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Abstract: —J. Blunden and T. Boyer In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. Anna Glacier in Switzerland and Ice Worm Glacier in the United States disappeared completely. In August, as a direct result of glacial thinning over the past 20 years, a glacial lake on a tributary of the Mendenhall Glacier in Alaska burst through its ice dam and caused unprecedented flooding on Mendenhall River near Juneau. Across the Arctic, the annual surface air temperature was the fourth highest in the 124-year record, and summer (July–September) was record warm. Smaller-than-normal snow cover extent in May and June contributed to the third-highest average peak tundra greenness in the 24-year record. In September, Arctic minimum sea ice extent was the fifth smallest in the 45-year satellite record. The 17 lowest September extents have all occurred in the last 17 years. In Antarctica, temperatures for much of the year were up to 6°C above average over the Weddell Sea and along coastal Dronning Maud Land. The Antarctic Peninsula also experienced well-above-average temperatures during the 2022/23 melt season, which contributed to its fourth consecutive summer of above-average surface melt. On 21 February, Antarctic sea ice extent and sea ice area both reached all-time lows, surpassing records set just a year earlier. Over the course of the year, new daily record-low sea ice extents were set on 278 days. In some instances, these daily records were set by a large margin, for example, the extent on 6 July was 1.8 million km2 lower than the previous record low for that day. Across the global oceans, the annual sea surface temperature was the highest in the 170-year record, far surpassing the previous record of 2016 by 0.13°C. Daily and monthly records were set from March onward, including an historic-high daily global mean sea surface temperature of 18.99°C recorded on 22 August. Approximately 94% of the ocean surface experienced at least one marine heatwave in 2023, while 27% experienced at least one cold spell. Globally averaged ocean heat content from the surface to 2000-m depth was record high in 2023, increasing at a rate equivalent to ∼0.7 Watts per square meter of energy applied over Earth’s surface. Global mean sea level was also record high for the 12th consecutive year, reaching 101.4 mm above the 1993 average when satellite measurements began, an increase of 8.1±1.5 mm over 2022 and the third highest year-over-year increase in the record. A total of 82 named tropical storms were observed during the Northern and Southern Hemispheres’ storm seasons, below the 1991–2020 average of 87. Hurricane Otis became the strongest landfalling hurricane on record for the west coast of Mexico at 140 kt (72 m s−1), causing at least 52 fatalities and $12–16 billion U.S. dollars in damage. Freddy became the world’s longest-lived tropical cyclones on record, developing into a tropical cyclone on 6 February and finally dissipating on 12 March. Freddy crossed the full width of the Indian Ocean and made one landfall in Madagascar and two in Mozambique. In the Mediterranean Sea—outside of traditional tropical cyclone basins—heavy rains and flooding from Storm Daniel killed more than 4300 people and left more than 8000 missing in Libya. The record-warm temperatures in 2023 created conditions that helped intensify the hydrological cycle. Measurements of total-column water vapor in the atmosphere were the highest on record, while the fraction of cloud area in the sky was the lowest since records began in 1980. The annual global mean precipitation total over land surfaces for 2023 was among the lowest since 1979, but global one-day maximum totals were close to average, indicating an increase in rainfall intensity. In July, record-high areas of land across the globe (7.9%) experienced extreme drought, breaking the previous record of 6.2% in July 2022. Overall, 29.7% of land experienced moderate or worse categories of drought during the year, also a record. Mexico reported its driest (and hottest) year since the start of its record in 1950. In alignment with hot and prolonged dry conditions, Canada experienced its worst national wildfire season on record. Approximately 15 million hectares burned across the country, which was more than double the previous record from 1989. Smoke from the fires were transported far into the United States and even to western European countries. August to October 2023 was the driest three-month period in Australia in the 104-year record. Millions of hectares of bushfires burned for weeks in the Northern Territory. In South America, extreme drought developed in the latter half of the year through the Amazon basin. By the end of October, the Rio Negro at Manaus, a major tributary of the Amazon River, fell to its lowest water level since records began in 1902. The transition from La Niña to El Niño helped bring relief to the prolonged drought conditions in equatorial eastern Africa. However, El Niño along with positive Indian Ocean dipole conditions also contributed to excessive rainfall that resulted in devastating floods over southeastern Ethiopia, Somalia, and Kenya during October to December that displaced around 1.5 million people. On 5 September, the town of Zagora, Greece, broke a national record for highest daily rainfall (754 mm in 21 hours, after which the station ceased reporting) due to Storm Daniel; this one-day accumulation was close to Zagora’s normal annual total.

