Miracle-dz/UniFAR-FTUs huggingface dataset:
Transduction of cultured fish cells with recombinant baculoviruses.

Five fish cell lines were tested for their ability to be transduced by Ac-CAlacZ, a recombinant baculovirus that is capable of expressing a beta-galactosidase reporter gene from the CAG promoter (consisting of a cytomegalovirus enhancer element, a chicken actin promoter and rabbit beta-globin termination sequences). TO (Tilapia ovary), EPC (carp), CHH-1 (Chum salmon heart fibroblast) and CHSE-214 (chinook salmon embryo) cells were transducible, as demonstrated by an in situ beta-galactosidase assay, whereas RTG-2 (rainbow trout gonad) cells were not. The EPC cell line was used for more detailed studies on baculovirus transduction. The transduction frequency was found to be higher at 28 degrees C than at 21 degrees C. Addition of the histone deacetylase inhibitor sodium butyrate increased the number of blue cells detected 5- to 7-fold. The m.o. i. was positively correlated with transduction frequency, although the relationship did not appear to be strictly linear, as has been observed with mammalian cells. The temperature at which baculoviruses were adsorbed to EPC cells did not affect levels of beta-galactosidase expression. We also examined expression levels of beta-galactosidase in EPC cells after infection with a baculovirus construct that overexpresses the vesicular stomatitis virus G protein and displays it on the virion surface. Expression levels with this virus were approximately 15-fold higher than were observed with Ac-CAlacZ.
Breast cancer classification: linking molecular mechanisms to disease prognosis

Breast cancer was traditionally perceived as a single disease; however, recent advances in gene expression and genomic profiling have revealed that breast cancer is in fact a collection of diseases exhibiting distinct anatomical features, responses to treatment and survival outcomes. Consequently, a number of schemes have been proposed for subtyping of breast cancer to bring out the biological and clinically relevant characteristics of the subtypes. Although some of these schemes capture underlying molecular differences, others predict variations in response to treatment and survival patterns. However, despite this diversity in the approaches, it is clear that molecular mechanisms drive clinical outcomes, and therefore an effective scheme should integrate molecular as well as clinical parameters to enable deeper understanding of cancer mechanisms and allow better decision making in the clinic. Here, using a large cohort of ∼550 breast tumours from The Cancer Genome Atlas, we systematically evaluate a number of expression-based schemes including at least eight molecular pathways implicated in breast cancer and three prognostic signatures, across a variety of classification scenarios covering molecular characteristics, biomarker status, tumour stages and survival patterns. We observe that a careful combination of these schemes yields better classification results compared with using them individually, thus confirming that molecular mechanisms and clinical outcomes are related and that an effective scheme should therefore integrate both these parameters to enable a deeper understanding of the cancer.
Discovery of a relativistic Fe line in PG 1425+267 with XMM-Newton and study of its short time-scale variability

We report results from the XMM–Newton observation of the radio-loud quasar PG 1425+267 (z= 0.366). The X-ray data above 2 keV exhibit a double-peaked emission feature in the Fe K band. The higher energy peak is found at 6.4 keV and is consistent with being narrow, while the lower energy one is detected at 5.3 keV and is much broader than the detector resolution. We confirm the significance of the detection of the broad red part of the line via Monte Carlo simulations (99.1 per cent confidence level). We explore two possible origins of the line profile, i.e., a single relativistic iron line from the accretion disc, and the superposition of a narrow 6.4-keV line from distant material and a relativistic one. We find that a contribution from a distant reflector is not required by the data. We also perform a time-resolved analysis searching for short time-scale variability of the emission line. Results tentatively suggest that the line is indeed variable on short time-scales (at the 97.3 per cent confidence level according to simulations) and better quality data are needed to confirm it on more firm statistical grounds. We also detect clear signatures of a warm absorber in the soft X-ray energy band.
A theory of cortical responses

