High Performance Research Articles

Family firm performance through transformational CEO leadership and familiness-related team forces

PurposeThe purpose of this study is to test the role of familiness-related team forces induced by the CEO of family firms. In particular, we report on the effects of the transformational leadership style of CEOs on their respective top-management team (TMT) and firm performance when viewed through a familiness lens.Design/methodology/approachSurvey measures were taken from a snowballed sample of 72 CEOs of German family firms as well as from 245 members of their TMTs. We tested the aggregated firm-level data with objective performance indicators of the firms they led.FindingsSupport was obtained for the three hypothesized team-force mediations and the four-path mediation model. The relationship between CEO’s transformational style and high family-firm performance is found to be serially mediated by TMT cohesion, behavioral integration and efficacy. Together, these three types of collective forces are assumed to be the familiness effect of a family-member CEO with a transformational leadership style.Originality/valueWith our model, we quantitatively tested familiness-type forces vis-à-vis firm performance. Theoretical and practical implications of these findings are discussed.

Uncovering the potential of industrial waste: turning discarded resources into sustainable advanced materials

To identify solutions for utilizing industrial wastes (slag, sludge, fly ash, and bottom ash) in the development of pro-environmental systems, this paper reviews existing literature and explores material characterization methods. A review analysis was conducted to uncover their potential, and it was found that many utilizations can be made to recycle them into sustainable materials. Structure characterization, optical-dielectric function, and morphology analysis were analyzed to confirm the recent review. Structural properties are represented by crystallite size and crystallinity, where nickel slag shows the smallest distribution (55 ± 10) nm with the highest crystallinity (25.42%), indicating its association with uniformity of response to external disturbances and micro-structural stability. From the analysis of optical and dielectric functions via Kramers Kronig relation, the widening of ∆(LO−TO) was shown by fly ash and slag indicating stable bonding suitable as x-ray shielding and sensor, while high electron loss functions were shown by sludge and bottom ash indicating high potential electronic transition performance. Based on their chemical and physical properties, these industrial wastes are not limited as construction materials and can even be upgraded to more advanced development materials.

Modulating composition and electronic structure enhance the catalytic performance of Co2MO4 (M=Fe, Ni, Cu) for NaBH4 hydrolysis

The synergistic effect between metals is of great significance for improving the performance of materials, but the mechanism of synergistic catalytic of bimetallic has rarely been reported in the hydrolysis of sodium borohydride (NaBH4, SB). In this paper, a flower shaped Co2FeO4 catalyst with high catalytic performance was selected from a series of CoxM3-xO4 (M = Fe, Ni, Cu) catalysts by controlling the composition. Based on the results of XPS characterization and density functional theory (DFT) calculation, the influence of component control on catalytic performance was discussed and explained from the perspective of electronic structure, and the "valence band center" and "D-band center" descriptors were introduced into the SB hydrolysis reaction. The simulation analysis results showed that the synergistic effect between Co–Fe elements resulted in the smallest center shift of the D band, the smallest binding energy of the hydrolysis reaction, and the best promoting effect on the electronic structure, manifested as the best catalytic performance. The calculation results were consistent with the XPS characterization results and the experimental results of hydrolysis performance testing, revealing the principle of bimetallic synergistic effect on catalytic performance.

Prognostic factors and predictive model construction in patients with non-small cell lung cancer: a retrospective study

ObjectiveThe purpose of this study was to construct a nomogram model based on the general characteristics, histological features, pathological and immunohistochemical results, and inflammatory and nutritional indicators of patients so as to effectively predict the overall survival (OS) and progression-free survival (PFS) of patients with non-small cell lung cancer (NSCLC) after surgery.MethodsPatients with NSCLC who received surgical treatment in our hospital from January 2017 to June 2021 were selected as the study subjects. The predictors of OS and PFS were evaluated by univariate and multivariable Cox regression analysis using the Cox proportional risk model. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling for 1 000 times) was used to internally verify the nomogram model, and C-index was used to represent the prediction performance of the nomogram model. The calibration graph method was used to visually represent its prediction compliance, and decision curve analysis (DCA) was used to evaluate the application value of the model.ResultsUnivariate and multivariate analyses were used to identify independent prognostic factors and to construct a nomogram of postoperative survival and disease progression in operable NSCLC patients, with C-index values of 0.927 (907–0.947) and 0.944 (0.922–0.966), respectively. The results showed that the model had high predictive performance. Calibration curves for 1-year, 2-year, and 3-year OS and PFS show a high degree of agreement between the predicted probability and the actual observed probability. In addition, the results of the DCA curve show that the model has good clinical application value.ConclusionWe established a predictive model of survival prognosis and disease progression in patients with non-small cell lung cancer after surgery, which has good predictive performance and can guide clinicians to make the best clinical decision.

