Although rRT-PCR is the gold standard method for SARS-CoV-2 detection, some factors, such as amplification inhibitors presence, lead to false-negative results. Here we describe differences between rRT-PCR results for SARS-CoV-2 infection in normal and diluted samples, simulating the need for dilution due to amplification inhibitors presence. Viral RNA extraction of nasopharyngeal swabs samples from 20 patients previously detected as 'Negative' and 21 patients detected as 'Positive' for SARS-CoV-2 was realized with the EasyExtract DNA-RNA (Interprise®). rRT-PCR was realized with OneStep/COVID-19 (IBMP) kit with normal and diluted (80µl of H₂O RNAse free) samples, totaling 82 tests. The results indicate that there is an average variation (ɑ < 0.05) delaying Cq between the amplification results of internal control (IC), N Gene (NG), and ORF-1ab (OF) of 1.811 Cq, 3.840 Cq, and 3.842 Cq, respectively. The extraction kit does not completely purify the inhibitor compounds, therefore non-amplification by inhibitors may occur. In this study, we obtained a 19.04% false-negative diagnosis after sample dilution, and this process reduces the efficiency of rRT-PCR to 29.80% for detecting SARS-CoV-2. Knowing the rRT-PCR standards of diluted samples can help in the identification of false-negative cases, and consequently avoid a wrong diagnosis.

This paper proposes several LabVIEW applications to accomplish the data acquisition, processing, features extraction and real-time classification of the electroencephalographic (EEG) signal detected by the embedded sensor of the NeuroSky Mindwave Mobile headset. The LabVIEW applications are aimed at the implementation of a Brain-Computer Interface system, which is necessary to people with neuromotor disabilities. It is analyzed a novel approach regarding the preparation and automatic generation of the EEG dataset by identifying the most relevant multiple mixtures between selected EEG rhythms (both time and frequency domains of raw signal, delta, theta, alpha, beta, gamma) and extracted statistical features (mean, median, standard deviation, route mean square, Kurtosis coefficient and others). The acquired raw EEG signal is processed and segmented into temporal sequences corresponding to the detection of the multiple voluntary eye-blinks EEG patterns. The main LabVIEW application accomplished the optimal real-time artificial neural networks techniques for the classification of the EEG temporal sequences corresponding to the four states: 0 - No Eye-Blink Detected; 1 - One Eye-Blink Detected; 2 – Two Eye-Blinks Detected and 3 – Three Eye-Blinks Detected. Nevertheless, the application can be used to classify other EEG patterns corresponding to different cognitive tasks, since the whole functionality and working principle could estimate the labels associated with various classes.

The processing of fossil fuels is the major environmental issue today which should be lessen. Biomass is gaining much interest these days as an alternate to energy generation. Lignocellulosic biomass (cellulose, hemicellulose and lignin) is abundant and has been used for a variety of purposes. Among them, the lignin polymer having phenyl-propanoid subunits linked together through C-C bonds or ether linkages, can produce numerous chemicals. It can be depolymerized by microbial activity together with certain enzymes (laccases and peroxidases). Both acetic acid and formic acid production by certain fungi contribute significantly to lignin depolymerization. Natural organic acids production by fungi has many key roles in nature that are strictly dependent upon organic acid producing fungus type. Fungal enzymatic conversion of lignocellulosic is beneficial over other physiochemical processes. Laccases, the copper containing proteins oxidize a broad spectrum of inorganic as well as organic compounds but most specifically phenolic compounds by radical catalyzed mechanism. Similarly, lignin peroxidases (LiP), the heme containing proteins perform a vital part in oxidizing a wide variety of aromatic compounds with H₂O_2. Lignin depolymerization yields value-added compounds, the important ones are BTX (Benzene, Xylene and Toluene) and phenols as well as certain polymers like polyurethane and carbon fibers. Thus, this review will provide a concept that biological modifications of lignin using acidophilic microbes can generate certain value added and environment friendly chemicals.

The vibration signal of the engine contains strong background noise and many kinds of modulating components, which is difficult to diagnose. Variational mode decomposition (VMD) is a recently introduced adaptive signal decomposition algorithm with a solid theoretical foundation and good noise robustness compared with empirical mode decomposition (EMD). VMD can effectively avoid endpoint effect and modal aliasing. However, VMD cannot effectively eliminate the random noise in the signal, so the random decrement technique is introduced to solve the problem. Based on the crankshaft bearing fault simulation experiment, the four kinds of wear state vibration signals are decomposed by VMD, and the modal components with smaller permutation entropy are selected as fault components. Then the fault component is processed by the random decrement technique, and the Hilbert envelope spectrum of the fault component is obtained. Compared with the fault feature extraction method based on EMD and EEMD, the feature extraction results of the proposed method are better than those of the above two methods. The simulation analysis and the simulation test of the crankshaft bearing fault verify the effectiveness of the proposed method.

The construction industry is responsible for 40 to 45% of primary energy consumption in Europe alone. Therefore, it is essential to find new materials with a lower environmental impact in order to attain sustainable housing. This study aims to determine and compare the environmental impact of two clay samples forming a basis for the manufacture of traditional brick, a standard material in building construction; traditional red clay brick and a brick based on clay mixed with a biological ingredient. The samples of fired clay were manufactured at the laboratory scale, the results being valid exclusively as indicators for the extrapolation of the analysis to other studies. The results of the environmental impact of these formulations have been examined through an evaluation of life-cycle analysis (LCA), observing that the incorporation of biological pore forming agents led to a decrease of around 15 to 20% of all impact categories studied. Thus, the suitability of using biological-based additives in clay bricks was confirmed both for their constructive characteristics (lighter material) and increased energy efficiency (better thermal insulation) considering the environmental point of view.

The consequences of growing urbanization can be perceived in multiple levels around the globe: overpopulated living conditions, water and air pollution, loss of open space, costly transportation infrastructure, food shortages, fires and floods. The Houston metropolitan area is an example of fast urban growth, with a population increase of more than sixteen percent in seven years, going from 5.8 million people in 2010 to 6.9 million in 2017 [1]. By 2045, the robust growth of the region is projected to lead to the addition of approximately five hundred square miles of developed area, including an estimated six million parking spaces, seven hundred eighty million square feet of non-residential uses, and three and a half billion square feet of residential use [2]. The accelerated development, in addition to physical features, geomorphic processes and human activities in the region are believed to have caused Houston to suffer through over fifty devastating floods since its settlement, despite some successful flood damage reduction projects. The present study focused on the potential outcomes of an increased use of green infrastructure in comparable urban areas, and its effects on flooding volume. Results from the research revealed that not only these measures would likely improve the performance of existing urban drainage systems and attenuate flood incidence in the area, but would also promote connectivity between areas otherwise detached or only accessible by car, improving walkability and incentivizing engagement in outdoor activities.

Cardamom is plant of the Zingiberaceae family. It has been used for the treatment of many diseases such as migraine, bronchitis, stomach and intestinal disorders. Cardamom contains triterpenes, resins, starch and fatty compounds. Phytosterols (stigmasterol, campesterol and β-sitosterol) are a group steroid alcohol in plants. They are used food, medicine and cosmetic industry. They are protective effects against some types of cancer too. Phytosterols are found in the vegetable oil such as the spindle, corn and soybean oil. This paper deals with the maximum oil and β-sitosterol yield were investigated by means of the supercritical CO₂ extraction of cardamom. The effect of operating parameters as temperature, pressure and CO₂ flow rate were investigated on oil yield. The amount of β-sitosterol was analyzed by Gas Chromatography-Mass Spectrometry (GC-MS) at optimized conditions. The optimized conditions were recorded as temperature of 40^oC, pressure of 200 bar and CO₂ flow rate of 4 L/min. The maximum oil yield and amount of β-sitosterol were found as 74.83 mg oil/g seed and 4.73 mg β-sitosterol/g seed cardamom under these conditions.

Azadirachta indica A. Juss (neem) extracts have been used in pharmaceutical applications as antitumor agents, due to their terpenes and phenolic compounds. To obtain extracts from neem leaves with potential antiproliferative effect, a sequential process of pressurized liquid extraction was carried out in a fixed bed extractor at 25 ºC and 100 bar, using hexane (SH), ethyl acetate (SEA) and then ethanol (SE) as solvents. An extraction using only ethanol (EE) was also conducted to compare the characteristics of the fractionated extracts. The results obtained by liquid chromatography-electrospray ionization mass spectrometry suggested the highest concentration of terpenes for SEA extract in comparison to SH, SE and EE extracts. Therefore, antiproliferative activity showed SEA extracts were the most efficient inhibitors to human tumor cells MCF-7, NCI-H460, HeLa, and HepG2 between all other extracts studied. However, hepatocellular normal cells were more resistant to SH, SEA, SE, and EE compared to malignant cells of breast, lung, hepatocellular, and cervical. Neem fractioned extracts obtained in the present study seem to be more selective for malignant cells compared to the normal cells.

Currently, metal nanoparticles have varied uses for different medical, pharmaceutical, and agricultural applications. Nano-biotechnology combined with green chemistry has great potential for the development of novel and necessary products that benefit human activities, while encourages the reduction of hazardous reagents for nanoparticle production. Green chemistry has an important role due to its contribution to unconventional synthesis methods of gold and silver nanoparticles from plant extracts, which have exhibited antimicrobial potential among other outstanding properties. Biodiversity-rich countries need to collect and convert knowledge from biological resources into processes, compounds, methods, and tools, which need to be achieved along with sustainable use and exploitation of biological diversity. Therefore, this review focuses on the importance of metal nanoparticles, the use of plant extract for their synthesis as well as other available methods, and the relevant antimicrobial activity that can be exploited in a sustainable model of agricultural management through a modern nanotechnological approach.

The exploitation and use of alternative synthetic methods, in the face of classical procedures that do not conform to the ethics of Green Chemistry, represent an ever present problem in pharmaceutical industry. The procedures for the synthesis of benzimidazoles have become a focus in synthetic organic chemistry, as they are building blocks of strong interest for the development of compounds with pharmacological activity. Various benzimidazole derivatives exhibit important activities such as antimicrobial, antiviral, anti-inflammatory and analgesic and some of the already synthesized compounds have found very strong application in medicine praxis. Here we report a selective and sustainable method for the synthesis of 1,2-disubstituted or 2-substituted benzimidazoles, starting from o-phenylenediamine in the presence of different aldehydes. The use of deep eutectic solvent (DES) both as reaction medium and reagent without any external solvent provides advantages in terms of yields as well as in the work up procedure of the reaction.

The number of green buildings has increased to address the global environmental crisis. However, green buildings face risks resulting from new materials and methods. In addition, these buildings are expected to perform at higher levels than traditional ones. The objectives of this study are to identify the possible risk factors for architects developing green building projects in South Korea and to assess risk mitigation measures. To attain this goal, fourteen risk factors and twelve mitigation measures were identified from a comprehensive literature review. A questionnaire survey was administered to architects practicing green building design. Findings revealed the ‘adoption of new technology and processes’ was the largest difference between green and traditional building projects. This study identified ‘financial risk,’ ‘design changes,’ and ‘client’s goal uncertainty’ as the top three risk factors in green building design. Additionally, the survey proposed the four most effective risk mitigation measures for green building projects: (1) ‘contract indicating each party’s roles, liabilities and limitations clearly’; (2) ‘utilizing integrated design process’; (3) ‘understanding client’s goal in green building projects’; and (4) ‘improving communication and coordination among stakeholders.’ There are a few studies focusing on the architects’ perceived risk concerning green building projects; however, this study expands the knowledge and fills the literature gap. Additionally, this study provides a comprehensive understanding of critical risks and mitigation measures that can benefit South Korea’s green building design practice through better risk management.

A valorization process of spent coffee grounds (SCG) was studied. Thus, a two-stage process, a stage of extraction of the polyphenols and a stage of obtaining activated carbon (AC) by a carbonization process, was performed. The extraction was carried out with a hydro-alcoholic solution in a pressure reactor, modifying time and temperature. To optimize the extraction of polyphenols, a two-level factorial design with three replications at the central values was used. The best results were obtained by performing the extraction at 80 °C during 30 min, using a mixture of EtOH:H2O 1:1 (v/v) as extraction solution. Caffeine and chlorogenic acid were the most abundant compounds in the analyzed extracts, ranging from 0.09 to 4.8 mg∙g^-1 and 0.06 to 9.7 mg∙g^-1, respectively. The precursor obtained in the extraction stage were transformed into AC. An experimental design was realized in order to analyze the influence of different variables in the AC obtained process (reaction time and amount of potassium hydroxide used). Actived carbons with BET specific surface (SBET) comprised between 1600 m^2∙g^-1 and 2330 m²∙g^-1 had a microporous surface. Under the optimum conditions, the obtained AC presented a maximum adsorption capacity of methylene blue (qm) between 411 mg∙g^-1 and 813 mg∙g^-1.

Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova's (SoTa), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova's, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

Network Embedding (NE) is an important method to learn the representations of network via a low-dimensional space. Conventional NE models focus on capturing the structure information and semantic information of vertices while neglecting such information for edges. In this work, we propose a novel NE model named BimoNet to capture both the structure and semantic information of edges. BimoNet is composed of two parts, i.e., the bi-mode embedding part and the deep neural network part. For bi-mode embedding part, the first mode named add-mode is used to express the entity-shared features of edges and the second mode named subtract-mode is employed to represent the entity-specific features of edges. These features actually reflect the semantic information. For deep neural network part, we firstly regard the edges in a network as nodes, and the vertices as links, which will not change the overall structure of the whole network. Then we take the nodes' adjacent matrix as the input of the deep neural network as it can obtain similar representations for nodes with similar structure. Afterwards, by jointly optimizing the objective function of these two parts, BimoNet could preserve both the semantic and structure information of edges. In experiments, we evaluate BimoNet on three real-world datasets and task of relation extraction, and BimoNet is demonstrated to outperform state-of-the-art baseline models consistently and significantly.

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

Tooth bud removal called Ibyinyo is the practice of removing the developing tooth buds, usually done on an infant, typically performed by traditional healers who believe that this practice will reduce fever and diarrhea in children. This practice is most prevalent in East-African countries, including Rwanda. These procedures are mostly performed in non-sterile conditions using basic sharp instruments. We will discuss the case of a 10-year-old female patient who was presented at the dental clinic, with two malformed permanent canine teeth. Clinical examination revealed malformed enamel and elongated permanent right maxillary canine tooth left mandibular canine tooth with crown malformation. She was also presented with retained (primary) left maxillary lateral incisor tooth and missing left maxillary canine tooth. In addition, the ectopic eruption of left maxillary central incisor tooth and missing permanent right mandibular canine tooth were noted. All these complications resulted from tooth bud removal that the patient had experienced in her early childhood. Her malformed right maxillary and left lower mandibular canine teeth were reshaped, using composite filling materials, to improve her appearance aesthetically. Ibyinyo is preventable damage, done out of ignorance and superstitious practices that can be stopped by growing social awareness. Therefore, educating parents through community-based campaigns on the detrimental consequences of early childhood tooth bud removal through Ibyinyo practice might be helpful to eradicate this harmful and unnecessary practice.

Mushrooms have long rich history in folk medicine, traditional and functional foods due to high content of dietary myco-nutrients. Currently, there is increased interest in finding appropriate food-grade green ex-traction systems capable of extracting these bioactive compounds from dietary mushrooms for applica-tions in various food, pharmacological or nutraceutical formulations. Herein, we evaluated a modified Swiss water process (SWP) method using alkaline and acidic pH at low and high temperature under pressurized conditions as a suitable green food grade solvent to obtained extracts enriched with my-co-nutrients (dietary phenolics, total antioxidants (TAA), vitamins, and minerals) from Chaga. Ultra-high performance liquid chromatography coupled to high resolution accurate mass tandem mass spectrometry (UHPLC-HRAMS-MS/MS) was used to assess the phenolic compounds and vitamin levels in the extracts, while inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the mineral con-tents. Over twenty phenolic compounds were quantitatively evaluated in the extracts and the highest total phenolic content and antioxidant activity was observed at pH11.5 at 100°C. The most abundant phenolic compounds present in Chaga extracts included phenolic acids such as protocatechuic acid 4-glucoside (0.7-1.08µg/mL), syringic acid (0.62-1.18µg/mL), and myricetin (0.68-1.3µg/mL). Vitamins are being reported for the first time in Chaga. pH 2.5 at 100°C treatment shows superior effects in extracting the B vitamins whereas pH 2.5 at 60 and 100°C treatments were outstanding for extraction of total fat-soluble vitamins. Vitamin E content was the highest for the fat-soluble vitamins in the Chaga extract under acidic pH (2.5) and high temp. (100°C) and ranges between 50 to 175 µg/100g Chaga. Antioxidant minerals ranged from 85.94 µg/g (pH7 at 100°C) to 113.86 µg/g DW (pH2.5 at 100°C). High temperature 100°C and a pH of 2.5 or 9.5. The treatment of pH11.5 at 100°C was the most useful for recovering phenolics and antioxidants from Chaga including several phenolic compounds reported for the first time in Chaga. SWP is being proposed herein for the first time as a novel, green food-grade solvent system for the extraction of myco-nutrients from Chaga and have potential applications as a suitable approach to extract nutrients from other matrices. Chaga extracts enriched with bioactive myconutrients and antioxidants may be suitable for further use or applications in the food and nutraceutical industries.

Huge amounts of chitin and chitosans can be found in the biosphere as important constituent of the exoskeleton of many organisms, as well as waste by worldwide seafood companies. Nowadays, politicians, environmentalists, and industrialists encouraged the use of these marine polysaccharides as renewable source, particularly when developed by alternative eco-friendly processes, especially in the production of regular cosmetics. The aim of this review is to outline the physicochemical and biological properties and the different bioextraction methods of chitin and chitosans sources, focusing on enzymatic deproteinization, bacteria fermentation, and enzymatic deacetylation methods. Thanks to their biodegradability, non-toxicity, biocompatibility, and bioactivity, the application of these marine polymers is widely used in the contemporary manufacturing of biomedical and pharmaceutical products. In the end, advanced cosmetic products based on chitin and chitosans are presented, analyzing different therapeutic aspects about skin, hair, nail, and oral care. The innovative formulations described can be considered as excellent solutions regarding problems in the various body anatomical sectors.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

In laser joining of copper (Cu) and aluminum (Al) sheets, the Al sheet is widely chosen as the top surface for laser irradiation because of increased absorption of laser beam and lower melting temperature of Al in contrast to Cu. This research focus on welding from Cu side to Al sheet. The main objective of irradiating the laser beam from the copper side (Cu on top) is to exploit higher solubility of Al in Cu. A significantly lower laser power can be used with 515 nm laser in comparison to 1030 nm. In addition to low laser power, a stable welding is obtained with 515 nm. Because of this advantage, 515 nm is selected for the current research. By fusion of Cu and Al the two sheet metals are welded, with presence of beneficial Cu solid solution phase and Al+Al2Cu in the joint with the brittle phases intermixed between the ductile phase. Therefore the mixed composition strengthens the joint. However excessive mixing leads to formation of more detrimental phases and less ductile phases. Therefore optimum mixing must be maintained. Energy dispersive X-ray spectroscopy (EDS) analysis indicate that large amount of beneficial Cu solid solution and Al rich phases is formed in the strong joint. From the tensile shear test for a strong joint, fracture is obtained on the heat-affected zone (HAZ) of Al. Therefore the key for welding from copper side is to have optimum melt with beneficial phases like Cu and Al+ Al2Cu and the detrimental phases intermixed between the ductile phases

This is a paper of Political Economy and Economic Policies into the European Green Deal framework to improve the Recovery Plan post-COVID-19. This paper is focused on the green jobs opportunity for Europe, especially for Spain. It is offered a systematization of concepts and calculations in the issue (attending the international institutions and forums proposals) to harmonize the recovery plans, to apply them beyond the energy sector and to align public and private sector, as well other key stakeholders in achieving this goal. The obtained outcome gives the creation of around 350.000 new green jobs and the necessity of a new workforce reskilled. This result makes necessary to coordinate sectoral plans by the policymakers in which all the involved entities might express their needs and views on the best education approach to renewables sector and green jobs.

Cold brew coffee is a new trend in coffee industry. This paper presents pilot studies into several aspect of this beverage. Using an online survey, the current practices of cold brew coffee preparation were investigated identifying a rather large variability with a preference for extraction of medium roasted Arabica coffee using 50-100 g/l at 8°C for about 1 day. Sensory testing using ranking and triangle tests showed that cold brew may be preferred over iced coffee (cooled down hot extracted coffee). Extraction experiments at different conditions combined with nuclear magnetic resonance (NMR) analysis showed that the usual extraction time may be longer than necessary as most compounds are extracted within only a few hours, while increasing turbulence (e.g. using ultrasonication) and temperature may additional increase the speed of extraction. NMR analysis also revealed a possible chemical differentiation between cold brew and hot brew using multivariate data analysis. Decreased extraction time and reduced storage times could be beneficial for cold brew product quality as microbiological analysis of commercial samples detected samples with spoilage organisms and contamination with Bacillus cereus.

The key anthropogenic effects on climate include the changes in land use and emission of greenhouse gases into the atmosphere. Depletion of vegetation poses serious threat that speeds the process of climate change and reduces carbon sequestration by the environment. Thus, the preservation of natural environment in urban areas is an essential component of the garden city model, proposed by Sir Ebenezer Howard in 1898, to ensure ecological balance. Recent Landsat images showed that Kumasi does not have the required percentage of green vegetation as was stipulated in the garden city model on which the city was built. It was observed that most parts of Kumasi's green vegetation have been lost to built environments. This study was conducted to assess the impact of urbanization on the garden city status and its effect on the micro-climate of the city. Significant changes in the vegetation cover of the city was evaluated from Landsat-TM imagery and analysis of a long term climatic data of Kumasi carried out over a 55-year period (1960 to 2015). It was observed that, climatic conditions have slightly changed, as mean surface temperature of has increased by 1.2 °C/ 55 years, due to the significant landuse changes from development of non-transpiring, reduced evaporative urban surfaces. However, the impact is not greatly felt due to the geographical location of the city on the globe despite the evidence of a considerable temperature change. Green vegetation conservation for the city is recommended as a top priority in future for city authorities and planners.

In the process of modernization and development, a human being always needed energy, which increased the dependency on the available sources of fossil fuel. Tetraselmis, a green algal genus belong to the order Chlorodendrales, are described by their strong green coloured chloroplast, flagellated cell bodies, and the occurrence of a pyrenoid within the chloroplast. In this study, four different strains of Tetraselmis species were successfully isolated from the saltpans Kovelong, Chennai, Tamil Nadu, India. The isolated strains were cultured in the normal basal medium and their morphological features were subsequently studied. The species of Tetraselmis straiata (T. straiata) Butcher BBRR1 was confirmed using molecular identification of 18S rRNA gene analysis and its observed systematic position. Among the four different isolates, T. straiata Butcher BBRR1 recorded a highest biomass concentration of 0.58 ± 0.021 g L^-1, 15% lipids, 19% proteins and 17% carbohydrates when it grown under laboratory condition. Whereas, in open raceway ponds, T. straiata BBRR1 produced 0.95 ± 0.06 g L^-1 biomass, 19% lipids, 28% proteins and 21% carbohydrates in an modified CFTRI I medium. The fatty acids profile of T. straiata Butcher BBRR1showed the presence of 33.14 % Palmitic acid, 22.64% 11- Octadecenoic acid and 21.94% Heptadecanoic acid. Since T. straiata BBRR1 can be cultivated in open ponds without a major contaminations, this species can be used as novel biomass feedstock to produce biofuels. This study may suggest the potential of T. straiata BBRR1 for biofuel production and could compete the energy demand in the future. In addition, this species contains healthful components of carotenoids, lipids and proteins, all these may provide a health benefits beyond basic nutrition.

This paper presents a comparison between indirect methods for assessing the buildability of 3D printed cementitious materials, including CRV or CSR test using rotational rheometry, unconfined uniaxial compression test (UUCT), a newly proposed confined uniaxial compression test (CUCT), and fast penetration test. The experimental program was conducted on the extruded samples of six printable mortars and two printable concretes with various rheological behavior achieved by the use of different additives and admixtures. Predictions of the material failure and the stability failure in hollow cylindrical structures are provided and compared with the results of the direct printing test. Benefits and disadvantages of the employed test methods are discussed, also taking into consideration a perspective of their use for automated in-situ control of the materials’ buildability.

