Minor Loss Research Articles

Bioinspired Synthesis of Silver Nanoparticles for the Remediation of Toxic Pollutants and Enhanced Antibacterial Activity.

This research presents a novel and environmentally friendly approach for the synthesis of multifunctional nanobiocomposites for the efficient removal of toxic heavy metal and dye, as well as the disinfection of wastewater microorganisms. The nanobiocomposites (KAC-CS-AgNPs) were prepared by incorporating photochemically generated silver nanoparticles (AgNPs) within a chitosan (CS)-modified, high-surface-area activated carbon derived from kenaf (KAC), using a unique self-activation method. The even distribution of AgNPs was visible in the scanning electron microscopy images and a Fourier transform infra red study demonstrated major absorption peaks. The experimental results revealed that KA-CS-AgNPs exhibited exceptional adsorption efficiency for copper (Cu2+), lead (Pb2+), and Congo Red dye (CR), and showed potent antibacterial activity against Staphylococcus aureus and Escherichia coli. The maximum adsorption capacity (mg g-1) of KAC-CS-AgNPs was 71.5 for Cu2+, 72.3 for Pb2+, and 75.9 for CR, and the adsorption phenomena followed on the Freundlich and Langmuir isotherm models and the second-order kinetic model (R2 > 0.99). KAC-CS-AgNPs also exhibited excellent reusability of up to four consecutive cycles with minor losses in adsorption ability. The thermodynamic parameters indicated that the adsorption process was spontaneous and endothermic in nature. The bacterial inactivation tests demonstrated that KAC-CS-AgNPs had a strong bactericidal effect on both E. coli and S. aureus, with MIC calculated for E. coli and S. aureus as 32 µg mL-1 and 44 µg mL-1, respectively. The synthesized bioinspired nanocomposite KAC-CS-AgNPs could be an innovative solution for effective and sustainable wastewater treatment and has great potential for commercial applications.

Investigating crowd logistics platform operations for local food distribution

PurposeShort food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).Design/methodology/approachA decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.FindingsResults show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.Originality/valuePlatform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.

Biased-Power Allocation and Shared-Antenna Selection Techniques for Spatial Modulation-Based Layer Division Multiplexing Systems

This study proposes two approaches for improving the effectiveness of spatial modulation integrated into layer division multiplexing (SM-LDM) in broadcasting systems: biased-power allocation (Bi-PA) and shared antenna selection (SAS). Even though different data rates are employed in SM-LDM systems, Bi-PA enhances bit error rate (BER) fairness across layers. The ideal power ratios are adaptively determined by balancing signal-to-interference plus noise ratios with a preference for the lower layer (LL) that involves a higher modulation order. SAS alleviates the complexity of successive interference cancellation and enhances spectral and energy efficiencies. Both the LL and upper layer (UL) share the antenna selection decision and transmit using a single antenna. The UL carries a space shift keying signal while the entire power is allocated for the LL. We analyze the spectral efficiency for the SAS-based SM-LDM system with finite alphabet inputs. Numerical results demonstrate the advantages of the proposed approaches. Compared to pre-assigned-PA (Pre-PA), Bi-PA shows nearly identical BERs for both layers and solves the error floor problem. The sharing property and common layer transmission of SAS-based SM-LDM yield a significant BER reduction relative to conventional SM-LDM. It provides gains ranging from 7 to 15 dB for LL at BER equal to 10−3, while UL performance ranges from slight gain to minor loss. Furthermore, both Bi-PA and SAS techniques enhance the achievable LL rate and sum-rate at low and intermediate signal-to-noise ratio values. They can achieve an improvement of up to two bits in LL rate and less than one bit in sum-rate at a signal-to-noise ratio of −0.5 dB. These findings show that both proposed techniques have a considerable impact on enhancing the fairness, BER performance, and feasible rates of SM-LDM systems, making them promise for broadcast system designs.

Improving the detection efficiency of IRAND based on machine learning

The challenges in detecting antineutrinos by segmented antineutrino detectors (AD) pushed us to get more exact results using new methods, including data mining and machine learning (ML). In this research, IRAND (a segmented plastic scintillator IRan ANtineutrino Detector; a 10×10 array of plastic scintillation) has been simulated using Geant4 Toolkit. Several features of energy deposition including behavior of time, energy, position have been collected and stored in detail from each event to provide the complete dataset with a minor loss for use in powerful ML packages. We utilized a variety of classifiers in ML in which Random Forest shows the best performance. Also, a Geant4-based dedicated code (IRAND-Sim) has been provided for IRAND.

