Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Different Modalities of an Acute Energy Deficit on Sleep and Next Morning Appetitive and Compensatory Behavior in Healthy Young Adults: The EDIES Protocol

Sleep is bi-directionally linked to energy balance. This crossover study design will evaluate the acute effect of a moderate energy deficit (500 kcal) induced by diet, exercise, or mixed (−250 kcal by diet and 250 kcal by exercise) on sleep and the next morning’s appetitive responses. The study sample comprises 24 healthy young adults. The experimental measurements will be conducted in a naturalistic, momentary manner and partly assessed by the participants. The participants will undergo a run-in period in order to stabilize their sleep schedules and provide them with training on the study protocol and measurements. Indirect calorimetry will be used to determine their resting metabolic rate and peak oxygen consumption (VO2 peak). Then, they will take part in a control session (CTL), followed by three energy deficit sessions in random order: a diet-induced energy deficit session (DED), an exercise-induced energy deficit session (EED), and a mixed energy deficit session (MED). All experimental sessions will be separated by a one-week washout. The participants’ sleep will be monitored by ambulatory polysomnography, and the next morning’s appetitive response will be evaluated via ad libitum food intake, appetite sensations, and food reward, measured by a food liking and wanting computerized test.
SPIN DYNAMICS SIMULATIONS OF COLLECTIVE EXCITATIONS IN MAGNETIC LIQUIDS

A novel approach is developed for computer simulation studies of dynamical properties of spin liquids. It is based on the Liouville operator formalism of Hamiltonian dynamics in conjunction with Suzuki-Trotter-like decompositions of exponential propagators. As a result, a whole set of symplectic time-reversible algorithms has been introduced for numerical integration of the equations of motion at the presence of both translational and spin degrees of freedom. It is shown that these algorithms can be used in actual simulations with much larger time steps than those inherent in standard predictor-corrector schemes. This has allowed one to perform direct quantitative measurements for spin-spin, spin-density and density-density dynamical structure factors of a Heisenberg ferrofluid model for the first time. It was established that like pure liquids the density spectrum can be expressed in terms of heat and sound modes, whereas like spin lattices in the ferromagnetic phase there exists one primary spin in the shape of spinspin dynamic structure factors describing the longitudinal and transverse spin fluctuations. As it was predicted in our previous paper [Mryglod I. , Folk R. et al., Physica A277 (2000) 389] we found also that a secondary wave peak appears additionally in the longitudinal spin-spin dynamic structure factor. The frequency position of this peak coincides entirely with that for a sound mode reflecting the effect of the liquid subsystem on spin dynamics. The possibility of longitudinal spin wave propagation in magnetic liquids at sound frequency can be considered as a new effect which has yet to be tested experimentally.
The main abdominoplasty techniques used in post-bariatric patients after massive
 weight loss: systematic review

Introduction: Obesity is defined by a body mass index (BMI) ≥30 kg/m2, and today approximately 2.1 billion adults are obese. With this high number of obese people, the demand for treatment via bariatric surgery has been increasing to reduce weight, resolve comorbidities and improve quality of life. However, intense weight loss can cause adverse physical, aesthetic, and psychological effects. Plastic surgery becomes essential to resolve these adverse effects. According to the International Society of Plastic Surgery, 112,116 abdominoplasties were performed in 2020, representing 8.6% of all plastic surgeries performed in Brazil. The objective is to present the main abdominoplasty techniques in post-bariatric patients. Method: Studies that met the previously defined inclusion criteria were included. Results: A total of 28 references were included in this systematic review. Discussion: Most seek abdominoplasty due to the excess skin remaining in various body regions and the impact on post-bariatric patients’ quality of life and mental health. The surgical techniques addressed are classic abdominoplasty; fleur-de-lis or anchor; circumferences; and Scarpa’s fascia. The total number of complications was 42%; the main ones observed were scarring, skin dehiscence, infection, and necrosis; the three added up to 32%. Conclusion: The improvement in the quality of life of patients undergoing abdominoplasty is evident, but further research is needed to relate abdominoplasty techniques to these patients with postoperative complications.
A New Construction Method of Neighbor Graph for Locality Preserving Projections

