bluuebunny/crossref_metadata_2025 huggingface dataset:
Achieving CO2 Emissions Reduction by Overcoming Well Integrity Challenges in High Pressure and Narrow Window Environments: A Case Study of a Giant Middle East Deep Gas Field
Authors: Ovwigho Efe Mulumba , Almuallim Mustafa , AlAwfi Mohammed
Published: November 2024

While drilling the 12″ section, a water bearing formation is encountered prior to reaching the target gas reservoir formation. This formation is sporadically-charged across the field requiring a KMW up to 21 ppg. This poses major well integrity challenges as it becomes critical to avoid losses in the resulting narrow mud window and ensuring proper cement placement. Inability to predict the mud window makes it impossible to define the drilling strategy to implement.

To understand the drilling challenges, in-depth offset wells analysis was performed. Based on mud weights required to drill across the reference formation, the heat-map for historical KMW was created based on confirmed well control events. It was difficult to predict formation-flow potential. Field geomechanics studies was then carried out to correlate the mapping done earlier. Once possibility of encountering abnormally pressured formation is flagged, in order prevent drilling risks such as loss circulation and poor cementing placement, proactive measures such as: Improved influx monitoring, drilling/cementing fluids optimization, liner-and-tieback system implementation, Managed Pressure Drilling/Cementing, optimized casing design were put in place.

The integrated approach led to quick influx detection, proper definition of mud window, i.e. Pore Pressure and Fracture Gradient together, helped to prevent the losses, design of fit-for-purpose bridging strategy to ensure full drilling fluid column at all time while avoiding the cost associated with fluid losses. Drilling the section with Managed Pressure Drilling system (MPD) and low mud weight led to achievement of high ROP leading to substantial time saving. The Liner string was run and Managed Pressure Cementing (MPC) was implemented to manage the equivalent circulating density (ECD), avoid losses and ensure good zonal isolation. Overall non-productive time was reduced by 40% as compared to the offset wells in the area.

Integrated drilling approach delivers great gains when there is good understanding of the well integrity challenges and solutions are tailored to solve identified problems.
Optogenetic Induction of Subcellular Ca2+ Events in Megakaryocytes and Platelets Using a Highly Ca2+-conductive Channelrhodopsin
Authors: Zhang Yujing , Yu-Strzelczyk Jing , Xu Congfeng , Shen Chengxing , Nagel Georg , Gao Shiqiang , Bender Markus
Published: November 2024

Calcium signaling is crucial across various cell types, but its spatiotemporal dynamics remain difficult to study due to limited methods. Optogenetics, with its high precision, can address this challenge. In this study, we introduced the channelrhodopsin variant ChR2 XXM2.0, which exhibits high light sensitivity and enhanced Ca2+ conductance in Xenopus oocytes, into bone marrow-derived megakaryocytes through viral transduction, aiming to clarify the poorly understood role of Ca2+ dynamics in these cells. ChR2 XXM2.0 expression was confirmed in megakaryocyte membranes, and its functionality validated through whole-cell patch-clamp and calcium imaging. Localized activation of ChR2 XXM2.0 at the cell periphery induced cell polarization, dependent on localized calcium influx, myosin IIA, and integrin αIIbβ3-fibrinogen interaction. Furthermore, we generated a transgenic mouse line with Pf4-Cre-dependent expression of ChR2 XXM2.0, enabling optogenetic manipulation of anucleate blood platelets via light-triggered calcium signaling. Illumination induced phosphatidylserine and P-selectin exposure in spread platelets. Our results highlight the importance of asymmetric subcellular calcium events in megakaryocyte polarity and demonstrate the feasibility of manipulating platelet function using optogenetics. Taken together, our study introduces the ChR2 XXM2.0 construct and its corresponding Cre-dependent transgenic mouse line as powerful tools for manipulating subcellular Ca2+ signaling, with potential applications for different cell types.
Root productivity contributes to carbon storage and surface elevation adjustments in coastal wetlands
Authors: Conroy Brooke M , Kelleway Jeffrey J , Rogers Kerrylee
Published: November 2024

Background and aims: Additions of organic matter in coastal wetlands contributes to blue carbon sequestration and adjustment to sea-level rise through vertical growth of substrates. To improve models of carbon sequestration and adaptation to sea-level rise, data of root mass and volume additions across tidal gradients are required. This study aims to characterise the influence of vegetation zonation and tidal position on root mass and volume dynamics within substrates. Methods: The root ingrowth technique was coupled with sediment cores to quantify below-ground root mass and volume production, standing stocks and turnover across two years to 90 cm depth at Kooweerup, Victoria, Australia. Measurements of vertical accretion quantified mineral sediment additions at the surface. Results: The results indicate a complex non-linear relationship between root production and tidal position, which is driven by variation in vegetation structure across mangrove (442–3427 g fine root mass m-2 yr-1), saltmarsh (540–860 g m-2 yr-1) and supratidal forest (599 g m-2 yr-1) zones. Fine root volume additions ranged from 274 to 4055 cm3 m-2 yr-1 across sampling locations. Root production was greatest for older mangroves and tidally defined optimal zones of production were evident for mangrove and saltmarsh. The live rooting zone extended beyond depths typically measured in studies, and for forested sampling locations, live roots were found as deep as 1.0 m. Conclusion: These data can be used to improve highly parameterised models accounting for carbon sequestration and substrate vertical adjustment across an intertidal gradient by quantifying both root mass and volume additions across the live rooting zone.
Motivate or suppress: The dual effects of leader bottom-line mentality on employee innovation behavior
Authors: Luo shiwen , Tong David Yoon Kin
Published: November 2024

