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A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

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Computer Modeling in engineering & Sciences 2024年第4期139卷 593-631页

作者： Nilkanth Mukund Deshpande Shilpa Gite Biswajeet Pradhan Abdullah Alamri Chang-Wook Lee department of Electronics&Telecommunication LavaleSymbiosis Institute of TechnologySymbiosis International(Deemed University)PuneMaharashtra412115India Electronics&Telecommunication Dr.Vithalrao Vikhe Patil College of EngineeringAhmednagarMaharashtra414111India Artificial Intelligence and Machine Learning department Symbiosis Institute of TechnologySymbiosis International(Deemed)UniversityPune412115India symbiosis Centre of Applied AI(SCAAI) Symbiosis International(Deemed)UniversityPune412115India Centre for AdvancedModelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering&ITUniversity of Technology SydneySydneyAustralia Earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia department of Geology&Geophysics College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia department of Science Education Kangwon National UniversityChuncheon-si24341Korea

Infection of leukemia in humans causes many complications in its later *** impairs bone marrow’s ability to produce *** diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this *** binary classification is employed to distinguish between normal and leukemiainfected *** addition,various subtypes of leukemia require different *** sub-classes must also be detected to obtain an accurate diagnosis of the type of *** entails using multi-class classification to determine the leukemia *** is usually done using a microscopic examination of these blood *** to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for *** utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of *** advanced deep-learning methods are also *** to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding *** study introduces a deep learning-machine learning combined approach for leukemia *** uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning *** transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature *** extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia *** the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the *** d

关键词： Leukemia diagnosis deep learning machine learning random forest XGBoost

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Biodegradability of bioplastics in different aquatic environments:A systematic review

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Journal of environmental Sciences 2024年第8期142卷 169-181页

作者： Maria Cristina Lavagnolo Valentina Poli Anna Maria Zampini Valentina Grossule department of Civil Environmental and Architectural Engineering-Laboratory of Environmental EngineeringUniversity of PadovaLungargine Rovetta 8Padova 35100Italy

Bioplastics were first introduced as environmentally friendly materials,with properties similar to those of conventional plastics.A bioplastic is defined as biodegradable if it can be decomposed into carbon dioxide under aerobic degradation,or methane and CO_(2)under anaerobic conditions,inorganic compounds,and new cellular biomass,by the action of naturally occurring *** definition however does not provide any information on the environmental conditions,timescale and extent at which decomposition processes should *** regard to the aquatic environment,recognized standards have been established to assess the ability of plastics to undergo biodegradation;however,these standards fail to provide clear targets to be met to allow labelling of a bioplastic as ***,these standards grant the user an extensive leeway in the choice of process *** these reasons,the comparison of results deriving from different studies is *** authors analysed and discussed the degree of biodegradability of a series of biodegradable bioplastics in aquatic environments(both fresh and salt water)using the results obtained in the laboratory and from on-site testing in the context of different research *** Oxygen Demand(BOD),CO_(2)evolution,surface erosion and weight loss were the main parameters used by researchers to describe the percentage of *** results showed a large variability both in weight loss and BOD,even when evaluating the same type of *** confirms the need for a reference range of values to be established with regard to parameters applied in defining the biodegradability of bioplastics.

关键词： Biodegradation Bioplastic Plastic Natural environment Plastic waste

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Assessment of the implementation status of best available techniques for cleaner production in the textile industry

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Frontiers of environmental Science & engineering 2024年第8期18卷 133-148页

作者： Mehmet Eren Yaman Emrah Ozturk Ulku Yetis Mehmet Kitis department of environmental engineering Suleyman Demirel UniversityIsparta 32260Turkey department of environmental Protection Technologies Isparta University of Applied SciencesIsparta 32200Turkey department of environmental engineering Middle East Technical UniversityAnkara 06800Turkey