Melanins are phenolic biopolymers synthesised by most of the living organism mainly for photoprotection or surviving in harsh conditions. Melanin is localised in different areas or complexed with different other biomolecules when observed from animals to microbes. This makes the melanin extraction procedure different in animal, plant and microbial tissues. Basically, the alkali-acid extraction is used in most protocols of which slight variations are there depending on the tissue used. This review will try to compile melanin extraction procedures from different cells and tissues ranging from animals to bacteria.

The current rapidly changing and highly competitive market has put companies under a great pressure not only to be successful, but also to sustain their success into the future. In addition, in recent years, companies have become more aware of the fact that it is no longer enough to take care of economic aspects, being crucial to also take care of environmental and social aspects in order to actually succeed and lead in the current and future markets. In this context, companies are urged to move towards more innovative manufacturing practices that maintain a healthy balance among economic, environmental and social performances, which are the three pillars of the sustainability performance. To give some insight into this issue, a Systematic Literature Review (SLR) is conducted in this paper regarding the current trends in the field, doing special focus on the link between lean-green manufacturing and the different sustainability aspects. The SLR concluded that lean and green implementations as stand-alone systems are usually not enough to ensure the required balance between the three pillars of sustainability, suggesting further combining them into a single approach. Researchers expect to achieve further improvements in the sustainability performance moving towards the next level of sustainability.

This paper describes the feasibility and probable benefits associated with greening the Tahliah Channel, a concrete drainage channel that was originally built to relieve urban flooding in Jeddah City, Saudi Arabia. It includes an estimation of irrigation needs for channel greening based on a standardized planting specification. The study also demonstrates alternative strategies for meeting the required irrigation demand, including water harvesting and graywater reuse on a residential scale. The study shows that greening Tahliah Channel is possible relying mainly on graywater reuse from the surrounding buildings. Also, the study shows that rainwater harvesting is not a reliable source for irrigation. Rather, it can cover only part of the irrigation needs (6%) and so can be used as a secondary supporting source. The positive results of this case study will be of interest to those in arid countries who are looking to upgrade and replace traditional, single function drainage infrastructure with more sustainable, green infrastructure systems. More specifically, the objectives of the study are consistent with the goals of the Saudi government’s ongoing initiative that advocates for more resilient and sustainable cities. (Vision 2030 year).

Evolutionary psychology theories propose that contact with green, natural environments may benefit physical health, but little comparable evidence exists for brown, natural environments, such as the desert. In this study, we examined the association between “brownness” and “greenness” with fasting glucose among young residents of El Paso, Texas. We defined brownness as the surface not covered by vegetation or impervious land within Euclidian buffers around participants’ homes. Fasting glucose along with demographic and behavioral data was obtained from the Nurse Engagement and Wellness Study (N = 517). We found that residential proximity to brownness was not associated with fasting glucose when modeled independently. In contrast, we found that residential greenness was associated with decreased levels of fasting glucose, despite the relatively low levels of greenness within the predominantly desert environment of El Paso. A difference between the top and bottom greenness exposure quartiles within a 250 m buffer was associated with a 3.5 mg/dL decrease in fasting glucose levels (95% confidence interval: -6.2, -0.8). Our results suggest that within the understudied context of the desert, green vegetation may be health-promoting to a degree that is similar to other, non-desert locations in the world that have higher baselines levels of green.

The rapid growth of the organic food market in Italy and in other developed countries has drawn the attention of researchers and practitioners. The diffusion of pro-environmental concerns and sustainable lifestyles among consumers are often cited as two of the main drivers of the increase in demand for organic food products. Consequently, unveiling the factors that influence consumers’ demand of, and preference for organic food is essential for all the actors involved in the supply chain. This paper presents the results of a research model which relates organic food purchase intention to consumers’ green consciousness, health motivations, food safety concerns, organic product knowledge, family and social context and perception of the intrinsic quality of food. A questionnaire, based on the Theory of Planned Behavior (TPB) and the extant literature on organic food choice, was developed and presented to a sample of 600 Italian consumers. Causal relations among variables were then tested using Structural Equation Modelling. The results suggest that, besides the existence of green consciousness, other variables may affect consumers’ preference for organic food: among these, specific and closely interlinked elements, such as food safety concerns and perceived quality heavily affected the intention to buy organic food products.

Research on green-certified buildings has often been focused on the benefits of green standards, such as energy efficiency, smart growth, resource conservation, and health protection. Recent studies suggest the adoption of a reductionist sustainability planning language can turn green-certified houses into luxury goods, attracting White, prime-age, college-educated households with some pro-environmental attitudes who replace existing long-term, lower-income residents in core urban areas. While many factors may work together in driving neighborhood change and gentrification in cities, the question this study aims to address is to what extent the supply of green-certified units can affect neighborhood change and gentrification? We use Central Virginia’s Multiple Listing Service (MLS) housing market transactions data and the U.S. Census Bureau’s socioeconomic data to present the differential effect of new construction of market-rate, green-certified units in a natural experiment using difference-in-differences estimates. We find that neighborhoods that include new, green-certified units have experienced a statistically significant increase in population, supporting new construction and positively affecting house prices. We also detect some negative effects on minorities and minority owners, but these effects have not yet reached statistical significance. This study finds strong evidence of green housing providing the conditions that make areas ripe for gentrification, but more studies should follow up to better measure and generalize this finding.

The number of documents published on the Web other languages than English grows every year. As a consequence, it increases the necessity of extracting useful information from different languages, pointing out the importance of researching Open Information Extraction (OIE) techniques. Different OIE methods have been dealing with features from a unique language. On the other hand, few approaches tackle multilingual aspects. In such approaches, multilingual is only treated as an extraction method, which results in low precision due to the use of general rules. Multilingual methods have been applied to a vast amount of problems in Natural Language Processing achieving satisfactory results and demonstrating that knowledge acquisition for a language can be transferred to other languages to improve the quality of the facts extracted. We state that a multilingual approach can enhance OIE methods, being ideal to evaluate and compare OIE systems, and as a consequence, to applying it to the collected facts. In this work, we discuss how the transfer knowledge between languages can increase the acquisition from multilingual approaches. We provide a roadmap of the Multilingual Open IE area concerning the state of the art studies. Additionally, we evaluate the transfer of knowledge to improve the quality of the facts extracted in each language. Moreover, we discuss the importance of a parallel corpus to evaluate and compare multilingual systems.

Forest carbon sequestration is a widely accepted natural climate solution, however, methods to determine net carbon offsets are limited to commercial carbon proxies and CO2 eddy covariance research. Non-CO2 greenhouse gases (GHG) (e.g., CH4, N2O) receive less attention in the context of forests, in part, due to emphasis on CO2 and the operational requirements and cost for three-gas eddy covariance platforms. In this study, Howland forest flux tower (CO2, CH4) and soil flux data (CO2, CH4, N2O), representing net emission reductions, are linked to their respective social costs to estimate commercial revenue if sold as a GHG social cost forest offset product (GHG-SCF). Estimated annual revenue for GHG-SCF products, applicable to realization of a Green New Deal, range from 120,000 covering the site area of 557 acres in 2021, to 12,000,000 for extrapolation to 40,000 acres in 2040, assuming a 3% discount rate. The Howland Forest CO2 flux record for two adjacent towers is compared to California Air Resources Board forest carbon proxy data for compliance sequestration offsets, the only project site where these approaches overlap. Overcrediting, incomplete carbon accounting with annual errors of up to 2,256%, inadequate third-party verification, and limited application to non-CO2 GHG’s are established. In contrast, direct measurement of one or more GHG’s offers new forest products and revenue incentives to restore and conserve forests worldwide.

Many corner detector techniques have already been used in extracting information from UAV images to perform various photogrammetric and mapping activities. Among these techniques is the Feature from Accelerated Segment Test (FAST) and the Harris corner detector. It is widely agreed that the evaluation of detectors is of great importance because it evaluates and enhances the accuracy of the detected features. This research evaluates the performance of FAST-9 and FAST-12 as well as the Harris detector in terms of the repeatability rate, completeness, and correctness under different threshold values. Each method is evaluated in terms of its ability for detection UAV objects (crowd and cars features). Then the common detected features between both FAST versions and the Harris detector are extracted. This is to determine which method performs best under different image conditions (e.g., illumination variations, camera position and orientation, and image noise). The results show that the size of the threshold plays a crucial role in determining the number of detected feature points. An increase in the threshold value leads to a decrease in the number of detected points and vice versa. Thus, the correctness decreases whereas the completeness increases as a function of the threshold values. Furthermore, the relationship between the FAST-9 and the Harris detector is slightly better than those between the FAST-12 and the Harris detector. This is because the number of common features between the FAST-9 and the Harris detector are relatively higher than those between the FAST-12 and the Harris detector.

The combination of eco-respectful epoxy compounds with the humins, a by-product of biomass chemical conversion technologies, allow the obtention of materials with high added value. In this work, we propose the chemical connection study of humins with two aliphatic diepoxides through the copolymerization reactions to synthesize sustainable bio-based thermosets. The mechanism insights for the crosslinking between the epoxides and humins was proposed considering the different functionalities of the humins structure. FT-IR spectroscopy, 1 D and 2 D NMR spectroscopy techniques were used to build the proposed mechanism. By these techniques, the principal chain connections and the reactivity of all the components were highlighted in the synthesized networks.

1) Background: A population-based cross-sectional study was conducted to understand how green cover and accessibility of common public open spaces in compact urban areas affect physical activeness of resident. 2) Methods: A total of 554 residents completed a structured questionnaire on quality-of-life, physical activity level, and healthy eating practice. 3) Results: The sampled population lived with green cover averaged 10.11 ± 7.95% (ranged 1.56–9.88), whereas majority (90%) of the residents performed physical activities at medium and high levels. Metabolic Equivalent of Task (MET)-minutes/week was associated with the green cover percentage (Pearson r = 0.092; p < 0.05). Irrespective of age and physical activity level, active residents commonly used public open spaces within district for performing exercise, especially parks and promenade were mostly used by older residents while sports facilities by the younger groups. 4) Conclusions: Current findings suggested promotion of exercise could be achieved by the design or redesign of built environment to include more parks accessible to the residents with the increase of vegetation.

Background. Nanotechnology is promising field for generating new applications. A green synthesis of nanoparticles through biological methods using plant extract have a reliable and ecofriendly approach to improve our global environment. Methods. Silver nanoparticles (AgNPs) were synthesized using aqueous extract of Anagalis arvensis L and silver nitrate and were physicochemically characterized. Results. The stability of AgNPs toward acidity, alkalinity, salinity and temperature showed that they remained stable at room temperature for more than two months. The SEM and TEM analysis of the AgNPs showed that they have a uniform spherical shape with an average size in the range of 40–78 nm. Further 1-Dibhenyl-2-Picrylhydrazl radical in Anagalis arvensis L.mediated AgNPs showed a maximum activity of 98% at concentration of 200μg/mL. Hydrogen peroxide scavenging assay in Anagalis arvensis L. mediated AgNPs showed a maximum activity of 85% at concentration of 200μg/mL. Reducing power of Anagalis arvensis L.Ag NPs exhibited a higher activity of 330 μg/mL at concentration of 200 μg/mL. These NPs have cytotoxic effects against brine shrimp (Artemia salina) nauplii with a value of 53% LD 178.04μg/mL. Conclusion. The AgNPs synthesized using Anagalis arvensis L. extract demonstrate a broad range of applications.

Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the validation and comparison of different spectral unmixing methods. In this paper we introduce the DLR HyperSpectral Unmixing (DLR HySU) benchmark dataset, acquired over German Aerospace Center (DLR) premises in Oberpfaffenhofen. The dataset includes airborne hyperspectral and RGB imagery of targets of different materials and sizes, complemented by simultaneous ground-based reflectance measurements. The DLR HySU benchmark allows a separate assessment of all spectral unmixing main steps: dimensionality estimation, endmember extraction (with and without pure pixe assumption), and abundance estimation. Results obtained with traditional algorithms for each of these steps are reported. To the best of our knowledge, this is the first time that real imaging spectrometer data with accurately measured targets are made available for hyperspectral unmixing experiments. The DLR HySU benchmark dataset is openly available online and the community is welcome to use it for spectral unmixing and other applications.

