Miracle-dz/UniFAR-FTUs huggingface dataset:
The ultrasound‐guided iPACK block with continuous adductor canal block for total knee arthroplasty

We report a case of pre-operative ultrasound-guided local anaesthetic infiltration of the interspace between the popliteal artery and the capsule of the posterior knee (iPACK), in a 75-year-old male undergoing total knee arthroplasty. This was supplemented with postoperative adductor canal block using a continuous catheter technique. We assessed postoperative analgesia at rest and during active flexion of the knee, opioid consumption, motor and functional recovery, and patient satisfaction, for three postoperative days. This technique provided effective motor-sparing analgesia, and was associated with excellent patient satisfaction.
Improvements to Consumption Prediction: Machine Learning Methods and Novel Features

Current models for predicting personal consumption expenditures (PCE) employ statistical techniques and rely upon traditional economic features. We compare vector autoregression and random forest regression models using traditional economic features as inputs to predict PCE. Additionally, we develop novel features derived from the earnings call transcripts of publicly traded U.S. companies using natural language processing (NLP) techniques. These new features reduce the mean square error (MSE) of the vector autoregression model by 7% and the random forest model by 23%. We find the random forest models outperformed the vector autoregression models, with a MSE reduction of 68%. We conclude the new features improve PCE predictions.
Motion compensated 3-dimensional wave-form image coding

The author proposes a technique for incorporate motion compensation in a general 3-D waveform coding environment. Examples are given for 3-D subband and DCT (discrete cosine transform) coding where motion compensation yields significant improvements as compared to the same technique without motion compensation. It is concluded that, for low rates, 3-D motion-compensated subband coding is a very efficient technique for the coding of image sequences. <<ETX>>
Authoring Topic Maps-based Digital Course Libraries

Digital course libraries are educational Web applications that contain instructional materials to assist students’ learning in a specific discipline (course). To address the critical issues of findability and reusability of learning resources, we propose a general framework for standards-based, ontologyaware course libraries and use it to develop an environment for building, maintaining, and using such libraries. The proposed environment, TM4L (Topic Maps for Learning), is based on the new ISO standard XML Topic Maps that provides a paradigm for organizing and retrieving online information and for interchanging semantic information on the Web. In this paper we present the TM4L authoring tool for creating ontology-aware Topic Maps-based repositories of learning materials (TM4L Editor).
Exploring Digisonde Ionogram Data with SAO-X and DIDBase

A comprehensive suite of software tools for ionogram data analysis and archiving has been developed at UMLCAR to support the exploration of raw and processed data from the worldwide network of digisondes in a low-latency, user-friendly environment. Paired with the remotely accessible Digital Ionogram Data Base (DIDBase), the SAO Explorer software serves as an example of how an academic institution conscientiously manages its resident data archive while local experts continue to work on design of new and improved data products, all in the name of free public access to the full roster of acquired ionospheric sounding data.
Wind energy assessment and mapping using terrain nonlinear autoregressive neural network (TNARX) and wind station data

Abstract This paper presents the potential of generating wind power using soft computing model and ground station data. In reality, the process of wind resource assessment is to set up an experiment in the targeted locations, and measure the wind speed and direction. In this paper, a prediction model based on the terrain based neural network named terrain nonlinear autoregressive neural network (TNARX) is proposed to forecast the wind speed in the areas not covered by measurements using a ground station located nearby. The model has meteorological, physical and topographical as input, while the wind speed is the target variable. The suitability of the proposed model was judged using statistical measures. The paper shows characteristics of wind speed and the most prevailing wind directions. The variation of wind speed at 10–40 m heights was obtained and presented. Wind speed distribution modelling was carried out using five statistical models. It was found that Weibull and Gamma fits the wind speed of the studied areas. Wind power and energy density results show the areas falls within class 1, which is possible for harnessing energy content in wind for small scale purposes.
Improving detection of clustered microcalcifications using morphological connected operators

Breast cancer is one of the major causes of death among all cancers for middle-aged and older women, mainly in developed countries, and its incidence is rising. Since the origin of this disease is not yet known, early detection is the best way to reduce the breast cancer mortality. Today, early detection is achieved by means of mammography. Radiologists look for certain signs and characteristics indicative of cancer when evaluating a mammogram. Among these signs is the presence of clustered microcalcifications. A microcalcification is a tiny calcium deposit that has accumulated in tissue in the breast, and it appears as a small bright spot on the mammogram. Due to the large amount of mammograms a radiologist must examine, there are many people developing computer-based systems to aid in the detection of the disease. This paper presents a method to improve automatic detection of clusters of microcalcifications in mammograms.
The In-between Generation. Immigrants and the Problem of a Dual Sense of Belonging

