Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Allocation Strategies of Power and Spreading Factors With Imperfect Orthogonality in LoRa Networks

The LoRa physical layer is one of the most promising Low Power Wide-Area Network (LPWAN) technologies for future Internet of Things (IoT) applications. It provides a flexible adaptation of coverage and data rate by allocating different Spreading Factors (SFs) and transmit powers to end-devices. We focus on improving throughput fairness while reducing energy consumption. Whereas most existing methods assume perfect SF orthogonality and ignore the harmful effects of inter-SF interferences, we formulate a joint SF and power allocation problem to maximize the minimum uplink throughput of end-devices, subject to co-SF and inter-SF interferences and power constraints. This results into a mixed-integer non-linear optimization, which, for tractability, is split into two sub-problems: firstly, the SF assignment for fixed transmit powers, and secondly, the power allocation given the previously obtained assignment solution. For the first sub-problem, we propose a low-complexity many-to-one matching algorithm between SFs and end-devices. For the second one, given its intractability, we transform it using two types of constraints’ approximation: a linearized and a quadratic version. Our performance evaluation demonstrates that the proposed SF allocation and power optimization methods enable to drastically enhance various performance objectives such as throughput, fairness and power consumption, and that they outperform baseline schemes.
Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks

In the last few years, Deep Learning (DL) has been showing superior performance in different modalities of biomedical image analysis. Several DL architectures have been proposed for classification, segmentation, and detection tasks in medical imaging and computational pathology. In this paper, we propose a new DL architecture, the NABLA-N network, with better feature fusion techniques in decoding units for dermoscopic image segmentation tasks. The NABLA-N network has several advances for segmentation tasks. First, this model ensures better feature representation for semantic segmentation with a combination of low to high-level feature maps. Second, this network shows better quantitative and qualitative results with the same or fewer network parameters compared to other methods. In addition, the Inception Recurrent Residual Convolutional Neural Network (IRRCNN) model is used for skin cancer classification. The proposed NABLA-N network and IRRCNN models are evaluated for skin cancer segmentation and classification on the benchmark datasets from the International Skin Imaging Collaboration 2018 (ISIC-2018). The experimental results show superior performance on segmentation tasks compared to the Recurrent Residual U-Net (R2U-Net). The classification model shows around 87% testing accuracy for dermoscopic skin cancer classification on ISIC2018 dataset.
Biogeographia – The Journal of Integrative Biogeography

Published and unpublished data on Ethiopian and mammals, mainly deriving from Italian sources, including some natural history museums, in the present contribution are intended as an amendment to the landmark Catalogue of Ethiopian and Eritrean mammals produced by Derek Yalden and collaborators between 1974 and 1996. Additionally, a few taxonomic notes including the proposal of two new subspecific names are included. The paper highlights the importance of historical data for a number of scientific applications, such as taxonomy, conservation biology, and restoration ecology. Two ‘cryptozoological’ records are also included.
Noncompact quasi‐Einstein manifolds conformal to a Euclidean space

The goal of this article is to investigate nontrivial m‐quasi‐Einstein manifolds globally conformal to an n‐dimensional Euclidean space. By considering such manifolds, whose conformal factors and potential functions are invariant under the action of an (n−1) ‐dimensional translation group, we provide a complete classification when λ=0 and m≥1 or m=2−n .
Flavin Conjugated Polydopamine Nanoparticles Displaying Light-Driven Monooxygenase Activity

A hybrid of flavin and polydopamine (PDA) has been explored as a photocatalyst, drawing inspiration from natural flavoenzymes. Light-driven monoxygenase activity has been demonstrated through the oxidation of indole under blue light irradiation in ambient conditions, to afford indigo and indirubin dyes. Compared to riboflavin, a flavin-polydopamine hybrid is shown to be more resistant to photobleaching and more selective toward dye production. In addition, it has been demonstrated that it can be recycled from the solution and used for up to four cycles without a marked loss of activity, which is a significant improvement compared to other heterogenous flavin catalysts. The mechanism of action has been explored, indicating that the PDA shell plays an important role in the stabilization of the intermediate flavin-peroxy species, an active component of the catalytic system rather than acting only as a passive nanocarrier of active centers.
Copper Utilization, Regulation, and Acquisition by Aspergillus fumigatus

