Search results for: Bilal Arshad

Authors: Minhas Alam, Muhammad Hidayat Rasool, Mohsin Khurshid, Bilal Aslam

Abstract:

The genus Acinetobacter has emerged as a significant concern in hospital-acquired infections, particularly due to the versatility of Acinetobacter baumannii in causing nosocomial infections. The organism's remarkable metabolic adaptability allows it to thrive in various environments, including the environment, animals, and humans. However, the extent of antimicrobial resistance in Acinetobacter species from veterinary settings, especially in developing countries like Pakistan, remains unclear. This study aimed to isolate and characterize Acinetobacter spp. from veterinary settings in Punjab, Pakistan. A total of 2,230 specimens were collected, including 1,960 samples from veterinary settings (nasal and rectal swabs from dairy and beef cattle), 200 from the environment, and 70 from human clinical settings. Isolates were identified using routine microbiological procedures and confirmed by polymerase chain reaction (PCR). Antimicrobial susceptibility was determined by the disc diffusion method, and minimum inhibitory concentration (MIC) was measured by the micro broth dilution method. Molecular techniques, such as PCR and DNA sequencing, were used to screen for antimicrobial-resistant determinants. Genetic diversity was assessed using standard techniques. The results showed that the overall prevalence of A. baumannii in cattle was 6.63% (65/980). However, among cattle, a higher prevalence of A. baumannii was observed in dairy cattle, 7.38% (54/731), followed by beef cattle, 4.41% (11/249). Out of 65 A. baumannii isolates, the carbapenem resistance was found in 18 strains, i.e. 27.7%. The prevalence of A. baumannii in nasopharyngeal swabs was higher, i.e., 87.7% (57/65), as compared to rectal swabs, 12.3% (8/65). Class D β-lactamases genes blaOXA-23 and blaOXA-51 were present in all the CRAB from cattle. Among carbapenem-resistant isolates, 94.4% (17/18) were positive for class B β-lactamases gene blaIMP, whereas the blaNDM-1 gene was detected in only one isolate of A. baumannii. Among 70 clinical isolates of A. baumannii, 58/70 (82.9%) were positive for the blaOXA-23-like gene, and 87.1% (61/70) were CRAB isolates. Among all clinical isolates of A. baumannii, blaOXA-51-like gene was present. Hence, the co-existence of blaOXA-23 and blaOXA-51 was found in 82.85% of clinical isolates. From the environmental settings, a total of 18 A. baumannii isolates were recovered; among these, 38.88% (7/18) strains showed carbapenem resistance. All environmental isolates of A. baumannii harbored class D β-lactamases genes, i.e., blaOXA-51 and blaOXA-23 were detected in 38.9% (7/18) isolates. Hence, the co-existence of blaOXA-23 and blaOXA-51 was found in 38.88% of isolates. From environmental settings, 18 A. baumannii isolates were recovered, with 38.88% showing carbapenem resistance. All environmental isolates harbored blaOXA-51 and blaOXA-23 genes, with co-existence in 38.88% of isolates. MLST results showed ten different sequence types (ST) in clinical isolates, with ST 589 being the most common in carbapenem-resistant isolates. In veterinary isolates, ST2 was most common in CRAB isolates from cattle. Immediate control measures are needed to prevent the transmission of CRAB isolates among animals, the environment, and humans. Further studies are warranted to understand the mechanisms of antibiotic resistance spread and implement effective disease control programs.

Keywords: Acinetobacter baumannii, carbapenemases, drug resistance, MSLT

Procedia PDF Downloads 31

Authors: S. A. Bhat, Ahmad Arif, Muneeb U. Rehman, Manzoor R Mir, S. Bilal, Ishraq Hussain, H. M Khan, S. Shanaz, M. I Mir, Sabhiya Majid

Abstract:

