Miracle-dz/UniFAR-FTUs huggingface dataset:
Surgical Management of the Problematic Hip in Adolescent and Young Adult Patients

Abstract Surgical management of the problematic hip in adolescent and young adult patients can be challenging. In many of these patients, hip arthrosis and pain occur secondary to hip dysplasia associated with chronic instability, whether the result of prior treatment or chronic unmanaged acetabular dysplasia. Surgical techniques such as the Bernese periacetabular osteotomy are performed to correct acetabular deficiency, restore hip joint stability, and eliminate pain. Patients with previous Legg‐Calvé‐Perthes disease or slipped capital femoral epiphysis frequently note onset of symptomatic hip arthrosis and pain in adolescence or young adulthood. Pain occurs secondary to pathologic impingement of the deformed proximal femur against the anterolateral acetabulum (ie, femoroacetabular impingement). The recent successful innovation of the transtrochanteric surgical hip dislocation approach provides complete access to the hip and offers the potential for comprehensive correction of both the often severe proximal femoral deformity and associated labral chondral disease secondary to Legg‐Calvé‐Perthes disease and slipped capital femoral epiphysis. Restoration of more normal proximal femoral morphology results in marked improvement in functional outcome. Effective orthopaedic management requires an understanding of the mechanisms of hip disease as well as surgical expertise.
Frequency-based multilayer neural network with on-chip learning and enhanced neuron characteristics

A new digital architecture of the frequency-based multilayer neural network (MNN) with on-chip learning is proposed. As the signal level is expressed by the frequency, the multiplier is replaced by a simple frequency converter, and the neuron unit uses the voting circuit as the nonlinear adder to improve the nonlinear characteristic. In addition, the pulse multiplier is employed to enhance the neuron characteristics. The backpropagation algorithm is modified for the on-chip learning. The proposed MNN architecture is implemented on field programmable gate arrays (FPGA's) and the various experiments are conducted to test the performance of the system. The experimental results show that the proposed neuron has a very good nonlinear function owing to the voting circuit. The learning behavior of the MNN with on-chip learning is also tested by experiments, which show that the proposed MNN has good learning and generalization capabilities. Simple and modular structure of the proposed MNN leads to a massive parallel and flexible network architecture, which is well suited for very large scale integration (VLSI) implementation.
A Web Service Discovery Method Based on Tag

With the growth of web service, traditional web service discovery mechanisms have become inefficient because of their low precision. Though the current semantic-based service discovery methods enhance the recall rate and precision in a way, most of the semantic-based service discovery methods are based on the new model of the semantic web and the ontology language, the number of the services based on the model of the semantic web and the ontology language is so little that these methods can not been used effectively. In this paper, we bring forward a new service discovery method based on the service tags. In order to discover service based on the services tags, we bring forward the algorithm QEBT and QPBT. Our experimental study shows that the algorithm QPBT is better than QEBT. Furthermore, both QEBT and QPBT are effective on discovering service.
Design and Implementation of the TRIPS Primary Memory System

In this paper, we describe the design and implementation of the primary memory system of the TRIPS processor. To match the aggressive execution bandwidth and support high levels of memory parallelism, the primary memory system is completely partitioned into four banks, can support up to 256 in-flight memory instructions, aggressive reordering of in-flight loads and stores, up to four loads and stores every cycle and up to 64 outstanding cache misses to sixteen different cache lines. The design was implemented using IBM 130 nm ASIC technology and occupies 21% of the processor area. We describe in detail the microarchitecture of the memory system, detailed design of two of the most complex and interesting components -the LSQ and the MHU -and discuss the rationale behind some of the design decisions. Our design experience suggests that the complexity of the partitioned memory system is comparable to less aggressive centralized implementations.
Simultaneous video synchronization and rare event detection via Cross-Entropy Monte Carlo optimization

We propose a novel approach for synchronizing multiple videos and simultaneously detecting rare events in these videos. Unlike conventional methods which deal with video synchronization and rare event detection separately, we cast these problems into an unified energy minimization framework and present a Cross-Entropy Monte Carlo (CEMC) based method to solve this problem. In our framework, rare event detection results are utilized to improve the accuracy of video synchronization. Reversely, video synchronization results are employed to efficiently detect rare events in multiple videos. Our experimental results show that our approach can accurately synchronize videos even when there is repetition of a same motion and arbitrary large time-shift between videos. Moreover, the experiments also demonstrate that our approach is advantageous in the detection of rare events in multiple videos, simultaneously, without any process of modeling or training.
Sequential individual resonance assignments in the 1H‐NMR spectra of polypeptides and proteins

