Miracle-dz/UniFAR-FTUs huggingface dataset:
Vertical and horizontal light heterogeneity along gradients of secondary succession in cool‐ and warm‐temperate forests

Abstract Aims Light availability varies drastically in forests, both vertically and horizontally. Vertical light heterogeneity (i.e., patterns of light attenuation from the forest canopy to the floor) may be related to light competition among trees, while horizontal light heterogeneity (i.e., variations in light intensity at a given height within forests) may be associated with light‐niche partitioning among tree species. However, light heterogeneity in vertical and horizontal directions and their associations with forest structure are rarely studied to date. Here we report the first comprehensive study to compare the vertical and horizontal light heterogeneity in differently aged forests in two forest types. Location Twelve forest stands of different ages in cool‐temperate forests (consisting of deciduous broad‐leaved trees) and five of different ages in warm‐temperate forests (evergreen conifer and deciduous broad‐leaved trees) in Japan. Methods We measured vertical light profiles at 1‐m intervals from the understorey (1 m above the ground) to the top canopy (12–22 m depending on stands) at 16 locations for each stand (20 m × 20 m). We also measured structural parameters (diameter at breast height, height, and crown dimensions) for all major trees in these stands. Results Along the secondary successional gradients, the vertical and horizontal light heterogeneity changed in a systematic manner in both forests. The vertical light attenuation rate was steeper in early succession and more gradual in late succession, and the horizontal light heterogeneity was relatively small in early succession and more pronounced in late succession. The vertical light attenuation rate was different between the two forest types; the light intensity dropped more sharply from the canopy surface in the cool‐temperate forests due to the crown being vertically shorter and denser (i.e., higher leaf density per unit volume). Conclusion In early succession, a steeper light attenuation rate is likely related to the strong light competition among co‐occurring trees and thus a self‐thinning process. In late succession, the high spatial light heterogeneity in forests (i.e., larger horizontal light heterogeneity and gradual light attenuation rate) may allow more species to partition light, and thus may enhance species coexistence and diversity.
‘. . . It Makes Me Want to Shut Down, Cover Up’: Female Bartenders’ Use of Emotional Labour While Receiving Unwanted Sexual Attention at a Public House

This article seeks to provide a detailed account of emotional labour adopted by female bartenders when faced with unwanted sexual attention at work. In the field, I implemented an ethnographic research design and maximised opportunities for data collection through the use of interviews with eight participants and participant observations while employed at the same venue. Drawing on previous theoretical thought, the data gathered will outline the learnt, and most common, forms of display rules barstaff demonstrate while engaging with unwanted interactions, and, from the viewpoint of the female barstaff, the expected display rules envisioned by some male customers. I also detail the collapse of display rules during some unwanted scenarios (e.g. infrequent) and the inevitable impact of implementing emotional labour under the duress of unwanted encounters–emotional dissonance and burnout. I conclude with a suggestion that there is a potential for a multitude of display rules that are adopted by barstaff dependent on the customer interaction (e.g. aggressive, sickness due to intoxication) in a public house.
Cell throughput contribution rate based sleep control algorithm for energy efficiency in 5G heterogeneous networks

Heterogeneous networks (HetNets) have been a trending topic of interest for researchers in 5G technology. A HetNet structure comprises a macro cell network assisted by small cell networks such as pico cells and femto cells. This additional hardware ensures distribution of the user equipment (UE) load of the main base station (MBS) at the cost of a surge in the overall system power consumption. Optimized power consumption coupled with enhanced cell throughput by dynamic small cell ON/OFF strategy improves the energy efficiency (EE) in dense HetNets. This paper proposes two algorithms to switch the small cell ON/OFF based on cell throughput contribution rate (CTCR). CTCR is the ratio of actual cell throughput to the maximum cell throughput with full utilization of the allotted bandwidth. In the first method, the threshold to decide small cell ON/OFF has been carefully defined considering two important factors—the MBS‐SBS distance and the ratio of small cell density to UE density such that less loaded small cells that are closer to the MBS are the candidates chosen for sleep mode. In the second method, a correction factor in the computation of CTCR is introduced. It is a logarithmic function of the relative distance of the small base station (SBS) to the radius of macro cell coverage. This steps up the threshold for SBS that are close to MBS. They are more suitable sleep state candidates as their UEs can be served directly by the MBS and enable large user throughput. Simulation results show that the EE of the proposed amended CTCR method is 8% more than proposed CTCR method and 30.66% better relative to conventional load‐based sleep control method.
Adverse Selection in the Group Life Insurance Market

