Miracle-dz/UniFAR-FTUs huggingface dataset:
Open source toolkit for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations

Understanding how the brain controls behavior requires observing and manipulating neural activity in awake behaving animals. Neuronal firing is timed at millisecond precision. Therefore, to decipher temporal coding, it is necessary to monitor and control animal behavior at the same level of temporal accuracy. However, commonly available processors are not designed for this task and it is challenging to deliver sensory stimuli and reinforcers as well as to read the behavioral responses they elicit with millisecond precision. We present here a set of tools that offer affordable solutions to achieve these goals, including a physical environment to train head-fixed animals, means of providing calibrated sound stimuli and technical details of delivering sensory cues, fluid reward and air puff punishment with measured latencies. Combined with electrophysiology and optogenetic manipulations, the millisecond timing accuracy will help interpret temporally precise neural signals and behavioral changes. Additionally, since software and hardware provided here can be readily customized to achieve a large variety of paradigms, these solutions enable an unusually flexible design of rodent behavioral experiments.
IDENTIFIKASI JENIS PADA KEJADIAN CETACEA TERDAMPAR DI INDONESIA DENGAN TEKNIK MOLEKULER

Kasus Cetacea atau Paus dan Lumba-lumba terdampar di Indonesia sejak berapa tahun terakhir ini semakin sering terungkap dan ditangani oleh banyak pihak. Data dari Whale Stranding Indonesia (WSI) mencatat 40 kasus Cetacea terdampar di berbagai tempat di Indonesia selama tahun 2016 hingga bulan Februari 2017. Salah satu kendala bagi para penyelamat di lapangan adalah sulitnya mengidentifikasi jenis secara morfologi karena pada beberapa kasus, individu yang terdampar tidak dalam kondisi utuh. WSI mencatat lebih dari 21% jenis pada kejadian Cetacea terdampar di Indonesia, tidak teridentifikasi. Penelitian ini bertujuan memperkenalkan pendekatan genetika molekuler dalam mengidentifikasi jenis pada Cetacea terdampar. Gen Control Region dari DNA mitokondria diamplifikasi dengan menggunakan metode Polymerase Chain Reaction (PCR). Data sekuen dibandingkan dengan data di genebank dan dilihat persentase kesamaannya. Penelitian ini menggunakan 36 sampel individu dan 26 diantaranya teramplifikasi dengan panjang basa berkisar antara 445-490 bp ( base pair ). Metode molekuler berhasil mengidentifikasi 15 spesies dan 13 genus Cetacea yang diambil dari beberapa tempat di Indonesia. Studi ini menunjukkan bahwa teknik genetika molekuler dapat dijadikan metode untuk mengidentifikasi jenis dari Cetacea, terutama mamalia terdampar yang sulit untuk diidentifikasi secara morfologi. Data molekuler yang dihasilkan dapat melengkapi database yang ada di Indonesia serta menjadi penunjang bagi penelitian tentang keragaman genetik dan hubungan antar populasi mamalia akuatik di Indonesia.
Enumerating all possible biosynthetic pathways from metabolic networks

Exhaustive identification of all alternate possible pathways that exist within metabolic networks can provide valuable insights into cellular metabolism. With the growing number of metabolic reconstructions, there is a need for an efficient method to enumerate pathways, which can also scale well to large metabolic networks, such as those corresponding to microbial communities. We developed MetQuest, an efficient graph-theoretic algorithm to enumerate all possible pathways of a particular length between a given set of source and target molecules. Our algorithm employs a guided breadth-first search to identify all feasible reactions based on the availability of the precursor molecules, followed by a novel dynamic-programming based enumeration, which assembles these reactions into pathways producing the target from the source. We demonstrate several interesting applications of our algorithm, ranging from predicting amino acid biosynthesis pathways to identifying the most diverse pathways involved in degradation of complex molecules. We also illustrate the scalability of our algorithm, by studying larger graphs such as those corresponding to microbial communities, and identify several metabolic interactions happening therein. A Python-based implementation of MetQuest is available at https://github.com/RamanLab/MetQuest
Duplex Proximity Sequencing (Pro-Seq): A method to improve DNA sequencing accuracy without the cost of molecular barcoding redundancy

