Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of genetic variation in Apis mellifera jemenitica (Hymenoptera: Apidae) based on mitochondrial Cytochrome Oxidase Subunit II and III

Morphometric and genetic characterization of many Apis mellifera subspecies are well-documented. A. m. jemenetica occurs naturally in Africa and Asia. In this study, genetic variation of mitochondrial Cytochrome Oxidase II (COII) and III (COIII) were analysed in 133 specimens of the endemic honeybee colonies within Saudi Arabia. The COII gene sequence length was 684 bp comprising nine synonymous (1.3%) and two non-synonymous single nucleotide polymorphisms (SNPs) (0.87%). Five variants of COII were not previously documented, one variant (MT755968) showed an extra restriction site when subjected to type II restriction endonuclease from Arthrobacter protophormiae (Apol) or to Haemophilus influenzae Rf (Hinf1). Changes in COII sequence separated samples into three haplogroups. Whereas, COIII gene sequence length was 780 bp, including 18 synonymous and five non-synonymous SNPs. Furthermore, variation in COII sequence was more informative based on restriction profiles and on amino acid changes compared with COIII gene sequence. Variants of COIII showed identical restriction sites when subjected to type II restriction endonuclease from Deinococcus radiophilus (DraI), and revealed high similarity to African subspecies. Results of this study are very useful in understanding genetic diversity and characterization of A. mellifera subspecies.
Intelligent distribution voltage control with distributed generation

In this thesis, three methods for the optimal participation of the reactive power of distributed generations (DGs) in unbalanced distributed network have been proposed, developed, and tested. These new methods were developed with the objectives of maintain voltage within permissible limits and reduce losses. The first method proposes an optimal participation of reactive power of all devices available in the network. The propose approach is validated by comparing the results with other methods reported in the literature. The proposed method was implemented using Simulink of Matlab and OpenDSS. Optimization techniques and the presentation of results are from Matlab. The co-simulation of Electric Power Research Institute’s (EPRI) OpenDSS program solves a three-phase optimal power flow problem in the unbalanced IEEE 13 and 34-node test feeders. The results from this work showed a better loss reduction compared to the Coordinated Voltage Control (CVC) method. The second method aims to minimize the voltage variation on the pilot bus on distribution network using DGs. It uses Pareto and Fuzzy-PID logic to reduce the voltage variation. Results indicate that the proposed method reduces the voltage variation more than the other methods. Simulink of Matlab and OpenDSS is used in the development of the proposed approach. The performance of the method is evaluated on IEEE 13-node test feeder with one and three DGs. Variables and unbalanced loads are used, based on real consumption data, over a time window of 48 hours. The third method aims to minimize the reactive losses using DGs on distribution networks. This method analyzes the problem using the IEEE 13-node test feeder with three different loads and the IEEE 123-node test feeder with four DGs. The DGs can be fixed or variables. Results indicate that integration of DGs to optimize the reactive power of the network helps to maintain the voltage within the allowed limits and to reduce the reactive power losses. The thesis is presented in the form of the three articles. The first article is published in the journal Electrical Power and Energy System, the second is published in the international journal Energies and the third was submitted to the journal Electrical Power and Energy System. Two other articles have been published in conferences with reviewing committee. This work is based on six chapters, which are detailed in the various sections of the thesis.
Characterisation of the human CYP2A7 gene : an analysis of its structure, regulation and expression

1 CHAPTER 1: INTRODUCTION 3 1.1 Metabolism of Xenobiotic and Cytochrome P450: General View and Historical Background 3 1.2 Evolution and Nomenclature 5 1.2.1 Cytochrome P450 nomenclature 5 1.2.2 Evolution of CYP superfamily 7 1.2. 3 Evolution of CYP2A subfamily 9 1.2. 4 The molecular mechanism of cytochrome P450 evolution 11 1.3 Structure and Metabolic Reactions of Cytochrome P450 13 1.3. 1 Structure of cytochrome P450 13 1.3. 2 Reactions catalysed by cytochrome P450 15 1.4 Roles of Cytochrome P450s in Activation of Chemical Carcinogens and Genetic Susceptibility to Diseases 20 1.4. 1 Activation ofprocarcinogens by P450 20 1.4. 2 Genetic susceptibility to disease 23 1.5 Aims of the Study 26 CHAPTER 2: MATERIALS AND METHODS 31 2.1 Materials 31 2.1.1 Commercial material sources 31 2.1.2 Non-commercial materials 31 2.2 Cell Culture 31 2.2.1 Cell lines 31 2.2.2 Conditions for cell culture 32 2.2. 3 Freezing cells for storage and retrieving stocks 32 2.2. 4 Feeding cells 33 2.2. 5 Sub-culture of cells 33
Penerapan Fuzzy Mamdani Untuk Sistem Pendukung Keputusan Pemilihan Telepon Seluler

