bluuebunny/crossref_metadata_2025 huggingface dataset:
Flow-diverter stents combined with flow-T stenting-assisted coiling for the treatment of a large basilar apex aneurysm: a case report with a 9-month follow-up
Authors: Wang Hao , Zhang Jingyu , Yang Huajiang , Zeng Shi , Guo Tengyun , Xu Lunshan , Yang Donghong
Published: January 2024

Background

Endovascular or surgical treatment of wide-neck, large basilar apex aneurysms is challenging. We present a novel concept for the treatment of complex basilar apex aneurysms using flow-diverter devices combined with the flow-T stenting-assisted coiling technique. Assess the efficacy and safety profile of the technique in this complex aneurysm.

Case description

A patient with multiple unruptured intracranial aneurysms underwent staged treatment. A large basilar apex aneurysm was treated with a flow-diverter stent combined with a flow-T stenting-assisted coiling technique in the first stage, and a giant supraclinoid aneurysm was treated with a flow-diverter stent applied in the second stage. Clinical presentations, technical details, intra- and perioperative complications, and clinical and angiographic outcomes were recorded, with a 9-month follow-up.

Results

The patient achieved full neurologic recovery postoperatively. Cerebral angiography performed postoperatively showed revascularization, good laminar flow, and no in-stent or adjacent stenosis.

Conclusion

Flow-diverter stents combined with flow-T stenting-assisted coiling for the treatment of giant basilar apex aneurysms is a feasible technique with efficacy demonstrated at a 9-month follow-up. Staged endovascular treatment of multiple intracranial aneurysms may be a safe and viable option.
NeuroAIreh@b: an artificial intelligence-based methodology for personalized and adaptive neurorehabilitation
Authors: Faria Ana Lúcia , Almeida Yuri , Branco Diogo , Câmara Joana , Cameirão Mónica , Ferreira Luis , Moreira André , Paulino Teresa , Rodrigues Pedro , Spinola Mónica , Vilar Manuela , Bermúdez i Badia Sergi , Simões Mario , Fermé Eduardo
Published: January 2024

Cognitive impairments are a prevalent consequence of acquired brain injury, dementia, and age-related cognitive decline, hampering individuals' daily functioning and independence, with significant societal and economic implications. While neurorehabilitation represents a promising avenue for addressing these deficits, traditional rehabilitation approaches face notable limitations. First, they lack adaptability, offering one-size-fits-all solutions that may not effectively meet each patient's unique needs. Furthermore, the resource-intensive nature of these interventions, often confined to clinical settings, poses barriers to widespread, cost-effective, and sustained implementation, resulting in suboptimal outcomes in terms of intervention adaptability, intensity, and duration. In response to these challenges, this paper introduces NeuroAIreh@b, an innovative cognitive profiling and training methodology that uses an AI-driven framework to optimize neurorehabilitation prescription. NeuroAIreh@b effectively bridges the gap between neuropsychological assessment and computational modeling, thereby affording highly personalized and adaptive neurorehabilitation sessions. This approach also leverages virtual reality-based simulations of daily living activities to enhance ecological validity and efficacy. The feasibility of NeuroAIreh@b has already been demonstrated through a clinical study with stroke patients employing a tablet-based intervention. The NeuroAIreh@b methodology holds the potential for efficacy studies in large randomized controlled trials in the future.
Brentuximab vedotin as a bridge to combination chemotherapy in gray zone lymphoma with severe liver impairment: a case report
Authors: Asrani Roshan , Cengiz Turgot Bora , Petersen Bruce E. , Anagnostou Theodora , Brody Joshua D.
Published: January 2024

Background

Gray zone lymphoma (GZL) is a rare lymphoma subtype characterized by features intermediate between diffuse large B-cell lymphoma (DLBCL) and classic Hodgkin lymphoma (cHL). The optimal first-line treatment for GZL remains undefined, particularly for patients with poor performance status or baseline organ impairment. Brentuximab vedotin (BV), a targeted therapy that binds to CD30, a TNFR superfamily member involved in NF-kB signaling, has shown promise in the treatment of CD30-positive lymphomas. However, its use in GZL, especially in patients with severe liver impairment, has not been reported previously.

Case description

We present a case of a 37-year-old male with GZL and severe liver impairment at initial presentation. The patient initially received monotherapy with BV, which resulted in a marked improvement in liver enzymes and bilirubin levels. Subsequently, combination cytotoxic chemotherapy consisting of dose-adjusted etoposide, prednisone, cyclophosphamide, and doxorubicin (DA-EP_CH) was added. Repeat imaging revealed near complete resolution of lymphadenopathy and significant reduction in hepatosplenomegaly. The patient completed a full course of chemotherapy and achieved a complete response. Follow-up examinations showed no evidence of recurrent disease, and the patient resumed full-time work.

