Flax (Linum usitatissimum L.), as the earliest oil and fiber crop, is a model plant for genetic inferences of plant domestication processes involving multiple domestication events. However, a puzzle has emerged from several genetic studies, as dehiscent cultivated flax is genetically more related to its progenitor pale flax (L. bienne Mill.), and winter cultivated flax is well mixed with oil or fiber cultivated flax, while capsular dehiscence and winter hardiness are the major characteristics of pale flax. For this, a comparative analysis was conducted with 16 Linum samples representing pale flax and four domestication groups of cultivated flax (oil, fiber, winter, and dehiscent) using 454 pyrosequencing, Sanger resequencing and microsatellite data. It was found that the genomic sampling of genetic variants from the three applied methods yielded similar genetic information on pale flax and four groups of cultivated flax. The revealed genetic relationships did not show significant departures from the previous findings, but instead supported an early, independent domestication of a primitive flax lineage for oil use, followed by a subsequent flax domestication process with multiple domestication events for capsular dehiscence, oil, fiber and winter hardiness. Domestication on capsular dehiscence occurred earlier than domestication on winter hardiness. Domestication on winter hardiness was more complicated than domestication on capsular dehiscence. Full article

The automatic segmentation of cardiac computed tomography (CT) and magnetic resonance imaging (MRI) plays a pivotal role in the prevention and treatment of cardiovascular diseases. In this study, we propose an efficient network based on the multi-scale, multi-head self-attention (MSMHSA) mechanism. The incorporation of this mechanism enables us to achieve larger receptive fields, facilitating the accurate segmentation of whole heart structures in both CT and MRI images. Within this network, features extracted from the shallow feature extraction network undergo a MHSA mechanism that closely aligns with human vision, resulting in the extraction of contextual semantic information more comprehensively and accurately. To improve the precision of cardiac substructure segmentation across varying sizes, our proposed method introduces three MHSA networks at distinct scales. This approach allows for fine-tuning the accuracy of micro-object segmentation by adapting the size of the segmented images. The efficacy of our method is rigorously validated on the Multi-Modality Whole Heart Segmentation (MM-WHS) Challenge 2017 dataset, demonstrating competitive results and the accurate segmentation of seven cardiac substructures in both cardiac CT and MRI images. Through comparative experiments with advanced transformer-based models, our study provides compelling evidence that despite the remarkable achievements of transformer-based models, the fusion of CNN models and self-attention remains a simple yet highly effective approach for dual-modality whole heart segmentation. Full article

Background: Dementia is a significant health issue worldwide. Mild cognitive impairment (MCI) can transform into dementia over time. General practitioners (GPs) may be the first to notice the cognitive deficit; therefore, it is crucial for them to have access to a screening test that can be administered quickly and efficiently. We explored the Hungarian version of the Test Your Memory self-administered dementia screening test in general practice for the early detection of dementia and cognitive impairment. Methods: In the four Hungarian cities with medical universities, 368 patients over the age of 50 attending GPs filled out the questionnaire within the framework of our cross-sectional study. Results: The total scores of the test showed a significant correlation with education and type of occupation and a significant negative correlation with age. The results of this research showed that the clock drawing and recall subtest scores deteriorate at the earliest age. Conclusion: The test can be filled out in a GP’s office easily and two of its subtests can raise the possibility that patients may need further assessment, especially if they have symptoms, at an earlier age than the other subtests. Full article

