Types Of Disturbances Research Articles

Functional traits and climate drive interspecific differences in disturbance-induced tree mortality.

With climate change, natural disturbances such as storm or fire are reshuffled, inducing pervasive shifts in forest dynamics. To predict how it will impact forest structure and composition, it is crucial to understand how tree species differ in their sensitivity to disturbances. In this study, we investigated how functional traits and species mean climate affect their sensitivity to disturbances while controlling for tree size and stand structure. With data on 130,594 trees located on 7617 plots that were disturbed by storm, fire, snow, biotic or other disturbances from the French, Spanish, and Finnish National Forest Inventory, we modeled annual mortality probability for 40 European tree species as a function of tree size, dominance status, disturbance type, and intensity. We tested the correlation of our estimated species probability of disturbance mortality with their traits and their mean climate niches. We found that different trait combinations controlled species sensitivity to disturbances. Storm-sensitive species had a high height-dbh ratio, low wood density and high maximum growth, while fire-sensitive species had low bark thickness and high P50. Species from warmer and drier climates, where fires are more frequent, were more resistant to fire. The ranking in disturbance sensitivity between species was overall consistent across disturbance types. Productive conifer species were the most disturbance sensitive, while Mediterranean oaks were the least disturbance sensitive. Our study identified key relations between species functional traits and disturbance sensitivity, that allows more reliable predictions of how changing climate and disturbance regimes will impact future forest structure and species composition at large spatial scales.

Material legacies can degrade resilience: Structure-retaining disturbances promote regime shifts on coral reefs.

Standing dead structures of habitat-forming organisms (e.g., dead trees, coral skeletons, oyster shells) killed by a disturbance are material legacies that can affect ecosystem recovery processes. Many ecosystems are subject to different types of disturbance that either remove biogenic structures or leave them intact. Here we used a mathematical model to quantify how the resilience of coral reef ecosystems may be differentially affected following structure-removing and structure-retaining disturbance events, focusing in particular on the potential for regime shifts from coral to macroalgae. We found that dead coral skeletons could substantially diminish coral resilience if they provided macroalgae refuge from herbivory, a key feedback associated with the recovery of coral populations. Our model shows that the material legacy of dead skeletons broadens the range of herbivore biomass over which coral and macroalgae states are bistable. Hence, material legacies can alter resilience by modifying the underlying relationship between a system driver (herbivory) and a state variable (coral cover).

Comparative analysis on recent deep learning techniques for identifying chatter in milling process

Milling seems to be the most extensively utilized production technology in modern manufacturing industries, and it plays a significant role. Chatter is a type of disturbance in the form of vibration that has a negative impact on machining operation. Chatter recognition utilizing sensor outputs is a hot topic in academia. Although some progress has indeed been documented utilizing various featurization techniques and ml techniques, conventional approaches have a number of limitations, including manual preparation and a huge dataset need. Although, these are widely being used to evaluate milling operations in terms of production efficiency & work piece surface quality,.they are not suited for real applications due to their computing duration and require large data for training process. Therefore, in this study, three well-performing deep learning approaches such as LSTM, DTW, and Bi-LSTM are used to provide an effective way for monitoring and managing chatter in the milling processes with the Duplex 2205 material. Here, some of the parameters like acceleration is measured while the milling operation is taking place, and the measured acceleration value is processed using selected three DL techniques for identifying the presence of chatter and are tested to see which one performs the best. The Bi-LSTM outperformed other approaches in detecting chatter present, according to the data.

The influence of free-surface vortex on underwater ghost imaging

The vortex generated in the gas–liquid interface may appear in the propagation path, and shows severe disturbance to light propagation, thus affects the final imaging. In this Letter, the influence from the vortex on underwater ghost imaging is investigated experimentally. We find a counter-intuitive phenomenon that imaging quality becomes worse when the vortex is close to the imaging target, which is absolutely different from the typical channel disturbances, such as atmospheric turbulence and scattering. This phenomenon can be explained by the influence mechanism of speckle variation and the effective data distribution on the bucket detector. Meanwhile, a modified imaging method based on the effective bucket samples is proposed to enhance imaging quality and verified in experiment.

