Floods are some of the most devastating crop disasters in Southeast Asia. The Pampanga River Basin in the Philippines is a representative flood-prone area, where cultivation patterns are varied according to the flood risk. However, quantitative analyses on the effects of flooding on cultivation patterns remain quite limited. Accordingly, this study analyzes MODIS LAI data (MCD15A2H) from 2007 to 2022 to evaluate annual and geographical differences in cultivation patterns in the Candaba municipality of the basin. The analysis consists of two stages of hierarchical clustering: a first stage for area classification and a second stage for the classification of annual LAI dynamics. As a result, Candaba is divided into four areas, which are found to be partly consistent with the observed flood risk. Subsequently, the annual LAI dynamics in each area are divided into two or three clusters. The obvious differences among the clusters are caused by flooding in the late rainy season, delaying the start of planting in the dry season. The clusters also indicate that the cultivation patterns slightly changed over the 16 years of the study period. The results of this study suggest that the two-stage clustering approach provides an effective tool for the analysis of MODIS LAI data when considering cultivation patterns characterized by annual and geographical differences.

Use of porous titanium (Ti) and Ti alloys in orthopedic implants or in light structures requires processing routes that could generate an as-much-as possible control in the pores amount, shape, size and connectivity. In this work, a colloidal approach to the processing of Ti porous structures by the inside foaming of a porogen into a gelled high solid content aqueous suspension of Ti powders, is presented. The prepared slurries contained different amounts of Methyl Cellulose (MC) as gelling agent (8, 10 and 12 g/L) and ammonium bicarbonate (BA) as porogen (15, 20, 25 wt. %). The gel-casted samples were heated at mild temperatures ranging (60, 70 and 80 °C) to promote the gelation and produce, at the same time, the porosity by the thermal decomposition of the ammonium bicarbonate. Different structures are obtained depending on the combination of the study variables

Dunaliella salina is a rich source of 9-cis β-carotene, which has been identified as important in the treatment of retinal dystrophies and other diseases. We previously showed that chlorophyll absorption of red light photons in D. salina is coupled to oxygen reduction and phytoene desaturation and increases the pool size of β-carotene [1]. Here we show for the first time that growth under red light also controls conversion of extant all-trans β-carotene to 9-cis β-carotene by β-carotene isomerases. Cells illuminated with red light from a light emitting diode (LED) during cultivation contained a higher 9-cis β-carotene content compared to cells illuminated with white or blue LED light. The 9-cis/all-trans β-carotene ratio in red light treated cultures reached >2.5:1 within 48 hours and was independent of light intensity. Illumination using red light filters that eliminated blue wavelength light also increased the 9-cis/all-trans β-carotene ratio. With norflurazon, a phytoene desaturase inhibitor which blocked downstream biosynthesis of β-carotene, extant all-trans β-carotene was converted to 9-cis β-carotene during growth with red light and the 9-cis/all-trans β-carotene ratio was ~2:1. With blue light under the same conditions, 9-cis β-carotene was likely destroyed at a greater rate than all-trans β-carotene (9-cis/all-trans ratio 0.5:1). Red light perception by the red light photoreceptor, phytochrome, may increase the pool size of anti-oxidant, specifically 9-cis β-carotene, both by upregulating phytoene synthase to increase the rate of biosynthesis of β-carotene and to reduce the rate of formation of reactive oxygen species (ROS), and by upregulating β-carotene isomerases to convert extant all-trans β-carotene to 9-cis β-carotene.

We reelaborate on the basic properties of PT symmetry from a geometrical Perspective. The transfer matrix associated with these systems induces a Möbius transformation in the complex plane. The trace of this matrix classifies the actions into three types that represent rotations, translations, and parallel displacements. We find that a PT invariant system can be pictured as a complex conjugation followed by an inversion in a circle. We elucidate the physical meaning of these geometrical operations and link them with measurable properties of the system.

The constitutively active tyrosine kinase BCR/ABL1 oncogene plays a key role in human chronic myeloid leukemia development and disease maintenance, and determines most of the features of this leukemia. For this reason, tyrosine kinase inhibitors are the first-line treatment, offering most patients a life expectancy like that of an equivalent healthy person. However, since the oncogene is not destroyed, lifelong oral medication is essential, even though this trigger adverse effects in many patients. Furthermore, leukemic stem cells remain quiescent and resistance is observed in approximately 25% of patients. Thus, new therapeutic alternatives are still needed. In this scenario, the emergence of CRISPR technology can offer a definitive treatment based on its capacity to disrupt coding sequences. This review describes CML disease and the main advances in the genome-editing field by which it may be treated in the future.

Phytoene is a colourless natural carotenoid that absorbs UV light and provides antioxidant and anti-inflammatory activities as well as protection against photodamage. It is therefore valued for its skin health and aesthetic benefits by the cosmetic industry, as well as by the health food sector. The halotolerant green microalga Dunaliella salina is one of the richest sources of natural carotenoids. We have previously investigated over-production of phytoene in D. salina after cultivation with the well-characterised mitosis inhibitor, chlorpropham. In this study, 15 herbicides with different modes of action were tested for their potential to promote phytoene accumulation. All herbicides showed different levels of capabilities to support phytoene over-production in D. salina. Most significantly, the two mitosis inhibitors tested in this study, propyzamide and chlorpropham, showed similar capacities to support over-production of phytoene by D. salina cultures, as phytoene desaturase inhibitors. The cellular content of phytoene increased by over 10-fold within 48 h after treatment with the mitosis inhibitors compared to untreated cultures. Results indicate a general effect of mitosis inhibitors on phytoene accumulation in D. salina. Furthermore, red light was found to significantly enhance the phytoene yield when used in combination with effective inhibitor treatments. Red light can be applied to maximize the production of phytoene from D. salina.

The halotolerant photoautotrophic marine microalga Dunaliella salina is one of the richest sources of natural carotenoids. Here we investigated the effects of high intensity blue, red and white light from light emitting diodes (LED) on the production of carotenoids by strains of D. salina under nutrient sufficiency and strict temperature control favouring growth. Growth in high intensity red light was associated with carotenoid accumulation and a high rate of oxygen uptake. On transfer to blue light, a massive drop in carotenoid content was recorded along with very high rates of photo-oxidation. In high intensity blue light, growth was maintained at the same rate as in red or white light, but without carotenoid accumulation; transfer to red light stimulated a small increase in carotenoid content. The data support chlorophyll absorption of red light photons to reduce plastoquinone in photosystem II, coupled to phytoene desaturation by plastoquinol:oxygen oxidoreductase, with oxygen as electron acceptor. Partitioning of electrons between photosynthesis and carotenoid biosynthesis would depend on both red photon flux intensity and phytoene synthase upregulation by the red light photoreceptor, phytochrome. Red light control of carotenoid biosynthesis and accumulation reduces the rate of formation of reactive oxygen species (ROS) as well as increases the pool size of anti-oxidant.

The pregnane X receptor (PXR) is the main nuclear receptor regulating the expression of xenobiotic metabolizing enzymes and is highly expressed in the liver and intestine. Recent studies have highlighted its additional role in lipid homeostasis, however, the mechanisms of these regulations are not fully elucidated. We investigated the transcriptomic signature of PXR activation in the liver of adult wild-type vs Pxr-/- C57Bl6/J male mice treated with the rodent specific ligand pregnenolone 16α-carbonitrile (PCN). PXR activation increased liver triglyceride accumulation and significantly regulated the expression of 1215 genes mostly xenobiotic metabolizing enzymes. Among the down-regulated genes, we identified a strong peroxisome proliferator-activated receptor α (PPARα) signature. Comparison of this signature with a list of fasting-induced PPARα target genes confirmed that PXR activation decreased the expression of more than 25 PPARα target genes, among which the hepatokine fibroblast growth factor 21 (Fgf21). PXR activation abolished plasmatic levels of FGF21. We provide a comprehensive signature of PXR activation in the liver and identify new PXR target genes that might be involved in the steatogenic effect of PXR. Moreover, we show that PXR activation down-regulates hepatic PPARα activity and FGF21 circulation, which could participate in the pleiotropic role of PXR in energy homeostasis.

Prediction of crop yield is essential for food security policymaking, planning, and trade. The objective of the current study is to propose novel crop yield prediction models based on hybrid machine learning methods. In this study, the performance of artificial neural networks-imperialist competitive algorithm (ANN-ICA) and artificial neural networks-gray wolf optimizer (ANN-GWO) models for the crop yield prediction is evaluated. According to the results, ANNGWO, with R of 0.48, RMSE of 3.19, and MEA of 26.65, proved a better performance in the crop yield prediction compared to the ANN-ICA model. The results can be used by either practitioners, researchers or policymakers for food security.

The properties of photonic quasicrystals ultimate rely on their inherent long-range order, a hallmark that can be quantified in many ways depending on the specific aspects to be studied. We use the Lempel-Ziv measure, a basic tool for information theoretic problems, to characterize the complexity of the specific structure under consideration. Using the generalized Fibonacci quasicrystals as our thread, we adress the relation between the optical response and the associated complexity.

Bronchopulmonary dysplasia (BPD) is a form of chronic lung disease that develops in neonates as a consequence of preterm birth and arrested fetal lung development. The incidence of BPD remains on the rise, as a result of increasing survival of extremely preterm infants. Severe BPD contributes to significant health care costs and is associated with prolonged hospitalizations, respiratory infections, and neurodevelopmental deficits. In this study, we aimed to detect novel biomarkers of severe BPD. We collected tracheal aspirates (TA) from preterm babies with mild/moderate (n = 8) and severe (n = 17) BPD, and we profiled the expression of 1048 miRNAs using a PCR array. Associations with biological pathways were determined with the Ingenuity Pathway Analysis (IPA) software. We found 31 miRNAs differentially expressed between the two disease groups (2-fold change, FDR < 0.05). Of these, 4 miRNAs displayed significantly higher expression levels, and 27 miRNAs had significantly lower expression levels in the severe BPD vs. the mild/moderate BPD group. IPA identified cell signaling and inflammation pathways associated with miRNA signatures. We conclude that TAs of extreme premature infants contain miRNA signatures associated with severe BPD. These signatures may serve as biomarkers of disease severity in infants with BPD.

The learning equations of an ANN are presented, giving an extremely concise derivation based on the principle of backpropagation through the descendent gradient. Then, a reflection is developed on the dual attention network that applies the learning equations and coordinates subnetworks toward purposeful behaviors. Speculation is made on possible developments of functionalities that could provide additional skills and at the same time shed light on competencies typical of ``natural intelligence".

In the last two decades, the discovery of various pathways involved in renal cell carcinoma (RCC) have led to the development of biologically-driven targeted therapies. Hypoxia inducible factors (HIFs), angiogenic growth factors, von Hippel-Lindau (VHL) gene mutations and oncogenic miRNAs play essential roles in the pathogenesis and drug resistance of clear cell renal cell carcinoma. These insights have led to the development of VEGF inhibitors, mTOR inhibitors and immunotherapeutic agents which have significantly improved outcomes of patients with advanced RCC. HIF inhibitors will be a valuable asset in the growing therapeutic armamentarium of RCC. Various histone deacetylase (HDAC)inhibitors, including selenium and agents such as PT2385 and PT2977, are being explored in various clinical trials as potential HIF inhibitors to ameliorate the outcomes of RCC patients. In this article, we will review the current treatment options and highlight the potential role of selenium in the modulation of drug resistance biomarkers expressed in ccRCC tumors.

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing distance away from the Madre de Dios headwaters (as the crow flies), did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

World Health Organization (WHO) has announced the monkeypox (MPX) epidemic a global public health emergency due to its re-emergence, remarkable increase in the number of MPX cases worldwide, and its potential spread. This paper introduces the symptoms, complications, and features of MPX; its transmission, diagnosis and testing, vaccines and treatment; MPX and sexually transmitted diseases, especially the human immunodeficiency virus (HIV); possible natural hosts or reservoirs of the monkeypox virus (MPXV). A useful tool for MPX and surgical safety recommendations are presented. The challenges in fighting the MPX epidemic, One Health strategy, and future research are discussed.

