bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal management strategies of renewable energy systems with hyperexponential service provisioning: an economic investigation
Authors: Varshney Shreekant , Shekhar Chandra , Dhanunjaya Reddy A. V. , Pritam K. S. , Kantipudi M. V. V. Prasad , Kotb Hossam , AboRas Kareem , Alqarni Mohammed
Published: December 2023

The current research proposes optimal management strategies for queueing modeling-based renewable energy systems with hyper-exponentially distributed maintenance/repair under the assumption of an admission control policy. Using the concept and steps of the matrix-analytical method, the steady-state probability distribution associated with energy systems is explicitly presented. A relatively straightforward computation that can help with modeling wind energy generation, investigating wind farm performance, optimizing energy based on system storage, reliability inspection, service maintenance planning, and numerous other purposes can be employed to mathematically derive several system performance indicators. The investigation findings are validated via quantitative outcomes, illustrative possesses, and a step-by-step recursive methodology for efficient management of the renewable energy system. Additionally, considering multiple governing parameter values, the nature-inspired optimization technique, Cuckoo Search (CS), is employed to demonstrate the optimum anticipated cost of renewable energy system. A comparison with other metaheuristics and semi-classical approaches is also presented to establish the best convergence results. In order to help system designers, policymakers, engineers, and researchers, several numerical examples are also provided to construct more practical strategies based on the production of energy, storage, and system management. The economic, parametric, and performance investigation findings are highlighted, and the opportunities and recommendations for further research are provided. In a nutshell, the outcomes of the present analysis can be adopted to formulate the most effective economic strategies and regulate decision-making processes in the energy sectors.
Mitigation of heat island effect by green stormwater infrastructure: a comparative study between two diverse green spaces in Nanjing
Authors: Xu Haishun , Sheng Kai , Gao Jing
Published: December 2023

Introduction

Studies have shown that green spaces and water bodies can alleviate heat island effects. However, uncertainty remains regarding the characteristics and influence of Green Stormwater Infrastructures (GSIs) on the cooling effects under different weather conditions. To address this issue, a comparative study was conducted between the green spaces in a wetland park with GSIs and a general green space without GSIs.

Methods

In this study, atmospheric temperatures were collected from both green spaces using mobile measurements to compare the cold island effect. In addition, the precise characteristics of the surface temperatures of the underlying surfaces in the wetland park were explored using an Unmanned Aerial Vehicle (UAV).

Results

The results revealed that green spaces with GSIs had a stronger cooling effect on the surrounding thermal environment than green spaces without GSIs, in most cases. The heat fluxes of different types of underlying surfaces in green spaces with different GSIs varied at different time periods. During the daytime, permeable pavement and some grasslands had a warming effect. The cooling effect of the other underlying surfaces was in the order of water bodies>arbors>shrubs>grasslands. At night, the changes in heat flux were lower, and only the arbors showed cooling due to evapotranspiration.

Discussion

These findings may provide innovative ideas and methods for planning GSIs to mitigate the urban heat island effects.
IL-17A-driven psoriasis is critically dependent on IL-36 signaling
Authors: Fischer Berenice , Kübelbeck Tanja , Kolb Antonia , Ringen Julia , Waisman Ari , Wittmann Miriam , Karbach Susanne , Kölsch Stephan Marcus , Kramer Daniela
Published: December 2023

Plaque psoriasis is an autoinflammatory and autoimmune skin disease, affecting 1-3% of the population worldwide. Previously, high levels of IL-36 family cytokines were found in psoriatic skin lesions, thereby contributing to keratinocyte hyperproliferation and infiltration of immune cells such as neutrophils. While treatment with anti-IL36 receptor (IL36R) antibodies was recently approved for generalized pustular psoriasis (GPP), it remains unclear, if targeting the IL36R might also inhibit plaque psoriasis. Here we show that antibody-mediated inhibition of IL36R is sufficient to suppress imiquimod-induced psoriasis-like skin inflammation and represses the disease’s development in a model that depends on IL-17A overexpression in the skin. Importantly, treatment with anti-IL36R antibodies inhibited skin inflammation and attenuated psoriasis-associated, systemic inflammation. This is possibly due to a widespread effect of IL36R inhibition, which not only suppresses pro-inflammatory gene expression in keratinocytes, but also the activation of other immune cells such as T-cells or dendritic cells. In conclusion, we propose that inhibition of the IL-36 signaling pathway might constitute an attractive, alternative approach for treating IL-17A-driven psoriasis and psoriasis-linked comorbidities.
Blockade of mGluR5 in astrocytes derived from human iPSCs modulates astrocytic function and increases phagocytosis
Authors: de Lima Izabella B. Q. , Cardozo Pablo L. , Fahel Julia S. , Lacerda Juliana P. S. , Miranda Aline S. , Teixeira Antônio L. , Ribeiro Fabiola M.
Published: December 2023

