bluuebunny/crossref_metadata_2025 huggingface dataset:
Space-time shape optimization of rotating electric machines
Authors: Cesarano Alessio , Dapogny Charles , Gangl Peter
Published: October 2024

This paper is devoted to the shape optimization of the internal structure of an electric motor, and more precisely of the arrangement of air and ferromagnetic material inside the rotor part with the aim to increase the torque of the machine. The governing physical problem is the time-dependent, nonlinear magneto-quasi-static version of Maxwell’s equations. This multiphase problem can be reformulated on a 2D section of the real cylindrical 3D configuration; however, due to the rotation of the machine, the geometry of the various material phases at play (the ferromagnetic material, the permanent magnets, air, etc.) undergoes a prescribed motion over the considered time period. This original setting raises a number of issues. From the theoretical viewpoint, we prove the well-posedness of this unusual nonlinear evolution problem featuring a moving geometry. We then calculate the shape derivative of a performance criterion depending on the shape of the ferromagnetic phase via the corresponding magneto-quasi-static potential. Our numerical frameworkto address this problem is based on a shape gradient algorithm. The nonlinear time periodic evolution problems for the magneto-quasi-static potential is solved in the time domain, with a Newton–Raphson method. The discretization features a space-time finite element method, applied on a precise, meshed representation of the space-time region of interest, which encloses a body-fitted representation of the various material phases of the motor at all the considered stages of the time period. After appraising the efficiency of our numerical framework on an academic problem, we present a quite realistic example of optimal design of the ferromagnetic phase of the rotor of an electric machine.
Derivation of a von Kármán plate theory for thermoviscoelastic solids
Authors: Badal Rufat , Friedrich Manuel , Machill Lennart
Published: October 2024

In this paper, we derive a von Kármán plate theory from a three-dimensional quasistatic nonlinear model for nonsimple thermoviscoelastic materials in the Kelvin–Voigt rheology, in which the elastic and the viscous stress tensor comply with a frame indifference principle [A. Mielke and T. Roubíček, Thermoviscoelasticity in Kelvin–Voigt rheology at large strains, Arch. Ration. Mech. Anal. 238 (2020) 1–45]. In a dimension-reduction limit, we show that weak solutions to the nonlinear system of equations converge to weak solutions of an effective two-dimensional system featuring mechanical equations for viscoelastic von Kármán plates, previously derived in Friedrich and Kružík [Derivation of von Kármán plate theory in the framework of three-dimensional viscoelasticity, Arch. Ration. Mech. Anal. 238 (2020) 489–540], coupled with a linear heat-transfer equation. The main challenge lies in deriving a priori estimates for rescaled displacement fields and temperatures, which requires the adaptation of generalized Korn’s inequalities and bounds for heat equations with [Formula: see text]-data to thin domains.
Research on Mobile Edge Computing Task Unloading Model Optimization and Intelligent Algorithms
Authors: Wu Beijia
Published: October 2024

To overcome the limitations of mobile devices in executing computing-intensive workloads, mobile edge computing emerged at the times required. It can effectively support computing intensive and delay critical applications executed by Internet of Things devices with limited computing power and energy constraints and becomes the key technology of next-generation networks. This research first determined the optimization framework of the mobile edge computing task unloading system, built a basic platform for mobile edge computing task unloading after system optimization, completed the drill transformation of intelligent algorithm based on the mobile edge computing task unloading algorithm of the optimized system, and studied its convergence and applicability. Finally, by comparing several different mobile edge computing tasks unloading models, Select a suitable mobile edge computing task unloading model, and complete the practical effect test. The results show that: (1) Compared with the traditional unloading mode, the optimized mobile edge computing task unloading system has higher work efficiency; (2) The whole process model of mobile edge computing task unloading completed in this study can reduce the task processing delay in the actual use process; (3) The unloading system with intelligent algorithms is more suitable for edge devices, providing a reference task unloading model for engineering practice.
Designing and Investigating the Impact of an AR Application for Learning Spatial Thinking Skills at Middle Level
Authors: Lashari Tahira Anwar , Afzal Tashfa , Lashari Sana Anwar , Irfan Rabia , Lashari Saima Anwar , Aziz Mian Talha
Published: October 2024

Spatial thinking is the ability to mentally visualize and manipulate 3D objects, identify patterns, and describe relationships among objects in a setting. These skills are highly predictive of success in engineering, architecture, graphic design, computer science, and other fields of education. In our education system, at the school level, teachers focus on something other than the development of the skills mentioned above. Which is passed on to the next cadre and even reflected in the professional lives of students. Most research on spatial thinking ability develops at the undergraduate or primary levels. However, there is a need to work on adolescents in middle school who are at the stage of learning and manipulating abstract concepts. In this study, a spatial thinking learning application based on AR technology is developed and evaluated using Unity 3D with AR foundation libraries. AR technology’s augmented and immersive characteristics helped adolescents (12–13 years) visualize objects in three dimensions and make inferences about them. One group pre and posttest pre-experimental research design was followed. Statistically significant results of pre- and post-surveys and graphs of in-app calculations provide evidence of learning. This experience allowed students to actively practice spatial constructs, enhance their spatial reasoning skills, and boost their self-efficacy while using these skills.
A Hybrid Interactive Decision-making Model Based on Multi-objective Optimization: An Application to Sustainable Supplier Selection
Authors: Bisht Garima , Kumar Arun
Published: October 2024

