Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel approach to segregate and identify functional loop regions in protein structures using their Ramachandran maps

The loops which connect or flank helices/sheets in protein structures are known to be functionally important. However, ironically they also belong to the part of protein whose structure is least accurately predicted. Here, a new method to isolate and analyze loop regions in protein structure is proposed using the spatial coordinates of the solved three‐dimensional structure. The extent of dispersion among points of successive amino acid residues in the Ramachandran map of protein region is utilized to calculate the Mean Separation between these points in the Ramachandran Plot (MSRP). Based on analysis of 2935 protein secondary structure regions obtained using DSSP software, spanning a range from 2 to 64 residues, taken from a set of 170 proteins, it is shown that helices (MSRP < 17) and strands (MSRP < 64) stand effectively demarcated from the loop regions (MSRP > 130). Analysis of 43 DNA binding and 98 ligand binding proteins revealed several loop regions with clear change in MSRP subsequent to binding. The population of such loops correlated with the magnitude of backbone displacement in the protein subsequent to binding. Can changes in MSRP quantify the temporal oscillations in dihedral angles among structured/unstructured regions in proteins? Molecular dynamics simulations (10 ns) revealed that deviations in MSRP among different snapshots in the trajectory were at least twofold higher for unstructured proteins in comparison with ordered proteins. The above results validate the use of MSRP parameter as a tool to identify and investigate functionally active loops and unstructured regions in protein structures. Proteins 2010. © 2009 Wiley‐Liss, Inc.
A novel generative encoding for evolving modular, regular and scalable networks

In this paper we introduce the Developmental Symbolic Encoding (DSE), a new generative encoding for evolving networks (e.g. neural or boolean). DSE combines elements of two powerful generative encodings, Cellular Encoding and HyperNEAT, in order to evolve networks that are modular, regular, scale-free, and scalable. Generating networks with these properties is important because they can enhance performance and evolvability. We test DSE's ability to generate scale-free and modular networks by explicitly rewarding these properties and seeing whether evolution can produce networks that possess them. We compare the networks DSE evolves to those of HyperNEAT. The results show that both encodings can produce scale-free networks, although DSE performs slightly, but significantly, better on this objective. DSE networks are far more modular than HyperNEAT networks. Both encodings produce regular networks. We further demonstrate that individual DSE genomes during development can scale up a network pattern to accommodate different numbers of inputs. We also compare DSE to HyperNEAT on a pattern recognition problem. DSE significantly outperforms HyperNEAT, suggesting that its potential lay not just in the properties of the networks it produces, but also because it can compete with leading encodings at solving challenging problems. These preliminary results imply that DSE is an interesting new encoding worthy of additional study. The results also raise questions about which network properties are more likely to be produced by different types of generative encodings.
Glass fibre polyester composite with in vivo vascular channel for use in self-healing

The embedment of adhesive-filled hollow glass fibres (HGF) has been reported as a way of combating micro-crack development in fibre-reinforced polymer (FRP) structures. However, hollow fibres can critically undermine the effectiveness of self-healing systems and have been reported to be a potential impediment to the healing agent flow path. On the other hand, attempting to use non-hollow vascular systems in higher dimensions has largely been restricted to bulk polymers that lack reinforcing fibres. This paper investigates an alternative technique where a simple two-dimensional (2D) network of hollow channels is created within a glass-fibre-reinforced polyester-composite structure. The network is created using a fugitive preforming material at the ply level of interest, similar to a direct ink writing procedure. The temporary structure is extracted as a part of the curing and post-curing processes. The channels formed are used to deliver cyanoacrylate adhesive (CA) to areas that have been damaged under a flexural three-point bending test. Subsequent post-repair mechanical testing, under the same mode, evaluates the success of the repair process. The results show good recovery of the stiffness, a paramount mechanical property, and indicate how the grade of the repairing agent used influences the recovered loading strength of the FRP samples.
Design and applications of digital diffractive gratings

This paper will report our recent works on fabrication, evaluation, and applications of gratings. We are using the Dammann parallel laser writing facility for fabrication of gratings. High-efficiency reflective gratings and large-sized grating are fabricated. We have fabricated high-power reflective laser vortex grating with expectation of a new laser drilling effect for laser fusion in the future, which is just evaluated by our developed method. These gratings are essential elements for high-power laser systems and other high-demanding metrology applications.
Journal of Graph Algorithms and Applications a Graph Drawing Application to Web Site Traffic Analysis

