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Post Thyroidectomy Assessment of Intact Parathyroid Hormone for Early Prediction of Hypocalcaemia

International Journal of Otolaryngology and Head & Neck Surgery 2024年第2期13卷 71-84页

作者： Md. Masum Billah Ripon Kumar Sarkar Md. Yousuf Ali Saad Zaman Md. Nazmul Hasan Md. Shehab Uddin Md. Mosleh Uddin Kazi Shameemus salam Farzana Binte Abedin Leera Department of Otolaryngology-Head & Neck Surgery Universal Medical College Hospital Dhaka Bangladesh Department of Otolaryngology-Head & Neck Surgery National Institute of Ear Nose and Throat Dhaka Bangladesh Shaheed Ahsan Ullah Master General Hospital Gazipur Bangladesh Department of Otolaryngology-Head & Neck Surgery Cumilla Medical College Cumilla Bangladesh Department of ENT Oncology National Institute of Cancer Research & Hospital Dhaka Bangladesh Department of ENT Outdoor Rajshahi Medical College Hospital Rajshahi Bangladesh Department of Otolaryngology-Head & Neck Surgery Bangabandhu Sheikh Mujib Medical University Dhaka Bangladesh Department of Biochemistry Delta Medical College Hospital Dhaka Bangladesh

Background: As the half-life of intact parathyroid hormone (iPTH) is very low, it reflects parathyroid insufficiency within minutes to hours after total thyroidectomy. Therefore, iPTH level assessment in the postoperative period can be used to predict the development of hypocalcaemia. The optimal time point to measure serum iPTH is important for the accurate prediction of hypocalcaemia. Aim: This paper aims to evaluate the ability of iPTH as an early predictive marker of hypocalcaemia and determine which time iPTH is more able to predict postoperative hypocalcaemia. Method: This prospective observational study was conducted in the Department of Otolaryngology-Head & Neck Surgery, BSMMU, Dhaka, from July 2020 to December 2021, with 67 patients who underwent total thyroidectomy. iPTH levels were measured on the day before the operation and at 1 hour, 4 hours, and 24 hours after the operation. *** levels were measured on the day before the operation and 1st postoperative day. All the data were compiled and sorted properly and were analyzed statistically. Results: Postoperative hypocalcaemia developed in 18 cases, with an incidence of 26.9%. Pearson correlation showed a significant correlation between postoperative iPTH at 1 hr, 4 h, and 24 hr with 1st postoperative calcium value. The Receiver operating characteristic (ROC) curve was processed for the postoperative iPTH at 1 hr, 4 h, and 24 hr. The sensitivity, specificity, cut-off value, and mean AUC found 93.9%, 94.4%, ≤14.0, 0.988;95.9%, 94.4%, ≤09.5, 0.993 and 91.8%, 94.4%, ≤11.0, 0.993 respectively. Conclusion: iPTH can be used as an early predictor of post-thy-roidectomy hypocalcaemia. 4 hr iPTH showed more sensitivity and specificity for a cut-off value near the laboratory reference range.

关键词： Total Thyroidectomy Hypocalcaemia Serum Intact Parathyroid Hormone Early Predictor of Hypocalcaemia

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Epidemiological and Clinical Profile and Immediate Outcome of Neonates Transferred from the Maternity Unit to the Neonatology Unit of the CSREF in Commune V of Bamako District, Mali

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Open Journal of Pediatrics 2024年第3期14卷 547-557页

作者： Maimouna Kante Ya Traoré Balilé Harber Beydari Mamadou Traoré Issiaka Koné Diéneba Sacko Maimouna Haidara Korotoumou Bamba Assitan Farota Abdoulaye Kassogué Mohamed Diarra Dramane Touré Abdoul salam Diarra Leyla Maïga Dicko Fatoumata Paediatric Ward CSR&#233f CV Bamako Mali Paediatric Ward of Nianankoro Fomba Hospital S&#233gou Mali Paediatric Ward of Kalaban CoroCSREF Bamako Mali Pediatric Department of the Mopti Reference Health Center Mopti Mali National Centre for Scientific and Technological Research Bamako Mali Paediatrics Department Mohamed VI Perinatal Clinic Bamako Mali Department of Paediatrics Gabriel Tour&#233 University Hospital Bamako Mali

