Studying models of healthy aging and exceptional longevity is crucial to understand a possible longevity signature as most of them show resistance to age-related diseases. In particular, semi- and supercentenarians are a highly selected group, having survived significant adversities, including the Spanish Flu and COVID-19 pandemics, indicating distinctive immune system characteristics. This paper analyse the inflammatory scores (INFLA-score, Systemic Inflammation Response Index (SIRI)) and Aging-Related Immune Phenotype (ARIP) indicators calculated from the dataset of the DESIGN project, including 249 participants aged 19-111 years, trying to understand the immune-inflammatory (IMFLAM) role to achieve longevity. Statistical analyses, including linear regression and one-way ANOVA, were performed to explore the correlations between these parameters and age. Both INFLA-score and SIRI showed a significant increase with age. However, no statistical difference is observed when analysing the values for semi- and supercentenarians with those for other age groups, whose values are similar to that of adults and less than younger centenariansRegarding ARIP values, it is noteworthy that when comparing the CD8 Naive/Effector scores between groups, no significant differences were observed between the semi- and supercentenarian group and the other groups. These results support the idea that the control of IMFLAM response can promote extreme longevity.

Background: The coexistence of HIV infection and latent tuberculosis infection (LTBI) presents a significant public health concern due to the increased risk of tuberculosis (TB) reactivation and progression to active disease. The multicenter observational cohort study, TUBHIVIT, conducted in Italy from 2017 to 2023, aimed to assess the prevalence of LTBI among people living with HIV (PLHIV) and their outcomes following LTBI screening and therapy initiation. Methods: We performed a prospective study in 5 referral centers for HIV care in Italy. PLHIV who consented to participate underwent QuantiFERON-TB Gold Plus and clinical, microbiological, and radiological assessments to exclude subclinical tuberculosis, as opportune. PLHIV diagnosed with LTBI that started chemoprophylaxis were followed until the ending of therapy. Results: A total of 1105 PLHIV were screened for LTBI using the QuantiFERON-TB Gold Plus test, revealing a prevalence of 3.4% of positive results (38/1105). Non-Italy-born individuals exhibited a significantly higher likelihood of testing positive. Thirty-one were diagnosed with LTBI, 1 showed active subclinical TB, 6 were lost to follow-up before discriminating between latent and active TB. Among PLHIV diagnosed with LTBI, 83.9% (26/31) started chemoprophylaxis. Most individuals received 6-9 months of isoniazid-based therapy. Of the 26 PLHIV commencing chemoprophylaxis, 18 (69.2%) completed the therapy, while 3 discontinued it and 5 were still on treatment at the time of the analysis. Adverse events were observed in two cases, while in one case the patient refused to continue the treatment.

This study addresses the importance of conducting mass movement susceptibility mapping and hazard assessment using quantitative techniques, including machine learning, in the Northern Lima Commonwealth (NLC). Previous exploration of the topographic variables revealed high correlation and multicollinearity among some of them, which led to dimensionality reduction through principal component analysis (PCA). Six susceptibility models were generated using weights of evidence, logistic regression, multilayer perceptron, support vector machine, random forest, and naive Bayes methods to produce quantitative susceptibility maps and assess the hazard associated with two scenarios: the first being an El Niño phenomenon and the second being an earthquake exceeding 8.8Mw. The main findings indicate that machine learning models exhibit excellent predictive performance for the presence and absence of mass movement events, as all models surpassed an AUC value of >0.9, with the random forest model standing out. In terms of hazard levels, in the event of an El Niño phenomenon or an earthquake exceeding 8.8Mw, approximately 40% of the NLC area would be exposed to the highest hazard levels. It also highlights the importance of integrating methodologies to reduce model uncertainty, such as comprehensive analysis of variables supported by high quality data and organized workflows. The findings of this research are expected to serve as a supportive tool for land managers in formulating effective disaster prevention and risk reduction strategies.

