bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a revised version of the transdiagnostic skills scale (T2S-R)
Authors: Vancappel Alexis , Gillet Nicolas , Fouquereau Evelyne , Chevalier Séverine , Aubouin-Bonnaventure Julia , Coillot Hélène , Mangolini Anna , Jansen Eline , Dicosimo Cinzia , El-Hage Wissam
Published: February 2024

Introduction

The transdiagnostic approach has been shown to offer promising prospects in psychopathology, based on the observation that common factors may be involved in different psychiatric disorders. The transdiagnostic skills scale (T2S) was developed recently to assess the skills that are disrupted in these disorders. However, studies have shown that the T2S has lower predictive power for externalizing than internalizing disorders. This may be due to the fact that the skills assessed do not include the control of urges and cravings. The aims of the current study are thus to develop a revised version of the T2S (T2S-R) integrating this dimension, and to assess its factor structure and invariance across employment status (workers vs. students) and the level of psychopathology.

Method

We recruited 1,298 French participants online through social media. They completed the revised version of the T2S and the symptomatic transdiagnostic test (S2T), which evaluates 11 clusters of psychiatric symptoms. We assessed the factor structure, internal consistency, invariance, and predictive validity of the revised T2S.

Results

We found a good fit for a bifactor exploratory structural equation modeling (B-ESEM) approach including a global skills factor and seven specific factors. The results also indicate that the new dimension (i.e., control of urges and cravings) has good predictive value, especially for externalizing problems. We also found total invariance of the scale across employment status and partial invariance across the level of psychopathology.

Conclusion

The revised version of the T2S-R has good psychometric properties. It predicts better externalizing problems than the original version. However, the scale remains more correlated with internalizing than externalizing problems. We discuss the implications of the results on the transdiagnostic conceptualization and the interest of using a mixed approach combining transdiagnostic and diagnostic analyses.
Anxiety disorders among children and adolescents during COVID-19 lockdowns and school closures: a cross-sectional study in Kuwait
Authors: Alamiri Bibi , Alkhamis Moh A. , Naguy Ahmed , Alenezi Hend F. , Al Shekaili Muna
Published: February 2024

Introduction

Investigating the epidemiology of mental health disorders resulting from COVID-19 intervention measures, primary school closures, and social isolation in children and adolescents needs to be prioritized over adults at the post-pandemic stage. Most preliminary psychosocial studies conducted during the pandemic have demonstrated that younger age groups are the most vulnerable to such implications. Thus, this study aims to estimate the probable prevalence of specific anxiety disorders in children and quantify their relationships with relevant demographic risk factors.

Methods

We used a cross-sectional study comprising 430 children aged between 8- and 18 years old living in Kuwait during the period of school closures as well as full and partial lockdowns. The survey included questions about participants’ characteristics, children's anxiety using the Screen for Child Anxiety Related Emotional Disorders Questionnaire (SCARED) scale, and children's emotions and behaviours using the Strengths and Difficulties Questionnaire (SDQ). Univariate and multivariate logistic regression analyses were used to summarize the demographic and characteristics of the participants and their association with general, social, and generalized anxieties, as well as behavioural and emotional difficulties.

Results

We inferred that 24.83% of our participants had at least one anxiety disorder, while 20.19% were classified as abnormal on the SDQ scale. Our multivariate analysis revealed that lockdown duration and sex of the child were consistently significant predictors (p-values < 0.05) of the broad spectrum of selected mental disorders. Additionally, we inferred notable increases in the likelihood of mental disorders associated with the increased duration of lockdowns.

Conclusions

Our findings revealed preliminary insights into the vulnerability of young populations to the indirect negative impacts of strict public health measures during pandemic emergencies. Thus, authorities should consider such implications when planning and implementing similar interventions in future pandemics.
A day in the life: psychological impact on emergency responders during the 22 March 2016 terrorist attacks
Authors: Muysewinkel Emilie , Vesentini Lara , Van Deynse Helena , Vanclooster Stephanie , Bilsen Johan , Van Overmeire Roel
Published: February 2024

Introduction

Terrorist attacks can cause severe long-term mental health issues that need treatment. However, in the case of emergency responders, research is often vague on the type of stressors that emergency responders encounter. For example, in addition to the threat that they work under, studies have shown that ill-preparation adds to the stress experienced by emergency responders. However, few studies have looked into the experience of emergency responders. In this study, we looked at the experience of emergency responders during the 22 March 2016 terrorist attacks in Belgium.

Methods

We used a qualitative design, in which we interviewed different types of emergency responders. Police officers, nurses, soldiers, firefighters, and Red Cross volunteers were included. Interviews were coded by two researchers and analyzed using a thematic approach.

Results

Four large themes were developed: constant threat and chaos, frustrations with lack of preparedness and training, ethical decisions, and debriefings. In addition, although emergency responders encountered constant threat, they often felt that they were ill-prepared for such attacks. One specific example was their lack of training in tourniquet usage. Furthermore, in a disaster setting, the emergency responders had to make life-and-death decisions for which they were not always prepared. Finally, debriefings were conducted in the aftermath of the attacks. Whereas most were perceived as positive, the debriefings among police officers were viewed as insufficient.

