Median Slope Research Articles

Assessment and monitoring of meteorological and hydrological drought in semiarid regions: The Wadi Ouahrane basin case study (Algeria)

The aim of this study is to use the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI) to investigate meteorological and hydrological drought in the Wadi Ouahrane basin of north Algeria. Indeed, in recent years, the Wadi Ouahrane basin has suffered from persistent and recurrent meteorological and hydrological droughts, which caused large economic losses and extreme difficulties for the local population, resulting in widespread out-migration and poverty throughout the country. In order to evaluate the SPI, 6 monthly rainfall series for the period 1972–2018 have been considered. Moreover, with the aim to evaluate the SRI, monthly runoff data from 1972 to 2018 were also collected in one station. Both the SPI and the SRI have been evaluated at 1-, 3-, 6-, 9-, 12- and 24-month timescales. Although a similar percentage of positive and negative values of both the indices has been detected for the different timescales, the temporal distribution of these values allowed us to identify the periods characterized by severe or extreme drought conditions such as 1982, the end of 1983, 1987–1990, 1992–1995 and, recently, 2014–2016. Finally, in order to detect drought temporal evolution in the period 1972–2018, the SPI and SRI series at the different multi-times scales were tested for trends through the Theil-Sen estimator (SS), the Mann–Kendall test (MK), the Modified Mann–Kendall test (MMK) and the Innovative Trend Method (ITA). As a result, although the SS evidenced negative values, the MK test did not show significant trends thus indicating stable drought conditions.

Robslopes: Efficient Computation of the (Repeated) Median Slope

Modern use of slope estimation often involves the (repeated) estimation of a large number of slopes on a large number of data points. Some of the most popular non-parametric and robust alternatives to the least squares estimator are the Theil-Sen and Siegel's repeated median slope estimators. The [robslopes](https://CRAN.R-project.org/package=robslopes) package contains fast algorithms for these slope estimators. The implemented randomized algorithms run in $\mathcal{O}(n\log(n))$ and $\mathcal{O}(n\log^2(n))$ expected time respectively and use $\mathcal{O}(n)$ space. They achieve speedups up to a factor $10^3$ compared with existing implementations for common sample sizes, as illustrated in a benchmark study, and they allow for the possibility of estimating the slopes on samples of size $10^5$ and larger thanks to the limited space usage. Finally, the original algorithms are adjusted in order to properly handle duplicate values in the data set.

Satellite-based long-term spatiotemporal trends of wildfire in the Himalayan vegetation

Analysis of the spatiotemporal pattern of burned areas over time is necessary to understand how fire behavior in the Himalayan region has altered as a result of the complex climatic variables. The differenced Normalized Burnt Ratio (NBR) is calculated utilizing the cloud-based platform Google Earth Engine (GEE) to quantify the extent of burned regions. The spatial distribution of burnt areas in the Himalayan region over the last 21 years has been examined and correlated with climatic and edaphic factors in the current study. The area affected by forest fire has shown a direct correlation with the land surface temperature, but an inverse relationship with surface soil moisture, pre-fire precipitation, pre-fire Normalized Difference Vegetation Index (NDVI) and pre-fire Enhanced Vegetation Index (EVI). The p-value for 9 of the 20 regions in which the research area has been divided for the spatial analysis is less than 0.05, implying that the regression model is statistically significant. Trend analysis done using Mann–Kendall test and Theil–Sen estimator state the distinct trends of burnt area and other meteorological and edaphic parameters in the Western, Central and Eastern Himalaya. The assessment of burned areas aids forest managers in mitigating the impacts and managing the forest fires, as well as in the implementation of the restoration methods following a forest fire.

