Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping modern economic rents: the good, the bad, and the grey areas

There is increasing consensus that modern capitalist economies suffer from excessive rent extraction in both financial and real economy sectors. However, scholars have yet to develop a coherent analytical framework for identifying the common characteristics of modern economic rents. In particular, there has been little attention paid to distinguishing ‘good’ rents—key to innovation and growth—from ‘bad’ forms which contribute to economic stagnation and inequalities of wealth and income. This paper takes some first steps in this direction. We first review the existing rent theory most pertinent to this distinction, including classical political economy, the early twentieth century institutionalists, neoclassical perspectives and Keynes’s analysis of financial rentiers. Secondly, we map and conceptualise some key stylised features of modern rents, drawing on descriptive empirical evidence. We then identify the key questions that these developments raise for rent theory, elaborating a new research and policy agenda.
Evaluating the Mental Health of Physician-Trainees Using an SMS Text Message–Based Assessment Tool: Longitudinal Pilot Study

Background Physician burnout is a multibillion-dollar issue in the United States. Despite its prevalence, burnout is difficult to accurately measure. Institutions generally rely on periodic surveys that are subject to recall bias. SMS text message–based surveys or assessments have been used in health care and have the advantage of easy accessibility and high response rates. Objective In this pilot project, we evaluated the utility of and participant engagement with a simple, longitudinal, and SMS text message–based mental health assessment system for physician-trainees at the study institution. The goal of the SMS text message–based assessment system was to track stress, burnout, empathy, engagement, and work satisfaction levels faced by users in their normal working conditions. Methods Three SMS text message-based questions per week for 5 weeks were sent to each participant. All data received were deidentified. Additionally, each participant had a deidentified personal web page to follow their scores as well as the aggregated scores of all participants over time. A 13-question optional survey was sent at the conclusion of the study to evaluate the usability of the platform. Descriptive statistics were performed. Results In all, 81 participants were recruited and answered at least six (mean 14; median 14; range 6-16) questions for a total of 1113 responses. Overall, 10 (17%) out of 59 participants responded “Yes” to having experienced a traumatic experience during the study period. Only 3 participants ever answered being “Not at all satisfied” with their job. The highest number of responses indicating that participants were stressed or burnt out came on day 25 in the 34-day study period. There were mixed levels of concern for the privacy of responses. No substantial correlations were noted between responses and having experienced a traumatic experience during the study period. Furthermore, 12 participants responded to the optional feedback survey, and all either agreed or strongly agreed that the SMS text message–based assessment system was easy to use and the number of texts received was reasonable. None of the 12 respondents indicated that using the SMS text message–based assessment system caused stress. Conclusions Responses demonstrated that SMS text message–based mental health assessments are potentially useful for recording physician-trainee mental health levels in real time with minimal burden, but further study of SMS text message–based mental health assessments should address limitations such as improving response rates and clarifying participants’ sense of privacy when using the SMS text message–based assessment system. The findings of this pilot study can inform the development of institution-wide tools for assessing physician burnout and protecting physicians from occupational stress.
The Relationship between Internet Patient Satisfaction Ratings and COVID-19 Outcomes

Our prior research showed that patient experience—as reported by Google, Yelp, and the Hospital Consumer Assessment of Healthcare Providers and Systems survey—is associated with health outcomes. Upon learning that COVID-19 mortality rates differed among U.S. geographic areas, we sought to determine if COVID-19 outcomes were associated with patient experience. We reviewed daily, U.S.-county-level-accrued COVID-19 infections and deaths during the first year of the pandemic using each locality’s mean online patient review rating, correcting for county-level demographic factors. We found doctor star ratings were significantly associated with COVID-19 outcomes. We estimated the absolute risk reduction (ARR) and relative risk reduction (RRR) for each outcome by comparing the real-world-observed outcomes, observed with the mean star rating, to the outcomes predicted by our model with a 0.3 unit higher average star rating. Geographic areas with higher patient satisfaction online review ratings in our models had substantially better COVID-19 outcomes. Our models predict that, had medical practices nationwide maintained a 4-star average online review rating—a 0.3-star increase above the current national average—the U.S may have experienced a nearly 11% lower COVID-19 infection rate and a nearly 17% lower death rate among those infected.
Stabilization for High Order Nonlinear Critical Systems

The aim of the thesis is to study the stabilization of the system x = f(x)+bu. Here the linearization system contains a high order controllable mode. First, by center manifold theory, we can reduce the dynamics of the given system (higher order system) to the dynamics of the center manifold system(lower order system). Second, using normal forms or Lyapunov function, we can find a sufficient condition such that the center manifold system is locally asymptotically stable. That is, we can control u(x) such that the given system is stabilized.
Semiautomatic Building Extraction by Least Squares Matching Based on GeoMetrical Constraints in Object Space