In this paper, a new construction method of neighbor graph is proposed for Locality Preserving Projections (LPP). LPP is a typical method of graph-based dimensionality reduction, and has been successfully applied in many practical problems such as face recognition. However, LPP mainly depends on its essential neighbor graph whose construction suffers from the following issues: the data set is vectorized to compute the k-nearest neighbor graph (adjacency graph), which leads to the lost of the correlative columns information. So, we propose a new neighbor graph construction method which can well show the spatial structure information of the original image matrices, to preserve the corresponding columns information. In order to test and evaluate our method’s performance, a series of experiments were performed on the well-known face databases: ORL and Yale face databases. The experimental results show that our method achieves better performance than LPP.
5HT1AR-FGFR1 Heteroreceptor Complexes Differently Modulate GIRK Currents in the Dorsal Hippocampus and the Dorsal Raphe Serotonin Nucleus of Control Rats and of a Genetic Rat Model of Depression

The midbrain raphe serotonin (5HT) neurons provide the main ascending serotonergic projection to the forebrain, including hippocampus, which has a role in the pathophysiology of depressive disorder. Serotonin 5HT1A receptor (R) activation at the soma-dendritic level of serotonergic raphe neurons and glutamatergic hippocampal pyramidal neurons leads to a decrease in neuronal firing by activation of G protein-coupled inwardly-rectifying potassium (GIRK) channels. In this raphe-hippocampal serotonin neuron system, the existence of 5HT1AR-FGFR1 heteroreceptor complexes has been proven, but the functional receptor–receptor interactions in the heterocomplexes have only been investigated in CA1 pyramidal neurons of control Sprague Dawley (SD) rats. In the current study, considering the impact of the receptor interplay in developing new antidepressant drugs, the effects of 5HT1AR-FGFR1 complex activation were investigated in hippocampal pyramidal neurons and in midbrain dorsal raphe serotonergic neurons of SD rats and of a genetic rat model of depression (the Flinders Sensitive Line (FSL) rats of SD origin) using an electrophysiological approach. The results showed that in the raphe-hippocampal 5HT system of SD rats, 5HT1AR-FGFR1 heteroreceptor activation by specific agonists reduced the ability of the 5HT1AR protomer to open the GIRK channels through the allosteric inhibitory interplay produced by the activation of the FGFR1 protomer, leading to increased neuronal firing. On the contrary, in FSL rats, FGFR1 agonist-induced inhibitory allosteric action at the 5HT1AR protomer was not able to induce this effect on GIRK channels, except in CA2 neurons where we demonstrated that the functional receptor–receptor interaction is needed for producing the effect on GIRK. In keeping with this evidence, hippocampal plasticity, evaluated as long-term potentiation induction ability in the CA1 field, was impaired by 5HT1AR activation both in SD and in FSL rats, which did not develop after combined 5HT1AR-FGFR1 heterocomplex activation in SD rats. It is therefore proposed that in the genetic FSL model of depression, there is a significant reduction in the allosteric inhibition exerted by the FGFR1 protomer on the 5HT1A protomer-mediated opening of the GIRK channels in the 5HT1AR-FGFR1 heterocomplex located in the raphe-hippocampal serotonin system. This may result in an enhanced inhibition of the dorsal raphe 5HT nerve cell and glutamatergic hippocampal CA1 pyramidal nerve cell firing, which we propose may have a role in depression.
Biomimetic Boron Nitride Nanoparticles for Targeted Drug Delivery and Enhanced Antitumor Activity