Discussion

GZL poses diagnostic challenges due to its overlapping features with DLBCL and cHL. Accurate diagnosis relies on comprehensive histopathological evaluation, immunophenotyping, and molecular analysis. The optimal first-line treatment for GZL remains uncertain. BV shows promise as an addition to chemotherapy in GZL, even in the presence of severe liver impairment. The molecular pathogenesis of GZL is complex and heterogeneous, frequently involving aberrant NF-kB signaling and impaired apoptosis regulation via loss of TP53 expression. Understanding the underlying molecular mechanisms is essential for developing targeted therapies and identifying predictive biomarkers for treatment response.

Conclusion

This case demonstrates the successful use of BV as a bridge to cytotoxic chemotherapy in a GZL patient with severe liver impairment, highlighting its potential safety and efficacy even in the setting of end-organ failure. Further investigation is warranted to define optimal treatment strategies, identify predictive biomarkers, and improve outcomes for patients with this rare and challenging lymphoma subtype.
A nomogram based on CT intratumoral and peritumoral radiomics features preoperatively predicts poorly differentiated invasive pulmonary adenocarcinoma manifesting as subsolid or solid lesions: a double-center study
Authors: Yang Zebin , Dong Hao , Fu Chunlong , Zhang Zening , Hong Yao , Shan Kangfei , Ma Chijun , Chen Xiaolu , Xu Jieping , Pang Zhenzhu , Hou Min , Zhang Xiaowei , Zhu Weihua , Liu Linjiang , Li Weihua , Sun Jihong , Zhao Fenhua
Published: January 2024

Background

The novel International Association for the Study of Lung Cancer (IASLC) grading system suggests that poorly differentiated invasive pulmonary adenocarcinoma (IPA) has a worse prognosis. Therefore, prediction of poorly differentiated IPA before treatment can provide an essential reference for therapeutic modality and personalized follow-up strategy. This study intended to train a nomogram based on CT intratumoral and peritumoral radiomics features combined with clinical semantic features, which predicted poorly differentiated IPA and was tested in independent data cohorts regarding models’ generalization ability.

Methods

We retrospectively recruited 480 patients with IPA appearing as subsolid or solid lesions, confirmed by surgical pathology from two medical centers and collected their CT images and clinical information. Patients from the first center (n =363) were randomly assigned to the development cohort (n = 254) and internal testing cohort (n = 109) in a 7:3 ratio; patients (n = 117) from the second center served as the external testing cohort. Feature selection was performed by univariate analysis, multivariate analysis, Spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the model performance.

Results

The AUCs of the combined model based on intratumoral and peritumoral radiomics signatures in internal testing cohort and external testing cohort were 0.906 and 0.886, respectively. The AUCs of the nomogram that integrated clinical semantic features and combined radiomics signatures in internal testing cohort and external testing cohort were 0.921 and 0.887, respectively. The Delong test showed that the AUCs of the nomogram were significantly higher than that of the clinical semantic model in both the internal testing cohort(0.921 vs 0.789, p< 0.05) and external testing cohort(0.887 vs 0.829, p< 0.05).

Conclusion

The nomogram based on CT intratumoral and peritumoral radiomics signatures with clinical semantic features has the potential to predict poorly differentiated IPA manifesting as subsolid or solid lesions preoperatively.
Effects of beta-blockers use on mortality of patients with acute respiratory distress syndrome: a retrospective cohort study
Authors: Dong Yukang , Sun Run , Fu Jiangquan , Huang Rui , Yao Huan , Wang Jingni , Wang Ying , Shen Feng
Published: January 2024

Introduction: Acute respiratory distress syndrome (ARDS) remains a challenging disease with limited prevention and treatment options. The usage of beta-blockers may have potential benefits in different critical illnesses. This study aimed to investigate the correlation between beta-blocker therapy and mortality in patients with ARDS.

Materials and methods: This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care (MIMIC) IV database and focused on patients diagnosed with ARDS. The primary outcome of the study was 30-day mortality. To account for confounding factors, a multivariable analysis was performed. Propensity score matching (PSM) was carried out on a 1:1 ratio. Robust assessments were conducted using inverse probability weighting (IPTW), standardized mortality ratio weighting (SMRW), pairwise algorithms (PA), and overlap weights (OW).

Results: A total of 1,104 patients with ARDS were included in the study. Univariate and multivariate Cox regression analyses found that the 30-day mortality for 489 patients (23.7%) who received beta-blockers was significantly lower than the mortality rate of 615 patients (35.9%) who did not receive beta-blockers. After adjusting for potential confounders through PSM and propensity score, as well as utilizing IPTW, SMRW, PA, and OW, the results remained robust, with the hazard ratios (HR) ranging from 0.42 to 0.58 and all p-values < 0.001. Evaluation of the E-values indicated the robustness of the results even in the presence of unmeasured confounding.

