Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying Climate and Catchment Control on Hydrological Drought in the Continental United States

The evolution of hydrological drought events is a result of complex (nonlinear) interactions between climate and catchment processes. To investigate such nonlinear relationship, we integrated a machine learning modeling framework based on the random forest (RF) algorithms with an interpretation framework to quantify the role of climate and catchment controls on hydrological drought. More particularly, our framework interprets a built RF machine‐learning model to identify dominant variables and visualize their functional dependence and interaction effects on hydrological drought characteristics utilizing concepts of minimal depth, interactive depth, and partial dependence. We test our proposed modeling framework based on a set of 652 continental United States catchments with minimal human interference for a period of 1979–2010. Application of this framework indicated presence of three distinct drought regimes, which includes, Regime 1: droughts with longer duration, less frequent and lesser intensity; Regime 2: droughts with moderate duration, moderate frequency, and moderate intensity; and Regime 3: droughts with shorter duration, more frequent, and more intense. RF algorithm was able to accurately model the drought characteristics (intensity, duration, and number of events) for all the three drought regimes as a function of selected variables. It was observed that the type of dominant variables as well as their nonlinear functional relationship with hydrological droughts characteristics can vary between three selected regimes. Our interpretation framework indicated that catchment characteristics have a significant role in controlling the hydrologic drought for catchments (regime 1), whereas both climate and catchment characteristics control hydrological drought in regimes 2 and 3.
The nature and age of Mesoproterozoic strike-slip faulting based on Re–Os geochronology of syntectonic copper mineralization, Assynt Terrane, NW Scotland

In ancient basement regions such as the Lewisian Complex, NW Scotland, the ages of brittle deformation events are commonly poorly constrained owing to a lack of datable fills. An array of NW–SE sinistral and antithetic east–west dextral faults related to a regionally recognized episode of brittle shearing cut Neoarchean gneisses and c. 2.25 Ga quartz–pyrite veins close to the trace of an unexposed, regional-scale NW–SE fault. Copper–iron mineralization occurs at an intersection between an antithetic dextral fault and an older c. 2.25 Ga quartz vein. Optical microscopy, SEM and XRD analyses reveal an array of intergrown, co-genetic copper–iron sulfides, hematite and barite. Complex millimetre-thick zoned alteration rims rich in epidote occur at contacts between the sulfides and gneisses. Rhenium–osmium copper–iron sulfide geochronology yields an age of c. 1.55 Ga for the hydrothermal mineralization event associated with faulting. Fault movements demonstrably overlap with mineralization based on the asymmetric fibrous growth forms of these minerals within local dextral shears, which acted as local channelways for mineralizing fluids during and after faulting. We tentatively propose that this regionally recognized strike-slip faulting, previously termed the ‘Late Laxfordian’, should be referred to as the ‘Assyntian’ to distinguish it from kinematically distinct Laxfordian events.
Reinterpretation of Multi-Stage Methods for Stiff Systems: A Comprehensive Review on Current Perspectives and Recommendations

In this paper, we compare a multi-step method and a multi-stage method for stiff initial value problems. Traditionally, the multi-step method has been preferred than the multi-stage for a stiff problem, to avoid an enormous amount of computational costs required to solve a massive linear system provided by the linearization of a highly stiff system. We investigate the possibility of usage of multi-stage methods for stiff systems by discussing the difference between the two methods in several numerical experiments. Moreover, the advantages of multi-stage methods are heuristically presented even for nonlinear stiff systems through several numerical tests.
Genome editing in the nematode Caenorhabditis briggsae using the CRISPR/Cas9 system

Abstract The CRISPR/Cas system has recently emerged as a powerful tool to engineer the genome of an organism. The system is adopted from bacteria where it confers immunity against invading foreign DNA. This work reports the first successful use of the CRISPR/Cas system in Caenorhabditis briggsae (a cousin of the well-known nematode C. elegans), to generate mutations via non-homologous end joining. We recovered deletion alleles of several conserved genes by microinjecting plasmids that express Cas9 endonuclease and an engineered CRISPR RNA corresponding to the DNA sequence to be cleaved. Evidence for somatic mutations and off-target mutations are also reported. Our approach allows for the generation of loss-of-function mutations in C. briggsae genes thereby facilitating a comparative study of gene function.
The disrupted workplace: are the digital and group skills needs of employers being addressed by universities?

