MDPI - Publisher of Open Access Journals

Current Oncology
Malignant Pleural Effusion: Diagnosis and Treatment—Up-to-Date Perspective
Animals
Defining the Role of IgE Against Cross-Reactive Carbohydrates in Dogs
International Journal of Molecular Sciences
The Role of Macrophages in Hepatocellular Carcinoma and Their Therapeutic Potential
Atoms
Gordon Decomposition of the Magnetizability of a Dirac One-Electron Atom in an Arbitrary Discrete Energy State
Geosciences
Environmental Effects of a Hellenistic Earthquake, Helike, Greece

Recent Articles

13 pages, 1172 KiB

Open AccessArticle

In Silico Identification of Banana High-Confidence MicroRNA Binding Sites Targeting Banana Streak GF Virus

by Muhammad Aleem Ashraf, Babar Ali, Maryam Fareed, Ahsan Sardar, Eisha Saeed, Samaa Islam, Shaher Bano and Naitong Yu

Appl. Microbiol. 2025, 5(1), 13; https://doi.org/10.3390/applmicrobiol5010013 (registering DOI) - 27 Jan 2025

Abstract

Banana streak GF virus (BSGFV) is the extremely dangerous monopartite badnavirus (genus, Badnavirus; family, Caulimoviridae) of banana (Musa acuminata AAA Group) that imposes a serious threat to global banana production. The BSGFV causes a devastating pandemic in banana crops, transmitted by deadly insect pest mealybug vectors and replicated through an RNA intermediate. The BSGFV is a reverse-transcribing DNA virus that has a monopartite open circular double-stranded DNA (dsDNA) genome with a length of 7325 bp. RNA interference (RNAi) is a natural mechanism that has revolutionized the target gene regulation of various organisms to combat virus infection. The current study aims to locate the potential target binding sites of banana-encoded microRNAs (mac-miRNAs) on the BSGFV-dsDNA-encoded mRNAs based on three algorithms, RNA22, RNAhybrid and TAPIR. Mature banana (2n = 3x = 33) miRNAs (n = 32) were selected and hybridized to the BSGFV genome (MN296502). Among the 32 targeted mature locus-derived mac-miRNAs investigated, two banana mac-miRNA homologs (mac-miR162a and mac-miR172b) were identified as promising naturally occurring biomolecules to have binding affinity at nucleotide positions 5502 and 9 of the BSGFV genome. The in silico banana-genome-encoded mac-miRNA/mbg-miRNA-regulatory network was developed with the BSGFV—ORFs using Circos software (version 0.69-9) to identify potential therapeutic target proteins. Therefore, the current work provides useful biological material and opens a new range of opportunities for generating BSGFV-resistant banana plants through the genetic manipulation of the selected miRNAs. Full article

(This article belongs to the Special Issue Microbial Evolutionary Genomics and Bioinformatics)

20 pages, 2081 KiB

Open AccessReview

Opportunities and Challenges in Harnessing Digital Technology for Effective Teaching and Learning

by Zhongzhou Chen and Chandralekha Singh

Trends High. Educ. 2025, 4(1), 6; https://doi.org/10.3390/higheredu4010006 - 27 Jan 2025

Abstract

Most of today’s educators are in no shortage of digital and online learning technologies available at their fingertips, ranging from Learning Management Systems such as Canvas, Blackboard, or Moodle, online meeting tools, online homework, and tutoring systems, exam proctoring platforms, computer simulations, and even virtual reality/augmented reality technologies. Furthermore, with the rapid development and wide availability of generative artificial intelligence (GenAI) services such as ChatGPT, we are just at the beginning of harnessing their potential to transform higher education. Yet, facing the large number of available options provided by cutting-edge technology, an imminent question on the mind of most educators is the following: how should I choose the technologies and integrate them into my teaching process so that they would best support student learning? We contemplate over these types of important and timely questions and share our reflections on evidence-based approaches to harnessing digital learning tools using a Self-regulated Engaged Learning Framework we have employed in our research in physics education that can be valuable for educators in other disciplines. Full article

