Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experimental Comparison of Similarity Assessment Measures for 3D Models on Constrained Surface Deformation

To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre‐experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a seri.
Improving population estimates by quantifying diving and surfacing patterns: a dugong example

Diving animals are available for detection from above the water when environmental conditions are favorable and the animals are near the surface. The number of animals that are unavailable for detection needs to be estimated to obtain unbiased population estimates. The current availability correction factors used in aerial surveys for the dugong (Dugong dugon) allow for variation in environmental conditions but use the average time dugongs spend near the surface (i.e., constant availability corrections). To improve availability estimates, we examined location and dive data from nine dugongs fitted with satellite telemetry units and time-depth recorders (TDRs) in eastern Australia. The effects of water depth, tidal conditions, and habitat types on dugong surfacing time were examined using generalized linear mixed models (GLMMs). We found that availability for detection differed with water depth, and depth-specific availability estimates were often lower than the constant estimates. The habitat effect was less influential, and there was no tidal effect. The number of dugongs estimated using depth-specific availabilities were higher than those obtained using constant availabilities across water depth. Hence, information on water depth can refine availability estimates and subsequent abundance estimates from dugong aerial surveys. The methodology may be applicable to other aquatic wildlife.
Design and Implementation of a Novel System for Correcting Posture Through the Use of a Wearable Necklace Sensor

Background To our knowledge, few studies have examined the use of wearable sensing devices to effectively integrate information communication technologies and apply them to health care issues (particularly those pertaining to posture correction). Objective A novel system for posture correction involving the application of wearable sensing technology was developed in this study. The system was created with the aim of preventing the unconscious development of bad postures (as well as potential spinal diseases over the long term). Methods The newly developed system consists of a combination of 3 subsystems, namely, a smart necklace, notebook computer, and smartphone. The notebook computer is enabled to use a depth camera to read the relevant data, to identify the skeletal structure and joint reference points of a user, and to compute calculations relating to those reference points, after which the computer then sends signals to the smart necklace to enable calibration of the smart necklace’s standard values (base values for posture assessment). The gravitational acceleration data of the user are collected and analyzed by a microprocessor unit-6050 sensor housed in the smart necklace when the smart necklace is worn, with those data being used by the smart necklace to determine the user’s body posture. When poor posture is detected by the smart necklace, the smart necklace sends the user’s smartphone a reminder to correct his or her posture; a mobile app that was also developed as part of the study allows the smart necklace to transmit such messages to the smartphone. Results The system effectively enables a user to monitor and correct his or her own posture, which in turn will assist the user in preventing spine-related diseases and, consequently, in living a healthier life. Conclusions The proposed system makes it possible for (1) the user to self-correct his or her posture without resorting to the use of heavy, thick, or uncomfortable corrective clothing; (2) the smart necklace’s standard values to be quickly calibrated via the use of posture imaging; and (3) the need for complex wiring to be eliminated through the effective application of the Internet of Things as well as by implementing wireless communication between the smart necklace, notebook computer, and smartphone.
Bayesian Methods for Contingency Tables

Bayesian alternatives to frequentist methods for fundamental problems in categorical data analysis, such as testing independence in two-way contingency tables and estimating probabilities of categories containing no observations, have been considered for at least four decades. Since the 1980s, Bayesian methods of model selection have also seen extensive and continuing development. These attempt to address the tendencies of frequentist approaches to arrive at overly complex models, and to disregard the effects of variability in model selection on model-based estimated effects and predictions. This entry briefly reviews several Bayes and empirical Bayes approaches to estimating probabilities of categories, testing equiprobability in a one-way table, testing independence in a two-way contingency table, and selecting among generalized linear models, with particular attention to loglinear models, for tables of higher dimension. Keywords: Bayesian methods; empirical Bayes; Bayes factors; BIC; Schwartz criterion; smoothed counts; loglinear models; model selection
A study on clinical profile and outcome of patients in PICU (paediatric intensive care unit) at tertiary care unit