Abstract Combination treatments for migraine prophylaxis present a promising approach to addressing the diverse and complex mechanisms underlying migraine. This review explores the potential of combining oral conventional prophylactics, onabotulinumtoxin A, monoclonal antibodies (mAbs) targeting the calcitonin gene-related peptide (CGRP) pathway, and small molecule CGRP receptor antagonists (gepants). Among the most promising strategies, dual CGRP inhibition through mAbs and gepants may enhance efficacy by targeting both the CGRP peptide and its receptor, while the combination of onabotulinumtoxin A with CGRP treatments offers synergistic pain relief. Oral non-CGRP treatments, which are accessible and often prescribed for patients with comorbid conditions, provide an affordable and practical option in combination regimens. Despite the potential of these combinations, there is a lack of evidence to support their widespread inclusion in clinical guidelines. The high cost of certain combinations, such as onabotulinumtoxin A with a CGRP mAb or dual anti-CGRP mAbs, presents feasibility challenges. Further large-scale trials are needed to establish safe and effective combination protocols and solidify their role in clinical practice, particularly for treatment-resistant patients. Graphical Abstract

Abstract Background and aim Migraine is a common disabling conditions which, globally, affects 15.2% of the population. It is the second cause of health loss in terms of years lived with disability, the first among women. Despite being so common, it is poorly recognised and too often undertreated. Specialty centres and neurologists with specific expertise on headache disorders have the knowledge to provide specific care: however, those who do not regularly treat patients with migraine will benefit from a synopsis on the most relevant and updated information about this condition. This paper presents a comprehensive view on the hallmarks of migraine, from genetics and diagnostic markers, up to treatments and societal impact, and reports the elements that identify migraine specific features. Main results The most relevant hallmark of migraine is that it has common and individual features together. Besides the known clinical manifestations, migraine presentation is heterogeneous with regard to frequency of attacks, presence of aura, response to therapy, associated comorbidities or other symptoms, which likely reflect migraine heterogeneous genetic and molecular basis. The amount of therapies for acute and for prophylactic treatment is really wide, and one of the difficulties is with finding the best treatment for the single patient. In addition to this, patients carry out different daily life activities, and might show lifestyle habits which are not entirely adequate to manage migraine day by day. Education will be more and more important as a strategy of brain health promotion, because this will enable reducing the amount of subjects needing specialty care, thus leaving it to those who require it in reason of refractory condition or presence of comorbidities. Conclusions Recognizing the hallmarks of migraine and the features of single patients enables prescribing specific pharmacological and non-pharmacological treatments. Medical research on headaches today particularly suffers from the syndrome of single-disease approach, but it is important to have a cross-sectional and joint vision with other close specialties, in order to treat our patients with a comprehensive approach that a heterogeneous condition like migraine requires.

Wind energy development in Central Asia can help alleviate drought and fragile ecosystems. Nevertheless, current studies mainly used the global climate models (GCMs) to project wind speed and energy. The simulated biases in GCMs remain prominent, which induce a large uncertainty in the projected results. To reduce the uncertainties of projected near-surface wind speed (NSW) and better serve the wind energy development in Central Asia, the Weather Research and Forecasting (WRF) model with bias-corrected GCMs was employed. Compared with the outputs of GCMs, dynamical downscaling acquired using the WRF model can better capture the high- and low-value centres of NSWS, especially those of Central Asia's mountains. Meanwhile, the simulated NSWS bias was also reduced. For future changes in wind speed and wind energy, under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, NSWS during 2031–2050 is projected to decrease compared with that in 1986–2005. The magnitude of NSWS reduction during 2031–2050 will reach 0.1 m s−1, and the maximum reduction is projected to occur over the central and western regions (>0.2 m s−1). Furthermore, future wind power density (WPD) can reveal nonstationarity and strong volatility, although a downward trend is expected during 2031–2050. In addition, the higher frequency of wind speeds at the turbine hub height exceeding 3.0 m s−1 can render the plain regions more suitable for wind energy development than the mountains from 2031 to 2050. This study can serve as a guide in gaining insights into future changes in wind energy across Central Asia and provide a scientific basis for decision makers in the formulation of policies for addressing climate change.

