Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixing in a salinity variance budget of the Salish Sea is controlled by river flow

A salinity variance framework is used to study mixing in the Salish Sea, a large fjordal estuary. Output from a realistic numerical model is used to create salinity variance budgets for individual basins within the Salish Sea for 2017-2019. The salinity variance budgets are used to quantify the mixing in each basin and estimate the numerical mixing, which is found to contribute about one-third of the total mixing in the model. Whidbey Basin has the most intense mixing, due to its shallow depth and large river flow. Unlike in most other estuarine systems previously studied using the salinity variance method, mixing in the Salish Sea is controlled by the river flow and does not exhibit a pronounced spring-neap cycle. A “mixedness” analysis is used to determine when mixed water is expelled from the estuary. The river flow is correlated with mixed water removal, but the coupling is not as tight as with the mixing. Because the mixing is so highly correlated with the river flow, the long-term average approximation M = QrSoutSin can be used to predict the mixing in the Salish Sea and Puget Sound with good accuracy, even without any temporal averaging. Over a three-year average, the mixing in Puget Sound is directly related to the exchange flow salt transport.
Licensing cost‐reducing innovations under supply function competition

In this paper, we study the problem of licensing cost-reducing innovations in a duopoly under supply function competition. We show that the innovator prefers fixed-fee licensing to no licensing if its cost advantage is not extremely large. Moreover, if its cost advantage is not extremely small, the innovator prefers fixed-fee licensing to royalty licensing, as well.
Interactions between Tryptophan Metabolism, the Gut Microbiome and the Immune System as Potential Drivers of Non-Alcoholic Fatty Liver Disease (NAFLD) and Metabolic Diseases

The prevalence of non-alcoholic fatty liver disease (NAFLD) is increasing and therefore is its burden of disease as NALFD is a risk factor for cirrhosis and is associated with other metabolic conditions such as type II diabetes, obesity, dyslipidaemia and atherosclerosis. Linking these cardiometabolic diseases is a state of low-grade inflammation, with higher cytokines and c-reactive protein levels found in individuals with NAFLD, obesity and type II diabetes. A possible therapeutic target to decrease this state of low-grade inflammation is the metabolism of the essential amino-acid tryptophan. Its three main metabolic pathways (kynurenine pathway, indole pathway and serotonin/melatonin pathway) result in metabolites such as kynurenic acid, xanturenic acid, indole-3-propionic acid and serotonin/melatonin. The kynurenine pathway is regulated by indoleamine 2,3-dioxygenase (IDO), an enzyme that is upregulated by pro-inflammatory molecules such as INF, IL-6 and LPS. Higher activity of IDO is associated with increased inflammation and fibrosis in NAFLD, as well with increased glucose levels, obesity and atherosclerosis. On the other hand, increased concentrations of the indole pathway metabolites, regulated by the gut microbiome, seem to result in more favorable outcomes. This narrative review summarizes the interactions between tryptophan metabolism, the gut microbiome and the immune system as potential drivers of cardiometabolic diseases in NAFLD.
Edge Intelligence-Based Ultra-Reliable and Low-Latency Communications for Digital Twin-Enabled Metaverse

In this letter, we propose a novel digital twin scheme supported metaverse by jointly considering the integrated model of communications, computing, and storage through the employment of mobile edge computing (MEC) and ultra-reliable and low latency communications (URLLC). The MEC-based URLLC digital twin architecture is proposed to provide powerful computing infrastructure by exploring task offloading, and task caching techniques in nearby edge servers to reduce the latency. In addition, the proposed digital twin scheme can guarantee stringent requirements of reliability and low latency, which are highly applicable for the future networked systems of metaverse. For this first time in the literature, our paper addresses the optimal problem of the latency/reliablity in digital twins-enabled metaverse by optimizing various communication and computation variables, namely, offloading portions, edge caching policies, bandwidth allocation, transmit power, computation resources of user devices and edge servers. The proposed scheme can improve the quality-of-experience of the digital twin in terms of latency and reliability with respect to metaverse applications.
Museums in a troubled world: renewal, irrelevance or collapse?

