Similar Background Research Articles

PV Identifier: Extraction of small-scale distributed photovoltaics in complex environments from high spatial resolution remote sensing images

The precise location and size of distributed photovoltaics (PVs) is critical to infer the actual installed capacity and assess the remaining PV generation potential, and is therefore the cornerstone of strategic planning for distributed PV deployment. However, identifying small-scale distributed PVs in complex contexts from high spatial resolution remote sensing (HSRRS) images to obtain their information remains an issue. In this study, we propose an advanced deep learning model, called PV Identifier, to enhance the identification accuracy of small-scale PV systems from HSRRS images. PV Identifier uses a fine-grained feature layer (FFL) compatible with the size of PVs to improve the detection capability of the small-scale distributed PVs. At the same time, it effectively distinguishes between PVs and similar background using a novel semantic constraint module (SCM). We test PV Identifier on a distributed PV dataset in California. Experiments show that the inclusion of the FFL positively affects the model's sensitivity to small distributed PVs. Specifically, the PV Identifier with the FFL increases the Recall of identifying residential rooftop PVs by 1.9% compared to the model without the FFL. In addition, the integration of the SCM effectively improves the model's ability to locate residential rooftop PVs in complex environments, resulting in a 1.8% increase in the corresponding Precision. Compared to the four commonly used segmentation models, PV Identifier exhibits superior identification performance for residential rooftop PVs and commercial and industrial PVs, with an Intersection over Union (IoU) of 74.1% and 89.3%, respectively, which is at least 4.1% and 1.8% higher than other models. Overall, PV Identifier provides a viable solution to the problem of identifying small-scale distributed PV in complex backgrounds from HSRRS images.

Commentary on “Frontiers: Breaking the Glass Ceiling: Empowering Female Entrepreneurs Through Female Mentors”

Mentoring is vital to developing talent. A critical puzzle in designing mentorship programs involves how mentors are matched to mentees: Would mentees benefit more from mentors with a similar or different demographic background? The article [Germann F, Andersen S, Chintagunta P, Vilcassim N (2024) Frontiers: Breaking the glass ceiling: Empowering female entrepreneurs through female mentors. Marketing Sci., 43(2):239–468] highlights that women entrepreneurs benefit more from having women as mentors relative to men as mentors. In this commentary, I highlight how the implications of this paper depend in part on our understanding of the potential mechanisms underlying the benefits of same-gender mentoring relationships for women. I posit that these benefits stem from differences not only in mentors’ provision of psychosocial support but also in their coaching and sponsorship behaviors. By considering these different mechanisms, I propose an alternative implication that involves training mentors to engage in more appropriate coaching and sponsorship behaviors. Thus, I expand the implications of this article from mentor matching to mentor training. I propose that, by learning how effective mentors coach and sponsor women, mentors in cross-gender relationships can be better equipped to help their mentees. History: Catherine Tucker served as the senior editor for this article.

Rice Counting and Localization in Unmanned Aerial Vehicle Imagery Using Enhanced Feature Fusion

In rice cultivation and breeding, obtaining accurate information on the quantity and spatial distribution of rice plants is crucial. However, traditional field sampling methods can only provide rough estimates of the plant count and fail to capture precise plant locations. To address these problems, this paper proposes P2PNet-EFF for the counting and localization of rice plants. Firstly, through the introduction of the enhanced feature fusion (EFF), the model improves its ability to integrate deep semantic information while preserving shallow spatial details. This allows the model to holistically analyze the morphology of plants rather than focusing solely on their central points, substantially reducing errors caused by leaf overlap. Secondly, by integrating efficient multi-scale attention (EMA) into the backbone, the model enhances its feature extraction capabilities and suppresses interference from similar backgrounds. Finally, to evaluate the effectiveness of the P2PNet-EFF method, we introduce the URCAL dataset for rice counting and localization, gathered using UAV. This dataset consists of 365 high-resolution images and 173,352 point annotations. Experimental results on the URCAL demonstrate that the proposed method achieves a 34.87% reduction in MAE and a 28.19% reduction in RMSE compared to the original P2PNet while increasing R2 by 3.03%. Furthermore, we conducted extensive experiments on three frequently used plant counting datasets. The results demonstrate the excellent performance of the proposed method.

