The Quality of Medicines in Community Pharmacies in Riyadh, Saudi Arabia: A Lot Quality Assurance Sampling (LQAS)-Based Survey

Objectives: To classify community pharmacies (CPs) in Riyadh, Saudi Arabia, in terms of the quality of medicines sold by them, using?the lot quality assurance sampling (LQAS) technique with a predefined threshold. Methods: Riyadh CPs were divided into 2 categories (“lots” for the purpose of LQAS), i.e., chain and independent CPs. Upper and lower rate thresholds for CPs that sell low-quality medicines were predefined as 20% and 5%, respectively. Consumer and provider risks were predefined as 0.05 and 0.10, respectively. The calculated number of randomly selected CPs required in each lot was 36;then, sale of low-quality medicines in >3 CPs implies a prevalence of >20% of such CPs according to LQAS. A randomly selected brand of amoxicillin (selected as a quality indicator of medicines because it is both widely counterfeited and heat-sensitive) was purchased from each pharmacy by a “mystery shopper”, checked for authenticity, and analyzed for drug content and content uniformity using a validated HPLC method. Results: Substandard amoxicillin was purchased in 9 pharmacies (4 chains and 5 independent). Both lots were thus rejected as unacceptable, which may indicate that consumers in Riyadh are at risk of purchasing substandard medicines at CPs. Conclusions: The quality of medicines sold in CPs in Riyadh did not meet our acceptability criterion, and appropriate intervention by decision makers is recommended. LQAS proved to be a practical, economical, and statistically valid sampling method for surveying the quality of medicines. It should enable decision makers to allocate resources for improvement more efficiently.

A METHOD OF IMAGE QUALITY ASSESSMENT FOR COMPRESSIVE SAMPLING VIDEO TRANSMISSION

Based on compressive sampling transmission model, we demonstrate here a method of quality evaluation for the reconstruction images, which is promising for the transmission of unstructured signal with reduced dimension. By this method, the auxiliary information of the recovery image quality is obtained as a feedback to control number of measurements from compressive sampling video stream. Therefore, the number of measurements can be easily derived at the condition of the absence of information sparsity, and the recovery image quality is effectively improved. Theoretical and experimental results show that this algorithm can estimate the quality of images effectively and is in well consistency with the traditional objective evaluation algorithm.

Quality Assessment of Attribute Data in GIS Based on Simple Random Sampling

On the basis of the principles of simple random sampling, the statistical model of rate of disfigurement (RD) is put forward and described in detail. According to the definition of simple random sampling for the attribute data in GIS, the mean and variance of the RD are deduced as the characteristic value of the statistical model in order to explain the feasibility of the accuracy measurement of the attribute data in GIS by using the RD. Moreover, on the basis of the mean and variance of the RD, the quality assessment method for attribute data of vector maps during the data collecting is discussed. The RD spread graph is also drawn to see whether the quality of the attribute data is under control. The RD model can synthetically judge the quality of attribute data, which is different from other measurement coefficients that only discuss accuracy of classification.

Urban Air Quality Assessment of Kathmandu by Passive Sampling Technique

This paper presents an assessment of air quality of the Kathmandu valley, capital city of Nepal. This is the largest urbanized area in the country of about 300 km2. In the last two decades an intensive development of demographic, traffic and industry growth in the region was observed which was reflected on the air quality degradation. In order to evaluate the urban air quality in Kathmandu, a field monitoring network for particle deposition, nitrogen dioxide （NO2） and sulphur dioxide （SO2） by passive sampling with high space resolution was implemented in co-operation with IVL-Sweden. The net work composed of 60 monitoring sites distributed in a grid of 1 × 1 km2 covering all over the main city and some rural valley. Monitoring were carried out for two seasons, rainy and dry as two campaign monitoring. The diffusive samplers were prepared and analyzed in IVL, Sweden. Good agreements in particle deposition between the two campaigns were observed. The particle deposition to the surrogate surface varied between 3 and 608 μg@cm2·monthl for the monitoring periods. The NOz concentrations on the other hand were quite similar in the two campaigns, and the SO2 concentrations were much lower in the first campaign compared to the second. The ranges of NO2 and SO2 concentrations were found to be from 5.6 to 52.6 μg/m3 and 0.6 to 23.4 μg·m-3 respectively. Arc Info/Arc map GIS 9.2 software was used for production of maps of spatial distribution of all the three parameters in the valley. Seasonal variation and traffic influence were also studied. Local meteorological effects in the distribution of pollutants were clearly observed and the NO2 concentrations were strictly related with traffic intensity.

