Miracle-dz/UniFAR-FTUs huggingface dataset:
A Calcar Collar Is Protective Against Early Torsional/Spiral Periprosthetic Femoral Fracture: A Paired Cadaveric Biomechanical Analysis.

BACKGROUND Periprosthetic fracture is a leading reason for readmission following total hip arthroplasty. Most of these fractures occur during the early postoperative period before bone ingrowth. Before ingrowth occurs, the femoral component can rotate relative to the femoral canal, causing a spiral fracture pattern. We sought to evaluate, in a paired cadaver model, whether the torsional load to fracture was higher in collared stems. The hypothesis was that collared stems have greater load to fracture under axial and torsional loads compared with collarless stems. METHODS Twenty-two cadaveric femora (11 matched pairs) with a mean age of 77 ± 10.2 years (range, 54 to 90 years) were harvested. Following dissection, the femora were evaluated with use of a dual x-ray absorptiometry scanner and T scores were recorded. We utilized a common stem that is available with the same intraosseous geometry with and without a collar. For each pair, 1 femur was implanted with a collared stem and the contralateral femur was implanted with a collarless stem with use of a standard broaching technique. A compressive 68-kg load was applied to simulate body weight during ambulation. A rotational displacement was then applied until fracture occurred. Peak torque prior to fracture was measured with use of a torque meter load cell and data acquisition software. RESULTS The median torque to fracture was 65.4 Nm for collared stems and 43.1 Nm for uncollared stems (p = 0.0014, Wilcoxon signed-rank test). The median T score was -1.95 (range, -4.1 to -0.15). The median difference in torque to fracture was 29.18 Nm. As expected in each case, the mode of failure was a spiral fracture around the implant. CONCLUSIONS Collared stems seemed to offer a protective effect in torsional loading in this biomechanical model comparing matched femora. CLINICAL RELEVANCE These results may translate into a protective effect against early periprosthetic Vancouver B2 femoral fractures that occur before osseous integration has occurred.
Timing of Partial Melting and Cooling across the Greater Himalayan Crystalline Complex (Nyalam, Central Himalaya): In-sequence Thrusting and its Implications

The timing of crustal melting and cooling has been investigated across the migmatites of the Greater Himalayan Crystalline Complex (GHC) in the Nyalam region, central Himalaya. Monazite U–Pb ages vary from 32 to 14 Ma and are linked to metamorphic conditions on the basis of monazite internal zoning, mineral inclusions, and changes in heavy rare earth element and Y composition. Metamorphic temperatures were estimated by Zr-in-rutile thermometry and cooling rates were further constrained by rutile U–Pb ages. The results reveal two distinct blocks within the GHC of the Nyalam region. The upper GHC experienced higher peak metamorphic temperatures (730–750 � C) and a higher degree of melting (15–25%). Partial melting was dominated by muscovite dehydration melting, which lasted from � 32 to 25 Ma, possibly until � 20 Ma. The lower GHC experienced lower peak metamorphic temperatures (640–675 � C) and a lower degree of melting (0–10%) mainly via H2O-saturated melting from 19 to 16 Ma. At different times, both upper and lower blocks experienced initial slow cooling (rates 35 6 8 and 10 6 5 � CM a –1 , respectively) followed by rapid cooling (100 6 20 � CM a –1 ). The documented diachronous metamorphism implies the presence of the ‘High Himalayan Thrust’ that was active at � 25–16 Ma within the GHC of the central Himalaya. Different degrees and durations of partial melting in the investigated section suggest that a channel flow process dominated the exhumation of the upper GHC migmatites at 25–16 Ma, whereas a critical taper process dominated the exhumation of the relatively lower-grade lower GHC rocks and cooled upper GHC migmatites at 16–10 Ma. We suggest that propagating thrusts along large tectonic boundaries together with low-viscosity lateral crustal flow could contribute to exhumation of high-grade metamorphic rocks in the Himalaya and other similar collisional orogens.
Sprite beads originating from inhomogeneities in the mesospheric electron density

Small, persistent luminous spots observed in sprites may be originated by underlying inhomogeneities in the density of free electrons. Using a streamer density model, we show that the collision of a streamer with a localized enhancement of ionization leaves a region of reduced conductivity and enhanced field in the streamer channel. We discuss the light emissions from this region and predict its spectrum. These emissions are identified with “sprite beads” and we propose that they may serve to investigate the spatial distribution of free electrons in the upper atmosphere above a thunderstorm.
Title Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms

We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined “index of chromosome sharing” (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of the shared segments from the genotypes of two individuals. To investigate the expected ICS distributions from firstto fifth-degree relatives and unrelated pairs, we used computationally generated genotypes to consider the effect of linkage disequilibrium and recombination. The distributions were used for probabilistic evaluation of the pairwise kinship analysis, such as likelihood ratio (LR) or posterior probability, without allele frequencies and haplotype frequencies. Using our method, all actual sample pairs from volunteers showed significantly high LR values (i.e., 10); therefore, we can distinguish distant relationships (up to the fifth-degree) from unrelated pairs based on LR. Moreover, we can determine accurate degrees of kinship in up to third-degree relationships with a probability of > 80% using the criterion of posterior probability 0.90, even if the kinship of the pair is totally unpredictable. This approach greatly improves pairwise kinship analysis of distant relationships, specifically in cases involving identification of disaster victims or missing persons.
The Impact of Financial Development on Economic Growth in Zimbabwe: Comparative Analysis of Stock Markets and Commercial Banks

The purpose of this paper is to examine the relationship between financial development—bank and stock market—and economic growth in Zimbabwe. Using data during the period from 2005 to 2013, the study employed a VECM for the short run Controls variables. This offers a possibility of applying VAR in order to use integrated multivariate time series and avoid spurious regression as the interest rates appear to have long run positive impact on economic growth. This means that banking sector performs better than the stock markets if the interest rate is positively related to economic growth. The findings suggest a positive relationship between efficient stock market and economic growth both in short run and long run. Interest rates have a negative effect, while market capitalisation has a positive effect on growth. It is concluded that financial sector is important in the process of sustainable economic development in Zimbabwe.
Face masks to prevent community transmission of viral respiratory infections: A rapid evidence review using Bayesian analysis

Background: Face masks have been proposed as an important way of reducing transmission of viral respiratory infections, including SARS-CoV-2. Objective: To assess the likelihood that wearing face masks in community settings reduces transmission of viral respiratory infections. Methods: We conducted a rapid evidence review and used a Bayesian statistical approach to analysing experimental and observational studies conducted in community-dwelling children and adults that assessed the effectiveness of face mask wearing (vs. no face masks) on self-reported, laboratory-confirmed, or clinically diagnosed viral respiratory infections. Results: Eleven RCTs and 10 observational studies met the inclusion criteria. The calculation of Bayes factors and cumulative posterior odds from the RCTs showed a moderate likelihood of a small effect of wearing surgical face masks in community settings in reducing self-reported influenza-like illness (ILI) (cumulative posterior odds = 3.61). However, the risk of reporting bias was high and evidence of reduction of clinically- or laboratory-confirmed infection was equivocal (cumulative posterior odds = 1.07 and 1.22, respectively). Observational studies yielded evidence of a negative association between face mask wearing and ILI but with high risk of confounding and reporting bias. Conclusions: Available evidence from RCTs is equivocal as to whether or not wearing face masks in community settings results in a reduction in clinically- or laboratory-confirmed viral respiratory infections. No relevant studies concerned SARS-CoV-2 or were undertaken in community settings in the UK.
The time‐varying performance of UK analyst recommendation revisions: Do market conditions matter?

This study examines the time-varying performance of investment strategies following analyst recommendation revisions in the UK stock market, with specific emphasis on the impact of changing market conditions. We find a negative relationship between the recommendation performance and market conditions as measured in terms of past market return and market volatility. In particular, the upgrade (downgrade) portfolio generates significantly positive (negative) net abnormal returns in bad market conditions (e.g., the dot-com bubble burst in 2000 and the credit crisis in 2007), but not in other periods of time. Moreover, our non-temporal threshold regression analysis shows that the reported negative relationship disappears when market conditions become better, i.e., when the past market return (market volatility) is higher (lower) than a certain level, indicating the importance of taking non-linearity into account in the long sample period as examined in this study. Our time-series bootstrap simulations further confirm that the superior recommendation performance in bad market conditions is not due to random chance; analysts have certain skills in making valuable up/downward revisions in bad markets.
Mental Models and Dynamic Capabilities in a Brazilian Family Company

This article analyzes how the concepts of paradigm, organizational culture, and cognition of resources influence the mindset of managers and skew the choice of which dynamic capabilities should be developed by an organization, in the process of innovation and change. A case study was carried out that examined a traditional 64-year-old family publishing house. In-depth interviews with the company’s partners were conducted, as well as a documental analysis. The results revealed that organizational paradigms skew the choice of which dynamic capabilities should be developed, prioritizing those that are in accordance with the organizational paradigm. Therefore, the organization tends to be aligned with its own paradigm, rather than aligning with context. It demonstrates the importance of the organizational paradigm, organizational culture, and cognition of resources in the mindset of managers. Throughout periods of innovation and change, those aspects may influence the decision- making process in the organization. This is considered a relevant aspect of understanding how some small businesses survive environmental changes while others succumb to them.
Featureless EMG pattern recognition based on convolutional neural network

