Constant Increments Research Articles (Page 1)

Verbal fluency (VF) represents an important aspect of intelligence, in which oral word generation is demanded following semantic or phonemic cues. Two reliable phenomena of VF execution have been reported: A decay in performance across 1-minute trial and a discrepancy score between the semantic and phonemic VF tests (VFTs). Although, these characteristics have been explained from various cognitive standpoints, the fundamental role of speech breathing has not yet been considered. Therefore, the present study aims to evaluate the role of respiratory function for word generation in VFTs in healthy individuals. Thirty healthy young adults performed VFTs during definite periods of 1 minute while wearing a pneumotachograph mask. Duration, peak and volume of airflow were acquired during inspirations and expirations. Also, respiratory rate and acoustic data of verbal responses were registered, and accuracy scores were calculated. Each 1-minute trial was divided into four intervals of 15-seconds where parameters were calculated. Repeated measures ANOVAs and repeated measures correlations were used in the statistical analyses. Data revealed that respiratory function was significantly coupled to VF performance mostly during inhalations. Small but constant increments of inhale airflow occurred in phonemic VFT as well as higher peak airflow in both tasks, being higher for semantic VFT. High respiratory rate characterized performance of both VFTs across intervals. Airflow adjustments corresponded to better VF accuracy, while increments in respiratory rate did not. The present study shows a complex interplay of breathing needs during VF performance that varies along the performance period and that notably connects to inspirations.

Free chlorine which refers to all chlorine present in water as Cl2, hypochlorous acid (HOCl), and hypochlorite ion (ClO-), is a widely used disinfectant in tap and swimming pool water, as well as for washing raw vegetables and other foods. The lack of disinfection of such water sources can lead to the outbreak of infectious diseases. Therefore, the World Health Organization (WHO) has developed guidelines for drinking water quality using Hazard Analysis and Critical Control Point (HACCP) principles for the food industry, and monitoring of free chlorine is becoming increasingly important.[1] Traditional methods for measuring free chlorine concentration, such as absorption spectrophotometry and the iodine method, face challenges in providing accurate continuous measurements. Similarly, electrochemical measurement methods face challenges in accuracy due to the variability in the electrochemical response of free chlorine. This variability is influenced by electrode surface conditions and pH variation, as the ratio of hypochlorous acid and hypochlorite ion present depends on pH. To overcome these challenges, we explored the potential of neural network-based machine learning techniques utilizing electrochemical responses to estimate free chlorine concentration. In this study, we developed a free chlorine sensor utilizing machine learning, employing a current-potential curve as input to estimate free chlorine concentration, regardless of pH variations.To collect data for training the neural network model, we built and employed an automated measurement system based on Raspberry Pi. This system facilitated the sequential preparation of various solutions using NaH2PO4, Na2HPO4, and sodium hypochlorite solutions, followed by electrochemical measurements using linear sweep voltammetry (LSV). A total of 480 LSV curves were generated, covering pH values ranging from 5.3 to 8.8, free chlorine concentrations from 0 ppm to 55 ppm, and scanning speeds of 100 mV/s with a range of 0.7 V to -1.5 V. Each measurement sequence consisted of 12 LSV curves representing various free chlorine concentrations. These concentrations were varied in constant increments at similar pH levels. In total, 40 sequences were performed through this process.Figures 1 and 2 show LSV curves obtained at pH 5.7 and pH 8.9, respectively. Under both pH conditions, the current increases with increasing free chlorine concentration. However, variations in curve shapes, particularly the reduction peak observed around -0.4 V, illustrate the influence of pH on the electrochemical response. This peak, attributed to the reduction of hypochlorous acid, becomes suppressed at higher pH levels due to the decreased proportion of hypochlorous acid relative to hypochlorite ion.Machine learning was conducted using 360 LSV curves for training and the remaining 120 LSV curves for validation, employing a neural network structure consisting of 5 affine layers with rectified linear unit (ReLU) as the intermediate layer and mean squared error (MSE) function as the output layer. Current value columns from LSV curves and corresponding free chlorine concentrations were utilized as inputs and outputs, respectively. The average error was low at 2.26 ppm, albeit with a maximum error of 15.4 ppm, attributed partly to variations in electrode surface conditions during measurements. To address this, we focused on the initial 0 ppm LSV curve in each sequence, which provides crucial information about changes in electrode surface conditions. Taking into account this insight, we performed a new approach. In this approach, we concatenated the current value columns from all LSV curves with the current value column from the corresponding 0 ppm LSV curve in the input data. This approach allowed us to effectively incorporate information about the electrode surface condition into machine learning, resulting in a significant improvement in accuracy. Figure 3 illustrates the predicted concentration plotted against actual concentration values, showing an average error of 1.04 ppm and a maximum error of 8.75 ppm, highlighting the efficacy of our machine learning approach.In conclusion, our developed sensor, which employs a neural network, demonstrates outstanding accuracy in estimating free chlorine concentration, even when the pH level is unknown.[1] World Health Organization, Guidelines for Drinking-Water Quality, 4th edn incorporating the first and second addenda, 2022. Figure 1

