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Fulltext Fundamental lifetime mechanisms in routing protocols for wireless sensor networks: a survey and open issues

Eslaminejad M, Razak SA

Sensors (Basel), 2012;12(10):13508-44.
PMID: 23202008 DOI: 10.3390/s121013508

Wireless sensor networks basically consist of low cost sensor nodes which collect data from environment and relay them to a sink, where they will be subsequently processed. Since wireless nodes are severely power-constrained, the major concern is how to conserve the nodes' energy so that network lifetime can be extended significantly. Employing one static sink can rapidly exhaust the energy of sink neighbors. Furthermore, using a non-optimal single path together with a maximum transmission power level may quickly deplete the energy of individual nodes on the route. This all results in unbalanced energy consumption through the sensor field, and hence a negative effect on the network lifetime. In this paper, we present a comprehensive taxonomy of the various mechanisms applied for increasing the network lifetime. These techniques, whether in the routing or cross-layer area, fall within the following types: multi-sink, mobile sink, multi-path, power control and bio-inspired algorithms, depending on the protocol operation. In this taxonomy, special attention has been devoted to the multi-sink, power control and bio-inspired algorithms, which have not yet received much consideration in the literature. Moreover, each class covers a variety of the state-of-the-art protocols, which should provide ideas for potential future works. Finally, we compare these mechanisms and discuss open research issues.
Fulltext Delaunay triangulation as a new coverage measurement method in wireless sensor network

Chizari H, Hosseini M, Poston T, Razak SA, Abdullah AH

Sensors (Basel), 2011;11(3):3163-76.
PMID: 22163792 DOI: 10.3390/s110303163

Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as 'fat', 'healthy' or 'thin' to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios.
Fulltext Generalized epilepsy with febrile seizure plus (GEFS+) spectrum: Novel de novo mutation of SCN1A detected in a Malaysian patient

Tan EH, Yusoff AA, Abdullah JM, Razak SA

J Pediatr Neurosci, 2012 May;7(2):123-5.
PMID: 23248692 DOI: 10.4103/1817-1745.102575

In this report, we describe a 15-year-old Malaysian male patient with a de novo SCN1A mutation who experienced prolonged febrile seizures after his first seizure at 6 months of age. This boy had generalized tonic clonic seizure (GTCS) which occurred with and without fever. Sequencing analysis of voltage-gated sodium channel a1-subunit gene, SCN1A, confirmed a homozygous A to G change at nucleotide 5197 (c.5197A > G) in exon 26 resulting in amino acid substitution of asparagines to aspartate at codon 1733 of sodium channel. The mutation identified in this patient is located in the pore-forming loop of SCN1A and this case report suggests missense mutation in pore-forming loop causes generalized epilepsy with febrile seizure plus (GEFS+) with clinically more severe neurologic phenotype including intellectual disabilities (mental retardation and autism features) and neuropsychiatric disease (anxiety disorder).
Fulltext An overview of data routing approaches for wireless sensor networks

Anisi MH, Abdullah AH, Razak SA, Ngadi MA

Sensors (Basel), 2012 03 27;12(4):3964-96.
PMID: 23443040 DOI: 10.3390/s120403964

Recent years have witnessed a growing interest in deploying large populations of microsensors that collaborate in a distributed manner to gather and process sensory data and deliver them to a sink node through wireless communications systems. Currently, there is a lot of interest in data routing for Wireless Sensor Networks (WSNs) due to their unique challenges compared to conventional routing in wired networks. In WSNs, each data routing approach follows a specific goal (goals) according to the application. Although the general goal of every data routing approach in WSNs is to extend the network lifetime and every approach should be aware of the energy level of the nodes, data routing approaches may focus on one (or some) specific goal(s) depending on the application. Thus, existing approaches can be categorized according to their routing goals. In this paper, the main goals of data routing approaches in sensor networks are described. Then, the best known and most recent data routing approaches in WSNs are classified and studied according to their specific goals.
De-novo mutations and genetic variation in the SCN1A gene in Malaysian patients with generalized epilepsy with febrile seizures plus (GEFS+)

Tan EH, Razak SA, Abdullah JM, Mohamed Yusoff AA

Epilepsy Res, 2012 Dec;102(3):210-5.
PMID: 22944210 DOI: 10.1016/j.eplepsyres.2012.08.004