This article concerns the nature of evoked brain responses and the principles underlying their generation. We start with the premise that the sensory brain has evolved to represent or infer the causes of changes in its sensory inputs. The problem of inference is well formulated in statistical terms. The statistical fundaments of inference may therefore afford important constraints on neuronal implementation. By formulating the original ideas of Helmholtz on perception, in terms of modern-day statistical theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. It turns out that the problems of inferring the causes of sensory input (perceptual inference) and learning the relationship between input and cause (perceptual learning) can be resolved using exactly the same principle. Specifically, both inference and learning rest on minimizing the brain's free energy, as defined in statistical physics. Furthermore, inference and learning can proceed in a biologically plausible fashion. Cortical responses can be seen as the brain’s attempt to minimize the free energy induced by a stimulus and thereby encode the most likely cause of that stimulus. Similarly, learning emerges from changes in synaptic efficacy that minimize the free energy, averaged over all stimuli encountered. The underlying scheme rests on empirical Bayes and hierarchical models of how sensory input is caused. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of cortical organization and responses. The aim of this article is to encompass many apparently unrelated anatomical, physiological and psychophysical attributes of the brain within a single theoretical perspective. In terms of cortical architectures, the theoretical treatment predicts that sensory cortex should be arranged hierarchically, that connections should be reciprocal and that forward and backward connections should show a functional asymmetry (forward connections are driving, whereas backward connections are both driving and modulatory). In terms of synaptic physiology, it predicts associative plasticity and, for dynamic models, spike-timing-dependent plasticity. In terms of electrophysiology, it accounts for classical and extra classical receptive field effects and long-latency or endogenous components of evoked cortical responses. It predicts the attenuation of responses encoding prediction error with perceptual learning and explains many phenomena such as repetition suppression, mismatch negativity (MMN) and the P300 in electroencephalography. In psychophysical terms, it accounts for the behavioural correlates of these physiological phenomena, for example, priming and global precedence. The final focus of this article is on perceptual learning as measured with the MMN and the implications for empirical studies of coupling among cortical areas using evoked sensory responses.
Real-Time Cognitive Workload Monitoring Based on Machine Learning Using Physiological Signals in Rescue Missions

High levels of cognitive workload decreases human’s performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly observable. However, cognitive workload affects several physiological signals that can be measured non-invasively. The main goal of this work is to develop a reliable machine learning algorithm to identify the cognitive workload induced during rescue missions, which is evaluated through drone control simulation experiments. In addition, we aim to minimize the computing resources usage while maximizing the cognitive workload detection accuracy for a reliable real-time operation. We perform an experiment in which 24 subjects played a rescue mission simulator while respiration, electrocardiogram, photoplethysmogram, and skin temperature signals were measured. State-of-the-art feature-based machine learning algorithms are investigated for cognitive workload characterization using learning curves, data augmentation, and cross-validation techniques. The best classification algorithm is selected, optimized, and the most informative features are selected. Finally, the generalization power of the optimized model is evaluated on an unseen test set. We obtain an accuracy level of 86% on the new unseen datasets using the proposed and optimized eXtreme Gradient Boosting (XGB) algorithm. Then, we reduce the complexity of the machine learning model for future implementation on resource-constrained wearable embedded systems, by optimizing the model and selecting the 26 most important features. Overall, a generalizable and low-complexity machine learning model for cognitive workload detection based on physiological signals is presented for the first time in the literature.
Mechanism of Cancer Cell Death Induced by Depletion of an Essential Replication Regulator

Background Depletion of replication factors often causes cell death in cancer cells. Depletion of Cdc7, a kinase essential for initiation of DNA replication, induces cancer cell death regardless of its p53 status, but the precise pathways of cell death induction have not been characterized. Methodology/Principal Findings We have used the recently-developed cell cycle indicator, Fucci, to precisely characterize the cell death process induced by Cdc7 depletion. We have also generated and utilized similar fluorescent cell cycle indicators using fusion with other cell cycle regulators to analyze modes of cell death in live cells in both p53-positive and -negative backgrounds. We show that distinct cell-cycle responses are induced in p53-positive and -negative cells by Cdc7 depletion. p53-negative cells predominantly arrest temporally in G2-phase, accumulating CyclinB1 and other mitotic regulators. Prolonged arrest at G2-phase and abrupt entry into aberrant M-phase in the presence of accumulated CyclinB1 are followed by cell death at the post-mitotic state. Abrogation of cytoplasmic CyclinB1 accumulation partially decreases cell death. The ATR-MK2 pathway is responsible for sequestration of CyclinB1 with 14-3-3σ protein. In contrast, p53-positive cancer cells do not accumulate CyclinB1, but appear to die mostly through entry into aberrant S-phase after Cdc7 depletion. The combination of Cdc7 inhibition with known anti-cancer agents significantly stimulates cell death effects in cancer cells in a genotype-dependent manner, providing a strategic basis for future combination therapies. Conclusions Our results show that the use of Fucci, and similar fluorescent cell cycle indicators, offers a convenient assay system with which to identify cell cycle events associated with cancer cell death. They also indicate genotype-specific cell death modes induced by deficient initiation of DNA replication in cancer cells and its potential exploitation for development of efficient cancer therapies.
Adaptable Neighbours: Movement Patterns of GPS-Collared Leopards in Human Dominated Landscapes in India

