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Acousto‐optic (AO) devices are known for their high parallel processing capabilities and efficient transduction, essential for real‐time processing systems. As a vital AO medium, chalcogenide glasses exhibit high AO figures of merit (M2), yet high M2 is often coupled with high acoustic attenuation (α). Thus, to obtain the trade‐off between M2 and α, a series of xGeSe2−(100−x)Sb2Se3 (40 ≤ x ≤ 85) is investigated for their AO properties. When GeSe2 content reaches 50%, a stable network of [GeSe4] and [Se2Sb–Se–SbSe2] units forms, minimizing energy loss and α while maintaining a high M2. Compared with conventional AO materials, this composition achieves an exceptional equilibrium between high M2 and reduced α, offering a distinct advantage in optimizing performance. This unique composition balance provides valuable insights for developing advanced chalcogenide glasses in AO applications. [ABSTRACT FROM AUTHOR]

The Mid-infrared ELT Imager and Spectrograph (METIS) is a first-generation instrument for the Extremely Large Telescope (ELT), Europe’s next-generation 39 m ground-based telescope for optical and infrared wavelengths, which is currently under construction at the European Southern Observatory (ESO) site at Cerro Armazones in Chile. METIS will offer diffraction-limited imaging, low- and medium-resolution slit spectroscopy, and coronagraphy for high-contrast imaging between 3 and 13 microns, as well as high-resolution integral field spectroscopy between 3 and 5 microns. The main METIS science goals are the detection and characterisation of exoplanets, the investigation of proto-planetary disks, and the formation of planets. The Single-Conjugate Adaptive Optics (SCAO) system corrects atmospheric distortions and is thus essential for diffraction-limited observations with METIS. SCAO will be used for all observing modes, with high-contrast imaging imposing the most demanding requirements on its performance. The Final Design Review (FDR) of METIS took place in the fall of 2022; the development of the instrument, including its SCAO system, has since entered the Manufacturing, Assembly, Integration and Testing (MAIT) phase. Numerous challenging aspects of an ELT Adaptive Optics (AO) system are addressed in the mature designs for the SCAO control system and the SCAO hardware module: the complex interaction with the telescope entities that participate in the AO control, wavefront reconstruction with a fragmented and moving pupil, secondary control tasks to deal with differential image motion, non-common path aberrations and mis-registration. A K-band pyramid wavefront sensor and a GPU-based Real-Time Computer (RTC), tailored to the needs of METIS at the ELT, are core components. This current paper serves as a natural sequel to our previous work presented in Hippler et al. (2018). It reflects all the updates that were implemented between the Preliminary Design Review (PDR) and FDR, and includes updated performance estimations in terms of several key performance indicators, including achieved contrast curves. We outline all important design decisions that were taken, and present the major challenges we faced and the main analyses carried out to arrive at these decisions and eventually the final design. We also elaborate on our testing and verification strategy, and, last not least, comprehensively present the full design, hardware and software in this paper to provide a single source of reference which will remain valid at least until commissioning. [ABSTRACT FROM AUTHOR]

Abstract Numerous studies have highlighted the simultaneous relationship between the Arctic Oscillation (AO) and weather/climate in Asia. However, the stability of the precursor signals in AO for Asian surface air temperature (SAT), which is important for short‐term climate prediction, has received little attention. In this study, a strengthened relationship is identified between the late‐winter AO and the early spring SAT over North and Northeast Asia (NNA) around the 1990s. During 1990–2022, a positive (negative) phase of AO during late winter is generally followed by significant warming (cooling) anomalies in the NNA during early spring, whereas this relationship is insignificant during 1961–1987. Further result shows a good persistence of the late‐winter AO to early spring after the 1990s. Accordingly, the AO exerts a strengthened impact on Mongolian anticyclone and Asian westerly anomalies through modulation of a Rossby wave train that propagates from the Arctic to the NNA in early spring, leading to significant SAT anomalies at NNA. Additionally, the AO‐related temperature anomalies intensified in the stratosphere after the 1990s, linking AO and stratospheric polar vortex (SPV). The intensified (weakened) SPV following positive (negative) AO facilitates warming (cooling) anomalies at NNA via downward‐propagating Eliassen‐Palm fluxes at wave number 1 and circumpolar westerlies in middle and lower troposphere. The seasonal persistence of AO and the strengthened relationship between AO and SPV synergistically enhance the influence of late‐winter AO on early spring SAT in the NNA, which might be attributed to the interdecadal changes in background circulation over the Arctic.

Purpose: To compare anterior plate fixation (SP fixation) both alone and in combination with an additional posterior sacroiliac screw (SP+SIS fixation) as a treatment for pelvic ring injuries with widening of the pubic symphysis and disruption to the anterior sacroiliac ligaments. Methods: To find studies with pelvic ring injuries (APC II; B2.3d) and SP or SP+SIS fixation, a systematic literature review was conducted by searching four databases. A protocol was published a priori at Open Science Framework (https://doi.org/10.17605/OSF.IO/3YHAV). Exclusion criteria included perineal injuries, chronic instability of the symphysis, complete sacroiliac separation, and pediatric patients (age

