Miracle-dz/UniFAR-FTUs huggingface dataset:
An Assessment of Global Macroeconomic Impacts Caused by Sea Level Rise Using the Framework of Shared Socioeconomic Pathways and Representative Concentration Pathways

Coastal areas provide important services and functions for social and economic activities. Damage due to sea level rise (SLR) is one of the serious problems anticipated and caused by climate change. In this study, we assess the global economic impact of inundation due to SLR by using a computable general equilibrium (CGE) model that incorporates detailed coastal damage information. The scenario analysis considers multiple general circulation models, socioeconomic assumptions, and stringency of climate change mitigation measures. We found that the global household consumption loss proportion will be 0.045%, with a range of 0.027−0.066%, in 2100. Socioeconomic assumptions cause a difference in the loss proportion of up to 0.035% without greenhouse gas (GHG) emissions mitigation, the so-called baseline scenarios. The range of the loss proportion among GHG emission scenarios is smaller than the differences among the socioeconomic assumptions. We also observed large regional variations and, in particular, the consumption losses in low-income countries are, relatively speaking, larger than those in high-income countries. These results indicate that, even if we succeed in stabilizing the global mean temperature increase below 2 °C, economic losses caused by SLR will inevitably happen to some extent, which may imply that keeping the global mean temperature increase below 1.5 °C would be worthwhile to consider.
Warming the tundra: reciprocal responses of invertebrate herbivores and plants

Rapid warming in northern ecosystems is simultaneously influencing plants, herbivores and the interactions among them. Recent studies suggest that herbivory could buffer plant responses to environmental change, but this has only been shown for vertebrate herbivores so far. The role of invertebrate herbivory in tundra ecosystems is often overlooked, but can be relevant in determining the structure and dynamics of tundra plant communities and may also affect how plants respond to warming. Invertebrate herbivores are also likely to respond more rapidly to warming than vertebrates because their behaviour and life cycles strongly depend on temperature. We investigated the effects of current season warming on Arctic moth caterpillars, their herbivory rates, and the subsequent responses of two common tundra plants, Salix arctica and Dryas octopetala. We manipulated both herbivore presence and temperature in a full-factorial field experiment at two elevations, using enclosures and passive warming chambers. Changes in temperature achieved through elevation and/or experimental warming directly affected caterpillars, herbivory and the responses of plants. Caterpillars performed worse (higher respiration rates and lower growth rates) in warmer, lower elevation plots and shifted their diets towards more nutritious foods, such that the relative intensity of herbivory changed for the two studied plants. Within-season responses of both forage plant species were weak, but invertebrate herbivores affected the responses of plants to elevation or experimental warming. Our results suggest that increased temperatures can reduce the performance of cold-adapted invertebrate herbivores, with potential consequences to the longer term responses of tundra plants to warming due to changes in herbivory rates and selective foraging.
Low Level of 25(OH)D Aggravates Target Organ Damage of Elderly Type 2 Diabetes

BACKGROUND: It is unclear about the association between vitamin D level and target organ damage in elderly patients with type 2 diabetes in China. Aim of this study was to investigate the relationship between vitamin D level and target organ damage in elderly patients with type 2 diabetes of Chinese population. METHODS: A retrospective study was performed on 254 elderly patients with type 2 diabetes (148 males and 106 females). According to assay of 25-hydroxy vitamin D [25(OH)D], the participants were divided into a deficiency group (n=129), an insufficiency group (n=77) and a sufficiency group (n=48). The clinical indicators of target organ damages among these groups were analyzed, and multivariate logistic regression analysis was performed to predict the target organ damage. RESULTS: Approximately 81.1% of patients were the low level of 25(OH)D with mean 25(OH)D below 30ng/ml. When compared with those in the sufficiency group, the level of left ventricular absolute mass index (LVMI), the morning urine albumin/uric creatinine ratio (ACR) and carotid intimal medial thickness (cIMT) increased significantly and creatinine clearance rate (CcR) decreased significantly in the deficiency group (P<0.05). The level of ACR and cIMT in the insufficiency group also increased significantly (P<0.05). There was a higher proportion in kidney, brain, artery and total target organ damage in the deficiency group or insufficiency group than those in the sufficiency group (P<0.05). Logistic regression analysis showed that low-level 25(OH)D (< 30ng/ml) was independently associated with total target organ damage in patients with elderly type 2 diabetes (OR = 3.58; 95%CI: 1.60-8.02,P =0.002) CONCLUSIONS: A condition of hypovitaminosis D is commonly present in Chinese patients with elderly type 2 diabetes. The low level of 25(OH)D may contribute to aggravate target organ damage of elderly type 2 diabetes.
Corrosion detection with ray-based and full-waveform guided wave tomography