Generalized epilepsy with febrile seizures plus (GEFS+) comprises a group of clinically and genetically heterogeneous epilepsy syndrome. Here, we provide the first report of clinical presentation and mutational analysis of SCN1A gene in 36 Malaysian GEFS+ patients. Mutational analysis of SCN1A gene revealed twenty seven sequence variants (missense mutation and silent polymorphism also intronic polymorphism), as well as 2 novel de-novo mutations were found in our patients at coding regions, c.5197A>G (N1733D) and c.4748A>G (H1583R). Our findings provide potential genetic insights into the pathogenesis of GEFS+ in Malaysian populations concerning the SCN1A gene mutations.
Genetic, epigenetic, and lineage-directed mechanisms in benzene-induced malignancies and hematotoxicity targeting hematopoietic stem cells niche

Dewi R, Hamid ZA, Rajab NF, Shuib S, Razak SA

Hum Exp Toxicol, 2020 May;39(5):577-595.
PMID: 31884827 DOI: 10.1177/0960327119895570

Benzene is a known hematotoxic and leukemogenic agent with hematopoietic stem cells (HSCs) niche being the potential target. Occupational and environmental exposure to benzene has been linked to the incidences of hematological disorders and malignancies. Previous studies have shown that benzene may act via multiple modes of action targeting HSCs niche, which include induction of chromosomal and micro RNA aberrations, leading to genetic and epigenetic modification of stem cells and probable carcinogenesis. However, understanding the mechanism linking benzene to the HSCs niche dysregulation is challenging due to complexity of its microenvironment. The niche is known to comprise of cell populations accounted for HSCs and their committed progenitors of lymphoid, erythroid, and myeloid lineages. Thus, it is fundamental to address novel approaches via lineage-directed strategy to elucidate precise mechanism involved in benzene-induced toxicity targeting HSCs and progenitors of different lineages. Here, we review the key genetic and epigenetic factors that mediate hematotoxicological effects by benzene and its metabolites in targeting HSCs niche. Overall, the use of combined genetic, epigenetic, and lineage-directed strategies targeting the HSCs niche is fundamental to uncover the key mechanisms in benzene-induced hematological disorders and malignancies.
Fulltext Nutrient intake and nutritional status of newly diagnosed patients with cancer from the East Coast of Peninsular Malaysia

Menon K, Razak SA, Ismail KA, Krishna BV

BMC Res Notes, 2014;7:680.
PMID: 25270226 DOI: 10.1186/1756-0500-7-680

Cancer therapy in Malaysia primarily focuses on the clinical management of patients with cancer and malnutrition continues to be one of the major causes of death in these patients. There is a dearth of information on the nutrient intake and status of newly diagnosed patients with cancer prior to the initiation of treatment. The present study aims to assess the nutrient intake and status of newly diagnosed patients with cancer from the East Coast of Peninsular Malaysia.
Fulltext Observing Consistency in Online Communication Patterns for User Re-Identification

Adeyemi IR, Razak SA, Salleh M, Venter HS

PLoS One, 2016;11(12):e0166930.
PMID: 27918593 DOI: 10.1371/journal.pone.0166930

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.
Cytotoxicity evaluation of vancomycin and its complex with beta-cyclodextrin on human glial cell line

Sofian ZM, Abdullah JM, Rahim AA, Shafee SS, Mustafa Z, Razak SA

Pak J Pharm Sci, 2012 Oct;25(4):831-7.
PMID: 23010001

The possible cytotoxic effects of vancomycin and its complex with beta-cyclodextrin (β-CD) on human glial cell line (CRL 8621) were studied accordingly by means of MTS assay. The cultured cells were incubated with various concentrations of vancomycin, β-CD as well as β-CD/vancomycin complex ranging from 4.69 to 300 ug/ml. A linear dose-dependency cytotoxicity followed by hermetic-like biphasic dose-dependence was observed after incubation period of 72 hours. In general, significant increase (p<0.001) of cell proliferation was observed at lower concentrations: <18.75 μg/ml for cells treated with β-CD and their complex while < 9.38 μg/ml for cells treated with vancomycin. In contrary, regardless of the treatments given, significant (p<0.001) reduce in cell survival was found at higher concentrations >150 μg/ml. In particular, 50 % inhibitory in vitro was achieved at the concentrations of 115.95 μg/ml (for β-CD), 116.48 μg/ml (for vancomycin) and 115.44 μg/ml (for β-CD/vancomycin complex).
The effect of dietary cricket meal (Gryllus bimaculatus) on growth performance, antioxidant enzyme activities, and haematological response of African catfish (Clarias gariepinus)

