Miracle-dz/UniFAR-FTUs huggingface dataset:
A multi-locus association analysis method integrating phenotype and expression data reveals multiple novel associations to flowering time variation in wild-collected Arabidopsis thaliana

When a species adapts to a new habitat, selection for the fitness traits often result in a confounding between genome-wide genotype and adaptive alleles. It is a major statistical challenge to detect such adaptive polymorphisms if the confounding is strong, or the effects of the adaptive alleles are weak. Here, we describe a novel approach to dissect polygenic traits in natural populations. First, candidate adaptive loci are identified by screening for loci that are directly associated to the trait or control the expression of genes known to affect it. Then, the multi-locus genetic architecture is inferred using a backward elimination association analysis across all the candidate loci using an adaptive false-discovery rate based threshold. Effects of population stratification are controlled by corrections for population structure in the pre-screening step and by simultaneously testing all candidate loci in the multi-locus model. We illustrate the method by exploring the polygenic basis of an important adaptive trait, flowering time in Arabidopsis thaliana, using public data from the 1,001 genomes project. Our method revealed associations between 33 (29) loci and flowering time at 10 (16)°C in this collection of natural accessions, where standard genome wide association analysis methods detected 5 (3) loci. The 33 (29) loci explained approximately 55 (48)% of the total phenotypic variance of the respective traits. Our work illustrates how the genetic basis of highly polygenic adaptive traits in natural populations can be explored in much greater detail by using new multi-locus mapping approaches taking advantage of prior biological information as well as genome and transcriptome data.
Evaluation and Hardware Implementation of Real-Time Color Compression Algorithms

A major bottleneck, for performance as well as power consumption, for graphics hardware in mobile devices is the amount of data that needs to be transferred to and from memory. In, for example, hardware accelerated 3D graphics, a large part of the memory accesses are due to large and frequent color buffer data transfers. In a graphic hardware block color data is typically processed using RGB color format. For both 3D graphic rasterization and image composition several pixels needs to be read from and written to memory to generate a pixel in the frame buffer. This generates a lot of data traffic on the memory interfaces which impacts both performance and power consumption. Therefore it is important to minimize the amount of color buffer data. One way of reducing the memory bandwidth required is to compress the color data before writing it to memory and decompress it before using it in the graphics hardware block. This compression/decompression must be done “on-the-fly”, i.e. it has to be very fast so that the hardware accelerator does not have to wait for data. In this thesis, we investigated several exact (lossless) color compression algorithms from hardware implementation point of view to be used in high throughput hardware. Our study shows that compression/decompression datapath is well implementable even with stringent area and throughput constraints. However memory interfacing of these blocks is more critical and could be dominating.
Comparing Server Energy Use and Efficiency Using Small Sample Sizes

Author(s): Coles, Henry C. ; Qin, Yong; Price, Phillip N. | Abstract: This report documents a demonstration that compared the energy consumption and efficiency of a limited sample size of server-type IT equipment from different manufacturers by measuring power at the server power supply power cords. The results are specific to the equipment and methods used. However, it is hoped that those responsible for IT equipment selection can used the methods described to choose models that optimize energy use efficiency.The demonstration was conducted in a data center at Lawrence Berkeley National Laboratory in Berkeley, California. It was performed with five servers of similar mechanical and electronic specifications; three from Intel and one each from Dell and Supermicro.Server IT equipment is constructed using commodity components, server manufacturer-designed assemblies, and control systems. Server compute efficiency is constrained by the commodity component specifications and integration requirements. The design freedom, outside of the commodity component constraints, provides room for the manufacturer to offer a product with competitive efficiency that meets market needs at a compelling price. A goal of the demonstration was to compare and quantify the server efficiency for three different brands. The efficiency is defined as the average compute rate (computations per unit of time) divided by the average energy consumption rate. The research team used an industry standard benchmark software package to provide a repeatable software load to obtain the compute rate and provide a variety of power consumption levels. Energy use when the servers were in an idle state (not providing computing work) were also measured.At high server compute loads, all brands, using the same key components (processors and memory), had similar results; therefore, from these results, it could not be concluded that one brand is more efficient than the other brands. The test results show that the power consumption variability caused by the key components as a group is similar to all other components as a group. However, some differences were observed. The Supermicro server used 27 percent more power at idle compared to the other brands. The Intel server had a power supply control feature called cold redundancy, and the data suggest that cold redundancy can provide energy savings at low power levels. Test and evaluation methods that might be used by others having limited resources for IT equipment evaluation are explained in the report.
An introduction to radar image processing in ecology