TNF-α is essential for induction and maintenance of inflammatory responses and its dysregulation is associated with susceptibility to various pathogens that infect the central nervous system. Activation of both microglia and astrocytes leads to TNF-α production, which in turn triggers further activation of these cells. Astrocytes have been implicated in the pathophysiology of a wide range of neurodegenerative diseases with either harmful or protective roles, as these cells are capable of secreting several inflammatory factors and also promote synapse elimination and remodeling. These responses are possible because they sense their surroundings via several receptors, including the metabotropic glutamate receptor 5 (mGluR5). Under neuroinflammatory conditions, mGluR5 activation in astrocytes can be neuroprotective or have the opposite effect. In the current study, we investigated the role of mGluR5 in hiPSC-derived astrocytes subjected to pro-inflammatory stimulation by recombinant TNF-α (rTNF-α). Our results show that mGluR5 blockade by CTEP decreases the secreted levels of pro-inflammatory cytokines (IL-6 and IL-8) following short rTNF-α stimulation, although this effect subsides with time. Additionally, CTEP enhances synaptoneurosome phagocytosis by astrocytes in both non-stimulated and rTNF-α-stimulated conditions, indicating that mGluR5 blockade alone is enough to drive synaptic material engulfment. Finally, mGluR5 antagonism as well as rTNF-α stimulation augment the expression of the reactivity marker SERPINA3 and reduces the expression of synaptogenic molecules. Altogether, these data suggest a complex role for mGluR5 in human astrocytes, since its blockade may have beneficial and detrimental effects under inflammatory conditions.
The combination of soluble forms of PD-1 and PD-L1 as a predictive marker of PD-1 blockade in patients with advanced cancers: a multicenter retrospective study
Authors: Kurosaki Takashi , Chamoto Kenji , Suzuki Shinichiro , Kanemura Hiroaki , Mitani Seiichiro , Tanaka Kaoru , Kawakami Hisato , Kishimoto Yo , Haku Yasuharu , Ito Katsuhiro , Sato Toshiyuki , Suminaka Chihiro , Yamaki Mami , Chiba Yasutaka , Yaguchi Tomonori , Omori Koichi , Kobayashi Takashi , Nakagawa Kazuhiko , Honjo Tasuku , Hayashi Hidetoshi
Published: December 2023

Introduction

The clinical relevance of soluble forms of programmed cell death-1 (sPD-1) and programmed cell death-ligand 1 (sPD-L1) remains unclear. We here investigated the relation between the efficacy of PD-1 blockade and pretreatment plasma levels of sPD-1 and sPD-L1 across a broad range of cancer types.

Methods

We retrospectively analyzed clinical data from 171 patients with advanced solid tumors who received nivolumab or pembrolizumab monotherapy regardless of treatment line. The concentrations of sPD-1 and sPD-L1 were measured with a fully automated immunoassay (HISCL system).

Results

The study subjects comprised patients with head and neck cancer (n = 50), urothelial cancer (n = 42), renal cell cancer (n = 37), gastric cancer (n = 20), esophageal cancer (n = 10), malignant pleural mesothelioma (n = 6), or microsatellite instability-high tumors (n = 6). High or low levels of sPD-1 or sPD-L1 were not significantly associated with progression-free survival (PFS) or overall survival (OS) for PD-1 blockade in the entire study population. Comparison of treatment outcomes according to combinations of high or low sPD-1 and sPD-L1 levels, however, revealed that patients with low sPD-1 and high sPD-L1 concentrations had a significantly poorer PFS (HR of 1.79 [95% CI, 1.13–2.83], p = 0.01) and a tendency toward poorer OS (HR of 1.70 [95% CI, 0.99–2.91], p = 0.05) compared with all other patients.

Conclusion

Our findings suggest that the combination of low sPD-1 and high sPD-L1 levels is a potential negative biomarker for PD-1 blockade therapy.
The clinical development of antibody-drug conjugates for non-small cell lung cancer therapy
Authors: Liu Xinlin , Deng Junwen , Zhang Renshuai , Xing Jiyao , Wu Yudong , Chen Wujun , Liang Bing , Xing Dongming , Xu Jiazhen , Zhang Miao
Published: December 2023

Despite the emergence of molecular targeted therapy and immune checkpoint inhibitors as standard first-line treatments for non-small cell lung cancer (NSCLC), their efficacy in some patients is limited by intrinsic and acquired resistance. Antibody-drug conjugates (ADCs), a revolutionary class of antitumor drugs, have displayed promising clinical outcomes in cancer treatment. In 2022, trastuzumab deruxtecan (Enhertu) was approved for treating HER2-mutated NSCLC, thereby underscoring the clinical value of ADCs in NSCLC treatment strategies. An increasing number of ADCs, focusing on NSCLC, are undergoing clinical trials, potentially positioning them as future treatment options. In this review, we encapsulate recent advancements in the clinical research of novel ADCs for treating NSCLC. Subsequently, we discuss the mechanisms of action, clinical efficacy, and associated limitations of these ADCs.
Complete genome sequence of Nguyenibacter sp. L1, a phosphate solubilizing bacterium isolated from Lespedeza bicolor rhizosphere
Authors: Li Xiao Li , Lv Xin Yang , Ji Jun Bin , Wang Wei Duo , Wang Ji , Wang Cong , He Hai Bin , Ben Ai Ling , Liu Ting Li
Published: December 2023

