Miracle-dz/UniFAR-FTUs huggingface dataset:
From NY to LA: A Look at the Wage Phillips Curve Using Cross-Geographical Data

This paper estimates the cross-geographical wage Phillips Curve (PC) and relates this object to the aggregate wage PC through the lens of a New Keynesian model of regions within a monetary union. We argue that a well-identfied cross-geographical PC, combined with a theoretical mapping from this object to the aggregate PC, provides an appealing alternative to estimating the latter from time-series variation. We employ this approach to study the recent debates over whether the wage PC slope has flattened in recent years and whether the wage PC is nonlinear. We find substantial evidence of a flattening of the wage PC during the recovery from the Great Recession, using both state and city panel data. We find no evidence of any economically meaningful nonlinearity. As our theoretical model shows, a flattening cross-geographical wage PC need not imply a flattening aggregate PC if intra-national labor mobility has risen and/or if monetary policy has become less passive. However, evidence points to the opposite, suggesting that the aggregate PC slope flattened at least as much.
CHAPTER 4 Conflict and Natural Resources : Is the Latin American and Caribbean Region Different from the Rest of the World ?

Oil-rich countries have civil wars at significantly higher rates than oil-poor countries. While other studies have demonstrated this pattern at a global level, this chapter demonstrates that it is equally valid in the Latin American and Caribbean (LAC) region. It also describes one important anomaly. In the LAC region, oil is only linked to government conflicts, while in the rest of the world, oil heightens the danger of both government conflicts (in which rebels fight for control of the central government) and secessionist conflicts (in which they fight for a sovereign state). This is not because the region produces petroleum with unusual properties, but because it is uniquely “secession-proof. ” Lessons about conflict prevention in oil-producing states developed at a global level are also valid for the LAC region.
Assessing environmental barriers by means of the Swedish craig hospital inventory of environmental factors among people post-stroke

Abstract Background When occupational therapists address environmental barriers to occupational engagement, some barriers might not be possible to reduce for single individuals, because decisions have to be taken at community or societal level, for example changes in public transport. Investigating environmental barriers by means of the Swedish Craig Hospital Inventory of Environmental Factors (CHIEF-S) may increase our understanding of the environmental impact on occupation engagement and the methodological challenges to assess environmental barriers. Aims To investigate and describe the magnitude of encountered environmental barriers in a group of people post-stroke and to assess psychometric properties of the CHIEF-S. Material and methods In total, 34 participants, who had sustained a stroke in Sweden were recruited. Results The participants reported in average 2,7 barriers and the total frequency-magnitude score of barriers (CHIEF-S score) was 0.45. The Cronbach’s α for the total CHIEF-S was 0.80 and the analysis of test-retest reliability revealed ICC = 0.86. The entire instrument demonstrated better psychometric properties than the single sub-scales. Conclusion In this study, the frequency-magnitude of environmental barriers encountered by people post-stroke are reported at a group level and adds information to the cumulative knowledge generation on perceived environmental barriers in the society. However, to inform which interventions are needed at a more detailed level, other data collection methods have to be added.
On the Contribution of Experimental Data to the Reduction of the Uncertainty of Fragility Curves

Ambient vibrations in buildings is of increasing interest for applications in mechanical engineering, civil engineering and earthquake engineering. For example, elastic fundamental frequency and damping ratio are two key-parameters for simplified seismic design and vulnerability assessment methods. Empirical relationships exist in codes to estimate this frequency and damping but experimental data could be used to improve them, accounting for national features of building design and, above all, the corresponding uncertainties. With advances in data acquisition systems (the number of measurement points, continuous recording, low-noise instruments) and advances in signal processing algorithms, further and better studies can be conducted on civil engineering structures for evaluating their modal parameters and their physical properties, with a high level of confidence. Moreover, permanent instrumentations also provide earthquake data helping in the improvement of the building response in case of a severe event. The aim of this paper is to show how the experimental data, providing from temporary or permanent instrumentation, can be used for adjusting behaviour models for each class of structure for vulnerability assessment, for monitoring the wandering effect of the elastic parameters on the fragility curves and their uncertainties.
Homogenization of Halide Distribution and Carrier Dynamics in Alloyed Organic-Inorganic Perovskites