Taufek NM, Aspani F, Muin H, Raji AA, Razak SA, Alias Z

Fish Physiol Biochem, 2016 Aug;42(4):1143-55.
PMID: 26886132 DOI: 10.1007/s10695-016-0204-8

This study was conducted to investigate the growth performance, biomarkers of oxidative stress, catalase (CAT), superoxide dismutase (SOD), and glutathione S-transferase (GST) as well as the haematological response of African catfish after being fed with fish feed containing different levels of cricket meal. The juvenile fish were assigned to three different treatments with isonitrogenous (35 %) and isoenergetic (19 kJ g(-1)) diets containing 100 % cricket meal (100 % CM), 75 % cricket meal (75 % CM), and 100 % fishmeal (100 % FM) as control groups for 7 weeks. The results indicated that a diet containing 100 % CM and 75 % CM improved growth performance in terms of body weight gain and specific growth rate, when compared to 100 % FM. The feed conversion ratio (FCR) and protein efficiency ratio (PER) did not differ significantly between all diets, but reduced FCR and increased PER were observed with a higher inclusion of cricket meal. A haematological examination of fish demonstrated no significant difference of red blood cells in all diets and white blood cells showed a significantly higher value in fishmeal-fed fish. On the other hand, haemoglobin and haematocrit significantly increased with increasing amounts of cricket meal in the diet. Antioxidant activity of CAT was higher in the 100 % CM group compared to fish fed other diets, whereas GST and SOD showed increasing trends with a higher incorporation of cricket, although insignificant differences were observed between all diets. These results suggest that cricket meal could be an alternative to fishmeal as a protein source in the African catfish diet.
Fulltext The heterogeneic distribution of Helicobacter pylori cag pathogenicity island reflects different pathologies in multiracial Malaysian population

Hanafiah A, Razak SA, Neoh HM, Zin NM, Lopes BS

Braz J Infect Dis, 2020 11 04;24(6):545-551.
PMID: 33157035 DOI: 10.1016/j.bjid.2020.10.005

BACKGROUND: Helicobacter pylori harbouring cag-pathogenicity island (cagPAI) which encodes type IV secretion system (T4SS) and cagA virulence gene are involved in inflammation of the gastric mucosa. We examined all the 27 cagPAI genes in 88 H. pylori isolates from patients of different ethnicities and examined the association of the intactness of cagPAI region with histopathological scores of the gastric mucosa.
RESULTS: 96.6% (n=85) of H. pylori isolates were cagPAI-positive with 22.4% (19/85) having an intact cagPAI, whereas 77.6% (66/85) had a partial/rearranged cagPAI. The frequency of cag2 and cag14 were found to be significantly higher in H. pylori isolated from Malays, whereas cag4 was predominantly found in Chinese isolates. The cag24 was significantly found in higher proportions in Malay and Indian isolates than in Chinese isolates. The intactness of cagPAI region showed an association with histopathological scores of the gastric mucosa. Significant association was observed between H. pylori harbouring partial cagPAI with higher density of bacteria and neutrophil activity, whereas strains lacking cagPAI were associated with higher inflammatory score.
CONCLUSIONS: The genotypes of H. pylori strains with various cagPAI rearrangement associated with patients' ethnicities and histopathological scores might contribute to the pathogenesis of H. pylori infection in a multi-ethnic population.
Fulltext Fairness-Oriented Semichaotic Genetic Algorithm-Based Channel Assignment Technique for Node Starvation Problem in Wireless Mesh Networks

Ghaleb FA, Al-Rimy BAS, Boulila W, Saeed F, Kamat M, Foad Rohani M, et al.

Comput Intell Neurosci, 2021;2021:2977954.
PMID: 34413885 DOI: 10.1155/2021/2977954

