Active Research Research Articles

Spatio-Temporal Contextual Learning for Single Object Tracking on Point Clouds.

Single object tracking (SOT) is one of the most active research directions in the field of computer vision. Compared with the 2-D image-based SOT which has already been well-studied, SOT on 3-D point clouds is a relatively emerging research field. In this article, a novel approach, namely, the contextual-aware tracker (CAT), is investigated to achieve a superior 3-D SOT through spatially and temporally contextual learning from the LiDAR sequence. More precisely, in contrast to the previous 3-D SOT methods merely exploiting point clouds in the target bounding box as the template, CAT generates templates by adaptively including the surroundings outside the target box to use available ambient cues. This template generation strategy is more effective and rational than the previous area-fixed one, especially when the object has only a small number of points. Moreover, it is deduced that LiDAR point clouds in 3-D scenes are often incomplete and significantly vary from frame to another, which makes the learning process more difficult. To this end, a novel cross-frame aggregation (CFA) module is proposed to enhance the feature representation of the template by aggregating the features from a historical reference frame. Leveraging such schemes enables CAT to achieve a robust performance, even in the case of extremely sparse point clouds. The experiments confirm that the proposed CAT outperforms the state-of-the-art methods on both the KITTI and NuScenes benchmarks, achieving 3.9% and 5.6% improvements in terms of precision.

Héctor Fernández-Álvarez (1944-2023).

This article memorializes Héctor Fernández-Álvarez (1944-2023). Héctor was an exceptional mentor, therapist, supervisor, professor, researcher, author, and leader, as well as a beloved brother, partner, father, and grandfather. The consummate renaissance person who embraced all manners of cultural expressions through an intentional wanderlust, he sought to understand all forms of human suffering and to alleviate senseless ones. Héctor's career spanned well over 5 decades. He received a licenciatura degree in 1967 from the University of Buenos Aires and a PhD in 1995 from the National University of San Luis, Argentina. Héctor held multiple academic appointments throughout Latin America and Spain. He authored over 100 journal articles or book chapters, and 16 books, including a novel, La Distancia (The Distance), and Fundamentals of an Integrated Model of Psychotherapy, one of the most respected psychotherapy books in Latin America and Spain. In 1977, Héctor challenged the constraints of a military dictatorship by founding Aiglé (the everlasting flame). Aiglé remains a nongovernmental organization that delivers clinical and community services and prepares mental health practitioners informed by an active research program that evaluates training and psychotherapeutic processes and outcomes. Over the years, Héctor advanced Aiglé as a practice-oriented research clinical setting to investigate psychotherapy as it unfolds in clinical practice. He developed an integrative model of care that resulted in Aiglé's cognitive-integrative model. Aiglé has grown to be a hallmark for research-based, leading-edge psychotherapy training in Latin America. Highlights of Héctor's career and professional contributions are noted. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Realigning the physical activity research agenda for population health, equity, and wellbeing

Realigning the physical activity research agenda for population health, equity, and wellbeing

Iteration-Free quantum approximate optimization algorithm using neural networks

The quantum approximate optimization algorithm (QAOA) is a leading iterative variational quantum algorithm for heuristically solving combinatorial optimization problems. A large portion of the computational effort in QAOA is spent by the optimization steps, which require many executions of the quantum circuit. Therefore, there is active research focusing on finding better initial circuit parameters, which would reduce the number of required iterations and hence the overall execution time. While existing methods for parameter initialization have shown great success, they often offer a single set of parameters for all problem instances. We propose a practical method that uses a simple, fully connected neural network that leverages previous executions of QAOA to find better initialization parameters tailored to a new given problem instance. We benchmark state-of-the-art initialization methods for solving the MaxCut problem of Erdős-Rényi graphs using QAOA and show that our method is consistently the fastest to converge while also yielding the best final result. Furthermore, the parameters predicted by the neural network are shown to match very well with the fully optimized parameters, to the extent that no iterative steps are required, thereby effectively realizing an iteration-free QAOA scheme.