Author(s): Correa-Baena, Juan-Pablo; Luo, Yanqi; Brenner, Thomas M; Snaider, Jordan; Sun, Shijing; Li, Xueying; Jensen, Mallory A; Nienhaus, Lea; Wieghold, Sarah; Poindexter, Jeremy R; Wang, Shen; Meng, Ying Shirley; Wang, Ti; Lai, Barry; Bawendi, Moungi G; Huang, Libai; Fenning, David P; Buonassisi, Tonio | Abstract: Perovskite solar cells have shown remarkable efficiencies beyond 22%, through organic and inorganic cation alloying. However, the role of alkali-metal cations is not well-understood. By using synchrotron-based nano-X-ray fluorescence and complementary measurements, we show that when adding RbI and/or CsI the halide distribution becomes homogenous. This homogenization translates into long-lived charge carrier decays, spatially homogenous carrier dynamics visualized by ultrafast microscopy, as well as improved photovoltaic device performance. We find that Rb and K phase-segregate in highly concentrated aggregates. Synchrotron-based X-ray-beam-induced current and electron-beam-induced current of solar cells show that Rb clusters do not contribute to the current and are recombination active. Our findings bring light to the beneficial effects of alkali metal halides in perovskites, and point at areas of weakness in the elemental composition of these complex perovskites, paving the way to improved performance in this rapidly growing family of materials for solar cell applications.
Cardiac rehabilitation is associated with greater improvements in psychological health following coronary artery bypass graft surgery when compared to percutaneous coronary intervention.

Following coronary revascularization, patients treated with coronary artery bypass graft surgery (CABG) have lower risk of major adverse cardiovascular events when compared to those treated with percutaneous coronary intervention (PCI). We compared changes in cardiovascular risk factors, such as psychological and cardiometabolic health indicators, among patients who completed cardiac rehabilitation (CR) following CABG and PCI. Longitudinal records of 278 patients who completed an outpatient CR program following CABG or PCI were analyzed. We compared changes in anxiety and depression assessed by the Hospital Anxiety and Depression Scale (HADS); health-related quality of life (HR-QoL) measured by the Medical Outcomes Study Short Form-36 (SF-36); and, indicators of cardiometabolic health (i.e., body mass, blood pressure, glucose and lipid profiles) between CABG and PCI groups using analysis of covariance (ANCOVA). At baseline, patients treated with PCI (n=191) had better physical function (i.e., physical functioning: 62.5±22.1 vs. 54.3±23.0 points, p=0.006; and role limitations due to physical health: 31.2±36.8 vs. 20.6±31.8 points, p=0.024) when compared to those treated with CABG (n=87). Following CR, patients treated with PCI showed significantly smaller improvements in depression (-0.4±3.1 vs. -1.3±2.7 points, p=0.036) and mental HR-QoL (mental component summary: 2.4±10.8 vs. 5.7±10.7 points, p=0.020) when compared to those treated with CABG. Novelty •Patients with coronary artery disease treated with PCI have smaller functional limitations but similar psychological health when compared to those treated with CABG at CR enrollment. •Patients participating in CR following PCI appear to achieve smaller psychological health benefits from CR when compared to those recovering from CABG.
Intravascular hemolysis triggers ADP-mediated generation of platelet-rich thrombi in pre-capillary pulmonary arterioles.