Introduction: Neonatal mortality remains a major public health concern. According to the World Health Organisation (WHO), the number of newborns dying each year has fallen from 5 million in 1990 to 2.4 million in 2019. The aim of our study was to describe the main morbid conditions and their lethality in newborns admitted to the paediatric ward of the CSREF in Commune V. Methodology: We conducted a 12-month prospective descriptive and analytical study from August 2020 to July 2021. Results: During the 12 months of the study, out of 2654 neonates admitted to hospital, 216 met our inclusion criteria, i.e. 8%. Newborns admitted in the first few hours of life represented 99.54% of cases. Full-term newborns accounted for 65.74% of the total. Forty-eight percent of newborns had hypothermia on admission. The most common diagnosis was asphyxia in 55.56% of cases, followed by neonatal infection in 27.78% and prematurity in 10.65%. Death was recorded in 22.2% of cases. Asphyxia was the main cause of neonatal death, followed by prematurity in our context. Conclusion: Improving the prognosis of newborn babies will require a thorough understanding of neonatal pathologies and the implementation of a pre- and perinatal prevention policy.

关键词： Newborns Morbidity Mortality

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Swarm-Based Extreme Learning Machine Models for Global Optimization

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Computers, Materials & Continua 2022年第3期70卷 6339-6363页

作者： Mustafa Abdul salam Ahmad Taher Azar Rana Hussien Artificial Intelligence Department Faculty of Computers and Artificial IntelligenceBenha UniversityBenha13518Egypt Scientific Computing Department Faculty of Computers and Artificial IntelligenceBenha UniversityBenha13518Egypt

Extreme Learning Machine(ELM)is popular in batch learning,sequential learning,and progressive learning,due to its speed,easy integration,and generalization ***,Traditional ELM cannot train massive data rapidly and efficiently due to its memory residence,high time and space *** ELM,the hidden layer typically necessitates a huge number of ***,there is no certainty that the arrangement of weights and biases within the hidden layer is *** solve this problem,the traditional ELM has been hybridized with swarm intelligence optimization *** paper displays five proposed hybrid Algorithms“Salp Swarm Algorithm(SSA-ELM),Grasshopper Algorithm(GOA-ELM),Grey Wolf Algorithm(GWO-ELM),Whale optimizationAlgorithm(WOA-ELM)andMoth Flame Optimization(MFO-ELM)”.These five optimizers are hybridized with standard ELM methodology for resolving the tumor type classification using gene expression *** proposed models applied to the predication of electricity loading data,that describes the energy use of a single residence over a fouryear *** the hidden layer,Swarm algorithms are used to pick a smaller number of nodes to speed up the execution of *** best weights and preferences were calculated by these algorithms for the hidden *** results demonstrated that the proposed MFO-ELM achieved 98.13%accuracy and this is the highest model in accuracy in tumor type classification gene expression *** in predication,the proposed GOA-ELM achieved 0.397which is least RMSE compared to the other models.

关键词： Extreme learning machine salp swarm optimization algorithm grasshopper optimization algorithm grey wolf optimization algorithm moth flame optimization algorithm bio-inspired optimization classification model and whale optimization algorithm

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Hepatic and renal effects of oral stingless bee honey in a streptozotocin-induced diabetic rat model

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World Journal of Experimental Medicine 2024年第1期14卷 113-123页

