Experiment and Analysis of Variance for Stabilizing Fine-Grained Soils with Cement and Sawdust Ash as Liner Materials.

Due to volume change and low strength, fine-grained soils are problematic in construction. Stabilization with cement and sawdust ash (SDA) by-products can improve engineering properties. This study aimed to investigate the effectiveness of cement and sawdust ash (SDA) in stabilizing fine-grained soils for liner applications. Varying proportions of cement (0-9%) and SDA (0-10%) were added to soil samples (n = 24). Specimens were tested for unconfined compressive strength (UCS), hydraulic conductivity (HC), and volumetric shrinkage strain (VSS). Two-way ANOVA analyzed stabilization effects. Optimal stabilization occurred with 6% cement and 6% SDA, resulting in significant increases in UCS (51 to 375 kN/m2) and decreases in HC (1.7 × 10-8 to 4.7 × 10-10 m/s) and VSS (12.8 to 3.51%) compared to untreated soil. ANOVA indicated that both cement and SDA had statistically significant (p < 0.05) effects on improving all three engineering properties. The addition of 6% cement and 6% SDA significantly improved the expansive soil's strength, hydraulic conductivity, and volume change properties. ANOVA confirmed the quantitative improvements and the significance of both stabilizers. Stabilization using the by-product SDA has the potential to be a sustainable soil improvement method.

Marble Powder as a Soil Stabilizer: An Experimental Investigation of the Geotechnical Properties and Unconfined Compressive Strength Analysis.

Fine-grained soils present engineering challenges. Stabilization with marble powder has shown promise for improving engineering properties. Understanding the temporal evolution of Unconfined Compressive Strength (UCS) and geotechnical properties in stabilized soils could aid strength assessment. This study investigates the stabilization of fine-grained clayey soils using waste marble powder as an alternative binder. Laboratory experiments were conducted to evaluate the geotechnical properties of soil-marble powder mixtures, including Atterberg's limits, compaction characteristics, California Bearing Ratio (CBR), Indirect Tensile Strength (ITS), and Unconfined Compressive Strength (UCS). The effects of various factors, such as curing time, molding water content, and composition ratios, on UCS, were analyzed using Exploratory Data Analysis (EDA) techniques, including histograms, box plots, and statistical modeling. The results show that the CBR increased from 10.43 to 22.94% for unsoaked and 4.68 to 12.46% for soaked conditions with 60% marble powder, ITS rose from 100 to 208 kN/m2 with 60-75% marble powder, and UCS rose from 170 to 661 kN/m2 after 28 days of curing, molding water content (optimum at 22.5%), and composition ratios (optimum at 60% marble powder). Complex modeling yielded R2 (0.954) and RMSE (29.82 kN/m2) between predicted and experimental values. This study demonstrates the potential of utilizing waste marble powder as a sustainable and cost-effective binder for soil stabilization, transforming weak soils into viable construction materials.

Role of the IL8 rs4073 polymorphism in central nervous system toxicity in patients receiving multidrug-resistant tuberculosis treatment.

OBJECTIVE: To determine the role of the IL8 rs4073 polymorphism in predicting the risk of central nervous system (CNS) toxicity in patients receiving standard pharmacological treatment for multidrug-resistant tuberculosis (MDR-TB). METHODS: A cohort of 85 consenting MDR-TB patients receiving treatment with second-line antituberculosis drugs had their blood samples amplified for the IL8 (rs4073) gene and genotyped. All patients were clinically screened for evidence of treatment toxicity and categorized accordingly. Crude and adjusted associations were assessed. RESULTS: The chief complaints fell into the following categories: CNS toxicity; gastrointestinal toxicity; skin toxicity; and eye and ear toxicities. Symptoms of gastrointestinal toxicity were reported by 59% of the patients, and symptoms of CNS toxicity were reported by 42.7%. With regard to the genotypes of IL8 (rs4073), the following were identified: AA, in 64 of the study participants; AT, in 7; and TT, in 11. A significant association was found between the dominant model of inheritance and CNS toxicity for the crude model (p = 0.024; OR = 3.57; 95% CI, 1.18-10.76) and the adjusted model (p = 0.031; OR = 3.92; 95% CI, 1.13-13.58). The AT+TT genotype of IL8 (rs4073) showed a 3.92 times increased risk of CNS toxicity when compared with the AA genotype. CONCLUSIONS: The AT+TT genotype has a tendency to be associated with an increased risk of adverse clinical features during MDR-TB treatment.