Incremental Data Drifting: Evaluation Metrics, Data Generation, and Approach Comparison

Incremental data drifting is a common problem when employing a machine-learning model in industrial applications. The underlying data distribution evolves gradually, e.g., users change their buying preferences on an E-commerce website over time. The problem needs to be addressed to obtain high performance. Right now, studies regarding incremental data drifting suffer from several issues. For one thing, there is a lack of clear-defined incremental drift datasets for examination. Existing efforts use either collected real datasets or synthetic datasets that show two obvious limitations. One is in particular when and of which type of drifts the distribution undergoes is unknown, and the other is that a simple synthesized dataset cannot reflect the complex representation we would normally face in the real world. For another, there lacks of a well-defined protocol to evaluate a learner’s knowledge transfer capability on an incremental drift dataset. To provide a holistic discussion on these issues, we create approaches to generate datasets with specific drift types, and define a novel protocol for evaluation. Besides, we investigate recent advances in the transfer learning field, including Domain Adaptation and Lifelong Learning, and examine how they perform in the presence of incremental data drifting. The results unfold the relationships among drift types, knowledge preservation, and learning approaches.

A digital twin model incorporating generalized metabolic fluxes to identify and predict chronic kidney disease in type 2 diabetes mellitus

We have developed a digital twin-based CKD identification and prediction model that leverages generalized metabolic fluxes (GMF) for patients with Type 2 Diabetes Mellitus (T2DM). GMF digital twins utilized basic clinical and physiological biomarkers as inputs for identification and prediction of CKD. We employed four diverse multi-ethnic cohorts (n = 7072): a Singaporean cohort (EVAS, n = 289) and a North American cohort (NHANES, n = 1044) for baseline CKD identification, and two multi-center Singaporean cohorts (CDMD, n = 2119 and SDR, n = 3627) for 3-year CKD prediction and risk stratification. We subsequently conducted a comprehensive study utilizing a single dataset to evaluate the clinical utility of GMF for CKD prediction. The GMF-based identification model performed strongly, achieving an AUC between 0.80 and 0.82. In prediction, the GMF generated with complete parameters attained high performance with an AUC of 0.86, while with incomplete parameters, it achieved an AUC of 0.75. The GMF-based prediction model utilizing complete inputs is the standard implementation of our algorithm: HealthVector Diabetes®. We have established the GMF digital twin-based model as a robust clinical tool capable of predicting and stratifying the risk of future CKD within a 3-year time horizon. We report the correlation of GMF with basic input parameters, their ability to differentiate between future health states and medication status at baseline, and their capability to quantify CKD progression rates. This holistic methodology provides insights into patients’ health states and CKD progression rates based on GMF metabolic profile differences, enabling personalized care plans.

Impact of homocysteine on acute ischemic stroke severity: possible role of aminothiols redox status

