Miracle-dz/UniFAR-FTUs huggingface dataset:
THE BLANCO COSMOLOGY SURVEY: DATA ACQUISITION, PROCESSING, CALIBRATION, QUALITY DIAGNOSTICS, AND DATA RELEASE

The Blanco Cosmology Survey (BCS) is a 60 night imaging survey of ∼80 deg2 of the southern sky located in two fields: (α, δ) = (5 hr, −55°) and (23 hr, −55°). The survey was carried out between 2005 and 2008 in griz bands with the Mosaic2 imager on the Blanco 4 m telescope. The primary aim of the BCS survey is to provide the data required to optically confirm and measure photometric redshifts for Sunyaev–Zel'dovich effect selected galaxy clusters from the South Pole Telescope and the Atacama Cosmology Telescope. We process and calibrate the BCS data, carrying out point-spread function-corrected model-fitting photometry for all detected objects. The median 10σ galaxy (point-source) depths over the survey in griz are approximately 23.3 (23.9), 23.4 (24.0), 23.0 (23.6), and 21.3 (22.1), respectively. The astrometric accuracy relative to the USNO-B survey is ∼45 mas. We calibrate our absolute photometry using the stellar locus in grizJ bands, and thus our absolute photometric scale derives from the Two Micron All Sky Survey, which has ∼2% accuracy. The scatter of stars about the stellar locus indicates a systematic floor in the relative stellar photometric scatter in griz that is ∼1.9%, ∼2.2%, ∼2.7%, and ∼2.7%, respectively. A simple cut in the AstrOmatic star–galaxy classifier spread_model produces a star sample with good spatial uniformity. We use the resulting photometric catalogs to calibrate photometric redshifts for the survey and demonstrate scatter δz/(1 + z) = 0.054 with an outlier fraction η < 5% to z ∼ 1. We highlight some selected science results to date and provide a full description of the released data products.
Digoxin potentiates the anticonvulsant effect of carbamazepine and lamotrigine against experimental seizures in mice

The worldwide high amount of multidrug-resistant epilepsy patients makes it urgent to find new approaches to treating, including the use of combinations of classic anticonvulsants with drugs that have an exclusively original mechanism of action, in particular digoxin. The aim of this work was to investigate the influence of low-dose cardiac glycoside digoxin on the anticonvulsant effect of carbamazepine and lamotrigine. Basic models of pentylenetetrazole-induced seizures and electro-induced paroxysms (maximal electroshock [MES]) in mice were used. Classic anticonvulsants were administered intragastrically in conditionally effective and sub-effective doses at 30 min, digoxin – subcutaneously at a dose of 0.8 mg/kg ( 1 / 10 LD 50 ) at 15 min before seizures induction. Pentylenetetrazole at a dose of 80 mg/kg was administered subcutaneously. The MES was reproduced by transmitting an electric current (strength – 50 mA, frequency – 50 Hz) through the corneal electrodes for 0.2 s. It was established that the coadministration of digoxin with carbamazepine and lamotrigine in sub-effective doses renders a marked anticonvulsant action on the model of pentylenetetrazole-induced seizures as well as on seizures induced by MES. Digoxin can reduce the doses of carbamazepine and lamotrigine with a corresponding reduction in the risk of side effects without compromising treatment efficacy.
On paths with three blocks P ( k, 1 , l )

A path P ( k, r, l ) is an oriented path consisting of k forward arcs, followed by r backward arcs, and then by l forward arcs. We prove the existence of any P ( k, 1 , l ) of length n − 1 in any (2 n +2)-chromatic digraph. Moreover, if D is an n -chromatic digraph containing a Hamiltonian directed path, then it contains any P ( k, 1 , l ) of length n − 1.
Spirituality, Universal Love and Mindful Consumption: An Examination of Consumption Practices of Sri Lankan Consumer Activists

Overconsumption, driven by materialism results in many environmental and social problems. The challenge of overconsumption can be addressed, by instilling mindful consumption which is truly driven by human values such as ‘spirituality’ and ‘universal love’. Unsustainable consumption (or environmentally unfriendly consumption) emphasizes the need for change towards the wellbeing of future generations (Sharma, 2014 ). Thus, the sustainability agenda can be effectively pursued with sustainable consumption practices among consumers at the individual level (Sheth, 2011). To meet the challenge of overconsumption at individual level, both behavior and mindset of individuals need to change, which can be achieved by instilling ‘mindful consumption’ (Sheth, 2011).
Autonomous Atomic Scale Manufacturing Through Machine Learning

