Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Nanophotonics: Silicon-Organic Hybrid Technology

Integrated photonic devices have gained increasing research interests. Especially silicon photonics have become very attractive for various optical applications. Using silicon-on-insulator as a material platform provides the ability to fabricate photonic devices with electronic devices on a single chip. Driven by substantial research investments, the integration of photonic devices on silicon-on-insulator substrates has reached a degree of maturity that already permits industrial adoption. However, silicon has the disadvantage of linear electro-optical effects, and, therefore, advanced modulation formats are difficult to realize when using silicon-based high-speed modulators. Hence, a new approach was proposed: the silicon-organic hybrid technology. This technology is a viable extension of the silicon-on-insulator material system for efficient high-speed modulation. We herewith present our theoretical and experimental investigations of the silicon-organic hybrid slot-waveguide ring resonator. The advanced device design is described in detail, which allows using both, the efficient silicon-on-insulator strip-waveguides and the silicon-organic hybrid slot-waveguides in single ring resonator. For the first time, we report the transmission spectra of such a resonator covered with an electro-optical polymer.
Getting Published and Having an Impact: Turning Rehabilitation Research Results Into Gold

In the rehabilitation research world in which “knowledge translation” and “evidence-based practice” have become ascendant (at least as catch phrases), researchers are asked to take on the challenge—in addition to methodological excellence—of ensuring that their work has an impact beyond its appearance in a peer-reviewed journal. Today’s researchers have many techniques at hand that will help them succeed in that quest, unlike the medieval alchemists whose challenge it was to turn base metals into gold (none of whom succeeded to our best knowledge). The “gold” that research results should lead to is a change in practice by a target audience—more importantly, a change that leads to improved lives of people with disabilities.
Interfacial electrohydrodynamic solitary waves under horizontal electric fields

Abstract Interfacial waves between two superimposed dielectric fluid layers under a horizontal electric field are investigated from asymptotic and numerical aspects. The fluid is taken to be inviscid, incompressible and non-conducting in each layer. The competing forces resulting from gravity, surface tension and electric field are all considered. A systematic procedure is proposed to derive model equations of multiple scales in various possible limits from the electrified Euler equations in the framework of the Zakharov–Craig–Sulem formulation. Based on thorough analyses of the Dirichlet–Neumann operators in the long-wave approximation, classic weakly nonlinear models – including the Boussinesq-type system, the Korteweg–de Vries (KdV) equation and its variants, and the Benjamin-type equation – are obtained under different scaling assumptions. In addition, strongly nonlinear models (without the smallness assumption on the wave amplitude) in the Benjamin and Barannyk–Papageorgiou–Petropoulos regimes are derived. In these models, the electric effects are shown to produce dispersive regularisations of long and short waves. A modified boundary integral equation method is developed to compute solitary waves in the original electrified Euler equations. Through comparisons with solitary-wave solutions in the Euler equations, it is found that in various asymptotic regimes, weakly nonlinear models are in overall good agreement when wave amplitudes are small. In contrast, the range of validity of the strongly nonlinear model is much broader. It is shown that the horizontal electric field plays a significant role in the physical system: it expands the range of parameters for the existence of progressive waves, changes the qualitative characteristics of solitary waves and leads to a new type of solitary wave, namely the KdV–wavepacket mixed type.
Delivery of a trauma-focused CBT group for heterogeneous single-incident traumas in adult primary care: a follow-on case study

Abstract Group therapy for adult post-traumatic stress disorder (PTSD) has been a subject of debate over the past few years. A recent update on five international clinical practice guidelines on the use of group-therapy for PTSD in adults ranged from moderate support (e.g. the International Society for Traumatic Stress Studies) to no recommendation (e.g. the National Institute for Health and Care Excellence, NICE). However, a unanimous recommendation was that practitioners collaborated with their clients and weighed up the guidelines and client preferences to make the appropriate decisions. The current case study was guided by these recommendations. A minority of clients presenting to the service expressed a preference for group therapy for their PTSD symptoms. The current study follows on from a previous shared-trauma therapy group. It illustrates how the service took the NICE guidelines fully into account alongside the clients’ needs and preferences to deliver a NICE-compliant heterogenous trauma-focused CBT group. Twenty-four clients presenting with PTSD from different single-incident traumas opted for group therapy. Clients attended one of three 8-session trauma-focused CBT groups depending on preference (e.g. date/time, location). The groups were conducted face-to-face on a weekly basis. Seventeen clients completed treatment. Eleven clients no longer showed clinically important symptoms of PTSD as assessed on the PCL-5 and interview. This was sustained at 3-month follow-up. Four other clients showed reliable change. Two clients showed minimal improvement. This study is discussed with reference to opportunities, challenges and recommendations for clinical practice and research. Key learning aims It is hoped that the reader of this case study will increase their understanding of the following: (1) Delivery of a trauma-focused CBT group for heterogeneous single-incident traumas. (2) Taking full consideration of the NICE guidelines alongside the clients’ needs and preferences. (3) Guiding the focus of therapy on processing the trauma memory and its aftermath. (4) Effective use of group processes to facilitate outcomes.
Modeling of Spring-Mass-Damper Piezoelectric Equivalent Circuit for Multi-cantilever in Harvesting wide-band vibration sources

