Under the “Korean emission trading system in the forestry sector (KETSF)” initiative, the South Korean government has developed several greenhouse gas (GHG) emissions reduction programs that include forestry activities as the cornerstones of the initiative. Forest management is deemed to be a major strategy to implement KETSF; this has been confirmed by most participants in the program, who have shown their preference for forest management projects as the most effective and encouraging strategy to participate in the KETSF program. For a successful implementation of KETSF projects is essential to explore methods that optimize the positive impacts of such strategies, thereby maximizing the economic returns and carbon stocks that result from the implementation of forest management activities. Thus, this study investigated several value-added KETSF projects in South Korea, which included simulated scenarios under two main forest management strategies: one based on an extension of the rotation age, and a second one based on reforestation with new species. Five forest management scenarios were examined and evaluated in their ability to maximize carbon stocks and economic returns. Based on the results, Scenarios 2 and 4 were identified as the best KETSF projects in terms of carbon stock increments. Additionally, the results indicated that projects including reforestation with new species added more economic value than projects that considered an extension of the rotation age. The study also revealed that KETSF projects generated revenue in both scenarios, by either extending the rotation age or by implementing reforestation with new species.

The growth of urban population, combined with an increase of extreme events due to climate changes call for a better understanding and representation of urban floods. Rainfall and infiltration are two important factors that affect the watershed response to a given precipitation event. In this paper, we evaluate the influence of the representation of infiltration and spatially variable rainfall on the computer simulation of the floods that affected the city of Hull, UK in June 2007. This work compares a uniform rainfall with one generated using Kriging with External Drift and a constant infiltration equal to the soil hydraulic conductivity with a neglected infiltration. The results of the four simulations are then compared with the flood extents observed by public authorities. It results that the computer model is able the reproduce the general dynamic of the flood and identify the main inundated areas. We found that neglecting the infiltration induce a better representation of this flood event. Furthermore, the use of radar rainfall results in an accuracy similar to the one obtained with a constant rainfall. This study indicates that when the spatial resolution of the rainfall data is low compared to the catchment size and the precipitation distribution is uniform, the spatial variability of the rainfall might not add significant information.

Strandings are one of the most worrying issues in relation to the conservation of cetacean species, and in the case of Chile, due to its geography and large extension of the coastline, monitoring and access to these events is difficult, making their study more complex. Chile has a shortage of specialized scientific forensic research facilities for cetacean; however, for this study it was able to collect data recorded from official institutions and sporadic scientific biological sampling oriented to investigate the causes of death or stranding. According to the Chilean government official database, we described that the main causes of unusual mortality events (UME) and mass strandings from year 2015 and 2016 were acute poisoning by biotoxin and trauma to the auditory complex, respectively, while individual strandings would have their causes in anthropogenic activities such as entanglements in fishing an aquaculture gear and collisions with vessels. The predominant species in mass strandings was the sei whale (Balaenoptera borealis). The geographical area of greatest prominence in mass strandings was the Aysén Region in the Central Patagonia of Chile, while the species mostly involved in individual strandings along the south-central, central, and northern coast of Chile was the small porpoise (Phocoena spinipinnis). The most common gross pathological findings were advance decay of the carcasses and nonspecific wounds of different nature, difficult to associate with possible causes of death without further histopathological studies.

The diagnosis and treatment of autoimmune diseases are major challenges. Their signs, symptoms, and their clinical severity change throughout the course of the disease. The available treatments for these conditions do not result in complete remission, and their long-term use generates several side effects. The main challenges in this field are the development of more sensitive diagnostic tools, and effective treatments. Studies in patients and animal models reported alterations in monocyte phenotype, activation, and function. These cells play an essential role in the pathogenesis of chronic inflammatory states and have become a target for extracorporeal monitoring and specific intervention. Nanoparticles (NPs) are ultrafine particles that can be used as contrast agents in diagnostic imaging techniques to detect specific cells in inflammatory infiltrates in tissues that are not easily accessible by biopsy. In addition, NPs can be designed to deliver drugs to a cell population or tissue. This review describes several experimental pieces of evidence demonstrating that monocytes and macrophages can specifically uptake various types of NPs, thus becoming detectable in vivo by magnetic resonance imaging and susceptible to be modulated by therapeutic agents. Hence, nanoparticles targeting mononuclear phagocytes represent promising tools for diagnosing and treatment.

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

The Haar wavelet decomposition technique is used to detect the planetary magnetosphere boundaries and discontinuities. We use the magnetometer data from the CASSINI and MESSENGER spacecraft to identify the abrupt changes in the magnetic field when the spacecraft crossed the magnetospheric bow shocks and magnetopauses of Saturn and Mercury, respectively. The results confirm that the Haar transform can efficiently identify the planetary magnetosphere boundaries characterized by the abrupt magnetic field changes. It is suggested that this technique can be applied to detect the planetary boundaries as well as the discontinuities such as the shock waves in the interplanetary space.

Blockchain technology has emerged as a necessity for the decentralization of payment methods and transactions, but it has brought with it many properties of distributed systems that have made it a crucial technology for overcoming some of society's challenges, especially in the context of decentralizing services, transparency of information, availability, and security. Its architecture and communication methods, although possessing some complex nuances to understand, particularly for the lay audience in the field of distributed systems, protocols, and computer networks. In this article, we will explore some topics of distributed systems related to blockchain technology.

The molecular structure and vibrational spectra of six 1,2,3-triazoles-containing molecules with possible anticancer activity were investigated. In two of them, the optimized geometry was determined in the monomer, cyclic dimer and staking forms using the B3LYP, M06-2X and MP2 methods. The effect of the para-substitution in the aryl ring was evaluated based on the changes in the molecular structure and atomic charge distribution of the triazole ring. Several relationships were obtained that could facilitate the selection of the substituents on the triazole ring for their further synthesis. The observed IR and Raman bands in the solid state of two of these compounds were accurately assigned according to the functional calculations on the monomer and dimer forms, together with the polynomic scaling equation procedure (PSE).

This study investigates the valorization potential of yellowfin tuna tails for the production of high-value commercial products. Muscle and skins were firstly mechanically separated by using a specifically designed device. The muscle was then used as a nitrogen source for the growth of the proteolytic enzymes-producer Bacillus subtilis, whereas the skins were employed for gelatin extrac-tion. The proteases from Bacillus subtilis were partially purified and used to produce antioxidant peptides from gelatin obtained. The gelatin obtained formed a gel upon cooling, with gelling and melting temperatures at 16 ºC and 22 ºC, respectively, and Bloom Strength of ≈ 160. RSM was used to determine the optimal hydrolysis conditions to obtain the highest antioxidant activity (35.96%, measured as DPPH radical scavenging activity), which were 50°C / 6.5 IU of enzyme. The findings emphasize the importance of an integrated approach to maximize the value of tuna by-products, promoting sustainability in the frame of circular bioeconomy. Overall, these results contribute to the efficient utilization of tuna by-products, waste reduction, and enhance economic viability of the tuna industry.

Post-quantum public cryptosystems introduced so far do not define an scalable public key infrastructure for the quantum era. We demonstrate here a public certification system based in Lizama’s non-invertible Key Exchange Protocol which can be used to implement a public key infrastructure (PKI), secure, scalable, interoperable and efficient. We show functionality of certificates across different certification domains. Finally, we discuss that non-invertible certificates can exhibit Perfect Forward Secrecy (PFS).

We introduce a new integral method for Quantum Key Distribution to perform sifting, reconciliation and amplification processes to establish a cryptographic key through the use of binary structures called frames which are capable to increase quadratically the secret key rate. The method can be implemented with the usual optical Bennett-Brassard (BB84) equipment allowing strong pulses in the quantum regime.

We introduce a novel key exchange protocol based on non-commutative matrix multiplication defined in $\mathbb{F}_p^{n \times n}$. The security of our method does not rely on computational problems as integer factorization or discrete logarithm whose difficulty is conjectured. We show that the public, secret and channel keys become indistinguishable to the eavesdropper under matrix multiplication. Remarkably, for achieving a 512-bit security level, the public key is 1024 bits and the private key is 768 bits, making them the smallest keys among post-quantum key exchange algorithms. Also, we discuss how to achieve key authentication, interdomain certification and Perfect Forward Secrecy (PFS). Therefore, Lizama's algorithm becomes a promising candidate to establish shared keys and secret communication between (IoT) devices in the quantum era.

We present an error reconciliation method for Quantum Key Distribution (QKD) that corrects 100% of errors generated in regular binary frames transmitted over a noisy quantum channel regardless of the quantum channel error rate. In a previous investigation, we introduced a novel distillation QKD algorithm whose secret key rate descends linearly with respect to the channel error rate. Now, as the main achievement of this work, we demonstrate an improved algorithm capable of retaining almost all the secret information enclosed in the regular binary frames. Remarkably, this technique increases quadratically the secret key rate as a function of the double matching detection events and doubly quadratically in the number of the quantum pulses. Furthermore, this reconciliation method opens up the opportunity to use less attenuated quantum pulses, would allow greater QKD distances at drastically increased secret key rate. Since our method can be implemented as a software update, we hope that quantum key distribution technology would be fast deployed over global data networks in the quantum era.

We introduce a novel key exchange protocol based on non-commutative matrix multiplication defined in $\mathbb{Z}_p^{n \times n}$. The security of our method does not rely on computational problems as integer factorization or discrete logarithm whose difficulty is conjectured. We claim that the unique eavesdropper's opportunity to get the secret/private key is by means of an exhaustive search which is equivalent to the unsorted database search problem. Furthermore, we show that the secret/private keys become indistinguishable to the eavesdropper. Remarkably, to achieve a 512-bit security level, the keys (public/private) are of the same size when matrix multiplication is done over a reduced 8-bit size modulo. Also, we discuss how to achieve key certification and Perfect Forward Secrecy (PFS). Therefore, Lizama's algorithm becomes a promising candidate to establish shared keys and secret communication between (IoT) devices in the quantum era.

The escalating environmental challenges that stem from urban residential waste in densely populated areas have become increasingly prominent in recent times. As a result, the waste management sector has experienced significant growth nationwide. However, due to the predominantly manual nature of these processes, their effectiveness falls short of meeting the current demand. Addressing these issues requires process enhancement. In this context, Industry 4.0, particularly the concept of Digital Twins, emerges as a potential avenue for refining processes. To tackle both current and future industry challenges, it is imperative to create a comprehensive methodology capable of generating effective solutions within the waste management sector. This paper provides an explanation of digital twins, outlines the methodological framework comprising an architectural structure and layered model, and details a series of sequential methodical stages for implementing digital twins based on the specific scope determined by the end-user. A noteworthy aspect is the transformative potential of digital twins in enhancing efficiency and precision within waste management practices. By providing a virtual real-time representation of the waste management system, digital twins empower simulations and experimentation to fine-tune processes. Furthermore, they facilitate informed decision-making by offering a detailed visualization of the complete system, simplifying the identification of challenges and opportunities for improvement. that this article derives from the presentation titled "Digital Twin application methodology for the improvement of production and service systems. Application to waste management processes" at the "Sustainable Smart Cities and Territories International Conference" held in the city of Manizales, Colombia, from 21st to 23rd June 2023.