In the early 2000s the Orchestre Symphonique de Montreal (OSM), one of Montreal's foremost cultural institutions, underwent two upheavals. First management was thrown into turmoil by the unexpected departure of the OSM's celebrated music director, Charles Dutoit, just as the orchestra and its Swiss conductor were about to mark 25 years of successful partnership with celebrations planned for the 2002-03 season. Then, in May 2005, the orchestra's management and board were faced with a strike by the orchestra's musicians. The authors describe the efforts of the orchestra's general manager, Madeleine Careau, to revive its fortunes, notably through a campaign to restore the OSM's prestige, which had been severely eroded by these two events. With the support of internal and external collaborators, Careau turned her attention to the most pressing issues, namely the choice of a new conductor, the orchestra's planned new concert hall and the creation of a foundation to ensure stable, long-term financing for the OSM. To help bring this recovery plan to fruition, Careau drew on her extensive network of contacts. An all-female leadership team was formed at the OSM, as Careau called on Melanie La Couture (CEO), Helene Desmarais (deputy board chair) and Monique Jerome-Forget (chair of the Quebec treasury board) to use their talents, expertise and influence to give new lustre to the OSM at home and abroad.
High-Throughput Color Imaging Hg2+ Sensing via Amalgamation-Mediated Shape Transition of Concave Cube Au Nanoparticles

Mercury, as one type of toxic heavy metal, represents a great threat to environmental and biological metabolic systems. Thus, reliable and sensitive quantitative detection of mercury levels is particularly meaningful for environmental protection and human health. We proposed a high-throughput single-particle color imaging strategy under dark-field microscopy (DFM) for mercury ions (Hg2+) detection by using individual concave cube Au nanoparticles as optical probes. In the presence of ascorbic acid (AA), Hg2+ was reduced to Hg which forms Au–Hg amalgamate with Au nanoparticles, altering their localized surface plasmon resonance (LSPR). Transmission electron microscopy (TEM) images demonstrated that the concave cube Au nanoparticles were approaching to sphere upon increasing the concentration of Hg2+. The nanoparticles underwent an obvious color change from red to yellow, green, and finally blue under DFM due to the shape-evolution and LSPR changes. In addition, we demonstrated for the first time that the LSPR of Au–Hg amalgamated below 400 nm. Inspired by the above-mentioned results, single-particle color variations were digitalized by converting the color image into RGB channels to obtain (green+blue)/red intensity ratios [(G+B)/R]. The concentration-dependence change was quantified by statistically analyzing the (G+B)/R ratios of a large number of particles. A linear range from 10 to 2000 nM (R2 = 0.972) and a limit of detection (LOD) of 1.857 nM were acquired. Furthermore, many other metal ions, like Cu2+, Cr3+, etc., did not interfere with Hg2+ detection. More importantly, Hg2+ content in industrial wastewater samples and in the inner regions of human HepG2 cells was determined, showing great potential for developing a single-particle color imaging sensor in complex biological samples using concave cube Au nanoparticles as optical probes.
Acquisition and reconstruction methods for magnetic resonance imaging

Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging modality that has a wide range of applications in both diagnostic clinical imaging and medical research. MRI has progressively gained in importance in clinical use because of its ability to produce high quality images of soft tissue throughout the body without subjecting the patient to any ionizing radiation. In addition to exquisite anatomical detail obtained from the conventional MRI, complementary physiological information is also available through emerging specialized applications of MRI such as magnetic resonance spectroscopic imaging, quantitative susceptibility mapping, functional MRI, and diffusion MRI. Despite its great versatility, MRI is limited by the long time required to acquire the data needed to form an image. Since a typical MRI protocol consists of multiple scans of the same patient, the total scan time is commonly extended beyond half an hour. During the session, the patient must remain perfectly still within a tight and closed environment, raising difficulties for certain populations such as children and patients with claustrophobia. The long acquisition time of MRI not only reduces the availability of the MRI scanner, but also results in patient discomfort, which often leads to motion that degrades image quality. Therefore, reducing the acquisition time of MRI is a well-motivated problem. This thesis proposes acquisition and reconstruction methods that increase the imaging efficiency of MRI and two of its emerging specialized applications, magnetic resonance spectroscopic imaging and quantitative susceptibility mapping. In particular, each of the proposed methods increases the imaging efficiency by achieving at least one of two aims: reduction of total scan time and improved image quality by mitigating image artifacts, while minimizing reconstruction time. Thesis Supervisor: Elfar Adalsteinsson Title: Professor of Electrical Engineering and Computer Science Professor, Institute for Medical Engineering and Science
Implications of the triple track strategy policy on poverty alleviation

This study aims to analyze the effect of the People's Business Credit, health expenditure, education expenditure, regional investment, and the number of workers on poverty alleviation from the implications of the triple track strategy policy on district/city governments in Central Java Province. This study uses secondary data from 2017 to 2019. The hypothesis testing in this study uses multiple regression analysis through the SPSS 23 program. The results of the test of the coefficient of determination (R2) obtained an Adjusted R Squared of 89%, which indicates that poverty is influenced by variables through the People's Business Credit, health spending, education spending, regional investment, and the number of workers. The results of the study partially show that education spending and regional investment have no effect on poverty alleviation, but the People's Business Credit, health spending, and the number of workers have an effect on poverty alleviation in district/city governments in Central Java Province.
An Improved Gas Leakage Model and Research on the Leakage Field Strength Characteristics of R290 in Limited Space

Some alternative refrigerants with excellent environmental performance often have different flammable limits. When refrigerant leaks, the external space may have a certain explosion risk if the refrigerant is not diffused timely. To understand the leakage and diffusion characteristics of the refrigerant, an improved gas leakage model was proposed in this paper, and the accuracy verification of the improved model was developed. Based on the above works, taking R290 as the research object, the variation law of the field strength between the leaked gas and external space and the influence of different initial leakage pressures on the field strength characteristics were analyzed. The simulation results showed that when the initial leakage pressure was 2 MPa, the R290 gas entered the external space as a supersonic jet, the gas underwent continuous expansion and compression processes in the near-field area and a Mach disk was formed within the flow area. During this process, parameters, such as the temperature, pressure, velocity and density of the leaked R290 gas, changed dramatically, and then the gas gradually returned to room temperature and normal pressure through interaction with the external space. The flammable area formed by the leaked R290 was mainly concentrated in the local flow area below the leak hole, and the existence of the Mach disk caused the R290 high concentration area to increase. With the increase in the initial leakage pressure, the distance from the Mach disk to the leak hole and the circumferential diameter of the Mach disk increased, and the flammable area increased slightly in the horizontal direction, whereas the flammable area increased significantly in the vertical direction.
Magnetic Losses in Soft Ferrites

We review the basic phenomenology of magnetic losses from DC to 1 GHz in commercial and laboratory-prepared soft ferrites considering recent concepts regarding their physical interpretation. This is based, on the one hand, on the identification of the contributions to the magnetization process provided by spin rotations and domain walls and, on the other hand, the concept of loss separation. It additionally contemplates a distinction between the involved microscopic dissipation mechanisms: spin damping and eddy currents. Selected experimental results on the broadband behavior of complex permeability and losses in Mn-Zn ferrites provide significant examples of their dependence on sintering methods, solute elements, and working temperature. We also highlight the peculiar frequency and temperature response of Ni-Zn ferrites, which can be heavily affected by magnetic aftereffects. The physical modeling of the losses brings to light the role of the magnetic anisotropy and the way its magnitude distribution, affected by the internal demagnetizing fields, acts upon the magnetization process and its dependence on temperature and frequency. It is shown that the effective anisotropy governs the interplay of domain wall and rotational processes and their distinctive dissipation mechanisms, whose contributions are recognized in terms of different loss components.
Remote Patient Body Temperature Monitoring Based- IEEE802.11a Internet of Things (IoT)

