Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Importance of Investigating Data Structure in Miniaturized NIR Spectroscopy Measurements of Food: The Case Study of Sugar

Alongside the increasing proofs of efficacy of miniaturized NIR instruments in food-related scenarios, it is progressively growing the number of end-users, even incentivized by the low-cost of the sensors. While attention is paid to the analytical protocol–from sampling to data collection, up to the data processing, the importance of error investigation in raw data is generally underestimated. Understanding the sources and the structure of uncertainty related to the raw data improves the quality of measurements and suggests the correct planning of the experiments, as well as helps in chemometric model development. The goal of chemometric modeling is to separate information from noise; therefore, a description of the nature of measurement error structure is necessary. Among the different approaches, we present the study of the Error Covariance Matrices (ECMs) and their decomposition in a bilinear structure as a powerful method to study the main sources of variability when using miniaturized NIR sensors in the actual way of use. Granulated and lump sugar samples were chosen as the case study and analyzed with two miniaturized spectrometers working in the NIR regions around 1350–2550 nm and 900–1750 nm, respectively, in dispersive reflectance mode. Results show that having some insights on multivariate measurement errors associated with spectra could be interesting in paving the way for several applications.
“Dual Anta-Inhibitors” of the A2A Adenosine Receptor and Casein Kinase CK1delta: Synthesis, Biological Evaluation, and Molecular Modeling Studies

Based on a screening of a chemical library of A2A adenosine receptor (AR) antagonists, a series of di- and tri-substituted adenine derivatives were synthesized and tested for their ability to inhibit the activity of the enzyme casein kinase 1 delta (CK1δ) and to bind adenosine receptors (ARs). Some derivatives, here called “dual anta-inhibitors”, demonstrated good CK1δ inhibitory activity combined with a high binding affinity, especially for the A2AAR. The N6-methyl-(2-benzimidazolyl)-2-dimethyamino-9-cyclopentyladenine (17, IC50 = 0.59 μM and KiA2A = 0.076 μM) showed the best balance of A2AAR affinity and CK1δ inhibitory activity. Computational studies were performed to simulate, at the molecular level, the protein–ligand interactions involving the compounds of our series. Hence, the dual anta-inhibitor 17 could be considered the lead compound of new therapeutic agents endowed with synergistic effects for the treatment of chronic neurodegenerative and cancer diseases.
Hard work will bear beautiful fruit. A comparison of two think-aloud protocol studies

In this article some of the results of two think-aloud protocol studies (Gerloff 1988 and Jââskelâinen 1990) are compared. The purpose of the comparison is to illustrate two findings: (I) that translation does not always get easier as professional experience increases, and (2) that professional translators do not always succeed better than non-professionals. The emphasis is on these somewhat disturbing observations because they are particularly suitable for illustrating tentative hypotheses about the role of affective factors in translation. These, in turn, have important implications for teaching translation.
Polarization control of open-circuit photovoltaic-photorefractive spatial solitons

An investigation is made of the influence of a general polarized background irradiance on the production of (1+1)D spatial solitons. In this context, general formulae are produced that permit the introduction of a linear polarization angle, or an elliptically polarized background intensity. The influence of the relative polarization between a focused beam and the background irradiance, on the transition from self-defocusing to self-focusing and the diffusion-induced self-bending angle is presented together with two types of polarization interface. The degree of control presented by the latter is shown in the form of computer simulations.
A band-limited signal extrapolation algorithm using pseudo inverse filtering and heuristic optimization

A bandlimited signal extrapolation algorithm is proposed. J.A. Cadzow's algorithm (1979) is modified to eliminate undesired outband spectra. An inverse filter stopband response is relaxed by adding small random numbers. A constrained heuristic optimization is suggested that can use arbitrary signal properties as constraints. Through numerical examples, it is shown how regularization techniques can improve SNR (signal-to-noise-ratio) by 20 dB. <<ETX>>
AI-Based Time-, Frequency-, and Space-Domain Channel Extrapolation for 6G: Opportunities and Challenges

