bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neural ordinary differential equation‐based model predictive controller for regulating glucose concentration in a fed‐batch CHO cell bioreactor
Authors: Chiu Kuo‐Chun , Du Dongping 
Published: February 2025

AbstractChinese hamster ovary (CHO) cells are widely used in the biopharmaceutical industry to produce recombinant proteins. Effective process control is crucial for managing biomanufactured product production in response to increasing market demand. Model predictive control (MPC) is an advanced controller compared to the traditional proportional integral derivative (PID) controller for handling complex nonlinear systems. However, existing MPC controllers fail to address challenges related to control accuracy, model plant mismatch (MPM), and computational load simultaneously. Neural ordinary differential equation (ODE), capable of effectively modelling dynamics within complex systems at high computational efficiency, has the potential to tackle these limitations. This study developed a neural ODE model‐based MPC to dynamically maintain glucose concentration in a fed‐batch CHO cell bioreactor simulation system. Additionally, benchmark studies were conducted to compare the control performance of neural ODE‐MPC with neural network (NN)‐based MPC and long short‐term memory (LSTM)‐based MPC. The results demonstrate that neural ODE‐MPC can provide reliable control performance in managing glucose concentration with lower control errors, small MPM, and higher computational efficiency compared to the benchmark systems. In conclusion, neural ODE‐MPC has the potential to address MPC challenges and enhance production efficiency in future industrial applications.
Fast DNA‐Based Molecular Classifier for Cancer Diagnosis Using Freeze‐Thaw Cycling†
Authors: Cao Mengyao , Xiong Xiewei , Li Li , Pei Hao 
Published: February 2025

Comprehensive SummaryMonitoring and analyzing expression levels of multiple biomarkers in biological samples can improve disease risk prediction and guide precision medicine but suffers from high cost and being time‐consuming. Here, we construct a fast molecular classifier based on freeze‐thaw cycling that implements an in silico support vector machine (SVM) classifier model at the molecular level with a panel of disease‐related biomarkers expression patterns for rapid disease diagnosis. The molecular classifier employs DNA reaction networks as the computing module and repeated dehydration and concentration process as the driving force to implement a set of simplified mathematical operations (such as multiplication, summation and subtraction) for efficient classification of complex input patterns. We demonstrate that the fast DNA‐based molecular classifier enables precise cancer diagnosis within a short turnaround time in synthetic samples compared to those of free diffusion classifiers. We envision that this all‐in‐one molecular classifier will create more opportunities for inexpensive, accurate, and rapid disease diagnosis, prognosis and therapy, particularly in emergency departments or the point of care.
Modular Synthesis and Cytotoxicity Evaluation of Dragocins A—C and Their Analogues: Discovery of a Potential Anticancer Agent
Authors: Wang Ziqiang , Wang Jianjun , Wang Peng , Song Ni , Liu Xue‐Wei , Li Ming 
Published: February 2025

Comprehensive SummaryDragocins A—C are structurally unique marine natural products featuring an uncommon tri‐oxa‐tricyclic[6.2.1]undecane moiety. However, their extremely low natural abundance has hindered extensive screening of their bioactivities. We hereby describe an efficient and modular approach to synthesizing dragocins A—C and their analogues using commercially available and inexpensive anisomycin and D‐ribosyl thioglycoside derivative as the starting materials. A key feature of our synthesis is the construction of the uncommon tri‐oxa‐tricyclic[6.2.1]undecane skeleton. This challenging architecture is achieved by the stereocontrolled formation of the β‐ribofuranosidic bond and the DDQ (2,3‐dichloro‐5,6‐dicyano‐1,4‐benzoquinone)‐promoted intramolecular cross‐dehydrogenative etherification at the benzylic position. Our synthesis is also characterized by the successful installation of a chlorine atom and a methoxy group at the tertiary C‐4' position via a late‐stage silver‐catalyzed decarboxylative chlorination reaction and an electrophilic etherification reaction of the enol intermediate. Cytotoxicity evaluations of the synthesized compounds revealed demethyl dragocin A, the N‐demethylated derivative of dragocin A, as a potential anticancer candidate due to its strong cytotoxicity against A549 lung, HCT116 colorectal and MCF7 breast cancer cell lines. This work also demonstrated the preliminary structure‐activity relationship of this compound, setting a solid foundation for developing novel anticancer candidates.
Super Resolved Structural Imaging of Mitochondrial Network using Orange Emissive Carbon Nanodots as Fluorescent Probe
Authors: Garg Richa , Kundu Runmi , Kaushik Kush , Salam Abdul , Kanti Nandi Chayan 
Published: February 2025

