Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular mechanisms of cell polarity in fission yeast.

The fission yeast, Schizosaccharomyces pombe, is a cylindrical cell formed as a consequence of highly polarised growth at precisely opposed cell ends. The aim of this thesis has been to understand the mechanisms by which fission yeast maintains growth sites at precisely opposed positions in the cell. I have characterised a transposable element Tfl for its application in tagged mutagenesis, to try and develop a useful method to identify new genes required for linear cell growth. Tfl integration was found to be significantly biased towards non-coding regions. It has a preference for the 5' ends of open reading frames but appears not to interfere with transcription of adjacent genes. These findings demonstrated that Tfl is not a useful tool for insertional mutagenesis. The cell end marker tea1p is important in fission yeast for growth in a straight line and I have investigated its role in linear cell growth as well as its delivery and localisation to the cell ends. Tea1p is loaded on microtubules in the vicinity of the nucleus and is transported to the cell ends on the plus ends of microtubules. Transport depends on mal3p but not tea2p and tip1p, all three of these proteins are associated with the plus ends of microtubules. A structure-function analysis of tea1p has identified a domain required for maintaining tea1p at the cell ends, and this domain has been used as the bait in a two-hybrid screen to identify tea1p interacting partners. The analysis has also revealed that tea1p has two distinct functions in the cell. On the tips of microtubules tealp organises the microtubular cytoskeleton, and at the cell ends it functions as a scaffold for other morphogenetic factors, which position the growth machinery properly so that growth is in a straight line.
Lane and road detection based on colorful image

A new method of structureless road detection based on colorful image was presented.The image was first divided into several small foursquare areas.And then,the characteristic information of road was gotten from the area which is assumed to be the road area.According to these information,the small foursquare areas could be classified.Using the method of self-motion threshold segmentation,each of the foursquare areas which include the shoulder of a road,were segmented into the road area and the other area.Lastly,the spots inside the road and the disconnected areas outside the road were eliminated.This method avoids analyzing each pixel of image.It performs with less calculation and higher speed,and satisfies robust real-time basically.It also resists the effect of shadows and water marks.
Combinatorial code analysis for understanding biological regulation

An important mechanism to achieve regulatory specificity in diverse biological processes is through the combinatorial interplay between different regulators, such as amongst transcription factors (TFs) during transcriptional regulation or between RNA binding proteins (RBPs) and microRNAs (miRNAs) during transcript degradation control. To advance our understanding of combinatorial regulation, we developed a computational pipeline called CCAT (Combinatorial Code Analysis Tool) for predicting genome-wide co-binding between biological regulators. In the first part of this thesis, we applied CCAT to the D. melanogaster genome to uncover cooperativity amongst TFs during embryo development. Using publiclyavailable TF binding specificity data and DNaseI chromatin accessibility data, we first predicted genome-wide binding sites for 324 TFs across five stages of D. melanogaster embryo development. We then applied CCAT in each of these developmental stages, and identified from 20 to 60 pairs of TFs in each stage whose predicted binding sites are significantly co-localized. Several of the co-binding pairs we found correspond to TFs that are known to work together. Further, pairs of binding sites predicted to cooperate were found to be consistently enriched in their evolutionarily conservation and their tendency to be found in regions bound in relevant ChIP experiments. Finally, we found that TFs tend to be co-localized with other TFs in a dynamic manner across developmental stages. In the second part of this thesis, we applied CCAT to explore whether RBPs and miRNAs cooperate to promote transcript decay. We concentrated on five highly conserved RBP motifs in human 3UTRs. A specific group of miRNA recognition sites were enriched within 50 nts from the RBP recognition sites for PUM and UAUUUAU. The presence of both a PUM recognition site and a recognition site for preferentially co-occurring miRNAs was associated with faster decay of the associated transcripts. For PUM and its co-occurring miRNAs, binding of the RBP to its recognition sites was iii predicted to release nearby miRNA recognition sites from RNA secondary structures. Overall, our CCAT analyses suggest that a specific set of RBPs and miRNAs work together to affect transcript decay, with the release of miRNA recognition sites via RBP binding as one possible model of cooperativity. Our pipeline provides a general tool for identifying combinatorial cooperativity in biological regulation. All generated data as well as source code are available at: http://cat.princeton. edu.
A Convolutional Network for Sleep Stages Classification

Sleep stages classification is a crucial task in the context of sleep studies. It involves the simultaneous analysis of multiple signals recorded during sleep. However, it is complex and tedious, and even the trained expert can spend several hours scoring a single night recording. Multiple automatic methods have tried to solve these problems in the past, most of them by classifying a feature vector that is engineered for a specific dataset. In this work, we avoid this bias using a deep learning model that learns relevant features without human intervention. Particularly, we propose an ensemble of 5 convolutional networks that achieves a kappa index of 0.83 when classifying a dataset of 500 sleep recordings.
Term Relatedness from Wiki-Based Resources Using Sourced PageRank

