Greening Buildings : How can the performance of existing commercial buildings be improved?

Efforts to improve the performance of commercial buildings have often focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants, something with even greater economic returns than energy savings. Reducing energy demand in commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This project investigates these factors and focuses on the performance of and interaction between: green design elements, indoor environment quality, tenant/ leasing agreements and culture, occupant experience, and building management practices.

Compliance with physical activity guidelines : prevalence in a population of children and youth

PURPOSE To use objective monitoring of physical activity to determine the percentages of children and youth in a population that met physical activity guidelines. METHODS A total of 375 students in grades 1–12 wore an accelerometer (CSA 7164) for seven consecutive days. Bouts of continuous activity and accumulation of minutes spent in physical activity at various intensities were calculated to determine how many students met three physical activity guidelines. RESULTS Over 90% of students met Healthy People 2010, Objective 22.6 and nearly 70% met the United Kingdom Expert Consensus Group guideline, both of which recommend daily accumulation of moderate physical activity. Less than 3% met Healthy People 2010, Objective 22.7, which calls for bouts of continuous vigorous physical activity. For the United Kingdom Expert Consensus Group guideline, compliance decreased markedly with age, but gender differences were not statistically significant. CONCLUSIONS Prevalence estimates for compliance with national physical activity guidelines varied markedly for the three guidelines examined. Objective monitoring of physical activity in youth appears to be feasible and may provide more accurate prevalence rates than self-report measures.

Profiling : an application assignment approach for green data centers

In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.

Understanding the performance of green commercial buildings: a Sustainable Built Environment National Research Centre (SBEnrc) briefing report

Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This project investigates these factors and focuses on the performance of and interaction between: green design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. This paper suggests six areas of strategic research that are needed to understand how conditions can be created to support productivity in green buildings, and deliver significant energy consumption reductions.

Inertial mass of a vortex in cuprate superconductors

We present here a calculation of the inertial mass of a moving vortex in cuprate superconductors. This is a poorly known basic quantity of obvious interest in vortex dynamics. The motion of a vortex causes a dipolar density distortion and an associated electric field which is screened. The energy cost of the density distortion as well as the related screened electric field contributes to the vortex mass, which is small because of efficient screening. As a preliminary, we present a discussion and calculation of the vortex mass using a microscopically derivable phase-only action functional for the far region which shows that the contribution from the far region is negligible and that most of it arises from the (small) core region of the vortex. A calculation based on a phenomenological Ginzburg-Landau functional is performed in the core region. Unfortunately such a calculation is unreliable; the reasons for it are discussed. A credible calculation of the vortex mass thus requires a fully microscopic non-coarse-grained theory. This is developed, and results are presented for an s-wave BCS-like gap, with parameters appropriate to the cuprates. The mass, about 0.5m(e) per layer, for a magnetic field along the c axis arises from deformation of quasiparticle states bound in the core and screening effects mentioned above. We discuss earlier results, possible extensions to d-wave symmetry, and observability of effects dependent on the inertial mass. [S0163-1829(97)05534-3].

Calculations of helium separation via uniform pores of stanene-based membranes

The development of low energy cost membranes to separate He from noble gas mixtures is highly desired. In this work, we studied He purification using recently experimentally realized, two-dimensional stanene (2D Sn) and decorated 2D Sn (SnH and SnF) honeycomb lattices by density functional theory calculations. To increase the permeability of noble gases through pristine 2D Sn at room temperature (298 K), two practical strategies (i.e., the application of strain and functionalization) are proposed. With their high concentration of large pores, 2D Sn-based membrane materials demonstrate excellent helium purification and can serve as a superior membrane over traditionally used, porous materials. In addition, the separation performance of these 2D Sn-based membrane materials can be significantly tuned by application of strain to optimize the He purification properties by taking both diffusion and selectivity into account. Our results are the first calculations of He separation in a defect-free honeycomb lattice, highlighting new interesting materials for helium separation for future experimental validation.

