Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Validation of an Explainable Radiomics Model to Predict High-Aggressive Prostate Cancer: A Multicenter Radiomics Study Based on Biparametric MRI

Simple Summary Prostate cancer (PCa) is one of the leading causes of mortality for men worldwide. PCa aggressiveness affects the patient’s prognosis, with less aggressive tumors, i.e., Grade Group (GG) 1 and 2, having lower mortality and better outcomes. For this reason, the aim of this study is to distinguish between GG ≤ 2 and ≥3 PCa using an automatic and noninvasive approach based on artificial intelligence methods. The results obtained are promising, as the system achieved robust results on a multicenter external dataset. If further validated, this approach, combined with the expert knowledge of urologists, could help identify PCa patients who have a better prognosis and may benefit from less invasive treatments. Abstract In the last years, several studies demonstrated that low-aggressive (Grade Group (GG) ≤ 2) and high-aggressive (GG ≥ 3) prostate cancers (PCas) have different prognoses and mortality. Therefore, the aim of this study was to develop and externally validate a radiomic model to noninvasively classify low-aggressive and high-aggressive PCas based on biparametric magnetic resonance imaging (bpMRI). To this end, 283 patients were retrospectively enrolled from four centers. Features were extracted from apparent diffusion coefficient (ADC) maps and T2-weighted (T2w) sequences. A cross-validation (CV) strategy was adopted to assess the robustness of several classifiers using two out of the four centers. Then, the best classifier was externally validated using the other two centers. An explanation for the final radiomics signature was provided through Shapley additive explanation (SHAP) values and partial dependence plots (PDP). The best combination was a naïve Bayes classifier trained with ten features that reached promising results, i.e., an area under the receiver operating characteristic (ROC) curve (AUC) of 0.75 and 0.73 in the construction and external validation set, respectively. The findings of our work suggest that our radiomics model could help distinguish between low- and high-aggressive PCa. This noninvasive approach, if further validated and integrated into a clinical decision support system able to automatically detect PCa, could help clinicians managing men with suspicion of PCa.
Transductive Classiﬁcation on Heterogeneous Information Networks with Edge Betweenness-based Normalization

This paper proposes a novel method for transductive classi-ﬁcation on heterogeneous information networks composed of multiple types of vertices. Such networks naturally represent many real-world Web data such as DBLP data (author, paper, and conference). Given a network where some vertices are labeled, the classiﬁer aims to predict labels for the remaining vertices by propagating the labels to the entire network. In the label propagation process, many studies reduce the importance of edges connecting to a high-degree vertex. The assumption is unsatisfactory when reliability of a label of a vertex cannot be implied from its degree. On the basis of our intuition that edges bridging across communities are less trustworthy, we adapt edge betweenness to imply the importance of edges. Since directly applying the conventional edge betweenness is ineﬃcient on heterogeneous networks, we propose two additional reﬁnements. First, the centrality utilizes the fact that networks contain multiple types of vertices. Second, the centrality ignores ﬂows originating from endpoints of considering edges. The experimental results on real-world datasets show our proposed method is more eﬀec-tive than a state-of-the-art method, GNetMine. On average, our method yields 92.79 ± 1.25% accuracy on a DBLP network even if only 1.92% of vertices are labeled. Our simple weighting scheme results in more than 5 percentage points increase in accuracy compared with GNetMine.
Highly Efficient and Differentially Driven Thin-Film Lithium Niobate Modulators Based on Reversely-Poled Arms

A novel structure with reversely-poled arms is proposed on the X-cut thin-film Lithium Niobate platform. A highly efficient and differentially driven phase-shifter can be achieved with a VπL of 1.37 V.cm (calculated to be equivalent to widely used single-ended push-pull scheme) and neglectable excess optical loss. A differentially driven modulator is demonstrated with 75GHz EO bandwidth and Vπ of 2 V.
An Algorithm Restricting Motion into Curve-Like Forbidden Regions

In robotic systems, there are often parts of the workspace where motion may cause damage to surrounding environment or the system itself. For such systems, forbidden regions are defined and motion into these are restricted by special algorithms. It is essential to keep these regions at optimal size and shape in order to ensure maximum operational capability whilst avoiding any risks of damage. In this paper, a hierarchical algorithm tackling these problems for two-axis gimballed systems and motion forbidden regions defined by second order curves is proposed. The method also supports safe operation in case of multiple dynamic forbidden regions in real-time. The proposed algorithm is verified through simulations and experiments conducted on an actual surveillance system.
Framework of Systems for Creating Intelligent Behaviors of Imaginary Creatures for Humans

