A Study on the Level of Technostress Among University Educators in Inner Mongolia,China

With the rapid development of science and technology,higher education in Inner Mongolia is ushering in unprecedented changes.Digital and intelligent educational tools provide students with a rich learning experience but also create new challenges for educators.Through a questionnaire survey of 17 universities in Inner Mongolia,this study examined the stress faced by university educators in the application of technology.The results showed that educators generally experienced technostress,and the most significant stress experienced was techno-invasion.Hence,this study recommended several strategies to assist educators in adapting to technological change and ease the technostress.

Unscented Kalman filter for a low-cost GNSS/IMU-based mobile mapping application under demanding conditions

For the last two decades,low-cost Global Navigation Satellite System(GNSS)receivers have been used in various applications.These receivers are mini-size,less expensive than geodetic-grade receivers,and in high demand.Irrespective of these outstanding features,low-cost GNSS receivers are potentially poorer hardwares with internal signal processing,resulting in lower quality.They typically come with low-cost GNSS antenna that has lower performance than their counterparts,particularly for multipath mitigation.Therefore,this research evaluated the low-cost GNSS device performance using a high-rate kinematic survey.For this purpose,these receivers were assembled with an Inertial Measurement Unit(IMU)sensor,which actively transmited data on acceleration and orientation rate during the observation.The position and navigation parameter data were obtained from the IMU readings,even without GNSS signals via the U-blox F9R GNSS/IMU device mounted on a vehicle.This research was conducted in an area with demanding conditions,such as an open sky area,an urban environment,and a shopping mall basement,to examine the device’s performance.The data were processed by two approaches:the Single Point Positioning-IMU(SPP/IMU)and the Differential GNSS-IMU(DGNSS/IMU).The Unscented Kalman Filter(UKF)was selected as a filtering algorithm due to its excellent performance in handling nonlinear system models.The result showed that integrating GNSS/IMU in SPP processing mode could increase the accuracy in eastward and northward components up to 68.28%and 66.64%.Integration of DGNSS/IMU increased the accuracy in eastward and northward components to 93.02%and 93.03%compared to the positioning of standalone GNSS.In addition,the positioning accuracy can be improved by reducing the IMU noise using low-pass and high-pass filters.This application could still not gain the expected position accuracy under signal outage conditions.

LexDeep:Hybrid Lexicon and Deep Learning Sentiment Analysis Using Twitter for Unemployment-Related Discussions During COVID-19

The COVID-19 pandemic has spread globally,resulting in financialinstability in many countries and reductions in the per capita grossdomestic product.Sentiment analysis is a cost-effective method for acquiringsentiments based on household income loss,as expressed on social media.However,limited research has been conducted in this domain using theLexDeep approach.This study aimed to explore social trend analytics usingLexDeep,which is a hybrid sentiment analysis technique,on Twitter to capturethe risk of household income loss during the COVID-19 pandemic.First,tweet data were collected using Twint with relevant keywords before(9 March2019 to 17 March 2020)and during(18 March 2020 to 21 August 2021)thepandemic.Subsequently,the tweets were annotated using VADER(lexiconbased)and fed into deep learning classifiers,and experiments were conductedusing several embeddings,namely simple embedding,Global Vectors,andWord2Vec,to classify the sentiments expressed in the tweets.The performanceof each LexDeep model was evaluated and compared with that of a supportvector machine(SVM).Finally,the unemployment rates before and duringCOVID-19 were analysed to gain insights into the differences in unemploymentpercentages through social media input and analysis.The resultsdemonstrated that all LexDeep models with simple embedding outperformedthe SVM.This confirmed the superiority of the proposed LexDeep modelover a classical machine learning classifier in performing sentiment analysistasks for domain-specific sentiments.In terms of the risk of income loss,the unemployment issue is highly politicised on both the regional and globalscales;thus,if a country cannot combat this issue,the global economy will alsobe affected.Future research should develop a utility maximisation algorithmfor household welfare evaluation,given the percentage risk of income lossowing to COVID-19.

