Night Peak Research Articles

Serum lipid and lipoprotein profiles and their association with intraocular pressure in primary open-angle glaucoma: an observational cross-sectional study in the Chinese population

BackgroundGlaucoma is a leading cause of vision impairment and permanent blindness. Primary open-angle glaucoma (POAG) is a prominent type of primary glaucoma; however, its cause is difficult to determine. This study aimed to analyze the serum lipid profile of Chinese POAG patients and assess its correlation with intraocular pressure (IOP).MethodsThe study included 1,139, 1,248, and 356 Chinese individuals with POAG, primary angle closure glaucoma (PACG), and controls, respectively. Peripheral whole blood samples were collected at the time of diagnosis. Enzymatic colorimetry was used to determine serum levels of different lipids: high-density lipoproteins (HDL), low-density lipoproteins (LDL), triglycerides, cholesterol, and very low-density lipoproteins (VLDL). Additionally, immunoturbidimetry was used to quantify serum levels of apolipoproteins A (APOA), B (APOB), E (APOE), and lipoprotein A [Lp(a)], while intraocular pressure (IOP) was measured in all patients with POAG.ResultsAfter adjusting for age and sex, patients with POAG exhibited elevated serum levels of VLDL, APOA, and APOE but mitigated cholesterol levels compared with the control participants. Significantly lower serum triglyceride, VLDL, and Lp(a) levels were found in patients with PACG than in control participants. Serum cholesterol (P = 0.019; β = -0.75, 95% confidence interval [CI]: -1.38 – -0.12) and HDL levels (P < 0.001; β = -2.91, 95% CI: -4.58 – -1.25) were inversely linked to IOP in patients with POAG, after adjusting for age, sex, and ocular metrics. In addition, serum Lp(a) levels were correlated with the average IOP (P = 0.023; β = -0.0039, 95% CI: -0.0073 – -0.006) and night peak (P = 0.027; β = -0.0061, 95% CI: -0.0113 – -0.0008) in patients with POAG.ConclusionsSignificantly different serum lipid and lipoprotein profiles were observed in POAG and PACG patients. This study highlighted the differences in serum lipid and lipoprotein levels among Chinese POAG patients and their relationship with IOP and IOP fluctuation. Serum lipid and lipoprotein profiles should be considered while evaluating glaucoma risk.

Understanding the potential of taxi sharing: The case of Chengdu

The emergence of taxi sharing enhances urban transport efficiency and reduces carbon emissions. Using GPS tracking data from taxis in Chengdu, China, this study first outlines conditions for identifying shareable taxi orders based on their origins and destinations. We then develop a three-phase computational model to optimize matches among all potential shareable orders, calculating the shareable mileage and the proportion of original mileage that could be shared. Our comprehensive temporal and spatial analysis reveal a significant market for taxi sharing in Chengdu, with higher potential on workdays than non-workdays and four distinct demand peaks throughout the day. The morning peak on workdays and the night peak on non-workdays are particularly pronounced. Most shareable orders originate within major city districts. We find a positive correlation between the potential of taxi sharing and average traffic speed, and negative correlations with order volume, regional economic development, and population density. Functional zones related to Enterprises, Motorcycle Services, and Transportation Services exhibit significantly higher sharing potential. Compared to traditional taxi operations, taxi sharing significantly reduces total travel mileage. This quantitative analysis offers insights into the potential demand for taxi sharing among urban residents and may help government authorities optimize taxi resources for the sustainable development of urban transport.

Adept Domestic Energy Load Profile Development Using Computational Intelligence‐Based Modelling

