Artificial intelligent based teaching and learning approaches: A comprehensive review

The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates

Stakeholder Delphi-perception analysis on impacts and responses of acid rain on agricultural ecosystems in the Vietnamese upland

Vietnam is one of most vulnerable countries to acid rain in Asia. In the Vietnamese Northern Mountains, acid rainwater affects negatively to local agricultural ecosystems. This paper analyzes how major agricultural stakeholders living in the mountains assess the impacts of acid rain and their responses on agricultural ecosystems. A two-round Stakeholder Delphi combined with the pressure-state-response (PSR) model allows ranking effects, mitigation and adaptation measures. Eight themes, 14 sub-themes, and 35 indicators for acid rain are structured in the PSR model. The results show that deforestation and rainfall variability relate to changes in the concentrations of acid ions in rainwater. Energy consumption in the industry and transportation, chemical fertilizer use in agriculture, and air pollution from neighboring areas contribute significantly to acid rain. Acid rain affects agriculture and decreases crop yields, causes arable land loss, reduces nutrients and organic matter, and accumulates heavy metals. Panel members perceive that applying local knowledge in agricultural practices, rational energy use, promotion of integrated agricultural policies, and changing farmer behaviors are measures to mitigate acid rain and its adverse effects. The results contribute to a vision on local adaptation actions and policy to foster the capacity and the resilience of major local group

The Relationship between Uterine, Fecal, Bedding, and Airborne Dust Microbiota from Dairy Cows and Their Environment: A Pilot Study

Simple Summary After calving, dairy cows face the risk of negative energy balance, inflammation, and immunosuppression, which may result in bacterial infection and disruption of the normal microbiota, thus encouraging the development of metritis and endometritis. This study characterized uterine, fecal, bedding, and airborne dust microbiota from postpartum dairy cows and their environment during summer and winter. The results clarify the importance of microbiota in cowshed environments, i.e., bedding and airborne dust, in understanding the postpartum uterine microbiota of dairy cows. Abstract The aim of this study was to characterize uterine, fecal, bedding, and airborne dust microbiota from postpartum dairy cows and their environment. The cows were managed by the free-stall housing system, and samples for microbiota and serum metabolite assessment were collected during summer and winter when the cows were at one and two months postpartum. Uterine microbiota varied between seasons; the five most prevalent taxa were Enterobacteriaceae, Moraxellaceae, Ruminococcaceae, Staphylococcaceae, and Lactobacillaceae during summer, and Ruminococcaceae, Lachnospiraceae, Bacteroidaceae, Moraxellaceae, and Clostridiaceae during winter. Although Actinomycetaceae and Mycoplasmataceae were detected at high abundance in several uterine samples, the relationship between the uterine microbiota and serum metabolite concentrations was unclear. The fecal microbiota was stable regardless of the season, whereas bedding and airborne dust microbiota varied between summer and winter. With regards to uterine, bedding, and airborne dust microbiota, Enterobacteriaceae, Moraxellaceae, Staphylococcaceae, and Lactobacillaceae were more abundant during summer, and Ruminococcaceae, Lachnospiraceae, Bacteroidaceae, and Clostridiaceae were more abundant during winter. Canonical analysis of principal coordinates confirmed the relationship between uterine and cowshed microbiota. These results indicated that the uterine microbiota may vary when the microbiota in cowshed environments changes

Indoor PM₀.₁ and PM₂.₅ in Hanoi: Chemical characterization, source identification, and health risk assessment

This study attempted to provide comprehensive insights into the chemical composition, source identification, and health risk assessment of indoor particulate matter (PM) in urban areas of Vietnam. Three hundred and twenty daily samples of PM₀.₁ and PM₂.₅ were collected at three different types of dwellings in Hanoi in two seasons, namely summer and winter. The samples were analyzed for 10 trace elements (TEs), namely Cr, Mn, Co, Cu, Ni, Zn, As, Cd, Sn, and Pb. The daily average concentrations of indoor PM₀.₁ and PM₂.₅ in the city were in the ranges of 7.0–8.9 μg/m³ and 43.3–106 μg/m³, respectively. The average concentrations of TEs bound to indoor PM ranged from 66.2 ng/m³ to 216 ng/m³ for PM₀.₁ and 391 ng/m³ to 2360 ng/m³ for PM₂.₅. Principle component analysis and enrichment factor were applied to identify the possible sources of indoor PM. Results showed that indoor PM₂.₅ was mainly derived from outdoor sources, whereas indoor PM₀.₁ was derived from indoor and outdoor sources. Domestic coal burning, industrial and traffic emissions were observed as outdoor sources, whereas household dust and indoor combustion were found as indoor sources. 80% of PM₂.₅ was deposited in the head airways, whereas 75% of PM₀.₁ was deposited in alveolar region. Monte Carlo simulation indicated that the intake of TEs in PM₂.₅ can lead to high carcinogenic risk for people over 60 years old and unacceptable non-carcinogenic risks for all ages at the roadside house in winter

Mycotoxin production of Alternaria strains isolated from Korean barley grains determined by LC-MS/MS

