Miracle-dz/UniFAR-FTUs huggingface dataset:
Provably Robust Adversarial Examples

We introduce the concept of provably robust adversarial examples for deep neural networks - connected input regions constructed from standard adversarial examples which are guaranteed to be robust to a set of real-world perturbations (such as changes in pixel intensity and geometric transformations). We present a novel method called PARADE for generating these regions in a scalable manner which works by iteratively refining the region initially obtained via sampling until a refined region is certified to be adversarial with existing state-of-the-art verifiers. At each step, a novel optimization procedure is applied to maximize the region's volume under the constraint that the convex relaxation of the network behavior with respect to the region implies a chosen bound on the certification objective. Our experimental evaluation shows the effectiveness of PARADE: it successfully finds large provably robust regions including ones containing $\approx 10^{573}$ adversarial examples for pixel intensity and $\approx 10^{599}$ for geometric perturbations. The provability enables our robust examples to be significantly more effective against state-of-the-art defenses based on randomized smoothing than the individual attacks used to construct the regions.
Hydroelastic Analysis of 3D Printed Marine Propeller Working at Low Reynolds Number

A method to predict the hydro-elastic performance of 3D printed marine propeller operating at low Reynolds number is presented. The propeller of an Autonomous Underwater Vehicle (AUV) typically operates at lower Reynolds number due to their small size. At this low Reynolds number, the flow is in the laminar-turbulent transition region. The hydrodynamics of these propellers is different from the propeller which operates in fully turbulent flow. Also, the propeller of AUV is typically manufactured using 3D printing of plastic material. The 3D printed materials are not strong enough like metals or composite materials. We investigate the global and local hydrodynamic characteristic of model scale propeller using CFD RANSE solver with γ-Reθ transition model. The twist of the propeller is calculated using a simple analytical expression based on the principle of torsional deflection. The performance of untwisted and twisted propeller are compared in terms of local flow characteristics like streamline pattern and global characteristics like hydrodynamic forces.
High-order terminal sliding-mode control for permanent magnet synchronous motor

A permanent magnet synchronous motor speed control based on high-order terminal sliding mode is proposed to improve the robustness and the response speed of the system.Based on the vector control principle,nonsingular terminal sliding modes are designed to make the motor speed,the d-axis current and the q-axis current reach the given values in a finite period of time.Meanwhile,high-order sliding modes are utilized to eliminate the chattering phenomenon,and to guarantee the stability of the system.The simulation results show that the motor speed can reach the given value more rapidly than that of a proportional integral(PI)control;and the system is robust with respect to the load disturbances.
The effects of true and pseudo-absence data on the performance of species distribution models at landscape scale

Potential distribution ranges of natural grassland in subtropical humid mountainous areas were predicted by species distribution models (SDMs) to examine the effects of true and pseudo-absence data on model performances that were scarcely assessed by using real data. Climate spaces of potential ranges of natural grassland were then constructed by principal components analysis (PCA). The distribution map projected by six model algorithms based on true absence data had all presented restricted distribution ranges of natural grassland along mountain ridges, whereas that based on pseudo-absence data presented wider distribution ranges. RF model was used to detect the effects of data record number and contribution of climate variables on model performance because of higher True Skill Statistics. Restricted distribution ranges of natural grassland projected by RF based on true absence data were similar to limited climate space quantified by PCA. However, climate variables related to occurrences of natural grassland were not consistent between RF and PCA results. Occurrences of natural grassland associated with treeline at low elevation were presumably determined by multiple climate factors at subtropical mountain ridges, such as relatively lower temperatures, heavy precipitations, and strong winds. Local climate dataset derived from meteorological stations and followed by altitudinal adjustment was available for modeling species distribution range in mountainous areas. Conclusively, true absence data had practically delineated geographical boundaries and characterized the climate environments of natural grassland. True absence data was recommended to collect along a known environmental gradient and used to construct training dataset with pseudo-absence data to improve model performance.
Study on Multimodal Confucius Institute Linguistic Landscape

