bluuebunny/crossref_metadata_2025 huggingface dataset:
Haptoglobin is dispensable for haemoglobin uptake by Trypanosoma brucei
Authors: Horáková Eva , Vrbacký Marek , Tesařová Martina , Stříbrná Eva , Pilný Jan , Vavrušková Zuzana , Vancová Marie , Sobotka Roman , Lukeš Julius , Perner Jan
Published: July 2024

Haptoglobin is a plasma protein of mammals that plays a crucial role in vascular homeostasis by binding free haemoglobin released from ruptured red blood cells. Trypanosoma brucei can exploit this by internalising haptoglobin-haemoglobin complex to acquire host haem. Here, we investigated the impact of haptoglobin deficiency (Hp-/-) on T. brucei brucei infection and the parasite´s capacity to internalise haemoglobin in a Hp-/- mouse model. The infected Hp-/- mice exhibited normal disease progression, with minimal weight loss and no apparent organ pathology, similarly to control mice. While the proteomic profile of mouse sera significantly changed in response to T. b. brucei, no differences in the infection response markers of blood plasma between Hp-/- and control Black mice were observed. Similarly, very few quantitative differences were observed between the proteomes of parasites harvested from Hp-/- and Black mice, including both endogenous proteins and internalised host proteins. While haptoglobin was indeed absent from parasites isolated from Hp-/-mice, haemoglobin peptides were unexpectedly detected in parasites from both Hp-/- and Black mice. Combined, the data support the dispensability of haptoglobin for haemoglobin internalisation by T. b. brucei during infection in mice. Since the trypanosomes knock-outs for their haptoglobin-haemoglobin receptor (HpHbR) internalised significantly less haemoglobin from Hp-/- mice compared to those isolated from Black mice, it suggests that T. b. brucei employs also an HpHbR-independent haptoglobin-mediated mode for haemoglobin internalisation. Our study reveals a so-far hidden flexibility of haemoglobin acquisition by T. b. brucei and offers novel insights into alternative haemoglobin uptake pathways.
Genome-wide characterization, phylogenetic and expression analysis of Galectin gene family in Golden pompano Trachinotus ovatus
Authors: Pan Jin-Min , Liang Yu , Zhu Ke-Cheng , Guo Hua-Yang , Liu Bao-Suo , Zhang Nan , Xian Lin , Zhu Teng-Fei , Zhang Dian-Chang
Published: July 2024

Galectins (Gals) are a type of S-type lectin that are widespread and evolutionarily conserved among metazoans, and can act as pattern recognition receptors (PRRs) to recognize pathogen-associated molecular patterns (PAMPs). In this study, 10 Gals (ToGals) were identified in the Golden pompano (Trachinotus ovatus), and their conserved domains, motifs, and collinearity relationships were analyzed. The expression of ToGals was regulated following infection to Cryptocaryon irritans and Streptococcus agalactiae, indicating that ToGals participate in immune responses against microbial pathogens. Further analysis was conducted on one important member, Galectin-3, subcellular localization showing that ToGal-3like protein is expressed both in the nucleus and cytoplasm. Recombinant protein obtained through prokaryotic expression showed that rToGal-3like can agglutinate red blood cells of rabbit, carp and golden pompano and also agglutinate and kill Staphylococcus aureus, Bacillus subtilis, Vibrio vulnificus, S. agalactiae, Pseudomonas aeruginosa, and Aeromonas hydrophila. This study lays the foundation for further research on the immune roles of Gals in teleosts.
The impact of global falsified medicines regulation on healthcare stakeholders in the legitimate pharmaceutical supply chain: a systematic review
Authors: Melia Ellen , English Aislinn , Naughton Bernard D.
Published: July 2024

Background

Falsified medicines and their international regulation impacts all healthcare sectors and their actors. These regulations aim to strengthen and protect the global pharmaceutical supply chain against falsified medicines. However, an evaluation of the impacts of these regulations on key stakeholders within the legitimate supply chain have not been explored.

Objective

This research aimed to evaluate both the positive and negative impacts of falsified medicines regulation on key stakeholders within the global pharmacy sector including including manufacturers, wholesalers, hospital pharmacies, community pharmacy and patients.

Design

This research consists of a systematic review and thematic analysis concerning falsified medicines regulation and the subsequent impacts of existing global regulations on healthcare. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and checklist were utilized for reporting in this systematic review.

Data sources and methods

A search of three databases, Embase, ProQuest and PubMed, was undertaken to determine studies applicable to the research question. The Mixed Methods Appraisal Tool (MMAT) was used to assess methodological quality and risk of bias for all included studies.

Results

From the initial 657 studies, a final set of 13 relevant studies were identified. The most frequently reported falsified medicines regulation was the Falsified Medicines Directive (FMD) [n = 11]. The impact of falsified medicines regulation in the literature related to four areas: (1) Financial, (2) Social, (3) Organizational, and (4) Pharmacy Practice. These common themes across the included studies frequently relate to challenges and/or concerns associated with falsified medicines regulation implementation as well as both the logistics and practicality of incorporating falsified medicines regulations into daily operations.

