Miracle-dz/UniFAR-FTUs huggingface dataset:
Building Semantic Segmentation of High-resolution Remote Sensing Image Buildings Based on U-net Network Model Based on Pytorch Framework

Modern remote sensing technology has developed rapidly in recent years. The high-resolution remote sensing images brought by new technologies have good application prospects in military and civilian fields, but the information contained in them is also richer, which increases the complexity of remote sensing image analysis and understanding. At present, artificial intelligence technology represented by deep learning has been widely used in the field of image processing. This paper adopts the U-net network model and uses the transfer learning method to train on the remote sensing image dataset published by the French National Institute of Information and Automation (Inria) to verify the effectiveness of the deep learning semantic segmentation method on high-resolution remote sensing images. and stability. Experiments show that the model has an accuracy of 86.86% in extracting buildings from images, a recall rate of 82.54%, and an average intersection ratio of 84.53%, which is effective in semantic segmentation of high-resolution remote sensing images.
A generalized predictive criterion for model selection

Given a random sample from some unknown model belonging to a finite class of parametric models, assume that the estimate of the density of a future observation is of interest San Martini & Spezzaferri (1984) proposed for this problem a predictive criterion based on the logarithmic utility function. The present authors investigate a generalization of this criterion that uses as a loss function an element of the class of α‐divergences discussed by Ali & Silvey (1966) and Csiszár (1967). They also discuss briefly the case in which the class of models considered is not exhaustive.
Investigating Walking Characteristics of Passengers in Subway Corridors by Video Processing based on YOLOX and Deepsort Algorithm

This paper studies the walking characteristics of passengers in the transfer corridor of a subway station. First, passenger detection and tracking are performed using YOLOX and deepsort algorithms, respectively. Then, the density, distance, speed and other characteristics of passengers are calculated. Finally, on this basis, the distribution of passenger speed, the characteristics of fundamental diagram and the relationship between speed and distance are analyzed. The following main conclusions are obtained: (1) The number of passengers with medium speed is more, while the number of passengers with higher speed or lower speed is less; (2) The passenger speed decreases with the increase of the density, but when the density reaches about 3.1 p/m2, the speed will increase; (3) The passenger speed has a linear relationship with the passenger distance.
Median-based Rules for Decision-making under Complete Ignorance

Abstract This article characterizes a class of rules for decision-making when an agent knows the possible states of the world and the outcome of each of his/her actions for each state, but does not have any information about the probabilities of the states. The existing literature in this framework has mainly considered ‘max’-based or ‘min’-based rules and their variants. Such rules reflect rather extreme forms of optimism or pessimism on the part of an agent. In contrast, this paper focuses on the median outcome(s) and characterizes a class of decision-making rules which reflects a more ‘balanced’ attitude towards uncertainty. We also discuss a possible interpretation of our result in terms of the ranking of alternative social states that an individual may have when he/she is under the Rawlsian ‘veil of ignorance’. JEL Classifications: D81
Psychosocial work environment stressors for school staff during the COVID-19 pandemic: Barriers and facilitators for supporting wellbeing

Introduction After periods of remote and/or hybrid learning as a result of the COVID-19 global pandemic, the return to in-person learning has been beneficial for both students and teachers, but it has not been without challenges. This study was designed to assess the impact of the return to in-person learning on the school experience, and efforts made to ease the transition in furthering a positive in-person learning environment. Materials and methods We conducted a series of listening sessions with 4 stakeholder groups: students (n = 39), parents (n = 28), teachers/school staff (n = 41), and a combination of listening sessions and semi-structured interviews with building level and district administrators (n = 12), focusing on in-school experiences during the 2021–2022 school year amidst the COVID-19 pandemic. A primarily deductive qualitative analysis approach was employed to code the data followed by a primarily inductive thematic analysis, followed by thematic aggregation, thus providing depth and identification of nuances in the data. Results Three main themes emerged around school staff experiences: (1) increased levels of stress and anxiety manifested in key ways, including students' challenges with personal behavior management contributing to increased aggression and staff shortages; (2) school staff described key contributors to stress and anxiety, including feeling excluded from decision making and challenges with clear and consistent communication; and (3) school staff described key facilitators that supported their management of anxiety and stress, including adaptability, heightened attention and resources to wellbeing, and leveraging interpersonal relationships. Discussion School staff and students faced significant stress and anxiety during the 2021–2022 school year. Further exploration and identification of approaches to mitigate key contributors to increased stress and anxiety for school staff, along with increased opportunities for implementing key facilitators that were identified as important in managing and navigating the increased stress and anxiety offer valuable opportunities for helping to create a supportive work environment for school staff in the future.
Recurrence Plot Application of RCS Sequence for Radar Target Classification with Micro-motion