Most studies undertaken on energy usage in buildings have shown that energy utilization is widely influenced by occupancy presence and occupants’ activities relative to the indoor environment, which may be widely dependent on weather conditions and user behaviors. However, the core drawback that has negated the proficient estimation of energy is the modelling of occupant behavior relative to energy use. Occupants’ behavior is a complex phenomenon and has a dynamic nature influenced by numerous internal, individual, and circumstantial factors. This research proposes a computational intelligence‐based model for household electricity usage profile development as impacted by core input variables—household activities, household financial status, and occupancy presence. The incorporation of these variables and their adaptiveness is expected to address and resolve unpredictability or nonlinearity concerns, thus allowing for adept energy usage estimation. The model addresses issues unresolved in many other studies, such as occupancy determination (deduction) and the impact on energy consumption. The performance precision of this approach has been demonstrated by trend series analysis, demand analysis, and correlation analysis. Based on the performance indicators including mean absolute percentage error (MAPE), mean square error (MSE), and root mean square error (RMSE), the model has shown proficient predictive output with respect to the metered (actual) energy usage data. The proposed model, compared to actual data, showed that average MAPE values for the respective day standard, morning peak, and night peak demand period (TOUs) are 2.8%, 1.88%, and 0.31% for all income groups, respectively. The aptitude to improve on energy prediction and evaluation accuracy, especially in these periods, makes it a highly suited tool for demand‐side management, power generation, and distribution planning activity. This will translate into power system reliability, reduce operation cost (lowest cost), and reduce greenhouse emissions (environmental pollution), thereby cumulating into sustainable cities.

Observation of nitrogen oxide-influenced chlorine chemistry and source analysis of Cl2 in the Yangtze River Delta, China

Atmospheric chlorine (Cl)- and nitrogen (N)-containing species such as Cl2, ClNO2, and N2O5 participate actively in atmospheric chemistry by triggering radical reactions that lead to the formation of secondary pollutants. Despite of their importance in atmospheric chemistry, the measurements of these species are scarce, due to analytical challenges. Herein, we report observation results of Cl2, ClNO2, and N2O5 from measurements using high-resolution time-of-flight chemical ionization mass spectrometry (HR-ToF-CIMS) in Shanghai and Changzhou in the highly industrialized and populated Yangtze River Delta (YRD) of East China. In Changzhou, the maximum concentrations of N2O5, ClNO2, and Cl2, were 0.4, 1.3, and 0.5 ppbv (1-min averages), respectively, while they were 0.5, 5.7, and 1.1 ppbv, respectively, in Shanghai. Much higher ClNO2 levels were found in Shanghai compared to Changzhou, although the concentrations of the precursor (N2O5) are similar, indicating different heterogenous N2O5 uptake and Cl activation efficiency at these two sites. The diurnal variation of Cl2 in Shanghai shows a strong daytime peak, which is contradictory to its fast lost by photolysis during daytime; the diurnal pattern of Cl2 in Changzhou shows a prominent night peak and a much smaller daytime peak than that in Shanghai. The heterogeneous uptake of ClNO2 and the photolysis of O3 on chloride-containing aerosols are believed to contribute to efficient Cl2 formation at night and day, respectively. The estimated heterogeneous uptake coefficient of O3 is 0.004 ± 0.007, with a maximum of 0.034. Further analysis on these heterogeneous reactions with the help of aerosol composition data (chloride, liquid water content, pH etc.) was also performed to ascertain the role of the secondary formation of Cl2 in daytime Shanghai. Through simple estimation methods, the maximum daytime production rate of Cl2 was estimated to be 0.95 ppbv h−1, while daytime photolysis of Cl2 contributed to 98% of Cl formation. Our results indicate that there is a large secondary source of Cl2 in the YRD region during the day, which can contribute substantially to Cl formation and requires more investigations.

Diurnal cycle of precipitation over the southeastern Tibetan Plateau and surrounding regions: Insights from intensity–frequency structure

AbstractBesides the respective importance of the frequency, intensity and diurnal cycle of precipitation, the diurnal cycle of intensity–frequency structure could reveal more physical details about the evolution process of precipitation systems. Here, an objective method to quantitatively depict the diurnal cycle of intensity–frequency structure of precipitation is proposed, and applied to complex terrains of the southeastern Tibetan Plateau (TP) and its surroundings. Results show the diurnal cycle of precipitation over the high terrain has a unimodal night peak, while low terrain with a frequency‐dominated night peak and an intensity‐dominated afternoon peak. Both weak and intense precipitation are more frequent at night than those in the afternoon over unimodal regions compared to bimodal regions. Further analysis reveals different diurnal evolution process of intensity–frequency structure within unimodal and bimodal regions, respectively, which reflects different spatiotemporal traits and evolution process of precipitation. Among unimodal regions, the elevated southeastern TP is featured by the synchronous decrease in both weak and intense precipitation from the night peak to the afternoon minimum. While the decrease of total precipitation in regions with lower terrain is dominated by the decrease of intense precipitation, but with an increase in weak precipitation simultaneously. Regarding bimodal regions, the intense precipitation over southern Hengduan Mountains has a more prominent role in leading the diurnal cycle of precipitation amount, compared with that over the southeastern Yungui Plateau. The proposed method provides a new perspective with more physical details to investigate precipitation characteristics in complex terrains, which could be further used to reasonably evaluate and improve the performance of numerical models.

