Common Objects Research Articles

State Aid to Electricity Producers: National and EU Law Aspects

At European Union level, there is a detailed regulatory framework allowing Member States to introduce state aid. State aid is always granted for a specific purpose and helps Member States to achieve their common objectives. The energy sector is being moved towards reaching targets for both energy efficiency and climate neutrality, with a gradual withdrawal from fossil fuels. However, it is not always easy to align these targets at Member State level and to create the appropriate national regulatory framework. Therefore, this article in the light of the two most recent judgements of the Constitutional Court of the Republic of Latvia (hereinafter – Constitutional Court), analyses the importance of a fixed term of state aid for electricity production and some aspects of state aid for biogas cogeneration plants, including the development of EU law perspective. The article also examines the impact of the enforcement of the Constitutional Court’s judgments in the area of state aid in Latvia and explains the emerging concept of environmental constitutionalism.

Human Interiority and Artificial Intelligence

This article addresses the issue of attributing phenomenal consciousness to Artificial Intelligence (AI), a mistake that can lead to ethically dangerous consequences and that is becoming widespread due to the advances of Large Language Models such as ChatGPT. We juxtapose advancements in AI with the notion of inner experience as it is present in humans. The study draws from various disciplines, including philosophy of mind, artificial intelligence, and theological texts such as "The Inner Castle" by Saint Theresa of Ávila and "Confessions" by Saint Augustine. Firstly, it reviews the current state of the relationship between phenomenal consciousness and AI, followed by a critique of the idea that advanced language models, like ChatGPT, can achieve an inner experience in the same sense we use the term to describe the human inner experience. A common objection is raised, suggesting that AI can become conscious by increasing its complexity. This is countered by presenting theoretical and empirical evidence on the independence of computational intelligence and phenomenal consciousness. The study concludes that, despite AI's notable cognitive abilities, it lacks the inner experience that characterizes human experience. Then, our second main contribution is an analogy of the dwellings of the Inner Castle to the range of different subjective experiences that are available to human beings, together with actions associated to them, which can be useful to understand where the machine can perform tasks that are similar to the human and where subjective experience is key. We are now in a pivotal moment where it is essential to understand the limitations of AI for deploying it ethically.

Has the cat got your tongue, or is something obstructing your throat? A review of imaging of ingested and aspirated foreign bodies in the paediatric population.

Children frequently swallow or inhale foreign objects, a situation that can be life-threatening. Radiographic imaging plays a lead role in the early identification and location of inhaled or swallowed objects is essential. Promptly identifying and locating inhaled or swallowed objects are essential, as some items require immediate removal. For example, button batteries in the throat can cause grave harm; magnets can attract each other through the gut and cause perforations; and other objects can obstruct the airway or intestinal tract. Radiologists must understand how these objects appear in images to assist doctors in treating patients effectively. Recognising signs of inhaled objects on radiographs is also crucial, as symptoms may not always be clear, and many inhaled objects are not visible on radiographs. Radiographs are the primary means of checking for swallowed or inhaled objects, although other tests like fluoroscopy and computed tomography may be used in complex cases. Doctors working with children should be acquainted with the appearance of these common objects on images and their clinical importance.

Comparative analysis of frequently used e-learning platforms

An online e-learning platform known as a learning management system (LMS) provides an interface between trainers, students, and administrators toward a common objective of learning. In the market, diverse LMSs with extensive functionalities are available to facilitate e-learning. In this article, we selected some popular LMSs majorly used by most schools and institutions for their teaching–learning process. We compared these LMSs in a discussion based on their technical specifications, technical features, administrative features, general features, and course management-related features. This comparative analysis could help users decide which LMS suits them best, according to their requirements. We also attempted to identify the limitations of these learning management systems so that users and organizations can determine which one is best suited to their needs.

