Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing CMIP6 Climate Model Simulations of Annual Global Mean Temperatures to a New Combined Data Product

A new statistical approach to validating climate models is introduced. First, five observational estimates of global mean surface temperature with estimated standard errors are combined into one data product, latent observed annual global temperature anomalies for the years 1880–2014, using a Bayesian hierarchical statistical approach. Summarizing these observed anomalies, estimates of smooth trend, levels of warming, and residual dependence as summarized by the spectral density function, are provided with simultaneous 95% credible bands. Then, corresponding estimates of smooth trend, levels of warming, and residual dependence are produced for sixth Climate Model Intercomparison Project (CMIP6) historical simulations analyzed at the annual global temperature anomaly scale, and compared to these bands. Among our results, we find that 93 out of the 318 CMIP6 historical model runs contain trends fitting inside the simultaneous bands for the smooth trend constructed from the data products, and for residual temporal dependence 69 out of 318 model runs contain spectral density functions that are within the corresponding data‐product‐based‐bands. We estimate the mean global temperature increase from 1995–2014 relative to 1880–1899, from the data product, to be 0.896°C with a 95% credible interval of between 0.877 and 0.915. We find that 14 CMIP6 model runs agree with this interval, 197 model runs lead to a smaller temperature increase globally, and 107 model runs lead to a larger temperature increase.
Automated Music Genre Classification through Deep Learning Techniques

Music Genre Classification (MGC) automatically categorizes music into different genres based on various musical attributes and features in a small number of music files. This is a crucial problem in the field of music information retrieval as it provides a way to organize and analyse large amounts of music files. MGC can be performed using conventional machine learning algorithms such as SVM, k-nearest neighbours, Decision trees, and neural networks. These algorithms learn to recognize different musical features and attributes to categorize the music files into different genres. The literature shows that the performance of conventional machine learning algorithms is inferior to deep learning algorithms such as CNN, RNN, etc., in various applications. Hence, the CNN algorithm is adapted to implement the classification of music files. This aims to classify music genres using CNN deep learning techniques. The performance of the algorithms for MGC can be evaluated using metrics such as accuracy, precision, recall, and F1-score. Additionally, the impact of different features and algorithms on the performance of MGC can be studied and compared. It has applications in areas such as automated music recommendation systems, music education, and music production. An accuracy of 83% is achieved by using CNN to accomplish the task of MGC.
Spatial and temporal pattern of benthic macroinvertebrate assemblages in two large Chinese freshwater lakes subjected to different degrees of eutrophication

Abstract Freshwater lakes are subjected to increasing eutrophication and algal blooms worldwide, which have dramatically impacted the aquatic biodiversity. This situation is especially true in the Yangtze River Floodplain, China. However, few researches have been focused on differences in the spatial and temporal patterns of benthic macroinvertebrates assemblages between the two adjacent lakes in this floodplain. In this study, we conducted seasonal investigations in 2021 to compare the spatial and temporal patterns of macroinvertebrates in Lakes Taihu and Lake Chaohu. Non-metric multidimensional scaling (NMDS) analyses showed Lake Taihu was found to have differences in assemblages within the lake, but Lake Chaohu was found to have uniform assemblage across the entire lake. Macrophyte-dominated lake regions (eastern Lake Taihu) were characterised by the highest species richness and diversity indices than those in other lake regions. The pollution sensitive species (e.g. EPT: Ephemeroptera, Plecoptera and Trichoptera) were only distributed in the macrophytic areas of Lake Taihu. Corbicula fluminea, polychaetes Nephtys oligobranchia and Capitella sp. were dominant in the middle central lake regions in Lake Taihu. Lake Chaohu and the northern Lake Taihu, with turbid algal-dominated state, were characterised by dominance of Oligochaetes and Chironomids. These differences were attributed to varying habitats and environmental parameters among different lake regions. Canonical correspondence analysis (CCA) demonstrated that macrophytes, chemical oxygen demand (CODMn), temperature, ammonium (NH3-N) and electric conductivity (EC) were detected as important factors influencing such macroinvertebrate assemblage patterns between these two lakes. This study contributes to the scientific knowledge of within lake habitats, community assemblages, nutrients and pollution within these lakes.
Comparative analyses of eight primer sets commonly used to target the bacterial 16S rRNA gene for marine metabarcoding-based studies