Fuzzy logic merupakan salah satu pendekatan yang menggunakan beberapa tahapan tertentu. Beberapa model fuzzy logic banyak diterapkan dalam menyelesaikan berbagai permasalahan salah satunya adalah fuzzy Mamdani.Banyaknya jenis telepon seluler yang tersedia dipasaran membuat para konsumen menjadi kesulitan untuk menentukan pilihannya. Permasalahan yang dipilih adalah membangun sistem pendukung pengambilan keputusan untuk membantu memberikan pilihan ponsel bagi para konsumen berdasarkan kriteria-kriteria yang diinginkan oleh konsumen tersebut. Kriteria yang digunakan dalam membantu menentukan pilihan ponsel yang diinginkan konsumen antara lain berdasarkan pada harga, ukuran layar ponsel, dan kapasitas memori. Dikarenakan kriteria-kriteria tersebut sifatnya relatif maka dibuat fuzzy Mamdani yang dapat digunakan model untuk mendapatkan pilihan yang tepat dari suatu yang samar. Hasil penelitian dalam pemilihan telepon seluler, berdasarkan data telepon seluler penulis melakukan beberapa pengujian yaitu pengujian dengan fuzzy dan pengujian menggunakan software Matlab yang dapat membantu mempercepat proses pengolahan data dan mendapatkan sebuah keputusan dengan cepat
Effects of maternal ritodrine hydrochloride administration on the heart rate of preterm fetal sheep with intraamniotic inflammation

Ritodrine hydrochloride is used for pregnancy prolongation and intrauterine fetal resuscitation. However, its clinical significance in intraamniotic inflammation during preterm labor and intrauterine fetal distress is unclear. We investigated the effects of maternal ritodrine hydrochloride administration (MRA; 200 μg/min for 2 h, followed by 800 μg/min for 2 h after 24 h) on fetal physiological parameters. For this purpose, we used chronically instrumented pregnant sheep at 113–119 d (term = 145 d) of gestation without (Group 1, n = 5) and with (Group 2, n = 5) intraamniotic inflammation induced by lipopolysaccharide injection into the amniotic cavity. The changes in fetal heart rate (FHR) and short-term variability (STV) and long-term variability (LTV) in FHR, fetal blood pressure, and fetal arterial blood gas (FABG) values were measured before and at 1 and 2 h after initiating MRA. Before MRA, all parameters were similar between Groups 1 and 2; however, there was significantly higher STV in Group 2 than in Group 1 before MRA at 800 μg/min, significantly higher partial arterial pressure of carbon dioxide in FABG in Group 2 than in Group 1 before MRA at 200 μg/min, and significantly lower blood glucose (BG) in Group 2 than in Group 1 before MRA at 800 μg/min. One hour after MRA, the FHR, STV, and LTV were significantly higher at 800 μg/min than those at the baseline in Group 1, as determined by the Friedman test; however, no significant difference was observed in Group 2. Additionally, the FABG pH significantly decreased 1 h after MRA at 800 μg/min in Group 2, whereas FABG lactate and BG significantly increased 2 h after MRA at 800 μg/min in Groups 1 and 2. Thus, short-term MRA at 800 μg/min increased the FHR, STV, and LTV significantly; these values were further modified under intraamniotic inflammation.
How common is hyperkalaemia? A systematic review and meta-analysis of the prevalence and incidence of hyperkalaemia reported in observational studies