Near-surface wind speed exerts profound impacts on many environmental issues, while the long-term (≥60 years) trend and multidecadal variability in the wind speed and its underlying causes in global high-elevation and mountainous areas (e.g., Tibetan Plateau) remain largely unknown. Here, by examining homogenized wind speed data from 104 meteorological stations over the Tibetan Plateau for 1961–2020 and ERA5 reanalysis datasets, we investigated the variability and long-term trend in the near-surface wind speed and revealed the role played by the westerly and Asian monsoon. The results show that the homogenized annual wind speed displays a decreasing trend (−0.091 m s−1 per decade, p

Abstract Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.

In situ surface wind observation is a critical meteorological data source for various research fields. However, data quality is affected by factors such as surface friction changes, station relocations and anemometer updates. Previous methods to address discontinuities have been insufficient, and processing methods have not always adhered to World Meteorological Organization (WMO) World Climate Programme guidelines. We analyzed data discontinuity caused by anemometer changes and station relocations in China's daily in situ near-surface (∼ 10 m) wind speed observations and the impact of the processing methods on wind speed trends. By comparing the wind speed discontinuities with the recorded location changes, we identified 90 stations that showed abnormally increasing wind speeds due to relocation. After removing those stations, we followed a standard quality control method recommended by the World Meteorological Organization to improve the data reliability and applied Thiessen polygons to calculate the area-weighted average wind speed. The result shows that China's recent reversal of wind speed was reduced by 41 % after removing the problematic stations, with an increasing trend of 0.017 m s−1 yr−1 (R2 = 0.64, P < 0.05), emphasizing the importance of robust quality control and homogenization protocols in wind trend assessments.

Abstract Background Although acute headache following COVID-19 vaccination is widely acknowledged, the long-term progression of these headaches remains poorly understood. Our objective was to identify various phenotypes of prolonged or worsened headaches associated with COVID-19 vaccination and document any changes in these phenotypes over an extended period. Additionally, we aimed to document the diverse headache presentations among patients with pre-existing primary headaches. Methods A multinational, prospective observational study was conducted to investigate prolonged or worsened headaches associated with COVID-19 vaccination. Questionnaires assessing COVID-19 vaccination-related headaches at three time points (initial visit, 3rd month follow-up, and 6th month follow-up) were developed for the study. Headache specialists/clinicians evaluated patients using these questionnaires in a prospective manner. Repeated K-means cluster analysis was performed to identify patient profiles with prolonged or worsened headaches related to COVID-19 vaccination. Results Among the 174 patients included in the study, there was a female-to-male ratio of 128 (73.6%) to 46 (26.4%). The mean age of the patient group was 45.2 ± 13.3 years, and 107 patients (61.5%) had a pre-existing history of primary headaches. Through the analysis, two major clusters were identified based on headache characteristics at each visit. During the first visit (n = 174), Cluster 1 primarily comprised patients with a history of primary headaches, frontal localization of pain, throbbing pain type, more severe headaches accompanied by symptoms such as nausea, phonophobia, photophobia, and osmophobia, and worsened by physical activity. In contrast, Cluster 2 consisted of patients with longer headache durations (over one month) and a stabbing/pressing quality of pain. Patients in Cluster 1 had a higher prevalence of migraine as the pre-existing primary headache disorder compared to Cluster 2 (90.48% vs. 68.18%, respectively; p = 0.005). Conclusion The identification of two distinct phenotypes of prolonged or worsened headaches related to COVID-19 vaccination can provide valuable clinical insights. Having an awareness of the potential worsening of headaches following COVID-19 vaccination, particularly in patients with a primary headache disorder such as migraine, can help clinicians and headache experts anticipate and adjust their treatment strategies accordingly. This knowledge can aid in preplanning treatment modifications and optimize patient care.