The trend of using larger scale antenna arrays will continue toward 6G systems, where the number of antennas will be further scaled up to improve spectral efficiency. However, the increase in the number of antennas will bring new challenges to the physical layer, such as frequent feedback in high-speed mobile communications, multiband coexistence overhead from sub-6 (gigahertz) GHz to terahertz (THz), and energy consumption due to increased antenna components and circuits. In this article, we introduce artificial intelligence (AI)-based channel extrapolation to address these problems. Specifically, we divide the channel extrapolation into time, frequency, and space domains according to different application scenarios. The channel propagation characteristics that affect the extrapolation of each domain, such as the spatial consistency property (SCP), partial reciprocity, and spatial nonstationarity, are analyzed. The motivations for selecting various AI models in each domain are explained, and the performance of AI models is compared. Furthermore, we find the gain of cross-domain channel extrapolation based on transfer learning (TL). The simulation results show that the experience of the AI model cross different domains can be mutually reinforcing. Finally, we introduce several challenges for AI-based channel extrapolation, which can be regarded as potential research directions for realizing future AI-powered 6G systems.
Solution of Vandermonde Systems of Equations

We obtain in this paper a considerable improvement over a method developed earlier by Ballester and Pereyra for the solution of systems of linear equations with Vandermonde matrices of coefficients. This is achieved by observing that a part of the earlier algorithm is equivalent to Newton's interpolation method. This allows also to produce a progressive algorithm which is significantly more efficient than previous available methods. Algol-60 programs and numerical results are included. Confluent Vandermonde systems are also briefly discussed.
Long-time behaviour for porous medium equations with convection

Long-time behaviour of solutions to porous medium equations with convection is investigated when the initial datum is a non-negative and integrable function on the real line. The long-time profile of the solutions is determined, and depends on whether the convective or the diffusive effect dominates for large times. Sharp temporal decay estimates are also provided.
Reconstruction of Quantitative Susceptibility Mapping From Total Field Maps With Local Field Maps Guided UU-Net

Quantitative susceptibility mapping (QSM) is an emerging computational technique based on the magnetic resonance imaging (MRI) phase signal, which can provide magnetic susceptibility values of tissues. The existing deep learning-based models mainly reconstruct QSM from local field maps. However, the complicated inconsecutive reconstruction steps not only accumulate errors for inaccurate estimation, but also are inefficient in clinical practice. To this end, a novel local field maps guided UU-Net with Self- and Cross-Guided Transformer (LGUU-SCT-Net) is proposed to reconstruct QSM directly from the total field maps. Specifically, we propose to additionally generate the local field maps as the auxiliary supervision during the training stage. This strategy decomposes the more complicated mapping from total maps to QSM into two relatively easier ones, effectively alleviating the difficulty of direct mapping. Meanwhile, an improved U-Net model, named LGUU-SCT-Net, is further designed to promote the nonlinear mapping ability. The long-range connections are designed between two sequentially stacked U-Nets to bring more feature fusions and facilitate the information flow. The Self- and Cross-Guided Transformer integrated into these connections further captures multi-scale channel-wise correlations and guides the fusion of multi-scale transferred features, assisting in the more accurate reconstruction. The experimental results on an in-vivo dataset demonstrate the superior reconstruction results of our proposed algorithm.
Available Potential Energy and Exergy in Stratified Fluids

Lorenz's theory of available potential energy (APE) remains the main framework for studying the atmospheric and oceanic energy cycles. Because the APE generation rate is the volume integral of a thermodynamic efficiency times the local diabatic heating/cooling rate, APE theory is often regarded as an extension of the theory of heat engines. Available energetics in classical thermodynamics, however, usually relies on the concept of exergy and is usually measured relative to a reference-state maximizing entropy at constant energy, whereas APE's reference state minimizes potential energy at constant entropy. This review seeks to shed light on the two concepts; it covers local formulations of available energetics, alternative views of the dynamics/thermodynamics coupling, APE theory and the second law of thermodynamics, APE production/dissipation, extensions to binary fluids, mean/eddy decompositions, APE in incompressible fluids, APE and irreversible turbulent mixing, and the role of mechanical forcing on AP.
Endothelial Dysfunction Syndromes after Allogeneic Stem Cell Transplantation

