Unpredictable Variations Research Articles

The Role of CYP450 Drug Metabolism in Precision Cardio-Oncology.

As many novel cancer therapies continue to emerge, the field of Cardio-Oncology (or onco-cardiology) has become crucial to prevent, monitor and treat cancer therapy-related cardiovascular toxicity. Furthermore, given the narrow therapeutic window of most cancer therapies, drug-drug interactions are prevalent in the cancer population. Consequently, there is an increased risk of affecting drug efficacy or predisposing individual patients to adverse side effects. Here we review the role of cytochrome P450 (CYP450) enzymes in the field of Cardio-Oncology. We highlight the importance of cardiac medications in preventive Cardio-Oncology for high-risk patients or in the management of cardiotoxicities during or following cancer treatment. Common interactions between Oncology and Cardiology drugs are catalogued, emphasizing the impact of differential metabolism of each substrate drug on unpredictable drug bioavailability and consequent inter-individual variability in treatment response or development of cardiovascular toxicity. This inter-individual variability in bioavailability and subsequent response can be further enhanced by genomic variants in CYP450, or by modifications of CYP450 gene, RNA or protein expression or function in various ‘omics’ related to precision medicine. Thus, we advocate for an individualized approach to each patient by a multidisciplinary team with clinical pharmacists evaluating a treatment plan tailored to a practice of precision Cardio-Oncology. This review may increase awareness of these key concepts in the rapidly evolving field of Cardio-Oncology.

Robust Control of Islanded Microgrid Frequency Using Fractional-Order PID

In this paper, a robust fractional-order PID (FOPID) controller is proposed to regulate islanded microgrid (MG) frequency. The considered MG is composed of a photovoltaic system, a wind turbine generation, a diesel generator, a battery energy storage system, the control unit, and loads. Some challenges in islanded MGs such as unpredictable variation in output power of renewable energy sources and model uncertainties, affect the system performance and lead to frequency deviations from the nominal value. For designing the proposed robust controller, the wind power and solar radiation are considered as disturbance inputs. Also, uncertainties are assumed in the inertia constant and the load damping coefficient parameters of the system. The FOPID parameters are determined by minimizing some constraints that guarantee robust stability and robust performance of the system. The performance of the proposed FOPID controller is compared with those of the classic PID and H∞ controllers. The effectiveness of the controller is illustrated through appropriate simulations.

Measurement and Forecasting of Port Tide Hydrostatic Component in North Tyrrhenian Sea (Italy)

Starting from the end of the 90s not perodic and unpredictable variations in the depth of harbor waters were observed. Long period (from 24 hours to a few days) and wide amplitude are their main features. Experience showed that this phenomenon is a risk for harbor navigation and mooring. It may be a serious obstacle to waterside port activities. The first observation of the data does not link the super-highs and the super-dry tides to the meteorological dynamic of sea-atmosphere interaction (i.e. Storm Effect). More, the attempt to compensate for these sea depth fluctuations by means of the well-known offshore hydrobarometric inverse parameter (1 [cm] sea level variation for &#451 [hPa] atmospheric pressure variation) underestimates the amplitude of the phenomenon. In the first years of 2000, the Italian Ministry of Transport launched a national project for the definition of thee-amplitude and time of these tidal anomalous waves. The measure of harbors hydrobarometric inverse factors showed a much more intense value than the theoretical one (computed for the offshore). These amplification factors are characteristic of each harbor and can be double (in exceptional cases even more) than offshore. The delay between the arrival times of these tidal waves (induced phenomenon) respect to the time of arrival of the atmospheric pressure variation (inducing phenomenon) depends on 1) morphology of the port basin sea floor and 2) harbor and off-shre water dynamics relationship (first approximation). For these reasons the hydro barometric inverse parameter is not effectiveness computable but it can be determined statistically.

