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Significance: Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging). Aim: This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs. Approach: Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended. Conclusion: Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

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The Hi-C method has emerged as an indispensable tool for analyzing the 3D organization of the genome, becoming increasingly accessible and frequently utilized in chromatin research. To effectively leverage 3D genomics data obtained through advanced technologies, it is crucial to understand what processes are undertaken and what aspects require special attention within the bioinformatics pipeline. This protocol aims to demystify the Hi-C data analysis process for field newcomers. In a step-by-step manner, we describe how to process Hi-C data, from the initial sequencing of the Hi-C library to the final visualization of Hi-C contact data as heatmaps. Each step of the analysis is clearly explained to ensure an understanding of the procedures and their objectives. By the end of this chapter, readers will be equipped with the knowledge to transform raw Hi-C reads into informative visual representations, facilitating a deeper comprehension of the spatial genomic structures critical to cellular functions.

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Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.

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Six luminescent europium organic complexes have been synthesized and studied for their luminescent properties. The synthesized complexes were analyzed through elemental analysis, XRD, SEM, EDAX, FT-IR, NMR and thermogravimetry. The complexes exhibit crystalline behavior and possess decent thermal stability. Photoluminescence study on complexes were conducted in both solid and solution states, the results indicate the characteristic red emission. With the addition of ancillary ligands, water molecules are replaced from inner coordination sphere, leading to enhanced luminescence properties. The colorimetric parameters (CIE, CP%, CCT, u', v') suggest aptness of these complexes in red light illuminating OLEDs. The J-O parameters were calculated experimentally and theoretically with the help of LUMPAC software. Theoretical and experimental results agree well reflecting the efficacy of the outcomes. As a result of red emission, these complexes could have interesting photonics applications. The biological studies indicate the probable use of these complexes in the medical industry.

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The advent of 3D printing technology has emerged as a key technical revolution in recent years, enabling the development and production of innovative medication delivery methods in the pharmaceutical sector. The designs, concepts, techniques, key challenges, and potential benefits during 3D-printing technology are the key points discussed in this review. This technology primarily enables rapid, safe, and low-cost development of pharmaceutical formulations during the conventional and additive manufacturing processes. This phenomenon has wide-ranging implications in current as well as future medicinal developments. Advanced technologies such as Ink-Jet printing, drop-on-demand printing, Zip dose, Electrohydrodynamic Printing (Ejet) etc., are the current focus of the drug delivery systems for enhancing patient convenience and improving medication compliance. The current and future applications of various software, such as CAD software, and regulatory aspects in 3D and 4D printing technology are discussed briefly in this article. With respect to the prospective trajectory of 3D and 4D printing, it is probable that the newly developed methods will be predominantly utilized in pharmacies and hospitals to accommodate the unique requirements of individuals or niche groups. As a result, it is imperative that these technologies continue to advance and be improved in comparison to 2D printing in order to surmount the aforementioned regulatory and technical obstacles, render them applicable to a vast array of drug delivery systems, and increase their acceptability among patients of every generation.

