Miracle-dz/UniFAR-FTUs huggingface dataset:
Descriptive Epidemiology of Melanoma Diagnosed between 2010 and 2014 in a Colombian Cancer Registry and a Call for Improving Available Data on Melanoma in Latin America

Simple Summary Melanoma is among the most aggressive types of skin cancer. For Latin American populations, we know very little about its patterns of occurrence and probabilities of survival. In this study, using data of the Bucaramanga Metropolitan Area Cancer Registry, we describe that the incidence rate is about 2 per 100,000 person-years, and that 5 years after diagnosis, 71% did not die of their melanoma. We also described the details of the characteristics and subgroups of survival. These findings help understand this disease better in this population and identified the need for more detailed and timely data in the whole region of Latin America. Abstract We aimed to improve the available information on morphology and stage for cutaneous melanoma in the population-based cancer registry of the Bucaramanga Metropolitan Area in Colombia. The incidence and survival rates and the distribution of melanoma patients by age, gender, anatomical subsite, and histological subtype were calculated. All 113 melanoma patients (median age 61) were followed up (median time 7.4 years). This exercise (filling in missing information in the registry by manual search of patient clinical record and other available information) yielded more identified invasive melanomas and cases with complete information on anatomical localization and stage. Age-standardized incidence and mortality rates were 1.86 and 1.08, being slightly higher for males. Most melanomas were localized on the lower limbs, followed by the trunk. For 35% of all melanomas, the morphological subtype remained unknown. Most of the remaining melanomas were nodular and acral lentiginous melanomas. Overall global and relative 5-year survival was 61.6% and 71.3%, respectively, with poorer survival for males than females. Melanomas on the head and neck and unspecified anatomical sites had the worst survival. Patients without stage information in their medical files had excellent survival, unlike patients for whom medical files were no longer available. This study shows the possibility of improving data availability and the importance of good quality population-based data.
Detecting Fake News Spreaders in Social Networks via Linguistic Detecting Fake News Spreaders in Social Networks via Linguistic and Personality Features: Notebook for PAN at CLEF 2020 and Personality Features: Notebook for PAN at CLEF 2020

This paper addresses the problem of automatically detecting fake news spreaders in social networks such as Twitter. We model the problem as a binary classiﬁcation task and consider several groups of features, including writing style, word and char n-grams, BERT semantic embedding, and sentiment analysis, which are computed from a set of tweets each user authored. Our proposed approach is evaluated on the dataset made available by the PAN at CLEF 2020 shared task on proﬁling fake news spreader, which provided labeled data in both English and Spanish. Experimental results show that we can detect fake news spreaders with an accuracy of 0.73 in English and 0.77 in Spanish when our approach is evaluated with 10-fold cross-validation on the provided training set, and with an accuracy of 0.71 in English and 0.76 in Spanish when the model is trained on the whole training set and tested on the provided test set. We also investigate the role of psycho-linguistic (LIWC) and personality features to detect fake news spreaders and ﬁnd out that personality features do have a signiﬁcant impact in user sharing behavior, achieving an accuracy of 0.72 in English and 0.80 in Spanish when evaluated with 10-fold cross-validation on the provided training set.
Crater-DETR: A Novel Transformer Network for Crater Detection Based on Dense Supervision and Multiscale Fusion

The crater detection (CD) presents challenges due to complex backgrounds, tiny scales, and dense distribution of small craters. To address these problems, we propose a new DEtection TRansformer (DETR) variant network for CD called Crater-DETR. First, we design the correspond regional attention upsample (CRAU) and pooling (CRAP) operators through cross-attention computing to address the problem of foreground–background confusion caused by the feature loss of small craters. Then, to address the weak supervision due to the fixed number query selection and to introduce dense supervision, we propose the dense auxiliary head supervise (DAHS) training. Next, automatic denoising (ADN) training is proposed to solve the problem of sparse positive queries in the decoder to improve the decoding capability. Finally, we propose a small object stable intersection over union (SOSIoU) loss to optimize the training process since the matching process is more unstable in small craters compared with other sizes of craters. Experimental results show that Crater-DETR achieves a precision of 88.13% on the DACD dataset, yielding state-of-the-art performance. Furthermore, our method also achieved the best performance on the ISDD and AI-TOD datasets, verifying its robustness.
Numerical Computation of Lyapunov Function for Hyperbolic PDE using LMI Formulation and Polytopic Embeddings

: We consider the problem of stability analysis and control synthesis for ﬁrst-order hyperbolic linear PDEs over a bounded interval with spatially varying coefﬁcients. We propose LMI-based conditions for the stability and for the design of boundary and distributed control for this class of systems. These LMI-based conditions involve an inﬁnite number of LMI. Hence, we show how to overapproximate these constraints using polytopic embeddings to reduce the problem to a ﬁnite number of LMI. We show the effectiveness of the overapproximation with several examples.
Exploring Positional Characteristics of Dual-Pixel Data for Camera Autofocus

