Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical features of low back pain in people with hip osteoarthritis: A cross sectional study.

BACKGROUND: Low back pain (LBP) is commonly reported in people with hip osteoarthritis (OA) and is a poor prognostic indicator of outcome in OA. This study aimed to identify the clinical features associated with LBP in people with hip OA attending orthopaedic and rheumatology clinics. METHODS: A cross-sectional study was undertaken. Twenty-four people with radiographically confirmed OA were recruited and completed self-report questionnaires for hip and LBP severity (Visual Analogue Scale), hip-related disability (Western Ontario and McMaster Universities Osteoarthritis Index) and back-related disability (Roland Morris Disability Questionnaire). Physical examination comprised spinal palpation, pelvic girdle pain provocation tests and hip and spinal range of motion tests. Between-group (presence/absence of LBP) differences in self-report and physical examination items were compared using Mann-Whitney U and Chi-squared tests. RESULTS: A total of 16/24 (66.7%) patients reported LBP. Those with LBP were younger, reported more pain locations and had higher self-report pain and disability. On physical examination, people with LBP and OA hip had reduced hip flexion, greater pain provocation with hip abduction, hip lateral rotation, spinal palpation and a greater number of painful pelvic girdle tests and spinal level palpation. CONCLUSIONS: Assessment of patients with hip OA should incorporate examination of the lumbar spine and pelvic regions. It appears from our study that LBP is a common co-morbidity in those with OA of the hip and may indicate greater severity of hip disease, although the small sample size limits interpretation of results. Further research should investigate the exact relationships between presence of LBP and hip OA.
IPART: an automatic protocol reverse engineering tool based on global voting expert for industrial protocols

ABSTRACT The industrial control system is an important part of many critical infrastructures and has a big influence on the security of them. With the rapid development of the industrial control system, there has been a significant increase for industrial control system to use the computer network, which has brought many security issues. Protocol security is one of the most important security issues. Many industrial protocols are unknown, which prevent firewall parsing and analysing network traffic, thus it brings a big challenge for intrusion detection, deep packet inspection and traffic management. One method to solve the problem is the reverse engineering technology. However, previous works are mainly for traditional network protocols and not very suitable for reversing industrial protocols. To address this problem, we propose IPART, an unsupervised tool for automatically reverse the format of the industrial protocol from network trace. IPART applies an extended voting expert algorithm to infer the boundaries of industrial protocol fields. Types of these fields are derived by statistical methods. It then classifies messages into sub-clusters by their field types and infers the format of each sub-cluster. Finally, IPART combines all results and gets the format tree of the protocol. We evaluate our work on three industrial protocols: Modbus, IEC104 and Ethernet/IP. Compared with some state-of-art approaches (lda model, Voting expert, netzob), our tool shows a better performance. IPART reverse industrial protocols mainly by three stages. The tool firstly split raw packages into tokens and infer the fields of the protocol. Both fields property (offset, length, etc.) and semantic (length, transition id, etc.). It then class messages belong to the same format to a cluster and each cluster approximates a format. Finally, the tool combines all formats and get the protocol format tree. GRAPHICAL ABSTRACT
Bundle Adjustment for Monocular Visual Odometry Based on Detected Traffic Sign Features

Monocular visual odometry (VO), which is a subset of simultaneous localization and mapping (SLAM) used to determine the position and orientation of a moving object by analyzing the associated monocular camera image sequences, is a critical part in the vision system of autonomous driving. However, based on the frame-by-frame pose estimation, drift error can be incrementally accumulated. Bundle adjustment (BA) is thus introduced to deal with the error-drift problem through correlating several image frames together to optimize camera poses and extracted 3D map points simultaneously. In this paper, we propose a joint BA framework which takes into account additional constraints from the detected road traffic signs. This framework can be effectively integrated into existing VO systems, as evidenced by the improved vehicular localization accuracy in experimental performance when compared with the state-of-the-art baseline VO method.
The design and implementation of vehicle-mounted satellite communication on the move based on MEMS gyro

As an important satellite communication technology, mobile communication has broad application prospects in the field of military and civilian applications. Low cost and high reliability have become one of the goals and difficulties in engineering design. In order to overcome the shortage of course information provided by inertial navigation or electronic compass, a beacon space search algorithm without course information is designed. A low cost gyro stabilization platform based on ARM and MEMS gyroscope is designed for the high mobility and complex working conditions of vehicles. The servo motor and photoelectric encoder are used to construct the multi-closed-loop control system to improve its fast response ability, and the pitch compensation and beacon space search algorithm are used to improve the precision of the system for star and tracking. It has good engineering application and popularization value.
Disambiguating the scientific names of cockroaches