Guided wave tomography is a very promising technique for evaluating remaining strength and durability of damaged structures. This paper evaluates the accuracy of three guided wave tomography algorithms, straight ray tomography, bent ray tomography, and full waveform inversion (FWI), to detect defects like corrosion in numerical simulations. The numerical simulations are conducted in a 1000 × 1000 × 10 mm aluminum plate with various defects. By comparing the numerical results of the three algorithms, it is demonstrated that guided wave tomography based on FWI has the highest resolution for thickness inversion. The presented study may provide a useful insight to choose appropriate guided wave tomography algorithms for nondestructive testing of plate-like structures.
Characterization of an indoor environmental chamber and identification of C1–C4 OVOCs during isoprene ozonolysis

An environmental chamber was built up and characterized at The Hong Kong Polytechnic University. The chamber consists of a 6 m3 poly tetrafluoroethylene-co-perfluoropropyl vinyl ether Teflon film reactor inside a stainless-steel enclosure stocked with a series of online gas-phase and aerosol-phase analytical instruments. Temperature and relative humidity are controllable and can be set to a range of 10–40 ± 1°C and 5–85%, ± 3%, respectively. An air purification system provides zero air for the chamber with concentrations of total volatile organic compounds < 1 ppb, NOX and O3 < 1 ppb and particles concentration < 102 particles·cm−3. Characterization experiments were performed under dry conditions (relative humidity< 5%) and ambient temperature (25°C). Average wall loss rates of O3 and NO2 were observed as 2.92 × 10−6 s−1 and 9.3 × 10−4 s−1 respectively, and the particle wall loss rate was 0.27 h−1. Dark ozonolysis of isoprene was studied using this chamber and the production of C1–C4 oxygenated volatile organic compounds such as formaldehyde, methacrolein and methyl vinyl ketone (MVK) was identified using proton-transfer-reaction time-of-flight mass spectrometry. Results of experiments indicate that this new facility can be used to investigate and simulate the gaseous chemistry and secondary aerosol formation.
A Novel Method for Sea Surface Temperature Prediction Based on Deep Learning

Sea surface temperature (SST) forecasting is the task of predicting future values of a given sequence using historical SST data, which is beneficial for observing and studying hydroclimatic variability. Most previous studies ignore the spatial information in SST prediction and the forecasting models have limitations to process the large-scale SST data. A novel model of SST prediction integrated Deep Gated Recurrent Unit and Convolutional Neural Network (DGCnetwork) is proposed in this paper. The DGCnetwork has a compact structure and focuses on learning deep long-term dependencies in SST time series. Temporal information and spatial information are all included in our procedure. Differential Evolution algorithm is applied in order to configure DGCnetwork’s optimum architecture. Optimum Interpolation Sea Surface Temperature (OISST) data is selected to conduct experiments in this paper, which has good temporal homogeneity and feature resolution. The experiments demonstrate that the DGCnetwork significantly obtains excellent forecasting result, predicting SST by different lengths flexibly and accurately. On the East China Sea dataset and the Yellow Sea dataset, the accuracy of the prediction results is above 98% on the whole and all mean absolute error (MAE) values are lower than 0.33°C. Compared with the other models, root mean square error (RMSE), root mean square percentage error (RMSPE), and mean absolute percentage Error (MAPE) of the proposed approach reduce at least 0.1154, 0.2594, and 0.3938. The experiments of SST time series show that the DGCnetwork model maintains good prediction results, better performance, and stronger stability, which has reached the most advanced level internationally.
Investigate the Equivalence of Neutrons and Protons in Single Event Effects Testing: A Geant4 Study