Model comparison and effect of flow and accessories on the pressure drop of the unit ff-df-270/el of Universidad de Cartagena

The effect of flow variation on the theoretical calculation of pressure drop in pipes with fittings in the unit FF-DF-270/EL of the Universidad de Cartagena was studied, determining the coefficient of minor losses (Kf) caused by 45° and 90° elbows, and three types of valves, using water as the process fluid. The flow rate (Q) was varied, using a valve, between 24, 20, 16, 12 L/min. Darcy's and Bernoulli's theorem methods were used to evaluate friction losses. Were found minimum error percentages of 0.04% and maximum 8.16%; loss coefficients adjusted by minimum squares were obtained with R2 of 0.999, comparing these Kf with the values reported in the plant manual and different authors. It was shown experimentally that the loss coefficient depends on each fitting, allowing the calculation of the theoretical pressure drop and comparing it with the experimental pressure drop, demonstrating that as the flow increases, an increase in pressure drop is generated. With the methodology applied in this research, the aim is to optimize pressure drop tests with fittings, and identify the characteristics of the pipe to obtain an optimum lower loss coefficient value.

Which patient benefit most from minimally invasive direct anterior approach total hip arthroplasty in terms of perioperative blood loss? A retrospective comparative study from a cohort of patients with primary degenerative hips

IntroductionTotal hip arthroplasty (THA) is a successful surgery, but despite the advancements in anesthesiology and orthopedics, sometimes blood transfusions are required to manage the anemia due to the blood loss, involving a substantial number of patients. The aim of this retrospective comparative study is to define how the choice of the surgical approach, either direct anterior (DA) or posterolateral (PL), may influence the postoperative blood loss and the need for transfusion in THA.Materials and methodsData collection was carried out retrospectively of THAs performed between 2016 and 2021 on primary hip osteoarthritis treated by DA or with PL approach. Clinical and perioperative anesthetic data were collected. Preoperative hemoglobin levels were compared with the lowest detected level by calculating ΔHb (hemoglobin decrease). Then, data from the two groups were cross-checked: duration of surgery, whether premedication with tranexamic acid, duration of the hospitalization, rate of need for hemotransfusions, and amount of blood transfused. The two samples were subdivided into subgroups according to age, BMI, tranexamic acid prophylaxis, and chronic treatment with drugs that alter coagulative properties.ResultsTime of surgery was longer for patients treated with DA access (mean DA: 78.8 min; mean PL: 74.8 min; p: 0.05; 95% CI), but the length of hospitalization was shorter for patients treated with DA group with a mean time of 6.23 days versus 7.12 days for the PL group (p < 0.01). DA THA resulted advantageous mainly in patients between 66 and 75 years, showing a reduced postoperative transfusion requirement in the postoperative period (DA: 13.43%—mean: 1.33 units; PL: 26.82%—mean: 1.18 units; p: 0.044, 95% CI). Patients that assume blood-altering drugs showed a higher transfusion rate (p < 0.01), but comparison of the two subgroups showed that the choice of the surgical approach did not significantly affect the transfusion rate in these patients (p: 0.512). Prophylaxis with tranexamic acid reduced the transfusion rate (p < 0.01).ConclusionPatients treated by minimally invasive direct anterior approach undergo a significantly shorter hospitalization. From the analysis of patient’s subgroups those aged between 66- and 75-years benefit from the DA approach mainly for the minor blood loss with less frequent transfusion requirement.

Analysis of Centrifugal Pump Machine Performance Using the Overall Equipment Effectiveness (OEE) Method (Case Study: PT. XYZ)

Improving performance in a company is a key factor in increasing efficiency and productivity. However, often the improvement efforts made are ineffective because they do not address the root cause of the problem. The Total Productive Maintenance (TPM) concept with its components can clearly identify the root cause of the problem and its contributing factors, allowing improvements to be focused on the appropriate aspects. One method of measuring machine performance used is Overall Equipment Effectiveness (OEE), which calculates factors such as availability, performance efficiency, and quality level. In a case study at PT.XYZ, OEE was used to analyze the performance of distribution pump machines. During the period of August 2022, the OEE value for each pump machine reached 99%, which exceeded the world-class OEE of 85%. However, the analysis showed that Idling Minor Stop Losses was the main cause of losses that affected machine effectiveness, with a percentage of losses reaching 82%.

