Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Method to Analyze Asynchronous P-CSMA

Different from synchronous mode, asynchronous p-CSMA has no timeslot. As a result, the propagation delay between nodes can not be ignored and will have heavy effect on the probability of packets collision. From the view of the packets collision, the paper for the first time establishes a preemptive asynchronous p-CSMA probability model with consideration of the propagation delay and reveals the essence of interaction within multi-nodes. The network performance can be evaluated through the targets of throughput and packets delay with the probability model. Based on a typical asynchronous p-CSMA network -- VDL2, simulations are also carried out to verify the correctness of this model in this paper. Finally, trends of key targets are given.
Asynchronous Rate Chaos in Spiking Neuronal Circuits

The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. Author Summary Cortical circuits exhibit complex temporal patterns of spiking and are exquisitely sensitive to small perturbations in their ongoing activity. These features are all suggestive of an underlying chaotic dynamics. Theoretical works have indicated that a rich dynamical reservoir can endow neuronal circuits with remarkable computational capabilities. Nevertheless, the mechanisms underlying chaos in circuits of spiking neurons remain unknown. We combine analytical calculations and numerical simulations to investigate this fundamental issue. Our key result is that chaotic firing rate fluctuations on the time scales of the synaptic dynamics emerge generically from the network collective dynamics. Our results pave the way in the study of the physiological mechanisms and computational significance of chaotic states in neuronal networks.
Leveraging Intermediated Interactions to Support Utilization of Persuasive Personal Health Informatics

Behavior change support systems (BCSS) and persuasive technologies for healthcare often entail users interacting with mobile devices. However, especially in developing countries, the target community is unfamiliar with and often intimidated by new technologies. In this paper we propose the use of intermediaries to facilitate interaction with a mobile phone-based application and to motivate ongoing use by the target beneficiaries. The application incentivizes utilization through gamification techniques, using badges, scoreboards, and other rewards. For example, a young girl might help her father keep track of his walking and diet, maintaining participation as much for her father's health as for the social awards given by the app. We explain how intermediaries can be leveraged to improve utilization and engagement of the beneficiaries, and describe factors affecting interaction between the participating pairs and interaction with the application. This study highlights the importance of social rapport - typically through a familial relationship - as a key component of the intervention. Finally, we discuss the implications of designing for the motivation of two different users: gamification, personalization and utility play different roles for the intermediary and the beneficiary but ultimately combine to make a more effective application for the beneficiary than one targeting the beneficiary alone.
Differentially Private Rank Aggregation

Given a collection of rankings of a set of items, rank aggregation seeks to compute a ranking that can serve as a single best representative of the collection. Rank aggregation is a well-studied problem and a number of effective algorithmic solutions have been proposed in the literature. However, when individuals are asked to contribute a ranking, they may be concerned that their personal preferences will be disclosed inappropriately to others. This acts as a disincentive to individuals to respond honestly in expressing their preferences and impedes data collection and data sharing. We address this problem by investigating rank aggregation under differential privacy, which requires that a released output (here, the aggregate ranking computed from individuals’ rankings) remain almost the same if any one individual’s ranking is removed from the input. We propose a number of differentially-private rank aggregation algorithms: two are inspired by non-private approximate rank aggregators from the existing literature; another uses a novel rejection sampling method to sample privately from a complex distribution. For all the methods we propose, we quantify, both theoretically and empirically, the “cost” of privacy in terms of the quality of the rank aggregation computed.
Programmed cell death in Dictyostelium.

Programmed cell death (PCD) of Dictyostelium discoideum cells was triggered precisely and studied quantitatively in an in vitro system involving differentiation without morphogenesis. In temporal succession after the triggering of differentiation, PCD included first an irreversible step leading to the inability to regrow at 8 hours. At 12 hours, massive vacuolisation was best evidenced by confocal microscopy, and prominent cytoplasmic condensation and focal chromatin condensation could be observed by electron microscopy. Membrane permeabilization occurred only very late (at 40-60 hours) as judged by propidium iodide staining. No early DNA fragmentation could be detected by standard or pulsed field gel electrophoresis. These traits exhibit some similarity to those of previously described non-apoptotic and apoptotic PCD, suggesting the hypothesis of a single core molecular mechanism of PCD emerging in evolution before the postulated multiple emergences of multicellularity. A single core mechanism would underly phenotypic variations of PCD resulting in various cells from differences in enzymatic equipment and mechanical constraints. A prediction is that some of the molecules involved in the core PCD mechanism of even phylogenetically very distant organisms, e.g. Dictyostelium and vertebrates, should be related.
Aiding Software Developers to Maintain Developer Tests