Effect of Audio-Visual-Based Art and Music Therapy in Reducing Adolescents Post Traumatic Stress Disorder.

PURPOSE: Post-traumatic stress disorder (PTSD) is a severe anxiety disorder that can develop due to exposure to any event that may result in psychological trauma. This study compared the effect of interactive audio-visual-based art and music therapy in reducing post-traumatic stress disorder in adolescents who survived abduction in Nigeria. METHODS: A quasiexperiment was carried out in two selected secondary schools in Northern Nigeria. The study sample comprised 470 students randomly divided into a control group of 235 and an experiment group of 235. The treatment group was further divided into art 118 and music 117 therapy groups, respectively. RESULTS: Results suggest that interactive audio-visual art therapy and music therapy is an effective intervention strategy for reducing the PTSD of school adolescents that have experienced kidnapping in Nigeria. However, art therapy is more effective in reducing PTSD than music therapy. DISCUSSION: We recommend the introduction of audio-visual-based music and art therapy to reduce the PTSD of adolescents that survived kidnapping in Nigeria. More focus should be made on art therapy, which is more effective in curtailing adolescents PTSD.

Role of the IL8 rs4073 polymorphism in central nervous system toxicity in patients receiving multidrug-resistant tuberculosis treatment / Papel do polimorfismo rs4073 do gene IL8 na toxicidade do sistema nervoso central em pacientes em tratamento para tuberculose multirresistente

ABSTRACT Objective: To determine the role of the IL8 rs4073 polymorphism in predicting the risk of central nervous system (CNS) toxicity in patients receiving standard pharmacological treatment for multidrug-resistant tuberculosis (MDR-TB). Methods: A cohort of 85 consenting MDR-TB patients receiving treatment with second-line antituberculosis drugs had their blood samples amplified for the IL8 (rs4073) gene and genotyped. All patients were clinically screened for evidence of treatment toxicity and categorized accordingly. Crude and adjusted associations were assessed. Results: The chief complaints fell into the following categories: CNS toxicity; gastrointestinal toxicity; skin toxicity; and eye and ear toxicities. Symptoms of gastrointestinal toxicity were reported by 59% of the patients, and symptoms of CNS toxicity were reported by 42.7%. With regard to the genotypes of IL8 (rs4073), the following were identified: AA, in 64 of the study participants; AT, in 7; and TT, in 11. A significant association was found between the dominant model of inheritance and CNS toxicity for the crude model (p = 0.024; OR = 3.57; 95% CI, 1.18-10.76) and the adjusted model (p = 0.031; OR = 3.92; 95% CI, 1.13-13.58). The AT+TT genotype of IL8 (rs4073) showed a 3.92 times increased risk of CNS toxicity when compared with the AA genotype. Conclusions: The AT+TT genotype has a tendency to be associated with an increased risk of adverse clinical features during MDR-TB treatment.

RESUMO Objetivo: Determinar o papel do polimorfismo rs4073 do gene IL8 na previsão do risco de toxicidade do sistema nervoso central (SNC) em pacientes em tratamento farmacológico padrão para tuberculose multirresistente (TBMR). Métodos: Amostras de sangue de uma coorte de 85 pacientes com TBMR que assinaram um termo de consentimento livre e esclarecido e que estavam recebendo tratamento com medicamentos antituberculosos de segunda linha foram amplificadas para o gene IL8 (rs4073) e genotipadas. Todos os pacientes foram avaliados clinicamente quanto a evidências de toxicidade do tratamento e categorizados de acordo com os achados. Foram avaliadas as associações brutas e ajustadas. Resultados: As principais queixas enquadraram-se nas seguintes categorias: toxicidade do SNC; toxicidade gastrointestinal; toxicidade cutânea; e toxicidade ocular e ototoxicidade. Sintomas de toxicidade gastrointestinal foram relatados por 59% dos pacientes, e sintomas de toxicidade do SNC foram relatados por 42,7%. Foram identificados os seguintes genótipos de IL8 (rs4073): AA, em 64 dos participantes; AT, em 7; TT, em 11. Houve associação significativa entre o modelo dominante de herança e toxicidade do SNC no modelo bruto (p = 0,024; OR = 3,57; IC95%: 1,18-10,76) e no ajustado (p = 0,031; OR = 3,92; IC95%: 1,13-13,58). O genótipo AT+TT do gene IL8 (rs4073) apresentou risco 3,92 vezes maior de toxicidade do SNC que o genótipo AA. Conclusões: O genótipo AT+TT tende a se associar a um maior risco de características clínicas adversas durante o tratamento da TBMR.