AbstractSuper‐resolution microscopy (SRM), coupled with appropriate small and photostable fluorescent probes, has revolutionized the ability to study organelle dynamics with unprecedented spatial and temporal resolution. An increasing trend of designing nanomaterial probes that have unprecedented advantages over organic molecular probes has become the frontier in SRM based imaging of subcellular organelles. Herein, we report the development of orange‐emissive fluorescent carbon nanodots (CNDs) via a one‐pot synthesis that has excellent capabilities to target mitochondria. Spectroscopic analysis confirms the presence of guanidine on the surface of CNDs, thus facilitating its ability to selectively target mitochondria. The CNDs were highly capable for the super‐resolution radial fluctuation (SRRF) imaging of the mitochondrial network and the morphology. The synthesized CNDs exhibited high photostability, biocompatibility, and non‐toxicity, which could be used for their application in mitochondria‐based imaging modalities.
On the Read‐Shockley energy for grain boundaries in 2D polycrystals
Authors: Fortuna Martino , Garroni Adriana , Spadaro Emanuele 
Published: February 2025

AbstractIn the 50's Read and Shockley proposed a formula for the energy of small angle grain boundaries in polycrystals based on linearized elasticity and an ansatz on the distribution of incompatibilities of the lattice at the interface between two grains. The logarithmic scaling of this formula has been rigorously justified without any ansatz on the geometry of dislocations only recently in an article by Lauteri and Luckhaus. In the present paper, building upon their analysis, we derive a two dimensional sharp interface limiting functional starting from the nonlinear semi‐discrete model introduced in Lauteri and Luckhaus: the line tension we obtain via ‐convergence depends on the rotations of the grains and the relative orientations of the interfaces, and for small angle grain boundaries has the Read and Shockley logarithmic scaling.
Stability of perfectly matched layers for Maxwell's equations in rectangular solids
Authors: Halpern Laurence , Rauch Jeffrey 
Published: February 2025

AbstractPerfectly matched layers are extensively used to compute approximate solutions for Maxwell's equations in using a bounded computational domain, usually a rectangular solid. A smaller rectangular domain of interest is surrounded by layers designed to absorb outgoing waves in perfectly reflectionless manner. On the boundary of the computational domain, an absorbing boundary condition is imposed that is necessarily imperfect. The method replaces the Maxwell equations by a larger system, and introduces absorption coefficients positive in the layers. Well posedness of the resulting initial boundary value problem is proved here for the first time. The Laplace transform of a resulting Helmholtz system is studied. For positive real values of the transform variable , the Helmholtz system has a unique solution from a variational form that yields limited regularity for rectangular domains. When is not real the complex variational form loses positivity. We smooth the domain and, in spite of this loss, construct solutions with uniform estimates. Using the regularity, we deduce Maxwell from Helmholtz, then remove the smoothing. The boundary condition at the smoothed boundary must be carefully chosen. A method of Jerison‐Kenig‐Mitrea is extended to compensate the nonpositivity of the flux.
On Dynamics of Basic Network Creation Games With Non‐Uniform Communication Interest
Authors: Dresler Maxime , Mansour Sanaï , Talhaoui Safaâ , Yamauchi Yukiko , Tixeuil Sébastien 
Published: February 2025

ABSTRACTWe consider the network construction process by selfish players. Each player is associated with a vertex of a communication graph and can simultaneously remove one incident edge and add a new incident edge. Each player is interested in a subset of players and the goal of each player is to minimize the average or maximum distance to these players. Starting from a given initial communication graph, a sequence of selfish edge swaps generates an evolution of the communication graph. Due to non‐uniform communication interest, this game may converge to a disconnected Nash equilibrium, which may attain infinite social costs. In this paper, we focus on the dynamics of this game. We first give theoretical analysis such as the existence of a best response cycle and a sufficient condition for keeping connectivity in dynamics. We then present simulation results to show the ratio of Nash equilibria with infinite cost, diameters of Nash equilibria, social cost, price of anarchy, price of stability, and convergence time.
Recursive Hybrid Compression for Sparse Matrix‐Vector Multiplication on GPU
Authors: Zhao Zhixiang , Wu Yanxia , Zhang Guoyin , Yang Yiqing , Hong Ruize 
Published: February 2025

