bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boosting Covalent Organic Framework Luminescence by Suppressing Nonradiative Pathways†
Authors: Liu Minghao , Cheng Yuan‐Zhe , Fu Yubin , Bi Shuai , Ding Xuesong , Han Bao‐Hang , Xu Qing , Zeng Gaofeng 
Published: December 2024

Comprehensive SummaryThe construction of luminescent two‐dimensional (2D) imine‐linked covalent organic frameworks (COFs) is a formidable challenge due to the strong interlayer stacking and bond rotations that typically suppress intramolecular charge transfer (ICT), leading to nonradiative energy dissipation. Herein, three COFs with tailored interlayer distances and bond rotations are designed to modulate the ICT behaviours. The targeted COF (TPAZ‐TPE‐COF) achieved a significantly enhanced photoluminescence quantum yield (PLQY) of 21.22% in the solid state by restricting bond rotation and enlarging the layer distance. This represents a 3.5‐fold and 530.5‐fold improvement over TPAZ‐PYTA‐COF (6.15%), which has a shortened interlayer space, and TPAZ‐PATA‐COF (0.04%), which exhibits strong bond rotations, respectively. Importantly, TPAZ‐TPE‐COF also exhibits exceptional sensing performance for iron ions, with a detection limit at the ppb level. Both experimental and theoretical analyses reveal that the prominent luminescent performance of TPAZ‐TPE‐COF is assigned to the effective suppression of nonradiative pathways, especially those arising from interlayer stacking and bond vibrations. These findings pave the way for deliberate construction of imine‐linked 2D COFs with high PL intensity, thereby expanding the portfolio of luminescent COFs with potential applications in sensing and optoelectronics.
Predictive analytics of selections of russet potatoes
Authors: Ferracina Fabiana , Krishnamoorthy Bala , Halappanavar Mahantesh , Hu Shengwei , Sathuvalli Vidyasagar 
Published: December 2024

AbstractWe explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high‐yield, disease‐resistant, and climate‐resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state‐of‐the‐art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1‐score, and Matthews correlation coefficient (MCC) for model evaluation. The top‐performing models, namely a feedforward neural network classifier (Neural Net), a histogram‐based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data‐generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data‐generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC‐ROC) and MCC. The simulation results highlight that non‐linear models like SVM and HGBC consistently show higher AUC‐ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision‐making in breeding programs.
Performance and recovery of turfgrasses irrigated with varying crop coefficients
Authors: Sevostianova Elena , VanLeeuwen Dawn , Serena Matteo , Sallenave Rossana , Leinauer Bernd 
Published: December 2024

AbstractDeficit irrigation is a water conserving practice that involves watering below an estimated evapotranspiration (ET) replacement level. Research is limited to comparing cool‐season (CS) and warm‐season (WS) turfgrass varieties grown in arid regions under varying deficit irrigation replacement levels. This study investigated the effects of five levels of reference evapotranspiration for short grass (ETOS) replacement (55%, 70%, 85%, 100%, and 115%) on the performance and fall recovery of several turfgrasses in the southwestern United States. Three years of field research evaluated green cover and visual quality of three CS Kentucky bluegrass (Poa pratensis L.) (four cultivars), tall fescue [Schedonorus arundinaceus (Schreb.)] (three cultivars), and perennial ryegrass (Lolium perenne L.) (three cultivars), and two WS turfgrasses bermudagrass (Cynodon dactylon L.) (three cultivars) and buffalograss Buchloe dactyloides (two cultivars). CS grasses required higher ETOS replacement than WS grasses to maintain acceptable quality (1–9, ≥6 = minimum acceptable) and coverage. Among CS grasses, Barserati Kentucky bluegrass maintained the best quality and green cover under deficit irrigation and demonstrated the most consistent ability to recover. Notably, bermudagrass performed well under deficit irrigation, maintaining acceptable visual quality and better green cover than CS species like Kentucky bluegrass and tall fescue at lower irrigation levels. Overall, there were significant differences among cultivars, demonstrating the importance of the selection process in drought tolerance. These findings support the promotion of drought‐resistant WS grasses to conserve water in arid regions without compromising turfgrass functionality. Future research should focus on variable and seasonal ETOS for irrigation of turfgrasses and estimating irrigation requirements.
High plant density optimizes leaf stomatal traits for accelerating the stomatal response rate at the lower cotton canopy
Authors: Li Xilin , Li Xiaoming , Zhang Tong , Xue Xiaofei , Dai Yunjing , Lei Zhangying , He Daohua 
Published: December 2024

