Miracle-dz/UniFAR-FTUs huggingface dataset:
Table 3 Procedural outcomes : complications and success rate Authors Method Number of Cases Complications Success Major Minor Tsang

/16/$ i.org/1 date, a number of methods have been developed to reduce complications and increase the success rate of the procedure. The aim of the present study was to evaluate the efficacy and the safety of echocardiography-guided pericardiocentesis under continuous echocardiographic monitoring in the management of pericardial effusion. We prospectively performed 161 pericardiocentesis procedures in 141 patients admitted from 1993 to 2015 in 3 centers. This procedure was performed for tamponade or large pericardial effusion in 157 cases and for diagnosis in 4 cases. A percutaneous puncture was performed where the largest amount of fluid was detected. To perform a real-time echo-guided procedure, a multi-angle bracket was mounted on the echocardiographic probe to support the needle and enable its continuous visualization during the puncture. The procedure was successful in 160 of 161 cases (99%). Two major complications occurred (1.2%): 1 mediastinal hematoma that required surgical drainage in a patient on anticoagulant therapy and 1 pleuropericardial shunt requiring thoracentesis. Seven minor complications occurred (4.3%): 1 pleuropericardial shunt, 1 case of transient AV type III block, 3 vasovagal reactions (1 with syncope), and 2 cases of acute pulmonary edema managed with medical therapy. No punctures of any cardiac chamber occurred, and emergency surgical drainage was not required in any case. In conclusion, echocardiography-guided pericardiocentesis under continuous visualization is effective, safe, and easy to perform, even in hospitals with low volumes of procedures with or without cardiac surgery. 2016 Elsevier Inc. All rights reserved. (Am J Cardiol 2016;117:1369e1374)
Private and Social Rates of Return to Secondary and Higher Education in New Zealand: Evidence from the 1991 Census

Abstract With significant increases in the demand for higher education in New Zealand since the 1980s, the question of the size of the returns to investments in education has been of significant interest. Despite this interest, studies have been few in number and based on aggregated measures from the 1960s to 1981. This study is the first to utilise micro‐level data from the 1991 New Zealand Census. The study employs and compares the conventional methods of regression earnings functions, and internal rate of return analyses of private and social rates of return. The results indicate that returns to education are economically significant, at rates that are higher for females, even when adjusting for hours of work and female labour force participation differences. The returns are subject to diminishing returns, and social rates of return are 1 per cent to 3 per cent lower than private returns—a result that is consistent with those of OECD countries, but among the smaller differences by international standards.
Ein Plädoyer für chronische Schmerzpatienten

112 Menschen mit chronischen Schmerzen wird oft mit Argwohn und Unverständnis begegnet. Die Patienten erscheinen mitunter behandlungsresistent, oder sie boykottieren physiotherapeutische Ratschläge. Wissenschaftliche Erkenntnisse über das komplexe Zusammenspiel von Nerven-, Immunund Hormonsystem eröffnen jetzt neue Wege für die erfolgreiche Therapie chronischer Schmerzpatienten. Fazit: Wer unter chronischen Schmerzen leidet, muss zum Experten seiner Schmerzen werden – nur so steigt seine Chance, im Leben aktiv und handlungsfähig zu bleiben.
hero in contemporary revolutionary and military literature: a typology of characters

The relevance of the issue stems from the urgent need to analyse with the help of the latest methods the new phenomena of modern Ukrainian literature, in particular the block of its revolutionary and military prose as one of the directions of modern literature. The aim of the work is to develop and thoroughly analyse the works of 2014-2020 dedicated to the Revolution of Dignity and the war in Eastern Ukraine, to study their genre nature, to clarify their characteristic features and to create a new typology of the modern literary hero. Among the main methods for processing diary texts were historical-biographical, comparative historical, comparative, structural-narratological, interdisciplinary, as well as elements of hermeneutical, intertextual methods, text and discourse analysis, etc. The paper provides a detailed analysis and proposes a new typology of the modern literary hero. The materials of the study can be used to prepare basic and special courses on the theory of literature, the history of Ukrainian and foreign literature, while working on manuals and textbooks, including those for higher education institutions, etc.
Developing a Reliable Welfare Assessment Tool for Captive Hibernatory Bear Species

