Miracle-dz/UniFAR-FTUs huggingface dataset:
CLASSIFYING MIXED PATTERNS OF PROTEINS IN MICROSCOPIC IMAGES WITH DEEP NEURAL NETWORKS

Nowadays, accurate diagnosis of diseases, their treatment and prognosis is a very acute problem of modern medicine. By studying information about human proteins, you can identify differentially expressed proteins. These proteins are potentially interesting biomarkers that can be used for an accurate diagnosis, prognosis, or selection of individual treatments, especially for cancer. A surprising finding from this research is that we have relatively few proteins that are tissue specific. Almost half of all proteins are categorized as housekeeping proteins, expressed in all cells. Only 2,300 proteins in the human body have been identified as tissue enriched, meaning they have elevated expression levels in certain tissues. Thanks to advances in high-throughput microscopy, images are generated too quickly for manual evaluation. Consequently, the need for automating the analysis of biomedical images is as great as ever to speed up the understanding of human cells and diseases. Historically, the classification of proteins was limited to individual patterns in one or more cell types, but in order to fully understand the complexity of a human cell, models must classify mixed patterns according to a number of different human cells. The article formulates the problem of image classification in medical research. In this area, classification methods using deep convolutional neural networks are actively used. Presented article gives a brief overview of the various approaches and methods of similar research. As a dataset was taken “The Human Protein Atlas”, that presents a tissue-based map of the human proteome, completed in 2014 after 11 years of research. All protein expression profiling data is publicly accessible in an interactive database, enabling tissue-based exploration of the human proteome. It was done an analysis of the work and the methods that were used during the research. To solve this problem, the deep neural network model is proposed taking into account the characteristics of the domain and the sample under study. The neural network model is based on Inception-v3 architecture. Optimization procedure contains combination of several tweaks for fast convergence: stochastic gradient descent with warm restarts (learning rate schedule for exploring different local minima), progressive image resizing (training starts from small resolution and sequentially increases each cycle of SGDR). We propose new method for threshold selection for F1 measure. Developed model can be used to create an instrument integrated into the medical system of intellectual microscopy to determine the location of the protein from a high-performance image.
Animal reservoirs of Trypanosoma brucei gambiense around the old Gboko sleeping sickness focus in Nigeria

The exact role of animal reservoirs in the epidemiology of Trypanosoma brucei gambiense, a parasite ravaging affected rural parts of sub-Saharan Africa, still remains unclear. However, the existence of the parasite in animals is well documented in other parts of Africa. A randomised cross sectional study was conducted in an old sleeping sickness focus in Nigeria by screening 600 cattle and 600 pigs using the card agglutination test for trypanosomosis (CATT) and identifying trypanosomes using ITS 1 and TgsGP PCRs. Data generated were analysed using the Chi square test and odds ratio at 95% confidence interval. The overall infection rates for the CATT and TgsGP-PCR were 8.9 and 0.9%, respectively which varied significantly between cattle (7.2%) and pigs (10.7%) with the CATT. The CATT based infection rates in relation to study sites, breeds and management practices varied significantly (p < 0.05) between 2.0 and 17.0%, while the PCR based ranged between 0 and 1.7%. Trypanosomes of animal origin identified by ITS 1 PCR were T. brucei (4.2%), Trypanosoma congolense forest (3.2%), T. congolense savannah (2.0%), Trypanosoma vivax (2.2%) and mixed infections (1.5%) in cattle as well as T. brucei (4.8%), T. congolense forest (1.8%), T. congolense savannah (1.0%) and mixed infections (1.2%) in pigs. T. brucei gambiense and other animal trypanosomes were identified among animals in the focus, indicating the existence of animal reservoirs of human infective T. b. gambiense. This suggests that the inclusion of reservoir control component in T. b. gambiense control programmes will help in the control of this parasite in this focus. Key words: Animal reservoirs, Trypanosoma brucei gambiense, sleeping sickness focus, card agglutination test for trypanosomosis (CATT), ITS-PCR, TgsGP-PCR, Gboko, Nigeria.
Kılıçoğlu, Gökhan and Kılıçoğlu, Derya Yılmaz and Hammersley-Fletcher,