Conclusion

Implementation and enforcement of falsified medicines regulation does not yet appear to categorically fulfill the primary aim of the regulations, to strengthen the drug supply chain. However, in recent years, such regulations have challenged the legitimate pharmaceutical supply change actors as they attempt to successfully implement these regulations. Studies mainly detail the negative impacts of regulation during the implementation phase but with the overall benefit pertaining to the prioritization and enhancement of patient care and safety within the healthcare sector.
Mini review on collagens in normal skin and pathological scars: current understanding and future perspective
Authors: Zhou Claire Jing , Guo Yuan
Published: July 2024

Pathological scar tissues are characterized by the presence of overabundant collagens whose structure and organization are also different from those in unwounded skin. This causes scar tissues to lose some functions performed by normal skin, and currently, there are no effective measures to prevent scar formation. Inflammation has been shown to modulate fibroblast proliferation, differentiation, and function, hence collagen production and organization. In this minireview, we provide an overview of the current understanding of collagen, specifically collagen type I and III which are main collagens in skin, structure and fibre formation and highlight their differences between normal skin and pathological scars. We discuss the role that cytokines play in modulating fibroblast function. We also identify some potential research directions which could help to further our understanding of the complex and dynamic wound healing and scar formation process.
The role of tRNA identity elements in aminoacyl-tRNA editing
Authors: Cruz Edwin , Vargas-Rodriguez Oscar
Published: July 2024

The rules of the genetic code are implemented by the unique features that define the amino acid identity of each transfer RNA (tRNA). These features, known as “identity elements,” mark tRNAs for recognition by aminoacyl-tRNA synthetases (ARSs), the enzymes responsible for ligating amino acids to tRNAs. While tRNA identity elements enable stringent substrate selectivity of ARSs, these enzymes are prone to errors during amino acid selection, leading to the synthesis of incorrect aminoacyl-tRNAs that jeopardize the fidelity of protein synthesis. Many error-prone ARSs have evolved specialized domains that hydrolyze incorrectly synthesized aminoacyl-tRNAs. These domains, known as editing domains, also exist as free-standing enzymes and, together with ARSs, safeguard protein synthesis fidelity. Here, we discuss how the same identity elements that define tRNA aminoacylation play an integral role in aminoacyl-tRNA editing, synergistically ensuring the correct translation of genetic information into proteins. Moreover, we review the distinct strategies of tRNA selection used by editing enzymes and ARSs to avoid undesired hydrolysis of correctly aminoacylated tRNAs.
Hippocampal formation-inspired global self-localization: quick recovery from the kidnapped robot problem from an egocentric perspective
Authors: Nakashima Takeshi , Otake Shunsuke , Taniguchi Akira , Maeyama Katsuyoshi , El Hafi Lotfi , Taniguchi Tadahiro , Yamakawa Hiroshi
Published: July 2024

It remains difficult for mobile robots to continue accurate self-localization when they are suddenly teleported to a location that is different from their beliefs during navigation. Incorporating insights from neuroscience into developing a spatial cognition model for mobile robots may make it possible to acquire the ability to respond appropriately to changing situations, similar to living organisms. Recent neuroscience research has shown that during teleportation in rat navigation, neural populations of place cells in the cornu ammonis-3 region of the hippocampus, which are sparse representations of each other, switch discretely. In this study, we construct a spatial cognition model using brain reference architecture-driven development, a method for developing brain-inspired software that is functionally and structurally consistent with the brain. The spatial cognition model was realized by integrating the recurrent state—space model, a world model, with Monte Carlo localization to infer allocentric self-positions within the framework of neuro-symbol emergence in the robotics toolkit. The spatial cognition model, which models the cornu ammonis-1 and -3 regions with each latent variable, demonstrated improved self-localization performance of mobile robots during teleportation in a simulation environment. Moreover, it was confirmed that sparse neural activity could be obtained for the latent variables corresponding to cornu ammonis-3. These results suggest that spatial cognition models incorporating neuroscience insights can contribute to improving the self-localization technology for mobile robots. The project website is https://nakashimatakeshi.github.io/HF-IGL/.
Blood-based protein biomarkers during the acute ischemic stroke treatment window: a systematic review
Authors: Rahmig Jan , Chanpura Aditya , Schultz Aaliyah , Barone Frank C. , Gustafson Deborah , Baird Alison E.
Published: July 2024

Background

Rapid and accurate acute ischemic stroke (AIS) diagnosis is needed to expedite emergent thrombolytic and mechanical thrombectomy treatment. Changes in blood-based protein biomarkers during the first 24 h of AIS, the time window for treatment, could complement imaging techniques and facilitate rapid diagnosis and treatment.