Simple Summary There are few welfare assessments that have been designed for captive zoo-housed species, including bears. Ideally, welfare assessment tools should be tested for reliability, feasibility and validity. This study assessed the reliability of a composite bear welfare assessment tool using keeper ratings. Two species of hibernating bears were assessed (brown and American black bears) across multiple zoos by multiple keepers. Keepers were asked to perform three assessments on the same bear. The welfare assessment tool was found to be reliable among multiple keepers assessing the same bears as well as each individual keeper performing multiple assessments over time. Further analysis showed good reliability, or unanimous ratings for each item within the assessment. This composite bear welfare assessment tool is a reliable and practical way for keepers to monitor the welfare of captive bears. Abstract Animal welfare assessments are essential for the identification of welfare hazards and benchmarking of welfare improvements, though welfare assessments for zoo species are lacking. Bears are commonly housed in zoos but currently no composite welfare assessment tool exists for captive bears. This study describes the development of such a tool for use across hibernating bear species. A draft tool was developed using indicators derived from the literature and a modified Delphi analysis with an international group of bear keepers. A total of 18 bear keepers from 12 zoos were recruited to trial the tool on 24 brown bears and American black bears. The participating keepers assessed their bears three times across a period of nine days. Intraclass correlation coefficients analysis was used to analyse inter-, intra-rater and item reliability. The inter- and intra-rater reliability showed good to excellent levels of agreement (>0.7, p < 0.05). Item reliability was also assessed and showed good to excellent levels of agreement (>0.75, p < 0.05). The resulting bear welfare assessment is an important step in identifying and understanding challenges to bear welfare in captivity.
Geometry Independent Hole Injection Current Model of GaN Ridge HEMTs

A drain current model of AlN/GaN based ridge (GIT) HEMTs has been developed for source-field-plate structures. The generation mechanism and the geometry independent equations of the hole injection current are developed with Boltzmann Function. Because the current simulations show good agreements with the measurements in multi-geometries, the model can be applied to ridge HEMTs to design power supply circuits.
Factors’ Affect on the Viettel Corporation Brand, Vietnam

Apparently, brand is now gradually becoming an important intangible asset of the business. It is really a sharp and useful tool to help businesses compete and develop sustainably. Today, many customers choose to buy goods because that product is affixed with a famous brand. Therefore, the brand has brought great value to the business. The article focusses on analysing the factors affecting the expansion of Viettel corporation brand from the perspective of customers, thereby proposing recommendations to help Viettel, in particular, and Vietnamese businesses, in general, to expand their brands successfully.
Data-driven Intelligence System for General Recommendations of Deep Learning Architectures

Choosing optimal Deep Learning (DL) architecture and hyperparameters for a particular problem is still not a trivial task among researchers. The most common approach relies on popular architectures proven to work on specific problem domains led on the same experiment environment and setup. However, this limits the opportunity to choose or invent novel DL networks that could lead to better results. This paper proposes a novel approach for providing general recommendations of an appropriate DL architecture and its hyperparameters based on different configurations presented in thousands of published research papers that examine various problem domains. This architecture can further serve as a starting point of investigating DL architecture for a concrete data set. Natural language processing (NLP) methods are used to create structured data from unstructured scientific papers upon which intelligent models are learned to propose optimal DL architecture, layer type, and activation functions. The advantage of the proposed methodology is multifold. The first is the ability to eventually use the knowledge and experience from thousands of DL papers published through the years. The second is the contribution to the forthcoming novel researches by aiding the process of choosing optimal DL setup based on the particular problem to be analyzed. The third advantage is the scalability and flexibility of the model, meaning that it can be easily retrained as new papers are published in the future, and therefore to be constantly improved.
Increased Tea Saponin Content Influences the Diversity and Function of Plantation Soil Microbiomes

Plant secondary metabolites (PSMs) contained in plant litter will be released into soil with the decomposition process, which will affect the diversity and function of soil microbiomes. The response of soil microbiomes to PSMs in terms of diversity and function can provide an important theoretical basis for plantations to put forward rational soil ecological management measures. ABSTRACT Plant secondary metabolites (PSMs) can affect the structures and functions of soil microbiomes. However, the core bacteria associated with PSMs, and their corresponding functions have not been explored extensively. In this study, soil physicochemical properties, tea saponin (TS) contents, microbial community compositions, and microbial community functions of different-age Camellia oleifera plantation soils from representative regions were analyzed. We evaluated the effects of plantation age increase on PSM accumulation, and the subsequent consequences on the structures and functions of soil microbiomes. Plantation ages increase positively correlated with accumulated TS contents, negative effects on soil physicochemical properties, and soil microbiome structures and functions. Clearly, the core functions of soil microbiomes transitioned to those associated with PSM metabolisms, while microbial pathways involved in cellulose degradation were inhibited. Our study systematically explored the influences of PSMs on soil microbiomes via the investigation of key bacterial populations and their functional pathways. With the increase in planting years, increased TS content simplified soil microbiome diversity, inhibited the degradation of organic matter, and enriched the genes related to the degradation of TS. These findings significantly advance our understanding on PSMs-microbiome interactions and could provide fundamental and important data for sustainable management of Camellia plantations. IMPORTANCE Plant secondary metabolites (PSMs) contained in plant litter will be released into soil with the decomposition process, which will affect the diversity and function of soil microbiomes. The response of soil microbiomes to PSMs in terms of diversity and function can provide an important theoretical basis for plantations to put forward rational soil ecological management measures. The effects of planting years on PSM content, soil physicochemical properties, microbial diversity, and function, as well as the interaction between each index in Camellia oleifera plantation soil are still unclear. We found that, with planting years increased, the accumulation of tea saponin (TS) led to drastic changes in the diversity and function of soil microbiomes, which hindered the decomposition of organic matter and enriched many genes related to PSM degradation. We first found that soil bacteria, represented by Acinetobacter, were significantly associated with TS degradation. Our results provide important data for proposing rational soil management measures for pure forest plantations.
Concomitant endoscopic biliary, duodenal and colonic stent placement for advanced carcinoma of gall bladder

