| 1. |
- Niemi, MEK, et al.
(författare)
-
- 2021
-
swepub:Mat__t
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
- Arslan, Muhammad, et al.
(författare)
-
Impact of Varying Load Conditions and Cooling Energy Comparison of a Double-Inlet Pulse Tube Refrigerator
- 2020
-
Ingår i: Processes. - : MDPI. - 2227-9717. ; 8:3
-
Tidskriftsartikel (refereegranskat)abstract
- Modeling and optimization of a double-inlet pulse tube refrigerator (DIPTR) is very difficult due to its geometry and nature. The objective of this paper was to optimize-DIPTR through experiments with the cold heat exchanger (CHX) along the comparison of cooling load with experimental data using different boundary conditions. To predict its performance, a detailed two-dimensional DIPTR model was developed. A double-drop pulse pipe cooler was used for solving continuity, dynamic and power calculations. External conditions for applicable boundaries include sinusoidal pressure from an end of the tube from a user-defined function and constant temperature or limitations of thermal flux within the outer walls of exchanger walls under colder conditions. The results of the system's cooling behavior were reported, along with the connection between the mass flow rates, heat distribution along pulse tube and cold-end pressure, the cooler load's wall temp profile and cooler loads with varied boundary conditions i.e. opening of 20% double-inlet and 40-60% orifice valves, respectively. Different loading conditions of 1 and 5W were applied on the CHX. At 150 K temperature of the cold-end heat exchanger, a maximum load of 3.7 W was achieved. The results also reveal a strong correlation between computational fluid dynamics modeling results and experimental results of the DIPTR.
|
|
| 6. |
- Habeeb, Rimsha, et al.
(författare)
-
Modified Standardized Precipitation Evapotranspiration Index: spatiotemporal analysis of drought
- 2023
-
Ingår i: Geomatics, Natural Hazards and Risk. - : Taylor & Francis. - 1947-5705 .- 1947-5713. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- Drought monitoring is a complicated issue as it requires multiple meteorological variables to monitor and anticipate drought accurately. Therefore, developing a method that enables researchers, data scientists, and planners to comprehend drought mitigation policies more accurately is essential. In this research, based on the concepts behind the calculation of the Standardized Precipitation Evapotranspiration Index (SPEI), a new drought index is proposed for regional drought monitoring: the Modified Standardized Precipitation Evapotranspiration Index (MSPEI). The potential of the proposed index is based on the estimation of Reference Evapotranspiration (ETo). Therefore, the Modified Hargreaves-Samani (MHS) equation based on fuzzy logic calibration is used to estimate ETo. The proposed index is validated on ten meteorological stations in Pakistan at a one-month time scale. Afterward, based on the Pearson correlation, the performance of the proposed index is compared with the commonly used drought index (SPEI). Results showed a significant correlation (r > 0.7) between the quantitative values of MSPEI and SPEI for all ten stations. Moreover, a modified Tjostheims coefficient is used to estimate and test the spatial correlation between SPEI and MSPEI for different drought classes. According to our findings, the association between the SW, ND, ED, EW, MW, and SD patterns of MSPEI and SPI is 0.74, 0.834, 0.673, 0.592, 0.393, and 0.434, respectively. Meanwhile, considering the significance of future drought trend detection, this research is further extended to detect the future trend of MSPEI by using the Hurst index. In accordance with the results, Bahawalnagar, Sialkot, Lahore, Kotli, and Gilgit all have HI values greater than 0.5 (0.63, 0.58, 0.56, 0.55, and 0.53, respectively). In contrast, Muzaffarabad, Skardu, and Jhelum have HI values 0.47, 0.45 and 0.38, respectively; however, HI values of 0.5 are observed at Dera Ismail Khan (DIK) and Islamabad. Therefore, this research provides a basis for developing and enhancing drought hazard characterization, encouraging researchers and policymakers to monitor and forecast regional droughts using a more accurate drought index.
|
|
| 7. |
- Hawkes, Jeffrey A., et al.
(författare)
-
An international laboratory comparison of dissolved organic matter composition by high resolution mass spectrometry : Are we getting the same answer?
- 2020
-
Ingår i: Limnology and Oceanography. - : Wiley. - 1541-5856. ; 18:6, s. 235-258
-
Tidskriftsartikel (refereegranskat)abstract
- High-resolution mass spectrometry (HRMS) has become a vital tool for dissolved organic matter (DOM) characterization. The upward trend in HRMS analysis of DOM presents challenges in data comparison and interpretation among laboratories operating instruments with differing performance and user operating conditions. It is therefore essential that the community establishes metric ranges and compositional trends for data comparison with reference samples so that data can be robustly compared among research groups. To this end, four identically prepared DOM samples were each measured by 16 laboratories, using 17 commercially purchased instruments, using positive-ion and negative-ion mode electrospray ionization (ESI) HRMS analyses. The instruments identified similar to 1000 common ions in both negative- and positive-ion modes over a wide range of m/z values and chemical space, as determined by van Krevelen diagrams. Calculated metrics of abundance-weighted average indices (H/C, O/C, aromaticity and m/z) of the commonly detected ions showed that hydrogen saturation and aromaticity were consistent for each reference sample across the instruments, while average mass and oxygenation were more affected by differences in instrument type and settings. In this paper we present 32 metric values for future benchmarking. The metric values were obtained for the four different parameters from four samples in two ionization modes and can be used in future work to evaluate the performance of HRMS instruments.
|
|
| 8. |
- Keating, C., et al.