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BACKGROUND: The neurovascular conflict (NVC) at the brainstem exit zone of the facial nerve is considered the primary etiology of primary hemifacial spasm (HFS). Therefore, microvascular decompression (MVD) has become the preferred treatment for HFS. Successful neurovascular decompression can achieve significant therapeutic effects, and accurately identifying the site of compression is crucial for the success of this surgery. Detailed diagnostic neuroimaging plays an important role in accurately identifying the site of compression.The purpose of this study is to explore the feasibility and predictive value of preoperative visualization assessment of the neurovascular relationship in HFS using 3D Slicer software based on multimodal imaging fusion. This aims to reduce the omission of responsible vessels and lower the incidence of postoperative complications, thereby potentially improving the efficacy and safety of the surgery. METHODS: This study retrospectively analyzed 80 patients with HFS who underwent MVD surgery. All patients underwent preoperative cranial MRI scans, including the 3D-FIESTA and the 3D-TOF MRA sequences. Three-dimensional models were reconstructed from the multimodal MRI images using 3D Slicer software. Independent observers, who were blinded to the surgical outcomes, evaluated the neurovascular relationships using both the three-dimensional models and multimodal MRI images. The assessment results were compared with intraoperative findings, and statistical analysis was conducted using SPSS 22.0 software. RESULTS: The agreement between preoperative assessment using the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence and intraoperative findings was represented by a Kappa value of 0.343, while the Kappa value for agreement between three-dimensional reconstruction and intraoperative findings was 0.637. There was a statistically significant difference between the two methods ( X2 = 18.852, P = 0.001 ). The sensitivity and specificity of the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence for evaluating neurovascular relationships were 92.4% and 100%, respectively, while for three-dimensional reconstruction, both were 100%. The Kappa value for agreement between preoperative the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence prediction of offending vessels and intraoperative findings was 0.625, while the Kappa value for agreement between three-dimensional reconstruction and intraoperative findings was 0.938, showing a statistically significant difference ( X2 = 317.798, P = 0.000 ). The Kappa value for agreement between preoperative the 3D-TOF MRA sequence combined with the 3D-FIESTA sequence assessment of the anatomical location of facial nerve involvement in neurovascular compression and intraoperative findings was 0.608, while the Kappa value for agreement between three-dimensional reconstruction and intraoperative findings was 0.918, also showing a statistically significant difference ( X2 = 504.647, P = 0.000 ). CONCLUSIONS: The preoperative visualization assessment of neurovascular relationships in HFS using 3D Slicer software based on multimodal imaging fusion has been demonstrated to be reliable. It is more accurate than combining the 3D-TOF MRA sequence with the 3D-FIESTA sequence and shows higher consistency with intraoperative findings. This method provides guidance for surgical procedures and thereby potentially enhances the efficacy and safety of surgeries to a certain extent.

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BACKGROUND: Stereotactic arrhythmia radioablation (STAR) is a therapeutic option for ventricular tachycardia (VT) where catheter-based ablation is not feasible or has previously failed. Target definition and its transfer from electro-anatomic maps (EAM) to radiotherapy treatment planning systems (TPS) is challenging and operator-dependent. Software solutions have been developed to register EAM with cardiac CT and semi-automatically transfer 2D target surface data into 3D CT volume coordinates. Results of a cross-validation study of two conceptually different software solutions using data from the RAVENTA trial (NCT03867747) are reported. METHODS: Clinical Target Volumes (CTVs) were created from target regions delineated on EAM using two conceptually different approaches by separate investigators on data of 10 patients, blinded to each other's results. Targets were transferred using 3D-3D registration and 2D-3D registration, respectively. The resulting CTVs were compared in a core-lab using two complementary analysis software packages for structure similarity and geometric characteristics. RESULTS: Volumes and surface areas of the CTVs created by both methods were comparable: 14.88 ± 11.72 ml versus 15.15 ± 11.35 ml and 44.29 ± 33.63 cm2 versus 46.43 ± 35.13 cm2. The Dice-coefficient was 0.84 ± 0.04; median surface-distance and Hausdorff-distance were 0.53 ± 0.37 mm and 6.91 ± 2.26 mm, respectively. The 3D-center-of-mass difference was 3.62 ± 0.99 mm. Geometrical volume similarity was 0.94 ± 0.05 %. CONCLUSION: The STAR targets transferred from EAM to TPS using both software solutions resulted in nearly identical 3D structures. Both solutions can be used for QA (quality assurance) and EAM-to-TPS transfer of STAR-targets. Semi-automated methods could potentially help to avoid mistargeting in STAR and offer standardized workflows for methodically harmonized treatments.

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Smart security devices, such as smart locks, smart cameras, and smart intruder alarms are increasingly popular with users due to the enhanced convenience and new features that they offer. A significant part of this convenience is provided by the device's companion smartphone app. Information on whether secure and ethical development practices have been used in the creation of these applications is unavailable to the end user. As this work shows, this means that users are impacted both by potential third-party attackers that aim to compromise their device, and more subtle threats introduced by developers, who may track their use of their devices and illegally collect data that violate users' privacy. Our results suggest that users of every application tested are susceptible to at least one potential commonly found vulnerability regardless of whether their device is offered by a known brand name or a lesser-known manufacturer. We present an overview of the most common vulnerabilities found in the scanned code and discuss the shortcomings of state-of-the-art automated scanners when looking at less structured programming languages such as C and C++. Finally, we also discuss potential methods for mitigation, and provide recommendations for developers to follow with respect to secure coding practices.

