Winter Peak Research Articles

Seasonal Dynamics of Varicella Incidence in Bulgaria

Aim: Spatial and temporal distribution of varicella is heterogenic and insufficiently studied in Europe. The present study tries to fill the gap that exists about the seasonality of the infection in Bulgaria. Materials & methods: A 4-year retrospective study of the monthly and seasonal varicella epidemiology was performed at both national and district level. Results: In Bulgaria, varicella incidence peaked during winter (37% of the 2015–2018 cases), followed by spring (33%) and autumn (23%). Highly populated districts were more likely to follow this pattern, while less inhabited districts with smaller urbanized areas showed different periodicity of the infection. Conclusion: Winter peak in varicella incidence is positively associated with high accumulation of people in the large cities (>75,000 inhabitants).

Evaluating the Energy-Saving Effects of a Utility Demand-Side Management Program: A Difference-in-Difference Coarsened Exact Matching Approach

This paper seeks to estimate the energy-saving effect of a Demand-Side Management program, specifically Gainesville Regional Utility’s (GRU) high-efficiency central Air Conditioner (AC) rebate program in which GRU offers incentives to its customers to replace their old, low-efficiency AC unit with a high-efficiency model. We use a difference-in-difference coarsened exact matching approach to reduce the imbalance of pre-treatment characteristics between treated and control households. We find substantial annual energy savings of the high-efficiency AC program. We disaggregate the energy-saving effects into summer peak effects, winter peak effects, and non-peak effects. The results indicate that the summer peak effects are substantial and statistically significant while there are little or no statistically significant effects of the program on winter peak demand. Also, by following program participants over a three-year period, we find that there is no statistically significant rebound effect of the high-efficiency AC rebate program.

Seasonal variation in the incidence of primary CNS lymphoma.

Primary CNS lymphoma is a rare and aggressive cancer that can develop in immunocompetent individuals, but little is known about risk factors and causes of disease. Previous studies have demonstrated seasonal patterns for lymphomas and brain tumors. This study examined the seasonal incidence pattern for primary CNSlymphoma. A retrospective review was performed for patients diagnosed with primary CNS lymphoma from 2000 through 2018 at our tertiary referral center. A total of 156 patients were categorized based on month of symptom onset, month of diagnosis, and month of recurrence if they experienced a relapse of their disease. The distributions were then analyzed for seasonal patterns. There was a significant, bimodal seasonal incidence pattern based on month of symptom onset (P < .001), with peaks in July (n = 19) and December (n = 23) and troughs in March (n = 4) and September (n = 5). There were no significant differences in patients' sex, age at presentation, length of follow-up, and progression-free survival across months. There were no seasonal patterns based on month of diagnosis (P = .450) or month of disease recurrence (P = .572). The incidence of primary CNS lymphoma has bimodal peaks in midsummer and early winter, which could provide insight into causative agents and mechanisms of disease.

Prospects for the use of wind power for heat supply to consumers in the western sector of the Russian Arctic

The problem of heat supply to remote dispersed consumers of the Arctic and the possibility of such a local renewable energy source as wind to be involved in are considered. The wind potency distribution over the western sector of the Russian Arctic is shown. Areas with enhanced wind potency are identified, which are the most promising ones for heating needs. Wind energy cadastre principal characteristics of the region are studied (average longterm wind speeds, seasonal distribution in average monthly speeds, wind speed frequency, etc.). There is a winter wind speed peak in coastal areas, which coincides with the cold season peak demand for heating power and electricity. This is the main prerequisite for the successful joint operation of current boiler rooms with wind power plants (WPP), which are able to provide a significant part of the heating load. It is shown that the use of wind energy will save (displace) a significant amount of expensive imported fuel and significantly reduce the working cost of heat generated. The climatic characteristics of the region are studied, and the values of reduced (taking into account the wind) outdoor temperature are estimated. The way how the wind strains the initial picture of the distribution of average annual air temperatures is shown. The consumer heating-load curve and its provision by WPPs possible participation and boiler rooms are considered. The share of high wind potency WPPs reaches 60-80% in one year.