Background: This study was carried out with the objectives to study the clinical profile and to find the outcome of children admitted to pediatric intensive care unit (PICU) of Kurnool medical college and hospital, Andhra Pradesh.Methods: A retrospective study was carried in children aged more than 28 days to 12 years admitted in PICU from 1st January 2016 to 31st December 2016 when a total of 600 patients were admitted.Results: Out of these, 400 (66.66%) cases were males and 200 (33.33%) cases were females. Maximum numbers of patients were in the age group of more than 28 days to 1 year which constituted 325 (54.16%) cases. This was followed by 1 year to less than 5 years age group which constituted 150 (i.e. 25%) cases. Under 5 years aged children constituted 500 (83.33%) cases. Next most common age group admitted was 5 years to 10 years with 85 (i.e. 14.16%) cases and 10 to 12 years age group constituted 40 (6.66%) cases. In this study, central nervous system was the commonest system involved (n=195, 32.5%). Other systems involved were: respiratory system (n=122, 20.33%), cardiovascular system (n=65, 10.83%), gastro-intestinal system (n=32, 5.33%), hematological (n=35, 5.83%) and renal system (n=23, 3.83%). Other causes include infections (n=97, 16.16%), metabolic (n=17, 2.83%), down syndrome (n=7, 1.16%) and poisoning (n=7, 1.16%) etc.Conclusions: Out of the 600 patients admitted to PICU, 168 (28%) patients died. 315 (52.5%) cases improved. 117 (19.5%) cases constituted those who were shifted to higher centre or another department or were taken against medical advice.
Comparison between the effectcs of remifentanil and fentanyl on blood pressure and cardiac dysrythmia during tracheal intubation in CABG.

Background and purpose: It has been found that the use of different drugs for laryngoscopy preparation and tracheal intubation results in controversy. The aim of this study is to compare the haemodynamic effects of remifentanil with fentanyl for tracheal intubation in patients undergoing coronary artery bypass grafting (CABG). Materials and methods: This is a randomized and double-blind study. We recruited 64 patients undergoing coronary artery bypass surgery. Subjects received in 3 separate groups: remifentanil, 5 microgram/kg, Fentanyl, 8 microgram/kg, and routine medication respectively. Systolic and diastolic blood pressure, heart rate and mean arterial pressure were measured during, before and after tracheal intubation and immediately, 1, 3, 5, 10, minutes after intubation. Patients were monitored for haemodynamic changes using electrocardiography. Results: Sixty four patients were enrolled in the study. Twenty four patients age at 66 ± 5.7 (60-84) years, received remifentanil, 23 patients with mean age of 65.7 ± 6 (60-80) years made up the routin group, and 17 patients with mean age of 65 ± 4.8 (61-76) years received fentanyl. Blood pressure and heart rate decreased after induction of anaesthesia in all groups. SBP and DBP significantly decreased in remifentanil group in comparison with other groups (p= 0.01, 0.03). It was pssoble to control hemodynamic response to tracheal intubation in all groups, although it was better in remifentanil group than other groups. Conclusion: Although the incidence of hypotension was higher, 0.5 microgram/kg of Remifentanil 8 microgram/kg of fentanyl and routine method (sufentanil) were all effective to attenuate patients’ blood pressure in response to tracheal intubation up to 3 minutes after intubation. (Irct ID: IRCT138905114492N1)
Transition mechanism design of a hybrid wheel-track-leg based on foldable rims

Hybrid mobile robots with multiple locomotion modes are getting more and more popular in search and rescue (SAR) and explosive object disposal (EOD) missions because of their good terrain adaptability. Present researchers devote themselves to develop efficient and reliable transition method between different locomotion modes to make the hybrid robot more compact and flexible. In this paper, we present a novel transition mechanism for a hybrid wheel-track based on foldable rims. The wheel rim is cut into four segments so that it is foldable. And the transition between wheel and track is achieved by the folding or unfolding of the foldable rim. According to its geometrical property during the transition process, a single-freedom supporting spoke is proposed to drive the foldable rim’s transformation. We analyze the length and angle varying principles of the supporting spoke by utilizing the kinematic mode based on screw theory. According to above results, five different kinds of transition mechanism of the supporting spoke is designed, performance comparison among which is conducted by dynamic simulations. Two of the five candidate transition mechanisms are picked up for their smaller driving force requirements. Their 3D printing prototypes are also fabricated and experiments show that the hybrid wheel-track can switch between wheel and track successfully. Compared to most hybrid robots which have separate wheels, tracks and legs, this transition mechanism makes the robot own both compact structure and multimodal locomotion.
Abundance of primates reveals Samkos Wildlife Sanctuary, Cardamom Mountains, Cambodia as a priority area for conservation

