Miracle-dz/UniFAR-FTUs huggingface dataset:
In-silico approaches to sequence and structure based scrutiny of nonsynonymous SNPs and synteny of ACAA2 for its implicated role in metabolomics

The science of metabolomics is exponentially growing with the boost in knowledge base of metabolites and development of bioinformatics data anal- ysis tools. Human ACAA2 gene codes for a 397 amino acid protein, 3- Ketoacyl-CoA thiolase, which is a mitochondrial enzyme responsible for cata- lyzing the thiolytic cleavage of 3-ketoacyl-CoA by thiolase, the last reaction of fatty-acid β-oxidation. Bioinformatics approaches were used to scrutinize the human ACAA2 protein. The tertiary structure of the protein was predicted us- ing a multitude of structure prediction servers including PHYRE2, (PS)-v2, I- TASSER and SAM-T08. Generated structures were then evaluated using ERRAT2, VERIFY3D, PROVE, PROCHECK and MoLProbity servers. PolyPhen-2 and SIFT servers were used to sort the damaging missense SNPs from the tolerable ones. The structural model of mutated sequence was also generated and superimposed on the normal structure using UCSF Chimera in order to find the regions of deviations. PoPMuSiC was used to analyze thermo- dynamic stability changes in mutated structure. Finally, syntenic analysis was performed using Cinteny in order to study the physical co-localization of the genetic loci with the ACAA2 gene. The model generated by PHYRE2 (normal mode) was found to be the best model so far which was selected for further studies. As a result of mutational analysis, substitution of D31Y caused by SNP rs11549282 was found to be damaging. Genomic context of Human and mouse ACAA2 was found to be the same up to 36 genes as predicted by Cinteny. This work will be helpful in detailed comprehension of the role of ACAA2 in fatty acid metabolism related disorders.
Visual Verification and Analysis of Cluster Detection for Molecular Dynamics

A current research topic in molecular thermodynamics is the condensation of vapor to liquid and the investigation of this process at the molecular level. Condensation is found in many physical phenomena, e.g. the formation of atmospheric clouds or the processes inside steam turbines, where a detailed knowledge of the dynamics of condensation processes will help to optimize energy efficiency and avoid problems with droplets of macroscopic size. The key properties of these processes are the nucleation rate and the critical cluster size. For the calculation of these properties it is essential to make use of a meaningful definition of molecular clusters, which currently is a not completely resolved issue. In this paper a framework capable of interactively visualizing molecular datasets of such nucleation simulations is presented, with an emphasis on the detected molecular clusters. To check the quality of the results of the cluster detection, our framework introduces the concept of flow groups to highlight potential cluster evolution over time which is not detected by the employed algorithm. To confirm the findings of the visual analysis, we coupled the rendering view with a schematic view of the clusters' evolution. This allows to rapidly assess the quality of the molecular cluster detection algorithm and to identify locations in the simulation data in space as well as in time where the cluster detection fails. Thus, thermodynamics researchers can eliminate weaknesses in their cluster detection algorithms. Several examples for the effective and efficient usage of our tool are presented.
Non-Cognitive Factors that Contribute to the Black Gender Gap in Community College Persistence

of a dissertation at the University of Miami. Dissertation supervised by Drs. Soyeon Ahn and Carol-Anne Phekoo No. of pages in text (117) Although female college students in the United States from all racial and ethnic groups outperform their male counterparts in key academic areas, including retention and persistence rates, the college persistence gap between Black women and Black men is the widest. The purpose of this study was to explore if there is a difference in intent-to-persist between Black males and Black females, and to identify the role non-cognitive factors may play. The survey results obtained from self-identified Black students at one community college were analyzed using a hierarchical multiple regression with four subsequent blocks to explore the effect on intent-to-persist using student gender, grit, family influences, sociocultural influences, and their interactions as predictors. The results of the study showed that family influence was found to be a significant predictor of persistence, regardless of gender. Also, while the persistence of Black males was virtually unaffected by sociocultural influences, Black female persistence was significantly, negatively affected by the same sociocultural influences. The results suggest that higher education personnel should validate all students but especially community college students who may be nontraditional, Black students should continue to overcome environmental pull while continuing to assertively pursue their academic goals and families should support their college students without exerting excessive pressure. Future research recommendations are provided.
Non-iterative Comprehensive Normalisation

