Miracle-dz/UniFAR-FTUs huggingface dataset:
MODELING OF DENGUE HEMORRHAGIC FEVER IN BOGOR USING BAYESIAN SUR-SAR

The purposes of this research are (1) To develop Seemingly Unrelated Regression (SUR) system constructed by correlated Spatial Autoregressive Model (SAR) with Bayesian approach for dynamic analysis of spatial and non-spatial contributions of Dengue Hemorrhagic Fever (DHF) case in Bogor, (2) To evaluate efficiency issues on parameters estimation with SUR system. Markov Chain Monte Carlo (MCMC) sampling scheme was used to estimate all of model parameters with the number of iteration whose burn-in period was discovered. The results indicated that : there was the similar pattern of DHF spread in Bogor during 2009 – 2011, the nearby areas had a significant role to the incidence of DHF in an area in the city of Bogor, and the non-spatial contributions of DHF cases in Bogor during 2009 -2011 included in this model were dynamic. Gain efficiency of parameters estimation on modeling of DHF in Bogor with SAR for each year during 2009-2011 can be obtained if we construct all of SAR with SUR system model.
Dual-Resonant Step-Up AC/DC Converter Based on Fixed Frequency Pulse Overlapping Modulation

To overcome the limitation of voltage regulation in resonant switched capacitor topology and introduce the soft switching characteristics into AC/DC converter, a dual-resonant step-up AC/DC converter based on fixed frequency pulse overlapping modulation is presented in this paper. The voltage regulation is achieved by regulating the overlapping time of the two switching pulses, and the switching frequency can be fixed for simplifying the implementation. The operational principle, voltage gain and power factor correction performance are analyzed in detail. Moreover, a simulation model with 165−265 Vrms input and 400 V/1 kW output is built to verify the above analysis, and a model with closed loop is built to verify the controllability.
Target Tracking Control of Space-Manipulators on Lie Groups

We present a full-pose end-effector control approach on Lie groups for free-floating space manipulators with non-zero momentum while tracking a moving target during proximity operations. We model space-manipulators as open-chain multi-body systems with 1-degree-of-freedom joints where the configuration space of the spacecraft is isomorphic to the Special Euclidean group SE(3). We formulate the dynamics of the spacecraft-manipulator via the Lagrange-Poincare equations and the dynamics of its target via Euler-Poincare equations to avoid kinematic singularities associated with parametrization of their poses. This model reduces the phase space of the space-manipulator by exploiting its inherent independence of the spacecraft's pose. We consider the full pose of the end-effector relative to the target as the system output, which transforms the output-tracking control problem into an output-regulation problem. To avoid parametrization singularities of this output, we perform feedback linearization on the matrix Lie group SE (3) in the reduced phase space of the space-manipulator. We then propose a feedback/feedforward proportional-integral-derivative workspace controller, based on coordinate-free pose and velocity error functions defined on the matrix Lie group associated with the target's relative pose. We provide analytical proof of the almost-global stability of the presented controller when regulating the end-effector's pose relative to the target towards identity.
Self-Supervised Multimodal Fusion Network for Knee Osteoarthritis Severity Grading

Knee osteoarthritis (OA) is a highly prevalent form of arthritis and a leading cause of physical disability, given the growing aging population. To assist the knee OA assessment, there is a demanding interest in computer-aided grading algorithms. Existing grading methods generally require resource-intensive annotated datasets for supervised training. Moreover, they only consider unimodal data, whilst multimodal medical images are rarely utilised to formulate better knee OA patterns. Therefore, in this study, a novel Self-supervised Multimodal Fusion Network (S-MFN) is proposed for multimodal unsupervised knee OA grading with X-ray and magnetic resonance imaging (MRI) modalities. Specifically, S-MFN involves two modality-specific streams to obtain knee OA representations from the two corresponding modalities. A modality-aware information exchange mechanism is devised to interactively formulate cross-modal patterns in a multi-scale manner regarding the scales of feature maps. To this end, a multimodal contrastive learning is introduced in a self-supervised manner through modality-specific and cross-modal modelling. Comprehensive experimental results on the widely used dataset, Osteoarthritis Initiative (OAI), demonstrate the effectiveness of the proposed method.
Non-uniform Deblurring by Deep Sharpness Edge Guided Model

In this paper, we propose a two-branch deblurring framework. Given a blurred image, we first extract the edge map and employ an edge refinement network to recover the structure. Then the refined edge map is utilized to guide the subsequent deblurring process for correct structure recovery. Specifically, we develop a lightweight omni-dimensional attention module for long-range dependencies modeling and plug it into the edge refinement network, which effectively handles blur patterns with high variation. Furthermore, we propose a dynamic feature upsample module, which integrates dynamic convolution with upsampling and adaptively deals with the non-uniform blur. Extensive experiments show that our method outperforms state-of-the-art methods.
Fog Computing for Deep Learning with Pipelines