Mapping of nighttime light trends and refugee population changes in Ukraine during the Russian–Ukrainian War

The nighttime lights accurately and coherently depict how humans live. This study uses nighttime light measurements to quantify changes in nighttime lighting and refugee population in Ukraine before and after the war. We combined the Theil–Sen estimator with the M-K test to explore the trends of nighttime light. In addition, we constructed a linear model using nighttime light data and a portion of the UNHCR refugee data. Our results reveal that 1 week after the start of the Russo-Ukrainian War, the nighttime light area and the average nighttime light DN value in Ukraine exhibited a steep decline of about 50 percent. Our findings showed taht refugee population changes calculated through models and nighttime light data were mostly consistent with UNHCR data. We thought that the nighttime light data might be used directly to dynamically estimate changes in the refugee movement throughout the war. Nighttime light changes has significant implications for international humanitarian assistance and post-war reconstruction.

Combined effects of runoff increase and sea level rise on the water exchange and saltwater intrusion for an estuary bay in non‐flood season

AbstractEstuary bays are vulnerable to salinization effects due to relative sea level rise and modification in upland hydrology owing to a variety of factors. Much research has evaluated the one‐sided effect of runoff discharge or sea level on the water exchange and saltwater intrusion for an estuary, while their combined effects have not been evaluated, especially for an estuary bay with narrow river mouth. Taking the Wanquan Estuary Bay (WEB), China, as study case, this paper has revealed the long‐term significant increasing trend of freshwater runoff in non‐flood season during years 1956–2017 using the Man‐Kendall trend analysis, robust principle component regression and Theil–Sen's estimator. A 3‐D hydrodynamic‐salinity‐tracer numerical model is built and calibrated based on the finite‐volume community ocean model, and the effects of runoff increase and sea level rise on the water exchange and saltwater intrusion are investigated. This paper shows the following: (1) The freshwater runoff during non‐flood season in WEB shows significant long‐term increasing trend, and the mean changing magnitude is 0.4546 m3/s/a. (2) The increased runoff accelerates the water exchange, and reduces the turn‐over time and saltwater intrusion in the WEB. The sea level rise reduces the water exchange and increase the saltwater intrusion. (3) For the estuary bay with narrow river mouth, the salinity distributions show more vertical stratification characteristics. The freshwater runoff has power relationships with the average turnover time and salinity, and the sea level has linear relationships. (4) The water exchange and salinity of an estuary bay is more vulnerable to the changed runoff than the sea level rise, while the impacts of sea level rise would increase for estuaries with wide river mouth. This paper provides support for the freshwater exploitation and utilization in estuary bay under the background of climate change and sea level rise.

The volumetric extended-Schmidt law: a unity slope

ABSTRACT We investigate the extended-Schmidt (ES) law in volume densities (ρSFR ∝ $(\rho _{\rm gas}\rho _{\rm star}^{0.5})^{\alpha ^{\rm VES}}$) for spatially resolved regions in spiral, dwarf, and ultra-diffuse galaxies (UDGs), and compare to the volumetric Kennicutt–Schmidt (KS) law (ρSFR ∝ $\rho _{\rm gas}^{\alpha ^{\rm VKS}}$). We first characterize these star formation laws in individual galaxies using a sample of 11 spirals, finding median slopes αVES = 0.98 and αVKS = 1.42, with a galaxy-to-galaxy rms fluctuation that is substantially smaller for the volumetric ES law (0.18 versus 0.41). By combining all regions in spirals with those in additional 13 dwarfs and one UDG into one single data set, it is found that the rms scatter of the volumetric ES law at given x-axis is 0.25 dex, which is also smaller than that of the volumetric KS law (0.34 dex). At the extremely low gas density regime as offered by the UDG, the volumetric KS law breaks down but the volumetric ES law still holds. On the other hand, as compared to the surface density ES law, the volumetric ES law instead has a slightly larger rms scatter, consistent with the scenario that the ES law has an intrinsic slope of αVES ≡1 but the additional observational error of the scale height increases the uncertainty of the volume density. The unity slope of the ES law implies that the star formation efficiency (= ρSFR/ρgas) is regulated by the quantity that is related to the $\rho _{\rm star}^{0.5}$.