Acceptance of COVID-19 vaccine and associated factors among healthcare workers in Katsina state: a cross-sectional study in Northwest Nigeria.

OBJECTIVES: Healthcare workers were prioritised to receive the COVID-19 vaccine in Nigeria. Administration of COVID-19 vaccination in Nigeria was challenging because of a lack of trust in vaccine safety and vaccine effectiveness among healthcare workers, who are expected to provide reliable information about vaccines and vaccine-preventable diseases in the communities. Hence, their acceptance and attitudes towards COVID-19 preventive practices could influence the acceptance of the vaccine by the local population. This cross-sectional study assessed the acceptance of the COVID-19 vaccine among healthcare workers in Katsina State. We predicted the variables that increased the vaccine acceptance using logistic regression analysis. SETTING: This hospital-based study was conducted at primary, secondary and tertiary healthcare facilities in Nigeria. PARTICIPANTS: A total of 793 healthcare workers were included in this study. Of these, 65.4% (n=519) were male. OUTCOME MEASURES: To assess acceptance of COVID-19 vaccine measures, and factors increasing acceptance among healthcare workers. RESULTS: Of the healthcare workers, 80% (638) were tested for the SARS-CoV-2, of whom 10.8% (n=65) tested positive. Approximately 97% (n=765) of them believed that the COVID-19 vaccine was safe, and 90% (n=714) received the first dose of the vaccine. Healthcare workers between 30 and 39 years were more likely to accept the vaccine (aOR: 7.06; 95% CI 2.36 to 21.07; p<0.001). Those who had been tested for COVID-19 were more likely (aOR:7.64; 95% CI 3.62 to 16.16; p<0.001) to accept the vaccine. CONCLUSIONS: Our findings showed that the age and prior COVID-19 testing were the main factors influencing the acceptance of the COVID-19 vaccine. There was high acceptance of the COVID-19 vaccine among healthcare workers in Katsina State, Nigeria. Future studies should focus on the completion of doses and serological testing for immunity.

Computer aided detection of tuberculosis using two classifiers.

Tuberculosis caused by Mycobacterium tuberculosis have been a major challenge for medical and healthcare sectors in many underdeveloped countries with limited diagnosis tools. Tuberculosis can be detected from microscopic slides and chest X-ray but as a result of the high cases of tuberculosis, this method can be tedious for both microbiologist and Radiologist and can lead to miss-diagnosis. The main objective of this study is to addressed these challenges by employing Computer Aided Detection (CAD) using Artificial Intelligence-driven models which learn features based on convolution and result in an output with high accuracy. In this paper, we described automated discrimination of X-ray and microscopic slide images of tuberculosis into positive and negative cases using pretrained AlexNet Models. The study employed Chest X-ray dataset made available on Kaggle repository and microscopic slide images from both Near East university hospital and Kaggle repository. For classification of tuberculosis and healthy microscopic slide using AlexNet+Softmax, the model achieved accuracy of 98.14%. For classification of tuberculosis and healthy microscopic slide using AlexNet+SVM, the model achieved 98.73% accuracy. For classification of tuberculosis and healthy chest X-ray images using AlexNet+Softmax, the model achieved accuracy of 98.19%. For classification of tuberculosis and healthy chest X-ray images using AlexNet+SVM, the model achieved 98.38% accuracy. The result obtained has shown to outperformed several studies in the current literature. Future studies will attempt to integrate Internet of Medical Things (IoMT) for the design of IoMT/AI-enabled platform for detection of Tuberculosis from both X-ray and Microscopic slide images.

