Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in studying whole mouse brain vasculature using high-resolution 3D light microscopy imaging

Abstract. Significance: The cerebrovasculature has become increasingly recognized as a major player in overall brain health and many brain disorders. Although there have been several landmark studies to understand details of these crucially important structures in an anatomically defined area, brain-wide examination of the whole cerebrovasculature, including microvessels, has been challenging. However, emerging techniques, including tissue processing and three-dimensional (3D) microscopy imaging, enable neuroscientists to examine the total vasculature in the entire mouse brain. Aim: Here, we aim to highlight advances in these high-resolution 3D mapping methods including block-face imaging and light sheet fluorescent microscopy. Approach: We summarize latest mapping tools to understand detailed anatomical arrangement of the cerebrovascular network and the organizing principles of the neurovascular unit (NVU) as a whole. Results: We discuss biological insights gained from studies using these imaging methods and how these tools can be used to advance our understanding of the cerebrovascular network and related cell types in the entire brain. Conclusions: This review article will help to understand recent advance in high-resolution NVU mapping in mice and provide perspective on future studies.
A 19 ps Precision and 170 M Samples/s Time-to-Digital Converter Implemented in FPGA with Online Calibration

This paper presents a 19 ps precision and 170 M samples/s time-to-digital converter (TDC) in FPGA. Through the direct count method and tapped delay line method, the coarse count and fine count can be extracted, respectively. The direct count is realized by the 350 M clock and the tapped delay line is constructed by the CARRY4 block. The ones-counter encoder is used to convert the thermometer code with bubble errors into binary code, which is applicable to all the FPGA chips. This work not only explains the schematic of the ones-counter encoder, but also shows how to configure it. Owing to the inconsistency of delay elements caused by process, bin-by-bin calibration is utilized to improve the differential nonlinearities (DNL) and integral nonlinearities (INL) of the TDC. A novel method was developed to compensate the influence of voltage and temperature. As the delay elements vary with voltage and temperature, a frequency counter is used to extrapolate and compensate its effect on the delay line. All of the above strategies use online calibration and improve the precision and sampling rate of TDC. The experimental results show the least significant bit (LSB) achieves 17.4 ps, the DNL is within [−0.90, 1.67] LSB, and the INL is in the range of [−1.90, 3.31] LSB.
Predictive Indicators of Kinematic Writing Ability in Patients with Parkinson’s Disease: Focusing on Cognition, Depression, and Motor Abilities

Objectives: Parkinson’s disease (PD) can affect not only motor abilities but also cognition and depression. The purpose of this study was to investigate the predictive indicators of kinematic writing ability in patients with Parkinson’s disease.Methods: Seventy-two subjects (47 patients with PD, 25 normal adults [NA]) performed tasks; including sentence writing along visual cues using software that could measure pen pressure, letter size, and writing speed.Results: Firstly, discriminant analysis showed that the writing speeds were good discriminators for the PD group. Secondly, the PD group showed positive correlation between the Korean version of the Montreal Cognitive Assessment (MoCA-K) score and pen pressure in the ‘writing within square blanks task’. They also showed a positive correlation between the Unified Parkinson’s Disease Rating Scale (UPDRS) score and letter size in the ‘free writing task’. The PD group showed a negative correlation between UPDRS score and writing speed in the ‘writing within square blank task’. Thirdly, the MoCA-K score showed significant explanatory power for pen pressure, and the UPDRS score showed significant explanatory power for the writing speed in the PD group.Conclusion: This study is significant in that it confirms the importance of considering various factors such as cognitive ability when examining the writing characteristics of patients with PD, which have been focused only on motor skills so far.
The Cross-Section of Municipal Bond Returns

This paper studies the cross-section of expected municipal bond returns. We show that municipal bond yields contain reliable information about differences in expected municipal bond returns across states of issuance, duration range, and credit quality. Hence, using information embedded in those yields, we can target higher expected returns by focusing on tax clientele effects, term premiums, and credit premiums. Indeed, a well-diversified, low-turnover systematic strategy that emphasizes all three drivers of expected municipal bond returns would have outperformed the municipal bond market by 48 basis points per year, on average, between November 2006 and December 2021.
A Note on The Empirics of Regional Financialisation

level would enhance the possibilities of future research to analyse the complex issues and questions tied to regional financialisation. ist und gegenwärtig einen Kompro miss zwischen Datenverfügbarkeit und Erklärungskraft der verwendeten Daten erfordert. Eine verbesserte Datenverfügbarkeit auf regionaler Ebene würde daher die Möglichkeiten künftiger Forschung, die komplexen Themen und Fragestellungen, die mit regionaler Fi nanzialisierung verknüpft sind, zu analysieren, wesentlich erweitern.
Reactive Power Planning in Large Power Systems using Genetic Algorithm

