Short Processing Time Research Articles

Queue Configurations and Operational Performance: An Interplay Between Customer Ownership and Queue Length Awareness

Problem definition: Contrary to traditional queueing theory, recent field studies in B2C services indicate that pooled queues may be less efficient than dedicated queues. Methodology/results: We use two online experiments in the healthcare delivery context to replicate this finding and assess the interplay of servers’ customer ownership and queue length awareness as potential underlying mechanisms. We operationalize customer ownership as the extent to which servers feel ownership toward their customers and queue length awareness as the extent to which servers are able to accurately quantify their number of customers. We find that, following a change in queue configuration, dedicated queues outperform pooled queues with respect to processing speed without sacrificing quality. The reduction in speed is partially mediated by the servers’ queue length awareness and partially suppressed by their ownership of customers in queue. The former is because servers turn out to be less likely to underestimate their load, which makes them work faster. The latter is because ownership of customers in queue may distract servers from the customer in service. When the queue configuration changes from a dedicated to a pooled one, the shorter processing times and higher levels of queue length awareness persist across the change, unlike the higher ownership of customers in the queue. Managerial implications: In discretionary service settings, switching to a dedicated queue is often beneficial in terms of operational performance, partly because the increased queue length awareness motivates servers to work faster; however, the increased degree of customer ownership of those in queue may distract them and result in a slowdown. Funding: This work was supported by the Wharton Behavioral Lab, the Claude Marion Endowed Faculty Scholar Award, the Wharton-INSEAD Alliance, and the Wharton Dean’s Research Fund. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.0202 .

Technologies to decontaminate aflatoxins in foods: a review

SummaryAflatoxins are toxic secondary metabolites produced by Aspergillus spp., found in staple food commodities. Aflatoxins are carcinogenic, teratogenic, and mutagenic and pose a serious threat to the health of humans. The identification and quantification of aflatoxins in foods is a major challenge to guarantee food safety. Therefore, developing feasible, sensitive, and robust methods for decontamination is paramount, with short processing time and negligible impact on quality. This review evaluates recent novel technologies for aflatoxins decontamination by physical methods (microwave heating, Gama and electron beam irradiation, pulse light and ultraviolet), chemical methods (ozone, natural plant extracts, and organic acids), and biological methods (atoxigenic Aspergillus strains, Trichoderma spp., and bacteria and yeast). The study highlights on the cutting‐edge technologies of smart packaging and artificial intelligence (AI). To achieve more efficiency and adaptability to different food matrices in aflatoxins decontamination, the study suggests integrating multiple strategies. The study also recommends integrating Partnership for Delivery (P4D) to share the responsibility to increase the chance for success and control aflatoxins in foods.

Neural quantile optimization for edge–cloud networking

We seek the best traffic allocation scheme for the edge–cloud networking subject to SD-WAN architecture and burstable billing. First, we formulate a family of quantile-based integer programming problems for a fixed network topology with random parameters describing the traffic demands. Then, to overcome the difficulty caused by the discrete feature, we generalize the Gumbel-softmax reparameterization method to induce an unconstrained continuous optimization problem as a regularized continuation of the discrete problem. Finally, we introduce the Gumbel-softmax sampling neural network to solve optimization problems via unsupervised learning. The neural network structure reflects the edge–cloud networking topology and is trained to minimize the expectation of the cost function for unconstrained continuous optimization problems. The trained network works as an efficient traffic allocation scheme sampler, outperforming the random strategy in feasibility and cost value. Besides testing the quality of the output allocation scheme, we examine the generalization property of the network by increasing the time steps and the number of users. We also feed the solution to existing integer optimization solvers as initial conditions and verify the warm-starts can accelerate the short-time iteration process. The framework is general, and the decoupled feature of the random neural networks is adequate for practical implementations.

