bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical Evidence of Methods and Timing of Proper Follow-Up for Head and Neck Cancers
Authors: Gili Riccardo , Caprioli Simone , Lovino Camerino Paola , Sacco Gianluca , Ruelle Tommaso , Filippini Daria Maria , Pamparino Silvia , Vecchio Stefania , Marchi Filippo , Del Mastro Lucia , Cittadini Giuseppe
Published: September 2024

Background: For patients with head and neck squamous cell carcinoma (HNSCC), after a single or multi-modality treatment, a specific follow-up strategy is needed, but there is no agreement between the main international societies on the proper methods and timing of follow-up. Methods: We performed a descriptive review to evaluate the available data and compare the main guidelines, giving some practical guidance to perform effective personalized follow-up strategies. Results and Conclusions: While clinical and endoscopic follow-up alone seems to be appropriate for early-stage HNSCCs, the addition of close radiologic follow-up in locally advanced HNSCCs is still debated, as there are no data indicating that an earlier detection of recurrence correlates with increased survival, while it is mandatory in the first three-six months to define the response to treatment. For patients who have undergone conservative surgery or have major pathological risk factors, the incidence of locoregional recurrence is higher, and locoregional radiologic follow-up (magnetic resonance imaging is preferred to computed tomography) should be considered. Positron emission tomography may be useful in cases of suspected locoregional persistence of disease, differentiating it from post-irradiation outcomes. Distant radiological follow-up can be considered in the detection of the second primary in cases of specific risk factors and for virus-related tumors. For the latter, the use of circulating DNA should always be considered. A brain scan is not recommended without specific symptoms. For all patients who do not fall into the above categories, clinical and endoscopic follow-up should be proposed, reserving radiological investigations only at the onset of symptoms.
Multi-Temporal Snow-Covered Remote Sensing Image Matching via Image Transformation and Multi-Level Feature Extraction
Authors: Fu Zhitao , Zhang Jian , Tang Bo-Hui
Published: September 2024

To address the challenge of image matching posed by significant modal differences in remote sensing images influenced by snow cover, this paper proposes an innovative image transformation-based matching method. Initially, the Pix2Pix-GAN conversion network is employed to transform remote sensing images with snow cover into images without snow cover, reducing the feature disparity between the images. This conversion facilitates the extraction of more discernible features for matching by transforming the problem from snow-covered to snow-free images. Subsequently, a multi-level feature extraction network is utilized to extract multi-level feature descriptors from the transformed images. Keypoints are derived from these descriptors, enabling effective feature matching. Finally, the matching results are mapped back onto the original snow-covered remote sensing images. The proposed method was compared to well-established techniques such as SIFT, RIFT2, R2D2, and ReDFeat and demonstrated outstanding performance. In terms of NCM, MP, Rep, Recall, and F1-measure, our method outperformed the state of the art by 177, 0.29, 0.22, 0.21, and 0.25, respectively. In addition, the algorithm shows robustness over a range of image rotation angles from −40° to 40°. This innovative approach offers a new perspective on the task of matching multi-temporal snow-covered remote sensing images.
Dimensional and Hierarchical Assessment of American Kennel Club Breeds and Behavioral Trait Descriptions
Authors: Zapata Sofia , Zapata Isain
Published: September 2024

The AKC functions as the largest and most influential dog breed registry and breed standard information source in the United States. AKC breed standards describe the breed’s overall appearance and behavior. Despite their popularity, the AKC behavioral descriptions and the traits used to quantify them have largely remained unexplored. In this study, we used eleven behavioral breed standard traits for 286 breeds collected for the official AKC source. Dog size and appearance were also evaluated. We employed pairwise correlation and factor analysis to define behavioral trait constructs and hierarchical clustering methods to evaluate the similarity of breed profiles. These methods revealed that although AKC data exhibit various individual correlations concurrent with known canine behavior, many breeds present behavioral trait constructs that do not align with the narratives presented in their standard and may be lacking crucial factors in dog behavior, as suggested by breed group clustering. Our dimensional analysis revealed three constructs, which we labeled as “Social Engagement”, “Pet Demands”, and “Vigilance”, that are very important and relevant to pet ownership. These results emphasize the importance of standardized observations when quantifying behavior and provide an overarching context regarding the strengths and weaknesses of these descriptions, allowing readers to better understand and predict their pet’s behavior.
The Impact of the Clinical Pharmacist-Led Diabetes Education on the Knowledge and Attitude of Individuals with Type II Diabetes Mellitus: An Interventional Study
Authors: Badi Safaa , Suliman Sara Zainelabdein , Almahdi Rayan , Aldomah Mohammed A. , Elkheir Habab Khalid , Ibrahim Mohamed Izham Mohamed , Ahmed Mohamed H.
Published: September 2024