Overexploitation of fisheries is a worldwide problem, which is leading to a large loss of diversity, and affects human communities indirectly through the loss of traditional jobs, cultural heritage, etc. To address this issue, governments have started accumulating data on fishing activities, to determine biomass extraction rates, and fisheries status. However, these data are often estimated from small samplings, which can lead to partially inaccurate assessments. Fishing can also benefit of the digitization process that many industries are undergoing. Wholesale fish markets, where vessels disembark, can be the point of contact to retrieve valuable information on biomass extraction rates, and can do so automatically. Fine-grained knowledge about the fish species, quantities, sizes, etc. that are caught can be therefore very valuable to all stakeholders, and particularly decision-makers regarding fisheries conservation, sustainable, and long-term exploitation. In this regard, this article presents a full workflow for fish instance segmentation, species classification, and size estimation from uncalibrated images of fish trays at the fish market, in order to automate information extraction that can be helpful in such scenarios. Our results on fish instance segmentation and species classification show an overall mean average precision (mAP) at 50% intersection-over-union (IoU) of 70.42%, while fish size estimation shows a mean average error (MAE) of only 1.27 cm.

Instrumental measurements of wind speed and direction from the 1920s to the 1940s from 13 stations in Sweden have been rescued and digitized, making 165 additional station years of wind data available through the Swedish Meteorological and Hydrological Institute's open data portal. These stations measured wind through different versions of cup-type anemometers and were mainly situated at lighthouses along the coasts and at airports. The work followed the protocol “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization consisting of (i) designing a template for digitization, (ii) digitizing records in paper journals by a scanner, (iii) typing numbers of wind speed and direction data into the template, and (iv) performing quality control of the raw observation data. Along with the digitization of the wind observations, meta data from the stations were collected and compiled as support to the following quality control and homogenization of the wind data. The meta data mainly consist of changes in observer and a small number of changes in instrument types and positions. The rescue of these early wind observations can help improve our understanding of long-term wind changes and multidecadal variability (e.g. the “stilling” vs. “reversal” phenomena) but also to evaluate and assess climate simulations of the past. Digitized data can be accessed through the Swedish Meteorological and Hydrological Institute and the following Zenodo repository: https://doi.org/10.5281/zenodo.5850264 (Zhou et al., 2022).

Chicken behavior recognition is crucial for a number of reasons, including promoting animal welfare, ensuring the early detection of health issues, optimizing farm management practices, and contributing to more sustainable and ethical poultry farming. In this paper, we introduce a technique for recognizing chicken behavior on edge computing devices based on video sensing mosaicing. Our method combines video sensing mosaicing with deep learning to accurately identify specific chicken behaviors from videos. It attains remarkable accuracy, achieving 79.61% with MobileNetV2 for chickens demonstrating three types of behavior. These findings underscore the efficacy and promise of our approach in chicken behavior recognition on edge computing devices, making it adaptable for diverse applications. The ongoing exploration and identification of various behavioral patterns will contribute to a more comprehensive understanding of chicken behavior, enhancing the scope and accuracy of behavior analysis within diverse contexts.

Background: Headache is the most common neurological side effect of coronavirus disease 2019 (COVID-19) vaccination. However, the underlying reason for COVID-19 postvaccine headache has not been fully understood. In this study, we addressed the potential association of vaccine-related headaches with a history of allergy, atopic diseases, as well as other comorbid conditions to gain insight about the pathophysiology of this headache. Materials and Methods: This study analyzed the data from the Vaccine Adverse Event Reporting System database and reorganized dataset accordingly. The study included individuals aged 16–85 years who received the first or second dose of COVID-19 vaccines approved by the Food and Drug Administration. Allergy and atopic disease histories (reported food or drug allergy, allergic rhinitis, asthma, and other autoimmune diseases) and other accompanying diseases such as depression, anxiety, sleep disorders, fibromyalgia, and obesity of these subjects were examined from the revised data, and their relationship with COVID-19 vaccine-related headaches was investigated. Results: We found a statistically significant positive association in patients with a history of headache after COVID-19 vaccination and reported a history of allergy (P < 0.001). In the allergy subgroup (n = 14547 [37.1%]), the frequency of headaches following COVID-19 vaccine was found to be higher in those with drug, food, and/or multiple allergies (P < 0.05). A statistically significant relationship was disclosed between asthma, autoimmune diseases, and headache, but no association was found with allergic rhinitis (P < 0.001, P = 0.160). Furthermore, the rate of headaches after vaccination was found to be higher in people with fibromyalgia and depression (P < 0.001, both). Conclusion: Significant associations between headaches triggered by the COVID-19 vaccine and histories of allergy, fibromyalgia, and depression may suggest a shared predisposing mechanism for pathophysiology. Knowledge about allergy history and related comorbid conditions can be helpful in predicting COVID-19 vaccine headache. Future prospective data may provide further enlightenment on management.