Combined biliary and duodenal stent placement has been reported previously in multiple series. Rarely, colonic obstruction may present simultaneously with duodenal and biliary obstruction in advanced pancreaticobiliary cancers. Biliary, duodenal and colonic obstruction managed simultaneously using endoscopic modalities have been reported in only one case report previously. Here we report outcomes of a case of carcinoma of the gall bladder with biliary, gastric outlet and colonic obstruction managed by endoscopic placement of biliary, gastroduodenal and colonic self-expanding metal stents. Copyright © 2021, Society of Gastrointestinal Intervention.
Balanced Scorecard Development as a Performance Management System in Saudi Public Universities: A Case Study Approach

This study’s main objective is developing a balanced scorecard (BSC) model as a performance management system for the University of Bisha, Kingdom of Saudi Arabia. The study aims to describe how the University can move from mission to vision using goals and objectives articulated in its strategic plan 2017–2022. The study uses a qualitative research approach. It comprises an extensive review of relevant literature, an in-depth analysis of documentation of the University’s strategic plan 2017–2022, and a comprehensive discussion and face-to-face interview with relevant executives. A BSC framework was developed as a complementary process for the University’s strategic plan 2017–2022. In addition, a strategy map was designed based on the BSC model. The BSC framework and strategy map can be used to assess and monitor the University’s performance towards achieving ‘Educational and Research Excellence’ status by translating its strategic objectives into action plans.
Determining Interrelationship Between Factors Impacting Foreign Direct Investment in Tourism: An ISM-based Approach

The burgeoning spectrum of tourist demand and changing tastes and preferences calls for developing the nation’s tourism profile. India, one of the fastest-growing economies and a potential attractor of tourists, is estimated to be the world’s third-largest tourism economy by 2028 (as per World Tourism and Travel Council [WTTC] estimates) and is expected to draw massive investment in this sector. Thus, the present study aims to analyse various factors impacting foreign flows in the tourism sector and develops a hierarchical structure among the identified factors through the interpretive structural modelling (ISM) technique. A MICMAC (Matrix of Cross-Impact Multiplications Applied to Classification) analysis is performed to categorise the identified factors based on the driving power and dependence level. The interrelationships among the variables were derived from the opinion gardened from 50 research and industry experts. The results showed that political stability plays a critical component in driving other variables in the system. Also, a stable system is likely to impact the economic environment of a nation positively, thus, creating a desirable profile for investors to invest in tourism businesses or the development of destinations.
Synchronization Through Uncorrelated Noise in Excitatory-Inhibitory Networks

Gamma rhythms play a major role in many different processes in the brain, such as attention, working memory, and sensory processing. While typically considered detrimental, counterintuitively noise can sometimes have beneficial effects on communication and information transfer. Recently, Meng and Riecke showed that synchronization of interacting networks of inhibitory neurons in the gamma band (i.e., gamma generated through an ING mechanism) increases while synchronization within these networks decreases when neurons are subject to uncorrelated noise. However, experimental and modeling studies point towardz an important role of the pyramidal-interneuronal network gamma (PING) mechanism in the cortex. Therefore, we investigated the effect of uncorrelated noise on the communication between excitatory-inhibitory networks producing gamma oscillations via a PING mechanism. Our results suggest that, at least in a certain range of noise strengths and natural frequency differences between the regions, synaptic noise can have a supporting role in facilitating inter-regional communication, similar to the ING case for a slightly larger parameter range. Furthermore, the noise-induced synchronization between networks is generated via a different mechanism than when synchronization is mediated by strong synaptic coupling. Noise-induced synchronization is achieved by lowering synchronization within networks which allows the respective other network to impose its own gamma rhythm resulting in synchronization between networks.
Business Intelligence and Data Warehouse Technologies for Traffic Accident Data Analysis in Botswana

