Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling between normal and lateral degrees of freedom of an electron in quantum wells and superlattices at zero and finite magnetic fields

We present the effective-barrier-height method to investigate the effects of coupling between normal and lateral degrees of freedom of an electron in the parabolic conduction-band approach. This is performed on electronic states in quantum wells (QW's) and superlattices (SL's) at zero and finite magnetic fields perpendicular to interfaces. The numerical calculations for ${\mathrm{G}\mathrm{a}\mathrm{A}\mathrm{s}/\mathrm{A}\mathrm{l}}_{x}{\mathrm{Ga}}_{1\ensuremath{-}x}\mathrm{As}$ materials show that the coupling effect leads not only to the shift of the sublevels in QW's and subband, in SL's toward the well bottom with increasing ${k}_{\mathrm{xy}}$ or $n$, but also to the disappearance of high excited states close to the top of the barrier when ${k}_{\mathrm{xy}}$ or $n$ exceeds a certain value owing to the the fast lowering of the effective-barrier height. We also investigate the variation of the shift of levels in QW's with the well width and found that this coupling effect becomes more striking in thin QW's.
Visualization of heat propagation in biological tissues with two-photon fluorescence microscopy

In this study, we have demonstrated by using time-lapsed two-photon fluorescence microscopy (2PFM), heat flow in biological tissues can be monitored based on temperature-induced fluorescence change of endogenous molecules. Compared to conventional infrared thermography or other thermal imaging tools, 2PFM provides not only sub-micrometer spatial resolution, but also optical sectioning capability inside tissues. As a proof of principle, 2PFM was used to monitor the fluorescence variation in a leaf of Eucalyptus Robusta Smith, which is placed on a home-made heater. By heating the leaf asymmetrically, significant changes of chlorophyll fluorescence were observed in the temperature range of 30°C to 60°C, leading to the visualization of heat conduction dynamics. From the analysis of temporal variation in fluorescence, 0.5°C thermal resolution was demonstrated and detailed temperature distribution can be quantized. Such a technique will be useful for the characterization of heat-related biophysical mechanisms with high spatial and temperature resolution in a thick tissue.
SARS-CoV-2 Emergency Management in the ASL 1 Abruzzo Companies, Italy: An Autumn 2022 Cross-Sectional Investigation

Background: The SARS-CoV-2 pandemic still represents a public health emergency that affects workplaces and forces employers to develop technical, organizational and procedural measures safeguarding workers’ health, particularly ‘fragile’ ones. This research aimed to assess employers’ adherence to the emergency measures planned by the Italian government to hinder COVID-19 during Autumn 2022. Methods: A cross-sectional study was conducted in Autumn 2022, with an 18-item questionnaire derived from the Italian State’s governmental indications, sent by email to 51 companies of Marsica and Peligna Valley, L’Aquila, Southern Italy. Results: A total of 20 recruited companies (65% were micro-enterprises, belonging to the food and financial sector) responded to the questionnaire within a mean time of 18 days (±11.64), which was lower for medium- and large-sized companies as well as for banking sector ones (p < 0.05). As regards intervention strategies, sanitization (92.7% of positive answers) and specific training (83.3%) showed almost full compliance in contrast to working organization (47.5%) and social distancing (61.7%). The companies that reported managing fragility (50%) belong almost exclusively to the banking sector, with predominantly office-based tasks. Conclusions: The study provided insight into critical issues relating to compliance with national legislative directives and the crucial role of occupational physicians as global advisors for all workplaces.
Improving CNN-base Stock Trading By Considering Data Heterogeneity and Burst

