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Background: The potato plant tuber is typically used at a rate of half million tons per year. However, its significant biomass in the form of leaf and stem of the plant is mainly unused. Different components of potato plant contain relatively high amount of toxic glycoalkaloids which limit the use of this biomass for various usages such as animal feed. These lignocellulosic wastes, 1 to 4 times the edible glands of the plant, can be utilized for production of biological butanol as an advanced biofuel, along with acetone and ethanol. Methods: In this study, extraction of acetone, ethanol, and methanol was used for reduction of glycoalkaloid content of biomass. The grinded leaves and stems were subjected to extraction of glycoalkaloids by solvent using Soxhlet, and then, before and after extraction of glycoalkaloids, were subjected to fermentation by Clostridium acetobutylicum. In addition, prior to fermentation, two stages of inhibitor removal and dilute acid pretreatment (1 wt%) at 180º C were performed for 1 hour to improve the yield of biological acetone, butanol, and ethanol (ABE) production. Findings: Leave and stem biomass of potato plant contained 74 and 48 mg/g glycoalkaloids, respectively. Butanol production was completely stopped in presence of higher than 0.07 mg/l glycoalkaloid in the fermentation media. After removing the inhibitors by solvents, fermentation led to the production of 3.2 and 3.8 g/l biological ABE from leaves and stems of potato plant, respectively. The amount of ABE production from leaves and stems after inhibitor removal increased by a factor of 4.7 and 2.4, respectively. Use of two consecutive stages of inhibitor removal and dilute acid pretreatment led to 14- and 4.7-fold higher ABE production from leaves and stems, respectively. Conclusion: Low glycoalkaloid content as a toxic substance can lead to complete disruption of the fermentation process. In addition, this substance can be removed using solvents and this renewable source can be used as one of the highly-produced wastes in the agricultural sector and as an important and inexpensive raw material for biofuel production.

Abstract The conversion of ballasted railway tracks into slab tracks using the preplaced aggregate concrete (PAC) technology over the bridges and in the tunnels has been introduced by many researchers but the flexural behavior of this composite system has not yet been studied. Therefore, in the first stage, a series of mortar and concrete mixture designs were proposed and evaluated. Subsequently, a concrete beam mold with dimensions of 3 * 0.6 * 0.5 m, which represented the track conditions, was developed and the bending behavior of the constructed beams in both conditions of the presence and absence of the concert B70 sleeper were investigated. The maximum bending force in the middle of the concrete beam without a sleeper (SE) equaled 177.5 kN. In addition, the average values of bending tolerance by the sleeper including a PAC beam for three specimens in the four modes of the positive moment of midspan (SPM), negative moment of midspan (SNM), positive moment of rail seat (SPR), and negative moment of rail seat (SNR) were 55.25 kN m, 32.5 kN m, 91.84 kN m, and 38.21 kN m, respectively, which met the requirements of the AREMA regulations.

Continuous monitoring and proper diagnosis of production systems are daily concerns that involve many manufacturers. In this context, this paper proposes a feasible and effective diagnostic methodology. It is based on a recurrent dynamic neural model application, in industrial anomaly detection, with a high identification rate. The general context of this approach is summarized in the improvement of the detection and control mechanisms using intelligent systems. These tools can collaborate objectively in industrial processes diagnosis, then in anomalies detection and classification to intervene correctly. The final purpose of this paper consists in guaranteeing the operational safety for processes, ensuring their reliability and affirming the production continuity

This paper presents a novel approach, i.e. a combination of gamma test and monitoring priority map, for optimal design of groundwater monitoring network (GMN) by considering the cumulative effects of industries, human activities, and natural factors on the groundwater quality. The proposed method was successfully applied to design an optimal network for groundwater salinity monitoring on Kish Island, Persian Gulf. The priority map of groundwater salinity monitoring was obtained based on the GALDIT index and two new factors including the average fluctuation of groundwater electrical conductivity (F) and distance from industries discharging saline effluents (P). The optimal number of monitoring wells was determined using a data analysis based on gamma test method. Then, a practical algorithm was presented to determine the optimal location of monitoring wells. Based on the results, the optimal number of monitoring wells is 110 and their location have an equitable distribution on the whole island.