Copper is an essential micronutrient for the opportunistic human pathogen, Aspergillus fumigatus. Maintaining copper homeostasis is critical for survival and pathogenesis. Copper-responsive transcription factors, AceA and MacA, coordinate a complex network responsible for responding to copper in the environment and determining which response is necessary to maintain homeostasis. For example, A. fumigatus uses copper exporters to mitigate the toxic effects of copper while simultaneously encoding copper importers and small molecules to ensure proper supply of the metal for copper-dependent processes such a nitrogen acquisition and respiration. Small molecules called isocyanides recently found to be produced by A. fumigatus may bind copper and partake in copper homeostasis similarly to isocyanide copper chelators in bacteria. Considering that the host uses copper as a microbial toxin and copper availability fluctuates in various environmental niches, understanding how A. fumigatus maintains copper homeostasis will give insights into mechanisms that facilitate the development of invasive aspergillosis and its survival in nature.
Global Burden Related to Nitrous Oxide Exposure in Medical and Recreational Settings: A Systematic Review and Individual Patient Data Meta-Analysis

The risk of adverse effects of nitrous oxide (N2O) exposure is insufficiently recognized despite its widespread use. These effects are mainly reported through case reports. We conducted an individual patient data meta-analysis to assess the prevalence of clinical, laboratory, and magnetic resonance findings in association with N2O exposure in medical and recreational settings. We calculated the pooled estimates for the studied outcomes and assessed the potential bias related to population stratification using principal component analysis. Eighty-five publications met the inclusion criteria and reported on 100 patients with a median age of 27 years and 57% of recreational users. The most frequent outcomes were subacute combined degeneration (28%), myelopathy (26%), and generalized demyelinating polyneuropathy (23%). A T2 signal hyperintensity in the spinal cord was reported in 68% (57.2–78.8%) of patients. The most frequent clinical manifestations included paresthesia (80%; 72.0–88.0%), unsteady gait (58%; 48.2–67.8%), and weakness (43%; 33.1–52.9%). At least one hematological abnormality was retrieved in 71.7% (59.9–83.4%) of patients. Most patients had vitamin B12 deficiency: vitamin B12 <150 pmol/L (70.7%; 60.7–80.8%), homocysteine >15 µmol/L (90.3%; 79.3–100%), and methylmalonic acid >0.4 µmol/L (93.8%; 80.4–100%). Consistently, 85% of patients exhibited a possibly or probably deficient vitamin B12 status according to the cB12 scoring system. N2O can produce severe outcomes, with neurological or hematological disorders in almost all published cases. More than half of them are reported in the setting of recreational use. The N2O-related burden is dominated by vitamin B12 deficiency. This highlights the need to evaluate whether correcting B12 deficiency would prevent N2O-related toxicity, particularly in countries with a high prevalence of B12 deficiency.
Ovarian preservation for premenopausal women with early-stage endometrial cancer: a Chinese retrospective study

Objective This study aimed to retrospectively investigate the safety of ovarian preservation of premenopausal women with stage 1a endometrial carcinoma. Methods We performed a population-based study to identify surgically treated stage Ia endometrial cancer of premenopausal women who were diagnosed between August 1989 and December 2015 in our center. Survival outcomes and recurrence rate were examined for premenopausal women who underwent ovarian preservation. Recurrence-free survival rates were calculated following generation of Kaplan–Meier curves and were compared with the log-rank test. Cox regression analysis was performed to identify the independent factors affecting the recurrence rate. Results Patients with ovarian preservation tended to be significantly younger at diagnosis, have less myometrial invasion, and were less likely to undergo lymphadenectomy compared with women treated with bilateral salpingo-oophorectomy. There was no significant difference in recurrence-free survival between the two groups. In the Cox regression model, ovarian preservation remained an independent prognostic factor for improved overall survival. Conclusion Ovarian preservation does not have a negative effect on oncological outcomes. Ovarian preservation can be applied to premenopausal women with stage Ia endometrial carcinoma.
Earlier age at menarche as a transdiagnostic mechanism linking childhood trauma with multiple forms of psychopathology in adolescent girls