Background
In the VUCA era, employee innovation behavior is critical to a enterprise success. In China's high power distance and collectivist culture, employee innovation behavior is often influenced by leadership authority, leading to a division between proactive and reactive innovation behavior, with each having a different effect on innovation performance. Innovation is influenced not only by leadership type but also by leadership mindset. As a unidimensional approach focused on bottom-line profits while neglecting other important factors, leader bottom-line mentality (LBLM) and its effect on employee innovation behavior, especially on proactive and reactive innovation, has yet to be thoroughly explored. Understanding this dual influence can help balance short-term profit goals with long-term innovation development.
Methods
This study employed a two-stage survey method, conducting a questionnaire survey with employees from 13 innovation-driven enterprises, ultimately collecting 351 valid responses. Using SPSS and MPLUS software, the data were analyzed through reliability and validity tests, confirmatory factor analysis, descriptive statistics, and linear regression to validate the proposed research hypotheses.
Results
the study finds that LBLM has a significantly negative effect on employee proactive innovation behavior but a positive effect on reactive innovation behavior. Moreover, employees' willingness to take risks mediates the relationship between LBLM and employee innovation behavior. At the same time, intrinsic work values negatively moderate the relationship between LBLM and Willingness to take risks, enhancing proactive innovation behavior and reducing reactive innovation behavior. On the other hand, extrinsic work values positively moderate the relationship, enhancing reactive innovation behavior and reducing proactive innovation behavior.
Conclusion
As a unidimensional mentality, LBLM has a double-edged effect on employee innovation behavior: it positively predicts reactive innovation behavior while negatively predicting proactive innovation behavior. However, this effect is moderated by work values; intrinsic work values weaken the double-edged effect, whereas extrinsic work values enhance its influence.
Microscopic parametrizations for gate set tomography under coloured noise
Authors: Viñas Pablo , Bermudez Alejandro
Published: November 2024

Gate set tomography (GST) allows for a self-consistent characterization of noisy quantum information processors (QIPs). The standard device-agnostic approach treats the QIPs as black boxes that are only constrained by the laws of physics, attaining full generality at aconsiderable resource cost: numerous circuits built from the gate set must be run in order to amplify each of the gate set parameters. In this work, we show that a microscopic parametrization of quantum gates under time-correlated noise on the driving phase, motivated by recent experiments with trapped-ion gates, reduces the required resources enabling a more efficient version of GST. By making use of the formalism of filter functions over the noise spectral densities, we discuss the minimal parametrizations of the gate set that include the effect of finite correlation times and non-Markovian quantum evolutions during the individual gates. We compare the estimated gate sets obtained by our method and the standard long-sequence GST, discussing their accuracies in terms of established metrics, as well as showcasing the advantages of the parametrized approach in terms of the sampling complexity for specific examples.
Intelligent Adaptive Service Grid Architecture Design and Performance Optimization for Future Networks
Authors: Hu YuFeng , Liu MinMin
Published: November 2024

With the development of future networks, the popularization of technologies such as 5G and the Internet of Things (IoT) has led to new characteristics of network environments with high dynamics, low latency, and complexity. Traditional service grid architectures have limitations in coping with the dynamics and complex traffic management of future networks, such as increased latency and inflexible traffic management. This study aims to design an intelligent and adaptive service grid architecture to optimize the performance to cope with the new challenges in future networks. To address the network routing optimization problem, this study uses deep Q-learning algorithms to achieve intelligent routing, which effectively reduces the network delay and packet loss rate. To address the complexity of traffic management in large-scale distributed systems, a dynamic traffic management module combining convolutional neural networks and long and short-term memory networks is designed to improve the accuracy of traffic prediction. To enhance network adaptability and fault recovery, the study introduces a network resilience enhancement module, which ensures service continuity under high load and fault conditions. In addition, efficient transmission and low resource consumption under multiple network protocols are realized by the design of protocol adaptive module. Experimental evaluation of the entire optimized architecture shows that this intelligent service grid architecture exhibits excellent performance in future network environments. The intelligent routing module effectively reduces network delay and packet loss, the dynamic traffic management module improves the accuracy of traffic prediction, the network resilience enhancement module ensures service continuity under high load and fault conditions, and the protocol adaptation module demonstrates efficient transmission and low resource consumption under multiple network protocols. Through the optimal design of the service grid architecture and the introduction of intelligent technologies, the performance and adaptability of service grids in future network environments are successfully enhanced, and the deficiencies faced by traditional service grids in dynamic network environments are addressed. This research provides important technical support and development direction for intelligent service grids in future networks.
Predicting 90-day mortality in patients with HBV-ACLF using machine learning tools
Authors: Liu Juan , Zhu Wentao , Deng Ting , Zhu Yin , Xu Qinglang , Shi Pei , Liang An , Wang Yuna , Fu Jiwei , Wu Xiaoping
Published: November 2024