Upskilling moves quickly in today’s ‘disrupted’ workplace, and skill sets need to change to meet the needs of the digital economy (Gray, 2016), sometimes referred to as the fourth industrial revolution (4IR). Using a mixed methods approach and drawing on data from relevant stakeholders, the aim of this research is to explore, evaluate and identify any mismatch between degree learning outcomes and employability skills. The research also proposes specific strategies to address identifiable skills gaps. Focusing on the views of Fashion Management (FM) alumni, the study highlights gaps in digital skills as well as gaps in professional /group skills which some alumni felt were missing from their university education. The research also notes the importance of digital skills in the workplace from the employers’ point of view. This strengthens the argument for employers and universities to work more symbiotically to address any gaps between degree outcomes and employability skills in order to provide graduates who are ‘work ready’ for 4IR.Given the findings, the authors recommend that the data gathered be used not only to inform and enhance our FM degree, but perhaps more importantly, and in a broader educational and academic context, that universities be mindful that they fully address the changing skills requirements of future employers. While this research focuses on FM alumni and employers, because of the creativity and management which are core to this course, the findings are relevant across many related management and creative industries university courses.
Crystal surface reactivity analysis using a combined approach of X-ray micro-computed tomography and vertical scanning interferometry

Dissolution rates of porous crystalline materials reflect the superposition of transport and surface control, mainly via the parameters saturation of the ambient fluid and distribution of surface energy. As a result, reacting surfaces evolve over time showing a heterogeneous distribution of surface rates. The spatiotemporal heterogeneity of surface reaction rates is analyzed using the rate map and rate spectra concept. Here, we quantify the dissolution rate variability covering the nm- to mm-scale of dissolving single-crystal and polycrystalline calcite samples, using a combined approach of X-ray micro-computed tomography (μ-CT) and vertical scanning interferometry (VSI). The dissolution experiments cover reaction periods from 15 minutes up to 54 days. The observed rate ranges are remarkably consistent over the entire reaction period but include a variability of about two orders of magnitude (10−9 − 3 × 10−7 mol m−2 s−1). The rate map data underscore the concurrent and superimposing impact of surface- vs. fluid flow controlled rate portions. The impact of fluid flow on reactivity at the mm-scale in the transport-controlled system is confirmed by 2-D reactive transport modeling. The sub-mm spatial heterogeneity of low vs. high reactivity surface portions of polycrystalline calcite is clearly below the mean crystal size. This suggests the dominant impact of highly reactive surface portions irrespective of the orientation of larger crystals on the overall surface reactivity. Correspondingly, the overall range of intrinsic reactivity heterogeneity as observed using singly crystal material is not further expanded for polycrystalline material. As a general conclusion, numerical reactive transport concepts would benefit from the implementation of a reactivity term resembling the experimentally observed existence of multiple rate components.
Multi-Access EDGE Computing (MEC): A Mainstay of 5G

The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. Multi-access edge computing (MEC) is an emerging ecosystem, which aims at converging telecommunication and IT services, providing a cloud computing platform at the edge of the radio access network. MEC offers storage and computational resources at the edge, reducing latency for mobile end users and utilizing more efficiently the mobile backhaul and core networks. This paper introduces a survey on MEC and focuses on the fundamental key enabling technologies. This paper will review Multi-access edge computing in context to 5G. In addition, this paper analyzes the MEC reference architecture along with its pros and cons.
Evaluation of Toluidine Blue-Mediated Photodynamic Therapy for Experimental Bacterial Keratitis in Rabbits

