Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Blockchain to Improve Decision Making That Benefits the Public Good

Human decision making is often prone to biases and irrationality. Group decisions add dynamic interactions that further complicate the choice process and frequently result in outcomes that are suboptimal for both the individual and the collective. We show that an implementation of a Blockchain protocol improves individuals’ decision strategies and increases the alignment between desires and outcomes. The Blockchain protocol affords (1) a distributed decision, (2) the ability to iterate repeatedly over a choice, (3) the use of feedback and corrective inputs, and (4) the quantification of intrinsic choice attributes (i.e., greed, desire for fairness, etc.). We test our protocol’s performance in the context of the Public Goods Game. The game, a generalized version of the Prisoner’s Dilemma, allows players to maximize their own gain or act in ways that benefit the collective. Empirical evidence shows that participants’ cooperation in the game typically decreases once a single player favors their own interest at the expense of others’. In our Blockchain implementation, “smart contracts” are used to safeguard individuals against losses and, consequently, encourage contributions to the public good. Across different tested simulations, the Blockchain protocol increases both the overall trust among the participants and their profits. Agents decision strategies remain flexible while they act as each other’s source of accountability (which can be seen as formalized distributed “Ulysses contract”). To highlight the contribution of our protocol to society at large we incorporated an entity that represents the public good. This benevolent independent beneficiary of the contributions of all participants (e.g., a charity organization or a tax system) maximized its payoffs when the Blockchain protocol was implemented. We provide a formalized implementation of the Blockchain protocol and discuss potential applications that could benefit society by more accurately capturing individuals’ preferences. For example, the protocol could help maximize profits in groups, facilitate democratic election that better reflect the public opinion, or enable group decision in circumstances where a balance between anonymity, diverse opinions, personal preferences and loss-aversion play a role.
DEEP-LEARNING FEATURES, GRAPHS AND SCENE UNDERSTANDING

Scene Understanding has been a major aspiration of computer vision from its early days. Its root lies in enabling the computer/robot/machine to understand, interpret and manipulate visual data, in similarity to what an average human eye does in front of a natural/artificial localized location/scene. This ennoblement of the machine have a widespread impact ranging from Surveillance, Aerial Imaging, Autonomous Navigation, Smart Cities and thus scene understanding have remained as an active area of research in the last decade. In the last decade, the scope of problems in the scene understanding community has broadened from Image Annotation, Image Captioning, Image Segmentation to Object Detection, Dense Image Captioning, Instance Segmentation etc. Advanced problems like Autonomous Navigation, Panoptic Segmentation, Video Summarization, Multi-Person Tracking in Crowded Scenes have also surfaced in this arena and are being vigorously attempted. Deep Learning has played a major role in this advancement/development. The performance metrics in some of these tasks have more than tripled in the last decade itself but these tasks remain far from solved. Success originating from deep learning can be attributed to the learned features. In simple words, features learned from a Convolutional Neural Network trained for annotation are in general far more suited for captioning then a non-deep learning method trained for captioning. Taking cue from this particular deep learning trend, we dived into the domain of scene understanding with the focus on utilization of prelearned-features from other similar domains. We focus on two tasks in particular: Automatic (multi-label)Image Annotation and (Road)Intersection Recognition. Automatic image annotation is one of the earliest problems in scene understanding and refers to the task of assigning (multiple) labels to an image based on its content. Whereas intersection recognition is the outcome of the new era of problems in scene understanding and it refers to the task of identifying an intersection from varied viewpoints in varied weather and lighting conditions. We focused on this significantly varied task approach to broaden the scope and generalizing capability of the results we compute. Both image annotation and intersection recognition pose some common challenges such as occlusion, perspective variations, distortions etc. While focusing on the image annotation task we further narrowed our domain by focusing on graph based methods. We again chose two different paradigms: a multiple kernel learning based non-deep learning approach and a deep-learning based approach, with a focus on bringing out contrast again. Through quantitative and qualitative results we show slightly boosted performance from the above mentioned paradigms. The intersection recognition task is relatively new in the field. Most of the work in field focuses on Places Recognition which utilized only single images. We focus on temporal information i.e. the traversal of the intersection/places as seen from a camera mounted on a vehicle.
Detectable SARS‐CoV‐2 viral RNA in feces of three children during recovery period of COVID‐19 pneumonia