Schools in Turkey are primarily influenced by the Ministry of National Education (Milli Eğitim Bakanlığı) through laws and regulations. Compliance with regulations might be characterised as superficial in many respects and can lead to schools ‘decoupling’ their espoused structures from the realities of practice. In other words, they might have policies to indicate compliance whilst at the same time practising in ways that are not coherent with these stated aims and ‘ideals’. Consequently, there can be incongruence between the apparent conformity and the reality of daily activities referred to by Brunsson as ‘organizational hypocrisy’. There are serious dangers with not recognising issues around proclaimed values and accepted expectations which may have pathological consequences for organisations. This article draws on semi-structured interviews with 21 staff including principals, vice principals and teachers from nine schools in the Eskişehir Provincial Directorate of National Education in Turkey to investigate the conditions under which hypocrisy is more likely to happen and what the consequences of it may be. We provide school staff with important insights on how to decrease hypocrisy in their schools and increase the authenticity of school approaches in a complex, educational environment.
Studies on the Effect of Salinity and Spraying of Microelements on Vegetative Growth of some Turfgrasses

Two field experiments were located at the place of Abu Jerida of Faculty of Agric. Damietta Univ. during two seasons of 20152016 and 2016-2017. The research aims to test the effect of chemical fertilizer as microelements and salinity on two species of turfgrass (paspalum and seashore paspalum). 16 treatments were arranged in split block design with 3 replicates as follows: 4 levels of salinity (control, 1800, 3600 and 7200 ppm) as main plot and 4 sources of micronutrient in foliar way (without, Fe, Mn and Zn) as sub plot. The obtained results could be summarized as follows: fresh and dry weight g/plant, moisture%, chlorophyll content, Fe, Zn and Mn content as well as protein and carbohydrates content % decreased with increasing salinity levels. However, application of micro elements improved the previous traits by causing significant increases in the values with the corresponding controls. Foliar application of iron was the most effective one. Except protein was with zinc. As for, Paspalum, found that seashore paspalum recorded higher mean values of fresh weight than paspalum. Regarding to the interaction effect found that using iron as foliar application under low level of salinity recorded the highest mean values of parameters under study.
Empirical Implementation of Industry 4.0 Model among Malaysian and Nigerian SMEs

The primary objective of this study is to examine the factors that influence the implementation of Industry 4.0 among Malaysian and Nigerian Small and Medium Enterprises. The Questionnaires were distributed to SMEs operators in both countries while analysis was done with 74 and 95 responses from Malaysia and Nigeria respectively using Partial Least Square Structural Equation Modelling (PLS-SEM 3). Based on the findings from Malaysian data, information access, cost reduction, and efforts coordination significantly and positively influence the implementation of IR 4.0 while reluctance behaviour is not significant. For Nigerian data, information access, reluctance behaviour and effort coordination significantly and positively influence implementation of Industry 4.0 while effort coordination is not significant. The implications for both academia, practitioners, and policy makers are highlighted.
Lipid residues in early hunter-gatherer ceramics from Finland

The adoption of pottery technology by hunter-gatherers in the Baltic region has mainly been placed within the concept of resource intensification, as a cultural choice that assisted an increased economic focus on aquatic resources. In Finland, a non-specialized pottery use has earlier been suggested on the basis of lipid residue analysis data for Early Neolithic1 ceramics from a number of sites on the south-west coast that involve processing of both aquatic and terrestrial animal prod ucts. Our study is an attempt to further explore the relationship between the early pottery use, diet and environment in this particular region. For this purpose, we expanded the range of early pottery traditions and localities to be analyzed, and applied gas chromatographic and mass spectrometric (GC-MS) analysis on the absorbed lipid residues. The study material comprises ceramics of the Säräisniemi 1 (Sär 1), Sperrings 1 (Ka I:1) and Sperrings 2 (Ka I:2) pottery traditions, as well as of the Jäkärlä Ware group, from coastal and inland sites spanning a period from ca. 5100 to 4000 cal BC. Our results strengthen the above observation for Early Neolithic Finland and further suggest that both aquatic and terrestrial animal resources were processed in vessels belonging to most of the analyzed groups, irrespective of coastal/inland site division and pottery ware culture. This additionally indicates a variability of motives behind the introduction of pottery within the Baltic Sea region, considering pottery use evidence in the neighbouring Estonia, where the earliest local and contemporaneous Narva pottery culture had a more specialized use focused on the processing of aquatic resources.
DECISION MAKING:A CASE STUDY

The aim of this paper is to investigate participation in decision making mediated by e-mail (e-PDM) among organisational members that are in similar hierarchical positions. Data analysis, based on an empirical research conducted in an Italian governmental agency, investigates the factors which affect the adoption of horizontal e-PDM in the workplace and to what extent this is mediated by the interplay between technology and social context. Our results suggest that social structuration of technology and social processes in organisations do have an impact on e-mail use for participative purposes, and that, along with group characteristics, leadership plays a major role in enabling work group members to increase horizontal e-PDM.
Automatically Generating Case Notes From Digital Transcripts of Doctor-patient Conversations Using Text Mining

