Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Class Classification of Blood Cells - End to End Computer Vision based diagnosis case study

The diagnosis of blood-based diseases often involves identifying and characterizing patient blood samples. Automated methods to detect and classify blood cell subtypes have important medical applications. Automated medical image processing and analysis offers a powerful tool for medical diagnosis. In this work we tackle the problem of white blood cell classification based on the morphological characteristics of their outer contour, color. The work we would explore a set of preprocessing and segmentation (Color-based segmentation, Morphological processing, contouring) algorithms along with a set of features extraction methods (Corner detection algorithms and Histogram of Gradients(HOG)), dimensionality reduction algorithms (Principal Component Analysis(PCA)) that are able to recognize and classify through various Unsupervised(k-nearest neighbors) and Supervised (Support Vector Machine, Decision Trees, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Naive Bayes) algorithms different categories of white blood cells to Eosinophil, Lymphocyte, Monocyte, and Neutrophil. We even take a step forwards to explore various Deep Convolutional Neural network architecture (Sqeezent, MobilenetV1,MobilenetV2, InceptionNet etc.) without preprocessing/segmentation and with preprocessing. We would like to explore many algorithms to identify the robust algorithm with least time complexity and low resource requirement. The outcome of this work can be a cue to selection of algorithms as per requirement for automated blood cell classification.
Prevention and Resolution of Conflicts in Social Navigation - a Survey

With the approaching goal of having robots collaborate in shared human-robot environments, navigation in this context becomes both crucial and desirable. Recent developments in robotics have encountered and tackled some of the challenges of navigating in mixed human-robot environments, and in recent years we observe a surge of related work that speciﬁcally targets the question of how to handle conﬂicts between agents in social navigation. These contributions oﬀer models, algorithms, and evaluation metrics, however as this research area is inherently interdisciplinary, many of the relevant papers are not comparable and there is no standard vocabulary between the researchers. The main goal of this survey is to bridge this gap by proposing such a common language, using it to survey existing work, and highlighting open problems. It starts by deﬁning a conﬂict in social navigation, and oﬀers a detailed taxonomy of its components. This survey then maps existing work while discussing papers using the framing of the proposed taxonomy. Finally, this paper propose some future directions and problems that are currently in the frontier of social navigation to help focus research eﬀorts.
Universal Consistency of Deep Convolutional Neural Networks

Compared with avid research activities of deep convolutional neural networks (DCNNs) in practice, the study of theoretical behaviors of DCNNs lags heavily behind. In particular, the universal consistency of DCNNs remains open. In this paper, we prove that implementing empirical risk minimization on DCNNs with expansive convolution (with zero-padding) is strongly universally consistent. Motivated by the universal consistency, we conduct a series of experiments to show that without any fully connected layers, DCNNs with expansive convolution perform not worse than the widely used deep neural networks with hybrid structure containing contracting (without zero-padding) convolutional layers and several fully connected layers.
A Label Management Mechanism for Retinal Fundus Image Classification of Diabetic Retinopathy

—Diabetic retinopathy (DR) remains the most prevalent cause of vision impairment and irreversible blindness in the working-age adults. Due to the renaissance of deep learning (DL), DL-based DR diagnosis has become a promising tool for the early screening and severity grading of DR. However, training deep neural networks (DNNs) requires an enormous amount of carefully labeled data. Noisy label data may be introduced when labeling plenty of data, degrading the performance of models. In this work, we propose a novel label management mechanism (LMM) for the DNN to overcome overﬁtting on the noisy data. LMM utilizes maximum posteriori probability (MAP) in the Bayesian statistic and time-weighted technique to selectively correct the labels of unclean data, which gradually purify the training data and improve classiﬁcation performance. Comprehensive experiments on both synthetic noise data (Messidor & our collected DR dataset) and real-world noise data (ANIMAL-10N) demonstrated that LMM could boost performance of models and is superior to three state-of-the-art methods.
Potential use of the N2/Ar ratio as a constraint on the oceanic fixed nitrogen loss

