The work-sampling method makes it possible to gain valuable insights into what is happening in production systems. Work sampling is a process used to estimate the proportion of shift time that workers (or machines) spend on different activities (within productive work or losses). It is estimated based on enough random observations of activities over a selected period. When workplace operations do not have short cycle times or high repetition rates, the use of such a statistical technique is necessary because the labor sampling data can provide information that can be used to set standards. The work-sampling procedure is well standardized, but additional contributions are possible when evaluating the observations. In this paper, we present our contribution to improving the decision-making process based on work-sampling data. We introduce a correlation comparison of the measured hourly shares of all activities in pairs to check whether there are mutual connections or to uncover hidden connections between activities. The results allow for easier decision-making (conclusions) regarding the influence of the selected activities on the triggering of the others. With the additional calculation method, we can uncover behavioral patterns that would have been overlooked with the basic method. This leads to improved efficiency and productivity of the production system. Full article

Strain differences have been reported for motor behaviors, and only a subset of spinal cord injury (SCI) patients develop neuropathic pain, implicating genetic or genomic contribution to this condition. Here, we evaluated neuropsychiatric behaviors in A/J, BALB/c, and C57BL/6 male mice and tested genetic or genomic alterations following SCI. A/J and BALB/c naive mice showed significantly less locomotor activity and greater anxiety-like behavior than C57BL/6 mice. Although SCI elicited locomotor dysfunction, C57BL/6 and A/J mice showed the best and the worst post-traumatic recovery, respectively. Mild (m)-SCI mice showed deficits in gait dynamics. All moderate/severe SCI mice exhibited similar degrees of anxiety/depression. mSCI in BALB/c and A/J mice resulted in depression, whereas C57BL/6 mice did not exhibit depression. mSCI mice had significantly lower mechanical thresholds than their controls, indicating high cutaneous hypersensitivity. C57BL/6, but not A/J and BLAB/c mice, showed significantly lower heat thresholds than their controls. C57BL/6 mice exhibited spontaneous pain. RNAseq showed that genes in immune responses and wound healing were upregulated, although A/J mice showed the largest increase. The cell cycle and the truncated isoform of trkB genes were robustly elevated in SCI mice. Thus, different genomics are associated with post-traumatic recovery, underscoring the likely importance of genetic factors in SCI. Full article

Interlocking Inter-Module Connections (IMCs) in Modular Steel Buildings (MSBs) have garnered significant interest from researchers. Despite this, the optimisation of plate thicknesses in such structures has yet to be extensively explored in the existing literature. Therefore, this paper focuses on optimising the thickness of interlocking IMCs in MSBs by leveraging established experimental and numerical simulation methodologies. The study developed various numerical models for IMCs with plate thicknesses of 4 mm, 6 mm, 10 mm, and 12 mm, all subjected to compression loading conditions. The novelty of this study lies in its comprehensive parametric analysis, which evaluates the slip prediction model. A random forest regression model, trained using the ‘TreeBagger’ function, was also implemented to predict slip values based on applied force. Sensitivity analysis and comparisons with alternative methods underscored the reliability and applicability of the findings. The results indicate that a plate thickness of 11.03 mm is optimal for interlocking IMCs in MSBs, achieving up to 8.08% in material cost reductions while increasing deformation resistance by up to 50.75%. The ‘TreeBagger’ random forest regression significantly enhanced slip prediction accuracy by up to 7% at higher force levels. Full article

A single-inductor, low-voltage, three-step self-starting boost converter is proposed for photovoltaic (PV) energy harvesting. In order to enhance energy transfer efficiency, a variable-step Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) scheme has been devised based on a novel pulse multiplication technique. Upon overcoming the speed and accuracy limitations, the maximum power point (MPP) of the PV model is accurately tracked. In the boost converter, the average inductor current is utilized to implement closed-loop control of the MPPT loop, enhancing the stability of the tracking process and enabling efficient energy transmission. Finally, the boost converter is implemented using a 0.18 μm CMOS process, which is capable of self-starting and maintaining stable operations at input voltages ranging from 90 mV to 300 mV, achieving a peak efficiency of 93%. Full article

