The choice-theoretic characterizations of risk changes and risk attitudes in cumulative prospect theory:a stochastic dominance approach

Stochastic dominance provides an effective tool to characterize individuals’ risk attitudes in decision making under risk by comparing risky prospects. The emergence of the cumulative prospect theory (CPT), developed by Kahneman and Tversky (1979) and Tversky and Kahneman (1992), provides a prominent alternative to the expected utility theory. This thesis aims to provide a choice-theoretic characterization for risk changes and risk attitudes under CPT using a stochastic dominance approach. This thesis identifies a set of stochastic dominance conditions to generalize the notions of increase in risk, strong risk aversion, downside risk and downside risk aversion to accommodate risk aversion, risk seeking and downside risk aversion preferences in the CPT paradigm. This study further investigates risk measures implied by risky choice behaviour of CPT decision makers. This thesis also extends the analyses to general reference point and inverse S-shaped value functions. The stochastic dominance conditions identified in this thesis provide an approach for risk preference elicitation in the paradigm of CPT without prior knowledge on the shape of value functions or probability weighting functions, which complements to existing risk preference elicitation approaches. Consequently, the equivalence of risk measures and stochastic dominance conditions enables risk preference elicitation through pairwise comparisons of risky prospects. The implications of this work in experimental studies and optimal decision problems (e.g. portfolio choice) shed new light into the application of CPT

DCTTS: Discrete Diffusion Model with Contrastive Learning for Text-to-speech Generation

In the Text-to-speech(TTS) task, the latent diffusion model has excellent fidelity and generalization, but its expensive resource consumption and slow inference speed have always been a challenging. This paper proposes Discrete Diffusion Model with Contrastive Learning for Text-to-Speech Generation(DCTTS). The following contributions are made by DCTTS: 1) The TTS diffusion model based on discrete space significantly lowers the computational consumption of the diffusion model and improves sampling speed; 2) The contrastive learning method based on discrete space is used to enhance the alignment connection between speech and text and improve sampling quality; and 3) It uses an efficient text encoder to simplify the model's parameters and increase computational efficiency. The experimental results demonstrate that the approach proposed in this paper has outstanding speech synthesis quality and sampling speed while significantly reducing the resource consumption of diffusion model. The synthesized samples are available at https://github.com/lawtherWu/DCTTS.Comment: 5 pages, submitted to ICASS

Study on the Cutting Temperature of the Textured Tool by 3D FEA Simulation

Temperature plays an important role in the life of cutting tools. However, it is sometimes difficult to observe instantaneously because of limited data acquisition, especially for the textured tool. In this paper, the performance of microgroove textured cutting tools for three-dimensional (3D) oblique dry turning of AISI 1045 steel was studied by finite element simulation. The effects of width, depth and spacing of strip micro-texture on cutting temperature and the effect of cutting speed on cutting temperature of strip micro-texture tool were studied. The results show that the maximum temperature of the tool and the tip temperature first increase and then decrease with the increase of micro-texture width. When the micro-texture depth increases, the maximum temperature and the tool tip temperature decrease first and then increase. The highest temperature and tip temperature of the tool gradually increase with the increase of micro-texture spacing. The highest temperature and tip temperature of the tool increase with the increase of cutting speed, feed speed and cutting depth. In addition, the effective mechanism of micro-texture parameter for the temperature was proposed. It provides profound guidance for optimizing the microstructure parameters and cutting process of cutting tools according to cutting temperature in this study. It also provides an effective and practical method for the design, innovation and development of micro-textured tools

A Novel Interdigital Capacitor Pressure Sensor Based on LTCC Technology

A novel passive wireless pressure sensor is proposed based on LTCC (low temperature cofired ceramic) technology. The sensor employs a passive LC circuit, which is composed of a variable interdigital capacitor and a constant inductor. The inductor and capacitor were fabricated by screen-printing. Pressure measurement is tested using a wireless mutual inductance coupling method. The experimental sensitivity of the sensor is about 273.95 kHz/bar below 2 bar. Experimental results show that the sensor can be read out wirelessly by external antenna at 600°C. The max readout distance is 3 cm at room temperature. The sensors described can be applied for monitoring of gas pressure in harsh environments, such as environment with high temperature and chemical corrosion