The coronavirus disease (COVID-19) situation keeps continued from the end of 2019 until right now. It is a deadly virus that kills many humans. Thailand's solutions have urged the public to be confident about the Government handling the 2019-novel Coronavirus. This research is to respond to the policy of promoting and developing innovation that is up to date, and it is a part of preventing epidemics related to the respiratory system. The proposed Internet of Things (IoT) Remote Patient Body Temperature Monitoring (RPBTM) brings the concept of an embedded infrared sensor with IEEE802.11a standard through the Internet of medical promotion platform. The system consists of distancing infrared body temperature MLX90614 DCI sensor embedded functional programming with IEEE802.11a WiFi microcontroller. To achieve the prototype's efficiency, the results are demonstrated as the following issues;1) the accuracy performance test in terms of the prototype's calibration and 2) the temperature measurement of each body part. The findings were found that the proposed RPBTM device has an error compared to the standard device, only 0.56 %. Moreover, the prototype measured the body parts such as the man's forehead, palm, and armpit and found that the forehead and armpit temperatures have a positive relationship at a high relationship (.860). Meanwhile, the forehead and palm temperatures have a positive relationship at a moderate level (.473). Hence, it can be hypothesized that the body part that should be selected to detect the body temperature is the forehead and armpit because it is close to absolute body temperature. © 2022 Wydawnictwo SIGMA-NOT. All rights reserved.
An Improved Earthquake Catalog During the 2018 Kı̄lauea Eruption From Combined Onshore and Offshore Seismic Arrays

The Island of Hawai’i was formed by repeated eruptions of basalts at an oceanic hotspot. Kı̄lauea, the youngest among the subaerial volcanoes of the island, erupted intensely in 2018. The eruption provided an opportunity to look into the mechanisms that operate at the volcano and associated earthquake activities, as it was recorded simultaneously, for the first time, by onshore and offshore seismometers. We used most of the publicly available seismic data during the eruption period, including temporary arrays, to build a more complete earthquake catalog during the eruption than that provided by the Hawaiian Volcano Observatory. We used a short‐time‐average/long‐time‐average method to identify potential earthquakes. The detections were associated with events and automatically picked with P‐wave and S‐wave arrivals, which were used to locate the events in a three‐dimensional velocity model. After re‐examining these earthquake events, their coda/duration magnitudes were determined. The resulting half‐year catalog contains 375,736 events with one of the highest daily earthquake numbers ever reported (6,128 on 21 June 2018). A great number of events were recorded during the caldera collapses, from its beginning until its rapid ending. The catalog also contains abundant events near the Pu’u‘ō‘ō vent and in the lower East Rift Zone, where an increase of seismicity in mid‐July and August indicated a step‐up in magma intrusion after the eruption.
Education, Age and Gender: Critical Factors in Determining Interventions for Child Brick Workers in Pakistan and Afghanistan

Working in factories fashioning bricks by hand seems the epitome of hazardous child labor. Yet, efforts to remove children from this work have shown little success; impoverished families balance the value of their children’s contribution against the risks they see. Unfortunately, psychosocial impacts are often not visible, and are rarely taken into consideration when designing interventions. A comprehensive occupational health study of children working in brick factories included a module on psychosocial risks and impacts. This analysis reports on the Pakistan and Afghanistan portion of the study which was administered to 450 child brick workers and 486 controls, aged 11–17. Factorial ANOVAs confirmed that working in brick factories was the strongest predictor of respondent’s psychosocial health. However, they also identified subgroups of children that escape this prediction. Older girls, for example, actually felt better when working, compared with staying at home. Schooling had positive associations, especially in younger boys and adolescent girls. In fact, the results of this study showed that those who are at greatest psychosocial risk were girls who do not go to school. These findings underscore the importance of assessing psychosocial impacts and tailoring policy and interventions to specific gender and age categories of young workers.
Deteksi Penyakit Mata Pada Citra Fundus Menggunakan Convolutional Neural Network (CNN)