Although the spanwise periodicity within the gap between two tandem circular cylinders has been observed by some researchers, there is a lack of systematic study on the properties of this pe-riodicity. For the spanwise periodicity within the gap, this study aims to ascertain its characteris-tics, its influences on the flow field, and its variation trend with increasing spacing ratio. By nu-merically simulating the flow around two tandem circular cylinders with a diameter ratio of d/D=0.6 and seventeen spacing ratios (L/D=1.00~6.00) at Re=3900, this study shows four flow re-gimes: Reattachment Flow (L/D=1.00~3.15), Bi-stable Flow (L/D=3.24), Intermittent Lock-in Co-shedding (L/D= 3.30~3.50) and Subharmonic Lock-in Co-shedding (L/D=4.00~6.00). Further, de-pending on the spanwise periodicity length of the time-averaged flow structures (i.e. Pz) within the gap, Reattachment Flow is, for the first time, subdivided into three new sub-flow regimes: Small-scale Periodic Reattachment (L/D=1.00~1.50, Pz/D=(0, 4]), Large-scale Periodic Reattachment (L/D=2.00~2.25, Pz/D>4) and Non-periodic Reattachment (L/D=2.50~3.15, no spanwise periodicity). The formation mechanisms are elaborated by analyzing the combined effect of both the L/D value and the spanwise-averaged time-averaged reattachment angle of the downstream cylinder. Moreover, this study proves that the newly-defined Small-scale Periodic Reattachment and Large-scale Periodic Reattachment are responsible for the pronounced asymmetry of the flow along the transverse direction within the gap. In addition, detailed flow properties and statistical pa-rameters are provided for each flow regime, such as velocity, vorticity, force coefficient, separa-tion/reattachment angle, Strouhal number and Q-criterion.

Abstract: Background: Exercise Training at work has the potential to improve employees’ produc-tivity, health, and well-being. However, exercise interventions to healthcare workers in hospitals may be challenged by a high time pressure and the ongoing workflow with patient care. Objective: The aim was to identify barriers and facilitators for participation in exercise training during work in a hospital department. Methods: Eight semi-structured interviews were conducted with hospital employees of different staff groups, who participated in 12 weeks exercise twice weekly. The data analysis was a thematic approach based on the Theoretical Domains Framework and the COM-B factors in the Behavior Change Wheel. Results: Barriers and facilitators varied between different groups. Barriers included limited structure, busyness, and a discouraging culture. Facilitators in-cluded gaining a feeling of community, psychological and physical well-being. Seven contextual subthemes were vital for successful implementation of exercise in a hospital setting. Conclusions: The informants appreciated exercise training during work and wished to participate. Inpatient departments’ informants had difficulties participating in the intervention, whilst those with more administrative tasks found it easier. This study identified barriers and facilitators vital for a successful implementation of an exercise training intervention in a hospital department to improve health, wellbeing, and productivity amongst hospital employees. It explains how future interventions can improve reach, adoption, and implementation of exercise training interventions for hospital staff.

Understanding vaccine hesitancy in organ transplant recipients (OTR) is critical, given clear, alt-hough attenuated, benefits from vaccination. Adult OTR were surveyed regarding vaccine-related values and a novel outcome variable called Vaccine Acceptance Composite Score (VACS) was built as the average Likert score of 7 domains of vaccination confidence. Of 46 OTR included (93.5% kidney transplant recipients), 32.6% were female, 13.3% Black, 6.77% Hispan-ic/Latino/a/x; median age was 58 years. Patients were most concerned about COVID-19 vac-cine-associated risks (46.3%), its potential effect on allograft (47.6%) and motives of government officials involved with vaccine policy (55.6%). Politically conservative patients were likely to have a significantly lower VACS, while those who lived with someone ≥65 had a higher VACS. The VACS was not significantly associated with race, income, religious beliefs, comorbidities, COVID-19 history, or influenza vaccination status. Higher VACS was significantly associated with ≥3 and ≥4 COVID-19 immunizations. This study highlighted political beliefs and elderly household members as correlates of vaccine acceptance among OTR. The VACS may be a useful tool to help standardize multifaceted analyses in vaccination-focused behavioral research, as well as identify individuals and groups at risk for vaccine hesitancy, who may benefit from tai-lored outreach and educational interventions.