Background: Geologically Climatic conditions of the state range from sub-tropical (Jammu), temperate (Kashmir) to cold artic (Ladakh) zones, which exerts significant influence on its agro-climatic conditions. Gastrointestinal parasitism is a major problem in sheep production worldwide. Materials and Methods: The present study was to evaluate the resistance status of sheep breeds reared in Kashmir Valley for natural resistance against Haemonchus contortus by natural pasture challenge infection. Ten microsatellite markers were used in the study for evaluation of association of Ovar-MHC with parasitic resistance in association with biochemical and parasitological parameters. Following deworming, 500 animals were subjected to selected contaminated pastures in a vicinity of the livestock farms of SKUAST-K and Sheep Husbandry Kashmir. For each animal about 10-15 ml blood was collected aseptically for molecular and biochemical analysis. Weekly fecal samples (3g) were taken, directly from the rectum of all experimental animals and examined for Fecal egg count (FEC) with modified McMaster technique. Packed cell volume (PCV) was determined within 2-5 h of blood collection, all the biochemical parameters were determined in serum by semi automated analyzer. DNA was extracted from all the blood samples with phenol-chloroform method. Microsatellite analysis was done by denaturing sequencing gel electrophoresis Results: Overall sheep from Bakerwal breed followed by Corriediale breed performed relatively better in the trial; however difference between breeds remained low. Both significant (P<0.05) and non-significant differences with respect to resistance against haemonchosis were noted at different intervals in all the parameters.. All the animals were typed for the microsatellites INRA132, OarCP73, DRB1 (U0022), OLA-DQA2, BM1818, TFAP2A, HH56, BM1815, IL-3 and BM-1258. An association study including the effect of FEC, PCV, TSP, SA, LW, and the number of alleles within each marker was done. All microsatellite markers showed degree of heterozygosity of 0.72, 0.72, 0.75, 0.62, 0.84, 0.69, 0.66, 0.65, 0.73 and 0.68 respectively. Significant association between alleles and the parameters measured were only found for the OarCP73, OLA-DQA2 and BM1815 microsatellite marker. Standard alleles of the above markers showed significant effect on the TP, SA and body weight. The three sheep breeds included in the study responded differently to the nematode infection, which may be attributed to their differences in their natural resistance against nematodes. Conclusion: Our data confirms that some markers (OarCP73, OLA-DQA2 and BM1815) within Ovar-MHC are associated with phenotypic parameters of resistance and suggest superiority of Bakerwal sheep breed in natural resistance against Haemonchus contortus.

Keywords: Ovar-Mhc, ovine leukocyte antigen (OLA), sheep, parasitic resistance, Haemonchus contortus, phenotypic & genotypic markers

Procedia PDF Downloads 682

Authors: Khethiwe Mtshali, Zamantungwa T. H. Khumalo, Stanford Kwenda, Ismail Arshad, Oriel M. M. Thekisoe

Abstract:

Ecologically, the gut, mammary glands and bloodstream consist of distinct microbial communities of commensals, mutualists and pathogens, forming a complex ecosystem of niches. The by-products derived from these body sites i.e. faeces, milk and blood, respectively, have many uses in rural communities where they aid in the facilitation of day-to-day household activities and occasional rituals. Thus, although livestock rearing plays a vital role in the sustenance of the livelihoods of rural communities, it may serve as a potent reservoir of different pathogenic organisms that could have devastating health and economic implications. This study aimed to simultaneously explore the microbial profiles of corresponding faecal, milk and blood samples from lactating cows using 16S rRNA metagenomic sequencing. Bacterial communities were inferred through the Divisive Amplicon Denoising Algorithm 2 (DADA2) pipeline coupled with SILVA database v138. All downstream analyses were performed in R v3.6.1. Alpha-diversity metrics showed significant differences between faeces and blood, faeces and milk, but did not vary significantly between blood and milk (Kruskal-Wallis, P < 0.05). Beta-diversity metrics on Principal Coordinate Analysis (PCoA) and Non-Metric Dimensional Scaling (NMDS) clustered samples by type, suggesting that microbial communities of the studied niches are significantly different (PERMANOVA, P < 0.05). A number of taxa were significantly differentially abundant (DA) between groups based on the Wald test implemented in the DESeq2 package (Padj < 0.01). The majority of the DA taxa were significantly enriched in faeces than in milk and blood, except for the genus Anaplasma, which was significantly enriched in blood and was, in turn, the most abundant taxon overall. A total of 30 phyla, 74 classes, 156 orders, 243 families and 408 genera were obtained from the overall analysis. The most abundant phyla obtained between the three body sites were Firmicutes, Bacteroidota, and Proteobacteria. A total of 58 genus-level taxa were simultaneously detected between the sample groups, while bacterial signatures of at least 8 of these occurred concurrently in corresponding faeces, milk and blood samples from the same group of animals constituting a pool. The important taxa identified in this study could be categorized into four potentially pathogenic clusters: i) arthropod-borne; ii) food-borne and zoonotic; iii) mastitogenic and; iv) metritic and abortigenic. This study provides insight into the microbial composition of bovine faeces, milk, and blood and its extent of overlapping. It further highlights the potential risk of disease occurrence and transmission between the animals and the inhabitants of the sampled rural community, pertaining to their unsanitary practices associated with the use of cattle by-products.

