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Pedestrian detection is a challenging and active research area in computer vision. Recognizing pedestrians helps in various utility applications such as event detection in overcrowded areas, gender, and gait classification, etc. In this domain, the most recent research is based on instance segmentation using Mask R-CNN. Most of the pedestrian detection method uses a feature of different body portions for identifying a person. This feature-based approach is not efficient enough to differentiate pedestrians in real-time, where the background changing. In this paper, a combined approach of scale-invariant feature map generation for detecting a small pedestrian and Mask R-CNN has been proposed for multiple pedestrian detection to overcome this drawback. The new database was created by recording the behavior of the student at the prominent places of the engineering institute. This database is comparatively new for pedestrian detection in the academic environment. The proposed Scale-invariant Mask R-CNN has been tested on the newly created database and has been compared with the Caltech [1], INRIA [2], MS COCO [3], ETH [4], and KITTI [5] database. The experimental result shows significant performance improvement in pedestrian detection as compared to the existing approaches of pedestrian detection and instance segmentation. Finally, we conclude and investigate the directions for future research.

This work reports the radon concentration level in the work environment of cement plants (CPs) located in the Sulaymaniyah city-North of Iraq. This survey for the radon concentration is performed in 24 sectors of three different CPs including Tasluja, Mass, and Bazian. The measurements were recorded using solid state nuclear track detector (CR-39 NTDs). The radon effective dose μSv/hr correlated weakly with the gamma effective dose μSv/hr to enhance the radon concentration measuring. The detector was fixed in different places of the plants such Crusher, Correction stores, Raw Mill (Grinding Mill), Preheater (Tower), Clinker, and Cement Storage. The arithmetic mean (AM) value of radon concentration (Ca) was found to be 98 ± 9, 101 ± 10, and 125 ± 10 Bq m−3 and the arithmetic mean value of annual effective dose (E) of radon was 0.767, 0.753, and 0.962 mSv y−1 for Tasluja, Mass, and Bazian CPs, respectively. The maximum values of about 222 ± 20 Bq m−3 and 1.402 mSv y−1, respectively, in sector III (Grinding) at Bazian CP. The achieved results reveal that the maximum value of radon concentration in all sectors of the CPs is below the international standard value (300 Bq m−3) of both the World Health Organization and International Commission on Radiological Protection.

Selected anthropometric measures of two hundred primary school pupils in Ibadan North Local Government Area of Oyo State were used to design classroom desks and tables. The relevant anthropometric measures were popliteal height, buttock-popliteal length, elbow rest height, hip breadth, shoulder height and elbow-hand grip. The pupils with age range from 5 to 14 years (mean = 9.8 years, SD = 2.9 years) were grouped into three age groups of 5-8 years, 9-12 years and 13-14 years. From the data obtained; 5th, 10th, 50th, 75th, 90th and 95th percentiles were computed. In addition, 2-Tail Paired samples T-Test was conducted for the measurements of the male and female pupils for the three- age groups at 0.05 level of significance. Based on the anthropometric data obtained, this paper proposes furniture design dimensions for seat height (32.0 cm, 37.3 cm and 40.3 cm for 5-8 years, 9 to 12 years and 13-14 years respectively). It proposes seat depth (33.0 cm, 38.0 cm and 41.0 cm for 5-8 years, 9 to 12 years and 13-14 years respectively) and seat width (30.0 cm, 31.0 cm and 31.0 cm for 5-8 years, 9 to 12 years and 13-14 years respectively). Moreover, it proposes backrest height (upper) (39.0 cm, 43.0 cm and 44.0 cm for 5-8 years, 9 to 12 years and 13-14 years respectively) and arm rest (12.0 cm, 13.0 cm and 15.0 cm for 5-8 years, 9 to 12 years and 13-14 years respectively). It also proposes desk height (42.0 cm, 49.0 cm and 53.3 cm for 5- 8 years, 9 to 12 years and 13-14 years respectively.

