This article describes the Pulsed-field gel electrophoresis clustering of the predominantSalmonellastrains (Salmonellaser. Albany,Salmonellaser. Brancaster, andSalmonellaser. Corvallis) isolated from poultry and processing environment in wet market and small-scale processing plant in Penang and Perlis, the northern states of Malaysia. Agar disk diffusion assay was performed to determine the phenotypic antibiotic resistance of theseSalmonellastrains. The most common antibiograms among the three predominantSalmonellaserovars were reported. The presence of integrase genes and antibiotic resistance genes conferring to resistance against β-lactams, aminoglycosides, tetracyclines, quinolones, sulphonamides and chloramphenicol, was detected via PCR amplification.
The present data article provides a descriptive and analytical exploration on the links between positive mental health, subjective happiness, forgiveness, humility, and information literacy self-efficacy among 969 undergraduate students from Indonesia, Malaysia, and Thailand. There are 355 males and 614 females with an average age of 20.47 years and a standard deviation of 1.87. Respondents are recruited by simple random sampling using face to face method, at one time data retrieval during 2019. The Indonesian, Malaysian and Thailand-version questionnaires were provided to each groups of participants according to their nationality and native language, using back-to-back analysis. The socio-demographic details of the respondents, descriptive statistics, confirmatory factor analysis, correlation matrix of all variables in all groups according to country, results of regression analysis of variables, and Kruskal Wallis for all five variables in all groups are provided.
Sudan is located in the heart of Africa and surrounded by eight countries with people of different ethnic origins. Historical records show that the population of the Sudan is a mixture of Arabic, West Asian Arabic and sub-Saharan African elements. The present survey provides data on allele lineages, and haplotype frequencies of Human Leukocyte Antigen (HLA) class I (HLA-A and HLA-B) and class II (HLA-DR and -HLA-DQ) loci in 11 Sudanese populations. The sampled individuals are all local transplant donors who provided informed consent for HLA analyses on their blood samples and were registered at National Cancer Institute, University of Gezira, Wad Medani. The HLA class I and II data reported here can be subjected for future analyses of genetic structure and health in Sudan. These include as reference datasets for identifying the association between HLA and diseases and for designing donor recruitment strategies.
The data presented in this article were generated through the gas chromatography (GC) with a flame ionization detector (FID). The flaxseed oil was converted into fatty acid methyl ester (FAME) then used in the GC with FID and observe the retention time of different fatty acid present in the flaxseed oil. The observed retention time was compared with the standard fatty acid to confirm the specific fatty acid presence in the flaxseed oil. The part of the data is used in the article "Optimization of the process variable for biodiesel production by transesterification of flaxseed oil and produced biodiesel characterizations" Renewable Energy journal (Ahmad et al., 2019).
The dataset presented here are part of the data planned to produce biodiesel from flaxseed. Biodiesel production from flaxseed oil through transesterification process using KOH as catalyst, and the operating parameters were optimized with the help of face-centered central composite design (FCCD) of response surface methodology (RSM). The operating independent variables selected such as, methanol oil ratio (4:1 to 6:1), catalyst (KOH) weight (0.40-1.0%), temperature (35 °C-65 °C), and reaction time (30 min-60 min) were optimized against biodiesel yield as response. The maximum yield (98.6%) of biodiesel from flaxseed can achieved at optimum methanol oil ratio (5.9:1), catalyst (KOH) weight (0.51%), reaction temperature (59.2 °C), and reaction time (33 min). The statistical significance of the data set was tested through the analysis of variance (ANOVA). These data were the part of the results reported in "Optimization of process variables for biodiesel production by transesterification of flaxseed oil and produced biodiesel characterizations" Renewable Energy [1].