A challenge in the clinical adoption of cell-free DNA (cfDNA) liquid biopsies for cancer care is their high cost compared to potential reimbursement. The most common approach used in liquid biopsies to achieve high specificity detection of circulating tumor DNA (ctDNA) among a large background of normal cfDNA is to attach molecular barcodes to each DNA template, amplify it, and then sequence it many times to reach a low-error consensus. In applications where the highest possible specificity is required, error rate can be lowered further by independently detecting the sequences of both strands of the starting cfDNA. While effective in error reduction, the additional sequencing redundancy required by such barcoding methods can increase the cost of sequencing up to 100-fold over standard next-generation sequencing (NGS) of equivalent depth. We present a novel library construction and analysis method for NGS that achieves comparable performance to the best barcoding methods, but without the increase in sequencing and subsequent sequencing cost. Named Proximity-Sequencing (Pro-Seq), the method merges multiple copies of each template into a single sequencing read by physically linking the molecular copies so they seed a single sequencing cluster. Since multiple DNA copies of the same template are compared for consensus within the same cluster, sequencing accuracy is improved without the use of redundant reads. Additionally, it is possible to represent both senses of the starting duplex in a single cluster. The resulting workflow is simple, and can be completed by a single technician in a work day with minimal hands on time. Using both cfDNA and cell line DNA, we report the average per-mutation detection threshold and per-base analytical specificity to be 0.003% and >99.9997% respectively, demonstrating that Pro-Seq is among the highest performing liquid biopsy technologies in terms of both sensitivity and specificity, but with greatly reduced sequencing costs compared to existing methods of comparable accuracy.
Evidence that the cell cycle is a series of uncoupled, memoryless phases

The cell cycle is canonically described as a series of 4 phases: G1 (gap phase 1), S (DNA synthesis), G2 (gap phase 2), and M (mitosis). Various models have been proposed to describe the durations of each phase, including a two-state model with fixed S-G2-M duration and random G1 duration1,2; a “stretched” model in which phase durations are proportional3; and an inheritance model in which sister cells show correlated phase durations2,4. A fundamental challenge is to understand the quantitative laws that govern cell-cycle progression and to reconcile the evidence supporting these different models. Here, we used time-lapse fluorescence microscopy to quantify the durations of G1, S, G2, and M phases for thousands of individual cells from three human cell lines. We found no evidence of correlation between any pair of phase durations. Instead, each phase followed an Erlang distribution with a characteristic rate and number of steps. These observations suggest that each cell cycle phase is memoryless with respect to previous phase durations. We challenged this model by perturbing the durations of specific phases through oncogene activation, inhibition of DNA synthesis, reduced temperature, and DNA damage. Phase durations remained uncoupled in individual cells despite large changes in durations in cell populations. To explain this behavior, we propose a mathematical model in which the independence of cell-cycle phase durations arises from a large number of molecular factors that each exerts a minor influence on the rate of cell-cycle progression. The model predicts that it is possible to force correlations between phases by making large perturbations to a single factor that contributes to more than one phase duration, which we confirmed experimentally by inhibiting cyclin-dependent kinase 2 (CDK2). We further report that phases can show coupling under certain dysfunctional states such as in a transformed cell line with defective cell cycle checkpoints. This quantitative model of cell cycle progression explains the paradoxical observation that phase durations are both inherited and independent and suggests how cell cycle progression may be altered in disease states.
MyWorkspace: VR Platform with an Immersive User Interface

With the recent development of virtual reality, it has been actively investigated to develop user interfaces for immersive interaction. Immersive user interfaces improve the efficiency and the capability of information processing in the virtual environment providing various services, and provide effective interaction in the field of ubiquitous and mobile computing. In this paper, we propose an virtual reality platform "My Workspace" which renders an 3D virtual workspace by using an immersive user interface. We develop an interface that integrates an optical see-through head-mounted display, a Wii remote controller, and a helmet with infrared LEDs. It estimates the user's gaze direction in terms of horizontal and vertical angles based on the model of head movements. My Workspace expands the current 2D workspace based on monitors into the layered 3D workspace, and renders a part of 3D virtual workspace corresponding to the gaze direction. The user can arrange various tasks on the virtual workspace and switch each task by moving his head. In this paper, we will also verify the performance of the immersive user interface as well as its usefulness with the usability test. 핵심어: immersive user interface, virtual reality, 3D workspace, head tracking, head mounted display *주저자 : 연세대학교 컴퓨터과학과 학부과정 e-mail: jwyoon@sclab.yonsei. ac.kr **공동저자 : 연세대학교 컴퓨터과학과 박사과정 e-mail: hjinh@sclab.yonsei. ac.kr ***교신저자 : 연세대학교 컴퓨터과학과 교수; e-mail: sbcho@cs.yonsei. ac.kr HCI2009 학술대회
Smart Deployment of Sensor Nodes Using SA & GFA