Keywords: microbial profiling, 16S rRNA, NGS, feces, milk, blood, lactating cows, small-scale farmers

Procedia PDF Downloads 85

Authors: A. Arshad, M. Lehtonen. M. Humayun

Abstract:

With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

Procedia PDF Downloads 287

Authors: Shailendra Kumar, Lokesh Kashyap, Puneet Khanna, Nishant Patel, Rakesh Kumar, Arshad Ayub, Kelika Prakash, Yudhyavir Singh, Krithikabrindha V.

Abstract:

Introduction: Spinal anesthesia is considered a standard anesthesia technique for caesarean delivery. The incidence of spinal hypotension during caesarean delivery is 70 -80%. Spinal hypotension may cause cerebral hypoperfusion in the mother, but physiologically cerebral autoregulatory mechanisms accordingly prevent cerebral hypoxia. Cerebral blood flow remains constant in the 50-150 mmHg of Cerebral Perfusion Pressure (CPP) range. Near-infrared spectroscopy (NIRS) is a non-invasive technology that is used to detect Cerebral Desaturation Events (CDEs) immediately compared to other conventional intraoperative monitoring techniques. Objective: The primary aim of the study is to correlate the change in cerebral oxygen saturation using NIRS with respect to a fall in mean blood pressure after spinal anaesthesia and to find out the effects of spinal hypotension on neonatal APGAR score, neonatal acid-base variations, and presence of Postoperative Delirium (POD). Methodology: NIRS sensors were attached to the forehead of all the patients, and their baseline readings of cerebral oxygenation on the right and left frontal regions and mean blood pressure were noted. Subarachnoid block was given with hyperbaric 0.5% bupivacaine plus fentanyl, the dose being determined by the individual anaesthesiologist. Co-loading of IV crystalloid solutions was given to the patient. Blood pressure reading and cerebral saturation were recorded every 1 minute till 30min. Hypotension was a fall in MAP less than 20% of the baseline values. Patients going for hypotension were treated with an IV Bolus of phenylephrine/ephedrine. Umbilical cord blood samples were taken for blood gas analysis, and neonatal APGAR was noted by a neonatologist. Study design: A prospective observational study conducted in a population of Thirty ASA 2 and 3 parturients scheduled for lower segment caesarean section (LSCS). Results: Mean fall in regional cerebral saturation is 28.48 ± 14.7% with respect to the mean fall in blood pressure 38.92 ± 8.44 mm Hg. The correlation coefficient between fall in saturation and fall in mean blood pressure is 0.057, and p-value {0.7} after subarachnoid block. A fall in regional cerebral saturation occurred 2±1 min before a fall in mean blood pressure. Twenty-nine out of thirty patients required vasopressors during hypotension. The first dose of vasopressor requirement is needed at 6.02±2 min after the block. The mean APGAR score was 7.86 and 9.74 at 1 and 5 min of birth, respectively, and the mean umbilical arterial pH of 7.3±0.1. According to DRS-98 (Delirium Rating Scale), the mean delirium rating score on postoperative day 1 and day 2 were 0.1 and 0.7, respectively. Discussion: There was a fall in regional cerebral oxygen saturation, which started before with respect to a significant fall in mean blood pressure readings but was statistically not significant. Maximal fall in blood pressure requiring vasopressors occurs within 10 min of SAB. Neonatal APGAR scores and acid-base variations were in the normal range with maternal hypotension, and there was no incidence of postoperative delirium in patients with post-spinal hypotension.

