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We introduce an algebraically active disturbance rejection-based control solution for the trajectory tracking problem of an uncertain second-order flat system with unknown external disturbances. To this end, we first algebraically identify the system’s unknown dynamics and the external disturbances with a linear set of time-varying integral expressions for the output and the control signal. We use the identified dynamics on an online feedback cancellation scheme to linearize the second-order system and cancel the uncertainties. With a proportional-integral controller we stabilize the linearized system without the need to estimate the velocity and have feedback from it. We carry out the stability analysis using linear systems theory. Finally, we evaluate the effectiveness of the proposed controller in a partially known 2-DOF manipulator.

This article employed pupillometry as a non-invasive technique to analyze pupillary light reflex (PLR) using LED flash stimuli. Particularly, for the experiments, only the red LED with a wavelength of 600 nm served as the light stimulation source. To stabilize the initial pupil size, a pre-stimulus (PRE) period of 3 s was implemented, followed by a 1 s stimulation period (ON) and a 4 s post-stimulus period (POST). Moreover, an experimental, low-cost pupillometer prototype was designed to capture pupillary images of 13 participants. The prototype consists of a 2-megapixel web camera and a lighting system comprising infrared and RGB LEDs for image capture in low-light conditions and stimulus induction, respectively. The study reveals several characteristic features for classifying the phenomenon, notably the mobility of Hjórth parameters, achieving classification percentages ranging from 97% to 99%, and offering novel insights into pattern recognition in pupillary activity. Moreover, the proposed device successfully captured the PLR from all the participants with zero reported incidents or health affectations.

**Introduction**: The authors reviewed close/positive margins in cutaneous squamous cell carcinoma of the head and neck, ensuing recurrence, regional or systemic metastasis, mortality and follow-up management. **Methods**: The design was a systematised review from January 2000 to July 2021. The MEDLINE database was searched with 15 articles out of 3104 meeting the inclusion criteria. Pertinent references underpinning the National Comprehensive Cancer Network’s Squamous Cell Skin Cancer Guidelines Version 2.2022 were reviewed. **Results**: Overall, there were 13,671 cutaneous squamous cell carcinoma lesions. We found pooled rates for positive excision (14.6% at 99% CI [12.97, 16.26]), ensuing recurrence (14.7% at 99% CI [13.51, 15.83]), regional or systemic metastasis (33.8% at 99% CI [33.77, 33.87]), and mortality (46.6% at 99% CI [42.53, 50.65]). Positive excisions most frequently involved the deep margin (73.7%), nose (34.5%) and ear (33.14%). Re-excision of positive margins appeared to confer worse recurrence (35.4%). We found pooled rates for close/positive excision (17% at 99% CI [15.22, 18.84]), ensuing recurrence (17% at 99% CI [15.76, 18.16]), regional or systemic metastasis (30.4% at 99% CI [26.15, 34.73]), and mortality (46.6% at 99% CI [42.53, 50.65]). Mean follow up was 51 months. Surgical re-excision with adequate margins appeared to be most efficacious, followed by radiotherapy. Chemoradiation and chemotherapy appeared less efficacious. **Conclusion**: Surgical re-excision with adequate margins remains the gold standard for close/positive margins in cutaneous squamous cell carcinoma of the head and neck, followed by radiotherapy.

Tungiasis is a skin parasitosis caused by a flea. It is very prevalent in underdeveloped countries and rare in developed countries, particularly in Europe. The disease is acquired through direct contact with infected soil, mainly on the feet after the host has been barefoot. The disease is typically self-limited and its diagnosis is essentially clinical due to its typical clinical presentation. This report presents a case of imported tungiasis in Portugal, in a 21-year-old male patient after returning from a vacation in a country with a high prevalence of this parasite. The patient had three typical tungiasis lesions, with no associated complications. The parasites were surgically excised without complications. The aim of this report is to contribute to knowledge of this pathology, which is largely unknown to the majority of the medical community. Its identification is essential due to the increase in globalization, tourism, and the importation of this pathology.

Abstract In areas surrounding large poultry industries, poultry litter is often an alternative nitrogen fertilizer for crop production. However, farmers who have not used poultry litter in the past have concerns regarding potential weed seed contamination. A survey was conducted to determine the occurrence of germinable weed seed in poultry litters (n = 61) submitted by growers and industry representatives across North Carolina. In a 9:1 potting media:poultry litter mix, a single grass seed germinated from the 61 surveyed poultry litters, equating to 0.3 viable seeds 100 g−1 poultry litter. Viable seed content averaged 1.1 seeds 100 g−1 litter using the extractable seedbank method on 25% of the litters from the survey, much higher than the grow out method, and the majority of seeds found were Amaranthaceae. A growth chamber experiment was then conducted and demonstrated that there was a negative relation between poultry litter application and weed seedling emergence. There was a 65%, 75%, and 85% reduction in Senna obtusifolia (L.) H.S. Irwin & Barneby, Setaria pumila (Poir.) Roem. & Schult., and Amaranthus palmeri S. Watson germination, respectively, from the control to highest application rate of poultry litter (26.9 Mg ha−1). A laboratory study showed that poultry litter leachates can decrease seed radicle length and integrity and is likely due to osmotic or salinity stress. The weed seed content in litter as well as the negative impact of poultry litter and its leachates on weed seedling emergence make it unlikely that poultry litter applications will significantly increase seedbanks above levels commonly observed in agricultural fields.