Emerging threat of drug-resistant tuberculosis and trends in the era of COVID-19: A descriptive study from northwestern Nigeria.

Background: Mycobacterium tuberculosis with resistance to first line and second line anti tuberculous drugs is a serious setback in the treatment of tuberculosis (TB). The COVID-19 pandemic constitutes a serious threat that could unwind the recent gains made thus far in the control of tuberculosis. This study aims to explore the pattern of drug resistant tuberculosis (DRTB) in our institution. We also aimed to explore the changing trends of TB in the era of the COVID-19 pandemic. Methods: This descriptive study included all DRTB patients admitted and managed in the hospital between January 2018 and December 2020. We compare TB case detection in the facility before and after COVID-19 pandemic. Drug susceptibility testing were expressed as frequencies and percentages. Results: The study found that there was 66.03%, 45.09% and 77.78% drop in case detection of drug-sensitive TB (DSTB), DRTB and Fluoroquinolone (FQ) resistant TB respectively in the year 2020 compared to 2019. The drop in cases was similar when the year 2020 was compared to 2018. Among the 132 patients in the cohort, resistance to isoniazid, fluoroquinolones and second-line injectable agents were reported as 23.48%, 12.88%, and 31.06% respectively. Conclusion: We question the potential reason why a drop in tuberculosis cases was observed in the year 2020 and we alert the Nigerian authorities that COVID-19 control efforts going hand-in-hand with intensified TB case finding and surveillance efforts and initiating proper TB treatment for persons with active TB are urgently needed.

Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases.

Reverse-Transcription Polymerase Chain Reaction (RT-PCR) method is currently the gold standard method for detection of viral strains in human samples, but this technique is very expensive, take time and often leads to misdiagnosis. The recent outbreak of COVID-19 has led scientists to explore other options such as the use of artificial intelligence driven tools as an alternative or a confirmatory approach for detection of viral pneumonia. In this paper, we utilized a Convolutional Neural Network (CNN) approach to detect viral pneumonia in x-ray images using a pretrained AlexNet model thereby adopting a transfer learning approach. The dataset used for the study was obtained in the form of optical Coherence Tomography and chest X-ray images made available by Kermany et al. (2018, https://doi.org/10.17632/rscbjbr9sj.3) with a total number of 5853 pneumonia (positive) and normal (negative) images. To evaluate the average efficiency of the model, the dataset was split into on 50:50, 60:40, 70:30, 80:20 and 90:10 for training and testing respectively. To evaluate the performance of the model, 10 K Cross-validation was carried out. The performance of the model using overall dataset was compared with the means of cross-validation and the currents state of arts. The classification model has shown high performance in terms of accuracy, sensitivity and specificity. 70:30 split performed better compare to other splits with accuracy of 98.73%, sensitivity of 98.59% and specificity of 99.84%.

A novel multi-model data-driven ensemble approach for the prediction of particulate matter concentration.

Accuracy in the prediction of the particulate matter (PM2.5 and PM10) concentration in the atmosphere is essential for both its monitoring and control. In this study, a novel neuro fuzzy ensemble (NF-E) model was proposed for prediction of hourly PM2.5 and PM10 concentration. The NF-E involves careful selection of relevant input parameters for base modelling and using an adaptive neuro fuzzy inference system (ANFIS) model as a nonlinear kernel for obtaining ensemble output. The four base models used include ANFIS, artificial neural network (ANN), support vector regression (SVR) and multilinear regression (MLR). The dominant input parameters for developing the base models were selected using two nonlinear approaches (mutual information and single-input single-output ANN-based sensitivity analysis) and a conventional Pearson correlation coefficient. The NF-E model was found to predict both PM2.5 and PM10 with higher generalization ability and least error. The NF-E model outperformed all the single base models and other linear ensemble techniques with a Nash-Sutcliffe efficiency (NSE) of 0.9594 and 0.9865, mean absolute error (MAE) of 1.63 µg/m3 and 1.66 µg/m3 and BIAS of 0.0760 and 0.0340 in the testing stage for PM2.5 and PM10, respectively. The NF-E could improve the efficiency of other models by 4-22% for PM2.5 and 3-20% for PM10 depending on the model.