Using a global ocean biogeochemical model, we investigate the suitability of the N2/Ar supersaturation ratio (ΔN2/Ar) as a tracer of marine nitrogen fixation and denitrification, i.e., the main biological processes that add or remove fixed nitrogen to or from the ocean. In a series of factorial simulations, we demonstrate that, in regions away from the oxygen minimum zones (OMZs), the ΔN2/Ar characteristics are mostly determined by benthic denitrification occurring in the deep ocean with minor contributions from benthic and water column denitrification at shallower depths. In the OMZs, the subsurface maxima of ΔN2/Ar are mainly determined by water column denitrification. In contrast, nitrogen fixation has little impact on ΔN2/Ar owing to the rapid loss of the N2 supersaturation signal through air‐sea exchange. We thus conclude that ΔN2/Ar can act as a powerful constraint on water column and benthic denitrification occurring in intermediate to deep waters, but it cannot be used to estimate nitrogen fixation. A comparison between the currently very limited observations of the ΔN2/Ar with our model results shows an acceptable level of agreement, suggesting that the model's prescribed rates and distributions of benthic and water column denitrification (i.e., 140 and 52 Tg N yr−1, respectively) are reasonable and confirm the results derived from other constraints.
The Effect of Temperature and Composition on the Al-Si Distribution in Anorthite

The type (b) superstructure reflections in CaAl^Si^Og, indicative of Al-Si order, are unchanged in heat-treated crystals until melting begins. Polymorphism of the type shown by the Naand üT-feldspars and best explained as due to Al-Si order-disorder, has no counterpart in pure anorthite. The presence of NaAlSizOf in solid solution disrupts the 1/1 -AltSi ratio of anorthite and it is possible to produce metastable disordered crystals by rapid crystallization of a melt containing some NaAlSi3Os. The Al-Si disorder can be of two types: short-range disorder, expressed by weakened (or absent) superstructure reflections, and long-range disorder ("out-of-step" domains within which a high degree of short-range order can be present), expressed by diffuse superstructure reflections. The effect of the metastable Al-Si disorder on the Oo-order/disorder relations is discussed, as is the effect of disorder on lattice constants.
f-Element-metal bond chemistry

Abstract Compared to the overwhelming prevalence of f-element-carbon, -nitrogen, -oxygen or -halide ligand linkages, the use of metal-based fragments as ligands is underdeveloped. This contrasts directly to the extensively developed fields of d- and p-block metal-metal complexes, which are still burgeoning. This review outlines the development of compounds that possess polarised covalent f-element-metal bonds. For this review, the f-element is defined as (i) a group 3 metal; (ii) a lanthanide metal; (iii) the actinide metals thorium or uranium. The metal is defined as: (i) a d-block transition metal; (ii) a group 13 metal (aluminium or gallium); (iii) a group 14 metal (silicon, germanium or tin); (iv) a group 15 metal (antimony or bismuth) metal. Although silicon, germanium and antimony are traditionally classified as metalloids, they are included for completeness. We focus on complexes that have been structurally authenticated by single crystal X-ray diffraction, and we highlight novel aspects of their syntheses, properties and reactivities.
Setting Objective Clinical Assessment Tools for Circadian Rhythm Sleep-Wake Disorders – A Community-Based Cross-Sectional Epidemiological Study