In this article, we introduce a fog system design for processing data collected from edge devices, such as mobile, sensor, and extended (mixed, augmented, virtual) reality equipment. Our system enables the network to provide hardware-accelerated processors for resource-intensive computations on data gathered from remote locations, such as 5G and beyond mobile networks. By splitting heavy computations into pipelines, and distributing them among processors in the edge, fog and the cloud, our design benefits from the processing power of the cloud, while utilizing fog devices with a lower network latency. We implement our design, and use it for distributed training and inference with industry-grade deep learning models for computer vision. We deploy our architecture in infrastructure including cloud and edge servers supporting GPU-accelerated computations. We benchmark pipelines in various deployment settings to study the overhead that they introduce. Our contributions are a new design for wide-area data processing, a framework that realizes this design and provides means of developing applications that are optimized in terms of infrastructure and hardware. These contributions are complemented with our benchmark results, which reveal the potential causes of processing overhead.
Development and optimization of solid lipid nanoparticle formulation for ophthalmic delivery of chloramphenicol using a Box-Behnken design

The purpose of the present study was to optimize a solid lipid nanoparticle (SLN) of chloramphenicol by investigating the relationship between design factors and experimental data using response surface methodology. A Box-Behnken design was constructed using solid lipid (X1), surfactant (X2), and drug/lipid ratio (X3) level as independent factors. SLN was successfully prepared by a modified method of melt-emulsion ultrasonication and low temperature-solidification technique using glyceryl monostearate as the solid lipid, and poloxamer 188 as the surfactant. The dependent variables were entrapment efficiency (EE), drug loading (DL), and turbidity. Properties of SLN such as the morphology, particle size, zeta potential, EE, DL, and drug release behavior were investigated, respectively. As a result, the nanoparticle designed showed nearly spherical particles with a mean particle size of 248 nm. The polydispersity index of particle size was 0.277 ± 0.058 and zeta potential was −8.74 mV. The EE (%) and DL (%) could reach up to 83.29% ± 1.23% and 10.11% ± 2.02%, respectively. In vitro release studies showed a burst release at the initial stage followed by a prolonged release of chloramphenicol from SLN up to 48 hours. The release kinetics of the optimized formulation best fitted the Peppas–Korsmeyer model. These results indicated that the chloramphenicol-loaded SLN could potentially be exploited as a delivery system with improved drug entrapment efficiency and controlled drug release.
The development of wheel throwing at Shahr-i Sokhta slow and fast revolutions towards statehood

L'article rapporte les resultats d'analyses radiographiques d'un echantillonage de ceramiques provenant du site urbain de Shahr-i Sokhta (IVe-IIIe millenaire, Iran) destinees a etudier l'evolution des techniques de fabrication de la ceramique, en particulier les technique du faconnage au tour ou en colombins
Rapid and low-cost screening for single and combined effects of drought and heat stress on the morpho-physiological traits of African eggplant (Solanum aethiopicum) germplasm

Drought and heat are two stresses that often occur together and may pose significant risks to crops in future climates. However, the combined effects of these two stressors have received less attention than single-stressor investigations. This study used a rapid and straightforward phenotyping method to quantify the variation in 128 African eggplant genotype responses to drought, heat, and the combined effects of heat and drought at the seedling stage. The study found that the morphophysiological traits varied significantly among the 128 eggplants, highlighting variation in response to abiotic stresses. Broad-sense heritability was high (> 0.60) for chlorophyll content, plant biomass and performance index, electrolyte leakage, and total leaf area. Positive and significant relationships existed between biomass and photosynthetic parameters, but a negative association existed between electrolyte leakage and morpho-physiological traits. The plants underwent more significant stress when drought and heat stress were imposed concurrently than under single stresses, with the impact of drought on the plants being more detrimental than heat. There were antagonistic effects on the morphophysiology of the eggplants when heat and drought stress were applied together. Resilient genotypes such as RV100503, RV100501, JAMBA, LOC3, RV100164, RV100169, LOC 3, RV100483, GH5155, RV100430, GH1087, GH1087*, RV100388, RV100387, RV100391 maintained high relative water content, low electrolyte leakage, high Fv/Fm ratio and performance index, and increased biomass production under abiotic stress conditions. The antagonistic interactions between heat and drought observed here may be retained or enhanced during several stress combinations typical of plants’ environments and must be factored into efforts to develop climate change-resilient crops. This paper demonstrates improvised climate chambers for high throughput, reliable, rapid, and cost-effective screening for heat and drought and combined stress tolerance in plants.
Sex-dependence of synaptic depression induced by activation of metabotropic glutamate receptors in rat hippocampus