In digital photography, autofocus is a key feature that aids high-quality image capture, and modern approaches use the phase patterns arising from dual-pixel sensors as important focus cues. However, dual-pixel data is prone to multiple error sources in its image capturing process, including lens shading or distortions due to the inherent optical characteristics of the lens. We observe that, while these degradations are hard to model using prior knowledge, they are correlated with the spatial position of the pixels within the image sensor area, and we propose a learning-based autofocus model with positional encodings (PE) to capture these patterns. Specifically, we introduce RoI-PE, which encodes the spatial position of our focusing region-of-interest (RoI) on the imaging plane. Learning with RoI-PE allows the model to be more robust to spatially-correlated degradations. In addition, we also propose to encode the current focal position of lens as lens-PE, which allows us to significantly reduce the computational complexity of the autofocus model. Experimental results clearly demonstrate the effectiveness of using the proposed position encodings for automatic focusing based on dual-pixel data.
A Game Theoretical Analysis of DAG-based ledgers Backbone

We study the rational behaviors of agents in DAG -Based Distributed Ledgers. We analyze generic algorithms that encapsulate the main actions of agents in a DAG -based distributed ledger: voting for a block, and checking its validity. Knowing that those actions have costs, and validating a block gives rewards to agents who participated in the validation procedure, we study using game theory how strategic agents behave while trying to maximize their gains. We consider scenarios with different type of agents and investigate if there exist equilibria where the properties of the protocols are guaranteed. The analysis is focused on the study of equilibria when invalid blocks may be issued. We found that in such a case, there exist equilibria where protocols properties may be violated. However, we also show that in all studied cases, there exist equilibria satifisfying the protocol properties.
ClimaMeter: Contextualising Extreme Weather in a Changing Climate

Climate change is a global challenge with multiple far-reaching consequences, including the intensification and increased frequency of many extreme weather events. In response to this pressing issue, we present ClimaMeter, a platform designed to assess and contextualise extreme weather events relative to climate change. The platform offers near real-time insights into the dynamics of extreme events, serving as a resource for researchers, policymakers
Emotional Eating and Diet-related Self-Efficacy, Motivation, and Emotional Eating and Diet-related Self-Efficacy, Motivation, and Norms in Adolescents Norms in Adolescents

Abstract The objective of the current study was to examine the association between emotional eating and self-efficacy, motivation, and social norms for consumption of fruits and vegetables (F/V) and energy-dense, nutrient-poor (EDNP) foods and beverages, as well as interactions with body mass index-z score (BMI-z). Adolescents completed self-report measures of demographics, emotional eating, and dietary health behavior theory constructs. Emotional eating was associated with lower self-efficacy for consumption of F/V and for limiting EDNP foods/beverages; greater motivation for limiting of EDNP foods/beverages; lower social norms for consumption of F/V; and greater social norms for consumption of EDNP foods/ beverages. There were no interactions with BMI-z. Evidence-based nutrition programs that leverage health behavior theories should be tailored to adolescents’ emotional eating.
Improving Critical Thinking Skills of Prospective Biology Teacher Students through Ethnoscience-Based Biology Learning

Ethnoscience is one of the activities in transforming indigenous science into scientific science that can be implemented in the biology learning process. The implementation of the ethnoscience stage in biology learning perhaps can improve students' critical thinking skills, which is the aim of this research. This research is experimental research using a pretest-posttest control group design. The research population consisted of 36 students. The sample selection used a random sampling technique consisting of 2 classes (experimental and control), each class consisting of 18 students. Research data was obtained through pretest and posttest. There are 10 questions with 5 indicators of critical thinking skills through a minimal structure essay test. The results of the research show that there is an increase in students' critical thinking skills in understanding concepts that integrate native community knowledge into scientific knowledge through the ethnoscience stage compared to critical thinking skills that do not go through ethnoscience-based learning in biology learning. Therefore, ethnoscience-based learning is recommended to be applied in the learning process in other subjects such as biotechnology and bioappliance to help improve critical thinking skills and other skills in simplifying content-rich biological material.
A Study on Internet Chinese Companies’ Response to “The Holding Foreign Companies Accountable Act” --Taking Ctrip, Baidu and BILIBILI as Examples