Impact of Water Quality Sampling Process on Environmental Monitoring Results

The sampling of environmental water should ensure the representativeness and integrity of the sampled water body,which has an important impact on the monitoring results.The sampling of different water bodies sampling will result in different monitoring results.Based on the study on the problems and influencing factors in the sampling process of environmental water quality,improvement measures during the sampling process were elaborated in the paper,with the aim to strengthen on-site control of water sampling,and reduce adverse effects on monitoring results.

Research on the Large-scale Network Intrusion Mode based on Principal Component Analysis and Drop Quality Sampling

In this paper, we conduct research on the large-scale network intrusion mode based on the principal component analysis and dropquality sampling. With the growing of network security issues, invasion detection becomes the study hotspot. There are two main types of thatinvasion detection technology, the fi rst is that misuse detection and the anomaly detection. Misuse detection can more accurately detect attacks,but high non-response rates, anomaly detection could detect the unknown attacks, but higher rate of false positives. Network invasion detectionproblem is summed up in the network data fl ow of discriminant problem, namely the judgment of network data fl ow is normal or malicious andin this sense here invasion detection problem can be understood as a pattern recognition problem. Our research integrates the PCA and samplingtechnique to propose the new idea on the IDS that is innovative and will promote the development of the corresponding techniques.

Exploring the Sample Quality Using Rough Sets Theory for the Supervised Classification of Remotely Sensed Imagery

In the supervised classification process of remotely sensed imagery, the quantity of samples is one of the important factors affecting the accuracy of the image classification as well as the keys used to evaluate the image classification. In general, the samples are acquired on the basis of prior knowledge, experience and higher resolution images. With the same size of samples and the same sampling model, several sets of training sample data can be obtained. In such sets, which set reflects perfect spectral characteristics and ensure the accuracy of the classification can be known only after the accuracy of the classification has been assessed. So, before classification, it would be a meaningful research to measure and assess the quality of samples for guiding and optimizing the consequent classification process. Then, based on the rough set, a new measuring index for the sample quality is proposed. The experiment data is the Landsat TM imagery of the Chinese Yellow River Delta on August 8th, 1999. The experiment compares the Bhattacharrya distance matrices and purity index zl and △x based on rough set theory of 5 sample data and also analyzes its effect on sample quality.

Yarn Quality Prediction for Small Samples Based on AdaBoost Algorithm

In order to solve the problems of weak prediction stability and generalization ability of a neural network algorithm model in the yarn quality prediction research for small samples,a prediction model based on an AdaBoost algorithm(AdaBoost model) was established.A prediction model based on a linear regression algorithm(LR model) and a prediction model based on a multi-layer perceptron neural network algorithm(MLP model) were established for comparison.The prediction experiments of the yarn evenness and the yarn strength were implemented.Determination coefficients and prediction errors were used to evaluate the prediction accuracy of these models,and the K-fold cross validation was used to evaluate the generalization ability of these models.In the prediction experiments,the determination coefficient of the yarn evenness prediction result of the AdaBoost model is 76% and 87% higher than that of the LR model and the MLP model,respectively.The determination coefficient of the yarn strength prediction result of the AdaBoost model is slightly higher than that of the other two models.Considering that the yarn evenness dataset has a weaker linear relationship with the cotton dataset than that of the yarn strength dataset in this paper,the AdaBoost model has the best adaptability for the nonlinear dataset among the three models.In addition,the AdaBoost model shows generally better results in the cross-validation experiments and the series of prediction experiments at eight different training set sample sizes.It is proved that the AdaBoost model not only has good prediction accuracy but also has good prediction stability and generalization ability for small samples.