Background: Diabetes mellitus is a complex condition to manage. Patients with a greater understanding and knowledge of their condition might achieve better glycemic control than others. This study aimed to evaluate the impact of clinical pharmacist-led diabetes education on the knowledge and attitude of individuals with type II diabetes mellitus (T2DM). Methods: This study was a quasi-experimental study which was conducted at a diabetes clinic in Khartoum, Sudan. The study population was adult individuals with T2DM who attended the diabetes clinic. The estimated sample size was 182 participants. The participants were selected randomly by a simple random sampling method. The knowledge and attitudes of the participants were assessed at baseline and at the end of the study after 12 months. The intervention was carried out through educational materials about diabetes and medications for its treatment. Results: The majority of the participants were females. The mean age was 54.5 (±10) years. Most participants had a family history of diabetes (69.2%). The mean knowledge score after the intervention was increased by 1.4 (±0.1) from baseline, p value (<0.001), while the mean attitude score was increased by 1.7 (±0.2) from baseline, p value (<0.001). At baseline, 14.8% of the participants had a high level of knowledge and 18.7% had a negative attitude, while after intervention for 12 months, 28.5% of them had a high level of knowledge and 16.8% had a negative attitude (p values < 0.001, 0.032, respectively). Conclusions: The knowledge of and attitudes towards diabetes differed significantly as a result of the educational program provided by the clinical pharmacist.
Tunable Polarization-Selective Absorption by Gating Ultrathin TiN Films in the Near-Infrared Region
Authors: Jiang Huan , Huang Junhao , Zhu Wenchang , Wang Yetian , V. Kildishev Alexander
Published: September 2024

Ultrathin titanium nitride (TiN) is a novel material platform for constructing active metasurfaces in the near-infrared region (NIR). Here, we realized tunable polarization-selective absorption by gating ultrathin TiN in an Ultrathin TiN Grating Metasurface (UTGM) and a gold resonator/TiN film Hybrid Metasurface (GTHM), respectively. The TM wave absorption (0.96) was much larger than that of the TE wave in the UTGM. When the carrier density decreased by 12%, the near-perfect TM absorption peak blue-shifted by 0.3 μm. Similarly, the linear dichroism (0.96) peak in GTHM blue-shifted by 0.12 μm when gating ultrathin TiN film. Active metasurfaces with tunable polarization-selective absorption have huge potential in dynamic integrated electro-optic devices in NIR.
Lightning Location Method Using Orthogonal Coded Polarization Optical Time-Domain Reflectometer in Optical Fiber Transmission
Authors: Lian Weihua , Su Xingrui , Li Wei , Wu Bin , Feng Xiaofang , Zhao Hanqi , Wang Desong , Wu Guilong , Liu Lin , Chen Yitong , Hu Kaijing
Published: September 2024

Lightning strike is one of the main factors affecting power transmission lines and may lead to broken strands and damage of transmission lines, resulting in abnormal power supply. To improve the accuracy of lightning location, this paper presents a polarization optical time-domain reflectometer (POTDR) lightning location method based on orthogonal coding technology. The lightning strike point can be located by detecting the state of polarization (SOP) mutation of Rayleigh backscattering in the POTDR system. The orthogonal coding technology is used to improve the distance and accuracy of POTDR lightning location. Through calculation and simulation analysis, the location accuracy is significantly improved at the same sensing distance compared with the ordinary POTDR lightning location method. The lightning strike location error can be limited to 200 m in 20 km sensing distance which meets the actual engineering needs. The results of this paper are important to improve the operation and maintenance efficiency of transmission lines and reduce maintenance costs in the power industry.
Identification of the BZR Family in Garlic (Allium sativum L.) and Verification of the AsBZR11 under Salt Stress
Authors: Peng Xianghan , Ruan Jiaojiao , Jiang Fangling , Zhou Rong , Wu Zhen
Published: September 2024

Brassinazole-Resistant (BZR) is an important transcription factor (TF) in the brassinosteroid (BR) signaling pathway, which plays a crucial role in plant growth, development and stress resistance. In this study, we performed a genome-wide analysis of BZRs in garlic (Allium sativum L.) and identified a total of 11 members of the AsBZR gene family. By comparing the expression patterns of AsBZR genes under salt stress, the candidate gene AsBZR11 with salt tolerance function was identified. Subcellular localization results showed that AsBZR11 was localized in the nucleus. The salt tolerance of overexpression lines improved, and the germination rate and root length of overexpression lines increased as compared with wild type. The content of reactive oxygen species (ROS) decreased, and the activity of antioxidant enzymes increased in AsBZR11-OE, suggesting that AsBZR11 has the function of improving plant salt tolerance. Our results enriched the knowledge of plant BZR family and laid a foundation for the molecular mechanism of salt tolerance of garlic, which will provide a theoretical basis for the subsequent creation of salt-tolerant germplasm resources.
Species Richness, Abundance, and Vertical Distribution of Epiphytic Bromeliads in Primary Forest and Disturbed Forest
Authors: Siaz Torres Sugeidi S. , de la Rosa-Manzano Edilia , Arellano-Méndez Leonardo U. , Aguilar-Dorantes Karla M. , Martínez Ávalos José Guadalupe , Juárez Aragón María Cruz
Published: September 2024