BackgroundAcute ischemic stroke (AIS) is one of the most common cerebrovascular diseases which accompanied by a disruption of aminothiols homeostasis. To explore the relationship of aminothiols with neurologic impairment severity, we investigated four aminothiols, homocysteine (Hcy), cysteine (Cys), cysteinylglycine (CG) and glutathione (GSH) in plasma and its influence on ischemic stroke severity in AIS patients.MethodsA total of 150 clinical samples from AIS patients were selected for our study. The concentrations of free reduced Hcy (Hcy), own oxidized Hcy (HHcy), free reduced Cys (Cys), own oxidized Cys (cysteine, Cyss), free reduced CG (CG) and free reduced GSH (GSH) were measured by our previously developed hollow fiber centrifugal ultrafiltration (HFCF-UF) method coupled with high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The concentration ratio of Hcy to HHcy (Hcy/HHcy), Cys to Cyss (Cys/Cyss) were also calculated. The neurologic impairment severity of AIS was evaluated using National Institutes of Health Stroke Scale (NIHSS). The Spearman correlation coefficient and logistic regression analysis was used to estimate and perform the correlation between Hcy, HHcy, Cys, Cyss, CG, GSH, Hcy/HHcy, Cys/Cyss and total Hcy with NIHSS score.ResultsThe reduced Hcy and Hcy/HHcy was both negatively correlated with NIHSS score in AIS patients with P = 0.008, r=-0.215 and P = 0.002, r=-0.249, respectively. There was no significant correlation of Cys, CG, GSH, HHcy, Cyss, Cys/Cyss and total Hcy with NIHSS score in AIS patients with P value > 0.05.ConclusionsThe reduced Hcy and Hcy/HHcy, not total Hcy concentration should be used to evaluate neurologic impairment severity of AIS patient.

Comparison of HPLC, HPTLC, and In Silico Lipophilicity Parameters Determined for 5-Heterocyclic 2-(2,4-Dihydroxyphenyl)-1,3,4-thiadiazoles

The 5-heterocyclic 2-(2,4-dihydroxyphenyl)-1,3,4-thiadiazoles were obtained as potential biologically active compounds. Lipophilicity is one of the most important physicochemical properties of compounds and was already taken into account during the drug candidates design and development. The lipophilicity of compounds was determined using the computational (log P) and chromatography (log kw, RMw) methods. The experimental ones included the reverse-phase column high performance liquid chromatography RP (HPLC) with C8, C18, phosphatidylcholine (IAM), and cholesterol stationary phases and the thin layer chromatography (RP-HPTLC) with C8 and C18 stationary phases and various organic modifiers under the isocratic conditions. Descriptive statistics, correlation, and PCA analyses were used to compare the obtained results. For lipophilicity estimation of the tested compounds by HPTLC, dioxane and MeOH seem to be particularly beneficial as organic modifiers. The chromatographic lipophilicity parameters log kw (RMw) were well correlated and highly redundant (85%) compared with those calculated. Most compounds possess lipophilicity parameters within the recommended range for drug candidates.

Design of Approximate Tree Multiplier Using Approximate Compressor for Image Processing Applications

Approximate computing enables high performance and efficiency of execution by using the overhead on compute units of a processor to give high speed. The speed and system delay are inversely proportional, necessitating massive parallel processes with massive hardware and power dissipation. Energy and area-efficient systems can be realized by reducing system accuracy and dependability. Approximate computing techniques can be used to reduce the number of computing resources needed for a given task and improve the performance of a system. This can be accomplished by lowering a computational model's accuracy and decreasing complexity, reducing power consumption, latency, and area requirements. This study examines an electrical circuit that performs multiplication of two equal integers and it proposes the use of a carry-in adder with two approximation compressors to reduce the size, latency, and power consumption while maintaining the same level of accuracy as current designs. The suggested algorithms were implemented in Xilinx Vivado and their effectiveness was evaluated using numerical performance metrics, including error rate, power consumption, delay, and power delay product in output result. The compressors suggested are used to implement 8 × 8 and 16 × 16 Dadda multipliers that perform comparably to state-of-the-art approximation multipliers.

Computational Investigation of a Reversible Energy Storage Medium in g-B5N3 Decorated by Lithium.

Graphene-like materials in two dimensions hold great promise for energy storage and transformation applications owing to their distinctive features, such as lightweight composition, porous geometry, etc. Among these materials, a recently discovered unit known as g-B5N3 has demonstrated high performance in energy storage and transformation. In our efforts to enhance its applicability in adsorbing energy gases, we propose a novel composite structure by decorating Li atoms on the surface of pristine g-B5N3. The electronic properties of this composite have been comprehensively investigated using a first-principles method. Our findings reveal that the added Li atoms can be securely anchored on the g-B5N3 with an adsorption energy of -3.01 eV. Furthermore, the Li atom transfers its partial 2s electrons to the g-B5N3, exhibiting considerable electropositivity. These metallic sites effectively polarize the adsorbed H2 molecules, enhancing the mutual electrostatic interactions. Each primitive cell of Li-doped g-B5N3 can adsorb up to 13 H2 molecules, resulting in a storage capacity up to 6.3 wt %. This capacity significantly surpasses the goal of 4.5 wt % set by the U.S. Department of Energy. Furthermore, the typical adsorption energy of -0.209 eV per molecule of H2 aligns with the energy range suitable for reversible hydrogen storage. This study underscores the potential of Li-doped g-B5N3 for energy gas adsorption, shedding light on further advancements in this field.