This paper presents a new approach to optimal reactive power planning based on a genetic algorithm which is a kind of search algorithm based on the mechanics of natural selection and genetics. This algorithm can search for a global solution using multiple path and treat integer problem naturally. In the method, discrete control variables are represented as integer strings (chromosomes). Two intentional operations are proposed to improve this chromosomes in addition to conventional operations. First one is "interbreeding" which crosses preferable subsystems each other to form a better combination of control variables. Second one is "manipulation" which improves power system profiles using Al-based stochastic "If-then" rules. Since "If-then" rules are deterministicly applied in expert systems, rules should be built without any conflict. The proposed method, however, applies such "If-then" rules stochastically. The proposed method was applied to practical 51-bus and 224-bus systems to show its feasibility and capabilitys. In both systems, the method shows very good convergent characteristics to global solutions in discrete value. During this research, many global or quasi-global solutions are found. It will be worthwhile to investigate these phenomena as further works.
Test and Simulation of an Active Vibration Control System for Helicopter Applications

A significant source of vibration in helicopters is the main rotor system, and it is a technical challenge to reduce the vibration in order to ensure the comfort of crew and passengers. Several types of passive devices have been applied to conventional helicopters in order to reduce the vibration. In recent years, helicopter manufacturers have increasingly adopted active vibration control systems (AVCSs) due to their superior performance with lower weight compared with passive devices. AVCSs can also maintain their performance over aircraft configuration and flight condition changes. As part of the development of AVCS software for light civil helicopter (LCH) applications, a test bench is constructed and vibration control tests and simulations are performed in this study. The test bench, which represents the airframe, is excited using a pair of counter rotating force generators (CRFGs) and a multiple input single output (MISO) AVCS that consists of three accelerometer sensors and a pair of CRFGs; a filtered-x least mean square (LMS) algorithm is applied for the vibration reduction. First, the vibration control tests are performed with uniform sensor weights; then, the change in the control performance according to changes in the sensor weight is investigated and compared with the simulation results. It is found that the vibration control performance can be tuned through adjusting the weights of the three sensors, even if only one actuator is used.
Brazilian BookTubers and the COVID-19 pandemic

Reading is an essential skill for coping to an increasingly connected society. This article aims to analyze reading skills moderated by young Brazilian BookTubers while they narrate their reading experiences during the COVID-19 pandemic. This study draws on multiple data sources and uses a mixed methods approach to explore their narratives in 10 videos on the best books of 2020. Results indicate BookTubers are developing a range of learning, literacy, and citizenship skills, but also suffer from pressures of connectivity, productivity, and exposure. In a pandemic context, marked by the mandatory isolation and unequal access to books and digital culture, they acknowledged reading as an encouragement for them and their audience to face hardships. However, despite these communities’ efforts to make Brazil a country of readers, the social gap that precedes the existence of digital culture widens and intensifies.
Evaluation of inter- and intra-observer variations in prostate gland delineation using CT-alone versus CT/TPUS

Background This study aims to explore the role of four-dimensional (4D) transperineal ultrasound (TPUS) in the contouring of prostate gland with planning computed tomography (CT) images, in the absence of magnetic resonance imaging (MRI). Materials and methods Five radiation oncologists (ROs) performed two rounds of prostate gland contouring (single-blinded) on CT-alone and CT/TPUS datasets obtained from 10 patients who underwent TPUS-guided external beam radiotherapy. Parameters include prostate volume, DICE similarity coefficient (DSC) and centroid position. Wilcoxon signed-rank test assessed the significance of inter-modality differences, and the intraclass correlation coefficient (ICC ) reflected inter- and intra-observer reliability of parameters. Results Inter-modality analysis revealed high agreement (based on DSC and centroid position) of prostate gland contours between CT-alone and CT/TPUS. Statistical significant difference was observed in the superior-inferior direction of the prostate centroid position (p = 0.011). All modalities yielded excellent inter-observer reliability of delineated prostate volume with ICC > 0.9, mean DSC > 0.8 and centroid position: CT-alone (ICC = 1.000) and CT/TPUS (ICC = 0.999) left-right (L/R); CT-alone (ICC = 0.999) and CT/TPUS (ICC = 0.998) anterior-posterior (A/P); CT-alone (ICC = 0.999) and CT/TPUS (ICC = 1.000) superior-inferior (S/I). Similarly, all modalities yielded excellent intra-observer reliability of delineated prostate volume, ICC > 0.9 and mean DSC > 0.8. Lastly, intra-observer reliability was excellent on both imaging modalities for the prostate centroid position, ICC > 0.9. Conclusion TPUS does not add significantly to the amount of anatomical information provided by CT images. However, TPUS can supplement planning CT to achieve a higher positional accuracy in the S/I direction if access to CT/MRI fusion is limited.
A Pilot Study of Nutrition Management in the Department of Pediatric Oncology Department of a Hospital in Kazakhstan

