Miracle-dz/UniFAR-FTUs huggingface dataset:
Etiological factors in young patients with Retinal Vein Occlusion

Objective: To present the etiological factors of patients with Retinal Vein Occlusion (RVO) under the age of 50 years. Methods: The study was conducted at Ege University Medicine Faculty Department of Ophthalmology. The clinical records of patients with RVO under the age of 50 seen between January 2014 and March 2018 were analyzed retrospectively. Forty patients comprised the study. Detailed ophthalmologic examination was performed. Past medical history, drug use, thrombophilic features, hyperviscosity syndromes and pathologies that may cause vasculitis were noted. Results: Forty patients, 22 (55%) male and 18 (45%) female, were included. Mean age was 41.6 ± 10.01 years. Mean intraocular pressure and best-corrected visual acuity were 16.8 ± 5.47mmHg and 0.76 ± 0.64 logMAR, respectively. Hyperhomocystenemia (15 patients, 37.5%), Behçet’s disease (three patients, 7.5%), diabetes and/or hypertension (16 patients, 40%), methylenetetrahydrofolate reductase gene mutation (11 patients, 27.5%), prothrombin gene mutation (four patients, 10%) and factor V Leiden mutation (five patients, 12.5%) were present among the patients as etiological factor. Multiple etiological factors were detected in 11 (27.5%) patients. Factor V Leiden mutation and methylenetetrahydrofolate reductase gene mutation were detected in one patient (2.5%) with Behçet’s disease. Four patients with diabetes and/or hypertension also had hyperhomocystenemia and one of them had additionally prothrombin gene mutation. Two patients with methylenetetrahydrofolate reductase gene mutation also had a factor V Leiden mutation and one of them had additionally a prothrombin gene mutation. Three patients with methylenetetrahydrofolate reductase gene mutation also had hyperhomocystenemia and one patient with prothrombin gene mutation also had methylenetetrahydrofolate reductase gene mutation. Conclusions: Etiological factors that might result in RVO in young individuals should be investigated in detail. Targeted therapies may help to prevent development of new RVOs and potential vascular problems in other organs.
General anaesthesia in the dental management of a child with cerebral palsy and autism: A Case Report

Background: Cerebral palsy described as a spectrum of movement and posture disorders which result from pathological injury to the developing fetal or infant brain. Many conditions associated with cerebral palsy require surgery. Purpose: This article presents case report of a 15-year old, autistic male patient with cerebral palsy who required urgent management of multiple gangren radix, multiple pulpitis and gingivitis. Case Management: General anaesthesia was chosen for the purpose of behaviour management. The dental procedure were restoration with flow able composite of 7 teeth, extraction of 15 gangren radix, scaling of maxilla and mandibular region, also preventive treatment with topical aplication of fluoride. Discussion: Principles to the care of a such patient including early recognition, parental support, multi-disciplinary planning of procedure requiring general anesthesia, continuity of anesthesia care, and clear guidelines about the perioperative management of uncooperative children. Dental surgery under general anaesthesia was done, the patient was received restoration with flow able composite of 7 teeth, extraction of 15 gangren radix, scaling calculus at maxilla and mandibular region, also preventive treatment with topical aplication of fluoride. Conclusion: The case report showed that dental treatment should be done in patient with cerebral palsy and autism comprehensively.
A Strategy for Assessing Acute (Transient) Pain or Discomfort in the Strength and Conditioning Environment

Experiencing acute (transient) pain and discomfort can be a characteristic of exercise and sport participation. In this context, acute pain or discomfort can be experienced by injured and injury-free athletes alike. Acute pain or discomfort in the strength and conditioning (S&C) environment can be experienced during particular movements or exercises. This may be the result of poor exercise technique and/ or soft-tissue dysfunction. This article proposes a possible strategy, which can be used by the S&C coach, to modify training based on the acute (transient) pain or discomfort experienced by athletes during training.
Trust-Building in a Patient Forum: The Interplay of Professional and Personal Expertise

