Miracle-dz/UniFAR-FTUs huggingface dataset:
Water Supply-Water Environmental Capacity Nexus in a Saltwater Intrusion Area under Nonstationary Conditions

Due to water supply increase and water quality deterioration, water resources are a critical problem in saltwater intrusion areas. In order to balance the relationship between water supply and water environment requirements, the nexus of water supply-water environment capacity should be well understood. Based on the Saint–Venant system of equations and the convection diffusion equation, the water supply-water environment capacity nexus physical equation is determined. Equivalent reliability is employed to estimate the boundary design water flow, which will then lead to a dynamic nexus. The framework for determining the nexus was then applied to a case study for the Pearl River Delta in China. The results indicate that the water supply-water environment capacity nexus is a declining linear relationship, which is different from the non-salt intrusion and tide-impacted areas. Water supply mainly relies on freshwater flow from upstream, while water environmental capacity is affected by both the design freshwater flow and the water levels at the downstream boundary. Our methods provide a useful framework for the quantification of the physical nexus according to the water quantity and water quality mechanisms, which are useful for freshwater allocation and management in a saltwater intrusion area or the tail area of cascade reservoirs.
BMC Systems Biology

Optimization aims to make a system or design as effective or functional as possible. Mathematical optimization methods are widely used in engineering, economics and science. This commentary is focused on applications of mathematical optimization in computational systems biology. Examples are given where optimization methods are used for topics ranging from model building and optimal experimental design to metabolic engineering and synthetic biology. Finally, several perspectives for future research are outlined
Xin Wu Big Switch Networks

Software Defined Networking (SDN) uses a logically centralized controller to replace the distributed control plane in a traditional network. One of the central challenges faced by the SDN paradigm is the scalability of the logical controller. As a network grows in size, the computational and communication demand faced by a controller may soon exceed the capabilities of a commodity server. In this work, we revisit the task division of labour between the controller and switches, and propose FOCUS, an architecture that offloads a specific subset of control functions, i.e., stable local functions, to the switches’ software stack. We implemented a prototype of FOCUS and analyzed the benefits of converting several SDN applications. Due to space restrictions, we only present results for ARP, LLDP and elephant flow detection. Our initial results are promising and they show that FOCUS can reduce a controller’s communication overhead by 50% to nearly 100%, and the computational overhead from 80% to 98%. Furthermore, we observe that FOCUS offloading to the switches saves switch CPU because FOCUS reduces the overheads for communication with the controller.
ProMal: Precise Window Transition Graphs for Android via Synergy of Program Analysis and Machine Learning

Mobile apps have been an integral part in our daily life. As these apps become more complex, it is critical to provide automated analysis techniques to ensure the correctness, security, and performance of these apps. A key component for these automated analysis techniques is to create a graphical user interface (GUI) model of an app, i.e., a window transition graph (WTG), that models windows and transitions among the windows. While existing work has provided both static and dynamic analysis to build the WTG for an app, the constructed WTG misses many transitions or contains many infeasible transitions due to the coverage issues of dynamic analysis and over-approximation of the static analysis. We propose ProMal, a "tribrid" analysis that synergistically combines static analysis, dynamic analysis, and machine learning to construct a precise WTG. Specifically, ProMal first applies static analysis to build a static WTG, and then applies dynamic analysis to verify the transitions in the static WTG. For the unverified transitions, ProMal further provides machine learning techniques that leverage runtime information (i.e., screenshots, UI layouts, and text information) to predict whether they are feasible transitions. Our evaluations on 40 real-world apps demonstrate the superiority of ProMal in building WTGs over static analysis, dynamic analysis, and machine learning techniques when they are applied separately.
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine Knowledge of Glasgow Coma Scale by Air-rescue Physicians

Objective: To assess the theoretical and practical knowledge of the Glasgow Coma Scale (GCS) by trained Air-rescue physicians in Switzerland. Methods: Prospective anonymous observational study with a specially designed questionnaire. General knowledge of the GCS and its use in a clinical case were assessed. Results: From 130 questionnaires send out, 103 were returned (response rate of 79.2%) and analyzed. Theoretical knowledge of the GCS was consistent for registrars, fellows, consultants and private practitioners active in physician-staffed helicopters. The clinical case was wrongly scored by 38 participants (36.9%). Wrong evaluation of the motor component occurred in 28 questionnaires (27.2%), and 19 errors were made for the verbal score (18.5%). Errors were made most frequently by registrars (47.5%, p = 0.09), followed by fellows (31.6%, p = 0.67) and private practitioners (18.4%, p = 1.00). Consultants made significantly less errors than the rest of the participating physicians (0%, p < 0.05). No statistically significant differences were shown between anesthetists, general practitioners, internal medicine trainees or others. Conclusion: Although the theoretical knowledge of the GCS by out-of-hospital physicians is correct, significant errors were made in scoring a clinical case. Less experienced physicians had a higher rate of errors. Further emphasis on teaching the GCS is mandatory.
Does Soil Moisture Affect Warm Season Precipitation Over the Southern Great Plains?