The modulation of synaptic efficacy by group I metabotropic glutamate receptors is dysregulated in several neurodevelopmental and neurodegenerative disorders impacting cognitive function. The progression and severity of these and other disorders are affected by biological sex, and differences in metabotropic glutamate receptor signalling have been implicated in this effect. In this study, we have examined whether there are any sex-dependent differences in a form of long-term depression of synaptic responses that is triggered by application of the group I metabotropic glutamate receptor agonist 3,5-dihydroxyphenylglycine (DHPG). We studied DHPG-induced long-term depression at the Schaffer collateral-commissural pathway in area CA1 of hippocampal slices prepared from three separate age groups of Sprague Dawley rats. In both juvenile (2-week-old) and young adult (3-month-old) rats, there were no differences between sexes in the magnitude of long-term depression. However, in older adult (>1-year-old) rats, DHPG-induced long-term depression was greater in males. In contrast, there were no differences between sexes with respect to basal synaptic transmission or paired-pulse facilitation in any age group. The specific enhancement of metabotropic glutamate receptor–dependent long-term depression in older adult males, but not females, reinforces the importance of considering sex as a factor in the study and treatment of brain disorders.
The nasal lymphatic route of CSF outflow: implications for neurodegenerative disease diagnosis and monitoring

ABSTRACT Cerebrospinal fluid (CSF) plays a crucial role in the brain's lymphatics as it traverses the central nervous system (CNS). Its primary function is to facilitate the outward transport of waste. Among the various CSF outflow pathways, the route through the cribriform plate along the olfactory nerves stands out as the most predominant. This review describes the outflow pathway of CSF into the nasal lymphatics. Additionally, we examine existing studies to describe mutual influences observed between the brain and extracranial regions due to this outflow pathway. Notably, pathological conditions in the CNS often influence CSF outflow, leading to observable changes in extracranial regions. The established connection between the brain and the nose is significant, and our review underscores its potential relevance in monitoring CNS ailments, including neurodegenerative diseases. Considering that aging – the most significant risk factor for the onset of neurodegeneration – is also a principal factor in CSF turnover alterations, we suggest a novel approach to studying neurodegenerative diseases in therapeutic terms.
Advances in functional MRI research in bipolar disorder: from the perspective of mood states

Bipolar disorder is characterised by recurrent and alternating episodes of mania/hypomania and depression. Current breakthroughs in functional MRI techniques have uncovered the functional neuroanatomy of bipolar disorder. However, the pathophysiology underlying mood instability, mood switching and the development of extreme mood states is less well understood. This review presents a comprehensive overview of current evidence from functional MRI studies from the perspective of mood states. We first summarise the disrupted brain activation patterns and functional connectivity that have been reported in bipolar disorder, irrespective of the mood state. We next focus on research that solely included patients in a single mood state for a better understanding of the pathophysiology of bipolar disorder and research comparing patients with different mood states to dissect mood state-related effects. Finally, we briefly summarise current theoretical models and conclude this review by proposing potential avenues for future research. A comprehensive understanding of the pathophysiology with consideration of mood states could not only deepen our understanding of how acute mood episodes develop at a neurophysiological level but could also facilitate the identification of biological targets for personalised treatment and the development of new interventions for bipolar disorder.
Urban tolerance does not protect against population decline in North American birds

Population declines of organisms are widespread and severe, but some species' populations have remained stable, or even increased. The reasons some species are less vulnerable to population decline than others are not well understood. Species that tolerate urban environments often have a broader environmental tolerance, which, along with their ability to tolerate one of the most human-modified habitats (i.e. cities), might allow them to persist in the face of diverse anthropogenic challenges. Here, we examined the relationship between urban tolerance and annual population trajectories for 397 North American bird species. Surprisingly, we found that urban tolerance was unrelated to species’ population trajectories. The lack of a relationship between urban tolerance and population trajectories may reflect other factors driving population declines independent of urban tolerance, challenges that are amplified in cities (e.g. climate warming, disease), and other human impacts (e.g. conservation efforts, broad-scale land-use changes) that have benefitted some urban-avoidant species. Overall, our results illustrate that urban tolerance does not protect species against population decline.
Sniffing out meaning: Chemosensory and semantic neural network changes in sommeliers

