Miracle-dz/UniFAR-FTUs huggingface dataset:
Innate and adaptive immune-directed tumour microenvironment in pancreatic ductal adenocarcinoma

One of the most deadly and aggressive cancers in the world, pancreatic ductal adenocarcinoma (PDAC), typically manifests at an advanced stage. PDAC is becoming more common, and by the year 2030, it is expected to overtake lung cancer as the second greatest cause of cancer-related death. The poor prognosis can be attributed to a number of factors, including difficulties in early identification, a poor probability of curative radical resection, limited response to chemotherapy and radiotherapy, and its immunotherapy resistance. Furthermore, an extensive desmoplastic stroma that surrounds PDAC forms a mechanical barrier that prevents vascularization and promotes poor immune cell penetration. Phenotypic heterogeneity, drug resistance, and immunosuppressive tumor microenvironment are the main causes of PDAC aggressiveness. There is a complex and dynamic interaction between tumor cells in PDAC with stromal cells within the tumour immune microenvironment. The immune suppressive microenvironment that promotes PDAC aggressiveness is contributed by a range of cellular and humoral factors, which itself are modulated by the cancer. In this review, we describe the role of innate and adaptive immune cells, complex tumor microenvironment in PDAC, humoral factors, innate immune-mediated therapeutic advances, and recent clinical trials in PDAC.
Analyse des contraintes résiduelles par la méthode de la rainure et du trou incrémental

The main of this study is to compare the residual stress in depth of a material with the increment hole drilling method and the incremental groove drilling method. The incremental groove drilling method allows obtaining the stress in two dimensions instead of one dimension with the hole drilling method. Mots clefs Contraintes residuelles, Methode du trou incremental, Methode de la rainure incremental, Interferometrie de speckle, ESPI.
Deep learning‐based helmet wear analysis of a motorcycle rider for intelligent surveillance system

Automatic helmet wear analysis of a motorcycle rider is a promising video surveillance application, as the helmets are indispensable for saving the lives of humans from head injuries during road accidents. This article presents an intelligent video surveillance system for automatically detecting the motorcyclists with and without safety helmets. If the motorcyclists are found without the helmet, his/her license plate (LP) number is recognised to initiate further actions such as deduction of penalty amount from one's account linked with the vehicle license and Aadhar Number (Applicable to Indian Scenario) by the traffic police and the legal authority. First, the foreground objects are segmented, using Gaussian mixture model (GMM) and then labelled. Afterwards, the proposed system adapts faster region-based convolutional neural network (faster R-CNN) for the detection of motorcycles in the labelled foreground objects to ensure the presence of motorcyclists. Subsequently, faster R-CNN is also used for the detection of the motorcyclists with and without helmet. Finally, the LP number of the motorcyclists without the helmet is recognised, using character-sequence encoding CNN model and spatial transformer (ST). The proposed framework is evaluated, using the performance metric and mean average precision (mAP) on the surveillance dataset and it outperforms the state-of-the-art algorithms.
Urban community development: Reviewing non-profit impact in the USA and Africa

Urban community development is a multifaceted challenge that demands innovative and sustainable solutions. This paper conducts a comprehensive review of the impact of non-profit organizations in facilitating urban community development, drawing comparisons between the contexts of the United States and various regions in Africa. With a focus on the role of non-profits, this study examines the strategies, challenges, and outcomes of community development initiatives in urban settings. The literature review provides an overview of urban community development and underscores the increasing importance of non-profit organizations as key contributors to positive change. The paper then delves into a comparative analysis of non-profit projects in urban areas, exploring both the similarities and distinctive factors influencing community development efforts in the USA and Africa. The methodology section details the research approach, emphasizing data collection from diverse sources, including academic literature, non-profit reports, and case studies. Through a qualitative analysis, the study identifies key themes, success factors, and challenges associated with non-profit engagement in urban community development. The comparative analysis reveals common patterns, such as the importance of community engagement and grassroots participation, as well as unique challenges shaped by cultural, economic, and governance differences. Success factors, including effective partnerships and adaptive strategies, emerge as crucial components in achieving sustainable outcomes. The implications and recommendations section discusses the potential policy changes, community engagement strategies, and areas for future research. Recognizing the vital role of non-profits in urban community development, this study aims to inform stakeholders, policymakers, and practitioners about effective approaches and lessons learned from both the USA and African contexts. This research underscores the dynamic nature of urban community development and emphasizes the significance of non-profit organizations in fostering positive change. By examining and comparing experiences in the USA and Africa, this study contributes to a nuanced understanding of effective strategies for non-profit impact in urban environments, offering insights that can inform future initiatives and policies on a global scale.
Feature Dimensionality Reduction With L2,p-Norm-Based Robust Embedding Regression for Classification of Hyperspectral Images