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16 pages, 405 KiB

Open AccessArticle

Open-Source FPGA Implementation of an I3C Controller

by Jorge André Gastmaier Marques, Sergiu Arpadi and Maximiliam Luppe

Chips 2025, 4(1), 6; https://doi.org/10.3390/chips4010006 - 27 Jan 2025

Abstract

Multiple serial interfaces have emerged to meet system requirements across devices, ranging from slower-speed buses, such as I²C, to high throughput serial interfaces, like JESD204. To address the need for a medium-speed protocol and to resolve I²C shortcomings, the MIPI Alliance developed the I3C specification, which is a royalty-free next-generation version of I²C with new features and backward compatibility. Since the MIPI Alliance’s I3C work only includes the specifications, it depends on third-party vendors to develop their own cores according to the specifications. Only a few processing systems contain I3C Controllers, each with its own partial implementation of the specification, and there are no open-source controller cores. Thus, this work presents an open-source I3C Controller HDL framework that operates at the maximum specified SDR frequency and is compatible with the Linux kernel. Both the core and Linux kernel drivers are available under permissive open-source licenses. The solution is mostly aimed at development boards with Xilinx Zynq and Intel Cyclone SoC; nevertheless, the structure of the project allows it to be ported to other vendors and carriers. Full article

14 pages, 3042 KiB

Open AccessArticle

Patient-Reported Perception of Exercise and Receptiveness to Mobile Technology in Cancer Survivors Living in Rural and Remote Areas

by Myriam Filion, Saunjoo L. Yoon, Becky Franks, Dea’vion Godfrey, Carina McClean, Jackson Bespalec, Erin Maslowski, Diana J. Wilkie and Anna L. Schwartz

Curr. Oncol. 2025, 32(2), 67; https://doi.org/10.3390/curroncol32020067 - 27 Jan 2025

Abstract

Purpose: Cancer survivors in rural and underserved areas face barriers such as limited access to oncology exercise programs and limited facilities, contributing to health inequities in cancer survivorship. This study explored cancer survivors’ thoughts on exercise and mobile technology for exercising with a mobile application (app) during and after treatment in rural and remote areas. Methods: Three online focus groups were conducted in February 2024 using semi-structured interviews with 12 open-ended questions. Eligible participants were adult cancer survivors or caregivers living in medically underserved areas, English-speaking, consented to being audiotaped, and attended one 60-min group interview. The discussions were transcribed verbatim and analyzed via a content analysis approach with consensus. Results: Fifteen participants attended from four States. None of the participants were advised to exercise; availability of exercise resources depended on geographic location and a cancer-specific exercise app was desired. They understood the benefits of exercise after diagnosis but expressed a need for more guidance during treatment. Geographic location shaped their activities, with most engaging in daily physical tasks rather than structured exercise. Most participants were receptive to using an exercise app to manage fatigue. Suggested key features to exercise with an app included live trainers, exercise checklists, visual benchmarks, and programs tailored to different fitness levels. Conclusions: These results emphasize the need for personalized resources, guidance, and on-demand accessibility to an exercise oncology app. A cancer-specific exercise mobile app will mitigate health inequities for cancer survivors residing in rural and remote areas. Full article

(This article belongs to the Section Oncology Nursing)

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12 pages, 1727 KiB

Open AccessArticle

Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization

by Dongok Kim, Chulkyun Ahn and Jong Hyo Kim

Tomography 2025, 11(2), 13; https://doi.org/10.3390/tomography11020013 - 27 Jan 2025

