Coagulation for treatment of swine slaughterhouse wastewater

In this study, wastewater taken from the Nam Phong swine slaughterhouse, Ho Chi Minh City, was used to evaluate the treatment efficiency of common coagulants, including Alum (Aluminum Sulfate - Al2(SO4)3.18H2O), Poly-Aluminum Chloride (PAC), and Ferrous Sulfate (FeSO4.7H2O), using a jar-test system. The experiments were conducted using the one-factor-at-a-time method to examine three variables which are pH, stirring speed, and coagulant dosage. The results showed that both Alum and PAC perform over 90% removal of colour, turbidity, COD, and total phosphorus (TP) from slaughterhouse wastewater at pH 7 with a stirring speed of 75 revolutions per minute (RPM) and average coagulant dosages of 450 mg/L for Alum and 550 mg/L for PAC. Meanwhile, under the appropriate conditions of pH equal to 10 and 75 RPM with a chemical dosage of 350 mg/L, COD and TP removal efficiencies by Ferrous Sulfate exceed 87%, but those of turbidity and colour only reach 25%. This finding could be a promising coagulation method as a pre-treatment for the swine slaughterhouse wastewater

Removal of inorganic nutrient and organic carbon from wastewater of Binh Dien market using the green alga Chlorella sp.

Traditional markets play a major role in socio-economics and constitutes a significant aspect of Vietnamese culture. However, wastewater streams discharged from the markets are generally characterized by a lot of inorganic nutrients and organic substances originated from fresh food processing units. They could lead to serious water contamination if discharged without proper treatment. This study applied microalgae Chlorella sp. for eliminating inorganic nutrients (NO3--N, NH4+-N and PO43--P) and organic carbon (Chemical oxygen demand-COD) from wastewater of the Binh Dien market. The removal efficiencies reached for NH4+-N > 86%, for NO3--N > 72%, and for PO43--P > 69%, respectively, at algal density of 49 x 104 cell mL-1, and for COD > 96% at algal density of 35 x 104 cell mL-1 after five cultivating days. The effluence satisfied the Vietnamese standard, column B, of the National technical regulation on industrial wastewater (QCVN 40:2011/BTNMT). The results demonstrated that the culture system composed of green algal Chlorella sp. could be a potential candidate for the removal of nutrients and organic carbon by a wastewater treatment process from the Binh Dien market

Reweighted nuclear norm regularization: A SPARSEVA approach

The aim of this paper is to develop a method to estimate high order FIR and ARX models using least squares with re-weighted nuclear norm regularization. Typically, the choice of the tuning parameter in the reweighting scheme is computationally expensive, hence we propose the use of the SPARSEVA (SPARSe Estimation based on a VAlidation criterion) framework to overcome this problem. Furthermore, we suggest the use of the prediction error criterion (PEC) to select the tuning parameter in the SPARSEVA algorithm. Numerical examples demonstrate the veracity of this method which has close ties with the traditional technique of cross validation, but using much less computations.Comment: This paper is accepted and will be published in The Proceedings of the 17th IFAC Symposium on System Identification (SYSID 2015), Beijing, China, 201

Big Picard theorem for meromorphic mappings with moving hyperplanes in Pn(C)

We present some extension theorems in the style of the Big Picard theorem for meromorphic mappings of Cm into Pn(C) with a few moving hyperplanes.Наведено дєякі теореми про продовження в стилі великої теореми Шкара для мероморфних відображень Cm в Pn(C) з деякими рухомими гіперплощинами

Uncertainty-Aware Performance Prediction for Highly Configurable Software Systems via Bayesian Neural Networks

Configurable software systems are employed in many important application domains. Understanding the performance of the systems under all configurations is critical to prevent potential performance issues caused by misconfiguration. However, as the number of configurations can be prohibitively large, it is not possible to measure the system performance under all configurations. Thus, a common approach is to build a prediction model from a limited measurement data to predict the performance of all configurations as scalar values. However, it has been pointed out that there are different sources of uncertainty coming from the data collection or the modeling process, which can make the scalar predictions not certainly accurate. To address this problem, we propose a Bayesian deep learning based method, namely BDLPerf, that can incorporate uncertainty into the prediction model. BDLPerf can provide both scalar predictions for configurations' performance and the corresponding confidence intervals of these scalar predictions. We also develop a novel uncertainty calibration technique to ensure the reliability of the confidence intervals generated by a Bayesian prediction model. Finally, we suggest an efficient hyperparameter tuning technique so as to train the prediction model within a reasonable amount of time whilst achieving high accuracy. Our experimental results on 10 real-world systems show that BDLPerf achieves higher accuracy than existing approaches, in both scalar performance prediction and confidence interval estimation

Vietnam research situation analysis on orphans and other vulnerable children

This item is archived in the repository for materials published for the USAID supported Orphans and Vulnerable Children Comprehensive Action Research Project (OVC-CARE) at the Boston University Center for Global Health and Development.Addressing the needs of orphans and vulnerable children (OVC) and mitigating negative outcomes of the growing OVC population worldwide is a high priority for national governments and international stakeholders across the globe who recognize this as an issue with social, economic, and human rights dimensions. Assembling the relevant available data on OVC in one place, and acknowledging the gaps that still exist in our knowledge, will assist policy makers and program implementers to make evidence-based decisions about how best to direct funding and program activities and maximize positive outcomes for children and their caretakers. This Research Situation Analysis, Vietnam Country Brief presents a program-focused summary of available information on: • The number of orphans and vulnerable children in Vietnam. • Current policies, programs and interventions designed and implemented to assist them. • Gaps in these policies, programs and interventions. • OVC research conducted between 2004 -2008. • Gaps in the OVC evidence base. The Brief analyzes the available data for critical gaps in the national response and our understanding about whether current interventions are fulfilling the needs and improving the lives of vulnerable children. The report then recommends actions required to increase the knowledge base for improving the effectiveness and impact of OVC programs.The USAID | Project SEARCH, Orphans and Vulnerable Children Comprehensive Action Research (OVC-CARE) Task Order, is funded by the U.S. Agency for International Development under Contract No. GHH-I-00-07-00023-00, beginning August 1, 2008. OVC-CARE Task Order is implemented by Boston University. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the funding agency

Application of the Fenton-like agent based on magnetic iron and manganese oxide in the degradation process of paracetamol in water

A Fenton-like catalyst MnO2-Fe3O4/SiO2 is synthesized via a two-step approach. The prepared composite has a mesoporous structure and a high surface area of 190 m2/g. The XRD pattern describes a specific peak of Fe3O4 magnetite on the baseline of amorphous silica. Furthermore, the FTIR spectra not only show the height assigned to stretching vibrations of Si-O-Si bonds, and Fe–O–Fe connections but also exhibit a small peak that matches the Mn–O bonds. SEM images exhibit a porous network structure of the composites with some holes among 30 – 100 nm clusters. The activity of the catalyst is determined in a paracetamol degradation as a Fenton oxidation. The paracetamol removal efficiency is at 85.6% with the optimal condition as initial pH 3, catalyst dosage of 0.15 g/50mL and H2O2 concentration of 1 mL/50 mL. In addition, the catalyst can be reused at least 5 times with a low reduction of the catalytic activity from 85.6% to 80.8%. The experiment results open a direction that has high efficiency in the treatment process of excess paracetamol in pharmacy wastewater

DEVELOPMENT AND APPLICATION OF THE ENVIRONMENTAL HYDRODYNAMIC 3D MODEL FOR COMPUTATION AND FORECASTING OF OIL POLLUTIONS IN COASTAL MARINE ENVIRONMENT

Joint Research on Environmental Science and Technology for the Eart