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Microbial community dynamics at high organic loading rates revealed by pyrosequencing during sugar refinerywastewater treatment in a UASB reactor

Liguo Zhang, Qiaoying Ban, Jianzheng Li

Frontiers of Environmental Science & Engineering 2018, Volume 12, Issue 4, doi: 10.1007/s11783-018-1045-8

Abstract:

High strength sugar refinery wastewater was treated in a mesophilic

Keywords： Upflow anaerobic sludge blanket     Sugar refinery wastewater     Organic loading rate     Pyrosequencing     Microbial    

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Fermentative hydrogen production from beet sugar factory wastewater treatment in a continuous stirred

Gefu ZHU, Chaoxiang LIU, Jianzheng LI, Nanqi REN, Lin LIU, Xu HUANG

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 1,   Pages 143-150 doi: 10.1007/s11783-012-0456-1

Abstract: A low pH, ethanol-type fermentation process was evaluated for wastewater treatment and bio-hydrogen productionfrom acidic beet sugar factory wastewater in a continuous stirred tank reactor (CSTR) with an effective

Keywords： fermentative hydrogen production     continuous stirred tank reactor (CSTR)     specific hydrogen production rate     beet sugarfactory wastewater     ethanol-type fermentation    

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Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 10,   Pages 1516-1532 doi: 10.1007/s11705-022-2283-7

Abstract: focuses on the integrated problem of long-term planning and short-term scheduling in a large-scale refinery-petrochemicalcomplex, and considers the overall manufacturing process from the upstream refinery to the downstreamThe results do not only illustrate the detailed operations in a refinery and petrochemical complex under

Keywords： planning     scheduling     refinery-petrochemical     convolutional neural network     heuristic algorithm    

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Impact of crude distillation unit model accuracy on refinery production planning

Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC

Frontiers of Engineering Management 2018, Volume 5, Issue 2,   Pages 195-201 doi: 10.15302/J-FEM-2017052

Abstract: In this work, we examine the impact of crude distillation unit (CDU) model errors on the results of refinery-wideOur results show that significant economic benefits can be obtained using accurate CDU models in refinery

Keywords： impact of model accuracy on production planning     swing cut+ bias CDU model     hybrid CDU model     refinery feedstockselection optimization     optimization of refinery operation    

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Lessons learned from developing and implementing refinery production scheduling technologies

Marcel JOLY, Mario Y. MIYAKE

Frontiers of Engineering Management 2017, Volume 4, Issue 3,   Pages 325-337 doi: 10.15302/J-FEM-2017033

Abstract: programs entirely implemented in an energy company devoted to developing and implementing an advanced refinery

Keywords： automation     decision making     oil refinery     optimization     production scheduling    

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Greenhouse gas emissions mitigation and economic viability of sugar crops in China

Frontiers of Agricultural Science and Engineering doi: 10.15302/J-FASE-2023529

Abstract:

● Sugarcane and sugar beet yield and carbon footprint rose with time

Keywords： Economic profits     GHG emissions     labor input     nitrogen input     sugar    

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Heat Integration retrofit analysis—an oil refinery case study by Retrofit Tracing Grid Diagram

Andreja NEMET, Jiří Jaromír KLEMEŠ, Petar Sabev VARBANOV, Valter MANTELLI

Frontiers of Chemical Science and Engineering 2015, Volume 9, Issue 2,   Pages 163-182 doi: 10.1007/s11705-015-1520-8

Abstract: The application of the developed tool has been validated on an oil refinery case study.

Keywords： Heat Integration     retrofit     Pinch Analysis     thermodynamic approach     oil refinery    

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Multiple input self-organizing-map ResNet model for optimization of petroleum refinery conversion units

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 6,   Pages 759-771 doi: 10.1007/s11705-022-2269-5

Abstract: This work introduces a deep-learning network, i.e., multi-input self-organizing-map ResNet (MISR), for modeling refining units comprised of two reactors and a separation train. The model is comprised of self-organizing-map and the neural network parts. The self-organizing-map part maps the input data into multiple two-dimensional planes and sends them to the neural network part. In the neural network part, residual blocks enhance the convergence and accuracy, ensuring that the structure will not be overfitted easily. Development of the MISR model of hydrocracking unit also benefits from the utilization of prior knowledge of the importance of the input variables for predicting properties of the products. The results show that the proposed MISR structure predicts more accurately the product yields and properties than the previously introduced self-organizing-map convolutional neural network model, thus leading to more accurate optimization of the hydrocracker operation. Moreover, the MISR model has smoother error convergence than the previous model. Optimal operating conditions have been determined via multi-round-particle-swarm and differential evolution algorithms. Numerical experiments show that the MISR model is suitable for modeling nonlinear conversion units which are often encountered in refining and petrochemical plants.

