Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploration of fault-related deep-circulation geothermal resources in the western branch of the East African Rift System: examples from Uganda and Tanzania

With support from the EAGER program, the geothermal exploration approach applied to prospects in the western branch of the East African Rift System (EARS) has been adopted from successful exploration and development of other global deep circulation resources. The western branch of the EARS is at an earlier evolutionary stage of continental rift development than the eastern branch, resulting in a different type of geothermal resource requiring different exploration and development strategies. Exploration in the eastern branch has identified numerous volcano-hosted, magmatically-heated geothermal resources with likely production temperatures of 200 to 350°C. In contrast, most western branch geothermal resources are heated by deep-circulation along structures that penetrate to several km depth in otherwise low permeability rocks. For these reasons the western branch resources are mostly <180°C and hosted in fractured upflows and/or lower temperature shallow sedimentary outflows. Exploration programs conducted at western rift prospects in Uganda and Tanzania since 2015 have highlighted the relevance of exploration strategies used at analogous areas in the Basin and Range region of the USA, where < 2% of the known resources are magmatically heated, that is, resources heated by emplacement of magma within 10 km from the ground surface. Exploration methods at deep circulation, fault-hosted systems are similar to those applied at volcano-hosted prospects, including the compilation and analysis of existing data, the initial prioritization of prospects based on fluid and gas geochemistry of thermal manifestations, and then detailed exploration of the higher priority areas. However, the priorities and conceptual context for subsequent data acquisition and analysis differ. For example, identifying key structural settings (e.g., fault step-overs) associated with Quaternary active fault segments and their position within the overall structural and stratigraphic framework should be given more emphasis at prospects that depend on deep-circulation in fault systems for their heat. Although resistivity methods like MT and TEM remain the most common geophysical methods used to explore deep-circulation geothermal systems, their interpretation has important conceptual differences, such as a greater focus on identifying formations that would enhance the development of fracture permeability or that might host outflow targets. Because of the relatively low level of confidence in identifying the smaller targets associated with deep-circulation zones based on surface data alone, temperature gradient wells are more often cost-effective to explore these systems than in magmaticallyheated ones. During the EAGER program from 2016 through 2018, two deep circulation geothermal prospects in Uganda and one in Tanzania have been explored following these standards, supporting resource capacity assessments and recommendations for TGH drilling.
Fostering “Family”: Communication Orientations in the Foster Parent-Child Relationship

Although foster families serve a critical societal role, little is known about foster family communication dynamics. The present study investigated the relationship of current foster parents’ (n = 158) communication with his/her foster child on foster parents’ perceptions of relational and child well-being. Structural equation modeling analysis revealed that foster parent-child communication is associated with foster parents’ perceptions of shared family identity, relational closeness, and child resiliency. These findings suggest the importance of domain-specific family communication orientations and underscore the critical role of open communication in foster families.
Correlation between Fast and Slow States Observed Post Substrate Hole Injection in P-MOSFETs

The recently reported post-stress degradation of MOSFETs is investigated in this paper. We found that during substrate hole injection fast and slow states are created. Once the injection is stopped and a positive gate voltage is applied, without injection, the slow states migrate toward the silicon silicon-dioxide interface and become fast states. This explains the previously reported increase in fast state density post Substrate hole injection. Keywords— Interface states, Substrate hole injection, Slow states, Trapped holes
Left-right supersymmetric option at a high-energy upgrade of the LHC

We investigate the possibility that a minimal realization of left-right supersymmetry can be reachable at a high-energy upgrade of the LHC, expected to operate at a center-of-mass energy of 27 TeV. This minimal scenario has a relatively light $SU(2)_R$ doubly-charged Higgs boson, which could decay dominantly into tau-lepton pairs. We explore the associated signals comprised of at least three hadronically-decaying taus, or with at least two hadronic taus and one same-sign-same-flavor charged lepton pair. Our analysis shows that the former signature is challenging to use for getting handles on the signal due to the large corresponding background, and that the latter one can lead to a handful of new physics events in an almost background-free environment. We however find that a signal comprised of three hadronically-decaying tau leptons is likely to be observed at a low luminosity of proton-proton collisions at a 27 TeV upgrade of the LHC.
Coronavirus Perceptions and Economic Anxiety

Abstract We provide one of the first systematic assessments of the development and determinants of economic anxiety at the onset of the coronavirus pandemic. Using a global data set on internet searches and two representative surveys from the United States, we document a substantial increase in economic anxiety during and after the arrival of the coronavirus. We also document a large dispersion in beliefs about the pandemic risk factors of the coronavirus and demonstrate that these beliefs causally affect individuals' economic anxieties. Finally, we show that individuals' mental models of infectious disease spread understate nonlinear growth and shape the extent of economic anxiety.
Improving Student’s Mathematical Communication Skills Through Mathematics Worksheet Based on Realistic Mathematics Education

