Average Minimum Research Articles

Local weather affects body condition of three North American songbird species on the Texas Coast.

Body condition is a frequently used physiological indicator of avian health and can be affected by an array of environmental variables. Although a number of studies have investigated the specific effects of individual weather variables on body condition in birds, few have analyzed the effects of both temperature and precipitation within the context of an extreme weather event such as hurricanes. In this study, we examined the relationship between breeding-season body condition and daily maximum temperature, daily minimum temperature, and monthly total precipitation for three passerine bird species at the Welder Wildlife Refuge near Rockport, Texas. We also evaluated yearly changes in body condition over a 12-year period for northern cardinals (Cardinalis cardinalis), painted buntings (Passerina ciris), and white-eyed vireos (Vireo griseus), focusing on the extreme precipitation event of Hurricane Harvey, which caused heavy localized flooding. We found that body condition declined with average daily minimum and maximum temperatures, while precipitation had varied, species-specific effects in the three species analyzed. Our results also suggest that northern cardinals experienced a notable reduction in average body condition in the 2 years following Hurricane Harvey. Taken together, we conclude that short-term precipitation and temperature drivers can be important correlates of body condition in songbirds and that severe weather events may reduce body condition in some bird species.

Growth of two varieties of pitahaya (Hylocereus monacanthus and Hylocereus ocamponis) with apllication Ascophyllum nodosum

The agronomic management of pitahaya can enhance its yield. Thus, the use of Ascophyllumnodosum contributes to plantdevelopment. The objective was to evaluate the effect of Ascophyllumnodosumon height, stem diameter, length, shoot diameterand heat accumulation. Two varieties were used: Hylocereusmonacanthus(Lem.) Britton & Rose, Hylocereusocamponis (Salm)Britton & Rose and three doses of Ascophyllumnodosum (0, 1.0 and 2.0 L ha-1), thus, generating six treatments. The variableswere analyzed with SAS at 0.05 probability. The average minimum and maximum temperature was 19 and 37 °C and the heataccumulation was 1912 UC. The greatest height was presented by Hylocereusmonacanthus with the high dose of Ascophyllumnodosum with an increase of 7 % in relation to the treatment without application. Stem diameter was 16 % greater in the twovarieties and with the higher dose compared to the plants without application. In shoot length, H.monacanthus and H.ocamponisoutperformed the lowest treatments by 19%. The varieties H.monacanthus and H.ocamponis with applications of high doses of A.nodosum generated the highest values in the variables studied.

IT Diagnostics of Parkinson’s Disease Based on the Analysis of Voice Markers and Machine Learning

The results of studying the parameters of the spectra of speech signals by machine learning with the use of neural networks are presented. This study was carried out in order to confirm experimentally the possibility of performing an assessment of these parameters for the detection of Parkinson’s disease in the early stages (IT diagnostics). During the study, the public database was used, which systematized the spectra of vowel sounds uttered by patients with Parkinson’s disease. The applied method is binary data classification. In the course of the study, the speech data spectrum was first preprocessed, which consisted of filtering it in order to remove its noise components and eliminate bursts and gaps in it. Then the parameters of the processed spectrum of speech data were determined: average value, maximum and minimum, peak, wavelet coefficients, MFCC and TQWT. After that, the object was selected using the PCA algorithm. The model was trained using the Knn and Random Forest algorithms, as well as the Bayesian neural network. The Bayesian optimization algorithm and the GridSearch method were used to find the best model hyperparameters. It has been established that when using Knn, Random Forest and Bayesian neural network, it is possible to increase the accuracy of recognition of Parkinson’s disease by 94.7; 88.16 and 74.74 %, respectively. A similar study by other scientists showed that the recognition accuracy of data sets was only 86 %.

