Miracle-dz/UniFAR-FTUs huggingface dataset:
Objective Assessment of Spasticity With a Method Based on a Human Upper Limb Model

This paper presents a method based on a human upper limb model that assesses the severity of spasticity in patients with stroke objectively. The kinematic model consists of four moving segments connected by four joints. The joint torques are computed using inverse dynamics with measurements from three inertial measurement units (IMUs) attached to the participant’s upper limb. The muscle activations are estimated using the joint torques via a musculoskeletal model which consists of 22 muscles. The severity of spasticity is then quantified by measuring the tonic stretch reflex threshold (TSRT) of the participant. 15 patient participants participated in the experiments where they were assessed by two qualified therapists using modified Ashworth scale (MAS), and their motions and EMG signals were captured at the same time. Using the upper limb model, the TSRT of each patient was measured and ranked. The estimated muscle activation profiles have a high correlation (0.707) to the EMG signal profiles. The null hypothesis that the rankings of the severity using the model and the MAS assessment have no correlation has been tested, and was rejected convincingly ( ${\text p} \approx 0.0003$ ). These findings suggest that the model has the potential to complement the existing practices by providing an alternative evaluation method.
Rapid Phenotypic Antibiotic Susceptibility Testing of Uropathogens Using Optical Signal Analysis on the Nanowell Slide

Achieving fast antimicrobial susceptibility results is a primary goal in the fight against antimicrobial resistance. Standard antibiotic susceptibility testing (AST) takes, however, at least a day from patient sample to susceptibility profile. Here, we developed and clinically validated a rapid phenotypic AST based on a miniaturized nanotiter plate, the nanowell slide, that holds 672 wells in a 500 nl format for bacterial cultivation. The multitude of nanowells allows multiplexing with a panel of six antibiotics relevant for urinary tract infections. Inclusion of seven concentrations per antibiotic plus technical replicates enabled us to determine a precise minimum inhibitory concentration for 70 clinical uropathogenic Escherichia coli isolates. By combining optical recordings of bacterial growth with an algorithm for optical signal analysis, we calculated Tlag, the point of transition from lag to exponential phase, in each nanoculture. Algorithm-assisted analysis determined antibiotic susceptibility as early as 3 h 40 min. In comparison to standard disk diffusion assays, the nanowell AST showed a total categorical agreement of 97.9% with 2.6% major errors and 0% very major errors for all isolate-antibiotic combination tested. Taking advantage of the optical compatibility of the nanowell slide, we performed microscopy to illustrate its potential in defining susceptibility profiles based on bacterial morphotyping. The excellent clinical performance of the nanowell AST, combined with a short detection time, morphotyping, and the very low consumption of reagents clearly show the advantage of this phenotypic AST as a diagnostic tool in a clinical setting.
A distributed parameter Maxwell-Slip hysteresis model for piezoelectric actuators

Hysteresis is an important nonlinearity existing in piezoelectric actuators. Modeling and compensation is a common approach to handle it. This paper proposes a distributed parameter Maxwell-slip (DPMS) model. It is extended from the Maxwell-slip (MS) model. The DPMS model replaces the spring-slider elements in the MS model by a sliding cell and a elastic cell with distributed parameters. The properties of the elastic cell are described by two functions, i.e. the saturation deformation function and the stiffness function. These two functions also govern the hysteresis generated by the DPMS model and only require a few parameters. An approach to identify model parameters are proposed. Experiments demonstrate the effectiveness of the DPMS model. With a linear function describing the saturation deformation function, only two parameters (the character length and a coefficient) are required and the normalized mean squire error is 1.96%. The hysteresis nonlinearity is reduced from 13.8% to 2.55% by 81.5% if it is compensated by the inverse DPMS model.
Learning a Representation Map for Robot Navigation using Deep Variational Autoencoder

