Miracle-dz/UniFAR-FTUs huggingface dataset:
Additive, dominance and epistatic variation for yield and its components in linseed (Linum usitatissimum L.)

Three testers, R-552, Garima and their hybrid R-552 x Garima, were crossed to 15 strains/varieties of linseed to estimate the epistatic, additive and dominance components of genetic variance. Modified triple test-cross analysis was done for nine metric traits. Epistasis was evident for all the characters under study except seeds/capsule. The i as well as j and l type epistasis were significant for most of the traits. Additive (D) component was important in all cases except capsules/plant, whereas dominance (H) was significant for seeds/capsule, days to maturity, 1000-seed weight, and oil content. All traits showed partial dominance, and directional element, F was nonsignificant for most of the traits, suggesting ambidirectional nature of dominance.
Online Bayesian Learning for Rate Selection in Millimeter Wave Cognitive Radio Networks

We consider the problem of dynamic rate selection in a cognitive radio network (CRN) over the millimeter wave (mmWave) spectrum. Specifically, we focus on the scenario when the transmit power is time varying as motivated by the following applications: i) an energy harvesting CRN, in which the system solely relies on the harvested energy source, and ii) an underlay CRN, in which a secondary user (SU) restricts its transmission power based on a dynamically changing interference temperature limit (ITL) such that the primary user (PU) remains unharmed. Since the channel quality fluctuates very rapidly in mmWave networks and costly channel state information (CSI) is not that useful, we consider rate adaptation over an mmWave channel as an online stochastic optimization problem, and propose a Thompson Sampling (TS) based Bayesian method. Our method utilizes the unimodality and monotonicity of the throughput with respect to rates and transmit powers and achieves logarithmic in time regret with a leading term that is independent of the number of available rates. Our regret bound holds for any sequence of transmits powers and captures the dependence of the regret on the arrival pattern. We also show via simulations that the performance of the proposed algorithm is superior than the stateof-the-art algorithms, especially when the arrivals are favorable.
Automatic Detection and Monitoring of Diabetic Retinopathy Using Efficient Convolutional Neural Networks and Contrast Limited Adaptive Histogram Equalization

Diabetic retinopathy is a medical condition of the damaged retina that is caused by diabetes and lack of proper monitoring and treatment, which usually leads to blindness. However, diabetic retinopathy monitoring requires an expert ophthalmologist. Recently, automatic monitoring models with acceptable efficiency are suggested as an alternative for expert ophthalmologists. In this paper, a new diabetic retinopathy monitoring model is proposed by using the Contrast Limited Adaptive Histogram Equalization method to improve the image quality and equalize intensities uniformly as the pre-processing step. Then, EfficientNet-B5 architecture is used for the classification step. The efficiency of this network is in uniformly scaling all dimensions of the network. The final model is trained once on a mixture of two datasets, Messidor-2 and IDRiD, and evaluated on the Messidor dataset. The area under the curve (AUC) is enhanced from 0.936, which is the highest value in all recent works, to 0.945. Also, once again, to further evaluate the performance of the model, it is trained on a mixture of two datasets, Messidor-2 and Messidor, and evaluated on the IDRiD dataset. In this case, the AUC is enhanced from 0.796, which is the highest value in all recent works, to 0.932. In comparison to other studies, our proposed model improves the AUC.
Identification and annotation of full-length genes in Atlantic salmon (Salmo salar)