A STUDY ON REPRODUCTIVE LIFE OF THE BENGALEE HINDU FEMALES: A COMPARATIVE ANALYSIS

Reproduction is the process by which new individuals of a species are produced and the genetic materials are passed through generation after generation (Tortora, 2003). The existence of a species is maintained through the urge for the reproduction. Pearl (1939) accounted the urge for reproduction as basic attribute of all living organisms. The expressive form of this urge for the reproduction could be accounted as reproductivity or fertility. The urge for the reproduction in human could not be expressed in its full strength due to several restrictive factors work on it. Demographically observed fertility or infertility is the result of a well-defined number of both biological and behavioural factors, which serve to mediate the influence of culture, society, economic conditions, living standards, and other similar background determinants on individual reproductive behavior (Frank et al., 1994). The hedonistic attitude of human for the reduction of fertility would be described through the "Demographic Transition Model" (DTM) which defines the transition from high birth rates and high death rates to low birth rates and low death rates as part of the economic development of a country from a pre-industrial to an industrialized economy (Thompson, 1929). In the present study an attempt has been made to understand the current status of the reproductive life of the contemporary Bengalee females and the effect of demographic transition as well as fertility transition on the same. Materials of the present cross sectional study comprises with 200 adult married Bengalee females belonging to different caste group lived in a semi urban region of west Bengal. Mean age of the population was 32.63 ± 10.64. The result shows a remarkable decadal change in the reproductive life of the population. Age at menarche seems to follow the secular trend to being decreasing when comparing with a data (mean age 12.79 ± 41.37 and 13.41 ± 1.48 respectively). Comparison with a previous work revealed that the rate of literate women, employed women, the family income etc have been increased noticeable. The number of contraceptive used or adopt family planning families has also been increased remarkably in comparison with the earlier data (64.5 % and 56% respectively). Accordingly the rate of live birth has been decreased. The present study also differs from the age at marriage and marriage conception interval (MCI). Thus the present work revealed that the females (mothers) as well as the couples are more conscious about their reproductive life and adopt different family planning methods. Sharp decadal changes on their reproductive life could also be noticed which may be the ultimate result of the demographic transition.

Comprehending Health of the Transgender Population in India Through Bibliometric Analysis.

Objective: In India research on health issues of transgender populations are very recent and limited though transgenders are an important sub-group of the population. Hence, this study attempts to understand the state of transgender health research in India through a systematic review of literature. Methods: A systematic literature review was conducted using bibliometric analysis. Initially, 132 studies were identified, and only 37 articles meeting selection criteria were subsequently selected for review using PRISMA 2020 guidelines. The research landscape was examined with tools such as Biblioshiny, Arc-GIS (10.1), and Vos-Viewer. Results: The review highlights that existing literature on transgender health in India mainly focuses on sexual health while neglecting their overall health status. It also emphasises the skewed geographical coverage of these studies. Based on the analysis, the interdisciplinary nature of the subject is illustrated in a three-field plot and through term co-occurrence. These indicate the need for culture-specific gender-affirmative services promoting a holistic approach to comprehend the health of transgender populations in India. Conclusion: In India research on transgender health is lopsided and at an initial stage. There is a need to develop diverse research focus on various health issues of transgenders that should also be geographically representative. Future in-depth research on this subject will enable optimizing resource allocation, developing effective gender-inclusive policies, and support holistic planning for better health status of transgender people in India, and other countries with similar socio-cultural background.

Research on Mobile Phone Backplane Defect Segmentation Based on MDAF-UNet

Mobile phone backplanes are an important part of mobile phones, and are often affected by a wide range of factors during the manufacturing process, resulting in defects of various scales and similar backgrounds. Therefore, accurately identifying these defects is crucial for improving mobile phone quality. To address this challenge, this paper proposes a multi-scale and dynamic attention fusion UNet (MDAF-UNet) model. The model innovatively combines normal convolution with dilated convolution. This allows the model to capture subtle features of defects and to perceive a larger range of feature variations. Moreover, an improved attention mechanism is introduced in this paper. It fuses channel attention and spatial attention, and dynamically adjusts the feature fusion strategy with learnable weights. This allows the model to increase the attention of important features and improve the effectiveness of feature representation. Experimental results on a publicly available dataset show that the MDAF-UNet model achieves 66.9% Mean Intersection over Union (MIoU), outperforming other state-of-the-art models. This result provides an effective solution to the mobile phone backplane defect segmentation problem.

