Reaction-controlled shape evolution and insights into the growth mechanism of CsPbBr3 nanocrystals.

The correlation between structural transformation and optical characteristics of cesium lead bromide (CsPbBr3) nanocrystals (NCs) suggests insights into their growth mechanism and optical performance. Systematic control of reaction parameters led to the successful fabrication of on-demand shape-morphing CsPbBr3 NCs. Transmission electron microscopy observations showed that the shape transformation from nanocubes to microcrystals could be accelerated by increasing the precursor:ligand molar ratio and reaction time. Further evidence for orthorhombic CsPbBr3 NCs was obtained from their selected-area electron diffraction pattern, which exhibits a twin domain induced by the presence of large NCs. Likewise, we observed a substantial decrease in photoluminescence (PL) intensity of CsPbBr3 due to surface decomposition or surface ligand loss resulting from increased size. In addition, fusion of smaller particles having other dimensionality induced the increase in the PL full-width at half maximum. In particular, existence of larger bulk material caused a reduction in the peak intensity in the absorption spectra and a trend of decreasing tendency in intensity of the absorption bands related to bromoplumbate species provided direct evidence of fully converted Cs-oleate.

The inverted U-shaped relationship between corporate social responsibility and default risk: The role of financing constraints.

With increased corporate liquidity and debt repayment pressure, CSR's "insurance" role has received more attention. We conducted a comprehensive empirical analysis of 4988 listed companies in the Chinese context during 2011-2020. Our research has three findings: First, the initial increase in CSR will lead to a rise in default risk. However, once the CSR level exceeds a specific threshold, the default risk decreases as the CSR rises. We tested the robustness of the results by replacing the explanatory and the explained variables and taking into account the lag time effect, which proved the reliability of our research conclusions. Second, the mediation analysis shows financing constraints play an important mediating role in this inverted U-shaped relationship. On the left side of the U-shape, CSR performance intensifies financing constraints, while on the right side, increasing CSR reduces financing constraints. Finally, we confirm heterogeneity in the impact of CSR on the default risk of different enterprises' ownership and size. Our study complements the current literature on the effects of CSR on default risk. We are making policymakers and stakeholders aware of the importance of mandatory CSR disclosure.

The effect of cinnamon supplementation on eating disorder indices among people suffering from binge eating disorder: a randomized controlled trial.

BACKGROUND: Binge eating disorder is one of the main eating disorders that is characterized by recurrent binge eating episodes that lead to complications like high blood pressure, diabetes, dyslipidemia, etc. Many psychological and biological factors can lead to binge eating disorder and one of the main physiological reasons is insulin resistance. Cinnamon is an old favorite that has positive effects on insulin sensitivity. So, we examined the effect of cinnamon on binge eating disorder in this study. METHODS: This study was conducted on 40 binge eating disorder patients with a BMI between 25 and 39.9 kg/m2. They were divided into two groups one of them consumed 6 g of cinnamon per day while the other group consumed 6 g of white wheat as a placebo. Before and after the study we examined weight, height, Body Shape Questionnaire (BSQ), and Binge Eating Scale (BES) scale in all participants and did the statistical analysis. RESULTS: There were no significant differences in baseline characteristics, gender, height, weight, BMI, education, and marriage status between the two groups. There were no significant changes between BSQ, BES, weight, and height after the study either. CONCLUSION: According to our findings, although the weight of the patients in the cinnamon group decreased significantly, after the end of the study, no significant difference was observed in the weight, BMI, and BAS and BSQ indices between the two groups. TRIAL REGISTRATION: The study protocol was registered in the Iran Registry of Clinical Trials (IRCT) center (IRCT code: IRCT20090822002365N26, Registration date: 2021/11/7).

Reverse Electrodialysis with Continuous Random Variation in Nanochannel Shape: Salinity Gradient-Driven Power Generation.

