Fast Changing Environmental Conditions Research Articles

Differential absorption laser spectroscopy at 8 kHz using precompensated current modulation

We present a differential laser absorption spectroscopy (DLAS) system operating at 1550 nm for rapid and sensitive gas concentration measurements. A dual-wavelength toggling mechanism is presented, which significantly reduces data processing, hence supporting a high update rate and data robustness against fast-changing environmental conditions. We showcase the ability to toggle between two wavelengths separated by 90 pm in 14 μs and with minimal chirp (∼1 pm), facilitating sensitive DLAS measurements at 8 kHz update rate. This performance is achieved by driving a 1550 nm diode laser with a modified square-wave current pulse, overcoming the thermal time constant limited wavelength-modulation response of the diode laser. A sensitive feedback mechanism ensures excellent long-term wavelength stability better than 1.4 pm peak-to-peak at 8 kHz toggling over 20 h. As a performance test, we measured the volumetric ratio (VMR) of hydrogen cyanide (HCN) gas in a fiber-coupled gas cell with less than 0.2% peak-to-peak variation over 20 h at 40 Hz. A best sensitivity in VMR of 8×10−6 was achieved at 25 ms integration time. The simplicity and high update rate of our system make it well-suited for gas monitoring in dynamic atmospheric and industrial environments. Further, it offers potential utility in applications requiring precise wavelength control, such as injection seeding of pulsed lasers. A simple analytical model is derived, which, in detail, supports the experimental results, hence offering a tool for future design optimization.

Empowering Agricultural Ecosystems: Leveraging 5G IoT for Enhanced Product Integrity and Sustainable Ecological Environments

The study explores the change-making potential of 5G IoT technology in improving the security of agro-products and contributing to conservation of environments in the ecological field. Through the process of a series conducted in expression using the real agricultural settings, the study gives a visible proof that food traceability, quality assurance, resource management and environment conservation all gain the significant improvements. By relying on IoT sensors utilizing the latest 5G connectivity, stakeholders can have real-time data analytics and communication to take well-informed decisions, optimize resource usage, and manage the environmental risks. The analytics showed a noticeable boost in product traceability with real-time tracking, temperature monitoring during transportation, and automatic data logging rendering success rates above 95%. Resource management benefits are demonstrated in H2O and fertilizer reduction, reaching 30%, and up to 20% higher yields of crops than is traditional. Ecological conservation results exhibit the improved ecosystem health and the possibility to detect environmental pollution in real-time allows operational conservation measures. The research emphasizes on the prospect of 5G IoT whose benefits might transform agricultural practices and guarantee the authenticity and sustainability of food in the face of fast-changing environmental conditions.

Ultra-Fast and Accurate MPPT Control Structure for Mobile PV System Under Fast-Changing Atmospheric Conditions

Photovoltaic (PV) system efficiency is highly dependent on atmospheric conditions, which are continuously varying. The presence of an efficient maximum power point tracking (MPPT) method suitable for fast-changing environmental conditions, even under partial shading conditions (PSC) is required to optimize the PV system efficiency. This paper proposes a different MPPT control structure, where the MPPT is nested in the proportional-integral (PI) voltage controller routine. By using the proposed control structure. The Analog-to-Digital Converter (ADC) samples are shared between the MPPT algorithm and PI controller. As a result, extreme dynamic tracking improvements while a cost-effective implementation is ensured. Using the proposed control structure, a high-speed MPPT is achieved, making it suitable for mobile PV systems subjected to fast-changing atmospheric conditions. As the tracking accuracy is high, the P&O subroutine usually used in GMPPT methods to maintain the GMPP is eliminated. Results revealed that with the proposed implementation scheme, the tracking speed and the transient energy losses can be four times better than the traditional scheme.