Use of radar in ornithology, chiropterology and entomology continues to increase, driven in part by widespread online data availability. In addition to research applications, rapid growth in areas such as wind energy and aviation has prompted the use of radar for conservation. While a variety of research applications motivate ecologists to gain basic radar literacy, the ability to process and analyse radar data sets can be a daunting task that may dissuade inexperienced ecological radar users. This effect is exacerbated by vague radar methodologies in the ecology literature, as well as the combination of complex techniques and unfamiliar terminology in other radar‐focused disciplines. While radar data come in many formats and levels of detail, a common type is the two‐dimensional radar image. As rasters of data with associated spatial coordinates, radar images are relatively easy to manipulate, especially for those familiar with basic raster computations. Furthermore, because radar image data require relatively small storage space, they can be readily downloaded from a number of online sources. With this in mind, radar images provide a convenient foundation for ecological applications. A primer on radar image interpretation and processing is presented, with a focus on image composition for typical atmospheric surveillance radar scans. Additionally, a selection of existing ecological radar image processing methods are overviewed. As a starting point, a basic algorithm for automated image processing is outlined that may be modified to create specialized workflows. Three examples of the application of this algorithm are included, illustrating its modification and use for automated feature extraction. By outlining a basic algorithm, we hope to provide a clear starting point for the beginning radar user. When combined with additional existing methods, this algorithm provides a wide range of refinements and modifications that can pave a path towards sophisticated radar processing workflows. In the long term, the ability of ecologists to independently analyse radar data will lead to better ecological interpretation of radar data and a more informed application to conservation policy.
RamaNet: Computational de novo helical protein backbone design using a long short-term memory generative neural network

The ability to perform de novo protein design will allow researchers to expand the variety of available proteins. By designing synthetic structures computationally, they can utilise more structures than those available in the Protein Data Bank, design structures that are not found in nature, or direct the design of proteins to acquire a specific desired structure. While some researchers attempt to design proteins from first physical and thermodynamic principals, we decided to attempt to test whether it is possible to perform de novo helical protein design of just the backbone statistically using machine learning by building a model that uses a long short-term memory (LSTM) architecture. The LSTM model used only the ϕ and ψ angles of each residue from an augmented dataset of only helical protein structures. Though the network’s generated backbone structures were not perfect, they were idealised and evaluated post generation where the non-ideal structures were filtered out and the adequate structures kept. The results were successful in developing a logical, rigid, compact, helical protein backbone topology. This paper is a proof of concept that shows it is possible to generate a novel helical backbone topology using an LSTM neural network architecture using only the ϕ and ψ angles as features. The next step is to attempt to use these backbone topologies and sequence design them to form complete protein structures. Author summary This research project stemmed from the desire to expand the pool of protein structures that can be used as scaffolds in computational vaccine development, since the number of structures available from the Protein Data Bank was not sufficient to allow for great diversity and increase the probability of grafting a target motif onto a protein scaffold. Since a protein structure’s backbone can be defined by the ϕ and ψ angles of each amino acid in the polypeptide and can effectively translate a protein’s 3D structure into a table of numbers, and since protein structures are not random, this numerical representation of protein structures can be used to train a neural network to mathematically generalise what a protein structure is, and therefore generate new a protein backbone. Instead of using all proteins in the Protein Data Bank a curated dataset was used encompassing protein structures with specific characteristics that will, theoretically, allow them to be evaluated computationally. This paper details how a trained neural network was able to successfully generate helical protein backbones.
AKTIVITAS FUNGISIDA EKSTRAK SEMBUNG DELAN ( Sphaeranthus indicus.L.) TERHADAP Phytophthora infestans PENYEBAB PENYAKIT HAWAR DAUN PADA TANAMAN KENTANG

Penelitian ini bertujuan untuk mengetahui aktivitas fungisida ekstrak sembung delan (S. indicus L.) terhadap P. infestans. Dalam skala laboratorium pengujian dilakukan dengan menumbuhkan koloni jamur di dalam cawan petri yang mengandung media PDA dan ekstrak kasar sembung delan dengan konsentrasi 0% sampai 5%. Sedangkan uji lapangan dengan konsentrasi yang sama formulasi ekstrak kasar sembung delan dilakukan dengan menggunakan rancangan acak kelompok (RAK), dengan parameter yang diamati adalah intensitas serangan P. infestans, jumlah umbi dan berat umbi kentang yang dihasilkannya. Hasil penelitian secara In - vitro diperoleh, daya hambat ektrak kasar sembung delan pada konsentrasi 1% sampai 5% menunjukkan hasil yang signifikan (P 0,05), tetapi terdapat perbedaan yang signifikan (P<0,05) pada berat umbi yang dihasilkan. Rata –rata terjadi peningkatan persentase berat umbi berkisar antara 31,9% sampai 46%.
Avian life in a seasonally arid tropical environment: adaptations and mechanisms in breeding, moult and immune function

