Search Results (224)

Inter-turn short-circuit (ITSC) faults in permanent magnet synchronous machines (PMSMs) present a significant reliability challenge in electric vehicle (EV) drivetrains, particularly under non-stationary operating conditions characterized by inverter-driven transients, variable loads, and magnetic saturation. Existing diagnostic approaches, including motor current signature analysis (MCSA) and wavelet-based methods, are primarily designed for steady-state conditions and rely on manual feature selection, limiting their applicability in real-time embedded systems. Furthermore, the lack of publicly available, high-fidelity datasets capturing the transient dynamics and nonlinear flux-linkage behaviors of PMSMs under fault conditions poses an additional barrier to developing data-driven diagnostic solutions. To address these challenges, this study introduces a simulation framework that generates a comprehensive dataset using finite element method (FEM) models, incorporating magnetic saturation effects and inverter-driven transients across diverse EV operating scenarios. Time-frequency features extracted via Discrete Wavelet Transform (DWT) from stator current signals are used to train a Transformer model for automated ITSC fault detection. The Transformer model, leveraging self-attention mechanisms, captures both local transient patterns and long-range dependencies within the time-frequency feature space. This architecture operates without sequential processing, in contrast to recurrent models such as LSTM or RNN models, enabling efficient inference with a relatively low parameter count, which is advantageous for embedded applications. The proposed model achieves 97% validation accuracy on simulated data, demonstrating its potential for real-time PMSM fault detection. Additionally, the provided dataset and methodology contribute to the facilitation of reproducible research in ITSC diagnostics under realistic EV operating conditions. Full article

The influence of social media personalities has grown significantly, especially among youth audiences who spend substantial time on platforms like TikTok. The emergence and popularity of different types of social media influencers accelerated during the COVID-19 pandemic in many countries, including South Africa. In turn, this period also saw a surge in youth audiences following these influencers. This rapid growth of influencer followings among young people is largely driven by specific types of content that resonate with them, thus encouraging continued engagement. However, the benefits that these young followers gain from engaging with various influencers and the factors driving their preferences for specific influencers remain underexplored, particularly within the context of South African students within higher education. Therefore, this study explores the types of social media influencers most followed by university students at a South African University and investigates the key factors that drive their preferences. A structured online questionnaire was distributed, gathering both multiple-choice and open-ended responses from students. The data were analyzed using categorical frequency counts and thematic analysis. The data highlight how students actively turn to influencers as emotional anchors, role models, and sources of practical guidance. Their engagement reflects a deep need for connection, inspiration, and identity formation in a challenging academic and social environment. These patterns show that influencer content is not just entertainment but plays a critical developmental role. Understanding these motivations helps educators, policymakers, and brands to align better with youth values. The significance of these results lies in how influencer content is now coming in to fill the emotional, cultural, and educational gaps left by traditional systems among the young South African university students in this modern era. Full article

Interoceptive impairments are increasingly recognized as psychopathology processes underlying emotional disorders. However, their relationship with depression remains inconclusive. Alexithymia may influence the association between interoception and depressive symptoms. This study aimed to examine the role of alexithymia between interoception and depression. Eighty-eight depressed patients (DEPs) and fifty healthy controls (HCs) were recruited. Interoceptive sensibility was assessed using the Multidimensional Assessment of Interoceptive Awareness, and interoceptive accuracy and interoceptive awareness were evaluated through heartbeat counting tasks. Alexithymia was measured with the Toronto Alexithymia Scale. In the DEP group, depressive symptoms were assessed using the Hamilton Depression Scale. In DEPs, none of the three dimensions of interoception were associated with depressive symptoms. The alexithymic depressed patients exhibited lower interoceptive sensibility than their non-alexithymic counterparts, while the latter did not differ from the HC group. Moreover, alexithymia mediated the link between interoceptive sensibility and depressive symptoms. These results suggested that impaired interoceptive sensibility may primarily contribute to alexithymia, which, in turn, leads to depression. This highlights the importance of addressing alexithymia in therapeutic interventions aimed at improving the interoceptive process in depressed individuals. Full article

