Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Ultrasound in the Evaluation of Inguinal Lymph Nodes in Patients with Vulvar Cancer: A Systematic Review and Meta-Analysis

Simple Summary Currently, around 30% of vulvar cancer cases at first diagnosis are spread to the inguinal lymph nodes. Preoperative staging of patients affected by vulvar carcinoma is still a hot topic. To date, MRI has shown a great diagnostic accuracy on defining disease extension to soft tissue and deep organs. At present, regarding the study of inguinal nodes, the PET/CT scan has shown a high negative predictive value, although in the presence of a suspicious/positive report it should be taken with caution. We report the results of a study aimed to investigate the role of groin ultrasound in the assessment of lymph nodal status in vulvar cancer. Furthermore, this review represents the most accurate collection of papers available in the literature. This work demonstrates that groin ultrasound can be considered a valuable tool for risk assessment of the presence of groin lymph node metastases. Achieving a high diagnostic accuracy would allow tailored surgical planning with access to minimally invasive surgery techniques for an increasing number of patients. Abstract Objective. To determine the efficacy of ultrasound in assessing the inguinal lymph nodes in patients with vulvar cancer. Methods. A systematic review of published research up to October 2020 that compares the results of ultrasound to determine groin node status with histology was conducted. All study types that reported primary data on the role of ultrasound in the evaluation of groin lymph nodes in vulvar cancer were included in the systematic review. Data retrieved from the included studies were pooled in random-effects meta-analyses. Results. After the screening and selection process, eight articles were deemed pertinent for inclusion in the systematic review and meta-analysis. The random-effects model showed a pooled Se of 0.85 (95% CI: 0.81–0.89), Sp of 0.86 (95% CI: 0.81–0.91), PPV of 0.65 (95% CI: 0.54–0.79) and NPV of 0.92 (95% CI: 0.91–0.94). There was a pooled LR+ and LR− of 6.44 (95% CI: 3.72–11.4) and 0.20 (95% CI: 0.14–0.27), respectively. The pooled accuracy was 0.85 (95% CI: 0.80–0.91). Conclusions. Although the studies had small sample sizes, this review represents the best summary of the data so far. Ultrasound has revealed high sensitivity and high negative predictive value in the assessment of nodal status in vulvar cancer.
The Impact of Public Opinion Pressure on Construction Company Green Innovations: The Mediating Effect of Leaders' Environmental Intention and the Moderating Effect of Environmental Regulation

Media has paid more attention recently on environmental issues caused by construction companies which imposes public opinion pressure on construction companies and could potentially impact their decision-making processes for green innovations. However, research on the relationship between public opinions pressure and construction company green innovation behavior is still limited. To understand how such public opinions pressure can impact construction companies' green transition and formulate advice accordingly, it is necessary to use empirical data to find the correlations. Therefore, this research has gathered questionnaire data of the construction companies in Chengdu-Chongqing economic circle of China to study the influencing mechanism of environmental public opinion pressure on enterprise green innovation behavior, analyzes the realization path of leaders' environmental intention as a mediating variable in the impact of environmental public opinion pressure on enterprise green innovation behavior, and reveals the role boundary of environmental regulation as a moderating variable in the impact of environmental public opinion pressure on enterprise green innovation behavior. The results show that environmental public opinion pressure has a significant positive impact on enterprise green innovation behavior. More specifically, enterprise green innovation behavior is affected by leaders' environmental intention and the latter plays a partial mediating role between environmental public opinion pressure and enterprise green innovation behavior. Environmental regulation also enhances the sensitivity of companies to environmental public opinion pressure, and therefore can significantly strengthen the relationship between environmental public opinion pressure and enterprise green innovation behavior. Further research find that, compared with incentive-based environmental regulations, mandatory environmental regulations make companies more sensitive to environmental public opinion pressure and has a more significant positive moderating effect. The research conclusions could be used to provide theoretical reference with empirical data for accelerating the green innovation transformation and promoting the high-quality development in the construction industry.
Analysis and Prediction of Corporate Finance and Exchange Rate Correlation Based on Machine Learning Algorithms

Based on the risk management of exposure to foreign exchange assets and liabilities and the application of financial derivatives, this paper provides an in-depth analysis of the financial and exchange rate risks of foreign-funded enterprises. Therefore, a method of evaluating the financial performance of listed financial enterprises based on principal component analysis and neural network model is proposed. First, principal components of alternative financial performance input-output indicators are extracted using principal component analysis. Subsequently, these principal components are used as input-output data for the DEA model to derive the relative validity evaluation results of the financial performance of individual financial enterprises and to provide a reference for decision making to improve the financial performance level of financial enterprises. Combined with the economic business data of the enterprises, an empirical test on exchange rate risk management is conducted and relevant suggestions are made on how foreign enterprises can reduce exchange rate risk losses. It has important theoretical value and practical significance for enterprise finance and exchange rate management.
Privacy protection in smart meters using homomorphic encryption: An overview

