Analysis of a Single Species Model with Dissymmetric Bidirectional Impulsive Diffusion and Dispersal Delay

In most models of population dynamics, diffusion between two patches is assumed to be either continuous or discrete, but in the real natural ecosystem, impulsive diffusion provides a more suitable manner to model the actual dispersal (or migration) behavior for many ecological species. In addition, the species not only requires some time to disperse or migrate among the patches but also has some possibility of loss during dispersal. In view of these facts, a single species model with dissymmetric bidirectional impulsive diffusion and dispersal delay is formulated. Criteria on the permanence and extinction of species are established. Furthermore, the realistic conditions for the existence, uniqueness, and the global stability of the positive periodic solution are obtained. Finally, numerical simulations and discussion are presented to illustrate our theoretical results

Mesoporous WO3 Nanofibers With Crystalline Framework for High-Performance Acetone Sensing

Semiconducting metal oxides with abundant active sites are regarded as promising candidates for environmental monitoring and breath analysis because of their excellent gas sensing performance and stability. Herein, mesoporous WO3 nanofibers with a crystalline framework and uniform pore size is successfully synthesized in an aqueous phase using an electrospinning method, with ammonium metatungstate as the tungsten sources, and SiO2 nanoparticles and polyvinylpyrrolidone as the sacrificial templates. The obtained mesoporous WO3 nanofibers exhibit a controllable pore size of 26.3–42.2 nm, specific surface area of 24.1–34.4 m2g−1, and a pore volume of 0.15–0.24 cm3g−1. This unique hierarchical structure, with uniform mesopores and interconnected channels, could facilitate the diffusion and transportation of gas molecules in the framework. Gas sensors, based on mesoporous WO3 nanofibers, exhibit an excellent performance in acetone sensing with a low limit of detection (<1 ppm), short response-recovery time (24 s/27 s), a linear relationship in a broad range, and good selectivity

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Response of macrofaunal assemblages to different pollution pressures of two types of ports

Pollution status and benthic ecological quality of the two types of ports were assessed based on heavy metals and macrofaunal assemblages. Macrofaunal abundance and biomass in the industrial port were significantly higher than those in the fishing port. The dominant species of the two ports were Echinocardium cordatum and Nephtys oligobranchia. The AZTI marine biotic index (AMBI), multivariate AMBI, and Shannon-Wiener diversity index demonstrated that the benthic ecological quality of the two ports was moderate to good. The benthic ecological quality of the distant port sites was better than those of the nearby port sites. The geoaccumulation index and the Hakanson potential ecological risk index indicated that mercury posed a serious threat to port sediment pollution. AMBI, multivariate AMBI, and Shannon-Wiener diversity index were not good indicators for heavy metal pollution. The dominant species and Pielou’s evenness index were significantly correlated with heavy metal pollution and were good biological indicators

Investigation of the Optimization of Unloading Mining Scheme in Large Deep Deposit Based on Vague Set Theory and Its Application

With the development of shallow surface mineral resources in metal mines, it is gradually turning to the stage of deep mining. According to the current mining depth and the average annual depth, during the period of “14th Five-Year Plan,” one-third of the underground metal mines will reach or exceed the mining depth of 1,000 m, with the deepest being 2,000 m. In the stage of deep mining, mines will face the conditions of high stress, high temperature, high well depth, and strong mining disturbance, which will greatly increase the difficulty of large-scale deep mining. Among them, the high ground stress environment is the principal problem of many technical problems in deep mining. The selection of mining method has become a prerequisite for solving the problem of efficient and safe mining of deep deposits. In this paper, the vague set theory was introduced into the selection of mining methods and a vague set model for deep unloading mining schemes was established. Taking the Jinchuan No. 2 mining area as the engineering background, four unloading schemes for deep mining were proposed, and the Vague set model was used for optimization. It is concluded that the mining approach with large-section unloading is the optimal unloading mining plan. The application shows that it has the advantages of high unloading efficiency, large production capacity, and low loss index. It has been fully promoted in the deep mining of the mining area. It is feasible and effective to use the vague set theory in the selection of deep unloading mining schemes, which provides a proper approach in the selection of deep unloading mining schemes

