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| 2. |
- Saeed, Aamer, et al.
(författare)
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Design, synthesis, biochemical and in silico characterization of novel naphthalene-thiourea conjugates as potential and selective inhibitors of alkaline phosphatase
- 2023
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Ingår i: Medicinal Chemistry Research. - : Springer Nature. - 1054-2523 .- 1554-8120. ; 32:6, s. 1077-1086
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Tidskriftsartikel (refereegranskat)abstract
- Naphthalene ring is present in a number of FDA-approved, commercially available medications, including naphyrone, terbinafine, propranolol, naproxen, duloxetine, lasofoxetine, and bedaquiline. By reacting newly obtained 1-naphthoyl isothiocyanate with properly modified anilines, a library of ten novel naphthalene-thiourea conjugates (5a-5j) were produced with good to exceptional yields and high purity. The newly synthesized compounds were observed for their potential to inhibit alkaline phosphatase (ALP) and scavenge free radicals. All of the investigated compounds displayed a more powerful inhibitory profile than the reference agent, KH2PO4 particularly compound 5h and 5a exhibited strong inhibitory potential against ALP with IC50 value of 0.365 +/- 0.011 and 0.436 +/- 0.057 mu M respectively. In addition, Lineweaver-Burk plots revealed the non-competitive inhibition mode of the most powerful derivative i.e., 5h (ki value 0.5 mu M). To investigate the putative binding mode of selective inhibitor interactions, molecular docking was performed. It is recommended that future research will focus on developing selective alkaline phosphatase inhibitors by modifying the structure of the 5h derivative.
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| 3. |
- Salih, Sinan Q., et al.
(författare)
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Viability of the advanced adaptive neuro-fuzzy inference system model on reservoir evaporation process simulation : case study of Nasser Lake in Egypt
- 2019
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Ingår i: Engineering Applications of Computational Fluid Mechanics. - UK : Taylor & Francis. - 1994-2060 .- 1997-003X. ; 13:1, s. 878-891
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Tidskriftsartikel (refereegranskat)abstract
- Reliable prediction of evaporative losses from reservoirs is an essential component of reservoir management and operation. Conventional models generally used for evaporation prediction have a number of drawbacks as they are based on several assumptions. A novel approach called the co-active neuro-fuzzy inference system (CANFIS) is proposed in this study for the modeling of evaporation from meteorological variables. CANFIS provides a center-weighted set rather than global weight sets for predictor–predictand relationship mapping and thus it can provide a higher prediction accuracy. In the present study, adjustments are made in the back-propagation algorithm of CANFIS for automatic updating of membership rules and further enhancement of its prediction accuracy. The predictive ability of the CANFIS model is validated with three well-established artificial intelligence (AI) models. Different statistical metrics are computed to investigate the prediction efficacy. The results reveal higher accuracy of the CANFIS model in predicting evaporation compared to the other AI models. CANFIS is found to be capable of modeling evaporation from mean temperature and relative humidity only, with a Nash–Sutcliffe efficiency of 0.93, which is much higher than that of the other models. Furthermore, CANFIS improves the prediction accuracy by 9.2–55.4% compared to the other AI models.
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| 4. |
- Tao, Hai, et al.
(författare)
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Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters
- 2023
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Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 175
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Tidskriftsartikel (refereegranskat)abstract
- This study uses machine learning (ML) models for a high-resolution prediction (0.1°×0.1°) of air fine particular matter (PM2.5) concentration, the most harmful to human health, from meteorological and soil data. Iraq was considered the study area to implement the method. Different lags and the changing patterns of four European Reanalysis (ERA5) meteorological variables, rainfall, mean temperature, wind speed and relative humidity, and one soil parameter, the soil moisture, were used to select the suitable set of predictors using a non-greedy algorithm known as simulated annealing (SA). The selected predictors were used to simulate the temporal and spatial variability of air PM2.5 concentration over Iraq during the early summer (May-July), the most polluted months, using three advanced ML models, extremely randomized trees (ERT), stochastic gradient descent backpropagation (SGD-BP) and long short-term memory (LSTM) integrated with Bayesian optimizer. The spatial distribution of the annual average PM2.5 revealed the population of the whole of Iraq is exposed to a pollution level above the standard limit. The changes in temperature and soil moisture and the mean wind speed and humidity of the month before the early summer can predict the temporal and spatial variability of PM2.5 over Iraq during May-July. Results revealed the higher performance of LSTM with normalized root-mean-square error and Kling-Gupta efficiency of 13.4% and 0.89, compared to 16.02% and 0.81 for SDG-BP and 17.9% and 0.74 for ERT. The LSTM could also reconstruct the observed spatial distribution of PM2.5 with MapCurve and Cramer's V values of 0.95 and 0.91, compared to 0.9 and 0.86 for SGD-BP and 0.83 and 0.76 for ERT. The study provided a methodology for forecasting spatial variability of PM2.5 concentration at high resolution during the peak pollution months from freely available data, which can be replicated in other regions for generating high-resolution PM2.5 forecasting maps.
