Miracle-dz/UniFAR-FTUs huggingface dataset:
Emerging threats and vaccination strategies of H9N2 viruses in poultry in Indonesia: A review

Avian influenza virus subtype H9N2 was first documented in Indonesia in 2017. It has become prevalent in chickens in many provinces of Indonesia as a result of reassortment in live bird markets. Low pathogenic avian influenza subtype H9N2 virus-infected poultry provides a new direction for the influenza virus. According to the latest research, the Indonesian H9N2 viruses may have developed through antigenic drift into a new genotype, posing a significant hazard to poultry and public health. The latest proof of interspecies transmission proposes that the next human pandemic variant will be the avian influenza virus subtype H9N2. Manipulation and elimination of H9N2 viruses in Indonesia, constant surveillance of viral mutation, and vaccine updates are required to achieve effectiveness. The current review examines should be investigates/assesses/report on the development and evolution of newly identified H9N2 viruses in Indonesia and their vaccination strategy.
Technical Analysis Ballast Water Treatment By Using Economizer Utilizing Main Engines Exhaust Heat To Comply With International Ship Ballast Water Management At "MV. Leader Win "

Based on the International Ballast Water Management regulations (IBWM), waste water ballast itself has the attention of some researchers to reduce the amount of waste species present in the ballast water with a variety of methods, as of biological, physical, mechanical, and chemical. The decision-making tools such as ballast water heater, flow-through system and others where possible these tools can minimize waste species in ballast water at a certain temperature or pressure of the flow according to the calculations. This study was aimed to calculate and analysis the effectiveness of the system treatment between Option 1 (Economizer & Bundle) and Option 2 (Economizer & Heat Excharger) then it will compare. First option is using economizer and bundles to transfer a heat from a source heat of exhaust gas then medium by thermal oil circulated. The second option is using economizer and heat excharger where a same heat source , but sea water from ballast tank sirculated to heat excharger. And from economizer to heat excharger is using thermal oil as a heat medium. For all calculation and anaalysis is using softwere HTRI. First option having a duty 2.503 MegaWatts at economizer and 1.9567 MegaWatts at bundles. Over design 2.01% at Economizer and 7.1%5 at bundles. Pessure drop 63.287 kPa at thermal oil after economizer and 68.196 kPa after bundles. Treatment time to this option is 44.424 hors. Second option having a duty 3.38 MegaWatts at economizer and 3.1227 MegaWatts at heat excharger. Over design 5.85% at Economizer and 3.49%5 at heat excharger. Pessure drop 38.697 kPa at thermal oil after economizer and 28.476 kPa after heat excharger. Treatment time to second option is 42.03 hours. Option 2 (Economizer & Heat Excharger) is more optimum than option in analytical techniques. By analysis of treatment system , are expected this thesis can be applied to either the MV. Leader Win Vessel to comply with the operational needs according to standard employability.
Personal Healthcare Agents for Monitoring and Predicting Stress and Hypertension from Biosignals

We live in exciting times. The fast paced growth in mobile computers has put powerful computational devices in the palm of our hands. Blazing fast connectivity has made human-human, human-machine, and machine-machine communication effortless. Wearable devices and the internet of things have made monitoring every aspect of our lives easier. This has given rise to the domain of quantified self where we can continuous record and quantify the various signals generated in everyday life. Sensors on smartphones can continuously record our location and motion profile. Sensors on wearable devices can track changes in our bodies’ physiological responses. This monitoring also has the capability to revolutionise the health care domain by creating more informed and involved patients. This has the potential to shift care-management from a physician-centric approach to a patient-centric approach allowing individuals to create more empowered patients and individuals who are in better control of their health. However, the data deluge from all these sources can sometimes be overwhelming. There is a need for intelligent technology that can help us navigate the data and take informed decisions. The goal of this work is to develop a mobile, personal intelligent agent platform that can become a digital companion to live with the user. It can monitor the covert and overt signal streams of the user, identify activity and stress levels to help the users’ make healthy choices regarding their lives. This thesis particularly targets patients suffering from or at-risk of essential hypertension since its a difficult condition to detect and manage. This thesis delivers the following contributions: 1) An intelligent personal agent platform for on-the-go continuous monitoring of covert and overt signals. 2) A machine learning algorithm for accurate recognition of activities using smartphone signals recorded from in-the-wild scenarios. 3) A machine learning pipeline to combine various physiological signal streams, motion profiles, and user annotations for on-the-go stress recognition. 4) We design and train a complete signal processing and classification system for hypertension prediction. 5) Through a small pilot study we demonstrate that this system can distinguish between hypertensive and normotensive subjects with high accuracy.
Global Geomagnetic Perturbation Forecasting Using Deep Learning