Evaluation of diurnal and postural intracranial pressure employing telemetric monitoring in idiopathic intracranial hypertension

ObjectivesIntracranial pressure (ICP) has been thought to vary diurnally. This study evaluates diurnal ICP measurements and quantifies changes in ICP occurring with changes in body posture in active idiopathic intracranial hypertension (IIH).MethodsThis prospective observational study utilized telemetric ICP monitoring in people with active IIH. Participants had the Raumedic p-Tel ICP intraparenchymal device (Raumedic, Hembrechts, Germany) surgically inserted. Changes in ICP in the supine position were evaluated. Then, the ICP was measured in the standing, sitting, supine, left lateral decubitus positions and with coughing and bending. Ultimately, changes in ICP over the course of 24 h were recorded. ISRCTN registration number 12678718.Results15 women were included, mean (standard deviation) age 29.5 (9.5) years, body mass index 38.1 (6.2) kg/m2, and baseline mean ICP of 21.2 (4.8) mmHg (equivalent to 28.8 (6.5) cmCSF). Mean ICP rose with the duration in the supine position 1.2 (3.3) mmHg over 5-minutes (p = 0.175), 3.5 (2.8) mmHg over 30-minutes (p = 0.0002) and by a further 2.1 (2.2) mmHg over 3 h (p = 0.042). Mean ICP decreased by 51% when moving from the supine position to standing (21.2 (4.8) mmHg to 10.3 (3.7) mmHg respectively, p = 0.0001). Mean ICP increased by 13% moving from supine to the left lateral decubitus position (21.2 (4.8) mmHg to 24.0 (3.8) mmHg, p = 0.028). There was no significant difference in ICP measurements at any point during the daytime, or between 5-minute standing or supine recordings and prolonged ambulatory daytime and end of night supine recordings respectively. ICP, following an initial drop, increased progressively in conjunction with lying supine position from 23:00 h to 07:00 h by 34% (5.2 (1.9) mmHg, p = 0.026).ConclusionThis analysis demonstrated that ICP does not appear to have a diurnal variation in IIH, but varies by position and duration in the supine position. ICP rose at night whilst the patient was continuously supine. Furthermore, brief standing and supine ICP measures in the day predicted daytime prolonged ambulatory measures and end of night peak ICP respectively. This knowledge gives reassurance that ICP can be accurately measured and compared at any time of day in an ambulant IIH patient. These are useful findings to inform clinical measurements and in the interpretation of ICP analyses in IIH.Trial registrationISTCRN (12678718).

