Uniqueness in inverse scattering with phaseless near-field data generated by superpositions of two incident plane waves

This paper is concerned with the uniqueness in inverse acoustic and electromagnetic scattering with phaseless near-field data generated by superpositions of two incident plane waves at a fixed frequency. It can be proved that the unknown scatterer can be uniquely determined by the phaseless near-field data. The proof is based on the analysis of the phase information and the application of Rellich's lemma together with the Green's formula for the radiating solutions to the Helmholtz equation or the Stratton--Chu formula for the radiating solutions to the Maxwell equations

Innovation policy and firm patent value: evidence from China

This study aims to contribute to the empirical literature that evaluates the impact of the Science & Technology (S&T) Outline, a Chinese innovation policy implemented in 2006, measured by the scale of patent value. We first create a comprehensive patent valuation model (CPVM), derived from the extended patent renewal model and a variety of feature indices, to measure a firm’s patent value. From a database with over 700,000 Chinese patents from 1985 to 2013, we find that the patent value increases after the release of the S&T Outline, and the scale of patent value after 2006 is about 26.52 times more than that before 2006. Further, we use a quasi-difference in differences (DID) model to estimate the growth effect caused by the innovation policy. The results indicate that the S&T Outline had a significant effect on the promotion of patent value, in industries with high patent intensity. Considering the lag effect of the S&T Outline, we construct innovation correlation networks to visualise and compare its promotion effect. We find that regional networks have a gathering tendency after policy implementation, while industrial networks have a decentralising tendenc

Karar Ağacı Algoritması Kullanılarak Çin Topraklarındaki Orta Dereceli Okul Öğrencilerine İlişkin Jeo-Uzamsal Düşünme Yeteneğinin Tahmin Edilmesi

Predicting secondary school students' geospatial thinking ability can provide targeted guidance for teachers. To date, few scholars have focused on predicting students’ geospatial thinking ability. In this paper, we address this gap by constructing a prediction model based on the decision tree algorithm, to predict the geospatial thinking ability of secondary school students. A total of 1029 secondary school students were surveyed using the Spatial Thinking Ability Test, the Students' Geography Learning Status Questionnaire, and the Middle Students Motivation Test. Our model indicates that geospatial thinking ability can be predicted by nine factors, in order of importance: academic achievement in geography, geography learning strategy, geography classroom environment, gender, learning initiative, learning goals, extra-curricular time spent learning geography, ego-enhancement drive, and interest in learning geography. The model accuracy is 81.25%. Specifically, our study is the first to predict geospatial thinking ability. It provides a tool for teachers that can help them identify and predict students' geospatial thinking ability, which is conducive to designing better teaching plans and making adjustments to the curriculum.Orta dereceli okul öğrencilerinin jeo-uzamsal düşünme yeteneklerinin tahmin edilmesi öğretmenler için hedefe yönelik rehberlik sağlayabilir. Şimdiye kadar az sayıda bilim insanı, öğrencilerin jeo-uzamsal düşünme yeteneklerinin tahmin edilmesine odaklanmıştır. Bu makalede, orta dereceli okul öğrencilerinin jeo-uzamsal düşünme yeteneklerinin tahmin edilmesi amacıyla karar ağacı algoritmasına dayanan bir tahmin modeli oluşturarak bu boşluğu doldurmayı amaçlıyoruz. Uzamsal Düşünme Yeteneği Testi, Öğrencilerin Coğrafya Öğrenimi Durumu Anketi ve Orta Dereceli Okul Öğrencileri Motivasyon Testi kullanılarak toplam 1029 orta dereceli okul öğrencisine anket uygulanmıştır. Modelimiz, jeo-uzamsal düşünme yeteneğinin dokuz etmenle tahmin edilebileceğine işaret etmektedir. Önem sırasına göre bu etmenler; coğrafya dersindeki akademik başarı, coğrafya öğrenimi stratejisi, coğrafya sınıf ortamı, cinsiyet, öğrenme inisiyatifi, öğrenme hedefleri, coğrafya öğreniminde harcanan müfredat harici zaman, benlik geliştirme dürtüsü ve coğrafya öğrenimine ilgi şeklindedir. Model doğruluk oranı %81,25’tir. Özellikle, çalışmamız jeo-uzamsal düşünme yeteneğinin tahmin edilmesine yönelik ilk çalışmadır. Öğretmenlere öğrencilerin jeo-uzamsal düşünme yeteneklerini saptamalarına ve tahmin etmelerine yardımcı olabilecek bir araç sunan çalışmamız böylelikle daha iyi eğitim planları hazırlanmasında ve müfredatta düzenlemeler yapılmasında fayda sağlayacaktır

dsRNA Virus Model Molecule and the Mechanism of PRRs and its Research Progress in Female Reproductive Tract Infections

Female animal genital tract opening on the body surface, prone to bacterial, viral, parasitic, and other pathogenic microorganism infections, leading to genital tract infectious diseases, such as endometritis, cervicitis, vaginitis, etc. Severe infection can lead to infertility, abortion, and even fetal death. Double-stranded RNA (dsRNA) is an important model molecule, which is widely present in the genome of viruses and generated in the process of virus replication. In mammals, dsRNA is considered to be an innate immune response signal for viral infection, which binds to the corresponding pattern-recognition receptors (PRRs) In vivo and then exerts biological functions. This review summarizes the signal transduction pathway induced by the binding of dsRNA model molecules to PRRs, research status of female genital tract infections and research progress of dsRNA in simulating viral infection in the female genital tract