The paper is an investigation on the impact of financial markets on the volatility of green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) of the Global Bloomberg Barclays MSCI Green Bond Index, for both the non and pandemic periods. For these purpose, after observing the dynamic joint correlations between all the variables through a DCC-GARCH, we adopt GARCH(1,1) and EGARCH(1,1) models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two EGARCH models is positive: so the “green” credit risk volatility is more sensitive to positive shocks than negative ones. With reference to the conditional mean, we note that if during the non pandemic time only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context.

Automated Electrocardiogram (ECG) processing is an important technique which helps in identifying abnormalities in the heart before any formal diagnosis. This research presents a real-time and lightweight R-assisted feature extraction algorithm and a heartbeat classification scheme which achieves highly accurate abnormality detection. In the proposed algorithm, we extract fifteen features from each heartbeat taken from raw Lead-II ECG signals. The features carry medically valuable information such as locations, amplitude and energy of ECG waves (P, Q, R, S, T waves) which are then used for detection of any abnormality that might be present in the heartbeat using various classification algorithms. We have used four popular databases from Physionet and extracted ten thousand ECG signals from each for training the models and benchmarking results. Four classification models i.e. Naïve Bays, k-Nearest Neighbor, Neural Network, Decision Tree were used for abnormality detection validating the efficiency of the system.

Information and communication technologies (ICT) are increasingly permeating our daily life and we ever more commit our data to the cloud. Events like the COVID-19 pandemic put an exceptional burden upon ICT infrastructures. This involves increasing implementation and use of data centers, which increased energy use and environmental impact. The scope of this work is to take stock on data center impact, opportunities, and assessment. First, we estimate impact entity. Then, we review strategies for efficiency and energy conservation in data centers. Energy use pertain to power distribution, IT-equipment, and non-IT equipment (e.g. cooling): Existing and prospected strategies and initiatives in these sectors are identified. Among key elements are innovative cooling techniques, natural resources, automation, low-power electronics, and equipment with extended thermal limits. Research perspectives are identified and estimates of improvement opportunities are presented. Finally, we present an overview on existing metrics, regulatory framework, and bodies concerned.

Abstract: Green walls and green dams are increasingly being considered as part of many nation-al and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria) from 1972 to 2019 by using Landsat imagery, Land Change Modeler and Open Land package. The future evolution of pine plantations for the year 2029 was also forecasted, based on an anthropogenic scenario (i.e., an-thropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but after that, pine plantations deteri-orated significantly due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land Change Modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation con-tinues at the same rate, the green dam will disappear in the Moudjbara region during the next few decades. Aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation

Numerous protocols have been published for extracting DNA from phlebotomines. Nevertheless, their small size is generally an issue in terms of yield, efficiency, and purity, for large-scale individual sand fly DNA extractions when using traditional methods. Even though this can be circumvented with commercial kits, these are generally cost-prohibitive for developing countries. We encountered these limitations when analysing parasite infection in Lutzomyia spp. by PCR [1] and, for this reason, we evaluated various modifications on a previously published protocol ([2] and Acardi personal communication). The most significant variation was the use of a different lysis buffer [3] to which added Ca2+ (buffer TESCa), because this ion protects proteinase K against autolysis, increases its thermal stability, and could have a regulatory function for its substrate-binding site [4]. Individual sand fly DNA extraction success was confirmed by amplification reactions using internal control primers that amplify a fragment of the cacophony gene [5,6]. To the best of our knowledge, this is the first time a lysis buffer containing Ca2+ has been reported for the extraction of DNA from sand flies.

Bauxite residue is the voluminous by-product of alumina production after Bayer process. Its high alkalinity causes disposal problems and harmful environmental impacts. However, the residue contains significant amounts of valuable elements such as rare earth elements including scandium. Greek bauxite residue contains a high amount of scandium close to its main resources. Taking into account scandium limited availability coupled with its high demand in modern technology, bauxite residue could be considered as a potential resource for scandium recovery. In this study, the optimization of scandium extraction from bauxite residue with sulfuric acid is investigated using Taguchi methodology. Based on previous studies acid molarity, leaching time, solid/liquid ratio and reaction temperature were selected as control parameters for the selective Sc recovery. Method optimization targeted the highest concentration of scandium combined with the lowest concentration of iron without taking into account applications constraints. The predicted values resulted by Taguchi methodology were affirmed by a confirmation experiment conducted at optimal conditions. Regression analysis provided the respective equations to be applied on several conditions depending on different applications.

In recent years, many researchers have begun to shift their focus onto the synthesis of nanomaterials as this field possesses immense potential that may provide incredible technological advances in the near future. The downside of conventional synthesis techniques, such as co-precipitation, sol-gel and hydrothermal methods, is that they necessitate the use of toxic chemicals, produce harmful by-products and require a considerable amount of energy; therefore, more sustainable fabrication routes are sought after. Biological molecules have been previously utilised as precursors to nanoparticle synthesis, thus eliminating the negative factors involved in traditional methods. In addition, transition-metal nanoparticles possess a wide scope of applications due to their multiple oxidation states and large surface areas; thereby allowing for a higher reactivity when compared to their bulk counterpart and rendering them an interesting research topic. However, this field is still relatively unknown and unpredictable. Therefore, this review aims to obtain a better understanding on the plant-mediated synthesis process of the major transition-metal and transition-metal oxide nanoparticles, and how different parameters affect their unique properties.

Open-plan office (OPO) layouts emerged to allow organizations to adapt to changing workplace demands. We explore the potential for OPOs to provide such adaptive capacity to respond to two contemporary issues for organizations: the chronic challenge of environmental sustainability, and the acute challenges emerging from the great COVID-19 homeworking experiment. We apply a socio-technical systems perspective and green ergonomics principles to investigate the relationship between an OPO environment and the occupants working within it. In doing so, we consider the relevant technical and human factors such as green technology and employee green behavior. We also consider how a green OPO might provide non-carbon benefits such as improving occupant wellbeing and supporting the emergence of a green organizational culture. Our investigation highlights several avenues through which an OPO designed with green ergonomic principles could benefit occupants, the organizations they work for, and the natural environment of which they are a part and on which they depend. We find reason to suspect that green OPOs could play an important role in sustainable development; and offer a research agenda to help determine whether in fact OPOs are another example of how going green is good business.

The science on the anthropogenic airborne aerosols impacting upon the World Heritage marble monument, the Taj Mahal, at Agra has been studied in the light of modern physico-chemical approaches. The study is an effort to understand yet unrecognized airborne species which were found on the surface of the Taj Mahal monument. These species have been analyzed in the light of current analytical methods to impart characterization features and their possible impacts on the surface of the marble. Chemical constituents of these substrates which were incorporated over the top surface of the monument have been identified. Interestingly, the carbon particulates which were thought in the micro level, popularly called “particulate matters” has now been identified even in the nano domain entity, which are chemically more reactive, have been found on the surface of the monument. Because of their high chemical activity these nano carbons do play newer chemistry in the presence of air and sunlight generating several reactive oxygen species (ROS).These ROS are capable to respond to complicated chemical reactions on the surface of the marble in association with deposited cyanophyceae and other deposits of plant origin causing rapid degradation. This study provides the nature of onslaught borne out by such monument exposed under the prevalent smoggy environmental scenario.

The influence of instrumental variables on farmers ‘perceptions using rotation fallow as sustainable agriculture practices had been the aim of our research. By using simultaneous equations models, this study tried to understand the relationship between green manure farmer’s perceptions on using rotation-fallow and planting green manure in Guangxi Province, south of China. The results showed that subsidizing green manure farmers based on standard subsidy by the unit of green manure sown area; the training on the green manure planting technology or the demonstration preaching; the green manure farmers preference for the kinds of subsidy (funds, seeds, and mechanical services) were the mostly great drivers of the program of restoring planting green manure in the study area. These incentives measures must be enhanced as priority to restore definitely green manure planting. However, the findings of the study showed that the total income of the 2017 year, the area of an agricultural field of household and the household members (16–65 years old), providing labor in the agricultural field, have some influences on planting green manure and on farmer’s perceptions on using rotation-fallow as sustainable agriculture practices. Brief, the unobserved factors which influenced the endogenous factors play an important role to enhance widely the impact of farmers’ perceptions on planting green manure.

Onions are an excellent source of a variety of essential antioxidants, polyphenols, and other phytonutrients. These onions were used to enhance the meal's flavour and aroma. Additionally, onions have long been recognised for their ability to change food texture, making it more pleasant for eating. Among the most significant phenolic compounds identified in onions was Quercetin, which has been proven to be very helpful for maintaining good health by reducing the risk of heart disease, cancer, and a number of other severe conditions. Polyphenol extraction is essential for the effective usage and research of these phytochemicals. Previously, the extraction process was complicated by a variety of traditional methods, but with the aid of contemporary technology, the procedure was simplified. Additionally, it was found that red onions had greater health benefits than yellow onions, which were the most commonly used kind at the time. Apart from their health benefits, polyphenols were well recognised for their industrial use in dyeing, polymer manufacturing, and resin synthesis.

Background: The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenges. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Results: Here, we propose a computational and experimental protocol for whole genome quantitative metagenomics studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatic protocol to analyse ONT sequences taxonomically and functionally and optimized pre-analytic protocols including stool collection and DNA extraction methods to maximize read length. This is a critical parameter for the sequence alignment and classification. Our protocol was evaluated using simulations of metagenomic communities which reflect naturally occuring compositional variations. Next, we validated both protocols using stool samples from a bariatric surgery cohort, sequenced with ONT, Illumina and SOLiD technologies. Results revealed similar diversity and microbial composition profiles. Conclusion: This protocol can be implemented in the clinical or research setting, bringing rapid personalized whole genome profiling of target microbiome species.

Phloem-feeding insects strive to offset the disadvantageous effects of stressors to sustain their offspring and survive. Adaptive responses to environmental stress are not well understood under complex influences of companion planting, natural enemies, and host gradient. In this study, under predation by lacewing Chrysoperla carnea Stephens (Neuroptera: Chrysopidae), we survey the responses of green peach aphid Myzus persicae Sulzer (Hemiptera: Aphididae), reared on different densities of cabbage Brassica oleracea L. (Brassicales: Brassicaceae) to its shallot companion Allium cepa (L.) var. aggregatum G. Don (Asparagales: Amaryllidaceae). Firstly, aphid aggregative abundance was strongly influenced by shallot perturbation, predator presence and changes in cabbage-host biomass, altering aphid phenotypic plasticity. Interestingly, the shallot and predation negative impacts can be of similar magnitudes. Secondly, changes in the cabbage-host availability and biomass, especially under predation, had a strong impact on aphid traits. Our study underscores the benefits of including shallots as crop-companions in augmenting pest control, but also suggests that the outcome of coupling companion planting with natural enemies is context-dependent and thus should be empirically applied. At the confluence of ecology and agronomy, this work provides insights on how manipulated functional biodiversity may function as an alternative strategy for pestilent herbivory management in model and green-house systems.

Owing to their extraordinary properties, carbon-based nanomaterials are gaining traction in biomedicine. Green synthesis is the cost-effective method for fabricating carbon-based nanomaterials due to its rapidity, renewable nature, and sustainability. This study emphasis on the graphene oxide (GO) reduction using a simple one-pot technique that does not require the use of toxic reducing agents. This article reports the green synthesis of reduced graphene oxide (RGO) using Hibiscus sabdariffa L. calyxes extract as the natural reducing agent. Additionally, this article also provides analysis RGO using X-ray diffraction (XRD), UV-Visible spectroscopy (UV-Vis), and Raman spectroscopy. XRD result showed that the GO peak at 11o diminished, and a new hump appear at 22o indicating that the GO is fully reduced when it is refluxed for 6 hours, at 100oC with 1:3 ratio of GO:PE. The UV-Vis data indicated absorption peak of GO (237 nm) and RGO (265 nm) at distinct locations. This finding shed new light on the enormous potential of Hibiscus sabdariffa L. calyxes extract for green GO reduction. As a result, this environmentally friendly method can help reduce dependence on chemical materials.