Abstract

Background/Objectives: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thickness has an adverse effect on the accuracy of the pulmonary nodule volumetry. Methods: We propose a deep learning based super-resolution technique to generate thin-slice CT images from thick-slice CT images. Analysis of the lung nodule volumetry and categorization accuracy was performed using commercially available AI-based lung cancer screening software. Results: The accuracy of pulmonary nodule categorization increased from 72.7 percent to 94.5 percent when thick-slice CT images were converted to generated-thin-slice CT images. Conclusions: Applying the super-resolution-based slice generation on thick-slice CT images prior to automatic nodule evaluation significantly increases the accuracy of pulmonary nodule volumetry and corresponding pulmonary nodule category. Full article

(This article belongs to the Section Artificial Intelligence in Medical Imaging)

24 pages, 987 KiB

Open AccessArticle

Pilot Data for a New Headphone-Based Assessment of Absolute Localization in the Assessment of Auditory Processing Disorder (APD)

by Jack Hargreaves, Julia Sarant, Bryn Douglas and Harvey Dillon

Audiol. Res. 2025, 15(1), 12; https://doi.org/10.3390/audiolres15010012 - 27 Jan 2025

Abstract

Background/Objectives: Localization deficit is often said to be a symptom of Auditory Processing Disorder (APD). However, no clinically viable assessment of localization ability has been developed to date. The current study presents pilot data for a new assessment of absolute auditory localization using headphones. Methods: Speech phrases encoded with non-individualized head-related transfer functions (HRTF) using real-time digital processing were presented to two cohorts of participants with normal hearing. Variations in the simulated environment (anechoic and reverberant) and signal to noise ratio (SNR) were made to assess each of these factors’ influences on localization performance. Experiment 1 assessed 30 young adults aged 21–33 years old and Experiment 2 assessed 28 young adults aged 21–29 years old. All participants had hearing thresholds better than 20 dB HL. Results: Participants performed the localization task with a moderate degree of accuracy (Experiment 1: Mean RMS error = 25.9°; Experiment 2: Mean RMS error 27.2°). Front–back errors (FBEs) were evident, contributing to an average RMS error that was notably elevated when compared to similar free-field tasks. There was no statistically significant influence from the simulated environment or SNR on performance. Conclusions: An exploration of test viability in the pediatric and APD-positive populations is warranted alongside further correction for FBEs; however, the potential for future clinical implementation of this measure of absolute auditory localization is encouraging. Full article

24 pages, 5859 KiB

Open AccessArticle

In Vivo Anti-Inflammatory and Wound Healing Activity of Extracts and Micro-Aerogels of Bursera microphylla A. Gray

by Juan Ramón Cañez-Orozco, Juan José Acevedo-Fernández, Julio César López-Romero, Victor Alonso Reyna-Urrutia, Ramón Enrique Robles-Zepeda and Heriberto Torres-Moreno

Stresses 2025, 5(1), 10; https://doi.org/10.3390/stresses5010010 - 27 Jan 2025

Abstract

Chitosan micro-aerogels (CsM) are an innovative strategy for the controlled release of healing and anti-inflammatory ingredients. Although Bursera microphylla has anti-inflammatory activity in vitro, its in vivo effect is unknown. This study evaluated the anti-inflammatory and wound-healing effects of extracts and micro-aerogels of B. microphylla. Chitosan micro-aerogels loaded with 0.5% (CsMBT-0.5) and 1% (CsMBT-1) B. microphylla ethanol extract were characterized by SEM, FTIR, TGA, and moisture absorption. Cytotoxicity was assessed by MTT assay, and anti-inflammatory effects in vitro were evaluated by NO quantification. Anti-inflammatory and wound-healing effects in vivo were tested in CD1 mice. The microparticles measured 135–180 μm. FTIR showed that the extract’s compounds remained unchanged during synthesis. TGA indicated degradation of the micro-aerogels between 250–350 °C and reduced moisture absorption when loaded with the extract. The extract inhibited NO release by 36% at 6.25 μg/mL and CsMBT-1 by 46% at 100 μg/mL (p < 0.05). The extract and CsMBT-0.5 in mice reduced ear swelling by 70% at 30 mg/mL (p < 0.0001). The extract reduced wound size by day 9, while CsMBT-0.5 accelerated wound closure from day 1 (p < 0.05), indicating that chitosan micro-aerogels were a promising anti-inflammatory and wound-healing treatment option. Full article