Machine Learning and Synthetic Minority Oversampling Techniques for Imbalanced Data: Improving Machine Failure Prediction

Prediction of machine failure is challenging as the dataset is often imbalanced with a low failure rate.The common approach to han-dle classification involving imbalanced data is to balance the data using a sampling approach such as random undersampling,random oversampling,or Synthetic Minority Oversampling Technique(SMOTE)algorithms.This paper compared the classification performance of three popular classifiers(Logistic Regression,Gaussian Naïve Bayes,and Support Vector Machine)in predicting machine failure in the Oil and Gas industry.The original machine failure dataset consists of 20,473 hourly data and is imbalanced with 19945(97%)‘non-failure’and 528(3%)‘failure data’.The three independent variables to predict machine failure were pressure indicator,flow indicator,and level indicator.The accuracy of the classifiers is very high and close to 100%,but the sensitivity of all classifiers using the original dataset was close to zero.The performance of the three classifiers was then evaluated for data with different imbalance rates(10%to 50%)generated from the original data using SMOTE,SMOTE-Support Vector Machine(SMOTE-SVM)and SMOTE-Edited Nearest Neighbour(SMOTE-ENN).The classifiers were evaluated based on improvement in sensitivity and F-measure.Results showed that the sensitivity of all classifiers increases as the imbalance rate increases.SVM with radial basis function(RBF)kernel has the highest sensitivity when data is balanced(50:50)using SMOTE(Sensitivitytest=0.5686,Ftest=0.6927)compared to Naïve Bayes(Sensitivitytest=0.4033,Ftest=0.6218)and Logistic Regression(Sensitivitytest=0.4194,Ftest=0.621).Overall,the Gaussian Naïve Bayes model consistently improves sensitivity and F-measure as the imbalance ratio increases,but the sensitivity is below 50%.The classifiers performed better when data was balanced using SMOTE-SVM compared to SMOTE and SMOTE-ENN.

Characterization of Formacell Lignin Derived from Black Liquor as a Potential Green Additive for Advanced Biocomposites

Black liquor is obtained as a by-product of the pulping process,which is used to convert biomass into pulp by removing lignin,hemicelluloses and other extractives from wood to free cellulose fibers.Lignin represents a major constituent in black liquor,with quantities varying from 20%to 30%,of which a very low share is used for manufacturing value-added products,while the rest is mainly burned for energy purposes,thus underestimating its great potential as a raw material.Therefore,it is essential to establish new isolation and extraction methods to increase lignin valorization in the development of bio-based chemicals.The aim of this research work was to determine the effect of KOH or ethanol concentration as an isolation agent on lignin yields and the chemical characteristics of lignin isolated from formacell black liquor of oil palm empty fruit bunch(OPEFB).Isolation of lignin was carried out using KOH with various concentrations ranging from 5%to 15%(w/v).Ethanol was also used to precipitate lignin from black liquor at concentrations varying from 5%to 30%(v/v).The results obtained showed that the addition of KOH solution at 12.5%and 15%concentrations resulted in better lignin yield and chemical properties of lignin,i.e.,pH values of 3.86 and 4.27,lignin yield of 12.78%and 14.95%,methoxyl content of 11.33%and 10.13%,and lignin equivalent weights of 476.25 and 427.03,respectively.Due to its phenolic structure and rich functional groups that are favorable for modifications,lignin has the potential to be used as a green additive in the development of advanced biocomposite products in various applications to replace current fossil fuel-based material,ranging from fillers,fire retardants,formaldehyde scavengers,carbon fibers,aerogels,and wood adhesives.

Energy Emissions Profile and Floating Solar Mitigation Potential for a Malaysia’s State

The establishment of the National Low Carbon City Master Plan(NLCCM)by Malaysia’s government presents a significant opportunity to minimize carbon emissions at the subnational or local scales,while simultaneously fostering remarkable economic potential.However,the lack of data management and understanding of emissions at the subnational level are hindering effective climate policies and planning to achieve the nationally determined contribution and carbon neutrality goal.There is an urgent need for a subnational emission inventory to understand and manage subnational emissions,particularly that of the energy sector which contribute the biggest to Malaysia’s emission.This research aims to estimate carbon emissions for Selangor state in accordance with the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories(GPC),for stationary energy activities.The study also evaluates the mitigation potential of Floating Solar Photovoltaic(FSPV)proposed for Selangor.It was found that the total stationary energy emission for Selangor for the year 2019 was 18,070.16 ktCO2e,contributed the most by the Manufacturing sub-sector(40%),followed by the Commercial and Institutional sub-sector;with 82%contribution coming from the Scope 2 emission.The highest sub-sector of Scope 1 emissions was contributed by Manufacturing while Scope 2 emissions from the Commercial and Institutional.Additionally,the highest fuel consumed was natural gas,which amounted to 1404.32 ktCO2e(44%)of total emissions.The FSPV assessment showed the potential generation of 2.213 TWh per year,by only utilizing 10%of the identified available ponds and dams in Selangor,equivalent to an emission reduction of 1726.02 ktCO2e,offsetting 11.6%Scope 2 electricity emission.The results from the study can be used to better evaluate existing policies at the sub-national level,discover mitigation opportunities,and guide the creation of future policies.