ABSTRACT Background The prevalence and incidence of hyperkalaemia, a potassium abnormality that can potentially have life-threatening consequences, are unclear. Methods The objective was to provide the most comprehensive overview of the epidemiology of hyperkalaemia to date within the general population, across different continents, in different healthcare settings and within pre-specified subgroups. Embase and MEDLINE were searched from database inception to 2 February 2021 using the Ovid SP platform. Relevant congress proceedings from 2018 to 2020 were also reviewed for inclusion. There was no language constraint applied. Observational studies from any time period and language reporting prevalence or incidence of hyperkalaemia within both adult and paediatric populations. Four investigators independently screened abstracts and assessed study quality of those meeting the pre-determined inclusion/exclusion criteria. Data extraction was conducted by the lead author with oversight from the senior author and data were pooled using a random-effects model. The measures assessed were the prevalence and incidence of hyperkalaemia. Prevalence was reported as a percentage, whilst incidence was reported as the rate per 100 person years. Results In total, 542 articles were included from an initial search of 14 112 articles. Across all adult studies, we report a prevalence of hyperkalaemia (by any definition/threshold) of 6.3% [95% confidence interval (CI): 5.8–6.8%], with an incidence of hyperkalaemia in the adult population of 2.8 (2.3–3.3) cases per 100 person years. Prevalence within the general population was 1.3% (1.0–1.8%), whilst incidence was 0.4 (0.2–0.8) cases per 100 person years. There was a variation by sex with a prevalence of 6.3% (4.9–8.0%) in males and 5.1% (4.0–6.6%) in females. Prevalence also varied according to the definition/threshold of hyperkalaemia used: >5 mmol/L—8.0% (7.2–8.9), ≥5.5 mmol/L—5.9% (3.5–10.0) and ≥6.0 mmol/L—1.0% (0.8–1.4); hyperkalaemia (by any definition/threshold) was highest amongst patients with end-stage kidney disease (21.5%; 18.3–25.3), kidney transplant patients (21.8%; 16.1–29.5) and patients with acute kidney injury (24.3%; 19.3–30.7). Conclusions This novel review provides a comprehensive and valuable resource on the prevalence and incidence of hyperkalaemia to better inform clinicians, healthcare providers and health policy makers on the burden of hyperkalaemia across different healthcare settings, patient populations and continents.
ANALISIS PENENTUAN TARIF JASA RAWAT INAP RUMAH SAKIT DENGAN MENGGUNAKAN ABC SISTEM (Studi Kasus di Rumah Sakit Haji Darjad (RSHD) Kota Samarinda)

Keyword : ABC, Cost driver, Aktivitas Tujuan dari penelitian ini adalah untuk perhitungan tarif jasa rawat inap rumah sakit dengan menggunakan Activity Based Costing pada Rumah Sakit Haji Darjad (RSHD) Kota Samarinda. Untuk mengatasi distorsi pada akuntansi tradisional Activity Based Costing (ABC) merupakan suatu sistem kalkulasi biaya yang pertama kali menelusuri biaya semua aktivitas dan kemudian keproduk yang dinilai dapat mengukur secara cermat biaya-biaya yang keluar dari setiap aktivitas. Metode penelitian yang digunakan dalam skripsi ini yaitu dengan menggunakan jenis penelitian deskriftif. Dari hasil penelitian ini menunjukan bahwa perhitungan tarif jasa rawat inap dengan menggunkan Activity Based Costing dan tarif yang sudah diterapkan rumah sakit dapat diketahui bahwa hasil perhitungan tarif rawat inap terdapat selisih untuk kelas III, karena untuk ruang kelas III pada Rumah Sakit Haji Darjad (RSHD) di tempatin lebih dari dua orang pasien. Pihak rumah sakit tetap akan mendapatkan laba walupun perhitungan tarif dengan metode Activity Based Costing memberikan hasil selisih lebih rendah.
The effect of droplet size on syntrophic dynamics in droplet-enabled microbial co-cultivation