Unit and integration tests can be invaluable during software maintenance as they help to understand pieces of code, they help with quality assurance and they build up confidence amongst developers. Unfortunately then, previous research has shown that unit tests do not always co-evolve nicely with the production code, thus leaving the software vulnerable. This paper presents TestNForce, a tool that helps developers to identify the unit tests that need to be altered and executed after a code change, thereby reducing the effort needed to keep the unit tests in sync with the changes to the production code. In order to evaluate TestNForce, we perform a user study that evaluates the adequacy, usefulness and completeness of TestNForce.
Touring a sequence of polygons

Given a sequence of <i>k</i> polygons in the plane, a start point <i>s</i>, and a target point, <i>t</i>, we seek a shortest path that starts at <i>s</i>, visits in order each of the polygons, and ends at <i>t</i>. If the polygons are disjoint and convex, we give an algorithm running in time <i>O(kn log (n/k))</i>, where <i>n</i> is the total number of vertices specifying the polygons. We also extend our results to a case in which the convex polygons are arbitrarily intersecting and the subpath between any two consecutive polygons is constrained to lie within a simply connected region; the algorithm uses <i>O(nk<sup>2</sup> log n)</i> time. Our methods are simple and allow shortest path queries from <i>s</i> to a query point <i>t</i> to be answered in time <i>O(k log n + m)</i>, where <i>m</i> is the combinatorial path length. We show that for nonconvex polygons this "touring polygons" problem is NP-hard.The touring polygons problem is a strict generalization of some classic problems in computational geometry, including the safari problem, the zoo-keeper problem, and the watchman route problem in a simple polygon. Our new results give an order of magnitude improvement in the running times of the safari problem and the watchman route problem: We solve the safari problem in <i>O(n<sup>2</sup> log n)</i> time and the watchman route problem (through a fixed point <i>s</i>) in time <i>O(n<sup>3</sup> log n)</i>, compared with the previous time bounds of <i>O(n<sup>3</sup>)</i> and <i>O(n<sup>4</sup>)</i>, respectively.
Physical Land Suitability for Civet Arabica Coffee: Case Study of Bandung and West Bandung Regencies, Indonesia

Indonesia has been widely known as the best Arabica coffee (Coffea arabica) producer, in terms of both aspects, quality and number of product. Currently, its production, however, declines to the 3rd rank internationally. Issues emerged in the coffee cultivation are: land unsuitability, low quality of seeds, and poor management. Among Arabica coffee types, wild civet coffee is the most expensive one and harvested from the coffee beans which have been digested naturally. The study aims to determine the physical suitability of land as well as the constraints related to land for civet Arabica coffee in selected study cases, e.g., Bandung and Bandung Barat. The research methods employ multi-criteria analysis, and combined with weighted overlaying techniques for mapping. The criteria include temperature, rainfall, humidity, duration of dry season, slope, altitude, type of soil, soil texture, and erosion potential. Parameters of civet (Paradoxurus hermaphroditus) are land use, altitude, and temperature. Local policy strongly supports the extensive management for land and the increase of coffee export. Processing data involved matching the comparison between guideline requirements for the land suitability classes, characteristics of Arabica coffee and civet habitat. The results covered the profile suitable land of the civet Arabica coffee in the study areas.
Efficient skyline computation over distributed interval data

The increasing volume of uncertain data has resulted in a dire need for supporting efficient uncertain data management. The skyline query as an important aspect of data management has received considerable attention in recent years, because of its importance in making intelligent decisions over complex data. Moreover, data collection and storage have become increasingly distributed, which makes the central assembly of data for storage and query infeasible and inefficient. Although many research efforts have been conducted to address the skyline query problem in various distributed scenarios, we still lack algorithms to address the queries over interval data, which is a special kind of attribute‐level uncertain data that widely exists in many applications. In this paper, we extensively study the skyline query over distributed interval data. We model the skyline query problem and define the distributed skyline query over interval data. Particularly, 2 efficient algorithms are proposed to retrieve the skylines progressively from distributed local sites with a highly optimized feedback framework. Moreover, we exploit 2 strategies for further improving the queries. Extensive experiments on synthetic and real datasets with real deployment are conducted to validate the effectiveness and efficiency of our proposals.
Access control in publish/subscribe systems

