This article analyzes the spatial and temporal dynamics of the mangrove in the Commune of Kafountine located in the southwest of Senegal in the Ziguinchor region. This through a comparative study using Landsat satellite images from the years 1972, 1986, 2000 and 2018. The methodology used is based on the exploitation of geospatial data by remote sensing, rainfall data from (1960 to 2015) and data socioeconomic. The results obtained show three main phases of mangrove development between 1972 and 2018. The first dynamic, between 1972 and 1986, was marked by a decline of 13,450 ha in mangrove areas due mainly to the drought that raged in the Sahelo-Sudanian zone during the decades 1970 and 1980. This phase is followed, between 1986 and 2000, by a regeneration of 4586 ha and an increase of 5897 ha of mangrove areas between 2000 and 2018 thanks to the return of rainfall and to awareness of the population on the need to protect their resources sustainably with the establishment of reforestation activities, the development of economic activities around the mangrove (oysters and fishing) and the establishment of management rules to try to greatly reduce the overexploitation of mangroves. Rising sea levels with the return to increasingly humid conditions on the Casamance scale also play a crucial role with the entry of increased volumes of relatively less salty seawater into estuaries

Keywords: dynamic, mangrove, estuary, remote sensing, Lower Casamance, Kafountine

[1]. Marius C. (1985). Mangroves du Sénégal et de la Gambie : écologie, pédologie, géochimie, mise en valeur et aménagement, Paris, ORSTOM, coll. Travaux et Documents, 357p.
[2]. Ndour N. (2005). Caractérisation et étude de la dynamique des peuplements de mangrove de la Réserve de Biosphère du Delta du Saloum (Sénégal), Dakar, UCAD, 180p.
[3]. FAO. (2007). The world's mangroves 1980-2005, Rome, 89p.
[4]. Ngom F. (2007). Les fonctions de mangrove dans la structuration et la biologie des peuplements de poissons de l'estuaire du Sine-Saloum, Université Cheikh Anta Diop de Dakar Faculté des Sciences et Techniques, Thése De Doctorat De Troisième Cycle De Biologie Animale, 148 p.
[5]. Cormier Salem M.C., Sy B.A., Cubizolle H., Bassene O.A. (2013). Impacts des changements démographiques et socio-économiques sur la perception et la gestion de la mangrove en Basse Casamance (Sénégal), Géocarrefour V.88 N° 4 Nouveau regards sur les zones humides, 229-135 p..

Vulcanization process has been widely used in footwear industry due to the effect of rubber sole quality. This paper is focused on study the effect of vulcanization process parameters on mechanical properties of rubber sole. The vulcanization process parameters such as molding temperature, molding pressure, and holding time were used as factors. The mechanical properties of rubber sole such as tensile strength and elongation at break were used as responses. Full factorial design with three times replicated was implemented for the experiment. Response prediction was conducted by using backpropagation neural network. The network architecture was developed by using 3 neurons on input layer, 16 neurons on hidden layer, and 2 neurons on output layer. The mean absolute errors between experiment and predicted values were 1.485% for tensile strength and 0.6% for elongation at break. Therefore, backpropagation neural network was recommended for predicting the responses of vulcanization process on rubber sole with good agreement compared to experiment result.

Keywords:vulcanization process, rubber sole, backpropagation neural network, response prediction

[1] Z. Amarta, B.O.P.Soepangkat, Sutikno, and R. Norcahyo, Multi response optimization in vulcanization process using backpropagation neural network-genetic algorithm method for reducing quality loss cost,AIP Conference Proceedings, 2019,2114 020003.
[2] B.O.P. Soepangkat, R. Norcahyo, D.R. Pamuji, and N. Lusi, Multi-Objective Optimization in End Milling Process of ASSAB XW-42 Tool Steel with Cryogenic Using Grey Fuzzy Logic and Backpropagation Neural Network-Genetic Algorithm (BPNN-GA) Approaches, International Review of Mechanical Engineering,12, 2018, 42-54.
[3] R. Norcahyo, B.O.P. Soepangkat, and Sutikno, Multi Response Optimization of Thrust Force and Delamination in Carbon Fiber Reinforced Polymer (CFRP) Drilling using Backpropagation Neural Network-Particle Swarm Optimization (BPNN-PSO), AIP Conference Proceedings, 2018,1983 040006
[4] A. Sateria, B.O.P. Soepangkat, andSuhardjono, Artificial Neural Network and Genetic Algorithm for Multi-Objective Optimization in Drilling of Glass Fiber Reinforce Polymer-Stainless Steel Stacks, AIP Conference Proceedings, 2018,1983 040007.
[5] L.V. Fausett, Fundamentals of Neural Networks: Architectures, Algorithm, and Applications (Prentice-Hall, 1994).