Bioactive peptides from by-products of shrimp processing: A review

Currently, the mismanagement of marine by-products (head, skin, guts, blood, and bones) is a problem for the seafood processing industry, causing economic losses and environmental problems. Shrimp is a high-protein marine plankton species, and after processing, 45% of the total weight is discarded. Therefore, processes must be developed to recover biomolecules from this waste. Hydrolysis of shrimp by-products is an efficient way to add value to the protein for the extraction of bioactive peptides. The present review focuses on recent research on the use of marine by-products to obtain bioactive peptides, especially those from shrimp waste, and discusses their benefits for human health. Protein hydrolysates from shrimp by-products are a viable and technological strategy to obtain peptides of different sizes and improved antioxidant, anti-hypertensive, anti-inflammatory, and hypocholesterolaemic activities. Therefore, the reuse and valorisation of shrimp by-products by obtaining bioactive peptides is an active research area, with potential applications and beneficial effects for human health, the environment, and the economy. However, further studies are needed to ensure their safe use, and to understand their mechanism of action.

DFT formalism studies on the structural and electronic properties of hexagonal graphene quantum dot with B, N and Si substitutional impurities

The study of carbon-based nanostructured materials is a highly active research field, that has made significant progress in the study of twodimensional materials and nanotechnology. The interest in these materials is mainly attributed to the fascinating properties they exhibit, as seen in the case of graphene as a 2D material, as well as emergence on numerous novel 2D materials and their heterostructures. Additionally, there is important interest in systems such as 2D quantum dots. Therefore, this work focuses on the systematic study of graphene quantum dots of various sizes, all within the framework of first-principles density functional theory. We started with the simplest graphene quantum dot (GQD) structure, benzene (C6H6), which consist of six carbon atoms passivated with hydrogen atoms. We then increased its size by adding more aromatic rings, resulting in the following GQD configurations: C24H12, C54H18, C96H24, C150H30 and C216H36. We report the density of states (DOS) and the imaginary part of the dielectric function (ε2) for the system, analyzing both the pristine configuration and the effect of both single and double (boron, nitrogen and silicon, denoted as Sa). The double substitutional atom study was done considering random, ortho-, meta-, and para-director positions just for the C94H24Sa2 GQD. In general, we can conclude that as the GQD increases in size, the HOMO-LUMO energy decreases. Furthermore, it is observed that boron and nitrogen exhibit their expected n-, and p-type doping characteristics, but this differs between single and double Sa substitutions. Additionally, the imaginary part of the dielectric function is highly sensitive to the positions of single and double substitutional atoms, as well as the polarization of incident light. Therefore, we suggest that these differences can be used to clearly determinate the type of substitutional atoms and their positions from optical measurements.

대한민국임시정부에 대한 일본 학계의 인식과 역사교과서의 서술 분석

In the first half of the twentieth century, during the Japanese colonial period, the Japanese general government in Korea and the Japanese central government did not recognize the Korean Provisional Government, dismissed it as an illegal organization(“shadow government”) and continuously suppressed its activities. As a result, the perception, description and evaluation of the Korean Provisional Government in some Japanese academic research and history textbooks remained very weak and scarce. In addition, many inaccurate and negative accounts have been found. Apart from the works of Sassa Mitsuaki(佐佐充昭), there are few contemporary works by Japanese scholars on the Provisional Government. Among Japanese history textbooks (on Japanese history and world history), those published by Shikkyo Publishing House stand out for giving a brief but relatively accurate account of the Provisional Government. Therefore, it is necessary to raise awareness of the Korean Provisional Government among Japanese scholars, promote comprehensive research and develop better ways to portray the Korean Provisional Government in Japanese textbook narratives. In this context, it is necessary to seek systematic solutions in the short, medium and long term. First, it will be necessary to strengthen and revitalize exchanges with international scholars and educators (especially Japanese scholars), including the promotion of more active joint research and joint publications. Second, it is necessary to promote research on the Provisional Government by Korean and foreign scholars and to internationalize, popularize and promote the results of such work. Third, more efforts should be made to improve the presentation of the activities of the Provisional Government in Japanese academic books, introductory books, humanities books and history textbooks. Fourth, Korean academic, educational and civil society organizations should promote more active and rigorous research and education on the subject. Fifthly, it is necessary to conduct free and honest research on the realities, achievements, successes and limitations of the Korean Provisional Government and the Korean Liberation Army. It will be important to promote discourse and storytelling and to create diverse content that can be consumed in everyday life. Finally, we must be careful not to ideologize under the influence of a particular political ideology or a teleological view of history in the way we perceive, evaluate and describe the Korean Provisional Government. In particular, it is necessary to reject ideologically biased perspectives from the Republic of Korea (South Korea), North Korea, Yanbian, China, Chinese and Japanese academia, Western academia and so on.