MASNet: mixed attention Siamese network for visual object tracking

Most Siamese-based trackers adopt correlation operation to perform similarity matching on feature fusion of template branch and search branch. However, the correlation operation directly uses the template feature to slide the window on the search area feature, and it is difficult to distinguish the target and background information when encountering similar target interference and background clutter, which can easily lead to tracking failure. In this paper, a mixed attention Siamese Network (MASNet) is proposed, which neatly integrates the modelling of global information and mutual information into the Siamese tracking framework. Specifically, through the learnable attention module, the local and global dependencies are adaptively integrated, and the rich context information is captured to improve the discrimination of the network for similar targets. After that, the correlation of the context information of the two branches is aggregated and adaptively encoded into the two branches, which makes up for the shortcomings of single correlation operation. In addition, the framework adopts a three-layer feature fusion method, which enables the tracker to better adapt to object deformation and similar object interference. Extensive experiments on OTB100, UAV123, GOT-10k and LaSOT show that the proposed tracking method achieves comparable performance to the advanced trackers.

Ensuring Dignity and Rights: Navigating Disability and Ageing Challenges

This article analyses the interplay between disability, ageing, and human rights, especially about the fundamental rights to food, shelter, and health for the population of a similar background as well as the powerless. The analyses are based on a literature review including policy documents and empirical findings. The focus is on how individuals with disabilities and older adults are confronted with obstacles and inequity in acquiring basic resources and public services. This includes the necessity of bridging the gap through influencing the legislators, providing social support and noble policies that will protect the rights of these groups. Furthermore, the article points to the value of autonomy and independence by providing special help, including the part where technologies as well as community-based services and suitable housing are discussed which in turn lead to improvement in quality of life and social integration. Also, it is aimed at guaranteeing appropriate and overall healthcare coverage, prevention services, and mental health support to cater for the specific needs of those with disabilities and old ages. The article which also highlights the strategies of food insecurity tackles the sustainable agriculture, nutrition education and the food recovery initiatives. In addition, it evaluates the role of providing secure and inclusive housing options, prioritizing affordable housing programs, and enabling the improvement of dwelling for senior people and disabled individuals. The role of diverse research strategies, the engagement of stakeholders, and the adoption of an intersectional perspective as a basis for development of sound evidence-based policies and practices that safeguard the dignity, autonomy, and rights of older adults with disabilities are emphasized throughout the article. Through these rights’ prioritization and the barriers’ check, societies can embrace the idea of equality and inclusion, and ultimately achieve social justice for everyone.

Green Fruit Detection with a Small Dataset under a Similar Color Background Based on the Improved YOLOv5-AT.

Green fruit detection is of great significance for estimating orchard yield and the allocation of water and fertilizer. However, due to the similar colors of green fruit and the background of images, the complexity of backgrounds and the difficulty in collecting green fruit datasets, there is currently no accurate and convenient green fruit detection method available for small datasets. The YOLO object detection model, a representative of the single-stage detection framework, has the advantages of a flexible structure, fast inference speed and excellent versatility. In this study, we proposed a model based on the improved YOLOv5 model that combined data augmentation methods to detect green fruit in a small dataset with a background of similar color. In the improved YOLOv5 model (YOLOv5-AT), a Conv-AT block and SA and CA blocks were designed to construct feature information from different perspectives and improve the accuracy by conveying local key information to the deeper layer. The proposed method was applied to green oranges, green tomatoes and green persimmons, and the mAPs were higher than those of other YOLO object detection models, reaching 84.6%, 98.0% and 85.1%, respectively. Furthermore, taking green oranges as an example, a mAP of 82.2% was obtained on the basis of retaining 50% of the original dataset (163 images), which was only 2.4% lower than that obtained when using 100% of the dataset (326 images) for training. Thus, the YOLOv5-AT model combined with data augmentation methods can effectively achieve accurate detection in small green fruit datasets under a similar color background. These research results could provide supportive data for improving the efficiency of agricultural production.