The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair.In the semiautomatic extraction system,the building model is defined by selected roof type input through human_machine interface and input points of rough position of the building by operator.With the geometrical constraints of the model,low_level and mid_level processing including edge detection,straight line segments extraction and line segments grouping are to establish the initial geometrical model of the roof_top. However,the initial geometrical model is not so accurate in geometry.To attain accurate results,straight_line extraction and positioning by least squares matching with object_space based geometrical constraints rectifies the initial geometrical model.The adjustment model integrates the straight edge pattern and 3D constraints together and is a well_studied optimal method.The edge model is based on strict zero_crossing definition,and the strict geometrical constraints of the corners of the extracted building as 'knowledge' that is clearly described by the adjustment model are fused with image feature,such as edge and straight line.The model uses all of the information and constraints of the building borders to attain an optimal result,so this is a model driven strategy that matches the roof model with the image pair depending on the criteria of least squares.In principle,the method does not need feature detection,so there are no threshold problemes.After gaining proper initial values,the adjustment model can flexibly process extraction of kinds of roof types by changing or assembling the geometrical constraints in object_space. On the other hand,the paper also discusses the scheme of practical system of semiautomatic extraction.To build a practical semiautomatic extraction system,correctness,accuracy,robustness,speed and interactivity,all these factors should be taken into account.In the paper,a robust algorithm of extracting main direction of the house is addressed.By detecting edge,tracing the edge chain vectors and extracting straight_line segments,a Weighted Histogram of Angles (WHoA) is generated by the angles of extracted line segments.With the histogram,the main direction of the building can be easily detected by searching the max value of the histogram.Histogram method is a statistical manner like Hough transformation; it can effectively remove the influences of gaps between collinear segments and racket segments.The experiments show that that main direction and outer border detection by the WHoA method is robust.The line segments extraction and confirming the main direction of the house could save the operator's input action and offer good initial values of the corners for the consequent adjustment evaluation.
The Dynamic Interplay between Loss of Semantic Memory and Semantic Learning Capacity: Insight from Neologisms Learning in Semantic Variant Primary Progressive Aphasia

Semantic Variant of Primary Progressive Aphasia (svPPA) has often been considered as a loss of knowledge stored in semantic memory, but might also be due to a general disruption of mechanisms allowing the acquisition, storage, and retrieval of semantic memories. In order to assess any parallelism in svPPA patients between loss of semantic knowledge and inability to acquire new semantic information, we administered a battery of semantic learning tasks to healthy individuals and svPPA patients, where they were requested to learn new conceptual representations and new word forms, and to associate the former with the latter. A strong relation was found between loss of semantic knowledge and disruption of semantic learning: (a) patients with severe svPPA had the lowest scores in the semantic learning tasks; (b) significant correlations were found between scores obtained in semantic learning tasks and scores obtained in semantic memory disorders in svPPA patients.
The Exploratory Sequential Design With Generalized Linear Models for the Learning Strategy Analysis

The researchers explored a mixed methods research design through the analysis of a set of interview data. Saldana’s model was utilized to complete the opening coding data and thematic coding data. Three themes were recognized to support the cooperative learning models. These included: a) Knowing by Undergone Events and Contexts, b) Implementation and Action, and c) Opinions and Perceptions, which consisted of a Cooperative Learning Model (CLM). The frequencies of the terms and phrases consisted of the evidence variables. A generalized linear model (GeLM) was utilized to examine the relationship between the three themes and Cooperative Learning Model. The GeLM analysis reported the relationships between the CLM and three themes. This was a new practice to integrate Saldana’s qualitative data analysis and the GeLM into one mixed methods design.
Mucin-Phenotype and Expression of the Protein V-Set and Immunoglobulin Domain Containing 1 (VSIG1): New Insights into Gastric Carcinogenesis

