Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of almond consumption on lipid profile in patients with type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials.

The aim of this meta-analysis was to assess the effects of almond consumption on the lipid profiles of type 2 diabetes mellitus (T2DM) patients. Eligible trials were searched from four electronic databases until Jan 2020. Five eligible articles were included in the final quantitative analysis. Overall, meta-analysis could not show any beneficial effect of almond consumption on total cholesterol (TC) weighted mean difference (WMD: 0.65 mg/dL, 95% CI: -7.52-8.82, p = .87), triglyceride (TG; WMD: 1.59 mg/dL, 95% CI: -21.77-24.96, p = .89), low-density lipoprotein cholesterol (LDL-C; WMD: -5.40 mg/dL, 95% CI: -13.30-2.50, p = .18), and high-density lipoprotein cholesterol (HDL-C; WMD: 1.57 mg/dL, 95% CI: -0.95-4.10, p = .22). However, subgroup analyses showed that serum LDL-C levels were significantly reduced in trials administered > 50 g/d almond. The data suggest that consumption of almond could not improve lipid profile in patients with T2DM.
Cultural Intelligence as a Core Competence of Inclusive Leadership

Abstract We live and work in a fast-paced multicultural world where change is becoming a new constant. In this context, in which racially and ethnically diverse companies are 35% more likely to perform better, inclusive leadership’s role becomes crucial. Knowing to handle and fructify diversity and inclusion (DI) is now crucial for any multicultural businesses’ expansion and development. On the other hand, cultural intelligence (CQ) refers to relating and working effectively and efficiently in culturally diverse situations. The purpose of this paper is to study and present a systematic bibliometric literature review focusing on cultural intelligence as a core enabler of inclusive leadership (IL). Our findings, rooted in the Web of Science Core Collection database and powered by VOSviewer bibliometric software, demonstrate that cultural intelligence is not only a main competence for both multinational leadership and global management but also a primary facilitator of inclusive leadership. Concretely, this research visually indicates a comprehensive direct link of the fields relating to CQ on one side and the ones related to multicultural and inclusive leadership on the other side. The bibliometric analysis is supposed to provide a solid reference for practitioners and researchers in multinational inclusive leadership’s new needed competencies
Primary and secondary sources of
ambient
formaldehyde
in the 
Yangtze River Delta based on OMPS observation

Abstract. Formaldehyde (HCHO) in the ambient air not only causes cancer but also is an ideal indicator for volatile organic compounds (VOCs) which are major precursors of ozone (O3) and secondary organic aerosol (SOA) near the surface. It is meaningful to differentiate between direct emission and secondary formation for HCHO pollution control and sensitivity study of O3 production. However, the understanding of the sources of HCHO is still poor in China, due to limited measurements of HCHO in the field, both spatially and temporally. In this study, tropospheric HCHO vertical column densities (VCDs) in the Yangtze River Delta (YRD), East China where HCHO pollution is serious were retrieved from Ozone Mapping and Profiler Suite (OMPS) onboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite from 2014 to 2017, and kept good agreement with the tropospheric HCHO columns measured by ground-based high resolution Fourier transform infrared spectrometry (FTS) with the correlation coefficient (R) of 0.78. Based on this, the cancer risk was estimated nationwide and in the YRD region. At least, 7840 people in the YRD region would develop cancer in their lives due to outdoor HCHO exposure, which occupied 23.4 % of total national cancer risk. Besides, the contributions of primary and secondary sources were apportioned, combining with primary and secondary tracers from surface observation. Overall, HCHO from secondary formation contributed most to ambient HCHO and can be regarded as the indication of the VOCs reactivity in Hangzhou and urban areas of Nanjing and Shanghai from 2015 to 2017, due to strong correlation between total HCHO and secondary HCHO. At industrial sites in Nanjing, primary emission influenced most to ambient HCHO in 2015 and showed an obvious decreasing trend. Seasonally, HCHO from secondary formation reached the maximum in summer and minimum in winter. In the spring, summer, and autumn, secondary formation played a curial effect on variation of ambient HCHO in urban regions of Nanjing, Hangzhou, and Shanghai; while in the winter the contribution from secondary formation became less significant. The understanding of the variation of the primary and secondary contributions to ambient HCHO is in favor for a better understanding the role of HCHO in atmospheric chemistry and formulating effective control measures to decrease HCHO pollution and cancer risk.
Effect of maturity stages on shelf life of papaya (Carica papaya L.)