Radioactive materials, containing high-count rate, are found in some areas in the world which have worldwide use as construction and facing material. The radiation doses, in the Garmik area, are about 268.6 nGy h-1, which are density population by residents of ten of villages and two towns. The outdoor terrestrial gamma-ray background in some region of Garmik area was studied in order to determine the absorbed gamma dose rates of the soils and rocks. Gamma ray spectra have been recorded using the advance nuclear measurement system (digital spectroscopy analyzer DSA with NaI (TI) detector). This method is very suitable for measuring outdoor gamma radiation dose because the gamma count and human -radiation exposure will not be lost by the method by which the whole radiation exposure has been determined. A new equation has been formulated for this method. The total dose rates inside Sulaimani city was (42.873) nGy h-1 considered as a normal local outdoor dose rate (background). The average values of outdoor dose rates of the studied samples, in Tatan, Hangazhal and Garmik areas have been found to be (226.1005, 257.477,322.541) nGy h-1 respectively. These values are nearly 6 times grater than the normal local outdoor dose rate of the background of Northeastern Iraq. The dose rate of each radioactive elements or isotopes have been determined for each spectrum of each mentioned area which are equal to 8.4554, 67.0995, 66.9057, 50.6143 nGy h-1 for Sulaimani city, Tatan, Hangazhal and Garmik respectively. The total rate of radionuclide is about 22.76% of total outdoor dose rate.

Abstract Deployment of ultracold atom interferometers (AI) into space will capitalize on quantum advantages and the extended freefall of persistent microgravity to provide high-precision measurement capabilities for gravitational, Earth, and planetary sciences, and to enable searches for subtle forces signifying physics beyond General Relativity and the Standard Model. NASA’s Cold Atom Lab (CAL) operates onboard the International Space Station as a multi-user facility for fundamental studies of ultracold atoms and to mature space-based quantum technologies. We report on pathfinding experiments utilizing ultracold 87Rb atoms in the CAL AI. A three-pulse Mach–Zehnder interferometer was studied to understand the influence of ISS vibrations. Additionally, Ramsey shear-wave interferometry was used to manifest interference patterns in a single run that were observable for over 150 ms free-expansion time. Finally, the CAL AI was used to remotely measure the Bragg laser photon recoil as a demonstration of the first quantum sensor using matter-wave interferometry in space.

Abstract Several outstanding issues concerning the ionosphere of Mars can be addressed with the support of radio occultation observations acquired near the solar zenith angle limit of 45 $$^{\circ }$$ ∘ . First, two fundamentally different types of instruments (topside radar sounding, radio occultations) have been used to characterize how the subsolar peak density changes over the solar cycle. Here we find that their results for solar minimum and solar maximum values of peak density are consistent. This verifies that systematic errors do not affect peak density measurements from either type of instrument. Second, reported descriptions of how the peak altitude changes with solar zenith angle are inconsistent. Specifically, values reported by radio occultation and radar sounder instruments for the characteristic lengthscale used to describe changes in peak altitude with solar zenith angle vary by a factor of two. We find that the change in peak altitude with solar zenith angle is governed by a lengthscale that is close to the thermospheric scale height, as predicted theoretically. However, this behavior is only apparent when the Mars–Sun distance is held fixed. Reported smaller values of this lengthscale, which are not consistent with theoretical expectations, were adversely affected by using near-terminator peak altitude values only, which display marked variability. Third, Viking Lander entry science data have been interpreted to suggest that the M1 layer is not present in the ionosphere at solar zenith angles of 45 $$^{\circ }$$ ∘ or smaller. We show radio occultation observations at 45 $$^{\circ }$$ ∘ in which the M1 layer is present. This suggests that the basic structure of the dayside ionosphere remains the same at all solar zenith angles. Graphical Abstract

Abstract Saturn’s moon Titan was explored by the Cassini spacecraft from 2004 to 2017. While Cassini revealed a lot about this Earth-like world, its radar observations could only provide limited information about Titan’s liquid hydrocarbons seas Kraken, Ligeia and Punga Mare. Here, we show the results of the analysis of the Cassini mission bistatic radar experiments data of Titan’s polar seas. The dual-polarized nature of bistatic radar observations allow independent estimates of effective relative dielectric constant and small-scale roughness of sea surface, which were not possible via monostatic radar data. We find statistically significant variations in effective dielectric constant (i.e., liquid composition), consistent with a latitudinal dependence in the methane-ethane mixing-ratio. The results on estuaries suggest lower values than the open seas, compatible with methane-rich rivers entering seas with higher ethane content. We estimate small-scale roughness of a few millimeters from the almost purely coherent scattering from the sea surface, hinting at the presence of capillary waves. This roughness is concentrated near estuaries and inter-basin straits, perhaps indicating active tidal currents.