Coronavirus Disease 2019 (COVID‐19) is a newly emerging infectious disease caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). After its first occurrence in Wuhan of China from December 2019, COVID‐19 rapidly spread around the world. According to the World Health Organization statement on 13 March 2020, there had been over 132 500 confirmed cases globally. Nevertheless, the case reports of children are rare, which results in the lack of evidence for preventing and controlling of children's infection. Here, we report three cases of SARS‐CoV‐2 infected children diagnosed from 3 February to 17 February 2020 in Tianjin, China. All of these three cases experienced mild illness and recovered soon after the treatment, with the nucleic acid of throat swab turning negative within 14, 11, and 7 days after diagnosis, respectively. However, after been discharged, all three cases were tested SARS‐CoV‐2 positive in the stool samples within 10 days, in spite of their remained negative nucleic acid in throat swab specimens. Therefore, it is necessary to be aware of the possibility of fecal‐oral transmission of SARS‐CoV‐2 infection, especially for children cases.
Political Alignment and Credit: Evidence from Local Governments in Mexico∗

Understanding how political economy forces drive the allocation of capital across constituencies is fundamental for fiscal policy and redistribution. In this paper, we study the extent to which the political party affiliation of local politicians affects the allocation of subnational credit. To that end, we use a close elections regression discontinuity design and study the allocation of government and private credit to municipal governments in Mexico. We find that municipalities represented by a member of the presidential party are 7.3 to 7.9 percentage points more likely to obtain public credit and receive 58.5% more credit per capita. This allocation is mostly driven by credit from the largest state-owned bank in Mexico, while we do not find significant differences in the allocation of credit by private banks. We then test whether aligned municipalities use the extra resources to increase the delivery of public goods. We document that municipalities represented by a member of the presidential party seem to increase expenditures in public investment, yet they do not report better quality of public infrastructure. Also, we do not find evidence showing that they crowd out other sources of external or internal revenue in the short run. These results provide causal empirical evidence on the idea that political economy forces are important to explain the accumulation of government debt.
A Case of Novel Coronavirus Disease 19 in a Chronic Hemodialysis Patient Presenting with Gastroenteritis and Developing Severe Pulmonary Disease

Novel coronavirus disease 2019 (COVID-19) is a highly infectious, rapidly spreading viral disease with an alarming case fatality rate up to 5%. The risk factors for severe presentations are concentrated in patients with chronic kidney disease, particularly patients with end-stage renal disease (ESRD) who are dialysis dependent. We report the first US case of a 56-year-old nondiabetic male with ESRD secondary to IgA nephropathy undergoing thrice-weekly maintenance hemodialysis for 3 years, who developed COVID-19 infection. He has hypertension controlled with angiotensin receptor blocker losartan 100 mg/day and coronary artery disease status-post stent placement. During the first 5 days of his febrile disease, he presented to an urgent care, 3 emergency rooms, 1 cardiology clinic, and 2 dialysis centers in California and Utah. During this interval, he reported nausea, vomiting, diarrhea, and low-grade fevers but was not suspected of COVID-19 infection until he developed respiratory symptoms and was admitted to the hospital. Imaging studies upon admission were consistent with bilateral interstitial pneumonia. He was placed in droplet-eye precautions while awaiting COVID-19 test results. Within the first 24 h, he deteriorated quickly and developed acute respiratory distress syndrome (ARDS), requiring intubation and increasing respiratory support. Losartan was withheld due to hypotension and septic shock. COVID-19 was reported positive on hospital day 3. He remained in critical condition being treated with hydroxychloroquine and tocilizumab in addition to the standard medical management for septic shock and ARDS. Our case is unique in its atypical initial presentation and highlights the importance of early testing.
Risk and Consequences of Postoperative Delirium in Cardiac Surgery

