Time Requirements Research Articles

A Scalable Histological Method to Embed and Section Multiple Brains Simultaneously.

The preparation and processing of rodent brains for evaluation by immunohistochemistry is time-consuming. A large number of mouse brains are routinely used in experiments in neuroscience laboratories to evaluate several models of human diseases. Thus, methods are needed to reduce the time associated with processing brains for histology. A scalable method was developed to embed, section, and stain multiple mouse brains using supplies found in any common histology laboratory. Section collection schemes can be scaled to provide identical bregma locations between adjacent sections for immunohistochemistry, facilitating comprehensive, high-quality immunohistochemistry. As a result, sectioning and staining times are considerably reduced as sections from multiple blocks are stained simultaneously. This method improves on previous procedures and allows multiple embedding and subsequent immunostaining of brains easily with a dramatically reduced time requirement. Furthermore, we expand this method for use in numerous mouse tissues, rat brain tissue, and post-mortem human brain and arterial tissues. In summary, this procedure allows the processing of many rodent or human tissues from perfusion through microscopy in 10 days or less.

Nutrition Strategies for Young Athletes: Myths and Realities-A Review

Young athletes are in a period of accelerated growth that requires satisfying the combined nutritional demands of sport, growth, and development. These nutritional needs can only be satisfied with science-based planning that is free of common nutritional myths. Studies demonstrate the importance of providing energy and nutrients in a way that optimally satisfies tissue requirements in real time

Characterization of the evolution of thermal maturity and pore structure of continental organic-rich shales

To clarify the evolution of thermal maturity and pore structure in continental organic-rich shales, calcareous shales of the Liaohe Basin (China) were pyrolyzed, and examined using Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), nitrogen sorption isotherms, and nuclear magnetic resonance (NMR) spectroscopy. The increase in Raman G‒D band separation and decrease in Raman ID/IG ratio with increasing thermal maturity indicate that these parameters provide superior thermal maturity indicators. This is also confirmed by the good linear correlation of G‒D band shifts and ID/IG with vitrinite reflectance (VR) and maximum temperature (Tmax), respectively. The relative detection accuracy (DA), sampling requirements (SR), sample preparation (SP), detection time (DT), and equipment requirement (ER) of VR, G‒D band shifts, ID/IG, Tmax, FTIR, and XPS indicate that Raman analysis is a simple, quick, and robust method to evaluate thermal maturity. The moderate SR, complex SP, and long DT suggest that VR and Tmax are less widely applicable for characterizing thermal maturity. The FTIR and XPS techniques provide semi-quantitative maturity indicators with poor DA and high ER. Pores observed within organic matter and minerals under SEM indicate that an increase in thermal maturity not only affects the development of organic pores but is also beneficial for the formation of mineral dissolution pores, such as those formed during the transformation of Na0.95Ca0.16Al1.16Si2.84O8 to Na0.84Ca0.02Al1.02Si2.98O8, a process confirmed by XRD. The BET and NMR data also indicate that the development of pore structure is closely related to the evolution of thermal maturity in calcareous shale. During the initial stage, primary pores are filled by bitumen generated from kerogen; this leads to a decrease in transition pores, mesopores, and shale porosity, and reduced pore connectivity. Then, secondary nanoscale pores, transition pores, and mesopores increase with increasing thermal maturity. The peak in secondary porosity is consistent with the liquid hydrocarbon production rate peak, a process that increases shale porosity and leads to improved pore connectivity. The dissolution of minerals induced by organic acids may also contribute to this secondary porosity. With a further increase in thermal maturity, secondary porosity at the microscale is further developed, while transition pores and mesopores collapse, resulting in reduced pore connectivity. The poor pore connectivity that occurs at both low and high VR values may be more conducive to the preservation of shale oil and gas. This study is significant for research into the evolution of thermal maturity and pore structure in continental organic-rich shales.