(This article belongs to the Collection Feature Papers in Human and Animal Stresses)

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17 pages, 1480 KiB

Open AccessReview

Pictorial Review of Paediatric Limp

by Shashank Chapala, Sahana Giliyaru, Rajesh Botchu, Suvinay Saxena, Karthikeyan P. Iyengar and Muthusamy Chandramohan

Pediatr. Rep. 2025, 17(1), 14; https://doi.org/10.3390/pediatric17010014 - 27 Jan 2025

Abstract

A limp is an abnormal, uneven or laboured gait typically resulting from pain, weakness, or structural deformity involving the hip, lower limb, spine or abdominopelvic abnormalities. Limps in children are common and have diverse causes that can be benign to life-threatening including trauma, congenital malformations, and neoplastic diseases. Diagnosis involves identifying gait abnormality thoroughly examining history and physical exam, assessing tenderness and range of motion, and completing targeted lab and radiographic studies. We present an imaging review of various usual and unusual causes of limp in different age groups such as in toddlers (1–3 years), children (4–10 years), and adolescents (11–16 years) with a comprehensive literature review. Full article

18 pages, 335 KiB

Open AccessEntry

Poverty, Allostasis, and Chronic Health Conditions: Health Disparities Across the Lifespan

by Val Livingston, Breshell Jackson-Nevels, Erica Brown-Meredith, Alexis Campbell, Brandon D. Mitchell, Candace Riddley, Alicia O. Tetteh, Velur Vedvikash Reddy and Aquila Williams

Encyclopedia 2025, 5(1), 16; https://doi.org/10.3390/encyclopedia5010016 - 27 Jan 2025

Definition

Definition: Poverty is an important social determinant of health disparities across the lifespan. Poverty also influences other life challenges such as pecuniary instability, food insecurity, housing instability, educational inequality, and limited career mobility. According to the World Bank, more than 700 million people worldwide live in global poverty, surviving on less than USD 2.15 a day. Poverty may also be viewed as a state of deprivation that limits access to resources that address basic needs (i.e., food, water, shelter, clothing, health), limiting an individual’s opportunity to participate optimally in society. A large body of research has identified a positive relationship between poverty and chronic health concerns such as heart disease, diabetes, high cholesterol, kidney problems, liver problems, cancer, and hypertension. This entry examines health disparities associated with economic status, discrimination, racism, stress, age, race/ethnicity, gender, gender identity, and nationality from a social justice perspective. Full article

(This article belongs to the Section Behavioral Sciences)

26 pages, 2753 KiB

Open AccessArticle

Duplication of a Type-P5B-ATPase in Laverania and Avian Malaria Parasites and Implications About the Evolution of Plasmodium

by Mark F. Wiser

Parasitologia 2025, 5(1), 6; https://doi.org/10.3390/parasitologia5010006 - 27 Jan 2025

Abstract

Two related P-type ATPases, designated as ATPase1 and ATPase3, were identified in Plasmodium falciparum. These two ATPases exhibit very similar gene and protein structures and are most similar to P5B-ATPases. There are some differences in the predicted substrate-binding sites of ATPase1 and ATPase3 that suggest different functions for these two ATPases. Orthologues of ATPase3 were identified in all Plasmodium species, including the related Hepatocystis and Haemoproteus. ATPase3 orthologues could also be identified in all apicomplexan species, but no clear orthologues were identified outside of the Apicomplexa. In contrast, ATPase1 orthologues were only found in the Laverania, avian Plasmodium species, and Haemoproteus. ATPase1 likely arose from a duplication of the ATPase3 gene early in the evolution of malaria parasites. These results support a model in which early malaria parasites split into two clades. One clade consists of mammalian malaria parasites and Hepatocystis but excludes P. falciparum and related Laverania. The other clade includes Haemoproteus, avian Plasmodium species, and Laverania. This contrasts to recent models that suggest all mammalian malaria parasites form a monophyletic group, and all avian malaria parasites form a separate monophyletic group. ATPase1 may be a useful taxonomic/phylogenetic character for the phylogeny of Haemosporidia. Full article

