Miracle-dz/UniFAR-FTUs huggingface dataset:
Interannual Variability of the Kuroshio Extension System and Its Impact on the Wintertime SST Field

Altimetry data from the ﬁrst 7-yr TOPEX/Poseidon (T/P) mission (October 1992–September 1999) are analyzed to investigate the interannual variability in regions of the Kuroshio Extension and its southern recirculation gyre. Large-scale, interannual changes of the Kuroshio Extension system are characterized by the oscillation between an elongated state and a contracted state. In the elongated state, the Kuroshio Extension has a larger eastward surface transport, a greater zonal penetration, and a more northerly zonal-mean path. All these characteristics are closely connected to the presence of an intense, zonally elongated southern recirculation gyre. In its contracted state, the Kuroshio Extension has a smaller eastward surface transport, a more southerly mean path, and is accompanied by a weaker southern recirculation gyre. During the T/P period, the Kuroshio Extension changed from the elongated state in 1992–93 to the contracted state in 1996–97, and back to the elongated state since late 1997. In addition to these large-scale changes, the mesoscale eddy ﬁeld also exhibited prominent interannual changes in the Kuroshio Extension region. In the upstream region between the Izu Ridge and the Shatsky Rise, the eddy kinetic energy level was generally low while the Kuroshio Extension was in its elongated state, and high while in the contracted state. Downstream of the Shatsky Rise, on the other hand, the EKE level was high (low) when the Kuroshio Extension was in the elongated (contracted) state. The large-scale, interannual changes in the Kuroshio Extension system have a signiﬁcant impact on the regional wintertime SST anomaly ﬁeld: the warm (cold) wintertime SST anomalies tend to persist in years when the Kuroshio Extension is in its elongated (contracted) state. A diagnostic analysis of the surface ocean heat balance indicates that the nonseasonal geostrophic advection by the ocean circulation works to reduce (increase) the wintertime SST anomalies when the Kuroshio Extension changes from an elongated (contracted) state to a contracted (elongated) state. The SST anomalies associated with the large-scale changes of the Kuroshio Extension have an area-averaged, peak-to- peak amplitude of (cid:46) 1 (cid:56) C and appear independent of the interannual SST changes in the tropical Paciﬁc Ocean.
Effects of Growing-Season Drought on Phenology and Productivity in the West Region of Central Hardwood Forests, USA

Studying the effects of drought on forest ecosystems is important in developing a better understanding of forest phenology and productivity. Many previous studies were based on single drought events, whereas effects of recurrent droughts have not been yet fully investigated. This study jointly analyzed the spatial–temporal change of drought patterns with forest phenology and productivity between 2000–2015 in the western Central Hardwood Forests at Missouri, Arkansas Illinois, Oklahoma, and Kansas of the US. Characteristics of forest phenology and productivity were captured by utilizing the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing 16-day MOD13Q1 data and Savitsky–Golay (S-G) filtering method. Spatial-temporal drought patterns were assessed by empirical orthogonal function (EOF) on self-calibrating Palmer Drought Severity Index (scPDSI) time series. Our results revealed four drought zones: sporadic severe drought zone, cyclic light drought zone, minor drought zone, and moderate drought zone. The results showed that at the regional scale, drought effects on forest phenology and productivity depended on forest type and drought intensity. The cyclic light drought did not result in a notable decline of growing season length and productivity, while both minor drought and severe drought were followed by a significant decrease of forest growing season length and productivity. This research presents an alternative method to analyze the impacts of drought on regional forest dynamics.
Randomized resonators as uniquely identifiable anti-counterfeiting tags

We discuss how LC circuits with randomized properties can be used as anti-counterfeiting tags. Work in progress is presented. Test circuits made using thin film technology easily achieve 20 to 3 bits of identification capacity. We describe our experimental setup, the radiofrequent response curves, and the stable features that can be extracted from them.
Languages with More Second Language Learners Tend to Lose Nominal Case