Smart Network Interface Selection for E-DTNs

We implement two energy models that accurately and comprehensively estimates the system energy cost and communication energy cost for using Bluetooth and Wi-Fi interfaces. The energy models running on a system is used to smartly pick the most energy optimal network interface so that data transfer between two end points is maximized.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

Metabolic efficiency with fast spiking in the squid axon

Fundamentally, action potentials in the squid axon are consequence of the entrance of sodium ions during the depolarization of the rising phase of the spike mediated by the outflow of potassium ions during the hyperpolarization of the falling phase. Perfect metabolic efficiency with a minimum charge needed for the change in voltage during the action potential would confine sodium entry to the rising phase and potassium efflux to the falling phase. However, because sodium channels remain open to a significant extent during the falling phase, a certain overlap of inward and outward currents is observed. In this work we investigate the impact of ion overlap on the number of the adenosine triphosphate (ATP) molecules and energy cost required per action potential as a function of the temperature in a Hodgkin–Huxley model. Based on a recent approach to computing the energy cost of neuronal action potential generation not based on ion counting, we show that increased firing frequencies induced by higher temperatures imply more efficient use of sodium entry, and then a decrease in the metabolic energy cost required to restore the concentration gradients after an action potential. Also, we determine values of sodium conductance at which the hydrolysis efficiency presents a clear minimum.

A numerical investigation on the flow physics of koi carp (Cyprinus carpio koi) burst-and-coast swimming

Abstract—Burst-and-coast is the most common locomotion type in freely routine swimming of koi carps (Cyprinus carpio koi), which consists of a burst phase and a coast phase in each cycle and mostly leads to a straight-line trajectory. Combining with the tracking experiment, the flow physics of koi carp’s burst-andcoast swimming is investigated using a novel integrated CFD method solving the body-fluid interaction problem. The dynamical equations of a deforming body are formulated. Following that, the loose-coupled equations of the body dynamics and the fluid dynamics are numerically solved with the integrated method. The two burst modes, MT (Multiple Tail-beat) and HT (Half Tail-beat), which have been reported by the experiments, are investigated by numerical simulations in this paper. The body kinematics is predicted and the flow physics is visualized, which are in good agreement with the corresponding experiments. Furthermore, the optimization on the energy cost and several critical control mechanisms in burst-and-coast swimming of koi carps are explored, by varying the parameters in its selfpropelled swimming. In this paper, energetics is measured by the two mechanical quantities, total output power CP and Froude efficiency Fr. Results and discussion show that from the standpoint of mechanical energy, burst-and-coast swimming does not actually save energy comparing with steady swimming at the same average speed, in that frequently changing of speed leads to decrease of efficiency.

Algorithmic challenges in green data centers

With data centers being the supporting infrastructure for a wide range of IT services, their efficiency has become a big concern to operators, as well as to society, for both economic and environmental reasons. The goal of this thesis is to design energy-efficient algorithms that reduce energy cost while minimizing compromise to service. We focus on the algorithmic challenges at different levels of energy optimization across the data center stack. The algorithmic challenge at the device level is to improve the energy efficiency of a single computational device via techniques such as job scheduling and speed scaling. We analyze the common speed scaling algorithms in both the worst-case model and stochastic model to answer some fundamental issues in the design of speed scaling algorithms. The algorithmic challenge at the local data center level is to dynamically allocate resources (e.g., servers) and to dispatch the workload in a data center. We develop an online algorithm to make a data center more power-proportional by dynamically adapting the number of active servers. The algorithmic challenge at the global data center level is to dispatch the workload across multiple data centers, considering the geographical diversity of electricity price, availability of renewable energy, and network propagation delay. We propose algorithms to jointly optimize routing and provisioning in an online manner. Motivated by the above online decision problems, we move on to study a general class of online problem named "smoothed online convex optimization", which seeks to minimize the sum of a sequence of convex functions when "smooth" solutions are preferred. This model allows us to bridge different research communities and help us get a more fundamental understanding of general online decision problems.