Tribological synergy of copper‐based metal–organic frameworks, carbon fibers and SiO2 in modifying the friction and wear properties of epoxy composites

AbstractCopper‐based metal–organic frameworks is anticipated to find applications in the field of friction materials owing to its plentiful surface‐active groups and distinctive framework structure. In this study, copper‐based metal–organic frameworks was synthesized through ultrasound‐assisted method and incorporated alone into carbon fiber reinforced epoxy composites or together with SiO2 nanoparticles towards the goal of improving the composites' friction and wear properties. It is revealed that copper‐based metal–organic frameworks alone cannot improve the friction and wear of carbon fiber reinforced epoxy composites simultaneously. The combination of copper‐based metal–organic frameworks and SiO2 nanoparticles was more effective in enhancing both the mechanical and tribological properties of studied composites. The composite material exhibits a friction coefficient of 0.104 under the specified test conditions of 10 MPa and 3.75 m/s. Additionally, the specific wear rate is impressively low, measuring only 5.64 × 10−7 mm3 N/m. Through morphological and chemical analysis on the worn surfaces and transfer films, the functioning mechanism of copper‐based metal–organic frameworks in modifying the mechanical and tribological properties was discussed. It was discovered that a tribological synergy exists between short carbon fibers, copper‐based metal–organic frameworks, and SiO2 fillers, leading to a shift in the wear mechanism of the composite materials from abrasive wear to adhesive wear. Concurrently, a shear‐prone transfer film forms on the surface of the counter steel surfaces. Findings of the present study pave a new route of designing high performance epoxy based tribo‐composites by using metal–organic frameworks.Highlights Cu‐BDC nanosheets were synthesized using ultrasound‐assisted techniques and incorporated as tribological fillers in EP composites. The combined use of Cu‐BDC, SiO2, and SCF fillers synergistically enhances the mechanical and tribological properties of EP composites. The composite material exhibits a friction coefficient of 0.104 under the specified test conditions of 10 MPa and 3.75 m/s, the specific wear rate is impressively low, measuring only 5.64 × 10−7 mm3N/m. During the sliding friction process of the composite materials, Cu‐BDC and SiO2 play a crucial role in reducing SCF pull‐out wear through their anchoring effect. The dynamic coordination bond structure of Cu‐BDC contributes to the formation of uniform and continuous transfer films on counter metal surfaces.

Nonlinear time-reversal interferometry with arbitrary quadratic collective-spin interaction

Abstract Atomic nonlinear interferometry has wide applications in quantum metrology and quantum information science. Here we propose a nonlinear time-reversal interferometry scheme with high robustness and metrological gain based on the spin squeezing generated by arbitrary quadratic collective-spin interaction, which could be described by the Lipkin-Meshkov-Glick (LMG) model. We optimize the squeezing process, encoding process, and anti-squeezing process, finding that the two particular cases of the LMG model, one-axis twisting and two-axis twisting outperform in robustness and precision, respectively. Moreover, we propose a Floquet driving method to realize equivalent time reverse in the atomic system, which leads to high performance in precision, robustness, and operability. Our study sets a benchmark in achieving high precision and robustness in atomic nonlinear interferometry.