Extensive studies have been proposed for on/off-road light and heavy equipment non-Pneumatic Tyres (NPTs) due to their advantages over the traditional pneumatic tyre in low rolling resistance, flat-proof, low maintenance. Many studies were focusing on the elastomer material asthe primary material using in NPT. In this paper, NPT finite element (FE)model with honeycomb spokes containingpolyurethance/carbon nanotubes (PU/CNTs) is investigated. The NPT static behaviour of vertical stiffness, and contact pressure are studied. Rolling resistance and dynamic shear stress are also studied. The parametric study shows that PU/CNT makes a significant effect on rolling resistance.

Keywords:Non-pneumatic tyre (NPT); rolling resistance; carbon nanotubes (CNTs); FEM.

[1]. Rhyne, T.B. and S.M. Cron, Development of a non-pneumatic wheel. Tire Science and Technology, 2006. 34(3): p. 150-169.
[2]. Veeramurthy, M., Modeling, finite element analysis, and optimization of Non-Pneumatic Tire (NPT) for the minimization of rolling resistance. 2011.
[3]. Rhyne, T.B. and S.M. Cron, A study on minimum rolling resistance. Tire Science and Technology, 2012. 40(4): p. 220-233.
[4]. Veeramurthy, M., et al., Optimisation of geometry and material properties of a non-pneumatic tyre for reducing rolling resistance. International Journal of Vehicle Design, 2014. 66(2): p. 193-216.
[5]. Kuwayama, I., H. Matsumoto, and H. Heguri, Experimental and numerical analysis of the conceptual next generation ecology tire (first report). SAE International Journal of Passenger Cars-Mechanical Systems, 2013. 6(2013-01-0741): p. 714-731

Drying operations play an important role in food industries. They are often the last step of the process manufacturing a product with a strong influence on the final quality. The drying relates to a wide variety of products. Methods are many and depend on the type and quantity of product to be dried and of water to be evaporated, the desired final quality, or functionality sought for the dried product.The study considers to different experiment: nutritional fruits (Mangoes, Bananas) and sand which is normal used as the draining porous media in traditional agriculture drying process. All three samples of fresh Mangoes (including two same thickness and sharp samples, the other one with different sharp),two samples of fresh Bananas with different surface exchange area, three samples of sand (with two same thickness and different moisture content, the other one with different thickness but same moisture content) are drying in the oven at 700C temperature. The result data has been recorded to plot curves and estimate. This gives a few to understand the theory of drying kinetics and provide information useful in dryer design.

Keywords:Drying, kinetics, water content, moisture content, hygroscopic products.

[1]. Patrick Gentilini, Oumaya Yazoghli-Marzouk, Vincent Delmotte, Yannick Descantes, Determination of the water content of fillerised fine aggregates in the saturated surface dry state. Construction and Building Materials, Elsevier, 2015, 98, pp.662-670.
[2]. Pauline M. Doran, Unit Operations in Bioprocess Engineering Principles (Second Edition), 2013, chapter 11, pp. 445-595.
[3]. Mujumdar Arun S, Handbook of industrial drying. Boca Raton: CRC Press, 2006.
[4]. A.M.Castro,E.Y.Mayorga,F.L.Moreno, Mathematical modelling of convective drying of fruits: A review, Journal of Food Engineering, Volume 223, April 2018, pp.152-167.
[5]. Zhang Min, Chen Huizhi, Mujumdar Arun S, Zhong Qifeng, Sun Jincai, Recent developments in high-quality drying with energy-saving characteristic for fresh foods, Drying Technol 2015, 33:1590-600.

