Minimum Monthly Research Articles

Hybrid signal processing/machine learning and PSO optimization model for conjunctive management of surface–groundwater resources

Conjunctive management of surface–groundwater resources systems by means of mathematical optimization–simulation techniques becomes an important issue for sustainable water resources development, namely in water-scarce regions. In this study, the particle swarm optimization (PSO) method has been coupled with a hybrid wavelet/ANFIS–fuzzy C-means (FCM) simulation model to determine the optimal agricultural irrigation water allocation in the Miandarband plain, western Iran. Firstly, the optimal amount of conveyed water (CW) from the Gavoshan Dam into the plain is determined by constrained PSO. The constraints are the long-term minimum monthly exceedance streamflows that are estimated for different exceedance probabilities—with a 70% value found to best reflect the average annual river inflow of 3.4 m3/s into the dam—using the two-parameter Weibull distribution as well as the classical Weibull nonparametric plotting position method. Then, based on the politically prioritized proportions of the dam’s allocated water for domestic, environmental and agricultural uses, as well as the share of the plain devoted to agriculture, the optimal monthly CW available for the plain (= 112 MCM/a) is obtained. However, the subsequent estimation of the irrigation water request (IWR) (= 265.8 MCM/a), calculated by the FAO-56 method and using empirical crop coefficients of the present agricultural pattern in the plain, indicates that there is an irrigation water deficit of 153.1 MCM/a that must be made up by groundwater withdrawal (GW), in a way that neither waterlogging nor severe drop conditions in groundwater levels (GL) will occur. The latter are then calculated by the hybrid wavelet/ANFIS (FCM) model, wherefore good performance indicators R2 and RMSE, equal to 0.98 and 0.21 m and 0.94 and 0.31 m in the training and testing phases, respectively, are obtained. Finally, PSO and the hybrid model are coupled to simulate the GL fluctuations—with the above GL constraints—under conjunctive use of the optimal surface (CW) and groundwater resources (GW) in the Miandarband plain. In conclusion, the innovative coupled simulation/optimization model turns out to be a very useful tool for optimal and sustainable conjunctive management of surface–groundwater resources in an irrigation area.

Persistent symptoms and decreased health-related quality of life after symptomatic pediatric COVID-19: A prospective study in a Latin American tertiary hospital

OBJECTIVES:To prospectively evaluate demographic, anthropometric and health-related quality of life (HRQoL) in pediatric patients with laboratory-confirmed coronavirus disease 2019 (COVID-19)METHODS:This was a longitudinal observational study of surviving pediatric post-COVID-19 patients (n=53) and pediatric subjects without laboratory-confirmed COVID-19 included as controls (n=52) was performed.RESULTS:The median duration between COVID-19 diagnosis (n=53) and follow-up was 4.4 months (0.8-10.7). Twenty-three of 53 (43%) patients reported at least one persistent symptom at the longitudinal follow-up visit and 12/53 (23%) had long COVID-19, with at least one symptom lasting for >12 weeks. The most frequently reported symptoms at the longitudinal follow-up visit were headache (19%), severe recurrent headache (9%), tiredness (9%), dyspnea (8%), and concentration difficulty (4%). At the longitudinal follow-up visit, the frequencies of anemia (11% versus 0%, p=0.030), lymphopenia (42% versus 18%, p=0.020), C-reactive protein level of >30 mg/L (35% versus 0%, p=0.0001), and D-dimer level of >1000 ng/mL (43% versus 6%, p=0.0004) significantly reduced compared with baseline values. Chest X-ray abnormalities (11% versus 2%, p=0.178) and cardiac alterations on echocardiogram (33% versus 22%, p=0.462) were similar at both visits. Comparison of characteristic data between patients with COVID-19 at the longitudinal follow-up visit and controls showed similar age (p=0.962), proportion of male sex (p=0.907), ethnicity (p=0.566), family minimum monthly wage (p=0.664), body mass index (p=0.601), and pediatric pre-existing chronic conditions (p=1.000). The Pediatric Quality of Live Inventory 4.0 scores, median physical score (69 [0-100] versus 81 [34-100], p=0.012), and school score (60 [15-100] versus 70 [15-95], p=0.028) were significantly lower in pediatric patients with COVID-19 at the longitudinal follow-up visit than in controls.CONCLUSIONS:Pediatric patients with COVID-19 showed a longitudinal impact on HRQoL parameters, particularly in physical/school domains, reinforcing the need for a prospective multidisciplinary approach for these patients. These data highlight the importance of closer monitoring of children and adolescents by the clinical team after COVID-19.