Phosphorus (P) deficiency is a predominant constraint on plant growth in acidified soils, largely due to the sequestration of P by toxic aluminum (Al) compounds. Indigenous phosphorus-solubilizing bacteria (PSBs) capable of mobilizing Al-P in these soils hold significant promise. A novel Al-P-solubilizing strain, Al-P Nguyenibacter sp. L1, was isolated from the rhizosphere soil of healthy Lespedeza bicolor plants indigenous to acidic terrains. However, our understanding of the genomic landscape of bacterial species within the genus Nguyenibacter remains in its infancy. To further explore its biotechnological potentialities, we sequenced the complete genome of this strain, employing an amalgamation of Oxford Nanopore ONT and Illumina sequencing platforms. The resultant genomic sequence of Nguyenibacter sp. L1 manifests as a singular, circular chromosome encompassing 4,294,433 nucleotides and displaying a GC content of 66.73%. The genome was found to host 3,820 protein-coding sequences, 12 rRNAs, and 55 tRNAs. Intriguingly, annotations derived from the eggNOG and KEGG databases indicate the presence of genes affiliated with phosphorus solubilization and nitrogen fixation, including iscU, glnA, and gltB/D associated with nitrogen fixation, and pqqBC associated with inorganic phosphate dissolution. Several bioactive secondary metabolite genes in the genome, including pqqCDE, phytoene synthase and squalene synthase predicted by antiSMASH. Moreover, we uncovered a complete metabolic pathway for ammonia, suggesting an ammonia-affinity property inherent to Nguyenibacter sp. L1. This study verifies the nitrogen-fixing and phosphate-dissolving abilities of Nguyenibacter sp. L1 at the molecular level through genetic screening and analysis. The insights gleaned from this study offer strategic guidance for future strain enhancement and establish a strong foundation for the potential incorporation of this bacterium into agricultural practices.
MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations
Authors: Chen Xingyu , Chen Fanxuan , Liang Chenglong , He Guoqiang , Chen Hao , Wu Yanchan , Chen Yinda , Shuai Jincen , Yang Yilei , Dai Chenyue , Cao Luhuan , Wang Xian , Cai Enna , Wang Jiamin , Wu Mengjing , Zeng Li , Zhu Jiaqian , Hai Darong , Pan Wangzheng , Pan Shuo , Zhang Chengxi , Quan Shichao , Su Feifei
Published: December 2023

Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.
Dyadic influences on awareness of condition in people with dementia: findings from the IDEAL cohort
Authors: Alexander Catherine M. , Martyr Anthony , Gamble Laura D. , Quinn Catherine , Pentecost Claire , Morris Robin G. , Clare Linda
Published: December 2023

Introduction

The discrepancy between caregiver-ratings and self-ratings of abilities is commonly used to assess awareness in people with dementia. We investigated the contribution of caregiver and dyadic characteristics to the difference in perspective between caregiver-informants and people with dementia about difficulties experienced, when considering awareness of condition.

Methods

We conducted exploratory cross-sectional analyses using data from the IDEAL cohort. Participants were 1,038 community-dwelling people with mild-to-moderate dementia, and coresident spouse/partner caregivers. The Representations and Adjustment to Dementia Index (RADIX) checklist reporting difficulties commonly experienced in dementia was completed by 960 caregiver-informants and 989 people with dementia. Difference in scores was calculated for 916 dyads. Demographic information, cognition, informant-rated functional ability and neuropsychiatric symptoms were recorded for the person with dementia. Self-reported data were collected on mood, comorbidity, religion, importance of religion, relationship quality, and caregiver stress.

Results

For most dyads, caregivers reported more RADIX difficulties than people with dementia. Caregiver RADIX ratings were more closely associated with informant-rated functional ability and neuropsychiatric symptoms than with cognition. More RADIX difficulties and higher stress were reported by female caregivers. Greater RADIX difference was associated with more caregiver stress, and older age but less depression in people with dementia.

Conclusion

Few dyadic characteristics were important, but caregiver stress was higher where caregivers reported more RADIX difficulties and/or the difference in perspective was greater, whereas partners with dementia reported better mood. In addition to offering information about awareness of condition, the caregiver rating and difference in perspectives could indicate where more support is needed.
An investigation of cardiac vagal tone over time and its relation to vigilance performance: a growth curve modeling approach
Authors: McGarry Shannon P. D. , Neilson Brittany N. , Brown Noelle L. , Strong Kaylin D. , Greenlee Eric T. , Klein Martina I. , Coyne Joseph T.
Published: December 2023

Introduction

Research over the last couple of decades has demonstrated a relationship between psychophysiological measures, specifically cardiac functions, and cognitive performance. Regulation of the cardiac system under parasympathetic control is commonly referred to as cardiac vagal tone and is associated with the regulation of cognitive and socioemotional states. The goal of the current study was to capture the dynamic relationship between cardiac vagal tone and performance in a vigilance task.