Effects of CO2 enrichment on the bloom-forming cyanobacterium Microcystis aeruginosa (Cyanophyceae): Physiological responses and relationships with the availability of dissolved inorganic carbon

Microcystis aeruginosa Kutz. 7820 was cultured at 350 and 700 muL.L-1 CO2 to assess the impacts of doubled atmospheric CO2 concentration on this bloom-forming cyanobacterium. Doubling Of CO2 concentration in the airflow enhanced its growth by 52%-77%, with pH values decreased and dissolved inorganic carbon (DIC) increased in the medium. Photosynthetic efficiencies and dark respiratory rates expressed per unit chl a tended to increase with the doubling of CO2. However, saturating irradiances for photosynthesis and light-saturated photosynthetic rates normalized to cell number tended to decrease with the increase of DIC in the medium. Doubling of CO2 concentration in the airflow had less effect on DIC-saturated photosynthetic rates and apparent photosynthetic affinities for DIC. In the exponential phase, CO2 and HCO3- levels in the medium were higher than those required to saturate photosynthesis. Cultures with surface aeration were DIC limited in the stationary phase. The rate of CO2 dissolution into the liquid increased proportionally when CO2 in air was raised from 350 to 700 muL.L-1, thus increasing the availability of DIC in the medium and enhancing the rate of photosynthesis. Doubled CO2 could enhance CO2 dissolution, lower pH values, and influence the ionization fractions of various DIC species even when the photosynthesis was not DIC limited. Consequently, HCO3- concentrations in cultures were significantly higher than in controls, and the photosynthetic energy cost for the operation of CO2 concentrating mechanism might decrease.