Web site traffic analysis studies how different pages forming Web sites are accessed by their target audience over time. From a business intelligence point of view, it represents one of the key activities for many private companies and public institutions. Recent papers pointed out that Web site traffic analysis is especially useful if it focuses on the user interest into the relevant concepts described in a Web site rather than counting user accesses to the distinct pages forming the Web site. This paper extends existing measures of conceptual Web site traffic analysis and describes a new system that supports this analysis by means of graph visualization techniques. The graph drawing engine of the system is a force-directed heuristic that computes a simultaneous embedding of two suitably defined graphs, that are non-planar in general. The heuristic is especially designed to take into account two important aesthetic criteria of the drawing: crossing resolution and geodesic edge tendency. We also present some experiments and case studies to show the effectiveness of the proposed approach in practice. AlgoDEEP Prot.2008TFBWL4. Since the grant is related to an industrial project, we cannot distribute the system. Also the real data sources used for testing the system cannot be revealed (as specified in the paper). However, in order to witness that the system is really working, we have produced a movie. It can be downloaded at the following URL: abstract of this research titled " Graph Vi-sualization Techniques for Conceptual Web-traffic Analysis " appears in the proceedings of the 3rd IEEE Pacific Visualization Symposium (PacificVis 2010).
A Qualitative Study Exploring Barriers Related to Use of Footwear in Rural Highland Ethiopia: Implications for Neglected Tropical Disease Control

Background The role of footwear in protection against a range of Neglected Tropical Diseases (NTDs) is gaining increasing attention. Better understanding of the behaviors that influence use of footwear will lead to improved ability to measure shoe use and will be important for those implementing footwear programs. Methodology/Principal Findings Using the PRECEDE-PROCEED model we assessed social, behavioral, environmental, educational and ecological needs influencing whether and when children wear shoes in a rural highland Ethiopian community endemic for podoconiosis. Information was gathered from 242 respondents using focus groups, semi-structured interviews and extended case studies. Shoe-wearing norms were said to be changing, with going barefoot increasingly seen as ‘shameful’. Shoes were thought to confer dignity as well as protection against injury and cold. However, many practical and social barriers prevented the desire to wear shoes from being translated into practice. Limited financial resources meant that people were neither able to purchase more than one pair of shoes to ensure their longevity nor afford shoes of the preferred quality. As a result of this limited access, shoes were typically preserved for special occasions and might not be provided for children until they reached a certain age. While some barriers (for example fit of shoe and fear of labeling through use of a certain type of shoe) may be applicable only to certain diseases, underlying structural level barriers related to poverty (for example price, quality, unsuitability for daily activities and low risk perception) are likely to be relevant to a range of NTDs. Conclusions/Significance Using well established conceptual models of health behavior adoption, we identified several barriers to shoe wearing that are amenable to intervention and which we anticipate will be of benefit to those considering NTD prevention through shoe distribution.
Heart Rate Variability and Sensorimotor Polyneuropathy in Type 1 Diabetes

OBJECTIVE Reduced heart rate variability (HRV) is classically viewed as an early phenomenon in diabetic sensorimotor polyneuropathy (DSP). We aimed to determine the characteristics of HRV across the spectrum of clinical DSP in type 1 diabetes. RESEARCH DESIGN AND METHODS Eighty-nine diabetic subjects and 60 healthy volunteers underwent assessment of RR interval variation (RRvar) during deep breathing and clinical and electrophysiological examination. We examined the distribution of age-standardized RRvar across the spectrum of clinical DSP, identified variables associated with RRvar in multivariate regression, and compared RRvar with validated measures of neuropathy. RESULTS Age-standardized RRvar had a significant, step-wise, inverse relationship with ordinal categories of increasing DSP severity (β = −5.4, P < 0.0001) among subjects with diabetes. Case subjects with DSP had substantially lower age-standardized RRvar compared with diabetic control subjects without DSP (β = −5.2, P < 0.01), although there was substantial overlap of RRvar between diabetic case subjects and control subjects and the healthy volunteer cohort. In multivariate analysis, advanced age was independently associated with lower RRvar in both healthy volunteers and diabetic subjects, whereas higher glycated hemoglobin A1c and systolic blood pressure were independently associated with lower RRvar in diabetic subjects. RRvar had a significant association with validated measures of large and small fiber neuropathy. CONCLUSIONS HRV may be a biomarker for clinical DSP and is associated cross-sectionally with both early and late measures of neuropathy. The low HRV observed in some control subjects without DSP and in most case subjects with severe DSP may signify that HRV has different prognostic implications in these groups, requiring further longitudinal study.
Determination of Optimal Microminiature Powder Injection Molding Parameters by Taguchi Approach

