Improving duckling hatchability and quality by optimization of egg turning angle during incubation.

Egg turning in incubation is crucial to the development of embryos and hatching performance. We aimed to develop a high performance duck egg incubation technique by enlarging and changing egg turning angles. Increasing turning angle from 45 to 75° did not affect the embryo early mortality during the first 15 d of incubation, which ranged from 3.5 to 4.0%, but accelerated chorioallantoic membrane (CAM) development by 17 h, and significantly (P < 0.01) reduced the late mortality from 9.4 ± 0.98% to 5.31 ± 0.63%. As the result, fertile egg hatchability increased from 91.03 ± 0.97% to 94.64 ± 0.61% (P < 0.05), so was healthy duckling rate from 87.24 ± 1.17% to 92.08 ± 0.55% (P < 0.05), and duckling live weight from 60.74 ± 0.63 g to 63.15 ± 0.35 g (P < 0.05). Changing turning angle from 75°to 60°during incubation d 15 to 25 further reduced late embryo mortality to 3.88 ± 0.47 and increased hatchability to 96.58 ± 0.68%. This changing angle turning hatched ducklings exhibited the highest growth performance during rearing than those hatched by 45 and 75° egg turning. The enhanced growth rate was paralleled by upregulations of somatotropic axis genes mRNA expression levels of the hypothalamus GHRH, liver GHR and IGF-1 during embryo incubation and duckling rearing. In conclusion, a changing angle egg turning incubation technique, 75°in the first 15 d and 60°thereafter, can enhance CAM development, upregulate somatotropic axis genes expressions, and can maximally improve embryo livability, duckling hatchability and growth performance.

Absolute direction in organelle movement.

In movement analysis, correlated random walk (CRW) models often use so-called turning angles, which are measured relative to the previous movement direction. To segregate between different movement modes, hidden Markov models (HMMs) describe movements as piecewise stationary CRWs in which the distributions of turning angles and step sizes depend on the underlying state. This typically allows for the segregation of movement modes that show different movement speeds. We show that in some cases, it may be interesting to investigate absolute angles, that is, biased random walks (BRWs) instead of turning angles. In particular, while discrimination between states in the turning angle setting can only rely on movement speed, models with absolute angles can be used to discriminate between sections of different movement directions. A preprocessing algorithm is provided that enables the analysis of absolute angles in the existing R package moveHMM. In a data set of movements of cell organelles, models using not the turning angle but the absolute angle could capture interesting additional properties. Goodness-of-fit was increased for HMMs with absolute angles, and HMMs with absolute angles tended to choose a higher number of states, suggesting the existence and relevance of prominent directional changes in the present data set. These results suggest that models with absolute angles can provide important information in the analysis of movement patterns if the existence and frequency of directional changes is of biological importance.

Exploring a distinct group of analytical functions linked with Bernoulli's Lemniscate using the q-derivative.

This research presents a new group of mathematical functions connected to Bernoulli's Lemniscate, using the q-derivative. Expanding on previous studies, the research concentrates on determining coefficient approximations, the Fekete-Szego functional, Zalcman inequality, Krushkal inequality, along with the second and third Hankel determinants for this recently established collection of functions. Additionally, the study derives the Fekete-Szego inequality for the function ξ f ( ξ ) and obtains the inverse function f - 1 ( ξ ) for this specific class. This research advances our understanding in this area and suggests for further exploration.

Turning Points in Professional Commitment Development: The Case of Novice Nurses.

We investigated the development of professional commitment over time and its relation to work experiences of novice nurses. We used a longitudinal mixed-method approach based on weekly reported quantitative commitment scores and qualitative descriptions of experiences. Specifically, we examined turning points in commitment trajectories and analyzed qualitative characteristics of the turning point. To determine a turning point, we firstly computed a smoothed trajectory for each individual and defined each point beyond the 95% interval of this smoothed trajectory as exceptional. Secondly, we explored whether the commitment development changed after an exceptional point with regard to the slope-valence or commitment strength. The sample consisted of 18 novice nurses. Two third of them revealed at least one turning point, thus the professional commitment development of novice nurses was characterized by peaks and dips that were followed by changes in the commitment development. The analysis showed that turning points followed by positive commitment development typically were characterized by positive experiences. These experiences often concerned relatedness or competence. Turning points followed by a negative development were not consistent: they could be positive, negative, or ambiguous experiences. Many of the negative experiences concerned negative organizational issues. We concluded that there is not a simple relation between commitment development and positive or negative characteristics of an experience. The context and underlying meaning of the experiences should be taken into account to interpret the commitment changes.