Micro-motion is of great significance for classification of spatial targets. Based on the RCS (Radar Cross Section) sequence induced by micro-motion, this paper proposes a spatial target classification method based on RP (Recurrence Plot) and CNN (Convolutional Neural Network). First, several micro-motion types of spatial targets are analyzed and thus different models are established. Then, according to the characteristics of delay time and embedding dimension, phase space reconstruction method is used to generate multi-channel and non-threshold RPs. Finally, RPs are inputted into Xception network to classify targets with different micro-motions. Compared with the original RCS sequence, RP-based method has high classification accuracy.
Organic Pollutants Associated with Plastic Debris in Marine Environment: A Systematic Review of Analytical Methods, Occurrence, and Characteristics

Plastic pollution has become one of the most serious environmental problems, and microplastics (MPs, particles < 5 mm size) may behave as a vehicle of organic pollutants, causing detrimental effects to the environment. Studies on MP-sorbed organic pollutants lack methodological standardization, resulting in a low comparability and replicability. In this work, we reviewed 40 field studies of MP-sorbed organic contaminants using PRISMA guidelines for acquiring information on sampling and analytical protocols. The papers were also scored for their reliability on the basis of 7 criteria, from 0 (minimum) to 21 (maximum). Our results showed a great heterogeneity of the methods used for the sample collection, MPs extraction, and instruments for chemicals’ identification. Measures for cross-contamination control during MPs analysis were strictly applied only in 13% of the studies, indicating a need for quality control in MPs-related research. The most frequently detected MP-sorbed chemicals were polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and organochlorine pesticides (OCPs). Most of the studies showed a good reliability (>75% of the total score), with 32 papers scoring 16 or higher. On the basis of the collected information, a standardizable protocol for the detection of MPs and MP-sorbed chemicals has been suggested for improving the reliability of MPs monitoring studies.
Determination of Embryotoxic effects of Atipamezole using in ovo model

Atipamezole is a specific α2-adrenergic receptor antagonist, and there exists insufficient information on its use during pregnancy. The aim of this study was to determine the embryotoxic activity of Atipamezole through an in ovo method. During the first stage of the study, 210 fertile eggs were divided into seven groups of 30 fertile eggs and placed in an incubator. On the seventh day of the first stage, no application was made to the control group. The second group was administered 50 microliters (µL) of saline solution, while the other groups were given Atipamezole at doses of 250, 125, 62.5, 31.25 and 15.62 micrograms·egg-1 (µg·egg-1) in 50 µL saline solution. In the second stage, according to the embryotoxic dose range determined from the first stage, 150 fertile eggs were divided into five groups of 30 fertile eggs and placed in an incubator. On the seventh day of the second stage, no application was made to the control group. Fifty µL of saline solution was administered to the second group. The other groups were given Atipamezole at doses of 220, 190 and 160 µg·egg-1 in 50 µL saline solution. After the incubation period, the eggs hatched, and the embryonic mortality rates were calculated. The mortality rate was determined to be 39.3% at the highest dose (250 µg·egg-1 = 5 miligrams·kilograms-1 –mg·kg-1–) (P<0.05), while the mortality rate at other doses was determined to be the same as the control group (P>0.05). In conclusion, it can be stated that the dose determined for Atipamezole in this study was very high compared to the recommended doses and it can be used in pregnancy as a benefit-loss calculation when necessary. However molecular or histopathological studies regarding the development of organ drafts are necessary to determine the safety of its use during pregnancy.
COM Shifter and Body Rotator for Step-by-Step Teleoperation of Bipedal Robots