This study aims to analyse the technical viability and economic feasibility of rainwater harvesting systems for single and multifamily residential buildings in the city of Florianópolis, Brazil. Simulations were conducted for representative buildings in the city under different water usage scenarios and system designs, in a total of 36 simulation scenarios. An economic analysis was performed for four scenarios over a twenty-year period. Both initial and operational costs were considered and net present value, internal rate of return and payback used as feasibility indicators. Almost all of the cases simulated were technically viable for the group of houses, and up to 78.9% for flats. As for the economic analysis, for houses, between 60.1% and 74.8% of the cases were economically feasible, achieving a discounted payback period ranging from 6.2 to 8.6 years. For flats, between 57.8% and 64.2% of the cases were economically feasible, achieving a discounted payback period ranging from 4.8 to 5.6 years. As the water tariff in the city underwent changes recently, the former and current tariff formats were compared. The current tariff format provides more economic benefits for saving potable water, and leads to a higher net present value and a shorter discounted payback period.

Yttrium oxide (Y2O3) resistive random-access memory (RRAM) devices were fabricated using the sol–gel process on indium tin oxide/glass substrates. These devices exhibited conventional bipolar RRAM characteristics, without requiring a high voltage forming process. The effect of current compliance on the Y2O3 RRAM devices was investigated and revealed that as the set current compliance values increased, the resistance values gradually decreased. Consequently, intermediate resistance values were obtained, which are suitable for multi-level cell (MLC) switching. The fabricated Y2O3 RRAM devices were capable of functioning as an MLC with a capacity of 2 bits in one cell, utilizing three low resistance states and one common high resistance state. The potential of the Y2O3 RRAM for neural networks was further explored through numerical simulations. Hardware neural networks based on the Y2O3 RRAM demonstrated effective digit image classification with a high accuracy rate of approximately 88%, comparable to the ideal software-based classification (~92%). This suggests that the proposed RRAM has the potential to be utilized as a memory component in practical neuromorphic systems.

COVID-19 pandemic has caused a large-scale havoc in almost every country across the globe, putting major challenges for the healthcare system in many parts of the world. Several of the laboratories are running in the race with undying efforts for developing potential vaccine, drugs or therapeutics to treat or prevent the infection. However, with the limited time window and high rate of infection, the task is very big for humanity to find a cure. With hundreds of genomic data of SARS-CoV-2 virus isolates from humans are being submitted almost every day, it is coming into knowledge that virus is mutating, slower in countries with sporadic cases, but higher in countries experiencing large outbreak. These types of mutations in virus may bring challenges in vaccine or therapeutic development for use in each and every country, as each hotspot region may have their own pattern of mutations in virus with ongoing outbreak. In our current study, we retrieved non-synonymous mutation data of around 12,225 SARS-CoV-2 virus samples isolated from humans globally, and discovered all mutations that are collectively happening in antibody epitope regions of the virus country-wise. We found a few numbers of epitope regions in SARS-CoV-2 that are highly conserved collectively in all variants and may be used for epitope-based vaccine development for whole world. We also found epitope regions that are conserved collectively in SARS-CoV-2 variants country-wise and can be used for customized epitope-based vaccine development in each different country.

For the last two decades, an increasing demand for low-cost adsorbents for drinking water treatment has been challenged in the rural areas of developing countries that have problems with arsenic (As) contamination. In this work, spent bleaching earth (SBE), a residual material that is formed during the process of refining vegetable oil, has been utilized to prepare the new magnetic adsorbent Fe-SBE/C by modifying its surface area through calcination and co-precipitation with iron. The experimental results demonstrate that Fe-SBE/C exhibits a substantial adsorption capacity towards both arsenite (As(III)) and arsenate (As(V)). Optimal pH conditions were found to be pH 10 for As(III) and pH 3 for As(V), resulting in adsorption percentages of 76.7% and 94.1%, respectively. Other experimental parameters such as calcination conditions, adsorbent dosage, iron-loading ratio, and the presence of co-existing ions were thoroughly investigated. The kinetic study revealed that the adsorption processes follow the Elovich and intraparticle diffusion models, suggesting a combined adsorption mechanism of boundary layer control and chemisorption. Furthermore, the isotherm followed the Langmuir model with a maximum adsorption capacity of 202.61 μg g-1 for As(III) and 187.61 μg g-1 for As(V). Through thermodynamic analysis and reinforcement by activation energy data, this research validates that the observed adsorption process is indicative through chemisorption. The regeneration study revealed the potential for multiple cycles of arsenic removal, highlighting the practical applicability of Fe-SBE/C in environmental contexts. In conclusion, the findings of this study underscore the efficacy of Fe-SBE/C in arsenic removal and present it as a promising and environmentally friendly solution for mitigating arsenic pollution.

