Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Registration for Panoramic Images and Mobile LiDAR Data Based on Phase Hybrid Geometry Index Features

The registration of panoramic images and mobile light detection and ranging (LiDAR) data is quite challenging because different imaging mechanisms and viewing angle differences generate significant geometric and radiation distortions between the two multimodal data sources. To address this problem, we propose a registration method for panoramic images and mobile LiDAR data based on the hybrid geometric structure index feature of phase. We use the initial GPS/IMU to transform the mobile LiDAR data into an intensity map and align the two images to complete registration. Firstly, a novel feature descriptor called a hybrid geometric structure index of phase (HGIFP) is built to capture the structural information of the images. Then, a set of corresponding feature points is obtained from the two images using the constructed feature descriptor combined with a robust false-match elimination algorithm. The average pixel distance of the corresponding feature points is used as the error function. Finally, in order to complete the accurate registration of the mobile LiDAR data and panoramic images and improve computational efficiency, we propose the assumption of local motion invariance of 3D–2D corresponding feature points and minimize the error function through multiple reprojections to achieve the best registration parameters. The experimental results show that the method in this paper can complete the registration of panoramic images and the mobile LiDAR data under a rotation error within 12° and a translation error within 2 m. After registration, the average error of rotation is about 0.15°, and the average error of translation is about 1.27 cm. Moreover, it achieves a registration accuracy of less than 3 pixels in all cases, which outperforms the current five state-of-the-art methods, demonstrating its superior registration performance.
Hot electron detectors and energy conversion in the UV and IR

Semiconductor materials are well suited for power conversion when the incident photon energy is slightly larger than the bandgap energy of the semiconductor. However, for photons with energy significantly greater than the bandgap energy, power conversion efficiencies are low. Further, for photons with energy below the bandgap energy, the absence of absorption results in no power conversion. Here we describe photon detection and power conversion of both high energy and sub-bandgap photons using hot carrier effects. For the absorption of high-energy photons, excited electrons and holes have excess kinetic energy, which results in the generation of hot electrons and holes. Energy is typically lost through a thermalization process between the carriers and the lattice. However, collection of carriers before thermalization allows for reduced power loss. Devices consisting of a three-layer stack (transparent conductor – insulator – metal) can be used to generate and collect these hot carriers. Alternatively, when a semiconductor is used, photons with energy below the semiconductor bandgap energy generally do not generate electrons and holes; however, hot carrier collection is still possible in semiconductor devices with a metal layer when a Schottky junction is formed at the semiconductor-metal interface. Such structures enable IR detection based on sub-bandgap photon absorption. Combining these concepts, hot carrier generation and collection and be exploited over a large range of incident wavelengths spanning the UV, visible, and IR.
Completing a soundscape questionnaire reduces the psychological distance of sound and hearing

Objective: People are often resistant to hearing-health education messages such as those aimed at the prevention of noise-induced hearing loss. This resistance may be due to psychological distance: the perceived relevance of hearing and awareness of sound to daily life. The soundscape is the internal, perceptual, experience of a sound environment. The objective of this study was to explore people’s thought processes when completing a questionnaire designed to assess the soundscape and, in particular, to investigate whether the experience reduced psychological distance of sound and their hearing. Design: Semi-structured interviews and qualitative data analysis. Setting: Questionnaires were completed on personal phones in any environment participants wished. Interviews were conducted via online video connection. Method: A soundscape questionnaire was administered to a convenience sample of adult volunteers who were then interviewed about the experience of completing it, and how doing so had influenced their views of sound and their hearing. Results: Themes in three main areas were identified: the questions, which were found to be challenging but interesting; the soundscape, and the insights of participants about their own soundscape experience; and participants’ new awareness of sound and their own hearing. Conclusion: The findings provide interesting feedback about the meaning of responses to the questionnaire and on how people thought while using it. Furthermore, the findings imply that bringing the soundscape to a person’s conscious awareness may successfully reduce psychological distance for them about their hearing and may, therefore, be a useful preliminary to hearing-health education interventions.
PDHS: Pattern-Based Deep Hate Speech Detection With Improved Tweet Representation

Automatic hate speech identification in unstructured Twitter is significantly more difficult to analyze, posing a significant challenge. Existing models heavily depend on feature engineering, which increases the time complexity of detecting hate speech. This work aims to classify and detect hate speech using a linguistic pattern-based approach as pre-trained transformer language models. As a result, a novel Pattern-based Deep Hate Speech (PDHS) detection model was proposed to detect the presence of hate speech using a cross-attention encoder with a dual-level attention mechanism. Instead of concatenating the features, our model computes dot product attention for better representation by reducing the irrelevant features. The first level of Attention is extracting aspect terms using predefined parts-of-speech tagging. The second level of Attention is extracting the sentiment polarity to form a pattern. Our proposed model trains the extracted patterns with term frequency, parts-of-speech tag, and Sentiment Scores. The experimental results on Twitter Dataset can learn effective features to enhance the performance with minimum training time and attained 88%F1Score.
Differentiation through flexibility in implementation: Strategic and substantive uses of discretion in EU directives