Enhancing reliability of failure modes and effects analysis dealing with linguistic distribution assessments: A consistency based approach

Failure modes and effects analysis is a proactive reliability-management engineering technique, it has been applied to improve reliability of processes, products, and services. Traditional failure modes and effects analysis method manifests three deficiencies with regard to form of risk assessments, determination of risk factor weights, and exploitation of failure modes’ risk levels. Although numerous studies have contributed to surmount these deficiencies, existing failure modes and effects analysis methods still face such issues. Moreover, a novel drawback has raised when failure modes and effects analysis participants adopt linguistic terms as risk assessments of failure modes, the reliability of linguistic distribution assessments as well as failure modes and effects analysis groups (participants with similar knowledge background are previously classified into a failure modes and effects analysis group) is overlooked. Therefore, this paper introduces the transformation of linguistic distribution assessments into fuzzy preference relations, as more effective modeling for investigating consistency, by using the newly defined possibility degrees of linguistic distribution assessments will be applied to devise four algorithms for enhancing reliability of assessments. Hence, the three deficiencies of traditional failure modes and effects analysis method are solved by means of a novel failure modes and effects analysis framework. Finally, a real example with respect to ranking failure modes of worm wheel grinding machine is developed to verify the performance and advantages of the proposed method, in which ten failure modes are ranked and the one with the highest risk level is selected, and consistency of risk assessments is improved to be acceptable.

High Dietary Folic Acid Supplementation Reduced the Composition of Fatty Acids and Amino Acids in Fortified Eggs.

The study aimed to evaluate the effects of dietary folic acid (FA) on the production performance of laying hens, egg quality, and the nutritional differences between eggs fortified with FA and ordinary eggs. A total of 288 26-week-old Hy-Line Brown laying hens (initial body weights 1.65 ± 0.10 kg) with a similar weight and genetic background were used. A completely randomized design divided the birds into a control group and three treatment groups. Each group consisted of six replicates, with twelve chickens per replicate. Initially, all birds were fed a basal diet for 1 week. Subsequently, they were fed a basal diet supplemented with 0, 5, 10, or 15 mg/kg FA in a premix for a duration of 6 weeks. Supplementation of FA could significantly (p < 0.05) enhance the FA content in egg yolks, particularly when 10 mg/kg was used, as it had the most effective enrichment effect. Compared to the control group, the Glu content in the 10 and 15 mg/kg FA groups showed a significant (p < 0.05) decrease. Additionally, the contents of Asp, Ile, Tyr, Phe, Cys, and Met in the 15 mg/kg FA group were significantly (p < 0.05) lower compared to the other groups. Adding FA did not have significant effects on the levels of vitamin A and vitamin E in egg yolk, but the vitamin D content in the 5 and 10 mg/kg FA groups showed a significant (p < 0.05) increase. Furthermore, the addition of FA did not have a significant effect on the levels of Cu, Fe, Mn, Se, and Zn in egg yolk. The dietary FA did not have a significant effect on the total saturated fatty acids (SFA) and polyunsaturated fatty acid (PUFA) content in egg yolk. However, the total monounsaturated fatty acid (MUFA) content in the 5 and 10 mg/kg groups significantly (p < 0.05) increased. These changes in nutritional content might be attributed to the increased very low-density lipoprotein (VLDL) protein content. The significant decrease in solute carrier family 1 Member 1 (SLC1A1), solute carrier family 1 Member 2 (SLC1A2), and solute carrier family 1 Member 3 (SLC1A3) gene expression compared to the control group appeared to be the reason for the decrease in amino acid content in egg yolk within the dietary FA group. The findings suggest that the appropriate addition of FA can enhance the levels of MUFA and vitamin D in egg yolks, thereby improving their nutritional value. Excessive intake of FA can decrease the effectiveness of enriching FA in egg yolk and impact the enrichment of certain amino acids. The yolk of eggs produced by adding 10 mg/kg of FA to the feed contains the optimal amount of nutrients. This study informs consumers purchasing FA-fortified eggs.

Petro-states, oil shocks, and regime change: Venezuela and Ecuador, 2013–2023

The literature on petrostates tends to blackbox the state. We argue, in contrast, that not all petro-states are configured equally. They thus respond to external crises differently. Despite sharing similar background conditions, the petro-state of Venezuela responded to the external oil shock of 2014–2015 by turning more authoritarian and predatory, whereas the petro-state of Ecuador tried to become more democratic and developmental. To explain this difference, we focus on three within-state institutional differences between these cases: the cohesion of hardliners, the reach of the coercive military and paramilitary apparatus, and the viability of the public and private sectors. In short, even petro-states operating under similar regimes (in this case, left-populist, semi-authoritarian) can exhibit different institutional make-ups, and these institutional differences help explain responses to similar external shocks.