Smartphone-Based Assessment of Mobility and Manual Dexterity in Adult People with Spinal Muscular Atrophy.

Background: More responsive, reliable, and clinically valid endpoints of disability are essential to reduce size, duration, and burden of clinical trials in adult persons with spinal muscular atrophy (aPwSMA). Objective: The aim is to investigate the feasibility of smartphone-based assessments in aPwSMA and provide evidence on the reliability and construct validity of sensor-derived measures (SDMs) of mobility and manual dexterity collected remotely in aPwSMA. Methods: Data were collected from 59 aPwSMA (23 walkers, 20 sitters and 16 non-sitters) and 30 age-matched healthy controls (HC). SDMs were extracted from five smartphone-based tests capturing mobility and manual dexterity, which were administered in-clinic and remotely in daily life for four weeks. Reliability (Intraclass Correlation Coefficients, ICC) and construct validity (ability to discriminate between HC and aPwSMA and correlations with Revised Upper Limb Module, RULM and Hammersmith Functional Scale - Expanded HFMSE) were quantified for all SDMs. Results: The smartphone-based assessments proved feasible, with 92.1% average adherence in aPwSMA. The SDMs allowed to reliably assess both mobility and dexterity (ICC > 0.75 for 15/22 SDMs). Twenty-one out of 22 SDMs significantly discriminated between HC and aPwSMA. The highest correlations with the RULM were observed for SDMs from the manual dexterity tests in both non-sitters (Typing, ρ= 0.78) and sitters (Pinching, ρ= 0.75). In walkers, the highest correlation was between mobility tests and HFMSE (5 U-Turns, ρ= 0.79). Conclusions: This exploratory study provides preliminary evidence for the usability of smartphone-based assessments of mobility and manual dexterity in aPwSMA when deployed remotely in participants' daily life. Reliability and construct validity of SDMs remotely collected in real-life was demonstrated, which is a pre-requisite for their use in longitudinal trials. Additionally, three novel smartphone-based performance outcome assessments were successfully established for aPwSMA. Upon further validation of responsiveness to interventions, this technology holds potential to increase the efficiency of clinical trials in aPwSMA.

Dependency of the drag coefficient on boundary layer stability beneath drifting sea ice in the central Arctic Ocean.

The ice-ocean drag coefficient C w and turning angle θ w are crucial parameters in ice-ocean coupled simulations, determining the transfer of momentum between the two media. These parameters are often treated as constants regardless of the static stability at the ice-ocean interface. This study investigates the variability of C w and θ w based on direct observations of thermal and kinetic energy balance. The observations were conducted beneath multiyear ice packs widely across the central Arctic during a period transitioning from ablation to refreezing, indicating significant variability of C w = 1-130 × 10-3 and θ w = - 19-1° at 5 m depth. Comparing different stations, the observations suggest a pronounced dependence of C w on the stability parameter ( µ ) resulting from mechanical and buoyant forcing. C w rapidly decays with increasing µ , indicating that the ice-to-ocean momentum transfer is enhanced for neutral or unstable conditions, while it is weakened for stable conditions. In addition, observed vertical profiles of currents revealed that | θ w | tends to be smaller for unstable and larger for stable conditions. We suggest that numerical simulations using constant values could result in an underestimate of large-scale near-surface currents during the ice growing period.

Optimization of machining parameters for turning operation of heat-treated Ti-6Al-3Mo-2Nb-2Sn-2Zr-1.5Cr alloy by Taguchi method.