Abstract The co-occurrence of multiple hazards can either exacerbate or mitigate risks. The interrelationships between multiple hazards greatly depend on the spatiotemporal scale and can be difficult to detect from large to local scales. In this paper, we identified coastal regions worldwide where the leading tropical (El Niño-Southern Oscillation, ENSO) and polar (Arctic Oscillation, AO; Southern Annular Mode, SAM) modes of climate variability simultaneously modify the seasonal conditions of multiple hazards, including the near-surface wind speed and swell and wind-sea wave powers. We classified the results at the national and municipal levels, with a focus on multiple hazards simultaneously occurring in space and time. The results revealed that the ENSO modulates multiple hazards, affecting approximately 40% of coastal countries, while the polar annular modes affect approximately 30% of coastal countries. The ENSO induced a greater diversity of multiple hazards, with Asian countries (e.g., Indonesia experienced increases of + 2% in wind and + 7% in swell) and countries in the Americas (e.g., Peru exhibited increases of + 1.5% in wind and + 6% in wind-sea) the most notably affected. The SAM imposed a greater influence on swells in the eastern countries of ocean basins (+ 2.5% in Chile) than in other countries, while the influence of the AO was greater in Norway and the UK (+ 12% for wind-sea and 8% for swell). Low-lying islands exhibited notable variations in pairwise hazards between phases and seasons. Our results could facilitate the interpretation of multihazard interactions and pave the way for a wide range of potential implementations of different coastal industries.

Abstract Nowadays, large numbers of organizations may opt for Aspect-Oriented Programming (AOP), which is an enhancement to Object-Oriented Programming (OOP). This is due to the addition of a number of concepts that have assisted in the production of more flexible and reusable components. One of the most important elements added by AOP is software reuse, which is based on reusability attributes. These attributes indicate the possibility of reusing one or more components in the development of a new system. It is one of the most essential attributes to evaluate the quality of a system’s components. Thus far, little attention has been paid to the process of measuring AOP reusability, and it has not yet been standardized. The objective of the current study is to come up with a reasonable measurement for AOP software reuse, which is simultaneously a significant topic for researchers while offering several advantages for organizations. Although numerous models have been built to estimate the reusability of software, most of them are not dedicated to Aspect-Oriented Software (AOS). In this study, a model has been designed for AOS reusability estimation and measurement based on a new equation depending on five attributes that have a range of positive and negative impacts on AOS reusability. Three of those attributes, namely coupling, cohesion, and design size, have been included in previous studies. This study proposes complexity and generality as two new attributes to be considered. Each of these attributes was measured based on the metrics also proposed in this study. A new equation to calculate AOS reusability was constructed based on the most important reusability attributes and metrics. Seven aspect projects were employed as a case study to apply the proposed equation. After the proposed equation was applied to the selected projects, we obtained new values of reusability to compare with the values that resulted from applying the previous equation. The fact that new values emerged indicates that the proposed reusability metrics and attributes had a significant effect.

In December 2022, the United States (US) experienced an extreme cold event. Its duration was 5 days, and it ranked third in intensity (−9.16 °C) during the period from 1979 to 2022. During the Early Stage (12–16 December), the surface air temperature (SAT) anomaly peaked at 2.98 °C. In the Development Stage (17–21 December), cold air moved towards North America (NA). This event reached its peak during the Outbreak Stage (22–26 December), with a minimum SAT anomaly of −9.16 °C. Concurrently, high pressure occurred in Alaska and the Archipelago region, while low-pressure centers occurred in the US. The U-component of wind (U-wind) was in a negative anomaly in the northern part of NA. The negative anomaly of the V-component of wind (V-wind) moved southward. These atmospheric structural changes facilitated the southward movement of cold air from the Arctic to NA. Furthermore, a positive (negative) U-wind anomaly was observed to obstruct (promote) the southward progression of cold air to NA. A linear regression analysis indicated that a negative Arctic Oscillation (AO) correlated with the accumulation of cold air in the Arctic, while a positive Arctic High led to the transport of cold air to NA. In an empirical orthogonal function (EOF) analysis, EOF1 (16.3%) was characterized by a warm Arctic and cold northern part of NA pattern, reflecting the cold air from the Arctic region moving southward into NA, while EOF2 (14.4%) depicted a cold Arctic and cold NA pattern, characterizing the outbreak of cold events in the US. In January 2024, the US experienced another extreme cold event. Its maximum intensity was −9.50 °C, and its duration was 8 days. The course of the two cold events was very similar. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The co-occurrence of multiple hazards can either exacerbate or mitigate risks. The interrelationships between multiple hazards greatly depend on the spatiotemporal scale and can be difficult to detect from large to local scales. In this paper, we identified coastal regions worldwide where the leading tropical (El Niño-Southern Oscillation, ENSO) and polar (Arctic Oscillation, AO; Southern Annular Mode, SAM) modes of climate variability simultaneously modify the seasonal conditions of multiple hazards, including the near-surface wind speed and swell and wind-sea wave powers. We classified the results at the national and municipal levels, with a focus on multiple hazards simultaneously occurring in space and time. The results revealed that the ENSO modulates multiple hazards, affecting approximately 40% of coastal countries, while the polar annular modes affect approximately 30% of coastal countries. The ENSO induced a greater diversity of multiple hazards, with Asian countries (e.g., Indonesia experienced increases of + 2% in wind and + 7% in swell) and countries in the Americas (e.g., Peru exhibited increases of + 1.5% in wind and + 6% in wind-sea) the most notably affected. The SAM imposed a greater influence on swells in the eastern countries of ocean basins (+ 2.5% in Chile) than in other countries, while the influence of the AO was greater in Norway and the UK (+ 12% for wind-sea and 8% for swell). Low-lying islands exhibited notable variations in pairwise hazards between phases and seasons. Our results could facilitate the interpretation of multihazard interactions and pave the way for a wide range of potential implementations of different coastal industries. [ABSTRACT FROM AUTHOR]

