Miracle-dz/UniFAR-FTUs huggingface dataset:
CMIP5 permafrost degradation projection:A comparison among different regions

The considerable impact of permafrost degradation on hydrology and water resources, ecosystems, human engineering facilities, and climate change requires us to carry out more in‐depth studies, at finer spatial scales, to investigate the issue. In this study, regional differences of the future permafrost changes are explored with respect to the regions (high altitude and high latitude, and in four countries) based on the surface frost index (SFI) model and multimodel and multiscenario data from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Results show the following: (1) Compared with seven other sets of driving data, Climatic Research Unit air temperature combined with Climate Forecast System Reanalysis snow data (CRU_CFSR) yield a permafrost extent with the least absolute area bias and was thus used in the simulation. The SFI model, driven by CRU_CFSR data climatology plus multimodel mean anomalies, produces a present‐day (1986–2005) permafrost area of 15.45 × 106 km2 decade−1, which compares reasonably with observations of 15.24 × 106 km2 decade−1. (2) The high‐altitude (Tibetan Plateau) permafrost area shows a larger decreasing percentage trend than the high‐latitude permafrost area. This indicates that, in terms of speed, high‐altitude permafrost thaw is faster than high‐latitude permafrost, mainly due to the larger percentage sensitivity to rising air temperature of the high‐altitude permafrost compared to the high‐latitude permafrost, which is likely related to their thermal conditions. (3) Permafrost in China shows the fastest thaw, which is reflected by the percentage trend in permafrost area, followed by the United States, Russia, and Canada. These discrepancies are mainly linked to different percentage sensitivities of permafrost areas in these four countries to air temperature change. (4) In terms of the ensemble mean, permafrost areas in all regions are projected to decrease by the period 2080–2099. Under representative concentration pathway (RCP)4.5, permafrost retreats toward the Arctic, and the thaw in every region mainly occurs at the southern edge of the permafrost area. Under RCP8.5, almost no permafrost is expected to remain in China, the United States, and the Tibetan Plateau. Permafrost in Russia will remain mainly in the western part of the east Siberian Mountains, and permafrost in Canada will retreat to the north of 65°N. Possible uncertainties in this study are primarily attributed to the climate model's coarse horizontal resolution. The results of the present study will be useful for understanding future permafrost degradation from the regional perspective.
On the design and fabrication of a large GTEM cell and its challenges

This paper presents the design of a large Gigahertz Transverse Electromagnetic (GTEM) cell for Electrical/Electronic Sub-Assembly (ESA) testing of a car or other information technology (IT) equipment as well as the challenges of its design and fabrication. The 7.5 meter long and 4 meter width and 4 meter height dimensions of this cell are large enough to test ESAs inside. The operating frequency band is from 30 MHz to 6 GHz based on CISPR standards. To increase the operating frequency of the GTEM and to improve the uniformity of the wave, hybrid absorbers are mounted at the end wall. These absorbers consist of ferrite tile and pyramid absorbers, which have large bandwidth and high performance. The dimensions of the GTEM cell are too large and therefore full wave simulation is difficult and time consuming. In this paper, we have introduced a two-step method to convert a pyramidal absorber into a one-layer flat absorber. This technique simplifies our GTEM cell full wave simulation. On the fabrication side, the effect of distortion of a long metal sheet on the performance of the room are numerically examined. Finally, the acceptable measurement results of the GTEM are reported.
High-Precision and Modular Decomposition Control for Large Hydraulic Manipulators

It is difficult to achieve a high-precision motion control in hydraulic manipulators due to their structural redundancy, strong coupling of closed-chain structures, and flow–pressure coupling. In this paper, a high-precision motion control method for hydraulic manipulators is proposed based on the traditional virtual decomposition control (VDC). The method proposed avoids an excessive virtual decomposition of the hydraulic manipulator and requires fewer model parameters than the traditional VDC. Further, the control precision improved by combining an adaptive real-time update of the inertial parameters. Compared with MBC, the proposed control method improved the motion accuracy of the hydraulic manipulator by more than 40% and 20% under elliptical and triangular trajectories. The simulation results showed that the proposed control method reduced the maximum position errors in Cartesian space by 90.4%, 86.8%, 23.6%, and 44.3% compared with PID and model-based control (MBC) in the absence of disturbances. The maximum position error in Cartesian space was reduced by 76.5% compared with that of MBC in a simulation with external disturbances. It can be seen from all the simulation results that with the proposed control method, the position error of the manipulator was less than 50 mm. The proposed control method effectively improved the motion precision of the examined hydraulic manipulator.
Ethical Theories and Controversial Intuitions