The aim of this work is to use Variational Autoencoder (VAE) to learn a representation of an indoor environment that can be used for robot navigation. We use images extracted from a video, in which a camera takes a tour around a house, for training the VAE model with a 4 dimensional latent space. After the model is trained, each real frame has a corresponding representation point on manifold in the latent space, and each representation point has corresponding reconstructed image. For the navigation problem, we map the starting image and destination image to the latent space, then optimize a path on the learned manifold connecting the two points, and finally map the path back through decoder to a sequence of images. The ideal sequence of images should correspond to a route that is spatially continuous - i.e. neighbor images in the route should correspond to neighbor locations in physical space. Such a route could be used for navigation with computer vision techniques, i.e. a robot could follow the image sequence from starting location to destination in the environment step by step. We implement this algorithm, but find in our experimental results that the resulting route is not satisfactory. The route consist of several discontinuous image frames along the ideal routes, so that the route could not be followed by a robot with computer vision techniques in practice. In our evaluation, we propose two reasons for our failure to automatically find continuous routes: (1) The VAE tends to capture global structures, but discard the details; (2) the Euclidean similarity metric used for measuring continuity between house images is sub-optimal. For further work, we propose: trying other generative models like VAE-GANs which may be better at reconstructing the details to learn the representation map, and adjusting the similarity metric in the path selecting algorithm.
State estimation of autonomous rotorcraft MAVs under indoor environments

This paper realizes a state estimation system for an autonomous rotorcraft micro aerial vehicle (MAV) under an indoor environment. Our system only relies on one monocular camera as a visual sensor, in addition to two controller sensors, barometer and inertial measurement unit (IMU). The barometer and IMU data are fused with image data so as to address the scale problem in monocular odometry. We implement state estimation algorithms on a DJI Matrice 100 MAV platform which is equipped with an Intel NUC computer plus an i5-6260U processor. Experimental results under an indoor environment show that the state estimation system has maximally 0.05m position bias and 0.1m loop deviation, which is suitable for many indoor applications such as search-and-rescue and disaster management.
Measurement of tissue stiffness using soft eGa-in sensors and pressure application

Modern prosthetic devices continue to improve their comfort, utility, and functionality with the advent of better manufacturing methods and understandings of human biomechanics. An essential aspect of any prosthetic is the custom fit needed to interface with the residual limb of an individual. Traditionally, these custom fit devices require professional revision and fitted interfaces created from materials that complement the geometry and composition of the residual limb. Soft, elastomeric sensors have the potential to measure tissue stiffness and create 4D models to produce these custom fit prosthetics without the need for traditional methods. For this study, soft sensors comprised of cast silicone (Ecoflex-0030) and liquid eutectic Gallium-Indium were designed to measure tissue stiffness at numerous locations on the body. Using 3D printed molds, two halves of each sensor were joined and liquid metal was injected between to create a highly elastic pressure-sensitive sensor. We demonstrated that a map of tissue stiffness can be generated when several of these sensors are deployed in an array and correlated to known positions on the body. This map can then be overlaid on a 3D scan to create a model for multi-material 3D printing. This approach could be used to generate custom, unique 3D printed prosthetic interfaces. If developed further and deployed in a full array, a diagnostic pressure cuff could be a versatile tool to any prosthetist or researcher studying tissue composition.
Efficacy of erbium-doped yttrium aluminum garnet laser with casein phosphopeptide amorphous calcium phosphate with and without fluoride for remineralization of white spot lesions around orthodontic brackets

ABSTRACT Objective: This study aimed to assess the efficacy of erbium-doped yttrium aluminum garnet (Er:YAG) laser, pastes containing casein phosphopeptide amorphous calcium phosphate (CPP-ACP) with and without fluoride and their combination for prevention of white spot lesions in the enamel. Materials and Methods: This in vitro experimental study was conducted on 90 extracted sound premolars. The teeth were then randomly divided into six groups of 15: (1) Control, (2) laser, (3) CPP-ACP with fluoride (GC MI Paste, RecaldentTM 900 ppm as NaF), (4) CPP-ACP without fluoride (GC Tooth Mousse RecaldentTM), (5) laser + CPP-ACP with fluoride, and (6) laser + CPP-ACP without fluoride. In each group, enamel surface was exposed to the remineralizing agent. The teeth were then subjected to pH cycling for 14 days. The teeth were then sectioned, polished, and underwent cross-sectional microhardness testing at 20–160 μ depth quantitatively. Using the Simpson's rule, the amount of mineral loss was calculated in each group. Statistical Analysis Used: ANOVA was used for the comparisons, and Tukey's test was applied for pairwise comparisons. Results: The highest mean volume percentage of microhardness at 20–60 μ depth belonged to the group laser + CPP-ACP with fluoride and the lowest belonged to the control group (P = 0.001). The differences were not significant at 80-120 μ depth (P > 0.05). These finding are confirmed according to △Z (mineral loss). Conclusion: Based on these results, Er: YAG laser was able to decrease demineralization and was a potential alternative to preventive dentistry and was more effective when combined with CPP-ACP products.
Evidence-Based Causal Chains for Linking Health, Development, and Conservation Actions