Online discussion forums for patients offer the benefits of community but the risks of misinformation. A physician-moderated forum may help to mitigate this tension. How do both the professional expertise of a physician moderator and the personal, experiential expertise of patients contribute to trust in a forum? A rhetorical analysis of a year of postings in an online Parkinson’s community reveals that both forms of expertise were trusted, demonstrating the possibility for them to complement each other. This study illustrates the broader ways trust is established in patient communities and offers implications for technical communicators as forum designers or moderators.
Exploiting Application Characteristics for Efficient System Support of Data-Parallel Machine Learning

Large scale machine learning has many characteristics that can be exploited in the system designs to improve its efficiency. This dissertation demonstrates that the characteristics of the ML computations can be exploited in the design and implementation of parameter server systems, to greatly improve the efficiency by an order of magnitude or more. We support this thesis statement with three case study systems, IterStore, GeePS, and MLtuner. IterStore is an optimized parameter server system design that exploits the repeated data access pattern characteristic of ML computations. The designed optimizations allow IterStore to reduce the total run time of our ML benchmarks by up to 50×. GeePS is a parameter server that is specialized for deep learning on distributed GPUs. By exploiting the layer-by-layer data access and computation pattern of deep learning, GeePS provides almost linear scalability from single-machine baselines (13× more training throughput with 16 machines), and also supports neural networks that do not fit in GPU memory. MLtuner is a system for automatically tuning the training tunables of ML tasks. It exploits the characteristic that the best tunable settings can often be decided quickly with just a short trial time. By making use of optimization-guided online trial-and-error, MLtuner can robustly find and re-tune tunable settings for a variety of machine learning applications, including image classification, video classification, and matrix factorization, and is over an order of magnitude faster than traditional hyperparameter tuning approaches.
Phase Transitions and Criticality in the Collective Behavior of Animals -- Self-organization and biological function

Collective behaviors exhibited by animal groups, such as fish schools, bird flocks, or insect swarms are fascinating examples of self-organization in biology. Concepts and methods from statistical physics have been used to argue theoretically about the potential consequences of collective effects in such living systems. In particular, it has been proposed that such collective systems should operate close to a phase transition, specifically a (pseudo-)critical point, in order to optimize their capability for collective computation. In this chapter, we will first review relevant phase transitions exhibited by animal collectives, pointing out the difficulties of applying concepts from statistical physics to biological systems. Then we will discuss the current state of research on the"criticality hypothesis", including methods for how to measure distance from criticality and specific functional consequences for animal groups operating near a phase transition. We will highlight the emerging view that de-emphasizes the optimality of being exactly at a critical point and instead explores the potential benefits of living systems being able to tune to an optimal distance from criticality. We will close by laying out future challenges for studying collective behavior at the interface of physics and biology.
Big Data Analytics for Network Intrusion Detection: A Survey

Analysing network flows, logs, and system events has been used for intrusion detection. Network flows, logs, and system events, etc. generate big data. Big Data analytics can correlate multiple information sources into a coherent view, identify anomalies and suspicious activities, and finally achieve effective and efficient intrusion detection. This paper presents methods and subsequent evaluation criteria for network intrusion detection, stream data characteristics and stream processing systems, feature extraction and data reduction, conventional data mining and machine learning, deep learning, and Big Data analytics in network intrusion detection. Current challenges of these methods in intrusion detection are also introduced.
Adaptive block online learning target tracking based on super pixel segmentation

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.
Differentiable Stochastic Halo Occupation Distribution