Polyimide (PI) is widely used in aerospace applications due to its excellent properties. However, the high concentration of atomic oxygen (AO) in low-earth orbit (LEO) significantly degrades its performance. This study employs reactive molecular dynamics (MD) simulations to analyze the AO erosion resistance of fluorinated polyimide (FPI) and polyhedral oligomeric silsesquioxane (POSS) composite polyimide models. The 35 ps simulation results indicate that the PI/POSS composite exhibits the best protective performance. The protection mechanism involves the formation of an SiO2 carbonized layer that prevents the transmission of AO and heat to the polyimide matrix, resulting in a normalized mass of 84.1% after erosion. The FPI model shows the second-best protective effect, where the introduction of -CF3 groups enhances the thermal stability of the polyimide matrix, resulting in a normalized mass of 80.7% after erosion. This study explores the protective effects and mechanisms of different polyimide protection methods at the molecular level, providing new insights for the design of AO erosion protection systems. [ABSTRACT FROM AUTHOR]

Nowadays, large numbers of organizations may opt for Aspect-Oriented Programming (AOP), which is an enhancement to Object-Oriented Programming (OOP). This is due to the addition of a number of concepts that have assisted in the production of more flexible and reusable components. One of the most important elements added by AOP is software reuse, which is based on reusability attributes. These attributes indicate the possibility of reusing one or more components in the development of a new system. It is one of the most essential attributes to evaluate the quality of a system's components. Thus far, little attention has been paid to the process of measuring AOP reusability, and it has not yet been standardized. The objective of the current study is to come up with a reasonable measurement for AOP software reuse, which is simultaneously a significant topic for researchers while offering several advantages for organizations. Although numerous models have been built to estimate the reusability of software, most of them are not dedicated to Aspect-Oriented Software (AOS). In this study, a model has been designed for AOS reusability estimation and measurement based on a new equation depending on five attributes that have a range of positive and negative impacts on AOS reusability. Three of those attributes, namely coupling, cohesion, and design size, have been included in previous studies. This study proposes complexity and generality as two new attributes to be considered. Each of these attributes was measured based on the metrics also proposed in this study. A new equation to calculate AOS reusability was constructed based on the most important reusability attributes and metrics. Seven aspect projects were employed as a case study to apply the proposed equation. After the proposed equation was applied to the selected projects, we obtained new values of reusability to compare with the values that resulted from applying the previous equation. The fact that new values emerged indicates that the proposed reusability metrics and attributes had a significant effect. [ABSTRACT FROM AUTHOR]

Many previous studies have examined the influence of Arctic sea ice on the weather/climate of the Northern Hemisphere. However, the precursor signals of Arctic sea ice regarding East Asian winter low temperatures, which are important for climate prediction, have received little attention. This study identified an out‐of‐phase relationship between the autumn sea ice area of the Kara Sea (SICK) and subsequent winter minimum temperature in Northeast China (NEC) during 1979–2019, that is, diminished SICK facilitates cooling anomalies at NEC. Further results showed that the Arctic Oscillation (AO) acts as a bridge in the linkage between the autumn SICK and minimum temperature in NEC. Diminished autumn SICK leads to a weakened polar vortex in both the troposphere and the stratosphere in the subsequent winter through vertical propagation of planetary waves, contributing to a negative phase of the AO. Accordingly, the SICK is followed by anomalous Rossby wave train that originates from Mediterranean Sea and propagates eastward to Northeast Asia. Thus, the SICK has substantially influences on the Mongolia cyclone and minimum temperature in NEC by modulation of the AO. Moreover, the shrinking SICK could lead to the upper‐level decelerated westerly anomalies at East Asia through altering the equator‐to‐pole temperature gradient and induce negative minimum temperature anomalies at NEC. The results of this study have importance regarding the prediction of low temperature anomalies over NEC. [ABSTRACT FROM AUTHOR]

Hepatocytes are one of the most physiologically relevant in vitro liver systems for human translation of clearance and drug-drug interactions (DDI). However, the cell membranes of hepatocytes can limit the entry of certain compounds into the cells for metabolism and DDI. Passive permeability through hepatocytes can be different in vitro and in vivo, which complicates the human translation. Permeabilized hepatocytes offer a useful tool to probe mechanistic understanding of permeability-limited metabolism and DDI. Incubation with saponin of 0.01% at 0.5 million cells/mL and 0.05% at 5 million cells/mL for 5 min at 37°C completely permeabilized the plasma membrane of hepatocytes, while leaving the membranes of subcellular organelles intact. Permeabilized hepatocytes maintained similar enzymatic activity as intact unpermeabilized hepatocytes and can be stored at −80°C for at least 7 months. This approach reduces costs by preserving leftover hepatocytes. The relatively low levels of saponin in permeabilized hepatocytes had no significant impact on the enzymatic activity. As the cytosolic contents leak out from permeabilized hepatocytes, cofactors need to be added to enable metabolic reactions. Cytosolic enzymes will no longer be present if the media are removed after cells are permeabilized. Hence permeabilized hepatocytes with and without media removal may potentially enable reaction phenotyping of cytosolic enzymes. Although permeabilized hepatocytes work similarly as human liver microsomes and S9 fractions experimentally requiring addition of cofactors, they behave more like hepatocytes maintaining enzymatic activities for over 4 h. Permeabilized hepatocytes are a great addition to the drug metabolism toolbox to provide mechanistic insights. [ABSTRACT FROM AUTHOR]