The global manufacturing trend is now focusing towards miniaturization. Microminiature Powder Injection Molding (μPIM) is a viable technology to fabricate complex and high performance miniaturized components. The μPIM technique was used to produce the near-net shape micro components in this study. Fine stainless steel powder with particle size of 5μm was mixed with a ternary water-based binder system. Micro dumbbells with the largest dimension of 9mm were replicated. In order to obtain successful and well molded micro dumbbells, the Design of Experiments (DOE) technique was applied to investigate the optimal parameters in injection molding process. Injection parameters such as injection pressure (A), injection temperature (B), powder loading (C), mold temperature (D), injection time (E) and holding time (F) were optimized by using stainless steel feedstocks. Taguchi approach is chosen and the results were evaluated with signal-to-noise (SN) ratio and analysis of variance (ANOVA). The results show that the feedstocks could be replicated by using μPIM method with the application of Taguchi approach.
Coding variant Met72Thr in the PEDF gene and risk of neovascular age-related macular degeneration and polypoidal choroidal vasculopathy

Purpose Using a candidate-gene approach, a recent case-control study identified a previously unknown association between neovascular age-related macular degeneration (AMD) and the coding Met72Thr variant in the pigment epithelium-derived factor (PEDF) gene in a Taiwan Chinese population. However, a subsequent replication study failed to see this association in a white European population. We noted an important difference in the sample ascertainment scheme between these two studies. The original study did not consider findings of indocyanine green (ICG) angiography for disease classification, which is the only way to obtain a clear image of polypoidal choroidal vasculopathy (PCV) lesions. This suggests that their cohort might include a considerable amount of PCV, given its high prevalence in the Chinese population. In contrast, the replication study intentionally excluded PCV from the case cohort on the basis of ICG angiograms. Therefore, the inconsistent finding might be caused by potential sample heterogeneity between these two studies. In this respect, this association needed to be examined in a case series of clearly defined individuals with neovascular AMD and PCV. The aim of this study was to validate the previously reported association of the PEDF Met72Thr variant in a well characterized Japanese population with neovascular AMD and PCV. Methods We genotyped the Met72Thr variant (rs1136287) in 116 patients with neovascular AMD, 140 patients with PCV, and 189 control participants in a Japanese population. Genotyping was performed using TaqMan technology. We tested for an association of this variant with neovascular AMD and PCV separately. We also evaluated population stratification in our study cohort. Results We found no statistically significant evidence for association between rs1136287 and either neovascular AMD or PCV under any genetic models (trend, genotypic, dominant, and recessive genetic models; p>0.05). Population structure analyses excluded stratification artifact in our study population. Conclusions We report a lack of association between the PEDF Met72Thr variant and either neovascular AMD or PCV in a Japanese population. We conclude that the Met72Thr variant does not play a significant role in the risk of developing neovascular AMD or PCV.
Fully automatic cross-associations

Large, sparse binary matrices arise in numerous data mining applications, such as the analysis of market baskets, web graphs, social networks, co-citations, as well as information retrieval, collaborative filtering, sparse matrix reordering, etc. Virtually all popular methods for the analysis of such matrices---e.g., k-means clustering, METIS graph partitioning, SVD/PCA and frequent itemset mining---require the user to specify various parameters, such as the number of clusters, number of principal components, number of partitions, and "support. " Choosing suitable values for such parameters is a challenging problem.Cross-association is a joint decomposition of a binary matrix into disjoint row and column groups such that the rectangular intersections of groups are homogeneous. Starting from first principles, we furnish a clear, information-theoretic criterion to choose a good cross-association as well as its parameters, namely, the number of row and column groups. We provide scalable algorithms to approach the optimal. Our algorithm is parameter-free, and requires no user intervention. In practice it scales linearly with the problem size, and is thus applicable to very large matrices. Finally, we present experiments on multiple synthetic and real-life datasets, where our method gives high-quality, intuitive results.
Harmonic analysis approach based on wavelet transform and neural network

The paper presents a new approach based on wavelet and neural network for the estimation of harmonic components in the power system. This proposed method preprocesses the signal using wavelet analysis to get feature extraction of signals. Then it analyses and calculates the feature vector by the artificial neural network (ANN), and the harmonic components of the current can be got. The combination of wavelet and ANN make up for each other's deficiencies and it can solve the frequency aliasing effectively. The structure of this method and the specific algorithm are presented. The simulation model is also built and the results show that the harmonic components can be detected at real time with high precision.
Cooperative communications with relay-selection: when to cooperate and whom to cooperate with?

