Statistical Trend Analysis Research Articles

TRENDS IN DEVELOPMENT AND DIVERSIFICATION OF EXPORTS OF THE REPUBLIC OF UZBEKISTAN

The article analyzes the dynamics of Uzbekistan's exports of goods and services from 2010 to 2023. It assesses the diversification of both the commodity structure and the geographic distribution of exports using the export product concentration index and the export diversification index. Statistical analysis of trends in Uzbekistan's exports during this period highlights the urgent need to accelerate diversification in both the structure and geography of exports. It emphasizes increasing the share of finished goods with high added value in the export portfolio, as well as diversifying and expanding services exports and enhancing regional export activities. To achieve this faster export diversification, a comprehensive set of interrelated measures is required across various areas of economic policy. This includes improvements in trade, investment, and industrial policies, along with deeper institutional reforms.

Investigating precipitation pattern and variability in the Niger Delta: a statistical analysis of trends and change points (1972–2022)

There has been significant variation in precipitation in different parts of the world, and increasingly this has been attributed to climate change. Despite reliance on rain-fed agriculture, detailed analysis of regional precipitation trends within specific sub-national areas, such as the Niger Delta, remains scant. This study examines annual rainfall trends over 51 years (1972–2022) across seven stations in the Niger Delta using different statistical methods. Descriptive statistics show different patterns among stations, some showing upward trends, others declines. Mean annual rainfall ranges from 1,969.05 mm in Akure to 2385.04 mm in Port Harcourt, showing significant regional variability. Linear regression and LOWESS analysis show mixed trends; Mann–Kendall and Spearman’s Rho tests showed significant increase in Owerri, while Sen’s slope analysis confirms varying trends across the region. Pettitt test results confirms Owerri’s significant increase in precipitation. This study contributes to a greater understanding of precipitation trends in the Niger Delta.

Trends in knee cartilage repair procedures in the United States, 2010 to 2020

IntroductionSurgical intervention of knee articular cartilage injuries may prevent degeneration in symptomatic patients. ObjectiveThis study aims to analyze trends, demographics, and yearly incidence of four different knee cartilage repair procedures in the U.S. from 2010 to 2020. MethodsThe PearlDiver database was queried for patients who underwent knee microfracture, autologous chondrocyte implantation (ACI), osteochondral autograft transfer (OAT) and osteochondral allograft transplantation (OCA) procedures from 2010 to 2020. Student t and χ-square tests were used for statistical comparisons and analysis of data trends. Regression models and Compound Annual Growth Rates (CAGR) further assessed trends of each procedure. Results220,674 patients from 2010 to 2020 were included in this study. Microfracture incurred a 62.4% decrease in occurrence (P < 0.001). Incidence of OCA trended upwards (37.7%; P = 0.065) whilst OAT procedures significantly decline (53.9%; P < 0.001). ACI procedure numbers remained relatively stable (11.2% increase; P = 0.847). ConclusionsThe incidence of microfracture significantly decreased in the United States from 2010 to 2020. There was a positive trend in the incidence of OCA cases, whilst the number of OAT cases decreased significantly. The number of ACI cases performed per year did not change significantly over the study period with the exception of an increase from 2017-2019. Microfracture procedures were performed in an older patient population than the other cartilage procedures. Males were more likely to undergo the four cartilage preservation surgeries compared to females. Similar studies should be carried out in other large health databases to confirm the external validity of these trends across the United States.

