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Journal of Environmental Sciences 2019年第8期31卷 179-191页

作者： Niloy Chandra Sarker md borhan Ann-Marie Fortuna Shafiqur Rahman Agricultural and Biosystems Engineering Department North Dakota State University USDA-ARS Grazinglands Research Laboratory

Manure is an impending source of carbon(C), sulfur(S) and water(H_2 O). Consequently,microbial populations utilize these constituents to produce methane(CH4), carbon dioxide(CO_2), greenhouse gases(GHGs), and hydrogen sulfide(H_2 S). Application of nanoparticles(NPs) to stored manure is an emerging GHG mitigation technique. In this study, two NPs: nano zinc oxide(nZnO) and nano silver(nAg) were tested in swine manure stored under anaerobic conditions to determine their effectiveness in mitigating gaseous emissions and total gas production. The biological sources of gas production, i.e., microbial populations were characterized via Quantitative Polymerase Chain Reaction(qPCR) analysis. Additionally, pH, redox, and VFAs were determined using standard methods. Each treatment of the experiment was replicated three times and NPs were applied at a dose of 3 g/L of manure. Also, headspace gas from all treatment replicates were analyzed for CH_4 and CO_2 gas concentrations using an SRI-8610 Gas Chromatograph and H_2 S concentrations were measured using a Jerome 631 X meter. Nanoparticles tested in this study reduced the cumulative gas volume by 16%–79% compared to the control. Among the NPs tested, only nZnO consistently reduced GHG concentrations by 37%–97%. Reductions in H_2 S concentrations ranged from 87% to97%. Gaseous reductions were likely due to decreases in the activity and numbers of specific gas producing methanogenic archaea and sulfate reducing bacterial(SRB)species.

关键词： Swine manure Nanoparticles Greenhouse gas Methanogen Sulfate reducing bacteria(SRB)

Nanoparticles in mitigating gaseous emissions from liquid dairy manure stored under anaerobic condition

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Journal of Environmental Sciences 2019年第2期31卷 26-36页

作者： Niloy Chandra Sarker Shafiqur Rahman md.Saidul borhan Parthiban Rajasekaran Swadeshmukul Santra Ali Ozcan Agricultural and Biosystems Engineering North Dakota State University NanoScience Technology Center University of Central Florida Burnett School of Biomedical Sciences University of Central Florida Department of Chemistry University of Central Florida Department of Materials Science and Engineering University of Central Florida

A number of mitigation techniques exist to reduce the emissions of pollutant gases and greenhouse gases(GHGs) from anaerobic storage of livestock manure. Nanoparticle(NP)application is a promising mitigating treatment option for pollutant gases, but limited research is available on the mode of NP application and their effectiveness in gaseous emission reduction. In this study, zinc silica nanogel(ZnSNL), copper silica nanogel(CuSNL), and N-acetyl cysteine(NACL) coated zinc oxide quantum dot(Qdot) NPs were compared to a control lacking NPs. All three NPs tested significantly reduced gas production and concentrations compared to non-treated manure. Overall, cumulative gas volumes were reduced by 92.73%–95.83%, and concentrations reduced by 48.98%–99.75% for H_2S, and 20.24%–99.82% for GHGs. Thus, application of NPs is a potential treatment option for mitigating pollutant and GHG emissions from anaerobically stored manure.

关键词： Nanoparticles Greenhouse gas Hydrogen sulfide Anaerobic storage Gaseous reduction

Effects of Increasing Rainfall Depths and Impervious Areas on the Hydrologic Responses

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Open Journal of Modern Hydrology 2023年第2期13卷 114-128页

作者： Mosammat Mustari Khanaum md Saidul borhan Department of Civil Construction and Environmental Engineering North Dakota State University Fargo USA Texas Department of Transportation Maintenance Division Austin USA