ABSTRACT We have controversial intuitions about the rightness of retributive punishment, keeping promises for its own sake, and pushing the heavy man off of the bridge in the footbridge trolley case. How do these intuitions relate to ethical theories? Should ethical theories aim to fit with and explain them? Or are only uncontroversial intuitions relevant to explanatory ethical theorising? I argue against several views that we might hold about the relationship between controversial intuitions and ethical theories. I then propose and defend the view that ethical theories should only aim to fit with and explain the intuitions that almost all people (who minimally understand the relevant issues) share. I argue that this view has interesting and important implications for ethical theorising and theorising about justice and equality.
Noise-Aware Optimization for Mobile Crowdsensing-Based Travel Time Estimation

Predicting the estimated time of arrival (ETA) is crucial for ride-hailing platforms and autonomous vehicle systems. Although deep neural network-based models have demonstrated high accuracy in ETA prediction, their loss functions often assume standard noise distribution, which fails to account for the noise distribution in real-world mobile crowdsensing travel orders. This study investigates the dynamic noise distribution in practical travel orders and identifies two key types of noise in ETA prediction: intrinsic noise at the start or end of the order and accumulated noise during travel. To address this issue, we propose a novel method called Noise-aware Optimization (NAO) for ETA prediction that generates dynamic noise distributions from real-world datasets and optimizes the ETA model through maximum likelihood estimation accordingly. We provide two specific forms of NAO for ETA prediction with Gaussian and Laplace noise distributions, respectively, to facilitate practical applications. Additionally, we compare commonly used regression loss functions with NAO under a probability interpretation to illustrate the principle of NAO. Our experiments conducted on the DiDi platform in two large cities demonstrate the superior effectiveness of NAO over other loss functions.
Laboratory Experiments on Form and Structure of Longshore Bars and Beaches

Beaches and bars have been formed during experiments conducted in a 46-foot wave tank at the Sedimentation Laboratory of the U.S. Geological Survey in Denver. By changing one variable factor at a time, elements responsible for major differences in primary structure and in shape of sand body have been determined. These elements are--differences in slope of sand floor (expressed in terms of water depth), intensity of wave action, and supply of sand. Stages in the growth of the bars and beaches were marked with dark layers of magnetite, and cross sections were preserved on masonite boards coated with liquid rubber, thus recording cross-stratification patterns and sand-body shapes. Longshore bars are produced at the point of wave break. In very shallow water an emergent bar commonly forms; in somewhat deeper water a submarine bar is built; and in still deeper water no bar forms. Increase in intensity of waves tends to build a bar toward, and even onto, the beach. Weaker waves build bars upward to form barriers, with lagoons to shoreward. Abundant sand furnished on the seaward side of a growing bar simulates conditions caused by some longshore and rip currents, and causes gentle seaward-dipping beds to form. In contrast, a limited sand supply results in growth of bars that characteristically have shoreward-dipping strata of steeper angle. Beach strata normally dip seaward at low angles from the crest to a point below water level. Offshore, the seaward extensions of these gently dipping beds include fore-set beds with relatively high angles which form a shoreface terrace. The sand body comprised of both sets of bedding builds outward if a large supply of sand is furnished. In shallow water, however, or at moderate depth where waves are strong, the period of beach growth is limited by the deposition of longshore bars which eliminate wave action as they grow into barriers and form lagoons. Under conditions in which no bar is built, growth of the beach and shoreface terrace is controlled by the amount of sand available; the proportion of top-set to fore-set beds is determined by the strength of waves.
Global pesticide consumption and pollution: with China as a focus

Varieties and consumption of pesticides worldwide have been increasing dramatically as increased human population and crop production. In this process pesticide misuses become more and more serious, which has resulted in heavy environmental pollution and health risk of humans. In order to safeguard human health, threatened species and ecosystems from pesticide pollution, the consumption and pollution of pesticides worldwide especially China were reviewed and documented in present study. Meanwhile, the development trend of pesticide varieties and consumption was also prospected and discussed. It was found that worldwide consumption structure of pesticides has undergone significant changes since 1960s. The proportion of herbicides in pesticide consumption increased rapidly and the consumption of insecticides and fungicides/bactericides declined. China has become the largest pesticide producer and exporter in the world. Pesticide pollution of air, water bodies and soils, and pesticide-induced deaths in China has been serious in past years. Bio-pesticides should be further developed in the future.
Ecological consumer behaviour: review and suggestions for future research