Bibliometric Insights into Research Hotspots and Trends in Obesity and Asthma from 2013 to 2023

Introduction: Obesity and asthma are closely linked, but the current state of research on this topic and future research directions have yet to be comprehensively explored. This study aims to provide an up-to-date overview of the research landscape in the field of obesity and asthma. Methods: A bibliometric analysis was conducted using the Web of Science Core Collection database to identify papers published on obesity and asthma between 2013 and 2023. VOSviewer software was utilized for statistical analysis and visualization of collaborative networks, research trends, literature sources, citation analysis, co-citation analysis, and keyword analysis. Results: A total of 3,406 records from 1,010 journals authored by 17,347 researchers affiliated with 4,573 institutes across 117 countries and regions were retrieved. The number of publications and citations increased annually. The USA and China contributed the majority of records. Major nodes in the collaboration network map included Harvard Medical School, Johns Hopkins University, University of Newcastle, Karolinska Institution, University of Toronto, and Seoul National University. Prolific authors included Anne E. Dixon, Erick Forno, Lisa G. Wood, Deepa Rastogi, and Fernando Holguin. Research trends and hotspots focused on metabolism studies, Mendelian randomization, gut microbiome, inflammation response, gene, biomarker research, and comorbidities were identified as potential future research frontiers. Conclusion: This study provides a comprehensive overview of the current research status and trends in the field of obesity and asthma. Our findings highlight the importance of understanding collaboration patterns, research hotspots, and emerging frontiers to guide future research in this area.

First Red List of Ecosystems assessment of a tropical glacier ecosystem to diagnose the pathways towards imminent collapse

Abstract Tropical glaciers are rapidly disappearing, particularly in isolated mountain peaks below 5,000 m elevation. These glaciers are fundamental substrates for unique cryogenic ecosystems in high tropical environments where the ice, melting water and rocky substrate sustain microbiological communities and other meso- and macro-biota. This study uses the Red List of Ecosystems guidelines to diagnose the collapse of the tropical glacier ecosystem of the Cordillera de Mérida, Venezuela. We undertook the assessment with existing estimates of glacier ice extent, indirect historical estimates of ice mass balance and global mechanistic models of future ice mass balance. We complemented these with additional statistical analysis of trends and bioclimatic suitability modelling to calculate and predict rates of decline and relative severity of degradation in selected ecosystem indicators. The evidence suggests an extreme risk of collapse (Critically Endangered) because of a prolonged and acute reduction in ice extent and changes in climatic conditions that are leading to the complete loss of ice mass. The ice substrate has declined 90% in the last 20 years, and observed acceleration of the rate of decline suggests it will probably disappear within the next 5 years. Loss of ice substrate will trigger an immediate loss of supraglacial, englacial and subglacial biotic compartments and initiate a decades-long succession of forefield vegetation. However, ongoing inventories of native biota and monitoring of ecosystem transitions can provide valuable insights and lessons for other ecosystems facing similar risks. The Red List of Ecosystems assessment protocol provides a useful framework for comparative analysis of cryogenic ecosystems.

Empirical analysis of the cyberattacks of the Russian–Ukrainian war

This research study aims to empirically analyze the cyberattacks that occurred in the context of the Russian–Ukrainian conflict between 2022 and 2023, with a specific focus on the impact of these attacks on civilian infrastructure and institutions. The data collection for this study is based on publicly available sources from the Cyber- Peace Institute, taking into account various types of incidents such as malware, distributed denial of service (DDoS) attacks, spam, information operations, and website defacements. The study employs a network theory approach to examine the structure and dynamics of incidents and campaigns, while additional statistical methods and trend analysis are used to assess sector-specific and geographic patterns, as well as changes in attack frequency and severity. The research aims to contribute to the existing literature on cyber warfare and to provide valuable insights into the cyber threats faced by civilian infrastructure and institutions during times of conflict.