Recently, a new procedure for the assignment of protein 1H‐nmr spectra was introduced that relies on stereochemical considerations of proton–proton distances in polypeptides and on the use of two‐dimensional nmr for obtaining 1H‐1H through‐bond and through‐space connectivity maps. In the present paper a particular aspect of this assignment procedure is discussed in more detail, i.e., how to obtain individual resonance assignments from identification of amino acid side‐chain spin systems and identification of neighboring residues in the amino acid sequence.
A New Non-intrusive Authentication Approach for Data Protection Based on Mouse Dynamics

Mouse-dynamics-related schemes have been shown to be feasible for user authentication systems, however, the existing approaches are either intrusive or not prompt response. Preventing unauthorized accesses to critical digital assets, namely, data stored in the file management system, is one of the major objectives of user authentication. We therefore propose a non-intrusive approach capable of verifying a user having performed a few times of file-related operations via a mouse. To evaluate the effectiveness of the proposed approach, the mouse movement of the file-related operations in Explorer, which is the most common way to search, open, save, copy, and/or delete files in Windows environments, is used for authentication. The experimental results show that the proposed approach is feasible and has three advantages: 1) it is non-intrusive, 2) it authenticates users in a short period of time, and 3) the quantity of mouse dynamics used for authentication purpose is lightweight.
Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test

The Bechdel test is a sequence of three questions designed to assess the presence of women in movies. Many believe that because women are seldom represented in film as strong leaders and thinkers, viewers associate weaker stereotypes with women. In this paper, we present a computational approach to automate the task of finding whether a movie passes or fails the Bechdel test. This allows us to study the key differences in language use and in the importance of roles of women in movies that pass the test versus the movies that fail the test. Our experiments confirm that in movies that fail the test, women are in fact portrayed as less-central and less-important characters.
Teachers as researchers: a 'fair dinkum' learning legacy

As we encounter a policy landscape where increasingly the education lexicon includes keywords such as data, evidence, quality, standards, it is interesting to revisit Garth Boomer's contribution regarding teachers as researchers. As an early-career classroom teacher in the mid-1970s, I was inspired by Boomer's provocation to engage with research as a practitioner seeking evidence of learning (or not learning). Since that time, convinced of the power of teacher research in enhancing both student and teacher learning, I have devoted a good deal of my academic life to finding ways of supporting teachers to engage in research - from finding funds to facilitate teacher-researcher networks, through designing research projects with teacher-researchers as key collaborators, to embedding practitioner inquiry in university courses wherever possible pre- and in-service.
Integrating tonal information into Mandarin name recognition with different strategies

Name recognition is a practical application of speech recognition technology. As Chinese is well known to be a tonal language, tonal information has an important influence on this task. In this paper we integrate tonal information into a speaker-independent Mandarin name recognizer, and two combination strategies: feature combination and posterior combination are investigated first. The recognizer is evaluated on an extremely challenging Mandarin name corpus, which includes 100 tonally confusing pairs. Although a significant improvement in the recognition accuracy can be achieved with either strategy, the system has a poor flexibility. Based on the analysis of the experimental results we propose a two-step process to improve the system performance further. It is shown that a maximal improvement of 29.96% in word accuracy can be achieved. At the same time the system has good flexibility with tonal information being integrated dynamically.
Sociodemographics, Comorbidities, Healthcare Utilization and Work Productivity in Japanese Patients with Adult ADHD

Objectives This study compared the sociodemographic characteristics, comorbidities, healthcare resource utilization, and work productivity among Japanese adults who reported being diagnosed with attention-deficit/hyperactivity disorder (ADHD) to those of a non-ADHD control population. Methods Data for this study were captured from an online survey of adults in Japan conducted by Kantar Health using consumer panels. A total of 84 survey participants reported they had received a diagnosis of ADHD from a physician. Survey responses pertaining to functional status and resource utilization from this ADHD group were compared to those from a non-ADHD control group of 100 participants. Comparisons between the ADHD and non-ADHD groups were made using chi-square tests for categorical variables and t-tests for continuous variables. Results Participants in the ADHD group were on average slightly younger with a higher proportion of males. ADHD respondents reported significantly more comorbid depression, sleep difficulties, headaches, and anxiety than non-ADHD controls. Over the previous 6 months, the ADHD group made more visits to healthcare providers and the emergency room, and had more hospitalizations than non-ADHD controls. The ADHD group also rated their overall health status lower than the non-ADHD control group. Respondents with ADHD reported a significantly higher degree of health-related work impairment compared to non-ADHD, with greater absenteeism and decreased work productivity. The ADHD group indicated their symptoms negatively impacted relationships, self-esteem, and regular daily activities. Conclusions Japanese adults with ADHD face a substantial burden of illness, including lower overall health status, increased number of comorbidities, greater healthcare utilization, and significant health-related occupational impairment compared to those without ADHD. Additional research is needed to develop a better understanding of both the consequences and treatment approaches for Japanese adults with ADHD.
Identification of highly gifted 5- and 6-year-old children: Measures to predict academic achievement.