A developed six-port reflectometry (SPR) system was integrated to measure the relative permittivity of tumor and normal breast tissue for medical diagnostic purpose. In order to obtain an accurate and precise measurement, the calibration process was done to the SPR using the well-known three-standard technique. Next, the studied dielectric probe was connected to the calibrated measurement-port of the SPR. The open end of the probe aperture was dibbed into the normal and tumor synthetic breast tissue samples to measure the synthetic breast tissues dielectric constant, ɛrʹ, and loss factor, ɛrʺ in the frequency range of 1.5 GHz to 3.3 GHz. Finally, the comparative studies were conducted between commercial VNA with Keysight 85070E dielectric probe and the studied SPR-probe system based on the measured magnitude of the reflection coefficient, phase shift, dielectric constant, and loss factor of the synthetic breast samples. The maximum absolute errors of the measured reflection coefficient magnitude, phase shift, dielectric constant, and loss factor were found to be 0.01, 1.07°, 1.12, and 0.75, respectively. It was ascertained that the predicted dielectric constant, ɛrʹ, is able to differentiate between normal, (ɛrʹ < 50) and tumor, (ɛrʹ > 50) breast tissues.

Background: The clinical outcomes of antiretroviral drugs may be modified by drug interactions; thus, it is important to update the drug interactions in people living with HIV. Aim: To update clinically relevant drug interactions in people living with HIV on antiretroviral therapy. Methods: A systematic review in Medline/PubMed database from July 2017 to December 2022, using the Mesh terms: Anti-retroviral agents and drug interactions or herb-drug interactions or food-drug interactions. Publications with drug interactions in humans, in English or Spanish, and with full text were retrieved. The clinical relevance of drug interaction was grouped into 5 levels according to gravity and probability of occurrence. Results: 361 articles were identified and 148 were included, which allowed the identification of 894 drug interaction pairs. Among these 894 drug pairs, 355 have not been identified previously; and 89 (25.1%) and 72 (20.2%) were of levels 1 and 2, respectively. In addition, for 197 (55.5%) pairs the mechanism was pharmacokinetic. The non-nucleoside reverse transcriptase inhibitors (NNRTIs) and the protease inhibitors (PIs) with 91 (25.6%) and 76 (21.4%) pairs, respectively were more frequent. Conclusions: In people living with HIV on antiretroviral therapy, we identify 355 new drug interaction pairs, of them 161 (45.3%) are assessed as levels 1 and 2 and thus, clinically relevant; a figure that is lower compared to 2014-2107 update. The pharmacokinetic mechanism is the most frequently identified. The non-nucleoside reverse transcriptase inhibitors (NNRTIs) and the protease inhibitors (PIs) are the antiretroviral groups with the highest number of clinically relevant drug interactions.

The cancer stem cell hypothesis suggests that neoplastic cells with stem characteristics hierarchically regulate tumor generation and its high cellular heterogeneity. These cells have been detected in all cancer types, and specific signaling pathways give the regulation of self-renewal and differentiation. In prostate cancer, androgen receptor signaling has been extensively studied, and in non-stem cells, it promotes cell proliferation and tumor progression, but in the cancer stem cell population, it negatively regulates processes such as self-renewal. However, in other types of cancer, such as breast and glioblastoma, the androgen receptor seems to favor the maintenance of cancer stem cells, suggesting that androgen signaling has different effects depending on the tumor context. This review discusses the role of androgen receptor in maintaining cancer stem cells by regulating proliferation, self-renewal, and differentiation, as well as the possible signaling pathways involved in these processes.

A whole-exome capture and next-generation sequencing applied to an 11 y/o patient with a clinical history of congenital hypotonia, generalized motor and cognitive neurodevelopmental delay, severe cognitive deficit, without any identifiable Syndromic pattern, and to her parents, disclosed a de novo heterozygous pathogenic mutation, c.697_699del p.Phe233del (rs786204835)(ACMG classification PS2, PM1, PM2, PP5), harbored in the PURA gene (MIM*600473) (5q31.3), associated to Autosomal Dominant Mental Retardation 31 (MIM # 616158). We used the significant improvement in the accuracy of protein structure prediction recently implemented in AlphaFold that incorporates novel neural network architectures and training procedures based on the evolutionary, physical, and geometric constraints of protein structures. The wild-type (WT) sequence and the mutated one, missing the Phe233, were reconstructed. The predicted local Distance Difference Test (lDDT) for the PURA WT and the PURA-Phe233del showed that the occurrence of the Phe233del affects between 220-320 amino acids. The distortion in the PURA structural confor-mation in the ~5Å surrounding area after the p.Phe233del produces a conspicuous disruption of the repeat III, where the DNA and RNA helix unwinding capability occurs. PURA Protein-DNA Docking corroborated these results in silico Analysis that showed a loss of the contact of the PURA-Phe233del III repeat domain model with the DNA. Together, i) the energetic and stereochemical, ii) the hydropathic indices and polarity surfaces, and iii) the hybrid Quantum Mechanics-Molecular Mechanics (QM-MM) analyses of the PURA molecular models demarcate at the atomic resolution the specific surrounding region affected by these mutations and paves the way for future cell-based functional analysis. To the best of our knowledge, this is the first report of a de novo mutation underpinning a PURA syndrome in a Latin American patient and highlights the importance of predicting the molecular effects in protein structure using artificial intelligence algorithms and molecular and atomic resolution stereochemical analyses.

The 1,2,3-triazole derivative 2-(4-chlorophenyl)-5-(pyrrolidin-1-yl)-2H-1,2,3-triazole-4-carboxylic acid with potential anticancer activity was used as a ligand in complex formation with the lan-thanum(III) ion. The molecular structure and vibrational spectra of the complex were optimized at three DFT levels and the scaled IR and Raman spectra were compared to the experimental ones. Several scaling procedures were used. Through a detailed analysis, the structure predicted for the newly synthetized La(III) complex was confirmed by the good accordance of the calculat-ed-experimental IR and Raman spectra. The best DFT method appears to be M06-2X with the Lanl2mb basis set, followed closely by Lanl2dz. The effect of the lanthanide atom on the molecular structure and atomic charge distribution of the triazole ring was evaluated. Potential free radical scavenging activity of both, ligand and complex, was investigated in several radical-generating model systems. Potential mechanisms of antioxidant action (hydrogen atom transfer – HAT and single electron transfer - SET) were elucidated.

We present a new post-processing method for Quantum Key Distribution (QKD) that raise cubically the secret key rate in the number of double matching detection events. In Shannon’s communication model information is prepared at Alice’s side then it is intended to pass it over a noisy channel. In our approach, secret bits do not rely in Alice’s transmitted quantum bits but in Bob’s basis measurement choices. Therefore measured bits are publicly revealed while bases selections remain secret. Our method implements sifting, reconciliation and amplification in a unique process, it just require a round iteration, no redundancy bits are sent and there is no limit in the correctable error percentage. Moreover, this method can be implemented as a post processing software into QKD technologies already in use.

Previously, using the conjugate frame-based reconciliation approach, we defined a method to correct errors produced in pairs of non-orthogonal quantum states that are transmitted through a quantum key distribution (QKD) link. The security of the frame-based reconciliation was discussed in order to deal with Photon Number Division (PNS) attack and Intercept and Forward (IR) attack, among others. However, until the time of publication we did not have the distillation software to test our method. In this article, following the conjugate frame distillation method, we present the implementation of the post-processing system that demonstrates that it is capable of correcting errors in the presence of error rates close to unity. The system shows that when the number of double-sensing events at Bob's station is as low as 100, the number of secret bits stays above 4500 bits in about 12 seconds, giving a secret rate of 375 bits per second while that the channel error rate reaches 90\%.

A mathematical model, composed of two non-linear differential equations that describe the population dynamics of CD4 T cells in the human immune system, as well as viral HIV particles, is proposed. The invariance region is determined, classical equilibria stability analysis is performed using the basic reproduction number, and numerical simulations are carried out, in order to illustrate stability results. Later, the model is modified with a delay term, which describes the time that cells require for immunological activation. This generates a two-dimensional integro-differential system, which is transformed into a system with three ordinary differential equations, via auxiliary variable use. For the new model, equilibrium points are determined, their local stability is examined, and results are studied by way of numerical simulation.

Pygoscelis penguin populations in the Antarctic Peninsula have dropped dramatically in the last 50 years. The main probable cause is the reduction in Krill (Euphausia superba), the most important feeding item for Pygoscelis penguins during breeding. The scientific community has expressed concerns on the potential that competition with the fishery during periods of low krill availability might be exacerbating the effects of climate change. By bringing together data on breeding success of penguin colonies throughout the Antarctic Peninsula with information of krill availability from acoustic survey and krill fishery monitoring data, we were able to show that fishery has had in the past an effect over breeding success. That is a consequence of a management strategy based on a constant catch level enabling the fishery to maintain the same levels of production even when krill availability is low. The total catch limit may have represented a substantial amount of the available krill biomass in some years, and we detected that when the catch goes over 5% of the available biomass during summer, breeding success of penguins decreased by one third. We discuss the implications of our findings to the revised ecosystem-based management strategy of the krill fishery in Antarctica.

Pipeline integrity is an important area of concern for the oil and gas, refining, chemical, hydrogen, carbon sequestration, and electric-power industries, due to the safety risks associated with pipeline failures. Regular monitoring, inspection, and maintenance of these facilities is therefore required for safe operation. Large standoff magnetometry (LSM) is a non-intrusive, passive magnetometer-based mea- surement technology that has shown promise in detecting defects (anomalies) in regions of elevated mechanical stresses. However, analyzing the noisy multi-sensor LSM data to clearly identify regions of anomalies is a significant challenge. This is mainly due to the high frequency of the data collection, mis-alignment between consecutive inspections and sensors, as well as the number of sensor measurements recorded. In this paper we present LSM defect identification approach based on ma- chine learning (ML). We show that this ML approach is able to successfully detect anomalous readings using a series of methods with increasing model complexity and capacity. The methods start from unsupervised learning with "point" methods and eventually increase complexity to supervised learning with sequence methods and multi-output predictions. We observe data leakage issues for some methods with randomized train/test splitting and resolve them by specific non-randomized splitting of training and validation data. We also achieve a 200x acceleration of support-vector classifier (SVC) method by porting computations from CPU to GPU leveraging the cuML RAPIDS AI library. For sequence methods, we develop a customized Convolutional Neural Network (CNN) architecture based on 1D convolutional filters to identify and characterize multiple properties of these defects. In the end, we report the scalability of the best-performing methods and compare them, for viability in field trials.

