Unpredictable Variations Research Articles

FPGA Implementation of Modified Reconfigurable Adaptive Gain Scheduling Controller

This article aims to put forward a modified type of adaptive gain scheduling that will be able to deal with the immeasurable and unpredictable variations of system variables by adapting its value at each time instance to follow any change in the input and overcome any disturbance applied to the system without the need to predetermine gains values. In addition, the inverse neural controller will precede the gain scheduling to eliminate the need for complex system linear zing and parameter estimation. Therefore, the problems of needing complex mathematics for system linearization and gains calculations have been solved. The performance of the presented controller was tested by comparing the step response of a DC-motor controlled via the proposed technique and the response of that motor when controlled by the inverse neural controller and PID controller. MATLAB/Simulink has been used for making the simulations and obtaining the results. In addition, the FPGA implementation of the proposed controller has been presented. The results showed a remarkable improvement in the transient response of the system for all of the rising time, delay time, settling time, peak overshoot, and steady-state error.

PAPS: A Serverless Platform for Edge Computing Infrastructures

Edge computing infrastructures are often employed to run applications with low latency requirements. Users can exploits nodes that are close to their physical positions so that the delay of sending computations and data to the Cloud is mitigated. Since users frequently change their locations, and the resources available in the Edge are limited, the management of these infrastructures poses new, difficult challenges. This paper presents PAPS (Partitioning, Allocation, Placement, and Scaling), a framework for the efficient, automated and scalable management of large-scale Edge topologies. PAPS acts as a serveless platform for the Edge. Service providers can upload applications as compositions of lightweight and stateless functions along with latency constraints. At runtime, PAPS manages these applications by executing them in containers, it changes their placement in the Edge topology according to the geographical distribution of the workload, and efficiently allocates resources according to their needs. This paper also presents the architecture of a PAPS prototype built atop Kubernetes and OpenFaaS. The assessment shows both the feasibility of the approach and the ability of efficiently managing hundreds of serverless concurrent functions and of dealing with intense and unpredictable workload variations.

Preclinical Testing of Radiopharmaceuticals for the Detection and Characterization of Osteomyelitis: Experiences from a Porcine Model.

The development of new and better radioactive tracers capable of detecting and characterizing osteomyelitis is an ongoing process, mainly because available tracers lack selectivity towards osteomyelitis. An integrated part of developing new tracers is the performance of in vivo tests using appropriate animal models. The available animal models for osteomyelitis are also far from ideal. Therefore, developing improved animal osteomyelitis models is as important as developing new radioactive tracers. We recently published a review on radioactive tracers. In this review, we only present and discuss osteomyelitis models. Three ethical aspects (3R) are essential when exposing experimental animals to infections. Thus, we should perform experiments in vitro rather than in vivo (Replacement), use as few animals as possible (Reduction), and impose as little pain on the animal as possible (Refinement). The gain for humans should by far exceed the disadvantages for the individual experimental animal. To this end, the translational value of animal experiments is crucial. We therefore need a robust and well-characterized animal model to evaluate new osteomyelitis tracers to be sure that unpredicted variation in the animal model does not lead to a misinterpretation of the tracer behavior. In this review, we focus on how the development of radioactive tracers relies heavily on the selection of a reliable animal model, and we base the discussions on our own experience with a porcine model.

Cold Stress in Wheat: Plant Acclimation Responses and Management Strategies.

Unpredicted variability in temperature is associated with frequent extreme low-temperature events. Wheat is a leading crop in fulfilling global food requirements. Climate-driven temperature extremes influence the vegetative and reproductive growth of wheat, followed by a decrease in yield. This review describes how low temperature induces a series of modifications in the morphophysiological, biochemical, and molecular makeup of wheat and how it is perceived. To cope with these modifications, crop plants turn on their cold-tolerance mechanisms, characterized by accumulating soluble carbohydrates, signaling molecules, and cold tolerance gene expressions. The review also discusses the integrated management approaches to enhance the performance of wheat plants against cold stress. In this review, we propose strategies for improving the adaptive capacity of wheat besides alleviating risks of cold anticipated with climate change.

Assessment of Epigenetic and Phenotypic Variation in Populus nigra Regenerated via Sequential Regeneration.