Objective The objective of this study was to evaluate the effect of toluidine blue-mediated photodynamic therapy on experimental bacterial keratitis in rabbits. Methods Bacterial keratitis was induced in rabbits by the injection of 200 μl Staphylococcus aureus (S. aureus) solution into the anterior stroma of the right cornea. Rabbits were randomly divided into four groups: toluidine blue O and red light (TBOR), levofloxacin eye drops (LEV), the combination of TBOR and LEV (TBOR + LEV), and a control group. Clinical manifestations, histopathology, and transmission electron microscopy were analyzed at various time points. Results Conjunctival injection and surface area of the corneal ulcer in the TBOR group and the TBOR + LEV group showed significant improvement from baseline after 7 days of treatment. Compared to baseline, the depth of corneal infiltration was decreased at day 14 in the TBOR and TBOR + LEV groups. Microscopic analysis of the TBOR and TBOR + LEV groups showed that the structure of each layer was intact, and there were no inflammatory cells in the corneal stroma. Additionally, IL-1β and TNF-α were highly expressed in the LEV and control groups but were lower in the TBOR and TBOR + LEV groups. Under transmission electron microscopy, the corneas in the TBOR and TBOR + LEV groups were intact, whereas in the LEV and control groups, double-walled structures corresponding to S. aureus were found in the superficial stromal layer. Conclusions TBOR demonstrated in vivo antibacterial efficacy against S. aureus. Translational Relevance This study found in vivo antibacterial efficacy of toluidine blue-mediated photodynamic therapy on rabbit experimental bacterial keratitis, thus providing an additional new option for clinical treatment of bacterial keratitis.
Effects of dietary mulberry leaf powder on growth performance, blood metabolites, meat quality, and antioxidant enzyme-related gene expression of fattening Hu lambs

Abstract: This study was conducted to investigate the effects of the mulberry [Morus alba var. multicaulis (Perrott.) Loud. ] leaf powder (MLP) supplementation in dietary concentrates on growth performance, blood metabolites, meat quality, and antioxidant enzyme (AOE) gene expression in fattening Hu lambs. Forty approximately 3-mo-old Hu lambs (16.5 ± 0.6 kg) were randomly allocated to five groups and fed with concentrates containing 0%, 15%, 30%, 45%, or 60% MLP (control, T15, T30, T45, and T60, respectively). The results showed that 15%–30% MLP supplementation maintained growth and carcass performance, and the weight of total stomach, especially of rumen in T15 and T30, were higher than those of the control. Dietary MLP supplementation decreased serum aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, cholesterol, and triglyceride levels, but increased the high-density lipoprotein levels. Moreover, MLP supplementation improved the longissimus lumborum muscle color (redness), tenderness, and water-holding capacity. It was further observed that 15% MLP supplementation enhanced all AOE mRNA levels apart from that of EPHX1. In summary, dietary MLP supplementation could partially improve the blood metabolites, meat quality, and AOE mRNA levels in the liver of fattening Hu lamb, and the level of 15% supplementation was the most promising.
Recovering Network Structures Based on Evolutionary Game Dynamics via Secure Dimensional Reduction

The curse of dimensionality is a challenging issue in network science: the problem of inferring the network structure from sparse and noisy data becomes more and more difficult, indeed, as their dimensionality increases. We here develop a general strategy for dimensional reduction using iteratively thresholded ridge regression screener, one statistical method aiming to resolve the problem of variable selection. After drastically reducing the dimensions of the problem, we then employ the lasso method, a convex optimization method, to recover the network structure. We demonstrate the efficiency of the dimensional reduction method, and particular suitability for the natural sparsity of complex networks, in which the average degree is much smaller than their total number of nodes. Analysis based on various game dynamics and network topologies show that higher reconstruction accuracies and smaller reconstruction times can be achieved by our method. Our approach provides, therefore, a novel insight to solve the reconstruction problem and has potential applications in a wide range of fields.
Long-term Outcomes in Young Adult Survivors of Colorectal Cancer: A Population-based Study