非粮原料燃料乙醇发酵关键技术的研究

生物质燃料乙醇是一种高度清洁的交通液体燃料，是减少温室气体排放，缓解大气污染的最佳技术选择。以非粮原料生产燃料乙醇可以在进行能源生产的同时保证粮食安全，有利于产业的可持续发展。在众多的非粮原料中，甘薯是我国开发潜力最大的生物质能源作物之一。我国占世界甘薯种植总面积和产量的90％。同时，甘薯的单位面积燃料乙醇产量远大于玉米和小麦。其成本是目前酒精中最低廉的，因此利用甘薯生产乙醇是发展生物质燃料乙醇的首要选择。目前采用薯类全原料主要采用分批发酵生产乙醇，其技术水平低，发酵强度低，一般在0.7－2.5g/（L•h），乙醇浓度低，甘薯发酵乙醇为6－8％(v/v)，能耗高，环境负荷大，污染严重。针对上述问题，本文从菌株选育、原料预处理、中试放大、残糖成分分析等方面进行研究。 为了研究乙醇发酵生产规模扩大过程中，大型发酵罐底部高压条件下，CO2对酵母乙醇发酵的影响，我们通过CO2 加压的方法进行模拟试验，研究结果表明，发酵时间随压强的升高而逐渐延长，高压CO2 对乙醇发酵效率影响不大，在0.3 MPa 以下时，发酵效率均可达到90%以上。高压CO2 对发酵的抑制作用是高压和CO2 这两个因素联合作用的结果。高压CO2 条件下，酵母胞外酶和胞内重要酶类的酶活均表现出特征性。0.2 MPa 下，酶活性的变化趋势和0.1 MPa 条件下的较为一致。而0.3 MPa 下的酶活变化趋势与0.4 MPa 下的酶活更为接近。通过全基因表达分析发现在CO2 压力为0.3 MPa 下，乙醇发酵途径中多个基因表达量下调，同时海藻糖合成酶和热激蛋白基因表达量上调。 筛选耐高温的乙醇酵母菌株能够解决糖化温度和发酵温度不协调的矛盾，实现真正意义上的边糖化边发酵。高温发酵还能够降低发酵时的冷却成本，实现乙醇的周年生产。本研究筛选出一株高温发酵菌株Y-H1，进而我们对该菌株的胞外酶和胞内乙醇代谢重要酶类的酶活性进行了分析。结果表明Y-H1 能够在40 ℃条件下正常进行乙醇发酵，发酵33h，最终乙醇浓度达到10.7%（w/w），发酵效率达到90%以上。同时发酵液最终pH 在3.5 左右，显示菌株具有一定的耐酸性能力。同时观察到40 ℃下，菌株的胞外酶和胞内乙醇代谢重要酶类的酶活性发生了变化，乙醇发酵途径中关键酶基因表达下调，而海藻糖合成酶与热激蛋白基因表达量上调，这些结果为进一步研究酵母菌耐热调控机理提供了依据。 糖蜜是一种大规模工业生产乙醇的理想原料，本研究利用选育高浓度乙醇发酵菌株结合配套的发酵稳定剂，研究了糖蜜高浓度乙醇发酵情况。结果表明采用冷酸沉淀预处理糖蜜溶液，采用分批补料的发酵方式，乙醇浓度最高达到了10.26% (w/w)，发酵时间为42 h。同时观察到在糖蜜发酵中，乙醛含量与乙醇浓度存在一定的相关性。 快速乙醇发酵对于缩短乙醇生产周期、降低乙醇生产成本、减少原料腐烂损失具有重要意义。本研究诱变和筛选得到了一株快速乙醇发酵菌株10232B。在优化后的发酵条件下，采用10L 发酵罐进行分批乙醇发酵，经过18h,乙醇的最终浓度达到88.5g/L,发酵效率93.6%，平均乙醇生产速度达到4.92 g/L/h。此菌株在保持较高乙醇生产浓度的同时，拥有快速生产乙醇的能力，适合作为快速乙醇发酵生产菌种。 由于鲜甘薯具有粘度大的特点，传统液化糖化处理很难在短时间内充分糖化原料；高粘度的醪液也难以进行管道输送，容易堵塞管路；同时，也会降低后续的乙醇发酵效率。 本文采用了快速粘度分析法对鲜甘薯糊化粘度特性进行了分析，进而对预处理条件进行了研究，在最佳预处理条件下，糖化2h 后，醪液葡萄糖值最高可达99.3，粘度4.5×104 mPa.s，而采用传统糖化工艺，醪液DE 值仅为85.8，粘度大于1.0×105 mPa.s。 此预处理方法也可用于快速糖化不加水的醪液。后续的乙醇发酵试验表明，通过此预处理方法获得的糖化醪液对乙醇发酵无负面影响。 在前期已实现了实验室水平的鲜甘薯燃料乙醇快速乙醇发酵基础上，进一步将发酵规模扩大到500L，在中试水平上对甘薯乙醇发酵进行了研究。结果表明在500L 中试规模，采用边糖化边发酵（SSF）工艺，在料液比为3∶1，发酵醪液最高粘度为6×104mPa.s 条件下，发酵37h，乙醇浓度达到了12.7%（v/v），发酵效率91%，发酵强度为2.7 g/（L•h）。与目前国内的薯类乙醇发酵生产技术水平具有明显的优越性。 为研究甘薯、木薯乙醇发酵中残糖的组成，采用了高效液相色谱—蒸发光散射检测法，对乙醇发酵残糖进行了分析。结果表明，甘薯、木薯乙醇发酵残糖均为寡聚糖，主要由葡萄糖、木糖、半乳糖、阿拉伯糖和甘露糖构成。随着发酵时间延长，寡聚糖中的葡萄糖、半乳糖、甘露糖可被缓慢的水解释放。提高糖化酶量仅在一定程度上降低残糖，过量的糖化酶反而会导致残糖增加。同时发现3, 5-二硝基水杨酸法不能准确测定甘薯、木薯乙醇发酵中的残总糖含量。进一步筛选了两株残糖降解菌株，对甘薯乙醇发酵残糖的降解利用率均达到了40%以上，而且还能显著降低发酵醪液粘度。经形态学和rRNA ITS 序列分析，确定这两株菌分别属于为木霉属和曲霉属黑曲霉组。 通过对以甘薯原料为代表的非粮原料发酵技术研究开发，以期形成乙醇转化率高，能耗低，生产效率高、季节适应性好，原料适应性广，经济性强，符合清洁生产机制的燃料乙醇高效转化技术，为具有我国特色的燃料乙醇发展模式提供技术支持。 Sweet potato is one of the major feedstock for the fuel ethanol production in China. The planting area and the yield in China take 90% of the world. Sweet potato is an efficient kind of energy crops. The energy outcome per area is higher than corn or wheat. And the manufacture cost of ethanol is the lowest, compared with corn and wheat. So sweet potato is the favorable crop for the bioethanol production in China. However, the low-level fermentation technology restricts the development of ethanol production by sweet potato, including slow ethanol production rate, low ethanol concentration and high energy cost. To solve these problems, we conducted research on the strain breeding, pretreatment, pilot fermentation test and residual saccharides analysis. To study the impact of hyperbaric condition at bottom of the large fermentor on yeast fermentation, high pressure carbon dioxide (CO2) was adopted to simulate the situation. The results showed that the fermentation was prolonged with the increasing pressure. The pressure of CO2 had little impact on the ethanol yield which could reach 90% under the pressure below 0.3 MPa. The inhibition was combined by the high pressure and CO2. Under the high CO2 pressure, the extracellular and important intracellular enzyme activities were different from those under normal state. The changes under 0.1 MPa and 0.2 MPa were similar. The changes under 0.3 MPa were closer to those under 0.4 MPa. The application of thermotolerance yeast could solve the problem of the inconsistent temperature between fermentation and saccharificaton and fulfill the real simultaneous saccharification and fermentation. And it could reduce the cooling cost. A thermotolerance strain Y-H1 