COMBINED METHOD OF ELECTRIC ENERGY CONSUMPTION MANAGEMENT OF PRODUCTION FACILITIES

The article investigates the methods of power consumption control. It is shown that the power shortage during peak hours makes it difficult to maintain a balance between generation and consumption capacity, which leads to the need to introduce restrictions on the electrical load of industrial consumers and the development of methods and tools to control power consumption. The need to manage energy consumption is due to a number of reasons, including: 1) the significant difference between peak load and night failure in power systems; 2) insufficient regulatory capacity of thermal power plants and nuclear power plants to cover the variable part of load schedules; 3) unfavorable tendency to reduce the share of shunting capacity in power systems caused by the consolidation of power units; 4) significant capital and energy costs associated with the construction and operation of peak units; 5) technical feasibility and economic feasibility of artificial alignment of load schedules. It is shown that the following methods of power consumption control are currently known: instantaneous rate; at the ideal norm; management on the forecast value; control with the use of average power on a moving time interval (moving window method) and combined methods that use different combinations, as well as the distribution of control influence between consumers - regulators (resource allocation method). It is better to consider such a control method that provides for a larger number of managed consumers random time distribution of possible short-term emissions, their minimum absolute value, as well as more complete use by the consumer of the declared capacity or allocated power and energy limits. According to these criteria, the listed management methods are compared. Moreover, the method of instantaneous rate is implemented in control or automatic control using a signal proportional to the average power for 1, 2 or 3 minutes, the method of the ideal norm involves measuring the average power of the consumer for short periods of time (up to three minutes) and comparing this value with the declared ( or limit) power, control with prediction is that the control signal is formed as the difference between the amount of possible power and predicted at the end of the control cycle. To increase the efficiency of power consumption management, a combined control method is proposed, which is a synthesis of two known methods - control at the ideal norm and control over the predicted value of power consumption, which combines the advantages of both methods. The condition of management is maintenance of such mode of power consumption at which the set capacity is not exceeded and its set value is used as much as possible. Fulfillment of this condition is provided by working off of the restrictions set to each step of management. Due to the fact that different control steps have different control reactions to the real process, appropriate control methods are used for different steps. In the first steps, when there is enough time to adopt the optimal control effect and it can be adjusted, the control is based on the forecast value of electricity consumption, in the last steps, which have special responsibility for the control process; control is carried out by the ideal norm. Thus, this method combines the advantages of forecast management (control effect is justified) and the method of management at the ideal norm (in the last step of management, which allows optimal use of the remaining power limit and not exceed the specified value) with a priori justified order of consumers-regulators.

RNN-Assisted Feature-Extraction VMD for Load Classification in Cloud Computing Platform

Cloud computing can improve the calculation and data storage ability for the control center in the power system. A new framework of the cloud-based control center is proposed in this paper. This cloud computing system can collect the load data from smart meters of the grid and classify demand-side management (DSM) loads that meet the specific requirements. The selected loads belong to the off-peak period (from 21:00 to 07:00 next day) and can contribute to shifting the night peak load. A feature extraction combined with Variational Mode Decomposition (FE-VMD) of the loads which can be trained in recurrent neural network (RNN) is proposed in this paper. Using the feature value to replace the actual load data, input data can be significantly reduced which is suitable for a vast amount of load in the power system. A case study of real load data from 200,000 customers has been classified with this method, and the accuracy is compared with the other methods. From simulation with MATLAB, it can be seen that the FE-VMD combined with the RNN method provides the best result of 89.8% recognition accuracy among these methods.

Spatiotemporally heterogeneous willingness to ridesplitting and its relationship with the built environment: A case study in Chengdu, China

The capability of ridesplitting service to address current urban transportation problems has attracted considerable research interest in recent years. Given that ridesplitting needs an adequate user base to realize “sharing”, its success highly depends on a comprehensive understanding of people’s willingness of using it. However, previous studies mainly focused on the ridesplitting willingness based on questionnaire surveys at the individual level, which may help transportation network companies find potential users, but lacked studies on people’s ridesplitting willingness from the perspective of the built environment and time-space integration, because the macro urban elements are difficult to be perceived by individuals and thus hard to reflect in questionnaires. Thus, this study estimates the ridesplitting willingness rate of different areas in a city at different times of the day by building a model on the shared order rate and shareability from the real-world DiDi Chuxing dataset, using Chengdu, China, as a case study. The spatial lag model (SLM) is further utilized to exam the relationship between the willingness rate, built environment and transportation-related variables. Results revealed the ridesplitting willingness rate has a significant spatiotemporal pattern between the urban centre and urban periphery and can be divided into morning peak, noon plateau, afternoon valley, night peak, and midnight valley. SLM models indicate that the ridesplitting willingness rate has a significant spatial dependency on its vicinity areas at the origin of the daytime periods or at the destination at night. The distance to urban centre, the distance to railway station, travel demand, accessibility to public transit, land use mixture, and the trip purpose are found to be the most relevant variables with the willingness rate, while the points of interest (POIs) are almost irrelevant. The findings of this study can be helpful to the future promotion of this sustainable service and formulation of policy to improve service quality.