The megacities´ sewage creates socioeconomic dependence related to water availability in the nearby zones, especially in countries with hydric stress. The present paper studies the water balance progression of realistic scenarios from 2005 to 2050 in the Mezquital Valley, the receptor of Mexico City untreated sewage since 1886, allowing agriculture irrigation in unsustainable conditions. WEAP model calculated the water demand and supply. Validation was performed with outflows data of the Tula River and simulated three scenarios: 1st) Steady-state based on inertial growth rates, 2nd) Transient scenario concerned climate change outcomes, with minor influence in surface water and hydric stress in 2050; 3rd) Transient scenario perturbed with a planned reduction of 36% in the imported wastewater and the start-up of a massive Water Treatment Plant, allowing drip and sprinkler irrigation since 2030. In the 2005-2017 period, 59% of the agriculture depended on the flood irrigation with megacity sewage. The water balance scenarios evaluated the sectorial supply of the ground and superficial water. Drip irrigation would reduce 42% of agriculture demands, but still does not grant the downflow hydroelectric requirements, aggravated by the lack of wastewater supply since 2030. This research alerts about how present policies compromise future Valley demands.

Incidental P losses from non-point sources may contribute to eutrophication and to decreased soil fertility. These incidents have been related to heavy rainfall on freshly fertilized agricultural soils and little is known about such incidents on more natural soils or in forests. The aim of this work is to determine if incidents of high P leaching also occur in spruce forests, and if such incidents are of significance in P cycling. We found a peak in the mineral soil solution showing that single events of high P leaching occur. The orthophosphate concentration in the Bf-horizon of the 80-year old spruce forest peaked in the autumn of the second year of a continuous monitoring. The concentration increased by more than 85 times compared to the highest concentration obtained earlier during the sampling. The amount leached during this 6 months peak is 10 times higher than the average annual leaching. This P leaching might be due to a combination of high P deposition/through-fall and a high anion exchange with dissolved-organic-carbon and Cl-. We suggest that single events of high sub-surface P leaching may contribute to the overall P leaching, and might increase with the global warming as more DOC is expected to be released to the soil solution.

Charcot-Marie-Tooth (CMT) syndrome is the most common progressive human motor and sensory peripheral neuropathy. CMT type 1E is a demyelinating neuropathy affecting Schwann cells due to pmp22 mutations, modelized by Trembler-J mice. Curcumin, a natural polyphenol com-pound obtained from turmeric (Curcuma longa), exhibits dose- and time-varying antitumor, antioxidant and neuroprotective properties, however, the neurotherapeutic actions of curcumin still remain elusive. Here, we propose curcumin as a possible natural treatment capable of enhancing cellular detoxification mechanisms, resulting in an improvement of the neurodegenerative Trembler-J phenotype. Using a refined method for obtaining enriched Schwann cell cultures, we evaluated the neurotherapeutic action of low dose curcumin treatment on the PMP22 expression, and on the chaperones (HSF1 and Hsp27) and autophagy/mTOR (HDAC6 and ribosomes) pathways in Trembler-J and wild-type genotypes. In wild-type Schwann cells, the action of cur-cumin resulted in strong stimulation of the chaperone and macroautophagy pathway, whereas the modulation of ribophagy showed a mild effect. However, despite the promising neuroprotective effects for the treatment of neurological diseases, we report (demonstrate?) that the action of cur-cumin in Trembler-J Schwann cells could be impaired due to the irreversible impact of ethanol used as a common curcumin vehicle necessary for administration. These results contribute to expand our still limited understanding of PMP22 biology in neurobiology, and expose the intrinsic lability of the neurodegenerative Trembler-J genotype. Furthermore, they unravel interesting physiological mechanisms of cellular resilience relevant for to the pharmacological treatment of the neurodegenerative Tremble J phenotype with curcumin and ethanol. We conclude that the analysis of the effects of the vehicle itself is an essential and in-escapable step to comprehensibly assess the own effects and full potential of curcumin treatment for therapeutic purposes.

Background: Zebrafish (Danio rerio) is a model organism emerged for the study of human cancer. Compared with the murine model, the zebrafish model has several properties ideal for personalized therapies. The transparency of the zebrafish embryos and the development of the pigment-deficient “casper” zebrafish line give the capacity to directly observe cancer formation and progression in the living animal. Automatic quantification of cellular proliferation in vivo is critical to the development of personalized medicine. Methods: A new methodology was defined to automatically quantify the cancer cellular evolution. ZFTool was developed to establish a base threshold that eliminates the embryo auto-fluorescence and automatically measures the area and intensity of GFP (green-fluorescent protein) marked cells and define a proliferation index. Results: Proliferation index automatically computed on different targets demonstrates the efficiency of ZFTool to provide a good automatic quantification of cancer cell evolution and dissemination. Conclusion: Our results demonstrate that ZFTool is a reliable tool for the automatic quantification of the proliferation index, being a measure of cancer mass evolution in zebrafish eliminating the influence of its autofluorescence.

Real time condition monitoring and precision health assessment system is a mandatory need for effective maintenance program in industrial sector. Rapid advancement in the information technology and other engineering technologies have invited more proactive attention from research and development in industrial sectors and particularly in condition monitoring of machines and related Industrial processes. In this work, drill bit condition monitoring techniques have been developed based on wavelet analysis and artificial neural networks (ANN) for automatic drill bit fault detection and classification. An experimental work has been conducted to capture the vibration signals for analysis. In this experiment, the CNC drill machine is used with high carbon steel drill bit and mild steel material as work piece. The cutting condition parameters are kept constant and the wear level is varied from 0.2 to 0.6 mm. The Data Acquisition system (DAQ) with Lab VIEW software is used to capture the vibration signals for drill bit with different wear conditions using accelerometer. The captured vibrations data are analyzed using continuous wavelet transform (CWT) with Morlet wavelet and Daubechies wavelet as a prime function. In general, the CWT coefficient is used to generate the inputs features to ANN for automatic tool condition classification, with two outputs (0, 1) for healthy and (1, 0) for faulty. The outcome of ANN showed 98% of accuracy in the wear prediction and this results show the effectiveness of the combed WT and ANN for automatic classification of tool wear conditions with high success rate.

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

We fabricate large-area atomically thin MoS₂ layers through the direct transformation of crystalline molybdenum trioxide (MoO₃) by sulfurization at relatively low temperatures. The obtained MoS₂ sheets are polycrystalline (~10-20 nm single-crystal domain size) with areas of up to 300×300 µm² with 2-4 layers in thickness and show a marked p-type behaviour. The synthesized films are characterized by a combination of complementary techniques: Raman spectroscopy, X-ray diffraction, transmission electron microscopy and electronic transport measurements.

3D bioprinting, like 3D printing, is a process that builds structures by depositing material layer by layer. In the specific case of bioprinting, these layers are composed of a biocompatible material together with living cells, allowing the creation of three-dimensional structures that recreate functional tissues and organs. Bioprinting cell-laden structures is complicated by the high rate of cell damage and stress that occurs during the process, caused by the high pressures and stresses to which they are subjected. To minimise damage during the process, it is important to study and optimise certain bioprinting conditions beforehand and to analyse how they affect the cells by means of computational simulations. In this review, both quantitative and qualitative data are collected to improve the nozzle geometry through computational simulation studies. Optimal ranges for nozzle diameter (0.2-1mm) and length (8-10mm; 300-900μm) have been defined, and recommendations for improving nozzle performance during bioprinting, such as the provision of an inner angle of 20-30°, an inner EDTA coating and a shear stress of less than 10kPa, have been gathered. Finally, based on the data collected, a design of experiments is proposed to obtain an optimal bioprinting configuration for a particular bioink.

Chironomus riparius is a well-established model organism in various fields such as ecotoxicology and ecology, and therefore environmental preferences, ecological interactions and metabolic traits are well-studied. With the recent publication of a high-quality draft genome, as well as different population genetic parameters such as mutation and recombination rate, the species can be used as an alternative to the Drosophila models in experimental population genomics or molecular ecology. To facilitate access to this promising experimental model species for a wider range of researchers, we describe experimental methods to first create and sustain long term cultures of C. riparius and then use them to perform repeatable and comparable experiments for various research questions.

Diagnosis of bovine tuberculosis (bTB) may be confounded by immunological cross-reactivity to Mycobacterium bovis antigens when animals are sensitised by certain nontuberculous mycobacteria (NTMs). Therefore, this study aimed to investigate NTM species diversity in African buffalo (Syncerus caffer) respiratory secretions and tissue samples, using a combination of novel molecular tools. Oronasal swabs were collected opportunistically from 120 immobilised buffaloes in historically bTB-free herds. In addition, bronchoalveolar lavage fluid (BALF; n=10) and tissue samples (n=19) were obtained during post-mortem examination. Mycobacterial species were identified directly from oronasal swab samples using the Xpert MTB/RIF Ultra qPCR (14/120 positive) and GenoType CMdirect (104/120 positive). In addition, all samples underwent mycobacterial culture, and PCRs targeting hsp65 and rpoB were performed. Overall, 55 NTM species were identified in 36 mycobacterial culture-positive swab samples with presence of esat-6 or cfp-10 detected in 20 of 36 isolates. The predominant species were M. avium complex and M. komanii. Nontuberculous mycobacteria were also isolated from 6 of 10 culture-positive BALF and 4 of 19 culture-positive tissue samples. Our findings demonstrate that there is a high diversity of NTMs present in buffaloes, and further investigation should determine their role in confounding bTB diagnosis in this species.

Round bodies in spirochete cultures have been a controversial subject since their description seven decades ago. We report the existence of round bodies (spherical cells) in cultures of Mucispirillum schaedleri, a spiral bacterium phylogenetically distant from spirochetes. Furthermore, when grown in biofilms, M. schaedleri demonstrates a unique morphology known as cording, which has been previously described only in mycobacteria. Thus, M. schaedleri has two distinct features, each previously thought to be unique to two different phylogenetically distant groups of bacteria.

In this research paper, design and development of pyramidal horn antenna for J-band application is reported. It is particularly designed for 17 dB gain and half beam width about 25 degrees at 6.93 GHz. Horn aperture, horn axial length and distance from the throat of the antenna to aperture are the main design constraints which are calculated and used for the antenna design and simulation. Beam width in E-plane and H-plane horn is calculated and it is 19.18 dB and 22.86 dB respectively. The reported antenna design shows good performance for J-band in radiometry, satellite, and radar applications.

Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using an intelligent (i.e., model-based and optimization-driven) approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer; (3) providing the optimization in SmartScan with a balance of exploration and exploitation to make it less myopic; and (4) improving SmartScan's computational efficiency via model order reduction using singular value decomposition. Sample 3D test artifacts are simulated and printed using SmartScan in comparison with common heuristic scan sequences. Reductions of up to 92% in temperature inhomogeneity, 86% in residual stress, 24% in maximum deformation and 50% in geometric inaccuracy were observed using SmartScan, without significantly sacrificing print speed. An approach for using SmartScan for printing complex 3D parts in practice, by integrating it as a plug-in to a commercial slicing software, was also demonstrated experimentally, along with its benefits in significantly improving printed part quality.

Waste heat recovery stands out as a promising technique to tackle both energy shortages and environmental pollution. Currently, this valuable resource, generated from processes like fuel combustion or chemical reactions, is often dissipated into the environment, despite its potential to significantly contribute to the economy. To harness this untapped potential, a travelling-wave thermo-acoustic generator has been designed and subjected to comprehensive experimental analysis. Fifty-two data corresponding to different working conditions of the system were extracted to build ANN, ANFIS and ANN-PSO models. Evaluation of performance metrics reveals that the ANN-PSO model demonstrates the highest predictive accuracy (R^2=0.9959), particularly in relation to output voltage. This research demonstrates the potential of machine learning techniques for the analysis of thermo-acoustic systems. By doing so, it is possible to get an insight into nonlinearities inherent to thermo-acoustic systems. This advancement empowers researchers to forecast the performance characteristics of alternative configurations with a heightened level of precision.

In this work, we report the caloric effect for an electronic system of the antidot type, modeled by combining a repulsive and attractive potential (parabolic confinement). In this system, we consider the action of a perpendicular external magnetic field and the possibility of having an Aharonov-Bohm flux (AB-flux) generated by a current passing through a solenoid placed inside the forbidden zone for the electron. The energy levels are obtained analytically, and the model is known as the Bogachek and Landman model. We propose to control the caloric response of the system by varying only the AB-flux, finding that in the absence of an external magnetic field, the maximization of the effect always occurs at the same AB-flux intensity independent of the temperature while fixing the external magnetic field at a non-zero value breaks this symmetry and changes the point where the caloric phenomenon is maximized and is different depending on the temperature to which the process is carried. Due to the great diversity in technological applications that have antidots in electronics, the possibility of controlling their thermal response just by varying the intensity of the internal current inside the solenoid can be a platform of interest for experimental studies.