A Study on Distribution of Characteristics of Microplastic in the Han-River Watershed

Microplastic pollution in the marine environment is a global issue. Recently, in South Korea, there has been active research on the establishment of testing methods and investigation of distribution characteristics of microplastics not only in marine environments but also in freshwater systems. In particular, it is necessary to study the distribution of microplastics such as rivers and lakes, which are drinking water sources, to affect the water quality environment, management, and countermeasures. This study identified the distribution of microplastics in the mainstream and tributary of the Han River water system. The freshwater, sediment, and biological species samples were pre-treated accordingly, and microplastics larger than 20 µm were analyzed using μ-FT-IR. As a result of the inter-laboratory study, in the same way as in this study, it was possible to confirm that the trusted recovery rate was 63.6%. The survey results indicated that the number of microplastics per location ranged from 1,173 to 8,940 particles/L in freshwater samples, 3,800 to 192,000 particles/kg in sediment samples, and 34 to 384 particles/individual in fish samples. The most commonly found microplastic materials were PP, PE, and PTFE. The size distribution of plastics appeared in the following order: 45~100 µm, 100~300 µm, 20~45 µm, and greater than 300 µm, with predominantly fragmented shapes observed.

The application of graphene oxide and ferroptosis in the diagnosis and treatment of colorectal cancer: a narrative review.

Colorectal cancer (CRC), a leading global malignancy, continues to challenge the medical community. Despite advancements in surgical, chemotherapeutic, radiation, targeted, and immunotherapeutic strategies, issues like resistance and side effects persist. This review illuminates the potential of ferroptosis, an emerging non-apoptotic cell death form, and graphene oxide (GO), with its distinctive physicochemical properties, in CRC therapy. The databases search included PubMed, Medline and Web of Science. Search terms focused on CRC, graphene, GO, ferroptosis, and related aspects in therapy and drug delivery. The time frame for literature retrieval was up to April 2024. Studies in languages other than English were excluded. Ferroptosis has been recognized for its role in addressing treatment resistance, a notable hurdle in effective CRC management. This form of cell death offers a promising avenue for enhancing the effectiveness of existing treatments. However, understanding its mechanisms and clinical implications in CRC remains an area of active research, with significant progress required for its practical application. Simultaneously, GO, a versatile two-dimensional material, has demonstrated substantial potential in biomedical applications, especially in cancer therapy. Its high specific surface area and unique π-electron domains facilitate the effective binding of chemotherapy drugs, target genes, and photosensitizers. This makes GO a promising candidate in cancer diagnosis and treatment, particularly through tumor photothermal and photodynamic therapy (PDT). Despite these advancements, GO's clinical application faces challenges, including in vitro cytotoxicity and decreased biodegradability, necessitating further research. This review focuses on the characteristics of GO and ferroptosis, as well as their applications in tumor diagnosis and treatment, with a particular emphasis on their potential in CRC.

Enhanced Medical Image Segmentation using Transfer Learning with Res101_UNet: Experimental Insights and Comparative Performance Analysis