Patients with hereditary or acquired hemolytic anemias have a high risk of developing in-situ thrombosis of the pulmonary vasculature. While pulmonary thrombosis is a major morbidity associated with hemolytic disorders, the etiological mechanism underlying hemolysis-induced pulmonary thrombosis remains largely unknown. Here, we use intravital lung microscopy in mice for the first time to assess the pathogenesis of pulmonary thrombosis following deionized-water induced acute intravascular hemolysis. Acute hemolysis triggered the development of αIIbβ3-dependent platelet-rich thrombi in precapillary pulmonary arterioles, which led to the transient impairment of pulmonary blood flow. The hemolysis-induced pulmonary thrombosis was phenocopied with intravenous ADP- but not thrombin-triggered pulmonary thrombosis. Consistent with a mechanism involving ADP release from hemolyzing erythrocytes, the inhibition of platelet-P2Y12 purinergic-receptor signaling attenuated pulmonary thrombosis and rescued blood flow in the pulmonary arterioles of mice following intravascular hemolysis. These findings are the first in vivo studies to suggest that acute intravascular hemolysis promotes ADP-dependent platelet activation leading to thrombosis in the pre-capillary pulmonary arterioles and that thrombin generation most likely does not play a significant role in the pathogenesis of acute hemolysis-triggered pulmonary thrombosis.
Towards Optical Connectomics : Feasibility of 3 D Reconstruction of Neural Morphology Using Expansion Microscopy and In Situ Molecular Barcoding

Reconstruction of the 3D morphology of neurons is an essential step towards the analysis and understanding of the structures and functions of neural circuits. Optical microscopy has been a key technology for mapping brain circuits throughout the history of neuroscience due to its low cost, wide usage in biological sciences and ability to read out information-rich molecular signals. However, conventional optical microscopes have limited spatial resolution due to the diffraction limit of light, requiring a tradeoff between the density of neurons to be imaged and the ability to resolve finer structures. A new technology called expansion microscopy (ExM), which physically expands the specimen multiple times before optical imaging, enables us to image fine structures of biological tissues with super resolution using conventional optical microscopes. With the help of ExM, we can also read out molecular information in the neural tissues optically. In this thesis, I will introduce our study of the properties, via computer simulation, of a candidate automated approach to algorithmic reconstruction of dense neural morphology, based on simulated data of the kind that would be obtained via two emerging molecular technologies-expansion microscopy (ExM) and in-situ molecular barcoding. We utilize a convolutional neural network to detect neuronal boundaries from protein-tagged plasma membrane images obtained via ExM, as well as a subsequent supervoxel-merging pipeline guided by optical readout of information-rich, cell-specific nucleic acid barcodes. We attempt to use conservative imaging and labeling parameters, with the goal of establishing a baseline case that points to the potential feasibility of optical circuit reconstruction, leaving open the possibility of higher-performance labeling technologies and algorithms. We find that, even with these conservative assumptions, an all-optical approach to dense neural morphology reconstruction may be possible via the proposed algorithmic framework. Thesis Supervisor: Edward S. Boyden, III Title: Y. Eva Tan Professor in Neurotechnology, Associate Professor of Media Arts and Sciences, Brain and Cognitive Sciences, and Biological Engineering
Object Proposals Localization and Geometric Filtering Model-Free Tracking Object Tracks Classification Inference Object Proposals Stereo Scene Flow Visual Odometry Classifier

The most common paradigm for vision-based multi-object tracking is tracking-by-detection, due to the availability of reliable detectors for several important object categories such as cars and pedestrians. However, future mobile systems will need a capability to cope with rich human-made environments, in which obtaining detectors for every possible object category would be infeasible. In this paper, we propose a model-free multi-object tracking approach that uses a categoryagnostic image segmentation method to track objects. We present an efficient segmentation mask-based tracker which associates pixel-precise masks reported by the segmentation. Our approach can utilize semantic information whenever it is available for classifying objects at the track level, while retaining the capability to track generic unknown objects in the absence of such information. We demonstrate experimentally that our approach achieves performance comparable to stateof-the-art tracking-by-detection methods for popular object categories such as cars and pedestrians. Additionally, we show that the proposed method can discover and robustly track a large variety of other objects.
microRNA-9 and -29a regulate the progression of diabetic peripheral neuropathy via ISL1-mediated sonic hedgehog signaling pathway

