Molecular Computing: from conformational pattern recognition to complex processing networks

Natural biomolecular systems process information in a radically different manner than programmable machines. Conformational interactions, the basis of specificity and self-assembly, are of key importance. A gedanken device is presented that illustrates how the fusion of information through conformational self-organization can serve to enhance pattern processing at the cellular level. The device is used to highlight general features of biomolecular information processing. We briefly outline a simulation system designed to address the manner in which conformational processing interacts with kinetic and higher level structural dynamics in complex biochemical networks. Virtual models that capture features of biomolecular information processing can in some instances have artificial intelligence value in their own right and should serve as design tools for future computers built from real molecules

Subset Feature Learning for Fine-Grained Category Classification

Fine-grained categorisation has been a challenging problem due to small inter-class variation, large intra-class variation and low number of training images. We propose a learning system which first clusters visually similar classes and then learns deep convolutional neural network features specific to each subset. Experiments on the popular fine-grained Caltech-UCSD bird dataset show that the proposed method outperforms recent fine-grained categorisation methods under the most difficult setting: no bounding boxes are presented at test time. It achieves a mean accuracy of 77.5%, compared to the previous best performance of 73.2%. We also show that progressive transfer learning allows us to first learn domain-generic features (for bird classification) which can then be adapted to specific set of bird classes, yielding improvements in accuracy

Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification

We propose a local modelling approach using deep convolutional neural networks (CNNs) for fine-grained image classification. Recently, deep CNNs trained from large datasets have considerably improved the performance of object recognition. However, to date there has been limited work using these deep CNNs as local feature extractors. This partly stems from CNNs having internal representations which are high dimensional, thereby making such representations difficult to model using stochastic models. To overcome this issue, we propose to reduce the dimensionality of one of the internal fully connected layers, in conjunction with layer-restricted retraining to avoid retraining the entire network. The distribution of low-dimensional features obtained from the modified layer is then modelled using a Gaussian mixture model. Comparative experiments show that considerable performance improvements can be achieved on the challenging Fish and UEC FOOD-100 datasets.Comment: 5 pages, three figure

Graded potential of neural crest to form cornea, sensory neurons and cartilage along the rostrocaudal axis

Neural crest cells arising from different rostrocaudal axial levels form different sets of derivatives as diverse as ganglia, cartilage and cornea. These variations may be due to intrinsic properties of the cell populations, different environmental factors encountered during migration or some combination thereof. We test the relative roles of intrinsic versus extrinsic factors by challenging the developmental potential of cardiac and trunk neural crest cells via transplantation into an ectopic midbrain environment. We then assess long-term survival and differentiation into diverse derivatives, including cornea, trigeminal ganglion and branchial arch cartilage. Despite their ability to migrate to the periocular region, neither cardiac nor trunk neural crest contribute appropriately to the cornea, with cardiac crest cells often forming ectopic masses on the corneal surface. Similarly, the potential of trunk and cardiac neural crest to form somatosensory neurons in the trigeminal ganglion was significantly reduced compared with control midbrain grafts. Cardiac neural crest exhibited a reduced capacity to form cartilage, contributing only nominally to Meckle's cartilage, whereas trunk neural crest formed no cartilage after transplantation, even when grafted directly into the first branchial arch. These results suggest that neural crest cells along the rostrocaudal axis display a graded loss in developmental potential to form somatosensory neurons and cartilage even after transplantation to a permissive environment. Hox gene expression was transiently maintained in the cardiac neural tube and neural crest at 12 hours post-transplantation to the midbrain, but was subsequently downregulated. This suggests that long-term differences in Hox gene expression cannot account for rostrocaudal differences in developmental potential of neural crest populations in this case

Use of Motorcycle Helmets in YOGYAKARTA : Some Observations and Comments

Cedera kepala merupakan sebab utama kematian dalam kecelakaan sepeda motor. Penelitian di Ame­rika Serikat, menunjukkan pemakaian helm mengurangi risiko cedera dan kematian. Penelitian ini mene­liti ketaatan terhadap peraturan pemakaian helm di Yogyakarta. Data dikumpulkan melalui observasi sistematik (N=9242) dan wawancara terbuka (n=150) di lima jalan utama yang berbeda di seluruh kota. Ketaatan umum terhadap peraturan pemakaian helm adalah 87% untuk pengemudi, dengan variasi kepen­tingan terhadap waktu dan tempat.Hanya 55% pengemudi memakai helm dengan baik (dengan tali di ikatkan) dan hanya 20% penumpang memakai helm. Jadi hanya 50% orang yang naik sepeda motor terlindungi secara maksimum. Di dalam wawancara, responden mengatakan ketidak-enakan fisik dan "malas" sebagai alasan paling umum untuk tidak memakai helm; beberapa orang menyatakan helm tidak perlu di jalan-jalan kota dan di waktu malam. Wawancara mengisyaratkan bahwa orang yang naik sepeda motor memakai helm kebanyakan karena takut di tegur polisi dan responden hanya tahu sedikit tentang nilai keselamatan helm. Banyaknya pemakaian helm sekarang ini merupakan ketaatan semu ("token compliance") terhadap peraturan. Dari hasil studi diusulkan cara-cara agar keselamatan pemakaian helm di Indonesia bisa di­tingkatkan

Comment: Judicial Accountability and Discipline

The judicial disciplinary process and the specter of politically motivated misconduct allegations against state judges poses an important challenge to judicial independence