Exploring and attributing change to fractional vegetation coverage in the middle and lower reaches of Hanjiang River Basin, China.

The middle and lower reaches of Hanjiang River Basin (MLHB), areas that have an important ecological function in China, have experienced great changes in the vegetation ecosystem driven by natural environmental change and human activity. Here, we explored the spatio-temporal dynamics of fractional vegetation coverage (FVC) and quantitatively analyzed its driving factors to advance current understanding of how the ecological environment has changed. Specifically, we used the dimidiate pixel model to calculate the FVC of the MLHB from 2001 to 2018 based on Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data. We then used Theil-Sen median slope (Sen's slope) and coefficient of variation (CV) to explore spatial and temporal variations, as well as characteristics in fluctuations. Finally, we utilized a geographical detector model (with spatial scale effects and spatial data discretization tests) to quantify the influence of the detected natural and human factors. Results showed that average annual FVC was 0.30-0.75 for ~90% of the study area over the 19-year study period with a heterogeneous spatial distribution. FVC variation trend displayed stability and improvement. Areas with higher FVC displayed greater stability. All 10 detected natural and anthropogenic factors were responsible for changes in FVC. The primary factors causing FVC to change were precipitation (in 2001) and slope (in 2018), followed by landform type, distance to water, and nighttime light (NTL) (in 2018). Precipitation and slope consistently displayed the largest interaction across all years. The interaction between human and topographical factors had gradually increasing significance on changes in FVC over the research period. The range and type of factors suitable for promoting vegetation growth were detected in the study area. Results of this study can provide a scientific basis for developing effective strategies for local vegetation protection, restoration, and land resource management.

Identification of Serum Metabolites for Predicting Chronic Kidney Disease Progression according to Chronic Kidney Disease Cause.

Early detection and proper management of chronic kidney disease (CKD) can delay progression to end-stage kidney disease. We applied metabolomics to discover novel biomarkers to predict the risk of deterioration in patients with different causes of CKD. We enrolled non-dialytic diabetic nephropathy (DMN, n = 124), hypertensive nephropathy (HTN, n = 118), and polycystic kidney disease (PKD, n = 124) patients from the KNOW-CKD cohort. Within each disease subgroup, subjects were categorized as progressors (P) or non-progressors (NP) based on the median eGFR slope. P and NP pairs were randomly selected after matching for age, sex, and baseline eGFR. Targeted metabolomics was performed to quantify 188 metabolites in the baseline serum samples. We selected ten progression-related biomarkers for DMN and nine biomarkers each for HTN and PKD. Clinical parameters showed good ability to predict DMN (AUC 0.734); however, this tendency was not evident for HTN (AUC 0.659) or PKD (AUC 0.560). Models constructed with selected metabolites and clinical parameters had better ability to predict CKD progression than clinical parameters only. When selected metabolites were used in combination with clinical indicators, random forest prediction models for CKD progression were constructed with AUCs of 0.826, 0.872, and 0.834 for DMN, HTN, and PKD, respectively. Select novel metabolites identified in this study can help identify high-risk CKD patients who may benefit from more aggressive medical treatment.

Satellite-Based Discrimination of Urban Dynamics-Induced Local Bias from Day/Night Temperature Trends across the Nile Delta, Egypt: A Basis for Climate Change Impacts Assessment