Boron nitride nanomaterials are being increasingly recognized as vehicles for cancer drug delivery that increase drug loading and control drug release because of their excellent physicochemical properties and biocompatibility. However, these nanoparticles are often cleared rapidly by the immune system and have poor tumor targeting effects. As a result, biomimetic nanotechnology has emerged to address these challenges in recent times. Cell-derived biomimetic carriers have the characteristics of good biocompatibility, long circulation time, and strong targeting ability. Here, we report a biomimetic nanoplatform (CM@BN/DOX) prepared by encapsulating boron nitride nanoparticles (BN) and doxorubicin (DOX) together using cancer cell membrane (CCM) for targeted drug delivery and tumor therapy. The CM@BN/DOX nanoparticles (NPs) were able to target cancer cells of the same type on its own initiative through homologous targeting of cancer cell membranes. This led to a remarkable increase in cellular uptake. In vitro simulation of an acidic tumor microenvironment could effectively promote drug release from CM@BN/DOX. Furthermore, the CM@BN/DOX complex exhibited an excellent inhibitory effect against homotypic cancer cells. These findings suggest that CM@BN/DOX are promising in targeted drug delivery and potentially personalized therapy against their homologous tumor.
Modeling Phase Changing Property of VO2 for Reconfigurable Microwave Frequency Selection Applications via Time-Resolved Microwave Conductivity

Vanadium dioxide (VO2) is characterized using the time-resolved microwave conductivity (TRMC) method for applications requiring reconfigurable microwave frequency selection. We demonstrate that TRMC is a flexible method for determining the microwave conductivity of thin film compounds of varied thicknesses that are both phase-changing and non-phase changing in nature. The method makes use of Ka-band microwave resonant waveguides to examine how thermally excited samples’ microwave conductivity changes in response to microwave-transmitted power through the system’s sensitivity factor. The sensitivity factor is illustrated by a study of incident waves (electromagnetic fields) on medium and waveguide perturbation analysis in VO2 thin films. The TRMC measurements show a low regime in the microwave conductivity below the transition temperature (<inline-formula> <tex-math notation="LaTeX">$T_{c}$ </tex-math></inline-formula>) of VO2 where <inline-formula> <tex-math notation="LaTeX">$T_{c}$ </tex-math></inline-formula> occurs near 65°C; this is associated with the dielectric characteristics of the charge carriers and points to the presence of shallow trap electron states. Longer electron hops enhance charge mobility and, consequently, the barrier energy above <inline-formula> <tex-math notation="LaTeX">$T_{c}$ </tex-math></inline-formula>, where these states are thermally discharged, resulting in a high thermally triggered microwave conductivity regime. The activation energy may come from a variety of complex contributions, like polaronic self-localizations, as well as a dynamic disorder brought on by the thermal oscillations of VO2 molecules. The calculated conductance values are simulated in CST Studio as plane wave incidence on medium to ascertain the fields’ microwave transmission behavior and contrast it with the experimental results to validate the model. Additionally, using the derived conductivities, the characteristics of well-known materials like copper (Cu) were confirmed.
Prior-Aware Cross Modality Augmentation Learning for Continuous Sign Language Recognition

Continuous sign language recognition (CSLR) aims to map a sign video into a sentence of text words in the same order as the signs. Generally, word error rate (WER), i.e., editing distance, is adopted as the main evaluation metric. Since this metric is not differentiable, current deep-learning-based CSLR methods usually resort to connectionist temporal classification (CTC) loss during optimization, which maximizes the posterior probability over the sequential alignment. Due to the optimization gap between CTC loss and WER, the decoded sequence with the maximum probability in CTC may not be the one with the lowest WER. To tackle this issue, we propose a novel prior-aware cross modality augmentation learning method. In our approach, we first generate the pseudo video-text pair by cross modality editing, i.e., substitution, deletion and insertion on the paired real video-text data. To ensure the pseudo data quality, we guide the editing with both textual grammar prior and visual pose transition consistency prior. In this way, the generated pseudo video and text sentence follow the underlying distribution of the sign language data, and sever as more genuine hard examples for the cross modality representation learning of our CSLR task. Based on the real and generated pseudo data, we optimize our CSLR framework with three loss terms. We evaluate our approach on popular large-scale CSLR datasets and extensive experiments demonstrate the effectiveness of our method.
Relative Neuroadaptive Effect of Resistance Training along the Descending Neuroaxis in Older Adults

