Assessment of consumer VR-headsets’ objective and subjective field of view (FoV) and its feasibility for visual field testing

Virtual reality as a research environment has seen a boost in its popularity during the last decades. Not only the usage fields for this technology have broadened, but also a research niche has appeared as the hardware improved and became more affordable. Experiments in vision research are constructed upon the basis of accurately displaying stimuli with a specific position and size. For classical screen setups, viewing distance and pixel position on the screen define the perceived position for subjects in a relatively precise fashion. However, projection fidelity in HMDs strongly depends on eye and face physiological parameters. This study introduces an inexpensive method to measure the perceived field of view and its dependence upon the eye position and the interpupillary distance, using a super wide angle camera. Measurements of multiple consumer VR headsets show that manufacturers’ claims regarding field of view of their HMDs are mostly unrealistic. Additionally, we performed a “Goldmann” perimetry test in VR to obtain subjective results as a validation of the objective camera measurements. Based on this novel data, the applicability of these devices to test humans’ field of view was evaluated.

Dynamics of Semiconductor Lasers under External Optical Feedback from Both Sides of the Laser Cavity

To increase the spectral efficiency of coherent communication systems, lasers with ever-narrower linewidths are required as they enable higher-order modulation formats with lower bit-error rates. In particular, semiconductor lasers are a key component due to their compactness, low power consumption, and potential for mass production. In field-testing scenarios their output is coupled to a fiber, making them susceptible to external optical feedback (EOF). This has a detrimental effect on its stability, thus it is traditionally countered by employing, for example, optical isolators and angled output waveguides. In this work, EOF is explored in a novel way with the aim to reduce and stabilize the laser linewidth. EOF has been traditionally studied in the case where it is applied to only one side of the laser cavity. In contrast, this work gives a generalization to the case of feedback on both sides. It is implemented using photonic components available via generic foundry platforms, thus creating a path towards devices with high technology-readiness level. Numerical results shows an improvement in performance of the double-feedback case with respect to the single-feedback case. In particularly, by appropriately selecting the phase of the feedback from both sides, a broad stability regime is discovered. This work paves the way towards low-cost, integrated and stable narrow-linewidth integrated lasers.

Response to Early Generation Genomic Selection for Yield in Wheat

We investigated increasing genetic gain for grain yield using early generation genomic selection (GS). A training set of 1,334 elite wheat breeding lines tested over three field seasons was used to generate Genomic Estimated Breeding Values (GEBVs) for grain yield under irrigated conditions applying markers and three different prediction methods: (1) Genomic Best Linear Unbiased Predictor (GBLUP), (2) GBLUP with the imputation of missing genotypic data by Ridge Regression BLUP (rrGBLUP_imp), and (3) Reproducing Kernel Hilbert Space (RKHS) a.k.a. Gaussian Kernel (GK). F2 GEBVs were generated for 1,924 individuals from 38 biparental cross populations between 21 parents selected from the training set. Results showed that F2 GEBVs from the different methods were not correlated. Experiment 1 consisted of selecting F2s with the highest average GEBVs and advancing them to form genomically selected bulks and make intercross populations aiming to combine favorable alleles for yield. F4:6 lines were derived from genomically selected bulks, intercrosses, and conventional breeding methods with similar numbers from each. Results of field-testing for Experiment 1 did not find any difference in yield with genomic compared to conventional selection. Experiment 2 compared the predictive ability of the different GEBV calculation methods in F2 using a set of single plant-derived F2:4 lines from randomly selected F2 plants. Grain yield results from Experiment 2 showed a significant positive correlation between observed yields of F2:4 lines and predicted yield GEBVs of F2 single plants from GK (the predictive ability of 0.248, P < 0.001) and GBLUP (0.195, P < 0.01) but no correlation with rrGBLUP_imp. Results demonstrate the potential for the application of GS in early generations of wheat breeding and the importance of using the appropriate statistical model for GEBV calculation, which may not be the same as the best model for inbreds.

Biocontrol of Anthracnose Disease on Chili Pepper Using a Formulation Containing Paenibacillus polymyxa C1

Anthracnose disease on chili pepper has been known to seriously interfere with the plant growth and obviously reduce the yield. The disease is caused by Colletotrichum spp. In Bali, Indonesia, six species of Colletotrichum have been identified: Colletotrichum scovillei, C. acutatum, C. nymphaeae, C. gloeosporioides, C. truncatum, and C. fructicola. However, among them the C. scovillei was found to be the most prevalent cause of anthracnose on chili pepper in Bali. Two species of antagonist against C. scovillei, namely Paenibacillus polymyxa C1 and Bacillus siamensis C7B, have been identified. In this study the effectiveness of P. polymyxa C1 formulation was evaluated under greenhouse condition on chili pepper cultivars Cabe Besar. Application of formulation was conducted by a mini hand sprayer once to five times with a week interval. Results of the study showed that treatment with five applications significantly (p < 0.05) reduced the disease incidence, disease intensity, and the yield loss of chili pepper cultivar Cabe Besar. Alose relationship was observed between the number of applications with disease intensity, with coefficient of determination (R2) at 0.929. These results revealed that the formulation of P. polymyxa C1 effectively control the anthracnose disease on chili pepper, particularly on chili pepper cultivar Cabe Besar, and thus can be recommended for field testing to confirm its stability under field conditions.

