Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct observation of hyperpolarization breaking through the spin diffusion barrier

The resurgence of nuclear hyperpolarization brings new insights into spin diffusion processes near paramagnetic centers. Dynamic nuclear polarization (DNP) is a widely used tool for overcoming the low intrinsic sensitivity of nuclear magnetic resonance spectroscopy and imaging. Its practical applicability is typically bounded, however, by the so-called “spin diffusion barrier,” which relates to the poor efficiency of polarization transfer from highly polarized nuclei close to paramagnetic centers to bulk nuclei. A quantitative assessment of this barrier has been hindered so far by the lack of general methods for studying nuclear polarization flow in the vicinity of paramagnetic centers. Here, we fill this gap and introduce a general set of experiments based on microwave gating that are readily implemented. We demonstrate the versatility of our approach in experiments conducted between 1.2 and 4.2 K in static mode and at 100 K under magic angle spinning (MAS)—conditions typical for dissolution DNP and MAS-DNP—and directly observe the marked dependence of polarization flow on temperature.
Skipping breakfast is associated with nutrient gaps and poorer diet quality among adults in the United States

Habitual breakfast consumption is associated with decreased risk for chronic disease as well as greater micronutrient intakes, espe-cially folate, calcium, iron, phosphorus, and vitamins A, B1, B2, B3, C, and D (1). Although breakfast is prioritized for children, many adults skip breakfast on a frequent basis (2). Suboptimal intakes of such micronutrients may exacerbate chronic disease devel-opment (3). Therefore, this study aimed to explore the differences in energy and nutrient intakes as well as diet quality across all meals for adults who consume versus skip breakfast. We hypothesized that adults who consume breakfast have better diet quality than breakfast skippers. Data were examined from 30,889 adults, 19 years or older, from the 2005 – 2016 National Health and Nutrition Examination Survey (NHANES). Participants were non-pregnant, non-institutionalized US citizens. The 24-hour dietary recall using the validated auto-mated multiple-pass method was used to record all intakes from midnight to midnight from the previous day. Recall data were trans-formed into nutrient estimates and MyPlate equivalents using the Food and Nutrient Database for Dietary Studies and Food Patterns Equivalents Database, respectively. Participants self-designated eating occasions (breakfast, lunch, dinner, snacks). Dietary intakes were aggregated across eating occasions to estimate intakes from each meal. Adults were classi ﬁ ed as breakfast skippers if they did not report food or beverage intake at breakfast during the recall. Micronutrient intakes for the total day were compared to the Estimated Average Requirement (EAR) or Adequate Intake (AI). The Healthy Eating Index-2015 was used to estimate diet quality compared to the
Vitamin D concentration, body mass index, ethnicity and SARS-CoV-2/COVID-19: initial analysis of the first- reported UK Biobank Cohort positive cases (n 1474) compared with negative controls (n 4643)

There is an urgent need to assess risk factors affecting individual likelihood of contracting the novel SARS-CoV-2 virus, and development of COVID-19. One potential risk factor is vitamin D de ﬁ ciency (1) . Vitamin D is important for immune defence against pathogens as it promotes macrophage antimicrobial responses and the regulation of antigen-presenting dendritic cells and suppressor T-cells (2) . However, it is unclear whether 25(OH)D concentration is associated with risk of contracting SARS-CoV-2 and/or developing COVID-19. We aimed to assess whether there is an association between serum 25(OH)D status and odds of testing positive for SARS-CoV-2, when controlling for confounders such as body mass index (BMI) and ethnicity. We used data from the UK Biobank, including n 1474 SARS-CoV-2 positive cases and n 4643 SARS-CoV-2 negative controls. The UK Biobank study was originally approved by the UK North West Multi-Centre Research Ethics Committee (MREC); application 11/NW/0382, with written severely vitamin D de ﬁ cient and results may differ in populations with 25(OH)D < 25 nmol/L. As the number of UK Biobank cases increases, we will expand our model to assess the association between 25(OH)D concentration and COVID-19-attributed mortality and symptom severity. Biobank (application DKDW and on the individual participant
A 6‐Month Report on the Impact of the Organ Procurement and Transplantation Network/United Network for Organ Sharing Acuity Circles Policy Change

