Search results for: machine and plant engineering

Authors: Reza Dehghani Bidgoli

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Information on different rangeland plants’ nutritive values at various phonological stages is important in rangelands management. This information helps rangeland managers to choose proper grazing times to achieve higher animal performance without detrimental effects on the rangeland vegetations. Effects of various plant parts’ phonological stages and vegetation types on reserve carbohydrates and forage quality indicators were investigated during the 2009 and 2010. Plant samples were collected in a completely randomized block (CRB) design. The species included, grasses (Secale montanum and Festuco ovina), forbs (Lotus corniculatus and Sanguisorba minor), and shrubs (Kochia prosterata and Salsola rigida). Aerial plant parts’ samples were oven-dried at 80oC for 24 hours, then analyzed for soluble carbohydrates, crude protein (CP), acid detergent fiber (ADF), dry matter digestible (DMD), and metabolizable energy (ME). Results showed that plants at the seedling stage had more reserve carbohydrates and from the three vegetation types (grass, forbs, and shrub), forbs contained more soluble carbohydrates compared to the other two (grasses and shrubs). Differences in soluble carbohydrate contents of different species at various phonological stages in 2 years were statistically significant. The forage quality indicators (CP, ADF, DMD, and ME) in different species, in different vegetation types, in the 2 years were statistically significant, except for the CP.

Keywords: grazing, soluble carbohydrate, protein, fiber, metabolizeable energy

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Authors: Tigist Girma Kidane, Yalew Dessalegn Asfaw

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Abstract: The current investigation aims to measure the longitudinal and transversal three-point bending tests of bamboo fibres polypropylene composites (BFPPCs) for the application of the automobile industry. Research has not been done on the properties of Ethiopian bamboo fibres for the utilization of composite development. The samples of bamboo plants have been harvested in 3–groups of age, 2–harvesting seasons, and 3–regions of bamboo species. Roll milling machine used for the extraction of bamboo fibres which has been developed by the authors. Chemical constituents measured using gravimetric methods. Unidirectional bamboo fibres prepreg has been produced using PP and hot press machine, then BFPPCs were produced using 6 layers of prepregs at automatic hot press machine. Age, harvesting month, and bamboo species have a statistically significant effect on the longitudinal and transverse flexural strength (FS), modulus of elasticity (MOE), and failure strain at α = 0.05 as evaluated by one-way ANOVA. 2–yrs old of BFPPCs have the highest FS and MOE, whereas November has the highest value of flexural properties. The highest to the lowest FS and MOE of BFPPCs has measured in Injibara, Mekaneselam, and Kombolcha, respectively. The transverse 3-point bending test has a lower FS and MOE compared to the longitudinal direction. The chemical constituents of Injibara, Mekaneselam, and Kombolcha have the highest to the lowest, respectively. 2-years old of bamboo fibres has the highest chemical constituent. The chemical constituents improved the flexural properties. Bamboo fibres in Ethiopia can be relevant for composite development, which has been applied in the area of requiring higher flexural properties.

Keywords: age, bamboo species, flexural properties, harvesting season, polypropylene

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Ime R. Udotong, Justina I. R. Udotong, Ofonime U. M. John

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Brass terminal, one of the several crude oil and petroleum products storage/handling facilities in the Niger Delta was built in the 1980s. Activities at this site, over the years, released crude oil into this 3 m-deep, 1500 m-long canal lying adjacent to the terminal with oil floating on it and its sediment heavily polluted. To ensure effective clean-up, three major activities were planned: Site characterization, bioremediation pilot plant construction and testing and full-scale bioremediation of contaminated sediment/bank soil by land farming. The canal was delineated into 12 lots and each characterized, with reference to the floating oily phase, contaminated sediment and canal bank soil. As a result of site characterization, a pilot plant for on-site bioremediation was designed and a treatment basin constructed for carrying out pilot bioremediation test. Following a designed sampling protocol, samples from this pilot plant were collected for analysis at two laboratories as a quality assurance/quality control check. Results showed that Brass Canal upstream is contaminated with dark, thick and viscous oily film with characteristic hydrocarbon smell while downstream, thin oily film interspersed with water were observed. Sediments were observed to be dark with mixture of brownish sandy soil with TPH ranging from 17,800 mg/kg in Lot 1 to 88,500 mg/kg in Lot 12 samples. Brass Canal bank soil was observed to be sandy from ground surface to 3m, below ground surface (bgs) it was silty-sandy and brownish while subsurface soil (4-10m bgs) was sandy-clayey and whitish/grayish with typical hydrocarbon smell. Preliminary results obtained so far have been very promising but were proprietary. This project is considered, to the best of technical literature knowledge, the first large-scale on-site bioremediation project in the Niger Delta region, Nigeria.