Intersection Point Determination Method: A novel MPPT approach for sudden and fast changing environmental conditions

It is challenging to obtain maximum power output from a Solar Photovoltaic System (SPVS) under uncertain weather conditions due to rapid change in temperature and irradiance. It is achievable through an application of an appropriate Maximum Power Point Tracking (MPPT) technique. The precise tracking of Maximum Power Point (MPP) is crucial for randomly varying irradiance and temperature due to sudden occurrence of clouds and rain during uncertain variable weather conditions. In this paper, an approach based on Intersection Point Determination Method (IPDM) is proposed to effectively track the MPP under such uncertain climatic conditions. It is an iterative method which starts with formation of a rectangle by drawing straight lines parallel to voltage and current axes of I–V curve, subsequently identifies the point of intersection of its diagonals. This identified intersection point is used as the initial point for the next iteration until the convergence is achieved i.e. the new intersection point superimposes the previous point in two successive iterations. The computer simulations have been carried out on a stand-alone (MSX-60) solar PVS of 60W along with a boost converter designed in MATLAB/Simulink. The performance of proposed IPDM technique is tested and compared with other well established MPPT techniques in four distinct theoretical test cases comprises all possible variable weather conditions to ensure its vast applicability. Further, an experimental setup is established in laboratory environment to also validate its performance for the real-life input variables. In which, the maximum and average power outputs are achieved to 50.5598 W and 30.6338 W respectively, for the unfavourable real-life weather conditions i.e. mostly a cloudy day with rainfall and sunshine for short durations. All these simulation results as obtained by all five MPPT methods are statistically validated through t-Tests with 5% of confidence of interval. The statistical analysis proves the superiority of the proposed IPDM technique as compared to the other four competing MPPT techniques. The proposed method is promising in terms of better convergence, fast tracking speed, negligible oscillations, and maximum power output in all possible weather conditions.

German fishery’s adaptation to historic events, Western Baltic Sea, 1890–1950

Marine social-ecological systems (SES) have been providing important cultural, social, and economic services for many centuries. They are, however, increasingly threatened by fast changing environmental, ecological, and socio-economic conditions. As historical marine research is increasingly developing into a multidisciplinary endeavour, it offers outstanding points of departure to analyse historic events and the response and adaptation of the respective SES. Such knowledge helps to inform today’s fisheries management and promotes successful management of changing ecosystems. Here, we compile and analyse historical data (1890–1950) of the German Western Baltic Sea fishery SES. This period is characterised by a series of strong impacts due to political, technological, economic, and ecological changes, such as two world wars, a global economic crisis, and other economic or ecological disasters. In our opinion, potential negative effects of those events were in the past attenuated by the system’s high capacity to adapt. However, most of the fishers´ historic options on how to respond and adapt have recently become no longer available. New threats (e.g. climate change) have emerged instead. We conclude that today’s fisheries management needs to integrate options of adaptation by exhausting all present or future opportunities. Adaptive fisheries management should not only focus on environmental change but need to include socio-economic change as well.

A Different Approach for Maximum Power Point Tracking (MPPT) Using Impedance Matching through Non-Isolated DC-DC Converters in Solar Photovoltaic Systems

This paper presents a maximum power point tracking (MPPT) algorithm in a solar photovoltaic (SPV) system that requires fewer sensors, is easy to implement, and offers a good tracking efficiency and speed. Among various MPPT algorithms found in literature, the perturb and observe (P&O) algorithm is most popular as it required less complex circuitry and is easy to implement, but it suffers against fast-changing environmental conditions mostly in the case of partial shading conditions and requires two sensors, i.e., voltage and current. This paper presents the one sensor-based method based on the modified converter design which eliminates the effect of partial shading conditions as well as the fast-changing environmental condition. The presented MPPT algorithm was implemented and tested using an FPGA-based NI-sbRIO card interfaced with Labview software.

Design and analysis of a novel adaptive learning control scheme for performance promotion of grid-connected PV systems

This paper addresses a hybrid adaptive iterative learning control strategy for controlling power converters that are used in photovoltaic systems to enhance maximum power point tracking capability in the presence of variable atmospheric conditions. The adaptation of the controller to the fast-changing environmental conditions is provided by a fractional-order proportional-integral type learning control mechanism. The developed control scheme is integrated into a grid-connected current-source flyback inverter to highlight the improvements in performance criteria such as convergence speed during transients, tracking accuracy, steady-state oscillations, and robustness. The performance analyses are carried out under various scenarios. The obtained results reveal that the dynamic response of the system is considerably increased under erratic atmospheric conditions while steady-state oscillations are decreased for stable operation conditions. The maximum absolute error that indicates the robustness of the proposed controller is decreased from 2.3704 to 2.1920. In addition, the error deviations of the proposed control algorithm are below 10%. The variance of the error, which shows steady-state stability, is reduced from 2.5123 to 1.6152. Also, the proposed controller reduces the amount of control energy by 20% when compared to the PI controller. Furthermore, the values of IAE and ISE are reported 10% lower in the proposed controller.