An experiment using cv. Taiwan was 786 laid out in factorial completely randomized design with thirty treatments and three replications was, carried out at Laboratory of Horticulture Section, College of Agriculture, Dhule (M.S.) during 2017. The experiment comprised of three factors viz. two maturity stages (25% mature and 50% mature), dipping them in aqueous solutions of spermine (1.0 mM and 2.0 mM) and calcium lactate (1% and 2%) for 5 minutes and drying for 30 minutes at room temperature, three packaging materials (newspaper, shrink film and polyethylene bags) were used. Results indicated a significant impact of interaction among maturity stages, spermine and calcium lactate and packaging material on all parameters included in the study. When considered interaction, twenty five percent mature fruits dipped in (2.0 mM) spermine with shrink packaging had the minimum physiological loss in weight. This treatment also recorded the maximum peel to pulp ratio, fruit firmness. The maximum shelf life of 16 days without sacrificing organoleptic quality by manipulating the time of harvesting, packaging and application of spermine.
The seasonality of three childhood infections in a pre-industrial society without schools

Background: The burden of many infectious diseases varies seasonally and a better understanding of the drivers of infectious disease seasonality would help to improve public health interventions. For directly transmitted highly-immunizing childhood infections, the leading hypothesis is that seasonality is strongly driven by social gatherings imposed by schools, with maxima and minima during school terms and holidays respectively. However, we currently have a poor understanding of the seasonality of childhood infections in societies without schools and whether these are driven by human social gatherings. Here, we used unique nationwide data consisting of >40 epidemics over 100 years in 18th and 19th century Finland, an agricultural pre-health care society without schools, to (i) quantify the seasonality of three easily identifiable childhood infections, smallpox, pertussis and measles and (ii) test the extent to which seasonality of these diseases is driven by seasonal social gatherings. Methods: We quantified the seasonality of transmission using time series Suscpetibel-Infected-Recovery models, wavelet analyses and general additive mixed models. Results: We found that all three infections were seasonal and the seasonality patterns differed from those in industrialized societies with schools. Smallpox and measles showed high transmission in the first half of the year, but we could not associate this with seasonal human gatherings events. For pertussis, however, transmission was higher during social gathering events such as New Year and Easter. Conclusions: Our results show that the seasonality of childhood infections is more variable than previously described in other populations and indicate a pathogen-specific role of human social aggregation in driving the infectious disease dynamics. Funding: Academy of Finland (278751, 292368), Nordforsk (104910), the Ehrnrooth Foundation, the Finnish Cultural Foundation, the University of Turku Foundation and the Doctoral Programme in Biology, Geography and Geology, University of Turku.
Leveraging large multi-center cohorts of Alzheimer disease endophenotypes to understand the role of Klotho heterozygosity on disease risk

