Miracle-dz/UniFAR-FTUs huggingface dataset:
Wear, oxidation and mechanical properties of a sequentially irradiated and annealed UHMWPE in total joint replacement

Ultra high molecular weight polyethylene (UHMWPE) has been used as a bearing surface in joint replacement prostheses for over 40 years. Recently, highly crosslinked UHMWPE (HXPE) materials were introduced based on the finding that crosslinking reduces wear. These first generation HXPE materials were produced by irradiation followed by heating below the melting temperature (annealing) or above the melting temperature (remelting). Both classes of HXPE material have demonstrated greatly reduced wear. However, remelted HXPE materials have reduced fatigue strength while annealed HXPE materials may oxidize when exposed to oxygen. A second generation HXPE material was produced using a sequential irradiation and annealing process (SXL). SXL materials have crosslinking levels equivalent to those of first generation HXPE materials, have fatigue and mechanical strength characteristics of first generation annealed HXPE material and have an oxidation resistance equivalent to that of virgin (unprocessed) UHMWPE. This combination of properties makes SXL HXPE a preferred material for bearing surfaces of joint prostheses.
On normal approximations to strongly mixing random fields

In this paper, we estimate the difference $|{\bf E} h(Z_V) -{\bf E} h(N)|$, where $Z_{V}$ is a sum over any finite subset V of the standard lattice ${\bf Z}^d$ of normalized random variables of the strongly mixing random field $\{X_a$, $a\in {\bf Z}^d\}$ (without assuming stationarity) and N is a standard normal random variable for the function $h:{\bf R}\to{\bf R}$, which is finite and satisfies the Lipschitz condition. In a particular case, the obtained upper bounds of $|{\bf E} h(Z_V) -{\bf E} h(N)|$ in Theorems 3 and 4 are of order $O(|V|^{-1/2})$.
Linearly polarized asymmetric dielectric resonator antenna for 5.2-GHz WLAN applications

A rectangular shape of asymmetric dielectric resonator antenna (DRA) excited by a coaxial probe is proposed and investigated. The asymmetric DRA geometry can offer an impedance bandwidth up to 51% for |S11| < −10 dB from 4.1 to 6.7 GHz. The antenna covers most of the wireless systems like 5.2, 5.5, and 5.8 GHz WLAN/Wi-MAX applications. The experimentally measured result shows that the efficiency is above 90% for the bandwidth of operation. The simulated and measured radiation patterns are consistent throughout the operational bandwidth. The measured peak gain over the band is 8.2 dBi. It is also observed that the newly proposed configuration reduces the DRA volume by 26% as compared to conventional rectangular DRA, with compact volume of 8.24 cm3. Good match between the measured and simulated results has been obtained.
Fully Soft-Switched Ultra-High Step-Up Converter With Very Low Switch Voltage Stress

In this article, a fully soft-switched ultra-high-voltage gain converter with very low switch voltage stress is presented. To achieve ultra-high-voltage gain and very low switch voltage stress, two phases of a high step-up boost converter based on coupled inductors and switched capacitors are combined. In this converter, the main and auxiliary switches operate at zero-voltage switching (ZVS) and all diodes turn-off at zero-current switching (ZCS). Thus, the reverse recovery problem of the diodes and the switching loss for all the semiconductor devices are mitigated. In addition, given that the voltage stress across the switches is remarkably low, mosfets with low drain-source resistance (RDS-on) can be utilized to substantially lower the conduction loss. Hence, all the mentioned advantages have contributed to the converter efficiency improvement. Also, the existence of the common ground between the input and the output expands the converter applicability and reduces the control circuit complexity. Finally, a 300 W laboratory prototype is implemented to verify the theoretical analysis and a comprehensive comparison with counterpart structures is presented to illustrate the advantages and disadvantages of the presented converter.
Multicenter validation of a deep-learning-based pediatric early-warning system for prediction of deterioration events