The draft Integrated Pollution Prevention and Control(IPPC)regulation mandates compliance with best available techniques(BATs)for textile manufacturers.A study in Turkish textile facilities,covering 56 units across four sub-sectors,assessed the status of 488 BATs through on-site visits and *** aim was to gauge the sector’s adherence to *** findings revealed that 37% of surveyed BATs were fully implemented,rising to 88% when considering potential future *** suggests a strong industry inclination toward adopting BATs for cleaner production and *** study highlighted significant BAT-related investments in the textile sector,driven by environmental concerns,regulations,customer demands,resource efficiency,competition,and cost-benefit ***,the study results also indicated that there is still much work to do for the implementation of some *** was found that 60 BATs had lower implementation ratios(IR:0%-43%).Lower IR values for these BATs are mainly due to factors like specificity,high costs,long payback periods,operational difficulties,limited expertise,space constraints,customer requirements,quality concerns,operational issues,and sector-specific *** study recommends similar assessments in other European industrial sectors to evaluate compliance with mandatory BATs outlined in the Industrial Emissions *** insights from this study on the Turkish textile sector can serve as a valuable guide for future evaluations.

关键词： Best available techniques(BAT) Cleaner production Green Deal Integrated Pollution Prevention and Control(IPPC) Textile sector

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Enhanced termination of zinc and cadmium ions from wastewater employing plain and chitosan-modified mxenes: synthesis, characterization,and adsorption performance

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Green Chemical engineering 2024年第3期5卷 339-347页

作者： Njood R.Azeez Suhaib S.Salih Mohammed Kadhom Harith N.Mohammed Tushar K.Ghosh department of Chemical engineering College of Engineering University of Tikrit department of environmental Science College of Energy and Environmental Science Al-Karkh University of Science department of Nuclear Science & engineering Institute University of Missouri-Columbia

Zinc and cadmium pollutants cause a significant environmental effect that cannot be ignored. Due to their considerable amount in an aqueous environment, industries are seeking suitable adsorbents that are environmentally friendly and inexpensive for removing metals from wastewater before disposing of them in surface waters. This research employed original MXene(MX) and chitosan-modified MXene(CSMX) to extract zinc(Zn(Ⅱ)) and cadmium(Cd(Ⅱ)) metal ions from water-based solutions. The composite material produced was analyzed using techniques such as X-ray Diffraction(XRD), Scanning Electron Microscopy(SEM), Fourier Transform Infrared Spectroscopy(FTIR), and Brunauer-Emmett-Teller(BET). The effects of contact duration, p H of the solution, and initial concentration of metal ions on the adsorption process of Zn(Ⅱ) and Cd(Ⅱ) onto both MX and CSMX composites were investigated. MX and prepared CSMX composite presented a high adsorption capacity for both studied heavy metals, which were 91.55 and 73.82 mg/g for Zn(Ⅱ) and Cd(Ⅱ) onto MX, 106.84 and 93.07 mg/g for Cd(Ⅱ) and Zn(Ⅱ) onto CSMX composite, respectively. Furthermore, the maximum competitive adsorption capacities for Zn(Ⅱ) onto MX and CSMX composites are 77.29 and 93.47 mg/g, and for are Cd(Ⅱ)60.30 and 79.66 mg/g, respectively. Hence, the removal capacities for both single and competitive metal ions were superior to CSMX composite. However, the adsorption capacities after five successive regeneration sequences were only dropped by 13.2% for Zn(Ⅱ) and 17.4% for Cd(Ⅱ) onto the CSMX composite compared to the first cycle. These results confirm that both metals could be efficiently terminated from wastewater, which makes the prepared CSMX composite a favorable candidate adsorbent in practical applications.

关键词： Adsorption Chitosan MXene Zn(II) Cd(II) Wastewater

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Estimating the frequency of traffic overloading on road bridges

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Journal of Traffic and Transportation engineering(English Edition) 2024年第4期11卷 776-796页

作者： Roberto Ventura Benedetto Barabino Giulio Maternini department of Civil Environmental Architectural Engineering and Mathematics University of Brescia