AbstractPlants are often exposed to fluctuating light from a few seconds to a few minutes due to cloud movements, mutual shading of leaves, and change in the angle of the sun. Slow stomatal response to fluctuating light leads to carbon loss, but the influence of planting density on light fluctuation frequency and on stomatal response and carbon gain has yet to be fully explored. To fill this knowledge gap, we investigated leaf morphology, stomatal anatomy and response rate, nitrogen content, biomass, and yield under low density, moderate density, and high density (HD) of cotton cultivar (Gossypium hirsutum L.). The results showed that higher planting density significantly increased light fluctuation frequency at the lower canopy. Stomatal size significantly decreased with the increase in planting density, while total stomatal density was consistent. Stomatal density had greater plasticity of determining maximum stomatal conductance than stomatal size. Faster stomatal response rate to fluctuating light under HD was attributed to smaller and denser stomata in the abaxial leaf side. Therefore, cotton under HD treatment had faster photosynthetic induction rate under light induction, resulting in greater carbon gain. We conclude that faster stomatal response rate achieved by the optimization of stomatal anatomy, especially the abaxial side, plays a crucial role in obtaining more carbon gain, biomass, and yield under HD cotton field. This finding indicates that selecting varieties with rapid stomatal response traits and planting at appropriate densities may optimize fluctuating light use to achieve higher yields.
The antiarthritic effect of CBR‐470‐1 in hypoxic environment is to increase the level of NOD‐like receptor family pyrin domain containing 3 ubiquitination by decreasing phosphoglycerate kinase 1 activity
Authors: Duan Ao , Ma Zemeng , Shao Xiaolong , Xiong Zhencheng , Zhang Chaoyi , Liu Wenzheng , Wang Guanglin , Hu Shouye , Lin Wei 
Published: December 2024

AbstractBackgroundHypoxia can affect the occurrence and development of inflammation in humans, but its effects on the disease progression of osteoarthritis (OA) remain unclear. Synovial macrophages play an essential role in the progression of arthritis. Specifically, the activation of the NOD‐like receptor family pyrin domain containing 3 (NLRP3) in macrophages induces the secretion of a series of inflammatory factors, accelerating the progression of OA.MethodsThe effects of CBR‐470‐1 were assessed in a mouse model of OA induced by destabilization of the medial meniscus (DMM) by micro‐computed tomography imaging, Safranin‐O and Fast Green staining, immunofluorescence staining and enzyme‐linked immunosorbent assay. Western Blot analysis was used to explore the underlying mechanism of these experimental results. Additionally, a co‐culture system of THP‐1 and chondrocytes was established to investigate the impact of CBR‐470‐1 on chondrocyte proliferation, apoptosis, migration and the regulation of chondrocyte‐related proteins within the system.ResultsIn hypoxic conditions, CBR‐470‐1 significantly inhibited the progression of OA in the DMM‐induced OA mouse model, but that effect disappeared in the DMM‐induced OA phosphoglycerate kinase 1 (PGK1)fl/flLyz2‐Cre mouse model. Not only that, CBR‐470‐1 can also improve the proliferation and migration of chondrocytes, reduce the apoptosis rate of chondrocytes, and regulate the expression of chondrocyte‐related proteins in the co‐culture system of THP‐1 and chondrocytes.ConclusionsThis study conducted a series of in vitro and in vivo experiments, revealing that hypoxia plays a pro‐inflammatory role by increasing PGK1 activity and reducing the binding of the deubiquitinating enzyme ubiquitin‐specific peptidase 14 to NLRP3, thereby reducing the ubiquitination level of NLRP3. CBR‐470‐1, a specific inhibitor of PGK1, can reduce PGK1 activity to reverse the role of hypoxia in the progression of OA. These findings lay a foundation for the development of OA treatment in a hypoxic environment.Key points
Hypoxia plays a pro‐inflammatory role by increasing PGK1 activity and thereby decreasing the ubiquitination level of NLRP3.
Hypoxia plays a pro‐inflammatory role by increasing PGK1 activity, reducing the binding of the deubiquitinating enzyme USP14 to NLRP3, and reducing the ubiquitination level of NLRP3.
CBR‐470‐1 reverses the role of hypoxia in the progression of osteoarthritis.
Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy
Authors: Hua Wei , Liu Jie , Li Yue , Yin Hua , Shen Hao‐Rui , Wu Jia‐Zhu , Kong Yi‐Lin , Pan Bi‐Hui , Liang Jun‐Heng , Wang Li , Li Jian‐Yong , Gao Rui , Liang Jin‐Hua , Xu Wei 
Published: December 2024