Studies indicate the educational needs of highly gifted students are best met through accelerated learning. It is difficult to recognize very young children that are suited for an accelerated curriculum because younger students frequently lack school records or portfolios used to identify gifted students. This study examined the accuracy of cognitive ability and achievement tests in predicting academic achievement by the end of second grade, correlating test results and final grade averages collected from sixteen children ages five to six who entered a public school program for high-ability learners in kindergarten. A multiple regression analysis indicated the Wechsler Preschool and Primary Scale of Intelligence produced the highest mean IQ score and a strong correlation with reading achievement. The Wechsler Individual Achievement Test contributed in small part to the prediction of academic achievement. The Naglieri Nonverbal Ability Test and the Kaufman Brief Intelligence Test-Second Edition had negative correlations with final grade averages, indicating they are not predictors of academic achievement for these students.
A Humanized Clinically Calibrated Quantitative Systems Pharmacology Model for Hypokinetic Motor Symptoms in Parkinson’s Disease

The current treatment of Parkinson’s disease with dopamine-centric approaches such as L-DOPA and dopamine agonists, although very successful, is in need of alternative treatment strategies, both in terms of disease modification and symptom management. Various non-dopaminergic treatment approaches did not result in a clear clinical benefit, despite showing a clear effect in preclinical animal models. In addition, polypharmacy is common, sometimes leading to unintended effects on non-motor cognitive and psychiatric symptoms. To explore novel targets for symptomatic treatment and possible synergistic pharmacodynamic effects between different drugs, we developed a computer-based Quantitative Systems Pharmacology (QSP) platform of the closed cortico-striatal-thalamic-cortical basal ganglia loop of the dorsal motor circuit. This mechanism-based simulation platform is based on the known neuro-anatomy and neurophysiology of the basal ganglia and explicitly incorporates domain expertise in a formalized way. The calculated beta/gamma power ratio of the local field potential in the subthalamic nucleus correlates well (R2 = 0.71) with clinically observed extra-pyramidal symptoms triggered by antipsychotics during schizophrenia treatment (43 drug-dose combinations). When incorporating Parkinsonian (PD) pathology and reported compensatory changes, the computer model suggests a major increase in b/g ratio (corresponding to bradykinesia and rigidity) from a dopamine depletion of 70% onward. The correlation between the outcome of the QSP model and the reported changes in UPDRS III Motor Part for 22 placebo-normalized drug-dose combinations is R2 = 0.84. The model also correctly recapitulates the lack of clinical benefit for perampanel, MK-0567 and flupirtine and offers a hypothesis for the translational disconnect. Finally, using human PET imaging studies with placebo response, the computer model predicts well the placebo response for chronic treatment, but not for acute treatment in PD.
Narrative analysis in linguistic research

This chapter introduces the key elements of traditional and new emerging socio-linguistic approaches to the analysis of narratives, focusing speci? cally on narrative networks. It illustrates how a narrative networks approach examines narratives not only as texts, but also as representative of an array of social processes in their own contexts of production and consumption. The chapter ? rst reviews the main de? nitions of narratives and illustrates traditional analytical perspectives,namely the componential and functional analyses. It then presents narrative net-works: its origins and theoretical principles. It outlines a step-by-step procedure for designing and analysing networks, showing how they can facilitate the critical analysis of narratives as sociolinguistic manifestations.
A low-glycemic-load versus low-fat diet in the treatment of fatty liver in obese children.

BACKGROUND Fatty liver is highly prevalent among obese children and represents a major risk factor for chronic liver diseases and severe metabolic complications. METHODS We randomly assigned 17 obese children 8-17 years of age with fatty liver to either an experimental low-glycemic-load or conventional low-fat diet for 6 months. Participants in both groups received nutrition education and behavioral counseling of equal intensity. The primary outcome was hepatic lipid content measured by proton magnetic resonance spectroscopy. Secondary outcomes included change in visceral fat, BMI, anthropometrics, alanine aminotransferase (ALT), and insulin resistance. RESULTS A total of 16 participants completed the study. Reported glycemic load decreased in the low-glycemic-load group and reported dietary fat decreased in the low-fat group. At baseline, liver fat was 23.8% [standard deviation (SD) 12.2] in the low-glycemic-load group and 29.3% (14.1) in the low-fat group. Liver fat decreased substantially in both groups at 6 months expressed as absolute percentage change, with no between-group differences [-8.8 (standard error (SE) 4.1) vs. -10.5 (3.7)%, respectively, p=0.76 for group×time interaction]. Secondary outcomes also improved on both diets, with no between-group differences. Baseline and change in ALT were strongly associated with hepatic fat content. CONCLUSIONS Weight-reducing diets focused either on glycemic load or dietary fat improved hepatic steatosis over 6 months. Additional research is needed to determine whether these diets differ in effectiveness over the long term. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00480922.
Non-rigid registration guided by landmarks and learning