In recent years, Global Navigation Satellite System reflectometry (GNSS-R) has been explored as a methodology for inland water body characterization. However, thorough characterization of the sensitivity and behavior of the GNSS-R signal to inland water bodies is still needed to progress this area of research. In this paper, we characterize the uncertainty associated with Cyclone Global Navigation Satellite System (CYGNSS) measurements on the determination of river width. The characterization study uses simulated data from a forward model that accurately simulates CYGNSS observations of mixed water/land scenes. The accuracy of the forward model is demonstrated by comparisons to actual observations of known water body shapes made at particular measurement geometries. Simulated CYGNSS data is generated over a range of synthetic scenes modeling a straight river subreach, and the results are analyzed to determine a predictive relationship between the peak SNR measured over the river subreaches and the river widths. An uncertainty analysis conducted using the predictive relationship indicates that for simplistic river scenes, the SNR over the river is predictive of the river width to within +/-5m. The presence of clutter (surrounding water bodies) within ~500m of the river causes perturbations in the SNR measured over the river that can render the river width retrievals unreliable. The results of this study indicate that under idealized conditions, GNSS-R data is able to measure river widths as narrow as 160m with high accuracy.

Industrial agriculture (IA) is the predominant model of food production since the Green Revolution in the 1950s. IA has been recognized among the main drivers of biodiversity loss, climate change and native pollinator decline. This is controversial, given that native agricultural pollinators are an important resource biota already contributing to crop yield, especially in areas defined as "world biodiversity hotspots” (WBH). These areas often overlap with agricultural zones hosting a significant proportion of cultivated land, mainly through intensive agricultural practices. Pollinator biodiversity and pollination services in these places are currently under threat due to the negative consequences of IA. The dual role of insects as key players allowing the maintenance of the natural ecosystem, as well as main crop pollinators, is particularly exacerbated and urgently requires conservation actions in WBH and food-producing zones. Here we summarize the known negative effects of IA on pollinator biodiversity and illustrate these problems by considering the case of Chile. Food exports represent a considerable part of the economy in this OECD “developing country” in the “Global South”, and a large part of its surface has been highlighted as a unique WBH. This area is currently being replaced by IA businesses at a fast pace, threatening local biodiversity. We present agroecological strategies for sustainable food production and pollinator conservation in food-producing WBHs like Chile. These alternatives recognize native pollinators as internal inputs that cannot be replaced by IA technological packages or external inputs and support the development of agroecological and biodiversity restoration practices to protect their existing biodiversity. We suggest a strategy that integrates four fundamental pillars for producing food in a sustainable way, recognizing biodiversity and local cultural heritage: 1) Share the land, restore and protect; 2) Ecological intensification; 3) Localized knowledge, research and technological development; and 4) Territorial planning and implementation of socio-agroecological policies. We suggest that this approach does not need greater modification of native pollination services that sustain the world with food and basic subsistence goods, but a paradigm change where the interdependency of nature and human wellbeing are recognized for ensuring the present and future of the world’s food security and sovereignty as well as considering the reduction of consumerism and food waste.

The symptoms of multiple sclerosis (MS) are determined by the location of demyelinating lesions in the white matter of the brain and spinal cord. Currently, magnetic resonance imaging (MRI) is the most common tool for diagnosing MS, understanding the course of the disease, and analyzing the effects of treatments. However, undesirable components may appear during the generation of MRI, such as noise or intensity variations. Mathematical morphology (MM) is a powerful image analysis technique that helps to filter the image and extract relevant structures. Granulometry is an image measurement tool of MM that determines the size distribution of objects in an image without explicitly segmenting each object. While, several methods have been proposed for the automatic segmentation of MS lesions in MRI, in some cases only simple data preprocessing, such as image resizing to standardize the input dimensions, has been performed before the algorithm training. Therefore, this paper proposes an MRI preprocessing algorithm performing elementary morphological transformations in brain images of MS patients and healthy individuals to delete undesirable components and extract the relevant structures such as MS lesions. Also, the algorithm computes the granulometry in MRI to describe the size qualities of lesions and trains two artificial neural networks (ANN) to predict MS diagnosis. The computing of differences in granulometry measurements of an image with MS lesions and a reference image (without lesions) can determine the size characterization of the lesions. Then, the ANNs were evaluated with the validation set and the performance results (test accuracy = 0.9753, and cross-entropy loss = 0.0247) show the proposed algorithm can support the decision of specialists for diagnosing MS and estimating the disease progress, based on granulometry values.

The first exposure to influenza is thought to impact subsequent immune responses later in life. The consequences of this can be seen during influenza epidemics and pandemics with differences in morbidity and mortality for different birth cohorts. There is a need for better understanding of how vaccine responses are affected by early exposures to influenza viruses. In this analysis of hemagglutination inhibition (HI) antibody responses in two cohorts of military personnel we noticed differences related to age, sex, prior vaccination, deployment and birth year. These data suggest that HI antibody production, in response to influenza vaccination, is affected by these factors. The magnitude of this antibody response is associated with, among other factors, the influenza strain that circulated following birth.

A new formalism is introduced that makes it possible to elucidate the physical and geometric content of quantum spacetime. It is based in the Minimum Group Representation Principle (MGRP). Within this framework new results for entanglement and geometrical/topological phases are found and implemented in cosmological and black hole space-times. Our main results here are: {\bf(i)} We find the Berry phases for inflation and for the cosmological perturbations and express them in terms of the observables, as the spectral scalar and tensor indices, $n_S$ an $n_T$, and the tensor to scalar ratio $r$. The Berry phase for de Sitter inflation is imaginary with the sign describing the exponential acceleration. {\bf(ii)} The pure entangled states in the minimum group (metaplectic) $Mp(n)$ representation for quantum de Sitter space-time and black holes are found. {\bf(iii)} For entanglement, the relation between the Schmidt type representation and the physical states of the $Mp(n)$ group is found: This is a {\it new non-diagonal} coherent state representation complementary to the known Sudarshan diagonal one. {\bf(iv)} Mean value generators of $Mp(2)$ are related to the adiabatic invariant and topological charge of the spacetime (matrix element of the transition $-\infty < t < \infty$). {\bf(v)} The basic {\it even} and {\it odd} $n$-sectors of the Hilbert space are intrinsic to the quantum spacetime and its discrete levels (in particular continuum for $n \rightarrow \infty$), they do not require any extrinsic generation process as the standard Schrodinger cat states, and are {\it entangled}. {\bf(vi)} The gravity or cosmological domains in one side and another of the Planck scale are {\it entangled}. Examples: The quantum primordial trans-Planckian de Sitter vacuum and the classical late de Sitter vacuum today; the central quantum gravity reqion and the external classical gravity region of black holes. The classical and quantum dual gravity regions of the space-time are entangled. {\bf(vii)} The general classical-quantum gravity duality is associated to the Metaplectic $Mp(n)$ group symmetry which provides the complete full covering of the phase space and of the quantum space-time mapped from it.

Relationships of the three bryophyte lineages (liverworts, mosses, and hornworts) to vascular plants is a pivotal question in the study of origin and evolution of land plants. In recent decades, this question has been subject to intense phylogenetic analyses using morphological characters, multigene DNA sequences, and genome structural characters. A tentative consensus reached ten years ago suggested that bryophytes are a paraphyletic group, with liverworts being sister to all other land plants and hornworts being sister to vascular plants. However, several more recent nuclear phylogenomic studies have concluded that bryophytes represent a monophyletic group that is sister to vascular plants. A discussion is presented here on strengths and weaknesses of different types of characters (morphological traits, nucleotide sequences, and genome structural arrangements), and their suitability for resolving deep phylogenetic relationships. Moreover, several criteria for credible phylogenetic reconstruction are proposed. Strong statistical support for reconstructed relationships should be derived from high quality, independent characters selected for suitability to the particular question being addressed. The relationships inferred in a study should be congruent with those from as many other lines of phylogenetic evidence as possible. Any incongruities should be explicable by well-understood biological mechanisms. It is concluded that the relationships of the three bryophyte lineages to vascular plants should currently be viewed as unresolved. This is a difficult phylogenetic problem; the land plants underwent a rapid radiation a long time ago. Yet, further exploration of analytical methods and careful choice of characters should lead to eventual elucidation of diversification patterns among early land plants.

The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective was to determine the flight pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study's lag; the lower the height, the greater the percentage of CBBs captured. In Experiments A and B, the traps placed at 0.5m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5m above the ground in the multi-level CT showed a higher capture percentage than the individually placed trap (also at 1.5m). The pattern of the capture and proportion of the CBB in the CTs were maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggested that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

Background: Antiplatelet medications such as aspirin and clopidogrel are used following thrombotic stroke or transient ischemic attack (TIA) to prevent a recurrent stroke. However, the antiplatelet treatments fail frequently, and patients experience recurrent stroke. One approach to lower the rates of recurrence, may be the individualized antiplatelet therapies (antiplatelet therapy modification (ATM)) based on the results of platelet function analysis (PFA). This review was undertaken to gather and analyse the evidence about the effectiveness of such approaches. Methods: We searched Medline, CINAHL, Embase, Web of Science and Cochrane databases to 7 January 2020. Results: Two observational studies involving 1136 patients were included. The overall effects of PFA-based ATM on recurrent strokes (OR 1.05; 95% CI 0.69 to 1.58), any bleeding risk (OR 1.39; 95% CI 0.92 to 2.10) or death hazard from any cause (OR 1.19; 95% CI 0.62 to 2.29) were not significantly different from the standard antiplatelet therapy without ATM. Conclusions: The two studies showed opposite effects of PFA-guided ATM on the recurrent strokes in aspirin non-responders, leading to an insignificant difference in the subgroup meta-analysis (OR 1.59; 95% CI 0.07 to 33.77), while the rates of any bleeding events (OR 1.04; 95% CI 0.49 to 2.17) or death from any cause (OR 1.17; 95% CI 0.41 to 3.35) were not significantly different between aspirin non-responders with ATM and those without ATM. There is a need for large randomized controlled trials which account for potential confounders such as ischemic stroke subtypes, technical variations in the testing protocols, patient adherence to therapy, and pharmacogenetic differences.

Liver cancer imposes a pervasive global health challenge, ranking among the most prevalent cancers worldwide. Its prevalence and mortality rates are on a concerning upward trajectory and exacerbated by the dearth efficacious treatment options. The Hippo signaling pathway, originally discovered in Drosophila, comprises four core components: MST1/2, WW45, MOB1A/B, and LATS1/2. This pathway regulates the cellular localization of the transcriptional coactivator YAP/TAZ (Yes-associated protein/PDZ-binding motif) through a series of enzymatic reactions. The Hippo/YAP/TAZZ pathway maintains a balance between cell proliferation and apoptosis, regu-lates tissue and organ sizes, and stabilizes the internal environment. Abnormalities of any genes within the Hippo signaling pathway, such as deletion or mutation, disturb the delicate balance between cell proliferation and apoptosis, creating a favorable condition for tumor initiation and progression. Mutations or epigenetic alterations in the Hippo signaling pathway components can lead to its inactivation. Consequently, YAP/TAZ becomes overexpressed and activated, promoting excessive cell proliferation and inhibiting apoptosis. This dysregulation is closely associated with the development of liver cancer. This review discusses the pivotal role of the Hippo signaling pathway in the pathogenesis and progression of liver cancer. By elucidating its mechanisms, we aim to offer new insights into potential therapeutic targets for effectively combating liver cancer.

In the rapidly advancing field of Artificial Intelligence (AI), this study presents a critical evaluation of the resilience and cybersecurity efficacy of leading AI models, including ChatGPT-4, Bard, Claude, and Microsoft Copilot. Central to this research is the use of innovative adversarial prompts designed to rigorously test the content moderation capabilities of these AI systems. The study introduces new types of adversarial tests and the Response Quality Score (RQS), a metric specifically developed to assess the nuances of AI responses. Additionally, the research spotlights FreedomGPT, an AI tool engineered to optimize the alignment between user intent and AI interpretation. The empirical results from this investigation are pivotal for assessing the current robustness and security of AI models. They highlight the necessity for ongoing development and meticulous testing to bolster AI defenses against an array of adversarial challenges. Importantly, the study also delves into the ethical and societal implications associated with employing advanced 'jailbreak' techniques in AI testing. The findings are significant for understanding AI vulnerabilities and formulating strategies to enhance the reliability and ethical soundness of AI technologies, paving the way for safer and more secure AI applications.