Two convincing paradigms have emerged for achieving scalability in widely distributed systems: publish/subscribe communication and role-based, policy-driven control of access to the system by applications. A strength of publish/subscribe is its many-to-many communication paradigm and loose coupling of components, so that publishers need not know the recipients of their data and subscribers need not know the number and location of publishers. But some data is sensitive, and its visibility must be controlled carefully for personal and legal reasons. We describe the requirements of several application domains where the event-based paradigm is appropriate yet where security is an issue. Typical are the large-scale systems required by government and public bodies for domains such as healthcare, police, transport and environmental monitoring. We discuss how a publish/subscribe service can be secured; firstly by specifying and enforcing access control policy at the service API, and secondly by enforcing the security and privacy aspects of these policies within the service network itself. Finally, we describe an alternative to whole-message encryption, appropriate for highly sensitive and long-lived data destined for specific domains with varied requirements. We outline our investigations and findings from several research projects in these areas.
Environmental Taxes in an Economy with Distorting Taxes and a Heterogeneous Population

During the last couple of decades, there has been a large literature discussing how the properties of emission taxes are affected by the existence of distortionary taxes. Most of this literature ignores distributional aspects of environmental taxes and other types of environmental policy instruments. The present paper considers a very simple model with heterogeneous households, differing in income earning ability. The tax system i s not necessarily fully optimal. Instead, a tax function is assumed the be exogenously given, but the parameters of this tax function are opmtimally chosen. The rule for the second-best opmtimal environmental tax is derived and compared with the Pigovian rule. The results derived in the present paper are related to the results from the literature on public goods provision under distortionary taxes.
Constructing historical long-term primary production in the Chesapeake Bay for use in ecosystem-based fisheries management models

Introduction Need for historical reconstruction of primary production A 2006 report by the National Research Council states that in order to deal with rapid changes in marine ecosystems brought about by human impacts, progress toward ecosystem-based management (or ecosystem approaches to management) is necessary (NRC 2006). Ecosystem-based management for fisheries requires a long-term historical perspective to enable policymakers to account for shifting baselines (sensu Pauly 1995). Such long-term perspective also fosters a better understanding of large-scale, long-term ecosystem mechanisms and, therefore, supports a broader understanding of what to account for in the future. Consequently, extensive data are needed to model fisheries ecosystems especially for periods of many decades. Historical fish population data can be obtained from fish surveys, existing models, and catch records. Unfortunately, historical data on primary producers and lower trophic levels are often less available, collected discontinuously, or measured in ways not readily transferable to the context of a fisheries-based modeling perspective. We are thus often compelled to use historical models and reconstructions of primary producers and lower trophic levels. Coupled physical-biological models such as Nutrients-Plankton-Zooplankton-Detritus models (e.g., Aksnes and Lie 1990, Xu and Hood 2006) can be used to estimate primary production; however, they simulate processes on fine spatial and temporal scales and cover relatively short time periods. This scale is not well suited for dynamic-modeling-based historical reconstruction of ecosystems, because computation time requirements to span a model for several decades would create prohibitively long simulation runs. In a more generalized fishery-ecosystem model, multiple simulation runs can be subjected to sensitivity analysis and thorough exploratory analyses. Such broader-scope approaches are recommended to account for wider ranges of ecosystem services and potential consequences as a result of fishing (NRC 2006). In this paper, we describe the development of a simple hydrodynamic model with a monthly time step to create a long-term forcing function for a fisheries ecosystem model of the Chesapeake Bay. Harding (1994) and Harding and Perry (1997) provided an analysis of historical and recent data on chlorophyll-a for the Chesapeake Bay. Such indices could be used as a forcing function for the fisheries model but the coverage for chlorophyll-a observations was sparse in the 1950s (though improved in the 1960s and 1970s). Good coverage started after 1984 when a systematic monitoring program began. Using a dynamic model, instead of static indices, allows us to explore the potential impact of historical changes in factors such as nutrient …
Discriminative Layered Nonnegative Matrix Factorization for Speech Separation

This paper proposes a discriminative layered nonnegative matrix factorization (DL-NMF) for monaural speech separation. The standard NMF conducts the parts-based representation using a single-layer of bases which was recently upgraded to the layered NMF (L-NMF) where a tree of bases was estimated for multi-level or multi-aspect decomposition of a complex mixed signal. In this study, we develop the DL-NMF by extending the generative bases in L-NMF to the discriminative bases which are estimated according to a discriminative criterion. The discriminative criterion is conducted by optimizing the recovery of the mixed spectra from the separated spectra and minimizing the reconstruction errors between separated spectra and original source spectra. The experiments on single-channel speech separation show the superiority of DL-NMF to NMF and L-NMF in terms of the SDR, SIR and SAR measures.
Functional Analysis of the Degradation of Cellulosic Substrates by a Chaetomium globosum Endophytic Isolate

