Non-IID representation learning on complex categorical data

University of Technology Sydney. Faculty of Engineering and Information Technology.Learning complex categorical data requires proper vector or metric representations of the intricate characteristics of that data. Existing methods for categorical data representation usually assume data is independent and identically distributed (IID). However, real-world data is often hierarchically associated with diverse couplings and heterogeneities (i.e., non-IIDness, e.g., various couplings such as value co-occurrences and attribute correlation and dependency, as well as heterogeneities such as heterogeneous distributions or complementary and inconsistent relations). Existing methods either capture only some of these couplings and heterogeneities or simply assume IID data in building their representations. This thesis aims to deeply understand and effectively represent non-IIDness in categorical data. Specifically, it focuses on (1) modeling heterogeneous couplings within and between attributes in categorical data; (2) disentangling attribute couplings with a mixture of heterogeneous distributions; (3) hierarchically learning heterogeneous couplings; (4) integrating complementary and inconsistent heterogeneous couplings; and (5) adaptively identifying and learning dynamic couplings and heterogeneities. Accordingly, this thesis proposes (1) a non-IID similarity metrics learning framework to model complex interactions within and between attributes in non-IID categorical data; (2) a decoupled non-IID learning framework to capture and embed heterogeneous distributions in non-IID categorical data with bounded information loss; (3) a heterogeneous metric learning method with hierarchical couplings to learn and integrate the heterogeneous dependencies and distributions in non-IID categorical data into a representation of a similarity metric; (4) an unsupervised heterogeneous coupling learning approach to integrate the complementary and inconsistent heterogeneous couplings in non-IID categorical data; and (5) an unsupervised hierarchical and heterogeneous coupling learning method to learn hierarchical and heterogeneous couplings on dynamic non-IID categorical data. Theoretical analyses support the effectiveness of the proposed methods and bound the information loss in their generated high-quality representations. Extensive experiments demonstrate that the proposed non-IID representation methods for complex categorical data perform significantly better than state-of-the-art methods in terms of multiple downstream learning tasks and representation-quality evaluation metrics

Experimental and Field Investigations on the Impact-Resistance Mechanical Properties of Negative Poisson’s Ratio Bolt/Cable

AbstractDynamic impact tests of negative Poisson’s ratio (NPR) and rebar bolts under different impact wavelengths were carried out using a self-developed NPR bolt tensile impact test system. Additionally, a field anti-impact test using blasting was performed to simulate rockburst, and the field anti-impact characteristics of the NPR and conventional cable were compared and analysed. The experimental test results revealed that the peak impact force of the NPR and rebar bolts was inversely proportional to the wavelength. The NPR bolt underwent only constant resistance structural deformation, and the rod body did not break. The rebar bolt body fractured and necked. Under the same impact wavelength, the impact force and elongation of the two bolt types were proportional to the impact velocity. Compared with the greater peak impact force of the rebar bolt, the NPR bolt output structure deformation reduced the peak impact force. At the same impact velocity, as the wavelength increased, the impact force of the NPR bolt decreased rapidly, and the number of peaks also decreased. The impact force peak value of the rebar bolt was high, the impact force-time curve had multipeak characteristics, and no apparent rapid attenuation occurred. The field test results indicated that the NPR cable could produce slip deformation under the action of an explosion impact force to absorb the impact energy and that it had special mechanical properties to maintain a constant resistance. Under the same equivalent blasting impact energy, the conventional cable test section collapsed completely. The NPR cable test section was stable overall, verifying that the NPR cable had better impact-resistance mechanical properties than conventional cable. The research results provide a reliable basis for the effectiveness of NPR bolts/cables in preventing rockbursts

Response of Gut Microbiota to Dietary Fiber and Metabolic Interaction With SCFAs in Piglets

Dietary fiber (DF) is increasingly thought to regulate diversity of piglet gut microbiota to alleviate weaning stress in piglets. This study was conducted to investigate the effects of DF on growth performance of piglets and composition of their gut microbiota, as well as the interaction between gut microbiota and short-chain fatty acids (SCFAs) in piglets. A total of 840 piglets were allocated to three dietary treatments consisting of a control group (CG), an alfalfa meal group (AG), and a commodity concentrated fiber group (OG) in a 30-day feeding trial. Gut mucosa and feces samples were used to determine bacterial community diversity by 16S rRNA gene amplicon sequencing. Fiber treatment had a positive effect on growth performance and metabolism of SCFAs in piglets, in particular, compared with CG, the diarrhea rate was significantly decreased, and the content of propionic acid (PA) in the cecum was markedly increased in AG. The Shannon indices of the jejunum microbiota in AG were higher than CG. At the genus level, compared to CG, in the duodenum, the relative abundance of Paenibacillus in AG and OG was higher; in the jejunum, the relative abundances of Bacillus, Oceanobacillus, Paenibacillus, Lactococcus, Enterococcus, and Exiguobacterium were higher, whereas the relative abundance of Mycoplasma was lower in AG; in the cecum, there was also lower relative abundance of Helicobacter in AG and OG, and furthermore, the relative abundance of Faecalibacterium in OG was higher than in CG and AG. Spearman correlation analysis showed that Pseudobutyrivibrio was positively correlated with acetic acid, PA, and butyric acid (BA), while Bacteroides and Anaerotruncus were negatively correlated with PA and BA. In addition, microbiota analyses among different intestine segments showed distinct differences in microbiota between the proximal and distal intestines. Bacteria in the proximal segments were mainly Firmicutes, while bacteria in the distal segments were mainly Bacteroidetes and Firmicutes. Overall, these findings suggested that DF treatment could reduce the diarrhea rate of piglets and had beneficial effects on gut health, which might be attributed to the alteration in gut microbiota induced by DF and the interaction of the gut microbiota with SCFAs