Conclusion: The findings suggest a potential association between beta-blocker usage and reduced mortality in critically ill patients with ARDS. However, further validation of this observation is needed through randomized controlled trials.
Genome-wide analysis and expression of the aquaporin gene family in Avena sativa L.
Authors: Zhou Xinyue , Yi Dengxia , Ma Lin , Wang Xuemin
Published: January 2024

Background

Oat (Avena sativa L.) belongs to the early maturity grass subfamily of the Gramineae subfamily oats (Avena) and has excellent characteristics, such as tolerance to barrenness, salt, cold, and drought. Aquaporin (AQP) proteins belong to the major intrinsic protein (MIP) superfamily, are widely involved in plant growth and development, and play an important role in abiotic stress responses. To date, previous studies have not identified or analyzed the AsAQP gene family system, and functional studies of oat AQP genes in response to drought, cold, and salt stress have not been performed.

Methods

In this study, AQP genes (AsAQP) were identified from the oat genome, and various bioinformatics data on the AQP gene family, gene structure, gene replication, promoters and regulatory networks were analyzed. Quantitative real-time PCR technology was used to verify the expression patterns of the AQP gene family in different oat tissues under different abiotic stresses.

Results

In this study, a total of 45 AQP genes (AsAQP) were identified from the oat reference genome. According to a phylogenetic analysis, 45 AsAQP were divided into 4 subfamilies (PIP, SIP, NIP, and TIP). Among the 45 AsAQP, 23 proteins had interactions, and among these, 5AG0000633.1 had the largest number of interacting proteins. The 20 AsAQP genes were expressed in all tissues, and their expression varied greatly among different tissues and organs. All 20 AsAQP genes responded to salt, drought and cold stress. The NIP subfamily 6Ag0000836.1 gene was significantly upregulated under different abiotic stresses and could be further verified as a key candidate gene.

Conclusion

The findings of this study provide a comprehensive list of members and their sequence characteristics of the AsAQP protein family, laying a solid theoretical foundation for further functional analysis of AsAQP in oats. This research also offers valuable reference for the creation of stress-tolerant oat varieties through genetic engineering techniques.
Cli-fi videos can increase charitable donations: experimental evidence from the United Kingdom
Authors: Shreedhar Ganga , Sabherwal Anandita , Maldonado Ricardo
Published: January 2024

Recent research has begun to investigate if climate fiction, or cli-fi, can increase people’s support for pro-climate initiatives. Emerging evidence focuses on whether cli-fi stories affect people’s self-reported emotions, attitudes, and intentions. Few studies, however, examine the effect of such stories on revealed behavior, and whether the cli-fi story medium, i.e., whether stories are presented in text, audio, or audio-visual format, matters. We investigate the causal effect of cli-fi stories, and the medium through which they are communicated (textual, audio, or audio-visual) on self-reported support for climate policy, individual and collective action intentions, and a revealed measure of charitable donations. In a pre-registered online experiment (n = 1,085 UK adults), participants were randomly assigned to one of 5 conditions – to read scientific information about climate change (scientific information condition), read a story unrelated to the environment (control), read a cli-fi story in which a protagonist took intentional pro-environmental actions (fiction text), listen to the same cli-fi story in audio format (fiction audio), or watch an animation of the cli-fi story (fiction video). When comparing the fiction-text, fact-text, and control conditions, we found that cli-fi stories are not always more effective than alternative climate communications: participants in the fact-text condition reported higher support for climate policies, and intentions of taking individual environmental actions, and negative feelings of sadness, disappointment, and guilt, compared to the text-based control and cli-fi text condition. When comparing the cli-fi media format, we found that cli-fi videos were most effective in increasing pro-environmental charitable donations in an incentivized choice task, and self-reported feelings of happiness, hope, and inspiration. The findings show that scientific information about the climate and climate-fiction have an important place in the climate communications toolkit and can offer distinct pathways to enhance support for policy and behavioral change. Communicators seeking to inspire individual pro-environmental actions can consider telling cli-fi stories in video, which may be more compelling. And communicators seeking to enhance public support for societal changes, via climate policies, may benefit from disseminating scientific information about climate change.
Diurnal patterns in Twitter sentiment in Italy and United Kingdom are correlated
Authors: Wang Sheng , Lightman Stafford , Cristianini Nello
Published: January 2024

Diurnal variations in indicators of emotion have been reliably observed in Twitter content, but confirmation of their circadian nature has not been possible due to the many confounding factors present in the data. We report on correlations between those indicators in Twitter content obtained from 9 cities of Italy and 54 cities in the United Kingdom, sampled hourly at the time of the 2020 national lockdowns. This experimental setting aims at minimizing synchronization effects related to television, eating habits, or other cultural factors. This correlation supports a circadian origin for these diurnal variations, although it does not exclude the possibility that similar zeitgebers exist in both countries including during lockdowns.
Effect of facial emotion recognition learning transfers across emotions
Authors: Bi Taiyong , Luo Wei , Wu Jia , Shao Boyao , Tan Qingli , Kou Hui
Published: January 2024

Introduction

Perceptual learning of facial expression is shown specific to the train expression, indicating separate encoding of the emotional contents in different expressions. However, little is known about the specificity of emotional recognition training with the visual search paradigm and the sensitivity of learning to near-threshold stimuli.

