Optimal DC Power Distribution System Design for Data Center with Efficiency Improvement

Data Center Power Distribution design is very popular today focusing on improved energy efficiency and reduced operating cost. Conventionally data centers use low efficiency electrical power distribution systems with large AC power transformers, high power losses, and AC UPS and PDU power conversions. Most IT servers utilize low voltage level (12V or 48V) as the power source, which requires a step-down transformer and AC to DC rectifiers in every PDU. The Proposed 380V DC Power Distribution System promises to deliver high transmission efficiency and low power component cost. This is a comprehensive design including data center physical architecture and equipment selection, centralized rectifier design, simulation and analysis, power loss analysis, and power requirement and system efficiency calculations. The core technical contribution is the design and simulation of a Buck-type current source rectifier using efficiency modeling analysis. This special converter is applied to data center power system to replace large scale AC transformers and distributed rectifiers. Related power and efficiency calculations aim to verify the viability, applicability, and practicality of this system design and to minimize power losses

Security Analysis of Filecoin's Expected Consensus in the Byzantine vs Honest Model

Filecoin is the largest storage-based open-source blockchain, both by storage capacity (>11EiB) and market capitalization. This paper provides the first formal security analysis of Filecoin's consensus (ordering) protocol, Expected Consensus (EC). Specifically, we show that EC is secure against an arbitrary adversary that controls a fraction $\beta$ of the total storage for $\beta m< 1- e^{-(1-\beta)m}$, where $m$ is a parameter that corresponds to the expected number of blocks per round, currently $m=5$ in Filecoin. We then present an attack, the $n$-split attack, where an adversary splits the honest miners between multiple chains, and show that it is successful for $\beta m \ge 1- e^{-(1-\beta)m}$, thus proving that $\beta m= 1- e^{-(1-\beta)m}$ is the tight security threshold of EC. This corresponds roughly to an adversary with $20\%$ of the total storage pledged to the chain. Finally, we propose two improvements to EC security that would increase this threshold. One of these two fixes is being implemented as a Filecoin Improvement Proposal (FIP).Comment: AFT 202

Semi-Sparsity for Smoothing Filters

In this paper, we propose an interesting semi-sparsity smoothing algorithm based on a novel sparsity-inducing optimization framework. This method is derived from the multiple observations, that is, semi-sparsity prior knowledge is more universally applicable, especially in areas where sparsity is not fully admitted, such as polynomial-smoothing surfaces. We illustrate that this semi-sparsity can be identified into a generalized $L_0$-norm minimization in higher-order gradient domains, thereby giving rise to a new "feature-aware" filtering method with a powerful simultaneous-fitting ability in both sparse features (singularities and sharpening edges) and non-sparse regions (polynomial-smoothing surfaces). Notice that a direct solver is always unavailable due to the non-convexity and combinatorial nature of $L_0$-norm minimization. Instead, we solve the model based on an efficient half-quadratic splitting minimization with fast Fourier transforms (FFTs) for acceleration. We finally demonstrate its versatility and many benefits to a series of signal/image processing and computer vision applications

The Directional Transport of Self-Propelled Ellipsoidal Particles Confined in 2D Channel

Transport phenomenon of self-propelled ellipsoidal particles confined in a smooth corrugated channel with a two-dimensional asymmetric potential and Gaussian colored noise is investigated. Effects of the channel, potential and coloured noise are discussed. The moving direction changes from along x axis to opposite x axis with increasing load f. Proper size of pore is good at the directional transport, but too large or too small pore size will inhibit the transport speed. Large x axis noise intensity will inhibit the directional transport phenomena. Proper y axis noise intensity will help to the directional transport. Transport reverse phenomenon appears with increasing self-propelled speed v0. Perfect sphere particle is more easier for directional transport than needlelike ellipsoid particle

Physiological and elemental changes of Trichodesmium in response to growth limitation by phosphorus, iron and zinc

