Valuations and plurisubharmonic singularities

We extend to higher dimensions some of the valuative analysis of singularities of plurisubharmonic (psh) functions developed by the last two authors. Following Kontsevich and Soibelman we describe the geometry of the space V of all normalized valuations on C[x_1,...,x_n] centered at the origin. It is a union of simplices naturally endowed with an affine structure. Using relative positivity properties of divisors living on modifications of C^n above the origin, we define formal psh functions on V, designed to be analogues of the usual psh functions. For bounded formal psh functions on V, we define a mixed Monge-Ampere operator which reflects the intersection theory of divisors above the origin of C^n. This operator associates to any (n-1)-tuple of formal psh functions a positive measure of finite mass on V. Next, we show that the collection of Lelong numbers of a given germ u of a psh function at all infinitely near points induces a formal psh function u' on V called its valuative transform. When \phi is a psh Holder weight in the sense of Demailly, the generalized Lelong number nu_\phi(u) equals the integral of u' against the Monge-Ampere measure of the valuative transform of \phi. In particular, any generalized Lelong number is an average of valuations. We also show how to compute the multiplier ideal of u and the relative type of u with respect to \phi in the sense of Rashkovskii, in terms of the valuative transforms of u and \phi.Comment: 37 pages, new version. Changed the terminology from convex fonctions to formal psh functions. Corrected statement about the continuity of formal psh functions. Added a proof of the continuity of psh envelopes (theorem 5.13). Clarified the exposition (removed a section on the action of finite maps on formal psh functions). Added new reference

The volume of an isolated singularity

We introduce a notion of volume of a normal isolated singularity that generalizes Wahl's characteristic number of surface singularities to arbitrary dimensions. We prove a basic monotonicity property of this volume under finite morphisms. We draw several consequences regarding the existence of non-invertible finite endomorphisms fixing an isolated singularity. Using a cone construction, we deduce that the anticanonical divisor of any smooth projective variety carrying a non-invertible polarized endomorphism is pseudoeffective. Our techniques build on Shokurov's b-divisors. We define the notion of nef Weil b-divisors, and of nef envelopes of b-divisors. We relate the latter to the pull-back of Weil divisors introduced by de Fernex and Hacon. Using the subadditivity theorem for multiplier ideals with respect to pairs recently obtained by Takagi, we carry over to the isolated singularity case the intersection theory of nef Weil b-divisors formerly developed by Boucksom, Favre, and Jonsson in the smooth case.Comment: 48 pages. v4: Appendix is new, plus several minor changes made throughout the paper following the referee's suggestions. Final version, to appear in Duke Math

Energy autonomous wireless sensing node working at 5 Lux from a 4 cm2 solar cell

Harvesting energy for IoT nodes in places that are permanently poorly lit is important, as many such places exist in buildings and other locations. The need for energy-autonomous devices working in such environments has so far received little attention. This work reports the design and test results of an energy-autonomous sensor node powered solely by solar cells. The system can cold-start and run in low light conditions (in this case 20 lux and below, using white LEDs as light sources). Four solar cells of 1 cm2 each are used, yielding a total active surface of 4 cm2. The system includes a capacitive sensor that acts as a touch detector, a crystal-accurate real-time clock (RTC), and a Cortex-M3-compatible microcontroller integrating a Bluetooth Low Energy radio (BLE) and the necessary stack for communication. A capacitor of 100 μF is used as energy storage. A low-power comparator monitors the level of the energy storage and powers up the system. The combination of the RTC and touch sensor enables the MCU load to be powered up periodically or using an asynchronous user touch activity. First tests have shown that the system can perform the basic work of cold-starting, sensing, and transmitting frames at +0 dBm, at illuminances as low as 5 lux. Harvesting starts earlier, meaning that the potential for full function below 5 lux is present. The system has also been tested with other light sources. The comparator is a test chip developed for energy harvesting. Other elements are off-the-shelf components. The use of commercially available devices, the reduced number of parts, and the absence of complex storage elements enable a small node to be built in the future, for use in constantly or intermittently poorly lit places

Host Cell Egress and Invasion Induce Marked Relocations of Glycolytic Enzymes in Toxoplasma gondii Tachyzoites