Introduction Circadian rhythm sleep-wake disorder (CRSWD) is an often-misdiagnosed group of sleep disturbances with limited data concerning diagnostic and therapeutic algorithms in the general population. Therefore, reported prevalence varies in the literature due to different case definitions, methodological, and environmental factors. Objectives The purpose of our cross-sectional study was to estimate the prevalence of CRSWD in the general population of Cyprus and to suggest clinical parameters for the assessment of atypical sleep schedules. The estimation was carried out by introducing normal preset sleep time limits, according to the imposed local environment and by administering well-established questionnaires for symptoms and consequence dysfunction, as objective evaluation tools. Methods In a nationwide epidemiological survey, 4118 Cypriot adult participants, selected and stratified to represent the general population, were interviewed on sleep habits and complaints by computer-assisted telephone interviewing (CATI). In the second stage, 250 adults were randomly selected from the initial representative sample, for a CRSWD assessment. According to the proposed diagnostic criteria, patients were interviewed about sleepiness and/or insomnia, and daytime dysfunction (fatigue, anxiety, and depression). They were also assessed by a weekly sleep diary for sleep schedules. Finally, all participants underwent a Type III Sleep Study, to rule out obstructive sleep apnea. Results From 195 enrolled participants (response rate 78%), 25 individuals (12.8%) met the criteria for CRSWD. The two most prevalent disorders were delayed sleep-wake phase disorder (DSWPD) (10pts, 5.1%) and shift work sleep disorder (SWD) (13, 6.7%). Less prevalent disorders included irregular sleep-wake rhythm disorder (ISWRD) (1, 0.5%) and advanced sleep-wake phase disorder (ASWPD) (1, 0.5%). Conclusions According to our data, CRSWDs are common in the general population of Cyprus, especially DSWPD and SWD. Affected individuals usually suffer from sleep deprivation and complain about insomnia, sleepiness and depression.
Effects of short-term grazing prohibition on soil physical and chemical properties of meadows in Southwest China

Background Grassland plays an important role in the ecosystem, but overgrazing harms the grassland system in many places. Grazing prohibition is an effective method to restore grassland ecosystems, and it plays a great role in realizing the sustainable development of grassland systems. Therefore, it is necessary to carry out research on the influence of regional grazing prohibition on the physical and chemical properties of different grassland systems. Methods In Potatso National Park, Southwest China, we selected experimental plots in the artificial grazing meadow area to study the effects of grazing prohibition on plant and soil indexes in subalpine meadows and swamp meadows. We investigated the biomass and species diversity of grazing prohibition treatment and grazing treatment plots and sampled and tested the soil index. The variation percentage was used to remove the original heterogeneity and yearly variation, allowing us to compare differences in plant index and soil index values between grazing prohibition and grazing treatments. Results Grazing prohibition increased the aboveground biomass, total biomass, total meadow coverage, average height, richness index, Shannon diversity index and evenness index and reduced the belowground biomass and root/shoot ratio in the subalpine meadow and swamp meadow. Additionally, grazing prohibition reduced the pH and soil bulk density and increased the soil total carbon, soil organic carbon, soil total nitrogen, soil hydrolyzable nitrogen, soil total phosphorus and soil available phosphorus in the subalpine meadow and swamp meadow. Nonmetric multidimensional scaling (NMDS) analysis showed that both plant indexes and soil indexes were significantly different between grazing and grazing prohibition treatments and between meadow types. Short-term grazing prohibition had a great impact on improving the fertility of meadow soil in the study area. We suggest that long-term and extensive research should be carried out to promote the restoration and sustainable development of regional grassland systems.
Identification of Independent and Communal Differentially Expressed Genes as Well as Potential Therapeutic Targets in Ischemic Heart Failure and Non-Ischemic Heart Failure