11 pages, 204 KiB

Open AccessArticle

Promoting Self-Efficacy of Nursing Students in Academic Integrity Through a Digital Serious Game: A Pre/Post-Test Study

by Laura Creighton, Christine Brown Wilson, Tara Anderson, Conor Hamilton, Guy Curtis, Christine Slade and Gary Mitchell

Nurs. Rep. 2025, 15(2), 45; https://doi.org/10.3390/nursrep15020045 - 27 Jan 2025

Abstract

Background: Academic integrity is an important component of nursing education, bridging academic ethics with professional practice. This study evaluated the effectiveness of a co-designed Academic Integrity digital serious game in improving nursing students’ self-efficacy related to academic integrity, academic offenses, professionalism, and artificial intelligence use. Methods: A pre-test/post-test design was employed, using a bespoke questionnaire to assess 303 first-year nursing students’ self-efficacy before and after playing the game. The questionnaire covered five subscales: academic integrity standards, academic offenses, professional values, feedback processes, and AI use in academic work. Results: Statistically significant improvements were observed across all subscales following the intervention, indicating enhanced self-efficacy in understanding and applying academic integrity principles, recognizing academic offenses, demonstrating professional behaviors, utilizing feedback, and appropriately using AI in academic contexts. Conclusions: The Academic Integrity digital serious game has the potential to be an effective tool for enhancing nursing students’ self-efficacy in the areas of academic and professional ethics. This approach shows promise for integrating academic integrity-based education in nursing curricula and preparing students for the ethical challenges of modern healthcare practice. This study was not registered. Full article

15 pages, 4208 KiB

Open AccessSystematic Review

The Beneficial Effects of Alpha-Blockers, Antimuscarinics, Beta 3-Agonist, and PDE5-Inhibitors for Ureteral Stent-Related Discomfort: A Systematic Review and Meta-Analysis from KSER Update Series

by Young Joon Moon, Doo Yong Chung, Do Kyung Kim, Hae Do Jung, Seung Hyun Jeon, Seok Ho Kang, Sunghyun Paick and Joo Yong Lee

Medicina 2025, 61(2), 232; https://doi.org/10.3390/medicina61020232 - 27 Jan 2025

Abstract

Background and Objectives: Ureteral stents are widely used in the field of urology but can cause varying degrees of side effects. This study utilized a network meta-analysis to evaluate stent-related discomfort (SRD) in patients with alpha-blockers (alfuzosin, tamsulosin, and silodosin), antimuscarinics (solifenacin), beta 3-agonists (mirabegron), and phosphodiesterase 5-inhibitors (tadalafil) versus a placebo. Materials and Methods: Relevant randomized controlled trials (RCTs) from 2006 to 2021 were identified from electronic databases, including PubMed, EMBASE, and the Cochrane Library. The following identifiers were included to assess the urinary symptom score (USS): participants (patients with ureteral stents), interventions (patients who took medication for stent discomfort), and outcomes (comparisons of the Ureteric Stent Symptoms Questionnaire (USSQ)). We also executed an independent quality assessment using the Scottish Intercollegiate Guidelines Network (SIGN). Results: A total of 16 RCTs were identified, and they included 1865 patients. Compared with the placebo, mirabegron (mean difference (MD): −3.87; 95% confidence interval (CI): −10.6–2.35), tadalafil (MD: −4.47; 95% CI: −10.8–1.63), and silodosin (MD: −4.02; 95% CI: −12–4.01) did not show significant differences to the placebo, whereas others did. Alfuzosin, mirabegron, silodosin, solifenacin, and tadalafil were not inferior to tamsulosin in terms of the USS using Bayesian analyses. In the random effect model, P-score tests showed that solifenacin possessed the highest P-score (p = 0.8484); tamsulosin was the second highest (p = 0.7054). As a result of the rank-probability test, solifenacin was also ranked highest in terms of USS, and tamsulosin was ranked second. Conclusions: Compared with the placebo, solifenacin, tamsulosin, and alfuzosin significantly decreased the USS. In our study, solifenacin may be considered the most effective medication for SRD. Full article

