Would Africa’s largest hydropower dam have profound environmental impacts?

In the face of rapid growth in the global demands for water, energy, and food, building large dams is expected to continue. Due to its potential opportunities and risks for the people of the Eastern Nile Basin, the Grand Ethiopian Renaissance Dam (GERD) on the Nile River has commanded regional and international attention. Once completed, it will rank the largest hydropower dam in Africa and among the largest worldwide. Discourse among scientists and negotiators from Ethiopia, Sudan, and Egypt on the design, initial filling, and long-term operation of the GERD is ongoing since the construction started in 2011, but no agreement has yet been reached. The discourse has hitherto focused on the impacts on hydropower production, water availability, and irrigated agriculture, with little attention to the dam’s potential environmental impacts. Here, we communicate our viewpoint on this gap, drawing on knowledge from other dams around the world and some GERD characteristics. The hydrological alterations associated with the GERD could adversely impact fish, aquatic plants, and biodiversity in the downstream due to possible changes in water temperature, salinity, and oxygen content. The GERD’s expected flooded area, location at low latitude in the tropics, and the deep turbine intakes could intensify greenhouse gas emissions, whereas the dam’s high reservoir depth would abate the emissions. The dam’s electricity could also reduce regional greenhouse gas emissions if combined with cleaner intermittent solar and wind energy sources. With a maximum reservoir area of 1904 km2, surface evaporation and consequently local extreme precipitation and humidity could increase. The aforementioned impacts could have transboundary ecological, agricultural, and health implications and, therefore, should be taken into consideration alongside the benefits of the dam

Cytokines as Immunological Markers for Follow up of Disease Activity During the Treatment of Pulmonary Tuberculosis

Background: Cytokines play a major role in protection against Mycobacterium tuberculosis infection and regulate the immune responses at a cellular level. Cytokine profile determines clinical outcome of the disease and responses to treatment as well. A T helper 1 (Th1) cytokine interferon gamma (IFN-U) is one of the most important cytokines which activate the macrophages to produce tumor necrosis factor-alpha (TNF-V). Excessive production of TNF-V have been implicated in immunopathogenesis of tuberculosis. A T helper 2 (Th2) response leads to release of IL-4, and IL-10 promoting an anti-inflammatory macrophage response. Interleukin-4(IL-4), has been implicated to down-regulate IFN-U, and thus has a harmful effect on TB patients. IL10 cytokine has thecapacity to inhibit Th1 activation and thus terminates cell mediated immune responses.Objective:The objective of the present study was to determine Th1 and Th2 cytokine profile in patients with tuberculosis to identify immunological marker for follow up of the disease activity, and to study the outcome of treatment.Methods: To examine this, blood samples were collected from newly diagnosed HIV negative pulmonary tuberculosis patients and from apparently healthy individuals as controls following an informed consent. Blood samples were as well collected at several intervals during the treatment with anti-tuberculosis drugs. Levels of IFN-U, TNF-V, IL-4 and IL-10 were measured pre and during treatment using commercial available enzyme-linked immune-sorbent assay (ELISA). Data were analyzed using SPSS 20. Receiver Operating Characteristic (ROC) Curve analysis has beencarried out to assess their discriminative power and to determine cut-off values. Analysis has been carried out further by calculating other measures of diagnostic test accuracy.Results: The median serum level of IL-4 was 20 and 35 pg/ml higher in new cases (untreated patients) and in patients under treatment with oral anti-tuberculosis, respectively, compared with that of controls (p=001). Levels of TNF- were significantly increased in patients before and afterthe treatment than those in control (p=0.001). New cases had the highest median level (10pg/ml) followed by those under treatment group (6pg/ml). Levels for IFN-U were not statistically different between patients and controls (p=0.351). Median levels of IL10 were similar in both controls and new cases groups (35pg/ml), but lower in patients under treatment group (20pg/ml). Increase in levels of IL-4 during treatment showed that Th2 immune responses still present and may indicate active disease and thus IL4 cytokine may be a possible marker for the disease activity.Conclusion: serum levels of TNF- in TB patients is useful in the evaluation of the disease activity during therapy, not replacing clinical parameters of disease activity in TB. Similar to TNF-, IL-4 can also be used as marker for TB severity. On the other hand IL-4test can be used to diagnose TBin highly exposed suspects where a positive result is more likely to indicate TB.Keywords: Tuberculosis; Cytokines; Immunological markers