Maintaining optimal nutritional status is important for children with cancer because it can affect clinical outcomes. This study aimed to prospectively study clinical practices in children's cancer departments to improve the nutritional health of children and adolescents receiving cancer treatment. Currently, there are no unified and harmonized protocols for assessing the nutritional status and nutritional support of children in pediatric wards in Kazakhstan. According to WHO research, most of the children admitted to hospitals already have significant nutritional status disorders, such as exhaustion and malnutrition, lipid metabolism disorders, hypovitaminosis and anemia. 200 children with cancer aged 6 months to 17 years (n=200) were recruited. Dietary data and other relevant anthropometric and biochemical data were collected using a data collection form validated and developed by the researchers. Data processing is still in progress. They were randomly allocated either to a treatment group or a control group (age-matched and gender matched). The treatment group received nutritional advice and support and the control group received the standard treatment. A significant decrease in the intake of protein and energy with the consumed diets, which are prescribed by doctors in daily practice, was revealed, which is a risk factor for the development of severe nutritional disorders (p>0.5). Patients who were assigned nutritional support in addition to the General diets during the study had higher nutrient intake. Comparing week zero with subsequent weeks of nutritional support, children in the main group showed significant improvements in the thickness of the triceps skin fold (P<0.001), the circumference of the middle shoulder (P<0.001), and the circumference of the arm muscles (P<0.001), showing that performing nutritional support is better for the evolution of nutrition (P<0.01). Proper use of nutritional support in children with cancer can prevent the development of nutritional deficiencies and associated risks. To improve nutrition management, attention should be paid to nutrition education and assessment tools for doctors and nurses.
Simultaneous Viewpoint- and Condition-Invariant Loop Closure Detection Based on LiDAR Descriptor for Outdoor Large-Scale Environments

Loop closure detection is the crucial issue of simultaneous localization and mapping in the field of autonomous driving and robotics. In outdoor large-scale and complex environments, the existing LiDAR-based methods still inevitably suffer from viewpoint, condition changes, and perceptual aliasing. To effectively fill the aforementioned drawbacks, in this article, a novel LiDAR-based multimodule cascaded Siamese convolutional neural networks is developed, named MMCS-Net, which simulates the human-eye mechanism to extract more discriminative and generic feature descriptors. The MMCS-Net is mainly composed of three complementary modules: Siamese full convolutional (CA_SFC) module with cascaded attention, rotation-invariant and topological feature enhancement (RT_E) module, and feature uniqueness enhancement and aggregation compression (UE_AC) module. In particular, the graph structure employed in RT_E can explicitly encode the local topological correlations of point clouds in terms of intensity and geometric clues in parallel. Extensive comparative experiments on KITTI, NCLT, LGSVL, and real vehicle datasets prove that our proposed method outperforms the state-of-the-art methods, and shows high robustness while ensuring the real-time requirements of resource-constrained robots.
Research on Precision Marketing Strategy and Personalized Recommendation Method Based on Big Data Drive

In view of the explosive growth of big data technology, precision marketing and personalized recommendation have also received the dividends of big data technology. The traditional extensive operation has not effectively combined the products of businesses with the needs of users, and the success rate of marketing is low, which has led to the crisis that operators may become “pipelines. ” To meet the personalized needs of users and precision, marketing technology has been developed. This paper is based on big data technology and personalized recommendation algorithm theory and takes the marketing strategy of the actual telecommunications industry as an empirical research method. The experimental results verify that the analysis model based on big data has a good recommendation effect in precision marketing and personalized recommendation and confirm the advantages of the recommendation algorithm based on user collaborative filtering in personalized recommendation algorithm.
A Physics-Assisted Deep Learning Microwave Imaging Framework for Real-Time Shape Reconstruction of Unknown Targets

In this article, an innovative approach to microwave imaging, which combines a qualitative imaging technique and deep learning (DL), is presented. The goal is to develop a tool for reliable and user-independent retrieval of the shape of unknown targets from the knowledge of the scattered fields. Qualitative imaging methods are powerful inverse scattering tools, as they provide morphological information in real time. However, their outcome is a continuous map, which has to be hard-thresholded to clearly identify the targets. This thresholding unavoidably results in case-dependent, often user-biased, results. To deal with this issue, a DL approach, based on a physics-assisted deep neural network, is proposed to automatically classify image pixels, i.e., to generate binary masks, separating the targets (foreground) from the background. In particular, the proposed network binarizes the output of a qualitative imaging inversion technique known as the orthogonality sampling method. For the sake of comparison, a DL method is also exploited, which generates the binary masks directly from the scattered fields without any qualitative imaging aid. A quantitative assessment of the performances of both methods and a test on experimental data are provided.
Quantifying the Visibility of Periodic Flicker