LONG-TERM OUTCOMES IN YOUNG ADULT SURVIVORS OF COLORECTAL CANCER: A POPULATION-BASED STUDY Shawn Forbes Master of Science 2009 Graduate Department of Health Policy, Management, and Evaluation University of Toronto Introduction: This study evaluated long-term outcomes of young survivors of colorectal cancer including survival, development of acute illnesses, and childbirth. Methods: Persons aged 20-44 diagnosed with colorectal cancer and surviving at least five years were identified using the Ontario Cancer Registry and compared to randomly selected controls. Outcomes included death, admission to hospital for acute illness, and childbirth in women, determined by linkage to provincial administrative data. Results: There were 917 cancer survivors in this study. Survivors were more likely to die (HR 8.2, 95%CI [5.8, 11.6]), and require admission to hospital for acute illness (rate ratio 3.4, 95%CI [2.9, 4.1]) than controls. There was no difference in admissions for childbirth in women (HR 0.6, 95%CI [0.3, 1.4]). Conclusions: Five-year survivors of colorectal cancer remain at high risk of long-term death and illness. Aggressive surveillance for recurrent malignant disease is necessary to mitigate
Climate Sensitivity of GFDL's CM4.0

GFDL's new CM4.0 climate model has high transient and equilibrium climate sensitivities near the middle of the upper half of CMIP5 models. The CMIP5 models have been criticized for excessive sensitivity based on observations of present‐day warming and heat uptake and estimates of radiative forcing. An ensemble of historical simulations with CM4.0 produces warming and heat uptake that are consistent with these observations under forcing that is at the middle of the assessed distribution. Energy budget‐based methods for estimating sensitivities based on these quantities underestimate CM4.0's sensitivities when applied to its historical simulations. However, we argue using a simple attribution procedure that CM4.0's warming evolution indicates excessive transient sensitivity to greenhouse gases. This excessive sensitivity is offset prior to recent decades by excessive response to aerosol and land use changes.
DNA Mixtures in Forensic Investigations: The Statistical State of the Art

Forensic science has experienced a period of rapid change because of the tremendous evolution in DNA profiling. Problems of forensic identification from DNA evidence can become extremely challenging, both logically and computationally, in the presence of complicating features, such as in mixed DNA trace evidence. Additional complicating aspects are possible, such as missing data on individuals, heterogeneous populations, and kinship. In such cases, there is considerable uncertainty involved in determining whether or not the DNA of a given individual is actually present in the sample. We begin by giving a brief introduction to the genetic background needed for understanding forensic DNA mixtures, including the artifacts that commonly occur in the DNA amplification process. We then review different methods and software based on qualitative and quantitative information and give details on a quantitative method that uses Bayesian networks as a computational device for efficiently computing likelihoods. This method allows for the possibility of combining evidence from multiple samples to make inference about relationships from DNA mixtures and other more complex scenarios.
Influence of potential grazers on picocyanobacterial abundance in Lake Biwa revealed with empirical dynamic modeling

ABSTRACT Picocyanobacteria in lakes generally occur as single cells (single-celled picocyanobacteria; SPcy) or colonies (colonial picocyanobacteria; CPcy), and the latter form has been considered an adaptation to grazing pressure. In addition to direct effects of grazing, grazers may also have important indirect effects on picocyanobacteria, such as those from nutrient regeneration and trophic cascades. Interactions between picocyanobacteria and their grazers in lakes can thus be complex and difficult to predict. To evaluate the influence of various grazers on SPcy and CPcy in Lake Biwa, Japan, we followed seasonal changes in their abundances and potential grazers at 2-week intervals over 2 years. The data collected were analyzed using empirical dynamic modeling (EDM), a model-free, nonlinear time-series method. We found that heterotrophic nanoflagellates (HNF), rotifers (Keratella, Polyarthra, and Trichocerca), cladocerans, and copepods played important and differing roles in controlling the abundances of SPcy and CPcy. Notably, HNF had an apparent positive influence on SPcy abundance, despite being considered major consumers of SPcy. This result suggested that the enhancement of SPcy growth due to nutrient regeneration by HNF might exceed losses from mortality due to grazing by HNF. EDM also suggested that colony formation by picocyanobacteria may be unidirectional, with SPcy tending to form CPcy. Our findings show that the seasonal dynamics of SPcy and CPcy in Lake Biwa are influenced by a variety of grazers, which may play differing ecological roles in the aquatic food web.
An analytic formulation for positive-unlabeled learning via weighted integral probability metric

