Miracle-dz/UniFAR-FTUs huggingface dataset:
Intensive Short Term Measurements of the Ambient Aerosol in the Greater Cincinnati Airshed

As part of a larger study undertaken in the Greater Cincinnati area to determine if diesel truck emissions are adjuvant to naturally occurring bioaerosols in the initiation of allergies in children, a more detailed intensive measurement campaign was undertaken to elucidate the characteristics of the ambient aerosol and compare to the regular, integrated measurements being conducted. The mass concentration, total number concentration, size distributions, and morphologies were established at several locations including a residential area far from major traffic (Mernic), a suburban area on both sides of a major highway (I-275, Blue Ash), a site in the city center very close to the highway (I-75, Findlay), and an enclosed oval track at a Truck Driving School. Differences between real-time tapered element oscillating microbalance (TEOM) average mass concentrations and integrated Harvard impactor (HI) measurements were observed, with the magnitude of the difference being dependent on location and the organic compounds (OC) concentrations in the sample. Qualitative variation of the peaks in real-time PM 2.5 concentrations were observed with variation in truck traffic at the Findlay site; and no peaks in real-time PM 2.5 levels were observed at Mernic. Minimal variation in PM 2.5 was observed with distance from the highway at the Blue Ash site (fewer trucks). The site at Mernic had a smaller fraction of aggregated particles in comparison to the other sites. The two-dimensional fractal dimensions measured at the Findlay, Blue Ash, and Truck Driving School sites were statistically identical (1.58–1.61) but were higher than that measured at the Mernic site (1.41). Implications of the intensive measurement campaign vis-à-vis the epidemiological study are discussed briefly.
Modeling Elasticity Trade-Offs in Adaptive Mixed Systems

In the past decade, elastic computing has emerged as a popular solution approach for on-demand computing resources' provisioning. Today, such dynamic resource provisioning is used not only in machine-based computing systems but also in mixed systems containing machine- and human-based computing elements. Many efforts have been undertaken to achieve resource elasticity. However, to provide a truly elastic computation, system designers also need to foresee trade-offs between cost, quality, and resources. Unfortunately, the lack of modeling tools leads to difficulty in designing on-demand provisioning strategy in mixed systems. In this paper we present a modeling tool named Elasticity Profile (EP) that specifies constructs for modeling the elastic behavior of mixed systems with respect to trade-offs between cost, quality, and resources. We also present a conceptual framework where our EP can be deployed, utilized, and bound to runtime systems. Furthermore, we demonstrate the suitability of EP model using several use cases.
A New Management Method for Reliable Peer-to-Peer Energy Sharing in Power Distribution Systems

The current expansion of renewable energies, restructuring in power systems, and high tendency to preserve the privacy of energy customers could lead to significant changes in distribution systems. Accordingly, studies on local markets have introduced a suitable framework for energy trading known as the Peer-to-Peer (P2P) market in distribution systems. Several research works have been done on the P2P market modeling and optimization in recent years. This paper aims to develop an appropriate P2P market framework in which the distribution system operator (DSO) can rerun the P2P market and maneuver in the case of the network failure. Respectively, in case of any grid failure, the P2P market can be adjusted according to new conditions of the grid, which is not studied in the previously developed methodologies. In addition to enabling the P2P framework to be usable when a network failure occurs in the system, this paper proposes a reliability cost model associated with participated sellers in the P2P market, which enables buyers to consider the reliability of the sellers in their decisions. Consequently, the developed scheme facilitates the reliable operation of distribution systems in a distributed manner. Finally, the developed structure is simulated on a 33-bus test system to analyze its effectiveness in operating the system.
Fast Consistency Checking for the Solaris File System