High‐performance, semi‐bio‐based degradable epoxy resins and their application to recyclable carbon fiber composites

AbstractEpoxy resins containing dynamic covalent networks enable recycling of carbon fiber composites. However, the simultaneous realization of high performance and mild condition recycling of composites is still a challenge. In the present work, we mixed citric acid epoxy resin with bisphenol A epoxy resin to form a hybrid resin (DER) that meets the requirements of medium temperature curing epoxy resin, and prepared a carbon fiber reinforced resin composite material (DER@CF) that can rapidly degrade and recycle carbon fibers under mild conditions. The Tg of the DER was 125.67 °C, and the tensile strength (79.63 MPa) was comparable to that of the bisphenol A epoxy resin (79.90 MPa). It degraded rapidly after 2 h in ethylene glycol solution at 120 °C. The tensile strength of DER@CF was 825 MPa, and clean fibers could be obtained after 8 h of treatment in ethylene glycol solution at 120 °C. The results of SEM, Raman and tensile tests showed that the recycled fibers were similar to the original fibers in terms of morphology, chemical structure and mechanical properties. © 2024 Society of Chemical Industry.

A Developed Tunnel Ventilation System Modeling for an Intelligent Transportation System

This paper presents a Laplace transform model for an urban tunnel ventilation system. This model allows one to witness higher performance for supervisory control and data acquisition (SCADA) in terms of monitoring and control of an urban area tunnel based on measurement systems. This proposed model illustrates the ventilation control system framework as well as the emergency response system for urban area tunnels such that smoother controllability and higher security in the operation of tunnels can be envisioned. The salient contributions of this work can be stated as a novel method for modeling tunnel ventilation systems and the implementation of an emergency response plan for a futuristic intelligent transportation system. The simulation results exhibit that the proposed model outperforms the ventilation system in the high-density traffic jams and further the efficient operation of the tunnel. Likewise, comparison results and experimental results are addressed to emphasize the validation of this method and to be helpful in proving the reliability of the results obtained in this study. These results show that the ventilation control system reaches the desired CO value either in high-traffic volume conditions or in normal traffic conditions.

Investigation of Proton Exchange Membrane Fuel Cell Performance by Exploring the Synergistic Effects of Reaction Parameters via Power Curve and Impedance Spectroscopy Analysis

In this paper, a comprehensive analysis of the parameters that affect polymer electrolyte membrane fuel-cell performance is presented. Experiments were conducted on a single fuel cell membrane with an active area of 5 cm2. To study the fuel cell operation, parametric studies of temperature, pressure and relative humidity values were conducted under cyclic voltammetry for impedance analysis. The impact of the behavior of all three parameters on the fuel-cell performance were recorded and analyzed. As the temperature increased from 50 °C to 74 °C, the Pt catalyst surface areas demonstrated lower activation losses as the membrane conductivity increased. It is confirmed that an increase in temperature accompanied higher humidity levels to provide sufficient cell hydration that resulted in a higher performance output. The impedance measurements indicate that low humidity levels resulted in higher cell resistance and mass transport losses. As the back pressure increased, the membrane resistance decreased, which also reduced mass transport losses. The results indicate that the important factors affecting the fuel cell performance are mass transport limitation and membrane resistance. Based on the results of this study, the optimum performance can be achieved by operating at higher pressures and temperatures with humidified reactant gases.

Scar tissue characterization to predict arrhythmia recurrence in patients undergoing ventricular tachycardia ablation: cardiac computed tomography compared with cardiac magnetic resonance