The Nile Delta is the most vital region of the desert-dominated country of Egypt. Due to its prominent level of vulnerability to climate change’s negative impacts and its low capacity for adaptation and mitigation, the current study aims to provide accurate quantification of temperature change across the Nile Delta as an integral basis for sustainability and climate change impacts assessment studies. This was achieved through monitoring urban dynamics and detecting LST trends in 91 cities and their rural surroundings. The relevant local urban bias was discriminated from regional/background changes present in diurnal/nocturnal temperature records. The temperature records were then corrected/adjusted by removing this urban bias. Owing to the insufficiency of ground-based meteorological observatories, the investigation utilized moderate resolution imaging spectroradiometer (MODIS) land surface temperatures (LSTs) and Landsat-based datasets (2000–2021). The widely used Mann–Kendall test (MKT) and Theil–Sen estimator (TSE) were employed to assess trends in urban sprawl, LST time series, and the implied association. The analysis revealed that the region has experienced dramatic urbanization, where the total urban expansion was greater than two-thirds (69.1%) of the original urban area in 2000. This was accompanied by a notable warming trend in the day/night and urban/rural LST records. The nocturnal LST exhibited a warming tendency (0.072 °C year−1) larger than the diurnal equivalent (0.065 °C year−1). The urban dynamics were positively correlated with LST trends, whereas the Mediterranean Sea appeared as a significant anti-urbanization moderator, in addition to the Nile River and the prevailing northerly/northwesterly winds. The urban–rural comparison approach disclosed that the urbanization process caused a warming bias in the nighttime LST trend by 0.017 °C year−1 (21.8%) and a cooling bias in the daytime by −0.002 °C year−1 (4.4%). All results were statistically significant at a confidence level of 99%. It is recommended that studies of climate-related sustainability and climate change impact assessment in the Nile Delta should apply a distinction of urban-induced local effect when quantifying the actual regional temperature change.

Ozone pollution in London and Edinburgh: spatiotemporal characteristics, trends, transport and the impact of COVID-19 control measures

Air pollution remains the most serious environmental health issue in the United Kingdom while also carrying non-trivial economic costs. The COVID-19 lockdown periods reduced anthropogenic emissions and offered unique conditions for air pollution research. This study sources fine-granularity geo-spatial air quality and meteorological data for the capital cities of two UK countries (i.e. England's capital London and Scotland's capital Edinburgh) from the UK Automatic Urban and Rural Network (AURN) spanning 2016–2022 to assess long-term trends in several criteria pollutants (PM10, PM2.5, SO2, NO2, O3, and CO) and the changes in ozone pollution during the pandemic period. Unlike other studies conducted thus far, this research integrates several tools in trend estimation, including the Mann-Kendall test, the Theil-Sen estimator with bootstrap resampling, and the generalized additive model (GAM). Moreover, several investigations, including cluster trajectory analysis, pollution rose plots, and potential source contribution function (PSCF), are also employed to identify potential origin sources for air masses carrying precursors and estimate their contributions to ozone concentrations at receptor sites and downwind areas. The main findings reveal that most of the criteria pollutants show a decreasing trend in both geographies over the seven-year period, except for O3, which presents a significant ascending trend in London and a milder ascending trend in Edinburgh. However, O3 concentrations have significantly decreased during the year 2020 in both urban areas, despite registering sharp increases during the first lockdown period. In turn, these findings indicate on one hand that the O3 generation process is in the VOC-limited regime in both UK urban areas and, on the other hand, confirm previous findings that, when stretching the analysis period, diminishing ozone levels can lead to NOx reduction even in VOC-controlled geographies. Trajectory analysis reveals that northern Europe, particularly Norway and Sweden, is a principal ozone pollution source for Edinburgh, whereas, for London, mainland Europe (i.e., the Benelux countries) is another significant source. The results have important policy implications, revealing that effective and efficient NOx abatement measures spur ozone pollution in the short-term, but the increase can be transient. Moreover, policymakers in London and Edinburgh should consider that both local and transboundary sources contribute to local ozone pollution.