Sustainable development is crucial for conserving resources and ensuring smooth supply chain operations. In the context of the complex task of supplier selection, the traditional assumptions of attribute independencies are frequently found to be inadequate. The effective interaction between attributes and their weights plays a crucial role in navigating the decision outcomes. This paper presents a Choquet integral-based hybrid interactive decision-making approach to address the two important issues regarding the weights and interaction of criteria. To achieve this aim, first a hybrid weight determination method is proposed, combining the merits of multi-objective optimization and clustering techniques. To comprehensively assess the interactions among attributes, a non-additive measure determination method is introduced, leveraging concepts such as standard deviation and correlation. This approach effectively captures the interdependencies among attributes, leading to a more accurate decision-making process. Then, the Choquet integral incorporates a logarithmic function, which serves to enhance the modeling of uncertainty and effectively address the complexities present in intricate decision-making situations. Furthermore, a comprehensive interactive MCDM model is constructed, serving as a framework for supplier selection. Finally, experimental and sensitivity analysis demonstrate the effectiveness and stability of the proposed approach.
An Improved Reptile Search Algorithm with Multiscale Adaptive Deep Learning Technique and Atrous Spatial Pyramid Pooling for IoT-based Smart Agriculture Management
Authors: Sangeetha Bathini , Pabboju Suresh
Published: October 2024

Smart farming is an enhanced option for increasing food production, resource management and labour. Existing prediction methods need trained experts to analyse the data, which is a time- consuming process, and thus, there is a need for smart farming with the Internet of Things (IoT). Hence, a well-developed IoT-assisted smart agriculture model is proposed for managing agricultural needs to improve the economic value of farmers. The proposed framework constitutes four major aspects like Crop prediction, Crop yield prediction, Plant disease prediction and Smart irrigation. Initially, the crop images are taken as the input and fed to the Multi-scale Adaptive and Attention-based Convolution Neural Network with Atrous Spatial Pyramid Pooling (MACNN-ASPP), where the dissimilar crops are classified and obtained. In the second aspect, the crop image as well as crop-related data, are fetched from the data sources and given as input. Further, the deep features of the image are extracted that are added with soil and environment condition data. Then this feature is subjected to the Multi-scale Adaptive and Attention-based One-Dimensional Convolution Neural Network with Atrous Spatial Pyramid Pooling (MA1DCNN-ASPP) for crop yield prediction. While in the third aspect, the leaf images are assembled from the data file and fed as input to the MACNN-ASPP for detecting the variety of diseases affecting the plants. In the final aspect, smart irrigation is done by collecting field images with related data. Further, the deep features retrieved from the field images are applied to MA1DCNN-ASPP, where the different conditions of the field will be attained. In order to develop the model adaptively, the hyper-parameters in the network are optimised using the Improved Reptile Search Algorithm (IRSA). Finally, the investigation is done over the proposed methodology using multiple evaluation metrics. In contrast with other approaches, the proposed smart agriculture outperforms the performance of managing crops without any hazardous effects. Accuracy validation executed in the implemented IRSA-MACNN-ASSP-based crop yield prediction model accomplished better efficiency as 6.89%, 4.45%, 2.19% and 1.08% better than the classical techniques like CNN, LSTM, 1DCNN and MA1DCNN-ASPP.
The Paradigm Shifts in Artificial Intelligence
Authors: Dhar Vasant
Published: October 2024

Even as we celebrate AI as a technology that will have far-reaching benefits for humanity, trust and alignment remain disconcertingly unaddressed.
A Cooperative Game Theory-Based Feature Selection for Efficient Hand Grasp Classification Using Minimal Number of sEMG Signals
Authors: Singh Shashank Kumar , Chaturvedi Amrita
Published: October 2024

Deploying bio-electrical signals and image processing (visual) techniques are the two popular means to provide input to generate grasp control for robotic and prosthetic devices. Visual perception-based techniques rely on computationally expensive image processing algorithms and are affected by lighting conditions. In contrast, grasp control based on bio-electric signals such as surface electromyography (sEMG) is invariant to lighting conditions. It can reflect human intent to hand motion or grasp with lesser computational costs. In this article, we propose an efficient machine learning pipeline to classify hand grasp using a minimal number of sEMG sensors. A cooperative game theory-based feature selection technique is applied to find the representative feature subset. The feature selection method uses a modified marginal contribution based on the class distribution coefficient to generate feature ranking. This feature ranking is further used to find the most representative feature subset from the extracted feature set. Our proposed pipeline has been evaluated on a benchmark dataset and has achieved a classification accuracy of 98.20%, using single-channel EMG when coupled with the XGBoost classifier. Thorough assessments were conducted to confirm the reliability of the results obtained. Our proposed pipeline holds the potential to facilitate the development of cost-effective sEMG prosthetics.
Tiny Pointers
Authors: Bender Michael A. , Conway Alex , Farach-Colton Martín , Kuszmaul William , Tagliavini Guido
Published: October 2024

This paper introduces a new data-structural object that we call the tiny pointer. In many applications, traditional

\(\log n\)

-bit pointers can be replaced with

\(o(\log n)\)

-bit tiny pointers at the cost of only a constant-factor time overhead and a small probability of failure. We develop a comprehensive theory of tiny pointers, and give optimal constructions for both fixed-size tiny pointers (i.e., settings in which all of the tiny pointers must be the same size) and variable-size tiny pointers (i.e., settings in which the average tiny-pointer size must be small, but some tiny pointers can be larger). If a tiny pointer references an item in an array filled to load factor

\(1-\delta\)

, then the optimal tiny-pointer size is

\(\Theta(\log\log\log n+\log\delta^{-1})\)

bits in the fixed-size case, and

\(\Theta(\log\delta^{-1})\)

expected bits in the variable-size case.