Estimation of daily global solar radiation from measured temperatures at Cañada de Luque, Córdoba, Argentina

Solar radiation is the most important source of renewable energy in the planet; it's important to solar engineers, designers and architects, and it's also fundamental for efficiently determining irrigation water needs and potential yield of crops, among others. Complete and accurate solar radiation data at a specific region are indispensable. For locations where measured values are not available, several models have been developed to estimate solar radiation. The objective of this paper was to calibrate, validate and compare five representative models to predict global solar radiation, adjusting the empirical coefficients to increase the local applicability and to develop a linear model. All models were based on easily available meteorological variables, without sunshine hours as input, and were used to estimate the daily solar radiation at Cañada de Luque (Córdoba, Argentina). As validation, measured and estimated solar radiation data were analyzed using several statistic coefficients. The results showed that all the analyzed models were robust and accurate (R2 and RMSE values between 0.87 to 0.89 and 2.05 to 2.14, respectively), so global radiation can be estimated properly with easily available meteorological variables when only temperature data are available. Hargreaves-Samani, Allen and Bristow-Campbell models could be used with typical values to estimate solar radiation while Samani and Almorox models should be applied with calibrated coefficients. Although a new linear model presented the smallest R2 value (R2 = 0.87), it could be considered useful for its easy application. The daily global solar radiation values produced for these models can be used to estimate missing daily values, when only temperature data are available, and in hydrologic or agricultural applications

Hydrological Modelling Using Gridded and Ground‐Based Precipitation Datasets in Data‐Scarce Mountainous Regions

Satellite‐ and gridded ground‐based precipitation data are crucial for understanding hydrological processes. However, the performance of these products needs rigorous evaluation before their integration into hydrological models. This study evaluates two types of precipitation products based on their hydrological simulation performance. The evaluation focuses on ground‐based precipitation datasets (GA and Aphrodite) and satellite‐based precipitation products (SPPs). The GA dataset combines rain gauge measurements with the Asian Precipitation—Highly‐Resolved Observational Data Integration Towards Evaluation (Aphrodite) dataset to fill gaps in areas with insufficient rain gauge coverage. It is also used for model calibration under Method I. In Method II, models are calibrated with Tropical Rainfall Measuring Mission (TRMM), Climate Hazards Group Infrared Precipitation (CHIRPS), Multi‐Source Weighted‐Ensemble Precipitation (MSWEP) and Aphrodite product without the station data. The study considers the Koshi River Basin located in the eastern Himalayas encompassing Nepal and China's Tibetan region. The basin supports downstream ecosystems and domestic, hydro‐power and irrigation development. Based on ranking of seven performance metrics, CHIRPS emerged as the best performing SPP whereas MSWEP ranked the lowest. When the five precipitation datasets were evaluated, GA performed the best, followed by CHIRPS, TRMM, MSWEP and Aphrodite respectively. In Method I, TRMM achieved the highest Nash−Sutcliffe Efficiency (NSE) value of 0.68, and MSWEP showed poor performance with an NSE value of −0.20. In Method II, CHIRPS showed the strongest performance with an NSE values of 0.82, whereas MSWEP performed slightly lower but still achieved an NSE value of 0.74. Seasonal analysis provided further valuable insights into selecting and blending precipitation datasets by identifying time series that performed best in specific seasons. These findings, alongside model uncertainty analyses, emphasise the influence of precipitation biases and underscore the value of integrating ground‐based and satellite data. Ultimately, this study contributes to advancing water resource planning and management strategies in the Koshi River Basin and similar mountainous regions

A proposed architecture for generic and scalable CDR analytics platform utilizing big data technology

Telecom Call Details Record (CDR) data-set is considered a rich source of valuable information that will bring new big revenues to Communication Service providers (CSP) as well as it will empower many out-telco services such as transportation, education, health programs, and business analysis in resource management and planning, decision making, and processes optimization. However, extracting these valuable information from raw CDRs with the classical SQL and BI systems is very costly and has poor performance measures. This is due to the big volume of CDR data-set, the high and growing data rate and the large number of fields it contains. Many CDR analytics systems were built using Big Data technology, to overcome the scalability problem of the centralized computing, but the heterogeneity usage of CDR analytics have not been considered; they were built for specific and predetermined use cases. This paper presents a proposed platform architecture for real, near-real time and batch CDR analysis to provide analytics for heterogeneous applications, through designing a high generic and scalable platform. This paper illustrates the platform design consideration along with how the proposed architecture was built. Moreover, it gives a brief functional description and implementation suggestions for each component in the architecture