Fatigue-based process window for laser beam powder bed fusion additive manufacturing

Abstract Background and Aims Patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD) have a considerably higher mortality than the general population. Nevertheless, in the United States, mortality rates in the CKD and ESKD populations have declined steadily over the last decade until the onset of the COVID-19 pandemic [1]. Through a quantitative analysis of the age- and time-dependence of mortality rates in renal patient populations in the US, we aimed at quantifying trends in life expectancy between 2011 and 2021. Method We analysed CKD and ESKD mortality rates as reported in the US Renal Data System's (USRDS) Annual Data Report 2023 for the years 2011–2021 [1]. There, CKD mortality rates were determined from a Medicare 5% random sample (CKD stages 4 and 5) for patients aged 65 and above (“CKD 65+”). ESKD mortality rates were obtained from the USRDS database; we analysed data for patients aged 45 and above (“ESKD 45+”). We used fits of analytical functions to the data to hosphorzed their dependence on age and time. This technique enables us to extract quantitative trends in time by tracking fit parameters. Results We found that for each year between 2011 and 2021, mortality rates in the adult CKD and ESKD populations in the US largely conformed to an exponential dependence on patient age, $m = {{m}_0}( t ){{2}^{a/{{\Delta }}a}}$, that is, mortality rates doubled over constant age increments ${{\Delta }}a$. While overall, mortality rates were declining between 2011 and 2019, the age increments over which mortality rates doubled were nearly identical for each year (CKD 65+: ${{\Delta }}a$ = 10.5 ± 0.4 y, ESKD 45+: ${{\Delta }}a$ = 15.1 ± 0.9 y; mean ± SD). Exploiting this simple relationship, we found that the changes in mortality rates over time could largely be reduced to a steady right-shift of an otherwise unchanged mortality curve over time (shown for the ESKD 45+ group in Fig. 1a). By quantifying this right-shift over time, we estimated the gain in 1-year survival probability for different ages (Fig. 1b,c). This gain in survival does not necessarily imply a prolonged time on renal replacement therapy (RRT), e.g., when patients concomitantly start RRT at a later age. The onset of the COVID-19 pandemic in 2020 coincides with an abrupt cessation of these positive trends, reflected by a setback of mortality curves close to those in the year 2016 for the CKD population and to before 2011 for the ESKD population. Conclusion Public health data on CKD and ESKD show systematic dependencies of mortality rates on age and time, which can be revealed using analytical parameterisations of the data. Using this technique, we can capture trends in mortality rates and 1-year survival probability in adult kidney patient populations in the US during the years 2011–2019 and can quantify the abrupt cessation of these trends during the onset of the COVID-19 pandemic. In the CKD population we observed a setback of mortality rates close to those in the year 2016 with the onset of the pandemic. Changes in mortality rates in the ESKD population were more distinct. Specifically in elderly patients (aged 65 and above) 1-year survival dropped abruptly to levels lower than those observed in the previous decade.