Apicomplexan parasites are dependent on an F-actin and myosin-based motility system for their invasion into and escape from animal host cells, as well as for their general motility. In Toxoplasma gondii and Plasmodium species, the actin filaments and myosin motor required for this process are located in a narrow space between the parasite plasma membrane and the underlying inner membrane complex, a set of flattened cisternae that covers most the cytoplasmic face of the plasma membrane. Here we show that the energy required for Toxoplasma motility is derived mostly, if not entirely, from glycolysis and lactic acid production. We also demonstrate that the glycolytic enzymes of Toxoplasma tachyzoites undergo a striking relocation from the parasites' cytoplasm to their pellicles upon Toxoplasma egress from host cells. Specifically, it appears that the glycolytic enzymes are translocated to the cytoplasmic face of the inner membrane complex as well as to the space between the plasma membrane and inner membrane complex. The glycolytic enzymes remain pellicle-associated during extended incubations of parasites in the extracellular milieu and do not revert to a cytoplasmic location until well after parasites have completed invasion of new host cells. Translocation of glycolytic enzymes to and from the Toxoplasma pellicle appears to occur in response to changes in extracellular [K+] experienced during egress and invasion, a signal that requires changes of [Ca2+]c in the parasite during egress. Enzyme translocation is, however, not dependent on either F-actin or intact microtubules. Our observations indicate that Toxoplasma gondii is capable of relocating its main source of energy between its cytoplasm and pellicle in response to exit from or entry into host cells. We propose that this ability allows Toxoplasma to optimize ATP delivery to those cellular processes that are most critical for survival outside host cells and those required for growth and replication of intracellular parasites

Harvesting energy in low light environments to power embedded systems

Design and test results of a LoRaWAN node powered with a small solar cell (8 sq. cm) down to 15 lux are presented. Various preading factors can be used (SF7 up to SF12)

REVERSION DE LA RESISTANCE DE PLASMODIUM FALCIPARUM PAR LES FLAVONOIDES(DES BIOL. MED.)

LYON1-BU Santé (693882101) / SudocSudocFranceF

Fusion d'espaces de représentations multimodaux pour la reconnaissance du rôle du locuteur dans des documents télévisuels

International audiencePerson role recognition in video broadcasts consists in classifying people into roles such as anchor, journalist, guest, etc. Existing approaches mostly consider one modality, either audio (speaker role recognition) or image (shot role recognition), firstly because of the non-synchrony between both modalities, and secondly because of the lack of a video corpus annotated in both modalities. Deep Neural Networks (DNN) approaches offer the ability to learn simultaneously feature representations (embeddings) and classification functions. This paper presents a multimodal fusion of audio, text and image embeddings spaces for speaker role recognition in asynchronous data. Monomodal embeddings are trained on exogenous data and fine-tuned using a DNN on 70 hours of French Broadcasts corpus for the target task. Experiments on the REPERE corpus show the benefit of the embeddings level fusion compared to the monomodal embeddings systems and to the standard late fusion method.L'identification du rôle d'un locuteur dans des émissions de télévision est un problème de classification de personne selon une liste de rôles comme présentateur, journaliste, invité, etc. À cause de la non-synchronie entre les modalités, ainsi que par le manque de corpus de vidéos annotées dans toutes les modalités, seulement une des modalités est souvent utilisée. Nous présentons dans cet article une fusion multimodale des espaces de représentations de l'audio, du texte et de l'image pour la reconnaissance du rôle du locuteur pour des données asynchrones. Les espaces de représentations monomodaux sont entraînés sur des corpus de données exogènes puis ajustés en utilisant des réseaux de neurones profonds sur un corpus d'émissions françaises pour notre tâche de classification. Les expériences réalisées sur le corpus de données REPERE ont mis en évidence les gains d'une fusion au niveau des espaces de représentations par rapport aux méthodes de fusion tardive standard. ABSTRACT Multimodal embedding fusion for robust speaker role recognition in video broadcast Person role recognition in video broadcasts consists in classifying people into roles such as anchor, journalist, guest, etc. Existing approaches mostly consider one modality, either audio (speaker role recognition) or image (shot role recognition), firstly because of the non-synchrony between both modalities, and secondly because of the lack of a video corpus annotated in both modalities. Deep Neural Networks (DNN) approaches offer the ability to learn simultaneously feature representations (embeddings) and classification functions. This paper presents a multimodal fusion of audio, text and image embeddings spaces for speaker role recognition in asynchronous data. Monomodal embeddings are trained on exogenous data and fine-tuned using a DNN on 70 hours of French Broadcasts corpus for the target task. Experiments on the REPERE corpus show the benefit of the embeddings level fusion compared to the monomodal embeddings systems and to the standard late fusion method. MOTS-CLÉS : Identification du rôle du locuteur, fusion multimodale, émissions de télévision