Our Netra NFS group at Sun set out to solve the challenging problem of providing remote Network File System (NFS) service with high performance and availability. An NFS server must guarantee the permanence of changes to the file system before acknowledging an NFS request. Thus, the server's underlying local file system must perform update operations synchronously to stable storage with potentially high latency. Our solution to this problem involves using the Solaris Unix File System (UFS), derived from the Berkeley Fast File System (FFS), in conjunction with nonvolatile RAM (NVRAM) as fast stable storage. We evaluated the system using the LADDIS benchmark and as a result, developed a cacheing technique for block-mapping information that gave us a 23% increase in measured server throughput in our standard RAID-5 server configuration. With recent increases in disk capacity and RAID technology, filesystem sizes have reached a point not imagined by the FFS designers, requiring an approach to checking file-system consistency that does not grow proportionately with file-system size. We examined several log-based solutions to providing fast crash recovery, but none could use the NVRAM effectively and meet our performance requirements. As an alternative, we developed an approach that uses UFS but maintains file-system working-set information, so that the consistency checker needs to examine only the active portions of a file system. This approach met our performance goals and also reduced file-system consistency-checking times to between 3% and 25% of those in the original UFS implementation.
Power cycling tests at high temperatures with IGBT power modules for hybrid electrical vehicle applications

In this publication, test results of power cycling tests are presented with 600V IGBT power modules for hybrid electrical vehicle (HEV) applications at high junction temperatures. First, the power cycling capability of standard packaging technology in wide ΔTj range is investigated. Afterwards the reliability improvement of new packaging technologies is shown.
The power crust

The power crust is a construction which takes a sample of points from the surface of a three-dimensional object and produces a surface mesh and an approximate medial axis. The approach is to first approximate the medial axis transform (MAT) of the object. We then use an inverse transform to produce the surface representation from the MAT. This idea leads to a simple algorithm with theoretical guarantees comparable to those of other surface reconstruction and medial axis approximation algorithms. It also comes with a guarantee that does not depend in any way on the quality of the input point sample. Any input gives an output surface which is the `watertight' boundary of a three-dimensional polyhedral solid: the solid described by the approximate MAT. This unconditional guarantee makes the algorithm quite robust and eliminates the polygonalization, hole-filling or manifold extraction post-processing steps required in previous surface reconstruction algorithms. In this paper, we use the theory to develop a power crust implementation which is indeed robust for realistic and even difficult samples. We describe the careful design of a key subroutine which labels parts of the MAT as inside or outside of the object, easy in theory but non-trivial in practice. We find that we can handle areas in which the input sampling is scanty or noisy by simply discarding the unreliable parts of the MAT approximation. We demonstrate good empirical results on inputs including models with sharp corners, sparse and unevenly distributed point samples, holes, and noise, both natural and synthetic. We also demonstrate some simple extensions: intentionally leaving holes where there is no data, producing approximate offset surfaces, and simplifying the approximate MAT in a principled way to preserve stable features.
Composable controllers for physics-based character animation

An ambitious goal in the area of physics-based computer animation is the creation of virtual actors that autonomously synthesize realistic human motions and possess a broad repertoire of lifelike motor skills. To this end, the control of dynamic, anthropomorphic figures subject to gravity and contact forces remains a difficult open problem. We propose a framework for composing controllers in order to enhance the motor abilities of such figures. A key contribution of our composition framework is an explicit model of the “pre-conditions” under which motor controllers are expected to function properly. We demonstrate controller composition with pre-conditions determined not only manually, but also automatically based on Support Vector Machine (SVM) learning theory. We evaluate our composition framework using a family of controllers capable of synthesizing basic actions such as balance, protective stepping when balance is disturbed, protective arm reactions when falling, and multiple ways of standing up after a fall. We furthermore demonstrate these basic controllers working in conjunction with more dynamic motor skills within a prototype virtual stunt-person. Our composition framework promises to enable the community of physics-based animation practitioners to easily exchange motor controllers and integrate them into dynamic characters.
CONFab: component based optimization of WSN protocol stacks using deployment feedback