This dissertation concerns itself with creating a new algorithm for automatically measuring the amount of relatedness between a given pair of terms. Research into term relatedness is important because it has been empirically demonstrated that using relatedness metrics can improve the performance of tasks in Natural Language Processing and Information Retrieval by expanding the usable vocabulary. Previous relatedness metrics have used a variety of sources of semantic data to judge term relatedness, including text corpora, expertly-constructed resources and, most recently, Wikipedia and Wiktionary. The primary focus of this dissertation is the creation of a new metric for deriving term relatedness from the graph structure of Wikipedia and Wiktionary using Sourced PageRank, a modified version of the PageRank algorithm, to generate the relatedness values. This new algorithm is compared to several existing relatedness metrics in two established task domains. The first domain measures the metric’s ability to replicate humangenerated relatedness values for term pairs. The second domain tests a metric’s ability to select the synonym of a given term from a list of possible candidates. In both of these experiments, the Sourced PageRank-based term relatedness algorithm that uses Wiktionary as its source of semantic data is able to compete with or exceed the performance of existing state-of-the-art algorithms in these task domains. Additionally, the different emphases of Wikipedia and Wiktionary are covered as part of this dissertation. This is an area that has not been emphasized in past work with Wiki-based
Automatic Garment Modeling From Front And Back Images

We present a system which can automatically generate a realistic garment model from two images of an existing garment. Without the requirement of tailoring expertise and tedious operation, our method takes the front and back images of a real garment as input, and the system will make reasonable geometric modeling as well as physical simulation of the garment. Combining with mannequin’s skeleton information, we propose a panel positioning method to place garment panels in appropriate positions. A key feature of our system is to automatically interpret sewn information, which effectively simpliﬁes user interaction. In addition, panel deformation method based on mannequin’s pose allows easy data capture. It extends the ﬂexibility and utility of our method. The experiments demonstrate the effectiveness on generating models of various garment styles
Outer-Sphere Oxidation of Ascorbic Acid

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Overview of Background Modeling Method Based on Pixel

Pixel-based background modeling methods which generaly used in the background subtraction are divided into two types: recursive and non-recursive.Firstly,the background modeling mothods are reviewed,and their possible applications and update status are summarized.Secondly,the performance of methods are compared arrording to their accuracy,time complexity and space complexity.Finally,the development and application of background modeling method are summaried and outlooked.
Research on Simultaneous Extraction of Vanadium and Chromium from High Chromium Vanadium Slag by Sub-molten Salt Method

In order to realize efficient and low-cost low-temperature simultaneous extraction of vanadium and chromium from high chromium vanadium slag,NaOH sub-molten salt liquid phase oxidation was employed according to phase of the slag. After the influences of reaction temperature of NaOH sub-molten salt system,NaOH-to-ore mass ratio and speed of stirring on vanadium extraction were studied,the optimum process parameters were obtained. With the reaction temperature of 220 ℃,NaOH concentration of 85%,NaOH-to-ore mass ratio of 10∶ 1,stirring speed of 950 r / min,atmospheric oxygen flow of 1 L / min and reaction time of 6 h,the leaching rates of vanadium and chromium reached 95% and 90% or above respectively,which indicates the realization of comprehensive utilization of vanadium slag.
Integration of the IEC TC 57 CIM with the IEC 61850 SCL Model and Modeling of the UCIM

An integrated unified common information model(UCIM) covering application levels ranging from the process level,the bay and substation levels to the control center level is developed based on the IEC TC 57 common information model(CIM) and IEC 61850 substation configuration description language(SCL). The rules for the SCL model and CIM to UCIM mapping processing are studied,based on which the power system models and applications are constructed,laying a foundation for the unified and correlated modeling of the power system primary and secondary equipments.The UCIM can be adopted to integrate current power system applications and develop new location-transparent applications.
Evaluation of different carbon materials in adsorption and solid-phase microextraction of 2,4,6-trichlorophenol from water

The adsorption process of 2,4,6-trichlorophenol (TCP) by carbonaceous materials, such as Carbopack B graphitized carbon black, Vulcan XC72 carbon black and two kinds of multi-walled carbon nanotubes, have been studied. The adsorption kinetics was best represented by the pseudo-second order kinetic model. Adsorption took place in accordance with the Freundlich equation. The materials were used to prepare novel, solid-phase microextraction (SPME) fibers. The efficiency of the fibers was evaluated using a gas chromatograph with an atomic emission detector for the extraction of TCP from the headspace of aqueous samples. Both the carbon nanotubes and carbon blacks coated fibers were of higher quality than commercially available fibers prepared from polydimethylsiloxane and polyacrylate. The results proved the ability of the proposed SPME fibers to detect TCP in water.
Evaluation on the Spatial Feasibility of the Overall Land Use Planning Based on GIS