Background: Increasing number of long-term gastrointestinal (GI) cancer survivors highlights the importance of understanding factors that contribute to their health-related quality of life (HRQoL). We investigated the risk factors of HRQoL, in-cluding demographics, clinical characteristics, and social and behavioral determinants of health (SBDH). Methods: Adult GI cancer survivors (n = 3,201) in the BRFSS surveys from 2014-2021 (except for 2015) were analyzed. Unadjusted/adjusted logistic regression was used. Results: The majority were female (54%) and White (78%), with a median age of 67. Survivors who were 65 years or older, diagnosed with colorectal cancer, or who had fewer comorbidities were more likely to report significantly better HRQoL. Significant social factors of poor HRQoL were being unmarried, racial and ethnic minorities, low socioeconomic status, and poor health care access. Significant behavioral factors of poor HRQoL were lack of physical activity, heavy alcohol consumption, and current smoking, with lack of physical activity being the most significant factor. Conclusions: The SBDH have a critical role in HRQoL. Future studies are warranted to develop a tailored survivorship intervention, such as physical rehabilitation and to ex-plore machine learning/artificial intelligence predictive models to identify cancer sur-vivors at a high risk of developing poor HRQoL.

Rapid SARS-CoV-2 self-tests have the potential to expand access to COVID-19 testing and improve community-level case detection, particularly in resource-constrained countries such as Kenya. However, prior to their introduction, their acceptability must be assessed. This qualitative study explored key decision-takers’ values towards SARS-CoV-2 self-testing in Kenya. Healthcare workers, representatives of civil society, and potential implementors from Mombasa and Taita-Taveta were selected as decision-takers. Semi-structured interviews and focus group discussions were used to collect data on their values towards self-testing. A thematic analysis approach was applied. Most informants considered that the Kenyan public is equipped to accept and use self-testing safely as an approach to help to reduce workload at public healthcare facilities, and know one’s COVID-19 status in a private manner. The informants emphasized the need to provide counselling to end-users, to support those needing to self-isolate, and to engage different civil society stakeholders in information provision on self-testing. Fear of stigma and of forced isolation were noted as potential deterrents to self-testing uptake for some individuals. In conclusion, there is high acceptability of self-testing in Kenya among decision-takers. However, enhanced education, counselling, and addressing deterrents to testing would be helpful to ensure effective use of SARS-CoV-2 self-testing in Kenya.

The ability to self-direct a research program determines graduate degree completion. Yet, research on incompletion of graduate physics programs assume students’ present level of self-direction adequate and neglects to recognize a lack of self-directed learning as key. One theoretical mathematical physicist focused on changing this challenge of physics graduate education by promoting self-directed learning through the type research flow that has been found to bring the greatest satisfaction to researchers with respect to their insights. This he provided through his space, time, open mindedness and theoretical contributions with his students and in collaboration with his colleagues. A self-directed learner himself, David J. Rowe developed methods of mentoring for encouraging physics graduate students to recognize symmetry as valuable in identifying solutions to problems quickly—helping these students take the lead in finding insightful resolutions to complex, multidimensional, mathematical physics uncertainties. How Rowe set about supporting self-directed learning in his graduate physics education interactions will be examined with the use of narrative research to interpret the texts and conversations with the author he made available. His techniques will be presented and recommendations made regarding how Rowe’s work in this regard can be modeled to improve self-direction in STEM graduate education.

The halotolerant microalga Dunaliella salina has been widely studied for natural β-carotene production. This work shows biochemical characterization of three newly isolated Dunaliella salina strains DF15, DF17 and DF40 compared with D. salina CCAP 19/30 (confirmed to be D. tertiolecta) and D. salina UTEX 2538 (also known as D. bardawil). Although all three new strains have been genetically characterized as Dunaliella salina strains, their ability to accumulate carotenoids and their capacity for photoprotection against high light stress are different. DF15 and UTEX 2538 reveal great potential for producing large amount of β-carotene and maintained a high rate of photosynthesis under light of high intensity; however, DF17, DF40 and CCAP 19/30 showed increasing photoinhibition with increasing light intensity, and reduced contents of carotenoids, in particular b-carotene, suggesting that the capacity of photoprotection is dependent on the cellular content of carotenoids, in particular β-carotene. Strong positive correlations were found between the cellular content of each of all-trans β-carotene, 9-cis β-carotene, all-trans α-carotene and zeaxanthin but not lutein in the D. salina strains. Lutein was strongly correlated with respiration in photosynthetic cells and strongly related to photosynthesis, chlorophyll and respiration, suggesting an important and not hitherto identified role for lutein in co-ordinated control of the cellular functions of photosynthesis and respiration in response to changes in light conditions, which is broadly conserved in Dunaliella strains. Statistical analysis based on biochemical data revealed a different grouping strategy from the genetic classification of the strains. The significance of these data for strain selection for commercial carotenoid production is discussed.

Cirrhosis is a critical global health issue, responsible for 2.4% of deaths worldwide in 2019. The Global Burden of Disease Study reported a near doubling of decompensated cirrhosis cases from 1990 to 2017. In the U.S., cirrhosis is the 12th leading cause of death and often requires hospitali-zation and procedural interventions for severe complications such as hepatocellular carcinoma, ascites, hepatic encephalopathy, and variceal bleeding. This study aims to identify racial, ethnic, and socioeconomic disparities in receiving critical interventions among U.S. patients with de-compensated cirrhosis during 2020-2021. We conducted a retrospective cross-sectional analysis using 2020-2021 National Inpatient Sample data of adult patients (≥18 years) with cirrhosis-related and cirrhosis complication-related ICD-10 codes and who underwent procedures for cirrhosis-related indications such as esophagogastroduodenoscopy (EGD) for variceal hemor-rhage, transjugular intrahepatic portosystemic shunt (TIPS) for variceal hemorrhage or refractory ascites, hemodialysis for acute kidney failure or hepatorenal syndrome, and liver transplantation We collected data on patient baseline clinicodemographic and procedural outcomes. Statistical analyses included multivariable logistic regression to assess for associations with outcomes. There were significant disparities in procedure utilization: White and Hispanic patients more likely than Black patients to receive EGD and TIPS, while Black and Hispanic patients had higher odds of receiving hemodialysis. Insurance type also influenced access, with Private/HMO insurance holders having higher odds of undergoing procedures. These findings underscore the need for targeted interventions to address healthcare inequities.

There is a general lack of research involving older lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) people. This systematic review aimed to synthesize Japanese and Swedish qualitative research on LGBTQ people aged 60 years or older. PRISMA guidelines were followed. Japanese and Swedish articles, published in English-language journals, were searched across PsychINFO, Medline, CINAHL, and Sociological Abstracts databases. Additional searches were carried out to include studies written in Japanese or Swedish. There were no papers from Japan, and five from Sweden were reviewed. Four articles were included, including 48 participants aged 60–94 years. We summarized the findings using a deductive thematic synthesis. Two major themes emerged: (a) quality of life, minority joy, and resilience (positive aspects), and (b) experiences of discrimination, stigmatization, and minority stress (negative aspects). The participants described a wish to be acknowledged for their own assets and unique life histories, and to be treated as everyone else. They emphasized the importance of knowledge of LGBTQ issues among nursing staff, so that older LGBTQ people are treated in a competent and affirmative way. The study revealed several important topics for understanding older LGBTQ people’s life circumstances and the severe lack of qualitative studies in Japan and Sweden.

Tributyltin (TBT) is one of the most toxic anthropogenic compounds introduced into the marine environment. Despite its global ban in 2008, TBT is still a problem of great concern due to its high affinity for particulate matter, providing a direct and potentially persistent route of entry into benthic sediments. Bioremediation strategies may constitute an alternative approach to conventional physicochemical methods, benefiting from the microorganism’s potential to metabolize anthropogenic compounds. In this work, a simple, precise and accurate static headspace gas chromatography method was developed to investigate the ability of TBT degrading microbes in sedimentary microcosms over a period of 120 days. The proposed method was validated for linearity, repeatability, accuracy, specificity, limit of detection and limit of quantification. The method was subsequently successfully applied for the detection and quantification of TBT and degrading compounds in sediment samples on day 0, 30, 60, 90 and 120 of the experiment employing the principles of green chemistry. On day 120 the concentration of TBT remaining in the microcosms ranged between 91.91 ng/g wet wt for the least effective microbial inoculant to 52.73 ng/g wet wt for the most effective microbial inoculant from a stating concentration of 100 ng/g wet wt.

Micronutrient deficiencies are a major public health problem. Beans are an important plant-based source of iron, zinc and copper, but their absorption is reduced in the presence of anti-nutrients such as phytates, polyphenols and tannins. Soaking and discarding the soaking water before cooking is unanimously recommended, but this can result in mineral loss. Data on the consequences for mineral bioaccessibility is still limited. This study aimed to evaluate iron, zinc and copper bioaccessibility in black beans cooked (regular pan, pressure cooker) with and without the soaking water. Minerals were quantified by ICP-MS, myo-inositol phosphates (InsP₅, InsP₆) by HPLC ion-pair chromatography, total polyphenols using Folin-Denis reagent and condensed tannins using Vanillin assay. Mineral bioaccessibility was determined by in vitro digestion and dialysis. All treatments resulted in a statistically significant reduction of total polyphenols (30%) and condensed tannins (20%). Only when discarding the soaking water a loss of iron (6%) and copper (30%) was observed, and InsP₆ was slightly decreased (7%) in one treatment. Bioaccessibility of iron and zinc were low (about 0.2% iron and 35% zinc), but copper presented high bioaccessibility (about 70%). Cooking beans under pressure without discarding the soaking water resulted in the highest bioaccessibility levels among all household procedures. Discarding the soaking water before cooking did not improve the nutritional quality of the beans.

Background: The protocol described in this paper is part of a research project coordinated 1 between three Spanish universities where a technology aimed at improving the quality of life of 2 people suffering from cerebral palsy will be developed. Part of the technology developed will consist 3 of developing an interface and a series of applications to increase motivation for daily physical activity. 4 The basis of these developments is based on the measurement of the emotional state of the subjects. 5 Methods: The experimental protocol is designed with two objectives, on the one hand to identify the 6 emotional state through physiological signals, and on the other to determine whether music can be 7 a motivating factor to promote physical activity. It has been specifically designed for subjects with 8 cerebral palsy taking into account the special characteristics of this population. These are people with 9 whom it is difficult to use questionnaires to have a basis to contrast with the measured physiological 10 signals, so measurements must be taken in carefully chosen daily life situations Discussion: As results 11 we hope to obtain which physiological parameters are the most robust to measure the emotional state 12 and how to design rehabilitation and physical activity promotion routines that are motivating, in 13 addition to being able to avoid risk factors during the performance of these routines. Trial registration: 14 NCT05621057. https://clinicaltrials.gov/ct2/show/NCT05621057

In an era where dietary habits significantly impact health, technological interventions can offer personalized and accessible food choices. This paper introduces Chef Dalle, a recipe recommen-dation system that leverages multimodal human-computer interaction (HCI) techniques to pro-vide personalized cooking guidance. The application integrates voice-to-text conversion via Whisper, ingredient image recognition through GPT-Vision, and employs TF-IDF vectorization alongside cosine similarity for personalized recipe recommendations. These methods enable users to interact with the system using voice, text, or images, accommodating various dietary re-strictions and preferences. Furthermore, the utilization of DALL-E 3 for generating recipe images enhances user engagement. User feedback mechanisms allow for the refinement of future rec-ommendations, demonstrating the system's adaptability. Chef Dalle showcases potential appli-cations ranging from home kitchens to grocery stores and restaurant menu customization, ad-dresses accessibility, promoting healthier eating habits. This paper underscores the significance of multimodal HCI in enhancing culinary experiences, setting a precedent for future developments in the field.

A correctly obtained Land-use/land-cover (LULC) prediction map is essential to under-standing and assessing future patterns. In the study, the LULC map of Urmia/Iran in 2030 was produced using two different prediction methods CA-Markov and Artificial Neural Network (ANN). In general, the study followed a methodology consisting of three steps. In the first steps, Landsat satellite images acquired in 2000, 2010 and 2020 were classified with maximum likelihood algorithm and LULC maps were prepared for each year. In the second stage, to investigate the LULC prediction methods' validation (CA-Markov and ANN) the LULC prediction map of 2020 was produced using the LULC map of 2000 and 2010; In this step, the predicted LULC map of 2020 and the actual LULC map of 2020 were evaluated by correctness, completeness and quality indexes. Finally, The LULC map for 2030 was prepared using all two algorithms and the change map was extracted. The results show that the area of soil and vegetation decreased, and built-up regions increased during the research period. The methods validation results show that the two algorithms are much closer to each other. Nevertheless, in general, ANN has the highest completeness (96.21%) and quality (93.8%) and CA-Markov the most correctness (96.47). This study shows that the CA-Markov algorithm is most successful in predicting the future that had larger areas and a higher percentage in the region (urban and vegetation cover) and the ANN algorithm in predicting phenomena that had smaller levels with fewer percentages (soil and rock).