Method/Results

We implemented a longitudinal growth curve modeling approach which unveiled a relationship between cardiac vagal tone and vigilance that was non-monotonic and dependent upon each person.

Discussion

The findings suggest that cardiac vagal tone may be a process-based physiological measure that further explains how the vigilance decrement manifests over time and differs across individuals. This contributes to our understanding of vigilance by modeling individual differences in cardiac vagal tone changes that occur over the course of the vigilance task.
He Rourou Whai Painga, an Aotearoa New Zealand dietary pattern for metabolic health and whānau wellbeing: protocol for a randomized controlled trial
Authors: Lithander Fiona E. , Parry Strong Amber , Braakhuis Andrea , Worthington Anna , Foster Meika , Rolleston Anna , Davies Cheryl , Mullaney Jane , Ross Cecilia , Conroy Denise , Merry Troy L. , Gearry Richard , Weatherall Mark , Krebs Jeremy D.
Published: December 2023

Background

Cardiometabolic diseases are highly prevalent in Aotearoa New Zealand. Dietary intake is a modifiable risk factor for such diseases and certain dietary patterns, specifically the Mediterranean diet (MedDiet), are associated with improved metabolic health. This study aims to test whether an intervention including a Mediterranean dietary pattern incorporating high quality New Zealand foods (NZMedDiet pattern) and behavior change science can improve the metabolic health of participants and their household/whānau.

Methods and analysis

This is a multi-center, three-stage trial with two parallel group superiority randomized controlled trials (RCTs), and a longitudinal cohort study embedded within the trial design. The first RCT (RCT 1) is a comparison of the NZMedDiet pattern compared to usual diet for 12 weeks. The Behavior Change Wheel was used to select and implement strategies to support participant adherence to the NZMedDiet, such as web-based nutrition education on healthy shopping and cooking. The second (RCT 2) compares online social support to no online social support for 12 weeks, administered to participants immediately following RCT 1. The third stage is a longitudinal cohort study where all participants are followed from the beginning of their start of the active intervention for 12 months in total. The primary outcome measure for each stage is the metabolic syndrome severity score (MetSSS). The duration of enrolment is 12–15 months. The total recruitment target is 200 index participants and their household/whānau members who participate with them, and the primary analyses will be intention to treat on index participants.

Discussion

The trial will test whether the NZMedDiet pattern and behavior change support improves the cardiometabolic health of people in Aotearoa New Zealand.

Clinical trial registration

https://www.anzctr.org.au/Default.aspx, identifier ACTRN12622000906752 and https://www.isrctn.com/, identifier ISRCTN89011056 (Spirit 2).
Public mental health through social media in the post COVID-19 era
Authors: Sharma Deepika , Singh Jaiteg , Shah Babar , Ali Farman , AlZubi Ahmad Ali , AlZubi Mallak Ahmad
Published: December 2023

Social media is a powerful communication tool and a reflection of our digital environment. Social media acted as an augmenter and influencer during and after COVID-19. Many of the people sharing social media posts were not actually aware of their mental health status. This situation warrants to automate the detection of mental disorders. This paper presents a methodology for the detection of mental disorders using micro facial expressions. Micro-expressions are momentary, involuntary facial expressions that can be indicative of deeper feelings and mental states. Nevertheless, manually detecting and interpreting micro-expressions can be rather challenging. A deep learning HybridMicroNet model, based on convolution neural networks, is proposed for emotion recognition from micro-expressions. Further, a case study for the detection of mental health has been undertaken. The findings demonstrated that the proposed model achieved a high accuracy when attempting to diagnose mental health disorders based on micro-expressions. The attained accuracy on the CASME dataset was 99.08%, whereas the accuracy that was achieved on SAMM dataset was 97.62%. Based on these findings, deep learning may prove to be an effective method for diagnosing mental health conditions by analyzing micro-expressions.
Explainability as the key ingredient for AI adoption in Industry 5.0 settings
Authors: Agostinho Carlos , Dikopoulou Zoumpolia , Lavasa Eleni , Perakis Konstantinos , Pitsios Stamatis , Branco Rui , Reji Sangeetha , Hetterich Jonas , Biliri Evmorfia , Lampathaki Fenareti , Rodríguez Del Rey Silvia , Gkolemis Vasileios
Published: December 2023

Explainable Artificial Intelligence (XAI) has gained significant attention as a means to address the transparency and interpretability challenges posed by black box AI models. In the context of the manufacturing industry, where complex problems and decision-making processes are widespread, the XMANAI platform emerges as a solution to enable transparent and trustworthy collaboration between humans and machines. By leveraging advancements in XAI and catering the prompt collaboration between data scientists and domain experts, the platform enables the construction of interpretable AI models that offer high transparency without compromising performance. This paper introduces the approach to building the XMANAI platform and highlights its potential to resolve the “transparency paradox” of AI. The platform not only addresses technical challenges related to transparency but also caters to the specific needs of the manufacturing industry, including lifecycle management, security, and trusted sharing of AI assets. The paper provides an overview of the XMANAI platform main functionalities, addressing the challenges faced during the development and presenting the evaluation framework to measure the performance of the delivered XAI solutions. It also demonstrates the benefits of the XMANAI approach in achieving transparency in manufacturing decision-making, fostering trust and collaboration between humans and machines, improving operational efficiency, and optimizing business value.
Learning-based intelligent trajectory planning for auto navigation of magnetic robots
Authors: Kou Yuanshi , Liu Xurui , Ma Xiaotian , Xiang Yuanzhuo , Zang Jianfeng
Published: December 2023