Methods

We performed a systematic review according to PRISMA guidelines. MEDLINE, EMBASE, Cochrane Library, and Web of Science databases were searched for eligible studies comparing levels of blood-based protein biomarkers in AIS patients with levels in healthy controls and stroke mimics. Protein biomarkers from the following pathophysiological categories were included: neurovascular inflammation (MMP-9, TNF-alpha), endothelial integrity (VCAM-1, ICAM-1), cell migration (E-Selectin, P-Selectin, L-Selectin), markers of glial and neuronal origin (GFAP, S100, S100B, NSE), and cardiac dysfunction (BNP, NT-proBNP). The literature search was limited to English-language publications before November 7th, 2023.

Results

A total of 61 studies from 20 different countries were identified, which included in total, 4,644 AIS patients, 2,242 stroke mimics, and 2,777 controls. Studies investigating TNF-alpha, MMP-9, VCAM-1, ICAM-1, E-Selectin, L-Selectin, GFAP, NSE, and S100B showed pronounced methodological heterogeneity, making between-study comparisons difficult. However, in 80% of NT-proBNP and BNP studies, and all P-selectin studies, higher biomarker levels were observed in AIS patients compared to healthy controls and/or patients with stroke mimics.

Conclusion

None of the biomarkers included showed sufficient evidence for additional diagnostic benefit for AIS. Comprehensive standardized global multicenter studies are needed to (1) permit comparability, (2) enable valid statements about protein-based biomarkers, and (3) reflect real-world scenarios.
Screening and assessment of malnutrition in patients with liver cirrhosis
Authors: He Yumei , Wang Zhiming , Wu Shiyan , Li Lu , Li Jiazhen , Zhang Yexing , Chen Boshi , Sun Xiaobin , Sun Chao , Wu Liping
Published: July 2024

The development and advancement of malnutrition is associated not only with the progression of hepatic dysfunction, but also with cirrhosis-related complications. However, the prevalence of malnutrition reported in different studies varies widely due to differences in diagnostic methods and patient investigation settings. Therefore, we need to identify malnourished patients promptly and accurately. The purpose of this review was to compare the validity and reliability of nutritional screening tools and to select the most appropriate nutritional risk screening for patients with cirrhosis. We compared nutritional risk screening tools such as the Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) and Liver Disease Undernutrition Screening Tool (LDUST). Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) is more feasible to screen cirrhotic patients for nutritional risk, and is highly reproducible, considering the impact of sodium and water retention; so it is practical to screen cirrhotic patients via RFH-NPT for nutritional risk, subsequently, to evaluate the nutritional status of patients with nutritional risk via the Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria. L3-SMI (third lumbar-skeletal muscle index) can accurately define sarcopenia in cirrhotic patients and also be used for clinical nutritional status assessment.
VKH-like uveitis during donafenib therapy for hepatocellular carcinoma: a case report and review of the literature
Authors: Liu Rui , Liu Guina , Lu Fang
Published: July 2024

Background

The incidence of uveitis has risen with the use of targeted therapies, particularly prevalent in the administration of immune checkpoint inhibitors and MAP-kinase pathway inhibitors. We report the first case of VKH-like uveitis linked to Donafenib employed for the primary hepatocellular carcinoma, highlighting the necessity of ophthalmological follow-up in patients undergoing treatment with Donafenib.

Case presentation

A 55-year-old man developed VKH-like symptoms, including sporadic white patches, tinnitus, headache, and mild bilateral vision reduction, after 18 months of treatment with Donafenib and Sintilimab for hepatocellular carcinoma. Based on ophthalmological examinations that fundus fluorescein angiography images demonstrating multiple focal areas of pinpoint hyperfluorescence, along with pooling indicative of neurosensory detachment and disc leakage in both eyes, choroid thickening in swept-source optical coherence tomography, and “sunset-glow” fundus appearance, a tentative diagnosis of VKH-like uveitis was made. Initially, his best-corrected visual acuity (BCVA) was 20/200 in the right eye and 20/80 in the left eye. Upon discontinuing Donafenib and starting a 3-month course of oral glucocorticoids, his BCVA improved to 20/30 in the right eye and 20/40 in the left eye.

Conclusion

Targeted drugs have been commonly used for cancer treatment in recent years, but challenges of ocular side effects emerged gradually. To optimize patient outcomes, regular ophthalmological follow-ups are essential for those undergoing treatment with targeted therapies like Donafenib.
Ophiopogonin D: review of pharmacological activity
Authors: Chen Ke-qian , Wang Shu-zhi , Lei Hai-bo , Liu Xiang
Published: July 2024

Background

Ophiopogon D is an important natural organic compound in Ophiopogon japonicus, which often has significant biological activity.

Purpose

The purpose of this review is to systemically summarize and discuss the pharmacological activity and underlying mechanisms of OP-D in recent years.

Method

PubMed and Web of Science were searched with the keywords:“Ophiopogon japonicus”, “Ophiopogon D” “pharmacology”, and “pharmacokinetics”. There was no restriction on the publication year, and the last search was conducted on 1 Jan 2024.

Results

Emerging evidence suggests that OP-D possess numerous pharmacological activities, including bone protection, cardiovascular protection, immune regulation, anti-cancer, anti-atherosclerosis, anti-inflammatory and anti-NAFLD.