committed to ABSTRACT The employer-sponsored life insurance (ESLI) market is particularly susceptible to adverse selection due to community-rated premiums, guaranteed issue coverage, and the existence of a well-functioning individual market as a substitute. Using administrative payroll and healthcare claims data from a large university, we find evidence of adverse selection in the supplemental ESLI market. Employees in worse health, as measured by the Charlson’s Comorbidity Index, are more likely to elect coverage than those in better health. Nonetheless, we also find that employees typically do not increase coverage following diagnosis of a severe illness even when they can without providing evidence of insurability. Furthermore, demand estimation shows that employees are not price-sensitive and that the estimated increases in premiums due to adverse selection are unlikely to cause significant welfare loss.
Linear and Nin-Linear Carrier Control of Soft Switched Isolated Boost Converter for Low Voltage Fuel Cell Applications

- In recent years fuel cells have become prominent as a renewable source of energy to meet the society’s energy requirements. These fuel cells need boosting up of the output voltage to interface to utility grid. Isolated Full Bridge Boost converter was mostly used for this purpose in fuel cell systems. Next efficiency and output voltage regulation are the two main aspects of the converter to consider. High efficiency is achieved by reducing the switching losses using zero current switching (ZCS). Then output voltage of the converter is regulated by applying closed loop control techniques like Linear peak current mode control (LPCM) and Non- Linear Carrier Control (NLC). Simulated results of converter with and without ZCS are presented. Losses and efficiencies at various loads are measured. The results show that losses are decreased and efficiency was increased from 62.4% to 96.5% at full load with ZCS technique and output voltage is regulated to 400V with LPCM and NLC control topology.
Inversion of Left Atrial Appendage Will Cause Compressive Stresses in the Tissue: Simulation Study of Potential Therapy

In atrial fibrillation (AF), thromboembolic events can result from the particular conformation of the left atrial appendage (LAA) bearing increased clot formation and accumulation. Current therapies to reduce the risk of adverse events rely on surgical exclusion or percutaneous occlusion, each of which has drawbacks limiting application and efficacy. We sought to quantify the hemodynamic and structural loads of a novel potential procedure to partially invert the “dead” LAA space to eliminate the auricle apex where clots develop. A realistic left atrial geometry was first achieved from the heart anatomy of the Living Heart Human Model (LHHM) and then the left atrial appendage inversion (LAAI) was simulated by finite-element analysis. The LAAI procedure was simulated by pulling the elements at the LAA tip and prescribing a displacement motion along a predefined path. The deformed configuration was then used to develop a computational flow analysis of LAAI. Results demonstrated that the inverted LAA wall undergoes a change in the stress distribution from tensile to compressive in the inverted appendage, and this can lead to resorption of the LAA tissue as per a reduced stress/resorption relationship. Computational flow analyses highlighted a slightly nested low-flow velocity pattern for the inverted LAA with minimal differences from that of a model without inversion of the LAA apex. Our study revealed important insights into the biomechanics of LAAI and demonstrated the inversion of the stress field (from tensile to compressive), which &can ultimately lead the long-term resorption of the LAA.
Econometric Modelling Based on Dynamic Count Regression and China Power Supply Dataset

Traditionally, economic data of power supply is often analyzed through the count regression model due to the type of empirical data in the decision-making process. However, in reality, it is difficult to use count data model for data with autoregressive features. The main reason is that the time series features and autoregressive attributes cannot be controlled through the count regression model, which violates the assumptions set by the model. Therefore, there may be errors in the empirical analysis results. This letter firstly describes the characteristic of the count regression model and the problem, and then we refine the multiplicative autoregressive count model for dynamic count data. The model has desirable theoretical properties and is trivial to incorporate into existing models for the count data. In this study, the multiplicative autoregressive counting model for dynamic counting data is improved. The model has ideal theoretical properties and can be easily incorporated into existing economic models of counting data, especially for power supply policy analyses.
Algorithm for Determining Time Series of Phase Transformations in the Solid State Using Long-Short-Term Memory Neural Network