Background
Acute chronic liver failure (ACLF) is characterized by a systemic inflammatory response, mainly associated with hepatitis B virus (HBV) in the Asia-Pacific region, and has a high mortality rate. We aimed to develop a stable and feasible prognostic prediction model based on machine learning (ML) tools to predict 90-day mortality in patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF).
Method
Clinical data from 573 patients with HBV-ACLF across two hospitals were retrospectively collected. Prognostic models of HBV-ACLF were constructed using support vector machine (SVM), decision tree (DT), random forest (RF), K nearest neighbour (KNN), least absolute shrinkage selection operator (LASSO), and logistic regression (LR). Model performance metrics included accuracy, area under the (AUC) receiver operating characteristic curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Results
In the training cohort, the RF prediction model demonstrated significantly higher AUC, sensitivity, specificity, PPV, and NPV than the LASSO, LR, SVM, DT, and KNN prediction models. However, the AUC of RF in the validation cohort was 0.728, with a decline in accuracy, specificity, and PPV to 0.688, 0.545, and 0.655, respectively. In the training cohort, the LASSO model had the lowest PPV at 0.739, while the KNN model had the lowest sensitivity at 0.694. In the testing and validation cohorts, the SVM and DT models exhibited the lowest sensitivity, both at 0.581. Although LR performed less effectively than RF in the training cohort, it outperformed the RF model in the testing and validation cohorts.
Conclusions
In summary, the LR predictive model demonstrates higher predictive efficacy and greater stability, making it more practical for clinical treatment decision-making.
Alcohol consumption in patients with hypertension in primary care comparing Phosphatidylethanol and AUDIT – Cross-sectional study
Authors: Thurfjell Åsa , Hagströmer Maria , Ivarsson Charlotte , Norrman Anders , Adami Johanna , Lundh Lena , Hasselström Jan
Published: November 2024

Background
Hazardous alcohol use often goes unidentified in management of hypertension. The aim was to describe alcohol consumption using the alcohol biomarker Phosphatidylethanol (PEth) and the Alcohol Use Disorders Identification Test (AUDIT) in relation to hypertension (controlled, uncontrolled, and treatment resistant). Additionally, analyse the correlation between PEth and AUDIT and compare their performance in identifying hazardous alcohol use.
Methods
Cross-sectional study of patients with hypertension (ICD-code I10.9) from primary care in Sweden (2022–2024). A random sample of 270 participants from three groups of hypertension, mmHg, (controlled < 140/<90, uncontrolled ≥ 140/≥90, and treatment resistant ≥ 140/≥90 with at least three antihypertensive drugs regardless of class) was included. Data on alcohol consumption were collected during clinical hypertension check-up. In relation to three groups of hypertension, prevalence of alcohol consumption with PEth µmol/L (< 0.05, 0.05–0.3, and > 0.3) and AUDIT points (0–7, 8–15, and 16–40) and hazardous alcohol use with PEth (≥ 0.120 µmol/L) and AUDIT (8p), was calculated. The Spearman rank correlation coefficient was calculated between PEth values and AUDIT scores.
Results
Mean age 67 ± 11 years, 42% were women. Using PEth, approximately 40% in all groups of hypertension had “no/low/sporadic” consumption according to PEth. Using AUDIT, about 85% in all groups of hypertension did not have hazardous alcohol use. With PEth, the prevalence of “high and regular consumption” was 6.4% in controlled hypertension, 5.3% in uncontrolled hypertension, and 19.2% in treatment-resistant hypertension (p = 0.027 controlled hypertension vs treatment resistant hypertension, p = 0.013 uncontrolled hypertension vs treatment resistant hypertension). In the entire study population, the prevalence of hazardous alcohol with PEth was 23.7% (men 27%, women 19.1%, p = 0.138) and with AUDIT 12.4% (men 17.1%, women 6.1%, p = 0.008). The Spearman rank correlation coefficient between PEth values and AUDIT scores was 0.590, p < 0.001. PEth identified 14.7% with hazardous alcohol use that AUDIT missed, while AUDIT identified 3.5% that PEth did not identify.
Conclusions
PEth identified higher alcohol consumption and higher prevalence of hazardous alcohol use, compared to AUDIT. The results suggest that PEth provides valuable information about alcohol consumption, and highlights the importance of identifying alcohol use, especially in patients with treatment resistant hypertension and in men.
Trial registration
Retrospectively registered in Clinical Trials, SLSO2022-0143, 2022-12-10.
Holocene shifts in marine mammal distributions around Northern Greenland revealed by sedimentary ancient DNA
Authors: Schreiber Lennart , Ribeiro Sofia , Jackson Rebecca , Kvorning Anna , Nota Kevin , O'Regan Matt , Pearce Christof , Seersholm Frederik , Seidenkrantz Marit-Solveig , Zimmermann Heike , Lorenzen Eline
Published: November 2024