(This article belongs to the Section Urology & Nephrology)

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11 pages, 288 KiB

Open AccessArticle

Should the Start of Immunosuppressive Treatment for COVID-19 Rely upon the Degree of Inflammation or the Time from Onset?

by José María Mora-Luján, Abelardo Montero, Francesc Formiga and Manuel Rubio-Rivas

Medicina 2025, 61(2), 233; https://doi.org/10.3390/medicina61020233 - 27 Jan 2025

Abstract

Background and Objectives: A COVID-19 model with a viral first-week phase and an inflammatory second phase has been proposed. It has been suggested that immunosuppressive treatment in the first week is harmful. This study aimed to analyze the potential damage of corticosteroids (CS) administered in the first week of COVID-19. Materials and Methods: This study was performed on a large cohort of consecutive COVID-19 patients admitted to Bellvitge University Hospital (Barcelona, Spain) from March 2020 to April 2021. Patients diagnosed with COVID-19 who were treated with 6 mg of dexamethasone a day for 10 days, and whose initiation of administration occurred within the first 2 weeks from symptom onset were included. We divided the cohort into the following two groups: patients for whom CS were initiated within the first 7 days after symptom onset vs. patients for whom CS were initiated between days 8 and 14. The degree of analytical inflammation (based on lymphocyte count, C-reactive protein, ferritin, lactate dehydrogenase, and D-dimer) upon admission was taken into account. The primary outcome was in-hospital mortality. Results: A total of 581 patients met the inclusion criteria. The results included, as follows: differences in age at baseline between groups (70.8 years old vs. 62.7, p < 0.001); moderate-to-severe dependency (11.9% vs. 4.2%, p = 0.003); the lymphocyte count (840 × 10⁶/L vs. 900, p = 0.033); D-dimer (400 ng/mL vs. 309, p < 0.001); and PaO₂/FiO₂ (290 vs. 311, p < 0.001). In-hospital mortality in patients who received CS in the first week of symptom onset was higher (29% vs. 12.8%, p < 0.001). The following risk factors were associated with higher in-hospital mortality: age (OR = 1.06, p < 0.001); Charlson index (OR = 1.34, p = 0.001); tachypnea > 20 bpm (OR = 2.58, p < 0.001); ≥3 high-risk criteria of inflammation (OR = 1.94, p = 0.012); and CS onset in the first week (OR = 2.17, p = 0.004). A higher PaO2/FiO2 (OR = 0.99, p < 0.001) and the use of remdesivir (OR = 0.53, p = 0.021) were identified as protective factors. However, when stratified by analytical inflammation criteria, the onset of CS in the first week did not reach statistical significance. Conclusions: The early administration of CS did not demonstrate a significant detrimental effect. These results highlight the need for a nuanced approach to CS therapy in COVID-19 that carefully weighs the risks and benefits based on individual patient characteristics and the severity of the inflammation. Full article

(This article belongs to the Section Infectious Disease)

16 pages, 5070 KiB

Open AccessArticle

AI-Driven Insect Detection, Real-Time Monitoring, and Population Forecasting in Greenhouses

by Dimitrios Kapetas, Panagiotis Christakakis, Sofia Faliagka, Nikolaos Katsoulas and Eleftheria Maria Pechlivani