ABSTRACT Most photosynthetically fixed carbon is contained in cell wall polymers present in plant biomasses, the largest organic carbon source in the biosphere. The degradation of these polymers for biotechnological purposes requires the combined action of several enzymes. To identify new activities, we examined which enzymes are activated by an endophytic strain of Chaetomium globosum to degrade cellulose-containing substrates. After biochemical analyses of the secretome of the fungus grown on cellulose or woody substrates, we took advantage of the available genomic data to identify potentially involved genes. After in silico identification of putative genes encoding either proteins able to bind to cellulose or glycohydrolases (GHs) of family 7, we investigated their transcript levels by reverse transcription-quantitative PCR (RT-qPCR). Our data suggest that eight genes compose the core of the cellulose-degrading system of C. globosum. Notably, the related enzymes belong structurally to the well-described GH families 5, 6, 7, 16, and 45, which are known to be the core of the cellulose degradation systems of several ascomycetes. The high expression levels of cellobiose dehydrogenase and two GH 61 enzymes suggest the involvement of this oxidoreductive synergic system in C. globosum. Transcript analysis along with relevant coding sequence (CDS) isolation and expression of recombinant proteins proved to be a key strategy for the determination of the features of two endoglucanases used by C. globosum for the first attack of crystalline cellulose. Finally, the possible involvement of transcriptional regulators described for other ascomycetes is discussed.
Solanesyl Diphosphate Synthase, an Enzyme of the Ubiquinone Synthetic Pathway, Is Required throughout the Life Cycle of Trypanosoma brucei

ABSTRACT Ubiquinone 9 (UQ9), the expected product of the long-chain solanesyl diphosphate synthase of Trypanosoma brucei (TbSPPS), has a central role in reoxidation of reducing equivalents in the mitochondrion of T. brucei. The ablation of TbSPPS gene expression by RNA interference increased the generation of reactive oxygen species and reduced cell growth and oxygen consumption. The addition of glycerol to the culture medium exacerbated the phenotype by blocking its endogenous generation and excretion. The participation of TbSPPS in UQ synthesis was further confirmed by growth rescue using UQ with 10 isoprenyl subunits (UQ10). Furthermore, the survival of infected mice was prolonged upon the downregulation of TbSPPS and/or the addition of glycerol to drinking water. TbSPPS is inhibited by 1-[(n-oct-1-ylamino)ethyl] 1,1-bisphosphonic acid, and treatment with this compound was lethal for the cells. The findings that both UQ9 and ATP pools were severely depleted by the drug and that exogenous UQ10 was able to fully rescue growth of the inhibited parasites strongly suggest that TbSPPS and UQ synthesis are the main targets of the drug. These two strategies highlight the importance of TbSPPS for T. brucei, justifying further efforts to validate it as a new drug target.
Isolating the Liquid Cloud Response to Recent Arctic Sea Ice Variability Using Spaceborne Lidar Observations

While the radiative influence of clouds on Arctic sea ice is known, the influence of sea ice cover on Arctic clouds is challenging to detect, separate from atmospheric circulation, and attribute to human activities. Providing observational constraints on the two‐way relationship between sea ice cover and Arctic clouds is important for predicting the rate of future sea ice loss. Here we use 8 years of CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations from 2008 to 2015 to analyze Arctic cloud profiles over sea ice and over open water. Using a novel surface mask to restrict our analysis to where sea ice concentration varies, we isolate the influence of sea ice cover on Arctic Ocean clouds. The study focuses on clouds containing liquid water because liquid‐containing clouds are the most important cloud type for radiative fluxes and therefore for sea ice melt and growth. Summer is the only season with no observed cloud response to sea ice cover variability: liquid cloud profiles are nearly identical over sea ice and over open water. These results suggest that shortwave summer cloud feedbacks do not slow long‐term summer sea ice loss. In contrast, more liquid clouds are observed over open water than over sea ice in the winter, spring, and fall in the 8 year mean and in each individual year. Observed fall sea ice loss cannot be explained by natural variability alone, which suggests that observed increases in fall Arctic cloud cover over newly open water are linked to human activities.