Image Stitching of Low-Resolution Retinography Using Fundus Blur Filter and Homography Convolutional Neural Network

Great advances in stitching high-quality retinal images have been made in recent years. On the other hand, very few studies have been carried out on low-resolution retinal imaging. This work investigates the challenges of low-resolution retinal images obtained by the D-EYE smartphone-based fundus camera. The proposed method uses homography estimation to register and stitch low-quality retinal images into a cohesive mosaic. First, a Siamese neural network extracts features from a pair of images, after which the correlation of their feature maps is computed. This correlation map is fed through four independent CNNs to estimate the homography parameters, each specializing in different corner coordinates. Our model was trained on a synthetic dataset generated from the Microsoft Common Objects in Context (MSCOCO) dataset; this work added an important data augmentation phase to improve the quality of the model. Then, the same is evaluated on the FIRE retina and D-EYE datasets for performance measurement using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The obtained results are promising: the average PSNR was 26.14 dB, with an SSIM of 0.96 on the D-EYE dataset. Compared to the method that uses a single neural network for homography calculations, our approach improves the PSNR by 7.96 dB and achieves a 7.86% higher SSIM score.

Comparison of Conventional and Microwave Heating

Carnot batteries (or Power-to-Heat-to-Power systems) are capable of increasing the use of electricity from photovoltaic or wind power plants to achieve decarbonisation of the electricity sector. To decouple electricity production from demand, these renewable power plants can be connected to the thermal energy storage system of a concentrated solar thermal power plant via electric heaters. As an alternative to electric heaters, microwaves are studied as a volumetric and selective heating method, avoiding the limitations of the Joule effect conventional heating when having solar salt (non-eutectic mixture of 60 wt % NaNO3 and 40 wt % KNO3), which is a storage medium with low thermal conductivity, working at a temperature very close to its affordable maximum temperature without degradation. In this work, the two heating methods are compared both experimentally and numerically. At experimental level, a microwave oven and a muffle furnace are used to record energy consumption and time for a common objective. Additionally, different crucible materials were used to test their suitability with microwaves. Only quartz glass was validated for microwave heating, while the porcelain and alumina based materials (Corundum and Alsint 99.7) failed while exposed to microwaves. Compared to conventional heating, heating solar salt with microwaves saved fifty minutes of time and ninety percent of consumption. These experiments were validated by numerical simulations, showing a different distribution in each experiment.

Limits of India–US Relations: Balancing Through Strategic Autonomy and Multi-alignment

The India–US relationship has often been described as a defining partnership. But the nature of the friendship in actuality is yet to assume depth. Despite convergences at multiple levels, it falls short of a true strategic partnership or deep friendship. The India–US relationship is neither a trusted nor an assured economic or security partnership. It is often tested by the vagaries of real-time issues, especially involving other great powers. That is why, despite signing the civilian nuclear deal, foundational agreements, being members of the QUAD and Indo-Pacific Economic Forum, and with the common objective of containing the rise of China, they are unable to work closely together on myriad bilateral, international and regional issues. There are differences over matters of primary interests and the type of partnership that each wants to establish. The United States was insensitive to Indian concerns in its abrupt drawdown from Afghanistan in 2021, sub-continental security threats emanating from the China–Pakistan axis and its continued military support to Pakistan. India’s neutral stand (read in the United States as being pro-Russian) in the Ukraine crisis marked by its abstention from voting against Russia in the UN and purchase of Russian oil despite strong objections from the US-led Western camp are cases in point. We argue that India’s US policy is a case of limited balancing dictated by compulsions and lacks depth. For rising India, a continued desire for strategic autonomy and multi-alignment—the post-non-alignment foreign policy principles—guides its foreign policy orientation. For Washington, a deeper relationship would imply India abandoning its visions of strategic autonomy and joining more formally in Washington’s orbit. These core national objectives of the two countries limit the level of partnership they can forge.

Introduction to Part 2 of the Themed Issue, ‘Racism and Colonialism in Hegel's Philosophy’: Common Objections and Questions for Future Research

In the first part of our editorial introduction to the themed issue ‘Racism and Colonialism in Hegel's Philosophy’ we outlined its rationale and some of its main topics. Here we address some common objections against research of this kind and formulate questions for further research.