Abstract Background Sepsis is a life-threatening condition which may arise from infection in any organ system and requires early recognition and management. Healthcare professionals working in any specialty may need to manage patients with sepsis. Educating medical students about this condition may be an effective way to ensure all future doctors have sufficient ability to diagnose and treat septic patients. However, there is currently no consensus on what competencies medical students should achieve regarding sepsis recognition and treatment. This study aims to outline what sepsis-related competencies medical students should achieve by the end of their medical student training in both high or upper-middle incomes countries/regions and in low or lower-middle income countries/regions. Methods Two separate panels from high or upper-middle income and low or lower-middle income countries/regions participated in a Delphi method to suggest and rank sepsis competencies for medical students. Each panel consisted of 13–18 key stakeholders of medical education and doctors in specialties where sepsis is a common problem (both specialists and trainees). Panelists came from all continents, except Antarctica. Results The panels reached consensus on 38 essential sepsis competencies in low or lower-middle income countries/regions and 33 in high or upper-middle incomes countries/regions. These include competencies such as definition of sepsis and septic shock and urgency of antibiotic treatment. In the low or lower-middle income countries/regions group, consensus was also achieved for competencies ranked as very important, and was achieved in 4/5 competencies rated as moderately important. In the high or upper-middle incomes countries/regions group, consensus was achieved in 41/57 competencies rated as very important but only 6/11 competencies rated as moderately important. Conclusion Medical schools should consider developing curricula to address essential competencies, as a minimum, but also consider addressing competencies rated as very or moderately important.

Military recruitment policy pursued by the British administration in the Southern Kordofan region usually referred to as the Nuba Mountains region, during the period 1900-1945 is discussed. The war conditions of 1940-1945 greatly altered the course of the military recruitment policy, a fact apparent in the lifting of the restriction on the enlistment of Nuba migrants who were resident in the North.

This study was a prospective, comparative study, used to determine & compare the efficacy of treatment with methyldopa vs labetalol with respect to maternal – perinatal benefits and adverse effects. Conducted in the Department of Obstetrics and Gynaecology in Vivekananda Institute of Medical Science, Ramakrishna Mission Seva Pratishthan, a total 425 patients were taken into the study. The patients were divided into two groups by simple random sampling method. They were monitored throughout pregnancy and delivery till 7 days postpartum. The results obtained were divided in 3 sections Effective BP control, Maternal outcome, Perinatal outcome, which were again divided into three periods – Antepartum, Intrapartum and Postpartum for better elaboration. The study revealed that labetalol helps in quicker and more efficacious control of BP in mothers developing gestational hypertension with chances of developing preeclampsia – eclampsia syndrome.

Soil Moisture (SM) is a key geophysical variable that enables a better understanding of the Earth’s hydrological processes. Missions like Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) have been the primary sources of SM estimations for years. The NASA-ISRO Synthetic Aperture Radar (NISAR) mission, planned to launch in 2024, will bring L-band and S-band SAR measurements that will be used for SM estimation. Consequently, investigations to link SMAP with NISAR to produce accurate SM retrievals at improved spatial resolutions will be a focus to many research initiatives. This investigation aims to set the basis to use polarimetric Global Navigation Satellite System-Reflectometry (GNSS-R) products to enhance the temporal resolution of NISAR’s L-band SAR data through its typical 12-day period. As a proof of concept, we model SMAP radar backscatter measurements from SMAP-Reflectometry (SMAP-R) measurements, using the 3 months of data collected by the SMAP radar while it was operational. The model is based on the sensitivity of polarimetric GNSS-R to roughness, vegetation, and SM, as well as on the complementary sensitivity existing between forward and backward scatter. Different regression models are implemented using single-, dual-, and full-polarization GNSS-R measurements synthetized from SMAP-R data. This study highlights the importance of the new constellations of polarimetric GNSS-R being built and shows how those frequent measurements can serve L-band SAR missions to improve their time resolution.