Age-related decline in voluntary force production represents one of the main contributors to the onset of physical disability in older adults and is argued to stem from adverse musculoskeletal alterations and changes along the descending neuroaxis. The neural contribution of the above is possibly indicated by disproportionate losses in voluntary activation (VA) compared to muscle mass. For young adults, resistance training (RT) induces muscular and neural adaptations over several levels of the central nervous system, contributing to increased physical performance. However, less is known about the relative neuroadaptive contribution of RT in older adults. The aim of this review was to outline the current state of the literature regarding where and to what extent neural adaptations occur along the descending neuroaxis in response to RT in older adults. We performed a literature search in PubMed, Google Scholar and Scopus. A total of 63 articles met the primary inclusion criteria and following quality analysis (PEDro) 23 articles were included. Overall, neuroadaptations in older adults seemingly favor top-down adaptations, where the preceding changes of neural drive from superior levels affect the neural output of lower levels, following RT. Moreover, older adults appear more predisposed to neural rather than morphological adaptations compared to young adults, a potentially important implication for the improved maintenance of neuromuscular function during aging.
L1-distance and classification problem by Bayesian method

ABSTRACT In this article we suggest a definition for the notion of L1-distance that combines probability density functions and prior probabilities. We also obtain the upper and lower bounds for this distance as well as its relation to other measures. Besides, the relationship between the proposed distance and quantities involved in classification problem by Bayesian method will be established. In practice, calculations are performed by Matlab procedures. As an illustration for applications of the obtained results, the article gives here an estimation for the ability to repay bank debt of some companies in Can Tho City, Vietnam.
Flexible Magnetic Sensors

With the merits of high sensitivity, high stability, high flexibility, low cost, and simple manufacturing, flexible magnetic field sensors have potential applications in various fields such as geomagnetosensitive E-Skins, magnetoelectric compass, and non-contact interactive platforms. Based on the principles of various magnetic field sensors, this paper introduces the research progress of flexible magnetic field sensors, including the preparation, performance, related applications, etc. In addition, the prospects of flexible magnetic field sensors and their challenges are presented.
A Unified Parallel CORDIC-Based Hardware Architecture for LSTM Network Acceleration

Deep Neural Networks (DNNs) have recently become the standard tool for solving various practical problems in a wide range of applications with state-of-the-art performance. Recurrent Neural Networks (RNNs) such as Long Short-Term Memory (LSTM) are a subset of DNNs with fully connected single or multi-layer networks. The complex neurons and internal states of LSTM networks enable them to build a memory of events, making them ideal for time series applications. Despite the great potential of LSTM networks, their heterogeneous operations and computational resource requirements create a vast gap when it comes to the fast processing time required in real-time applications using low-power, low-cost edge devices. This work proposes a novel hardware architecture that combines serial-parallel computation with matrix algebra concepts and efficient low-power computer arithmetics for LSTM network acceleration. The hardware is based on a systolic ring of outer-product-based processing elements (PEs) and a reusable single activation function block (AFB). PEs and AFB are implemented using the coordinate rotation digital computer algorithm (CORDIC) in the linear and hyperbolic modes. Unlike most approaches, the proposed hardware can be configured to perform recurrent and non-recurrent fully connected layers (FC) computations, making it suitable for various low-power edge applications. The architecture is validated on the Xilinx PYNQ-Z1 development board using an open-source time series dataset. The implemented design achieves <inline-formula><tex-math notation="LaTeX">$\text{114} \mu \text{s}$</tex-math><alternatives><mml:math><mml:mrow><mml:mtext>114</mml:mtext><mml:mi>μ</mml:mi><mml:mtext>s</mml:mtext></mml:mrow></mml:math><inline-graphic xlink:href="mohamed-ieq1-3268400.gif"/></alternatives></inline-formula> average latency and <inline-formula><tex-math notation="LaTeX">$\text{1.8 GOPS}$</tex-math><alternatives><mml:math><mml:mrow><mml:mtext>1.8</mml:mtext><mml:mspace width="4.pt"/><mml:mtext>GOPS</mml:mtext></mml:mrow></mml:math><inline-graphic xlink:href="mohamed-ieq2-3268400.gif"/></alternatives></inline-formula> throughput. The proposed design's low latency and <inline-formula><tex-math notation="LaTeX">$\text{0.438 W}$</tex-math><alternatives><mml:math><mml:mrow><mml:mtext>0.438</mml:mtext><mml:mspace width="4.pt"/><mml:mtext>W</mml:mtext></mml:mrow></mml:math><inline-graphic xlink:href="mohamed-ieq3-3268400.gif"/></alternatives></inline-formula> power consumption makes it suitable for resource-constrained edge platforms.
Analysis of the 4d9 −4d8 (4f + 6p) transition array of Sn VI