Conclusions

Emergency responding to terrorist attacks has many different dimensions of events that can cause stress. Our study revealed that preparation is key, not only in terms of material but also in terms of ethics and debriefings.
Advanced theoretical-applied model based on the PD approach in the light of healthcare-associated infections: what have we achieved so far?
Authors: Cohen Ricky , Gesser-Edelsburg Anat
Published: February 2024

Healthcare-associated infections remain a persistent concern despite decades of research and intervention efforts. Adherence to infection prevention and control guidelines by health professionals remains a challenge, necessitating innovative strategies. The Positive Deviance (PD) approach, rooted in harnessing localized solutions, holds promise but lacks comprehensive frameworks and empirical validation to bolster its theoretical underpinnings. This perspective article serves a dual purpose: first, to examine the unique challenges of applying the PD approach in the context of HAIs; and second, to introduce a robust theoretical-applied model developed in response to these challenges. This article addresses these gaps through a multi-faceted model developed in a mixed-methods study across three Israeli governmental hospitals and comprises four essential components that address the identified gaps in existing research. This article enriches the dialog on PD’s applicability in HAIs by providing a robust model that not only offers solutions but reshapes the approach to healthcare hygiene and safety. It responds to critical gaps highlighted in the literature, offering tailored interventions by practical, context-specific solutions to improve adherence to IPC guidelines in the long term. Methodological clarity is also a key focus, offering a toolkit for practical implementation. This bottom-up approach empowers HPs to drive change, fostering a culture of innovation and improvement in healthcare settings.
Effects of physical activity and sedentary behaviors on cardiovascular disease and the risk of all-cause mortality in overweight or obese middle-aged and older adults
Authors: Zhang Yongqiang , Liu Xia
Published: February 2024

Aim

The aim of this study was to respectively explore the relationships between physical activity and sedentary behaviors and cardiovascular disease (CVD) and all-cause mortality risk in overweight/obese middle-aged and older patients, and also assess the interaction between physical activity and sedentary behaviors.

Methods

Data of middle-aged and older adults with body mass index (BMI) ≥25 kg/m2 were extracted from the National Health and Nutrition Examination Surveys (NHANES) database in 2007–2018 in this retrospective cohort study. Weighted univariate and multivariate logistic regression analyses were used to explore the associations between physical activity and sedentary behaviors and CVDs; weighted univariate and multivariate Cox regression analyses were used to explore the relationships between physical activity and sedentary behaviors with the risk of all-cause mortality. The interaction effect between physical activity and sedentary behaviors on CVD and all-cause mortality was also assessed. We further explored this interaction effect in subgroups of age and BMI. The evaluation indexes were odds ratios (ORs), hazard ratios (HRs), and 95% confidence intervals (CIs).

Results

Among 13,699 eligible patients, 1,947 had CVD, and 1,560 died from all-cause mortality. After adjusting for covariates, patients who had high sedentary time seemed to have both high odds of CVD [OR = 1.24, 95% CI: (1.06–1.44)] and a high risk of all-cause mortality [HR = 1.20, 95% CI: (1.06–1.37)]. Furthermore, being insufficiently active was linked to high odds of CVD [OR = 1.24, 95% CI: (1.05–1.46)] as well as a high risk of all-cause mortality [HR = 1.32, 95% CI: (1.15–1.51)]. High sedentary time and being insufficiently active had an interaction effect on both high odds of CVD [OR = 1.44, 95% CI: (1.20–1.73)] and high risk of all-cause mortality [HR = 1.48, 95% CI: (1.24–1.76)]. Individuals of different ages with/without obesity need to focus on the potential CVD/mortality risk of high sedentary time and low physical activity (all P < 0.05).

Conclusion

Reducing sedentary time combined with increasing physical activity may benefit health by reducing both the risk of CVD and all-cause mortality in overweight or obese middle-aged and older adults.
Sense of coherence promotion and occupational and family stress mitigation may improve heart health behaviors in middle-aged working women: a structural equation modelling approach
Authors: Moon Ji Hyun , Seo Eunhye
Published: February 2024

Aims

This study aimed to construct a model that describes heart health behaviors in middle-aged working women and verify the goodness-of-fit of the model based on Salutogenesis.

Methods and results

This study adopted a cross-sectional design. Participants were 330 middle-aged working women in South Korea. Data were analyzed using structural equation modelling with Sobel’s Z test. In the multiple mediation model, stress coping strategy (β = 0.26; p < 0.001), social support (β = 0.41; p < 0.001), and health self-efficacy (β = 0.36; p < 0.001) had significant direct effects on sense of coherence (SOC). SOC had a significant direct effect on occupational (β = −0.72; p < 0.001) and family stress (β = −0.76; p < 0.001). Additionally, SOC (β = 0.67; p < 0.001), occupational stress (β = −0.46; p < 0.001), and family stress (β = −0.28; p < 0.001) had significant direct effects on heart health behaviors. Moreover, SOC had a significantly partial mediating effect on heart health behaviors through occupational stress (Z = 3.17; p = 0.002) and family stress (Z = 2.26; p = 0.024).