Detection of atmosphere CCl<sub>2</sub>F<sub>2</sub> spatio-temporal variations by ground-based high resolution Fourier transform infrared spectroscopy

Atmospheric dichlorodifluoromethane (CCl<sub>2</sub>F<sub>2</sub>, CFC-12), as a synthetic chemical agent, is a main stratospheric ozone-depleting substance in atmosphere. Studies of the detection techniques and the temporal and spatial distribution of CFC-12 have great significance in understanding the variation trend of regional CFCs and their influence on stratospheric ozone. In this study, the method of retrieving the vertical profile and total column for CFC-12 is studied based on ground-based high-resolution Fourier transform infrared spectroscopy (FTIR). The spectral window for CFC-12 retrieval is selected as 922.5–923.6 cm<sup>–1</sup>, where the interfering gases are H<sub>2</sub>O, O<sub>3</sub>, and CO<sub>2</sub>. The result of error analysis shows that the average total error is 1.27%, including the systematic error 0.76% and random error 1.02%. The vertical profiles and total columns of atmospheric CFC-12 in Hefei during the period from 2017 to 2020 were retrieved based on the optimal estimation algorithm. The vertical profiles of CFC-12 show that the concentration of atmospheric CFC-12 is high in the troposphere and low stratosphere at the altitude of 0–20 km, and then decreases, very low at height above 40 km. The total column average kernel of retrieved CFC-12 profiles is higher at 15–20 km, and the typical signal degree of freedom of CFC-12 is 1.217. Moreover, the long-term total columns of atmosphere CFC-12 observed show obvious seasonal variation in Hefei. Total columns of atmosphere CFC-12 are higher in summer and lower in winter and early spring. The maximum monthly concentration of CFC-12 is about 1.13 × 10<sup>16</sup> mol·cm<sup>–2</sup> in July, and the minimum monthly concentration is 1.00 × 10<sup>16</sup> mol·cm<sup>–2</sup> in March. Also, the annual average total columns of atmospheric CFC-12 decreased slightly from 2017 to 2020, with an increasing rate of –0.68%. This reflects the effect of China's implementation of CFCs control ban policy. Furthermore, in order to verify the accuracy of ground-based FTIR observation, we compare our ground-based observation data with ACE-FTS/ SCISAT satellite version 4.1 level 2 data. There are 16 pairs of matching points between satellite observation and ground observation data, and the correlation coefficient is 0.73 for two CFC-12 partial columns at the height of 16–28 km, showing good agreement between ground-based FTIR data and satellite data. The long-term observations demonstrate the accuracy and reliability of ground-based high-resolution FTIR technology for detecting the vertical distribution and seasonal variation of atmosphere CFC-12.

Energy Demand and Its Implication on Wind/PV System Sizing in Machakos, Kenya

Energy is an essential factor underpinning all elements of economy in the society. Its utilization greatly depends on the individual’s lifestyle and habitation. In rural areas, people use less electronic appliances compared to urban areas. However, the rapid development in technology and variety of applications have triggered the desire for more power in both rural and urban regions. To meet the energy demand, the world’s generation capacity has to keep growing. Renewable energy sources offer a better solution in quenching this demand. This paper presents the findings on energy utilization and a suitable sized wind/PV system model for an average rural household in Machakos. Energy demand assessment was done using probability sampling which involved clustering and random selection of households. The range of daily energy load in Machakos was found to be 0.052 to 4.23 kWh with most of the households consuming less than 1.5 kWh in a day. The daily average energy consumption for the three selected zones namely; Katheka-kai, Kiandani and Kathiani were 1.092, 0.99 and 1.4 kWh respectively, with an average load of 1.161 kWh. Over 50% of the households consume less than 1 kWh per day where the average loads were 0.56, 0.59 and 0.595 kWh respectively, with a daily average of 0.582 kWh. A wind/PV systems was sized for a sample household with a load of 0.588 kWh. Based on the minimum month solar insolation of 4.677 kWh/m2 and the available wind speed range of 1.0-10.0 m/s in the sites, a stand-alone wind/PV hybrid system was sized with component sizes as: 12 V, 165 W Panel, 12 V, 250 AH battery, 12 V, 225 W inverter and a wind turbine with a cut in, rated and cut-off wind speeds of 1.0, 5.0 and 15.0 m/s.