Large-scale ocean‒atmosphere circulations (LOACs) have a pronounced effect on the near-surface wind speed (NSWS). In this study, we discussed the contributions of zonal and meridional flows to NSWS changes and identify the possible association between the Northern Hemisphere Annular Mode (NAM) and the NSWS changes over eastern China from 1979 to 2017. Results show that the reduction in NSWS over eastern China was mainly dominated by the weakening of the zonal wind component. NAM has a considerable effect on the NSWS over eastern China. When the NAM exhibits positive phases, the zonal-mean westerly weakens at low-to-mid-latitudes (10°–40°N). Meanwhile, descending flows prevail near 40°N, and ascending flows persist near 65°N in the troposphere. In the lower troposphere, there are northerly anomalies at low-to-mid-latitudes and southerly anomalies at mid-to-high latitudes (40°–70°N). The anomalous meridional flows transport heat from low to high latitudes and weaken the north‒south air temperature gradient. The decreased air temperature gradient over East Asia reduces the pressure gradient near the surface, decreasing NSWS in eastern China. NAM variations could dominate (32.0 ± 15.8)% of the changes in the annual mean NSWS. Nevertheless, the contribution of NAM to the interannual changes of the zonal component in NSWS could reach (45.0 ± 12.9)%.

Safety and efficacy of vaccines against the SARS-CoV-2 coronavirus has been demonstrated in clinical trials and next by their real world use through the course of the ongoing COVID-19 pandemic. However, very rare adverse events have been detected post-authorization in certain parts of the world. This meeting report summarizes an EMA workshop’s discussion on the epidemiology, clinical presentation and biology of thrombosis with thrombocytopenia syndrome after adenovirus vector COVID-19 vaccination. General agreement was reached by international regulators, scientists and developers on the steps needed to fill the gaps in the characterization of this new syndrome. In particular, actions should be taken to improve the post-vaccination surveillance activities in low and middle income countries and investigate potential genetic predisposition factors.

Infective endocarditis (IE) is a life-threating entity with three main complications: heart failure (HF), uncontrolled infection (UI) and embolic events (EEs). HF and UI are the main indications of cardiac surgery and have been studied thoroughly. On the other hand, much more uncertainty surrounds EEs, which have an abrupt and somewhat unpredictable behaviour. EEs in the setting of IE have unique characteristics that must be explored, such as the potential of hemorrhagic transformation of stroke. Accurately predicting which patients will suffer EEs seems to be pivotal to achieve an optimal management of the disease, but this complex process is still not completely understood. The indication of cardiac surgery in order to prevent EEs in the absence of HF or UI is in question as scientific evidence is controversial and mainly of a retrospective nature. This revision addresses these topics and try to summarize the evidence and recommendations about them.

Extreme stratospheric polar vortex (SPV) events can influence winter tropospheric circulation for up to 60 d. Their impacts on air temperature have been extensively studied recently. However, there is a research gap in their effects on wind speeds and its extremes. This study aims to evaluate, for the first time, the impacts of such extreme SPV events on observed and modelled near-surface wind gusts across Europe. We have analysed wind gust data coming from: station-based observations (for the Iberian Peninsula and Scandinavia), the ERA5 reanalysis and the SEAS5 and GloSea6 seasonal forecasting systems. We assess their similarities in reproducing 4 parameters of their corresponding distributions: median, standard deviation, skewness and kurtosis. For all these datasets, the results indicate that extreme positive SPV events are followed by negative wind gust anomalies in Southern Europe and positive in Northern Europe. Whereas, negative SPV events (such as Sudden Stratospheric Warmings) have positive gust anomalies in Southern Europe and negative in the north. A central region shows negligible anomalies in both cases. This highlights the ability of SPV as a predictor for short-medium-term forecasting of extreme wind events, which would have direct applications to many socioeconomic and environmental issues such as the estimation of wind-power generation.