Pada tahun 2020, terdapat 1,1 milyar orang yang mengalami kehilangan penglihatan di seluruh dunia. Jumlah ini diproyeksikan akan terus bertambah hingga mencapai 1,76 milyar orang pada tahun 2050. Penyebab utama kebutaan untuk anak-anak dan remaja adalah penyakit mata, yang dapat dicegah apabila dilakukan deteksi dan penanganan lebih dini. Oleh sebab itu, pada penelitian ini diusulkan metode berbasis Convolutional Neural Network (CNN) untuk mendeteksi penyakit mata pada citra fundus. Metode yang diusulkan menggunakan metode transfer learning dengan arsitektur jaringan MobileNetV2 sebagai base model. Arsitektur head model yang diusulkan, yang terdiri dari lapisan global average pooling dan diikuti oleh 2 lapisan fully-connected, mampu memberikan akurasi yang paling tinggi dan efisiensi paling baik dibandingkan dengan arsitektur head model lainnya. Eksperimen pada dataset citra fundus yang terdiri dari 601 citra dengan berbagai macam penyakit mata menunjukkan bahwa metode yang diusulkan mampu memberikan performa yang baik dengan nilai akurasi sebesar 72%, precision sebesar 72%, recall sebesar 72%, dan F1-score sebesar 72%. Hasil eksperimen menunjukkan bahwa metode yang diusulkan dapat memberikan akurasi yang lebih tinggi dan lebih efisien dibandingkan dengan menggunakan arsitektur CNN lainnya, seperti ResNet50V2, InceptionV3, InceptionResNetV2, VGG16, dan VGG19.
Exploring the Process of Lifelong Learning: The Biographies of Five Canadian Women Coaches

Coaches learn from a number of different situations and their past experiences influence what they choose to pay attention to and learn (Werthner & Trudel, 2009). Understanding the process of learning to coach can be explored holistically over the course of an individual’s lifespan. This thesis is guided by Jarvis’ (2006, 2007, 2009) theory of human learning, which takes a psychosocial perspective to understanding the way that individuals perceive their social situations, change their biographies, and become who they are over the course of their lives. The purpose of this dissertation is to explore the biographies of five Canadian women coaches to understand how the multitude of experiences throughout their lives have contributed to their learning and coaching development. Four in-depth interviews were conducted and transcribed verbatim with each coach. From these interviews a biographical narrative analysis was created to document how each coach learned throughout her life. The transcripts and narrative analyses were member checked to augment trustworthiness. Four articles and one research note comprise the results section. The main points in this dissertation are as follows: (a) experiences in primary and secondary socialization influenced the coaches’ approaches to coaching; (b) specific meaningful learning experiences helped the coaches develop and become experienced as coaches; (c) values develop throughout life experiences and influence coaching actions; (d) Jarvis’ theory is used to explore my own process of learning throughout the PhD degree, and how this learning was influenced by my lifetime of experiences to date; and (e) a brief research note highlights how the research process was a co-creation between the researcher and the participants. These findings add to the emerging body of literature on female coaches and coach learning by further understanding how the coaches’ biographies determined what kinds of learning opportunities they each found meaningful; the importance of social connections in learning to coach; and the importance of reflection in understanding the interconnections of learning from life experiences. The study may motivate women coaches in understanding how lifelong learning influences their career paths and it informs coach education programs about the muddled reality of coaches’ learning and development.
Encouraging students' metacognitive skills through inquiry learning

This study's purpose of find the inquiry-based learning effect on the metacognitive skills of high school students. This study uses a quasi-experimental method with a pre-test and post-test design. The sample size is 65 science students at a high school in Manokwari. Data analysis using the Mann Whitney test. The results showed Sig 0.00 <0.05, which means differences in metacognitive skills in the experimental and control groups. It can be concluded that there is an effect of inquiry-based learning on students' metacognitive skills.