Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Irrigation System

Appropriate soil water level is a necessary pre-requisite for optimum plant growth. Also, water being an essential element for life sustenance, there is the necessity to avoid its undue usage. Irrigation is a dominant consumer of water. This calls for the need to regulate water supply for irrigation purposes. Fields should neither be over-irrigated nor under-irrigated. Over time, systems have been implemented towards realizing this objective of which automated processes are the most popular as they allow information to be collected at high frequency with less labor requirements. Bulk of the existing systems employ micro-processor based systems. These systems offer several technological advantages but are unaffordable, bulky, difficult to maintain and less accepted by the technologically unskilled workers in the rural scenario.
Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review

Learning styles, learners’ preferred ways to learn, can be applied to design personalized learning courses for the individual learner. One of those applications is the recommender system. This study ran a systematic literature review on the recommender system utilizing learning styles from two dependable academic libraries, IEEE Xplore and ScienceDirect, which included six reviewed topics; research objective, research methodology, educational recommendation, learning styles theory, learning style identification, and recommendation algorithm. Finally, the obtained information was examined and summarized in order to develop a unique strategy for leveraging the utilization of learning style theory for a recommender system to improve learning efficiency.
Experiments on Collisional Grain Charging of Micron-sized Preplanetary Dust

Collisions between micron-sized grains and larger objects with velocities up to several 10 m s-1 are believed to be an important physical process in the solar nebula with respect to the preplanetary dust aggregation. Former collision experiments demonstrated that grain-target collisions of micron-sized particles were marked by obvious electrostatic effects. Among those were the observation of particles which, after mechanical rebound, returned to the target and finally stuck, and of particle deposition on targets influenced by the presence of conducting materials. Therefore, it is clear that the dust aggregation process cannot adequately be described without investigating collisional grain charging experimentally. We present experiments on the collisional grain charging of micron-sized grains impacting target surfaces which, in contrast to former work, consist both of nonconducting material and the experiments involving smaller particles than before. Collisional grain charging is stronger than previously discussed with respect to preplanetary grains and should be considered concerning the preplanetary dust aggregation, the formation of lightning in the solar nebula, and a coupling of charged grains to magnetic fields.
SYMMETRIC CORONAL JETS: A RECONNECTION-CONTROLLED STUDY

Current models and observations imply that reconnection is a key mechanism for destabilization and initiation of coronal jets. We evolve a system described by the theoretical symmetric jet formation model using two different numerical codes with the goal of studying the role of reconnection in this system. One of the codes is the Eulerian adaptive mesh code ARMS, which simulates magnetic reconnection through numerical diffusion. The quasi-Lagrangian FLUX code, on the other hand, is ideal and able to evolve the system without reconnection. The ideal nature of FLUX allows us to provide a control case of evolution without reconnection. We find that during the initial symmetric and ideal phase of evolution, both codes produce very similar morphologies and energy growth. The symmetry is then broken by a kink-like motion of the axis of rotation, after which the two systems diverge. In ARMS, current sheets formed and reconnection rapidly released the stored magnetic energy. In FLUX, the closed field remained approximately constant in height while expanding in width and did not release any magnetic energy. We find that the symmetry threshold is an ideal property of the system, but the lack of energy release implies that the observed kink is not an instability. Because of the confined nature of the FLUX system, we conclude that reconnection is indeed necessary for jet formation in symmetric jet models in a uniform coronal background field.
New Wolf–Rayet stars in the Large Magellanic Cloud

On a detecte six nouvelles etoiles de type Wolf Rayet dans le Grand Nuage de Magellan. Deux sont de type WN, trois de type WC. Cinq sur les six ont ete confirmes spectralement. Deux des etoiles WC sont proches de 30 Doraduset d'environ 3 mag plus faibles que toute autre etoile WC dans le GNM
Theory & Methods: Bayesian Measures of the Minimum Detectable Concentration of an Immunoassay

The minimum detectable concentration (MDC) is one of the most important properties of an assay. It is a statement about the smallest physical quantity an assay can reliably measure, and is used in assay design and quality control assessments. A plethora of measures of the MDC have been reported in a widely scattered literature. Many of these were developed at a time when accuracy and relevance had to be sacrificed for computational feasibility. This paper identifies limitations of existing measures and demonstrates how Bayesian inference may be used to overcome these limitations. Several new measures of the MDC are developed. These are conceptually simpler than existing measures, and are free of analytical approximations. The recent advances in Bayesian computation make them efficient to evaluate. A procedure developed in this paper measures the difference in the quality of two assays and shows that the new Bayesian measures perform better than existing measures.
Robust Homography Estimation Based on Nonlinear Least Squares Optimization