The shape of nanochannels plays a crucial role in the ion selectivity and overall performance of reverse electrodialysis (RED) systems. However, current research on two-dimensional nanochannel shapes is largely limited to a few fixed asymmetric forms. This study explores the impact of randomly shaped nanochannels using dimensionless methods, controlling their randomness by varying their length and shape amplitude. The research systematically compares how alterations in the nanochannel length and shape amplitude influence various system performance parameters. Our findings indicate that increasing the nanochannel length can significantly enhance the system performance. While drastic changes in the nanochannel shape amplitude positively affect the system performance, the most significant improvements arise from the interplay between the nanochannel length and shape amplitude. This compounding effect creates a local optimum, resulting in peak system performance. Within the range of dimensionless lengths from 0 to 30, the system reaches its optimal performance at a dimensionless length of approximately 25. Additionally, we explored two other influencing factors: the nanochannel surface charge density and the concentration gradient of the solution across the nanochannel. Optimal performance is observed when the nanochannel has a high surface charge density and a low concentration gradient, particularly with random shapes. This study advances the theoretical understanding of RED systems in two-dimensional nanochannels, guiding research towards practical operational conditions.

Further evaluation of the shape of atomic Hirshfeld surfaces: M...H contacts and homoatomic bonds.

It is well known that Hirshfeld surfaces provide an easy and straightforward way of analysing intermolecular interactions in the crystal environment. The use of atomic Hirshfeld surfaces has also demonstrated that such surfaces carry information related to chemical bonds which allow a deeper evaluation of the structures. Here we briefly summarize the approach of atomic Hirshfeld surfaces while further evaluating the kind of information that can be retrieved from them. We show that the analysis of the metal-centre Hirshfeld surfaces from structures refined via Hirshfeld Atom Refinement (HAR) allow accurate evaluation of contacts of type M...H, and that such contacts can be related to the overall shape of the surfaces. The compounds analysed were tetraaquabis(3-carboxypropionato)metal(II), [M(C4H3O4)2(H2O)4], for metal(II)/M = manganese/Mn, cobalt/Co, nickel/Ni and zinc/Zn. We also evaluate the sensitivity of the surfaces by an investigation of seemingly flat surfaces through analysis of the curvature functions in the direction of C-C bonds. The obtained values not only demonstrate variations in curvature but also show a correlation with the hybridization of the C atoms involved in the bond.

Fluorescent Polylactic acid composite incorporating lignin-based carbon quantum dots for sustainable 4D printing applications.

Fluorescent 4D printing materials, as innovative materials that combine fluorescent characteristics with 4D printing technology, have attracted widespread interest and research. In this study, green lignin-derived carbon quantum dots (CQDs) were used as the fluorescent module, and renewable poly(propylene carbonate) polyurethane (PPCU) was used for toughening. A new low-cost fluorescent polylactic acid (PLA) composite filament for 4D printing was developed using a simple melt extrusion method. The strength of the prepared composite was maintained at 32 MPa, while the elongation at break increased 8-fold (34 % increase), demonstrating excellent shape fixed ratio (∼99 %), recovery ratio (∼92 %), and rapid shape memory recovery speed. The presence of PPCU prevented fluorescence quenching of the CQDs in the PLA matrix, allowing the composite to emit bright green fluorescence under 365 nm ultraviolet light. The composite exhibited shear thinning behavior and had an ideal melt viscosity for 3D printing. The results obtained demonstrated the versatility of these easy-to-manufacture and low-cost filaments, opening up a novel and convenient method for the preparation of strong, tough, and multifunctional PLA materials, increasing their potential application value.

Sub-okra leaf shape conferred via chromosomal introgression from Gossypium barbadense L. improves photosynthetic productivity in short-season cotton (Gossypium hirsutum L.).

Leaf shape is a vital agronomic trait that affects plant and canopy architecture, yield, and other production attributes of upland cotton. Compared with normal leaves, lobed leaves have potential advantages in improving canopy structure and increasing cotton yield. A chromosomal introgression segment from Gossypium barbadense L. conferring sub-okra leaf shape to Gossypium hirsutum L. was identified on chromosome D01. To determine the effects of this transferred sub-okra leaf shape on the leaf anatomical characteristics, photosynthesis-related traits, and yield of short-season cotton, we performed a field experiment with three sets of near-isogenic lines carrying okra, sub-okra, and normal leaf shape in Lu54 (L54) and Shizao 2 (SZ2) backgrounds. Compared with normal leaves, sub-okra leaves exhibited reduced leaf thickness and smaller leaf mass per area; moreover, the deeper lobes of sub-okra leaves improved the plant canopy structure by decreasing leaf area index by 11.24%-22.84%. Similarly, the intercepted PAR rate of lines with sub-okra leaf shape was also reduced. The chlorophyll content of sub-okra leaves was lower than that of okra and normal leaf shapes; however, the net photosynthetic rate of sub-okra leaves was 8.17%-29.81% higher than that of other leaf shapes at most growth stages. Although the biomass of lines with sub-okra leaf shape was less than that of lines with normal leaves, the average first harvest yield and total yield of lines with the sub-okra leaf shape increased by 6.36% and 5.72%, respectively, compared with those with normal leaves. Thus, improvements in the canopy structure and photosynthetic and physiological characteristics contributed to optimizing the light environment, thereby increasing the yield of lines with sub-okra leaf shape. Our results suggest that the sub-okra leaf trait from G. barbadense L. may have practical applications for cultivating short-season varieties with high photosynthetic efficiency, and improving yield, which will be advantageous for short-season varieties.