This study was conducted to propose the Green Economic Development Plan for Manufacturing S.M.E.s based on financial performance and operations thru Green Initiatives. The descriptive survey method used to gather data to determine the green initiative's implementation of small and medium (S.M.E.s) manufacturing enterprises. Green initiatives use as a basis for crafting a green economic development plan. Document analysis was also employed to obtain data from any available printed materials and records provided by the respondents. Such methods of gathering information used to validate data gathered from local and foreign-related literature. The observation also employed to survey the assets owned and validate any green initiatives practiced, including their implementation. The study's findings show that among the green initiatives implemented by SMMEs, which resulted in the reduction of total costs and expenses, were the proper disposal and segregation of waste materials, water management by recycling wastewater and using water-efficient equipment, natural resources, and raw materials management. SMMEs should encourage active participation and support of suppliers and customers in achieving G.E.D.'s objectives by developing incentive schemes.Furthermore, SMMEs should continue to benchmark with G.E.D. Practitioners are operating locally and abroad to adopt best greening strategies and regularly network with concerned government agencies for continuous updating on G.E.D. Initiatives that may benefit the firm. Further research may be conducted on green initiatives implemented by small and medium enterprises in other industry sectors.

The versatile one-pot green synthesis of a highly concentrated and stable colloidal dispersion of AgNPs was carried out using the self-assembled tannic acid without using any other hazardous chemicals. Tannic acid (Plant-based polyphenol) was used as a reducing and stabilizing agent for silver nitrate in a mild alkaline condition. The synthesized AgNPs were characterized for their concentration, capping, size distribution, and shape. The experimental results confirmed the successful synthesis of nearly spherical and highly concentrated (2281 ppm) AgNPs, capped with poly-tannic acid (AgNPs-PTA). The average particle size of AgNPs-PTA was found 9.90 ± 1.60 nm. The colloidal dispersion of synthesized nanoparticles was observed stable for more than 15 months in the ambient environment (25 oC, 65 % relative humidity). The synthesized AgNPs-PTA showed an effective antimicrobial activity against Staphylococcus Aureus Escherichia coli. Ag-PTA also exhibited enhanced catalytic properties. It reduces 4-nitrophenol into 4-aminophenol in the presence of NaBH4 with a normalized rate constant (Knor = K/m) of 615.04 mL·s-1·mg-1. Furthermore, AgNPs-PTA were stable for more than 15 months under ambient conditions. The unique core-shell structure and ease of synthesis render the synthesized nanoparticles superior to others, with potential for large-scale applications, especially in the field of catalysis and biomedical.

Chitosan decorated copper nanoparticles (CS/CuNPs) catalysts were synthesized via reduction methods utilizing green protocol. The CS/CuNPs hybrid catalysts were tested for the synthesis of quinoline derivatives utilizing one-pot multicomponent reaction (MCR) under ultrasonic irradiation. The best catalyst (CS/CuNPs) that provided good conversion reaction yield and high turnover frequency (TOF) was characterized using Fourier transform infrared (FTIR), Thermogravimetric analyses (TGA), X-ray diffraction (XRD), , scanning electron microscopy (SEM), transmission electron microscope (TEM) and X-ray photoelectron spectroscopy (XPS) techniques. Generalization of the scope of the proposed catalytic process was studied using different aldehydes. Excellent products yield and high TOF in even shorter reaction time (~5 min) was attained. Recyclability performance of the catalyst over five times re-use without detectable loss in product yield was recorded. The current method is green process utilizing environmentally benign catalyst and considered to be promising sustainable protocol for the synthesis of fine chemicals.

This paper studies the impact of agricultural subsidies and product certification on the use rate of green pesticides based on experimental economics. We found that agricultural subsidies effectively increased the utilization rate of green pesticides. If the agricultural subsidies raised from 20% to 100%, the green pesticides’ using rate increased by 438.51%. We also found that product certification increased the utilization rate of green pesticides by 376.16%%.The increase of agricultural subsidies is more effective than the product certification. Under a higher proportion of agricultural subsidies, farmers’ behavior will maintain “status bias”. Therefore, there are three suggestions proposed. Firstly, because of high price of green pesticides and lower production, the subsidies for agricultural materials should raise greatly to effectively improve the utilization rate of green pesticides. It is recommended that green pesticide provided free of charge in some wealthy areas. Secondly, both subsidies and product certification can improve the use rate of green pesticides. However, since the effect of agricultural subsidies is better than product certification, and farmers may have status bias. Therefore, it is recommended to give priority to the substantial increase on the proportion of agricultural subsidies, and then to product certification.

The concept of green energy is now at the forefront of development discourse, with the United Nations Sustainable Development Goals (SDGs) 7, 11, and 12 all aimed at promoting green energy consumption to combat the three planetary crises: climate change, biodiversity loss, and pollution. Similarly, issues regarding Africa’s natural resource curse have caused a stir in the growth and development literature for some time now and there is no sign that it will die out. This study, the first of its kind, simultaneously assesses the impact of green energy consumption and Africa’s natural resources rents on economic growth by applying the Feasible Generalized Least Square (FGLS) estimator and the dynamic panel models of the Pooled Mean Group (PMG) and Mean Group (MG) estimators on data from 1990 to 2020 for 24 selected African countries. The results show that green energy consumption has a short-run growth-limiting effect and a long-run growth-enhancing effect in Africa. The study also found evidence of the natural resource curse phenomenon in Africa. The study, therefore, calls for the advancement and usage of green energy for both domestic and industrial production in Africa. The study further calls for a revamp in the global tax policy to curb illicit financial activities and strengthening institutional quality for transparency and accountability in the entire value chain of natural resource management in Africa.

Sharing the same raw material, recycling and composting are in direct conflict with incineration of municipal solid waste in combined heath and power plants. Indeed, waste-to-energy plants in regions with high recycling rates import urban waste from other countries to use otherwise unused capacity, and raise revenues. Using the case of Italy’s second largest and economically most developed region, I discuss the economic viability of municipal solid waste incineration to produce electricity and heath in the context of the increasing role of electricity production from renewable energy sources as well as of the emerging mass-scale uptake of bioplastics. Four lessons and three guidelines aimed to local authorities and policy makers emerge from the present study.

Recently, cloud technology has become popular for smart societies. The Cloud technology has made dynamical network changes by enabling the construction of a logical network without building a physical network. Despite recent research on the cloud, it is necessary to study security functions for the identification of fake VNFs and the encryption of communication between entities. In this paper, we proposed an LW_PKI mechanism that detects a fake VNF and guarantees data security through mutual authentication between VNFs. To evaluate the LW_PKI, we built a MANO environment to test the performance of authentication and key generation for data security. In addition, we applied the artificial intelligence algorithm to detect abnormal behavior by using real attack data in the MANO environment. The LW_PKI guaranteed the reliability of a smart service by enhancing the security of the cloud environment.

Most of the commonly used Ionic Liquids (ILs) contain bulky organic cations with suitable anions. With our COMPLET (Concept of Melting Point Lowering due to Ethoxylation), we follow a different approach. We use simple, low-toxic, cheap and commercially available anions of the type Cx(EO)yCH2COO– to liquefy presumably any simple metal ion, independently of its charge. In the simplest case, the cation can be sodium or lithium, but synthesis of Ionic Liquids is also possible with cations of higher valences such as transition or rare earth metals. Anions with longer alkyl chains are surface active and form surface active ionic liquids (SAILs), which combine properties of ionic and nonionic surfactants at room temperature. They show significant structuring even in their pure state, i.e. in the absence of water or any other added solvent.

Background: the devastating outbreak of COVID-19 poses serious challenges for the diagnostics laboratories, which are often facing global shortage of reagents and equipment. With the aim of increasing the diagnostic throughput for SARS-CoV-2 molecular test, the purpose of this study was to validate an additional RNA extraction method respect to those already recommended by WHO and the US Centers for Disease Control and Prevention (CDC). Methods: a new protocol for RNA extraction from nasopharyngeal swab was set up, adapting the Qiagen RNeasy 96 plate and validated on a set of 100 clinical samples analyzed in parallel by Roche-Magnapure method (already recommended by CDC guidelines). Results: the internal control and target genes analysis showed a good agreement between the two extraction methods indicating that the two methods can be considered equivalent and that the RNeasy-adapted method can be applied for the SARS-CoV-2 diagnostics. The addition of this new extraction method resulted in a throughput increase for SARS-CoV-2 molecular test of about 2000 samples/month during the initial months of the pandemic emergency in which the lack of reagents for the extraction led to an insufficient sample processing throughput of the analysis of the swabs.

One of the critical tools for early detection and subsequent evaluation of the incidence of lung diseases is chest radiography. At a time when the speed and reliability of results, especially for COVID-19 positive patients, is important, the development of applications that would facilitate the work of untrained staff involved in the evaluation is also crucial. Our model takes the form of a simple and intuitive application, into which you only need to upload X-rays: tens or hundreds at once. In just a few seconds, the physician will determine the patient's diagnosis, including the percentage accuracy of the estimate. While the original idea was a mere binary classifier that could tell if a patient was suffering from pneumonia or not, in this paper we present a model that distinguishes between a bacterial disease, a viral infection, or a finding caused by COVID-19. The aim of this research is to demonstrate whether pneumonia can be detected or even spatially localized using a uniform, supervised classification.

Braskem is the only company in the world that produces green polyethylenes (HDPE – high density polyethylene and LLDPE – linear low density polyethylene) derived from the dehydration of sugarcane ethanol. Although the performance of green and fossil nominally same polyethylenes are equivalent, commercial clients may use blends of up to 51% of green polyethylenes and 49% of fossil polyethylenes and still have the right to use the I’m greenTM label which appeals to environmental conscious consumers and places these companies in a noticeable position. The Annual Income Statement - AISs from 2010, when Braskem started production of green PE, until 2018, show there was growth of revenues. Despite of the production of polyethylenes have continued stable and the number of green polyethylenes patents have decreased since 2014, the profits with the BRKM5 stocks increased. There is no transparency of how carbon credits were gained and in the AIS. Investments in securities in the Brazilian financial market (BRKM5 and carbon credits) are much more attractive than the investment in new patents, because they generate greater gains (268% increase in the average share price of BRKM5 from 2012 to 2018) and do not require large investments in R&D.

Marine invertebrates are model organisms in several areas of biological sciences, being a source of massive biological information. Although, the scientific relevance of marine invertebrates, the research with them can be limited for their tissue characteristics and troubles for the replication of physical and chemical properties of seawater. Thence, the main goal of this laboratory workflow is to provide a useful methodological approach to reduce the experimental limitations during the study of marine invertebrates. The present study describes experimental methodologies for the collection, transport, and maintenance of sessile tunicates. Also, an approach to observe and characterize, a diverse population of blood cells in marine invertebrates, by several cytological stains and electron microscopy. Lastly, suggestions and protocols to extract quality RNA from samples with high concentrations of salts, pigments, secondary metabolites, and polysaccharides. This methodological approach can be easily adapted to other marine invertebrates, moreover uses low-cost reagents and widely available laboratory equipment. Making possible the study of different types of marine animals in diverse locations.

Many classic visual monocular SLAM systems have been developed over the past decades, however, most of them will fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments based on ORB-SLAM. The article mainly concentrates on two aspects. Firstly, DLRSAC is proposed to extract static features from the dynamic scene based on awareness of nature difference between motion and static, which is integrated into initialization of DM-SLAM. Secondly, we design candidate map points selection mechanism based on neighborhood mutual exclusion to balance the accuracy of tracking camera pose and system robustness in motion scenes. Finally, we conduct experiments in the public dataset and compare DM-SLAM with ORB-SLAM. The experiments verify the superiority of the DM-SLAM.

Over the years, sustainability, impact on the environment, as well as the operation expenditure have been a major concern to the deployment of mobile cellular base stations worldwide. This is because the mobile cellular base stations are known to consume a high percentage of power within the mobile cellular network. Such energy consumption contributes to the emission of Greenhouse Gases (GHG) through the use of conventional diesel generating a set. As a result, the mobile cellular operators are faced with the dilemma of minimising the power consumption, GHG emission, and the operation cost, while improving the Quality of Service of the networks. In attempting to find a solution, this study presents the feasibility and simulation of a solar photovoltaic (PV) with battery hybrid power system (HPS) as a predominant source of power for a specific mobile cellular base station site situated in Soshanguve area of the city of Pretoria, South Africa. It also presents the technical development, showed the environmental advantage and cost benefits of using a solar PV-battery HPS to power a base station site of a 24 hrs daily load of 241.10 kWh/d and the peak load of 20.31 kW as compared to using the HPS of solar PV-diesel generating set-battery. The solar resource pattern for the city of Pretoria was collected from The National Aeronautics and Space Administration and modelled statistically. Thus, the statistical modelling done using solar radiation resource exposure characteristic patterns of Pretoria, South Africa, revealed an average annual daily solar radiation of 5.4645 Wh/m2/d and 0.605 clearness index. The simulation and the design were done using the Hybrid Optimization Model for Electric Renewables and Matlab/Simulink software. The simulation finding shows that the HPS of solar PV-battery combination has about 59.62 % saving on Net Present Cost, Levelized Cost of Energy, and 80.87% saving on Operating cost as against conventional BS powered with Gen Set-Battery.