A Novel Multiple Dependent State Sampling Plan Based on Time Truncated Life Tests Using Mean Lifetime

The design of a new adaptive version of the multiple dependent state(AMDS)sampling plan is presented based on the time truncated life test under the Weibull distribution.We achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans.A warning sign for acceptance number was proposed to increase the probability of current lot acceptance.The optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk.A simulation study was presented to support the proposed sampling plan.A comparison between the proposed and existing sampling plans,namely multiple dependent state(MDS)sampling plans and a modified multiple dependent state(MMDS)sampling plan,was considered under the average sampling number and operating characteristic curve values.In addition,the use of two real datasets demonstrated the practicality and usefulness of the proposed sampling plan.The results indicated that the proposed plan is more flexible and efficient in terms of the average sample number compared to the existing MDS and MMDS sampling plans.

Comparison of uniform resampling and nonuniform sampling direct-reconstruction methods in k-space for FD-OCT

The nonuniform distribution of interference spectrum in wavenumber k-space is a key issue to limit the imaging quality of Fourier-domain optical coherence tomography(FD-OCT).At present,the reconstruction quality at different depths among a variety of processing methods in k-space is still uncertain.Using simulated and experimental interference spectra at different depths,the effects of common six processing methods including uniform resampling(linear interpolation(LI),cubic spline interpolation(CSI),time-domain interpolation(TDI),and K-B window convolution)and nonuniform sampling direct-reconstruction(Lomb periodogram(LP)and nonuniform discrete Fourier transform(NDFT))on the reconstruction quality of FD-OCT were quantitatively analyzed and compared in this work.The results obtained by using simulated and experimental data were coincident.From the experimental results,the averaged peak intensity,axial resolution,and signal-to-noise ratio(SNR)of NDFT at depth from 0.5 to 3.0mm were improved by about 1.9 dB,1.4 times,and 11.8 dB,respectively,compared to the averaged indices of all the uniform resampling methods at all depths.Similarly,the improvements of the above three indices of LP were 2.0 dB,1.4 times,and 11.7 dB,respectively.The analysis method and the results obtained in this work are helpful to select an appropriate processing method in k-space,so as to improve the imaging quality of FD-OCT.

Analytical quality-by-design approach for sample treatment of BSA-containing solutions

The sample preparation of samples conlaining bovine serum albumin（BSA）,e.g..as used in transdermal Franz diffusion cell（FDC） solutions,was evaluated using an analytical qualily-by-design（QbD）approach.Traditional precipitation of BSA by adding an equal volume of organic solvent,often successfully used with conventional HPLC-PDA,was found insufficiently robust when novel fused-core HPLC and/or UPLC-MS methods were used.In this study,three factors（acetonitrile（%）.formic acid（%） and boiling time（min）） were included in the experimental design to determine an optimal and more suitable sample treatment of BSAcontaining FDC solutions.Using a QbD and Derringer desirability（D） approach,combining BSA loss,dilution factor and variability,we constructed an optimal working space with the edge of failure defined as D〈0.9.The design space is modelled and is confirmed to have an ACN range of 83 ± 3% and FA content of 1 ±0.25%.

Integrated assessment of sea water quality based on BP artificial neural network

In order to carry out an integrated assessment of sea water quality objectively, this paper based on the concept and principle of artificial neural network, generated appropriate training samples for BP artificial neural network model through the method of producing samples to the concentration of various pollution index of sea water quality from the viewpoint of threshold, established the BP artificial neural network model of sea water quality assessment using multi-layer neural network with error back-propagation algorithm. This model was used to assess water environment and obtain sea water quality categories of offshore area in Bohai Bay through calculating. The calculations shown that pollution index in river＇s wet season was higher than that in dry season from 2004 to 2007, and the pollution was particularly serious in 2005 and 2006, but a little better in 2007. The assessed results of cases shown that the model was reasonable in design and higher in generalization, meanwhile, it was common, objective and practical to sea water quality assessment.

Air quality nearby road traffic tunnel portals: BTEX monitoring

A monitoring campaign of BTEX （benzene, toluene, ethylbenzene, o- m- and p-xylene） was carried out nearby two tunnel portals in the urban area of Naples with the aim to verify air quality in this kind of urban sites. Sampling was carried out using the active adsorption technique. Sampling time was 1 h. Ambient temperature and traffic flow measurements were carried out during each sampling operation. The results indicate that average benzene concentrations at both sites exceed the limit value of 10 μg/Nm^3 established by the European Community （EC） （Dir. 2000/69）. Concentration levels of other BTEX are relatively high as well. A correlation between BTEX concentration and two wheeler vehicle flow was observed.