The curse of dimensionality and noise corruption are two tough problems that need to be solved in hyperspectral image (HSI) classification. However, the current feature dimensionality reduction methods, including both feature extraction (FE) and feature selection ones, cannot simultaneously solve the above two problems well. To address this issue, this article proposes a novel method called <inline-formula> <tex-math notation="LaTeX">$L_{2, p}$ </tex-math></inline-formula>-norm-based robust embedding regression (<inline-formula> <tex-math notation="LaTeX">$L_{2, p}$ </tex-math></inline-formula>-RER) for robust feature dimensionality reduction of HSI, which can effectively suppress the impact of noises and reduce the feature dimensions. Specifically, <inline-formula> <tex-math notation="LaTeX">$L_{2, p}$ </tex-math></inline-formula>-RER first integrates projection learning with robust principle component analysis (RPCA) to remove noise in a low-dimensional space. Second, an embedding regression (ER) regularization is proposed to improve the discriminability of the extracted low-dimensional features. Third, an <inline-formula> <tex-math notation="LaTeX">$L_{2, 1}$ </tex-math></inline-formula>-norm constraint (<inline-formula> <tex-math notation="LaTeX">$L_{2, 1}$ </tex-math></inline-formula>-NC) is imposed to improve the interpretability of the learned projection matrix, which can jointly extract the key features from all bands with their physical meanings certainly preserved. Last but most important, the <inline-formula> <tex-math notation="LaTeX">$L_{2, p}$ </tex-math></inline-formula>-norm that can adaptively balance the sparsity and the convexity is employed to model the noise and regression residual in the embedded low-dimensional space, which can further enhance the robustness and generalization of the proposed method. In addition, extensive experiments conducted on three benchmark HSI datasets validated the effectiveness of the proposed method.
Assessment of Sensory Processing Issues in Children with Neurodevelopmental Disorders and Experiences of Maltreatment

This study aims to identify the sensory characteristics of children with both developmental disabilities such as ASD and ADHD and a history of child maltreatment (DM group), children with developmental disabilities (DD group), and typically developed children (TD group). The sensory characteristics of 24 children were assessed through virtual reality and self-administered questionnaires. The results elucidated that the duration of gazing at the “teacher” (60–75 s) was significantly different with the DM group’s gaze being shorter than the DD group’s gaze (p = 0.042). The duration of the “others” gaze (45–60 s) was also significantly different with the DM group’s gaze being longer than the DD and TD groups’ gaze (p = 0.018; p = 0.030). Additionally, the scores for tactile sensitivity, taste/smell sensitivity, under-responsive/seeks sensation, and the total short-term sensory profile were significantly different between the DM-DD and DD-TD groups. The scores of the heart rate perception test and Multidimensional Assessment of Interoceptive Awareness were significantly lower in the DM and DD groups. In conclusion, children who have experienced trauma and developmental disabilities may have different sensory characteristics than children with only developmental disabilities or none, implying the need for further research and tailored care.
Frequency-Domain Imaging Algorithm for SA-BiSAR Based on Azimuth Dealiasing

For the Doppler parameters coupling and spectral aliasing in the hybrid sliding spotlight mode of the spaceborne–airborne bistatic SAR (SA-BiSAR), a frequency-domain imaging algorithm based on echo preprocessing is proposed in this article. The article utilizes the idea of spectral analysis (SPECAN) technology to remove the spectrum aliasing by echo preprocessing, without subaperture partition and subaperture stitching operations, which reduces the computational burden. On this basis, the Legendre orthogonal polynomial expansion method is used to achieve a high-accuracy approximation of the SA-BiSAR slant range function. Combined with the method of series reversion, the accurate two-dimensional (2-D) spectrum of the point target is derived so that the high-quality decoupling of the 2-D spectrum is achieved. Finally, the compensation functions are designed to complete the focusing imaging in the frequency domain. The simulation results of point targets and distributed targets show that the imaging algorithm proposed in this article has good focusing performance and can improve the imaging quality of scene edge points.
The Role of K-12 Teachers as Agents for Change (RTP)