In recent years, there have been quite a few attempts to apply intelligent techniques to financial trading, i.e., constructing automatic and intelligent trading framework based on historical stock price. Due to the unpredictable, uncertainty and volatile nature of financial market, researchers have also resorted to deep learning to construct the intelligent trading framework. In this paper, we propose to use CNN as the core functionality of such framework, because it is able to learn the spatial dependency (i.e., between rows and columns) of the input data. However, different with existing deep learning-based trading frameworks, we develop novel normalization process to prepare the stock data. In particular, we first empirically observe that the stock data is intrinsically heterogeneous and bursty, and then validate the heterogeneity and burst nature of stock data from a statistical perspective. Next, we design the data normalization method in a way such that the data heterogeneity is preserved and bursty events are suppressed. We verify out developed CNN-based trading framework plus our new normalization method on 29 stocks. Experiment results show that our approach can outperform other comparing approaches.
Multivariate analysis techniques for representing graphs and contingency tables

Graph spectra have been used for about 40 years to recover the structure of graphs. Different kinds of spectra are capable of finding multiway cuts corresponding to different optimization criteria. While eigenvalues give estimates for the objective functions of the discrete optimization problems, eigenvectors are used to find clusters of vertices which approximately solve the problems. These methods are reminiscent of some classical methods of multivariate statistical analysis (see Appendix C). Throughout this chapter, methods of principal component analysis and correspondence analysis are used to solve quadratic placement tasks on weighted graphs and contingency tables. As a result, we get low dimensional representation of the graph’s vertices or rows and columns of the contingency table by means of linear methods so that the representation somehow favors our classification criteria. Non-linearities are treated by mapping the data into a feature space (reproducing kernel Hilbert space). We also generalize the notion of representation for joint distributions.
Development of near-infrared paired-agent imaging for in vivo quantification of drug receptor occupancy in tumor

Receptor occupancy (RO) correlates the dose of drug administered to the percentage of receptors occupied by the drug compound, which helps decide dosing of drug candidates entering clinical trials, and tailor drug dosage for individualized therapies. However, in vivo measurement of RO in solid tumor is hindered by both tissue properties and technical limitations. Here we present the progress of developing a near-infrared, paired-agent imaging (PAI) approach for real-time measurement of anti-tumor drug RO in vivo. In this study, xenograft murine model with orthotopic tumor implant was imaged using a pair of imaging agent: ABY-029, an affibody-dye conjugate, targeting epidermal growth factor receptor (EGFR), together with IRDye 680LT, a pharmacokinetically similar probe devoid of EGFR specificity. Concentration of tumor EGFR free of drug binding was quantified by binding potential (BP), a parameter calculated from fluorescence signals of the agent pair. We demonstrated that BP was decreased by subsequent administration of drug homolog, indicating drug-EGFR engagement in the tumor. The results demonstrated the ability of PAI to reflect displacement of EGFR-bound ABY-029 by anti-EGFR drug molecules, and the potential to be applied for in vivo RO measurement.
Results of treatment with alemtuzumab in a Spanish cohort of patients with multiple sclerosis in the real world: The RealMS study

Background Alemtuzumab (ALZ) is a humanized monoclonal antibody approved for the treatment of patients with highly active relapsing-remitting multiple sclerosis (RRMS) administered in two annual courses. The objective of this study was to describe the effectiveness and safety data of ALZ and to report the health resource utilization in patients receiving this treatment. Methods In this retrospective, non-interventional study, information was retrieved from patients' medical charts at one center in Spain. Included patients were ≥18 years old, and ALZ treatment was initiated between 1 March 2015 and 31 March 2019, according to routine clinical practice and local labeling. Results Of 123 patients, 78% were women. The mean (standard deviation, SD) age of patients at diagnosis was 40.3 (9.1) years, and the mean time since diagnosis was 13.8 (7.3) years. Patients were previously treated with a median (interquartile range; IQR) number of two (2.0–3.0) disease-modifying treatments (DMTs). Patients were treated with ALZ for a mean (SD) of 29.7 (13.8) months. ALZ reduced the annualized relapse rate (ARR) (1.5 before vs. 0.05 after; p < 0.001) and improved the median EDSS (4.63 before vs. 4.00 after; p < 0.001). Most (90.2%) patients were relapse-free while receiving ALZ. The mean number of gadolinium-enhancing [Gd+] T1 lesions was reduced (1.7 before vs. 0.1 after; p < 0.001), and the mean number of T2 hyperintense lesions was maintained (35.7 before vs. 35.4 after; p = 0.392). A total of 27 (21.9%) patients reported 29 autoimmune diseases: hyperthyroidism (12), hypothyroidism (11), idiopathic thrombocytopenic purpura (ITP) (3), alopecia areata (1), chronic urticaria (1), and vitiligo (1). The mean number of health resources (outpatient visits, emergency room visits, hospital admissions, and tests performed in the hospital) used while patients were treated with ALZ progressively decreased from year 1 to year 4, except for a slight increase at year 2 of outpatient visits. Conclusion The ReaLMS study provides real-world evidence that ALZ can promote clinical and magnetic resonance imaging disease remission, as well as disability improvement in patients with MS, despite several prior DMT failures. The ALZ safety profile was consistent with data available from clinical trials and other real-world studies. Healthcare resource use was reduced throughout the treatment period.
Maximum loadability of power systems using interior point nonlinear optimization method