Cockroaches are typically recognized as an order or a suborder in insects, sometimes rank-free. Many scientific names for cockroaches are in use, most of them are ambiguous because of frequent changes of the spelling and definition, and the discrepancy between phenetics and cladistics. Omission of the authorship of the name and of the definition further confuses readers, which include taxonomists. The underlying causes of the ambiguity are the paraphyly of cockroaches and various reproduction strategies (crucial in cockroach classification) of fossil cockroaches. This paper historically reviews the scientific names for cockroaches, and recommends the following names with phylogenetic definition (details and authorship are given in the text): 1) Blattodea are cockroaches with internal ovipositors (producing oothecae of the extant type) and all descendants including termites; 2) suborder Blattaria are Blattodea minus termites; 3) order Dictyoptera are cockroaches that produce genuine oothecae and all descendants including Blattodea, Mantodea and Alienoptera; 4) Holopandictyoptera are all insects that are recognized as cockroaches and their descendants; 5) Eoblattodea are the so-called ‘roachoids’, i.e., cockroaches bearing long external ovipositors, no genuine oothecae. Accordingly, the cockroaches in the broader sense fall into three taxa: Blattaria, basal Dictyoptera, and Eoblattodea.
Debiased Bayesian inference for average treatment effects

Bayesian approaches have become increasingly popular in causal inference problems due to their conceptual simplicity, excellent performance and in-built uncertainty quantification ('posterior credible sets'). We investigate Bayesian inference for average treatment effects from observational data, which is a challenging problem due to the missing counterfactuals and selection bias. Working in the standard potential outcomes framework, we propose a data-driven modification to an arbitrary (nonparametric) prior based on the propensity score that corrects for the first-order posterior bias, thereby improving performance. We illustrate our method for Gaussian process (GP) priors using (semi-)synthetic data. Our experiments demonstrate significant improvement in both estimation accuracy and uncertainty quantification compared to the unmodified GP, rendering our approach highly competitive with the state-of-the-art.
Online Optimal Perception-Aware Trajectory Generation

This article proposes an online optimal active perception strategy for differentially flat systems meant to maximize the information collected via the available measurements along the planned trajectory. The goal is to generate online a trajectory that minimizes the maximum state estimation uncertainty provided by the employed observer. To quantify the richness of the acquired information about the current state, the smallest eigenvalue of the constructibility Gramian is adopted as a metric. In this article, we use B-splines for parametrizing the trajectory of the flat outputs and we exploit a constrained gradient descent strategy for optimizing online the location of the B-spline control points in order to actively maximize the information gathered over the whole planning horizon. To show the effectiveness of our method in maximizing the estimation accuracy, we consider two case studies involving a unicycle and a quadrotor that need to estimate their poses while measuring two distances w.r. t. two fixed landmarks. Concurrent estimation of calibration/environment parameters is also considered for illustrating how the proposed method copes with instances of active self-calibration and map building.
Korean Morphological Analysis with Tied Sequence-to-Sequence Multi-Task Model

Korean morphological analysis has been considered as a sequence of morpheme processing and POS tagging. Thus, a pipeline model of the tasks has been adopted widely by previous studies. However, the model has a problem that it cannot utilize interactions among the tasks. This paper formulates Korean morphological analysis as a combination of the tasks and presents a tied sequence-to-sequence multi-task model for training the two tasks simultaneously without any explicit regularization. The experiments prove the proposed model achieves the state-of-the-art performance.
Fischer's Mastery of Surgery

Emphasizing both the science and craft of surgery, "Fischer's Mastery of Surgery", Sixth Edition, embraces a scope consistent with the broad training of a general surgeon, providing extensive coverage of vascular surgery as well as of common thoracic, breast, esophageal, endocrine, colorectal, gastric, pancreatic, liver, and biliary procedures. Organized for ease of use, each procedural chapter reviews the essentials of diagnosis, anatomy, and pre-operative planning, but focuses most heavily on step-by-step depictions and descriptions of procedures. Each chapter concludes, as is traditional for this classic text, with an editorial commentary that puts the chapter material in a broad context and provides helpful critiques of the most recent literature. The path to surgical mastery begins here! Step-by-step guidance takes readers through each procedure, with tips and cautions from leading surgeons; more than 3,400 illustrations offer a surgeon's-eye-view of the most advanced approaches; over 450 renowned contributors share their surgical expertise with readers; focus on evidence-based surgery reveals the science behind each approach; a companion website includes the fully searchable text and exclusive web-only chapters not found in the text. NEW in the Sixth Edition: over a dozen new chapters address endovascular treatment of varicose veins, fasciotomy, minimally invasive parathyroidectomy, reconstruction of the chest wall, thoracic aortic transaction, vascular injury to extremities; fully updated material details the latest developments in vascular procedures, including both open and endovascular procedures; and new full-color design throughout the text, including many new color images, help readers visualize and remember key anatomic features and surgical techniques.
Detection and Synchronization of Video Sequences for Event Reconstruction