Optimization of Water Pipe Network and Formulation of Pumping Rate

Minimizing water delivery costs and increasing water supply dependability are the two key objectives in designing and operating of water distribution systems. An analytical solution for the best pipe diameters of a water distribution pipe network was created in this study. The raw water was collected from a water canal and transported to a treatment plant (WTP). The cleansed water was pushed into the water distribution network via the pumping station. The derivative approach was used in the optimization process, and the cost functions incorporating the various capital and operating expenses were used. The initial diameters were adjusted to reach the least-cost diameters. The study shows that the optimum design of a pipe network (PNW) achieves saving a total cost of about 12.3% after utilizing our unique method. The optimal pumping rate in the PNW can also be determined using an analytical approach that considers the optimum value that occurs when the minor and friction losses in the entire network are at their lowest. The analytical solution for the optimum pumping rate shows a rigid value of optimum pumping rate (Qopt) which is 5296.32 m3/day. On comparative estimates, this figure is very close to that of 5,300 m3/day interpreted from the graphical solution, with negligible deviation. The total cost and optimum pumping rate results for the analyzed PNW example demonstrate the correctness of the analytical solutions, reliability, and dependability of the assumptions.

QoS-Aware Precoding in Downlink Massive MIMO LEO Satellite Communications

Satellite communications (SATCOM) are essential parts of future wireless networks and are moving towards standardization in 6G. Low Earth Orbit (LEO) SATCOM show significant performance gain in global wireless access services, due to their minor path loss and short propagation delay, compared with other SATCOM counterparts. A quality of service (QoS)-aware precoding design is presented in this work to enhance the performance of massive multiple-input multiple-output (MIMO) LEO SATCOM. In particular, we set up a multi-objective optimization problem to balance the system energy efficiency (EE) and the percentage of users achieving their QoS requirements. An efficient algorithm is developed for obtaining the precoding vectors. Numerical results show that the proposed algorithm leads to a larger percentage of users achieving their QoS requirements and brings improvements in EE performance, compared with conventional approaches.

Using Federated Learning for Collaborative Intrusion Detection Systems

Neural networks have become cutting edge machine learning models for detecting network attacks. Traditional implementations provide fast and accurate predictions, but require centralised storage of labelled historical data for training. This solution is not always suitable for real-world applications, where regulatory constraints and privacy concerns hamper the collection of sensitive data into a single server. Federated Learning has recently been proposed as a framework for training a centralised model without the need to share data between different providers. We use the CICIDS2017 dataset provided by the Canadian Institute of Cybersecurity to demonstrate the benefits of Neural Networks-based Federated Learning for the detection of the most relevant types of network attacks. We conclude that a federated-trained neural network outperforms locally-trained models (at isoarchitecture) in terms of F1-score and False Negative detection ratio. Further, such model has a minor loss of performance and convergence rapidity compared to a model trained over a hypothetical centralised dataset.

Application of the Total Productive Maintenance to Increase the Overall Value of Equipment Effectiveness on Ventilator Machines

A ventilator machine is a medical device that plays an important role in handling Covid-19 cases during a pandemic. Covid 19 patients are arriving at a referral hospital in Jakarta, meaning that the hospital must prepare its medical equipment, including a ventilator machine. The ventilator machine experienced problems because the efficiency of the machine decreased so many patients waited in the ICU room. Machine effectiveness has an average value of 62.26% so it has an impact on disrupting patient services at home. The purpose of this research is to look for factors that cause the lack of effective value of ventilator machines and find effective solutions to increase the effectiveness of ventilator machines so that they can serve Covid-19 patients during a pandemic. This research method combines Focus Group Discussion in determining 5W+1H and implementing the pillars of Total Productive Maintenance to improve the Overall Effectiveness of Equipment on Ventilator machines. This study found a breakdown factor of 54.10%, idle and minor loss of 41.20%, and others of 4.70%. The effect of overall improvement has been able to increase the average effectiveness value by 85.00% from Sep 2021-Feb 2022, so this is supported by the hospital's program in terms of increasing the effectiveness of machines in patient care.

