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Abstract Aim The present study was performed to characterize and compare the perfusion of vaginal and uterine arteries after challenging the reproductive tract of dairy cows via natural mating, artificial insemination (AI), or intravaginal deposition (vaginal fundus) of different biological fluids or a placebo. Materials and methods In a double-blind study, six German Holstein cows were administered PGF2α during dioestrus and 48 h later treated with GnRH. Intravaginal or intrauterine treatments were carried out 12 h after GnRH was administered. Animals served as their controls, using a cross-over design with an interval of 14 days between experiments. The experimental animals were allocated to receive the following treatments: natural mating (N), intrauterine artificial insemination (A), intravaginal deposition (vaginal fundus) of 6 mL raw semen (R) or 6 mL seminal plasma (S), and compared to their controls [control 1: 6 mL placebo (P: physiological saline); control 2: no treatment (C)). Corresponding time intervals were chosen for the untreated control oestrus. Blood flow volume (BFV) in the uterine (u) and vaginal (v) arteries ipsilateral to the ovary bearing the preovulatory follicle was determined using transrectal Doppler sonography. Results All animals exhibited oestrus and ovulated between 30 and 36 h after GnRH. Transient increases (P 0.05). Only mating and deposition of either raw semen, seminal plasma or AI increased uBFV (P

Clearing and construction activities related to the Maya Train (Tren Maya) project resulted in potential and inevitable impacts to archaeological caves sites in largely undeveloped areas of Quintana Roo. An effort coordinated by Mexico’s National Institute of Anthropology and History (INAH) involved accelerated digital documentation of two caves – via SLAM-enabled mobile LiDAR scanning and targeted photogrammetry – to facilitate prompt visualization and evaluation of terrestrial and subterranean geospatial relationships. Mobile LiDAR is well suited to the challenges of capturing the complex, multilevel morphology of caves and was readily deployed across and through priority environments. Specific archaeological features – such as ancient Maya rock art and masonry shrines – were documented via photogrammetry, and the resulting higher-resolution models co-referenced with the georeferenced mobile LiDAR-generated point clouds of each cave and the surrounding topographic context. This integrative approach contributed to a more informed decision-making process, with respect to conservation and construction, and provided baseline data for future monitoring of the affected cave sites.

Abstract Working forests comprise a large proportion of forested landscapes in the southeastern United States and are important to the conservation of bats, which rely on forests for roosting and foraging. While relationships between bat ecology and forest management are well studied during summer, winter bat ecology remains understudied. Hence, we aimed to identify the diet composition of overwintering bats, compare the composition of prey consumed by bat species, and determine the potential role of forest bats as pest controllers in working forest landscapes of the southeastern U.S. Coastal Plain. During January to March 2021–2022, we captured 264 bats of eight species. We used DNA metabarcoding to obtain diet composition from 126 individuals of seven bat species identifying 22 orders and 174 families of arthropod prey. Although Coleoptera, Diptera, and Lepidoptera were the most consumed orders, we found that bats had a generalist diet but with significant differences among some species. We also documented the consumption of multiple insect pests (e.g., Rhyacionia frustrana) and disease vectors (e.g., Culex spp). Our results provide important information regarding the winter diet of bats in the southeastern U.S. Coastal Plain and their potential role in controlling economically relevant pest species and disease vectors.

Abstract Detecting entanglement in multipartite quantum states is an inherently probabilistic process, typically with a few measured samples. The level of confidence in entanglement detection quantifies the scheme’s validity via the probability that the signal comes from a separable state, offering a meaningful figure of merit for big datasets. Yet, with limited samples, avoiding experimental data misinterpretations requires considering not only the probabilities concerning separable states but also the probability that the signal came from an entangled state, i.e. the detection scheme’s efficiency. We demonstrate this explicitly and apply a general method to optimize both the validity and the efficiency in small data sets providing examples using at most 20 state copies. The method is based on an analytical model of finite statistics effects on correlation functions which takes into account both a Frequentist as well as a Bayesian approach and is applicable to arbitrary entanglement witnesses.

In this study, a method for depositing and patterning the thermosensitive polymer poly(N-isopropylacrylamide) on SiO2 surfaces is presented for potential use in nano-sized microfluidic channels. Two approaches based on nanolithographic processes are shown for this purpose. In both cases, a self-assembling monolayer consisting of (3-aminopropyl)-dimethylethoxysilane was bound to the hydroxyl group of the substrate surface and subsequently functionalized with the polymerization initiator α-bromoisobutyryl bromide. In the first approach the silane monolayer itself was patterned using a photoresist and a lift-off process, followed by the selective deposition of the initiator, which starts a substrate-induced atom transfer radical polymerization for the growth of polymer on the silane monolayer. In the second approach, the lift-off takes place after the polymerization on the substrate surface. The result of this study shows the successful application of the process steps for the nano-dimensioned grafting of poly(N-isopropylacrylamide) onto SiO2 substrates. The reaction time of the silane monolayer with the polymerization initiator and the composition of the reaction solution used were found to have the greatest influence of the processes. AFM and XPS analysis of the functionalized surfaces revealed patterned growth of both the self-assembling monolayer and the polymer structures.

O artigo apresenta o desenvolvimento e a análise de resultados do projeto Macunaíma, caso aplicado de IA utilizada para a criação de roteiros e de storyboards, que une narrativa, áudio e imagens geradas automaticamente. Tecnicamente, foram utilizados modelos de IA para geração de texto (ChatGPT) e imagem (Stable Diffusion), com uma interface web que permite a interação do usuário. As dimensões de Coesão Temporal da Narrativa, Coesão Cinematográfica da cena e Coesão Gráfica foram verificadas, assim como foi criado um protótipo de visualização de dados para identificar as narrativas geradas e direções de aprimoramentos da ferramenta. Apontamos o uso de visualização de dados como crucial na análise destes modelos complexos, em especial pela quantidade de informação envolvida.

Decomposing complex unitary evolution into a series of constituent components is a cornerstone of practical quantum information processing. While the decomposition of an n×n unitary into a product of 2×2 subunitaries (which can for example be realized by beam splitters and phase shifters in linear optics) is well established, we show how for any m>2 this decomposition can be generalized into a product of m×m subunitaries (which can then be realized by a more complex device acting on m modes). If the cost associated with building each m×m multimode device is less than constructing with m(m−1)/2 individual 2×2 devices, we show that the decomposition of large unitaries into m×m submatrices is more resource efficient and exhibits a higher tolerance to errors, than its 2×2 counterpart. This allows larger-scale unitaries to be constructed with lower errors, which is necessary for various tasks, not least boson sampling, the quantum Fourier transform, and quantum simulations.