Efficient handling of fault properties using the Juxtaposition Table Method

Abstract Faults are known to affect the way that fluids can flow in clastic oil and gas reservoirs. Fault barriers either stop fluids from passing across or they restrict and direct the fluid flow, creating static or dynamic reservoir compartments. Representing the effect of these barriers in reservoir models is key to establishing optimal plans for reservoir drainage, field development and production. Fault property modelling is challenging, however, as observations of faults in nature show a rapid and unpredictable variation in fault rock content and architecture. Fault representation in reservoir models will necessarily be a simplification, and it is important that the uncertainty ranges are captured in the input parameters. History matching also requires flexibility in order to handle a wide variety of data and observations. The Juxtaposition Table Method is a new technique that efficiently handles all relevant geological and production data in fault property modelling. The method provides a common interface that is easy to relate to for all petroleum technology disciplines, and allows a close cooperation between the geologist and reservoir engineer in the process of matching the reservoir model to observed production behaviour. Consequently, the method is well suited to handling fault property modelling in the complete life cycle of oil and gas fields, starting with geological predictions and incorporating knowledge of dynamic reservoir behaviour as production data become available.

Managing Resident Workforce and Education During the COVID-19 Pandemic: Evolving Strategies and Lessons Learned.

Background:The novel coronavirus and associated Coronavirus Disease 2019 (COVID-19) is rapidly spreading throughout the world, with robust growth in the United States. Its drastic impact on the global population and international health care is swift, evolving, and unpredictable. The effects on orthopaedic surgery departments are predominantly indirect, with widespread cessation of all nonessential orthopaedic care. Although this is vital to the system-sustaining measures of isolation and resource reallocation, there is profound detriment to orthopaedic training programs.Methods:In the face of new pressures on the finite timeline on an orthopaedic residency, the Emory University School of Medicine Department of Orthopaedics has devised a 5-pronged strategy based on the following: (1) patient and provider safety, (2) uninterrupted necessary care, (3) system sustainability, (4) adaptability, and (5) preservation of vital leadership structures.Results:Our 5 tenants support a 2-team system, whereby the residents are divided into cycling “active-duty” and “working remotely” factions. In observation of the potential incubation period of viral symptoms, phase transitions occur every 2 weeks with strict adherence to team assignments. Intrateam redundancy can accommodate potential illness to ensure a stable unit of able residents. Active duty residents participate in in-person surgical encounters and virtual ambulatory encounters, whereas remotely working residents participate in daily video-conferenced faculty-lead, case-based didactics and pursue academic investigation, grant writing, and quality improvement projects. To sustain this, faculty and administrative 2-team systems are also in place to protect the leadership and decision-making components of the department.Conclusions:The novel coronavirus has decimated the United States healthcare system, with an unpredictable duration, magnitude, and variability. As collateral damage, orthopaedic residencies are faced with new challenges to provide care and educate residents in the face of safety, resource redistribution, and erosion of classic learning opportunities. Our adaptive approach aims to be a generalizable tactic to optimize our current landscape.

Changes in Check Plot Yields over Time in Three Long-Term Winter Wheat Experiments

ABSTRACTLong-term trials conducted by Oklahoma State University convey relevant information on the changes of yield over time. These changes might be due to different factors such as weather, soil organic matter or available nutrients. In long-term experiments, yield of the check plot (no fertilizer) can reveal added information about the environment when studied alone. Long-term trials can be used to evaluate trends that cannot be understood over short periods. Three long-term experiments (Experiment 502, Experiment 222 and Magruder Plots) were used to evaluate changes in check plot yields over time in continuous winter wheat. These changes were expected to provide a better understanding of fertilizer N response and yield potential. Check plots and nitrogen fertilized plots had similar variability over the years, with coefficient of variations (CVs) for both near 30%. Overall means for the check plot (Magruder Plots, Experiment 222 and Experiment 502) were 1072, 1078 and 1674 kg ha−1,respectively. The unpredictable variability in grain yields from year to year in both fertilized and unfertilized plots was further documented and that highlights the need for mid-season determination of fertilizer nitrogen rates. Unpredictable variability is thus expected and should be internalized at the outset of every planting season.

Fault-Tolerant Neuro Adaptive Constrained Control of Wind Turbines for Power Regulation with Uncertain Wind Speed Variation

This paper presents a novel adaptive fault-tolerant neural-based control design for wind turbines with an unknown dynamic and unknown wind speed. By utilizing the barrier Lyapunov function in the analysis of the Lyapunov direct method, the constrained behavior of the system is provided in which the rotor speed, its variation, and generated power remain in the desired bounds. In addition, input saturation is also considered in terms of smooth pitch actuator bounding. Furthermore, by utilizing a Nussbaum-type function in designing the control algorithm, the unpredictable wind speed variation is captured without requiring accurate wind speed measurement, observation, or estimation. Moreover, with the proposed adaptive analytic algorithms, together with the use of radial basis function neural networks, a robust, adaptive, and fault-tolerant control scheme is developed without the need for precise information about the wind turbine model nor the pitch actuator faults. Additionally, the computational cost of the resultant control law is reduced by utilizing a dynamic surface control technique. The effectiveness of the developed design is verified using theoretical analysis tools and illustrated by numerical simulations on a high-fidelity wind turbine benchmark model with different fault scenarios. Comparison of the achieved results to the ones that can be obtained via an available industrial controller shows the advantages of the proposed scheme.