Part-load analysis and preliminary annual simulation of a constant inventory supercritical CO2 power plant for waste heat recovery in cement industry

The present work investigates the part-load performance of a MW-scale sCO2 power plant designed as waste heat recovery unit for an existing cement plant located in Czech Republic, in the framework of the H2020 funded project CO2OLHEAT. The study first presents the selected power plant configuration and then focuses on the evaluation of its part-load operation due to variation of flue gas mass flow rate and temperature. The range of flue gas conditions at the outlet of the upstream process is retrieved from a preliminary statistical analysis of historical trends obtained through the cement plant monitoring. The numerical model developed for this study aims at providing realistic results thanks to the adoption of turbomachinery performance maps provided by the turbomachinery manufacturer of the project. Moreover, heat exchangers have been modelled through a discretized approach which has been validated against manufacturer data, while piping inventory and pressure losses have been assessed through a preliminary sizing that considers the actual distances to be covered in the cement plant. Performance decay is estimated for the whole range of flue gas conditions, reporting the most significant power cycle parameters, and identifying the main causes of efficiency loss. The part-load analysis is carried out considering a constant CO2 inventory, in order to reduce the system complexity and capital cost and simplify plant operation. Results show that the operation entails minor variation of the compressors operative points in the whole range of operating conditions of the cement plant, avoiding the risk of anti-surge bypass activation. Moreover, the plant is able to work close to the nominal thermodynamic cycle efficiency (20.5 %–23.0 %) for most of the year and benefits from part-load operation in terms of overall performance. In the last part of the work, a preliminary techno-economic analysis of the plant is also presented to highlight the potential advantages of sCO2 technology for waste heat recovery applications. The results of the part-load performance of the plant are combined with the flue gases data obtained from the preliminary statistical analysis and the cement plant historical monitoring. An annual electricity production equal to 13′909.7 MWh is obtained, corresponding to 6560 equivalent hours and a system capacity factor of 74.9 %. The investment cost of each CO2OLHEAT plant component is estimated by means of cost correlations obtained from literature and the non-discounted payback time is computed as a function of the electricity selling price. The results show that, even considering electricity prices before 2022, the payback time of the CO2OLHEAT plant is estimated to be lower than 8 years, justifying the industrial interest in the proposed technology.

Spatiotemporal analysis of malaria in the state of Mato Grosso-Legal Amazon, Brazil: identification of high-risk áreas

The objective of the study was to analyze temporal and geographic data to identify high-risk areas for malaria occurrence in the state of Mato Grosso within the Legal Amazon. High-risk areas were identified through scan statistics, and the relative risk (RR) was characterized using cluster maps. Statistical temporal trend analysis was conducted using Prais-Winsten autoregression. A total of 20,819 cases were identified, with higher incidence rates among men. Malaria was predominantly diagnosed via thick blood smear microscopy, with Plasmodium vivax being the most prevalent species. The average incidence ranged from 0.01 to 2,849.85, with higher averages observed in the North, West, and Northwest regions. The Global Moran analysis revealed a positive correlation (0.47) between incidence rates and regions with a higher number of cases, while Local Moran identified distinct infection clusters. Eight risk clusters were delineated using scan statistics, with the highest RR recorded at 90.09. The spatiotemporal scan classified three statistically significant high-risk clusters exhibiting stationary temporal trends. These findings highlight the delineation of high-risk areas for malaria infection in Mato Grosso.

Synergistic patient factors are driving recent increased pediatric urgent care demand.

We aimed to use the high fidelity urgent care patient data to model the factors that have led to the increased demand at our local pediatric urgent care centre. The dataset for this retrospective cohort study was obtained from our local healthcare centre's national reporting data for pediatric urgent care visits from 2006 to 2022. Variables analyzed included: basic patient demographics, chief complaint, triage urgency, date and time of registration/discharge, discharge diagnosis, and discharge destination. Statistical analysis of non-linear trends was summarized by locally estimated scatterplot smoothing splines. For machine learning, we used the tidymodels R package. Models were validated in training using k-fold cross validation with k = 5. We used univariate linear regression as a baseline model. After the data was standardized, correlation and homoscedasticity were evaluated between all parameter permutations. This dataset consisted of 164,660 unique visits to our academic centre's pediatric urgent care. Over the study period, there was an overall substantial increase in the number of urgent care visits per day, with a rapid increase beyond previous levels in 2021 and further in 2022. The increased length of stay trend was consistent across presenting complaint categories. The proportion of patients without primary care in 2022 was 2.5 times higher than in 2013. A random forest machine learning model revealed the relative importance of features to predicting a visit in 2022 were: longer stay, later registration in the day, diagnosis of an infectious illness, and younger age. This study identified a combination of declining primary care access, circulating viral infections, and shifting chief complaints as factors driving the recent increase in frequency and duration of visits to our urgent care service.