With an ever-growing amount of unexpected menaces in crowded places such as terrorist attacks, it is paramount to develop techniques to aid investigators reconstructing all details about an event of interest. To extract reliable information about the event, all kinds of available clues must be jointly exploited. As a matter of fact, today’s sources of information are plenty and varied, as important events affecting many people are typically documented by different sources. Both witnesses’ smartphones and security cameras can provide valuable information coming from multiple viewpoints and time instants — "the eyes of the crowd". In this paper, we focus on the specific problem of automatically detecting and temporally synchronizing videos depicting the same event of interest. Videos can be either near-duplicates (i.e., edited copies of the same original source) or sequences shot by different users from different vantage points. The proposed method relies upon a video fingerprinting technique capable of describing how video semantic content evolves in time. The solution does not assume a priori information about cameras location, and it only exploits visual cues, not relying on audio channels.
A Structural Model for the Coevolution of Networks and Behavior

Abstract This paper introduces a structural model for the coevolution of networks and behavior. We characterize the equilibrium of the underlying game and adopt the Bayesian Double Metropolis-Hastings algorithm to estimate the model. We further extend the model to incorporate unobserved heterogeneity and show that ignoring this heterogeneity can lead to biased estimates in simulation experiments. We apply the model to study R&D investment and collaboration decisions in the chemical and pharmaceutical industry and find a positive knowledge spillover effect. Our model also provides a tractable framework for a long-run key player analysis.
Vibratory stimulation for the alleviation of chronic pain.

: The pain relieving effect of vibratory stimulation was studied in 731 patients suffering from acute pain (135 patients) or chronic pain (596 patients). Most of the patients had previously undergone treatments of various kinds without sufficient pain relief. The effect of vibratory stimulation was assessed before, during and after stimulation using different rating scales. About 70% of the patients reported reduction of pain during vibratory stimulation. In many patients there was a clear relation between the degree of reduction of pain and the intensity of pain before the beginning of stimulation. In general, relief of pain by more than 50% during stimulation was obtained in the patients who reported light, light to moderate, or moderate pain. The patients with moderate to severe, or severe pain before stimulation generally reported a reduction of pain of 50% or less. The best pain reducing site was found to be either the area of pain or close to it, the antagonistic muscle or a trigger point near the painful area. In most patients suffering from musculoskeletal pain the best pain reducing effect was obtained when the vibratory stimulation was applied with moderate pressure (at which contact was achieved with underlying bone) at a frequency of 50-150 Hz. To obtain a maximal duration of pain relief the stimulation had to be applied for 30-45 minutes. Many of the patients experienced pain relief lasting for more than 3 hours. It may be noticed that in many patients the pain relief lasted for 12 hours or more. There was a good correlation between the degree of pain relief and its duration. In the patients who experienced a pain reduction of 50% or less the pain relief generally lasted for less than 6 hours while in the patients who experienced pain relief of more than 50% it lasted for more than 6 hours. In comparison with high or low frequency TENS, vibratory stimulation was found to be as effective and in some patients even more effective in reducing chronic musculoskeletal or orofacial pain. The effect of 20 Hz, 100 Hz and 200 Hz vibratory stimulation, high frequency TENS, low frequency TENS and "placebo" vibratory stimulation was examined in various chronic musculoskeletal pain syndromes. 82% of the patients experienced a relief of pain with any of the above mentioned methods; 47% of the patients experienced a reduction of pain with vibratory stimulation or TENS stimulation. (ABSTRACT TRUNCATED AT 400 WORDS)
Toward an open access to high-frequency lake modeling and statistics data for scientists and practitioners – the case of Swiss lakes using Simstrat v2.1