Co-cultivation in microfluidic droplets has emerged as a versatile tool for the study of natural and synthetic microbial communities. In particular, the identification and characterization of syntrophic interactions in these communities is attracting increasing interest due to their critical importance for the functioning of environmental and host-associated communities as well as new biotechnological applications. However, one critical parameter in droplet-enabled co-cultivation that has evaded appropriate evaluation is the droplet size. Given the same number of initial cells, a larger droplet size can increase the length scale secreted metabolites must diffuse as well as dilute the initial concentration of cells and exchanged metabolites, impacting the community dynamics. To evaluate the effect of droplet size on a spectrum of syntrophic interactions, we cultivated a synthetic model system consisting of two E. coli auxotrophs, whose interactions could be modulated through supplementation of related amino acids in the medium. Our results demonstrate that the droplet size impacts substantially numerous aspects of the growth of a cross-feeding bi-culture, particularly the growth capacity, maximum specific growth rate, and lag time, depending on the degree of the interaction. This work heavily suggests that one droplet size does not fit all types of interactions; this parameter should be carefully evaluated and chosen in experimental studies that aim to utilize droplet-enabled co-cultivation to characterize or elucidate microbial interactions.
On the Application of Artificial Intelligence and Feature Selection in Sports Science Education and Research: A Case Study

In sports science education and research, the use of artificial intelligence methods along with feature selection algorithms can be of great help for developing prediction models where experimental studies based on measurements are not feasible. In this paper, we present a case study in regards to how sports science can benefit from the use of artificial intelligence methods combined with a feature selection algorithm. More specifically, the purpose of our study is to develop prediction models for upper body power (UBP), which is one of the most important factors affecting the performance of cross-country skiers during races. The dataset, which includes 75 subjects, was obtained from the College of Education, Health and Development of Montana State University. Multilayer Perceptron (MLP) and Single Decision Tree (SDT) along with the minimum-redundancy maximum-relevance (mRMR) feature selection algorithm were used to produce prediction models for predicting the 10-second UBP (UBP10) and 60-second UBP (UBP60). The predictor variables in the dataset are protocol, gender, age, body mass index (BMI), maximum oxygen uptake (VO2max), maximum heart rate (HRmax), time and heart rate at lactate threshold (HRLT) whereas UBP10 and UBP60 are the target variables. Based on the ranking scores of predictor variables assigned by the mRMR, 16 different prediction models have been developed. By using 10-fold cross-validation, the efficiency of the prediction models has been calculated with their multiple correlation coefficients (Râ€™s) and standard error of estimates (SEEâ€™s). The results show that using less amount of predictor variables than the full set of predictor variables can be useful for prediction of UBP10 and UBP60 with comparable error rates. The model consisting of the predictor variables gender, BMI, VO2max, HRLT and time yields the lowest SEEâ€™s for prediction of UBP10, while the model including the predictor variables gender, age, BMI and VO2max gives the lowest SEEâ€™s for prediction of UBP60, whichever regression method is used. Using these two models instead of the full set of predictor variables yields up to 4.95% and 6.83% decrement rates in SEEâ€™s for MLP and SDT based UBP prediction models, respectively.Keywords: multilayer perceptron; single decision tree; sports science education;
Neural effective connectivity explains subjective fatigue in stroke

Abstract Persistent fatigue is a major debilitating symptom in many psychiatric and neurological conditions, including stroke. Post-stroke fatigue has been linked to low corticomotor excitability. Yet, it remains elusive as to what the neuronal mechanisms are that underlie motor cortex excitability and chronic persistence of fatigue. In this cross-sectional observational study, in two experiments we examined a total of 59 non-depressed stroke survivors with minimal motoric and cognitive impairments using ‘resting-state’ MRI and single- and paired-pulse transcranial magnetic stimulation. In the first session of Experiment 1, we assessed resting motor thresholds—a typical measure of cortical excitability—by applying transcranial magnetic stimulation to the primary motor cortex (M1) and measuring motor-evoked potentials in the hand affected by stroke. In the second session, we measured their brain activity with resting-state MRI to assess effective connectivity interactions at rest. In Experiment 2 we examined effective inter-hemispheric connectivity in an independent sample of patients using paired-pulse transcranial magnetic stimulation. We also assessed the levels of non-exercise induced, persistent fatigue using Fatigue Severity Scale (FSS-7), a self-report questionnaire that has been widely applied and validated across different conditions. We used spectral dynamic causal modelling in Experiment 1 and paired-pulse transcranial magnetic stimulation in Experiment 2 to characterize how neuronal effective connectivity relates to self-reported post-stroke fatigue. In a multiple regression analysis, we used the balance in inhibitory connectivity between homologue regions in M1 as the main predictor, and have included lesioned hemisphere, resting motor threshold and levels of depression as additional predictors. Our novel index of inter-hemispheric inhibition balance was a significant predictor of post-stroke fatigue in Experiment 1 (β = 1.524, P = 7.56 × 10−5, confidence interval: 0.921 to 2.127) and in Experiment 2 (β = 0.541, P = 0.049, confidence interval: 0.002 to 1.080). In Experiment 2, depression scores and corticospinal excitability, a measure associated with subjective fatigue, also significantly accounted for variability in fatigue. We suggest that the balance in inter-hemispheric inhibitory effects between primary motor regions can explain subjective post-stroke fatigue. Findings provide novel insights into neural mechanisms that underlie persistent fatigue.
Web Services Approach to Library Federated Search: Bangalore University Academic Library Network(Bal-Net) Initiative