Continuous flow high-pressure homogenization for preserving the nutritional quality and stability of watermelon juice under simulated market storage conditions

This study examined the efficacy of continuous flow high-pressure homogenization (CFHPH) under varying pressures, inlet temperatures, and flow rates, in preserving the nutritional quality and stability of watermelon juice during simulated market conditions and compared it with traditional high-temperature short-time (HTST) processing. The retention of ascorbic acid, carotenoids, and amino acids was analyzed using liquid chromatography, while PPO (polyphenol oxidase) and POD (peroxidase) enzyme activity was assessed using a UV–vis spectrophotometer.We observed a significant decrease (p ≤ 0.05) in ascorbic acid levels after 15 days of storage. For carotenoids, the impact was influenced by the interaction of pressure, flow rate, and inlet temperature within CFHPH, with no clear trend emerging regarding their preservation over 45 days of storage at 4 °C. However, overall retention of carotenoids surpassed that of HTST samples. Both methods enhanced free amino acid contents significantly and decreased PPO and POD activity, with HTST being slightly more effective. Ornithine and histidine concentrations significantly increased, with up to a fourfold rise in samples treated with 300 MPa pressure and up to a tenfold rise for HTST at 95 °C after 45 days of storage. This study suggests optimizing the CFHPH process to enhance the shelf-life and nutritional value of watermelon juice, offering consumers a healthier and longer-lasting choice. Industrial relevanceOur findings highlight CFHPH's higher retention of bioactive compounds, reduction in degradative enzyme activity, and enhancement of the amino acid profile, making it a compelling choice for the fruit juice processing industry. Despite the energy-intensive nature of CFHPH, its ability to preserve vital bioactive compounds like carotenoids and ascorbic acid addresses the growing consumer demand for nutritious and stable juice options. The benefits of CFHPH in maintaining juice quality and nutritional value may outweigh the associated energy costs, making it a promising technology for fruit juice processing.

Accuracy and time efficiency of a novel deep learning algorithm for Intracranial Hemorrhage detection in CT Scans

PurposeTo evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).Materials and methodsThis retrospective study was conducted using a prototype algorithm that evaluated 502 NCCT head scans with ICH in context of TBI.Four board-certified radiologists evaluated in consensus the CT scans to establish the standard of reference for hemorrhage presence and type of ICH. Consequently, all CT scans were independently analyzed by the algorithm and a board-certified radiologist to assess the presence and type of ICH. Additionally, the time to diagnosis was measured for both methods.ResultsA total of 405/502 patients presented ICH classified in the following types: intraparenchymal (n = 172); intraventricular (n = 26); subarachnoid (n = 163); subdural (n = 178); and epidural (n = 15). The algorithm showed high diagnostic accuracy (91.24%) for the assessment of ICH with a sensitivity of 90.37% and specificity of 94.85%. To distinguish the different ICH types, the algorithm had a sensitivity of 93.47% and a specificity of 99.79%, with an accuracy of 98.54%. To detect midline shift, the algorithm had a sensitivity of 100%. In terms of processing time, the algorithm was significantly faster compared to the radiologist’s time to first diagnosis (15.37 ± 1.85 vs 277 ± 14 s, p < 0.001).ConclusionA novel deep learning algorithm can provide high diagnostic accuracy for the identification and classification of ICH from unenhanced CT scans, combined with short processing times. This has the potential to assist and improve radiologists’ ICH assessment in NCCT scans, especially in emergency scenarios, when time efficiency is needed.

The Impact of Thermal Treatment Intensity on Proteins, Fatty Acids, Macro/Micro-Nutrients, Flavor, and Heating Markers of Milk-A Comprehensive Review.