Background Heart failure (HF) is a rapidly growing public health problem, and its two main etiological types are non-ischemic heart failure (NIHF) and ischemic heart failure (IHF). However, the independent and common mechanisms of NIHF and IHF have not been fully elucidated. Here, bioinformatic analysis was used to characterize the difference and independent pathways for IHF and NIHF, and more importantly, to unearth the common potential markers and therapeutic targets in IHF and NIHF. Methods Two data sets with accession numbers GSE26887 and GSE84796 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the independent and communal DEGs of NIHF and IHF, a functional annotation, protein–protein interaction (PPI) network analysis, co-expression and drug–gene interaction prediction analysis, and mRNA-miRNA regulatory network analysis were performed for DEGs. Results We found 1146 independent DEGs (DEGs2) of NIHF mainly enriched in transcription-related and 2595 independent DEGs (DEGs3) of IHF mainly enriched in immune-related. Moreover, 185 communal DEGs (DEGs1) were found between NIHF and IHF, including 93 upregulated genes and 92 downregulated genes. Pathway enrichment analysis results showed that GPCR pathways and biological processes are closely related to the occurrence of HF. In addition, three hub genes were identified from PPI network, including CCL5, C5 and TLR3. Conclusion The identification of DEGs and hub genes in this study contributes to a novel perception for potential functional mechanisms and biomarkers or therapeutic targets in NIHF and IHF.
Oral glucose tolerance test in diabetes, the old method revisited

The oral glucose tolerance test (OGTT) has been widely used both in clinics and in basic research for a long time. It is applied to diagnose impaired glucose tolerance and/or type 2 diabetes mellitus in individuals. Additionally, it has been employed in research to investigate glucose utilization and insulin sensitivity in animals. The main aim of each was quite different, and the details are also somewhat varied. However, the time or duration of the OGTT was the same, using the 2-h post-glucose load glycemia in both, following the suggestions of the American Diabetes Association. Recently, the use of 30-min or 1-h post-glucose load glycemia in clinical practice has been recommended by several studies. In this review article, we describe this new view and suggest perspectives for the OGTT. Additionally, quantification of the glucose curve in basic research is also discussed. Unlike in clinical practice, the incremental area under the curve is not suitable for use in the studies involving animals receiving repeated treatments or chronic treatment. We discuss the potential mechanisms in detail. Moreover, variations between bench and bedside in the application of the OGTT are introduced. Finally, the newly identified method for the OGTT must achieve a recommendation from the American Diabetes Association or another official unit soon. In conclusion, we summarize the recent reports regarding the OGTT and add some of our own perspectives, including machine learning and others.
Application of artificial intelligence-driven endoscopic screening and diagnosis of gastric cancer

The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available. The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions. Simultaneously, with the development of convolutional neural network, artificial intelligence (AI) has made unprecedented breakthroughs in medical imaging, including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding. In the past demi-decade, applications of AI systems in gastric cancer have also emerged. With AI’s efficient computational power and learning capacities, endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes. So far, several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes, with most systems achieving an accuracy of more than 80%. However, their feasibility, effectiveness, and safety in clinical practice remain to be seen as there have been no clinical trials yet. Nonetheless, AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection, treatment guidance and prognosis prediction of gastric lesions. This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.
Glycemic control and its determinants among patients with type 2 diabetes mellitus at Menelik II Referral Hospital, Ethiopia

Objective: The objective of the study was to explore the level of glycemic control and its determinants among patients with type 2 diabetes mellitus at Menelik II Referral Hospital, Addis Ababa, Ethiopia. Methods: Cross-sectional study design was employed. The sample size was determined using a single proportion formula and 245 patients with type 2 diabetes mellitus were involved in this study. Systematic sampling method was used to select the study subjects. Standard questionnaire was used to collect patient’s biographic data, economic data, self-care activities, and patient compliance to medications. Summary statistics of a given data were calculated. Logistic regression model was used to measure the relationship between the outcome and predictor variable. Direction and strength of association was expressed using odds ratio and 95% confidence interval. Result: More than three-fourth, 191 (80.3%) of diabetic patients had poor glycemic control. Poor glycemic control was found to be 7.03 times higher among diabetic patients with duration of 5–10 years (adjusted odds ratio = 7.03, 95% confidence interval = 2.7–18.6). Similarly, diabetic patients with a duration of above 10 years were poorly controlled their blood sugar level (adjusted odds ratio = 2.3, 95% confidence interval = 1.028–5.08) in comparison to diabetic patients with a duration of fewer than 5 years. It was also found that compliance with a specific diet was significantly associated with good control of blood sugar level (adjusted odds ratio = 3.7, 95% confidence interval = 1.24–11.13). Conclusion: The magnitude of patients with poor glycemic control was high. Duration of diabetes and non-compliance with diets high in fruits, vegetables, and diets low in fat and sugar were significantly related to uncontrolled blood glucose levels. Therefore, developing strategies targeted toward improving blood glucose control with special attention to diabetes mellitus (DM) patients with a duration of ⩾5 years and those who poorly comply with their diet was strongly recommended.
Hematologic Findings in Pregnancy: A Guide for the Internist