Keywords: cerebral oxygenation, LSCS, NIRS, spinal hypotension

Procedia PDF Downloads 46

Authors: Anubhav Kumar Dwivedi, Arshad Khan, S. N. Tripathi, Manish Joshi, Gaurav Mishra, Dinesh Nath, Naveen Tiwari, B. K. Sapra

Abstract:

In a nuclear reactor accident scenario, a large number of fission products may release to the piping system of the primary heat transport. The released fission products, mostly in the form of the aerosol, get deposited on the inner surface of the piping system mainly due to gravitational settling and thermophoretic deposition. The removal processes in the complex piping system are controlled to a large extent by the thermal-hydraulic conditions like temperature, pressure, and flow rates. These parameters generally vary with time and therefore must be carefully monitored to predict the aerosol behavior in the piping system. The removal process of aerosol depends on the size of particles that determines how many particles get deposit or travel across the bends and reach to the other end of the piping system. The released aerosol gets deposited onto the inner surface of the piping system by various mechanisms like gravitational settling, Brownian diffusion, thermophoretic deposition, and by other deposition mechanisms. To quantify the correct estimate of deposition, the identification and understanding of the aforementioned deposition mechanisms are of great importance. These mechanisms are significantly affected by different flow and thermodynamic conditions. Thermophoresis also plays a significant role in particle deposition. In the present study, a series of experiments were performed in the piping system of the National Aerosol Test Facility (NATF), BARC using metal aerosols (zinc) in dry environments to study the spatial distribution of particles mass and number concentration, and their depletion due to various removal mechanisms in the piping system. The experiments were performed at two different carrier gas flow rates. The commercial CFD software FLUENT is used to determine the distribution of temperature, velocity, pressure, and turbulence quantities in the piping system. In addition to the in-built models for turbulence, heat transfer and flow in the commercial CFD code (FLUENT), a new sub-model PBM (population balance model) is used to describe the coagulation process and to compute the number concentration along with the size distribution at different sections of the piping. In the sub-model coagulation kernels are incorporated through user-defined function (UDF). The experimental results are compared with the CFD modeled results. It is found that most of the Zn particles (more than 35 %) deposit near the inlet of the plenum chamber and a low deposition is obtained in piping sections. The MMAD decreases along the length of the test assembly, which shows that large particles get deposited or removed in the course of flow, and only fine particles travel to the end of the piping system. The effect of a bend is also observed, and it is found that the relative loss in mass concentration at bends is more in case of a high flow rate. The simulation results show that the thermophoresis and depositional effects are more dominating for the small and larger sizes as compared to the intermediate particles size. Both SEM and XRD analysis of the collected samples show the samples are highly agglomerated non-spherical and composed mainly of ZnO. The coupled model framed in this work could be used as an important tool for predicting size distribution and concentration of some other aerosol released during a reactor accident scenario.

Keywords: aerosol, CFD, deposition, coagulation

Procedia PDF Downloads 121

Authors: Awatef Ahmed Ben Ramadan, Aqsa Arshad

Abstract:

Background: There is a huge Muslim migration movement to North America and Europe for several reasons, primarily refuge from war areas and partly to search for better work and educational chances. There are always concerns regarding first-Generation Immigrant women's health and computer literacy, an adequate understanding of the health systems, and the use of the existing healthcare technology and services effectively and efficiently. Language proficiency level, preference for cultural and traditional remedies, socioeconomic factors, fear of stereotyping, limited accessibility to health services, and general unfamiliarity with the existing health services and resources are familiar variables among these women. Aims: The current study aims to assess the health and digital literacy of first-generation Muslim women in Atlanta city. Also, the study aims to examine how the COVID-19 pandemic has encouraged the use of health information technology and increased technology awareness among the targeted women. Methods: The study design is cross-sectional correlational research. The study will be conducted to produce preliminary results that the investigators want to have to supplement an NIH grant application about leveraging information technology to reduce the health inequalities amongst the first-generation immigrant Muslim women in Atlanta City. The investigators will collect the study data in two phases using different tools. Phase one was conducted in June 2022; the investigators used tools to measure health and digital literacy amongst 42 first-generation immigrant Muslim women. Phase two was conducted in November 2022; the investigators measured the Knowledge, Attitude, and Practice (KAP) of using health information technology such as telehealth from a sample of 45 first-generation Muslim immigrant women in Atlanta; in addition, the investigators measured how the current pandemic has affected their KAP to use telemedicine and telehealth services. Both phases' study participants were recruited using convenience sampling methodology. The investigators collected around 40 of 18 years old or older first-generation Muslim immigrant women for both study phases. The study excluded Immigrants who hold work visas and second-generation immigrants. Results: At the point of submitting this abstract, the investigators are still analyzing the study data to produce preliminary results to apply for an NIH grant entitled "Leveraging Health Information Technology (Health IT) to Address and Reduce Health Care Disparities (R01 Clinical Trial Optional)". This research will be the first step of a comprehensive research project to assess and measure health and digital literacy amongst a vulnerable community group. The targeted group might have different points of view from the U.S.-born inhabitants on how to: promote their health, gain healthy lifestyles and habits, screen for diseases, adhere to health treatment and follow-up plans, perceive the importance of using available and affordable technology to communicate with their providers and improve their health, and help in making serious decisions for their health. The investigators aim to develop an educational and instructional health mobile application considering the language and cultural factors that affect immigrants' ability to access different health and social support sources, know their health rights and obligations in their communities, and improve their health behavior and behavior lifestyles.