Our tiny-pointer constructions also require us to revisit several classic problems having to do with balls and bins; these results may be of independent interest.

Using tiny pointers, we apply tiny pointers to five classic data-structure problems. We show that:

A data structure storing

\(n\)

\(v\)

-bit values for

\(n\)

keys with constant-factor time modifications/queries can be implemented to take space

\(nv+O(n\log^{(r)}n)\)

bits, for any constant

\(r\gt0\)

, as long as the user stores a tiny pointer of expected size

\(O(1)\)

with each key—here,

\(\log^{(r)}n\)

is the

\(r\)

-th iterated logarithm.

Any binary search tree can be made succinct, meaning that it achieves

\((1+o(1))\)

times the optimal space, with constant-factor time overhead, and can even be made to be within

\(O(n)\)

bits of optimal if we allow for

\(O(\log^{*}n)\)

-time modifications—this holds even for rotation-based trees such as the splay tree and the red-black tree.

Any fixed-capacity key-value dictionary can be made stable (i.e., items do not move once inserted) with constant-factor time overhead and

\((1+o(1))\)

-factor space overhead.

Any key-value dictionary that requires uniform-size values can be made to support arbitrary-size values with constant-factor time overhead and with an additional space consumption of

\(\log^{(r)}n+O(\log j)\)

bits per

\(j\)

-bit value for an arbitrary constant

\(r\gt0\)

of our choice.

Given an external-memory array

\(A\)

of size

\((1+\varepsilon)n\)

containing a dynamic set of up to

\(n\)

key-value pairs, it is possible to maintain an internal-memory stash of size

\(O(n\log\varepsilon^{-1})\)

bits so that the location of any key-value pair in

\(A\)

can be computed in constant time (and with no IOs).

In each case tiny pointers allow for us to take a natural space-inefficient solution that uses pointers and make it space-efficient for free.
Efficiently Enlarging RDMA-Attached Memory with SSD
Authors: Yang Zhe , Wang Qing , Liao Xiaojian , Lu Youyou , Huang Keji , Shu Jiwu
Published: October 2024

RDMA-based in-memory storage systems offer high performance but are restricted by the capacity of physical memory. In this article, we propose TeRM to extend RDMA-attached memory with SSD. TeRM achieves fast remote access on the SSD-extended memory by eliminating page faults of RDMA NIC and CPU from the critical path. We also introduce a set of techniques to reduce the consumption of CPU and network resources. Evaluation shows that TeRM performs close to the performance of the ideal upper bound where all pages are pinned in the physical memory. Compared with existing approaches, TeRM significantly improves the performance of unmodified RDMA-based storage systems, including a file system and a key-value system.
Decomposed Prototype Learning for Few-Shot Scene Graph Generation
Authors: Li Xingchen , Xiao Jun , Chen Guikun , Feng Yinfu , Yang Yi , Liu An-An , Chen Long
Published: October 2024

Today's scene graph generation (SGG) models typically require abundant manual annotations to learn new predicate types. Therefore, it is difficult to apply them to real-world applications with massive uncommon predicate categories whose annotations are hard to collect. In this article, we focus on
Few-Shot SGG (FSSGG)
, which encourages SGG models to be able to quickly transfer previous knowledge and recognize unseen predicates well with only a few examples. However, current methods for FSSGG are hindered by the high intra-class variance of predicate categories in SGG: On one hand, each predicate category commonly has multiple semantic meanings under different contexts. On the other hand, the visual appearance of relation triplets with the same predicate differs greatly under different subject–object compositions. Such great variance of inputs makes it hard to learn generalizable representation for each predicate category with current few-shot learning (FSL) methods. However, we found that this intra-class variance of predicates is highly related to the composed subjects and objects. To model the intra-class variance of predicates with subject–object context, we propose a novel
Decomposed Prototype Learning (DPL)
model for FSSGG. Specifically, we first construct a decomposable prototype space to capture diverse semantics and visual patterns of subjects and objects for predicates by decomposing them into multiple prototypes. Afterwards, we integrate these prototypes with different weights to generate query-adaptive predicate representation with more reliable semantics for each query sample. We conduct extensive experiments and compare with various baseline methods to show the effectiveness of our method.
Investigating the Structural, Linear/Nonlinear Optical, and Photoluminescence Characteristics of CuO/ZnMn2O4 Nanocomposite for Physicochemical Applications
Authors: Heiba Zein K. , Ghannam M. M. , Abozied Asmaa M. , Abdellatief M. , Ali Essam E. , Badawi Ali , Mohamed Mohamed Bakr
Published: October 2024

The structural, optical, and photoluminescence performance of CuO/ZnMn2O4 nanocomposites was investigated for optical applications. Nanocomposites of xCuO/(1-x)ZnMn2O4 (x; 0 to 0.7) were equipped using the sol-gel route. Synchrotron X-ray diffraction data were collected to examine the structural parameters. Rietveld refinement analysis reveals that the crystallite size decreases upon raising x from 0 to 0.7. High-resolution transmission electron microscopy revealed that the distribution of particle sizes demonstrates a relatively broad spectrum within the nanometer range. Raman spectroscopy investigations were applied to examine the structure’s vibrations. Scanning electron microscopy was used to examine the morphology of the formed samples. UV–vis spectrophotometry was applied to collect optical absorbance and reflectance measurements of the samples. Optical energy gap