Epidemiology of Influenza among patients with influenza-like illness and severe acute respiratory illness in Pakistan: A 10-year surveillance study 2008-17.

In Pakistan, the burden of influenza was largely unknown, as no formal surveillance system was in place. In 2008, an influenza surveillance system was set up in eight sentinel sites. This study describes the epidemiology of influenza virus using a 10-year surveillance data from 2008 to 2017. Nasopharyngeal/throat swabs were collected from patients with influenza-like illness (ILI) and severe acute respiratory illness (SARI) along with relevant epidemiological information. The samples were tested using real-time reverse transcriptase-polymerase chain reaction for the detection and characterization of influenza viruses. A total of 17 209 samples were tested for influenza, out of which 3552 (20.6%) were positive; 2151/11 239 (19.1%) were patients with ILI, whereas 1401/5970 (23.5%) were patients with SARI. Influenza A/H1N1pdm09 was the predominant strain with 40.6% (n = 1442) followed by influenza B (936, 26.4%). Influenza A/H1N1pdm09 was predominant among the children (5-14 years) and adults (15-64 years). Influenza B strain was predominantly found in the elderly age group (≥ 65 years) accounting for 48% of cases followed by children (2-4 years) accounting for 37% of cases. This 10-year surveillance data provides evidence of influenza activity in the country throughout the year with seasonal winter peaks. The results could be used to strengthen the epidemic preparedness and response plan.

Promotion of Trombe wall through demand-side management

The present paper explores the feasibility of developing a demand-side management (DSM) strategy with the purpose of making advantage of the shifted solar energy use of Trombe wall (TW) systems to the evening hours while both the electric utility and its customers enjoy economic benefits. In many countries the winter peak hours coincide with the early evening hours and therefore replacing the electric heaters with TW systems during these hours would facilitate the peak clipping strategy in DSM. The aim of the current work is to offer means of overcoming the difficulties concerned with the implementation of such a DSM program and developing a comprehensive method to determine whether the outlined DSM program can be economically justifiable. The proposed method is examined under the North Cyprus (NC) conditions. According to the simulations performed for a 35 m2 room, integrated with a TW, an estimated 355.35 kWh of electricity is saved in each house participating in the program during the peak hours in winter. A peak clipping of 17.5-MW is expected to be achieved with 6842 houses. If a rebate of 1588.25 EUR is invested by the utility per house, a net present value of 5,031,514 EUR is estimated over a life time of 20 years. The life cycle cost indicators under different conditions and risks that might befall during the project implementation are also investigated. In all considered possibilities the savings-to-investment ratio of the DSM program is greater than 1.0, implying that there is economic feasibility.

P0559AKI SEASONALITY IN ENGLAND

Abstract Background and Aims Incidence of Acute Kidney Injury (AKI) is known to be seasonal, peaking in winter months among hospitalised patients. Previous studies have suggested that the seasonality of AKI is likely to be influenced by the seasonality of the underlying acute illnesses that are associated with AKI. Mortality of patients with AKI has also been reported as being higher in winter, reflecting well-described excess winter mortality associations. Here we describe the seasonal variations of AKI alerts in England and the associated mortality rate using linked national databases. Method Serum creatinine changes compatible with KDIGO AKI stage 1, 2 and 3 are sent by laboratories in England as AKI alerts to the treating clinicians and the UK Renal Registry (UKRR). We linked the electronic AKI alerts to the Hospital Episode Statistics (HES) data, to identify patients who were hospitalised. We carried out descriptive statistics, and investigate the seasonal effect to the 30-day patient mortality from date of getting AKI alert, using multivariable Cox regression and sequentially adjusting for age, sex, Index of multiple deprivation (IMD) and peak AKI stage Results Winter has the highest number of AKI episodes (N=81,276), which is 6% higher than that in summer (N=76,329) (Table 1). For patients who had an AKI episode and admitted to hospitals, the crude 30-day mortality is higher in the winter season when compared to the summer [HR 1.28 (1.25-1.31), p&amp;lt;0.01] (Figure 1). After adjusting season by age, peak AKI stage, IMD and sex, winter season still has significantly higher 30-day mortality than summer [HR 1.24 (1.21-1.27), p&amp;lt;0.01]. Winter mortality peak is confounded by age and AKI severity, which explained the drop of hazard ratio at winter peaks; whereas season is not confounded by deprivation and sex. The pattern of seasonality varies with age, in age group 18-39, there were 26.1% of AKI episodes in summer and 23.3% in winter, whereas in age group &amp;gt;75, there were 23.7% in summer and 27.1% in winter. Conclusion Analysis of England data confirms seasonal peak in AKI during winter months. Additionally it shows increased risk of mortality for patients with AKI in winter months. Future work will investigate the impact of comorbidities and case-mix on outcomes. By understanding the seasonal variation of AKI, we can potentially plan preventive care and improve clinical practice.