Studies on Variation of Temperature and Rainfall using Climatological data for the Plain and Hill zones of Uttarakhand

The present study examines long-term annual, seasonal and monthly changes and short-term fluctuations in monsoonal rainfall and temperature over plain and hill zones of Uttarakhand. Both rainfall and temperature data for period of 1981-2020 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen’s slope estimator were used to examine and analyze the problems. The detailed analysis of the data for 40 years indicates that the annual range of temperature is increasing in the hill zone. In the context of agriculture, the observed trends in temperature and rainfall patterns pose significant implications for farming practices and crop yields in Uttarakhand. The increasing annual range of temperature, particularly in the hill zone, suggests a heightened risk of temperature extremes such as heat waves and cold spells. During the monsoon season, while rainfall levels may remain relatively stable or exhibit minor fluctuations, the variability highlighted by the box and whisker plots underscores the importance of preparedness for both excess and deficit rainfall scenarios.

Decreasing trends in PM2.5 and BC concentrations observed on central and southwestern Japanese Islands

The interannual trends in fine particulate matter (PM2.5) and black carbon (BC) concentrations at remote stations in central (Noto) and southwestern (Fukue) Japan were investigated using statistical trend analysis and the chemical transport model, Regional Air Quality Model 2 (RAQM2ver3). The concentrations of PM2.5 and BC in Noto and Fukue exhibited seasonal variations and decreased from 2013 to 2020. Higher concentrations of PM2.5 and BC were observed during the spring season (April) in both locations. The PM2.5 concentrations peaked in Fukue approximately one month earlier than in Noto, while the BC concentration peak in Noto occurred one month earlier than that of PM2.5. The total reductions in PM2.5 concentrations in Noto and Fukue were 7.5 ± 5.0 and 3.8 ± 0.95 μg m−3, corresponding to reduction rates 1.1 ± 0.7 and 0.5 ± 0.95 μg m−3year−1, respectively, compared to the concentrations in 2013. The total reduction in BC concentrations in Noto from 2013 to 2019 was estimated to be 0.13 ± 0.1 μg m−3, amounting to 0.018 ± 0.014 μg m−3year−1 reduction rate. The results of the source–receptor relationships analysis suggest that the decreases in PM2.5 and BC concentrations in Fukue and Noto were significantly influenced by reductions in amounts transported from central China (CCHN, 30–40°N), northern China (NCHN, >40°N) and Japan (JPN) after 2015/2016. The decrease in emissions from these three regions accounted for the observed reductions in particulate concentrations.

KENYA: MULTIAGENCY STRATEGIES FOR CONFLICT MANAGEMENT IN LAIKIPIA COUNTY

The paper examined multiagency strategies for conflict management in Laikipia County, Kenya. It provided a solid foundation for understanding the context of the effect of multiagency approaches on conflict management. A descriptive survey research design was used incorporating both quantitative and qualitative primary data from a questionnaire, FGDs, and Key Informants interviews. The area of study was Laikipia County, Kenya with a focus on Laikipia West Sub County. Stratified random sampling was used to select respondents while the purposive sampling technique was used to select informants with in-depth knowledge and experience relevant to the research objectives. Qualitative data was coded, thematically categorized, and synthesized. Statistical modeling and trend analysis for quantitative data were performed with the aid of SPSS V.29. The result was presented using graphs, and charts while prioritizing validity and reliability through rigorous document selection and analysis methods. The research addressed the effectiveness of past strategies, emphasizing the importance of nuanced assessments that considered scope, context, implementation, outcomes, and dissemination. The findings emphasized the need for a nuanced and comprehensive assessment approach, covering scope and context, implementation and outcomes, challenges, and opportunities. The paper advocated for participatory approaches, long-term impact assessment, flexible frameworks, formal dialogue platforms, capacity building, strong leadership, resource mobilization, and continuous learning and adaptation to ensure effective conflict management. It concluded that while multiagency approaches can effectively manage conflicts, successful implementation requires meticulous planning and execution, tailored to the specific dynamics of the conflict landscape. The paper recommended a continued focus on participatory approaches, establishing formal dialogue platforms, and prioritizing strong leadership and inclusivity, benefiting policymakers, multiagency leaders, practitioners, and stakeholders involved in conflict management in Laikipia County. Keywords: Multiagency actions, participatory approach, multiagency strategies, conflict management.