Using Pharmacogenomics Testing to Optimize Care in Children with Acute Hematologic Malignancies

Background Inter-patient variation in the pharmacokinetics of drugs can result in unpredictable variability in occurrence of adverse events and toxicity as well as variation in therapeutic efficacy. Although a multitude of factors contribute to this observed variation, inherited variation in genes involved in drug metabolism and transport has been shown to play a significant role. Genetic polymorphisms can influence the gene expression and/or activity, thereby impacting drug pharmacokinetics and causing inter-individual variation in drug levels which can alter risk of toxicity or therapeutic efficacy. The goal of this study is to identify pharmacogenomic biomarkers predicting drug response and toxicity in children receiving chemotherapy for acute hematologic malignancies. Identification of such biomarkers will establish relevant biomarkers for allowing for personalizing therapy to achieve maximum benefit and minimal side effects in future studies. Study Design and Methods: Study Population Male and female participants are included with no restrictions based on racial and/or ethnic origin. All patients aged 26 years of younger who have received at least one year of treatment for acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML) and have experienced organ toxicity CTCAE v5.0 Grade 3 or higher at the University of Florida are offered participation. Subjects meeting eligibility criteria are excluded if they cannot provide a blood specimen. Study Design This pilot study proposes to identify and characterize pharmacogenomic variations that lead to different systemic toxicity profiles in pediatric patients receiving commonly used chemotherapy agents for ALL and AML. Agents of interest include drugs used during induction chemotherapy cycles which include Vincristine, Methotrexate, Cytarabine, Daunorubicin, Prednisone, Dexamethasone, 6-thioguanine, Cyclophosphamide, 6-mercaptopurine, and Etoposide. A single-nucleotide polymorphism (SNP) panel to evaluate SNPs in pharmacokinetic pathway genes of the selected drugs has been created. Genotyping is performed using Taqman genotyping assays and the Quant studio real time PCR system. We are investigating genes involved in the pharmacokinetics of the selected chemotherapy agents such as ABCB1, GSTM1, GSTT1, BCL2, MCL1, BCL2L11, MTHFR, SLC29A1, FMO3, DYNC2H1, TPMT, NUDT15, GSTP1, SOD2, and TP53. Toxicities that are correlated to SNP genotypes include the following: renal injury defined as creatinine clearance 29-15 ml/min/1.73 m2 or less; hepatic injury defined by increase in serum total bilirubin > 3.0 times the upper normal limit; hematological impairment including severe neutropenia, thrombocytopenia, and anemia leading to treatment delays; number of neutropenic fever hospitalizations; thromboembolic events; pancreatitis; cardiotoxicity defined by decline in ejection fraction by > 20% of baseline; neurotoxicity defined by examination and alterations in function; and insulin-dependent glucose resistance. The relationship and prevalence of SNP variations to the defined toxicities is analyzed. Statistical Considerations and Study Endpoint Complete case analysis will be performed. Toxicities per CTCAE v5.0 are graded by ordinal statistics. We aim to describe rates of pharmacogenomic SNP variants and the prevalence of specific toxicities related to these variants. The sample size of 100 patients was selected because this number should allow us to be relatively precise in our conclusions while still allowing for estimates of variability. Factors such as the rarity of pediatric cancer and the numbers of patients treated at our institution were considered in selecting this sample size. A chi-square test is used to evaluate for an association between SNP variants and toxicity grading. To quantify identified associations, multinomial logistic regression analysis will be performed. A P-value <0.05 is considered statistically significant. Study Endpoints: The study endpoint is to identify pharmacogenomic SNP variants of children undergoing treatment for acute hematologic malignancies and to provide an analysis of the relationship between these variants and clinically graded toxicities. Identification of these biomarkers would help guide subsequent validation in a larger cohort and establish clinically relevant biomarkers for personalization of acute leukemia therapy. Disclosures No relevant conflicts of interest to declare.