At the beginning of the 21st century, a large number of Chinese companies went public in the United States due to many advantages such as easier access to financing, better corporate governance structure, and different listing conditions. However, in January 2020, with the disclosure of a short-selling report on Luckin Coffee's year-long financial data falsification and fraud, Luckin Coffee's trading was officially suspended on NASDAQ in June 2020, accompanied by a high level of concern from international capital markets about Chinese stocks. Within the following year, the US Senate introduced the Foreign Company Accountability Act, which tightened securities market regulations at the legal level and raised the threshold for companies from "unenforceable inspection" regions, including China, to list in the US. Data shows that more than 90% of the listed companies facing mandatory delisting as a result of the Foreign Company Accountability Act are Chinese companies. This paper provides a preliminary behavioral analysis of Chinese stocks by examining the paths taken by several Chinese stocks in response to the conflicting effects of the Foreign Company Accountability Act and the Chinese corporate system, and the subsequent results achieved.
Decomposed and Distributed Modulation to Achieve Secure Transmission

Due to the broadcast nature of wireless transmissions, they are exposed to all surrounding entities and thus vulnerable to eavesdropping. To counter this vulnerability, we propose a new physical-layer secure transmission scheme, called DDM-Sec, based on decomposed and distributed modulation (DDM). DDM-Sec realizes traditional QPSK modulation by using two cooperative transmitters (Txs), each generating a BPSK signal, in a distributed manner. The legitimate receiver (Rx) can decode the desired/intended information from the mixed received signal while preventing the eavesdropper from accessing the legitimate user's information. DDM-Sec can effectively exploit the randomness of wireless channels to encrypt data transmission, enrich the spatial signatures of the legitimate transmission by employing two cooperative Txs. Moreover, DDM-Sec distributes user's information to two transmissions so that none of the decomposed signals alone carry the legitimate user's full information. Our theoretical analysis, hardware experiment, and simulation have shown that DDM-Sec can effectively prevent the eavesdropping, and hence guarantee the secrecy of the legitimate user's data transmission.
UvA-DARE (Digital Academic Repository) Potential for an Arctic-breeding migratory bird to adjust spring migration phenology to Arctic amplification

Arctic amplification, the accelerated climate warming in the polar regions, is causing a more rapid advancement of the onset of spring in the Arctic than in temperate regions. Consequently, the arrival of many migratory birds in the Arctic is thought to become increasingly mismatched with the onset of local spring, consequently reducing individual fitness and potentially even population levels. We used a dynamic state variable model to study whether Arctic long-distance migrants can advance their migratory schedules under climate warming scenarios which include Arctic amplification, and whether such an advancement is constrained by fuel accumulation or the ability to anticipate climatic changes. Our model predicts that barnacle geese Branta leucopsis suffer from considerably reduced reproductive success with increasing Arctic amplification through mistimed arrival, when they cannot anticipate a more rapid progress of Arctic spring from their wintering grounds. When geese are able to anticipate a more rapid progress of Arctic spring, they are predicted to advance their spring arrival under Arctic amplification up to 44 days without any reproductive costs in terms of optimal condition or timing of breeding. Negative effects of mistimed arrival on reproduction are predicted to be somewhat mitigated by increasing summer length under warming in the Arctic, as late arriving geese can still breed successfully. We conclude that adaptation to Arctic amplification may rather be constrained by the (un)predictability of changes in the Arctic spring than by the time available for fuel accumulation. Social migrants like geese tend to have a high behavioural plasticity regarding stopover site choice and migration schedule, giving them the potential to adapt to future climate changes on their flyway.
Efﬁcient land seismic data reconstruction from sparse measurements

Acquisition of high-quality land seismic data requires (expensive) dense source and receiver geometry to avoid aliasing-related problems. Alternatively, acquisition using the concept of compressive sensing (CS) allows for similarly high quality land seismic data using fewer measurements provided that the designed geometry and sparse recovery strategy are well matched. We propose a complex wavelet-based sparsity-promoting waveﬁeld reconstruction strategy to overcome challenges in land seismic data interpolation using the compressive sensing framework. Despite having lower angular sensitivity than curvelets, complex wavelets enable the improved reconstruction of sparsely acquired land data while being faster and requiring less storage. The complex wavelet transform operates outside of the Fourier domain, which localizes aliasing-related artifacts likely to be present in ﬁeld data, and yields reconstructions with fewer artifacts and higher signal-to-noise ratios. We demonstrate that the data recovery success depends on both the number and the geometry of the missing traces as revealed by analyzing reconstructions from multiple realizations of trace geometry and data decimation ratios. Using half the number of traces required by the regular sampling rules and thus reducing the acquisition costs, we show that data are appropriately reconstructed provided that there are no big gaps in the strategic places.
Totally endoscopic versus conventional septoplasty assisted by Totally endoscopic versus conventional septoplasty assisted by endoscope endoscope