E

g

was determined utilizing the Kubelka-Munk method. The refractive index investigations were explored based on seven empirical formulas. The nonlinear optical parameters were explored as a function of CuO contents. The influence of CuO amount on the photoluminescence spectra was investigated. CIE chromaticity diagrams showed that all samples have various degrees of blue-violet colors. A significant improvement was achieved in the linear/nonlinear optical performance of nano ZnMn2O4 by forming CuO/ZnMn2O4 heterojunction, supporting the possible use of CuO/ZnMn2O4 nanocomposites in various optical applications.
Differences in gut microbiota and metabolites between wrestlers with varying precompetition weight control effect
Authors: Fu Pengyu , Wang Cuiping , Zheng Shuai , Gong Lijing
Published: October 2024

The purpose of this study is to observe the differences in precompetition diet structure, adaptability to training, gut microbiota, and metabolites of wrestlers with different weight control effects and analyze the correlation between them, aiming to provide scientific guidance and advice on weight control for wrestlers.
Dynamic Evaluation of the Effect of Soil Analysis on Monocultures
Authors: Vargas Dayhanna S. , Torres Luz K. , Osorio Juan C.
Published: October 2024

Soil stands as one of the principal resources for agricultural development, with this activity encompassing approximately 38% of the Earth’s surface. The resulting product is directed towards human consumption and animal feed, as well as energy crops, among other purposes. Given the pivotal role of this activity and the escalating demand for its products within the economic sphere, coupled with population growth, the need arises not only for increased crop yield but also for addressing the per capita reduction in available land. Consequently, an imperative arises to explore emerging alternatives for soil conservation and restoration in pursuit of this goal. Thus, a dynamic system model is introduced to assess the patterns of land use for agricultural cultivation in Colombia. Modelling is a useful tool for system conceptualisation, understanding, projection of future scenarios and hypothesis testing about the impact of disruptions in a system’s overall behaviour about changes in its components. The main purpose of this article is to evaluate, through simulation with system dynamics, soil recovery scenarios from the use of residues from the same crops, specifically in the case of monocultures, such as sugarcane. Similar studies have not been found in the literature review and, therefore, this work is novel and establishes a starting point to continue exploring these soil recovery alternatives. The formulation of this model was accomplished through the utilization of the Vensim DSS software (Version 5.10a), followed by simulations of various land use scenarios across two distinct types of crops. The outcomes of these simulations unveiled a gradual degradation of the soil. To counter this trend, scenarios were evaluated, with composting emerging as a viable and significant alternative. There are some scenarios in which land degradation is lower by more than 50% compared with those in which the alternative is not considered. The composting process reduces costs in terms of fertilization, labour and support for environmental enhancement by restoring physical, chemical and biological soil properties. This study proposes for this model to be extended to other agricultural chains, thereby demonstrating its potential for guiding decisions regarding land use and crop activity scheduling that share similarities with the system under investigation.
Impact of Vitamin E Supplementation on High‐Density Lipoprotein in Patients With Haptoglobin Genotype–Stratified Diabetes: A Systematic Review of Randomized Controlled Trials
Authors: Zheng Pan-pan , Zhang Li-wen , Sheng Dan , Wang Min-zhen , Li Rong , Zhao Wei-li , Liu Rongmei , Xiu Xian , Zhao Yu-sha , Min Xi , Wang Zhi-kai , Liu Zan-chao
Published: October 2024

Background: Vitamin E, an essential micronutrient with antioxidant potential, can dramatically reduce the cardiovascular risk in individuals with haptoglobin (Hp) 2‐2 genotype diabetes; however, the underlying mechanism remains unclear.

Objective: The objective of this study is to evaluate the effect of vitamin E supplementation on high‐density lipoprotein (HDL) levels and function in individuals with diabetes stratified by Hp genotype.

Methods: All relevant studies published up to May 2023 were systematically reviewed using PubMed, Cochrane Library, Web of Science, Chinese Wanfang, China Science and Technology Journal, and Chinese National Knowledge Infrastructure databases. Randomized controlled trials that evaluated the effects of vitamin E supplementation on HDL levels were included. The outcomes assessed were changes in HDL concentrations, cholesterol efflux, and HDL‐associated lipid peroxides.

Results: In total, 163 publications were selected. Based on inclusion and exclusion selection and quality assessment, five studies with 463 participants were included. Vitamin E supplementation did not exert any effect on HDL levels in individuals with diabetes with any Hp genotype. Three of the five studies revealed that vitamin E improved cholesterol efflux and HDL lipid peroxides in individuals with Hp2‐2 diabetes but did not positively impact HDL function in Hp1 carriers.