Drought is a natural phenomenon that has adverse effects on agriculture, the economy, and human well-being. The primary objective of this research was to comprehensively understand the drought conditions in Sistan and Balouchestan Province from 2002 to 2017 from two perspectives: vegetation cover and hydrology. To achieve this goal, the study utilized MODIS satellite data in the first part to monitor vegetation cover as an indicator of agricultural drought. In the second part, GRACE satellite data were employed to analyze changes in groundwater resources as an indicator of hydrological drought. To assess vegetation drought, four indices were used: Vegetation Health Index (VHI), Vegetation Drought Index (VDI), Visible Infrared Drought Index (VSDI), and Temperature Vegetation Drought Index (TVDI). To validate vegetation drought indices, they were compared with Global Land Data Assimilation System (GLDAS) precipitation data. The vegetation indices showed a strong, statistically significant correlation with GLDAS precipitation data in most regions of the province. Among all indices, the VHI showed the highest correlation with precipitation (moderate (0.3–0.7) in 51.7% and strong (≥0.7) in 45.82% of lands). The output of vegetation indices revealed that the study province has experienced widespread drought in recent years. The results showed that the southern and central regions of the province have faced more severe drought classes. In the second part of this research, hydrological drought monitoring was conducted in fifty third-order sub-basins located within the study province using the Total Water Storage (TWS) deficit, Drought Severity, and Total Storage Deficit Index (TSDI Index). Annual average calculations of the TWS deficit over the period from April 2012 to 2016 indicated a substantial depletion of groundwater reserves in the province, amounting to a cumulative loss of 12.2 km3 Analysis results indicate that drought severity continuously increased in all study basins until the end of the study period. Studies have shown that all the studied basins are facing severe and prolonged water scarcity. Among the 50 studied basins, the Rahmatabad basin, located in the semi-arid northern regions of the province, has experienced the most severe drought. This basin has experienced five drought events, particularly one lasting 89 consecutive months and causing a reduction of more than 665.99 km3. of water in month 1, placing it in a critical condition. On the other hand, the Niskoofan Chabahar basin, located in the tropical southern part of the province near the Sea of Oman, has experienced the lowest reduction in water volume with 10 drought events and a decrease of approximately 111.214 km3. in month 1. However, even this basin has not been spared from prolonged droughts. Analysis of drought index graphs across different severity classes confirmed that all watersheds experienced drought conditions, particularly in the later years of this period. Data analysis revealed a severe water crisis in the province. Urgent and coordinated actions are needed to address this challenge. Transitioning to drought-resistant crops, enhancing irrigation efficiency, and securing water rights are essential steps towards a sustainable future.

Abstract This paper is devoted to studying the nonlinear problem with slightly subcritical and supercritical exponents ( S ± ε ) : Δ 2 u − c n Δ u + d n u = K u n + 4 n − 4 ± ε $(S_{\pm \varepsilon}): \Delta ^{2}u-c_{n}\Delta u+d_{n}u = Ku^{ \frac{n+4}{n-4}\pm \varepsilon}$ , u > 0 $u>0$ on S n $S^{n}$ , where n ≥ 5 $n\geq 5$ , ε is a small positive parameter and K is a smooth positive function on S n $S^{n}$ . We construct some solutions of ( S − ε ) $(S_{-\varepsilon})$ that blow up at one critical point of K. However, we prove also a nonexistence result of single-peaked solutions for the supercritical equation ( S + ε ) $(S_{+\varepsilon})$ .

Abstract Sand production is a major issue in the oil and gas industry. Unconsolidated sand can be produced with the oil or gas a cause many issues to the production facilities. Enzyme-induced carbonate precipitation (EICP) is a promising method for sand consolidation and is characterized by its environment friendliness. Numerous studies have shown its effectiveness in ambient conditions. However, oil and gas downhole well operations are high pressure and high-temperature conditions. The objective of this study is to investigate effect of high temperature on EICP reaction and its efficiency in terms of uniformity to consolidate different types of sand samples. In this paper, the behavior of EICP solutions is examined in high temperatures from 25 to 90 °C. The study shows that high temperature environment doesn’t handicap efficiency but in contrast it can favor the reaction if optimum concentration of reactants has been selected. The temperature effect is also discussed in terms of controllability of reaction which can favor application of reaction. Qualitive analysis shows when EICP solutions containing more than 50,000 ppm of metal ions and stoichiometrically surplus urea requires exposure to heat for reaction progress. The effect of sand particle size and its implication on the consolidation process was examined. Particle size of fine and medium sand ranged from 125 to 250 µm and 250 to 425 µm respectively while for coarse sand 70% sand particle size was between 425 and 700 µm. Designed EICP solutions achieve 9,000 psi for medium and almost 5,000 psi intrinsic specific energy for coarse sand samples. However, treated samples were subject to non-uniform distribution of strength of which can be up to 8,000 psi difference between top and bottom half of the samples.

