Multi-period Project Portfolio Selection under Risk considerations and Stochastic Income

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, considering risks, stochastic incomes, and possibility of investing extra budget in each time period. Due to the complexity of the problem, an effective meta-heuristic method hybridized with a local search procedure is presented to solve the problem. The algorithm is based on genetic algorithm (GA), which is a prominent method to solve this type of problems. The GA is enhanced by a new solution representation and well selected operators. It also is hybridized with a local search mechanism to gain better solution in shorter time. The performance of the proposed algorithm is then compared with well-known algorithms, like basic genetic algorithm (GA), particle swarm optimization (PSO), and electromagnetism-like algorithm (EM-like) by means of some prominent indicators. The computation results show the superiority of the proposed algorithm in terms of accuracy, robustness and computation time. At last, the proposed algorithm is wisely combined with PSO to improve the computing time considerably

A Fuzzy Expert System for Supporting Returned Products Strategies

A key strategic consideration in the recovery system of any product is to make proper decisions on reverse manufacturingalternatives including both recovery and disposal options. The nature of such decisions is complex due to the uncertaintyexisting in the quality of the product returns and lack of information about the product. Consequently, the need of correct diagnosis of recovery/ disposal options for the returned products necessitates the development of a comprehensive model considering all technical and non-technical parameters. Although human experts with the aid of practical experience may handle such complex problems, this procedure is time consuming and may lead to imprecise decisions. This study presents a fuzzy rule-based system to provide a correct decision mechanism for ranking the recovery/disposal strategies byknowledge acquisition through a simple reverse supply chain with a collection center for each particular returned product.The proposed system has applications with a focus on brown goods, although the system may be applied to other similarkinds of products through some changes. To achieve the objective of this study, the proposed model is used to analyze acase of mobile phone, ending up in coherent results

A Critical Review of Short-Term Water Demand Forecasting Tools—What Method Should I Use?

The challenge for city authorities goes beyond managing growing cities, since as cities develop, their exposure to climate change effects also increases. In this scenario, urban water supply is under unprecedented pressure, and the sustainable management of the water demand, in terms of practices including economic, social, environmental, production, and other fields, is becoming a must for utility managers and policy makers. To help tackle these challenges, this paper presents a well-timed review of predictive methods for short-term water demand. For this purpose, over 100 articles were selected from the articles published in water demand forecasting from 2010 to 2021 and classified upon the methods they use. In principle, the results show that traditional time series methods and artificial neural networks are among the most widely used methods in the literature, used in 25% and 20% of the articles in this review. However, the ultimate goal of the current work goes further, providing a comprehensive guideline for engineers and practitioners on selecting a forecasting method to use among the plethora of available options. The overall document results in an innovative reference tool, ready to support demand-informed decision making for disruptive technologies such as those coming from the Internet of Things and cyber–physical systems, as well as from the use of digital twin models of water infrastructure. On top of this, this paper includes a thorough review of how sustainable management objectives have evolved in a new era of technological developments, transforming data acquisition and treatment.</jats:p

The effect of the venom of the yellow Iranian scorpion Odontobuthus doriae on skeletal muscle preparations in vitro