Maximum hardness and hardened depth are the responses of interest in relation to the laser hardening process. These values define heat treatment quality and have a direct impact on mechanical performance. This paper aims to develop models capable of predicting the shape of the hardness profile depending on laser process parameters for controlling laser hardening quality (LHQ), or rather the response values. An experimental study was conducted to highlight hardened profile sensitivity to process input parameters such as laser power (P_L), beam scanning speed (V_S) and initial hardness in the core (H_C). LHQ modeling was conducted by modeling attributes extracted from the hardness profile curve using two effective techniques based on the punctual and geometrical approaches. The process parameters with the most influence on the responses were laser power, beam velocity and initial hardness in the core. The obtained results demonstrate that the geometrical approach is more accurate and credible than the punctual approach according to performance assessment criteria.

Recent years have experienced an increase in construction and demolition waste (C&amp;DW), which is the most significant solid waste stream. C&amp;DW is contributing to exceeding all planetary boundaries and presents a range of other issues. In order to better understand the existing research on C&amp;DW, a global bibliographic analysis was undertaken through seven groups of keyword searches and the results visualised using VOCviewer. The results show that C&amp;DW receives only a modest research attention compared to other areas of waste, and this is despite an exponential increase in C&amp;DW research since 2016. The analyses also show that concrete is the most researched material in terms of C&amp;DW, and that reuse, recycling, and circular economy are so far attracting only proportionally modest research attention. This signals a need for further acceleration of the C&amp;DW research, and specifically for more research on reuse, recycling, and circular economy for materials other than concrete.

This paper presents an innovative testing framework, testFAILS, designed for the rigorous evaluation of AI Linguistic Systems, with a particular emphasis on various iterations of ChatGPT. Leveraging orthogonal array coverage, this framework provides a robust mechanism for assessing AI systems, addressing the critical question, "How should we evaluate AI?" While the Turing test has traditionally been the benchmark for AI evaluation, we argue that current publicly available chatbots, despite their rapid advancements, have yet to meet this standard. However, the pace of progress suggests that achieving Turing test-level performance may be imminent. In the interim, the need for effective AI evaluation and testing methodologies remains paramount. Our research, which is ongoing, has already validated several versions of ChatGPT, and we are currently conducting comprehensive testing on the latest models, including ChatGPT-4, Bard and Bing Bot, and the LLaMA model. The testFAILS framework is designed to be adaptable, ready to evaluate new bot versions as they are released. Additionally, we have tested available chatbot APIs and developed our own application, AIDoctor, utilizing the ChatGPT-4 model and Microsoft Azure AI technologies

. The Tau protein is associated with microtubule function in the neuron and is crucial for normal axonal transport. In several different neurodegenerative disorders, Tau misfolding leads to hyper-phosphorylation (p-Tau) and intracellular p-Tau aggregates known as neurofibrillary tangles (NFTs). This is particularly evident in individuals with Down syndrome (DS), who develop Alzheimer’s disease-like (AD) neuropathology early in life with almost complete penetrance, associated with the development of dementia symptoms in their 40s or 50s. Our previous findings have shown that certain forms of p-Tau are present already in childhood in individuals with DS in neuron-derived exosomes, suggesting an early phosphorylation profile in this population that could influence the development of AD pathology. Misfolded p-Tau isoforms are known to be seeding competent and may be responsible for spreading AD pathology in different regions of the brain. This review is focused on the accumulation of p-Tau in the brain of individuals with DS and potential consequences for brain function.

Secondary and tertiary prevention strategies targeting people with disabilities to improve their health and wellbeing is important. In Sweden, >95% of all children with cerebral palsy (CP) participate in a follow-up program, where one of the goals is the prevention of hip dislocations. We reviewed the incidence of hip dislocations from 2010 to 2019 and the number of children who underwent different types of hip surgeries. The number of hip dislocations was reduced from 8.8% before introduction of the program to 0.3-0.4% up to 2015, followed by a gradual increase to 0.8% in 2019. The proportion of children who underwent adductor-psoas lengthening as their primary preventive surgery decreased from 50% in 2017 to 37% in 2019 with a corresponding increase of children undergoing femoral osteotomy, indicating more children underwent surgery at a later stage. Reasons for the increased number of children with hip dislocation may be that more children have moved to Sweden in recent years without corresponding compensation in health care resources and increased waiting times for surgery due to, among other things, a shortage of nurses. The results highlight the importance of constantly monitoring follow-up programs.

African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral variants on clinical outcomes and infection-dynamics in pigs experimentally infected with ASFV, we have designed a deep sequencing strategy. Variant analysis revealed 3 distinct SNPs present in the virus inoculum (at 2.4%, 0.7%, and 13% frequency, respectively) that were maintained within all infected pigs (1-6 % frequency, and the latter at 16-21%). Several pigs displayed other unique SNPs at &lt;10% frequency. In addition, a deletion of 10487 bp (resulting in the complete loss of 21 genes) was present at nearly 100% frequency in the ASFV DNA from one pig at position 6362-16849. This deletion was also found to be present at low levels in the virus inoculum and in two other infected pigs. The current methodology can be used for the currently circulating Eurasian ASFVs and also adapted to other ASFV strains and genotypes. Comprehensive deep sequencing is critical for following ASFV molecular evolution, especially for identification of modifications that affect virus virulence.

The increasing demand for higher inclusion cleanliness levels motivates the control over the formation and evolution of inclusions in the steel production process. In this work, the evolution of the chemical composition and size distribution of inclusions throughout a slab production process of Al-killed steel, including ladle furnace (LF) treatment and continuous casting (CC), was followed. The initial solid Al2O3 and Al2O3-MgO inclusions were modified to liquid Al2O3-CaO-MgO inclusions during LF treatment. The evolution of the size distributions during LF treatment was associated with the growth and removal of inclusions, as new inclusions were not created after the deoxidation process, according to a population density function (PDF) analysis. Additionally, the size distributions tended to be similar as the LF treatment progressed regardless of their initial features, whereas they differed during CC. Analysis of the upper tails of the distributions through generalized extreme values theory showed that inclusion distributions shifted from larger to smaller sizes as the process progressed. There were great changes in the distributions of large inclusions throughout the LF treatment and between the end of the LF treatment and the start of the CC process. Additionally, distributions of large inclusions differed at the end of the LF treatment, whereas such differences decreased as CC progressed.

Nano medicine seeks to deliver a valuable set of research tools and clinically useful devices in the near future. The current medical field is in dire need of new commercial applications in the pharmaceutical industry that may include advanced drug delivery systems, new therapies, and in vivo imaging. Here in this experimental study, the nano materials used in DNA biosensors like silver nano dots were incorporated as nano biosensors are used for both therapeutic and diagnostic applications. The most important step while preparing a DNA biosensor is the immobilization of DNA probe on the surface of a sensing device such as an electrode. The amount of immobilized DNA probe will influence the accuracy sensitivity, selectivity and life of a DNA biosensor directly. Because of the high surface to volume ratio and excellent biological compatibility, nano materials can enlarge the sensing surface area to increase the amount of immobilized DNA and the DNA mixed with nano materials can keep its biologically activity well.In this study,silver nano dots created in our lab were functionalized with thio nucleides and were used as nano sensor probes in bio bar code assays.

Primocane-fruiting (PF) blackberries are adaptable to different production systems. To increase yields in PF blackberries, their primocanes are typically tipped or topped in summer to encourage branch formation from axillary buds below the cut. In this study, we determined in PF ‘Prime-Ark Traveler’ whether early emerging primocanes were more productive than those that emerged later in the season and the effect of primocane bending and defoliation on flowering. The primocanes that emerged in April produced 64% more flower shoots than those that emerged after May. Also, these findings indicate the alternative primocane management practices of selecting the early emerging primocanes and bending to orient primocanes horizontally and leaf removal increase budbreak and flower shoot emergence. The present work contributes toward a better understanding of primocane emergence time and orientation-flowering relations and how they mediate crop performance in PF blackberry.

Uveal melanoma (UM) is the most common primary cancer of the eye and is associated with a high rate of metastatic death. UM can be stratified into two main classes based on metastatic risk, with class 1 UM having a low metastatic risk and class 2 UM having a high metastatic risk. Class 2 UM have a distinctive genomic, transcriptomic, histopathologic, and clinical phenotype characterized by biallelic inactivation of the BAP1 tumor suppressor gene, an immune suppressive microenvironment enriched for M2-polarized macrophages, and poor response to checkpoint inhibitor immunotherapy. To identify potential mechanistic links between BAP1 loss and immune suppression in class 2 UM, we performed an integrated analysis of UM samples, as well as genetically engineered UM cell lines and uveal melanocytes (UMC). Using RNA sequencing (RNA-seq), we found that the most highly up-regulated gene associated with BAP1 loss across these datasets was PROS1, which encodes a ligand that triggers phosphorylation and activation of the immunosuppressive macrophage receptor MERTK. The inverse association between BAP1 and PROS1 in class 2 UM was confirmed by single-cell RNA-seq, which also revealed that MERTK was up-regulated in CD163+ macrophages in class 2 UM. Using ChIP-seq, BAP1 knockdown in UM cells resulted in an accumulation of H3K27ac at the PROS1 locus, suggesting epigenetic regulation of PROS1 by BAP1. Phosphorylation of MERTK in RAW 264.7 monocyte-macrophage cells was increased upon co-culture with BAP1-/- UMCs, and this phosphorylation was blocked by depletion of PROS1 in the UMCs. These findings were corroborated by multi-color immunohistochemistry, where class 2/BAP1-mutant UMs demonstrated increased PROS1 expression in tumor cells and increased MERTK phosphorylation in CD163+ macrophages compared to class 1/BAP1-wildtype UMs. Taken together, these findings provide a mechanistic link between BAP1 loss and suppression of the tumor immune microenvironment in class 2 UMs, and they implicate the PROS1-MERTK pathway as a potential target for immunotherapy in UM.

MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of Flight) is a type of mass spectrometry (MS) that has been widely implemented for the rapid identification of microorganisms over the last decade. The accuracy and flexibility of this method has encouraged researchers to implement the analysis of protein spectra obtained by MALDI-TOF for the discrimination of close-related species and bacterial typing. In this study, a standardized methodology based on the detection of species-specific protein peaks from the spectra obtained with MALDI-TOF is described. The methodology was applied to a collection of Cryptococcus spp. (n=70) previously characterized by Amplified Fragment Length Polymorphism (AFLP) and sequencing of the ITS1-5.8S-ITS2 region. An expanded ad-hoc database was also built for their discrimination with MALDI-TOF. This approach did not allow the discrimination of the interspecies hybrids. However, the performance of peak analysis with the application of the PLS-DA and SVM algorithms in a two-step analysis allowed 96.95% and 96.55% correct discrimination of C. neoformans from the interspecies hybrids, respectively. Besides, PCA analysis prior to SVM provided 98.45% correct discrimination of the 3 analyzed species in a one-step analysis. The method is cost-efficient, rapid and user-friendly. The procedure can also be automatized for an optimized implementation in the laboratory routine.

Depression continues to be a glaring global challenge. The most worrisome trend is eating up the youthful generation more than anyone could predict years back. As Addis & Martell (2004) note, these adolescents end up succumbing to conditions that can be traced wholly from depression. Behavioral activation can be a rewarding intervention that will go a long way in cutting down on these cases and ensure the youthful global population's lives are safeguarded if applied and monitored to ensure correct and collective implementation processes and systems. The insights and arguments presented in the research paper will focus on the utility of behavioral activation in reducing depression cases among adolescents.