Spring-mass-damper system is popular to be used as an analytical model for a cantilever based energy harvesting system for its simplicity in delivering a closed form solution. In this paper, a simple model of two piezoelectric energy harvesters is being developed to investigate the performance of a more generic multi-cantilever system. The electrical domain of both of the piezoelectric energy harvesters are modeled separately as an individual transformer. Spring-mass-damper model is used to model the mechanical domain of the piezoelectric cantilever under external mechanical excitation analogous to its equivalent electrical circuit consisting of resistor, inductor and capacitor. The analytical model of the mutli-cantilever is being validated with experiment results.
Scoping reviews and rapid reviews

ABSTRACT Scoping reviews and rapid reviews are intentional approaches to systematically synthesize research. In sport and exercise psychology, scoping reviews can summarize information to describe what is known on a relevant topic. Rapid reviews offer accelerated knowledge synthesis through a streamlined timely and cost-effective approach that is directed and guided by stakeholders. Both scoping and rapid reviews are used to synthesize the literature, and also to describe and assess conceptual, theoretical, and methodological trends, identify gaps in research and practice, and inform future sport and exercise psychology research and practice directions. We offer evidence-based and field-specific guidelines to conduct scoping reviews and rapid reviews. These types of syntheses in sport and exercise psychology are important for advancing research and practice and highlight the value of collaborations with key stakeholders. Our guidelines will help with the uniformity and dependability of scoping and rapid reviews while also advancing the impact and value of this type of research.
The fermented soy whey produced by a combined lactic acid bacteria starter shows improved flavor and the function in alleviating dextran sulphate sodium induced colitis in mice

ABSTRACT In this study, Lactiplantibacillus plantarum BC299, Lactobacillus delbrueckii subsp. bulgaricus 717 and Streptococcus thermophilus 176 were used as combined starter cultures to produce a fermented soy whey beverage. The results showed that the fermentation of the combined starter cultures increased the content of lactic acid, acetic acid, succinic acid, and malic acid, while decreased the content of citric acid, fumaric acid and propionic acid. Meanwhile, the fermentation also effectively changed the proportion of volatile flavor substances. The higher sensory score of the fermented soy whey also confirmed the flavor improvement effect of the combined starter cultures. In addition, the in vivo results of animal experiments showed that the fermented soy whey could significantly improve the disease activity index (DAI) and colon morphology in dextran sulfate sodium (DSS) induced colitis mice. This study showed that the combined lactic acid bacteria starter cultures had important value-added relevance on the effective reuse of the soy whey by-product.
Visual Affordance and Function Understanding

Nowadays, robots are dominating the manufacturing, entertainment, and healthcare industries. Robot vision aims to equip robots with the capabilities to discover information, understand it, and interact with the environment, which require an agent to effectively understand object affordances and functions in complex visual domains. In this literature survey, first, “visual affordances” are focused on and current state-of-the-art approaches for solving relevant problems as well as open problems and research gaps are summarized. Then, sub-problems, such as affordance detection, categorization, segmentation, and high-level affordance reasoning, are specifically discussed. Furthermore, functional scene understanding and its prevalent descriptors used in the literature are covered. This survey also provides the necessary background to the problem, sheds light on its significance, and highlights the existing challenges for affordance and functionality learning.
Monte Carlo Dose Calculation – A QA Method for SRT and SBRT Plans in Treating Multiple and Small Metastatic Lesions

