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Early puberty poses a significant challenge for male Atlantic salmon in aquaculture due to its negative impact on growth and welfare. The regulation of puberty in vertebrates involves 2 key reproductive hormones: follicle-stimulating hormone (FSH) and luteinizing hormone (LH) and their gonadal receptors. In male mice lacking FSH receptor, testes size is reduced, but fertility is maintained, while medaka and zebrafish with a disrupted fshr gene exhibit near normal testis size and fertility. In these fishes both Fsh and Lh are present during puberty and Lh may rescue fertility, while in salmonid fish only Fsh is present in the circulation during puberty. Using CRISPR-Cas9, we produced crispants with a high prevalence of fshr mutations at the target site, which remained fertile, although more than half showed a testis development deviating from wild-type (wt) males. Crossing out these F0 crispants to each other produced a viable F1 generation showing frameshift (fshr−/−) or in-frame mutations (fshrif/if). Nearly all wt males matured while all fshr−/− males remained immature with small testes containing A spermatogonia as the furthest developed germ cell type and prepubertal plasma androgen levels. Also, the pituitary transcript levels of gnrhr2bba and lhb, but not for fshb, were reduced in the fshr−/− males compared with maturing males. More than half of the fshrif/if mutant males showed no or a delayed maturation. In conclusion, Atlantic salmon show the unique characteristic that loss of Fshr function alone results in male infertility, offering new opportunities to control precocious puberty or fertility in salmon.

The Mediterranean basin is one of the world’s most vulnerable regions to climate change. The fast rise of temperatures and the decrease of precipitation are some of climate change issues. Aquifers’ recharge will be also decreased in the next century. Hydroeconomic modelling is a suitable tool to analyse the effects of climate change on the future state of groundwater resources at regional scales. Hydroeconomic models of Mahdia Ksour Essef coastal aquifer, Tunisia, were developed to show how climate change affects the groundwater scarcity and farmers’ profits. The models contain hydrological and economic parameters. Six scenarios covering three policies (no cooperation between farmers, partial cooperation regime and full cooperation regime) and two situations (normal conditions and climate change situations) are evaluated. The simulation results show the potential impacts of climate change scenarios on the aquifer water table level, groundwater extractions, crops superficies and famers’ benefits for each policy in the future. The full cooperation regime gives the best results in terms of aquifer sustainability and social welfare mainly under the climate change conditions.

Gravitational lensing is a powerful tool for studying the distribution of mass in the Universe. Understanding the magnification bias effect in gravitational lensing and its impact on the flux of sub-millimetre galaxies (SMGs) is crucial for accurate interpretations of observational data. This study aims to investigate the magnification bias effect and analyse the mass density profiles of different types of foreground lenses, including quasi-stellar objects, galaxies, and clusters. The specific goals are to compare the lens types, assess the impact of angular resolution on the analysis, and determine the adequacy of theoretical mass density profiles in explaining the observed data, using four different theoretical mass density profiles. The magnification bias was estimated using the cross-correlation function between the positions of background SMGs and foreground lens samples. Stacking techniques were employed to enhance the signal at smaller angular separations, and the more precise positions from the WISE catalogue were utilised to improve positional accuracy. The cross-correlation measurements revealed distinctive central excess and outer power-law profiles, with a lack of signal in the intermediate region. The analysis of mass density profiles indicated limitations in the selected profiles' ability to explain the observed data, highlighting the need for additional considerations. The results suggest the presence of isolated galactic halos and the importance of considering environmental factors and close satellites in future investigations. The derived masses and best-fit parameters contribute to our understanding of lensing systems and provide constraints on the nature of central galaxies. Notably, the intriguing lack of signal around 10 arcsec challenges current understanding and calls for further quantitative analysis and confirmation of the observed feature.

Water supply in the Mahdia region of Tunisia originates mainly from groundwater sources. As a common pool resource, these aquifers are highly susceptible to overexploitation, resulting in the classical tragedy of the commons. In this study, a hydro-economic optimization model was developed to determine the most efficient allocation of groundwater resources between farmers in the present and also by considering the needs of future generations. An economic analysis was performed with the model to find efficient policies that contribute to decrease aquifer overuse in normal and drought years and improve its sustainability. Financial analysis of returns and costs of producing irrigated crops were determined in the Mahdia-Ksour Essef aquifer, in which the benefits of drip, flood, and sprinkler irrigation were compared for each crop. The efficiency of alternative scenarios (baseline scenario “no policies undertaken” and water policy scenarios) were compared. Data for the analysis were obtained from multiple sources. Results show the importance of cooperation between farmers. The consideration of pumping costs along time in the farmers’ benefit equation allows the recovery of the water table level over the next two decades. This study assessed the importance of policy interventions to maximize social benefits for sustainable groundwater management. This paper introduced a case application of a dynamic model for managing an aquifer of the Mahdia region in Tunisia. This overused coastal aquifer requires the urgent application of the proposed water policies to maintain groundwater’s natural level and prevent the propagation of saltwater intrusion. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Water supply in the Mahdia region of Tunisia originates mainly from groundwater sources. As a common pool resource, these aquifers are highly susceptible to overexploitation, resulting in the classical tragedy of the commons. In this study, a hydro-economic optimization model was developed to determine the most efficient allocation of groundwater resources between farmers in the present and also by considering the needs of future generations. An economic analysis was performed with the model to find efficient policies that contribute to decrease aquifer overuse in normal and drought years and improve its sustainability. Financial analysis of returns and costs of producing irrigated crops were determined in the Mahdia-Ksour Essef aquifer, in which the benefits of drip, flood, and sprinkler irrigation were compared for each crop. The efficiency of alternative scenarios (baseline scenario “no policies undertaken” and water policy scenarios) were compared. Data for the analysis were obtained from multiple sources. Results show the importance of cooperation between farmers. The consideration of pumping costs along time in the farmers’ benefit equation allows the recovery of the water table level over the next two decades. This study assessed the importance of policy interventions to maximize social benefits for sustainable groundwater management. This paper introduced a case application of a dynamic model for managing an aquifer of the Mahdia region in Tunisia. This overused coastal aquifer requires the urgent application of the proposed water policies to maintain groundwater’s natural level and prevent the propagation of saltwater intrusion. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Recovering the polarized cosmic microwave background (CMB) is crucial for shading light on Cosmic Inflation. Methods with different characteristics should be developed and optimized. We aim to use a neural network called CENN and train it for recovering the E and B modes of the CMB. We train the network with realistic simulations of 256x256 pixel squared patches at 100, 143 and 217 GHz Planck channels, which contain the CMB, thermal dust, synchrotron, PS and noise. We make several trainings sets: 30, 25 and 20 arcmin resolution patches at the same position in the sky. After being trained, CENN is able to recover the CMB signal at 143 GHz in Q and U patches. Then, we use NaMaster for estimating the EE and BB power spectrum for each input and output patches in the test dataset, as well as the difference between input and output power spectra and the residuals. We also test the methodology using a different foreground model at 5 arcmin resolution without noise. We recover the E-mode generally founding residuals bellow the input signal at all scales. In particular, we found a value of about 0.1 muK2 at l<200, decreasing below 0.01 muK2 at smaller scales. For the B-mode, we similarly recover the CMB with residuals between 0.01 and 0.001 muK2. We also train the network with 5 arcmin Planck simulations without noise, obtaining clearly better results with respect the previous cases. For a different foreground model, the recovery is similar, although B-mode residuals increase above the input signal. In general, we found that, the network performs better when training with the same resolution used for testing. Based on the results, CENN seems to be a promising for recovering both E and B modes at sub-degree scales in ground-base experiments such as POLARBEAR, SO and CMB-S4. Once extending its applicability at all sky, it could be an alternative component separation method for LiteBIRD satellite., Comment: 11 pages, 10 figures, Submitted to A&A