Cu-based ternary oxides with delafossite structure have received considerable attention in recent years for their versatility in a wide range of applications, among which is the possibility to use them in heterostructure solar cells as hole transport layers, due to their promising behavior as p-type conducting oxides. Ab initio calculations have been performed with density functional theory to investigate the role of the trivalent metal within the CuMO₂ structure and the dependence of structural and electronic properties with the species (M = Al, Ga, In, Fe, Cr, Co, Sc, Y) occupying the site of the metal. Generalized Gradient Approximation also including a Hubbard term and nonlocal Heyd–Scuseria–Enzerhof screened hybrid functional schemes were tested and their results were compared. Excellent agreement with experimental lattice parameters and measured gaps have been found. The use of hybrid functionals in HSE approximation considerably improves the bandgaps when compared with the experimental results but takes considerable time to converge, hence the need to explore less demanding methodologies. Trends in the geometry as well as in the electronic properties are discussed, and the effect of mixing different metals (CuM_xN_1−xO₂, M, N being the aforementioned elements) in the geometry and electronic properties of these delafossite materials is investigated. Due to the high cost of HSE calculations, especially when supercells are needed to model several x concentrations, statistical models and techniques based on machine learning have also been explored to predict HSE bandgap values from GGA and structural information. Full article

Implant therapy is a common treatment option in dentistry and orthopedics, but its application is often associated with an increased risk of microbial contamination of the implant surfaces that cause bone tissue impairment. This study aims to develop two silver-enriched platelet-rich plasma (PRP) multifunctional scaffolds active at the same time in preventing implant-associated infections and stimulating bone regeneration. Commercial silver lactate (L) and newly synthesized silver deoxycholate:β-Cyclodextrin (B), were studied in vitro. Initially, the antimicrobial activity of the two silver soluble forms and the PRP enriched with the two silver forms has been studied on microbial planktonic cells. At the same time, the biocompatibility of silver-enriched PRPs has been assessed by an MTT test on human primary osteoblasts (hOBs). Afterwards, an investigation was conducted to evaluate the activity of selected concentrations and forms of silver-enriched PRPs in inhibiting microbial biofilm formation and stimulating hOB differentiation. PRP-L (0.3 µg/mm²) and PRP-B (0.2 µg/mm²) counteract Staphylococcus aureus, Staphylococcus epidermidis and Candida albicans planktonic cell growth and biofilm formation, preserving hOB viability without interfering with their differentiation capability. Overall, the results obtained suggest that L- and B-enriched PRPs represent a promising preventive strategy against biofilm-related implant infections and demonstrate a new silver formulation that, together with increasing fibrin binding protecting silver in truncated cone-shaped cyclic oligosaccharides, achieved comparable inhibitory results on prokaryotic cells at a lower concentration. Full article

Emerging data indicate that lung macrophages (LM) may provide a novel biomarker to classify disease endotypes in bronchopulmonary dysplasia (BPD), a form of infant chronic lung disease, and that augmentation of the LM phenotype may be a potential therapeutic target. To contribute to this area of research, we first used Optical Redox Imaging (ORI) to characterize the responses to H₂O_2-induced oxidative stress and caffeine treatment in an in vitro model of mouse alveolar macrophages (AM). H₂O₂ caused a dose-dependent decrease in NADH and an increase in FAD-containing flavoproteins (Fp) and the redox ratio Fp/(NADH + Fp). Caffeine treatment did not affect Fp but significantly decreased NADH with doses of ≥50 µM, and 1000 µM caffeine treatment significantly increased the redox ratio and decreased the baseline level of mitochondrial ROS (reactive oxygen species). However, regardless of whether AM were pretreated with caffeine or not, the mitochondrial ROS levels increased to similar levels after H₂O₂ challenge. We then investigated the feasibility of utilizing ORI to examine macrophage redox status in tracheal aspirate (TA) samples obtained from premature infants receiving invasive ventilation. We observed significant heterogeneity in NADH, Fp, Fp/(NADH + Fp), and mitochondrial ROS of the TA macrophages. We found a possible positive correlation between gestational age and NADH and a negative correlation between mean airway pressure and NADH that provides hypotheses for future testing. Our study demonstrates that ORI is a feasible technique to characterize macrophage redox state in infant TA samples and supports further use of this method to investigate lung macrophage-mediated disease endotypes in BPD. Full article