Methods

In the present study, we adopted a visual search paradigm to measure the recognition of facial expressions. In Experiment 1 (Exp1), Experiment 2 (Exp2), and Experiment 3 (Exp3), subjects were trained for 8 days to search for a target expression in an array of faces presented for 950 ms, 350 ms, and 50 ms, respectively. In Experiment 4 (Exp4), we trained subjects to search for a target of a triangle, and tested them with the task of facial expression search. Before and after the training, subjects were tested on the trained and untrained facial expressions which were presented for 950 ms, 650 ms, 350 ms, or 50 ms.

Results

The results showed that training led to large improvements in the recognition of facial emotions only if the faces were presented long enough (Exp1: 85.89%; Exp2: 46.05%). Furthermore, the training effect could transfer to the untrained expression. However, when the faces were presented briefly (Exp3), the training effect was small (6.38%). In Exp4, the results indicated that the training effect could not transfer across categories.

Discussion

Our findings revealed cross-emotion transfer for facial expression recognition training in a visual search task. In addition, learning hardly affects the recognition of near-threshold expressions.
Is the mainstream construction of mood disorders resistant to systemic thinking?
Authors: Fellin Lisa C. , Zizevskaia Ekaterina , Galbusera Laura
Published: January 2024

Introduction

In this study we explore how the diagnostic category of mood disorders is constructed in two handbooks of Psychopathology as an example of the mainstream construction of psychopathology. Despite the increasing criticism and lack of evidence, the debunked chemical imbalance theory of the etiology of depression still dominates the professional and pop/folk understanding and interventions.

Methods

We analysed the breadth of the inference field and the type of etiopathogenetic contents of the explanations of mood disorders using the “1to3” Coding System.

Results

Our findings show that the dominant explanations draw almost exclusively onto monadic explanations, followed by limited dyadic ones. Intrapersonal etiopathogenetic contents prevailed, and biomedical explanations were dominant in both textbooks.

Discussion

We critically discuss the underpinnings of these results and address the clinical implications of these biased representations, as well as potential alternative approaches to psychopathology.
Transient ischemic attack in the twenty first century: is it still a useful construct?
Authors: Caplan Louis R.
Published: January 2024

Some argue that the term transient ischemic attack (TIA) has become obsolete in the current age of advanced modern technology. Let us look back and analyze the term, its support and detraction, and its potential continued usefulness. The best way to begin is a review of the history of the term.
The need for communication between researchers and policymakers for the deployment of bioengineered carbon capture and sequestration crops
Authors: Gakpo Joseph Opoku , Hecate Arden , Ahmad Jabeen , Choi Jaimie , Matus Salvador Cruz , Mugisa Jill Dana , Ethridge Sandra , Utley Delecia , Zarate Sebastian
Published: January 2024

Bioengineered/genome-edited carbon capture and sequestration (BE/GEd-CCS) crops are being developed to mitigate climate change. This paper explores how technology, regulation, funding, and social implications, could shape the development and deployment of these crops. We conclude that some of the technological efforts to create BE/GEd-CCS crops may work. Still, stakeholders must agree on generally accepted methods of measuring how much carbon is captured in the soil and its value. The regulatory space for BE/GEd-CCS crops remains fluid until the first crops are reviewed. BE/GEd-CCS crops have received considerable initial funding and may benefit financially more from other federal programs and voluntary carbon markets. BE/GEd-CCS crops may continue perpetuating social equity concerns about agricultural biotechnology due to a lack of oversight. We argue that stakeholders need to pursue a multidisciplinary view of BE/GEd-CCS crops that draw in varying perspectives for effective development and deployment. Communication is needed between researchers and policymakers involved in either developing BE/GEd-CCS crops or developing voluntary carbon markets. We argue for the start of a conversation both across disciplines and between researchers and policymakers about the development and deployment of BE/GEd-CCS crops.
General anesthesia with local infiltration reduces urine retention rate and prolongs analgesic effect than spinal anesthesia for hemorrhoidectomy
Authors: Lin Chun-Yu , Liu Yi-Chun , Chen Jun-Peng , Hsu Pei-Hsuan , Chang Szu-Ling
Published: January 2024

Introduction

Postoperative pain and complications pose significant challenges following a hemorrhoidectomy. Attaining effective anesthesia with minimal complications is crucial. The ideal anesthesia method for ambulatory hemorrhoidectomy remains uncertain. This study aimed to investigate whether the combination of general anesthesia plus local infiltration (GAL) is associated with lower complications and reduced pain compared to spinal anesthesia (SA) in the context of hemorrhoidectomy.

Methods

This retrospective single-center cohort study, conducted in a tertiary medical center in East Asia, evaluated excisional hemorrhoidectomies performed between January 1, 2017, and March 31, 2023, utilizing GAL or SA. Data on the six most common complications-pain, constipation, acute urine retention (AUR), bleeding, nausea, and headache-were extracted from medical records. A total of 550 hemorrhoidectomies were included: 220 in the GAL group and 330 in the SA group. Patient characteristics were comparable between the two groups.