This paper presents a controller for step-by-step teleoperation of bipedal robots, in which the user commands the robot’s foot motions in a step-by-step manner through a pair of handheld 3-dimensional pointing devices. The proposed controller is intended to allow users to precisely manipulate the swing foot motions to traverse rough terrains by avoiding obstacles. It aims to realize quick response to user commands and stable automatic balancing even under erroneous user commands. The main components of the proposed controller are a COM (center-of-mass) shifter and a body rotator, which are simple sensory feedback controllers that do not involve first-in first-output (FIFO) buffers, time-series generation, or online optimization. The COM shifter is a controller to produce a COM motion according to a reference zero moment point (ZMP). The body rotator complements the COM shifter to produce an appropriate angular momentum rate to enhance the regulation of ZMP. The proposed controller is validated in our interactive/realtime simulation environment.
Childhood Obesity and the Cryptic Language of the Microbiota: Metabolomics’ Upgrading

The growing obesity epidemic in childhood is increasingly concerning for the related physical and psychological consequences, with a significant impact on health care costs in both the short and the long term. Nonetheless, the scientific community has not yet completely clarified the complex metabolic mechanisms underlying body weight alterations. In only a small percentage of cases, obesity is the result of endocrine, monogenic, or syndromic causes, while in much more cases, lifestyle plays a crucial role in obesity development. In this context, the pediatric age appears to be of considerable importance as prevention strategies together with early intervention can represent important therapeutic tools not only to counteract the comorbidities that increasingly affect children but also to hinder the persistence of obesity in adulthood. Although evidence in the literature supporting the alteration of the microbiota as a critical factor in the etiology of obesity is abundant, it is not yet fully defined and understood. However, increasingly clear evidence is emerging regarding the existence of differentiated metabolic profiles in obese children, with characteristic metabolites. The identification of specific pathology-related biomarkers and the elucidation of the altered metabolic pathways would therefore be desirable in order to clarify aspects that are still poorly understood, such as the consequences of the interaction between the host, the diet, and the microbiota. In fact, metabolomics can characterize the biological behavior of a specific individual in response to external stimuli, offering not only an eventual effective screening and prevention strategy but also the possibility of evaluating adherence and response to dietary intervention.
Photoionization of lithium

The photoionization of lithium from threshold to 50 eV above threshold is calculated using the method of polarized orbitals. The method is applied in as orthodox a manner as possible; this means that total wave functions are constructed as by Temkin and Lamkin (1961) using only the static dipole part of the perturbation of core electrons by the outer part of the external electron. According to other previously given prescriptions, both initial (bound) and final (continuum) wave functions are so polarized, only the length form of the matrix is calculated, and bilinear terms from the polarization contributions are retained (although their effect in this calculation is small). The results themselves are essentially identical to those of a recent diagrammatic calculation of Chang and Poe (1975) (in the region below 5 eV where thay have calculated), and as such they differ in certain significant components from exchange-adiabatic and extended-polarization results of Matese and LaBahn (1969) (although their overall result is similar). The s- and p-wave e-Li(+) phase shifts, which are derived as by-products of this calculation, are also presented and compared with other phase-shift calculations.
Stuck Pipe Prediction Using Adaptive Nero-Fuzzy Inference System Based on Feature Analysis