In gastric cancer (GC), intestinal metaplasia (IM) is a common precursor lesion, but its relationship to the MUC2/MUC5AC/CDX2 axis is not completely understood. Although V-set and immunoglobulin domain containing 1 (VSIG1) is supposed to be a specific marker for gastric mucosa and GC, respectively, no data about its relationship with IM or mucin phenotype have been published. The aim of our study was to explore the possible linkage between IM and these four molecules. The clinicopathological features of 60 randomly selected GCs were examined in association with VSIG1, MUC2, MUC5AC and CDX2. Two online database platforms were also used to establish the transcription factors (TFs) network involved in MUC2/MUC5AC/CDX2 cascade. IM was more frequently encountered in females (11/16 cases) and in patients below 60 years old (10/16 cases). Poorly differentiated (G3) carcinomas tended to show a loss of CDX2 (27/33 cases) but not of MUC2 and MUC5AC. MUC5AC and CDX2 were lost in parallel with the depth of invasion of the pT4 stage (28/35 and 29/35 cases), while an advanced Dukes-MAC-like stage was only correlated with CDX2 and VSIG1 loss (20/37 and 30/37 cases). VSIG1 was directly correlated with MUC5AC (p = 0.04) as an indicator of gastric phenotype. MUC2-negative cases showed a propensity towards lymphatic invasion (37/40 cases) and distant metastases, while CDX2-negative cases tended to associate with hematogenous dissemination (30/40 cases). Regarding the molecular network, only 3 of the 19 TFs involved in this carcinogenic cascade (SP1, RELA, NFKB1) interacted with all targeted genes. In GC, VSIG1 can be considered an indicator of gastric phenotype carcinomas, where carcinogenesis is mainly driven by MUC5AC. Although infrequently encountered in GC, CDX2 positivity might indicate a locally advanced stage and risk for vascular invasion, especially in tumors developed against the background of IM. The loss of VSIG1 indicates a risk for lymph node metastases.
Elastic Seismic Imaging Enhancement of Sparse 4C Ocean-Bottom Node Data Using Deep Learning

The ocean-bottom node (OBN) seismic acquisition system is designed to gather high-fidelity, wide-azimuth, and long-offset four-component (4C) data, which includes shear waves and enables the use of the elastic assumption in imaging and inversion. However, deploying geophysical instruments on the seafloor is difficult and costly, leading to the usual adoption of sparse node spacing. This can, however, lead to poor illumination and imaging challenges, especially in the shallow subsurface near the seafloor. To address these issues in the context of 4C elastic imaging, we propose a deep learning-based method using a multiscale convolutional neural network (Ms-CNN) to improve the imaging quality of OBN surveys with sparse data acquisition. As an alternative to interpolating the sparse seismic data in the data domain, which can be a challenging task due to the limitations attributed to sampling theorem and the often larger amounts of data compared to the image, we train an Ms-CNN in a supervised fashion to map from sparse data images of P-wave to P-wave (PP) and P-wave to S-wave (PS) sections produced by 4C Gaussian beam migration to the equivalent dense data images, allowing for the direct processing of sparse data to improve imaging quality. Here, we combine the mean absolute error and multiscale structure similarity index measure in the loss function to optimize the network’s training process and to help improve the performance. The effectiveness of the method is demonstrated through experiments on synthetic and field data, resulting in improved event continuity and reduced noise in migration results from sparse OBN acquisitions.
Lying by telling the truth – the risks of deception by paltering and hypocrisy in corporate social responsibilities context

ABSTRACT This research investigated how fashion corporations’ paltering-based deceptive marketing, specifically related to corporate social responsibility (CSR), might influence consumers. Specifically, it investigated if it evokes hypocrisy perceptions to influence consumers’ purchase decisions and how the mediating roles of consumer-corporation-relationship and consumer-based corporate-reputation can explain such influences. Using a two-factor online experiment (paltering x message replications), data were collected from 252 US consumers. PROCESS results indicated that CSR-paltering positively evoked hypocrisy and, in turn, dampened consumer-corporation-relationship and corporate-reputation. Such hypocrisy significantly reduced purchase-intentions, but only when mediated through consumer-corporation-relationship. No significant negative relationships between deception and purchase-intentions were observed when mediated by hypocrisy alone or combined with corporate-reputation. Additionally, paltering directly influenced relational and reputational evaluations. The novelty of this research lies in its focus on paltering-based deception, prevalent within the fashion industry, and how technically true yet misleading CSR marketing influences consumers. This study also responds to the urgent scholarly calls for investigating deception’s role in consumers’ hypocrisy and adds how this new type of deception is also an attributing factor. Further, it provides corporations insight into how CSR paltering, despite its technically true information, can damage consumers’ relational and reputational attachments and their behavioral intentions if discovered.
Usefulness of ultrasound in confirming the correct placement of Ryle’s tube compared to the traditional method of auscultation in normal versus overweight and obese patients

