport, and in some sports events injuries may commonly be the main reason for sport career termination. Injury prevention and adequate treatment and rehabilitation of injuries are thus essential to avoid the long-term consequences of severe sport injuries.
Semantic Computing and Computer Science

Semantic Computing is an emerging research field that has drawn much attention from both academia and industry. It addresses the derivation and matching of semantics of computational "content" where "content" may be anything including text, multimedia, hardware, network, etc. which can be mapped to many areas in Computer Science that involve analyzing and processing the intentions of humans with computational content. This paper discusses some potential applications of Semantic Computing in Computer Science.
Bifurcation study of three-phase inverter system with interacting loads

Plenty of distributed generation (DG) units directly export DC power such as the PV arrays. As a commercial interface, three-phase voltage-source inverters (VSIs) are commonly equipped for the power conversion from the DC power sources to the AC utility. In a practical DG system, the grid-connected loads are full of dynamics at the point of common connection (PCC). Thus, grid-connected loads inevitably have mutual interaction with VSI at PCC, which may have an impact on the stability and deteriorate the regulation capability of VSI. In this paper, the oscillatory behavior of single three-phase VSI is studied in the presence of resistive loads. The corresponding oscillation boundaries of the system are numerically collected for various circuit conditions with respect to the emergence of a low-frequency oscillation as a Hopf-type phenomenon.
Interactive Machine Translation using Hierarchical Translation Models

Current automatic machine translation systems are not able to generate error-free translations and human intervention is often required to correct their output. Alternatively, an interactive framework that integrates the human knowledge into the translation process has been presented in previous works. Here, we describe a new interactive machine translation approach that is able to work with phrase-based and hierarchical translation models, and integrates error-correction all in a unified statistical framework. In our experiments, our approach outperforms previous interactive translation systems, and achieves estimated effort reductions of as much as 48% relative over a traditional post-edition system.
A Social-Ecological Approach to Promote Self-Determination

This article describes a social-ecological approach for promoting and enhancing self-determination among individuals with developmental disabilities. A five-level model is presented, based on the interaction of person and environmental factors, that identifies a series of social mediator variables (i.e., social effectiveness, social capital, social inclusion), which the authors believe can successfully influence self-determination improvement efforts and enhance the efficacy of self-determination interventions. The impact of these mediators on intervention outcomes is considered within an interactional, social-ecological context of person-specific (individual characteristics) and environment-specific (provision of opportunities to make choices) contexts. This approach will guide the activities of a five-year National Training Consortium on self-determination involving five universities and funded by the U.S. Administration on Developmental Disabilities. The expected long-term outcomes associated with this initiative include improved self-determination options, greater social inclusion, and enhanced quality of life for people with developmental disabilities.
Experience Playing a Musical Instrument and Overnight Sleep Enhance Performance on a Sequential Typing Task

The smooth, coordinated fine motor movements required to play a musical instrument are not only highly valued in our society; they also predict academic success in areas that generalize beyond the motor domain, including reading and math readiness, and verbal abilities. Interestingly, motor skills that overlap with those required to play a musical instrument (e.g., sequential finger tapping) markedly improve (get faster) over a night of sleep, but not after a day spent awake. Here we studied whether individuals who play musical instruments that require fine finger motor skill are better able to learn and consolidate a simple motor skill task compared to those who do not play an instrument, and whether sleep-specific motor skill benefits interact with those imparted by musical experience. We used the motor sequence task (MST), which taps into a core skill learned and used by musicians, namely, the repetition of learned sequences of key presses. Not surprisingly, we found that musicians were faster than non-musicians throughout the learning session, typing more correct sequences per 30-sec trial. In the 12hrs that followed learning we found that sleep and musical experience both led to greater improvement in performance. Surprisingly, musicians retested after a day of wake performed slightly better than non-musicians who had slept between training and retest, suggesting that musicians have the capacity to consolidate a motor skill across waking hours, while non-musicians appear to lack this capacity. These findings suggest that the musically trained brain is optimized for motor skill consolidation across both wake and sleep, and that sleep may simply promote a more effective use of this machinery. In sum, there may be something special about musicians, perhaps a neurophysiological advantage, that leads to both the expected—greater motor speed at learning—and the surprising—greater motor skill improvement over time.