This paper considers a resource allocation problem involving servers and mobile users (MUs) operating in a serverless edge computing (SEC)-enabled Internet of Things (IoT) network. Each MU has a fixed budget, and each server is powered by the grid and has energy harvesting (EH) capability. Our objective is to maximize the revenue of the operator that operates the said servers and the number of resources purchased by the MUs. We propose a Stackelberg game approach, where servers and MUs act as leaders and followers, respectively. We prove the existence of a Stackelberg game equilibrium and develop an iterative algorithm to determine the final game equilibrium price. Simulation results show that the proposed scheme is efficient in terms of the SEC’s profit and MU’s demand. Moreover, both MUs and SECs gain benefits from renewable energy. Full article

We established a protocol for the traditional Korean medicine examination (KME) and methodically gathered data following this protocol. Potential indicators for KME were extracted through a literature review; the first KME protocol was developed based on three rounds of expert opinions. The first KME protocol’s feasibility was confirmed, and data were collected over four years from traditional Korean medicine (KM) hospitals, focusing on healthy adults, using the final KME protocol. A literature review identified 175 potential core indicators, condensed into 73 indicators after three rounds of expert consultation. The first KME protocol, which was categorized under questionnaires and medical examinations, was developed after the third round of expert opinions. A pilot study using the first KME protocol was conducted to ensure its validity, leading to modifications resulting in the development of the final KME protocol. Over four years, data were collected from six KM hospitals, focusing on healthy adults; we obtained a dataset comprising 11,036 healthy adults. This is the first protocol incorporating core indicators of KME in a quantitative form and systematically collecting data. Our protocol holds potential merit in evaluating predisposition to diseases or predicting diseases. Full article

Camellia oleifera is a woody oil crop with the highest oil yield and the largest cultivation area in China, and C. oleifera seed oil is a high-quality edible oil recommended by the Food and Agriculture Organization of the United Nations. The objectives of this study were to investigate the variation in fruit yield traits and seed chemical compositions of wild C. oleifera in China and to identify the differences between wild C. oleifera and cultivated varieties. In this study, we collected wild C. oleifera samples from 13 sites covering the main distribution areas of wild C. oleifera to comprehensively evaluate 25 quantitative traits of wild C. oleifera fruit and seed chemical compositions and collected data of 10 quantitative traits from 434 cultivated varieties for a comparative analysis of the differences between wild and cultivars. The results showed that the coefficients of variation of the 25 quantitative traits of wild C. oleifera ranged from 2.605% to 156.641%, with an average of 38.569%. The phenotypic differentiation coefficients ranged from 25.003% to 99.911%, with an average of 77.894%. The Shannon–Wiener index (H’) ranged from 0.195 to 1.681. Based on the results of principal component analysis (PCA) and phenotypic differentiation coefficients, 10 traits differed significantly between wild C. oleifera and cultivated varieties, while the differentiation coefficients (V_ST) for fresh fruit weight, oleic acid, unsaturated fatty acids, stearic acid, and saturated fatty acids were more than 95%, of which fresh fruit weight and oleic acid content were potential domestication traits of C. oleifera. The results of this study can contribute to the efficient excavation and utilization of wild C. oleifera genetic resources for C. oleifera breeding. Full article

Vitis vinifera L. subsp. sylvestris (sylvestris) is the only native wild grapevine in Eurasia (Europe and western Asia) and is the existing ancestor of the grapevine varieties (for wine and table grape production) belonging to the subsp. sativa. In Slovenia, the prevailing opinion has been that there are no Slovenian sylvestris habitats. This study describes sylvestris in Slovenia for the first time and aims to present an overview of the locations of the wild grapevine in the country. In this project, a sample set of 89 accessions were examined using 24 SSR and 2 SSR markers plus APT3 markers to determine flower sex. The accessions were found in forests on the left bank of the Sava River in Slovenia, on the border between alluvial soils and limestone and dolomite soils, five different sites, some of which are described for the first time. The proportion of female to male accessions differed between sites. At two sites, female plants dominated; at others, the ratio was balanced. The plants’ genetic diversity and structure were compared with autochthonous and unique varieties of subsp. sativa from old vineyards in Slovenia and with rootstocks escaped from nature from abandoned vineyards. Sylvestris was clearly distinguishable from vinifera and the rootstocks. Based on genetic analyses, it was confirmed that Slovenian sylvestris is closest to the Balkan and German sylvestris groups. Meanwhile, a safety duplication of the wild grapevine accessions has been established at the University Centre of Viticulture and Enology Meranovo, Faculty of Agriculture and Life Sciences at the University of Maribor. Full article