This paper is the third in a series on submillimeter galaxy magnification bias, focusing on the tomographic scenario. It refines the methodology used to constrain the halo occupation distribution model and cosmological parameters within a flat $\Lambda$CDM model, using updated data. The study aims to optimize CPU time, explore strategies for analyzing different redshift bins, and assess the impact of excluding the GAMA15 field. The tomographic approach involves dividing the redshift range into bins and analyzing cross-correlation measurements between submillimeter and foreground galaxies. The results show good agreement between the mean-redshift and full model cases, with an increase in the minimum mass of lenses at higher redshifts. The inferred cosmological parameters have narrower posterior distributions, indicating reduced measurement uncertainties compared to previous studies. Excluding the GAMA15 field reduces the cross-correlation signal, suggesting sample variance within the large-scale structure. Extending the redshift range improves robustness against sample variance and produces similar but tighter constraints. The study highlights the importance of sample variance and redshift binning in tomographic analyses, and suggests using additional wide-area fields and updated foreground catalogues for more effective implementation., Comment: This work is the third of a series of three. 17 pages and 19 figure. submitted to A&A

The measurement of the cross-correlation function is crucial to assess magnification bias in galaxy surveys. Previous works used mini-tile subsampling, but accurately determining the integral constraint (IC) correction for unbiased estimation is challenging due to various factors. We present a new methodology for estimating the cross-correlation function, utilizing full field area and reducing statistical uncertainty. Covariance matrices were estimated by dividing each field into at least five patches using a k-mean clustering algorithm. Robustness was assessed by comparing spectroscopic and photometric lens samples, yielding compatible results. Cross-correlation and auto-correlation analyses in the GAMA fields revealed a stronger signal in GAMA15, likely due to rare large-scale structure combinations. Our findings highlight the robustness of the new methodology and suggest sample-specific effects. Subsequent papers in this series will explore other aspects of magnification bias and address potential biases from the GAMA15 signal on cosmological parameter constraints., Comment: This work is the first one of a three-paper serie. 14 pages, 9 figures, submitted for publication by A&A

El SMC (sheet molding compound) es un material compuesto comúnmente usado para fabricar piezas por un proceso de moldeo por compresión en caliente. Este compuesto cuenta con dos características claves para el sector de la automoción: permite producir piezas con una elevada cadencia y presenta una gran flexibilidad para el diseño de piezas de diversas formas y tamaños. Su gran inconveniente, como el de los materiales compuestos, en general, es que no se pueden reciclar y al final de su vida útil terminan almacenados en vertederos. En este trabajo, presentamos un nuevo SMC sostenible fácilmente reciclable mediante el uso de una resina termoplástica líquida patentada en el CSIC, SMC (sheet moulding compound) is a composite material commonly used to manufacture parts by a hot compression moulding process. This composite has two key characteristics for the automotive sector: it allows parts to be produced at a high rate of production and it has great flexibility for the design of parts of various shapes and sizes. However, like other composite materials, its primary drawback lies in the limited recyclability, resulting in their disposal in landfills at the end of their lifespan. In this work, we present a new and sustainable SMC using a liquid thermoplastic resin patented at CSIC

This study develops a hydro-economic model for the coastal aquifer Mahdia Ksour Essef in Tunisia in order to analyze how external shocks (climate change, energy price increase) and management policies can affect groundwater sustainability during the coming decades. Twenty-one scenarios covering three management policies (free market, partial cooperation, and full cooperation policy) under various potential climate and economic changes are evaluated. The results of scenario simulations show the potential impact of energy soaring prices and climate change on the aquifer’s water table level, groundwater extractions, cropland areas, and farmers’ benefits under each policy option in the future. They also show that the best scenario to address the effects of climate change would need to take into account environmental externalities and efficient energy prices. The findings of this study are very important in the context of climate change and uncertain global energy markets and provide feasible alternatives to preserve the regional economy and aquifer sustainability.

This study develops a hydro-economic model for the coastal aquifer Mahdia Ksour Essef in Tunisia in order to analyze how external shocks (climate change, energy price increase) and management policies can affect groundwater sustainability during the coming decades. Twenty-one scenarios covering three management policies (free market, partial cooperation, and full cooperation policy) under various potential climate and economic changes are evaluated. The results of scenario simulations show the potential impact of energy soaring prices and climate change on the aquifer’s water table level, groundwater extractions, cropland areas, and farmers’ benefits under each policy option in the future. They also show that the best scenario to address the effects of climate change would need to take into account environmental externalities and efficient energy prices. The findings of this study are very important in the context of climate change and uncertain global energy markets and provide feasible alternatives to preserve the regional economy and aquifer sustainability.