The reliability analysis allows to estimate the system's probability of detecting and identifying outlier. Failure to identify an outlier can jeopardise the reliability level of a system. Due to its importance, outliers must be appropriately treated to ensure the normal operation of a system. The system models are usually developed from certain constraints. Constraints play a central role in model precision and validity. In this work, we present a detailed optical investigation of the effects of the hard and soft constraints on the reliability of a measurement system model. Hard constraints represent a case in which there exist known functional relations between the unknown model parameters, whereas the soft constraints are employed for the case where such functional relations can slightly be violated depending on their uncertainty. The results highlighted that the success rate of identifying an outlier for the case of hard constraints is larger than soft constraints. This suggested that hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. After identifying and removing possible outliers, one should set up the soft constraints to propagate the uncertainties of the constraints during the data processing. This recommendation is valid for outlier detection and identification purpose.

With the Sendai Framework (2015-2030) and the Paris Agreement (2015), the UN has been promoting at a global level, the priority objectives to protect the life and well-being of people, these documents of global consensus have scheduled in several countries, an extensive list of actions of responsibilities and commitments to the environment, to address natural disasters among those of greatest impact earthquakes and floods and among earthquakes (seismic activity). The materialization of the disaster is a natural or human-induced event, it manifests itself in permanent changes in society and by its origin it is classified as natural, anthropogenic (anthropogenic) and mixed, creating a worldwide problematic situation of immediate reaction. The attention and alert in the scientific community have been adding efforts, but in a disorganized way, with limited human and material resources and with globalized strategies still to be improved. The literature review of disaster risk management due to seismic activity, from 2008 to 2023, allows us to have updated information to identify the factors and deepen them, with the understanding, comprehension, and multidisciplinary knowledge. The selected researches that mention the factors (elements) that influence risk management of natural disasters due to seismic activity (RMNDDSA) allow us to know the advances and spaces to approach them, which constitutes the motivation to study the twenty-four (24) factors present in this type of disasters. The selected research articles indicate important advances that associate disaster risk management (DRM) and communication technology (ICTs). The technological means mentioned are well received and accepted by society, capable of detecting and communicating in real time seismic activity worldwide, with the help of social mobile networks, technological platforms, Twitter, Facebook, and others.

The present work sets out the evaluation of composite laminates through optimization objective functions. Genetic Algorithms (GA), as well as Simulated Annealing (SA), were performed in order to determine the optimal ply orientations of a fiber-reinforced polymer laminate for three given load cases: 1) in-plane loads, 2) combined moments, and 3) in-plane loads and combined moments. It searches the optimal orientation layup, which fulfills at the same time both the maximum strain criterion and the Tsai-Wu failure criterion. Construction of an objective function based on the strains and the stresses involves a minimization process to deformations and a maximization of the safety factor. For the first load case, the initial solution is [±45/0/90/±45]s, and the best solution is [(45/135)2/452]s. For the second load case, [-45/45/45/-45/0/90]s is the initial layup sequence, then the best solution obtained is [(45/-45)2/452]s, where plies at 0° and 90º are not necessary even when axial loads are applied. For the third study case, the original layup sequence is [0/45/-45/45/0/90]s; meanwhile, the best solution calculated is [21/24/145/140/45/49]s. An interesting observation is that each pair of layers has a 5º gap. The simulations show that the qualitative results from the GA are better than the SA, but with a significantly higher computational cost. These kinds of computational tools are expected to be used as a reference guide for an optimal fiber configuration with respect to the common orientations used when composite laminates are designed for a structural application.

The aim of this work is to evaluate the impact of proposed modifications to conventional capturing and discharging effluents devices in Subsurface Flow Wetland (SSFW) systems. Main modifications proposed consist on extending the influence of the capture and discharge device in such a way that the SSFW width and height are fully covered. Additionally an SSFW prototype was built as pilot including the proposed modifications and the impact of the innovative device is measured based on the efficiency of the Chemical Oxygen Demand (COD) removal as compared to a traditionally built SSFW. The results show that for the innovative device, the COD removal was 10% higher than for the conventional device.

Cervical cancer is preventable through vaccination, early detection, and treatment of precancerous lesions. However, global inequalities mean that the disease remains a leading cause of cancer death around the world, with over 80% of new cases and 90% of deaths occurring in low and middle-income countries (LMICs). In El Salvador, joint efforts between the Ministry of Health (MoH) and the non-profit organization Basic Health International (BHI) have been in place since 2008 with the goal of reducing the country’s disease burden. While the World Health Organization’s (WHO) call to action to eliminate cervical cancer provided worldwide momentum to implement new public health initiatives, the COVID-19 pandemic disrupted ongoing programs and jeopardized plans for the future. The purpose of this manuscript is to describe the progress that El Salvador has achieved in improving cervical cancer prevention, the impact of the pandemic on current strategies, and potential solutions that can help the country meet the WHO’s strategic targets by 2030 to accelerate the elimination of cervical cancer.

The objective of this work is to evaluate the impact of the innovative modifications made to the conventional effluent capture and discharge devices used in subsurface flow wetlands (SSFW). The main modifications developed consist on extending the influence of the capture and discharge device in such a way that the SSFW width and height are fully covered. This improved innovative device was applied and evaluated in two subsurface flow wetlands, one on a pilot scale and one on a real scale. To evaluate the impact of the innovative device with respect to conventional one in the operational functioning of subsurface flow wetlands, the elimination of chemical oxygen demand was measured and compared. The results show that for the innovative device, the COD removal was 10% higher than for the conventional device, confirming the validity and effectiveness of the modifications implemented in the effluent capture and discharge devices used in SSFW.

In this paper we evaluate the effects of hard and soft constraints on the Iterative Data Snooping (IDS), an iterative outlier elimination procedure. Here, the measurements of a levelling geodetic network were classified according to the local redundancy and maximum absolute correlation between the outlier test statistics, referred to as clusters. We highlight that the larger the relaxation of the constraints, the higher the sensitivity indicators MDB (Minimal Detectable Bias) and MIB (Minimal Identifiable Bias) for both the clustering of measurements and the clustering of constraints. There are circumstances that increase the family-wise error rate (FWE) of the test statistics, increase the performance of the IDS. Under a scenario of soft constraints, one should set out at least three soft constraints in order to identify an outlier in the constraints. In general, hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. In that process, one should opt to set out the redundant hard constraints. After identifying and removing possible outliers, the soft constraints should be employed to propagate their uncertainties to the model parameters during the process of least-squares estimation.

The use of mathematical models of physiological systems in medicine has allowed the development of diagnostic, treatment, and medical educational tools, but their application for predictive, preventive, and personalized purposes is restricted by their complexity. Although there are strategies that reduce the complexity of applying models by fitting techniques, they focus on a single instant of time, neglecting the effect of the system's temporal evolution. The aim of this work is to propose a dynamic fitting strategy of physiological models with large number of parameters and a constrained amount of experimental data, focused on obtaining better predictions based on the system's temporal trend and useful to predict future states. It was applied in a cardiorespiratory model as a case study. Experimental data from a longitudinal study of healthy adult subjects under aerobic exercise were used for fitting and validation. The model predictions obtained at steady-state using the proposed strategy and the nominal values of the parameters were compared. The best results corresponded mostly to the proposed strategy, mainly regarding the overall prediction error. The results evidenced the usefulness of the dynamic fitting strategy, highlighting its use for predictive, preventive, and personalized applications.

An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.

This article aims at presenting the results that were found in the design and implementation of a new management model of Critical Success Factors for improving the effects of research projects. The model was based on the theory of structural equations derived from factor analyses and multiple linear regression models. For achieving the purpose, the authors developed an empirical evidence analysis founded on a literature review in the knowledge area of project management. Afterwards, the process of identification of the CSFs was carried out for a group of research projects launched in Colombia as a result of the application and measurement of an instrument. They were the basis for the development of a structural relationship modeling. Also, this contributed to determine the CSFs that explain the generation of effects of research projects, and the project management execution process from which it can be carried out based on said measurement indicators.

In this contribution, different lane-keeping control strategies for Autonomous Ground Vehicles (AGV) have been analyzed and compared. The AGV must be oriented and kept within a given reference path using the front wheel steering angle as the control action for a specific longitudinal velocity. While non-linear models can describe the lateral dynamics of the vehicle in an accurate manner, they might lead to difficulties when computing some real-time control laws such as Model Predictive Control (MPC). Linear Parameter Varying (LPV) models can provide a trade-off between computational complexity and model accuracy. Another way to reduce computational complexity is to explore other control strategies, for example, the one based on the Inverse Kinematic Bicycle model (IKIBI). Additionally, AGV sensors typically work at different measurement acquisition frequencies so that Kalman Filters (KF) are usually needed for sensor fusion. If these frequencies are slower than the actuation rate, a multi-rate KF may be needed. The two control strategies (MPC using a LPV model and IKIBI) have been compared in simulations over a circuit path in the presence of process and measurement Gaussian noise. The MPC controller has shown to provide a more accurate lane-keeping behavior than an IKIBI control strategy. Finally, it has been seen that Dual-Rate Extended Kalman Filters (DREKF) constitute an essential tool when only slow and noisy sensor feedback is available in an AGV lane-keeping application.

Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms, and greedy heuristic) that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework, and tested in both business-like event logs as recorded in a higher educational ERP system, and a real case scenario involving a set of Dutch municipalities.

The vocal folds are found in the larynx and their vibrations produce the voice. Little is known about morphology and the size of cattle larynx. The aim of the study was to quantify the shape asymmetry of the vocal folds in calves obtained post-mortem using a geometric morphometric approach. A sample of 14 larynges from calves (in an age range 335 to 625 days) belonging to “Bruna dels Pirineus” breed and its F1 crosses was obtained in an abattoir during the first semester of 2021. Landmark sets were superimposed on images of fixed transverse sections of larynges. Using geometric morphometric techniques, we analysed the presence of asymmetries. Results demonstrate differences between right and left vocal fold sides as directional asymmetry, at least in fixed structures. Our findings provide a foundation for quantifying the possible contribution of vocal organ asymmetry among cattle. This study can be considered the first to detect vocal fold asymmetries in cattle. Studies with a larger sample size are needed to validate the information in large populations. One limitation is that the present study does not have samples from adult animals, so it would be interesting to know if the results are similar among them.

Measurements of systems taken along a continuous functional dimension, such as time or space, are ubiquitous in many fields, from the physical and biological sciences to economics and engineering. Such measurements can be viewed as realisations of an underlying smooth process sampled over the continuum. However, traditional methods for independence testing and causal learning are not directly applicable to such data, as they do not take into account the dependence along the functional dimension. By using specifically designed kernels, we introduce statistical tests for bivariate, joint, and conditional independence for functional variables. Our method not only extends the applicability to functional data of the Hilbert-Schmidt independence criterion (HSIC) and its d-variate version (d-HSIC), but also allows us to introduce a test for conditional independence by defining a novel statistic for the conditional permutation test (CPT) based on the Hilbert-Schmidt conditional independence criterion (HSCIC), with optimised regularisation strength estimated through an evaluation rejection rate. Our empirical results of the size and power of these tests on synthetic functional data show good performance, and we then exemplify their application to several constraint- and regression-based causal structure learning problems, including both synthetic examples and real socio-economic data.