Experimental techno-economic analysis of an autonomous photovoltaic system operating in Chocó, Colombia

Despite of scientific efforts to evaluate economically the photovoltaic plants integrating the costs generated by the technical behavior of the system, few studies have demonstrated the behavior of the economic parameters from experimental data obtained from the photovoltaic plants in real-time operation. On the other hand, the cost analysis carried out by various authors breaks down the equation for calculating the Levelized cost of energy in independent terms without considering the marketing options of local markets in remote regions.This article discusses the results of a lead–acid battery system monitored over six years of operation. The system is part of a 20 kWp independent, modular photovoltaic power plant and is divided into two parallel circuits, each consisting of 24 batteries. Technical parameters such as state of charge, Pb-A system voltage, temperature, and charge/discharge currents were monitored, along with power flow before and after the Pb-A system inverter. The incremental charge/discharge efficiency between two parallel circuits, the duration of the charge and discharge cycles, and the Coulombic efficiency were evaluated from the measured data. A statistical analysis of the state of charge was performed to specify the energy delivered from the series of battery banks. This allowed for an evaluation and understanding of the operational performance of the photovoltaic system from a technical and economic point of view. The average minimum and maximum state of charge for bank 1 was 78.9% and 99.96%, respectively, and for bank 2 was 78.15% and 99.83%, respectively, for the monitored period. The efficiency of the incremental cycle varies for Sb1 from 92% to 99% and for Sb2 between 80% and 99%. From the monitoring of these parameters and using actual costs, the Levelized Cost of Electricity was determined for various discount rates.

Intrapuparial development and age estimation of Sarcophaga peregrina (Diptera: Sarcophagidae) for postmortem interval estimation

Sarcophaga peregrina Robineau-Desvoidy, 1830 (Diptera: Sarcophagidae) is a widely distributed species in the Palearctic, Oriental and Australian regions. Numerous studies and case reports have confirmed the value of this species in forensic investigations, but methods for estimating the age of the intrapuparial period of this species are lacking. In this study, S. peregrina pupae were sampled at 16 °C, 19 °C, 22 °C, 25 °C, 28 °C, 31 °C, and 34 °C. Morphological changes within the puparium were observed under a stereomicroscope. The results of the study showed that S. peregrina could complete its intrapuparial development at each of the seven tested constant temperatures. As the temperature increased, the average minimum duration of the intrapuparial period of S. peregrina decreased from 706.7 ± 28.1 h at 16 °C to 170.7 ± 4.6 h at 34 °C. The intrapuparial morphological changes of S. peregrina can be divided into 12 sub-stages. While some structures such as the compound eyes, mouthparts, antennae, thorax, legs, wings, and abdomen can be used individually to estimate intrapuparial age, we observed all these structures with local magnification photographs and classified the developmental process of these structures into 6–11 stages. The time range for the appearance of each sub-stage or structure was recorded in detail. The results of this study provide important basic data for estimating the minimum postmortem interval using the intrapuparial morphology of S. peregrina.

Climate change impacts on snow cover area and snowmelt runoff in the Ajichai Basin‐Iran

AbstractDuring snowmelt in mountainous areas, runoff can play an important role in providing water to the region. This study examined the effect of climate change on runoff in Ajichai, Iran, since it affects air warming and faster melting of snow and ice. Using the sixth report provided by IPCC, the future temperature and precipitation in the years 2015–2100 were predicted using two scenarios, SSP1‐2.6 and SSP5‐8.5. According to the results, the average annual minimum and maximum temperatures would increase by 1° during this period, but precipitation would decrease by about 3%. Based on the Snow Runoff Model (SRM) model and the snow cover area (SCA) obtained from Google Earth Engine and MODIS daily images from 2013 to 2018, runoff caused by snow melting was simulated. Based on the Pearson correlation coefficient between snow cover and temperature and precipitation, the SCA was estimated in three decades: 2031–2040, 2061–2070, and 2091–2100. With reasonable accuracy, the SRM was able to simulate runoff. In the SSP1 scenario, the SCA in spring and winter will remain the same throughout all three decades, but in the SSP5 scenario, it will decrease by about 17%. In the future, the runoff will decrease by up to 6% in the winter and increase in the spring.