Neutron radiation on advanced integrated circuits (ICs) is becoming important for their reliable operation. However, a neutron test on ICs is expensive and time-consuming. In this work, we employ Monte Carlo simulation to examine if a proton test can replace or even accelerate the neutron test, and we found that 200 MeV protons are the closest to resembling neutron radiation with five main differences. This 200 MeV concur with the suggestion from National Aeronautics and Space Administration (NASA, Washington, DC, USA). However, the impacts of the five differences on single event effects (SEEs) require future work for examination.
THE ROLE OF POSITIVE INTERACTIONS IN COMMUNITIES: LESSONS FROM INTERTIDAL HABITATS

Positive interactions that result from neighbors buffering one another from stressful conditions are predictably important community forces in physically stressful habitats. Here, we examine the generality of this hypothesis in marine intertidal communities. Intertidal communities have historically played a large role in the development of community ecology since they occur across pronounced physical gradients and are easily manipulated. Positive interactions, however, have not been emphasized in studies of intertidal communities. We first review studies of intertidal marsh plant communities that suggest that positive interactions play a dominant role in the structure and dynamics of these common assemblages. We then present the results of an experimental manipulation on New England rocky shores that suggests that group benefits are as important in maintaining the upper intertidal limits of dominant spaceholders on rocky shores as the negative forces of competition and predation are in maintaining lower d.
Effects of wetness duration and temperature on infection of geranium by Botrytis cinerea

Duration and temperature of postinoculation wetness periods were investigated in relation to infection of flowers and leaves of geranium by Botrytis cinerea. Infection was assessed indirectly by estimating sporulation incidence of the pathogen in inoculated tissues. Sporulation incidence in whole flowers inoculated with conidia increased sharply when wetness duration at 15, 21, 25, and 30 degrees C was increased from 8 to 24 h, 4 to 12 h, 4 to 12 h, and 4 to 6 h, respectively. The pathogen did not sporulate after shorter wetness periods at these temperatures or after 24 h wetness at 5 and 10 degrees C. No sporulation was observed in sepals, petals, and stamens when the wet period at 25 degrees C was less than or equal to 4 h, or in pistils and pedicels when wetness lasted less than or equal to 6 h, but sporulation increased to 100, 100, 100, 73, and 60% in the respective organs as the wet period was increased to 24, 12, 12, 24, and 24 h. Following conidial inoculations of the foliage, B. cinerea sporulated in 1-week-old leaves only when the postinoculation wetness period at 15, 21, 25, and 30 degrees C was greater than or equal to 6, greater than or equal to 4, greater than or equal to 6, and greater than or equal to 6 h, respectively, and in 10-week-old leaves when wetness at the respective temperatures lasted greater than or equal to 6, greater than or equal to 6, greater than or equal to 8, and greater than or equal to 28 h. Sporulation was observed in 4-week-old leaves after greater than or equal to 12, grater than or equal to 8, and greater than or equal to 6 h wetness at 15, 21, and 25 degrees C, respectively. The pathogen did not sporulate in leaves of any age group when postinoculation wet periods were 0 to 24 h at 5 or 10 degrees C, or in 4-week-old leaves at 30 degrees C. Botrytis cinerea sporulated more frequently in 1- and 10-week-old leaves than in 4-week-old leaves when wetness lasted for 8 to 24 h at 25 degrees C. The pathogen infected leaves more efficiently when conidia were applied to geranium petals that after 24 h were positioned on the leaves, than when conidia were applied directly to the leaves. Logistic regression models were developed that adequately described effects of postinoculation wetness duration and temperature on sporulation incidence and, by inference. infection incidence, in flowers and leaves.
Bacteria in the small intestine of lichen‐fed Norwegian reindeer (Rangifer tarandus tarandus)