Assessing the accuracy and reliability of satellite-derived precipitation products in the Kosi River basin (India).

The present research endeavors to examine the effectiveness of four gridded precipitation datasets, namely Integrated Multi-satellite Retrievals for GPM (IMERG), Tropical Precipitation Measuring Mission (TRMM), Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), with the observed rainfall data of eight rain gauge stations of India Meteorological Department (IMD) from 2001 to 2019 in Kosi River basin, India. Various statistical metrics, contingency tests, trend analysis, and rainfall anomaly index were utilized at daily, monthly, seasonal, and annual time scales. The categorical metrics namely probability of detection (POD) and false alarm ratio (FAR) indicate that MERRA-2 and IMERG datasets have the highest level of concurrence with the observed daily data. Statistical analysis of gridded datasets with observed dataset of IMD showed that the performance of the IMERG dataset is better than MERRA-2, PERSIANN, and TRMM datasets with "very good" coefficient of determination (R2) and Nash-Sutcliffe Efficiency values for monthly data. Trend analysis of gridded seasonal data of IMERG showed similar trends of observed seasonal data whereas other dataset differs. IMERG also performed well in identifying wet and dry years based on annual data. Discrepancies of the satellite sensor in capturing the precipitation have also been discussed. Thus, the IMERG dataset can be effectively used for hydro-meteorological and climatological investigations in cases of lack of observed datasets.

Statistical analysis of trends in Battery Electric Vehicles: Special reference to vehicle weight reduction, electric motor, battery, and interior space dimensions

Electric vehicles (EVs) are increasingly being used, as they are more environmentally friendly than conventional vehicles with internal combustion engines (ICE). Battery electric vehicles (BEVs) can be said to have zero exhaust emissions only if the electricity used to drive these vehicles is obtained in an environmentally friendly way. It is common knowledge that BEVs have a significantly higher overall mass than conventional vehicles. The significantly higher total vehicle weight of BEVs can have various adverse effects on energy consumption during movement and the vehicle's dynamics. In contrast to the negative aspects of BEVs, there are also positive aspects that are primarily related to the comfort of drivers and passengers, considering the main fact that they do not require the presence of a floor tunnel. In this paper, trends related to BEVs in the previous five years were statistically analysed. Changes in average sizes related to BEVs are shown, primarily internal dimensions that can be of crucial importance when deciding between BEVs and conventional vehicles. In the paper itself, other important trends are presented, both for the electric motor itself and for the batteries used in BEVs.

Assessing Process Control in the Foundry

Relying on scrap rates alone to assess process control in the foundry can be deceiving. Depending on the inspection method used, it is possible to sort grossly non-conforming parts, while still allowing a wide window of acceptance, masking a process that is out of control. Modern methods of acoustic resonance testing (ART) allow for detailed data logging of both part weight and resonant frequency peak data. Monitoring these two factors at the lot level can give foundry managers insight into how consistent their process is both within a single date code and across multiple date codes. The information collected during quality testing can and should be combined with statistical information gathered at the front of the foundry (design, tooling, molding, inoculation, pouring, cooling, and shakeout) and used to adjust the process to achieve smaller data spreads and more consistent and repeatable process control. Once a process is deemed to be under control, consideration should be given to monitoring the defined specification limits and subsequent control limits using statistical trend analysis as a means for ensuring a process is not approaching a condition in which the opportunity for quality issues can arise.

