Miracle-dz/UniFAR-FTUs huggingface dataset:
Katome: de novo DNA assembler implemented in rust

Katome is a new de novo sequence assembler written in the Rust programming language, designed with respect to future parallelization of the algorithms, run time and memory usage optimization. The application uses new algorithms for the correct assembly of repetitive sequences. Performance and quality tests were performed on various data, comparing the new application to `dnaasm', `ABySS' and `Velvet' genome assemblers. Quality tests indicate that the new assembler creates more contigs than well-established solutions, but the contigs have better quality with regard to mismatches per 100kbp and indels per 100kbp. Additionally, benchmarks indicate that the Rust-based implementation outperforms `dnaasm', `ABySS' and `Velvet' assemblers, written in C++, in terms of assembly time. Lower memory usage in comparison to `dnaasm' is observed.
WMT17 En-De APE Shared Task Data

Training data for the WMT 2017 Automatic post-editing task (the same used for the Sentence-level Quality Estimation task). They consist in 11,000 English-German triplets (source, target and post-edit) belonging to the IT domain and already tokenized. All data is provided by the EU project QT21 (http://www.qt21.eu/).
College Enquiry Chatbot Using Knowledge in Database

: The College Enquiry Chatbot project is built using Microsoft Bot Builder, LUIS.ai and MongoDB for database[3]. This System is a web application which provides answer to the query of the student[2]. Students just have to query to the bot and bot will answer to student question[1]. Students can ask questions using any English text format[1]. There is no specific format the user has to follow[2]. The System uses built in Artificial Intelligence to answer the query provided by LUIS.ai. The system replies using an effective Graphical User Interface which implies that as if a real person is talking to the user[4]. First, bot will send query to the LUIS.ai. LUIS.ai will send its response to bot after that bot will fetch value from database and then give answer to user question[2].
Library Services Platform Path to Cloud Computing Adoption in Nigerian Academic Libraries: A Review

The library and Information science (LIS) profession have evolved over time taking advantage of prevailing technology. The arrival of computers and other communication technologies led to major changes in the ways library services are rendered and the profession practiced. Library Management Systems (LMS) is one of such earlier areas where ICT have been applied to the operations of the library during the library computerization era. The arrival of the renascent Cloud Computing is generating new areas of research in relation to librarians’ uptake of this new technology. Cloud computing is being leveraged by developers of library systems to facilitate the envisaged move away from ILS/LMS to a more robust system that can handle some of the shortcomings of the ILS/LMS. These new systems are called Library services platforms (LSP). While both established and new library systems vendors are turning out different products, libraries have begun to shift away to these new platforms. This paper reviews cloud computing in libraries and projects LSPs as the reliable path to its adoption in Nigerian academic libraries. Recommendations were made based on the outcomes of this study.
Ring topology of an optical phase delayed nonlinear dynamics for neuromorphic photonic computing

Nowadays most of computers are still based on concepts developed more than 60 years ago by Alan Turing and John von Neumann. However, these digital computers have already begun to reach certain physical limits of their implementation via silicon microelectronics technology (dissipation, speed, integration limits, energy consumption). Alternative approaches, more powerful, more efficient and with less consume of energy, have constituted a major scientific issue for several years. Many of these approaches naturally attempt to get inspiration for the human brain, whose operating principles are still far from being understood. In this line of research, a surprising variation of recurrent neural network (RNN), simpler, and also even sometimes more efficient for features or processing cases, has appeared in the early 2000s, now known as Reservoir Computing (RC), which is currently emerging new brain-inspired computational paradigm. Its structure is quite similar to the classical RNN computing concepts, exhibiting generally three parts: an input layer to inject the information into a nonlinear dynamical system (Write-In), a second layer where the input information is projected in a space of high dimension called dynamical reservoir and an output layer from which the processed information is extracted through a so-called Read-Out function. In RC approach the learning procedure is performed in the output layer only, while the input and reservoir layer are randomly fixed, being the main originality of RC compared to the RNN methods. This feature allows to get more efficiency, rapidity and a learning convergence, as well as to provide an experimental implementation solution. This PhD thesis is dedicated to one of the first photonic RC implementation using telecommunication devices. Our experimental implementation is based on a nonlinear delayed dynamical system, which relies on an electro-optic (EO) oscillator with a differential phase modulation. This EO oscillator was extensively studied in the context of the optical chaos cryptography. Dynamics exhibited by such systems are indeed known to develop complex behaviors in an infinite dimensional phase space, and analogies with space-time dynamics (as neural network ones are a kind of) are also found in the literature. Such peculiarities of delay systems supported the idea of replacing the traditional RNN (usually difficult to design technologically) by a nonlinear EO delay architecture. In order to evaluate the computational power of our RC approach, we implement two spoken digit recognition tests (classification tests) taken from a standard databases in artificial intelligence TI-46 and AURORA-2, obtaining results very close to state-of-the-art performances and establishing state-of-the-art in classification speed. Our photonic RC approach allowed us to process around of 1 million of words per second, improving the information processing speed by a factor ~3.
Relationship between Planting Density and Tree Growth Process of Betula alnoides Mid-young Plantations in Pingxiang,Guangxi