The purpose of this paper aims at establishing a quantitative indicators and methodology to evaluate the spatial feasibility of the overall land use planning. Methods employed include literature analysis, empirical analysis, and GIS spatial analysis. The result indicates that 1) suitability index, coordination index and rationality index are chosen as the principal index to evaluate the spatial feasibility; 2) the application can be demonstrated by this method through an example of Yinchuan City. It is concluded that 1) this indicator and methodology can be applied to spatial layout assessment of land use planning. 2) The suitability index, coordination index and rationality index of Yinchuan land-use planning are 36.11, 34.12 and 70.23, which is evaluated as reasonable. 3) Unreasonable distribution regions and their causes are identified combined with visual analysis. The research is importantly significant for identifying problems in the spatial feasibility of the overall land-use planning.
Comparison of SVM and Spectral Embedding in Promoter Biobricks’ Categorizing and Clustering

Background In organisms’ genomes, promoters are short DNA sequences on the upstream of structural genes, with the function of controlling genes’ transcription. Promoters can be roughly divided into two classes: constitutive promoters and inducible promoters. Promoters with clear functional annotations are practical synthetic biology biobricks. Many statistical and machine learning methods have been introduced to predict the functions of candidate promoters. Spectral Eigenmap has been proved to be an effective clustering method to classify biobricks, while support vector machine (SVM) is a powerful machine learning algorithm, especially when dataset is small. Methods The two algorithms: spectral embedding and SVM are applied to the same dataset with 375 prokaryotic promoters. For spectral embedding, a Laplacian matrix is built with edit distance, followed by K-Means Clustering. The sequences are represented by numeric vector to serve as dataset for SVM trainning. Results SVM achieved a high predicting accuracy of 93.07% in 10-fold cross validation for classification of promoters’ transcriptional functions. Laplacian eigenmap (spectral embedding) based on editing distance may not be capable for extracting discriminative features for this task. Availability Codes, datasets and some important matrices are available on github https://github.com/shangjieZou/Promoter-transcriptional-predictor/tree/source-code
Cache-conscious concurrent data structures

The power wall, the instruction-level parallelism wall, and the memory wall are driving a shift in microprocessor design from implicitly parallel architectures to- wards explicitly parallel architectures. A necessary condition for peak scalability and performance on modern hardware is application execution that is aware of the memory hierarchy. The thesis of this dissertation is that cache-conscious con- current data structures for many-core systems will show significant performance improvements over the state of the art in concurrent data structure designs for those applications that must contend with the deleterious effects of the memory wall. Lock-free cache-conscious data structures that maintain the abstraction of a linearizable set have been studied previously in the context of unordered data structures. We explore novel alternatives, namely lock-free cache-conscious data structures that maintain the abstraction of a linearizable ordered set. The two primary design contributions of this dissertation are the lock-free skip tree and lock-free burst trie algorithms. In both algorithms, read-only operations are wait-free and modification operations are lock-free. The lock-free skip tree has relaxed structural properties that allow atomic operations to modify the free without invalidating the consistency of the data structure. We define the dense skip tree as a variation of the skip tree data structure, and prove cache-conscious properties of the dense skip tree. The proof techniques represent a significant departure from the methods outlined in the original skip tree paper. We show that cache-conscious, linearizable concurrent data structures have advantageous performance that can be measured across multiple architecture platforms. The improved performance arises from better treatment of the memory wall phenomenon that is ubiquitous to current multi-core systems and almost certainly will continue to affect future many-core systems.
Active diagnosis of discrete event systems

While the need for accurate and timely diagnosis of system failures and the advantages of automated diagnostic systems are well appreciated, diagnosability considerations are often not explicitly taken into account in system design. In particular, design of the controller and that of the diagnostic subsystem are decoupled and this may significantly affect the diagnosability properties of a system. In this paper we present an integrated approach to control and diagnosis. More specifically, we present an approach for the design of diagnosable systems by appropriate design of the system controller. This problem, which we refer to as the active diagnosis problem, is studied in the framework of discrete event systems (DES). We formulate the active diagnosis problem as a supervisory control problem where the legal language is an "appropriate" sublanguage of the system language. We present an iterative procedure for determining the supremal controllable, observable, and diagnosable sublanguage of the legal language, and for obtaining the supervisor that synthesizes this language. This procedure provides both a controller that ensures diagnosability of the closed-loop system and a diagnoser for online failure diagnosis. We illustrate our approach using a simple pump-valve system.
Issues and Challenges in Web Crawling for Information Extraction