Schizophrenia comprises various symptom domains, including positive and negative symptoms. Machine learning showed that a) negative symptoms are significantly interrelated with PHEM (psychosis, hostility, excitation, and mannerism) symptoms, formal thought disorders (FTD) and psychomotor retardation (PMR); and b) stable phase schizophrenia comprises two distinct classes, namely Major Neuro-Cognitive Psychosis (MNP, largely overlapping with deficit schizophrenia) and Simple NP (SNP). In this study, we recruited 120 MNP patients and 54 healthy subjects and measured the above-mentioned symptom domains. In MNP, there were significant associations between negative and PHEM symptoms, FTD and PMR. A single latent trait, which is essentially unidimensional, underlies these key domains of schizophrenia and MNP and additionally shows excellent internal consistency reliability, convergent validity, and predictive relevance. Confirmatory Tedrad Analysis indicates that this latent vector fits a reflective model. The lack of discriminant validity shows that PHEM and negative symptoms greatly overlap and probably measure the same construct. Soft Independent Modeling of Class Analogy (SIMCA) shows that MNP (diagnosis based on negative symptoms) is better modeled using PHEM symptoms, FTD, and PMR than negative symptoms. In conclusion, in stable phase MNP, a restricted sample of the schizophrenia population, negative and PHEM symptoms, FTD and PMR belong to one underlying latent vector reflecting overall severity of schizophrenia (OSOS). The bi-dimensional concept of “positive” and “negative” symptoms cannot be validated and, therefore, future research in stable phase schizophrenia should consider that the latent phenomenon OSOS as well as its 8 reflective manifestations are the key factors of schizophrenia phenomenology.

Respiratory syncytial virus (RSV) infection is a major cause of severe respiratory disease in infants and young children worldwide. Two vaccines targeting the elderly and pregnant women have been recently approved employing the prefusion form of the RSV-fusion protein (F). However, there are currently no vaccines for infants. Studies have shown a fusion-inactive prefusogenic F form is significantly more immunogenic and produces higher antibody titers to both the prefusion and postfusion structures of the F protein. Here we have developed RSV virus-like particles (RSV-VLPs) consisting of prefusogenic F, RSV glycoprotein and matrix proteins, produced them using the baculovirus expression system, and studied their protective efficacy in Balb/c mice. Morphology and successful assembly of VLPs were confirmed by transmission electron microscopy and western blot. Mice immunized with VLPs developed high levels of serum IgG and neutralizing antibodies as compared with mice immunized with inactivated virus. The VLP vaccine also induced higher levels of IFNγ and IL4, elicited limited proliferation of CD4+ and CD8+ T cells but higher cytotoxic-T-lymphocyte responses. VLP immunization abolished lung pathology in the mice after RSV challenge. Overall, our results indicate that RSV-VLPs consisting of prefusogenic F, glycoprotein and matrix proteins are a potential vaccine candidate against RSV.

The photosystem I (PSI) of the green alga Chlamydomonas reinhardtii associates with 10 light-harvesting proteins (LHCI) to form the PSI-LHCI complex. Binding of LHCII to PSI may also occur and is controlled by a process called state transitions. Hereby, two LHCII trimers bind to the PSAL, PSAH and PSAO side of PSI to produce the PSI-LHCI-LHCII complex. In this work, we took advantage of chemical crosslinking of proteins in conjunction with mass spectrometry to identify protein-protein interactions between the light-harvesting proteins of PSI and PSII. We detected binding of LHCBM proteins to the LHCA1-PSAG side of PSI and identified protein-protein interactions of LHCSR3 with LHCA5 and LHCA3. Our data indicate that the binding of LHCII to PSI is more versatile as anticipated and reveal that LHCSR3 likely regulates excitation energy transfer to the PSI core via LHCA5/LHCA3.