Epiphytes represent a key component in tropical forests. They are affected by anthropogenic and natural disturbances suffered by forests, since they depend on their hosts and the microclimatic conditions they generate. We analyzed differences in abundance, species richness, and vertical distributions of epiphytic bromeliads in primary and disturbed forests. We found a higher abundance (5316 individuals) and species richness (8 species) of bromeliads in disturbed forest than in primary forest (1360 individuals and 4 species, respectively). Most bromeliads (97%) were found on Taxodium mucronatum, a dominant tree with rough bark in the disturbed forest (gallery forest). Bromeliads were more abundant in the middle of the tree and diminished towards the trunk base and the upper crown. Tillandsia baileyi was the most abundant bromeliad, and the size categories of this species differentially colonize trees in gallery forest according to Johansson zones; seedlings of T. baileyi abundantly colonize the upper canopy, and juveniles colonize the middle canopy or secondary branches. Gallery forest represents an important reservoir for epiphytic bromeliads. Hence, it is important to extend this kind of study to wetland sites to understand the role they play as a habitat for epiphytes, as well as the dynamics and ecological processes that occur in such habitats.
Understanding Powder Behavior in Continuous Feeding: Powder Densification and Screw Layering
Authors: Fathollahi Sara , Janssen Pauline H. M. , Bekaert Bram , Vanderroost Dirk , Vanhoorne Valerie , Dickhoff Bastiaan H. J.
Published: September 2024

Background: Precise continuous feeding of active pharmaceutical ingredients (APIs) and excipients is crucial in a continuous powder-to-tablet manufacturing setup, as any inconsistency can affect the final tablet quality. Method: This study investigated the impact of various materials on the performance of a continuous twin-screw loss-in-weight (LIW) feeder. The materials tested included spray-dried lactose, anhydrous lactose, granulated lactose, microcrystalline cellulose (MCC), an MCC–lactose preblend (50%:50% w/w ratio), and a co-processed excipient (lactose–lactitol at a 95%:5% w/w ratio). The feeding performance of these excipients was systematically assessed, focusing on powder densification and screw layering within the LIW feeder. Results: The results demonstrated densification for the spray-dried lactose and preblend. Densification was more pronounced during the initial feeding cycles for spray-dried lactose, but decreased gradually over time. In contrast, the densification remained relatively constant throughout the feeding process for the preblend. Notably, minor screw layering was observed for both spray-dried lactose and anhydrous lactose, with the extent of this issue reducing over time for the spray-dried lactose. Interestingly, granulated lactose grades did not show screw layering, making them preferable for blending with APIs prone to severe screw layering. The LIW feeder control system successfully managed powder densification and minor screw layering, maintaining the mass flow rate at the set point for all investigated materials. Conclusions: These findings inform the selection of optimal excipients, appropriate tooling for LIW feeders, and the enhancement of control strategies to shorten startup times. By addressing these factors, the precision and reliability of continuous feeding processes can be improved.
Fe2NiSe4 Nanowires Array for Highly Efficient Electrochemical H2S Splitting and Simultaneous Energy-Saving H2 Production
Authors: Ding Tong , Cen Nanheng , Fan Rui , Li Long , Du Yonghong , Tang Chun , Guo Heng , Li Yiping , Liu Zongshe
Published: September 2024

The electrochemical removal of abundant and toxic H2S from highly sour reservoirs has emerged as a promising method for hydrogen production and desulfurization. Nevertheless, the ineffectiveness and instability of current electrocatalysts have impeded further utilization of H2S. In this communication, we introduce a robust array of Fe2NiSe4 nanowires synthesized in situ on a FeNi3 foam (Fe2NiSe4/FeNi3) via hydrothermal treatment. This array acts as an active electrocatalyst for ambient H2S splitting. It offers numerous exposed active sites and a rapid electron transport channel, significantly enhancing charge transport rates. As an electrode material, Fe2NiSe4/FeNi3 displays remarkable electrocatalytic efficiency for both sulfide oxidation and hydrogen evolution reactions. This bifunctional electrode achieves efficient electrochemical H2S splitting at a low potential of 440 mV to reach a current density of 100 mA∙cm−2, with a faradaic efficiency for hydrogen production of approximately 98%. These findings highlight its significant potential for desulfurization and energy-efficient hydrogen generation.
Multi-Parameter Experimental Investigation on the Characteristics of Acidizing Effectiveness in High-Temperature Carbonate Formation
Authors: Zhao Zhiheng , Zheng Youcheng , Liu Qiang , Zhang Yan , Tang Yong , Xu Yuan
Published: September 2024