Simple Summary Hemato-poietic stem cell transplantation is associated with significant endothelial dysfunction, which may result in severe complications. Endothelial dysfunction induces the expression of multiple substances including, cell adhesion molecules, pro-inflammatory cytokines, and coagulation factors resulting in activation of the complement system, and promoting a procoagulant and proinflammatory state. The pathophysiological process that mediates the endothelial damage is not clearly understood and the aim of this study is a comprehensive review of the existing knowledge. Moreover, the levels of soluble molecules released in the systemic circulation as a result of endothelial damage may serve as biomarkers for the early diagnosis and the pre-emptive treatment of post-transplant syndromes. The review of the existing literature presented in detail shows that the ideal biomarker with sufficient sensitivity and specificity for the early diagnosis of post-transplant complications does not currently exist. Future studies should focus on the identification of novel biomarkers with sufficient specificity and sensitivity. Abstract Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only therapy with a curative potential for a variety of malignant and non-malignant diseases. The major limitation of the procedure is the significant morbidity and mortality mainly associated with the development of graft versus host disease (GVHD) as well as with a series of complications related to endothelial injury, such as sinusoidal obstruction syndrome/veno-occlusive disease (SOS/VOD), transplant-associated thrombotic microangiopathy (TA-TMA), etc. Endothelial cells (ECs) are key players in the maintenance of vascular homeostasis and during allo-HSCT are confronted by multiple challenges, such as the toxicity from conditioning, the administration of calcineurin inhibitors, the immunosuppression associated infections, and the donor alloreactivity against host tissues. The early diagnosis of endothelial dysfunction syndromes is of paramount importance for the development of effective prophylactic and therapeutic strategies. There is an urgent need for the better understanding of the pathogenetic mechanisms as well as for the identification of novel biomarkers for the early diagnosis of endothelial damage. This review summarizes the current knowledge on the biology of the endothelial dysfunction syndromes after allo-HSCT, along with the respective therapeutic approaches, and discusses the strengths and weaknesses of possible biomarkers of endothelial damage and dysfunction.
A facile synthesis method and spectral characterization of silicon dioxide and magnetite nanoparticles

: Nanomaterials have attracted the tremendous interest of a vast number of researchers due to their unique characteristics. Metallic nanoparticles, especially magnetite nanoparticles (M) have thermal, mechanical, optical, electrical, and magnetic properties that differ from those of the bulk material enabling these nanoparticles to be applied in a huge number of application fields such as; industrial, medical, engineering, and scientific research. Also, ceramic nanoparticles such as silicon dioxide nanoparticles(S) due to their high porosity, high surface-to-volume ratio, and biocompatibility, they are used broadly in many applications increasingly. The preparation of these nanoparticles has become a highly demand. Therefore, the hydrothermal method to synthesize magnetite nanoparticles exhibited a good result in producing a cubic crystal with a low crystal size of 4 nm in a facile procedure. Silica nanoparticles were fabricated via a simple preparation method, the sol-gel method using a nontoxic precursor with a crystal size of 37 nm. The characterization of the as-prepared nanoparticles was attempted using x-ray diffraction (XRD), infra-red (IR) spectra, energy-dispersive x-ray spectroscopy (EDS), transmission electron microscope (TEM), and scanning electron microscope (SEM), and the results showed that the fabricated nanoparticles have a crystal phase with identified particles and morphological shapes. ----------------------------------------------------------------------------------------------------------------------------------
Synthesis and Anti-Angiogenic Activity of Novel c(RGDyK) Peptide-Based JH-VII-139-1 Conjugates