Trend of respiratory pathogens during the COVID-19 epidemic

In Italy, the first SARS-CoV-2 infections were diagnosed in Rome, Lazio region, at the end of January 2020, but sustained transmission occurred later, since the end of February. From 1 February to 12 April 2020, 17,164 nasopharyngeal swabs were tested by real time PCR for the presence of SARS-CoV-2 at the Laboratory of Virology of National Institute for Infectious Diseases "Lazzaro Spallanzani" (INMI) in Rome. In the same period, coincident with the winter peak of influenza and other respiratory illnesses, 847 samples were analyzed by multiplex PCR assay for the presence of common respiratory pathogens. In our study the time trend of SARS-CoV-2 and that of other respiratory pathogens in the same observation period were analysed. Overall, results obtained suggest that the spread of the pandemic SARS-CoV-2 virus did not substantially affect the time trend of other respiratory infections in our region, highlighting no significant difference in rates of SARS-CoV-2 infection in patients with or without other respiratory pathogens. Therefore, in the present scenario of COVID-19 pandemic, differential diagnosis resulting positive for common respiratory pathogen(s) should not exclude testing of SARS-CoV-2.

Lightening the load: quantifying the potential for energy-efficient lighting to reduce peaks in electricity demand

One of the key challenges to greater renewable electricity supplies is the temporal mismatch between non-dispatchable renewable sources and peaks in electricity demand. In addition, increased electrification coupled with the de-carbonisation of electricity generation is likely to increase the scale of demand peaks. This could force investment in carbon-intensive peaker generation or capital intensive storage capacity as well as additional transmission and distribution network capacity which may then be substantially underutilised. Whilst considerable effort has been devoted to testing a range of demand response interventions to reduce or shift consumption, less attention has been given to the ability of certain appliances to permanently reduce demand at peak through energy efficiency. In this paper, we use a published model of future energy-efficient lighting uptake together with multi-year measured lighting demand data from a sample of residential households to model the potential power (MW) and energy (MWh) reductions of a ‘business as usual’ rate of efficient lighting adoption. Our estimates suggest that whilst lighting comprises ~ 4% of overall New Zealand annual electricity consumption, it comprises up to 12% of evening peak electricity consumption in winter. As a result, we estimate that by 2029, more efficient residential lighting could reduce New Zealand’s total annual demand by 1 TWh and reduce the highest winter evening peaks (at 17:00) by at least 500 MW (9%). The winter evening demand reduction would be roughly equivalent to avoiding the need for additional generation capacity of the scale of New Zealand’s Huntly Power Stations 1–4 (coal/gas) plus the Stratford peaker plant (gas open-cycle) and has clear implications for any electricity system that is intending to transition towards ~ 100% renewable generation at least cost.