Arctic marine ecosystems have undergone notable reconfigurations in response to Holocene environmental shifts. Yet our understanding of how marine mammal occurrence was impacted remains limited, due to their relative scarcity in the fossil record. We reconstructed the occurrence of marine mammals across the past 12,000 years through genetic detections based on sedimentary ancient DNA from four marine sediment cores collected around Northern Greenland, and integrated the findings with local and regional environmental proxy records. Our findings indicate a close association between the establishment of marine mammals at densities detectable in marine sediments and the deglaciation of marine environments at the onset of the Holocene. Further, we identified air temperature as a significant driver of community change across time. Several marine mammals were detected in the sediments earlier than in the fossil record, for some species by several thousands of years. During the Early-to-Mid Holocene, a period of past warmer climate, we recorded northward distribution shifts of temperate and low-arctic marine mammal species. Our findings provide unique, long-term baseline data on the occurrence of marine mammals around Northern Greenland, providing novel insights into past community dynamics and the effects of Holocene climatic shifts on the region’s marine ecosystems.
Investigating the intrinsic factors related with anterior disc displacement in temporomandibular disorder: a preliminary MRI study
Authors: Wang Botao , Wu Mei , Chen Zhiye
Published: November 2024

To observe the structure of temporomandibular joint (TMJ) in patients with TMD by magnetic resonance imaging (MRI), and to investigate the related factors of anterior disc displacement in patients with TMD.Which were classified into TMD without displacement group (97 TMJs), anterior displacement (147TMJs, including anterior displacement with reduction 69 TMJs and without reduction 78 TMJs), the observed variables were focused on the bone structures of TMJ ( the depth, the anteroposterior diameter, the index of TMJ fossa, the morphology, location, medial-lateral diameter, anteroposterior diameter and the index of TMJ condyle) and the other structures indexes involved in the temporomandibular movement (mouth opening movement range, soft tissue of bilaminar region, superior band of the bilaminar zone, morphology and signal of the lateral pterygoid muscle(LPM), joint effusion, osteoarthritis). The three groups were subjected to one-way analysis of variance and chi-square test, while binary logistic regression analysis was employed to establish a regression model and construct the receiver operating characteristic curve. The present study demonstrated that various structural and clinical factors, particularly the altered bone structure of the TMJ, hypertrophy of the LPM, and joint effusion, significantly contribute to the ADD in patients with TMDs.
Perceived teacher support profiles and mathematics engagement, mathematics anxiety, mathematics attitude: A latent profile analysis approach
Authors: Zhou Yu , Jing Bin , Pi Zhongling , Zhang Jing , Han Yifei , Ma Hongliang
Published: November 2024

Background
The critical role of perceived teacher support in mathematics learning has been widely recognized, but individual student differences have often been overlooked in previous studies.
Methods
This study adopts a person-centered approach to study the perceived teacher support in the process of mathematics learning, uses latent profile analysis to classify 1314 students, and uses one-way analysis of variance to explore the differences between students with different profiles. Further, a mediation model is established to explore the relationship between different perceived teacher support profiles and and mathematics engagement, mathematics anxiety, and mathematics attitude.
Results
Latent profile analysis identified three profiles: low (5.78%), medium (44.29%), and high perceived teacher support (49.93%). There were no significant differences in gender or grade among students with different profiles. But they show significant differences in mathematics engagement, mathematics anxiety, and mathematics attitude. Further analysis revealed that there are differences in behavioral engagement, cognitive engagement, emotional engagement, classroom anxiety, learning motivation, and learning strategies. The mediation effect analysis showed that students with higher perceived teacher support exhibited stronger mathematics attitudes, which in turn increased their mathematics engagement. However, mathematics anxiety did not serve as a mediating factor.
Conclusion
The study showed that individual differences in perceived teacher support affect students’ mathematics engagement mathematics anxiety, and mathematics attitudes. Students who perceive a higher level of teacher support show a more positive attitude toward mathematics, which promotes mathematics engagement. This study provides empirical evidence for teachers to implement personalized support.
Effect of the heterocyclic ring-fusion on the photochemical reactivity of 1,4- dihydropyridines, polyhydroquinolines, and decahydroacridine-1,8-diones
Authors: Hosseininasab Fatemeh S. , Memarian Hamid R. , Asgari Mehrnoosh
Published: November 2024