Supervisory Committee Dr. Ben F. Koop (Department of Biology) Supervisor Dr. John Taylor (Department of Biology) Departmental Member Dr. Christopher Upton (Department of Biochemistry and Microbiology) Outside Member Large-scale expressed sequence tags (ESTs) in Atlantic salmon (Salmo salar) are examined to answer questions regarding salmonid transcriptomes. ESTs represent raw and incomplete gene sequences that need to be read, assembled and analyzed with computer software. The goal of this thesis was to develop an automatically curated and publicly accessible set of annotated full-length genes, representing a near-complete transcript set for Salmo salar. In turn, these genes provide the framework for studies in gene expression, conservation, and molecular evolution. The work presented here also touches on the results of a molecular evolution study, as an example of how full-length gene identification can be used to answer biological questions. Previous to this study, a limited number of Atlantic salmon cDNA libraries and ESTs were known. To further the goal of determining complete gene sequences, highly enriched full-length cDNA libraries and full-length libraries were created and sequenced, resulting in the ability to identify a large number of full-length reference genes. Together, all libraries represent a diverse pool of transcriptome sequences for Salmo salar. iv The goal of producing an accurate large-scale full-length gene set on a duplicated genome is not trivial. Complete systems for this objective do not readily exist. EST sequencing, EST assembly, and data storage, are just a few of the initial computational issues that are addressed. Once these issues are resolved, the multi-step workflow of fulllength gene determination is described. The final challenge involving the development of a concise and universally accessible system for visualization is discussed. The resulting computational framework that has been developed is shown to be able to handle the intricacies and the size of a duplicated salmonid genome. It has been largely accepted that Atlantic salmon have undergone a recent genome duplication. Gene paralogs provide one source of evidence for this event. Analysis of paralogs revealed signatures of asymmetric evolution possibly due to relaxation of selective pressure. This thesis provides a complete Bioinformatics analysis pipeline to analyze and to visualize a set of full-length reference genes for Atlantic salmon. Using full-length genes as a framework, the topic of molecular evolution was addressed to show evidence of asymmetrical evolution among gene duplicates. The full-length reference genes, along with ESTs and all putative transcripts, have been made publicly available. These results serve as a valuable genomic resource for next-generation sequencing and for all other salmonid research endeavours.
A Stacking Ensemble Model to Predict Daily Number of Hospital Admissions for Cardiovascular Diseases

With lifestyle and environmental changes, the prevalence of cardiovascular diseases (CVDs) is trending upwards, putting pressure on the limited medical resources. Accurate forecasting of daily counts of hospital admissions (HAs) for CVDs is helpful to optimize medical resources. In this study, we proposed a stacking ensemble model with direct prediction strategy to predict the daily number of CVDs admissions using HAs data, air pollution data, and meteorological data. The sequential forward floating selection method with early stopping was applied for feature selection. Five machine learning models, including linear regression (LR), support vector regression (SVR), extreme gradient boosting (XGBoost), random forest (RF), and gradient boosting decision tree (GBDT), were utilized as base learners to construct the stacking model. We compared the performance of the proposed stacking model with the five base learners in three datasets. The experimental results indicated that our model performed best in three datasets under four evaluation criteria, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). Particularly, in the CVDs dataset, the MAPE is 15.103 for LR, 11.862 for SVR, 10.571 for XGBoost, 10.378 for GBDT, 10.333 for RF, and 9.679 for the stacking model. Compared with the best base learner RF, the MAPE, RMSE, and MAE of the stacking model decreased by 6.3%, 7.4%, and 6.3%, respectively, and the R2 improved by 1.7%. It is evident that the proposed stacking model can effectively forecast the daily number of hospitalizations for CVDs and provide decision support for hospital managers.
Pilot study on music-heart entrainment in a pianist during a live performance

Entrainment between music features and heart rhythms have been reported but, to date, evidence in support of music-heart synchronization are still inconsistent. We studied the possible music-heart entrainment in a skilled pianist during a live performance before an audience. We recorded ECG before and during the concert. We derived the beat-to-beat RR time series and analyzed heart rate variability in the time domain and with non linear analysis, to evaluate the autonomic changes associated with 4 different music pieces. Results indicated an autonomic modulation specific for each piece and the decrease and increase of parasympathetic and sympathetic tone across the whole session. Also, for each music piece, analysis of correlation between the music envelope and the RR series revealed a negative correlation which could be the expression of the entrainment of music on heart rhythm.
Seed conservation for preservation of genetic variability in Salvia splendens