Abstract Background Although early life adversity (ELA) increases risk for psychopathology, mechanisms linking ELA with the onset of psychopathology remain poorly understood. Conceptual models have argued that ELA accelerates development. It is unknown whether all forms of ELA are associated with accelerated development or whether early maturation is a potential mechanism linking ELA with psychopathology. We examine whether two distinct dimensions of ELA – threat and deprivation – have differential associations with pubertal timing in girls, and evaluate whether accelerated pubertal timing is a mechanism linking ELA with the onset of adolescent psychopathology. Methods Data were drawn from a large, nationally representative sample of 4937 adolescent girls. Multiple forms of ELA characterized by threat and deprivation were assessed along with age at menarche (AAM) and the onset of DSM-IV fear, distress, externalizing, and eating disorders. Results Greater exposure to threat was associated with earlier AAM (B = −0.1, p = 0.001). Each 1-year increase in AAM was associated with reduced odds of fear, distress, and externalizing disorders post-menarche (ORs = 0.74–0.85). Earlier AAM significantly mediated the association between exposure to threat and post-menarche onset of distress (proportion mediated = 6.2%), fear (proportion mediated = 16.3%), and externalizing disorders (proportion mediated = 2.9%). Conclusions Accelerated pubertal development in girls may be one transdiagnostic pathway through which threat-related experiences confer risk for the adolescent onset of mental disorders. Early pubertal maturation is a marker that could be used in both medical and mental health settings to identify trauma-exposed youth that are at risk for developing a mental disorder during adolescence in order to better target early interventions.
CHAMELEON: A Deep Learning Meta-Architecture for News Recommender Systems [Phd. Thesis]

Recommender Systems (RS) have became a popular research topic and, since 2016, Deep Learning methods and techniques have been increasingly explored in this area. News RS are aimed to personalize users experiences and help them discover relevant articles from a large and dynamic search space. The main contribution of this research was named CHAMELEON, a Deep Learning meta-architecture designed to tackle the specific challenges of news recommendation. It consists of a modular reference architecture which can be instantiated using different neural building blocks. As information about users' past interactions is scarce in the news domain, the user context can be leveraged to deal with the user cold-start problem. Articles' content is also important to tackle the item cold-start problem. Additionally, the temporal decay of items (articles) relevance is very accelerated in the news domain. Furthermore, external breaking events may temporally attract global readership attention, a phenomenon generally known as concept drift in machine learning. All those characteristics are explicitly modeled on this research by a contextual hybrid session-based recommendation approach using Recurrent Neural Networks. The task addressed by this research is session-based news recommendation, i.e., next-click prediction using only information available in the current user session. A method is proposed for a realistic temporal offline evaluation of such task, replaying the stream of user clicks and fresh articles being continuously published in a news portal. Experiments performed with two large datasets have shown the effectiveness of the CHAMELEON for news recommendation on many quality factors such as accuracy, item coverage, novelty, and reduced item cold-start problem, when compared to other traditional and state-of-the-art session-based recommendation algorithms.
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning

The integration of machine learning (ML) in numerous critical applications introduces a range of privacy concerns for individuals who provide their datasets for model training. One such privacy risk is Membership Inference (MI), in which an attacker seeks to determine whether a particular data sample was included in the training dataset of a model. Current state-of-the-art MI attacks capitalize on access to the model's predicted confidence scores to successfully perform membership inference, and employ data poisoning to further enhance their effectiveness. In this work, we focus on the less explored and more realistic label-only setting, where the model provides only the predicted label on a queried sample. We show that existing label-only MI attacks are ineffective at inferring membership in the low False Positive Rate (FPR) regime. To address this challenge, we propose a new attack Chameleon that leverages a novel adaptive data poisoning strategy and an efficient query selection method to achieve significantly more accurate membership inference than existing label-only attacks, especially at low FPRs.
Analysis of Optical and Electrical Responses of $\boldsymbol{\mu}$ -OLED With Metallized ITO Coplanar Waveguide Electrodes Submitted to Nanosecond Electrical Pulses

In this paper, the optical and electrical pulse responses of an optimized high-speed organic light-emitting diode (OLED) is investigated as a function of the pulse duration. The original design is based on the coplanar waveguide electrodes that are implemented on a transparent and conductive oxide thin film. The designed electrodes with reduced serial resistances (13 <inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula>) allow to maximize the pulse energy delivery and to feed the organic device with short electrical pulses of few nanoseconds for the first time. This is achieved by designing the electrodes to have 50-<inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> characteristic impedance, thanks to microwave techniques, and by implementing small values of capacitance (4.5 pF). The experimental results demonstrate <inline-formula> <tex-math notation="LaTeX">$\boldsymbol \mu $ </tex-math></inline-formula>-OLED electrical and optical responses to electrical excitation pulses as short as 2.5 ns, for the first time, and state-of-the-art current densities above 1.7 kA/cm<sup>2</sup>. Moreover, and rather unexpectedly, the developed characterization procedure to extract the reported results demonstrated the first direct measurement of the electroluminescence lifetime of organic materials in the nanosecond time scale.
Fisetin and 5‐fluorouracil: Effective combination for PIK3CA‐mutant colorectal cancer