Sleep Disturbances in Children With Atopic Dermatitis: A Scoping Review.

Atopic dermatitis (AD) is associated with various quality of life concerns including poor sleep. Sleep impairments in children with AD are associated with increased risk of short stature, metabolic syndrome, mental illness and neurocognitive dysfunction. Although the association between AD and sleep disturbance is well established, the specific types of sleep disturbance in pediatric AD patients and their underlying mechanisms are not fully understood. A scoping literature review was performed to characterize and summarize the types of sleep disturbance in children (less than 18 years of age) with AD. 31 papers met inclusion criteria and extracted data were analyzed in an iterative manner. Two types of sleep disturbances were found to be more prevalent in pediatric AD patients in comparison to controls. One category was related to loss of sleep (increased frequency or duration of awakenings, increased sleep fragmentation, delayed sleep onset, decreased total sleep duration, and decreased sleep efficiency). Another category was associated with unusual behaviors during sleep (restlessness/limb movement/scratching, sleep-disordered breathing including obstructive sleep apnea and snoring, nightmares, nocturnal enuresis and nocturnal hyperhidrosis). Some mechanisms underlying these sleep disturbances include pruritus and induced scratching and increased proinflammatory markers induced by sleep loss. Sleep disturbance appears to be associated with AD. We recommend clinicians to consider interventions that may reduce sleep disturbances in children with AD. Further investigation of these sleep disturbances is needed to elucidate pathophysiology, develop additional treatments, and reduce negative impacts on the health outcomes and quality of life in pediatric AD patients.

Interference Analysis of Postpaid kWh Meters According to Standard Operational Procedures at PT. PLN Ulp Helvetia Medan Indonesia

In this work, we report that various electronic device are continuously being developed to support human life. The scale also varies, ranging from simple household appliances to heavy industrial equipment. In the process of collecting household electrical power, a kWh Meter is needed to simplify and minimize employee errors in inputting data on household and industrial electricity usage in the Medan City area. In its operation, operational and non-operational disturbances often occur such as congestion at the kWh meter, fire at the kWh meter, and other unavoidable disturbances. In overcoming disturbances that occur in kWh Meters, Inspection and Maintenance of kWh meters can be carried out, especially on digital / Postpaid kWh Meters. This report contains the type of kWh that is often used, the components in the kWh meter, the types of disturbances that often occur in the kWh meter, the impact on the damage to the kWh meter, and how to overcome these types of disturbances.

Penetration of DWT & ANFIS to Power Transmission Disturbances

This study proposes a hybrid method to classify and estimate the location of short circuit disturbance on power transmission lines. The hybrid method uses Discrete Wavelet Transform (DWT) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The transmission system is implemented in a real system, in which the electric power transmission system on the KP bus to the GS bus is with a length of 64 Km. The DWT is used to process information from each phase voltage and current transient signal as well as the zero-sequence current for one cycle after the disturbance has started. The ANFIS classification is designed to detect disturbance on each phase and ground in determining the type of short circuit disturbance. ANFIS estimation is used to measure the location of disturbance that occur on the transmission line. The training and testing data are generated by simulating the types of short circuit disturbance using software with variations in disturbance location and fault resistance. The result is that the disturbance classification is with 100% accuracy and the estimated disturbance location is with the lowest error of 0.0006% and the highest error is 0.03%.

Diagnosis and treatment strategy of permanent tooth developmental disturbances caused by primary tooth trauma

The trauma to primary tooth may lead to developmental disturbances of permanent tooth. Because the traumatic events are often forgotten as accurred earlier, the timely diagnosis and intervention treatment are not conducted, resulting in aesthetic and functional disorders. This paper systematically elaborates the types of developmental disturbances in permanent tooth after traumatic injuries to the primary predecessor, and the etiology, mechanism, related factors as well as the treatment options, in order to provide references for the prevention of serious complications in inherited permanent tooth caused by primary tooth trauma.

