Study and Modelization of Veterinary Drug Residue Kinetics on Sawdust as Absorptive Biomaterial in Eastern Algeria during January 2017 to June 2018

Abstract

Sawdust, an affordable resource, is being investigated as an adsorbent to eliminate residual contaminants from water. Wood processing residues such as bark and sawdust have been widely studied for some years for their adsorption and removal properties of toxic metals contained in contaminated effluents. The aim of our study is to know the source of chemical contamination of water by using spectrophotometry methods in field ultraviolet, the kinetic study of sodium salicylate adsorption on sawdust was modelized according to two kinetic models (pseudo first and second order), to determine the most optimal pattern to describe this phenomenon, was based in the comparison on the correlation coefficient (R 2 ) between the absorbance and the wavelength for both models and evaluate the optimal time of contact solid/liquid. Present results indicated that the correlation coefficient (R 2 =0.999) for the pseudo-second order, which means that this model is the best for future studies in the kinetics of adsorption of sodium salicylate by sawdust, with a time of contact solid /liquid optimal is 44.5 minutes.

Data Analytics in Small and Medium Enterprises (SME)

“…Second,extantresearchstudiesareconductedfromoperationalviewpoint,asaresultmostofthem highlighteithertheapplicationofanalyticsorimpactonfirmafterapplication (Saleem,et.al.,2020;Popovič, et.al, 2020;Kikawa, et.al., 2020). Subsequently, studies lack managerial and strategic viewpointasadiscussion.However,thesestudiesidentifytheroleofstrategicandmanagerialdecision makingbutdidnotundergoadeepdiveintothisresearchtheme.Third,mostofprominentstudiesin thisresearchdomainpaidattentionatfirmlevel,therefore,alargerimpactonSMEecosystemand cohortisnottakenintoconsideration (Puklavec,et.al.,2018;Nam,et.al.,2021;Gavrila&deLucas, 2021).Futurestudiesmaywishtoexplorehumanperspective,strategicandmanagerialviewpoint, andSMEecosystemasabasefordataanalyticsinSME.…”

“…Around40%ofnationalincomeindevelopingcountriesand50%ofemploymentworldwideare representedbySmallandMediumEnterprise(SME).SMEacrosstheworldhavegrowntremendously inrecentyearsandtheyareexpectedtogrowthreetimesmoreby2030.Oncontrary,some65%of themfailorexitfrommarketeveryyear,duetoseveralreasons,suchaslackofcapability,limited funds,andlackofstrategicuseofresourcesparticularlydata (Tarek&Adel,2016;Wang&Wang, 2020).SMEplaysavitalroleinmostoftheemergingeconomies (Ward&Rhodes,2014).Remarkably, researchinthedomainofSMEshaveshowngrowinginterestamongacademia,policymakersand industryduringlastdecade.ManyresearchstudieshavehighlightedtheimportanceofSMEand theircontributioninmoderneconomy.Despiteofthis,SMEsarevulnerableandlackstrengthto withstand global competition. Subsequently it is suggested, that to survive and stay competitive, SMEsmustactpro-active,observebusinesstrends,andusedatatactically (Raj,et.al.,2016;Ojiako, et.al.,2015).Therefore,tobuildconcertedeffortstoimproveSMEcompetitiveness,dataanalytics inSMEneedsattention.…”

“…DataanalyticsinSME,simplyput,istheapplicationofstatisticalmethodsandtechnologyto processthehistoricaldataanddrawmeaningfulresults.Theseresultscanfacilitatestrategicdecision making,improvedperformanceandbetterbusinessfuture (Wang&Wang,2020).Emergedinlate 2000s,dataanalyticshavebeenhighlightedasacriticalsuccessfactorformanybusinessesinemerging economies (Nam,et.al.,2021;Liu,Y,et.al.,2020).Dataanalyticsinbusinessactsasadriverof growth in highly competitive business environment (Naeini, et.al., 2019). However, if compared tolargeenterprises,smallenterprisereflectsloworientationtowardsadoptionofdataanalyticsin business (Ojiako,et.al,2015;.Surprisingly,fewsectorsinSMElike healthcare,manufacturing,e-commerce,andretailhaveshownhighacceptanceofdataanalyticsin businessactivities (Miyamoto,2015;Gudfinnsson,et.al.,2019;Maroufkhani,et.al.,2020).Mostof theSMEsareusingdataanalyticsinreportmanagement,financialupdates,supplychainfunction andCRMfunctionsonly (Naeini,et.al.,2019;Ajibade.&Mutula,2019;Gavrila&deLucas,2021). Asaresult,itindicatesthateventodaySMEsareeitherexperiencingdiscomfortorinhibitionin implementationofdataanalytics.Thus,thereexistsahugeundefinedgapbetweenSMEsnotinvesting indataanalyticsasagainstSMEsusingdataanalyticsextensively.Toidentifyreasonsbehindgap, itisessentialtoidentifytheinhibitors,restrainingforcesandenablersofdataanalyticsinSMEs.…”