Particulate Matter and Adverse Respiratory Health Outcome: Exposure of Street Vendors in Kolkata city in India

Exposure to airborne particulates is a major occupational hazard especially for outdoor workers who spending time outdoors at ground level getting exposed to traffic fumes and roadside dust. Aim of this study was to assess respiratory health symptoms and determine the change of lung functions of the roadside vendors and its association with traffic-related exposures and their working experience. A cross-sectional study was conducted in key market places of Kolkata – Gariahat (GH), Esplanade-Park Street (EP), Shyambazar-Hatibagan (SH) and Behala (BE). Particulate (PM10 and PM2.5) levels and meteorological parameters (wind speed, temperature and relative humidity) were monitored in the morning, afternoon and night over the period of October 2019 to February 2020. Lung function status (FEV1, FVC, FEV1/FVC ratio and PEF) was measured for 111 purposively selected participants. PM concentration was observed higher in the morning and night peak hours for all sites. At SH area the average occupational exposure level for PM10 and PM2.5 were observed as 1502.22 μg/m3h and 684.01 μg/m3h. Percentage predicted FEV1 (%FEV1) of street vendors was found decreasing with their work experience and the worst-case scenario was observed in the EP area, with the corresponding value being 70.75%, 49.15% and 47.3% for less than 10 years, 10 to 20 years and more than 20 years participation respectively. The higher particulate burden was observed to have declining lung function status of the street vendors. A strong policy framework should be adopted to improve outdoor working environment for outdoor workers.

Abnormal night melatonin level in a patient with well-controlled epilepsy without sleep disturbances – could it be associated with levetiracetam therapy: A case report

We present a case report of a 23-year old male with newly diagnosed epilepsy manifested with generalized tonic seizures. Levetiracetam (LEV) was started and the patient was seizure free. The patient demonstrated intermediate chronotype determined by the Morningness-Eveningness Questionnaire (MEQ). There was no epileptiform activity on electroencephalography (EEG) and polysomnography (PSG), sleep architecture disturbances (PSG) or daytime sleepiness (Epworth sleepiness score, Multiple sleep latency test) at the onset and after 3 months of LEV therapy. The melatonin serum levels after 3 months of LEV treatment were 22.00 pg/ml at 3 a.m. and 23.60 pg/ml at 8 a.m. - there was no normal night peak concentration. This abnormality may be associated with a later night peak melatonin concentration, the treatment with levetiracetam being a possible explanation. We consider the presented clinical case of special interest because of the combination of absence of normal night peak melatonin concentration, normal sleep parameters and non-extremely presented chronotype. We suggest that such patients could benefit from add-on therapy with melatonin.

Voltage Stability Analysis of an Interconnected Power System Considering Varied Output of Wind Power Plants

A sound power system must have voltage values at all buses that do not exceed the tolerance limit of ± 5% with small power losses. Voltage instability can be caused by interference or sudden power generation outage from the system. Indonesia's Southern Sulawesi power system has been interconnected with wind power plants located in Sidrap Regency and Jeneponto Regency. Wind speed energy used by wind power plants to generate electricity vary and not always constant. Hence, this can cause fluctuations and produce varied outputs that will affect the voltage profile and stability of the Southern Sulawesi interconnection system. Therefore, it is essential to assess the voltage stability of the Southern Sulawesi power system after the integration of Sidrap and Jeneponto WPPs. First, this study analyzes the voltage profile of the Southern Sulawesi interconnection system voltage after integrating the Sidrap wind power plants and Jeneponto Wind Power Plant during the peak day load and peak night load. Second, the study assesses the voltage stability with a varied output power of both Sidrap and Jeneponto Wind Power Plant. After integrating Sidrap and Jeneponto Wind Power Plants, the results showed that the voltage values at all system buses are stable and within the IEEE standard (between 0.95 p.u. and 1.05 p.u.). In addition, the voltages of the Southern Sulawesi power system with various outputs of both WPPs are still stable and within the IEEE standard.

