In this study, Decyl derivatives (Ia, Ib, Ic), were prepared as cationic biocidal salts that lower the tensioactif and have anti-microbial properties. These salts have single or double alkyl chains with varying lengths (C8= Ia, C12 = Ib, C16 = Ic). Because of their molecular structures, phosphonium salts with long alkyl chains, such as Decyl triphenyl phosphonium bromide C16 = Ic have shown potent antibacterial activity.It demonstrated bactericidal efficacy against the fungi A. flavus is (25 mm), C. albicans (30 mm), S. aureus (35 mm) and P. aerognosa (40 mm), grew as the length of the alkyl chain rose at doses of 2.8 and 28 uM, respectively.It has been observed that phosponium salt with the longest alkyl chain (C16) killed all bacterial cells about (110 cells per milliliter) within 30 minutes of contact.The fact that the double decyl groups in the phosphonium biocide demonstrated the broadest range of activity against tested pathogens and the highest bacteriostatic activity against MRSA (MIC = 0.98 ug/ml) is noteworthy.When measuring against the same cationics in copper Cu (II), cobalt Co (II) complexes, it exhibit a significant increase in biocidal activity towards the targeted bacterial strains and fungi, comparing their parent cationic ion to those connected with cobalt, it is evident that the inhibitory zone diameter steadily increases such as fungi A. flavus (41 mm) and C. albicans (35 mm) as well as bacteria found in Pseudomonas aeruginosa (42 mm) and Staphylococcus auerus (60 mm), respectively. Keyword: Quaternary phosphonium salts, Surface active agent, Biological activity

Today, thanks to AI particularly Deep – Learning, How Face manipulations in video seems quite realistic. They are called Deep Fake which is the creation of such AI-generated videos. The term Deepfake used mainly to demonstrate the process of generating realistic videos of this kind with the help of technology. Rather, it can be rather difficult to differentiate such Deep Fake (DF) pieces from each other. In order to detect this challanges, in this article, a methodology of Hybrid CNN and RNN is presented. In particular, moderate CNN referred to as ResNet152 for feature extraction from the video, and Long Short Term Memory as the RNN model for classifying the video manipulation as well as temporal artifacts in frames.

This study aimed at determining the transpiration characters of Juniperus macrocarpa in a close to 40-year-old even-aged stand categorized into three classes based on canopy size, over a two-year period (2011-2012). The site is located in Palaiochora, 77 km south of Chania, on the southwest coast of Crete. Sap flow techniques (Granier-type) were used to determine water use. Annual trends in sap flow were generally bell-shaped, and varying significantly between seasons and canopy classes. Winter sap flow was minimal but trees were active when temperatures were above freezing point and trees depended on deep water (below 60 cm) for transpiration. Rates increased from 1.46Ld-1 in winter to 3.32 Ld-1 in the spring, irrespective of tree canopy class, because of improvement in weather conditions. Maximum transpiration rates were observed during the growing season with an average of 134.42 Ld-1 for dominant trees and 8.68Ld-1 for suppressed ones. The daily variations in photosynthetically active radiation, vapor pressure deficit, air temperature, and surface soil water were the principal drivers for transpiration during the growing season. The findings have shown that climate in Crete does not limit the expansion of J. macrocarpa and that this expansion will have potentially significant impacts on the ecohydrology of the system.

This paper explores the use of multi-criteria optimization to find better combination of parameters of friction welding process to provide better mechanical properties at the welded joints. This is achieved by developing a new hybrid methodology by integrating TOPSIS method and entropy measurement. TOPSIS method is used to find the order preference by similarity to ideal solution. Entropy method is used to find the weights of output responses. The mechanical strength of friction welded joints depends on several process parameters namely size of work piece, spindle speed, friction time, forging time, friction pressure, etc., Better combination of process parameters leads to quality joint, reduction of cost and wastages. Hybrid TOPSIS method was proposed to predict parameters that resulting superior mechanical properties. Specimen were produced with the predicted parameters and tested to confirm the superiority. Taguchi’s L9 orthogonal array is selected for conducting experiments. It is observed that friction time and spindle speed are the foremost factors but friction pressure influences less on mechanical strength.