The homography between image pairs is normally estimated by minimizing a suitable cost function given 2D keypoint correspondences. The correspondences are typically established using descriptor distance of keypoints. However, the correspondences are often incorrect due to ambiguous descriptors which can introduce errors into following homography computing step. There have been numerous attempts to filter out these erroneous correspondences, but it is unlikely to always achieve perfect matching. To deal with this problem, we propose a nonlinear least squares optimization approach to compute homography such that false matches have no or little effect on computed homography. Unlike normal homography computation algorithms, our method formulates not only the keypoints’ geometric relationship but also their descriptor similarity into cost function. Moreover, the cost function is parametrized in such a way that incorrect correspondences can be simultaneously identified while the homography is computed. Experiments show that the proposed approach can perform well even with the presence of a large number of outliers.
Meropenem Incorporated ZnO Nanoflakes as Nano Antibiotics: Efficient Antimicrobial Activity against Metallo β-lactamase Producing Clinical Isolates

The number of fatalities caused by multidrug-resistant (MDR) bacteria is over 700,000 annually due to widespread antibiotic usage. So, there is a need of new antibiotics, materials that work like antibiotics, or combinations of antibiotics with nanomaterials that could help in treating the infections which is caused by MDR bacteria. The present study describes the synthesis of ZnO nanoflakes using a co-precipitation method. The ZnO nanoflakes and ZnO nanoflakes combinations with carbapenem antibiotics were tested against carbapenem-resistant (CR) clinical isolates. The SEM analysis showed surface morphology of the synthesized nanoflakes-like structure of ZnO. All 67 CR isolates were tested and showed inhibitory action at varying concentrations of ZnO nanoflakes. ZnO nanoflakes were found to have an inhibitory effect against Escherichia coli and Klebsiella pneumoniae at lowest concentration of 1.25 mg.ml-1 of ZnO NPs with average zone size (mean ±SD) 1.91±2.94 mm and 2.00±4.14 mm and the average zone size of ZnO nanoflakes against Acinetobacter baumanni and Pseudomonas aeruginosa was 9.89±0.76 mm and 10.17±0.39 mm at 2.5 mg.ml-1 concentration. The combined action of ZnO nanoflakes with Meropenem 10 mcg demonstrated synergetic activity against CR pathogens, with an average zone of inhibition measuring 15.2 mm in diameter. ZnO nanoflakes illustrated considerable antibacterial activity against MBL-producing gram-negative clinical isolates at the lowest concentration. Chemically synthesized ZnO nanoflakes may offer a superior future expectation as a nano-antibiotic to treat the infection caused by CRE bacteria.
First report of citrus virus A in Australia

Citrus virus A (CiVA) was detected for the first time in Australia in a living pathogen collection. Buds were originally collected from a Washington navel field tree prior to 1970 and graft-inoculated onto a Symons sweet orange indicator plant. The virus was detected using conventional and quantitative reverse transcription polymerase chain reactions and high-throughput sequencing. This Australian variant, known as CL223, shares 96.3% (RNA1) and 96.7% (RNA2) nucleotide identity with isolates of CiVA from South Africa and China, respectively. Foliar symptoms of leaf flecking and oak leaf patterns, consistent with detections of CiVA in other regions, were observed on the foliage of the original accession and inoculated indicator plants. Subsequent surveys of an Australian citrus variety collection detected a different CiVA sequence variant in two accessions of Pera sweet orange; this variant had 97% similarity to CL223, the other Australian variant.
Aurora B SUMOylation Is Restricted to Centromeres in Early Mitosis and Requires RANBP2