This article presents an overview of the literature on privacy protection in smart meters with a particular focus on homomorphic encryption (HE). Firstly, we introduce the concept of smart meters, the context in which they are inserted the main concerns and oppositions inherent to its use. Later, an overview of privacy protection is presented, emphasizing the need to safeguard the privacy of smart‐meter users by identifying, describing, and comparing the main approaches that seek to address this problem. Then, two privacy protection approaches based on HE are presented in more detail and additionally we present two possible application scenarios. Finally, the article concludes with a brief overview of the unsolved challenges in HE and the most promising future research directions.
Fresnel Volume Ground Penetrating Radar Attenuation Difference Tomography and Incorporating Geostatistical Constraints in Nonlinear Inverse Problems

The role of geophysics in the characterization and monitoring of hydrological systems is rapidly expanding to advance the understanding of fluid flow in the Earth. The non-invasive probing of the subsurface using different geophysical methods provides a wide range of possibilities to study the static and dynamic nature of subsurface flow systems. Water resource management is both a local and global concern. Fate and transport of contaminants, environmental remediation, and contaminant monitoring require accurate and spatially extensive knowledge of the heterogeneous subsurface. Direct measurements using borehole techniques are accurate but lack sufficient spatial coverage to determine hydraulic parameters at a large scale. In this thesis I focus on two broad areas: (a) improvement of the physics in tomographic imaging using cross-hole ground-penetrating radar and (b) development of a methodology to incorporate geostatistical scale information into the geophysical images that naturally leads to uncertainty estimation in a statistical sense. Although this method is applicable do inverse problems in general, it is demonstrated in conjunction with a ground-penetrating radar velocity tomography problem. Tomography, a commonly used method in exploration geophysics, is increasingly used in near-surface applications to determine property distributions such as the seismic or radar velocity of the material traversed by propagating seismic or electromagnetic energy. Near-surface investigations using tomographic methods pose significant scientific challenges in terms of determining the uncertainty in the geophysical parameter estimates. This difficulty results from the less-than-optimal coverage needed to image the desired scale of the heterogeneity and infinite frequency assumption that is the basis for commonly used ray theoretical radar tomograms. I examine the attenuation responses
Plasmodium knowlesi Cytoadhesion Involves SICA Variant Proteins

Plasmodium knowlesi poses a health threat throughout Southeast Asian communities and currently causes most cases of malaria in Malaysia. This zoonotic parasite species has been studied in Macaca mulatta (rhesus monkeys) as a model for severe malarial infections, chronicity, and antigenic variation. The phenomenon of Plasmodium antigenic variation was first recognized during rhesus monkey infections. Plasmodium-encoded variant proteins were first discovered in this species and found to be expressed at the surface of infected erythrocytes, and then named the Schizont-Infected Cell Agglutination (SICA) antigens. SICA expression was shown to be spleen dependent, as SICA expression is lost after P. knowlesi is passaged in splenectomized rhesus. Here we present data from longitudinal P. knowlesi infections in rhesus with the most comprehensive analysis to date of clinical parameters and infected red blood cell sequestration in the vasculature of tissues from 22 organs. Based on the histopathological analysis of 22 tissue types from 11 rhesus monkeys, we show a comparative distribution of parasitized erythrocytes and the degree of margination of the infected erythrocytes with the endothelium. Interestingly, there was a significantly higher burden of parasites in the gastrointestinal tissues, and extensive margination of the parasites along the endothelium, which may help explain gastrointestinal symptoms frequently reported by patients with P. knowlesi malarial infections. Moreover, this margination was not observed in splenectomized rhesus that were infected with parasites not expressing the SICA proteins. This work provides data that directly supports the view that a subpopulation of P. knowlesi parasites cytoadheres and sequesters, likely via SICA variant antigens acting as ligands. This process is akin to the cytoadhesive function of the related variant antigen proteins, namely Erythrocyte Membrane Protein-1, expressed by Plasmodium falciparum.
Bilateral Privacy-Preserving Worker Selection in Spatial Crowdsourcing

