Spatial prioritization of dugong habitats in India can contribute towards achieving the 30 × 30 global biodiversity target.

Indian coastal waters are critical for dugong populations in the western Indian Ocean. Systematic spatial planning of dugong habitats can help to achieve biodiversity conservation and area-based protection targets in the region. In this study, we employed environmental niche modelling to predict suitable dugong habitats and identify influencing factors along its entire distribution range in Indian waters. We examined data on fishing pressures collected through systematic interview surveys, citizen-science data, and field surveys to demarcate dugong habitats with varying risks. Seagrass presence was the primary factor in determining dugong habitat suitability across the study sites. Other variables such as depth, bathymetric slope, and Euclidean distance from the shore were significant factors, particularly in predicting seasonal suitability. Predicted suitable habitats showed a remarkable shift from pre-monsoon in Palk Bay to post-monsoon in the Gulf of Mannar, indicating the potential of seasonal dugong movement. The entire coastline along the Palk Bay-Gulf of Mannar region was observed to be at high to moderate risk, including the Gulf of Mannar Marine National Park, a high-risk area. The Andaman Islands exhibited high suitability during pre- and post-monsoon season, whereas the Nicobar Islands were highly suitable for monsoon season. Risk assessment of modelled suitable areas revealed that < 15% of high-risk areas across Andaman and Nicobar Islands and Palk Bay and Gulf of Mannar, Tamil Nadu, fall within the existing protected areas. A few offshore reef islands are identified under high-risk zones in the Gulf of Kutch, Gujarat. We highlight the utility of citizen science and secondary data in performing large-scale spatial ecological analysis. Overall, identifying synoptic scale 'Critical Dugong Habitats' has positive implications for the country's progress towards achieving the global 30 × 30 target through systematic conservation planning.

Comparison of the effect of audiovisual and verbal instructions on patient performance while performing automated Humphrey visual field testing.

Purpose: To compare the effect of audiovisual and verbal instructions on patient performance while performing automated Humphrey visual field testing. Methods: This was a prospective study. A total 120 patients divided into groups of 40 each were recruited from the glaucoma outpatient department (OPD). All patients were aged 35-75 years with no previous experience of performing HFA. Patients with hearing impairment, any other cognitive impairment, and best-corrected visual acuity (BCVA) ≤6/36 on Snellen's visual acuity were excluded. The first two groups were given strict (conservative) and lenient (liberal) verbal instructions. The instructions were adapted from those listed in the manufacturer's instruction. and the third group was shown a standard video depicting in detail how perimetry was to be performed. A questionnaire was given to each patient before and after the test to assess the patient's performance. Results: Patients diagnosed with glaucoma during testing in each group were 29 (72.50%), 30 (75.0%), and 33 (82.5%) in the video instructed, strictly verbal, and leniently verbal groups, respectively. The overall mean deviation (MD) in the right eye (RE) was of - 3.38 (-4.9 to 1.9) and in the left eye (LE) was - 3.96 (-6.4 to - 1.9). Reliable field was slightly higher for the video instructed group (47.5%) and lowest for the strictly verbal group (22.5%) (P = 0.033). A higher number of patients were very motivated in the video instructed group (27%) (P = 0.041). Post-test questionnaires showed that 40% of patients felt they have performed the test with 100% accuracy in video group with less guessing. A higher number of patients in the video instructed group (85%) felt instruction was helpful in performing the test (P = 0.001). Conclusion: The video groups were more motivated and had better confidence to perform the test with less anxiety and stress and with probably better understanding of the procedure due to visual effects enhancing their understanding.

Spatio-temporal analysis identifies marine mammal stranding hotspots along the Indian coastline.

Marine mammal strandings provide vital information on species' life histories, population health and status of marine ecosystems. Opportunistic reporting of strandings also serve as a powerful low-cost tool for monitoring these elusive mammals. We collated data over ~ 270 years available through various open access databases, reports and publications. Annual strandings along the Indian coast (mean = 11.25 ± SE 9.1) increased in the last two years of the study (2015-2017, mean = 27.66 ± SE 8.5 strandings /year). We found that stranding events spike during June-September along the west coast and during December-January along the east coast. We identified several sections of the coastline, such as Mumbai (0.38 strandings/km), Kozhikode (0.28 strandings/km),  Tuticorin (0.4 strandings/km), Rameswaram (1.82 strandings/km), Chennai (0.32 strandings/km) and Bhubaneshwar (0.26 strandings/km) with a higher number of stranded animals reported. Emerging Hotspot Analysis located new and consecutive hotspots along the north-west coast, and sporadic hotspots along the south-east coast. We recommend establishing regional stranding response centres at the identified hotspots coordinated by a National Stranding Centre with adequately trained personnel and central funding support. Regular stranding response training programs for field veterinarians, and frontline personnel of State Forest Departments near stranding hotspots would provide an improved understanding of marine mammal health and threats in Indian waters. Further, the suggested National Stranding Centre needs to maintain a 'National Stranding Database' for long-term marine mammal conservation planning in India.

Ontology-Based Personalized Cognitive Behavioural Plans for Patients with Mild Depression.

Cognitive Behavioural Therapy (CBT) is an action-oriented psychotherapy that combines cognitive and behavioural techniques for psychosocial treatment for depression, and is considered by many to be the golden standard in psychotherapy. More recently, computerized CBT (CCBT) has been deployed to help increase availability and access to this evidence-based therapy. In this vein, a CBT ontology, as a shared common understanding of the domain, can facilitate the aggregation, verification, and operationalization of computerized CBT knowledge. Moreover, as opposed to black-box applications, ontology-enabled systems allow recommended, evidence-based treatment interventions to be traced back to the corresponding psychological concepts. We used a Knowledge Management approach to synthesize and computerize CBT knowledge from multiple sources into a CBT ontology, which allows generating personalized action plans for treating mild depression, using the Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL). We performed a formative evaluation of the CBT ontology in terms of its completeness, consistency, and conciseness.