Background Early recognition of deterioration events is crucial to improve clinical outcomes. For this purpose, we developed a deep-learning-based pediatric early-warning system (pDEWS) and aimed to validate its clinical performance. Methods This is a retrospective multicenter cohort study including five tertiary-care academic children’s hospitals. All pediatric patients younger than 19 years admitted to the general ward from January 2019 to December 2019 were included. Using patient electronic medical records, we evaluated the clinical performance of the pDEWS for identifying deterioration events defined as in-hospital cardiac arrest (IHCA) and unexpected general ward-to-pediatric intensive care unit transfer (UIT) within 24 hours before event occurrence. We also compared pDEWS performance to those of the modified pediatric early-warning score (PEWS) and prediction models using logistic regression (LR) and random forest (RF). Results The study population consisted of 28,758 patients with 34 cases of IHCA and 291 cases of UIT. pDEWS showed better performance for predicting deterioration events with a larger area under the receiver operating characteristic curve, fewer false alarms, a lower mean alarm count per day, and a smaller number of cases needed to examine than the modified PEWS, LR, or RF models regardless of site, event occurrence time, age group, or sex. Conclusions The pDEWS outperformed modified PEWS, LR, and RF models for early and accurate prediction of deterioration events regardless of clinical situation. This study demonstrated the potential of pDEWS as an efficient screening tool for efferent operation of rapid response teams.
The Flight of the Space Shuttle Discovery (STS‐119)

This article is intended to model the ascent of the space shuttle for high school teachers and students. It provides a background for a sufficiently comprehensive description of the physics (kinematics and dynamics) of the March 16, 2009, Discovery launch. Our data are based on a comprehensive spreadsheet kindly sent to us by Bill Harwood, the “CBS News” space consultant. The spreadsheet provides detailed and authentic information about the prediction of the ascent of flight STS‐119, the 36th flight of Discovery and the 125th shuttle flight to date. We have used the data for our calculations and the production of the graphs. A limited version of the ascent data is available on the “CBS News” STS‐119 trajectory timeline.1
Predicting hypertension onset from longitudinal electronic health records with deep learning

Abstract Objective Hypertension has long been recognized as one of the most important predisposing factors for cardiovascular diseases and mortality. In recent years, machine learning methods have shown potential in diagnostic and predictive approaches in chronic diseases. Electronic health records (EHRs) have emerged as a reliable source of longitudinal data. The aim of this study is to predict the onset of hypertension using modern deep learning (DL) architectures, specifically long short-term memory (LSTM) networks, and longitudinal EHRs. Materials and Methods We compare this approach to the best performing models reported from previous works, particularly XGboost, applied to aggregated features. Our work is based on data from 233 895 adult patients from a large health system in the United States. We divided our population into 2 distinct longitudinal datasets based on the diagnosis date. To ensure generalization to unseen data, we trained our models on the first dataset (dataset A “train and validation”) using cross-validation, and then applied the models to a second dataset (dataset B “test”) to assess their performance. We also experimented with 2 different time-windows before the onset of hypertension and evaluated the impact on model performance. Results With the LSTM network, we were able to achieve an area under the receiver operating characteristic curve value of 0.98 in the “train and validation” dataset A and 0.94 in the “test” dataset B for a prediction time window of 1 year. Lipid disorders, type 2 diabetes, and renal disorders are found to be associated with incident hypertension. Conclusion These findings show that DL models based on temporal EHR data can improve the identification of patients at high risk of hypertension and corresponding driving factors. In the long term, this work may support identifying individuals who are at high risk for developing hypertension and facilitate earlier intervention to prevent the future development of hypertension.
Low-lying planar isomers of neutral and charged B22 clusters

Using the density functional theory, we investigate low-energy structures of B22 clusters. Our study shows that a 22-atom boron cluster prefers a three-dimensional double ring structure with a diameter of 0.58 nm for all of its charged states. This result combined with previous results of our calculations on B21, and by others on B19, B20 and B24 shows that boron clusters in the size range 19–24 show oscillation between planar and ring structures. Clusters with an odd number of atoms in this size regime tend to form planar structures, while clusters with an even number of atoms prefer three-dimensional ring structures. We have also studied several isomers of cationic and anionic B22 clusters.
Service Through Personal Encounters or Technology; the Preferences and Privacy Concerns of Generation Z