A field experiment in growing spring wheat (Triticum aestivum L.—cv. ‘Monsun’) under organic, integrated and conventional farming systems was conducted over the period of 2020–2022 at the Czesławice Experimental Farm (Lubelskie Voivodeship, Poland). The first experimental factor analyzed was the farming system: A. organic system (control)—without the use of chemical plant protection products and NPK mineral fertilization; B. conventional system—the use of plant protection products and NPK fertilization in the range and doses recommended for spring wheat; C. integrated system—use of plant protection products and NPK fertilization in an “economical” way—doses reduced by 50%. The second experimental factor was irrigation strategy: 1. no irrigation—control; 2. double irrigation; 3. multiple irrigation The aim of the research was to determine the physical, chemical, and enzymatic properties of loess soil under spring wheat crops as influenced by the factors listed above. The highest organic C content of the soil (1.11%) was determined in the integrated system with multiple irrigation of spring wheat, whereas the lowest one (0.77%)—in the conventional system without irrigation. In the conventional system, the highest contents of total N (0.15%), P (131.4 mg kg⁻¹), and K (269.6 mg kg⁻¹) in the soil were determined under conditions of multiple irrigation. In turn, the organic system facilitated the highest contents of Mg, B, Cu, Mn, and Zn in the soil, especially upon multiple irrigation of crops. It also had the most beneficial effect on the evaluated physical parameters of the soil. In each farming system, the multiple irrigation of spring wheat significantly increased moisture content, density, and compaction of the soil and also improved its total sorption capacity (particularly in the integrated system). The highest count of beneficial fungi, the lowest population number of pathogenic fungi, and the highest count of actinobacteria were recorded in the soil from the organic system. Activity of soil enzymes was the highest in the integrated system, followed by the organic system—particularly upon multiple irrigation of crops. Summing up, the present study results demonstrate varied effects of the farming systems on the quality and health of loess soil. From a scientific point of view, the integrated farming system ensures the most stable and balanced physicochemical and biological parameters of the soil due to the sufficient amount of nutrients supplied to the soil and the minimized impact of chemical plant protection products on the soil. The multiple irrigation of crops resulting from indications of soil moisture sensors mounted on plots (indicating the real need for irrigation) contributed to the improvement of almost all analyzed soil quality indices. Multiple irrigation generated high costs, but in combination with fertilization and chemical crop protection (conventional and integrated system), it influenced the high productivity of spring wheat and compensated for the incurred costs (the greatest profit). Full article

In the context of building a new type of power system, the optimal operation of high-proportion new-energy distribution networks (HNEDNs) is a current hot topic. In this paper, a stochastic distribution robust optimization method for HNEDNs that considers energy-storage refinement modeling is proposed. First, an energy-storage lifetime loss model based on the rainfall-counting method is constructed, and then an optimal operation model of an HNEDN considering energy storage refinement modeling is constructed, aiming to minimize the total operation cost while taking into account the energy cost and the penalty cost of abandoning wind and solar power. Then, a source-load uncertainty model of HNEDN is constructed based on the Wasserstein distance and conditional value at risk (CvaR) theory, and the HNEDN optimization model is reconstructed based on the stochastic distribution robust optimization method; based on this, the multiple linearization technique is introduced to approximate the reconstructed model, which aims to both reduce the difficulty in solving the model and ensure the quality of the solution. Finally, the modified IEEE 33-bus power distribution system is used as an example for case analysis, and the simulation results show that the method presented in this paper, through reducing the loss of life in the battery storage device, can reduce the average daily energy storage depreciation cost compared to an HNEDN optimization method that does not take the energy storage life loss into account; this, in turn, reduces the total operating cost of the system. In addition, the stochastic distribution robust optimization method used in this paper can adaptively adjust the economy and robustness of the HNEDN operation strategy according to the confidence level and the available historical sample data on new energy-output prediction errors to obtain the optimal HNEDN operation strategy when compared with other uncertainty treatment methods. Full article

Our study explored the accuracy of Fitbit recorded step count during the use of an assistive device (two-wheeled walker and standard cane) at various body positions (wrists, hips, and ankles). Participants (n = 11) ambulated an obstacle course (50 m total, including turns and a step up/down) a total of three times (two-wheeled walker, standard cane, and a deviceless control trial). Fitbit generated step counts (at the wrists, hips, and ankles) were then compared to the individual’s “actual” step count captured through video analysis. During the cane trial and the deviceless trial, all positions were significantly correlated (r = 0.764 to 0.984; p < 0.006) with the actual step count. However, increased variability (demonstrated by increased limits of agreement) was observed when the Fitbit was worn on the wrist (compared to the hips or ankles). During the walker trial, the step count was significantly correlated to the actual step count at the ankle and hip positions (r = 0.669 to 0.888; p < 0.017) with an average error of 1.5%, while it was not statistically correlated at the wrist with a 31.2% average error. Our study suggests that Fitbits are a good predictor of actual step count, with the caveat that the location of the Fitbit should be considered if an assistive device (e.g., two-wheeled rolling walker and single-point cane) is being used. Full article