Next-generation sequencing (NGS), especially metabarcoding, is commonly used to study the diversity and distribution of microbes in diverse ecosystems. The choice of primer set is critical, given the drawbacks of short amplicons and amplicon sequencing bias inherent to metabarcoding. However, comparative analyses of primer sets have rarely been conducted using field samples. In this study, we compared eight commonly used primer sets, all targeting hypervariable regions in the bacterial 16S rRNA gene: 27F/338R (V1–V2), V2f/V3r (V2–V3), PRK341F/PRK806R (V3–V4), 341F/785R (V3–V4), 515F/806RB (V4), 515F/806R (V4), 515F-Y/926R (V4–V5), and B969F/BA1406R (V6–V8). We conducted NGS in triplicate, with >0.8 billion bases in total using coastal seawater samples. The representation of bacterial community composition varied significantly across the eight primer sets, despite being from the same sample. The 27F/338R primer set showed the highest number of operational taxonomic units (OTUs) and read counts, and accounted for 68% of all the order-level taxa found. Remarkably, a novel complementary combination of two primer sets, 27F/338R and 515F/806RB, covered 89% of all the orders that were present. Compared to other primer sets, this combination detected more OTUs of the orders Pelagibacterales and Rhodobacterales, which are ubiquitous in the oceans. As such, use of this combination in future studies may help to reduce diversity bias in ocean-derived samples, in particular temperate coastal samples.
Essai de discrimination de deux populations de vandoise (Leuciscus leuciscus, L., 1758) par étude de la forme de leurs écailles : aspects méthodologiques

Le Centre de Production Nucleaire (CPN) du Bugey rejette ses eaux de refroidissement dans le Rhone en rive droite. L'echauffement artificiel des eaux du Rhone est a l'origine d'importantes variations d'abondance des poissons echantillonnes a proximite du rejet. Les echanges entre les populations de poissons du Rhone et de I'Ain, affluent qui debouche en rive droite a 10 kilometres a l'aval du rejet d'eau echauffee, semblent jouer un role determinant dans la strategie adaptative des especes presentes. L'importance de ces echanges necessite une caracterisation des populations presentes qui peut etre obtenue par l'analyse de la forme du contour des ecailles. La presente etude expose la methode utilisee qui est appliquee a deux echantillons de vandoises (Leuciscus leuciscus, L., 1758), prelevees dans le Rhone a l'amont du CPN et dans le bassin versant de I'Ain. La technique de saisie automatique du contour de chaque ecaille, son codage, le calcul de descripteurs independants de l'orientation et de la taille des ecailles sont brievement presentes. L'analyse discriminante entre les deux echantillons, totalisant un effectif de 127 individus, selectionne dix descripteurs de forme dont neuf sont constitues par les parametres du developpement en series de Fourier du contour des ecailles. Une validation du type “jacknife” permet d'apprecier le pouvoir predictif de cette methode : 85 % des individus sont bien affectes par l'analyse discriminante a la definition de laquelle ils n'ont pas participe. Des propositions sont formulees pour ameliorer ce resultat. Un premier examen des vandoises capturees sur le Rhone a l'aval du CPN permet de confirmer l'hypothese de la provenance en proportion importante de vandoises de I'Ain dans la zone soumise a l'echauffement au debut du printemps.
Apparent Metabolizable Energy and Amino Acid Digestibility of Corn of Different Origin Fed to Male Broilers from 12 to 18 Days of Age

Simple Summary Understanding differences in the utilization of corn nutrients by broilers is essential for poultry nutritionists and feed producers that use corn of different origin in their feed formulation programs. In the present study, broilers were fed diets formulated with corn samples from the United States, Argentina, and Brazil to assess apparent metabolizable energy and amino acid digestibility. The results indicated similar nutrient utilization by broilers, regardless of the origin. Abstract Apparent metabolizable energy (AME) and apparent ileal amino acid digestibility (AIAAD) of corn samples from the United States (USA), Argentina (ARG), and Brazil (BRA) fed to 432 and 324 YPM × Ross 708 male broilers from 12 to 18 d of age were evaluated using the total collection method (experiment 1) and index method (experiment 2), respectively. In experiment 1, broilers were fed either a basal diet with 30% dextrose inclusion, or a test diet obtained by the replacement of dextrose with corn from each origin. In experiment 2, broilers were fed one of three test diets in which corn from each origin was the only source of AA. All dietary treatments had 12 replicate cages. Similar (p > 0.05) AME (dry-matter basis) values were observed between corn samples. The highest gap in AME (43 kcal/kg) was found between corn from BRA (3694 kcal/kg) and corn from the USA (3651 kcal/kg). Likewise, similar (p > 0.05) AIAAD values were observed for all AA apart from tryptophan (Trp), as corn from BRA (77.45%) had a higher (p = 0.024) Trp digestibility than corn from the USA (72.53%). Overall, a similar nutrient utilization by the birds was observed for the corn samples, regardless of origin.
DELFINES: Detecting Laser Fault Injection Attacks via Digital Sensors