Carbonate formation is the key reservoir in Sichuan Basin for natural gas development. Compared with the early stage of development, the burial depth of targeted formation becomes deeper, and the formation temperature gets higher. So, the characteristics of acidizing effectiveness in high-temperature carbonate formations make this evaluation slightly difficult. Currently, it is common that a single parameter is considered to study acidizing effectiveness by simulation and experiment methods. In this paper, for a more accurate investigation of acidizing effectiveness, multiple parameters, including permeability change rate, fracture conductivity, and surface roughness, were introduced by a series of experiments. It is revealed that the permeability change rate is more than 57% when using gelled acid. As the amount of diverting agent increases in diverting acid, the viscosity of the acid grows to its peak with the reaction, making it easier to block the high permeability core temporarily and divert to acidify the low permeability core, where the permeability change rate of the low permeability core goes from 51.6% to 64.2%, which shows well acidizing effectiveness. In addition, the short-term and long-term conductivity of the samples from the three different formations are more than 200 mD∙m under high closure stress. The conductivity of Maokou Formation is the largest due to its high content of carbonate minerals and high dissolution rate. And the results of long-term conductivity are consistent with those of surface roughness, making the evaluation results more reliable for acidizing effectiveness. It is worth noting that temperature is a factor that cannot be ignored in the evaluation of acidizing effectiveness because it has a great influence on the performance of the acid system, such as viscosity and the reaction-reduced rate, leading to an acidizing effectiveness affect. So, the temperature resistance of an acid system is important as well.
Systematic Exploration of the Interactions between Pyrite and Coal from the View of Density Functional Theory
Authors: Xi Peng , Sun Fengling , Tang Xiaoyu , Fan Xiaoping , Lu An , Lu Kaifei , Zhuo Qiming
Published: September 2024

Coal is often adhered to by pyrite during slime flotation, causing an increase in the sulfur content of clean coal. In order to study the mechanism of pyrite adhesion to coal surfaces, different coal structural units were built and optimized, and the most stable adsorption model of them on pyrite surfaces was determined. The mechanism of pyrite particles adhering to the surface of coal slurries was explored with the method of DFT. The results showed that the interaction mechanism between pyrite surface and Ph-OH and Ph-O-CH3 was the result of a weak interaction between the H atom of Ph-OH and Ph-O-CH3 and the S atom of the pyrite surface. The interaction mechanism between the pyrite surface and Ph-COOH and Ph-CO-CH3 was both as a result of H-S interactions and weak Fe-O interactions. On the whole, there were weak interactions between pyrite particles and the coal slurry, and the pyrite particles can spontaneously adsorb on the surface of the coal slurry.
A Fault Diagnosis Method for Pumped Storage Unit Stator Based on Improved STFT-SVDD Hybrid Algorithm
Authors: Bai Jie , Liu Xuan , Dou Bingjie , Yang Xiaohui , Chen Bo , Zhang Yaowen , Zhang Jiayu , Wang Zhenzhong , Zou Hongbo
Published: September 2024

Stator faults are one of the common issues in pumped storage generators, significantly impacting their performance and safety. To ensure the safe and stable operation of pumped storage generators, a stator fault diagnosis method based on an improved short-time Fourier transform (STFT)-support vector data description (SVDD) hybrid algorithm is proposed. This method establishes a fault model for inter-turn short circuits in the stator windings of pumped storage generators and analyzes the electrical and magnetic states associated with such faults. Based on the three-phase current signals observed during an inter-turn short circuit fault in the stator windings, the three-phase currents are first converted into two-phase currents using the principle of equal magnetic potential. Then, the STFT is applied to transform the time-domain signals of the stator’s two-phase currents into frequency-domain signals, and the resulting fault current spectrum is input into the improved SVDD network for processing. This ultimately outputs the diagnosis result for inter-turn short circuit faults in the stator windings of the pumped storage generator. Experimental results demonstrate that this method can effectively distinguish between normal and faulty states in pumped storage generators, enabling the diagnosis of inter-turn short circuit faults in stator windings with low cross-entropy loss. Through analysis, under small data sample conditions, the accuracy of the proposed method in this paper can be improved by up to 7.2%. In the presence of strong noise interference, the fault diagnosis accuracy of the proposed method remains above 90%, and compared to conventional methods, the fault diagnosis accuracy can be improved by up to 6.9%. This demonstrates that the proposed method possesses excellent noise robustness and small sample learning ability, making it effective in complex, dynamic, and noisy environments.
Intelligent Prediction of Rate of Penetration Using Mechanism-Data Fusion and Transfer Learning
Authors: Huang Zhe , Zhu Lin , Wang Chaochen , Zhang Chengkai , Li Qihao , Jia Yibo , Wang Linjie
Published: September 2024

Rate of penetration (ROP) is crucial for evaluating drilling efficiency, with accurate prediction essential for enhancing performance and optimizing parameters. In practice, complex and variable downhole environments pose significant challenges for mechanistic ROP equations, resulting in prediction difficulties and low accuracy. Recently, data-driven machine learning models have been widely applied to ROP prediction. However, these models often lack mechanistic constraints, limiting their performance to specific conditions and reducing their real-world applicability. Additionally, geological variability across wells further hinders the transferability of conventional intelligent models. Thus, combining mechanistic knowledge with intelligent models and enhancing model stability and transferability are key challenges in ROP prediction research. To address these challenges, this paper proposes a Mechanism-Data Fusion and Transfer Learning method to construct an intelligent prediction model for ROP, achieving accurate ROP predictions. A multilayer perceptron (MLP) was selected as the base model, and training was performed using data from neighboring wells and partial data from the target well. The Two-stage TrAdaBoost.R2 algorithm was employed to enhance model transferability. Additionally, drilling mechanistic knowledge was incorporated into the model’s loss function as a constraint to achieve a fusion of mechanistic knowledge and data-driven approaches. Using MAPE as the measure of accuracy, compared with conventional intelligent models, the proposed ROP prediction model improved prediction accuracy on the target well by 64.51%. The model transfer method proposed in this paper has a field test accuracy of 89.71% in an oilfield in China. These results demonstrate the effectiveness and feasibility of the proposed transfer learning method and mechanistic–data integration approach.
Insights from Bibliometric Analysis of Epilepsy Research in Morocco between 1969 and 2024
Authors: Zennati Abdelaziz , Ousaaid Driss , Khabbal Youssef
Published: September 2024