Introduction: Electromagnetically controlled small-scale robots show great potential in precise diagnosis, targeted delivery, and minimally invasive surgery. The automatic navigation of such robots could reduce human intervention, as well as the risk and difficulty of surgery. However, it is challenging to build a precise kinematics model for automatic robotic control because the controlling process is affected by various delays and complex environments.

Method: Here, we propose a learning-based intelligent trajectory planning strategy for automatic navigation of magnetic robots without kinematics modeling. The Long Short-Term Memory (LSTM) neural network is employed to establish a global mapping relationship between the current sequence in the electromagnetic actuation system and the trajectory coordinates.

Result: We manually control the robot to move on a curved path 50 times to form the training database to train the LSTM network. The trained LSTM network is validated to output the current sequence for automatically controlling the magnetic robot to move on the same curved path and the tortuous and branched new paths in simulated vascular tracks.

Discussion: The proposed trajectory planning strategy is expected to impact the clinical applications of robots.
Organic food consumption in China: food safety concerns, perceptions, and purchase behavior under the moderating role of trust
Authors: Cao Dayu , Xie Qiang , Yao Xiaoying , Zheng Yan
Published: December 2023

Introduction

In tandem with economic growth and enhanced individual income levels, the demand for superior food quality has seen a significant uptick, leading to increased consumer interest in organic food products. However, studies focused on organic food consumption reveal a strikingly low conversion rate of this interest into actual purchasing behavior, particularly in the context of China. It is, therefore, crucial to implement effective strategies to bridge this gap, thereby fostering the growth of China's organic food sector.

Methods

This research introduces the theory of perceived values and innovation resistance into the stimulus-organism-response (SOR) theoretical model, exploring the interrelationships among various facets of food safety concerns, perceived values, perceived risks, and organic purchasing behavior. Furthermore, the moderating influence of trust in these relationships is taken into account. Employing structural equation modeling, data from 352 organic food consumers in China's premier cities were analyzed.

Results and discussion

Findings substantiated the significant interplay between perceived values and risks with food safety concerns. It was also observed that perceived values had a positive and significant impact on purchasing behavior, while perceived risks exerted a negative and significant influence. Importantly, the relationship between nutritional value and risk barrier with purchase behavior was found to be moderated by the level of trust. This study may help organic food producers, retailers, and policymakers bridge the consumers' intention-behavior gap.
The autologous chondral platelet-rich plasma matrix implantation. A new therapy in cartilage repair and regeneration: macroscopic and biomechanical study in an experimental sheep model
Authors: Peláez-Gorrea Pau , Damiá-Giménez Elena , Rubio-Zaragoza Mónica , Cuervo-Serrato Belén , Hernández-Guerra Ángel María , Miguel-Pastor Laura , Del Romero-Martínez Ayla , Sopena-Juncosa Joaquín , Torres-Torrillas Marta , Santana Angelo , Cugat-Bertomeu Ramón , Vilar-Guereño José Manuel , Carrillo-Poveda Jose Maria
Published: December 2023

Introduction

Articular cartilage injuries are a severe problem, and the treatments for these injuries are complex. The present study investigates a treatment for full-thickness cartilage defects called Autologous Chondral Platelet Rich Plasma Matrix Implantation (PACI) in a sheep model.

Methods

Chondral defects 8 mm in diameter were surgically induced in the medial femoral condyles of both stifles in eight healthy sheep. Right stifles were treated with PACI and an intraarticular injection with a plasma rich in growth factors (PRGF) solution [treatment group (TRT)], while an intraarticular injection of Ringer’s lactate solution was administered in left stifles [Control group (CT)]. The limbs’ function was objectively assessed with a force platform to obtain the symmetry index, comparing both groups. After 9 and 18 months, the lesions were macroscopically evaluated using the International Cartilage Repair Society and Goebel scales.

Results

Regarding the symmetry index, the TRT group obtained results similar to those of healthy limbs at 9 and 18 months after treatment. Regarding the macroscopic assessment, the values obtained by the TRT group were very close to those of normal cartilage and superior to those obtained by the CT group at 9 months.