Laser Fault Injection Attacks (LFIA) are a major concern in physical security of electronic circuits as they allow an attacker to inject a fault with a very high spatial accuracy. They are also often considered by information technology security evaluation facilities (ITSEFs) to deliver security certification, as Common Criteria, of embedded systems. Time or spatial redundancy can be foreseen as protection methods but they are costly and do not ensure immunity against multiple laser injections. The detection would be efficient if the detecting sensors meet enough density and sensitivity to cover the functional blocks being protected. Most sensors rely on analog and specific technology. In this article, we propose a method to detect LFIAs via a fully digital sensor based on a time to digital converter (TDC) and show its efficacy in detecting such faults in various conditions related to the current induced by the laser, the characteristics of the power grid network (PGN) of the circuit and the environmental variables (voltage, temperature). The simulation results obtained using a 45nm Nangate technology confirms the high efficiency of the proposed scheme in detecting LFIAs in a large range of such conditions.
Propuesta de una metodología para el ajuste de un modelo de ignición con información extraída desde sensores remotos

Los incendios forestales son un fenómeno que, en el caso de Chile, son provocados en un 99,7% por los seres humanos. El aumento de la interfaz urbano – forestal, en conjunto con el Cambio Climático han llevado a un aumento en la severidad de los incendios. Con el fin de evitar daños ecológicos y sociales, es necesario crear sistemas efectivos de prevención, que minimicen los costos. Por aquello se propone una metodología para un modelo de ignición, que se basa únicamente en información que puede ser extraída desde sensores remotos de forma rutinaria. Estas fuentes de información poseen ventajas evidentes cuando se comparan con otras fuentes de datos, tales como; encuesta, muestreos de campos, censos, y pueden ser actualizadas con mayor frecuencia. Usando un modelo de clasificación Random Forest se consigue una exactitud cercana al 93% en las estimaciones, comparables a estudios hechos a nivel nacional e internacional. Las variables que más contribuyen al modelo son la temperatura media anual, la mediana de NDVI, la altitud y un índice global de modificación antrópica, que sintetiza la influencia antrópica en el territorio. La importancia de un modelo como el presentado es que sus insumos pueden ser actualizados de forma más dinámica y a un menor costo. Palabras Claves: Palabras Claves: Sensores Remotos, Incendios Forestales, Random Forest, prevención, Modelo de Ignición.
To what extent does river routing matter in hydrological modeling?

Abstract. Spatially distributed hydrology and land surface models are typically applied in combination with river routing schemes that convert instantaneous runoff into streamflow. Nevertheless, the development of such schemes has been somehow disconnected from hydrologic model calibration research, although both seek to achieve more realistic streamflow simulations. In this paper, we seek to bridge this gap to understand the extent to which the configuration of routing schemes affects hydrologic model parameter searches in water resources applications. To this end, we configure the Variable Infiltration Capacity (VIC) model coupled with the mizuRoute routing model in the Cautín River basin (2770 km2), Chile. We use the Latin hypercube sampling (LHS) method to generate 3500 different model parameters sets, for which basin-averaged runoff estimates are obtained directly (no routing or instantaneous runoff case) and are subsequently compared against outputs from four routing schemes (unit hydrograph, Lagrangian kinematic wave, Muskingum–Cunge, and diffusive wave) applied with five different routing time steps (1, 2, 3, 4, and 6 h). The results show that incorporating routing schemes may alter streamflow simulations at sub-daily, daily, and even monthly timescales. The maximum Kling–Gupta efficiency (KGE) obtained for daily streamflow increases from 0.64 (instantaneous runoff) to 0.81 (for the best routing scheme), and such improvements do not depend on the routing time step. Moreover, the optimal parameter sets may differ depending on the routing scheme configuration, affecting the baseflow contribution to total runoff. Including routing models decreases streamflow values in flood frequency curves and may alter the probabilistic distribution of the medium- and low-flow segments of the flow duration curve considerably (compared to the case without routing). More generally, the results presented here highlight the potential impacts of river routing implementations on water resources applications that involve hydrologic models and, in particular, parameter calibration.
Geochemistry of hydrothermal vent fluids from the northern Juan De Fuca Ridge

Abstract : To rigorously constrain the role of organic compounds in crustal alteration processes at mid-ocean ridges, quantitative information on the abundances and distributions of organic compounds in hydrothermal vent fluids is required. This thesis was undertaken to provide this information for several low-molecular weight organic compounds (C(1)-C(4) alkanes, C(2)-C(3) alkenes, benzene and toluene) in fluids collected in July, 2000, at three sites on the northern Juan de Fuca Ridge: the Dead Dog and ODP Mound fields, which are located at Middle Valley, and the Main Endeavour Field (MEF), located on the Endeavour segment. The relative abundances of alkane-alkene pairs were used to constrain subsurface reaction zone temperatures. Isotopic systematics of CO2, C(1)-C(4) alkanes, and benzene provided information on the residence times of fluids in the subsurface and the reaction mechanisms that control the distributions of aqueous organic compounds. The presence of organic compounds in these fluids also controlled the distributions of inorganic compounds-most notably, H(2). Integration of the data on both organic and inorganic species in these fluids provides a powerful tool to befter constraining models of subsurface conditions in hydrothennal vent environments.
Gully Control in SAT Watersheds

