Forest diversity and community dynamics along an altitudinal gradient of Ailaoshan Mountain (Yuanyang, Yunnan Province, China)

In order to evaluate forest community diversity, the quantity of forest community succession along an altitudinal gradient from 1690 to 2016 m above sea level, the understanding of relationships between diversity and community dynamics, and data from sampling plots of forest communities were studied. Forest communities were mid-mountain moist evergreen broad-leaved forests on the southern slope of the Ailaoshan Mountain in Yuanyang County (near the Hani terraces) in Yunnan Province, China. The results showed that (1) the mean species richness, ecological dominance, and evenness (E) were 9.16, 0.31, and 0.27, respectively. The mean Shannon-Wiener Index and Coverage Weighted Foliage-Height Diversity Index were 0.84 and 0.41, respectively. (2) The mean live aboveground biomass (AGS) was 99.23 Mg/ha and the mean Composition Index (CI) was 182.17. Species diversity (including E, richness, and Shannon-Wiener Index), live AGS, and CI could be predicted by the mid-domain effect (MDE), which displayed a unimodal pattern against elevation. (3) Richness, E, Shannon-Wiener Index, and Coverage Weighted Foliage-Height Diversity Index increased with CI. Ecological dominance decreased with increased CI, following a quadratic relationship. Whittaker Index decreased with both increased CI and AGS, with a quadratic relationship. Much forest diversity could be explained by the MDE. However, forest dynamics were seriously disturbed by human activities. More attention should focus on increasing forest diversity in order to prevent the degradation of forest ecological functions thus resulting in threats to the sustainable development of the local ecological systems

Residue Analysis and Exposure Assessment of Methylsiloxane Oligomers in Fried Chicken and French Fries

The fried food in fast food is deeply loved by consumers. However, with the increasing concern about the safety of volatile methylsiloxanes, the residue of oligomer monomer of methylsiloxanes from defoamer PDMS in fried food needs to be studied urgently. In this study, an efficient and sensitive method for the determination of methylsiloxane oligomers in fried chicken and French fries was established using QuEChERS-gas chromatography-tandem mass spectrometry (GC-MS/MS). A total of 33 fried chickens and 30 French fries purchased from fast food restaurants were analyzed and a preliminary exposure assessment using a point assessment method was carried out. The results showed that octamethyl cyclotetrasiloxane (D4)~hexamethyldisiloxane (D18) and decamethyl tetrasiloxane (L4)~triaconta methyltetradecasiloxane (L14) were detected, and the median total content of methylsiloxane oligomers in fried chicken (514.61 ng·g−1) was higher than that in French fries (83.4 ng·g−1). The estimated daily intake (EDI) of methylsiloxanes (molecular weight <1000) in fried chicken and French fries was 164.94 ng·kg−1·d−1 and 13.09 ng·kg−1·d−1, respectively, which was lower than the PDMS acceptable daily intake (ADI) (0.8 mg·kg−1·d−1). However, the potential hazards of some volatile methylsiloxanes such as D4~dodecamethyl cyclohexasiloxane (D6) need to be further investigated after long-term low dose intake and enrichment. This study provides a scientific basis for the safety evaluation and subsequent in-depth study of methylsiloxanes residues in fried food fast food