For today vehicles, ride comfort and dynamic control, are crucial criteria for customers and also for the selection of an appropriate vehicle. Tractors as vehicles are exposed to random vibrations caused by unevenness of road or soil profile, moving elements within the tractor or implements, while setting on a rigid seat without a backrest. Whole-body vibration transmission influences comfort, performance, and long-term health of the operator. This current study is to evaluate and controlled an agricultural tractor whole-body vibration comfort efficiency, which constitutes one aspect of the physical environment that can cause discomfort to operators, based on standard mathematical formulae and frequency analyses. A gravel road texture was selected and used. To assess vibrations transmitted to the operator, vibration dose values, kurtosis, international road roughness index and power spectral densities of the tractor (seat and floor) recorded signals were evaluated. Seat Effective Amplitude Transmissibility values based on the tractor seat pan vibration dose value (controlled and uncontrolled) outputs in the three-direction lateral, longitudinal and vertical) qualify vibration comfort efficiency. Tri-axial accelerometers were usually mounted on the tractor seat pan and floor. Data are frequency weighted in order to model the human response to vibration in that location and direction.

Bridges of all types are an essential part of infrastructure systems; they play an important role in the economic and social aspects and are of a great importance when an earthquake occurs, since they provide emergency response and rescue operations. Therefore, bridges vulnerability assessment has been a major focus in earthquake research. \nThe present paper consists of a comparison study between two different popular types of bridges in Algeria that are the Multi-Span Simply Supported (MSSS) and Multi-Span Continuous (MSC) reinforced concrete girder bridges. For this purpose, three-dimensional nonlinear finite elements models were performed and seismic fragility curves of the later were developed using nonlinear time history analyses. \nThe comparison of the obtained results shows that the MSSS is more vulnerable than the MSC concrete girder bridge at all damage states where the fixed bearings present the most fragile components in both types of studied bridges. These results deal with the reality of such existing bridges behavior during past earthquakes, which means that the structure continuity increases the seismic resistance of a bridge and reduces seismic risk.

The industry of oil and gas (O&G) suffers from delay to get enough information about equipment in case of maintenance and delay in communication between stakeholders. With the highly increasing of the data of oil and gas (O&G) industry the concept of Internet of Things (IoT) become a must to be applied to sense and monitor every area of O&G operations. The proposed system aims to solve the problems that faces the oil and gas (O&G) industry by allowing stakeholders to get much information about the (O&G) operation. The system helps in preventing the loss of money from the lack of unavailable information. Also the system helps in improving and developing the operation of maintenance procedure to get a high quality of service.

Wireless Sensor Network assumes an imperative part to monitor and gather information from complex geological ranges. Energy conservation plays a fundamental role in WSNs since such sensor network is designed to be in non-accessible areas and has gained popularity since the last decade. The main issue of Wireless Sensor Network is energy consumption. Therefore, management of energy consumption of the sensor node is the main area of our research. Generally, Sensor nodes use non-changeable batteries for power supply and the lifetime of Sensor node greatly depends on these batteries. The replacement of these batteries is very difficult in many applications and an alternative solution to this problem is to use Energy Harvesting system in Wireless Sensor Network to provide a permanent power supply to sensor nodes. This process of extracting energies from the nature and converting it into electrical energy is called energy harvesting. Energy can be harvested from the environment for sensor nodes. There are many sources of energies in nature like solar, wind, thermal etc. which can be harvested and used for WSNs. In this research we suggest using energy harvesting system for Cluster Heads in a clustering based Wireless Sensor Networks. We will compare our proposed technique to a well-known clustering algorithm, Low Energy Adaptive Cluster Hierarchy (LEACH).

This study gives complete convention to orderly production of computerized information on tyrosinase creating microorganisms secluded from soil. Three bacterial tyrosinase were identified using 16S rRNA gene sequencing method. The assembled 16S rRNA sequences were used to create digital data of given sequences. These include the Quick Response (QR) codes, Chaose Game Representation (CGR), Chaose Game Representation (FCGR) of Frequency and Principal Component Analysis (PCA). The QR codes will be used to read sequence without internet connection. Presence of dots in CGR and color of FCGR block gives in-depth idea about the nucleotides and their pairing. PCA has given overview of their distribution which co-relates with results of phylogenetic tree. The visuals have given an extra information about tyrosinase producing bacteria. These generated visuals will be beneficial for assessment and comparison of bacteria.

