bluuebunny/crossref_metadata_2025 huggingface dataset:
Blame framing and prior knowledge influence moral judgments for people involved in the Tulsa Race Massacre among a combined Oklahoma and UK sample
Authors: Durham Justin D. , Rosen Adon F. G. , Gronlund Scott D.
Published: February 2024

Introduction

How an event is framed impacts how people judge the morality of those involved, but prior knowledge can influence information processing about an event, which also can impact moral judgments. The current study explored how blame framing and self-reported prior knowledge of a historical act of racial violence, labeled as Riot, Massacre, or Event, impacted individual’s cumulative moral judgments regarding the groups involved in the Tulsa Race Massacre (Black Tulsans, the Tulsa Police, and White Tulsans).

Methods and results

This study was collected in two cohorts including undergraduates attending the University of Oklahoma and individuals living in the United Kingdom. Participants were randomly assigned to a blame framing condition, read a factual summary of what happened in Tulsa in 1921, and then responded to various moral judgment items about each group. Individuals without prior knowledge had higher average Likert ratings (more blame) toward Black Tulsans and lower average Likert ratings (less blame) toward White Tulsans and the Tulsa Police compared to participants with prior knowledge. This finding was largest when what participants read was framed as a Massacre rather than a Riot or Event. We also found participants with prior knowledge significantly differed in how they made moral judgments across target groups; those with prior knowledge had lower average Likert ratings (less blame) for Black Tulsans and higher average Likert ratings (more blame) for White Tulsans on items pertaining to causal responsibility, intentionality, and punishment compared to participants without prior knowledge.

Discussion

Findings suggest that the effect of blame framing on moral judgments is dependent on prior knowledge. Implications for how people interpret both historical and new events involving harmful consequences are discussed.
The oscillatory features of visual processing are altered in healthy aging
Authors: Lévesque Mélanie , Arguin Martin
Published: February 2024

The temporal features of visual processing were compared between young and elderly healthy participants in visual object and word recognition tasks using the technique of random temporal sampling. The target stimuli were additively combined with a white noise field and were exposed very briefly (200 ms). Target visibility oscillated randomly throughout exposure duration by manipulating the signal-to-noise ratio (SNR). Classification images (CIs) based on response accuracy were calculated to reflect processing efficiency according to the time elapsed since target onset and the power of SNR oscillations in the 5–55 Hz range. CIs differed substantially across groups whereas individuals of the same group largely shared crucial features such that a machine learning algorithm reached 100% accuracy in classifying the data patterns of individual participants into their proper group. These findings demonstrate altered perceptual oscillations in healthy aging and are consistent with previous investigations showing brain oscillation anomalies in the elderly.
Comparing COVID-19 severity in patients hospitalized for community-associated Delta, BA.1 and BA.4/5 variant infection
Authors: Sočan Maja , Mrzel Maja , Prosenc Katarina , Korva Miša , Avšič-Županc Tatjana , Poljak Mario , Lunar Maja M. , Zupanič Tina
Published: February 2024

Background

Despite decreasing COVID-19 disease severity during the Omicron waves, a proportion of patients still require hospitalization and intensive care.

Objective

To compare demographic characteristics, comorbidities, vaccination status, and previous infections in patients hospitalized for community-associated COVID-19 (CAC) in predominantly Delta, Omicron BA.1 and BA.4/5 SARS-CoV-2 waves.

Methods

Data were extracted from three national databases—the National COVID-19 Database, National Vaccination Registry and National Registry of Hospitalizations.

Results

Among the hospitalized CAC patients analyzed in this study, 5,512 were infected with Delta, 1,120 with Omicron BA.1, and 1,143 with the Omicron BA.4/5 variant. The age and sex structure changed from Delta to BA.4/5, with the proportion of women (9.5% increase), children and adolescents (10.4% increase), and octa- and nonagenarians increasing significantly (24.5% increase). Significantly more patients had comorbidities (measured by the Charlson Comorbidity Index), 30.3% in Delta and 43% in BA.4/5 period. The need for non-invasive ventilatory support (NiVS), ICU admission, mechanical ventilation (MV), and in-hospital mortality (IHM) decreased from Delta to Omicron BA.4/5 period for 12.6, 13.5, 11.5, and 6.3%, respectively. Multivariate analysis revealed significantly lower odds for ICU admission (OR 0.68, CI 0.54–0.84, p < 0.001) and IHM (OR 0.74, CI 0.58–0.93, p = 0.011) during the Delta period in patients who had been fully vaccinated or boosted with a COVID-19 vaccine within the previous 6 months. In the BA.1 variant period, patients who had less than 6 months elapsed between the last vaccine dose and SARS-CoV-2 positivity had lower odds for MV (OR 0.38, CI 0.18-0.72, p = 0.005) and IHM (OR 0.56, CI 0.37- 0.83, p = 0.005), but not for NIVS or ICU admission.