11-year-old Betula alnoides plantations for density trial with five planting spacing treatments were investigated through stem analysis at Pingxiang City,Guangxi,to assess the effects of initial density on tree growth process.The results showed that the initial density had no remarkable effects on tree height growth and stem shape index,while there were significant differences in diameter at breast height(DBH),individual tree volume and stand volume among treatments of initial density,and the stand volume of treatment of 2 m × 3 m was significantly higher than that of other treatments.The fast growing period of DBH trended to increase with the decrease of initial density,the DBH growth commenced to decrease since the sixth year after planted under the 1.5 m × 2 m treatment,while it decreased mostly since the eighth year under other treatments,indicating that thinning should be conducted at the sixth year for 1.5 m × 2 m treatment,and at the eighth year for 2 m × 3 m and 3 m × 3 m treatments,while for other treatments,it was delayed with the decrease of density.All the current and mean annual increment curves of tree height crossed when 5-6 years old,and did not reach quantity mature until 11 years old for all density treatments,while remarkable differences of the current annual increment of individual tree volume were seen among treatments.Taking factors such as growth performance,stand volume,and use efficiency of forest land,etc.into consideration,2 m × 3 m was determined as the most optimum planting density in the present study.
Characterizing blood glucose response to specific meals in pre-diabetes: a small scale study

Our research area is prediction of blood glucose level. Usually, we use a combination of two state-of-the-art models reflecting the real process happening in the body. However, this model cannot handle the blood glucose control system for pre-diabetes cases. In this paper, we present an approach that tries to give prediction for two hours period after meals based on a dietary log and a calibration measurement.
Karyological evidence for meiosis in the three different types of life cycles existing in Agaricus bisporus

In Agaricus bisporus all cytological studies performed until now concerned the pseudohomothallic and bisporic var. bisporus. In the past 12 y two tetrasporic varieties have been described, the heterothallic var. burnettii and the homothallic var. eurotetrasporus. Our aim was to compare the behavior of the nuclei in the vegetative and reproductive cells of the three varieties with light microscopy (Feulgen and DAPI staining) and transmission electron microscopy. Most of the vegetative cells contained 3–5 nuclei in the three varieties. Nuclear migrations through the septum were detected. In the basidia relative locations of nuclei and vacuoles, meiotic spindle alignments, relative content of nuclear DNA and synaptonemal complexes were measured or observed. From the observation of numerous asynchronous second division of meiosis within basidia of var. bisporus and var. burnettii a new hypothesis emerges to explain the nonrandom distribution of the four meiotic products in the two spores of the bisporic basidia. Karyogamy and meiosis similarly occurred in the three varieties. In the case of A. bisporus var. eurotetrasporus this implies that the reproductive mode is sexual and therefore homothallic in the strict sense. The three different types of life cycles are described.
ETH Zurich’s University Collections and Archives in the Digital Age. Innovative Indexing, Digitisation and Publication of Unique Materials

ETH Zurich’s university collections and archives encompass around twenty facilities with unique holdings. Their diversity reflects the historic development of collections at the university and its modern potential for research and teaching. ETH Zurich makes its collections and archives available for research and teaching in a form that befits the digital age. To this end, it combines ETH Library’s skills in information science with the expertise of the collection owners in the departments in accordance with the Strategy 2015 to 2020, which was passed by the Executive Board in 2014. This paper presents the strategic approach of ETH Zurich’s Executive Board and focuses on the role of ETH Library in the current line of action.
Acoustic Signal Classification for Deforestation Monitoring: Tree Cutting Problem

This paper deals with tree cutting real-world problem, causing significant damages to forests. The sensing and classification of acoustic signal emitted during tree cutting, is used to extract information of tree cutting events using sensors. Detecting the acoustic signal due to saw scratching power level in presence of ambiance noise and the other choral noise sources is a major issue in a forest environment. An acoustic sensor experimental setup is established for capturing the acoustic signal generated due to cross cut sawing with varying distances. Based on the experimental analysis, saw scratching acoustic signal is found with appropriate for tree cutting detection. The acoustic signal pre-processing is performed with the help of a SNR algorithm. The extraction of features in frequency space is done by using modified MFCC and spectral features extraction. Modified MFCC feature based dynamic time warping (MDTW) and spectral feature based Gauss-Bayesian classifier (SGBC) are used and compared.
Single spore strains without producing fruit body isolated from Cordyceps militeris and their RAPD analysis