The present study tries to explore the mechanism of symbolic meaning generation. It firstly introduces the concept of symbolic meaning, then we will further discuss symbolic meaning from multimodal perspective. It is found that the symbolic meaning of the Confucius Institute linguistic landscape plays an important role in constructing the contextual meaning in visual space, and the symbolic meaning is mainly achieved by attracting attention, shaping impression and cultivating interest. The multimodal Confucius institute linguistic landscape allows for an understanding of how different trajectories of multimodal semiotic resources meet at particular times and places, and therefore helps us to know the significance of symbolic meaning during the constructive process of multimodal linguistic landscape.
A sliding window approach to optimize the time-varying parameters of a spatially-explicit and stochastic model of COVID-19

The implementation of non-pharmaceutical public health interventions can have simultaneous impacts on pathogen transmission rates as well as host mobility rates. For instance, with SARS-CoV-2, masking can influence host-to-host transmission, while stay-at-home orders can influence mobility. Importantly, transmission rates and mobility patterns can influence pathogen-induced hospitalization rates. This poses a significant challenge for the use of mathematical models of disease dynamics in forecasting the spread of a pathogen; to create accurate forecasts in spatial models of disease spread, we must simultaneously account for time-varying rates of transmission and host movement. In this study, we develop a statistical model-fitting algorithm to estimate dynamic rates of SARS-CoV-2 transmission and host movement from geo-referenced hospitalization data. Using simulated data sets, we then test whether our method can accurately estimate these time-varying rates simultaneously, and how this accuracy is influenced by the spatial population structure. Our model-fitting method relies on a highly parallelized process of grid search and a sliding window technique that allows us to estimate time-varying transmission rates with high accuracy and precision, as well as movement rates with somewhat lower precision. Estimated parameters also had lower precision in more rural data sets, due to lower hospitalization rates (i.e., these areas are less data-rich). This model-fitting routine could easily be generalized to any stochastic, spatially-explicit modeling framework, offering a flexible and efficient method to estimate time-varying parameters from geo-referenced data sets.
DNAmFitAge: biological age indicator incorporating physical fitness

Physical fitness is a well-known correlate of health and the aging process. DNA methylation (DNAm) data lend themselves for estimating chronological and biological age through epigenetic clocks. However, current epigenetic clocks did not yet use measures of mobility, strength, lung, or endurance physical fitness parameters in their construction. Here, we develop blood DNAm biomarkers for fitness parameters gait speed (walking speed), hand grip strength, forced expiratory volume in one second (FEV1), and maximal oxygen uptake (VO2max). We then use these DNAm biomarkers to construct DNAmFitAge, a new biological age indicator that incorporates physical fitness with epigenetic mortality risk estimators. Adjusting DNAmFitAge for chronological age generates a novel measure of epigenetic age acceleration, FitAgeAcceleration, which is informative for physical activity level (p=1.2E-12), mortality risk (p=5.9E-13), coronary heart disease risk (p=0.0051), comorbidities (p=9.0E-9), and disease-free status (p=1.1E-6) across several large validation datasets. These newly constructed DNAm biomarkers and DNAmFitAge provide researchers and physicians a new method to incorporate physical fitness into epigenetic clocks and emphasizes the effect of lifestyle on the aging process.
Kelvin-Helmholz Instability Driven Shedding of Cavitation Clouds in Microchannels

The paper shows visualization of cavitation inside a microchannel. While the initial aim of the study was to establish supercavitating conditions inside a microchannel, yet we found that this regime is suppressed due to the formation of a Kelvin-Helmholtz instability, which triggers a semi periodical attached cavity collapse. In-depth observations using high speed imaging with visible light and X-rays revealed that this is in fact besides the re-entrant jet and the shock wave a third mechanism leading to the shedding of cloud cavitation.
Approaching Bus OD Matrices Based on Data Reduced from Bus IC Cards