The role of ICT as LT in shaping inclusive and special education – a systematic review for 2012–2023

PurposeDigital inequalities are pressing concerns, especially for students in need of special educational support. In recent years, numerous reviews have been published on the use of learning technologies (LT) in inclusive and special education. They mostly provide findings for specific groups, technologies, and countries. This systematic review aims to identify changes in the use of information and communication technologies (ICT) as LT that evolved globally in inclusive and special education over the last 12 years.Design/methodology/approachWeb of Science, Scopus, and EBSCOhost were systematically searched for publications for 2012 to 2023. Only peer-reviewed English publications were included to ensure a comprehensive review. The findings of the 421 included papers were then analysed, reflecting diverse perspectives at the technology, learners, teachers, and institutional levels.FindingsThe most used devices were computers, iPads/tablets, and specifically designed apps. More studies were conducted in separate settings than in inclusive ones. The primary participant groups were students on the autism spectrum. More than half the research publications were related to technology use. Technology development was the most common research objective, with approximately 40% of test hypotheses based on standardised tests or observations.Research limitations/implicationsBy shifting the focus from specific disabilities to a more usability-based approach, we can envision a future in which the quality of education for all students is substantially improved.Practical implicationsLT have the potential to significantly contribute to creating the least restrictive learning environment for students in need of special educational support. One step for practitioners is to consider the interdependencies between the different dimensions of heterogeneity relevant to digital inclusion. In order to solve these complex pedagogical tasks appropriately, multidisciplinary cooperation is necessary, involving experts in technical, pedagogical, didactic and inclusive education in digitalised societies.Originality/valueAll data were meticulously collected and analysed to ensure credibility and originality.

When do contemporary wildfires restore forest structures in the Sierra Nevada?

BackgroundFollowing a century of fire suppression in western North America, managers use forest restoration treatments to reduce fuel loads and reintroduce key processes like fire. However, annual area burned by wildfire frequently outpaces the application of restoration treatments. As this trend continues under climate change, it is essential that we understand the effects of contemporary wildfires on forest ecosystems and the extent to which post-fire structures are meeting common forest restoration objectives. In this study, we used airborne lidar to evaluate fire effects across yellow pine and mixed conifer (YPMC) forests of California’s Sierra Nevada. We quantified the degree to which forest structures in first-entry burned areas (previously unburned since ~ 1900s) and unburned controls aligned with restoration targets derived from contemporary reference sites. We also identified environmental conditions that contributed to more restorative fire effects.ResultsRelative to unburned controls, structural patterns in first-entry burned areas aligned more closely with reference sites. Yet, across all burn severities, first-entry wildfires were only moderately successful at meeting targets for canopy cover (48% total area) and ladder fuels (54% total area), and achieving these targets while also producing tree clump and opening patterns aligning with reference sites was less common (16% total area). Moderate-severity patches had the highest proportion of restorative fire effects (55–64% total area), while low- and high-severity patches were either too dense or too open, respectively. Our models (and publicly-available mapped predictions) indicated a higher probability of restorative effects within 1 km of previous fires, within the mid-upper climate range of the YPMC zone, and under moderate fire intensities (~ 1–2 m flame lengths).ConclusionsFirst-entry wildfires can sometimes restore structural conditions by reducing canopy cover and ladder fuels and increasing structural heterogeneity, especially within moderate-severity patches. However, these initial fires represent just one step toward restoring dry forest ecosystems. Post-fire landscapes will require additional low- to moderate-intensity fires and/or strategic management interventions to fully restore structural conditions. In yet unburned forests, managers could prioritize mechanical treatments at lower elevations, early-season burning at mid to high elevations, and resource objective wildfires in landscapes with mosaics of past wildfires.