There is a growing appreciation of the diversity and uniqueness of tropical organisms, but evidence about the selection pressures that shape this diversity remains sketchy. In this thesis, I investigated how variation in life history traits arises from tropical environmental seasonality, starting with exploration of the annual cycle of the Common Bulbul Pycnonotus barbatus in Nigeria. This revealed that breeding was not seasonal, but moult was timed almost entirely to the wet season with only few individuals moulting into the dry season, suggesting that breeding and to a lesser extent moult, are decoupled from season, allowing me to test how breeding and moult affect immune function independent of seasonal conditions. On testing this, I found that season explained variation in immune function better than breeding or moult, but unexpectedly, immune indices were higher in the dry season and during breeding, contrary to expectations that infection risk is higher in the wet season, and that breeding constrains resources for immune function. Furthermore, I compared immune indices along the cool-wet to hot-dry environmental gradient in Nigeria and found that immune indices were rather similar. I then tested the effect of diet alteration on immune function, body mass and moult of bulbuls in captivity and found that bulbuls fed on fruits had better immune function, body mass and moult than those fed on invertebrates. These findings together suggest environmental conditions affect immune function more directly than via resource allocation trade-offs, but that variation in immune function does not follow simple environmental productivity pattern.
Antibacterial activity of Commiphora molmol in wound infections

The isolates of bacteria from patients’ infected wound from Hail General Hospital and King Khalid Hospital (Hail city, KSA) showed Gram positive as 37.5% while Gram negative as 62.5%. The Gram positive isolates were Staphylococcus aureus (31.25%) and Bacillus subtilis (6.25%) while Gram negative isolates were Escherichia coli (12.5%), Klebsiella pneumoniae (12.5%), Pseudomonas aeruginosa (12.5%), Serratia marcescens (12.5%) and Enterobacter cloacae (12.5%). The sensitivity of bacteria isolates tested against six different antibiotics: Streptozocin (STN), Piperacillin (PRL), Ceftazidime (CAZ), Ciprofloxacin (CIP), Imipenem (IMI), and Aztreonam (ATM) antibiotics. All these antibiotics showed sensitivity against Bacillus subtilis; Staphylococcus aureus found resistant to all except IMI; E. coli sensitive to all except PRL; while Enterobacter clocae was sensitive to all except STN and CIP. The inhibitory effect of diethyl ether extract from Commiphora molmol (Myrrh) on Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Klebsiella pneumoniae and Enterobacter cloacae was obvious but no inhibitory effect shown on Pseudomonas aeruginosa and Serratia marcescens. The hexane extract from Commiphora molmol (Myrrh) showed minor inhibitory effect against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, and Klebsiella pneumoniae. The water extract from Commiphora molmol (Myrrh) showed no inhibitory effect against all bacterial islaots. The antimicrobial properties of C. molmol diethyl ether, hxane and water extracts against clinical isolates of Gram positive and Gram negative bacteria could be the first report. Based on the results diethyl ether extract tested can be considered as effective anti-bacterial natural product while the results for water extract and hexane extract showed no efficacy. Keywords: Bacterial isolates, Antimicrobial resistance pattern
A comparison of control samples for ChIP-seq of histone modifications

The advent of high-throughput sequencing has allowed genome wide profiling of histone modifications by Chromatin ImmunoPrecipitation (ChIP) followed by sequencing (ChIP-seq). In this assay the histone mark of interest is enriched through a chromatin pull-down assay using an antibody for the mark. Due to imperfect antibodies and other factors, many of the sequenced fragments do not originate from the histone mark of interest, and are referred to as background reads. Background reads are not uniformly distributed and therefore control samples are usually used to estimate the background distribution at any given genomic position. The Encyclopedia of DNA Elements (ENCODE) Consortium guidelines suggest sequencing a whole cell extract (WCE, or “input”) sample, or a mock ChIP reaction such as an IgG control, as a background sample. However, for a histone modification ChIP-seq investigation it is also possible to use a Histone H3 (H3) pull-down to map the underlying distribution of histones. In this paper we generated data from a hematopoietic stem and progenitor cell population isolated from mouse foetal liver to compare WCE and H3 ChIP-seq as control samples. The quality of the control samples is estimated by a comparison to pull-downs of histone modifications and to expression data. We find minor differences between WCE and H3 ChIP-seq, such as coverage in mitochondria and behaviour close to transcription start sites. Where the two controls differ, the H3 pull-down is generally more similar to the ChIP-seq of histone modifications. However, the differences between H3 and WCE have a negligible impact on the quality of a standard analysis.
Antioxidant defence system in protein fractions of common carp (Cyprinus carpio) seminal plasma

