Neoadjuvant targeted immunotherapy followed by surgical resection versus upfront surgery for hepatocellular carcinoma with macrovascular invasion: A multicenter study.

Background: This study aimed to investigate the safety and efficacy of preoperative targeted immunotherapy followed by surgical resection for hepatocellular carcinoma (HCC) patients with macrovascular invasion. Method: Clinical information of HCC patients with macrovascular invasion was collected from four medical centers. These patients were divided into two cohorts: the upfront surgery group (n=40) and the neoadjuvant group (n=22). Comparisons between the two groups were made with appropriate statistical methods. Results: HCC Patients with macrovascular invasion in the neoadjuvant group were associated with increased incidence of postoperative ascites (72.73% vs. 37.5%, P=0.008), but shorter postoperative hospital stay (10 days vs. 14 days, P=0.032). Furthermore, targeted immunotherapy followed by surgical resection significantly reduced the postoperative recurrence rate at both 3 months and 1 year (9% versus 28.9%, 32.1% versus 67.9%, respectively; P=0.018), but increased the postoperative nononcologic mortality rate within 1 year (20.1% vs. 2.8%; P= 0.036). Conclusion: For HCC patients with macrovascular invasion, preoperative targeted immunotherapy significantly decreased the postoperative tumor recurrence rate while maintaining relative safety, but such a treatment may also result in chronic liver damage and increased risk of nononcologic mortality.

Monolithic PMN-39PT nanograting-assisted second harmonic generation enhancement.

Second harmonic generation plays a vital role in frequency conversion which mutually promotes the laser technology and allows the wavebands extension of new coherent source. The monolithic crystals are supposed to be a superior choice for harmonic generation due to long interaction distance, however, the phase-mismatch brought a sharp reduction in the conversion efficiency. Although birefringent phase-matching and quasi-phase-matching techniques are commonly utilized to fill the phase gap in monolithic crystals, these techniques are limited by the natural refractive index of crystal and the domain engineering, respectively. In recent years, subwavelength structures evolve as a flexible scheme to realize phase matching by engineering the geometry features of crystals. Here, structured nanogratings are designed and fabricated on a monolithic PMN-39PT (Pb(Mg1/3Nb2/3)O3-0.39PbTiO3) substrate, a novel ferroelectric crystal with promising optical prospect, for enhancing second harmonic generation, where birefringent or quasi phase-matching is hard to achieve. The nanograting-assisted second harmonic generation enhancement is observed which is not limited by the availability of thin crystalline films. Meanwhile, a boost in the second harmonic signal synchronously promotes the cascading third harmonic generation. This method may provide an alternative solution for enhanced harmonic generation on monolithic substrates and develop potential nonlinear optical materials for frequency conversion.

Flexophotovoltaic Effect and Above-Band-Gap Photovoltage Induced by Strain Gradients in Halide Perovskites.

We have measured the flexophotovoltaic effect of single crystals of halide perovskites MAPbBr_{3} and MAPbI_{3}, as well as the benchmark oxide perovskite SrTiO_{3}. For halide perovskites, the flexophotovoltaic effect is found to be orders of magnitude larger than for SrTiO_{3}, and indeed large enough to induce photovoltages bigger than the band gap. Moreover, we find that in MAPbI_{3} the flexophotovoltaic effect is additional to a native bulk photovoltaic response that is switchable and ferroelectric-like. The results suggest that strain gradient engineering can be a powerful tool to modify the photovoltaic output even in already well-established photovoltaic materials.

Ultrahigh Energy Storage Density and Efficiency in Orthorhombic PLZST Antiferroelectric Ceramics via Composition Regulation.