TC21 alloy is a high-strength titanium alloy that has been gaining attention in various industries for its excellent combination of strength, toughness, and corrosion resistance. Given that this alloy is hard to cut material, therefore this study aims to optimize the process parameters of Turing this alloy under different conditions (i.e. as-received alloy, and heat-treated alloy). The L9 Taguchi approach-base orthogonal array is used to determine the optimum cutting parameters and the least number of experimental trials required. The achievement of this target, three different cutting parameters are used in the experimental work; each cutting parameter has three levels. The cutting speeds are chosen as 120, 100, and 80 m/min. The feed rates' values are 0.15, 0.1, and 0.05, mm/rev, and the depth of cut values are 0.6, 0.4, and 0.2 mm. After applying three steps of heat treatment (First step: is heating the sample to 920 °C for 1 h then decreasing to 820 °C also for 1 h, second step: cooling the sample to room temperature by water quenching (WQ), the third step: holding the sample at 600 °C for 4 h (Aging process)). The results revealed that the triple heat treatment led to the change in the microstructure from (α + ß) to (α + ß) with secondary α platelets (αs) formed in residual ß matrix leading to a decreased surface roughness by 56.25% and tool wear by 24.18%. The two most critical factors that affect the tool insert wear and surface roughness are the death of cut and cutting speed, which contribute 46.6% and 46.7% of the total, respectively. Feed rate, on the other hand, has the least importance, contributing 20.2% and 31.9% respectively.

Surface Topography in Cutting-Speed-Direction Ultrasonic-Assisted Turning.

Ultrasonic vibration has been employed to assist in turning, introducing intermittent machining to reduce average cutting force, minimize tool wear, and enhance machining efficiency, thereby improving surface roughness. However, achieving intermittent cutting necessitates specific conditions, with a cutting speed or feed rate falling below the critical speed associated with the ultrasonic vibration parameters. This study presents a theoretical model for surface formation in cutting-speed-direction ultrasonic-assisted turning (CUAT), covering both continuous and intermittent machining regimes. Experimental validation was conducted on C45 carbon steel and 201 stainless steel to demonstrate the applicability of the theoretical model across different materials. Digital microscope analysis revealed 3D topography consistency with the theoretical formula. Surface roughness evaluations were performed for both CUAT and CT (conventional turning) methods. The results indicated a significant reduction in roughness Ra for C45 steel samples machined with CUAT, up to 80% compared to CT at a cutting speed of 20 m/min, while only exhibiting slight fluctuations when turning 201 stainless steel. Detailed analysis and explanation of these phenomena are presented herein.

Evaluation of the Surface Integrity and Recast Layer in Electrical Discharge Turning of WC-Co Composites.

Tungsten carbide (WC) and its composites are typically associated with high hardness and high wear resistance, posing challenges in conventional machining processes like turning. To address the machining difficulties of WC-Co, electrical discharge turning (EDT) was proposed. The rotational speed in EDT is a key factor influencing the machining results; however, conflicting reports exist about its impact on the EDT process. Therefore, the effect of rotational speed on three different machining regimes, including roughing, semi-finishing, and finishing, was investigated using energy-dispersive X-ray spectroscopy (EDX), SEM, and roughness tests. Additionally, elemental mapping was applied to illustrate the element distribution on the machined surface. The results indicated that increasing the rotational speed led to a 10% to 17% decrease in the recast layer thickness and a 14% to 54% reduction in the surface roughness (Ra).

Optimization of ultra-precision CBN turning of AISI D2 using hybrid GA-RSM and Taguchi-GRA statistic tools.

Ultra-precision turning is a crucial process in the manufacturing industry as it helps to produce parts with high dimensional accuracy, surface finish, and tolerance. The process is similar to traditional turning but is carried out under special circumstances to achieve greater precision and surface finish. The process can be applied to conventional structural materials, but the demand for machining hardened steels is increasing. The optimization of ultra-precision turning of AISI D2 using cubic boron nitride (CBN) tools is a crucial aspect in the field of high-quality machining. This study aims to evaluate the performance of the process and identify the optimal parameters that result in the best quality components while using a CBN tool's ultra-precision turning of AISI D2. Ultra-precision turning process factors such as cutting speed, feed, and depth of cut were experimentally investigated to enhance the response output, such as surface roughness and cutting force components. The full factorial experimental design was used for determining the process characteristics under different conditions, and experimental results were applied to search for the optimum response of machining performance. The optimization process was done by combining the hybrid genetic algorithm-response surface methodology (GA-RSM) and the Taguchi-grey relational analysis (GRA) statistical tools. These methods are useful in situations where the relationship between the input variables and the output responses is complex and non-linear. The results showed that a hybrid GA-RSM approach, combined with Taguchi-GRA statistical analysis, can effectively find optimal process parameters, leading to the best combination of surface roughness and cutting force. In hybrid Taguchi - GRA, the optimal cutting conditions were found to be a cutting speed of 175 m/min, a feed of 0.025 mm, and a depth of cut of 0.06 mm. The findings of this study provide valuable insights for the optimization of ultra-precision CBN turning operations, contribute to the development of precision manufacturing technology, and can be used as a reference for similar machining processes.