Clinical Factors That Affect Fiducial Tracking in Robotic SABR for Lung Tumors

SABR is a treatment option for patients with lung tumors that employs fiducials to track tumors during the breathing cycle. Currently, there is a paucity of data on how relative fiducial location and patient clinical characteristics affect fiducial tracking and clinical outcomes. This study aimed to identify factors that reduce the number of fiducials tracked with respiratory motion management during SABR. An institutional review board-approved retrospective review was performed of patients receiving robotic SABR for lung tumors at our institution from 2016 to 2019. Clinical data including demographics, medical history, treatment data, and follow-up were collected. Fiducial geometries were obtained with Velocity contouring software and MATLAB. Mann-Whitney U, χ2, and t tests were completed using MedCalc. A total of 73 patients with 77 treatments were identified. The χ2 analysis revealed that chronic obstructive pulmonary disease was associated with having 3 or more fiducials tracked (P=.034). Tumors in lower lobes were associated with higher rates of uncertainty errors (P=.015). The number of fiducials tracked had no effect on local tumor control or overall survival, with a median of 36 months of follow-up. A total of 28 treatments had fiducial centroid data available for geometric analysis. The most common tracking errors were rigid body error (RBE; 57%) and spacing errors (36.4%). Spacing errors had a shorter average minimum interfiducial distance than nonspacing errors (1.0 cm vs 1.7 cm, respectively; P=.017). RBE treatments had a longer average maximum distance than non-RBE treatments (4.0 cm vs 3.0 cm; P=.022). Greater motion in lower lobes can contribute to certain tracking errors that prevent more fiducials from being tracked. Maintaining interfiducial distance between experimentally determined guidelines may limit spacing errors and RBEs, the 2 most common tracking errors. An increased number of patients in a data set may result in stronger correlations between patient and tumor factors and outcomes.

CO-OCCURRENCE OF MOSQUITO COMMUNITIES IN DISTURBED ENVIRONMENTS USING MARKOV RANDOM FIELDS (MRFs) IN ST. JOHNS COUNTY, FLORIDA

The distribution of mosquito communities is predicted by complex micro- and macrohabitat systems. While macrohabitat variables are significant in modeling the distribution of individual mosquito species, the distribution of mosquito communities in disturbed urban and semi-urban environmental gradients was overlooked in most of the previous models. In our study, we used conditional Markov Random Fields (CRF) to evaluate spatial co-occurrence patterns between mosquito vectors of eastern equine encephalitis (EEEV) and west Nile virus (WNV) in a disturbed urban environment in Saint John’s County, Florida. We aimed to 1) quantify the strength and direction of spatial unconditional and conditional correlations between mosquito assemblages in disturbed environments, and 2) evaluate whether the strength of correlations between mosquito assemblages is conditional on landscape or climate variables. We leveraged the longitudinal surveillance effort using Biogents sentinel traps (BGS) conducted by Anastasia Mosquito Control Districts in disturbed urban environments during 2017-2020. The distribution of high mosquito abundance, especially Aedes albopictus, Ae. aegypti, Ae. vexans, Ae. taeniorhynchus, Culex nigripalpus, Cx. salinarius, and Cx. quinquefasciatus, were conditionally correlated with other EEEV and WNV vector species in reduced woody and herbaceous wetlands and evergreen forests (-54.44%), and in urban developed landscapes (3.44%) during 2019 and 2020. Moreover, conditional correlations between mosquito species pairs were positively associated with increased total precipitation and in areas with high average minimum and maximum temperatures. Our results show that the micro- and macrohabitat characteristics demonstrated spatial effects on distribution and correlations between species pairs of EEEV and WNV mosquito vectors across disturbed environments. Our findings could be used to better understand the joint effects of drivers on mosquito diversity at a specific locality, interspecific interactions among mosquito assemblages, and how this diversity changes across environmental gradients.