Students' mathematical communication skills are still low. The reason is that the presentation of material is less related to student life. The purposes of this research is to develop mathematics worksheets based on Realistic Mathematics Education to improve students' communication skills. This type of research is the Plomp design research model with three stages, namely the preliminary investigation, prototyping stage, and assessment phase. The instruments used were observation sheets, interview guidelines, questionnaires, and tests. The results showed that the worksheet was practical, effective, and valid, and was able in improving students' mathematical communication skills. The use of problems related to the students’ life makes learning more meaningful.
Management of the Bronchial Asthma Patients at Practice of Family Doctors

With purpose to assess the primary care for bronchial asthma (BA) patients the anonymous survey of 175 family doctors was performed. We established low percent (2,9%) of self-depended diagnosis of BA by family doctors. It showed their extremely poor role in the primary BA diagnosis. The most frequently diagnosis of BA made by pulmonologist or allergist (75,4%). The management of a patient with BA was performed by a family doctor in collaboration with allergist or pulmonologist in 53,2% of cases, 70% family doctors meet with BA patients for control of disease every 1-3 month. They prescribed correct basis therapy with inhaled corticosteroid (ICS) or combination of ICS with long-action beta agonist most of patients. Misinterpretation of asthma control are showed by most of family doctors. The vast majority of patients (98.8%) had at least one exacerbation of asthma per year. Only 25% of family doctors treated patients with BA exacerbation self-dependently. They used nebulization of high doses of bronchodilators and ICS for treatment of BA exacerbation in outpatient setting for 91,4% of cases. We found low level of prescriptions of systemic corticosteroids for treatment of BA exacerbations in outpatient setting and misunderstanding of systemic corticosteroid therapy. Family doctors need additional educational activities and monitoring adherence to national and international guidelines.
Individual Fairness Under Composition

Much of the literature on fairness in classiﬁcation considers the case of a single classiﬁer used once, in isolation. However, fairness is not a property of isolated classiﬁers alone, it is also a property of classiﬁers composed into systems, and systems must handle repeated use and interaction with other fair (or unfair) systems. We initiate the study of composition of individually fair classiﬁers proposed in [Dwork, Hardt, Pitassi, Reingold, Zemel, 2011]. We ﬁnd that fairness does not behave well under composition and propose directions to remedy the situation.
Vitamin D Deficiency in College-Age Male Basketball Players: Sports Medicine Physicians Can Play an Important Role

Sports medicine physicians need to be aware of the inherent risks in the sport that they serve. There are certain risk factors that can be easily controlled through diet and supplementation. There is interest in the vitamin D levels of athletes who compete indoors worldwide. In the United States (U. S.), data has been reported on the inadequacy of serum 25(OH)D levels in high level athletes, especially those who compete in doors. The National Basketball Association (NBA) released deidentified data on 279 players from 2009 through 2013. Vitamin D levels were categorized as follows: (a) deficient (<20ng/mL); (b) insufficient (20-32 ng/mL); and sufficient (>32ng/mL). Surprisingly, 79.3% were either vitamin D deficient or insufficient, as defined in this study. The average vitamin D levels for all players was 25.6 ± 10.2 ng/mL, which was categorized as insufficient. 1 In another study in the U. S. , preliminary data in gymnasts report especially alarming levels of vitamin D, with 37% recording levels in the single digits. 2 These findings are extremely ABSTRACT
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

In many real-world settings, a team of agents must coordinate its behaviour while acting in a decentralised fashion. At the same time, it is often possible to train the agents in a centralised fashion where global state information is available and communication constraints are lifted. Learning joint action-values conditioned on extra state information is an attractive way to exploit centralised learning, but the best strategy for then extracting decentralised policies is unclear. Our solution is QMIX, a novel value-based method that can train decentralised policies in a centralised end-to-end fashion. QMIX employs a mixing network that estimates joint action-values as a monotonic combination of per-agent values. We structurally enforce that the joint-action value is monotonic in the per-agent values, through the use of non-negative weights in the mixing network, which guarantees consistency between the centralised and decentralised policies. To evaluate the performance of QMIX, we propose the StarCraft Multi-Agent Challenge (SMAC) as a new benchmark for deep multi-agent reinforcement learning. We evaluate QMIX on a challenging set of SMAC scenarios and show that it significantly outperforms existing multi-agent reinforcement learning methods.
Predictors of mortality among a cohort of HIV/AIDS patients on anti-retroviral therapy in coastal South India