Effect of fear of falling on turning performance among patients with chronic stroke.

BACKGROUND: Turning difficulties have been reported in stroke persons, but studies have indicated that fall history might not significantly affect turning performance. Fear of falling (FOF) is common after a fall, although it can occur in individuals without a fall history. RESEARCH QUESTION: Could FOF have an impact on turning performance among chronic stroke patients? METHODS: This cross-sectional study recruited 97 stroke persons. They were instructed to perform 180° and 360° turns, and their performance was represented by angular velocity. FOF was evaluated using the Falls Efficacy Scale-International (FES-I). Falls that occurred 12 months prior to the study assessment were recorded. RESULTS: A higher FES-I score was significantly correlated with a decline in angular velocity in all turning tasks after adjustment for demographic data. The correlation remained significant after controlling for falls history. Participants with a high level of FOF exhibited significantly slower angular velocities during all turning tasks compared with those with a low level of FOF. Participants with a moderate level of FOF had a significantly slower angular velocity than did those with a low level of FOF during the 360° turn to the paretic side only. SIGNIFICANCE: A higher level of FOF, regardless of fall history, was significantly associated with a reduced angular velocity during turning. A high level of FOF affected turning performance in all tasks. Turning performance may not be affected by fall experience. Anxiety about falling may have a greater effect on turning performance than does fall history.

Applications of turning point analysis in behavioral medicine research: A systematic scoping review.

BACKGROUND: Turning Point Analysis (TPA) is a methodological approach that allows scholars to retrospectively capture change over time by identifying instances of critical change (i.e., turning points) encountered across a given time period. While TPA has been used to examine time as a variable in health and illness experiences, the use of the method in behavioral medicine scholarship may be limited by the lack of understanding of TPA procedures and applicability. OBJECTIVE: To describe how TPA has been used and enhance its accessibility by identifying and synthesizing methods of TPA data collection and analysis. METHODS: A systematic search of electronic databases, including Academic Source Premier, Psychology and Behavioral Sciences Collection, APA PsycInfo, and ProQuest Dissertation and Theses Database, was conducted in May 2020. In July 2020, we used hand searching to identify additional articles, including forward and back tracking seminal articles on TPA. Studies were screened in duplicate. RESULTS: Of the 1184 studies screened for this review, we included 52. Studies used TPA to examine relational (k = 40), organizational (k = 6), and individual (k = 6) variables and included an analysis of either turning points (k = 28), the trajectories of change over time created by the turning points (k = 3), or both (k = 21). Turning points and trajectories were captured and analyzed using qualitative and quantitative analytic approaches, with most studies using either purely qualitative (k = 26) or mixed methods (k = 21). CONCLUSIONS: The findings of this review provide insight into the varied applications of TPA and suggest the potential value of this methodological approach in better understanding health experiences across time. By synthesizing the procedural and analytic steps to conducting a TPA, this review could also increase the accessibility and use of TPA in behavioral medicine research.

Specificity and valence of adolescents' turning point memory narratives: Relationships with depressive symptoms over time.

Although recent research suggests that, for community youth, greater specific (episodic) detail in self-relevant turning point memory narratives predicts depressive symptoms over time, no research has investigated whether the narratives' specificity similarly predicts depression. Therefore, we investigated whether recalling a specific (unique, 24-hour or less) turning point narrative predicted youth depressive symptoms concurrently and across 6 months (Study 1), and, for a subset of participants, three years (Study 2). We also examined whether the valence of the implication of the experience for self (the resolution) explained additional variance and interacted with memory specificity. For Study 1 (N = 320, M = 16.9 years, 81% female), a specific (rather than a non-specific) turning point predicted greater depressive symptoms concurrently but not longitudinally, whereas a negative resolution predicted both concurrent and longitudinal depressive symptoms. The moderation result showed that a specific turning point predicted escalating depressive symptoms across six months when the resolution was negative. Study 2 (N = 68) additionally showed that a specific turning point predicted increased depressive symptoms three years later. These findings contrast with research suggesting that specific memories are related to better mental health and highlight the complexity of the role of memory in emerging youth depression.