PbZrO3-based antiferroelectric (AFE) ceramic materials have emerged as potential candidates for the next generation of high-energy multilayer ceramic capacitors (MLCCs) because of their distinctive characteristics of double hysteresis loops. The energy storage efficiency of orthorhombic AFE ceramics with ultrahigh storage density is relatively low, which hinders their practical application. In this study, the low efficiency limit of PLZST-based orthorhombic ceramics was overcome by precisely adjusting the Sn4+ content in the (Pb0.95Ca0.02La0.02)(Zr0.99-xSnxTi0.01)O3 AFE ceramics. On one hand, the addition of Sn4+ disrupts the original long-range dipole and improves the rapid response of polarization reversal under the applied voltage. As a result, the difference in electric hysteresis under an electric field is reduced, leading to a significant improvement in energy storage efficiency. On the other hand, increasing the Sn4+ content suppresses the formation of oxygen vacancies, inhibiting grain growth and strengthening grain bonding. This results in ceramics with a high breakdown field strength. Ultimately, the resulting PLCZST ceramics reveal an expressively improved recoverable energy density of 10.2 J cm-3 together with a high energy efficiency of 91.4% under a high applied electric field of 560 kV cm-1. The present study demonstrates the tunability of performance in orthorhombic PLZST AFE ceramics, thereby introducing a ceramic material with exceptional energy storage capabilities for MLCC applications.

Sevelamer reverses liver fibrosis by deactivation of hepatic stellate cells.

Liver fibrosis is a chronic liver disease characterized by a progressive wound healing response caused by chronic liver injury. Currently, there are no approved clinical treatments for liver fibrosis. Sevelamer is used clinically to treat hyperphosphatemia and has shown potential therapeutic effects on liver diseases. However, there have been few studies evaluating the therapeutic effects of sevelamer on liver fibrosis, and the specific mechanisms are still unclear. In this study, we investigated the antifibrotic effects of sevelamer-induced low inorganic phosphate (Pi) stress in vitro and in vivo and analyzed the detailed mechanisms. We found that low Pi stress could inhibit the proliferation of activated hepatic stellate cells (HSCs) by promoting apoptosis, effectively suppressing the migration and epithelial-mesenchymal transition (EMT) of hepatic stellate cells. Additionally, low Pi stress significantly increased the antioxidant stress response. It is worth noting that low Pi stress indirectly inhibited the activation and migration of HSCs by suppressing transforming growth factor ß (TGF-ß) expression in macrophages. In a rat model of liver fibrosis, oral administration of sevelamer significantly decreased blood phosphorus levels, improved liver function, reduced liver inflammation, and increased the antioxidant stress response in the liver. Our study revealed that the key mechanism by which sevelamer inhibited liver fibrosis involved binding to gastrointestinal phosphate, resulting in a decrease in blood phosphorus levels, the downregulation of TGF-ß expression in macrophages, and the inhibition of HSC migration and fibrosis-related protein expression. Therefore, our results suggest that sevelamer-induced low Pi stress can attenuate hepatic stellate cell activation and inhibit the progression of liver fibrosis, making it a potential option for the treatment of liver fibrosis and other refractory chronic liver diseases.

Moderate Fields, Maximum Potential: Achieving High Records with Temperature-Stable Energy Storage in Lead-Free BNT-Based Ceramics.

The increasing awareness of environmental concerns has prompted a surge in the exploration of lead-free, high-power ceramic capacitors. Ongoing efforts to develop lead-free dielectric ceramics with exceptional energy-storage performance (ESP) have predominantly relied on multi-component composite strategies, often accomplished under ultrahigh electric fields. However, this approach poses challenges in insulation and system downsizing due to the necessary working voltage under such conditions. Despite extensive study, bulk ceramics of (Bi0.5Na0.5)TiO3 (BNT), a prominent lead-free dielectric ceramic family, have seldom achieved a recoverable energy-storage (ES) density (Wrec) exceeding 7 J cm-3. This study introduces a novel approach to attain ceramic capacitors with high ESP under moderate electric fields by regulating permittivity based on a linear dielectric model, enhancing insulation quality, and engineering domain structures through chemical formula optimization. The incorporation of SrTiO3 (ST) into the BNT matrix is revealed to reduce the dielectric constant, while the addition of Bi(Mg2/3Nb1/3)O3 (BMN) aids in maintaining polarization. Additionally, the study elucidates the methodology to achieve high ESP at moderate electric fields ranging from 300 to 500 kV cm-1. In our optimized composition, 0.5(Bi0.5Na0.4K0.1)TiO3-0.5(2/3ST-1/3BMN) (B-0.5SB) ceramics, we achieved a Wrec of 7.19 J cm-3 with an efficiency of 93.8% at 460 kV cm-1. Impressively, the B-0.5SB ceramics exhibit remarkable thermal stability between 30 and 140 °C under 365 kV cm-1, maintaining a Wrec exceeding 5 J cm-3. This study not only establishes the B-0.5SB ceramics as promising candidates for ES materials but also demonstrates the feasibility of optimizing ESP by modifying the dielectric constant under specific electric field conditions. Simultaneously, it provides valuable insights for the future design of ceramic capacitors with high ESP under constraints of limited electric field.