Conclusion

OP-D has a potential value in the prevention and treatment of many diseases. We hope that this review will contribute to therapeutic development and future studies of OP-D.
An anatomical study of the subarachnoid space surrounding the trigeminal ganglion in horses—in preparation for a controlled glycerol rhizotomy in equids
Authors: Becker Richard , Haenssgen Kati , Precht Christina , Khoma Oleksiy-Zakhar , Hlushchuk Ruslan , Koch Christoph , Kaessmeyer Sabine , de Preux Mathieu
Published: July 2024

Introduction

Equine trigeminal-mediated headshaking is a painful neuropathic disorder comparable to trigeminal neuralgia in humans. The selective destruction of pain fibers within the trigeminal ganglion, called rhizotomy, is the surgical treatment of choice for idiopathic trigeminal neuralgia refractory to medical treatment in humans. The human trigeminal ganglion is enclosed by a dural recess called the Meckel’s or trigeminal cave, in which the ganglion is surrounded by a cerebrospinal fluid (CSF)-filled subarachnoid space. During glycerol rhizotomy, glycerol is percutaneously injected in this CSF-filled space. Until now, information about the anatomy of the dural recess and the subarachnoid space surrounding the trigeminal ganglion is lacking in horses. The aim of this study was to explore if a CSF-filled subarachnoid space around the trigeminal ganglion exists in horses.

Materials and methods

Six equine cadaver heads were investigated for CSF accumulation around the ganglion with a 3 Tesla MRI. After anatomical dissection to expose the trigeminal root, a polymer-based radiopaque contrast agent was injected through the porus trigeminus into the subarachnoid space (cisternography). The exact delineation and the volume of the contrast agent accumulation were determined on subsequent micro-computed tomographic scans and segmentation. Finally, the distribution of the contrast agent within the subarachnoid space was examined histologically in three specimens.

Results

In all 12 specimens included in this study, the trigeminal ganglion was surrounded by a subarachnoid space forming a trigeminal cistern. The mean volume of the trigeminal cave in this study was 0.31 mL (±SD: 0.11 mL). Distribution of the contrast agent along the peripheral nerves (i.e., ophthalmic, maxillary and/or mandibular nerve) was observed in 7 out of 12 specimens.

Discussion/conclusion

A subarachnoid space surrounding the trigeminal ganglion exists in the horse and could be targeted for glycerol rhizotomy in horses suffering from trigeminal-mediated headshaking. However, the clinical relevance of contrast agent distribution along the peripheral nerves remains to be assessed.
Development and optimization of sampling techniques for environmental samples from African swine fever virus-contaminated surfaces with no organic contaminants
Authors: Kwon Taeyong , Gebhardt Jordan T. , Lyoo Eu Lim , Gaudreault Natasha N. , Trujillo Jessie D. , Woodworth Jason C. , Paulk Chad B. , Jones Cassandra K. , Richt Juergen A.
Published: July 2024

African swine fever (ASF) is a highly contagious diseases in domestic pigs and wild boars with up to 100% mortality. ASF virus (ASFV) is a causative agent responsible for ASF and highly resistant in environments, which creates a significant challenge for the control and eradication of the virus. Despite the geographical expansion of ASFV and international movement of products to sustain the swine production system, there is limited knowledge on the use of environmental samples to perform surveillance to prevent the introduction of ASFV into ASFV-free areas and for control of transmission in affected areas. Therefore, this study aimed to develop and optimize sampling techniques for environmental samples for ASFV detection. The stainless steel surfaces were contaminated with ASFV-infected blood, swabbed using different devices, and then processed through different techniques. The environmental samples were processed and tested using qPCR analysis. The results showed that the use of pre-moistened gauze surgical sponges, sweeping pads, and sponge sticks resulted in increased sensitivity, when compared to either dry sampling devices or Dacron swab. In particular, the combination of the sponge stick and the commercial nucleic acid preservative supported the best detection of ASFV DNA on the clean stainless steel surfaces evaluated. Pre-incubation for the short period of time and centrifugation at low speed were sufficient to provide satisfactory diagnostic sensitivity of ASFV detection using qPCR for environmental samples. Our findings contribute to the development of techniques for environmental samples for ASFV surveillance to prevent the introduction and dissemination of ASFV.
Effect of supplementation with Glycyrrhiza uralensis extract and Lactobacillus acidophilus on growth performance and intestinal health in broiler chickens
Authors: Li Ximei , Li Jiawei , Yuan Haotian , Chen Yan , Li Shuaibing , Jiang Susu , Zha Xi Yingpai , Zhang Guohua , Lu Jianxiong
Published: July 2024