This article analyses the extent to which European Union (EU) directives allow for variation in domestic implementation. Such flexibility in implementation may be used to deal with heterogeneity among member states. Based on an original dataset of 164 directives adopted between 2006 and 2015, we find that the use of flexibility is associated more with efforts to accommodate differences between national policies (substantive use of discretion) than with attempts to facilitate the decision-making process in and between EU legislative institutions (strategic use of discretion). Although flexibility may be used to address some of the same concerns that drive differentiated integration (DI), the situations in which each is most likely to be used are distinct because they approach the divergences between member states differently.
A Review on Trust Management in the Social Internet of Things: Issues and Challenges

In today's era, every electrical and electronic device is connected very intelligently. These electronic devices like sensors, RFIDs, actuators are becoming an important part of the structure. It is required to connect to the internet. Internet is used in every aspect of daily life. There are drastic changes in the usage of the most demanding and useful technology known as the Internet of Things (IoT). In this field, IoT has been shown one of the important which connect various physical objects with the internet with unique identification. Billions of objects are enabled with the internet and interconnected with each other to interface with Human-to-Machine or Machine-to-Machine to take decisions of data transaction without human involvement. This internet enables devices connected to our social life which is terme as Social Internet of Things (SIoT). Hence we can say SIoT is an expansion IoT. People and things are connected with social networks which are known as Human to Things (H2T) interactions. Some of the devices are authentic and some are suspicious. The essential utilization of services within SIoT makes a secured network closely rely on origin of services (Service provider) and services accesed by end terminal (Service requester). Due to a lack of trust technologies, trust SIoT is still not so much popular in the market as demanding technology for the researcher and developer. Device owners are worried about sharing the data or receiving any information. Therefore, trust devices are required to identify in the connected network.Hence minimization of risk and uncertaintity within the system are analyse by the degree of trust for Particular Trust Management System(TMS). Trust and Trustworthiness are novel fields in social networking environment clearlify by investigating the research article under SIoT. In present paper, our contribution starts with the introduction and then is further fragmented in three phases.The first phase represent the basic of trust and SIoT. Second phase categorizes the trust management solutions from the literature review. The third phase identifies and discuses issues, challenges and requirement in current scenario of SIoT and also depicts how developing trust and trustworthiness among social devices interaction as challenging task.
Analysis Of Foreign Debt and Foreign Investment On Economic Growth

This study examines the influence of foreign debt and foreign investment on economic growth in Indonesia from 2015 to 2020. The study was conducted with a quantitative approach. The research sample was conducted in 2 cities, namely, Malang and Jogjakarta with 200 respondents. Analysis tool using Structural Equation Modeling. The results of the study state that foreign debt has a positive and insignificant effect on economic growth in Indonesia, Foreign investment has a positive and significant impact on economic growth in Indonesia. The government needs to take steps to reduce foreign debt and try to increase investment in Indonesia so that development in Indonesia is more advanced. The government needs to increase foreign investment to support economic growth.
Optimizing the Choice for Adjuvant Chemotherapy in Gastric Cancer

Simple Summary Gastric cancer is the fourth largest cause of tumor-related death worldwide. Despite advances in the management of resectable cancer and improvements in early diagnosis, especially in east Asia where screening campaigns are actively performed, many patients experience recurrence and die because of the disease. Adjuvant systemic chemotherapy is administered after radical surgery in order to reduce the risk of recurrence and death. The modality of administration and regimens of chemotherapy in this setting are different between Eastern and Western countries. In Asia, adjuvant chemotherapy is traditionally given after surgery, while in Europe it is commonly scheduled after preoperative chemotherapy and surgery (perioperative chemotherapy), and in Northern America it is usually combined with radiotherapy (chemoradiotherapy). All these approaches are sustained by well-designed phase III clinical studies, and none may be considered superior to the others in the absence of head-to-head comparisons. The identification of predictive and/or prognostic factors could help to select patients at higher risk of recurrence and those more likely to receive a benefit from the adjuvant treatment. This would allow clinicians to avoid the administration of undue toxicity to non-responder patients and even to reduce the cost of unnecessary treatment. Abstract Advances in the management of gastric cancer have improved patient survival in the last decade. Nonetheless, the number of patients relapsing and dying after a diagnosis of localized gastric cancer is still too high, even in early stages (10% in stage I). Adjuvant systemic chemotherapy has been proven to significantly improve outcomes. In the present article we have critically reviewed the clinical trials that guide the current clinical practice in the adjuvant treatment of patients affected by resectable gastric cancer, focusing on the different approaches worldwide, i.e., adjuvant chemotherapy, adjuvant chemoradiotherapy, and perioperative chemotherapy. We also delineate the clinical–pathological characteristics that are commonly taken into account to identify patients at a higher risk of recurrence and requiring adjuvant chemotherapy, and also describe novel biomarkers and therapeutic agents that might allow personalization of the treatment.
Contribution of coherent structures to the buoyancy heat flux under different conditions of stationarity over Amazonian forest sites