Current health care systems require clinicians to spend a substantial amount of time to digitally document their interactions with their patients through the use of electronic health records (EHRs), limiting the time spent on face-to-face patient care. Moreover, the use of EHRs is known to be highly inefficient due to additional time it takes for completion, which also leads to clinician burnout. In this project, we explore the feasibility of developing an automated case notes system for psychiatrists using text mining techniques that will listen to doctor-patient conversations, generate digital transcripts using speech-to-text conversion, classify information from the transcripts in to relevant categories, and automatically generate structured case notes. In our preliminary work, we develop a human powered doctor-patient conversation transcript annotator and obtain a gold standard dataset through National Alliance of Mental Illness (NAMI) Montana. We model the task of classifying parts of conversations in to six broad categories such as medical and family history as a supervised classification problem and apply several popular machine learning algorithms. According to our preliminary experimental results obtained through 5-fold cross validation, Support Vector Machines are able to classify an unseen transcript with an average AUROC (area under the receiver operating characteristic curve) score of 89%. Finally, we use part-of-speech (POS) tagging, grammatical rules of English language and verb conjugation, we generate written versions of the pieces of text belonging to different categories. These formal text are aggregated in to filling different sections of the EHR forms.
Chapter 3 HPV Diagnosis in Vaccination Era

It will be necessary to diagnose HPV in processes other than cervical cancer, and we refer not only to their involvement in tumors with a demonstrated relationship, as in the anal region, but also to other locations in which their participation is suggested, as in the oropharyngeal tumors. Standardization in the collection and sample processing will be crucial in order to achieve accurate results involving an aid in the diagnosis and prognosis of these processes and their possible prevention.
Foxes, voles, and waders: drivers of predator activity in wet grassland landscapes

Impacts of generalist predators on declining prey populations are a major conservation issue, but management of this situation is constrained by limited knowledge of the factors influencing predator distribution and activity. In many declining populations of ground-nesting waders, high levels of nest and chick predation are preventing population recovery. Red foxes, Vulpes vulpes, are the main predator but their primary prey is small mammals. On wet grasslands managed for breeding waders, small mammals are concentrated in tall vegetation outside of fields, and nests closer to these patches are less likely to be predated. To assess whether these patterns result from fox attraction to small mammals, and thus the potential for management of tall vegetation to influence nest predation rates, we quantify seasonal and spatial variation in fox and small mammal activity in relation to tall vegetation patches. Across wet grassland sites, tall vegetation patches of any size (> 0.05 ha) supported small mammals and small mammal activity increased throughout the wader breeding season, while the use of fox track plots within fields declined seasonally. Although within field fox track plot use did not vary with distance to tall vegetation, over the 1064 nights of trail camera recording, foxes were seen in areas with tall vegetation on 13 nights compared with short vegetation on only two nights. These findings suggest that lower predation rates of lapwing nests close to tall vegetation could reflect fox attraction to areas with small mammal activity, but any such effects would primarily operate later in the breeding season, and may therefore primarily influence late nests and chicks.
Online system identification by sparse component analysis based on wavelet transform

Recently, online identification of structures, only based on the measured outputs during the vibration, has received much attention. One of the most powerful methods of offline system identification is the sparse component analysis (SCA) method which is a subset of blind source identification (BSI) methods. This method by transferring the dynamic responses from time domain to frequency one has led to the sparsity in the data and accordingly the modal parameters of the system are identified. In this research, a Wavelet Transform based Sparse Component Analysis (WT-SCA) method is suggested to identify the system. Then, using WT-SCA and a semi-active tuned mass damper (STMD), an algorithm is presented to achieve a smart structure. The results show that the WT-SCA is able to identify the system momentarily with an acceptable accuracy and also reduce the dynamic responses of a structure equipped with STMD.
Running title: Diet and temperature effects on Daphnia