Numerous observational and modeling studies have addressed the impact of soil moisture on subsequent precipitation (primarily its initiation), yet consensus remains elusive. Here we quantify the relationship between soil moisture and precipitation amplification over the U.S. Southern Great Plains. Warm season (June–September) days for the 2002–2011 period (with ~1220 total days) are partitioned into three dynamic regimes based on daily water vapor convergence, among which afternoon precipitation event days are identified based on simple criteria. We find that antecedent soil moisture conditions are negatively correlated with subsequent afternoon precipitation magnitude for low dynamic regimes, but this correlation becomes positive for high dynamic regimes. In contrast, this correlation is markedly reduced in magnitude and becomes insignificant when all regime days are considered. These results are also confirmed by analyzing the precipitation histogram and diurnal cycle. Furthermore, different pathways are provided for precipitation amplification for low and high dynamic regimes.
A self-tuning, self-protecting, self-healing session state management layer

Management of semi-persistent state, such as user-session state, is one factor that complicates failure management in clustered three-tier Internet applications [5]. We observe that the specific properties of user-session state can be exploited to design a lightweight state storage layer that offers many of the same ease-of-management and ease-of-recovery properties as stateless components such as Web servers. We describe SSM, a self-tuning, self-protecting, and self-healing session state management layer that provides a storage and retrieval mechanism for semi-persistent, serial-access user session state. SSM is fast, scalable, fault-tolerant, and recovers instantly from individual node failures. Any SSM node may be rebooted at any time and there is no special recovery code, so the performance cost of “eager” recovery is near zero, simplifying recovery policy management when SSM is integrated into a larger system.
Blurry Image Deblurred Image Compute Camera Motion Drift Correction Sensor Data Blur Scale Estimation Deblur Image Blurry Image Compute Camera Motion Drift Correction Deblur Image Deblurred Image Sensor Data 2

We present a deblurring algorithm that uses a hardware attachment coupled with a natural image prior to deblur images from consumer cameras. Our approach uses a combination of inexpensive gyroscopes and accelerometers in an energy optimization framework to estimate a blur function from the camera’s acceleration and angular velocity during an exposure. We solve for the camera motion at a high sampling rate during an exposure and infer the latent image using a joint optimization. Our method is completely automatic, handles per-pixel, spatially-varying blur, and out-performs the current leading image-based methods. Our experiments show that it handles large kernels – up to at least 100 pixels, with a typical size of 30 pixels. We also present a method to perform “ground-truth” measurements of camera motion blur. We use this method to validate our hardware and deconvolution approach. To the best of our knowledge, this is the first work that uses 6 DOF inertial sensors for dense, per-pixel spatially-varying image deblurring and the first work to gather dense ground-truth measurements for camera-shake blur.
Dynamic Channel Bonding in Spatially Distributed High-Density WLANs

In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense range of each other. Then, we assess the performance of DCB in high-density IEEE 802.11ac/ax WLANs by means of simulations. We show that there may be critical interrelations among nodes in the spatial domain–even if they are located outside the carrier sense range of each other–in a chain reaction manner. Results also reveal that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair situations where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique optimal DCB policy for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.
Plant-pollinator Interactions in a Changing Climate

Climate change is shifting the seasonal timing of many biological events, and the possibility of non-parallel shifts in different taxa has raised concerns about phenological decoupling of interacting species. My thesis investigates interactions between climate, phenology, and pollination, using the plants and pollinators of Rocky Mountain meadows as a study system. Interannual variation in timing of snowmelt since the 1970s has been associated with changes in the assemblages of concurrently flowering species in these meadows, suggesting that plant species differ in their phenological responses to climate. Differences between plants and pollinators in responsiveness to changing climate could, in principle, cause early-flowering plants to flower too early in warm years, before pollinators are active. In fact, I found only transient evidence for pollinator deficits in one early-flowering species (Mertensia fusiformis), even in an early-snowmelt year. However, the assemblage of pollinators visiting M. fusiformis does change predictably over the season, with likely consequences for selection on floral morphology in years when pollen is limiting. Hence, earlyand late-flowering populations may evolve in response to phenology of the pollinator community. Differences between plant and
Stratified Point Sampling of 3D Models

