High sensitivity face shear magneto-electric composite array for weak magnetic field sensing

© 2020 Author(s). A magnetic field sensor is designed and fabricated using a piezoelectric face shear mode Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT)/Metglas magneto-electric (ME) composite. An outstanding ME coupling coefficient up to 1600 V/(cm Oe) was experimentally achieved, being ∼50% higher than the value from the extensional PMN-PT/Metglas ME composite with the same volume. The detection limit was found to be 2 × 10-6 Oe for the DC magnetic field, while it was 2 × 10-8 Oe for the AC magnetic field. The sensitivity of the face shear mode PMN-PT/Metglas ME composite is about one order of magnitude higher than that of a 32 extensional mode PMN-PT/Metglas based ME composite in sensing a weak DC magnetic field. A sensing array was also designed based on the ME composite to image weak DC magnetic fields, demonstrating a great potential promising for sensing weak magnetic fields

Crystal growth, structure and thermal properties of noncentrosymmetric single crystals PrCa4O(BO3)3+

Noncentrosymmetric praseodymium calcium oxyborate single crystals, PrCa4O(BO3)3 (PrCOB), were grown by the Czochralski technique. The monoclinic unit cell parameters were found to be a = 8.177 Å, b = 16.157 Å, c = 3.629 Å and Z = 2 with space group Cm. Crystal density was measured using the Archimedes method, being on the order of 3.47 g cm-3. Thermal properties of PrCOB were investigated, where the specific heat was found to be 0.63 J g-1 °C-1 at room temperature, increasing to 0.85 J g-1°C-1 at 700°C. The thermal expansion coefficients were measured to be α11 = 7.99, α22 = 4.90 and α33 = 9.46 (10-6/°C), respectively. In addition, thermal diffusivity λ22 and thermal conductivity κ22 as a function of temperature were studied, where λ22 was observed to decrease from 0.89 to 0.58 mm2 s-1, while κ22 was found to maintain the same value, being ∼1.90 W m-1°C-1 over the temperature range of 20-700°C. 2013 The Royal Society of Chemistry

Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness

Surgical action triplet recognition provides a better understanding of the surgical scene. This task is of high relevance as it provides to the surgeon with context-aware support and safety. The current go-to strategy for improving performance is the development of new network mechanisms. However, the performance of current state-of-the-art techniques is substantially lower than other surgical tasks. Why is this happening? This is the question that we address in this work. We present the first study to understand the failure of existing deep learning models through the lens of robustness and explainabilty. Firstly, we study current existing models under weak and strong $\delta-$perturbations via adversarial optimisation scheme. We then provide the failure modes via feature based explanations. Our study revels that the key for improving performance and increasing reliability is in the core and spurious attributes. Our work opens the door to more trustworthiness and reliability deep learning models in surgical science

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios

Multi-object tracking in traffic videos is a crucial research area, offering immense potential for enhancing traffic monitoring accuracy and promoting road safety measures through the utilisation of advanced machine learning algorithms. However, existing datasets for multi-object tracking in traffic videos often feature limited instances or focus on single classes, which cannot well simulate the challenges encountered in complex traffic scenarios. To address this gap, we introduce TrafficMOT, an extensive dataset designed to encompass diverse traffic situations with complex scenarios. To validate the complexity and challenges presented by TrafficMOT, we conducted comprehensive empirical studies using three different settings: fully-supervised, semi-supervised, and a recent powerful zero-shot foundation model Tracking Anything Model (TAM). The experimental results highlight the inherent complexity of this dataset, emphasising its value in driving advancements in the field of traffic monitoring and multi-object tracking.Comment: 17 pages, 7 figure

Dissolution of cellulose in ionic liquid–DMSO mixtures : roles of DMSO/IL ratio and the cation alkyl chain length

The dissolution behavior of cellulose in the mixtures of dimethyl sulfoxide (DMSO) and different ionic liquids (ILs) at 25 °C was studied. High solubility of cellulose was reached in the mixtures of ILs and DMSO at mole fractions of 1:2, 1:2, and 1:1 for 1-butyl-3-methylimidazolium acetate, 1-propyl-3-methylimidazolium acetate, and 1-ethyl-3-methylimidazolium acetate, respectively. At high DMSO/IL molar ratios (10:1–2:1), a longer alkyl chain of the IL cation led to higher cellulose solubility. However, shorter cation alkyl chains favored cellulose dissolution at 1:1. Rheological, Fourier transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (NMR) measurements were used to understand cellulose dissolution. It was found out that the increase of the DMSO ratio in binary mixtures caused higher cellulose solubility by decreasing the viscosity of systems. For cations with longer alkyl chains, stronger interaction between the IL and cellulose and higher viscosity of DMSO/IL mixtures were observed. The new knowledge obtained here could be useful to the development of cost-effective solvent systems for biopolymers

The origin of ultrahigh piezoelectricity in relaxor-ferroelectric solid solution crystals

The discovery of ultrahigh piezoelectricity in relaxor-ferroelectric solid solution single crystals is a breakthrough in ferroelectric materials. A key signature of relaxor-ferroelectric solid solutions is the existence of polar nanoregions, a nanoscale inhomogeneity, that coexist with normal ferroelectric domains. Despite two decades of extensive studies, the contribution of polar nanoregions to the underlying piezoelectric properties of relaxor ferroelectrics has yet to be established. Here we quantitatively characterize the contribution of polar nanoregions to the dielectric/piezoelectric responses of relaxor-ferroelectric crystals using a combination of cryogenic experiments and phase-field simulations. The contribution of polar nanoregions to the room-temperature dielectric and piezoelectric properties is in the range of 50-80%. A mesoscale mechanism is proposed to reveal the origin of the high piezoelectricity in relaxor ferroelectrics, where the polar nanoregions aligned in a ferroelectric matrix can facilitate polarization rotation. This mechanism emphasizes the critical role of local structure on the macroscopic properties of ferroelectric materials