Enhanced Protection Coordination for Inverter Interfaced Distributed Generation (IIDG) with a Robust Multi-Loop Controller

Increasing penetration of inverter interfaced distributed generation (IIDG) in distribution networks has severely impacted protection coordination. False tripping, sympathetic tripping, protection blinding, failure of reclosing, and increase in short circuit levels are the critical complications and consequently disturbed the protection setting of the distribution network. This paper presents a novel multiloop current control scheme based on single integrator backstepping with a proportional resonant (PR) controller assisted by the whale optimization algorithm (WOA) to integrate IIDG in the distribution network. This control approach is designed to mitigate the maloperation of the overcurrent protection, due to the IIDG's current contribution during various types of faults. Inner loop backstepping is utilized to track converter side current and in addition, the PR controller is designed to track grid current in an outer loop. Using the proposed methodology, the injected current to the grid is effectively controlled to the rated level during several types of faults or disturbances. The performance of the proposed control strategy is verified by time-domain results and through eigenvalues trajectory and results have been compared with a current state-of-the-art which corroborates the effective control capability of the present controller.

Disturbance observer-based adaptive neural guidance and control of an aircraft using composite learning

An adaptive neural guidance and control system is proposed in this paper for a generic fixed-wing aerial robot. Unlike most of the existing low-level control systems, which utilize a non-adaptive guidance loop, in this work both the guidance and control loops are trained using an efficient adaptive neural algorithm. A feedforward neural network is employed in each loop to identify uncertain dynamics, while an adaptive disturbance observer allows to compensate for both the external disturbances and estimation error of the neural network. This would lead to a resilient flight control system, and thus, the asymptotic stability of both the guidance and control loops can be theoretically ensured for a generic aerial robot subject to different types of nonparametric internal and external disturbances. Besides, to enhance the learning efficiency, a composite learning method is adopted in which the neural network and the disturbance observer are trained using a composite error function consisting of the tracking error and the estimation error of an introduced adaptive state observer. To the best of the authors’ knowledge, this is the first completely adaptive integrated guidance and control system with guaranteed stability under parametric and nonparametric internal and external disturbances. The introduced control system is then applied to a simulation model of an electric aircraft that has been validated on the basis of real data and flight experiments. The obtained results indicate that the proposed approach could be considered a reliable guidance and control system for a generic fixed-wing aerial vehicle in the presence of actuator faults, unmodeled dynamics, external disturbances, and measurement noises.

What you need to know about assessing a patient with diplopia.

Diplopia occurs when two images are subjectively seen of a single object. It has a variety of causes, which range in severity from benign to sight or life threatening if left untreated. Clinical assessment of diplopia includes taking a comprehensive history to delineate the exact type of visual disturbance experienced by the patient and examination to pinpoint the aetiology, which is crucial for further management. This article discusses the causes of diplopia, along with risk factors and other associated symptoms, to facilitate diagnosis and management. Efficient and effective diagnosis is important, as some pathologies require immediate treatment to save the eyesight and/or life of the patient. This article will concentrate solely on binocular diplopia.

Assessment of Voltage Fluctuations for Battery Storage Systems Providing Frequency Response Services

This paper investigates voltage fluctuations caused by the operation of battery energy storage (BES) units which provide frequency response (FR) and fast frequency response (FFR) services using a test network based on a typical part of the United Kingdom (UK) mainland system. This paper provides an overview of current FR/FFR services currently used in the UK, and a summary of their typical modes of operation. Using DIgSILENT Powerfactory, the paper introduces a simple frequency disturbance generator to mimic typical frequency disturbances that would occur in the UK network, and then subsequently uses a representative test distribution network to show how voltage disturbances associated with BES units can develop across the electrical network. The paper provides a contribution to knowledge by creating a systematic approach for assessing voltage disturbance and flicker concerns for BES units on island networks, using a simple control algorithm and novel frequency disturbance generator.