“Estar Tranquilo”: Using a Life-course Approach to Explore Perceptions of Well-being among Older Adults in Curicó, Chile

This study assesses perceptions of well-being between two groups of older adults in Curicó, Chile. One group (n=12) were residents of a long-term care center (known as ELEAM), while another group (n=13) were members of two clubs for older adults – Estrellitas del Vaticano (Vatican’s Little Stars) and Club Campo Lindo (Beautiful Countryside) – who lived in their own homes. Data collection consisted of life-story narratives to explore differences in how older adults in different living situations – long-term residential care vs. independent living – define and perceive what it means to be well in older age. Both groups were paired according to the variables of age, educational level, socioeconomic status, and physical status. In this article, I explore how both groups expressed their desire to estar tranquilo or “be peaceful” in their older age; however, each group achieved this state in different ways. ELEAM residents focused on fostering good relationships with fellow residents and maintaining their autonomy. In contrast, club members focused on practicing their religion, maintaining family relationships, and engaging in activities. Although participants shared similar backgrounds and lived through the same historical events (i.e., military dictatorship), their current situations impacted their perceptions of well-being. For individuals to achieve their desired level of well-bing or to estar tranquilo required that they adapt to different living arrangements: club members had to adapt to living without their children, and ELEAM residents to living in an institution.

Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI

Detecting human-object interactions (HOI) in a few-shot setting remains a challenge. Existing meta-learning methods struggle to extract representative features for classification due to the limited data, while existing few-shot HOI models rely on HOI text labels for classification. Moreover, some query images may display visual similarity to those outside their class, such as similar backgrounds between different HOI classes. This makes learning more challenging, especially with limited samples. Bongard-HOI epitomizes this HOI few-shot problem, making it the benchmark we focus on in this paper. In our proposed method, we introduce novel label-uncertain query augmentation techniques to enhance the diversity of the query inputs, aiming to distinguish the positive HOI class from the negative ones. As these augmented inputs may or may not have the same class label as the original inputs, their class label is unknown. Those belonging to a different class become hard samples due to their visual similarity to the original ones. Additionally, we introduce a novel pseudo-label generation technique that enables a mean teacher model to learn from the augmented label-uncertain inputs. We propose to augment the negative support set for the student model to enrich the semantic information, fostering diversity that challenges and enhances the student’s learning. Experimental results demonstrate that our method sets a new state-of-the-art (SOTA) performance by achieving 68.74% accuracy on the Bongard-HOI benchmark, a significant improvement over the existing SOTA of 66.59%. In our evaluation on HICO-FS, a more general few-shot recognition dataset, our method achieves 73.27% accuracy, outperforming the previous SOTA of 71.20% in the 5- way 5-shot task.

Graph-based algorithm for exploring collaboration mechanisms and hidden patterns among top scholars

During past several decades, extensive interdisciplinary collaboration has greatly promoted the scientific innovation. Especially, collaborations among top scholars have become major driving forces in advancing scientific progress. Therefore, this article focusses on the mechanism and modes underlying collaboration of scholars. The advantage of this paper resides in its capacity to elucidate the hierarchical architecture and dynamics of top scholars' collaboration, discern the hidden collaborative association probabilities, and provide recommendation for fostering intellectual exchange and information dissemination. Results show that: (1) In terms of collaboration features, it exhibits a significant clustering effect. The largest three communities concentrate in Asia, Europe, and North America. Meanwhile, we further introduce dominant flow analysis, an algorithm originated from the geography, to excavate hierarchy architecture of collaborations. We have identified three kinds of scholars who perform distinct roles in the dissemination of knowledge: leading scholars tend to play a guiding role, senior scholars tend to act as a bridge to enlarge the collaboration range, and general scholars predominantly contribute to the collaborations. (2) In terms of formation mechanism of collaborations, we found the collaboration of top scholars are grounded in their publications’ quality instead of quantity. Furthermore, the closed rather than opened triangular configuration potently catalyzes knowledge transmission. (3) Meanwhile, hidden collaborative partnerships are extrapolated based on the model proposed in this article. In these hidden patterns, scholars who are geographically close and have similar research background potentially develop further research collaborations, and at least one scholar in collaborations has high citations.