Ultrahigh Electrostrictive Effect in Lead-Free Ferroelectric Ceramics Via Texture Engineering.

The electrostrictive effect, which induces strain in ferroelectric ceramics, offers distinct advantages over its piezoelectric counterpart for high-precision actuator applications, including anhysteretic behavior even at high frequencies, rapid reaction times, and no requirement for poling. Historically, commercially available electrostrictive materials have been lead oxide-based. However, global restrictions on the use of lead in electronic components necessitate the exploration of lead-free electrostrictive ceramics with a high strain performance. Although various engineering strategies for producing materials with high strain have been proposed, they typically come at the expense of increased strain hysteresis. Here, we describe the extraordinary electrostrictive response of (Ba0.95Ca0.05)(Ti0.88Sn0.12)O3 (BCTS) ceramics with ultrahigh electrostrictive strain and negligible hysteresis achieved through texture engineering leveraging the anisotropic intrinsic lattice contribution. The BCTS ceramics exhibit a high unipolar strain of 0.175%, a substantial electrostrictive coefficient Q33 of 0.0715 m4 C-2, and an ultralow hysteresis of less than 0.8%. Notably, the Q33 value is three times greater than that of high-performance lead-based Pb(Mg1/3Nb2/3)O3 electrostrictive ceramics. Multiscale structural analyses demonstrate that the electrostrictive effect dominates the BCTS strain response. This research introduces a novel approach to texture engineering to enhance the electrostrictive effect, offering a promising paradigm for future advancements in this field.

Determination of major and trace elements in plant samples by inductively coupled plasma optical emission spectrometry with deep eutectic solvent extraction based on choline chloride and carboxylic acids.

A rapid, precise, and environmentally friendly approach utilizing an ultrasound assisted deep eutectic solvent-based extraction method was developed for the extraction of Ca, Fe, K, Mg, Mn, Na, P, S and Zn from plant samples. The investigation was conducted on deep eutectic solvents that are based on choline chloride and carboxylic acids. The determination of target analytes in the extracts was carried out using inductively coupled plasma-optical emission spectrometry (ICP-OES). The DESs based on malic acid were found to exhibit the highest extraction recovery values (95-106%). The parameters affecting the extraction of target analytes were optimized using standard reference materials. The target analytes can be effectively extracted from plant samples using 0.5 g of DESs and ultrasonication for 40 minutes. The determination results of the reference samples indicated that the relative error (RE) was below 15.1%, and the relative standard deviation (RSD) was less than 6.3%, demonstrating excellent accuracy and precision. The proposed method was employed to quantify target analytes in actual plant samples. The accuracy of this method was not significantly different from that of the microwave digestion method. The proposed method has been demonstrated to be a valid approach for the determination of target elements in actual plant samples.

Irreversible repolarization of tumour-associated macrophages by low-Pi stress inhibits the progression of hepatocellular carcinoma.