Background and Aims: Auscultation to verify Ryle's tube position is difficult in obese patients. We compared the usefulness of ultrasonography (USG) versus auscultation in confirming the correct Ryle's tube placement in normal versus overweight or obese patients, time taken for confirmation, and incidence of reinsertion. Material and Methods: A prospective, observational study was carried out on 80 patients. Patients with a body mass index (BMI)>25 kg/m2 formed group O and those with BMI <25 kg/m2 constituted group N. After Ryle's tube insertion correct placement was first confirmed by auscultation. The presence of a gurgling sound over the epigastrium was graded (definite/doubtful/absent). During USG evaluation, if Ryle's tube was not visualized at the subxiphoid region, 20mL of air was injected, looking for dynamic fogging in the stomach. If auscultation yielded doubtful or absent results and USG also failed to confirm, Ryle's tube was repositioned and confirmed. Results: Group O had a significantly higher BMI. Auscultation time and the time taken for USG confirmation were significantly longer in group O. The percentage of patients with definite auscultatory signs was significantly higher in group N. Significantly higher number of patients in group O had doubtful/absent auscultatory signs. Ryle's tube and fogging visualization with USG and the requirement of reinsertion were comparable in both groups. The percentage of patients with definite auscultatory confirmation and definite USG confirmation were comparable in group N. However, in group O, significantly lesser patients had definite auscultatory confirmation compared to definite USG signs. Conclusion: Confirmation of the correct placement of Ryle's tube using ultrasound is easier than auscultation in overweight and obese patients. In normal patients, both techniques are equally useful.
Genetic algorithm based on novel constraints addressing method

A new method to handle constrained optimization is proposed in this paper,to overcome certain disadvantages of the current methods.This method searches the solution space of the problem through the admixture crossover of feasible and infeasible solutions,and performs the selection operation on feasible and infeasible populations respectively.It avoids the difficulty of selecting the penalty factor in penalty strategy and makes the handling constraint simplify.Numerical results show that it is an effective method.
Scintillation Properties of Garnets and Oxyorthosilicates With Different Dopants

The development of novel scintillators for ionizing radiation detectors is still playing a significant role in high-energy physics, medical, and homeland security applications. New detector concepts require a unique combination of material properties such as rising and decay times, and light output, and in the case of collider experiments, the radiation hardness cerium-doped garnet-type scintillation materials have been intensively developed in the last few years. Among them, Y3Al5O12 (YAG), Lu3Al5O12 (LuAG), and Gd3Al2Ga3O12 (GAGG) with high radiation hardness recognized for both gamma and proton irradiation were found to be the most promising materials. Many modern detector systems based on scintillation materials require high-count rates. This involves the use of bright scintillators with fast rise and decay times in combination with modern ultrafast photodetectors such as silicon photo multipliers (SiPMs). A possible solution for such kind of applications is a family of lutetium–yttrium oxyorthosilicates (Lu2(1-x)Y2xSiO5, LSO, LYSO, and YSO). Here, we report on the characterization of different types of garnets with various dopants and in shapes of pixels and bulk and on the study of properties of LSO, LYSO, YSO solely doped by Ce, as well as LYSO materials with Ca and Mg co-doping from different producers.
Comparison of Common Algorithms for Single-Pixel Imaging via Compressed Sensing

Single-pixel imaging (SPI) uses a single-pixel detector instead of a detector array with a lot of pixels in traditional imaging techniques to realize two-dimensional or even multi-dimensional imaging. For SPI using compressed sensing, the target to be imaged is illuminated by a series of patterns with spatial resolution, and then the reflected or transmitted intensity is compressively sampled by the single-pixel detector to reconstruct the target image while breaking the limitation of the Nyquist sampling theorem. Recently, in the area of signal processing using compressed sensing, many measurement matrices as well as reconstruction algorithms have been proposed. It is necessary to explore the application of these methods in SPI. Therefore, this paper reviews the concept of compressive sensing SPI and summarizes the main measurement matrices and reconstruction algorithms in compressive sensing. Further, the performance of their applications in SPI through simulations and experiments is explored in detail, and then their advantages and disadvantages are summarized. Finally, the prospect of compressive sensing with SPI is discussed.
ALZHEIMER'S DISEASE AND ITS RELATIONSHIP WITH THE MICROBIOTA-GUT-BRAIN AXIS.

BACKGROUND Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease, characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. Several pathways enable bidirectional communication between the central nervous system (CNS), the intestine and its microbiota, constituting the microbiota-gut-brain axis. OBJECTIVE Review the pathophysiology of AD, relate it to the microbiota-gut-brain axis and discuss the possibility of using probiotics in the treatment and/or prevention of this disease. METHODS Search of articles from the PubMed database published in the last 5 years (2017 to 2022) structure the narrative review. RESULTS The composition of the gut microbiota influences the CNS, resulting in changes in host behavior and may be related to the development of neurodegenerative diseases. Some metabolites produced by the intestinal microbiota, such as trimethylamine N-oxide (TMAO), may be involved in the pathogenesis of AD, while other compounds produced by the microbiota during the fermentation of food in the intestine, such as D-glutamate and fatty acids short chain, are beneficial in cognitive function. The consumption of live microorganisms beneficial to health, known as probiotics, has been tested in laboratory animals and humans to evaluate the effect on AD. CONCLUSION Although there are few clinical trials evaluating the effect of probiotic consumption in humans with AD, the results to date indicate a beneficial contribution of the use of probiotics in this disease.