Photo-oxidation of 1,4-dihydropyridine, polyhydroquinoline, and decahydroacridine-1,8-dione derivatives was investigated by exposing them to the UV light to elucidate the extent of the ring-fusion and the impact of molecular rigidity on the photo-oxidation completion time. The results indicated that the extent of the ring-fusion affects the time of irradiation, which is mostly due to the rigidity of the heterocyclic ring core regarding the freedom of rotation of the attached CO-groups and the effective delocalization of the nitrogen lone pair towards the attached conjugated part. Furthermore, the results showed the impact of the steric and electronic effects of the C-aryl substitution on the rate of the photo-oxidation. Among these three series of compounds, decahydroacridine-1,8-diones, and 1,4-dihydropyridines have the largest and lowest rate of the photo-oxidation, respectively. The geometry of the considered heterocyclic compounds and their corresponding photo-oxidation intermediates was optimized using the density functional theory (DFT) B3LYP method with 6-311 + + G(d,p) basis set. Computational results explained that the deviations of the N1- and C4-atoms of the dihydropyridine ring core from the ring boat plane can affect the rate of the photoreaction of these three series of compounds. These deviations are dependent on the preferred orientation of the CO group towards the heterocyclic ring, the rigidity of the molecule, and the type, position, and electronic nature of the additional substituent on the aryl ring. The dihedral angle scanning clarified the intramolecular interaction of unbounded atoms in the molecules besides the extent of the electron delocalization on the total energy content of the molecules.
Plants diseases diagnosis based on MobileNet and Inception Architectures
Authors: Halidou Aminou , Olle Daniel Georges Olle , Von Kallon Daramy Vandi , Baraza William John , Akou Obam , Melvin Fokam Ninyim Astride
Published: November 2024

Food shortages are some of the direct consequences of plant diseases in Developing countries. Artificial intelligence combined with image processing can help respond to these threats. In this paper, Inception v3 and MobileNet v2 are presented for plant disease detection using smartphones. We implemented the proposed methods and conducted the detection experiments carried out on an open dataset of 54305 images of leaves containing 14 species, spread over 38 distinct classes of combinations [plants, diseases], including healthy plants. The models were also run on the improved version of this dataset including 87867 images, and where there was no imbalance between classes. The results show that the Inception v3 method outperforms MobileNet v2, a state-of-the art model in terms of precision both on the original dataset and its augmented version, which makes it a very useful advisory or early warning tool. It should be noted that the presented method could be further improved by integrating several other varieties of plant 1 species and diseases taken under real culture conditions from several geographical areas.
MUC 21 is downregulated in oral squamous cell carcinoma and associated with poor prognosis
Authors: Mao Lisha , Wang Xiangpu , Zou Anna , Guo Siyuan , Chen Sijia , Su Ying , Ge Lihua , Yang Jing , Wang Xuejiu
Published: November 2024

Background
Mucins are usually associated with more aggressive tumor behavior and poorer clinical outcomes. However, MUC21 has never been studied in oral squamous cell carcinoma (OSCC). MUC21 has been observed to contribute to the anti-adhesion effects of cancer cells in vitro. It might serve as an important molecule in OSCC.
Methods
Our microarray data based on 10 oral squamous cell carcinoma (OSCC) and paired adjacent normal tissue (para-OSCC), and similar data sets from GEO and TCGA RNAseq data were analyzed to screen out the differentially expressed genes including MUC21. RT-PCR analysis was carried out to further confirm the alteration of MUC21 and the epithelial differentiation related co-expressed genes in OSCC. Then, the relationship of MUC21 changes in OSCC with the corresponding clinical characteristics and outcomes was investigated using immunohistochemistry (IHC) on other 102 paired samples of OSCC and para-OSCC. OSCC cell lines SCC15 and HSC-3 with MUC21 overexpression or knockdown were studied in vitro through CCK8, Annexin V/PI assays, wound healing, and Transwell experiments.
Results
MUC21 was significantly downregulated in OSCC compared with normal oral tissue, as evidenced by high throughput gene expression datasets, RT-PCR and immunohistochemistry analysis. Additionally, 11 genes co-expressed with MUC21 were revealed. Among them, the mucosae differentiation related KRT4, KRT13, and CRNN were further confirmed by RT-PCR and IHC. The downregulation of MUC21 was associated with pathological lymph node metastasis, poorer tumor differentiation, and shorter survival rates. However, hardly no statistically significant changes were detected in CCK8 analysis, Annexin V/PI assays, wound healing, and Transwell experiments on the OSCC cell lines with MUC21 overexpression or knockdown.
Conclusion
Low MUC21 expression in OSCC is associated with less epithelial differentiation, more clinical aggressiveness and worse prognosis. MUC21 could serve as a new prognostic marker in OSCC, though it might not be a driver oncogene.
Wireless Sensor Network coverage optimization Based on an Improved Pied kingfisher optimization algorithm
Authors: zhao yan , su xinliang , shi hanyang
Published: November 2024

The node coverage optimization problem of wireless sensor network (WSN) is a critical challenge in practical applications of WSN. In this paper, in order to solve the problem of uneven distribution and low coverage when WSN nodes are randomly deployed, a WSN coverage optimization strategy based on the improved pied Kingfisher optimization (IPKO) is proposed. The proposed improved pied Kingfisher optimization consists of three steps. First, a logistic-sine map is incorporated during population initialization to ensure a more homogeneous population distribution. Second, a subtractive averaging strategy is employed to enhance the convergence ability of the algorithm and strengthen the global search capability. Third, a subtraction-average-based optimizer is integrated during the commensalism phase to expand the population search range. The results of the simulation experiments prove that the performance of IPKO excellent in WSN coverage optimization. Especially in some large network scenarios, IPKO achieves a coverage of 97.86%, which represents a 20% improvement over the initial coverage. Simulation results show that our WSN coverage optimization strategy is efficient and the network coverage can be enhanced dramatically by the proposed IPKO.
Sources of Phytophthora nicotianae in South African citrus nurseries
Authors: McNeil Jason , Bophela Khumbuzile , Coutinho Teresa , Niekerk Jan van , Waals Jacquie van der
Published: November 2024