A Comprehensive Method for Assessing Meat Freshness Using Fusing Electronic Nose, Computer Vision, and Artificial Tactile Technologies

The traditional methods cannot be used to meet the requirements of rapid and objective detection of meat freshness. Electronic nose (E-Nose), computer vision (CV), and artificial tactile (AT) sensory technologies can be used to mimic humans’ compressive sensory functions of smell, look, and touch when making judgement of meat quality (freshness). Though individual E-Nose, CV, and AT sensory technologies have been used to detect the meat freshness, the detection results vary and are not reliable. In this paper, a new method has been proposed through the integration of E-Nose, CV, and AT sensory technologies for capturing comprehensive meat freshness parameters and the data fusion method for analysing the complicated data with different dimensions and units of six odour parameters of E-Nose, 9 colour parameters of CV, and 4 rubbery parameters of AT for effective meat freshness detection. The pork and chicken meats have been selected for a validation test. The total volatile base nitrogen (TVB-N) assays are used to define meat freshness as the standard criteria for validating the effectiveness of the proposed method. The principal component analysis (PCA) and support vector machine (SVM) are used as unsupervised and supervised pattern recognition methods to analyse the source data and the fusion data of the three instruments, respectively. The experimental and data analysis results show that compared to a single technology, the fusion of E-Nose, CV, and AT technologies significantly improves the detection performance of various freshness meat products. In addition, partial least squares (PLS) is used to construct TVB-N value prediction models, in which the fusion data is input. The root mean square error predictions (RMSEP) for the sample pork and chicken meats are 1.21 and 0.98, respectively, in which the coefficient of determination () is 0.91 and 0.94. This means that the proposed method can be used to effectively detect meat freshness and the storage time (days)

pH-Responsive Cross-Linked Low Molecular Weight Polyethylenimine as an Efficient Gene Vector for Delivery of Plasmid DNA Encoding Anti-VEGF-shRNA for Tumor Treatment

RNA interference (RNAi) is a biological process through which gene expression can be inhibited by RNA molecules with high selectivity and specificity, providing a promising tool for tumor treatment. Two types of molecules are often applied to inactivate target gene expression: synthetic double stranded small interfering RNA (siRNA) and plasmid DNA encoding short hairpin RNA (shRNA). Vectors with high transfection efficiency and low toxicity are essential for the delivery of siRNA and shRNA. In this study, TDAPEI, the synthetic derivative of low-molecular-weight polyethylenimine (PEI), was cross-linked with imine bonds by the conjugation of branched PEI (1.8 kDa) and 2,5-thiophenedicarboxaldehyde (TDA). This biodegradable cationic polymer was utilized as the vector for the delivery of plasmid DNA expressing anti-VEGF-shRNA. Compared to PEI (25 kDa), TDAPEI had a better performance since experimental results suggest its higher transfection efficiency as well as lower toxicity both in cell and animal studies. TDAPEI did not stimulate innate immune response, which is a significant factor that should be considered in vector design for gene delivery. All the results suggested that TDAPEI delivering anti-VEGF-shRNA may provide a promising method for tumor treatment

Impact of biogenic SOA loading on the molecular composition of wintertime PM2.5 in urban Tianjin: an insight from Fourier transform ion cyclotron resonance mass spectrometry

Biomass burning is one of the key sources of urban aerosols in the North China Plain, especially in winter when the impact of secondary organic aerosols (SOA) formed from biogenic volatile organic compounds (BVOCs) is generally considered to be minor. However, little is known about the influence of biogenic SOA loading on the molecular composition of wintertime organic aerosols. Here, we investigated the water-soluble organic compounds in fine particles (PM2.5) from urban Tianjin by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Our results show that most of the CHO and CHON compounds were derived from biomass burning; they contain O-poor and highly unsaturated compounds with aromatic rings, which are sensitive to photochemical reactions, and some of which probably contribute to light-absorbing chromophores. Under moderate to high SOA loading conditions, the nocturnal chemistry is more efficient than photooxidation to generate secondary CHO and CHON compounds with high oxygen content. Under low SOA-loading, secondary CHO and CHON compounds with low oxygen content are mainly formed by photochemistry. Secondary CHO compounds are mainly derived from oxidation of monoterpenes. But nocturnal chemistry may be more productive to sesquiterpene-derived CHON compounds. In contrast, the number- and intensity-weight of S-containing groups (CHOS and CHONS) increased significantly with the increase of biogenic SOA-loading, which agrees with the fact that a majority of the S-containing groups are identified as organosulfates and nitrooxy-organosulfates that are derived from the oxidation of BVOCs. Terpenes may be potential major contributors to the chemical diversity of organosulfates and nitrooxy-organosulfates under photo-oxidation. While the nocturnal chemistry is more beneficial to the formation of organosulfates and nitrooxy-organosulfates under low SOA-loading. The SOA-loading is an important factor associating with the oxidation degree, nitrate group content and chemodiversity of nitrooxy-organosulfates. Furthermore, our study suggests that the hydrolysis of nitrooxy-organosulfates is a possible pathway for the formation of organosulfates.</p