Milk thermal treatment, such as pasteurization, high-temperature short-time processing, and the emerging ultra-short-time processing (<0.5 s), are crucial for ensuring milk safety and extending its shelf life. Milk is a nutritive food matrix with various macro/micro-nutrients and other constituents that are possibly affected by thermal treatment for reasons associated with processing strength. Therefore, understanding the relationship between heating strength and milk quality is vital for the dairy industry. This review summarizes the impact of thermal treatment strength on milk's nutritional and sensory properties, the synthesizing of the structural integrity and bioavailability of milk proteins, the profile and stability of fatty acids, the retention of macro/micro-nutrients, as well as the overall flavor profile. Additionally, it examines the formation of heat-induced markers, such as Maillard reaction products, lactulose, furosine, and alkaline phosphatase activity, which serve as indicators of heating intensity. Flavor and heating markers are commonly used to assess the quality of pasteurized milk. By examining former studies, we conclude that ultra-short-time-processing-treated milk is comparable to pasteurized milk in terms of specific parameters (such as whey protein behavior, furosine, and ALP contents). This review aims to better summarize how thermal treatments influence the milk matrix, guiding the dairy industry's development and balancing milk products' safety and nutritional value.

Pulsed Electric Fields Effects on Proteins: Extraction, Structural Modification, and Enhancing Enzymatic Activity.

Pulsed electric field (PEF) is an innovative physical method for food processing characterized by low energy consumption and short processing time. This technology represents a sustainable procedure to extend food shelf-life, enhance mass transfer, or modify food structure. The main mechanism of action of PEF for food processing is the increment of the permeability of the cell membranes by electroporation. However, it has also been shown that PEF may modify the technological and functional properties of proteins. Generating a high-intensity electric field necessitates the flow of an electric current that may have side effects such as electrochemical reactions and temperature increments due to the Joule effect that may affect food components such as proteins. This article presents a critical review of the knowledge on the extraction of proteins assisted by PEF and the impact of these treatments on protein composition, structure, and functionality. The required research for understanding what happens to a protein when it is under the action of a high-intensity electric field and to know if the mechanism of action of PEF on proteins is different from thermal or electrochemical effects is underlying.

Optimasi Penjadwalan Mesin Bor Manual pada Produksi Side Chair Menggunakan Metode Shortest Processing Time (SPT)

CV Mandiri Abadi is a manufacturing industry that operates on a make-to-order system, specifically for side chair products, necessitating a carefully considered scheduling system. Issues with the use of manual drilling machines causing delays in component deliveries to the warehouse prompted an evaluation of optimal production scheduling using the shortest processing time (SPT) method. This study includes detailed calculations to determine average completion time, utilization, average job time, and average job delay. Analysis results show that using manual drilling machines achieved an average completion time of 854.28 minutes, a proposed utilization improvement of 28%, an average job time of 3.46 minutes, and an average delay of 614.14 minutes. This approach is more effective in optimizing processing time and reducing delivery delays. Therefore, the use of the shortest processing time (SPT) method is recommended to improve production performance within the company.

Accurate and rapid mercury susceptibility detection in aquatic samples using fluorescent probe integrated rhodamine with pyridyl isothiocyanate

Mercury, one of the various harmful metals, is particularly significant in affecting aquatic organisms, currently gaining more attentions and sparking discussions. In response to the limitations of traditional detections, fluorescent probes have emerged as a promising solution with some advantages, such as weaker background interference, shorter processing time, higher accuracy. Thus, a novel fluorescent probe, FS-Hg-1, has been developed for assessing mercury ion (Hg2+) concentrations in aquatic products. This probe displays specific recognition of mercury ions in fluorescence spectra. Notably, FS-Hg-1 exhibits a distinct color change to pink when combined with Hg2+ (with a 948-fold increase in absorption at 568 nm) and a substantial fluorescence change towards Hg2+ (361-fold increase, excitation at 562 nm, emission at 594 nm) in N, N-dimethylformamide. The probe boasts a detection limit of 0.14 μM and rapid reaction with Hg2+ within 10 s, showing an excellent linear correlation with [Hg2+] in the range of 0 to 10 μM. Through thorough analysis using FS-Hg-1, the results align with those from the standard method (P > 0.05), with spiked recovery rates ranging from 108.4% to 113.2%. With its precise recognition, low detection limit, and remarkable sensitivity, this fluorescent assay proves effective in mercury concentration determination in aquatic samples without interference. The potential of FS-Hg-1 is promising for speedy detection of residual Hg2+ and holds significance in ensuring food safety.