Conclusions: Although vitamin E supplementation did not significantly impact HDL levels in individuals with diabetes of any Hp genotype, it may improve HDL function in individuals with Hp2‐2 diabetes. These findings indicate a pharmacogenetic interaction between vitamin E and the Hp genotype on HDL function. Moreover, vitamin E supplementation may be an effective strategy for specific individuals with diabetes.
Experimental Intensification and Modeling of Solid–Liquid Extraction of Polyphenols From Rice Husk Waste Using Organic Solvents
Authors: Abraham-Diego José Iván , Reynel-Ávila Hilda Elizabeth , Bonilla-Petriciolet Adrián , Moreno-Pérez Jaime
Published: October 2024

In the present study, the experimental intensification and modeling of the extraction process of antioxidants from rice husks using different organic solvents (ethanol, methanol, and acetone, and their mixtures with water) were analyzed and discussed. The best experimental extraction conditions to recover polyphenols from rice husks were identified, and the extraction kinetic data were modeled using the mechanistic and pseudo–second‐order models. The experimental results showed that the solvent‐based extraction of polyphenols from rice husks was endothermic where the ethanol and methanol offered the best separation performance. The polyphenol extraction process using ethanol and acetone was mainly influenced by the percentage of water contained in the solvent mixture used as separation medium, whereas the extraction temperature significantly affected the polyphenol extraction with methanol. The rice husk‐based extracts obtained with methanol and ethanol showed the highest total content of polyphenols (66.72 and 60.68 of gallic acid equivalent/g of biomass) and antioxidant capacity (71.93% and 72.02% 2,2‐diphenyl‐1‐picrylhydrazyl [DPPH] inhibition). The mechanistic model offered the best performance to describe the experimental polyphenol extraction, and its results were used to discuss and analyze the mass transfer parameters associated with the intraparticle diffusion of this extraction process. These results contribute to the valorization of rice husk residues as a potential feedstock to be incorporated in the biorefinery context for obtaining value‐added products.
Partial Disassembly and Consideration of Part Relationships in Multiproduct, Multiperiod Capacitated Disassembly Scheduling With Parts Commonality
Authors: Zare Sajed , Fakhrzad Mohammad Bagher , Khademi Zare Hassan , Hosseini-Nasab Hasan
Published: October 2024

This paper proposes a new mixed‐integer linear programming (MILP) model to consider a multiproduct, multiperiod capacitated disassembly scheduling model with parts commonality and partial disassembly. The major contribution of this research is to probe the possibility of partial disassembly and separation of parts until the desired part is obtained. When disassembly is partial, parts that are not in demand will not disassemble, saving time and costs. In addition, another contribution introduced in this paper is the consideration of relationships between parts. By incorporating these relationships into the disassembly scheduling problem, our proposed model offers a more comprehensive and efficient solution. The objective is to provide the best plan for selecting partial disassembly modes and scheduling disassembly due to capacity constraints to meet the demand for leaf parts over the planning time horizon and minimize setup, holding, operating, and supply costs. The proposed model is solved using the CPLEX solver, and numerical experiments using selected literature data for problem sizes and sensitivity analyses of key model parameters are carried out to demonstrate the proposed model’s consistency and robustness. In addition, significant managerial insights have been proposed based on sensitivity analysis to determine the applicability of the proposed model. Key insights reveal that increasing period capacity reduces total costs but requires careful balancing with capacity‐building expenses. Additionally, aligning part demand with the return product structure can significantly cut costs, and managing inventory through the procurement or disposal of less demanded parts can optimize operations.
Optimal Network Analysis through Vertex Order Coloring of Intuitionistic Fuzzy Graph Operations
Authors: Meenakshi A. , Dhanushiya S. , Qin Hong , Elangovan Muniyandy
Published: October 2024

Intuitionistic fuzzy graphs (IFGs) are a powerful tool for modeling uncertainty and complex relationships. They offer versatile frameworks for addressing real‐world challenges. In this research, we have introduced intuitionistic fuzzy vertex order coloring (IFVOC) and analyzed the alpha‐strong (), beta‐strong (), and gamma‐strong () vertices through their degree. We explored important theorems based on the types of strong vertices, broadening the scope of our study. We analyzed multiple IFG products to determine the most optimal network based on some important metrics, including the weight and total number of vertices, the chromatic number, and the weight of the graph’s minimum spanning tree. We systematically evaluate different types of IFG products, such as conormal, modular, residue, and maximal, and consider their implications for fuzzy graph structure and connectivity. We have investigated new metrics to measure the presence and importance of vertices in the graph, assessing both their frequency and overall impact. Additionally, we have investigated the impact of product operations on the significance of nodes and the resultant minimum spanning tree, providing insights into the overall robustness and efficiency of each product. We have explored how variations in product operations impact the distribution of vertices and the characteristics of the minimum spanning tree and chromatic number, elucidating the trade‐offs between different product options. We have modeled the product graph as a network to represent complex systems composed of interconnected entities. The outcomes of this research contribute to the advancement of IFG theory and its use in various fields, such as network design, strategic planning, and system analysis.
CD27-Armored BCMA CAR T-cell Therapy (CBG-002) for Relapsed and Refractory Multiple Myeloma: A Phase I Clinical Trial
Authors: Xu Yang , Zhang Xuzhao , Xin Dijia , Zhang Jiawei , Wang Luyao , Fan Yili , Chen Boxiao , Lei Wen , Qiu Xi , Jiang Huawei , Xiao Xibin , Huang Liansheng , Yu Jiandong , Yang Xin , Yang Wenjun , Zhu Jiangao , Qian Wenbin
Published: October 2024