In this paper; we propose a new cooperative communication protocol, which achieves higher bandwidth efficiency while guaranteeing the same diversity order as that of the conventional cooperative schemes. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. In particular, we discuss the multi-node decode-and-forward cooperative scenarios, where arbitrary N relays are available. The source determines when it needs to cooperate with one relay only, and which relay to cooperate with in case of cooperation, i.e., "When to cooperate? " and "Whom to cooperate with? ". An optimal relay is the one which has the maximum instantaneous scaled harmonic mean functionof its source-relay and relay-destination channel gains. For the symmetric scenario, we derive an approximate expression of the bandwidth efficiency and obtain an upper bound on the symbol error rate (SER) performance. We show that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Moreover, we present the tradeoff between the achievable bandwidth efficiency and the corresponding SER. Finally, the obtained analytical results are verified through computer simulations.
Hardware isolation technique for IRC-based botnets detection

Botnets are widely considered one of the most dangerous threats on the internet due to their modular and adaptive nature which makes them difficult to defend against. In contrast to previous generations of malicious codes, botnets have a command and control (C2) infrastucture which allows them to be remotely controlled by their masters. A command and control infrastructure based on Internet Relay Chat protocol (IRC-based C2) is one of the most popular C2) infrastructures botnet creators use to deploy their botnets' malwares (IRC botnets). In this paper, we propose a novel approach to detect and eliminate IRC botnets. Our approach consists of inserting a reconfigurable hardware isolation layer between the network link and the target. Our reconfigurable hardware is an FPGA System-on-Chip (FPGA SoC) that uses both anomaly-based detection and signature-based detection approaches to identify IRC botnets. Since, unlike other viruses, to be able to freely communicate with their masters, botnets' primary objective is to disable any protection mechanism (firewalls, antivirus applications) found on the target machine; our hardware-based isolation infrastructure presents an improvement over existing software-based solutions.We evaluated our architecture codenamed BotPGA using real-world IRC botnets' non-encrypted network traces. The results show that BotPGA can detect real-world non-encrypted malicious IRC traffic and botnets with high accuracy.
The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach

We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-built portion of a map, or is exploring new territory. This is a difficult decision problem, requiring the probability of being outside of the current known map. To estimate this probability, we model the structure of a "typical" environment as a hidden Markov model that generates sequences of views observed by a robot navigating through the environment. A Dirichlet prior over structural models is learned from previously explored environments. Whenever a robot explores a new environment, the posterior over the model is estimated by Dirichlet hyperparameters. Our approach is implemented and tested in the context of multi-robot map merging, a particularly difficult instance of the revisiting problem. Experiments with robot data show that the technique yields strong improvements over altemative methods.
Towards a novel approach of structural schema matching

Modern enterprise system landscapes leverage heterogeneous applications. In order to launch and maintain communication, matching the schema of these diverse applications is of key importance. Since the manual matching of schemas is time-consuming and error prone, only the application of automated schema matchers constitute a viable solution to this problem. Several solutions are available to solve this problem, but an unwelcome common characteristic of them is that their accuracy may become mediocre under certain conditions; consequently an expensive follow-on human correctional step cannot be omitted. We would like to improve the performance of schema matchers so as to reduce costs. In this paper, we present our new schema matching solution, which is based on a unique structural matching approach which takes into account the similarity of neighboring nodes. Our schema matcher also makes use of our related terms set comparison approach, which we have separately tested and later integrated into a complex hybrid schema matcher.
Behavior based autonomous navigation using passages as landmarks for path definition

This work presents a solution to a mobile robot autonomous navigation utilizing minimum representation of the environment. It is done under simulation of a differential wheels robot inside a 2D environment with a layout very close to a real situation for laboratories, offices and classrooms. The solution takes into consideration local and long run navigation and utilizes only behavior-based architecture. A first approach utilizes only reactive behaviors solving very well local navigation. It also gives a partial solution to long run navigation in a simple environment, with only two rooms, doing that without path definition. A complete solution for an environment with many rooms is developed adding to the previous approach more behaviors that will take care of path definition and control. A linear graph, having the passages as landmarks, structures the environment representation and is the basis for the algorithm of path definition that gives an efficient solution. The approach used does not show a central planner and controller as in traditional deliberative architectures; planning and control arises from the independent parallel functioning of all the behaviors.
A novel force sensing integrated into the trocar for minimally invasive robotic surgery

Minimally invasive robotic surgery holds a fundamental role in modern surgery. However, one of its major limitations compared to classic laparoscopy is that the surgeon can only rely on visual perception, for the lack of haptic force feedback. A new solution for a force sensor placed at the end-tip of the trocar is presented here. This solution allows measuring the interaction forces between the surgical instrument and the environment without any changes to the instrument structure and with full adaptability to different robot platforms and surgical tools. A prototype of the sensor has been realized with 3D printed technology for a proof of concept. The static and dynamic characterization of the sensor is provided together with experimental validation.