Hydrologic modeling is a popular tool for estimating the hydrological response of a watershed. However, modeling processes are becoming more complex due to land-use changes such as urbanization, industrialization, and the expansion of agricultural activities. The primary goal of the research was to use the HEC-HMS model to evaluate the impact of impervious soil layers and the increase in rainfall-runoff processes on hydrologic processes. For these purposes, the Watershed Modelling System (WMS) and Hydrologic Engineering Center’s-Hydrologic Modeling System (HEC-HMS) models were used in this study to simulate the rainfall-runoff process. To compute runoff rate, runoff volume, base flow, and flow routing methods SCS curve number, SCS unit hydrograph, recession, and loss routing methods were selected for the research, respectively. To reduce the processing time and computational complexity, a small section of the Pipestem Creek Watershed was selected to understand the methods and concepts associated with the hydrologic simulation model building. A DEM along with other required data such as land use land cover data, soil type data, and meteorological data was utilized to delineate the watershed in WMS. The output of WMS was utilized to run the HEC-HMS model for five different scenario analyses. All the relevant data were plugged in to the model to get the desired map. Subsequently, outlets at appropriate locations were selected for the sub-basin delineation for further analysis. Finally, the model was parametrized to get successful simulation results. Overall, peak discharges and runoff volumes were increased with increasing storm depths and impervious areas. Peak discharges were increased to 36% and 51% when rainfall depths were increased by 10% and 20% from the initial rainfall depth, respectively. Runoff volumes were also increased to 35% and 49% for the same scenarios, respectively. Peak discharges were increased to 12% and 78% with a 10% and 20%, respectively, incre

关键词： Peak Discharge Runoff Impervious Area HEC-HMS WMS

Sensors and Methods for Measuring Greenhouse Gas Emissions from Different Components of Livestock Production Facilities

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Journal of Geoscience and Environment Protection 2022年第12期10卷 242-272页

作者： md Saidul borhan Mosammat Mustari Khanaum Texas Department of Transportation Maintenance Division Austin TX USA Civil Construction and Environmental Engineering Department North Dakota State University Fargo ND USA

Greenhouse gas monitoring on a broader scale is necessary to ensure that a cap-and-trade system is effective, reduces measurement uncertainty, and detects fraudulent or illegal activities. The recent strict air quality regulation in livestock production facilities has accelerated the need for accurate on-farm determination of greenhouse gas (GHG) emission rates (ERs) from livestock operations in the United States under a wide range of production, management, and climate conditions. The estimation of GHG emissions from different ground-level sources or at a property line is a very complicated process, and such measurements require multidirectional expertise including engineering, micrometeorology, agronomy, applied physics, and chemistry. Accurate measurement of gaseous concentration from an emitting source is a prerequisite and of paramount importance for estimating emissions rates (ERs) using any micro-meteorological and sampling device-based method. This paper provides an overview of the state-of-the-art sensors and analyzers used to measure GHG concentrations. Sensor and analyzer selection and their performance in the laboratory and field were discussed. In addition, protocols for data quality control (QC) and quality assurance (QA) when deploying sensors in the area for long-term use were also discussed. In addition, the preparation of measurement systems, coupling of air samplers with sensing systems for measuring gaseous concentrations, and uncertainties inherent to such measurement methods as a whole to estimate ERs were discussed in this paper.

关键词： Flux-Chamber Spectroscopic Techniques Separation Techniques Uncertainty Open-Path FTIR CRDS TDLAS

Evaluating Model Effectiveness for Soil Infiltration Attribute: Comparison of Green-Ampt, Horton and Modified Green-Ampt Infiltration Models

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Journal of Geoscience and Environment Protection 2023年第2期11卷 57-68页

作者： Mosammat Mustari Khanaum md. Saidul borhan Civil Construction and Environmental Engineering North Dakota State University Fargo ND USA Texas Department of Transportation Maintenance Division TxDOT Austin TX USA

Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous factors. Accurate estimation of soil infiltration is required for future irrigation, and many other purposes. To estimate the infiltration process, there are numerous models. The majority of them have some presumptions, a unique calculation method, and some limitations. The purpose of the paper was to assess the model’s performance for a similar hypothetical scenario involving soil infiltration. It compared the infiltration rate, runoff rate, and incremental infiltration versus time for three different infiltration models: the Green-Ampt model (GA), the Horton model and the Modified Green-Ampt (MGA) model. A spreadsheet was used to calculate the Horton model, and HYDROL-INF (V 5.03) was used to simulate the other two models. Among those three models, the MGA model outperformed those three models, while the GA model produced greater infiltration rate than rainfall, which was insensible. The study showed that the MGA model, which provides useful infiltration predictions, outperformed the other two infiltration models. Since the Horton model does not consider ponding conditions, it is only applicable when the effective rainfall intensity exceeds the final infiltration capacity. Moreover, the GA model’s initial infiltration rate is irrational because it disregards the intensity of the rainfall. The results of this study will assist in selecting the most accurate method for estimating soil infiltration for agricultural purposes.