In wireless sensor networks, network connectivity problems and sensor coverage are mainly affected by the restricted communication and sensing range of the nodes. To solve all these problems, many studies have been undertaken till now but most of these works is limited to be applied to the real environments because these do not consider various environmental factors that affect wireless sensor network deployment. In this paper, we propose a node deployment strategy that considers environmental factors and the number of nodes for surveillance . Deployment of the sensor nodes, and relay nodes considering all features of the surveillance and reconnaissance sensor networks as well as environmental factors. Smarty deploying the sensor nodes is very important if we are considering the performance of wireless sensor nodes (wsn). This paper focuses on real time deployment of sensor nodes using unmanned aerial vehicle (UAV). Smart deployment has importance in battlefield surveillance, disaster monitoring, environmental and habitat monitoring etc. It plays a very important role mainly in disasters affecting areas like flood affected or fire affected forests for sensing different conditions and physical data out there. The objective of this paper is to deploy sensor nodes smartly only in terrain of interest not in fire or water so that it can conserve environment and can reduce the loss of sensor nodes from being deploy in fire or water. Image segmentation of the images captured by camera situated on a board of UAV. Comparison of these optimization tools SA and GFA are presented here for different images. Simulation results show that GFA performs better than SA when compared with no. of individuals and SA is faster than GFA.
The complete mitochondrial genome of Thryssa setirostris (Engraulinae, Engranlidae, Clupeoidei) and phylogenetic studies of Clupeoidei

Abstract The complete mitochondrial genome of Thryssa setirostris has been determined. The whole sequence was 16,926 bp in length and included 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and 1 control region (D-loop). The overall base composition is A 29.88%, C 29.23%, G 16.77%, T 24.02%, with a slightly A + T bias of 54%. With the exception of ND6 and eight tRNA genes, all other mitochondrial genes are encoded on the heavy strand. Phylogenetic tree was constructed based on 13 protein-coding genes sequences of 21 clupeoidei species, and the result showed that T. setirostris is most closely related to T. dussumieri. These mitogenome sequence data will be useful for population genetics and phylogenetic analysis of the Clupeoidei.
EVAPRO: economic and financial evaluation of water supply projects

The present paper describes a computer-based system for water supply project appraisal called EVAPRO, standing for EVAluation of water PROjects. The aim of EVAPRO is to facilitate economic and financial assessment of water supply projects under different investment and operating scenarios, and changes to initial system configuration. The software consists of automating the feasibility study of water projects using information about population and water demand forecasts, potential water resources, investment decisions, financial resources and water pricing policy. It embodies a set of tools, including linear programming techniques, numerical methods and financial calculations, and combines operational optimization with financial analysis to assess the feasibility of water supply
Method for automatic assessing of the gradient filter threshold for fast processing of dynamic scenes objects

In this paper, we present a new method based on the use of information provided by the gradient methods for determining the geometric parameters of objects with high accuracy. The algorithm is based on the use of data obtained after image processing by gradient filters. Also, it reacts to the slightest change in the contours of objects of the dynamic image scenes. Repeated experiments using more than 5000 real images were processed to improve the theory. Given a high refresh rate of modern systems, a position of the Center Of Gravity (COG) in the dynamic images is changing gradually even for rapid motion. Using this feature, COG for each frame of a training sample is defined under various threshold values by means of an algorithm. A number of elements (frames) in the training sample are selected depending on the type of the dynamic object, a task set and on the initial conditions. The suggested method is recommended for further use by the expert system, in parallel with its own operation, with a goal to maintain a threshold value on the optimal level in case of dynamic perturbing factors. After the research, we found that the prediction accuracy increased that essentially improved results. A number of experiments demonstrated increasing the accuracy of determination of the center of blurred objects. Also, we have eliminated the human factor. All of the calculations are done automatically. These data are very useful and important for all areas of science where high accuracy of the results is necessary.
Emerging antibiotic resistance and plasmid dna in escherichia coli isolated from respiratory tract infections in Bangladesh

Worldwide antibiotic resistance (AR) is a public health threat, places everyone at great risk.1 By 2050, it is anticipated that AR will cause 10 million deaths and US $60–100 trillion global economic loss if AR developing rate is constant as now.2 The rising bacterial resistance among Respiratory Tract Infections (RTI) has become a commonplace event. The resistance among RTIs causative pathogens of Streptococcus pneumoniae, Klebsiella pneumoniae, Pseudomonas aeruginosa and Escherichia coli contributes a significant cause of global morbidity and mortality as well.3–5 Additionally, inappropriate prescribing of antibiotics in RTIs has become a remarkable malpractice by prescribers.6,7 This practice further magnifies the emergence of antibiotic–resistant bacterial strains in addition to increased adverse effect, treatment cost, resource use and consultation with doctors.6,8 Difficulty in establishing bacterial etiology at the time of prescription in RTIs is another barrier to rational antibiotic prescribing in Bangladesh.9,10 The limited context specific surveillance data on antimicrobial sensitivity in Bangladesh further complicates antibiotic prescribing decisions by prescribers.10 The AR surveillance information has even paramount importance to develop local and national antibiotic guidelines.
r in the