was isolated in our research. It gave high ethanol concentration of 10.7%（w/w）at 40 ℃ for 33 h. The ethanol yield efficiency was over 90%. At 40 ℃, the extracellular and important intracellular enzyme activities of Y-H1 showed the difference with normal state, which may indicate its physiological changes at the high temperature. Molasses is another feedstock for industrial ethanol production. By our ethanol-tolerance strain and the regulation reagents, the fermentation with high ethanol concentration was investigated. In fed-batch mode combined with cold acid deposition, the highest ethanol concentration was 10.26% (w/w) for 42h. The aldehyde concentration in fermentation was found to be related to ethanol concentration. The development of a rapid ethanol fermentation strain of Zymomonas mobilis is essential for reducing the cost of ethanol production and for the timely utilization of fresh material that is easily decayed in the Chinese bioethanol industry. A mutant Z. mobilis strain, 10232B, was generated by UV mutagenesis. Under these optimized conditions, fermentation of the mutant Z. mobilis 10232B strain was completed in just 18 h with a high ethanol production rate, at an average of 4.92 gL-1h-1 per batch. The final maximum ethanol concentration was 88.5 gL-1, with an ethanol yield efficiency of 93.6%. This result illustrated the potential use of the mutant Z. mobilis 10232B strain in rapid ethanol fermentation in order to help reduce the cost of industrial ethanol production. As fresh sweet potato syrup shows high viscosity, it is hard to be fully converted to glucose by enzymes in the traditional saccharification process. The high-viscosity syrup is difficult to be transmitted in pipes, which may be easily blocked. Meanwhile it could also reduce the later ethanol fermentation efficiency. To solve these problems, effects of the pretreatment conditions were investigated. The highest dextrose equivalent value of 99.3 and the lowest viscosity of 4.5×104 mPa.s were obtained by the most favorable pretreatment conditions, while those of 85.8 and over 1.0×105 mPa.s was produced by traditional treatment conditions. The pretreatment could also be applied on the material syrup without adding water. The later experiments showed that the pretreated syrup had no negative effect on the ethanol fermentation and exhibited lower viscosity. The fuel ethanol rapid production from fresh sweet potato was enlarged in the 500L pilot scale after its fulfillment on the laboratory level. The optimal ratio of material to water was 3 to 1 in 500L fermentor. With low-temperature-cooking (85 ℃) using SSF, the Saccharomyces cerevisiae was able to produce ethanol 97.44 g/kg for 37h, which reached 92% of theoretical yield. The average ethanol production rate was 4.06 g/kg/h. And the maximum viscosity of syrup reached 6×104mPa.s. The results showed its superiority over current industrial ethanol fermentation. The compositions of the residual saccharides in the ethanol fermentation by sweet potato and cassava were analyzed by high performance liquid chromatography coupled with evaporative light-scattering detector. The results showed that all the residual saccharides were oligosaccharides, mainly composed of glucose, xylose, galactose, arabinose and mannose. The glucose, galactose and mannose could be slowly hydrolyzed from oligosaccharides in syrup during a long period. To increase the glucoamylase dosage could lower the residual saccharides to a certain extent. However, excess glucoamylase dosage led to more residual saccharides. And the method of 3, 5-dinitrosalicylic acid could not accurately quantify the residual total saccharides content. Two residual saccharides degrading strains were isolated, which could utilize 40% of total residual saccharide and lower the syrup viscosity. With the analysis of morphology and internal transcribed spacer sequence, they were finally identified as species of Trichoderma and Aspergillus niger.