Spatiotemporal Variation of Net Primary Productivity and Its Response to Climate Change and Human Activities in the Yangtze River Delta, China

Exploring the temporal and spatial changes, as well as driving factors, of net primary productivity (NPP) of terrestrial ecosystems is essential for maintaining regional carbon balance. This work focuses on the spatiotemporal variation and future trends of NPP and the response mechanisms of NPP to various driving factors. The Theil–Sen estimator, as well as Mann–Kendall and Hurst exponent methods, were used to analyze the spatiotemporal dynamics and future trends of NPP, and geographical detectors and correlation analysis were used to reveal the response of NPP to various driver changes to environmental factors. The results showed that the NPP was generally on an increasing trend in the Yangtze River Delta region from 2000 to 2019, with the average NPP value of 550.17 g C m−2 a−1, of which 85.90% was the increasing regions and 14.10% was the decreasing regions, showing a significant spatiotemporal heterogeneity characteristic. The trend of future changes in NPP is dominated by an anti-persistence trend in the study area, i.e., the opposite of the past trend. Notably, annual precipitation is the most significant positive driver of NPP; while NPP was negatively correlated with population, meanwhile, different land use/land cover (LULC) also significantly affected the spatial distribution of NPP. Besides, there was a two-factor enhanced interaction between the various drivers on NPP, with the highest interaction occurring between temperature and elevation. Overall, this study provides data support for future regional NPP predictions and ecosystem evaluations.

The Response of Land Surface Temperature Changes to the Vegetation Dynamics in the Yangtze River Basin

Land surface temperature (LST) is a key parameter in the study of surface energy balance and climate change from local through to global scales. Vegetation has inevitably influenced the LST by changing the surface properties. However, the thermal environment pattern in the Yangtze River Basin (YRB) still remains unclear after the implementation of large-scale ecological restoration projects. In this study, the temporal and spatial variation characteristics of LST were analyzed based on the Theil–Sen estimator, Mann–Kendall trend analysis and Hurst exponent from 2003 to 2021. The relationships between vegetation and LST were further revealed by using correlation analysis and trajectory-based analysis. The results showed that the interannual LST was in a state of fluctuation and rise, and the increasing rate at night time (0.035 °C·yr−1) was faster than that at day time (0.007 °C·yr−1). An obvious cooling trend could be identified from 2007 to 2012, followed by a rapid warming. Seasonally, the warming speed was the fastest in summer and the slowest in autumn. Additionally, it was found that autumn LST had a downward trend of 0.073 °C·yr−1 after 2015. Spatially, the Yangtze River Delta, Hubei province, and central Sichuan province had a significant warming trend in all seasons, except autumn. The northern Guizhou province and Chongqing showed a remarkable cooling trend only in autumn. The Hurst exponent results indicated that the spring LST change was more consistent than the other three seasons. It was found by studying the effect of land cover types on LST changes that sparse vegetation had a more significant effect than dense vegetation. Vegetation greening contributed 0.0187 °C·yr−1 to the increase in LST in winter, which was spatially concentrated in the central region of the YRB. For the other three seasons, vegetation greening slowed the LST increase, and the degree of the effect decreased sequentially in autumn, summer, spring and winter. These results improve the understanding of past and future variations in LST and highlight the importance of vegetation for temperature change mitigation.

Electrocardiogram-Artificial Intelligence and Immune-Mediated Necrotizing Myopathy: Predicting Left Ventricular Dysfunction and Clinical Outcomes