The In-between Generation. Immigrants and the Problem of a Dual Sense of Belonging The aim of this paper is an anthropological analysis of three individual biographies of Macedonian-speaking Muslims migrants in Italy. An author focuses on the generation called by her in-between generation. It means young people who migrated from Macedonia with their parents at the early age. They have studied or already completed their education in Italy, they speak Italian fluently and most of their friends are Italian. However, they are still speak Macedonian at home, visit their country of origin every year and are aware of their strong belonging to the Macedonian-speaking Muslim group. Therefore, they should constantly negotiate between traditional values of their parents, and their own patterns of life. The significant issues and tensions regard religious practices, daily habits like food and dress, and – that is most sensitive – gender relations. Pokolenie pomiedzy. Imigranci a problem podwojnej przynalezności Celem artykulu jest antropologiczna analiza biografii trojga macedonskojezycznych muzulmanow, nalezących do grupy imigrantow we Wloszech. Autorka skupia sie na mlodych ludziach, ktorzy na wczesnym etapie zycia wyemigrowali z Macedonii z rodzicami. W literaturze nazywa sie ich „pokoleniem 1,5”, podczas gdy w omawianych badaniach wybrano termin „pokolenie pomiedzy”; poniewaz rozmowcy jako imigranci znajdują sie miedzy pierwszym a drugim pokoleniem imigracyjnym, są zawieszeni pomiedzy wartościami i ideami kraju pochodzenia i kraju przyjmującego, pomiedzy dziecinstwem i doroslością. Studiowali lub ukonczyli edukacje we Wloszech, mowią plynnie po wlosku, a wiekszośc ich przyjaciol to Wloszki/Wlosi. Jednak wciąz mowią po macedonsku w domu, co roku odwiedzają kraj pochodzenia i mają silną świadomośc przynalezności do grupy macedonskojezycznych muzulmanow. Z tego wzgledu wciąz muszą prowadzic negocjacje miedzy tradycyjnymi wartościami rodzicow a wlasnymi wzorami zycia. Znaczący problem i źrodlo konfliktow stanowią praktyki religijne, elementy kultury codzienności, takie jak ubior czy pozywienie, oraz – co najbardziej drazliwe – relacje genderowe.
A new paradigm for the personalized delivery of iodinated contrast material at cardiothoracic computed tomography angiography

In North America more than 40 million doses of iodinated X-Ray contrast medium are delivered to patients undergoing CT imaging every year. This particular pharmaceutical is necessary to enable Computed Tomography of soft tissue, tumors, and vasculature. Very few of the contrast enhanced procedures are performed with the dose of the drug tailored to the individual patient or procedure and nearly every patient receives the same dose of contrast material. This dissertation presents a methodology to allow the routine administration of a personalized dose of contrast material to generate contrast enhancement sufficient for diagnosis during cardiothoracic CT Angiography imaging. Parameter estimation of a patient specific model is performed using Maximum Likelihood Estimation (MLE) with data generated from the scanner during a pre-diagnostic "test" injection of contrast agent. A non-parametric system identification technique, using the truncated Singular Value Decomposition, is also developed for deriving a patient specific prediction of contrast enhancement. The MLE technique produces contrast enhancement predictions with less error than the tSVD method. It is also shown that the MLE method is less sensitive to data length and has greater noise immunity. A novel, patient-specific contrast protocol generation algorithm is also presented. It is based upon a constrained minimization (Sequential Quadratic Programming) that enforces constraints on the input parameters while minimizing the volume of contrast sufficient to achieve a prospectively chosen enhancement target. A physiologically based pharmacokinetic (PBPK) numeric model is developed and used to validate the contrast prediction and protocol generation techniques. Finally, a novel, instrumented, flow phantom is developed and used to validate the identification and protocol generation techniques.
Automated Facial Expression Recognition Using Gradient-Based Ternary Texture Patterns

Recognition of human expression from facial image is an interesting research area, which has received increasing attention in the recent years. A robust and effective facial feature descriptor is the key to designing a successful expression recognition system. Although much progress has been made, deriving a face feature descriptor that can perform consistently under changing environment is still a difficult and challenging task. In this paper, we present the gradient local ternary pattern (GLTP)—a discriminative local texture feature for representing facial expression. The proposed GLTP operator encodes the local texture of an image by computing the gradient magnitudes of the local neighborhood and quantizing those values in three discrimination levels. The location and occurrence information of the resulting micropatterns is then used as the face feature descriptor. The performance of the proposed method has been evaluated for the person-independent face expression recognition task. Experiments with prototypic expression images from the Cohn-Kanade (CK) face expression database validate that the GLTP feature descriptor can effectively encode the facial texture and thus achieves improved recognition performance than some well-known appearance-based facial features.
Content adaptation architecture with efficient usage of cached data in a multimedia proxy server

