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One of the primary trends in the technological growth of offshore wind turbines is the movement toward larger-rotor machines with higher hub height. Recently, offshore wind turbine sizes, especially hub height, rotor diameter, and nameplate capacity, have increased dramatically and are expected to increase further. This growth in offshore wind turbine size enhances the turbine power coefficient for the same wind speeds significantly and also led to the reductions of levelized cost of electricity (LCOE) and total installed cost (TIC) of the turbines. This work examines the growth in the nameplate size and capacity of offshore wind turbines installed in Europe through the years as new installations and total installations. Effects and results of this growth in nameplate size and capacity on the LCOE, TIC, wind farm capacity, turbine-specific power capacity, turbine capacity factor (CF), sea surface area needed per GW, and the number of turbines per GW are examined and discussed in detail. As a result, this study aims to contribute to the literature and provide technical and innovative information to turbine manufacturers by presenting various aspects of offshore wind turbine technology development in Europe. The rapid technological developments in this sector show that the average CF has increased from 42 to 44% in the last decade, and the LCOE value has reduced from 0.156 USD/kWh to 0.096 USD/kWh.

© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Global warming is pressuring policymakers to change climate policies in shifting the global economy onto a net-zero pathway. While financial assets are responsive to policy changes and development, climate change policies are becoming increasingly unpredictable, making policy decision less certain. This study investigates connectedness and spillover effects of US climate policy uncertainty on energy stocks, alternative energy stocks, and carbon emissions futures. We analyzed spillover and connectedness before and after the Paris Agreement. We employed monthly frequency data from August 2005 to March 2021 and applied DY (2012) method and MGARCH approach. We found that world energy stocks and carbon emissions futures are connected to US climate policy uncertainty. Uncertainty in climate policy and world energy stocks act as information transmitters in return spillover, while global alternative energy and carbon market are shock receivers. On volatility spillover, climate policy uncertainty, energy stocks, and carbon emissions future are shocks transmitters, while alternative energy stocks are receivers. We observe increase in connectedness following the Paris Agreement suggesting strengthened global efforts in tackling climate change. DCC and ADCC estimations revealed spillover effects of climate policy on futures returns and volatilities of world energy stocks and carbon emissions futures and the shocks could be transmitted through to the energy sector. During period of uncertainty in US climate policy, carbon allowances can potentially serve as a safe haven for energy stocks and provide downside protection for alternative energy stocks, hence hedging against climate transition risks.

We intended to compare the doctors with a convolutional neural network (CNN) that we had trained using our own unique method for the Lateral Pillar Classification (LPC) of Legg–Calve–Perthes Disease (LCPD). Thousands of training data sets are frequently required for artificial intelligence (AI) applications in medicine. Since we did not have enough real patient radiographs to train a CNN, we devised a novel method to obtain them. We trained the CNN model with the data we created by modifying the normal hip radiographs. No real patient radiographs were ever used during the training phase. We tested the CNN model on 81 hips with LCPD. Firstly, we detected the interobserver reliability of the whole system and then the reliability of CNN alone. Second, the consensus list was used to compare the results of 11 doctors and the CNN model. Percentage agreement and interobserver analysis revealed that CNN had good reliability (ICC = 0.868). CNN has achieved a 76.54% classification performance and outperformed 9 out of 11 doctors. The CNN, which we trained with the aforementioned method, can now provide better results than doctors. In the future, as training data evolves and improves, we anticipate that AI will perform significantly better than physicians.

Individuals on the autism spectrum often experience pragmatic social conversation difficulties that include showing interest in their conversational partners. This may become particularly evident during adolescence when conversation with peers is the primary medium for social interaction. This study used a multiple baseline design across participants to investigate the effects of a brief intervention package on the partner-focused conversation of three adolescents with autism. Results showed increased partner-focused questions and comments for all participants. Social validity assessments indicated that the intervention led to meaningful improvements in peer conversations.

© 2022, The Author(s), under exclusive licence to Springer Nature B.V.In this study, we examine the volatility of exchange rates to exogenous monetary shocks by dividing the volatility into subsections of “interdependence” and “contagion” during FED’s easing for the period from 2010:11 to 2018:7. Conventional methods are neither suitable to differentiate those components nor to identify the co-movements concerning time and frequency analysis, which are critical for timing in asset management and policymaking. Therefore, wavelet analysis is introduced to differentiate such components. The contribution of the study is threefold: First, this study compensates for the lack of research capturing the volatility structure of exchange rates during exogenous shocks. Second, we show both the long-term and short-term impact with associated frequency ranges. Third, we show that identifying the impact of a shock in different components and frequency ranges can provide valuable insights for the timing of market preventions and asset allocation.

© 2022, The Author(s), under exclusive licence to Springer Nature B.V.Economic development may have distinct implications for the environment based on gender-differentiated employment in various sectors of the economy. This is the first major attempt to incorporate gender in environmental modeling using sector-wise female employment status and gender parity index. In this study, we investigate the environment-gender nexus through the Environmental Kuznets Curve (EKC) hypothesis in 36 Asian countries for the period 1991–2017 by panel data estimations. We find in all estimations through panel FMOLS that (a) per capita GDP positively affects CO2 emissions and (b) per capita CO2 is affected by per capita GDP squared negatively, thus confirming EKC for panel Asian data with 971 observations. The estimations of the paper also confirm the EKC hypothesis through panel data models in which GDP and GDP squared variables. Our findings suggest male and female labor market participation impacts the environment differently, particularly in the agricultural sectors. We also find that an increased schooling ratio (gender parity index) negatively impacts environmental degradation. The findings of the present study are expected to give insights into policymakers for understanding the theoretical and statistical association between environmental quality and male/female labor force in agricultural and industrial sectors for 36 Asian countries.