Keywords: bioremediation, contaminated sediment, land farming, oily sludge, oil terminal

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Authors: Carola Cappa

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Chickpea cooking water (known as aquafaba, AF) is a “waste” product having interesting technological properties exploitable for sustainable plant-based food applications that can encounter a larger consumers demand. Different process conditions to obtain AF were defined; the addition of hydrocolloid (i.e., guar gum) and lactic acid to improve the techno-functionalities of aquafaba was explored, and the effects of these ingredients on the foaming properties and the quality of plant-based target confectionery products were investigated. Meringues having a solid foam structure and a simple formulation (i.e., foaming agent and sugar) and chocolate mousse were chosen as target foods. The effects of the sugar particle size reduction on the empirical and fundamental rheological properties of the foaming agent and of the mousse were evaluated. The treatment did not significantly change the viscosity of the system, while the overrun and foam stability were affected by sugar particle size, and mousse with coarse sugar was characterized by a higher consistency, confirming the importance of the particle size of the ingredients on the texture of the final product. This study proved that AF, a recycled “waste” product, possesses interesting techno-functionalities properties further enhanced by adding lactic acid and modulable according to ingredient particle size; these AF results are useable for plant-based food applications.

Keywords: foaming properties, foam stability, foam texture, particle size, acidification, aquafaba

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Authors: I. Ahumada, L. Ascar, C. Pedraza, J. Montecino

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It has been found that the addition of biosolids to soil is beneficial to soil health, enriching soil with essential nutrient elements. Although this sludge has properties that allow for the improvement of the physical features and productivity of agricultural and forest soils and the recovery of degraded soils, they also contain trace elements, organic trace and pathogens that can cause damage to the environment. The application of these biosolids to land without the total reclamation and the treated wastewater can transfer these compounds into terrestrial and aquatic environments, giving rise to potential accumulation in plants. The general aim of this study was to evaluate the bioavailability of bisphenol A (BPA), and 17 α-ethynyl estradiol (EE2) in a soil-biosolid system using wheat (Triticum aestivum) plant assays and a predictive extraction method using a solution of hydroxypropyl-β-cyclodextrin (HPCD) to determine if it is a reliable surrogate for this bioassay. Two soils were obtained from the central region of Chile (Lo Prado and Chicauma). Biosolids were obtained from a regional wastewater treatment plant. The soils were amended with biosolids at 90 Mg ha-1. Soils treated with biosolids, spiked with 10 mgkg-1 of the EE2 and 15 mgkg-1 and 30 mgkg-1of BPA were also included. The BPA, and EE2 concentration were determined in biosolids, soils and plant samples through ultrasound assisted extraction, solid phase extraction (SPE) and gas chromatography coupled to mass spectrometry determination (GC/MS). The bioavailable fraction found of each one of soils cultivated with wheat plants was compared with results obtained through a cyclodextrin biosimulator method. The total concentration found in biosolid from a treatment plant was 0.150 ± 0.064 mgkg-1 and 12.8±2.9 mgkg-1 of EE2 and BPA respectively. BPA and EE2 bioavailability is affected by the organic matter content and the physical and chemical properties of the soil. The bioavailability response of both compounds in the two soils varied with the EE2 and BPA concentration. It was observed in the case of EE2, the bioavailability in wheat plant crops contained higher concentrations in the roots than in the shoots. The concentration of EE2 increased with increasing biosolids rate. On the other hand, for BPA, a higher concentration was found in the shoot than the roots of the plants. The predictive capability the HPCD extraction was assessed using a simple linear correlation test, for both compounds in wheat plants. The correlation coefficients for the EE2 obtained from the HPCD extraction with those obtained from the wheat plants were r= 0.99 and p-value ≤ 0.05. On the other hand, in the case of BPA a correlation was not found. Therefore, the methodology was validated with respect to wheat plants bioassays, only in the EE2 case. Acknowledgments: The authors thank FONDECYT 1150502.

Keywords: emerging compounds, bioavailability, biosolids, endocrine disruptors

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Authors: David Rafetseder, Walter Bauer, Florian Poltschak, Wolfgang Amrhein

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A flat double-stator linear induction machine (DSLIM) with a short squirrel-cage mover is designed for high thrust force at moderate speed < 5m/s. The performance and motor parameters are determined on the basis of a 2D time-transient simulation with the finite element (FE) software Maxwell 2015. Design guidelines and transformation rules for space vector theory of the LIM are presented. Resulting thrust calculated by flux and current vectors is compared with the FE results showing good coherence and reduced noise. The parameters of the equivalent circuit model are obtained.