Overview on the first human cytogenetic research in Sudan

Introduction: The present study is the first human cytogenetic project in Sudan which was titled: Cytogenetic and FISH analyses in Sudanese patients with dysmorphic features, ambiguous genitalia, and infertility. The aim of the present study was not only to characterize the genetic alterations in patients with dysmorphic features, ambiguous genitalia and/or infertility among Sudanese population, but also to attract the medical community attention to the importance of human cytogenetics in clinical genetics practice, and also to facilitate the introduction and clinical application of such valuable service in Sudan. Materials and Methods: In this study chromosomal G–banding and fluorescence in situ hybridisation (FISH) analysis were performed on 44 Sudanese patients, 29 females, 14 males, and one patient with unassigned sex. Patients age ranging between 17 days-39 years (mean 18 years), Of the 44 patients, 20 had ambiguous genitalia, 8 dysmorphic features, 11 have puberty and/or fertility complains, and 5 were healthy individual (parents of 3 patients with dysmorphic features). Results: Cytogenetic analysis of 20 patients complaining of ambiguous genitalia (13 females and 6 males, and one case with unassigned sex) showed that 8 has karyotypes different from their assigned sex and the other cases showed karyotypes consistent with Edward syndrome (47,XX,+18) (case 7), and a case with 45,Xdel(X)(p11) (case 11) respectively, when using FISH the 45,Xdel(X)(p11) case showed translocation of the SRY (sex-determining region Y), gene to the active X chromosome. For the 8 patients of dysmorphic features; five showed karyotypes consistent with Down syndrome, of which one showed Robertsonian translocation, with both FISH and ordinary G-banding, and the other three showed normal karyotypes. All the parents showed normal karyotypes. Among the infertility cases all showed normal karyotypes, except for two which showed karyotypes consistent with Turner syndrome and one which showed a male karyotype although the case was raised as a female; ultrasound showed a mass in the position of prostate. Discussion: The study, the ever first one in Sudan, assured the importance, the possibility, and the need for cytogenetic and FISH analysis in diagnosis, management and genetic counseling of genetic diseases caused by constitutional chromosomal changes among Sudanese patients. Sudan Journal of Medical Sciences Vol. 1(1) 2006: 25-3

Big data analysis solutions using mapReduce framework

Recently, data that generated from variety of sources with massive volumes, high rates, and different data structure, data with these characteristics is called Big Data. Big Data processing and analyzing is a challenge for the current systems because they were designed without Big Data requirements in mind and most of them were built on centralized architecture, which is not suitable for Big Data processing because it results on high processing cost and low processing performance and quality. MapReduce framework was built as a parallel distributed programming model to process such large-scale datasets effectively and efficiently. This paper presents six successful Big Data software analysis solutions implemented on MapReduce framework, describing their datasets structures and how they were implemented, so that it can guide and help other researchers in their own Big Data solutions

Analysis of Tooth Extraction Causes and Patterns

PURPOSE: The purpose of this study was to investigate the causes and patterns of extraction of permanent teeth in the targeted population. METHODS: The study was conducted for a period of 11 months. An especially designed form was used to record the causes for extraction of a permanent tooth. Further, it was analyzed for age, gender, education, occupation, smoking, tooth position, endodontic treatment, chewing, esthetics, needs replacement, type of existing prosthesis, and causes for extraction. The various causes which were considered to determine association with the tooth extraction were dental caries, periodontal problems, trauma, orthodontics, prosthodontic failures, endodontic failures, and others. RESULTS: The percentage of extractions was almost the same in males and females aged. Maximum extractions were noticed in 36–45 years of age group (32.5%). The presence of caries was observed to be the main reason for extraction (68.1%), followed by periodontal problems (17.6%) and orthodontic problems (4.8%). The most frequently extracted posterior teeth were first mandibular molar (22.2%), followed by the third maxillary molar (15.2%). CONCLUSION: Dental caries was found to be the most common reason for the extraction of teeth. Molar teeth were found to be the most frequently extracted, with an increased number of extracted first premolars as a result of orthodontic treatment. Maxillary teeth are extracted more than mandibular, mainly due to caries and periodontal problems