Omeprazole prescriptions for older adults in health care units in Curitiba, Brazil: an analysis based on Beers Criteria

OBJECTIVE: To evaluate omeprazole prescriptions for older adults based on the Beers Criteria, with an analysis of indications and duration of use longer than eight weeks. METHODS: In this retrospective cross-sectional study, data were collected from the electronic medical records of older adults with an omeprazole prescription seen at two health care units in Curitiba, Brazil, between June and August 2019. Data were subjected to descriptive statistical analysis, Student t and χ2 tests. RESULTS: Medical records of 386 patients were analyzed, and 69.95% were female. The mean age was 71 (SD, 8.15) years. Most patients had incomplete primary education (50.52%) and income level ranging from one to two Brazilian minimum monthly wages (39.90%). No indication for omeprazole prescription was found in 23.83% of medical records. Use longer than eight weeks was predominant for all indications in 96.60% of medical records. Duration of use more extended than the Beers Criteria recommendation was independent of sex (p = 0.327), education (p = 0.805), and income level (p = 0.629). A relationship between polypharmacy and long-term drug use was demonstrated (p < 0.001). CONCLUSION: The results of this study suggest the need for periodic review of omeprazole prescriptions considering deprescribing when they appropriate.

Mayfly Nymphs as Water Pollution Bioindicator

Ephemeroptera is an order of insects, comprising of over 3000 species (Barber-James et al., 2008). Ephemeroptera means Short lived, winged adults having lifespan about 1–2 hours to few days and maximum of 14 days. They are terrestrial in adult life and aquatic in the immature called naiads (nymphs). The sub-imago is the early, reproductively immature adult and the mature ones are imago. The nymphal stage of mayflies is always aquatic and they are dominant in life history stage. Depends upon external factors such as temperature, food availability and current velocity the nymphs undergo a series of molts as they grow (Brittain and Sartori, 2003). Water temperature is higher at summer season and lower at winter season. The maximum pH value recorded in the month of August (monsoon) and minimum in the April (summer). The pH was alkaline throughout study period. The maximum values recorded in the month of summer and winter. The high Do in summer attributed to increase in temperature and duration of bright sunlight. The maximum value recorded in the month of December (winter) and absent in the month of March (monsoon). The results showed that nymphs of mayfly are abundant in the month of March, April and May because of suitable water conditions like temperature, pH and DO. The lower number of nymphs observed in month of July, August and September in rainy season.

РЕГУЛЮВАННЯ ОСНОВНИХ ФУНКЦІЙ ОПЛАТИ ПРАЦІ: ПРОБЛЕМИ ТА МЕТОДОЛОГІЯ УДОСКОНАЛЕННЯ СОЦІАЛЬНО-ЕКОНОМІЧНОЇ ПОЛІТИКИ

The article examines the problems of formation and implementation of socio-economic policy aimed at regulating the remuneration’ main functions in Ukraine, substantiates the methodology of its improvement. Measures to regulate remuneration under the national strategy for economic diversification and productive employment include: legislative balancing of basic standards and guarantees of living environment and wages; coordination of their quantitative and qualitative parameters in the current methods of social protection; optimization of approaches to the distribution and redistribution of added value and consumption funds of business entities; balancing, increasing the efficiency of the state strategy of the national economy’ innovative modernization according to urgent investment and infrastructure priorities. Remuneration as an economic category has an extremely significant impact on the results, achievements, prospects of the areas’ set of socio-economic policy and development, assessment of their justification quality, as well as implementation, monitoring, adjustment of priorities. This connection, which is determined by the role of human potential and social capital as a whole in the functioning of neo- and post-industrial economies, is growing stronger due to the global spread of relevant technological modes. Numerous problems of achieving and balancing the sustainable socio-economic development Ukraine, unsatisfactory economic diversification, modernization, efficiency at the level of the country, its regions and individual enterprises, relatively low level of living standards, quality of reproduction and motivations of the significant part of workforce to productive labor in the national economy require radical improvement of parameters and mechanisms for regulating both the processes and amounts of remuneration, as well as its inverse positive impact on the quality of Ukrainian socio-economic policy and development in general. The wages’ purchasing power is derived from the quantitative and qualitative parameters of physiologically sufficient and socially acceptable living norms and standards, embodied in the consumer basket and the subsistence minimum for able-bodied, minimum and average monthly wages.