AgriEngineering 2025, 7(2), 29; https://doi.org/10.3390/agriengineering7020029 - 27 Jan 2025

Abstract

Insecticide use in agriculture has significantly increased over the past decades, reaching 774 thousand metric tons in 2022. This widespread reliance on chemical insecticides has substantial economic, environmental, and human health consequences, highlighting the urgent need for sustainable pest management strategies. Early detection, insect monitoring, and population forecasting through Artificial Intelligence (AI)-based methods, can enable swift responsiveness, allowing for reduced but more effective insecticide use, mitigating traditional labor-intensive and error prone solutions. The main challenge is creating AI models that perform with speed and accuracy, enabling immediate farmer action. This study highlights the innovating potential of such an approach, focusing on the detection and prediction of black aphids under state-of-the-art Deep Learning (DL) models. A dataset of 220 sticky paper images was captured. The detection system employs a YOLOv10 DL model that achieved an accuracy of 89.1% (mAP₅₀). For insect population prediction, random forests, gradient boosting, LSTM, and the ARIMA, ARIMAX, and SARIMAX models were evaluated. The ARIMAX model performed best with a Mean Square Error (MSE) of 75.61, corresponding to an average deviation of 8.61 insects per day between predicted and actual insect counts. For the visualization of the detection results, the DL model was embedded to a mobile application. This holistic approach supports early intervention strategies and sustainable pest management while offering a scalable solution for smart-agriculture environments. Full article

(This article belongs to the Section Computer Applications and Artificial Intelligence in Agriculture)

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19 pages, 1164 KiB

Open AccessArticle

Analysis of Olive Detachment Force to Improve Olive Shaker Efficiency Through Branch Modeling

by Giuseppe Macoretta, Sofia Matilde Luglio, Federico Conforti, Michele Abruzzo, Lorenzo Gagliardi, Marco Fontanelli and Michele Raffaelli

AgriEngineering 2025, 7(2), 28; https://doi.org/10.3390/agriengineering7020028 - 27 Jan 2025

Abstract

Mechanical shaking enables efficient harvesting of olives, especially in hilly regions where automated farming is not feasible. This study delves into branch and olive detachment modeling to enhance the efficiency of a hand-held branch shaker. Shaking time, forces, accelerations, olive detachment forces and harvesting efficiency were experimentally measured. The fruit maturity index affected the force needed to detach the olive, with the highest value for olives at the C0 stage of maturity (5.93 N). No difference emerged among the tested shaking times (6 s and 12 s), neither in terms of harvest efficiency (mean 81.17%) nor in terms of damage (rate of 5.30). Therefore, the lower time was considered the most appropriate. Multibody and a Finite Element (FE) models were developed to investigate the branch response and the olive detachment condition. The stresses predicted by the FE harmonic analysis (about 8 MPa), based on the excitation force and shaking frequency measured during the tests, was in line with the measured olive detachment forces (3 to 8 MPa). The shaking frequency and the average branch acceleration in proximity to the shaker hook were 15 Hz and 50m/s², respectively. Further studies could focus on the impact of the branch shaker on operator health, particularly risks from prolonged vibration exposure. Full article

11 pages, 2142 KiB

Open AccessArticle

Rhizobium Inoculants Mitigate Corn Herbicide Residual Effects on Soybean Germination

by Ncomiwe Maphalala, Alaina Richardson, Sabrina Quevedo Sastre, Aricia Ritter Correa, Fernanda Reolon de Souza and Te Ming Tseng