Conclusion

Occupational and family stress mediated the relationship between SOC and heart health behaviors in middle-aged working women.

Clinical evidence

Interventions that mitigate occupational and family stress may improve heart health behaviors among middle-aged working women.
Research on the risk governance of fraudulent reimbursement of patient consultation fees
Authors: Sun Jiangjie , Wang Yue , Zhang Yuqing , Li Limin , Li Hui , Liu Tong , Zhang Liping
Published: February 2024

Background

The fundamental medical insurance fund, often referred to as the public’s “life-saving fund,” plays a crucial role in both individual well-being and the pursuit of social justice. Medicare fraudulent claims reduce “life-saving money” to “Tang’s monk meat”, undermining social justice and affecting social stability.

Methods

We utilized crawler technology to gather textual data from 215 cases involving fraudulent health insurance claims. Simultaneously, statistical data spanning 2018 to 2021 was collected from the official websites of the China Medical Insurance Bureau and Anhui Medical Insurance Bureau. The collected data underwent comprehensive analysis through Excel, SPSS 26.0 and R4.2.1. Differential Auto-Regressive Moving Average Model (ARIMA (p, d, q)) was used to fit the fund safety forecast model, and test the predictive validity of the forecast model on the fund security data from July 2021 to October 2023 (the fund security data of Anhui Province from September 2021 to October 2023).

Results

The outcomes revealed that fraudulent claims by health insurance stakeholders adversely impact the equity of health insurance funds. Furthermore, the risk management practices of Medicare fund administrators influence the publication of fraudulent claims cases. Notably, differences among Medicare stakeholders were observed in the prevalence of fraudulent claims. Additionally, effective governance of fraudulent claims risks was found to have a positive impact on the overall health of healthcare funds. Moreover, the predictive validity of the forecast model on the national and Anhui province’s fund security data was 92.86% and 100% respectively.

Conclusion

We propose four recommendations for the governance of health insurance fraudulent claims risk behaviors. These recommendations include strategies such as “combatting health insurance fraudulent claims to preserve the fairness of health insurance funds”, “introducing initiatives for fraud risk governance and strengthening awareness of the rule of law”, “focusing on designated medical institutions and establishing a robust long-term regulatory system”, and “adapting to contemporary needs while maintaining a focus on long-term regulation”.
Mapping the scarcity of data on antibiotics in natural and engineered water environments across India
Authors: Rathinavelu Sasikaladevi , Uluseker Cansu , Sonkar Vikas , Thatikonda Shashidhar , Nambi Indumathi M. , Kreft Jan-Ulrich
Published: February 2024

Antimicrobial resistance is a growing public health concern, increasingly recognized as a silent pandemic across the globe. Therefore, it is important to monitor all factors that could contribute to the emergence, maintenance and spread of antimicrobial resistance. Environmental antibiotic pollution is thought to be one of the contributing factors. India is one of the world’s largest consumers and producers of antibiotics. Hence, antibiotics have been detected in different environments across India, sometimes at very high concentrations due to their extensive use in humans and agriculture or due to manufacturing. We summarize the current state of knowledge on the occurrence and transport pathways of antibiotics in Indian water environments, including sewage or wastewater and treatment plants, surface waters such as rivers, lakes, and reservoirs as well as groundwater and drinking water. The factors influencing the distribution of antibiotics in the water environment, such as rainfall, population density and variations in sewage treatment are discussed, followed by existing regulations and policies aimed at the mitigation of environmental antimicrobial resistance in India, which will have global benefits. Then, we recommend directions for future research, development of standardized methods for monitoring antibiotics in water, ecological risk assessment, and exploration of strategies to prevent antibiotics from entering the environment. Finally, we provide an evaluation of how scarce the data is, and how a systematic understanding of the occurrence and concentrations of antibiotics in the water environment in India could be achieved. Overall, we highlight the urgent need for sustainable solutions to monitor and mitigate the impact of antibiotics on environmental, animal, and public health.
Alzheimer's disease detection using data fusion with a deep supervised encoder
Authors: Trinh Minh , Shahbaba Ryan , Stark Craig , Ren Yueqi
Published: February 2024