Wireless sensor networks are characterized by a large number of non-standardized protocols and varying application requirements. This creates need for a systematic approach to rapidly design and optimize deployment specific protocol stacks. We employ component based optimization as a candidate solution, and use it as a basis for an extensible software framework called CONFab. We treat a particular protocol stack as a collection of interdependent configurable components. CONFab captures a deployment scenario description, relates it to the desired performance metrics, and correspondingly suggests suitable protocol stacks and parameter settings. It utilizes ontology centric knowledge base to select components from a pool of alternatives, reason on their compatibility and, thus create appropriate protocol stacks. The framework is equipped with a number of additional plugins that allow, for instance, to incorporate feedback from deployed systems and user inputs to anticipate network performance. We use a set of well-known MAC and routing protocols to validate the framework on the Indriya testbed in different user specified application and deployment conditions. The results indicate that CONFab with its component based approach helps in obtaining suitable protocol stacks and thereby achieving high performance characteristics.
The Effect of Entrepreneurship Education and Sociological on Student's Entrepreneurial Intention : The Perspective of Entrepreneurial Skills Theory and Social Capital Theory

This study aims to analyze the effect of entrepreneurship education and sociological factors on the entrepreneurial intentions of students. Two theories integrated into this research were the Entrepreneurial Skills Theory and Social Capital Theory. The research adopts a quantitative approach, applying structural equation modeling (SEM) and Partial Least Square (PLS) for analysis. The non-probability sampling technique used was Purposive Sampling to determine the research sample. The study participants consisted of 68 college students in Tasikmalaya, Indonesia, selected to complete an online questionnaire. The research findings indicated that entrepreneurship education and sociological factors significantly and positively influence students' entrepreneurial intentions. Furthermore, both the Entrepreneurial Skills Theory and Social Capital Theory not only have individual positive impacts but also complement each other in shaping students' entrepreneurial intentions. The integration of entrepreneurship education, combining the development of individual skills with the strengthening of social relationships and collaboration, was an effective foundation for motivating and preparing students to face challenges in the business world.
Correction to “Reconstruction of the flanks of the Mid‐Atlantic Ridge, 28° to 29°N: Implications for evolution of young oceanic lithosphere at slow‐spreading centers”

[1] We reconstruct the flanks of the Mid-Atlantic Ridge (MAR) between 28° and 29°N from 1 to 10 Ma at intervals of 1 Myr for the purpose of investigating evolution of young oceanic lithosphere morphology and its variation through time using an innovative method that combines seafloor subsidence correction with interpolated isochrons and rotation poles. Reconstruction results are consistent with formation of abyssal hills every 1 to 2 Myr in 2–3 Myr old lithosphere at the outer edge of the ridge mountains as a result of transition from dynamic regime near the axis to isostatic regime of the flanks. The oblique passage of structures formed at the axial valley walls through this transition zone may play a role in the development of inside corner high bathymetry. Asymmetric juxtaposition of abyssal hill morphology in reconstruction is indicative of independent formation and evolution of the morphotectonic fabric on opposing flanks. The two major factors affecting asymmetric ridge flank morphology are found to be sense of axial offset and fluctuation of magmatic activity at the segment scale. Sense of axial offset determines the relative distribution of inside and outside corner bathymetry on the flanks. Enhanced magma supply and associated segment propagation may contribute to half-spreading rate asymmetry, accretion of thicker crust, and formation of larger abyssal hills on the faster spreading flank. Consistent alignment in reconstruction of the base of the steep walls bounding inside corner bathymetry confirms that they mark the boundaries between segments on the flanks and that the deep sediment-filled basins, typically identified as discordant zones, are attributable to outside corner bathymetry.
A new instrument for estimating the survival of patients with metastatic epidural spinal cord compression from esophageal cancer