Seeds 2025, 4(1), 6; https://doi.org/10.3390/seeds4010006 - 27 Jan 2025

Abstract

Corn residual herbicides offer a practical approach to comprehensive weed management throughout the growing season. However, the use of residual pre-emergence herbicides can have a negative impact on crops grown in succession or within a rotation. A study was carried out to determine the effect of the residual activity of selected corn herbicides on soybeans. The objective of the study was to evaluate the impact of these herbicides on the germination of inoculated soybean seeds. Experiments were conducted in greenhouse conditions to check the carryover effect on soybean germination. Treatment combinations of two pre-herbicides and two inoculants were applied: atrazine (2241 g ai ha⁻¹), mesotrione (105 g ai ha⁻¹), and Bradyrhizobium japonicum, Bradyrhizobium japonicum + Bacillus subtilis, respectively. A randomized complete block design evaluated six treatment combinations, including the control. All treatments, except uninoculated treatments, presented efficacy in reducing the carryover effects of corn residual herbicides on the germination of soybeans. An increase in final germination percentage was observed with Bradyrhizobium japonicum + Bacillus subtilis co-inoculation plus atrazine (24% increase) and Bradyrhizobium japonicum plus mesotrione treatment combinations (19% increase). Inoculating soybean seeds with rhizobium bacteria can reduce the carryover effects on the germination of soybean seeds grown in soil applied with atrazine and mesotrione. Full article

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Abstract

The pore structure plays a crucial role in soil systems. It affects a range of processes essential for soil ecological functions, such as the transport and retention of water and nutrients, as well as gas exchanges. The mechanical and hydrological characteristics of soil are predominantly determined by the three-dimensional pore pore-space structure. A precise analysis of pore structure can help specialists understand how these shapes impact plant root activity, leading to better cultivation practices. X-ray computed tomography provides detailed information without destroying the sample. However, manually delineating pore structure and estimating porosity are challenging tasks. This work proposes an automated method for 3D pore segmentation and characterization using convolutional neural networks with attention mechanisms. The method introduces a novel approach that combines attention at both channel and spatial levels, enhancing the segmentation and property estimation, providing valuable insights for a more detailed study of soil conditions. In experiments conducted with a private dataset, the segmentation results achieved mean Dice values of 99.10% ± 0.0004 and mean IoU values of 98.23% ± 0.0008. Additionally, in tests with Phaeozem Albic, the automatic method provided porosity estimates comparable to those obtained by a method based on integral geometry and morphology. Full article

19 pages, 22875 KiB

Open AccessArticle

A Semi-Automated Machine-Learning Tool for Assessing Building Phases: Discriminant Analysis of Mortars from the 2022 Excavation at the Sarno Bath Complex in Pompeii

by Simone Dilaria, Caterina Previato, Michele Secco and Maria Stella Busana

Heritage 2025, 8(2), 51; https://doi.org/10.3390/heritage8020051 - 27 Jan 2025

Abstract

This study presents the results of the analyses of 15 structural mortars from the building at civ. 21, level +0 of the Sarno Bath complex in Pompeii. These samples were collected during recent stratigraphic excavations (year 2022) for detailed in-laboratory compositional characterization, aiming to trace the construction phases of the originating walls. The 2022 samples were firstly analyzed via quantitative phase analysis–X-ray powder diffraction. The resulting quantitative mineralogical profiles were then processed alongside those analyzed in previous studies from level +0 structures of the Sarno Baths using multivariate statistical methods, including principal component analysis (PCA) and discriminant analysis, applied to quantitative phase analysis (QPA)–X-ray powder diffraction data (XRPD), to identify and map the construction phases. This approach enabled the correlation of the 2022 samples with previously established construction phases. Polarized-light optical microscopy and scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS) were then primarily used for validation purposes. These methods highlighted the compositional differences between samples and revealed significant features related to the use of specific raw materials. These results confirm the reliability of the semi-automated sample processing proposed in this research, adopting discriminant analysis as a machine-learning-based tool for defining construction phases in Pompeian contexts. Full article

(This article belongs to the Special Issue It's All a Matter of Time: Exploring the Past, Present and Future of Artworks through Dating, Authentication, Material Characterization, Monitoring and Restoration)

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