AbstractPrecision medicine in less‐defined subtype diffuse large B‐cell lymphoma (DLBCL) remains a challenge due to the heterogeneous nature of the disease. Programmed cell death (PCD) pathways are crucial in the advancement of lymphoma and serve as significant prognostic markers for individuals afflicted with lymphoid cancers. To identify robust prognostic biomarkers that can guide personalized management for less‐defined subtype DLBCL patients, we integrated multi‐omics data derived from 339 standard R‐CHOP‐treated patients diagnosed with less‐defined subtype DLBCL from three independent cohorts. By employing various machine learning algorithms, we pinpointed eight pivotal genes linked to PCD, specifically FLT3, SORL1, CD8A, BCL2L1, COL13A1, MPG, DYRK2 and CAMK2B. Following this, we established a Programmed Cell Death Index (PCDI) utilizing the aforementioned genes and amalgamated it with pertinent clinical characteristics to formulate a predictive nomogram model for prognosis. We observed a significant correlation between the PCDI, pre‐treatment circulating tumour DNA (ctDNA) burden, minimal residual disease (MRD) status and immune features. Furthermore, our research indicated that patients with elevated PCDI scores could potentially show resistance to conventional chemotherapy treatments, yet they might derive an advantage from alternative inhibitors targeting specific signalling pathways. Conclusively, leveraging these results, we have created an online analytical tool (https://xulymphoma.shinyapps.io/PCDI_pred/) designed for the prognostic prediction of patients with less‐defined subtype DLBCL. This tool facilitates the forecasting of outcomes for these patients, enhancing the precision of their clinical management.Key points
Developing the Programmed Cell Death Index (PCDI) utilizing multiple machine learning algorithms for patients with less‐defined subtype diffuse large B‐cell lymphoma.
The difference in clinical characteristics, circulating tumour DNA burden and immune profiling between patients with distinct PCDI groups.
A potentially effective regimen was speculated for patients with high PCDI scores who tend to exhibit worse progression‐free survival.
Hybrid CNN‐GNN Framework for Enhanced Optimization and Performance Analysis of Frequency‐Selective Surface Antennas
Authors: Palanisamy SatheeshKumar , Karunanithi Sathya , Periyasamy Baskaran , Samidurai Srithar , Salau Ayodeji Olalekan 
Published: December 2024