Imaging through thick scattering media based on envelope-informed learning with a simulated training dataset

Computational imaging faces significant challenges in dealing with multiple scattering through thick complex media. While deep learning has addressed some ill-posed problems in scattering imaging, its practical application is limited by the acquisition of the training dataset. In this study, the Gaussian-distributed envelope of the speckle image is employed to simulate the point spread function (PSF), and the training dataset is obtained by the convolution of the handwritten digits with the PSF. This approach reduces the requirement of time and conditions for constructing the training dataset and enables a neural network trained on this dataset to reconstruct objects obscured by an unknown scattering medium in real experiments. The quality of reconstructed objects is negatively correlated with the thickness of the scattering medium. Our proposed method provides a new way, to the best of our knowledge, to apply deep learning in scattering imaging by reducing the time needed for constructing the training dataset.

A Transformer and Visual Foundation Model-Based Method for Cross-View Remote Sensing Image Retrieval

Abstract. Retrieving UAV images that lack POS information with georeferenced satellite orthoimagery is challenging due to the differences in angles of views. Most existing methods rely on deep neural networks with a large number of parameters, leading to substantial time and financial investments in network training. Consequently, these methods may not be well-suited for downstream tasks that have high timeliness requirements. In this work, we propose a cross-view remote sensing image retrieval method based on transformer and visual foundation model. We investigated the potential of visual foundation model for extracting common features from cross-view images. Training is only conducted on a small, self-designed retrieval head, alleviating the burden of network training. Specifically, we designed a CVV module to optimize the features extracted from the visual foundation model, making these features more adept for cross-view image retrieval tasks. And we designed an MLP head to achieve similarity discrimination. The method is verified on a publicly available dataset containing multiple scenes. Our method shows excellent results in terms of both efficiency and accuracy on 15 sub-datasets (10 or 50 scene categories) derived from the public dataset, which holds practical value in engineering applications with streamlined scene categories and constrained computational resources. Furthermore, we initiated a comprehensive discussion and conducted ablation experiments on the network design to validate its efficacy. Additionally, we analyzed the presence of overfitting within the network and deliberated on the limitations of our study, proposing potential avenues for future enhancements.

Towards efficient control synthesis for nonlinear wave energy conversion systems: impedance-matching meets the spectral-domain

Existing studies within the literature that focus on designing parametric energy-maximizing controllers for Wave Energy Converter (WEC) systems predominantly rely on the impedance-matching (IM) principle, originally developed for linear time-invariant systems. Alternatively, iterative optimization routines are commonly employed for nonlinear WECs. However, these approaches often face a trade-off between effectiveness in maximizing energy extraction and computational efficiency. To address this limitation, this study proposes a computationally efficient controller tuning method for analogous synthesis in the case of nonlinear WECs. The proposed approach combines a statistical linearization technique known as spectral-domain modeling with the IM principle, to synthesize a Proportional–Integrative (PI) controller for a nonlinear WEC. Furthermore, a comparison is performed with two other synthesis methods: one based on a standard (i.e. linear) frequency-domain representation of the WEC that incorporates the IM principle, and the other employing a gradient-free optimization routine applied to the nonlinear time-domain model of the WEC for PI parameter tuning through exhaustive numerical search. A discussion on the effectiveness of each tuning method in maximizing energy absorption is provided, including an appraisal of their associated computational time requirements. Numerical analyses demonstrate that the proposed method, which integrates spectral-domain modeling and IM, can achieve (almost) optimal PI controller design for a nonlinear WEC. Furthermore, this study addresses the inaccuracies inherent in the frequency-domain approach and significantly reduces the computational time compared to the exhaustive search procedure. The findings of this research represent a significant advancement towards the development of simple, effective, and efficient IM-based techniques for synthesis of controllers in nonlinear WEC systems

Problems of closing criminal proceedings due to the expiration of pre-trial investigation deadlines