Spatial and Temporal Variation of Particulate Matter (PM10 and PM2.5) and Its Health Effects during the Haze Event in Malaysia

This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.

Mechanism of antagonistic effects of Andrographis paniculata methanolic extract against Staphylococcus aureus

Objective: To investigate the effects of Andrographis paniculata(Burm.f.) Wall. Ex Nees(A. paniculata) on expressions and activities of catalase, superoxide dismutase and alkylhydroperoxide reductase C in Staphylococcus aureus(S. aureus) with respect to its survival in vitro. Methods: Antioxidative property of methanolic leaves extract of A. paniculata(0.06 mg/m L). Minimum inhibitory concentration(MIC) was determined by its ability to reduce hydrogen peroxide(H_2O_2) toxicity against S. aureus ATCC 25923(3.8×10~8 cfu/m L). Effects of the extract on expressions of kat A(encoding catalase), sod A and sod M [encoding superoxide dismutases(SODs)], and ahp C [encoding alkylhydroperoxide reductase C(AhpC)] in S. aureuswere determined by RT-q PCR and corresponding enzyme activity assays were performed. Nitroblue tetrazolium reduction(NBT) assay was performed to determine effects of the extract on intracellular and extracellular levels of O_2-in S. aureus. Results: Cells challenged with 7.5 mmol/L H_2O_2 showed 0% survival in 30 min whereas 25% survived after treatment with the extract and H_2O_2. Cells that were treated with the extract alone had 43% survival in the same exposure period. Expressions of sod A and sod M genes in extract-treated cells were lowered 0.8-fold and 0.7-fold, respectively with decrease in total SOD activity of 26.8 U compared to untreated cells, 32.4 U(P<0.05). In contrast, extract-treated S. aureus cells showed 3.3-fold increase in kat A expression with corresponding increase in catalase activity of 1.828 U compared to untreated cells which was 1.248 U,(P<0.05). More profoundly, ahp C expression was increased 61-fold in extract-treated cells,(P<0.05) with corresponding increase in Ahp C activity of 0.018 U compared to untreated cells, 0.012U,(P<0.05). Extract-treated cells had significantly lower intra-and extracellular O_2-levels with absorbance readings(A_(575nm)) of 0.340 and 0.524 compared to untreated cells which were 0.516 and 0.928(P<0.05), respectively. Conclusions: Taken together these results suggest that the low MIC of A. paniculatamethanolic leaves extract(0.06 mg/m L) reduce H_2O_2 toxicity and more importantly, was in itself effectively inhibitory against S. aureus. Further, our observations suggest that a probable mode of its inhibitory mechanism against S. aureus is by reducing total SOD activity through downregulation of sod A and sod M expressions.

Antimicrobial effect of Malaysian vegetables against enteric bacteria

Objective: To investigate the antibacterial activities of green vegetables(pennywort,mint, garlic, parsley and celery) against four common enteric bacteria [Salmonella enterica(ATCC 25957)(S. enterica), Shigella flexneri(ATCC 12022)(S. flexneri),Escherichia coli(ATCC 43889)(E. coli) and Enterobacter cloacae(ATCC 13047)(E. cloacae)] as an alternative medicine for controlling food borne diarrhea disease and the synergistic effect of green vegetables against those bacteria.Methods: Five common vegetables(pennywort, mint, garlic, parsley and celery) were purchased and extracted. The antimicrobial activities of these extracts were tested against four common enteric bacteria(S. enterica, S. flexneri, E. coli and E. cloacae). Ten different concentrations of the extracts(from 640 to 1.25 mg/m L) were prepared and used for the study. The minimal inhibitory concentration(MIC) was determined by the broth dilution method. The antimicrobial activities were assessed by using both well diffusion and disc diffusion methods.Results: Garlic extract showed excellent inhibitory effects on all enteric bacteria. Other plants(parsley, celery, mint and pennywort) were not effective against enteric bacteria.The MIC of garlic against S. flexneri and E. cloacae was 40 mg/m L. The MIC of S. enterica and E. coli were 20 and 10 mg/m L, respectively. The performance of the well diffusion method was better than that of the disc diffusion method with clear and sharp inhibition zones of tested bacteria against plant extracts.Conclusions: Garlic had excellent antimicrobial effects against enteric bacteria and was recommended to be given to patients with gastroenteritis. The other vegetables(pennywort, mint, parsley and celery) showed no inhibitory effects on enteric bacteria but still can be used for its richness in vitamins and fibers. The performance of the well diffusion method was better than that of the disc diffusion method in detecting the antibacterial effects of green vegetables.