In this paper, we construct an academic literature knowledge graph based on the relationship between documents to facilitate the storage and research of academic literature data. Keywords are an important type of node in the knowledge graph. To solve the problem that there are no keywords in some documents for several reasons in the process of knowledge graph construction, an improved keyword extraction algorithm called TP-CoGlo-TextRank is proposed by using word frequency, position, word co-occurrence frequency, and a word embedding model. By combining the word frequency and position in the document, the importance of words is distinguished. By introducing the GloVe word-embedding model, which brings the external knowledge of documents into the TextRank algorithm, and combining the internal word co-occurrence frequency in the documents, the word-adjacency relationship is transferred non-uniformly. Finally, the words with the highest scores are combined into phrases if they are adjacent in the original text. The validity of the TP-CoGlo-TextRank algorithm is verified by experiments. On this basis, the Neo4j graph database is used to store and display the academic literature knowledge graph, to provide data support for research tasks such as text clustering, automatic summarization, and question-answering systems. Full article

This paper presents a study on the effectiveness of two turbulence models, the large eddy simulation (LES) model and the k-ε turbulence model, in predicting mixing time within a ladle furnace using the computational fluid dynamics (CFD) technique. The CFD model was developed based on a downscaled water ladle from an industrial ladle. Corresponding experiments were conducted to provide insights into the flow field, which were used for the validation of CFD simulations. The correlation between the flow structure and turbulence kinetic energy in relation to mixing time was investigated. Flow field results indicated that both turbulence models aligned well with time-averaged velocity data from the experiments. However, the LES model not only offered a closer match in magnitude but also provided a more detailed representation of turbulence eddies. With respect to predicting mixing time, increased flow rates resulted in extended mixing times in both turbulence models. However, the LES model consistently projected longer mixing times due to its capability to capture a more intricate distribution of turbulence eddies. Full article

Background and objectives: The objective of this research was to analyze the correlation of the neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), soluble programmed cell death ligand 1 (sPD-L1), and Schlafen 11 (SLFN11) with the response to first-line chemotherapy in a cohort of small cell lung cancer (SCLC) patients, and to determine their potential as predictive serum biomarkers. Materials and Methods: A total of 60 SCLC patients were included. Blood samples were taken to determine CRP, sPD-L1, and SLFN11 levels. The first sampling was performed before the start of chemotherapy, the second after two cycles, and the third after four cycles of chemotherapy. Results: The patients who died earlier during the study had NLR and SLFN11 concentrations significantly higher compared to the survivor group. In the group of survivors, after two cycles of chemotherapy, the NLR ratio decreased significantly (p < 0.01), but after four cycles, the NLR ratio increased (p < 0.05). Their serum SLFN11 concentration increased significantly (p < 0.001) after two cycles of chemotherapy, but after four cycles, the level of SLFN11 fell significantly (p < 0.01). CRP, NLR, and SLFN11 were significant predictors of patient survival according to Kaplan–Meier analysis. The combination of inflammatory parameters and SLFN11 with a cutoff value above the 75th percentile of the predicted probability was associated with significantly lower overall survival in SCLC patients (average survival of 3.6 months vs. 4.8 months). Conclusion: The combination of inflammatory markers and the levels of two specific proteins (sPD-L1, SLFN11) could potentially serve as a non-invasive biomarker for predicting responses to DNA-damaging therapeutic agents in SCLC. Full article

The U.K. food system exhibits strong unsustainability indicators across multiple dimensions, both in terms of food and nutritional insecurity and in terms of adverse climate change, biodiversity, and physical resource impacts. These indices of an unsustainable and inequitable social metabolism are the result of capitalist agriculture and society in general and, more specifically, of neoliberal and austerity policies adopted with vigour since the global financial crisis. The causal, capitalistic, and, latterly, more neoliberal bases of the U.K. food system are delineated in the first section of the paper. These bases are then detailed in terms of their impacts in exacerbating climate change, biodiversity (and resource) decline and loss, and food and nutritional insecurity. The political narratives and policy frameworks available to dissemble, mitigate, or, more rarely, to address (resolve) these impacts are then delineated. It is argued that the only policy framework available that strongly integrates food security (social equity) with ecological sustainability is political agroecology and an accompanying degrowth strategy. The final section of the paper details what political agroecology and degrowth might entail for the U.K. food system. Full article