Occasional outbreaks of Phytophthora-related diseases, including fibrous root rot of Citrus nursery trees, are indicative of the presence of Phytophthora spp. in citrus nurseries. Diseases caused by Phytophthora spp. are known to occur despite management strategies such as water and rootstock management, testing, and oomycete-fungicide application. The objective of this study was to investigate infection pathways and the sources of Phytophthora inoculum in citrus nurseries in South Africa. Twelve commercial citrus nurseries were sampled for Phytophthora inoculum throughout the major citrus-producing regions of South Africa. Phytophthora nicotianae inoculum was retrieved from soil surrounding the tunnels at all the nurseries sampled, the growing media of pots and unused growing media. Other notable inoculum loci included the gloves and boots of nursery personnel, the cement structures used to raise the pots, moss and leaf litter surrounding pots, filled and used seedling trays, wheelbarrows, tractor wheels and shade netting were found to be contaminated in nurseries. Phytophthora citrophthora inoculum was not recovered from any of the sites sampled. Irrigation water tested at the nurseries showed an absence of Phytophthora inoculum and was thus clean at the time of study. Phytophthora nicotianae inoculum was present in the nursery environment and may be spread to plants through mechanical vectors such as gloves, boots, wheelbarrows and tractors as Phytophthora inoculum was detected on this equipment.
Effect of Synthesized ZnWO 3 /MIL-101(Cr) Nanocomposite on Lactoferrin Adsorption for Wastewater Treatment
Authors: Mofidian Roozbeh , Abdi Behnaz , Malmir Hosna
Published: November 2024

In this research, we increase the efficiency of the ZnWO3 catalyst by using the MIL-101(Cr) catalyst. By coupling these two catalysts, we can use them to achieve faster adsorption of lactoferrin in wastewater treatment. Regarding the adsorption of lactoferrin in wastewater, using nanocomposite can significantly improve the absorption of lactoferrin. Oxidizing lactoferrin can help reduce organic pollutants in wastewater and improve water quality. This nanocomposite can increase the speed of chemical reactions, which leads to higher efficiency in adsorbing lactoferrin and other organic pollutants. Also, these photocatalysts can improve the recyclability and reusability of ZnWO3/MIL-101(Cr), help reduce the costs of treatment operations, and remove other pollutants in wastewater. On the other hand, using this type of nanocomposite may reduce environmental damage and help preserve natural resources. ZnWO3/MIL-101(Cr) nanocomposite was identified using FT-IR, XRD, UV-vis, and SEM analyses.
SEGMTM: A Spectrum Prediction Method Based on Enhanced Graph Convolution and Multi-scale Time Decomposition
Authors: Meng Yong , Chen Suting , Lu Xinyu , Xu Wenliang , Shi Zhenxing , Zhou Xuefen
Published: November 2024

The development of wireless communication technology has led to increasing pressure on spectrum resources, making the rational allocation and utilization of these resources a significant challenge both now and in the future. Although spectrum data is a complex nonlinear time series, it exhibits a high degree of temporal and spatial correlation, providing new directions for addressing the issue of spectrum resource scarcity. In response to this situation, this study constructs a multi-scale spatio-temporal spectrum prediction method based on deep learning. First, we analyze the correlations present in different channels of spectrum data and utilize singular spectrum analysis (SSA) to decompose the complex spectrum data into a series of frequency components with underlying structures and patterns. Subsequently, we propose a spectrum prediction model (SEGMTM) that includes an attention-based enhanced graph convolutional network module (A-EGCN) and a multi-scale temporal module (MTM) to model the spatial and temporal correlations of the spectrum data, respectively. Furthermore, to reduce model complexity, we design a D-Regression module for auxiliary predictions. We validate the effectiveness of the proposed method through spectrum quality prediction and spectrum state prediction on two real measured spectrum datasets. Experimental results demonstrate that the proposed method achieves outstanding performance in both prediction tasks, with particularly notable advantages in long-term prediction tasks. In the spectrum quality prediction task, evaluation metrics show an improvement of 1.72% to 21.19%, while in the spectrum state prediction task, the accuracy improves by 1.28% to 3.51%.
Predicting demography from species traits: larval development time and its sensitivity to warming depend on egg size in corals
Authors: Figueiredo Joana , Baird Andrew H. , Harii Saki , Connolly Sean R.
Published: November 2024