Structural Shielding Evaluation: A Case Study of the Radiography Room of a Rural Hospital in Jos, Nigeria.

INTRODUCTION: Most Nigerian rural hospitals constructed before the publication of the 2005 National Council on Radiation Protection and Measurements Report No. 147 did not undergo a performance assessment at the time of construction. To avoid overexposure to ionizing radiation and to ensure adequate protection of patients, workers, and the public, the shielding barriers need to be evaluated to ascertain that they conform to this standard. METHODS: This study evaluates the shielding barriers for the general radiography room in a rural hospital in Jos, Nigeria. The workload information, generator voltage waveform, anode material, filtration, and anode angle with XRAYBARR calculation model were used to estimate the thickness of lead, concrete, gypsum, steel, plate glass, and wood required to shield the X-ray facility installed in the hospital. The design dose limit was compared to the estimated shielded dose, and the calculated shielded barrier thickness to the design shielded barrier thickness was also compared. RESULTS: The unshielded radiation doses inside the X-ray room were high, indicating that the radiological department of the study area is not minimizing radiation doses to patients. The calculated doses beyond the barriers were greater than the design dose limit, indicating that the shielded barriers in place were not adequate and did not comply with the international standard. DISCUSSION: Hospitals must understand the type of shielding materials that can provide adequate protection and to what extent they can protect their radiography rooms. Management and radiation protection agencies need to ascertain whether these barriers are still adequate or require reinforcement through regular quality assurance testing. Due to an increase in workload associated with an increase in population and urbanization, proper policies are needed more than ever in this and other rural hospitals in Nigeria. CONCLUSION: The tested X-ray rooms did not comply with international recommendations for shielding thickness. Except for the door, console, and changing room, a 0.5 mm-thick lead reinforcement is required. It is also recommended that quality assurance testing occur on an annual basis.

COVID-19 in children: a case series from Nigeria.

INTRODUCTION: The global spread of COVID-19 remains unabated in the past few months with a rise in the number of available literature on the novel virus. There are very few paediatric studies and are mainly from developed countries with a paucity of information on the clinical manifestation of COVID-19 disease in African children, including Nigeria. METHODS: We described the clinical presentation, laboratory findings, treatment and outcome in a group of five Nigerian children managed at a COVID-19 isolation and treatment centre in Nigeria. RESULTS: We managed a total of five children with an age range of 3 months to 8 years in the last four weeks (16th April to 15th May 2020). Three of the five children were males. All the children had close contact with family members that tested positive for COVID-19. Out of the five children, one had moderate disease, three had mild symptomatic disease, and one was asymptomatic. Two out of the five children had lymphocytosis. Out of the four children who had chest radiograph, two had features of pneumonia. CONCLUSION: COVID-19 is not uncommon in Nigerian children, and all had a confirmed family member with COVID-19. Besides, contrary to leucopaenia with lymphopaenia observed in the adult's population, we found lymphocytosis in this cohort and about 50.0% had pneumonic changes on chest radiograph.

An emotional artificial neural network for prediction of vehicular traffic noise.

Road traffic is a leading source of environmental noise pollution in large cities, which greatly affects the health and well-being of people. A reliable method for the prediction of road traffic noise is required for monitoring and assessment of traffic noise exposure. This study presents the first application of the Emotional Artificial Neural Network (EANN), as a new generation of neural network method for modeling the road traffic noise in Nicosia, North Cyprus. The efficiency of the EANN model was validated in comparison with the classical feed-forward neural network (FFNN) using two different scenarios with different input combinations. In the first scenario, vehicular classification (the number of cars, medium vehicles, heavy vehicles) and average speed were considered as the models' inputs. In the second scenario, the total traffic and percentage of heavy vehicles were used instead of the classification where the input parameters were total traffic volume, average speed and percentage of heavy vehicles. Application of the EANN model in the prediction of road traffic noise could improve the efficiency of the FFNN, MLR and empirical models at the verification stage up to 14%, 35% and 37%, respectively. Classifying the traffic volume into sub-classes (in scenario 1) before feeding them into the models improved the performance of the EANN and FFNN models at the verification stage by 8% and 12%, respectively. Sensitivity analysis of the input parameters indicated that total traffic volume is the most relevant factor influencing road traffic noise in the study area followed by the number of cars, medium vehicles, heavy vehicles, average speed and percentage of heavy vehicles, respectively.