Seasonal Variations in Public Inquiries into Laryngitis: An Infodemiology Study

Acute laryngitis is a common disease with self-limiting nature. Since the leading cause is attributed to viral infections and thus self-limiting, many affected individuals do not seek professional medical help. However, because the major symptom of hoarseness imposes a substantial burden in everyday life, it might be speculated that web-based search interest on this condition follows incidence rates, with highest peaks during winter months. The aim of this study was to evaluate global public health-information seeking behaviour on laryngitis-related search terms. We utilized Google Trends to assess country-specific, representative laryngitis-related search terms for English and non-English speaking countries of both hemispheres. Extracted time series data from Australia, Brazil, Canada, Germany, the United Kingdom, and the United States of America, covering a timeframe between 2004 and 2019 were first assessed for reliability, followed by seasonality analysis using the cosinor model. Direct comparisons revealed different, representative laryngitis-related search terms for English- and non-English speaking countries. Extracted data showed a trend of higher reliability in countries with more inhabitants. Subsequent graphical analysis revealed winter peaks in all countries from both hemispheres. Cosinor analysis confirmed these seasonal variations to be significant (all P < 0.001). Public interest in laryngitis-related, online health information displayed seasonal variations in countries from both hemispheres, with highest interest during winter months. These findings emphasize the importance to optimize the distribution of reliable, web-based health education in order to prevent the spread of misinformation and to improve health literacy among general populations.

Ambulance dispatch calls attributable to influenza A and other common respiratory viruses in the Netherlands (2014-2016).

BackgroundAmbulance dispatches could be useful for syndromic surveillance of severe respiratory infections. We evaluated whether ambulance dispatch calls of highest urgency reflect the circulation of influenza A virus, influenza B virus, respiratory syncytial virus (RSV), rhinovirus, adenovirus, coronavirus, parainfluenzavirus and human metapneumovirus (hMPV).MethodsWe analysed calls from four ambulance call centres serving 25% of the population in the Netherlands (2014‐2016). The chief symptom and urgency level is recorded during triage; we restricted our analysis to calls with the highest urgency and identified those compatible with a respiratory syndrome. We modelled the relation between respiratory syndrome calls (RSC) and respiratory virus trends using binomial regression with identity link function.ResultsWe included 211 739 calls, of which 15 385 (7.3%) were RSC. Proportion of RSC showed periodicity with winter peaks and smaller interseasonal increases. Overall, 15% of RSC were attributable to respiratory viruses (20% in out‐of‐office hour calls). There was large variation by age group: in <15 years, only RSV was associated and explained 11% of RSC; in 15‐64 years, only influenza A (explained 3% of RSC); and in ≥65 years adenovirus explained 9% of RSC, distributed throughout the year, and hMPV (4%) and influenza A (1%) mainly during the winter peaks. Additionally, rhinovirus was associated with total RSC.ConclusionHigh urgency ambulance dispatches reflect the burden of different respiratory viruses and might be useful to monitor the respiratory season overall. Influenza plays a smaller role than other viruses: RSV is important in children while adenovirus and hMPV are the biggest contributors to emergency calls in the elderly.

Dynamic features of near-inertial oscillations in the Northwestern Pacific derived from mooring observations from 2015 to 2018

Near-inertial oscillation is an important physical process transferring surface wind energy into deep ocean. We investigated the near-inertial kinetic energy (NIKE) variability using acoustic Doppler current profiler measurements from a mooring array deployed in the tropical western Pacific Ocean along 130°E at 8.5°N, 11°N, 12.6°N, 15°N, and 17.5°N from September 2015 to January 2018. Spatial features, decay timescales, and significant seasonal variability of the observed NIKE were described. At the mooring sites of 17.5°N, 15°N, and 12.6°N, the NIKE peaks occurred in boreal autumn and the NIKE troughs were observed in boreal spring. By contrast, the NIKE at 11°N and 8.5°N showed peaks in winter and troughs in summer. Tropical cyclones and strong wind events played an important role in the emergence of high-NIKE events and explained the seasonality and latitudinal characteristics of the observed NIKE.

