| 1. |
- Shakoor, Awais, et al.
(author)
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A global meta-analysis of greenhouse gases emission and crop yield under no-tillage as compared to conventional tillage
- 2020
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In: Science of the Total Environment. - : Elsevier BV. - 1879-1026 .- 0048-9697.
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Journal article (peer-reviewed)abstract
- No-tillage (NT) practice is extensively adopted with aims to improve soil physical conditions, carbon (C) sequestration and to alleviate greenhouse gases (GHGs) emissions without compromising crop yield. However, the influences of NT on GHGs emissions and crop yields remains inconsistent. A global meta-analysis was performed by using fifty peer-reviewed publications to assess the effectiveness of soil physicochemical properties, nitrogen (N) fertilization, type and duration of crop, water management and climatic zones on GHGs emissions and crop yields under NT compared to conventional tillage (CT) practices. The outcome reveals that compared to CT, NT increased CO2, N2O, and CH4 emissions by 7.1, 12.0, and 20.8%, respectively. In contrast, NT caused up to 7.6% decline in global warming potential as compared to CT. However, absence of difference in crop yield was observed both under NT and CT practices. Increasing N fertilization rates under NT improved crop yield and GHGs emission up to 23 and 58%, respectively, compared to CT. Further, NT practices caused an increase of 16.1% CO2 and 14.7% N2O emission in the rainfed areas and up to 54.0% CH4 emission under irrigated areas as compared to CT practices. This meta-analysis study provides a scientific basis for evaluating the effects of NT on GHGs emissions and crop yields, and also provides basic information to mitigate the GHGs emissions that are associated with NT practice.
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| 2. |
- Klar, Joakim, 1974-, et al.
(author)
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Altered paracellular cation permeability due to a rare CLDN10B variant causes anhidrosis and kidney damage
- 2017
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In: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 13:7
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Journal article (peer-reviewed)abstract
- Claudins constitute the major component of tight junctions and regulate paracellular permeability of epithelia. Claudin-10 occurs in two major isoforms that form paracellular channels with ion selectivity. We report on two families segregating an autosomal recessive disorder characterized by generalized anhidrosis, severe heat intolerance and mild kidney failure. All affected individuals carry a rare homozygous missense mutation c.144C>G, p.(N48K) specific for the claudin-10b isoform. Immunostaining of sweat glands from patients suggested that the disease is associated with reduced levels of claudin-10b in the plasma membranes and in canaliculi of the secretory portion. Expression of claudin-10b N48K in a 3D cell model of sweat secretion indicated perturbed paracellular Na+ transport. Analysis of paracellular permeability revealed that claudin-10b N48K maintained cation over anion selectivity but with a reduced general ion conductance. Furthermore, freeze fracture electron microscopy showed that claudin-10b N48K was associated with impaired tight junction strand formation and altered cis-oligomer formation. These data suggest that claudin-10b N48K causes anhidrosis and our findings are consistent with a combined effect from perturbed TJ function and increased degradation of claudin-10b N48K in the sweat glands. Furthermore, affected individuals present with Mg2+ retention, secondary hyperparathyroidism and mild kidney failure that suggest a disturbed reabsorption of cations in the kidneys. These renal-derived features recapitulate several phenotypic aspects detected in mice with kidney specific loss of both claudin-10 isoforms. Our study adds to the spectrum of phenotypes caused by tight junction proteins and demonstrates a pivotal role for claudin-10b in maintaining paracellular Na+ permeability for sweat production and kidney function.
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| 3. |
- Ali, Subhan, et al.
(author)
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The enlightening role of explainable artificial intelligence in medical & healthcare domains : A systematic literature review
- 2023
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In: Computers in Biology and Medicine. - : Elsevier. - 0010-4825 .- 1879-0534. ; 166
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Journal article (peer-reviewed)abstract
- In domains such as medical and healthcare, the interpretability and explainability of machine learning and artificial intelligence systems are crucial for building trust in their results. Errors caused by these systems, such as incorrect diagnoses or treatments, can have severe and even life-threatening consequences for patients. To address this issue, Explainable Artificial Intelligence (XAI) has emerged as a popular area of research, focused on understanding the black-box nature of complex and hard-to-interpret machine learning models. While humans can increase the accuracy of these models through technical expertise, understanding how these models actually function during training can be difficult or even impossible. XAI algorithms such as Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) can provide explanations for these models, improving trust in their predictions by providing feature importance and increasing confidence in the systems. Many articles have been published that propose solutions to medical problems by using machine learning models alongside XAI algorithms to provide interpretability and explainability. In our study, we identified 454 articles published from 2018- 2022 and analyzed 93 of them to explore the use of these techniques in the medical domain.