In this paper, the authors quantitatively investigated the joint impact of the Arctic Oscillation (AO) and El Niño‐Southern Oscillation (ENSO) on vegetation net primary productivity (NPP) over Indo‐Myanmar in boreal winter from 1981 to 2018, and found that there is a significant in‐phase variation between them. When the warm ENSO co‐occurs with the positive AO, the NPP in more than 80% of the grids in the study region significantly increases by approximately 24 gC m−2. For the cold ENSO plus the negative AO, the regionally averaged NPP anomalies are approximately −10 gC m−2, and the local minimum is as low as −60 gC m−2. The combination of AO and ENSO can explain approximately 36% of the total variance of NPP in Indo‐Myanmar. The AO/ENSO linkages to the NPP are very likely due to regional precipitation anomalies through atmospheric circulation. In association with the positive (negative) AO, the Rossby wave, propagating eastward along the subtropical jet stream, brings an anomalous cyclone (anticyclone) over Indo‐Myanmar. This enhances (weakens) Indo‐Myanmar Trough, and resulting in more (less) regional precipitation. During the warm (cold) ENSO, through the Gill‐type response, an anomalous high (low)‐pressure appears in the lower and middle troposphere over Philippine‐South China Sea. The Walker circulation is also weaker (stronger) than normal. These are conducive to anomalous southerly (northerly) winds in Indochina. As a result, in the warm ENSO plus positive AO winters, the mean precipitation anomaly in Indo‐Myanmar increased by 27% as averaged for five data sets. In contrast, when the cold ENSO co‐occurs with negative AO, the precipitation is significantly reduced where the largest anomaly exceeds 100 mm in the ERA5. The precipitation changes are consistent with the local NPP anomalies, whereas the temperature does not seem to be a dominant limiting factor. Plain Language Summary: Vegetation is closely dependent on regional climatic conditions such as temperature and precipitation, whereas these meteorological elements are sensitive to large‐scale climate factors. Therefore, it is necessary to explore the vegetation drivers and underlying physical mechanisms. In this research, we focused on investigating the joint impact of the Arctic Oscillation (AO) and El Niño‐Southern Oscillation (ENSO) on vegetation net primary productivity (NPP) over Indo‐Myanmar in boreal winter from 1981 to 2018, the results show that the combination of AO and ENSO can explain approximately 36% of the total variance in regional NPP. The AO/ENSO linkages to the NPP are very likely due to regional precipitation anomalies through atmospheric circulation. In association with the positive (negative) AO, an eastward Rossby wave propagating along the subtropical jet stream brings an anomalous cyclone (anticyclone) over Indo‐Myanmar. During the warm (cold) ENSO, a southerly (northerly) wind anomaly prevails over Indochina via the Gill‐type response and weaker (stronger) Walker circulation than normal. As a result, when the warm (cold) ENSO co‐occurs with the positive (negative) AO winters, Indo‐Myanmar could experience more (less) precipitation than normal, which can lead to more NPP here. Key Points: There is a significant and robust in‐phase variation between the Arctic Oscillation (AO)/El Niño‐Southern Oscillation (ENSO) and net primary productivity (NPP) over Indo‐Myanmar in boreal winterThe combination of AO and ENSO can explain 36% of the total variance in NPPPrecipitation plays a critical bridge in teleconnection between AO/ENSO and local NPP and explains nearly 40% of the total variance in NPP [ABSTRACT FROM AUTHOR]

Partial discharge (PD) is a primary factor leading to the deterioration of insulation in electrical equipment. However, it is hard for traditional methods to precisely extract PD signals in increasingly complex engineering environments. This paper proposes a new PD signal denoising method combining Aquila Optimizer–Variational Mode Decomposition (AO-VMD) and K-Singular Value Decomposition (K-SVD) algorithms. Firstly, the AO algorithm optimizes critical parameters of the VMD algorithm. For the PD signal overwhelmed by noise, the AO-VMD algorithm can decompose it and reconstruct it by using kurtosis. In this process, the majority of the noise is removed, and the characteristics of the original signal are shown. Subsequently, the K-SVD algorithm performs sparse decomposition on the signal after OA-VMD, constructs a learned dictionary, and captures the characteristics of the signal for continuous learning and updating. After the dictionary learning is completed, the best matching atoms from the dictionary are selected to precisely reconstruct the original noiseless signal. Finally, the proposed method is compared with three traditional algorithms, Adaptive Ensemble Empirical Mode Decomposition (AEEMD), SVD-VMD, and the Adaptive Wavelet Multilevel Soft Threshold algorithm, on the simulated signal and the actual engineering signal. The results both demonstrate that the algorithm proposed by this paper has superior noise reduction and signal extraction performance. [ABSTRACT FROM AUTHOR]

The temporal variability of air temperature in the Middle Volga region from 1828 to 2021 is considered according to instrumental observations at the oldest meteorological station in the east of the East European Plain (Kazan University) and throughout the Asian part of Russia against the background of long-term climate fluctuations in the Northern Hemisphere of Earth. A general trend toward an increase in air temperature was revealed. It was found that climate change in Kazan was consistent with the climatic processes that occurred in the Middle Volga region as a whole. The greatest warming for the entire observation period was observed in the winter and spring seasons of the year. In December, warming occurred at a maximum rate of 0.28 °C/10 years. At the same time, the most intense warming process was observed from 1991 to 2021. The analysis of low-frequency fluctuations in the series of monthly average air temperatures made it possible to identify different periods of change, both in type (direction) and intensity. It is shown that in the Middle Volga region, positive anomalies of air temperature have occurred more often than negative ones in recent decades. Statistical data processing was also carried out for 30-year periods, starting from the first period, i.e., 1841–1870. This made it possible to reveal long-term changes in air temperature. Comparisons of climatic parameters in two periods, i.e., 1828–1945 and 1946–2021, allowed us to reliably detect the climatic beginning of the increasingly identifiable Anthropocene epoch (since 1946), characterized by a sharp increase in air temperature, increased interannual variability of the air temperature regime, and a significant increase (by about three times) in the rate of warming in the Middle Volga region. A correlation was made between atmospheric circulation indices and air temperature fluctuations in Kazan over different periods. The closest relationship was found for the 1990–2020 period. It is shown that the contribution of global factors to air temperature variability in the Middle Volga region during the Anthropocene reached 37% in winter and 32% in summer; in annual terms, this contribution amounted to 54%. [ABSTRACT FROM AUTHOR]