Abstract The 2021 IPCC report found that most studies show declining trends for the global diurnal temperature range (DTR) since the 1950s, decreasing mainly during 1960–1980. This issue is revisited here using an up‐to‐date in‐situ data set, Hadley Center Integrated Surface Database, constrained by rigorous station selection conditions. The global observed DTR trend was found to reverse during 1980–2021, increasing significantly at a rate of 0.091 ± 0.008°C decade−1. The trend was dominated by a faster rate of increasing daily maximum air temperature. This increasing observed trend in the past four decades was not fully captured in raw CMIP6 models, as models only partially capture the spatial patterns. With global CMIP6 outputs and regionally‐available observations, the global land DTR was then estimated, through emergent constraints, to be 0.063 ± 0.012°C decade−1. The study raises concern for risks of increasing DTR globally and provides new insights into global DTR assessment.

Abstract This study analyses for the first time observed surface mean wind speed (SWS) and gusts over the Iberian Peninsula (IP) in the frequency domain for 1961–2019, with the goal of exploring sources of predictability in the interannual and decadal scales. The main result is the high significant correlation between surface winds and the stratospheric polar vortex for periods close to 1 year with a time lag of about 2–3 months with respect to the antiphase, that is, a negative correlation in which the polar vortex modulates winds in the region. Furthermore, we found that the SWS and gusts are decoupled for periods between 9 and 11 years with a marked seasonal dependence in its intensity. Finally, we detected discrepancies between the spectra shown by surface winds from observations and ERA5‐Land reanalysis, suggesting that simulated data do not accurately reproduce the variability of surface wind speeds.

Tree radial growth is characterized by not only the annual ring-width increment but also shifts in the tree-ring geometric center (TRGC) if subjected to asymmetric external forcing, such as gravity downslope or prevailing winds. Previous dendrochronological studies have used the asymmetric growth derived from tree-ring widths to reconstruct wind speed changes. Here we propose a novel method that uses quantitative TRGC measurements to estimate wind speed. We investigated TRGC shifts in northeast China, where the prevailing westerly winds are strong and persistent. We found that the TRGC showed significant correlations (r ​= ​0.64, p ​

Measurement(s) specimen size • fish species Technology Type(s) homography estimation • expert’s knowledge Sample Characteristic - Organism Mediterranean fish Sample Characteristic - Environment fish market Sample Characteristic - Location Levantine Balearic sea

Abstract Background Aripiprazole is a second-generation antipsychotic, efficacious in patients with schizophrenia during acute episodes. Due to its pharmacological profile, aripiprazole may be of interest in patients with specific clinical profiles who have not been studied extensively in randomised clinical trials. Objectives To capture experience with aripiprazole in everyday psychiatric practice using the Delphi method in order to inform decision-making on the use of aripiprazole for the treatment of patients with schizophrenia in clinical situations where robust evidence from clinical trials is lacking. Methods The scope of the survey was defined as the management of schizophrenia in adults. A systematic literature review was performed to identify the different clinical situations in which aripiprazole has been studied, and to describe the level of clinical evidence. Clinical profiles to include in the Delphi survey were selected if there was a clear interest in terms of medical need but uncertainty over the efficacy of aripiprazole. For each clinical profile retained, five to seven specific statements were generated and included in a questionnaire. The final 41-item questionnaire was proposed to a panel of 406 French psychiatrists with experience in the treatment of schizophrenia. Panellists rated their level of agreement using a Likert scale. A second round of voting on eleven items was organised to clarify points for which a consensus was not obtained in the first round. Results Five clinical profiles were identified in the literature review (persistent negative symptoms, pregnancy, cognitive dysfunction, addictive comorbidity and clozapine resistance). Sixty-two psychiatrists participated in the first round of the Delphi survey and 33 in the second round. A consensus was obtained for 11 out of 41 items in the first round and for 9/11 items in the second round. According to the panellists’ clinical experience, aripiprazole can be used as maintenance treatment for pregnant women, is relevant to preserve cognitive function and can be considered an option in patients with a comorbid addictive disorder or with persistent negative symptoms. Conclusion These findings may help physicians in choosing relevant ways to use aripiprazole and highlight areas where more research is needed to widen the evidence base.