Keywords: equivalent circuit model, finite element model, linear induction motor, space vector theory

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Rishabh Ambavanekar

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Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

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Authors: Nada Bezić, Valerija Dunkić, Rušćić Mirko

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Astragalus monspessulanus L. ssp. illyricus (Bernhardt) Chater is endemic species of Fabaceae family and belongs to hemicryptophyte. This plant grows wild in the sub-Mediterranean area. We analyzed the composition of the essential oil of stems and leaves of A. monspessulanus L. ssp. Illyricus, collected in Tijarica, near Split, Croatia. Water distilled essential oils from aerial parts of investigation plant have been analysed by GC and GC/MS using VF-5ms capillary column. The total yield of oil was 0.08%, based on dry weight of samples. Thirty-eight compounds were representing 88.5% of the total oil. This essential oil was characterized by a high concentration of cis-myrtanol (20.5%), geranyl acetate (9.6%) and phytone (6.6%). Previous research in the species A. monspessulanus have included flavoalkaloids and flavonoids composition. The present study gives additional knowledge about secondary metabolites contents on the genus Astragalus.

Keywords: essential oil, isovaleric acid, Valeriana tuberosa, geranyl acetate, phytone

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Authors: Soumya Sajjan

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Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

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Authors: Emily Wood, James K. Westphal, Itamar Lerner

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Background: Polysomnography (PSG) recordings are regularly used in research and clinical settings to study sleep and sleep-related disorders. Typical PSG studies are conducted in professional laboratories and performed by qualified researchers. However, the number of sleep labs worldwide is disproportionate to the increasing number of individuals with sleep disorders like sleep apnea and insomnia. Consequently, there is a growing need to supply cheaper yet reliable means to measure sleep, preferably autonomously by subjects in their own home. Over the last decade, a variety of devices for self-monitoring of sleep became available in the market; however, very few have been directly validated against PSG to demonstrate their ability to perform reliable automatic sleep scoring. Two popular mobile EEG-based systems that have published validation results, the DREEM 3 headband and the Z-Machine, have never been directly compared one to the other by independent researchers. The current study aimed to compare the performance of DREEM 3 and the Z-Machine to help investigators and clinicians decide which of these devices may be more suitable for their studies. Methods: 26 participants have completed the study for credit or monetary compensation. Exclusion criteria included any history of sleep, neurological or psychiatric disorders. Eligible participants arrived at the lab in the afternoon and received the two devices. They then spent two consecutive nights monitoring their sleep at home. Participants were also asked to keep a sleep log, indicating the time they fell asleep, woke up, and the number of awakenings occurring during the night. Data from both devices, including detailed sleep hypnograms in 30-second epochs (differentiating Wake, combined N1/N2, N3; and Rapid Eye Movement sleep), were extracted and aligned upon retrieval. For analysis, the number of awakenings each night was defined as four or more consecutive wake epochs between sleep onset and termination. Total sleep time (TST) and the number of awakenings were compared to subjects’ sleep logs to measure consistency with the subjective reports. In addition, the sleep scores from each device were compared epoch-by-epoch to calculate the agreement between the two devices using Cohen’s Kappa. All analysis was performed using Matlab 2021b and SPSS 27. Results/Conclusion: Subjects consistently reported longer times spent asleep than the time reported by each device (M= 448 minutes for sleep logs compared to M= 406 and M= 345 minutes for the DREEM and Z-Machine, respectively; both ps<0.05). Linear correlations between the sleep log and each device were higher for the DREEM than the Z-Machine for both TST and the number of awakenings, and, likewise, the mean absolute bias between the sleep logs and each device was higher for the Z-Machine for both TST (p<0.001) and awakenings (p<0.04). There was some indication that these effects were stronger for the second night compared to the first night. Epoch-by-epoch comparisons showed that the main discrepancies between the devices were for detecting N2 and REM sleep, while N3 had a high agreement. Overall, the DREEM headband seems superior for reliably scoring sleep at home.

Keywords: DREEM, EEG, seep monitoring, Z-machine

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Authors: Anush Patric, M. Jadeyegowda, M. N. Ramesh, M. Ravikumar, C. R. Ajay