ObjectiveTo characterize the utility of an existing electrocardiogram (ECG)-artificial intelligence (AI) algorithm of left ventricular dysfunction (LVD) in immune-mediated necrotizing myopathy (IMNM). Patients and MethodsA retrospective cohort observational study was conducted within our tertiary-care neuromuscular clinic for patients with IMNM meeting European Neuromuscular Centre diagnostic criteria (January 1, 2000, to December 31, 2020). A validated AI algorithm using 12-lead standard ECGs to detect LVD was applied. The output was presented as a percent probability of LVD. Electrocardiograms before and while on immunotherapy were reviewed. The LVD-predicted probability scores were compared with echocardiograms, immunotherapy treatment response, and mortality. ResultsThe ECG-AI algorithm had acceptable accuracy in LVD prediction in 74% (68 of 89) of patients with IMNM with available echocardiograms (discrimination threshold, 0.74; 95% CI, 0.6-0.87). This translates into a sensitivity of 80.0% and specificity of 62.8% to detect LVD. Best cutoff probability prediction was 7 times more likely to have LVD (odds ratio, 6.75; 95% CI, 2.11-21.51; P=.001). Early detection occurred in 18% (16 of 89) of patients who initially had normal echocardiograms and were without cardiorespiratory symptoms, of which 6 subsequently advanced to LVD cardiorespiratory failure. The LVD probability scores improved for patients on immunotherapy (median slope, −3.96; R = −0.12; P=.002). Mortality risk was 7 times greater with abnormal LVD probability scores (hazard ratio, 7.33; 95% CI, 1.63-32.88; P=.009). ConclusionIn IMNM, an AI-ECG algorithm assists detection of LVD, enhancing the decision to advance to echocardiogram testing, while also informing on mortality risk, which is important in the decision of immunotherapy escalation and monitoring.

Increasing groundwater storage and maintaining irrigation through managed aquifer recharge

Aquifers providing groundwater for agriculture are in many cases unsustainably managed, resulting in environmental degradation and socioeconomic impacts. In this context, strategies that contribute to recovering groundwater reserves and satisfactorily maintaining irrigation are essential. Los Arenales Aquifer (Spain) experienced a dramatic decline in groundwater level in the last quarter of the 20th century due to intensive agricultural abstractions. We assess whether this aquifer has recovered in recent years and the potential contribution of managed aquifer recharge (MAR). We evaluate the significance of groundwater level trends and their magnitude through the (regional) Mann-Kendall test and the Theil-Sen estimator. We also calculate the average groundwater level and explore factors that could influence the observed trends, such as MAR, land use, agricultural water demand, and water management measures. We also contrast two groundwater management regions located within Los Arenales Aquifer, namely Los Arenales (LA), which has implemented MAR, and Medina del Campo (MC), to obtain further insight into groundwater development. The hydro statistical analyses reveal a continuous drop in groundwater levels of about −1.3 m/year in LA between 1985 and 2001, followed by a consistent recovery. In MC, groundwater levels decrease in two out of three analysis periods. We show that MAR is spatially and temporally correlated with increasing groundwater level trends. Land use, agricultural water demand, and water management measures have remained similar throughout the analysis period or have a limited impact on groundwater use. Furthermore, the only significant water management measure MC differs from LA is MAR. These pieces of evidence point to MAR as the primary mechanism for replenishing Los Arenales Aquifer, showing the potential of this tool to recover stressed aquifers and sustain irrigation in the area and beyond.

Clinical and Pathological Features of Chinese Patients with Type 2 Diabetes, Biopsy-Proven Diabetic Kidney Disease, and Rapid eGFR Decline.

ObjectiveThe rate of kidney function decline in patients with diabetic kidney disease (DKD) is known to differ. This study analyzed the clinicopathologic features and related risk factors affecting long-term renal survival in Chinese type 2 diabetic patients with rapid estimated glomerular filtration rate (eGFR) decline.MethodsIn this retrospective descriptive study, 191 DKD patients were first classified as rapid eGFR decliners and slow eGFR decliners on the basis of the median eGFR slope value (−8.0 mL/min/1.73 m2/year). In total, 96 patients with rapid eGFR decline were included in the analyses and subsequently allocated to end-stage renal disease (ESRD) and non-ESRD groups. Baseline clinicopathological data of rapid eGFR decliners were collected. Cox proportional hazard analysis was performed to calculate the hazard ratios (HRs) for progression to ESRD.ResultsDuring a median follow-up of 25 months, 52 (54.2%) rapid eGFR decliners progressed to ESRD. These 52 rapid eGFR decliners had poorer renal function, lower hemoglobin and albumin concentrations, higher total cholesterol and baseline proteinuria levels, and more severe interstitial inflammation than those who did not progress to ESRD. After adjustment for age, gender, baseline eGFR, proteinuria, hemoglobin level, serum albumin concentration, and histopathologic parameters, multivariate Cox proportional hazard analysis revealed that eGFR (HR 0.973, 95% CI 0.956–0.989) and proteinuria (HR 1.125, 95% CI 1.030–1.228) were associated with the increased risk of progression to ESRD.ConclusionHigher proteinuria and lower eGFR were independent risk factors for renal progression in Chinese patients with type 2 diabetes and rapid eGFR decline.