In this paper, the performance of featureless EMG pattern recognition in classifying hand and wrist movements are presented. The time-frequency distribution (TFD), spectrogram is employed to transform the raw EMG signals into time-frequency representation (TFR). The TFRs or spectrogram images are then directly fed into convolutional neural network (CNN) for classification. Two CNN models are proposed to learn the features automatically from the images without the need of manual feature extraction. The performance of CNN with different number of convolutional layers is examined. The proposed CNN models are evaluated using the EMG data from 10 intact and 11 amputee subjects through the publicly access NinaPro database. Our results show that CNN classifier offered the best mean classification accuracy of 88.04% in recognizing hand and wrist movements.
Task Allocation With Unmanned Surface Vehicles in Smart Ocean IoT

The unmanned surface vehicles (USVs) have been regarded as a promising paradigm to automatically perform emergency tasks in a dynamic maritime traffic environment. However, the performance of maritime communication between USVs and offshore platforms becomes a critical challenge, and the efficiency of task allocation for USVs in the smart ocean is low. In this article, a novel task allocation scheme for USVs in the smart ocean Internet of Things (IoT) is proposed to improve the efficiency of task allocation. First, the offshore platform is developed to provide maritime communication for USVs in the smart ocean IoT. Second, the network resource allocation process between USVs and offshore platforms is modeled as the second price sealed auction game, where the optimal bidding strategy of USV is derived by the $Q$ -learning to maximize the utilities of USVs and offshore platforms. Third, the task allocation scheme is proposed to improve the number of allocated tasks. Finally, the performance of the proposed scheme is conducted based on extensive simulations. The simulation results show that the proposed scheme can significantly improve the number of allocated tasks compared with the conventional schemes.
Explorer Are Food Animals Responsible for Transfer of Antimicrobial-Resistant Escherichia coli or Their Resistance Determinants to Human Populations ?

The role of farm animals in the emergence and dissemination of both AMR bacteria and their resistance determinants to humans is poorly understood and controversial. Here, we systematically reviewed the current evidence that food animals are responsible for transfer of AMR to humans. We searched PubMed, Web of Science, and EMBASE for literature published between 1940 and 2016. Our results show that eight studies (18%) suggested evidence of transmission of AMR from food animals to humans, 25 studies (56%) suggested transmission between animals and humans with no direction specified and 12 studies (26%) did not support transmission. Quality of evidence was variable among the included studies; one study (2%) used high resolution typing tools, 36 (80%) used intermediate resolution typing tools, six (13%) relied on low resolution typing tools, and two (5%) based conclusions on co-occurrence of resistance. While some studies suggested to provide evidence that transmission of AMR from food animals to humans may occur, robust conclusions on the directionality of transmission cannot be drawn due to limitations in study methodologies. Our findings highlight the need to combine high resolution genomic data analysis with systematically collected epidemiological evidence to reconstruct patterns of AMR transmission between food animals and humans.
A COMPUTER RESOURCE FOR THE ELEMENTARY SCHOO

The appropriate and effective uses of the computer in an individualized school were examined in this project. The project investigated the uses of computers for instructional assistance, including testing, management, tutorial instruction, drill and practice, exploration and discovery, and problem solving; the design of a small computer time-sharing system with a multi-language capability, and the processes underlying developmental work in computer assisted instruction. A small mobile computer system was used at the Oakleaf Elementary School in Baldwin-Whitehall, Pennsylvania, to test the program components; computer system design; computer assisted testing; computer-assisted instruction in spelling, mathematizs, and problem solving techniques; and computer-assisted management. Plans for 1972-73 were presented for each area, with considerations for determining the computer's potential. (PS)
Particle-based artificial three-dimensional stem cell spheroids for revascularization of ischemic diseases

Material technology can simulate hypoxic stem cells for vascular regeneration, providing new insights into synthetic biology. Development of new approaches to biomimetically reconstruct vasculature networks remains challenging in regenerative medicine. We introduce a particle-based artificial stem cell spheroid (ASSP) technology that recapitulates paracrine functions of three-dimensional (3D) SSPs for vasculature regeneration. Specifically, we used a facile method to induce the aggregation of stem cells into 3D spheroids, which benefited from hypoxia microenvironment–driven and enhanced secretion of proangiogenic bioactive factors. Furthermore, we artificially reconstructed 3D spheroids (i.e., ASSP) by integration of SSP-secreted factors into micro-/nanoparticles with cell membrane–derived surface coatings. The easily controllable sizes of the ASSP particles provided superior revascularization effects on the ischemic tissues in hindlimb ischemia models through local administration of ASSP microparticles and in myocardial infarction models via the systemic delivery of ASSP nanoparticles. The strategy offers a promising therapeutic option for ischemic tissue regeneration and addresses issues faced by the bottlenecked development in the delivery of stem cell therapies.
Loughborough University Institutional Repository Towards a learning framework for dancing robots