Spatiotemporal variability and trend of rainfall and temperature in Sidama Regional State, Ethiopia

This study aims to investigate spatiotemporal variability, trends, and anomaly in rainfall and temperature in the Sidama region, Ethiopia. The TerraClimate gridded dataset on a monthly time scale for 30 years (1991–2020) with a horizontal resolution of approximately 4 km was used for the study. Trends in annual and seasonal rainfall and temperature were assessed using a nonparametric test (Mann-Kendal test) and Sen’s slope to test the statistical significance and magnitude of trends (increase/decrease), respectively. Our findings revealed that annual rainfall, summer (Hawado), and spring (Badhessa) rainfall have shown an increasing trend in most parts of the region, except for its northwest parts. We found a low annual rainfall variability (CV < 13%) over the southeastern and northwestern parts of the region. Rainfall variability revealed the difference in both time and space across the region. Six drought years (1999, 2001, 2002, 2003, 2012, and 2019) with different magnitudes were identified across the region. Annual average maximum (up to 0.4 °C decade−1) and minimum (up to 0.25 °C decade−1) temperatures revealed significantly increasing trends across the region. The standardized anomaly in the mean annual temperature indicated that the years in the recent decade (2011–2020) are getting warmer compared to the past two decades (1991–2010) due to natural and anthropogenic activities causing weather extremes in the region. The results of this study for rainfall contradict the other studies in the rift valley part of the region. Therefore, we suggest appropriate climate change adaptation strategies so that there is high rainfall and temperature variability across the region and between seasons.

ON THE POSSIBILITY OF USING REANALYSIS DATA TO ESTIMATE THE WATER TEMPERATURE OF THE CASPIAN SEA

Water temperature is one of the important hydrometeorological characteristics of large bodies of water, because of its influence on biological and chemical processes. In this work, water temperature data from coastal observation points of Kazakhstan and remote sensing data of the Earth, such as satellite images, and reanalysis, were considered. In the longterm context, in the Kazakh sector of the Caspian Sea, the water temperature ranged from 10.8 ⁰С (Peshnoi) to 12.7 ⁰С (Kulaly Island). The effectiveness of the use of reanalysis data with the use of statistical criteria was evaluated. These quality criteria characterize the reliability of the results, and ERA5 realism data are effective and can be used for analysis, and research. All the databases under consideration showed that SST the average monthly minimum values are observed in January, and the maximum values are observed in the summer period. The change in water temperature over the years has a positive trend.

Analysis of Stochastic Patterns of Daily Minimum Extreme Temperature of Karachi in Global Climate Change Perspective

Effects of climate change are a critical and globally accepted phenomenon and gradually becoming inevitable and catching the attention of policymakers around the world. Temperature is a principal climatic factor and is defined as the degree or intensity of heat causing huge consequences on human beings’ lives. This paper suggests some stochastic approaches to do an analysis of the Karachi region’s daily minimum extreme temperature from Jan 1, 2010, to Dec 31, 2014. It is observed that the average daily minimum temperature fits the Markov chain and its limiting probability has reached steady-state conditions after 20 to 87 steps or transitions. The results indicate that after 20 to 87 days the distribution becomes stationary. The smaller steady-state time represents the stationary of the data series, whereas long-term behavior shows non-stationarity in trend behavior in the respective seasonal time series. Furthermore, the overall annual dormancy of 24 o C to 31o C daily minimum temperature was analyzed early part of the summer season. This study can be useful for weather variability forecasting.

Characterizing Coastal Wind Speed and Significant Wave Height Using Satellite Altimetry and Buoy Data

Wind speed and significant wave height are the most relevant metocean variables that support a wide range of engineering and economic activities. Their characterization through remote sensing estimations is required to compensate for the shortage of in situ observations. This study demonstrates the value of satellite altimetry to identify typical spatial patterns of wind speed and significant wave height in the northeastern region of the United States. Data from five altimetry satellite missions were evaluated against the available in situ observations with a 10 km sampling radius and a 30 min time window. An objective analysis of the collective altimeter dataset was performed to create aggregated composite maps of the wind speed and significant wave height. This asynchronous compositing of multi-mission altimeter data is introduced to compile a sufficient sampling of overpasses over the area of interest. The results of this approach allow for quantifying spatial patterns for the wind speed and significant wave height in the summer and winter seasons. The quality of altimeter estimations was assessed regarding the distance from the coast and the topography. It was found that while the altimeter data are highly accurate for the two variables, bias increases near the coast. The average minimum and maximum wind speed values detected in buoy stations less than 40 km from the coast were not matched by the aggregated altimeter time series. The method exposes the spatial and time gaps to be filled using data from future missions. The challenges of the objective analysis near the coast, especially in semi-enclosed areas, and the implications of the altimeter estimations due to the land contamination are explained. The results indicate that the combination of altimetry data from multiple satellite missions provides a significant complementary information resource for nearshore and coastal wind and wave regime estimations.