In the international scenario of agriculture, Brazil stands out as the main producer and consumer of common bean (Phaseolus vulgaris L.) The increase in the productive potential of the crop is mainly due to breeding programs. The objective of this study was to estimate genetic parameters, predict genotypic values with REML/BLUP (Restricted Maximum Likelihood/Best Linear Unbiased Prediction) and, based on these values, study the variability in common bean cultivars with carioca and black grain. Twenty three agromorphological descriptors were evaluated, among them grain yield. Deviance analysis detected significant differences between the cultivars in both groups. Selective accuracy (Ac) was considered high for most of the traits. Broad-sense heritability (h_g² ) ranged from 0.05 to 0.72, but it was low for the trait yield (YLD). In the carioca grain group, the h_g² values for the traits related to plant morphology were higher than in the black group. Nevertheless, the h_g² values in the black group were higher in relation to the pod and seed traits. The correlations for YLD were moderate but different in the two commercial groups studied. In the black group, variables related to the seed morphology were correlated with grain yield, and in the carioca group, traits related to seed quantity. Based on the groupings, variability among the cultivars was observed. Three distinct clusters were formed for the carioca group and four for the black group. Based on the predicted genetic values, genetic variability and the most adapted and stable cultivars were detected among the cultivars in the studied environments.

Threats to natural ecosystems are closely linked to human development, and the lack, insufficiency or inefficiency of public policies are some of the most important drivers of negative effects on the environment. The contribution of the IUCN’s Red List of Ecosystems (RLE) to conservation topics has been discussed in previous studies; however, to date its implications for conservation in public policies have not been addressed. This perspective discusses how the RLE may support the improvement and development of these policies, specifically through the implications for public policy of each of the criteria that substantiate the threat status of ecosystems. We aim to provide a plausible baseline to the operationalization of RLE in public and conservation policy, facilitating the work of governments, practitioners and decision makers. Finally, we provide recommendations and examples as to how to proceed in creating and modifying different public policy instruments, such as land-use planning, spatial zoning, tax reduction, compensation schemes, climate change adaptation plans, management of introduced species, development offsets and restoration investment. This perspective contributes to implement RLE into public policy and to improve ecosystem conservation by expanding the current scope of RLE into practical and political dimensions through plausible actions, policies and strategies.

Synucleins are a family of small, soluble proteins mainly expressed in neural tissue and in certain tumors. Since their discovery, tens of thousands of scientific reports have been published about this family of proteins as they are associated to severe human diseases. Although the physiological function of these proteins still elusive, their relation with neurodegeneration and cancer was clearly described over the years. In this review, we summarize data connecting synucleins and cancer, going from the structural description of these molecules, to their involvement in tumor-related processes, and discuss the putative use of this proteins as cancer molecular biomarkers.

An iterative outlier elimination procedure based on hypothesis testing, commonly known as Iterative Data Snooping (IDS) among geodesists, is often used for the quality control of the modern measurement systems in geodesy and surveying. The test statistic associated with IDS is the extreme normalised least-squares residual. It is well-known in the literature that critical values (quantile values) of such a test statistic cannot be derived from well-known test distributions, but must be computed numerically by means of Monte Carlo. This paper provides the first results about Monte Carlo-based critical value inserted to different scenarios of correlation between the outlier statistics. From the Monte Carlo evaluation, we compute the probabilities of correct identification, missed detection, wrong exclusion, overidentifications and statistical overlap associated with IDS in the presence of a single outlier. Based on such probability levels we obtain the Minimal Detectable Bias (MDB) and Minimal Identifiable Bias (MIB) for the case where IDS is in play. MDB and MIB are sensitivity indicators for outlier detection and identification, respectively. The results show that there are circumstances that the larger the Type I decision error (smaller critical value), the higher the rates of outlier detection, but the lower the rates of outlier identification. For that case, the larger the Type I Error, the larger the ratio between MIB and MDB. We also highlight that an outlier becomes identifiable when the contribution of the measures to the wrong exclusion rate decline simultaneously. In that case, we verify that the effect of the correlation between the outlier statistics on the wrong exclusion rates becomes insignificant from a certain outlier magnitude, which increases the probability of identification.

The rapid emergence of COVID-19 necessitated policy responses worldwide, focusing on vaccination and mobility restrictions. However, studies on individual non-pharmacological preventive measures are less common. In particular, Chile represents a unique scenario for analyzing the adoption of preventive measures and changes amid aggressive communication and vaccination campaigns. This study aims to provide insights into public adherence to non-pharmacological measures in the face of diseases, using a cohort of 386 participants from 2021 to 2022. This was achieved by employing a questionnaire to measure adherence to self-care practices and by analyzing contact tracing data from health authorities. We performed bivariate analysis and a linear regression model. Mask-wearing in public places was the most commonly used measure (95.9% in 2021 and 89.9% in 2022). The median adherence score increased from 18 to 19 for both measurements, respectively. The regression model shows that women are more likely to adopt preventive behaviors in both waves and being a young adult (30-49 years) predicted the adoption of behavioral precautions in 2022. Adherence to preventive measures increased even with high vaccination coverage, likely due to the epidemiological situation with the Omicron variant circulating in 2022.

Background: External beam radiation therapy requires a sophisticated and laborious planning procedure. To improve the efficiency and quality of the planning procedure, machine learning predictions of the dose distributions have been introduced to speed up the planning procedure and to serve as quality assurance. The most recent dose prediction models are based on deep learning U-Nets that give good approximations of the dose in 3D almost instantly. It is our purpose to train a 3D dose prediction for glioblastoma VMAT treatment and test its robustness and sensitivity for the purpose of quality assurance of automatic contouring. Methods: From a cohort of 125 glioblastoma (GBM) patients, VMAT plans were created according to a clinical protocol. The initial model was trained on a concatenated 3D U-Net. A total of 60 cases were used for training, 15 for validation and 20 for testing. The prediction model was tested for sensitivity to dose changes according to realistic contour variations. Additionally, the model was tested for robustness by exposing it to a worst-case test set containing out-of-distribution cases.Results: The initially trained prediction model had a dose score of 0.94 Gy and a mean DVH score for all structures of 1.95 Gy. In terms of sensitivity, the model was able to predict the dose changes that occurred due to the contour variations with a mean error of 1.38 Gy.Conclusions: We obtained a 3D VMAT dose prediction model for GBM with limited data, providing good sensitivity to realistic contour variations. We tested and improved the model's robustness, by targeted updating the training set, making it a useful technique for dose awareness in the contouring evaluation and quality assurance.

The loop and knot securities of 2 braided and 2 monofilament sutures of four diameters (3.0, 2.0, 0, 1) were evaluated with a tensiometer for four 4-throw knots known to be secure with a 2.0 polyfilament suture. Loop security of monocryl 1 is low, being 14.7 + 3.0 Newton (N) for a 3-throw half-knot (H3) and 15.4 + 2.4 N and 28.3+ 10 N for 2 (SSs) and 4-throw (SSsSsSs) symmetrical sliding half-hitches. This is lower than 18, 24, and 46 N for similar knots with vicryl. Polyfilament sutures have excellent knot security for all diameters. Occasionally, some slide to open with slightly lower knot security, especially for larger diameters, although not clinically problematic. Knot se-curity of monofilament sutures was unpredictable for all 4 knots, especially for larger diameters, resulting in many clinically insecure knots. A secure monofilament knot requires a 6-throw knot with 2 symmetrical sliding half-hitches or 2 symmetrical half-knots secured with 4 asymmetric blocking half-hitches. In conclusion, with polyfilament sutures, 4 or 5-throw half-knot or half-hitch sequences result in secure knots. For monofilament sutures, loop and knot security is much less, half-knot combinations should be avoided, and secure knots require 6-throw knots with 4 asym-metric half hitches. This conclusion is valid for gynecologic laparoscopic and open surgery, and for surgery in general.

In this study, we developed a model that can predict whether patients with cerebral arteriovenous malformation (AVM) will be cured 36 months after intervention by means of stereotactic radiosurgery (SRS), and identified the most important predictors that explain the probability of being cured. A machine learning (ML) approach was applied using decision tree (DT) and logistic regression (LR) techniques on historical data (sociodemographic, clinical, treatment, angioarchitecture, and radiosurgery procedure) of 202 patients with AVM who underwent SRS at the Instituto de Radiocirugía del Perú (IRP) between 2005 and 2018. The LR model obtained the best results for predicting AVM cure with an accuracy of 92.16%, sensitivity of 92.86%, specificity of 88.89%, precision of 97.50%, and AUC of 97.62%, which shows that ML models are suitable for use for predicting the prognosis of medical conditions such as AVM and can be a support tool for medical decision-making. In addition, several factors were identified that could explain whether patients with AMV would be cured at 36 months with the highest likelihood: the location of the AVM, the occupation of the patient, and the presence of hemorrhage.

The assessment of the prevalence of Subclinical Mastitis (SCM) in dairy farms is essential to validate the health status of the mammary gland. The aim of the study was to assess the prevalence of SCM in dual purpose livestock systems in Arauca, Colombian Orinoquia, through the analysis of the values found by the field diagnostic tests California Mastitis Test (CMT) and Electric Conductivity (EC). Milk samples were taken from the individual mammary quarters of 481 cows. The general prevalence, per affected room and the total number of rooms was determined according to the values obtained for each test using two methods of analysis. An ANOVA was performed to determine the difference between prevalence’s, a correlation analysis, and an analysis of sensitivity and specificity. The general prevalence was similar between the tests (CMT = 31.4%; EC = 29.7%) (p > 0.05). The prevalence of the total quarters was lower with EC (11.3% vs 14.2%) (p < 0.05). The correlations between tests were significant, but with low values (rs = 0.20-0.25). CMT and EC test concordance showed a sensitivity between 0.35-0.45 and a specificity of 0.75-0.90. The two tests showed positive results in detecting the same animals with or without the presence of the infection, although some animals that were positive for one test were not positive for the other test. The test EC classified animals and their quarters as SCM positive or negative in a more similar way to that obtained with CMT. The two diagnostic tests showed a general low prevalence of SCM in the livestock systems evaluated.

The participation of civil society is essential for environmental health policies to be effective. The objective of this study was to know the perceptions of government officials, members of civil society, and academics about environmental health problems and its governance in Bucaramanga Metropolitan Area, Colombia. In the region there is a strong citizen movement that defends the moorland ecosystem (paramo) as source of drinking water, of large-scale mining projects. A multi-method study was carried out including the review of newspaper and scientific articles, a citizen survey, and interviews and focus groups with identified key stakeholders. The findings indicate that government officials prioritize their actions on issues related to air and water pollution and environmental education. In contrast, citizens prioritize water availability from the moorland ecosystem. There are some advances in the management of environmental health, mainly related to greater citizen awareness. The participation of civil society in the environmental health governance must be enforced to broaden the issues of interest and prioritize the activities in the short- and long-term policy planning. An experience between high school students and the academy that measures air pollutants can be the first meeting point with government officials in the pathway to improve the environmental governance in the territory.