Hematologic changes in pregnancy are common and can potentially lead to maternal and fetal morbidity. Here, we present various hematologic manifestations seen in pregnant women. Iron deficiency anemia (IDA) is the most common cause of anemia in pregnancy. Physiologically, the state of pregnancy results in increased iron demand. Iron deficiency is important to diagnose and treat early for better maternal and fetal outcomes. An algorithmic approach is used for the repletion of iron storage, starting with oral elemental iron daily and escalating to intravenous iron if necessary. Folate and cobalamin are necessary elements for deoxyribonucleic acid (DNA) synthesis, fetal growth, and maternal tissue development, and deficiency in these elements can be a cause for anemia in pregnancy. Thrombocytopenia is currently the second most common hematologic condition in pregnancy after anemia. There is a wide range of etiology for thrombocytopenia in pregnancy from benign to life-threatening causes that require prompt diagnosis and treatment. These conditions include gestational thrombocytopenia, thrombotic thrombocytopenic purpura, pregnancy-associated atypical hemolytic-uremic syndrome, and immune thrombocytopenia. Acquired bleeding disorders that can cause major complications in pregnancy include von Willebrand disease (vWD) and coagulation factor deficiencies. Women with vWD are at increased risk of pregnancy bleeding and postpartum hemorrhage. Pregnancy can also produce a physiologic hypercoagulable state, leading to life-threatening conditions like thromboembolism. Diagnosis, treatment options, and guidelines for the management of these conditions will be explored in this review.
Intraoperative Oxygen Concentration and Postoperative Delirium After Laparoscopic Gastric and Colorectal Malignancies Surgery: A Randomized, Double-Blind, Controlled Trial

Purpose Postoperative delirium (POD) is common in elderly patients undergoing laparoscopic surgery for gastric and colorectal malignancies. POD may be affected by different fraction of inspired oxygen (FiO2). The purpose of this study was to compare the effects of different FiO2 on POD. Patients and Methods A randomized, double-blind controlled trial was performed in Qingdao Municipal Hospital Affiliated to Qingdao University. A total of 662 patients aged 65 to 85 years old underwent isolated laparoscopic radical gastrectomy, radical resection of colon cancer, or radical resection of rectal cancer only. A random number table method was used to divide the patients into two groups: 40% FiO2 (group A) and 80% FiO2 (group B). The primary endpoint was the incidence of POD, which was assessed by the Confusion Assessment Method (CAM) twice daily during the first 7 postoperative days, and POD severity was measured by the Memorial Delirium Assessment Scale (MDAS). The secondary endpoints were the intraoperative regional cerebral oxygen saturation (rSO2), Bispectral (BIS) index, invasive arterial blood pressure (IABP), oxygen saturation (SpO2), end-tidal carbon dioxide partial pressure (PETCO2), the number of atelectasis cases and visual analogue scale (VAS) scores on days 1–7 after surgery. Results The incidence of POD was 19.37% (122/630), including 20.38% (64/314) in group A and 18.35% (58/316) in group B. No statistical significance was found in the incidence of POD between the two groups (P > 0.05); compared with group B, SpO2, rSO2 and PaO2 decreased at T2 to T4 time point (P < 0.01), and the incidence of postoperative atelectasis decreased (P < 0.05) in group A. Conclusion The incidence of POD was not significantly affected by different FiO2 and the incidence of postoperative atelectasis was decreased at low FiO2.