An economic order quantity model under constant purchasing price increments

An economic order quantity model under constant purchasing price increments

Normative values and prediction equations for the modified incremental step test in healthy adults aged 18–83 years

Experimental collapse investigation and nonlinear modeling of a single-span stone masonry arch bridge

A recurring question regarding Likert items is whether the discrete steps that this response format allows represent constant increments along the underlying continuum. This question appears unsolvable because Likert responses carry no direct information to this effect. Yet, any item administered in Likert format can identically be administered with a continuous response format such as a visual analog scale (VAS) in which respondents mark a position along a continuous line. Then, the operating characteristics of the item would manifest under both VAS and Likert formats, although perhaps differently as captured by the continuous response model (CRM) and the graded response model (GRM) in item response theory. This article shows that CRM and GRM item parameters hold a formal relation that is mediated by the form in which the continuous dimension is partitioned into intervals to render the discrete Likert responses. Then, CRM and GRM characterizations of the items in a test administered with VAS and Likert formats allow estimating the boundaries of the partition that renders Likert responses for each item and, thus, the distance between consecutive steps. The validity of this approach is first documented via simulation studies. Subsequently, the same approach is used on public data from three personality scales with 12, eight, and six items, respectively. The results indicate the expected correspondence between VAS and Likert responses and reveal unequal distances between successive pairs of Likert steps that also vary greatly across items. Implications for the scoring of Likert items are discussed.

Approximating probability distributions can be a challenging task, particularly when they are supported over regions of high geometrical complexity or exhibit multiple modes. Annealing can be used to facilitate this task which is often combined with constant a priori selected increments in inverse temperature. However, using constant increments limits the computational efficiency due to the inability to adapt to situations where smooth changes in the annealed density could be handled equally well with larger increments. We introduce AdaAnn, an adaptive annealing scheduler that automatically adjusts the temperature increments based on the expected change in the Kullback-Leibler divergence between two distributions with a sufficiently close annealing temperature. AdaAnn is easy to implement and can be integrated into existing sampling approaches such as normalizing flows for variational inference and Markov chain Monte Carlo. We demonstrate the computational efficiency of the AdaAnn scheduler for variational inference with normalizing flows on a number of examples, including posterior estimation of parameters for dynamical systems and probability density approximation in multimodal and high-dimensional settings.

Abstract In the non‐linear evaluation of the behavior of steel, concrete and steel‐concrete composite cross‐sections, increment and iteration strategies are necessary for the complete construction of the moment‐curvature relationship (M‐Φ). For the correct simulation of sections composed of strain‐softening materials, a numerical strategy based on constant force increments does not capture the downward branch of the M‐Φ relationship. Therefore, the present study aims to couple the strain compatibility method to the path‐following strategies to go beyond the critical bending moment points in the construction of the relations that describe the complete cross‐section mechanical behavior. In this context, the generalized displacement technique, which depends on a generalized stiffness parameter, and the minimum residual displacement method, are adapted to the cross‐sectional non‐linear problem. To validate the proposed numerical formulation, the results obtained here are compared with the numerical data available in the literature. Additionally, the softening effect on the concrete was increased to induce descending stretches in the moment‐curvature relationship, and this condition was correctly evaluated.

Geometric Modeling of Serrated Cutters for Endmilling Forces using Local Oblique Cutting and Rake Normal Correspondence

Traditional cardiopulmonary exercise test (CPET) protocols are difficult to apply to patients who have difficulty walking on a treadmill. Therefore, this study aimed to develop an aquatic treadmill (AT) CPET protocol involving constant increments in exercise load (metabolic equivalents (METs)) at regular intervals. Fourteen healthy male participants were enrolled in this study. The depth of the water pool was set to the umbilicus level of each participant, and the water temperature was maintained at 28–29 °C. The testing protocol comprised a total of 12 stages at different speeds. The starting speed was 0.7 km/h, which was increased by 0.6 or 0.7 km/h every 2 min. Heart rate, blood pressure, oxygen uptake, minute ventilation, respiratory exchange ratio, and rate of perceived exertion were recorded at each stage. All values showed a significant increasing trend with stage progression (p < 0.001). Peak oxygen uptake and heart rate values were 29.76 ± 3.75 and 168.36 ± 13.12, respectively. We developed a new AT CPET protocol that brings about constant increments in METs at regular intervals. This new AT CPET protocol could be a promising alternative to traditional CPET protocols for patients who experience difficulty walking on a treadmill.