Salvia is an important ornamental plant, grown in flower beds or as border plant in gardens. Its bright coloured flowers are attractive and bloom over a long period. These are primarily raised throagh the seeds. Seed contains valuable genetic material and form a major component of genetic conservation owing to simpler handling, inexpen-sive means of storage and genetically stables on long-term conservation. Salvia seeds are small and remain viable for a shorter period under ambient conditions. Seeds of Cv. Flare with 8.0 percent moisture were packed in moisture pervious, semi pervious and impervious containers and stored at low and sub-zero temperatures for 10 years. None of seeds germinated after a year's storage under ambient conditions. About 70 percent of seeds germinated when stored at 5 and-20°C after 5 years. Further, it was reduced to 22 and 66 percent respectively after 10 years of storage. Seed vigour was also preserved with the storage. Further, seedlings did not exhibit any variations for morpho-logical characters. It is advantageous to store dry seeds in laminated aluminium foil pouches at -20°C for effective conservation of seed germplasm
Population characteristics of the abalone Haliotis roei on intertidal platforms in the Perth metropolitan area

Abstract Basic population characteristics of the commercial abalone species Haliotis roei are compared on a heavily fished intertidal platform and a platform with no fishing pressure. Seasonal and annual variations in population density were large on both platforms, though densities were lower on the fished platform (Trigg) than the unfished area (Waterman). Most abalone at Waterman were adults of 2+ years (>60 mm), while few animals of this size occurred at Trigg. There were not sufficient adults at Trigg for reproduction on the platform to replenish the population, and it is postulated that replenishment comes from larvae originating from adjacent platforms. A subtidal rock with an unfished population of H. roei recovered at a rate of only about 10% per year, suggesting that heavily overfished populations would recover slowly, if at all.
Characteristics of AC PDs on epoxy insulation surface excited by different impulse voltages in SF6 gas

In this paper the behavior of partial discharges (PDs) on epoxy insulation under AC and impulse superimposed voltages are experimentally investigated in SF6 gas. The lightning impulse (LI) and the switching impulse (SI) voltages with different polarity are superimposed on different phases of the AC voltage. PDs are measured by three sensors, a 50 Ω measurement impedance, an ultra-high frequency sensor and a photomultiplier tube. The max PD amplitude, PD pulse number and PD duration under AC voltage after an impulse voltage are summarized and analyzed. The effect of the impulse superposition phase, the impulse type and the impulse polarity on the characteristics of AC PDs are discussed. Results show that after a positive impulse voltage was applied on the positive semi-wave of AC voltage (0 to 180°), PDs in the negative half cycle of the AC voltage can be remarkably excited. A negative impulse voltage was applied on the negative semi-wave (180 to 360°), AC PDs can be initiated in the positive half cycle of AC voltage. PDs excited by a LI voltage is severe than excited by a SI. PDs excited by a positive impulse is intense than excited by a negative impulse.
Energy-Efficient Access-Point Sleep-Mode Techniques for Cell-Free mmWave Massive MIMO Networks With Non-Uniform Spatial Traffic Density

Cell-free massive multiple-input multiple-output (MIMO) is a novel beyond 5G (B5G) and 6G paradigm that, through the use of a common central processing unit (CPU), coordinates a large number of distributed access points (APs) to coherently serve mobile stations (MSs) on the same time/frequency resource. By exploiting the characteristics of new less-congested millimeter wave (mmWave) frequency bands, these networks can improve the overall system spectral and energy efficiencies by using low-complexity hybrid precoders/decoders. For this purpose, the system must be correctly dimensioned to provide the required quality of service (QoS) to MSs under different traffic load conditions. However, only heavy traffic load conditions are usually taken into account when analysing these networks and, thus, many APs might be underutilized during low traffic load periods, leading to an inefficient use of resources and waste of energy. Aiming at the implementation of energy-efficient AP switch on/off strategies, several approaches have been proposed in the literature that only consider rather unrealistic uniform spatial traffic distribution in the whole coverage area. Unlike prior works, this paper proposes energy efficient AP sleep-mode techniques for cell-free mmWave massive MIMO networks that are able to capture the inhomogeneous nature of spatial traffic distribution in realistic wireless networks. The proposed framework considers, analyzes and compares different AP switch ON-OFF (ASO) strategies that, based on the use of goodness-of-fit (GoF) tests, are specifically designed to dynamically turn on/off APs to adapt to both the number and the statistical distribution of MSs in the network. Numerical results show that the use of properly designed GoF-based ASO strategies under a non-uniform spatial traffic distribution can serve to considerably improve the achievable energy efficiency.
Characterization of impaired repolarization by quantification of the QT delay in response to heart rate changes from stress test recordings