The article is dedicated to addressing the current issues in the theory and practice of closing criminal proceedings during the pre-trial investigation stage, particularly focusing on the basis of closing due to the expiration of pre-trial investigation deadlines. The problem of closing criminal proceedings by the investigating judge based on paragraph 10 of Part 1 of Article 284 of the Criminal Procedure Code of Ukraine is currently the subject of active discussions among legal professionals. This basis is directly related to the pre-trial investigation stage and, according to the current established practice of the Supreme Court, is classified as exclusive competence of the prosecutor, limiting the Investigating Judge's ability to exercise effective judicial control during the pre-trial investigation stage. It is noted that the absence of these powers in the Investigating Judge entails the risk of violating the reasonable time requirements for pre-trial investigation, as the pre-trial investigation deadline is not just a formality. Enshrining in procedural law the prosecutor's obligation to apply to the court with an accusatory document or close the criminal proceedings as soon as possible but not later than the procedural deadline after notifying the suspect of the accusation is a guarantee of the fundamental right of individuals to have their cases heard within a reasonable time frame. Unfortunately, in practical terms, this guarantee is not always implemented, and the lack of effective judicial control only contributes to the spread of prosecutorial inactivity. The article suggests that the most optimal solution to this problem is the alternative competence of both the prosecutor and the Investigating Judge regarding the authority to close criminal proceedings during the pre-trial investigation stage. This would help achieve a balance of interests between the parties involved in criminal proceedings and prevent abuses of power. To improve the mechanism for ensuring compliance with reasonable deadlines, the author proposes expanding and specifying the powers of the Investigating Judge when closing criminal proceedings. Specifically, it is suggested to add Part 2-1 to Article 284 of the Criminal Procedure Code of Ukraine: «Criminal proceedings at the pre-trial investigation stage are closed by the Investigating Judge based on the grounds provided for in paragraph 10 of this article if the suspect does not object to the closure on these grounds.»

LSTM network optimization and task network construction based on heuristic algorithm

This work aims to advance the security management of complex networks to better align with evolving societal needs. The work employs the Ant Colony Optimization algorithm in conjunction with Long Short-Term Memory neural networks to reconstruct and optimize task networks derived from time series data. Additionally, a trend-based noise smoothing scheme is introduced to mitigate data noise effectively. The approach entails a thorough analysis of historical data, followed by applying trend-based noise smoothing, rendering the processed data more scientifically robust. Subsequently, the network reconstruction problem for time series data originating from one-dimensional dynamic equations is addressed using an algorithm based on the principles of Stochastic Gradient Descent (SGD). This algorithm decomposes time series data into smaller samples and yields optimal learning outcomes in conjunction with an adaptive learning rate SGD approach. Experimental results corroborate the remarkable fidelity of the weight matrix reconstructed by this algorithm to the true weight matrix. Moreover, the algorithm exhibits efficient convergence with increasing data volume, manifesting shorter time requirements per iteration while ensuring the attainment of optimal solutions. When the sample size remains constant, the algorithm’s execution time is directly proportional to the square of the number of nodes. Conversely, as the sample size scales, the SGD algorithm capitalizes on the availability of more information, resulting in improved learning outcomes. Notably, when the noise standard deviation is 0.01, models predicated on SGD and the Least-Squares Method (LSM) demonstrate reduced errors compared to instances with a noise standard deviation of 0.1, highlighting the sensitivity of LSM to noise. The proposed methodology offers valuable insights for advancing research in complex network studies.

Understanding non-participation in local governance institutions in Indonesia

Community-centered approaches are crucial and impactful strategies for the global climate and biodiversity crisis. However, these approaches hinge upon participation for both pragmatic and ethical reasons. While there is a growing body of research in this field, most studies focus on those who opt in to these community-based approaches. Research focuses on how interventions do or do not achieve the intended cross-sectoral outcomes that are flagship among these strategies. Few studies seek to understand the objective and subjective constraints of non-participants. We investigated why community members chose not to participate in a community-centered conservation approach in West Kalimantan, Indonesia. We used snowball saturation sampling and semi-structured interviews across nine villages, surveying both non-participants and key informants. Our results show that non-material factors such as time, lack of understanding, and feeling uninvited drove non-participation. Non-participants did not identify a lack of interest in program activities or services as a primary reason for opting out. Key informants suggested that participation could be improved with better outreach around objectives, potential benefits, and data feedback loops that quickly communicated results to community members. These results have implications for conservation strategies around the globe as findings suggest investing in non-material factors (e.g., improved messaging and considerations of time burdens) are significant constraints to participation. Payment for ecosystem services and carbon finance schemes often invest considerable time and money in incentivizing participation with material benefits, and our results suggest a more significant consideration should be placed on time requirements, messaging/outreach, adaptive feedback loops, and democratizing data ownership.

MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models

RNA modification serves as a pivotal component in numerous biological processes. Among the prevalent modifications, 5-methylcytosine (m5C) significantly influences mRNA export, translation efficiency and cell differentiation and are also associated with human diseases, including Alzheimer’s disease, autoimmune disease, cancer, and cardiovascular diseases. Identification of m5C is critically responsible for understanding the RNA modification mechanisms and the epigenetic regulation of associated diseases. However, the large-scale experimental identification of m5C present significant challenges due to labor intensity and time requirements. Several computational tools, using machine learning, have been developed to supplement experimental methods, but identifying these sites lack accuracy and efficiency. In this study, we introduce a new predictor, MLm5C, for precise prediction of m5C sites using sequence data. Briefly, we evaluated eleven RNA sequence-derived features with four basic machine learning algorithms to generate baseline models. From these 44 models, we ranked them based on their performance and subsequently stacked the Top 20 baseline models as the best model, named MLm5C. The MLm5C outperformed the-state-of-the-art predictors. Notably, the optimization of the sequence length surrounding the modification sites significantly improved the prediction performance. MLm5C is an invaluable tool in accelerating the detection of m5C sites within the human genome, thereby facilitating in the characterization of their roles in post-transcriptional regulation.

Digital Problem Based Learning for Facilitating the Acquisition of Collaborative Competencies

Is Networked Learning (NL) and Problem-Based Learning (PBL) the future of education to foster collaboration? Networked learning has been proposed to be combined with PBL. Both are pedagogies and philosophies influenced by traditions of open learning, radical pedagogies and humanistic educational ideas. Problem-based learning is a constructivist, student-centered, and problem-based approach used at the medical education at Aalborg University (AAU). During COVID, AAU fast-tracked the implementation of Digital PBL (DPBL) methods. Digital PBL opens new possibilities for collaborations across platforms and holds a potential to improve learning. This potential has yet to be released through systematic efforts to understand the possibilities in the context of medical education.The curriculum at the medical education at AAU is centered around the seven roles of physicians originally described in the Canadian framework, CanMEDS. Healthcare systems becomes increasingly complex, interconnected, and rely on interdisciplinary teamwork. The Collaborator role thus becomes more important than ever before. Physicians are expected to excel in clinical expertise and collaborate effectively with other healthcare professionals, patients, and families.The specific focus on collaboration is a good example of alignment between PBL-, NL pedagogy and the CanMEDS framework, and could be important to further exploration using DPBL.This study will investigate the possibilities of DPBL within the medical education at AAU by exploring and testing digitally supported pedagogical design options for facilitating the acquisition of collaborative competencies.This explorative sequential mixed-method study will explore user-needs and perspectives using DPBL in the medical education. This contextualized knowledge will inform the development of a new teaching intervention aimed at enhancing the Collaborator role. It will be evaluated using quantitative measures of student engagement, time requirements, satisfaction and self-report learning outcomes. The data will be merged with focus group interviews to gain an in-depth understanding of the quantitative results.The theoretical background will be learning design, including constructivism. This approach will be employed using the ACAD-model. The DPBL will include a digital element, the podcast media, and a pedagogical practice encouraging the medical students to engage actively in the learning process. This is facilitated by podcast production in groups.At NLC24 the findings of the user-needs and perspectives will be presented and interpreted as part of the design and frame of the podcast intervention. The intervention will take place in autumn 2024 and this can answer if NL and PBL is part of the future education to foster collaboration.

Models of Herpes Simplex Virus Latency

Our current understanding of HSV latency is based on a variety of clinical observations, and in vivo, ex vivo, and in vitro model systems, each with unique advantages and drawbacks. The criteria for authentically modeling HSV latency include the ability to easily manipulate host genetics and biological pathways, as well as mimicking the immune response and viral pathogenesis in human infections. Although realistically modeling HSV latency is necessary when choosing a model, the cost, time requirement, ethical constraints, and reagent availability are also equally important. Presently, there remains a pressing need for in vivo models that more closely recapitulate human HSV infection. While the current in vivo, ex vivo, and in vitro models used to study HSV latency have limitations, they provide further insights that add to our understanding of latency. In vivo models have shed light on natural infection routes and the interplay between the host immune response and the virus during latency, while in vitro models have been invaluable in elucidating molecular pathways involved in latency. Below, we review the relative advantages and disadvantages of current HSV models and highlight insights gained through each.