In this study, we tested the hypothesis that overexpression of miR-9 and miR-29a may contribute to DPN development and progression. We performed a meta-analysis of miR expression profile studies in human diabetes mellitus (DM) and the data suggested that miR-9 and miR-29a were highly expressed in patients with DM, which was further verified in serum samples collected from 30 patients diagnosed as DM. Besides, ISL1 was confirmed to be a target gene of miR-9 and miR-29a. Lentivirus-mediated forced expression of insulin gene enhancer binding protein-1 (ISL1) activated the sonic hedgehog (SHH) signaling pathway, increased motor nerve conduction velocity and threshold of nociception, and modulated expression of neurotrophic factors in sciatic nerves in rats with DM developed by intraperitoneal injection of 0.45% streptozotocin, suggesting that ISL1 could delay DM progression and promote neural regeneration and repair after sciatic nerve damage. However, lentivirus-mediated forced expression of miR-9 or miR-29a exacerbated DM and antagonized the beneficial effect of ISL1 on DPN. Collectively, this study revealed potential roles of miR-9 and miR-29a as contributors to DPN development through the SHH signaling pathway by binding to ISL1. Additionally, the results provided an experimental basis for the targeted intervention treatment of miR-9 and miR-29a.
Pre-Growth Culture Conditions Affect Type 1 Fimbriae-Dependent Adhesion of Salmonella

Among various fimbrial structures used by Salmonella enterica to colonize host tissues, type 1 fimbriae (T1F) are among the most extensively studied. Although some experiments have shown the importance of T1F in the initial stages of Salmonella infection, their exact role in the infection process is not fully known. We suggested that different outcomes of T1F investigations were due to the use of different pre-infection growth conditions for the induction of the T1F. We utilized qPCR, flow cytometry, and a wide range of adhesion assays to investigate Salmonella Choleraesuis and Salmonella Typhimurium adhesion in the context of T1F expression. We demonstrated that T1F expression was highly dependent on the pre-infection growth conditions. These growth conditions yielded T1F+ and T1F- populations of Salmonella and, therefore, could be a factor influencing Salmonella-host cell interactions. We supported this conclusion by showing that increased levels of T1F expression directly correlated with higher levels of Salmonella adherence to the intestinal epithelial IPEC-J2 cell line.
Does Emotion Regulation Predict Gains in Exercise-Induced Fitness? A Prospective Mixed-Effects Study with Elite Helicopter Pilots

Emotion regulation (ER) is a strong predictor of different aspects of mental health and wellbeing. However, only recently has ER been examined in relation to physical activity and its effects on fitness. In the present study, 26 elite helicopter pilots, serving in the Spanish Air Force, were physically trained for 6 months, and their level of fitness (maximum oxygen consumption and time to exhaustion in a treadmill-running test) was assessed before and after that period. Additionally, two indices of emotion regulation (general adaptiveness of ER strategies, as measured by the Emotion Regulation Questionnaire (ERQ), and negative urgency, as measured by the UPPS-P questionnaire) measured at baseline were used as prospective predictors of fitness improvement. After controlling for individual features, baseline fitness, and type of training, better emotion regulation strategies (more cognitive reappraisal plus less expressive suppression) predicted larger fitness gains (p = 0.028). Incidental emotion regulation, as measured by the negative urgency index, failed to predict pre–post-fitness changes (p = 0.734). These results suggest that fostering emotion regulation skills may improve the effectiveness of fitness training programs.
Improved Handwritten Digit Recognition Using Convolutional Neural Networks (CNN)