Intestinal microbiota community is an important factor affecting the nutritional and health status of poultry, and its balance is crucial for improving the overall health of poultry. The study aimed to investigate the effect of dietary supplementation with Glycyrrhiza uralensis extract (GUE), Lactobacillus acidophilus (Lac) and their combination (GL) on growth performance and intestinal health in broilers in an 84-day feeding experiment. Supplementary 0.1% GUE and 4.5×107 CFU/g Lac significantly increased average daily gain (ADG), and GL (0.1% GUE and 4.5×107 CFU/g Lac) increased ADG and average daily feed intake (ADFI), and decreased feed conversion rate (FCR) in broilers aged 29 to 84 d and 1 to 84 d. Dietary GUE, Lac and GL increased the superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX) activity and decreased Malondialdehyde (MDA) content in the jejunum mucosa of broilers, and increased secretory IgA (sIgA) content in broilers at 84 d. Moreover, GUE, Lac and GL increased cecal microbial richness and diversity, and modulated microbial community composition. Both GUE and Lac reduced the harmful bacteria Epsilonbacteraeota, Helicobacter, and H. pullorum at 28 d and Proteobacteria, Escherichia, and E. coli at 84 d, while Lac and GL increased beneficial bacteria Lactobacillus and L. gallinarum at 28 d. Compared with individual supplementation, GL markedly increased the SOD activity and the sIgA content, and reduced Helicobacter and Helicobacter pullorum. In conclusion, GUE and Lactobacillus acidophilus as feed additives benefit growth performance and intestinal health, and their combined use shows an even more positive effect in broilers.
A Reliability Quantification Method for Deep Reinforcement Learning-Based Control
Authors: Yoshioka Hitoshi , Hashimoto Hirotada
Published: July 2024

Reliability quantification of deep reinforcement learning (DRL)-based control is a significant challenge for the practical application of artificial intelligence (AI) in safety-critical systems. This study proposes a method for quantifying the reliability of DRL-based control. First, an existing method, random network distillation, was applied to the reliability evaluation to clarify the issues to be solved. Second, a novel method for reliability quantification was proposed to solve these issues. The reliability is quantified using two neural networks: a reference and an evaluator. They have the same structure with the same initial parameters. The outputs of the two networks were the same before training. During training, the evaluator network parameters were updated to maximize the difference between the reference and evaluator networks for trained data. Thus, the reliability of the DRL-based control for a state can be evaluated based on the difference in output between the two networks. The proposed method was applied to DRL-based controls as an example of a simple task, and its effectiveness was demonstrated. Finally, the proposed method was applied to the problem of switching trained models depending on the state. Consequently, the performance of the DRL-based control was improved by switching the trained models according to their reliability.
Artificial Intelligence-Based System for Retinal Disease Diagnosis
Authors: Orlova Ekaterina V.
Published: July 2024

The growth in the number of people suffering from eye diseases determines the relevance of research in the field of diagnosing retinal pathologies. Artificial intelligence models and algorithms based on measurements obtained via electrophysiological methods can significantly improve and speed up the analysis of results and diagnostics. We propose an approach to designing an artificial intelligent diagnosis system (AI diagnosis system) which includes an electrophysiological complex to collect objective information and an intelligent decision support system to justify the diagnosis. The task of diagnosing retinal diseases based on a set of heterogeneous data is considered as a multi-class classification on unbalanced data. The decision support system includes two classifiers—one classifier is based on a fuzzy model and a fuzzy rule base (RB-classifier) and one uses the stochastic gradient boosting algorithm (SGB-classifier). The efficiency of algorithms in a multi-class classification on unbalanced data is assessed based on two indicators—MAUC (multi-class area under curve) and MMCC (multi-class Matthews correlation coefficient). Combining two algorithms in a decision support system provides more accurate and reliable pathology identification. The accuracy of diagnostics using the proposed AI diagnosis system is 5–8% higher than the accuracy of a system using only diagnostics based on electrophysical indicators. The AI diagnosis system differs from other systems of this class in that it is based on the processing of objective electrophysiological data and socio-demographic data about patients, as well as subjective information from the anamnesis, which ensures increased efficiency of medical decision-making. The system is tested using actual data about retinal diseases from the Russian Institute of Eye Diseases and its high efficiency is proven. Simulation experiments conducted in various scenario conditions with different combinations of factors ensured the identification of the main determinants (markers) for each diagnosis of retinal pathology.
Threshold Active Learning Approach for Physical Violence Detection on Images Obtained from Video (Frame-Level) Using Pre-Trained Deep Learning Neural Network Models
Authors: Abundez Itzel M. , Alejo Roberto , Primero Primero Francisco , Granda-Gutiérrez Everardo E. , Portillo-Rodríguez Otniel , Antonio Velázquez Juan Alberto
Published: July 2024