Facilitating Dam Removal Decisions With Multiple Objectives

ABSTRACTProactive and transparent decision‐making about the long‐term management of dams, including rehabilitation, retrofit, and removal, is critical for successfully managing this aging infrastructure and presents an opportunity to weigh the many services and disservices dams provide. Existing tools to support dam removal decisions often constrain decision processes by considering only a limited set of user objectives. We identified 18 dam removal objectives in the literature and found that most of the 41 dam removal decision‐support tools we evaluated included only two or three objectives. Common objectives of previous dam removals like reducing safety hazard and expanding recreational opportunities were included in few decision‐support tools. To facilitate dam removal decisions with diverse objectives, we created a new web application, which supports decisions with the 18 objectives that we identified in the literature. The application guides users to select appropriate objectives, choose metrics and methods to evaluate management alternatives, and identify additional decision‐support tools to weigh alternatives relative to selected objectives. We demonstrate this web application as a resource for the dam management community of practice with a case study of a dam removal decision in Athens, Georgia, USA. More broadly, we propose the process outlined here as a model for aligning diverse objectives in other types of river infrastructure decisions. Given the contribution of this infrastructure to declining biodiversity, intensifying climate, and development needs, failing to align multiple objectives in river infrastructure decisions can represent consequential, missed opportunities.

Learning to detect slip through tactile estimation of the contact force field and its entropy properties

Slip detection during object grasping and manipulation plays a vital role in object handling. Visual feedback can help devise a strategy for grasping. However, for robotic systems to attain a proficiency comparable to humans, integrating artificial tactile sensing is increasingly essential, especially in consistently handling unfamiliar objects. We introduce a novel physics-informed, data-driven approach to detect slip continuously for control-oriented tasks. Our work leverages the inhomogeneity of tactile sensor readings during slip events to develop distinct features and formulates slip detection as a classification problem. We test multiple data-driven models on 10 common objects under different loading conditions, textures, and materials to evaluate our approach. The resulting best classification algorithm achieves a high average accuracy of 95.61%. Practical application in dynamic robotic manipulation demonstrates the effectiveness of the proposed real-time slip detection and prevention.

Юрий Жданов – гений места (genius loci): Ростова, Дона и Северного Кавказа

The article highlights the main events of the Rostov period of the life and work of the outstanding organizer of science, socio-political figure and scientist I.A. Zhdanov in the context of the concept of the “genius of the place”. The analysis made it possible to identify, using the example of his biography, common objective and subjective factors, the combination of which makes it possible to transform the individual activity of the genius of the place into positive effects of the city of Rostov-on-Don, the Rostov region, and the North Caucasus region. The key positions of understanding Zhdanov's personality as the genius of the place are considered: regional ideological identification, contribution to the development of the territory, socio-cultural identity, historical reconstruction of the main events. It is shown how the scientific and social activities of Yu.A. Zhdanov contributed to the process of changes in the local Don and North Caucasian communities. An attempt was made to correlate the substantive aspects of the works of the genius of the place and his biography with the basic, fundamental elements of the history and culture of the Don and the North Caucasus. Data collection was carried out through the analysis of scientific periodicals, media materials and publications on social networks, memories of residents and representatives of regional authorities, as well as personal observations of the author.

Study on Experiences with and Awareness of Swallowing Accidents during Dental Treatments among Domestic Dental Professionals

Objective: This study examined the causes of swallowing accidents experienced by dental professionals during dental treatment. In addition, an attempt was made to understand the awareness of swallowing accidents and identify factors influencing swallowing accident experiences. Methods: An online survey was conducted among 390 dental healthcare professionals to assess their experiences and perceptions of swallowing accidents. Quantitative analysis was performed on the collected data using statistical software. Frequency analysis, analysis of variance (ANOVA), and t-tests were used as analysis methods. Results: Swallowing accidents were prevalent among dental healthcare professionals (63.3%) and occurred most frequently in patients aged 41 to 60 years, with a higher incidence in men. Common foreign objects, including prostheses and extracted teeth, typically pass through the upper gastrointestinal tract. No significant difference was reported between the occupation and experience of dental workers and their perception of swallowing accidents. These findings indicate that awareness of the risk of swallowing accidents is not related to occupation or work experience. Conclusions: The substances and types of treatments that cause swallowing accidents vary. Therefore, the prevention of swallowing accidents occurring during dental treatment is important. In addition, increasing the awareness and education is necessary.

