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The interfacial topography of biomaterials has been identified as a major biophysical regulator of cell behavior and function, a role played through the interplay with biochemical cues. In this work, we demonstrate the potential of laser as a versatile technology for the direct fine-tuning of the topography of Bacterial nanocellulose (BNC) with bioinspired topographies and micropatterns on a cell size scale. Two lasers were used, with different wavelengths—IR (CO2, 10600 nm) and UV (tripled Nd: YVO4, 355 nm) —attempting to reproduce the Pitcher-plant topography and to create cell-contact guidance patterns, respectively. Different topographies with parallel grooves featuring a 20–300 μm period were generated on the BNC surface with high fidelity and reliability of the generated microstructures, as demonstrated by 3D optical profilometry and scanning electron microscopy. Moreover, it was demonstrated by X-ray photoelectron spectroscopy that laser processing does not result in detectable chemical modification of BNC. The developed anisotropic microstructures can control cell behavior, particularly regarding morphology, alignment, and spatial distribution. Thus, this proof-of-concept study on the high-resolution laser patterning of BNC opens new perspectives for the development of cell-modulating laser-engineered BNC interfaces, scaffolds, and other advanced medical devices, which can potentially broaden the application of BNC in the biomedical field.

Cobalt-cemented carbide micro-end mills were coated with diamond grown by chemical vapor deposition (CVD), with the purpose of micro-machining cemented carbides. The diamond coatings were designed with a multilayer architecture, alternating between sub-microcrystalline and nanocrystalline diamond layers. The structure of the coatings was studied by transmission electron microscopy. High adhesion to the chemically pre-treated WC-7Co tool substrates was observed by Rockwell C indentation, with the diamond coatings withstanding a critical load of 1250 N. The coated tools were tested for micro-end-milling of WC-15Co under air-cooling conditions, being able to cut more than 6500 m over a period of 120 min, after which a flank wear of 47.8 μm was attained. The machining performance and wear behavior of the micro-cutters was studied by scanning electron microscopy and energy-dispersive X-ray spectroscopy. Crystallographic analysis through cross-sectional selected area electron diffraction patterns, along with characterization in dark-field and HRTEM modes, provided a possible correlation between interfacial stress relaxation and wear properties of the coatings. Overall, this work demonstrates that high adhesion of diamond coatings can be achieved by proper combination of chemical attack and coating architecture. By preventing catastrophic delamination, multilayer CVD diamond coatings are central towards the enhancement of the wear properties and mechanical robustness of carbide tools used for micro-machining of ultra-hard materials.

Among the unique opportunities and developments that are currently being triggered by the fourth industrial revolution, developments in cutting tools have been following the trend of an ever more holistic control of manufacturing processes. Sustainable manufacturing is at the forefront of tools development, encompassing environmental, economic, and technological goals. The integrated use of sensors, data processing, and smart algorithms for fast optimization or real time adjustment of cutting processes can lead to a significant impact on productivity and energy uptake, as well as less usage of cutting fluids. Diamond is the material of choice for machining of non-ferrous alloys, composites, and ultrahard materials. While the extreme hardness, thermal conductivity, and wear resistance of CVD diamond coatings are well-known, these also exhibit highly auspicious sensing properties through doping with boron and other elements. The present study focuses on the thermal response of boron-doped diamond (BDD) coatings. BDD coatings have been shown to have a negative temperature coefficient (NTC). Several approaches have been adopted for monitoring cutting temperature, including thin film thermocouples and infrared thermography. Although these are good solutions, they can be costly and become impractical for certain finishing cutting operations, tool geometries such as rotary tools, as well as during material removal in intricate spaces. In the scope of this study, diamond/WC-Co substrates were coated with BDD by hot filament chemical vapor deposition (HFCVD). Scanning electron microscopy, Raman spectroscopy, and the van der Pauw method were used for morphological, structural, and electrical characterization, respectively. The thermal response of the thin diamond thermistors was characterized in the temperature interval of 20–400 °C. Compared to state-of-the-art temperature monitoring solutions, this is a one-step approach that improves the wear properties and heat dissipation of carbide tools while providing real-time and in-situ temperature monitoring.