The contribution of coherent structures (CSs) to daytime buoyancy heat flux was calculated for three forest sites in the Amazon region and a wetland site. Ejections and sweeps had similar contributions to fluxes at all sites, and when decomposing this contribution in scales, the resulting spectra were narrower for the forests. When accounting for times scales from 10 to 200s, CSs contributed to approximately 80% of fluxes for Caxiuanã forest site, with lower values for other locations. Among the forest, the contribution for the Jaru site was the lowest (≈66%) due to peak of contribution being close to 200s.
Mechanism of controlling robust and stable charging of open quantum batteries

Quality of charging and discharging of energy in quantum batteries are mostly affected by environmental dissipations, so the advantages of using such devices depend on the protection of them from the dissipations. In this work, we show that under a certain engineering of coupling strengths of each reservoir modes with elements of charging process (charger and battery), the extension of dissipative reservoir leads to a robust charging against the arisen dissipation. The extension of reservoir is provided by auxiliary systems each of which is similar to the coupled charger–battery system and has the same interactions with the reservoir modes as of the charger and battery constituents. It is demonstrated that the robustness of charging process is well controlled by the number of involved auxiliary systems. Furthermore, a method for stable charging is proposed which provides storing energy in a loss-free dark state of the battery. Also, we observe that the robustness of charging process is related to formation of bound state for the total system (charger–battery-extended reservoir) which in turns can be manipulated by the number of involved auxiliary systems.
Methodology in Robust and Nonparametric Statistics

Introduction and Synopsis Introduction Synopsis Preliminaries Introduction Inference in Linear Models Robustness Concepts Robust and Minimax Estimation of Location Clippings from Probability and Asymptotic Theory Problems Robust Estimation of Location and Regression Introduction M-Estimators L-Estimators R-Estimators Minimum Distance and Pitman Estimators Differentiable Statistical Functions Problems Asymptotic Representations for L-Estimators Introduction Bahadur Representations for Sample Quantiles L-Statistics with Smooth Scores General L-Estimators Statistical Functionals Second-Order Asymptotic Distributional Representations L-Estimation in Linear Model Breakdown Point of L- and M-Estimators Further Developments Problems Asymptotic Representations for M-Estimators Introduction M-Estimation of General Parameters M-Estimation of Location: Fixed Scale Studentized M-Estimators of Location M-Estimation in Linear Model Studentizing Scale Statistics Hadamard Differentiability in Linear Models Further Developments Problems Asymptotic Representations for R-Estimators Introduction Asymptotic Representations for R-Estimators of Location Representations for R-Estimators in Linear Model Regression Rank Scores Inference Based on Regression Rank Scores Bibliographical Notes Problems Asymptotic Interrelations of Estimators Introduction Estimators of location Estimation in linear model Approximation by One-Step Versions Further developments Problems Robust Estimation: Multivariate Perspectives Introduction The Notion of Multivariate Symmetry Multivariate Location Estimation Multivariate Regression Estimation Affine-Equivariant Robust Estimation Efficiency and Minimum Risk Estimation Stein-Rule Estimators and Minimum Risk Efficiency Robust Estimation of Multivariate Scatter Some Complementary and Supplementary Notes Problems Robust Tests and Confidence Sets Introduction M-Tests and R-Tests Minimax Tests Robust Confidence Sets Multiparameter Confidence Sets Affine-Equivariant Tests and Confidence Sets Problems Robust Estimation: Multivariate Perspectives Introduction The Notion of Multivariate Symmetry Multivariate Location Estimation Multivariate Regression Estimation Affine-Equivariant Robust Estimation Efficiency and Minimum Risk Estimation Stein-Rule Estimators and Minimum Risk Efficiency Robust Estimation of Multivariate Scatter Some Complementary and Supplementary Notes Problems Robust Tests and Confidence Sets Introduction M-Tests and R-Tests Minimax Tests Robust Confidence Sets Multiparameter Confidence Sets Affine-Equivariant Tests and Confidence Sets Problems
AN ANALYSIS OF MRI BRAIN IMAGE BY DEEP
LEARNING AND MULTI-CLASS SVM