Understanding the nature of the interactions between humans and wildlife is of vital importance for conflict mitigation. We equipped five leopards with GPS-collars in Maharashtra (4) and Himachal Pradesh (1), India, to study movement patterns in human-dominated landscapes outside protected areas. An adult male and an adult female were both translocated 52 km, and exhibited extensive, and directional, post release movements (straight line movements: male = 89 km in 37 days, female = 45 km in 5 months), until they settled in home ranges of 42 km2 (male) and 65 km2 (female). The three other leopards, two adult females and a young male were released close to their capture sites and used small home ranges of 8 km2 (male), 11 km2 and 15 km2 (females). Movement patterns were markedly nocturnal, with hourly step lengths averaging 339±9.5 m (SE) during night and 60±4.1 m during day, and night locations were significantly closer to human settlements than day locations. However, more nocturnal movements were observed among those three living in the areas with high human population densities. These visited houses regularly at nighttime (20% of locations <25 m from houses), but rarely during day (<1%). One leopard living in a sparsely populated area avoided human settlements both day and night. The small home ranges of the leopards indicate that anthropogenic food resources may be plentiful although wild prey is absent. The study provides clear insights into the ability of leopards to live and move in landscapes that are extremely modified by human activity.
Verifiability on the run: an experimental study on the verifiability approach to malingered symptoms

Several studies on the verifiability approach found that truth-tellers report more verifiable details than liars. Therefore, we wanted to test whether such a difference would emerge in the context of malingered symptoms. We obtained statements from undergraduates (N = 53) who had been allocated to three different conditions: truth-tellers, coached malingerers and naïve malingerers. Truth-tellers carried out an intensive physical exercise and after a short interval wrote a report about their experience and elicited symptoms. The two malingering groups had to fabricate a story about the physical activity and its symptoms. Truth-tellers did not generate more verifiable details than malingerers. However, malingerers reported more non-verifiable details than truth-tellers. Coached and naïve malingerers did not differ in this respect. Relative to truth-tellers, naïve malingerers reported more symptoms-related non-verifiable details, while coached malingerers reported more exercise-related non-verifiable details. Focusing on non-verifiable details may inform the detection of malingered symptoms.
Parametric investigation of load-induced structure remodeling in the proximal femur

The process of adaptive bone remodeling can be simulated with a self-optimizing finite element method. The basic remodeling rules attempt to obtain a constant value for the strain energy per unit bone mass, by adapting density. The precise solution is dependent on the loads, initial conditions, and the parameters of the remodeling rule. While there are several investigations on developing algorithms leading to the bone density distribution in the proximal femur, these algorithms often require a large number of iterations. The aim of this study was to develop a more efficient adaptive bone remodeling algorithm, and to identify how the bone density distribution of the proximal femur was affected by parameters that govern the remodeling process. The forces at different phases of the gait cycle were applied as boundary conditions. The bone density distributions from these forces were averaged to estimate the density distribution in the proximal femur. The effect of varying the initial bone density, spatial influence function, non-linear order of the adaptive algorithm, and the influence range on the converged solution were investigated. The proposed procedure was shown to converge in a fewer number of iterations and requiring less computational time, while still generating a realistic bone density distribution. It was also shown that varying the identified parameters within reasonable upper and lower bounds had very little impact on the qualitative form of the converged solution. In contrast, the convergence rate was affected to a greater degree by variation of these parameters. In all cases, the solutions obtained are comparable with the actual density in the proximal femur, as measured by Dual-energy X-ray absorptiometry (DEXA) scans.
Teachers’ Beliefs Regarding Subtypes of Socially Withdrawn and Aggressive Behaviors on the Playground Across the Early School Years

ABSTRACT Research Findings: The purpose of this study was to examine teachers’ beliefs about and responses to children’s withdrawn behaviors (reticence and solitary-passive behavior) and aggressive behaviors (relational and physical aggression) on the playground across grades (preschool through 2nd grade) and by gender. Participants included 171 female teachers of preschool (n = 46), kindergarten (n = 45), 1st-grade (n = 41), and 2nd-grade (n = 39) classes from a Mountain West community. Overall, reticence was perceived as less appropriate than solitary-passive behavior, and physical aggression was perceived as less appropriate than relational aggression, although both forms of aggression were seen as less appropriate than both forms of withdrawal. Likewise, it was found that teachers do not take as proactive an approach to dealing with all withdrawn behaviors as they do in dealing with aggressive behaviors. Practice or Policy: Important gender differences were found and are discussed.
The Role Mining Process Model - Underlining the Need for a Comprehensive Research Perspective