Background: Traditional septoplasty is being phased out in favor of endoscopic septoplasty. It ensures minimal tissue dissection and fewer surgical problems. Aim of the study: Evaluation the effectiveness of the endoscopic septoplasty for correction of different types of septal deformity (deviation_ spur ) compared to endoscopic assisted conventional septoplasty. Patients and Methods: This prospective study was conducted on 60 patients of both sex, who attached to the out-patient E.N. T clinic at Bab El Sharaya (Sayed Galal) Hospital from April of 2021 to March of 2022 distributed as 2 same groups: Group A included thirty patients submit to totally endoscopic septoplasty and group B involved thirty patients underwent conventional septoplasty assisted by endoscope . All the patients suffering from nasal obstruction due to a significant septal deviation. Results: Both groups had no significant differences in age or gender. While there was a substantial difference in the duration of operation and intraoperative blood loss between the two groups. The length ranged from 20 to 50 minutes in group A and 35 to 65 minutes in group B, while the blood loss ranged from 25 to 65 ml in group A and 45 to 90 ml in group B. In this study, the difference between the endoscopic and conventional groups was statistically insignificant in terms of early post-operative complications like nasal synechiae, septal hematoma, septal perforation, or CSF leakage, as well as the intraoperative flap and late post-operative complications after 3 months in both groups. Conclusion: Both techniques are effective in reducing nasal obstruction and related symptoms with fewer overall complications in the endoscopic approach.
Proving Renaming for Haskell via Dependent Types: A Case-Study in Refactoring Soundness Extended Abstract

We present a formally veriﬁed renaming refactoring for a subset of Haskell 98 giving a case-study in proving soundness properties of Haskell refactorings. Our renaming is implemented in the dependently-typed language Idris, which allows us to encode soundness proofs as an integral part of the implementation. We give the formal deﬁnition of our static semantics for our Haskell 98 subset, which we encode as part of the AST, ensuring that only well-formed programs may be represented and transformed. This forms a foundation upon which refactorings can be formally speciﬁed. We then deﬁne soundness of refactoring implementations as conformity to their speciﬁcation. We demonstrate our approach via renaming, a canonical and well-understood refactoring, giving its implementation alongside its formal speciﬁcation and soundness proof.
The impact of diversification strategy on corporate financial performance

Using Yunnan Baiyao as a research case, this paper examines the impact of a firm's diversification strategy on its financial performance after its implementation. By exploring the impact of the firm's dynamic capabilities on the diversification strategy and analyzing the financial and non-financial factors before and after Yunnan Baiyao's implementation of the diversification strategy, we find that Yunnan Baiyao's adoption of the diversification strategy has contributed to the firm's financial performance to a certain extent. At the same time, the company also faces a series of risks and challenges.
Single-Threshold Food Labeling Policies

: We study the aggregate and heterogeneous effects of a front-of-package labeling policy implemented in Chile. We find that consumers reduced their sugar and caloric intake by 9% and 6%, reductions explained by consumers purchasing healthier products and firms reformulating their offerings. On the demand side, labels prompt consumers to substitute within categories rather than between categories. Within-category responses are more pronounced when labels provide new information. On the supply side, we observe bunching at regulatory thresholds with substantial heterogeneity across categories, consistent with heterogeneous costs of product reformulation. We conclude that considering policy-response heterogeneity is key for effective policy design
Scholarly Commons @ Baptist Health South Florida Scholarly Commons @ Baptist Health South Florida

: Improvements in cardiovascular disease (CVD) rates among young adults in the past 2 decades have been offset by increasing racial/ethnic and gender disparities, persistence of unhealthy lifestyle habits, overweight and obesity, and other CVD risk factors. To enhance the promotion of cardiovascular health among young adults 18 to 39 years old, the medical and broader public health community must understand the biological, interpersonal, and behavioral features of this life stage. Therefore, the National Heart, Lung, and Blood Institute, with support from the Office of Behavioral and Social Science Research, convened a 2-day workshop in Bethesda, Maryland, in September 2017 to identify research challenges and opportunities related to the cardiovascular health of young adults. The current generation of young adults live in an environment undergoing substantial economic, social, and technological transformations, differentiating them from prior research cohorts of young adults. Although the accumulation of clinical and behavioral risk factors for CVD begins early in life, and research suggests early risk is an important determinant of future events, few trials have studied prevention and treatment of CVD in participants <40 years old. Building an evidence base for CVD prevention in this population will require the engagement of young adults, who are often disconnected from the healthcare system and may not prioritize long-term health. These changes demand a repositioning of existing evidence-based treatments to accommodate new sociotechnical contexts. In this article, the authors review the recent literature and current research opportunities to advance the cardiovascular health of today’s young adults.