Impact of ohmic heating extraction on the bioactive components of parsley: comparison with conventional and green extraction techniques

The extraction process is an important step that is widely used in food, agriculture, cosmetics, pharmaceuticals, modern and alternative medicine, etc. Because of plants contain low amount of beneficial phytochemicals, obtaining high amounts of the desired compound is important in terms of extraction efficiency. In recent years, modern and green technologies have become more important; they also bring advantages such as high selectivity, less solvent, time, and energy requirements. Apigenin (4′, 5, 7-trihydroxyflavone), a naturally occurring flavonoid, possesses a variety of pharmaceutical properties such as anticancer, anti-inflammatory, and antioxidant properties which are very important for human health. Parsley is one of the most common herbs used in cuisines and is known as the best source of apigenin. Therefore, this study aimed to investigate the effects of various extraction methods on the extraction of biologically active compounds from parsley leaves. Conventional (maceration), ultrasound-assisted extraction (UAE), and ohmic heating extraction (OHE) methods were compared in terms of yield, total phenolic content (TPC), total flavonoid content (TFC), antioxidant activities, and apigenin quantities. The results showed that the UAE and OHE techniques had higher extraction efficiency than the maceration method. UAE achieved satisfactory extraction efficiency, shorter processing time, high energy savings, and retention of heat-labile compounds. OHE, as an advanced heating technology, increased the permeability of cell membranes, facilitating the release of bioactive compounds. The results revealed that the OHE technique was the most effective method for apigenin extraction (159.63 ppb) and antioxidant activity.

Paper fiber-reinforced polypropylene composites from nonwoven preforms: A study on compression molding optimization from a manufacturing perspective

This work optimizes compression molding manufacturing for wet-formed nonwoven paper and polypropylene fiber mats. A central composite designed experiment investigated the effects of fiber reinforcement concentration, compression molding temperature, pressure, and time on composite laminate performance. We assess the composites’ density, panel thickness, water uptake, flexural behavior, and Izod impact strength. Models predicted and optimized composite performance using objective function analysis with penalties applied for undesirable conditions, such as processing time or low reinforcement concentration. Paper fiber content has the largest impact on composite properties, followed by processing time, molding pressure, and temperature. Composite optimization depends on penalty conditions; low fiber content penalties favor low fiber content panels with short processing times, while high fiber content penalties favor high fiber content panels with long processing times. This work suggests that molding composites with a greater fraction of renewable feedstock requires a commensurate increase in processing intensity.

Exploring co-processing strategies for multi-material spark plasma sintering of pure Cu with AlSi10Mg by master sintering curves

Manufacturing complex multi-material metallic components without assembly operations is currently being explored using novel additive manufacturing techniques. For materials combinations that are difficult to process via melting-based processes, multi-material spark plasma sintering (SPS) appears as a promising alternative. However, due to different sintering kinetics, materials with very different melting points might have to be co-sintered at non-optimal conditions. In this work, the potential to improve the co-sinterability of dissimilar materials, namely pure copper and AlSi10Mg, is evaluated by altering the sintering kinetics of copper using different particle size distributions (PSD). Using the master sintering curve (MSC) approach, the densification behaviour of spherical pure copper powder during SPS is evaluated systematically to study the influence of PSD, uniaxial applied pressure, and isothermal holding temperature. An intermediate-sized monomodal and close-to-optimal bimodal PSD are compared for processing at lower sintering temperatures. It was observed that, compared to an intermediate monomodal PSD, a near-optimal bimodal powder mixture yields fully dense Cu–AlSi10Mg components at lower temperature and shorter process times. Therefore, the use of a bimodal mixture enables multi-material sintering, offers energy and cost savings to produce multi-material components, and improves compatibility between materials with very different melting points.