The purpose of this study was to investigate the effects of different diluents and freezing methods on the quality of thawed sperm after cryopreservation and find an inexpensive and practical method for freezing Hu ram semen for use in inseminations under farm conditions. Ejaculates were collected from five Hu rams. In experiment I, ejaculates were diluted with eight different freezing diluents (basic diluents A, B, C, D, E, F, G, and H). After dilution and cooling, the samples were loaded into 0.25 mL straws and frozen using the liquid nitrogen fumigation method. In experiment II, diluent C was used as the basic diluent and the semen was frozen using liquid nitrogen fumigation and two program-controlled cooling methods. For analysis, frozen samples were evaluated in terms of motility parameters (total motility (TM), progressive motility (PM)), biokinetic characteristics (straight-line velocity (VSL), average path velocity (VAP), curvilinear velocity (VCL), amplitude of lateral head displacement (ALH), wobble movement coefficient (WOB), average motion degree (MAD)), reactive oxygen species (ROS) level, and membrane and acrosome integrity. In experiment I, diluent C had higher TM, PM, and acrosome and membrane integrity and lower ROS compared to other extenders (p < 0.05) except diluent A. Diluent C exhibited higher (p < 0.05) VCL, VAP, ALH, WOB, and MAD compared to diluents B, D, E, and F. In experiment II, TM and all biokinetic characteristics did not show significant differences (p > 0.05) amongst the three freezing methods. Liquid nitrogen fumigation resulted in higher (p < 0.05) PM, membrane integrity, acrosome integrity, and lower ROS level compared to the program. In conclusion, the thawed semen diluted with diluent C had higher quality compared to other diluents. The liquid nitrogen fumigation demonstrated superior semen cryopreservation effects compared to the program-controlled cooling method using diluent C. Full article

Microplastic pollution is a pervasive global issue affecting various ecosystems. Despite the escalating production and well-documented contamination in both aquatic and terrestrial environments, the research focused on airborne microplastics and their interaction with terrestrial birds remains limited. In this study, we collected fecal sacs from Common swifts (Apus apus) to investigate their diet and to evaluate the potential ingestion of microplastics by both adults and nestlings. The diet was mainly composed of Hymenoptera and Coleoptera and did not differ among sexes and age classes. The 33% of nestlings’ and 52% of adults’ fecal sacs contained anthropogenic items, the totality of which was in the shape form of fibers. The 19.4% of the anthropogenic items were chemically characterized as microplastics, either polyethylene terephthalate (PET; two microfibers) or cellophane (four microfibers). Airborne anthropogenic items, including microplastic, might be passively ingested during the Common swift aerial feeding. In addition, our findings suggest that these ingested microparticles have the potential to be transferred to the offspring through food. While further research is essential to elucidate the pathways of microplastic ingestion, our results reinforce the evidence of the transfer of anthropogenic items from the atmosphere to the biota. Full article

Pyroptosis represents a type of cell death mechanism notable for its cell membrane disruption and the subsequent release of proinflammatory cytokines. The Nod-like receptor family pyrin domain containing inflammasome 3 (NLRP3) plays a critical role in the pyroptosis mechanism associated with various diseases resulting from particulate matter (PM) exposure. Tert-butylhydroquinone (tBHQ) is a synthetic antioxidant commonly used in a variety of foods and products. The aim of this study is to examine the potential of tBHQ as a therapeutic agent for managing sinonasal diseases induced by PM exposure. The occurrence of NLRP3 inflammasome-dependent pyroptosis in RPMI 2650 cells treated with PM < 4 µm in size was confirmed using Western blot analysis and enzyme-linked immunosorbent assay results for the pyroptosis metabolites IL-1β and IL-18. In addition, the inhibitory effect of tBHQ on PM-induced pyroptosis was confirmed using Western blot and immunofluorescence techniques. The inhibition of tBHQ-mediated pyroptosis was abolished upon nuclear factor erythroid 2-related factor 2 (Nrf2) knockdown, indicating its involvement in the antioxidant mechanism. tBHQ showed potential as a therapeutic agent for sinonasal diseases induced by PM because NLRP3 inflammasome activation was effectively suppressed via the Nrf2 pathway. Full article

Chatbots are computer programs that mimic human conversation using text or voice or both. Users’ acceptance of chatbots is highly influenced by their persona. Users develop a sense of familiarity with chatbots as they use them, so they become more approachable, and this encourages them to interact with the chatbots more readily by fostering favorable opinions of the technology. In this study, we examine the moderating effects of persona traits on students’ acceptance and use of chatbot technology at higher educational institutions in the UK. We use an Extended Unified Theory of Acceptance and Use of Technology (Extended UTAUT2). Through a self-administrated survey using a questionnaire, data were collected from 431 undergraduate and postgraduate computer science students. This study employed a Likert scale to measure the variables associated with chatbot acceptance. To evaluate the gathered data, Structural Equation Modelling (SEM) coupled with multi-group analysis (MGA) using SmartPLS3 were used. The estimated Cronbach’s alpha highlighted the accuracy and legitimacy of the findings. The results showed that the emerging factors that influence students’ adoption and use of chatbot technology were habit, effort expectancy, and performance expectancy. Additionally, it was discovered that the Extended UTAUT2 model did not require grades or educational level to moderate the correlations. These results are important for improving user experience and they have implications for academics, researchers, and organizations, especially in the context of native chatbots. Full article

