Environmental concerns and soaring energy prices have brought huge pressure of energy saving and emission reduction to tissue paper mills. Electricity is one of the main energy sources of tissue paper mills. The production characteristics of tissue paper mills make it easy to decrease energy cost by using time-of-use (TOU) electricity tariffs. This study investigates the bi-objective energy-efficiency scheduling of tissue paper mills under time-of-use electricity tariffs, the objectives of which are makespan and energy cost. First, considering the processing energy cost, setup energy cost, and transportation energy cost, an energy cost model of a tissue paper mill under TOU electricity tariffs is established. Second, the energy-efficiency scheduling model under TOU electricity tariffs is built based on the energy cost model. Finally, on the basis of decomposition and teaching−learning optimization, this study proposes a novel multi-objective evolutionary algorithm and further combined... [more]

Emerging evidence highlights the relevance of extracellular vesicles (EVs) in modulating human diseases including but not limited to cancer, inflammation, and neurological disorders. EVs can be found in almost all types of human body fluids, suggesting that their trafficking may allow for their targeting to remote recipient cells. While molecular processes underlying EV biogenesis and secretion are increasingly elucidated, mechanisms governing EV transportation, target finding and binding, as well as uptake into recipient cells remain to be characterized. Understanding the specificity of EV transport and uptake is critical to facilitating the development of EVs as valuable diagnostics and therapeutics. In this mini review, we focus on EV uptake mechanisms and specificities, as well as their implications in human diseases.

Poor lubrication performance of low-sulfur fuel leads to increased wear of diesel engine components. In order to improve the lubrication properties of low-sulfur fuel, we successfully prepared graphene lubricant additives by dielectric barrier discharge plasma-assisted ball milling. The tribological properties of graphene lubricant additives in two types of 0# diesel oils with different sulfur content were evaluated by high-frequency reciprocating rig (HFRR). The results indicated that the expanded graphite was exfoliated and refined into graphene sheets with nine layers by the synergistic effect of the heat explosive effect of the discharge plasma, the impact of mechanical milling function, and the cavitation effect of 0# diesel oil. The organic functional groups of 0# diesel oil were successfully grafted on the surface of graphene sheets. The addition of 0.03 wt % graphene resulted in 20% reduction in the friction coefficient (COF) and 28% reduction in wear scar diameter (WSD) compar... [more]

Classical enzyme kinetic theories are summarized and linked with modern discoveries here. The sequential catalytic events along time axis by enzyme are analyzed at the molecular level, and by using master equations, this writing tries to connect the microscopic molecular behavior of enzyme to kinetic data (like velocity and catalytic coefficient k) obtained in experiment: 1/k = t equals to the sum of the times taken by the constituent individual steps. The relationships between catalytic coefficient k, catalytic rate or velocity, the amount of time taken by each step and physical or biochemical conditions of the system are discussed, and the perspective and hypothetic equations proposed here regarding diffusion, conformational change, chemical conversion, product release steps and the whole catalytic cycle provide an interpretation of previous experimental observations and can be testified by future experiments.

Process measurements are contaminated by random and/or gross measuring errors, which degenerates performances of data-based strategies for enhancing process performances, such as online optimization and advanced control. Many approaches have been proposed to reduce the influence of measuring errors, among which expectation maximization (EM) is a novel and parameter-free one proposed recently. In this study, we studied the EM approach in detail and argued that the original EM approach is not feasible to rectify measurements contaminated by persistent biases, which is a pitfall of the original EM approach. So, we propose a modified EM approach here to circumvent this pitfall by fixing the standard deviation of random error mode. The modified EM approach was evaluated by several benchmark cases of process data rectification from literatures. The results show advantages of the proposed approach to the original EM in solving efficiency and performance of data rectification.