Alzheimer's disease (AD) is affecting a growing number of individuals. As a result, there is a pressing need for accurate and early diagnosis methods. This study aims to achieve this goal by developing an optimal data analysis strategy to enhance computational diagnosis. Although various modalities of AD diagnostic data are collected, past research on computational methods of AD diagnosis has mainly focused on using single-modal inputs. We hypothesize that integrating, or “fusing,” various data modalities as inputs to prediction models could enhance diagnostic accuracy by offering a more comprehensive view of an individual's health profile. However, a potential challenge arises as this fusion of multiple modalities may result in significantly higher dimensional data. We hypothesize that employing suitable dimensionality reduction methods across heterogeneous modalities would not only help diagnosis models extract latent information but also enhance accuracy. Therefore, it is imperative to identify optimal strategies for both data fusion and dimensionality reduction. In this paper, we have conducted a comprehensive comparison of over 80 statistical machine learning methods, considering various classifiers, dimensionality reduction techniques, and data fusion strategies to assess our hypotheses. Specifically, we have explored three primary strategies: (1) Simple data fusion, which involves straightforward concatenation (fusion) of datasets before inputting them into a classifier; (2) Early data fusion, in which datasets are concatenated first, and then a dimensionality reduction technique is applied before feeding the resulting data into a classifier; and (3) Intermediate data fusion, in which dimensionality reduction methods are applied individually to each dataset before concatenating them to construct a classifier. For dimensionality reduction, we have explored several commonly-used techniques such as principal component analysis (PCA), autoencoder (AE), and LASSO. Additionally, we have implemented a new dimensionality-reduction method called the supervised encoder (SE), which involves slight modifications to standard deep neural networks. Our results show that SE substantially improves prediction accuracy compared to PCA, AE, and LASSO, especially in combination with intermediate fusion for multiclass diagnosis prediction.
Translocation of tropical peat surface to deeper soil horizons under compaction controls carbon emissions in the absence of groundwater
Authors: Samuel Marshall Kana , Evers Stephanie
Published: February 2024

Compaction is recognized as an effective method for mitigating the risk of fires by enhancing soil moisture levels. This technique involves restricting peat pore spaces through compaction, facilitating improved capillary action for water retention and rehydration. The compaction of tropical peatlands, while beneficial for fire prevention, has the potential to influence biogeochemical processes and subsequent carbon emissions. The magnitude of compaction and groundwater level are strongly coupled in such environments, making it difficult to distinguish the control of physicochemical properties. Therefore, this study seeks to understand how peat compaction affects its properties, carbon emissions, and their relationship, with a focus on geophysical processes. Intact peat samples were collected from a secondary peat swamp forest and an oil palm plantation in Selangor, Peninsular Malaysia. Compaction treatments were applied to achieve three levels of volume reduction. CO2 and CH4 emissions were measured using an automated gas analyzer, and the physicochemical properties of the peat were determined. The results revealed that mechanical compaction significantly altered the physicochemical properties of the secondary forest peat, displaying an opposite pattern to the oil palm plantation, particularly regarding total nitrogen and sulfur. Moreover, the average reduction percentage ratio of CO2 emissions (from 275.4 to 182.0 mg m-2 hr-1; 33.9%) to CH4 uptakes (from -17.8 to -5.2 µg m-2 hr-1; 70.1%) (~1:2) indicated distinct stages of decomposition and translocation of less decomposed peat to deeper layers due to compaction, predominantly in secondary peat swamp forest samples. The oil palm plantation samples were unaffected by compaction in terms of physicochemical properties and carbon emissions, indicating the ineffectiveness of this approach for reducing fire risk in already drained systems. This study underscores the necessity of understanding the effects of compaction in the absence of groundwater to accurately evaluate the widespread application of this technique.
An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality
Authors: Montagne Gilles , Mascret Nicolas , Bossard Martin , Chomienne Loïc , Ledouit Simon , Rao Guillaume , Tordi Nicolas , Verhulst Eulalie , Kulpa Richard
Published: February 2024

The ambition of our contribution is to show how an interdisciplinary framework can pave the way for the deployment of innovative virtual reality training sessions to improve anticipation skills in top-level athletes. This improvement is so challenging that some authors say it is like “training for the impossible”. This framework, currently being implemented as part of a project to prepare athletes for the 2024 Olympic Games in Paris, based on the ecological-dynamics approach to expertise, is innovative in its interdisciplinary nature, but also and above all because it overcomes the limitations of more traditional training methods in the field designed to optimize anticipation skills in top-level athletes. The ambition is to tackle successive challenges ranging from the design of virtual partners and opponents to the deployment of training programs in virtual reality, while ensuring the acceptability and acceptance of such innovative virtual reality training protocols and measuring associated workloads.
Case report: Treatment of cyclobenzaprine ingestion in two dogs with intravenous intralipid therapy
Authors: Dreese Kaitlyn , Odunayo Adesola , Bucknoff Melissa C.
Published: February 2024

Introduction

The objective of this case series is to describe the clinical signs and outcome of cyclobenzaprine ingestion in two dogs treated with intralipid emulsion (ILE) and supportive care.

Case or series summary

Two dogs presented for evaluation of cyclobenzaprine ingestion. A 4-year-old female spayed Rat Terrier (dog 1) presented within 4 h of ingestion of cyclobenzaprine (between 9.7 and 25.9 mg/kg). The dog experienced abnormal behavior, agitation, tremors, tachycardia, and hypertension. There were no significant clinicopathological abnormalities. The dog was treated with ILE, cyproheptadine, and activated charcoal. All clinical signs resolved after treatment. A 5-month-old female intact mixed-breed dog (dog 2) presented after ingestion of an unknown amount of cyclobenzaprine 2–3 h prior to presentation. The dog experienced dull mentation, tremors, loss of gag reflex, tachycardia, and hypertension. There were no significant clinicopathological abnormalities. Orogastric decontamination was performed via gastric lavage, and activated charcoal was given via orogastric tube, followed by ILE. All clinical signs resolved after therapeutic intervention.