Monitoring Needs for Gene Drive Mosquito Projects: Lessons From Vector Control Field Trials and Invasive Species

As gene drive mosquito projects advance from contained laboratory testing to semi-field testing and small-scale field trials, there is a need to assess monitoring requirements to: i) assist with the effective introduction of the gene drive system at field sites, and ii) detect unintended spread of gene drive mosquitoes beyond trial sites, or resistance mechanisms and non-functional effector genes that spread within trial and intervention sites. This is of particular importance for non-localized gene drive projects, as the potential scale of intervention means that monitoring is expected to be more costly than research, development and deployment. Regarding monitoring needs for population replacement systems, lessons may be learned from experiences with Wolbachia-infected mosquitoes, and for population suppression systems, from experiences with releases of genetically sterile male mosquitoes. For population suppression systems, assessing monitoring requirements for tracking population size and detecting rare resistant alleles are priorities, while for population replacement systems, allele frequencies must be tracked, and pressing concerns include detection of gene drive alleles with non-functional effector genes, and resistance of pathogens to functional effector genes. For spread to unintended areas, open questions relate to the optimal density and placement of traps and frequency of sampling in order to detect gene drive alleles, drive-resistant alleles or non-functional effector genes while they can still be effectively managed. Invasive species management programs face similar questions, and lessons may be learned from these experiences. We explore these monitoring needs for gene drive mosquito projects progressing through the phases of pre-release, release and post-release.

DEVELOPING DIVISITE (DISCOVERY LISTENING WEBSITE) TO FACILITATE STUDENTS’ LEARNING IN LISTENING SUBJECT

The aim of this research is for developing DIVISITE (Discovery Listening Website) to facilitate students learning in listening subject. The design of this research is educational R&D. The subjects of this study were second-semester students of the English Department for the 2020/2021 academic year STKIP PGRI Trenggalek. The research procedure includes need analysis, studying theories of educational, developing the educational product, validating product to expert, and field-testing the product. By using the website and combined with the three stages in the Discovery Listening technique, it can increase students' learning motivation and comprehension toward listening material. This can be seen from the results of pre-motivation getting a score of 1051 (almost disagree). This means that respondents rarely plan listening learning activities. Then, the results of the post-motivation questionnaire obtained a score of 1810 (almost agree). That is, there is an increase related to students' learning motivation in learning listening by using the Discovery Listening Website. In conclusion, based on the research findings described above. This research has been able to develop DIVISITE (Discovery Listening Website) and facilitate student learning in listening. Furthermore, this research was able to achieve the research objectives, namely DIVISITE (Discovery Listening Website) to facilitate students learning in listening subject.

Wetland Ecosystem Monitoring Through Water Quality Perspectives

Water quality monitoring is an important tool in determining the safety and suitability of water for various desired and intended uses. The procedures involved in the evaluation of water quality are numerous and multifaceted. Therefore, taking into consideration the specific objectives of water quality monitoring, sampling design is of vital importance. Most of the physical parameters of water quality are determined via in-situ measurements using modern testing equipment/field testing kits. Although there are some good field-based sensors that are being used for evaluation of water quality, the chemical parameters traditionally are mostly analyzed through laboratory-based experiments. This chapter is aimed to offer an inclusive knowledge and insights on the importance and assessment of physico-chemical parameters that are of high priority for monitoring the water quality of wetlands.

The Future of Virtual Reality and Deep Learning in Visual Field Testing

The visual field (VF) examination is a useful clinical tool for monitoring a variety of ocular diseases. Despite its wide utility in eye clinics, the test as currently conducted is subject to an array of issues that interfere in obtaining accurate results. Visual field exams of patients suffering from additional ocular conditions are often unreliable due to interference between the comorbid diseases. To improve upon these shortcomings, virtual reality (VR) and deep learning are being explored as potential solutions. Virtual reality has been incorporated into novel visual field exams to provide a portable, 3D exam experience. Deep learning, a specialization of machine learning, has been used in conjunction with VR, such as in the iGlaucoma application, to limit subjective bias occurring from patients' eye movements. This chapter seeks to analyze and critique how VR and deep learning can augment the visual field experience by improving accuracy, reducing subjective bias, and ultimately, providing clinicians with a greater capacity to enhance patient outcomes.

Enabling Systems Innovation in Climate Change Adaptation: Exploring the Role for MEL

Traditional monitoring, evaluation, and learning (MEL) approaches, methods, and tools no longer reflect the dynamic complexity of the severe (or “super-wicked”) problems that define the Anthropocene: climate change, environmental degradation, and global pandemics. In late 2019, the Adaptation Fund’s Technical Evaluation Reference Group (AF-TERG) commissioned a study to identify and assess innovative MEL approaches, methods, and technologies to better support and enable climate change adaptation (CCA) and to inform the Fund’s own approach to MEL. This chapter presents key findings from the study, with seven recommendations to support a systems innovation approach to CCA: Promote and lead with a CCA systems innovation approach, engaging with key concepts of complex systems, super-wicked problems, the Anthropocene, and socioecological systems. Engage better with participation, inclusivity, and voice in MEL. Overcome risk aversion in CCA and CCA MEL through field testing new, innovative, and often more risky MEL approaches. Demonstrate and promote using MEL to support and integrate adaptive management. Work across socioecological systems and scales. Advance MEL approaches to better support systematic evidence and learning for scaling and replicability. Adapt or develop MEL approaches, methods, and tools tailored to CCA systems innovation.