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| 5. |
- Zeb, Shah, et al.
(författare)
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NOMA Enhanced Backscatter Communication for Green IoT Networks
- 2019
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Ingår i: 16th International Symposium on Wireless Communication Systems (ISWCS). - : VDE Verlag GmbH. ; , s. 640-644
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Konferensbidrag (refereegranskat)abstract
- Backscatter communication has recently emerged as a promising technology to enable passive sensing-based Internet-of-things (IoT) applications. In a backscatter communication network, uplink transmissions of multiple nodes are usually multiplexed in time- or frequency-domain to avoid collisions, yet it is desirable to improve the uplink capacity further. In this paper, we study a wireless-powered backscatter communication system, where the sensors use a hybrid channel access scheme by combining time division multiplexing access(TDMA) with power-domain non-orthogonal multiple access(PD-NOMA) to enhance the system performance in terms of outage probability and throughput. Our analysis shows that the proposed PD-NOMA increases both the spectrum efficiency and the throughput of the system.
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| 6. |
- Hashmi, Muhammad Usman, et al.
(författare)
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Concomitant Skew and Phase Correction (CSPC) for Industry 5.0 Enabler Pervasive Distributed Computing Systems
- 2023
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Ingår i: IEEE Transactions on Consumer Electronics. - : Institute of Electrical and Electronics Engineers Inc.. - 0098-3063. ; 70:1, s. 1511-1518
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Tidskriftsartikel (refereegranskat)abstract
- Synchronizing time among pervasive distributed computing nodes is critical and also a key enabler for proper functioning and coordination in an Industry 5.0 environment. It enables distributed data logging, coordination of distributed algorithms, and event driven interactions in a synchronized manner which is not possible without having a common notion of time in an Industry 5.0 environment. Synchronization ensures that data generated by pervasive nodes is consistent and accurate. Diverse synchronization methods are available, however, these existing methods use multiple timestamp exchanges for correction of clock skew. Concomitant Skew and Phase Correction (CSPC) method proposed in this article uses Phase Embedded and Skew Estimated Timestamp (PESET). In contrary to existing methods, single PESET is sufficient to compute clock skew offset along with phase offset at the receiving node. The experimental results also validate single PESET can be used instead of multiple timestamp exchanges in low latency Industry 5.0 environments. This does not only lead to save the computational resources of the Industry 5.0 environments, also enable them as energy efficient networks.
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| 7. |
- Hou, Muzhou, et al.
(författare)
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Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
- 2018
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Ingår i: Energies. - : MDPI. - 1996-1073. ; 11:12
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Tidskriftsartikel (refereegranskat)abstract
- Accurate global solar radiation prediction is highly essential for related research on renewable energy sources. The cost implication and measurement expertise of global solar radiationemphasize that intelligence prediction models need to be applied. On the basis of long-term measured daily solar radiation data, this study uses a novel regularized online sequential extreme learning machine, integrated with variable forgetting factor (FOS-ELM), to predict global solar radiation at Bur Dedougou, in the Burkina Faso region. Bayesian Information Criterion (BIC) is applied to build the seven input combinations based on speed (Wspeed), maximum and minimum temperature (Tmax and Tmin), maximum and minimum humidity (Hmax and Hmin), evaporation (Eo) and vapor pressure deficiency (VPD). For the difference input parameters magnitudes, seven models were developed and evaluated for the optimal input combination. Various statistical indicators were computed for the prediction accuracy examination. The experimental results of the applied FOS-ELM model demonstrated a reliable prediction accuracy against the classical extreme learning machine (ELM) model for daily global solar radiation simulation. In fact, compared to classical ELM, the FOS-ELM model reported an enhancement in the root mean square error (RMSE) and mean absolute error(MAE) by (68.8–79.8%). In summary, the results clearly confirm the effectiveness of the FOS-ELM model, owing to the fixed internal tuning parameters.