Twenty-four Alternaria strains were isolated from barley grain samples. These strains were screened for the production of mycotoxins on rice medium using thin layer chromatography. All 24 strains produced at least one of the five mycotoxins (ALT, AOH, ATX-I, AME, and TeA). Three representative strains, namely EML-BLDF1-4, EML-BLDF1-14, and EML-BLDF1-18, were further analyzed using a new LC–MS/MS-based mycotoxin quantification method. This method was used to detect and quantify Alternaria mycotoxins. We used positive ion electrospray mass spectrometry with multiple reaction mode (MRM) for the simultaneous quantification of various Alternaria mycotoxins produced by these strains. Five Alternaria toxins (ALT, ATX-I, AOH, AME, and TeA) were detected and quantified. Sample preparation included methanol extraction, concentration, and injection into LC–MS/MS. Limit of detection ranged from 0.13 to 4 μg/mL and limit of quantification ranged from 0.25 to 8 μg/mL

SOME REMARKS ON THE LOGARITHMIC SIGNATURES OF FINITE ABELIAN GROUPS

In the paper about the cryptosystem MST3, Svaba and Trung pro- posed a way to build a cryptosystem based on the concept of logarithmic signa- tures, and they choose Suzuki\u27s group, which is not abelian for implementing. Recently, to reason why these methods cannot be applied to abelian groups; Sv- aba, Trung and Wolf developed some algorithms to factorize the fused transver- sal logarithmic signatures (FTLS). Their attacks can be avoided by some mod- ications, which is the aim of this paper, where we will use the weakness of the discrete logarithm problem (DLP) to propose two cryptosystems. The rst one is based on the new concept about quasi-logarithmic signature of nite solvable groups, which is the generalization of logarithmic signatures. The second is built on the logarithmic signatures of nite cyclic 2-groups, which include two interesting examples on Pell\u27s curves and elliptic curves over nite elds

Sources of Multidrug Resistance in Patients With Previous Isoniazid-Resistant Tuberculosis Identified Using Whole Genome Sequencing: A Longitudinal Cohort Study

Background Meta-analysis of patients with isoniazid-resistant tuberculosis given standard first-line anti-tuberculosis treatment indicated an increased risk of multi-drug resistant tuberculosis (MDR-TB) emerging (8%), compared to drug-sensitive tuberculosis (0.3%). Here we use whole genome sequencing (WGS) to investigate whether treatment of patients with pre-existing isoniazid resistant disease with first-line anti-tuberculosis therapy risks selecting for rifampicin resistance, and hence MDR-TB. Methods Patients with isoniazid-resistant pulmonary TB were recruited and followed up for 24 months. Drug-susceptibility testing was performed by Microscopic observation drug-susceptibility assay (MODS), Mycobacterial Growth Indicator Tube (MGIT) and by WGS on isolates at first presentation and in the case of re-presentation. Where MDR-TB was diagnosed, WGS was used to determine the genomic relatedness between initial and subsequent isolates. De novo emergence of MDR-TB was assumed where the genomic distance was five or fewer single nucleotide polymorphisms (SNPs) whereas reinfection with a different MDR-TB strain was assumed where the distance was 10 or more SNPs. Results 239 patients with isoniazid-resistant pulmonary tuberculosis were recruited. Fourteen (14/239, 5.9%) patients were diagnosed with a second episode of tuberculosis that was multi-drug resistant. Six (6/239, 2.5%) were identified as having evolved MDR-TB de novo and six as having been re-infected with a different strain. In two cases the genomic distance was between 5-10 SNPs and therefore indeterminate. Conclusions In isoniazid-resistant TB, de novo emergence and reinfection of MDR-TB strains equally contributed to MDR development. Early diagnosis and optimal treatment of isoniazid resistant TB are urgently needed to avert the de novo emergence of MDR-TB during treatment

Petunia × hybrida floral scent production is negatively affected by high‐temperature growth conditions

Increasing temperatures due to changing global climate are interfering with plant–pollinator mutualism, an interaction facilitated mainly by floral colour and scent. Gas chromatography–mass spectroscopy analyses revealed that increasing ambient temperature leads to a decrease in phenylpropanoid‐based floral scent production in two Petunia × hybrida varieties, P720 and Blue Spark, acclimated at 22/16 or 28/22 °C (day/night). This decrease could be attributed to down‐regulation of scent‐related structural gene expression from both phenylpropanoid and shikimate pathways, and up‐regulation of a negative regulator of scent production, emission of benzenoids V (EOBV). To test whether the negative effect of increased temperature on scent production can be reduced in flowers with enhanced metabolic flow in the phenylpropanoid pathway, we analysed floral volatile production by transgenic ‘Blue Spark’ plants overexpressing CaMV 35S‐driven Arabidopsis thaliana production of anthocyanin pigments 1 (PAP1) under elevated versus standard temperature conditions. Flowers of 35S:PAP1 transgenic plants produced the same or even higher levels of volatiles when exposed to a long‐term high‐temperature regime. This phenotype was also evident when analysing relevant gene expression as inferred from sequencing the transcriptome of 35S:PAP1 transgenic flowers under the two temperature regimes. Thus, up‐regulation of transcription might negate the adverse effects of temperature on scent production.We demonstrate that petunia flowers produce less volatile phenylpropanoid compounds, in both scent bouquets and internal pools, in response to elevated temperatures. We reveal that the decrease in floral scent is correlated with reduced transcript levels of scent‐related genes, and that the adverse effect of high temperature can be negated by expressing transcriptional up‐regulators. We believe that the conclusions and implications drawn from the original data presented in our manuscript will be of particular interest to a broad spectrum of your readers, particularly in view of recent changes in global climate and the risk of environmental disruption of plant–pollinator mutualism.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112003/1/pce12486-sup-0001-si.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/112003/2/pce12486.pd