The spectrum of tin was photographed in the 150-250 A region on a 10.7 m spectrograph at the NIST Laboratory in Gaithersburg, USA, and the 3 m spectrograph in Troitsk, Russia, using a triggered spark source. In the 4d9 −4d8 (4f + 6p) transition array of Sn VI spectrum 85 lines have been classified. Sixty-three levels belonging to the 4d84f and 4d86p configurations have been established. Parametric least-squares-fitting calculations including configuration interaction between the 4d8(5p + 6p + 4f + 5f + 6f) and 4p54d10 configurations were carried out to interpret the observed spectrum adequately.
DSM-Assisted Unsupervised Domain Adaptive Network for Semantic Segmentation of Remote Sensing Imagery

The semantic segmentation of high-resolution remote sensing imagery (RSI) is an essential task for many applications. As a promising unsupervised learning method, unsupervised domain adaptation (UDA) methods remarkably contribute to the advancement of high-resolution RSI semantic segmentation. Previous methods focus on reducing the domain shift of orthophotos, suffering from some limitations because the available information in orthophotos is relatively homogeneous. This article proposes a framework to introduce digital surface model (DSM) data for the unsupervised semantic segmentation of RSI. The proposed method combines RSI with DSM through two modules, namely, multipath encoder (MPE) and multitask decoder (MTD), and aligns global data distribution in the source and target domains with a UDA module. A refined postfusion (RPF) module is proposed in the inference phase to exploit the height information fully for refining the segmentation results. Specifically, MPE is designed to utilize RSI and DSM to train the segmentation network jointly, which iteratively fuses RSI and DSM features at multiple levels to enhance their feature representations. MTD is designed to produce fusion prediction maps by filtering interference information of DSM and yielding accurate segmentation masks of DSM and RSI. Experimental results show that the proposed method substantially improves the semantic segmentation performance on high-resolution RSI and outperforms state-of-the-art methods. This article provides a methodological reference for fusing multimodal data in various RSI-based unsupervised tasks.
Case series of low dose rituximab for membranous nephropathy; a single centre experience

Introduction: Rituximab is the recent treatment of choice for primary membranous nephropathy However, dose of rituximab mentioned in literature is high and not economical in middle income countries. Low dose rituximab based on CD 19 cell count can be tried as an alternative for high dose rituximab for inducing clinical remission in appropriate clinical settings. Case Series: Four patients were administered low dose rituximab and initial CD 19 count was monitored for optimal rituximab response. Three males and one female are part of this case series. Renal biopsies showed membranous nephropathy with tissue phospholipase A2 receptor (PLA2R) positivity in two cases. Serum PLA2R was positive for the same two cases. Two patients completely remitted after one year, one male patient required additional rituximab dose based on CD19 count, one patient required single dose of rituximab for partial remission in the background of tacrolimus with steroids. One patient failed to remit on low dose rituximab protocol. Conclusion: Low dose Rituximab can be tried as a favorable alternative for high dose Rituximab in appropriate clinical settings.