Somatic variation has been demonstrated in tissue culture regenerated plants of many species. In the genus Populus, phenotypic variation caused by changes in 5-methylcytosine within the plant genome have been reported. To date, the phenotypic and epigenetic stability of plants regenerated from sequential regeneration has not been tested in trees. In this study, we detected DNA methylation of CCGG sites in regenerated plants of five generations in Populus nigra using methylation-sensitive amplified polymorphisms, and evaluated their growth performance and physiological traits. About 10.86–26.80% of CCGG sites in the regenerated plant genome were demethylated and 5.50–8.45% were methylated, resulting in significantly lower DNA methylation levels among all regenerated plants than among donor plants. We detected a significant difference in methylation levels between first regeneration regenerated plants (G1) and those of the other four generations (G2–G5); there were no significant differences among the four later generations. Therefore, the dramatic decrease in DNA methylation levels occurred only in the first and second poplar regenerations; levels then stabilized later in the regeneration process, indicating that two regeneration events were sufficient to change the methylation statuses of almost all CCGG sites sensitive to regeneration. Differences in growth and physiological traits were observed between regenerated plants and donor plants, but were significant only among plants of certain generations. Significant correlations were detected between methylation level and transpiration rate, net photosynthetic rate, peroxidase activity, and instant water utilization efficiency, indicating the involvement of epigenetic regulation in this unpredictable phenotypic variation.

Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles.

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

A Baltic Dry Index Prediction using Deep Learning Models

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model’s predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.

Effect of expansion media and fibronectin coating on growth and chondrogenic differentiation of human bone marrow-derived mesenchymal stromal cells

In the field of regenerative medicine, considerable advances have been made from the technological and biological point of view. However, there are still large gaps to be filled regarding translation and application of mesenchymal stromal cell (MSC)-based therapies into clinical practice. Indeed, variables such as cell type, unpredictable donor variation, and expansion/differentiation methods lead to inconsistencies. Most protocols use bovine serum (FBS) derivatives during MSC expansion. However, the xenogeneic risks associated with FBS limits the use of MSC-based products in clinical practice. Herein we compare a chemically defined, xenogeneic-free commercial growth medium with a conventional medium containing 10% FBS and 5 ng/ml FGF2. Furthermore, the effect of a fibronectin-coated growth surface was investigated. The effect of the different culture conditions on chondrogenic commitment was assessed by analyzing matrix deposition and gene expression of common chondrogenic markers. Chondrogenic differentiation potential was similar between the FBS-containing αMEM and the chemically defined medium with fibronectin coating. On the contrary, the use of fibronectin coating with FBS-containing medium appeared to reduce the differentiation potential of MSCs. Moreover, cells that were poorly responsive to in vitro chondrogenic stimuli were shown to improve their differentiation potential after expansion in a TGF-β1 containing medium. In conclusion, the use of a xenogeneic-free medium provides a suitable alternative for human bone marrow MSC expansion, due the capability to maintain cell characteristic and potency. To further improve chondrogenic potential of BMSCs, priming the cells with TGF-β1 during expansion is a promising strategy.

How Stable Are Transport-Related Attitudes over Time?

The utility of attitudes in travel demand forecasting requires predictability. Any attempt to simulate future attitudes, as is done in such models, would be impractical if they were subject to substantial unpredictable variation over time. We investigate the stability of attitudes using waves of the COVID Future survey answered 3.5–11 months apart. Attitudinal statements have moderate stability while factor-analyzed attitudes demonstrate moderately high stability. This stability is consistent across demographic groups. Attitudes about COVID-19 are particularly stable, while those about remote work and communication are more unstable. We conclude that attitudes display enough stability over 6 months to be useful.

Polarimetric Properties of Blazars Caught by the WEBT

Active galactic nuclei come in many varieties. A minority of them are radio-loud, and exhibit two opposite prominent plasma jets extending from the proximity of the supermassive black hole up to megaparsec distances. When one of the relativistic jets is oriented closely to the line of sight, its emission is Doppler beamed and these objects show extreme variability properties at all wavelengths. These are called “blazars”. The unpredictable blazar variability, occurring on a continuous range of time-scales, from minutes to years, is most effectively investigated in a multi-wavelength context. Ground-based and space observations together contribute to give us a comprehensive picture of the blazar emission properties from the radio to the γ-ray band. Moreover, in recent years, a lot of effort has been devoted to the observation and analysis of the blazar polarimetric radio and optical behaviour, showing strong variability of both the polarisation degree and angle. The Whole Earth Blazar Telescope (WEBT) Collaboration, involving many tens of astronomers all around the globe, has been monitoring several blazars since 1997. The results of the corresponding data analysis have contributed to the understanding of the blazar phenomenon, particularly stressing the viability of a geometrical interpretation of the blazar variability. We review here the most significant polarimetric results achieved in the WEBT studies.