Conjugation with the small ubiquitin-like modifier (SUMO) modulates protein interactions and localisation. The kinase Aurora B, a key regulator of mitosis, was previously identified as a SUMOylation target in vitro and in assays with overexpressed components. However, where and when this modification genuinely occurs in human cells was not ascertained. Here, we have developed intramolecular Proximity Ligation Assays (PLA) to visualise SUMO-conjugated Aurora B in human cells in situ. We visualised Aurora B-SUMO products at centromeres in prometaphase and metaphase, which declined from anaphase onwards and became virtually undetectable at cytokinesis. In the mitotic window in which Aurora B/SUMO products are abundant, Aurora B co-localised and interacted with NUP358/RANBP2, a nucleoporin with SUMO ligase and SUMO-stabilising activity. Indeed, in addition to the requirement for the previously identified PIAS3 SUMO ligase, we found that NUP358/RANBP2 is also implicated in Aurora B-SUMO PLA product formation and centromere localisation. In summary, SUMOylation marks a distinctive window of Aurora B functions at centromeres in prometaphase and metaphase while being dispensable for functions exerted in cytokinesis, and RANBP2 contributes to this control, adding a novel layer to modulation of Aurora B functions during mitosis.
HYPERCYCLIC OPERATORS ON NON-NORMABLE FRECHET SPACES

Abstract Every infinite dimensional separable non-normable Frechet space admits a continuous hypercyclic operator. A large class of separable countable inductive limits of Banach spaces with the same property is given, but an example of a separable complete inductive limit of Banach spaces which admits no hypercyclic operator is provided. It is also proved that no compact operator on a locally convex space is hypercyclic.
Schizo-Net: A novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning on Electroencephalogram-Based Brain Connectivity Indices

Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents <inline-formula> <tex-math notation="LaTeX">$\textit {Schizo-Net}$ </tex-math></inline-formula>, a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain connectivity indices are estimated from the windowed EEG activity, and six different deep learning architectures (with varying neurons and hidden layers) are trained. The present study is the <inline-formula> <tex-math notation="LaTeX">$\textit {first}$ </tex-math></inline-formula> which considers a large number of brain connectivity indices, especially for SCZ. A detailed study was also performed that identifies SCZ-related changes occurring in brain connectivity, and the vital significance of BCI is drawn in this regard to identify the biomarkers of the disease. <inline-formula> <tex-math notation="LaTeX">$\textit {Schizo-Net}$ </tex-math></inline-formula> surpasses current models and achieves 99.84% accuracy. An optimum deep learning architecture selection is also performed for improved classification. The study also establishes that Late fusion technique outperforms single architecture-based prediction in diagnosing SCZ.
Covering Set-Based Inner-Cluster Data Aggregation Scheme for Wireless Sensor Networks

For reducing the communication overhead of data aggregation, authors proposed an covering set-based inner-cluster data aggregation scheme for wireless sensor networks. The network is clustered upon deployment; nodes achieve the inner-cluster neighbors’ identifiers by information exchanging and transmit the list of inner-cluster neighbors to the cluster head to help the cluster head deducing the inner-cluster covering set. Each node selects a neighbor form inner-cluster covering set as reference point and keeps silent if it has the same reading with reference point. Simulation shows that the proposed scheme lowers the communication overhead of data aggregation effectively.
Acoustic Monitoring of Black-Tufted Marmosets in a Tropical Forest Disturbed by Mining Noise

Simple Summary Communication is one way that animals use to obtain and defend resources, escape predators and attract sexual partners. However, this process can be disrupted by anthropogenic noise, which often differs from natural sounds in frequency, duration and intensity. This study aimed to understand whether, and how, calls emitted by black-tufted marmosets (Callithrix penicillata) are affected by mining noise. We compared ambient noise and the acoustic parameters of the contact calls of these animals in two study areas, one near and one far from the Brucutu Mine, Minas Gerais, Brazil. We found background noise to be higher in the area near the mine, and marmoset vocalizations more frequent, compared to the far area. Calls emitted in the near area also differed in spectral parameters from the far area, which suggests an effort by the animals to adapt their vocal activity to a noisier environment. Our results indicate that mining noise may affect the acoustic communication of black-tufted marmosets. These results may be taken as a starting point for establishing public policies to promote preventive and/or mitigative measures to protect wildlife around sites of mining activity. Moreover, measures to regulate any noisy activities in relation to wild animals are pressing since these are lacking in Brazil. Abstract All habitats have noise, but anthropogenic sounds often differ from natural sounds in terms of frequency, duration and intensity, and therefore may disrupt animal vocal communication. This study aimed to investigate whether vocalizations emitted by black-tufted marmosets (Callithrix penicillata) were affected by the noise produced by mining activity. Through passive acoustic monitoring, we compared the noise levels and acoustic parameters of the contact calls of marmosets living in two study areas (with two sampling points within each area)—one near and one far from an opencast mine in Brazil. The near area had higher anthropogenic background noise levels and the marmosets showed greater calling activity compared to the far area. Calls in the near area had significantly lower minimum, maximum and peak frequencies and higher average power density and bandwidth than those in the far area. Our results indicate that the mining noise affected marmoset vocal communication and may be causing the animals to adjust their acoustic communication patterns to increase the efficiency of signal propagation. Given that vocalizations are an important part of social interactions in this species, concerns arise about the potential negative impact of mining noise on marmosets exposed to this human activity.
A numerical model for hydrothermal transport in unsaturated freezing soils considering thermodynamics equilibrium