In the absence of demographic data, readily measurable life history traits, like egg size, can be used to predict how vital rates vary across species, facilitating modeling and analysis of high-diversity assemblages. We assessed the larval survival and competency dynamics of four previously unstudied coral species at current and warmed temperatures, and combined it with data for three other species to assess how well egg size predicts the sensitivity to warming of mortality and the minimum time to competency, both determinants of larval dispersal. Minimum time to competency increased with egg size; moreover, warming-induced reductions in time to competency were greater for species with larger eggs. In contrast, mortality rate and its response to warming were both independent of egg size. These findings show how assemblage-level responses to environmental change can be inferred for diverse communities and indicate how warming-induced changes in larval biology may reshape reef coral metacommunities.
Outcomes of Percutaneous Endoscopic Gastrostomy (PEG) in HIV patients
Authors: Mantri Nikhitha , Sun Haozhe , Kandhi Sameer Datta , Allena Nishant , Anwar Muhammad Yasir , Hayagreev Vibha , Penikilapate Shalini , Alemam Ahmed , Muntazir Hassan A , Acherjee Trishna , Patel Harish , Makker Jasbir
Published: November 2024

Percutaneous Endoscopic Gastrostomy (PEG) insertion, a routine procedure for long-term enteral nutrition, serves as a crucial intervention for patients incapable of tolerating oral intake or meeting adequate nutritional requirements. PEG placement carrier complication of bleeding and infection. Impact of PEG tubes on the 30-day and long term mortality in HIV patients is unknown. Despite the ongoing utilization of PEG in HIV patients, a comprehensive exploration of its outcomes are yet to be explored. We intended to study the impact of HIV positive status on one month post-PEG mortality and review other PEG related complication. We reviewed all the PEG placed in our institution and compared the complication and mortality outcome between patient who are HIV positive and HIV negative. Our study was comprised of the 639 PEG placed on 461 patients, from which 85 patients (n = 18%) with HIV positive. Our findings reveal a statistically significant increase (p-value 0.001) in post-PEG insertion site bleeding in the HIV group (15.3%) compared to the non-HIV group (4.5%), with no discernible disparity in the utilization of anti-coagulation or anti-platelet agents between the two groups. Notably, the 1-year mortality rate in the HIV group stands at 37.6% (p < 0.001), contrasting sharply with the non-HIV group's rate of 17.8%. This study underscores the need for heightened vigilance and tailored management strategies when considering PEG procedures in the context of HIV, given the observed elevated bleeding risks and increased 1-year mortality rates in this patient population. Further research is warranted to elucidate the underlying factors contributing to these outcomes, facilitating the development of targeted interventions to optimize the care of HIV patients undergoing PEG placement.
RAVL: A Region Attention Yolo with Two-Stage Training for Enhanced Object Detection
Authors: Cai Weiwen , Du Huiqian , Xie Min
Published: November 2024

Improving the accuracy of object detection has been a key focus of recent research. However, many existing approaches fail to fully utilize location labels to effectively suppress irrelevant background features, which limits detection performance, particularly in the detection of small objects. In this paper, we propose a novel region attention mechanism to address this limitation, which combines of a region attention module(RAM) and a two-stage training strategy(TSTS). The RAM comprises a Squeeze-and-Excitation (SE) block, which dynamically assigns weights to multi-channel feature maps to generate a saliency map, and a fusion block that integrates the features with the saliency map to enhance object features while suppressing background features. We embed the RAM into the shallow layer of any version of YOLO, creating an object detector named Region Attention YOLO (RAVL). RAVL is trained using a two-stage training strategy (TSTS). In the first stage, “no background” images are generated based on the location labels, and a vanilla detector YOLOv8 is trained on them to produce ground truth “no background” features. In the second stage, RAVL is trained from scratch on the original infrared images by minimizing a detection loss and a region attention loss. The region attention loss ensures that the low-level features extracted from “no background” and original images are similar, thereby improving overall detection accuracy. Extensive experiments of YOLOv5, YOLOv8, YOLOv9 and YOLOv10 on the FLIR infrared image datasets and the VisDrone2019 visible light dataset demonstrate that our method can significantly improve the detection performance. YOLOv8 achieves the mAP0.5 score of 81.7% on the FLIR dataset and 42.1% on the VisDrone2019 dataset, which is 3.1% and 5.0% higher than that not using our method. Especially for small objects bicycle in FLIR and pedestrian in VisDrone2019, 5.7% and 7.9% higher mAP0.5 respectively.
Profiles of clinical service use for suicide ideation and suicide attempts across Australian cultural and linguistic groups: A latent class analysis using data from the National Study of Mental Health and Wellbeing (2020-2022)
Authors: Rajaram Gowri , Robinson Jo , Witt Katrina
Published: November 2024

