Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemoradiotherapy versus radiotherapy in patients with advanced nasopharyngeal cancer: phase III randomized Intergroup study 0099.

PURPOSE The Southwest Oncology Group (SWOG) coordinated an Intergroup study with the participation of Radiation Therapy Oncology Group (RTOG), and Eastern Cooperative Oncology Group (ECOG). This randomized phase III trial compared chemoradiotherapy versus radiotherapy alone in patients with nasopharyngeal cancers. MATERIALS AND METHODS Radiotherapy was administered in both arms: 1.8- to 2.0-Gy/d fractions Monday to Friday for 35 to 39 fractions for a total dose of 70 Gy. The investigational arm received chemotherapy with cisplatin 100 mg/m2 on days 1, 22, and 43 during radiotherapy; postradiotherapy, chemotherapy with cisplatin 80 mg/m2 on day 1 and fluorouracil 1,000 mg/m2/d on days 1 to 4 was administered every 4 weeks for three courses. Patients were stratified by tumor stage, nodal stage, performance status, and histology. RESULTS Of 193 patients registered, 147 (69 radiotherapy and 78 chemoradiotherapy) were eligible for primary analysis for survival and toxicity. The median progression-free survival (PFS) time was 15 months for eligible patients on the radiotherapy arm and was not reached for the chemo-radiotherapy group. The 3-year PFS rate was 24% versus 69%, respectively (P < .001). The median survival time was 34 months for the radiotherapy group and not reached for the chemo-radiotherapy group, and the 3-year survival rate was 47% versus 78%, respectively (P = .005). One hundred eighty-five patients were included in a secondary analysis for survival. The 3-year survival rate for patients randomized to radiotherapy was 46%, and for the chemoradiotherapy group was 76% (P < .001). CONCLUSION We conclude that chemoradiotherapy is superior to radiotherapy alone for patients with advanced nasopharyngeal cancers with respect to PFS and overall survival.
NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures

Abstract Precision medicine relies on the identification of robust disease and risk factor signatures from omics data. However, current knowledge-driven approaches may overlook novel or unexpected phenomena due to the inherent biases in biological knowledge. In this study, we present a data-driven signature discovery workflow for DNA methylation analysis utilizing network-coherent autoencoders (NCAEs) with biologically relevant latent embeddings. First, we explored the architecture space of autoencoders trained on a large-scale pan-tissue compendium (n = 75 272) of human epigenome-wide association studies. We observed the emergence of co-localized patterns in the deep autoencoder latent space representations that corresponded to biological network modules. We determined the NCAE configuration with the strongest co-localization and centrality signals in the human protein interactome. Leveraging the NCAE embeddings, we then trained interpretable deep neural networks for risk factor (aging, smoking) and disease (systemic lupus erythematosus) prediction and classification tasks. Remarkably, our NCAE embedding-based models outperformed existing predictors, revealing novel DNA methylation signatures enriched in gene sets and pathways associated with the studied condition in each case. Our data-driven biomarker discovery workflow provides a generally applicable pipeline to capture relevant risk factor and disease information. By surpassing the limitations of knowledge-driven methods, our approach enhances the understanding of complex epigenetic processes, facilitating the development of more effective diagnostic and therapeutic strategies.
Implications of tumour heterogeneity on cancer evolution and therapy resistance: lessons from breast cancer

Tumour heterogeneity is pervasive amongst many cancers and leads to disease progression, and therapy resistance. In this review, using breast cancer as an exemplar, we focus on the recent advances in understanding the interplay between tumour cells and their microenvironment using single cell sequencing and digital spatial profiling technologies. Further, we discuss the utility of lineage tracing methodologies in pre‐clinical models of breast cancer, and how these are being used to unravel new therapeutic vulnerabilities and reveal biomarkers of breast cancer progression. © 2023 The Pathological Society of Great Britain and Ireland.
Glucocorticoid feedback paradox: a homage to Mary Dallman

Abstract As the end product of the hypothalamus-pituitary-adrenal (HPA) axis, the glucocorticoid hormones cortisol and corticosterone coordinate circadian activities, stress-coping, and adaptation to change. For this purpose, the hormone promotes energy metabolism and controls defense reactions in the body and brain. This life-sustaining action exerted by glucocorticoids occurs in concert with the autonomic nervous and immune systems, transmitters, growth factors/cytokines, and neuropeptides. The current contribution will focus on the glucocorticoid feedback paradox in the HPA-axis: the phenomenon that stress responsivity remains resilient if preceded by stress-induced secretion of glucocorticoid hormone, but not if this hormone is previously administered. Furthermore, in animal studies, the mixed progesterone/glucocorticoid antagonist RU486 or mifepristone switches to an apparent partial agonist upon repeated administration. To address these enigmas several interesting phenomena are highlighted. These include the conditional nature of the excitation/inhibition balance in feedback regulation, the role of glucose as a determinant of stress responsivity, and the potential of glucocorticoids in resetting the stress response system. The analysis of the feedback paradox provides also a golden opportunity to review the progress in understanding the role of glucocorticoid hormone in resilience and vulnerability during stress, the science that was burned deeply in Mary Dallman’s emotions.
Elastic-plastic modeling method based on temporal convolutional network