Results

The AUR rate was significantly lower in the GAL group compared to the SA group (15.5% vs. 32.1%, P < 0.001). Although the proportion of pain scores ≥4 did not differ significantly between the GAL and SA groups (36.2% vs. 39.8%, P = 0.429), the pain score curve indicated a stable trend. Overall, the GAL group exhibited a lower rate of adverse effects (56.9% vs. 67.4%, P = 0.023). There were no significant differences in the rates of other complications and emergency department readmission between the GAL and SA groups.

Discussion

GAL emerges as a favorable choice for anesthesia in hemorrhoidectomy, demonstrating a lower incidence of urine retention and a prolonged analgesic effect in multiple hemorrhoidectomies. These findings support the conclusion that GAL represents an optimal anesthetic method for enhancing the postoperative experience in patients undergoing hemorrhoidectomy.
Paraparesis due to angio-neurotropic Gurltia paralysans in a domestic cat (Felis catus) and retrospective study on feline gurltiosis cases in South America
Authors: Gómez Marcelo , Muñoz Pamela , Moroni Manuel , Mieres Marcelo , Bernal Valentina , Rosenfeld Carla , Taubert Anja , Hermosilla Carlos
Published: January 2024

Introduction

The nematodeGurltia paralysansis a neglected angio-neurotropic parasite causing chronic meningomyelitis in domestic cats (Felis catus) as well as wild felids of the genusLeopardusin South America. AdultG. paralysansnematodes parasitize the leptomeningeal veins of the subarachnoid space and/or meningeal veins of the spinal cord parenchyma. The geographic range ofG. paralysansencompasses rural and peri-urban regions of Chile, Argentina, Uruguay, Colombia and Brazil.

Methods

This case report presents clinical and pathological findings of aG. paralysans-infected cat suffering from severe thrombophlebitis and meningomyelitis resulting in ambulatory paraparesis. Neurological examination of affected cat localized the lesions at the thoracolumbar (T3–L3) and lumbosacral (L4–Cd4) segments. Molecular and morphological characteristics of extracted nematodes from parasitized spinal cord veins confirmedG. paralysans. Additionally, data obtained from a questionnaire answered by cat owners of 12 past feline gurltiosis cases (2014–2015) were here analyzed. Questionnaire collected data on age, gender, geographic location, type of food, hunting behavior, type of prey, and other epidemiological features ofG. paralysans-infected cats.

Results and Discussion

Data revealed that the majority of cats originated from rural settlements thereby showing outdoor life styles with hunting/predatory behaviors, being in close contact to wild life [i.e. gastropods, amphibians, reptiles, rodents, birds, and wild felids (Leopardus guinia)] and with minimal veterinary assistance. Overall, this neglected angio-neurotropicG. paralysansnematode still represents an important etiology of severe thrombophlebitis and meningomyelitis of domestic cats living in endemic rural areas with high biodiversity of definitive hosts (DH), intermediary (IH), and paratenic hosts (PH). The intention of this study is to generate awareness among veterinary surgeons as well as biologists on this neglected feline neuroparasitosis not only affecting domestic cats but also endangered wild felid species of the genusLeoparduswithin the South American continent.
Frequent Errors in Modeling by Machine Learning: A Prototype Case of Predicting the Timely Evolution of COVID-19 Pandemic
Authors: Héberger Károly
Published: January 2024

Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread with a similar speed independently from the tasks: regression and classification. This work summarizes frequent errors committed by certain authors with the aim of helping scientists to avoid them. Methods: The principle of parsimony governs the train of thought. Fair method comparison can be completed with multicriteria decision-making techniques, preferably by the sum of ranking differences (SRD). Its coupling with analysis of variance (ANOVA) decomposes the effects of several factors. Earlier findings are summarized in a review-like manner: the abuse of the correlation coefficient and proper practices for model discrimination are also outlined. Results: Using an illustrative example, the correct practice and the methodology are summarized as guidelines for model discrimination, and for minimizing the prediction errors. The following factors are all prerequisites for successful modeling: proper data preprocessing, statistical tests, suitable performance parameters, appropriate degrees of freedom, fair comparison of models, and outlier detection, just to name a few. A checklist is provided in a tutorial manner on how to present ML modeling properly. The advocated practices are reviewed shortly in the discussion. Conclusions: Many of the errors can easily be filtered out with careful reviewing. Every authors’ responsibility is to adhere to the rules of modeling and validation. A representative sampling of recent literature outlines correct practices and emphasizes that no error-free publication exists.
Numerical Algorithms in III–V Semiconductor Heterostructures
Authors: Tsoulos Ioannis G. , Stavrou V. N.
Published: January 2024

In the current research, we consider the solution of dispersion relations addressed to solid state physics by using artificial neural networks (ANNs). Most specifically, in a double semiconductor heterostructure, we theoretically investigate the dispersion relations of the interface polariton (IP) modes and describe the reststrahlen frequency bands between the frequencies of the transverse and longitudinal optical phonons. The numerical results obtained by the aforementioned methods are in agreement with the results obtained by the recently published literature. Two methods were used to train the neural network: a hybrid genetic algorithm and a modified version of the well-known particle swarm optimization method.
Distributed Data-Driven Learning-Based Optimal Dynamic Resource Allocation for Multi-RIS-Assisted Multi-User Ad-Hoc Network
Authors: Zhang Yuzhu , Xu Hao
Published: January 2024