research data indicate that I n early seventies marketing was considered as an activity rather unfriendly to the environment. It has been criticized as a contributing factor to what is known as "overconsumption". Overconsumption is considered as responsible for certain aspects of environmental degradation of today. In nineties facing the crisis and protecting the environment is the "name of the game". ABSTRACT there is a rather contradictory picture of consumer views. In U.S.A 70% to 90% have suggested that they are concerned with or influenced by the environmental impacts of their purchases (Chase and Smith, 1992; Cramer, 1991). In a A. ). Waiter Thompson survey in 1990 (Shrum, et aI., 1995) 82% of the respondents supported that they would be willing to pay 5% more for a product that was environmentally friendly, while the previous year that part was only In this paper a literature review on Ecological Conscious Consumer (E.C.C.) and his/her behaviour is presented. A taxonomic synopsis of the findings is appeared in a detailed table. The data analysis leads to the conclusion that several important differences exist. Most of the studies have focused on fragmentary aspects of E.C. C. A theoretical framework is proposed, as an attempt to meet the challenges of such a research effort. The dimensions of this framework are also discussed. Future research may undertake the task to provide data within this holistic and multidimensional approach.
Pedestrian Object Detection Algorithm Based on Improved YOLOv5s

Traditional pedestrian object detection techniques, represented by YOLOv5, are limited in real-world applications due to their large parameter volumes and high computational complexity. In response to this problem, we propose an improved YOLOv5s pedestrian object detection algorithm. Firstly, we introduce the lightweight network GhostNet into the structure of YOLOv5s to achieve lightweight detection networks. On this basis, a CBAM based on the attention mechanism is proposed to enhance feature extraction and improve the performance of the model while reducing the model parameters. Secondly, we replace the CIoU loss function in the original network with the EIoU loss function, which enables the network training process to converge faster. Finally, we construct a pedestrian object detection dataset to verify the accuracy and real-time performance of the model. The experimental results show that while maintaining high accuracy, the parameter volume of the improved YOLOv5s algorithm is reduced by 45.8% compared to the original algorithm.
Deep Learning as a Solution for Egg Quality Assessment

The society is aware of the essential nutrients present in eggs, such as protein, vitamins, and minerals. The eggshell can indicate and be utilized to detect and assess egg quality. Dirty eggs pose a significant risk to consumers as they can harbor harmful Salmonella bacteria, leading to adverse health consequences. Automating the process of selecting and classifying clean and dirty eggs is an alternative solution that is more efficient, as manual labor is time-consuming, complex, and monotonous. Therefore, it is necessary to develop an automated egg classification system. This research aims to develop a classification process for dirty and clean eggs. The methodology employs GLCM-Deep Learning to automatically identify dirty and clean eggs. Three optimizers are used: Adam optimizer, rmsprop optimizer, and sgd optimizer, with the RELU activation function. The dataset consists of a total of 1000 images of dirty eggs and 1000 clean eggs, with 400 samples in the test dataset. The best result from the GLCM-Deep Learning model was achieved using the rmsprop optimizer with an accuracy of 62.5%. This research is of great importance as it addresses the complexity and inefficiency in egg classification and selection processes, and enables automatic determination and evaluation of egg quality.
Classification of the minerals of the tourmaline group

A systematic classification of the tourmaline-group minerals, general formula X Y3 Z6 (Γ6Oi8) (B03)3 V3W, is proposed, based on chemical composition and ordering at the different crystallographic sites of the tourmaline structure. There are currently thirteen accepted tourmaline species. However, based on the actual chemical composi­ tions of holotype material, several of these species were imprecisely or incorrectly defined. A proper definition of these species is proposed. A crystal-chemical feature that extends the number of possible end-members is the anion occupancy of the W-site (dominated by OH-, F~ or O2-) and the V-site (dominated by OH- or, more rarely, 02~). Thus, based on the W-site alone, there can be hydroxy-, fluor-, or oxy-end-members. Furthermore, the presence of dominant O2- at the W-site commonly requires local cation-ordering at the Y- and Z-sites. The tourmaline-group min­ erals can be divided into three principal groups based on the dominant species at the X-site: alkali tourmalines (Na), calcic tourmalines (Ca) and X-site-vacant tourmalines (O: vacancy). These groups are further divided, initially based on the W-site occupancy, then by the (actual or inferred) V-site occupancy, next by the (actual or inferred) F-site occupancy and, finally, by the (actual or inferred) Z-site occupancy. A systematic classification procedure is developed that takes into account different levels of knowledge of the chemical composition and site occupancy of the tourmaline. Several examples are used to illustrate the application of this classification procedure.
Tectonic Block Attribution of the Wenchuan and Yushu Earthquakes Distinguished by Focal Mechanism Types