The impact of land use and cover changes on river flows in Wundanyi Catchment of Taita Hills, Kenya (1970–2030)

&lt;p&gt;Taita Hills are one of the most important biodiversity hotspots of Kenya but are experiencing a high rate of deforestation due to the to the conversion of its original forestland to agriculture and settlement during the last century. These landscape dynamics, coupled with rainfall fluctuations in these critical ecosystems, may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of land use/cover change (LUCC) in the Wundanyi catchment from 1970 to 2030 and predict their specific and combined effects on surface runoff and stream flow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modeling using both historical and primary data from the Wundanyi catchment and Landsat TM and ETM+ imagery of Taita Hills for 1990, 2000, and 2010. Results show highly variable mean seasonal and annual values of discharge in Wundanyi catchment, probably attributed to environmental changes affecting Taita Hills in general and Wundanyi catchment in particular. Compared to 1990, major land use/cover changes in 2010 were featured by the expansion of built-up area (250%), plantation forest (23.7%), broadleaved forest (17.4%), and thicket (15.9%). It was also notable the decrease in woodland (−30.3%), cropland (−21.6%), and shrubland (−0.8%). Dynamic spatial trends by the year 2030 will be evidenced by increased thicket by 0.41% per annum (&lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; = 81.6%) and by decreased plantation forests (−0.13%; &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; = 91.3%), woodland (−0.10%; &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; = 77.6%), shrubland (−0.11%; &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; = 85.2%), broadleaved forests (−0.03%; &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; = 56.6%) and cropland (−0.09%; &lt;em&gt;R&lt;/em&gt;&lt;sup&gt;2&lt;/sup&gt; of 84.4). These changes will shape the catchment landscape and influence its hydrology, unless the existing forest and agricultural policy interventions are enforced. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in the Wundanyi catchment.&lt;/p&gt;

"Effects of floating aquatic vegetation and canal sediment on phosphorus in drainage discharges in agricultural canals: A case study in the everglades agricultural area, Florida"

Phosphorus (P) discharge from agricultural and urban drainage is known for causing downstream eutrophication worldwide. Agricultural best management practices that are designed to reduce P load out of farms target different P species from various sources such as fertilizers leaching and farm soil and canal sediment erosion, however, few studies have assessed the impact of floating aquatic vegetation (FAV) on canal sediment and farm drainage water quality. This study evaluated the impact of FAVs on canal sediment properties and P water quality in drainage canals in the Everglades Agricultural Area in south Florida, USA. Non-parametric statistical methods, correlation analysis, trend analysis and principal component analysis (PCA) were used to determine the relationship between FAV coverage with sediment properties and P water quality parameters. Results showed that FAV coverage was correlated with the highly recalcitrant and most stable form of P in the sediment layer (Residual P Pool). FAV coverage also correlated with the dissolved organic P (DOP) which was the smallest P pool (7 %) of total P concentration in drainage water, therefore FAV coverage had no correlation with farm P load. The trend analysis showed no trend in farm P loads, despite a decline in FAV coverage at farm canals over an 8-year period. Phosphorus content in the sediment surface layer was strongly associated with farm P load and had a significant correlation with particulate P (PP) and soluble reactive P (SRP) which constituted 47 % and 46 % of the total P concentration in the drainage water, respectively. Equilibrium P concentration assays also showed the potential to release SRP from the sediment layer. The P budget established for this study reveals that sediment stores the largest P mass (333 kg P), while FAVs store the smallest P mass (8 kg P) in a farm canal, highlighting the significant contribution of canal sediment to farm P discharges. Further research is required to evaluate the impact of sediment removal and canal maintenance practices that help reduce farm P discharges.