Myotoxic phospholipases A₂ are responsible for many clinical signs in envenomation by Bothropssnakes. A new myotoxic acidic PLA₂ Asp 49 was isolated from Colombian Bothrops asper venom. It was isolated by high efficiency liquid chromatography and named BaCol PLA₂. It had a molecular weight of 14180.69 Da and an isoelectric point of 4.4. The complete sequenceobtained by cDNA cloning, with access number in the gene bank MF319968; this sequenceevidenced a mature product of 124 amino acids with Asp in 49 position. In vivoassaysin mice demonstrated profuse oedemaand myotoxicity evidenced by increase of creatinakinasa in plasma and severe and diffuse damage to the muscular fibers, further vacuolization and hyalinization necrosis of the sarcoplasm showed by histopathology with hematoxylin and eosin staining of gastrocnemius muscle. In vitro studies showed cell membrane damage without phosphatidylserine exposure, an early apoptosis hallmark. Further BaCol PLA₂ evidenced high indirect hemolytic activityand moderate anticoagulant action. The toxin showed homology with others acidic PLA₂ isolated from Bothrops venoms, including one isolated from B. asper of Costa Rica. Unlike this, BaCol PLA₂ was myotoxic.

Introduction: Leprosy, caused by Mycobacterium leprae is one of the oldest infectious diseases in human history and its eradication is linked to poverty control, lack of basic sanitation, the fragility of health, and education services. Objective: To evaluate the frequency of blood groups (ABO/Rh) and the sociodemographic and clinical profile of Angolan patients with Leprosy treated at the Anti-Tuberculosis and Leprosy Dispensary in Luanda, the capital city of Angola. Methodology: A descriptive, introspective, cross-sectional study with a quantitative approach was carried out with 102 patients of Luanda, in the second half of 2021. Results: Of the 102 patients included in the study, the majority belonged to the ORh+ group (51.9%), followed by the BRh+ group (27.4%) and ARh+ (18.6%), most were under 51 years of age ( 87.3%), with low education (54.9%), coming from urban areas (44.1%). As for clinical conditions, most had a multibacillary infection (93.1%), diagnosed mainly by smear microscopy (75.5%) without other infection (79.4%), some of them with complications (28.4%) and individuals with non-O blood group showed changes in the blood count. Conclusion: Leprosy seems to be common in ORh+ individuals, it continues to affect especially those residing in areas of population agglomerations and with low education, presenting itself as a multibacillary infection, where changes in the blood count are greater in non-O individuals.

Introduction: Soft tissue sarcomas (STS) are low-incidence tumors whose clinical and histopathological factors are associated with adverse oncological outcomes. This study evaluated prognostic factors (PF) associated with tumor recurrence and overall survival (OS) in patients diagnosed with STS of the extremities, treated at the Instituto Nacional de Cancerología (INC), Bogotá, Colombia. Materials and methods: An analytical observational study of a historical cohort was carried out, including patients diagnosed with STS and managed surgically in the Functional Unit for Breast and Soft Tissue Tumors of the INC from January 2008 to December 2018. Results: A total of 227 patients were included; 74.5% had tumors greater than 5 cm. Most patients (29.1%) were in stage IIIB at diagnosis. Age was associated with higher mortality (HR=1.01; CI95%: 1–1.02; p=0.048); tumor persistence at admission to the INC (HR=2.34; CI95%: 1.25–4.35; p=0.007), and histologic grade III (HR=5.36; CI95%: 2.29–12.56; p=<0.001) showed statistical significance in the multivariate analysis for recurrence of any type, as were the PFs associated with a higher risk of local recurrence (HR=2.85; CI95%: 1.23–6.57; p=0.014 and HR=6.09; CI95%: 2.03–18.2; p=0.001), respectively. Tumor size (HR=1.03; CI95%: 1–1.06; p=0.015) and histologic grade III (HR=4.53; CI95%: 1.42–14.49; p=0.011) were associated with a higher risk of distant recurrence. Conclusion: This cohort showed that in addition to histologic grade and tumor size, tumor persistence at the time of admission has an impact on disease recurrence, so STS should be managed by a multidisciplinary team with experience in this pathology in high-volume reference centers.

Vegetable oils contain fatty acids, phenolic compounds, natural antioxidants, and fat-soluble vitamins, which are beneficial against different diseases. Oil extraction methods can, however, affect their composition. This study aims to characterize the chemical composition of oils from two Andean seeds, cañihua (Chenopodium pallidicaule) and tarwi (Lupinus mutabilis), extracted with different organic solvents, petroleum ether, hexane, and ethanol. This study compares these oils with commercial sunflower, rapeseed, and olive oils. Results showed that oils extracted with hexane had the highest yield, while those extracted with ethanol had higher antioxidant activity and total phenolic compound content. Additionally, using ethanol makes the process more sustainable than non-green solvents. The composition of tarwi and cañahua oils extracted with ethanol includes fatty acids, tocopherols, antioxidants, and phenolic compounds associated with health benefits.

Low-frequency audible noise generated by the magnetostriction effect inherent to the operation of power transformers has become a major drawback, especially in cases where the electrical substation is located in urban areas subject to strict environmental regulations that imposes sound pressure limits, differing for day and night periods. Such regulations apply a +5 dB penalty if a tonal component of noise is present, which is clearly the case of magnetostriction noise, typically concentrated at twice the industrial frequency (50 Hz or 60 Hz, depending on the country). The strategy used to eliminate the tonal characteristics, therefore contributing to establish compliance with the applicable regulation and to alleviate the discomfort it causes to the human ear, consisted in superimposing to the substation noise a masking sound synthesized from “sounds of nature” with suitable intensities, to flatten the noise spectrum while enhancing the soundscape. The masking system (heavy-duty speakers powered by a microprocessor platform) was validated at an already judicialized urban scenario. Measurement results confirmed that the masking solution was capable of flattening the tonal frequencies, whose beneficial effect yielded the cancellation of the public civil action filed by the neighbors. The proposed solution is ready to be replicated to other scenarios.

Cattle spread throughout the American continent during the colonization years, originating creole breeds that adapted to a wide range of climate conditions. Population of creole cattle in Peru is decreasing mainly due to the introduction of more productive breeds in recent years. During the last 15 years, there have been a significant progress on cattle genomics. However, little is known about the genetics of the Peruvian creole cattle (PCC) even though its importance to (i) improve productivity in the Andean region, (ii) agricultural labor, and (iii) cultural traditions. In addition, the origin and phylogenetic relationship of the PCC is still unclear. In order to promote the conservation of the PCC, we sequenced for the first time the mitochondrial genome of a creole bull from the highlands of Arequipa, which also possessed exceptional fighting skills and was employed for agricultural tasks. The total mitochondrial genome sequence is 16,339 bp in length with the base composition of 31.43 % for A, 28.64 % for T, 26.81 % for C, and 13.12 % for G. It contains 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes and a control region. Among the 37 genes, 28 were positioned on the H-strand and nine were positioned on the L-strand. The most frequently used codons were CUA (Leucine), AUA (Isoleucine), AUU (Isoleucine), AUC (Isoleucine), y ACA (Threonine). Maximum likelihood reconstruction using complete mitochondrial genome sequences clearly demonstrated that the PCC is strongly related to native African breeds, giving insights into the ancestry of PCC. The annotated mitochondrial genome of PCC would serve as an important genetic data set for further breeding work and conservation strategies.

Molecular iodine (I2) induces apoptotic, antiangiogenic, and antiproliferative effects in breast cancer cells. Little is known about its effects on the tumor immune microenvironment. We studied the effect of oral (5 mg/day) I2 supplementation alone (I2) or together with conventional chemotherapy (Cht+I2) on the im-mune component of breast cancer tumors from a previously published pilot study conducted in Mexico. RNA-seq, I2 and Cht+I2 samples showed significant increases in expression of Th1 and Th17 pathways. Tumor immune composition determined by deconvolution analysis revealed significant increases in M0 macrophages and B lymphocytes in both I2 groups. Real-time RT-PCR showed that I2 tumors overexpress T-BET (p = 0.019) and interferon-gamma (IFNγ; p = 0.020) and silence tumor growth factor-beta (TGFβ; p = 0.049); whereas in Cht+I2 tumors, GATA3 is silenced (p = 0.014). Preliminary methylation analysis shows that I2 activates IFNγ gene promoter (by increasing its unmethylated form) and silences TGFβ in Cht+I2. In conclusion, our data showed that I2 supplements induce the activation of the immune response and that when combined with Cht, the Th1 pathways are stimulated. The molecular mechanisms involved in these responses are being analyzed, but preliminary data suggest that methylation/demethylation mechanisms could also participate.

Coronavirus disease 2019 (COVID-19) is associated with high risk of malnutrition, primarily in elderly people; assessing nutritional risk using appropriate screening tools is critical. This systematic review identified applicable tools and assessed their measurement properties. Literature was searched in the MEDLINE, Embase, and LILACS databases. Four studies conducted in China met the eligibility criteria. Sample sizes ranged from six to 182, and participants’ ages from 65 to 87 years. Seven nutritional screening and assessment tools were used: the Nutritional Risk Screening 2002 (NRS-2002), Mini Nutritional Assessment (MNA), MNA-short form (MNA-sf), Malnutrition Universal Screening Tool (MUST), Nutritional Risk Index (NRI), Geriatric NRI (GNRI), and modified Nutrition Risk in the Critically ill (mNUTRIC) score. Nutritional risk was identified in 27.5% to 100% of participants. The NRS-2002, MNA, MNA-sf, NRI, and MUST demonstrated high sensitivity; the MUST had better specificity. The MNA and MUST demonstrated better criterion validity. The MNA-sf demonstrated better predictive validity for poor appetite and weight loss; the NRS-2002 demonstrated better predictive validity for prolonged hospitalization. mNUTRIC score demonstrated good predictive validity for hospital mortality. Most instruments demonstrate high sensitivity for identifying nutritional risk, but none are acknowledged as the best for nutritional screening in elderly COVID-19 patients.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting both the evolution of this field and its integration to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, the review sheds light on the potential implications of WBT for the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation with the EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

The structure of wound dressing materials presents one of the most relevant characteristics for effective skin tissue repair. Electrospinning is a common technique used to produce polymeric fibres that can mimic fibrillar disposition of skin extracellular matrix, favouring cell migration, and thus regeneration of the damaged tissue. Moreover, beads, also known as by-products of electrospinning, have potential as reservoirs for sustained drug release. Processing parameters, such as molecular weight and viscosity of the polymer solution, can affect the desirable morphologies of electrospun films. Thereby, this work had the purpose of producing and characterized electrospun polycaprolactone (PCL) mats loaded with propolis, a popular extract in traditional medicine with potential for skin repair aid. Films with different morphologies were obtained depending on the storage period of the solution prior to the lectrospinning, probably due to the PCL hydrolysis. FTIR analyses of the extract confirmed propolis composition. GPC and viscosity analyses demonstrated that the decrease in molar mass over the storage period was responsible for nanostructure diversity. Propolis acts as a lubricant agent, affecting the spun solutions' viscosity and the thermal properties and hydrophilicity of the films. All films are within the value range of the water vapour transpiration rate of the commercial products. The presence of beads did not affect the propolis release pattern. However, "in vitro" wound healing assay showed that propolis-loaded films composed by beaded fibres increased the cell migration process. Thus, it can be inferred that these films presented the potential for wound dressing application.