Discussion

This is the first report documenting clinical signs of cyclobenzaprine toxicity in two dogs followed by successful treatment with gastric emptying, ILE, and supportive care.
Topology Optimization of Shape Memory Alloy Actuators for Prescribed Two-Way Transforming Shapes
Authors: Yang Kaike , Luo Junpeng , Yuan Zhaoting , Ma Wenjing , Hou Jie , Gu Xiaojun , Wang Deen , Yuan Qiang
Published: February 2024

This paper proposes a new topology optimization formulation for obtaining shape memory alloy actuators which are designed with prescribed two-way transforming shapes. The actuation behaviors of shape memory alloy structures are governed by austenite-martensite phase transformations effected by thermal-mechanical loading processes; therefore, to realize the precise geometric shape variations of shape memory alloy actuators, traditional methods involve iteration processes including heuristic structural design, numerical predictions and experimental validation. Although advanced structural optimization methods such as topology optimization have been used to design three-dimensional (3D) shape memory alloy actuators, the maximization/minimization of quantities such as structural compliance or inaccurate stroke distances has usually been selected as the optimization objective to obtain feasible solutions. To bridge the gap between precise shape-morphing requirements and efficient shape memory alloy actuator designs, this paper formulates optimization criteria with quantitatively desired geometric shapes, and investigates the automatic designs of two-way prescribed shape morphing shape memory alloy structures based on the proposed topology optimization method. The super element method and adjoint method are used to derive the analytical sensitivities of the objective functions with respect to the design variables. Numerical examples demonstrate that the proposed method can obtain 3D actuator designs that have the desired two-way transforming shapes.
Distributed Fixed-Time Formation Tracking Control for the Multi-Agent System and an Application in Wheeled Mobile Robots
Authors: Ma Ling , Gao Yufeng , Li Bo
Published: February 2024

This work addresses the issue of multi-agent system (MAS) formation control under external disturbances and a directed communication topology. Firstly, a new disturbance observer is proposed to effectively reconstruct and compensate for external disturbances within a short period of time. Then, the integral terminal sliding mode technology is introduced to devise a novel distributed formation control protocol, ultimately realizing the stability of the MAS within a fixed time. Moreover, by means of rigorous Lyapunov theory analyses, a faster formation convergence rate and more accurate consensus accuracies are achieved in the proposed fixed-time strategy with variable exponent form. Finally, the formation tracking control scheme is applied to a multi-wheeled mobile robot (WMR) system. The experimental results strongly support the fine effectiveness of the control scheme designed in this work.
Mitigation of Shock-Induced Separation Using Square-Shaped Micro-Serrations—A Preliminary Study
Authors: Yu Fangyou , Gao Zhanbiao , Zhang Qifan , Yue Lianjie , Chen Hao
Published: February 2024

Suppressing shock-induced flow separation has been a long-standing problem in the design of supersonic vehicles. To reduce the structural and design complexity of control devices, a passive control technique based on micro-serrations is proposed and its controlling effects are preliminarily investigated under test conditions in which the Mach number is 2.5 and the ramp creating an incident shock is 15 deg. Meanwhile, a vorticity-based criterion for assessing separation scales is developed to resolve the inapplicability of the zero skin friction criterion caused by wall unevenness. The simulations demonstrate that the height of the first stair significantly influences the separation length. Generally, the separation length is shorter at higher stairs, but when the height is greater than half of the thickness of the incoming boundary layer, the corresponding separation point moves upstream. A stair with a height of only 0.4 times the thickness of the boundary layer reduces the separation length by 2.69%. Further parametric analysis reveals that while the remaining serrations have limited effects on the flow separation, an optimization of their shape (depth and width) can create more favorable spanwise vortices and offer a modest improvement of the overall controlling performance. Compared to the plate case, a 9.13% reduction in the separation length can be achieved using a slightly serrated design in which the leading stair is 0.1 high and the subsequent serrations are 0.2 deep and 0.05 wide (nondimensionalized, with the thickness of the incoming boundary layer). Meanwhile, the micro-serration structure even brings less drag. Considering the minor modification to the structure, the proposed method has the potential for use in conjunction with other techniques to exert enhanced control on separations.
Effects of Burial Furrow Parameters on Soil Water Movement under Subsurface Stalk Composite Pipe Irrigation
Authors: Wu Feng , Feng Xuefang , Liu Xuemei , Wu Di , Zai Songmei , Liu Linbao
Published: February 2024