Peptide–drug conjugates are delivery systems for selective delivery of cytotoxic agents to target cancer cells. In this work, the optimized synthesis of JH-VII-139-1 and its c(RGDyK) peptide conjugates is presented. The low nanomolar SRPK1 inhibitor, JH-VII-139-1, which is an analogue of Alectinib, was linked to the ανβ3 targeting oligopeptide c(RGDyK) through amide, carbamate and urea linkers. The chemostability, cytotoxic and antiangiogenic properties of the synthesized hybrids were thoroughly studied. All conjugates retained mid nanomolar-level inhibitory activity against SRPK1 kinase and two out of four conjugates, geo75 and geo77 exhibited antiproliferative effects with low micromolar IC50 values against HeLa, K562, MDA-MB231 and MCF7 cancer cells. The activities were strongly related to the stability of the linkers and the release of JH-VII-139-1. In vivo zebrafish screening assays demonstrated the ability of the synthesized conjugates to inhibit the length or width of intersegmental vessels (ISVs). Flow cytometry experiments were used to test the cellular uptake of a fluorescein tagged hybrid in MCF7 and MDA-MB231 cells that revealed a receptor-mediated endocytosis process. In conclusion, most conjugates retained the inhibitory potency against SRPK1 as JH-VII-139-1 and demonstrated antiproliferative and antiangiogenic activities. Further animal model experiments are needed to uncover the full potential of such peptide conjugates in cancer therapy and angiogenesis-related diseases.
Steady and unsteady wind loading of buildings and structures

Wind loads are conveniently divided into steady (time-average) loads and unsteady (time-dependent) loads. The latter arise from fluctuating forces due to turbulence as well as from self-excited aerodynamic instability. The relevant characteristics of atmospheric winds—speed profile and turbulence—and their dependence on the local terrain are briefly discussed. For design based on steady wind loadings the design wind speed is dependent on the acceptable degree of risk. Force and pressure coefficients may be influenced by Reynolds number, surface roughness, wind characteristics and proximity to other structures. Unsteady loadings due directly to turbulence are assessed through the concept of aerodynamic admittance. Only the vortex-shedding and galloping mechanisms leading to aerodynamic instability are reviewed here, together with some design features for avoiding such excitations. To predict the response of even conventional structures while in the design stages further information is needed on the speeds and turbulence characteristics of natural winds, especially of those over cities. Further investigations concerning the aerodynamic admittance and the aerodynamic excitation of practical structures are also needed. Research on these properties involves wind-tunnel studies in which the separate effects of intensity and scale of turbulence must be determined, and improved techniques for simulating the characteristics of natural winds in wind tunnels are required. A major difficulty in the application of these aerodynamic data to the prediction of structural response is the uncertainty in the assessment of values of the structural damping.
Quantification of polyimide carbonization after laser ablation

Polyimide was irradiated with a XeCl excimer laser (308 nm) and the ablated area and its surrounding were studied using transmission electron microscopy (TEM) and confocal Raman microscopy. Ring-like structures surrounding the ablated area were detected at all fluences. At fluences lower than 250 mJ/cm−2 the formation of conical structures was observed within the irradiated area. The width of the rings increases with fluence and only slightly with the number of pulses. The rings consist mainly of polycrystalline carbon with a relatively high bond angle disorder, with thickness decreasing radially from the crater edge. The thickness of the deposited carbon was determined from TEM analysis and calculated from the intensity ratios of Raman bands assigned to carbon and polyimide using a two layer model. Comparing the two results an estimate of the absorption coefficient of the deposited carbon could be obtained. On top of the cone structures carbon was detected with a higher degree of crystallinity and lower.
Duration of Immunotherapy in Non-Small Cell Lung Cancer Survivors: A Lifelong Commitment?