It has been suggested that lactic acid‐producing bacteria may protect the epithelium of the mammalian gastrointestinal tract from pathogenic micro‐organisms. Consistent with this, bacteria isolated from the mucosa of the small intestine of five lichenfed, semi‐domesticated reindeer included mainly Streptococcus spp. However, the population densities of bacteria associated with the mucosa and in the intestinal contents were generally low and there was a large amount of variation both between animals and with site of sampling. It therefore seems unlikely that Streptococcus spp. are essential for the function of the small intestine in captive reindeer, and their role here remains uncertain.
Maternal Parasite Load Increases Sprint Speed and Philopatry in Female Offspring of the Common Lizard

Organisms living in variable environments may suffer dramatic fitness losses as a consequence of fluctuations in habitat quality (Boyce and Perrins 1987). Individuals can adopt one of two strategies to reduce fitness costs associated with a deteriorating environment: either be phenotypically plastic or search for a better environment by leaving unfavorable sites. Furthermore, if individuals can receive cues about environmental conditions and can "transmit" such information to progeny, they should enjoy a considerable selective advantage. Prenatal maternal effects caused by environmental conditions encountered uring gestation are known to contribute to offspring phenotype (Herrenkohl 1979; Newman 1988; Bernardo 1991; Kaplan 1992). Two adaptive hypotheses have been proposed to explain this nongenetic form of heredity. The first, the "local adaptation hypothesis," claims that maternal effects could be a mechanism to preadapt offspring to the selective environment they are likely to encounter (Brody and Lawlor 1984; McGinley et al. 1987) by causing, for instance, offspring to grow antipredator spines, as in rotifers (Gilbert 1966). The second, the "dispersal hypothesis," postulates maternal control of offspring dispersal (Schroeder and Boag 1988; Ims 1990; Hanski et al. 1991), by forcing them to leave (Lidicker and Stenseth 1992), for instance, or by exposing them to particular hormones (Ims 1989). However, the adoption of any of these strategies will depend on their associated costs and benefits. Therefore, when dispersal is a constrained trait because of energetic osts (Shields 1987), increased aggressiveness of strangers (McShea 1990), or increased risk of predation during the dispersal phase (Christian and Tracy 1981), we should expect the prevalence of the local adaptation strategy. In this note we report an empirical test of these two hypotheses. Our study on the common lizard (Lacerta vivipara) shows that poor maternal condition during gestation, caused by ectoparasites ( ee Lehmann 1993 for a review of the impact of ectoparasites on host's fitness), affects offspring dispersal with opposite trends in males and females. "Preadaptation," measured as the ability to sprint faster (Arnold 1986), occurred only in females, which tended to be more philopatric than did males. The benefit arising from the maternal effect is expressed in terms of increased survival rate for female offspring ofparasitized mothers when compared with their male offspring.
A Study of Neural Machine Translation from Chinese to Urdu

Machine Translation (MT) is used for giving a translation from a source language to a target language. Machine translation simply translates text or speech from one language to another language, but this process is not sufficient to give the perfect translation of a text due to the requirement of identification of whole expressions and their direct counterparts. Neural Machine Translation (NMT) is one of the most standard machine translation methods, which has made great progress in the recent years especially in non-universal languages. However, local language translation software for other foreign languages is limited and needs improving. In this paper, the Chinese language is translated to the Urdu language with the help of Open Neural Machine Translation (OpenNMT) in Deep Learning. Firstly, a Chineseto Urdu language sentences datasets were established and supported with Seven million sentences. After that, these datasets were trained by using the Open Neural Machine Translation (OpenNMT) method. At the final stage, the translation was compared to the desired translation with the help of the Bleu Score Method.
Fair Network Optimization with the Cellular Network Traffic Management Model Using Lingo 13.0

This study aims to analyze the optimal internet pricing scheme model using the Cloud Radio Access Network (C-RAN) model by involving the Fair Network. C-RAN is a centralized radio access network, where the equipment used is connected to a cellular antenna to process signals and send them to the core network. This problem is solved optimally as a Mixed Integer Nonlinear Programming (MINLP) problem. The optimal financing scheme is applied to a local data server, including data hotspot traffic. The C-RAN model is modified into 2 cases and the maximum profit is obtained in case 1. The C-RAN model is formed by establishing initial consumption ( P M ) and maximum bandwidth consumption ( B 0 ). The model was completed with the help of the LINGO program. Based on the analysis that has been done, the results of this study indicate that the C-RAN model can be utilized by the Internet Service Provider (ISP) to produce the maximum solution.
Sexual differentiation in Pelmatohydra robusta. I. Response to a temperature change is dependent on the duration of an asexual period after hatching

