Remote Sensing - based precision agriculture tool for the sugar industry

This project aimed to develop remote sensing applications that were both relevant and of commercial benefit to the Australian sugar industry and therefore adoptable. Such applications included the in season mapping of crop vigour so as to guide future management strategies, the identification of specific abiotic and biotic cropping constraints, and the conversion of GNDVI variability maps into yield at the block, farm and regional level. In order to achieve these applications the project team reviewed an array of remote sensing platforms, timing of imagery capture, software and analysis protocols; as well as distribution formats of derived imagery products, to a range of end users. The project developed strong collaborative linkages with all levels of the industry including mills, productivity services, agronomists, growers and researchers and increased its initial coverage from three individual farms in Bundaberg, Burdekin and the Herbert, coinciding with project CSE022, to include over 33,000 crops grown across 6 growing regions (Mulgrave, Herbert, Burdekin, Bundaberg, ISIS and Condong) during the 2011/2012 season

Remote Sensing - based precision agriculture tool for the sugar industry

This project aimed to develop remote sensing applications that were both relevant and of commercial benefit to the Australian sugar industry and therefore adoptable. Such applications included the in season mapping of crop vigour so as to guide future management strategies, the identification of specific abiotic and biotic cropping constraints, and the conversion of GNDVI variability maps into yield at the block, farm and regional level. In order to achieve these applications the project team reviewed an array of remote sensing platforms, timing of imagery capture, software and analysis protocols; as well as distribution formats of derived imagery products, to a range of end users. The project developed strong collaborative linkages with all levels of the industry including mills, productivity services, agronomists, growers and researchers and increased its initial coverage from three individual farms in Bundaberg, Burdekin and the Herbert, coinciding with project CSE022, to include over 33,000 crops grown across 6 growing regions (Mulgrave, Herbert, Burdekin, Bundaberg, ISIS and Condong) during the 2011/2012 season

Predicting students’ academic performance using e-learning logs

The outbreak of coronavirus disease 2019 (COVID-19) drives most higher education systems in many countries to stop face-to-face learning. Accordingly, many universities, including Jordan University of Science and Technology (JUST), changed the teaching method from face-to-face education to electronic learning from a distance. This research paper investigated the impact of the e-learning experience on the students during the spring semester of 2020 at JUST. It also explored how to predict students’ academic performances using e-learning data. Consequently, we collected students’ datasets from two resources: the center for e-learning and open educational resources and the admission and registration unit at the university. Five courses in the spring semester of 2020 were targeted. In addition, four regression machine learning algorithms had been used in this study to generate the predictions: random forest (RF), Bayesian ridge (BR), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost). The results showed that the ensemble model for RF and XGBoost yielded the best performance. Finally, it is worth mentioning that among all the e-learning components and events, quiz events had a significant impact on predicting the student’s academic performance. Moreover, the paper shows that the activities between weeks 9 and 12 influenced students’ performances during the semester

Combating propaganda texts using transfer learning

Recently, it has been observed that people are shifting away from traditional news media sources towards trusting social networks to gather news information. Social networks have become the primary news source, although the validity and reliability of the information provided are uncertain. Memes are crucial content types that are very popular among young people and play a vital role in social media. It spreads quickly and continues to spread rapidly among people in a peer-to-peer manner rather than a prescriptive. Unfortunately, promoters and propagandists have adopted memes to indirectly manipulate public opinion and influence their attitudes using psychological and rhetorical techniques. This type of content could lead to unpleasant consequences in communities. This paper introduces an ensemble model system that resolves one of the most recent natural language processing research topics; propaganda techniques detection in texts extracted from memes. The paper also explores state-of-the-art pretrained language models. The proposed model also uses different optimization techniques, such as data augmentation and model ensemble. It has been evaluated using a reference dataset from SemEval-2021 task 6. Our system outperforms the baseline and state-of-the-art results by achieving an F1-micro score of 0.604% on the test set

Potential Dependence of Surfactant Adsorption at the Graphite Electrode / Deep Eutectic Solvent Interface

Atomic force microscope (AFM) and cyclic voltammetry (CV) are used to probe how ionic surfactant adsorbed layer structure affects redox processes at deep eutectic solvent (DES)/graphite interfaces. Unlike its behaviour in water, sodium dodecyl sulphate (SDS) in DESs only adsorbs as a complete layer of hemicylindrical hemimicelles far above its critical micelle concentration (CMC). Near the CMC it forms a tail-to-tail monolayer at OCP and positive potentials, and which desorbs at negative potentials. In contrast, cetyltrimethylammonium bromide (CTAB) adsorbs as hemimicelles at low concentrations, and remains adsorbed at both positive and negative potentials. The SDS horizontal monolayer has little overall effect on redox processes at the graphite interface, but hemimicelles form an effective and stable barrier. The stronger solvophobic interactions between the C16 versus C12 alkyl chains in the DES allow CTAB to self-assemble into a robust coating at low concentrations, and illustrate how the structure of the DES/electrode interface and electrochemical response can be engineered by controlling surfactant structure

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Society for Endocrinology (SfE) guidelines for the diagnosis and management of post bariatric hypoglycaemia

Post bariatric hypoglycaemia (PBH) is typically a post-prandial hypoglycaemia occurring about 2-4 hours after eating in people who have undergone bariatric surgery. PBH develops relatively late after surgery and often after discharge from post-surgical follow-up by bariatric teams, leading to variability in diagnosis and management in non-specialist centres. AIM: to improve and standardise clinical practice in the diagnosis and management of PBH. OBJECTIVES: (1) to undertake an up-to-date review of the current literature; (2) to formulate practical and evidence-based guidance with regards on the diagnosis and treatment of PBH; (3) to recommend future avenues for research in this condition. METHOD: A scoping review was undertaken after an extensive literature search. A consensus on the guidance and confidence in the recommendations was reached by the steering group authors prior to review by key stakeholders. OUTCOME: We make pragmatic recommendations for the practical diagnosis and management of PBH including criteria for diagnosis and recognition, as well as recommendations for research areas that should be explored

Antimicrobials: a global alliance for optimizing their rational use in intra-abdominal infections (AGORA)

Intra-abdominal infections (IAI) are an important cause of morbidity and are frequently associated with poor prognosis, particularly in high-risk patients. The cornerstones in the management of complicated IAIs are timely effective source control with appropriate antimicrobial therapy. Empiric antimicrobial therapy is important in the management of intra-abdominal infections and must be broad enough to cover all likely organisms because inappropriate initial antimicrobial therapy is associated with poor patient outcomes and the development of bacterial resistance. The overuse of antimicrobials is widely accepted as a major driver of some emerging infections (such as C. difficile), the selection of resistant pathogens in individual patients, and for the continued development of antimicrobial resistance globally. The growing emergence of multi-drug resistant organisms and the limited development of new agents available to counteract them have caused an impending crisis with alarming implications, especially with regards to Gram-negative bacteria. An international task force from 79 different countries has joined this project by sharing a document on the rational use of antimicrobials for patients with IAIs. The project has been termed AGORA (Antimicrobials: A Global Alliance for Optimizing their Rational Use in Intra-Abdominal Infections). The authors hope that AGORA, involving many of the world's leading experts, can actively raise awareness in health workers and can improve prescribing behavior in treating IAIs