The aim of this study was to examine brightness effect, which is the perceptual property of visual stimuli, on brain responses obtained during visual processing of these stimuli. For this purpose, brain responses of the brain to changes in brightness were explored comparatively using different emotional images (pleasant, unpleasant and neutral) with different luminance levels. Moreover, electroencephalography recordings from 12 different electrode sites of 31 healthy participants were used. The power spectra obtained from the analysis of the recordings using short time Fourier transform were analyzed, and a statistical analysis was performed on features extracted from these power spectra. Statistical findings obtained from electrophysiological data were compared with those obtained from behavioral data. The results showed that the brightness of visual stimuli affected the power of brain responses depending on frequency, time and location. According to the statistically verified findings, the distinctive effect of brightness occurred in the parietal and occipital regions for all the three types of stimuli. Accordingly, the increase in the brightness of pleasant and neutral images increased the average power of responses in the parietal and occipital regions whereas the increase in the brightness of unpleasant images decreased the average power of responses in these regions. However, the increase in brightness for all the three types of stimuli reduced the average power of frontal and central region responses (except for 100-300 ms time window for unpleasant stimuli). The statistical results obtained for unpleasant images were found to be in accordance with the behavioral data. The results also revealed that the brightness of visual stimuli could be represented by changing the activity power of the brain cortex. The main contribution of this research was to comprehensively examine brightness effect on brain activity for images with different emotional content and different frequency bands at different time windows of visual processing for different brain regions. The findings emphasized that the brightness of visual stimuli should be viewed as an important parameter in studies using emotional image techniques such as image classification, emotion evaluation and neuro-marketing.

Cyrene was evaluated for the first time as a potential sustainable mobile phase solvent in re-versed-phase chromatography. As a benign biodegradable solvent, Cyrene is an attractive re-placement to classical non-green organic chromatographic solvents such as acetonitrile and a modifier, co-eluent to known green solvents such as ethanol. Compared to ethanol, Cyrene is less toxic, non-flammable, bio-based, biodegradable and cheaper solvent. A fire safety spider Chart was generated to compare the properties of Cyrene to ethanol and show its superiority as a greener solvent. Cyrene's behaviour, advantages, and drawbacks in reversed-phase chromatography, including cut-off value, elution power, selectivity, and effect on the column, were investigated using a model drug mixture of moxifloxacin and metronidazole. A monolithic C18 (10 x 4.6 mm) column was used as a stationary phase. Different ratios of Cyrene: ethanol with an aqueous portion of sodium acetate buffer mobile phases were tested. A mobile phase consisting of Cyrene: ethanol: 0.1 M sodium acetate buffer pH 4.25 (8:13:79, v/v) was selected as most suitable mobile phase system for separating and simultaneously determining metronidazole and moxifloxacin. The greenness and whiteness of the method were evaluated using the qualitative green assessment tool AGREE and the white analytical chemistry assessment tool RGB12. Further potentials of Cyrene as a solvent or modifier in normal phase chromatography, liquid chromatography-mass spectrometry, and supercritical fluid chromatography are discussed.

Deep learning classification is the state-of-the-art of machine learning approach. Earlier work proves that the deep convolutional neural network has successfully and brilliantly in different applications such as images or video data. Recognizing and clarifying the remote sensing aspect of the earth's surface and exploit land cover and land use (LCLU). First, this article summarized the remote sensing emerging application and challenges for deep learning methods. Second, we propose four approaches to learn efficient and effective CNNs to transfer image representation on the ImageNet dataset to recognize LCLU datasets. We use VGG16, Inception-ResNet-V2, Inception-V3, and DenseNet201 models to extract features from the EACC dataset. We use pre-trained CNNs on ImageNet to extract features. For feature selection we proposed principal component analysis (PCA) to improve accuracy and speed up the model. We train our model by multi-layer perceptron (MLP) as a classifier. Lastly, we apply the multi-granularity encoding ensemble model. We achieve an overall accuracy of 92.3% for the nine-class classification problem. This work will help remote sensing scientists understand deep learning tools and apply them in large-scale remote sensing challenges

NMR spectral datasets, especially in systems with limited samples, can be difficult to interpret if they contain multiple chemical components (phases, polymorphs, molecules, crystals, glasses, etc…) and the possibility of overlapping resonances. In this paper, we benchmark several blind source separation techniques for analysis of NMR spectral datasets containing negative intensity. For benchmarking purposes, we generated a large synthetic datasbase of quadrupolar solid-state NMR-like spectra that model spin-lattice T1 relaxation or nutation tip/flip angle experiments. Our benchmarking approach focused exclusively on the ability of blind source separation techniques to reproduce the spectra of the underlying pure components. In general, we find that FastICA (Fast Independent Component Analysis), SIMPLISMA (SIMPLe-to-use-Interactive Self-modeling Mixture Analysis), and NNMF (Non-Negative Matrix Factorization) are top-performing techniques. We demonstrate that dataset normalization approaches prior to blind source separation do not considerably improve outcomes. Within the range of noise levels studied, we did not find drastic changes to the ranking of techniques. The accuracy of FastICA and SIMPLISMA degrades quickly if excess (unreal) pure components are predicted. Our results indicate poor performance of SVD (Singular Value Decomposition) methods, and we propose alternative techniques for matrix initialization. The benchmarked techniques are also applied to real solid state NMR datasets. In general, the recommendations from the synthetic datasets agree with the recommendations and results from the real data analysis. The discussion provides some additional recommendations for spectroscopists applying blind source separation to NMR datasets, and for future benchmark studies. Applications of blind source separation to NMR datasets containing negative intensity may be especially useful for understanding complex and disordered systems with limited samples and mixtures of chemical components.

Weed seedbank is an indication of future weed infestation potential of the species and is essential for making strategic planning for its sustainable management. Parthenium weed (Parthenium hysterophorus L.) is an invasive alien species threatening the biodiversity and the environment in Malaysia. A study was, therefore, conducted to estimate the soil seedbank of the weed at four soil depths of four villages of Kuala Muda, Kedah. The aim was to indicate the critical s of parthenium weed seedbank in Malaysia. Soil samples were collected from the sites using a soil core. The seeds were extracted from the soil samples with sieve shaker at the Universiti Malaysia Kelantan laboratory, Jeli Campus. The study indicates that the weed seedbank is in critical level at the area. The highest number of weed seeds (6915/m2) was found in Kg. Kongsi 6, followed by Kg. Sungai Tok Rawang (4481 seeds/m2). The top layer of soil, 0-5 cm, contained the maximum number of weed seeds (4878 seeds/m2) and a significant number of seeds (316 seeds/m2) were noticed at 10-15 cm soil depth. The study suggests the Malaysian government to take immediate action to control parthenium weed seedbank of the sites.

Graphene is a remarkable material with numerous applications. Due to its thin and lightweight design, it is ideal for a variety of applications. The synthesis of high-quality graphene in a cost-effective and environmentally friendly manner continues to be a significant challenge. Chemical reduction is considered to be the most advantageous method for preparing reduced graphene oxide (rGO). However, this process necessitates the use of toxic and harmful substances, which can have a detrimental effect on the environment and human health. Thus, to accomplish the objective, the green synthesis principle has prompted researchers worldwide to develop a simple method for green reduction of graphene oxide (GO), which is readily accessible, sustainable, economical, renewable, and environmentally friendly in nature. For example, the use of natural materials such as plants is generally considered safe. Furthermore, plants contain reducing and capping agents. The current review will focus on the discovery and application of rGO synthesis using extracts from a variety of different parts of the plant. The review aims to aid current and future researchers in their search for a novel plant extract that acts as a reductant in the green synthesis of rGO. The review aims to assist current and future researchers in their research for a novel plant extract that acts as a reductant in the green synthesis of rGO as well as their potential applications in a variety of industries.

In the search for new 2D materials beyond graphene with similar exemplary properties Stanene the new graphene relative was successfully synthesized and characterized in 2016 [14]. This new material which consists of atomically thin tin (Sn) atoms arranged in a hexagonal lattice has shown great promise in gas sensing applications in its pristine, doped and functionalized forms as evidenced by the recent research outputs following its discovery. Researchers have discovered that with its exotic properties it is highly efficient in the detection of the environmentally harmful gases like SO2, NO2, CO2, NH3 and can serve as a multifunctional gas sensor. In this focused and up-to-date review we aim to group the literature on first principles studies of stanene regards to its application for gas sensing and critically examine the success/failures of its multifunctional gas sensing properties as compared to graphene. We systematically present and discusses how structural deformations, defects and doping effect the gas sensing performance. Despite the impressive progress in the field of gas sensing with stanene shown by first principles calculations, many challenges in large scale synthesis, device fabrication and commercialization need to be addressed. The current review can help understand the current status and drawbacks of stanene and identify future directions in this field.

Global warming and climate change have led to extreme changes in climatic conditions in recent years. The Taiwan government designates the construction of the Kinmen County as low carbon islands, to promote the operation of 100 electric motorcycles and battery demonstration. This study combined with island tourism, after boarding the island, visitors can rent electric motorcycles from the passenger service center and coordinate with the island tour map to show the location of the battery exchange points, so as to facilitate the search. During the operation, the amount of electric motorcycle lease is 15,551 times, the total mileage of motor vehicle is 284,404 km, the number of battery exchange is 622 times, the lease income is about NT$900,000. To reduce carbon and economic benefits of the assessment, compared to the motorcycles (50 c.c), electric motorcycles (EM 100) can reduce the carbon emissions by 8,726 kg, reducing energy costs of NT$422,594.

The aim of this work was the study and evaluation of winery by-products in the framework of circular bioeconomy. Grape seeds and grape skins from Greek traditional Ionian Islands varieties were analyzed in an attempt to provide the appropriate basis for model development of their sustainable exploitation at a local or regional level. The wastes collected directly from the wineries immediately after the vinification process and analyzed by chromatographic and spectroscopic techniques. Also, annual production and yields were estimated. Grape seed oil quality was evaluated based on fatty acid methyl esters (FAMEs) composition. Grape skins phenolic fraction was extracted by an eco-friendly, non-toxic water-glycerol solvent system and were detected qualitatively. Also, total phenolic content (TPC) and antioxidant activity were measured. Based on estimated yields, our results demonstrate that winery by-products have the potential to promote the cyclical bioeconomy in a modern economic growth model that will reduce waste, and environmental costs as they can be reused as whole material in foods, dietary supplements, cosmetic ingredients, food colorants and preservatives.

A microwave assisted method for synthesis of 2-substituted benzimidazoles has been developed. The combination of molar ratio N-phenyl-o-phenylenediamine:benzaldehyde (1:1) using microwave irradiation and only 1% mol of Er(OTf)3 provide an efficient, environmental and mild access to a diversity of benzimidazoles under solvent-free conditions.

One of the most important component of a Geographic Information Retrieval (GIR) is the geoparser, which performs toponym recognition, disambiguation, and geographic coordinate resolution from unstructured text domain. However, news articles which report several events across many place references mentioned in the document is not yet adequately modeled by regular geoparser types where the scope of resolution is either on toponym-level or document-level. The capacity to detect multiple events, geolocate its true locations and coordinates along with their numerical arguments are still missing from modern geoparsers, much less in Indonesian news corpora domain. We propose a novel type event geoparser which integrates an ACE-based event extraction model and provides precise event-level scope resolution. The geoparser casts the geotagging and event extraction as sequence labeling and uses Conditional Random Field with keywords feature obtained using Aggregated Topic Model as a semantic exploration from large corpus, which eventually increases the generalizability of the model. The geoparser also use Smallest Administrative Level feature along with Spatial Minimality-derived algorithm to improve the identification of Pseudo-location entities, resulting 19.4% increase for weighted F1 score. As a side effect of event extraction, the geoparser also extracts various numerical arguments and able to generate thematic choropleth map from a single news story.