Epilepsy is a critical neurological condition characterized by the disturbance of the excitatory neuron network, resulting in recurrent seizures. It is a serious health problem requiring intensive attention. The present study was designed to use bibliometric analysis to assess scientific research output on pharmacogenetics in epilepsy and drug-resistant epilepsy in Morocco during 1969–2024. The main objective of this study was to analyze scientific production and research development and to introduce available solutions to manage the elevating burden of epilepsy. The strategy approach comprised a suitable search scheme to collect publications related to epilepsy using the Scopus database. All the documents retrieved were analyzed to determine several parameters, including the number of publications annually, type of documents, institution and author productivity, and relevant sources. Studies on pharmacogenetics and drug-resistant epilepsy in Morocco are limited. The findings revealed that the number of articles has increased during the last decade. Publications remain scarce, especially on pharmacogenetics and drug-resistant epilepsy, and the most widely available publications include articles on epilepsy, seizures, mental illness, and anticonvulsant agents. Based on the search strategy, a bibliometric analysis identified potential subjects for further study. Consequently, research on epilepsy is essential to fully understand the condition, but it remains insufficient, and further studies are required, particularly on the pharmacogenetics of epilepsy.
Forgotten Victims of War: A Rapid Review of Counseling Needs and a Proposed Intervention Model for Civilian Survivors
Authors: Alghazo Runna , Premuda-Conti Paola
Published: September 2024

The counseling needs of civilian war victims, particularly those not classified as refugees, have been largely neglected in academic counseling research. This study addresses this gap by conducting a rapid literature review to evaluate the current state of counseling services available to these individuals. Using Google Scholar and Web of Science, we identified and reviewed studies on counseling services for war veterans, refugees, and civilians in conflict zones. This review revealed a significant lack of structured counseling support for non-refugee civilian war victims, despite their high vulnerability. Findings indicate that while substantial efforts have been made to support refugees and veterans, the mental health needs of civilians who remain in conflict areas are often unmet, with existing services being sparse and inadequately documented. To address this issue, we propose a preliminary model that includes culturally sensitive counseling programs, training for local counselors, and international collaboration to provide sustainable support. This study highlights the urgent need for focused research and practical interventions to develop comprehensive counseling programs for these overlooked victims of war, and encourages researchers to address this critical gap in mental health services.
Plio-Pleistocene Small Mammal-Based Biochronology of Eastern Anatolia and Transcaucasus
Authors: Tesakov Alexey S. , Frolov Pavel , Simakova Alexandra , Yakimova Albina , Titov Vadim , Ranjan Pranav , Çelik Hasan , Trifonov Vladimir
Published: September 2024

The known Plio-Pleistocene mammalian record, mainly represented by small mammals, and its biotic and geological context in the vast region of Eastern Turkey and Transcaucasus provides a sound base for regional biochronology. Recently obtained faunal associations and the main evolutionary lineages found in the region support direct correlations to the European (ELMA/MN/MQ) and the Eastern European (faunal complexes/MQR-MNR) biochronological systems. Important data on palynology, aquatic and terrestrial mollusks, and magnetostratigraphy integrate the reviewed material into a robust local biochronology. The range of standard biochrons of Early Pliocene through late Early Pleistocene and the regional Anatolian zones M-P are reliably detected. The Early Pleistocene time range (zone P) is refined based on rhizodont lagurines Borsodia and Euro-Asian larger voles Mimomys ex gr. pliocaenicus. The successive zone R for Early Pleistocene faunas with early rootless Microtini is proposed.
Monks, Blogs and Three Media Cases: Russian-Speaking Buddhist Communities in the Era of Social Media
Authors: Ostrovskaya Elena , Badmatsyrenov Timur
Published: September 2024

This paper focuses on the problem of how Buddhism was reinstitutionalized in Russia in the frame of the meta process of mediatization. The empirical part of this study included two stages and was conducted during 2020–2024. In this paper, the authors focused mainly on the peculiarities of constructing strategies in the Internet and new media via traditional Gelug ethnic offline organizations, the Russian branches of the International Karma Kagyu Community, International Dzogchen Community and Russian-speaking community of Theravada converts. The methodological framework of the research included the institutional perspective developed by the Danish media scholar Stig Hjarvard for studying the mediatization of religion and the concept of “mediatized public religion” by Mia Lövheim and Marta Axner, as well as the concept of “digital religious innovators” by Heidi Campbell. The authors revealed that the processes of digitalization and mediatization have resulted in the emergence of Russian mediatized Buddhism. Various trends in modern Russian Buddhism are disproportionally represented in the public sphere of media; representation directly correlates with the strategies that Digital Buddhist creatives of different streams—Gelugpa traditional, Dzogchen, Theravada or Karma Kagyu—have chosen in relation to the Internet and new media.
Exploring Literature in Islam Beyond (Secularized) Christian Normativity in Western Academia
Authors: Gallien Claire
Published: September 2024