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The calibration industry is renowned for its diverse and sophisticated equipment and complex processes, which necessitate innovative solutions to keep pace with rapidly advancing technology. This paper introduces an enhancement to an existing microservice-based cloud architecture, aimed at effectively managing the inherent complexity within this field. The enhanced architecture seamlessly integrates various equipment types and communication technologies, aligning diverse stakeholder expectations into a unified system that ensures efficient and accurate calibration processes. It highlights the integration of microservices to facilitate various methods of uncertainty calculation and the generation of digital calibration certificates (DCCs). A case study on RF power measurement illustrates the practical application and benefits of the enhanced architecture. Although initially focused on RF power measurement, the flexible architecture allows for future expansions to accommodate new standards and measurement techniques. The enhanced system offers a comprehensive approach to managing data flow from calibration equipment to the final generation of DCCs, utilizing cloud-based services for efficient data processing. As a future direction, this extension sets the groundwork for broader applicability across multiple measurement types, ensuring readiness for upcoming advancements in metrology.

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The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter-receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios. It is still unclear, however, how the CFO detection capability would hold up in more dynamic time-varying channels where there is a higher mobility. This paper experimentally demonstrates the identification accuracy of CFO for wireless devices in time-varying channels. To this end, a software-defined radio (SDR) testbed is deployed to collect CFO values in real environments, where real transmission and reception are conducted in a vehicular setup. The collected CFO values are used to train machine-learning (ML) classifiers to be used for device identification. While CFO exhibits good detection performance (97% accuracy) for low-mobility scenarios, it is found that higher mobility (35 miles/h) degrades (72% accuracy) the effectiveness of CFO in distinguishing between legitimate and non-legitimate transmitters. This is due to the impact of the time-varying channel on the quality of the exchanged pilot signals used for CFO detection at the receivers.

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The analysis of utilising unmanned aerial vehicles (UAVs) to form flying networks in obstacle conditions and various algorithms for obstacle avoidance is conducted. A planning scheme for deploying a flying LiFi network based on UAVs in a production facility with obstacles is developed and described. Such networks are necessary to ensure reliable data transmission from sensors or other sources of information located in dangerous or hard-to-reach places to the crisis centre. Based on the planning scheme, the following stages are described: (1) laying the LiFi signal propagation route in conditions of interference, (2) placement of the UAV at the specified points of the laid route for the deployment of the LiFi network, and (3) ensuring the reliability of the deployed LiFi network. Strategies for deploying UAVs from a stationary depot to form a flying LiFi network in a room with obstacles are considered, namely the strategy of the first point for the route, the strategy of radial movement, and the strategy of the middle point for the route. Methods for ensuring the uninterrupted functioning of the flying LiFi network with the required level of reliability within a given time are developed and discussed. To implement the planning stages for deploying the UAV flying LiFi network in a production facility with obstacles, the "Simulation Way" and "Reliability Level" software tools are developed and described. Examples of utilising the proposed software tools are given.

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Software-Defined Networking (SDN) has revolutionized network management by providing unprecedented flexibility, control, and efficiency. However, its centralized architecture introduces critical security vulnerabilities. This paper introduces a novel approach to securing SDN environments using IOTA 2.0 smart contracts. The proposed system utilizes the IOTA Tangle, a directed acyclic graph (DAG) structure, to improve scalability and efficiency while eliminating transaction fees and reducing energy consumption. We introduce three smart contracts: Authority, Access Control, and DoS Detector, to ensure trusted and secure network operations, prevent unauthorized access, maintain the integrity of control data, and mitigate denial-of-service attacks. Through comprehensive simulations using Mininet and the ShimmerEVM IOTA Test Network, we demonstrate the efficacy of our approach in enhancing SDN security. Our findings highlight the potential of IOTA 2.0 smart contracts to provide a robust, decentralized solution for securing SDN environments, paving the way for the further integration of blockchain technologies in network management.

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A well can be produced and exploited when it has production power, in other words, if the well does not have enough pressure, it will not be able to flow. Artificial production is a method to increase the lifespan of well production. The well studied in this article has a significant annual lower pressure drop; So now with the current pressure of the existing well, it is not possible to send the oil of this well to the separator of the first stage of the exploitation unit. Among the existing solutions to maintain or increase production and increase the flow pressure of the well, is the use of artificial extraction. In this article, an attempt has been made to simulate the effect of using a core pipe, gas pumping and installing an electric submersible pump (ESP) on the production flow rate and flow pressure of the well by using the well data and the static and current pressure test. The current production data with the PIPESIM software was checked, and then the best extraction method for the studied well. Finally, the installation of an ESP was determined and selected as the best method of artificial extraction.