In the search for improvement in the properties of gadolinium-based contrast agents, cyclodextrins (CDs) are interesting hydrophilic scaffolds with high molecular weight. The impact of the hydrophilicity of these systems on the MRI efficacy has been studied using five β-CDs substituted with DOTA or TTHA ligands which, respectively, allow for one (q = 1) or no water molecule (q = 0) in the inner coordination sphere of the Gd3+ ion. Original synthetic pathways were developed to immobilize the ligands at C-6 position of various hydroxylated and permethylated β-CDs via an amide bond. To describe the influence of alcohol and ether oxide functions of the CD macrocycle on the relaxation properties of the Gd3+ complexes, 1H Nuclear Magnetic Relaxation Dispersion (NMRD) profiles, and 17O transverse relaxation rates have been measured at various temperatures. The differences observed between the hydroxylated and permethylated β-CDs bearing non-hydrated GdTTHA complexes can be rationalized by a s... [more]

In this work, a study was carried out to compare the filtering and hydrodynamic properties of granular filters with solid spherical granules and spherical granules with modifications in the form of micropores. We used the discrete element method (DEM) to construct the geometry of the filters. Models of granular filters with spherical granules with diameters of 3, 4, and 5 mm, and with porosity values of 0.439, 0.466, and 0.477, respectively, were created. The results of the numerical simulation are in good agreement with the experimental data of other authors. We created models of granular filters containing micropores with different porosity values (0.158−0.366) in order to study the micropores’ effect on the aerosol motion. The study showed that micropores contribute to a decrease in hydrodynamic resistance and an increase in particle deposition efficiency. There is also a maximum limiting value of the granule microporosity for a given aerosol particle diameter when a further increas... [more]

Tableting by direct compression (DC) is one of the simplest and most cost-effective drug manufacturing approaches. However, most active pharmaceutical ingredients (APIs) and excipients lack the compression and flow properties required to meet the needs of high-speed industrial tablet presses. Therefore, the majority of DC APIs and excipients are modified via processing/co-processing particle engineering techniques to boost their properties. Spray drying is one of the most commonly employed techniques to prepare DC grades of APIs and excipients with prominent advantages. This review aims to present an overview of the commercially marketed and investigationally-prepared DC APIs and excipients produced by spray drying.

Discharge water from fish farms is a clean, renewable, and abundant energy source that has been used to obtain renewable energy via small hydropower plants. Small hydropower plants may be installed at offshore fish farms where suitable water is obtained throughout the year. It is necessary to meet the challenges of developing small hydropower systems, including sustainability and turbine efficiency. The main objective of this study was to investigate the possibility of constructing a small hydropower plant and develop 100 kW class propeller-type turbines in a fish farm with a permanent magnet synchronous generator (PMSG). The turbine was optimized using a computer simulation, and an experiment was conducted to obtain performance data. Simulation results were then validated with experimental results. Results revealed that streamlining the designed shape of the guide vane reduced the flow separation and improved the efficiency of the turbine. Optimizing the shape of the runner vane decre... [more]

Proton transfer reactions are one of the most fundamental processes in biochemistry. We present a simplistic approach for estimating proton transfer probabilities in a membrane protein, cytochrome c oxidase. We combine short molecular dynamics simulations at discrete protonation states with a Monte Carlo approach to exchange between those states. Requesting for a proton transfer the existence of a hydrogen-bonded connection between the two source and target residues of the exchange, restricts the acceptance of transfers to only those in which a proton-relay is possible. Together with an analysis of the hydrogen-bonded connectivity in one of the proton-conducting channels of cytochrome c oxidase, this approach gives insight into the protonation dynamics of the hydrogen-bonded networks. The connectivity and directionality of the networks are coupled to the conformation of an important protein residue in the channel, K362, rendering proton transfer in the entire channel feasible in only o... [more]