Because the deformation of the material under load is strongly correlated with the loading path, the Temporal Convolutional Network (TCN), which can satisfy the time-series learning, is chosen to model the elastic-plastic intrinsic relationship of the material. The ABAQUS software is used to write scripts to construct the data set required for training. After training and learning the stress-strain states and their increments for different loading states, the constructed network model can well characterize the yielding process and the subsequent yielding evolution of the material. Compared with the traditional phenomenological model, it has better flexibility and computational efficiency, and provides a new method for constructing the constitutive model of materials.
Research on unexploded grenade target recognition algorithm based on YOLOv5

In recent years, target recognition has been applied more and more in the military field, which plays a vital role in military information intelligence, so the research on target recognition of unexploded grenade has great practical significance and military value. Based on deep learning, this paper enhances the data by rotating, clipping, adjusting brightness, etc., increases the sample size and diversity of the dataset, and then verifies through experiments, and the results show that the improved method can effectively identify unexploded grenade targets in real time.
Ladera Inestable en Leintz-Gatzaga. Estudio Geotécnico y Control del Deslizamiento con Técnicas Terrestres y Espaciales.

Rosser NJ, Petley DN, Lim M, Dunning SA, Allison RJ (2005) Terrestrial laser scanning for monitoring the process of hard rock coastal cliff erosion. Q J Eng Geol Hydrogeol 38:363–375. Rosser NJ, Lim N, Petley DN, Dunning S, Allison RJ (2007) Patterns of precursory rockfall prior to slope failure. J Geophys Res 112:F04014. Royan, M; Vilaplana, J.M. (2012) Distribucion espacio-temporal de los desprendimientos de rocas en la montana de Montserrat. Revista Cuaternario y Geomorfologia, (26) 1-2. Woodcoock, N.H. , (1977). Specification of fabric shapes using an eigen value method. Geological Society of America Bulletin 88,1231–1236. VIII Simposio Nacional sobre Taludes y Laderas Inestables Palma de Mallorca, Junio 2013 E.Alonso, J. Corominas y M. Hurlimann (Eds.) CIMNE, Barcelona, 2013
Implementation and evaluation of a soft tactile sensor using electrical impedance tomography

Compliant tactile sensing has received increasing interests in human-robot interactions and soft robotic sensing. However, it is still challenging to achieve high sensing performance over an area with low wiring complexity. This paper is to implement and evaluate a soft, distributed sensor that is enabled by the technique of electrical impedance tomography (EIT), which allows areal sensing using only boundary measurements. To achieve mechanical compliance of the sensor, a functional natural rubber composites filled with exfoliated graphite (EG/NR) is fabricated by spray coating. Long-term stability of the sensing material is evaluated under cyclic tests, and a high gauge factor of 6.25 is obtained, which can be explained from the evolution of the micromorphology under strain. A continuous sensing area with a diameter of 12 cm is prepared, and 16 electrodes are attached along the periphery to implement distributed sensing. The performance of the sensor is characterized under indentation tests. Results show that the intensity sensitivity monotonically decreases with the distance to the boundary, and consistent response is obtained along all the radial directions, providing predictable performance over the sensing area.
ATTRM6: A Distributed IPv6 Address Traceback and Threatener Restriction Mechanism Based on Smart Contract

To address the problems that current studies for enhancing network accountability based on IPv6 addresses do not support cross-Autonomous Systems (AS) or restrict threatener behaviors, a distributed IPv6 Address Traceback and Threatener Restriction Mechanism (ATTRM6) based on smart contract is proposed. Tracing servers of each AS form a blockchain and invoke smart contract functions to store address information of different ASes on the blockchain. When IPv6 address traceback is needed across ASes, the traceback server of a specific AS reads addresses information stored on the blockchain to identify the threatener. Considering the restriction scheme for threatener associated with IPv6 addresses, and proposing a Punishment-Forgiveness Policy (PFP) to dynamically adjust the reputation of threatener, and store restricted threatener and their reputation on the blockchain, thus providing data support to each AS to take restriction measures. Compared with information sharing based on a centralized database, the ATTRM6 mechanism can accomplish more reliable sharing. Experimental results show that the ATTRM6 mechanism has low overhead and can effectively perform IPv6 address traceback and threatener restriction.
Scintillation Effect Compensation by EDFA-Aided Periodic Threshold Decision for FSO Communications