The light reflected from an object depends not only on object colours but also on lighting geometry and illuminant colour.As a consequence the raw colour recorded by a camera is not a reliable cue for object based tasks such as recognition and tracking.One solution to this problem is to find functions of image colours that cancel out dependencies due to illumination.While many invariant functions cancel out either dependency due to geometry or dependency due to illuminant colour,only the comprehensive normalisation has been shown (theoretically and experimentally)to cancel both. However,this invariance is bought at the price of an iterative procedure. In this paper we develop a non iterative log comprehensive normalisation procedure.We begin by reviewing the idea that lighting effects due to geometry and light colour can,under certain reasonable simplifying assumptions,both be modelled using simple scalar multipliers.We nowtake logarithms and turn geometry and light colour dependency into additive processes.We show how in this log color space two simple projection operators lead to invariance to geometry and light colour. Moreover,because projection operators are idempotent, illuminant invariance is achieved in a single step. Experiments demonstrated that log comprehensive normalisation used as a preprocessing step supports accurate colour based object recognition independent of lighting conditions.
The effects of bone density and crestal cortical bone thickness on micromotion and peri-implant bone strain distribution in an immediately loaded implant: a nonlinear finite element analysis

Purpose This study investigated the effects of bone density and crestal cortical bone thickness at the implant-placement site on micromotion (relative displacement between the implant and bone) and the peri-implant bone strain distribution under immediate-loading conditions. Methods A three-dimensional finite element model of the posterior mandible with an implant was constructed. Various bone parameters were simulated, including low or high cancellous bone density, low or high crestal cortical bone density, and crestal cortical bone thicknesses ranging from 0.5 to 2.5 mm. Delayed- and immediate-loading conditions were simulated. A buccolingual oblique load of 200 N was applied to the top of the abutment. Results The maximum extent of micromotion was approximately 100 μm in the low-density cancellous bone models, whereas it was under 30 μm in the high-density cancellous bone models. Crestal cortical bone thickness significantly affected the maximum micromotion in the low-density cancellous bone models. The minimum principal strain in the peri-implant cortical bone was affected by the density of the crestal cortical bone and cancellous bone to the same degree for both delayed and immediate loading. In the low-density cancellous bone models under immediate loading, the minimum principal strain in the peri-implant cortical bone decreased with an increase in crestal cortical bone thickness. Conclusions Cancellous bone density may be a critical factor for avoiding excessive micromotion in immediately loaded implants. Crestal cortical bone thickness significantly affected the maximum extent of micromotion and peri-implant bone strain in simulations of low-density cancellous bone under immediate loading.
Implementing a Java JIT compiler in Haskell: case study

We present a JVM prototype implemented in the purely-functional language Haskell. It exploits several features of the language, such as strong static typing to implement an intermediate representation, and abstraction mechanism to express machine code generation in the manner of a domain specific language. The compiler consists of (i) a pass to transform Java bytecode to a register-based intermediate representation, (ii) application of an existing data-flow analysis framework to our intermediate representation and (iii) machine code generation that targets the x86 architecture. The implementation follows a compile-only approach. To implement certain Java features efficiently, code patching is used. Various code samples demonstrate the elegance of our prototype. Results prove reasonable performance compared to real-world implementations.
Image browsing using hierarchical clustering

Digital images and video clips are becoming popular due to the increase in the availability of consumer devices that capture digital images and video clips. Digital content is also growing over the Internet. The increase of the digital content creates a need for user-friendly tools to browse through large volumes of digital material. We present a clustering-based browsing algorithm. Images are automatically clustered using a hierarchical clustering algorithm and users can then browse through the images by navigating the tree structure that results from the clustering. We have tested the algorithm on a large number of images.
Evaluation of Microbial Bacterial and Fungal Diversity in Cerebrospinal Fluid Shunt Infection

Background Cerebrospinal fluid shunt infection can be recalcitrant. Recurrence is common despite appropriate therapy for the pathogens identified by culture. Improved diagnostic and therapeutic approaches are required, and culture-independent molecular approaches to cerebrospinal fluid shunt infections have not been described. Objectives To identify the bacteria and fungi present in cerebrospinal fluid from children with cerebrospinal fluid shunt infection using a high-throughput sequencing approach, and to compare those results to those from negative controls and conventional culture. Methods This descriptive study included eight children ≤18 years old undergoing treatment for culture-identified cerebrospinal fluid shunt infection. After routine aerobic culture of each cerebrospinal fluid sample, deoxyribonucleic acid (DNA) extraction was followed by amplification of the bacterial 16S rRNA gene and the fungal ITS DNA region tag-encoded FLX-Titanium amplicon pyrosequencing and microbial phylogenetic analysis. Results The microbiota analyses for the initial cerebrospinal fluid samples from all eight infections identified a variety of bacteria and fungi, many of which did not grow in conventional culture. Detection by conventional culture did not predict the relative abundance of an organism by pyrosequencing, but in all cases, at least one bacterial taxon was detected by both conventional culture and pyrosequencing. Individual bacterial species fluctuated in relative abundance but remained above the limits of detection during infection treatment. Conclusions Numerous bacterial and fungal organisms were detected in these cerebrospinal fluid shunt infections, even during and after treatment, indicating diverse and recalcitrant shunt microbiota. In evaluating cerebrospinal fluid shunt infection, fungal and anaerobic bacterial cultures should be considered in addition to aerobic bacterial cultures, and culture-independent approaches offer a promising alternative diagnostic approach. More effective treatment of cerebrospinal fluid shunt infections is needed to reduce unacceptably high rates of reinfection, and this work suggests that one effective strategy may be reduction of the diverse microbiota present in infection.
Human Flesh Search Model Incorporating Network Expansion and GOSSIP with Feedback