Comparison between IRI-2012, IRI-2016 models and F2 peak parameters in two stations of the EIA in Vietnam during different solar activity periods

This paper presents observations of the F2-layer critical frequency (foF2) and height (hmF2) obtained at Phu Thuy (21.03°N, 105.95°E) and Bac Lieu (9.28°N, 105.73°E) observatories in Vietnam. The data have been examined for all seasons, during high and low solar activities, and compared with the foF2 and hmF2 of the International Reference Ionosphere model (IRI-2012, IRI-2016 two options: AMTB, SHU). Phu Thuy observatory is located at the Northern Crest of the EIA and Bac Lieu in the trough of the EIA, therefore the foF2 values at Phu Thuy are higher than at Bac Lieu. The results show that the IRI-2012 model estimates well the observed foF2 at both stations during high and low solar activities. During high solar activity, models estimate well the calculated hmF2 in summer for both stations. At Phu Thuy in equinoxes AMTB reproduces the night peak better than IRI-2012 and SHU, but higher and later about 2–3 h, in winter the performance of AMTB is worst. At Bac Lieu, the IRI-2016 options reproduce the night peak and underestimates it, but IRI-2012 does not do it. The pre-noon peaks are underestimated by all the models, except IRI-2012 which overestimates the hmF2 pre-noon peaks at Bac Lieu. At Phu Thuy the pre-noon hmF2 peak is higher than the post-dusk one. At Bac Lieu the post-dusk peak is higher except in summer. During low solar activity, the IRI models estimate relatively well the shape of the calculated hmF2 at both stations. The IRI-2012 models explained better the observed foF2 (deviation of 2.5%) during solstices than during equinoxes (14.2%) for high solar activity. The IRI-2012 model explained better the observed foF2 in spring (7.8%) than in autumn (19.9%), matched better the calculated hmF2 in solstice (5.4%) than during equinoxes (11.8%). The performance of AMTB is worst at both stations for both the high and low solar activity periods except in autumn at Bac Lieu for the low solar year. IRI-2012 is best at the stations for both high and low solar activity periods, except in summer for the high solar activiy year when SHU is the best at Phu Thuy. These results can be used to improve the future IRI model.

Association of clinic and ambulatory heart rate parameters with mortality in hypertension.

Resting heart rate (HR) taken in the office has been shown to be associated with cardiovascular outcomes in the general population, hypertension and heart failure. It is unknown whether 24-h oscillographic pulse rate measurement as an approximation of HR derived from ambulatory blood pressure monitoring (ABPM) associates with cardiovascular outcomes in hypertensive patients. We evaluated ABPM recordings from 56 901 patients with complete 3373 421 HR measures entering the final analysis from the Spanish Blood Pressure Monitoring Registry for a median follow-up time of 5.1 years. We explored the association of office HR, mean 24-h HR, mean day HR, mean night HR as well as day-night HR differences, morning mean HR, morning HR surge and night peak HR to all-cause death, cardiovascular death and noncardiovascular death. Data were analyzed by Cox regression analysis, analysis of variance and chi-square test. The Spanish ABPM Registry recorded data in 223 primary care centers in Spain from 2004 until 31 December 2014 at the end of recruitment. Office HR was 3.5 bpm higher than mean 24-h HR, office mean HR versus mean night was 10.4 bpm higher and mean day versus mean night HR 9.3 bpm higher, while there were no relevant difference between office and mean day HR. Office mean, 24-h day and night HR more than 90 bpm were associated with an increased risk for all-cause and noncardiovascular death, whereas for cardiovascular death only mean night HR was predictive. The strongest association to all-cause death was observed with mean night HR [hazard ratio 3.80 (2.87-5.03)], mean 24-h HR [2.85 (2.30-3.54)] and mean day HR [2.22 (1.83-2.70)]. Day-night dipping of more than 8 bpm was associated with a 20% lesser risk on all-cause, cardiovascular and noncardiovascular death. Results were robust after adjusting for relevant risk indicators. HR parameters derived from ABPM provide important information, in particular association with death by mean night HR, mean 24-h HR and reduced day-night HR dipping less than 8 bpm superior to office HR.