Analyses of faculty citation activity usually focus on counts as a function of author characteristics such as rank, gender, previous citation levels, and other factors influencing productivity and career path. Citation analyses of publications consider aspects such as number of authors, author reputation, author order, length of the title, methodology, and impact factors of the publication. While publication topics or discipline are considered to be important factors, they are more difficult to analyze, and therefore performed less frequently. This paper attempts to do that for the field of urban planning. Urban planning is multi-disciplinary and includes consideration of social, economic, technological, environmental, and political systems that shape human settlement patterns. It has been suspected that some topics are more “popular” and have larger audiences, therefore are cited more often. Using nearly 15,000 urban planning publications, this paper presents an analysis of topics to assess which are cited most frequently. The classification of publications was performed using a Support Vector Machine (SVM), a machine learning (ML) approach to text classification, using citation data from Google Scholar. The citation levels for the resulting categories are analyzed and discussed.

Polymethyl methacrylate (PMMA) polymer is widely used in various fields today. In order to thoroughly reveal the structural impact performance of PMMA materials, this paper is based on the comprehensive Johnson-Cook constitutive model and damage failure model, and accurately confirm the J-C constitutive and damage failure model parameters of PMMA through material test data, The dynamic process of steel bullet impacting PMMA plate structure is analyzed by finite element software ABAQUS. The calculation results show that the numerical simulation results in this paper are in good agreement with the experimental test data. Therefore, the feasibility and accuracy of the impact analysis of PMMA structures based on J-C constitutive and damage failure models in this paper are studied. Finally, based on the J-C constitutive model and damage failure model, the variation of the residual velocity of the bullet with the PMMA plate thickness is analyzed in depth, that is, the results show that the residual velocity of the bullet has a certain linear relationship with the plate thickness.

This study aimed to investigate the occurrence of the artificial sweetener aspartame (E951) in a wide range of foods and beverages sampled by food control authorities in Germany between 2000 and 2022. The dataset was obtained through the Consumer Information Act. The results showed that aspartame was present in a wide range of product groups tested, most commonly in powdered drink bases (84%) and flavored milk drinks (78%). In the solid food groups, the highest mean aspartame content was found in chewing gum (1543 mg/kg, n=241), followed by sports foods (1453 mg/kg, n=125), fiber supplements (1248 mg/kg, n=11), powdered drink bases (1068 mg/kg, n=162), and candies (437 mg/kg, n=339). Liquid products generally had the highest aspartame content in diet soft drinks (91 mg/l, n=2021), followed by regular soft drinks (59 mg/l, n= 574), flavored milk drinks (48 mg/kg, n=207), and mixed beer drinks (24 mg/l, n=40). These results suggest that aspartame is widely used in foods and beverages in Germany and that certain product groups contain higher concentrations of the sweetener than others. However, the levels of aspartame found were generally within the legal limits set by the European Union. These findings provide the first comprehensive overview of aspartame in the German food market and may be particularly useful in informing the forthcoming working groups of the WHO International Agency for Research on Cancer (IARC) and the WHO/FAO Joint Expert Committee on Food Additives (JECFA), which are in the process of evaluating the human health hazards and risks associated with the consumption of aspartame.

A low-cost data logging platform is presented for environmental monitoring projects that provides long-term operation in remote or submerged environments. Three premade “breakout boards” from the open-source Arduino ecosystem are assembled into the core of the platform. The components are selected based on low-cost and ready availability, making the loggers easy to build and modify without specialized tools, or a significant background in electronics. Power optimization techniques are explained. The platform has proven to be highly reliable, and capable of operating for more than a year on standard AA batteries. The flexibility of the system is illustrated with two ongoing field studies recording drip rates in a cave, and water flow in a flooded cave system.

One of the non-linear phenomena that affect high bandwidth and long reach communication systems is the non-linear phenomenon called four-wave mixing (FWM). Unfortunately, the simulation of such systems aiming to obtain their design parameter limitations require more time as the number of channels increases. In this paper, we propose a new high-performance computational model to obtain optimal design parameters in a multi san Dense Wavelength Division Multiplexing (DWDM) system, limited by FWM and the intrinsic Amplified Spontaneous Emission (ASE) noise of optical amplifiers employed in each segment. The simulation in this work provides a complete optical design characterization and compares the efficiency and speed improvement of the proposed parallelization model versus a previous sequential model. Additionally, an analysis of the computational complexity of parallel model is presented, where two parallel implementations are used. First, Open Multi−Processing (OpenMP), based on the use of a central, multi-core processing unit is used and secondly the Compute Unified Device Arquitecture (CUDA), which is based on the use of graphics processing unit. Results show that parallelism improves to up to 40 times the performance of the simulation when nested parallelization with CUDA is used, over de sequential method and up to 6 times compared with the implementation with OpenMP using 12 processors. Within our parallel implementation, it is possible to simulate with an increased number of channels, that was unpractical in the sequential simulation.

This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. In this case, the mutation parameter is dynamically moved during the evolution process by using a shadowed and general type-2 fuzzy systems. The main idea of this work is to make a performance comparison between using shadowed and general type 2 fuzzy systems as controllers of the mutation parameter in differential evolution. The performance is compared with the problem of optimizing fuzzy controllers for a D.C. Motor. Simulation results show that general type-2 fuzzy systems are better when higher levels of noise are considered in the controller.

The catalytic parameters describing enzyme catalysis are discussed in the context of the design of de novo enzymes. It is shown that high values of the catalytic efficiency may in some cases reflect tight substrate binding and lead to an immediate levelling-off of rates to reach a low plateau, an undesirable scenario for many industrial applications. It is argued that increasing the catalytic rate constant should be a main target in de novo enzyme engineering.

It remains unclear in the literature what is the cause of the so-called alkali-carbonate reaction (ACR) damage to concrete yet, a consensus is reached when considering dedolimitization as non-expansive. However, expansion and cracks as distress features are often attributed to alkali-silica reaction (ASR) when evidence of a reactive mineral is found in the aggregate. Evidently, different types of aggregates may produce different types and degrees of damage. Therefore, this work aims to assess the damage to concrete generated and propagated by the so-called ACR susceptible reactive Kingston coarse aggregate through mechanical testing (i.e., direct shear test), microscopy (the damage rating index – DRI), and other techniques. Distinct induced expansion levels (i.e., 0%, 0.05%, 0.12%, and 0.20%) were selected to compare the distress caused by ACR to concrete affected by ASR. Result show that the behaviour of ACR, namely as captured through the DRI, is inconsistent with that of ASR thus attesting to ACR being a distinct distress mechanism.

Thermostatically controlled loads have great potential to make a significant contribution to improving energy efficiency in the building sector, which is responsible for 40% of greenhouse gas emissions in the EU. This, in addition to the environmental damage, represents a huge expense in the electricity bill. Therefore, it is very important to train engineers on how to design energy management systems for TCLs. With this goal in mind, it would be very useful to have a simulation-based educational tool (SBET) to understand thermostatically controlled loads, their characteristics and possibilities in energy efficiency. In addition, it would be very useful if this tool could be introduced in engineering curricula to help students to be better trained and enter the labor market with more opportunities. Based on the shortcomings detected, this work develops a SBET specifically designed to teach about TCLs (SBET-TCLs), both about their intrinsic characteristics and their better management. To verify the developed SBET-TCL, it has been tested in a real scenario: A survey was carried out among the students of the subject 'Alternative Energy Sources' of the degrees of Industrial Engineering. The results show that the use of SBET-TCL has very positive effects on the learning process.

In industrial environments, nesting consists in cutting or extracting pieces from a material sheet, with the purpose of minimizing the surface of the sheet used. This problem is present in different types of industries, such as shipping, aeronautics, woodworking, footwear, and so on. In this work, the aim is to find an acceptable solution to solve complex nesting problems. The research developed is oriented to sacrifice accuracy for speed so as to obtain robust solutions in less computational time. To achieve this, a greedy method and a genetic algorithm have been implemented, being the latter responsible for generating a sequence for the placement of the pieces, where each piece is placed in its current optimal position with the help of a representation system for both the pieces and the material sheet.

The development of the smart city concept and the inhabitants’ need to reduce travel time, as well as society’s awareness of the reduction of fuel consumption and respect for the environment, lead to a new approach to the classic problem of the Travelling Salesman Problem (TSP) applied to urban environments. This problem can be formulated as “Given a list of geographic points and the distances between each pair of points, what is the shortest possible route that visits each point and returns to the departure point?” Nowadays, with the development of IoT devices and the high sensoring capabilities, a large amount of data and measurements are available, allowing researchers to model accurately the routes to choose. In this work, the purpose is to give solution to the TSP in smart city environments using a modified version of the metaheuristic optimization algorithm TLBO (Teacher Learner Based Optimization). In addition, to improve performance, the solution is implemented using a parallel GPU architecture, specifically a CUDA implementation.

The migration from MATLAB to Python (M-to-PY) has gained significant traction in recent computational research. While MATLAB has long served as a linchpin in myriad scientific endeavors, there's an emerging trend to rejuvenate these projects using Python's extensive AI tools and libraries. This study presents a semi-automated process for M-to-PY conversion, using a detailed case study of an image skeletonization project comprising fifteen MATLAB files and a 1404-image dataset. Skeletonization is foundational for ongoing 3D motion detection research using AI transformers, predominantly developed in Python. The utilization of ChatGPT-4, acting as an AI co-programmer, is pivotal in this conversion. By leveraging the public OpenAI API, we developed an M-to-PY converter prototype, evaluated its efficacy using test cases from the Bard bot, and subsequently employed the converted code in an AI application. The dual contributions encompass a well-tested M-to-PY converter and a Skeleton App capable of sketching and skeletonizing any given image, enriching the AI toolset. This study accentuates how AI resources, like ChatGPT-4, can simplify code transitions, opening doors for innovative AI implementations using primarily MATLAB-coded scientific research.

HIV-1 transcribes only one kind of transcript – the full length genomic RNA. To make the mRNA transcripts for the accessory proteins Tat and Rev, the genomic RNA must completely splice. The mRNA transcripts for Vif, Vpr, and Env must splice but not completely. Genomic RNA (which also functions as mRNA for the Gag and Gag/Pro/Pol precursor polyproteins) must not splice at all. HIV-1 can tolerate a surprising range in the relative abundance of individual transcript types, and a surprising amount of aberrant and even odd splicing; however, it must not over-splice, which results in the loss of full length genomic RNA and has a dramatic fitness cost. Cells typically do not tolerate unspliced/incompletely spliced transcripts, so HIV-1 has to circumvent this cell policing mechanism to allow some splicing while suppressing most. Splicing is controlled by RNA secondary structure, cis-acting regulatory sequences which bind splicing factors, and the viral protein Rev. There is still much work to be done to clarify the combinatorial effects of these splicing regulators. These control mechanisms represent attractive targets to induce over-splicing as an antiviral strategy. Finally, splicing has been implicated in latency, but to date there is little supporting evidence for such a mechanism. In this review we apply what is known of cellular splicing to understand splicing in HIV-1, and also present data from our newer and more sensitive deep sequencing assays quantifying the different HIV-1 transcript types.

The primary attraction of IaaS is providing elastic resources on demand. It becomes imperative that IaaS-users have an effective methodology for learning what resources they require, how many resources and for how long they need. However, the heterogeneity of resources, the diversity resource demands of different cloud applications and the variation of application-user behaviors pose IaaS-users big challenge. In this paper, we purpose a unified resource demand forecasting model suiting for different applications, various resources and diverse time-varying workload patterns. With the model, taking input from parameterized applications, resources and workload scenarios, the corresponding resources demands during any time interval can be deduced as output. The experiments configure concrete functions and parameters to help understanding the above model.

Adolescent alcohol and marijuana use pose significant developmental risks. This study examined internalizing and externalizing problems as risk factors and prospective self as a protective factor in relation to alcohol and marijuana use. Self-report data were collected from a diverse sample (N = 2017) of 15-17-year-olds using the Youth Self Report (YSR) for behavior issues and Prospective Self, a factor derived variable reflecting future orientation, resistance to peer influence, and academic aspirations. Participants reported on 15 health risk behaviors, including alcohol and marijuana use. Weighted linear regressions evaluated associations between risk and protective factors and substance use. Model 1 included sociodemographic covariates. Model 2 added risk and protective factors, and Model 3 included interactions of internalizing and externalizing behaviors with prospective self. Results indicated higher externalizing behavior was linked to increased alcohol and marijuana use, while higher prospective self and internalizing behavior were linked to reduced alcohol use. Higher prospective self was associated with less marijuana use. Interaction terms were largely non-significant, except for the interaction between prospective self and internalizing behavior, where higher internalizing problems and high prospective self were linked to increased marijuana use. Findings highlight the importance of prospective self, especially at clinically elevated levels of behavior problems, and suggest further exploration of the unexpected positive association between internalizing behavior and prospective self with marijuana use.