ABSTRACTFrequency‐selective surface (FSS) antennas are critical in modern communication systems, where optimizing their design for enhanced performance is essential. However, traditional methods often struggle with the complexity of FSS structures, leading to suboptimal designs. This paper addresses these limitations by proposing a novel CNN‐GNN hybrid network (CGHN) framework for FSS antenna optimization. The proposed methodology integrates convolutional neural networks (CNNs) for efficient feature extraction of spatial patterns within FSS designs and graph neural networks (GNNs) to model the relational dependencies between unit cells. This approach ensures that both local features and global interactions are captured, leading to more accurate and optimized antenna designs. The objective is to enhance the performance of FSS antennas by leveraging the complementary strengths of CNNs and GNNs, with an emphasis on improving design accuracy and efficiency. The novelty lies in the combination of CNN's localized pattern recognition with GNN's relational learning, which together enable a comprehensive understanding of the antenna's behavior. The proposed CGHN framework achieves a 96.78% accuracy rate in predicting optimal FSS designs, with a 23.84% boost in performance due to CNN‐driven feature extraction. Additionally, implementing stochastic gradient descent with gradient clipping increased the F1 score by 15%. Compared with existing techniques, the proposed method demonstrates significant improvements in both accuracy and efficiency, making it a superior choice for FSS antenna design optimization.
Reliable Data Delivery and Load Balancing in Improved Energy Efficient RPL Routing Protocol for Low Power and Lossy Networks
Authors: Dinesh P. S. , Palanisamy C. 
Published: December 2024

ABSTRACTThe energy‐constrained nodes and tree‐like topology of Low‐Power and Lossy Networks (LLNs) frequently result in serious problems when energy bottlenecks occur. This occurrence affects the network performance in terms of node failure, lower connectivity, and higher energy consumption. This paper proposes a novel solution to these problems by integrating an Energy Efficient Multipath Routing Protocol (EM‐RPL) with a Load‐Based Energy Efficient RPL (LBEE‐RPL) protocol. To address energy bottlenecks, the proposed EM‐RPL protocol initiates the crucial mechanisms as subnode switching mechanism and an improved Trickle timer. The network's energy load is balanced by the subnode switching mechanism, which redistributes traffic away from overloaded nodes. The enhanced Trickle timer guarantees prompt identification and response to energy shortage conditions. This method enhances overall network performance while addressing the issue of data imbalance in energy consumption. An extensive simulation shows the proposed EM‐RPL significantly increases network lifetime and energy efficiency. Specifically, integrating these protocols leads to a notable reduction in power consumption and a rise in the network's operational lifespan. The important problem of energy management in LLNs is effectively resolved by this work, which offers improved performance and sustainability for a range of Internet of Things (IoT) and related fields applications.
Metal‐Free Direct Synthesis of Secondary Amides and Nitriles Using O‐(2‐Pyrimidinyl)‐N‐Boc Hydroxylamine
Authors: Divedi Ashirwad , Verma Saumya , Chandra Dinesh , Bhargav Shivam , Verma Ved Prakash , Jat Jawahar L. 
Published: December 2024

AbstractA novel hydroxylamine‐derived aminating agent, O‐(2‐pyrimidinyl)‐N‐Boc hydroxylamine (PymONHBoc), has been designed and synthesized, from readily available 2‐chloropyrimidine. This reagent demonstrates superior shelf stability and ease of handling compared to other hydroxylamine‐derived reagents. Here, we present a metal‐free method for the direct conversion of ketones and aldehydes into sec‐amides and nitriles using PymONHBoc as the aminating agent. This method efficiently converts a wide range of aliphatic and aromatic carbonyl compounds into the corresponding amides and nitriles with good to excellent yields under ambient conditions. The use of PymONHBoc is advantageous, as it facilitates the in situ generation of the activated oxime intermediate, concomitantly producing a non‐interfering byproduct.
Cs2CO3‐I2 Promoted Efficient Synthesis of Flavones and Flavanones: Total Synthesis of Narengenin and Apigenin
Authors: Arjun Chavan Kailas , Erande Rohan D. 
Published: December 2024

AbstractFlavonoids are an important class of naturally existing scaffolds known for their diverse biological activities and have been immensely synthesized using stoichiometric reagent amounts. Herein, we report a reliable, robust, one‐pot, transition metal and additive‐free protocol for the synthesis of flavones and flavanones from 2‐hydroxyacetophenone and substituted aldehydes. Our developed method utilizes Cs2CO3 as a base and iodine as an oxidant in H2O: DMSO (9 : 1) solvent system, which provides direct access to many flavones and flavanones in excellent yields under milder reaction conditions with simple yet easily available substrates. In application, naturally occurring compounds such as naringenin and apigenin have been successfully synthesized using developed protocol.
Exploring the impact of perioperative analgesia on postoperative chronic analgesic prescriptions in patients with lung cancer undergoing minimally invasive thoracic surgery: A retrospective observational study
Authors: Yabuki Shizuha , Kaiho Yu , Tarasawa Kunio , Ikumi Saori , Iwasaki Yudai , Imaizumi Takahiro , Fujimori Kenji , Fushimi Kiyohide , Yamauchi Masanori 
Published: December 2024