Facing the challenge of NDVI dataset consistency for improved characterization of vegetation response to climate variability.

Non-linear trend detection in Earth observation time series has become a standard method to characterize changes in terrestrial ecosystems. However, results are largely dependent on the quality and consistency of the input data, and only few studies have addressed the impact of data artifacts on the interpretation of detected abrupt changes. Here we study non-linear dynamics and turning points (TPs) of temperate grasslands in East Eurasia using two independent state-of-the-art satellite NDVI datasets (CGLS v3 and MODIS C6) and explore the impact of water availability on observed vegetation changes during 2001-2019. By applying the Break For Additive Season and Trend (BFAST01) method, we conducted a classification typology based on vegetation dynamics which was spatially consistent between the datasets for 40.86 % (459,669 km2) of the study area. When considering also the timing of the TPs, 27.09 % of the pixels showed consistent results between datasets, suggesting that careful interpretation was needed for most of the areas of detected vegetation dynamics when applying BFAST to a single dataset. Notably, for these areas showing identical typology we found that interrupted decreases in vegetation productivity were dominant in the transition zone between desert and steppes. Here, a strong link with changes in water availability was found for >80 % of the area, indicating that increasing drought stress had regulated vegetation productivity in recent years. This study shows the necessity of a cautious interpretation of the results when conducting advanced characterization of vegetation response to climate variability, but at the same time also the opportunities of going beyond the use of single dataset in advanced time-series approaches to better understanding dryland vegetation dynamics for improved anthropogenic interventions to combat vegetation productivity decrease.

Intelligent Vehicle Path Planning Based on Optimized A* Algorithm.

With the rapid development of the intelligent driving technology, achieving accurate path planning for unmanned vehicles has become increasingly crucial. However, path planning algorithms face challenges when dealing with complex and ever-changing road conditions. In this paper, aiming at improving the accuracy and robustness of the generated path, a global programming algorithm based on optimization is proposed, while maintaining the efficiency of the traditional A* algorithm. Firstly, turning penalty function and obstacle raster coefficient are integrated into the search cost function to increase the adaptability and directionality of the search path to the map. Secondly, an efficient search strategy is proposed to solve the problem that trajectories will pass through sparse obstacles while reducing spatial complexity. Thirdly, a redundant node elimination strategy based on discrete smoothing optimization effectively reduces the total length of control points and paths, and greatly reduces the difficulty of subsequent trajectory optimization. Finally, the simulation results, based on real map rasterization, highlight the advanced performance of the path planning and the comparison among the baselines and the proposed strategy showcases that the optimized A* algorithm significantly enhances the security and rationality of the planned path. Notably, it reduces the number of traversed nodes by 84%, the total turning angle by 39%, and shortens the overall path length to a certain extent.

Bi-layer cBN-based composites reinforced with oxide and non-oxide microfibers of refractory compounds.

Research into new composites utilizing cubic boron nitride (PcBN) shows promise for enhancing cutting tool performance. The unique properties of these materials stem from the addition of microfibers made of refractory compounds to their structure. This study looks at developing two-layer composites based on cBN group BL, reinforced with SiCw and Al2O3w microfibers. The goal is to improve tool stability when cutting hardened steels with impact loads. PcBN composite samples were made by sintering a mixture of cBN powder with bundles and microfibers under 7.7 GPa pressure. Bond material selection was based on analyzing the relationship between Poisson's ratio (η) and plasticity parameter (G/B). The density, Young's modulus, Poisson's ratio, and hardness of the composites were determined, and the microstructure of samples with TiCN bond was studied. Tool-life tests were conducted on two-layer cutting inserts made of PcBN reinforced with SiCw and Al2O3w microfibers during the machining of hardened KhVG steel (HRC 55) under impact loads at cutting speeds of 100 and 200 m/min.

Frontal and parietal cortices activation during walking is repeatable in older adults based on fNIRS.