To provide accurate and fast 3-D dose verification for hypofractionated stereotactic radiotherapy (SRT/SBRT) of small and multi targets calculated with a Varian Eclipse treatment planning system (TPS) delivered on a Varian accelerator. Ten brain and lung hypofractionated SRT/SBRT linac-based and CyberKnife plans were generated by the Eclipse system for delivery on the accelerator with the Millenium-120 leaf multileaf collimator (MLC) and Multiplan for the CyberKnife machine. These clinical SRT/SBRT plans required accurate quality assurance measurements to obtain absolute point dose and 3-D dose distributions due to the low number of fractions and high fraction doses. For small-field and multi-target plans, the EGS4/MCSIM code was used to calculate the dose distribution. A 0.125 cc ion chamber, a 0.016 cc pin-point chamber and Kodak EDR2 film were used for the measurements and the results were compared with Monte Carlo (MC) calculations. The dosimetry for small-field and multi-target treatment plans is challenging due to the comparable range of secondary electrons and the field sizes defined by SRT/SBRT MLC segments. Our MC simulations can accurately reproduce the linac dose distributions (within 1%/1 mm) three dimensionally. For the clinical SRT/SBRT plans investigated in this work, the MC doses agreed within 3% with ion chamber measurements and within 2%/2 mm with film measurements. The doses calculated by the Eclipse AAA algorithm and Multiplan differed by no more than 5% from MC calculations for small (4–40 cc) Planning Target Volumes (PTVs). MC dose calculation provides accurate and fast 3-D dose verification for hypofractionated SRT for small and multi-target treatment plans generated by a Varian Eclipse TPS on a Varian accelerator and Multiplan treatment planning on the CyberKnife System.
Classifying COVID-19 and Viral Pneumonia Lung Infections through Deep Convolutional Neural Network Model using Chest X-Ray Images

Context: Automated detection of COVID-19 in real time can greatly help clinicians to handle increasing number of cases for preliminary screening. Deep CNN models trained with sufficiently large datasets may become best candidates to meet the purpose. Aims: This study aims for automated detection and classification of COVID-19 and viral pneumonia diseases by applying deep CNN model using chest X-ray images. The proposed model performs multiclass classification to meet the purpose. Settings and Design: The proposed model is built on top of VGG16 architecture with pretrained ImageNet weights. The model was fine-tuned using additional custom layers to deliver better performance specific to the target. Subjects and Methods: A total of 15,153 samples are used in this work. These samples include chest X-ray images of COVID-19, viral pneumonia, and normal cases. The entire dataset was split into train and test sets, with a ratio of 80:20 before training the model. To enhance important image features, image preprocessing and augmentation were applied before feeding the image batches to the model. Statistical Analysis Used: Performance of the model is evaluated through accuracy, precision, recall, and F1 score performance metrics. The results produced by the model are also compared with other recent leading studies. Results: The proposed model has achieved a classification accuracy of 98% with 98% precision, 96% recall, and 97% F1 score on the test dataset for multiclass classification. The area under receiver operating characteristic curve score was 0.99 for all three cases of multiclass classification. Conclusions: The proposed classification model may be highly useful for the preliminary diagnosis of COVID-19 and viral pneumonia cases, especially during heavy workloads and large quantities.
Stress Prediction of the Particle Structure of All-Solid-State Batteries by Numerical Simulation and Machine Learning

All-Solid-state batteries (ASSBs) are non-flammable and safe and have high capacities. Thus, ASSBs are expected to be commercialized soon for use in electric vehicles. However, because the electrode active material (AM) and solid electrolyte (SE) of ASSBs are both solid particles, the contact between the particles strongly affects the battery characteristics, yet the correlation between the electrode structure and the stress at the contact surface between the solids remains unknown. Therefore, we used the results of numerical simulations as a dataset to build a machine learning model to predict the battery performance of ASSBs. Specifically, the discrete element method (DEM) was used for the numerical simulations. In these simulations, AM and SE particles were used to fill a model of the electrode, and force was applied from one direction. Thus, the stress between the particles was calculated with respect to time. Using the simulations, we obtained a sufficient data set to build a machine learning model to predict the distribution of interparticle stress, which is difficult to measure experimentally. Promisingly, the stress distribution predicted by the constructed machine learning model showed good agreement with the stress distribution calculated by DEM.
The Effect of Hydro-Morphology and Habitat Alterations on the Functional Diversity and Composition of Macrophyte Communities in the Large River

Macrophyte communities have major role in the functioning of freshwater ecosystems. However, there is gap in knowledge about how natural and anthropogenic hydro-morphological disturbances affect their functional diversity and trait structure, particularly in the temperate large rivers. In this study we investigated the effect of hydro-morphology on functional diversity and trait structure of macrophyte communities in the middle section of the Danube course. We collected macrophyte and environmental data from 947 sampling units in the main river channel and connected side waterbodies. We extracted data on 18 traits with 65 trait states and calculated seven functional diversity metrics and cumulative weighted means of trait states (CWMs). We applied redundancy analysis (RDA) to investigate the response of functional diversity metrics to the environmental variables, and Variation Partitioning to determine whether natural, or anthropogenic subset of hydro-morphological factors is more important predictor of functional diversity. To relate CWMs and environmental variables, we performed RLQ and fourth-corner analysis, followed by false discovery rate procedure. Hydro-morphological variables explained 36.7% of the variability in the functional diversity metrics. Combined effect of two subsets of environmental variables explained largest part of the variability in functional diversity metrics. Six associations between traits and environmental variables were found. We found that functional diversity metrics indicate prevailing ecological processes, from environmental to biotic filtering, along the natural—anthropogenic hydro-morphological gradient. We concluded that functional diversity metrics are potentially useful tools in the identification of the causes of ecological degradation, and could be applied in river bioassessments and management.
An Analysis on the Factors for Cervical Insufficiency Causing Adverse Emotions Among Pregnant Women at Different Gestation Phases