This paper is devoted to studying the nonlinear problem with subcritical exponent $(S_{\varepsilon}) : \Delta^{2}u-c_n\Delta u+d_nu = Ku^{\frac{n+4}{n-4}-\varepsilon}$, $u>0$ on $ S^n$, where $n\geq5$, $ \varepsilon$ is a small positive parameter and $K$ is a a smooth positive function on $S^n$. We construct some solutions which blow up at $q$ different critical points of $K$.

Abstract The Soil Moisture Active Passive (SMAP) mission has dramatically benefited our knowledge of the Earth’s surface processes. The SMAP mission was initially designed to provide complementary L-band measurements from a radiometer and a radar, producing geophysical measurements at a finer spatial resolution than the radiometer alone. Both instruments, sensitive to the geophysical parameters in the swath, provided independent measurements at different spatial resolutions. A few months after SMAP’s launch, the radar transmitter’s high-power amplifier suffered an anomaly, and the instrument could no longer return data. During recovery activities, the SMAP mission switched the radar receiver frequency facilitating the reception of Global Positioning System (GPS) signals scattered off the Earth’s surface, and enabling the radar to become the first spaceborne polarimetric Global Navigation Satellite System – Reflectometry (GNSS-R) instrument. With more than 7 years of continued measurements, SMAP GNSS-R data are the most extensive existing GNSS-R dataset and the only one providing GNSS-R polarimetric measurements. We demonstrate that the SMAP polarimetric GNSS-R reflectivity, derived from Stokes parameters mathematical formulation, can enhance the radiometer data over dense vegetation areas, recovering some of the original SMAP radar capability to contribute to the science products and pioneering the first polarimetric GNSS-R mission.

The Soil Moisture Active–Passive (SMAP) mission has greatly contributed to the use of remote sensing technologies for monitoring the Earth’s land surface and estimating geophysical parameters that influence the climate system. Since the SMAP mission switched its radar receiver to allow the reception of Global Positioning System (GPS) signals, Global Navigation Satellite System Reflectometry (GNSS-R) configuration has been enabled, providing full polarimetric forward scattering measurements of the Earth’s surface, also known as SMAP Reflectometry or SMAP-R. Polarimetric GNSS-R is beneficial for sensing land surface properties, especially for more accurate estimations of soil moisture (SM) in densely vegetated areas. In this study, we explore the opportunity to enhance SMAP mission soil moisture estimates using reflected GNSS signals. We achieve this by interpolating the sparse reflectivity data with terrain information to disaggregate radiometer brightness temperatures. Our main objective is to present a novel algorithm based on Graph Signal Processing (GSP) that uses reflectometry data to enhance SMAP radiometer observations and ultimately improve SM retrievals. By implementing methods from the GSP field, we formulate the reflectivity interpolation problem as a signal reconstruction on a graph, where the weights of the edges between the nodes are chosen as a function of geophysical information. Subsequently, using the retrieved reflectivity maps, we increase the resolution of the brightness temperature data, leading to an improvement in the SM estimates. Initial findings indicate that our GSP method presents a promising alternative for analyzing sparse remote sensing observations, leveraging Earth’s surface geophysical information. This approach results in a notable improvement, with a reduced Root Mean Square Error (RMSE) of 11.8% compared to SMAP data and a reduction in unbiased RMSE (uRMSE) by 14.7% over vegetated areas.