6 single spore strains without producing fruit body were isolated from the original Cordyceps militeris,WWM04 with producing fruit body.The genetic diversity of SSP2,SSP7,SSP19 and SSP21 strains without producing fruit body,the original strain and the strain after 12 transferred from the original strain was analyzed by the RAPD method.The results show that the primers S37 and S61 are of apparently specific to the amplified bands of six strains,which establishes the basic for the degenerate molacular marker of Cordyceps militeris and confirms heterokaryosis and parasexuality of Cordyceps militeris.to some extent.
Studies on the Q/B values and food consumption of major fishes in the East China Sea and the Yellow Sea

Based on the trawl surveys in the East China Sea and the Yellow Sea and determination of the related annual average temperature (T),asymptotic weight (W∞),the aspect ratio of caudal fin (A) and stomach contents (Ft),Q/B values of 103 fish species were calculated by three empirical models.The Q/B values ranged from 3.09 (for Lophius litulon )to 19.13 (for Benthosema pterotum) and the average value was 7.97. The amount of annual food consumption by the fish species was assessed based on the Q/B values and the amount of biomass.In the Yellow Sea,the major species including Engraulis japonicus,Trachurus japonicus,Scomber japonicus,Liparis tanakai,and Larimichthys polyactis,was consumed 4.49×106 tons/year.In the East China Sea,the major species such as Trachurus japonicus,Trichiurus haumela,Acropoma japonicum Gunther,Engraulis japonicus,and Scomberomorus niphonius,was consumed 1.75×106 tons/year.Food consumption by 97 fish species in the Yellow Sea and the East China Sea were 4.66×106 tons/year and 2.78×106 tons/year,respectively.Meanwhile,the quantity of major food organisms such as Euphausiids,Engraulis japonicus,Acropoma japonicum Gunther,Benthosema pterotum,Apogon lineatus,Loligo japonica Hoyle,Copepoda,Sergestidae,Leptochela gracilis and Crangon affinis consumed in the East China Sea and the Yellow Sea was evaluated.The total amount of major food organisms consumed in the East China Sea and the Yellow Sea was 5.55×106 tons/year,accounting for 74.6% of the total food consumption by 97 fish species.
Optimized Resource-to-Task Scheduler for Cloud Service

A key concern in cloud computing setting is to capitalize on turnover by accommodating all arriving needs and to diminish bad consequences for cloud providers. Attaining these purposes extremely depends on optimal usage of accessible resources in datacenters. To diminish the power and time consumption in cloud computing environment, the previous work evaluate the process of identifying level of each server peer consuming power and task execution time to perform Web requests from client peers. This work explains inadequacies caused by the absence of resource organization method and propose a geometric representation using Scheduler-based Optimal Resource Allocation (S-ORA). The proposed S-ORA scheme investigates the suitability of commercial cloud service using A-mazon EC2 to hierarchical data exchange between multiple cloud instances with minimal resource utilization. The experimental evaluation shows that proposed performance of cloud computing services including Amazon EC2, with suitable management of resources result in an increment of proﬁt by reducing rejected requests of the cloud.
Virtual Reality Application in Data Visualization and Analysis

This thesis is aimed for finding a solution for non-gaming application of Virtual Reality technology in data visualization and analysis. Starting by reconstructing the concept of Virtual Reality, the paper then describes the principles, concepts and techniques of designing a Virtual Reality application. In the last part of the thesis, a detailed description of how a prototype implemented is presented to provide a preview of how data visualization and analysis and Virtual Reality technology can be combined together in order to enable users to perceive and comprehend data in a possibly better way.
Cross- Layer Dependability Modeling and Abstraction in Systems on Chip

—The Resilience Articulation Point (RAP) model aims at provisioning researchers and developers with a probabilistic fault abstraction and error propagation framework covering all hardware/software layers of a System on Chip. RAP assumes that physically induced faults at the technology or CMOS device layer will eventually manifest themselves as a single or multiple bit ﬂip(s). When probabilistic error functions for speciﬁc fault origins are known at the bit or signal level, knowledge about the unit of design and its environment allow the transformation of the bit-related error functions into characteristic higher layer representations, such as error functions for data words, Finite State Machine (FSM) state, macro interfaces or software variables. Thus, design concerns at higher abstraction layers can be investigated without the necessity to further consider the full details of lower levels of design. This paper introduces the ideas of RAP based on examples of radiation induced soft errors in SRAM cells and sequential CMOS logic. It shows by example how prob- abilistic bit ﬂips are systematically abstracted and propagated towards higher abstraction levels up to the application software layer, and how RAP can be used to parameterize architecture level resilience methods.
RDFa Core 1.1Syntax and processing rules for embedding RDF through attributes

