Multielectron Redox Chemistry of Transition Metal Complexes Supported by a Non‐Innocent N3P2 Ligand: Synthesis, Characterization, and Catalytic Properties

A new redox‐active, diarylamido‐based ligand (LN3P2) capable of κ5‐N,N,N,P,P chelation has been used to prepare a series of complexes with the general formula [MII(LN3P2)]X, where M = Fe (1; X = OTf), Co (2; X = ClO4), or Ni (3; X = ClO4). The diarylamido core of monoanionic LN3P2 is derived from bis(2‐amino‐4‐methylphenyl)amine, which undergoes condensation with two equivalents of 2‐(diphenylphosphanyl)benzaldehyde to provide chelating arms with both arylphosphine and imine donors. X‐ray structural, magnetic, and spectroscopic studies indicate that the N3P2 coordination environment generally promotes low‐spin configurations. Three quasi‐reversible redox couples between +1.0 and –1.5 V (vs. Fc+/Fc) were observed in voltammetric studies of each complex, corresponding to MII/MIII oxidation, LN3P2‐based oxidation, and MII/MI reduction (in order of highest to lowest potential). Spectroscopic and computational analyses of 3ox – generated via chemical one‐electron oxidation of 3 – revealed that a stable diarylaminyl radical (LN3P2·) is formed upon oxidation. The ability of the CoII complex (2) to function as an electrocatalyst for H2 generation was evaluated in the presence of weak acids. Moderate activity was observed using 4‐tert‐butylphenol as the proton source at potentials below –2.0 V. The insights gained here will assist in the future design of pentadentate mixed N/P‐based chelates for catalytic processes

A mobile cloud computing framework integrating multilevel encoding for performance monitoring in telerehabilitation

Recent years have witnessed a surge in telerehabilitation and remote healthcare systems blessed by the emerging low-cost wearable devices to monitor biological and biokinematic aspects of human beings. Although such telerehabilitation systems utilise cloud computing features and provide automatic biofeedback and performance evaluation, there are demands for overall optimisation to enable these systems to operate with low battery consumption and low computational power and even with weak or no network connections. This paper proposes a novel multilevel data encoding scheme satisfying these requirements in mobile cloud computing applications, particularly in the field of telerehabilitation. We introduce architecture for telerehabilitation platform utilising the proposed encoding scheme integrated with various types of sensors. The platform is usable not only for patients to experience telerehabilitation services but also for therapists to acquire essential support from analysis oriented decision support system (AODSS) for more thorough analysis and making further decisions on treatment

BIODIVERSITY OF THE BUNDALA NATIONAL PARK AND RAMSAR WETLAND

The Bundala National Park (6216 ha) is located in the Hambantota District, within the SoutheasternArid Zone of Sri Lanka. T:lC park consists mainly of dry thorny scrubland and lagoons;Koholankala (390 ha), Malala (6511 ha), Embilikala (430 ha) and Bundala (520 ha). Theseshallow water lagoons form a complex wetland system that harbours a rich bird life, includingseveral species of migratory waterfowl. Bundala is Sri Lanka's first Ramsar wetland-a wetlandof international importance especially for migratory waterfowl. Recent studies have indicatedthat the Bundala National Park and its wetlands are being degraded by various adverse factors,Therefore, this survey was intended to document the present status of biodiversity in thisprotected area, and the threats it faces today. The systematic survey on biodiversity extendedfrom January to April 2001, during which the area was visited at fortnightly intervals, The faunaand flora were surveyed using scientifically valid inventorying techniques. The survey enabledto document 7 major terrestrial vege.ation/habitat types (dry thorny scrubland, Arid zone forests,sand dune vegetation, gentle sea shore vegetation, Arid zone maritime grasslands/pastures,Riverine forest, anomalous Mesquite (Prosopis) scrublands and 6 wetland types (saltmarsh,mangrove, brackish water lagoons, sandy and rocky sea shore, seasonal water holes and tanks,saltern) in Bundala. A total of j83 plant species have been documented from the abovevegetation and habitat types in Bundala, These include 6 endemics and 7 species that areconsidered as nationally threatened. Shrubs and herbs (plants with leaves and non-woody stems)are the predominant plant life forms of Bundala. A total of 324 species of vertebrates have beenrecorded from Bundala National Park, of which 11 species are endemic, while 29 species arenationally threatened. Among the invertebrates are 52 species of colourful butterflies.At present, the biodiversity of Bundala National Park is facing several threats, which could besummarised under habitat deterioration and degradation (i.e., Shell mining, driving of vehiclesoff the recommended tracks, discharge of irrigation water in to lagoons, release of sludge intothe Bundala lagoon), direct exploitation of species (poaching, felling of trees, road kills), spreadof invasive alien species (4 animal species and 15 plant species), prolonged drought, andunplanned land-use practices. It is envisaged that these findings would contribute to theconservation and management of this globally important PA