Companies nowadays use service personalization, both online and in the real world and most consumers have higher satisfaction with a product tailormade to their needs. Personalized recommendation systems, booking mobile applications are there to make the guest experience better and to tailor the products and experiences to the guest's needs. However, to be able to provide such service, personal data collection is inevitable. Even in the case of a satisfied consumer, privacy concerns are always present. As the hospitality service product become more digitalized, it is essential to consider if the Personalization - Privacy paradox is equally real for all age groups or target groups the hotel has. Would different age groups have different digital security concerns from each other? In this research paper, we only look at the example of Gen-Z tourism students and their willingness to share personal information in exchange for personalized service and whether they prefer these services online over face- to -face encounters.
Final Report of a Novel and Successful Online Pubic Health Capacity Building Experiment – Peoples-uni

The People’s Open Access Education Initiative (Peoples-uni) was established as an educational charity to help reduce inequalities in access to the higher education required to build Public Health capacity through workforce development for health professionals in low-to middle-income countries (LMICs). Online learning, using open source software, Open Educational Resources and an international cadre of volunteer tutors, underpinned a low cost programme which produced a number of successful outcomes including university validated master’s level awards, continuing professional development, positive feedback from students
Exponential Inequalities in Stochastic Inverse Problems Using an Iterative Method

We consider an iterative method in order to solve linear inverse problems. We establish exponential inequalities for the probability of the distance between the approximated solution and the exact one for a calibration problem. The approximate is given by an iterative method with Gaussian errors. We treat an operator equation of the form Ax = u, where A is a compact operator.
Recent Advances in Touch Sensors for Flexible Displays

A touch screen that combines a display and a touch sensor array is a critical component enabling human-machine interaction. The progress made in flexible touch screen technologies also vigorously drives the development and application of flexible electronics in various fields. Over the past decade, there have been enormous research and development efforts on new structures and materials for touch sensors in flexible displays, especially for flexible organic light-emitting diode (OLED) displays. Herein, this review discusses the mechanics and structures of flexible touch screens, including their benefits and drawbacks. The recent advances in the structures and electrode materials (e.g., ITO, silver nanowires, metal mesh, graphene, carbon nanotubes, and conductive polymers) are reviewed, and the challenges and prospects of these technologies are also explored.
On integrable solutions of a nonlinear Volterra integral equation under Carathéodory conditions

In this paper we study the existence of solutions of a nonlinear Volterra integral equation in the space of Lebesgue integrable functions on an unbounded interval. Our existence result is obtained under the assumption that functions involved in the considered integral equation satisfy conditions of Carathéodory type. The main tool used in the investigations of the paper is the combination of the technique of measures of weak noncompactness with the classical Schauder fixed point principle. The obtained result generalizes several ones obtained earlier in many papers and monographs.
Pilot Findings on SARS-CoV-2 Vaccine-Induced Pituitary Diseases: A Mini Review from Diagnosis to Pathophysiology