Spatial Crowdsourcing (SC) has been adopted in various applications such as Gigwalk and Uber, where a platform takes location-based tasks (e.g., picking up passengers) from a requester and selects suitable workers to perform them. In most existing works, the platform selects workers based on the requester and worker information, which suffers from serious privacy issues. Some works have considered privacy issues, but they still suffer from either of two limitations: (i) Privacy of the requester and worker cannot be protected simultaneously; (ii) Third-party trusted entities are usually required. Motivated by this, we focus on protecting the privacy of both the requester and the worker without third-party entities while selecting workers. We use randomized response, a widely recognized and prevalent privacy model achieving Local Differential Privacy (LDP), to jointly protect the privacy of workers’ locations and charges based on the location-charge correlation. For the requester, we present a novel mechanism called randomized matrix multiplication to hide the real task locations. More importantly, we prove that the worker selection based on the protected information is non-submodular and NP-hard, which cannot be addressed in polynomial time. To this end, we present an approximate algorithm to solve the problem efficiently, of which the effectiveness is measured by the approximation ratio, i.e., the ratio of the optimal solution to the approximate solution. Finally, simulations based on real-world datasets illustrate that our worker selection outperforms the state-of-the-art method on both privacy protection and worker selection.
Observer-Based Adaptive Scaled Tracking Control for Nonlinear MASs via Command-Filtered Backstepping

This article focuses on the problem of adaptive scaled consensus tracking control for uncertain nonlinear multiagent systems (MASs) subjected to unknown mixed control gains, input delays, and external disturbances. First, a new form of nonlinear MAS is presented by linear state transformation. Second, a state observer based on adaptive radial basis function neural networks is developed to estimate the unmeasured states. A command filter control scheme is deployed to address the problem of increased sharply complexity derived from the conventional backstepping design with the increase of the system order, and the filtered error is compensated by the error compensation mechanism. Third, by taking advantage of the Lyapunov–Krasovskii functionals, a compensation control strategy is intended to exclude the impact of input delays. In addition, a Nussbaum-gain function is used to deal with the problem of uncertain control direction. An adaptive output feedback control approach is raised to construct the scaled consensus tracking control protocol, error compensating signals, and adaptive laws. It is proved that the tracking errors are driven to a small residual set, and all the signal variables are bounded in the closed-loop system. Finally, the effectiveness of the proposed approach is verified by two numerical simulations.
Hybrid employment recommendation algorithm based on Spark

Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.
Gender Inequality in Pakistan: An Assessment

The gender analysis reveals the widening discrepancy between men and women in a number of sectors, as well as the difficulties Pakistan confronts in addressing these issues. There are only a few data points available on gender gaps in specific areas like educational success, health, and political engagement that could be used to help us reach this goal. A lack of resources and opportunities, as well as a scarcity of knowledge and information, exacerbate the gender gap. In terms of political engagement, educational attainment, and economic production, the study looks at Pakistan's gender disparities. We gathered data from a range of government, foreign development, and local non-governmental organizations for this study. Based on the findings of a gender assessment, a variety of techniques and policies can be implemented to address gender issues. Government education spending should prioritize gender equality while identifying places where there is a greater gender divide. Increased government spending on education and political engagement will have a huge positive impact on rural women.
Investigation of User Effects on Mobile Phased Antenna Array from 5 to 6 GHz

The goal of this paper is to evaluate the impact of the user to the performance of a phased antenna array in the frequency range from 5 to 6 GHz. The design consists of four quarter wavelength dipoles printed on the short edge of an FR4 substrate. Simulations including a 105° phase shifter proved that the antenna array can cover a 120° beamwidth, with a gain of 7 dBi. The analysis of the user effects in terms of total scan pattern (TSP) and coverage efficiency is carried out via simulations both in data mode and in talk mode. The comparison with the performance in free space shows a loss in gain from 2 dB up to 7 dB, due to the user hand and the user hand-head respectively. Simulation results have been confirmed by the measurements of the prototype with a hand and head phantoms.
Bloodstream Infections Caused by Carbapenem-Resistant Pathogens in Intensive Care Units: Risk Factors Analysis and Proposal of a Prognostic Score