This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present context of cellular networks, device-to-device (D2D) communication stands out as a promising technique to enhance the spectrum efficiency. Simultaneously, RIS have gained considerable attention due to their ability to enhance the quality of dynamic wireless networks by maximizing the spectrum efficiency without increasing the power consumption. However, prevalent centralized D2D transmission schemes require global information, leading to a significant signaling overhead. Conversely, existing distributed schemes, while avoiding the need for global information, often demand frequent information exchange among D2D users, falling short of achieving global optimization. This paper introduces a framework comprising an outer loop and inner loop. In the outer loop, decentralized dynamic resource allocation optimization has been developed for self-organizing network communication aided by RIS. This is accomplished through the application of a multi-player multi-armed bandit approach, completing strategies for RIS and resource block selection. Notably, these strategies operate without requiring signal interaction during execution. Meanwhile, in the inner loop, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm has been adopted for cooperative learning with neural networks (NNs) to obtain optimal transmit power control and RIS phase shift control for multiple users, with a specified RIS and resource block selection policy from the outer loop. Through the utilization of optimization theory, distributed optimal resource allocation can be attained as the outer and inner reinforcement learning algorithms converge over time. Finally, a series of numerical simulations are presented to validate and illustrate the effectiveness of the proposed scheme.
Impacts of Capital Endowment on Farmers’ Choices in Fertilizer-Reduction and Efficiency-Increasing Technologies (Preferences, Influences, and Mechanisms): A Case Study of Apple Farmers in the Provinces of Shaanxi and Gansu, China
Authors: Chen Yihan , Xiang Wen , Zhao Minjuan
Published: January 2024

On the basis of data collected from 1208 apple farmers in the provinces of Shaanxi and Gansu, this study utilizes the weighted-frequency method to investigate the priority sequence of farmers’ preferences in choosing fertilizer-reduction and efficiency-increasing technologies. Subsequently, ordered-probit models, a mediating-effect model, and a moderating-effect model are employed to empirically analyze the influence of capital endowment on farmers’ choices related to fertilizer-reduction and efficiency-increasing technologies and their underlying mechanisms. The study further examines how agricultural-technology extension moderates these mechanisms. The main findings are: (1) The priority sequence of farmers’ choices concerning fertilizer-reduction and efficiency-increasing technologies is as follows: organic fertilizer substitution, new efficient fertilizers, soil testing and formula fertilization, green manure cultivation, straw mulching, fertilizer-reduction application, and deep mechanical application. (2) Capital endowment significantly enhances farmers’ choices in fertilizer-reduction and efficiency-increasing technologies. (3) The mechanism analyses indicate that capital endowment can promote farmers’ choices in fertilizer-reduction and efficiency-increasing technologies by improving their information-acquisition capabilities. (4) Moderation effects reveal that agricultural-technology extension methods, such as technical training, financial subsidies, and government publicity, significantly and positively moderate the relationship between information-acquisition capabilities and farmers’ choices in fertilizer-reduction and efficiency-increasing technologies. The moderating effects of educational attainment and generational differences on different agricultural-technology extension methods are heterogeneous. Technical training, financial subsidies, and government publicity can effectively enhance the positive impact of information-acquisition capabilities on farmers with a higher educational attainment. Financial subsidies can effectively strengthen the positive impact of information-acquisition capabilities on the older generation of farmers. Therefore, it is recommended to prioritize the accumulation of farmers’ capital endowment, improve their information-acquisition capabilities, and intensify agricultural-technology extension efforts, especially taking into account farmers’ educational attainment and generational differences.
Calibration of Simulation Parameters for Fresh Tea Leaves Based on the Discrete Element Method
Authors: Li Dongdong , Wang Rongyang , Zhu Yingpeng , Chen Jianneng , Zhang Guofeng , Wu Chuanyu
Published: January 2024