Numerous studies have shown the positive correlation between high levels of Pi and tumour progression. A critical goal of macrophage-based cancer therapeutics is to reduce anti-inflammatory macrophages (M2) and increase proinflammatory antitumour macrophages (M1). This study aimed to investigate the relationship between macrophage polarization and low-Pi stress. First, the spatial populations of M2 and M1 macrophages in 22 HCC patient specimens were quantified and correlated with the local Pi concentration. The levels of M2 and M1 macrophage markers expressed in the peritumour area were higher than the intratumour levels, and the expression of M2 markers was positively correlated with Pi concentration. Next, monocytes differentiated from THP-1 cells were polarized against different Pi concentrations to investigate the activation or silencing of the expression of p65, IκB-α and STAT3 as well as their phosphorylation. Results showed that low-Pi stress irreversibly repolarizes tumour-associated macrophages (TAMs) towards the M1 phenotype by silencing stat6 and activating p65. Moreover, HepG-2 and SMCC-7721 cells were cultured in conditioned medium to investigate the innate anticancer immune effects on tumour progression. Both cancer cell lines showed reduced proliferation, migration and invasion, as epithelial-mesenchymal transition (EMT) was inactivated. In vivo therapeutic effect on the innate and adaptive immune processes was validated in a subcutaneous liver cancer model by the intratumoural injection of sevelamer. Tumour growth was significantly inhibited by the partial deprivation of intratumoural Pi as the tumour microenvironment under low-Pi stress is more immunostimulatory. The anticancer immune response, activated by low-Pi stress, suggests a new macrophage-based immunotherapeutic modality.

Entity-Graph Enhanced Cross-Modal Pretraining for Instance-Level Product Retrieval.

Our goal in this research is to study a more realistic environment in which we can conduct weakly-supervised multi-modal instance-level product retrieval for fine-grained product categories. We first contribute the Product1M datasets and define two real practical instance-level retrieval tasks that enable evaluations on price comparison and personalized recommendations. For both instance-level tasks, accurately identifying the intended product target mentioned in visual-linguistic data and mitigating the impact of irrelevant content are quite challenging. To address this, we devise a more effective cross-modal pretraining model capable of adaptively incorporating key concept information from multi-modal data. This is accomplished by utilizing an entity graph, where nodes represented entities and edges denoted the similarity relations between them. Specifically, a novel Entity-Graph Enhanced Cross-Modal Pretraining (EGE-CMP) model is proposed for instance-level commodity retrieval, which explicitly injects entity knowledge in both node-based and subgraph-based ways into the multi-modal networks via a self-supervised hybrid-stream transformer. This could reduce the confusion between different object contents, thereby effectively guiding the network to focus on entities with real semantics. Experimental results sufficiently verify the efficacy and generalizability of our EGE-CMP, outperforming several SOTA cross-modal baselines like CLIP Radford et al. 2021, UNITER Chen et al. 2020 and CAPTURE Zhan et al. 2021.

[Mechanism of gigantol in transmembrane transport in human lens epithelial cells].

Gigantol is a phenolic component of precious Chinese medicine Dendrobii Caulis, which has many pharmacological activities such as prevent tumor and diabetic cataract. This paper aimed to investigate the molecular mechanism of gigantol in transmembrane transport in human lens epithelial cells(HLECs). Immortalized HLECs were cultured in vitro and inoculated in the laser scanning confocal microscopy(LSCM) medium at 5 000 cells/mL. The fluorescence distribution and intensity of gigantol marked by fluorescence in HLECs were observed by LSCM, and the absorption and distribution of gigantol were expressed as fluorescence intensity. The transmembrane transport process of gigantol in HLECs were monitored. The effects of time, temperature, concentration, transport inhibitors, and different cell lines on the transmembrane absorption and transport of gigantol were compared. HLECs were inoculated on climbing plates of 6-well culture plates, and the ultrastructure of HLECs was detected by atomic force microscopy(AFM) during the transmembrane absorption of non-fluorescent labeled gigantol. The results showed that the transmembrane absorption of gigantol was in time and concentration-dependent manners, which was also able to specifically target HLECs. Energy and carrier transport inhibitors reduced gigantol absorption by HLECs. During transmembrane process of gigantol, the membrane surface of HLECs became rougher and presented different degrees of pits, indicating that the transmembrane transport of gigantol was achieved by active absorption of energy and carrier-mediated endocytosis.