In this work, we demonstrate how differentiable stochastic sampling techniques developed in the context of deep Reinforcement Learning can be used to perform efficient parameter inference over stochastic, simulation-based, forward models. As a particular example, we focus on the problem of estimating parameters of Halo Occupation Distribution (HOD) models which are used to connect galaxies with their dark matter halos. Using a combination of continuous relaxation and gradient re-parameterisation techniques, we can obtain well-defined gradients with respect to HOD parameters through discrete galaxy catalogs realisations. Having access to these gradients allows us to leverage efficient sampling schemes, such as Hamiltonian Monte-Carlo, and greatly speed up parameter inference. We demonstrate our technique on a mock galaxy catalog generated from the Bolshoi simulation using a standard HOD model and find near identical posteriors as standard Markov Chain Monte Carlo techniques with an increase of ∼8x in convergence efficiency. Our differentiable HOD model also has broad applications in full forward model approaches to cosmic structure and cosmological analysis.
Application of Evolutionary Programming Method to Solve a Hydro Thermal System Problem

: This paper proposes a Evolutionary Programming (EP) and Tabu Search (TS) methods to solve hydro thermal system consisting of 3 thermal and 1 hydro unit. The results obtained by TS method and EP algorithm heve been compared. The convergence and the reliability characteristics of the proposed algorithms are graphically analyzed. From the results obtained it is proved that the both algorithms is capable of solving highly nonlinear problems.
Tight Complexity Bounds for Counting Generalized Dominating Sets in Bounded-Treewidth Graphs

We investigate how efficiently a well-studied family of domination-type problems can be solved on bounded-treewidth graphs. For sets $\sigma,\rho$ of non-negative integers, a $(\sigma,\rho)$-set of a graph $G$ is a set $S$ of vertices such that $|N(u)\cap S|\in \sigma$ for every $u\in S$, and $|N(v)\cap S|\in \rho$ for every $v\not\in S$. The problem of finding a $(\sigma,\rho)$-set (of a certain size) unifies standard problems such as Independent Set, Dominating Set, Independent Dominating Set, and many others. For all pairs of finite or cofinite sets $(\sigma,\rho)$, we determine (under standard complexity assumptions) the best possible value $c_{\sigma,\rho}$ such that there is an algorithm that counts $(\sigma,\rho)$-sets in time $c_{\sigma,\rho}^{\sf tw}\cdot n^{O(1)}$ (if a tree decomposition of width ${\sf tw}$ is given in the input). For example, for the Exact Independent Dominating Set problem (also known as Perfect Code) corresponding to $\sigma=\{0\}$ and $\rho=\{1\}$, we improve the $3^{\sf tw}\cdot n^{O(1)}$ algorithm of [van Rooij, 2020] to $2^{\sf tw}\cdot n^{O(1)}$. Despite the unusually delicate definition of $c_{\sigma,\rho}$, an accompanying paper shows that our algorithms are most likely optimal, that is, for any pair $(\sigma, \rho)$ of finite or cofinite sets where the problem is non-trivial, and any $\varepsilon>0$, a $(c_{\sigma,\rho}-\varepsilon)^{\sf tw}\cdot n^{O(1)}$-algorithm counting the number of $(\sigma,\rho)$-sets would violate the Counting Strong Exponential-Time Hypothesis (#SETH). For finite sets $\sigma$ and $\rho$, these lower bounds also extend to the decision version, and hence, our algorithms are optimal in this setting as well. In contrast, for many cofinite sets, we show that further significant improvements for the decision and optimization versions are possible using the technique of representative sets.
Effect of Lower-Extremity Eccentric Training on Physical Function in Community-Dwelling Older Adults

Abstract Aims: The purpose of this study was to observe the effects of eccentric endurance training (ET) on physical function in community-dwelling older adults. Methods: Participants were randomly assigned to control (n = 15; 67.5 ± 2.6 yrs) and ET (n = 15; 69.0 ± 4.4 yrs) groups. The ET group completed 1 week of familiarization and 8 weeks of training on an eccentric step machine. Participants completed two, 5–15 minute sessions per week, with RPE-based intensity. Pre-, mid-, and post-training assessments were conducted for the 30-second sit-to-stand (30CST), Berg Balance Scale (BBS), single leg stance with eyes closed (SLS-EC), Functional Gait Assessment (FGA), Timed Up-and-Go (TUG), and maximal eccentric strength (MES). Results: Significant improvements in 30CST, BBS, FGA, and TUG performance were observed for the ET group only (p < .05). Conclusions: This study provides evidence that 8-weeks of progressive ET improves muscular fitness, gait characteristics, and overall physical function.
Anthropometric Obesity Indices, Body Fat Percentage, and Grip Strength in Young Adults with different Physical Activity Levels