Contrastive Deep Encoding Enables Uncertainty-aware Machine-learning-assisted Histopathology

Deep neural network models can learn clinically relevant features from millions of histopathology images. However generating high-quality annotations to train such models for each hospital, each cancer type, and each diagnostic task is prohibitively laborious. On the other hand, terabytes of training data -- while lacking reliable annotations -- are readily available in the public domain in some cases. In this work, we explore how these large datasets can be consciously utilized to pre-train deep networks to encode informative representations. We then fine-tune our pre-trained models on a fraction of annotated training data to perform specific downstream tasks. We show that our approach can reach the state-of-the-art (SOTA) for patch-level classification with only 1-10% randomly selected annotations compared to other SOTA approaches. Moreover, we propose an uncertainty-aware loss function, to quantify the model confidence during inference. Quantified uncertainty helps experts select the best instances to label for further training. Our uncertainty-aware labeling reaches the SOTA with significantly fewer annotations compared to random labeling. Last, we demonstrate how our pre-trained encoders can surpass current SOTA for whole-slide image classification with weak supervision. Our work lays the foundation for data and task-agnostic pre-trained deep networks with quantified uncertainty.Comment: 18 pages, 8 figure

EQ-5D-3L Derived Population Norms for Health Related Quality of Life in Sri Lanka

Background Health Related Quality of Life (HRQoL) is an important outcome measure in health economic evaluation that guides health resource allocations. Population norms for HRQoL are an essential ingredient in health economics and in the evaluation of population health. The aim of this study was to produce EQ-5D-3L-derived population norms for Sri Lanka. Method A population sample (n =  780) was selected from four districts of Sri Lanka. A stratified cluster sampling approach with probability proportionate to size was employed. Twenty six clusters of 30 participants each were selected; each participant completed the EQ-5D-3L in a face-to-face interview. Utility weights for their EQ-5D-3L health states were assigned using the Sri Lankan EQ-5D-3L algorithm. The population norms are reported by age and socio-economic variables. Results The EQ-5D-3L was completed by 736 people, representing a 94% response rate. Sixty per cent of the sample reported being in full health. The percentage of people responding to any problems in the five EQ-5D-3L dimensions increased with age. The mean EQ-5D-3L weight was 0.85 (SD 0.008; 95%CI 0.84-0.87). The mean EQ-5D-3L weight was significantly associated with age, housing type, disease experience and religiosity. People above 70 years of age were 7.5 times more likely to report mobility problems and 3.7 times more likely to report pain/discomfort than those aged 18-29 years. Those with a tertiary education were five times less likely to report any HRQoL problems than those without a tertiary education. A person living in a shanty was 4.3 more likely to have problems in usual activities than a person living in a single house. Conclusion The population norms in Sri Lanka vary with socio-demographic characteristics. The socioeconomically disadvantaged have a lower HRQoL. The trends of population norms observed in this lower middle income country were generally similar to those previously reported in high income countries

Real-time decoding of covert attention in higher-order visual areas

Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online ‘winner-takes-all approach’ with quadrant-specific parameter estimates, to achieve single-block classification of brain activations. These were linked to the covert allocation of attention to real-world images presented at 4-quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, ‘cognitive BCIs’ access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury

Groundwater quality and antibiotic resistance of coliform bacteria in Wilgamuwa, an area of Chronic Kidney Disease of unknown etiology (CKDu) in Sri Lanka