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Kodagu district which is situated in Central Western Ghats regions falls in one of the hottest of hot spots of biodiversity which is recognised by UNESCO. The district has one of the highest densities of community managed sacred forests in the world with rich floral and faunal diversity. It is a habitat for more than ten different types of Ethnic Indigenous tribal groups commonly called ‘Girijanas’ (Soligas, Yarvas, Jenukuruba, Bettakuruba etc.), who are having the rich knowledge of medicinal value of the plants that are commonly available in the forest. The tribal men of this region are the treasure house of the traditional plant knowledge and health care practices. An ethnobotanical survey was undertaken in tribal areas of the district to collect information about some of the indigenous medicinal plant knowledge of tribal people by semi-structured interviews, ranking exercises and field observations on their native habitat in order to evaluate the potential medicinal uses of local plants. The study revealed that, the ethnobotanical information of 83 plant species belonging to 45 families, of the total 83 species documented, most plants used in the treatment were trees (11 species), shrubs (41 species), herbs (22 species) and rarely climbers (9 species) which are used in the treatment of Hyperacidity, Respiratory disorders, Snake bite Abortifacient, Anthelmintic, Paralysis, Antiseptic, Fever, Chest pain, Stomachic, Jaundice, Piles, Asthma, Malaria, Renal disorders, Malaria and many other diseases. Maximum of 6 plant species each of Acanthaceae, Apiaceae and were used for drug preparation, followed by Asclepiadaceae, Liliaceae, Fabaceae, Verbenaceae, Caesalpinaceae, Bombaceae, Papilonaceae, Solanaceae, Rubiaceae, Myrtaceae, Amaranthaceae, Asteraceae, Ascelepidaceae, Cucurbitaceae, Apocyanaceae, and Solanaceae etc. In our present study, only medicinal plants and their local medicinal uses are recorded and presented. Information was obtained by local informants having the knowledge about medicinal plants. About 23 local tribes were interviewed. For each plant, necessary information like botanical name, family of plant species, local name and uses are given. Recent trend shows a decline in the number of traditional herbal healers in the tribal areas since the younger generation is not interested to continue this tradition. Hence, there is an urgent need to record and preserve all information on plants used by different ethnic/tribal communities for various purposes before it reaches to verge of extinction. In addition, several wild medicinal plants are declining in numbers due to deforestation and forest fires. There is need for phytochemical analysis and conservation measures to be taken for conserving medicinal plant species which is far better than allopathic medicines and these do not cause any side effects as they are the natural disease healers. So, conservation strategies have to be practiced in all levels and sectors by creating awareness about the value of such medicinal plants, and it is necessary to save the disappearing plants to strengthen the document and to conserve them for future generation.

Keywords: diseases, ethnic groups, folk medicine, Kodagu, medicinal plants

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Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

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In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

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Authors: Mosab kh. A. A. Bashir, E. Mohamed-Ahmed

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The aim of the study is to compare the results of the external exposure and the range of the dose spread by the patients, hospitalized in two different groups of 3-5 d receiving radioiodine therapy because of thyroid cancer, and one of group were giving the local diuretic plant (barley) as local juice. The control group was 28 patients they were isolated as international precautions after taken I-131 capsule 100 mCi, and their external exposure was recorded day by day after first 24 hrs. and the distance for external measurement was 1 m at the abdominal level. The mean of external exposure values of patients at fourth day were 30.24±12.92 µSv h−1. The second group after taking I-131 capsule 100 mCi we were given barley juice (250 mL) after every meal three times on day and their external exposure was recorded day by day after first 24 hrs. The mean of external exposure values of patients of this group at third day was 26.92±9.89 (14-55) µSv h−1. It was observed that the external exposure from the second group clearly decreased to low levels which contributed to the decrease in patient dose and also to the decrease in the exposure from the patient to his/her family.

Keywords: local diuretic juice, therapy, radiation medicine, diuretic plant

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Authors: M. Derraz, M. Farhaoui

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Problem statement: In the water treatment processes, the coagulation and flocculation processes produce sludge according to the level of the water turbidity. The aluminum sulfate is the most common coagulant used in water treatment plants of Morocco as well as many countries. It is difficult to manage Sludge produced by the treatment plant. However, it can be used in the process to improve the quality of the treated water and reduce the aluminum sulfate dose. Approach: In this study, the effectiveness of sludge was evaluated at different turbidity levels (low, medium, and high turbidity) and coagulant dosage to find optimal operational conditions. The influence of settling time was also studied. A set of jar test experiments was conducted to find the sludge and aluminum sulfate dosages in order to improve the produced water quality for different turbidity levels. Results: Results demonstrated that using sludge produced by the treatment plant can improve the quality of the produced water and reduce the aluminum sulfate using. The aluminum sulfate dosage can be reduced from 40 to 50% according to the turbidity level (10, 20, and 40 NTU). Conclusions/Recommendations: Results show that sludge can be used in order to reduce the aluminum sulfate dosage and improve the quality of treated water. The highest turbidity removal efficiency is observed within 6 mg/l of aluminum sulfate and 35 mg/l of sludge in low turbidity, 20 mg/l of aluminum sulfate and 50 mg/l of sludge in medium turbidity and 20 mg/l of aluminum sulfate and 60 mg/l of sludge in high turbidity. The turbidity removal efficiency is 97.56%, 98.96%, and 99.47% respectively for low, medium and high turbidity levels.