This study evaluates, for the first time, the effects of UV/PMS and UV/H₂O₂/PMS processes on the degradation of sunscreen agents in synthetic and natural water matrices and compares their effectiveness with the more conventional UV/H₂O₂. Investigations were conducted using a mixture of organic UV filters containing 4-methylbenzylidene camphor (4-MBC) and 2-ethylhexyl-4-methoxycinnamate. Among the investigated UV-driven AOPs, UV/PMS/H₂O₂ was the most effective in synthetic water, while in natural water, the highest degradation rate was observed during the degradation of EHMC by UV/PMS. The degradation of UV filters in the UV/PMS system was promoted by sulfate radical (68% of the degradation), with hydroxyl radical contributing approximately 32%, while both radical species contributed approximately equally to the degradation in the UV/H₂O₂/PMS system. The Vibrio fischeri assay showed an increase in inhibition (up to 70%) at specific stages of UV/H₂O₂ treatment when applied to natural water, which further decreased to 30%, along with an increase in UV fluence and progressive degradation. The Pseudomonas putida test recorded minor toxicity (<15%) after treatments. Magnetic biochar utilized in conjunction with UV-driven AOPs exhibited superior performance in eliminating residual contaminants, providing an efficient and sustainable approach to mitigate sunscreen agents in water treatment. Full article

The usage of copper (Cu) ores containing low or no arsenic (As) has reduced, and Cu ores containing high levels of As have emerged as vital mineral resources for Cu extraction and processing. The quality of the Cu ores has decreased from 1.6% to approximately 1.0%. The proportion of As to Cu in 15% of Cu resources currently reaches 1:5. However, during the extraction and processing of Cu ores, As presents significant environmental harm. Hence, safely and effectively removing As is paramount in Cu smelting and processing, holding substantial importance in fostering environmentally sustainable practices within the Cu extraction and processing industry. This article consolidates the resource distribution of As-containing Cu (ACC) ores, comprehensively and systematically evaluates the present advancements in extracting techniques for these minerals, and identifies the challenges inherent in pyrometallurgical and wet processes for treating ACC deposits. Pyrometallurgy is a simple primary roasting technique and has widespread applicability in the treatment of various ACC minerals. Its disadvantages are the emission of exhaust gas and the high treatment costs associated with it. The wet arsenic removal method boasts advantages including minimal air pollution and a high resource recovery rate, significantly aiding in Cu concentrate recovery; its major drawback is the production of As-containing wastewater. The hydrometallurgical removal of As from ACC mines involves extracting As through leaching. Recently, biometallurgy has presented innovative solutions using specialized microorganisms to bioleach or bioabsorb As, but large-scale industrial applications still lack specific practical implementation. This review explores the underlying causes of the challenges encountered in processing ACC minerals. Additionally, it highlights pyrometallurgical roasting coupled with high-temperature filtration as a pivotal advancement in the extraction and processing of ACC ores. Full article

Machine learning technologies are being integrated into robotic systems faster to enhance their efficacy and adaptability in dynamic environments. The primary goal of this research was to propose a method to develop an Autonomous Mobile Robot (AMR) that integrates Simultaneous Localization and Mapping (SLAM), odometry, and artificial vision based on deep learning (DL). All are executed on a high-performance Jetson Nano embedded system, specifically emphasizing SLAM-based obstacle avoidance and path planning using the Adaptive Monte Carlo Localization (AMCL) algorithm. Two Convolutional Neural Networks (CNNs) were selected due to their proven effectiveness in image and pattern recognition tasks. The ResNet18 and YOLOv3 algorithms facilitate scene perception, enabling the robot to interpret its environment effectively. Both algorithms were implemented for real-time object detection, identifying and classifying objects within the robot’s environment. These algorithms were selected to evaluate their performance metrics, which are critical for real-time applications. A comparative analysis of the proposed DL models focused on enhancing vision systems for autonomous mobile robots. Several simulations and real-world trials were conducted to evaluate the performance and adaptability of these models in navigating complex environments. The proposed vision system with CNN ResNet18 achieved an average accuracy of 98.5%, a precision of 96.91%, a recall of 97%, and an F1-score of 98.5%. However, the YOLOv3 model achieved an average accuracy of 96%, a precision of 96.2%, a recall of 96%, and an F1-score of 95.99%. These results underscore the effectiveness of the proposed intelligent algorithms, robust embedded hardware, and sensors in robotic applications. This study proves that advanced DL algorithms work well in robots and could be used in many fields, such as transportation and assembly. As a consequence of the findings, intelligent systems could be implemented more widely in the operation and development of AMRs. Full article