Stalk composite pipe (SCP), a novel product used for subsurface irrigation, is primarily composed of crop stalks, soil, and water. In subsurface SCP irrigation (SSI), comprehending the effects of burial furrow parameters on soil water movement is critical. However, the precise effects are not known. Here, we aimed to assess the effects of varying burial furrow dimensions, including widths of 15, 20, and 25 cm, depths of 10, 15, and 20 cm, and backfilling-soil bulk densities of 1.1, 1.2, and 1.3 g cm−3, on wetted distance and soil water movement. We conducted an indoor soil bin experiment and numerical simulation using HYDRUS-2D in 2020–2021 in Zhengzhou City, Northern China. Wider burial furrows resulted in increased wetted distance and soil water content, ultimately leading to greater effect in a horizontal direction. In the horizontal profile, the average soil water content of the SSI treatments, which used burial furrow widths of 15, 20, and 25 cm, were 1.121, 1.230, and 1.280 times higher, respectively, than those of CK. The burial furrow depth had minimal effect on the wetted distance, whereas adjusting the burial furrow depth primarily affected the saturation depth. The speed of wetting-front migration was affected by the backfilling-soil bulk density. For a given soil and crop, it is advisable to determine first the burial furrow width and backfilling-soil bulk density. Subsequently, the burial furrow depth should be established based on the distribution of the crop’s roots. Our findings offer a scientific basis for using SSI.
Relationship among Soil Biophysicochemical Properties, Agricultural Practices and Climate Factors Influencing Soil Phosphatase Activity in Agricultural Land
Authors: Campdelacreu Rocabruna Patrícia , Domene Xavier , Preece Catherine , Peñuelas Josep
Published: February 2024

Phosphorus (P) is a vital macronutrient crucial for crop productivity. Plants absorb P salts, mainly orthophosphate, from the soil, yet the primary P source resides in organic materials. Acid and alkaline phosphatases (the predominant forms of soil phosphomonoesterases (APases)) are crucial for alleviating P deficiency in plants and play a vital role in releasing P from organic materials via hydrolysis. Our aim was to summarize the direction of the relationship between a variety of influential factors on acid and alkaline phosphatase activity in agricultural lands and identify gaps in knowledge. Our findings indicate a strong linkage between both APases and soil pH, positively influenced by clay content, organic matter, microbial biomass carbon, and nitrogen. Adopting healthy soil practices like balanced organic fertilizer usage, optimal soil water levels, reduced tillage, crop rotation, and using beneficial plant microbes help boost both APase activity. However, the connection between APases and crop productivity remains uncertain due to insufficient research in this area. We identified gaps in knowledge in relation to meso-macrofauna, alongside essential plant nutrients such as potassium, nutrient ratios, and the synergistic effects of various factors on APase response. Understanding the rapid, efficient assimilation of P through APases in the plant-soil and/or plant-microbiota ecosystem it can be crucial for crop productivity and yields.
The Discrete Taxonomic Classification of Soils Subjected to Diverse Treatment Modalities and Varied Fertility Grades Utilizing Machine Olfaction
Authors: Liu Shuyan , Chen Xuegeng , Huang Dongyan , Wang Jingli , Jiang Xinming , Meng Xianzhang , Gao Xiaomei
Published: February 2024

Soil classification stands as a pivotal aspect in the domain of agricultural practices and environmental research, wielding substantial influence over decisions related to real-time soil management and precision agriculture. Nevertheless, traditional methods of assessing soil conditions, primarily grounded in labor-intensive chemical analyses, confront formidable challenges marked by substantial resource demands and spatial coverage limitations. This study introduced a machine olfaction methodology crafted to emulate the capabilities of the human olfactory system, providing a cost-effective alternative. In the initial phase, volatile gases produced during soil pyrolysis were propelled into a sensor array comprising 10 distinct gas sensors to monitor changes in gas concentration. Following the transmission of response data, nine eigenvalues were derived from the response curve of each sensor. Given the disparate sample counts for the two distinct classification criteria, this computational procedure yields two distinct eigenspaces, characterized by dimensions of 112 or 114 soil samples, each multiplied by 10 sensors and nine eigenvalues. The determination of the optimal feature space was guided by the “overall feature information” derived from mutual information. Ultimately, the inclusion of random forest (RF), multi-layer perceptron (MLP), and multi-layer perceptron combined with random forest (MLP-RF) models was employed to classify soils under four treatments (tillage and straw management) and three fertility grades. The assessment of model performance involved metrics such as overall accuracy (OA) and the Kappa coefficient. The findings revealed that the optimal classification model, MLP-RF, achieved impeccable performance with an OA of 100.00% in classifying soils under both criteria, which showed almost perfect agreement with the actual results. The approach proposed in this study provided near-real-time data on the condition of the soil and opened up new possibilities for advancing precision agriculture management.
Insights into the Belowground Biodiversity and Soil Nutrient Status of an Organic Apple Orchard as Affected by Living Mulches
Authors: Furmanczyk Ewa M. , Malusà Eligio , Kozacki Dawid , Tartanus Malgorzata
Published: February 2024