Purpose: This study aimed to explore the test-retest reliability of fNIRS in measuring frontal and parietal cortices activation during straight walking and turning walking in older adults, in order to provide a theoretical foundation for selecting assessment tools for clinical research on motor control and some diseases such as Parkinson's disease in older adults. Methods: 18 healthy older participants (69.1 ± 0.7 years) were included in this study. The participants completed straight walking and figure-of-eight turning walking tasks at self-selected speeds. Intra-class correlation coefficients (ICCs) and Bland-Altman scatter plots were used to assess the test-retest reliability of oxyhemoglobin (HbO2) changes derived from fNIRS. p < 0.05 was considered statistically significant. Results: The test-retest reliability of HbO2 in prefrontal cortex (ICC, 0.67-0.78) was good and excellent, in frontal motor cortex (ICC, 0.51-0.61) and parietal sensory cortex (ICC, 0.53-0.62) is fair and good when the older adults performed straight and turning walking tasks. Bland-Altman diagram shows that the data consistency is fair and good. Conclusion: fNIRS can be used as a clinical measurement method to evaluate the brain activation of the older adults when walking in a straight line and turning, and the results are acceptable repeatability and consistency. However, it is necessary to strictly control the testing process and consider the possible changes in the repeated measurements.

"It's time for a change. I need to. I have to": Substance misuse recovery turning points of unhoused Alaskans.

Substance misuse is a pernicious health concern for many unhoused people. A deep understanding of turning points - what propels someone to take concrete action toward addressing substance misuse - is needed to inform recovery policies and practices. This study sought to identify common elements in turning points among unhoused people vis-à-vis a phenomenological qualitative approach. Twenty people (Mage = 47.47, SD = 9.75; 50% female) who self-identified as being in recovery while unhoused participated in semi-structured interviews in Anchorage, Alaska, a community with high rates of both houselessness and substance misuse. Survival (life- and health-sustaining), individual (intrapersonal), and relational (interpersonal) motivations all shaped turning points. Limitations include the possible underrepresentation of individuals using a harm-reduction approach or capturing differences by housing type. Programs to address substance misuse should consider these motivations. Future research should identify and refine turning points and work to understand how they interact with change processes.

Gait asymmetry and symptom laterality in Parkinson's disease: two of a kind?

BACKGROUND: The laterality of motor symptoms is considered a key feature of Parkinson's disease (PD). Here, we investigated whether gait and turning asymmetry coincided with symptom laterality as determined by the MDS-UPRDS part III and whether it was increased compared to healthy controls (HC). METHODS: We analyzed the asymmetry of gait and turning with and without a cognitive dual task (DT) using motion capture systems and wearable sensors in 97 PD patients mostly from Hoehn & Yahr stage II and III and 36 age-matched HC. We also assessed motor symptom asymmetry using the bilateral sub-items of the MDS-UPDRS-III. Finally, we examined the strength of the association between gait asymmetry and symptom laterality. RESULTS: Participants with PD had increased gait but not more turning asymmetry compared to HC (p < 0.05). Only 53.7% of patients had a shorter step length on the more affected body side as determined by the MDS-UPDRS-III. Also, 54% took more time and 29% more steps during turns toward the more affected side. The degree of asymmetry in the different domains did not correlate with each other and was not influenced by DT-load. CONCLUSIONS: We found a striking mismatch between the side and the degree of asymmetry in different motor domains, i.e., in gait, turning, and distal symptom severity in individuals with PD. We speculate that motor execution in different body parts relies on different neural control mechanisms. Our findings warrant further investigation to understand the complexity of gait asymmetry in PD.

Driving Behavior during Left-Turn Maneuvers at Intersections on Left-Hand Traffic Roads.

Understanding left-turn vehicle-pedestrian accident mechanisms is critical for developing accident-prevention systems. This study aims to clarify the features of driver behavior focusing on drivers' gaze, vehicle speed, and time to collision (TTC) during left turns at intersections on left-hand traffic roads. Herein, experiments with a sedan and light-duty truck (< 7.5 tons GVW) are conducted under four conditions: no pedestrian dummy (No-P), near-side pedestrian dummy (Near-P), far-side pedestrian dummy (Far-P) and near-and-far side pedestrian dummies (NF-P). For NF-P, sedans have a significantly shorter gaze time for left-side mirrors compared with light-duty trucks. The light-duty truck's average speed at the initial line to the intersection (L1) and pedestrian crossing line (L0) is significantly lower than the sedan's under No-P, Near-P, and NF-P conditions, without any significant difference between any two conditions. The TTC for sedans is significantly shorter than that for trucks with near-side pedestrians (Near-P and NF-P) and far-side pedestrians in Far-P. These insights can contribute to the ongoing development of accident-prevention safety systems for left-turning maneuvers at intersections.