ЭКСПЕРИМЕНТАЛЬНОЕ ИССЛЕДОВАНИЕ ДЕФОРМАЦИОННОГО ПРОЦЕССА НА РАЗЛОМЕ В МЕТАСТАБИЛЬНОМ СОСТОЯНИИ ПЕРЕД ЗЕМЛЕТРЯСЕНИЕМ

According to the steady state of fault and energy balance, we provided a new idea to observe the precursors for a stressed fault. The meta-instability (or sub-instability) state of a fault is defined as the transition phase from peak stress to critical stress of fast instability (earthquake generation) during a full period of slow loading and fast unloading. The accumulative deformation energy begins to release in this stage. Identifying its deformation before fast instability would be beneficial to obtain premonitory information, and to evaluate the seismic risks of tectonic regions. In this study, we emphasized to analyze deformation process of the meta-instable stage with stain tensor data from a straight precut fault in granite at a slow loading rate, and observed the tempo-spatial features during the full deformation process of the fault. Two types of tectonic zones and instabilities occur on the stick-slip fault. The low- and high-value segments in the volume strain component appear along the fault strike with a load increment. The former first weakens and then becomes initial energy release segments; the latter forms strong stress-interlocking areas and finally turns into the initial region of fast instability. And there are two stages in the entire instable process of the fault: the initial stage is associated with the release of the low volume strain segments, which means fault pre-slips, slow earthquakes or weak earthquakes. The second one characterizes a strong earthquake through the release of high volume strain parts. The rupture acceleration in the first stage promotes the generation of the second. Moreover, fault instability contains two types of strain adjustments along the fault: the front-like strain change along the transition segments from low- to high- strain portions with volume strain release, and the compressive strain pulse of fault instability after the volume strain release extends to a certain range with loading increment. In laboratory experiments, the front-type strain occurs about 12 seconds before fast fault instability; the compressive pulse initiates within less than 0.1 second, and then the fault turns quickly into a dynamic strain adjustment, which appears quasi-synchronously between different measurement points, and, finally, an earthquake is generated.Предлагается новый подход к выделению предвестников землетрясения в зоне разлома с высоким уровнем напряжений, опирающийся на понятия его устойчивого состояния и энергетического баланса. В условиях экспериментального воспроизведения модели прерывистого «stick-slip» в пределах полного цикла медленной нагрузки и быстрой разгрузки деформируемого образца с разрезом, имитирующим разлом, предельные состояния его метастабильности и метанестабильности при пиковом критическом напряжении определяются как переходная фаза от устойчивости к неустойчивости со спонтанной генерацией импульсной подвижки (т.е. генерации землетрясения). С переходом модельного разлома в состояние метанестабильности стартует процесс медленного, пространственно-дискретного, избирательного высвобождения накопленных на нем напряжений. Выявление этого процесса до его перехода в стадию быстрой нестабильности имеет важное прогнозное значение для превентивной оценки риска в тектонически активных регионах. В выполненном авторами экспериментальном исследовании проанализированы вариации тензора напряжений в нагруженном гранитном образце с прямолинейным разрезом в течение метанестабильной стадии, а также проведено наблюдение пространственно-временных особенностей этого параметра в течение всего процесса деформации модельного разлома.Установлено, что по простиранию разлома имеют место сегменты с низкими и высокими значениями объемной деформации, которым соответствуют два типа нестабильности. Первые закладываются на участках с пониженной прочностью и становятся сегментами начального высвобождения энергии в начальную стадию нестабильности. Вторые, наоборот, характерны для участков упрочнения разлома, где происходит блокировка напряжений, и впоследствии превращаются в начальные области быстрой нестабильности.В рамках процесса нестабильности разлома выделены две стадии. В первую стадию происходит реализация небольших медленных сдвиговых смещений на разломе в пределах сегментов первого типа, именуемых в литературе предсмещениями, низкочастотными, медленными или тихими землетрясениями и т.д. Сегментация развивается с ускорением, что способствует переходу деформационного процесса во вторую стадию, когда происходит быстрое динамической объединение сегментов обоих типов с реализацией большого смещения по разлому, что соответствует сильному землетрясению в природе.В условиях нестабильности разлома зафиксированы два типа деформации вдоль его простирания: фронтальная миграция деформации вдоль сегментов первого типа при смещениях по ним к сегментам второго и импульс деформации сжатия после реализации объемной деформации после смещения, распространяющийся на определенное расстояние в условиях роста приложенной к образцу нагрузки. В выполненных экспериментах фронтальная деформация возникала примерно за 12 с до быстрой нестабильности разлома, а импульс сжатия начинается менее чем за 0,1 с до неё. Динамическая деформация на разломе проявляется квазисинхронно по простиранию разлома во всех точках измерения

Long Noncoding RNA Expression Signatures of Metastatic Nasopharyngeal Carcinoma and Their Prognostic Value

Long noncoding RNAs (lncRNAs) have recently been found to play important roles in various cancer types. The elucidation of genome-wide lncRNA expression patterns in metastatic nasopharyngeal carcinoma (NPC) could reveal novel mechanisms underlying NPC carcinogenesis and progression. In this study, lncRNA expression profiling was performed on metastatic and primary NPC tumors, and the differentially expressed lncRNAs between these samples were identified. A total of 33,045 lncRNA probes were generated for our microarray based on authoritative data sources, including RefSeq, UCSC Knowngenes, Ensembl, and related literature. Using these probes, 8,088 lncRNAs were found to be significantly differentially expressed (2-fold). To identify the prognostic value of these differentially expressed lncRNAs, four lncRNAs (LOC84740, ENST00000498296, AL359062, and ENST00000438550) were selected; their expression levels were measured in an independent panel of 106 primary NPC samples via QPCR. Among these lncRNAs, ENST00000438550 expression was demonstrated to be significantly correlated with NPC disease progression. A survival analysis showed that a high expression level of ENST00000438550 was an independent indicator of disease progression in NPC patients (). In summary, this study may provide novel diagnostic and prognostic biomarkers for NPC, as well as a novel understanding of the mechanism underlying NPC metastasis and potential targets for future treatment