Rainfall analysis and deriving design storm for hydrological modelling of Koyna dam catchment area in Maharashtra state of India

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event.In this study, 40 years (1982–2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series.From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment.

Climate variability and river flow changes in Wundanyi sub-catchment of Taita hills, Kenya

&lt;p&gt;Wundanyi sub-catchment of Taita hills is experiencing a high rate of deforestation due to the conversion of all its original forestland to agriculture and settlement during the last century. The landscape dynamics coupled with rainfall fluctuations in these critical ecosystems may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of selected hydroclimatic variables in Wundanyi sub-catchment from 1970 to 2030 and their specific and combined effects on surface runoff and streamflow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modelling using both historical and primary hydroclimatic data from Wundanyi and Voi weather stations. Results show highly variable mean seasonal and annual values of temperature, rainfall, runoff and discharge in both Wundanyi and Voi weather stations. Increasing mean temperatures and rainfall were observed during the long dry season (JJAS), while decreasing seasonal discharges were observed during both the JJAS dry season and the OND short rainy season. These anomalies were pronounced in 1980–1981, 1986–1987 and 1992–1993, probably due to both global and local environmental changes affecting Taita Hills in general and Wundanyi sub-catchment in particular. The predicted effects of rainfall fluctuation were supported by declining surface runoff of 1.3% during JJAS, and an increase of 0.8% during the OND, with similar effects on river discharges. The combined effects of climate variability and Land use and cover changes (LUCC) on surface runoff were estimated to an increase of 200 mm during JJAS and 370 mm during OND, and while river discharges increased by 2.37 m&lt;sup&gt;3&lt;/sup&gt;/s and 1.93 m&lt;sup&gt;3&lt;/sup&gt;/s during JJAS and OND, respectively. Consequently, natural forest covers have significant control effects on surface runoff and can boost river discharges amid diverse agricultural cropping practices. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in Wundanyi sub-catchment.&lt;/p&gt;

The impact of over-the-top service providers on the Global Mobile Telecom Industry: A quantified analysis and recommendations for recovery

Telecom industry is significantly evolving all over the globe than ever. Mobile users’ number is increasing remarkably. Telecom operators are investing to get more users connected and to improve user experience, however, they are facing various challenges. Decrease of main revenue streams of voice calls, SMS (Short Message Service) and LDC (Long distance calls) with a significant increase in data traffic. In contrary, with free cost, OTT (Over the top) providers such as WhatsApp and Facebook communication services rendered over networks that built and owned by MNOs. Recently, OTT services gradually substituting the traditional MNOs` services and became ubiquitous with the help of the underlying data services provided by MNOs. The OTTs` services massive penetration into telecom industry is driving the MNOs to reconsider their strategies and revenue sources. Objective: The research objective is to critically evaluate the impact of OTT providers on MNOs. With the empirical evidences, the research explores a quantified impact of OTTs on MNOs main revenue streams, and breakdown this impact to highlight effect`s significance. Followed by a statistical trend analysis of global MNOs` revenue over the last decade. Additionally, the research aims to compile, evaluate, and analyze set of former proposed strategies for MNOs to overcome the OTTs` impact. Methods: Referring to available open source raw data collected from GSMA and official telecommunications regulatory authorities worldwide, the research develops a statistical model based on regression and extrapolation to analyze the global MNOs` revenue trend. Findings: This study reveals a hidden revenue loss for global telecommunications industry represented in all MNOs all over the world. The study corelates the hidden revenue loss to OTTs evolution. The study finds out that SMS is the most impacted traditional service of MNOs and predicted that it will vanish at quarter 4 of 2022. Recommendations: MNOs to apply 4 different strategies varying from competing to partnering with OTTs based on the services overlapping level and OTT size. MNOs need to target OPEX and CAPEX reductions and develop their own multi-functional customer-oriented OTT application.