지자체 기후변화 대응을 위한 지역별 기후변화의 특성분석: 장기 관측자료를 중심으로

We investigated regional climate changes in South Korea over the last 40 years (1980 ~ 2019). The country was divided into 10 areas of Seoul, Gyeonggi, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju. We used the regional climate data (daily temperature and precipitation) measured by Korea Meteorological Administration (KMA) at 61 sites. There has been an annual average temperature increase of 1.4℃ for the last 40 years in Korea, with a range of +1.0℃ (Jeonnam) ~ +1.8℃ (Gangwon). The increases in annual minimum and maximum temperatures were even larger; the increase in annual maximum temperature was as high as 2.2℃ over a broad range of trends (+0.2℃ (Jeonnam) ~ +5.6℃ (Gyeonggi)). The change of annual total precipitation was not clear, but the southern part of Korea showed an increasing trend (Jeju(+206.4 mm/40years)), and the central part of Korea showed a decreasing trend (Chungnam (-119.6mm/40years)). The trend of annual temperature variability was negative in central Korea (Gyeonggi (-4.2℃/40 years)) and positive in southern Korea (Gyeongnam (+1.0℃ /40years)). The changes in the trends of monthly temperature variabilitiy differed by season; March (Gangwon (+0.1℃/40years) ~ Seoul (+3.6℃/40years)) and August (Jeju (-0.9℃/40 years) ~ Chungbuk (+2.9℃/40 years)) showed increasing trends due to the greater increase in maximum monthly temperatures. In comparison, September (Gyeongnam (-0.6℃/40 years) ~ Jeju (-3.5℃/40years)) and December (Seoul (+0.2℃/40 years) ~ Jeonbuk (-4.4℃/40 years)) showed decreasing trends due to the greater increase in minimum monthly temperatures. Those changes might cause different seasonal health impacts. Warming trends were noted in climate extreme indices over the last 40 years. For example, there was an almost one-month increase in the number of summer days (Tmax ≥ 25℃) in Seoul and 15-day increase in the number of tropical nights (Tmin ≥ 25℃) in Jeju. There was a similar decrease (14 days) in cold days (Tmin ≤ -12℃) in Gangwon. Our results show that regional differences in climate change over the last 40 years should be considered for establishing and implementing regional climate change adaptation policies.

THERMAL REGIME DURING COLD ACCLIMATION AND DORMANT SEASON OF GRAPEVINES IN CONTEXT OF CLIMATE CHANGES- HILLS OF CRAIOVA VINEYARD (ROMANIA)

The thermal regime during the autumn-winter seasons plays a decisive role in cold acclimation and survival grapevine in cold climates. This study aims at assessing the time variability of the thermal regime during dormant season, between 1961-2021, in the Hills of Craiova vineyard and its potential implications on the grapevine, especially regarding its acclimation to cold and its vulnerability to frost. The following observations and analytical data were used in order to assess parameters and indicators with negative thermal stress potential: minimum and maximum temperature (daily, monthly averages), absolute maximum and minimum monthly temperatures, the duration of frost (days), the frequency of several low-temperature thresholds and the temperatures preceding frost episodes.

Frozen ground change and its potential influence on river discharge in the Tienshan Mountains, northwestern China

ABSTRACT According to simulations, permafrost area in the Tienshan Mountains has decreased by about 1.73 × 104 km2 (or 20.91%) from the 1960s to the 2000s, and the freeze state of seasonally frozen ground (SFG) exhibited delaying freeze, advancing thaw, shortening freeze days and shallowing freeze depth. River discharge has changed largely, especially for winter and minimum monthly discharge. The rivers with low catchment permafrost coverage tended to have the highest increasing rates in winter discharge, minimum monthly discharge, winter discharge ratio (proportion of winter discharge contribution to total annual flow) and minimum monthly discharge ratio (proportion of minimum monthly discharge contribution to total annual flow). Gradually increasing correlations of maximum seasonally frozen depth (SFD) with the hydrological variables may indicate that the response of river discharge to frozen ground change is a long-term process. Possibly a result of frozen ground degradation, summer precipitation may strengthen the influences on low flow.