Wireless mesh networks (WMNs) have emerged as a scalable, reliable, and agile wireless network that supports many types of innovative technologies such as the Internet of Things (IoT), Wireless Sensor Networks (WSN), and Internet of Vehicles (IoV). Due to the limited number of orthogonal channels, interference between channels adversely affects the fair distribution of bandwidth among mesh clients, causing node starvation in terms of insufficient bandwidth distribution, which impedes the adoption of WMN as an efficient access technology. Therefore, a fair channel assignment is crucial for the mesh clients to utilize the available resources. However, the node starvation problem due to unfair channel distribution has been vastly overlooked during channel assignment by the extant research. Instead, existing channel assignment algorithms equally distribute the interference reduction on the links to achieve fairness which neither guarantees a fair distribution of the network bandwidth nor eliminates node starvation. In addition, the metaheuristic-based solutions such as genetic algorithm, which is commonly used for WMN, use randomness in creating initial population and selecting the new generation usually leading the search to local minima. To this end, this study proposes a Fairness-Oriented Semichaotic Genetic Algorithm-Based Channel Assignment Technique (FA-SCGA-CAA) to solve node starvation problem in wireless mesh networks. FA-SCGA-CAA maximizes link fairness while minimizing link interference using a genetic algorithm (GA) with a novel nonlinear fairness-oriented fitness function. The primary chromosome with powerful genes is created based on multicriterion links ranking channel assignment algorithm. Such a chromosome was used with a proposed semichaotic technique to create a strong population that directs the search towards the global minima effectively and efficiently. The proposed semichaotic technique was also used during the mutation and parent selection of the new genes. Extensive experiments were conducted to evaluate the proposed algorithm. A comparison with related work shows that the proposed FA-SCGA-CAA reduced the potential node starvation by 22% and improved network capacity utilization by 23%. It can be concluded that the proposed FA-SCGA-CAA is reliable to maintain high node-level fairness while maximizing the utilization of the network resources, which is the ultimate goal of many wireless networks.
Disconnecting surgery at alveus and cornu ammonis of hippocampus, amygdala superficialis, and amygdala medial nuclei for epilepsy associated with attention deficit hyperactivity disorder

Idris Z, Zakaria Z, Halim SA, Razak SA, Ghani ARI, Abdullah JM

Childs Nerv Syst, 2021 05;37(5):1797-1802.
PMID: 32949261 DOI: 10.1007/s00381-020-04893-z

The neural basis for epilepsy and attention deficit hyperactivity disorder (ADHD) is currently incompletely known. We reported a young girl with both epilepsy and ADHD, who had a calcified lesion in the right basolateral amygdalo-hippocampal region extending to the ventral striatum. The child underwent disconnecting surgery and biopsy of the lesion. Fascinatingly, the child's behavior changed immediately after the surgery from inattentive and impulsive to nearly normal behavior experiencing no more breakthrough seizures since after 3 years of surgery. The Schaltenbrand Wahren Brain Atlas revealed alveus, cornu ammonis, amygdala superficialis, and medium as the disconnected region in this surgery.
Fulltext Towards Integrated Air Pollution Monitoring and Health Impact Assessment Using Federated Learning: A Systematic Review

Neo EX, Hasikin K, Mokhtar MI, Lai KW, Azizan MM, Razak SA, et al.

Front Public Health, 2022;10:851553.
PMID: 35664109 DOI: 10.3389/fpubh.2022.851553

Environmental issues such as environmental pollutions and climate change are the impacts of globalization and become debatable issues among academics and industry key players. One of the environmental issues which is air pollution has been catching attention among industrialists, researchers, and communities around the world. However, it has always neglected until the impacts on human health become worse, and at times, irreversible. Human exposure to air pollutant such as particulate matters, sulfur dioxide, ozone and carbon monoxide contributed to adverse health hazards which result in respiratory diseases, cardiorespiratory diseases, cancers, and worst, can lead to death. This has led to a spike increase of hospitalization and emergency department visits especially at areas with worse pollution cases that seriously impacting human life and health. To address this alarming issue, a predictive model of air pollution is crucial in assessing the impacts of health due to air pollution. It is also critical in predicting the air quality index when assessing the risk contributed by air pollutant exposure. Hence, this systemic review explores the existing studies on anticipating air quality impact to human health using the advancement of Artificial Intelligence (AI). From the extensive review, we highlighted research gaps in this field that are worth to inquire. Our study proposes to develop an AI-based integrated environmental and health impact assessment system using federated learning. This is specifically aims to identify the association of health impact and pollution based on socio-economic activities and predict the Air Quality Index (AQI) for impact assessment. The output of the system will be utilized for hospitals and healthcare services management and planning. The proposed solution is expected to accommodate the needs of the critical and prioritization of sensitive group of publics during pollution seasons. Our finding will bring positive impacts to the society in terms of improved healthcare services quality, environmental and health sustainability. The findings are beneficial to local authorities either in healthcare or environmental monitoring institutions especially in the developing countries.
Fulltext Depressive, Anxiety, and Stress Symptoms in Parents of Children Being Admitted for Febrile Seizures in a Tertiary Hospital in the East Coast of Malaysia

Othman A, Razak SA, Nasir A, Ghazali AK, Mohd Radzi MAR

Eur J Investig Health Psychol Educ, 2023 Jun 09;13(6):1015-1025.
PMID: 37366781 DOI: 10.3390/ejihpe13060077