There is substantial evidence that most K-12 teachers who want to incorporate engineering design into their courses learn their skills independently or through an extracurricular professional development (PD) program. Regardless of the value of these PD programs, rookie teachers are frequently required to make personal sacrifices (e.g., time, money, and stress) to participate and thus hindering their long-term progress. To offer an alternative, four Teacher Leaders Engineering Network (TaLENt) fellows from primary and secondary schools served as change agents for novice engineering teachers for one academic year to promote the integration of engineering design in their classrooms. This research aimed to understand how school-based teacher leaders can support peer educators in authentically integrating engineering design within their core subjects. Our research questions were: 1) To what extent was the High-Quality Engineering Guidebook used within each TaLENt fellow's Project? 2) How did the TaLENt fellows characterize their values while collaborating with their novice peers? Employing a qualitative method, we used constant comparative analysis and triangulation to understand our collected datasets: TaLENt fellow narratives (N = 4 autobiographical texts), teacher project artifacts, and focus group transcripts. We found that TaLENt engineering PD increased peer collaboration, instructional risk-taking, and connections to cross-curricular subjects for novice teachers. Moreover, the action-based research approach paired with the High-Quality Engineering framework allowed inexperienced educators a say in their education, which helped reduce common misunderstandings about content alignment with engineering (such as the extent to which it applies to fields like physics or biology) and subsided anxiety about the processes of incorporating engineering in the classroom. The significance of this study is to highlight the value of teachers as in-school leaders. As states continue to adopt Next Generation Science Standards or incorporate engineering processes into their state-level curriculum, novice teachers will rely on their peers to strengthen their teaching practices within the subject, all while supporting the cultural needs of students. Our research shows the importance of in-school engineering PD facilitated by teacher leaders, especially for new and inexperienced engineering teachers; therefore, we recommend more investigation into implementing this type of PD. This change in professional development will make planning engineering lessons less stressful for novice teachers due to a reduced sense of isolation.
Anaphylactic reaction requiring epinephrine in a 10‐year‐old patient undergoing peanut challenge while on dupilumab therapy

use of emergency medication was checked again and the family received detailed nutritional counselling. Dupilumab is a highly eﬀective biologic for the treatment of moderate to severe atopic dermatitis and severe asthma 5,6 . Our patient also showed signiﬁcant improvement in eczema and asthma. Dupilumab also lowers food-speciﬁc IgE antibodies 9 . However, the clinical impact of the suppression is unclear. In our case, despite very low speciﬁc IgE antibodies to peanut and its components, the patient showed an anaphylactic reaction to peanut requiring treatment with epinephrine. Even though this is only a ﬁrst case report and data from controlled studies are still pending, this case shows that clinical relevance should in any case be checked in a controlled setting despite reduced and low peanut IgE levels so that emergency measures can be initiated immediately in case of provocation.
IFNs in host defence and parasite immune evasion during Toxoplasma gondii infections

Interferons (IFNs) are a family of cytokines with diverse functions in host resistance to pathogens and in immune regulation. Type II IFN, i.e. IFN-γ, is widely recognized as a major mediator of resistance to intracellular pathogens, including the protozoan Toxoplasma gondii. More recently, IFN-α/β, i.e. type I IFNs, and IFN-λ (type III IFN) have been identified to also play important roles during T. gondii infections. This parasite is a widespread pathogen of humans and animals, and it is a model organism to study cell-mediated immune responses to intracellular infection. Its success depends, among other factors, on the ability to counteract the IFN system, both at the level of IFN-mediated gene expression and at the level of IFN-regulated effector molecules. Here, I review recent advances in our understanding of the molecular mechanisms underlying IFN-mediated host resistance and immune regulation during T. gondii infections. I also discuss those mechanisms that T. gondii has evolved to efficiently evade IFN-mediated immunity. Knowledge of these fascinating host-parasite interactions and their underlying signalling machineries is crucial for a deeper understanding of the pathogenesis of toxoplasmosis, and it might also identify potential targets of parasite-directed or host-directed supportive therapies to combat the parasite more effectively.
North-South Environmental Bargaining: Ozone, Climate Change, and Biodiversity

In the negotiations over the Montreal Protocol on the Ozone, India and China drove a hard bargain and secured unprecedented commitments from the industrialized countries to transfer resources, both monetary and technological, to help underwrite ozone-friendly development policies. The precedent of using environmental protection as a bargaining chip has informed deliberations on climate change and biodiversity, but it seems doubtful that governments from less developed regions will be able to ex tract significant concessions in intergovernmental negotiations over these issues. My research suggests that successful bargaining by the South is determined in large part by the strategic nature of the bargaining situation, which differs in the three cases examined: ozone, climate change, and biodiversity.
Tolerance of Ambiguity and Engineering Identity