Portugal has had in the last months several changes in Labour Law in different areas

I - The increase in the minimum wage In January 2020 the minimum wage was increased to 635 euros per month, and it was implemented on 1 January 2020 by Decree-Law no. 167/2019 of 21 November. The aim of the new Government is to reach 750 Euros in 2023. Article 273, no. 1, of Portuguese Labour Code guarantees all employees a minimum monthly wage, to be annually established by specific legislation, following consultation of the social partners because this topic requires a binding opinion by th...

Impacts of climate change on the flow of the transboundary Koshi River, with implications for local irrigation

ABSTRACT This study assesses climate change impacts on the hydrological regime of a river basin and its implications for future irrigation water availability in the Koshi River basin using RCPs 4.5 and 8.5 over short-term (2016-2045), mid-century (2036-2065) and end-of-century (2071-2100) periods. Average flow in the Koshi River is projected to increase. Projections of average minimum monthly river flow suggest that the areas of winter wheat and monsoon paddy rice could be increased. However, the planting period of paddy rice should be delayed by one month (July to August) to capture the expected increased water availability in the river.

Study of Affecting Factors of Meteorological Parameters on Solar Radiation in Kathmandu Valley

Solar radiation data are great significance for solar energy systems. This study aimed to estimate monthly and seasonal average daily global solar radiation on a horizontal surface in Kathmandu (27.7oN, 85.5oE, 1350 masl), Nepal, by using CMP6 pyranometer in 2012. The influence of the global solar irradiation from different physical as well as meteorological parameters was analyzed. Besides this, the research highlighted that there is high level of fluctuation of the measured value of global solar irradiance due to local weather conditions. As a result of this measurement, the maximum, minimum monthly and yearly mean solar radiation values were (21.32 ± 4.14) MJ/m2/day in May,(10.93 ± 2.03) MJ/m2/day in January and (16.68 ± 4.60)MJ/m2/day found respectively. Annual average of clearness index, maximum temperature, minimum temperature, relative sunshine hour, air mass are 0.51 ± 0.12, (26.23 ± 4.96)oC, (12.38 ± 6.83)oC, 0.57 ± 0.165 and 1.54 ± 0.42 respectively. There is positive correlation of maximum temperature and negative correlation of air mass with global solar radiation.

Spatiotemporal Variability in Snow Parameters from MODIS Data Using Spatially Distributed Snowmelt Runoff Model (SDSRM): a Case Study in Dibang Basin, Arunachal Pradesh

Snow parameters play a very important role in hydrological cycle, local weather pattern, and climate change, eventually influencing total runoff, river flows, and water availability through the amount and timing of snow melt. In this paper, the spatiotemporal variations of snow parameters in Dibang basin, Arunachal Pradesh, India, for a period of 10 years (2006–2015) were analyzed using Spatially Distributed Snowmelt Runoff Model (SDSRM) coupled with remote sensing and GIS techniques. SDSRM was selected due of its capability to simulate snow parameters in scarcely/un-gauged basin where observed data are not available. Moderate Resolution Imaging Spectroradiometer (MODIS) albedo at 500 m resolution from Terra satellite was used to obtain daily snow albedo for the study area. The analysis of 10 years showed that maximum average snow density occurred in the month of June and minimum in the month of December; maximum average snow depth in January and minimum in July; maximum average snow water equivalent (SWE) in January and minimum in July and August; maximum average degree-day factor (DDF) in June and minimum in December; maximum average snowmelt depth in July and minimum in the month of January. Considering the yearly maximum and minimum average, snow density ranged from 404.84 to 522.84 kg/m3 with an average of 461.76 kg/m3; snow depth ranged from 0.01 to 0.68 m with an average of 0.24 m; SWE ranged from 0.01 to 0.29 m with an average of 0.11 m; DDF ranged from 0.45 to 0.58 cm/ °C-day with the average of 0.51 cm/ °C-day; and snowmelt depth ranged from 0.02 to 0.11 m/day with the average of 0.06 m/day. From the yearly temporal analysis, only snow density showed a slight decreasing trend, while the other snow parameters like snow depth, SWE, DDF, and snowmelt depth had a slight increasing trend. Based on yearly temporal analysis of each month, March and November showed an increasing trend for all the snow parameters out of which snow density and DDF showed a significant increasing trend in the month of March, while a slight decreasing trend was observed in the month of August, September, and October. The modeled SWE was compared with the observed SWE, and it was found that they were in good agreement with each other. The other snow parameters were also found to be within comparable ranges reported by other studies. Thus, this study demonstrated the capability of SDSRM to simulate snow parameters over an alpine watershed in Eastern Himalaya and can be recommended for use in un-gauged/scarcely gauged basins over the Himalayan region.