Integrated metabolomics and metagenomics analysis of plasma and urine identified microbial metabolites associated with coronary heart disease

Coronary heart disease (CHD) is top risk factor for health in modern society, causing high mortality rate each year. However, there is no reliable way for early diagnosis and prevention of CHD so far. So study the mechanism of CHD and development of novel biomarkers is urgently needed. In this study, metabolomics and metagenomics technology are applied to discover new biomarkers from plasma and urine of 59 CHD patients and 43 healthy controls and trace their origin. We identify GlcNAc-6-P which has good diagnostic capability and can be used as potential biomarkers for CHD, together with mannitol and 15 plasma cholines. These identified metabolites show significant correlations with clinical biochemical indexes. Meanwhile, GlcNAc-6-P and mannitol are potential metabolites originated from intestinal microbiota. Association analysis on species and function levels between intestinal microbes and metabolites suggest a close correlation between Clostridium sp. HGF2 and GlcNAc-6-P, Clostridium sp. HGF2, Streptococcus sp. M143, Streptococcus sp. M334 and mannitol. These suggest the metabolic abnormality is significant and gut microbiota dysbiosis happens in CHD patients

Effect of Nano-CaCO3 on the Mechanical Properties and Durability of Concrete Incorporating Fly Ash

Concrete mixtures consisting of nanomaterials and fly ash have been shown to be effective for improving the performance of concrete. This study investigates the combined effects of nano-CaCO3 and fly ash on the mechanical properties and durability of concrete; the mix proportion is optimized through orthogonal experiments. In the first phase, nine concrete mixtures were prepared with three water-to-binder ratios (0.4, 0.5, and 0.6), three fly ash contents (15%, 20%, and 25% replacement of the cement weight), and three nano-CaCO3 contents (1%, 2%, and 3% replacement of the cement weight). Based on the orthogonal analysis, the optimal concrete mix proportion was determined as a water-to-binder ratio of 0.4, 20% fly ash, and 1% nano-CaCO3. In the second phase, further investigations were carried out to examine the superiority of the optimal concrete and evaluate the synergistic effect of nano-CaCO3 and fly ash. The results showed that nano-CaCO3 contributed to increasing the compressive strength of fly ash concrete at the early ages, but its effect was quite limited at later ages. Furthermore, the scanning electron microscopy analysis revealed that the seeding effect, filling effect, and pozzolanic effect were the primary mechanisms for the improvement of concrete performance

Surface and Underwater Acoustic Source Discrimination Based on Machine Learning Using a Single Hydrophone

In shallow water, passive sonar usually has great difficulty in discriminating a surface acoustic source from an underwater one. To solve this problem, a supervised machine learning method using only one hydrophone is implemented in this paper. Firstly, simulated training data are generated by a normal mode model KRAKEN with the same environment setup as that in SACLANT 1993 experiment. Secondly, the k-nearest neighbor (kNN) classifiers are trained and evaluated using the scores of precision, recall, F1 and accuracy. Thirdly, the random subspace kNN classifiers are finely trained on three hyperparameters (the number of nearest neighbors, the number of predictors selected at random and the number of learners in the ensemble) to obtain the best model. Fourthly, a deep learning method called ResNet-18 is also applied, and it reaches the best balance between precision and recall, while the accuracies of both simulation and experimental data are all 1.0. Further, data from all 48 hydrophones of the vertical linear array (VLA) are analyzed using the three kinds of machine learning methods (kNN, random subspace kNN and ResNet-18) separately, and the results are compared. It is concluded that the performance of random subspace kNN is the best. Both the simulation and experimental results suggest the feasibility of machine learning as a surface and underwater acoustic source discrimination method even with only a single hydrophone

Synergetic effects of LiNi1/3Co1/3Mn1/3O2-LiMn2O4 blended materials on lithium ionic transport for power performance

Synergetic effects of LiNi1/3Co1/3Mn1/3O2-LiMn2O4 blended materials on lithium ionic transport for power performanc