Abstract Background Delirium is a common complication after cardiac surgery that leads to increased costs and worse outcomes. This retrospective study evaluated the potential risk factors and postoperative impact of delirium on cardiac surgery patients. Methods One thousand two hundred six patients who underwent open-heart surgery within a single year were included. Uni- and multivariate analyses of a variety of pre, intra-, and postoperative parameters were performed according to differences between the delirium (D) and nondelirium (ND) groups. Results The incidence of delirium was 11.6% (n = 140). The onset of delirium occurred at 3.35 ± 4.05 postoperative days with a duration of 5.97 ± 5.36 days. There were two important risk factors for postoperative delirium: higher age (D vs. ND, 73.1 ± 9.04 years vs. 69.0 ± 11.1 years, p < 0.001) and longer aortic cross-clamp time (D vs. ND, 69.8 ± 49.9 minutes vs. 61.6 ± 53.8 minutes, p < 0.05). We found that delirious patients developed significantly more frequent postoperative complications, such as myocardial infarction (MI) (D vs. ND, 1.43% [n = 3] vs. 0.28% [n = 2], p = 0.05), cerebrovascular accident (D vs. ND, 10.7% [n = 15] vs. 3.75% [n = 40], p < 0.001), respiratory complications (D vs. ND, 16.4% [n = 23] vs. 5.72% [n = 61], p < 0.001), and infections (D vs. ND, 36.4% [n = 51] vs. 16.0% [n = 170], p < 0.001). The hospital stay was longer in cases of postoperative delirium (D vs. ND, 23.2 ± 13.6 days vs. 17.4 ± 12.8 days, p < 0.001), and fewer patients were discharged home (D vs. ND, 56.0% [n = 65] vs. 66.8% [n = 571], p < 0.001). Conclusions Because the propensity for delirium-related complications is high after cardiac surgery, a practical, preventative strategy should be developed for patients with perioperative risk factors, including higher age and a longer cross-clamp time.
Acute Effects of Three Different Meal Patterns on Postprandial Metabolism in Older Individuals with a Risk Phenotype for Cardiometabolic Diseases: a Randomized Controlled Crossover Trial.

SCOPE The aim of this study was to investigate acute postprandial responses to intake of meals typical for Mediterranean and Western diets. METHODS In a randomized crossover design, overweight and obese participants with a risk phenotype for cardiometabolic diseases consumed three different iso-energetic meals: Western diet high-fat (WDHF), Western diet high-carbohydrate (WDHC), and Mediterranean diet (MED) meal. Blood samples were collected at fasting and 1, 2, 3, 4, 5 h postprandially and analyzed for parameters of lipid and glucose metabolism, inflammation, oxidation and antioxidant status. RESULTS Compared to MED and WDHF meals, intake of a WDHC meal resulted in prolonged and elevated increases in glucose and insulin. Elevations for triglycerides were enhanced after the WDHF meal compared to the MED and the WDHC meal. Glucagon-like peptide-1 and interleukin-6 increased postprandially without meal differences. Apart from vitamin C showing an increase after the MED meal and a decrease after WDHF and WDHC meals, antioxidant markers decreased postprandially without meal differences. Plasma interleukin-1β was not affected by meal intake. CONCLUSIONS Energy-rich meals induced hyperglycemia, hyperlipemia, an inflammatory response and a decrease in antioxidant markers. A meal typical for the Mediterranean diet resulted in favorable effects on glycemic, insulinemic and lipemic responses. This article is protected by copyright. All rights reserved.
Regional Differences in Human Biliary Tissues and Corresponding In Vitro–Derived Organoids