In the process of underground drilling in coal mine, there are some cases of drilling resistance but not stuck pipe. The method of data training model to predict stuck drilling will often lead to a high false alarm rate and reduce the prediction accuracy. Therefore, this paper proposes an improved adaptive nero-fuzzy inference system prediction method based on feature analysis (ANFIS-FA). The rotational speed with the strongest correlation was selected as the feature analysis object through principal component analysis, and then the sliding window was used to extract the amplitude change to construct the penalty factor, so as to improve the prediction results of ANFIS. In this paper, the actual drilling data are used for experiments. The results show that ANFIS-FA reduces the false alarm rate and improves the prediction accuracy, which has certain guiding significance for practical drilling.
A 79.2-μW 19.5-kHz-BW 94.8-dB-SNDR Fully Dynamic DT ΔΣ ADC Using CLS-Assisted FIA With Sampling Noise Cancellation

This brief proposes a fully dynamic discrete-time (DT) <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\Delta }\boldsymbol {\Sigma }$ </tex-math></inline-formula> ADC using a correlated level shifting (CLS)-assisted floating inverter amplifier (FIA) with a sampling noise cancellation (SNC) technique. The CLS-assisted FIA improves amplifier gain with a single-stage configuration, which has lower input-referred noise than the cascaded one. In combination with the proposed SNC, the noise contribution of the 1 <inline-formula> <tex-math notation="LaTeX">$^{\mathrm{ st}}$ </tex-math></inline-formula>-stage integrator can be minimized. We also propose a novel passive integrator cascaded with a passive adder that avoids unwanted inter-stage loading without a speed penalty. The prototype of the proposed ADC fabricated in a 65nm bulk CMOS process realizes a fully dynamic operation and achieves 94.8 dB SNDR with an OSR of 256 for 19.5 kHz bandwidth while consuming 79.2<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\mu }\text{W}$ </tex-math></inline-formula> from a 1.2V supply at a 10 MHz sampling frequency. The Schreier and Walden FoMs are respectively 178.7 dB and 45.2fJ/conv. -step, which are the best among recent fully dynamic DT <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {\Delta }\boldsymbol {\Sigma }$ </tex-math></inline-formula> ADCs with similar bandwidth.
Plant Species Classification Using Leaf Edge Feature Combination with Morphological Transformations and SIFT Key Point

This paper presents a new approach to plant classification by using leaf edge feature combination with Morphological Transformations and defining key points on leaf edge with SIFT. There are three steps in the process. Image preprocessing, feature extraction, and image classification. In the image preprocessing step, image noise is removed with Morphological Transformations and leaf edge detect with Canny Edge Detection. The leaf edge is identified with SIFT, and the plant leaf feature was extracted by CNN according to the proposed method. The plant leaves are then classified by random forest. Experiments were performed on the PlantVillage dataset of 10 classes, 5 classes of healthy leaves, and 5 classes of diseased leaves. The results showed that the proposed method was able to classify plant species more accurately than using features based on leaf shape and texture. The proposed method has an accuracy of 95.62%.
3-D Transmitting Pattern Manipulation Structures Using Slotline Bandpass Filter Elements: Synthetic Design and Implementation

This article proposes a novel design concept of 3-D transmitting pattern manipulation structures (PMSs) using slotline bandpass filter (BPF) elements. First, the parallel-coupled slotline is utilized to synthetically design a slotline element by employing the equivalent transmission line model. Then, two types of elements are designed to implement the proposed PMS. The element-I with a variable transmission phase is realized by adjusting the resonant frequency of slotline structure, while keeping the transmission magnitude almost equal to 0 dB within an operating bandwidth of 13.2%. The element-II is obtained by connecting two element-Is in series for a larger range of transmission phase with an operating bandwidth of 10.3%. After that, two 3-D transmitting PMSs (PMS-I with <inline-formula> <tex-math notation="LaTeX">$8\times20$ </tex-math></inline-formula> elements and PMS-II with <inline-formula> <tex-math notation="LaTeX">$10\times30$ </tex-math></inline-formula> elements) are obtained by quasi-periodically arranging element-I and element-II, respectively. Finally, two prototypes of PMS-I and PMS-II are fabricated and tested to validate our design concept. Measurements and simulations agree well with each other, showing the desired transmission angles of (<inline-formula> <tex-math notation="LaTeX">$\theta _{I}=10^{\circ }$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\phi _{I}$ </tex-math></inline-formula> = 90°) for PMS-I and (<inline-formula> <tex-math notation="LaTeX">$\theta _{II}=20^{\circ }$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\phi _{II}$ </tex-math></inline-formula> = 90°) for PMS-II with the highest efficiencies of 92.8% and 88.9%. Therefore, the proposed 3-D transmitting PMS can be evidently used as a promising candidate to form the transmission waves for the future smart radio environment.
Soil nutrient dissimilarity and litter nutrient limitation as major drivers of home field advantage in riparian tropical forests