Rainfall and Runoff Trend Analysis in the Wadi Mina Basin (Northern Algeria) Using Non-Parametric Tests and the ITA Method

The aim of this paper is to analyze the temporal tendencies of monthly, seasonal, and annual rainfall and runoff in the Wadi Mina basin (north-western side of Africa) using data from five stations in the period from 1973–2012. With this aim, first, a trend analysis was performed using two non-parametric tests: the Theil–Sen estimator and the Mann–Kendall test. Then, to identify trends in the different rainfall and runoff values of the series, the Innovative Trend Analysis technique was further applied. The results of the application of the non-parametric tests on the rainfall data showed a general negative rainfall trend in the Wadi Mina basin for different timescales. Similarly, the results evidenced a general reduction in the runoff values, in particular in the Sidi Abdelkader Djillali and Oued Abtal stations, even though the results obtained for the Oued Abtal station are influenced by a dam. These results were further analyzed through Sen’s method, which enabled the trend identification of the different values (low, medium, and high) of the series.

The effects of facilitatory and inhibitory kinesiotaping of Vastus Medialis on the activation and fatigue of superficial quadriceps muscles

This study aimed to investigate how facilitatory and inhibitory KT of the Vastus Medialis affected the activation and the fatigue indices of VM, Vastus Lateralis (VL) and Rectus Femoris (RF) throughout a dynamic fatigue protocol. Seventeen collegiate athletes (Ten males, seven females, age: 24.76 ± 3.99 years, height: 1.73 ± 0.10 m, mass: 68.11 ± 8.54 kg) voluntarily participated in four dynamic fatigue protocol sessions in which no-tape (control condition), inhibitory, facilitatory and sham KTs were applied to the Vastus Medialis in each session. The protocol included 100 dynamic maximum concentric knee extensions at 90°/s using an isokinetic dynamometry device. The knee extensor muscle activities were recorded using wireless surface electromyography. The average muscle activity (Root mean square) during the first three repetitions and the repetitions number of 51–100, respectively, were used to calculate the before and after exhaustion muscle activity. Furthermore, median frequency slope during all repetitions was reported as the fatigue rate of muscles during different KT conditions and for the control condition (no-tape). The results showed neither muscle activation (significance for the main effect of KT; VM = 0.82, VL = 0.72, RF = 0.19) nor fatigue rate (significance for the main effect of KT; VM = 0.11 VL = 0.71, RF = 0.53) of the superficial knee extensor muscles were affected in all four conditions. These findings suggest that the direction of KT cannot reduce, enhance muscle activity or cause changes in muscle exhaustion. Future studies should investigate the generalizability of current findings to other populations.

Impact of Climate Change on Food Security in Kazakhstan

Global food production faces immense pressure, much of which can be attributed to climate change. A detailed evaluation of the impact of climate change on the yield of staple crops in Kazakhstan, a major food exporter, is required for more scientific planting management. In this study, the Mann–Kendall test and Theil–Sen Median slope were used to determine climate trends and staple food yields over the past 30 years; random forest was used to analyze the importance of monthly climatic factors; states were classified according to climatic factors through systematic clustering method; and lastly, the influence of climate on yield was analyzed using panel regression models. The upward trend in wind speed and potato yield throughout Kazakhstan was apparent. Furthermore, barley and wheat yields had increased in the southeast. We determined that for wheat, frostbite should be prevented after the warmer winters in the high-latitude areas. Except for July–August in the low-latitude areas, irrigation water should be provided in the other growth periods and regions. As similar effects were reported for barley, the same preventive measures would apply. For potatoes, tuber rot, caused by frost or excessive precipitation in May, should be prevented in high-latitude areas; soil dryness should be alleviated during the germination and seedling stages in low-latitude areas; and irrigation and cooling should be maintained during tuber formation and maturation. Furthermore, hot dry air in March and April could damage the crops.