Creating a century-long homogenized near-surface wind speed observation dataset is essential to improve our current knowledge about the uncertainty and causes of wind speed stilling and recovery. Here, we rescued paper-based records of wind speed measurements dating back to the 1920s at 13 stations in Sweden and established a four-step homogenization procedure to generate the first 10-member centennial homogenized wind speed dataset (HomogWS-se) for community use. Results show that about 38 % of the detected change points were confirmed by the known metadata events, and the average segment length split by the change points is ∼11.3 years. Compared with the raw wind speed series, the homogenized series is more continuous and lacks significant non-climatic jumps. The homogenized series presents an initial wind speed stilling and subsequent recovery until the 1990s, whereas the raw series fluctuates with no clear trend before the 1970s. The homogenized series shows a 25 % reduction in the wind speed stilling during 1990–2005 than the raw series, and this reduction is significant when considering the homogenization uncertainty. The homogenized wind speed series exhibits a significantly stronger correlation with the North Atlantic oscillation index than that of the raw series (0.54 vs. 0.29). These results highlight the importance of the century-long homogenized series in increasing our ability to detect and attribute multidecadal variability and changes in wind speed. The proposed homogenization procedure enables other countries or regions to rescue their early climate data and jointly build global long-term high-quality datasets. HomogWS-se is publicly available from the Zenodo repository at https://doi.org/10.5281/zenodo.5850264 (Zhou et al., 2022).

Over the past decades, droughts and heatwaves frequently appeared in Western Europe (45°–65°N, 10°W–20°E) during boreal summer, causing huge impacts on human society and ecosystems. Although these extremes are projected to increase in both frequency and intensity under a warming climate, our knowledge of their interdecadal variations and causes is relatively limited. Here we show that the droughts and heatwaves in Western Europe have shifted in their trends in the last decade: for 1979–2012, wind speed and precipitation have both strengthened in Western Europe; for 2012–2020, however, Western Europe have experienced declined wind speed, decreased precipitation, and higher air temperature, leading to more frequent droughts and heatwaves there. Recent changes in the WE climate and extremes are related to the variations of the North Atlantic westerly jet stream. In 1979–2012 (2012–2020), the westerly jet stream shifted equatorward (poleward), which enhanced (reduced) transportation of water vapor fluxes from the North Atlantic Ocean to the European land areas, resulting in wetter (drier) surface in Western Europe. Further analysis suggests that phase changes in the Pacific Decadal Oscillation could have played a key role in regulating the position of the jet stream, providing important implications for decadal predictions of the Western Europe summertime climate and weather extremes.

Currently, the ability to automatically detect human behavior in image sequences is one of the most important challenges in the area of computer vision. Within this broad field of knowledge, the recognition of activities of people groups in public areas is receiving special attention due to its importance in many aspects including safety and security. This paper proposes a generic computer vision architecture with the ability to learn and recognize different group activities using mainly the local group’s movements. Specifically, a multi-stream deep learning architecture is proposed whose two main streams correspond to a representation based on a descriptor capable of representing the trajectory information of a sequence of images as a collection of local movements that occur in specific regions of the scene. Additional information (e.g. location, time, etc.) to strengthen the classification of activities by including it as additional streams. The proposed architecture is capable of classifying in a robust way different activities of a group as well to deal with the one-class problems. Moreover, the use of a simple descriptor that transforms a sequence of color images into a sequence of two-image streams can reduce the curse of dimensionality using a deep learning approach. The generic deep learning architecture has been evaluated with different datasets outperforming the state-of-the-art approaches providing an efficient architecture for single and multi-class classification problems.

Artificial intelligence techniques have been increasingly applied in healthcare to help in many areas, from assisting clinical diagnoses to preventing diseases. In this paper, a machine learning approach to predict cholesterol levels using non-invasive and easy-to-collect data is presented. Specifically, it uses clinical and anthropometric data gathered by nutritionists during weight loss intervention (dieting) periods. The prediction power analysis of different patient variables is aimed at improving both non-invasive diagnosis quality and screening of associated diseases. Moreover, a clustering analysis has been carried out to identify different groupings of patients that might share some characteristics that have so far remained inconspicuous but might contain a valuable diagnosis or prognosis information for clinical experts. The experiments show a mean absolute percentage error rate (MAPE) of 4.39% in cholesterol estimation via regression, as well as clustering of patients within four profiles in which variable values share commonalities among cluster members.