Analyzing the Functional Interdependence of Verbal Behavior with Multiaxial Radar Charts.

The functional analysis of complex verbal behavior requires an evaluation of topographically similar responses under multiple sources of control. Traditional graphical displays of behavior were designed to show the manipulation of isolated controlling variables and may not be amenable to displaying the multidimensional properties of complex behavior. Researchers have recently demonstrated the use of multiaxial radar charts for comparing the functional performance of biological systems. Here we extend the use of multidimensional analyses to compare the relative performance distributions of verbal behavior across four potential controlling variables. First, we provide a conceptual analysis of intraverbal and extraverbal control as continua along which stimuli range from formal to thematic and explain how the intersection of these stimulus fields creates a radar chart for multidimensional analysis. Then we demonstrate how data may be gathered through a verbal operant experimental analysis. We employed repeated measures to map the conditioning history of a child with autism spectrum disorder across 2 years of early intensive behavioral intervention and analyzed the results using shape descriptors for quantitative comparisons. We also compared the polygonal language profiles of children with autism against that of a neurotypical peer. Extending a multidimensional analysis to the field of verbal behavior provides the basis for a language growth chart that researchers and clinicians can use to monitor language acquisition over time. We discuss the use of radar charts as a framework for understanding the interdependence of verbal operants and suggest their use for complex analyses of complex verbal behavior. Supplementary Information: The online version contains supplementary material available at 10.1007/s40614-024-00404-6.

Shape Memory Polymers with Patternable Recovery Onset Regulated by Light.

Shape memory polymers (SMPs) show attractive prospects in emerging fields such as soft robots and biomedical devices. Although their typical trigger-responsive character offers the essential shape-changing controllability, having to access external stimulation is a major bottleneck toward many applications. Recently emerged autonomous SMPs exhibit unique stimuli-free shape-shifting behavior with its controllability achieved via a delayed and programmable recovery onset. Achieving multi-shape morphing in an arbitrary fashion, however, is infeasible. In this work, a molecular design that allows to spatio-temporally define the recovery onset of an autonomous shape memory hydrogel (SMH) is reported. By introducing nitrocinnamate groups onto an SMH, its crosslinking density can be adjusted by light. This affects greatly the phase separation kinetics, which is the basis for the autonomous shape memory behavior. Consequently, the recovery onset can be regulated between 0 to 85 min. With masked light, multiple recovery onsets in an arbitrarily defined pattern which correspondingly enable multi-shape morphing can be realized. This ability to achieve highly sophisticated morphing without relying on any external stimulation greatly extends the versatility of SMPs.

OpenSim Moco tracking simulations efficiently replicate predictive simulation results across morphologically diverse shoulder models.

OpenSim Moco enables solving for an optimal motion using Predictive and Tracking simulations. However, Predictive simulations are computationally prohibitive, and the efficacy of Tracking in deviating from its reference is unclear. This study compares Tracking and Predictive approaches applied to the generation of morphology-specific motion in statistically-derived musculoskeletal shoulder models. The signal analysis software, CORA, determined mean correlation ratings between Tracking and Predictive solutions of 0.91 ± 0.06 and 0.91 ± 0.07 for lateral and forward-reaching tasks. Additionally, Tracking provided computational speed-up of 6-8 times. Therefore, Tracking is an efficient approach that yields results equivalent to Predictive, facilitating future large-scale modelling studies.