Clinical trials of single drugs intended to slow the progression of Alzheimer’s Disease (AD) have been notoriously unsuccessful. Combinations of repurposed drugs could provide effective treatments for AD. The challenge is to identify potentially effective combinations. To meet this challenge, machine learning (ML) was used to extract the knowledge from two leading AD databases, and then “the machine” predicted which combinations of the drugs in common between the two databases would be the most effective as treatments for AD. Specifically, three-layered artificial neural networks (ANNs) with compound, gated units in their internal layer were trained using ML to predict the cognitive scores of participants, separately in either database, given other data fields including age, demographic variables, comorbidities, and drugs taken. The predictions from the separately trained ANNs were statistically highly significantly correlated. The best drug combinations, jointly determined from both s... [more]

In this work, highly crystalline CdS nanorods (NRs) were successfully synthesized by a facile, one-step solvothermal method. The as-prepared CdS NRs powder was characterized by XRD, FESEM, Raman, PL, XPS, BET, and UV-visible techniques to evaluate the structural, morphological, and optical properties. The photocatalytic performance of the as-synthesized CdS NRs was investigated for the photodegradation of RhB dye under visible light irradiations. It has been found that CdS NRs show maximum RhB degradation efficiency of 88.4% in 120 min. The excellent photodegradation ability of the CdS NRs can be attributed to their rod-like structure together with their large surface area and surface state. The kinetic study indicated that the photodegradation process was best described by the pseudo-first-order kinetic model. The possible mechanism for the photodegradation of RhB dye over CdS NRs was proposed in this paper.

Thermal desalination is yet a reliable technology in the treatment of brackish water and seawater; however, its demanding high energy requirements have lagged it compared to other non-thermal technologies such as reverse osmosis. This review provides an outline of the development and trends of the three most commercially used thermal or phase change technologies worldwide: Multi Effect Distillation (MED), Multi Stage Flash (MSF), and Vapor Compression Distillation (VCD). First, state of water stress suffered by regions with little fresh water availability and existing desalination technologies that could become an alternative solution are shown. The most recent studies published for each commercial thermal technology are presented, focusing on optimizing the desalination process, improving efficiencies, and reducing energy demands. Then, an overview of the use of renewable energy and its potential for integration into both commercial and non-commercial desalination systems is shown. Fi... [more]

Due to the substantial usage of fossil fuels, the utilization of lignocellulosic biomass as renewable sources for fuels and chemical production has been widely explored. The dissolution of lignocellulosic biomass in proper solvents is vital prior to the extraction of its important constituents, and ionic liquids (ILs) have been found to be efficient solvents for biomass dissolution. However, the high viscosity of ILs limits the dissolution process. Therefore, with the aim to enhance the dissolution of lignocellulosic biomass, a series of new ether-functionalized ILs with low viscosity values were synthesized and characterized. Their properties, such as density, viscosity and thermal stability, were analyzed and discussed in comparison with a common commercial IL, namely 1-butyl-3-methylimidazolium chloride (BMIMCl). The presence of the ether group in the new ILs reduces the viscosity of the ILs to some appreciable extent in comparison to BMIMCl. 1-2(methoxyethyl)-3-methylimidazolium ch... [more]

When considering the interaction between the impeller and diffuser, it is necessary to provide logical and systematic guidance for their matching optimization. In this study, the goal was to develop a comprehensive matching optimization strategy to optimize the impeller and diffuser of a mixed flow pump. Some useful tools and methods, such as the inverse design method, computational fluid dynamics (CFD), design of experiment, surrogate model, and optimization algorithm, were used. The matching optimization process was divided into two steps. In the first step, only the impeller was optimized. Thereafter, CFD analysis was performed on the optimized impeller to get the circulation and flow field distribution at the outlet of the impeller. In the second step of optimization, the flow field and circulation distribution at the inlet of the diffuser were set to be the same as the optimized impeller outlet. The results show that the matching optimization strategy proposed in this study is eff... [more]