Decomposition is a key process driving carbon and nutrient cycling in ecosystems worldwide. The home field advantage effect (HFA) has been found to accelerate decomposition rates when litter originates from “home” when compared to other (“away”) sites. It is still poorly known how HFA plays out in tropical, riparian forests, particularly in forests under restoration. We carried out three independent reciprocal litter transplant experiments to test how litter quality, soil nutrient concentrations, and successional stage (age) influenced HFA in tropical riparian forests. These experimental areas formed a wide gradient of soil and litter nutrients, which we used to evaluate the more general hypothesis that HFA varies with dissimilarity in soil nutrients and litter quality. We found that HFA increased with soil nutrient dissimilarity, suggesting that litter translocation uncouples relationships between decomposers and litter characteristics; and with litter N:P, indicating P limitation in this system. We also found negative HFA effects at a site under restoration that presented low decomposer ability, suggesting that forest restoration does not necessarily recover decomposer communities and nutrient cycling. Within each of the independent experiments, the occurrence of HFA effects was limited and their magnitude was not related to forest age, nor soil and litter quality. Our results imply that HFA effects in tropical ecosystems are influenced by litter nutrient limitation and soil nutrient dissimilarity between home and away sites, but to further disentangle major HFA drivers in tropical areas, a gradient of dissimilarity between litter and soil properties must be implemented in future experimental designs.
Repeated confidence intervals and prediction intervals using stochastic curtailment under fractional Brownian motion

ABSTRACT Repeated confidence intervals (RCIs) and prediction intervals (PIs) can be used for the design and monitoring of group sequential trials. Stochastically curtailed tests (SCTs) under fractional Brownian motion (FBM) have been studied for the interim analysis of clinical trials (Zhang et al., 2015). In this article, we derive RCIs and PIs based on SCTs under FBM for one-sided derived tests (Jennison and Turnbull, 2000). Comparisons of RCI width and sample size requirement are made to those under Brownian motion (BM) and to those of Pocock and O'Brien-Fleming design types for various type I, type II error rates, and number of interim analyses. Interim data from Beta-Blocker Heart Attack Trial are used to illustrate how to design and monitor clinical trials using these RCIs and PIs under FBM. Results show that these one-sided derived tests based on SCTs have narrower final confidence intervals and require smaller sample sizes than those using classical group sequential designs. The Hurst parameter has more impact on the RCI width than on the sample size requirements for the proposed designs.
A comparison of the radio–submillimetre spectra of BL Lacertae objects and flat-spectrum radio quasars

We present quasi-simultaneous radio, millimetre and submillimetre spectra of 22 BL Lac objects and 24 radio-loud, violently variable quasars. These data are used to test the hypothesis that BL Lacs and OVV quasars are fundamentally different objects. We find a considerable degree of consistency of the overall spectral shape in all sources and conclude that the same basic physical model applies to the continuum emission over this frequency range in both cases. There is clear evidence in the data for the BL Lacs to have flatter 150-375 GHz spectra, and we attribute the effect to an intrinsic difference between the underlying jets in the two types of object. A similar difference in the 37-270 GHz spectral indices between the two types can be attributed to a simple redshifting of the synchrotron self-absorption turnover.