Application of Sarima Models in Modelling and Forecasting Monthly Rainfall in Nigeria

Application of SARIMA model in modelling and forecasting monthly rainfall in Nigeria was considered in this study. The study utilizes the Nigerian monthly rainfall data between 1980-2015 obtained from World Bank Climate Portal. The Box-Jenkin’s methodology was adopted. SARIMA (2,0,1) (2,1,1) [12] was the best model among others that fit the Nigerian rainfall data (1980-2015) with maximum p-value from Box-Pierce Residuals Test. The study forecasts Nigeria’s monthly rainfall from 2018 through 2042. It was discovered that the month of April is the period of onset of rainfall in Nigeria and November is the period of retreat. Based on the findings, Nigeria will experience approximately equal amount of rainfall between 2018 to 2021 and will experience a slight increase in rainfall amount in 2022 to about 1137.078 (mm). There will be a decline of rainfall at 2023 to about 1061 (mm). Rainfall values will raise again to about 1142.756 (mm) in 2024 and continue to fluctuate with decrease in variation between 2024 to 2042, then remain steady to 2046 at approximately 1110.0 (mm). Nigerian Government should provide a more mechanized and drier season farming methods to ease the outage of rainfall in future that may be caused due to natural (or unpredictable) variation.

Learning Temporary Block-Based Bidirectional Incongruity-Aware Correlation Filters for Efficient UAV Object Tracking

In the field of UAV object tracking, correlation filter based approaches have received lots of attention due to their computational efficiency. The methods learn filters by the ridge regression and generate response maps to distinguish the specified target from the background. An ideal filter can predict the object’s position in a new frame, and in turn, can backtrack the object in the past frames. However, the neglect of tracking reversibility in most methods limits the potential of using inter-frame information to improve performance. In this work, a novel bidirectional incongruity-aware correlation filter is presented based on the nature of tracking reversibility. The proposed method incorporates the response-based bidirectional incongruity, which represents the gap between the filters’ discriminative difference in the forward and backward tracking perspective caused by object appearance changes. It enables the filter not only to inherit the discriminability from previous filters but also to enhance the generalization capability to unpredictable appearance variations in upcoming frames. Moreover, a temporary block-based strategy is introduced to empower the filter accommodate more drastic object appearance changes and make more effective use of inter-frame information. Comprehensive experiments are conducted on three challenging UAV tracking benchmarks, including UAV123@10fps, DTB70, and UAVDT. Experimental results indicate that the proposed method has superior performance compared with the other 34 state-of-the-art trackers. Our approach permits real-time performance at ~46.8 FPS on a single CPU and is suitable for UAV online tracking applications.

Optimisation du traitement par β-Lactamines chez le patient de réanimation en hyperclairance rénale

L'optimisation du traitement par β-Lactamines représente toujours un défi complexe chez le patient de soins critiques, compte tenu de la large variabilité des concentrations d'antibiotiques en relation avec d’importantes interactions pharmacocinétiques et pharmacodynamiques (PK/PD). D’une part, il est communément admis que les patients présentant une insuffisance rénale justifient une diminution des posologies afin de limiter le risque de toxicité. D’autre part, certains patients peuvent également présenter une hyperclairance rénale (HCR), désormais reconnue comme un des principaux facteurs de risque de sous-dosage et d’échec thérapeutique des agents anti-infectieux à élimination urinaire. L’hyperclairance est une entité fréquente en réanimation chirurgicale, probablement sous-diagnostiquée en l’absence de mesure de clairance urinaire de la créatinine (CLCR). Pour certaines β-lactamines prescrites en probabiliste, plusieurs études de pharmacocinétique suggèrent une augmentation des posologies recommandées afin d’atteindre les objectifs PK/PD chez les patients atteints d'HCR. En cas d’impossibilité de monitorer les concentrations plasmatiques dans des délais brefs, l'optimisation des posologies de β-lactamines selon le monitorage quotidien de la CLCR est une stratégie sûre et efficace pour améliorer les taux de succès thérapeutique. L’HCR étant un phénomène fluctuant, cette stratégie impose un monitorage quotidien de la CLCR afin d’adapter les posologies et limiter le risque de surdosage.