Road traffic accidents are a serious problem for the nation of Botswana. A large amount of money is used to compensate those who are affected by road accidents. Traffic accidents are one of the major causes of Deaths in Botswana. It is important for relevant organizations to have a reliable source of data for accurate evaluation of traffic accidents. Similarly, data on vehicle registration must be transformed and be readily available to assist managerial decision makers. In this article, we deploy a Business Intelligence (BI) and Data Warehouse (DW) solution in an attempt to assist the relevant departments in their road traffic accidents and vehicle registration evaluation. In Our evaluation of the traffic accidents our findings suggest that across accident severity, Damage Only accidents had the most interesting recent trend with a 11.93% decrease in the last 3 years on record. Count of Accident Severity for Damage Only accidents dropped from 13,491 to 11,881 between 2018 and 2020 whilst Minor accidents experienced the longest period of growth. Most accidents take place in rural locations and more accidents take place during the weekend. At 28,439, Sunday had the highest number of accidents and was 47.59% higher than Wednesday, which had the lowest count of accidents at 19,269. The results for vehicle registration reveal that the number of vehicle registration decreased for the last 3 years on record. The number of vehicles registered dropped from 65535 to 24457 during its steepest decline between 2019 and 2021.
An Efficient Piano Performance Evaluation Model Using DTW based on Deep Learning

A piano performance scoring algorithm based on Convolutional Neural Network (CNN), Dynamic Time Warping (DTW) and Linear Regression are developed. A note-based method is used to make the CNN get a high F1-score so that it can better extract audio features. Combining the actual expert scoring benchmarks with the results from CNN and DTW, a set of more professional indicators, the used linear regression to predict the score and test model on a real database which is provided by a piano association are developed. Finally, the prediction score models based on NN transcription models with different precisions are compared.
Proterozoic to Phanerozoic Tectonism in Southwestern Montana Basement Ranges Constrained by Low Temperature Thermochronometric Data

Crystalline basement rocks of southwestern Montana have been subjected to multiple tectonothermal events since ∼3.3 Ga: the Paleoproterozoic Big Sky/Great Falls orogeny, Mesoproterozoic extension associated with Belt‐Purcell basin formation, Neoproterozoic extension related to Rodinia rifting, and the late Phanerozoic Sevier‐Laramide orogeny. We investigated the long‐term (>1 Ga), low‐temperature (erosion/burial within 10 km of the surface) thermal histories of these tectonic events with zircon and apatite (U‐Th)/He thermochronology. Data were collected across nine sample localities (n = 55 zircon and n = 26 apatite aliquots) in the northern and southern Madison ranges, the Blacktail‐Snowcrest arch, and the Tobacco Root uplift. Our zircon (U‐Th)/He data show negative trends between single aliquot date and effective uranium (a radiation damage proxy), which we interpreted with a thermal history model that considers the damage‐He diffusivity relationship in zircon. Our model results for these basement ranges show substantial cooling from temperatures above 400°C to near surface conditions between 800 and 510 Ma. Subsequent Phanerozoic exhumation culminated by ∼75 Ma. Late Phanerozoic cooling is coincident with along‐strike Sevier belt thin‐skinned thrusting in southeastern Idaho, and older than exhumation in basement‐involved uplifts of the Wyoming Laramide province. Our long‐term, low‐temperature thermal record for these southwestern Montana basement ranges shows that: (a) these basement blocks have experienced multiple episodes of upper crustal exhumation and burial since Archean time, possibly influencing Phanerozoic thrust architecture and (b) the late Phanerozoic thick‐skinned thrusting recorded by these rocks is among the earliest thermochronologic records of Laramide basement‐involved shortening and was concomitant with Sevier belt thin‐skinned thrusting.
Independent Study in Robotics: Researching Skill Models for Autonomous Food Preparation

In the recent years, we have seen great progress in learning-based methods for deformable object manipulation. Various works like [1], [2] have showcased that large-scale interaction sequences with objects can lead to learning robust downstream skills. These skills can then be used to compose skill libraries, which are then combined with planning based approaches to solve long-horizon tasks. However, one area where such data-driven methods continue to be a challenge to develop is food preparation. Based on the various physical properties of the food object (adhesion, damping, poisson coefficient, plasticity, stress and strain properties, viscosity) it may react and deform differently to the same action. For example, lets take the simple task of pushing a food object. For the same control scheme, actions, and forces, a cut potato may deform and displace very differently as compared to a slice of cucumber. Further, one of the areas we specifically considered was dough manipulation. Dough is especially difficult to model due to its plastic nature which is not only inhibited in other food objects, but whose properties are different from similar plastic objects like clay. In this work we address the task of building a large-scale dataset for interacting with food objects of different properties in order to extend learning-based methods to food preparation skills. Further, due to the current circumstances of the COVID-19, we explore this task in two phases: 1. Using Physical hardware 2. In Simulation.