Super-Durable, Tough Shape-Memory Polymeric Materials Woven from Interlocking Rigid-Flexible Chains.

Developing advanced engineering polymers that combine high strength and toughness represents not only a necessary path to excellence but also a major technical challenge. Here for the first time a rigid-flexible interlocking polymer (RFIP) is reported featuring remarkable mechanical properties, consisting of flexible polyurethane (PU) and rigid polyimide (PI) chains cleverly woven together around the copper(I) ions center. By rationally weaving PI, PU chains, and copper(I) ions, RFIP exhibits ultra-high strength (twice that of unwoven polymers, 91.4 ± 3.3 MPa), toughness (448.0 ± 14.2 MJ m-3), fatigue resistance (recoverable after 10 000 cyclic stretches), and shape memory properties. Simulation results and characterization analysis together support the correlation between microstructure and macroscopic features, confirming the greater cohesive energy of the interwoven network and providing insights into strengthening toughening mechanisms. The essence of weaving on the atomic and molecular levels is fused to obtain brilliant and valuable mechanical properties, opening new perspectives in designing robust and stable polymers.

Untethered Microgrippers for Biopsy in the Upper Urinary Tract.

Untethered microrobots offer the possibility to perform medical interventions in anatomically complex and small regions in the body. Presently, it is necessary to access the upper urinary tract to diagnose and treat Upper Tract Urothelial Carcinoma (UTUC). Diagnostic and treatment challenges include ensuring adequate tissue sampling, accurately grading the disease, achieving completeness in endoscopic treatment, and consistently delivering medications to targeted sites. This work introduces microgrippers (µ-grippers) that are autonomously triggered by physiological temperature for biopsy in the upper urinary tract. The experiments demonstrated that µ-grippers can be deployed using standard ureteral catheters and maneuvered using an external magnetic field. The µ-grippers successfully biopsied tissue samples from ex vivo pig ureters, indicating that the thin-film bilayer springs' autonomous, physiologically triggered actuation exerts enough force to retrieve urinary tract tissue. The quality of these biopsy samples is sufficient for histopathological examination, including hematoxylin and eosin (H&E) and GATA3 immunohistochemical staining. Beyond biopsy applications, the µ-grippers' small size, wafer-scale fabrication, and multifunctionality suggest their potential for statistical sampling in the urinary tract. Experimental data and clinical reports underscore this potential through statistical simulations that compare the efficacy of µ-grippers with conventional tools, such as ureteroscopic forceps and baskets.

Population-based in silico modeling of anatomical shape variation of the knee and its impact on joint loading in knee osteoarthritis.

Anatomical knee joint features and osteoarthritis (OA) severity are associated, however confirming causals link to altered knee loading is challenging. This study leverages statistical shape models (SSM) to investigate the relationship between joint shape/alignment and knee loading during gait in knee OA (KOA) patients to understand their contribution to elevated medial knee loading in OA. Musculoskeletal (MSK) models were created for the mean as well as the first eight SSM principal modes of variation (-3,-2,-1, +1, +2, +3 standard deviations for each mode) and used as input to a MSK modeling framework. Using an identical KOA gait pattern (i.e., joint kinematics and ground reaction forces), we ran simulations for each MSK model and evaluated medial compartment loading magnitude and contact distribution at the instant of first and second peak of knee joint loading. An increase in external rotation, posterior tibia translation and a decrease in medial joint space and medial femoral condylar size predisposed the medial compartment knee joint to overloading during gait. This was coupled with an anterior and medial shift in contact location with increasing external rotated tibial position and increasing posterior tibial translation with respect to the femur. Next, results also highlighted a posterior shift of the medial compartment loading location with decreasing medial joint space. This study provides important population-based insights on how knee shape and alignment predispose individuals with KOA to elevated medial compartmental knee loading. This information can be crucial in assessing the risk for medial KOA development and progression.

Heatmap-Based Active Shape Model for Landmark Detection in Lumbar X-ray Images.