Is the Side Bridge Test Valid and Reliable for Assessing Trunk Lateral Flexor Endurance in Recreational Female Athletes?

Simple SummaryAlthough the side bridge test has been widely used for assessing trunk lateral flexor endurance in sport, clinical, and scientific settings, to the best of the authors’ knowledge, no study has analyzed its validity and reliability in an only female population. The surface electromyography of eight abdominal, back, shoulder and hip muscles was measured during the test to analyze its validity. A one-week test-retest design was performed to evaluate its reliability. No significant differences were found between the trunk lateral flexors and the deltoids. The study data showed that the test performance could be significantly predicted by external oblique and deltoid normalized median frequency slopes and by body mass and trunk height. Based on the results of this study, the shoulder muscle activation and fatigue and the individuals’ anthropometric characteristics, especially the mass, played an important role in the side bridge test performance, which questions the validity of this multi-joint test to specifically assess trunk lateral flexor endurance. In addition, although the side bridge test showed a good data consistency, its intra-subject variability was high, which reduces its utility when small intra-subject changes in muscle endurance are important (e.g., elite sport).The side bridge test (SBT) is one of the most popular tests to assess isometric trunk lateral flexor endurance. The aim of this study was to assess the validity and reliability of the SBT in healthy females. Twenty-four (24.58 ± 3.92 years) physically active (1–2 h of moderate physical activity, 2–3 times a week) females voluntarily participated in this study. The surface electromyography (EMG) of eight abdominal, back, shoulder and hip muscles was measured during the SBT. Normalized median frequency slopes (NMFslope) were calculated to analyze the muscle fatigue. The EMG amplitudes were normalized to maximum EMG values to assess muscle activity intensity. A one-week test-retest design was performed to evaluate the SBT reliability through the ICC3,1 and typical error. Higher NMFslopes and normalized EMG amplitudes were found in deltoids, abdominal obliques, rectus abdominis, and erector spinae in comparison to latissimus dorsi, gluteus medius, and rectus femoris. However, no significant differences were found between the trunk lateral flexors and the deltoids. Linear regression analysis showed that SBT performance could be significantly predicted by external oblique and deltoid NMFslope (adjusted R2 = 0.673) and by body mass and trunk height (adjusted R2 = 0.223). Consistency analysis showed a high intraclass correlation coefficient (0.81) and a relatively high typical error (10.95 s). Despite the good relative reliability of the SBT, its absolute reliability was low and its validity questionable, as the shoulder muscle activation and fatigue and the individuals’ anthropometric characteristics played an important role in SBT performance.

Modeling the tensile mechanical properties of silver birch timber boards

In this paper, the variability of tensile mechanical properties of silver birch timber is investigated and models for the prediction of tension strength and stiffness are developed. Through visual inspections and non-destructive tests, various strength and stiffness related indicators are identified. Destructive tension tests are subsequently performed for the determination of strength and stiffness. On each timber board, strains are measured at four localized regions, whereby, the stiffness of knot sections and clear wood sections are determined. Variability in strength, stiffness, density, knots, grain angle, and annual ring width are investigated along with the relationships between them. A hierarchical model is developed for the prediction of timber board stiffness and the reduction of stiffness due to knots. Models for the prediction of timber board strength and knot cluster strength are developed according to equality and inequality information of the failed specimens, by means of censored regression analysis. Results indicate suitable global and local predictions for silver birch timber, given the dynamic modulus of elasticity, median slope of grain, and knot geometries.