Abstract The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

IntroductionPrecipitation as the most important climatic element is always studied from two perspectives of time and place. Emphasis on the time perspective determines temporal changes and emphasis on the location perspective determines the spatial variation of precipitation. Since Iran is located in an arid and semi-arid region, it lacks large internal and adjacent water resources to supply moisture to its precipitation, and as a result, most of its precipitation moisture sources must be supplied from the surrounding water levels. One of the methods that can be used to study the course of rainfall in the past and present is to analyze the trend of time series at different scales. So far, statistical methods have been presented for the analysis of time series routines, which can be divided into two general categories: parametric and non-parametric methods. Southeastern Iran, which includes Sistan-Baluchestan province, Kerman, southern Khorasan and the eastern parts of Hormozgan province, They are one of the arid regions of Iran. Restriction on water resources and annual precipitation in this part of the country have severely limited agricultural and industrial activities. The lives and deaths of the majority of people are also related to the low precipitation that falls throughout the year. Therefore, considering that a comprehensive study on precipitation trends in the region has not been done, the purpose of this study is to investigate the annual and seasonal precipitation trends by stations in southeastern Iran. The results of this study can play an important role in understanding the precipitation trend in the southeast region for planning related to water resources management, management of unexpected events such as floods and also the optimal utilization of those precipitations.MethodologyIn order to conduct this study, in order to recruit rainy periods, daily precipitation data were obtained from synoptic stations in the southeast of the country, including selected stations in the three provinces of Hormozgan, Sistan and Baluchestan and Kerman during a 30-year period (1987-2016). Two Mann-Kendall tests and the Sen’s Slope Estimate are among the most common non-parametric methods of trend analysis when considering hydrometeorology. Various studies conducted using these two methods indicate the importance of their widespread use in the rapid evolution of time. Identify the data change using the Man-Kendall method, specify its type and time. The non-parametric Kendall test was proposed by Mann and then developed by Kendall (1975) based on ranking data in a time series. This method is widely and widely used in the analysis of the process of hydrological and meteorological series.Discussion and resultsThe trend of average annual, seasonal precipitation and maximum 24-hour precipitation in southeastern IranConsidering that in the annual, seasonal and maximum 24-hour precipitation trend diagrams, the intersection of the U and U' sequences above and below the significant lines did not occur, which means that acceptance is random (acceptance of H0 hypothesis) and there is no significant trend (H1) variable. Precipitation is in the southeast of Iran and in fact the condition is -1.96 (ti)< U or 1.96 (ti) >U and has a static series.In the Sen's Slope Estimate test, the total reduction of winter precipitation slope was equal to -0.350 mm, which in the case of 95% confidence of the upper and lower slopes of this slope is equal to -0.123 and -0.835, respectively, and in the case of 99% of the slopes. High and low are 1.604 and -2.318, respectively, per year. The Sen’s Slope Estimate test for annual rainfall, summer, autumn, winter and maximum 24-hour precipitation has estimated the negative precipitation slope. Mann Kendall test estimate shows a decrease in precipitation in winter of -1.71 per year.Annual, seasonal and maximum 24-hour precipitation trend by stations in southeastern IranIn the study of changes in annual precipitation using Mann-Kendall test, it is observed that the annual precipitation trend in most stations in the southeast (except Bam and Chabahar) has a decreasing trend. The Sen’s Slope Estimate showed is the highest precipitation at any given time at Bandar-Lengeh station at -4.16 mm per year. The time series of Man-Kendall test in the seasons of the year indicates that in spring, summer and autumn, the precipitation trend in most stations is decreasing, but this trend is not significant in any of the stations in southeastern Iran and only in winter precipitation In Bandar-Lengeh, Jask and Kish stations, it has a decreasing trend at 95% significance level. Sen’s Slope Estimate data showed that the amount of precipitation decreases in the mentioned stations.ConclusionThe results of by using Methods the Mann-Kendall test showed that the mean annual precipitation trend as well as spring, summer and autumn seasons of southeast Iran was not significant and only winter precipitation had a significant and decreasing trend. Estimates of the slope of sen indicate that the slope of precipitation in southeastern Iran in winter is -0.350 mm in year. The annual precipitation trend of BandarAbbas, BandarLengeh, Abumousa and Kish stations at 95% and Jask and Iranshahr stations at 90% were significant. Test statistics showed that the highest annual precipitation reduction was at the Bandar-e-Lange station at -4.16 mm in year. In spring, summer, and fall, precipitation was not significant in any of the stations in the southeast of Iran and winter precipitation in Bandar-e-Lengh, Jask, and Kish stations had a 95% significant decrease. Assessment of 24-hour rainfall variations showed that the above mentioned precipitation had a decreasing trend at 99.9% at BandarAbbas stations and 95% at Bandarlange, Jask, Abumousa and Kish stations. According to the tests and analyzes performed in this study, what is certain is that in all stations in southeastern Iran, a significant positive trend in annual, seasonal and maximum 24-hour rainfall was not observed at the level of 99% and 95%, and most precipitation trends from It is a kind of decrease and has revealed the fact of decrease in rainfall in the southeastern climate of Iran during the years 1987 to 2016, which decrease in annual rainfall is mostly related to the winter of -1.71 per year.