Keywords: coagulation process, coagulant dose, sludge reuse, turbidity removal

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Authors: Bahriye Gülgün, Gökhan Balik, Şükrü Dursun, Kübra Yazici

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The main reasons such as economic growth of society increase of the world population and rapid changes of industrialization cause the amount and the types of pollutants to increase over time. Soil pollution is the typical side effect of industrial activities. As a result of industrial activities, there are large amounts of heavy metal emission every year. Heavy metals are one of the highest pollution sources according to the soil pollution aspect. The usage of hyperaccumulator plants to clean heavy metal polluted soils and the selection of plants for phytoremediation gain importance recently. There are limited numbers of researches on the ornamental plant types of phytoremediation thus; researches on this subject are important. This research is prepared based on the ornamental plant types with phytoremediation abilities.

Keywords: phytoremediation, ornamental plants, landscape reclamation, soil reclamation, environmental pollution

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Authors: Florian Mach, Eric Hund, Malte Stonis

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The dismantling of disused industrial facilities such as nuclear power plants or refineries is an enormous challenge for the planning and control of the logistic processes. Existing control models do not meet the requirements for a proper dismantling of industrial plants. Therefore, the paper presents an approach for the control of dismantling and post-processing processes (e.g. decontamination) in plant decommissioning. In contrast to existing approaches, the dismantling sequence and depth are selected depending on the capacity utilization of required post-processing processes by also considering individual characteristics of respective dismantling tasks (e.g. decontamination success rate, uncertainties regarding the process times). The results can be used in the dismantling of industrial plants (e.g. nuclear power plants) to reduce dismantling time and costs by avoiding bottlenecks such as capacity constraints.

Keywords: dismantling management, logistics planning and control models, nuclear power plant dismantling, reverse logistics

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Authors: Nishaben Desai Dholakiya, Anirban Roy, Ranjan Dey

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Understanding ocean thermodynamics has become increasingly critical as Earth's oceans serve as the primary planetary heat regulator, absorbing approximately 93% of excess heat energy from anthropogenic greenhouse gas emissions. This investigation presents a comprehensive analysis of Arabian Sea surface seawater thermodynamics, focusing specifically on heat capacity (Cp) and thermal expansion coefficient (α) - parameters fundamental to global heat distribution patterns. Through high-precision experimental measurements of ultrasonic velocity and density across varying temperature (293.15-318.15K) and salinity (0.5-35 ppt) conditions, it characterize critical thermophysical parameters including specific heat capacity, thermal expansion, and isobaric and isothermal compressibility coefficients in natural seawater systems. The study employs advanced machine learning frameworks - Random Forest, Gradient Booster, Stacked Ensemble Machine Learning (SEML), and AdaBoost - with SEML achieving exceptional accuracy (R² > 0.99) in heat capacity predictions. the findings reveal significant temperature-dependent molecular restructuring: enhanced thermal energy disrupts hydrogen-bonded networks and ion-water interactions, manifesting as decreased heat capacity with increasing temperature (negative ∂Cp/∂T). This mechanism creates a positive feedback loop where reduced heat absorption capacity potentially accelerates oceanic warming cycles. These quantitative insights into seawater thermodynamics provide crucial parametric inputs for climate models and evidence-based environmental policy formulation, particularly addressing the critical knowledge gap in thermal expansion behavior of seawater under varying temperature-salinity conditions.

Keywords: climate change, arabian sea, thermodynamics, machine learning

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Authors: Karima Sekkoum Abdelkrim Cheriti, Leila Feguigui

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Algeria has a large plant biodiversity accounting more than 4125 species (123 Families) and is endowed with resources of medicinal plants growing on various bioclimatic zones from subhumide to semi-arid and Saharan. On the other hand, the ethnopharmacology investigation remains the principal way to improve, evaluate, and finding bioactive substances derived from medicinal plants. In continuation of our works in Saharan ethpharmacopeae and phytochemistry of Saharan medicinal plants, we focus our attention on the importance of local ethnopharmacology especially to treat gastro-intestinal disorders in the south west of Algeria (El Baydh, Naama and Bechar region) as platform for bioactive substances discovery and further development. Our present investigation deals with an ethnopharmacological study on medicinal plants used for the treatment of gastro-intestinal disorders in the south west of Algeria. The study presents the uses of plants in local traditional herbal medicines, determines the homogeneity of informant traditional knowledge and the preferred medicinal plants used to treat gastro-intestinal disorders. The results indicated that Asteraceae and Lamiaceae are the most locally used families and medicines were prepared in the form of powder or infusion and used orally. Aerial parts were the most frequently used plant part. Thus, the results can be used as platform for bioactive substances discovery and further development especially for the preferred plant species used in the treatment of gastro-intestinal disorders.