Background: Hantavirus cardiopulmonary syndrome (HCPS) has a high lethality. About two-thirds of the severe cases may be rescued by extracorporeal membrane oxygenation (ECMO). However, about half of the patients supported by ECMO suffer major complications. High volume hemofiltration (HVHF) is a depurative extracorporeal support that provides homeostatic balance allowing hemodynamic stabilization in some critically ill patients. Methods: We implemented HVHF prior to ECMO consideration in the last five severe HCPS patients requiring mechanical ventilation and vasoactive drugs admitted to our intensive care unit. Patients were considered HVHF-responders if ECMO was avoided and nonresponders if ECMO support was needed. Results: The first two patients required ECMO, while the last three did not. Patients had a maximum serum lactate of 8.4 [4.3-14] mMol/L and a lowest cardiac index of 1.76 [1.45-2.9] L/min/m2. Nonresponders were connected later to HVHF, displayed progressive tachycardia and decreasing stroke volume. The opposite was true for HVHF-responders who also received targeted-HVHF compounded by aggressive hyperoncotic albumin, sodium bicarbonate and calcium supplementation plus ultrafiltration to avoid fluid overload. All patients survived, but one of the ECMO patients suffered a vascular complication. Conclusion: HVHF may contribute to support severe HCPS patients avoiding the need for ECMO in some of them. Early connection and targeted-HVHF may increase the chance of success.

Geodetic networks are essential for most geodetic, geodynamics and civil projects, such as monitoring the position and deformation of man-made structures, monitoring the crustal deformation of the Earth, establishing and maintaining a geospatial reference frame, mapping, civil engineering projects and so on. Before the installation of geodetic marks and gathering of survey data, geodetic networks need to be designed according to the pre-established quality criteria. In this study, we present a method for designing geodetic networks based on the concept of reliability. We highlight that the method discards the use of the observation vector of Gauss-Markov model. In fact, the only needs are the geometrical network configuration and the uncertainties of the observations. The aim of the proposed method is to find the optimum configuration of the geodetic control points so that the maximum influence of an outlier on the coordinates of the network is minimum. Here, the concept of Minimal Detectable Bias defines the size of the outlier and its propagation on the parameters is used to describe the external reliability. The proposed method is demonstrated by practical application of one simulated levelling network. We highlight that the method can be applied not only for geodetic network problems, but also in any branch of modern science.

(1) Background: This text emphasizes concerns regarding the safety of Spanish police officers at-tributed to inadequate training, employing biomechanics for the analysis and mitigation of risks during Use of Force training. The elevated global prevalence of musculoskeletal disorders under-scores the imperative for effective occupational health measures. The study concentrates on evalu-ating injury risks in novice police officers during Use of Force training. (2) Research method: The movements of police officers were captured using a Rokoko Smartsuit Pro equipped with 19 sen-sors. The Biomechanics of Bodies software processed the data, providing REBA and Marras risk scores. Statistical tests were conducted, and Operational Tactical Procedures (OTP) were inte-grated into police training. A diverse group of officers participated, categorized by training level and equipped with the Rokoko Smartsuit. (3) Results: The study evaluates police force training us-ing REBA and Marras methods. REBA scores indicate a moderate to high injury risk, suggesting effective technique design. ANOVA reveals no significant differences between training levels. Marras analysis, characterized by non-normal distribution, unveils varied risk perceptions among groups via the Kruskal-Wallis test. (4) Conclusions: The analysis of both the REBA and Marras methods implies the effectiveness of the OTP technique in reducing injury risks across dif-ferent training levels. The ANOVA test indicates no significant differences in REBA Maximum Scores between the groups. However, the Kruskal-Wallis test for Marras Probability of high-risk values suggests distinctions in medians between training levels. The combined analysis visually illustrates variations in membership regions between expert, intermediate, and novice groups.

Plant extracts have been evaluated to determine their bioactivities and their potential use in wound healing. In this study, a conductive composite material, based on graphene oxide (GO), nanocellulose (CNF) and tannins (TA) from pine bark, reduced using polydopamine (PDA), was developed for wound dressing. The amount of CNF and TA was varied in the composite material and a complete characterization including SEM, FTIR, XRD, XPS, TGA was performed. Also, the conductivity, mechanical properties, cytotoxicity, and in vitro wound healing of the materials were evaluated. The results showed a successful physical interaction between CNF, TA and GO. In-creasing the CNF amount in the composite reduced the thermal properties, surface charge and conductivity of the material, but its strength, cytotoxicity and wound healing performance were improved. The TA incorporation slightly reduced the cell viability and migration, which may be associated with the doses used and the chemical composition of the extracts. However, the in vitro obtained results demonstrated that these composite materials can be suitable for wound healing.

The design and engineering of antibacterial materials is key for preventing bacterial adherence and proliferation in biomedical and house-hold instruments. Silver nanoparticles (AgNPs) and chitosan (CHI) are broad-spectrum antibacterial materials with different properties, whose combined application is currently under optimization. This study proposes the formation of antibacterial films with AgNPs embedded in carboxymethylcellulose/chitosan multilayers by the layer-by-layer (LbL) method. The films were deposited onto nanoporous silicon (nPSi), an ideal platform for bioengineering applications, due to its biocompatibility, biodegradability, and bioresorbability. We focus on two alternative multilayer deposition processes: cyclic dip coating (CDC) and cyclic spin coating (CSC). The physicochemical properties of the films were the subject of microscopic, microstructural and surface-interface analyses. The antibacterial activity of each film was investigated against Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive) bacteria strains as model microorganisms. According to the findings, CDC technique produced multilayer films with higher antibacterial activity for both bacteria compared to the CSC method. Bacteria adhesion inhibition was observed from only 3 cycles. The developed AgNPs-multilayer composite film offers advantageous antibacterial properties for biomedical applications.

The generation of eucalypt sawdust has increased in Uruguay with the expansion of pulp and paper industrial sites. Currently, most of this readily available feedstock is either not used or applied for producing heat and power by combustion in biomass boilers. In this work, eucalypt sawdust was subjected to steam explosion as the first step for cellulosic ethanol production within the biorefinery concept. The effect of sawdust moisture content, pretreatment temperature and residence time were evaluated, along with the influence of water washing of steam-exploded solids on enzymatic hydrolysis and fermentation yields. After steam explosion, 60% xylans and 97% acetyl groups were recovered mainly as oligomers and acetic acid in the pretreatment liquor. Eucalypt sawdust moisture content affected the enzymatic hydrolysis performance and glucan conversion efficiency. Water washing after pretreatment improved hydrolysis efficiencies and ethanol production yields by 10% with respect to the unwashed pretreated solids at the same experimental condition. The best ethanol yields were obtained using PSSF (pre-saccharification and simultaneous saccharification and fermentation) after pretreatment at 205°C for 10 min, using sawdust with an 8% moisture content. In this case, 227 L ethanol and 40 kg total xylose (including xylo-oligomers) were obtained per ton of dry eucalypt sawdust.

This paper presents a novel micro-segmented genetic algorithm (μsGA) to identify the best solution for the locomotion of a quadruped robot designed on a rectangular ABS plastic platform. We compare our algorithm with three similar algorithms found in the specialized literature: a standard genetic algorithm (GA), a micro-genetic algorithm (μGA), and a micro artificial immune system (μAIS). The quadruped robot prototype guarantees the same conditions for each test. The platform was developed using 3D printing for the structure and can accommodate the mechanisms, sensors, servomechanisms as actuators. It also has an internal battery and a multicore embedded system (mES) to process and control the robot locomotion. This research proposes a μsGA that segments the individual into specific bytes. μGA techniques are applied to each segment to reduce the processing time; the same benefits as the GA are obtained, while the use of a computer and the high computational resources characteristic of the GA are avoided. This is the reason why some research in robot locomotion is limited to simulation. The results show that the performance of μsGA is better than the three other algorithms (GA, μGA and AIS). The processing time was reduced using a mES architecture that enables parallel processing, meaning that the requirements for resources and memory were reduced. This research solves the problem of continuous locomotion of a quadruped robot, and gives a feasible solution with real performance parameters using a μsGA bio-micro algorithm and a mES architecture.

Vaccination has proven to be one of the most effective strategies against the COVID 19 pandemic. Several studies have evaluated and confirmed its effectiveness in different populations, particularly in reducing severe outcomes such as hospitalization and death. However, the potential of vaccination to protect against infection itself has been overlooked. The aim of this study was to determine the effectiveness of the booster dose in a sample of Colombian patients during the fourth wave of COVID-19 pandemic, which was associated with the emergence and predominance of the Omicron variant. A cross-sectional study was conducted on individuals who underwent RT-PCR testing for COVID-19 detection in a dedicated laboratory in Bogotá, Colombia, between December 30th 2021 and February 7th 2022. A total of 1,468 subjects were included in the study. The comparison between fully vaccinated individuals with a booster dose and those without the booster dose revealed a 28% reduction in the odds of infection (OR = 0.719 CI 0.531 - 0.971). Age (OR = 1,009 CI 1,001 - 1,018) and low economic status (OR= 1,812 CI 1,416- 2,319) were associated with an increased risk of infection.These findings suggest the need for booster vaccination in the general population to improve the prevention rates of SARS-CoV-2 infection and mitigate severe outcomes.

Atherogenesis and dyslipidemia increase the risk of cardiovascular disease, which is the leading cause of death in developed countries. While blood lipid levels have been studied as disease predictors, their accuracy in predicting cardiovascular risk is limited due to its high interindividual and interpopulation variability. The lipid ratios: atherogenic index of plasma (AIP=log TG/HDL-C) and the Castelli risk index 2 (CI2=LDL-C/HDL-C) have been proposed as better predictors of cardiovascular risk, but the genetic variability associated to these ratios has not been investigated. This study aimed to identify genetic associations with these indexes. The study population (n=426) included males (40%) and females (60%) aged 18-52 years (mean 39 years), the Infinium GSA array was used for genotyping. Regression models were developed using R and PLINK. AIP was associated with variation on APOC3, KCND3, CYBA, CCDC141/TTN, and ARRB1 (p-value < 2.1E-6) the three former previously associated to blood lipids, while CI2 was associated with variants on DIPK2B, LIPC, and 10q21.3 rs11251177 (p-value 1.1E-7) the latter previously linked to coronary atherosclerosis and hypertension. KCND3 rs6703437 was associated with both indexes. This study is the first to characterize the potential link between genetic variation and atherogenic indexes, AIP and CI2, highlighting the relation between genetic variation and dyslipidemia predictors. These results also contribute to consolidating the genetics of blood lipid and lipid indexes.