Conclusion

The likelihood of developing severe CAC in hospitalized patients was higher in those with the Delta and Omicron BA.1 variant compared to BA.4/5.
Medical errors, affected sites, and adverse consequences among patients in the orthopaedic department: Does age matter?
Authors: Liu Paicheng , Cheng Jianxin , Yang Yuxuan , Zhu Haipeng
Published: February 2024

Background

Orthopaedics have become the focus of research on patient safety due to the high incidence of medical errors. Previous studies were based on all orthopaedic patients and rarely conducted empirical analyses from the perspective of age. This study aimed to fill the academic gap in the age variable by comparing medical errors, affected sites, and adverse consequences in orthopaedic patients.

Methods

This retrospective study included 329 litigation claims against orthopaedists using data from China Judgments Online. First, we performed computer crawling and screened 5,237 litigation documents using keywords, including medical errors. Second, 2,536 samples were retained through systematic random sampling, and 549 irrelevant cases were deleted after manual reading. Finally, three clinicians from different medical departments selected 329 incidents related to orthopaedics for further analysis, according to the description of the lawsuits. Three other professional orthopaedists evaluated the patients’ ages, affected sites of medical errors, and adverse consequences.

Results

The greatest number of medical errors was observed in the joints (30.43%) for all orthopaedic patients. However, adult patients (aged 18–60 years) were most susceptible to errors in the extremities (30.42%). A higher rate of complications was associated with a higher rate of morbidity/mortality for the corresponding patients. Medical errors correlated with complications occurred in the following sites: joints (15.38%), extremities (12.50%), spine (16.95%), multiple sites (15.38%), and hands and feet (14.81%). In addition to surgical errors, over 10% of all orthopaedic patients experienced missed diagnoses. The incidence of insufficient adherence to informed consent obligations was 13.5% among adult patients and was much higher in paediatric and older adults patients. When orthopaedic patients suffered from medical technical errors, iatrogenic mortality/morbidity would decrease by 0.3% for one unit increase in age.

Conclusion

Dividing patients into different ages demonstrated diverse results in terms of medical errors and affected sites. Negligence in diagnosis and examination can be fatal factors that endanger safety, and complications may cause morbidity/mortality. When patients suffered from technical errors, age is inversely proportional to mortality/morbidity. Special attention needs to be paid to technical errors in the younger older adults population (60–64 years old), which has inspired implications in promoting aging and public health.
Virtual reality perceptual training can improve the temporal discrimination ability of swinging during softball batting
Authors: Nasu Daiki , Baba Takamichi , Imamura Takumi , Yamaguchi Masumi , Kitanishi Yoshitake , Kashino Makio
Published: February 2024

Perception and action uncoupling in fastball sports anticipatory training is often criticized. Nevertheless, perception-only training offers distinct advantages, such as flexibility concerning time, place, and injury limitations. Therefore, the effectiveness of this training approach warrants evaluation. This study developed a virtual reality (VR) training system based on the idea that the two visual pathways in the brain are associated with visual information attributes, rather than perception or action. A key feature of this study's perception-only training was its presentation of not only the opponent's kinematics but also the ball's flight information (the attributes that guide hitting) to train the visual system necessary for real situations. Seventeen female softball batters were assigned to two groups: a training group (N = 9) and a control group (N = 8). Only the training group underwent the VR anticipatory skill training to discriminate the different ball speeds. Both groups completed a perception test and an action test on the VR during the pre- and post-training periods. The perception test assessed response accuracy (RA) in discriminating ball speed, and the action test assessed the temporal difference in swing onset (delta onset). Comparison of these two outcome variables between groups revealed that perception-only training improved both perceptual and action responses. This study demonstrated the effectiveness of perception-only training and emphasized the need for its thoughtful utilization and design.
Sustainability of shared economy in the agri-food, tourism, and hospitality industries
Authors: Alloh Karel , Abrham Josef , Sanova Petra , Čermák Michal , Petrzilka Slavibor , Schilla Filip
Published: February 2024

Introduction

This study aims to provide a systematic literature review on the sustainability of shared economy in the food, agricultural, and hospitality sectors. We assess relationships between the sharing economy and sustainability in the examined industries. Furthermore, we identify gaps in knowledge and recommend possible research directions for future studies.

Methods

This study provides a systematic literature review on sustainable sharing economy in the hospitality and agri-food sectors. We applied the Procedure for Systematic Reviews and Meta-Analyses (PRISMA). Based on the mentioned methodological procedure, we conducted a literature search through scientific databases Scopus and Web of Science. The research period is 2014–2023.

Results

Using the Procedure for Systematic Reviews and Meta-Analyses (PRISMA), we extracted 2185 scientific articles from the Scopus and Web of Science databases published between 2014 and 2023. A total of 117 studies met the eligibility criteria. Based on the review, we identified the following frequently researched areas in the literature: sustainable housing sharing, urban and community sustainability, energy efficiency and carbon footprint, public sector regulation and sustainability, food sharing, exchanges and networks, food waste-reducing platforms, and food-based applications.