Conclusion

This new bioregenerative treatment modality can regenerate hyaline articular cartilage. High functional outcomes have been reported, together with a good quality repair tissue in sheep. Therefore, PACI treatment might be a good therapeutic option for full-thickness chondral lesions.
Effects of different rates of propofol with or without S-ketamine on ventricular function in healthy cats – a randomized study
Authors: Marangoni Sabrine , Ubiali Matheus , Ambrosini Francieli , Jahnel Larissa , Vilani Julia M. , Steagall Paulo V. , Vilani Ricardo Guilherme D’Otaviano de Castro
Published: December 2023

Propofol is used for anesthetic induction in cats and procedural sedation in countries where alfaxalone is not available. Studies have reported propofol-related effects in echocardiography variables in dogs and humans. However, there is a lack of echocardiography studies investigating propofol-related effects on cats. This study aimed to use echocardiography to investigate echocardiographic changes in three protocols using propofol: propofol-slow (2 mg/kg/min, PS); propofol-fast (8 mg/kg/min, PF); propofol-ketamine (S-ketamine 2 mg/kg bolus followed by propofol 2 mg/kg/min; PK) in healthy premedicated (gabapentin–buprenorphine–acepromazine; 200 mg/cat, 0.4, and 0.1 mg/kg, respectively), non-intubated cats. Echocardiographic measurements were obtained at three time points: baseline (before the administration of propofol), end of propofol titration (end-point, T0), and 15 min after T0 (T15). Propofol at a lower rate continued from T0 to T15. Echocardiographic and physiological variables included fractional shortening (FS%), ejection fraction (EF%), HR, BP, and others. Propofol requirements at T0 for PF, PS, and PK groups were 5.0 ± 0.9, 3.8 ± 0.7, and 2.4 ± 0.5 mg/kg, respectively. EF% neither change over time nor between groups. PF and PK showed a reduction in FS% at T0 (47 ± 6 to 34 ± 6 and 42 ± 6 to 36 ± 5, respectively). BP reduced significantly in PF and PS groups (136 ± 26 to 105 ± 13 and 137 ± 22 to 115 ± 15 mmHg, respectively). It is unclear whether changes in echocardiography variables were of clinical relevance related to treatment groups or a result of within-group individual responses.
Influence of Test Room Acoustics on Non-Native Listeners’ Standardized Test Performance
Authors: Kawata Makito , Tsuruta-Hamamura Mariko , Hasegawa Hiroshi
Published: December 2023

Understanding the impact of room acoustics on non-native listeners is crucial, particularly in standardized English as a foreign language (EFL) proficiency testing environments. This study aims to elucidate how acoustics influence test scores, considering variables overlooked in prior research such as seat position and baseline language proficiency. In this experiment, 42 Japanese university students’ performance on standardized EFL listening tests was assessed in two rooms with distinct acoustic qualities, as determined by the speech transmission index (STI) and reverberation time (RT). The rooms differed significantly in their STI values and RT measurements, with one exhibiting high speech intelligibility qualities of ≥0.66 STI and RT0.5–2kHz < 0.7 s and the other falling below these benchmarks. The findings revealed that listening test scores were consistently higher in the acoustically favorable room across all participants. Notably, the negative effect of poor acoustics was more pronounced for students with lower baseline language proficiency. No significant score differences were observed between front- and rear-seat positions, suggesting that overall room acoustics may be more influential than individual seating locations. The study concludes that acoustics play a significant role in the standardized EFL test performance, particularly for lower-proficiency learners. This highlights the necessity of standardized testing environments to be more carefully selected in order to ensure the fair and reliable assessment of language proficiency.
A Novel Hierarchical Recursive Nonsingular Terminal Sliding Mode Control for Inverted Pendulum
Authors: Le Hiep Dai , Nestorović Tamara
Published: December 2023

This paper aims to develop a novel hierarchical recursive nonsingular terminal sliding mode controller (HRNTSMC), which is designed to stabilize the inverted pendulum (IP). In contrast to existing hierarchical sliding mode controllers (HSMC), the HRNTSMC significantly reduces the chattering problem in control input and improves the convergence speed of errors. In the HRNTSMC design, the IP system is first decoupled into pendulum and cart subsystems. Subsequently, a recursive nonsingular terminal sliding mode controller (RNTSMC) surface is devised for each subsystem to enhance the error convergence rate and attenuate chattering effects. Following this design, the HRNTSMC surface is constructed by the linear combination of the RNTSMC surfaces. Ultimately, the control law of the HRNTSMC is synthesized using the Lyapunov theorem to ensure that the system states converge to zero within a finite time. By invoking disturbances estimation, a linear extended state observer (LESO) is developed for the IP system. To validate the effectiveness, simulation results, including comparison with a conventional hierarchical sliding mode control (CHSMC) and a hierarchical nonsingular terminal sliding mode control (HNTSMC) are presented. These results clearly showcase the excellent performance of this approach, which is characterized by its strong robustness, fast convergence, high tracking accuracy, and reduced chattering in control input.
Enhancing Vibration Control in Cable–Tip–Mass Systems Using Asymmetric Peak Detector Boundary Control
Authors: Acho Leonardo , Pujol-Vázquez Gisela
Published: December 2023