Using multiple approaches, the modulation of climate variability on global ocean waves from 1981 to 2020 is investigated based on a wave hindcast model forced by ERA5 winds. These climate variabilities include El Niño–Southern Oscillation (ENSO), Antarctic Oscillation (AAO), Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Indian Ocean Dipole. Linear regression and composite analysis results indicate that El Niño‐induced low‐pressure systems in December–February (DJF) generate energetic waves in the Pacific Ocean. Positive AAO events are associated with the southward movement of westerlies in the Southern Hemisphere and thus produce long‐period Southern Ocean swell that impacts the South Pacific Ocean. In the Northern Hemisphere, positive AO is associated with strengthening winds which generate larger waves around the Icelandic region. An empirical orthogonal function approach was further undertaken to study interannual variability of significant wave height (Hs) anomalies. In DJF, mode 1 marks the impacts of ENSO and PDO in the Pacific Ocean and AO in the North Atlantic Ocean. Mode 2 is controlled by AO, which is characterized by a dipole pattern in the North Atlantic Ocean. Mode 3 describes the AAO footprints in the Southern Ocean and the eastern Pacific Ocean. In June–August, the leading mode is influenced by AAO and AMO. Mode 2 indicates the importance of ENSO and PDO which exhibit opposite patterns in the Pacific Ocean sector of the Southern Ocean. Finally, a wavelet coherence analysis is conducted on the principal components and climate indexes, which shows their respective evolutions over the time–frequency domain. Plain Language Summary: The impacts of climate variability (El Niño–Southern Oscillation, Antarctic Oscillation, Arctic Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, and Indian Ocean Dipole) on global ocean waves over the period 1981–2020 are investigated using four approaches (linear regression, composite analysis, empirical orthogonal function, and wavelet analysis). The use of multiple analysis approaches ensures a comprehensive understanding of the role such climate oscillations play in modulating the global wave climate. The comparisons between these approaches further enhance our understanding of wave variability resulting from climate oscillations. Key Points: Four mathematical approaches are used to comprehensively understand the impacts of climate variability on global ocean wavesLarge‐scale wave climate patterns and teleconnections are associated with different climate oscillationsEmpirical orthogonal function modes of significant wave height are modulated by individual or multiple climate oscillations [ABSTRACT FROM AUTHOR]

A thorough understanding of the fundamental relation of traffic flow variables is critical for the efficient operation of traffic systems. However, their relationships in mixed traffic are challenging to model due to the continuously changing vehicle composition. This paper proposes a composition-based approach for estimating the fundamental relationships between traffic flow variables using empirical data. The methodology seeks to eliminate the difficulties in class-specific ss identification by introducing a continuous wavelet transformation with oblique cumulative arrival and oblique occupancy time plots. We used machine learning (ML) algorithms to delineate regimes and showed the fundamental diagrams for a given location that has a composition-invariant free-flow branch but has distinct composition-specific branches in congestion. Also, it was observed that the congested regime (CR) has a wide scatter indicating possible stochastic inter-class interactions for varying vehicular composition. We proposed a distance optimization method to re-cluster the CR data and found that the proposed method improves the fit with the empirical observations. The inter-class interactions result illustrates that the heavy vehicles will dominate the high-speed vehicles with the increase of AO. It is found that beyond a critical level of AO in congestion, all vehicle class travel at the same speed. Finally, it is found that validation with different datasets shows that the proposed methodology is robust in estimating fundamental diagrams under mixed traffic conditions.

This work analyses the monthly spatial distribution of extreme sea levels in the Baltic Sea as well as the relationship of these levels with the NAO and AO indicators. The research was based on hourly sea level data from the 45 tide gauge stations gathered in the years 1960 to 2020. The analysis shows that the duration of extreme sea levels tends to increase moving from along the line joining the open sea and the gulf end. This is associated with the narrowing of the gulf and the geomorphological and bathymetric configuration of the coastal zone. The duration of high and low sea levels in the Baltic Sea decreases from a maximum in January to a minimum in the months of May to August, then it increases again until the end of the year. This cycle corresponds well to the annual occurrence of storm surges, which are affected by the annual changes in atmospheric circulation. The impact of the variations of the circulation on extreme sea levels was confirmed by examining the relation between maximum, minimum and mean levels of the Baltic waters and the zone circulation indices NAO and AO for each month of the year and the seasons in the multiyear period 1960–2020. The results indicate that the strongest correlations exist between sea levels and NAO/AO in the winter months. There is a spatial differentiation of the correlation and its increase from the southwest to the northeast in Baltic Sea.