A population balance model to modulate shear for the control of aggregation in Taxus suspension cultures.

Cellular aggregation in plant suspension cultures directly affects the accumulation of high value products, such as paclitaxel from Taxus. Through application of mechanical shear by repeated, manual pipetting through a 10 ml pipet with a 1.6 mm aperture, the mean aggregate size of a Taxus culture can be reduced without affecting culture growth. When a constant level of mechanical shear was applied over eight generations, the sheared population was maintained at a mean aggregate diameter 194 μm lower than the unsheared control, but the mean aggregate size fluctuated by over 600 μm, indicating unpredictable culture variability. A population balance model was developed to interpret and predict disaggregation dynamics under mechanical shear. Adjustable parameters involved in the breakage frequency function of the population balance model were estimated by nonlinear optimization from experimentally measured size distributions. The optimized model predictions were in strong agreement with measured size distributions. The model was then used to determine the shear requirements to successfully reach a target aggregate size distribution. This model will be utilized in the future to maintain a culture with a constant size distribution with the goal of decreasing culture variability and increasing paclitaxel yields.

Unpredictable Nanoparticle Retention in Commonly Used Plastic Syringes Introduces Dosage Uncertainties That May Compromise the Accuracy of Nanomedicine and Nanotoxicology Studies

In recent animal experiments with suspensions of radiolabeled TiO2 nanoparticles large and highly variable radioactivity fractions were retained in disposable plastic syringes. After unloading between 10% and up to 70% of the loaded dose were still present in the syringes. As a consequence the effectively delivered nanoparticle dose to the animals was frequently much smaller than the nominal dose of the nanoparticles loaded into the syringe. The high variability of this nanoparticle retention challenges the application of a precise, predefined dose and creates a major error source when normalizing organ and tissue contents to the dose loaded into the syringe, which is usually set as the applied dose. A control study was performed employing six commonly used syringe types with seven types of radiolabeled oxide and metallic nanoparticles. For this purpose the syringes were loaded with a given volume of nanoparticle suspension, the radioactivity was measured, the syringe was unloaded and the activity measurement was repeated with the empty syringe. The highest retention values were found when using TiO2 nanoparticle suspensions with Tuberkulin type syringes. In the worst case between 6.6% and 79.1% of the nanoparticles were retained in the syringe. When using the same nanoparticle suspension with an insulin-type syringe the retention was reduced to 1.4% to 20.6%. For amorphous silica nanoparticles the maximum observed retention was 8% and for Au nanoparticles it was 5.1%. Further data gathered from in vivo animal imaging studies show that nanoparticle retention in syringes also affects experiments with nanoparticles such as exosomes, polymersomes, and protein-based nanoparticles investigated for possible applications in nanomedicine. Since the retention is highly variable the effectively applied dose cannot be determined by applying a simple syringe retention factor. The present work shall alert to the problem and illustrate its possible magnitude and unpredictable variability. As mitigation strategy adequate checks with different syringe types are proposed in order to find out whether a given combination of syringe type and nanoparticle suspension is affected by nanoparticle retention and, if necessary, to select a different syringe type that minimizes retention.

A Priori Identification of Skillful Extratropical Subseasonal Forecasts

AbstractThe current generation of subseasonal operational model forecasts has, on average, low skill for leads beyond 3 weeks. This is likely a fundamental property of the climate system, due to the relative high amplitude of unpredictable weather variability compared to potentially predictable, but generally weaker, climate signals. Thus, for subseasonal forecasts to be useful, their high versus low skill events should be identified at time of forecast. We show that a linear inverse model (LIM), an empirical‐dynamical model constructed from covariability statistics of wintertime (December–March) weekly averaged observational analyses, can be used to identify, a priori, the expected extratropical subseasonal surface and midtropospheric forecast skill. The LIM's predicted signal‐to‐noise ratio identifies the subset (10%–30%) of Weeks 3–6 forecasts—of the LIM and two operational models from the National Centers for Environmental Prediction and the European Centre for Medium‐Range Weather Forecasts—with relatively higher skill versus the much larger remainder of forecasts whose skill cannot be distinguished from random chance.