On February 4th , 2020, the Organ Procurement and Transplantation Network (OPTN)/United Network for Organ Sharing (UNOS) implemented a new liver and intestinal organ distribution system called the "Acuity Circles" (AC) model. The primary impetus for this change was concern that DSA and regional boundaries were a major contributor of geographic disparities in liver transplantation (LT). 1.
Review: Obesity and COVID-19: A Detrimental Intersection

Obesity has been recognized as an independent risk factor for critical illness and major severity in subjects with coronavirus disease 2019 (COVID-19). The role of fat distribution, particularly visceral fat (often linked to metabolic abnormalities), is still unclear. The adipose tissue represents a direct source of cytokines responsible for the pathological modifications occurring within adipose tissue in obese subjects. Adipokines are a crucial connection between metabolism and immune system: their dysregulation in obesity contributes to chronic low-grade systemic inflammation and metabolic comorbidities. Therefore the increased amount of visceral fat can lead to a proinflammatory phenotypic shift. This review analyzes the interrelation between obesity and COVID-19 severity, as well as the cellular key players and molecular mechanisms implicated in adipose inflammation, investigating if adipose tissue can constitute a reservoir for viral spread, and contribute to immune activation and cytokines storm. Targeting the underlying molecular mechanisms might have therapeutic potential in the management of obesity-related complications in COVID-19 patients.
High-Resolution Analysis Identifies High Frequency of KIR-A Haplotypes and Inhibitory Interactions of KIR With HLA Class I in Zhejiang Han

Killer cell immunoglobulin-like receptors (KIR) interact with human leukocyte antigen (HLA) class I molecules, modulating critical NK cell functions in the maintenance of human health. Characterizing the distribution and characteristics of KIR and HLA allotype diversity across defined human populations is thus essential for understanding the multiple associations with disease, and for directing therapies. In this study of 176 Zhejiang Han individuals from Southeastern China, we describe diversity of the highly polymorphic KIR and HLA class I genes at high resolution. KIR-A haplotypes, which carry four inhibitory receptors specific for HLA-A, B or C, are known to associate with protection from infection and some cancers. We show the Chinese Southern Han from Zhejiang are characterized by a high frequency of KIR-A haplotypes and a high frequency of C1 KIR ligands. Accordingly, interactions of inhibitory KIR2DL3 with C1+HLA are more frequent in Zhejiang Han than populations outside East Asia. Zhejiang Han exhibit greater diversity of inhibitory than activating KIR, with three-domain inhibitory KIR exhibiting the greatest degree of polymorphism. As distinguished by gene copy number and allele content, 54 centromeric and 37 telomeric haplotypes were observed. We observed 6% of the population to have KIR haplotypes containing large-scale duplications or deletions that include complete genes. A unique truncated haplotype containing only KIR2DL4 in the telomeric region was also identified. An additional feature is the high frequency of HLA-B*46:01, which may have arisen due to selection pressure from infectious disease. This study will provide further insight into the role of KIR and HLA polymorphism in disease susceptibility of Zhejiang Chinese.
Circulating Survivin Protein Levels in Lung Cancer Patients Treated With Platinum-Based Chemotherapy