Inthispaper,weprovidequantitativeevidenceshowingthatlanguagesspokenbymanysecond languagespeakerstendtohaverelativelysmallnominalcasesystemsornonominalcaseatall. In our sample, all languages with more than 50% second language speakers had no nominal case. The negative association between the number of second language speakers and nominal casecomplexitygeneralizestodifferentlanguageareasandfamilies.Astherearemanystudies attestingtothedifficultyofacquiringmorphologicalcaseinsecondlanguageacquisition,this result supports the idea that languages adapt to the cognitive constraints of their speakers, as wellastothesociolinguisticnichesoftheirspeakingcommunities.Wediscussourresultswith respecttosociolinguistictypologyandtheLinguisticNicheHypothesis,aswellaswithrespect toqualitativedatafromhistoricallinguistics.Allinall,multiplelinesofevidenceconvergeon the idea that morphosyntactic complexity is reduced by a high degree of language contact involving adult learners.
Molecular testing of observer identification of carnivore feces in the field

Abstract Collection of carnivore feces is common in wildlife ecology studies, but misidentification of scats can compromise data quality. We tested the ability of observers to identify coyote (Canis latrans) feces in the Alaska Range from 2000–2002. We extracted DNA from 834 fecal samples and used an unambiguous mtDNA analysis to differentiate coyote scats from those of sympatric carnivores. We successfully amplified DNA from 78% of the extracts, and 92% of these samples were from coyotes. We rated our certainty level when collecting scats in the field, and the proportion correctly identified matched well with expected proportions. For example, 100% of scats that we rated “100% certain” were from coyotes (n=129), 96% of scats rated “95% certain” were from coyotes (n=174), and 88% of scats rated “90% certain” were from coyotes (n=62). Thus, we demonstrate that trained observers can identify coyote scats in the field with accuracy that should be sufficient for diet studies, even in the presence of other similar-sized carnivores. Rating observer certainty is useful for later analyses because researchers can decide what level of uncertainty is acceptable for their purposes and exclude samples accordingly.
Increasing Magnitude of Hurricane Rapid Intensification in the Central and Eastern Tropical Atlantic

Rapid intensification (RI) of hurricanes is notoriously difficult to predict and can contribute to severe destruction and loss of life. While past studies examined the frequency of RI occurrence, changes in RI magnitude were not considered. Here we explore changes in RI magnitude over the 30‐year satellite period of 1986–2015. In the central and eastern tropical Atlantic, which includes much of the main development region, the 95th percentile of 24‐hr intensity changes increased at 3.8 knots per decade. In the western tropical Atlantic, encompassing the Caribbean Sea and the Gulf of Mexico, trends are insignificant. Our analysis reveals that warming of the upper ocean coinciding with the positive phase of Atlantic Multidecadal Oscillation, and associated changes in the large‐scale environment, has predominantly favored RI magnitude increases in the central and eastern tropical Atlantic. These results have substantial implications for the eastern Caribbean Islands, some of which were devastated during the 2017 hurricane season.
Psychometric properties and factor structure of the Satisfaction with Life Scale in an elderly Portuguese retirees students sample

Título: Propiedades psicométricas y estructura de los factores de la escala de Satisfacción con la Vida en una muestra de estudiantes mayores portugueses jubilados. Resumen: El objetivo principal de este estudio ha sido analizar las propiedades psicométricas de la escala de Satisfacción con la Vida (SWLS) en una muestra de 363 estudiantes jubilados pertenecientes a varias universidades portuguesas. El 70% de los participantes eran mujeres frente a un 30% de hombres, con una media de edad de 67 años (SD = 7.59) y un rango de edad comprendido entre 48 y 90 años. Se realizó un Análisis Factorial Exploratorio con R Commander y un Análisis Factorial Confirmatorio con Amos 18.0. El modelo que obtuvo un mejor ajuste estaba compuesto por un único factor. El índice de consistencia interna de la escala en su conjunto fue de . 777. En cuanto a la validez concurrente, los análisis correlacionales mostraron una correlación negativa y significativa con la escala de soledad de UCLA y con la de depresión (GDS-15). El SWLS es una escala aplicable en futuras investigaciones sobre población mayor para medir su satisfacción con la vida. Algunas limitaciones y resultados de sus aplicaciones en otras muestras son discutidos. Palabras clave: Satisfacción con la vida; soledad; depresión; validez y fiabilidad. Abstract: The main purpose of this study is to analyse the psychometric properties of the Satisfaction with Life Scale (SWLS) in a 363 retirees students sample from several Portuguese universities. The 70% were female (253) and 30% were male (110) with an average age of 67 years (SD = 7.59) and a range from 48 to 90 years. R Commander was used for Exploratory Factor Analysis (EFA) and Amos 18.0 module for Confirmatory Factor Analysis (CFA). One factor solution was the best-fitting model. The internal consistency of the SWLS was . 777. Correlational analysis showed negative relationships with loneliness (UCLA Scale) and symptoms of depression (GDS-15), supporting concurrent validity. The SWLS can be used with confidence in future research among elderly students to measure their life satisfaction. Some limitations of the results and its applications in other samples are discussed.
A Fairness-aware Hybrid Recommender System