Application on traffic flow prediction of machine learning in intelligent transportation

With the development of human society, the shortcomings of the existing transportation system become increasingly prominent, so people hope to use advanced technology to achieve intelligent transportation. However, the recognition rate of most methods of detecting video vehicles is too low and the process is complicated. This paper uses machine learning theory to design a variety of pattern classifiers, including Adaboost, SVM, RF, and SVR algorithms, to classify vehicles. Support vector regression (SVR) is a support vector regression algorithm based on the basic principles of support vector machine (SVM) and then generalized to the regression problem. This paper proposes a short-term traffic flow prediction model based on SVR and optimizes SVM parameters to form an improved SVR short-term traffic flow prediction model. It can be obtained from experiments that the classification error rate of support vector regression (SVR) is the lowest (3.22%). According to the prediction of morning and night peak hours, this paper concludes that the MAPE of SVR is reduced by 19.94% and 42.86%, respectively, and the RMSE is reduced by 29.71% and 47.22%, respectively. Experiments show that the improved algorithm can obtain the optimal parameter combination of SVR faster and better and can effectively improve the accuracy of traffic flow prediction. The target tracking pedestrian counting method proposed in this paper has significantly improved the counting accuracy. The calculation of HOG features can be further expanded, such as the selection of neighborhoods when calculating HOG features, and finally a more efficient pedestrian counting framework is implemented.

Timing of CCl4-induced Liver Cirrhosis Modulates Locomotor And Melatonin Circadian Rhythms In Rats

Patients with liver cirrhosis usually suffer from disturbances in sleep and melatonin rhythms. Since their homeostasis is tightly interconnected and regulated by the circadian clock, we aimed to use them as biomarkers to investigate if the time of exposure to a hepatotoxin would affect the level of haptic injury and possibilities of recovery. This is to simulate a situation where an organism is exposed to a hepatic toxin regularly at a specific time of day. Probably due to an environmental or lifestyle constraint. We monitored the circadian rhythms of locomotor activity and melatonin as biomarkers for liver health level in a chronic CCl4-induced cirrhotic rat model. Cirrhotic rats expressed circadian locomotor activity that has shallower amplitudes compared to controls with higher activity during daytime and lower activity during the night compared to controls. Night CCl4-treatment appeared correlated with more rhythm disturbance than daytime treatment. For melatonin, daytime CCl4-treatment abolished circadian rhythmicity, but night treatment was correlated with 6-hour rhythm advance and reduction of the melatonin’s night peak. Recovery was partial; however, it was better from daytime treatment than from night treatment. Histopathological evaluation of liver confirmed the above findings showing evidence of more severe liver lesions in the night than daytime treated rats. These results suggest that the CCl4 hepatotoxin effects are clock modulated, which imposes careful consideration of the time factor in the design of research experiments and medical treatment programs for liver and sleep patients.

Could electricity demand contribute to diversifying the mix and mitigating CO2 emissions? A fresh daily analysis of the French electricity system

This paper introduces an innovative line of study to the current literature, by assessing the interactions, in France, between electricity sources, and periods with differing electricity consumption; namely morning off-peak, morning peak, middle off-peak, and night peak, using high-frequency data, specifically, daily data. This paper also analyses the impact of these interactions on both the diversification of the electricity mix, and on carbon dioxide emissions. Thus, this research could help identify the conditions needed, in both supply and demand, for a successful transition towards renewable energies. A Vector Autoregressive model has been employed to detect the presence of endogeneity, and to show the interactions between electricity supply and demand. Consumption in France has been problematic for the management of a portfolio containing rigid and intermittent base load sources. High peak consumption at night has increased the necessity to deploy a flexible electricity generating source, in other words, fossil fuels, and is one of the reasons for nuclear de-activation. In comparison, high morning peak consumption is rational and desirable. Indeed, morning peaks have been satisfied by a portfolio of renewable energies, decreasing the harmful impact of electricity on the environment, and keeping electricity costs low.

Progesterone and Cortisol Levels in Blood and Hair of Wild Pregnant Red Deer (Cervus Elaphus) Hinds.