Abstract Background The role of imaging in evaluating patients undergoing ventricular tachycardia (VT) ablation is crucial for planning, procedural success, and clinical outcomes. In daily practice, cardiac computed tomography (CCT) assessing wall thinning and late iodine uptake (LI) and cardiac magnetic resonance (CMR) assessing late-gadolinium enhancement (LGE) are most commonly implemented. However, data comparing the two imaging modalities for scar tissue characterization is scarce. Aims To compare the performance of both imaging modalities for scar tissue characterization in ischemic (ICM) and non-ischemic (NICM) patients undergoing VT ablation and predict procedural outcomes. Methods In a retrospective analysis, consecutive patients undergoing both CCT and LGE-CMR before scheduled VT ablation were included. The presence and extent of scar was assessed by means of each imaging modality using dedicated softwares (MUSIC and ADAS). To compare scar distribution and agreement between the two modalities, a scar classification scheme was used for all 17 AHA segments: 0 points (no scar present), 1 point (scar <50% of total segment area), 2 points (scar representing 50-99% of total segment area) or 3 points (scar present in 100% of the segment area).<scar<100%)><scar<100%> Results 36 patients (67±10 years; 97% male; LVEF 39±10%; 72% ischemic) undergoing CCT and LGE-CMR before scheduled VT ablation were included. In the ICM group, mean detected scar burden was higher than in the NICM group on LGE-CMR (total volume: 62.3±32.9g vs. 32.8±9.5g, p<0.001), using wall thinning model (WT)(mean scar area 69.0±45.6 cm2 vs. 23.4±23.6cm2, p=0.005) as well as LI (dense scar area: 39.2±28.1 cm2 vs. 11.0±6.3 cm2 , p=0.005). The absolute score difference per segment and patient between CCT and LGE-CMR was calculated and summed for all patients divided by the number of patients. Differences were more pronounced for NICM compared to ICM and LGE-CMR showed better concordance to LI than WT in both NICMP and ICM (Figure). Total procedure time was 205±68 min (ablation time 28±16 min; fluoroscopy time 15 ± 12 min). During a follow-up period of 19±7 months, 87 sustained VT episodes in 12 patients (33%) were documented. Three patients (8%) underwent a second VT ablation and one patient (3%) died during follow-up. In ICM, total scar volume on LGE-CMR and scar area on LI showed numerically higher predictive value for VT recurrence than total scar area by means of WT (AUC: LGE 0.76, LI 0.78 and WT 0.65 respectively), while in NICM scar characterization by means of WT yielded higher performance to predict VT recurrence than LI or LGE-CMR (AUC: LGE 0.67, LI 0.58, WT 0.83 respectively). Conclusions In patients undergoing VT ablation, both LGE-CMR and CCT are valuable for scar tissue characterization. Late iodine uptake on CCT showed a high concordance with LGE-CMR in both NICM and ICM.</scar<100%></scar<100%)>

Sex Differences in Athletic Performance Response to the Imagery and Mental Toughness of Elite Middle- and Long-Distance Runners

This study aimed to determine whether there is a difference between the levels of imagery and mental toughness in the context of sports performance in male and female athletes. A total of 344 track and field athletes, 205 male (59.6%, 23.3 ± 4.0 years) and 139 female (40.4%, 22.9 ± 4.0 years), voluntarily participated in the study. Imagery Inventory and Mental Toughness Inventory in Sport were used as data collection tools in the study. In the evaluation of athletic performance, athletes were asked about their ranks in the years 2020, 2021, and 2022 and were categorized according to the scoring tables specified by the International Association of Athletics Federation. A MANOVA analysis was used to determine whether there was a difference between low (−2% to +5%), medium (+6 to +11%), and high (+12 to +17%) performers among male and female athletes, and a post hoc analysis was used to determine the source of the difference. According to the present findings, there was no significant difference between the imagery and mental toughness levels of athletes with high, medium, and low performance among male athletes. On the contrary, a significant difference was detected between the imagery and mental toughness levels of female athletes with medium and high performances, showing that athletes in the high-performance range had higher levels of imagery (Eta2 = 8) and mental toughness (Eta2 = 10) than athletes in the medium- and low-performance ranges. The findings of this study show that imagery and emotional intelligence are important factors for sports performance. In this context, coaches and sports psychologists can include these parameters in their training programs to achieve the optimal performance range.

Extraction of essential oil from Salvia fruticosa using a newly developed microwave-assisted distillation system for industrial applications

In this study, an industrial-scale microwave-assisted distillation (MWAD) is designed by combining 12 magnetrons with 1 kW, and the essential oil of the S. fruticosa plant is obtained, as a novelty. Also, the effect of microwave (MW) power applied at different times and powers on essential oil yield (%) and energy consumption is experimentally investigated and the statistical analysis using experimental data is carried out using the Design Expert program. For each test, 5 kg of dried plants as an herb are utilized and placed in a 100-L steam boiler. When the results are examined, the proposed MWAD system reduces the distillation time by half compared to the conventional distillation (CD) system. In terms of energy consumption, there is a huge energy saving due to the time being reduced by half. Moreover, compared to the essential oil yield obtained in the CD system, there is an increase in yield (average value of 15%) in the MWAD system. According to the chemical analysis results, no negative effect of MW power on essential oil quality is observed. However, MW power affects the percentage changes of some terpene groups. As a result, the MWAD system can be safely used in industrial distillation processes as an alternative to CD systems due to its high performance and low energy consumption.