基于Loose r-sample的网格质量保持技术

为保证虚拟手术系统中的网格质量,提出一种基于Loose r sample理论的快速表面网格重建算法。记录满足Loose r sample采样定理的点集,用以描述物体的轮廓。通过约束Delaunay方法对该点集进行三角化,标记顶点和Delaunay单元,重构新的网格。实验结果表明,该算法能够保证生成网格的质量,简化仿真复杂度。

Water Quality of Selected Fishing Beaches of Lake Victoria Kenyan Gulf

Lake Victoria the second largest fresh water body in the world located in East Africa is a shared resource between Kenya, Tanzania and Uganda and enjoys a wide range of streams and rivers from as far as Burundi and Rwanda. The lake has environmentally undergone physical, chemical and biological changes in the last four decades, particularly rise in its trophic condition and decline in oxygen level, which affects the water quality and fish population dynamics. This study therefore set out to determine the quality of water in selected fishing beaches of Lake Victoria, Kenya with a view to report the possible pollution levels. pH was highest at Nyamasari and Kotieno (9.3 ± 0.1) and lowest at Nyachebe and Kichinjio (7.08 ± 0.1) whereas temperature was highest at Nyamasari (29.5°C ± 0.0°C) and lowest at Kichinjio (23.4°C ± 0.2°C). DO was highest at Kotieno (10.3 ± 0.2 mgL) and lowest at Seka (2.4 ± 0.1 mgL). Turbidity was highest at Uyoga (125.5 ± 0.90 NTU) and lowest at Osieko (2.7 ± 0.1 NTU). Ammoniacal nitrogen was highest at Dunga (1278.3 ± 0.8 μ∙gl-1) and lowest at Nyamasari (12.4 ± 0.8), all a factor of human activities, lake substratum and effluents from rivers and surface runoff. All parameters assessed showed significant differences across sampling sites and depth except pH which did not vary significantly with distance from lakeshore. Further, all parameters did not show a clear pattern with respect to distance from the lakeshore possibly due to adequate mixing in the gulf. There is a need for further water quality monitoring by seasons to inform policy decisions towards sustainable lake exploitation.

Passive Samplers Deployment in the Ayapel Swamp for Monitoring Temporal Dynamics of Mercury in the Water Column

Passive sampling is a simple and efficacious sampling technique that guarantees a safe collection and transportation of samples to the analysis site, and obtaining results with more temporal resolution. As a case of study, passive samplers were deployed in the Ayapel Swamp, Colombia, located in the influence zone of open pit gold mines. Mercury, iron and manganese were sampled at two different depths by the Chemcatcher? passive sampler and regular grab sampling. Additionally, dissolved oxygen, oxidation-reduction potential, pH and water temperature were measured. The results showed that depth and time did not have a significant influence (ANOVA, confidence level of 95%) on mercury concentration on both passive samplers and grab sampling. However, concentration of Fe and Hg in passive samplers had a high positive correlation, but it may be because depth increase during sampling period caused the dilution of both analytes. In conclusion, passive samplers proved to be a valuable tool for understanding the response of mercury to the Ayapel Swamp dynamics.

Effects of Conservation Methods of Water Samples on Determination of Total Phosphorus

Effects of conservation methods of water samples on determination of total phosphorus were analyzed from aspects of methods of adding conserving agent, SS concentration, natural sedimentation time, conservation temperature and time. The results showed that SS concentration in water and natural sedimentation time had the greatest impact on the determination of total phosphorus, while the influence of methods of adding conserving agent, conservation temperature and time was relatively smaller. TP concentration in water samples conserved irregularly was higher than the standard value due to the existence of SS and microorganisms in water, and the deviation became larger with the increase of SS concentration in water. In addition, quality control measures and matters needing attention during the conservation process of water samples were put forward to improve the accuracy of TP concentration.