Whole-genome sequencing of <em>Oryza brachyantha</em> reveals mechanisms underlying <em>Oryza</em> genome evolution

The wild species of the genus Oryza contain a largely untapped reservoir of agronomically important genes for rice improvement. Here we report the 261-Mb de novo assembled genome sequence of Oryza brachyantha. Low activity of long-terminal repeat retrotransposons and massive internal deletions of ancient long-terminal repeat elements lead to the compact genome of Oryza brachyantha. We model 32,038 protein-coding genes in the Oryza brachyantha genome, of which only 70% are located in collinear positions in comparison with the rice genome. Analysing breakpoints of non-collinear genes suggests that double-strand break repair through non-homologous end joining has an important role in gene movement and erosion of collinearity in the Oryza genomes. Transition of euchromatin to heterochromatin in the rice genome is accompanied by segmental and tandem duplications, further expanded by transposable element insertions. The high-quality reference genome sequence of Oryza brachyantha provides an important resource for functional and evolutionary studies in the genus Oryza

Serum proteome analysis for profiling protein markers associated with carcinogenesis and lymph node metastasis in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC), one of the most common cancers in population with Chinese or Asian progeny, poses a serious health problem for southern China. It is unfortunate that most NPC victims have had lymph node metastasis (LNM) when first diagnosed. We believe that the 2D based serum proteome analysis can be useful in discovering new biomarkers that may aid in the diagnosis and therapy of NPC patients. To filter the tumor specific antigen markers of NPC, sera from 42 healthy volunteers, 27 non-LNM NPC patients and 37 LNM NPC patients were selected for screening study using 2D combined with MS. Pretreatment strategy, including sonication, albumin and immunoglobulin G (IgG) depletion, was adopted for screening differentially expressed proteins of low abundance in serum. By 2D image analysis and MALDI-TOF-MS identification, twenty-three protein spots were differentially expressed. Three of them were further validated in the sera using enzyme-linked immunosorbent assay (ELISA). Our research demonstrates that HSP70, sICAM-1 and SAA, confirmed with ELISA at sera and immunohistochemistry, are potential NPC metastasis-specific serum biomarkers which may be of great underlying significance in clinical detection and management of NPC

A fine assessment technology for medium-high exploration degree plays

The current evaluation methods mainly focus on plays without hydrocarbon discoveries. By integrating three techniques, i.e., spatial quantitative prediction technology of hydrocarbon bearing probability, overlapping processing technology for multi-layer spatial hydrocarbon bearing probability, petroleum resources abundance fractal simulation restricted by corresponding spatial hydrocarbon bearing probability, a new fine evaluation method was put forward. This method, based on spatial grids and combining planar and vertical evaluation results, focuses on the assessment of multi-layer plays. Compared with the present methods, it has advantages such as comprehensive assessment, precise processing results, comprehensive data collection and application, exploration effectiveness. By this Method, 38 secondary structural belts in the middle-upper exploration formations in the Turpan-Hami Basin were evaluated. Favorable drilling areas in each belts were pointed out based on the spatial probability of hydrocarbon bearing. Their corresponding geological favorability index and residual oil resources revealed that the Shengbei, Huoyanshan, Lukeqin, Shanle Structural Belts are the most favorable belts for exploration. 摘 要: 现行的区带评价方法主要针对尚无油气发现的区带，在剖析其局限性的基础上，将含油气概率空间定量预测技术、多层系空间含油气概率叠合处理技术、含油气概率约束下的油气资源丰度空间定量模拟技术紧密结合，提出一种平面与纵向相结合、基于空间网格的多层系区带精细评价新方法。相对于现行的区带评价方法，具有评价综合性、评价及评价结果精细性、资料应用与信息采集全面性、应用实效性等优点。采用该方法对吐哈盆地中上部层系38个二级构造带进行评价，根据空间含油气概率评价结果，明确了各构造带内部有利钻探区；依据各区带地质评价值、待发现资源量评价值进行二因素综合排队优选，指出胜北、火焰山、鲁克沁、鄯勒等构造带是下步勘探的最有利构造带。图6表1参25 Key words: play, spatial probability of hydrocarbon bearing, spatial resources abundance, multi-layer overlapping process, Turpan-Hami Basin, favorable secondary structural belt