Increased spatio-temporal heterogeneity in the repolarization of the ventricles is related to cardiac instabilities. Slowed adaptation of the QT interval to sudden abrupt changes in heart rate (HR), measured with the time constant of a first-order-like response, has been identified as a biomarker for arrhythmic risk. Since abrupt HR changes are difficult to induce in patients, an exercise stress test, where ramp-like HR variations are observed, is considered. The time lag between the QT response and the expected HR-dependent QT time series is characterized by a time constant, hypothesized to have the same value as in the case of the step response. The delay is estimated by minimizing the Mean Square Error on the stress and recovery phases, in 14 high-risk patients of the FINCAVAS database, reaching average values of 26.3 and 40.6 seconds, respectively, comparable with the time lags measured in response to sudden step-like HR changes.
Automatically and Adaptively Identifying Severe Alerts for Online Service Systems

In large-scale online service system, to enhance the quality of services, engineers need to collect various monitoring data and write many rules to trigger alerts. However, the number of alerts is way more than what on-call engineers can properly investigate. Thus, in practice, alerts are classified into several priority levels using manual rules, and on-call engineers primarily focus on handling the alerts with the highest priority level (i.e., severe alerts). Unfortunately, due to the complex and dynamic nature of the online services, this rule-based approach results in missed severe alerts or wasted troubleshooting time on non-severe alerts. In this paper, we propose AlertRank, an automatic and adaptive framework for identifying severe alerts. Specifically, AlertRank extracts a set of powerful and interpretable features (textual and temporal alert features, univariate and multivariate anomaly features for monitoring metrics), adopts XGBoost ranking algorithm to identify the severe alerts out of all incoming alerts, and uses novel methods to obtain labels for both training and testing. Experiments on the datasets from a top global commercial bank demonstrate that AlertRank is effective and achieves the F1-score of 0.89 on average, outperforming all baselines. The feedback from practice shows AlertRank can significantly save the manual efforts for on-call engineers.
Color Spaces and Regions of Interest in Camera Based Heart Rate Estimation

Camera-based heart rate (HR) estimation is used with different color spaces and regions of interest (ROIs). In this work, seven commonly used ROIs were determined via facial landmarks focusing on forehead, cheeks and glabella, and one ROI was derived by level set segmentation. For each ROI, 25 signals of eight color spaces were derived and HR estimation accuracy was determined. Both color channel and ROI showed significant effects $(p < 0.001)$ on the accuracy of HR estimation. Glabella or forehead ROI combined with HSV-H or NTSC-Q color channel (accuracy: up to 73.3 %) as well as level set ROI with NTSC-Q color channel (accuracy: 68.7%) performed best.
Variable-Phase All-Pass Network Synthesis and Its Application to a 14–54 GHz Multiband Continuous-Tune Phase Shifter in Silicon