Generative Adversarial Networks are powerful generative models that are used in different areas and with multiple applications. However, this type of model has a training problem called mode collapse. This problem causes the generator to not learn the complete distribution of the data with which it is trained. To force the network to learn the entire data distribution, MSSGAN is introduced. This model has multiple generators and distributes the training data in multiple subspaces, where each generator is enforced to learn only one of the groups with the help of a classifier. We demonstrate that our model performs better on the FID and Sample Distribution metrics compared to previous models to avoid mode collapse. Experimental results show how each of the generators learns different information and, in turn, generates satisfactory quality samples.

We present a browser-based App for smartphones that is freely available to end-users for collecting geotagged and oriented photos depicting vegetation biomass and fuel characteristics. Our solution builds on advantages of smartphones, allowing their use as easy sensors to collect data by imaging forest ecosystems. The strength and innovation of the proposed solution is based on the following points: (i) using a low memory footprint App, streaming images and data with as little data-volume and memory as needed; (ii) using JavaScript APIs that can be launched from both a browser or as an installed App, as it applies features such as service workers and Progressive Web App; (iii) storing both image and survey data (geolocation and sensor orientation) internally to the device on an indexed database, and synchronizing the data to a cloud-based server when the smartphone is online and when all other safety tests have been successfully passed. The goal is to achieve properly positioned and oriented photos that can be used as training and testing data for future estimation of the surface fuel types based on automatic segmentation and classification via Machine Learning and Deep Learning.

Abstract We propose and explore the Regge limit for correlation functions of five local primary operators in conformal field theories. After reviewing some features of Regge theory for flat-space scattering amplitudes, we analyze the analytic structure of conformal blocks both in position and Mellin space in the Regge limit and propose an extension of conformal Regge theory for five-point functions. As a byproduct of our analysis we also introduce a new basis of three-point correlation functions for operators with spin and the associated Euclidean conformal blocks.

We present a proportional–integral–derivative-based controller plus an adaptive slide surface to solve the trajectory tracking control problem for a fully actuated vessel with unknown parameters perturbed by slowly varying external unknown dynamics. The controller design assumes that the vessel moves at low speed and frequency, its physical parameters are unknown, and its state is measurable. The control approach ensures error tracking convergence toward a small vicinity at the origin. We conduct the corresponding stability analysis using the Lyapunov theory and saturation functions. We tested the controller through two numerical experiments—a turning ellipse maneuver and a rest-to-rest maneuver—where the vessel parameters were unknown, and we obtained satisfactory results.

Within the framework of sustainable supply chain management and logistics, this work tackles the complex challenge of optimizing inventory levels across varied storage facilities. It introduces a comprehensive many-objective optimization model designed to minimize holding costs, energy consumption, and shortage risk concurrently, thereby integrating sustainability considerations into inventory management. The model incorporates the distinct energy consumption profiles associated with various storage types and evaluates the influence of stock levels on energy usage. Through an examination of a 60-day production schedule, the dynamic relationship between inventory levels and operational objectives is investigated, revealing a well-defined set of optimal solutions that highlight the trade-off between energy savings and shortage risk. Employing a 30-day rolling forward analysis with daily optimization provides insights into the evolving nature of inventory optimization. Additionally, the model is extended to encompass a five-objective optimization by decomposing shortage risk, offering a nuanced comprehension of inventory risks. The outcomes of this research provide a range of optimal solutions, empowering supply chain managers to make informed decisions that strike a balance among cost, energy efficiency, and supply chain resilience.

Many proteins in higher eukaryotes, especially those with crucial functions, have multiple isoforms with redundant roles providing protection against potential functional deficiencies in one isoform. However, these isoforms can also have some unique roles. Protein kinase B, also known as Akt, is one such protein that has three isoforms encoded on different genes. Due to high sequence similarity and the general lack of specific reagents, most studies on Akt generalize their findings and do not distinguish between the isoforms. Using an established chemical genetic strategy and a set of known Akt substrates, this work explores substrate specificity of Akt isoforms under steady state conditions in two commonly used cell lines. This strategy can be applied to study any Akt isoform-specific substrates of interest in any cell line of choice as long as the cell line can be transfected.

Amando de Miguel in memoriam (1937-2023). Recuerdos de un maestro abierto a la sociología y la metodología cualitativista

The modern S-Matrix Bootstrap provides non-perturbative bounds on low-energy aspects of scattering amplitudes, leveraging the constraints of unitarity, analyticity and crossing. Typically, the solutions saturating such bounds also saturate the unitarity constraint as much as possible, meaning that they are almost exclusively elastic. This is expected to be unphysical in d>2 because of Aks' theorem. We explore this issue by adding inelasticity as an additional input, both using a primal approach in general dimensions which extends the usual ansatz, and establishing a dual formulation in the 2d case. We then measure the effects on the low-energy observables where we observe stronger bounds than in the standard setup.