Considering the growing prevalence of carbapenem-resistant Gram-negative bacteria (CR-GNB) bloodstream infection (BSI) in intensive care units (ICUs), the identification of specific risk factors and the development of a predictive model allowing for the early identification of patients at risk for CR-Klebsiella pneumoniae, Acinetobacter baumannii or Pseudomonas aeruginosa are essential. In this retrospective case–control study including all consecutive patients showing an episode of BSI in the ICUs of a university hospital in Italy in the period January–December 2016, patients with blood culture positive for CR-GNB pathogens and for any other bacteria were compared. A total of 106 patients and 158 episodes of BSI were identified. CR-GNBs induced BSI in 49 patients (46%) and 58 episodes (37%). Prognosis score and disease severity at admission, parenteral nutrition, cardiovascular surgery prior to admission to ICU, the presence of sepsis and septic shock, ventilation-associated pneumonia and colonization of the urinary or intestinal tract were statistically significant in the univariate analysis. The duration of ventilation and mortality at 28 days were significantly higher among CR-GNB cases. The prognostic model based on age, presence of sepsis, previous cardiovascular surgery, SAPS II, rectal colonization and invasive respiratory infection from the same pathogen showed a C-index of 89.6%. The identified risk factors are in line with the international literature. The proposal prognostic model seems easy to use and shows excellent performance but requires further studies to be validated.
Basic study for Human Spatial Cognition Based on Brain Activity during Car Driving

—The purpose in this research is to contribute to developing of assistive robot and related-apparatus. Recently, there is a pressing need to develop a new system which assists and acts for car driving and wheelchair for the elderly as the population grows older. In terms of developing a new system, it is thought that it is important to examine behaviors as well as spatial recognition. Therefore, experiments have been performed for an examination of human spatial perceptions, especially right and left recognition, during car driving using NIRS. In previous research, it has been documented that there were significant differences at dorsolateral prefrontal cortex at left hemisphere during virtual driving task and actual driving. In this paper, brain activity during car driving was measured and detailed analysis was performed by segmentalizing brain activity during car driving on the basis of subjects’ motion. So, we report the relationship between brain activity and movement concerned with perception during driving in this paper.
A study of mobile robot motion planning

This thesis studies motion planning for mobile robots in various environments. The basic tools for the research are the configuration space and the visibility graph. A new approach is developed which generates a smoothed minimum time path. The difference between this and the Minimum Time Path at Visibility Node (MTPVN) is that there is more clearance between the robot and the obstacles, and so it is safer. The accessibility graph plays an important role in motion planning for a massless mobile robot in dynamic environments. It can generate a minimum time motion in 0(n2»log(n)) computation time, where n is the number of vertices of all the polygonal obstacles. If the robot is not considered to be massless (that is, it requires time to accelerate), the space time approach becomes a 3D problem which requires exponential time and memory. A new approach is presented here based on the improved accessibility polygon and improved accessibility graph, which generates a minimum time motion for a mobile robot with mass in O((n+k)2»log(n+k)) time, where n is the number of vertices of the obstacles and k is the number of obstacles. Since k is much less than n, so the computation time for this approach is almost the same as the accessibility graph approach. The accessibility graph approach is extended to solve motion planning for robots in three dimensional environments. The three dimensional accessibility graph is constructed based on the concept of the accessibility polyhedron. Based on the properties of minimum time motion, an approach is proposed to search the three dimensional accessibility graph to generate the minimum time motion. Motion planning in binary image representation environment is also studied. Fuzzy logic based digital image processing has been studied. The concept of Fuzzy Principal Index Of Area Coverage (PIOAC) is proposed to recognise and match objects in consecutive images. Experiments show that PIOAC is useful in recognising objects. The visibility graph of a binary image representation environment is very inefficient, so the approach usually used to plan the motion for such an environment is the quadtree approach. In this research, polygonizing an obstacle is proposed. The approaches developed for various environments can be used to solve the motion planning problem without any modification. A simulation system is designed to simulate the approaches.
Exciton-polaritons in low dimensional structures

Some special features of polaritons, quasi-particles being normal modes of system of excitons interacting with photons in so called strong coupling regime, are theoretically and numerically analyze in low dimensional systems. In Chapter 1 is given a brief overview of 0D, 1D and 2D semiconductor structures with a general introduction to the polariton field. Chapter 2 is devoted to micro / nano wires. The so called whispering gallery modes are studied in the general case of an anisotropic systems as well as polariton formation in ZnO wires. Theoretical model is compared with an experiment. In the Chapter 3 Josephson type dynamics with Bose-Einstein condensates of polaritons is analyzed taking into account pseudospin degree of freedom. Chapter 4 start with an introduction to Aharonov-Bohm effect, as the best known represent of geometrical phases. An another geometrical phase – Berry phase, occurring for a wide class of systems performing adiabatic motion on a closed ring, is main subject of this section. We considered one proposition for an exciton polariton ring interferometer based on Berry phase effect. Chapter 5 concerns one 0D system : strongly coupled quantum dot exciton to cavity photon. We have discussed possibility of obtaining entangled states from a quantum dot embedded in a photonic crystal in polariton regime.