B-cell maturation antigen (BCMA) chimeric antigen receptor (CAR) T-cell therapy has been approved for the treatment of relapsed and refractory multiple myeloma (RRMM); however, whether patients have long-term responses has yet to be established. We investigated the feasibility of CBG-002, a CD27-armored BCMA CAR T-cell therapy, to improve clinical efficacy in patients with RRMM. We present preclinical data showing the activity of CBG-002 against myeloma and results from a phase I clinical trial (NCT04706936) evaluating its safety and efficacy in patients with RRMM. The primary endpoint was safety, as assessed by grade 3 or 4 adverse events (AE). Key secondary endpoints were overall response rate (ORR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS). A total of 11 patients were enrolled and received CBG-002 therapy. Nine patients developed grade 1 or 2 cytokine release syndrome (CRS), whereas no patients experienced grade 3 or higher CRS or immune effector cell–associated neurotoxicity syndrome. Other grade 3 or higher AEs included neutropenia (72.7%), thrombocytopenia (45.5%), and anemia (36.4%). At a median follow-up of 16.7 months, the ORR was 81.8%, including a stringent complete response/complete response rate of 45.5%, very good partial response rate of 18.2%, and partial response rate of 18.2%, with a median DOR of 8.9 (range 1.8–21.9) months. The median OS was not reached, and the median PFS was 8.5 (2.7–22.9) months. In this phase I study, CBG-002, a CD27-armored BCMA CAR T-cell therapy, demonstrated safety and clinical efficacy in patients with RRMM.
Supplementary Table S3 from ATF6 Promotes Colorectal Cancer Growth and Stemness by Regulating the Wnt Pathway
Authors: Rodvold Jeffrey J. , Grimmer Matthew , Ruiz Karen , Marsters Scot A. , Oikonomidi Ioanna , Tan-Aristy Eileen , Pham Victoria C. , Sarkar Tamal , Harnoss Jonathan M. , Shatz-Binder Whitney , Modrusan Zora D. , Wu Thomas D. , Lill Jennie R. , Villemure Elisia , Rudolph Joachim , de Sousa e Melo Felipe , Ashkenazi Avi
Published: October 2024

Materials Table
Supplementary Figure S3 from ATF6 Promotes Colorectal Cancer Growth and Stemness by Regulating the Wnt Pathway
Authors: Rodvold Jeffrey J. , Grimmer Matthew , Ruiz Karen , Marsters Scot A. , Oikonomidi Ioanna , Tan-Aristy Eileen , Pham Victoria C. , Sarkar Tamal , Harnoss Jonathan M. , Shatz-Binder Whitney , Modrusan Zora D. , Wu Thomas D. , Lill Jennie R. , Villemure Elisia , Rudolph Joachim , de Sousa e Melo Felipe , Ashkenazi Avi
Published: October 2024

ATF6 disruption attenuates cell cycle progression and upregulates specific CDK inhibitors
Figure 8 from ATF6 Promotes Colorectal Cancer Growth and Stemness by Regulating the Wnt Pathway
Authors: Rodvold Jeffrey J. , Grimmer Matthew , Ruiz Karen , Marsters Scot A. , Oikonomidi Ioanna , Tan-Aristy Eileen , Pham Victoria C. , Sarkar Tamal , Harnoss Jonathan M. , Shatz-Binder Whitney , Modrusan Zora D. , Wu Thomas D. , Lill Jennie R. , Villemure Elisia , Rudolph Joachim , de Sousa e Melo Felipe , Ashkenazi Avi
Published: October 2024

Wnt surrogate restores Wnt pathway activity and growth of PDM-272 organoids in context of ATF6 inhibition. A, mRNA gene expression as determined by RT-qPCR of ATF6, Wnt signaling genes (AXIN2, LGR5, and TCF7) and Myc signaling genes (MYC and CDCA7) of PDM-272 organoid treated with Wnt surrogate fusion protein (0.015 nmol/L) in the absence or presence of Ceapin-A7 (3 μmol/L) after 2 days (n = 3). B, Confluence of PDM-272 organoid treated with Wnt surrogate fusion protein (0.01 nmol/L) in the absence or presence of Ceapin-A7 (3 μmol/L) for 10 days (n = 3). C, Viability of PDM-272 organoid, as treated in B (n = 3). D, Light microscopy images of organoids in B after 10-day treatment. E, Expression of ER13 stratified οf colonic tumor epithelial cell subtypes and divided by stem subsets and differentiated subsets. F, Expression of ATF6 as stratified cell subtypes described in E. G, Co-expression of ATF6 and known Wnt signaling (AXIN2, LGR5, and TCF7) and Myc signaling (MYC and CDCA7) for various colon cancer epithelial cell subtypes. Avg, average; imm, immature; prolif, proliferation. *, P < 0.05; ***, P < 0.001.
Chinese Expert Consensus on the Combination of Targeted Therapy and Immunotherapy with Locoregional Therapy for Intermediate/Advanced Hepatocellular Carcinoma
Authors: Bi Xinyu , Lu Yinying , Chen Bo , Yang Zhengqiang , Hong Zhixian , Wang Hanping , Sun Yongkun , Wang Xiaodong , Yuan Chunwang , Zeng Daobing , Huang Zhen , Zhou Aiping , Zhang Wen , Du Shunda , Zhao Jianjun , Zhou Jianguo , Zhai Yirui , Che Xu , Zhao Hong , Zhao Haitao , Cai Jianqiang
Published: October 2024

Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality; it ranks as the second most common cause of cancer deaths in China. Most HCC patients are first diagnosed at an advanced stage. In recent years, targeted therapy combined with immunotherapy has become the preferred regimen for systemic treatment of intermediate-advanced HCC, while targeted therapy combined with immunotherapy plus local treatment could further improve the efficacy in many clinical studies. To better guide the clinical treatment for effective and safe combination therapy, our interdisciplinary panel on the treatment of intermediate-advanced HCC comprising hepatologists, hepatobiliary surgeons, oncologists, radiologists, interventional radiologists, and traditional Chinese medicine physicians have formulated this consensus based on current clinical studies and clinical medication experience for reference. The consensus contained 15 recommendations, including the applicable population and management, local treatment selection, conversion strategy, treatment strategy after tumor progression and management of common adverse reactions.
Real-World Use of Ruxolitinib in Patients with Myelofibrosis and Anemia or Thrombocytopenia at Diagnosis
Authors: Yu Jingbo , Bland Emily , Schuler Tammy , Cordaro Thomas , Braunstein Evan
Published: October 2024

Introduction: Ruxolitinib is approved for treatment of myelofibrosis. We evaluated ruxolitinib in patients with anemia (hemoglobin <10 g/dL) or thrombocytopenia (platelet count ≤100 × 109/L) at diagnosis. Methods: This was a retrospective, secondary analysis of a Cardinal Health Oncology Provider Extended Network medical chart review of adults with myelofibrosis diagnosed between 2012 and 2016 who received first-line ruxolitinib. Results: 176 patients received first-line ruxolitinib and were included in this analysis. At diagnosis, 120 patients had hemoglobin concentrations <10 g/dL and 59 had a platelet count ≤100 × 109/L. Most patients (95%) with thrombocytopenia also had anemia. Median time of observation after diagnosis was 21.4 months. Among patients with anemia or thrombocytopenia, ruxolitinib dose at end of study was ≥10 mg twice daily (bid) in 88.3% and 83.1%, respectively. Ruxolitinib treatment was ongoing in 76.1% of patients overall and was rarely discontinued for anemia or thrombocytopenia (n = 2 total, 1.1%). Per the treating physician, 79.7% of patients had improved symptoms and 62.7% improved spleen size. Conclusion: Most patients with myelofibrosis and anemia or thrombocytopenia at diagnosis tolerated and maintained a ruxolitinib dose ≥10 mg bid for nearly 2 years, resulting in clinical benefit. This real-world evidence supports observations from prospective clinical trials of ruxolitinib in myelofibrosis.
Real-World Effectiveness and Safety of Carotegrast Methyl in Japanese Patients with Moderately Active Ulcerative Colitis
Authors: Ohmori Toshihide
Published: October 2024

Introduction: Carotegrast methyl (CGM) is an oral, small-molecule α4-integrin antagonist, which became clinically available in Japan in May 2022. CGM is approved for remission induction treatment for moderately active ulcerative colitis (UC) with an inadequate response or intolerance to 5-aminosalicylates. Methods: We performed a single-center, retrospective, observational study of Japanese patients with moderately active UC to assess the real-world effectiveness and safety of CGM as remission induction treatment. Results: Of 14 patients, 71% (10/14) were women, and the median (range) age was 47 (20–68) years. Disease types were proctitis in 7% (1/14), left-sided colitis in 50% (7/14), and total colitis in 43% (6/14). With a median (range) treatment duration of 8 (2–26) weeks, the rate of endoscopic improvement (Mayo endoscopic subscore [MES] of 0 or 1) was 64% (9/14), and the rate of endoscopic remission (MES of 0) was 57% (8/14). After treatment with CGM, the median (range) MES decreased significantly from 3.0 (2–3) to 0.0 (0–3) (p = 0.008), the Mayo score decreased significantly from 7.0 (5–9) to 0.0 (0–9) (p = 0.006), and the clinical activity index decreased significantly from 6.0 (1–11) to 0.0 (0–9) (p = 0.015). Stool and diarrhea frequencies decreased significantly after initiating CGM, and the percentage of patients with bloody stool and abdominal pain tended to decrease. The cumulative relapse-free rate at week 26 among 9 patients who achieved endoscopic improvement with CGM was 77.8% (95% confidence interval, 36.5%–93.9%). No adverse drug reactions, including progressive multifocal leukoencephalopathy, were reported during the study period. Conclusion: This single-center, retrospective, observational study of 14 Japanese patients with UC showed that CGM was safe and effective as a remission induction treatment for moderately active UC with an inadequate response to 5-aminosalicylates in real-world settings.
The Clinical Value of Serum Creatinine-to-Bilirubin Ratio in Predicting the Severity and Prognosis of Acute Pancreatitis
Authors: Chen Jun-Yi , He Jun-Lian , Feng Feng-Yi , Yang Xiao-Ya , Xie Wen-Rui
Published: October 2024