Introduction: As the number of patients on anti-retroviral therapy (ART) rises, it is important to identify factors that predict mortality among these patients so that they can be closely monitored. Aim of the study was to determine the mortality rate among a cohort of HIV patients on naive ART and to assess the predictors of mortality among them. Material and methods: In this retrospective study, records of 249 patients living with HIV (PLHIV) who were ART naive, enrolled in the ART centre attached to Kasturba Medical College Hospital, Mangalore from February 2012 to February 2015, were analysed. Univariate and multivariate logistic regression was carried out to assess the factors predicting mortality among these patients. Results: By the end of the study period, 47 out of 249 patients died, giving an overall mortality rate of 18.8%. The mean age of the PLHIV was 43.4 ± 9.1 years. WHO stage 3/4 disease was present in 47.4% of patients. On univariate analysis, mortality was found to be significantly associated with alcohol consumption, being non-ambulatory, underweight (body mass index [BMI] < 18.5 kg/m2), WHO stage 3 or 4 disease, presence of opportunistic infections (OIs), presence of tuberculosis, being on an efavirenz-based regimen, poor adherence (< 95%), CD4 count < 350 cells/mm3, anaemia and raised creatinine levels. However, on multivariate analysis, presence of OIs and low BMI were found to independently predict mortality. Conclusions: Our study identifies lower BMI and presence of OIs as independent risk factors predicting mortality.
The Influence of pH of Saliva on the Release of Nickel and the Surface Roughness of Stainless Steel as Medical Devices

Metal is common as medical devices. Stainless steel (SS316L) has low carbon composition in order to increase corrosion resistance. The release of stainless steel ions can occur due to corrosion and affect the surface roughness. This study determined the influence of pH level of saliva on the concentration of nickel ions release and the surface roughness of SS316L. Twelve specimens of SS316L sized (10x10x1)mm were divided into 3 groups (artificial saliva with pH 3, 5, and 7). Samples were stored in the incubator at 37°C for 14 days. The concentration of nickel ions released was measured using atomic absorption spectrophotometry (ppm). The surface roughness was measured before and after the immersion using surface roughness measuring instrument (µm). The result showed the concentration of nickel ion released (ppm) were 0.099±0.023 (pH 3), 0.045±0.020 (pH 5), and 0.000±0.000 (pH 7). While the surface roughness (µm) were 0.22±0.06 (pH 3), 0.12±0.04 (pH 5), and 0.1±0.03 (pH 7). One-way ANOVA proved that the pH level of saliva significantly influenced the concentration of nickel ions and the surface roughness (p <0.05). It can be concluded that the lower pH level of saliva, the higher concentration of nickel ions released and the rougher the surface of SS316L.
FZA-APNCA Control Strategy for WG/HG/PV Based Microgrid at Unbalanced Nonlinear Loads

To achieve harmonics compensation in a distributed generation (DG) unit, a flexible zero attracting affine projection normalized correlation algorithm (FZA-APNCA) is used in this paper. The proposed control provides improved convergence without affecting the harmonics compensation when connected to unbalanced and nonlinear loads. In proposed islanded microgrid, by using the proposed FZA-APNCA both system stability and load power sharing capability are achieved. In addition, the robustness of the implemented control structure is investigated by comparing it with conventional controls. The proposed system is a combination of wind turbine driven permanent magnet brushless DC generator (PMBLDCG), battery energy storage (BES), solar PV array and synchronous reluctance generator (SyRG) used for hydro generation. Where, BES (Battery Energy Storage) is attached at the DC link, which maintains the power balance under perturbation in generation and loads. Test results from the laboratory prototype are validated and are meeting the requirement of the IEEE 1547.4 standard.
An Efficient Hardware Implementation of Walsh Hadamard Transform for JPEG XR

Walsh Hadamard Transform (WHT) is an important transformation technique used in image and signal processing applications like image compression, filtering and speech processing. The WHT becomes an automatic choice in JPEG XR image compression standard due to the simple computation technique. The kernel matrix used in WHT consists of only two values namely +1 and -1, hence input coefficients are either added or subtracted. This paper proposes a high throughput pipelined architecture for computing WHT by reusing common sub-expressions. In the proposed design, computation is performed by adding and subtracting the input data and store the intermediate results (sub-expressions) in the register stacks for reuse. The architecture is designed and implemented in XC3S700AN-4 device and maximum frequency of operation obtained is 162 MHz. The comparison of the computing speed of the proposed architecture with the previously available designs has been done based on the throughput which is defined as the time interval for computing overall results of an 8×8 image matrix. The proposed architecture consumes 395 nS time (Throughput) to generate the result of an 8×8 image matrix which is 51% lesser than that of the best available design.
Analysis of Static and Dynamic Infrared Images for Thyroid Nodules Investigation