Keywords: ethnopharmacology, gastro-intestinal, phytochemical, South Algeria, Sahara, endemic species

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Authors: Ammar Ouahab, Meriem Houichi , Sanna Mihoubi

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Background: Nigella sativa is an annual flowering plant, belongs to the Ranunculaceae family. It has many pharmacological activities such as anti-inflammatory; anti-bacterial; anti-hepatotoxic activities etc. Materials: In order to predict the pharmacological activity of Nigella Sativa’s compounds, some web based servers were used, namely, PubChem, Molinspiration, ADMET-SAR, PASS online and PharMapper. In addition to that, AutoDOCK was used to investigate the different molecular interactions between the selected compounds and their target proteins. Results: All compounds displayed a stable interaction with their targets and satisfactory binding energies, which means that they are active on their targets. Conclusion: Nigella sativa is an effective medicinal plant that has several ethno-medical uses; the latter uses are proven herein via an in-silico study of their pharmacological activities.

Keywords: Nigella sativa, AutoDOCK, PubChem, Molinspiration, ADMET-SAR, PharMapper, PASS online server, docking

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Authors: Alireza Rasekh, Peter Sergeant, Jan Vierendeels

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This paper copes with the numerical simulation for convective heat transfer in the stator disk of an axial flux permanent magnet (AFPM) electrical machine. Overheating is one of the main issues in the design of AFMPs, which mainly occurs in the stator disk, so that it needs to be prevented. A rotor-stator configuration with 16 magnets at the periphery of the rotor is considered. Air is allowed to flow through openings in the rotor disk and channels being formed between the magnets and in the gap region between the magnets and the stator surface. The rotating channels between the magnets act as a driving force for the air flow. The significant non-dimensional parameters are the rotational Reynolds number, the gap size ratio, the magnet thickness ratio, and the magnet angle ratio. The goal is to find correlations for the Nusselt number on the stator disk according to these non-dimensional numbers. Therefore, CFD simulations have been performed with the multiple reference frame (MRF) technique to model the rotary motion of the rotor and the flow around and inside the machine. A minimization method is introduced by a pattern-search algorithm to find the appropriate values of the reference temperature. It is found that the correlations are fast, robust and is capable of predicting the stator heat transfer with a good accuracy. The results reveal that the magnet angle ratio diminishes the stator heat transfer, whereas the rotational Reynolds number and the magnet thickness ratio improve the convective heat transfer. On the other hand, there a certain gap size ratio at which the stator heat transfer reaches a maximum.

Keywords: AFPM, CFD, magnet parameters, stator heat transfer

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Authors: Lizhi Ma, Chengcheng Hu, Fuxian Wong

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Partial reduce (P-Reduce) has set a state-of-the-art performance on distributed machine learning in the heterogeneous environment over the All-Reduce architecture. The dynamic P-Reduce based on the exponential moving average (EMA) approach predicts all the intermediate model parameters, which raises unreliability. It is noticed that the approximation trick leads the wrong way to obtaining model parameters in all the nodes. In this paper, SAP-Reduce is proposed, which is a variant of the All-Reduce distributed training model with staleness-aware dynamic P-Reduce. SAP-Reduce directly utilizes the EMA-like algorithm to generate the normalized weights. To demonstrate the effectiveness of the algorithm, the experiments are set based on a number of deep learning models, comparing the single-step training acceleration ratio and convergence time. It is found that SAP-Reduce simplifying dynamic P-Reduce outperforms the intermediate approximation one. The empirical results show SAP-Reduce is 1.3× −2.1× faster than existing baselines.

Keywords: collective communication, decentralized distributed training, machine learning, P-Reduce

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Authors: A. H. Taghdisi, M. Mirmohammadi, S. Kamali