Variation in developmental rates is not linked to environmental unpredictability in annual killifishes.

Comparative evidence suggests that adaptive plasticity may evolve as a response to predictable environmental variation. However, less attention has been placed on unpredictable environmental variation, which is considered to affect evolutionary trajectories by increasing phenotypic variation (or bet hedging). Here, we examine the occurrence of bet hedging in egg developmental rates in seven species of annual killifish that originate from a gradient of variation in precipitation rates, under three treatment incubation temperatures (21, 23, and 25°C). In the wild, these species survive regular and seasonal habitat desiccation, as dormant eggs buried in the soil. At the onset of the rainy season, embryos must be sufficiently developed in order to hatch and complete their life cycle. We found substantial differences among species in both the mean and variation of egg development rates, as well as species‐specific plastic responses to incubation temperature. Yet, there was no clear relationship between variation in egg development time and variation in precipitation rate (environmental predictability). The exact cause of these differences therefore remains enigmatic, possibly depending on differences in other natural environmental conditions in addition to precipitation predictability. Hence, if species‐specific variances are adaptive, the relationship between development and variation in precipitation is complex and does not diverge in accordance with simple linear relationships.

LANDSLIDE HAZARD ASSESSMENT APPROACH ON THE PROVINCIAL ROAD IN EAST JAVA

Landslide hazard mapping on the road infrastructure has 2 (two) main sources. The first is through a landslide inventory survey, and the second is through recording data on past landslide events. Each of the methods above has advantages and disadvantages. The most appropriate moment in making a landslide hazard map is when a certain disaster strikes an area with a certain measured impact. The Unpredictable variables that have been hidden and difficult to predict will be eliminated. Disaster events in disaster-prone mapping become a key variable as well as a validator. The characteristic of the landslide on road is also very specific, depends on the nature of the vehicle's spatial movement, and the scope of the affected area which is narrow but extends along the slopes coincide with the road. The most appropriate disaster mapping in measuring the level of hazard, vulnerability, and risk on the road is based on landslide record data. That is because the variables used to predict landslide events are extremely varied and too many are unknown. Assessing a map using a landslide disaster occurrence on the road is easier than making a map through the calculation method of certain variables that are overlapped. Based on the calculation of frequency analysis for 12 years, the daily rainfall value of 126.2 mm per day is the threshold of rain which has a probability of a landslide of 95% on the road infrastructure in East Java Province.

Reliability Evaluation of Underwater Sensor Network in Shallow Water Based on Propagation Model

Underwater wireless sensor networks are composed of numerous vehicles/sensors that are deployed in précised acoustic vicinity to execute collaborative monitoring and data assembling tasks. These sensor nodes establish an acoustic communication link among them and the surface station. The unpredictable variations in the underwater parameters (depth; temperature; salinity; pH) introduce changes in signal speed randomly, which affect the link formation. Hence, designing a feasible channel model is essential to estimate the effect of underwater parameters and their losses (absorption loss, spreading loss) on the connectivity of underwater networks. In this work, an acoustic channel model has been considered which distinguishes the effect of frequency and the aforementioned parameters on link formation. A methodology for evaluating the reliability of the underwater sensor network deployed in shallow water scenarios based on the acoustic propagation model has been proposed. The network is deployed as 3D reference architecture, where the nodes are randomly deployed in a fixed scenario depth and the source node is deployed with an adjustable buoy length. The influence of underwater parameters, network parameters, and simulation time on the two-terminal reliability of underwater sensor networks has been analyzed. The simulation results indicated that the maximum reliability is achieved at lower frequencies when compared to higher frequencies.

Relationship Between Climate Change and Food Security in Sub-Saharan Africa

The soaring cases of coronavirus pandemic coupled with unpredictable climatic variations posed danger to human lives and food security. This work examined “Relationship between climate change and food security in sub-Saharan Africa.” Using the Generalized Method of Moments technique with preliminary diagnostic tests on panel data across the 17 sub-Sahara African countries, the dependent variable is agricultural output, while the independent variables are temperature, rainfall, government expenditure on agriculture, inflation, exchange rate, gross fixed capital formation, and labor force. The findings revealed that climate change exerts negative impact on food security through temperature variations which degenerated during the period under review. The results also showed positive significant impact on government expenditure which increased during the period. The work recommended that government should embark on massive productive investments to reinvigorate and re-engineer the economy. The government and appropriate agencies should also put in place hybrid technology of high yield crops adaptive to change in climate as well as effective mechanism for food storage to secure food for the future.