Water Cycle Algorithm (WCA): A New Technique to Harvest Maximum Power from PV

Renewable energy or alternative energy is extracted through renewable resources. These are considered as an alternative from conventional fossil fuel-based sources because conventional energy sources are depleting rapidly and raised concerns over increasing environmental impacts. Among many renewable sources, solar energy has a substantial part to meet the increased energy demand with reduced environmental effects. Solar irradiance and temperature are key factors upon which photovoltaic (PV) power generation depends but its optimum operating point gets affected by variation in the above-mentioned environmental factors. Finding the optimum operating point is a challenge due to the nonlinear solar behavior and varying nature of environmental conditions. To overcome these challenges, maximum power point (MPP) searching algorithms are exploited to get optimum power from the PV energy system. Maximum power point tracking (MPPT) behavior is different for various weather conditions, for instance, partial shading (PS), and uniform irradiance (UI) conditions. Numerous MPPT methods came to be used to find the optimum power. This work deals with the development of a novel technique for MPP finding of a PV system on the basis of the Water Cycle Algorithm (WCA) under PS conditions. It turns out to be good in terms of exploration and exploitation. Thus, it has the capability to avoid getting stuck in local minima (LM) and to find the global maxima (GM). The performance of the WCA technique is examined on four different types of P-V patterns for UI, PS and fast changing environmental conditions through MATLAB simulation and experimental setup. The findings of WCA are compared with the previous well-known soft computing methods such as PSO, ACS, DFO, and conventional method P&O to evaluate performance. The outcomes reveal that the WCA algorithm overtakes P&O from the perspective of robustness, accuracy, efficiency, and stability, as well as PSO in respect of converging speed and efficiency.

English

This review paper attempts to give account of how plant characterization assists the availability of information on desirable plant traits, to enhance selective breeding for environmental stresses and thus attain sustainable forage production. Plant characterization is referred to as an account for heritable characters varying from agronomical, morphological to molecular markers.  It simplifies grouping of accessions, development of core collections, identification of gaps and retrieval of valuable germplasm for breeding programmes resulting in better insight about the composition of the collection and its genetic diversity. Plant characterization by morphological, physiological and agronomic traits has long been used in selective breeding. Advancement of characterization to the use of molecular markers speed up the process and permits optimal utilization of the adaptive traits harboured in all breeds for stressful environments. In countries like Tanzania, where agro-climatic conditions are challenging, technological progress is slow and market institutions are poorly developed, selecting highly adaptive local varieties is important. Knowledge from characterization of local varieties could be used to breed adaptive and resilient varieties. This will help the farmers to produce enough forage in the fast changing and stressful environmental conditions.   Key words: Characterization, Cenchrus ciliaris, drought, salinity, traits.

Short Communication: The presence of Bull shark Carcharhinus leucas (Elasmobranchii: Carcharhinidae) in the fresh waters of Sumatra, Indonesia