Investigating dependence structures across various fields holds paramount importance. Consequently, the creation of new copula families plays a crucial role in developing more flexible stochastic models that address the limitations of traditional and sometimes impractical assumptions. The present article derives some reasonable conditions for validating a copula of the ratio-type form $uv/(1-\theta f(u\left)g\right(v\left)\right)$. It includes numerous examples and discusses the admissible range of parameter $\theta$, showcasing the diversity of copulas generated through this framework, such as Archimedean, non-Archimedean, positive dependent, and negative dependent copulas. The exploration extends to the upper bound of a general family of copulas, $uv/(1-\theta \varphi (u,v\left)\right)$, and important properties of the copula are discussed, including singularity, measures of association, tail dependence, and monotonicity. Furthermore, an extensive simulation study is presented, comparing the performance of three different estimators based on maximum likelihood, $\rho -$inversion, and the moment copula method. Full article

Internet of Things (IoT) devices often operate with limited resources while interacting with users and their environment, generating a wealth of data. Machine learning models interpret such sensor data, enabling accurate predictions and informed decisions. However, the sheer volume of data from billions of devices can overwhelm networks, making traditional cloud data processing inefficient for IoT applications. This paper presents a comprehensive survey of recent advances in models, architectures, hardware, and design requirements for deploying machine learning on low-resource devices at the edge and in cloud networks. Prominent IoT devices tailored to integrate edge intelligence include Raspberry Pi, NVIDIA’s Jetson, Arduino Nano 33 BLE Sense, STM32 Microcontrollers, SparkFun Edge, Google Coral Dev Board, and Beaglebone AI. These devices are boosted with custom AI frameworks, such as TensorFlow Lite, OpenEI, Core ML, Caffe2, and MXNet, to empower ML and DL tasks (e.g., object detection and gesture recognition). Both traditional machine learning (e.g., random forest, logistic regression) and deep learning methods (e.g., ResNet-50, YOLOv4, LSTM) are deployed on devices, distributed edge, and distributed cloud computing. Moreover, we analyzed 1000 recent publications on “ML in IoT” from IEEE Xplore using support vector machine, random forest, and decision tree classifiers to identify emerging topics and application domains. Hot topics included big data, cloud, edge, multimedia, security, privacy, QoS, and activity recognition, while critical domains included industry, healthcare, agriculture, transportation, smart homes and cities, and assisted living. The major challenges hindering the implementation of edge machine learning include encrypting sensitive user data for security and privacy on edge devices, efficiently managing resources of edge nodes through distributed learning architectures, and balancing the energy limitations of edge devices and the energy demands of machine learning. Full article

The independence and autonomy of both elderly and disabled people have been a growing concern in today’s society. Therefore, wheelchairs have proven to be fundamental for the movement of these people with physical disabilities in the lower limbs, paralysis, or other type of restrictive diseases. Various adapted sensors can be employed in order to facilitate the wheelchair’s driving experience. This work develops the proof concept of a brain–computer interface (BCI), whose ultimate final goal will be to control an intelligent wheelchair. An event-related (de)synchronization neuro-mechanism will be used, since it corresponds to a synchronization, or desynchronization, in the mu and beta brain rhythms, during the execution, preparation, or imagination of motor actions. Two datasets were used for algorithm development: one from the IV competition of BCIs (A), acquired through twenty-two Ag/AgCl electrodes and encompassing motor imagery of the right and left hands, and feet; and the other (B) was obtained in the laboratory using an Emotiv EPOC headset, also with the same motor imaginary. Regarding feature extraction, several approaches were tested: namely, two versions of the signal’s power spectral density, followed by a filter bank version; the use of respective frequency coefficients; and, finally, two versions of the known method filter bank common spatial pattern (FBCSP). Concerning the results from the second version of FBCSP, dataset A presented an F1-score of 0.797 and a rather low false positive rate of 0.150. Moreover, the correspondent average kappa score reached the value of 0.693, which is in the same order of magnitude as 0.57, obtained by the competition. Regarding dataset B, the average value of the F1-score was 0.651, followed by a kappa score of 0.447, and a false positive rate of 0.471. However, it should be noted that some subjects from this dataset presented F1-scores of 0.747 and 0.911, suggesting that the movement imagery (MI) aptness of different users may influence their performance. In conclusion, it is possible to obtain promising results, using an architecture for a real-time application. Full article