Abstract Sustainability challenges for nature and people are complex and interconnected, such that effective solutions require approaches and a common theory of change that bridge disparate disciplines and sectors. Causal chains offer promising approaches to achieving an integrated understanding of how actions affect ecosystems, the goods and services they provide, and ultimately, human well-being. Although causal chains and their variants are common tools across disciplines, their use remains highly inconsistent, limiting their ability to support and create a shared evidence base for joint actions. In this article, we present the foundational concepts and guidance of causal chains linking disciplines and sectors that do not often intersect to elucidate the effects of actions on ecosystems and society. We further discuss considerations for establishing and implementing causal chains, including nonlinearity, trade-offs and synergies, heterogeneity, scale, and confounding factors. Finally, we highlight the science, practice, and policy implications of causal chains to address real-world linked human–nature challenges.
Model-Free Trajectory Tracking Control of Two-Particle Magnetic Microrobot

We report a novel model-free trajectory tracking control scheme for two-particle magnetic microrobot (TPMM), which is capable of performing two-dimensional locomotion on a surface in fluid. In the control scheme, the dynamic model of the microrobot and external disturbances are lumped together and treated as the generalized disturbance, which eliminates the complex dynamics modeling of the microrobot due to the hydrodynamics and boundary effect. By employing an extended state observer, the motion states of the microrobot (i.e., position and velocity) are estimated, and the generalized disturbance is compensated. Then, a linear trajectory tracking controller is designed by utilizing the estimated motion states. Furthermore, a visual servoing control system is implemented and extensive real-time trajectory tracking experiments are conducted. The experimental results show the effectiveness of the proposed control scheme for realizing high-precision trajectory tracking for TPMM samples with different body-lengths and surrounding fluids.
Reliability and scalability improvements to identity federations by managing SAML metadata with distributed ledger technology

In identity federations, users assigned to identity providers (IDPs) can access applications operated by service providers (SPs) without SP-specific credentials for authentication and authorization. While OpenID Connect and SAML are the two most widely adopted federation standards, using them inherently results in a trade-off between data quality guarantees and scalability, given how they handle the Metadata about the involved IDPs and SPs. This paper presents a novel approach for federation membership and federation Metadata management based on Distributed Ledger Technology. It applies the core idea of Certificate Transparency, as known from Global-PKI certificate authorities for X.509v3 server certificates, to SAML federation Metadata; therefore, it achieves OpenID Connect's federation building flexibility without losing the significant advantages of traditional SAML federations. An implementation based on Hyperledger Fabric is used to evaluate typical use cases by measuring impacts on Metadata distribution latency and Metadata size, and to discuss the feasibility of the presented approach.
High prevalence of bronchiectasis in emphysema-predominant COPD patients

