Visual Anomaly Detection in Event Sequence Data

Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When applied to the analysis of event sequence data, the task of anomaly detection can be complex because the sequential and temporal nature of such data results in diverse definitions and flexible forms of anomalies. This, in turn, increases the difficulty in interpreting detected anomalies. In this paper, we propose an unsupervised anomaly detection algorithm based on Variational AutoEncoders (VAE) to estimate underlying normal progressions for each given sequence represented as occurrence probabilities of events along the sequence progression. Events in violation of their occurrence probability are identified as abnormal. We also introduce a visualization system, EventThread3, to support interactive exploration and interpretations of anomalies within the context of normal sequence progressions in the dataset through comprehensive one-to-many sequence comparison. Finally, we quantitatively evaluate the performance of our anomaly detection algorithm and demonstrate the effectiveness of our system through a case study

Tissue microarray immunohistochemical detection of brachyury is not a prognostic indicator in chordoma.

Brachyury is a marker for notochord-derived tissues and neoplasms, such as chordoma. However, the prognostic relevance of brachyury expression in chordoma is still unknown. The improvement of tissue microarray technology has provided the opportunity to perform analyses of tumor tissues on a large scale in a uniform and consistent manner. This study was designed with the use of tissue microarray to determine the expression of brachyury. Brachyury expression in chordoma tissues from 78 chordoma patients was analyzed by immunohistochemical staining of tissue microarray. The clinicopathologic parameters, including gender, age, location of tumor and metastatic status were evaluated. Fifty-nine of 78 (75.64%) tumors showed nuclear staining for brachyury, and among them, 29 tumors (49.15%) showed 1+ (<30% positive cells) staining, 15 tumors (25.42%) had 2+ (31% to 60% positive cells) staining, and 15 tumors (25.42%) demonstrated 3+ (61% to 100% positive cells) staining. Brachyury nuclear staining was detected more frequently in sacral chordomas than in chordomas of the mobile spine. However, there was no significant relationship between brachyury expression and other clinical variables. By Kaplan-Meier analysis, brachyury expression failed to produce any significant relationship with the overall survival rate. In conclusion, brachyury expression is not a prognostic indicator in chordoma

Function, transport, and regulation of amino acids: What is missing in rice?

Amino acids are essential plant compounds serving as the building blocks of proteins, the predominant forms of nitrogen (N) distribution, and signaling molecules. Plant amino acids derive from root acquisition, nitrate reduction, and ammonium assimilation. Many amino acid transporters (AATs) mediating transfer processes of amino acids have been functionally characterized in Arabidopsis, whereas the function and regulation of the vast majority of AATs in rice (Oryza sativa L.) and other crops remain unknown. In this review, we summarize the current understanding of amino acids in the rhizosphere and in metabolism. We describe their function as signal molecules and in regulating plant architecture, flowering time, and defense against abiotic stress and pathogen attack. AATs not only function in root acquisition and translocation of amino acids from source to sink organs, regulating N uptake and use efficiency, but also as transporters of non-amino acid substrates or as amino acid sensors. Several AAT genes show natural variations in their promoter and coding regions that are associated with altered uptake rate of amino acids, grain N content, and tiller number. Development of an amino acid transfer model in plants will advance the manipulation of AATs for improving rice architecture, grain yield and quality, and N-use efficiency

Inventory of Spatio-Temporal Methane Emissions from Livestock and Poultry Farming in Beijing

Livestock and poultry farming sectors are among the largest anthropogenic methane (CH4) emission sources, mainly from enteric fermentation and manure management. Previous inventories of CH4 emission were generally based on constant emission factor (EF) per head, which had some weaknesses mainly due to the succession of breeding and feeding systems over decades. Here, more reliable long-term changes of CH4 emissions from livestock and poultry farming in Beijing are estimated using the dynamic EFs based on the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method, and high-resolution spatial patterns of CH4 emissions are also estimated with intensive field survey. The results showed that the estimated CH4 emissions derived by dynamic EFs were approximately 13–19% lower than those based on the constant EF before 2010. After 2011, however, the dynamic EFs-derived CH4 emissions were a little higher (3%) than the constant EF method. Temporal CH4 emissions in Beijing had experienced four developing stages (1978–1988: stable; 1989–1998: slow growth; 1999–2004: rapid growth and reached hot moments; 2005–2014: decline) during 1978–2014. Over the first two decades, the contributions of pigs (45%) and cattle (46%) to annual CH4 emission were similar; subsequently, the cattle emitted more CH4 compared to the pigs. At a spatial scale, Shunyi, Daxing, and Tongzhou districts with more cattle and pigs are the hotspots of CH4 emission. In conclusion, the dynamic EFs method obviously improved the spatio-temporal estimates of CH4 emissions compared to the constant EF approach, and the improvements depended on the period and aquaculture structure. Therefore, the dynamic EFs method should be recommended for estimating CH4 emissions from livestock and poultry farming in the future

Decreased Number and Expression of nNOS-Positive Interneurons in Basolateral Amygdala in Two Mouse Models of Autism

The basolateral amygdala (BLA) controls socio-emotional behaviors and is involved in the etiology of autism. We have recently shown that virtually every neuronal nitric oxide synthase (nNOS) positive cell is a GABAergic inhibitory interneuron in the mouse BLA. Here, stereology was used to quantify the number of nNOS-expressing interneurons in valproic acid (VPA)-exposed C57BL/6J (B6) and BTBR T+Itpr3tf/J (BTBR) mice models of autism. Additionally, the protein and mRNA levels of nNOS in the BLA were quantitatively assessed by western blot and qRT-PCR analysis, respectively. Our results showed the decreased number of nNOS interneurons in the BLA of animal models relative to autism. Consistently, nNOS was significantly reduced in the VPA-exposed and BTBR mice at both protein and mRNA levels. Together, these preliminary findings suggest that down-regulation of nNOS may be an attractive target for the pharmacological intervention in autism

Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making - Fig 1

<p>A. 2-arm bandit task trial timeline. Participants completed 30 games, each with 16 trials. On each trial of each game, participants had to assign one token (stacked horizontally at the top of the screen) to one of the two lottery arms. After placing each token, they either earned 1 point if the token turned green or zero points if the token turned red. Each trial lasted about 2s, including participants’ trial reaction time to assign a token and a 500ms outcome phase shoeing the token color once assigned. At the end of each 16-trials game, participants saw a brief screen (4s) with their total points earned in the game, and the next game followed. At the beginning of the task, participants were instructed to try earning as many points as possible in the task. They were further told upfront they would be paid in proportion to their total points earned in the game (actual paid amounts ranged from $5 to$10). Each trial decision and the arms reward rates were recorded. B. DBM illustration and the generative equations. The reward rate of each arm are assumed to be independently drawn at the start of a game from a Beta distribution <i>q</i>_{0 =} Beta (<i>α</i>_<i>0</i>, <i>β</i>_<i>0</i>), fixed throughout the game, and with mean <i>r = (α</i>_<i>0</i>)/(<i>α</i>_<i>0</i> + <i>β</i>_<i>0</i>)_. DBM assumes that subjects believe that the reward rate <i>θ</i> for any arm can reset on any trial with probability 1-<i>γ</i>, otherwise it is the same value as the last trial.</p