On the nonlinear characteristics of two-phase flow system as modified Fitzhugh-Nagumo model

Two-phase flow systems are used in many industries for high heat transfer because these systems utilize latent heat of vaporization. However, these systems are susceptible to two-phase flow instabilities, which have been studied for the last several decades, mainly using numerical simulations and, to some extent, nonlinear stability analysis. These instabilities lead to flow excursions or flow oscillations and have recently been related to various nonlinear phenomena obtained by numerical continuation software. Further research of the instabilities shows that such systems’ behavior is like the FitzHugh-Nagumo (FHN) model. Therefore, the existing two-phase flow model (with some reasonable approximations) is modified into a form identical to the FHN model. It is demonstrated that the modified model reasonably captures the physical attributes of the existing model. Moreover, it is shown that the phenomena described in the FHN model are the same as predicted by earlier models. Since FHN models and their various attributes are relatively well established, they can control the instabilities or operate the two-phase system at desired conditions. The characteristics of the system dynamics with various types of disturbance (instantaneous and periodic) have been investigated. The system provides an unattainable periodicity for periodic perturbation. In comparison, it responds with a single large amplitude or spike dynamics for instantaneous perturbation.

Timber harvest and wildfires drive long-term habitat dynamics for an arboreal rodent

Animals dependent on old, closed-canopy forests may be particularly sensitive to forest disturbances, such as timber harvest and high-severity fires, that may take centuries to recover from. Tracking habitat trends can provide broader context to conservation decisions, including the role of forest disturbance type. We assessed habitat dynamics across the range of the red tree vole (Arborimus longicaudus), a canopy-obligate rodent with low-mobility that typically occurs in old forests. We developed and applied a red tree vole habitat model to imagery data each year across 37 years (1986–2022). We quantified changes in habitat across four regions that differed by land ownership and dominant disturbance type. Overall, habitat declined 18 % since implementation of a major conservation initiative (1994–2022). Habitat change was highest in the northern coast (65 %) where timber harvest was the most common disturbance. Within interior regions, several large wildfires in the previous two decades correlated with a 15 % decline of habitat on federal lands, particularly at the northern range periphery where tree voles were already scarce due to historic disturbances. Recruitment of old forest and subsequent recolonization by red tree voles and other low mobility species after high-severity disturbance can take centuries whereas old forest loss can happen rapidly. Given their strong association with old forest, scarcity within historic disturbance footprints, and relatively limited geographic range, we anticipate red tree voles will remain a species of conservation concern.

A novel hierarchical temperature control method of an electric oven and its experimental evaluation

PurposeOvens are semi-industrial multipurpose equipment that are used to provide a desired temperature for specific chemical processes. Temperature regulation in the presence of different type of disturbances and dealing with nonlinear dynamics with large dead time (up to a few minutes) are some undesirable factors that have to be considered in the controller design procedure of the oven systems. Due to these factors, the classical PID controller tuned using Cohen-Coon or Ziegler–Nichol’s tuning methods often fails to meet satisfactory closed-loop performance.Design/methodology/approachIn this paper, to deal with the limitations on the oven system due to the undesirable factors, a hierarchical automaton-guided form controller has been designed. The proposed controller includes several discrete PI controllers, each of which operates locally in the defined operating regions whose separation idea is specific to this paper. Based on the idea proposed in the separation of regions, the controller’s coefficients tuning rules are extracted prior to any determination. Then, a supervisor controller has assumed the task of switching between local controllers. In the next step, by considering a conceptual model for the oven system and using a candidate Lyapunov function, the stability conditions of closed-loop system are discussed and the necessary conditions for the asymptotic stability are derived. The proposed controller is practically implemented with the help of the Arduino Nano platform.FindingsUsing several experiments, the superiority of the proposed hierarchical controller in terms of performance and energy consumption has been demonstrated.Originality/valueThe proposed hierarchical controller has been implemented practically and an acceptable closed-loop performance has been achieved. To illustrate the efficiency of the proposed method, the closed-loop stability of this method is shown using the Lyapunov theory.