Gully erosion is geographically a widespread problem. It is common in the semi-arid region, characterized by denuded landscape and flash floods. An estimated 4 million ha of land in India and 29 million ha of land in Africa are affected by severe gully erosion. Gully erosion is more difficult and expensive to control than other types of soil erosion. A full understanding of erosion processes at various stages of gully development is essential to achieve gully stabilization. Without proper understanding often the measures taken for controlling gully were found unnecessary or ineffective. This report provides the basic knowledge of gully formation and its causes. The classification of gullies and the basic principles of its control are explained. Drawing primarily the experiences from the several on-farm watershed projects implemented by ICRISAT, the report provides the practical approach for gully control in the context of overall watershed development and management. The basic considerations and the design details of various gully control structures, viz., loose rock dam, double-row post-brush dam, double-row post-stone dam, single-row post-stone dam, stone wall dam, masonry check-dam, earthen check-dam and gabion structures are covered in detail. The key hydrological data, i.e., runoff volume and peak runoff rate measured at the watershed scale along with design peak runoff rate for the various locations in India are given. These data will greatly assist the watershed implementing agencies in the selection, design, construction and maintenance of gully control structures
Financial Risk and Resource Adequacy in Markets With High Renewable Penetration

This article considers the evolution of electricity market design as systems shift toward carbon-free technologies. Growth in wind and solar generation is likely to lead to increased price volatility on diurnal and seasonal timescales. In the standard risk-neutral optimization framework, volatility does not pose any theoretical issues for market design. Because revenue volatility has the potential to lead to a higher cost of capital for investments in competitive markets, however, many observers have questioned the viability of competitive models for resource adequacy as wind and solar grow in importance. To assess the role of risk management in overall market performance, we construct a stochastic equilibrium model incorporating financial entities as hedge providers for investors in generation capacity. Unlike in the standard optimization framework, the cost of capital in the equilibrium framework is endogenously determined by interannual revenue volatility and the risk measures used by market participants. Surprisingly, exploratory numerical tests suggest that overall investment risk may be lower in systems dominated by variable renewables due to reduced exposure to fuel price uncertainty. However, changes in investment risk are not uniform across resource types, and increased risk for peaking and backup resources contributes to lower reliability in the modeled future systems.
To Check or Not to Check? A Comment on the Contemporary Psychometrics (ConPsy) Checklist for the Analysis of Questionnaire Items

In a recent paper, the first version of the contemporary psychometrics (ConPsy) checklist for assessing measurement tool quality has been published. This checklist aims to provide guidelines and references to researchers to assess measurement properties for newly developed measurement instruments. The ConPsy checklist recommends appropriate statistical methods for measurement instrument evaluation to guide researchers in instrument development and to support peer review. In this opinion article, I critically review some aspects of the checklist and question the usefulness of certain psychometric analyses in research practice.
Sensitivity of surface soil moisture retrieval to satellite-derived vegetation descriptors over wheat fields in the Kairouan plain

ABSTRACT Soil moisture estimation is a key component in hydrological processes and irrigation amounts' estimation. The synergetic use of optical and radar data has been proven to retrieve the surface soil moisture at a field scale using the Water Cloud Model (WCM). In this work, we evaluate the impact of staellite-derived vegetation descriptors to estimate the surface soil moisture. Therefore, we used the Sentinel-1 data to test the polarization ratio (${\rm{\sigma }}_{{\rm{VH}}}^0/{\rm{\sigma }}_{{\rm{VV}}}^0$σVH0/σVV0) and the normalized polarization ratio (IN) and the frequently used optical Normalized Difference vegetation Index (NDVI) as vegetation descriptors. Synchronous with Sentinel-1 acquisitions, in situ soil moisture were collected over wheat fields in the Kairouan plain in the center of Tunisia. To avoid the bare soil roughness effect and the radar signal saturation in dense vegetation context, we considered the data where the NDVI values vary between 0.25 and 0.7. The soil moisture inversion using the WCM and NDVI as a vegetation descriptor was characterized by an RMSE value of 5.6 vol.%. A relatively close performance was obtained using IN and (${\rm{\sigma }}_{{\rm{VH}}}^0/{\rm{\sigma }}_{{\rm{VV}}}^0$σVH0/σVV0) with RMSE under 7. 5 vol.%. The results revealed the consistency of the radar-derived data in describing the vegetation for the retrieval of soil moisture.