Geomagnetically Induced Currents (GICs) arise from spatio‐temporal changes to Earth's magnetic field, which arise from the interaction of the solar wind with Earth's magnetosphere, and drive catastrophic destruction to our technologically dependent society. Hence, computational models to forecast GICs globally with large forecast horizon, high spatial resolution and temporal cadence are of increasing importance to perform prompt necessary mitigation. Since GIC data is proprietary, the time variability of the horizontal component of the magnetic field perturbation (dB/dt) is used as a proxy for GICs. In this work, we develop a fast, global dB/dt forecasting model, which forecasts 30 min into the future using only solar wind measurements as input. The model summarizes 2 hr of solar wind measurement using a Gated Recurrent Unit and generates forecasts of coefficients that are folded with a spherical harmonic basis to enable global forecasts. When deployed, our model produces results in under a second, and generates global forecasts for horizontal magnetic perturbation components at 1 min cadence. We evaluate our model across models in literature for two specific storms of 5 August 2011 and 17 March 2015, while having a self‐consistent benchmark model set. Our model outperforms, or has consistent performance with state‐of‐the‐practice high time cadence local and low time cadence global models, while also outperforming/having comparable performance with the benchmark models. Such quick inferences at high temporal cadence and arbitrary spatial resolutions may ultimately enable accurate forewarning of dB/dt for any place on Earth, resulting in precautionary measures to be taken in an informed manner.
Identity formation of non-native English-speaking teachers and prospective teachers through perceptions towards native-speakerism: the Turkish Cypriot story

In this article we report on a study in which we used native-speakerism as a lens to investigate the identity formation of non-native English-speaking teachers and prospective teachers in Northern Cyprus. A qualitative method through narratives was used to access the thoughts and experiences of the participants. In the study the participants’ identity formation was revealed by 3 concepts: self-image, self-efficacy, and beliefs about teaching and learning. The findings reveal that the participants had positive and high self-efficacy and self-image with regard to teaching English. Weaknesses often create self-doubt; the participants recognised their weaknesses which propelled them to invest more in themselves. Wheatley (2002) states that teachers’ learning and professional growth can be instigated through a level of self-doubt and weaknesses about their abilities. Similarly, their beliefs, a core reflection of their identity, were catalysts to being English language teachers.
A Systematic Review: Genetic and Environmental Risk Factors of Human Eating Disorders under Adoption and Twin Study Designs