Depressing relaxation and conduction loss of polar polymer materials by inserting bulky charge traps for superior energy storage performance in high-pulse energy storage capacitor applications.

Polymer-based dielectrics are chiefly used in high-pulse energy storage capacitors for their high breakdown strength, prominent processability, and low cost. Nevertheless, state-of-the-art commercial polymer-based dielectrics such as biaxially oriented polypropylene (BOPP), cannot satisfy the high energy density requirement in many fields because of their low permittivity. Limited success has been achieved in developing polar polymeric dielectrics with high energy density because of the quickly increased energy loss from polarization relaxation and charge conduction under a high electric field and temperature. To achieve high energy density and low loss in polar polymer dielectrics simultaneously, electron-deficient vinyl quinoline (VQQ) units are pre-copolymerized with methyl methacrylate (MMA) followed by blending with a PMMA matrix. The bulky and electron-deficient VQQs have successfully depressed the relaxation of PMMA and significantly decreased charge conduction under an elevated electric field. As a result, a rather high energy discharging efficiency (over 90%) could be finely maintained up to 800 MV m-1, and an energy density of 16.1 J cm-3 could be obtained, which are much better than those of reported polymer dielectrics. The strong space charge trapping effect of the low content of VQQ is well addressed by thermally stimulated depolarization currents (TSDC) and density functional theory analysis (DFT) of increasing breakdown strength, energy density and discharging efficiency. This work offers a promising strategy for achieving high energy density and low loss in polar polymer dielectrics for their commercial application in energy storage capacitors.

Temperature phase transitions in silver niobate and lithium tantalate-modified silver niobate ceramics.

The temperature behaviour of 0.955 AgNbO3-0.045 LiTaO3 and AgNbO3 ceramics was studied in the range from 10 to 415 K using Raman spectroscopy. Ab initio calculations of the Raman spectra in the Pmc21 phase of AgNbO3 were carried out using three potentials (A-PZ, PBE, and PBEsol) for spectral interpretation. The peculiarities in the Raman spectra in AgNbO3 ceramics are observed and explained. The differences in the spectra of the 0.955 AgNbO3-0.045 LiTaO3 and AgNbO3 ceramics are shown. The temperatures of the structural changes in the 0.955 AgNbO3-0.45 LiTaO3 and AgNbO3 ceramics were discussed. A structural phase transition below 120 K was observed in silver niobate. A phase transition was observed at 310 K and below 150 K in 0.955 AgNbO3-0.045 LiTaO3.

Enhanced Energy Storage Properties in Lead-Free (Na0.5Bi0.5)0.7Sr0.3TiO3-Based Relaxor Ferroelectric Ceramics through a Cooperative Optimization Strategy.

Although relaxor ferroelectrics have been widely investigated owing to their various advantages, there are still impediments to boosting their energy-storage density (Wrec) and energy-storage efficiency (η). In this paper, we propose a cooperative optimization strategy for achieving comprehensive outstanding energy-storage performance in (Na0.5Bi0.5)0.7Sr0.3TiO3 (NBST)-based ceramics by triggering a nonergodic-to-ergodic transformation and optimizing the forming process. The first step of substituting NaNbO3 (NN) for NBST generated an ergodic state and induced polar nanoregions under the guidance of a phase-field simulation. The second step was to apply a viscous polymer process (VPP) to the 0.85NBST-0.15NN ceramics, which reduced porosity and increased compactness, resulting in a significant polarization difference and high breakdown strength. Consequently, 0.85NBST-0.15NN-VPP ceramics optimized by this cooperative two-step strategy possessed improved energy-storage characteristics (Wrec = 7.6 J/cm3, η = 90%) under 410 kV/cm as well as reliable temperature adaptability within a range of 20-120 °C, outperforming most reported (Na0.5Bi0.5) TiO3-based ceramics. The improved energy-storage performance validates the developed ceramics' practical applicability as well as the advantages of implementing a cooperative optimization technique to fabricate similar high-performance dielectric ceramics.