Load limits, which appear to be routinely exceeded by trucks, occasionally result in road bridge failures. Therefore, predicting failures is crucial for safeguarding road safety. Past studies have largely focused on forecasting bridge failure event probability using the reliability analysis method, whilst occasionally accounting for vehicular overloading effects. Only recently, a study has investigated design traffic overloading event frequency using generalised linear regression models(GLRMs), including a power component and negative binomial regressions(NBRs). However, as far as the authors know, artificial neural network models(ANNMs) have never been applied to this field. This paper is an attempt to fill in these gaps. First a frequencybased metric of traffic overloading was adopted as a driver of failure probability. Second, two alternative ‘frequency' models were specified, calibrated, and validated. The former was based on a GLRM, the latter on ANNMs. Then, these models were compared using regression plots(RPs), measures of errors(Mo Es) and the ratio between the number of observed vs predicted design load overcoming events to evaluate their performance. The models analysed more than 2 million weigh-in-motion(WIM) data records from a pilot station on a bridge on a heavily used ring road in Brescia(Italy). Results showed that ANNMs outperformed *** have a higher correlation coefficient(between predicted and target frequencies),lower Mo Es, and a closer-to-unity ratio(between predicted and target frequencies). These findings may increase prediction accuracy of design traffic overloading events and give road authorities more effective traffic management to protect bridges from load hazards.

关键词： Road bridges Traffic load hazard Econometry Machine learning Weigh-in-motion Big-data analysis

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Surface engineering with ionic polymers on membranes for boron removal

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Frontiers of Chemical Science and engineering 2024年第5期18卷 61-69页

作者： Xiting Zhang Chenyi Fang J Paul Chen Sui Zhang department of Chemical and Biomolecular engineering National University of SingaporeSingapore 117576Singapore department of Civil and environmental engineering National University of SingaporeSingapore 119260Singapore College of Chemistry and environmental engineering Shenzhen UniversityShenzhen 518060China

Removal of boric acid from seawater and wastewater using reverse osmosis membrane technologies is imperative and yet remains inadequately addressed by current commercial *** research efforts performed post-modification of reverse osmosis membranes to enhance boron rejection,which is usually accompanied by substantial sacrifice in water *** study delves into the surface engineering of low-pressure reverse osmosis membranes,aiming to elevate boron removal efficiency while maintaining optimal salt rejection and water *** were modified by the self-polymerization and co-deposition of dopamine and polystyrene sulfonate at varying ratios and *** surfaces became smoother and more hydrophilic after *** optimum membrane exhibited a water permeability of 9.2±0.1 L·m^(-2)·h^(-1)·bar^(-1),NaCl rejection of 95.8%±0.3%,and boron rejection of 49.7%±0.1% and 99.6%±0.3% at neutral and alkaline pH,*** water permeability is reduced by less than 15%,while the boron rejection is 3.7 times higher compared to the blank *** research provides a promising avenue for enhancing boron removal in reverse osmosis membranes and addressing water quality concerns in the desalination process.

关键词： membrane low-pressure reverse osmosis boron surface engineering

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Evaluation of the coefficient of lateral stress at rest of granular materials under repetitive loading conditions

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Journal of Rock Mechanics and Geotechnical engineering 2024年第5期16卷 1709-1721页

作者： Heerym Han Hyunwook Choo Junghee Park department of Civil and environmental engineering Hanyang UniversitySeoul04763South Korea department of Civil and environmental engineering Incheon National UniversityIncheon22012South Korea

Although the internal stress state of soils can be affected by repetitive loading,there are few studies evaluating the lateral stress(or K_(0))of soils under repetitive *** study investigates the changes in K_(0) and directional shear wave velocity(V_(s))in samples of two granular materials with different particle shapes during repetitive loading.A modified oedometer cell equipped with bender elements and a diaphragm transducer was developed to measure the variations in the lateral stress and the shear wave velocity,under repetitive loading on the loading and unloading *** study produced the following results:(1)Repetitive loading on the loading path resulted in an increase in the K_(0) of test samples as a function of cyclic loading number(i),and(2)Repetitive loading on the unloading path resulted in a decrease in K_(0) according to *** shear wave velocity ratio(i.e.V_(s)(HH)/V_(s)(VH),where the first and second letters in parentheses corresponds to the directions of wave propagation and particle motion,respectively,and V and H corresponds to the vertical and horizontal directions,respectively)according to i supports the experimental observations of this ***,when the tested material was in lightly over-consolidated state,there was an increase in K_(0) during repetitive loading,indicating that it was the initial K_(0),rather than the loading path,which is responsible for the change in K_(0).The power model can capture the variation in the K_(0) of samples according to ***,the K_(0)=1 line acts as the boundary between the increase and decrease in K_(0) under repetitive loading.