Organoids provide a powerful system to study epithelia in vitro. Recently, this approach was applied successfully to the biliary tree, a series of ductular tissues responsible for the drainage of bile and pancreatic secretions. More precisely, organoids have been derived from ductal tissue located outside (extrahepatic bile ducts; EHBDs) or inside the liver (intrahepatic bile ducts; IHBDs). These organoids share many characteristics, including expression of cholangiocyte markers such as keratin (KRT) 19. However, the relationship between these organoids and their tissues of origin, and to each other, is largely unknown.
Experimental Estimation of 44 Pharmaceutical Polar Organic Chemical Integrative Sampler Sampling Rates in an Artificial River under Various Flow Conditions

The present study pertains to a polar organic chemical integrative sampler (POCIS) laboratory calibration to estimate the sampling rates for 44 pharmaceuticals featuring a wide range of polarity (–0.6 < octanol/water partition coefficient [log KOW] < 5.4). The calibration was performed at 16.0 ± 1.5 °C for 4 water flow velocities (0, 2–3, 6–7, and 20 cm/s) in both a tank (for calibration at 0 cm/s) and a laboratory‐scale artificial river filled with 200 and 500 L of tap water spiked with 0.3 µg/L of each compound, respectively. Twelve new sampling rates and 26 sampling rates already available in the literature were determined, whereas the sampling rates for 6 pharmaceuticals could not be determined due to nonlinearity or poor accumulation in POCIS. An increase in the sampling rate value with flow velocity was observed, which is consistent with a decrease in the effective thickness of the water boundary layer at the POCIS membrane surface. Environ Toxicol Chem 2020;39:1186–1195. © 2020 SETAC
A comparative dosimetric study of seven radiation techniques for breast cancer after mastectomy and immediate breast reconstruction

Background: To explore the optimal irradiation technique for breast cancer after mastectomy and immediate breast reconstruction. Methods: Ten breast cancer patients undergoing immediate breast reconstruction after mastectomy were included. We compared the target volume coverage, doses to breast implant and organs at risks (OARs) using seven techniques, including three-dimensional conformal radiation therapy (3DCRT), field-in-field intensity-modulated radiation therapy (FIF-IMRT), the mixture of 3DCRT and IMRT (HYBRID), IMRT, flattening filter-free (FFF)-IMRT, volumetric-modulated arc therapy (VMAT) and FFF-VMAT. Results: IMRT, FFF-IMRT, VMAT, and FFF-VMAT had better conformity index compared to 3DCRT, FIF-IMRT, and HYBRID. The IMRT and FFF-IMRT had the improved homogeneity index in comparison with VMAT and FFF-VMAT. IMRT and FFF-IMRT also had significantly lower dose to breast implant compared to 3DCRT, FIF-IMRT, and HYBRID. However, the volume of ipsilateral lung receiving 10 Gy (V10) and mean dose of ipsilateral lung in VMAT and FFF-VMAT were higher than those of other techniques. The dose to ipsilateral lung in IMRT was in the range of traditional radiation techniques and VMAT. The V10 of heart in IMRT, FFF-IMRT, VMAT, and FFF-VMAT were significantly higher than that of other techniques, and the V40 were improved in IMRT, VMAT and FFF-VMAT compared with 3DCRT, FIF-IMRT, and HYBRID. The FFF technique did not affect the dose to target volume coverage, breast implants, and OARs in IMRT and VMAT. Conclusions: Among the seven radiation techniques, IMRT achieves similar or superior target volume coverage and a better breast implant sparing.
Evaluating hospital tools and services that were co-produced with patients: A rapid review.