Simple SummaryThe red deer, also known as the royal deer or European deer, is an artiodactyl mammal belonging to the Cervidae family, widely diffused in almost all of continental Europe. At the beginning of autumn in the Northern Hemisphere, the mating season begins. The males of red deer, called stags, are synchronized with the females, called hinds; indeed, at the beginning of the mating season, they show a marked increase in testosterone to match the hinds’ estrus cycle. Gestation lasts about 230 days, so that calves are born in mid to late spring, the most favorable period for their survival. Scientific data on the reproduction physiology of this peculiar species in wild conditions are lacking, including hormonal variations during pregnancy. The present study describes mean levels of two critical hormones, cortisol and progesterone, in both blood and hair of wild pregnant red deer hinds. Correlation analysis confirmed how animals hunted in later phases of pregnancy have higher hair progesterone.The red deer (Cervus elaphus L., 1758) is one of the largest deer species in the world. Females are seasonal polyestrous, with negative photoperiod: the increase of the night peak of melatonin determines the secretion of GnRH and, therefore, LH and FSH. To date there is little information regarding the hormonal control during pregnancy for this species; this could be due to the difficulty of sampling wild subjects, while farmed animals’ hormonal concentrations may not reflect the physiology of the animal in a natural state. In this study we evaluated the concentration of cortisol and progesterone, extracted from blood and hair, on 10 wild and pregnant red deer females. Belonging to the population of the Bolognese Apennines (Italy), the hinds were sampled in the January–March 2018 period, according to the regional selective hunting plan. Plasma progesterone (P4) ranged from a minimum of 1.9 to a maximum of 7.48 ng/mL; while hair P4 concentrations varied from 41.68 to 153.57 pg/mg. The plasma and hair cortisol ranges are respectively 0.4–2.97 ng/mL and 0.03–0.55 pg/mg; the only significant correlation was found between hair concentration of P4 and the date of death. The results of this preliminary study represent a small step towards a better knowledge of this species’ physiology during pregnancy.

Energy storage system design for large-scale solar PV in Malaysia: technical and environmental assessments

Abstract The Paris agreement, signed in 2015, is a commitment by the nations to set targets to reduce greenhouse gases emissions. In line with that, Malaysia is committed to lower its greenhouse gases emissions by 45% by 2030. This target is supported by the massive projects of Large-Scale Solar PV, of which 1 GW will be operating by 2020. However, the peak generation of this huge capacity, which occurs at noon, will not meet the peak electricity demand which occurs in the morning and in the evening, and this issue, in such scale, has not been addressed yet. Besides the direct use of solar generated electricity, storing electricity at the peak generation time and delivering it at the desired time may be the best usage of such intermittent energy. This project aims to design the optimal large-scale storage system for the Malaysian scenario. A comprehensive power system is simulated through HOMER Pro, including various storage technologies in different locations, selected according to the planned Large-Scale Solar capacity, the solar irradiation and the electricity demand. The power system has been sized according to two approaches. In the first approach, the storage is sized to satisfy the night peak demand, which occurs between 8pm and 10pm. In the second approach, the daily average demand is determined, and the storage is sized to satisfy all the demand above this average. The proposed power system is feasible only in five locations under the first approach, and not feasible in all the locations under the second approach. Based on HOMER Pro simulation outcomes, the best energy storage type is the 1 MWh Zinc Bromide flow battery.

Pedestrian exposure to Nitrogen Dioxide (NO2) and Carbon Monoxide (CO): A case study of Surabaya, Indonesia

The increase in motor vehicles used every day also increases the rate of pollution. Motor vehicles are the main source of the nitrogen dioxide (NO2) and carbon monoxide (CO) pollutants that can be dangerous for human health in excessive amounts. This study investigates the patterns of NO2 and CO concentrations in the ambient air, specifically on the sidewalks of two big streets in Surabaya. Measurements were taken over a period of 15 hours using a portable monitoring device. The results indicated that the NO2 concentration would decrease by 0.008 mg/m3 and 0.012 mg/m3, respectively, at peak times during the day and night. Meanwhile, the CO concentration would increase by 1.486 mg/m3 during the peak time at night. The factors that significantly influenced NO2 were day variation (weekday or weekend), morning peak hour, noon peak hour, night peak hour, and temperature. Regression with these factors had an R2 value of 30.7%. For CO, the significant factors were night peak time, temperature, wind direction, and the number of vehicles, with an R2 value of 16.9%.