Conclusion

The studies reviewed confirmed growing research interest in the sustainability of the shared economy in agri-food and hospitality. The number of studies in the Web of Science and Scopus databases has increased over the last decade. Our systematic review indicates that shared accommodation and food sharing are dominant topics in the literature. The sustainability of shared accommodation has been examined in previous studies, mainly concerning the impacts on cities and communities. In food sharing, we identified relevant linkages between food waste and sharing platforms.
Improving risk communication: a proof-of-concept randomised control trial assessing the impact of visual aids for neurosurgical consent
Authors: Chatzopoulou Despoina , Jalal Arif Hanafi Bin , Stoyanov Danail , Marcus Hani J. , Pandit Anand S.
Published: February 2024

Introduction

Informed consent is a fundamental component in the work-up for surgical procedures. Statistical risk information pertaining to a procedure is by nature probabilistic and challenging to communicate, especially to those with poor numerical literacy. Visual aids and audio/video tools have previously been shown to improve patients' understanding of statistical information. In this study, we aimed to explore the impact of different methods of risk communication in healthy participants randomized to either undergo the consent process with visual aids or the standard consent process for lumbar puncture.

Material and methods

Healthy individuals above 18 years old were eligible. The exclusion criteria were prior experience of the procedure or relevant medical knowledge, lack of capacity to consent, underlying cognitive impairment and hospitalised individuals. After randomisation, both groups received identical medical information about the procedure of a lumbar puncture in a hypothetical clinical scenario via different means of consent. The control group underwent the standard consent process in current clinical practice (Consent Form 1 without any illustrative examples), whereas the intervention group received additional anatomy diagrams, the Paling Palette and the Paling perspective scale. Anonymised questionnaires were received to evaluate their perception of the procedure and its associated risks.

Results

Fifty-two individuals were eligible without statistically significant differences in age, sex, professional status and the familiarity of the procedure. Visual aids were noted to improve the confidence of participants to describe the risks by themselves (p = 0.009) and participants in the intervention group felt significantly less overwhelmed with medical information (p = 0.028). The enhanced consent process was found to be significantly more acceptable by participants (p = 0.03). There was a trend towards greater appropriateness (p = 0.06) and it appeared to have “good” usability (median SUS = 76.4), although this also did not reach statistical significance (p = 0.06)

Conclusion

Visual aids could be an appropriate alternative method for medical consent without being inferior regarding the understanding of the procedure, its risks and its benefits. Future studies could possibly compare or incorporate multiple interventions to determine the most effective tools in a larger scale of population including patients as well as healthy individuals.
Effects of adding Allium mongolicum Regel powder and yeast cultures to diet on rumen microbial flora of Tibetan sheep (Ovis aries)
Authors: Wang Chunhui , Fan Juan , Ma Keyan , Wang Huihui , Li Dengpan , Li Taotao , Ma Youji
Published: February 2024

The purpose of this experiment was to study the effect of Allium mongolicum Regel powder (AMR) and yeast cultures (YC) on rumen microbial diversity in Tibetan sheep in different Ecological niches. A total of 40 male Tibetan lambs with an initial weight of 18.56 ± 1.49 kg (6 months old) were selected and divided into four groups (10 sheep/pen; n = 10). In the Control Group, each animal was grazed for 8 h per day, in Group I, each animal was supplemented with 200 g of concentrate per day, in Group II, each animal was supplemented with 200 g of concentrate and 10 g of AMR per day, in Group III, each animal was supplemented with 200 g of concentrate and 20 g of YC per day. The experiment lasted 82 days and consisted of a 7-day per-feeding period and a 75-day formal period. The results indicated that at the phylum level, the abundance of Bacteroidota and Verrucomimicrobiota in L-Group II and L-Group III was increased, while the abundance of Proteobacteria was decreased in the LA (Liquid-Associated) groups. The proportion of F/B in S-Group II and S-Group III was increased compared to S-Group I and S-CON in the SA (Soild-Associated) group. At the genus level, the abundance of uncultured_rumen_bacterium and Eubacterium_ruminantium_group in L-Group II and L-Group III was increased. Furthermore, while the abundance of Rikenellaceae_RC9_gut_group was decreased in the LA, the abundance of Prevotella and Eubacterium_ruminantium_group was increased in the S-Group II and S-Group III compared to S-Group I and S-CON. The abundance of probable_genus_10 was the highest in S-Group II in the SA group. After the addition of YC and AMR, there was an increase in rumen microbial abundance, which was found to be beneficial for the stability of rumen flora and had a positive impact on rumen health.
Squid meal and shrimp hydrolysate as novel protein sources for dog food
Authors: Guilherme-Fernandes Joana , Aires Tiago , Fonseca António J. M. , Yergaliyev Timur , Camarinha-Silva Amélia , Lima Sofia A. C. , Maia Margarida R. G. , Cabrita Ana R. J.
Published: February 2024