The survivin protein contributes to the development and progression of tumors. Protein expression and mRNA levels correlate with clinicopathological parameters and survival of cancer patients. Our purpose was to evaluate whether circulating survivin levels have any diagnostic or predictive value in lung cancer. 118 patients with advanced stage lung cancer participated in our study. 53 suffered from adenocarcinoma (ADC), 33 from squamous cell carcinoma (SqCC), and 32 from small cell lung cancer (SCLC). We also enrolled 21 control subjects. Blood samples were collected before and after two cycles of chemotherapy. We measured survivin concentrations with ELISA. Non-parametric tests were used for analysis. We did not find significant difference in survivin levels between patients and control subjects (17.19/0–829.74/vs. 49.13/0–165.92/pg/ml; p = 0.07). We found lower survivin concentrations in patients with SqCC (0/0–171.24/pg/ml) than in those with ADC (24.94/0–626.46 pg/ml) and SCLC (45.51/0–829.74/pg/ml) (ADC vs. SqCC p < 0.0001, ADC vs. SCLC p = 0.0405, SqCC vs. SCLC p < 0.0001). Survivin levels were higher in stage IV patients than in patients without distant metastases (p = 0.0061), and concentrations were progressively higher with increasing number of metastatic organ sites (p = 0.04). We observed a decrease in survivin levels in ADC patients after platinum plus pemetrexed chemotherapy (26.22/0–626.46/pg/ml before vs. 0/0–114.36/pg/ml after; p = 0.01). Neither progression-free nor overall survival correlated with survivin levels at baseline. Our data imply that survivin may be involved in the development of metastases and it might be used as a biomarker of disease progression. However, circulating survivin concentrations do not predict survival of patients with lung cancer.
Personal Heart Health Monitoring Based on 1D Convolutional Neural Network

The automated detection of suspicious anomalies in electrocardiogram (ECG) recordings allows frequent personal heart health monitoring and can drastically reduce the number of ECGs that need to be manually examined by the cardiologists, excluding those classified as normal, facilitating healthcare decision-making and reducing a considerable amount of time and money. In this paper, we present a system able to automatically detect the suspect of cardiac pathologies in ECG signals from personal monitoring devices, with the aim to alert the patient to send the ECG to the medical specialist for a correct diagnosis and a proper therapy. The main contributes of this work are: (a) the implementation of a binary classifier based on a 1D-CNN architecture for detecting the suspect of anomalies in ECGs, regardless of the kind of cardiac pathology; (b) the analysis was carried out on 21 classes of different cardiac pathologies classified as anomalous; and (c) the possibility to classify anomalies even in ECG segments containing, at the same time, more than one class of cardiac pathologies. Moreover, 1D-CNN based architectures can allow an implementation of the system on cheap smart devices with low computational complexity. The system was tested on the ECG signals from the MIT-BIH ECG Arrhythmia Database for the MLII derivation. Two different experiments were carried out, showing remarkable performance compared to other similar systems. The best result showed high accuracy and recall, computed in terms of ECG segments and even higher accuracy and recall in terms of patients alerted, therefore considering the detection of anomalies with respect to entire ECG recordings.
Design and Comparison of Image Hashing Methods: A Case Study on Cork Stopper Unique Identification

Cork stoppers were shown to have unique characteristics that allow their use for authentication purposes in an anti-counterfeiting effort. This authentication process relies on the comparison between a user’s cork image and all registered cork images in the database of genuine items. With the growth of the database, this one-to-many comparison method becomes lengthier and therefore usefulness decreases. To tackle this problem, the present work designs and compares hashing-assisted image matching methods that can be used in cork stopper authentication. The analyzed approaches are the discrete cosine transform, wavelet transform, Radon transform, and other methods such as difference hash and average hash. The most successful approach uses a 1024-bit hash length and difference hash method providing a 98% accuracy rate. By transforming the image matching into a hash matching problem, the approach presented becomes almost 40 times faster when compared to the literature.
Critical Aspects of Person Counting and Density Estimation

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r. t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.
Psychophysical Determination of the Relevant Colours That Describe the Colour Palette of Paintings