Functional recovery after total hip/knee replacement in obese people: A systematic review.

Several studies have investigated the influence of body mass index (BMI) on functional gain after total hip replacement (THR) or total knee replacement (TKR) in osteoarthritis, with contradictory results. This systematic literature review was conducted to ascertain whether obesity affects functional recovery after THR or TKR in the short (<1 year), medium (<3 years) and long term (>3 years). The study was registered with PROSPERO and conducted according to the PRISMA guidelines. A systematic literature search was conducted across Medline and EMBASE databases for articles published between 1980 and 2020 that investigated patient-reported measures of functional recovery after THR and TKR in participants with osteoarthritis and obesity (defined as BMI ≥30kg/m2). Twenty-six articles reporting on 68,840 persons (34,955 for THR and 33,885 for TKR) were included in the final analysis: 5 case-control studies, 21 cohort studies (9 for THR only, 10 for TKR only and 2 for both). The average minimum follow-up was 36.4 months, ranging from 6 weeks to 10 years. Most studies found significantly lower pre-operative patient-reported functional scores for participants with obesity. After THR, there was a small difference in functional recovery in favor of those without obesity in the short term (<6 months), but the difference remained below the minimal clinically important difference (MCID) threshold and disappeared in the medium and long term. After TKR, functional recovery was better for those with obesity than those without in the first year, similar until the third year, and then decreased thereafter. Although there is a paucity of high-quality evidence, our findings show substantial functional gains in people with obesity after total joint replacement. Functional recovery after THR or TKR does not significantly differ, or only slightly differs, between those with and without obesity, and the difference in functional gain is not clinically important. CRD42018112919.

Mapping and Analysis of Monthly Average Maximum and Minimum Air Temperature Distribution of Muğla Province in Geographic Information Systems (GIS) Environment with IDW Method

Muğla province, which is located in Southwest Anatolia and has a surface area of 13,338 km2, generally has a mountainous and rough terrain. In this study, it is aimed to map and analyze the distribution of monthly and annual maximum and minimum average temperature values of Muğla province by using the Inverse Distance Weighted (IDW) interpolation method. For this purpose, meteorological data of 13 stations of the General Directorate of Meteorology in Muğla and the stations of Gölhisar, Bozdoğan, Kaş, Elmalı, which are close to the borders of the province, were used. The average values of the annual and monthly maximum and minimum temperatures of these stations were transferred to the ArcGIS environment with the help of Geographic Information Systems (GIS) and their distribution was mapped with the IDW method. According to these maps, the highest average annual temperature in Muğla is in Milas and its surroundings, while the lowest is the provincial borders in the northeast of Muğla center and Seydikemer district. These two places are followed by Datça district, which is located on a long peninsula. The places with the highest annual minimum average temperatures are around Datça and Marmaris districts, while the lowest is the Burdur provincial border in the northeast of Kavaklıdere and Seydikemer. The maximum average temperature in the province is July (between 41.6-41.1°C in Milas and Köyceğiz), and the lowest is January (between 14-17°C in Muğla center and Kavaklıdere). The minimum average temperatures in the province are highest in June (between 37.7-34.6°C in Marmaris), and the lowest in January (between -7.9 and -6.6°C in Kavaklıdere). Elevation conditions, maritime influence and aspect conditions, and the intrusion of thermal pressure areas, especially in summer, have been effective in the distribution of maximum and minimum average temperature values in the province. These values may also vary depending on time during the year

House-warming: Wild king cobra nests have thermal regimes that positively affect hatching success and hatchling size