This paper proposes a nonlinear optimization interior point (IP) method for the determination of maximum loadability in a power system. Details of the implementation of pure primal-dual and predictor-corrector primal-dual IP algorithms are presented. It is shown that most of the computational effort of the algorithm is taken by the formation and factorization of the augmented Hessian matrix of the IP algorithm. The size of this matrix can be as large as ten times the number of buses in the system. Comparisons of the two IP implementations with large scale power systems with as many as 4000 buses are presented. It is shown that the IP algorithm constitutes an effective method for the determination of the maximum loadability in a power system.
Antibody–Biopolymer Conjugates in Oncology: A Review

Cancer is one of the most prevalent diseases and affects a large proportion of the population worldwide. Conventional treatments in the management include chemotherapy, radiotherapy, and surgery. Although being well-accepted, they have many lacunas in the form of severe side effect resulting from lack of targeted delivery. Antibody biopolymer conjugates are a novel method which is an add-on to older methods of immunization. It is used in various diseases and disorders. It ensures the targeted delivery of molecules to increase its efficacy and reduce unwanted effects of the molecule/drug to normal cells. It shows miraculous results in the treatment and management of several cancers even in advanced stages. Herein, we present the chemistry between biopolymer and antibody, their effects on cancer as well as the basic differences between antibody–drug conjugates and antibody–biopolymer conjugates.
On the Stability of Internal Baroclinic Jets in a Rotating Atmosphere.

Abstract We consider the quasi-geostrophic instability of a circumpolar vortex in which there is available kinetic energy of lateral shear as well as available potential energy due to meridional temperature gradients. Stability criteria are developed for the case of an internal jet, i.e., where the meridional temperature gradients at the ground vanish. The internal jet is stable if the gradient of potential vorticity in isentropic surfaces does not vanish. If it vanishes at a closed isopleth of constant mean zonal vorticity, the jet is unstable. The special role played by the kinematic and thermodynamic boundary conditions in the theory of baroclinic stability is clarified by re-examining earlier theories in the light of an analogy to two-dimensional shear flow. Simple baroclinic flow with rigid horizontal boundaries is isomorphic to Couette flow with free boundaries. The presence of meridional temperature gradients at boundaries relaxes the constraints on the boundary pressure perturbations and makes pos.
The Use of Silver Nitrate as an Elicitor to Increase Bioactive Compounds in Artichoke [Cynara cardunculus var. scolymus (L.) Fiori] Callus Culture