This study assesses Human Thermal Comfort in two selected areas: a Green Infrastructure (GI) area represented by a garden and a high-rise building area, in the Central Business District (CBD) of Melbourne, Australia. Three-dimensional microclimatic modelling software, ENVI-met version 4 was used to simulate the microclimate. The indices of Predicted Mean Vote (PMV), Physiological Equivalent Temperature (PET) and Universal Temperature Climate Index (UTCI) were used to quantify the level of thermal comfort in the research areas. The simulation results showed that at midday, the difference in temperature between the garden area and the high-rise building area was approximately 1°C. Increasing temperatures at midday led to a change in the level of thermal comfort for both the areas, even though it was not significant. In general, the thermal perception in the GI area was slightly ‘cooler’ than in the high-rise building area. The results of the study indicated the important role of GI in improving the thermal comfort in urban areas.

The objective to fast-track the mapping and registration of large numbers of unrecorded land rights globally, leads to the experimental application of Artificial Intelligence (AI) in the domain of land administration, and specifically the application of automated visual cognition techniques for cadastral mapping tasks. In this research, we applied and compared the ability of rule-based systems within Object Based Image Analysis (OBIA), as opposed to human analysis, to extract visible cadastral boundaries from Very high resolution (VHR) World View-2 image, in both rural and urban settings. From our experiments, machine-based techniques were able to automatically delineate a good proportion of rural parcels with explicit polygons where the correctness of the automatically extracted boundaries was 47.4% against 74.24% for humans and the completeness of 45% for machine, as against 70.4% for humans. On the contrary, in the urban area, automatic results were counterintuitive: even though urban plots and buildings are clearly marked with visible features such as fences, roads and tacitly perceptible to eyes, automation resulted in geometrically and topologically poorly structured data, that could neither be geometrically compared with human digitised, nor actual cadastral data from the field. These results provide an updated snapshot with regards to the performance of contemporary machine-drive feature extraction techniques compared to conventional manual digitising.

Enormous quantities of softwood and hardwood tree bark are generated yearly in the pulp and woodworking industry. Chemical compounds which can be found in bark extracts have important biological properties and therefore a high potential for using in the production of special formulations. In the present study, extraction of Picea abies bark with organosolv solvents was investigated to achieve a high yield of desirable compounds. For the extraction four different solvent ratios of ethanol and water were applied. The temperature range of extraction was set between 40 and 100 °C and stirring velocity of 400 rpm. Extractions were performed with a solid/liquid ratio of 1:20. Yields of phenolics, flavonoids and tannins were determined using gallic acid for total phenolic content (TPC), quercetin for total flavonoid content (TFC) and tannic acid for total tannins content (TTC) as calibration compounds. Qualitative analysis of phenolic constituents was performed after their derivatization, by gas chromatography coupled with mass spectrometry identification. The total yield of bark extract of 14.75 wt.% was achieved by using an ethanol/water ratio of 50% (v/v) and a temperature of 100 °C. Gas chromatography results show 9 aromatic carboxylic acids as phenolic acids and quercetin and (+)-catechin as flavonoid compounds. Highest concentrations of TPC = 3.21 mg gallic acid equivalent/g, TCF = 0.62 mg quercetin equivalent/g and TTC = 0.84 tannic acid equivalent/g were determined at the same process conditions by photometric method. This study determined the conditions for organosolv extraction of useful compounds and suggests that some of extractives, e.g., taxifolin and rhamnetin presented in the spruce bark extracts, have antiviral (SARS-CoV-2) effects. Therefore, this warrants further evaluation of the antiviral properties of spruce bark constituents.

Public access to high quality green environments has become a key issue for city managers and a matter of environmental justice. Remnants of natural ecosystems allow citizens a direct contact with nature, but conversely the presence of people contributes further to the existing disturbances. Urban pressures on ecosystem remnants may act to favour the expansion of some invasive species in cities. Whilst the negative impacts of invasive species on ecosystem function is well documented little is known how invasive species influence the use of green spaces by people. Here, we examined one of the few remnants of urban riparian forests in Europe, the Vistula river valley in Warsaw which has recently become an attractive recreation site. Despite their high ecological value, the poplar and willow forests have been increasingly taken over by the invasive tree species Acer negundo. We examined the status of the invasion process and the relationship between recreational ecosystem services and the characteristics of the tree stands – tree species, tree density and age and NDVI values. We found the willow forest to be more susceptible to invasion by A. negundo than the poplar forest, which was revealed in significantly higher share of the maple individuals and their greater volume per unit area. Presence of A. negundo affected biodiversity resulting in decreased undergrowth density and number of species. The use intensity by the public, assessed on the basis of trampling intensity and the density of existing informal tracks, were negatively correlated to the presence of A. negundo. This study highlights the need to integrate invasive species management into green infrastructure planning and management.

The purpose of this paper is to analyze how Green Business Models (BMs) established by small and medium enterprises (SMEs) can incorporate product and process decarbonization in their components (value proposition, creation and capture) and to what extent this incorporation is affected by SME size. We use a database comprising 1,161 observations of SMEs, 466 in 2014 and 695 in 2016. The results show that SMEs’ value propositions give an intermediate valuation to both legally required and voluntary reduction of environmental impact, irrespective of SME size and the year analyzed. Regarding value creation, SMEs adopt practically no environmental practices, and there are significant differences according to size, with more difficulties than advantages stemming from small size. The study also shows that such environmental practices are not effective in reducing carbon. This diagnosis indicates that SMEs need help from the administration if they are to play a key role in the process of transformation toward a low-carbon economy. Legislative actions involving harsher environmental protection measures might help shape value propositions that place greater importance on reducing environmental impact, whereas training actions on available environmental techniques, promotion of research on how to adapt such techniques to SMEs and the development of specific practices for SMEs might enhance environmental value creation and capture in their BMs.

The present work encompasses an application-oriented perspective to the possible employment of gold nanoparticles as nanomedicine in cancer therapeutics. The rationale of the work lies in the growing needs for assessment of advanced alternative treatment of cancer employing functionalized nanoparticles as nanomedicine. Gold nanoparticles fabricated via green chemistry methods by leaves of a time-honored medicinal plant, Piper betle were ascertained for their synthesis and properties under the umbrella of characterization of nanoparticles, through various techniques like UV-vis spectroscopy, FTIR spectroscopy, X-ray diffraction, and scanning electron microscopy. The cytotoxicity assay of well-characterized gold nanoparticles was monitored against lung cancer cell line (A549) by metabolic and imaging assays. MTT assay or the metabolic assay was performed for a range of nanoparticles’ concentrations. The results were promising and proved to be a leading-edge venture, envisaging the possibility of gold nanoparticles for cancer therapeutics.

The hygrothermal transfer is very important for the design of a building envelope for thermal comfort and economic and energy analysis of the building envelope. The applications of various materials in building envelope have been studied extensively. The study presents several models for the hygrothermal transfer for various building walls. Several energy and mass conservation equations with different boundary conditions and input considerations were presented in this paper for concrete, bricks and wooden walls. The effect of hysteresis was ignored in developing most model equations, while few considered flow pattern of fluid through the wall surfaces. Due to the flexibility of Luikov models, it formed the basis for modelling the coupled heat and mass transfer for porous material independent of hygroscopic nature with different boundary conditions defined according to the geometry and orientations. The influence of type of wall, orientation, thickness, the density of the material and climatic variations on the temperature and moisture evolutions within the building materials was more pronounced. Literature, presenting imaging models using imagery software like COMSOL multi-physics, CFD etc. were scarce considering that microscopic imagery is now deployed to measure the heat and moisture evolution in materials. Future models should include shrinkage or expansion influence on the fibrous material like wood due to their behaviour under environmental condition.

Public green and open spaces fulfil various social, ecological, economic, and aesthetic roles, which complement each another, but can also compete with one another. COVID-19 pandemic catalysed multiple societal changes, including citizens’ perception, needs and expectations posed towards urban green spaces. This article discusses the extent to which the temporally and geographically changed patterns of experiencing these natural spaces also influenced users’ perception and behaviour as well as their appreciation of the conservation areas. The study is based upon two surveys carried out in the greater metropolitan region of Vienna, the capital city of Austria. A quantitative survey (representative online panel) among Viennese population (n=1012), as well as qualitive interviews with experts responsible for conservation areas, administrators of federal parks, along with NGOs representatives were carried out in spring and summer 2021. Our study shows the changed use of urban and suburban large green spaces and conservation areas: first, from the perspective of those responsible for the areas as well as the visitors. Both perspectives supplement one another. They highlight also changed perception of urban citizens towards green spaces during COVID-19 pandemic. An increased importance of time spent in nature (68%) and possibility to visit large green areas (67%) was reported by Viennese citizens. Also, higher recognition of green spaces located close to home was observed among 69% of the respondents. Thus, the presented study contributes to the ongoing international discussion on the transition of societal needs and its effects on urban green spaces induced by the pandemic. Presented results deliver solid arguments highlighting the need of urgent transformation towards a more sustainable, resilient and healthy urban space.

The effectiveness of forest resources depends on the comprehensiveness and rationality of their consumption and processing into finished products. This article discusses a problem of utilising solid fir wood greenery residues generated during the industrial production of essential oils. Bioconversion is considered to be the most promising utilization method. The objective of this research was to study the chemical composition of bioconversion products of fir wood greenery-based substrates. The РР-3.2 strain of Pleurotus pulmonarius (Fr.) Quél was used as a biodestructor. In the process of bioconversion, the contents of polysaccharides and lignin substances is reduced to 38 and 28 % respectively. Up to 20 % of protein accumulates in bioconversion products of fir wood greenery. The amount of nucleic acids is not more than 1.5 g per 1 kg, the contents of heavy metals, such as mercury, cadmium, arsenic, lead, do not exceed maximum permissible concentration standards. The substrate weight loss reaches 15 %. When fallen leaves and post-extraction poplar bud residues are added to the substrate, the substrate-destroying activity of fungi rises, as well as the protein content increases by 3 %. The digestibility of products as a result of bioconversion increases 1.6–2.8 times depending on the substrate composition. The obtained data enable to recommend post-fermented substrates based on fir wood greenery and balsam poplar biomass for use as a protein feed additive.

As the world is striving to recover from the shockwaves triggered by the Covid-19 crisis, all hands are needed on deck to transition towards a green recovery and make peace with nature as prerequisites of a global sustainable development pathway. In this paper, we examine the blockchain hype and the gaps in data and tools to build promising use cases for blockchain technology to accelerate global efforts in the decade of action towards achieving the SDGs. We attempted to break the hype-cycle portraying blockchain’s superiority by navigating a rational blockchain use case development approach. By prototyping an SDG Acceleration Scorecard to use blockchain-enabled solutions as SDG accelerators, we aim to provide useful insights towards developing an integrated approach that is fit-for-purpose to guide organizations and practitioners in their quest to make informed decisions to design and implement blockchain-backed solutions as SDG accelerators. Acknowledging the limitations in prototyping such tools, we believe these are minimally viable products and should be considered as living tools that can further evolve as the blockchain technology is getting mature, its pace of adoption increasing, and its lessons learned, good practices and standards widely shared and internalized by teams and organizations working on innovation for development.

This scoping study aims to explore the relationships between urban green spaces (UGSs) and cancer. We followed the PRISMA extension for scoping reviews (protocol published in 2018). Eligibility criteria for papers were: 1) to be concerned with UGSs, 2) reporting effects of UGSs on cancer-related outcomes including direct or indirect measures, 3) reporting randomized controlled trials, prospective cohort studies, case studies, observational studies, non-comparative studies, 4) in English or French. The search covered primary studies in the published and unpublished (grey) literatures searching by hand and electronic databases (MEDLINE, Green File, CINAHL and ScienceDirect). Among 1703 records screened by two reviewers independently, 29 were included for qualitative synthesis. We classify the cancers concerned and the effects reported i.e. protective effect, risk or without association. The most investigated cancers are bladder, breast and lung cancer. Our study also identified contributing factors and their mediating effects between UGSs and cancer. Results highlight the wide variety of possible mediating factors between the use of green spaces and cancer occurrence, remission and/or prevention. Knowledge gaps and future research perspectives should be oriented to qualitative research on protective factors, the role of mental health in recovering from cancer and health inequalities.