The use of multimedia data is growing at a rapid rate, and bringing multimedia services to terminals with limited capabilities is a major challenge. Efficient schemes are hence required for adapating the multimedia content for delivery to devices with limited resources. In the conventional server and proxy-based architectures, the adaptation is performed either at the server or at the proxy resulting in the loading of the server and the proxy. In this paper we propose a novel distributed adaptation architecture suitable for resource-limited multimedia terminals as well as wired connections with high bandwidths. Here, the data can be adapted at the proxy or at the server, resulting in a faster adaptation process. In addition, we propose an efficient cache replacement policy at the proxy. The proposed architecture is very flexible for both mobile and wired networks. The experimental results show that the proposed architecture improves the performance of the proxy and the server, and reduces network congestion and latency.
Integrating Systematic and Local Search Paradigms: A New Strategy for MaxSAT

Systematic search and local search paradigms for combinatorial problems are generally believed to have complementary strengths. Nevertheless, attempts to combine the power of the two paradigms have had limited success, due in part to the expensive information communication overhead involved. We propose a hybrid strategy based on shared memory, ideally suited for multi-core processor architectures. This method enables continuous information exchange between two solvers without slowing down either of the two. Such a hybrid search strategy is surprisingly effective, leading to substantially better quality solutions to many challenging Maximum Satisfiability (MaxSAT) instances than what the current best exact or heuristic methods yield, and it often achieves this within seconds. This hybrid approach is naturally best suited to MaxSAT instances for which proving unsatisfiability is already hard; otherwise the method falls back to pure local search.
Inter-organisational knowledge networks: synthesising dialectic tensions of university-industry knowledge discovery

Purpose Despite growth in use of inter-organisational relationships for knowledge co-creation, many collaborations struggle to realise the synergistic benefits of these networks. This paper aims to explore the evolving dialectic tensions evident within an inter-organisational relationship and the governance consideration to optimise the knowledge process. Design/methodology/approach A longitudinal case of a university-industry knowledge network is selected for study. The single case analysis aligns with the dialectical epistemology, which dismisses the expectation of homogeny or constancy across network cases. Findings The research highlights the circular condition between dialectic tensions evident within inter-organisational relations and the governance mechanisms developed to synthesis the network knowledge discovery capability. The research shows that these tensions are a natural part of the network existence and often advantageous to knowledge creation. The research also highlights that governance is required at multiple levels within the network entity to optimise knowledge exchange and discovery. Originality/value The research adds to the limited application of dialectical thinking to inter-organisational networks. It highlights the structural and relational governance mechanisms that interplay to optimise their knowledge process capability. The research also highlights the multiple levels within networks at which tensions can originate, requiring knowledge governance at the micro, meso and macro level to address the complexity of the inter-organisational relationship. This research provides a better understanding of how knowledge within inter-organisational relations can be managed for mutual benefit and value creation.
A comparison of three think-aloud protocols used to evaluate a voice intelligent agent that expresses emotions

ABSTRACT This study proposes two adapted think-aloud protocols for the evaluation of a voice intelligent agent. In the adapted retrospective think-aloud (RTA) protocol, users verbalise their thoughts based on the chat history after task-completion. In the adapted interactive think-aloud (ITA) protocol, users verbalise their thoughts regarding the intelligent agent being evaluated without the help of a facilitator. This study compares these two protocols with the classical think-aloud protocol (CTA) for evaluating an intelligent agent in terms of task time and verbal utterances. The influence of the intelligent agent’s emotional expression is also considered. The results suggest RTA is suitable for collecting user experience and causal explanation of utterances, CTA for collecting recommendation and prediction utterances, and ITA for collecting problem formulation and recommendation utterances. Furthermore, CTA and RTA can collect more total utterances, while CTA and ITA are influenced less the VIA’s emotional expression. This study provides guidelines by which future evaluators can choose suitable think-aloud protocols.
60.2: Efficient Light‐field Rendering using Depth Maps