Artificial intelligence based ensemble model for prediction of vehicular traffic noise.

Vehicular traffic noise is the main source of noise pollution in major cities around the globe. A reliable and accurate method for the estimation of vehicular traffic noise is therefore essential for creating a healthy noise-free environment. In this study, 2 linear (simple average and weighted average) and 2-nonlinear (neural network and neuro-fuzzy) ensemble models were developed by combining the outputs of three Artificial Intelligence (AI) based non-linear models; Adaptive Neuro Fuzzy Inference System (ANFIS), Feed Forward Neural Network (FFNN), Support Vector Regression (SVR) and one Multilinear regression (MLR) model to enhance the performance of the single black box models in predicting vehicular traffic noise of Nicosia city, North Cyprus. In this way, first a nonlinear sensitivity analysis was applied to select the most relevant and dominant input parameters of the traffic data obtained from 12 observation points in the study area. The most dominant parameters in order of their importance were determined to be number of cars, number of van/pickups, number of trucks, average speed and number of buses. Classifying the number of vehicles into five categories before feeding the traffic data into the AI models was observed to improve performance of the single models up to 29% in the verification phase. Out of the four ensembles models developed, the nonlinear ANFIS ensemble was found to be the most robust by improving the performance of ANFIS, FFNN, SVR and MLR models in the verification stage by 11%, 19%, 21% and 31%, respectively.

COVID-19 in children: a case series from Nigeria

Introduction: the global spread of COVID-19 remains unabated in the past few months with a rise in the number of available literature on the novel virus. There are very few paediatric studies and are mainly from developed countries with a paucity of information on the clinical manifestation of COVID-19 disease in African children, including Nigeria. Methods: we described the clinical presentation, laboratory findings, treatment and outcome in a group of five Nigerian children managed at a COVID-19 isolation and treatment centre in Nigeria. Results: we managed a total of five children with an age range of 3 months to 8 years in the last four weeks (16th April to 15th May 2020). Three of the five children were males. All the children had close contact with family members that tested positive for COVID-19. Out of the five children, one had moderate disease, three had mild symptomatic disease, and one was asymptomatic. Two out of the five children had lymphocytosis. Out of the four children who had chest radiograph, two had features of pneumonia. Conclusion: COVID-19 is not uncommon in Nigerian children, and all had a confirmed family member with COVID-19. Besides, contrary to leucopaenia with lymphopaenia observed in the adult's population, we found lymphocytosis in this cohort and about 50.0% had pneumonic changes on chest radiograph

FPGA-Based Processor Acceleration for Image Processing Applications.

FPGA-based embedded image processing systems offer considerable computing resources but present programming challenges when compared to software systems. The paper describes an approach based on an FPGA-based soft processor called Image Processing Processor (IPPro) which can operate up to 337 MHz on a high-end Xilinx FPGA family and gives details of the dataflow-based programming environment. The approach is demonstrated for a k-means clustering operation and a traffic sign recognition application, both of which have been prototyped on an Avnet Zedboard that has Xilinx Zynq-7000 system-on-chip (SoC). A number of parallel dataflow mapping options were explored giving a speed-up of 8 times for the k-means clustering using 16 IPPro cores, and a speed-up of 9.6 times for the morphology filter operation of the traffic sign recognition using 16 IPPro cores compared to their equivalent ARM-based software implementations. We show that for k-means clustering, the 16 IPPro cores implementation is 57, 28 and 1.7 times more power efficient (fps/W) than ARM Cortex-A7 CPU, nVIDIA GeForce GTX980 GPU and ARM Mali-T628 embedded GPU respectively.

Adsorption of aqueous Cd(II) and Pb(II) on activated carbon nanopores prepared by chemical activation of doum palm shell.