The globe artichoke belongs to the Asteraceae family and has become more and more popular among other vegetables due to its beneficial health-promoting features that are related to bioactive compounds present in leaves. The plant materials have inadequate proportions of valuable bioactive compounds in nature, so researchers are emphasizing on how to enhance their amounts. In vitro techniques with integrated novel practices can be employed to enhance phytochemicals from any plant. The current study aimed to determine and assess valuable bioactive components in 3 artichoke cultivars via callus cultures which were subjected to a treatment of 4 different concentrations (2.5, 5.0, 10.0, and 15.0 mg L-1) of silver nitrate. Results indicated that well-balanced levels of plant growth regulators were necessary for stimulating the callus formation of globe artichoke. The findings of the current study also revealed the importance of cultivar differences regarding callus formation. Experimental results revealed that variation in silver nitrate concentrations had a significant effect on biomass, total phenolic content and total antioxidant activities. The results of the current, study may offer a good strategy by promoting bioactive compounds of globe artichoke leaves for utilizing in large-scale industries, pharmacology, and food supplements.
Online parameter estimation applied to mixed conduction/radiation

This paper describes online parameter estimation and modeling applied to a mixed conduction/radiation heat transfer as is the case often witnessed in Space Hardware Qualification. We investigate several recent techniques such as the Extended Kalman Filter and the Unscented Kalman Filter. Results show that EKF fails in parameter estimation in cases where tests featured strong non linearities. UKF was found to perform well in all the experimental test conditions.
3D Modeling of Lacus Mortis Pit Crater with Presumed Interior Tube Structure

When humans explore the Moon, lunar caves will be an ideal base to provide a shelter from the hazards of radiation, meteorite impact, and extreme diurnal temperature differences. In order to ascertain the existence of caves on the Moon, it is best to visit the Moon in person. The Google Lunar X Prize(GLXP) competition started recently to attempt lunar exploration missions. Ones of those groups competing, plan to land on a pit of Lacus Mortis and determine the existence of a cave inside this pit. In this pit, there is a ramp from the entrance down to the inside of the pit, which enables a rover to approach the inner region of the pit. In this study, under the assumption of the existence of a cave in this pit, a 3D model was developed based on the optical image data. Since this model simulates the actual terrain, the rendering of the model agrees well with the image data. Furthermore, the 3D printing of this model will enable more rigorous investigations and also could be used to publicize lunar exploration missions with ease.
Maladaptive task-unrelated thoughts: Self-control failure or avoidant behavior? Preliminary evidence from an experience sampling study

Introduction Task-unrelated thoughts (TUT) play an important role in everyday life functioning (e.g., anticipating the future, or providing a mental break). However, TUT might also be maladaptive, impairing cognitive performance emotion regulation, and increasing the risk of psychological disorders. In the present study, we aimed to test how self-reported control over TUT and task valence moderate the link between task difficulty and TUT intensity, testing the context regulation and avoidant alternative hypotheses of TUT occurrence. Method Forty-nine participants took part in an experience sampling study. They were asked to answer five times a day for 5 days a series of questions assessing the intensity, valence, control over TUT, and their momentary affect along with characteristics of the task they were currently performing. They also filled in trait questionnaires assessing their tendency to daydream, ruminate, and their beliefs on emotions' usefulness and controllability. Results The results showed that both task difficulty and one's lower control over thoughts along with their interaction significantly increased TUT intensity. Task negative valence significantly predicted TUT intensity and moderated the link between task difficulty and TUT intensity. In addition, the tendency to daydream and beliefs in the controllability of negative emotions affect the relations in this model. Discussion To the best of our knowledge, this study is the first to provide quantitative evidence from an experience sampling study on the role of the valence of currently performed tasks and beliefs on emotions on TUT intensity. It might be an important indication for research and clinical practice that maladaptive TUT might not be only linked to self-control failure but also to emotion regulation strategies one is using.
Systematic Review of Tumor Segmentation Strategies for Bone Metastases