Mapping habitat suitability for gastrointestinal nematodiasis of ruminants in southern Caspian Sea littoral: a predicted risk pattern model based on the MaxEnt.

Herein, we provide the ecological niches of gastrointestinal nematode infections in Guilan, Mazandaran, and Golestan provinces. For this purpose, 2688 fecal specimens of sheep and cattle were subjected tothe flotation method. For modeling procedure, the results were analyzed by considering 23 bioclimatic and environmental variables as well as 96 points/locations. Maximum entropy (model MaxEnt) was used to visualize the spatial distribution of gastrointestinal nematodes. The relative importance of all variables was also assessed by using jackknife analysis. The highest proportion of sheep infection with strongyle-type egg was observed in Golestan province (57.8%) and the lowest in Guilan province (49.5%), and eggs per gram (EPG) was around 21-29. The parasites with the highest proportion of infection in both domestic animals included strongyle-type eggs. Among the different bioclimatic and environmental variables, the biggest contributor to habitat suitability of the gastrointestinal nematode presence was found to be minimum temperature ofthe coldest month (Bio6), precipitation of driest quarter (Bio17), precipitation of coldest quarter (Bio19), and altitude. The MaxEnt model was able to provide a suitable guidance for predicting the probability distribution of gastrointestinal nematodes under bioclimatic and environmental variables, and the findings pave way for integrated gastrointestinal nematode surveillance and control strategies in the southernstrip of Caspian Sea. In addition, the low intensity of gastrointestinal nematodiasis in ruminants may be associated with the frequent administration of anthelmintic drugs, where actions are needed to investigate drug resistance in the areas concerned and to provide anthelmintic drugs administration in a targeted manner.

Reproductive phenology and its drivers in a tropical rainforest national park in China: Implications for Hainan gibbon (Nomascus hainanus) conservation

Reproductive plant phenology, such as the seasonal timing of flowering or fruiting, influences many aspects of tropical forest communities, but there are few studies examining potential drivers of phenological patterns, especially in south China. We explored phenological patterns in Hainan Tropical Rainforest National Park (HNNP) in China and their major climatic and biotic drivers, based on phenological and distribution data for >2000 species from the Flora of Hainan. Specifically, we address the following questions: (1) What are the phenological patterns for all species in HNNP and for Hainan gibbon food plants only? (2) What are the environmental drivers of reproductive phenology? (3) Whether the flowering and fruiting dates are phylogenetic conserved? (4) Does reproductive phenology vary with functional groups, like growth forms, pollination modes and fruit types? Our results show flowering peaks in late spring and early summer, while fruiting phenology was concentrated during late summer and fall. Closely related species tend to have similar flowering and fruiting dates. The number of flowering species was primary controlled by mean maximum monthly temperature while minimum monthly temperature was the most important variable in shaping fruiting patterns of all species. For fruiting of gibbon food plants, mean monthly precipitation was the most important variable. Our study found January to May was food shortage period, which has important implications for Hainan gibbon conservation. We should take targeted ecological restoration by planting gibbon food species with phenologies between January and May, and take targeted provisioning to attract gibbons into a new habitat by providing fruits between January and May.

Prediction model of ecological environmental water demand based on big data analysis

The existing prediction model of eco-environmental water demand has the problem of large prediction error. In order to solve the above problems, the prediction model of eco-environmental water demand is constructed based on big data analysis. In order to reduce the prediction error of the ecological environment water demand prediction model, the framework of the ecological environment water demand prediction model is built. On this basis, the principal component analysis method is used to select the auxiliary variables of the model. Based on the selected auxiliary variables, the minimum monthly average flow method is used to analyze the basic water demand of the ecological environment, the leakage water demand and the water surface evaporation ecological environment water demand, so as to analyze based on the results, the water demand of ecological environment is predicted by big data analysis technology, and the prediction of water demand of ecological environment is realized. The experimental results show that compared with the existing ecological environment water demand prediction model, the prediction error of the model is within 19.3, which fully shows that the constructed ecological environment water demand prediction model has better prediction effect and can provide a certain reference value for the actual use of water resources. • The framework of water demand prediction model reduces the prediction error. • Using the 3 σ rule to eliminate the abnormal data. • The minimum monthly average flow method is used to obtain the basic water demand.