Management practices and technologies for efficient biological sample collection from domestic animals with special reference to Indian field conditions

Management strategies and the use of advanced technologies are equally important for determining the sample number and sampling frame for successful field sampling for animal disease prevalence studies.The quality of the biological samples collected in the field has a direct bearing on the integrity of the data generated,prevalence estimates and subsequent policy decisions on disease control.Hence,compromising the quality of biological samples collected in the field could potentially undermine the priority setting principles in disease control strategies.Biological samples collected from domestic animals in the field are precious materials and require meticulous planning for sample collection,sample storage in the field,transportation,and storage in the laboratory.Poorly managed field sampling has a significant detrimental impact on the sample quality and quantity and directly affects the accuracy of disease prevalence data.A bad choice of sampling tools,containers,storage and transport all have a negative impact on the integrity of the sample and consequently have an impact on the outcome.Over the last two years,as part of our one health animal sampling work in ndia,we have observed challenges and opportunities in the field sampling of animals for disease prevalence studies.This paper aims to provide information on management practices and technologies for efficient biological sample collection from the field and ensure that good quality samples are available fortesting.

Adequate Advance Provided by a Familiar Fluid Dynamic Balance Principle to Tools and Techniques for Water Quality Interpretation: Experienced in Yaoundé(Cameroun) 2^ndSupply Dam

In a fluid (liquid or gas) at rest, the isobars are horizontal surface. This fluid dynamic balance theorem provides adequate advance to tools and techniques for Water Quality Interpretation. We deal in this paper, with an effective way of exploiting the familiar communicating containers’ principle. That formally consists on providing water samples from desired depths of rivers, oceans, retention dams, etc. The prevailing limiting factor to achieve this feat is the length of our sampling pipes named Mbane Bathymetric Tube (MBT) designed for this purpose when rivers or retention dams are very deep. Providing drinking water to urban growing populations is a challenge that no government can escape. Therefore, improving the tools and techniques for water quality interpretation is an adequate advance for drinking water managerial techniques because this allows the recovery of contaminated water which abounds on the earth by acquiring appropriate wastewater treatment stations. The aim of the manuscript is to provide a brief theoretical description of our designed sampling equipment to allow everyone who is going to use it to solve in advance problems brought by Archimedes’ pressure force when experiencing the sampling pipes. Archimedes’ pressure force acts mainly when moving the sampling pipes to water lower levels and then opening its protective cover which allows the communication with the supply dam.

Drinking Water Quality Clinics and Outreach in Delaware Focusing on Educating Master Well Owners

The United States Environmental Protection Agency (EPA) has the authority to regulate the public water systems. The EPA does not have the jurisdiction to regulate private drinking water wells. This leaves approximately fifteen percent of the nation’s population without any regulation being held in place to protect their source of drinking water. With that fifteen percent of the US population having private wells for drinking water, it makes the number of people whose drinking water is unprotected by regulation at a little over 15 million US households. This concern is even more acute in areas with groundwater that is close to the surface. Delaware residents live in a region with low elevation which is very close to the coast with low elevation and the shallow groundwater makes us concern about contaminated well water even more intense. As one of the Water Resources Program partners, we have offered free Drinking Water Quality Clinics to local well owners over the past 4 years in Delaware State University. Since 2009, over 400 Delaware residents have benefited from these clinics. At each clinic, an information session was offered in the evening, with an opportunity to hear from and speak with a drinking water well expert. Participants were given sample bottles and water testing performed the following day included pH, nitrite, nitrate, sulfate, alkalinity, fluoride, hardness, iron, lead, cadmium, arsenic, Total Coliform, and E. coli. Over half of the samples returned out of range values for pH, while 72 returned results positive for Total Coliform and Escherichia coli bacterium. Data are examined for correlations, and improved understanding of local well owners. These tests shared with local well owners insights into what may be wrong with their water. In addition, any tests that came back outside of the normal range were reported to homeowners in writing. Mailed with the written reports were also information specific to what test results were outside of the limits, and actions to take to correct the exact problem the well owners encountered. The data reported here are examined to discuss the correlations of information, and ways that the Drinking Water Quality Clinics have improved our understanding of local wells and ownerships. In conclusion, regular testing on a yearly basis is the most effective way to ensure that public health is maintained.