Keywords: first-generation immigrant Muslim women, telehealth, COVID-19 pandemic, health information technology, health and digital literacy

Procedia PDF Downloads 59

Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

Abstract:

We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

Procedia PDF Downloads 118

Authors: Muhammad Bilal Shaikh

Abstract:

Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 39

Authors: Jia H. Wong, Jingli Zhang, Habsah Mohamad, Iswatun H. Abdullah Ripain, Muhammad Bilal, Amelia J. Lloyd, Abdul A. Mohamed Yusoff, Jafri M. Abdullah

Abstract:

Epilepsy is one of the most common neurological diseases affecting more than 50 million of people worldwide. Epilepsy is a state of recurrent, spontaneous seizures with multiple syndromes and symptoms of different causes of brain dysfunction, prognosis, and treatments; characterized by transient, occasional and stereotyped interruptions of behavior whereby the excitatory-inhibitory activities within the central nervous system (CNS) are thrown out of balance due to various kinds of interferences. The goal of antiepileptic treatment is to enable patients to be free from seizures or to achieve control of seizures through surgical treatment and/or pharmacotherapy. Pharmacotherapy through AED plays an important role especially in countries with epilepsy treatment gap due to costs and availability of health facilities, skills and resources, yet there are about one-third of the people with epilepsy have drug-resistant seizures. Hence, this poses considerable challenges to the healthcare system and the effort in providing cost-effective treatment as well as the search for alternatives to treatment and management of epilepsy. Enhancement of γ-aminobutyric acid (GABA)-mediated inhibitory neurotransmission is one of the key mechanisms of actions of antiepileptic drugs. GABA type > a receptors (GABAAR) are ligand-gated ion channels that mediate rapid inhibitory neurotransmission upon the binding of GABA with a heteropentameric structure forming a central pore that is permeable to the influx of chloride ions in its activated state. The major isoform of GABAA receptors consists of two α1, two β2, and one γ2 subunit. It is the most abundantly expressed combinations in the brain and the most commonly researched through Xenopus laevis oocytes. With the advancing studies on ethnomedicine and traditional treatments using medicinal plants, increasing evidence reveal that spice and herb plants with medicinal properties play an important role in the treatment of ailments within communities across different cultures. Capsaicin is the primary natural capsaicinoid in hot peppers of plant genus Capsicum, consist of an aromatic ring, an amide linkage and a hydrophobic side chain. The study showed that capsaicins conferred neuroprotection in status epilepticus mouse models through anti-ictogenic, hypothermic, antioxidative, anti-inflammatory, and anti-apoptotic actions in a dose-dependent manner. In this study, five capsaicin derivatives were tested for their ability to increase the GABA-induced chloride current on α1β2γ2S of GABAAR expressed on Xenopus laevis oocytes using the method of two-microelectrode voltage clamp. Two of the capsaicin derivatives, IS5 (N-(4-hydroxy-3-methoxybenzyl)-3-methylbutyramide) and IS10 (N-(4-hydroxy-3-methoxybenzyl)-decanamide) at a concentration of 30µM were able to significantly increase the GABA-induced chloride current with p=0.002 and p=0.026 respectively. This study were able to show the enhancement effect of two capsaicin derivatives with moderate length of hydrocarbon chain on this receptor subtype, revealing the promising inhibitory activity of capsaicin derivatives through enhancement of GABA-induced chloride current and further investigations should be carried out to verify its antiepileptic effects in animal models.

Keywords: α1β2γ2 GABAA receptors, α1β2γ2S, antiepileptic, capsaicin derivatives, two-microelectrode voltage clamp, Xenopus laevis oocytes

Procedia PDF Downloads 338