To generate light-field display images, a large amount of cameras or input images is required. This creates difficulties in designing both the acquiring system and memory storage. In this paper, we propose an efficient light-field rendering algorithm using only a few input color and depth images. Using a depth map and estimated camera parameters, synthesized light-field images were directly generated. With the use of this algorithm, the memory load is much lighter than with a conventional light-field rendering algorithm. This algorithm is also much simpler than the imagebased rendering (IBR) algorithm because it does not involve the generation of many multiview images. Author Keywords Depth-image-based rendering; image-based rendering; light-field rendering, multi-projection; light-field display; 3D display; glassfree 3D
Supporting Group Workspaces Based on WebDAV

WebDAV is an IETF standard protocol which support asynchronous collaborative authoring on the Web. The recently published WebDAV Access Control Protocol provides various methods of controlling the resources on a WebDAV server and their properties, helping high-level group activities to be performed through the WebDAV server. Based on the WebDAV access control protocol, we developed Group Workspaces which support exchanging and/or sharing data among the group members. Any member of a Group Workspace can create and share resources among the members. Also, any member can add, change or delete the resources. To support the Group Workspaces, we developed a client application named GroupExplorer, which solely supports Group Workspaces. We constructed the server for Group Workspaces using Jakarta Slide - a WebDAV server supporting the WebDAV Access Control Protocol.
Address Translation Layer for Byte-Addressable Non-Volatile Memory-Based Solid State Drives

Because of the need for processing and managing the massive amounts of big data in smart/wearable devices and driverless vehicles, semiconductor companies are focusing on developing byte-addressable non-volatile memory (NVM)-based storage systems. The byte-addressable NVMs, such as phase-change memory, resistive memory, and magnetoresistive memory, are regarded as an alternative to NAND flash memories. There have been many proposals and studies on the use of NVM as main memory in the memory hierarchy. However, there has not been much academic research on using NVM as a substitute for NAND flash memories. This paper provides a system architecture for an NVM-based solid state drive based on some speculations/assumptions on the hardware characteristics of NVMs. It applies the previously proposed address-mapping algorithms of conventional solid state drives to the NVM-based solid state drives and examines their suitability. The optimization of I/O parallelism of static and dynamic address mapping algorithms is compared and analyzed. This paper also observes the effect of log block policies on the hardware characteristics of the NVMs.
Outage probability for maximal ratio combining of arbitrarily correlated faded signals corrupted by multiple Rayleigh interferers

Due to the functional complexity of its signal-to-interference (SIR) ratio, the outage probability of maximum ratio combining is available only for certain independent and identically distributed (i.i.d.) fading environments. In this paper, we partially relax this restriction by allowing the signal channel-gain vector to follow a general fading distribution with arbitrary spatial correlation. The problem is tackled in a novel framework. The key step is to represent the probability density of the reciprocal of SIR, conditioned on signal vector, as the higher-order derivative of a simple exponential function in signal power whereby a generic formula for outage probability can be determined. The application of the generic formula to Rayleigh, Rician, and Nakagami faded signals is elaborated. Numerical results are also presented for illustration.
Platelet glycoprotein Ibα polymorphisms modulate the risk for myocardial infarction

Summary Platelet glycoprotein Iba (GPIba) gene polymorphisms have been reported to affect the risk of developing coronary heart disease. Here, within the GPIba gene, we determine the association between the variable number of tandem repeats (VNTR), the -5C/T Kozak sequence dimorphism, and the human platelet antigen (HPA)-2 polymorphisms with occurrence of myocardial infarction (MI). Patients (n=180) presenting survivors of MI were compared to 180 controls matched by age, gender, and race. Carriers of VNTR-CD genotype had a 2-fold higher risk for MI compared to controls. The prevalence of VNTR-BC was lower among patients than among controls (P=.007). These data are in agreement with recent reports of increased plug formation by human platelets containing VNTRCD but no other VNTR genotypes. Among patients, the number of vessels severely occluded was greater among carriers of the D-allele (P=.019) or VNTR-CD (P=.026) and lower among carriers of the C-allele (P=.003) or VNTR-CC (P=.0009) compared to non-carriers of these alleles. No influence was seen with the Kozak or HPA-2 polymorphisms. Determination of VNTR of the GPIba gene may prove useful for identifying high-risk individuals for MI.
Development of a Novel, Tree-Like Branching Continuum Robot with Variable Topology

This thesis describes the design and physical realization of a novel branching continuum robot, aimed at inspection and cleaning operations in hard-to-reach environments at depths greater than human arm lengths. The design, based on a hybrid concentric-tube/tendon actuated continuum trunk core, features two pairs of fully retractable continuum branches. The retractable nature of the branches allows the robot to actively change its topology, allowing it to penetrate narrow openings and expand to adaptively engage complex environmental geometries. We detail and discuss the realization of a physical prototype of the design, and its testing in several simulated application environments.