Effective multiple pedestrian tracking system in video surveillance with monocular stationary camera

Multiple pedestrian tracking in video surveillance is still a pressing challenge, especially under static and dynamic occlusions and target appearance variations. Considering these complex environments in video surveillance, a multiple pedestrian tracking system with special processing procedures is proposed in this paper. In the proposed tracking system, pedestrian candidates are detected on each frame and registered as the tracked targets or associated with existing targets when their situations are suitable. The registered pedestrian targets are tracked frame by frame and terminated when the termination criteria are satisfied. In order to distinguish these target individuals, multi-sample adaptive modeling (MSAM) is proposed, which is used to adapt to a new target’s unpredictable pose variation. Furthermore, static occlusions are annotated for each scene, which may occlude pedestrians in the annotated regions. These occluded targets are modified by the assigned rules and treated differently in the process of target association. Aiming to enhance the effect of target association, each target’s location on the current frame is predicted with information on the previous frames using a Kalman filter. The predicted location is regarded as the center of the search region of the corresponding target. The experimental results show that the proposed tracker achieves the best performance among the five state-of-the-art trackers on three publicly available databases.

Geology and Mining: Mineral Resources and Reserves: Their Estimation, Use, and Abuse

Editor’s note: The Geology and Mining series, edited by Dan Wood and Jeffrey Hedenquist, is designed to introduce early-career professionals and students to a variety of topics in mineral exploration, development, and mining, in order to provide insight into the many ways in which geoscientists contribute to the mineral industry. Abstract Resource and reserve estimation is a critical step in mine development and the progression from mineral exploration to commodity production. The data inputs typically change over time and reflect variations in geoscientific knowledge as well as the modifying factors required by regulation for estimating a reserve. These factors include mineral (ore) processing, metallurgical treatment of the ore, infrastructure requirements for mine and workforce, and the transportation of processed products to buyers; others that will affect the production of metals and/or minerals from a deposit include economic, marketing, legal, environmental, social, and governmental factors. All are needed by the mining industry to quantify the contained mineralization within mineral deposits that likely warrant the significant capital investment required to build a mine. However, these resource and reserve data are estimates that change over time due to unpredicted variations in the initial inputs. Paramount to the two estimates are the quality and accuracy of the geologic inputs and the communication of these to the professionals tasked with making each estimate. Geostatistical processing of the grade of the resource has become a dominant element of the estimation process, but this requires transparent and informed communication between geologists and mining engineers with the geostatistician responsible for mathematically processing the grade data. Regulatory constraints also mean that estimated resources and reserves seldom capture the full extent of a mineral deposit. Similarly, co- and by-product metals and minerals that are commonly produced by mines may not be captured by resource and reserve estimates because of their limited economic contribution. This suggests that reporting standards for co- and by-products—particularly for the critical metals that may have a sharp increase in demand—need improvement. Finally, the importance of these data to the mining industry is such that informing investors and the broader public about the nature of resource and reserve estimates, and the meaning of associated terminology, is also essential when considering the global metal and mineral supply, and the role of mining in modern society.

Temperature-Dependent Optical Properties of Graphene on Si and SiO2/Si Substrates

Systematic investigations are performed to understand the temperature-dependent optical properties of graphene on Si and SiO2/Si substrates by using a variable angle spectroscopic ellipsometry. The optical constants of graphene have revealed changes with the substrate and temperature. While the optical refractive index (n) of monolayer graphene on Si exhibited clear anomalous dispersions in the visible and near-infrared region (400–1200 nm), the modification is moderate for graphene on SiO2/Si substrate. Two graphene sheets have shown a pronounced absorption in the ultraviolet region with peak position related to the Van Hove singularity in the density of states. By increasing the temperature from 300 K to 500 K, for monolayer graphene on Si, the n value is gradually increased while k decreased. However, the optical constants [n, k] of monolayer graphene on SiO2/Si exhibited unpredictable wave variations. In the wavelength range of 400–1200 nm, an experiential formula of a like-Sellmeier equation is found well suited for describing the dispersions of graphene on Si and SiO2/Si substrates.