Pelmatohydra robusta were cultured at 18°C in an asexual state for 1-8 months after hatching and then transferred to 10°C to induce sexual differentiation. When hydra were transferred to the lower temperature within a few months after hatching, they required a much longer time for the formation of mature germ cells than did hydra transferred 6-8 months after hatching. This indicates that the onset of budding in P. robusta is not always accompanied by sexual maturation. An asexual period of 6-7 months was required for P. robusta to become sufficiently mature for sexual differentiation. During the asexual period, the growth required for sexual maturation progressed uniformly within a clone, regardless of the budding status of the individual polyps. This indicates that part (or all) of a clone is not rejuvenated by budding.
ASTEROIDS: A Stixel Tracking Extrapolation-Based Relevant Obstacle Impact Detection System

This paper presents a vision-based collision-warning system for ADAS in intelligent vehicles, with a focus on urban scenarios. In most current systems, collision warnings are based on radar, or on monocular vision using pattern recognition. Since detecting collisions is a core functionality of intelligent vehicles, redundancy is essential, so that we explore the use of stereo vision. First, our approach is generic and class-agnostic, since it can detect general obstacles that are on a colliding path with the ego-vehicle without relying on semantic information. The framework estimates disparity and flow from a stereo video stream and calculates stixels. Then, the second contribution is the use of the new asteroids concept as a consecutive step. This step samples particles based on a probabilistic uncertainty analysis of the measurement process to model potential collisions. Third, this is all enclosed in a Bayesian histogram filter around a newly introduced time-to-collision versus angle-of-impact state space. The evaluation shows that the system correctly avoids any false warnings on the real-world KITTI dataset, detects all collisions in a newly simulated dataset when the obstacle is higher than 0.4 m, and performs excellent on our new qualitative real-world data with near-collisions, both in daytime and nighttime conditions.
A Bibliometric Analysis of the Intellectual Structure of Studies on Slavery in the 21st Century

Slavery is usually regarded as the dark side of business practices. However, and maybe, because of that, research on the slavery’s residues and its contemporary forms is fundamental. Therefore, we aimed to answer the following questions: What is the intellectual structure of recent publications on slavery in the business research area? How is the past of slavery remembered (or forgotten) in this century’s researches on business research area? To answer these questions, we extracted publications from the Scopus database, and then, we grouped the references using the bibliometric software Bibexcel. Finally, to identify the subgroups and to create the visualization map, we used VOSviewer. Results indicate that the intellectual structure of slavery-related studies can be grouped into nine pillars that cover diverse topics, such as heritage tourism, critical accounting and management history, and the perpetuation of the legacy of slavery in the globalized world.
Goal Estimation of Mandatory Lane Changes Based on Interaction between Drivers

In this paper, we propose a novel method to estimate a goal of surround vehicles to perform a lane change at a merging section. Recently, autonomous driving and advance driver-assistance systems are attracting great attention as a solution to substitute human drivers and to decrease accident rates. For example, a warning system to alert a lane change performed by surrounding vehicles to the front space of the host vehicle can be considered. If it is possible to forecast the intention of the interrupting vehicle in advance, the host driver can easily respond to the lane change with sufficient reaction time. This paper assumes a mandatory situation where two lanes are merged. The proposed method assesses the interaction between the lane-changing vehicle and the host vehicle on the mainstream lane. Then, the lane-change goal is estimated based on the interaction under the assumption that the lane-changing driver decides to minimize the collision risk. The proposed method applies the dynamic potential field method, which changes the distribution according to the relative speed and distance between two subject vehicles, to assess the interaction. The performance of goal estimation is evaluated using real traffic data, and it is demonstrated that the estimation can be successfully performed by the proposed method.