Point sampling is an important intermediate step for a variety of computer graphics applications, and specialized sampling strategies have been developed to satisfy the requirements of each problem. In this article, we present a technique to generate a stratified sampling of 3D models that is applicable across many domains. The algorithm voxelizes the model and selects one sample per voxel, restricted to the original model's surface. Parameters allow control of the uniformity of the sample placement and the minimum distance between samples. We demonstrate the effectiveness of this technique in selecting stroke locations for painterly rendering models and for producing sampled geometry used as input to shape descriptors.
Keywords: Reinforcement Learning, Neural Networks, Adaptive Multi-agent Systems, Agent Economies Pricing in Agent Economies Using Neural Networks and Multi-agent Q-learning

This paper investigates how adaptive software agents may utilize reinforcement learning algorithms such as Q-learning to make economic decisions such as setting prices in a competitive marketplace. For a single adaptive agent facing xed-strategy opponents, ordinary Q-learning is guaranteed to nd the optimal policy. However , for a population of agents each trying to adapt in the presence of other adaptive agents, the problem becomes non-stationary and history dependent, and it is not known whether any global convergence will be obtained, and if so, whether such solutions will be optimal. This paper studies simultaneous Q-learning by two competing seller agents in three moderately realistic economic models. This is the simplest case in which interesting multi-agent phenomena can occur, and the state space is small enough so that lookup tables can be used to represent the Q-functions. Despite the lack of theoretical guarantees, simultaneous convergence to self-consistent optimal solutions is obtained in each model, at least for small values of the discount parameter. In some cases, such convergence is also found even at large discount parameters. Furthermore, the Q-derived policies increase prootability and damp out or eliminate cyclic price \wars" compared to simpler policies based on zero lookahed or short-term lookahead. The use of function approximators (neural nets) instead of lookup tables is also investigated; preliminary ndings indicate that reasonably good policies can be obtained even though the absolute accuracy of the function approximation may be poor.
The impact of smartphone applications on bowel preparation, compliance with appointments, cost-effectiveness, and patients’ quality of life for the colonoscopy process: A scoping review

The aim of this scoping review is to evaluate the impact of smartphone application (SPA) technology in patients undergoing elective colonoscopy to measure compliance with appointments, cost-effectiveness, bowel preparation, and quality of life. The scoping review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. Ovid Medline, Web of Science, Science Direct, Scopus, Cochrane Library, and PubMed were screened up to Oct 14, 2020, and bibliographies of the retrieved articles were included. Based on pre-specified inclusion and exclusion criteria, 8 primary studies were included in the final analysis from a total of 3,979 non-duplicate articles. Seven out of eight studies measured the bowel preparation quality. In six of these studies, patients in the smartphone group had a successful bowel preparation when compared with the control arm; on the other hand, one study did not find any differences between groups. Adherence to colonoscopy screening was assessed by one study. Patients in the digital intervention arm were significantly more likely to complete a screening test. Patient satisfaction during the periprocedural period of colonoscopy was assessed by five studies which reported significantly higher patient satisfaction in the intervention arm compared to the control arm. None of the studies measured cost-effectiveness. We came to the conclusion that a well-designed, user-friendly SPA can help and guide patients undergoing colonoscopy through the process of following up on their appointments, adhering to bowel preparation, and better understanding their disease condition. Future trials investigating SPAs should include cost-effectiveness and adherence to appointments as an endpoint.
EcoAndroid: An Android Studio Plugin for Developing Energy-Efﬁcient Java Mobile Applications (Extended Abstract) *

—Mobile devices have become indispensable in our daily life and reducing the energy consumed by them has become essential over recent years. For economical and environmental reasons, as well as enhancing the user experience, extending battery duration has become a non-functional requirement developers should be concern with. However, developing energy-efﬁcient mobile applications is not a trivial task. To address this problem, we present EcoAndroid, a publicly-available Android Studio plugin that automatically applies a set of energy patterns to Java source code. It currently supports ten different cases of energy-related refactorings, over ﬁve energy patterns taken from the literature. We used EcoAndroidto analyze 100 Java mobile applications from F-Droid and we found that 35 of the projects had a total of 95 energy code smells detected by the plugin. We used EcoAndroidto automatically refactor all the code smells identiﬁed. We submitted the 42 refactorings that introduced code ﬁxes (and not just informational warnings) as pull requests to the maintainers of the respective projects. Of a total of 42 pull requests, we received replies to 25 of them (59.5%); of those, 20 (80%) were accepted and merged into the original projects. In total, we contributed to improve the energy efﬁciency of 12 different Android mobile applications. These results, together with the results obtained in a user study with 12 participants, show that EcoAndroid is useful, usable, and the alterations proposed by the tool are easily accepted by developers.
General Convergent Expectation Maximization (EM)-Type Algorithms for Image Reconstruction with Background Emission and Poisson Noise