关键词： Coefficient of lateral stress at rest Repetitive loading Granular materials Shear wave velocity Stiffness anisotropy

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Antibiotic ciprofloxacin removal from aqueous solutions by electrochemically activated persulfate process:Optimization,degradation pathways,and toxicology assessment

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Journal of environmental Sciences 2024年第9期143卷 85-98页

作者： Elif Yakamercan Ahmet Aygün Halis Simsek environmental engineering department Bursa Technical UniversityBursaTurkey Agricultural and Biological engineering department Purdue UniversityWest LafayetteINUSA

Ciprofloxacin(CIP)is a commonly used antibiotic in the fluoroquinolone group and is widely used in medical and veterinary medicine disciplines to treat bacterial *** CIP is discharged into the sewage system,it cannot be removed by a conventional wastewater treatment plant because of its recalcitrant *** this study,boron-doped diamond anode and persulfate were used to degrade CIP in an aquatic solution by creating an electrochemically activated persulfate(EAP)*** added to the system as a coactivator and the process was called EAP+*** effects of independent variables,including pH,Fe^(2+),persulfate concentration,and electrolysis time on the systemwere optimized using the response surface *** results showed that the EAP+Fe process removed 94%of CIP under the following optimum conditions:A pH of 3,persulfate/Fe^(2+)concentration of 0.4 mmol/L,initial CIP concentration 30 mg/L,and electrolysis time of 12.64 *** removal efficiency was increased from 65.10%to 94.35%by adding Fe^(2+)as a transition *** degradation products,7 pathways,and 78 intermediates of CIP were studied,and three of those intermediates(m/z 298,498,and 505)were *** toxicological analysis based on toxicity estimation software results indicated that some degradation products of CIP were toxic to targeted animals,including fathead minnow,Daphnia magna,Tetrahymena pyriformis,and *** optimumoperation costswere similar in EAP and EAP+Fe processes,approximately 0.54€/m^(3).

关键词： Ciprofloxacin Response surface methodology Electrochemically activated persulfate Electrooxidation

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Spherical Bi_(2)O_(3)/ATO catalyst with N_(2)pre-reduction electrocatalytic reduction of CO_(2)to formic acid

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Journal of environmental Sciences 2024年第6期140卷 331-340页

作者： Junying Yi Yuli Chen Dongze Lai Bihong Lv Xiaomin Wu Guohua Jing department of environmental Science&engineering College of Chemical EngineeringHuaqiao UniversityXiamenFujian 361021China

To achieve carbon neutrality,the Chinese government needs to gain a comprehensive understanding of the sources and drivers of greenhouse gas(GHG)emissions,particularly at the county *** County in eastern China is a typical example of an industrial transformation from quarrying to a low-carbon *** study analyzed the decoupling types and structural characteristics of GHG emissions and the driving factors of carbon dioxide(CO_(2))emissions in the Anji from 2006 to 2019,and explored the differences between countylevel and provincial-level or city-level *** was observed that energy-related activities are the main source of GHG emissions in Anji and that economic development is the driving factor behind the increasing CO_(2)***,industrial transformation and upgradation coupled with the alternative use of clean energy limit the growth of GHG *** study details the GHG emissions of county during the industrial transformation stage and provides corresponding policy recommendations for county governments.

关键词： N_(2)prereduction CO_(2)electroreduction Bi_(2)O_(3)/ATO catalyst Formate

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A reinforcement learning approach for thermostat setpoint preference learning

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Building Simulation 2024年第1期17卷 131-146页

作者： Hussein Elehwany Mohamed Ouf Burak Gunay Nunzio Cotrufo Jean-Simon Venne department of environmental engineering Carleton UniversityOttawaCanada departmentof Building Civiland Environmental EngineeringConcordia UniversityMontrealCanada BrainBox Al Inc. MontrealCanada

Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy *** OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints *** recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant *** studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat *** paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat *** algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of *** simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration *** substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.

关键词： reinforcement learning preference learning occupant-centric controls smart thermostats off-policy learning

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