Denoising of the gradient artifact present in simultaneous studies of muscle blood oxygen level dependent (BOLD) signal and electromyography (EMG)

The MR-induced gradient artifact affects EMG recordings during simultaneous muscle BOLD/EMG acquisitions. However, no dedicated hardware can remove the gradient artifact easily, and alternative methods are expensive and time-consuming. This study aimed to develop three denoising methods requiring different processing levels and MR-compatible hardware.At two time points, surface EMG was recorded from the lower leg of 6 participants (50:50 sex ratio, age = 26.24.6 yrs., height = 173.59.2 cm, weight = 71.511.4 kg) using a plantar flexion-based block design consisting of 30s of rest followed by 30s of flexion for 5 min, under three conditions: inside the MRI bore, with and without a BOLD sequence (3 T, BOLD sequence, GRE EPI, 10 slices, 64×64 matrix, 2 mm thickness, and TE/TR/flip = 35/3000 ms/70), and outside the MRI environment. Simultaneous BOLD/EMG recordings were denoised using average artifact subtraction with three methods of artifact template creation, each having varying timing and hardware requirements. Method M1 builds the artifact template by recording the scanner triggers coming from the MRI; M2 creates the artifact template with a constant artifact period computed as TR/[number of slices]; M3 estimates the artifact template by looking at the periodicity of the gradient artifact located in the EMG recordings. Following postprocessing, SNR analysis was performed, comparing rest-to-flexion periods, to assess the efficacy of denoising methods and to compare differences between conditions.Linear mixed-effects models showed no significant differences in the mean SNR between denoising methods (p = 0.656). Furthermore, EMG SNR measurements were significantly affected by the magnetic environment (p < 0.05) but not by muscle fatigue over time (p = 0.975).EMG recordings contaminated with gradient artifacts during simultaneous BOLD/EMG can be efficiently denoised using all proposed methods, with two methods requiring no extra hardware. With minimal post-processing, EMG can easily be performed during muscle BOLD MRI studies.

Timing-accurate scheduling and allocation for parallel I/O operations in real-time systems

In industrial real-time systems, the I/O operations are often required to be both timing predictable, i.e., finish before the deadline to ensure safety, and timing accurate, i.e., start at or close to an ideal time instant for optimal I/O performance. However, for I/O-extensive systems, such strict timing requirements raise significant challenges for the scheduling of I/O operations, where execution conflicts widely exist if the I/O operations are scheduled at their ideal time instants. Existing methods mainly focus on one I/O device and apply simple heuristics to schedule I/O operations, which cannot effectively resolve execution conflicts, hence, undermining both timing predictability and accuracy. This paper proposes novel scheduling and allocation methods to maximize the timing accuracy while guaranteeing the predictability of the system. First, on one I/O device, a fine-grained schedule using Mixed Integer Linear Programming (MILP) is constructed that optimizes the timing accuracy of the I/O operations. Then, for systems containing multiple I/O devices of the same type, two novel allocations are proposed to realize parallel timing-accurate I/O control. The first utilizes MILP to further improve the timing accuracy of the system, whereas the second is a heuristic that provides competitive results with low overheads. Experimental results show the proposed methods outperform the state-of-the-art in terms of both timing predictability and accuracy by 37% and 25% on average (up to 5.56x and 33%), respectively.

Instructional design of blended learning in higher education: an analytical review of international research

Relevance. The relevance of this study lies in the fact that in modern conditions the huge potential of constantly updated digital educational technologies is not sufficiently used in blended learning. Purpose. The purpose of the study was to rethink traditional learning in accordance with the requirements of digital time, to consider the possibilities and contradictions of online learning, as well as to study blended learning in more depth. Methodology. The research tasks involved analysing literature at the intersection of pedagogy, psychology, information technology, and technical sciences. Also, comparative analysis, modelling, and synthesis were used. As a research methodology, interdisciplinary, systemic, activity, synergetic approaches, project methods, and blended learning didactics were implemented, the results of the experiment were analyzed and its results were summarized, and the differentiation of digital resources in education was compared. Results. It was determined that a methodology for assessing the formation of general and professional competencies of students through blended learning can be achieved by creating tools for measuring expected competencies. The results of previous studies have revealed the lack of resources that can provide a link between online and offline learning, and the need to develop a blended learning design using digital communication in learning. The analysis of the process of transformation of education during the pandemic and after it revealed the lack of didactic and technological justification for blended learning. Conclusions. The study provides a comprehensive analysis of blended learning in the digital era, offering practical tools and highlighting areas for further development in educational practices. Keywords: blended learning; instructional design; digital communications; information technology; educational trends; new directions in learning; multimedia