Background COPD has been identified as an etiology or related disease of bronchiectasis, and bronchiectasis has been classified as a comorbidity of COPD. In this study, we investigated the prevalence of bronchiectasis in different phenotypes of COPD subjects and the correlation between bronchiectasis and different phenotypes, especially emphysema. Methods COPD patients were recruited from April 2012 to December 2015. The presence of bronchiectasis and related information were statistically analyzed. COPD subjects were separated into subgroups in two ways: COPD with and without bronchiectasis groups and emphysema-predominant (emphysema index, EI≥9.9%) and non-emphysema-predominant (EI<9.9%) groups. Results In total, 1,739 COPD patients were incorporated into the study, among which 140 cases (8.1%) were accompanied with radiological bronchiectasis. COPD patients with concomitant bronchiectasis presented worse pulmonary function (FEV1% predicted, P<0.001), higher EI (15.0% vs 13.4%, P<0.001), and higher proportion of pulmonary hypertension and cor pulmonale (6.4% vs 2.4%, P=0.005 and 23.6% vs 16.1%, P=0.022) than patients without bronchiectasis. Of all the COPD patients, 787 with EI data were divided into emphysema-predominant (n=369) and non-emphysema-predominant groups (n=418). The proportion of bronchiectasis was 16.5% and 10.3% (P=0.01), respectively. Severity of bronchiectasis increased as the degree of airflow limitation (r=−0.371, P<0.001) and emphysema increased (r=0.226, P=0.021). After adjusting confounding factors, FEV1% predicted (OR, 1.636; 95% CI, 1.219–2.197; P=0.001) and EI (OR, 1.993; 95% CI, 1.199–3.313; P=0.008) were significantly related with the presence of bronchiectasis in COPD patients. Conclusion The proportion of bronchiectasis is higher in emphysema-predominant COPD subjects. Emphysema measured by EI and FEV1% predicted are independent predictors for bronchiectasis in COPD subjects, while the underlying mechanism deserves further investigation.
Comparative Genomics of Escherichia coli Sequence Type 219 Clones From the Same Patient: Evolution of the IncI1 blaCMY-Carrying Plasmid in Vivo

This study investigates the evolution of an Escherichia coli sequence type 219 clone in a patient with recurrent urinary tract infection, comparing isolate EC974 obtained prior to antibiotic treatment and isolate EC1515 recovered after exposure to several β-lactam antibiotics (ceftriaxone, cefixime, and imipenem). EC974 had a smooth colony morphology, while EC1515 had a rough colony morphology on sheep blood agar. RAPD-PCR analysis suggested that both isolates belonged to the same clone. Antimicrobial susceptibility tests showed that EC1515 was more resistant to piperacillin/tazobactam, cefepime, cefpirome, and ertapenem than EC974. Comparative genomic analysis was used to investigate the genetic changes of EC974 and EC1515 within the host, and showed three plasmids with replicons IncI1, P0111, and IncFII in both isolates. P0111-type plasmids pEC974-2 and pEC1515-2, contained the antibiotic resistance genes aadA2, tetA, and drfA12. IncFII-type plasmids pEC974-3 and pEC1515-3 contained the antibiotic resistance genes blaTEM−1, aadA1, aadA22, sul3, and inuF. Interestingly, blaCMY−111 and blaCMY−4 were found in very similar IncI1 plasmids that also contained aadA22 and aac(3)-IId, from isolates EC974 (pEC974-1) and EC1515 (pEC1515-1), respectively. The results showed in vivo amino acid substitutions converting blaCMY−111 to blaCMY−4 (R221W and A238V substitutions). Conjugation experiments showed a high frequency of IncI1 and IncFII plasmid co-transference. Transconjugants and DH5α cells harboring blaCMY-4 or blaCMY-111 showed higher levels of resistance to ampicillin, amoxicillin, cefazolin, cefuroxime, cefotaxime, cefixime, and ceftazidime, but not piperacillin/tazobactam, cefpime, or ertapenem. All known genes (outer membrane proteins and extended-spectrum AmpC β-lactamases) involved in ETP resistance in E. coli were identical between EC974 and EC1515. This is the first study to identify the evolution of an IncI1 plasmid within the host, and to characterize blaCMY−111 in E. coli.
A hybrid energy harvesting framework for energy efficiency in wireless sensor networks based smart grid applications