Background Suicide ideation and suicide attempts represent a public health problem in Australia, for which most people do not seek formal clinical care. However, little research currently exists on the prevalence of STB within the culturally and linguistically diverse (CALD) community, and whether the help-seeking behaviours of CALD persons differs from non-CALD persons.Methods This is a secondary analysis of data from the National Study of Mental Health and Wellbeing, which surveyed a representative sample of Australian residents aged 16–85 years (N = 15,882) between December 2020 and October 2022. The prevalence of lifetime suicide ideation and suicide attempts by region of birth were calculated, and latent class analysis was used to examine patterns in both formal and informal help-seeking for both suicide ideation and suicide attempts separately. Logistic regression models were used to identify and quantify associations between region of birth and likelihood of class membership.Results Of the sample, 2602 (16.4%) reported suicide ideation and 753 (4.8%) people reported a suicide attempt. The prevalence of both was generally higher in the Australian-born population (18.3%), and lowest in people born in South Asia (5.9%). Most people reported no, or limited, use of clinical services for suicide ideation (76%) or suicide attempt (60%). People born in East Asia and the Pacific or Sub-Saharan Africa were 55% less likely and 70% less likely, respectively, to seek help from clinical services for suicide ideation compared to Australian-born people. People with moderate English proficiency were 92% less likely than people with native English proficiency to seek help from clinical services following a suicide attempt.Conclusions Most people in this sample were did not use clinical services for suicide ideation or suicide attempts. This is particularly so for persons born in East Asia and the Pacific or Sub-Saharan Africa. There is a need to understand and address social and cultural factors which may prevent people from these regions from engaging with clinical services. The CALD population in general may benefit from enhanced cultural responsiveness from clinical services, including the use of bicultural support workers and interpreters to improve help-seeking from clinical services.
Drug-caged drug: photoredox catalysis-enabled dual decaging of nitric oxide and local anesthetics for simultaneous antibacterial treatment and pain relief
Authors: Hu Jinming , Zhang Jiqian , Gan Guihai , Cao Chenchen , Zheng Shaoqiu , Wang Peng , Liu Xuesheng
Published: November 2024

Bacterial infections often result in significant pain, negatively impacting patient outcomes and quality of life. Conventional therapies primarily focus on pathogen eradication but frequently overlook the associated pain, thereby limiting their overall clinical effectiveness. Herein, we propose a 'drug-caged drug' strategy in which the secondary amine group of the local anesthetic tetracaine (TTC) is selectively caged by nitric oxide (NO), forming the TTC-NO prodrug. The TTC-NO prodrug is co-loaded with the photocatalyst fac-Ir(ppy)3 into poly(ethylene glycol)-b-poly(ε-caprolactone) (PEG-b-PCL) micellar nanoparticles (TTC-NO@M), enabling dual uncaging of TTC and NO under mild visible light irradiation through a photocatalytic mechanism. We demonstrate that TTC-NO@M exhibits combined antibacterial, anti-inflammatory, and analgesic activities by simultaneously releasing NO and TTC. This strategy effectively treats MRSA-infected mice in both cutaneous wound and septic arthritis models while alleviating infection-associated pain. This work offers a promising approach to address the dual challenges of bacterial infections and the associated pain.
Determinants of child intra-migration and exposure to abusive labor tasks: A phenomenological study
Authors: Zeleke Kassahun Dejene , Bekele Habtamu Wondimu
Published: November 2024

The specific objectives of the study were to identify the reasons (push and pull factors) behind child migration, to investigate the sectors where children are likely to work and to evaluate the effects of engaging in abusive labor on their overall well-being, including education, health, and social interaction with their peers. The study was conducted using qualitative research methodology and a phenomenological study design. Purposive sampling techniques were employed to select the informants. For data collection, the researchers employed vital informant interviews, in-depth interviews, and focus group discussions as data collection tools to gather information to attain research objectives. Data from the informant was analyzed using thematic qualitative analytical research methods. The result shows that there are many factors influencing rural-to-urban child migration. One of the reasons for the finding was poverty; the others were the disintegration of families or loss of parents, poor social service, poor childcare culture, family's low value for education, domestic violence, seasonal factors, and displacement due to war. Furthermore, children are engaged in trim work, such as domestic servants in the private sector and selling items on the streets. Finally, for children who engage in labor, their social well-being (education, health, and social interaction with their peer group) is affected, and their labor has negative consequences for their social well-being. The Research recommends government and N.G.O. intervention, family planning for large families, poverty alleviation, and economic support for poor households and children. Finally, children should be engaged in school at an early age.
Broadening the candidate set of parametric models when extrapolating survival: the case for models with U-shaped hazards.
Authors: Gallacher Daniel , Connock Martin
Published: November 2024

In health technology assessment (HTA), extrapolation of time-to-event data is common to estimate the benefit of a new health technology beyond the observed period of data. The regular set of parametric models commonly used for extrapolation does not include models which assume a U-shaped hazard rate, that is initially decreasing and then increasing hazard rate.
We compared the visual and statistical fit and prediction of models which assume a U-shaped hazard rate (Chen, bathtub and Rayleigh) to the regular set of parametric models (exponential, log-normal, log-logistic, Weibull, generalised gamma, Gompertz) across a range of settings and data types, including hip arthroplasty, functional tricuspid regurgitation and knee osteoarthritis.
U-shaped hazard models outperformed or matched standard parametric models in visual fit, goodness of fit statistics and long-term predictions when compared to extended follow-up.
Bathtub models should feature routinely in HTA submissions involving extrapolation of survival data, allowing for exploration of a wider range of scenarios and potentially more accurate predictions, resulting in better informed valuation and decision making for emerging health technologies.