Incubation temperature in nests of oviparous reptiles affects reproductive success indicators, including hatching time and success, offspring size, fitness, and behaviour. The female king cobra builds an above ground nest to incubate and protect its eggs. However, it is not clear how thermal regimes inside king cobra nests respond to external environmental temperature regimes, especially in subtropical regions that witness high diel and seasonal temperature fluctuations. To better understand the relationship between inside nest temperatures and hatching outcomes for this snake, we monitored the thermal regimes of 25 natural king cobra nests in the subtropical forests of the Western Himalayas in Uttarakhand state, northern India. We hypothesized that inside nest temperatures would be higher than outside (ambient) temperatures and that thermal regimes inside nests would affect hatching success and hatchling size. Internal and external temperatures at nest sites were measured every hour until hatching, via automatic data loggers. We then calculated hatching success of eggs and measured hatchling length and weight. Mean inside nest temperatures were consistently higher by about 3.0 °C than outside environmental temperatures. External temperature reduced with increasing elevation of nest sites and was the best determinant of inside nest temperature, which had a smaller range of variability. Physical characteristics of nests (size and leaf materials used) did not influence nest temperature significantly, but nest size was positively related to clutch size. Mean inside nest temperature was the best predictor of hatching success. Average daily minimum nest temperature, which indicates a possible lower threshold for thermal tolerance by eggs, was also correlated positively with hatching success. Mean daily maximum temperature was a significant predictor of mean length of hatchlings, but not of mean hatchling weight. Our study provides unequivocal evidence for the critical thermal benefits of king cobra nests for increased reproductive success, in subtropical environments with lower and sharply fluctuating temperature regimes.

Total mercury in small mammals from forest ecosystems (nearby Cherepovets, Vologda region)

The aim of the research is to determine the total mercury (THg) in small mammals in forest ecosystems at a distance of 3 – 8 km from the boundaries of the industrial site of PJSC Severstal near Cherepovets, Vologda region. THg in the pelage and organs of the Ural field mouse (Apodemus uralensis, Pallas, 1811) varies from less than 0.001 to 0.56 mg/kg of dry weight (DW), the average maximum THg value was in the spleen (0.18 ± 0.07 mg/kg) and minimum in the muscles (0.02 ± 0.01 mg/kg). The content of THg in the pelage and organs of the common shrew (Sorex araneus, Linnaeus, 1758) varies from 0 to 4.57 mg /kg DW, the average maximum value of THg was in pelage (0.76 ± 0.15 mg / kg) and the average minimum in the liver (0.11 ± 0.01 mg /kg). The estimated mean THg level in the common shrew in the wet years 2021-2022 is lower than in the dry years 2009 and 2010. The reason for this is not clear. The results indicate the need for further investigation of changes in the total mercury content in the terrestrial ecosystem.

Life-history characteristics and climate correlates of dioecious plant species in central southern Australia

Context The proportion of dioecious species can vary considerably among climates and habitats. However, studies often involve isolated communities or large diverse areas and fail to capture how proportions vary across diverse landscapes.Aims To identify (1) life-history associations of terrestrial dioecious plant species in central southern Australia, (2) whether proportion of dioecy varies spatially across central southern Australia, and (3) whether proportion of dioecy is correlated with life-history and/or climate factors.Methods Species growth form, pollination mechanisms and seed-dispersal features were extracted from herbarium databases to determine potential dioecy-linked traits. Distribution data for native terrestrial species in 66 Interim Biogeographical Regionalisation of Australia subregions were extracted from the Australasian Virtual Herbarium to calculate the proportion of total native species richness that are dioecious. Climate data for each subregion were also obtained from Terrestrial Ecology Research Network databases to investigate relationships among climate, life-history traits and dioecy.Key results Woodiness, abiotic pollination and endozoochory were more prevalent in dioecious than non-dioecious taxa. Proportion of dioecy ranged from 1.7% to 8.5% among subregions and correlated negatively with annual temperature range, January to March rainfall and precipitation seasonality and with average annual daily mean, minimum, maximum and average annual minimum temperature. The highest-ranked models of dioecy incorporated the additive effects of the relative proportion of woody species and either annual temperature ranges, January to March rainfall or average annual daily maximum temperature.Conclusions Dioecy was associated with woodiness, abiotic pollination and endozoochory, in line with studies of other flora, with the model of stable temperature range and woodiness being the highest-ranked model of dioecy.Implications Areas with higher proportions of dioecy can be targeted for future investigations into dioecious plant ecology to aid conservation and ecosystem management.