Effects of anthropogenic disturbances on diaspore removal by ants: A meta-analysis

Anthropogenic changes in natural landscapes are identified as a major driver of biodiversity loss worldwide. Consequently, important ecosystem functions, such as seed dispersal by animals, can be lost, which threaten the stability of essential ecological processes. Given the current scenario of large seed disperser's loss, secondary dispersal by ants has been identified as an important alternative to mitigate the impacts caused by human changes. However, empirical evidence shows contradictory effects of anthropogenic disturbances on diaspore removal by ants. Here, we conducted a global meta-analysis from 22 studies (65 comparisons) comparing diaspore removal by ants in disturbed versus preserved areas to investigate general trends to different anthropogenic disturbances. Specifically, we evaluate: (i) the effects of anthropogenic disturbances on diaspore removal by ants comparing temperate and tropical regions, and (ii) comparing different disturbance types (agriculture related disturbances, fragmentation, mining, fire, etc.) on diaspore removal by ants. We found an overall negative effect of anthropogenic disturbances on diaspore removal by ants (26% decrease), both in temperate and tropical regions (38% and 19% decrease, respectively). In addition, diaspore removal by ants responded negatively to disturbances related to fragmentation (24% decrease) and mining (83% decrease). However, we found no evidence of effects in areas subjected to agricultural processes (0.9% decrease). Our findings suggest that human disturbances might compromise crucial early stages to the natural regeneration in ecosystems such the seed dispersal.

Effects of deforestation and forest degradation on ecosystem service indicators across the Southwestern Amazon

The Southwestern Amazon (SWA) is home to one of the Earth́s remaining intact ecosystems and a key provider of continental atmospheric moisture flows. However, the integrity of this region is threatened by global changes in climate and local to regional changes in land-use and land-cover. Here, unlike most Amazonia-land-change research which has focused primarily on deforestation, we evaluated the effects of both deforestation and forest degradation on three Ecosystem Service Indicators (ESIs) – evapotranspiration (ET), land surface temperature (LST), and precipitation (P) – at the local and watershed scale across the SWA between 2003 and 2020. We computed annual and monthly ESI differences over distinct forest conditions and buffers around disturbed areas (degraded or deforested). We also determined the influence of forest disturbance trends on ESI trends at the pixel and watershed level through a Partial Mann-Kendall approach. The results show that ESI differences among different forest conditions are statistically-significant and more pronounced during the dry season. In comparison with intact forest, monthly P rates were up to 25 % lower over any type of disturbance; whereas ET rates were up to 15 % and 48 % lower, and LST rates up to 1.6 °C and 4.4 °C higher, over degraded and deforested areas, respectively. ET and LST edge effects were only significant within buffers around some of the most heavily disturbed areas. At the pixel scale, negative trends in ET and positive trends in both LST and P were more frequently explained by forest disturbances as these trends themselves become more pronounced. ET and LST trends determined by disturbances were generally located near roads, rivers, and human settlements; and surprisingly, we found that degradation more often influences these trends than deforestation, which we attribute to the practice of converting deforested areas into crops whose growing season ET and LST rates are similar to those in natural vegetation. At the watershed scale, the analysis suggested that the climate implications of degradation and deforestation have not scaled up to this level yet; however, literature has shown that even the local impacts we report here can have important implications for areas outside of the SWA, which emphasizes the importance of continuing to conserve this remote region.

Microbial community structural response to variations in physicochemical features of different aquifers.