ABSTRACT Three experiments that measure the visibility of periodic flicker are presented. Temporal light modulations were presented to a large visual field to make the results valid for general lighting applications. In addition, the experiments were designed to control for flicker adaptation. In the first experiment, the sensitivity of human observers to light modulations with a sinusoidal waveform at several temporal frequencies up to 80 Hz was measured. The results showed that the sensitivity to flicker (that is, the inverse of the Michelson contrast) is as high as 500 for frequencies between 10 and 20 Hz, which is more than twice the maximum sensitivity reported in the literature. In the second experiment, the sensitivity to flicker for light modulations with complex waveforms, composed of two or three frequency components, was measured. Sensitivity to flicker was found to be higher than the sum of the sensitivities of the individual frequency components of the complex waveform. Based on these results, we defined the flicker visibility measure (FVM), predicting flicker visibility by a weighted summation of the relative energy of the frequency components of the waveform. In the third experiment, sensitivity to realistic waveforms (that is, waveforms of light emitting diode [LED] light sources available on the market) was measured. The flicker predictions of FVM showed a high correlation with the experimental data, in contrast to some other existing flicker measures, including flicker index and percent flicker, demonstrating the usefulness of the measure to objectively assess the visibility of periodic flicker for lighting applications.
Technology aware circuit design for smart sensors on plastic foils

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Study of P-Phenylenediamine (PPD) Concentrations after Hair Dye Mixing: A Call for Safety Reassessment

Para-phenylenediamine (PPD) is a chemical that is widely used in hair dyes. Multiple safety and regulatory agencies have categorized PPD as a potent sensitizer. In addition, PPD has carcinogenicity and genotoxicity attributes and, consequently, it is regulated at a maximal concentration of 2.0%. The aim of this study was to test whether the limit for PPD is surplus, and hence whether the consumer may be exposed to unnecessarily PPD levels. Experimentally, the analysis of PPD was performed using HPLC, where method validation and an inter-laboratory comparison test (ILC) were conducted to evaluate method performance. Thirty-three commercial products were analyzed, and five products were chosen to study the unconsumed PPD. Successfully, the implemented method confirmed its suitability and validity for the determination of PPD. For ILC results, PPD levels were 0.97 ± 0.04% and 0.92 ± 0.02%, quantified by our laboratory and an accredited laboratory, respectively. For all products, the initial concentration (T0) of PPD was lower than the regulatory limit. After 45 min, the content of PPD significantly reduced compared to T0. One product showed unconsumed PPD to be as high as 96% following the recommended dyeing time. In conclusion, the existence of high levels of unreacted PPD increases the likelihood of allergic events and elevates the risk of PPD-related chemicals. Collaborative efforts between industries, regulatory bodies, and health-related decision makers are deemed necessary to establish safe concentrations for PPD.
Motives for physical exercise in older adults from different contexts: typology and organization in practice

This study was undertaken to understand the reasons related to typology and organization in physical practice taking into account the perceptions of the older adults. Four focus groups were conducted with a total of 39 older adults. The study participants consisted of 30 women and 9 men (mean age of men and women was M = 68 and 67.1, SD = 4.7 years, respectively), from three contexts. These environments were rural area, a neighbourhood at risk of exclusion and a high socio-economic urban context. The methodological analysis is inductive, emergent, delineating the speeches from the specific to the general, through the process of codifying the grounded theory. Several factors appeared after the emergent analysis of the interventions of older adults. In this line, social support and goal setting were prominent factors that served as facilitators for adherence to physical exercise programs. The encouragement and company of others were factors that facilitated adherence to the physical exercise. Relating to sex differences, older male adults prefer to exercise alone, compared to women. Researchers and health professionals can use these results to tailor motivational messages and promote health-enhancing behavioural interventions for older adult populations.
Adsorptive Capacity Study of Mesoporous Carbon-Doped TiO2 and its Application in Cu(II) Removal from Water

Mesoporous carbon-doped TiO2 (MCT) was synthesized via a template-free method in combination with solvothermal treatments. The structure, particle size and composition of this adsorbent were measured using XRD, TEM and XPS. Also, the usability of isothermal models for Cu (II) onto mesostructured adsorbent was implicated in these cases. The adsorptive capacity of MCT for Cu (II) was assessed using ICP-MS technique. The maximal adsorptive capacity was 16.9 mg g-1, and the ion-exchange action of Cu (II) was found to be the predominant adsorption.