Febrile seizures in children are an alarming experience for parents. This study aimed to assess the psychological functioning of parents of children when they were being admitted for treatment of febrile seizures in the hospital, the importance of which is clear, since parents are the primary custodian of their children. This is a cross-sectional study conducted on 110 participants whose child had been admitted for a febrile seizure to Hospital Universiti Sains Malaysia from September 2020 until June 2021. The depression, anxiety, and stress levels were determined based on a validated Bahasa Melayu questionnaire of the Depression Anxiety Stress Scale (DASS-21). In addition, multiple logistic regression was used to determine the associated factors related to the participants' psychological functioning. The mean age of children with febrile seizures were 21 months old, and most children showed features of simple febrile seizures (71.8%). The prevalence of anxiety, stress, and depression were 58.2%, 29%, and 23.6%, respectively. Using multiple logistic regression, child age, family history of febrile seizures, family history of epilepsy, and length of stay in the ward were found to be significantly associated with anxiety when adjusted for other variables. Otherwise, for depression and stress, no significant associated variables were found when adjusted for other variables. Anxiety was highly reported by participants when their children were admitted for febrile seizures. Several factors impacted their anxiety, including the lower the child's age was, participants with no family history of febrile seizures before, and the longer duration of hospital stay. Therefore, further study and intervention on reducing the parent's anxiety could be emphasized in the future.
Fulltext Artificial intelligence-assisted air quality monitoring for smart city management

Neo EX, Hasikin K, Lai KW, Mokhtar MI, Azizan MM, Hizaddin HF, et al.

PeerJ Comput Sci, 2023;9:e1306.
PMID: 37346549 DOI: 10.7717/peerj-cs.1306

BACKGROUND: The environment has been significantly impacted by rapid urbanization, leading to a need for changes in climate change and pollution indicators. The 4IR offers a potential solution to efficiently manage these impacts. Smart city ecosystems can provide well-designed, sustainable, and safe cities that enable holistic climate change and global warming solutions through various community-centred initiatives. These include smart planning techniques, smart environment monitoring, and smart governance. An air quality intelligence platform, which operates as a complete measurement site for monitoring and governing air quality, has shown promising results in providing actionable insights. This article aims to highlight the potential of machine learning models in predicting air quality, providing data-driven strategic and sustainable solutions for smart cities.
METHODS: This study proposed an end-to-end air quality predictive model for smart city applications, utilizing four machine learning techniques and two deep learning techniques. These include Ada Boost, SVR, RF, KNN, MLP regressor and LSTM. The study was conducted in four different urban cities in Selangor, Malaysia, including Petaling Jaya, Banting, Klang, and Shah Alam. The model considered the air quality data of various pollution markers such as PM2.5, PM10, O3, and CO. Additionally, meteorological data including wind speed and wind direction were also considered, and their interactions with the pollutant markers were quantified. The study aimed to determine the correlation variance of the dependent variable in predicting air pollution and proposed a feature optimization process to reduce dimensionality and remove irrelevant features to enhance the prediction of PM2.5, improving the existing LSTM model. The study estimates the concentration of pollutants in the air based on training and highlights the contribution of feature optimization in air quality predictions through feature dimension reductions.
RESULTS: In this section, the results of predicting the concentration of pollutants (PM2.5, PM10, O3, and CO) in the air are presented in R2 and RMSE. In predicting the PM10 and PM2.5concentration, LSTM performed the best overall high R2values in the four study areas with the R2 values of 0.998, 0.995, 0.918, and 0.993 in Banting, Petaling, Klang and Shah Alam stations, respectively. The study indicated that among the studied pollution markers, PM2.5,PM10, NO2, wind speed and humidity are the most important elements to monitor. By reducing the number of features used in the model the proposed feature optimization process can make the model more interpretable and provide insights into the most critical factor affecting air quality. Findings from this study can aid policymakers in understanding the underlying causes of air pollution and develop more effective smart strategies for reducing pollution levels.
Nerve conduction study of healthy Asian Malays: the influence of age on median, ulnar, and sural nerves

Awang MS, Abdullah JM, Abdullah MR, Tahir A, Tharakan J, Prasad A, et al.