Throughout the past few decades, artificial intelligence and machine learning have seen a lot of active research in areas such as computer vision, natural language processing, and speech processing. As a result, deep learning models became state-of-the-art for computer vision tasks such as object detection, classification, segmentation, and other allied tasks. Of course, the fruits of this research are extended to the design of robust and reliable digital health systems as well as other applications in the healthcare sector. Many clinical applications require the automatic segmentation of medical images. Recent deep learning-based approaches have demonstrated state-of-the-art performance in medical image segmentation tasks. In addition to their ability to automatically extract features and generalize over large amounts of data, transfer learning based deep learning models have proven to be handy for data scared areas like medical domains. In this research, we investigate and demonstrate the efficacy of a DCNN-based transfer learning model -Res101_Unet, which has been trained and/or fine-tuned to execute tumor tissue segmentation tasks in MRI, CT, PET, and X-RAY pictures of medical organ scans with little data. For our experimental study, we employed two image datasets: 'Liver Tumor' and 'Gland Colon Cancer', both obtained from the Kaggle portal. This experimental setup includes an Open-Source segmentation model API. Our findings indicate that domain similarity-based transfer learning can be used to data-scarce sectors. We achieved 98.47% accuracy and a IoU score of 0.9891 on Liver Tumor data and 0.6956 accuracy and a IoU score of 0.7043 on gland colon dataset.

Terrorist activity research methodology. Part 1: research basics

Terrorist activity research methodology. Part 1: research basics

Quantum circuits for discrete graphical models

Graphical models are useful tools for describing structured high-dimensional probability distributions. The development of efficient algorithms for generating samples thereof remains an active research topic. In this work, we provide a quantum algorithm that enables the generation of unbiased and independent samples from general discrete graphical models. To this end, we identify a coherent embedding of the graphical model based on a repeat-until-success sampling scheme which clearly identifies whether a drawn sample represents the underlying distribution. Furthermore, we show that the success probability for finding a valid sample can be lower bounded with a quantity that depends on the number of maximal cliques and the model parameter norm. Moreover, we rigorously proof that the quantum embedding conserves the key property of graphical models, i.e., factorization over the cliques of the underlying conditional independence structure. The quantum sampling algorithm also allows for maximum likelihood learning as well as maximum a posteriori state approximation for the graphical model. Finally, the proposed quantum method shows potential to realize interesting problems on near-term quantum processors. In fact, illustrative experiments demonstrate that our method can carry out sampling and parameter learning not only with idealized simulations of quantum computers but also on actual quantum hardware solely supported by simple readout error mitigation.

Development and Evaluation of Conformal Prediction Methods for Quantitative Structure-Activity Relationship.

The quantitative structure-activity relationship (QSAR) regression model is a commonly used technique for predicting the biological activities of compounds using their molecular descriptors. Besides accurate activity estimation, obtaining a prediction uncertainty metric like a prediction interval is highly desirable. Quantifying prediction uncertainty is an active research area in statistical and machine learning (ML), but the implementation for QSAR remains challenging. However, most ML algorithms with high predictive performance require add-on companions for estimating the uncertainty of their prediction. Conformal prediction (CP) is a promising approach as its main components are agnostic to the prediction modes, and it produces valid prediction intervals under weak assumptions on the data distribution. We proposed computationally efficient CP algorithms tailored to the most widely used ML models, including random forests, deep neural networks, and gradient boosting. The algorithms use a novel approach to the derivation of nonconformity scores from the estimates of prediction uncertainty generated by the ensembles of point predictions. The validity and efficiency of proposed algorithms are demonstrated on a diverse collection of QSAR data sets as well as simulation studies. The provided software implementing our algorithms can be used as stand-alone or easily incorporated into other ML software packages for QSAR modeling.

Bispecific Antibodies for the Management of Relapsed/Refractory Multiple Myeloma.

Bispecific antibodies (BsAbs) are artificially engineered antibodies that can bind simultaneously to the CD3 subunit within the T-cell receptor complex and an antigen on tumor cells, leading to T-cell activation and tumor cell killing. BsAbs against BCMA or GPRC5D have shown impressive clinical activity in heavily pretreated patients with relapsed/refractory multiple myeloma (RRMM), with some agents having already received regulatory approval after the third (by the European Medicines Agency, EMA) or fourth (by the Food and Drug Administration, FDA) line of therapy; the results of early-phase clinical trials targeting FcRH5 are also promising. Overall, BsAbs as monotherapy correlated with an ORR that exceeded 60%, with a high CR rate ranging between 25% and 50% and a median PFS of around 1 year among patients with a median of 4-6 prior lines of therapy. The main toxicities include cytokine release syndrome, cytopenias, hypogammaglobulinemia, and infections; on-target off-tumor adverse events involving the skin, mucosa, hair, and nails may also occur with anti-GPRC5D BsAbs. Active research to increase their efficacy and improve their tolerance is still in progress, including combination therapies and application in earlier treatment lines and the development of novel agents. A better understanding of the mechanisms of resistance is a challenge and could lead to more personalized approaches.