Since the emergence of the COVID-19 pandemic at the end of 2019, a massive vaccination campaign has been undertaken rapidly and worldwide. Like other vaccines, the COVID-19 vaccine is not devoid of side effects. Typically, the adverse side effects of vaccination include transient headache, fever, and myalgia. Endocrine organs are also affected by adverse effects. The major SARS-CoV-2 vaccine-associated endocrinopathies reported since the beginning of the vaccination campaign are thyroid and pancreas disorders. SARS-CoV-2 vaccine-induced pituitary diseases have become more frequently described in the literature. We searched PubMed/MEDLINE for commentaries, case reports, and case series articles reporting pituitary disorders following SARS-CoV-2 vaccination. The search was reiterated until September 2022, in which eight case reports were found. In all the cases, there were no personal or familial history of pituitary disease described. All the patients described had no previous SARS-CoV-2 infection prior to the vaccination episode. Regarding the type of vaccines administered, 50% of the patients received (BNT162b2; Pfizer–BioNTech) and 50% received (ChAdOx1 nCov-19; AstraZeneca). In five cases, the pituitary disorder developed after the first dose of the corresponding vaccine. Regarding the types of pituitary disorder, five were hypophysitis (variable clinical aspects ranging from pituitary lesion to pituitary stalk thickness) and three were pituitary apoplexy. The time period between vaccination and pituitary disorder ranged from one to seven days. Depending on each case’s follow-up time, a complete remission was obtained in all the apoplexy cases but in only three patients with hypophysitis (persistence of the central diabetes insipidus). Both quantity and quality of the published data about pituitary inconveniences after COVID-19 vaccination are limited. Pituitary disorders, unlike thyroid disorders, occur very quickly after COVID-19 vaccination (less than seven days for pituitary disorders versus two months for thyroid disease). This is partially explained by the ease of reaching the pituitary, which is a small gland. Therefore, this gland is rapidly overspread, which explains the speed of onset of pituitary symptoms (especially ADH deficiency which is a rapid onset deficit with evocative symptoms). Accordingly, these pilot findings offer clinicians a future direction to be vigilant for possible pituitary adverse effects of vaccination. This will allow them to accurately orient patients for medical assistance when they present with remarkable symptoms, such as asthenia, polyuro-polydipsia, or severe headache, following a COVID-19 vaccination.
Enhancement of Endurance Performance by Periodic Optimal Camber Control

A new method for endurance maximization is proposed. This method consists of the periodic optimal control of variable camber in a coordinated process with a corresponding control of throttle and elevator. It is shown that the proposed method can significantly increase the endurance when compared with the best steady-state flight. Using camber as a control provides an efficient means for improving the lift/drag ratio at each flight condition during the unsteady phases of periodic optimal endurance cruise. Engine considerations include fuel consumption during idling phases. They also address a reduction of the number of engine cycles in regard to alternate operating at a high and low thrust setting. The optimal control technique used is based on the minimum principle and the method of multiple shooting. Necessary conditions for optimality, including optimal control of variable camber setting, are analyzed.
Construction of AFLP-based cosegregation groups of tetraploid Plicatula species and identification of markers linked to apomixis

Abstract Most species of Plicatula are important native forages. This work aimed to build framework cosegregation groups of the apomictic tetraploid race of Paspalum guenoarum cv. Rojas and localize the locus controlling apomixis in the species. An interspecific population derived from crossing a completely sexual tetraploid plant of P. plicatulum and an apomictic tetraploid individual of P. guenoarum cv. Rojas was used. Both, disomic and tetrasomic inheritance were detected in both parental genotypes. In P. guenoarum, ten cosegregation groups were built, including 50 markers expanding for 583 cM. The estimated genome coverage was 63.95%. The apomixis locus was located in the linkage group M8, together with seven other loci (four paternal and three biparental markers). The group extended for 59 cM. The four paternal markers showed strong linkage to apomixis, and two of them mapped at 4 and 7 cM at both sides of the locus. Five female linkage groups were constructed with markers segregating from P. plicatulum. One of them (F3) being homologous to the male group carrying apomixis. The linkage groups presented here constitute the first genetic frame for species of Plicatula group. Moreover, molecular markers linked to apomixis in P. guenoarum can assist fundamental research and breeding programs.
Application of phase-retrieval x-ray diffractometry to carbon doped SiGe(C)∕Si(C) superlattice structures. II. High resolution reconstruction using neural network root finder technique

A neural network root finder approach for finding complex roots of high-degree complex polynomials was applied as part of the phase-retrieval x-ray diffractometry technique to reconstruct strain profiles in SiGe(C)∕Si(C) superlattice structures. The high spatial resolution, 5A, as a result of significantly higher degree of the complex polynomial, 1400 roots, allowed us to obtain more accurate results for the strain profile distribution in SiGe(C)∕Si(C) superlattice structures. Previously, such high quality analysis was fundamentally impossible due to the limitations imposed by conventional numerical methods of finding complex polynomial roots.
Adult Image Detection Based on AdaBoost