AbstractBackgroundLung cancer surgery is associated with a high incidence of chronic postsurgical pain (CPSP), which necessitates long‐term analgesic prescriptions. However, while essential for managing pain, these have shown various adverse effects. Current guidelines recommend using peripheral nerve blocks over epidural anaesthesia for perioperative analgesia in minimally invasive thoracic surgery (MITS). However, the impact of perioperative analgesia on chronic analgesic prescriptions remains unclear. Therefore, this study investigated chronic analgesic prescription patterns following MITS in patients with lung cancer who received either perioperative epidural anaesthesia or nerve block.MethodsWe conducted a retrospective cohort study using data from the Japanese Diagnosis Procedure Combination database. Data were extracted from patients with primary lung cancer who underwent MITS between April 2018 and March 2022. Patients were divided into two groups based on the perioperative analgesia they received: the epidural anaesthesia group and the nerve block group. We compared the proportion of analgesic prescriptions 3–6 months postoperatively between both groups using multivariable logistic regression analysis. Inverse probability of treatment weighting was used to balance the covariates between the two groups.ResultsAmong the 38,719 eligible patients, 4513 (11.6%) were prescribed postoperative analgesics. We found no significant difference in the proportion of analgesic prescriptions between the epidural anaesthesia and nerve block groups (odds ratio, 1.00; 95% confidence interval, 0.99–1.01).ConclusionsThis nationwide retrospective study suggests that the choice between perioperative epidural anaesthesia or nerve block in patients with lung cancer undergoing MITS does not influence the proportion of postoperative chronic analgesic prescriptions.
Influence of Different Taste Feed Additives on Feed Intake and Growth Performance in Growing Goats
Authors: Naveen P. , Kour Harneet , Malik Raman , Naliyapara Hardik , Gabbur Anil , Rana Parul , Goyal Amandeep 
Published: December 2024

ABSTRACTThe present study was carried out to evaluate the influence of different taste feed additives on feed intake and growth performance in Alpine × Beetal growing goats. For this, a 90‐day growth trial was conducted on 36 growing goats of 3–4 months age which were divided into six groups of six animals each. Animals in all groups were fed individually to meet the requirement for both maintenance and growth as per ICAR 2013. Individual taste feed additives were added in their concentrate mixture of total mixed ration (TMR) as food‐grade sucrose (sweet) at the rate of 75 g/kg DM (SWE), NaCl (salt) at the rate of 15 g/kg DM (SAL), food‐grade citric acid (sour) at the rate of 10 g/kg DM (SOU), urea (bitter) at the rate of 5 g/kg DM (BIT) and food‐grade monosodium glutamate (umami) at the rate of 10 g/kg DM (UMA). The study revealed significantly higher (p < 0.01) average dry matter intake (DMI) (kg/day) in SWE (0.541 ± 0.034) and SAL (0.560 ± 0.041) groups compared to CON (0.476 ± 0.039). Average daily body weight gain (g/d/animal) was significantly higher (p < 0.01) in sweet and salt taste‐supplemented groups compared to control. Body measurements including heart girth, withers height, body length and hip height were similar among six treatments. Feed conversion efficiency (kg live weight gain/100 kg DMI) and feed conversion ratio (kg DMI/kg live weight gain) were unaffected due to taste supplementation. While supplementation of sweet taste increased the digestibility of NDF and ADF, sweet‐ and salt‐supplemented groups increased DCP as well as TDN intake. It was concluded that addition of sweet and salt taste in TMR had a positive impact on feed intake and growth performance in growing goats.