Our study examines how dengue incidence is associated with spatial (demographic and socioeconomic) alongside temporal (environmental) factors at multiple scales. We used the incidence of dengue in Ibagué, Colombia, from 2013 to 2018, to examine the associations with climate, socioeconomic and demographic factors from the census and satellite imagery at various levels of local spatial aggregation, including Manzanas, Secciones, Sectores, and Comunas. Our findings show a significant effect of spatial variables at finer levels of aggregation, showing varying degrees of correlation with dengue incidence. Temporal variables such as temperature and precipitation displayed consistent patterns across all spatial levels, with notable variations in Relative Risk (RR). Our study employs Geographically Weighted Regression (GWR) to identify relevant socioeconomic and demographic predictors. Then, these predictors were integrated into hierarchical models implemented in Integrated Nested Laplace Approximation (INLA) at each spatial level to assess spatiotemporal interactions. We comprehensively analyzed the three distinct models developed for each level: spatial, temporal, and spatiotemporal. A comparative evaluation of the models reveals that while higher aggregation levels often yield a better overall model fit, finer levels offer more detailed insights into the localized impacts of socioeconomic and demographic variables on dengue incidence. Our results underscore the importance of considering macro and micro-level factors in epidemiological modeling and highlight the potential for targeted public health interventions based on localized risk factor analysis. Notably, the intermediate level Secciones emerged as the most informative, balancing spatial heterogeneity and case distribution density, thereby providing a robust framework for understanding the spatial determinants of dengue.

Currently, various industrial processes are carried out in fluidized bed reactors, such as fermentation, water treatment, and algae growth. Knowing its internal dynamics is fundamental for the intensification of these processes. This work assesses the motion of fluidized calcium alginate spheres under the influence of an upward fluid flow within a 1.2 m high and 0.1 m inner diameter acrylic column. The Radioactive Particle Tracking technique is a proper methodology to study the internal dynamics of these kinds of equipment. Liquid-Solid Fluidized Bed is compared with the Gas-Liquid-Solid Fluidized Bed operation mode in terms of mixing behavior. Data gathered is analyzed in view of Shannon entropy as a dynamic mixing measure. Mixing times are found to be of the same order of magnitude. However, the Liquid-Solid Fluidized Bed achieves a lower homogenization degree. Also, we found good agreement between two criteria for assessing stability for the mixed state: the Shannon Entropy time-series plateau and the Glansdorff-Prigogine criterion based on Fisher information.

Members of the Fusarium oxysporum species complex (FOSC) has the capacity to specialize into host-specific pathogens known as formae speciales through horizontal gene transfer between pathogenic and endophytic individuals. To this day, the origin of these formae speciales and the genetic determinants dictating the switch from endophytic to pathogenic Fusarium oxysporum (Fox) are still unknown. F. oxysporum f. sp. vanillae (Fov), member of FOSC, is the causal agent of root and stem rot disease, representing the main phytosanitary problem in vanilla plantations worldwide. Here we analyzed the RNA-seq libraries resulting from the interaction vanilla-Fov at early and late stages of the infection, and what we initially identified as control in a previous study, detecting the presence of Fox endophytes. We identified virulence, hypervirulence, sporulation, conidiation, necrosis, and production of fusaric acid as key processes taking place during Fov-vanilla interaction. Through comparison with endophytic Fox, we found that Fov can infect vanilla thanks to the presence of pathogenicity islands and genomic regions associated with supernumerary chromosomes. These play a central role as carriers of genes involved with pathogenic activity and could have being obtained by Fov through horizontal gene transfer. We also found that, unlike other pathogenic members of FOSC, Fov do not use Secreted in Xylem proteins (SIX) to infect vanilla.

Our aim was to determine the secondary antibody deficiency profiles of patients in a mesoregion of São Paulo state, Brazil, focusing on infectious diseases. Demographic characteristics, clinical and laboratory data were obtained from electronic files; infections were classified as organ-specific and graded as mild, moderate, life-threatening, and fatal. Non-Hodgkin lymphoma (NHL) accounted for 30% of patients, nephrotic syndrome (NS) 25%; chronic lymphocyte leukemia 20%, and multiple myeloma 15%. Patients with NS were younger than those in other groups, and hypo-γ-globulinemia was detected in 94.1%, IgG <400 mg/dL in 60.0%, IgA <40 mg/dL in 55.0%, and CD19 <20 cells/mm³ in 30.0%. One hundred and one infections were found; 82.1% were classified as mild or moderate, 7.9% as life-threatening, and 1.9% as fatal. Respiratory tract infections were more prevalent (41.5%), and pneumonia accounted for 19.8%. Lower levels of infections were found in patients with NS compared with NHL (P=0.0001). Most patients progressed to hypo-γ-globulinemia and secondary antibody deficiency after treatment with immunosuppressants, and mild and moderate infections were predominant. These therapies are increasing in patients with different diseases, therefore monitoring hypo-γ-globulinemia and infections may help to identify patients at high risk for severe complications, antibiotic prophylaxis or treatment, and immunoglobulin replacement

Air pollution includes particle-bound Polycyclic Aromatic hydrocarbons (PAHs) which eventually reach the placenta triggering adverse perinatal outcomes by long-term exposure. Late-ly, air pollution has increased over the Metropolitan Area of Medellin-Colombia (MAMC) but its effects on pregnancy are still unknown. In this research, we made a real-time analysis of airborne total PAHs using a photoelectric sensor for residential places influenced by industrial and traffic sources contrasting southern and northern MAMC during the second peak of the bimodal ten-dency for PM2.5 emissions in this region. Additionally, we analyzed individual PAHs by GC/MS coupled to pressurized hot water extraction methodology. Data was applied in an Inhalation In-take Model to assess pregnancy exposure. The average concentration of PAHs over southern MAMC was three times higher than over northern MAMC where the abortion rate has been 1.4 times higher presented in database. Previous research found that PAHs act as an Endo-crine-Disrupting Chemical (EDC) during pregnancy and even heavy congeners could reside in umbilical cord blood. Finally, the annual series of abortion rates in the MAMC showed a signifi-cant correlation with the annual average levels of PM2.5 which are associate to PAHs. Although this significant correlation does not imply causality, our results suggest an important connection between both variables. This latter finding opens a gap in deeply understanding how regions with high PAHs-convergence influences abortion rates in MAMC.

Objetives: Adequate donor-recipient matching is necessary to achieve the best renal function after transplantation. The nephron load received from the donor, which can be reflected in variables such as age, sex and body mass index, may influence the evolution of the graft. Our objetive was develop a combined score according to the donor-recipient pairing in age, sex and body mass index, and assess its influence on the evolution of the renal graft. Materials and methods: Transplant patients between 2013 and 2020 who had at least 1 year of post-transplant follow-up. A ranking of 0 to 2 points was awarded according to the match between donor and recipient for sex, age and body mass index individually, with higher rank to greater mismatch. Subsequently, a Score with value of 0 to 6 points was created with the combined ranking of the indivudual variables, analyzing its influence on the evolution of the graft by multivariate linear regression. Results: 280 patients followed for 4.3 years of median. Worse renal function was observed at the end of follow-up as the range of each variable increased separately, and the Score created, with a worsening of renal function as the combined Score increased in the multivariate analysis: Coefficient B= -2.4 ml/min, p=0.018. Conclusions: An adequate match between donor and recipient in age, sex and body mass index using this combined Score can help achieve better kidney function after transplantation.

Three-phase induction motors play a key role in industrial operations. However, their failure can result in serious operational problems. This study focuses on the early identification of faults through accurate diagnosis and classification of faults in three-phase induction motors, using artificial intelligence techniques, by analyzing current, temperature, and vibration signals. Experiments were conducted on a test bench, simulating real operating conditions, including stator phase unbalance, bearing damage and shaft unbalance. To classify the faults, an Auto-Regressive Neural Network with Exogenous Inputs (NARX) was developed. The parameters of this network were determined through a process of selecting the best network, using the scanning method with multiple training and validation iterations, with the introduction of new data. The results of these tests showed that the network had excellent generalization in all the situations evaluated, achieving the following accuracy rates: Motor without fault = 94.2%, Unbalance fault = 95%, Bearings with fault =98% and Stator with fault = 95%.

Plantago major L. is a worldwide available plant that has been used traditionally for several medical application due to its properties such as wound healing, anti-inflammatory, antimicrobial etc. This work aimed to develop and evaluate nanostructured PCL electrospun dressing with P. major extract encapsulated in nanofibers for application in wound healing. The extract from leaves was obtained by extraction in a mixture of water:ethanol= 1:1 of the freeze-dried extract presented a minimum inhibitory concentration (MIC) for Staphylococcus Aureus susceptible and resistant to methicillin of 5.3 mg/mL, a high antioxidant capacity, but a low content of total flavonoids. Electrospun mats without defects were successfully produced using two P. major extract concentrations based on MIC value. The extract incorporation in PCL nanofibers was confirmed by FTIR and contact angle measurements. The PCL/P. major extract was evaluated by DSC and TGA demonstrating that incorporation of the extract decreases the thermal stability of the mats as well as the degree of crystallinity of PCL-based fibers. The P. major extract incorporation on electrospun mats produced a significant swelling degree (more than 400%) and increased the capacity of adsorbing wound exudates and moisture, important characteristics for skin healing. The extract-controlled release evaluated by in vitro study in PBS (pH, 7.4) shows that P. major extract delivery from the mats occurs in the first 24 h, demonstrating their potential capacity to be used in wound healing.

Diabetes mellitus entails increased atherosclerotic burden and medial arterial calcification but the precise mechanisms are not fully elucidated. Our aim was to investigate the implication of CD36 in inflammation and calcification processes orchestrated by vascular smooth muscle cells (VSMCs) under hyperglycemic and atherogenic conditions. We examined the expression of CD36, pro-inflammatory cytokines, endoplasmic reticulum (ER) stress markers and mineralization-regulating enzymes by RT-PCR in human VSMCs, cultured in medium containing normal (5 mM) or high glucose (22 mM) for 72 h with or without oxLDL (24 h). The uptake of DiI-labelled oxLDL was quantified by flow citometry and fluorimetry and calcification assays were performed in VSMC cultured in osteogenic medium and stained by alizarin red. We observed an induction in the expression of CD36, cytokines, calcification markers and ER stress markers under high glucose that was exacerbated by oxLDL. These results were confirmed in carotid plaques from subjects with diabetes versus non-diabetic subjects. Accordingly, the uptake of DiI-labelled oxLDL was increased after exposure to high glucose. Silencing of CD36 abolished the induction of CD36 and reduced the expression of calcification enzymes and mineralization of VSMC. Our results indicate that CD36 signaling is involved in hyperglycemia and oxLDL-induced vascular calcification in diabetes.