Butanol is a key microbial product that provides a route from renewable carbohydrate resources to a "drop-in" liquid biofuel, broadening its market in the near future. The acceptable performance of butanol as a neat or a blended fuel in different engines both from the technical and environmental points of view has attracted a wide range of research for reviving the old acetone-butanol-ethanol (ABE) fermentation. In this review, recent findings on fuel characteristics of butanol, different generations of substrate for large scale butanol production, and alternative process designs for upstream, mainstream, and downstream operations have been critically reviewed and discussed. In the upstream, studies devoted to designing and optimization of pretreatments based on prerequisites of butanol production, e.g., maximizing cellulose and hemicellulose recovery and minimizing lignin degradation, are presented. In the mainstream, different microbial systems and process integrations developed for facilitating ABE production (e.g., in-situ butanol removal) are scrutinized. Finally, innovations in ABE recovery and purification as "Achilles Heel" of butanol production processes which directly controls the energy return on investment (EROI), are reviewed and discussed.

Highway runoff is one of the most significant non-point sources of pollution for the terrestrial and aquatic environment with biological, physical, and chemical effects. Considering local characteristics, treatment practices, and determining factors are essential for highway runoff management. The aim of this paper is to survey the review of highway runoff management in Europe with emphasis on runoff characterization, treatment, and modeling approaches and identifying possible knowledge gaps exists based on our review. The results showed that highway runoff has spatiotemporal variation, which is the main factor in the regional selection of the best management practice (BMP). Also, recent studies have poorly deemed characterization of highway runoff in different climatic scenarios, performance assessment of the current BMPs, and uncertainty analysis in modeling approaches. Furthermore, economic and risk analysis, along with decision-making methods, provide an optimum plan for the design and operation of BMPs.

Road construction has a negative environmental impact on the surrounding aquatic environment, requiring the continuous monitoring of surface water quality. Here, optimization of the water quality monitoring network (WQMN) is an essential step in supporting the sustainable development of road construction projects. This study introduces Gamma Test theory (GTT) as a practical method for optimizing the WQMN of surface waters during road construction. The water quality index (WQI) was computed in 48 monitoring stations for six monitoring periods from 2017 to 2019; data was acquired from a primary monitoring network over a new highway in southern Norway. Based on the results, it is possible to reduce the number of stations by 23% in comparison with the original empirical network. The proposed method could be useful to design the monitoring networks of projects with limited construction time and budget, as well as projects lacking enough data.

The bioconversion of lignocellulose into monosaccharides is critical for ensuring the continual manufacturing of biofuels and value-added bioproducts. Enzymatic degradation, which has a high yield, low energy consumption, and enhanced selectivity, could be the most efficient and environmentally friendly technique for converting complex lignocellulose polymers to fermentable monosaccharides, and it is expected to make cellulases and xylanases the most demanded industrial enzymes. The widespread nature of thermophilic microorganisms allows them to proliferate on a variety of substrates and release substantial quantities of cellulases and xylanases, which makes them a great source of thermostable enzymes. The most significant breakthrough of lignocellulolytic enzymes lies in lignocellulose-deconstruction by enzymatic depolymerization of holocellulose into simple monosaccharides. However, commercially valuable thermostable cellulases and xylanases are challenging to produce in high enough quantities. Thus, the present review aims at giving an overview of the most recent thermostable cellulases and xylanases isolated from thermophilic and hyperthermophilic microbes. The emphasis is on recent advancements in manufacturing these enzymes in other mesophilic host and enhancement of catalytic activity as well as thermostability of thermophilic cellulases and xylanases, using genetic engineering as a promising and efficient technology for its economic production. Additionally, the biotechnological applications of thermostable cellulases and xylanases of thermophiles were also discussed.