Flow through a free-space channel underlain by a porous layer is considered. Both regions are saturated with particle-laden fluid driven by the same pressure gradient. Velocity distribution in both regions are derived and velocity and shear stress conditions at the interface are obtained. Effects of mixture and porous medium parameters on the flow characteristics are investigated in Cartesian and in curvilinear coordinates. Analysis shows that when the dust-phase velocity is the product of a position function and the fluid-phase velocity, the particle number density does not influence conditions at the interface between the two layers.

Keywords: Fluid-particle mixture; Porous layers; Slip flow; Interfacial conditions.

[1]. M.S. Abu Zaytoon and M.H. Hamdan, The Flow of a Saffman's Dusty Gas with Pressure-Dependent Viscosity through Porous Media. Elixir Appl. Math. 98 (2016) pp. 42550-42554.
[2]. F.M. Allan and M.H. Hamdan, Fluid-particle Model of Flow through Porous Media: The Case of Uniform Particle Distribution and Parallel Velocity Fields, Applied Mathematics and Computation, Vol.183, #2, 2006, pp. 1208-1213.
[3]. S.M. Alzahrani and M.H. Hamdan, Gas-Particulate Models of Flow through Porous Structures, Int. Journal of Engineering Research and Applications,Vol. 6, Issue 2, (Part - 3) February 2016, pp.54-59.
[4]. S.M. Alzahrani and M.H. Hamdan, Mathematical Modelling of Dusty Gas Flow through Isotropic Porous Media with Forchheimer Effects, Int. J. Enhanced Research in Science, Technology and Engineering, 5 # 5, (2016), pp. 116-124.
[5]. M.M. Awartani and M.H. Hamdan, Some Admissible Geometries in the Study of Steady Plane Flow of a Dusty Fluid through Porous Media, Applied Mathematics and Computation, Vol. 100#1, 1999, pp. 85-92.

To compare the effects of different vehicle models on the dynamic response of periodic viaducts (PV) under seismic waves, a moving mass-PV model and amoving mass-spring system (MSS)-PV model under seismic waves are established by using the finite element method and Fourier transform. In order to solve the dynamic response of PV under seismic waves and MSS, the dynamic response of PV under unit series moving load component is calculated first, then the motion equation of upper mass of MSS and coupled equation of PV and the lower part of MSS are established according to Newton's second law. Solving the above equations can obtain the Fourier coefficients of the MSS-PV interaction force and the Fourier coefficients of the restoring force of the MSS spring. By using the above Fourier coefficients and the dynamic responses of PV under unit series moving load component and seismic waves, the overall dynamic response of PV under seismic waves and moving MSS can be obtained finally.The process of solving the problem of the dynamic response of PV under the moving mass and seismic waves is similar to the method mentioned above..........

Keywords: Periodic viaduct; Seismic waves; moving mass-spring system; finite element; Fourier transform

[1]. Matsuura A. Dynamic behavior of bridge girder for high speed railway bridge[J]. Railway Technical Research Institute Quarterly Reports, 1979, 20(02):35-42.
[2]. Miyamoto T, Ishida H, Matsuo M. The dynamic behavior of railway vehicle during earthquake. vehicle dynamics simulation on track vibrating in transversal& vertical directions[J]. Transactions of the Japan Society of Mechanical Engineers Series C, 1998, 64(626):3928-3935.
[3]. Wu Y S, Yang Y B, Yau J D. Three-dimensional analysis of train-rail-bridge interaction problems[J]. Vehicle System Dynamics, 2001, 36(01):1-35.
[4]. Miyamoto T, Ishida H. Numerical analysis focusing on the running safety of an improved bogie during seismic vibration[J]. Quarter Reporter of RTRI, 2008, 49(03):173-177.
[5]. Yau J D. Response of a train moving on multi-span railway bridges undergoing ground settlement[J]. Engineering Structures, 2009, 31(09):2115-2122.