Paper mill sludge as a renewable substrate for the production of acetone-butanol-ethanol using Clostridium sporogenes NCIM 2337

In the present study, pre-treated paper mill sludge (PMS) was evaluated extensively as a substrate for production of acetone-butanol-ethanol using Clostridium sporogenes NCIM 2337. The PMS was subjected to three types of pre-treatment methods namely alkali, mechanical, and thermal treatment and was analyzed by SEM. The pre-treatment of PMS by alkali was observed to be more effective over the other pre-treatment methods. The alkali pre-treated sludge was then made to undergo fermentation, which showed the conventional process of acidogenesis followed by solventogenesis. The acetone, butanol, and ethanol concentration for 15% alkali pre-treated PMS was estimated to be maximum.     

Health benefits of orally administered anti-IL-10 antibody in milk-fed dairy calves

The primary objective of this randomized controlled trial was to determine whether anti-IL-10 egg yolk antibodies fed upon arrival to a calf ranch would lower the prevalence of Cryptosporidium parvum shedding in naturally challenged preweaned dairy calves. The secondary objectives included measuring the effect of anti-IL-10 antibodies on calf health, performance, and shedding of less common diarrheal pathogens. A total of 133 calves, enrolled at 24 to 72 h of age, received a daily dose of 0.96 g of egg yolk powder with anti-IL-10 antibodies (MAB, n = 71) or without anti-IL-10 antibodies (MEP, n = 62) split between 2 feedings for the first 11 d on feed at a calf ranch. Daily health evaluations were completed for 15 d after arrival and on d 56. Digital weights were collected at enrollment and d 56, and hipometer weights were collected at enrollment and d 7 and 56. Packed cell volume and serum total protein concentration were measured at enrollment and on d 7 and 14. Fecal pH was measured at enrollment and on d 5 and 14, and fecal pathogen (C. parvum, coronavirus, rotavirus, and Salmonella spp.) shedding was assessed at d 5 and 14. Continuous outcomes were compared between groups using a Student's t-test or Wilcoxon rank sum test. Fecal pathogen shedding at d 14, respiratory disease at d 56, and antibiotic usage were compared using relative risk (RR) and chi-squared test. Fecal pH (median and interquartile range) on d 14 was 6.65 (6.39–6.99) and 6.52 (5.97–6.81) for MAB and MEP, respectively. On d 56, the risk of respiratory disease was lower for MAB compared with MEP (RR = 0.40; confidence interval = 0.16–0.99). The risk for antibiotic treatment was lower for MAB- compared with MEP-treated calves (RR = 0.38; confidence interval = 0.17–0.88). The risk of shedding rotavirus was higher in MAB (RR = 1.38; confidence interval = 1.10–1.81) calves. After multivariable analyses, hipometer weights (least squares means ± standard error) were 1.7 ± 0.8 kg greater on d 56 in MAB compared with MEP; however, ADG was 0.04 ± 0.02 kg/d lower in MAB calves. Total health score, diarrhea days, average respiratory score, packed cell volume, and serum total protein were not affected by feeding anti-IL-10 egg antibodies. In summary, feeding anti-IL-10 antibodies was associated with increased fecal pH, reduced risk of respiratory disease later in the preweaning period, and decreased antibiotic usage despite higher rotavirus infection. These findings might be associated with improved mucosal immunity, enhanced host defenses, or reduced susceptibility and warrant further investigation.     

基于卷积神经网络的葡萄叶片氮含量识别方法

为实现对葡萄叶片氮素含量快速、便捷的识别，在卷积神经网络VGG-16网络结构基础上，将数据增广后的图像按不同梯度划分进行模型训练，通过十折交叉验证法探究最佳的训练集与验证集分配比例，并构建4个不同深度的网络模型进行训练对比，采用全局平均池化代替全连接层约简网络参数量。训练结果表明，氮含量梯度设为0.70%、0.35%和0.175%时，室内简单背景识别准确率分别为85.9%、76.2%和71.1%；晴天室外复杂背景下识别准确率分别为44.6%、35.0%和30.4%。研究结果表明利用VGG-16建立的网络学习模型对葡萄叶片氮含量识别提供了一种新的便捷方法，对农业信息化和智能化技术应用具有一定促进作用。     