There are growing evidences that the damage which is caused to the spermatozoa by the reactive oxygen species (ROS) plays a key role in male infertility. The seminal plasma is endowed with many enzymatic and non-enzymatic antioxidants which protect the spermatozoa against oxidative stress. The present study was undertaken to compare the level of superoxide dismutase (SOD), glutathione reductase (GR) and glutathione peroxidase (GPx) in separated protein fractions of whole common carp Cyprinus carpio seminal plasma. Seminal plasma from six male common carp was separated into four fractions. The fractions differed from each other in their total seminal plasma protein content and antioxidant status. The highest value of SOD (2.81 ± 0.11 mU/mg protein) was found in fraction 4, and the lowest (1.83 ± 0.18 mU/mg protein) in fraction 1. There were significant variations (ANOVA; P = 0.05) in GR activity, mainly between fractions 1, 2, and 4. The lowest value of GPx activity (14.9 ± 0.4 mU/mg protein) was found in fraction 2; however, the GPx activity showed low variability among fractions. We conclude that distinct seminal plasma fractions differ in antioxidant capacity. The inclusion of fractions with high levels of SOD, GR, and GPx in sperm storage medium may enhance protection against oxidative stress and promote sperm survival during the in vitro storage.
Fault-tolerant Control of Permanent Magnet Synchronous Generator in Wind Turbines

Increase of wind turbine availability is one of the main goals in wind energy research trends. The paper concerns with avoiding wind turbine shut-down under generator stator insulation degradation. We propose a fault-tolerant control that modulates the machine magnetic flux and reallocates the electrical stress from faulty to healthy generator stator parts, and extracts the maximum available power in the faulty operation under a strict condition of stopping further fault propagation. The algorithm is set for the case of 700 kW wind turbine with direct-drive permanent magnet synchronous generator but can be applied for any other type of generator as well. Proposed method is suitable for a wide range of generator operation and fault conditions, from early stage of fault-development to inter-turn short circuit. The method is also conceived as a modular extension to the conventional wind turbine control system. Simulation results are obtained and possible wind turbine operating area under different stage of fault is mapped.
Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex

Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic model of the mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically-detailed or point-neurons, with identical network connectivity. Both variants were compared to each other and to experimental recordings of neural activity during presentation of visual stimuli to awake mice. While constructing and tuning these networks to recapitulate experimental data, we identified a set of rules governing cell-class specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single cell abstraction, spatially extended or point-models, both perform similarly at the level of firing rate distributions. All data and models are freely available as a resource for the community.
Human-animal teams as an analog for future human-robot teams

Our work posits that existing human-animal teams can serve as an analog for developing effective human-robot teams. Existing knowledge of human-animal partnerships can be readily applied to the HRI domain to foster accurate mental models and appropriately calibrated trust in future human-robot teams. Human-animal relationships are examined in terms of the benefiting roles animals can play in enabling effective teaming, as well as the level of team interdependency and team communication, with the goal of developing applications in future human-robot teams.
Analysis of three dimensional cell cultures using mass spectrometry imaging

In order to better replicate disease and response to therapeutics 3D cell culture methods have been increasingly developed for use in research and industry. Two key areas where 3D cell cultures are being used as alternative models to animals are the study of prevalent diseases such as cancer and therapeutic toxicity testing in key metabolising organs such as the liver. Matrix-assisted Laser Desorption Ionisation Mass Spectrometry Imaging (MALDI-MSI) is an untargeted molecular imaging technique capable of imaging multiple molecules within a single experiment. This can be utilised for the investigation of molecular mechanisms of biological function or treatment response within 3D cell cultures, however, optimised methods are required for the analysis of these models. In this thesis, a novel 3D cell culture model of osteosarcoma was developed. Sample preparation and MALDI-MSI workflows were optimised initially for small molecule analysis. Following this, doxorubicin responses in the 3D osteosarcoma model were assessed. Detection of doxorubicin-induced changes to lipids and metabolites in 3D cell culture were subsequently detected, and Principle Component Analysis (PCA) used to identify metabolite signatures associated with doxorubicin treatment. Methods were then adapted for MALDI-MSI of proteotypic peptides within the model and a novel method for peptide quantitative mass spectrometry imaging (QMSI) was developed. MALDI-MSI successfully allowed the identification and quantification of 25 proteotypic peptides, using a 120-peptide standard array, demonstrating, for the first time, that QMSI is possible for proteomic quantification in 3D cell cultures. Development of, and preliminary MSI analysis of, a novel 3D cell culture model of liver toxicity is reported. The L-pNIPAM scaffold and HepG2 cell lines used demonstrates hepatocyte differentiation and is potentially suitable for monitoring of hepatic metabolism and adverse drug reaction. Taken together, these studies represent a considerable development in simultaneous quantification of metabolites, lipids and proteins in 3D cell cultures.