AUDITORIA DE CONFORMIDADE LEGAL AMBIENTAL: PERSPECTIVAS, DESAFIOS E IMPORTÂNCIA

Environmental legal compliance audits have established themselves as an essential tool in modern environmental management, being increasingly used by companies and organizations that seek to ensure the adequacy of their activities to environmental standards. The audit process involves a systematic assessment of an organization’s processes, products and activities, verifying whether they comply with the legal requirements applicable by current environmental laws, provisions and standards. There are several types of environmental legal compliance auditing. This article seeks to explore in depth the main aspects related to environmental legal compliance audits, addressing their concepts, objectives, application methods, practical challenges and strategic importance in the current context in relation to legal compliance audit processes relevant to the NBR ABNT standard ISO 14.001:2015, Environmental Due Diligence and CONAMA Resolution 306/2002. Despite it is a powerful control tool, environmental legal compliance auditing faces practical challenges, which can compromise its effectiveness if not properly managed. Although the legal assessment of ISO 14001, environmental Due Diligence and the environmental audit of CONAMA Resolution 306 share the common objective of promoting environmental compliance, each has different focuses and is applicable in different contexts. ISO 14001 focuses on continuous and internal management, while environmental Due Diligence is focused on specific transactions and hidden risks. The CONAMA 306 audit offers a broader view of compliance and environmental performance, focusing on large projects and legal inspection. Thus, each approach presents specific advantages and challenges, being complementary in many business situations, especially when it comes to companies that deal with major environmental impacts.

Improving Reference-based Distinctive Image Captioning with Contrastive Rewards

Distinctive Image Captioning (DIC) — generating distinctive captions that describe the unique details of a target image — has received considerable attention over the last few years. A recent DIC method proposes to generate distinctive captions by comparing the target image with a set of semantic-similar reference images, i . e ., reference-based DIC (Ref-DIC). It aims to force the generated captions to distinguish between the target image and the reference image. Unfortunately, reference images used by existing Ref-DIC works are easy to distinguish: these reference images only resemble the target image at scene-level and have few common objects, such that a Ref-DIC model can trivially generate distinctive captions even without considering the reference images. For example, if the target image contains objects “ towel ” and “ toilet ” while all reference images are without them, then a simple caption “ A bathroom with a towel and a toilet ” is distinctive enough to tell apart target and reference images. To ensure Ref-DIC models really perceive the unique objects (or attributes) in target images, we first propose two new Ref-DIC benchmarks. Specifically, we design a two-stage matching mechanism, which strictly controls the similarity between the target and reference images at the object-/attribute- level (v.s. scene-level). Secondly, to generate distinctive captions, we develop a Transformer-based Ref-DIC baseline TransDIC . It not only extracts visual features from the target image, but also encodes the differences between objects in the target and reference images. Taking one step further, we propose a stronger TransDIC++ , which consists of an extra contrastive learning module to make full use of the reference images. This new module is model-agnostic, which can be easily incorporated into various Ref-DIC architectures. Finally, for more trustworthy benchmarking, we propose a new evaluation metric named DisCIDEr for Ref-DIC, which evaluates both the accuracy and distinctiveness of the generated captions. Experimental results demonstrate that our TransDIC++ can generate distinctive captions. Besides, it outperforms several state-of-the-art models on the two new benchmarks over different metrics.