Habitat fragmentation caused by hydroelectric dams has depleted fish populations worldwide. Restocking actions are usually adopted to recover those populations, but hatchery management protocols rarely guarantee the maintenance of genetic diversity and a balanced contribution among captive breeders each generation. Here, a set of 10 microsatellite markers was used to assess the genetic diversity (average allelic richness AR = 10.87 and expected heterozygosity HE = 0.742, respectively) and structuring of Megaleporinus obtusidens, a migratory freshwater fish inhabiting over 2500 km of the São Francisco River in Brazil. Three main genetic clusters were identified in this species across the river basin that could be related to the sharply different climatic and hydrologic regimes from the Upper to the Lower course. A significant reduction (> 50%) in genetic diversity was observed in the broodstock when compared to their wild conspecifics, especially in the allelic richness. The information here presented will aid for management of genetic resources of this species in the São Francisco River taking as reference the genetic clusters identified. Furthermore, the results indicated that restocking is not necessary unless signals of population depletion occurs and, if so, hatchery reproductive protocols should rely on artificial fertilization rather than mass spawning.

Two-dimensional axial and manually-oriented reformatted images are traditionally used to analyze coronary data provided by multidetector-row computed tomography angiography (MDCTA). While apparently more accurate in evaluating calcified vessels, 2D methods are time-consuming compared with automated 3D approaches. The purpose of this study was to evaluate the performance of a modified automated 3D approach (using manual vessel isolation and different window and level settings) in a population with high calcium scores who underwent coronary half-millimeter 16-detector-row CT angiography (16 x 0.5-MDCTA). ECG-gated 16 x 0.5-MDCTA (16 x 0.5 mm cross-sections, 0.35 x 0.35 x 0.35 mm3 isotropic voxels, 400 ms rotation) was performed after injection of iopamidol (120-ml, 300 mg/ml) in 19 consecutive patients (11 male, 62+/-10 years-old). Native arteries were independently evaluated for >or=50%-stenoses using both manual 2D and modified automated 3D approaches. Stents and bypass grafts were excluded. Conventional coronary angiography was visually analyzed by 2 observers. Median Agatston calcium score was 434. Sensitivities, specificities, positive and negative predictive values for detection of >or=50% coronary stenoses using the 2D and modified 3D approaches were, respectively: 74%/63%, 76%/80%, 45%/34%, and 91%/93% (p=NS for all comparisons). Overall diagnostic accuracies were 75 and 78%, respectively (p=NS). Uninterpretable vessels were, respectively: 37% (77/209) and 35% (73/209) - p=NS. Time to analyze a single study was 160+/-23 and 53+/-11 min, respectively (p<0.01). This modified automated 3D approach is equivalent to and significantly less time consuming than the traditional manual 2D method for evaluation of >or=50%-stenoses by 16 x 0.5-MDCTA in native coronary arteries of patients with high calcium scores.

The study carried out describes some specific forms of scientific communication in the fields of family therapy and family psychology. It includes as primary source of data three journals (Family Process, Journal of Family Psychology and Therapie Familiale) and two electronic lists: (1) a family studies list titled FAMLYSCI, and (2) the American Marriage and Family Therapy Association's electronic list (MFTNET). The scientific communication processes analyzed included the study of forms of scientific collaboration, gender distribution of authors and the study of the development of controversial (i.e. polemical or non-consensus) research questions. The methods used included: (a) a bibliometric and citation analysis study carried out in order to characterized each journal profile and role; (b) a network analysis carried out in order to identify the most prominent research subjects and teams in each field; (c) a controversies analysis carried out with the goal of identifying the type of polemical issues selected by journal editors and the gender distribution of controversies participants. Within the frame of the mentioned methods a set of dimensions and variables and dimensions were selected accordingly to the above stated goals. Concerning the bibliometric and citational approach the variables selected were: number of articles published, average number of references per article, number and gender of first authors and co-authors, country of professional address of first authors, institutions where the research took place, key words used in the title of the articles, patterns of acknowledgment and grants and awards. The network analysis associated the research questions implied by the articles titles with the most prolific research teams in each field. Finally, the controversies analysis identified the controversies subject, the type of controversy and the participants gender. An adjunctive frame of analysis included the examination of the two mentioned electronic lists, specifying gender of participants, institutions of electronic addresses and countries involved. The results obtained point to a set of specific features of the emergence and consolidation processes of family therapy and family psychology. The analysis of the journal Therapie Familiale also demonstrates specific attributes of the dissemination of scientific information in the French speaking community of family therapists and researchers.