The paper proposes a framework of systems for creating intelligent behaviors of imaginary creatures for humans, which is built upon a framework of swarm intelligence optimization algorithms. The paper assumes and models an imaginary slime mold, which is an amoeboid unicellular creature, as an imaginary creature in the framework concretely. In addition, the paper conducts basic evaluations of the framework. Various swarm intelligence optimization algorithms have been proposed so far, but there is a common feature among them. That is that a set of search points in a search space, which are called individuals, move around in the space according to algorithm specific rules using fitness values of the individuals, and the differences among algorithms are in algorithm specific rules. Therefore, under the use of one swarm intelligence optimization algorithm, that is, one particular set of rules, if a fitness function is varied, behaviors of individuals are also varied. Based on this fact, the proposed framework optimizes a parametric fitness function for individuals to behave intelligently for a human. In the basic evaluation of the concrete system, a fitness function of computer program which returns a fitness value calculated with a distribution of individuals is used instead of a human, and it is demonstrated that optimization of a parametric fitness function indeed yields desired behaviors of individuals.
Analytics and Data-Driven Methods and Practices in Platform Ecosystems: a systematic literature review

The emergence of platform ecosystems has transformed the business landscape in many industries, giving rise to novel modes of interorganizational cooperation and value co-creation, as well as unconventional challenges. The vast traces of data generated by platform ecosystems makes them ripe for the use of analytics and data-driven methods aimed at improving their health, performance, business outcomes, and evolution. However, the research on the application of analytics within platform ecosystems is limited and spread across multiple disciplines. To address this gap, we conducted a systematic literature review on the application of analytics and data-driven methods and practices within platform ecosystems. A total of 56 studies were reviewed, and underwent data extraction, analysis, and synthesis processes. In addition to presenting themes and patterns in the recent and relevant literature on platform ecosystems analytics, our review offers the following outcomes: an actionable overview of the analytics toolbox currently used within platform ecosystems—spanning domains such as machine learning, deep learning, data science, modelling, simulation, among others—; a roadmap for practitioners to achieve analytics maturity; and a summary of underexplored research areas.
Implications of Exposure to Air Pollution on Male Reproduction: The Role of Oxidative Stress

Air pollution, either from indoor (household) or outdoor (ambient) sources, occurs when there is presence of respirable particles in the form of chemical, physical, or biological agents that modify the natural features of the atmosphere or environment. Today, almost 2.4 billion people are exposed to hazardous levels of indoor pollution, while 99% of the global population breathes air pollutants that exceed the World Health Organization guideline limits. It is not surprising that air pollution is the world’s leading environmental cause of diseases and contributes greatly to the global burden of diseases. Upon entry, air pollutants can cause an increase in reactive oxygen species (ROS) production by undergoing oxidation to generate quinones, which further act as oxidizing agents to yield more ROS. Excessive production of ROS can cause oxidative stress, induce lipid peroxidation, enhance the binding of polycyclic aromatic hydrocarbons (PAHs) to their receptors, or bind to PAH to cause DNA strand breaks. The continuous and prolonged exposure to air pollutants is associated with the development or exacerbation of pathologies such as acute or chronic respiratory and cardiovascular diseases, neurodegenerative and skin diseases, and even reduced fertility potential. Males and females contribute to infertility equally, and exposure to air pollutants can negatively affect reproduction. In this review, emphasis will be placed on the implications of exposure to air pollutants on male fertility potential, bringing to light its effects on semen parameters (basic and advanced) and male sexual health. This study will also touch on the clinical implications of air pollution on male reproduction while highlighting the role of oxidative stress.
Fingerprinting Obfuscated Proxy Traffic with Encapsulated TLS Handshakes

The global escalation of Internet censorship by nation-state actors has led to an ongoing arms race between censors and obfuscated circumvention proxies. Research over the past decade has extensively examined various fingerprinting attacks against individual proxy protocols and their respective countermeasures. In this paper, however, we demonstrate the feasibility of a protocol-agnostic approach to proxy detection, enabled by the shared characteristic of nested protocol stacks inherent to all forms of proxying and tunneling activities. We showcase the practicality of such an approach by identifying one specific fingerprint–encapsulated TLS handshakes–that results from nested protocol stacks, and building similarity-based classifiers to isolate this unique fingerprint within encrypted traffic streams. Assuming the role of a censor, we build a detection framework and deploy it within a mid-size ISP serving upwards of one million users. Our evaluation demonstrates that the traffic of obfuscated proxies, even with random padding and multiple layers of encapsulations, can be reliably detected with minimal collateral damage by fingerprinting encapsulated TLS handshakes. While stream multiplexing shows promise as a viable countermeasure, we caution that existing obfuscations based on multiplexing and random padding alone are inherently limited, due to their inability to reduce the size of traffic bursts or the number of round trips within a connection. Proxy developers should be aware of these limitations, anticipate the potential exploitation of encapsulated TLS handshakes by the censors, and equip their tools with proactive countermeasures.
Japan's Negative Risk Premium in Interest Rates: The Liquidity Trap and the Fall in Bank Lending