Medical staff inspect lumbar X-ray images to diagnose lumbar spine diseases, and the analysis process is currently automated using deep-learning techniques. The detection of landmarks is necessary in the automatic process of localizing the position and identifying the morphological features of the vertebrae. However, detection errors may occur owing to the noise and ambiguity of images, as well as individual variations in the shape of the lumbar vertebrae. This study proposes a method to improve the robustness of landmark detection results. This method assumes that landmarks are detected by a convolutional neural network-based two-step model consisting of Pose-Net and M-Net. The model generates a heatmap response to indicate the probable landmark positions. The proposed method then corrects the landmark positions using the heatmap response and active shape model, which employs statistical information on the landmark distribution. Experiments were conducted using 3600 lumbar X-ray images, and the results showed that the landmark detection error was reduced by the proposed method. The average value of maximum errors decreased by 5.58% after applying the proposed method, which combines the outstanding image analysis capabilities of deep learning with statistical shape constraints on landmark distribution. The proposed method could also be easily integrated with other techniques to increase the robustness of landmark detection results such as CoordConv layers and non-directional part affinity field. This resulted in a further enhancement in the landmark detection performance. These advantages can improve the reliability of automatic systems used to inspect lumbar X-ray images. This will benefit both patients and medical staff by reducing medical expenses and increasing diagnostic efficiency.

Generalisation to novel exemplars of learned shape categories based on visual and auditory spatial cues does not benefit from multisensory information.

Although the integration of information across multiple senses can enhance object representations in memory, how multisensory information affects the formation of categories is uncertain. In particular, it is unclear to what extent categories formed from multisensory information benefit object recognition over unisensory inputs. Two experiments investigated the categorisation of novel auditory and visual objects, with categories defined by spatial similarity, and tested generalisation to novel exemplars. Participants learned to categorise exemplars based on visual-only (geometric shape), auditory-only (spatially defined soundscape) or audio-visual spatial cues. Categorisation to learned as well as novel exemplars was then tested under the same sensory learning conditions. For all learning modalities, categorisation generalised to novel exemplars. However, there was no evidence of enhanced categorisation performance for learned multisensory exemplars. At best, bimodal performance approximated that of the most accurate unimodal condition, although this was observed only for a subset of exemplars within a category. These findings provide insight into the perceptual processes involved in the formation of categories and have relevance for understanding the sensory nature of object representations underpinning these categories.

SDF4CHD: Generative modeling of cardiac anatomies with congenital heart defects.

Congenital heart disease (CHD) encompasses a spectrum of cardiovascular structural abnormalities, often requiring customized treatment plans for individual patients. Computational modeling and analysis of these unique cardiac anatomies can improve diagnosis and treatment planning and may ultimately lead to improved outcomes. Deep learning (DL) methods have demonstrated the potential to enable efficient treatment planning by automating cardiac segmentation and mesh construction for patients with normal cardiac anatomies. However, CHDs are often rare, making it challenging to acquire sufficiently large patient cohorts for training such DL models. Generative modeling of cardiac anatomies has the potential to fill this gap via the generation of virtual cohorts; however, prior approaches were largely designed for normal anatomies and cannot readily capture the significant topological variations seen in CHD patients. Therefore, we propose a type- and shape-disentangled generative approach suitable to capture the wide spectrum of cardiac anatomies observed in different CHD types and synthesize differently shaped cardiac anatomies that preserve the unique topology for specific CHD types. Our DL approach represents generic whole heart anatomies with CHD type-specific abnormalities implicitly using signed distance fields (SDF) based on CHD type diagnosis. To capture the shape-specific variations, we then learn invertible deformations to morph the learned CHD type-specific anatomies and reconstruct patient-specific shapes. After training with a dataset containing the cardiac anatomies of 67 patients spanning 6 CHD types and 14 combinations of CHD types, our method successfully captures divergent anatomical variations across different types and the meaningful intermediate CHD states across the spectrum of related CHD diagnoses. Additionally, our method demonstrates superior performance in CHD anatomy generation in terms of CHD-type correctness and shape plausibility. It also exhibits comparable generalization performance when reconstructing unseen cardiac anatomies. Moreover, our approach shows potential in augmenting image-segmentation pairs for rarer CHD types to significantly enhance cardiac segmentation accuracy for CHDs. Furthermore, it enables the generation of CHD cardiac meshes for computational simulation, facilitating a systematic examination of the impact of CHDs on cardiac functions.

Nanoporous, Ultrastiff, and Transparent Plastic-like Polymer Hydrogels Enabled by Hydrogen Bonding-Induced Self-Assembly.