The optimization data presented here are part of the study planned to remove the caffeine from aqueous solution through the large surface area optimized H3PO4-activated Acacia mangium wood activated carbon (OAMW-AC). The maximum adsorption capacity of the OAMW-AC for caffeine adsorption was achieved (30.3 mg/g) through optimized independent variables such as, OAMW-AC dosage (3.0 g/L), initial caffeine concentration (100 mg/L), contact time (60 min), and solution pH (7.7). The adsorption capacity of OAMW-AC was optimized with the help of rotatable central composite design of response surface methodology. Under the stated optimized conditions for maximum adsorption capacity, the removal efficiency was calculated to be 93%. The statistical significance of the data set was tested through the analysis of variance (ANOVA) study. Data confirmed the statistical model for caffeine adsorption was significant. The regression coefficient (R2) of curve fitting through the quadratic model was found to be 0.9832, and the adjusted regression coefficient was observed to be 0.9675.
In this article, data on the demographic parameters of the Aedes albopictus were collected from those areas in Shah Alam, Malaysia that had experienced a dengue outbreak. The surveys were conducted from March to December 2017. The eggs of the Ae. albopictus were collected using ovitraps, and were analysed based on the demographic parameters in a controlled environment in an insectarium. The data were comprised of four types of biological information on the life demographic parameters of the Ae. albopictus that were monitored based on specific localities. The data were inferred information regarding egg productivity (n), egg development (%), immature development (days), and survivorship (days).
Periplaneta americana is a cosmopolitan pest cockroach endemic to tropical and subtropical climates. It occurs frequently in urban sewer and wastewater system and transit in human proximities, spreading pathogens that causes serious public health concerns such as asthma, allergies, and others. By using the Next-generation Sequencing (NGS) known as Illumina NovaSeq 6000, this article documents for the draft genome data set of P. americana collected in Penang Island, Malaysia. This article displays the pair-end 150 bp genome dataset and results on the sequence quality. This genome dataset presents the information for further understanding of P. americana populations at molecular level and the opportunity to develop effective control and management strategies for the species. This dataset is available under Sequence Read Archive (SRA) databases with the SRR23867103.
In this article, five variables including type of substrates, sizes of substrates, mass ratio of spawn to substrates (SP/SS), temperature and pretreatment of substrates were used to model mycelium growth in Pleurotus sp. (oyster mushroom) cultivation by using agricultural wastes via two level factorial analysis. Two different substrates which were empty fruit bunch (EFB) and sugarcane bagasse (SB) were used. Analysis of Variance (ANOVA) for both mycelium extension rate (M) and nitrogen concentration in mycelium (N) showed that the confidence level was greater than 95% while p-value of both models were less than 0.05 which is significant. The coefficient of determination (R2) for both M and N were 0.8829 and 0.9819 respectively. From the experiment, the best condition to achieve maximum M (0.8 cm/day) and N (656 mg/L) was by using substrate B, 2.5 cm size of substrate, 1:14 for SP/SS, incubated at ambient temperature and application of steam treatment. The data showed that EFB can be used to replace sawdust as a media for the oyster mushroom cultivation. Data analysis was performed using Design Expert version 7.0.
This study is on the distribution of rare earth elements (REEs) concentrations in sediments collected from 113 sampling locations of Linggi River. The analysis of sediment samples was performed by Neutron Activation Analysis (NAA) and Inductively Coupled Plasma - Mass spectrometer (ICP-MS). The main compositions of Linggi river sediments were silt > sand > clay. The mean of total concentrations of REEs (ΣREE), light REEs (ΣLREE) and heavy REEs (ΣHREE) in Linggi sediment were 249, 228, and 22.0 mg/kg, respectively. The results of Linggi river sediment were normalised to several reference shale values. REEs of Linggi river sediments were comparable to MUQ reference shale values. Enrichment factors (EF) of mean values indicate Linggi River sediment can be categorised as having minor to moderate enrichment.
This dataset contains data from a survey of officers in correctional institutions throughout Indonesia. A total of 1284 officers completed the survey regarding their self-assessment of proactive work behavior, perceived organizational support, person-environment fit, proactive personality, and role breadth self-efficacy. In addition to raw data, this dataset presents the characteristics of respondents, a description of respondents' answers, and statistical validation of this survey data. This dataset can be reused by researchers for the evaluation of factors that encourage proactive behavior in the correctional context. In addition, this dataset can be utilized by policy makers related to human resource management in correctional institutions in Indonesia.