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| 4. |
- Kastrati, Zenun, 1984-, et al.
(author)
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Soaring Energy Prices : Understanding Public Engagement on Twitter Using Sentiment Analysis and Topic Modeling With Transformers
- 2023
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In: IEEE Access. - : IEEE. - 2169-3536. ; 11, s. 26541-26553
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Journal article (peer-reviewed)abstract
- Energy prices have gone up gradually since last year, but a drastic hike has been observedrecently in the past couple of months, affecting people’s thrift. This, coupled with the load shedding andenergy shortages in some parts of the world, led many to show anger and bitterness on the streets and on socialmedia. Despite subsidies offered by many Governments to their citizens to compensate for high energy bills,the energy price hike is a trending topic on Twitter. However, not much attention is paid to opinion mining onsocial media posts on this topic. Therefore, in this study, we propose a solution that takes advantage of botha transformer-based sentiment analysis method and topic modeling to explore public engagement on Twitterregarding energy prices rising. The former method is employed to annotate the valence of the collected tweetsas positive, neutral and negative, whereas the latter is used to discover hidden topics/themes related to energyprices for which people have expressed positive or negative sentiments. The proposed solution is tested ona dataset composed of 366,031 tweets collected from 01 January 2021 to 18 June 2022. The findings showthat people have discussed a variety of topics which directly or indirectly affect energy prices. Moreover,the findings reveal that the public sentiment towards these topics has changed over time, in particular, in2022 when negative sentiment was dominant.
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| 5. |
- Tahira, Shireen, et al.
(author)
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Handover Based IMS Registration Scheme for Next Generation Mobile Networks
- 2017
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In: Wireless Communications & Mobile Computing. - : John Wiley & Sons. - 1530-8669 .- 1530-8677. ; 2017
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Journal article (peer-reviewed)abstract
- Next generation mobile networks aim to provide faster speed and more capacity along with energy efficiency to support video streaming andmassive data sharing in social and communication networks. In these networks, user equipment has to register with IPMultimedia Subsystem (IMS) which promises quality of service to the mobile users that frequently move across different access networks. After each handover caused due to mobility, IMS provides IPSec Security Association establishment and authentication phases. The main issue is that unnecessary reregistration after every handover results in latency and communication overhead. To tackle these issues, this paper presents a lightweight Fast IMS Mobility (FIM) registration scheme that avoids unnecessary conventional registration phases such as security associations, authentication, and authorization. FIM maintains a flag to avoid deregistration and sends a subsequent message to provide necessary parameters to IMS servers after mobility. It also handles the change of IP address for user equipment and transferring the security associations from old to new servers. We have validated the performance of FIM by developing a testbed consisting of IMS servers and user equipment. The experimental results demonstrate the performance supremacy of FIM. It reduces media disruption time, number of messages, and packet loss up to 67%, 100%, and 61%, respectively, as compared to preliminaries.
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| 6. |
- Zulfiqar, Shumaila, et al.