Organizations that migrate from identity-centric to role-based Identity Management face the initial task of defining a valid set of roles for their employees. Due to its capabilities of automated and fast role detection, role mining as a solution for dealing with this challenge has gathered a rapid increase of interest in the academic community. Research activities throughout the last years resulted in a large number of different approaches, each covering specific aspects of the challenge. In this paper, firstly, a survey of the research area provides insight into the development of the field, underlining the need for a comprehensive perspective on role mining. Consecutively, a generic process model for role mining including pre- and post-processing activities is introduced and existing research activities are classified according to this model. The goal is to provide a basis for evaluating potentially valuable combinations of those approaches in the future.
Simple yet Effective Visuo-Spatial Topological Mapping

We describe a hybrid visuo-spatial topological approach in which global visual localization is triggered at junctions detected in a novel egocentric spatial approximation of the generalized Voronoi diagram. Transited vertices of this GVD are shown empirically to be useful and robust topological features. Visual vertex discrimination is performed without spatial cues, ameliorating junction ambiguity. Several large-scale trials are reported demonstrating fully autonomous exploration and mapping in mixed indoor/outdoor environments
Investigating instructor misbehaviors in the online classroom

ABSTRACT As online courses continue to gain popularity in higher education, researchers need to examine how instructors’ communication and behavior impact student experiences in online settings. More specifically, research that re-examines findings from the traditional, face-to-face classroom within the online class is beneficial not only for building research but also for providing educators with practical online teaching strategies. Thus, the purpose of this study was to replicate previous research examining student perceptions of instructor misbehaviors in the context of the online classroom. Results from this study highlight nine online instructor misbehavior categories, with several specific misbehaviors unique to the online classroom. Based on these categories, implications for instructors teaching online are discussed.
Human RECQ5 helicase promotes repair of DNA double-strand breaks by synthesis-dependent strand annealing

Most mitotic homologous recombination (HR) events proceed via a synthesis-dependent strand annealing mechanism to avoid crossing over, which may give rise to chromosomal rearrangements and loss of heterozygosity. The molecular mechanisms controlling HR sub-pathway choice are poorly understood. Here, we show that human RECQ5, a DNA helicase that can disrupt RAD51 nucleoprotein filaments, promotes formation of non-crossover products during DNA double-strand break-induced HR and counteracts the inhibitory effect of RAD51 on RAD52-mediated DNA annealing in vitro and in vivo. Moreover, we demonstrate that RECQ5 deficiency is associated with an increased occupancy of RAD51 at a double-strand break site, and it also causes an elevation of sister chromatid exchanges on inactivation of the Holliday junction dissolution pathway or on induction of a high load of DNA damage in the cell. Collectively, our findings suggest that RECQ5 acts during the post-synaptic phase of synthesis-dependent strand annealing to prevent formation of aberrant RAD51 filaments on the extended invading strand, thus limiting its channeling into potentially hazardous crossover pathway of HR.
A New Boson with a Mass of 125 GeV Observed with the CMS Experiment at the Large Hadron Collider

The CMS detector team describes their experiment and observation of decay products from a standard model Higgs boson, allowing its mass to be determined. The Higgs boson was postulated nearly five decades ago within the framework of the standard model of particle physics and has been the subject of numerous searches at accelerators around the world. Its discovery would verify the existence of a complex scalar field thought to give mass to three of the carriers of the electroweak force—the W+, W–, and Z0 bosons—as well as to the fundamental quarks and leptons. The CMS Collaboration has observed, with a statistical significance of five standard deviations, a new particle produced in proton-proton collisions at the Large Hadron Collider at CERN. The evidence is strongest in the diphoton and four-lepton (electrons and/or muons) final states, which provide the best mass resolution in the CMS detector. The probability of the observed signal being due to a random fluctuation of the background is about 1 in 3 × 106. The new particle is a boson with spin not equal to 1 and has a mass of about 125 giga–electron volts. Although its measured properties are, within the uncertainties of the present data, consistent with those expected of the Higgs boson, more data are needed to elucidate the precise nature of the new particle.
The Intensity of Government–Opposition Divide as Measured through Legislative Speeches and What We Can Learn from It: Analyses of Japanese Parliamentary Debates, 1953–2013

Abstract Through the analysis of legislative speeches made by prime ministers and party representatives in parliamentary sessions in Japan from 1953 to 2013, we argue that it is possible to place parties according to a dimension that captures their confrontational nature within a parliamentary democracy and its evolution over time. Using this dimension extracted via a well-known scaling algorithm (Wordfish), we develop an index of the intensity of the government–opposition divide that is directly related to the dynamics of the electoral cycle of Japanese politics. We then show how this new index greatly facilitates the investigation of two important aspects of Japanese legislative politics (the survival rate of governments and the speed of passage of cabinet bills) compared to a situation in which we focus on more traditional measures capturing the ideological position of the parties alone.