Control Systems for Dynamic Processes with Single Degree of Freedom with Automatic Adaption of the Structure and Parameters of the System to an External Load

An adaptive method of control of a system with single degree of freedom along a given trajectory of displacement under the conditions of unpredictable variation of a surmountable external load is set forth. Simulation of the load with the use of a special force vector that reflects the nature of its variation is proposed. The components of the force vector (averaged values of partial derivatives of the load with respect to time and spatial coordinate) are calculated from the working information which the control system receives at previous moments of displacement of the control object. The order of the model is the maximumorder of the derivatives included in the model. The general structure and derivation of formulas for models of zero, first and second order are given. The practical case of measurement of the angular displacement of a shaft using incremental encoders is given separately. Initially, direct load models are considered in which time is the independent variable. Then, for a drive with incremental encoders, inverse models are presented separately in which the angle of rotation of the output shaft is the independent coordinate. Conditions under which the adequacy of the parameters of the power vector and the redundancy and insufficiency of the order of the control model is estimated are considered separately. Based on these conditions, a general algorithm for the functioning of the control system by means of which both the parameters and the structure of the control system may be dynamically changed is given.

Spatially Explicit Model for Statistical Downscaling of Satellite Passive Microwave Soil Moisture

We introduce a spatially explicit statistical downscaling (SESD) method that fuses multiscale geospatial data with the soil moisture (SM) product from NASA’s SM Active and Passive (SMAP) satellite. The multiscale data included the 9-km resolution SMAP SM image, 1-km resolution normalized difference vegetation index (NDVI), 1-km digital elevation model (DEM), 1-km resolution MODIS land surface temperature (LST), 500-m resolution gross primary productivity (GPP), 30-m resolution topographical water index (TWI), and West Texas Mesonet (WTM) station data. We used the random forest (RF) machine learning method to make a downscaled SM prediction at the 1-km resolution. Then, a regression kriging was applied to model the unpredicted variability at local scales to produce downscaled SM using the WTM station data. Due to the low number of ground truth samples, the validation was based on Monte -Carlo cross validation (CV) to calculate the unbiased root-mean-square deviation (ubRMSD), root-mean-square deviation (RMSD), and bias of the test set randomly separated from the training set from the WTM station data. Model validation showed that the downscaled SM data at the 1-km resolution can significantly improve the accuracy of the SM product as well as enhancing its spatial resolution. This article has its novelty in using the spatially explicit model to reconcile the scale difference from satellite data and ground observations.

Hypersonic flight control considering parametric variations and VGI effects

Despite advantages of variable geometry inlet (VGI) in improving scramjet efficiency, a concern of its negative effects on aerodynamics persists. This paper presents a novel longitudinal control for the hypersonic vehicle model with further considerations on both strong VGI effects and unpredictable parametric variations, which is practical but hard to handle. Our design uses an auxiliary signal and a bound adaptation mechanism to synthetically accommodate VGI effects (including VGI servomechanism characteristics and VGI couplings with aerodynamics), time-varying parameters and structural flexibility while achieving good tracking performances via a relatively low-dimension adaptive algorithm.

Pharmacokinetics of Tacrolimus in Egyptian Liver Transplant Recipients: Role of the Classic Co-variables