The world’s growing pet population is raising sustainability and environmental concerns for the petfood industry. Protein-rich marine by-products might contribute to mitigating negative environmental effects, decreasing waste, and improving economic efficiency. The present study evaluated two marine by-products, squid meal and shrimp hydrolysate, as novel protein sources for dog feeding. Along with the analysis of chemical composition and antioxidant activity, palatability was evaluated by comparing a commercial diet (basal diet) and diets with the inclusion of 150 g kg−1 of squid meal or shrimp hydrolysate using 12 Beagle dogs (2.2 ± 0.03 years). Two in vivo digestibility trials were conducted with six dogs, three experimental periods (10 days each) and three dietary inclusion levels (50, 100 and 150 g kg−1) of squid meal or shrimp hydrolysate in place of the basal diet to evaluate effects of inclusion level on apparent total tract digestibility (ATTD), metabolizable energy content, fecal characteristics, metabolites, and microbiota. Both protein sources presented higher protein and methionine contents than ingredients traditionally used in dog food formulation. Shrimp hydrolysate showed higher antioxidant activity than squid meal. First approach and taste were not affected by the inclusion of protein sources, but animals showed a preference for the basal diet. Effects on nutrient intake reflected the chemical composition of diets, and fecal output and characteristics were not affected by the increasing inclusion levels of both protein sources. The higher ATTD of dry matter, most nutrients and energy of diets with the inclusion of both by-products when compared to the basal diet, suggests their potential to be included in highly digestible diets for dogs. Although not affected by the inclusion level of protein sources, when compared to the basal diet, the inclusion of squid meal decreased butyrate concentration and shrimp hydrolysate increased all volatile fatty acids, except butyrate. Fecal microbiota was not affected by squid meal inclusion, whereas inclusion levels of shrimp hydrolysate significantly affected abundances of Oscillosperaceae (UCG-005), Firmicutes and Lactobacillus. Overall, results suggest that squid meal and shrimp hydrolysate constitute novel and promising protein sources for dog food, but further research is needed to fully evaluate their functional value.
Optimizing Speech Emotion Recognition with Deep Learning and Grey Wolf Optimization: A Multi-Dataset Approach
Authors: Tyagi Suryakant , Szénási Sándor
Published: February 2024

Machine learning and speech emotion recognition are rapidly evolving fields, significantly impacting human-centered computing. Machine learning enables computers to learn from data and make predictions, while speech emotion recognition allows computers to identify and understand human emotions from speech. These technologies contribute to the creation of innovative human–computer interaction (HCI) applications. Deep learning algorithms, capable of learning high-level features directly from raw data, have given rise to new emotion recognition approaches employing models trained on advanced speech representations like spectrograms and time–frequency representations. This study introduces CNN and LSTM models with GWO optimization, aiming to determine optimal parameters for achieving enhanced accuracy within a specified parameter set. The proposed CNN and LSTM models with GWO optimization underwent performance testing on four diverse datasets—RAVDESS, SAVEE, TESS, and EMODB. The results indicated superior performance of the models compared to linear and kernelized SVM, with or without GWO optimizers.
Multi-Augmentation-Based Contrastive Learning for Semi-Supervised Learning
Authors: Wang Jie , Yang Jie , He Jiafan , Peng Dongliang
Published: February 2024

Semi-supervised learning has been proven to be effective in utilizing unlabeled samples to mitigate the problem of limited labeled data. Traditional semi-supervised learning methods generate pseudo-labels for unlabeled samples and train the classifier using both labeled and pseudo-labeled samples. However, in data-scarce scenarios, reliance on labeled samples for initial classifier generation can degrade performance. Methods based on consistency regularization have shown promising results by encouraging consistent outputs for different semantic variations of the same sample obtained through diverse augmentation techniques. However, existing methods typically utilize only weak and strong augmentation variants, limiting information extraction. Therefore, a multi-augmentation contrastive semi-supervised learning method (MAC-SSL) is proposed. MAC-SSL introduces moderate augmentation, combining outputs from moderately and weakly augmented unlabeled images to generate pseudo-labels. Cross-entropy loss ensures consistency between strongly augmented image outputs and pseudo-labels. Furthermore, the MixUP is adopted to blend outputs from labeled and unlabeled images, enhancing consistency between re-augmented outputs and new pseudo-labels. The proposed method achieves a state-of-the-art performance (accuracy) through extensive experiments conducted on multiple datasets with varying numbers of labeled samples. Ablation studies further investigate each component’s significance.
An Iris Image Super-Resolution Model Based on Swin Transformer and Generative Adversarial Network
Authors: Lu Hexin , Zhu Xiaodong , Cui Jingwei , Jiang Haifeng
Published: February 2024

The process of iris recognition can result in a decline in recognition performance when the resolution of the iris images is insufficient. In this study, a super-resolution model for iris images, namely SwinGIris, which combines the Swin Transformer and the Generative Adversarial Network (GAN), is introduced. SwinGIris performs quadruple super-resolution reconstruction for low-resolution iris images, aiming to improve the resolution of iris images and thereby improving the recognition accuracy of iris recognition systems. The model utilizes residual Swin Transformer blocks to extract depth global features, and the progressive upsampling method along with sub-pixel convolution is conducive to focusing on the high-frequency iris information in the presence of more non-iris information. In order to preserve high-frequency details, the discriminator employs a VGG-style relative classifier to guide the generator in generating super-resolution images. In experimental section, we enhance low-resolution (56 × 56) iris images to high-resolution (224 × 224) iris images. Experimental results indicate that the SwinGIris model achieves satisfactory outcomes in restoring low-resolution iris image textures while preserving identity information.
What Is a Causal Graph?
Authors: Dawid Philip
Published: February 2024