关键词： Infiltration Groundwater Recharge Green-Ampt Horton Model Modified Green-Ampt

Anisotropic leaky-like perturbation with subwavelength gratings enables zero crosstalk

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Light(Science & Applications) 2023年第6期12卷 1153-1161页

作者： md Faiyaz Kabir md borhan Mia Ishtiaque Ahmed Nafiz Jaidye Syed Z.Ahmed Sangsik Kim Department of Electrical and Computer Engineering Texas Tech UniversityLubbockTX 79409USA Department of Physics and Astronomy Texas Tech UniversityLubbockTX 79409USA School of Electrical Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141South Korea

Electromagnetic coupling via an evanescent field or radiative wave is a primary characteristic of light,allowing optical signal/power transfer in a photonic circuit but limiting integration density.A leaky mode,which combines both evanescent field and radiative wave,causes stronger coupling and is thus considered not ideal for dense *** we show that a leaky oscillation with anisotropic perturbation rather can achieve completely zero crosstalk realized by subwavelength grating(SWG)*** oscillating fields in the SWGs enable coupling coefficients in each direction to counteract each other,resulting in completely zero *** experimentally demonstrate such an extraordinarily low coupling between closely spaced identical leaky SWG waveguides,suppressing the crosstalk by≈40 dB compared to conventional strip waveguides,corresponding to≈100 times longer coupling *** leaky-SWG suppresses the crosstalk of transverse–magnetic(TM)mode,which is challenging due to its low confinement,and marks a novel approach in electromagnetic coupling applicable to other spectral regimes and generic devices.

关键词： crosstalk coupling enable

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

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Open Journal of Air Pollution 2023年第4期12卷 142-159页

作者： Mosammat Mustari Khanaum md Saidul borhan Farzana Ferdoush Mohammed Ali Nause Russel Mustafa Murshed Department of Civil Construction and Environmental Engineering North Dakota State University Fargo USA Texas Department of Transportation Maintenance Division Austin USA Department of Arts and Sciences Ahsanullah University of Science and Technology Dhaka Bangladesh School of Social & Environmental Sustainability University of Glasgow Glasgow UK Department of Economics Andrew Young School of Policy Studies Georgia State University Atlanta USA

Air quality is a critical concern for public health and environmental regulation. The Air Quality Index (AQI), a widely adopted index by the US Environmental Protection Agency (EPA), serves as a crucial metric for reporting site-specific air pollution levels. Accurately predicting air quality, as measured by the AQI, is essential for effective air pollution management. In this study, we aim to identify the most reliable regression model among linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression, and K-nearest neighbors (KNN). We conducted four different regression analyses using a machine learning approach to determine the model with the best performance. By employing the confusion matrix and error percentages, we selected the best-performing model, which yielded prediction error rates of 22%, 23%, 20%, and 27%, respectively, for LDA, QDA, logistic regression, and KNN models. The logistic regression model outperformed the other three statistical models in predicting AQI. Understanding these models' performance can help address an existing gap in air quality research and contribute to the integration of regression techniques in AQI studies, ultimately benefiting stakeholders like environmental regulators, healthcare professionals, urban planners, and researchers.

关键词： Regression Analysis Air Quality Index Linear Discriminant Analysis Quadratic Discriminant Analysis Logistic Regression K-Nearest Neighbors Machine Learning Big Data Analysis

The link between intracellular calcium signaling and exosomal PD-L1 in cancer progression and immunotherapy

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Genes & Diseases 2024年第1期11卷 321-334页

作者： md Rakibul Alam md Mizanur Rahman Zhiguo Li Department of Toxicology and Cancer Biology College of MedicineUniversity of KentuckyLexingtonKY 40506USA Department of Medicine(Nephrology) Faculty of Medicine and DentistryUniversity of AlbertaEdmontonAlberta T6E2H7Canada