帕金森氏病关联miRNAs的功能和调控

帕金森病（Parkinson's disease, PD）是一种老年期常见的神经系统退行性疾病，致病过程复杂，其发病机制尚未明确，目前普遍认为帕金森病的发生与环境、遗传和年龄等多个因素有关。microRNAs（miRNAs）是一种内源性的小分子非编码RNAs，在转录后水平调控人类基因组中约1/3的基因。大量研究表明，帕金森病与miRNAs存在密切关联，在PD的发生发展、诊断甚至治疗过程中起到重要作用。本综述讨论了最近研究报道的和帕金森病相关的miRNAs，并分析了miRNAs的特异性表达在帕金森病的致病机制和诊断中发挥的作用。     

Phospholipid Cyclosporine Prodrugs Targeted at Inflammatory Bowel Disease (IBD) Treatment: Design,Synthesis, and in Vitro Validation

Novel phospholipid (PL)-cyclosporine conjugates were prepared and studied as potential prodrugs for inflammatory bowel disease (IBD). Our approach relies on phospholipase A₂ (PLA₂), which is overexpressed in the inflamed intestinal tissues, as the prodrug activator to potentially release cyclosporine at the site of inflammation. PL-cyclosporine prodrug conjugates with methylene linkers of various lengths between the sn-2 position of the PL and cyclosporine were synthesized and evaluated for in vitro activation. Surprisingly, despite previous work indicating that conjugates with six methylene linkers between the lipid and drug would suffer rapid enzymatic hydrolysis, with cyclosporine this was not observed. However, compounds with longer linkers (n=10, 12 methylene units) display complete release of the drug by PLA₂-catalyzed hydrolysis, thus demonstrating the importance and profound impact of structural fine-tuning. This study represents a proof-of-concept for our hypothesis and a first step towards a truly targeted IBD treatment with cyclosporine that could be administered throughout the GI tract.     

Hierarchical learning using deep optimum-path forest

Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested in developing tools for the automatic identification of Parkinson’s disease using machine learning and the concept of BoVW. The proposed approach concerns a hierarchical-based learning technique to design visual dictionaries through the Deep Optimum-Path Forest classifier. The proposed method was evaluated in six datasets derived from data collected from individuals when performing handwriting exams. Experimental results showed the potential of the technique, with robust achievements.     

基于视觉颜色感知——光学相似的图像去雾方法

针对雾霾环境影响致使户外获取的图像质量严重下降问题，提出了一种基于视觉颜色感知—光学相似的图像去雾方法。充分利用人眼感知颜色的视觉机理，结合图像的相似性原理，构造了光学相似度函数，建立了新的基于视觉颜色感知—光学相似的图像去雾模型并设计相关算法，进而进行仿真验证。仿真实验结果表明，提出的方法在对有雾图像清晰化处理过程中效果明显，并与现有的图像去雾方法在主观视觉和客观量化方面进行图像去雾效果对比，进一步表明提出的方法在清晰化含雾图像处理中取得了较好的效果。     

改进的卷积神经网络单幅图像超分辨率重建

针对经典的基于卷积神经网络的单幅图像超分辨率重建方法网络较浅、提取的特征少、重建图像模糊等问题，提出了一种改进的卷积神经网络的单幅图像超分辨率重建方法，设计了由密集残差网络和反卷积网络组成的新型深度卷积神经网络结构。原始低分辨率图像输入网络，利用密集残差学习网络获取更丰富的有效特征并加快特征梯度流动，其次通过反卷积层将图像特征上采样到目标图像大小，再利用密集残差学习高维特征，最后融合不同卷积核提取的特征得到最终的重建图像。在Set5和Set14数据集上进行了实验，并和Bicubic、K-SVD、SelfEx、SRCNN等经典重建方法进行了对比，重建出的图像在整体清晰度和边缘锐度方面更好，另外峰值信噪比（PSNR）平均分别提高了2.69?dB、1.68?dB、0.74?dB和0.61?dB。实验结果表明，该方法能够获取更丰富的细节信息，得到更好的视觉效果，达到了图像超分辨率的增强任务。     

不同发射率下红外热图像的非稳态温度场测量研究

通过分析红外测温公式,研究物体发射率对红外热图像测温精度的影响,并找出影响物体发射率的因素。根据经典计算方法,发现了物体发射率在红外热图像测温应用中的局限。从红外热图像的角度对发射率的计算进行了建模,基于修正物体发射率得到提高红外热图像对非稳态温度场测量精度的模型。对铸铁、不锈钢进行了3组测温实验,红外热图像直接测量的最大误差分别为2.1℃、1.7℃、2.3℃,而所提出的方法测量的最大误差分别为1.0℃、0.7℃、1.6℃。通过对比分析3组测量结果数据验证了测量方法的可行性。