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The dataset in this paper explains the functional requirements in the form of Business Process Modelling Notation (BPMN) diagrams from three software applications: employee cooperative, store, and mini hospital. Data were collected from clients or owners of software in three business software projects developed by development teams (including the authors) through requirements elicitation activities. The functional requirements are presented as a BPMN diagram. There are 67 data objects, each presenting a single functional requirement or process. Apart from being presented in diagram form, the BPMN diagram of the functional requirements is also provided in the form of an XML Process Definition Language (XPDL) file, making it possible for users of this dataset to export it using business process management platform tools. Due to the rarity of functional requirements presented in the form of BPMN diagrams for research and education, this dataset plays an important role in research and education in the fields of requirements engineering, software engineering, software metrics, business process modelling, and other relevant fields.

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This study presents a detailed methodology for integrating three-dimensional (3D) printing technology into preoperative planning in neurosurgery. The increasing capabilities of 3D printing over the last decade have made it a valuable tool in medical fields such as orthopedics and dental practices. Neurosurgery can similarly benefit from these advancements, though the creation of accurate 3D models poses a significant challenge due to the technical expertise required and the cost of specialized software. This paper demonstrates a step-by-step process for developing a 3D physical model for preoperative planning using free, open-source software. A case involving a 62-year-old male with a large infiltrating tumor in the sacrum, originating from renal cell carcinoma, is used to illustrate the method. The process begins with the acquisition of a CT scan, followed by image reconstruction using InVesalius 3, an open-source software. The resulting 3D model is then processed in Autodesk Meshmixer (Autodesk, Inc., San Francisco, CA), where individual anatomical structures are segmented and prepared for printing. The model is printed using the Bambu Lab X1 Carbon 3D printer (Bambu Lab, Austin, TX), allowing for multicolor differentiation of structures such as bones, tumors, and blood vessels. The study highlights the practical aspects of model creation, including artifact removal, surface separation, and optimization for print volume. It discusses the advantages of multicolor printing for visual clarity in surgical planning and compares it with monochromatic and segmented printing approaches. The findings underscore the potential of 3D printing to enhance surgical precision and planning, providing a replicable protocol that leverages accessible technology. This work supports the broader adoption of 3D printing in neurosurgery, emphasizing the importance of collaboration between medical and engineering professionals to maximize the utility of these models in clinical practice.

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BACKGROUND: Precise preoperative radiological evaluation of aural atresia is of utmost importance for surgical planning. Until now, multislice computed tomography (MSCT) has been used but it cannot adequately visualize small structures such as the stapes. Flat-panel volume CT (fpVCT) with its secondary reconstructions (fpVCTSECO) offers a high-resolution visualization of the middle ear. New otosurgical planning software also enables detailed 3D reconstruction of the middle ear anatomy. AIM OF THE WORK: Evaluation of the use of fpVCTSECO in combination with an otosurgical planning software for a more accurate diagnosis and treatment of congenital aural atresia. MATERIAL AND METHODS: Seven patients with congenital aural atresia underwent preoperative MSCT (600 µm slice thickness) and corresponding fpVCT (466 µm slice thickness). In addition, fpVCTSECO (99 µm slice thickness) were reconstructed. The Jahrsdoerfer and Siegert grading scores were determined and their applicability in the abovementioned imaging modalities was evaluated. In addition, the malleus incus complex was analyzed in 3D rendering. RESULTS: Imaging with fpVCTSECO enabled reliable visualization of the abnormalities, in particular the ossicular chain. A significant difference in the Siegert grading score was found. In addition, the malleus-incus complex could be visualized better in 3D. DISCUSSION: The introduction of new imaging techniques and surgical planning techniques into the diagnostic concept of aural atresia facilitates the identification of malformed anatomy and enables systematic analysis. This combination can also help to more accurately classify the pathology and thus increase the safety and success of the surgical procedure.