A Comparative Dataset of Annotated Broccoli Heads Recorded with Depth Cameras from a Moving Vehicle

An extensive, publicly available dataset is presented—the LAR Broccoli dataset—which contains 20,000 manually annotated images of broccoli heads captured from a moving tractor at an organic farm in the UK. The dataset contains images of the same row of broccoli heads recorded at 30 frames per second (fps) with three different cameras. Two off-the-shelf, relatively low-cost depth-sensing cameras were used, with the tractor moving at a speed of around 1 km/h, in addition to a webcam, with the tractor moving twice as fast. The utility of the dataset is demonstrated in four ways. First, three different state-of-the-art detector models were trained on the dataset, achieving an overall mean Average Precision (mAP) score of over 95% for the best-performing detector. The results validate the utility of the dataset for the standard task of in-field broccoli head recognition. Second, experiments with transfer learning were conducted, initialised with a smaller pre-trained broccoli detection model, and refined with the LAR Broccoli dataset. Third, we assessed the advantages of transfer learning not only using mAP but also according to time and space requirements for training models, which provides a proxy metric for energy efficiency, a practical consideration for real-world model training. Fourth, the cross-camera generalisation among the three camera systems was compared. The results highlight that testing and training detector models using different camera systems can lead to reduced performance, unless the training set also includes some images captured in the same manner as those in the test set.

Improving topological cluster reconstruction using calorimeter cell timing in ATLAS

Clusters of topologically connected calorimeter cells around cells with large absolute signal-to-noise ratio (topo-clusters) are the basis for calorimeter signal reconstruction in the ATLAS experiment. Topological cell clustering has proven performant in LHC Runs 1 and 2. It is, however, susceptible to out-of-time pile-up of signals from soft collisions outside the 25 ns proton-bunch-crossing window associated with the event’s hard collision. To reduce this effect, a calorimeter-cell timing criterion was added to the signal-to-noise ratio requirement in the clustering algorithm. Multiple versions of this criterion were tested by reconstructing hadronic signals in simulated events and Run 2 ATLAS data. The preferred version is found to reduce the out-of-time pile-up jet multiplicity by ∼50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\sim }50\\%$$\\end{document} for jet pT∼20\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p_{\ extrm{T}}\\sim 20$$\\end{document} GeV and by ∼80%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\sim }80\\%$$\\end{document} for jet pT≳50\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p_{\ extrm{T}} \\gtrsim 50$$\\end{document} GeV, while not disrupting the reconstruction of hadronic signals of interest, and improving the jet energy resolution by up to 5% for 20<pT<30\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$20< p_{\ extrm{T}} < 30$$\\end{document} GeV. Pile-up is also suppressed for other physics objects based on topo-clusters (electrons, photons, τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au $$\\end{document}-leptons), reducing the overall event size on disk by about 6%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$6\\%$$\\end{document} in early Run 3 pile-up conditions. Offline reconstruction for Run 3 includes the timing requirement.

Abstract PO2-28-12: Rapid diagnosis of breast biopsies with open-top light-sheet microscopy