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Evening primrose (Oenothera biennis L.) is a biennial and herbaceous and one of the most important species of medicinal plants in the world. due to the production of unsaturated fatty acids such as linoleic acid, alpha-linolenic acid, etc. in its seeds and roots, and compounds such as kaempferol in its leaves, Evening primrose has important medicinal efficiency such as reducing premenstrual problems, acceleration of wound healing, inhibiting platelet aggregation, sedation of cardiovascular diseases, and treatment of viral infections. The sap of the plant is used to treat warts, and the plant itself is used as a charm against mental and spiritual diseases and poisonous animals. Its leaves have significant antibacterial activity against yellow staphylococci. It is also used in the treatment of poisoning, especially the toxication caused by the consumption of alcoholic beverages, in the treatment of arteriosclerosis and diseases caused by liver cell insufficiency. Low germination and production speed are the problems of evening primrose growth and propagation. In the present study, extracts were obtained from four components (flowers, stems, seeds, leaves) of the evening primrose plant using the Soxhlet apparatus. To measure the antibacterial properties against MDR bacteria, microbial methods, including dilution, cultivation on a plate containing nutrient agar culture medium, and disc diffusion in agar, were performed using Staphylococcus aureus and Escherichia coli bacteria on all four extracts. The maximum antibacterial activity related to the dilution method was obtained in all extracts. In the plate culture method, antibacterial activity was obtained for all extracts in the nutrient agar medium. The maximum diameter of the non-growth halo was obtained in the disc diffusion method in agar in the leaf extract. The statistical analysis of the microbial part was done by one-way ANOVA test (SPSS). By comparing the amount of omega-3 in extracts of Iranian and foreign oils available in the market and the extracts extracted from evening primrose plant samples with gas chromatography, it is shown that the stem extract had the most omega-3 (oleic acid) and compared to the extract of the mentioned oils, it had the highest amount of omega-3 overall. Also, the amount of omega-3 in the extract of Iranian oils was much higher than in the extract of foreign oils. It should be noted that the extract of foreign oils had a more complete composition of omega-3 than the extract of Iranian oils.

Keywords: antibacterial activity, MDR bacteria, evening primrose, omega-3

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Authors: Peyman Mosberian-Tanha, Mona Rezaei

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Aquaculture sector is the fastest growing food sector with annual growth rate of about 10%. The sustainability of aquaculture production, however, has been debated mainly in relation to the feed ingredients used for farmed fish. The industry has been able to decrease its dependency on marine-based ingredients in line with policies for more sustainable production. As a result, plant-based ingredients have increasingly been incorporated in aquaculture feeds, especially in feeds for popular carnivorous species, salmonids. The effect of these ingredients on salmonids’ health and performance has been widely studied. In most cases, plant-based diets are associated with varying degrees of health and performance issues across salmonids, partly depending on inclusion levels of plant ingredients and the species in question. However, aquaculture sector is facing another challenge of concern. Environmental challenges in association with climate change is another issue the aquaculture sector must deal with. Data from trials in salmonids subjected to environmental challenges of various types show adverse physiological responses, partly in relation to stress. To date, there are only a limited number of studies reporting the interactive effects of adverse environmental conditions and dietary regimens on salmonids. These studies have shown that adverse environmental conditions exacerbate the detrimental effect of plant-based diets on digestive function and health in salmonids. This indicates an additional challenge for the aquaculture sector to grow in a sustainable manner. The adverse environmental conditions often studied in farmed fish is the change in certain water quality parameters such as oxygen and/or temperature that are typically altered in response to climate change and, more specifically, global warming. In a challenge study, we observed that the in the fish fed a plant-based diet, the fish’s ability to absorb dietary energy was further reduced when reared under low oxygen level. In addition, gut health in these fish was severely impaired. Some other studies also confirm the adverse effect of environmental challenge on fish’s gut health. These effects on the digestive function and gut health of salmonids may result in less resistance to diseases and weaker performance with significant economic and ethical implications. Overall, various findings indicate the multidimensional negative effects of climate change, as a major environmental issue, in different sectors, including aquaculture production. Therefore, a comprehensive evaluation of different ways to cope with climate change is essential for planning more sustainable strategies in aquaculture sector.

Keywords: aquaculture, climate change, sustainability, salmonids

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Authors: Yahia. Kourd, N. Guersi D. Lefebvre

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In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.

Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor

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Authors: Jose A. Aznar-Moreno, Xi Jiang, Stefan Burén, Luis M. Rubio

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Integration of prokaryotic nitrogen fixation (nif) genes into the plastid genome for expression of functional nitrogenase components could render plants capable of assimilating atmospheric N2 making their crops less dependent of nitrogen fertilizers. The nitrogenase Fe protein component (NifH) has been used as proxy for expression and targeting of Nif proteins within plant and yeast cells. Here we use tobacco plants with the Azotobacter vinelandii nifH and nifM genes integrated into the plastid genome. NifH and its maturase NifM were constitutively produced in leaves, but not roots, during light and dark periods. Nif protein expression in transplastomic plants was stable throughout development. Chloroplast NifH was soluble, but it only showed in vitro activity when isolated from leaves collected at the end of the dark period. Exposing the plant extracts to elevated temperatures precipitated NifM and apo-NifH protein devoid of [Fe4S4] clusters, dramatically increasing the specific activity of remaining NifH protein. Our data indicate that the chloroplast endogenous [Fe-S] cluster biosynthesis was insufficient for complete NifH maturation, albeit a negative effect on NifH maturation due to excess NifM in the chloroplast cannot be excluded. NifH and NifM constitutive expression in transplastomic plants did not affect any of the following traits: seed size, germination time, germination ratio, seedling growth, emergence of the cotyledon and first leaves, chlorophyll content and plant height throughout development.