Two genetic variants (rs9536314 and rs9527025) in the Klotho gene, encoding a transmembrane protein, implicated on longevity and associated with brain resilience during normal aging, were recently shown to be associated with Alzheimer disease (AD) risk in cognitively healthy individuals that are APOE4 carriers. Specifically, the individuals heterozygous for this variant (KL-SVHET+), showed lower risk of developing AD. Furthermore, a neuroprotective effect of KL-VSHET+ has been suggested against amyloid burden for cognitively normal individuals. However, inconsistent associations and a smaller sample size of existing studies pose significant hurdles in drawing definitive conclusions. Here, we have performed a well-powered association analysis between KL-VSHET+ and five different AD endophenotypes; brain amyloidosis measured by positron emission tomography (PET) scans (n = 5,541) or cerebrospinal fluid A{beta} levels (CSF; n = 5,093), as well as biomarkers associated with tau pathology: the CSF Tau (n = 5,127), phosphorylated Tau (pTau; n = 4,778) and inflammation: CSF soluble triggering receptor expressed on myeloid cells 2 (sTREM2; n = 2,123) levels. Our results found nominally significant associations of KL-VSHET+ status with biomarkers for brain amyloidosis (e.g. CSF A{beta} positivity; odds ratio [OR] = 0.67 [95% CI, 0.55-0.78], {beta} = 0.72, P = 0.007) and tau pathology (e.g. biomarker negative for CSF Tau; OR = 0.39 [95% CI, 0.19-0.77], {beta} = -0.94, P = 0.007, and pTau; OR = 0.50 [95% CI, 0.27-0.96], {beta} = -0.68, P = 0.04) in elderly (60-80 years old) individuals that are cognitively normal and APOE4 carriers. Our work supports previous findings and suggests that the KL-VSHET+ on a APOE4 genotype background may exert a protective effect by modulating the A{beta}, Tau, and pTau burden and resulting cognitive decline in older controls susceptible to AD. The biological mechanism underlying APOE4 and KL-VSHET+ interaction and the neuroprotective effect of KL-related pathways against amyloid accumulation may warrant future investigation as a target for preclinical pharmacological studies to explore novel AD drug targets.
A Mixed Frequency BVAR for the Euro Area Labour Market

We introduce a Bayesian Mixed-Frequency VAR model for the aggregate euro area labour market that features a structural identification via sign restrictions. The purpose of this paper is twofold: we aim at (i) providing reliable and timely forecasts of key labour market variables and (ii) enhancing the economic interpretation of the main movements in the labour market. We find satisfactory results in terms of forecasting, especially when looking at quarterly variables, such as employment growth and the job finding rate. Furthermore, we look into the shocks that drove the labour market and macroeconomic dynamics from 2002 to early 2020, with a first insight also on the COVID-19 recession. While domestic and foreign demand shocks were the main drivers during the Global Financial Crisis, aggregate supply conditions and labour supply factors reflecting the degree of lockdown-related restrictions have been important drivers of key labour market variables during the pandemic.
Mutual Funds’ Reporting Frequency and Strategic Share Repurchases

We study the consequences of increased reporting frequency in a delegated asset management framework. We build on economic theory establishing that more frequent information about an agent's action increases the agent's career concerns and short-termism. Consistent with theory, we find that following a regulatory change that increased the reporting frequency of mutual funds' portfolio holdings, mutual funds are more likely to divest from firms that miss a quarterly earnings target. This suggests that funds managers become more short-term focused as missing an earning target leads to a negative market reaction. Next, we find that mutual fund managers' short-termism translates into portfolio firms' short-termism, as firms strategically increase share repurchases following the regulatory change. Finally, we find that increasing share repurchases pays off, as it significantly mitigates mutual funds' outflows. Our results shed light on how increased reporting frequency between mutual fund managers and their investors induce firms' short-termism.
LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time

When deploying deep learning models to a device, it is traditionally assumed that available computational resources (compute, memory, and power) remain static. However, real-world computing systems do not always provide stable resource guarantees. Computational resources need to be conserved when load from other processes is high or battery power is low. Inspired by recent works on neural network subspaces, we propose a method for training a"compressible subspace"of neural networks that contains a fine-grained spectrum of models that range from highly efficient to highly accurate. Our models require no retraining, thus our subspace of models can be deployed entirely on-device to allow adaptive network compression at inference time. We present results for achieving arbitrarily fine-grained accuracy-efficiency trade-offs at inference time for structured and unstructured sparsity. We achieve accuracies on-par with standard models when testing our uncompressed models, and maintain high accuracy for sparsity rates above 90% when testing our compressed models. We also demonstrate that our algorithm extends to quantization at variable bit widths, achieving accuracy on par with individually trained networks.
From Quantum Many-Body Systems to Ideal Fluids