Impact of teacher professional development on student achievement with a focus on Bosnia and Herzegovina: Analyzing TIMSS 2019 results in Western Balkan countries and Croatia

Students in Bosnia and Herzegovina (B&amp;amp;H) score very low on international assessments (TIMSS &amp;amp; PISA), lower than the countries in the region with which it shares similar background. In this paper the characteristics of teachers’ professional development (TPD) in the region of Western Balkan countries (Albania, B&amp;amp;H, Kosovo, Montenegro, North Macedonia, and Serbia) and Croatia are brought into correlation with average results in mathematics and science on TIMSS 2019. Research questions analyze teachers’ attitudes towards their profession and investigate the impact of professional development (PD) of mathematics and science teachers in the last two years, with a specific focus on the situation in B&amp;amp;H, on students’ achievement in mathematics and science. The findings indicate a lack of TPD as a contributing factor to lower results in B&amp;amp;H. The research suggests that B&amp;amp;H should consider reforms in the education system and enhance teachers’ attitudes towards their profession through intensified PD programs to advance education and learning.

Abstract 491: Aerosol delivery of immunotherapy and hesperetin nanoparticles in murine lung cancer model

Abstract Purpose: Radiation is the most common modality for lung cancer treatment method. Radiationinduces apoptosis, causing cancer cells to be fragmented and expose the cancer-associatedantigens to the tumor microenvironment. These can be recognized by antigen-presenting cells(APC) to induce the antineoplastic effect by activating cytotoxic T cells. Our prior studies showadding immunoadjuvant like AntiCD40 with radiation can further activate the APCs in its anti-tumor (M1) format. Recent studies have shown that flavonoids like Hesperetin, an ACE2receptor agonist also can induce apoptosis in cancer cells whereas ACE2 receptors are abundant in lung cancer cells.This project aims to develop a novel treatment for non-small cell lung cancer (NSCLC) using nanotechnology for inhalation drug delivery Hesperetin, a flavonoid with antioxidant and pro-apoptotic activity; bound to PLGA-coated nanoparticles (Hesperetin Nanoparticles, HNPs) andAntiCD40 aiming for localized targeted dosing to reduce the treatment-related systemic toxicity.We plan to test the efficacy and safety of this aerosol spray. Methods: In-vitro studies were performed in human A549 (ATCC) and murine LLC1 (ATCC)lung cancer cell lines for growth (MTT) and clonogenic survival assays to demonstrate the anti-cancer cell activity of Hesperetin (Sigma). Next, HNP was prepared using NanoFabTx™ nano-formulation reagent kits (Millipore-Sigma). A syngeneic orthotopic murine model of Lungadenoma was generated in wild (+/+) C57/BL6 background mice with similar background LLC1cell lines. We developed syngeneic orthotopic murine lung tumors with luciferase genetransfected LL/2-Luc2 (ATCC) Lewis Lung Cancer cell line in wild-type C57BL/6 mice(Techonic). Lung tumor-bearing mice were treated with HNP, antiCD40, or both with aerosolspray with a control group treated with the solvent (dH2O) only. To assess the drug delivery withaerosol treatment ex-vivo lung tissue was analyzed for Fluorescence tagged antiCD40 andnanoparticle uptakes. A survival assay was performed to analyze the efficacy of aerosoltreatment of HNPs with or without AntiCD40. All cohorts were also analyzed for body score, body weight, and liver and kidney functions. Results: We were able to successfully develop an aerosol drug delivery model to administer bothAnti-CD40 and HNP in a murine lung cancer model. In our analysis of an orthotopic murinelung cancer model, we demonstrate a high intake of the HNP and AntiCD40 by the cancer cellssparing the normal lung tissue. Moreover, the highest percentage of survival rate was observed with the combination aerosol treatment with HNP+AntiCD40 (p&amp;lt;0.001), compared to CD40alone (p&amp;lt;0.01) or HNP (p&amp;lt;0.01) alone. Comments: This treatment model will allow us to make the lung cancer treatment method easilyavailable for the mass population without having hazardous radiation treatment in the lungcancer model. Citation Format: Sayeda Yasmin-Karim, Geraud Richard, Amanda Fam, Alina-Marissa Ogurek, G. Mike Makrigiorgos. Aerosol delivery of immunotherapy and hesperetin nanoparticles in murine lung cancer model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 491.