Non-uniformly sized activated carbons were derived from doum palm shell, a new precursor, by carbonization in air and activation using KOH, NaOH and ZnCl2. The activated carbon fibres were characterised by X-ray diffraction, N2 adsorption-desorption, scanning electron microscopy, particle size analysis and evaluated for Cd(II) and Pb(II) removal. The 40-50 nm size, less graphitic, mesoporous NaOH activated carbon yielded high adsorption efficiency, pointing largely to the influence surface area. The performance of the KOH based activated carbon was arguably explained for the first time in terms of crystallinity. The efficiencies of the mesoporous ZnCl2-formulated activated carbon diminished due to the presence of larger particles. Batch adsorption of divalent metals revealed dependence on adsorbent dose, agitation time, pH and adsorbate concentrations with high adsorption efficiencies at optimum operating parameters. The equilibrium profiles fitted Langmuir and Freundlich isotherms, and kinetics favoured pseudo-second order model. The study demonstrated the practicability of the removal of alarming levels of cadmium and lead ions from industrial effluents.

Challenges in the management of early versus late presenting congenital diaphragmatic hernia in a poor resource setting.

BACKGROUND: Despite the advances in management, congenital diaphragmatic hernia (CDH) has continued to pose a significant challenge to paediatric surgeons. This is amplified in a setting like ours where there is a dearth of facilities to cope with the problem of CDH. This study was undertaken to highlight the peculiarities of the management of CDH in a poor resource setting. METHODS: All confirmed cases of CDH were prospectively documented from 2003 till date. RESULTS: Seven children were treated from 2003 till date. The diaphragmatic defect was on the left side in six (83.8%) and on the right side in one (17.7%). All the patients had primary closure of the defect without patch via an abdominal approach. The three patients presenting at birth died while the remaining four patients survived. CONCLUSION: With inadequate neonatal intensive care facilities, the severe early presenting CDH has a dismal prognosis. In contrast, the late presenting CDH poses more diagnostic challenges; but once identified and appropriate treatment instituted, it has an excellent prognosis. We recommend that physicians should include CDH in the differential diagnosis of patients with birth asphyxia and in patients with chronic respiratory symptoms with failure to thrive.

Challenges in the management of early versus late presenting congenital diaphragmatic hernia in a poor resource setting

Background: Despite the advances in management; congenital diaphragmatic hernia (CDH) has continued to pose a significant challenge to paediatric surgeons. This is amplified in a setting like ours where there is a dearth of facilities to cope with the problem of CDH. This study was undertaken to highlight the peculiarities of the management of CDH in a poor resource setting. Methods: All confirmed cases of CDH were prospectively documented from 2003 till date. Results: Seven children were treated from 2003 till date. The diaphragmatic defect was on the left side in six (83.8) and on the right side in one (17.7). All the patients had primary closure of the defect without patch via an abdominal approach. The three patients presenting at birth died while the remaining four patients survived. Conclusion: With inadequate neonatal intensive care facilities; the severe early presenting CDH has a dismal prognosis. In contrast; the late presenting CDH poses more diagnostic challenges; but once identified and appropriate treatment instituted; it has an excellent prognosis. We recommend that physicians should include CDH in the differential diagnosis of patients with birth asphyxia and in patients with chronic respiratory symptoms with failure to thrive

Photocatalytic treatment of 4-chlorophenol in aqueous ZnO suspensions: intermediates, influence of dosage and inorganic anions.

The photocatalytically driven removal of eco-persistent 4-chlorophenol from water using ZnO is reported here. Kinetic dependence of transformation rate on operating variables such as initial 4-chlorophenol concentration and photocatalyst doses was investigated. A complete degradation of 4-chlorophenol at 50 mg L(-1) levels was realised in 3h. Analytical profiles on 4-chlorophenol transformation were consistent with the best-line fit of the pseudo zero-order kinetics. The addition of small amounts of inorganic anions as SO(4)(2-), HPO(4)(-), S(2)O(8)(2-) and Cl(-) revealed two anion types: active site blockers and rate enhancers. Fortunately, Cl(-) and SO(4)(2-) commonly encountered in contaminated waters enhanced the rate of 4-chlorophenol degradation. The reaction intermediates and route to 4-chlorophenol mineralisation were elucidated by combined RP-HPLC and GC-MS methods. In addition to previously reported pathway products of 4-chlorophenol photo-oxidation catechol was detected. A radical mechanism involving o-hydroxylation is proposed to account for the formation of catechol.