In the numerical analysis of manufacturing processes of metal parts, many material properties depending on, for example, the temperature or stress state, must be taken into account. Often these data are dependent on the temperature changes over time. Strongly non-linear material property relationships are usually represented using diagrams. In numerical calculations, these diagrams are analyzed in order to take into account the coupling between the properties. An example of these types of material properties is the dependence of the kinetics of phase transformations in the solid state on the rate and history of temperature change. In literature, these data are visualized Continuous Heating Transformation (CHT) and Continuous Cooling Transformation (CCT) diagrams. Therefore, it can be concluded that time series analysis is important in numerical modeling. This analysis can also be performed using neural networks. This work presents a new approach to storing and analyzing the data contained in the discussed CCT diagrams. The application of Long-Short-Term Memory (LSTM) neural networks and their architecture to determine the correct values of phase fractions depending on the history of temperature change was analyzed. Moreover, an area of research was elements that determine what type of information should be stored by LSTM network coefficients, e.g., whether the network should store information about changes of single phase transformations, or whether it would be better to extract data from differences between several networks with similar architecture. The purpose of the studied network is strongly different from typical applications of artificial neural networks. The main goal of the network was to store information (even by overfitting the network) rather than some form of generalization that allows computation for unknown cases. Therefore, the authors primarily investigated in the ability of the layer-based LSTM network to store nonlinear time series data. The analyses presented in this paper are an extension of the issues presented in the paper entitled “Model of the Austenite Decomposition during Cooling of the Medium Carbon Steel Using LSTM Recurrent Neural Network”.
Improvements for Therapeutic Intervention from the Use of Web Applications and Machine Learning Techniques in Different Affectations in Children Aged 0–6 Years

Technological advances together with machine learning techniques give health science disciplines tools that can improve the accuracy of evaluation and diagnosis. The objectives of this study were: (1) to design a web application based on cloud technology (eEarlyCare-T) for creating personalized therapeutic intervention programs for children aged 0–6 years old; (2) to carry out a pilot study to test the usability of the eEarlyCare-T application in therapeutic intervention programs. We performed a pilot study with 23 children aged between 3 and 6 years old who presented a variety of developmental problems. In the data analysis, we used machine learning techniques of supervised learning (prediction) and unsupervised learning (clustering). Three clusters were found in terms of functional development in the 11 areas of development. Based on these groupings, various personalized therapeutic intervention plans were designed. The variable with most predictive value for functional development was the users’ developmental age (predicted 75% of the development in the various areas). The use of web applications together with machine learning techniques facilitates the analysis of functional development in young children and the proposal of personalized intervention programs.
ENTANGLEMENT OF BRIGHT AND DARK MODES IN PT-SYMMETRIC NANOANTENNA

: The generic model of two coupled multimode plasmonic nanospheres with gain and loss forming a Parity-Time symmetric dimer is considered. Analytical solutions based on a quasi-static approximation are used to explore the behavior of the eigenmodes in such a coupled nanoantenna system as a function of their separation distances and their gain-loss level. It is shown that the introduction of the same amount of gain and loss modifies the composition of eigenmodes and breaks their orthogonality. The resulting entanglement of different spatial order and symmetry modes can be advantageously exploited to actively control the scattering properties of such multimode PT-symmetric nano-antennas.
Positive sequence induction motor speed control drive model for time-domain simulations

The implementation of a positive sequence model for a squirrel cage induction motor speed control drive for use in time-domain simulations of power systems is addressed. The drive model modulates the motor stator voltage magnitude and frequency to maintain constant rotor speed. A non-ideal operation of the rectifier has been assumed. The performance of the model is assessed using a three-machine nine bus WSCC equivalent system and a test distribution system. To simulate the time-domain behaviour, an independently developed simulation program is used. It shows that the behaviour of the motor model in the independently developed simulation program is comparable and coincident to the behaviour of a motor model in commercial software. Furthermore, the need to include induction motor speed drive models in commercial software to analyse the behaviour of realistic systems is highlighted.
Effects of Landscape Configuration on the Body Condition of Migratory and Resident Tropical Birds

Landscape structure and configuration may affect bird body condition, with contrasting effects on resident and migratory species. There is little empirical evidence to support this hypothesis in tropical regions, where land-use change poses a major threat to biodiversity. We aimed to assess the effects of landscape structure and configuration on the body condition of neotropical migrant and resident bird species. We compiled body condition data (using the scaled mass index) of nine bird species (five resident and four migratory). We characterized landscape structure and configuration at 26 localities. We evaluated the effects of landscape metrics on bird body condition using Bayesian linear mixed models. The landscapes in our study largely varied in forest, crop, and grassland cover, as well as in landscape metrics. When we examined migrant birds, we found a positive effect of landscape connectivity and crop cover on body condition. Similarly, body condition of resident birds was positively affected by connectivity and crop cover, but also by forest patch area and capture day. Changes in landscape structure and configuration may indirectly alter the access to resources, causing additional energy expenditures, leading to a deteriorated body condition. Conversely, landscape heterogeneity may have a positive effect on bird body condition. Therefore, we recommend maintaining connectivity and complementary resources in the landscape.
Terazosin versus Alfuzosin in Treatment of Acute Urinary Retention in Patients with Benign Prostatic Hypertroph