The hormonal change during the climacterium causes a decrease of the estrogen level and an increase of the follicle-stimulating hormone (FSH). This imbalance can cause discomforts, which are often treated with a hormonal therapy, where often side effects occur. With the melissa preparation, which is presented in this observation of application, a traditional phytopharmacon is available as an alternative for the treatment of the symptoms of climacteric discomforts. Theaimwas, toexaminethe effectandtoleranceof the drugduringdailypractice. 105 female patients with typical climacteric discomforts were included in the study. 92.3% of the female patients showed a statistically highly significant improvement of the discomforts. In more than 90% of the cases, tolerance and compliance were rated very good or good .
Aerosol optical thickness and scattering phase function retrieval from solar radiances recorded over water: a revised approach

The possibility of deriving aerosol optical thickness and phase function values for certain scattering angles from solar radiances recorded over the oceans is examined. Radiative transfer simulations results for the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectrometer (MODIS) instruments are presented. These results indicate that an iterative procedure should be used for the simultaneous determination of the two quantities.
Alignment-Free Approaches for Predicting Novel Nuclear Mitochondrial Segments (NUMTs) in the Human Genome

The nuclear human genome harbors sequences of mitochondrial origin, indicating an ancestral transfer of DNA from the mitogenome. Several Nuclear Mitochondrial Segments (NUMTs) have been detected by alignment-based sequence similarity search, as implemented in the Basic Local Alignment Search Tool (BLAST). Identifying NUMTs is important for the comprehensive annotation and understanding of the human genome. Here we explore the possibility of detecting NUMTs in the human genome by alignment-free sequence similarity search, such as k-mers (k-tuples, k-grams, oligos of length k) distributions. We find that when k=6 or larger, the k-mer approach and BLAST search produce almost identical results, e.g., detect the same set of NUMTs longer than 3kb. However, when k=5 or k=4, certain signals are only detected by the alignment-free approach, and these may indicate yet unrecognized, and potentially more ancestral NUMTs. We introduce a “Manhattan plot” style representation of NUMT predictions across the genome, which are calculated based on the reciprocal of the Jensen-Shannon divergence between the nuclear and mitochondrial k-mer frequencies. The further inspection of the k-mer-based NUMT predictions however shows that most of them contain long-terminal-repeat (LTR) annotations, whereas BLAST-based NUMT predictions do not. Thus, similarity of the mitogenome to LTR sequences is recognized, which we validate by finding the mitochondrial k-mer distribution closer to those for transposable sequences and specifically, close to some types of LTR.
Bees use anthropogenic habitats despite strong natural habitat preferences

Habitat loss and alteration is widely considered one of the main drivers of the current loss of pollinator diversity. Unfortunately, we still lack a comprehensive analysis of habitat importance, use and preference for major groups of pollinators. Here, we address this gap analysing a large dataset of 15,762 bee specimens (more than 400 species) across northeast USA. We found that natural habitats sustain the highest bee diversity, with many species strongly depending on such habitats. By characterizing habitat use and preference for the 45 most abundant species, we also show that many bee species can use human-altered habitats despite exhibiting strong and clear preferences for forested habitats. However, only a few species appear to do well when the habitat has been drastically modified. We conclude that although altered environments may harbor a substantial number of species, preserving natural areas is still essential to guarantee the conservation of bee biodiversity.
Collaborations between CpG sites in DNA methylation

DNA methylation patterns have profound impacts on genome stability, gene expression, and development. The molecular base of DNA methylation patterns has long been focused at single CpG sites level. Here, we construct a kinetic model of DNA methylation with collaborations between CpG sites, from which a correlation function was established based on experimental data. The function consists of three parts that suggest three possible sources of the correlation: movement of enzymes along DNA, collaboration between DNA methylation and nucleosome modification, and global enzyme concentrations within a cell. Moreover, the collaboration strength between DNA methylation and nucleosome modification is universal for mouse early embryo cells. The obtained correlation function provide insightful understanding for the mechanisms of inheritance of DNA methylation patterns.
Implementation of Spyware Detection Using Data Mining With Decision Tree Algorithm

Any software that monitors user behavior, or gathers information about the user without adequate notice, consent, or control from the user. " Spyware represents a serious threat to confidentiality since it may result in loss of control over private data for computer users. This type of software might collect the data and send it to a third party without informed user consent. Our approach is inspired by DM-based malicious code detectors, which are known to work well for detecting viruses and similar software We extract binary features, called n- grams, from both spyware and software and apply to train classifiers that are able to classify unknown binaries by analyzing extracted n-grams. Keywords: N-Gram, ARFF (Attribute Relation File Format) CFBE (Common Feature-based Extraction), FBFE (Frequency-based Feature Extraction), RFS (Reduced Feature Sets).