This study analyzed the effects of various educational materials used in Tool Box Meetings conducted prior to work at construction sites on educational effectiveness. Specifically, the study examined the impact of changes in information quantity, linguistic explanation, and the number of educational materials on the cognitive load of construction workers. The study involved 345 construction workers. Group A utilized visual materials with higher information quantity compared to Group B. Group B, in turn, used visual materials that simplified the information to match linguistic explanations provided for Group A’s materials. Group C conducted the education meeting by reducing the number of educational materials from 13 to 8 after using Group B’s materials. Cognitive load, based on recall counts and recall rates, was then analyzed. In Group A, the use of visual educational materials with high information quantity was associated with reduced learning effectiveness, likely due to increased cognitive load. Meanwhile, in Group B, using educational materials that simplified information to match linguistic explanations resulted in an increase in recall counts and recall rates. In Group C, reducing the number of educational materials resulted in no difference in recall counts compared to Group B; however, there was an increase in the overall recall rate. Based on these research findings, it was concluded that utilizing visually simplified materials aligned with linguistic explanations and considering the cognitive load of workers to establish an appropriate number of educational materials are effective approaches in Tool Box Meeting education. Full article

This paper proposes a family of high-efficiency DC-DC boost converters employing voltage-doubling coupled-inductor technology with a low component count. By varying the homonymous winding connections of the coupled inductor, three topologies are developed: parallel (PWCDVD-CLBC), series (SWCDVD-CLBC), and flipped-parallel (FPWCDVD-CLBC). These converters achieve high-voltage gain, continuous input current, and low-voltage stress across components. The PWCDVD-CLBC and FPWCDVD-CLBC configurations exhibit voltage gains proportional to the turn ratio, while the SWCDVD-CLBC shows an inverse relation, enabling reduced turn ratios. Detailed operational principles, mathematical analysis, and performance advantages are presented. A comparative evaluation demonstrates a higher voltage gain, realizes continuous input current, and has lower voltage stresses. The experimental results validate the theoretical analysis and confirm the feasibility and efficiency of the proposed designs. Full article

Cognitive–motor integration is the coordination of cognitive and motor processes; it is commonly impaired among people living with dementia (PWD) and may be improved through exercise. This pilot randomized controlled trial (1:1) aimed to determine the effect of 6 months of exercise on cognitive–motor integration compared to usual care in n = 42 PWD at two residential care facilities. Participants completed single- and dual-task standing (30 s of standing while counting backward by 1 s), walking (4 m walk while naming words), and timed-up-and-go (TUG) tests (TUG with a category task), measured using APDM inertial sensors at baseline and 6 months (age = 82 years, 35% female, Montreal Cognitive Assessment = 10.2 ± 5.9, NCT05488951). The adapted Otago Exercise Program involved 60 min of lower-body strength and balance exercises and walking 3x/week for 6 months. Usual care involved regular social activities and healthcare appointments. Exercise provoked increased single-task stride length and increased dual-task TUG turn velocity compared to usual care (p < 0.05). Usual care may reduce the ability to appropriately select cautious gait, as the usual care group exhibited faster dual-task gait speed at 6 months compared to the OEP plus usual care (p < 0.05), which was faster than their single-task gait speed. Our results support implementing the OEP to improve cognitive–motor integration in PWD. Full article