In this study, a boundary controller based on a peak detector system has been designed to reduce vibrations in the cable–tip–mass system. The control procedure is built upon a recent modification of the controller, incorporating a non-symmetric peak detector mechanism to enhance the robustness of the control design. The crucial element lies in the identification of peaks within the boundary input signal, which are then utilized to formulate the control law. Its mathematical representation relies on just two tunable parameters. Numerical experiments have been conducted to assess the performance of this novel approach, demonstrating superior efficacy compared to the boundary damper control, which has been included for comparative purposes.
Prediction of Potato (Solanum tuberosum L.) Yield Based on Machine Learning Methods
Authors: Kurek Jarosław , Niedbała Gniewko , Wojciechowski Tomasz , Świderski Bartosz , Antoniuk Izabella , Piekutowska Magdalena , Kruk Michał , Bobran Krzysztof
Published: December 2023

This research delves into the application of machine learning methods for predicting the yield of potato varieties used for French fries in Poland. By integrating a comprehensive dataset comprising agronomical, climatic, soil, and satellite-based vegetation data from 36 commercial potato fields over five growing seasons (2018–2022), we developed three distinct models: non-satellite, satellite, and hybrid. The non-satellite model, relying on 85 features, excludes vegetation indices, whereas the satellite model includes these indices within its 128 features. The hybrid model, combining all available features, encompasses a total of 165 features, presenting the most-comprehensive approach. Our findings revealed that the hybrid model, particularly when enhanced with SVM outlier detection, exhibited superior performance with the lowest Mean Absolute Percentage Error (MAPE) of 5.85%, underscoring the effectiveness of integrating diverse data sources into agricultural yield prediction. In contrast, the non-satellite and satellite models displayed higher MAPE values, indicating less accuracy compared to the hybrid model. Advanced data-processing techniques such as PCA and outlier detection methods (LOF and One-Class SVM) played a pivotal role in model performance, optimising feature selection and dataset refinement. The study concluded that machine learning methods, particularly when leveraging a multifaceted approach involving a wide array of data sources and advanced processing techniques, can significantly enhance the accuracy of agricultural yield predictions. These insights pave the way for more-efficient and -informed agricultural practices, emphasising the potential of machine learning in revolutionising yield prediction and crop management.
A Transfer Learning-Based Deep Convolutional Neural Network for Detection of Fusarium Wilt in Banana Crops
Authors: Yan Kevin , Shisher Md Kamran Chowdhury , Sun Yin
Published: December 2023

During the 1950s, the Gros Michel species of bananas were nearly wiped out by the incurable Fusarium Wilt, also known as Panama Disease. Originating in Southeast Asia, Fusarium Wilt is a banana pandemic that has been threatening the multi-billion-dollar banana industry worldwide. The disease is caused by a fungus that spreads rapidly throughout the soil and into the roots of banana plants. Currently, the only way to stop the spread of this disease is for farmers to manually inspect and remove infected plants as quickly as possible, which is a time-consuming process. The main purpose of this study is to build a deep Convolutional Neural Network (CNN) using a transfer learning approach to rapidly identify Fusarium wilt infections on banana crop leaves. We chose to use the ResNet50 architecture as the base CNN model for our transfer learning approach owing to its remarkable performance in image classification, which was demonstrated through its victory in the ImageNet competition. After its initial training and fine-tuning on a data set consisting of 600 healthy and diseased images, the CNN model achieved near-perfect accuracy of 0.99 along with a loss of 0.46 and was fine-tuned to adapt the ResNet base model. ResNet50’s distinctive residual block structure could be the reason behind these results. To evaluate this CNN model, 500 test images, consisting of 250 diseased and healthy banana leaf images, were classified by the model. The deep CNN model was able to achieve an accuracy of 0.98 and an F-1 score of 0.98 by correctly identifying the class of 492 of the 500 images. These results show that this DCNN model outperforms existing models such as Sangeetha et al., 2023’s deep CNN model by at least 0.07 in accuracy and is a viable option for identifying Fusarium Wilt in banana crops.
Optimizing Initial Nitrogen Application Rates to Improve Peanut (Arachis hypogaea L.) Biological Nitrogen Fixation
Authors: Liu Ying , Yan Zhenhui , Wang Jianguo , Zhao Jihao , Liu Yiyang , Zou Jie , Li Lin , Zhang Jialei , Wan Shubo
Published: December 2023

The application of nitrogen fertilizer is crucial to the growth and biological nitrogen fixation of peanut, especially in the seedling stage where nodules have not yet formed. However, it is still uncertain how much initial nitrogen fertilizer should be applied to promote peanut root growth, nodule formation, and biological nitrogen fixation (BNF). There, a 2-year pot experiment was conducted using Huayu 22 (HY22, large-grain cultivar) and Huayu 39 (HY39, small-grain cultivar) as experimental materials to research the effects of different initial nitrogen fertilizer application rates on peanut root growth (root weight, root length, root mean diameter, root activity) and biological nitrogen fixation capacity (nodule number, nodule weight, biological nitrogen fixation, and nitrogen fixation potential per plant). N0, as control, four initial nitrogen fertilizer application rates were established: 15 kg·hm−2 (N15), 30 kg·hm−2 (N30), 45 kg·hm−2 (N45), and 60 kg·hm−2 (N60). The present results showed that the nodule number, nodule dry weight, nitrogenase activity, and biological nitrogen fixation of the HY22 cultivar under the N15 treatment were higher compared to those under other treatments over the two growing seasons. In addition, the cultivar of HY39 treated with the N15 treatment also increased the nitrogen fixation potential per plant and BNF relative to other treatments. Although the application of 60 kg·hm−2 nitrogen increased the root surface area and root volume, it decreased the nitrogenase activity, nodule dry weight, and nitrogen fixation potential per plant of HY22 and HY39 varieties in both growing seasons. Above all, an initial nitrogen application of 15 kg·hm−2 may be the optimal treatment for promoting peanut nodule formation and biological nitrogen fixation.
Effects of Water and Nitrogen Regulation on Cotton Growth and Hydraulic Lift under Dry Topsoil Conditions
Authors: Wang Zhiyu , Zhang Kun , Shao Guangcheng , Lu Jia , Gao Yang
Published: December 2023