The objective of this project is to setup a co-operative framework and develop a central index system for accessing the collections of all Affiliated College Libraries of Bangalore University. This is ought to be achieved by applying a new approach for search and retrieval via SRU/W combined with MARC and Dublin core meta-data paradigm; harvest meta-data using Open Archives Initiative – Protocol for Meta-data Harvesting. The project includes a server, client and portal, functionality partly running on Server and client browser resulting in a low implementation barrier, maximum scalability, and browser independence, as well as giving users control over the search interface and what collections to search.
Salient alternatives facilitate implicatures

Sentences can be enriched by considering what the speaker does not say but could have done, the alternative. We conducted two experiments to test whether the salience of the alternative contributes to how people derive implicatures. Participants responded true or false to underinformative categorical sentences that involved quantifiers. Target sentences were sometimes preceded by the alternative and sometimes by a control sentence. When the target was preceded by the alternative, response times to implicature responses were faster than when preceded by the control sentence. This suggests that (1) alternative salience influences higher-level reasoning (2) the cost of deriving implicatures in sentence verification paradigms is due in part to low alternative salience.
Machine Learning with Quantum Seagull Optimization Model for COVID-19 Chest X-Ray Image Classification

Early and accurate detection of COVID-19 is an essential process to curb the spread of this deadly disease and its mortality rate. Chest radiology scan is a significant tool for early management and diagnosis of COVID-19 since the virus targets the respiratory system. Chest X-ray (CXR) images are highly useful in the effective detection of COVID-19, thanks to its availability, cost-effective means, and rapid outcomes. In addition, Artificial Intelligence (AI) techniques such as deep learning (DL) models play a significant role in designing automated diagnostic processes using CXR images. With this motivation, the current study presents a new Quantum Seagull Optimization Algorithm with DL-based COVID-19 diagnosis model, named QSGOA-DL technique. The proposed QSGOA-DL technique intends to detect and classify COVID-19 with the help of CXR images. In this regard, the QSGOA-DL technique involves the design of EfficientNet-B4 as a feature extractor, whereas hyperparameter optimization is carried out with the help of QSGOA technique. Moreover, the classification process is performed by a multilayer extreme learning machine (MELM) model. The novelty of the study lies in the designing of QSGOA for hyperparameter optimization of the EfficientNet-B4 model. An extensive series of simulations was carried out on the benchmark test CXR dataset, and the results were assessed under different aspects. The simulation results demonstrate the promising performance of the proposed QSGOA-DL technique compared to recent approaches.
Influence of race in the estimation of glomerular filtration rate in patients with a high cardiovascular and renal risk

The estimation of glomerular filtration rate (GFR) is usually indirectly calculated from serum creatinine in routine clinical practice. This indirect estimated GFR (eGFR) determination is then used to perform therapeutic decisions. However, serum creatinine may be influenced not only by GFR,but also by muscle mass and diet, therefore age, sex, race [Black/African American (AA) versus other], height and weight have been used to adjust the eGFR [1]. While age, sex or height are biological variables, race/ethnicity certainly has a biological/genetic background but also carries a strong social and psychological burden and is usually a very sensitive topic. As a consequence, many medical centres have removed the race adjustment from eGFR despite the lack of studies assessing the potential clinical impact of this decision [2, 3]. The Disease Collaboration (CKD-EPI) equation to estimate GFR from serum creatinine was developed and validated across 10 studies including people with and without chronic kidney disease (CKD). The race was classified as AA or other as assigned by the study participants or the investigators