The position of the fetal head during engagement and progression in the birth canal is the primary cause of dystocic labor and arrest of progression, often due to malposition and malrotation. The authors performed an investigation on pregnant women in labor, who all underwent vaginal digital examination by obstetricians and midwives as well as intrapartum ultrasonography to collect four “geometric parameters”, measured in all the women. All parameters were measured using artificial intelligence and machine learning algorithms, called AIDA (artificial intelligence dystocia algorithm), which incorporates a human-in-the-loop approach, that is, to use AI (artificial intelligence) algorithms that prioritize the physician’s decision and explainable artificial intelligence (XAI). The AIDA was structured into five classes. After a number of “geometric parameters” were collected, the data obtained from the AIDA analysis were entered into a red, yellow, or green zone, linked to the analysis of the progress of labor. Using the AIDA analysis, we were able to identify five reference classes for patients in labor, each of which had a certain sort of birth outcome. A 100% cesarean birth prediction was made in two of these five classes. The use of artificial intelligence, through the evaluation of certain obstetric parameters in specific decision-making algorithms, allows physicians to systematically understand how the results of the algorithms can be explained. This approach can be useful in evaluating the progress of labor and predicting the labor outcome, including spontaneous, whether operative VD (vaginal delivery) should be attempted, or if ICD (intrapartum cesarean delivery) is preferable or necessary. Full article

In this study, a methodology for synthesizing oleogels based on linseed oil and emulsifiers, such as beeswax and Tween 20 and Tween 80, was developed. Linseed oil served as the main oil phase, while beeswax acted as a gelling and emulsifying agent. Tween compounds are non-ionic surfactants composed of hydrophobic and hydrophilic parts, allowing for the formation of a stable system with promising properties. Surface wetting analysis of the obtained oleogels, FT-IR spectroscopy, and determination of relative and absolute humidity over time, as well as optical microscope analysis and rheological analysis of the obtained oleogels, were conducted as part of the research. The results indicate that increasing the amount of Tween 20 decreases the hydrophilicity of the oleogel, while Tween 80 exhibits the opposite effect. Surface energy analysis suggests that a higher content of Tween 20 may lead to a reduction in the surface energy of the oleogels, which may indicate greater material stability. Changes in relative humidity and FT-IR spectral analysis confirm the influence of emulsifiers on the presence of characteristic functional groups in the structure of the oleogels. Additionally, microscopic analysis suggests that an emulsifier with a longer hydrophobic tail leads to a denser material structure. Full article

As the world embarks on a global mission to tackle climate change, reducing carbon represents a key challenge given the escalating global warming. The U.K. is among many other nations that are determined to decarbonise all sectors and strive to achieve a net zero carbon target by 2050. While much attention has been paid to improving performance and reducing carbon emissions in electrical machines, the current research landscape focuses mainly on the thermal and electromagnetic facets. Surprisingly, carbon emissions from the production stage, especially those related to raw material consumption, remain a largely unexplored area. This paper wishes to shed light on a neglected dimension by providing a comprehensive review of carbon emissions in the manufacture of electrical machines, thus contributing significantly to the wider discourse on carbon emission reduction by comparing the carbon emission values associated with various materials commonly used for the main components of these machines. A further case study is included to assess and explore the impact of material alterations on a synchronous machine, from a carbon emission perspective. A reliable material guide will provide engineers at the design stage with the critical insight needed to make informed material selection decisions, highlighting the critical role of carbon emission values beyond conventional thermal and electromagnetic considerations, achieving sustainable and environmentally conscious electrical machine design. Full article