Water quality monitoring and assessment in drinking water resources are of great importance. The entry of pollutants and nutrients into water resources may cause problems for public health and can increase the bioaccumulation and biodiversity risks. This issue is more critical for dam lakes with more retention time, a primary source for drinking, agriculture, fish farming, and industry. This study applies the universal water quality index (U-WQI) to evaluate the dam lake quality in an arid area and identifies the sources of upstream pollutants over time (2016–2020). For this, 16 physical, chemical, and microbial parameters were quarterly measured in three points of Ilam dam lake in Ilam City, Iran. Then, U-WQI was calculated to evaluate water quality for drinking and cold water fish farming. Over the course of monitoring, the average U-WQI for drinking and fish farming was 176.7 and 190.2, respectively. Seasonal changes in the index suggest that fish farming in spring is more suitable than other seasons since the U-WQI decreases in summer and winter.

In this paper, we address the problem of tracking an object with pose and appearance changes, under possible occlusions by presenting an effective way to embed the texture information provided by the Local Binary Pattern (LBP), Local Ternary Pattern (LTP) and the Complete Local Binary Pattern (CLBP) in the mean shift framework. We combine the information of color distribution with variants of Local Binary Pattern texture for the purpose of robust tracking. Four adaptive scale and orientation mean shift trackers are proposed; the LBP_MS, LTP_MS, CLBP_MS1 and the CLBP_MS2. The last tracker can handle both textured and non-textured objects, and deals with the specific weaknesses of motion trackers, such as failures under specific conditions. As it can exploit more of the image information, we use seven public videos that contain a variety of challenges to illustrate the accuracy of the proposed approaches. The trackers successfully cope with fast moving objects, target scale and orientation changes, and prove to be more stable and less prone to drift away from the target than purely colored or feature-based ones. Keywords: Tracking, Motion, Texture

Background and Objective: University students are among vulnerable groups to tendency towards substance use. Accordingly, this study aimed to investigate the role of personal, familial, and social risk and protective factors in the prediction of tendency to this behavior among students.Materials and Methods: This descriptive correlational study was carried out on 431 students of Shahid Beheshti University of Medical Sciences who were selected by convenience sampling. Data were collected by Risk and Protective Factors Inventory (RPFI) and Youth Risk Taking Scale (YRTS) and then, were analyzed by Pearson correlation method and stepwise multivariate regression.Results: Data analysis using Pearson Correlation Coefficient showed significant relationships between personal (e.g. attitude towards substance use and tendency to drug use; r=0.6, PConclusion: In conclusion, current results indicated that a series of individual, familial, and social factors affect tendency towards substance use among students. Accordingly, identifying vulnerable students using suitable screening tests and providing them with primary prevention programs is of the utmost importance.

Iranian Gum Tragacanth (IGT) is among the most natural polymers which has interesting properties such as nontoxic nature, biodegradability and high resistance to bacterial attacks making it applicable for tissue scaffolds, protective clothing, and wound healing. In the current work, polyvinyl alcohol (PVA)/IGT nanocomposite fibre is prepared by using the electrospinning (ELS) technique in an aqueous solution with different volume ratios of 60/40, 70/30, 80/20, and 90/10. To enhance the chemical and mechanical stability of the produced samples, different amounts of nanoclay powder (1% and 3%) are added also to the solution. The blended nanofibres are characterized by scanning electron microscopy (SEM), Fourier-transform infrared (FTIR), and bioactivity evaluation in phosphate buffered saline (PBS) and simulated body fluid (SBF) solutions. The FTIR analysis indicated that PVA and IGT may have H+ bonding interactions. The results revealed that with a higher amount of IGT, a superior degradation as well as a higher chemical and biological stability could be obtained in the nanobiocomposite blend fibres. Furthermore, the blend nanofibre samples of 80/20 and 3% nanoclay powder exhibit a significant improvement during evaluation of its properties.