Ultrasound-Guided versus Fluoroscopy-Guided Deep Cervical Plexus Block for the Treatment of Cervicogenic Headache

Objective. The aim of this study was to compare the efficacy of ultrasound-guided deep cervical plexus block with fluoroscopy-guided deep cervical plexus block for patients with cervicogenic headache (CeH). Methods. A total of 56 patients with CeH were recruited and randomly assigned to either the ultrasound-guided (US) or the fluoroscopy-guided (FL) injection group. A mixture of 2–4 mL 1% lidocaine and 7 mg betamethasone was injected along C2 and/or C3 transverse process. The measurement of pain was evaluated by patients’ ratings of a 10-point numerical pain scale (NPS) before and 2 wks, 12 wks, and 24 wks after treatments. Results. The blocking procedures were well tolerated. The pain intensity, as measured by NPS, significantly decreased at 2 wks after injection treatment in both US and FL groups, respectively, compared with that of baseline (P < 0.05). The blocking procedures had continued, and comparable pain relieving effects appeared at 12 wks and 24 wks after treatment in both US and FL groups. There were no significant differences observed in the NPS before and 2 wks, 12 wks, and 24 wks after treatment between US and FL groups. Conclusions. The US-guided approach showed similar satisfactory effect as the FL-guided block. Ultrasonography can be an alternative method for its convenience and efficacy in deep cervical plexus block for CeH patients without radiation exposure

A novel microdeletion of 517 kb downstream of the PAX6 gene in a Chinese family with congenital aniridia

Abstract Background To identify the disease-causing gene in a Chinese family affected with congenital aniridia. Methods Patients underwent systematic ophthalmic examinations such as anterior segment photography, fundus photography, optical coherence tomography, and fundus fluorescein angiography. The proband was screened for pathogenic variants by whole exome sequencing (WES) and copy number variant (CNV) analysis. Real-time quantitative PCR (RT-qPCR) was applied to confirm the CNV results. Breakpoints were identified by long-range PCR followed by Sanger sequencing. Results All seven members of this Chinese family, including four patients and three normal individuals, were recruited for this study. All patients showed bilateral congenital aniridia with nystagmus, except the son of the proband, who presented with bilateral partial coloboma of the iris. A novel heterozygous deletion (chr11:31,139,019–31,655,997) containing the 3’ regulatory enhancers of the PAX6 gene was detected in this family. We also reviewed the reported microdeletions downstream of PAX6 in patients with aniridia. Conclusions We identified a novel microdeletion, 517 kb in size located about 133 kb downstream of the PAX6 gene, responsible for congenital aniridia in this Chinese family, which expands the spectrum of aniridia-associated mutations in PAX6

A Deep-Learning-Based Artificial Intelligence System for the Pathology Diagnosis of Uterine Smooth Muscle Tumor

We aimed to develop an artificial intelligence (AI) diagnosis system for uterine smooth muscle tumors (UMTs) by using deep learning. We analyzed the morphological features of UMTs on whole-slide images (233, 108, and 30 digital slides of leiomyosarcomas, leiomyomas, and smooth muscle tumors of uncertain malignant potential stained with hematoxylin and eosin, respectively). Aperio ImageScope software randomly selected ≥10 areas of the total field of view. Pathologists randomly selected a marked region in each section that was no smaller than the total area of 10 high-power fields in which necrotic, vascular, collagenous, and mitotic areas were labeled. We constructed an automatic identification algorithm for cytological atypia and necrosis by using ResNet and constructed an automatic detection algorithm for mitosis by using YOLOv5. A logical evaluation algorithm was then designed to obtain an automatic UMT diagnostic aid that can “study and synthesize” a pathologist’s experience. The precision, recall, and F1 index reached more than 0.920. The detection network could accurately detect the mitoses (0.913 precision, 0.893 recall). For the prediction ability, the AI system had a precision of 0.90. An AI-assisted system for diagnosing UMTs in routine practice scenarios is feasible and can improve the accuracy and efficiency of diagnosis