Using germ cell-free (GCF), sterile, dnd-knockout salmon for farming could solve the problems associated with precocious maturation and genetic introgression of farmed breeds into wild populations. However, prior to using GCF fish in the salmon farming industry, it is crucial to understand if, or how, the GCF phenotype differs from wild type (WT) counterparts in terms of growth and welfare. To characterize the GCF phenotype throughout a production cycle, we reared GCF and WT salmon in indoor common garden tanks for 3 years, until harvest size. Regarding body size, smoltification markers (mRNA levels of gill Na+/K+-ATPase [NKA] subunits), plasma stress indicators (pH, glucose, sodium, chloride, calcium), relative heart size, prevalence of vertebra deformities and fillet proximate composition, GCF fish could not be distinguished from WTs. Transient differences were detected in plasma concentrations of lactate and osmolality, and only a few genes were differentially expressed in WT and GCF transcriptomes of muscle and pituitary. At harvest, fillets from GCF and WT salmon contained the same amount of omega-3 fatty acids, however the relative content of omega-3 fatty acids was higher in GCF compared to WT males. Towards harvest size, body growth rate, condition factor and relative liver size were significantly higher in WT than in GCF fish, probably relating to initiation of puberty in WTs. Since GCF salmon never become sexually mature, it is possible to postpone the time of harvest to exploit the growth potential uninhibited by sexual maturation. In conclusion, GCF salmon performed to a large extent similarly to their WT counterparts but had the clear advantage of never maturing.

Aims. The main goal of this paper is to derive observational constraints on the halo mass fuction (HMF) by performing a tomographic analysis of the magnification bias signal on a sample of background submillimeter galaxies. The results can then be compared with those from a non-tomographic study. Methods. We measure the cross-correlation function between a sample of foreground GAMA galaxies with spectroscopic redshifts in the range $0.1 < z < 0.8$ (and divided up into four bins) and a sample of background submillimeter galaxies from H-ATLAS with photometric redshifts in the range $1.2 < z < 4.0$. We model the weak lensing signal within the halo model formalism and carry out a Markov chain Monte Carlo algorithm to obtain the posterior distribution of all HMF parameters, which we assume to follow the Sheth and Tormen (ST) three-parameter and two-parameter fits. Results. While the observational constraints on the HMF from the non-tomographic analysis are not stringent, there is a remarkable improvement in terms of uncertainty reduction when tomography is adopted. Moreover, with respect to the traditional ST triple of values from numerical simulations, the results from the three-parameter fit predict a higher number density of halos at masses below $10^{12}M_{\odot}/h$ at 95% credibility. The two-parameter fit yields even more restricting results, with a larger number density of halos below $10^{13}M_{\odot}/h$ and a lower one above $10^{14}M_{\odot}/h$, this time at more than 3$\sigma$ credibility. Our results are therefore in disagreement with the standard N-body values for the ST fit at 2$\sigma$ and 3$\sigma$, respectively.

This letter is about confinement in QCD. At the moment we have pictures of confinement to complete our understanding of the physics of strongly interacting particles, interaction which asks for confinement. As it is said in [1] : " In principle it should be possible to derive the confinement hypothesis from the QCD Lagrangian. At this time, no rigorous derivation exists, so it is not absolutely clear that the confinement hypothesis is a bone fide prediction of QCD" . In this letter we show that a sufficient (of course not necessary) condition for confinement is that topological structure of vacuum in Nature does not correspond to the $\theta$-vacuum. Therefore, if different vacua with nontrivial winding number cannot be connected by tunneling, we obtain confinement as a consequence., Comment: 10 pages

The increasing concern about the degradation of water-dependent ecosystems calls for considering ecosystems benefits in water management decision-making. Sustainable water management requires adequate economic and biophysical information on water systems supporting both human activities and natural ecosystems. This information is essential for assessing the impact on social welfare of water allocation options. This paper evaluates various alternative water management policies by including the spatial and sectoral interrelationships between the economic and environmental uses of water. A hydroeconomic model is developed to analyze water management policies for adaptation to reduced water availability in the Ebro Basin of Spain. The originality in our contribution is the integration of environmental benefits across the basin, by using endemic biophysical information that relates stream flows and ecosystem status in the Ebro Basin. The results show the enhancement of social welfare that can be achieved by protecting environmental flows, and the tradeoffs between economic and environmental benefits under alternative adaptation strategies. The introduction of water markets is a policy that maximizes the private benefits of economic activities, but disregards environmental benefits. The results show that the current institutional policy where stakeholders cooperate inside the water authority, provides lower private benefits but higher environmental benefits compared to those obtained under water markets, especially under severe droughts. However, the water authority is not allocating enough environmental flows to optimize social welfare. This study informs strategies for protection of environmental flows in the Ebro Basin, which is a compelling decision under the imminent climate change impacts on water availability in coming decades.

Constraining the polarisation properties of extragalactic point sources is a relevant task not only because they are one of the main contaminants for primordial cosmic microwave background B-mode detection if the tensor-to-scalar ratio is lower than r = 0.001, but also for a better understanding of the properties of radio-loud active galactic nuclei. We develop and train a machine learning model based on a convolutional neural network to learn how to estimate the polarisation flux density and angle of point sources embedded in cosmic microwave background images knowing only their positions. To train the neural network, we use realistic simulations of patches of area 32x32 pixels at the 217 GHz Planck channel with injected point sources at their centres. The patches also contain a realistic background composed by dust, the CMB and instrumental noise. Firstly, we study the comparison between true and estimated polarisation flux densities for P, Q and U. Secondly, we analyse the comparison between true and estimated polarisation angles. Finally, we study the performance of our model with real data and we compare our results against the PCCS2. We obtain that our model is reliable to constrain the polarisation flux above 80 mJy. For this limit, we obtain errors lower than 30%. Training the same network with Q and U, the reliability limit is above +-250 mJy for determining the polarisation angle of both Q and U sources with a 1sigma uncertainty of +-29deg and +-32deg for Q and U sources respectively. We obtain similar results to the PCCS2 for some sources, although we also find discrepancies in the 300-400 mJy flux density range with respect to the Planck catalogue. Based on these results, our model seems to be a promising tool to give estimations of the polarisation flux densities and angles of point sources above 80 mJy in any catalogue with practically null computational time., Comment: 9 pages, 9 Figures. Forthcoming article Astronomy & Astrophysics journal

In this work, we want to exploit the magnification bias of the SMGs using two different foreground samples, quasi-stellar objects (QSOs) and galaxies. Our aim is to study and compare their mass density profiles and estimate their masses and concentrations. The background SMG sample consists of objects observed by \textit{Herschel} with 1.2

Component separation is the process with which emission sources in astrophysical maps are generally extracted by taking multi-frequency information into account. It is crucial to develop more reliable methods for component separation for future CMB experiments. We aim to develop a new method based on fully convolutional neural networks called the Cosmic microwave background Extraction Neural Network (CENN) in order to extract the CMB signal in total intensity. The frequencies used are the Planck channels 143, 217 and 353 GHz. We validate the network at all sky, and at three latitude intervals: lat1=0^{\circ}