This study explored the development of neuromuscular fatigue responses during progressive cycling exercise. The sample comprised 32 participants aged 22.0 ± 0.54 years who were assigned into three groups: endurance-trained group (END, triathletes, n = 10), strength-trained group (STR, bodybuilders, n = 10) and control group (CG, recreationally active students, n = 12). The incremental cycling exercise was performed using a progressive protocol starting with a 3 min resting measurement and then 50 W workload with subsequent constant increments of 50 W every 3 min until 200 W. Surface electromyography (SEMG) of rectus femoris muscles was recorded during the final 30 s of each of the four workloads. During the final 15 s of each workload, participants rated their overall perception of effort using the 20-point rating of the perceived exertion (RPE) scale. Post hoc Tukey’s HSD testing showed significant differences between the END and STR groups in median frequency and mean power frequency across all workloads (p < 0.001 and p < 0.01, respectively). Athletes from the END group had significantly lower electromyogram amplitude responses than those from the STR (p = 0.0093) and CG groups (p = 0.0006). Increasing RPE points from 50 to 200 W were significantly higher in the STR than in the END group (p < 0.001). In conclusion, there is a significant variation in the neuromuscular fatigue profiles between athletes with different training backgrounds when a cycling exercise is applied. The approximately linear trends of the SEMG and RPE values of both groups of athletes with increasing workload support the increased skeletal muscle recruitment with perceived exertion or fatiguing effect.

Simple SummaryThe multiple structural and functional adaptive changes vary depending on the mode of training. The purpose of this study was to examine the acute effects of progressive submaximal cycling on selected cardiorespiratory and metabolic variables in endurance- and strength-trained athletes. The sample comprised participants with different training background: endurance trained group (triathletes), strength trained group (bodybuilders), and a control group (recreationally active students). The research problem was based on the verification of the minor non-specific cardiometabolic responses in strength and endurance trained athletes during a progressive submaximal cycling exercise test. The substantive finding of this study was that endurance- and strengthtrained athletes differed only in the metabolic responses of respiratory exchange ratio and blood lactate concentration, whereas the acute cardiorespiratory variables did not demonstrate any statistically relevant differences. Based on our findings we recommend that endurance-trained athletes follow a concurrent training program, combined strength and endurance training, to improve neuromuscular parameters and thus optimize their economy of movement and endurance-specific muscle power capacity.The purpose of this study was to examine the acute effects of a progressive submaximal cycling exercise on selected cardiorespiratory and metabolic variables in endurance and strength trained athletes. The sample comprised 32 participants aged 22.0 ± 0.54 years who were assigned into three groups: an endurance trained group (END, triathletes, n = 10), a strength trained group (STR, bodybuilders, n = 10), and a control group (CON, recreationally active students, n = 12). The incremental cycling exercise was performed using a progressive protocol starting with a 3 min resting measurement and then a 50 W workload with subsequent constant increments of 50 W every 3 min until 200 W. The following cardiometabolic variables were evaluated: heart rate (HR), oxygen uptake (VO2), carbon dioxide production (VCO2), respiratory exchange ratio (RER), systolic and diastolic blood pressure (SBP and DBP), and blood lactate (BLa−). We found the between-group differences in metabolic variables (the average RER and BLa−) were statistically significant (Tukey’s HSD test: CON vs. STR, p < 0.01 and p < 0.05, respectively; CON vs. END, p < 0.001; END vs. STR, p < 0.001). RER and BLa– differences in all groups depended on the workload level (G-G-epsilon = 0.438; p < 0.004 and G-G-epsilon = 0.400; p < 0.001, respectively). There were no significant differences in cardiorespiratory variables between endurance- and strength-trained groups. In conclusion, this study demonstrated that acute cardiorespiratory responses at each of the four submaximal workloads were comparable in endurance- compared to strength-trained athletes, but significantly different compared to recreationally active men. However, there were significant differences in the metabolic responses of RER and BLa−. Based on our findings we recommend that endurance-trained athletes follow a concurrent training program, combined strength and endurance training, to improve neuromuscular parameters and thus optimize their economy of movement and endurance-specific muscle power capacity.