Recent advancements in Artificial Intelligence (AI), Deep Learning (DL), and computer vision have revolutionized various industrial processes through image classification and object detection. State-of-the-art Optical Character Recognition (OCR) and Object Detection (OD) technologies, such as YOLO and PaddleOCR, have emerged as powerful solutions for addressing challenges in recognizing textual and non-textual information on printed stickers. However, a well-established framework integrating these cutting-edge technologies for industrial applications still needs to be discovered. In this paper, we propose an innovative framework that combines advanced OCR and OD techniques to automate visual inspection processes in an industrial context. Our primary contribution is a comprehensive framework adept at detecting and recognizing textual and non-textual information on printed stickers within a company, harnessing the latest AI tools and technologies for sticker information recognition. Our experiments reveal an overall macro accuracy of 0.88 for the sticker OCR across three distinct patterns. Furthermore, the proposed system goes beyond traditional Printed Character Recognition (PCR) by extracting supplementary information, such as barcodes and QR codes present in the image, significantly streamlining industrial workflows and minimizing manual labor demands.

Leptospirosis is a re-emerging zoonotic disease that has had an unprecedented impact on most health systems in the world. The spectrum of symptoms is variable and usually ranges from asymptomatic cases to severe manifestations involving multiple organ dysfunction accompanied by jaundice, hemorrhage, meningitis, and acute kidney injury that requires the need for intensive care assistance. Although early antibiotic treatment is usually effective, in severe cases it may require renal replacement therapy, invasive mechanical ventilation, vasoactive support, and invasive hemodynamic monitoring, increasing the risk of death. In Latin America, the real burden of acute kidney injury in this condition is unknown and may be underestimated due to the rapid progression of the disease, similar to other vector zoonoses, and the low coverage of diagnostic tests in primary care, especially in rural regions. Therefore, below, we review the clinical aspects and describe the scientific, clinical, and therapeutic evidence of acute kidney injury attributed to Leptospira spp. and its relevance in patients with severe leptospirosis in Latin America.

Follicular helper CD4+ T cells (TFH) are a major cellular pool for the maintenance of HIV reservoir. Therefore, the delineation of the follicular (F)/germinal center (GC) immune landscape will significantly advance our understanding of HIV pathogenesis. We have applied multiplex confocal imaging, in combination with relevant computational tools, to investigate, F/GC in situ immune dynamics in viremic (vir-HIV), antiretroviral treated (cART HIV) People Living With HIV (PLWH) and compare them to reactive, non-infected controls. Lymph nodes (LNs) from viremic and cART PLWH could be further grouped based on their TFH cell densities in high-TFH and low-TFH subgroups. These subgroups were also characterized by different in situ distribution of PD1hi TFH cells. The significantly accumulated follicular, compared to extrafollicular, FOXP3hi CD4+ T cells found in the low-TFH cART-HIV group were characterized by a less scattered in situ distribution and strongly correlated with the cell density of CD8+ T cells in this group. An inverse correlation between plasma viral load and LN GrzBhiCD8+ T and CD16hiCD15lo cells was found. Our data reveal the complex GC immune landscaping in HIV infection and suggest that follicular FOXP3hi CD4+ T cells could be negative regulators of TFH cell prevalence in cART-HIV.

Excess energy from photosynthesis can be collected through biophotovoltaic platforms to generate green electrical power. This research evaluated the in-situ performance of different CAM (Crassulaceae acid metabolism) plants from Calama city located in the Atacama Desert for energy recovery as biophotovoltaic cell (BPV) using AISI 316L and Cu as electrodes. The species evaluated were Aloe perfoliata, Cereus jamacaru, Austrocylindropuntia subulata, Agave potatorum, Malephora crocea, and Kalanchoe daigremontiana. The results indicate that K. daigremontiana can be used as in-situ BFV because it has a maximum cell potential of 0.248 V and a minimum of 0.139 V with a recurrence close to 89% in the ranges [0.2 - 0.25] V. This is one of the few investigations that evaluate the potential of native CAM plants as BFV energy sources, providing new knowledge for the development of sustainable alternatives for horticultural crop production systems.

Introduction: The SARS-CoV-2/COVID-19 pandemic has triggered the need for developing rapidly effective and safety vaccines to prevent infection, particularly in those at-risk populations such as medical personnel. The objective of this study was to assess perception of COVID-19 vaccination amongst Colombian physicians featuring two different sceneries of COVID-19 vaccination. Methods: A cross-sectional analytical study was carried out through an online survey, directed at medical staff in several cities in Colombia. The percentage of physicians who have a positive perception to be vaccinated and the associated factors that determine that decision were determined. A binomial regression analysis adjusted for age and sex was carried out, taking as a dependent variable the acceptance of free vaccination with an effectiveness of 60 and 80%. The most significant factors were determined in the non-acceptance of vaccination. Results: Between 77.1% and 90.8% of physicians in Colombia, accept COVID-19 vaccination, according to the scenario evaluated where the effectiveness of the vaccine was 60 or 80%, respectively. Medical specialty, have ever paid for a vaccine, recommend administrating the vaccine to their parents or people over 70 years and dispense the vaccine to their children were the factors to be vaccinated for free with an effectiveness of 60% and 80%. Conclusions: There is a high perception of the intention to vaccinate physicians in Colombia against COVID-19. But it is very similar to that of the general population, according to results reported in other studies.

The study of neurodegenerative diseases using pluripotent stem cells requires new methods to assess neurodevelopment and neurodegeneration of specific neuronal subtypes. The cholinergic system, characterized by its use of the neurotransmitter acetylcholine, is one of the first to degenerate in Alzheimer’s disease and is also affected in frontotemporal dementia. We developed a differentiation protocol to generate basal forebrain cholinergic neurons (BFCNs) from induced pluripotent stem cells (iPSCs) aided by the use of small molecule inhibitors and growth factors. Ten iPSC lines were successfully differentiated into BFCNs using this protocol. The neuronal cultures were characterised through RNA and protein expression, and functional analysis of neurons was confirmed by whole-cell patch clamp. We have developed a reliable protocol using only small molecule inhibitors and growth factors, while avoiding transfection or cell sorting methods, to achieve a BFCN culture that expresses the characteristic markers of cholinergic neurons.

In the present work, the interactions between hydrocortisone and cyclodextrins were investigated. The cyclodextrins selected for this study were hydroxypropyl-α-cyclodextrin, hydroxypropyl-β-cyclodextrin and hydroxypropyl-γ-cyclodextrin. The study was carried out using density measurements, 1H-NMR and FT-IR spectroscopy. Preliminary studies show that hydroxypropyl-α-cyclodextrin has a low affinity for hydrocortisone, while hydroxypropyl-β-cyclodextrin and hydroxypropyl-γ-cyclodextrin have a good affinity for hydrocortisone in both solid state and solution. The study was carried out at two temperatures: 298.15 K and 310.15 K. The results suggest that at both temperatures, the system 2-HP-β-CD + HC induces an increase in the solvent structure, with increasing the solute concentration in the solution, while on the contrary the system 2-HP-γ-CD + HC induces a decrease in the solvent structure when the concentration of the solute in the system increases.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

: Immune checkpoint inhibitors (ICI) cemiplimab and pembrolizumab have revolutionized the treatment of advanced cutaneous squamous cell carcinoma (cSCC). We aimed to evaluate the effectiveness and safety of ICI in a real-world cSCC population, including patients with conditions which would exclude clinical trial participation. In this single-center, retrospective cohort study, we included all non-trial patients with advanced cSCC treated with ICI between 2017 and 2022. We evaluated investigator-assessed best overall response (BOR) and immune-related adverse events (irAEs). We correlated survival outcomes with age, performance status, immune status and irAEs. For the 36 patients identified, best overall response (BOR) to ICI was partial response (PR) in 41.7%, complete response (CR) in 27.8%, and stable disease in (SD) 13.9% of patients. The PFS rate at 1 year was 63%; median PFS was not reached (NR). The median OS was 38.6 months (95% CI 25.4-NR). Immune compromised patients, ECOG performance 2-3, and age ≥75 years were not significantly associated with PFS or OS. IrAE grade 3-4 were seen in 13.9% of patients. In our Canadian experience with real-world patients, ICI was an effective and safe treatment for advanced cSCC patients. Patients achieved great benefit with ICI regardless of age, immune status or ECOG performance status.

Expression of miR-21 has been found to be altered in almost all types of cancers and it has been classified as an oncogenic microRNA. In addition, expression of tumor suppressor gene RECK is associated with miR-21 overexpression in high-grade cervical lesions. In the present study we analyze the role of miR-21 in RECK gene regulation in cervical cancer cells. To identify the downstream cellular target genes of upstream miR-21, we silenced endogenous miR-21 expression using siRNAs. We analyzed the expression of miR-21 and RECK, as well as functional effects on cell proliferation and migration. We found that in cervical cancer cells there was an inverse correlation between miR-21 expression and RECK mRNA and protein expression. SiRNAs to miR-21 increased luciferase reporter activity in construct plasmids containing the RECK-3′-UTR microRNA response elements MRE21-1, MRE21-2, and MRE21-3. The role of miR-21 in cell proliferation was also analyzed and cancer cells transfected with siRNAs exhibited a markedly reduced cell proliferation and migration. Our findings indicate that miR-21 post-transcriptionally down-regulates the expression of RECK to promote cell proliferation and cell migration inhibition in cervical cancer cell survival. Therefore, miR-21 and RECK may be potential therapeutic targets in gene therapy for cervical cancer.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

Hydrogels are three-dimensional crosslinked materials known for their ability to absorb water, exhibit high flexibility, biodegradability, biocompatibility, and mimic properties of different tissues in the body. However, their application is limited by inherent deficiencies in mechanical properties. To address this issue, reduced graphene oxide (rGO) and tannins (TA) were incorporated into alginate hydrogels (Alg) to evaluate the impact of the concentration of these nanomaterials on mechanical and adhesive, as well as cytotoxicity and wound healing properties. Tensile mechanical tests demonstrated improvements in tensile strength, elastic modulus, and toughness upon the incorporation of rGO and TA. Additionally, the inclusion of these materials allowed a greater energy dissipation during continuous charge-discharge cycles. However, the samples did not exhibit self-recovery under environmental conditions. Adhesion was evaluated on pig skin, revealing that higher concentrations of rGO led to enhanced adhesion, while the concentration of TA did not significantly affect this property. Moreover, adhesion remained consistent after 10 adhesion cycles, and contact time before the separation between the material and the surface did not affect this property. The materials were not cytotoxic and promoted healing in human fibroblast model cells. Thus, an Alg/rGO/TA hydrogel with enhanced mechanical, adhesive, and wound healing properties was successfully developed.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.