Green ICT has received significant attention in organizations to reduce global warming since last decade. Several maturity models have been proposed for tracking green ICT practices in organizations. Current literature shows that SMEs around the world try to follow some common strategies such as virtualization, consolidation of devices, energy efficiency and disposal of ICT equipment for greening ICT. The increasing interest for green ICT practices in organizations is not only due to the desire to attain environment-friendly atmosphere but mainly because of sustaining business goals such as cost reduction, competitive advantages and stakeholders’ pressure. Nevertheless, due to the lack of green ICT knowledge, organizations, specially SMEs, tend to ignore those practices. Therefore, this research proposes a framework that provides combination of existing green and sustainable ICT maturity models by mapping them with the strategies the businesses are already following. Out of this framework, a web application has been developed that provides questionnaire for SMEs to identify their present situation of green ICT practices and guidelines for improvement. The results have been analyzed by testing the application in some SMEs of Finland and Bangladesh. Finally, a survey has been conducted to attain SMEs’ perception about the possibility of sustainable development of businesses through this application.

This article addresses the question why initiatives in the field of green business and sustainable development often fail. Therefore, it dismantles some typical patterns of failure and shows – as a case study – how these patterns can be challenged through an innovative educational concept: the green business and sustainable development school. The applied methodology is a real-life project that is designed through blended, interdisciplinary elements from business model canvas, Theory U, participation and design thinking. The results of the school initiative are discussed and evaluated by four distinctive stakeholder groups and outline the school’s supporting potential to overcome typical patterns of failure by the younger generation in the future. This article concludes with ideas to enhance the school concept reaching out to even more stakeholder-groups to increase its reliability and viability.

Natural rivers in urban areas bear significant potential to provide ecosystem services for the surrounding inhabitants. However, surface sealing by houses and street networks, urban drainage, disposal of waste and wastewater resulting from advancing urbanization usually lead to the deterioration of urban rivers and their riparian areas. This ultimately damages their ability to provide ecosystem services. This paper presents an innovative methodology for a rapid and low-cost assessment of the ecological status of urban rivers and riparian areas in developing countries under data scarce conditions. The methodology uses a combination of field data and freely available high-resolution satellite images to assess three ecological status categories: river hydromorphology, water quality, and riparian land cover. The focus here is on the assessment of proxies for biophysical structures and processes representing ecological functioning that enable urban rivers and riparian areas to provide ecosystem services. These proxies represent a combination of remote sensing land cover- and field-based indicators. Finally, the three ecological status categories are combined to quantify the potential of different river sections to provide regulating ecosystem services. The development and application of the methodology is demonstrated and visualized for each 100 m section of the Pochote River in the City of León, Nicaragua. This spatially distributed information of the ecosystem service potential of individual sections of the urban river and riparian areas can serve as important information for decision making regarding the protection, future use, and city development of these areas, as well as the targeted and tailor-made development of nature-based solutions such as green infrastructure.

A study has been carried out on Ta and Nb recovery by liquid-liquid extraction process using 4-methylacetophenone (4-MAcPh) as organic phase. The 4-MAcPh was compared to methylisobutylketone (MIBK) with respect to extraction efficiencies (kD values) at different concentrations of H2SO4 in the aqueous phase. The results showed a similar extraction of Nb for both solvents. However, for Ta extraction efficiency is increased by a factor of 1.3 for 4-MAcPh. In addition, the MIBK solubilized completely after 6 mol L-1 of H2SO4 against only a loss of 0.14 to 4% for 4-MAcPh between 6 and 9 mol L-1 of H2SO4. The potential of 4-MAcPh has also been studied to selectively recover Ta from a model capacitor waste solution. The results showed a selectivity for Ta in the presence of impurities such as Fe, Ni, Mn. The 4-MAcPh also presents the advantage of having physicochemical properties adapted to its use in liquid-liquid extraction technologies such as mixer-settlers.

The production of instant green tea requires hot-water extraction, which is time consuming and contributes to losses in aromatic compounds. In this study, an ultrasonic-assisted technology was used to improve the extraction efficiency of green tea, thereby shortening extraction time from 45 to 15 min. In pure water, the dissolution of caffeine and theanine did not change significantly, but total catechin dissolution increased by 0.23 mg/mL and total tea polyphenol dissolution decreased by 3.2 mg/mL. In 76.2% ethanol, the dissolution of caffeine and theanine did not change significantly, but total catechin dissolution increased by 1.57mg/mL and total tea polyphenol dissolution decreased by 1.5 mg/mL. Additionally, we used microwave-assisted technology to further improve the extraction efficiency of green tea, which shortened the extraction time to 2 min. However, the extraction rate remained unchanged. In pure water, the dissolution of caffeine and theanine did not change significantly, but the dissolution of total catechins increased by 0.41 mg/mL and the dissolution of tea polyphenols decreased by 2.9 mg/mL. Ultrasonic treatment increased the proportion of 3-hydroxybutan-2-one, (5S)-5-(hydroxymethyl)oxolan-2-one and 2-phenylethanol, which were the main aroma compounds in tea. Microwave treatment changed the aroma compounds in tea, causing losses in aroma compounds with low boiling point and maintaining (5S)-5-(hydroxymethyl)oxolan-2-one. The taste and aroma of instant green tea improved based on sensory evaluation results.

Urban stormwater runoff is a significant source of pollutants into surface water bodies. One such pollutant, 1H-benzotriazole, is a persistent, recalcitrant trace organic contaminant commonly used as a corrosion inhibitor in airplane deicing processes, automobile liquids, and engine coolants. This study explored the removal of 1H-benzotriazole from stormwater using bench-scale biofilter mesocosms planted with California native sedge, Carex praegracilis, over a series of three storm events and monitoring period. Benzotriazole metabolites glycosylated benzotriazole and benzotriazole alanine were detected and benzotriazole and glycosylated benzotriazole partitioning in the system were quantified. With a treatment length of seven days, 97.1% of benzotriazole was removed from stormwater effluent from vegetated biofilter mesocosms. Significant concentrations of benzotriazole and glycosylated benzotriazole were observed in the C. praegracilis leaf and root tissue. Additionally, a significant missing sink of benzotriazole developed in the vegetated biofilter mesocosms. This study suggests that vegetation may increase the operating lifespan of bioretention basins by enhancing degradation of dissolved trace organic contaminants, thus increasing the sorption capacity of the geomedia.

Coffee is rich in phenolic acids, such as caffeic acid and chlorogenic acid (CGA). Polyphenol-rich diets have been shown to reduce the risk of metabolic syndrome (MeTS). Background and Objectives: This systematic review and meta-analysis discusses the effects of coffee consumption and its dose-response on MeTS parameters. Materials and Methods: PubMed and Scopus® were searched for relevant articles published between 2015 and 2020. This review focused on randomised controlled trials (RCTs) investigating the effect of coffee consumption on anthropometric measurements, glycaemic indices, lipid profiles, and blood pressure. Data from relevant studies were extracted and analysed using random, fixed, or pooled effects models with 95% confidence intervals (CIs). Results: Green coffee extract (GCE) supplementation (180 to 376 mg) was found to reduce waist circumference (weighted mean difference (WMD) = -0.39; 95% CI: -0.68, -0.10), triglyceride levels (WMD = -0.27; 95% CI: -0.43, -0.10), high-density lipoprotein-cholesterol levels (WMD = 0.62; 95% CI: 0.34, 0.90), systolic blood pressure (WMD = -0.44; 95% CI: -0.57, -0.32), and diastolic blood pressure (WMD = -0.83; 95% CI: -1.40, -0.26). Decaffeinated coffee (510.6 mg) reduced the fasting blood glucose levels (WMD = -0.81; 95% CI: -1.65, 0.03). The meta-analysis showed that the intake of GCE containing 180 to 376 mg of CGA (administered in a capsule) and liquid decaffeinated coffee containing 510.6 mg of CGA improved the MeTS outcomes in study participants. Conclusions: The findings of the review suggested that the effect of coffee on MeTS parameters varies depending on the types and doses of coffee administered. A more detailed RCT on specific coffee doses (with adjustment for energy and polyphenol intake) and physical activity is needed to further confirm the observed outcomes.

A renewable cyclic monoterpene obtained from citrus peel, limonene is widely used as a fra-grance, nutraceutical ingredient, antibacterial, biopesticide, and green extraction solvent. Indus-trial demand largely exceeds supply. After reviewing recent advances in the recovery of limonene from citrus peel and residues with a particular attention to benign-by-design extractive processes, we focus on the latest results in its dehydrogenation to p-cymene via heterogeneous catalysis.

The utilization of eco-fonts for office printing is a sustainable, “green” printing concept, which has obvious economic benefits. As a result, it has a significant effect on environmental sustainability. This practice's fundamental problem is the decreased quality of text printed using eco-fonts compared to those printed with regular fonts. The aim of this research is eco-font efficiency estimation, i.e. determination of toner usage reduction level of inkjet-printed documents typed with this font type, as well as estimation of the extent humans perceive differences between text printed with eco-font and the one printed by its “non-eco“ equivalent. Combining the instrumental measuring method and digital image analysis, it was found that this simple principle (eco-font utilization) enables substantial toner usage reduction for an inkjet printing system. At the same time, a visual test showed that the visual experience of text printed using eco-font was sufficient. In addition, awareness of the benefits that eco-font utilization brings, change users’ attitude towards eco-font quality. The concept of removing the black pixel from this commonly used Thai font has a great potential for the sustainability printing process, and this simple solution could be applied to other languages as part of the GIT campaign.

Simultaneous extraction of trypsin inhibitors and soy isoflavones from soybean meal was investigated using the non-destructive phytochemical extraction process, namely aqueous micellar system. The ethoxylated aliphatic alcohols Genapol X-080, Tergitol 15-S-7, and Tergitol 15-S-9, all non-toxic and biodegradable surfactants, were assessed as potential extractants. A Box-Behnken multifactorial design with the application of the Derringer desirability was used to determine the conditions that maximized the trypsin inhibitors and isoflavone extraction while minimizing the protein extraction. The optimum condition of 5% m/m of surfactant in 50 mM aqueous sodium citrate solution pH 4.5, at 45 °C for 45 min, was established for the three surfactants. The novel methodology would allow the extraction of the main soybean antinutritional factors, trypsin inhibitors, and the valuable isoflavones, preserving the nutritional quality of the treated material. This represents a sustainable alternative methodology for industrial purposes due to its low cost, biodegradability, non-toxicity, and easy scaling up.

Green credit policy as an important tool to guide China's sustainable economic development, how to effectively play the function of capital deployment and improve the efficiency of industrial green innovation is an important issue facing the construction of ecological civilization. This paper uses China's Green Credit Guideline introduced in 2012 as a quasi-natural experiment , based on relevant panel data of industries from 2007 to 2018, uses the Super-SBM model including non-expected output to measure the green innovation efficiency of 35 industries in China, and constructs the PSM-DID model to explore how green credit policy impact on the green innovation efficiency of heavily polluted industries, the results show that : green credit policy significantly contributes to green innovation efficiency of heavily polluted industries with a lag. Further study finds that green credit policy pushes heavily polluted industries to improve green innovation efficiency by increasing financing cost and R&D investment; meanwhile, the heterogeneity test shows that the higher the state-owned share of industry, the greater the promoted effect of green credit policy on green innovation efficiency of heavily polluted industries. Finally, in order to accelerate the implementation of green credit policy and promote the green innovation efficiency of heavily polluted industries, relevant countermeasures are proposed from three aspects: banks, enterprises and government.

Global temperature rise due to hydrocarbon gases emission that are produced by generating the electrical power has a great attention by the researchers to reduce it till zero emission is successfully achieved. Sustainable energy source such as solar energy, wind, hydro-energy and sea wave energy are focal areas to replace the fossil fuel by clean energy. In this article, daylight is used to minimize the power consumption that required for indoor lighting using electric roller blind. Smart controller is designed to adjust the position of the roller blind stepper motor, and hence, adjust the roller blind opening, based on the preset light intensity, to achieve precise utilization of daylight inside the room. If the desired Lux is not achieved for any reason, the smart controller adjusts the LED circuit current to boost the light intensity to achieve precisely the desired Lux. Comprehensive test cases using MATLAB-Simulink is carried out to verify the performance of the proposed smart controller. Techno-economic analysis is introduced to evaluate the benefits of installing the controller. Summary and recommendation are given at the end.