Anyone specialising in Islamic theology at a Western university is aware of the fact that their teaching and research will either be recognised by the institution as falling under the category of “Islamic Studies” or “Divinity”. In the first case, Islam is predominantly considered a cultural phenomenon and studied as such. In the second case, for reasons that have to do with what Marianne Moyaert in her latest book Christian Imaginations of the Religious Other has conceptualised as “Christian normativity” and the “religionisation” of other faiths, Islamic theology is de facto understood as Islamic speculative theology (kalām). In both cases, the understanding of how Islam theorises and practices theology is significantly restricted, when not altogether ignored. This article unpacks the genealogy of the secular version of a Christian epistemic framework that dominates the study of Islamic theology in the West and engages with the issues related to its application in the field of Islamic theology. In doing so, it opens a critical space for the investigation of Islamic literary productions as both dissensual and consensual theological terrains, through the analysis of the poetry of two theologians and polymathic scholars from two different periods of Islamic history, namely Ibn al-Fāriḍ (d. 632/1235) and Sidi Muḥammad Ibn al-Ḥabīb (d. 1390/1971).
Composting as a Cleaner Production Strategy for the Soil Resource of Potato Crops in Choconta, Colombia
Authors: Ortega-Ramírez Angie Tatiana , García Moreno Daniela , Reyes Tovar Miriam
Published: September 2024

Choconta is the municipality in Colombia with the greatest prevalence of potato planting, representing 70.90% of the total territory. However, this crop has been affected by the presence of pests, diseases, and chemical contaminants from pesticides and chemical fertilizers that deteriorate the soil and, therefore, the quality of the final product. Compost (organic waste with specific characteristics and made from waste generated in Choconta) was studied as a sustainable production strategy to increase soil quality and thereby the quality of the local potato crop. For this purpose, a 3 × 2 experiment design was implemented with three treatments (0%, 25%, and 50% compost) and two variables (young potato and mature potato) in duplicate for 4 months. In this experiment, the use of compost led to an improved final product, which went from a floury texture to a dense and creamy texture. The use of compost also reduced the levels of heavy metals, such as lead, with a higher removal in treatment 3 (50% composting). The estimated direct cost of the composting process was USD 280.85, slightly lower than that of the application of fertilizers at USD 294.48. The use of fertilizers has a higher environmental impact due to the use of chemical products that have environmental and health implications. Using compost did not influence tuber harvest time but had a positive impact on tuber texture quality and on soil resources through the reduction in heavy metals, especially lead (16.40–18.03 ppm for treatment 1, 17.96–18.49 ppm for treatment 2, and 15.67–17.88 ppm for treatment 3). Using compost could be environmentally and economically beneficial for local farmers, and it promotes the circular economy and sustainable communities.
Mapping Financial Connections: Market Integration in Emerging Economies through Graph Theory
Authors: Cortés Rufé Marc , Martí Pidelaserra Jordi
Published: September 2024

In this study, we explore the financial and economic integration of BRICS nations (Brazil, Russia, India, China, and South Africa) and key emerging economies (Egypt, Saudi Arabia, and the UAE) using graph theory, aiming to map intersectoral connections and their impact on financial stability and market risk. The research addresses a critical gap in the literature; while political and economic linkages between nations have been widely studied, the specific connectivity between sectors within these economies remains underexplored. Our methodology utilizes eigenvector centrality and Euclidean distance to construct a comprehensive network of 106 publicly listed firms from 2013 to 2022, across sectors such as energy, telecommunications, retail, and technology. The primary hypothesis is that sectors with higher centrality scores—indicative of their interconnectedness within the broader financial network—demonstrate greater resilience to market volatility and contribute disproportionately to sectoral profitability. The analysis yielded several key insights. For instance, BHARTI AIRTEL LIMITED in telecommunications exhibited an eigenvector centrality score of 0.9615, positioning it as a critical node in maintaining sectoral stability, while AMBEV SA in the retail sector, with a centrality score of 0.9938, emerged as a pivotal player influencing both profitability and risk. Sectors led by companies with high centrality showed a 20% increase in risk-adjusted returns compared to less connected entities, supporting the hypothesis that central firms act as stabilizers in fluctuating market conditions. The findings underscore the practical implications for policymakers and investors alike. Understanding the structure of these networks allows for more informed decision making in terms of investment strategies and macroeconomic policy. By identifying the central entities within these economic systems, both policymakers and investors can target their efforts more effectively, either to support growth initiatives or to mitigate systemic risks. This study advances the discourse on emerging market integration by providing a quantitative framework to analyze intersectoral connections, offering critical insights into how sectoral dynamics in emerging economies influence global financial trends.
Shrimp Larvae Counting Based on Improved YOLOv5 Model with Regional Segmentation
Authors: Duan Hongchao , Wang Jun , Zhang Yuan , Wu Xiangyu , Peng Tao , Liu Xuhao , Deng Delong
Published: September 2024