In a recent study devoted to the influence of electromagnetic radiation reaction on the motion of radiating charged particles in magnetized black hole spacetimes the authors claim that the tail term cannot be neglected in the complete DeWitt–Brehme equation, putting into doubt the previous papers where such an approximation was used. Here, we demonstrate by using simple dimensional arguments that such a statement is misleading in many astrophysically relevant situations. In the case of relativistic electrons moving around a stellar-mass black hole, the tail term is ignorable if a magnetic field of at least a few Gauss is present.On the other hand, in different situations, the tail term can be relevant, as demonstrated in the case of orbital widening, where it can even amplify the effect. Full article

In an era where technology increasingly blurs the boundaries between humans and machines, artifacts have become crucial mediums for critically examining the technological, social, and ethical dimensions of Human–Computer Interaction (HCI). This study explores artifacts as a key yet underutilized medium for speculation in the evolving field of HCI from a systemic perspective. While artifacts increasingly enable HCI to move beyond optimizing user experiences towards critically and collaboratively envisioning futures, perspectives comprehensively examining artifacts across the speculative design process and their impacts remain limited. Through a literature review of 53 speculative artifacts within the scope of HCI, this research elucidates the roles of artifacts across intention, making, and impact. Four categories of speculative artifacts emerged—Reflective, Exploratory, Interventional, and Heuristic—demonstrating how artifacts employ material, ambiguous, functional, and provocative forms to shape experiences, behaviors, and social norms. This study highlights the need for HCI to increasingly recognize the capacity of artifacts to support critical, sustained, participatory speculation by providing tangible representations of alternative futures. Speculative artifacts thus serve as powerful mediums to engage in societal discourse around the ethics and values of emerging technologies and to envision and enact responsible innovation. The materialization of alternative futures through artifacts allows researchers to reimagine socio-technological relationships, pushing design into inclusive, controversial spaces where diverse stakeholders can collaboratively shape desired and undesired futures. Full article

According to the definition provided by the United Nations, “climate change” describes the persistent alterations in temperatures and weather trends. These alterations may arise naturally, such as fluctuations in the solar cycle. Nonetheless, since the 19th century, human activities have emerged as the primary agent for climate change, primarily attributed to the combustion of fossil fuels such as coal, oil, and gas. Climate change can potentially influence the well-being, agricultural production, housing, safety, and employment opportunities for all individuals. The immune system is an important interface through which global climate change affects human health. Extreme heat, weather events and environmental pollutants could impair both innate and adaptive immune responses, promoting inflammation and genomic instability, and increasing the risk of autoimmune and chronic inflammatory diseases. Moreover, climate change has an impact on both soil and gut microbiome composition, which can further explain changes in human health outcomes. This narrative review aims to explore the influence of climate change on human health and disease, focusing specifically on its effects on the immune system and gut microbiota. Understanding how these factors contribute to the development of physical and mental illness may allow for the design of strategies aimed at reducing the negative impact of climate and pollution on human health. Full article