To address the problem of a lack of accurate parameters in the discrete element simulation study of the machine-picked fresh tea leaf mechanized-sorting process, this study used machine-picked fresh tea leaves as the research object, established discrete element models of different fresh tea leaf components in EDEM software version 7.0.0. based on the bonded particle model using three-dimensional scanning inverse-modeling technology, and calibrated the simulation parameters through physical tests and virtual simulation tests. Firstly, the intrinsic parameters of machine-picked tea leaves were measured using physical tests; the physical-stacking tea leaf test was conducted using the cylinder lifting method, the tea leaf repose angle being 32.62° as measured from the stacking images using CAD. With the physical repose angle as the target value, the Plackeet–Burman test, the steepest-ascent test and the Box–Behnken optimization test were conducted in turn, and the results showed that the static friction coefficient between tea leaves, the rolling friction coefficient between tea leaves and the static friction coefficient between tea leaves and PVC have a major effect on the repose angle, and the optimal combination of the three significant parameters was determined. Finally, five simulations were conducted using the optimal combination of parameters, the relative error between the repose angle measured by the simulation test and the physical repose angle being just 0.28%. Moreover, the t-test obtained p > 0.05, indicating that there was no significant difference between the simulation test results and the physical test results. The results showed that the calibrated discrete element simulation parameters obtained could provide a reference for the discrete element simulation study of fresh tea leaves.
Application of a Mechanistic Model to Explore Management Strategies for Biological Control of an Agricultural Pest
Authors: Barton Madeleine G. , Parry Hazel , Umina Paul A. , Binns Matthew R. , Heddle Thomas , Hoffmann Ary A. , Holloway Joanne , Severtson Dustin , Van Helden Maarten , Ward Samantha , Wood Rachel , Macfadyen Sarina
Published: January 2024

Despite the known benefits of integrated pest management, adoption in Australian broadacre crops has been slow, in part due to the lack of understanding about how pests and natural enemies interact. We use a previously developed process-based model to predict seasonal patterns in the population dynamics of a canola pest, the green peach aphid (Myzus persicae), and an associated common primary parasitic wasp (Diaeretiella rapae), found in this cropping landscape. The model predicted aphid population outbreaks in autumn and spring. Diaeretiella rapae was able to suppress these outbreaks, but only in scenarios with a sufficiently high number of female wasps in the field (a simulated aphid:wasp density ratio of at least 5:1 was required). Model simulations of aphid-specific foliar pesticide applications facilitated biological control. However, a broad-spectrum pesticide negated the control provided by D. rapae, in one case leading to a predicted 15% increase in aphid densities compared to simulations in which no pesticide was applied. Biological and chemical control could therefore be used in combination for the successful management of the aphid while conserving the wasp. This modelling framework provides a versatile tool for further exploring how chemical applications can impact pests and candidate species for biological control.
Predicting the Power Requirement of Agricultural Machinery Using ANN and Regression Models and the Optimization of Parameters Using an ANN–PSO Technique
Authors: Upadhyay Ganesh , Kumar Neeraj , Raheman Hifjur , Dubey Rashmi
Published: January 2024

Optimizing the design and operational parameters for tillage tools is crucial for improved performance. Recently, artificial intelligence approaches, like ANN with learning capabilities, have gained attention for cost-effective and timely problem solving. Soil-bin experiments were conducted and data were used to develop ANN and regression models using gang angle, velocity ratio, soil CI, and depth as input parameters, while tractor equivalent PTO (PTOeq) power was used as an output. Both models were trained with a randomly selected 90% of the data, reserving 10% for testing purposes. In regression, models were iteratively fitted using nonlinear least-squares optimization. The ANN model utilized a multilayer feed-forward network with a backpropagation algorithm. The comparative performance of both models was evaluated in terms of R2 and mean square error (MSE). The ANN model outperformed the regression model in the training, testing, and validation phases. A well-trained ANN model was integrated with the particle-swarm optimization (PSO) technique for optimization of the operational parameters. The optimized configuration featured a 36.6° gang angle, 0.50 MPa CI, 100 mm depth, and 3.90 velocity ratio for a predicted tractor PTOeq power of 3.36 kW against an actual value of 3.45 kW. ANN–PSO predicted the optimal parameters with a variation between the predicted and the actual tractor PTOeq power within ±6.85%.
Neonicotinoid Insecticide-Degrading Bacteria and Their Application Potential in Contaminated Agricultural Soil Remediation
Authors: Zeng Yuechun , Sun Shaolin , Li Pengfei , Zhou Xian , Wang Jian
Published: January 2024

Recent advances in the microbial degradation of persistent organic pollutants have the potential to mitigate the damage caused by anthropogenic activities that are harmfully impacting agriculture soil ecosystems and human health. In this paper, we summarize the pollution characteristics of neonicotinoid insecticides (NNIs) in agricultural fields in China and other countries and then discuss the existing research on screening for NNI-degrading functional bacterial strains, their degradation processes, the construction of microbial consortia, and strategies for their application. We explore the current needs and solutions for improving the microbial remediation rate of NNI-contaminated soil and how these solutions are being developed and applied. We highlight several scientific and technological advances in soil microbiome engineering, including the construction of microbial consortia with a broad spectrum of NNI degradation and microbial immobilization to improve competition with indigenous microorganisms through the provision of a microenvironment and niche suitable for NNI-degrading bacteria. This paper highlights the need for an interdisciplinary approach to improving the degradation capacity and in situ survival of NNI-degrading strains/microbial consortia to facilitate the remediation of NNI-contaminated soil using strains with a broad spectrum and high efficiency in NNI degradation.
Influence of Nitrogen Applications during Grain-Filling Stage on Rice (Oryza sativa L.) Yield and Grain Quality under High Temperature
Authors: Dou Zhi , Zhou Yicheng , Zhang Yaoyuan , Guo Wei , Xu Qiang , Gao Hui
Published: January 2024