25 Food quality and temperature can affect zooplankton production in lakes by altering 26 organismal metabolism. However, the influence of these factors on consumer nutritional 27 physiology and population biomass remains relatively understudied in natural populations. Here, 28 we examined seasonal changes in body stoichiometry, biochemistry, and population biomass in 29 two Daphnia species collected from two separate lakes differing in dietary phosphorus (P) 30 supply. Food quality, measured as seston carbon:P (C:P) ratios, varied throughout the study in 31 each lake, and water temperatures generally increased across the growing season. Daphnid 32 elemental composition was correlated with food quality in both populations, but relationships 33 between daphnid body stoichiometry and temperature were consistently stronger as Daphnia 34 body C:P ratios and content of major biochemical pools declined simultaneously throughout the 35 summer, which largely coincided with increased water temperatures. Warmer temperatures were 36 associated with relaxed %P-RNA coupling as daphnid body RNA content declined and P content 37 remained relatively high. These responses combined with temperature related decreases in 38 Daphnia body %lipids and %C appeared to explain declines in daphnid body C:P ratios in both 39 lakes over the growing season. Seasonal changes in population biomass were related to both food 40 quality and water temperature in the lower nutrient lake. Biomass production under more 41 eutrophic conditions however was unrelated to food quality and was instead associated with 42 seasonal temperature changes in the higher nutrient lake. Overall, our study shows that seasonal 43 changes in temperature and resource quality may differentially affect consumer stoichiometry 44 and biomass production in lake ecosystems by altering consumer elemental metabolism. 45 46 47
The production of meaningful route directions using landmark extraction

In order for automated navigation systems to operate effectively, the route instructions they produce must be clear, concise and easily understood by users. The quality and coherence of route instructions may be improved via landmark chunking, whereby a turning instruction is given with reference to a nearby landmark. In order to incorporate a landmark within a coherent sentence, it is necessary to first understand how that landmark is conceptualised by travellers — whether it is perceived as point-like, line-like or area-like. This conceptualisation determines which prepositions and verbs are appropriate when referring to the landmark. This thesis investigates the viability of automatically classifying the conceptualisation of landmarks relative to a given city context. First, we construct a web-based annotation interface to solicit gold-standard judgements from expert annotators over a set of landmarks for three major cities (Melbourne, Hamburg and Tokyo). We then experiment with the use of web data to learn the default conceptualisation of those landmarks, analysing their occurrence in a fixed set of lexico-syntactic patterns. Based on this, we develop two automated landmark classifiers and evaluate them against the gold standard annotations, investigating patterns of convergence or divergence in landmark categorisation.
Patch-Based Representation of Visual Speech

Visual information from a speaker's mouth region is known to improve automatic speech recognition robustness, especially in the presence of acoustic noise. To date, the vast majority of work in this field has viewed these visual features in a holistic manner, which may not take into account the various changes that occur within articulation (process of changing the shape of the vocal tract using the articulators, i.e lips and jaw). Motivated by the work being conducted in fields of audio-visual automatic speech recognition (AVASR) and face recognition using articulatory features (AFs) and patches respectively, we present a proof of concept paper which represents the mouth region as a ensemble of image patches. Our experiments show that by dealing with the mouth region in this manner, we are able to extract more speech information from the visual domain. For the task of visual-only speaker-independent isolated digit recognition, we were able to improve the relative word error rate by more than 23\% on the CUAVE audio-visual corpus.
Structure of the human k-opioid receptor in complex with JDTic

Opioid receptors mediate the actions of endogenous and exogenous opioids on many physiological processes, including the regulation of pain, respiratory drive, mood, and—in the case of k-opioid receptor (k-OR)—dysphoria and psychotomimesis. Here we report the crystal structure of the human k-OR in complex with the selective antagonist JDTic, arranged in parallel dimers, at 2.9 Å resolution. The structure reveals important features of the ligand-binding pocket that contribute to the high affinity and subtype selectivity of JDTic for the human k-OR. Modelling of other important k-OR-selective ligands, including the morphinan-derived antagonists norbinaltorphimine and 59-guanidinonaltrindole, and the diterpene agonist salvinorin A analogue RB-64, reveals both common and distinct features for binding these diverse chemotypes. Analysis of site-directed mutagenesis and ligand structure–activity relationships confirms the interactions observed in the crystal structure, thereby providing a molecular explanation for k-OR subtype selectivity, and essential insights for the design of compounds with new pharmacological properties targeting the human k-OR.
Inspection method of images' overlap of UAV photogrammetry based on features matching

The overlapping degree of UAV aerial imagery is an important parameter in judging the quality of aerial photography. This paper applies the technology of image feature matching to realize the automatic inspection of low-altitude UAV aerial image overlap. It utilizes the feature point matching and homography transformation model, which can accurately identify the overlapping area of the image and overcome the defect caused by the large rotation angle of UAV’s images and irregular overlap area. We use various feature-extracting algorithms to verify the practicability of this method. It shows that it can calculate the overlapping degree of adjacent aerial images efficiently and accurately, which improve the production efficiency of aerial photogrammetry.