Current concepts of natural course and in management of medial epicondylitis: a clinical overview.

Medial epicondylitis (ME), called "golfer's elbow", is not frequent or serious disease but can cause symptoms that are bothersome in everyday life. Therefore knowledge about this condition may improve diagnostic-therapeutic process. In this article detailed information concerning pathophysiology and symptomatology of ME was described.

Ultrasonography as a diagnostic tool for posteromedial corner pathologies: a pictorial essay.

The posteromedial corner (PMC) is a common location for knee joint pain, and accurate diagnosis is essential for appropriate treatment. The frequent causes of pain in the PMC include pathologies of the posterior part of the medial meniscus, damage to articular cartilage, popliteal cysts and the semimembranosus tendinopathy.Currently, magnetic resonance imaging is the gold standard for assessing knee joint disorders, but its availability and cost can limit its use in some cases.

Building a Real-Time Testing Platform for Unmanned Ground Vehicles with UDP Bridge.

Perception and vehicle control remain major challenges in the autonomous driving domain. To find a proper system configuration, thorough testing is needed. Recent advances in graphics and physics simulation allow researchers to build highly realistic simulations that can be used for testing in safety-critical domains and inaccessible environments.

Finding the best hardware configuration for 2D SLAM in indoor environments via simulation based on Google Cartographer.

One of the most challenging topics in robotics is simultaneous localization and mapping (SLAM) in the indoor environments. Due to the fact that Global Navigation Satellite Systems cannot be successfully used in such environments, different data sources are used for this purpose, among others light detection and ranging (LiDARs ), which have advanced from numerous other technologies. Other embedded sensors can be used along with LiDARs to improve SLAM accuracy, e.

Induction of Brain Insulin Resistance and Alzheimer's Molecular Changes by Western Diet.

The term Western diet (WD) describes the consumption of large amounts of highly processed foods, rich in simple sugars and saturated fats. Long-term WD feeding leads to insulin resistance, postulated as a risk factor for Alzheimer's disease (AD). AD is the main cause of progressive dementia characterized by the deposition of amyloid-β (Aβ) plaques and neurofibrillary tangles consisting of the hyperphosphorylated tau (p-Tau) protein in the brain, starting from the entorhinal cortex and the hippocampus.

Adaptive Hurst-Sensitive Active Queue Management.

An Active Queue Management (AQM) mechanism, recommended by the Internet Engineering Task Force (IETF), increases the efficiency of network transmission. An example of this type of algorithm can be the Random Early Detection (RED) algorithm. The behavior of the RED algorithm strictly depends on the correct selection of its parameters.

Cost-effective filtering of unreliable proximity detection results based on BLE RSSI and IMU readings using smartphones.

Indoor environments are a major challenge in the domain of location-based services due to the inability to use GPS. Currently, Bluetooth Low Energy has been the most commonly used technology for such services due to its low cost, low power consumption, ubiquitous availability in smartphones and the dependence of the signal strength on the distance between devices. The article proposes a system that detects the proximity between static (anchors) and moving objects, evaluates the quality of this prediction and filters out the unreliable results based on custom metrics.

Supervised Learning of Neural Networks for Active Queue Management in the Internet.

The paper examines the AQM mechanism based on neural networks. The active queue management allows packets to be dropped from the router's queue before the buffer is full. The aim of the work is to use machine learning to create a model that copies the behavior of the AQM PIα mechanism.

Diffusion Model of a Non-Integer Order Controller with TCP/UDP Streams.

In this article, a way to employ the diffusion approximation to model interplay between TCP and UDP flows is presented. In order to control traffic congestion, an environment of IP routers applying AQM (Active Queue Management) algorithms has been introduced. Furthermore, the impact of the fractional controller PIγ and its parameters on the transport protocols is investigated.

LiDAR Point Cloud Generation for SLAM Algorithm Evaluation.

With the emerging interest in the autonomous driving level at 4 and 5 comes a necessity to provide accurate and versatile frameworks to evaluate the algorithms used in autonomous vehicles. There is a clear gap in the field of autonomous driving simulators. It covers testing and parameter tuning of a key component of autonomous driving systems, SLAM, frameworks targeting off-road and safety-critical environments.

Current concepts of natural course and in management of frozen shoulder: A clinical overview.

Frozen Shoulder (FS) by many specialists is still considered a benign, self-limiting condition, which usually resolves without intervention. This concept originated in the 70', stating that FS will proceed from "the freezing" phase, with the predominance of inflammation and pain to "the frozen" phase with marked stiffness in the joint and "the thawing" phase, with a progressive return to the normal Range Of Motion (ROM) and function. Nevertheless, numerous authors have recently challenged this concept, arguing that most patients with FS will never fully recover, and suffer from residual pain and loss of function.

Efficient Feature Selection for Static Analysis Vulnerability Prediction.