Characteristics of preferred gait patterns: considerations for exercise prescription

Gait patterns have been widely studied in different fields of science for their particular characteristics. A dynamic approach of human locomotion considers walking and running as two stable behaviors adopted spontaneously under certain levels and natures of constraints. When no constraints are imposed, people naturally prefer to walk at the typical speed (i.e., around 4.5 km.h-1) that minimizes metabolic energy cost. The preferred walking speed (PWS) is also known to be an indicator of mobility and an important clinical factor in tracking impairements in motor behaviors. When constrained to move at higher speeds (e.g., being late), people naturally switch their preference to running for similar optimization reasons (e.g., physiological, biomechanical, perceptual, attentionnal costs). Indeed, the preferred transition speed (PTS) marks the natural seperation between walking and running and consistently falls within a speed range around 7.5 km.h-1. This chapter describes the constraint-dependant spontaneous organisation of the locomotor system, specifically on the walk-to-run speed continuum. We provide examples of the possibility of long-term adaptations of preferred behaviors to specific constraints such as factors related to traditional clothing or practice. We use knowledge from studies on preferred behaviors and on the relationship between affect and exercise adherence as a backdrop to prescribing a walk exercise program with an emphasis on populations with overweight or obesity.

DIP: Density Inference Protocol for wireless sensor networks and its application to density-unbiased statistics

Wireless sensor networks have recently emerged as enablers of important applications such as environmental, chemical and nuclear sensing systems. Such applications have sophisticated spatial-temporal semantics that set them aside from traditional wireless networks. For example, the computation of temperature averaged over the sensor field must take into account local densities. This is crucial since otherwise the estimated average temperature can be biased by over-sampling areas where a lot more sensors exist. Thus, we envision that a fundamental service that a wireless sensor network should provide is that of estimating local densities. In this paper, we propose a lightweight probabilistic density inference protocol, we call DIP, which allows each sensor node to implicitly estimate its neighborhood size without the explicit exchange of node identifiers as in existing density discovery schemes. The theoretical basis of DIP is a probabilistic analysis which gives the relationship between the number of sensor nodes contending in the neighborhood of a node and the level of contention measured by that node. Extensive simulations confirm the premise of DIP: it can provide statistically reliable and accurate estimates of local density at a very low energy cost and constant running time. We demonstrate how applications could be built on top of our DIP-based service by computing density-unbiased statistics from estimated local densities.