Recommender systems are used in variety of domains affecting people's lives. This has raised concerns about possible biases and discrimination that such systems might exacerbate. There are two primary kinds of biases inherent in recommender systems: observation bias and bias stemming from imbalanced data. Observation bias exists due to a feedback loop which causes the model to learn to only predict recommendations similar to previous ones. Imbalance in data occurs when systematic societal, historical, or other ambient bias is present in the data. In this paper, we address both biases by proposing a hybrid fairness-aware recommender system. Our model provides efficient and accurate recommendations by incorporating multiple user-user and item-item similarity measures, content, and demographic information, while addressing recommendation biases. We implement our model using a powerful and expressive probabilistic programming language called probabilistic soft logic. We experimentally evaluate our approach on a popular movie recommendation dataset, showing that our proposed model can provide more accurate and fairer recommendations, compared to a state-of-the art fair recommender system.
Remote sensing of vegetation 3-D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions

[1] Biodiversity and habitat face increasing pressures due to human and natural influences that alter vegetation structure. Because of the inherent difficulty of measuring forested vegetation three-dimensional (3-D) structure on the ground, this important component of biodiversity and habitat has been, until recently, largely restricted to local measurements, or at larger scales to generalizations. New lidar and radar remote sensing instruments such as those proposed for spaceborne missions will provide the capability to fill this gap. This paper reviews the state of the art for incorporatinginformation on vegetation 3-D structure into biodiversity and habitat science and management approaches, with emphasis on use of lidar and radar data. First we review relationships between vegetation 3-D structure, biodiversity and habitat, and metrics commonly used to describe those relationships. Next, we review the technical capabilities of new lidar and radar sensors and their application to biodiversity and habitat studies to date. We then define variables that have been identified as both useful and feasible to retrieve from spaceborne lidar and radar observations and provide their accuracy and precision requirements. We conclude with a brief discussion of implications for spaceborne missions and research programs. The possibility to derive vegetation 3-D measurements from spaceborne active sensors and to integrate them into science and management comes at a critical juncture for global biodiversity conservation and opens new possibilities for advanced scientific analysis of habitat and biodiversity.
3 D Micro-CT Analysis of Void and Gap Formation in Curved Root Canals

Objective: This study used microcomputed tomography (micro-CT) to compare the volumes of voids and gaps in curved root canals instrumented and filled using various techniques. Methods: Twenty extracted mandibular first molars with two curved mesial root canals were used. Root canals were instrumented using a self-adjusting file (SAF) or Revo-S file system. For standardization, mesiobuccal canals were instrumented with SAF and mesiolingual canals were instrumented with Revo-S in each root. The canals were divided into four experimental groups (n=10 in each). The canals were then filled via cold lateral compaction (CLC) or a thermoplasticized injectable technique (TT) using gutta-percha and AH Plus root canal sealer. The roots were scanned with a micro-CT, and the volumes of the voids and gaps were calculated using three-dimensional (3D) micro-CT images. Data were analyzed using unpaired tand Kruskal-Wallis tests. A value of P < 0.05 was considered significant. Results: None of the tested techniques provided voidor gap-free fillings. Nevertheless, the SAF showed more gap formation than the Revo-S, and TT showed higher gap formation in all experimental groups. These differences, however, were not statistically significant (p>0.05). Conclusion: The SAF and Revo-S rotary file systems yielded comparable results. No statistically significant difference was found between the results of the various instrumentation and filling techniques.
Flow: Deep Reinforcement Learning for Control in SUMO