: Behavioral genetic methods have been largely used in research to study the genetic and environmental risk factors of human mental disorders, including the eating disorders (EDs). Among these quantitative methods, twin and adoption study designs are powerful tools in identifying the nature and nurture components leading to EDs. Molecular genetic methods are introduced in studying EDs recently to study specific candidate genes on human genome. The present work is to (a) review twin and adaption studies of the eating disorders; (b) summarize the major findings in the context of heritability, environmentality, and their interplay under the ACE model; (c) explore the candidate genes for understanding the fundamental cause of EDs on a molecular base. On the basis of this review, the contribution of heritability lies in the range of 0.41 to 0.65. Shared environmental influences are considered neglectable and non-shared environmental influences occupy 0.35 to 0.64. Anorexia Nervosa (AN) and Bulimia Nervosa (BN) vary in these categories but only to a limited extent. Different sexualities and specific experiences of individuals might interact with the genetic risk of EDs. Several candidate genes are identified at the molecular level, but more are yet to be discovered in future studies. Based on the reviewed twin studies and adoption studies, we conclude that heritability contributes to a large extent to general EDs while the rest is accounted by non-shared environmentality. Other specific factors, including subcategories AN and BN, sexualities, specific symptoms, exhibit
ANMCO position paper on antithrombotic treatment of patients with atrial fibrillation undergoing intracoronary stenting and/or acute coronary syndromes

Abstract Patients with atrial fibrillation (AF) undergoing percutaneous coronary intervention (PCI) with or without acute coronary syndromes (ACS) represent a subgroup with a challenging pharmacological management. Indeed, if on the one hand, antithrombotic therapy should reduce the risk related to recurrent ischaemic events and/or stent thrombosis; on the other hand, care must be taken to avoid major bleeding events. In recent years, several trials, which overall included more than 12 000 patients, have been conducted demonstrating the safety of different therapeutic combinations of oral antiplatelet and anticoagulant agents. In the present ANMCO position paper, we propose a decision-making algorithm on antithrombotic strategies based on scientific evidence and expert consensus to be adopted in the periprocedural phase, at the time of hospital discharge, and in the long-term follow-up of patients with AF undergoing PCI with/without ACS.
Leveraging Cooperative Education Experiences to Enhance and Develop the Capstone Design Course

Paul Plotkowski is the founding Dean of the Padnos College of Engineering and Computing and Professor of Engineering at Grand Valley State University. Over the past 20 years he has led the development of an emerging engineering program into a comprehensive college that now offers 7 BS and 3 MS degrees to a population of over 2,000 students. He holds BSE, MSE and Ph.D. degrees from Oakland University.
The Causing Factors of Attention-Deficit Hyperactivity Disorder and Its Association with Other Psychiatric and Physical Disorders

: Attention-deficit hyperactivity disorder (ADHD) is a major neurodevelopmental health concern characterized by impairing patterns of inattention, impulsivity, and hyperactivity. As the causes of ADHD are multifaceted, this paper explores the etiology of ADHD and its induced factors through assessments of familial aggression and environmental impacts. Family studies and twin studies are involved in explaining the findings. Besides, this paper also aims to evaluate the co-occurrence risk of ADHD with other psychiatric disorders and physical disorders by noticing that comorbidity among this tripartite relationship is significant. Psychiatric comorbidities in ADHD are discussed in terms of mood disorders and substance use disorders; on the other hand, physical diseases mainly cover chronic inflammatory diseases and allergic diseases. Based on the evidence, ADHD is a genetic-related disorder with few shared environmental influences, which means that familial risk increases with a decreasing distance of biological relationships. Also, ADHD has high comorbidities with psychiatric disorders, including bipolar disorder, major depression, anxiety, and substance use disorder. Regarding physical diseases, cystic fibrosis, asthma, allergic rhinitis, and atopic dermatitis are found to coexist with ADHD. From clinical perspectives, our work on familial risk evaluation could facilitate the identification of ADHD in the family units to initiate medical care in the early stage. The co-occurrence feature may provide a detailed overview for exploring more possibilities to establish a more precise and complete diagnostic system.
Continuous circulation system

Recent events have emphasised the need for increased safety in the conduct of drilling operations, particularly in deepwater. Although not directly related to the apparent cause of the blowout in the Gulf of Mexico, the ability to maintain continuous, uninterrupted circulation and a steady downhole pressure regime while making up or breaking out drill pipe connections should significantly enhance safety when drilling the pressure-sensitive formations encountered in deepwater wells, explains Jim Jenner CEng FEI.
QualityCrowd - Crowdsourcing for Subjective Video Quality Tests