The community structure of groundwater microorganisms has a significant impact on groundwater quality. However, the relationships between the microbial communities and environmental variables in groundwater of different recharge and disturbance types are not fully understood. In this study, measurements of groundwater physicochemical parameters and 16S rDNA high-throughput sequencing technology were used to assess the interactions between hydrogeochemical conditions and microbial diversity in Longkou coastal aquifer (LK), Cele arid zone aquifer (CL), and Wuhan riverside hyporheic zone aquifer (WH). Redundancy analysis indicated that the primary chemical parameters affecting the microbial community composition were NO3 -, Cl-, and HCO3 -. The species and quantity of microorganisms in the river-groundwater interaction area were considerably higher than those in areas with high salinity [Shannon: WH (6.28) > LK (4.11) > CL (3.96); Chao1: WH (4,868) > CL (1510) > LK (1,222)]. Molecular ecological network analysis demonstrated that the change in microbial interactions caused by evaporation was less than that caused by seawater invasion under high-salinity conditions [(nodes, links): LK (71,192) > CL (51,198)], whereas the scale and nodes of the microbial network were greatly expanded under low-salinity conditions [(nodes, links): WH (279,694)]. Microbial community analysis revealed that distinct differences existed in the classification levels of the different dominant microorganism species in the three aquifers. Environmental physical and chemical conditions selected the dominant species according to microbial functions. Gallionellaceae, which is associated with iron oxidation, dominated in the arid zones, while Rhodocyclaceae, which is related to denitrification, led in the coastal zones, and Desulfurivibrio, which is related to sulfur conversion, prevailed in the hyporheic zones. Therefore, dominant local bacterial communities can be used as indicators of local environmental conditions.

Identification of Large-Scale Travelling Ionospheric Disturbances (LSTIDs) Based on Digisonde Observations

In this paper we analyze Digisonde observations obtained in the European region to specify the effects of large-scale travelling ionospheric disturbances (LSTIDs) on the ionospheric characteristics that define the conditions in the bottomside ionosphere. While this type of disturbances affects all frequency ranges in the F region, the most pronounced effect is detected in the foF2 critical frequency, where the density is the highest. During LSTID activity, a significant uplifting of the F2 layer is observed to accompany an oscillation pattern in the foF2. Concurrent variations in the height of the peak electron density hmF2 and the corresponding scale height, Hm are also observed. These findings are used to propose a new methodology for the identification of LSTIDs, comprising a combination of different criteria. The efficiency of the proposed methodology is tested at middle latitudes during geomagnetically quiet and disturbed intervals as well as during time periods of lower atmosphere forcing affecting the ionosphere.

Experience with anti NMDA receptor antibody encephalitis in a tertiary care hospital in Pakistan

Background and objective: 
 Anti NMDA receptor (Anti-NMDAR) antibody encephalitis is an increasingly recognized form of auto immune encephalitis. The objective of this study was to determine the demographic, clinical and laboratory factors associated with this syndrome. 
 Methods:
 All cases presenting to neurology, Pakistan institute of medical sciences, Islamabad, from June 2017 till January 2020 were reviewed retrospectively. Patients fulfilling the diagnostic criteria for Anti NMDA receptor (Anti-NMDAR) antibody encephalitis were included. All patients were evaluated with cerebrospinal fluid (CSF)routine examination, MRI brain, autoimmune encephalitis profile and for presence of oligoclonal bands (OCB) in CSF. Statistical analysis was done using SPSS version 23.0.
 Results:
 A total of 7 patients were diagnosed as having Anti-NMDARantibody encephalitis. Five patients were female and two were male. Four patients had some type of psychiatric disturbances upon presentation of these behavioral abnormalities and irritability were found in all four. Orofacial abnormal movements were found in four patients while one patient had myoclonic seizures.
 Conclusion:
 Anti-NMDARreceptor encephalitis is a common cause of encephalitis associated with neurological and psychiatric symptoms. Delay in diagnosis can occur due to non-specific symptoms and signs present in early stages of illness,this can lead to long term neurological disability.