We detail the motivation and design decisions underpinning Flow, a computational framework integrating SUMO with the deep reinforcement learning libraries rllab and RL-lib, allowing researchers to apply deep reinforcement learning (RL) methods to traﬃc scenarios, permitting vehicle and infrastructure control in highly varied traﬃc environments. Users of Flow can rapidly design a wide variety of traﬃc scenarios in SUMO, enabling the development of controllers for autonomous vehicles and intelligent infrastructure across a broad range of settings. Flow facilitates the use of policy optimization algorithms to train controllers that can optimize for highly customizable traﬃc metrics, such as traﬃc ﬂow or system-wide average velocity. Training reinforcement learning agents using such methods requires a massive amount of data, thus simulator reliability and scalability were major challenges in the development of Flow. A contribution of this work is a variety of practical techniques for overcoming such challenges with SUMO, including parallelizing policy rollouts, smart exception and collision handling, and leveraging subscriptions to reduce computational overhead. Todemonstrate the resulting performance and reliability of Flow, we introduce the canonical single-lane ring road benchmark and brieﬂy discuss prior work regarding that task. We then pose a more complex and challenging multi-lane setting and present a trained controller for a single vehicle that stabilizes the system. Flow is an open-source tool and available online at https://github.com/cathywu/flow .
Error-Oblivious Sample Preparation With Digital Microfluidic Lab-on-Chip

Microfluidic chips are now being increasingly used for fast and cost-effective implementation of biochemical protocols. Sample preparation involves dilution and mixing of fluids in certain ratios, which are needed for most of the protocols. On a digital microfluidic biochip (DMFB), these tasks are usually automated as a sequence of droplet mix-split steps. In the most widely used (1:1) mix-split operation for DMFBs, two equal-volume droplets are mixed followed by a split operation, which, ideally, should produce two daughter-droplets of equal volume (balanced splitting). However, because of uncertain variabilities in fluidic operations, the outcome of droplet-split operations often becomes erroneous, i.e., they may cause unbalanced splitting. As a result, the concentration factor (CF) of each constituent fluid in the mixture may become erroneous during sample preparation. All traditional approaches aimed to recover from such errors deploy on-chip sensors to detect possible volumetric imbalance, and adopt either checkpointing-based rollback or roll-forward techniques. Most of them suffer from significant overhead in terms of assay-completion time, reactant-cost, and uncertainties in termination due to randomly occurring split-errors. In this paper, we propose a new approach to accurate dilution preparation on a DMFB that is oblivious to volumetric split-errors. It does not need any sensor and can handle multiple split-errors, deterministically. The proposed method is customized for each target-CF based on the criticality of split-errors in each mix-split step. Simulation experiments on various test-cases demonstrate the effectiveness of the proposed method.
Transport variability of the Brazil Current from observations and a data assimilation model