Objectives: This work was performed to study the pharmacokinetics of tacrolimus in adult liver transplant recipients after optimization of all the known classic factors contributing to inter-patient variability in whole blood tacrolimus levels. Also, to detect if any variability in whole blood tacrolimus levels still exists or this variability is only a function of the classic co-variables so that their optimization will diminish or eliminate it. Methods: Twenty-Six male patients with end-stage liver disease undergoing living donor liver transplantation were selected from the Gastroenterology Department of the International Medical Center, Cairo, Egypt, were enrolled in the study. A patient is initially considered to be a candidate for this study when tacrolimus was indicated as a part of a triple immune suppressive regimen with mycophenolate mofetil and prednisolone. Patients were selected to have non-significant variations in their demographics and pretreatment clinical data. Blood samples were drawn from each patient before the morning dose at specified intervals and the whole blood was assayed for tacrolimus, using Chemiluminescent Microparticle Immunoassay method (CMIA). Six months after liver transplantation, patients were classified into 3 groups based on their tacrolimus trough levels; normalized by its daily dose (C/D ratio), into fast, intermediate and slow metabolizers. Results: The results revealed unpredictable variability in whole blood tacrolimus levels among patients at each sampling time and a marked inter-patient variability in mean whole blood tacrolimus levels among individuals throughout the six months post transplantation period, (P value: <0.0001). Considerable inter-patient variability was also evident in tacrolimus pharmacokinetics. During 1st month post-transplant, tacrolimus C/D ratio varied from 0.53 to 12.2 (ng/ml*1/mg) and tacrolimus oral clearance (CL/F) varied from 3.4 to 79.4 L/hr. At 3rd month post-transplant, tacrolimus C/D ratio varied from 0.78 to 8.50 (ng/ml*1/mg) and tacrolimus CL/F varied from 4.9 to 53.2 L/hr. At 6th month post-transplant, tacrolimus C/D ratio varied from 0.73 to 7.10 (ng/ml*1/mg) and tacrolimus CL/F varied from 5.9 to 56.8 L/hr. The overall mean C/D ratio and oral clearance also showed a great variability among patients with a mean of 2.80±1.89 (CV: 67.5%) and 21.3±12.9 (CV:60.7%), respectively. Conclusion: The variability in whole blood tacrolimus concentrations and tacrolimus pharmacokinetics existed in spite of careful patient selection and optimization of all the classic co-variables known to affect tacrolimus concentrations, suggesting the presence of other unstudied factors; the recently evolving genetic factors might contribute to this variability. It is recommended to still considering therapeutic drug monitoring as an integral part of tacrolimus therapy to control variations in response until the discovery of a model that considers all the expected covariates to predict the response.

Does nature of livelihood regulate the urban community's vulnerability to climate change? Guwahati city, a case study from North East India

There is dearth of studies on climate change based vulnerabilities of the urban people. It has been a matter of widespread debate whether nature of livelihood has any role to play in regulating the vulnerabilities of an individual. To find an answer, in a first ever attempt, this study tested three different approaches viz. Livelihood Vulnerability Index (LVI), LVI IPCC (Intergovernmental Panel on Climate Change) models and Climate Vulnerability Index (CVI) to estimate climate change vulnerability of urban communities from various livelihoods in Guwahati city, Assam, India. Guwahati is considered to be the gateway to the seven North Eastern states of India and therefore strategically very important for this region. A structured survey was conducted involving 200 stakeholders from various livelihood sectors viz. construction workers, perishable item sellers, farmers, taxi/auto driver/rickshaw puller/coolie, tea stall/fast food seller, gas cylinder deliverymen, street vendors/salespersons, traffic police/police, doctors and boatmen. Data was systematically aggregated and examined using the above-mentioned composite indices. The differential vulnerabilities were compared and results suggested that the farmers were the most vulnerable community by virtue of their high sensitivity towards health, economic losses, exacerbated by their poor adaptive capacity toward unpredictable climatic variations. Doctors were the least vulnerable owing to their higher levels of awareness and adaptive capacity. These results reiterated the importance of awareness and access to resources in regulating vulnerability. The vulnerability scores also revealed that LVI and Model II (M II) of LVI IPCC approaches were the two most suitable indices and could be used for comparative vulnerability analysis. These pragmatic approaches can be used to assess the community vulnerabilities and could stimulate robust Climate Smart Urban Planning (CSUP).

Sliding Mode Control for Nonlinear Stochastic Semi-Markov Switching Systems With Application to SRMM

In this paper, the sliding mode control (SMC) design for nonlinear stochastic semi-Markov switching systems (S-MSSs) is studied via the bound of time-varying transition rate matrix, in which semi-Markov switching parameters, stochastic disturbance, uncertainty, and nonlinearity are all considered in a unified framework. The system under consideration is more general, which covers the Markov switching system with sojourn-time-independent transition rate matrix as a special case. Many practical systems subject to unpredictable structural variations can be characterized by nonlinear stochastic S-MSSs with sojourn-time-dependent transition rate matrix. The specific information about the bound of time-varying transition rate matrix is known for the sliding mode controller design. First, by using the stochastic semi-Markov Lyapunov function, sojourn-time-dependent sufficient conditions are developed to guarantee the closed-loop sliding mode dynamics stochastically stable. Then, the SMC law is constructed to ensure the reachability of the sliding mode dynamics in a finite-time level. Finally, one joint of space robot manipulator model is described as nonlinear stochastic S-MSSs to illustrate the validity of the proposed SMC design method.