Disorder of the thyroid glands is a widespread health problem. Early detection of thyroid cancer increases the chances of effective treatment. Dynamic infrared thermal imaging (DITI) is an examination technique that has been recently studied and applied for investigation and diagnosis of different diseases. Patterns allowing differentiate regions of malignant from benignant nodules is a task of great importance in DITI. In this work, two techniques of analysis of thyroid nodules with infrared thermography are investigated: the use of a single thermogram and the use of temperature series. The images used are available for public use by other researchers, and the used techniques are completely described as well as the achieved results. No other works using infrared images until now have considered DITI examination for thyroid nodules investigation. Moreover, it is the first work to release the used images for public use and possible future comparison.
On Computation of Texture Descriptors from Sum and Difference Histograms

Texture information is used in some computational activities such as pattern recognition and segmentation. One of the most used methods to obtain this information uses the Haralick descriptors that are calculated from the Gray Level Occurrence Matrix (GLCM) that has a quadratic cost. On the other hand, in this work we discuss an approach that has linear cost and achieves the same results using Sum and Difference Histograms (SDH). A set of nine equations from SDH presenting similar results to GLCM have been introduced some time ago, however, their differences may vary greatly in absolute values. This work presents an evolution in this direction that allows obtaining descriptors numerically equal or with a very small variation around 10−1. In addition, another six new equations are added in this study for other descriptors. All results from SDH use less computational resources and present the same behavior as those obtained by GLCM. This work illustrates the above-mentioned statement.
Evaluating Skills Dimensions: Case Study on Occupational Changes in the UAE

Rapid technological advances have led to profound changes to skills composition in the workplace. Low skilled jobs are gradually being replaced by automated systems, while there is a gaining demand for jobs which require interpersonal and technological skills. In this study, a combination of data science techniques are used to study this phenomenon. Firstly, matrix factorization and clustering methods are used to extract skills dimensions from O∗NET, a database of occupations-skills matchings compiled by the US Department of Labor. A method of evaluating the performance of each of these methods is proposed and used to determine the ideal extraction procedure. Next, the relative importance of different occupations was estimated using a corpus of job advertisements collected from local job sites, which we adopt as a proxy for demand. Finally, the results of this analysis are used to measure shifts in the demand for the skills and abilities associated with these occupations. This procedure is applicable to any job market. However as a test of its effectiveness, it was used to study two important economic sectors in the United Arab Emirates (UAE): Oil & Gas and Banking & Finance. The findings of this study will help us to determine the jobs and skills which will be most impacted by structural and technological change, and provide recommendations to ensure that the UAE workforce is well equipped to adapt to these changes.
Optimal Power Flow in Microgrids using Genetic Algorithm

Intelligent algorithms are becoming more prevalent in the domain of optimization and optimal power flow (OPF). They possess inherent advantages such as the ability to avoid entrapment in the local minimum of the optimization problem and converge onto a global solution. This paper presents the use of genetic algorithm (GA) to the OPF problem in a local microgrid setup with regard to minimization of cost which includes the installation costs for the solar PV array and the battery storage.
Secret Key Generation from a Two Component Compound Source with Rate Constrained One Way Communication: Perfect Secrecy

Secret key generation at two terminals is considered. Each terminal observes one of the outputs of a two component source. The two source outputs are correlated. Additionally one terminal can send a message to the second terminal via a noiseless public channel. It is assumed that this message is rate constrained. An eavesdropper with access to the public communication should be kept ignorant of the secret key. The maximum secret key rate that can be achieved such that the key is uniformly distributed and meets the perfect secrecy requirement is determined. This result is established for a compound source model.
Some Progress on Quantum Error Correction for Discrete and Continuous Error Models

Quantum computing has increasingly gained attention for decades since it can surpass classical computing in various aspects. A crucial issue of quantum computing is how to protect information from noise interference such that the error rate during quantum information processing can be limited within an acceptable bound. The technique to address this issue is quantum error correction (QEC). Developing QEC technologies needs to define noise as formal error models and design QEC approaches for these error models. Discrete error models and continuous error models are two kinds of definitions of noise. The former assumes noise occurs independently and can be discretized into a set of basic errors. The former also has a tool, named quantum operations, to describe a specific error model. The latter describes that noise is continuous in time by using differential equations. In this paper, we categorize QEC approaches into three types according to the different error models: discrete error models, specific error models, and continuous error models. We also analyze the state-of-the-art QEC approaches and discuss some future directions. Furthermore, we propose the perturbed error models and their possible definitions, aiming to find the effect of the perturbation during quantum information processing.