Computational biology and bio inspired techniques are part of a larger revolution that is increasing the processing, storage and retrieving of data in major way. This larger revolution is being driven by the generation and use of information in all forms and in enormous quantities and requires the development of intelligent systems for gathering, storing and accessing information. This chapter describes the concepts, design and implementation of a distributed web crawler that runs on a network of workstations and has been used for web information extraction. The crawler needs to scale (at least) several hundred pages per second, is resilient against system crashes and other events, and is capable to adapted various crawling applications. Further this chapter, focusses on various ways in which appropriate biological and bio inspired tools can be used to implement, automatically locate, understand, and extract online data independent of the source and also to make it available for Semantic web agents like a web crawler. Subrata Paul Vignan Institute of Technology and Management, India Anirban Mitra Vignan Institute of Technology and Management, India Swagata Dey MIPS, MITS, Rayagada, India Issues and Challenges in Web Crawling for Information Extraction
Bro Intrusion Detection System

Bro is a Unix-based Network Intrusion Detection System (IDS). Bro monitors network traffic and detects intrusion attempts based on the traffic characteristics and content. Bro detects intrusions by comparing network traffic against rules describing events that are deemed troublesome. These rules might describe activities (e.g., certain hosts connecting to certain services), what activities are worth alerting (e.g., attempts to a given number of different hosts constitutes a "scan"), or signatures describing known attacks or access to known vulnerabilities. If Bro detects something of interest, it can be instructed to either issue a log entry or initiate the execution of an operating system command. Bro targets high-speed (Gbps), high-volume intrusion detection. By judiciously leveraging packet filtering techniques, Bro is able to achieve the performance necessary to do so while running on commercially available PC hardware, and thus can serve as a cost effective means of monitoring a sites Internet connection.
The Effectiveness of Strategic Information Systems Planning for Technical Resources, Personnel Resources, and Data Security in Environments of Heterogeneity and Hostility

Environmental uncertainty is believed to influence strategic information systems planning (SISP). Research suggests that more such uncertainty would prompt more SISP, and that more SISP would produce greater planning success. This study tested those expected relationships. A questionnaire defined SISP in terms of the planning activities for technical resources, personnel resources, and data security. It measured environmental uncertainty as heterogeneity and hostility where hostility consisted of scarcity and competition. It assessed planning success as a second order construct composed of alignment, analysis, cooperation, and improvement in capabilities. A postal survey collected data from 161 IS executives. Constructs were extensively validated. Heterogeneity predicted personnel resources and data security planning. Scarcity predicted technical and personnel resources planning. Technical and personnel resources planning predicted planning success. The research contributed by highlighting the potential impact of heterogeneity and hostility on SISP, and that of technical resources, personnel resources, and data security planning on SISP success.
Second Language Acquisition (SLA) as a Promoting Factor in Language Change

In long-standing language contact situations, SLA mechanisms can account for changes in LI. While it is obvious that LI influence on L2 can be accounted for as a transfer effect, I postulate that SLA effects are responsible for certain aspects of L2 influence on LI as well. This is transparent if early stages of SLA are compared to early stages of language contact: what is affected most in both cases is the lexicon. Examples are drawn from Pennsylvania German, a German-based language spoken in the USA and in contact with American English (AE) for c. 300 years. The data imply that the conceptual matrix of the Speakers’ minds has shifted from German to AE, resulting in constructions that can be traced to AE, while the conscious language choice is still German. This conceptual shift relates to a stage in SLA, when the learner begins to get a grasp of the internal systematicity of the L2 and reduces the transfer of structural LI material to L2, i.e. the beginning of a structuralization process in the learner’s interlanguage. The quality and sequence of the “invading” material in language contact is strikingly similar to the sequence of the material composed in the process of SLA, implying a close relationship between the two processes.
Simulation Research on Improved BLDCM Direct Torque Control System

In this paper,an improved Brushiess DC motor direct torque control method of eliminating flux observer was proposed based on the theory of fuzzy adaptive PID.A speed regulator was designed based on the fuzzy adaptive PID control algorithm and electromagnetic torque observer.The formula of Electromagnetic torque observer was derived and the switch table of simplified direct torque control was made.The simulation based on MATLAB/SIMULINK shows that the simplified direct torque control of brushiess DC motor has less torque ripple than current hysteresis control and stronger anti-interference.The Brushiess DC motor control system based on fuzzy adaptive PID control has faster speed response and much less overshoot than Brushiess DC motor control system based on traditional PID control.