Abstract. The Brazil Current transports from observations and the Hybrid Coordinate Model (HYCOM) model are analyzed to improve our understanding of the current's structure and variability. A time series of the observed transport is derived from a three-dimensional field of the velocity in the South Atlantic covering the years 1993 to 2015 (hereinafter called Argo & SSH). The mean transports of the Brazil Current increases from 3.8 ± 2.2 Sv (1 Sv is 106 m3 s−1) at 25∘ S to 13.9 ± 2.6 Sv at 32∘ S, which corresponds to a mean slope of 1.4 ± 0.4 Sv per degree. Transport estimates derived from HYCOM fields are somewhat higher (5.2 ± 2.7 and 18.7 ± 7.1 Sv at 25 and 32∘ S, respectively) than those from Argo & SSH, but these differences are small when compared with the standard deviations. Overall, the observed latitude dependence of the transport of the Brazil Current is in agreement with the wind-driven circulation in the super gyre of the subtropical South Atlantic. A mean annual cycle with highest (lowest) transports in austral summer (winter) is found to exist at selected latitudes (24, 35, and 38∘ S). The significance of this signal shrinks with increasing latitude (both in Argo & SSH and HYCOM), mainly due to mesoscale and interannual variability. Both Argo & SSH, as well as HYCOM, reveal interannual variability at 24 and 35∘ S that results in relatively large power at periods of 2 years or more in wavelet spectra. It is found that the interannual variability at 24∘ S is correlated with the South Atlantic Subtropical Dipole Mode (SASD), the Southern Annular Mode (SAM), and the Niño 3.4 index. Similarly, correlations between SAM and the Brazil Current transport are also found at 35∘ S. Further investigation of the variability reveals that the first and second mode of a coupled empirical orthogonal function of the meridional transport and the sea level pressure explain 36 and 15 % of the covariance, respectively. Overall, the results indicate that SAM, SASD, and El Niño–Southern Oscillation have an influence on the transport of the Brazil Current.
Liquid‐top mixed‐phase cloud detection from shortwave‐infrared satellite radiometer observations: A physical basis

Meteorological clouds often exist in the liquid phase at temperatures below 0°C. Traditionally, satellite‐derived information on cloud phase comes from narrow bands in the shortwave and thermal infrared, with sensitivity biased strongly toward cloud top. In situ observations suggest an abundance of clouds having supercooled liquid water at their tops but a predominantly ice phase residing below. Satellites may report these clouds simply as supercooled liquid, with no further information regarding the presence of a subcloud top ice phase. Here we describe a physical basis for the detection of liquid‐top mixed‐phase clouds from passive satellite radiometer observations. The algorithm makes use of reflected sunlight in narrow bands at 1.6 and 2.25 µm to optically probe below liquid‐topped clouds and determine phase. Detection is predicated on differential absorption properties between liquid and ice particles, accounting for varying Sun/sensor geometry and cloud optical properties. When tested on numerical weather prediction model simulated cloud fields, the algorithm provided threat scores in the 0.6–0.8 range and false alarm rates in the 0.1–0.2 range. A case study based on surface and satellite observations of liquid‐top mixed‐phase clouds in northern Alaska was also examined. Preliminary results indicate promising potential for distinction between supercooled liquid‐top phase clouds with and without an underlying mixed‐phase component.
Towards automatic calibration of 2-D flood propagation models

Abstract. Hydraulic models for flood propagation description are an essential tool in many fields and are used, for example, for flood hazard and risk assessments, evaluation of flood control measures, etc. Nowadays there are many models of different complexity regarding the mathematical foundation and spatial dimensions available, and most of them are comparatively easy to operate due to sophisticated tools for model setup and control. However, the calibration of these models is still underdeveloped in contrast to other models like e.g. hydrological models or models used in ecosystem analysis. This has two primary reasons: first, lack of relevant data against which the models can be calibrated, because flood events are very rarely monitored due to the disturbances inflicted by them and the lack of appropriate measuring equipment in place. Second, 2-D models are computationally very demanding and therefore the use of available sophisticated automatic calibration procedures is restricted in many cases. This study takes a well documented flood event in August 2002 at the Mulde River in Germany as an example and investigates the most appropriate calibration strategy for a simplified 2-D hyperbolic finite element model. The model independent optimiser PEST, that enables automatic calibrations without changing model code, is used and the model is calibrated against over 380 surveyed maximum water levels. The application of the parallel version of the optimiser showed that (a) it is possible to use automatic calibration in combination of 2-D hydraulic model, and (b) equifinality of model parameterisation can also be caused by a too large number of degrees of freedom in the calibration data in contrast to a too simple model setup. In order to improve model calibration and reduce equifinality, a method was developed to identify calibration data, resp. model setup with likely errors that obstruct model calibration.