Simple Summary With recent progress in radiation therapy, patients with bone metastases can be treated curatively, provided precise delineation of metastatic lesions is adequately identified. Tumor segmentation is a highly active area of research, but only limited studies have been on bone metastasis. This review aims to investigate methods for differentiating benign from malignant bone lesions and characterizing malignant bone lesions specifically in the context of bone metastases. While computer vision techniques have opened new opportunities for quantifying cancer growth with minimal expert supervision, fully automatic segmentation algorithms still require improvement. This is partly due to limited contrast between tumors and surrounding tissue and the lack of a widely agreed upon “gold standard” for defining these boundaries. Additionally, many studies do not provide evidence that their proposed methods are suitable for use in clinical practice. Abstract Purpose: To investigate the segmentation approaches for bone metastases in differentiating benign from malignant bone lesions and characterizing malignant bone lesions. Method: The literature search was conducted in Scopus, PubMed, IEEE and MedLine, and Web of Science electronic databases following the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A total of 77 original articles, 24 review articles, and 1 comparison paper published between January 2010 and March 2022 were included in the review. Results: The results showed that most studies used neural network-based approaches (58.44%) and CT-based imaging (50.65%) out of 77 original articles. However, the review highlights the lack of a gold standard for tumor boundaries and the need for manual correction of the segmentation output, which largely explains the absence of clinical translation studies. Moreover, only 19 studies (24.67%) specifically mentioned the feasibility of their proposed methods for use in clinical practice. Conclusion: Development of tumor segmentation techniques that combine anatomical information and metabolic activities is encouraging despite not having an optimal tumor segmentation method for all applications or can compensate for all the difficulties built into data limitations.
A Deep Learning-Based Attack Detection Mechanism Against Potential Cascading Failure Induced by Load Redistribution Attacks

The occurrence of load redistribution (LR) attacks has disastrous consequences for the power system, but these attacks have a significant impact when they cause cascading failures in the system. The mechanisms and strategies for detecting and designing LR attacks resulting in overflow on lines have been the focus of different studies. But fewer studies have been done to detect LR attacks that cause cascading failures. This paper presents a mechanism for identifying LR attacks that, besides causing overflow on lines, have the potential to generate cascading failure. A novel LR attack scheme with cascading failure potential is first proposed for this purpose. The detection mechanism has a basic exploitable structure based on analyzing the estimated cyber load data through the energy management system and a deep learning network. The performance evaluation of the detection mechanism is implemented with regard to the IEEE standard 118-bus system. Various attack scenarios under different conditions (topologies, target lines, and attack load level variations $(\alpha)$ ) are used to verify the effectiveness of the proposed framework. The results clearly show an acceptable level of accuracy for the proposed mechanism, which can distinguish between LR attacks via the overload purpose while also showing the system’s secure state.
CARACTERÍSTICAS PRELIMINARES SOCIODEMOGRÁFICAS DOS PESCADORES ARTESANAIS DE ELASMOBRÂNQUIOS NO SUL DA BAHIA, BRASIL

Aspectos sociodemográficos, características das embarcações, aspectos comerciais e sazonalidades das pescarias são características importantes ao setor pesqueiro artesanal que captura elasmobrânquios em suas atividades. Estas informações foram de imperativa significância na construção dessa pesquisa, tornando-se assim, um fator primordial na busca de informações pertinentes de como a pesca impacta este táxon. Objetivou-se identificar as características sociodemográficas dos pescadores, as características das pescarias, como embarcações, petrechos de pesca e o identificar as espécies elasmobrânquios que são capturadas pela pesca artesanal e comercializadas nas comunidades de pescadores de Alcobaça e Prado (Bahia - BA). Utilizou-se o método de entrevistas estruturadas/semiestruturadas aplicada aos pesadores das cidades e identificação e quantificação dos elasmobrânquios desembarcados. Constatou-se que os pescadores das cidades apresentam os mesmos padrões de pesca (petrechos, escolhas dos locais de pesca e sazonalidades para as pescarias), mas há diferenças entre os tipos de embarcação e alguns aspectos sociodemográficos. Durante o período amostral nenhum elasmobrânquio foi observado em pescarias na cidade de Prado. A partir desta pesquisa, verificou-se que os pescadores destas cidades não apresentam pesca direcionada aos elasmobrânquios, mas comercializam os animais que foram capturados no comércio local.