Comparison of Sodium Selenite and Selenium-Enriched Spirulina Supplementation Effects After Selenium Deficiency on Growth, Tissue Selenium Concentrations, Antioxidant Activities, and Selenoprotein Expression in Rats.

Selenium contributes to physiological functions through its incorporation into selenoproteins. It is involved in oxidative stress defense. A selenium deficiency results in the onset or aggravation of pathologies. Following a deficiency, the repletion of selenium leads to a selenoprotein expression hierarchy misunderstood. Moreover, spirulina, a microalga, exhibits antioxidant properties and can be enriched in selenium.. Our objective was to determine the effects of a sodium selenite or selenium-enriched spirulina supplementation. Thirty-two female Wistar rats were fed for 12 weeks with a selenium-deficient diet. After 8 weeks, rats were divided into 4 groups and were fed with water, sodium selenite (20 μg Se/kg body weight), spirulina (3 g/kg bw), or selenium-enriched spirulina (20 μg Se/kg bw + 3 g spirulina/kg bw). Another group of 8 rats was fed with normal diet during 12 weeks. Selenium concentration and antioxidant enzyme activities were measured in plasma, urine, liver, brain, kidney, heart, and soleus. Expression of GPx (1, 3), Sel (P, S, T, W), SEPHS2, TrxR1, ApoER2, and megalin were quantified in liver, kidney, brain, and heart. We showed that a selenium deficiency leads to a growth delay, reversed by selenium supplementation despite a minor loss of weight in week 12 for SS rats. All tissues displayed a decrease in selenium concentration following deficiency. The brain seemed protected. We demonstrated a hierarchy in selenium distribution and selenoprotein expression. A supplementation of sodium selenite improved GPx activities and selenoprotein expression while a selenium-enriched spirulina was more effective to restore selenium concentration especially in the liver, kidney, and soleus.

Rapamycin treatment increases survival, autophagy biomarkers and expression of the anti-aging klotho protein in elderly mice.

Previous investigations have demonstrated that treatment of animals with rapamycin increases levels of autophagy, which is a process by which cells degrade intracellular detritus, thus suppressing the emergence of senescent cells, whose pro-inflammatory properties, are primary drivers of age-associated physical decline. A hypothesis is tested here that rapamycin treatment of mice approaching the end of their normal lifespan exhibits increased survival, enhanced expression of autophagic proteins; and klotho protein-a biomarker of aging that affects whole organism senescence, and systemic suppression of inflammatory mediator production. Test groups of 24-month-old C57BL mice were injected intraperitoneally with either 1.5 mg/kg/week rapamycin or vehicle. All mice administered rapamycin survived the 12-week course, whereas 43% of the controls died. Relative to controls, rapamycin-treated mice experienced minor but significant weight loss; moreover, nonsignificant trends toward decreased levels of leptin, IL-6, IL-1β, TNF-α, IL-1α, and IGF-1, along with slight elevations in VEGF, MCP-1 were observed in the blood serum of rapamycin-treated mice. Rapamycin-treated mice exhibited significantly enhanced autophagy and elevated expression of klotho protein, particularly in the kidney. Rapamycin treatment also increased cardiomyocyte Ca2+ -sensitivity and enhanced the rate constant of force re-development, which may also contribute to the enhanced survival rate in elderly mice.

Proposed frequency decoupling-based fuzzy logic control for power allocation and state-of-charge recovery of hybrid energy storage systems adopting multi-level energy management for multi-DC-microgrids

This paper proposes a decentralized multiple-Direct-Current-Microgrid (multi-DCMG) system to supply affordable load demands while addressing challenges posed by Hybridized-Energy-Storage-Systems (H-ESS) limitations, consumption/generation complexities, and renewables volatility. The paper's contributions include a system feasibility assessment for isolated users and a demonstration of the effectiveness of the control strategies adopted. To improve system resiliency and reliability, the proposed system adopts a high-control level for energy/power balances, using a Mamdani 50 rule-based Fuzzy Logic energy management system (FL-EMS) to supervise State-of-Charge (SoC) recovery. The low-control level manages/supervises DC-DC power converters' powers adopting Proportional-Integral (PI), Hysteresis-Current-Controller (HCC), and Linear-Quadratic-Regulator (LQR) in closed-Control-loops, besides an advanced low-pass-filtering (A-LPF) for load frequency decoupling. The results show that the proposed H-ESS outperformed single-ESS systems in dynamic load changes and renewables' uncertainty, and supercapacitors improved load supply, voltage regulation, and current tracking. However, expensive costs and slow restoration of H-ESS banks from critical SoCs are major drawbacks. The global system assessment demonstrated promising results through proper FL-EMS setpoint computation, stable Bus voltage with 0.55–6.9% deviations due to robust controllers, accurate SoC recovery of HESS batteries at critical SoCs (<10% and >90%), fast and accurate convergence with 3.35–3.37% mismatch, and 99.3% supply efficiency at minor power losses of 0.7–1.55%.