Prognosis of Hydro-Meteorological Attributes based on Simulation and Projection of Streamflow in a High-Altitude Basin using Hydrologiska Byråns Vattenbalansavdelning (HBV) Model

Subsistence of freshwater resources at high altitude regions has remained a paradox for stakeholder communities at both regional and global levels. To address such an issue, Hydrologiska Byrans Vattenbalansavdelning Light (hereafter HBV) model was used to assess hydro-meteorological shifts triggered under climate change scenarios in snow dominant region of Chitral river basin. The model performed well both during calibration and validation periods with Nash Sutcliffe Efficiency values of 0.91 and 0.81 respectively on daily time scale in the basin. The HBV was thereafter engaged for the projection of streamflow in the Chitral river basin using projected data of four statistically downscaled climate models with four emission scenarios for the 21st century. Multi-model ensemble projections of precipitation revealed an increase of up to 165% in monsoon inception period and an increase in temperature of up to 9.5°C in winter to summer transitioning period for the 2070‒2099 time slice under a high-end emission scenario. An increase of up to 122% in evapotranspiration was projected in the peak winter months for the 2070‒2099 time slice under the high-end emission scenario. Attributed to the significant increases in the temperature and the liquid precipitation, it was projected that basin streamflow had potential to increase by up to 182 % in the monsoon inception period for the 2070‒2099 time slice under the high-end emission scenario. It further indicated that precipitation might be falling as liquid rain most of the year, and snow will hardly accumulate in prognosticated future environements of the basin.

Deep Ocean Particle Flux in the Northern South China Sea: Variability on Intra-Seasonal to Seasonal Timescales

Based on time-series sediment trap observation at 1003-m depth in the northern South China Sea from 2014 to 2015, we used sinking particle flux combined with remote sensing-derived environmental data to infer mechanisms of the biological carbon pump. Total particle flux, particulate organic carbon, CaCO3, and lithogenic (inorganic)fluxes peaked in winter and autumn but showed minima in summer, ranging from 59.7 to 413.2 mg m−2 d−1, 2.1 to 18.2 mg m−2 d−1, 32.9 to 197.9 mg m−2 d−1, and 12.0 to 73.6 mg m−2 d−1, respectively. Similarly, opal flux varied from 6.9 to 109.6 mg m−2 d−1, with a prominent peak in winter and minimum in summer. However, a secondary maximum of opal in autumn was barely noticeable compared with other components. A deeper mixed-layer depth related to the northeast monsoon and surface cooling, overlapping with the effect of cyclonic eddies, is responsible for the strong winter fluxes. When an anticyclonic eddy suppresses the subsurface nutrient supply, primary production and subsequent export flux in summer were reduced substantially. With respect to maximum lithogenic and CaCO3 fluxes in autumn, a large aerosol optical depth suggests the scavenging and mineral ballast effects as potential causes. This study highlights the importance of intra-seasonal physical processes (e.g., mesoscale eddies and aerosol deposition) to the deep particle flux in the South China Sea as well as monsoonal transition.

Ambient temperature, seasonal influenza and risk of cardiovascular disease in a subtropical area in Southern China

BackgroundGiven the regular winter recurrence of influenza epidemics and the biologically plausible association between seasonal influenza and cardiovascular events, researchers assumed a valid and reliable influenza forecast could envision the timing and burden of winter surge in cardiovascular (CVD) hospitalizations. This, however, is well justified only in temperate regions. In this study, we aim to investigate the temporal association between ambient temperature, seasonal influenza and risk of cardiovascular events in a subtropical city. MethodsGeneralized additive model was used in conjunction with distributed-lag non-linear model of quasi-Poisson family to estimate the association of interest with daily CVD admissions as outcome and daily influenza admissions as predictor, while controlling for meteorological factors (i.e. temperature, relative humidity, wind speed and total rainfall) and respiratory pollutants (i.e. nitrogen dioxide, sulphur dioxide, ozone and PM10). Results were expressed in the form of relative risk (RR). ResultsUsing median as the reference value, a U-shaped association was observed between CVD admissions and temperature. A slight decrease in RR was detected mainly towards the lower end of the temperature scale after adjusting for influenza admissions. Risk of CVD admission was found to be positively associated with the number of influenza hospitalization cases; this association remained consistent and statistically significant across subgroups of age except for those aged 5–49 years. ConclusionThe slight reduction in CVD admission risk towards the lower end of the temperature scale after controlling for influenza activity might be attributed to the winter peaks of influenza, meaning that the effect of low temperature on CVD admissions might be partly mediated by influenza infection. In summary, this study reassures us that ambient temperature is independently associated with CVD hospital admissions and offers support for a positive association between seasonal influenza activity and cardiovascular events in Hong Kong.