Abstract. Hasan V, Widodo MS. 2020. Short Communication: The presence of Bull shark Carcharhinus leucas (Elasmobranchii: Carcharhinidae) in the fresh waters of Sumatra, Indonesia. Biodiversitas 21: 4433-4439. A single subadult specimen of Bull shark Carcharhinus leucas was photographed and captured by local fisherman using casting net on June 2020 in the upper Indragiri River, Riau Province, Indonesia. Carcharhinus leucas are one of only a few species of elasmobranchs that live in both marine and freshwater environments. This species currently listed as a near-threatened species based on the IUCN Red List Status. Singel specimen identified as C. leucas by the coloration of fresh specimen: white belly and greyish back, first dorsal fin high, tip of second dorsal and caudal fins black. Meristic characters measurement results as follows: total length 102 cm; fork length 86.3 cm; preanal length 65.1 cm; pre pelvic length 51.9 cm; pre pectoral length 22.5 cm; pre-orbital length 8.3 cm; head length 25 cm; pre-first dorsal length 29.4 cm; pre-second dorsal length 56 cm, and pre-caudal length 78.1 cm. This photo is considered as the third record from freshwaters of Sumatra after in the Batang Hari River, Jambi Province in 1997, and in the Musi River, South Sumatra Province in 2019. The photographic records indicate that a single specimen of C. leucas was found in the upper Indragiri River recorded more than 150 km inland. These results enhanced the understanding of C. leucas distribution in Sumatra freshwaters. Monitoring is needed to assess the possibility of the importance of the upper Indragiri River as a migration route, nursery, and growth ground of C. leucas. Studying small scale habitat use of C. leucas is challenged by their preferred habitats in freshwaters environments with fast-changing environmental conditions. Water conditions in the upper Indragiri River, namely salinity 0‰, temperature 25-27°C, dissolved oxygen 3.9-11.1 mg/l, are ideal for A. leucas habitat.

Physiological Capabilities of Cryoconite Hole Microorganisms.

Cryoconite holes are miniature freshwater aquatic ecosystems that harbor a relatively diverse microbial community. This microbial community can withstand the extreme conditions of the supraglacial environment, including fluctuating temperatures, extreme and varying geochemical conditions and limited nutrients. We analyzed the physiological capabilities of microbial isolates from cryoconite holes from Antarctica, Greenland, and Svalbard in selected environmental conditions: extreme pH, salinity, freeze-thaw and limited carbon sources, to identify their physiological limits. The results suggest that heterotrophic microorganisms in cryoconite holes are well adapted to fast-changing environmental conditions, by surviving multiple freeze-thaw cycles, a wide range of salinity and pH conditions and scavenging a variety of organic substrates. Under oxic and anoxic conditions, the communities grew well in temperatures up to 30°C, although in anoxic conditions the community was more successful at colder temperatures (0.2°C). The most abundant cultivable microorganisms were facultative anaerobic bacteria and yeasts. They grew in salinities up to 10% and in pH ranging from 4 to 10.5 (Antarctica), 2.5 to 10 (Svalbard), and 3 to 10 (Greenland). Their growth was sustained on at least 58 single carbon sources and there was no decrease in viability for some isolates after up to 100 consecutive freeze-thaw cycles. The elevated viability of the anaerobic community in the lowest temperatures indicates they might be key players in winter conditions or in early melt seasons, when the oxygen is potentially depleted due to limited flow of meltwater. Consequently, facultative anaerobic heterotrophs are likely important players in the reactivation of the community after the polar night. This detailed physiological investigation shows that despite inhabiting a freshwater environment, cryoconite microorganisms are able to withstand conditions not typically encountered in freshwater environments (namely high salinities or extreme pH), making them physiologically more similar to arid soil communities. The results also point to a possible resilience of the most abundant microorganisms of cryoconite holes in the face of rapid change regardless of the location.

Dynamic response of East Asian Greater White-fronted Geese to changes of environment during migration: Use of multi-temporal species distribution model

Understanding how migratory species select habitats is essential for applied ecology and biological conservation. Although migratory species move across a wide range of environments during migration, their dynamic response to environments has rarely been considered. Taking advantage of the fine spatial-temporal resolution of satellite tracking data, we studied habitat selection of East Asian greater white-fronted geese (Anser albifrons) along their spring migration route from Yangtze River Basin to Lena Delta and Yana Bay. We developed a novel methodology to improve dynamic species distribution models (SDMs) by incorporating environmental variables derived from remotely sensed data precisely corresponding to migration time. Our results demonstrate that distance to the nearest water body, elevation, human population density and temperature contribute greatly to the models. Water-related and topographic factors (e.g., elevation, slope and distance to the nearest water body) were consistently associated with habitat selection of the geese from wintering area to breeding area, while the varied influences of temperature and human population density in different migration periods are closely related to their adaptation to local environments. In addition, response curves of vegetation index indicate that the geese are more strongly associated with food quality than quantity in wintering area and stopover sites. By building SDMs in different periods, we provide a unique dynamic perspective on how a long-distance migrant responds to different environments. The methodology proposed here could be integrated to future conservation management plans for predicting species relationship with fast changing environmental conditions.