Keywords： hydrocracking     convolutional neural networks     self-organizing map     deep learning     data-driven optimization    

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neural network-based production process modeling and variable importance analysis approach in corn to sugar

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 3,   Pages 358-371 doi: 10.1007/s11705-022-2190-y

Abstract: Corn to sugar process has long faced the risks of high energy consumption and thin profits.network-based production process modeling and variable importance analysis approach is proposed for corn to sugarbased on the selected most important sites to maintain high quality and stable production for corn to sugar

Keywords： big data     corn to sugar factory     neural network     variable importance analysis    

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Production of pectic extracts from sugar beet pulp with antiproliferative activity on a breast cancer

Jacqueline CONCHA, Caroline WEINSTEIN, María Elvira Zú?IGA

Frontiers of Chemical Science and Engineering 2013, Volume 7, Issue 4,   Pages 482-489 doi: 10.1007/s11705-013-1342-5

Abstract: In the last years, sugar beet pectins have been the subject of several investigations involving extractionIn this work, sugar beet pectin extraction was performed in the following steps: lipid extraction with

Keywords： pectic extracts     antiproliferative activity     breast cancer     enzymatic treatment    

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Refinery production scheduling toward Industry 4.0

Marcel JOLY, Darci ODLOAK, Mario Y. MIYAKE, Brenno C. MENEZES, Jeffrey D. KELLY

Frontiers of Engineering Management 2018, Volume 5, Issue 2,   Pages 202-213 doi: 10.15302/J-FEM-2017024

Abstract: Understanding the holistic relationship between refinery production scheduling (RPS) and the cyber-physical

Keywords： cyber-physical systems     optimization     petrochemical industry     scheduling     smart manufacturing    

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CAR T cells redirected against tumor-specific antigen glycoforms: can low-sugar antigens guarantee a

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 322-338 doi: 10.1007/s11684-021-0901-2

Abstract: Immune-based therapies have experienced a pronounced breakthrough in the past decades as they acquired multiple US Food and Drug Administration (FDA) approvals for various indications. To date, six chimeric antigen receptor T cell (CAR-T) therapies have been permitted for the treatment of certain patients with relapsed/refractory hematologic malignancies. However, several clinical trials of solid tumor CAR-T therapies were prematurely terminated, or they reported life-threatening treatment-related damages to healthy tissues. The simultaneous expression of target antigens by healthy organs and tumor cells is partly responsible for such toxicities. Alongside targeting tumor-specific antigens, targeting the aberrantly glycosylated glycoforms of tumor-associated antigens can also minimize the off-tumor effects of CAR-T therapies. Tn, T, and sialyl-Tn antigens have been reported to be involved in tumor progression and metastasis, and their expression results from the dysregulation of a series of glycosyltransferases and the endoplasmic reticulum protein chaperone, Cosmc. Moreover, these glycoforms have been associated with various types of cancers, including prostate, breast, colon, gastric, and lung cancers. Here, we discuss how underglycosylated antigens emerge and then detail the latest advances in the development of CAR-T-based immunotherapies that target some of such antigens.

Keywords： cancer immunotherapy     chimeric antigen receptor     solid tumors     tumor-associated antigen     glycosylation     O-glycans     adoptive cell therapy    

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hydrothermal carbon supporting metal oxide nanoparticles as efficient catalyst for mono-dehydration of sugar

Cheng PAN, Chao FAN, Wanqin WANG, Teng LONG, Benhua HUANG, Donghua ZHANG, Peigen SU, Aqun ZHENG, Yang SUN

Frontiers in Energy 2022, Volume 16, Issue 5,   Pages 822-839 doi: 10.1007/s11708-020-0677-0

Abstract: Most known catalytic dehydration of sugar alcohols such as D-sorbitol and D-mannitol can only produceOn the other hand, high mono-dehydration selectivity is obtained for both sugar alcohols by using allstudy provides an efficient, mild, eco-friendly, and cost-effective system for mono-dehydration of sugar