In order to reduce pollutants of the emission from diesel vehicles, complex after-treatment technologies have been proposed, which make the fault detection of diesel engines become increasingly difficult. Thus, this paper proposes a canonical correlation analysis detection method based on fault-relevant variables selected by an elitist genetic algorithm to realize high-dimensional data-driven faults detection of diesel engines. The method proposed establishes a fault detection model by the actual operation data to overcome the limitations of the traditional methods, merely based on benchmark. Moreover, the canonical correlation analysis is used to extract the strong correlation between variables, which constructs the residual vector to realize the fault detection of the diesel engine air and after-treatment system. In particular, the elitist genetic algorithm is used to optimize the fault-relevant variables to reduce detection redundancy, eliminate additional noise interference, and im... [more]

Hydrogen is increasingly considered as an environmentally friendly energy source as it stores a large amount of chemical energy per unit mass (142 MJ·kg−1) that can be released without the emission of combustion by-products. The presented research is based on simulation modeling of biohydrogen production projects from agricultural waste. Based on the probability theory and mathematical statistics, the models of the variable market value of biohydrogen and natural gas are substantiated. The results of the research indicate that in 2019, projects regarding the production of biohydrogen from agricultural raw materials were mostly unprofitable for the investors. However, starting in 2030, the forecasted return on investment in biohydrogen production projects from agricultural raw materials indicates that such projects will be profitable for investors, and the number and scale of such projects will significantly increase worldwide.

Generally, energy management in smart buildings is formulated by mixed-integer linear programming, with different optimization goals. The most targeted goals are the minimization of the electricity consumption cost, the electricity consumption value from external power grid, and peak load smoothing. All of these objectives are desirable in a smart building, however, in most of the related works, just one of these mentioned goals is considered and investigated. In this work, authors aim to consider two goals via a multi-objective framework. In this regard, a multi-objective mixed-binary linear programming is presented to minimize the total energy consumption cost and peak load in collective residential buildings, considering the scheduling of the charging/discharging process for electric vehicles and battery energy storage system. Then, the Pascoletti-Serafini scalarization approach is used to obtain the Pareto front solutions of the presented multi-objective model. In the final, the pe... [more]

The present article discusses the potential for hydrogen separation using a metal hydride separator, which facilitates the generation of hydrogen contained in syngas following the thermal recovery of wastes. The article provides a detailed description of the separator heat balance using analytical calculations and optimised calculations, and by applying numerical methods. The proposed concept of a separator intended for hydrogen separation from syngas offers a solution to a problem associated with the use of metal hydride alloy powders; in particular, their low thermal conductivity. In order to eliminate big temperature differences in the alloy, a heat transfer intensifier was implemented in the metal hydride alloy volume; the intensifier was made of metal and exhibited high thermal conductivity. For the purpose of comparing the thermal fields, the first stage comprised the creation of a numerical simulation of hydrogen absorption without the use of an intensifier. Subsequently, three... [more]

Experiments were conducted simulating hydrothermal conversion of heavy oil in the presence of carbonate, kaolin, Al2O3, Ni2+ and Cu2+, NiO mixed with poly-α-olefins, C6H8O7, C2H4O2 at 290−375 °C and 10−135 bar. Al2O3, carbonate at 375 °C and 135 bar, accelerated the resin degradation. Experiments with carbonate at 350 °C and 10 bar showed no significant composition changes. NiSO4, CuSO4, kaolin mineral, at 350 °C and 78 bar, accelerated decomposition of resins (from 35.6% to 32.5%). Al2O3 and carbonate at 290 °C and 14 bar led to the destruction of asphaltenes (from 6.5% to 4.7% by weight), which were adsorbed on the surface of carbonate. Al2O3, NiO, poly-α-olefins at 350 °C and 78 bar accelerated C−C bond cracking of high-boiling asphaltenes. C6H8O7, rock-forming carbonate, at 360 °C and 14 bar, contributed to the polymerization and polycondensation of hydrocarbons with the formation of additional resins. C2H4O2 and kaolin at 360 °C and 12 bar affected the reduction in the resin conte... [more]

This paper reviews the most recent information about the main operations to produce energy from carbonaceous materials, namely biomass and wastes through the integration of gasification, syngas cleaning and solid oxide fuel cells (SOFCs), which have shown to be a good option for combined heat and power (CHP) production, due to high efficiency and low environmental impact. However, some challenges still need to be overcome, mainly when mixed feedstocks with high contents of hazardous contaminants are used, thus syngas cleaning and conditioning is of major importance. Another drawback is SOFC operation, hence new materials especially for the anode has been proposed and tested. An overall process to produce CHP by gasification integration with SOFC is proposed.

