矢量语音传感器微阵列

人工智能的普及促进了语音交互技术的发展,语音传感器阵列作为智能语音交互的硬件前端,成为语音交互领域的前沿研究方向.矢量语音传声器自有的偶极子指向性、零点深度以及阵列体积小便于集成的特点特别符合语音交互技术对硬件设备的要求.基于此,通过采用两组矢量敏感单元"共点正交"形成矢量微阵列实现声源空间锐化波束指向,其不受瑞利限与空间采样率限制,与传统空间离散分布的声压麦克风阵列有着本质区别,是矢量微阵列的核心优势所在.矢量微阵列传声器弥补了现有双麦阵列的不足,具有更为广阔的应用前景,作为智能语音交互的硬件前端,对推动智能语音交互领域的发展具有重要意义.     

传统牦牛酸奶源高产胞外多糖乳酸菌特性及发酵性能

为了研究四川藏区传统牦牛酸奶中高产胞外多糖乳酸菌特性及发酵性能，以本实验室分离出的六株高产胞外多糖乳酸菌为研究对象，以菌株生长量、耐酸性、胆盐耐受力、渗透压耐受力和细胞表面疏水性为指标进行特性研究；以发酵酸奶的凝乳时间、持水力、酸化及后酸化能力、挥发性物质及质构等为指标进行发酵性能研究。菌株的生长曲线表明，6株菌株分别在14 h（218、276、266）、16 h（271、285、231）进入对数生长稳定期，其中编号218的菌株生长量最高，OD值为2.188。耐受性实验结果表明，菌株276具有良好的耐酸能力（P<0.05）；菌株266、218、231耐胆盐的能力较强；6株菌株均具有较好的耐渗透压的能力，其中菌株285对高渗透压的耐受性较强；菌株285和218在两种有机试剂中的疏水性均显著（P<0.05）高于其他菌株，且与十六烷的结合效果较好。发酵试验结果表明，6株菌株所发酵酸奶均在6~8 h内凝固，酸乳在冷藏期间，活菌数均保持在107 CFU/mL以上，均符合发酵剂的标准，其中菌株276的最高为3.22×106 CFU/mL；菌株218发酵制得的酸奶质构特性较好，持水力和酸化能力较其余菌株均最强，分别为60.98%和83 °T；菌株276、266抗后酸化能力较好；菌株231产香性能最优，乙醛含量为24~26 μg/mL，双乙酰含量为1.58~3.73 μg/mL，能够明显改善酸奶的风味。通过综合比较6株高产胞外多糖乳酸菌特性及发酵性能，菌株218为一株性能良好、具有良好稳定性的菌株，可作为乳酸菌发酵剂且具有一定的应用潜力。研究为利用四川藏区传统牦牛酸奶中分离出的高产胞外多糖乳酸菌在发酵乳制品的应用提供理论依据。     

基于禁忌搜索的晶体位置谱分割与校准方法

为满足不同规格晶体探测器对分割校准晶体条响应事件位置数据的需求，开发了一种以禁忌搜索算法为核心，结合UDP数据帧、二维高斯模型及光导折射率的位置信息分割校准方法。实验结果表明，本方法在溢出率为5%时，峰谷比可达1218，空间分辨率达17 mm，晶体条响应位置识别准确度高达99%，滤除了引发伪峰的噪声，避免了过分割问题。在面对多种规格晶体阵列的位置谱时，本方法能依照阵列规格将晶体条区域的响应自动校准编号并输出晶体位置查找表，实现响应事件的精确校准。     

超高效液相色谱-串联质谱法同时检测糕点中6种甜味剂

目的建立超高效液相色谱-串联质谱法同时测定糕点中6种常用合成甜味剂的分析方法。方法选用超纯水作为提取溶剂,涡旋和超声提取后,低温离心,取部分上清液加入正己烷除脂,Waters Atlantis■T3色谱柱、甲醇-5 mmol/L甲酸铵(含0.1%甲酸)作为流动相、亲水亲脂平衡型固相萃取柱HLB(hydrophile-lipophile balance)净化。结果6种甜味剂在质量浓度为10~200 ng/mL的曲线范围内呈良好线性关系,相关系数r均大于0.999,平均加标回收率在85.0%-98.2%之间,相对平均偏差(relative standard deviation,RSD)为1.3%~6.7%。结论该方法具有前处理简单、灵敏度高、检测速度快等优点,适合糖精钠、甜蜜素、三氯蔗糖、阿斯巴甜、阿力甜、纽甜的检测,但不适用于安赛蜜的检测。     

生态封场技术在非正规垃圾堆放场治理中的应用

本文通过对各项治理技术比选,提出了生态封场技术在非正规垃圾堆放场治理中的应用,并结合实际案例给出了详细治理方案.     

某化工厂污水处理运行管理实践

简要介绍某化工厂污水处理装置日常运行管理,通过技术改造及优化调整运行参数,在装置开停工或装置工况异常产生的高负荷冲击下,确保污水生化处理系统稳定运行.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Pressure-induced transparency of MgO,Al2O3, AlN,and cBN ceramics at room temperature

The in situ axial X-ray diffraction patterns of four ceramic powder samples (MgO, Al₂O₃, AlN, and cBN) that were compressed in a diamond anvil cell under uniaxial non-hydrostatic conditions were recorded. The microscopic deviatoric stress as a function of the pressure was determined from the X-ray diffraction peak broadening analysis: the curves increased approximately linearly with the pressure at the initial compression stage and then levelled off under further compression. Pressure-induced transparency was observed in all of the samples under compression, and the pressure at the turning point on the curves of the microscopic deviatoric stress versus pressure corresponded to the pressure at which the samples became transparent. Analysis of the microstructural features of the pressure-induced transparent samples indicated that the compression caused the grains to fracture, and the broken grains bonded with each other. We demonstrated that the ceramics’ pressure-induced transparency was a process during which the grains were squeezed and broken, the pores were close between the grains, and the broken grains were re-bonded under compression.