Dry topsoil and relatively moist subsoil can occur in specific areas and times, limiting plant growth but creating conditions for hydraulic lift (HL). There is a lack of a rational water and nitrogen (N) strategy to improve cotton growth and maintain HL. This study investigated the effects of three topsoil water conditions (W0.6: 60–70%, W0.5: 50–60%, and W0.4: 40–50% of field capacity) and three N rates (N120-120, N240-240, and N360-360 kg N ha−1) plus one control treatment on cotton growth and HL under dry topsoil conditions in 2020 and 2021. The results showed that plant height and leaf area increased with increasing N rate, but the differences among topsoil water conditions were relatively small, except for leaf area in 2021. The HL water amount of all treatments increased gradually and then continued to decline during the observation period. There was a trend that the drier the topsoil or the more N applied, the greater the amount of HL water. Additionally, topsoil water conditions and N rate significantly affected the total HL water amount and root morphological characteristics (root length, surface area, and volume). Seed and lint cotton yield tended to decrease with increasing topsoil dryness at N240 or N360, except for lint yield in 2021, or with decreasing N rate, especially under W0.6. As topsoil became drier, the total evapotranspiration (ET) decreased, while with the increase in N rate, ET showed small differences. Water use efficiency increased with a higher N rate, while N partial factor productivity (PFPN) did the opposite. Furthermore, the PFPN under W0.4 was significantly lower than that under W0.6 at N240 or N120. These findings could be useful for promoting the utilization of deep water and achieving sustainable agricultural development.
An Insight into the Prevention and Control Methods for Bacterial Wilt Disease in Tomato Plants
Authors: Wu Sixuan , Su Hao , Gao Fuyun , Yao Huaiying , Fan Xuelian , Zhao Xiaolei , Li Yaying
Published: December 2023

Continuous cropping is the primary cultivation method in Chinese facility agriculture, and the challenge of it stands as a global issue in soil remediation. Growing tomatoes continuously on the same plot for an extended period can result in outbreaks of tomato bacterial wilt. It is caused by the soil-borne bacterium Ralstonia solanacearum, a widespread plant pathogen that inflicts considerable damage on economically significant crops worldwide. Simultaneously, this plant pathogen proves extremely resilient, as it can adhere to plant residues and persist through the winter, continuing to infect plants in subsequent years. Scientists have dedicated considerable efforts towards finding effective methods to manage this disease. This article delineates the characteristics of tomato bacterial wilt and the various types of pathogenic bacteria involved. It systematically reviews the progress in research aimed at controlling tomato bacterial wilt, encompassing both physical and biological aspects concerning soil and plants. Emphasis is placed on the principles and current applications of these control measures, alongside proposed improvements to address their limitations. It is anticipated that the future of tomato bacterial wilt control will revolve around the development of a novel environmental protection system and efficient control strategies, focusing on microecological management and enhancing tomato resistance against bacterial wilt through breeding.
Prediction of Oxygen Distribution in Silos and Chambers Filled with Various Agricultural Commodities
Authors: Kaloudis Efstathios , Agrafioti Paraskevi , Athanassiou Christos
Published: December 2023

In the context of post-harvest pest management in agricultural products, the adoption of modified atmospheres presents an eco-friendly alternative to conventional pesticides. This study focuses on nitrogen gas as a potential agent for insect control in stored commodities, utilizing computational simulations (by employing the convection–diffusion equation) to investigate its penetration and distribution within two common storage configurations: chamber-contained pallets and silos. The results highlight the influence of boundary conditions, commodity porosity, and convection effects on nitrogen dispersion. In chamber scenarios, the first boundary condition considers that pallets are placed inside a chamber with uniform (99.5%) nitrogen concentration, whereas in the second one, the concentration gradually increases from 78% to 99.5%. The average duration required for O2 concentration to reach 1% is approximately 10.7 h and 133.3 h for the two boundary conditions, respectively. Among the agricultural commodities, walnuts (kernels) exhibit the shortest duration, while prunes require the longest time. In silos, convection and diffusion interact to establish a consistent diffusion layer thickness. Most agricultural products exhibit similar behavior, with average times of 13.5 h, 25.4 h, and 37.0 h for three heights (10 m, 20 m, and at the silo’s top at 30 m), respectively.