The purposes of this study were to determine whether moderately physically active (MPA) and highly physically active (HPA) male (n = 96, age = 22.5 ± 1.7 years) and female (n = 85, age = 21.3 ± 1.6 years) young adults differed in their anthropometric obesity indices (AOIs), body fat percentage (BF%), and muscular strength, and also to examine the associations between physical activity level (PAL) and the abovementioned variables. Participants were measured for body height and weight, BF%, waist and hip circumferences, and maximal isometric grip strength. According to their PAL, estimated by the short version of the International Physical Activity Questionnaire, they were assigned to MPA and HPA subgroups. Regardless of gender, results indicated that participants in the MPA groups had significantly higher values of body weight, waist and hip circumference, BF%, and BMI than participants in the HPA groups. No significant differences were found between physical activity groups in terms of grip strength. The AOIs and BF% were found to be significantly and negatively correlated with the PAL in both genders. In conclusion, the findings of the study suggest that high habitual physical activity is associated with lower adiposity markers. However, the differences in the hand grip strength of the contrasting activity groups were negligible.
Ocena dostępności dawców koncentratów krwinek płytkowych o oznaczonych antygenach leukocytarnych i płytkowych dla pacjentów z przeciwciałami anty-HLA i/lub anty-HPA

Clinical efficacy of PC transfusions in patients immunized with Human Leukocyte Antigens (HLA) and/or Human Platelet Antigens (HPA) can be improved by relying on platelets from donors typed for HPA and/or HLA. A specific group of PC recipients are newborns with alloimmune thrombocytopenia (FNAIT) resulting from maternal alloimmunization during pregnancy against specific fetal platelet antigens HPA (especially HPA-1a) produced by the mother as a result of fetomaternal HPA incompatibility. The study aim was to assess the demand and availability for HPA/HLA typed donors in Poland. Outcome of a survey distributed to 23 Polish blood transfusion centers (CKiK) supplemented by data acquired in direct contact (phone) revealed that: 1/ demand for PCs from donors with HLA and/or HPA typed antigens was reported in 7/23 (33.3%) CKiK; 2 / over a 1.5 year period, 1 788 PCs were prepared for patients with anti-HLA- antibodies, 63 PCs for patients with anti-HPA-antibodies and 58 PCs - for patients with anti-HLA and anti-HPA antibodies. FNAIT neonates were transfused with 35 PCs from register donors and 176 PCs from casual donors; 3 / in 13/23 CKiK (61.9%) PC selection for immunized patients was mainly based on crossmatching in LCT; 4 / registers report of 12,885 donors typed for HLA Class I antigens including 417 donors typed for HPA; 5 / nation-wide there are 133 HPA-1a negative donors available for immunized patients; they were selected after typing of 5 872 donors; The number of HPA/HLA typed donors for immunized patients is insufficient. as compared to other countries. Moreover, the demand for registered donors is steadily growing due to expension of FNAIT diagnostics currently performed at the Institute of Hematology and Transfusion Medicine (IHiT) but also in the laboratories of CKiK. One of the responsibilities of the blood transfusion service is to provide PCs for immunized patients.
Roof plane extraction from airborne lidar point clouds