Adopting smart technologies for supply chain management leads to higher profits. The manufacturer and retailer are two supply chain players, where the retailer is unreliable and may not send accurate demand information to the manufacturer. As an advanced smart technology, Radio Frequency Identification (RFID) is implemented to track and trace each product’s movement on a real-time basis in the inventory. It takes this supply chain to a smart supply chain management. This research proposes a Machine Learning (ML) approach for on-demand forecasting under smart supply chain management. Using Long-Short-Term Memory (LSTM), the demand is forecasted to obtain the exact demand information to reduce the overstock or understock situation. A measurement for the environmental effect is also incorporated with the model. A consignment policy is applied where the manufacturer controls the inventory, and the retailer gets a fixed fee along with a commission for selling each product. The manufacturer... [more]

The aim of the present study was to synthesize various samples of activated carbon (AC) from different agricultural sources as precursors, like orange peels, tea stalks, and kiwi peels, as well as sucrose. The synthesis of AC was achieved with chemical activation using H3PO4 and KOH. The produced AC samples were tested as adsorbents for the removal of a pharmaceutical model compound, pramipexole dihydrochloride (PRM), from synthetic aqueous synthetic solutions. The produced-from-sucrose AC presented the higher yield of synthesis (~58%). The physicochemical features of the materials were analyzed by FTIR spectroscopy, N2 physisorption, and SEM imaging. More specifically, the AC sample derived from sucrose (SG-AC) had the highest specific surface area (1977 m2/g) with the total pores volume, mesopores volume, and external surface area being 1.382 cm3/g, 0.819 cm3/g, and 751 m2/g, respectively. The effect of the initial pH and PRM concentration were studied, while the equilibrium results... [more]

The mechanical-biological waste treatment plants (MBTP), which include the municipal waste biogas plants, have an important role in sustainable urban development. Some plants are equipped with a sewage pre-treatment plant, which is then directed to the sewerage system and the treatment plant. Others, on the other hand, have only a non-drainage tank. The parameters of technological sewage (TS) or processing technology could reduce sewage contamination rates. In addition to the quality of sewage from waste treatment plants, the emission of odours is also an important problem, as evidenced by the results obtained over the sewage pumping station tank. The conducted statistical analysis shows a significant positive correlation between odour concentration (cod) and volatile organic compounds (VOCs). Analysing the individual compounds, a high positive correlation was also found—the strongest being between H2S, NH3 and VOCs. In the case of sewage compounds, the insignificant correlation betwee... [more]

Whole wheat flour possesses many nutritional properties because of its abundant bioactive components which are affected by cultivar, but little attention is paid to its relationship with storage conditions. In this study, phenolic extracts of whole wheat flour from four cultivars stored under different conditions (aerated and under vacuum) and different times (0, 2, 4, 8 weeks) were obtained. The total polyphenol (TPC) and flavonoid (TFC) contents, composition of phenolic acids, and antioxidant activities (AA) of phenolic extracts were evaluated. The results showed that Verna exhibited the highest levels of TPC, TFC, and AA for both storage conditions among the four cultivars. Moisture content, TFC, and AA fluctuated during storage. After 8 weeks, the TPC, TFC, and AA decreased with respect to Week 0 in all the cultivars. The TPC losses ranged between 16.39% and 20.88% and TFC losses from 14.08% to 31.18%. The AA losses were approximately 30% from the DPPH assay, but no significant los... [more]