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To evaluate our two non-machine learning (non-ML)-based algorithmic approaches for detecting early ischemic infarcts on brain CT images of patients with acute ischemic stroke symptoms, tailored to our local population, to be incorporated in our telestroke software. One-hundred and thirteen acute stroke patients, excluding hemorrhagic, subacute, and chronic patients, with accessible brain CT images were divided into calibration and test sets. The gold standard was determined through consensus among three neuroradiologist. Four neuroradiologist independently reported Alberta Stroke Program Early CT Scores (ASPECTSs). ASPECTSs were also obtained using a commercial ML solution (CMLS), and our two methods, namely the Mean Hounsfield Unit (HU) relative difference (RELDIF) and the density distribution equivalence test (DDET), which used statistical analyze the of the HUs of each region and its contralateral side. Automated segmentation was perfect for cortical regions, while minimal adjustment was required for basal ganglia regions. For dichotomized-ASPECTSs (ASPECTS < 6) in the test set, the area under the receiver operating characteristic curve (AUC) was 0.85 for the DDET method, 0.84 for the RELDIF approach, 0.64 for the CMLS, and ranged from 0.71-0.89 for the neuroradiologist. The accuracy was 0.85 for the DDET method, 0.88 for the RELDIF approach, and was ranged from 0.83 - 0.96 for the neuroradiologist. Equivalence at a margin of 5% was documented among the DDET, RELDIF, and gold standard on mean ASPECTSs. Noninferiority tests of the AUC and accuracy of infarct detection revealed similarities between both DDET and RELDIF, and the CMLS, and with at least one neuroradiologist. The alignment of our methods with the evaluations of neuroradiologist and the CMLS indicates the potential of our methods to serve as supportive tools in clinical settings, facilitating prompt and accurate stroke diagnosis, especially in health care settings, such as Colombia, where neuroradiologist are limited.

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BACKGROUND: The HHUS market is very complex due to a multitude of equipment variants and several different device manufacturers. Only a few studies have compared different HHUS devices under clinical conditions. We conducted a comprehensive prospective observer study with a direct comparison of nine different HHUS devices in terms of B-scan quality, device handling, and software features under abdominal imaging conditions. METHODS: Nine different HHUS devices (Butterfly iQ+, Clarius C3HD3, D5CL Microvue, Philips Lumify, SonoEye Chison, SonoSite iViz, Mindray TE Air, GE Vscan Air, and Youkey Q7) were used in a prospective setting by a total of 12 experienced examiners on the same subjects in each case and then assessed using a detailed questionnaire regarding B-scan quality, handling, and usability of the software. The evaluation was carried out using a point scale (5 points: very good; 1 point: insufficient). RESULTS: In the overall evaluation, Vscan Air and SonoEye Chison achieved the best ratings. They achieved nominal ratings between "good" (4 points) and "very good" (5 points). Both devices differed significantly (p < 0.01) from the other seven devices tested. Among the HHUS devices, Clarius C3HD3 and Vscan Air achieved the best results for B-mode quality, D5CL Microvue achieved the best results for device handling, and SonoEye Chison and Vscan Air achieved the best results for software. CONCLUSIONS: This is the first comprehensive study to directly compare different HHUS devices in a head-to-head manner. While the majority of the tested devices demonstrated satisfactory performance, notable discrepancies were observed between them. In particular, the B-scan quality exhibited considerable variation, which may have implications for the clinical application of HHUS. The findings of this study can assist in the selection of an appropriate HHUS device for specific applications, considering the clinical objectives and acknowledging the inherent limitations.

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One of the aims of population genetics is to identify genetic differences/similarities among individuals of multiple ancestries. Many approaches including principal component analysis, clustering, and maximum likelihood techniques can be used to assign individuals to a given ancestry based on their genetic makeup. Although there are several tools that implement such algorithms, there is a lack of interactive visual platforms to run a variety of algorithms in one place. Therefore, we developed PopMLvis, a platform that offers an interactive environment to visualize genetic similarity data using several algorithms, and generate figures that can be easily integrated into scientific articles.

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The developments in conversational AI raised urgent questions about the future direction of many aspects of society, including computing education. The first reactions to the fast-paced evolution of conversational agents were varied: Some announced "the end of programming," while others considered this "premature obituary of programming." Some adopted a defensive approach to detecting the use of conversational AI and avoiding an increase in plagiarism, while others questioned, "So what if ChatGPT wrote it?" Nevertheless, questions arise about whether computing education in its current form will still be relevant and fit for purpose in the era of conversational AI. Recognizing these diverse reactions to the advent of conversational AI, this paper aims to contribute to the ongoing discourse by exploring the current state through three perspectives in a dedicated literature review: adoption of conversational AI in (1) software engineering education specifically and (2) computing education in general, and (3) a comparison with software engineering practice. Our results show a gap between software engineering practice and higher education in the pace of adoption and the areas of use and generally identify preliminary research on student experience, teaching, and learning tools for software engineering.