ABSTRACTSparse Matrix‐Vector Multiplication (SpMV) is a fundamental operation in scientific computing, machine learning, and data analysis. The performance of SpMV on GPUs is crucial for accelerating various applications. However, the efficiency of SpMV on GPUs is significantly affected by irregular memory access patterns, high memory bandwidth requirements, and insufficient exploitation of parallelism. In this paper, we propose a Recursive Hybrid Compression (RHC) method to address these challenges. RHC begins by splitting the initial matrix into two portions: an Ellpack (ELL) portion and a Coordinate (COO) portion. This partitioning is followed by further recursive division of the COO portion into additional ELL and COO portions, continuing this process until predefined termination criteria, based on a percentage threshold of the number of nonzero elements, are met. Additionally, we introduce a dynamic partitioning method to determine the optimal threshold for partitioning the matrix into ELL and COO portions based on the distribution of nonzero elements and the memory footprint. We develop the RHC algorithm to fully exploit the advantages of the ELL kernel on GPUs and achieve high thread‐level parallelism. We evaluated our proposed method on two different NVIDIA GPUs: the GeForce RTX 2080 Ti and the A100, using a set of sparse matrices from the SuiteSparse Matrix Collection. We compare RHC with NVIDIA's cuSPARSE library and three state‐of‐the‐art methods: SELLP, MergeBase, and BalanceCSR. RHC achieves average speedups of 2.13, 1.13, 1.87, and 1.27 over cuSPARSE, SELLP, MergeBase, and BalanceCSR, respectively.
Research on Multi‐Scale Parallel Joint Optimization CNN for Arrhythmia Diagnosis
Authors: Chen Wenping , Wang Huibin , Chen Zhe , Zhang Lili 
Published: February 2025

ABSTRACTThe morphological characteristics of electrocardiograms (ECGs) serve as a fundamental basis for diagnosing arrhythmias. Convolutional neural networks (CNNs), leveraging their local receptive field properties, effectively capture the morphological features of ECG signals and have been extensively employed in the automatic diagnosis of arrhythmias. However, the variability in the duration of ECG morphological features renders single‐scale convolutional kernels inadequate for fully extracting these features. To address this limitation, this study proposes a multi‐scale parallel joint optimization convolutional neural network (MPJO_CNN). The proposed method utilizes convolutional kernels of varying scales to extract ECG features, further refining these features via parallel computation and implementing a joint optimization strategy to enhance classification performance. Experimental results demonstrate that on the MIT‐BIH arrhythmia database, this method not only achieved state‐of‐the‐art performance, with an accuracy of 99.41% and an F1 score of 98.09%, but also showed high sensitivity to classes with fewer samples.
A Robust Watermarking for Camera‐Captured Images Using Few‐Shot Learning and Simulated Noise Layer
Authors: Yuan Guoquan , Zhao Xinjian , Zhang Shuaiqi , Chen Shi , Wei Shanming 
Published: February 2025

ABSTRACTWith the rise of social media and the spread of a large number of pictures on the Internet, protecting data privacy and verifying copyright has become hot research. A common method is to use digital watermarking. However, the existing blind watermarking methods only consider embedding the watermark in the image itself and ignore the fact that the attacker can remove the watermark through other shooting devices. Therefore, to solve this problem, we propose an image watermarking method based on few‐shot learning. We use an autoencoder to learn the embedding and extraction of watermarks. Then, we propose a framework named Simulated Candid Shooting Layer (SCSL). The SCSL simulates a variety of candid scenes as noise data using meta‐learning and enhances the robustness of image watermarking. Experiments show that the proposed method is superior to the state of the art in watermarking technologies in both robustness and invisibility of watermarking. Specifically, it achieved an improvement of over 8% in evaluation metrics against JPEG attacks. The proposed SCSL framework further enhanced these metrics by more than 5%.
Psychosocial Factors Associated With Posttraumatic Stress Disorder Symptom Clusters in a Sample of Women Survivors of Intimate Partner Violence
Authors: Bellot Valenzuela Ana , Montorio Cerrato Ignacio , Muñoz Rivas Marina 
Published: February 2025