High temperature frequently occurs during rice’s early grain-filling period in the south of China, negatively affecting rice yield and quality and posing a major threat to local rice production. This experiment researched the influence of 3.5 °C warming during the first 20 grain-filling days on rice yield and quality and emphatically investigated the effects of the low-broadcast nitrogen fertilizer application level (LBN), high-broadcast nitrogen fertilizer application level (HBN) and foliar nitrogen fertilizer application (FN) at heading on the rice organ temperature, leaf photosynthesis, chlorophyll fluorescence, yield and grain quality, pasting and thermal properties under high temperature in 2020 and 2022, with a widely planted japonica rice variety, “Wuyunjing31”, in order to explore the practical mitigation measures for reducing the adverse impact of high temperature on rice productivity. The results showed that high temperatures during grain filling increased the rice plant temperature, damaged the chlorophyll fluorescence system and decreased the net photosynthesis rate. This led to a decline in the seed-setting rate and grain weight, resulting in a 7.0% and 13.9% yield loss in 2020 and 2022, respectively. In addition, high temperature caused a decline in the head rice rate and an increase in chalk occurrence and pasting temperature, thereby deteriorating rice grain quality. Under high temperatures, HBN enhanced the rice yield by 3.6% and 13.0% in 2020 and 2022, respectively, while FN enhanced the rice yield by 11.5% in 2022. The increase in yield was linked to the increased seed-setting rate and 1000-grain weight. LBN did not significantly affect the rice yield under high temperatures. The positive effects of nitrogen fertilizer measures on rice yield were associated with their role in lowering plant temperature and protection against the damage to the chlorophyll fluorescence system. All three nitrogen application measures generally improved rice milling quality and appearance quality under high temperature, with HBN generally showing the greatest impact. Under high temperature, LBN and FN tended to make the texture of cooked rice softer due to the decreased consistency, retrogradation enthalpy and retrogradation percentage, and this was closely associated with the decline in amylose content. In summary, nitrogen supplementation at the heading could efficiently mitigate the adverse impact of high temperature during the early grain-filling period on rice yield and quality.
Alternative and Sustainable Protein Sources in Pig Diet: A Review
Authors: Lestingi Antonia
Published: January 2024

The search for alternative protein sources to soybean meal (SBM) in animal feeding is a strategic objective to reduce production costs and contribute to sustainable animal production. Spirulina, due to the high protein content, has emerged as a potential cost-effective, sustainable, viable, and high-nutritional-value food resource for many animal species. Insect larvae (Tenebrio molitor and Hermetia illucens) are also considered potential alternatives to SBM, given their high edible percentage of almost 100%, as well as a protein value higher than that of vegetable proteins. Rapeseed meal and grain legumes, such as fava beans, peas, lupins, and chickpea, can also be used as locally producible protein ingredients. This study reviews the nutritional value of these potential alternatives to SBM in pig diets, and their effects on animal performance, digestion, immune system, and the physicochemical and sensorial characteristics of meat, including processed pork products. The limits on their use in pig feeding are also reviewed to indicate gaps to be filled in future research on the supplementation level of these potential alternative protein sources in pig diets.
Public Patterns and Determinants of Antibiotic Self-Medication and Antibiotic Knowledge in Southern Jordan
Authors: Al-Tarawneh Alaa , Ali Tasneem , Al-Taani Ghaith M
Published: January 2024

Antibiotic self-medication, which refers to acquisition and using antibiotics to treat infections based on personal experience and/or without a doctor’s advice or prescription, is a significant public health issue jeopardizing patient health outcomes. The purpose of the present cross-sectional online survey was to assess the frequency of self-medication among the general public in various geographical locations in southern Jordan, as well as to examine the determinants to self-medication. The survey was distributed through several social media networks over the period November–December 2022, and included demographic information as well as items related to the use and abuse of antibiotics, information sources about antibiotics, the duration of use of antibiotics, and assessment of the public knowledge about appropriate antibiotic use. Inferential analysis, such as the Chi-Square test and logistic regression, were adopted to assess the associations between the different variables with self-medication. A total of 984 respondents were enrolled in the study. Of these, 752 had been using antibiotics during the last year. However, the self-medicating cases were 413 of the 752. The main source of information about the utilization of antibiotics among participants in the survey was pharmacists. The participants commonly (36.0%) tended to use antibiotics until the symptoms disappeared. Nearly half of the respondents reported usually taking antibiotics for treating a runny nose (rhinorrhea). The logistic regression analysis indicated that self-medication with antibiotics was significantly associated with female gender (p-value < 0.001), low educational level (p-value = 0.014), rural living location (p-value 0.003), no health insurance (p-value = 0.001) and occupation (p-value = 0.005). Meanwhile age had no significant relationship to self-medication. Finally, the results revealed poor understanding of key appropriate antibiotic usage, which inevitably influences self-medication practice. It is crucial to come up with several programs and governmental policies to suppress widespread antibiotic self-medication as it will affect the health of future generations of Jordanian citizens.