(author)
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Identification of a novel variant in GPR56/ADGRG1 gene through whole exome sequencing in a consanguineous Pakistani family
- 2021
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In: Journal of clinical neuroscience. - : Elsevier. - 0967-5868 .- 1532-2653. ; 94, s. 8-12
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Journal article (peer-reviewed)abstract
- GPR56 gene is best known for its pivotal role in cerebral cortical development. Mutations in GPR56 give rise to cobblestone-like brain malformation, white matter changes and cerebellar dysplasia. This study aimed to identify causative variant in a consanguineous family having five individuals affected with developmental delay, mild to severe intellectual disability, speech impairment, strabismus and seizures. Whole exome sequencing was performed to identify mutation in affected individuals. Variants were filtered and further validated by Sanger sequencing and segregation analysis. A novel frameshift variant c.1601dupT leading to p.Ala535GlyfsTer17) was identified in GPR56 gene by whole exome sequencing and subsequent filtering. All five affected individuals were homozygous for the mutant allele while four asymptomatic individuals carried the variant in heterozygous state. Radiological findings of a representative patient presented features of GPR56-associated cobblestone like brain malformation. MRI findings suggested paucity of sulci, dilated ventricular system and brainstem atrophy. The microgyria were observed in a simplified gyral pattern (cobblestone). This single bp insertion, and the consequent frame-shift, results in the truncation of GPR56 protein. This could result in a malformed cortex giving the brain a cobblestone like shape. Our study identified a 7th novel frameshift variant from Pakistani population in GPR56 gene, thus broadening mutation spectrum.
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| 7. |
- Ahmed, Ammar, et al.
(author)
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Enhancing wrist abnormality detection with YOLO : Analysis of state-of-the-art single-stage detection models
- 2024
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In: Biomedical Signal Processing and Control. - : Elsevier. - 1746-8094 .- 1746-8108. ; 93
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Journal article (peer-reviewed)abstract
- Diagnosing and treating abnormalities in the wrist, specifically distal radius, and ulna fractures, is a crucial concern among children, adolescents, and young adults, with a higher incidence rate during puberty. However, the scarcity of radiologists and the lack of specialized training among medical professionals pose a significant risk to patient care. This problem is further exacerbated by the rising number of imaging studies and limited access to specialist reporting in certain regions. This highlights the need for innovative solutions to improve the diagnosis and treatment of wrist abnormalities. Automated wrist fracture detection using object detection has shown potential, but current studies mainly use two-stage detection methods with limited evidence for single-stage effectiveness. This study employs state-of-the-art single-stage deep neural network-based detection models YOLOv5, YOLOv6, YOLOv7, and YOLOv8 to detect wrist abnormalities. Through extensive experimentation, we found that these YOLO models outperform the commonly used two-stage detection algorithm, Faster R-CNN, in fracture detection. Additionally, compound-scaled variants of each YOLO model were compared, with YOLOv8 m demonstrating a highest fracture detection sensitivity of 0.92 and mean average precision (mAP) of 0.95. On the other hand, YOLOv6 m achieved the highest sensitivity across all classes at 0.83. Meanwhile, YOLOv8x recorded the highest mAP of 0.77 for all classes on the GRAZPEDWRI-DX pediatric wrist dataset, highlighting the potential of single-stage models for enhancing pediatric wrist imaging.
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| 8. |
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| 9. |
- Ali, Subhan, et al.
(author)
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Visualizing Research on Explainable Artificial Intelligence for Medical and Healthcare
- 2023
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In: 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). - : IEEE. - 9798350335323 - 9798350335316 ; , s. 1-6
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Conference paper (peer-reviewed)abstract
- Understanding complex machine learning and artificial intelligence models have always been challenging because these models are black-box, and often we don't know what information models rely upon to infer. Explainable Artificial Intelligence (XAI) has emerged as a new exciting field to explain and understand these machine learning models as humans can understand and improve them. In the past few years, there have been numerous research articles on explainable artificial intelligence for medical and healthcare. 1687 documents are being studied and analysed using bibliometric methods in this work. There are certain systematic reviews on the same topic, but this study is the first of its kind to use a quantitative method to analyze a large number of publications. The results of this study show that the research in this field took place in 2011, and there have been quite many publications in the following years. We have also identified top-cited journals and articles. Through thematic analysis, we have found some important thematic areas of research in the field of XAI for medical and healthcare. The findings showed that the USA is the global leader in XAI research, followed by China and Canada at second and third place, respectively.
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| 10. |
- Batra, Rakhi, et al.
(author)
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Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples's Attitudes toward the Vaccination Drive
- 2021
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In: Sustainability. - : MDPI. - 2071-1050. ; 13:10
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Journal article (peer-reviewed)abstract
- It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users's tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.
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