An understanding of the determinants of academic success of engineering students is important to improve the learning environment. The identity of a person is composed of several component identities. These various identities include but are not limited to, personal, identity, social identity, and professional identity. The correlation between professional identity and professional success as indicated by research has prompted the focus on development of engineering identity in engineering students. The tolerance of ambiguity of problem spaces is also being explored to move the learning environment closer towards a real-world problem space. This paper provides results of a study conducted at an HBCU to determine a correlation between tolerance of ambiguity, engineering identity. The responses of a cross-section of engineering students to validated surveys on engineering identity and tolerance of ambiguity were collected. The study indicated that the length of stay in college enhanced the engineering identity of the students. However, it was observed that the length of stay in college did not impact the tolerance of ambiguity.
Neurocognitive Examination of the Impact of Design Project Representation on Student Motivation and Performance

The ASME Vision 2030 Project (V2030) outlined a set of goals to aid in the development of engineering education to better face the current and future demands of the profession. Part of this vision proposed the implementation of designed-based curricula throughout the degree program. These design courses are meant to introduce students to implementing theoretical knowledge into real-world applications and design tasks. The purpose of this preliminary study is to investigate the impact of design courses on the neurocognition of mechanical engineering students. This study utilizes a group of students in a sequential series of cornerstone design courses. The study makes use of an electroencephalography (EEG) device to monitor the participant's brain activity during a design task. This data will compare brain activity when the participants are presented with differing modalities of design exercises. A modified version of the Motivated Strategies for Learning Questionnaire (MSLQ) will self-assess the student’s motivation toward the design tasks. The robustness of this study allows for the ability to examine the impact of both brain activation, motivation, and learning style on the student’s design. Motivation, brain activation, and learning style are measured regarding a student’s demographics, including gender, residency, and age, to determine if a correlation is present. The results of the study indicate that there is a correlation between change in brain activation in the beta frequency located in the right frontal cortex and design problem modality. These findings further present a strong correlation between the brain activations and self-reported motivations of the students. Specifically, a student’s cognition motivation had a positive influence with design problems presented as pictures. Further it was determined that a kinesthetic learning style benefitted from pictural design problems, as well.
Community structure of microbes in natural environments

Community structure refers to the taxonomic types of microbes and their relative abundance in an environment. This chapter focuses on bacteria with a few words about fungi; protists and viruses are discussed in Chapters 9 and 10. Traditional methods for identifying microbes rely on biochemical testing of phenotype observable in the laboratory. Even for cultivated microbes and larger organisms, the traditional, phenotype approach has been replaced by comparing sequences of specific genes, those for 16S rRNA (archaea and bacteria) or 18S rRNA (microbial eukaryotes). Cultivation-independent approaches based on 16S rRNA gene sequencing have revealed that natural microbial communities have a few abundant types and many rare ones. These organisms differ substantially from those that can be grown in the laboratory using cultivation-dependent approaches. The abundant types of microbes found in soils, freshwater lakes, and oceans all differ. Once thought to be confined to extreme habitats, Archaea are now known to occur everywhere, but are particularly abundant in the deep ocean, where they make up as much as 50% of the total microbial abundance. Dispersal of bacteria and other small microbes is thought to be easy, leading to the Bass Becking hypothesis that “everything is everywhere, but the environment selects. ” Among several factors known to affect community structure, salinity and temperature are very important, as is pH especially in soils. In addition to bottom-up factors, both top-down factors, grazing and viral lysis, also shape community structure. According to the Kill the Winner hypothesis, viruses select for fast-growing types, allowing slower growing defensive specialists to survive. Cultivation-independent approaches indicate that fungi are more diverse than previously appreciated, but they are less diverse than bacteria, especially in aquatic habitats. The community structure of fungi is affected by many of the same factors shaping bacterial community structure, but the dispersal of fungi is more limited than that of bacteria. The chapter ends with a discussion about the relationship between community structure and biogeochemical processes. The value of community structure information varies with the process and the degree of metabolic redundancy among the community members for the process.
A PROBABILITY-BASED STATISTICAL METHOD TO EXTRACT WATER BODY OF TM IMAGES WITH MISSING INFORMATION

Abstract. Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.