Teleconnection patterns are one of the key features to understanding high‐frequency natural climate variability. The North Sea‐Caspian Pattern (NCP) was identified as a middle tropospheric dipole and its hydroclimatological implications have been substantially restricted to the Eastern Mediterranean region. Thus, the hydroclimatological influences of the NCP in the Euro‐Mediterranean region were investigated via a comparative approach with dominant tropospheric teleconnections in the Eurasian region and synoptic features such as ridge‐trough positioning and strength. By using high‐resolution ERA5 reanalysis data, cross‐correlations between indexes, anticorrelations at 500 hPa and composite anomaly maps for seasonally representative months were produced to understand the working mechanism of the NCP. Comparisons included the East Atlantic/Western Russian (EAWR) pattern, a rotated principal component analysis (RPCA) variant of NCP which utilizes pole‐based representation. Analysis revealed that the NCP was correlated well with the Mediterranean trough displacement and with the strength of the East Asian trough. Climate anomalies indicated by the NCP were greater and more spatially consistent compared to other teleconnections. The NCP also showed higher contrasts of temperature and precipitation than the EAWR based on the composite anomaly maps. In conclusion, the NCP explained climate variability in all seasons linking remote centres of action within Eurasia's east and west extremes. [ABSTRACT FROM AUTHOR]

Time-varying relationships between two atmospheric oscillation modes and precipitation (rainfall and snow) in the western portion of the Carpathian Mountains and the northern part of the Pannonian Plain are investigated in this paper. The Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO) modes were used to explain the intra-annual variability of monthly rainfall totals and new snow over a 36-year period (1981-2017) observed at a dense network of 177 rain gauges and 33 snow rods located throughout the investigated area, respectively. The Continuous Wavelet Transform (CWT) was deployed as a band-pass fllter to quantify the spectral coherence and attribution (based on signal-to-noise ratio) of the NAO and AO modes to the precipitation variability. The temporal and spatial patterns of NAO and AO-related signal variance in monthly rainfall totals and fresh snowpack were evaluated on seasonal and monthly bases. The NAO mode explained the major historically observed snow calamities, such as the snowy cold spell of January 1985 that hit central and southern Europe, bringing heavy snowfall to the investigated region and many other parts of Europe. This event was the beginning of a prolonged cold wave in Europe, with extremely low air temperatures across the continent. Our analyses showed that the AO mode appears to have only a limited effect on the overall variability of new snowpack in late winter. The attribution of NAO and AO modes to the variability of monthly rainfall totals is less pronounced compared to new snowpack. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) is a primary factor leading to the deterioration of insulation in electrical equipment. However, it is hard for traditional methods to precisely extract PD signals in increasingly complex engineering environments. This paper proposes a new PD signal denoising method combining Aquila Optimizer–Variational Mode Decomposition (AO-VMD) and K-Singular Value Decomposition (K-SVD) algorithms. Firstly, the AO algorithm optimizes critical parameters of the VMD algorithm. For the PD signal overwhelmed by noise, the AO-VMD algorithm can decompose it and reconstruct it by using kurtosis. In this process, the majority of the noise is removed, and the characteristics of the original signal are shown. Subsequently, the K-SVD algorithm performs sparse decomposition on the signal after OA-VMD, constructs a learned dictionary, and captures the characteristics of the signal for continuous learning and updating. After the dictionary learning is completed, the best matching atoms from the dictionary are selected to precisely reconstruct the original noiseless signal. Finally, the proposed method is compared with three traditional algorithms, Adaptive Ensemble Empirical Mode Decomposition (AEEMD), SVD-VMD, and the Adaptive Wavelet Multilevel Soft Threshold algorithm, on the simulated signal and the actual engineering signal. The results both demonstrate that the algorithm proposed by this paper has superior noise reduction and signal extraction performance.

The Aquila optimizer (AO) is a recently developed swarm algorithm that simulates the hunting behavior of Aquila birds. In complex optimization problems, an AO may have slow convergence or fall in sub-optimal regions, especially in high complex ones. This paper tries to overcome these problems by using three different strategies: restart strategy, opposition-based learning and chaotic local search. The developed algorithm named as mAO was tested using 29 CEC 2017 functions and five different engineering constrained problems. The results prove the superiority and efficiency of mAO in solving many optimization issues.

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Transcatheter aortic valve implantation (TAVI) is an established choice for the treatment of severe aortic stenosis (AS) in patients who are deemed inoperable or at high surgical risk. There are limited data for the safety and effi cacy of the method in patients with bicuspid aortic valve (BAV), the most common congenital valve defect. Patients with BAV were excluded from randomized clinical trials (RCTs), comparing TAVI to surgery due to the heterogeneous anatomy of this nosological unit and concerns about unsatisfactory procedural and clinical outcomes after TAVI. With the improvement of the design of the new generations devices, with the growing technical experience of the teams and the progress in the imaging techniques, better results and fewer complications are observed, which could be a prerequisite for expanding the indications for TAVI in patients with BAV. This review presents TAVI treatment options for patients with BAV, the results of available registers in terms of safety and effi cacy of the procedure, and future perspectives.

An extreme cold event outbreaks in Eastern China (EC) in December 16–22, 2023. Its maximum intensity (−8.30 °C) and duration (7 days) are in the second place in December during 1980–2023. In Early Stage (December 6–10), surface air temperature (SAT) anomalies reach the highest at 6.77 °C, exceeding mean value by two standard deviations. The variation of SAT anomalies (differences of SAT anomalies between the last day and the first day for a given period) is 0.60 °C. In Development Stage (December 11–15), SAT anomalies begin to decline but remain positive. In Outbreak Stage (December 16–22), the variation of SAT anomalies reaches a minimum of −3.17 °C, reflecting the cooling of EC. From December 1, cold air gradually gathers in Siberia under the influence of Arctic high moving southward. Cold air is locked in Siberia due to negative anomalies of geopotiential height (GH) and the westerlies anomalies between 40°–50°N. On December 11, these negative GH anomalies begin to move southeastward, and the westerlies anomalies weaken to a easterlies. From December 16–22, EC experiences an extreme cold event due to the southward of Arctic high and the eastward of Ural and Okhotsk high. On the basis of the zonal wind index (ZI) phase changes from negative to positive and the jet stream moves southeastward, the strong (weak) jet stream is spotted to block (promote) the southward of cold air. Linear regression shows that negative Arctic Oscillation (AO) conducts to the concentration of cold air in Siberia. Positive Siberia High (SH) pushes cold air to EC. SAT anomalies decrease by 2.29 °C in EC with the increase of 1 unit for SH. In empirical orthogonal function (EOF) analysis, EOF1 (28.07%) is characterized by warm Arctic and cold Siberia (WA-CS), which reflects the effect of SH on the occurrence of extreme cold events.