Clamping enables enhanced electromechanical responses in antiferroelectric thin films.

Thin-film materials with large electromechanical responses are fundamental enablers of next-generation micro-/nano-electromechanical applications. Conventional electromechanical materials (for example, ferroelectrics and relaxors), however, exhibit severely degraded responses when scaled down to submicrometre-thick films due to substrate constraints (clamping). This limitation is overcome, and substantial electromechanical responses in antiferroelectric thin films are achieved through an unconventional coupling of the field-induced antiferroelectric-to-ferroelectric phase transition and the substrate constraints. A detilting of the oxygen octahedra and lattice-volume expansion in all dimensions are observed commensurate with the phase transition using operando electron microscopy, such that the in-plane clamping further enhances the out-of-plane expansion, as rationalized using first-principles calculations. In turn, a non-traditional thickness scaling is realized wherein an electromechanical strain (1.7%) is produced from a model antiferroelectric PbZrO3 film that is just 100 nm thick. The high performance and understanding of the mechanism provide a promising pathway to develop high-performance micro-/nano-electromechanical systems.

#1413 High performance of ACLARA calculator of rat creatinine clearance for the chronic follow up of renal function

Abstract Background and Aims A neural network-based calculator to estimate rat creatinine clearance (ClCr), as a measurement of the glomerular filtration rate (GFR), from paired plasma creatinine concentration and body weight data has been recently developed [1]. Like human GFR estimating formulae, ACLARA averts long experimental procedures and reduces animal stress (by obviating the use of individual isolation in metabolic cages). This tool is publicly available for free use among the scientific community (https://idal.uv.es/aclara/). When collated with experimentally measured ClCr, ACLARA performs very well at comparing experiments in the whole, showing almost identical behavior of all experimental groups and conditions. Yet, ACLARA was trained mostly with data from short experiments involving acute changes in renal function, and from young rats. Fewer data from older animals was included in the development of the calculator. Thus, its field performance on longer evolution of renal function in adult rats has not yet been sufficiently validated. Accordingly, the aim of this work was to deepen in the assessment of ACLARA in the long-term evolution of rat ClCr. Method The evolution of measured (mClCr) versus ACLARA-estimated ClCr (eClCr) was compared at different time points over a period of 3 months in 20 male Wistar rats with chronic renal damage and 8 age-matched controls. In total, 176 data pairs of mClCr and eClCr were obtained. On the one hand, mClCr was determined by the usual experimental procedure [2]. Briefly, rats were allocated in metabolic cages to obtain 24-hour urine samples and urine flow (UF). Creatinine concentration was measured in the urine (Cru) and plasma (Crp) by a colorimetric assay based on the Jaffe's reaction, and mCrCl was then calculated as Cru x UF / Crp. On the other hand, eClCr was estimated with the ACLARA calculator from the corresponding Crp and body weight data. A Pearson's correlation study between mClCr and eClCr was carried out. Results Our results reveal that the information provided by the 90-day evolution of mClCr and eClCr is virtually identical at the whole experiment level (see Fig. 1). Furthermore, ACLARA seems to provide slightly more coherent and homogeneous information, as the considerable experimental error introduced by urine collection is averted in eClCr but present in mClCr. At the individual data level, ACLARA-estimated values are slightly lower than the corresponding measurements. The correlation between mClCr and eClCr was highly significant (r Pearson= 0.83; p < 0.0001). Conclusion ACLARA shows high performance at estimating CrCl in rats of growing age. Our results support its use also in chronic studies in which renal function must be evaluated. Funding This research was funded by grants from Instituto de Salud Carlos III (ISCIII), Ministerio de Ciencia e Innovación (PI21/01226 and PI21/00548 co-funded by the European Union; and RICORS2040, RD21/0005/0004, co-funded by the European Union – NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR)) and from Consejería de Educación, Junta de Castilla y León (IES160P20), co-funded by FEDER funds. Joana Mercado-Hernández is recipient of a predoctoral fellowship from the Junta de Castilla y Leon (Spain) and the European Social Fund from the European Commission.