The yellow Iranian scorpion Odontobuthus doriae can cause fatal envenoming, but its mechanism of action is unclear. One of the reported manifestations of envenoming is moderate to severe involuntary tremor of skeletal muscle. In order to understand better the mechanism of action of this venom on skeletal muscle function, we examined the effects of the venom in vitro on chick biventer cervicis (CBC) and mouse hemidiaphragm (MHD) nerve muscle preparations. O. doriae venom (0.3-10mug/ml) initially increased and then decreased twitch height. The venom also caused contracture in both preparations. In mouse triangularis sterni preparations, used for all intracellular recording techniques, the venom enhanced the release of acetylcholine and induced repetitive firing of nerve action potentials and endplate potentials in response to single-shock stimulation. With extracellular recording techniques, scorpion venom (1mug/ml) was found to cause changes to the perineural waveform associated with nerve terminal action potentials consistent with effects on Na(+) and K(+) currents. The main facilitatory effects of O. doriae venom are likely to be due to toxins that affect Na(+) channels in nerve-muscle preparations similar to most Old World scorpion venoms, but blocking effects on K(+) channels are also possible. Such effects could lead to initial enhancement of transmitter release that could underlie the muscle tremors seen in victims. Toxins acting on Na(+) and K+ currents have been isolated from the venom [Jalali, A., Bosmans, F., Amininasab, M., Clynen, E., Cuypers, E., Zaremirakabadi, A., Sarbolouki, M.N., Schoofs, L., Vatanpour, H., Tytgat, J., 2005. OD1, the first toxin isolated from the venom of the scorpion Odontobuthus doriae active on voltage-gated Na(+) channels. FEBS Lett. 579, 4181-4186; Abdel-Mottaleb, Y., Clynen, E., Jalali, A., Bosmans, F., Vatanpour, H., Schoofs, L., Tytgat, J., 2006. The first potassium channel toxin from the venom of the Iranian scorpion Odontobuthus doriae. FEBS Lett. 580, 6254-6258]; however, the muscle paralysis seen at higher concentrations of venom may be due to additional, as yet uncharacterised, components of the venom

Lewis Acid Coordination Redirects S-Nitrosothiol Reduction

S-Nitrosothiols (RSNOs) serve as air-stable reservoirs for nitric oxide in biology and are responsible for a myriad of physiological responses. While copper enzymes promote NO release from RSNOs by serving as Lewis acids capable of intramolecular electron-transfer, redox innocent Lewis acids separate these two functions to reveal the effect of coordination on structure and reactivity. The synthetic Lewis acid B(C6F5)3 coordinates to the RSNO oxygen atom in adducts RSNO-B(C6F5)3, leading to profound changes in the RSNO electronic structure and reactivity. Although RSNOs possess relatively negative reduction potentials (-1.0 to -1.1 vs. NHE), B(C6F5)3 coordination increases their reduction potential by over 1 V into the physiologically accessible +0.1 V vs. NHE. Outer-sphere chemical reduction results in formation of the Lewis acid stabilized hyponitrite dianion trans-[LA–O–N=N–O–LA]2– (LA = B(C6F5)3) that releases N2O upon acidification. Mechanistic and computational studies support initial reduction to the [RSNO-B(C6F5)3]•/- radical-anion susceptible to N-N coupling prior to loss of RSSR

Lewis Acid-Assisted Reduction of Nitrite to Nitric and Nitrous Oxide via the Elusive Nitrite Radical Dianion

Reduction of nitrite anions [NO2]- takes place in a myriad of environments such as in the soil as part of the biogeochemical nitrogen cycle as well as in acidified nuclear waste. Nitrite reduction typically takes place within the coordination sphere of a redox active transition metal. Lewis acid coordination, however, can dramatically modify the reduction potential of this polyoxoanion to allow for reduction under non-aqueous conditions (-0.74 V vs. NHE). This strategy enables the isolation of a borane-capped nitrite dianion [NO2]2- along with its spectroscopic study consistent with reduction to the N(II) oxidation state. Protonation of the nitrite dianion results in facile loss of nitric oxide (NO) while reaction of the nitrite dianion with nitric oxide results in disproportionation to nitrous oxide (N2O) and nitrite, connecting three redox levels in the global nitrogen cycle

Current methods for synthesis of magnetic nanoparticles

The synthesis of different kinds of magnetic nanoparticles (MNPs) has attracted much attention. During the last few years, a large portion of the articles published about MNPs have described efficient routes to attain shape-controlled and highly stable MNPs with narrow size distribution. In this review, we have reported several popular methods including co-precipitation, microemulsion, thermal decomposition, solvothermal, sonochemical, microwave-assisted, chemical vapor deposition, combustion, carbon arc, and laser pyrolysis, for the synthesis of magnetic nanoparticles