Abstract. One-dimensional hydrodynamic models are nowadays widely recognized as key tools for lake studies. They offer the possibility to analyze processes at high frequency, here referring to hourly timescales, to investigate scenarios and test hypotheses. Yet, simulation outputs are mainly used by the modellers themselves and often not easily reachable for the outside community. We have developed an open-access web-based platform for visualization and promotion of easy access to lake model output data updated in near-real time (http://simstrat.eawag.ch, last access: 29 August 2019). This platform was developed for 54 lakes in Switzerland with potential for adaptation to other regions or at global scale using appropriate forcing input data. The benefit of this data platform is practically illustrated with two examples. First, we show that the output data allows for assessing the long-term effects of past climate change on the thermal structure of a lake. The study confirms the need to not only evaluate changes in all atmospheric forcing but also changes in the watershed or throughflow heat energy and changes in light penetration to assess the lake thermal structure. Then, we show how the data platform can be used to study and compare the role of episodic strong wind events for different lakes on a regional scale and especially how their thermal structure is temporarily destabilized. With this open-access data platform, we demonstrate a new path forward for scientists and practitioners promoting a cross exchange of expertise through openly sharing in situ and model data.
Intrusion Detection in Wireless Ad Hoc Network

Security of the Ad Hoe network is becoming more concerned as the research of this field carry on.Ad Hoc network is generally more vulnerable to threats due to its features of open medium,dynamic network topology,limited bandwidth and resources,cooperation algorithms,and lack of centralized monitoring point.But most techniques devel- oped in the wired network are not applicable in Ad Hoc network,new models and algorithms have been proposed in this new environment.In this paper we analyze and compare the existing intrusion detection techniques and also address the research trends in this area.
Static Image-Based Emotion Recognition Using Convolutional Neural Network

Emotion recognition systems have been used frequently both socially and commercially. Various classification methods are used to perform emotion recognition. The convolutional neural network (CNN) has a popular position among these classification methods. The CNN modeling process, which is left to the user experience, is a hard challenging task. Instead of modeling a new system, transfer learning from pre-trained models often increases performance and prevents loss of time. In this paper, a new dataset, created with the help of image search engines, is classified with transfer learning supported CNN. Data preprocessing methods were also applied to increase classification success. The results obtained with experimental studies are presented in detail.
Central Nervous System Infectious Diseases and Therapy

In this age of modern era, the use of internet must be maximized. Yeah, internet will help us very much not only for important thing but also for daily activities. Many people now, from any level can use internet. The sources of internet connection can also be enjoyed in many places. As one of the benefits is to get the on-line central nervous system infectious diseases and therapy book, as the world window, as many people suggest.
On Ridges and Valleys

Ridges and valleys are earth's relief structures. They can have an imaging counterpart provided we model a digital image as a landscape by considering grey level values as height. These two dual entities have received comparatively little attention from the computer vision community with regard to others like edges or corners. In this paper, we first propose a taxonomy or classification of the several definitions of ridge and valley lines and review their implementation on discrete images. Then, we illustrate the application of one type of characterization, a creaseness measure, to solve several problems of image registration, where ridge and valley lines are taken as landmarks.
Data Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. * Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems* Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems* Contains 45 bioinformatics problems that have been investigated in recent research
Pazopanib (Votrient®) for the treatment of locally advanced and/or metastatic renal cell carcinoma

Pazopanib, an orally administered antineoplastic agent targeting multiple tyrosine kinase inhibitors (TKIs), is one of currently 6 approved targeted agents for the treatment of locally advanced and/or metastatic renal cell carcinoma (RCC). Based on the safety and efficacy results of a pivotal phase III trial the EMA granted conditional approval for pazopanib for the treatment of RCC. The primary endpoint – progression free survival (PFS) – analysis demonstrated superiority of pazopanib compared to placebo (HR 0.46; 95% CI, 0.34 to 0.62; p<0.0001) in the overall study population. This superiority effect was more pronounced within the treatment-naive subgroup compared to the cytokine pre-treated subgroup. Response rate in the overall study population was 30% and 3% for the intervention and control group, respectively. The most common observed adverse events (AEs) were diarrhea, hypertension, hair colour changes, nausea, vomiting, anorexia, hemorrhagic events, elevations in alanine aminotransferase (ALT) and elevations in aspartate aminotransferase (AST). Grade 3/4 AEs were observed in 33%/7% in the pazopanib treated group compared to 14%/6% in the placebo arm. Though both regulatory agencies, the FDA and the EMA, considered within their benefit-risk assessments that the benefits of the pazopanib treatment outweigh its risks, they requested mature data on overall survival and comparative data of the head-to-head comparison of pazopanib and sunitinib.