The analysis of frost heave in unsaturated subgrade soils should consider the coupled movement of liquid water, vapor, and heat, accompanied by phase transition of water, vapor, and ice. In this paper, the equilibrium relationship of the three phases of water in soils was comprehensively considered, and the water head and vapor density were determined under frozen and unfrozen conditions from the perspective of thermodynamics. Based on that, the governing equations of mass and energy conservation were then derived and a new transient finite element model was developed, considering the behavior of the phase change and coupled hydrothermal transport under frozen as well as unfrozen conditions. Since the discontinuities between the frozen and the unfrozen zones may bring difficulties to the numerical solution, two kinds of smoothing techniques were proposed to solve the discontinuities at the phase transition interface, which guaranteed robust convergence and enhanced computational efficiency. The model proposed was verified by comparing with some available test results and applied to analyze the frost heave process of unsaturated subgrade under impermeable road pavements, demonstrating the model's accuracy and applicative prospect. It is revealed that the movement of liquid water and vapor in the frozen zones may still exist, and its mechanism and performance are different from that in unfrozen zones. The significance of vapor migration on the subgrade frost heave is also emphasized.
Joint target-detection and tracking smoothers

A multi-object Bayes filter analogous to the single-object Bayes filter can be derived using Finite Set Statistics for the estimation of an unknown and randomly varying number of target states from random sets of observations. The joint target-detection and tracking (JoTT) filter is a truncated version of the multi-object Bayes filter for the single target detection and tracking problem. Despite the success of Finite-Set Statistics for multi-object Bayesian filtering, the problem of multi-object smoothing with Finite Set Statistics has yet to be addressed. I propose multi-object Bayes versions of the forward-backward and two-filter smoothers and derive optimal non-linear forward-backward and two-filter smoothers for jointly detecting, estimating and tracking a single target in cluttered environments. I also derive optimal Probability Hypothesis Density (PHD) smoothers, restricted to a maximum of one target and show that these are equivalent to their Bayes filter counterparts.
Phase transitions in Yang-Mills theories and their gravity duals

This thesis is a study of the thermal phase structure of systems that admit dual gauge theory and string theory descriptions. In a pair of examples, we explore the connection between perturbative Yang-Mills and gravitational thermodynamics which arises from the fact that these descriptions probe different corners of a single phase diagram. The structure that emerges from a detailed study of these isolated regions generally suggests a natural conjecture how they may be connected to one another within the full phase diagram. This permits the identification of interesting phenomena in the gauge and gravity regimes under a continuous change in parameters. We begin by studying the AdS5/CFT4 system which, when the supergravity description is valid, exhibits a first order Hawking-Page phase transition as a function of temperature from a thermal gas of gravitons to a large black hole. In the perturbative Yang-Mills regime, we find that the free theory exhibits a weakly first order deconfinement transition whose precise nature at small nonzero coupling depends on the result of a nontrivial perturbative computation. It is conjectured that this deconfinement transition is continuously connected in the full phase diagram to the Hawking-Page transition at strong coupling, with the confined phase identified with the graviton gas and the deconfined phase identified with the black hole. We then turn to the study of Gregory-Laflamme (GL) black hole/black string transitions in supergravity and their realization in a setup that admits a dual description
Stress Analysis in Viscoelastic Materials

The problems of stress analysis for linearly viscoelastic materials are considered. This is the simplest group of materials which exhibit the general stress‐strain characteristics found in polymers and plastics. Three basic aspects are considered: measurement of material properties, determination from these of the operator equations between stress and strain or equivalently of the viscoelastic model, and use of this in the theoretical analysis of stress distributions. Quasi‐static analysis, in which inertia forces are negligible, is treated quite generally. The wave problems which arise when inertia effects are included are restricted to one‐dimensional space variations. A series of typical solutions of these types is discussed.