Abstract We conducted a primate survey in Samkos Wildlife Sanctuary, western Cambodia, during the wet season in 2009. We visually confirmed the presence of five out of six primate species thought to occur in the area: Bengal slow loris Nycticebus bengalensis, Indochinese silvered langur Trachypithecus germaini, pileated gibbon Hylobates pileatus, pig-tailed macaque Macaca leonina and long-tailed macaque Macaca fascicularis. We did not find any sign of the stump-tailed macaque Macaca arctoides and suggest it is absent in Samkos Wildlife Sanctuary and possibly from the Cardamom Mountains. We provide the abundance measures for each primate species; the three most abundant species were Bengal slow loris, Indochinese silvered langur and pileated gibbon. We propose Samkos Wildlife Sanctuary as a priority for primate conservation in Cambodia.
Oxford TRECVID 2008 - Notebook paper

The Oxford/IIIT team participated in the high-level feature extraction and interactive search tasks. A vision only approach was used for both tasks, with no use of the text or audio information. For the high-level feature extraction task, we used two different approaches, both based on a combination of visual features. One used a SVM classifier using a linear combination of kernels, the other used a random forest classifier. For both methods, we trained all high-level features using publicly available annotations [24]. The advantage of the random forest classifier is the speed of training and testing. In addition, for thepeople feature, we took a more targeted approach. We used a real-time face detector and an upper body detector, in both cases running on every frame. One run C OXVGG 4 4 was submitted using only Random forest approach for all concepts except two people. It performed best on Dog and hand, and came over the median for all the classes except kitchen and airplane. In the interactive search task, our team came third overall with an mAP of 0.158. The system used was identical to last year with the only change being a source of accurate upper body detections.
Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed

The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.
Magnetohydrodynamics of protoplanetary discs

Protoplanetary discs are made of gas and dust orbiting a young star. They are also the birth place of planetary systems, which motivates a large amount of observational and theoretical research. In these lecture notes, I present a review of the magnetic mechanisms applied to the outer regions ($R\gtrsim 1\ \mathrm {AU}$) of these discs, which are the planet-formation regions. In contrast to usual astrophysical plasmas, the gas in these regions is noticeably cold ($T < 300\ \mathrm {K}$) and dense, which implies a very low ionisation fraction close to the disc midplane. In these notes, I deliberately ignore the innermost $(R\sim 0.1\ \mathrm {AU})$ region, which is influenced by the star–disc interaction and various radiative effects. I start by presenting a short overview of the observational evidence for the dynamics of these objects. I then introduce the methods and approximations used to model these plasmas, including non-ideal magnetohydrodynamics, and the uncertainties associated with this approach. In this framework, I explain how the global dynamics of these discs is modelled, and I present a stability analysis of this plasma in the local approximation, introducing the non-ideal magneto-rotational instability. Following this mostly analytical part, I discuss numerical models that have been used to describe the saturation mechanisms of this instability, and the formation of large-scale structures by various saturation mechanisms. Finally, I show that local numerical models are insufficient because magnetised winds are also emitted from the surface of these objects. After a short introduction on wind physics, I present global models of protoplanetary discs, including both a large-scale wind and the non-ideal dynamics of the disc.
Genetic Improvement @ ICSE 2020

Following Prof. Mark Harman of Facebook's keynote and formal presentations (which are recorded in the proceed- ings) there was a wide ranging discussion at the eighth inter- national Genetic Improvement workshop, GI-2020 @ ICSE (held as part of the International Conference on Software En- gineering on Friday 3rd July 2020). Topics included industry take up, human factors, explainabiloity (explainability, jus- tifyability, exploitability) and GI benchmarks. We also con- trast various recent online approaches (e.g. SBST 2020) to holding virtual computer science conferences and workshops via the WWW on the Internet without face to face interac- tion. Finally we speculate on how the Coronavirus Covid-19 Pandemic will a ect research next year and into the future.
Low Dimensional State Representation Learning with Reward-shaped Priors