It was critical to classify and identify brain tumours in order to protect human life. These two were assessed for difficult issues in a medical imaging. It is regarded as crucial for CAD. It develops as a result of the brain's unregulated cell growth. It was divided into two categories. There are two types of tumours: benign and malignant. The function of an automatic monitoring system using a Cable Neural Network, soft max, and numerous classes of Support Vector Machine is examined in this study. It was readily seen that following the proper learning techniques yields flawless results. Early detection of a brain tumour helps to ensure the patient's safety. It is used to give the correct treatment and provides the important notion to the doctor to treat the patient perfectly. A medical image database was very difficult to classify. Founding and diving brain tumor, the combination of support vector machine and cable neural network are classified the input Magnetic Resonance Image that was non-tumor and tumor. This examined method was valued by the fig share dataset and analyze the examined method to produce high perfection. A multiclass support vector machine was driven with the characteristics of cable neural network. Investigating and testing the process used 5 fold validation process with Fig share, Harvard and Radio pedia data set. The examined methods was valued by fig share data set and produced division perfection of 98.96% of cable neural network along with softmax and provides a perfection of 99.8% of cable neural network along with M-support vector machine.
Association between CHADS2, CHA2DS2-VASc, ATRIA, and Essen Stroke Risk Scores and Functional Outcomes in Acute Ischemic Stroke Patients Who Received Endovascular Thrombectomy

Background: CHADS2, CHA2DS2-VASc, ATRIA, and Essen stroke risk scores are used to estimate thromboembolism risk. We aimed to investigate the association between unfavorable outcomes and stroke risk scores in patients who received endovascular thrombectomy (EVT). Methods: This study was performed using data from a nationwide, multicenter registry to explore the selection criteria for patients who would benefit from reperfusion therapies. We calculated pre-admission CHADS2, CHA2DS2-VASc, ATRIA, and Essen scores for each patient who received EVT and compared the relationship between these scores and 3-month modified Rankin Scale (mRS) records. Results: Among the 404 patients who received EVT, 213 (52.7%) patients had unfavorable outcomes (mRS 3–6). All scores were significantly higher in patients with unfavorable outcomes than in those with favorable outcomes. Multivariable logistic regression analysis indicated that CHADS2 and the ATRIA score were positively correlated with unfavorable outcomes after adjusting for body mass index and variables with p < 0.1 in the univariable analysis (CHADS2 score: odds ratio [OR], 1.484; 95% confidence interval [CI], 1.290–1.950; p = 0.005, ATRIA score, OR, 1.128; 95% CI, 1.041–1.223; p = 0.004). Conclusions: The CHADS2 and ATRIA scores were positively correlated with unfavorable outcomes and could be used to predict unfavorable outcomes in patients who receive EVT.
¿Qué hacer? Repertorios de acción frente a las injusticias percibidas en los lugares de trabajo en Santiago de Chile

Resumen ¿Qué hacen los trabajadores asalariados para responder a situaciones de injusticia en sus lugares de trabajo? Este artículo examina distintos repertorios de acción desplegados por trabajadores en el contexto laboral chileno, caracterizado por altos niveles de desigualdad salarial y una débil estructura sindical. Se analizan ocho grupos focales en los cuales trabajadores conversaron acerca de cómo responder a injusticias percibidas en el mundo laboral. Se identifican cinco repertorios que cuentan con diversos grados de legitimidad según el nivel socioeconómico del grupo: neoliberal, managerial, sindical, fatalista y resiliente. Se argumenta que el repertorio neoliberal ofrece a los grupos profesionales una mayor capacidad de respuesta ante injusticias distributivas y procedimentales, mientras que el repertorio resiliente ofrecería a trabajadores no calificados un set de herramientas culturales para hacer frente a los agravios a la dignidad en los lugares de trabajo. Los grupos de supervisores adoptarían en mayor medida un repertorio managerial, impulsados por gestionar el clima laboral en contextos de baja legitimidad de los sindicatos y miedo al conflicto. Se concluye que en contextos laborales fuertemente desregulados, como el caso chileno, una apropiación diferenciada de repertorios podría contribuir a reforzar las desigualdades existentes en el trabajo.
Design and Analysis of Single Inverter-Fed Brushless Wound Rotor Vernier Machine

In this paper, a brushless wound rotor vernier machine (Bl-WRVM) with a single inverter configuration is proposed to achieve the brushless operation. In the proposed topology, a single inverter is connected with series-connected ABC and XYZ windings through which the current flow produces the magnetomotive force with fundamental and sub-harmonic components, respectively. The XYZ windings have similar pole pairs to the excitation windings, whereas its number of poles is different from the ABC winding. A 24-slot stator, 4-pole armature ABC winding, 2 Pole armature XYZ and excitation windings, and 44-pole field winding for the outer rotor is designed and 2D finite element analysis is carried out to determine the performance of the machine. The proposed topology makes the Bl-WRVM cost-effective by applying only a single inverter as compared to a dual-inverter Bl-WRVM and it improves its torque quality.