Job shop scheduling problem (JSSP) is an NP-hard problem and one of the most intractable combinatorial optimization problems in the manufacturing industry. An optimal solution to JSSP optimizes machine utilization, reduces lead times, improves efficiency of manufacturing system and reduces costs. As the number of jobs & machines increase, the job shop scheduling problems approaches NP-hard difficulty. This paper proposes the job-shop environment in limited computational time by using soft computing technique. In order to efficiently solve the JSSP, a method that the hybrid algorithms i.e. Ant Colony Optimization algorithm (ACO) and Fire Fly Optimization (FFO) is proposed to find a good enough schedule in a reasonable computation time. The proposed approach is applied to a JSSP comprising 5 jobs on 5 machines with random processing time. From the investigational results showed that the hybrid optimization achieves maximum accuracy and minimum completion time compared to individual algorithms. Test results demonstrate that the obtaining well enough schedules is successful in the aspects of solution quality and computational efficiency.

The effect of different levels of inulin (0, 1.5 and 3 %) and probiotic bacteria including Lactobacillus acidophilus and Lactobacillus casei on chemical properties (pH and titratable acidity) and viable count of probiotic strain of sweet cream during 30 days at 15-day intervals at (4°C) were studied. All experiments were carried out in three replications. The results showed that during the refrigerator storage of samples, pH decreased and acidity increased significantly. Addition of inulin caused significant changes in pH, acidity and the viability of probiotic strains. By increasing the level of inulin to 3%, the pH of the cream samples decreased, and the acidity and counts of the probiotics increased significantly, which was more significant in Lactobacillus acidophilus, although the treatment containing Lactobacillus acidophilus had the highest acidity. The probiotic survival evaluation also indicated that inulin treatment at 3% level was the best treatment for increasing the viability of the probiotics in cream. The results showed that the addition of prebiotics, such as inulin, could play an important role in increasing the viability of probiotics. In general, changes in the chemical properties of sweet cream during the refrigerator storage were standard, which could be considered as a synbiotic product and sweet Cream as a dairy product can also be considered as a good carrier for probiotic bacteria. .

Pollution by heavy metals due to anthropogenic, industrial and automobile activities is a regional and global problem. This paper gives information about the seed germination and seedling growth performance of mung bean (Vigna radiata) in response to treatment of copper and chromium (0, 25, 50 and 100 ppm) in single and combined treatments as compared to control. Seed germination of V. radiata showed that increased in concentration of both metal treatments from 25 to 100 ppm reduced germination percentage which was more prominent as compared to control treatment.\nSeedling growth variables i.e. root and shoot length, seedling size, root/shoot ratio and seedling dry weights were also declined with the increase in concentration of copper and chromium in the substrate as compared to control treatment. Seedlings growth of V. radiata gradually reduced with increased in concentrations of Cr as compared to control. The inhibitory effects of combined metals treatments (Cu+Cr) showed high percentage of decreased in seedling growth variable as compared to control. The order of effects of metal treatment at 25-100 ppm concentrations as compared to control was found in the order as Cu>Cr>Cu+Cr. The combined metal treatments of Cu+Cr were found more toxic as compared to individual treatment of Cu and Cr and control.\nTolerance indices and seedling vigor index of V. radiata for individuals and combined metal treatment decreased with the increase in concentration of metal treatment from 25 to 100 ppm for Cu and Cr singly and in combination (Cu+Cr) as compared to control. The highest percentage of decrease in seedling tolerance and seedling vigor indices in seedlings of V. radiata was recorded at 100 ppm when treated with combined metal treatment of copper and chromium. A seedling vigor and tolerance index at 25 ppm was better for single treatment of Cu and Cr treatments as compared to combined treatment of Cu+Cr.

Automobile exhaust emission are a dominant source of urban environmental pollution due to movement of high traffic density and believed to have detrimental negative impact on plant growth rapidly since last couple of decades. This study describe the effects of autoexhaust emission on the seed germination and seedling growth behavior of Senna alata (L.) Roxb. (Ringworm) flowering tree growing as street tree in different road side of the city of Karachi. The effects of automobile exhaust emission on the seed germination and early seedling growth performance of S. alata was recorded. The auto emission showed negative effects on seedling height, leaf area (sq. cm), total plant fresh weight, total plant dry weight, root dry weight, stem dry weight, leaf dry weight, root / shoot ratio for fresh weight and root / shoot ratio for dry weight of S. alata growing in polluted sites (Tariq Road, Bahadurabad, Khalid Bin Waleed Road, Gulshan-e-Iqbal Gulshan-e-Iqbal) of city as compared to Karachi University Campus (Cleaner site). The seeds of S. alata collected from the Karachi University campus, which is considered as control site showed better percentage of seed germination and seedling growth as compared to the seeds of the same species collected from the different polluted areas of the city. A high percentage of decrease in seed germination was found for the seeds collected from the Tariq Road, followed by Bahadurabad, Khalid Bin Waleed Road and Gulshan-e-Iqbal Gulshan-e-Iqbal as compared to control. Seedling length was also highly decreased for seeds of same species collected from Tariq Road as compared to control. High percentage of decrease in seedling dry weight was found for seeds of same species collected from Tariq Road, Bahadurabad, Khalid Bin Waleed Road, and Gulshan-e-Iqbal Gulshan-e-Iqbal as compared to control. Root growth of S. alata was significantly decreased in the polluted seedlings as compared to control.\nAccording to tolerance test it was observed that seedling growth of S. alata showed lowest percentage of tolerance to auto exhaust emission were in order of samples collected from Gulshan-e-Iqbal>Bahadurabad>Khalid Bin Waleed Road>Tariq Road as compared to relatively clean area (University campus).