Effect of microwave combined with ultrasonic pretreatment on the flavor of composite stewed soup‐stock

AbstractIn order to increase the content of flavoring components and nutrients in the stock, effects of microwave (MW) combined with ultrasonic pretreatment on water‐soluble proteins, flavor nucleotides, volatile gas constituents and sensory evaluation in the stewed stock were explored. The results showed that, compared with the control group (CK), MW, and ultrasonic (US) pretreatment could significantly promote the degradation of nucleotides and form a large number of 5′‐flavor nucleotides. The combined treatment of MW and US promoted protein hydrolysis and increased the content of water‐soluble protein. The microwave combined ultrasonication pretreated stew stock had the brightest color and the overall sensory score was better than that of the CK. In addition, GC–MS analysis showed that a total of 49 volatile substances were detected in the stock samples. After microwave combined ultrasonication pretreatment, the relative contents of aldehydes and alcohols in the stock increased significantly. The sensor response value of the electronic nose was the highest, indicating that the intensity of flavor characteristics increased. Therefore, MW combined with ultrasonic pretreatment can effectively promote the formation and dissolution of nutrients, and increase the content of flavorful nucleotides and volatile gases.Practical applicationThis study provides a novel processing method for traditional stewed stock. Ultrasonic combined with MW treatment can quickly degrade the protein in the raw material and dissolve it into the stock. At the same time, it promotes the formation of flavor nucleotides and accelerates the Maillard reaction to produce more flavor substances. The technology has the advantages of short processing time, environmental protection and safety. It can be used as a potential pretreatment technology to regulate the flavor of stock‐soup.

Influence of the processing parameters on the degradation of poly(lactic acid) (PLA) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and modification of their molecular weight using chain extenders

Poly(lactic acid) (PLA) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) exhibit valuable mechanical properties like high stiffness and tensile strength but are sensitive to processing parameters. The influence of these parameters was evaluated by measuring the variation of melt viscosity during processing. For all experiments, in the absence of chain extenders, the decrease in melt viscosity clearly showed the degradation of polymers during processing. This is more pronounced for PHBV than PLA. In order to compensate for the degradation and, if possible, improve the melt strength of these bio-based polymers, two chain extenders have been evaluated: dicumyl peroxide (DCP) and a polymeric epoxy acrylate chain extender (Joncryl® ADR 4400). DCP reacts quickly with PLA and PHBV, while the epoxy-acrylate chain extender shows slower kinetics. For the PLA, with both investigated chain extenders, an increase in the molecular weight as compared with the virgin polymer and eventually the apparition of an insoluble fraction due to branching and crosslinking are observed. In the case of PHBV, the degradation is compensated by using DCP, requiring short processing times. No significant increase in molecular weight was observed when using the polymeric epoxy acrylate chain extender, requiring longer residence times, although the apparition of a gel fraction suggests the presence of branching and crosslinking.

Highly Sensitive 3D‐Nanoplasmonic‐Based Epidermal Growth Factor Receptor Mutation Multiplex Assay Chip for Liquid Biopsy

Economical mutation detection method with high analytical and clinical sensitivity is necessary for early cancer diagnosis and screening. In this study, a novel 3D‐nanoplasmonic‐based multiplex mutation assay chip is developed to detect epidermal growth factor receptor (EGFR) mutations. This assay kit comprises a 3D‐nanoplasmonic substrate immobilized with capture probes and primer–probe sets for recombinase polymerase amplification, wild‐type inhibition, and fluorescence detection, enabling multiplex detection of EGFR exon 19 deletions, exon 20 insertions, and exon 21 L858R point mutations. The strategy facilitates the detection of all deletions and insertions within the target region with extremely high analytical sensitivity, detecting as low as 1 × 10−9% mutation frequency, implying three copies/reactions and 100 zM. The synergistic effects of plasmon‐enhanced fluorescence from the 3D‐nanoplasmonic substrate and wild‐type inhibitor contribute to this high analytical sensitivity. Moreover, the developed chip exhibits 100% accuracy in the clinical testing of plasma samples from normal individuals and patients with benign lung tumor and malignant lung tumor. With high sensitivity and multiplexing capabilities, this assay operates at a low reaction temperature (around 37 °C) and requires a short processing time, ≈70 min post‐cell‐free DNA extraction. These features make the chip a valuable tool for easy and widespread cancer screening.