Both seasonal and extreme climate conditions are influenced by long-term natural internal variability. However, in general, long-term hazard variation has not been incorporated into coastal risk assessments. There are coastal regions of high interest, such as urban areas, where a large number of people are exposed to hydrometeorological hazards, and ecosystems, which provide protection, where long-term natural variability should be considered a design factor. In this study, we systematized climate analysis to identify high-interest regions where hazard long-term variability should be considered in risk assessment, disaster reduction, and future climate change adaptation and protection designs. To achieve this goal, we examined the effect of the leading modes of climate variability (Arctic Oscillation, Southern Annular Mode, and El Niño–Southern Oscillation) on the variation in the recurrence of extreme coastal hazard events, including as a first step sea surface temperature, winds, and waves. Neglecting long-term variability could potentially lead to the underperformance of solutions, or even irreversible damage that compromises the conditions of ecosystems for which nature-based solutions are designed.

This study investigates thermospheric seasonal variations composed of annual and semiannual oscillations (AO and SAO) in the column density ratio of atomic oxygen to molecular nitrogen observed by Global‐scale Observations of Limb and Disk. On the basis of multiple analysis approaches, it is revealed that the AO is the predominant component at middle latitudes, while the SAO tends to be increasingly important toward the lower latitudes. The SAO is also evident in the southern mid‐latitudes. Quantitative analyses demonstrate that AO (SAO) peaks around winter solstices (equinoxes). Additionally, the seasonal variation at low‐latitudes exhibits greater amplitudes in the early morning and around noon, whereas it gradually weakens from early morning toward late afternoon at mid‐latitudes. A hypothesis is that seasonal variations are likely modulated by atmospheric tides, including those generated in the thermosphere and those propagating upward from the lower atmosphere. Plain Language Summary: Annual and semiannual variations are the most prominent phenomenon standing out on the seasonal scale in the thermosphere‐ionosphere system. Despite being recognized for decades, the characteristics of the AO and SAO are not yet well delineated, and relevant physics is not fully understood, due largely to limited observations and sampling constraints of low‐Earth‐orbit (LEO) satellites. For instance, distinguishing the local time versus longitude variations in the thermosphere is not feasible with LEO satellites alone. Leveraging the synoptic observations enabled by the Global‐scale Observations of Limb and Disk (GOLD) mission, we identified the AO and SAO in the column density ratios of atomic oxygen to molecular nitrogen at low and middle latitudes. More importantly, since GOLD provides full coverage of daytime local times on a daily basis, we quantified the local time dependence of seasonal variations in composition. Prevalent local time modulations could be driven by atmospheric tides. Key Points: Pronounced annual and semiannual oscillations (AOs and SAOs) are seen in Global‐scale Observations of Limb and Disk ∑O/N2AO is predominant at mid‐latitudes, and SAO is evident in both low‐latitudes and southern mid‐latitudesLocal time modulations of seasonal variations are prominent at low‐ and mid‐latitudes [ABSTRACT FROM AUTHOR]

The climate effect and environmental pollution caused by dust discharged into the atmosphere have attracted much attention. However, the driving factors of dust emissions have not been studied thoroughly. Here, spatiotemporal variations in dust emissions and the relationship between dust emissions and large-scale atmospheric circulation in East Asia from 2000 to 2021 were investigated using Modern-Era Retrospective Analysis for Research and Applications version 2, Cloud-Aerosol Lidar Pathfinder Satellite Observations, ERA5 reanalysis data, and climate indices. Results showed that the Taklimakan Desert in the Tarim Basin, the Gurbantonggut Desert in the Junggar Basin, the Turpan Basin, and the Gobi Desert in western Inner Mongolia and southern Mongolia are the main sources of dust emissions in East Asia. The period of strong dust emissions is from March to May, and emissions to the atmosphere were mainly distributed at 0–4 km in the troposphere. In the eastern and southwestern Tarim Basin, northern Junggar Basin, and parts of the Gobi Desert in southern Mongolia, dust emissions have significantly increased over the past 22 years, whereas in the southwestern Tibetan Plateau, southwestern Inner Mongolia, and a small part of the northern Mongolian Gobi Desert there was a significant decreasing trend. The winter North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were significantly negatively correlated with East Asian dust emissions the following spring. The various phases of the AO/NAO coupling have clear different effects on East Asian dust emissions in the spring. When the AO/NAO coupling was negative (positive), the East Asian trough and Siberian High were strengthened (weakened), the frequency of cold air activity increased (weakened), 800 hPa wind speed strengthened (weakened), and East Asian emissions increased (decreased). In AO−/NAO+ years, the Asian polar vortex was stronger to the south and the East Asian trough was stronger to the west. The Lake Baikal trough was in the deepening phase, which caused more polar cold air to move into East Asia, aggravating the intensity of dust activity. In the AO+/NAO− years, the Siberian High and East Asian trough weakened, which was unfavorable to the southward movement of cold air from Siberia. Therefore, the frequency of windy weather in East Asia decreased, partly weakening dust emissions. However, a positive geopotential anomaly in northeast China and a negative geopotential anomaly in South Asia triggered an anomalous enhancement in easterly wind in the tropospheric area over northwest China. Strengthening of the Balkhash trough provides favorable conditions for gale weather in northwest China. The frequency of gale weather increased, and dust emissions were enhanced in northwest China. [ABSTRACT FROM AUTHOR]