Aims. The main goal of this paper is to derive observational constraints on the halo mass fuction (HMF) by performing a tomographic analysis of the magnification bias signal on a sample of background submillimeter galaxies. The results can then be compared with those from a non-tomographic study. Methods. We measure the cross-correlation function between a sample of foreground GAMA galaxies with spectroscopic redshifts in the range $0.1 < z < 0.8$ (and divided up into four bins) and a sample of background submillimeter galaxies from H-ATLAS with photometric redshifts in the range $1.2 < z < 4.0$. We model the weak lensing signal within the halo model formalism and carry out a Markov chain Monte Carlo algorithm to obtain the posterior distribution of all HMF parameters, which we assume to follow the Sheth and Tormen (ST) three-parameter and two-parameter fits. Results. While the observational constraints on the HMF from the non-tomographic analysis are not stringent, there is a remarkable improvement in terms of uncertainty reduction when tomography is adopted. Moreover, with respect to the traditional ST triple of values from numerical simulations, the results from the three-parameter fit predict a higher number density of halos at masses below $10^{12}M_{\odot}/h$ at 95% credibility. The two-parameter fit yields even more restricting results, with a larger number density of halos below $10^{13}M_{\odot}/h$ and a lower one above $10^{14}M_{\odot}/h$, this time at more than 3$\sigma$ credibility. Our results are therefore in disagreement with the standard N-body values for the ST fit at 2$\sigma$ and 3$\sigma$, respectively.

The increasing concern about the degradation of water-dependent ecosystems calls for considering ecosystems benefits in water management decision-making. Sustainable water management requires adequate economic and biophysical information on water systems supporting both human activities and natural ecosystems. This information is essential for assessing the impact on social welfare of water allocation options. This paper evaluates various alternative water management policies by including the spatial and sectoral interrelationships between the economic and environmental uses of water. A hydroeconomic model is developed to analyze water management policies for adaptation to reduced water availability in the Ebro Basin of Spain. The originality in our contribution is the integration of environmental benefits across the basin, by using endemic biophysical information that relates stream flows and ecosystem status in the Ebro Basin. The results show the enhancement of social welfare that can be achieved by protecting environmental flows, and the tradeoffs between economic and environmental benefits under alternative adaptation strategies. The introduction of water markets is a policy that maximizes the private benefits of economic activities, but disregards environmental benefits. The results show that the current institutional policy where stakeholders cooperate inside the water authority, provides lower private benefits but higher environmental benefits compared to those obtained under water markets, especially under severe droughts. However, the water authority is not allocating enough environmental flows to optimize social welfare. This study informs strategies for protection of environmental flows in the Ebro Basin, which is a compelling decision under the imminent climate change impacts on water availability in coming decades.

Today’s military and commercial aircraft avionics and general systems are built around complex networks of intelligent devices. Maintenance and troubleshooting of these systems often require access to the data bus or networks connecting the system components. Whether it is on the integration test bench, Final Assembly Line (FAL) or at the Maintenance and Repair Organization (MRO), these tasks are usually performed by means of many, expensive, heavy and intrusive equipment. The MMIBS (Mini-Multi Interface Box Simulator) is a very compact, portable, multipurpose, lightweight, low-power, and easy-of-use electronics test means intended to improve digital aircraft ground testing and maintenance troubleshooting. It is capable of perform functional testing and simulating aeronautical equipment through most common aeronautical communication interfaces, such as AFDX, CAN BUS, ARINC 429, MIL-STD-1553, RS-422, RS-232, RS-485, Discrete and Analog I/O and RVDT (Rotary Variable Differential Transformer) reading capabilities. Besides, the system is highly configurable and reprogrammable by means of intuitive Python-based scripting. System is also able to be controlled with an intuitive, user-friendly and dedicated HMI (Human Machine Interface). In this mode, the user can conform a MMIBS WIFI network, allowing multiple MMIBS operating in parallel to cover complex testing scenarios. The MMIBS device integrates all the aeronautical communication and signaling in a volume of 12x12x12cm and weight of 1200g and provides an autonomy of 5 hours. In this way, our solution combines performance, reliability, low maintenance costs, and ease-of-use to support efficient ground maintenance operations.

In this work we want to study the average mass density profile of tens to hundreds of clusters of galaxies acting as lenses that produce a magnification bias on the SMGs, and to estimate their associated masses and concentrations for different richness ranges. The background sample is composed of SMGs observed by Herschel with 1.2

Point Source (PS) detection is an important issue for future Cosmic Microwave Background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal at small scales. Improving its multifrequency detection would allow to take into account valuable information otherwise neglected when extracting PS using a channel-by-channel approach. We develop a method based on Neural Networks (NNs) to detect PS in multifrequency realistic simulations and compare its performance against one of the most popular methods, the matrix filters. The frequencies used are 143, 217 and 353 GHz and we impose a Galactic cut of 30 degrees. We produce simulations by adding contaminating signals to the PS maps as the CMB, the Cosmic Infrared Background, the Galactic thermal emission, the thermal Sunyaev-Zel'dovich effect and the instrumental noise. These simulations are used to train two NNs called Flat and Spectral MultiPoSeIDoN. The first one considers PS with a flat spectrum and the second one is more realistic because it takes into account the spectral behavior of the PS. Using a detection limit of 60 mJy, Flat MultiPoSeIDoN reachs the 90% of completeness level at 58 mJy and at 79, 71 and 60 for the spectral case at 143, 217 and 353 GHz respectively, while the matrix filters reach it at 84, 79 and 123 mJy. Using safer 4{\sigma} detection limit does not help to improve these results. In all cases, MultiPoSeIDoN obtain a much lower number of spurious sources than the filter. The NNs recover the flux density of the detections with a relative error of 10% above 100 mJy, while the filter above 150 mJy. Based on the results, NNs are the perfect candidates to substitute filters to detect multifrequency PS in future CMB experiments. Moreover, we have shown that a multifrequency approach can detect sources with higher accuracy than single-frequency approaches also based on NNs., Comment: Forthcoming article Astronomy and Astrophysics since 23 November 2021. Received: 26 July 2021 / Accepted: 05 November 2021