This article surveys the variety of ways in which a directed acyclic graph (DAG) can be used to represent a problem of probabilistic causality. For each of these ways, we describe the relevant formal or informal semantics governing that representation. It is suggested that the cleanest such representation is that embodied in an augmented DAG, which contains nodes for non-stochastic intervention indicators in addition to the usual nodes for domain variables.
Proxy-Based Sliding Mode Force Control for Compliant Grinding via Diagonal Recurrent Neural Network and Prandtl-Ishlinskii Hysteresis Compensation Model
Authors: Li Zhiyuan , Sun Lei , Liu Jidong , Qin Yanding , Sun Ning , Zhou Lu
Published: February 2024

Traditional industrial robots often face challenges in achieving a perfectly polished surface on a workpiece because of their high mechanical rigidity. The active compliance force control device installed at the robotic arm’s end enables high-precision contact force control between the grinding tool and the workpiece. However, the complex hysteresis nonlinearity between cylinder air pressure and output force, as well as various random disturbances during the grinding process, can affect the accuracy of the contact force and potentially impact the grinding effect of the workpiece, even causing irreversible damage to the surface of the workpiece. Given the complex random variation of cylinder output force in the actual grinding process, a rate-dependent hysteresis model based on diagonal recurrent neural network and Pradtl–Ishlinskii models named dRNN-PI is designed to compensate for the complex nonlinear hysteresis of the cylinder and calculate the desired air pressure to maintain a steady contact force on the workpiece. The proxy-based sliding mode control (PSMC) is utilized to quickly track the desired air pressure without overshooting. This paper also proves the controller’s stability using the Lyapunov-based methods. Finally, the accuracy of the proposed hysteresis compensation model and the effectiveness and robustness of the PSMC are verified by experiment results.
Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
Authors: Wang Yang , Hao Tianze , Liu Yibo , Xiao Huaping , Liu Shuhai , Zhu Hongwu
Published: February 2024

Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.
Effect of Water Conservation and Nitrogen Reduction on Root Growth and Yield in Spring Maize in Typical Sand Interlayered Soil
Authors: Sun Wei , Shi Haibin , Li Xianyue , Miao Qingfeng , Yan Jianwen , Feng Zhuangzhuang , Qi Yinglong , Feng Weiying
Published: February 2024

Given the low water and fertiliser use efficiency and the extensive distribution of sand interlayered soil in the Hetao irrigation district (HID), this study aimed to investigate the effects of different irrigation and fertilisation regimes on root parameters and yield in spring maize grown in sand interlayered soil. A two-year field plot experiment was conducted using the spring maize “Ximeng 3358” under three irrigation and nitrogen levels. Root length (RL), surface area (RS), diameter (RD), volume (RV), and length density (RLD), grain yield, and water use efficiency (WUE) were examined. Root growth was inhibited at the sand layer, with approximately 72.46–87.37% of the roots concentrated in the 0–40 cm soil layer. Notably, the proportion of roots in the bottom layer was 24.61–87.37% higher than that in the sub-bottom layer. Moreover, RL, RS, RD, and RV peaked in the medium irrigation and nitrogen fertilisation (I2F2) treatment. Furthermore, correlation analysis showed that the root parameters were significantly positively correlated with yield and WUE, with RS being most correlated to yield and WUE. Roots at a narrow row spacing of 20 cm (NR20) and at a depth of 10–20 cm were strongly correlated with yield and WUE. Conclusively, the I2F2 treatment can be used as the optimal combination of water and nitrogen for sand interlayered soil farmlands.
ALIKE-APPLE: A Lightweight Method for the Detection and Description of Minute and Similar Feature Points in Apples
Authors: Huang Xinyao , Xu Tao , Zhang Xiaomin , Zhu Yihang , Wu Zheyuan , Xu Xufeng , Gao Yuan , Wang Yafei , Rao Xiuqin
Published: February 2024