ABSTRACT Planar patches are important primitives for polyhedral building models. One of the key challenges for successful reconstruction of three-dimensional (3D) building models from airborne lidar point clouds is achieving high quality recognition and segmentation of the roof planar points. Unfortunately, the current automatic extraction processes for planar surfaces continue to suffer from limitations such as sensitivity to the selection of seed points and the lack of computational efficiency. In order to address these drawbacks, a new fully automatic segmentation method is proposed in this article, which is capable of the following: (1) processing a roof point dataset with an arbitrary shape; (2) robustly selecting the seed points in a parameter space with reduced dimensions; and (3) segmenting the planar patches in a sub-dataset with similar attributes when region growing in the object space. The detection of seed points in the parameter space was improved by mapping the accumulator array to a 1D space. The range for region growing in the object space was reduced by an attribute similarity measure that split the roof dataset into candidate and non-candidate subsets. The experimental results confirmed that the proposed approach can extract planar patches of building roofs robustly and efficiently.
Clinical Evidence Technologies and Patient Care

Clinical evidence technologies (CETs) are information sources derived from medical research literature that may assist health care providers in continued learning, decision-making, and patient care. Examples of CETs include: MEDLINE/PubMed and Cochrane Reviews, research journal literature, print and electronic medical texts, clinical topic summaries, guidelines, and interactive decision tools. Clinicians utilize CETs to find answers to questions that arise during patient care. However, it was unclear if CETs had a measurable impact on provider practice or patient outcomes. A literature review identified twenty-two articles evaluating CETs’ impact. Study designs included surveys, observational studies, randomized controlled trials and quasi-experimental methods. The review revealed mixed evidence of CET impact on provider-level outcomes such as improved diagnoses and treatments, and on patient level outcomes such as length of hospital stay and mortality. Additional research was needed to determine whether certain CETs or CET types have impact on patient care outcomes in clinically targeted areas. We conducted a cluster-randomized controlled trial (CRCT) to evaluate the effect of a dermatology-focused CET (VisualDx) when used by primary care providers. We found no difference in the patient skin disease outcomes of resolution of symptoms and return visits for the same problem in that trial. Thirty-two PCPs and 433 patients participated. In proportional hazards modelling adjusted for provider clusters, the time from index visit to skin problem resolution was similar in both groups (Hazard Ratio=0.92; 95% Confidence Interval (CI)=0.70, 1.21; P=0.54). Patient follow-up appointments did not differ significantly between groups (Odds Ratio=1.26; CI=0.94, 1.70; P=0.29). In a follow up mixed-methods study, we sought to understand why VisualDx did not make a difference. All CRCT provider participants were surveyed about their experience in the trial. VisualDx users (intervention arm) were interviewed about their experience using the CET. Ease of access and usefulness for patient communication facilitated successful use while irrelevant search results and use of other sources were barriers. Although PCPs reported benefits, they did not perceive the CET as useful often enough to motivate using it frequently or exclusively, thereby reducing the likelihood of it making a difference in the problem resolution and return appointment outcomes. There was no difference in skin problem resolution or number of follow-up visits when PCPs used VisualDx. PCPs did not perceive VisualDx as “useful” often enough for to use it frequently, or exclusively, thereby reducing the likelihood of this CET making a difference in patient-level outcomes.
Statistical Shape Analyses of Patients with Scaphocephaly After Surgical Remodeling.

AIM A surgical procedure is viewed as a typical treatment choice for patients with sagittal craniosynostosis. Barrel-stave osteotomies and cranial remodelling are the preferred surgical methods, but it is not always possible to understand whether remodelling has been successful especially in the first postoperative day. We aim to investigate the differences in the head shapes of scaphocephaly patients during the pre- and postoperative phases. MATERIAL AND METHODS Cranium shape data were collected from the two-dimensional digital images. The generalised Procrustes analysis was used to obtain mean shapes in the pre- and postoperative phases. The shape deformation of the cranium from the pre- to postoperative phases was evaluated using the thin plate spline method. RESULTS There was no significant cranial shape difference in the pre and postoperative phases. The high-level deformations from the pre- to postoperative phase were seen in thin plate spline graphs. The highest deformation was observed at the biparietal dimension. CONCLUSION In this study, we showed that the structural deformation of the cranium was correlated with sagittal craniosynostosis. The present study also shows that pre- and postoperative head shapes of patients with scaphocephaly can be compared using head shape with the landmark-based geometric morphometric method by taking into consideration the topographic distribution.