(1) Background: The hemostatic system and tumor biology display a tight and reciprocal interaction where clotting products enhance tumor growth and dissemination, and the tumor, in turn, triggers a hypercoagulable and inflammatory state. Evaluating circulating biomarkers related to thrombo-inflammatory may provide a promising tool for predicting tumor outcomes, especially in non-small cell lung cancer (NSCLC) characterized by unfavorable outcomes. (2) Aim: In a prospective cohort of NSCLC patients, we evaluated whether thromboinflammatory biomarkers could predict early disease progression (DP) during the first 6 months of first-line anticancer treatment. (3) Methods: 719 newly diagnosed advanced-stage NSCLC patients were included. Complete blood cell count, high-sensitivity C-reactive protein (hs-CRP), FVIII, fibrinogen, D-dimer, thrombin-antithrombin (TAT) complexes, and prothrombin fragment1+2(F1+2) were tested in blood samples collected before starting chemotherapy. DP was gathered during follow-up. (4) Results: The 6-month cumulative incidence rate for DP was 49%. Univariable Cox regression analysis identified metastatic status, BMI, hemoglobin, leukocytes, hs-CRP, FVIII, fibrinogen, TAT, and D-dimer as significant predictors of DP. In a multivariable analysis that included all previously significant variables, only hs-CRP and D-Dimer levels remained strongly associated with DP. The two variables were used to establish a risk stratification model that significantly identified patients at high risk of DP at 6 months (HR 2.9; 95% CI, 2.3–3.7), which can be applied to 3, 9, and 12 months. (5) Conclusions: Our model easily and precisely estimates early DP during chemotherapy. If externally validated, this model can significantly enhance the allocation of medical resources in managing advanced NSCLC, ensuring that patients receive the most effective care possible. Full article

This study on the isolation, identification, and characterization of the probiotic properties of lactic acid bacterial strains from the rose blossom of Rosa damascena Mill. (R. damascena) is crucial for discovering novel, plant-derived probiotics with potential health benefits and applications in food, medicine, and cosmetics. Nine lactic acid bacterial (LAB) strains were isolated from rose blossom of R. damascena, and they were identified to the species level by applying physiological and biochemical (API 50 CHL), and molecular genetic (16S rRNA gene sequencing) methods. The isolates were identified as belonging to the Lactobacillus helveticus, Lactobacillus acidophilus, and Lactiplantibacillus plantarum species. Some probiotic properties of the newly isolated and identified LAB strains were examined: their antibacterial activity against pathogens by the agar well diffusion method, and their antibiotic resistance profile by the agar paper disc diffusion method. The LAB strains studied demonstrated significant antibacterial activity against the Escherichia coli, Staphylococcus aureus, Salmonella Abony, Proteus vulgaris, Listeria monocytogenes, and Enterococcus faecalis pathogens and were resistant to most of the antibiotics used in clinical practice, which in turn suggested the possibility of their joint inclusion in therapy, in the composition of probiotic preparations. A batch fermentation process was conducted with Lactiplantibacillus plantarum 5/20, and the kinetic parameters of the batch fermentation process were determined in order to obtain a concentrate with a high viable cell count (10¹³CFU/cm³). The resultant concentrate was freeze-dried, and freeze-dried preparations with a high viable cell count (over 10¹² CFU/g) were obtained. Research on LAB strains isolated from R. damascena could reveal valuable LAB strains with significant probiotic properties. These strains will be suitable for various applications in the composition of starter cultures for functional beverages and foods, as well as probiotic preparations, showcasing the untapped potential of plant-associated microbiota. Full article