The aim of this article was to conduct a spatial and territorial analysis of the urban mining potential of the European Metropolis of Lille (MEL), which had 1,174,273 inhabitants in 2018. This involved quantifying construction and demolition waste (CDW) deposits and analyzing their spatial distribution. The chosen quantification approach utilized building and demolition permits as input data, along with waste diagnostics for Construction and Building Materials Products (CBMPs) obtained from stakeholders in the building sector. Waste quantities were estimated using the production rate calculation method (GRC). Specifically, the calculation based on surface area combined with GIS geographic information systems. CDW quantities were categorized by demolition rehabilitation and construction; by type (hazardous non-hazardous inert); and by urban fabric. For the MEL area, the findings revealed that building sites covered the largest surface area, with over 8 million m² being constructed between 2013 and 2022. The construction activity, including renovation, is expected to constitute approximately 20% of the MEL’s building stock from 2013 to 2022. During the same period, 5.51% of the MEL’s building stock was demolished. This corresponds to nearly 6 million tons of CDW being generated during this period, averaging 661318 tons per year. Demolition sites contributed 73% of the total CDW production, compared to 22% for new construction and 4% for renovation sites. Inert waste continued to dominate the composition of waste, accounting for 90% of the total with 9% for non-hazardous waste and 1% for hazardous waste. Semi-detached and grouped houses business fabrics and townhouses or collective fabrics were identified as the primary type of waste-producing urban fabrics. Furthermore, our GIS-based methodology enabled the analysis of CDW quantity distribution by municipality, providing essential data for understanding the urban mining potential and the disparity between construction material requirements for new buildings and resources derived from building demolition. This approach facilitates the assessment of (1) a geographical area’s reliance on construction materials, and (2) the significance of reusing and recycling products equipment materials and waste (PEMW) in new construction to achieve circular economy objectives and to comply with the Extended Producer Responsibility (EPR) channel initiated in France in 2023. Over the period from 2013 to 2022, annual construction material requirements remained significantly higher than resources from building demolition and rehabilitation, ranging between 29% and 35%. Additionally, the analysis indicated a potential 41% rate of substitution of new construction materials with secondary primary materials in the MEL, varying by municipality and typology, with higher rates in rural communities and lower rates in urban communities. Full article

Efforts to create a sustainable future require careful and complex thinking, interdisciplinary and cross-organizational collaboration, and effective and ethical communication. However, the structural biases of digital communication technologies foster modes of thought and expression that undermine or impede these necessities. While one possible solution to this problem is digital literacy, the two prevailing paradigms of digital literacy both reproduce the myth of technological neutrality. This myth further inhibits sustainability by wrongly suggesting that digital technologies are appropriate to all communication goals and tasks. As a corrective to these models, I propose a new paradigm of digital literacy, one rooted in media ecology. The adoption of this model, I maintain, allows us to consciously co-create our social world rather than merely inhabit it. Full article

Background/Objectives: A highly porous titanium cup with a three-dimensional metal interface was recently introduced to improve biological fixation and survival. However, radiography has revealed concerns regarding these cups, despite their excellent short- and mid-term clinical outcomes. This study compared the clinical and radiographic results of a highly porous titanium cup with those of a hydroxyapatite-coated porous titanium cup after primary total hip arthroplasty (THA). Methods: Fifty-one primary THAs were investigated. A highly porous titanium cup was used in 17 hips, and a hydroxyapatite-coated porous titanium cup was used in 34 hips. No significant differences in preoperative patient demographic characteristics were observed between the two groups. The 2-year postoperative clinical and radiographic results were compared. Results: Radiolucent lines were observed in 13 (76%) of 17 hips with highly porous titanium cups and in none (0%) of 34 hips with hydroxyapatite-coated porous titanium cups (p < 0.001). In the highly porous titanium cup group, radiolucent lines were observed in five hips (29%) in one zone, two hips (11%) in two zones, and six hips (35%) in three zones. No cup loosening was observed in either group. Conclusions: Radiolucent lines were significantly more frequent in highly porous titanium cups. This study suggests that, compared to the three-dimensional structure of porous titanium, the hydroxyapatite coating of porous titanium had a greater influence on bone ingrowth in the short term. The meaning of these findings in the long-term is unclear yet. Full article