Current image feature extraction methods fail to adapt to the fine features of apple image texture, resulting in image matching errors and degraded image processing accuracy. A multi-view orthogonal image acquisition system was constructed with apples as the research object. The system consists of four industrial cameras placed around the apple at different angles and one camera placed on top. Following the image acquisition through the system, synthetic image pairs—both before and after transformation—were generated as the input dataset. This generation process involved each image being subjected to random transformations. Through learning to extract more distinctive and descriptive features, the deep learning-based keypoint detection method surpasses traditional techniques by broadening the application range and enhancing detection accuracy. Therefore, a lightweight network called ALIKE-APPLE was proposed for surface feature point detection. The baseline model for ALIKE-APPLE is ALIKE, upon which improvements have been made to the image feature encoder and feature aggregation modules. It comprises an Improved Convolutional Attention Module (ICBAM) and a Boosting Resolution Sampling Module (BRSM). The proposed ICBAM replaced max pooling in the original image feature encoder for downsampling. It enhanced the feature fusion capability of the model by utilizing spatial contextual information and learning region associations in the image. The proposed BRSM replaced the bilinear interpolation in the original feature aggregator for upsampling, overcoming the apple side image’s geometric distortion and effectively preserving the texture details and edge information. The model size was shrunk by optimizing the number of downsampling operations from the image encoder of the original model. The experimental results showed that the average number of observed keypoints and the average matching accuracy were improved by 166.41% and 37.07%, respectively, compared with the baseline model. The feature detection model of ALIKE-APPLE was found to perform better than the optimal SuperPoint. The feature point distribution of ALIKE-APPLE showed an improvement of 10.29% in average standard deviation (Std), 8.62% in average coefficient of variation (CV), and 156.12% in average feature point density (AFPD). Moreover, the mean matching accuracy (MMA) of ALIKE-APPLE improved by 125.97%. Thus, ALIKE-APPLE boasts a more consistent allocation of feature points and greater precision in matching.
Fine-Tuning Quantitative Trait Loci Identified in Immortalized F2 Population Are Essential for Genomic Prediction of Hybrid Performance in Maize
Authors: Wang Pingxi , Ma Xingye , Jin Xining , Wu Xiangyuan , Zhang Xiaoxiang , Zhang Huaisheng , Wang Hui , Zhang Hongwei , Fu Junjie , Xie Yuxin , Chen Shilin
Published: February 2024

Maize breeding is greatly affected by hybrid vigor, a phenomenon that hybrids exhibit superior performance than parental lines. The immortalized F2 population (IMF2) is ideal for the genetic dissection and prediction of hybrid performance. Here, in this study, we conducted the QTL mapping and genomic prediction of six traits related to plant architecture using an IMF2 population. Broad-sense heritability of these traits ranged from 0.85 to 0.94. Analysis of genetic effects showed that additive variance was the main contributor to phenotypic variations. The mapping of quantitative trait loci (QTLs) revealed 10 to 16 QTLs (including pleiotropic loci and epistatic QTLs) for the six traits. Additionally, we identified 15 fine-tuning QTLs for plant height (PH). For genomic prediction (GP), the model of additive and dominance (AD) exhibited higher prediction accuracy than those fitting general combining ability (GCA) and its combination with special combining ability (SCA) effects for all tested traits. And adding the epistasis (E) effect into the AD model did not significantly increase its prediction accuracy. Moreover, the identified 15 fine-tuning QTLs of PH, which exerted large genomic prediction effects, were verified by the marker effect of GP. Our results not only provide an approach for the fine-mapping of fine-tuning QTLs but also serve as references for GP breeding in crops.
The Influence of Shallow Groundwater on the Physicochemical Properties of Field Soil, Crop Yield, and Groundwater
Authors: Li Xurun , Li Zhao , Fu Weizhang , Li Fadong
Published: February 2024

The depth of shallow groundwater significantly influences crop growth and yield by altering the physicochemical properties of farmland soil profiles. Concurrently, shallow groundwater is subject to various changes, and it remains unclear how alterations in shallow groundwater depth within field soil impact soil physicochemical properties, crop yields, and the overall dynamics of groundwater transformations. To address these uncertainties, this study utilized a sample plot equipped with a volume lysimeter and implemented four distinct groundwater depths as treatment conditions: G0 (no groundwater depth), G1 (a groundwater depth of 40 cm), G2 (a groundwater depth of 70 cm), G3 (a groundwater depth of 110 cm), and G4 (a groundwater depth of 150 cm). This study was carried out on a weekly basis to monitor fluctuations in ion content in shallow groundwater and soil moisture after the summer maize harvest, and special attention was afforded to non-irrigation conditions. This study also scrutinized the distribution of salt and nutrients in soil profiles and assessed changes in summer maize yield. Very interesting findings were obtained by conducting the study. Firstly, the shallower the groundwater depth, the higher the water and salt content of the soil surface. Small, frequent rainfall events (precipitation ≤ 25 mm) facilitated the effective removal of salt from the soil surface. Despite increased rainfall contributing to salt ion dilution in groundwater, the risk of soil surface salinization increased at the surface level. Secondly, a linear relationship existed between groundwater depth and surface soil moisture and salt content. With every 10 cm increase in groundwater depth, the surface soil moisture and salt content decreased by 0.56% and 0.06 g/kg, respectively. Soil nutrients tended to accumulate in the surface layer, with nutrient content increasing with depth. However, C/N was not notably affected by groundwater depth. Thirdly, Na+ and K+ consistently dominated the soil surface. As soil salinity increased, the prevalence of Cl− and SO42− increased, with the rate of SO42− increase surpassing that of chlorine. HCO3− altered by rainfall served as an indicator of soil alkalization characteristics, while Na+ and K+ in soil, along with Cl− and SO42− derived from groundwater, represented soil salt composition and salinization trends. Ultimately, under the conditions of this study, the most favorable groundwater depth for the growth of summer maize was determined to be 1.1 m. Analyzing the impact of different shallow groundwater depths on the physicochemical properties of farmland soil enhances our understanding of the mechanisms of interaction between groundwater and soil in agricultural ecosystems. This knowledge is instrumental in significantly improving the soil environment, thereby ensuring optimal crop yields.
Foliar Application of Biostimulant Mitigates Water Stress Effects on Soybean
Authors: Melo Gabriel Bressiane , da Silva Alessandro Guerra , da Costa Alan Carlos , Alves da Silva Adnan , Rosa Márcio , Bessa Layara Alexandre , Rodrigues Carlos Ribeiro , Castoldi Gustavo , Vitorino Luciana Cristina
Published: February 2024