One of basic issues of the sustainable development is the protection of the natural environment. Very important is the waste recycling and the introducing of green technological processes. The use of Fly Ashes (FA), from coal combustion in power plants presents a very important problem in all countries, in which the energy production is based on this fuel. Fly ashes, owing to the spherical shape of their particles, provide consistency, easy placement and compaction of fresh concrete. Phosphogypsum (PG) is a waste product generated by the chemical industry during phosphoric acid production. The processing of PG waste was carried out in waste-free manner by heat treatment with mixing. Biopolymers (BP) were formed on the basis of epoxy resin and fillers in the form of starch or cellulose waste. The study concerned development of composites based on waste FA, PG and BP. Constant Magnetic Field (CMF) characterised by magnetic induction value B = 1 T was an additional parameter improving, under specific conditions, the physical properties of the resultant composites. With respect to absorbability of the tested samples, as a result of exposure to CMF their weight changed by 7,4 % for composites. With respect to flexural strength of the tested samples is concerned, CMF processing caused a change of 11,9 % for homogeneous materials (cement) and of 7,0 % for composites. With respect to compressive strength of the tested samples, CMF processing caused a change of 6,6 % for homogeneous materials (cement) and of 4,6 % for composites. One can apply new composites as: building materials, substructure of the ground, concealed installation insulation layer and polymer materials.

Generation Expansion Planning (GEP) aims to determine the least cost capacity expansion plan to meet forecasted demand inward a pre-defined reliability criterion and emission constraint over a planning horizon. This paper presents the application of Differential Evolution (DE), Opposition-based Differential Evolution (ODE) and Self-adaptive Differential Evolution (SaDE) algorithms to GEP problem, where the power generating system of an Indian state Tamil Nadu is taken as study region. GEP problem has been solved for short-term (6-years) and long-term (12-years) planning horizon by considering least-cost, reliable supply and lowest emission to the environment using DE, ODE and SaDE also validated by Dynamic Programming (DP). GEP problem is solved for seven diverse cases such as, Case 1: Base case, Case 2: GEP with Energy Conservation (EC), Case 3: GEP with high penetration of Renewable Energy Sources (RES), Case 4: GEP with penalty costs on emissions from high emission plants (HEP), Case 5: GEP with energy storage technologies (EST), Case 6: Combination of Cases 2, 3&4 and Case 7: Combination of Cases 2, 3, 4&5. The results simultaneously provide the type and capacity of each type of power plant need to be expanded in each year of the planning horizon at least cost.

The job-shop scheduling issues The Job Shop Scheduling Problem (JSSP) has created as a standout among the most captivating arranging models now in vogue which is concerned with the hardest combinatorial change issues. In this paper considered two unique destinations that is make span time and tardiness work, utilizing enlivened hybrid Grey Wolf-Chicken Swarm Optimization algorithm models. The most extraordinary completion (makes pan), and the tardiness are considered in the meantime. In the proposed figuring, a couple of prior standards are shown to assemble the hidden people with a strange condition of significant worth. The hybrid algorithm count relies on upon the re-enactment of the swarming behavior of wolves’ individuals. The base detachments of each individual wolves and swarms from sustenance and from most bewildering thickness of the group are considered as the objective work for the improvement. The results show that proposed hybrid Optimization algorithm can accomplish good optimization results in terms various iteration levels of both optimization accuracy and robustness also easily applied in real industrial conditions and for large size problems. proposed method consumes 3.86s for 1000 iteration compared with GA (28.72s) and ACO (26.06s), proposed method was very less time period and cost for 6 machines to complete 16 jobs.