With the aim of ascertaining the effects of the widths (A) of valleys on near-surface turbulence, flows over an isolated symmetric three-dimensional valley of constant depth (H) and slopes are characterized in a large-boundary-layer wind tunnel. Starting at A = 4H, valley widths were systematically varied to A = 12H with constant increments of 2H. High-resolution laser-Doppler velocimetry measurements were made at several equivalent locations above each of the resulting valley geometries and compared with data from undisturbed flows over flat terrain. Flow separation caused by the first ridges generated inner-valley recirculation bubbles with lengths dependent on the valley widths. Secondary recirculation zones were also observed downstream from the crests of the second ridges. Results show that the width modifications exert the strongest effects on turbulence within the valleys and the vicinities of the second ridges. Above these locations, maximal magnitudes of turbulence are generally found for the larger width geometries. Furthermore, lateral turbulence overpowers the longitudinal counterparts nearest to the surface, with maximal gains occurring for the smaller widths. Our data indicate that valley widths are impactful on near-surface flows and should be considered together with other more established geometric parameters of influence.

Formation and evolution of fracture spacing on various geometric surfaces in layered materials

A novel numerical-iterative-approach for strain-softening surrounding rock incorporating rockbolts effectiveness and hydraulic-mechanical coupling based on Three-Dimensional Hoek-Brown strength criterion

Body size is a trait that broadly influences the demography and ecology of organisms. In unitary organisms, body size tends to increase with age. In modular organisms, body size can either increase or decrease with age, with size changes being the net difference between modules added through growth and modules lost through partial mortality. Rates of colony extension are independent of body size, but net growth is allometric, suggesting a significant role of size-dependent mortality. In this study, we develop a generalizable model of partitioned growth and partial mortality and apply it to data from 11 species of reef-building coral. We show that corals generally grow at constant radial increments that are size independent, and that partial mortality acts more strongly on small colonies. We also show a clear life-history trade-off between growth and partial mortality that is governed by growth form. This decomposition of net growth can provide mechanistic insights into the relative demographic effects of the intrinsic factors (e.g. acquisition of food and life-history strategy), which tend to affect growth, and extrinsic factors (e.g. physical damage, and predation), which tend to affect mortality.

Computed tomography perfusion (CTP) allows the estimation of pretreatment ischemic core after acute ischemic stroke. However, CTP-derived ischemic core may overestimate final infarct volume. We aimed to evaluate the accuracy of CTP-derived ischemic core for the prediction of final infarct volume according to time from stroke onset to recanalization in 104 patients achieving complete recanalization after mechanical thrombectomy who had a pretreatment CTP and a 24-h follow-up MRI-DWI. A range of CTP thresholds was explored in perfusion maps at constant increments for ischemic core calculation. Time to recanalization modified significantly the association between ischemic core and DWI lesion in a non-linear fashion (p-interaction = 0.018). Patients with recanalization before 4.5 h had significantly lower intraclass correlation coefficient (ICC) values between CTP-predicted ischemic core and DWI lesion (n = 54; best threshold relative cerebral blood flow (rCBF) < 25%, ICC = 0.673, 95% CI = 0.495–0.797) than those with later recanalization (n = 50; best threshold rCBF < 30%, ICC = 0.887, 95% CI = 0.811–0.935, p = 0.013), as well as poorer spatial lesion agreement. The significance of the associations between CTP-derived ischemic core and clinical outcome at 90 days was lost in patients recanalized before 4.5 h. CTP-derived ischemic core must be interpreted with caution given its dependency on time to recanalization, primarily in patients with higher chances of early recanalization.