This paper proposes the scintillation effect compensation by erbium-doped fiber amplifier (EDFA)-aided periodic threshold decision (PTD) for free-space optical (FSO) communications. PTD technique is introduced to compensate a significant intensity fluctuation of the received on-off keying (OOK) signal caused by the scintillation effect. Based on the quasi-static features of the atmospheric turbulence channel, the decision threshold of the multiple OOK bits are periodically estimated without the channel state information (CSI). Besides, the pre-amplifier EDFA is applied before photodiode (PD) to improve the performance of PTD by the optical power amplification and gain saturation. The proposed EDFA-assisted PTD is analyzed in simulation under different scintillation effects. Simulation results revealed that the performance of proposed EDFA-aided PTD was improved dramatically compared to the conventional PTD and adaptive threshold decisions.
Research on automatic vehicle lane changing model based on MASAC-discrete algorithm

Reinforcement learning has great potential in solving complex decision-making problems in autonomous driving, especially in traffic scenarios where autonomous and human driving vehicles are mixed. This article describes the lane changing problem of mixed traffic expressway vehicles as a multi-agent reinforcement learning problem, in which autonomous vehicles learn a strategy adapted to human driving vehicles through collaboration to maximize traffic throughput. This article extends the SAC-Discrete algorithm to the multi-agent reinforcement learning framework and proposes the MASAC-Discrete algorithm. In addition, this article also proposes a motion prediction safety controller that includes a motion predictor and motion replacement module to ensure driving safety during training and testing. This article trains, evaluates, and tests the proposed method on a highway simulator under three different levels of traffic modes. The simulation results show that even in high traffic density situations, this method can significantly reduce collision rates while maintaining high efficiency. In the considered highway scenarios, its performance is superior to several state-of-theart benchmark algorithms.
Elevated levels of tumor necrosis factor-alpha in Zairian neonate plasmas: implications for perinatal infection with the human immunodeficiency virus.

Plasma levels of tumor necrosis factor-alpha (TNF alpha) and the ability of plasmas to induce HIV expression in chronically infected cell lines were measured in samples from adults, cord blood, and neonates from Zaire and North America. Plasma levels of TNF alpha were higher in Zairian neonates born to HIV-negative and -positive mothers than in uninfected Zairian adults (612 vs. 128 vs. 8 pg/mL, P < .001); this dichotomy persisted until children were 9 months old. Plasmas from neonates of HIV-negative Zairian mothers also stimulated higher levels of reverse transcriptase from HIV-infected cell lines than did plasma from HIV-negative Zairian adults (1339 vs. 110 cpm, P < .001). Similar patterns were noted in plasmas from HIV-negative North American adults and neonates; however, TNF alpha levels were markedly lower, and smaller differences were noted among North American adults and neonates than those in the Zairian cohort. Markedly elevated plasma TNF alpha levels in Zairian neonates and infants may play a role in the pathogenesis and progression of HIV disease in this patient population.
Defining the capabilities and competencies of high-performing family physicians: a mixed methods study

Introduction High-performing primary care is recognised as the foundation of an effective and efficient healthcare system. Many medical graduates report they are not prepared for independent practice. To date, no research has been conducted to identify the key capabilities and competencies of high-performing family medicine graduates in Canada. This pilot project aims to identify the capabilities and competencies of high-performing early-career family physicians in Ontario, Canada, and explore opportunities for enhancing learning, teaching and assessment within family medicine residency programmes. Methods and analysis Employing a mixed-methods explanatory sequential study design, this research will use a theory-driven Professional Capability Framework, previously validated in studies across nine professions, to guide the investigation. The first (quantitative) phase involves surveying ~50 high-performing early-career family physicians identified as high performing by educators, colleagues and leaders. The objective of the survey is to identify the key competencies and personal, interpersonal and cognitive capabilities of high-performing family physicians. The second (qualitative) phase involves conducting workshops with stakeholders, including educators, professional associations, regulators and colleges, to test the veracity of the results. Quantitative data will be analysed using descriptive statistics, and qualitative data will be analysed using Braun and Clarke’s thematic analysis. The first and second phases will identify the key capabilities and competencies required to confidently adapt to the independent practice of comprehensive family medicine and inform fit-for-purpose educational strategies for teaching, learning and assessment. Ethics and dissemination The study is approved by the University of Toronto’s Health Sciences Research Ethics Board (#41799). Research findings will be discussed with professional bodies, educators responsible for family medicine curricula and universities. Study findings will also be disseminated through academic conferences and academic publications in peer-reviewed journals. Project summaries and infographics will be developed and disseminated to key stakeholders.
Cooperative activities of dICA69N-BAR and dCIP4F-BAR domain proteins regulate membrane tubule organization in vivo