New modular platform based on multi-adjuvanted amphiphilic chitosan nanoparticles for efficient lipopeptide vaccine delivery against group A streptococcus

An effective vaccine against group A streptococcus(GAS)is highly desirable for definitive control of GAS infections.In the present study,two variants of amphiphilic chitosan nanoparticles-based GAS vaccines were developed.The vaccines were primarily composed of encapsulated KLH protein(a source of T helper cell epitopes)and lipidated M-protein derived B cell peptide epitope(lipoJ14)within the amphiphilic structure of nanoparticles.The only difference between themwas one of the nanoparticles vaccines received additional surface coating with poly(I:C).The formulated vaccines exhibited nanosized particles within the range of 220–240 nm.Cellular uptake study showed that nanoparticles vaccine without additional poly(I:C)coating has greater uptake by dendritic cells and macrophages compared to nanoparticles vaccine that was functionalized with poly(I:C).Both vaccines were found to be safe in mice and showed negligible cytotoxicity against HEK293 cells.Upon immunization in mice,both nanoparticle vaccines produced high antigen-specific antibodies titres that were regulated by a balanced Th1 and Th2 response compared to physical mixture.These antibodies elicited high opsonic activity against the tested GAS strains.Overall,our data demonstrated that amphiphilic chitosan nanoparticles platform induced a potent immune response even without additional inclusion of poly(I:C).

Strength Performance and Microstructure Characteristic of Naturally-Bonded Fiberboard Composite from Malaysian Bamboo(Bambusa vulgaris)

This study investigated the mechanical properties and microstructural characteristics of fiberboard composite produced by naturally-bonded Malaysian bamboo fiber(Bambusa vulgaris).The components that obtained through soda pulping of bamboo culms such as fiber and black liquor,were used for the preparation of high-density fibreboard composite at two target densities of 850 and 950 kg/m^(3).The bamboo fiberboard composite(BFC)were then produced at 200°C and two pressing parameters of 125 and 175 s/mm.The mechanical properties,e.g.,flexural strength and internal bonding(IB)of BFC samples were evaluated according to BS EN 310:1993 and BS EN 319:1993,respectively.It was found that the mechanical performance of the composite with 850 kg/m^(3)density was significantly higher than 950 kg/m^(3)ones,especially for the samples with 125 s/mm pressing parameter.Microstructure characteristic of the BFC samples illustrated that the fiber linkages were cracked in the composites with higher density,e.g.,the composite with the density of 950 kg/m^(3)and also black liquor were slightly degraded at longer pressing time,which led to the reduction in mechanical properties,especially in IB strength.

On the nonclassical dynamics of cavity-assisted four-channel nonlinear coupler

The non-classical properties of light propagating in four-channel Kerr waveguides, confined in an optical cavity, are studied. The solution to the Hamiltonian of field operators is obtained semi-analytically by using symmetrically ordered phase-space representation. Full quantum analysis of the input coherent fields displays a strong transition of photon property between the super-Poissonian and sub-Poissonian statistics. It is found that the cavity-assisted multichannel system exhibits enhanced squeezing both in single-and compound-mode. This multichannel system may be utilized as an efficient quantumlight generator.

MELex: The Construction of Malay-English Sentiment Lexicon

Currently,the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon.Thus,this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis.In this study,a new lexicon for sentiment analysis is constructed.A detailed review of existing approaches has been conducted,and a new bilingual sentiment lexicon known as MELex(Malay-English Lexicon)has been generated.Constructing MELex involves three activities:seed words selection,polarity assignment,and synonym expansions.Our approach differs from previous works in that MELex can analyze text for the two most widely used languages in Malaysia,Malay,and English,with the accuracy achieved,is 90%.It is evaluated based on the experimentation and case study approaches where the affordable housing projects in Malaysia are selected as case projects.This finding has given an implication on the ability of MELex to analyze public sentiments in the Malaysian context.The novel aspects of this paper are two-fold.Firstly,it introduces the new technique in assigning the polarity score,and second,it improves the performance over the classification of mixed language content.