Data presented in this article focused on the application of Methyl Ester Sulphonate (MES) surfactant and nanopolystyrene in water based drilling fluid. Data from rheology study using Bingham and Power law models showed that the synergy of MES and nanopolystyrene improved the formulated drilling fluid. Filtration study under LPLT and HPHT conditions showed that MES and nanopolystyrene drilling fluid reduced filtration loss by 50.7% at LPLT and 61.1% at HPHT conditions. These filtration data were validated by filter cake permeability and scanning electron microscope images.
The readiness to change among drug addicts is a key strength for successful treatment. Self-awareness, self-determination, and self-efficacy have been identified as the fundamentals of readiness that should be embraced by drug addicts while in treatment. In this article, the shared data were applied to assess the effect of individual psycho-educational intervention based on integrated self-awareness and self-determination theories (i-SEAZ) on self-efficacy amongst opioid-dependent patients undergoing methadone treatment (MT). The effectiveness of the i-SEAZ module was evaluated in a total of 75 opioid-dependent MT participants from five Methadone Clinics under the Ministry of Health, Malaysia located across Klang Valley. The experimental group consisted of 38 participants who received 10 sessions of individual i-SEAZ alongside MT, whereas 37 participants of the control group only received MT. The shared data were collected through three questionnaires, namely Scale for Self-Consciousness Assessment (SSCA), Treatment Motivation Questionnaire (TMQ), and General Self Efficacy (GSE). Data collection was performed twice; the first instance was two weeks prior to initiation of i-SEAZ (pretest), and the second was two weeks post completion of i-SEAZ (posttest). The extracted data were precisely represented in terms of means and standard deviations (SDs).
Smart Grid Industry 4.0 (SGI4.0) defines a new paradigm to provide high-quality electricity at a low cost by reacting quickly and effectively to changing energy demands in the highly volatile global markets. However, in SGI4.0, the reliable and efficient gathering and transmission of the observed information from the Internet of Things (IoT)-enabled Cyber-physical systems, such as sensors located in remote places to the control center is the biggest challenge for the Industrial Multichannel Wireless Sensors Networks (IMWSNs). This is due to the harsh nature of the smart grid environment that causes high noise, signal fading, multipath effects, heat, and electromagnetic interference, which reduces the transmission quality and trigger errors in the IMWSNs. Thus, an efficient monitoring and real-time control of unexpected changes in the power generation and distribution processes is essential to guarantee the quality of service (QoS) requirements in the smart grid. In this context, this paper describes the dataset contains measurements acquired by the IMWSNs during events monitoring and control in the smart grid. This work provides an updated detail comparison of our proposed work, including channel detection, channel assignment, and packets forwarding algorithms, collectively called CARP [1] with existing G-RPL [2] and EQSHC [3] schemes in the smart grid. The experimental outcomes show that the dataset and is useful for the design, development, testing, and validation of algorithms for real-time events monitoring and control applications in the smart grid.
Blockchain-based reliable, resilient, and secure communication for Distributed Energy Resources (DERs) is essential in Smart Grid (SG). The Solana blockchain, due to its high stability, scalability, and throughput, along with low latency, is envisioned to enhance the reliability, resilience, and security of DERs in SGs. This paper presents big datasets focusing on SQL Injection, Spoofing, and Man-in-the-Middle (MitM) cyberattacks, which have been collected from Solana blockchain-based Industrial Wireless Sensor Networks (IWSNs) for events monitoring and control in DERs. The datasets provided include both raw (unprocessed) and refined (processed) data, which highlight distinct trends in cyberattacks in DERs. These distinctive patterns demonstrate problems like superfluous mass data generation, transmitting invalid packets, sending deceptive data packets, heavily using network bandwidth, rerouting, causing memory overflow, overheads, and creating high latency. These issues result in ineffective real-time events monitoring and control of DERs in SGs. The thorough nature of these datasets is expected to play a crucial role in identifying and mitigating a wide range of cyberattacks across different smart grid applications.