In this paper, a method of detecting adult images based on AdaBoost was proposed. We focused on the detection of the adult images that have naked breasts or naked genitalia. By using basic and rotated Haar-like features extracted from the samples in the training set, we trained a cascade detector. The detector would classify the image whether to be a pornographic one or not. The results showed that this method achieved a high detection rate and a low false alarm rate.
3D-CUBE readiness model for industry 4.0: technological, organizational, and process maturity enablers

ABSTRACT This paper proposes a new Readiness Model, 3D-CUBE, to assess the current state of manufacturing companies in the digital transformation context. Using a systematic literature review with 8-Steps-Search-Flow and a hypothetical-deductive framework (considering maturity as an 'input' enabler and not as an 'output'), the best information of 63 existing models was selected from 486 studies found in 10 databases. The 3D-CUBE was elaborated, with 3 dimensions (X = Organizational , Y = Technological , and Z = Process Maturity), 6 sub-dimensions, and 21 elements, including a scale 0-5 to assess the company readiness level. For the company’s Data Collection, a 3D-CUBE Questionnaire was developed, which provides a radar graph and calculates the company’s score with a readiness vector R=(X,Y,Z). Based on the existing model’s shortcoming, 3D-CUBE is a new contribution to this research stream, to help companies in getting ready for Industry 4.0.
Screening Discriminating SNPs for Chinese Indigenous Pig Breeds Identification Using a Random Forests Algorithm

Chinese indigenous pig breeds have unique genetic characteristics and a rich diversity; however, effective breed identification methods have not yet been well established. In this study, a genotype file of 62,822 single-nucleotide polymorphisms (SNPs), which were obtained from 1059 individuals of 18 Chinese indigenous pig breeds and 5 cosmopolitan breeds, were used to screen the discriminating SNPs for pig breed identification. After linkage disequilibrium (LD) pruning filtering, this study excluded 396 SNPs on non-constant chromosomes and retained 20.92~−27.84% of SNPs for each of the 18 autosomes, leaving a total of 14,823 SNPs. The principal component analysis (PCA) showed the largest differences between cosmopolitan and Chinese pig breeds (PC1 = 10.452%), while relatively small differences were found among the 18 indigenous pig breeds from the Yangtze River Delta region of China. Next, a random forest (RF) algorithm was used to filter these SNPs and obtain the optimal number of decision trees (ntree = 1000) using corresponding out-of-bag (OOB) error rates. By comparing two different SNP ranking methods in the RF analysis, the mean decreasing accuracy (MDA) and mean decreasing Gini index (MDG), the effects of panels with different numbers of SNPs on the assignment accuracy, and the statistics of SNP distribution on each chromosome in the panels, a panel of 1000 of the most breed-discriminative tagged SNPs were finally selected based on the MDA screening method. A high accuracy (>99.3%) was obtained by the breed prediction of 318 samples in the RF test set; thus, a machine learning classification method was established for the multi-breed identification of Chinese indigenous pigs based on a low-density panel of SNPs.
Filamentation of magnetosonic wave and generation of magnetic turbulence in laser plasma interaction

This paper presents a theoretical model for the magnetic turbulence in laser plasma interaction due to the nonlinear coupling of magnetosonic wave with ion acoustic wave in overdense plasma. For this study, dynamical equations of magnetosonic waves and the ion acoustic waves have been developed in the presence of ponderomotive force due to the pump magnetosonic wave. Slowly converging and diverging behavior has been studied semi-analytically, this results in the formation of filaments of the magnetosonic wave. Numerical simulation has also been carried out to study nonlinear stage. From the results, it has been found that the localized structures become quite complex in nature. Further, power spectrum has been studied. Results show that the spectral index follows (∼k−2.0) scaling at smaller scale. Relevance of the present investigation has been shown with the experimental observation.