Counting shrimp larvae is an essential part of shrimp farming. Due to their tiny size and high density, this task is exceedingly difficult. Thus, we introduce an algorithm for counting densely packed shrimp larvae utilizing an enhanced You Only Look Once version 5 (YOLOv5) model through a regional segmentation approach. First, the C2f and convolutional block attention modules are used to improve the capabilities of YOLOv5 in recognizing the small shrimp. Moreover, employing a regional segmentation technique can decrease the receptive field area, thereby enhancing the shrimp counter’s detection performance. Finally, a strategy for stitching and deduplication is implemented to tackle the problem of double counting across various segments. The findings from the experiments indicate that the suggested algorithm surpasses several other shrimp counting techniques in terms of accuracy. Notably, for high-density shrimp larvae in large quantities, this algorithm attained an accuracy exceeding 98%.
Reducing Data Uncertainties: Fuzzy Real-Time Safety Level Methodology for Socio-Technical Systems
Authors: Zeleskidis Apostolos , Charalampidou Stavroula , Dokas Ioannis M.
Published: September 2024

This paper presents the fuzzy real-time safety level (Fuzzy RealTSL) methodology. It aims to address the data uncertainties resulting from a lack of sensors in complex sociotechnical systems and reduce the need for the determination of their safety level in real-time during their operation. To achieve this, the methodology utilizes: (1) safety constraints from STPA (systems theoretic process analysis) analysis and EWaSAP (early-warning-signs analysis process), (2) fuzzy logic as the mathematical backbone to identify the degree of confidence about the occurrence of unsafe system states, (3) a modified centroid point and spread ordering to enable ordering sequences of unsafe system states that can lead to accidents according to how detrimental they are to the system safety. The RealTSL methodology is presented through its step-by-step application to the panel alignment system of a solar park utilizing rotating solar arrays. This paper aims to open a new perspective on the STAMP literature for discussions of uncertainties from a lack of information about the system’s state and to make it easier to measure its safety level. Knowing the safety level of a system in real-time is crucial for the systems in question as it enables proactive risk management and enhances decision-making by providing immediate insights into potential hazards, thus safeguarding against accidents.
A Narrative Review of Therapeutic Options in Systemic Sclerosis Associated Interstitial Lung Disease
Authors: Harrington Robert , Harkins Patricia , Conway Richard
Published: September 2024

Background: Interstitial lung disease (ILD) has replaced scleroderma renal crisis as the leading cause of mortality in systemic sclerosis (SSc), with a 10-year mortality of 40%. There have been well-powered randomised control trials (RCTs) demonstrating the effect of cyclophosphamide (CYC), mycophenolic acid (MMF), nintedanib and tocilizumab (TCZ) in SSc-ILD but a paucity of sufficiently powered studies investigating other agents in the disease. Methods: This is a narrative review which examines the existing evidence for immunosuppressive treatments, transplant and adjunctive therapies in SSc-ILD by reviewing the key landmark trials in the last two decades. Results: MMF for 2 years is as effective as oral CYC for 1 year. Rituximab (RTX) is non-inferior to CYC. TCZ appears to have a beneficial effective regardless of the extent of lung involvement. Conclusions: There is now a strong evidence base supporting the use of MMF as the first line option in SSc-ILD. RTX, CYC and TCZ are viable therapeutic options if there is ILD progression on MMF. Anti-fibrotic and pulmonary arterial (PAH) treatments likely add long-term synergistic benefits. There remains a role for lung transplantation in select patients.
Participatory Democracy in Southern Africa: Explaining Botswana’s Exceptionalism
Authors: Reiter Bernd
Published: September 2024

Botswana has had fair and stable elections since its independence in 1966. It has a relatively high standard of living, a relatively well-functioning welfare state, and relatively low levels of government corruption. Voter participation is among the highest in the world, topping 80 percent in the past elections. Access to education and healthcare is free to all citizens. How can we best explain Botswana’s exceptionalism in the political, economic, and social realms, and what policy lessons does the case of Botswana contain? This article shows that it is Botswana’s millennial tradition of direct village democracy, kgotla, that best explains its exceptional performance. I visited Botswana in May of 2023 to evaluate the importance of participatory democracy in Botswana and assess its explanatory power. When comparing local participation to other, potentially relevant causal factors, I find that local political participation provides the most robust explanation for good governance in Botswana. In Botswana, citizens are able to hold their elected officials accountable, learn how politics works by acquiring the necessary technical knowledge (techne) through participating in regular, monthly public assemblies, and, as a result, make better-informed political decisions.
A Bibliometric Analysis on the Topic of Social Policy
Authors: Carradore Marco
Published: September 2024