Reinforcement Learning has been able to solve many complicated robotics tasks without any need for feature engineering in an end-to-end fashion. However, learning the optimal policy directly from the sensory inputs, i.e the observations, often requires processing and storage of a huge amount of data. In the context of robotics, the cost of data from real robotics hardware is usually very high, thus solutions that achieve high sample-efficiency are needed. We propose a method that aims at learning a mapping from the observations into a lower-dimensional state space. This mapping is learned with unsupervised learning using loss functions shaped to incorporate prior knowledge of the environment and the task. Using the samples from the state space, the optimal policy is quickly and efficiently learned. We test the method on several mobile robot navigation tasks in a simulation environment and also on a real robot. A video of our experiments can be found at: https://youtu.be/dgWxmfSv95U
Curriculum learning for annotation-efficient medical image analysis: scheduling data with prior knowledge and uncertainty

Convolutional neural networks (CNNs) for multi-class classification require training on large, representative, and high quality annotated datasets. However, in the field of medical imaging, data and annotations are both difficult and expensive to acquire. Moreover, they frequently suffer from highly imbalanced distributions, and potentially noisy labels due to intra- or inter-expert disagreement. To deal with such challenges, we propose a unified curriculum learning framework to schedule the order and pace of the training samples presented to the optimizer. Our novel framework reunites three strategies consisting of individually weighting training samples, reordering the training set, or sampling subsets of data. The core of these strategies is a scoring function ranking the training samples according to either difficulty or uncertainty. We define the scoring function from domain-specific prior knowledge or by directly measuring the uncertainty in the predictions. We perform a variety of experiments with a clinical dataset for the multi-class classification of proximal femur fractures and the publicly available MNIST dataset. Our results show that the sequence and weight of the training samples play an important role in the optimization process of CNNs. Proximal femur fracture classification is improved up to the performance of experienced trauma surgeons. We further demonstrate the benefits of our unified curriculum learning method for three controlled and challenging digit recognition scenarios: with limited amounts of data, under class-imbalance, and in the presence of label noise.
Does rainforest logging threaten marine turtles?

Abstract Industrial logging is expanding rapidly in Central African rainforests. We suggest that logging operations in this region pose an indirect threat to nesting marine turtles, especially the Critically Endangered leatherback turtle Dermochelys coriacea. This occurs because some logs are being lost or abandoned during downriver transport to coastal timber yards; the lost logs float out to sea and then often wash ashore, where they accumulate on beaches used by nesting turtles. We used a light aircraft to survey logs along the entire coastline of Gabon, and also studied the impacts of logs at Pongara Beach, one of the world's most important turtle nesting areas, during the 2002-2003 and 2003-2004 breeding seasons. Nearly 11,000 lost logs were counted along Gabon's beaches, with an estimated commercial value of USD 11.1 million. Logs were unevenly distributed along the coast, reaching a peak density of 247 logs km-1. At Pongara, logs blocked 30.5% of the beach. These logs had a number of negative effects on marine turtles, causing 8-14% of all nesting attempts (n = 2,163) to be aborted or disrupted. Initiatives to remove lost logs and driftwood from critical nesting beaches may be the most effective means to reduce their deleterious impacts on threatened marine turtles.
Prediction of the growth response to elevated CO2 : a search for physiological criteria in closely related grass species.

Using 11 closely related grass species, we tested the capacity of physiological criteria to predict the growth response to elevated CO2 and to categorize the species with regard to their CO2 response. A growth analysis was conducted under productive conditions both at ambient (350 μmol mol-1 ) and elevated (700 μmol mol-1 ) CO2 . The relative growth rate stimulation was regressed against each of the growth rate components measured at ambient CO2 . Growth response to CO2 was positively correlated with specific leaf area (sla, the leaf surface area per unit of leaf weight), leaf area ratio (the leaf area per unit of total plant dry weight) and negatively correlated with net assimilation rate and leaf nitrogen concentration, both per unit of leaf area. We suggest that sla has a predominant role in these relationships. Different hypotheses are proposed and discussed in order to explain why species with low sla are less responsive to elevated CO2 . Neither biomass allocation, relative growth rate, shoot or root specific activities per unit of mass, nor chemical composition were significantly correlated with growth response to CO2 . The four predictive criteria mentioned above coherently differentiate the five wild annual species (higher sla, stronger growth response to CO2 ) from the four wild perennials. The two perennial crop species, with the highest sla, were more responsive than the wild species.