Relating microalgal response to nutrient status in a mangrove-dominated estuary

Mangrove-dominated estuaries are highly dynamic and productive systems. The Mngazana Estuary occurs in the sub-tropical biogeographical region along the east coast of South Africa. The present study assessed the water column dynamics in the mangrove-dominated estuary by investigating the response of phytoplankton to the variability in environmental factors and nutrient concentrations in 2014–2015. Freshwater flow into the estuary was variable with a peak at 0.90 m3 s−1 and a monthly average flow of approximately 0.86 m3 s−1. Nutrient concentrations showed seasonal fluctuations in the estuary and are likely derived from both allochthonous (terrestrial runoff) and autochthonous (internal cycling) sources. Results indicate significant, yet unpredictable spatial and temporal variability in phytoplankton, with the main channel exhibiting higher phytoplankton biomass (~ 15 µg l−1) compared to the tidal creeks (~ 8 µg l−1) and phytoplankton composition shifting from pronounced diatom presence (summer 2015) along the main channel to dinoflagellate dominance along the tidal creeks (winter 2015). The potential influences of human activities, ranging from livestock presence to road bridge construction during this study are noted. This study confirms the need for further investigation on mangrove nutrient fluxes to understand their role on the water column microalgal dynamics particularly when freshwater abstraction is high.

Interindividual variation and consistency of migratory behavior in the Eurasian woodcock

Diverse spatio-temporal aspects of avian migration rely on relatively rigid endogenous programs. However, flexibility in migratory behavior may allow effective coping with unpredictable variation in ecological conditions that can occur during migration. We aimed at characterizing inter- and intraindividual variation of migratory behavior in a forest-dwelling wader species, the Eurasian woodcock Scolopax rusticola, focusing on spatio-temporal consistency across repeated migration episodes. By satellite-tracking birds from their wintering sites along the Italian peninsula to their breeding areas, we disclosed a remarkable variability in migration distances, with some birds flying more than 6,000 km to Central Asian breeding grounds (up to 101°E). Prebreeding migration was faster and of shorter duration than postbreeding migration. Birds moving over longer distances migrated faster during prebreeding migration, and those breeding at northernmost latitudes left their wintering areas earlier. Moreover, birds making longer migrations departed earlier from their breeding sites. Breeding site fidelity was very high, whereas fidelity to wintering areas increased with age. Migration routes were significantly consistent, both among repeated migration episodes and between pre- and postbreeding migration. Prebreeding migration departure date was not significantly repeatable, whereas arrival date to the breeding areas was highly repeatable. Hence, interindividual variation in migratory behavior of woodcocks was mostly explained by the location of the breeding areas, and spatial consistency was relatively large through the entire annual cycle. Flexibility in prebreeding migration departure date may suggest that environmental effects have a larger influence on temporal than on spatial aspects of migratory behavior.

On characterizing heterogeneities from velocity logs using Hölderian regularity analysis: A case study from Algerian tight Devonian reservoirs

This paper aims at studying the singularity behavior of geophysical well logs to understand the geological model by extracting valuable information that cannot be derived using the conventional analysis techniques. Since well logs exhibit unpredictable spatial variations associated to a regularity evolving both in time and space, they are modeled by multifractional Brownian motions (mBm). These stochastic processes are indexed by the local Hölder exponent H which measures the degree of the regularity at every depth.First, synthetic logs have been simulated to assess the performance of the three suggested methods for estimating the local Hölder function H(z): Peltier and Lévy-Véhel (PLV), Bianchi and the detrending moving (DMA) algorithms. The obtained results illustrates that the PLV algorithm is the most efficient regularity estimator.Then, the regularity analysis is implemented on P- and S-wave velocity logs recorded at four Algerian exploration wells crossing two reservoirs, specifically the Devonian and Silurian reservoirs. Our findings showed good correlations between the local regularity functions H(z) and the lithological changes, and each change is marked by jumps of H value. In addition, as can be confirmed by the interpretation of petrophysical logs, the resulting local regularity profiles can indicate the distribution of clays and fluids present in the reservoirs. It is worth noting that the suggested regularity analysis might be of a high interest in investigating facies changes as well as in characterizing geological heterogeneities of subsurface.