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ASSESSMENT OF BIODIVERSITY IN THE MUTHURAJAWELA WETLAND SANCTUARY

Muthurajawela wetland. located as the west coast of Sri Lanka is the largestcoastal peal bag of the island. At present. the biodiversity of Muthurajawela isthreatened by unplanned development activities and growing human population.Therefore, an ecological survey was carried out in order to assess the presentstatus of biodiversity in Muthurajawela, and also to identify critical habitats forthe conservation and sustence of biodiversity. Field monitoring of fauna and florawas carried out at fortnightly intervals, using scientifically accepted rapidbiodiversity assessment techniques (fauna - line transects; flora - plots, Braun-Blanquet cover), The data was analysed using ecological indices(diversity/species richness), and critical habitats were identified using avifauna asa correlate of biodiversity. Ground truthing of vegetation maps was carried out todocument changes of major vegetation communities.The study enabled to identify 192 species of flora, distributed over seven majorvegetation communities at Muthurajawela; marsh, lentic flora, reed swamp, shortgrassland, scrubland, stream bank flora and mangrove swamp. The vertebratefauna documented included 40 species of fish, 14 species of amphibians, 31species of reptiles, 102 species of birds and 22 species of mammals. Among thetotal vertebrate species documented, 17 are endemic, 26 are considered asnationally threatened, while 36 are new records to Muthurajawela. The selectedinvertebrate species documented consisted of 48 species of butterflies and 22species odonates, the latter which turned out to be a useful indicator of habitatquality. The threats documented included direct exploitation (poaching, cutting oftrees), habitat degradation/modification (land reclamation, dumping of garbage,clearing of natural vegetation, pollution and eutrophication) and the spread ofseveral alien invasive species (including unmanaged domestic animals). Thenorthern part of the marsh serve as an ecotone, with a mixture of the above plantcommunities/habitat types which were relatively undisturbed. Analysis carriedout using ecological indices highlighted the northern region as a high biodiversityzone, which is critical for the conservation and future sustenance of biodiversity atMuthurajawela. Ground truthing of vegetation maps, supported with results of thevegetation survey showed that the composition of dominant flora has changedover a period of 10 years, in most places in the Muthurajawela Wetland, as aresult of human disturbances. Data on the avifauna also highlighted aconsiderable decrease in migrant birds at Muthurajawela, possibly due to habitatdeterioration.The findings have important conservation and managementimplications, in particular greater emphasis need to be placed on the more ciritcalareas of the marsh. An important policy implication would be the need

AN ASSESSMENT OF BIODIVERSITY IN THE REKAWA, USSANGODA AND KALAMETIYA INLAND COASTAL ECOSYSTEMS IN SOUTHERN SRI LANKA

The survey was carried out to document the status of inland biodiversity in the Rekawa,Ussangoda and Kalametiya area along the Southern coastal zone of Sri Lanka. Thesurvey extended from October 2002 - March 2003 (6 months). A reconnaissance surveyof the inland areas was conducted, prior to the regular field sampling, in order to selectrepresentative sampling sites within the Ruk area. Eight sites were selected for regularfield sampling at fortnightly intervals, and the plants and animals of the area weresurveyed in a scientific manner, using appropriate sampling techniques.The survey area harbours a variety of natural and man-made vegetationlhabitat types,including both terrestrial and wetland systems. A total of 287 plant species belonging to222 genera under 94 families were documented from the above inland vegetationlhabitattypes of the Ruk area. Several sub types of Mangroves, based mainly on floristics, couldbe found in the RUK area. These include the Lumnitzera dominated stands (Rekawa),Ceriops dominated stands (Rekawa), Avicennia dominated stands (Rekawa), Mixedstands (Rekawa, Kahanda), Excoecaria dominated stands (between Lunawa andKalametiya) and Sonneratia dominated stands (Kalametiya, Malpeththawa). It isinteresting to note that some mangrove stands are represented by only a single species.A total of 328 species of vertebrates were recorded from the RUK area, of which 14species (4%) are endemic, while 27 species (8%) are nationally threatened. Thevertebrates include 52 species of fish, 17 species of amphibians, 49 species of reptiles,184 species of birds, and 26 species of mammals. The invertebrates include 72 species ofcolorful butterflies, 25 spec.es of terrestrial molluscs an": 9 species of aquatic molluscs.Three beach stretches that are important turtle nesting sites, eleven birding hotspots andthree bird roosting sites were identified within the RUK area.The study area has been identified for major development initiatives, under the SouthernDevelopment Programme of the Government of Sri Lanka. Therefore, the relevantconservation agencies should take steps to ensure that, biodiversity conservation concernsare adequately addressed in specific developmental activities planned for the area.