The present study focuses on the distribution of precipitation in different spatial and temporal patterns based on monthly, seasonal and annual time scales using TRMM data derived from 92 different cells in the south of the Caspian Sea. In addition, to account for the impact of the geographical conditions such as elevation, latitude and longitude on rain values, the Pearson correlation method was used. In terms of the average monthly precipitation in the south of the sea, the results showed that the highest average belonged to November (87 mm), followed by December (74 mm), and finally March and October (67 mm and 66 mm), respectively. The highest negative correlation (0.862) between rain and longitude was observed in autumn at a significant level of 0.01. In addition, the highest negative correlation (0.87) between rain and longitude was found in November at a significant level of 0.01. The maximum annual rain was 892-1305 mm measured in Guilan Province. Precipitation showed a tendency to decline toward the east of Golestan Province, so that the minimum annual precipitation (321-393 mm) was recorded in its western and northeastern parts. The precipitation was positively correlated with elevation and there was a strong inverse relationship between rain and longitude.

The Study of Rice Agroclimatology in LenjanIntroductionToday, agroclimatology is one of the major trends in hydrology and meteorology, which has a crucial role in fulfilling the food requirements of different communities. The production of agricultural products is strongly correlated with precipitation and agreeable weather conditions each year. Many crops are traditionally grown in areas with harsh climatic conditions, which result in low yields and the lack of optimal exploitation of climate production capacities. One basic way to develop and promote agricultural activities in the country is to cultivate lands according to the ecological conditions. A perquisite of such development is to recognize the wide range of associated factors, including climatic and land factors. Rice cultivation, as an ecological and economic phenomenon as well as a behavioral pattern originating from human-environment interaction, is at the mercy of environmental conditions, especially climate, water and soil resources, and natural factors play a pivotal role in providing favorable conditions for rice cultivation. Identifying suitable areas for growing crops and favorable climatic and topographic conditions can improve crop production. Lenjan county, situated in a semi-arid region, has severe temperature daily, seasonal and annual fluctuations, which have worked to the detriment of various activities, especially agriculture in this city. The Zayandehrud river running through the city has laid the ground for the development of agriculture and animal husbandry. Given the huge agricultural and horticultural potentials of this county, further analysis and planning are warranted. In this research, attempts have been made to investigate the agroclimatology of Lenjan county for rice cultivation.MethodologyLenjan county is located 35 km southwest of Isfahan in the Zayandehrud valley. The meteorological stations studied here include Isfahan, Lenjan, Daran, Natanz and Najafabad. The data were obtained from the Meteorological Organization and the General Directorate of Agricultural Jihad in Isfahan and Charmahal Bakhtiari provinces. In this study, the daily and monthly meteorological data related to the parameters of temperature, precipitation, and relative humidity derived from these stations over a 15-year statistical period (1996-2012) were used. Then, the correlation between climatic elements and rice yield in selected stations was analyzed. Finally, after preparing climatic maps, altitude and slope levels were drawn using the Kriging method. Also, in the GIS, the final zoning map of areas suitable/unsuitable for rice cultivation was drawn according to relevant elements. Discussion and ResultsParameters and indices of rice agroclimatology in the west of Isfahan province, which are of paramount importance in the growing season and different stages of growing rice, were studied and analyzed. The growth degree day of the rice for the whole growing period is 1500 degree day. Hence, in light of the values obtained from the active temperatures, it was observed that all stations were effective in terms of growth day degree and have favorable conditions concerning active growth day degree. The minimum critical temperature of rice is -1 °C, and in none of the stations, the mean temperature during the growing period was lower than 0 °C. The maximum days this temperature was below 10 °C during the statistical period was reported at Najafabad station, but this