作者： Suriati Mohd Nasir Anis Farihan Ismail Tuan Salwani Tuan Ismail Wan Faiziah Wan Abdul Rahman Wan Amir Nizam Wan Ahmad Tengku Ahmad Damitri Al-Astani Tengku Din Kuttulebbai Nainamohammed salam Sirajudeen Department of Chemical Pathology School of Medical SciencesUniversiti Sains MalaysiaKota Bharu 16150KelantanMalaysia Endocrinology Laboratory Department of Chemical PathologySchool of Medical SciencesUniversiti Sains MalaysiaKota Bharu 16150KelantanMalaysia Department of Pathology School of Medical SciencesUniversiti Sains MalaysiaKota Bharu 16150KelantanMalaysia Biomedicine Program School of Health SciencesHealth CampusUniversiti Sains MalaysiaKota Bharu 16150KelantanMalaysia Department of Basic Medical Sciences Kuliyyah of MedicineInternational Islamic University MalaysiaBandar Indera MahkotaKuantan 25200PahangMalaysia

BACKGROUND Diabetes is known damage the liver and kidney,leading to hepatic dysfunction and kidney *** is believed to help in lowering the blood glucose levels of diabetic patients and reducing diabetic ***,the effect of stingless bee honey(SBH)administration in relieving liver and kidney damage in diabetes has not been *** To investigate the effect of SBH administration on the kidney and liver of streptozotocin-induced(STZ;55 mg/kg)diabetic Sprague Dawley *** The rats were grouped as follows(n=6 per group):non-diabetic(ND),untreated diabetic(UNT),metformin-treated(MET),and SBH+metformin-treated(SBME)*** successful diabetic induction,ND and UNT rats were given normal saline,whereas the treatment groups received SBH(2.0 g/kg and/or metformin(250 mg/kg)for 12 *** biochemical parameters and histological changes using hematoxylin and eosin(H&E)and periodic acid–Schiff(PAS)staining were *** On H&E and PAS staining,the ND group showed normal architecture and cellularity of Bowman’s capsule and tubules,whereas the UNT and MET groups had an increased glomerular cellularity and thickened basement *** SBH-treated group showed a decrease in hydropic changes and mild cellularity of the glomerulus vs the ND group based on H&E staining,but the two were similar on PAS ***,the SBME-treated group had an increase in cellularity of the glomerulus on H&E staining,but it was comparable to the SBH and ND groups on PAS *** diabetic rats had tubular hydropic tubules,which were smaller than other *** fatty vacuole formation and dilated blood sinusoids in liver tissue were seen in the SBH ***,the UNT group had high glucose levels,which subsequently increased MDA levels,ultimately leading to liver *** treatment reduced this damage,as evidenced by having the lowest fasting glucose,serum alanine transaminase,aspartate transaminase,and alkaline phosphatase l

关键词： Diabetes Streptozotocin Stingless bee honey Hematoxylin and eosin Periodic acid-Schiff Liver Kidney

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Insights on the molecular mechanism of neuroprotection exerted by edible bird’s nest and its bioactive constituents

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Food Science and Human Wellness 2023年第4期12卷 1008-1019页

作者： Weiyi Chu Chia Wei Phan Seng Joe Lim Abdul salam Babji Department of Pharmaceutical Life Sciences Faculty of PharmacyUniversiti MalayaKuala Lumpur 50603Malaysia Clinical Investigation Centre University Malaya Medical CentreLembah Pantai Kuala Lumpur 59100Malaysia Mushroom Research Centre Universiti MalayaKuala Lumpur 50603Malaysia Department of Food Sciences Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaUKM BangiSelangor 43600Malaysia Innovation Centre for Confectionery Technology(MANIS) Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaUKM BangiSelangor 43600Malaysia

Neurodegenerative diseases are often associated with the accumulation of oxidative stress and *** bird’s nest(EBN)is a glycoprotein(sialylated mucin glycopeptides)found to be beneficial against neurodegenerative ***,anti-inflammatory,and anti-apoptotic properties of EBN in preserving neuronal cells were widely researched using in vitro and in vivo *** effects of EBN are often linked to its great number of antioxidants and anti-inflammatory *** compounds in EBN,especially sialic acid,add value to neurotrophic potential of EBN and contribute to neuronal repair and *** studies reporting the neuroprotective effects of EBN,their molecular mechanisms,and neuroactive composition were gathered in this review to provide better insights on the neuroprotective effects of EBN.