In smart grid applications, Wireless Sensor Net-works (WSNs) which consist of battery limited sensor nodes are used on critical equipments of power distribution grids for monitoring purposes. WSN nodes have tight energy constraints hence it is important to reduce the energy consumption of sensor nodes due to harsh propagation characteristics of smart grid environment. One possible way to reduce the energy consumption is to utilize transmission power control where transmission powers are adjusted according to channel conditions. Another technique is to employ energy harvesting schemes to provide additional power for nodes by using environmental energy sources. Solar and electromagnetic energies are two possible environmental energy sources in outdoor substation environments. Solar energy can be efficiently exploited in a sunny day. On the other hand, electromagnetic energy can be used at any time. In this work, we propose a hybrid energy harvesting model that exploits both solar and electromagnetic energies and develop a Mixed Integer Programming (MIP) method to minimize the energy dissipation of sensor nodes. By using the MIP framework, we quantify the impact of the proposed hybrid energy harvesting model as well as transmission power control on the energy saving of nodes.
Influence of ESPAR antenna radiation patterns shape on PPCC-based DoA estimation accuracy

In the article, we show the influence of three different electronically steerable parasitic array radiator (ESPAR) antenna radiation patterns on the overall direction of arrival (DoA) estimation accuracy when power-pattern cross-correlation (PPCC) algorithm, relying on received signal strength (RSS) values, is used for the estimation. The ESPAR antenna designs were obtained for three optimization goals, which resulted in different radiation patterns. To check the applicability of every ESPAR antenna to wireless sensor network (WSN) applications, we have verified their achievable DoA estimation accuracy in numerical tests. The results indicate, that it is possible to provide an ESPAR antenna design for WSN applications, which have narrow radiation pattern and also provide acceptable DoA estimation accuracy.
Genetic Analysis with Random Amplified Polymorphic DNA of the Multiple Enterocin-Producing Enterococcus lactis 4CP3 Strain and Its Efficient Role in the Growth of Listeria monocytogenes in Raw Beef Meat

In this manuscript, a multiple enterocin-producing Enterococcus lactis strain named 4CP3 was used to control the proliferation of Listeria monocytogenes in refrigerated raw beef meat model. Also, the intraspecific genetic differentiation of 4CP3 strain was assessed by Random Amplified Polymorphic DNA Polymerase Chain Reaction (RAPD-PCR) analysis. E. lactis 4CP3 strain was found to produce the enterocins A, B, and P. It displayed activity against L. monocytogenes EGDe 107776 by agar-well diffusion method. The application of E. lactis 4CP3 culture at 107 CFU/g in raw beef meat was evaluated using both ANOVA and ANCOVA linear models in order to examine its effect on the growth of the pathogen L. monocytogenes during refrigerated storage. Hence, a very interesting result in decreasing (P<0.05) and suppressing the growth of L. monocytogenes in refrigerated raw beef meat was shown during 28 days of storage. In conclusion, E. lactis 4CP3 strain might be useful for prevention of the proliferation and survival of L. monocytogenes in raw meat during refrigerated storage.
Teaching-learning-based optimization algorithm for hybrid flow shop scheduling problem with assembly operations

This paper addresses assembly-type hybrid flow shop scheduling problem (AHFSP) with the minimization of total tardiness and makespan. The products have parts which are first processed in hybrid flow shop and then are assembled at the assembly stage. To solve this problem, a part-based solution representation is adopted and a teachers' teaching-learning-based optimization (TTLBO) is proposed. Teachers chosen from a non-dominated set undergo a self-learning phase and a teaching phase and these phases are implemented by multiple neighborhood search and global search, respectively. More- over, the learning phase of learners is removed and the learning of teachers is intensified to avoid the low-efficiency computation. Extensive experiments are conducted to test the performance of TTLBO. The computational results demonstrate that TTLBO is an effective and competitive method for multi- objective AHFSP.
Control of repetition frequency of a femtosecond laser by an external cavity working as the length sensor

New lasers, special digital signal processing electronics, algorithms and new materials for optics enabled development of new absolute distance measurement methods. The phenomenon of the mode-lock of the femtosecond pulse laser increased a number of potential applications with distance surveying where a stable generator of very short and periodically repeated coherent pulses can be used. The aim of the work is a presentation of our unique control algorithm for measuring the length of unknown distance with direct traceability to a time standard. The principle is based on a passive optical cavity with mirrors keeping distance to be measured. Time spacing of short femtosecond pulses generated by femtosecond laser is optically phase locked to the cavity free spectral range. A value of the repetition frequency of the laser determines the measured distance in that case.