Learning Automata based fuzzy MPPT controller for solar photovoltaic system under fast changing environmental conditions

Learning Automata based fuzzy MPPT controller for solar photovoltaic system under fast changing environmental conditions

The Modified Risk Factors of Health Heads of the Medical Organizations

Purpose: study and evaluation of modifiable potential risk factors of health of heads of medical organizations in terms of structural and technological modernization of the health system, the growing need for highly qualified management personnel. Efficiency of activity of medical associations largely due to the level of health managers, allowing to solve problems of activities of medical organizations in the modern fastchanging environmental conditions. Based on international experience and our own research the authors identified features of the state of health of heads of medical organizations, and the degree of exposure to risk factors for no communicable diseases; considered approaches to assess motivation and psychological readiness to promote the health and potential of managerial personnel in the formation of health-saving behavior. Methods: in the present study, the following methods were used: systemic approach, content analysis, methods of social diagnosis (questionnaires, interviews), comparative analysis, method of expert evaluations, and method of statistical processing of information. Results: reviewed and proposed approaches to use preventive measures prevention of risk factors of non-communicable diseases healthcare leaders, forming health-preserving behavior. Conclusions and Relevance: in modern scientific studies on the health of medical workers, including heads of medical institutions, defined the modern methodological approaches to formation of health-saving behavior and maintaining healthy lifestyle health care workers. Despite the high awareness of heads of medical organizations in the area of influence of risk factors on health, accessibility of medical care for the diagnosis and correction of risk factors of chronic no communicable diseases, risk factors of health among healthcare leaders have sufficient prevalence. Health-promoting behavior model is not a conscious lifestyle leader and formed as a reaction if you have symptoms of health disorders. Among the leaders of medical organizations appears typical for the whole population the situation: lack of awareness of the true state of their health, the presence of manifestations of the negative impact of modifiable risk factors of health, low motivation and psychological readiness for health promotion. The necessary intensification of actions aimed at shaping the attitudes of the heads of medical institutions for their health as the managed category healthy behavior. The health of the heads of medical institutions affect the efficiency of healthcare organizations and is reflected in the quality of medical care provided to the population.

Dual surface sliding mode controller for photovoltaic systems enhanced by a ripple domain search maximum power point tracking algorithm for fast changing environmental conditions

In this research, a dual surface sliding mode controller is proposed and implemented to increase robustness and speed of boost converter, its asymptotic response is proved in the presence of disturbances. In addition, a filtered mapping pulse width modulation technique is developed to attenuate the chattering problem caused by finite frequency switching. Ripple domain search (RDS), a precise maximum power point tracking (MPPT) algorithm, is suggested to find the maximum power point (MPP) in photovoltaics. RDS uses the inherent ripple problem of the converter as a tool for finding MPP. By combining the proposed fast controller and the RDS algorithm, a fast and robust MPPT technique is obtained, which is simple to implement, eliminates the need for initial parameter tuning and is free from oscillations. Moreover, the proposed controlling method and MPPT algorithm are tested using Mitsubishi Electric MF170W module and their efficiency is compared with conventional methods (including P & O) in fast irradiation changing conditions. The proposed method harvests a 6% higher power than P & O and constant voltage. Compared with incremental conductance 24% more power is harvested. Finally, the practicality of the controller and algorithm was experimentally validated with a prototype system using a 5 W Evergreen module.