Caesarean Scar Pregnancy: Single Dose of Intrasac Ultrasound-Guided Methotrexate Injection Seems to be a Safe Option for Treatment.

The purpose of the study was to assess the efficacy of local ultrasound-guided methotrexate injection in patients with caesarean section scar pregnancy, to chart the course of beta-human chorionic gonadotropin levels (HCG) after treatment, and to see if HCG levels are correlated with clinical presentation. Between May 2018 and January 2021, data were collected retrospectively from the Early Pregnancy Unit of a tertiary hospital. Our clinic assessed 20 patients; one disputed terminating the pregnancy and was not included in the research. The remaining 19 patients, with a median age of 34 years, received intragestational sac methotrexate injection under ultrasound guidance. 7w3d was the median gestational age. These women had one to four previous caesarean sections, with a mean of 1.60±9. Patients with caesarean scar pregnancy most typically presented with spotting (42.1%), whereas 26.3% were asymptomatic. Except in cases of pain, the symptomatic women's HCG levels were lower than in the non-symptomatic women. The level of HCG in patients with pain was approximately double that of non-pain patients (p=0.2557). In our series, intragestational sac methotrexate injection was effective in 17/19 women, or 89.5% (95%CI: 75.7-100%). HCG levels were undetectable in 97.6±30 days on average (minimum: 42 days, maximum: 147 days). Caesarean scar pregnancy is a rare possibly fatal condition with no consensus on the optimal treatment. An experienced Early Pregnancy Unit member performing local methotrexate injections under ultrasound guidance is a feasible and successful strategy in clinically stable patients.

Covertness and Secrecy Study in Untrusted Relay-Assisted D2D Networks

This article investigates the covertness and secrecy of wireless communications in an untrusted relay-assisted device-to-device (D2D) network consisting of a full-duplex base station (BS), a user equipment (UE), and an untrusted relay <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R}$ </tex-math></inline-formula> . For the covertness, we attempt to prevent Willie from detecting the very existence of communications via a D2D link from UE to R and cellular link from R to BS, while for the secrecy, we aim to prevent the untrusted relay from eavesdropping the UE message. To explore the fundamental covertness and secrecy in such a network, we first provide theoretical modelings for the average minimum detection error rate of Willie, and the average covert/secrecy rate from UE to BS under the underlay and overlay modes, respectively. Based on these models, th we further explore the optimal power control at UE, R, and BS to achieve the average covert rate maximization (MCR) for UE with the constraints of covertness and security requirements under the underlay mode. We also identify the optimal transmit powers and the optimal spectrum partition factor for MCR under the overlay mode. Finally, the exhaust searching method is adopted to solve the MCR problems, and extensive numerical and simulation results are presented to validate our theoretical analysis and to illustrate the average covert rate and secrecy rate of UE under various scenarios.

Future Sediment Transport Ability and its Consequences in the Urbanized River Basin

The urbanization process of the Kathmandu Valley has a significant impact on LULC change, river runoff, and sediment transport capability. The historical sediment flow pattern indicates that the sediment transport capacity of the basin has increased even when precipitation and river discharge decreased. So, the sediment regression model is developed in this study in relation to discharge, precipitation, and built-up area change. Model parameters are calibrated and validated through the measured sediment discharge of the basin and the performance of the model is evaluated through NSE, PBIAS, and R2. In the future, the sediment transport capacity of the channel is projected for average monthly, maximum, and minimum flow conditions by +4.33%, +6%, and -2.66% respectively per decade due to the rise in the urban area (+6% per decade). Increasing the rigid ground surface through urbanization reduces the sediment generation through the watershed and balances the sediment transport capability, excess erosion is produced in the river channel causing a change in the river morphology. The findings of this study will be useful for planning and management of the river basin and the river structures.