The transverse momentum distribution of J/ψ mesons produced in pp collisions at the center-of-mass energy 5 TeV, 7 TeV，and 13 TeV is described by the modified Hagedorn function which is based on the Tsallis function and Hagedorn function. The calculated results by the modified Hagedorn function are in accord with experimental data measured by the LHCb Collaboration at LHC. The related parameters are obtained and analyzed.

Considered one of the finest first-generation Nigerian writers, John Pepper Clark-Bekederemo, who passed away on 13th October, 2020, had been categorised as a Eurocentric writer. This work assesses the authenticity or otherwise of this critics’ perception of Clark by critiquing his America, their America. By analysing this autobiography vis-à-vis the notion of self and other which is a theoretical concern in contemporary travel writing, it was established, among other things, that every culture has its dark sides which it must not feel too proud to change as time and situation demand; that Clark vehemently rejects the Americans’ claim of sophistication and superiority of their culture over African culture. The paper concludes that contemporary travel writing should be a rightful site for negotiating cultural, political and diplomatic compromises between the Self and the Other since the gulf may be difficult to close altogether.

This paper proposes training improvement methods of artificial neural networks (ANN) trajectory predictors. First, a dynamic power system time-series trajectory is split into several different segments to simplify the original ANN training problem. Moreover, the time-derivative of the trajectory is included to obtain an augmented loss function. Compared to previous studies which mainly focused on increasing the prediction accuracy, the aim of these novel techniques is to reduce the computational burden where the ANN output performance is still acceptable. The effectiveness of the developed methods is validated based on the WSCC three-machine nine-bus and IEEE 39-bus system models. The mean absolute error (MAE) and trajectory prediction results are analyzed, in which the numbers of neurons, hidden layers, and training epochs are constrained during the ANN training process. Rotor-angle difference between generators and the system frequency are investigated as the dynamic trajectories of the power system models. It is revealed that when the ANN architecture and epochs are constrained, the MAE results can be reduced, and the ANN training results can better reflect the original trajectory using the improvement approaches.

Based on collected power generation data associated with solar irradiance, PV system conversion efficiency and cell temperature, an hourly solar PV power estimation model by a parallel artificial neural network (ANN) and particle swarm optimization (PSO) algorithm is proposed. Weight matrices related to different seasons and geographic areas for estimation power generations have been trained by real measured operation data. The parallel PSO algorithm with heuristic global optimization technique assists the ANN training process to get near optimal solutions precisely. The accuracy and reliability of estimation is audited by actual details of photovoltaic power stations in various regions and scales. The results of estimation model can not only assist the electricity dispatcher to explicitly monitor the trend of solar power generation in different areas, but also coordinate with traditional power plants to meet load demand more accurately. The presented model will bring benefits to power dispatching for larger scales of intermittent and unstable solar power generation.

Variations in groundwater levels that are noticed in different parts of the world are typically the primary focus of research carried out in hydrology. The fluctuating levels of groundwater can be ascribed to several different factors, some of which include an increase in the demand for water, inappropriate irrigation practices, improper management of soil, and unregulated extraction from aquifers. It is necessary to effectively manage groundwater resources to have a trustworthy method of measuring and forecasting groundwater levels. The dynamics of groundwater are inherently uneven and difficult to understand. As a result, applying methods driven by data could potentially yield significant gains in hydrology. In this study, two data-driven models were utilized to estimate groundwater levels at a total of 4 monitoring wells located in Colorado state, USA. These models included ARIMA and ANN. The comparative analysis of the algorithms made use of a data set that had one month's worth of information from each of the years 1980 to 2019. The models were put through their paces, and the results of those tests were statistically and visually assessed. To evaluate the relative accuracy and precision of the models, the mean absolute error (MAE), mean square error (MSE), and root-mean-square error (RMSE) were used. When compared to ARIMA, the analysis demonstrates that ANN can produce the most accurate forecasts of groundwater levels in Colorado state USA.

Tailings generated by mining account for the largest proportion of global waste from industrial activities. Copper is relatively uncommon world-wide, with low concentrations in sediments and waters, yet is very elevated around mining sites. On the Keweenaw Peninsula of Michigan, USA, jutting out into Lake Superior, 140 mines extracted native copper from the Portage Lake Volcanic Series, part of an intercontinental rift system. Between 1901-1932, two mills at Gay (Mohawk, Wolverine) sluiced 22.7 million metric tonnes (MMT) of copper-rich tailings (stamp sands) into Grand (Big) Traverse Bay. Here we examine: 1) 3D coastal elevation and reef bathymetry, 2) particle dispersal, 3) copper concentrations and leaching, plus 4) shoreline toxicity. About 10 MMT of tailings created a migrating coastal beach that stretches 7 km from the Gay pile to the Traverse River Seawall. Another 10 MMT are moving underwater on the coastal shelf, threatening Buffalo Reef, an important lake trout and whitefish breeding ground. Aerial photos, ALS (plane) LiDAR, and relatively inexpensive UAS (drone) surveys characterize shoreline structure and aid initial remediation. Because sands (natural beach quartz, stamp sand basalt) are silicates of similar density, particle dispersal is similar and challenging. However, stamp sand beaches contrast greatly with natural sand beaches in both physical profile and chemistry. Dispersing particles retain copper, and release toxic concentrations. Leaching is elevated by exposure to high DOC and low pH waters. Field experiments, shoreline seining, and benthic sampling confirm serious impacts on aquatic biota, supporting tailings removal.

Recent advancements in neural language models, particularly attention-based architectures like the Transformer, have substantially surpassed traditional methods in various natural language processing tasks. These models adeptly generate nuanced token representations by considering contextual relations within a sequence. However, augmenting these models with explicit syntactic knowledge, such as part of speech tags, has been found to remarkably bolster their effectiveness, especially under constrained data scenarios. This study introduces the Linguistic Enhanced Transformer (LET), which integrates multiple syntactic features, showing a notable increase in translation accuracy, evidenced by an improvement of up to 1.99 BLEU points on subsets of the WMT '14 English-German dataset. Furthermore, this paper demonstrates that enriching BERT models with syntax-aware embeddings enhances their performance on several GLUE benchmark tasks.

In the paper, we explore the notion of global digital citizenship, particularly with respect to museums and cultural heritage organizations. In this perspectives study, we explore current examples of how museums can adapt to the tenets of global digital citizenship necessary to navigate and participate in increasingly interconnected digital worlds and culture, and to collectively address global challenges.

The literature on substance use usually extracts conclusions from data with correlational methods. Our study shows the usefulness of complementing ordered logistic regression (OLR) and fuzzy set qualitative comparative analysis (fsQCA) to assess factors inducing cannabis consumption in a sample of 1,935 teenagers. OLR showed a significant influence of gender (odd ratio (OR) =0.383, p<0.0001), parental monitoring (OR=0.587, p=0.0201); religiousness (OR=0.476, p=0.006); parental tolerance to substance use (OR=42.01, p<0.0001) and having close peers that consume substances (OR=5.60, p<0.0001). FsQCA has allowed fitting linkages between factors from a complementary perspective. (1) Coverage (cov) and consistency (cons) attained by solutions explaining use (cons=0.808, cov=0.357) are clearly lower than by recipes of non-use (cons=0.952, cov=0.869) (2) The interaction of gender, a tolerant family to use and the attitude toward substances by peers is very consistent to explain cannabis use. (3) The most important recipe explaining resistance to cannabis is simply parental disagreement with substance consumption (cons=0.956, cov=0.861) (4) Factors as gender, religiosity, parental monitoring and age show also a relevant impact on attitude toward cannabis use. However, whereas some of them impact symmetrically on use and non-use this does not follow in factors such as parental monitoring or age.

This literature review focusses on diagnostics of Equine Asthma (EA), possible influencing factors on diagnostic techniques and latest developments in diagnosing horses during EA remission or in case of subclinical disease. Routine EA diagnostics include clinical examination of the respiratory system including percussion and auscultation, clinical pathology including white blood cells and arterial blood gas analysis, bronchoscopy to evaluate the amount and viscosity of respiratory secretion, bronchoalveolar lavage and cytology of tracheal aspirates (TA) and bronchoalveolar lavage fluid (BALF). Grading of EA severity and inflammatory subtype is based on BALF cy-tology, while TA cytology helps to rule out previous bacterial infections. Different factors have an impact on the airways regarding structure of the epithelium, cytology and inflammatory markers possibly influencing the diagnosis of EA. Short-term exercise increases the total cell count and inflammatory mediators in BALF of men, asymptomatic horses and other species. Further factors involve cold or chlorinated air, long-term training effects and the co-incidence of further respir-atory disease, in particular exercise-induced pulmonary hemorrhage. As BALF cytology may be unremarkable during EA remission and low-grade disease, exercise and other factors stressing the bronchial epithelium may help to diagnose these patients.

Chagas disease (CD) is one of the most devasting parasitic diseases in the Americas affecting 7 to 8 million people worldwide. In vitro and in vivo experiments have demonstrated that decreased growth hormone (GH) serum levels occur as CD progresses. Interestingly, inactivating mutations in the GH receptor in humans induce Laron syndrome (LS), a clinical entity characterized by increased GH and decreased insulin growth factor-1 (IGF-1) serum levels. The largest cohort of LS subjects lives in the southern provinces of Ecuador. Remarkably, CD prevalence in these individuals is diminished despite living in highly endemic areas. In the current ex vivo study, we employed serum from GHR -/- mice, also known as LS mice (a model of GH resistance with high GH and low IGF-1 levels), and serum from bovine GH (bGH) transgenic mice (high GH and IGF-1), to test the effect on T. cruzi infection. We infected mouse fibroblast L-cells treated with serum from each type of mouse with metacyclic trypomastigotes from Trypanosoma cruzi (etiological CD infectious agent). Treatment with GHR-/- serum (LS mice) significantly decreased infection by 28% compared to 48% seen in control wild-type mouse serum (WT). Treatment with bGH mouse serum significantly decreased infection by only 41% compared to 54% from WT controls. Our results suggest that high GH and low IGF-1 in blood circulation, as typically seen in LS individuals, confers partial protection against T. cruzi infection.

Assistance dogs provide significant benefits to older adult owners. However, despite protective legislation, aged care facilities continue to not allow owners to retain their dog on relocation. The purpose of the current study was to explore whether older adults should be allowed to retain their dog on relocation to an aged care facility, and what factors should impact this decision. Further, if allowed to retain their dog, what would be the best practice to allow for this. A deliberative democracy methodology was used, with a range of key stakeholders recruited. Focus groups were held, with follow up questionnaire to establish deliberation for all questions. Results indicated that with sufficient objective measurement, fair decisions can be made to ensure the welfare and wellbeing for owner and dog. Key policy and procedure changes would also be necessary to ensure ongoing support, such as training, care plans, and emergency directives. By ensuring sufficient policies and procedures are in place, training and support could lead to an ideal outcome where facilities could be at the forefront of a better future for aged care.

Objectives: 1) to demonstrate the anti-inflammatory and anabolic effect of Ozone by determining in serum samples the biochemical levels of IL-6 and IGF-1 in knee osteoarthritis (OA) patients in a real world in Rehabilitation Setting; 2) to evaluate clinical effectiveness by Visual Analog Scale (VAS) and WOMAC scale, and biochemical effect by C-reactive protein (CRP), uric acid and erythrocyte sedimentation rate (ESR). Material and methods: 65 patients with knee OA Kellgren Lawrence (KL) grade 2 or more were analyzed in a retrospective observational study. The study run from January 2018 to September 2021. Inclusion criteria: a) patients 18 years or older; b) with knee OA KL 2º or more; c) biochemical analysis before-and-after treatment; d) pain more than 3 on VAS. Exclusion Criteria: a) previous knee surgery; b) favism; c) pregnancy; d) any other disease that originates lack of collaboration for infiltration. Primary Outcome variables: a) IL-6; b) IGF-1 in diabetes mellitus (DM)/obese and non-DM/non-obese patients; both before-and-after Ozone treatment. Secondary Outcome variables: a) CRP, b) ESR, c) uric acid, d) VAS pain, e) WOMAC pain, function and stiffness. Ozone protocol consisted of 4 sessions (once a week) of an intra-articular infiltration of 20 mL (20µg/mL concentration) of a gas mixture of Oxygen-Ozone 95-5% (produced by Ozone generator Ozonosan-α Plus ®). For biochemical evaluation, SNIBE MAGLUMI ™ IL-6 (CLIA) and SNIBE MAGLUMI ™ IGF-1 (CLIA) kits were used. CRP and uric acid were analyzed by Abbott Alinity c kit; and ESR was evaluated by DIESSE VES MATIC CUBE 30. Results: There is a linear correlation between age and OA severity. IL-6 decreased both in DM and non-DM patients and in all OA KL grades (from 2.7 to 1.59 pg/mL). IGF-1 decreased in total group (OA + DM + obesity) from 112.09 to 107.19 ng/mL. When only knee OA patients were analyzed, Ozone improved IGF-1 levels (from 100.17 to 102.03 ng/mL). Ozone decreased CRP, ESR, uric acid, and improved VAS pain, WOMAC pain, function and stiffness (p<0.05). Conclusions: Ozone is a valid option for the management of knee osteoarthritis in real world Rehabilitation Setting, because of its anti-inflammatory, metabolic and anabolic properties. Ozone downregulates pro-inflammatory IL-6 cytokine. Ozone has a metabolic/hypoglycemic effect on obese/diabetic knee osteoarthritis patients by reducing IGF-1. Ozone has an anabolic effect on non-diabetic/non-obese patients by improving IGF-1. Ozone reduces other biomarkers of inflammation (CRP, ESR and uric acid) and improves, pain, function and quality of life.