(författare)
-
Drivers of ecological assembly in the hindgut of Atlantic Cod fed a macroalgal supplemented diet
- 2022
-
Ingår i: Npj Biofilms and Microbiomes. - : Springer Science and Business Media LLC. - 2055-5008. ; 8:1
-
Tidskriftsartikel (refereegranskat)abstract
- It is difficult to disentangle the many variables (e.g. internal or external cues and random events) that shape the microbiota in the gastrointestinal tract of any living species. Ecological assembly processes applied to microbial communities can elucidate these drivers. In our study, farmed Atlantic cod (Gadus morhua) were fed a diet of 10% macroalgae supplement (Ulva rigida [ULVA] or Ascophyllum nodosum [ASCO] or a non-supplemented control diet [CTRL]) over 12 weeks. We determined the influence of ecological assembly processes using a suite of null-modelling tools. We observed dissimilarity in the abundance of common OTUs over time, which was driven by deterministic assembly. The CTRL samples showed selection as a critical assembly process. While dispersal limitation was a driver of the gut microbiome for fish fed the macroalgae supplemented diet at Week 12 (i.e., ASCO and ULVA). Fish from the ASCO grouping diverged into ASCO_N (normal) and ASCO_LG (lower growth), where ASCO_LG individuals found the diet unpalatable. The recruitment of new taxa overtime was altered in the ASCO_LG fish, with the gut microbiome showing phylogenetic underdispersion (nepotistic species recruitment). Finally, the gut microbiome (CTRL and ULVA) showed increasing robustness to taxonomic disturbance over time and lower functional redundancy. This study advances our understanding of the ecological assembly and succession in the hindgut of juvenile Atlantic cod across dietary treatments. Understanding the processes driving ecological assembly in the gut microbiome, in fish research specifically, could allow us to manipulate the microbiome for improved health or resilience to disease for improved aquaculture welfare and production.
|
|
| 9. |
- Keating, C., et al.
(författare)
-
Temporal changes in the gut microbiota in farmed Atlantic cod (Gadus morhua) outweigh the response to diet supplementation with macroalgae
- 2021
-
Ingår i: Animal Microbiome. - : Springer Science and Business Media LLC. - 2524-4671. ; 3:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background Aquaculture successfully meets global food demands for many fish species. However, aquaculture production of Atlantic cod (Gadus morhua) is just 2.5% of total market production. For cod farming to be a viable economic venture specific challenges on how to increase growth, health and farming productivity need to be addressed. Feed ingredients play a key role here. Macroalgae (seaweeds) have been suggested as a functional feed supplement with both health and economic benefits for terrestrial farmed animals and fish. The impact of such dietary supplements to cod gut integrity and microbiota, which contribute to overall fish robustness is unknown. The objective of this study was to supplement the diet of juvenile Atlantic cod with macroalgae and determine the impacts on fish condition and growth, gut morphology and hindgut microbiota composition (16S rRNA amplicon sequencing). Fish were fed one of three diets: control (no macroalgal inclusion), 10% inclusion of either egg wrack (Ascophyllum nodosum) or sea lettuce (Ulva rigida) macroalgae in a 12-week trial. Results The results demonstrated there was no significant difference in fish condition, gut morphology or hindgut microbiota between the U. rigida supplemented fish group and the control group at any time-point. This trend was not observed with the A. nodosum treatment. Fish within this group were further categorised as either 'Normal' or 'Lower Growth'. 'Lower Growth' individuals found the diet unpalatable resulting in reduced weight and condition factor combined with an altered gut morphology and microbiome relative to the other treatments. Excluding this group, our results show that the hindgut microbiota was largely driven by temporal pressures with the microbial communities becoming more similar over time irrespective of dietary treatment. The core microbiome at the final time-point consisted of the orders Vibrionales (Vibrio and Photobacterium), Bacteroidales (Bacteroidetes and Macellibacteroides) and Clostridiales (Lachnoclostridium). Conclusions Our study indicates that U. rigida macroalgae can be supplemented at 10% inclusion levels in the diet of juvenile farmed Atlantic cod without any impact on fish condition or hindgut microbial community structure. We also conclude that 10% dietary inclusion of A. nodosum is not a suitable feed supplement in a farmed cod diet.
|
|
| 10. |
- Niaz, Rizwan, et al.