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| 8. |
- Hussain, Fida, et al.
(författare)
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A modeling approach for low-temperature SOFC-based micro-combined heat and power systems
- 2019
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Ingår i: International Journal of Modern Physics B. - : WORLD SCIENTIFIC PUBL CO PTE LTD. - 0217-9792. ; 33:4
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Tidskriftsartikel (refereegranskat)abstract
- The world's challenge is to determine a more efficient, economical and environmental-friendly energy source to compete and replace the ongoing conventional energy resources. Solid oxide fuel cells (SOFCs) provide a highly efficient system to use divergent energy resources and have proved to provide the cleanest energy, least energy use, and lowest emissions. A techno-economic study is required to investigate the model design for SOFC-based micro-combined heat and power (m-CHP) systems for applications in terms of educational and commercial buildings. This work models and explores the optimized application of hydrogen gas-fueled SOFC-based m-CHP systems in educational buildings. Two educational departments' loads are presented and model of SOFC-based m-CHP system against the different electric power demands is performed, in order to provide a techno-economic assessment of the technology. For successful development of the technology, results are related to system rightsizing, operating strategies, thermal to electric ratios, and match between end-use, with an aim towards classifying the overall feasibility and essential application requirements.
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| 9. |
- Hussain, Fida, et al.
(författare)
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Comparative electrochemical investigation of zinc based nano-composite anode materials for solid oxide fuel cell
- 2019
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Ingår i: Ceramics International. - : Elsevier. - 0272-8842 .- 1873-3956. ; 45:1, s. 1077-1083
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Tidskriftsartikel (refereegranskat)abstract
- The structural and electrochemical properties of zinc based nano-composites anode materials with a composition of X0.25Ti0.5Zn0.70 (where X = Cu, Mn, Ag) have been investigated in this present study. The proposed Xo.zsTiousZno.70 oxide materials have been synthesized through sol-gel method. The doping effect of Cu, Mn, and Ag on TiZn oxides were analyzed in terms of electronic conduction and power density in hydrogen atmosphere at comparatively low temperature in the range of 650 degrees C. The crystal structure and surface morphology were examined by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis techniques. The XRD patterns of composites depict that the average crystalline sizes lie in the range of 20-100 nm. Four -probe DC conductivity technique was used to measure the conductivity of the materials and maximum electrical conductivity of Ag0.25Ti0.05Zn0.70 oxide was found to be 7.81 S/cm at 650 degrees C. The band gap and absorption spectra were determined by ultra-violet visible (UV-Vis) and Fourier Transform Infrared spectroscopy (FTIR) techniques respectively. The maximum power density was achieved to be 354 mW/cm(2) at 650 degrees C by Ag0.25Ti0.05Zn0.70 oxide anode with SDC (electrolyte) and BSCF (conventional cathode) materials.
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| 10. |
- Khan, Mumtaz Ali, et al.
(författare)
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Health risks associated with radon concentrations in carbonate and evaporite sequences of the uranium-rich district Karak, Pakistan
- 2022
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Ingår i: Frontiers in Environmental Science. - : Frontiers Media S.A.. - 2296-665X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- The present research was carried out to investigate the behavior of radon (222Rn) concentrations over the carbonate and evaporite sequences and to assess the related health hazards. A total of 50 points from three different stratigraphic units, namely, the Bahadurkhel Salt, Jatta Gypsum, and the Kohat Formation of the Eocene age, were analyzed for radon concentrations in the district of Karak, Khyber Pakhtunkhwa, Pakistan. Measurements for radon levels were made by using RAD7 of Durridge, United States. The highest average 222Rn concentration (16.5 Bq/L) was found in the limestone unit of the Kohat Formation of the Eocene age. However, the lowest radon levels were observed in the salt-bearing strata of the Bahadurkhel Salt of the Eocene age. The study revealed that the average radon concentration in all the lithologies varied in the order of RnLimestone > RnSalt > RnGypsum. The findings of the current research suggest that the study area is safe from radon-related health hazards.
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