Social policy relates to a variety of social phenomena. Over recent decades, it has attracted the interest of scholars from a variety of academic disciplines as well as that of national and international organizations. This study applied the bibliometric approach to identify and analyse articles present in the Web of Science database, published in the English language, containing the term social policy in the title, abstract, or author keywords. Bibliometric networks and analyses were conducted using bibliometrix and VOSviewer software. The results show that the publication trend of articles on social policy varied over time and in association with social phenomena; for instance, an increase in publications occurred in the wake of the 2008 financial crisis. COVID-19, environmental issues, migration, and austerity were the main social policy topics being addressed in more recent investigations. This paper advances our knowledge about the research trends on the topic of social policy. This analysis included all articles published until the end of 2023 and can thus be considered to be up to date at the time of publication. It highlights the latest topics social policy has become interested in and the range of research disciplines it is associated with.
Environmental Biomonitoring of Heavy and Toxic Metals Using Honeybees and Their Products—An Overview of Previous Research
Authors: Zavrtnik Saša , Loborec Jelena , Kapelj Sanja , Grčić Ivana
Published: September 2024

Humans and bees share millennia of history that have resulted in ever-increasing connection and interdependence. Thus, today, it is impossible to ignore the influence of humans on bees, particularly regarding the decrease in their numbers due to environmental contamination. Although they do not cause immediate mortality, heavy and toxic metals, along with dangers such as bee diseases, pesticides, habitat destruction, and climate change, threaten the number of bees and should not be ignored. Honeybees, their colonies, and their products are recognized as accumulators of metals and biological indicators of the presence of these metals in all environmental components. This study is an overview of prominent research from the past three decades on heavy and toxic metal levels in honeybees (Apis mellifera L.), honey, wax, and pollen. This research compares metals such as Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Se, and Zn in natural environments and in an environment where anthropogenic pressure manifests. The presented studies represent a range of research using analytical methods to determine the presence of heavy and toxic metals in different segments of bees and their products, linking these findings with the state of the environment. It has been repeatedly established that if heavy and toxic metals are present in higher concentrations in components of the environment that are under anthropogenic pressure, then their concentrations in bees, honey, and wax will also be higher. By summarizing this research in one place, this study can provide guidelines for future scientific work on this subject, promoting sustainable development through safe beekeeping and healthy bees.
Overcoming the Learning Curve in Robot-Assisted Spinal Surgery—How Does It Compare to O-Arm Navigation?
Authors: Paramasivam Meenakshi Sundaram Pirateb , Lai Mun Chun , Kaliya-Perumal Arun-Kumar , Oh Jacob Yoong-Leong
Published: September 2024

Background: Robotic systems have the potential to significantly enhance the accuracy and outcomes of spinal surgery. Adopting this new technology requires an examination of its learning curve and influencing factors. This study analyzes the learning curve associated with using the Mazor X Stealth Edition system for pedicle screw placement and performs a matched-pair analysis to compare operative durations between robot-assisted and navigation-based surgeries, evaluating the efficiency of the robotic system. Methods: We collected retrospective operative data from patients who underwent robot-assisted pedicle screw placements between December 2020 and June 2024 and conducted a cumulative sum (CuSUM) analysis to assess the learning curve, focusing on the robotic system’s setup duration. Additionally, we compared a group of patients who underwent robot-assisted pedicle screw placements with a pair-matched group who underwent O-arm-based navigation-assisted pedicle screw placements. Results: There was a notable decrease in the robotic setup duration, with a significant shift in trend observed after the first 20 cases. While the initial setup time was 24 minutes, it reduced to 17 minutes in later cases, reflecting a marked improvement in efficiency as the surgeon gained more experience with the robot. Conclusion: Our findings indicate there were no added difficulties using the robotic system compared to the navigation system. Moreover, the learning curve for the robotic system can be quickly surmounted, and it offers clear advantages over previous systems, making it a valuable tool for pedicle screw application.
Real-Time Identification of Strawberry Pests and Diseases Using an Improved YOLOv8 Algorithm
Authors: Xie Danyan , Yao Wenyi , Sun Wenbo , Song Zhenyu
Published: September 2024

Strawberry crops are susceptible to a wide range of pests and diseases, some of which are insidious and diverse due to the shortness of strawberry plants, and they pose significant challenges to accurate detection. Although deep learning-based techniques to detect crop pests and diseases are effective in addressing these challenges, determining how to find the optimal balance between accuracy, speed, and computation remains a key issue for real-time detection. In this paper, we propose a series of improved algorithms based on the YOLOv8 model for strawberry disease detection. These include improvements to the Convolutional Block Attention Module (CBAM), Super-Lightweight Dynamic Upsampling Operator (DySample), and Omni-Dimensional Dynamic Convolution (ODConv). In experiments, the accuracy of these methods reached 97.519%, 98.028%, and 95.363%, respectively, and the F1 evaluation values reached 96.852%, 97.086%, and 95.181%, demonstrating significant improvement compared to the original YOLOv8 model. Among the three improvements, the improved model based on CBAM has the best performance in training stability and convergence, and the change in each index is relatively smooth. The model is accelerated by TensorRT, which achieves fast inference through highly optimized GPU computation, improving the real-time identification of strawberry diseases. The model has been deployed in the cloud, and the developed client can be accessed by calling the API. The feasibility and effectiveness of the system have been verified, providing an important reference for the intelligent research and application of strawberry disease identification.