May 2002 Japan's interest rates have been compressed toward zero because of pressure coming through the foreign exchanges. Twenty years of current account surpluses have led to a huge build up of claims – mainly dollars – on foreigners. Because of ongoing fluctuations in the yen/dollar exchange rate, Japanese financial institutions will only willingly hold these dollar claims if the nominal yield on them is substantially higher than on yen assets. In the 1990s to 2002 as U.S. interest rates have come down, portfolio equilibrium has been sustained only when nominal interest rates on yen assets have been forced toward zero. One consequence is the now infamous liquidity trap for Japanese monetary policy. A second consequence is the erosion of the normal profit margins of Japan's commercial bank leading to a slump in new bank credit and an inability to grow out of the overhang of old bad loans. Working Papers Index
Left Barrel Cortical Neurons Activity following Transplantation of Stem Cells into Right Lesioned-Barrel Cortex in Rats

Objective: Stem cells (SCs) can improve the functional defects of brain injury. Rodents use their whiskers to get tactile information from their surroundings. The aim of this study was to investigate whether the transplantation of SCs into the lesioned barrel cortex can help neuronal function in the contralateral cortex. Materials and Methods: Sixteen male Wistar rats (200-230 g) were used in this experimental study. We induced a mechanical lesion in the right barrel cortex area of rats by removing this area by a 3 mm skin punch. Four groups containing one intact group of rats: group 1: control, and three lesion groups, group 2: lesion+un-differentiated dental pulp SCs (U-DPSCs), group 3: lesion+differentiated dental pulp SCs (D-DPSCs), and group 4: cell medium (vehicle) that were injected in the lesion area. Three weeks after transplantation of SCs or cell medium, the rats’ responses of left barrel cortical neurons to controlled deflections of right whiskers were recorded by using the extracellular single-unit recordings technique. Results: The results showed that the neural spontaneous activity and response magnitude of intact barrel cortex neurons in the lesion group decreased significantly (P<0.05) compared to the control group while ON and OFF responses were improved in the D-DPSCs (P<0.001) group compared to the vehicle group three weeks after transplantation. Conclusion: Transplantation of dental pulp mesenchymal SCs significantly improved the neural responses of the left barrel cortex that was depressed in the vehicle group.
LipAT: Beyond Style Transfer for Controllable Neural Simulation of Lipstick using Cosmetic Attributes

Lipstick virtual try-on (VTO) experiences have become widespread across the e-commerce sector and assist users in eliminating the guesswork of shopping online. However, such experiences still lack in both realism and accuracy. In this work, we propose LipAT, a neural framework that blends the strengths of Physics-Based Rendering (PBR) and Neural Style Transfer (NST) approaches to directly apply lipstick onto face images given lipstick attributes (e.g., colour, finish type). LipAT consists of a physics aware neural lipstick application module (LAM) to apply lipstick on face images given its attributes and Lipstick Refiner Module (LRM) to improve the realism by refining the imperfections. Unlike the NST approaches, LipAT allows precise and controllable lipstick attribute preservation, without requiring crude approximations and inference of various intertwined environment factors (e.g., scene lighting, face structure etc) involved in image generation that is required for accurate PBR. We propose an experimental framework with quantitative metrics to evaluate different desirable aspects of the lipstick attribute driven try-on alongside user studies to further validate our findings. Our results show that LipAT considerably outperforms fully-automated PBR approaches in preserving realism and the NST approaches in preserving various lipstick attributes such as finish types.
The Decay of Two Adjacent Sunspots Associated with Moving Magnetic Features

The relationship between the decay of sunspots and moving magnetic features (MMFs) plays an important role in understanding the evolution of active regions. We present observations of two adjacent sunspots, the gap between them, and a lot of MMFs propagating from the gap and the sunspots' outer edges in NOAA Active Region 13023. The MMFs are divided into two types based on their magnetic field inclination angle: vertical (0° < γ < 45°) and horizontal (45° ≤ γ < 90°) MMFs (V-MMFs and H-MMFs, respectively). The main results are as follows: (1) the mean magnetic flux decay rates of the two sunspots are −1.7 × 1020 and −1.4 × 1020 Mx day−1; (2) the magnetic flux generation rate of all MMFs is calculated to be −1.9 × 1021 Mx day−1, which is on average 5.6 times higher than the total magnetic flux loss rate of the sunspots; (3) the magnetic flux of V-MMFs (including a pore separated from the sunspots) is 1.4 times larger than the total lost magnetic flux of the two sunspots, and in a later stage when the pore has passed through the reference ellipse, the magnetic flux generation rate of the V-MMFs is almost the same as the magnetic flux loss rate of the sunspots; and (4) within the gap, the magnetic flux of V-MMFs is one-third of the total magnetic flux. Few V-MMFs stream out from the sunspots at the nongap region. All observations suggest that MMFs with vertical magnetic fields are closely related to the disintegration of the sunspot, and most of the MMFs from the gap may originate directly from the sunspot umbra.
Recent advances in combined Positron Emission Tomography and Magnetic Resonance Imaging