Consistency-based semi-supervised learning for oriented object detection

Semi-Supervised Object Detection (SSOD) has emerged as a potent framework that leverages unlabeled data to reduce annotation costs while enhancing model performance. Nevertheless, existing SSOD methods primarily concentrate on the conventional localization of horizontal objects, overlooking the common arbitrary-oriented objects in aerial scenes. Extending semi-supervised learning to oriented object detection still encounters two major challenges: (1) There is an inconsistency between classification and localization in oriented object detectors, which means that pseudo-labels selected solely based on classification scores cannot properly represent the localization quality. (2) The static and monotonic pseudo-label selection process fails to dynamically filter pseudo-labels for different tasks and categories throughout the iteration process, inevitably introducing accumulated noise and bias into the supervisory signals for the student model. To mitigate this problems, we proposed a novel consistency-based semi-supervised oriented object detection framework, named CSLO-Det. Specifically, Task Alignment Learning (TAL) is proposed to improve the consistency in terms of both features and learning objectives, thereby facilitating a more robust selection of pseudo-labels. Noise-Resistant Pseudo-label Mining (NR-PM) is introduced to separately and dynamically exploits positives for the classification and localization task. Moreover, diverging from the conventional semi-supervised learning frameworks that utilize pseudo-boxes, our method applies pixel-level dense supervision during unsupervised training, which improves detection performance. Comprehensive experiment results reveal that the proposed CSLO-Det attains state-of-the-art performance under multiple semi-supervised datasets.

Pressure distribution based 2D in-bed keypoint prediction under interfered scenes

In-bed pose estimation holds significant potential in various domains, including healthcare, sleep studies, and smart homes. Pressure-sensitive bed sheets have emerged as a promising solution for addressing this task considering the advantages of convenience, comfort, and privacy protection. However, existing studies primarily rely on ideal datasets that do not consider the presence of common daily objects such as pillows and quilts referred to as interference, which can significantly impact the pressure distribution. As a result, there is still a gap between the models trained with ideal data and the real-life application. Besides the end-to-end training approach, one potential solution is to recognize the interference and fuse the interference information to the model during training. In this study, we created a well-annotated dataset, consisting of eight in-bed scenes and four common types of interference: pillows, quilts, a laptop, and a package. To facilitate the analysis, the pixels in the pressure image were categorized into five classes based on the relative position between the interference and the human. We then evaluated the performance of five neural network models for pixel-level interference recognition. The best-performing model achieved an accuracy of 80.0% in recognizing the five categories. Subsequently, we validated the utility of interference recognition in improving pose estimation accuracy. The ideal model initially shows an average joint position error of up to 30.59 cm and a Percentage of Correct Keypoints (PCK) of 0.332 on data from scenes with interferences. After retraining on data including interference, the error is reduced to 13.54 cm and the PCK increases to 0.747. By integrating interference recognition information, either by excluding the parts of the interference or using the recognition results as input, the error can be further minimized to 12.44 cm and the PCK can be maximized up to 0.777. Our findings represent an initial step towards the practical deployment of pressure-sensitive bed sheets in everyday life.

Optimal boundary control in a micromixer

This work studies mathematical foundations for optimal boundary control of mixers which mix two fluid phases. Existence of optima is proved and the influence of common objective functionals is discussed.

Between Transcendental and National: Wooden Churches of Slovakia

ABSTRACT The Eastern Carpathian Mountain region is home to Slavic peoples, who celebrate the bringing of Christianity by Saints Cyril and Methodius in the ninth century. The mountainous region retains small village churches, some dating from the eighteenth century, each established within agrarian communities by Roman Catholic, Greek Catholic, Protestant, or Orthodox denominations. Despite village subjugation under the Austro-Hungarian Empire, Nazi occupation, Russian “liberation” and Socialist-era suppression of non-Orthodox denominations, these exquisite vernacular structures have remained and illustrate the continuing transcendental experience for worshipers but also now shared with those who celebrate them as symbols of national resistance, as well as tourists who come to experience them as UNESCO World Heritage sites. Sharing a common church object, traditional typological and formal aesthetic approaches that have been established by researchers for these structures are contrasted against a phenomenologically rooted set of embodied modes for meaning across examples from extant structures within Slovakia. Embodied approaches provide, via modes of lived experience, a deep offering into what each church shares with their ecological landscape, village, and history; a holistic visceral tapestry key to their appreciation complimenting the typological and differently affirming their continuing value.