ABSTRACTThe DSM‐5 classifies posttraumatic stress disorder (PTSD) symptomatology into four distinct clusters and numerous studies have examined the psychosocial risk factors predicting these clusters across various types of trauma. However, no research has specifically explored the unique predictors of PTSD clusters in women survivors of intimate partner violence (IPV) This retrospective study analysed the DSM‐5‐proposed psychosocial predictors of PTSD symptom clusters (severity of violence, previous trauma, social support, emotional regulation, coping strategies and blame) in 333 women who had filed a police report for IPV. Through linear step regression analysis, five models were estimated for the four clusters and the PTSD diagnosis dissociation specifier. The findings showed both common and specific factors associated with the different PTSD clusters. Unsatisfactory emotional processing and negative self‐focussing emerged as the predominant factors common to PTSD clusters and, to a lesser extent, emotional impoverishment and emotions of guilt. Childhood trauma was identified as a risk factor in all clusters, although its influence was attenuated when emotional regulation was considered. The severity of violence was a specific predictor for the intrusion cluster, and emotional avoidance predicted the PTSD cluster of avoidance symptoms. Social support acted as a protective factor for the cluster of mood disorders. The adjusted R2 for the models ranged from 0.23 to 0.45. Taken together, the results highlight the need to distinguish specific symptom categories within the overall diagnosis of PTSD and offer an empirical perspective for better understanding and more accurate treatment for women survivors of IPV with PTSD.
KJA: Kookaburra Jellyfish Algorithm Based Task Offloading in UAV‐Enabled Mobile Edge Computing Network
Authors: Umarji Anand R. , Chouhan Dharamendra 
Published: February 2025

ABSTRACTMobile edge computing (MEC) is extensively utilized for supporting diverse mobile applications and the Internet of Things (IoT). One of MEC's prime operations is utilizing unmanned aerial vehicles (UAVs) included with the MEC servers for providing computational aids for offloaded tasks by mobile users in temporal hotspot regions or a few emerging situations like sports areas or environmental disaster regions. However, despite the various merits of UAVs executed with MEC servers, it is constrained by their insufficient sensible energy consumption and computational resources. Furthermore, owing to the complication of UAV‐aided MEC systems, energy consumption optimizations and computation resource optimizations cannot be obtained better in conventional optimization schemes. In this research, the kookaburra jellyfish algorithm (KJA) is presented for task offloading in a UAV‐enabled MEC network. The main objective is to enhance the efficiency of task offloading in UAV‐enabled MEC networks by optimizing energy consumption, computational resources, and communication time using the KJA. Initially, the UAV‐enabled MEC network model is simulated. Next, task computation is performed, and thereafter, task uploading is carried out. Then, task offloading is executed using KJA with consideration of multiobjective models, namely, energy consumption, communication time, and cost. Moreover, KJA is devised by integrating kookaburra optimization algorithm (KOA) with jellyfish search optimizer (JSO). Afterward, the task offloading process and data transmission are conducted. In addition, KJA obtained minimum energy, load, and time of 0.448 J, 0.122, and 1.036 s.
8 × 200 Gbps Hybrid PON and Digital Filter Multiple Access Incorporating Fiber‐FSO Link Impairments in a Wheel Architecture
Authors: Kumari Meet , Arya Vivek 
Published: February 2025

ABSTRACTDigital filter multiple access passive optical network (DFMA‐PON) is adopted in recent years as it offers the high bandwidth, elastic network slicing, low latency, fixed data rate, and massive end‐user comparability. To overcome limited system capacity, low transmission rate and fiber fault in existing DFMA‐PONs, a wheel architecture based full‐duplex 8 × 200 Gbps DFMA‐PON integrated system using fiber and free space optics (FSO) link is presented in this paper. Results depict that maximum FSO channel range can be attained up to 2600 m together with 50 km fiber range under weak‐to‐strong turbulent, haze, rain, fog, and snow conditions. Besides, faithful fiber reach of 200 km can be obtained with fixed 100 m FSO distance at receiver sensitivity of −17.2 dBm and 1.5 dB power penalty. System can support 230 numbers end units at high optical signal to noise ratio of 29–88 dB with 50–200 Gbps throughput, together with high split ratio of 256 to −3.2 dB high gain as well as 2 dB noise figure. In addition, the comparative analysis with the previous work reveals that the proposed architecture offers optimum results than existing PONs. This system helps to enhance the disaster resilience with high network security, reliability, and survivability of 5G based networks.
Postmortem Redistribution of Oxycodone
Authors: Defraia Beatrice , Focardi Martina , Aprile Anna , Vogliardi Susanna , Bianchi Ilenia , Menozzi Lorenzo , Favretto Donata 
Published: February 2025