Machine learning algorithms for integrating clinical features to predict intracranial hemorrhage in patients with acute leukemia.

BACKGROUND: Intracranial hemorrhage (ICH) in acute leukemia (AL) patients leads to high morbidity and mortality, treatment approaches for ICH are generally ineffective. Thus, early identification of which subjects are at high risk of ICH is of key importance. Currently, machine learning can achieve well predictive capability through constructing algorithms that simultaneously exploit the information coming from clinical features. METHODS: After rigid data preprocessing, 42 different clinical features from 948 AL patients were used to train different machine learning algorithms. We used the feature selection algorithms to select the top 10 features from 42 clinical features. To test the performance of the machine learning algorithms, we calculated area under the curve (AUC) values from receiver operating characteristic (ROC) curves along with 95% confidence intervals (CIs) by cross-validation. RESULTS: With the 42 features, RF exhibited the best predictive power. After feature selection, the top 10 features were international normalized ratio (INR), prothrombin time (PT), creatinine (Cr), indirect bilirubin (IBIL), albumin (ALB), monocyte (MONO), platelet (PLT), lactic dehydrogenase (LDH), fibrinogen (FIB) and prealbumin (PA). Among the top 10 features, INR, PT, Cr, IBIL and ALB had high predictive performance with an AUC higher than 0.8 respectively. CONCLUSIONS: The RF algorithm exhibited a higher cross-validated performance compared with the classical algorithms, and the selected important risk features should help in individualizing aggressive treatment in AL patients to prevent ICH. Efforts that will be made to test and optimize in independent samples will warrant the application of such algorithm and predictors in the future.

Modeling and control of cable-driven continuum robot used for minimally invasive surgery.

Continuum robot has great advantages in minimally invasive surgery (MIS) due to the slenderness and dexterity. But the friction and backlash result in the low trajectory tracking accuracy. This paper aims to study the transmission process of the driving force and the error compensation method. The statics is performed considering the frictional transmission process, and the variation of friction force with driving force is revealed by the model. The hysteresis effect of the tip trajectory is revealed. Then the relationship between the load history and the robot shape is studied, next, the deflection of the robot subject to the different loading forces can be predicted. The correctness of the mechanical model is verified by numerical simulation and experiments. Furthermore, the control methods according to the cable length and the driving force are compared respectively, and a method of error compensation according to the cable length is worked out considering the mechanical model. The rationality of the compensation method is validated by experiment. The results show that the compensation method based on cable length greatly improves the control accuracy, and the maximum deviation is 1.08 mm. The established model and compensation method create conditions for clinical application of the proposed continuum robot.

Augmented reality for stroke rehabilitation during COVID-19.