Seasonality and schizophrenia: a comprehensive overview of the seasonal pattern of hospital admissions and potential drivers.

Schizophrenia is a severe neuropsychiatric disorder with heterogeneous aetiology mostly affecting younger people and causing immense disability. Seasonal patterns may be observed in schizophrenia hospital admissions with possible association with changing climatic parameters and socio-demographic characteristics. This study critically reviewed studies that have assessed seasonal variations of hospital admissions for schizophrenia and/or explored an association with climate parameters and/or other potential factors. Following PRISMA guidelines, a systematic literature search was conducted using electronic databases (e.g. MEDLINE, Science Direct, PsycINFO, Pub Med) from inception to February 29, 2020. Thirty five papers were identified, of which only six (17.1%) examined evidence for a seasonal pattern or monthly excess of hospital admissions and the remaining twenty nine (82.9%) assessed climatic and socio-demographic attributes relating to the seasonal pattern or increased hospitalisation for schizophrenia. While most studies reported a summer peak in hospital admission rates, other studies reported a winter peak. Most of the evidence indicated that higher temperatures (> 28°C) were positively correlated with schizophrenia admission rates. The individual effects of other climatic parameters (e.g. relative humidity, rainfall, atmospheric pressure, sunlight) were less frequently assessed. Males, people of 21-60years old, and those married were more vulnerable to climatic variability specifically to higher temperatures. Further studies using large sample sizes, analysis of a wide range of interacting environmental variables and sophisticated statistical approaches are needed to better understand the underlying mechanisms involved. This will also provide more reliable statistical evidence that will help in the prevention and better management of cases.

Gap-filling snow-depth time-series with Kalman Filtering-Smoothing and Expectation Maximization: Proof of concept using spatially dense wireless-sensor-network data

We assessed the performance of Kalman Filtering-Smoothing and Expectation Maximization (EM-KF) in gap filling snow-depth sensor data. To this end, hourly snow-depth data from three spatially dense wireless-sensor networks were randomly removed and imputed using EM-KF. Maximum gap size was 40+ hours and differences between artificially removed and gap-filled data larger than 20 cm were removed before computing Root Mean Square Error and Bias. These differences are spurious over- and underestimations that can generally be identified through visual inspection, likely due to instability in the gap-filling process. The expected accuracy of EM-KF in this initial, controlled proof of concept is close to measurement uncertainty (1 to 2 cm for ultrasonic depth sensors). Compared to regressing missing data against nearby sensors, a frequently used strategy in the field, EM-KF tends to yield smaller errors in networks with a comparatively large number of co-located sensors (nine and eight as opposed to four in a third network). In these data-rich networks, maximum differences in daily Root Mean Square Errors between EM-KF and a regression are up to 6 to 8 cm at a daily time scale, with peaks in winter and in particular during snowfalls. EM-KF yields superior results particularly during snowfalls, likely because it exploits the temporal structure and uncertainty in the data through a state-space model. In the third network with fewer co-located sensors, differences in accuracy between EM-KF and a multilinear regression were inconsistent. This implies that the performance of EM-KF benefits from increasing the amount of available information and with increasing dependency of data across nodes. Temporally and spatially dense snow-depth data are being increasingly collected in operational contexts: EM-KF may support supervised filling of gaps in these data – particularly during snowfall events – and thus provide continuous-time information for avalanche or water-resources forecasting in snow-dominated regions. Automatic, unsupervised gap-filling using EM-KF will necessarily need more research to identify reasons of spurious over- and underestimations. Future work should also upscale this proof of concept to operational sensor networks spanning large water basins to bring conclusions closer to real-world applications.