Penaeid shrimp genome provides insights into benthic adaptation and frequent molting

Crustacea, the subphylum of Arthropoda which dominates the aquatic environment, is of major importance in ecology and fisheries. Here we report the genome sequence of the Pacific white shrimp Litopenaeus vannamei, covering similar to 1.66 Gb (scaffold N50 605.56 Kb) with 25,596 protein-coding genes and a high proportion of simple sequence repeats (>23.93%). The expansion of genes related to vision and locomotion is probably central to its benthic adaptation. Frequent molting of the shrimp may be explained by an intensified ecdysone signal pathway through gene expansion and positive selection. As an important aquaculture organism, L. vannamei has been subjected to high selection pressure during the past 30 years of breeding, and this has had a considerable impact on its genome. Decoding the L. vannamei genome not only provides an insight into the genetic underpinnings of specific biological processes, but also provides valuable information for enhancing crustacean aquaculture

Single-atom tailoring of platinum nanocatalysts for high-performance multifunctional electrocatalysis

Platinum-based nanocatalysts play a crucial role in various electrocatalytic systems that are important for renewable, clean energy conversion, storage and utilization. However, the scarcity and high cost of Pt seriously limit the practical application of these catalysts. Decorating Pt catalysts with other transition metals offers an effective pathway to tailor their catalytic properties, but often at the sacrifice of the electrochemical active surface area (ECSA). Here we report a single-atom tailoring strategy to boost the activity of Pt nanocatalysts with minimal loss in surface active sites. By starting with PtNi alloy nanowires and using a partial electrochemical dealloying approach, we create single-nickel-atom-modified Pt nanowires with an optimum combination of specific activity and ECSA for the hydrogen evolution, methanol oxidation and ethanol oxidation reactions. The single-atom tailoring approach offers an effective strategy to optimize the activity of surface Pt atoms and enhance the mass activity for diverse reactions, opening a general pathway to the design of highly efficient and durable precious metal-based catalysts

Single-atom tailoring of platinum nanocatalysts for high-performance multifunctional electrocatalysis

Platinum-based nanocatalysts play a crucial role in various electrocatalytic systems that are important for renewable, clean energy conversion, storage and utilization. However, the scarcity and high cost of Pt seriously limit the practical application of these catalysts. Decorating Pt catalysts with other transition metals offers an effective pathway to tailor their catalytic properties, but often at the sacrifice of the electrochemical active surface area (ECSA). Here we report a single-atom tailoring strategy to boost the activity of Pt nanocatalysts with minimal loss in surface active sites. By starting with PtNi alloy nanowires and using a partial electrochemical dealloying approach, we create single-nickel-atom-modified Pt nanowires with an optimum combination of specific activity and ECSA for the hydrogen evolution, methanol oxidation and ethanol oxidation reactions. The single-atom tailoring approach offers an effective strategy to optimize the activity of surface Pt atoms and enhance the mass activity for diverse reactions, opening a general pathway to the design of highly efficient and durable precious metal-based catalysts

Investigating the protective effects of CED-9 against yeast cell death

The BCL-2 family proteins are best known for their regulation of the apoptosis process. However, these proteins have also been reported to have other day-job functions in healthy cells but these are still poorly studied. It has been documented that anti- and pro-apoptotic BCL-2 family proteins can promote and maintain cell homeostasis, but to what extent these functions are related to their apoptotic roles is still unclear. Here in Chapter one, I have expressed the anti-apoptotic C. elegans BCL-2 homolog CED-9 in the model yeast Saccharomyces cerevisiae, which lacks BCL-2 homologs or other apoptosis machinery, and found that it can protect yeast from heat-induced cell death, consistent with previous reports for several BCL-2 family proteins. Thus, yeast could provide a potential model for studying non-apoptotic functions of BCL-2 family proteins. However, it is first necessary to eliminate the possibility of alternative explanations for the suppression of cell death in yeast expressing BCL-2 family proteins. Two approaches were explored, one to rapidly degrade CED-9 using the auxin-degron system, and the other to quickly induce expression of CED-9, seeking to validate its protective effect. In these studies to date, CED-9 was not definitely demonstrated to suppress cell death induced by heat-ramp without confounding explanations. Although some of these were overcome (e.g. thermocycler heating variations (Chapter two), additional approaches are needed to verify that animal BCL-2 family proteins directly protect yeast from cell death. If successful, the results will support the study of non-apoptotic functions of BCL-2 family proteins, which can open new questions for the broader roles that they play in the cell and how they function in homeostasis and disease states. Alternatively, they could lay to rest this long-standing assumption. Chapter two focuses on further development of the heat-ramp assay used in Chapter one to induce yeast cell death. The thermocyclers are one of the most commonly used machines in the research lab and the clinic. The quality of a thermocycler can impact PCR results and affect the interpretations of quantitative determinations. Programmable thermocyclers can also be used for small-volume incubations and other assays that require precise temperatures such as the yeast heat-ramp assay reported by our lab. Therefore, to validate the heating performance of new edition thermocyclers, I have tested the inter- and intra-thermocycler variation of six different commercial models that are currently available on the market using the heat-ramp assay. To our surprise, and in contrast to older models, all six models lacked sufficiently even heating to be usable for high throughput yeast cell death assays without significant corrections. Each heating block has areas of over-heating and under-heating that are readily detected by our yeast cell death assay, with each model exhibiting unique patterns of heating. These variations within and between the six thermocyclers are significant and reproducible. We urge manufacturers to address the problems of heating inconsistency across thermocycler heat blocks, and users should be aware of these potential confounders