In Murky Waters: Crittercam on Juvenile Bull Sharks (Carcharhinus leucas)

AbstractAssessing bull shark (Carcharhinus leucas) behavior is relevant for conservation and risk management. However, information on bull sharks—in particular, behavior of juveniles—is very limited in some parts of the world. Studying small-scale habitat use of juvenile bull sharks is challenged by their preferred habitats in estuarine environments with fast-changing environmental conditions. A number of advanced methods including acoustic telemetry, baited remote underwater video, and satellite tagging have been used to shed light on habitat utilization, food preferences, and movement. We tested the application of an underwater video camera recorder (“Crittercam”) combined with acoustic tags on three juvenile bull sharks during daytime and nighttime deployments and demonstrated the feasibility and limitations of this technique for juvenile bull shark research. All three tagged individuals used deeper channels (>5 m) moving alongside the river bank in a crisscross manner. We used additional information on habitat type and depth to support the findings. Our results provide important insights for future tagging studies combining tagging technologies to monitor bull sharks in coastal environments.

Trait plasticity in species interactions: a driving force of community dynamics

Evolutionary community ecology is an emerging field of study that includes evolutionary principles such as individual trait variation and plasticity of traits to provide a more mechanistic insight as to how species diversity is maintained and community processes are shaped across time and space. In this review we explore phenotypic plasticity in functional traits and its consequences at the community level. We argue that resource requirement and resource uptake are plastic traits that can alter fundamental and realised niches of species in the community if environmental conditions change. We conceptually add to niche models by including phenotypic plasticity in traits involved in resource allocation under stress. Two qualitative predictions that we derive are: (1) plasticity in resource requirement induced by availability of resources enlarges the fundamental niche of species and causes a reduction of vacant niches for other species and (2) plasticity in the proportional resource uptake results in expansion of the realized niche, causing a reduction in the possibility for coexistence with other species. We illustrate these predictions with data on the competitive impact of invasive species. Furthermore, we review the quickly increasing number of empirical studies on evolutionary community ecology and demonstrate the impact of phenotypic plasticity on community composition. Among others, we give examples that show that differences in the level of phenotypic plasticity can disrupt species interactions when environmental conditions change, due to effects on realized niches. Finally, we indicate several promising directions for future phenotypic plasticity research in a community context. We need an integrative, trait-based approach that has its roots in community and evolutionary ecology in order to face fast changing environmental conditions such as global warming and urbanization that pose ecological as well as evolutionary challenges.

Optimized Maximum Power Point Tracker for Fast-Changing Environmental Conditions

This paper presents a high-performance maximum power point tracker (MPPT) optimized for fast cloudy conditions, e.g., rapidly changing irradiation on the photovoltaic panels. The rapidly changing conditions are tracked by an optimized hill-climbing MPPT method called dP-P&O. This algorithm separates the effects of the irradiation change from the effect of the tracker's perturbation and uses this information to optimize the tracking according to the irradiation change. The knowledge of the direction of the irradiation change enables the MPPT to use different optimized tracking schemes for the different cases of increasing, decreasing, or steady irradiance. When the irradiance is changing rapidly this strategy leads to faster and better tracking, while in steady-state conditions it leads to lower oscillations around the MPP. The simulations and experimental results show that the proposed dP-P&O MPPT provides a quick and accurate tracking even in very fast changing environmental conditions.

A New Algorithm for Rapid Tracking of Approximate Maximum Power Point in Photovoltaic Systems

This paper presents a new algorithm for tracking maximum power point in photovoltaic systems. This is a fast tracking algorithm, where an initial approximation of maximum power point is (MPP) quickly achieved using a variable step-size. Subsequently, the exact maximum power point can be targeted using any conventional method like the hill-climbing or incremental conductance method. Thus, the drawback of a fixed small step-size over the entire tracking range is removed, resulting in reduced number of iterations and much faster tracking compared to conventional methods. The strength of the algorithm comes from the fact that instead of tracking power, which does not have a one-to-one relationship with duty cycle, it tracks an intermediate variable /spl beta/, which has a monotonically increasing, one-to-one relationship. The algorithm has been verified on a photovoltaic system modeled in Matlab-Simulink software. The algorithm significantly improves the efficiency during the tracking phase as compared to a conventional algorithm. It is especially suitable for fast changing environmental conditions. The proposed algorithm can be implemented on any fast controller such as the digital signal processor. All the details of this study are presented.