Registration methods frequently rely on prior information in order to generate anatomical meaningful transformations between medical scans. In this paper, we propose a novel intensity based non-rigid registration framework, which is guided by landmarks and a regularizer based on Principle Component Analysis (PCA). Unlike existing methods in this domain, the computational complexity of our approach reduces with the number of landmarks. Furthermore, our PCA is invariant to translations. The additional regularizer is based on the outcome of this PCA. We register a skull CT scan to MR scans aquired by a MR/PET hybrid scanner. This aligned CT scan can then be used to gain an attenuation map for PET reconstruction. As a result we have a Dice coefficient for bone areas at 0.71 and a Dice coefficient for bone and soft issue areas at 0.97.
Secure Regression on Distributed Databases

This article presents several methods for performing linear regression on the union of distributed databases that preserve, to varying degrees, confidentiality of those databases. Such methods can be used by federal or state statistical agencies to share information from their individual databases, or to make such information available to others. Secure data integration, which provides the lowest level of protection, actually integrates the databases, but in a manner that no database owner can determine the origin of any records other than its own. Regression, associated diagnostics, or any other analysis then can be performed on the integrated data. Secure multiparty computation, based on shared local statistics effects computations necessary to compute least squares estimators of regression coefficients and error variances by means of analogous local computations that are combined additively using the secure summation protocol. We also provide two approaches to model diagnostics in this setting, one using shared residual statistics and the other using secure integration of synthetic residuals.
The event-triggered integral criterion for sensor sampling

The paper presents the performance evaluation of the event-triggered integral criterion for sensor sampling. The proposed asynchronous sampling pattern is the extension of the simple "send on delta" strategy used e.g. in LonWorks/EIA-709 control networking technology. The analytical formula for evaluation the mean and the maximum rate of event-based traffic versus the sampling resolution is derived. The simulation results verifying the derived formula are reported. The definition of the integral "send on delta" concept and the framework of its implementation in Neuron C programming language are presented.
SpaceActor - Interface Prototypes for Virtual Environments

Expanding 3D technology involves several disciplines in designing 3D UI. By referring to principles of product design processes we explore new interface concepts and develop prototypes of usable and comprehensible 3D UI. SpaceActor serves as a general label for this endeavour. In this paper we present two new input devices with their corresponding control-display mappings. Both input devices are characterised by two modes of navigation. The NaviStick refers to the metaphors of driving a motorcycle and flying an aeroplane. The Kwisath is based on the metaphors of control lever (joystick) and flying lance. Both input devices allow a continuous change in navigation modes to be experienced by the user. Such a concept yields new user experiences travelling through 3D space. We describe our design based approach and report our first observations of the developed 3D UI concerning supported spatial awareness and convenience of movement. For this we carried out an exploratory test which had the purpose of gathering evidence supporting our iterative prototyping.
Routing Security in Ad Hoc Networks

The existing ad hoc routing protocols do not accommodate any security and are highly vulnerable to attacks. We discuss threats and attacks against ad hoc routing under several areas of application. We also look at some suggested solutions that could be used when secure protocols are designed. The current protocols should not be used in hostile environments unless the applications are especially designed to operate under insecure routing or until protocols with enhanced security are introduced.
THE ROLE OF PERCEPTUAL EPISODES IN LEXICAL PROCESSING

Nearly all theories of spoken word perception presume a lexicon with singular entries corresponding to each word. In turn, the perceptual system is presumed to operate by matching entries to the variable signals that speakers produce, requiring either normalization or sophisticated guessing. In contrast, episodic theories assume that people store multiple entries, in the form of detailed perceptual traces, for each known word. Such episodic theories are robust to variation, and they provide a natural account of extra-linguistic learning, such as learning voices. This paper presents a new experiment on episodic effects in word perception, and it reviews the application of a multiple-trace model to the data. Theoretical issues are briefly discussed, including the critical role of selective attention, and the relation of episodic theories to other burgeoning views.