(författare)
-
Assessing the Probability of Drought Severity in a Homogeneous Region
- 2022
-
Ingår i: Complexity. - UK : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2022
-
Tidskriftsartikel (refereegranskat)abstract
- The standardized precipitation index (SPI) is one of the most widely used indices for characterizing and monitoring drought in various regions. SPI's applicability has regional and time-scale constraints when it observes in several homogeneous climatic regions with similar characteristics. It also does not provide sufficient knowledge about precipitation deficits and the spatiotemporal evolution of drought. Therefore, a new method, the regional spatially agglomerative continuous drought probability monitoring system (RSACDPMS), is proposed to obtain spatiotemporal information and monitor drought characteristics more expeditiously. The proposed framework uses spatially agglomerative precipitation (SAP) and copulas’ functions to continuously monitor the drought probability in the homogenous region. The RSACDPMS is validated in the region of the Northern area of Pakistan. The outcomes of the current study provide a better quantitative way to obtain appropriate information about precipitation deficits and the spatiotemporal evolution of drought.
|
|
| 11. |
- Raza, Muhammad Ahmad, et al.
(författare)
-
A New Bayesian Network-Based Generalized Weighting Scheme for the Amalgamation of Multiple Drought Indices
- 2023
-
Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526.
-
Tidskriftsartikel (refereegranskat)abstract
- Drought is one of the most multifaceted hydrologic phenomena, affecting several factors such as soil moisture, surface runoff, and significant water shortages. Therefore, monitoring and assessing drought occurrences based on a single drought index are inadequate. The current study develops a multiscalar weighted amalgamated drought index (MWADI) to amalgamate multiple drought indices. The MWADI is mainly based on the normalized average dependence posterior probabilities (ADPPs). These ADPPs are obtained from Bayesian networks (BNs)-based Markov Chain Monte Carlo (MCMC) simulations. Results have shown that the MWADI correlates more with the standardized precipitation index (SPI) and the standardized precipitation temperature index (SPTI). As proposed, the MWADI synthesizes drought characteristics of different multiscalar drought indices to reduce the uncertainty of individual drought indices and provide a comprehensive drought assessment.
|
|
| 12. |
- Raza, Muhammad Ahmad, et al.
(författare)
-
Bayesian logistic regression analysis for spatial patterns of inter-seasonal drought persistence
- 2023
-
Ingår i: Geocarto International. - : Taylor & Francis. - 1010-6049 .- 1752-0762. ; 38:1
-
Tidskriftsartikel (refereegranskat)abstract
- Drought is one of the disastrous natural hazards with complex seasonal and spatial patterns. Understanding the spatial patterns of drought and predicting the likelihood of inter-seasonal drought persistence can provide substantial operational guidelines for water resource management and agricultural production. This study examines drought persistence by identifying the spatial patterns of seasonal drought frequency and inter-seasonal drought persistence in the northeastern region of Pakistan. The Standardized Precipitation Index (SPI) with a three-month time scale is used to examine meteorological drought. Furthermore, Bayesian logistic regression is used to calculate the probability and odds ratios of drought occurrence in the current season, given the previous season's SPI values. For instance, at Balakot station, for the summer-to-autumn season, the value of the odds ratio is significant (6.78). It shows that one unit increase in SPI of the summer season will cause a 5.78 times to increase in odds of autumn drought occurrence. The average drought frequency varies from 37.3 to 89.1%, whereas the average inter-seasonal drought persistence varies from 21.9 to 91.7% in the study region. Results indicate that some areas in the study region, like Kakul and Garhi Dupatta, are more prone to drought and vulnerable to inter-seasonal drought persistence. Furthermore, the Bayesian logistic regression results reveal a negative relationship between spring drought occurrence and winter SPI, demonstrating that the overall study region is more prone to winter-to-spring drought persistence and less vulnerable to summer-to-autumn drought persistence. Overall study has concluded that the region's seasonal drought forecast is challenging due to uncertain drought persistence patterns. However, the Bayesian logistic regression model provides more accurate and precise regional seasonal drought forecasts. The outcome of the present study provides scientific evidence to develop early warning systems and manage seasonal crops in Pakistan.
|
|
| 13. |
- Rehman, Atiq Ur, et al.
(författare)
-
Salp Swarm Algorithm for Drift Compensation in E-nose
- 2023
-
Ingår i: 2023 15th International Conference on Advanced Computational Intelligence, ICACI 2023. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350321456
-
Konferensbidrag (refereegranskat)abstract
- E-nose technology relies on the proper functioning of sensors to identify and discriminate between different chemicals and odors. The long-term reliability of e-nose technology is hindered by the phenomenon of sensor drift. The effect of sensor drift is seen as a random and unpredictable shift in the data domain. This random shift in data deteriorates the performance of machine learning algorithms used in e-nose technology. Swarm intelligence based optimization has been successfully applied in different domains to deal with NP-hard optimization problems. In this paper, a swarm intelligence-based metaheuristic is proposed to deal with the sensors drift issue in e-nose technology. The proposed framework is validated using a benchmark dataset of sensor drift, and a significant improvement is observed in terms of the classification accuracy of different industrial gases. The proposed framework has the following benefits over conventional approaches: (i) there is no need for sensor re-calibration; (ii) there is no need for sensor replacement; (iii) there is no need for target domain data; and (iv) there is no need for domain transformation. Instead, the proposed work relies only on the source domain data and optimizes the feature space to deal with sensor drift. This makes the proposed framework more suitable for real applications of E-nose technology.
|
|