Lifespan extension was recently achieved in Caenorhabditis elegans nematodes by mitochondrial stress and mitophagy, triggered via iron depletion. Conversely in man, deficient mitophagy due to Pink1/Parkin mutations triggers iron accumulation in patient brain and limits survival. We now aimed to identify murine fibroblast factors, which adapt their mRNA expression to acute iron manipulation, relate to mitochondrial dysfunction and may influence survival. After iron depletion, expression of the plasma membrane receptor Tfrc with its activator Ireb2, the mitochondrial membrane transporter Abcb10, the heme-release factor Pgrmc1, the heme-degradation enzyme Hmox1, the heme-binding cholesterol metabolizer Cyp46a1, as well as the mitophagy regulators Pink1 and Parkin showed a negative correlation to iron levels. After iron overload, these factors did not change expression. Conversely, a positive correlation of mRNA levels with both conditions of iron availability was observed for the endosomal factors Slc11a2 and Steap2, as well as for the iron-sulfur-cluster (ISC)-containing factors Ppat, Bdh2 and Nthl1. Positive correlation only after iron depletion was observed for the iron export factor Slc40a1, mitochondrial iron transporters Slc25a28, Abcb7 and Abcb8, mitochondrial ISC-containing factors Glrx5, Nfu1, Bola1 and Abce1, cytosolic Aco1 and Tyw5, as well as nuclear Dna2, Elp3, Pold1 and Prim2. The latter are regulators of nucleotide synthesis and DNA quality control, which have known importance for growth and lifespan. The only Pink1-/- triggered transcript modulation was the reduced expression of the ISC-containing ribosomal factor Abce1. These mammalian findings support previous fly data that Pink1 influences co-translational quality control via Abce1, as well as mitophagy. Our findings provide the first systematic survey how iron dosage triggers homeostatic transcriptional regulations and elucidate how iron deprivation results in mitophagy.

It is estimated that about 50% of geriatric rehabilitation patients suffer from sarcopenia. Thereby, malnutrition is frequently associated with sarcopenia and dietary intake is the main modifiable risk factor. During hospitalization, older adults are recommended to consume more dietary protein than the current recommended dietary allowance of 0.8 g/kg body weight per day to optimize the recovery of muscular strength and physical function. This prospective study examined the effect of a short-term protein supplementation with protein-enriched foods and drinks on hand-grip strength, nutritional status and physical function in older patients at risk of malnutrition during a three week inpatient orthopedic rehabilitation stay. The Mini Nutritional Assessment (MNA) was used to assess malnutrition. Patients with a MNA score ≤ 23.5 points were randomly assigned to an intervention group (goal: to consume 1.2–1.5 g protein/kg body weight per day) or a control group (standard care). Both groups carried out the same rehabilitation program. Physical recovery parameters were determined at admission and discharge. There was a trend for participants in the intervention group to consume more protein than the control group (P = 0.058): 95.3 (SD 13.2) g/day as compared to 77.2 (SD 24.2) g/day, which corresponds to a mean protein intake of 1.6 (SD 0.3) g/kg/day vs. 1.3 (SD 0.5) g/kg/day. Dietary protein supplementation increased body weight by an average of 0.9 (SD 1.1) kg and fat mass by an average of 0.9 (SD 1.2) kg as compared with baseline (P = 0.039 and P = 0.050, respectively). There was no significant change in hand-grip strength, body composition and physical function. In conclusion, a short-term intervention with protein-enriched foods and drinks enabled older patients at risk of malnutrition to increase their protein intake to levels that are higher than their required intake. In these older individuals with appropriate protein intake, dietary protein supplementation did not result in a greater improvement in physical recovery outcomes during short-term inpatient rehabilitation. The intervention improved dietary protein intake, but further research (e.g., a full-scale randomized controlled trial with sufficient power) is required to determine the effects on physical function outcomes.

Offshore vessels (OVs) often requires precise station-keeping and some vessels, for example, vessel involves in geotechnical drilling generally use Spread Mooring (SM) or Dynamic Positioning (DP) systems. Most of these vessels are equipped with both systems to cover all ranges of water depths. However, determining which systems to use for a particular operational scenario depends on many factors and requires significant balancing in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors for both the SM and DP station keeping systems. Operational information and cost data are collected for several field operations, and Artificial Neural Networks (ANN) is trained using those data samples. After that, the trained ANN is used to predict the components of cost for any given environmental situation, fieldwork duration and water depth. Later, the total cost is investigated against water depth for both DP and SM systems to determine the most cost-effective option. The results are validated using two operational scenarios for a specific geotechnical vessel. This decision-making algorithm can be further developed by adding up more operational data for various vessels and can be applied in the development of sustainable decision-making business models for OVs operators.

Smart buildings concept aims at the use of the smart technology to reduce energy consumption as well as improvement of the comfort conditions and users’ satisfaction. It is based on the use of smart sensors to follow both outdoor and indoor conditions as well as software for the control of comfort and security devices. The optimal control of the energy devices requires software for indoor temperature forecasting. This paper presents an ANN – based model for the indoor temperature forecasting. The model is developed using data recoded in an old building of the engineering school Polytech’Lille. Data covered both indoor and outdoor conditions. Analysis of the relevance of the input parameters allowed to develop a simplified forecasting model of the indoor temperature that uses only the outdoor temperature as well as the history of the façade temperature as input parameters. The paper presents successively, data collection, the ANN concept used in the temperature forecasting, and finally the ANN model developed for the façade and indoor forecasting. It shows that an ANN-based model using outdoor and façade temperature sensors provides a good forecasting of the indoor temperature. This model could be used for the optimal control of buildings energy devices.

Background: The management of gestational diabetes mellitus (GDM) focuses on dietary interventions, physical activity, and pharmacological therapy. Strategies that enhance adherence to the diet could play a pivotal role in managing this population. Objective: To compare the effectiveness of outpatient nutritional guidance supplemented by digital media with exclusively standard outpatient nutritional guidance in pregnant women with GDM. Methods: This was a randomized, patient-blinded clinical trial conducted at the Diabetes and Pregnancy outpatient clinic from February 2021 to January 2023. Pregnant women with GDM were randomly allocated into two groups: the Control Group (CG) received exclusively outpatient nutritional guidance, and the Intervention Group (IG) received outpatient nutritional guidance along with reminders via WhatsApp. Dietary intake (calories, carbohydrates, lipids, proteins, and fibers) was evaluated using 24-hour dietary recalls (24HR). Glycemic control and the need for pharmacological treatment were also assessed. Mann-Whitney tests were applied to numerical variables, and Fisher's exact test or Chi-square tests were used for categorical variables. Results: 81 women were included, 34 allocated to the CG, and 47 to the IG. Patients were followed for a period of 4 to 8 weeks. Few differences were observed in glycemic control between the two groups over the follow-up period. There were no statistical differences in pharmacological therapy (p=0.498); 188 24HR were conducted in the CG and 290 in the IG. A statistically significant increase in lipid intake was observed in the IG over the follow-up period compared to the CG (p

In this article, the evolution in space and in time of the coronavirus pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries. Self-organizing neural networks possess the capability for clustering countries in the space domain based on their similar characteristics with respect to their coronavirus cases. In this form enabling finding the countries that are having similar behavior and thus can benefit from utilizing the same methods in fighting the virus propagation. To validate the approach, publicly available datasets of coronavirus cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of time series of the countries. Then, a hybrid combination of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient COVID-19 forecasting of the countries. Relevant conclusions have emerged from this study, that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. A lot of the existing works concerned with the Coronavirus have look at the problem mostly from the temporal viewpoint that is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant to improve the forecasting ability. The most relevant contribution of this article is the proposal of combining neural networks with a self-organizing nature for clustering countries with high similarity and the fuzzy fractal approach for being able to forecast the times series and help in planning control actions for the Coronavirus pandemic.

Fats and oils are the most common contaminants in wastewater and are usually discarded through physical processes. This paper studies its elimination through an environmentally friendly biological treatment, yielding good results on both laboratory scale and in the field. In this study a comparative evaluation of the biodegradation of fats and oils in two scenarios were developed in an activated sludge plant at laboratory scale, and a wastewater treatment plant. The full-scale values for some key parameters are compared, such as the oil concentration in the influent and effluent, mass loading and removal efficiency and biodegradation systems. Activated sludge plant at laboratory scale working on a mass load range from 0.2 to 0.8 (kg COD / day / kg MLSS) initially reaches levels of 75% biodegradation thereafter influent concentration is increased and thereby the mass load is increased in a range of working system under high load and biodegradation rates ranging from 71 to 64% are achieved. The actual system consists of a treatment plant wastewater with an aerobic digester for sludge treatment. Fats and oils are retained in a previous degreaser to biological treatment and subsequently sent to the aerobic sludge digester, constituting of thus on a single substrate, resembling an activated sludge plant with extended aeration mode, and levels of biodegradation in the range of 69 to 92%. From this work, we can say that the choice of biological treatment for fats and oils is feasible and adequate. Furthermore, the biomass presents great adaptability to the oil substrate, favored in this case for being the only source of carbon, therefore fats and oils should be removed using biological treatment, instead of the flotation procedure or at most using it as an intermediate process

Mitochondria are involved in many cellular processes and their main role is cellular energy production. They constantly undergo fission and fusion, and these counteracting processes are under strict balance. The cytosolic dynamin-related protein 1, Drp1 or dynamin-1-like protein (DNM1L) mediates mitochondrial and peroxisomal division. Defects in the DNM1L gene results in a complex neurodevelopmental disorder with heterogeneous symptoms affecting multiple organ systems. Currently there is no curative treatment available for this condition. We have previously described a patient with a de novo heterozygous c.1084G>A (p.G362S) DNM1L mutation and studied the effects of a small molecule, Bezafibrate, on mitochondrial functions in this patient’s fibroblasts compared to controls. Bezafibrate normalized growth on glucose-free medium, ATP production, oxygen consumption and s improved mitochondrial morphology in patient’s fibroblasts, albeit concomitantly causing a mild increase ROS production. Further studies would be needed to show the consistency of the response to Bezafibrate, possibly using fibroblasts from patients with different mutations in DNM1L, and this treatment should be confirmed in clinical trials. However, taking into account the favorable effects in our study, we suggest that Bezafibrate could be a possible treatment option for patients with certain DNM1L mutations.

Globally, between 10% and 15% of couples experience infertility. Given the high demand for Assisted Reproductive Techniques (ART), there is growing interest in exploring modifiable factors influencing their outcomes. In this context, the objective of this review was to investigate the impact of adherence to the Mediterranean Diet (MD), recognized for its benefits in reproductive health, on ART outcomes. Methodology: A systematic review was conducted following the PRISMA methodology. International databases were consulted, selecting studies published between 2010 and 2023, in English and Spanish, involving patients aged 18-55, and examining intermediate and/or clinical outcomes of ART. Systematic reviews, meta-analyses, and animal studies were excluded. Results: Of the 9 included articles, 5 found statistically significant associations between adherence to the MD and positive outcomes in ART, such as a higher number and quality of embryos, clinical and biochemical pregnancy, and live births. However, other studies found no such associations. Conclusions: There is a potential association between adherence to the MD and ART outcomes. The evidence is very limited, necessitating further investigation.