Abstract Wine tasting is a very complex process that integrates a combination of sensation, language, and memory. Taste and smell provide perceptual information that, together with the semantic narrative that converts flavor into words, seem to be processed differently between sommeliers and naïve wine consumers. We investigate whether sommeliers' wine experience shapes only chemosensory processing, as has been previously demonstrated, or if it also modulates the way in which the taste and olfactory circuits interact with the semantic network. Combining diffusion‐weighted images and fMRI (activation and connectivity) we investigated whether brain response to tasting wine differs between sommeliers and nonexperts (1) in the sensory neural circuits representing flavor and/or (2) in the neural circuits for language and memory. We demonstrate that training in wine tasting shapes the microstructure of the left and right superior longitudinal fasciculus. Using mediation analysis, we showed that the experience modulates the relationship between fractional anisotropy and behavior: the higher the fractional anisotropy the higher the capacity to recognize wine complexity. In addition, we found functional differences between sommeliers and naïve consumers affecting the flavor sensory circuit, but also regions involved in semantic operations. The former reflects a capacity for differential sensory processing, while the latter reflects sommeliers' ability to attend to relevant sensory inputs and translate them into complex verbal descriptions. The enhanced synchronization between these apparently independent circuits suggests that sommeliers integrated these descriptions with previous semantic knowledge to optimize their capacity to distinguish between subtle differences in the qualitative character of the wine.
TIE-GANs: single-shot quantitative phase imaging using transport of intensity equation with integration of GANs

Abstract. Significance Artificial intelligence (AI) has become a prominent technology in computational imaging over the past decade. The expeditious and label-free characteristics of quantitative phase imaging (QPI) render it a promising contender for AI investigation. Though interferometric methodologies exhibit potential efficacy, their implementation involves complex experimental platforms and computationally intensive reconstruction procedures. Hence, non-interferometric methods, such as transport of intensity equation (TIE), are preferred over interferometric methods. Aim TIE method, despite its effectiveness, is tedious as it requires the acquisition of many images at varying defocus planes. The proposed methodology holds the ability to generate a phase image utilizing a single intensity image using generative adversarial networks (GANs). We present a method called TIE-GANs to overcome the multi-shot scheme of conventional TIE. Approach The present investigation employs the TIE as a QPI methodology, which necessitates reduced experimental and computational efforts. TIE is being used for the dataset preparation as well. The proposed method captures images from different defocus planes for training. Our approach uses an image-to-image translation technique to produce phase maps and is based on GANs. The main contribution of this work is the introduction of GANs with TIE (TIE:GANs) that can give better phase reconstruction results with shorter computation times. This is the first time the GANs is proposed for TIE phase retrieval. Results The characterization of the system was carried out with microbeads of 4 μm size and structural similarity index (SSIM) for microbeads was found to be 0.98. We demonstrated the application of the proposed method with oral cells, which yielded a maximum SSIM value of 0.95. The key characteristics include mean squared error and peak-signal-to-noise ratio values of 140 and 26.42 dB for oral cells and 100 and 28.10 dB for microbeads. Conclusions The proposed methodology holds the ability to generate a phase image utilizing a single intensity image. Our method is feasible for digital cytology because of its reported high value of SSIM. Our approach can handle defocused images in such a way that it can take intensity image from any defocus plane within the provided range and able to generate phase map.
Exploring the mechanical, vibrational optoelectronic, and thermoelectric properties of novel half-Heusler FeTaX (X = P, As): a first-principles study

In this study, the density functional theory (DFT) was employed to study the structural, electronic, optical, and thermoelectric characteristics of half-Heusler (HH) FeTaX (X = P or As). Optimization of the structures was achieved using Perdew–Burke–Ernzerhof (PBE) parametrized generalized gradient approximation (GGA). These HH FeTaX (X = P, As) showed indirect bandgaps of 0.882 eV and 0.748 eV, respectively. The predicted density of states (DOS) spectra suggest that Fe-d and Ta-d states contribute predominantly to both valence and conduction bands, whereas P/As-p states contribute less. Optical properties were investigated to assess their potential in optoelectronic applications. The estimated values of various optical parameters and low loss suggest that the studied HH FeTaX (X = P, As) are suitable for optoelectronic device applications. The thermoelectric responses of the studied HH FeTaX (X = P, As) were computed, and their highest power factors at high temperature reflects their usage in thermoelectric devices.
Clinical effects of acupuncture for the treatment of pressure ulcers: A comprehensive systematic review and meta‐analysis

Abstract The aim of this study was to assess the efficacy of acupuncture in the treatment of pressure ulcers. Randomized controlled trials evaluating the effects of acupuncture on pressure ulcers were identified through a comprehensive literature search on public database. The quality assessment of the included trials was performed based on the guidance of the Cochrane Reviewers' Handbook, and pooled analyses were performed by using the RevMan 5.4 software. The pooled results demonstrated that acupuncture in combination with standard wound care was significantly superior to standard wound care alone with regard to effective rate (RR 1.17, 95% CI [1.10, 1.24]), reduction in Wound Size (MD −2.78, 95% CI [−2.43, −1.44]), healing time (MD −6.24, 95% CI [−12.32, −0.17]) and the amount of 24‐h exudate (MD −0.86, 95% CI [−1.54, −0.18]). In conclusion, this study suggests that acupuncture can be used as an adjunctive therapy to promote healing of pressure ulcers.