As in Gonzalez-Nuevo et al. 2017 and Bonavera et al. 2019, the high-z sub-millimetre galaxies can be used as background sample for gravitational lensing studies thanks to their magnification bias. In particular, as in Bonavera et al. 2020 the magnification bias can be exploited in order to constrain the free parameters of a Halo Occupation Distribution (HOD) model and some of the main cosmological parameters. In this work the magnification bias has been evaluated as cosmological tool in a tomographic set up. The cross-correlation function (CCF) data have been used to jointly constrain the astrophysical parameters $M_{min}$, $M_{1}$ and $\alpha$ in each one of the selected redshift bins and the $\Omega_{M}$, $\sigma_{8}$, and $H_0$ cosmological ones ($\Lambda$CDM). Moreover, we explore the possible time evolution of the dark energy density introducing also the $\omega_0, \omega_a$ parameters in the joint analysis ($\omega_0$CDM and $\omega_0\omega_a$CDM). The CCF has been measured between a foreground spectroscopic sample of GAMA galaxies that has been divided into four redshift bins (0.1-0.2, 0.2-0.3, 0.3-0.5 and 0.5-0.8) and a sample of H-ATLAS galaxies with photometric redshifts >1.2. The CCF is modelled using a description that depends on HOD and cosmological parameters that are estimated with MCMC in different cases. For the $\Lambda$CDM model, the analysis yields a maximum posterior value at 0.26 with $[0.17,0.41]$ 68\% C.I. for $\Omega_M$ and at 0.87 with $[0.75,1]$ 68\% C.I. for $\sigma_8$. With our current results $H_0$ is not yet constrained. With the $\omega_0$CDM model, the constraints on $\Omega_M$ and $\sigma_8$ are similar, but we found a maximum posterior value for $\omega_0$ at -1 with $[-1.56, -0.47]$ 68\% C.I. In the $\omega_0\omega_a$CDM model, the results are -1.09 with $[-1.72, -0.66]$ 68\% C.I. for $\omega_0$ and -0.19 with $[-1.88, 1.48]$ 68\% C.I. for $\omega_a$., Comment: accepted A&A

Today’s military and commercial aircraft avionics and general systems are built around complex networks of intelligent devices. Maintenance and troubleshooting of these systems often require access to the data bus or networks connecting the system components. Whether it is on the integration test bench, Final Assembly Line (FAL) or at the Maintenance and Repair Organization (MRO), these tasks are usually performed by means of many, expensive, heavy and intrusive equipment. The MMIBS (Mini-Multi Interface Box Simulator) is a very compact, portable, multipurpose, lightweight, low-power, and easy-of-use electronics test means intended to improve digital aircraft ground testing and maintenance troubleshooting. It is capable of perform functional testing and simulating aeronautical equipment through most common aeronautical communication interfaces, such as AFDX, CAN BUS, ARINC 429, MIL-STD-1553, RS-422, RS-232, RS-485, Discrete and Analog I/O and RVDT (Rotary Variable Differential Transformer) reading capabilities. Besides, the system is highly configurable and reprogrammable by means of intuitive Python-based scripting. System is also able to be controlled with an intuitive, user-friendly and dedicated HMI (Human Machine Interface). In this mode, the user can conform a MMIBS WIFI network, allowing multiple MMIBS operating in parallel to cover complex testing scenarios. The MMIBS device integrates all the aeronautical communication and signaling in a volume of 12x12x12cm and weight of 1200g and provides an autonomy of 5 hours. In this way, our solution combines performance, reliability, low maintenance costs, and ease-of-use to support efficient ground maintenance operations.

Today’s military and commercial aircraft avionics and general systems are built around complex networks of intelligent devices. Maintenance and troubleshooting of these systems often require access to the data bus or networks connecting the system components. Whether it is on the integration test bench, Final Assembly Line (FAL) or at the Maintenance and Repair Organization (MRO), these tasks are usually performed by means of many, expensive, heavy and intrusive equipment. The MMIBS (Mini-Multi Interface Box Simulator) is a very compact, portable, multipurpose, lightweight, low-power, and easy-of-use electronics test means intended to improve digital aircraft ground testing and maintenance troubleshooting. It is capable of perform functional testing and simulating aeronautical equipment through most common aeronautical communication interfaces, such as AFDX, CAN BUS, ARINC 429, MIL-STD-1553, RS-422, RS-232, RS-485, Discrete and Analog I/O and RVDT (Rotary Variable Differential Transformer) reading capabilities. Besides, the system is highly configurable and reprogrammable by means of intuitive Python-based scripting. System is also able to be controlled with an intuitive, user-friendly and dedicated HMI (Human Machine Interface). In this mode, the user can conform a MMIBS WIFI network, allowing multiple MMIBS operating in parallel to cover complex testing scenarios. The MMIBS device integrates all the aeronautical communication and signaling in a volume of 12x12x12cm and weight of 1200g and provides an autonomy of 5 hours. In this way, our solution combines performance, reliability, low maintenance costs, and ease-of-use to support efficient ground maintenance operations.

Today’s military and commercial aircraft avionics and general systems are built around complex networks of intelligent devices. Maintenance and troubleshooting of these systems often require access to the data bus or networks connecting the system components. Whether it is on the integration test bench, Final Assembly Line (FAL) or at the Maintenance and Repair Organization (MRO), these tasks are usually performed by means of many, expensive, heavy and intrusive equipment. The MMIBS (Mini-Multi Interface Box Simulator) is a very compact, portable, multipurpose, lightweight, low-power, and easy-of-use electronics test means intended to improve digital aircraft ground testing and maintenance troubleshooting. It is capable of perform functional testing and simulating aeronautical equipment through most common aeronautical communication interfaces, such as AFDX, CAN BUS, ARINC 429, MIL-STD-1553, RS-422, RS-232, RS-485, Discrete and Analog I/O and RVDT (Rotary Variable Differential Transformer) reading capabilities. Besides, the system is highly configurable and reprogrammable by means of intuitive Python-based scripting. System is also able to be controlled with an intuitive, user-friendly and dedicated HMI (Human Machine Interface). In this mode, the user can conform a MMIBS WIFI network, allowing multiple MMIBS operating in parallel to cover complex testing scenarios. The MMIBS device integrates all the aeronautical communication and signaling in a volume of 12x12x12cm and weight of 1200g and provides an autonomy of 5 hours. In this way, our solution combines performance, reliability, low maintenance costs, and ease-of-use to support efficient ground maintenance operations.