Bus OD matrices are crucial inputs for bus dispatching and bus network optimization. With a wide application of IC (Intelligent card) card technologies, it is both meaningful and valuable to investigate how the data collected from bus IC cards can be fully utilized to approach OD matrices and calculate the numbers of bus transfers and trip frequencies. Based on the characteristics of bus IC card data, this paper develops methods for estimating both stop-based ODs and link-based ODs between two stops using data mining technology. The paper further considers what information else can be obtained from IC card data. The proposed methods aim to approach bus stop OD data and regional trip OD data using a systematic framework based on GIS. Meanwhile, a flow chart is given in the paper to help reduce bus OD data. It was concluded that GIS, which combines data processing function with geographical attributes, is the best way to process IC card data. Using this method, the problems related to bus OD matrices, transfer times, and trip frequencies, can be resolved effectively.
Erosional Development and Morphometric Dynamics of Sarujharna River Basin, East Singhbhum, Jharkhand

Being south-eastern part of famous Chotanagpur Plateau of India , the Sarujharna Basin is deemed to be considered as a small museum of Indian geology and geomorphology. On the tectonically stable and frequently modified Dhanjori Highlands (south-west of S inghbhum Shear Zone, copper belt ) rivers l ike Sankh, Netra , Sarujharna, Jou, Gara etc. crave out several geomorphic architects (youth-old phase) which signify the variable intensity of erosion. Having different magnitude of rock résistance and forest cover, monsoonal wet-dry type of climate plays a crucial role in hillslope erosion and channel erosion. The present article emphasizes on the spatial distribution and quantifica tion of fluvial erosion taking drainage basins and slope facets as an ideal geomorphic unit. Side by side, to realize the pattern of erosion we have focused on surface runoff, length of overland flow, constant of channel maintenance, hillslope erosion model, length and number of 1 order stream which are the indirect morphometric measurements of normal erosion. Along with it Geographical Information System is used to show the physical appearance of erosion in thematic maps.
Path Planning for Autonomous Mobile Robots

Summary Building autonomous and intelligent robots has been an elusive dream for researchers for some time. Simultaneous Localization and Mapping (SLAM) systems have contributed towards achieving this goal by making robots better in navigating through complex environments. Until now it has only been possible to train and teach robots to move around in particular environments using a certain set of rules and heuristics. With the sudden surge in interest in AI and Machine Learning, a lot of effort has been put in into making robots intelligent and for them to automatically learn their paths in unknown environments (also referred to as Path Planning). This however has been met with mixed results as either the solution proposed is not too practical (e.g. requires too much training) or has limited success (e.g. works in specific environments). In this research, we develop a novel autonomous path planning framework using Deep Learning which can learn to navigate in unknown environments. The system has been tested on state-of-the-art Active Vision Dataset with promising results.
A Research on the Textual Interpretation and English Translation of Chinese Taoist Metaphorical System in Zhouyi

The metaphors in Chinese Taoist ancient works have unique literary features. The book Zhouyi cantong qi has received high attention since Tang dynasty as one of the most important works in Chinese alchemy. Metaphorical expressions are widely used to symbolize the alchemical process both for inner and external alchemy. From an intercultural perspective, the paper discusses the translations of metaphorical system and key terms in two English translations of Zhouyi cantong qi separately by Zhou Shiyi and Fabrizio Pregadio. It finds out that translators’ perception of the main idea of the book largely affected their translation process and strategies, Chinese translator used more liberal translation strategy than the western translator, and both translators effectively kept the images of metaphors of the source text. The use of metaphorical words in phrases and sentences makes the whole text of Cantong qi full of mystery.
Enlightenment on the Variations in the Structure of Guangzhou Inhabitant Mode Share