Obtaining high quality images is very important in many areas of applied sciences. In this paper, we proposed general convergent and robust expectation maximization (EM)-Type algorithms for image reconstruction with background emission when the measured data is corrupted by Poisson noise. These methods are separated into two steps: EM step and regularization step, and these algorithms are shown to be equivalent to EM algorithms with a priori information and alternating minimization methods. The convergence of the algorithms is shown in several diﬀerent ways. To overcome contrast reduction introduced by regularizations, EM-Type algorithms with Bregman iterations are introduced. The numerical experiments using diﬀerent regularizations show the performance of these methods.
Multiple sequence alignment with user-defined constraints at GOBICS

Most multi-alignment methods are fully automated, i.e. they are based on a fixed set of mathematical rules. For various reasons, such methods may fail to produce biologically meaningful alignments. Herein, we describe a semi-automatic approach to multiple sequence alignment where biological expert knowledge can be used to influence the alignment procedure. The user can specify parts of the sequences that are biologically related to each other; our software program uses these sites as anchor points and creates a multiple alignment respecting these user-defined constraints. By using known functionally, structurally or evolutionarily related positions of the input sequences as anchor points, our method can produce alignments that reflect the true biological relationships among the input sequences more accurately than fully automated procedures can do.
3 Automatic Recognition of VNICs

We investigate the lexical and syntactic flexibility of a class of idiomatic expressions. We develop measures that draw on such linguistic properties, and demonstrate that these statistical, corpus-based measures can be successfully used for distinguishing idiomatic combinations from non-idiomatic ones. We also propose a means for automatically determining which syntactic forms a particular idiom can appear in, and hence should be included in its lexical representation.
STUDENT EVALUATION IN HIGHER EDUCATION : A COMPARISON BETWEEN COMPUTER ASSISTED ASSESSMENT AND TRADITIONAL EVALUATION

The Department of Management at the Neri Bloomfield School of Design and Education, prepares students to teach management and accounting at high schools. The department's pedagogical aims are to provide students relevant tools, so they would be able to deal effectively with needs existing at high schools. The department deals with different levels, including theoretical and technological knowledge.
Subseismic-scale reservoir deformation: introduction

Abstract This volume examines the current best practice and new challenges in reservoir characterization and modelling of small- to subseismic-scale deformation features through case studies, experimental results and modelling. The papers in this volume include contributions on four themes related to the small-scale deformation of hydrocarbon reservoirs: the characterization of deformation in porous sandstones; novel characterization techniques; quantifying and characterizing deformation in carbonates; and modelling small-scale features. It includes eight papers from the conference Small to Subseismic-Scale Reservoir Deformation, organized by the Petroleum Group of the Geological Society and held in London from 29 to 30 October 2014, plus two additional papers. The observations in this introduction reflect the authors’ experiences and opinions, presentations at the conference and the papers within this volume.
A SURVEY OF STUDIES ON THE PERFECT AND PLUPERFECT TENSES IN NORTH SAMOYEDIC LANGUAGES

Ago Künnap  Abstract: There are too few devices in Samoyedic languages to express a completed/ accomplished action, so one of the ways to do it is just the use of perfect and pluperfect. Samoyedic languages have no common markers for moods and tenses, only a few of them occur in most of the languages mentioned. The Samoyedic system of conjugation is mainly based on verbal nouns, its mood and temporal markers mostly coincide with participle and gerund markers. The Tundra Nenets perfect is formed by means of the participle markers -{ + (- m +), the pluperfect – by means of the compound marker - β + (- m +) . -\. In Enets the marker - bi as indicates an earlier meaning of the perfective participle that has disappeared by now, the pluperfect is formed by means of the compound suffixes -b i (- … i ) . -\ (-\ i ). In Nganasan the marker -‟V- expresses the past, more exactly the perfective preterit. The perfect has the compound marker - b V (- h V) + - t V (-§V). Both perfect and pluperfect are used widely in the languages under observation, particularly in folkloristic texts. The formation and the use of perfect and pluperfect are mostly similar. As far as the Samoyedic participle marker - b V is concernd, then G. J. Ramstedt (1952) refers to the Turkic perfect-gerund marker - p (- yp , - up ) and to the Mongol preterit perfect marker - bai , - bei , - ba ,