The November 14, 2001 Mw7.8 Kunlun Mountain Pass earthquake, the March 21, 2008 Mw7.2 Yutian earthquake and the May 12, 2008 Mw7.9 Wenchuan earthquake all occurred in the middle of Tibet Plateau and formed a new seismicity group. The epicenters of the Kunlun Mountain Pass earthquake and Wenchuan earthquake are located at the northern and eastern boundary of the Bayan Har Block, respectively and the Yutian earthquake at the western end of it. GPS observational data indicate that this block moves to east. The rupture characteristics of the three large earthquakes in different parts of the block suggest the mechanical consistency of the Bayan Har block motion. The intensity and frequency of Yutian aftershocks significantly increased before the main shock and the stronger aftershocks of the Wenchuan earthquake, which proves that there is an internal relation between the three large earthquakes. The April 14, 2010 Mw6.9 Yushu earthquake, the November 19, 1996 Mw6.9 Karakorum Mountain earthquake and the November 08, 1997 Mw 7.5 Mani earthquake all occurred on the southern boundary of the Bayan Har block, and their focal mechanisms are consistently left-lateral strike slip, which were caused by the eastward motion of the Qiangtang block and formed a new strong earthquake group. The results show that the block has the character of rigid body motion which is the common origin of the two large earthquake groups.
Protection of Indigenous Knowledge: Mismatch Between The Convention on Biological Diversity and TRIPS Agreement

Malaysia is in the midst of drafting a national law to regulate access to its genetic resources and to ensure equitable sharing of benefits derived from its commercialisation. One of the issues being addressed in the drafting process relates to the protection of indigenous peoples’ resources and traditional knowledge. The Convention on Biological Diversity (CBD) establishes an obligation to seek prior and informed consent for the use of any traditional knowledge and seeks to ensure benefit-sharing. The contemporary international intellectual property rights (IPR) framework under the Trade-Related Aspects of Intellectual Property Rights Agreement (TRIPS Agreement), however, does not contain such a requirement for benefit-sharing. Thus, the main objective of this article is to study the protection of indigenous peoples’ resources and knowledge under the existing IPR legal framework. The relationship between the IPR system under the TRIPS Agreement and the access and benefit-sharing principles of the CBD relating to traditional knowledge will be the main focus of the analysis. This article will demonstrate the existing international IPR framework does not provide adequate protection for traditional knowledge and is inconsistent with provisions of the CBD.
A new framework for estimating and decomposing the uncertainty of climate projections

Climate projections obtained by running global climate models (GCMs) are subject to multi-source uncertainties. The existing framework based on analysis of variance (ANOVA) for decomposing such uncertainties is unable to include the interaction effect between GCM and internal climate variability, which ranks only second to the main effect of GCM in significance. In this study, a three-way ANOVA framework is presented, and all main effects and interaction effects are investigated. The results show that, although the overall uncertainty (O) is mainly contributed by main effects, interaction effects are considerable. Specifically, in the 21st century, the global mean (calculated at the grid-cell level and then averaged, the same below) relative contributions of all main effects are 54% for precipitation and 82% for temperature; those of all interaction effects are respectively 46% and 18%. As the three-way ANOVA cannot investigate the uncertainty components resulting from uncertainty sources, it is improved by deducing the relationship between uncertainty components resulting from uncertainty sources and those resulting from the main effects and interaction effects. By the improved three-way ANOVA, O is decomposed into uncertainty components resulting from emission scenario (S), GCM (M), and internal climate variability (V). The results reveal that O is mainly contributed by M in the 21st century for precipitation, and by M before the 2060s whereas by S thereafter for temperature. The robustness of the V characterization is explored by investigating the variation of V on the number of included ensemble members. The underestimating extent of the V contribution is roughly an average of 4% for precipitation and 1% for temperature.
Classification of Dental Caries Level Using Conjugate Gradient Backpropagation Models

Oral diseases are among the most prevalent noncommunicable diseases, affecting approximately 3.5 billion individuals globally. Untreated caries of primary and permanent teeth, severe periodontal disease, edentulism (total tooth loss), and lip and oral cavity cancer are the most burdensome oral diseases and conditions. Untreated dental caries is the most prevalent noncommunicable disease and a significant global public health concern, accounting for approximately 2 billion cases of all oral diseases. Several studies have shown that machine learning can help read patient conditions more quickly and accurately. This research designs a classification system using Multi-Layer Perceptron to determine the level of dental caries. The dental image consists of four dental caries levels, then extracted using a Gabor filter. Multi-Layer Perceptron performance in classifying dental caries levels shows promising results. Conjugate Gradient Backpropagation with Powell-Beale Restarts and Conjugate Gradient Backpropagation with Fletcher-Reeves Updates were used for the classification stage. The training result shows that Conjugate Gradient Backpropagation with Fletcher-Reeves Updates has a better accuracy average than Conjugate Gradient Backpropagation with Powell-Beale Restarts. The highest accuracy achieved by Conjugate Gradient Backpropagation with Powell-Beale Restarts is 96,5%.