Intracellular membrane tubules play a crucial role in diverse cellular processes, and their regulation is facilitated by Bin-Amphiphysin-Rvs (BAR) domain-containing proteins. This study investigates the roles of dICA69N-BAR and dCIP4F-BAR in vivo, focusing on their impact on in vivo tubule organization. Through cell culture and immunofluorescence staining, we observed co-localization of endogenous dICA69 with dCIP4-induced membrane tubules, indicating their potential recruitment for tubule formation and maintenance. Additionally, dCIP4-positive tubules exhibit enrichment of actin regulatory proteins such as Wasp, SCAR, Arp2, Arp3, and Syndapin. Overexpressing dICA69N-BAR in S2R+ cells reveals distinct punctate patterns in the perinuclear region. An earlier study indicated that F-BAR proteins spontaneously segregate from the N-BAR domain-containing proteins during membrane tubule formation. In contrast, our observation supports a model in which different BAR-domain family members can associate with the same tubule and cooperate to fine-tune the tubule width. Moreover, our analysis highlights how dCIP4F-BAR facilitates the redistribution of dICA69N-BAR punctae, leading to altered patterns within the cells. These cooperative activities of dICA69N-BAR and dCIP4F-BAR are vital for the precise organization of intracellular tubules. Understanding the underlying mechanisms governing this cooperation provides valuable insights into cellular dynamics and the organization of membrane tubules. The implications extend to various physiological and pathological conditions related to intracellular membrane dynamics.
The interplay between focus of attention, respiratory phases, and the Heartbeat Evoked Potential

The Heartbeat Evoked Potential (HEP) is an EEG fluctuation that reflects the cortical processing of cardiac signals. HEP amplitude increases during various tasks involving cardiac interoception. Recent research has also indicated that HEP amplitude and cardiac interoceptive accuracy are higher during exhalation compared to inhalation. This difference may be due to the suppression of heartbeat-related sensations during inhalation and the amplification of sensations during exhalation through attentional mechanisms. Despite significant advancements in HEP research, the interactions between the HEP, interoceptive attention, and respiration are still unclear. In this study, we developed a novel experimental paradigm to investigate the relationship between HEP amplitude and respiratory phases during tasks that involve attention to cardiac interoception, non-cardiac interoception (specifically, respiration), and exteroceptive stimuli. The tasks included the Heartbeat Counting Task and the Breath Counting Task as interoceptive tasks, as well as the Cardiac-Tone Counting Task and the Breath-Tone Counting Task as exteroceptive tasks. Results demonstrated significant increases in HEP amplitude during the Heartbeat Counting Task compared to the Cardiac-Tone Counting Task and the Breath Counting Task, mostly observed over fronto-central electrodes in a late time-window. Notably, the amplitude increases during the Heartbeat Counting Task were primarily driven by HEPs recorded during exhalation, while inhalation had minimal impact. These findings align with the predictive coding model of interoceptive perception, suggesting that HEP amplitude reflects a precision-weighting process of prediction errors related to cardiac sensations that is specifically influenced by attention directed toward the heart. Furthermore, our findings emphasize the crucial role of exhalation in this precision-weighting process. These results may have considerable implications for the development of respiratory interventions to fine-tune cardiac interoception.
Bitmojis and Beyond: Incorporating the Studio Habits of Mind Into Online Art Instruction

Although our art classrooms are rich with demonstrations, discussions, and artmaking, the COVID-19 pandemic brought unprecedented challenges to art educators wanting to engage students in studio-rich practices. As one solution, Bitmoji classrooms emerged in response to emergency remote teaching (ERT), “a temporary shift of instructional delivery to an alternate delivery mode due to crisis circumstances” (Hodges et al., 2020, para. 13). Bitmoji classrooms— containing an instructor’s avatar (Bitmoji) and typically presented using Google Slides—are virtual spaces populated with images and objects that hyperlink to videos, web tools, games, learning management systems (LMS), texts, and other resources. Bitmoji classrooms often visually mimic a classroom, although sometimes they represent an imagined space.