We give a rigorous, quantitative derivation of the incompressible Euler equation from the many-body problem for $N$ bosons on $\mathbb{T}^d$ with binary Coulomb interactions in the semiclassical regime. The coupling constant of the repulsive interaction potential is $~1/(\varepsilon^2 N)$, where $\varepsilon \ll 1$ and $N\gg 1$, so that by choosing $\varepsilon=N^{-\lambda}$, for appropriate $\lambda>0$, the scaling is supercritical with respect to the usual mean-field regime. For approximately monokinetic initial states with nearly uniform density, we show that the density of the first marginal converges to 1 as $N\rightarrow\infty$ and $\hbar\rightarrow 0$, while the current of the first marginal converges to a solution $u$ of the incompressible Euler equation on an interval for which the equation admits a classical solution. In dimension 2, the dependence of $\varepsilon$ on $N$ is essentially optimal, while in dimension 3, heuristic considerations suggest our scaling is optimal. Our proof is based on a Gronwall relation for a quantum modulated energy with an appropriate corrector and is inspired by recent work of Golse and Paul arXiv:1912.06750 on the derivation of the pressureless Euler-Poisson equation in the classical and mean-field limits and of Han-Kwan and Iacobelli arXiv:2006.14924 and the author arXiv:2104.11723 on the derivation of the incompressible Euler equation from Newton's second law in the supercritical mean-field limit. As a byproduct of our analysis, we also derive the incompressible Euler equation from the Schr\"odinger-Poisson equation in the limit as $\hbar+\varepsilon\rightarrow 0$, corresponding to a combined classical and quasineutral limit.
Trident Pyramid Networks for Object Detection

Feature pyramids have become ubiquitous in multi-scale computer vision tasks such as object detection. Given their importance, a computer vision network can be divided into three parts: a backbone (generating a feature pyramid), a neck (refining the feature pyramid) and a head (generating the final output). Many existing networks operating on feature pyramids, named necks, are shallow and mostly focus on communication-based processing in the form of top-down and bottom-up operations. We present a new neck architecture called Trident Pyramid Network (TPN), that allows for a deeper design and for a better balance between communication-based processing and self-processing. We show consistent improvements when using our TPN neck on the COCO object detection benchmark, outperforming the popular BiFPN baseline by 0.5 AP, both when using the ResNet-50 and the ResNeXt-101-DCN backbone. Additionally, we empirically show that it is more beneficial to put additional computation into the TPN neck, rather than into the backbone, by outperforming a ResNet-101+FPN baseline with our ResNet-50+TPN network by 1.7 AP, while operating under similar computation budgets. This emphasizes the importance of performing computation at the feature pyramid level in modern-day object detection systems. Code is available at https://github.com/CedricPicron/TPN .
Effect of Visual Cues on Pointing Tasks in Co-located Augmented Reality Collaboration

Visual cues are essential in computer-mediated communication. It is especially important when communication happens in a collaboration scenario that requires focusing several users’ attention on a specific object among other similar ones. This paper explores the effect of visual cues on pointing tasks in co-located Augmented Reality (AR) collaboration. A user study (N = 32, 16 pairs) was conducted to compare two types of visual cues: Pointing Line (PL) and Moving Track (MT). Both are head-based visual techniques. Through a series of collaborative pointing tasks on objects with different states (static and dynamic) and density levels (low, medium and high), the results showed that PL was better on task performance and usability, but MT was rated higher on social presence and user preference. Based on our results, some design implications are provided for pointing tasks in co-located AR collaboration.
Emulating homoeostatic effects with metal-oxide memristors T-dependence