An unreasonable tendency prevails on the structure of inhabitant mode share in domestic cities at present. The requirement of city development and situation of traffic supply behind traffic demand need a reasonable structure of the mode share. By comparing the relevant data of investigation of myriad inhabitant trip between 1998 and 2003 in Guangzhou, the paper analyzes the inner reason of variations and expounds the management characteristics of bicycle,motorcycle,car,and bus in Guangzhou combining with the traffic situation in other cities. In the end, it concludes some advices about the structure of mode share management on the base of the successful experience in Guangzhou.
Principles for Self-Assembly and Pattern Formation in Large-Scale Neuronal Networks

The organization of neuronal populations into synchronously oscillating functional groups lies at the core of vital brain functions. However, little is known about the laws governing the behavior of such large-scale networks. Here, we describe fundamental physical principles which explain how self-sustained synchronous oscillations arise and spread as a result of natural interactions between external stimuli, connectivity, and recovery properties of neuronal populations. In addition, we show how synchronization in one region promotes or inhibits synchronization in another. These theoretical predictions were confirmed by comparison with human electrocorticographic recordings. Our findings advance understanding of functional behavior of large neuronal populations and have broad implications for the analysis of self-assembly in diverse classes of networks.
Measuring and Evaluating the Work-Related Stress of Nurses in Saudi Arabia during the Covid-19 Pandemic

Prior to the emergence of Covid-19, Saudi Arabia (SA) had never faced the challenge of dealing with a global pandemic. Significantly, the current crisis has impacted all industries and sectors in the country, including the healthcare system, and has led to an emphasis on human life being more precious and valuable than economic profit. This study focuses on the impact of Covid-19 on the health of nurses, including their quality of life, during 2020. Understanding the position of the nursing profession during the pandemic, including the most effective methods of preventing work-related stress is important. Information was acquired through an online survey method (i.e. self-completion), known as the Expanded Nursing Stress Scale (ENSS), which was distributed to nurses in all regions of SA. It was found that the main aspects impacting nurses' work-related stress include gender, employment type, training, and dealing with infected patients. In addition, they highlight that such stress plays a substantial role in patient safety and nurses' satisfaction at work, as well as the future survival of organizations. The emergence of Covid-19 as a novel infectious disease has increased nurses' uncertainty and work-related stress. The results of this research will provide insights into the views of both nurses and their managers, in order to identify the main indicators of stress.
Enzymatic Activities in the Intestinal Apparatus of Chickens after Peroral Intake of Humates

The effects of dietary intake of humates on the proteolytic, amylolytic and cellulolytic activities in the intestine of broiler chickens Ross 308 (starting weight 37.79 ± 0.58 g) were analyzed. Three experimental (A, B, C) and one control groups of birds (n=120) were fed with mixtures Hyd1 236.0 (day 1 10), Hyd2 222.40 (day 11 30), Hyd3 193.30 (day 31 42) g.kg crude protein. Humates (HM or HN) were added into feed mixtures: A group – 0.7% HM containing an absorbent of mycotoxins, B group – 0.7% HN without the absorbent, C group – 0.3% HM and the control without humates. There were measured body weights and feed consumption, as well as the average daily weight gains and the feed conversion ratio, were calculated once a week. On one hand, the positive effects of 0.7% humates were observed on the increase (P <0.05) of proteolytic on day 21 (B) by 7.92 (azocaseing.ml .min.g), cellulolytic on day 28 (A) by 0.89 (glucose mol.l.ming) in the intestine of broiler chickens measured in the excrement. On the other hand, the decrease (P <0.001) of amylolytic activities was observed on day 33 (A) by 1.58 and (B) by 1.43 (glucose mol.l.ming). In the case of intake of 0.3% humates, the proteolytic or cellulolytic were decreased in C on day 21 or 28 by 16.39 and 2.41, respectively. The recommended level of added humates into a feed of chickens is 0.7%.
A patient and physician friendly stimulation protocol using long acting FSH and progestin priming should be the future of IVF