Today’s military and commercial aircraft avionics and general systems are built around complex networks of intelligent devices. Maintenance and troubleshooting of these systems often require access to the data bus or networks connecting the system components. Whether it is on the integration test bench, Final Assembly Line (FAL) or at the Maintenance and Repair Organization (MRO), these tasks are usually performed by means of many, expensive, heavy and intrusive equipment. The MMIBS (Mini-Multi Interface Box Simulator) is a very compact, portable, multipurpose, lightweight, low-power, and easy-of-use electronics test means intended to improve digital aircraft ground testing and maintenance troubleshooting. It is capable of perform functional testing and simulating aeronautical equipment through most common aeronautical communication interfaces, such as AFDX, CAN BUS, ARINC 429, MIL-STD-1553, RS-422, RS-232, RS-485, Discrete and Analog I/O and RVDT (Rotary Variable Differential Transformer) reading capabilities. Besides, the system is highly configurable and reprogrammable by means of intuitive Python-based scripting. System is also able to be controlled with an intuitive, user-friendly and dedicated HMI (Human Machine Interface). In this mode, the user can conform a MMIBS WIFI network, allowing multiple MMIBS operating in parallel to cover complex testing scenarios. The MMIBS device integrates all the aeronautical communication and signaling in a volume of 12x12x12cm and weight of 1200g and provides an autonomy of 5 hours. In this way, our solution combines performance, reliability, low maintenance costs, and ease-of-use to support efficient ground maintenance operations.

In this work we want to study the average mass density profile of tens to hundreds of clusters of galaxies acting as lenses that produce a magnification bias on the SMGs, and to estimate their associated masses and concentrations for different richness ranges. The background sample is composed of SMGs observed by Herschel with 1.2

Point Source (PS) detection is an important issue for future Cosmic Microwave Background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal at small scales. Improving its multifrequency detection would allow to take into account valuable information otherwise neglected when extracting PS using a channel-by-channel approach. We develop a method based on Neural Networks (NNs) to detect PS in multifrequency realistic simulations and compare its performance against one of the most popular methods, the matrix filters. The frequencies used are 143, 217 and 353 GHz and we impose a Galactic cut of 30 degrees. We produce simulations by adding contaminating signals to the PS maps as the CMB, the Cosmic Infrared Background, the Galactic thermal emission, the thermal Sunyaev-Zel'dovich effect and the instrumental noise. These simulations are used to train two NNs called Flat and Spectral MultiPoSeIDoN. The first one considers PS with a flat spectrum and the second one is more realistic because it takes into account the spectral behavior of the PS. Using a detection limit of 60 mJy, Flat MultiPoSeIDoN reachs the 90% of completeness level at 58 mJy and at 79, 71 and 60 for the spectral case at 143, 217 and 353 GHz respectively, while the matrix filters reach it at 84, 79 and 123 mJy. Using safer 4{\sigma} detection limit does not help to improve these results. In all cases, MultiPoSeIDoN obtain a much lower number of spurious sources than the filter. The NNs recover the flux density of the detections with a relative error of 10% above 100 mJy, while the filter above 150 mJy. Based on the results, NNs are the perfect candidates to substitute filters to detect multifrequency PS in future CMB experiments. Moreover, we have shown that a multifrequency approach can detect sources with higher accuracy than single-frequency approaches also based on NNs., Comment: Forthcoming article Astronomy and Astrophysics since 23 November 2021. Received: 26 July 2021 / Accepted: 05 November 2021

As in Gonzalez-Nuevo et al. 2017 and Bonavera et al. 2019, the high-z sub-millimetre galaxies can be used as background sample for gravitational lensing studies thanks to their magnification bias. In particular, as in Bonavera et al. 2020 the magnification bias can be exploited in order to constrain the free parameters of a Halo Occupation Distribution (HOD) model and some of the main cosmological parameters. In this work the magnification bias has been evaluated as cosmological tool in a tomographic set up. The cross-correlation function (CCF) data have been used to jointly constrain the astrophysical parameters $M_{min}$, $M_{1}$ and $\alpha$ in each one of the selected redshift bins and the $\Omega_{M}$, $\sigma_{8}$, and $H_0$ cosmological ones ($\Lambda$CDM). Moreover, we explore the possible time evolution of the dark energy density introducing also the $\omega_0, \omega_a$ parameters in the joint analysis ($\omega_0$CDM and $\omega_0\omega_a$CDM). The CCF has been measured between a foreground spectroscopic sample of GAMA galaxies that has been divided into four redshift bins (0.1-0.2, 0.2-0.3, 0.3-0.5 and 0.5-0.8) and a sample of H-ATLAS galaxies with photometric redshifts >1.2. The CCF is modelled using a description that depends on HOD and cosmological parameters that are estimated with MCMC in different cases. For the $\Lambda$CDM model, the analysis yields a maximum posterior value at 0.26 with $[0.17,0.41]$ 68\% C.I. for $\Omega_M$ and at 0.87 with $[0.75,1]$ 68\% C.I. for $\sigma_8$. With our current results $H_0$ is not yet constrained. With the $\omega_0$CDM model, the constraints on $\Omega_M$ and $\sigma_8$ are similar, but we found a maximum posterior value for $\omega_0$ at -1 with $[-1.56, -0.47]$ 68\% C.I. In the $\omega_0\omega_a$CDM model, the results are -1.09 with $[-1.72, -0.66]$ 68\% C.I. for $\omega_0$ and -0.19 with $[-1.88, 1.48]$ 68\% C.I. for $\omega_a$., Comment: accepted A&A

Water scarcity and water quality degradation are major problems in many basins across the world, especially in arid and semiarid regions. The severe pressures on basins are the consequence of the intensification of food production systems and the unrelenting growth of population and income. Agriculture is a major factor in the depletion and degradation of water resources, and contributes to the emissions of greenhouse gases (GHG). Our study analyzes water allocation and agricultural pollution into watercourses and the atmosphere, with the purpose of identifying cost-effective policies for sustainable water management in the Ebro River Basin (Spain). The study develops an hydroeconomic model that integrates hydrological, economic and water quality aspects, capturing the main spatial and sectoral interactions in the basin. The model is used to analyze water scarcity and agricultural pollution under normal and droughts conditions, providing information for evaluating mitigation and adaptation policies. Results indicate that drought events increase nitrate concentration by up to 63% and decrease water availability by 42% at the mouth of Ebro River, highlighting the tradeoffs between water quantity and quality. All mitigation and adaptation policies reduce the effects of climate change, improving water quality and reducing GHGs’ emissions, thus lowering environmental damages and enhancing social well-being. Manure fertilization and optimizing the use of synthetic fertilizers are important cost-effective policies increasing social benefits in a range between 50 and 160 million Euros. Results show that irrigation modernization increases the efficient use of nitrogen and water, augmenting social benefits by up to 90 million Euros, and enlarging stream flows at the river mouth. In contrast, manure treatment plants reduce private and social benefits even though they achieve the lowest nitrate concentrations. Our study provides insights on the synergies and tradeoffs between e