关键词： Antioxidant Composition Edible bird nest Neurodegenerative disease Neuroprotection Sialylated mucin glycopeptide

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Multifunction Battery Energy Storage System for Distribution Networks

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Energy Engineering 2022年第2期119卷 569-589页

作者： Omar H.Abdalla Gamal Abdel-salam Azza A.A.Mostafa Department of Electrical Power&Machines Helwan UniversityCairoEgypt Technical Affairs Sectors South Cairo Electricity Distribution CompanyCairoEgypt Department of Energy Efficiency and Renewables Egyptian Electric Utility and Customer Protection Regulatory AgencyCairoEgypt

Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution *** of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity *** this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley *** paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation *** determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a *** addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s *** methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC *** simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming *** Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.

关键词： Battery energy storage system photovoltaic penetration peak load reduction valley filling MILP optimization

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Robust triboelectric information-mat enhanced by multi-modality deep learning for smart home

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InfoMat 2023年第1期5卷 139-160页

作者： Yanqin Yang Qiongfeng Shi Zixuan Zhang Xuechuan Shan Budiman salam Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingaporeSingapore National University of Singapore Suzhou Research Institute(NUSRI) SuzhouPeople's Republic of China Singapore Institute of Manufacturing Technology and National University of Singapore(SIMTech-NUS)Joint Lab on Large-area Flexible Hybrid Electronics National University of SingaporeSingaporeSingapore Printed Intelligent Device Group Singapore Institute of Manufacturing TechnologyAgency for ScienceTechnology and Research(A*STAR)SingaporeSingapore NUS Graduate School-Integrative Sciences and Engineering Programme(ISEP) National University of SingaporeSingaporeSingapore

In metaverse,a digital-twin smart home is a vital platform for immersive communication between the physical and virtual *** nanogenerators(TENGs)sensors contribute substantially to providing smart-home ***,TENG deployment is hindered by its unstable out-put under environment ***,we develop a digital-twin smart home using a robust all-TENG based information mat(InfoMat),which consists of an in-home mat array and an entry *** interdigital electrodes design allows environment-insensitive ratiometric readout from the mat array to can-cel the commonly experienced environmental *** position sensing is also achieved because of the interval arrangement of the mat ***,the two-channel entry mat generates multi-modality informa-tion to aid the 10-user identification accuracy to increase from 93% to 99% compared to the one-channel ***,a digital-twin smart home is visualized by real-time projecting the information in smart home to virtual reality,including access authorization,position,walking trajectory,dynamic activities/sports,and so on.

关键词： digital twin environment-insensitive multi-modality deep learning scalability smart home triboelectric information-mat

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Intrusion Detection Systems Using Blockchain Technology: A Review, Issues and Challenges

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Computer Systems Science & Engineering 2022年第1期40卷 87-112页

作者： salam Al-E’mari Mohammed Anbar Yousef Sanjalawe Selvakumar Manickam Iznan Hasbullah National Advanced IPv6 Centre of Excellence(NAv6) Universiti Sains Malaysia11800 USMPenangMalaysia Computer Sciences Department Northern Border University(NBU)9280 NBUAr’arthe Kingdom of Saudi Arabia

Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection ***,the current approaches have challenges in detecting intrusions,which may affect the performance of the overall detection system as well as network *** the time being,one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain *** technology moves in the direction of persistent revolution and *** is a chain of blocks that covers information and maintains trust between individuals no matter how far apart they ***,blockchain was integrated into intrusion detection systems to enhance their overall *** has also been adopted in health-care,supply chain management,and the Internet of *** uses robust cryptography with private and public keys,and it has numerous properties that have leveraged security’s performance over peer-to-peer networks without the need for a third *** explore and highlight the importance of integrating blockchain with intrusion detection systems,this paper provides a comprehensive background of intrusion detection systems and blockchain ***,a comprehensive review of emerging intrusion detection systems based on blockchain technology is ***,this paper suggests important future research directions and trending topics in intrusion detection systems based on blockchain technology.