Projected long-term effects of colorectal cancer screening disruptions following the COVID-19 pandemic.

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in colorectal cancer (CRC) outcomes due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term CRC outcomes was measured by the number of life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in CRC outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

Sprouting Inhibition after CIPC Spraying on Early and Mid-season Potato Varieties during Storage in Semi-underground Warehouse at Room Temperature in Summer

This study was carried out to determine the sprouting period of early and mid-season varieties, which includes ‘Atlantic’, ‘Chubaek’, and ‘Superior’, during the summer storage period in a semi-underground warehouse without cooling system. And also it was investigated the effect of chlorpropham [Propan-2-yl N-(3-chlorophenyl)carbamate, CIPC] treatment on the sprouting inhibition for the varieties. This study was conducted to figure out a sprout inhibitory effect when CIPC was applied to 1kg of the potato tubers at concentrations of 10 mg and 20 mg which are lower than the treatment concentrations of ca 30 mg prescribed by the positive list system (PLS). The internal temperature of the warehouse used in this experiment was lowered by 5°C or more than the outside temperature. The difference between the lowest and highest temperature during the experiment throughout the day was 5°C. It showed the effect of reducing to 1/2 of the difference in outdoor temperature. As for the sprouting of potatoes, the extremely early variety ‘Chubaek’ sprouts appeared at the 6th week of storage of control and it was the fastest sprouting potato among the control groups of the varieties. Sprouting began to appear in the Superior at the 6th week of storage, while the ‘Atlantic’ sprouted at the 8th week of storage. The appearance of sprouts was suppressed in all treatment groups of ‘Atlantic’ and ‘Superior’ varieties in CIPC treatments. Sprouts were observed in all treatment groups of ‘Chubaek’ after the 7th week, but the elongations of the sprouts in tubers were completely inhibited until the 8th week of storage. ‘Atlantic’ and ‘Superior’ seemed to have a sprouting inhibitory effect even with a low CIPC concentration of 10 mg·kg-1, with the exception of extremely early variety ‘Chubaek’ that breaks out of the dormancy quickly. Although weight loss occurred continuously during storage, it was minor loss of 0.7-1.6%. There was no consistent trend for changes of the loss in the varieties and CIPC treatments. Most common pathological disorder was the dry rot during the experiment, but only few were affected. The use of the tubers treated at 18°C and 90% RH for 10 days and the rack of refrigeration system which lead to lack of convection seemed to have suppressed the spread of pathogens.

Diagnosis, Treatment, and Prevention of Sport-related Concussion

Concussion is a serious injury with potential long-term cognitive complications. Due to the prevalence of undiagnosed concussions and their detriments to health, concussion treatment and prevention are important topics of exploration. By investigating concussion diagnosis and management, the types of treatment, and preventive methods, this study demonstrates the positive role of active rehabilitation in concussion management. It presents opportunities for future studies to focus on more specific types of exercise and possible rule regulations. Results show that concussion symptoms may vary according to severity, from minor headaches and loss of concentration to depression, dementia, and impaired cognitive function. Clinical or syndromic concussion diagnosis is the most used and reliable subjective assessment method in the contemporary health and scientific field. Immediate removal from sport and vigorous exercise is crucial after athletes experience a concussion to avoid exacerbating the symptoms or causing an additional concussion. Contrary to the belief of complete rest after a concussion, early sub-symptom aerobic exercise and a gradual return to sports participation are important and effective measures for concussion treatment. Patients experiencing prolonged symptoms may also benefit from aerobic exercises. Additionally, there is no effective equipment for preventing concussions in the current sports world. Sports rule changes and education could be efficacious in preventing concussions.