Most natural supporting tissues possess both exceptional mechanical strength, a significant amount of water, and the anisotropic structure, as well as nanoscale assembly. These properties are essential for biological processes, but have been challenging to emulate in synthetic materials. In an effort to achieve simultaneous improvement of these trade-off features, a hydrogen bonding-induced self-assembly strategy was introduced to create nanoporous plastic-like polymer hydrogels. Multiple hydrogen bonding-mediated networks and nanoporous orientation structures endow transparent hydrogels with remarkable mechanical robustness. They exhibit Young's modulus of up to 223.7 MPa and a breaking strength of up to 10.3 MPa, which are superior to those of most common polymer hydrogels. The uniform porous nanostructures of hydrogen-bonded hydrogels contribute to a significantly larger specific surface area compared to conventional hydrogels. This allows for the retention of high mechanical properties in environments with a high water content of 70 wt %. A rubbery stage is observed during the heating process, which can reverse and reshape the manufacture of objects with various desired 2D or 3D shapes using techniques such as origami and kirigami. Finally, as a proof-of-concept, the outstanding mechanical properties of poly(MAA-co-AA-co-NVCL) hydrogel, combined with its high water content, make it suitable for applications such as smart temperature monitors, multilevel information anticounterfeiting, and artificial muscles.

A shape memory cationized chitosan sponge loaded with thrombin for high-effective hemostasis and antibacterial activity.

This study presents a thrombin-loaded cationized chitosan (TCCS) sponge with highly effective hemostatic and antibacterial activity. The TCCS sponge, prepared using a multistep method, features a porous structure, favorable mechanical properties, excellent water absorption ability, and shape recovery triggered by water or blood. The TCCS sponge exhibited strong antibacterial activity against Methicillin-resistant Staphylococcus aureus and Escherichia coli. Additionally, it demonstrated enhanced procoagulant and hemostatic efficacy in rat tail amputation and rat liver perforation wound models compared to commercial hemostats. Furthermore, the sponge exhibited favorable biocompatibility and biosafety. These findings suggest that the TCCS sponge has substantial potential for practical applications in managing severe hemorrhages and bacterial infections.

Magnetization dynamics in single and trilayer nanowires.

We have studied the magnetization dynamics of single Py(t) (t= 20 nm, 50 nm) and trilayer [Py(50)/Pd(tPd)/Py(20)] nanowire arrays fabricated over large areas using deep ultraviolet lithography technique. The dynamic properties are sensitive to the field orientation and magnetic film thicknesses. A single resonant mode corresponding to the excitations at the bulk part of the wire is detected in all the single-layer nanowire arrays. Furthermore, the spacer layer thickness influenced the dynamic properties in trilayer samples due to the different coupling mechanisms. A single resonant mode is observed intPd= 2 nm trilayer nanowires with a sharp frequency jump from 13 GHz to 15 GHz across the reversal regime. This indicates the exchange coupling and the coherence in magnetization precession in the ferromagnetic layers. On the other hand, wires with 10 nm-spacer display two well-resolved modes separated by ∼3 GHz with a gradual change in frequency across the reversal regime from-26mT to-46mT, indicating the presence of long-range dipolar interactions instead of exchange coupling. The spacer layer of the proposed spin-valve-type structure can be tailored for desired microwave splitters or combiners.

A Novel Design of a Torsional Shape Memory Alloy Actuator for Active Rudder.

SMA actuators are a group of lightweight actuators that offer advantages over conventional technology and allow for simple and compact solutions to the increasing demand for electrical actuation. In particular, an increasing number of SMA torsional actuator applications have been published recently due to their ability to supply rotational motion under load, resulting in advantages such as module simplification and the reduction of overall product weight. This paper presents the conceptual design, operating principle, experimental characterization and working performance of torsional actuators applicable in active rudder in aeronautics. The proposed application comprises a pair of SMA torsion springs, which bi-directionally actuate the actuator by Joule heating and natural cooling. The experimental results confirm the functionality of the torsion springs actuated device and show the rotation angle of the developed active rudder was about 30° at a heating current of 5 A. After the design and experiment, one of their chief drawbacks is their relatively slow operating speed in rudder positioning, but this can be improved by control strategy and small modifications to the actuator mechanism described in this work.