Exosomes are small membrane vesicles containing microRNA,RNA,DNA fragments,and proteins that are transferred from donor cells to recipient *** cells release exo-somes to reprogram the factors associated with the tumor microenvironment(TME)causing tu-mor metastasis and immune *** evidence revealed that cancer cell-derived exosomes carry immune inhibitory molecule program death ligand 1(PD-L1)that binds with re-ceptor program death protein 1(PD-1)and promote tumor progression by escaping immune ***,some FDA-approved monoclonal antibodies are clinicallyused for cancer treatment by blocking PD-1/PD-L1 *** notable treatment outcomes,some pa-tients show poor drug *** PD-L1 plays a vital role in lowering the treatment response,showing resistance to PD-1/PD-L1 blockage therapy through recapitulating the ef-fect of cell surface *** enhance therapeutic response,inhibition of exosomal PD-L1 is *** signaling is the central regulator of tumorigenesis and can regulate exosome biogenesis and secretion by modulating Rab GTPase family and membrane fusion ***-mune checkpoints are also connected with calcium signaling and calcium channel blockers like amlodipine,nifedipine,lercanidipine,diltiazem,and verapamil were also reported to suppress cellular PD-L1 ***,to enhance the PD-1/PD-L1 blockage therapy response,the reduction of exosomal PD-L1 secretion from cancer cells is in our therapeutic *** this review,we proposed a therapeutic strategy by targeting calcium signaling to inhibit the expression of PD-L1-containing exosome levels that could reduce the anti-PD-1/PD-L1 therapy resistance and increase the patient's drug response rate.

关键词： Calcium signaling CD8^(+)T cells Exosomal PD-L1 Exosomes biogenesis Immunosuppression Immunotherapy

Synergistic enhancement of photocatalytic and antimicrobial efficacy of nitrogen and erbium co-doped ZnO nanoparticles

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Journal of Rare Earths 2024年第5期42卷 859-868,I0002页

作者： Sudipta Mondal Moniruzzaman Jamal Sikder Ashikuzzaman Ayon md Jannatul Ferdous Anik md Muktadir Billah Department of Materials and Metallurgical Engineering Bangladesh University of Engineering and TechnologyDhaka1000Bangladesh School of Materials Engineering Purdue UniversityWest LafayetteIN47907USA Department of Materials Science and Engineering University of CaliforniaBerkeleyCA94720USA Department of Materials Science and Engineering Northwestern UniversityEvanstonI28USA

Using the chemical co-precipitation approach,a series of nitrogen(N) and erbium(Er) co-doped ZnO nanoparticles(NPs) was effectively synthesized to enhance the photocatalytic and antibacterial *** characterization techniques,including X-ray diffraction(XRD),X-ray photoelectron spectro scopy(XPS),scanning electron microscopy(SEM),UV-vis,and photoluminescence(PL) spectroscopy,were carried out to validate the evaluated photocatalytic and antibacterial *** analysis confirms the pure wurtzite ZnO phase without the presence of any secondary *** analysis confirms the succe ssful incorporation of nitrogen and erbium into the ZnO *** optical bandgap of ZnO calculated from UV-vis spectroscopy shows a redshift after Er-N co-doping,with the lowest bandgap of 3.215 eV calculated for Zn_(0.97)Er_(0.03)N_(0.01)O_(0.99) *** images demonstrate the formation of nanorods after N-Er co-doping,followed by gradually increase d rod diameter and length after N-Er ***,the photocatalytic activities of ZnO samples we re measured by their ability to facilitate the photodegradation of Rhodamine B under UV *** with 1 mol% N doping exhibits 88% photodegradation of RhB under UV light within 360 min,and the photodegradation and antibacterial activity are greatly improved with Er *** fact,3 mol% Er-1 mol% N doped ZnO NPs demonstrate the highest photocatalytic activity,with approximately 96% degradation after 360 min,as well as superior antibacterial activity against Staphylococcus aureus(Gram-positive bacteria) and Pseudomonas aeruginosa(Gram-negative bacteria) with the highest zone of inhibition(ZOI) of 16 nm,due to nanorod formation,increased reactive oxygen species(ROS),and decreased electron-hole recombination,as validated by SEM,XPS,and PL spectroscopy.

关键词： Chemical co-precipitation Co-doping Bandgap Photocatalysis Rare earths Antimicrobial

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

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Computers, Materials & Continua 2024年第4期79卷 1205-1222页

作者： Jungpil Shin md.AlMehedi Hasan md.Maniruzzaman Taiki Watanabe Issei Jozume School of Computer Science and Engineering The University of AizuAizuwakamatsuFukushima965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

关键词： Person identification leap motion hand gesture random forest support vector machine