In an early study, the so-called “relevant colour” in a painting was heuristically introduced as a term to describe the number of colours that would stand out for an observer when just glancing at a painting. The purpose of this study is to analyse how observers determine the relevant colours by describing observers’ subjective impressions of the most representative colours in paintings and to provide a psychophysical backing for a related computational model we proposed in a previous work. This subjective impression is elicited by an efficient and optimal processing of the most representative colour instances in painting images. Our results suggest an average number of 21 subjective colours. This number is in close agreement with the computational number of relevant colours previously obtained and allows a reliable segmentation of colour images using a small number of colours without introducing any colour categorization. In addition, our results are in good agreement with the directions of colour preferences derived from an independent component analysis. We show that independent component analysis of the painting images yields directions of colour preference aligned with the relevant colours of these images. Following on from this analysis, the results suggest that hue colour components are efficiently distributed throughout a discrete number of directions and could be relevant instances to a priori describe the most representative colours that make up the colour palette of paintings.
Comparative analysis of immunosuppressive therapies for myelin oligodendrocyte glycoprotein antibody-associated optic neuritis: a cohort study

Aims The optimal immunosuppressive therapy (IST) in patients with myelin oligodendrocyte glycoprotein antibody-associated optic neuritis (MOG-ON) remains uncertain. This study aimed to observe the disease course of MOG-ON and evaluate the therapeutic efficacy and tolerability of conventional immunosuppressants through Chinese cohort analysis. Methods This bidirectional cohort study included 121 patients with MOG-ON between January 2015 and December 2018. The clinical features and annualised relapse rate (ARR) of patients with and without IST were analysed. Results The median age at onset was 17.5 years, and the sex ratio (F:M) was 1.24. Of 121 patients, 77 patients relapsed and 61 patients were younger than 18 years at disease onset. The overall median ARR of 63 patients in the non-IST group was 0.5, with 46.0% patients showing relapse at a median follow-up of 33.5 months. In the IST group, the ARR decreased from 1.75 pre-IST to 0.00 post-IST in 53 patients who received IST exceeding 6 months, with 20.8% patients showing relapse at a median follow-up of 23.8 months. The relapse rates of patients treated with rituximab (RTX) and mycophenolate mofetil (MMF) were not statistically different, but the rate of discontinuation was significantly lower in the RTX-treated group (18.2% vs 57.7%, p=0.0017). Conclusion This study provides Class III evidence that both MMF and RTX may lower disease activity in patients with MOG-ON, and RTX showed better tolerability than MMF. However, observation after a single attack remains a good option because less than half of patients not on treatment suffered a relapse.
Bevacizumab, carboplatin, and paclitaxel in the first line treatment of advanced ovarian cancer patients: the phase IV MITO-16A/MaNGO-OV2A study

Objective To explore the clinical and biological prognostic factors for advanced ovarian cancer patients receiving first-line treatment with carboplatin, paclitaxel, and bevacizumab. Methods A multicenter, phase IV, single arm trial was performed. Patients with advanced (FIGO (International Federation of Gynecology and Obstetrics) stage IIIB-IV) or recurrent, previously untreated, ovarian cancer received carboplatin (AUC (area under the curve) 5), paclitaxel (175 mg/m2) plus bevacizumab (15 mg/kg) on day 1 for six 3-weekly cycles followed by bevacizumab single agent (15 mg/kg) until progression or unacceptable toxicity up to a maximum of 22 total cycles. Here we report the final analysis on the role of clinical prognostic factors. The study had 80% power with a two-tailed 0.01 α error to detect a 0.60 hazard ratio with a factor expressed in at least 20% of the population. Both progression-free and overall survival were used as endpoints. Results From October 2012 to November 2014, 398 eligible patients were treated. After a median follow-up of 32.3 months (IQR 24.1–40.4), median progression-free survival was 20.8 months (95% CI 19.1 to 22.0) and median overall survival was 41.1 months (95% CI 39.1 to 43.5). Clinical factors significantly predicting progression-free and overall survival were performance status, stage, and residual disease after primary surgery. Neither baseline blood pressure/antihypertensive treatment nor the development of hypertension during bevacizumab were prognostic. There were two deaths possibly related to treatment, but no unexpected safety signal was reported. Conclusions Efficacy and safety of bevacizumab in combination with carboplatin and paclitaxel and as maintenance were comparable to previous data. Hypertension, either at baseline or developed during treatment, was not prognostic. Performance status, stage, and residual disease after primary surgery remain the most important clinical prognostic factors. Trial registration number EudraCT 2012-003043-29; NCT01706120.
Millimeter-Wave Wide-Band Bandpass Filter in CMOS Technology Using a Two-Layered Highpass-Type Approach With Embedded Upper Stopband