temperature was never recorded at Isfahan station. All stations experience weak frosts until the end of April, which in high-elevation lasts until the last ten days of May. Mild frost is also reported only at stations above 2000-m elevation and in April. Severe frost also recorded only at very high-elevation stations (altitude above 2250 m) and in the first half of April. The minimum water consumption of rice from cultivation to maturity is not sufficient in any of the stations studied. Hence, all stations must be irrigated throughout the growing season (from planting to maturity). The germination date was May 10 at Daran and Lenjan stations, June 5-10 at Isfahan station, and June 20 at Najafabad and Natanz stations. Tillering date was also from July 5 to 15 at Lenjan and Daran stations, from July 24 to 15 at Isfahan, and from August 10-20 at Najafabad and Natanz stations. This period lasts for 20 days at Lenjan station. The growth period of rice at Lenjan station was 22 days. The flowering date was from August 20 to September 10 at Lenjan and Daran stations, from September 1 to 15 at Isfahan station, and from September 25 to October 5 at Najafabad stations. At Lenjan station, the flowering period lasted for 30 days. The maturity of rice grains was from October 5 to 20 at Lenjan and Daran stations, from September 28 to October 15 at Isfahan, and from October 21 to November 7 at Najafabad and Natanz stations. The length of maturity period at Lenjan station is 15 days Finally, after designing climate maps, altitudes and slopes were drawn by GIS and the final map of areas suitable for rice cultivation was designed according to relevant elements. The best areas were mostly located in the central and eastern parts, which overlapped with the plains. Moreover, an area of 294 square kilometers covered stretches that were not suitable for rice growth, particularly regions in the highlands of the west and north of the map, where the rainfall is lower than in other areas. These expanses are primarily located in the highlands and the vicinity of the highlands consisting of rocky and sloping lands. Infertile expanses, covering an area of 45 square kilometers, include mountains and areas bereft of agricultural soil. ConclusionThe results of this study show that in the west of Isfahan province, there is a fertile expanse in an area of 492 square kilometers, which sits on the central areas and alluvial plains. Lenjan county is located in this area, where the late frost in spring and the early autumn cause the minimum damage. The initial growth of roots and stems and the rise of clusters are fairly quick, but adequate water could not be supplied by rainfall. Fertile zones cover the bulk of the map, which is an area of about 738 square kilometers. l.

Objective: Hemodialysis (HD) vascular access (VA) failure is the dominant cause of morbidity and the major cost of care for ESRD patients. The aim of the present work is to assess the serum level of vascular cell adhesion molecule and P- selectin in HD patients as markers for early thrombotic VA event. Methodology: 90 CKD patients divided into three groups: group I: 10 subjects apparently health, group II: 10 Patients with CKD stage IV-V on medical treatment and group III: 70 Patients with CKD stage V on HD with recent VA insertion divided into 2 subgroups: Subgroup III a: 57 patients with AV shunt and subgroup III b: 13 patients with permanent catheter. Laboratory investigations done (blood urea, serum creatinine, eGFR, CBC, PT, and INR), imaging and serum VCAM 1, P selectin before and 6 months after HD Results: There was positive connection between VCAM and P selectin and dialysis with statistics in form of p value (

In vision-based surveillance systems, pedestrian recognition and path prediction are critical concerns. Advanced computer vision applications, on the other hand, confront numerous challenges due to differences in pedestrian postures and scales, backdrops, and occlusion. To tackle these challenges, we present a YOLOv5-based deep learning-based pedestrian recognition and path prediction method. The updated YOLOv5 model was first used to detect pedestrians of various sizes and proportions. The proposed path prediction method is then used to estimate the pedestrian's path based on motion data. The suggested method deals with partial occlusion circumstances to reduce object occlusion-induced progression and loss, and links recognition results with motion attributes. After then, the path prediction algorithm uses motion and directional data to estimate the pedestrian movement's direction. The proposed method outperforms the existing methods, according to the results of the experiments. Finally, we come to a conclusion and look into future study.