Simple Summary Lung cancer is one of the most common human cancers and the leading cause of cancer-related mortality worldwide. The advent of immunotherapy for the treatment of non-small cell lung cancer has significantly improved progression-free survival, overall survival, and the patient’s quality of life in comparison to chemotherapy. Currently, it is estimated that long-term survival can be achieved in more than 15% of patients treated with immunotherapy. Therefore, the optimal duration of immunotherapy in long survivors needs to be established to avoid overtreatment, side effects, and high costs and at the same time, protect them from potential disease relapse. The aim of this review is to discuss all the aspects related to the optimal duration of immunotherapy in long survivors with non-small cell lung cancer. Abstract Lung cancer is one of the most common human malignancies and the leading cause of cancer-related death worldwide. Novel therapeutic approaches, like targeted therapies against specific molecular alterations and immunotherapy, have revolutionized in the last decade the oncological outcomes in patients affected by non-small cell lung cancer (NSCLC). The advent of immunotherapy for the treatment of NSCLC has significantly improved overall and progression-free survival, as well as the patient’s quality of life in comparison to traditional chemotherapy. Currently, it is estimated that long-term survival can be achieved in more than 15% of NSCLC patients treated with immunotherapy. Therefore, the optimal duration of immunotherapy in long survivors needs to be established to avoid overtreatment, side effects, and high costs and at the same time, protect them from potential disease relapse or progression. We performed a narrative review to discuss all the aspects related to the optimal duration of immunotherapy in long survivors with NSCLC. Data regarding the duration of immunotherapy in the most impacting clinical trials were collected, along with data regarding the impact of toxicities, side effects, and costs for healthcare providers. In addition, the two-year immunotherapy scheme in patients who benefit from first-line or subsequent treatment lines are examined, and the need for biomarkers that can predict outcomes during and after immunotherapy cessation in patients affected by NSCLC are discussed.
Impact of Conventional and Deep Learning-based Point Cloud Geometry Coding on Deep Learning-based Classification Performance

Deep learning (DL)-based point cloud (PC) classification is a key computer vision task for many applications, notably autonomous driving, surveillance, and cultural heritage. In many application scenarios, PCs must be coded to reach practical rates for storage and transmission purposes, and thus they suffer from more or less intense compression artifacts. After the specification of two MPEG PC coding standards, DL-based PC coding has gained momentum, reaching competitive compression performance, especially for dense PCs. Since using decoded PCs, which may suffer from compression artifacts, may impact the final classification performance, the main goal of this paper is to study the impact of static PC geometry coding on DL-based classification. This study is performed on the ModelNet40 test dataset using the conventional G-PCC coding standard and the DL-based PC geometry codec which was the top performing solution responding to the recent JPEG Pleno PC Coding Call for Proposals. Two highly performing DL-based classifiers are used, considering the original PC geometry before and after voxelization, as well as the decoded PC geometry for different rates and qualities. As expected, coding has an impact on the classification performance, especially for the lower rates/qualities. For very sparse PCs, conventional coding still has advantage, contrarily to dense PCs, but this should change in the future with DL-based tools becoming the most natural solutions for both PC geometry coding and classification.
New Insights into Bitopic Orthosteric/Allosteric Ligands of Cannabinoid Receptor Type 2

Very recently, we have developed a new generation of ligands targeting the cannabinoid receptor type 2 (CB2R), namely JR compounds, which combine the pharmacophoric portion of the CB2R positive allosteric modulator (PAM), EC21a, with that of the CB2R selective orthosteric agonist LV62, both synthesized in our laboratories. The functional examination enabled us to identify JR14a, JR22a, and JR64a as the most promising compounds of the series. In the current study, we focused on the assessment of the bitopic (dualsteric) nature of these three compounds. Experiments in cAMP assays highlighted that only JR22a behaves as a CB2R bitopic (dualsteric) ligand. In parallel, computational studies helped us to clarify the binding mode of these three compounds at CB2R, confirming the bitopic (dualsteric) nature of JR22a. Finally, the potential of JR22a to prevent neuroinflammation was investigated on a human microglial cell inflammatory model.
Saddlepoint approximations as smoothers

This note investigates the sense in which saddlepoint approximations act as smoothers of discrete distributions. The discrete problem is embedded in a continuous model that closely matches it on the discrete sample space, with saddlepoint approximation yielding an inference that is almost exact for the continuous model. The same applies to conditional distributions. An example is given and implications for inference are discussed. Copyright Biometrika Trust 2002, Oxford University Press.