With the development of on-line forum technology and the pervasive participation of the public, the Human Flesh Search is becoming an arising phenomenon which makes a great impact on our daily life. There arose big research interests in social, legal issues resulted from HFS, however, very little work has been conducted to understand how it comes into being and how it dynamically evolves. This paper proposes a modeling and simulation approach incorporating network expansion and GOSSIP propagation with feedback for a better understanding of the human flesh search phenomenon. Based on the acquisition and analysis of the netizens’ surfing behavior data, the evolution of the HFS is modeled as a network growth process with proper dynamic input, which is characterized by heavy-tail and burst-oriented distribution, modeling as a Weibulloid process. Then, an improved GOSSIP model with feedback is proposed to represent the information propagation, processing and aggregation during the HFS. New insights for HFS are gained through a set of simulation experiments.
Video Stabilization for Micro Air Vehicles

In Today’s world, Micro Air Vehicles (MAVs) equipped with digital cameras are increasing in number for real time applications. MAVs are widely used because of small, low weight, low cost and flexibility in the design. However, the video captured by MAVs will consist of unwanted translations and rotations due to atmospheric conditions. Hence, a video stabilization algorithm is needed to compensate the frames and then to avoid losing of any valuable information in video. This paper presents a real time video stabilization algorithm and mainly consists of three steps. Firstly, the key points from each frame are calculated by using Harris Corner Detection algorithm. Secondly, the descriptors between the two frames are used to calculate the affine transformation. Finally, this affine transformation is used to compensate the two successive frames in a video. This work mainly focuses on the digital image processing based video stabilization. The programming was primarily using MATLAB and later the algorithm was implemented on Raspberry Pi using Opencv-Python Programming.
Backlog and Delay Reasoning in HARQ System

Recently, hybrid-automatic-repeat-request (HARQ) systems have been favored in particular state-of-the-art communications systems since they provide the practicality of error detections and corrections aligned with repeat-requests when needed at receivers. The queueing characteristics of these systems have taken considerable focus since the current technology demands data transmissions with a minimum delay provisioning. In this paper, we investigate the effects of physical layer characteristics on data link layer performance in a general class of HARQ systems. Constructing a state transition model that combines queue activity at a transmitter and decoding efficiency at a receiver, we identify the probability of clearing the queue at the transmitter and the packet-loss probability at the receiver. We determine the effective capacity that yields the maximum feasible data arrival rate at the queue under quality-ofservice constraints. In addition, we put forward non-asymptotic backlog and delay bounds. Finally, regarding three different HARQ protocols, namely Type-I HARQ, HARQ-chase combining (HARQ-CC) and HARQ-incremental redundancy (HARQ-IR), we show the superiority of HARQ-IR in delay robustness over the others. However, we further observe that the performance gap between HARQ-CC and HARQ-IR is quite negligible in certain cases. The novelty of our paper is a general cross-layer analysis of these systems, considering encoding/decoding in the physical layer and delay aspects in the data-link layer.
Experimental Identification and Analysis of the Dynamics of a PHANToM Premium 1.5A Haptic Device

The dynamics of a PHANToM Premium 1.5A haptic device from SensAble Technologies, Inc. is experimentally identified and analyzed for different installations of the device and its accessories, such as the typical upright, upside down, with gimbal and counterbalance weight, and with force sensor.1 An earlier formulation of the robot dynamic model is augmented with a friction model, linearly parameterized, and experimentally identified using least squares. The identified dynamics are experimentally evaluated with an inverse dynamics controller and verified by comparing user hand force estimates with the measured values. The contribution of different dynamic terms such as inertial, Coriolis and centrifugal, gravitational, and Coulomb and viscous friction are demonstrated and discussed. The identified model can be used for a variety of haptic applications, such as hand force estimation, accurate active gravity compensation and counterbalance weight determination for various installation conditions, and model-based control for haptic simulation and teleoperation.
A protocol for instruction stream processing

The behaviour produced by an instruction sequence under execution is a behaviour to be controlled by some execution environment: each step performed actuates the processing of an instruction by the execution environment and a reply returned at completion of the processing determines how the behaviour proceeds. In this paper, we are concerned with the case where the processing takes place remotely. We describe a protocol to deal with the case where the behaviour produced by an instruction sequence under execution leads to the generation of a stream of instructions to be processed and a remote execution unit handles the processing of that stream of instructions.
Vascular Smooth Muscle Cells Undergo Telomere-Based Senescence in Human Atherosclerosis: Effects of Telomerase and Oxidative Stress