Synthesis of novel ternary NiO–CdO-Nd2O3 nanocomposite for biodiesel production

Novel tri-phase NiO–CdO-Nd2O3 nanocomposite was prepared by coprecipitation method and its catalytic activity in transesterification reaction was studied. The synthesized nanocomposite was characterized by using FTIR, XRD, SEM and EDX to explore the functional, structural morphological and compositional properties respectively. In FTIR studies the vibrational bands for NiO, CdO and Nd2O3 have been observed. The XRD pattern of nanocomposite revealed its crystalline nature and average particle size was calculated as 28nm. The SEM studies of nanocomposite revealed that the shape of nanocomposite is semi-circle and oval shaped. EDX analysis represented elemental composition of ternary composite. The newly prepared catalyst was used as heterogeneous catalyst in transesterification of triglycerides from mustard oil into fatty acid methyl esters as biodiesel fuel. The oval shaped nanoparticles showed good catalytic activity in biodiesel synthesis. The obtained biodiesel was thoroughly characterized using FTIR and 1H NMR spectroscopic techniques. FT-IR analysis was also used to find out percentage yield using absorption spectra of different oil & methanol molar ratio. The FAMEs composition of obtained biodiesel was determined by GC-MS analysis which showed presence of methyl palmitoleate (C16:1), methyl linoleate (C18:2), methyl oleate (C18:1), metyl erucate (C22:1) and methyl behenate (C22:0) at various retention time. The quality of fuel parameters such as density, viscosity, cloud, pour and flash points were determined using ASTM methods and found within limits. The effect of several parameters on yield of biodiesel such as oil to methanol ratio (1:6, 1:9, 1:12, 1:15 and 1:18) catalyst amount (0.1, 0.5 and 0.9g) time of reaction (1.5, 2.5, 5.0 and 7.5h) and effect of temperature (60–80 °C with interval of 5 °C) were studied in detail and optimized. The 80% yield of biodiesel was achieved at optimum conditions of 1:15 oil:methanol ratio, 0.5 g catalyst concentration, 5 h reaction time and 80 °C temperature. The reusability of catalyst was tested by using three times and the results were good with minor loss of catalytic activity.

How many sites? Methods to assist design decisions when collecting multivariate data in ecology

Abstract Sample size estimation through power analysis is a fundamental tool in planning an ecological study, yet there are currently no well‐established procedures for when multivariate abundances are to be collected. A power analysis procedure would need to address three challenges: designing a parsimonious simulation model that captures key community data properties; measuring effect size in a realistic yet interpretable fashion; and ensuring computational feasibility when simulation is used both for power estimation and significance testing. Here, we propose a power analysis procedure that addresses these three challenges by: using for simulation a Gaussian copula model with factor analytical structure, fitted to pilot data; assuming a common effect size across all taxa, but applied in different directions according to expert opinion (to “increaser”, “decreaser” or “no effect” taxa); using a critical value approach to estimate power, which reduces computation time by a factor of 500 (if we would otherwise use 999 resamples to estimate each p‐value) with minor loss of accuracy. The procedure is demonstrated on pilot data from fish assemblages in a restoration study, where it was found that the planned study design would only be capable of detecting relatively large effects (change in abundance by a factor of 1.7 or more). The methods outlined in this paper are available in accompanying R software (the ecopower package), which allows researchers with pilot data to answer a wide range of design questions to assist them in planning their studies.

Offshore Wind Energy and Marine Biodiversity in the North Sea: Life Cycle Impact Assessment for Benthic Communities.

Large-scale offshore wind energy developments represent a major player in the energy transition but are likely to have (negative or positive) impacts on marine biodiversity. Wind turbine foundations and sour protection often replace soft sediment with hard substrates, creating artificial reefs for sessile dwellers. Offshore wind farm (OWF) furthermore leads to a decrease in (and even a cessation of) bottom trawling, as this activity is prohibited in many OWFs. The long-term cumulative impacts of these changes on marine biodiversity remain largely unknown. This study integrates such impacts into characterization factors for life cycle assessment based on the North Sea and illustrates its application. Our results suggest that there are no net adverse impacts during OWF operation on benthic communities inhabiting the original sand bottom within OWFs. Artificial reefs could lead to a doubling of species richness and a two-order-of-magnitude increase of species abundance. Seabed occupation will also incur in minor biodiversity losses in the soft sediment. Our results were not conclusive concerning the trawling avoidance benefits. The developed characterization factors quantifying biodiversity-related impacts from OWF operation provide a stepping stone toward a better representation of biodiversity in life cycle assessment.