Multifunctional Ln2 compounds with butterfly-shaped structures: Remarkable Single-Molecule Magnet behaviors, and biological activities

The efficient design and reasonable construction of multifunctional Ln(III)-based compounds with fascinating structures have always attracted great concern, and it is also an immense challenge in recent times for chemists and materials scientists. Herein, two new binuclear Ln(III)-based compounds with molecular formula [Ln2L2(dbm)2(CH3OH)2]·xCH3OH·yCHCl3 (LnIII = Tb (1), x =2, y = 0; LnIII = Dy (2), x =0, y = 2; H2L = (E)-N'-(5-bromo-2-hydroxy-3-methoxybenzylidene)nicotinohydrazide; and Hdbm = 1,3-diphenyl-1,3-propanedione) have been constructed by a polydentate Schiff base ligand (H2L) via solvothermal method. The structures, magnet behaviors, and biological activities of compounds 1 and 2 have been studied systematically. Structure studies suggest that the two Ln2 compounds 1 and 2 are isostructural and possess butterfly-shaped molecular structures. Magnetic studies exhibit that Dy2 compound 2 shows remarkable single-molecule magnet behavior under zero-field conditions with Ueff/kB = 55.91 K and τ0 = 4.02×10−7 s. Moreover, solid-state fluorescent properties research shows that the two Ln2 compounds display the characteristic Tb3+ and Dy3+ ions luminescence at room temperature. Furthermore, biological activities research reveal that the two Ln2 compounds have better antibacterial activities against four common types of bacteria (Escherichia coli, Staphylococcus aureus, Candida albicans, and Bacillus subtilis) than the polydentate Schiff base ligand (H2L) and β-diketo salts Ln(dbm)3⋅2H2O (Ln(III) = TbIII and DyIII). The interaction between Ln2 compounds (1 and 2) and calf thymus DNA have also been studied, and the result reveal that both Tb2 and Dy2 compounds were mainly intercalated with calf thymus DNA. To our knowledge, compounds 1 and 2 are rarely reported multifunctional Ln(III)-based compounds owning single-molecule magnet behavior, fluorescent properties, and biological activities simultaneously.

Understanding barriers and facilitators to palliative and end-of-life care research: a mixed method study of generalist and specialist health, social care, and research professionals

BackgroundPalliative care provision should be driven by high quality research evidence. However, there are barriers to conducting research. Most research attention focuses on potential patient barriers; staff and organisational issues that affect research involvement are underexplored. The aim of this research is to understand professional and organisational facilitators and barriers to conducting palliative care research.MethodsA mixed methods study, using an open cross-sectional online survey, followed by working groups using nominal group techniques. Participants were professionals interested in palliative care research, working as generalist/specialist palliative care providers, or palliative care research staff across areas of North West England. Recruitment was via local health organisations, personal networks, and social media in 2022. Data were examined using descriptive statistics and content analysis.ResultsParticipants (survey n = 293, working groups n = 20) were mainly from clinical settings (71%) with 45% nurses and 45% working more than 10 years in palliative care. 75% were not active in research but 73% indicated a desire to increase research involvement. Key barriers included lack of organisational research culture and capacity (including prioritisation and available time); research knowledge (including skills/expertise and funding opportunities); research infrastructure (including collaborative opportunities across multiple organisations and governance challenges); and patient and public perceptions of research (including vulnerabilities and burdens). Key facilitators included dedicated research staff, and active research groups, collaborations, and networking opportunities.ConclusionsProfessionals working in palliative care are keen to be research active, but lack time, skills, and support to build research capabilities and collaborations. A shift in organisational culture is needed to enhance palliative care research capacity and collaborative opportunities across clinical and research settings.