Fibular morphology is not associated with incidence of peroneal tendon dislocation.

The association of peroneal tendon dislocation with peroneal bone morphology and postoperative redislocation rates remains unknown. This study compared the fibula morphology in patients with peroneal tendon dislocation with that in a control population. The study enrolled 48 patients who underwent surgery for peroneal tendon dislocation at our institution during between 2018 and 2023. Thirty-five patients with preoperative magnetic resonance imaging of the ankle were defined as Group D and 35 with magnetic resonance imaging of the ankle for other reasons and with similar background data were selected as the control group (Group C). The posterior tilting angle of the fibula, posterolateral angle and posterolateral edge angle were evaluated at the plafond level. The posterior tilting angle, posterolateral angle and retromalleolar bone shape according to the Rosenberg classification (flat, convex, concave) were evaluated at the midpoint between the plafond and the tip. At the plafond level, the posterior tilting, posterolateral and posterolateral edge angles were 57.7 ± 11.1°, 123.8 ± 12.3° and 90.8 ± 13.7°, respectively, in Group D and 64.1 ± 15.4°, 121.1 ± 12.3° and 88.7 ± 12.2°, respectively, in Group C, with no significant differences. No significant between-group differences existed in the posterior tilting and posterolateral angles at the midpoint level. Moreover, no significant differences existed in distribution of the bone geometry according to the Rosenberg classification. There were no differences in morphology between patients with peroneal tendon dislocation and controls. This study provides useful information on the indications for primary surgery and whether bony approach is useful for peroneal tendon dislocation. Level IV.

Camouflaged Object Detection That Does Not Require Additional Priors

Camouflaged object detection (COD) is an arduous challenge due to the striking resemblance of camouflaged objects to their surroundings. The abundance of similar background information can significantly impede the efficiency of camouflaged object detection algorithms. Prior research in this domain has often relied on supplementary prior knowledge to guide model training. However, acquiring such prior knowledge is resource-intensive. Furthermore, the additional provided prior information is typically already embedded in the original image, but this information is underutilized. To address these issues, in this paper, we introduce a novel Camouflage Cues Guidance Network (CCGNet) for camouflaged object detection that does not rely on additional prior knowledge. Specifically, we use an adaptive approach to track the learning state of the model with respect to the camouflaged object and dynamically extract the cues of the camouflaged object from the original image. In addition, we introduce a foreground separation module and an edge refinement module to effectively utilize these camouflage cues, assisting the model in fully separating camouflaged objects and enabling precise edge prediction. Extensive experimental results demonstrate that our proposed methods can achieve superior performance compared with state-of-the-art approaches.

Peer interactions during storybook reading on children’s knowledge construction: an experimental study on K2 and K3 children

This study explored the effects of peer interactions on kindergarten children’s construction of conservation and conflict resolution knowledge during storybook reading. Previous studies have identified that peer interactions can support the meaning-making processes of children in social relationships and problem-solving, but little is known about whether the interaction with mixed-age or more competent peers is more important in supporting knowledge construction. Sixty-four younger children in K2 and older children in K3 with similar socioeconomic backgrounds were recruited from a Montessori kindergarten in Kunming, China. An experimental design was applied to explore age group and conserver dominance effects on conservation and conflict resolution. Children were assigned randomly to eight groups in three 30-to-40-min intervention sessions. Each session had a different theme for the children to learn about conservation and conflict resolution concepts and a hands-on activity to practice and discuss. ANOVAs were performed to test group effects, while multiple regression analyses were conducted to explore individual variations in age and pre-test scores in predicting post-test scores. Conservation knowledge was significantly better among children who differed in age groups in the post-test, but differences were not found in conflict resolution knowledge. Groups balanced with equal conservers and non-conservers improved the best, suggesting that peer social interactions can facilitate conservation and conflict resolution construction. These results provide new insights for early childhood educators to support peer interactions and children’s development. Implications, limitations, and future research are discussed.