Water scarcity and water quality degradation are major problems in many basins across the world, especially in arid and semiarid regions. The severe pressures on basins are the consequence of the intensification of food production systems and the unrelenting growth of population and income. Agriculture is a major factor in the depletion and degradation of water resources, and contributes to the emissions of greenhouse gases (GHG). Our study analyzes water allocation and agricultural pollution into watercourses and the atmosphere, with the purpose of identifying cost-effective policies for sustainable water management in the Ebro River Basin (Spain). The study develops an hydroeconomic model that integrates hydrological, economic and water quality aspects, capturing the main spatial and sectoral interactions in the basin. The model is used to analyze water scarcity and agricultural pollution under normal and droughts conditions, providing information for evaluating mitigation and adaptation policies. Results indicate that drought events increase nitrate concentration by up to 63% and decrease water availability by 42% at the mouth of Ebro River, highlighting the tradeoffs between water quantity and quality. All mitigation and adaptation policies reduce the effects of climate change, improving water quality and reducing GHGs’ emissions, thus lowering environmental damages and enhancing social well-being. Manure fertilization and optimizing the use of synthetic fertilizers are important cost-effective policies increasing social benefits in a range between 50 and 160 million Euros. Results show that irrigation modernization increases the efficient use of nitrogen and water, augmenting social benefits by up to 90 million Euros, and enlarging stream flows at the river mouth. In contrast, manure treatment plants reduce private and social benefits even though they achieve the lowest nitrate concentrations. Our study provides insights on the synergies and tradeoffs between e

Water scarcity and water quality degradation are major problems in many basins across the world, especially in arid and semiarid regions. The severe pressures on basins are the consequence of the intensification of food production systems and the unrelenting growth of population and income. Agriculture is a major factor in the depletion and degradation of water resources, and contributes to the emissions of greenhouse gases (GHG). Our study analyzes water allocation and agricultural pollution into watercourses and the atmosphere, with the purpose of identifying cost-effective policies for sustainable water management in the Ebro River Basin (Spain). The study develops an hydroeconomic model that integrates hydrological, economic and water quality aspects, capturing the main spatial and sectoral interactions in the basin. The model is used to analyze water scarcity and agricultural pollution under normal and droughts conditions, providing information for evaluating mitigation and adaptation policies. Results indicate that drought events increase nitrate concentration by up to 63% and decrease water availability by 42% at the mouth of Ebro River, highlighting the tradeoffs between water quantity and quality. All mitigation and adaptation policies reduce the effects of climate change, improving water quality and reducing GHGs’ emissions, thus lowering environmental damages and enhancing social well-being. Manure fertilization and optimizing the use of synthetic fertilizers are important cost-effective policies increasing social benefits in a range between 50 and 160 million Euros. Results show that irrigation modernization increases the efficient use of nitrogen and water, augmenting social benefits by up to 90 million Euros, and enlarging stream flows at the river mouth. In contrast, manure treatment plants reduce private and social benefits even though they achieve the lowest nitrate concentrations. Our study provides insights on the synergies and tradeoffs between e

Detrimental corrosion is an ever-concerning challenge for metals and alloys. One possible remedy is to apply organic corrosion inhibitors. Despite progress in molecular assembly and inhibitor research, better mechanistic insight on the molecular level is needed. Here we report on the behavior of well-defined artificial molecular interfaces created by micro-contact printing of thiol-inhibitor molecules and subsequent backfilling. The obtained heterogeneity and defects trigger localized dealloying-corrosion of well-defined Cu3Au surfaces. The stability of applied inhibitor molecules depends on alloy surface morphology and on intermolecular forces of the molecular layers. On extended terraces, dealloying preferentially starts at the boundary between areas composed of the two different chain-length inhibitor molecules. Inside of the areas hardly any nucleation of initial pits is visible. Step density strongly influences the morphology of the dealloying attack, while film heterogeneity avoids cracking and controls molecular-scale corrosion attack. The presented surface-science approach, moreover, will ultimately allow to verify the acting mechanisms of inhibitor-cocktails to develop recipes to stabilize metallic alloy surfaces., SCOPUS: ar.j, info:eu-repo/semantics/published

The often used simplistic correlations between molecular electronic parameters and experimentally determined corrosion inhibition efficiencies are critically evaluated for a set of 24 heterocyclic organic compounds, tested as corrosion inhibitors for copper in 3 wt.% NaCl aqueous solution. Twelve different molecular electronic descriptors—such as ionization potential, electron affinity, HOMO–LUMO gap, dipole moment—are tested and it is shown that none of them displays any noticeable correlation with the inhibition efficiency. Our results, therefore, cast serious doubt on reported correlations between such parameters and inhibition efficiency, obtained for only a few inhibitors, which are abundant in the literature. We also discuss some pros and cons of inhibition efficiency as a metric for evaluating the performance of corrosion inhibitors, and introduce a new metric termed inhibition power that uses the universal logarithmic scale and dimensionless decibel (dB) units., info:eu-repo/semantics/published

The initiation of corrosion can be triggered by defects in the adsorbed layer of organic inhibitors. A detailed knowledge of the intermolecular forces between the inhibitor molecules and the interfacial bonding will be decisive to unravel the mechanisms driving the corrosion initiation. In this work, adsorbed organic layers of 2-mercapto-5-methoxybenzimidazole (SH-BimH-5OMe) and 5-amino-2-mercaptobenzimidazole (SH-BimH-5NH2) were compared regarding their performance mitigating copper corrosion. Atomic force microscopy was used to address the stability and intermolecular forces of the self-assembled monolayers, using imaging and force measurement modes. For a film formed by amino-derivative molecules, a gold-coated tip frequently picked up individual molecules (molecular fishing) in force-distance measurements. For layers of the methoxy-derivative, no fishing events were observed, pointing to a constant functional layer. X-ray photoelectron spectroscopy revealed that SH-BimH-5OMe molecules form a stronger bond with the surface and more stable SAM layers on Cu surfaces as compared to SH-BimH-5NH2 molecules. Results of computational density functional theory modeling and electrochemical corrosion tests are in line with the microscopy and spectroscopy results. In particular, with aid of computational modeling the less ordered structure of the SH-BimH-5NH2 monolayer is attributed to dual bonding ability of SH-BimH-5NH2 that can adsorb with either S or NH2 groups., SCOPUS: ar.j, info:eu-repo/semantics/published