Neoadjuvant Immunotherapy in Non-melanoma Skin Cancers of the Head and Neck.

Neoadjuvant immunotherapy will change the standard of care for advanced resectable cutaneous squamous cell carcinoma (cSCC) and possibly other non-melanoma skin cancers. With pathological complete response rates around 50% for cSCC in early studies, neoadjuvant therapy allows patients the possibility of significant reduction in tumor size, de-escalation of adjuvant therapy, and improved long-term outcomes. Patients must be carefully selected to ensure that there is a margin of safety with respect to resectability, such that if a tumor progresses on neoadjuvant therapy, there remains a curative surgical option that is acceptable to the patient. The optimal treatment paradigm is an area of active research, with many researchers questioning whether adjuvant therapy, or even local therapy, is necessary in patients who seem to have a complete response. The ability to predict who will respond will become even more critical to answer, as a significant number of patients do not want to risk their disease progressing, especially in cosmetically sensitive areas of the head and neck. Recent studies in melanoma show promise for improved response rates using combination therapies, and these strategies may apply to cSCC as well. The use of LAG-3 inhibitors or mRNA vaccine technology may further improve the utility of neoadjuvant strategies.

The state of scientific research of militia activity in Ukraine during the period of partial liberalisation of the political regime in the USSR (1953–1962)

The state of scientific research of militia activity in Ukraine during the period of partial liberalisation of the political regime in the USSR (1953–1962)

Personal Libraries in Russia: Research Results

The study of personal libraries is important for understanding socio-cultural processes that cannot be assessed by examining other historical events, phenomena and facts. The article deals with the monograph by O.N. Ilyina “Personal Libraries in Russia: Terminology and Historiography” (St. Petersburg, 2022), published in the series “The Book in Russia in the 19th — early 20th Century” by the Russian National Library and the winner of the All-Russian competition of scientific works on library science, bibliography and book studies in the nomination “The best scientific work in the field of library science” in 2023. The structure of the historical and book studies edition, the content of the chapters and the peculiarities of the author’s approach to the coverage of historiography, as well as the stages of the formation of terminology for the study of personal libraries in the domestic humanitarian knowledge in the second half of the 18th — early 21st century are characterized. The emphasis is made on the artificiality of the division of periods in the study of personal libraries in 1917, noted by O.N. Ilyina, because up to the end of the 1920s, book historians, whose professional career began before the October events of 1917, continued to carry out active research activities. This idea is confirmed by contemporary works devoted to the life and work of book historians and bibliographers born in the second half of the 19th century. Special attention is paid to the terminology for describing the history of book collections as a whole (and the collections within them), as well as book marks and marginalia in individual copies. A number of remarks on the design of the reference apparatus of the edition and the rubrication of the text are made, which, however, do not prevent interested readers. The quality, relevance and scientific novelty of the monograph are noted.

Puerariae lobatae Radix: Progress in Extraction, Separation Methods and Pharmacological Activities Research

Kudzu root (Puerariae lobatae Radix) is the tuberous root of Pueraria lobata, family Leguminosae. Kudzu root contains a variety of beneficial active ingredients such as puerarin, daidzin, daidzein, genistenin, 3′-hydroxy puerarin, β-sitosterol, stigmasterol, arachidic acid, and so on. Modern medical research shows that active ingredients in kudzu root are widely used clinically as raw materials for the treatment of hyperglycemia, non-alcoholic fatty liver disease, myocardial infarction, alcohol addiction, oxidative stress, inflammatory response, and retinal blockage due to their various pharmacological effects such as improving cardiovascular circulation, lowering blood lipids, lowering blood pressure, lowering blood sugar, being antipyretic, being estrogen-like, and relieving alcohol. China has rich resources of kudzu root, and active ingredients are usually extracted before it is made into a preparation, so whether the extraction and separation process is reasonable will directly affect the ease of preparation and the efficacy of the treatment. This paper reviews the process methods for the extraction and separation of active ingredients in kudzu root and its common pharmacological activities. The aim is to provide some references for readers to compare the advantages and disadvantages of various extraction and separation methods as well as understand the active ingredients and pharmacological activities of kudzu root.