Trichodesmium spp. is a colonial diazotrophic cyanobacterium found in the oligotrophic (sub)tropical oceans, where dissolved inorganic phosphorus (DIP) can be depleted. To cope with low P concentrations, P can be scavenged from the dissolved organic P (DOP) pool. This requires deployment of multiple enzymes that are activated by trace metals such as iron (Fe) and zinc (Zn), as the concentrations of these metals in the open ocean can often be extremely low and their physicochemical speciation further constrains their bioavailability, the potentially enhanced trace element requirements for P acquisition enzymes under stronger P limitation has the potential to exert control on the growth of Trichodesmium and thereby impact global nitrogen and carbon cycles. In this thesis, I applied a continuous culture technique under trace-metal-controlled conditions to vary the supply of DIP, DOP, Fe and Zn to test the impact of the relative availability of P sources, Fe, and Zn availability on the growth and physiological changes in Trichodesmium. Firstly, this study revealed 3.5-fold elevated Zn requirements of Trichodesmium when MPA was used as the sole source of P in comparison to growth on DIP. Secondly, this study provided for the first time the elemental stoichiometry of Trichodesmium grown under Fe limitation and Fe-P co-limitation conditions and revealed the response of Trichodesmium to nutrient limitation from the perspective of metabolite changes. Thirdly, this study revealed ~10-fold elevated nickel (Ni) requirement of Trichodesmium under Zn limitation. Together, the research presented in this thesis demonstrates that Trichodesmium can significantly change its elemental stoichiometry in response to different elemental limitation conditions. Ultimately, these data will provide a useful resource for ocean biogeochemical models that may in the future resolve P, Fe and Zn

Critical Transmission Sectors of Energy-Water-GHG Nexus

Využití vody, spotřeba energie a emise skleníkových plynů (GHG) jsou rozhodujícími ukazateli a do značné míry souvisí s udržováním nebo dosahováním environmentální a sociální udržitelnosti. Tato práce prezentuje vyvinuté metodiky. Představuje také provedené případové studie, které prozkoumaly a identifikovaly Water-Energy-GHG Nexus (WEGN) z pohledu dodavatelského řetězce. Pro analýzu a návrh sítě WEGN jsou navrženy tři metodiky, které jsou založeny na nové aplikaci a integraci modelu vstup-výstup (IO), geografického informačního systému (GIS) a sítě dodavatelského řetězce (SCN), a zároveň řeší výzvy, které dříve neumožňovali praktické implementace. Použitelnost těchto metod je prokázána třemi komplexními případovými studiemi zaměřenými na odvětvovou environmentální účinnost, regionální environmentální účinnost a kritické přenosy WEGN. Mezi mé příspěvky v této oblasti patří: i. Nový nástroj pro hodnocení založený na IO pro identifikaci regionální environmentální účinnosti z hlediska WEGN, zejména pro regiony, které jsou úzce propojenyobchodem. ii. Pokročilá integrace metodik GIS a IO (GIS-IO) za účelem odhalení a mapování sítě WEGN, sledování kritických meziregionálních a sektorových toků WEGN, vyjasnění regionálních, odvětvových a celosvětových vzorců sítě WEGN a určení souvisejících výhod pro různé regiony. iii. Efektivní metoda hodnocení založená na IO a SCN pro kvantifikaci sektorových koeficientů WEGN. Navrhované metodiky, s podporou sady komplexních základních rovnic, transformují komplikované výzvy identifikace a analýzy sítě WEGN do snadno srozumitelného formátu, z čehož vznikají robustní řešení pro zlepšení posuzování environmentální udržitelnosti a zmírnění environmentálních tlaků. Například v jedné z případových studií ukazují výsledky nového přístupu GIS-IO zjevné rozdíly mezi různými zeměmi v rámci EU27, mezi různými sektory a také pokud srovnáme EU27 jako blok zemí, s ostatními státy světa. Analýza ukázala, že země EU27 přispěly o 1.4 Gt nižšími emisemi CO2, o 64.5 Gm3 menší spotřebou vody a 4.9 × 104 PJ nižší spotřebou energie ve srovnání se zbytkem světa, přičemž generovaly ekvivalentní ekonomickou produkci. To má dramatický dopad na globální prostředí. Největší úspěch v CWE mezi zeměmi EU27 měly Německo, Francie a Itálie. Práce doporučuje, aby EU27 poskytovala více technické podpory zemím, které těchto výsledků nedosahují, aby se zvýšila účinnost využívání zdrojů.Water utilisation, energy consumption and Greenhouse Gas (GHG) emissions are crucial indicators and very much related for maintaining or achieving the Environmental and social sustainability. This thesis presents the methodologies have been developed and case studies have been conducted to explore and identify the Water-Energy-GHG Nexus (WEGN) from the supply chain perspective. Three methodologies which are based on the application and integration of the Input-Output (IO) model, Geographic Information System (GIS) and Supply Chain Network (SCN) are proposed, for analysing and designing the WEGN network, while also addressing challenges that have previously prevented practical implementation. The applicability of these methodologies is demonstrated by three comprehensive case studies focused on the sectoral environmental efficiency, regional environmental efficiency and critical transmissions of WEGN. My contributions to the field include: i. Novel IO based assessment tool for identifying regional environmental efficiency in terms of WEGN, especially for the regions that are closely connected by interregional trade. ii. Sophisticated Integrating the GIS and IO methodologies (GIS-IO) to reveal and map WEGN network, tracking the critical inter-regional and -sectoral WEGN flows, clarifying the regional, sectoral and worldwide patterns of WEGN network, and identifying the associated benefits for different regions. iii. Efficient IO and SCN based assessment approach (IO-SCN) for quantifying the sectoral WEGN coefficients. The proposed methodologies, with the support of a set of comprehensive underlying equations, transform the complicated WEGN network identification and analysis challenges into an easily understandable format, from which arises robust solutions for improving environmental sustainability assessment and mitigating environmental pressures. As an example in one of the case studies, the results run by the novel approach of GIS-IO reveals that apparent disparities between different countries within EU27, different sectors, as well in the EU27 as a block of nations compared and the rest of the world. The EU27 countries contributed 1.4 Gt less CO2 emissions, 64.5 Gm3 less water utilisation and 4.9×104 PJ less energy consumption, compared to the rest of the world, while generating the equivalent economic output. This has a dramatic effect on the global environment. Germany, France and Italy benefited most in the CWE network in the EU27. We recommend that the EU27 provide more technical support to upstream countries to improve the efficiency of resource utilisation.