As the development of atom scale devices transitions from novel, proof-of-concept demonstrations to state-of-the-art commercial applications, automated assembly of such devices must be implemented. Here we present an automation method for the atomic fabrication process using deep learning. We trained a convolutional neural network to identify and locate surface features in scanning tunneling microscope images of the technologically relevant hydrogen-terminated silicon surface. Once the positions and types of surface features are determined, the predefined atomic structures are patterned in a defect-free area. Augmentation with previously developed autonomous tip shaping and patterning modules allows for atomic scale fabrication with minimal user intervention.
Gravitino condensation, supersymmetry breaking and inflation

Motivated by dualistic considerations of the reality of quark condensation in quantum chromodynamics, and the connections of supergravity to the exotic physics of string and M-theory, in this thesis we investigate the dynamical breaking of local supersymmetry via gravitino condensation. We firstly demonstrate non-perturbative gravitino mass generation via this mechanism in flat spacetime, and from this derive the condensate mode wavefunction renormalisation. By then calculating the full canonically normalised one-loop effective potential for the condensate mode about a de Sitter background, we demonstrate that, contrary to claims in the literature, this process may both occur and function in a phenomenologically viable manner. In particular, we find that outside of certain unfortunate gauge choices, the stability of the condensate is intimately tied via gravitational degrees of freedom to the sign of the tree-level cosmological constant. Furthermore, we find that the energy density liberated may provide the necessary inflation of the early universe via an effective scalar degree of freedom, provided by the condensate, acting as the inflaton. However, in so doing we find that simultaneously phenomenologically viable inflation and supersymmetry breaking via this approach are mutually incompatible in the simplest supergravity settings. As this mechanism takes place in the gravitational sector, relying on the ubiquitous gravitino torsion terms, we argue that it can also enjoy a certain universality in the context of supergravity and string theories, in that it does not rely on specific or arbitrary choices of potential and/or matter content. This then allows straightforward transplantation of these results into other settings. We present in detail our findings establishing contact between this scenario and known phenomenology, and discuss future avenues for research.
THE CONCEPTUAL MODEL FOR AGILE TECHNIQUES AND METHOD

However, there have been limited studies that have developed Agile Techniques Model that adequately compared the pros and cons of various types of agile techniques. To address these issues, we conducted our research and develop our conceptual model that provides insights and understanding on agile techniques and methods to top managements, software developers, project managers, and researchers. Our research develops the Agile Techniques Model to help explore the pros and cons of various agile techniques. The theoretical background for our research model is the stakeholder theory. The results from our model support the conclusion that the agile project quality management method developed in the last 15 years has proven to be useful when compared to the traditional method. However, the main interest of this research is to follow up on both the positive and negative factors to further test its probability. The information described in our model, proves that the agile project quality management method demonstrates both pros and cons on the techniques used within a project. The case studies from the literature in our research reiterate that agile methods increase productivity on the products for customers, but lacking communication is a common negative factor that stands out among all the cons.
A direct imaging search for close stellar and sub‐stellar companions to young nearby stars

A total of 28 young nearby stars (ages ≤60 Myr) have been observed in the Ks-band with the adaptive optics imager Naos-Conica of the Very Large Telescope at the Paranal Observatory in Chile. Among the targets are ten visual binaries and one triple system at distances between 10 and 130 pc, all previously known. During a first observing epoch a total of 20 faint stellar or sub-stellar companion-candidates were detected around seven of the targets. These fields, as well as most of the stellar binaries, were re-observed with the same instrument during a second epoch, about one year later. We present the astrometric observations of all binaries. Their analysis revealed that all stellar binaries are co-moving. In two cases (HD 119022 AB and FG Aqr B/C) indications for significant orbital motions were found. However, all sub-stellar companion candidates turned out to be non-moving background objects except PZ Tel which is part of this project but whose results were published elsewhere. Detection limits were determined for all targets, and limiting masses were derived adopting three different age values; they turn out to be less than 10 Jupiter masses in most cases, well below the brown dwarf mass range. The fraction of stellar multiplicity and of the sub-stellar companion occurrence in the star forming regions in Chamaeleon are compared to the statistics of our search, and possible reasons for the observed differences are discussed. (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Theory of electron transport and emission from a semiconductor nanotip

An effective mass based model accounting for the conduction band quantization in semiconductor nanotip is developed to describe injected electron transport and subsequent electron emission from the nanotip. A transfer matrix formalism is used to treat electron scattering induced by the variation in the tip diameter and the electron emission. Numerical analysis of the scattering and emission probabilities is performed for a simple diamond nanotip geometry. Our scattering and emission models are subsequently combined with a Monte Carlo (MC) approach to simulate electron transport through the nanotip. The MC simulations, also accounting for the phonon scattering and externally applied electric field, are performed for the nanotip and an equivalent width diamond slab. An effect of the level quantization, electron scattering due to the nanotip diameter variation, and phonon scattering on the nanotip emission properties is identified and compared with the case of the bulk slab.
Post-Newtonian evolution of massive black hole triplets in galactic nuclei – I. Numerical implementation and tests