Objective To compare the efficacy and adverse reactions of terazosin and alfuzosin in treatment of acute urinary retention in patients with benign prostatic hypertrophy. Design Case control study. Setting Emergency department of a regional hospital in Hong Kong. Methods Our study included all adult male with age at least 18 years old presented with acute urinary retention, having residual urine volume greater than or equal to 300 ml after urinary catheterisation and with a presumed diagnosis of benign prostatic hypertrophy. Patients treated with terazosin from December 2013 to February 2014 were retrospectively included while patients treated with alfuzosin from April to September 2014 were prospectively included. We compared the two groups on: trial without catheter (TWOC) rate, potential adverse effects including drug-associated postural hypotension, haemodynamic changes and prolongation of corrected QT interval in electrocardiogram. Cost effectiveness analysis was performed. Results A total of 116 patients were included with 59 and 57 patients in the terazosin and alfuzosin group respectively. Logistic regression showed that residual urine volume (odds ratio [OR]=0.998, 95% confidence interval [CI]=0.996-0.999, p=0.008) and presence of precipitating factors (OR=2.264, 95% CI=1.045-5.793, p=0.045) were independent predictors of successful TWOC. There was no significant difference in the TWOC rate for patients treated with alfuzosin and terazosin. There was significantly more symptomatic postural hypotension in the terazosin group compared with the alfuzosin group. The number need to treat with alfuzosin for terazosin to avoid one adverse drug effect was 12.3 patients (95% CI=4.7-21.6) and 9.9 patients (95% CI=5.3-84.6) to reduce one postural hypotension and symptomatic postural hypotension respectively. Conclusions Alfuzosin is comparable to terazosin in TWOC rate. However, alfuzosin is associated with a lower rate of symptomatic postural hypotension and less haemodynamic impact than terazosin. (Hong Kong j.emerg.med. 2015;22:210-218)
Embeddings and Distance-based Demand for Differentiated Products

We propose a simple method to estimate demand in markets for differentiated products. The method augments price and quantity data with triplets data (of the form "product A is closer to B than it is to C'') obtained from an online survey. Using a machine learning algorithm, the triplets data are used to estimate an embedding---i.e., a low-dimensional representation of the latent product space. Distances between pairs of products, computed from the embedding, discipline substitution patterns in a simple log-linear demand model. This approach solves the dimensionality problem of product-space demand models (too many cross-price elasticity parameters to estimate). We illustrate the performance of the method by estimating demand for ready-to-eat cereals and comparing our estimates to those obtained from the standard method of (BLP). We find that our elasticity estimates imply credible substitution patterns and compare favorably to the BLP estimates. Beyond our current implementation of the method, the embedding data can be incorporated in either characteristic-space demand approaches, or in more complex product-space models. Full paper available at https://papers.ssrn. com/ sol3/papers.cfm? abstract_id=4113399.
Fear Among the Feared: Arab Americans’ Fear of Crime in an Ethnic Enclave Community

Drawing on racial threat hypothesis and in-depth interviews with first- and second-generation Arab immigrants, this study explores Arab immigrants’ perceptions of risk and fear of crime in an ethnic enclave community. We find that Arab immigrants’ fear of crime is shaped by the unique context in which they live, with this particular population perceiving members of other minority groups as the greatest threat to their culture, community, and safety. This study extends the minority threat perspective, which typically highlights the majority group’s fear of immigrants and other minorities, by examining the inverse of this relationship. Specifically, what and who do immigrants fear at a time when they are perceived as one of the most threatening populations in the U.S.?
E-learning: new strategies and trends

The aim of this paper is to present a personal point of view on the possible future trends in distance learning. The starting point of this study is represented by a review of the main innovations in digital and information technologies. This step is necessary since the evolution of distance learning is strictly correlated to the evolution of the technology that can be exploited to increase learning quality. The main arguments discussed in this paper are: massive open on-line courses (MOOCs), flipped classrooms and the evolution of the learning objects based on web and on internet technology. Concerning MOOCs, a critical analysis of the status of this type of learning is necessary to understand their possible evolution and/or their substitution. A huge number of case studies demonstrated the validity of the flipped classroom and the possibility to adopt this approach into e-learning is surely interesting. The last part of the paper is instead dedicated to future technologies like: mobile learning, 3D virtual laboratories and internet of things. As discussed, this latest innovations can push the evolution of distance learning offering real student-centered solutions.