关键词： Blockchain intrusiondetectionsystem networksecurity maliciousattacks

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Enhanced Heap-Based Optimizer Algorithm for Solving Team Formation Problem

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Computers, Materials & Continua 2022年第12期73卷 5245-5268页

作者： Nashwa Nageh Ahmed Elshamy Abdel Wahab Said Hassan Mostafa Sami Mustafa Abdul salam Faculty of Science Suez Canal UniversityIsmailiaEgypt Faculty of Computers and Artificial Intelligence Helwan UniversityHelwanEgypt Faculty of Computers and Artificial Intelligence Benha UniversityBenha 13518Egypt Faculty of Computer Studies Arab Open UniversityCairoEgypt

Team Formation(TF)is considered one of the most significant problems in computer science and *** is defined as forming the best team of experts in a social network to complete a task with least *** real-world problems,such as task assignment,vehicle routing,nurse scheduling,resource allocation,and airline crew scheduling,are based on the TF *** has been shown to be a Nondeterministic Polynomial time(NP)problem,and high-dimensional problem with several local optima that can be solved using efficient approximation *** paper proposes two improved swarm-based algorithms for solving team formation *** first algorithm,entitled Hybrid Heap-Based Optimizer with Simulated Annealing Algorithm(HBOSA),uses a single crossover operator to improve the performance of a standard heap-based optimizer(HBO)*** also employs the simulated annealing(SA)approach to improve model convergence and avoid local minima *** second algorithm is the Chaotic Heap-based Optimizer Algorithm(CHBO).CHBO aids in the discovery of new solutions in the search space by directing particles to different regions of the search *** HBO’s optimization process,a logistic chaotic map is *** performance of the two proposed algorithms(HBOSA)and(CHBO)is evaluated using thirteen benchmark functions and tested in solving the TF problem with varying number of experts and ***,the proposed algorithms were compared to well-known optimization algorithms such as the Heap-Based Optimizer(HBO),Developed Simulated Annealing(DSA),Particle SwarmOptimization(PSO),GreyWolfOptimization(GWO),and Genetic Algorithm(GA).Finally,the proposed algorithms were applied to a real-world benchmark dataset known as the Internet Movie Database(IMDB).The simulation results revealed that the proposed algorithms outperformed the compared algorithms in terms of efficiency and performance,with fast convergence to the global minimum.

关键词： Team formation problem optimization problem genetic algorithm heap-based optimizer simulated annealing hybridization method chaotic local search

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Rough Sets Hybridization with Mayfly Optimization for Dimensionality Reduction

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Computers, Materials & Continua 2022年第10期73卷 1087-1108页

作者： Ahmad Taher Azar Mustafa Samy Elgendy Mustafa Abdul salam Khaled M.Fouad Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Computer Studies Arab Open UniversityCairoEgypt Faculty of Information Technology and Computer Science Nile UniversityShikh ZaidEgypt

Big data is a vast amount of structured and unstructured data that must be dealt with on a regular *** reduction is the process of converting a huge set of data into data with tiny dimensions so that equal information may be expressed *** tactics are frequently utilized to improve classification or regression challenges while dealing with machine learning *** achieve dimensionality reduction for huge data sets,this paper offers a hybrid particle swarm optimization-rough set PSO-RS and Mayfly algorithm-rough set MA-RS.A novel hybrid strategy based on the Mayfly algorithm(MA)and the rough set(RS)is proposed in *** performance of the novel hybrid algorithm MA-RS is evaluated by solving six different data sets from the *** simulation results and comparison with common reduction methods demonstrate the proposed MARS algorithm’s capacity to handle a wide range of data ***,the rough set approach,as well as the hybrid optimization techniques PSO-RS and MARS,were applied to deal with the massive data ***-hybrid RS’s method beats other classic dimensionality reduction techniques,according to the experimental results and statistical testing studies.

关键词： Dimensionality reduction metaheuristics optimization algorithm mayfly particle swarm optimizer feature selection

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