Despite continuing research on the development of better quality metrics, subjective tests are still indispensable for the assessment of video quality. These tests are both time-consuming and expensive and require installing a suitable laboratory that fulfills the corresponding ITU recommendations. In this thesis the use of crowdsourcing in conjunction with the internetbased performing of such tests shall be examined comparing the results of such a test and the results of conventional laboratory tests. For performing this test the web-based software QualityCrowd was developed, which allows the simple planning and conducting of subjective tests. The software uses Amazon's crowdsourcing platform Mechanical Turk to assign the assessment of the videos to the crowd. Amazon provides the infrastructure for distibuting large numbers of almost any task and paying the workers afterwards. Another aspect is the evaluation of the technical issues that arise from an internet-based video test. In particular, the problems concerning the compression, delivery and playback of the videos in the participants' browsers are discussed. After considering the various possibilities, a decision in favour of lossless compression using H.264/AVC and playback with Adobe's Flash Player is taken. The gathered data show very high correlation with the data from the laboratories they are compared with. Although there are also some significant deviations, the results in general are quite promising and indicate the suitability of the use of crowdsourcing for subjective video tests. Even though the test could not be conducted publicly and the workers be paid, the costs of a test like this one are estimated. It shows that - compared to conventional laboratory tests - a clear cut in costs can be achieved.
Proposed Improvements to the Tor Handshake

Tor is the world’s largest anonymous communication network. It conceals its users’ identities by sending their traﬃc through three successive Tor relays. To establish connections between users, relays, and destinations, Tor uses a unique two-staged handshake. The ﬁrst stage is a modiﬁed version of TLS 1.2 and the second stage is a fully encrypted exchange of Tor cells. The two-stage process enables both parties to au-thenticate while masking the diﬀerences that the Tor’s handshake has from standard TLS. The Tor handshake has multiple shortcomings when compared to widely-used cryptographic protocols like TLS and QUIC. It has high latency that detracts from the user experience and increased complexity that makes maintenance challenging. The ﬁrst stage of the handshake also only supports TLS 1.2 despite TLS 1.3’s release in 2018. Our work presents an analysis of Tor’s handshake and proposes improvements. We ﬁnd messages in the second stage of the Tor handshake that are redundant. Most notably, the responder sends a certiﬁcate that is not necessary for authentication. Removing these messages reduces the data transferred in the handshake without compromising the key exchange or authentication. Further, we ﬁnd that removing backward compatibility from the Tor handshake allows for the trivial use of TLS 1.3 in the ﬁrst stage. This reduces the round-trips and improves the security of the Tor handshake.
Verifiable and forward private conjunctive keyword search from DIA tree

In a dynamic searchable encryption (DSE) scheme, a cloud server can search on encrypted data that the client stores and updates from time to time. Due to information leakage during the search and update phase, DSE schemes are prone to file injection attacks. If during document addition, a DSE scheme does not leak any information about the previous search results, the scheme is said to be forward private. A DSE scheme that supports conjunctive keyword search should be forward private. There has been a fair deal of work on designing forward private DSE schemes in the presence of an honest-but-curious cloud server. However, a malicious cloud server might not run the protocol correctly and still want to be undetected. In a verifiable DSE, the cloud server not only returns the result of a search query but also provides proof that the result is computed correctly. We design a forward private DSE scheme that supports conjunctive keyword search. At the heart of the construction is our proposed data structure called dynamic interval accumulation tree (DIA tree). It is an accumulator based authentication tree that efficiently returns both membership and non-membership proofs. Using the DIA tree, we can convert any single key-word forward private DSE scheme to a verifiable forward private DSE scheme that can support conjunctive query as well. Our proposed scheme has the same storage as the base DSE scheme and low computational overhead at the client-side. We have shown the efficiency of our design by comparing it with existing conjunctive DSE schemes. The comparison also shows that our scheme is suitable for practical use.
Particle-Based Adaptive Sampling for Curriculum Learning