Winter peaks in web-based public inquiry into epistaxis

PurposeEpistaxis represents the most frequent ear, nose, throat-related emergency symptom. Seasonal variation in epistaxis incidence, with peaks during winter months, is widely accepted, although the literature itself remains inconclusive. The objective of this study was to evaluate public inquiry into nose bleeding, by considering Google-based search query frequency on “Epistaxis”-related search terms and to assess possible seasonal variations globally.MethodsEpistaxis-related search terms were systematically collected and compared using Google Trends (GT). Relative search volumes for the most relevant epistaxis-related terms, covering a timeframe from 2004 to 2019 were analysed using cosinor time series analysis for the United States of America, Germany, the United Kingdom, Italy, Canada, Australia, and New Zealand.ResultsGraphical representation revealed seasonal variations with peaks during winter months in the majority of countries included. Subsequent cosinor analysis revealed these variations to be significant (all p < 0.001).ConclusionPublic interest in seeking epistaxis-related information through the Internet displayed seasonal patterns in countries from both hemispheres, with the highest interest during winter months. Further studies exploring causality with environmental factors are warranted.

Experimental investigation of underground seasonal cold energy storage using borehole heat exchangers based on laboratory scale sandbox

In order to overcome the intermittent nature of renewable energy resources, borehole thermal energy storage (BTES) systems are found to be a feasible option these days. Previous research data shows that most of the BTES projects are related to heat storage and there are very few underground cold storage applications. The proposed research work is based on the experimental strategy to determine the extracted energy storage potential in typical weather condition areas. It emphasizes on the mathematical model for soil extracted energy storage system and derives similar function relationship of soil TES system based on similarity theory. A laboratory-scale sandbox is designed with similar scale factor n = 20. Sandbox system is operated in peak winter months from October to March according to the weather data for Dunhuang, China. Approximately 69 % of the input energy is charged into the soil. Soil temperature is reduced up to 11 °C during the extraction period. The maximum heat flux value is recorded 65 W.m−2. The experimental results reveal the practicality of proposed research method. It can be used to fulfill cooling load requirements for air conditioning systems and solar thermal power plants located in desert areas with water shortage issues.

Meteorological and chronobiological factors and the occurrence of acute aortic dissection.

Although a number of studies have demonstrated seasonal variations in acute cardiovascular events, the association between winter and low temperatures and the incidence rate of acute aortic dissection has not been fully elucidated. In this study, we investigated the association between meteorological and chronobiological factors and the occurrence of acute aortic dissection classified by the Stanford type, sex and age. We retrospectively collected 131 patients who had been admitted consecutively to our institution with acute aortic dissection, including 58 type A patients and 73 type B patients, from January 2013 to December 2017. The meteorological data were downloaded from the homepage of the Japan Meteorological Agency. The daily incidence of aortic dissection was higher in winter (10.2%) than in fall (5.3%) (P = 0.04), and a significant winter peak was also observed in the sub-groups of males and type B, while there were no significant differences in the proportions of type A, female, and ≤ 70- and > 70-year-old patients. The maximum, mean and minimum temperatures on the days with aortic dissection were significantly lower than on the days without aortic dissection. Divided into four seasons, lower temperatures were found only in spring. The most significant and greatest difference was observed between the maximum temperature on the day of aortic dissection and that at 2days earlier. The multivariate logistic regression analysis showed that the difference in the maximum temperature between the day of and 2days before the incident (odds ratio 0.91; 95% confidence interval 0.87-0.96; P < 0.01) as well as the maximum temperature (odds ratio 0.97; 95% confidence interval 0.95-0.99; P = 0.02) were significantly associated with the incidence of aortic dissection. Cold weather and a sudden decrease in temperature might trigger aortic dissection, although the influence might differ among sub-groups.