Exploring the Role of Chatbots in the Recruitment Process in Latin America

Objective: This study aims to explore the implementation and expectations of using chatbots in the personnel recruitment process in Latin American companies, focusing on their application, challenges, and perceived benefits. Theoretical Framework: Personnel recruitment and selection have evolved with the incorporation of Artificial Intelligence (AI), specifically through the use of chatbots. The literature highlights AI's ability to automate repetitive tasks, improve the efficiency of the recruitment process, and reduce human biases. However, there is a lack of research in the Latin American context regarding the experience and skills necessary to successfully implement chatbots in recruitment. Method: A multiple case study was conducted in seven Latin American companies from various sectors, using qualitative interviews with human resources professionals and managers. The case study methodology was applied to understand the implementation and expectations of using chatbots in the recruitment process. Transcriptions of the interviews were analyzed using a constructivist approach oriented towards grounded theory. Results and Discussion: The research presents two relevant aspects, previous experience with chatbots and expectations for their use in the recruitment process. Chatbots are primarily used for customer service, replacing traditional methods such as email and phone calls. Best practices include programming aspects, information quality, feedback, and change management. Benefits include the automation of repetitive tasks, improvement in efficiency, and cost reduction, while challenges include proper programming, bias management, and cultural adaptation. Regarding the use of chatbots and the Recruitment Process, their potential benefit in shortening process times was perceived. Various activities were identified where they could be useful, especially in the initial stages of recruitment, although the need for a human component in the final stages to evaluate emotional and aptitude aspects was recognized. Chatbots are considered reliable as a complement in the early stages of the process, but challenges are posed in programming, bias management, and adaptation to recruitment needs. Research Implications: The successful implementation of chatbots in the recruitment process could improve efficiency, reduce costs, and enhance the company's image. However, careful consideration of identified challenges such as proper programming, bias management, and integration with the human component of recruitment is required.

On the Origin of soft ticks (Parasitiformes, Ixodoidea, Argasidae)

The origin of the common evolutionary branch of soft and hard ticks is dated to the later Permian, approximately coinciding with the Permian extinction, and divergence of the common branch of Ixodoidea into ancestral forms of Argasidae and Ixodidae occurred in the Triassic. Ancestors of the common branch of Ixodoidea (Ixodidae, Argasidae, Nuttalliellidae) were not bloodsucking arthropods and were closely related to modern representatives of Holothyridae. Bloodsucking and, later, temporary ectoparasitism had developed only after divergence of the main branches (Ixodidae, Argasidae and Nuttalliellidae), independently in each group. At early stages of the soft tick evolution, bloodsucking was a short-time process, long-time feeding had developed later in larvae and promoted dispersal of ticks. Maintenance of the short-time feeding can be explained by adaptation to dwelling in bird nests or in shelters visited by birds, and later, also in mammal burrows. Displacements of gnathosomе to the ventral side of idiosome hampered combing of a parasite from the host during short-time bloodsucking. Short-time feeding resulted in maintenance and development of coxal glands as the main organ for removal of superfluous liquid during bloodsucking. Adaptation to shelter habitats (nests, burrows, rock crevices, under dead tree cork, etc.) promoted development of polyphagia and adaptations for long-term starvation.

Primary clarification of mammalian cell culture fluid using enhanced sedimentation on inclined surfaces inside the single-use disposable Sudhin BioSettler150.

The first downstream processing step in the purification of a biopharmaceutical protein secreted into mammalian cell culture fluid is the primary clarification of the culture fluid. As cell densities in the fed-batch and increasingly more common perfusion bioreactors have increased over last two decades through intensified upstream bioreactor production processes, the traditional primary clarification unit operations of centrifugation and/or microfiltration become more challenging with issues like frequent desludging, cell disruption due to shear damage and quick fouling of membranes. We have developed a novel compact cell settler device exploiting the enhanced sedimentation on inclined surfaces and demonstrated that this settler device can be adapted easily to remove and contain cells or cell clumps from the clarified supernatant collected via the top effluent of the settler. In this work, we present high product recovery results during primary clarification of mammalian cell culture supernatant using our novel single-use disposable BioSettler150 while processing about 10 L of cell culture broth within short processing times of about 4 h.