Public authorities and private companies have used video cameras as part of surveillance systems, and one of their objectives is the rapid detection of physically violent actions. This task is usually performed by human visual inspection, which is labor-intensive. For this reason, different deep learning models have been implemented to remove the human eye from this task, yielding positive results. One of the main problems in detecting physical violence in videos is the variety of scenarios that can exist, which leads to different models being trained on datasets, leading them to detect physical violence in only one or a few types of videos. In this work, we present an approach for physical violence detection on images obtained from video based on threshold active learning, that increases the classifier’s robustness in environments where it was not trained. The proposed approach consists of two stages: In the first stage, pre-trained neural network models are trained on initial datasets, and we use a threshold (μ) to identify those images that the classifier considers ambiguous or hard to classify. Then, they are included in the training dataset, and the model is retrained to improve its classification performance. In the second stage, we test the model with video images from other environments, and we again employ (μ) to detect ambiguous images that a human expert analyzes to determine the real class or delete the ambiguity on them. After that, the ambiguous images are added to the original training set and the classifier is retrained; this process is repeated while ambiguous images exist. The model is a hybrid neural network that uses transfer learning and a threshold μ to detect physical violence on images obtained from video files successfully. In this active learning process, the classifier can detect physical violence in different environments, where the main contribution is the method used to obtain a threshold μ (which is based on the neural network output) that allows human experts to contribute to the classification process to obtain more robust neural networks and high-quality datasets. The experimental results show the proposed approach’s effectiveness in detecting physical violence, where it is trained using an initial dataset, and new images are added to improve its robustness in diverse environments.
Response Characteristics of Harvester Bolts and the Establishment of the Strongest Response Structure’s Kinetic Model
Authors: Wang Li , Wang Guoqiang , Zhai Xujun , Tang Zhong , Wang Bangzhui , Li Pengcheng
Published: July 2024

The bolts and connections of each working part of a rice combine harvester can suffer from severe instantaneous impacts and alternating loads, and these strong impacts and loads cause instantaneous fracture and fatigue failure of the bolt face and even the loosening, detachment, and fracture of the bolt. The main vibration directions and the most complex vibration parts of the bolts and connections in the main working parts of a combine harvester under time-variable multiload excitation were obtained through the analysis of response signals in terms of time-domain and frequency–domain characteristics via a vibration response experiment. This study revealed that the random peak value of the vibrating screen is 12.5622, which is the severe impact and collision standard. For the vibrating screen, the local peak in the 4-Y direction was the main load of the destroying bolt connection (the impact reached 60.57 m/s2, 96.91 m/s2) and the vibration energy intensity in the 4-Z direction was mainly concentrated at 12.42 m/s2, which is the maximum vibration energy value in the three directions (the peak vibration value reached 109~115.68 m/s2), so the bolted connections of the vibrating screen are the most vulnerable to destruction. Therefore, a kinetic model and a microscopic response model of a vibrating screen were established via the centralized mass method to explore the kinetic response characteristics of bolted structures subjected to multiple excitation loads, thus providing a mathematical model for identifying the features of bolted connections based on static characteristics.
Peanut-Shelling Technologies and Equipment: A Review of Recent Developments
Authors: Liao Xuan , Xie Huanxiong , Hu Zhichao , Wang Jiannan , Liu Minji , An Jiyou , Wei Hai , Zhang Huijuan
Published: July 2024

Peanut is an important oil crop and cash crop, with a wide range of applications in many fields such as the food industry, light industry, and chemical industry. Mechanized shelling is a necessary part of the post-production processing of peanuts, and it is also the key to determining the quality of peanut products. Reducing shelling damage is an effective way to improve the quality and comprehensive benefits of peanut products. Consequently, it is of great significance to strengthen the research on damage reduction in mechanized peanut-shelling. China is a large peanut producer, but the research on mechanized shelling started relatively late, and the existing technology is not compatible with the high-quality shelling requirements of farmers. This paper reviews the status of mechanized peanut-shelling technology, compares the technical characteristics and equipment development of the world’s important peanut producing countries, it summarizes and proposes the suggestions to reduce loss from the aspects of varieties, agronomy, technology, and technical equipment; further deepen innovative research; and strengthen the construction of peanut-shelling socialized service systems. It is expected to provide reference for effectively reducing damage and improving quality of China’s mechanized shelling, and promoting the sustainable development of peanut shelling industry.
Interaction Mechanisms between Blades and Maize Root–Soil Composites as Affected by Key Factors: An Experimental Analysis
Authors: Liu Xuanting , Gao Peng , Qi Hongyan , Zhang Qifeng , Guo Mingzhuo , Ma Yunhai
Published: July 2024

To design a high-performance stubble-breaking device, studying the interaction mechanisms between blades and root–soil composites is urgent. A simplified experimental method was proposed to investigate the cutting process and the effects of key factors on cutting by conducting cutting experiments on remolded root–soil composites and maize root–soil composites. The results showed that the soil support force and root–soil interface force significantly impacted cutting. Higher soil compaction and root–soil interface forces helped avoid root dragging, but higher soil compaction and thicker roots led to greater resistance. The superposition and accumulation effects significantly increased the cutting force, especially when root distribution was denser; as the oblique angle and bevel angle increased, the root-cutting force and dragging distance first decreased and then increased. Compared with orthogonal cutting, the optimal angles were both 45° and reduced the root-cutting force by 60.47% and 15.12% and shortened the dragging distance by 22.33 mm and 8.76 mm, respectively. Increasing the slide-cutting angle and cutting speed helped reduce the root-cutting force and dragging distance; however, it also faced greater pure-cutting force. Consequently, the interaction mechanisms between blades and root–soil composites revealed in this study provide a design and optimization basis for stubble-breaking devices, thus promoting the development of no-till technology.
Rapid Detection of Fertilizer Information Based on Near-Infrared Spectroscopy and Machine Learning and the Design of a Detection Device
Authors: Ma Yongzheng , Wu Zhuoyuan , Cheng Yingying , Chen Shihong , Li Jianian
Published: July 2024