The current Web is primarily made up of an enormous number of documents that have been created using HTML. These documents contain significant amounts of structured data, which is largely unavailable to tools and applications. When publishers can express this data more completely, and when tools can read it, a new world of user functionality becomes available, letting users transfer structured data between applications and web sites, and allowing browsing applications to improve the user experience: an event on a web page can be directly imported into a user’s desktop calendar; a license on a document can be detected so that users can be informed of their rights automatically; a photo’s creator, camera setting information, resolution, location and topic can be published as easily as the original photo itself, enabling structured search and sharing. 1 RDFa Core 1.1 RDFa Core 1.1
Reward Design in Cooperative Multi-agent Reinforcement Learning for Packet Routing

In cooperative multi-agent reinforcement learning (MARL), how to design a suitable reward signal to accelerate learning and stabilize convergence is a critical problem. The global reward signal assigns the same global reward to all agents without distinguishing their contributions, while the local reward signal provides different local rewards to each agent based solely on individual behavior. Both of the two reward assignment approaches have some shortcomings: the former might encourage lazy agents, while the latter might produce selfish agents. In this paper, we study reward design problem in cooperative MARL based on packet routing environments. Firstly, we show that the above two reward signals are prone to produce suboptimal policies. Then, inspired by some observations and considerations, we design some mixed reward signals, which are off-the-shelf to learn better policies. Finally, we turn the mixed reward signals into the adaptive counterparts, which achieve best results in our experiments. Other reward signals are also discussed in this paper. As reward design is a very fundamental problem in RL and especially in MARL, we hope that MARL researchers can rethink the rewards used in their systems.
A Data-driven Approach to the Automatic Classification of Korean Poetry

Automatic classification of text is an increasingly important area of research. It has important applications in virtual assistants and recommender systems. Among the different types of literary works, the poem is one of the most difficult to classify automatically because of the prolific use of metaphors and the short length. In this research, we propose a data-driven approach to automatically classify Korean poems. We use three different methods for finding keywords which can train the classifiers. Our results show that the proposed approach can produce better classification accuracy than using a predefined list of keywords created by a human expert. Index Terms — automatic classification, data-driven, poem, text mining, Korean text, keyword extraction
Syntactic Enhancement: Bootstrapping for Second Language Reading

This paper aimed to identify factors that inhibit effective second language (L2) reading and to suggest technology-enhanced reading designed for providing L2 readers with bootstrapping resources. To this end, this paper also addresses the importance of syntactic and prosodic awareness in L2 reading, drawing on L2 reading theories and a number of empirical studies from a body of research related to L2 development. Syntactic and prosodic awareness contribute to L2 reading development as they are highly associated with fluent and accurate reading abilities. However, it is challenging for L2 learners to acquire syntactic and prosodic knowledge due to limited cognitive capacities related to L2 learning, limited prior linguistic knowledge that is usually gained from oral communication, and linguistic differences between native languages and a target language. Addressing these challenges, this paper reviews a potentially useful technological tool of text presentation technology that may help increase syntactic awareness. Although empirical studies that tested the usefulness of technologyenhanced reading tools produced mixed results, their findings imply a viable alternative way of reading and call for future research to validate it.
Strategies for developing a science communicator through authentic science writing assignments

To prepare biology undergraduates to be able to read and evaluate the primary literature, it is beneficial to teach students how to write documents in the style of professional science style manuscripts. By breaking manuscripts into individual section assignments, we can distribute instruction across a four-year undergraduate curriculum to scaffold writing practice mastery. These skills are aided by peer review, writing tutor instruction, and assignment repetition. Students gain not only competency in writing about the discipline, but can better understand and critically evaluate the written work of others. The science writing and communication skills gathered over the course of this curricular framework provide all students with expertise in accessing science themselves and disseminating science to others.
Using and Extending the ACG technology: Endowing Categorial Grammars with an Underspecified Semantic Representation

Underlining the computational properties of Abstract Categorial Grammars, we show how to extend them while keeping some of their properties. In particular, we show how to enable the modeling of non-linear languages. We give as an example the encoding of an underspecified semantic representation language, and apply it to categorial grammars. So that we can model ambiguities of quantifier scopes only at the semantic level, and not at the syntactic level anymore.