ABSTRACTThe abuse of oxycodone (OC) as a “recreational” drug has increased in the last two decades the risk of fatalities. We report two drug‐related deaths in which OC intoxication was considered the cause of death. Two brothers, a 19‐year‐old male (Subject 1) and a 27‐year‐old male (Subject 2), were found dead in their bedroom, lying on their beds. They were testified as alive in the morning, both deeply sleeping and loudly snoring in their beds; they were found dead later in the afternoon. On death scene investigation, two packs of 40 mg OxyContin extended release and one alprazolam blister were found. The external examination was performed 72 h after death with the collection of blood from femoral vein, vitreous humor, and urine samples. There were no trace of injection and no external signs of injury. A complete autopsy was performed 10 days after death with the collection of peripheral blood from the femoral vein; central blood from the right ventricle; urine; gastric contents; and bile, adipose tissue, kidney, liver, brain, skeletal, and cardiac muscle tissue samples. The toxicological ascertainment evidenced the presence of OC, alprazolam, and bromazepam in fluids and tissues. For Subject 1, the concentration of OC in peripheral blood collected 72 h after death (0.33 mg/L) was similar to the concentration in vitreous humor (0.41 mg/L); vitreous humor to peripheral blood ratio was 1.24. Ten days after death, OC levels were more than 10 times higher in peripheral blood (5.14 mg/L) and about six times higher compared to central blood specimen (1.78 mg/L), while OC levels in urine were, as expected, analogous. For Subject 2, OC concentration in peripheral blood collected 72 h after death (0.50 mg/L) was similar to vitreous humor (0.87 mg/L). At Day 10 after death, OC levels were four times higher in peripheral blood (2.10 mg/L) while levels in central blood were lower (0.40 mg/L). OC concentration in urine was substantially similar at the two times of collection. OC levels in gastric contents were quite high (more than 50 mg/L). The analyses of specimens collected at two different times clearly demonstrate variation of blood OC concentrations with time. Postmortem redistribution from organs was also evidenced by high concentrations of OC in tissues such as the liver and kidney.
Application of DNA Methylation–Based Age Estimation to Construct an Age Structure of Humpback Whales in a Newly Emerged Wintering Ground Around Hachijojima Island, Tokyo Metropolis, Japan
Authors: Igarashi Kohei , Tanabe Atsushi , Sahara Hiroeki , Nozaki Reiko , Kondo Hidehiro , Katsumata Taiki , Tamura Shingo , Yamakoshi Tadashi , Mori Mizuki , Miyagi Marin , Nakamura Gen , Kanda Naohisa , Murase Hiroto 
Published: February 2025

ABSTRACTUsing a noninvasive DNA methylation (DNAm)–based age estimation method, we investigate the age structure of humpback whales that newly emerged around Hachijojima Island, Tokyo Metropolis, Japan to uncover the role of this area for this species. We measured DNAm frequencies at three age‐related genes (GRIA2, CDKN2A, and TET2) from 26 biopsy skin samples of 21 unique humpback whales (15 males and 6 females) randomly collected in the winters of 2018–2021 and estimated their ages using the known age estimation model for humpback whales. The estimated ages of the 21 individuals were 2.95–30.40 years old with a mean of 12.02, and the resulting age structure in 5‐year increments was roughly normally distributed with a peak at 10.00–14.99 class, suggesting the dominance of young adult males in this water. The observations (young males, male aggressive behavior for mating, whale song, and mother–calf pair) indicated that newly emerged humpback whales appeared to utilize Hachijojima Island as their new wintering ground, expanding the northern limit of the wintering area in the western North Pacific from previously known.