Objective: Needle phobias and concern about the discomfort remain significant disincentives for many women contemplating in vitro fertilization (IVF). The number of injections required in an IVF cycle is increased by the use of most medications which prevent premature ovulation. Mechanism: long-acting follicular stimulation hormone (LA-FSH) that was developed 15 years ago has the ability to stimulate folliculogenesis in a patient for seven days with a single injection, with comparable outcomes to daily injections in assisted reproduction. Many clinicians were hesitated to use it in their patients, fearing an inability to decrease levels of FSH stimulation for 7 days and the resultant increased risks of ovarian hyperstimulation syndrome (OHSS). This occurred prior to the widespread adoption of Gonadotropinreleasing hormone (GnRH)-agonist triggering and freeze all embryos for the prevention of OHSS. Conclusions: We suggest LA-FSH protocol with the use of progestins to prevent ovulation, which could be an alternative way to treat IVF patients without any compromise of the effectiveness of the treatments or the safety of the patients.
Information model of PLM customer requirement on costume enterprise

In order to track the customer information in PLM,the paper puts forward a multi-view informational model of customer requirement for PLM.The mechanism of mapping-relation between view models is studied based on a formalized function method.The dynamic characteristic of view information is depicted by adopting multilayer behavioral system.In the example modeling,the matrix is applied to obtain such information as data,process,and resource of different types of customers and in different phases in PLM.On the basis of customer requirement,PLM establishes the strategy of design,manufacture,sale and call back.Finally,the theory is verified by practical examples.The result reveals that the information model of customer requirement in PLM system optimizes the resource of requirement structure in system implementation and better meets customers' requirements.
Tagging Words for Simple, Efficient, Effective and Zero-Shot Topic Control in Neural Abstractive Summarization

Existing approaches for topic-controllable 001 summarization either incorporate topic em-002 beddings or modify the attention mechanism. 003 The incorporation of such approaches in a 004 particular summarization model requires the 005 adaptation of its codebase, a process that 006 can be complex and time-consuming. In-007 stead, we propose a model-agnostic topic-008 controllable summarization method employ-009 ing a simple tagging-based formulation that 010 can effortlessly work with any summarization 011 model. In addition, we propose a new topic-012 oriented evaluation measure to quantitatively 013 evaluate the generated summaries based on 014 the topic affinity between the generated sum-015 mary and the desired topic. Experimental re-016 sults show that the proposed tagging-based 017 formulation can achieve similar or even bet-018 ter performance compared to the embedding-019 based approach, while being at the same time 020 significantly faster. Furthermore, we con-021 ducted a user study which validates the re-022 liability of the proposed measure. Finally, the 023 proposed method can be successfully used for 024 zero-shot topic controllable summarization 025 without any modification. 026
Spatiotemporal variability in Swedish lake ecosystems

Studying ecosystem dynamics is critical to monitoring and managing linked systems of humans and nature. Due to the growth of tools and techniques for collecting data, information on the condition of these systems is more widely available. While there are a variety of approaches for mining and assessing data, there is a need for methods to detect latent characteristics in ecosystems linked to temporal and spatial patterns of change. Resilience-based approaches have been effective at not only identifying environmental change but also providing warning in advance of critical transitions in social-ecological systems (SES). In this study, we examine the usefulness of one such method, Fisher Information (FI) for spatiotemporal analysis. FI is used to assess patterns in data and has been established as an effective tool for capturing complex system dynamics to include regimes and regime shifts. We employed FI to assess the biophysical condition of eighty-five Swedish lakes from 1996–2018. Results showed that FI captured spatiotemporal changes in the Swedish lakes and identified distinct spatial patterns above and below the Limes Norrlandicus, a hard ecotone boundary which separates northern and southern ecoregions in Sweden. Further, it revealed that spatial variance changed approaching this boundary. Our results demonstrate the utility of this resilience-based approach for spatiotemporal and spatial regimes analyses linked to monitoring and managing critical watersheds and waterbodies impacted by accelerating environmental change.