Low-cost air pollution monitoring system-an opportunity for reducing the health risk associated with physical activity in polluted air.

The issue of air pollution by particulate matter (PM) concerns many places in the world. At the same time, many residents undertake physical activity (recreation, rehabilitation, sport) in the open air. Generally, the amount of dust concentration depends on both the place (center or periphery of the city) and the time of day. In the present study we describe the outcome of monitoring of the state of air pollution by particle matter (PM10) in the Kraków agglomeration area in order to show that it can provide information concerning air quality in the area where people practice varied kinds of sports in the open air. The measurements of PM10 have been made by a few stations with identical construction working as one network. The details of the air pollution monitoring system and its data quality verification have been described. The network stations made multipoint observations across the Kraków Metropolitan Area during the year 2017 in eight locations. The locations selected represent a diverse spectrum of terrain conditions in which the Kraków agglomeration community undertakes physical activity. For most months of 2017, the minimum monthly average 4-hour PM10 concentrations were recorded between 10–14 h, regardless of location, whereas the maximum was between 18–22. We also noticed a huge differences in the average monthly value of PM10 in some locations within the Kraków agglomeration—ranging between 4.9–339.0 µg m−3. This indicates that some regions of the city are more suitable for performance of physical activity in the open air than others. In conclusion, we postulate that a low-cost air pollution monitoring system is capable of providing valuable information concerning air quality in a given region, which seems to be of importance also to people who practice varied sports activities in the open air.

Seasonal trends in oto-rhino-laryngology outpatient clinics in the North Indian state of Punjab: a 3 year pilot study

Background: Otorhinolaryngological disorders are amongst the common reason for seeking medical advice in health care setup. This study was conducted in a tertiary care hospital and medical college in North India. The monthly records of 93438 patients were analysed over a period of 3 years from January 2016 to December 2019. All monthly outpatient visits for ear nose throat (ENT) ailments, in the state with extremes of weather were recorded. No such epidemiological data about the attendance rates of patients to outpatient department (OPD) with respect to changing seasonal patterns is available. The aim of this study was to identify the various trends in the attendance pattern of ENT outpatient clinics with respect to the changes in the seasons.Methods: The monthly record of 93438 patients attending the general and speciality outpatient clinics of Dayanand Medical College, Ludhiana were studied. The study period was from January 2017 to December 2019).Results: A total of 93438 patients attended ENT OPD in three years from 2017 to 2019. Male: female ratio as 1.22:190. 1 percent of the patients belonged to 3rd and 4th decade of life , 9.9 percent of the patients were children. Patients from rural background comprised (63.1%) of the total number of patients The summer months of July, September have shown the maximum attendance during the year. The winter months of February and December have shown minimum attendance.Conclusions: Maximum patient visits were recorded in the month of July and minimum during the winter months of November to February.

Wave resource assessment and wave energy exploitation along the Indian coast

The present study investigates the feasibility of wave energy exploitation along the Indian coast using 19-year (2000–2018) hindcasted wave data generated by WAVEWATCH-III with a fine spatial resolution (0.1° × 0.1°) and temporal resolution (6 h). The wave model is validated against 12-month measured wave data collected at multiple buoy sites and compared with 19-year ERA5 data across the study area. The results show good agreement between model data and the other two datasets. The spatio-temporal variability analysis of wave energy flux reveals that southern coast of India has the mean wave energy flux ranging from 6 to 10 kW/m with a minimum monthly (<2.0), seasonal (<1.0) and annual (<0.2) variability which could be a promising area for future wave energy exploitation. A detailed analysis of wave power resource has been discussed for nine hotspot locations which were selected based on the optimum hotspot index, geographical restrictions on bathymetry and distance to the shore. Further, each hotspot has been analysed through combined scatter and energy diagrams. Finally, electrical power output is estimated at each hotspot using five wave energy converters and observed that the annual energy production at most of the locations is above 800 MWh with more than 70% availability.