Precision dose prediction for breast cancer patients undergoing IMRT: The Swin-UMamba-Channel Model

BackgroundRadiation therapy is one of the crucial treatment modalities for cancer. An excellent radiation therapy plan relies heavily on an outstanding dose distribution map, which is traditionally generated through repeated trials and adjustments by experienced physicists. However, this process is both time-consuming and labor-intensive, and it comes with a degree of subjectivity. Now, with the powerful capabilities of deep learning, we are able to predict dose distribution maps more accurately, effectively overcoming these challenges. MethodsIn this study, we propose a novel Swin-UMamba-Channel prediction model specifically designed for predicting the dose distribution of patients with left breast cancer undergoing radiotherapy after total mastectomy. This model integrates anatomical position information of organs and ray angle information, significantly enhancing prediction accuracy. Through iterative training of the generator (Swin-UMamba) and discriminator, the model can generate images that closely match the actual dose, assisting physicists in quickly creating DVH curves and shortening the treatment planning cycle. Our model exhibits excellent performance in terms of prediction accuracy, computational efficiency, and practicality, and its effectiveness has been further verified through comparative experiments with similar networks. ResultsThe results of the study indicate that our model can accurately predict the clinical dose of breast cancer patients undergoing intensity-modulated radiation therapy (IMRT). The predicted dose range is from 0 to 50 Gy, and compared with actual data, it shows a high accuracy with an average Dice similarity coefficient of 0.86. Specifically, the average dose change rate for the planning target volume ranges from 0.28 % to 1.515 %, while the average dose change rates for the right and left lungs are 2.113 % and 0.508 %, respectively. Notably, due to their small sizes, the heart and spinal cord exhibit relatively higher average dose change rates, reaching 3.208 % and 1.490 %, respectively. In comparison with similar dose studies, our model demonstrates superior performance. Additionally, our model possesses fewer parameters, lower computational complexity, and shorter processing time, further enhancing its practicality and efficiency. These findings provide strong evidence for the accuracy and reliability of our model in predicting doses, offering significant technical support for IMRT in breast cancer patients. ConclusionThis study presents a novel Swin-UMamba-Channel dose prediction model, and its results demonstrate its precise prediction of clinical doses for the target area of left breast cancer patients undergoing total mastectomy and IMRT. These remarkable achievements provide valuable reference data for subsequent plan optimization and quality control, paving a new path for the application of deep learning in the field of radiation therapy.

Immunofluorescence staining of chloroplast proteins with frozen sections of plant tissues.

Immunofluorescence staining with frozen sections of plant tissues and a nest tube is convenient and effective, and broadens the applicability of immunofluorescence staining. Immunofluorescence staining is an indispensable and extensively employed technique for determining the subcellular localization of chloroplast division proteins. At present, it is difficult to effectively observe the localization of target proteins in leaves that are hard, or very thin, or have epidermal hair or glands with the current immunofluorescence staining methods. Moreover, signals of target proteins were predominantly detected in mesophyll cells, not the cells of other types. Thus, the method of immunofluorescence staining was further explored for improvement in this study. The plant tissue was embedded with 50% PEG4000 at -60℃, which was then cut into sections by a cryomacrotome. The sections were immediately immersed in fixation solution. Then, the sample was transferred into a special nested plastic tube, which facilitated the fixation and immunofluorescence staining procedures. The use of frozen sections in this method enabled a short processing time and reduced material requirements. By optimizing the thickness of the sections, a large proportion of the cells could be well stained. With this method, we observed the localization of a chloroplast division protein FtsZ1 in the wild-type Arabidopsis and various chloroplast division mutants. Meanwhile, the localization of FtsZ1 was also observed not only in mesophyll cells, but also in guard cells and epidermal cells in a lot of other plant species, including many species with hard leaf tissues. This method is not only easy to use, but also expands the scope of applicability for immunofluorescence staining.