Massive black-hole binaries (MBHBs) are thought to be the main source of gravitational waves (GWs) in the low-frequency domain surveyed by ongoing and forthcoming Pulsar Timing Array campaigns and future space-borne missions, such as {\it eLISA}. However, many low-redshift MBHBs in realistic astrophysical environments may not reach separations small enough to allow significant GW emission, but rather stall on (sub)pc-scale orbits. This "last-parsec problem" can be eased by the appearance of a third massive black hole (MBH) -- the "intruder" -- whose action can force, under certain conditions, the inner MBHB on a very eccentric orbit, hence allowing intense GW emission eventually leading to coalescence. A detailed assessment of the process, ultimately driven by the induced Kozai-Lidov oscillations of the MBHB orbit, requires a general relativistic treatment and the inclusion of external factors, such as the Newtonian precession of the intruder orbit in the galactic potential and its hardening by scattering off background stars. In order to tackle this problem, we developed a three-body Post-Newtonian (PN) code framed in a realistic galactic potential, including both non-dissipative 1PN and 2PN terms, and dissipative terms such as 2.5PN effects, orbital hardening of the outer binary, and the effect of the dynamical friction on the early stages of the intruder dynamics. In this first paper of a series devoted at studing the dynamics of MBH triplets from a cosmological perspective, we describe, test and validate our code.
Contact Interactions in Higgs-Vector Boson Associated Production at the ILC

We explore new physics (NP) effects in Higgs-vector boson associated production at a future International Linear Collider (ILC) via ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}Zh,Zhh$, using effective field theory (EFT) techniques. In particular, we focus on a certain class of dimension 6 operators, which are generated by tree-level exchanges of a new heavy vector field in the underlying theory. These operators induce new contact terms of the form $\ensuremath{\psi}\ensuremath{\psi}\ensuremath{\phi}D\ensuremath{\phi}$, involving the Standard Model (SM) fermions ($\ensuremath{\psi}$), gauge-bosons ($D$ is the covariant derivative) and the SM Higgs field ($\ensuremath{\phi}$). We investigate the high-energy behavior of these new effective interactions in ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}Zh,Zhh$, imposing bounds from electroweak precision measurements, and show that the ILC is an excellent testing ground for probing this type of NP via ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}Zh,Zhh$. We also address the validity of the EFT expansion and we study the correlation between the $hZ$ and $hhZ$ signals, which can be utilized in future searches for NP in these channels.
Radio properties of Compact Steep Spectrum and GHz‐Peaked Spectrum radio sources

Compact steep spectrum (CSS) and GHz-peaked spectrum (GPS) radio sources represent a large fraction of the extragalactic objects in flux density-limited samples. They are compact, powerful radio sources whose synchrotron peak frequency ranges between a few hundred MHz to several GHz. CSS and GPS radio sources are currently interpreted as objects in which the radio emission is in an early evolutionary stage. In this contribution I review the radio properties and the physical characteristics of this class of radio sources, and the interplay between their radio emission and the ambient medium of the host galaxy. (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Context-based pruning for scalable object detection

Most existing approaches to object detection scale linearly with the number of classes. We investigate several pruning strategies which result in sub-linear scaling. We exploit fast context classiﬁcation based on deep features to select a reduced set of detectors. This prevents the unnecessary computation of detectors which are not expected within the context. Results show a linear speed-up in the number of classes on action recognition and a 5 times speed-up for general object detection with a negligible loss of accuracy. In addition, we show how the proposed pruning strategies can be incorporated into the fully connected layers of Deep Convolutional Neural Networks.
Latent class analysis of the social determinants of health-seeking behaviour for delivery among pregnant women in Malawi