The impact of living mulches established with three officinal plants (Alchemilla vulgaris, Fragaria vesca and Mentha x piperita) on the soil bacterial microbiome and activity, the nematodes population, and the nutrient status of an organic apple orchard was assessed. The composition and diversity of the bacterial communities were differentially modified by living mulches. The activity of the bacterial microbiome associated with F. vesca was higher and utilized more C sources in comparison to other treatments. The combined analysis of the core bacterial microbiome and metabolic activity pointed to a potential effect of F. vesca on different levels of the soil’s trophic network. The living mulches did not affect the overall number of nematodes, but in some cases, they modified the structure of the population: F. vesca induced the highest share of bacteria feeders and the lowest number of herbivores and fungal feeders. The living mulches modified the availability of some nutrients and the pH. Multivariate analysis of the whole dataset showed several potential inter-dependencies between the assessed parameters that are worthy of further study. In conclusion, the introduction of multifunctional living mulches based on officinal plants induced changes to the soil’s genetic and functional biodiversity and chemical properties. These modifications could deliver ecosystem services particularly relevant to organic apple orchards.
Machine Learning Offers Insights into the Impact of In Vitro Drought Stress on Strawberry Cultivars
Authors: Şimşek Özhan
Published: February 2024

This study aimed to assess the susceptibility of three strawberry cultivars (“Festival”, “Fortuna”, and “Rubygem”) to drought stress induced by varying polyethylene glycol (PEG) concentrations in the culture medium. Plantlets were cultivated on a solid medium supplemented with 1 mg/L BAP, and PEG concentrations (0, 2, 4, and 6 mg/L) were introduced to simulate drought stress. Morphological changes were observed, and morphometric analysis was conducted. Additionally, artificial neural network (ANN) analysis and machine learning approaches were integrated into this study. The results showed significant effects of PEG concentrations on plant height and multiplication coefficients, highlighting genotype-specific responses. This study employed various machine learning models, with random forest consistently demonstrating superior performance. Our findings revealed the random forest model outperformed others with a remarkable global diagnostic accuracy of 91.164%, indicating its superior capability in detecting and predicting water stress effects in strawberries. Specifically, the RF model excelled in predicting root length and the number of roots for “Festival” and “Fortuna” cultivars, demonstrating its reliability across different genetic backgrounds. Meanwhile, for the “Rubygem” cultivar, the multi-layer perceptron (MLP) and Gaussian process (GP) models showed particular strengths in predicting proliferation and plant height, respectively. These findings highlight the potential of ML models, particularly RF, to enhance agricultural breeding and cultivation strategies through accurate phenotypic predictions, suggesting a promising direction for future research to improve these predictions further. This research contributes to understanding strawberry responses to drought stress and emphasizes the potential of machine learning in predicting plant characteristics.
Prediction Model of Flavonoids Content in Ancient Tree Sun−Dried Green Tea under Abiotic Stress Based on LASSO−Cox
Authors: Li Lei , Wu Yamin , Wang Houqiao , He Junjie , Wang Qiaomei , Xu Jiayi , Xia Yuxin , Yuan Wenxia , Chen Shuyi , Tao Lin , Wang Xinghua , Wang Baijuan
Published: February 2024

To investigate the variation in flavonoids content in ancient tree sun–dried green tea under abiotic stress environmental conditions, this study determined the flavonoids content in ancient tree sun−dried green tea and analyzed its correlation with corresponding factors such as the age, height, altitude, and soil composition of the tree. This study uses two machine−learning models, Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression, to build a predictive model based on the selection of effective variables. During the process, bootstrap was used to expand the dataset for single−factor and multi−factor comparative analyses, as well as for model validation, and the goodness−of−fit was assessed using the Akaike information criterion (AIC). The results showed that pH, total potassium, nitrate nitrogen, available phosphorus, hydrolytic nitrogen, and ammonium nitrogen have a high accuracy in predicting the flavonoids content of this model and have a synergistic effect on the production of flavonoids in the ancient tree tea. In this prediction model, when the flavonoids content was >6‰, the area under the curve of the training set and validation set were 0.8121 and 0.792 and, when the flavonoids content was >9‰, the area under the curve of the training set and validation set were 0.877 and 0.889, demonstrating good consistency. Compared to modeling with all significantly correlated factors (p < 0.05), the AIC decreased by 32.534%. Simultaneously, a visualization system for predicting flavonoids content in ancient tree sun−dried green tea was developed based on a nomogram model. The model was externally validated using actual measurement data and achieved an accuracy rate of 83.33%. Therefore, this study offers a scientific theoretical foundation for explaining the forecast and interference of the quality of ancient tree sun−dried green tea under abiotic stress.
Development and Effects of Organic Farms in Poland, Taking into Account Their Location in Areas Facing Natural or Other Specific Constraints
Authors: Zieliński Marek , Wrzaszcz Wioletta , Sobierajewska Jolanta , Adamski Marcin
Published: February 2024