Background: In the last decade, increasing evidence has suggested that high-grade serous ovarian cancers may have their origin in the fallopian tube rather than the ovary. This emerging theory presents an opportunity to prevent epithelial ovarian cancer by incorporating prophylactic bilateral salpingectomy into all surgical procedures for average-risk women. The aim of this review is to investigate the hypothesis that bilateral salpingectomy (BS) may have a negative impact on ovarian reserve, not only following hysterectomy for benign uterine pathologies but also when performed during cesarean sections as a method of sterilization or as a treatment for hydrosalpinx in Assisted Reproductive Technology interventions. Methods: PubMed, Medline, Google Scholar, and Cochrane were searched for original studies, meta-analyses, and opinion articles published between 2014 and 2024. Results: Out of 114 records from the database search, after the removal of duplicates, 102 articles were considered relevant for the current study. Conclusions: Performing opportunistic salpingectomy seems to have no adverse impact on ovarian function in the short term. However, because there is an existing risk of damaging ovarian blood supply during salpingectomy, there are concerns about potential long-term adverse effects on the ovarian reserve, which need further investigation. Full article

Background: Vestibular schwannoma (VS), also known as acoustic neuroma, is a benign, well-encapsulated, and slow-growing tumor that originates from Schwann cells, which form the myelin sheath around the vestibulocochlear nerve (VIII cranial nerve). The surgical treatment of this condition presents a challenging task for surgeons, as the tumor’s location and size make it difficult to remove without causing damage to the surrounding structures. In recent years, fluorescein sodium (FS) has been proposed as a tool to enhance surgical outcomes in VS surgery. This essay will provide an analytical comparison of the use of FS in VS surgery, evaluating its benefits and limitations and comparing surgical outcomes with and without FS-assisted surgery. Methods: In a retrospective study conducted at San Filippo Neri Hospital, we examined VS cases that were operated on between January 2017 and December 2023. The patients were divided into two groups: group A, which consisted of patients who underwent surgery without the use of FS until January 2020 (102 cases), and group B, which included patients who underwent surgery with FS after January 2020 (55 cases). All operations were performed using the retrosigmoid approach, and tumor size was classified according to the Koos classification system. The extent of surgical removal was evaluated using both the intraoperative surgeon’s opinion and postoperative MRI imaging. Preoperatively and postoperatively, facial nerve function and hearing were assessed. In group B, FS was used to assist the surgical procedures, which were performed using a surgical microscope equipped with an integrated fluorescein filter. Postoperative clinical and MRI controls were performed at six months and annually, with no patients lost to follow-up. Results: This study investigated the impact of intraoperative fluorescein exposure on tumor resection and clinical outcomes in patients with VS. The study found a statistically significant difference in the tumor resection rates between patients who received fluorescein intraoperatively (p = 0.037). Further analyses using the Koos classification system revealed a significant effect of fluorescein exposure, particularly in the Koos 3 subgroup (p = 0.001). Notably, no significant differences were observed in hearing loss or facial nerve function between the two groups. A Spearman correlation analysis revealed a positive correlation between tumor size and Koos, age, and size, but no significant correlation was found between facial nerve function tests. Conclusions: FS-assisted surgery for VS may potentially enhance tumor resection, allowing for more comprehensive tumor removal. Full article

This study presents a method based on active preference learning to overcome the challenges of designing reward functions for autonomous navigation. Results obtained from training with artificially designed reward functions may not accurately reflect human intentions. We focus on the limitations of traditional reward functions, which often fail to facilitate complex tasks in continuous state spaces. We propose the adoption of active preference learning to resolve these issues and to generate reward functions that align with human preferences. This approach leverages an individual’s subjective preferences to guide an agent’s learning process, enabling the creation of reward functions that reflect human desires. We utilize mutual information to generate informative queries and apply information gained to balance the agent’s uncertainty with the human’s response capacity, encouraging the agent to pose straightforward and informative questions. We further employ the No-U-Turn Sampler (NUTS) method to refine the belief model, which outperforms that constructed using the Metropolis algorithm. Subsequently, we retrain the agent using reward weights derived from active preference learning. As a result, our autonomous driving vehicle can navigate between random starting and ending points without dependence on high-precision maps or routing, relying solely on its forward vision. We validate our approach’s performance within the CARLA simulation environment. Our algorithm significantly improved the success rate of autonomous driving navigation tasks that originally failed due to artificially designed rewards, increasing it to approximately 60%. Experimental results show significant improvement over the baseline algorithm, providing a solid foundation for enhancing navigation capabilities in autonomous driving systems and advancing the field of autonomous driving intelligence. Full article