Climate change has emerged as a challenge for soybean cultivation around the world, stimulating the development of technological alternatives that aim to mitigate the damage caused by water deficit. From this perspective, algae extract-based biostimulants have been tested to reduce water stress in several crops, but little is known about their effects on soybean. Thus, we hypothesize that a commercial biostimulant based on Ascophyllum nodosum can improve the physiological performance and water relations of Glycine max plants subjected to water deficit. To test this hypothesis, we set up an experiment in controlled conditions in a greenhouse, considering five treatments (control; application of biostimulant; water deficit (WD); WD + application of biostimulant; and WD + split application of biostimulant). The experiment was designed in completely randomized blocks with four replications per treatment and conducted in polyethylene pots containing 10 L of soil and three plants per pot. The irrigation was carried out daily; the water deficit was 50% soil moisture at field capacity, starting at the R1 stage (beginning of flowering, where there is at least one flower open at any node on the plant) and maintained for ten days. The biostimulant was applied concurrently with the onset of water deficit. We confirmed the hypothesis that foliar application of 1.0 L ha−1 of the biostimulant reduces the deleterious effects of the common water deficit at the beginning of the reproductive stage of soybean through the reduction of damage from oxidative stress (reduction of malondialdehyde synthesis by 31.2% in relation to the WD plants), maintenance of water potential and cellular homeostasis (10.2% increase in relative water content when compared with WD plants), and conservation of the contents of chlorophyll in leaves and stimulation of photosynthesis and carboxylation (68% increase in net photosynthetic rate and 49.3% increase in carboxylation efficiency in relation to WD plants). However, when applied in installments, the biostimulant was not efficient in reducing soybean water stress. Therefore, we conclude that the application of a biostimulant based on A. nodosum can help reduce the harmful effects of water deficit on soybean plants, opening up perspectives for the mass use of this extract in agricultural crops produced on a large scale.
Physiological and Biochemical Background of Deacclimation in Plants, with Special Attention Being Paid to Crops: A Minireview
Authors: Stachurska Julia , Janeczko Anna
Published: February 2024

Global climate change, which is connected to global warming and changes in weather patterns, affects various parts of the environment, including the growth/development of plants. Generally, a number of plant species are capable of acquiring tolerance to frost after exposure to cold (in the cold-acclimation/cold-hardening process). In the last few decades, there have been more and more frequent periods of higher temperatures—warm periods that, e.g., break down the process of cold acclimation. This generates deacclimation, which could stimulate growth and lower frost tolerance in plants. Generally, deacclimation causes the reversal of changes induced by cold acclimation (i.e., in concentration of sugars, accumulation of protective proteins, or hormonal homeostasis). Unlike cold acclimation, the phenomenon of deacclimation has been less studied. The aim of this article was (1) to briefly describe the problem of deacclimation, with more attention being paid to its significance for economically important winter crop species, (2) to review and characterize the physiological-biochemical changes that are induced in plants by deacclimation, and (3) to discuss the possibilities of detecting deacclimation earlier in order to counteract its effects on crops.
Effects of Probiotic Lactiplantibacillus plantarum HJLP-1 on Growth Performance, Selected Antioxidant Capacity, Immune Function Indices in the Serum, and Cecal Microbiota in Broiler Chicken
Authors: Yang Caimei , Wang Shuting , Li Qing , Zhang Ruiqiang , Xu Yinglei , Feng Jie
Published: February 2024

This research study aimed to investigate the effects of Lactiplantibacillus plantarum (L. plantarum) on growth performance, oxidation resistance, immunity, and cecal microbiota in broilers. This work classed three hundred and sixty 1-day-old male broilers into three groups randomly, including a control group (CON, basal diet) and antibiotic (ANT, 75 mg kg−1 chlortetracycline added into basal diet) and probiotic groups (LP, 5 × 108 CFU kg−1Lactiplantibacillus plantarum HJLP-1 contained within basal diet). Animals were then fed for 42 days, and each group comprised eight replicates with 15 broilers. Compared with CON, L. plantarum supplementation significantly improved the average daily weight gain (AWDG) (p < 0.05) while reducing the feed–gain ratio over the entire supplemental period (p < 0.05). Birds fed L. plantarum had markedly lower serum ammonia and xanthine oxidase levels (p < 0.05) than those in the ANT and CON groups. Significant improvements (p < 0.05) in superoxide dismutase, catalase, and serum IgM and IgY contents in broilers fed L. plantarum were also observed when compared with those in the CON and ANT groups. Both L. plantarum and antibiotics decreased pro-inflammatory factor IL-1β levels significantly (p < 0.05), while only L. plantarum promoted anti-inflammatory factor IL-10 levels in the serum (p < 0.05) compared with CON. L. plantarum (p < 0.05) increased acetic acid and butyric acid concentrations in cecal contents when compared to those in CON and ANT. Among the differences revealed via 16S rRNA analysis, L. plantarum markedly improved the community richness of the cecal microbiota. At the genus level, the butyric acid-producing bacteria Ruminococcus and Lachnospiraceae were found in higher relative abundance in samples of L. plantarum-treated birds. In conclusion, dietary L. plantarum supplementation promoted the growth and health of broilers, likely by inducing a shift in broiler gut microbiota toward short-chain fatty acid (SCFA)-producing bacteria. Therefore, L. plantarum has potential as an alternative to antibiotics in poultry breeding.
Genome-Wide Analysis of Milk Production Traits and Selection Signatures in Serbian Holstein-Friesian Cattle
Authors: Ristanic Marko , Zorc Minja , Glavinic Uros , Stevanovic Jevrosima , Blagojevic Jovan , Maletic Milan , Stanimirovic Zoran
Published: February 2024