Monthly climatology data for salinity fronts in the South Atlantic have been created from satellite SMOS sea surface salinity (SSS) measurements taken from 2011–2019, processed at the Barcelona Expert Center of Remote Sensing (BEC), and provided as high-resolution (1/20°) daily SSS data. The SSS fronts have been identified with narrow zones of enhanced horizontal gradient magnitude (GM) of SSS, computed using the Belkin–O’Reilly algorithm (BOA). The SSS gradient fields generated by the BOA have been log-transformed to facilitate feature recognition. The log-transformation of SSS gradients markedly improved the visual contrast of gradient maps, which in turn allowed new features to be revealed and previously known features to be documented with a monthly temporal resolution and a mesoscale (~100 km) spatial resolution. Monthly climatologies were generated and analyzed for large-scale open-ocean SSS fronts and for low-salinity regions maintained by the Rio de la Plata discharge, Magellan Strait outflow, Congo River discharge, and Benguela Upwelling. A 2000 km-long triangular area between Africa and Brazil was found to be filled with regular quasi-meridional mesoscale striations that form a giant ripple field with a 100 km wave length. South of the Tropical Front, within the subtropical high-salinity pool, a trans-ocean quasi-zonal narrow linear belt of meridional SSS maximum (Smax) was documented. The meridional Smax belt shifts north–south seasonally while retaining its well-defined linear morphology, which is suggestive of a yet unidentified mechanism that maintains this feature. The Subtropical Frontal Zone (STFZ) consists of two tenuously connected fronts, western and eastern. The Brazil Current Front (BCF) extends SE between 40 and 45°S to join the subantarctic front (SAF). The STFZ trends NW–SE across the South Atlantic, seemingly merging with the SAF/BCF south of Africa to form a single front between 40 and 45°S. In the SW Atlantic, the Rio de la Plata plume migrates seasonally, expanding northward in winter (June–July) from 39°S into the South Brazilian Bight, up to Cabo Frio (23°S) and beyond. The inner Plata front moves in and out seasonally. Farther south, the Magellan Strait outflow expands northward in winter (June–July) from 53°S up to 39–40°S to nearly join the Plata outflow. In the SE Atlantic, the Congo River plume spreads radially from the river mouth, with the spreading direction varying seasonally. The plume is often bordered from the south by a quasi-zonal front along 6°S. The diluted Congo River water spreads southward seasonally down to the Angola–Benguela Front at 16°S. The Benguela Upwelling is delineated by a meridional front, which extends north alongshore up to 20°S, where the low-salinity Benguela Upwelling water forms a salinity front, which is separate from the thermal Angola–Benguela Front at 16°S. The high-salinity tropical water (“Angola water”) forms a wedge between the low-salinity waters of the Congo River outflow and Benguela Upwelling. This high-salinity wedge is bordered by salinity fronts that migrate north–south seasonally. Full article

In warm climates with high levels of solar irradiation, solar shading plays a determinant role on buildings’ envelope performance, both during summer and winter conditions. In this research, an evaluation of the solar shading effect on sunny façades through IR thermography non-destructive testing was performed. Sunny and shaded areas revealed temperature differences of 7.4 °C in summer conditions and up to 1.2 °C in wintertime. Moreover, solar shading was shown to be beneficial not only for decreasing surface temperature in summertime but also for reducing convective air flow in wintertime. In addition, it was found that the prevalence of dense shadows, especially with non-reflective materials in louvres, is favorable. External Thermal Insulation Constructive Systems (ETICS) must be shadowed and the use of clear colors is recommended to reinforce homogeneity in the surface in wintertime and reduce solar absorptance in summertime. Under steady-state calculations, thermal losses can be reduced up to 30% at night in wintertime and up to 50–60% at daytime in summertime because of the shadowing. However, another important finding lied in the confirmation of the performance gap that arises between using air temperature, sol-air temperature and the actual surface temperature data, in such a way that the two former implied high levels of inaccuracy and overestimated the performance of the buildings compared to the actual behavior. Some of the main conclusions can be extrapolated to other circumstances. Full article

Prior to the recent implementation of the Mpp51Aa2 pesticidal protein (ThryvOn), transgenic cotton cultivars have historically offered no control of the cotton fleahopper (Pseudatomocelis seriatus (Reuter)). To evaluate the feeding behavior of cotton fleahoppers on ThryvOn cotton, electropenetrography (EPG) using a Giga-8 DC instrument was used to monitor the probing activity of fourth- and fifth-instar cotton fleahopper nymphs on both ThryvOn and non-ThryvOn cotton squares. Nymphs were individually placed on an excised cotton square for 8 h of EPG recording, after which resulting waveforms were classified as non-probing, cell rupturing, or ingestion. Although there were significantly more cell rupturing events per insect on ThryvOn (mean ± SEM, 14.8 ± 1.7) than on non-ThryvOn squares (mean ± SEM, 10.3 ± 1.6), there was no difference attributable to ThryvOn in the average number of ingestion events per insect. However, the average duration of ingestion events was significantly shorter on squares with ThryvOn (mean ± SEM, 509 ± 148 s) than on squares without (mean ± SEM, 914 ± 135 s). This suggests that cotton fleahoppers continued to probe despite their inability to sustain ingestion. These results provide conclusive evidence that the Mpp51Aa2 pesticidal protein affects the feeding behavior of cotton fleahopper nymphs. Full article