Introduction: Fractures of the distal ulna, excluding the styloid, are rare. The cause of injury is often a fall on an outstretched hand with an extended wrist, and in most cases there is a concomitant distal radius fracture. The aims of this retrospective study were to investigate the results of the current treatment of distal ulna fractures in adults, with or without a concomitant distal radius fracture, and if a recently presented fracture classification could predict outcome. Materials and methods: Patients, 18 years or older, treated for a fracture of the distal third of ulna in our county, were included. Fractures of the styloid tip were excluded. The radiographs of the fractures were independently classified by two specialists in radiology according to the 2018 AO/OTA classification. Follow-up was performed 5–7 years after the injury, through the questionnaire Patient-Rated Wrist Evaluation (PRWE) and new radiographs of both wrists. Results: Ninety-six patients with 97 fractures were included and filled out the PRWE. 65 patients also had new radiographs taken. 79 patients were women and the mean age at the time of injury was 63 years (SD 14.5). The most common fracture class was the extra-articular transverse fracture, 2U3A2.3 (42%). We found that 40% of the fractures had been treated by internal fixation and only 2 fractures had not healed, one conservatively treated and one operated. The median PRWE was 15 (IQR 33.5). The PRWE score was significantly worse in the operated ulna fractures (p = 0.01) and this was also true for extra-articular transverse fractures 2U3A2.3 (p = 0.001). Initial displacement was more common in operated transverse fractures, but it could not be proven that this was the reason for the inferior result. Conclusions: Distal ulna fractures almost always unite and the result is comparable to that of isolated distal radius fractures when measured by PRWE. Based on the opinions of the radiologists and how often a consensus discussion was needed for classification, we found the updated AO classification system difficult to use, if dependent only on standard radiographic views. In the present study, transverse extra-articular ulna fractures did not benefit from internal fixation regardless if associated with a distal radius fracture or isolated. [ABSTRACT FROM AUTHOR]

This paper gives a descriptive account of negation in Jungli (Ao), a Tibeto-Burman language spoken by the Aos in Nagaland, Northeast India. Jungli has two negative markers, the negative prefix 'mə̄-' and the prohibitive marker 'tə̀-'. I examine the occurrence and restriction of these two prefixes in sentence constructions involving tense and aspect markers, modal markers, copulas, interrogatives and converb constructions. A short description of negative words in Jungli is also presented. [ABSTRACT FROM AUTHOR]

Copyright of National Palace Museum Research Quarterly is the property of National Palace Museum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change exposes more frequent natural hazards and physical vulnerabilities to the built and natural environments. Extreme precipitation and temperature events will have a significant impact on both the natural environment and human society. However, it is unclear whether precipitation and temperature extremes increase physical vulnerabilities across scales and their links with large-scale climate indices. This study investigates the relationship between precipitation and temperature extremes, as recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), and large scale climatological phenomenon indices (Indian Summer Monsoon Index (ISMI), Arctic Oscillation (AO), and North Atlantic Oscillation (NAO)), using India as a case study. Our findings show that extreme warm indices were primarily negatively related to ISMI and positively related to extreme cold indices. According to Pearson's correlation coefficients and Wavelet Transform Coherence (WTC), extreme warm indices were negatively related to ISMI and positively related to extreme cold indices. The extreme precipitation indices had a significant positive relationship, primarily with AO. Furthermore, from 1951 to 2018, India experienced an increase in warm extremes over western, central, and peninsular India, while cold indices increased over northwest India. Precipitation extremes of more than one day, more than five days, very wet and extremely wet days have increased across India except in the Indo-Gangetic plains, while heavy and very heavy precipitation days, consecutive wet days, and consecutive dry days have decreased. [ABSTRACT FROM AUTHOR]

Since the 1950s, the terrestrial carbon uptake has been characterized by interannual variations, which are mainly determined by interannual variations in gross primary production (GPP). Using an ensemble of seven-member TRENDY (Trends in Net Land—Atmosphere Carbon Exchanges) simulations during 1951–2010, the relationships of the interannual variability of seasonal GPP in China with the sea surface temperature (SST) and atmospheric circulations were investigated. The GPP signals that mostly relate to the climate forcing in terms of Residual Principal Component analysis (hereafter, R-PC) were identified by separating out the significant impact from the linear trend and the GPP memory. Results showed that the seasonal GPP over China associated with the first R-PC1 (the second R-PC2) during spring to autumn show a monopole (dipole or tripole) spatial structure, with a clear seasonal evolution for their maximum centers from springtime to summertime. The dominant two GPP R-PC are significantly related to Sea Surface Temperature (SST) variability in the eastern tropical Pacific Ocean and the North Pacific Ocean during spring to autumn, implying influences from the El Niño—Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). The identified SST and circulation factors explain 13%, 23% and 19% of the total variance for seasonal GPP in spring, summer and autumn, respectively. A clearer understanding of the relationships of China's GPP with ocean—atmosphere teleconnections over the Pacific and Atlantic Ocean should provide scientific support for achieving carbon neutrality targets. [ABSTRACT FROM AUTHOR]