Hybrid imaging modalities combine two or more medical imaging techniques offering exciting new possibilities to image the structure, function and biochemistry of the human body in far greater detail than has previously been possible to improve patient diagnosis. In this context, simultaneous Positron Emission Tomography and Magnetic Resonance (PET/MR) imaging offers great complementary information, but it also poses challenges from the point of view of hardware and software compatibility. The PET signal may interfere with the MR magnetic field and vice-versa, posing several challenges and constrains in the PET instrumentation for PET/MR systems. Additionally, anatomical maps are needed to properly apply attenuation and scatter corrections to the resulting reconstructed PET images, as well motion estimates to minimize the effects of movement throughout the acquisition. In this review, we summarize the instrumentation implemented in modern PET scanners to overcome these limitations, describing the historical development of hybrid PET/MR scanners. We pay special attention to the methods used in PET to achieve attenuation, scatter and motion correction when it is combined with MR, and how both imaging modalities may be combined in PET image reconstruction algorithms.
The World Trade Center Exposome and Health Effects in 9/11 Rescue and Recovery Workers

In the aftermath of the World Trade Center (WTC) attack, rescue and recovery workers faced hazardous conditions and toxic agents. Prior research linked these exposures to adverse health effects, but mainly examined individual factors, overlooking complex mixture effects. This study applies an exposomic approach encompassing the totality of responders’ experience, defined as the WTC exposome. We analyzed data from 34,096 members of the WTC Health Program General Responder, including mental and physical health, occupational history, traumatic and environmental exposures using generalized weighted quantile sum regression. We find a significant association between the exposure mixture index all investigated health outcomes. Factors identified as risk factors include working in an enclosed heavily contaminated area, construction occupation, and exposure to blood and body fluids. Conversely, full-time employment emerged as a protective factor. This exposomics study emphasizes the importance of considering combined exposures. In an era marked by more frequent and severe natural disasters due to the evolving climate crisis, the exposomic framework holds promise as a valuable tool for disaster preparedness.
Intermolecular interactions in mixed dye systems and the effects on dye wastewater treatment processes

Dye wastewater discharge is a critical concern across textiles, paper, cosmetics, and other industries. This study explores the impact of dye–dye interactions on chemical coagulation and ultrafiltration process. Using basic and reactive dyes, representing cationic and anionic compounds, the intricate interplay between these dyes was examined through spectroscopic analysis. Remarkably, interactions between dyes of opposite charges exhibited significant effects on both techniques. Electrostatic attractions played a key role. Positive coagulant hydrolysates selectively attracted negative dyes, while negatively charged membranes effectively captured positive dyes. Combining dyes with opposite charges resulted in enhanced removal efficiency, addressing challenging dyes collectively. This discovery offers a novel approach to improving dye removal, utilizing opposite-charged dye mixtures can tackle stubborn dyes unmanageable by conventional methods.
Intention to quit and its correlates among dieticians residing in the United Arab Emirates during the COVID-19 pandemic: A cross-sectional survey

Background The COVID-19 pandemic precipitated increased workload, stress, and burnout on healthcare providers on the frontlines of the pandemic, dieticians were no exception. Such unprecedented occupational risks and stressors contributed to a higher intention to quit, potentially leading to workforce shortages, and hindering the delivery of quality care, especially for patients with chronic conditions. The aim of this study was to examine the prevalence factors associated with the intention to quit among dieticians in the United Arab Emirates during a public health emergency. Methods The study utilized a cross-sectional design with an online survey sent to dieticians between January and May 2021. The final version of the questionnaire included four sections: A sociodemographic section, intention to quit, work-related practices and challenges, as well as the resilience scale using the 25 items- Connor-Davidson Resilience Scale© (CD-RISC). Descriptive statistics as well as simple and multiple logistic regression analyses were carried out to explore factors associated with the intention to quit among dieticians. Results Study results revealed that a quarter of dieticians intend to quit their jobs. Higher odds of intention to quit among dieticians were significantly associated with male gender, younger age, having a chronic condition, being non-resilient, feeling unappreciated, using online platforms for dietary counseling, reporting increased workload, and working from home or in a blended format during the pandemic. Conclusion This study revealed a high intention to quit among dieticians during the COVID-19 pandemic and identified a few correlates for the intention to quit that could support the development of evidence-based interventions. Such interventions should address through targeted programs the challenges faced by male dieticians, younger dieticians, as well as dieticians with Chronic health conditions. Furthermore, the findings of this study showed that promoting resilience among dieticians is crucial in reducing their intention to quit.