Traditional systems of handwriting recognition have relied on handcrafted features and a large amount of prior knowledge. Training an Optical character recognition (OCR) system based on these prerequisites is a challenging task. Research in the handwriting recognition field is focused around deep learning techniques and has achieved breakthrough performance in the last few years. Still, the rapid growth in the amount of handwritten data and the availability of massive processing power demands improvement in recognition accuracy and deserves further investigation. Convolutional neural networks (CNNs) are very effective in perceiving the structure of handwritten characters/words in ways that help in automatic extraction of distinct features and make CNN the most suitable approach for solving handwriting recognition problems. Our aim in the proposed work is to explore the various design options like number of layers, stride size, receptive field, kernel size, padding and dilution for CNN-based handwritten digit recognition. In addition, we aim to evaluate various SGD optimization algorithms in improving the performance of handwritten digit recognition. A network’s recognition accuracy increases by incorporating ensemble architecture. Here, our objective is to achieve comparable accuracy by using a pure CNN architecture without ensemble architecture, as ensemble architectures introduce increased computational cost and high testing complexity. Thus, a CNN architecture is proposed in order to achieve accuracy even better than that of ensemble architectures, along with reduced operational complexity and cost. Moreover, we also present an appropriate combination of learning parameters in designing a CNN that leads us to reach a new absolute record in classifying MNIST handwritten digits. We carried out extensive experiments and achieved a recognition accuracy of 99.87% for a MNIST dataset.
Analysis of Diabetes Mellitus-Related Amputations in the State of Espírito Santo, Brazil

Background and objectives: Diabetes mellitus (DM) stands out among the most important public health problems worldwide since it represents a high burden on health systems and is associated with higher hospitalization rates, and a higher incidence of cardiovascular diseases. Amputations are among the most common complications, leading to disability and increasing care costs. This research aims to analyze the prevalence of DM-related amputations, comorbidities and associated risk factors in the diabetic population residing in the State of Espírito Santo, Brazil. Materials and Methods: This is a quantitative, exploratory, cross-sectional study with a time series design and the use of secondary data registered and followed by the system of Registration and Monitoring of Hypertension and Diabetes—SisHiperdia. Results: The sample consisted of 64,196 diabetic patients, out of them, 3.9% had type 1 DM, 10.9% with type 2 DM, and 85.2% with DM coexisting with hypertension. Most were female (66.6%), aged 40 to 59 years (45.6%), and 60 years and older (45.2%). The prevalence of DM-related amputations in the analyzed sample was 1.2% in type 1 DM, 1.5% in type 2 DM, and 2.2% in concomitant DM and hypertension. Higher amputation rates were observed in males in the age group above 60 years in type 1 DM and type 2 DM and were slightly higher in the age groups up to 29 years in DM with hypertension. A higher prevalence of amputation was related to smoking, physical inactivity, acute myocardial infarction (AMI), stroke, chronic kidney disease (CKD), and diabetic foot (DF) in all types of DM. Conclusions: The present study showed a significant prevalence of DM-related amputations. An increased prevalence was evidenced when correlated with smoking, physical inactivity, AMI, stroke, CKD, and DF with significant statistical associations, except for a sedentary lifestyle in type 1 DM.
Italian Consensus Statement on Patient Engagement in Chronic Care: Process and Outcomes

Patient engagement has been recognized as a key priority in chronic care. However, scholars agree that guidelines are needed to ensure effective patient engagement strategies. To this end, a Consensus Conference process was promoted with the following methodological steps: (1) extensive literature review about patient engagement initiatives in chronic care; (2) a stakeholders survey to collect best practices and (3) workshops with experts. On the basis of the information collected, a consensus statement was drafted, revised, and finalized by a panel of select renowned experts. These experts agreed in defining engagement as an eco-systemic concept involving multiple actors all of which contribute to influence patients’ willingness and ability to engage in chronic care. Moreover, experts recommended, whenever possible, to adopt standardized instruments to assess engagement levels and related unmet needs. Then, experts strongly advised appropriate trainings for healthcare professionals about patient engagement strategies. Furthermore, the importance of promoting healthcare professionals’ wellbeing has been advocated. Family caregivers, as well as patients’ organizations - should be trained and engaged to increase the effectiveness of interventions dedicated to patients. Finally, experts agreed that digital technologies should be considered as a crucial enhancer for patient engagement in chronic care.