Background To analyze the anxiety, depression, and related factors among pregnant women with cervical insufficiency, so as to provide a reference for clinical psychological intervention as an adjuvant therapy. Methods A total of 101 cases in China with cervical insufficiency were included in the observation group by a convenience sampling method, and 114 normal healthy women of childbearing age were selected as the control group. Participants were investigated and observed for anxiety and depression by SAS and SDS, respectively, to analyze the emotional state and influencing factors of the patients with cervical insufficiency. Stratified by the first, second and third trimesters, our study used whether depressive or not and whether anxiety or not as the dichotomous variables. A multivariate Logistic regression was adopted to analyze the influencing factors. Relevant influencing factors were screened out by the forward stepwise method in combination with professional knowledge and the number of variables. Results There were statistical significant differences in SAS and SDS between observation group and control group and the incidence rate of anxiety and depression was higher in pregnant women with CI. Multivariate Logistic regression demonstrated that history of abnormal pregnancy was the main influencing factor for anxiety and depression in the early and middle gestation phases, and cervical insufficiency was the factor influencing the anxiety in early gestation and both anxiety and depression in the late gestation phase. Conclusion Cervical insufficiency may have a negative impact on the emotions of pregnant women. Individualized and targeted mental care should be added into clinic work to prevent negative outcomes.
Transition From Diencephalic Syndrome to Hypothalamic Obesity in Children With Suprasellar Low Grade Glioma: A Case Series

Background Children with suprasellar low grade glioma (LGG) frequently develop problems to maintain their body weight within the normal range, due to hypothalamic dysfunction. Hypothalamic damage may result in the diencephalic syndrome (DS), characterized by underweight or failure to thrive, but also in hypothalamic obesity (HO). Children with LGG presenting with DS at young age often develop HO later in life. The underlying pathophysiology for this change in body mass index (BMI) is not understood. Previous hypotheses have focused on the tumor or its treatment as the underlying cause. To better understand its etiology, we aimed to relate changes in BMI over time in children with suprasellar LGG presenting with DS to age, tumor progression, treatment, and endocrine function. We hypothesize that the development of HO in children with LGG presenting with DS is related to maturation status of the hypothalamus at time of injury and thus age. Methods In this retrospective case series, all cases diagnosed in the Netherlands with suprasellar located LGG, currently treated or followed, with a history of DS developing into HO were included. Results In total, 10 children were included. Median age at LGG diagnosis was 1.5 years (range 0.4–5.5), median BMI SDS was −2.64. The children developed overweight at a median age of 4.5 years (2.2–9.8). The median total difference in BMI SDS between underweight and obesity was +5.75 SDS (4.5–8.7). No association could be found between transition of DS to HO and onset of a pituitary disorder (present in 70.0%), surgery, chemotherapy, or tumor behavior. Two had developed central precocious puberty (CPP), both while having underweight or normal weight. Conclusion The shift from DS to HO in children with hypothalamic LGG may be associated with age and not to tumor behavior, treatment characteristics or pituitary function. The development of CPP in these children seems not to be related to obesity. Our findings may indicate that the clinical picture of hypothalamic dysfunction reflects the maturation state of the hypothalamus at time of lesioning. Future prospective studies are needed to better understand underlying causative mechanisms of the morbid changes in body weight.
The Expansion of a Single Bacteriophage Leads to Bacterial Disturbance in Gut and Reduction of Larval Growth in Musca domestica

The housefly larvae gut microbiota influences larval health and has become an important model to study the ecology and evolution of microbiota–host interactions. However, little is known about the phage community associated with the housefly larval gut, although bacteriophages are the most abundant members of the microbiota and have the potential to shape gut bacterial communities. Changes to bacteriophage composition are associated with disease, but how phages impact insect health remains unclear. We noticed that treating 1-day-old housefly larvae with ~107, ~109, and ~1011 phage particles per ml of bacteriophages led to changes in the growth and development of housefly larvae. Additionally, treating housefly larvae with bacteriophages led to bacterial composition changes in the gut. Changes in the compositions of these gut bacteria are mainly manifested in the increase in harmful bacteria, including Pseudomonas and Providencia and the decrease in beneficial bacteria, including Enterobacter and Klebsiella, after different growth and development periods. The alterations in gut microbiota further influenced the larval growth and development. Collectively, these results indicate that bacteriophages can perturb the intestinal microbiome and impact insect health.