We consider the problem of learning a binary classifier from only positive and unlabeled observations (PU learning). Although recent research in PU learning has succeeded in showing theoretical and empirical performance, most existing algorithms need to solve either a convex or a non-convex optimization problem and thus are not suitable for large-scale datasets. In this paper, we propose a simple yet theoretically grounded PU learning algorithm by extending the previous work proposed for supervised binary classification (Sriperumbudur et al., 2012). The proposed PU learning algorithm produces a closed-form classifier when the hypothesis space is a closed ball in reproducing kernel Hilbert space. In addition, we establish upper bounds of the estimation error and the excess risk. The obtained estimation error bound is sharper than existing results and the excess risk bound does not rely on an approximation error term. To the best of our knowledge, we are the first to explicitly derive the excess risk bound in the field of PU learning. Finally, we conduct extensive numerical experiments using both synthetic and real datasets, demonstrating improved accuracy, scalability, and robustness of the proposed algorithm.
FACTORS ASSOCIATED WITH PHYSICAL ACTIVITY IN PATIENTS UNDERGOING BARIATRIC SURGERY

Physical activity is an important lifestyle target for post-bariatric surgery patients that may be associated with improved weight loss, lower incidence of weight regain, and improvements in selective health-related outcomes. Despite these benefits, engagement in physical activity in less than optimal in post-bariatric surgery patients. Identifying psychosocial variables associated with physical activity may lead to the development of interventions that better address the challenges to participating in physical activity experienced after bariatric surgery, and enhance physical activity in these patients. PURPOSE: To examine associations between selective psychosocial variables and physical activity in patients who had undergone bariatric surgery within the past 2 years. METHODS: Eighty-three patients who had undergone bariatric surgery (age 44.0±11.8 years, BMI 44.0±11.8 kg/m2) self-reported current physical activity and select psychosocial constructs. Additionally, participants provided retrospective information on physical activity and select psychosocial constructs prior to surgery. RESULTS: Subjects increased leisure-time physical activity by a median 508.00 (48.00, 1138.00) kcal/week from pre- to post-bariatric surgery. Physical activity was significantly associated with a number of pre- and post-surgical psychosocial constructs in the bivariate analyses; however, only social support, fitness orientation, physical function and self-classified weight emerged as significant predictors of physical activity engagement in subsequent stepwise regression analyses. CONCLUSIONS: These findings may suggest that both pre- and post-bariatric surgery intervention may need to target important constructs that include the encouragement of social support, strategies to enhance the effort individuals put forward to engage in physical activity, focus on enhancing physical function, and awareness of weight status with the goal of improving engagement in physical activity.
Integration of engineering design in early education: How to achieve it

Young boys and girls make houses and beds from cloths and cartons for their dolls, erect shelters and fences for toy animals, build ramps and garages from blocks for toy cars, and lift objects using a rope and reel for having fun. Thanks to their experiences with such design-based games, children combine science with engineering and try to understand and explain the facts and happenings around them with their own information and explanations. In recent years, the literature heavily provided marked evidence that integration of engineering design into science and maths curricula from preschool up to the end of senior high school offers various learning opportunities. Despite bearing potentials for achieving objectives of preschool education, curriculum integration poses the question of ‘How to achieve the integration’ to preschool teachers. In this research, engineering design methods were introduced to a number of preschool teachers so that they could build a learning environment on engineering design in their classes and then an account of implementation of such an activity as a part of preschool education. Keywords: Engineering design, pre-school period, STEM education.