Introduction In the era of Sustainable Development Goals, reducing maternal and neonatal mortality is a priority. With one of the highest maternal mortality ratios in the world, Malawi has a significant opportunity for improvement. One effort to improve maternal outcomes involves increasing access to high-quality health facilities for delivery. This study aimed to determine the role that quality plays in women’s choice of delivery facility. Methods A revealed-preference latent class analysis was performed with data from 6625 facility births among women in Malawi from 2013 to 2014. Responses were weighted for national representativeness, and model structure and class number were selected using the Bayesian information criterion. Results Two classes of preferences exist for pregnant women in Malawi. Most of the population 65.85% (95% CI 65.847% to 65.853%) prefer closer facilities that do not charge fees. The remaining third (34.15%, 95% CI 34.147% to 34.153%) prefers central hospitals, facilities with higher basic obstetric readiness scores and locations further from home. Women in this class are more likely to be older, literate, educated and wealthier than the majority of women. Conclusion For only one-third of pregnant Malawian women, structural quality of care, as measured by basic obstetric readiness score, factored into their choice of facility for delivery. Most women instead prioritise closer care and care without fees. Interventions designed to increase access to high-quality care in Malawi will need to take education, distance, fees and facility type into account, as structural quality alone is not predictive of facility type selection in this population.
An anomaly detection method based on random convolutional kernel and isolation forest for equipment state monitoring

samples since the data are not labeled, thus the model failing to precisely characterize the normal state and leading to inaccurate detection. Cheng et al. proposed a solution by using a combination of detection loss and reconstruction loss to optimize the learning process, reducing the model’s ability of reconstructing the outliers [4]. Some traditional ML models also have similar problems, such as the OCSVM suffering from the anomalies in training which lead to bias of the support vectors [20]. Guo et al. used LOF clustering methods to preprocess the training data of OCSVM to reduce the influence of anomalous samples [7]. Most of the traditional ML based anomaly detection models are on the assumption that outliers Anomaly detection plays an essential role in health monitoring and reliability assurance of complex system. However, previous researches suffer from distraction by outliers in training and extensively relying on empiric-based feature engineering, leading to many limitations in the practical application of detection methods. In this paper, we propose an unsupervised anomaly detection method that combines random convolution kernels with isolation forest to tackle the above problems in equipment state monitoring. The random convolution kernels are applied to generate cross-dimensional and multi-scale features for multi-dimensional time series, with combining the time series decomposing method to select abnormally sensitive features for automatic feature extraction. Then, anomaly detection is performed on the obtained features using isolation forests with low requirements for purity of training sample. The verification and comparison on different types of datasets show the performance of the proposed method surpass the traditional methods in accuracy and applicability. Highlights Abstract Random convolution kernel applied in anomaly • detection for automatic feature extraction. The establishment of the initialization strategy of • the 2-D random kernel. The anomaly-sensitivity evaluation is based on • time series decomposing method. Method effectiveness are verified on varying da-• taset and with result analysis.
Revisiting Point Cloud Simplification: Supplementary Material

We implemented the projector network using three multi-layer perceptrons (MLP) followed by Batch Normalization [1] and ReLU activation functions [4]. The filter sizes were set to 64. The GNN following the stacked MLPs was also ReLU activated with a filter size of 64. Following [5, 6], we use a relatively small neighborhood size of k=7 nearest neighbors as the input graph connectivity. The initial point of FPS is randomly selected since we did not observe any influence on the performance. We selected 15 neighbours for each cluster center selected by FPS, as suggested in . The filter size of the attention-based refinement layer was set to 3, mapping the (64+3) features of the selected points to (x, y, z) coordinates. We trained our model for 150 epochs with learning rate of 0.001 and a weight decay of 0.99 on every epoch using the Adam optimizer [2].
Load Carriage and Physical Exertion Influence Soldier Emotional Responses

ABSTRACT Introduction Regular aerobic exercise benefits psychological health, enhancing mood in clinical and nonclinical populations. However, single bouts of exercise exert both positive and negative effects on emotion. Exercise reliably increases emotional arousal. Its effects on emotional valence are thought to depend on an interplay between cognitive and interoceptive factors that change as a function of exercise intensity, as studied in clinical, healthy, and athlete populations. However, special populations, such as military, first responders, and endurance athletes, have unique physical exertion requirements that can coincide with additional cognitive, physical, and environmental stressors not typical of the general population. Load carriage is one such activity. The present study examined emotional valence and arousal during sustained, heavy load carriage akin to military training and operations. Methods Thirteen (one woman) active duty soldiers completed a V̇O2max test, a 2-h loaded (up to 50% body mass) and unloaded (empty rucksack) treadmill foot march (3 mph/4% incline) on separate days, during which they rated their exertion and emotional valence and arousal every 40 min. They also completed measures of positive and negative affect and anxiety before and every 20 min after the foot march. Results Two hours of loaded foot march led to elevated perceived exertion and less positive, more negative and anxious feelings. Higher rated exertion and more negative emotion were associated with higher percent HRmax and V̇O2peak at multiple time points. Conclusions These results support affect exertion models such as the Dual Mode Theory, whereby physical exertion becomes less pleasant with increasing intensity, and provide insights into how affective responses applied contexts may help predict time to fatigue or failure.