An on-chip millimeter-wave (mm-wave) broad-band bandpass filter (BPF) developed in bulk CMOS technology is reported. It is based on a two-layered implementation in which the circuit structure patterned in the top layer exhibits a highpass-type filtering response, whereas an upper stopband is created by the bottom-layer cell when coupled to the top-layer one to obtain a composite overall quasi-elliptic-type wide-band BPF functionality. The locations of the transmission zeros (TZs), which confer sharp-rejection capabilities to the overall frequency response, can be flexibly adjusted with the values of the capacitors that are employed in both layers. A simplified equivalent lumped-element circuit model of the proposed wide-band BPF approach is provided and applied to multi-stage BPF arrangements for higher-selectivity designs. Furthermore, for practical-demonstration purposes, an on-chip passive-integrated single-stage broad-band BPF prototype on silicon with 34.5-GHz center frequency and 61.2% 3-dB relative bandwidth is designed, manufactured, and characterized.
Soft Twisting Pneumatic Actuators Enabled by Freeform Surface Design

Twisting motion plays an important role in kinematics of soft robots. However, current twisting actuators usually suffer from complex mechanical design with multiple materials and undesired coupling with bending and stretching motions. In this letter, we propose a new class of soft twisting pneumatic actuators that purely rely on the freeform chamber geometry to achieve large bi-directional twisting rotations. The freeform chamber surface integrates geometric flexibility in the cross section, lateral profile, and axial chirality, which are parameterized as design variables. We develop a finite element analysis model and investigate the effect of the geometry parameters on the actuators’ mechanical behavior. The actuator naturally undergoes combined twisting and axial motions, and achieves a bi-directional twisting rotation of 116.7<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula>, blocking torque of 0.81 N <inline-formula><tex-math notation="LaTeX">$\cdot$</tex-math></inline-formula> m, and energy density of 1907 J/m <inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula>, well in line with the theoretical prediction. When it is constrained from axial motions, the actuator delivers pure twisting motion, achieving a bi-directional twisting rotation of 72.5<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula>, blocking torque of 0.56 N<inline-formula><tex-math notation="LaTeX">$\cdot$</tex-math></inline-formula> m, and energy density of 925 J/m<inline-formula><tex-math notation="LaTeX">$^3$</tex-math></inline-formula>. This letter represents an important step toward leveraging the full potential of the freeform geometry design to create novel compact soft-bodied actuators and robots.
Emerging Technologies: Challenges and Opportunities for Logic Synthesis

In computer engineering, logic synthesis is a process by which an abstract specification of desired circuit behavior is turned into a design implementation in terms of logic gates. Historically, logic synthesis was tightly related to the physical implementation of the logic gates. Nowadays, pushed by the forecasted end of Moore’s law, several emerging technologies (e.g., nanodevices, optical computing, quantum computing) are candidates to either replace or co-exist with the de facto standard CMOS technology. The main consequence of the rising of those emerging technologies is that the logic synthesis has to face new issues and, at the same time, exploits new opportunities. The goal of this paper is thus to present three emerging technologies (Vertical Nanowire Field Effect Transistors, Ferroelectric Transistors, and Memristors), how to use them to implement logic gates, and the main challenges and issues for the logic synthesis.