一种潜在5-HT1A脑受体显像剂99Tcm-Bicine/HYNIC-MPP2的制备及其生物性能

优化合成了含有1-(2-甲氧基苯基)哌嗪(MPP)结构的配体2-(4-(2-甲氧基苯基)哌嗪基)乙胺-6-叔丁基氧羰基肼基吡啶-3-甲酸(HYNIC-MPP2).在室温下以N,N-二(2-羟基乙基)氨基乙酸(Bicine)为共配体制备得到配合物~(99)Tc~m-Bicine/HYNIC-MPP2,其放射化学纯度大于95%,并且在6 h内保持稳定.脂水分配系数和电泳实验结果表明,该放射性标记配合物是水溶性和电中性的.正常小鼠体内生物分布实验结果表明,~(99)Tc~m-Bicine/HYNIC-MPP2有一定的脑摄取(注射后2 min时为0.31%ID/g).脑区域分布及抑制实验显示,该配合物在5-HT_(1A)受体含量丰富的海马组织有较高摄取(注射后2 min时为1.00%ID/g),而在受体含量低的小脑组织中摄取也低(注射后2 min时为0.63%ID/g).抑制后,海马摄取降低较多(注射后2 min时为0.42%ID/g),而小脑摄取则无明显变化.抑制前后海马/小脑比值分别为1.59和0.89.由此可见该标记配合物与5-HT_(1A)受体具有一定特异性结合,是一种新的潜在5-HT_(1A)受体显像剂.     

Effect of temperature on studtite stability: Thermogravimetry and differential scanning calorimetry investigations

The main objective of this work is the study of the influence of temperature on the stability of the uranyl peroxide tetrahydrate (UO₂O₂ · 4H₂O) studtite, which may form on the spent nuclear fuel surface as a secondary solid phase. Preliminary results on the synthesis of studtite in the laboratory at different temperatures have shown that the solid phases formed when mixing hydrogen peroxide and uranyl nitrate depends on temperature. Studtite is obtained at 298 K, meta-studtite (UO₂O₂ · 2H₂O) at 373 K, and meta-schoepite (UO₃ · nH₂O, with n < 2) at 423 K. Because of the temperature effect on the stability of uranyl peroxides, a thermogravimetric (TG) study of studtite has been performed. The main results obtained are that three transformations occur depending on temperature. At 403 K, studtite transforms to meta-studtite, at 504 K, meta-studtite transforms to meta-schoepite, and, finally, at 840 K, meta-schoepite transforms to U₃O₈. By means of the differential scanning calorimetry the molar enthalpies of the transformations occurring at 403 and 504 K have been determined to be −42 ± 10 and −46 ± 2 kJ mol⁻¹, respectively.     

Al-Si共晶合金与1Cr18Ni9Ti不锈钢的相容性研究

用粉末冶金法制备了Al-Si共晶合金与1Cr18Ni9Ti不锈钢反应堆扩散偶。采用电子显微镜（SEM）、能谱分析仪（EDS）、X射线衍射仪（XRD）D究了扩散偶在560℃和650℃时的相容性及扩散层形成机理。结果表明,扩散温度对两种材料之间的相容性有显著影响;650℃时,Al-Si共晶合金与1Cr18Ni9Ti之间通过浸润和扩散反应形成了比较明显的扩散层。XRD谱也表明,扩散层中存在Fe2Al5化合物;560℃时Al-Si共晶合金与1Cr18Ni9Ti之间仅发生固相反应,形成的扩散层很薄,二者相容性较好。     

Influence of Methanol on Prion Reduction during High Temperature and High Pressure Oleochemical Processes

Prion‐reduction in standard biodiesel processes is caused by acidic and alkaline conditions. In the alternative RepCat biodiesel process, efficient prion‐reduction can be achieved by high‐temperature/pressure. However, a possible increase in thermostability of prions in the presence of methanol during these conditions has not previously been investigated, and is verified in this work. Samples are spiked with prions, treated with methanol, and incubated at 220 °C at 80 bar for 30 min. No traces of protease‐resistant prion protein (as proxy for prions) are detected in tallow or glycerine (as the final by‐product) after treatment. Serial dilutions of spiked prions show at least 6 log₁₀ prion reduction. More importantly, similar effects are detected using milder conditions of 200 °C at 70 bar for 15 min, representing the worst‐case conditions of the process. In conclusion, this study shows that methanol does not increase the thermostability of prions and the RepCat process can efficiently eliminate prions and is therefore safe for the usage of category 1 tallow. Practical Applications: The study further supports the applicability of RepCat process in reducing prion‐contamination in the presence of methanol. Furthermore, the conditions leads to a considerable reduction of prions in glycerine obtained as by‐product.     