Inspired by nature, curriculum learning (CL) has been shown to be a promising approach to increase the performance and sample efficiency of a reinforcement learning (RL) agent on difficult tasks. In combination with transfer learning it enables the agent to leverage previous experience on a series of task variants with increasing difficulty, allowing for a more guided training process and a more versatile agent. Often, these curricula are represented as series of distributions, from which concrete tasks can be sampled and trained on. Although this representation allows for a lot of flexibility when generating curricula, the nature of distributions lead to some inefficiencies during the sampling and training process. Depending on the task, newly sampled tasks might end up in regions already covered by previous curriculum distributions, leading to less informative agent runs and training. In this thesis, we propose the usage of particle-based variational inference methods (ParVIs) to more effectively sample new tasks from less covered areas of the task space. The agent is only evaluated on these new tasks but is trained on both previous and new experiences. We specifically investigate two methods in the space of ParVIs called Stein variational gradient descent (SVGD) and Stein points (SP) and develop new sampling algorithms based on them to use for curriculum learning. These algorithms are later investigated on both pedagogical examples and also on a RL task using self-paced reinforcement learning (SPRL) for generating curricula. These experiments allow us to gain some insights into the inner workings of curriculum learning in the space of RL and how ParVIs can be used in the future to improve sampling in curriculum learning. Stein discrepancy by adding and removing samples according to our curriculum distribution. We were able to show that these samplers do not suf-fer from the same problems as the SVGD based approach and integrated them into an curriculum learning for reinforcement learning algorithm called self-paced reinforcement learning. While the application of this modified SPRL did not yield the expected results, we pointed out a few shortcomings of our method and proposed some future work, which could lead to improved results and a more efficient sample process for curriculum learning.
Accidental Landmarks: How Showing (and Removing) Emphasis in a 2D Visualization Affected Retrieval and Revisitation

Many visualizations display large datasets in which it can be difficult for users to find (and re-find) specific items. In systems that provide highlighting tools (e.g., filtering or brushing), emphasized points can become “accidental landmarks” – visual anchors that help users remember locations that are near the emphasized points. Acciden- tal landmarks could be useful (by aiding revisitation), but if users become dependent on them, removing or changing the highlight- ing could cause problems. We provide designers with information about these issues through two crowdsourced studies in which peo- ple learned a set of item locations (in visualizations with or without emphasized points); we then removed or changed the highlighting to see if performance suffered. In the first study, which used a simple grid of points, results showed that changing or removing emphasized points significantly impeded users’ ability to re-find targets, but the highlighting did not improve performance during training. In the second study, which used a more complex scatterplot, we found that highlighting significantly improved performance during training, but that removing or changing the emphasis points only reduced re-finding performance for a few target types. Our work demonstrates that visualization designers need to consider how transient visual effects such as emphasis can affect spatial learning and revisitation, and provides new knowledge about how visual features can affect performance.
Edinburgh Research Explorer Precision animal breeding

We accept that we are responsible for the quality of life of animals in our care. We accept that the activities of man affect all the living things with which we share this planet. But we are slow to realize that as a result we have a duty of care for all living things. That duty extends to the breeding of animals for which we are responsible. When animals are bred by man for a purpose, the aim should be to meet certain goals: to improve the precision with which breeding outcomes can be predicted; to avoid the introduction and advance of characteristics deleterious to well-being; and to manage genetic resources and diversity between and within populations as set out in the Convention on Biological Diversity. These goals are summed up in the phrase precision animal breeding. They should apply whether animals are bred as sources of usable products or services for medical or scientiﬁc research, for aesthetic or cultural considerations, or as pets. Modern molecular and quantitative genetics and advances in reproductive physiology provide the tools with which these goals can be met.