BACKGROUND: The lack of the rehabilitation professionals is a global issue and it is becoming more serious during COVID-19. An Augmented Reality Rehabilitation System (AR Rehab) was developed for virtual training delivery. The virtual training was integrated into the participants' usual care to reduce the human trainers' effort so that the manpower scarcity can be eased. This also resulted in the reduction of the contact rate in pandemics. OBJECTIVE: To investigate the feasibility of the AR Rehab-based virtual training when integrated into the usual care in a real-world pandemic setting, by answering questions of whether the integrated trials can help fulfill the training goal and whether the trials can be delivered when resources are limited because of COVID-19. METHODS: Chronic stroke participants were randomly assigned to either a centre-based group (AR-Centre) or a home-based group (AR-Home) for a trial consisting of 20 sessions delivered in a human-machine integrated intervention. The trial of the AR-Centre was human training intensive with 3/4 of each session delivered by human trainers (PTs/OTs/Assistants) and 1/4 delivered by the virtual trainer (AR Rehab). The trial of the AR-Home was virtual training intensive with 1/4 and 3/4 of each session delivered by human and virtual trainers, respectively. Functional assessments including Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and Lower Extremity (FMA-LE), Functional Ambulation Category (FAC), Berg Balance Scale (BBS), Barthel Index (BI) of Activities of Daily Living (ADL), and Physical Component Summary (SF-12v2 PCS) and Mental Component Summary (SF-12v2 MCS) of the 12-Item Short Form Health Survey (SF-12v2), were conducted before and after the intervention. User experience (UX) using questionnaires were collected after the intervention. Time and human resources required to deliver the human and virtual training, respectively, and the proportion of participants with clinical significant improvement were also used as supplementary measures. RESULTS: There were 129 patients from 10 rehabilitation centres enrolled in the integrated program with 39 of them were selected for investigation. Significant functional improvement in FMA-UE (AR-Centre: p = 0.0022, AR-Home: p = 0.0043), FMA-LE (AR-Centre: p = 0.0007, AR-Home: p = 0.0052), SF-12v2 PCS (AR-Centre: p = 0.027, AR-Home: p = 0.036) were observed in both groups. Significant improvement in balance ability (BBS: p = 0.0438), and mental components (SF-12v2 MCS: p = 0.017) were found in AR-Centre group, while activities of daily living (BI: p = 0.0007) was found in AR-Home group. Contact rate was reduced by 30.75-72.30% within AR-All, 0.00-60.00% within AR-Centre, and 75.00-90.00% within AR-Home. CONCLUSION: The human-machine integrated mode was effective and efficient to reduce the human rehabilitation professionals' effort while fulfilling the training goals. It eased the scarcity of manpower and reduced the contact rate during the pandemics.

Competition between Ferroelectric and Ferroelastic Domain Wall Dynamics during Local Switching in Rhombohedral PMN-PT Single Crystals.

The possibility to control the charge, type, and density of domain walls allows properties of ferroelectric materials to be selectively enhanced or reduced. In ferroelectric-ferroelastic materials, two types of domain walls are possible: pure ferroelectric and ferroelastic-ferroelectric. In this paper, we demonstrated a strategy to control the selective ferroelectric or ferroelastic domain wall formation in the (111) single-domain rhombohedral PMN-PT single crystals at the nanoscale by varying the relative humidity level in a scanning probe microscopy chamber. The solution of the corresponding coupled electro-mechanical boundary problem allows explaining observed competition between ferroelastic and ferroelectric domain growth. The reduction in the ferroelastic domain density during local switching at elevated humidity has been attributed to changes in the electric field spatial distribution and screening effectiveness. The established mechanism is important because it reveals a kinetic nature of the final domain patterns in multiaxial materials and thus provides a general pathway to create desirable domain structure in ferroelectric materials for applications in piezoelectric and optical devices.

Identifying the kind behind SMILES-anatomical therapeutic chemical classification using structure-only representations.

Anatomical Therapeutic Chemical (ATC) classification for compounds/drugs plays an important role in drug development and basic research. However, previous methods depend on interactions extracted from STITCH dataset which may make it depend on lab experiments. We present a pilot study to explore the possibility of conducting the ATC prediction solely based on the molecular structures. The motivation is to eliminate the reliance on the costly lab experiments so that the characteristics of a drug can be pre-assessed for better decision-making and effort-saving before the actual development. To this end, we construct a new benchmark consisting of 4545 compounds which is with larger scale than the one used in previous study. A light-weight prediction model is proposed. The model is with better explainability in the sense that it is consists of a straightforward tokenization that extracts and embeds statistically and physicochemically meaningful tokens, and a deep network backed by a set of pyramid kernels to capture multi-resolution chemical structural characteristics. Its efficacy has been validated in the experiments where it outperforms the state-of-the-art methods by 15.53% in accuracy and by 69.66% in terms of efficiency. We make the benchmark dataset, source code and web server open to ease the reproduction of this study.