Although human atherosclerosis is associated with aging, direct evidence of cellular senescence and the mechanism of senescence in vascular smooth muscle cells (VSMCs) in atherosclerotic plaques is lacking. We examined normal vessels and plaques by histochemistry, Southern blotting, and fluorescence in situ hybridization for telomere signals. VSMCs in fibrous caps expressed markers of senescence (senescence-associated β-galactosidase [SAβG] and the cyclin-dependent kinase inhibitors [cdkis] p16 and p21) not seen in normal vessels. In matched samples from the same individual, plaques demonstrated markedly shorter telomeres than normal vessels. Fibrous cap VSMCs exhibited markedly shorter telomeres compared with normal medial VSMCs. Telomere shortening was closely associated with increasing severity of atherosclerosis. In vitro, plaque VSMCs demonstrated morphological features of senescence, increased SAβG expression, reduced proliferation, and premature senescence. VSMC senescence was mediated by changes in cyclins D/E, p16, p21, and pRB, and plaque VSMCs could reenter the cell cycle by hyperphosphorylating pRB. Both plaque and normal VSMCs expressed low levels of telomerase. However, telomerase expression alone rescued plaque VSMC senescence despite short telomeres, normalizing the cdki/pRB changes. In vivo, plaque VSMCs exhibited oxidative DNA damage, suggesting that telomere damage may be induced by oxidant stress. Furthermore, oxidants induced premature senescence in vitro, with accelerated telomere shortening and reduced telomerase activity. We conclude that human atherosclerosis is characterized by senescence of VSMCs, accelerated by oxidative stress-induced DNA damage, inhibition of telomerase and marked telomere shortening. Prevention of cellular senescence may be a novel therapeutic target in atherosclerosis.
Status, Quality and Attention: What’s in a (Missing) Name? ∗

How much are we inﬂuenced by an author’s identity when evaluating their work? This paper addresses this question in the context of open standards development. We exploit a natural experiment, whereby author names were occasionally replaced by et al in a series of email messages used to announce new submissions to the Internet Engineering Task Force (IETF). By comparing the eﬀect of obscuring high versus low status author names, we measure the impact of status signals on the IETF publication process. Our results suggest that name-based signals can explain up to three-quarters of the diﬀerence in publication outcomes across status cohorts. However, this signaling eﬀect disappears for a set of pre-screened proposals that receive more scrutiny than a typical submission. We also show that working papers from high status authors receive more attention on electronic discussion boards, which may help in developing these ideas and bringing them forward to publication.
DeLorean: Recording and Deterministically Replaying Shared-Memory Multiprocessor Execution Ef?ciently

Support for deterministic replay of multithreaded execution can greatly help in finding concurrency bugs. For highest effectiveness, replay schemes should (i) record at production-run speed, (ii) keep their logging requirements minute, and (iii) replay at a speed similar to that of the initial execution. In this paper, we propose a new substrate for deterministic replay that provides substantial advances along these axes. In our proposal, processors execute blocks of instructions atomically, as in transactional memory or speculative multithreading, and the system only needs to record the commit order of these blocks. We call our scheme DeLorean. Our results show that DeLorean records execution at a speed similar to that of release consistency (RC) execution and replays at about 82% of its speed. In contrast, most current schemes only record at the speed of Sequential Consistency (SC) execution. Moreover, DeLorean only needs 7.5% of the log size needed by a state-of-the-art scheme. Finally, DeLorean can be configured to need only 0.6% of the log size of the state-of-the-art scheme at the cost of recording at 86% of RCpsilas execution speed - still faster than SC. In this configuration, the log of an 8-processor 5-GHz machine is estimated to be only about 20GB per day.
Multi-view Laplacian sparse feature selection for web image annotation

Recently, semi-supervised sparse feature selection, which can exploit the large number unlabeled data and small number labeled data simultaneously, has placed an important role in web image annotation. However, most of the semi-supervised feature selection methods are developed for single-view data, which can not reveal and leverage the correlated and complemental information between different views. Recently, multi-view learning has obtained much research attention, so we apply multi-view learning into semi-supervised sparse feature selection and propose a multi-view semi-supervised sparse feature selection method based on graph Laplacian, namely Multi-view Laplacian Sparse Feature Selection (MLSFS) in this paper. MLSFS can realize sparse feature selection by utilizing the correlated and complemental information between different views. A simple iterative method is proposed to solve the objective function of MLSFS. We apply our algorithm into image annotation and conduct experiments on two web image datasets. The results show that the proposed multi-view method outperforms the single-view methods.