BACKGROUND: Although eight-plates have been shown to be effective in correcting angular deformities of the knee, the literature is scarce regarding the efficiency of this method in treatment of children with LLD. OBJECTIVES: The aim of this study was to determine the efficiency, rates of correction and complications of epiphysiodesis using eight-plate in the management of children with leg length discrepancy (LLD). METHODS: Eleven consecutive patients with LLD (7 boys, median age = 9, age range 6–11 years) who were treated by temporary epiphysiodesis using eight-plates were retrospectively reviewed and included in the study. The main indication for temporary epiphysiodesis was an LLD between 2 and 5 cm in all patients. LLD and lower limb alignment were examined on lower extremity weight-bearing radiography preoperatively and at skeletal maturity. Longitudinal correction rate was calculated. The final LLD was categorized as ‘’good result’’ (final LLD 2 cm). RESULTS: The mean treatment period with the eight-plate was 44 (min to max = 32–72) months, and the mean follow-up from the index surgery to the final follow-up was 62 (min to max = 39–106) months. The mean LLD was significantly reduced from 39 (range 25–50) mm preoperatively to 22.40 (range 6–55) mm postoperatively (p = 0.006). The mean longitudinal correction rate was found to be 0.48 mm/mo. Radiographic evidence of lower limb deformity in frontal and sagittal planes was determined in neither preoperative nor postoperative deformity analysis. No major complications were recorded. CONCLUSION: For the management of children with LLD of 2–5 cm, temporary hemiepiphysiodesis using the eight-plate seems to be an effective treatment with low complication rates.

Retraction of the left lobe of the liver is an important step in most bariatric surgical procedures. The left lobe of the liver may be enlarged, and laceration, hematoma, or necrosis may develop in the liver due to retraction. In this study, the results of use of the Nathanson retractor (NR) and PretzelFlex retractor (PFR) in the patients undergoing laparoscopic sleeve gastrectomy (LSG) were compared. The patients who underwent LSG were divided into three groups based on the type of liver retraction device used. Group 1: NR was used fixed during the operation; Group 2: PF retractor was used; Group 3: NR were used only for fundus dissection and when necessary. All groups were evaluated in terms of demographic characteristics, liver function tests, and developing complications. The study was conducted with a total of 120 consecutive patients. Operation time in the second group was found to be significantly lower than the other two groups (p = 0.009; p = 0.001; p

Internet of Things is emerging as a commercial phenomenon. It is conjectured that billions of appliances will be connected within the current Internet infrastructure by 2020. These networked appliances require low-power radio and reliability. Hence, IEEE brought up a very efficient, reliable and deterministic time-frequency enabled medium access control protocol, IEEE 802.15.4e time slotted channel hopping (TSCH), on top of low power IEEE 802.15.4 radio for the industrial market. IEEE 802.15.4e TSCH is able to run a communication schedule for MAC upon a communication schedule is built. However, the issue of how such scheduling will be made, updated, and maintained is beyond the scope of the IEEE 802.15.4e TSCH standard. The unit responsible for these tasks is also out of its scope. That means, required scheduling mechanism is absent in this standard. In order to complete this gap, several communication scheduling algorithms are introduced in the literature. In this study, we first introduce another decentralized divergecast communication scheduling algorithm, called as DIGEST, where divergecast implies that network traffic moves in any directions opposed to convergecast where network traffic moves from leave nodes to root. That DIGEST algorithm tries to schedule time slots by selecting a neighbor node at first. When choosing a neighbor node, it tries to make almost equal number of dedicated time slots to each neighbor. In this way, it can provide better schedules with neighbor nodes than other scheduling algorithms. We evaluate the effectiveness of DIGEST, Diva, and Berkeley's Aloha-based scheduling algorithms under static and mobile environments by running extensive simulations. Our simulation results indicate that the DIGEST algorithm is superior to the others in terms of the neighbor connectivity ratio.

Since the early twentieth century, disinfecting water has been an essential process to prevent the introduction of harmful organisms, especially pathogenic organisms. Due to the reaction between anthropogenic contaminants present in water and the chemicals used to disinfect water, compounds known as disinfection by-products (DBPs) are formed during the water disinfection process. Chlorination, the most dominant water disinfection method, produces DBPs that have drawn a lot of attention and health concerns. The most commonly used removal technology for trichloromethane (TCM) is adsorption, and the use of activated carbon, iron oxides, and nanoparticles has been widely investigated. Studies have found that using nano-zero valent iron with nano-catalytic metals (Cu, Ni etc.) to synthesize bimetallic nanoparticles increases the removal of organic pollutants. The current study investigates the adsorption of trichloromethane (TCM) by synthesized Fe/Cu bimetallic nanoparticles. The response surface methodology (RSM) was used to investigate the effect of independent variables on the removal of TCM. According to the CCD results, TCM concentration and reaction time were determined as the most effective parameters. The lowest TCM concentrations have low removal efficiencies, while the lowest TCM concentration (50 µg/L) can be removed up to 60%. The highest TCM concentration can be 500 µg/L to achieve a removal below the limits with 500 mg/L Fe/Cu concentration and 24 min of reaction time. Life cycle assessment (LCA) was applied to Fe/Cu nanoparticle synthesis, and results indicated that the highest environmental impact was from the mixture of reactant stage.