The present Perspective analyzes the remarkable evolution of the Amyloid Cascade Hypothesis 2.0 (ACH2.0) theory of Alzheimer’s disease (AD) since its inception a few years ago, as reflected in the diminishing role of amyloid-beta (Aβ) in the disease. In the initial iteration of the ACH2.0, Aβ-protein-precursor (AβPP)-derived intraneuronal Aβ (iAβ), accumulated to neuronal integrated stress response (ISR)-eliciting levels, triggers AD. The neuronal ISR, in turn, activates the AβPP-independent production of its C99 fragment that is processed into iAβ, which drives the disease. The second iteration of the ACH2.0 stemmed from the realization that AD is, in fact, a disease of the sustained neuronal ISR. It introduced two categories of AD—conventional and unconventional—differing mainly in the manner of their causation. The former is caused by the neuronal ISR triggered by AβPP-derived iAβ, whereas in the latter, the neuronal ISR is elicited by stressors distinct from AβPP-derived iAβ and arising from brain trauma, viral and bacterial infections, and various types of inflammation. Moreover, conventional AD always contains an unconventional component, and in both forms, the disease is driven by iAβ generated independently of AβPP. In its third, the current, iteration, the ACH2.0 posits that proteolytic production of Aβ is suppressed in AD-affected neurons and that the disease is driven by C99 generated independently of AβPP. Suppression of Aβ production in AD seems an oxymoron: Aβ is equated with AD, and the later is inconceivable without the former in an ingrained Amyloid Cascade Hypothesis (ACH)-based notion. But suppression of Aβ production in AD-affected neurons is where the logic leads, and to follow it we only need to overcome the inertia of the preexisting assumptions. Moreover, not only is the generation of Aβ suppressed, so is the production of all components of the AβPP proteolytic pathway. This assertion is not a quantum leap (unless overcoming the inertia counts as such): the global cellular protein synthesis is severely suppressed under the neuronal ISR conditions, and there is no reason for constituents of the AβPP proteolytic pathway to be exempted, and they, apparently, are not, as indicated by the empirical data. In contrast, tau protein translation persists in AD-affected neurons under ISR conditions because the human tau mRNA contains an internal ribosomal entry site in its 5′UTR. In current mouse models, iAβ derived from AβPP expressed exogenously from human transgenes elicits the neuronal ISR and thus suppresses its own production. Its levels cannot principally reach AD pathology-causing levels regardless of the number of transgenes or the types of FAD mutations that they (or additional transgenes) carry. Since the AβPP-independent C99 production pathway is inoperative in mice, the current transgenic models have no potential for developing the full spectrum of AD pathology. What they display are only effects of the AβPP-derived iAβ-elicited neuronal ISR. The paper describes strategies to construct adequate transgenic AD models. It also details the utilization of human neuronal cells as the only adequate model system currently available for conventional and unconventional AD. The final alteration of the ACH2.0, introduced in the present Perspective, is that AβPP, which supports neuronal functionality and viability, is, after all, potentially produced in AD-affected neurons, albeit not conventionally but in an ISR-driven and -compatible process. Thus, the present narrative begins with the “omnipotent” Aβ capable of both triggering and driving the disease and ends up with this peptide largely dislodged from its pedestal and retaining its central role in triggering the disease in only one, although prevalent (conventional), category of AD (and driving it in none). Among interesting inferences of the present Perspective is the determination that “sporadic AD” is not sporadic at all (“non-familial” would be a much better designation). The term has fatalistic connotations, implying that the disease can strike at random. This is patently not the case: The conventional disease affects a distinct subpopulation, and the basis for unconventional AD is well understood. Another conclusion is that, unless prevented, the occurrence of conventional AD is inevitable given a sufficiently long lifespan. This Perspective also defines therapeutic directions not to be taken as well as auspicious ways forward. The former category includes ACH-based drugs (those interfering with the proteolytic production of Aβ and/or depleting extracellular Aβ). They are legitimate (albeit inefficient) preventive agents for conventional AD. There is, however, a proverbial snowball’s chance in hell of them being effective in symptomatic AD, lecanemab, donanemab, and any other “…mab” or “…stat” notwithstanding. They comprise Aβ-specific antibodies, inhibitors of beta- and gamma-secretase, and modulators of the latter. In the latter category, among ways to go are the following: (1) Depletion of iAβ, which, if sufficiently “deep”, opens up a tantalizing possibility of once-in-a-lifetime preventive transient treatment for conventional AD and aging-associated cognitive decline, AACD. (2) Composite therapy comprising the degradation of C99/iAβ and concurrent inhibition of the neuronal ISR. A single transient treatment could be sufficient to arrest the progression of conventional AD and prevent its recurrence for life. Multiple recurrent treatments would achieve the same outcome in unconventional AD. Alternatively, the sustained reduction/removal of unconventional neuronal ISR-eliciting stressors through the elimination of their source would convert unconventional AD into conventional one, preventable/treatable by a single transient administration of the composite C99/iAβ depletion/ISR suppression therapy. Efficient and suitable ISR inhibitors are available, and it is explicitly clear where to look for C99/iAβ-specific targeted degradation agents—activators of BACE1 and, especially, BACE2. Directly acting C99/iAβ-specific degradation agents such as proteolysis-targeting chimeras (PROTACs) and molecular-glue degraders (MGDs) are also viable options. (3) A circumscribed shift (either upstream or downstream) of the position of transcription start site (TSS) of the human AβPP gene, or, alternatively, a gene editing-mediated excision or replacement of a small, defined segment of its portion encoding 5′-untranslated region of AβPP mRNA; targeting AβPP RNA with anti-antisense oligonucleotides is another possibility. If properly executed, these RNA-based strategies would not interfere with the protein-coding potential of AβPP mRNA, and each would be capable of both preventing and stopping the AβPP-independent generation of C99 and thus of either preventing AD or arresting the progression of the disease in its conventional and unconventional forms. The paper is interspersed with “validation” sections: every conceptually significant notion is either validated by the existing data or an experimental procedure validating it is proposed. Full article