Compiler compatible 5.66 Mb/mm2 8T 1R1W register file in 14 nm FinFET technology

1-read/1-write (1R1W) register file (RF) is a popular memory configuration in modern feature rich SoCs requiring significant amount of embedded memory. A memory compiler is constructed using the 8T RF bitcell spanning a range of instances from 32 b to 72 Kb. An 8T low-leakage bitcell of 0.106 μm² is used in a 14 nm FinFET technology with a 70 nm contacted gate pitch for high-density (HD) two-port (TP) RF memory compiler which achieves 5.66 Mb/mm² array density for a 72 Kb array which is the highest reported density in 14 nm FinFET technology. The density improvement is achieved by using techniques such as leaf-cell optimization (eliminating transistors), better architectural planning, top level connectivity through leaf-cell abutment and minimizing the number of unique leaf-cells. These techniques are fully compatible with memory compiler usage over the required span. Leakage power is minimized by using power-switches without degrading the density mentioned above. Self-induced supply voltage collapse technique is applied for write and a four stack static keeper is used for read Vmin improvement. Fabricated test chips using 14 nm process have demonstrated 2.33 GHz performance at 1.1 V/25 °C operation. Overall V_min of 550 mV is achieved with this design at 25 °C. The inbuilt power-switch improves leakage power by 12x in simulation. Approximately 8% die area of a leading 14 nm SoC in commercialization is occupied by these compiled RF instances.     

A novel multi-focus image fusion method based on distributed compressed sensing

Multi-focus image fusion aims to produce an all-in-focus image by merging multiple partially focused images of the same scene. The main work is identifying the focused region and then composing all the focused regions. In this paper, a novel efficient multi-focus image fusion method based on distributed compressed sensing (DCS) is proposed. Firstly, the low-frequency and high-frequency images are obtained by comparing the variance of the source images, which are further utilized to get the low-frequency and high-frequency dictionaries. Secondly, DCS using joint sparsity model-1 (JSM-1) is applied to reconstruct the precise high-frequency images. Thirdly, the decision map is obtained based on all the high-frequency images and then improved by the morphological processing. Finally, the focused pixels are chosen from the source images through the decision map. Experimental results indicate that the proposed DCS-based method can be competitive with or even outperform some state-of-the-art methods in terms of both visual and quantitative metric evaluations.     

Controllable 1D Patterned Assembly of Colloidal Quantum Dots on PbSO4 Nanoribbons

Control of the 1D self‐assembly pattern of colloidal quantum dots (QDs) on PbSO₄ nanoribbon (NRb) templates is achieved. The internal structure of the NRbs is investigated by X‐ray diffraction, revealing the isotropic packing of the PbSO₄ nanoclusters in the NRbs. Colloidal QDs in a chloroform/hexane mixture are adsorbed onto the region close to the edges of the NRbs and form a 1D assembly of straight single line or double lines by controlling the amount of OAm. This is the first demonstration of a densely packed 1D self‐assembly of colloidal QDs with a straight line pattern without the use of any molecular bridge or adhesive. Atomic force microscopy measurements of the NRbs show depressions in the phase profile along the width of the NRbs, corresponding to the position of the 1D QD chain. The amount of adsorbed QDs on the NRbs in solution decreases as the addition of OAm increases, suggesting that additional OAm prevents interaction between the QDs and NRbs but facilitates the uniform adsorption of the 1D assembly. The low‐dimensional self‐assembly of colloidal QDs in this study opens up the possibility for the creation of anisotropically assembled QD superstructures.     

A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.