Keywords: NifH, chloroplast, nitrogen fixation, crop improvement, transplastomic plants, fertilizer, biotechnology

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Authors: Geisa Lima Mesquita Zambrosi, Maisa Ciampi Guillardi, Flávia Rodrigues Patrício, Oliveiro Guerreiro Filho

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Certified agricultural products are important components of the food industry. However, certifiers have been expanding the list of restricted or prohibited pesticides, limiting the options of products for phytosanitary control of plant diseases, but without offering alternatives to the farmers. Soybean and coffee leaf rust, brown eye spots, and Phoma leaf spots are the main fungal diseases that pose a serious threat to soybean and coffee cultivation worldwide. In conventional farming systems, these diseases are controlled by using synthetic fungicides, which, in addition to intensifying the occurrence of fungal resistance, are highly toxic to the environment, farmers, and consumers. In organic, agroecological, or regenerative farming systems, product options for plant protection are limited, being available only copper-based compounds, and biodefensivesornon-standard homemade products. Therefore, there is a growing demand for effective bioprotectors with low environmental impact for adoption in more sustainable agricultural systems. Then, to contribute to covering such a gap, we have developed a compound based on plant extracts and metallic elements for foliar application. This product has both biostimulant and bioprotective action, which promotes sustainable disease control, increases productivity as well as reduces damage to the environment. The product's components have complementary mechanisms that promote protection against the disease by directly acting on the pathogens and activating the plant's natural defense system. The protective ability of the product against three coffee diseases (coffee leaf rust, brown eye spot, and Phoma leaf spot) and against soybean rust disease was evaluated, in addition to its ability to promote plant growth. Our goal is to offer an effective alternative to control the main coffee fungal diseases and soybean fungal diseases, with a biostimulant effect and low toxicity. The proposed product can also be part of the integrated management of coffee and soybean diseases in conventional farming associated with chemical and biological pesticides, offering the market a sustainable coffee and soybean with high added value and low residue content. Experiments were carried out under controlled conditions to evaluate the effectiveness of the product in controlling rust, phoma, and cercosporiosis in comparison to control-inoculated plants that did not receive the product. The in vitro and in vivo effects of the product on the pathogen were evaluated using light microscopy and scanning electron microscopy, respectively. The fungistatic action of the product was demonstrated by a reduction of 85% and 95% in spore germination and disease symptoms severity on the leaves of coffee plants, respectively. The formulation had both a protective effect, acting to prevent infection by coffee leaf rust, and a curative effect, reducing the rust symptoms after its establishment.

Keywords: plant disease, natural fungicide, plant health, sustainability, alternative disease management

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Authors: Vinod Nair, C. Sadasivan

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Beta-lactam antibiotics are the most frequently prescribed medications in modern medicine. The antibiotic resistance by the production of enzyme beta-lactamase is an important mechanism seen in microorganisms. Resistance to beta-lactams mediated by beta-lactamases can be overcome successfully with the use of beta-lactamase inhibitors. New generations of the antibiotics contain mostly synthetic compounds, and many side effects have been reported for them. Combinations of beta-lactam and beta-lactamase inhibitors have become one of the most successful antimicrobial strategies in the current scenario of bacterial infections. Plant-based drugs are very cheap and having lesser adverse effect than synthetic compounds. The synergistic effect of eugenol acetate with beta-lactams restores the activity of beta-lactams, allowing their continued clinical use. It is reported here the enhanced inhibitory effect of phytochemical, eugenol acetate, isolated from the plant Syzygium aromaticum with beta-lactams on beta-lactamase. The compound was found to have synergistic effect with the antibiotic amoxicillin against antibiotic-resistant strain of S.aureus. The enzyme was purified from the organism and incubated with the compound. The assay showed that the compound could inhibit the enzymatic activity of beta-lactamase. Modeling and molecular docking studies indicated that the compound can fit into the active site of beta-lactamase and can mask the important residue for hydrolysis of beta-lactams. The synergistic effects of eugenol acetate with beta-lactam antibiotics may justify, the use of these plant compounds for the preparation of β-lactamase inhibitors against β-lactam resistant S.aureus.

Keywords: betalactamase, eugenol acetate, synergistic effect, molecular modeling

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Authors: Forouzan Salehi Fergeni

Abstract:

Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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