Failure Analysis

Two approaches to failure analysis are explained: analysis of individual failures and statistical analysis. Various criteria for failure sorting and classification are presented, as well as the main causes and mechanisms of failures. The text is accompanied by figures with characteristic fracture patterns. The chapter is complemented by an example of computer aided sorting of failures in railway driving vehicles

ARFA: An Asymmetric Receptive Field Autoencoder Model for Spatiotemporal Prediction

Spatiotemporal prediction aims to generate future sequences by paradigms learned from historical contexts. It holds significant importance in numerous domains, including traffic flow prediction and weather forecasting. However, existing methods face challenges in handling spatiotemporal correlations, as they commonly adopt encoder and decoder architectures with identical receptive fields, which adversely affects prediction accuracy. This paper proposes an Asymmetric Receptive Field Autoencoder (ARFA) model to address this issue. Specifically, we design corresponding sizes of receptive field modules tailored to the distinct functionalities of the encoder and decoder. In the encoder, we introduce a large kernel module for global spatiotemporal feature extraction. In the decoder, we develop a small kernel module for local spatiotemporal information reconstruction. To address the scarcity of meteorological prediction data, we constructed the RainBench, a large-scale radar echo dataset specific to the unique precipitation characteristics of inland regions in China for precipitation prediction. Experimental results demonstrate that ARFA achieves consistent state-of-the-art performance on two mainstream spatiotemporal prediction datasets and our RainBench dataset, affirming the effectiveness of our approach. This work not only explores a novel method from the perspective of receptive fields but also provides data support for precipitation prediction, thereby advancing future research in spatiotemporal prediction.Comment: 0 pages, 5 figure