The online detection of fertilizer information is pivotal for precise and intelligent variable-rate fertilizer application. However, traditional methods face challenges such as the complex quantification of multiple components and sensor-induced cross-contamination. This study investigates integrating near-infrared principles with machine learning algorithms to identify fertilizer types and concentrations. We utilized near-infrared transmission spectroscopy and applied Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), and Back-Propagation Neural Network (BPNN) algorithms to analyze full spectrum data. The BPNN model, using S-G smoothing, demonstrated a superior classification performance for the nutrient ions of four fertilizer solutions: HPO42−, NH4+, H2PO4− and K+. Optimization using the competitive adaptive reweighted sampling (CARS) method yielded BPNN model RMSE values of 0.3201, 0.7160, 0.2036, and 0.0177 for HPO42−, NH4+, H2PO4−, and K+, respectively. Building on this foundation, we designed a four-channel fertilizer detection device based on the Lambert–Beer law, enabling the real-time detection of fertilizer types and concentrations. The test results confirmed the device’s robust stability, achieving 93% accuracy in identifying fertilizer types and concentrations, with RMSE values ranging from 1.0034 to 2.4947, all within ±8.0% error margin. This study addresses the practical requirements for online fertilizer detection in agricultural engineering, laying the groundwork for efficient water–fertilizer integration technology aligned with sustainable development goals.
Spectral-Frequency Conversion Derived from Hyperspectral Data Combined with Deep Learning for Estimating Chlorophyll Content in Rice
Authors: Du Lei , Luo Shanjun
Published: July 2024

As a vital pigment for photosynthesis in rice, chlorophyll content is closely correlated with growth status and photosynthetic capacity. The estimation of chlorophyll content allows for the monitoring of rice growth and facilitates precise management in the field, such as the application of fertilizers and irrigation. The advancement of hyperspectral remote sensing technology has made it possible to estimate chlorophyll content non-destructively, quickly, and effectively, offering technical support for managing and monitoring rice growth across wide areas. Although hyperspectral data have a fine spectral resolution, they also cause a large amount of information redundancy and noise. This study focuses on the issues of unstable input variables and the estimation model’s poor applicability to various periods when predicting rice chlorophyll content. By introducing the theory of harmonic analysis and the time-frequency conversion method, a deep neural network (DNN) model framework based on wavelet packet transform-first order differential-harmonic analysis (WPT-FD-HA) was proposed, which avoids the uncertainty in the calculation of spectral parameters. The accuracy of estimating rice chlorophyll content based on WPT-FD and WPT-FD-HA variables was compared at seedling, tillering, jointing, heading, grain filling, milk, and complete periods to evaluate the validity and generalizability of the suggested framework. The results demonstrated that all of the WPT-FD-HA models’ single-period validation accuracy had coefficients of determination (R2) values greater than 0.9 and RMSE values less than 1. The multi-period validation model had a root mean square error (RMSE) of 1.664 and an R2 of 0.971. Even with independent data splitting validation, the multi-period model accuracy can still achieve R2 = 0.95 and RMSE = 1.4. The WPT-FD-HA-based deep learning framework exhibited strong stability. The outcome of this study deserves to be used to monitor rice growth on a broad scale using hyperspectral data.
Evaluation of the Efficiency of Machine Learning Algorithms for Identification of Cattle Behavior Using Accelerometer and Gyroscope Data
Authors: Mladenova Tsvetelina , Valova Irena , Evstatiev Boris , Valov Nikolay , Varlyakov Ivan , Markov Tsvetan , Stoycheva Svetoslava , Mondeshka Lora , Markov Nikolay
Published: July 2024

Animal welfare is a daily concern for livestock farmers. It is known that the activity of cows characterizes their general physiological state and deviations from the normal parameters could be an indicator of different kinds of diseases and conditions. This pilot study investigated the application of machine learning for identifying the behavioral activity of cows using a collar-mounted gyroscope sensor and compared the results with the classical accelerometer approach. The sensor data were classified into three categories, describing the behavior of the animals: “standing and eating”, “standing and ruminating”, and “laying and ruminating”. Four classification algorithms were considered—random forest ensemble (RFE), decision trees (DT), support vector machines (SVM), and naïve Bayes (NB). The training relied on manually classified data with a total duration of 6 h, which were grouped into 1s, 3s, and 5s piles. The obtained results showed that the RFE and DT algorithms performed the best. When using the accelerometer data, the obtained overall accuracy reached 88%; and when using the gyroscope data, the obtained overall accuracy reached 99%. To the best of our knowledge, no other authors have previously reported such results with a gyroscope sensor, which is the main novelty of this study.
Influence of Post-Harvest Processing and Drying Techniques on Physicochemical Properties of Thai Arabica Coffee
Authors: Aung Moon Sai , Wongsakul Sirirung , Kitazawa Hiroaki , Saengrayap Rattapon
Published: July 2024