This article presents a novel synthesis procedure to implement variable-phase all-pass networks (VP-APNs). The synthesis procedure is based on linear-phase all-pass transfer functions, enabling implementation at millimeter waves. Using the proposed synthesis, VP-APNs with analog and digital control are implemented for the first time in silicon. Using 0.25- $\mu \text{m}$ BiCMOS, the VP-APNs are manufactured and measured, validating the synthesis procedure. Finally, the validated VP-APNs are combined to realize a phase shifter. By combining the analog and digitally controlled networks, we obtain a continuous-tune phase shifter with multiband capabilities, successfully covering several bands from 14 to 54 GHz. This includes Ku-, K-, Ka-, and V-band, as well as both 5G bands around 28 and 39 GHz.
Performance of Hybrid PON Architecture using On-Off Keying and Differential Quadrature Phase Shift Keying

With an increase in network traffic, optical networks find their use in communication of high rate data systems and are used in the access part of the network. The main technology used here is the Hybrid Passive Optical Network (Hybrid PON) which provides longer reach and a higher data rate. Wavelength Division Multiplexing (WDM) PON can make the transmission through optical fiber possible for a long distance at a high data rate. A Hybrid PON utilizes the advantages of WDM-PON as well as share the same wavelength with a number of users. This research basically aims at improving the data rate and in increasing the reach of such a network by using different modulation techniques and amplifiers. Normally On-Off Keying (OOK) is used in such an access network scenario. We have analyzed the effect of the Differential Quadrature Phase Shift Keying (DQPSK) line technique in comparison to the usual On-Off Keying (OOK) technique with and without Erbium-Doped Fiber Amplifier (EDFA).
Frequency-Dependent Effects of Exhalatory-Gated Transcutaneous Vagus Nerve Stimulation on Cardiac Autonomic Regulation in Hypertension

The objective of this study was to determine potential effects of respiratory-gated auricular vagal afferent nerve stimulation (RAVANS) on cardiovagal activity in hypertensive patients. Twenty hypertensive subjects $(54.55\pm 6.23$ years; 12 females) underwent five randomized sessions of RAVANS at frequencies of 0, 2, 10, 25, and 100 Hz. Continuous electrocardiogram (ECG) and pulse rate signals were collected during 10-minute baseline, 30-minute stimulation, and 10-minute recovery periods using a Grass LP511 AC amplifier and piezo device. LabChart was used to acquire ECG and pulse signals and to process heart rate variability (HRV) indices. A significant increase in high frequency (HF) power (%) was observed during the RAVANS-100 Hz session from baseline to recovery $l\mathrm{n}=0.039$) when compared to sham, adjusting for sex and baseline values. HRV evaluation for other frequencies did not yield significant results. These results suggest that RAVANS has a frequency-dependent effect on the modulation of cardiovagal activity (HF-HRV) in hypertension.
Entropy characteristics of heart rate wavelet multiscale components in epileptic children before and after seizures

In this work, we analyze the information content of the multiple time scale components of heart rate variability (HRV) in children with focal epilepsy. HRV components are extracted from 30 pediatric patients, monitored 10 min and 10 s before and after focal epileptic seizures, using wavelet multiscale decomposition (with 5, 15, 30, 60, 120, 180 s time scale), and then characterized computing Entropy (E), permutation entropy (PE), conditional entropy (CE) and information storage (IS). Moving from preictal to postictal windows, we find statistically significant differences in the CE and IS values of HRV components at short time scales, which reflect autonomic imbalance and appear as potential candidates of descriptive features for HRV monitoring in epilepsy.
The effect of microclimatic parameters and the birth date on the number of Mahogany mink kits born and reared

Abstract The objective of the study was to determine the number of Mahogany kits born and reared under changing microclimatic conditions on the farm. We found a significant influence of air temperature and relative humidity on the reproduction of Mahogany minks. Due to low temperature and high relative humidity during that period (20–25 April), the percentage of dead kits in a litter was the highest (13.7%), and the percentage of kits reared was the lowest at 76.2%, as compared to 87.8–94.2% in other periods. We established that the later a birth occurred, the lower the number of kits in the litter. We observed that as temperature was increased and relative humidity was decreased, the percentage of dead kits in a litter became lower. The negative effect of high relative humidity on the reproduction results was confirmed by negative values of the correlation between humidity and the number of kits born and reared.