Neglected Tropical Diseases (NTD) represent a serious threat to humans, especially for those living in poor or developing countries. Almost one-sixth of the world population is at risk of suffering from these diseases and many thousands die because of NTDs, to which we should add the sanitary, labor and social issues that hinder the economic development of these countries. Protozoan-borne diseases are responsible for more than one million deaths every year. Visceral leishmaniasis, Chagas disease or sleeping sickness are among the most lethal NTDs. Despite not being considered an NTD by the World Health Organization (WHO), malaria must be added to this sinister group. Malaria, caused by the apicomplexan parasite Plasmodium falciparum, is responsible for thousands of deaths each year. The treatment of this disease has been losing effectiveness year after year. Many of the medicines currently in use are obsolete due to their gradual loss of efficacy, their intrinsic toxicity and the emergence of drug resistance or a lack of adherence to treatment. Therefore, there is an urgent and global need for new drugs. Despite this, the scant interest shown by most of the stakeholders involved in the pharmaceutical industry makes our present therapeutic arsenal scarce, and until recently, the search for new drugs has not been seriously addressed. The sources of new drugs for these and other pathologies include natural products, synthetic molecules or repurposing drugs. The most frequent sources of natural products are microorganisms, e.g., bacteria, fungi, yeasts, algae and plants, which are able to synthesize many drugs that are currently in use (e.g. antimicrobials, antitumor, immunosuppressants, etc.). The marine environment is another well-established source of bioactive natural products, with recent applications against parasites, bacteria and other pathogens which affect humans and animals. Drug discovery techniques have rapidly advanced since the beginning of the millennium

Helminthiasis is one of the gravest problems worldwide. There is a growing concern on less available anthelmintics and the emergence of resistance creating a major threat to human and livestock health resources. Novel and broad-spectrum anthelmintics are urgently needed. The free-living nematode Caenorhabditis elegans could address this issue through automated high-throughput technologies for the screening of large chemical libraries. This review discusses the strong advantages and limitations for using C elegans as a screening method for anthelmintic drug discovery. C elegans is the best model available for the validation of novel effective drugs in treating most, if not all, helminth infections, and for the elucidation the mode of action of anthelmintic candidates. This review also focuses on available technologies in the discovery of anthelmintics published over the last 15 years with particular attention to high-throughput technologies over conventional screens. On the other hand, this review highlights how combinatorial and nanomedicine strategies could prolong the use of anthelmintics and control resistance problems.

The work analyses the atmospheric corrosion resistance of two widely used weathering steels: ASTM A-242 and ASTM A-588. The steels were exposed for up to 5 years in different types of atmosphere: rural, urban, industrial and marine. The atmospheric corrosion resistance of the steels was evaluated and the rust layers formed on them were characterised by X-ray diffraction, optical microscopy and scanning electron microscopy. The most relevant conclusions reached include the following: (a) the visual appearance (colouring) of the rust, rust texture, nature of the corrosion products and compactness of the rust layers formed are similar in both types of weathering steel. (b) No great differences are observed in the corrosion resistance. Slight differences occur in the industrial atmosphere, where ASTM A-242 presents 10–13% less corrosion than ASTM A-588. (c) In the C2-C3 ISO corrosivity atmosphere both types of weathering steels are adequate for unpainted use. However are not suitable in higher ISO corrosivity atmosphere.

Background: Our understanding of the molecular mechanisms implementing pubertal maturation of the testis in vertebrates is incomplete. This topic is relevant in Atlantic salmon aquaculture, since precocious male puberty negatively impacts animal welfare and growth. We hypothesize that certain miRNAs modulate mRNAs relevant for the initiation of puberty. To explore which miRNAs regulate mRNAs during initiation of puberty in salmon, we performed an integrated transcriptome analysis (miRNA and mRNA-seq) of salmon testis at three stages of development: an immature, long-term quiescent stage, a prepubertal stage just before, and a pubertal stage just after the onset of single cell proliferation activity in the testis. Results: Differentially expressed miRNAs clustered into 5 distinct expression profiles related to the immature, prepubertal and pubertal salmon testis. Potential mRNA targets of these miRNAs were predicted with miRmap and filtered for mRNAs displaying negatively correlated expression patterns. In summary, this analysis revealed miRNAs previously known to be regulated in immature vertebrate testis (miR-101, miR-137, miR-92b, miR-18a, miR-20a), but also miRNAs first reported here as regulated in the testis (miR-new289, miR-30c, miR-724, miR-26b, miR-new271, miR-217, miR-216a, miR-135a, miR-new194 and the novel predicted n268). By KEGG enrichment analysis, progesterone signaling and cell cycle pathway genes were found regulated by these differentially expressed miRNAs. During the transition into puberty we found differential expression of miRNAs previously associated (let7a/b/c), or newly associated (miR-15c, miR-2184, miR-145 and the novel predicted n7a and b) with this stage. KEGG enrichment analysis revealed that mRNAs of the Wnt, Hedgehog and Apelin signaling pathways were potential regulated targets during the transition into puberty. Likewise, several regulated miRNAs in the pubertal stage had earlier been associated (miR-20a, miR-25, miR-181a, miR-202

Fsh-mediated regulation of zebrafish spermatogenesis includes modulating the expression of testicular growth factors. Here, we study if and how two Sertoli cell-derived Fsh-responsive growth factors, anti-Müllerian hormone (Amh; inhibiting steroidogenesis and germ cell differentiation) and insulin-like growth factor 3 (Igf3; stimulating germ cell differentiation), cooperate in regulating spermatogonial development. In dose response and time course experiments with primary testis tissue cultures, Fsh up-regulated igf3 transcript levels and down-regulated amh transcript levels; igf3 transcript levels were more rapidly up-regulated and responded to lower Fsh concentrations than were required to decrease amh mRNA levels. Quantification of immunoreactive Amh and Igf3 on testis sections showed that Fsh increased slightly Igf3 staining but decreased clearly Amh staining. Studying the direct interaction of the two growth factors showed that Amh compromised Igf3-stimulated proliferation of type A (both undifferentiated [Aund] and differentiating [Adiff]) spermatogonia. Also the proliferation of those Sertoli cells associated with Aund spermatogonia was reduced by Amh. To gain more insight into how Amh inhibits germ cell development, we examined Amh-induced changes in testicular gene expression by RNA sequencing. The majority (69%) of the differentially expressed genes was down-regulated by Amh, including several stimulators of spermatogenesis, such as igf3 and steroidogenesis-related genes. At the same time, Amh increased the expression of inhibitory signals, such as inha and id3, or facilitated prostaglandin E2 (PGE2) signaling. Evaluating one of the potentially inhibitory signals, we indeed found in tissue culture experiments that PGE2 promoted the accumulation of Aund at the expense of Adiff and B spermatogonia. Our data suggest that an important aspect of Fsh bioactivity in stimulating spermatogenesis is implemented by restricting the different inhibitory effects of A