Coffee post-processing drying eliminates moisture content, reduces fungal and microbe growth, and develops unique aroma and flavor compounds. Thai coffee producers use controlled-environment drying (CED) techniques to improve the quality and cupping scores of the coffee. This research investigated how different drying methods, including sun drying (SD), controlled-environment drying at 20–30 °C, 50–55% RH, and fast drying (FD) at 30–45 °C influenced the physicochemical characteristics of coffee undergoing dry (DP), washed (WP), and honey (HP) processing. Results showed that true density, moisture content, water activity, color, caffeine, trigonelline, chlorogenic acid, caffeic acid, sucrose, and fructose in green coffee beans were significantly affected (p < 0.05) by both drying technique and post-harvest processing. Drying techniques and processing directly impacted the characteristics of green (GCB) and roasted coffee beans (RCB). Findings suggested a correlation between CED, SD, and FD based on the physicochemical and biochemical properties and sugar contents of both green and roasted coffee beans.
Modification and Performance Evaluation of a Biomass Pelleting Machine
Authors: Jekayinfa Simeon Olatayo , Ola Folorunso Adegboyega , Akande Fatai Bukola , Adesokan Mutairu Abiola , Abdulsalam Ibrahim Akinola
Published: July 2024

The use of biomass as a source of energy has been identified to be energy intensive, involving high handling costs. However, pelletization reduces the bulk density of biomass, thereby reducing the handling costs and enhancing ease of use. This study modified and evaluated an existing hand-operated fish feed pelleting machine. The parts of the machine that were redesigned were the hopper and the power transmission unit. Corncob was used to evaluate the modified machine using the die hole diameter (5, 6 and 7 mm) and the binder quantity (0, 2.5 and 5 wt%) as factors. The average results obtained for machine efficiency, throughput, pellet length and bulk density were 58.83%, 4.24 kg/h, 15.51 mm and 0.160 g/cm3, respectively. The die hole diameter had a significant effect on the pellet length only. The binder quantity had a significant effect on machine efficiency, throughput and pellet length. Machine efficiency and throughput decreased as the quantity of binder increased, and the pellet length increased with the increasing quantity of binder.
X-ray Microtomography Analysis of Integrated Crop–Livestock Production’s Impact on Soil Pore Architecture
Authors: Gaspareto José V. , Pires Luiz F.
Published: July 2024

Integrated crop–livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze the soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of the soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no tillage (NT) with ryegrass as the cover crop (C) and silage (S) were studied. The micromorphological properties of the soil were analyzed via X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8 × 103), volume (c. 26%), and the number of pores (c. 32%) in a rod-like shape. However, the MT(S), NT(C), and NT(S) systems showed greater tortuosity (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivity (c. 8.3 × 103, c. 6.9 × 103, and c. 6.2 × 103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves the soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.
Biological Control Using Ants: Current Status, Opportunities, and Limitations
Authors: Lutinski Junir Antônio , Lutinski Cladis Juliana , Ortiz Alécio , Zembruski Fernanda Staub , Ripke Marcia Orth , Garcia Flávio Roberto Mello
Published: July 2024

Interest in biological pest control using ants in agroforestry and agricultural systems has increased in recent decades due to the diversity and abundance of these insects in different ecosystems. Biological pest control has emerged as an alternative to reduce the impact of production on agroecosystems, and ants play a crucial role in this context. Therefore, this study aimed, based on an extensive and rigorous literature review, to describe the potential of ants as biological control agents, as well as the pests that have been targeted by this control. The search was carried out between July and November 2023, using databases such as Lilacs, Scielo, and Google Scholar. The selected descriptors were “Predatory ants”, “Natural enemy ants”, and “Chemical defense ants”, used in Portuguese, English, and Spanish. These terms were used in isolation and with the Boolean operator “AND”. A total of 47 articles published between 1976 and 2023 were reviewed. The results showed that 34 genera and 70 species of ants have potential for use in biological control. Among the most notable genera are Camponotus, Crematogaster, Oecophylla, Pheidole, Solenopsis, and Wasmannia. Their role as biological control agents can be complementary, contributing to the maintenance and balance of agroecosystems through pest predation, which can reach 100% efficiency. The predatory potential of ants has been verified, with an emphasis on biological control against invertebrate pests of cultivated plants. Among the pests potentially controlled by ants are mites, coleopterans, fruit flies, bedbugs, lepidopterans, thrips, mollusks, and other ants. The scientific literature already contains robust evidence proving the potential of ants as biological control agents, especially for invertebrate pests.