The normal colon epithelium is transformed into its neoplastic counterpart through a series of genetic alterations in driver genes including activating mutations in PIK3CA. Treatment often involves surgery followed by 5‐fluorouracil (5‐FU) based therapy, which has limited efficiency and serious side effects. We sought to determine whether fisetin, a dietary flavonoid, alone or in combination with 5‐FU affected tumorigenesis in the mammalian intestine. We first determined the effect of fisetin, 5‐FU or their combination on PIK3CA‐mutant and PIK3CA wild‐type colon cancer cells by assessing cell viability, colony formation, apoptosis and effects on PI3K/AKT/mTOR signaling. Treatment of PIK3CA‐mutant cells with fisetin and 5‐FU reduced the expression of PI3K, phosphorylation of AKT, mTOR, its target proteins, constituents of mTOR signaling complex and this treatment increased the phosphorylation of AMPKα. We then determined whether fisetin and 5‐FU together or singly affected tumorigenesis in ApcMin/+ mice that also express constitutively active PI3K in the distal small intestine and colon. Tumor incidence was markedly lower in fisetin‐treated FC13K1ApcMin/+ mice that also express constitutively active PI3K in distal small intestine and colon, as compared to control animals, indicating that fisetin is a strong preventive agent. In addition, the combination of fisetin and 5‐FU also reduced the total number of intestinal tumors. Fisetin could be used as a preventive agent plus an adjuvant with 5‐FU for the treatment of PIK3CA‐mutant colorectal cancer.
An oscillator model better predicts cortical entrainment to music

Significance Previous work in humans has found rhythmic cortical activity while listening to rhythmic sounds such as speech or music. Whether this activity reflects oscillatory dynamics of a neural circuit or instead evoked responses to the rhythmic stimulus has been difficult to determine. Here, we devised a metric to tease apart the two hypotheses by analyzing phase lag across many stimulation rates. We test this phase concentration metric using numerical simulations and generate quantitative predictions to compare against recorded magnetoencephalography data. Both previously recorded and new data were better predicted by a model of oscillatory dynamics than evoked responses. This work, therefore, provides definitive evidence for the presence of an oscillatory dynamic in auditory cortex during processing of rhythmic stimuli. A body of research demonstrates convincingly a role for synchronization of auditory cortex to rhythmic structure in sounds including speech and music. Some studies hypothesize that an oscillator in auditory cortex could underlie important temporal processes such as segmentation and prediction. An important critique of these findings raises the plausible concern that what is measured is perhaps not an oscillator but is instead a sequence of evoked responses. The two distinct mechanisms could look very similar in the case of rhythmic input, but an oscillator might better provide the computational roles mentioned above (i.e., segmentation and prediction). We advance an approach to adjudicate between the two models: analyzing the phase lag between stimulus and neural signal across different stimulation rates. We ran numerical simulations of evoked and oscillatory computational models, showing that in the evoked case,phase lag is heavily rate-dependent, while the oscillatory model displays marked phase concentration across stimulation rates. Next, we compared these model predictions with magnetoencephalography data recorded while participants listened to music of varying note rates. Our results show that the phase concentration of the experimental data is more in line with the oscillatory model than with the evoked model. This finding supports an auditory cortical signal that (i) contains components of both bottom-up evoked responses and internal oscillatory synchronization whose strengths are weighted by their appropriateness for particular stimulus types and (ii) cannot be explained by evoked responses alone.
Individual Precursors of Student Homework Behavioral Engagement: The Role of Intrinsic Motivation, Perceived Homework Utility and Homework Attitude

Currently, the concept of engagement is crucial in the field of learning and school achievement. It is a multidimensional concept (e.g., behavioral, emotional, and cognitive dimensions) that has been widely used as a theoretical framework to explain the processes of school engagement and dropout. However, this conceptual framework has been scarcely used in the field of homework. The aim of the present study was to analyze the role of intrinsic motivation, perceived homework utility, and personal homework attitude as precursors of student homework engagement (behavioral engagement) and, at the same time, how such engagement is the precursor of academic achievement. Seven hundred and thirty students of Compulsory Secondary Education (CSE) (7th to 10th grade) from fourteen schools northern Spain participated. A structural equation model was elaborated on which intrinsic motivation, perceived utility and attitude were observed variables, and student engagement (time spent on homework, time management, and amount of teacher-assigned homework done) and academic achievement (Mathematics, Spanish Language, English Language, and Social Science) were latent variables. The results reveal that (i) intrinsic motivation is a powerful precursor of student behavioral engagement (also perceived utility and attitude, although to a lesser extent), and (ii) academic achievement is closely linked to the level of student engagement, qualifying the results of many of the previous studies conducted from a task-centered perspective (as opposed to a person-centered perspective).