Introduction: Bilirubin (BIL) and creatinine (Cr) have long been recognized as potential early indicators of disease severity. A recent study found that the Cr-to-BIL ratio (CTR) was more sensitive and specific than either serum Cr or BIL alone. Our research focused on the clinical significance of CTR in evaluating the severity and prognosticating outcomes of acute pancreatitis (AP) in patients. Methods: Patients diagnosed with AP at the First Affiliated Hospital of Guangdong Pharmaceutical University between July 1, 2016, and December 31, 2020 were included. The analysis then focused on examining the relationship between CTR levels and the severity of the illness, the occurrence of complications, and the prognosticating outcomes for individuals diagnosed with AP. A total of 286 AP patients were enrolled. Results: Multivariate regression analyses indicated that AP patients with elevated CTR levels were more likely to develop severe AP. They exhibited higher MODS, Ranson, and APACHE-II scores, an increased incidence of organ failures (acute heart failure [AHF], acute kidney injury [AKI], and acute myocardial infarction), higher 30-day all-cause mortality rates, and a worse prognosis, often requiring more frequent use of vasoactive and diuretic agents compared to those with lower CTR levels. When CTR >14.05, AP patients had increased occurrence of AHF and AKI, higher 30-day all-cause mortality rates, more frequently using vasoactive agent and diuretic agent. Besides, the disease severity scores (MODS, Ranson, and APACHE-II) and hospital stays were markedly increased. Conclusion: AP patients with elevated CTR levels are prone to more severe disease progression, increased complications, and poorer outcomes compared to those with lower CTR levels.
The Association between a Recorded Diagnosis of Obesity and Clinically Significant Weight Loss in the Primary Care Setting: A Nationwide Registry
Authors: Kasher Meron Michal , Koren-Morag Nira , Oieru Dan
Published: October 2024

Introduction: Overweight and obesity (OW/OB) are underdiagnosed. The primary aim was to assess whether a diagnosis of OW/OB recorded by a primary care physician (PCP) is associated with clinically significant weight loss, compared to a missed diagnosis. The secondary aim was to investigate the association between OW/OB diagnosis and patient attendance at dietary consultations. Methods: This retrospective, observational cohort study was conducted using a nationwide healthcare database. The study included a random sample of 200,000 adults with BMI ≥25 kg/m2, recorded on a primary care visit, between 2014 and 2020. Patients with prior diagnosis of OW/OB or obesity-related complications were excluded. The independent variable was OW/OB diagnosis recorded by the PCP immediately after BMI measurement. The outcome variable was ≥5% weight loss at a second weight measurement within 9–15 months. Multivariate regression analysis was applied. Results: Of the 200,000 people with OW/OB, 36,033 (18.0%) had a diagnosis of OW/OB, and 37,368 (18.7%) had a second body weight measurement, of which 7,635 (20.4%) lost ≥5% of their baseline body weight. The prescription rate of anti-obesity medication was 1.2% and did not differ between patients who achieved weight loss and those who did not. Those with a recorded diagnosis were 2.6 times more likely to visit a dietitian (odds ratio [OR] 2.57, 95% confidence interval [CI]: 2.56–2.64) and 2.5 times more likely to achieve weight loss (OR 2.53, 95% CI: 2.46–2.60). After adjusting for multiple confounders, including attendance at dietary consultation, people who received OW/OB diagnosis were 32% more likely to achieve weight loss (OR 1.32, 95% CI: 1.28–1.36, p < 0.001) compared to people with missed diagnosis. Conclusions: Recording a diagnosis of obesity among relatively healthy people is associated with clinically significant weight loss at 1-year follow-up, independent of attendance at dietary consultation. Early obesity diagnosis is a significant opportunity to promote weight loss in the primary care setting and may affect weight trajectory.
Dexmedetomidine Alleviates the Long-Term Neurodevelopmental Toxicity Induced by Sevoflurane in the Developing Brain
Authors: Yang Ting-Ting , Wei Ran , Jin Fei-Fei , Yu Wei , Zhang Fang , Peng Yu , Zhang Shu-Jun , Qi Si-Hua , Liu Jia-Ren
Published: October 2024

Introduction: Sevoflurane is an extensively used anesthetic for pediatric patients; however, numerous studies showed that sevoflurane (SEVO) may cause long-term neurodevelopmental toxicity. Dexmedetomidine (DEX) has been shown to be protective against SEVO-induced neurotoxicity, but the mechanism remains unclear. The effects and mechanisms of different DEX administration routes on SEVO-induced neurotoxicity and long-term cognitive defects were determined and further investigated the role of sex in these processes. Methods: Male and female Sprague Dawley rats at postnatal day 7 (PND7) received an intraperitoneal injection of DEX (10 μg/kg) before or after exposure to 2.5% SEVO for 6 h, or before and after SEVO exposure. The respiratory and mortality rates of the pups were recorded during anesthesia. Neuroapoptosis was evaluated by TdT-mediated dUTP nick-end labeling staining. Immunohistochemistry and immunofluorescence were employed to detect the expression of caspase-3 in neuronal cells and neurons. The expression of GSK-3β and DISC1 was determined by Western blotting or RT-qPCR. Morris water maze (MWM) test was used to evaluate the learning and memory ability of rats until they were 3 weeks and 5 weeks old. Results: Compared with the control group, exposure to 2.5% SEVO resulted in increased neuroapoptosis and decreased the expression of DISC1 at levels of mRNA and protein and phosphorylated GSK-3β in the developing brain. SEVO exposure during critical neurodevelopmental periods could cause persistent cognitive defects in adolescent male and female rats and inhibited DISC1 and phosphorylated GSK-3β protein expression. The neurotoxic impacts of SEVO were lessened by the administration of DEX (10 μg/kg) before or after exposure. Conclusion: Our findings suggest that DEX (10 μg/kg) mitigates the neurotoxic effects of SEVO on the developing rat brain as well as postnatal cognitive defects by regulating the DISC1/GSK-3β signaling.