Abstract Background. This study was initiated to create a predictive instrument for estimating the survival of patients with metastatic epidural spinal cord compression (MESCC) from esophageal cancer. Methods. In 27 patients irradiated for MESCC from esophageal cancer, the following nine characteristics were evaluated for potential impact on survival: age, gender, Eastern Cooperative Oncology Group (ECOG) performance score, histology, number of involved vertebrae, ambulatory status before irradiation, further bone metastases, visceral metastases, and dynamic of developing motor deficits before irradiation. In addition, the impact of the radiation regimen was investigated. According to Bonferroni correction, p-values of < 0.006 were significant representing an alpha level of < 0.05. Results. ECOG performance score (p < 0.001), number of involved vertebrae (p = 0.005), and visceral metastases (p = 0.004) had a significant impact on survival and were included in the predictive instrument. Scoring points for each characteristic were calculated by dividing the 6-months survival rates (in %) by 10. The prognostic score for each patient was obtained by adding the scoring points of the three characteristics. The prognostic scores were 4, 9, 10, 14 or 20 points. Three prognostic groups were formed, 4 points (n = 11), 9-14 points (n = 12) and 20 points (n = 4). The corresponding 6-months survival rates were 0%, 33% and 100%, respectively (p < 0.001). Median survival times were 1 month, 5 months and 16.5 months, respectively. Conclusions. This new instrument allows the physician estimate the 6-months survival probability of an individual patient presenting with MESCC from esophageal cancer. This is important to know for optimally personalizing the treatment of these patients.
Minimum-Delay Multicast Algorithms for Mesh Overlays

We study delivering delay-sensitive data to a group of receivers with minimum latency. This latency consists of the time that the data spends in overlay links as well as the delay incurred at each overlay node, which has to send out a piece of data several times over a finite-capacity network connection. The latter part is a significant portion of the total delay as we show in the paper, yet it is often ignored or only partially addressed by previous multicast algorithms. We analyze the actual delay in multicast trees and consider building trees with minimum-average and minimum-maximum delay. We show the NP-hardness of these problems and prove that they cannot be approximated in polynomial time to within any reasonable approximation ratio. We then present a set of algorithms to build minimum-delay multicast trees that cover a wide range of application requirements-min-average and min-max delay, for different scales, real-time requirements, and session characteristics. We conduct comprehensive experiments on different real-world datasets, using various overlay network models. The results confirm that our algorithms can achieve much lower delays (up to 60% less) and up to orders-of-magnitude faster running times (i.e., supporting larger scales) than previous related approaches.
Call center capacity allocation with random workload

We consider a call center staffing problem with two types of costumers of which the arrival rates are allowed to be a random and non-stationary. In order to efficiently cope with such random workload fluctuations, the workforce presents some flexibility: the agents can be, in real-time, affected to each type of customers according to the instantaneously observed workload and the associated/relative cost criteria. We model this staffing problem as a cost optimization-based newsboy-type model. We then show how to numerically solve this model. In order to deal with the randomness characterizing the workloads of the call processes, we consider several solution tracks. First, we solve the model under the assumption that the workloads are deterministic and equal to their average values. In the second approach, we explicitly formulate in the optimization model the stochastic nature of the workloads. As a third approach, we develop a robust-type solution. Via several numerical analyzes we show the impact of the arrival rates randomness on the optimal staffing policy and on the operating costs.
Mitigating DNS random subdomain DDoS attacks by distinct heavy hitters sketches

Random Subdomain DDoS attacks on the Domain Name System (DNS) infrastructure are becoming a popular vector in recent attacks (e.g., recent Mirai attack on Dyn). In these attacks, many queries are sent for a single or a few victim domains, yet they include highly varying non-existent subdomains generated randomly. Motivated by these attacks we designed and implemented novel and efficient algorithms for distinct heavy hitters (dHH). A (classic) heavy hitter (HH) in a stream of elements is a key (e.g., the domain of a query) which appears in many elements (e.g., requests). When stream elements consist of ¡key, subkey¿ pairs, (¡domain, subdomain¿) a distinct heavy hitter (dhh) is a key that is paired with a large number of different subkeys. Our algorithms dominate previous designs in both the asymptotic (theoretical) sense and practicality. Specifically the new fixed-size algorithms are simple to code and with asymptotically optimal space accuracy tradeoffs. Based on these algorithms, we build and implement a system for detection and mitigation of Random Subdomain DDoS attacks. We perform experimental evaluation, demonstrating the effectiveness of our algorithms.
Novel Acrylonitrile Derivatives, YHO-13177 and YHO-13351, Reverse BCRP/ABCG2-Mediated Drug Resistance In Vitro and In Vivo