Keywords： hydrothermal carbon     morphology     catalyst     mono-dehydration     sugar alcohol    

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Electrochemical sensor investigation of carbon-supported PdCoAg multimetal catalysts using sugar-containing

Firat Salman, Hilal C. Kazici, Hilal Kivrak

Frontiers of Chemical Science and Engineering 2020, Volume 14, Issue 4,   Pages 629-638 doi: 10.1007/s11705-019-1840-1

Abstract: Novel PdCoAg/C nanostructures were successfully synthesized by the polyol method in order to develop electrocatalysts, related to the glucose sensor performance of the high glycemic index in beverages. The characterization of this novel PdCoAg/C electrocatalyst was performed by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and high-resolution transmission electron microscopy equipped with energy dispersive X-ray. The characterization results revealed that electronic state of the PdCoAg/C electrocatalyst was modified by the addition of the third metal. The electrochemical performances of the sensor were investigated by cyclic voltammetry and differential pulse voltammetry. The prepared enzyme-free sensor exhibited excellent catalytic activity against glucose with a wide detection range (0.005 to 0.35 mmol∙L ), low limit of detection (0.003 mmol∙L ), high sensitivity (4156.34 µA∙mmol ∙L∙cm ), and long-term stability (10 days) because of the synergistic effect between the ternary metals. The glucose contents of several energy drinks, fruit juices, and carbonated beverages were analyzed using the novel PdCoAg/NGCE/C sensor system. These results indicate the feasibility for applications in the foods industry.

Keywords： non-enzymatic     glucose detection     ternary metals     glycemic index     beverages    

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The Mission is Possible: Fighting Sugar and Fat for a Healthier Heart

Baofeng Yang, Rui Wang

Engineering 2023, Volume 20, Issue 1,   Pages 1-2 doi: 10.1016/j.eng.2022.10.003

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Title Author Date Type Operation

Microbial community dynamics at high organic loading rates revealed by pyrosequencing during sugar refinerywastewater treatment in a UASB reactor

Liguo Zhang, Qiaoying Ban, Jianzheng Li

Journal Article

Fermentative hydrogen production from beet sugar factory wastewater treatment in a continuous stirred

Gefu ZHU, Chaoxiang LIU, Jianzheng LI, Nanqi REN, Lin LIU, Xu HUANG

Journal Article

Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex

Journal Article

Impact of crude distillation unit model accuracy on refinery production planning

Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC

Journal Article

Lessons learned from developing and implementing refinery production scheduling technologies

Marcel JOLY, Mario Y. MIYAKE

Journal Article

Greenhouse gas emissions mitigation and economic viability of sugar crops in China

Journal Article

Heat Integration retrofit analysis—an oil refinery case study by Retrofit Tracing Grid Diagram

Andreja NEMET, Jiří Jaromír KLEMEŠ, Petar Sabev VARBANOV, Valter MANTELLI

Journal Article

Multiple input self-organizing-map ResNet model for optimization of petroleum refinery conversion units

Journal Article

neural network-based production process modeling and variable importance analysis approach in corn to sugar

Journal Article

Production of pectic extracts from sugar beet pulp with antiproliferative activity on a breast cancer

Jacqueline CONCHA, Caroline WEINSTEIN, María Elvira Zú?IGA

Journal Article

Refinery production scheduling toward Industry 4.0

Marcel JOLY, Darci ODLOAK, Mario Y. MIYAKE, Brenno C. MENEZES, Jeffrey D. KELLY

Journal Article

CAR T cells redirected against tumor-specific antigen glycoforms: can low-sugar antigens guarantee a

Journal Article

hydrothermal carbon supporting metal oxide nanoparticles as efficient catalyst for mono-dehydration of sugar

Cheng PAN, Chao FAN, Wanqin WANG, Teng LONG, Benhua HUANG, Donghua ZHANG, Peigen SU, Aqun ZHENG, Yang SUN

Journal Article

Electrochemical sensor investigation of carbon-supported PdCoAg multimetal catalysts using sugar-containing

Firat Salman, Hilal C. Kazici, Hilal Kivrak

Journal Article

The Mission is Possible: Fighting Sugar and Fat for a Healthier Heart

Baofeng Yang, Rui Wang

Journal Article