This data article informs about Chiropteran diversity, new records, ecosystem services and possible pathogen carriers in fragmented forests (sub-divided by utility corridors, man-made structures, untouched and secondary plantations) within districts Setiu (Setiu Research Station), Hulu Terengganu (Saok and Lasir waterfalls) and Besut (Gunung Tebu Forest Reserve) of state Terengganu, Peninsular Malaysia. These bats were captured using harp traps and mist nets that were set 10 m apart across flyways, streams and less cluttered trees in the 50 m × 50 m transect zones (identified at each site). All animals were distinguished by morphology and gender before their release at the site of capture. The data comprise of five bat family groups Hipposideridae, Megadermatidae, Pteropodidae, Rhinolophidae and Vespertilionidae. It is interesting to note that untouched Saok Waterfalls is home to wide variety of bats listed (68.8%), followed by secondary forests of Gunung Tebu Forest Reserve (24.8%), untouched Lasir Waterfalls (4.8%) and lastly, Setiu Research Station as least favored (1.6%). Chiroptera like Cynopterus brachyotis (n = 23, 37.7%), Hipposideros bicolor (n = 6, 9.8%) and Scotophilus kuhli (n = 6, 9.8%) were most dominant in the checklist whereas Hipposideros armiger, Murina suilla and Scotophilus kuhlii are new data records in the fragmented forests of Terengganu. The data were interpret into Shannon, Simpson, Margalef, Menhinik and Evenness indices to individually or collectively distinguish chiropteran variety in Terengganu State whereas weight-forearm length (W/FA) informs about chiropteran Body Condition Index (-0.25 to 0.25). The function of bats were also identified to distinguish service providers (pollination and forests regeneration) and zoonotic pathogen carriers (in particular to Leptospira bacteria, Nipah virus and Sindbis virus).
The Amomum genus comprises of perennial, tropical, herbaceous plants that are distributed globally and possess both medicinal and ornamental properties. These plants contain a variety of secondary metabolites, including compounds with antioxidant and antimicrobial properties. This is the first transcriptomic analysis of seven Amomum species from Peninsular Malaysia, utilizing leaves, stems, and roots as sample material. Paired-end Illumina HiSeq technology was used for data generation which includes raw data, cleaned reads, de novo assembly, and functional annotation. The data is accessible via NCBI BioProject (PRJNA936673).
The presentation of this data focuses on analysing the dynamic role of economic growth, foreign direct investment and financial globalization uncertainty on financial development of selected leading African economies, spanning the year 1970 to 2018, and the data were obtained from world development indicators and global financial development databases. Second generation econometrics techniques were deployed for the analysis. We began with the descriptive and correlation statistics in order to ascertain the normality of the data. Also, homogeneity and cross-sectional dependency tests were carried out to validate the whether or not the data is heterogeneous and depend upon each other across the series. As well, the [3] co-integration and dynamic common correlated effect [1] and pool mean group [2] estimates were applied to confirm the presence of long-run relationship and their effects on the financial development among the sampled countries.
This data was obtained from a cross-sectional survey of 188 final year Bachelor of Business Administration (BBA) students in a Malaysian Public University. The survey was self-administered to final year BBA students undergoing seminar course prior to the commencement of their industrial training in the coming semester. A regression analysis was conducted in order to assess the link between students' self-esteem, pro-active personality, and social support with their career adaptability using the Statistical Package of the Social Sciences (SPSS) 20. Specifically, this data article provides data about the participants' demographic characteristics, as well as the mean, standard deviation and reliability of the measured constructs. It is believed by the authors that the dataset will guide policy makers on the choice of predictor(s) that could boost the level of students' career adaptability, most especially during the school to work transition, in this current volatile labour market.
This paper presents the dataset of undergraduates learning habits during and before the occurrence of pandemic COVID-19 under the scope of sociodemographic and psychological aspects. This dataset consists of four (4) main sections which are students' demographic, psychological disruption, students' learning habits and integration of online sessions with sustainability topics. A total of 37 variables were distributed via an online survey platform. The link of the online survey was circulated to the students using few social media platforms such as WhatsApp groups, Telegram, and faculties' Facebook starting from June 1 until June 31, 2020. There was a total of 668 respondents accompanied by consent were agreed to join the survey. This dataset can have an important role for research and education in identifying the impact on learning performance among the undergraduate students during COVID-19 pandemic based on different sociodemographic and psychological aspects.