Water Security in India Threat Mapping: Impact of Climate Change

Water has been a much discussed topic in India in recent years. Starting from the government’s decision on inter-river linking, construction of dams to localised state conflicts over sharing, water touches a chord across religion both ethnically and politically. Hence if water becomes skewed owing to continuous lack of rainfall and simultaneous exploitation for human consumption, it could soon attain a national narrative that would have a bearing on the national economy, agricultural output, religious tourism (given that river is the religious lifeline of the country) subaltern conflicts and much more. The report illustrates five contributing factors/parameters/ issues to water insecurity such as: ground water depletion, glacial retreat, rainfall, temperature fluctuation, national water governance and civil society initiatives such as various water conservation practices. The issues were then studied in each ecological zone to understand the broader link between the causes of water scarcity and climatic variabilit

Rising Radicalisation in India’s Neighbourhood: Bangladesh and Myanmar (NIAS Wednesday Discussion Report)

Report of the Wednesday Discussion Meeting held on 8 June 201

India-Bangladesh: What if the BNP returns?

Bangladesh is gearing up for its general election in December, this year. With its two main political parties—the BNP and AL (Awami League) led by Begum Khaleda Zia and Sheikh Hasina respectively hedging against each other—the election will be decisive in determining the future of bi-party politics in the country along with shaping the roadmap for Bangladesh in the region. After holding power for two consecutive terms an anti-incumbency wave could be identified against the Awami League. The electoral ground is fertile for the Bangladesh Nationalist Party chief, Khaleda Zia, to come out of her political hibernation and contest the election. But the imprisonment of the BNP (Bangladesh Nationalist Party) chairperson, Khaleda Zia, on corruption charges just before the country entered the voting phase has raised two questions. First, how will the arrest of BNP chief impact the electoral future and bi-party politics in Bangladesh? Is this verdict a death- knell for the party? Secondly, would this election result affect the current India-Bangladesh relations

A real-time proximity querying algorithm for haptic-based molecular docking

Intermolecular binding underlies every metabolic and regulatory processes of the cell, and the therapeutic and pharmacological properties of drugs. Molecular docking systems model and simulate these interactions in silico and allow us to study the binding process. Haptic-based docking provides an immersive virtual docking environment where the user can interact with and guide the molecules to their binding pose. Moreover, it allows human perception, intuition and knowledge to assist and accelerate the docking process, and reduces incorrect binding poses. Crucial for interactive docking is the real-time calculation of interaction forces. For smooth and accurate haptic exploration and manipulation, force-feedback cues have to be updated at a rate of 1 kHz. Hence, force calculations must be performed within 1ms. To achieve this, modern haptic-based docking approaches often utilize pre-computed force grids and linear interpolation. However, such grids are time-consuming to pre-compute (especially for large molecules), memory hungry, can induce rough force transitions at cell boundaries and cannot be applied to flexible docking. Here we propose an efficient proximity querying method for computing intermolecular forces in real time. Our motivation is the eventual development of a haptic-based docking solution that can model molecular flexibility. Uniquely in a haptics application we use octrees to decompose the 3D search space in order to identify the set of interacting atoms within a cut-off distance. Force calculations are then performed on this set in real time. The implementation constructs the trees dynamically, and computes the interaction forces of large molecular structures (i.e. consisting of thousands of atoms) within haptic refresh rates. We have implemented this method in an immersive, haptic-based, rigid-body, molecular docking application called Haptimol_RD. The user can use the haptic device to orientate the molecules in space, sense the interaction forces on the device, and guide the molecules to their binding pose. Haptimol_RD is designed to run on consumer level hardware, i.e. there is no need for specialized/proprietary hardware

Adaptive GPU-accelerated force calculation for interactive rigid molecular docking using haptics

Molecular docking systems model and simulate in silico the interactions of intermolecular binding. Haptics-assisted docking enables the user to interact with the simulation via their sense of touch but a stringent time constraint on the computation of forces is imposed due to the sensitivity of the human haptic system. To simulate high fidelity smooth and stable feedback the haptic feedback loop should run at rates of 500 Hz to 1 kHz. We present an adaptive force calculation approach that can be executed in parallel on a wide range of Graphics Processing Units (GPUs) for interactive haptics-assisted docking with wider applicability to molecular simulations. Prior to the interactive session either a regular grid or an octree is selected according to the available GPU memory to determine the set of interatomic interactions within a cutoff distance. The total force is then calculated from this set. The approach can achieve force updates in less than 2 ms for molecular structures comprising hundreds of thousands of atoms each, with performance improvements of up to 90 times the speed of current CPU-based force calculation approaches used in interactive docking. Furthermore, it overcomes several computational limitations of previous approaches such as pre-computed force grids, and could potentially be used to model receptor flexibility at haptic refresh rates

SAFE: An EEG dataset for stable affective feature selection

An affective brain-computer interface (aBCI) is a direct communication pathway between human brain and computer, via which the computer tries to recognize the affective states of its user and respond accordingly. As aBCI introduces personal affective factors into human-computer interaction, it could potentially enrich the user’s experience during the interaction. Successful emotion recognition plays a key role in such a system. The state-of-the-art aBCIs leverage machine learning techniques which consist in acquiring affective electroencephalogram (EEG) signals from the user and calibrating the classifier to the affective patterns of the user. Many studies have reported satisfactory recognition accuracy using this paradigm. However, affective neural patterns are volatile over time even for the same subject. The recognition accuracy cannot be maintained if the usage of aBCI prolongs without recalibration. Existing studies have overlooked the performance evaluation of aBCI during long-term use. In this paper, we propose SAFE—an EEG dataset for stable affective feature selection. The dataset includes multiple recording sessions spanning across several days for each subject. Multiple sessions across different days were recorded so that the long-term recognition performance of aBCI can be evaluated. Based on this dataset, we demonstrate that the recognition accuracy of aBCIs deteriorates when re-calibration is ruled out during long-term usage. Then, we propose a stable feature selection method to choose the most stable affective features, for mitigating the accuracy deterioration to a lesser extent and maximizing the aBCI performance in the long run. We invite other researchers to test the performance of their aBCI algorithms on this dataset, and especially to evaluate the long-term performance of their methods

A Review of Virtual Reality Based Training Simulators for Orthopaedic Surgery

This review presents current virtual reality based training simulators for hip, knee and other orthopaedic surgery, including elective and trauma surgical procedures. There have not been any reviews focussing on hip and knee orthopaedic simulators. A comparison of existing simulator features is provided to identify what is missing and what is required to improve upon current simulators. In total 11 total hip replacement pre-operative planning tools were analysed, plus 9 hip trauma fracture training simulators. Additionally 9 knee arthroscopy simulators and 8 other orthopaedic simulators were included for comparison. The findings are that for orthopaedic surgery simulators in general, there is increasing use of patient-specific virtual models which reduce the learning curve. Modelling is also being used for patient-specific implant design and manufacture. Simulators are being increasingly validated for assessment as well as training. There are very few training simulators available for hip replacement, yet more advanced virtual reality is being used for other procedures such as hip trauma and drilling. Training simulators for hip replacement and orthopaedic surgery in general lag behind other surgical procedures for which virtual reality has become more common. Further developments are required to bring hip replacement training simulation up to date with other procedures. This suggests there is a gap in the market for a new high fidelity hip replacement and resurfacing training simulator

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201