The A* algorithm is widely used in mobile robot path planning; however, it faces challenges such as unsmooth planned paths, redundant nodes, and extensive search areas. This paper proposes a hybrid algorithm combining an improved A* algorithm with the Dynamic Window Approach. By quantifying grid obstacle data to extract environmental information and employing a grid-based environmental modeling method, the proposed approach enhances path smoothness at turns using second-order Bezier curve smoothing. It improves the heuristic function and child node selection process, applying these advancements in experimental path planning scenarios. A simulated 2D map was constructed using point cloud scanning in RViz to validate the hybrid algorithm through simulations and real-world outdoor tests. Experimental results demonstrate that, compared to the A* and DWA algorithms, the improved hybrid algorithm enhances search efficiency by 10.93%, reduces search node count by 32.26%, decreases the number of turning points by 36.36% and the value of turning angle by 34.83%, shortens the total path length by 22.05%, and improves overall path smoothness. Simulations and field tests confirm that the proposed hybrid algorithm is more stable, significantly reduces collision probability, and demonstrates its applicability for mobile robot localization and navigation in real-world environments. Full article

Dairy herds around the world are undergoing several changes. Herd sizes are increasing, as are both milk yield and quality. The implementation of new technologies in various domains of dairy production is leading to an increase in the quantity of data available. This, in turn, creates a need to extract useful information from these data to improve production efficiency. This paper presents the findings of a preliminary study that utilizes a machine learning (ML) approach to assess the accuracy of somatic cell count (SCC) and neutrophils + lymphocytes count/mL (PLCC) in identifying cows at risk of developing intramammary infection (IMI) due to major pathogens. These pathogens (MajPs) include S. aureus, S. agalactiae, S. uberis, and S. dysgalactiae. This study identified these pathogens either by real-time PCR (qPCR) methods or by conventional bacteriology, following the cows’ calving process. This study encompassed a total of 424 cows and 1696 quarter milk samples. A comparison of the two methods revealed significant disparities in the prevalence of MajPs, with the qPCR method demonstrating a higher prevalence than conventional bacteriology. However, the prevalence of negative results was comparable, with both methods yielding approximately 71.0% and 72.1%, respectively. The comprehensive results of this study substantiated that all the cellular markers exhibited the most accurate when MajP IMI was diagnosed using quarter milk samples, but this result is mainly due to the very high specificity. The cellular markers exhibited nearly equivalent performance, irrespective of the ML algorithm employed. The findings indicate that approaches based on SCC or PLCC may be useful for identifying healthy cows or quarters. However, it is essential to confirm all “non-negative” results through subsequent analysis within 7–15 days to ensure accuracy. However, further studies are necessary to enhance diagnostic accuracy. Full article

Optical microfiber biosensors demonstrate exceptionally ultra-high sensitivity at the dispersion turning point (DTP). However, the DTP is highly susceptible to variations in dimensional and external environmental factors, and the spectral response is mismatched from preparation in air to application in a liquid environment, making the DTP difficult to control effectively. In this work, we propose a method that bridges the relationship between the interference spectra of air and aqueous environments. By counting the interference peaks in air, we can accurately predict the DTP position in liquids. Meanwhile, it provides a new balance between sensitivity and wide linear dynamic range, achieving wide dynamic range detection across various concentrations. The optical microfiber coupler (OMC) is fabricated using the hydrogen–oxygen flame melting tapering method. In addition, the concentration, temperature, and solvent used for the sensor’s biofunctional layer are optimized. Finally, in refractive index sensing, a maximum sensitivity of 1.17 × 105 ± 0.038 × 105 nm/RIU is achieved. For biosensing, a wide dynamic range detection of cardiac troponin I (cTnI) is realized at concentrations of 12–48 ng/mL, 120–480 pg/mL, and 120–480 fg/mL. Full article