Med Sci Monit, 2007 Jul;13(7):CR330-2.
PMID: 17599028

Nerve conduction study is essential in the diagnosis of focal neuropathies and diffuse polyneuropathies. There are many factors that can affect nerve conduction velocity, and age is one of them. Most of the many studies of this effect, and the values from them, were on Caucasian subjects. Therefore, this study was designed to investigate the effect of age on conduction velocity among healthy Asian Malay subjects by analyzing its influence on the median, ulnar, and sural nerves.
Evaluation of the Cytotoxicity of Levodopa and its Complex with Hydroxypropyl-ß-Cyclodextrin (HP-ß-CD) to an Astrocyte Cell Line

Sofian ZM, Shafee SS, Abdullah JM, Osman H, Razak SA

Malays J Med Sci, 2014 Dec;21(Spec Issue):6-11.
PMID: 25941458

A simple, reliable a 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxy-phenyl)-2-(4-sulfophenyl)-2H-tetrazolium, (MTS) assay was conducted to evaluate the potential cytotoxic effects of levodopa, a "gold standard therapy" for Parkinsonism, and its complex with Hydroxypropyl-β-Cyclodextrin (HP-β-CD) on an astrocyte cell line. The cells were incubated in a range of concentrations from 4.69 to 300 μg/mL levodopa, HP-β-CD or the complex for up to 72 hours. At every 24-hour interval, the optical density (OD), which reflects the number of viable cells, was recorded. In general, linear dose-dependent cytotoxicity profiles were observed for the cells subjected to levodopa or the complex, whereas a slightly triphasic response was observed for the cells exposed to HP-β-CD. A significant difference (P < 0.05) in cytotoxicity was detected between the HP-β-CD-treated group and the levodopa-treated group. In particular, we observed that the cells treated with the complex, even at the highest concentrations (> 200 μg/mL), exhibited improved tolerability in a time-dependent manner, which may indicate the potential ability of HP-β-CD to mask the toxic effects of levodopa via complexation.
Pathogenic hitchhiker diversity on international ships' ballast water at West Malaysia port

Salleh NA, Rosli FN, Akbar MA, Yusof A, Sahrani FK, Razak SA, et al.

Mar Pollut Bull, 2021 Nov;172:112850.
PMID: 34391012 DOI: 10.1016/j.marpolbul.2021.112850

This study investigates bacterial diversity and potential pathogens in the international ships' ballast water at Tanjung Pelepas Port, Malaysia, using 16S rRNA amplicon sequencing. Thirty-four bacterial phylum, 305 families, 577 genera, and 941 species were detected in eight ballast water samples of different origins. The similarity of the bacterial composition between samples was found to be random and not tied to geographical locations. The bacterial abundance did not seem to be affected by related physicochemical except for temperature. Ballast water samples with a temperature lower than 25 °C showed a relatively lower bacterial abundance. A total of 33 potential pathogens were detected from all ballast water samples. Pseudomonas spp., Tenacibaculum spp., Flavobacteriaceae spp., Halomonas spp., and Acinetobacter junii are the potential pathogens with more than 10% OTU prevalence. This study would provide beneficial information for further enhancing ballast water microorganism guidelines in Malaysia.
Fulltext A Hybrid Lightweight System for Early Attack Detection in the IoMT Fog

Hameed SS, Selamat A, Abdul Latiff L, Razak SA, Krejcar O, Fujita H, et al.

Sensors (Basel), 2021 Dec 11;21(24).
PMID: 34960384 DOI: 10.3390/s21248289

Cyber-attack detection via on-gadget embedded models and cloud systems are widely used for the Internet of Medical Things (IoMT). The former has a limited computation ability, whereas the latter has a long detection time. Fog-based attack detection is alternatively used to overcome these problems. However, the current fog-based systems cannot handle the ever-increasing IoMT's big data. Moreover, they are not lightweight and are designed for network attack detection only. In this work, a hybrid (for host and network) lightweight system is proposed for early attack detection in the IoMT fog. In an adaptive online setting, six different incremental classifiers were implemented, namely a novel Weighted Hoeffding Tree Ensemble (WHTE), Incremental K-Nearest Neighbors (IKNN), Incremental Naïve Bayes (INB), Hoeffding Tree Majority Class (HTMC), Hoeffding Tree Naïve Bayes (HTNB), and Hoeffding Tree Naïve Bayes Adaptive (HTNBA). The system was benchmarked with seven heterogeneous sensors and a NetFlow data infected with nine types of recent attack. The results showed that the proposed system worked well on the lightweight fog devices with ~100% accuracy, a low detection time, and a low memory usage of less than 6 MiB. The single-criteria comparative analysis showed that the WHTE ensemble was more accurate and was less sensitive to the concept drift.

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