Breast cancer resistance protein (BCRP/ABCG2) confers resistance to anticancer drugs such as 7-ethyl-10-hydroxycamptothecin (SN-38, an active metabolite of irinotecan), mitoxantrone, and topotecan. In this study, we examined the reversing effects of YHO-13177, a novel acrylonitrile derivative, and its water-soluble diethylaminoacetate prodrug YHO-13351 on the BCRP-mediated drug resistance. YHO-13177 potentiated the cytotoxicity of SN-38, mitoxantrone, and topotecan in both BCRP-transduced human colon cancer HCT116 (HCT116/BCRP) cells and SN-38–resistant human lung cancer A549 (A549/SN4) cells that express BCRP, but had little effect in the parental cells. In addition, YHO-13177 potentiated the cytotoxicity of SN-38 in human lung cancer NCI-H460 and NCI-H23, myeloma RPMI-8226, and pancreatic cancer AsPC-1 cells that intrinsically expressed BCRP. In contrast, it had no effect on P-glycoprotein–mediated paclitaxel resistance in MDR1-transduced human leukemia K562 cells and multidrug resistance-related protein 1–mediated doxorubicin resistance in MRP1-transfected human epidermoid cancer KB-3-1 cells. YHO-13177 increased the intracellular accumulation of Hoechst 33342, a substrate of BCRP, at 30 minutes and partially suppressed the expression of BCRP protein at more than 24 hours after its treatment in both HCT116/BCRP and A549/SN4 cells. In mice, YHO-13351 was rapidly converted into YHO-13177 after its oral or intravenous administration. Coadministration of irinotecan with YHO-13351 significantly increased the survival time of mice inoculated with BCRP-transduced murine leukemia P388 cells and suppressed the tumor growth in an HCT116/BCRP xenograft model, whereas irinotecan alone had little effect in these tumor models. These findings suggest that YHO-13351, a prodrug of YHO-13177, could be clinically useful for reversing BCRP-mediated drug resistance in cancer chemotherapy. Mol Cancer Ther; 10(7); 1252–63. ©2011 AACR.
Separations in Communication Complexity Using Cheat Sheets and Information Complexity

While exponential separations are known between quantum and randomized communication complexity for partial functions (Raz, STOC 1999), the best known separation between these measures for a total function is quadratic, witnessed by the disjointness function. We give the first super-quadratic separation between quantum and randomized communication complexity for a total function, giving an example exhibiting a power 2.5 gap. We further present a 1.5 power separation between exact quantum and randomized communication complexity, improving on the previous ≈ 1.15 separation by Ambainis (STOC 2013). Finally, we present a nearly optimal quadratic separation between randomized communication complexity and the logarithm of the partition number, improving upon the previous best power 1.5 separation due to Goos, Jayram, Pitassi, and Watson. Our results are the communication analogues of separations in query complexity proved using the recent cheat sheet framework of Aaronson, Ben-David, and Kothari (STOC 2016). Our main technical results are randomized communication and information complexity lower bounds for a family of functions, called lookup functions, that generalize and port the cheat sheet framework to communication complexity.
Local control strategies for groups of mobile autonomous agents

The problem of achieving a specified formation among a group of mobile autonomous agents by distributed control is studied. If convergence to a point is feasible, then more general formations are achievable too, so the focus is on convergence to a point (the agreement problem). Three formation strategies are studied and convergence is proved under certain conditions. Also, motivated by the question of whether collisions occur, formation evolution is studied.