How can we make robots learn how to dance? How do humans learn to dance? An emerging culture of dancing robots is becoming more prominent in the research community with more emphasis on how we can show of our own creativity rather than allowing the robots to develop their own cognitive and psychological behaviours to the music being played. There are many different types of music and indeed, many different robots and many ways, in which they can dance to music however, much of the work carried out in this field concern limiting robots to dance in particular ways to a specific music and no adaptive behaviour implemented in them to be able to respond intuitively to music in general. We propose in this paper, a way in which such a problem can begin to be looked into, by introducing fundamental things that should be learnt that are necessary for dancing. We programmed a virtual robot to learn to dance to the beat as well as recognise the downbeat of any time-signature and tailor its movements to the loudness of music, using the Sarsa and the Sarsa( λ ) algorithms from reinforcement learning as the learning framework. Experimental results show that it is possible to make robots learn to dance to these fundamental rhythmic features of music.
Comparative study on the taxonomic relevance of gnathosomal structures in the family Zerconidae (Acari: Mesostigmata)

Taxonomic relevance of hypostomal, subcapitular, epistomal and cheliceral characters within the family Zerconidae is discussed with remarks on ontogeny, sexual-, individualand interspecific variability of these characters. The general structure and chaetotaxy of the hypostome and subcapitulum is one of the most invariant among gnathosomal parts, only the shape of hypostomal, capitular and palp trochantral setae seem to have diagnostic relevance. A method is proposed for description of relative robustness of chelicerae. The importance of observation of subcapitular, hypostomal and cheliceral morphology is emphasized by the example of Syskenozercon and Rotundozercon. A more careful typified system of the epistome morphology (which was previously considered as a character of generic importance) in the known Zerconidae taxa is presented.
The genetic architecture of a host shift: An adaptive walk protected an aphid and its endosymbiont from plant chemical defenses

A complex series of mutational events protected a mutualistic symbiosis during the shift of an insect to a toxic host plant. Host shifts can lead to ecological speciation and the emergence of new pests and pathogens. However, the mutational events that facilitate the exploitation of novel hosts are poorly understood. Here, we characterize an adaptive walk underpinning the host shift of the aphid Myzus persicae to tobacco, including evolution of mechanisms that overcame tobacco chemical defenses. A series of mutational events added as many as 1.5 million nucleotides to the genome of the tobacco-adapted subspecies, M. p. nicotianae, and yielded profound increases in expression of an enzyme that efficiently detoxifies nicotine, both in aphid gut tissue and in the bacteriocytes housing the obligate aphid symbiont Buchnera aphidicola. This dual evolutionary solution overcame the challenge of preserving fitness of a mutualistic symbiosis during adaptation to a toxic novel host. Our results reveal the intricate processes by which genetic novelty can arise and drive the evolution of key innovations required for ecological adaptation.
Freshwater mollusks and environmental assessment of Guandu River, Rio de Janeiro, Brazil

Abstract: The Guandu River Basin is extremely important to state of Rio de Janeiro, as a water supplier of several municipalities. However, the malacological knowledge and environmental status is not well known to this basin. The aim of this paper is to present an inventory of freshwater mollusks, as well as an environmental assessment through a Rapid Assessment Protocol, of ten sampling sites at Guandu River basin in six municipalities (Pirai, Paracambi, Japeri, Seropedica, Queimados and Nova Iguacu). Thirteen species of molusks were found, eight native ( Pomacea maculata , Biomphalaria tenagophila , Gundlachia ticaga , Gundlachia radiata , Omalonyx matheroni , Diplodon ellipticus , Anodontites trapesialis and Eupera bahiensis ) and five exotics ( Melanoides tuberculata, Ferrissia fragilis , Physa acuta, Corbicula fluminea and Corbicula largillierti ). The environmental analysis ranked most sites as “modified”. The expansion of exotic species with their associated negative effects, as well the gap in knowledge of native species calls attention to the need of future studies of biology and ecology of the species found.
Classification of the fibronectin variants with curvelets Anca -

The role of the extracellular matrix (ECM) in the evolution of certain diseases (e.g. fibrosis, cancer) is generally accepted but yet to be completely understood. A numerical model that captures the physical properties of the ECM, could convey certain connections between the topology of its constituents and their associated biological features. This study addresses the analysis and modeling of fibrillar networks containing Fibronectin (FN) networks, a major ECM molecule, from 2D confocal microscopy images. We leveraged the advantages of the fast discrete curvelet transform (FDCT), in order to obtain a multiscale and multidirectional representation of the FN fibrillar networks. This step was validated by performing a classification among the different variants of FN upregulated in disease states with a multi-class classification algorithm, DAG-SVM. Subsequently, we designed a method to ensure the invariance to rotation of the curvelet features. Our results indicate that the curvelets offer an appropriate discriminative model for the FN networks, that is able to characterize the local fiber geometry.