Organic farms should, by definition, place particular emphasis on the protection of agricultural soils, landscape care and activities aimed at producing high-quality agricultural products. However, when joining this production system, the farms face many challenges in order to make these contributions to society at the expected level. The main aim of the study is to determine the scale of disproportions in production effects achieved by farms between organic and conventional production systems, taking into account the quality of natural management conditions. An equally important goal is to determine the factors in Polish agriculture that determine whether to conduct this production system. The paper aims to indicate the direction of development of organic farming in the EU, including Poland, based on the Eurostat data for 2012–2020. It was noted that the current development of the organic farming sector in EU member states has been at different rates. In Poland, its development strength largely depends on the presence of ANCs. Nearly ¾ of organic utilized agriculture area (UAA) is located in communes with a large share of them. Organic farms achieve lower production effects in comparison to conventional farms, and their disproportions also depend on the quality of natural farming conditions. In Poland, the personal competences of farmers are also an important determinant in joining organic farming.
Habitat Diversity Increases Chrysoperla carnea s.l. (Stephens, 1836) (Neuroptera, Chrysopidae) Abundance in Olive Landscapes
Authors: Paredes Daniel , Mendes Sara , Sousa José Paulo
Published: February 2024

Chrysoperla carnea s.l., a vital predator in olive groves, plays a key role in reducing the reliance on pesticides. Despite its efficacy, habitat diversification at the landscape level can compromise its effectiveness as a generalist natural enemy, diverting its attention from olive pests to other resources. To unravel its habitat preferences and maximize biocontrol services, a comprehensive study was conducted, collecting specimens monthly across diverse habitats in a Portuguese olive grove landscape. These habitats included shrublands, “montado,” grasslands, eucalyptus and pine forests, vineyards, and olive groves. The findings revealed C. carnea s.l. displayed a widespread presence in all habitats, with peak abundance initially observed in olive groves, coinciding with the presence of its preferred prey, Prays oleae. However, the peak abundance of this species varies among habitats, with the highest numbers initially observed in olive groves, gradually decreasing throughout the summer and reaching the lowest levels in vineyards. Significantly, habitat diversification at the landscape level contributes to an increased abundance of C. carnea s.l. in olive groves. This suggests that diversifying available resources aids in sustaining natural enemy populations in proximity to the targeted crop, thereby enhancing their efficacy in pest control. Consequently, we advocate for stakeholders in olive cultivation to promote landscape-scale habitat diversity by preserving, restoring, or fostering alternative habitats surrounding olive groves.
RNN-Based Approach for Broccoli Harvest Time Forecast
Authors: Lohachov Mykhailo , Korei Ryoji , Oki Kazuo , Yoshida Koshi , Azechi Issaku , Salem Salem Ibrahim , Utsumi Nobuyuki
Published: February 2024

This article investigates approaches for broccoli harvest time prediction through the application of various machine learning models. This study’s experiment is conducted on a commercial farm in Ecuador, and it integrates in situ weather and broccoli growing cycle observations made over seven years. This research incorporates models such as the persistence, thermal, and calendar models, demonstrating their strengths and limitations in calculating the optimal broccoli harvest day. Additionally, Recurrent Neural Network (RNN) models with Long Short-term Memory (LSTM) layers were developed, showcasing enhanced accuracy with an error of less than 2.5 days on average when combined with outputs from the calendar model. In the final comparison, the RNN models outperformed both the thermal and calendar models, with an error of 3.14 and 2.5 days, respectively. Furthermore, this article explores the impact of utilizing Global Ensemble Forecast System forecast weather data as a supplementary source to the in situ observations on model accuracy. The analysis revealed the limited effect of extension with a 9-day forecast on the experimental field, reaching an error reduction of up to 0.04 days. The findings provide insights into the effectiveness of different modeling approaches for optimizing broccoli harvest times, emphasizing the potential of RNN techniques in agricultural decision making.
Growth and Nutritional Responses of Zucchini Squash to a Novel Consortium of Six Bacillus sp. Strains Used as a Biostimulant
Authors: Savvas Dimitrios , Magkana Paraskevi , Yfantopoulos Dionisios , Kalozoumis Panagiotis , Ntatsi Georgia
Published: February 2024

The use of biostimulants consisting of plant growth-promoting rhizobacteria (PGPR) has been rapidly expanding in horticulture in recent years. In the current study, a novel mix of six Bacillus sp. strains (B. subtilis, B. pumilus, B. megaterium, B. amyloliquefaciens, B. velezensis, B. licheniformis) was tested as a PGPR biostimulant in two experiments with zucchini squash (Cucurbita pepo L.). The first experiment took place in greenhouse soil in winter, while the second experiment was conducted in an open field during summer. In both experiments, seeds of the local landrace “Kompokolokytho” and the commercial hybrid “ARO-800” were either inoculated or non-inoculated with the PGPR biostimulant. The application of the six Bacillus sp. strains increased both the vegetative growth and the yield of zucchini squash, and these effects were associated with significantly higher shoot phosphorus levels in both experiments and both genotypes. Furthermore, at the end of the cultivation, the colony-forming units of Bacillus sp. were appreciably higher in plants originating from inoculated compared to non-inoculated seeds, indicating that the tested mix of Bacillus sp. can be successfully applied through seed inoculation. “ARO-800” produced more vegetative and fruit biomass than “Κompokolokytho” under greenhouse cropping conditions, while in the open field crop, both genotypes performed equally. Presumably, this response occurred because “ARO-800” did not express its full yield potential in the open field due to stress imposed by the high summer temperatures, while the local landrace, which is traditionally grown in open fields, may be more resilient to stress conditions frequently encountered in open fields.