To improve the genomic evaluation of milk-related traits in Holstein-Friesian (HF) cattle it is essential to identify the associated candidate genes. Novel SNP-based analyses, such as the genetic mapping of inherited diseases, GWAS, and genomic selection, have led to a new era of research. The aim of this study was to analyze the association of each individual SNP in Serbian HF cattle with milk production traits and inbreeding levels. The SNP 60 K chip Axiom Bovine BovMDv3 was deployed for the genotyping of 334 HF cows. The obtained genomic results, together with the collected phenotypic data, were used for a GWAS. Moreover, the identification of ROH segments was performed and served for inbreeding coefficient evaluation and ROH island detection. Using a GWAS, a polymorphism, rs110619097 (located in the intron of the CTNNA3 gene), was detected to be significantly (p < 0.01) associated with the milk protein concentration in the first lactation (adjusted to 305 days). The average genomic inbreeding value (FROH) was 0.079. ROH islands were discovered in proximity to genes associated with milk production traits and genomic regions under selection pressure for other economically important traits of dairy cattle. The findings of this pilot study provide useful information for a better understanding of the genetic architecture of milk production traits in Serbian HF dairy cows and can be used to improve lactation performances in Serbian HF cattle breeding programs.
Impact of Climate Change on the Distribution of Three Rare Salamanders (Liua shihi, Pseudohynobius jinfo, and Tylototriton wenxianensis) in Chongqing, China, and Their Conservation Implications
Authors: Ma Qi , Wan Lipeng , Shi Shengchao , Wang Zhijian
Published: February 2024

The Wushan Salamander (Liua shihi), Jinfo Salamander (Pseudohynobius jinfo), and Wenxian Knobby Salamander (Tylototriton wenxianensis) are rare national Class II protected wild animals in China. We performed MaxEnt modeling to predict and analyze the potential distribution and trends of these species in Chongqing under current and future climate conditions. Species distribution data were primarily obtained from field surveys, supplemented by museum collections and the existing literature. These efforts yielded 636 records, including 43 for P. jinfo, 23 for T. wenxianensis, and 570 for L. shihi. Duplicate records within the same 100 m × 100 m grid cell were removed using ENMTools, resulting in 10, 12, and 58 valid distribution points for P. jinfo, T. wenxianensis, and L. shihi, respectively. The optimization of feature class parameters (FC) and the regularization multiplier (RM) were applied using R package “ENMeval 2.0” to establish the optimal model with MaxEnt. The refined models were applied to simulate the suitable distribution areas for the three species. The results indicate that the current suitable habitat area for L. shihi accounted for 9.72% of the whole region of the Chongqing municipality. It is projected that, by 2050, the proportion of suitable habitat will increase to 12.54% but will decrease to 11.98% by 2070 and further decline to 8.80% by 2090. The current suitable habitat area for P. jinfo accounted for 1.08% of the whole region of the Chongqing municipality, which is expected to decrease to 0.31%% by 2050, 0.20% by 2070, and 0.07% by 2090. The current suitable habitat area for T. wenxianensis accounted for 0.81% of the whole region of the Chongqing municipality, which is anticipated to decrease to 0.37% by 2050, 0.21% by 2070, and 0.06% by 2090. Human disturbance, climate variables, and habitat characteristics are the primary factors influencing the distribution of three salamander species in Chongqing. The proximity to roads significantly impacts L. shihi, while climate conditions mainly affect P. jinfo, and the distance to water sources is crucial for T. wenxianensis. The following suggestions were made based on key variables identified for each species: (1) For L. shihi, it is imperative to minimize human disturbances and preserve areas without roads and the existing vegetation within nature reserves to ensure their continued existence. (2) For P. jinfo, the conservation of high-altitude habitats is of utmost importance, along with the reduction in disturbances caused by roads to maintain the species’ ecological niche. (3) For T. wenxianensis, the protection of aquatic habitats is crucial. Additionally, efforts to mitigate the impacts of road construction and enhance public awareness are essential for the preservation of this species and the connectivity of its habitats.