Abstract Introduction: Breast cancer is typically diagnosed through a diagnostic work-up that involves specialized breast imaging, image-guided biopsy, and pathological assessment. Pathology results require 2 to 7 business days before a diagnosis is rendered, creating anxiety in women presenting with a breast abnormality. Decreasing pathology evaluation lead-time has the potential to reduce anxiety, streamline patient care, and reduce heathcare costs. In this pilot study, we evaluated the potential of open-top light-sheet microscopy to deliver a preliminary breast pathology diagnosis within 30 minutes of biopsy. Methods: Fresh 14-gauge breast biopsies (N=40) in normal saline were received directly from the breast imaging clinic and immediately stained using the nuclear marker SYBR Gold (Invitrogen) and pan-protein marker Atto 655 NHS Ester (Sigma) prepared in dimethyl sulfoxide, washed, and cleared for imaging at a refractive index of 1.46 using 2,2’-Thiodiethanol (Sigma). The full process requires approximately 14 minutes for staining and clearing. After staining, we placed the biopsy in an in-house-built specimen holder and imaged a 100 micron cross section along the full length of the biopsy using our custom open-top light-sheet microscope. Images were subsequently converted computationally to a standard H&amp;E color format using Fiji and Aivia (Leica) software and were ready for evaluation by a pathologist the same day they were collected. mages were assessed by two pathologists with subspecialization in breast pathology for a two-category diagnosis: benign or atypical. After imaging, the biopsy was frozen, a frozen section was cut, and an H&amp;E-stained slide was produced. Results: Using the protocol above, we demonstrated the ability to stain, clear, image, and visualize needle core biopsies within 30 minutes of receiving the tissue sample. Processing and converting the data to an H&amp;E color palette required additional time, surpassing the 30-minute turnaround time goal. The images contained readily identifiable stroma, epithelial cells, immune cells, and duct structures to a depth of 100 microns. 29/40 biopsies yielded interpretable results. 11/40 had insufficient staining, clearing, or imaging quality for diagnosis. The number of non-diagnostic images improved in the second half of the study (5%) compared to the first half of the study (50%) with sample prep and imaging optimization. Agreement between the two breast pathologists on classifying the biopsies as benign vs. atypical was 89.7%. Discussion: We describe a novel method to obtain a microscopic image of breast core biopsy specimens to facilitate preliminary diagnosis within 30 minutes of receipt of tissue. The quality of the images produced by the method shows promise for preliminary diagnosis, especially after protocol optimization for the second half of the study. Additional optimization is needed in data processing to meet the 30-minute turnaround time requirement. This optimization can be achieved by parallelization of the data processing on a cluster or cloud, which is currently under investigation by our team. Citation Format: Brandy Olin Pope, Rebeca Alvarez, Charles Childers, Suzanne Dintzis, Sarah Javid, Nicholas Reder, Habib Rahbar. Rapid diagnosis of breast biopsies with open-top light-sheet microscopy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-28-12.

DEVELOPING COMPETENT MANAGERS THROUGH PEDAGOGIC PRACTICES- A CONTRADICTION ANALYSIS FOR B-SCHOOLS OF NORTHEAST INDIA

With the rising demand for a “competent workforce” in the 21st-century business environment, Workplace learning is the centre stage of higher learning curriculum, which nobody can deny. In this direction management education plays its role as a path-leader. To nurture and prepare future managers for the changing requirements of the business world Bilimoria (2000), B-Schools can play a pivotal role. A plethora of research established on the issue of the “curriculum gap” to equip learners with the identified and relevant workplace competencies. Management education imparted by the B-schools and universities must deliver the most relevant workplace competencies.It is very important that the present educational system broadens its scope and equips future graduates with the latest and relevant competencies as per the demand of the industry. Does it so in reality and practice? In the global arena of management education, Indian B-schools are not resistant to the pressures of the recent times requirements of the industries. To meet the interests of society, industry, government, and the global community in general, Indian business schools must reinvent their management education to ensure its relevance over time. The present study is an effort to delve into associating workplace competencies most desired by industry with relevant standard pedagogic practices and comprehend how they differ from each other, based on the students and faculty of the select B-schools who perceive the source of workplace competencies through the various educational practices by the Russel and Rao Proximity Analysis.

HISOL: High-energy soliton dynamics enable ultrafast far-ultraviolet laser sources

Ultrafast laser sources in the far ultraviolet (100–300 nm) have been the subject of intense experimental efforts for several decades, driven primarily by the requirements of advanced experiments in ultrafast science. Resonant dispersive wave emission from high-energy laser pulses undergoing soliton self-compression in a gas-filled hollow capillary fiber promises to meet several of these requirements for the first time, most importantly by combining wide-ranging wavelength tuneability with the generation of extremely short pulses. In this Perspective, we give an overview of this approach to ultrafast far-ultraviolet sources, including its historical origin and underlying physical mechanism, the state of the art and current challenges, and our view of potential applications both within and beyond ultrafast science.