Skin pigmentation ensures efficient photoprotection and relies on the pigment melanin, which is produced by epidermal melanocytes and transferred to surrounding keratinocytes. While the molecular mechanisms of melanin synthesis and transport in melanocytes are now well characterized, much less is known about melanin transfer and processing within keratinocytes. Over the past few decades, distinct models have been proposed to explain how melanin transfer occurs at the cellular and molecular levels. However, this remains a debated topic, as up to four different models have been proposed, with evidence presented supporting each. Here, we review the current knowledge on the regulation of melanin exocytosis, internalization, processing, and polarization. Regarding the different transfer models, we discuss how these might co-exist to regulate skin pigmentation under different conditions, i.e., constitutive and facultative skin pigmentation or physiological and pathological conditions. Moreover, we discuss recent evidence that sheds light on the regulation of melanin exocytosis by melanocytes and internalization by keratinocytes, as well as how melanin is stored within these cells in a compartment that we propose be named the melanokerasome. Finally, we review the state of the art on the molecular mechanisms that lead to melanokerasome positioning above the nuclei of keratinocytes, forming supranuclear caps that shield the nuclear DNA from UV radiation. Thus, we provide a comprehensive overview of the current knowledge on the molecular mechanisms regulating skin pigmentation, from melanin exocytosis by melanocytes and internalization by keratinocytes to processing and polarization within keratinocytes. A better knowledge of these molecular mechanisms will clarify long-lasting questions in the field that are crucial for the understanding of skin pigmentation and can shed light on fundamental aspects of organelle biology. Ultimately, this knowledge can lead to novel therapeutic strategies to treat hypo- or hyper-pigmentation disorders, which have a high socio-economic burden on patients and healthcare systems worldwide, as well as cosmetic applications.

Species distributional or trait data based on range map (extent-of-occurrence) or atlas survey data often display spatial autocorrelation, i.e. locations close to each other exhibit more similar values than those further apart. If this pattern remains present in the residuals of a statistical model based on such data, one of the key assumptions of standard statistical analyses, that residuals are independent and identically distributed (i.i.d), is violated. The violation of the assumption of i.i.d. residuals may bias parameter estimates and can increase type I error rates (falsely rejecting the null hypothesis of no effect). While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take spatial autocorrelation into account in tests of statistical significance. Here, we describe six different statistical approaches to infer correlates of species' distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations. A comprehensive comparison of the relative merits of these methods is beyond the scope of this paper. To demonstrate each method's implementation, however, we undertook preliminary tests based on simulated data. These preliminary tests verified that most of the spatial modeling techniques we examined showed good type I error control and precise parameter estimates, at least when confronted with simplistic simulated data containing spatial autocorrelation in the errors. However, we found that for presence/absence data the results and conclusions were very variable between the different methods. This is likely due to the low information content of binary maps. Also, in contrast with previous studies, we found that autocovariate methods consistently underestimated the effects of environmental controls of species distributions. Given their widespread use, in particular for the modelling of species presence/absence data (e.g. climate envelope models), we argue that this warrants further study and caution in their use. To aid other ecologists in making use of the methods described, code to implement them in freely available software is provided in an electronic appendix.

Deep reinforcement learning (DRL) has demonstrated its potential in solving complex manufacturing decision-making problems, especially in a context where the system learns over time with actual operation in the absence of training data. One interesting and challenging application for such methods is the assembly sequence planning (ASP) problem. In this paper, we propose an approach to the implementation of DRL methods in ASP. The proposed approach introduces in the RL environment parametric actions to improve training time and sample efficiency and uses two different reward signals: (1) user’s preferences and (2) total assembly time duration. The user’s preferences signal addresses the difficulties and non-ergonomic properties of the assembly faced by the human and the total assembly time signal enforces the optimization of the assembly. Three of the most powerful deep RL methods were studied, Advantage Actor-Critic (A2C), Deep Q-Learning (DQN), and Rainbow, in two different scenarios: a stochastic and a deterministic one. Finally, the performance of the DRL algorithms was compared to tabular Q-Learnings performance. After 10,000 episodes, the system achieved near optimal behaviour for the algorithms tabular Q-Learning, A2C, and Rainbow. Though, for more complex scenarios, the algorithm tabular Q-Learning is expected to underperform in comparison to the other 2 algorithms. The results support the potential for the application of deep reinforcement learning in assembly sequence planning problems with human interaction.

Bulging of the inguinal region is a frequent complaint in the pediatric population and sonographic findings can be challenging for radiologists. In this review we update the sonographic findings of the most common disorders that affect the inguinal canal in neonates and children, with a focus on the processus vaginalis abnormalities such as congenital hydroceles, indirect inguinal hernias and cryptorchidism, illustrated with cases collected at a quaternary hospital during a 7-year period. We emphasize the importance of correctly classifying different types of congenital hydrocele and inguinal hernia to allow for early surgical intervention when necessary. We have systematically organized and illustrated all types of congenital hydrocele and inguinal hernias based on embryological, anatomical and pathophysiological findings to assist readers in the diagnosis of even complex cases of inguinal canal ultrasound evaluation in neonates and children. We also present rare diagnoses such as the abdominoscrotal hydrocele and the herniation of uterus and ovaries into the canal of Nuck.