Common software vulnerabilities can result in severe security breaches, financial losses, and reputation deterioration and require research effort to improve software security. The acceleration of the software production cycle, limited testing resources, and the lack of security expertise among programmers require the identification of efficient software vulnerability predictors to highlight the system components on which testing should be focused. Although static code analyzers are often used to improve software quality together with machine learning and data mining for software vulnerability prediction, the work regarding the selection and evaluation of different types of relevant vulnerability features is still limited.

Long-Range Dependent Traffic Classification with Convolutional Neural Networks Based on Hurst Exponent Analysis.

The paper examines the ability of neural networks to classify Internet traffic data in terms of self-similarity expressed by the Hurst exponent. Fractional Gaussian noise is used for the generation of synthetic data for modeling the genuine ones. It is presented that the trained model is capable of classifying the synthetic data obtained from the Pareto distribution and the real traffic data.

Does surgical site infection after Caesarean section in Polish hospitals reflect high-quality patient care or poor postdischarge surveillance? Results from a 3-year multicenter study.

Background: Caesarean sections (CSs) are associated with a high infection risk. Surgical site infection (SSI) incidence is among the markers of effectiveness of infection prevention efforts. The aim of this study was to analyze risk factors for SSI, incidence, and microbiology in patients who underwent CS.

Device-associated pneumonia of very low birth weight infants in Polish Neonatal Intensive Care Units.

Purpose: Late-Onset Pneumonia (LO-PNEU) is still the most important complication associated with the hospitalization of infants with very low birth weight (<1501g). The purpose of this paper is to summarize the results of an ongoing surveillance program defining LO-PNEU as associated or not associated with respiratory support in the NICU and distribution of causative pathogens from the Polish Neonatology Surveillance Network (PNSN).

Materials And Methods: Surveillance of infections was conducted in the years 2009-2011 at six Polish NICUs.

Late-onset bloodstream infections of Very-Low-Birth-Weight infants: data from the Polish Neonatology Surveillance Network in 2009-2011.

Background: Late-Onset Bloodstream Infections (LO-BSI) continue to be one of the most important complications associated with hospitalization of infants born with very low birth weight (VLBW). The aims of this study were to assess the epidemiology of LO-BSI together with the risk factors and the distribution of causative pathogens at six Polish neonatal intensive care units that participated in the Polish Neonatology Surveillance Network from January 1, 2009 to December 31, 2011.

Methods: The surveillance covered 1,695 infants whose birth weights were <1501 grams (VLBW) in whom LO-BSI was diagnosed >72 hours after delivery.

Necrotising enterocolitis in preterm infants: epidemiology and antibiotic consumption in the Polish neonatology network neonatal intensive care units in 2009.

Unlabelled: The aim of this study was to describe the epidemiology of necrotising enterocolitis (NEC), antibiotic consumption and the usefulness of microbiological tests in very low birth weight (VLBW) Polish newborns.

Methods: Prospective surveillance was performed in the year 2009 by local infection control teams. The study covered 910 infants hospitalized in six Polish neonatal intensive care units.

[Epidemiology of infections in very low birth weight infants. Polish Neonatology Network research].

Aim Of Study: 1. prospective record of infections; 2. prevention of nosocomial infections by providing current data about infections, which are significant for making therapeutic decisions.

Infections reported in newborns with very low birth weight who required surgical treatment. Data from the Polish Neonatology Surveillance Network.

Aim: To determine the risk of various forms of infections appearing in very low birth weight newborns (VLBW) during the period of 30 days after surgical treatment in hospitals which have perinatal care departments with neonatal intensive care units that form the Polish Neonatology Surveillance Network (PNSN).

Material And Methods: Continuous prospective monitoring of infections was carried out from January 1st to December 31st 2009 in six neonatal intensive care units which form the Polish Neonatal Surveillance Network. (PNSN).

Enterobacteriaceae infections of very low birth weight infants in Polish neonatal intensive care units: resistance and cross-transmission.

Background: The aims of our study were analysis of the occurrence of infections by members of the Enterobacteriaceae family in 6 Polish neonatal intensive care units in 2009, their drug resistance, the epidemiology of extended-spectrum β-lactamase (ESBL)-producing strains and the possibility of using modern tools of microbiology diagnosis in infection control, especially for the reduction of antimicrobial resistance.

Methods: A prospective surveillance covered 910 newborns. Case patients were defined as neonates with very low birth weight who had clinical signs of septicemia, pneumonia or necrotizing enterocolitis.

Early-onset infections of very-low-birth-weight infants in Polish neonatal intensive care units.

Aim: The objective of this study was to investigate the incidence, causes, the risk factors, etiologic agents and the outcomes of early-onset infections (EOIs) in very-low-birth-weight newborns in Polish neonatal intensive care units.

Methods: Continuous prospective infection surveillance conducted during 2009 at 6 Polish neonatal intensive care units and included 910 newborns whose birth weight was lower than 1500 g. Infections were defined according to the Gastmeier's criteria.