Nanosecond Pulse Generation Using the Stimulated Brillouin Scattering Effect in a Photonic Crystal Fiber

A nanosecond pulsed laser is demonstrated using the stimulated Brillouin scattering(SBS)effect in a nonlinear photonic crystal fiber(PCF).The Brillouin fiber laser(BFL)uses a 50-m-long PCF in a simple ring cavity to generate a self-starting pulse as the Brillouin power reaches 16.5 dBm based on the relaxation oscillation technique.The BFL generates a pulse train with repetition rates of 2.7 MHz and 5.4 MHz depending on the BP power.The pulse width of the laser is obtained to be 190 ns at the BP power of 16.5 dBm and is maintained at around 72 ns as the pump power is set within 17.7 dBm and 18.5 dBm.The maximum pulse energy of 20 nJ is obtained at BP power of 17.4 dBm.This SBS based pulse laser is fairly stable at room temperature.

Effects of Planting Density of Rubber Tree Clone(RRIM 2020 Clone and RRIM 2025 Clone)Wood to Particleboard Properties

The depletion of log resources encourages research into alternative ways to sustain the wood supply.Therefore,the 4-year-old Rubber Research Institute of Malaysia(RRIM)clones series,RRIM 2020 and RRIM 2025,were chosen as potential raw materials for particleboard in this study.The purpose of this study was to assess the effects of planting density and rubber tree clones on the mechanical and physical properties of single-layer particleboard.The planting densities used were low,moderate-low,moderate-high,and high,representing 500,1000,1500,and 2000 trees/ha,respectively.Prior to manufacturing,the RRIM 2000 series clone trees were harvested,cut,chipped,flaked,and screened.The mechanical and physical properties were evaluated in accordance with the Japanese Industrial Standard(JIS A 5908-2003).The findings revealed that both planting density and clone had a significant impact on the mechanical and physical properties of particleboard with a thickness of 10 mm and a density of 700 kg/m3.RRIM 2020 specimens with low planting density had superior modulus of elasticity(MOE),modulus of rupture(MOR),and internal bonding(IB)values of 2415,19,and 1.7 MPa,respectively.Furthermore,moderate-low planting density demonstrated the lowest thickness swelling(TS)and water absorption(WA)values and was comparable to control particleboard from commercial clone Prang Besar(PB),PB260.In terms of rubber clones,RRIM 2020 particleboard met the minimum requirements of the JIS standard for mechanical properties and outperformed RRIM 2025.This study recommended a low planting density of 500 trees/ha and the RRIM 2020 clone as a suitable raw material for particleboard manufacturing with a ten percent urea formaldehyde resin content.

Prediction of Whitefly Population and Infestation Based on Multitrophic Analysis between Competitor Pest,Plant Traits and Natural Enemy

Interaction among arthropods(insect-acarine)was investigated at all trophic levels in agro-ecosystem and affects the population dynamic and diversification of arthropod pests and intensity of natural enemy(parasitism)as well as stimulates the plant chemical defence.In the present study of two cropping periods,nutrient concentration and early infestation of plant-sucking pests are known to trigger different degrees of interactions(plant’s parameters)which potentially alert abundance and diversity of the insect pests.Clearer interaction and magnitude of impact could be assessed(multivariate analysis of variance(MANOVA)and redundancy analysis(RDA))and observed between arthropods(insect-acarine)community and plants’parameters from the strongest to the lowest effects.The two factors could have affected the community of insect-pests with various degrees of pressure effect and interaction that occurred naturally,thus leading to the predictable abundance of insect-acarine populations under eggplant leaves in response to plant physical characteristics(e.g.,size of leaves,number of leaves and plant height)and biochemical constituents(flavonoid,phenolic,peroxidase andβ-1,3-glucanase).Based on multivariate analyses of multitrophic interaction,MANOVA and RDA have the potential to elucidate the complex interaction among plant performance,abundance of pests and activity chemical defence compounds.Both analyses interpreted similar interactions of measured parameters in different ways.Whitefly population in this study was predictable by aphids,thrips and total phenolic contents in eggplant.Eggplant has capable defence systems against insect-acarine pests after stimulation(pre-infestation).In relation to IPM strategy,early stages of plant growth are known as susceptible periods for pests attack but the plant becomes more tolerant during the fruiting stage.