Memristor technologies have been rapidly maturing for the past decade to support the needs of emerging memory, artificial synapses⁠, logic gates⁠ and bio-signal processing⁠ applications. So far, however, most concepts are developed by exploiting the tuneable resistive state of memristors with other physical characteristics being ignored⁠. Here, we report on the thermal properties of metal-oxide memristors and demonstrate how these can be used to emulate a fundamental function of biological neurons: homoeostasis. We show that thermal control mechanisms, frequently dismissed for their generally slow and broad-brush granularity, may in fact be an appropriate approach to emulating similarly slow and broad-brush biological mechanisms due to their extreme simplicity of implementation. We further demonstrate that metal-oxide memristors can be utilised as thermometers and exhibit a programmable temperature sensitivity. This work paves the way towards future systems that employ the rich physical properties of memristors, beyond their electrical state-tuneability, to power a new generation of advanced electronics solutions.
Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding

Knowledge graph embedding involves learning representations of entities -- the vertices of the graph -- and relations -- the edges of the graph -- such that the resulting representations encode the known factual information represented by the knowledge graph and can be used in the inference of new relations. We show that knowledge graph embedding is naturally expressed in the topological and categorical language of \textit{cellular sheaves}: a knowledge graph embedding can be described as an approximate global section of an appropriate \textit{knowledge sheaf} over the graph, with consistency constraints induced by the knowledge graph's schema. This approach provides a generalized framework for reasoning about knowledge graph embedding models and allows for the expression of a wide range of prior constraints on embeddings. Further, the resulting embeddings can be easily adapted for reasoning over composite relations without special training. We implement these ideas to highlight the benefits of the extensions inspired by this new perspective.
Seasonality in Surface Quasigeostrophic Turbulence with Variable Stratification

Traditional surface quasigeostrophic theory assumes a vertically uniform stratification. As a consequence, the theory is only valid at horizontal scales smaller than 10 km (in the mid-latitude open ocean). At larger scales, the vertical structure of the ocean’s stratification becomes important. We present a generalization of surface quasigeostrophic theory that accounts for the ocean’s vertical stratification. We find that the seasonality of upper ocean stratification (in particular, the seasonality in mixed-layer depth) implies a seasonality in surface quasigeostrophic turbulence. Deep wintertime mixed-layers lead to a surface quasigeostrophic turbulence with strong buoyancy gradients, vortices spanning a wide range of scales, and with large-scale strain evident. In contrast, shallow summertime mixed-layers lead to a surface quasigeostrophic turbulence that is spatially local, lacks large-scale strain, and appears diffuse in space. The variable stratification theory also predicts a seasonal kinetic energy spectrum. If the submesoscales (1-100 km) are in the forward cascade of buoyancy variance, the theory predicts a wintertime spectrum proportional to k−7/3. In contrast, the lack of scale invariance across the submesoscales in summer causes the cascade theory to fail. However, simulations generally suggest a kinetic energy spectrum that is flatter in summer than in winter. This seasonality is opposite to that found in the ocean at the submesoscales. We conclude by suggesting that submesoscale interior quasigeostrophic turbulence must be seasonal as well because it also depends on the vertical structure of the ocean stratification.
Di-$\pi^0$ correlations in $p+$$p$, $p+$$\mathrm{Al}$ and $p+$$\mathrm{Au}$ collisions at $\sqrt{s_{\mathrm{_{NN}}}}$ = 200 GeV at STAR

The STAR Collaboration reports measurements of back-to-back azimuthal correlations of diπ0 produced at forward pseudorapidity (2.6 < η < 4.0) in p+p, p+Al and p+Au collisions at a center-of-mass energy per nucleon-nucleon pair of 200 GeV. A clear suppression of the correlated away-side yields is observed in p+Au and for the first time in p+Al collisions, compared with the p+p data. The enhanced suppression found in p+Au with respect to p+Al collisions exhibits the saturation scale (Qs ) dependence on the mass number A. The observed suppression of back-to-back pairs as a function of event activity and transverse momentum points to non-linear gluon dynamics arising at high parton densities.