PURPOSE To describe the process and outcomes of services or products co-produced with patients in hospital settings. DATA SOURCES Database searches on Medline, CINAHL and Business Source between 2008 and 2019. STUDY SELECTION Studies that evaluate the products of co-production in hospital settings. DATA EXTRACTION Primary outcome is the individual and organizational outcomes resulting from co-production. Study characteristics, co-production process, level of engagement and intensity of engagement were also extracted. RESULTS OF DATA SYNTHESIS A total of 13 studies were included. Types of co-produced outputs were health services and care processes, tools and resources, and technology-based products, such as mobile application. Most studies engaged patients at a consultative or involvement level, with only four studies engaging patients as partners. Moderate-to-high acceptability and usability by patients and health services were reported for co-produced outputs. Organizational outcomes were also reported qualitatively as producing various positive effects, such as improved communication and diagnostic process. Positive patient outcomes were reported for co-produced outputs in qualitative (e.g. improved social support) and quantitative results (e.g. reduction of clinic wait time). No patient clinical outcomes were reported. CONCLUSION Co-produced outputs have moderate-to-high acceptability, usability or uptake. There is insufficient evidence on other organizational or patient outcomes due to the lack of reporting of outcomes in co-production. Future research should focus on the outcomes (i.e. effects on patients and health service providers), not just the output of co-production. This is critical to provide feedback to advance the knowledge and implementation of co-production.
Review of the evidence for robotic-assisted robotic cystectomy and intra-corporeal urinary diversion in bladder cancer

Radical cystectomy, pelvic lymph node dissection and urinary diversion is the gold-standard treatment for muscle-invasive bladder cancer. The surgery is both complex and highly morbid. Robotic cystectomy is now in its 16th year with established techniques and sufficient research maturity to enable comparison with its open counterpart. The present review focuses on the current evidence for robotic cystectomy and assesses various metrics including oncological, perioperative, functional, surgeon-specific and cost outcomes. The review also encapsulates the current evidence for intra-corporeal urinary diversion and its current status in the cystectomy arena.
1 Coding classroom dialogue : Methodological considerations for researchers

Systematic analysis or coding of classroom dialogue is useful for assessing the role of high-quality interaction in supporting learning. However, although coding is an immensely complex and cognitively demanding activity that has taxed researchers over decades, the methodological challenges are often not discussed or problematised in empirical reports. Accordingly, this paper aims to help researchers make sense of the challenges, strengths and practical applications of using systematic coding schemes for analysing classroom dialogue. It presents an in-depth analysis of the pros and cons of contrasting approaches and the key methodological considerations, including scope, grain size, reliability and validity. It goes on to provide a worked example, illustrating how one team tackled the challenges in adapting for a new research objective an earlier coding scheme developed for use across diverse contexts. Two original, theory-informed analytic tools created to study the relationship between dialogic teaching and student learning in English primary schools are shared and made available for others’ use or adaptation. The paper offers practical guidance for developing or adapting coding schemes for different research purposes. It highlights the need for further precision and critical attention to the ways in which scholars are investigating dialogic practices intended to support learning.
Utiliy of VEGF and sVEGFR-1 in Bronchoalveolar Lavage Fluid for Differential Diagnosis of Primary Lung Cancer

Lung cancer is currently the most frequently occurring cancer and one of the leading causes of cancer-related death in the world (Cao et al., 2011). A major factor in the high mortality of lung cancer patients is the presence of metastatic tumors in approximately two-thirds of patients at the time of diagnosis (Wingo et al., 1999). Published data indicated that detection of lung cancer at earlier stages could potentially increase survival rates by 10to 50-fold (Wingo et al., 1999). However, lung cancer screening by chest X-ray and sputum cytology have proven ineffective in increasing patient survival (Ellis et al., 2001; Marcus, 2011), leading to the search for more sensitive and specific tests. Nowadays, fiberoptic bronchoscopy is the most commonly used method for diagnosing lung cancer (Karahalli et al., 2001; Mazzone et al., 2002). Patients suspected of having lung cancer often undergo fiberscopic examination and bronchoalveolar lavage fluid (BALF) was used as a clinical marker for lung cancer diagnosis has been described (Charalabopoulos et al., 2007; Emad et al., 2008). Angiogenesis is a complex process regulated by several growth factors among which vascular endothelial growth factor (VEGF) plays an important role (Ferrara et al., 1997; Ferrara, 2002). A VEGF-specific tyrosine