A Partial discharge (PD) occurrence in high-voltage (HV) and medium-voltage (MV) power assets is a warning sign of insulation system degradation or defective manufacturing/assembly, that may cause catastrophic damage and eventually lead to the breakdown of the power equipment. Ultra-high frequency (UHF) PD measurement technology has extensively been used to monitor the insulation health of the HV or MV equipment due to its high immunity against ambient noise and conducted disturbances. This paper presents experimental validation of a new design of a UHF planar rectangular microstrip antenna that can be used for PD monitoring of HV and/or MV power equipment, such as power transformers. The designed planar rectangular microstrip antenna has a compact size of 80mmx70mmx1.6mm. Laboratory experiments were performed to validate the antenna sensitivity to PD activity caused by insulation defects created inside an oil-filled transformer tank model. PD measurement results confirm that the proposed rectangular microstrip antenna has high sensitivity and high signal-to-noise ratio (SNR), thanks to its capability to suppress external noise disturbances, especially during online PD monitoring. Thus, the proposed UHF antenna seems to be a promising and alternative PD sensor that can be employed in UHF PD monitoring systems of HV or MV power equipment.

The genus Amomum encompasses six medicinal species that are extensively utilized and have a significant historical background. Due to their morphological similarities, however, the presence of counterfeit and substandard products remains a challenge. Accurate plant identification is therefore essential to address these issues. This study utilized 11 newly sequenced samples along with extensive data from NCBI to perform molecular identification of these six species. The plastomes of Amomum displayed a typical quadripartite structure with conserved gene content, yet showed independent variations in the SC/IR boundary shifts at both inter- and intra-specific levels. Our approach incorporated ITS, ITS1, ITS2, complete plastomes, matK, rbcL, and psbA-trnH sequences for molecular identification, which effectively differentiated the six medicinal species within the genus Amomum, as confirmed by distance-based and phylogenetic tree analyses. Among these, the ITS, ITS1, and complete plastomes sequences demonstrated the highest identification success rate (3/6), followed by ITS2, matK, and psbA-trnH (1/6). In contrast, rbcL failed to identify any species. This research successfully established a reliable molecular identification method for Amomum plants, to protect wild plant resources and promote the sustainable use of medicinal plants and restrict the exploitation of these resources.

Global warming and the associated increasing frequency of heatwaves are on the rise leading to numerous health complications. Diabetic patients are more vulnerable to heat exposure than healthy individuals, owing to their impaired sweating ability, however, little is known about how heat exposure may impact the function of skin cells, commonly keratinocytes. Our recent report provided the first proof-of-concept revealing that the metabolic composition of sweat EVs is associated with metabolic changes in healthy individuals and type 2 diabetes patients. Given this and the shared cellular proprieties of eccrine sweat glands with keratinocytes, we questioned whether the metabolic changes in sweat EVs may mirror the responses of keratinocytes upon heat exposure. To this, we exposed HaCat, which were maintained in low (mimicking healthy condition) and high glucose (mimicking diabetes condition) to acute (90 min), chronic (48 h), and repetitive heat exposure at 40 ⁰C. Through conducting a set of experiments including a targeted metabolomics approach, Greiss assay, western blotting analysis, and electron microscopy studies. The data demonstrate that heat exposure results in substantial changes of metabolite levels belonging to amino acids, pyrimidine metabolism, and glycolysis pathways in high glucose maintained HaCat cells when compared to those noted in low glucose condition. Exploring the molecular mechanisms through which heat exposure may impact the metabolic composition in keratinocytes, our discoveries highlight nitric oxide (NO) as a novel biomarker that the level is correlated with heat duration and frequency. Furthermore, data reveal that the HSP-70 protein levels and mitochondrial morphology are consequently altered. This study provides evidence of shared metabolic alterations in keratinocytes and sweat EVs collected from clinical study and proposes, for the first time, NO as a novel biomarker for monitoring changes in health and diabetes upon heat exposure.

Genetic disorders are quite a major topic of discussion and debate in the recent world of biological sciences. Turner’s syndrome is one such disorder caused by a chromosome aneuploidy and it has characteristic symptoms in the patient or the affected individual. The amniotic fluid is a complex biological material found in the amniotic sac of pregnant women and they can provide valuable knowledge and understanding of the pathogenesis of this particular chromosomal abnormality. In this study, global gene expression analysis of cell-free RNA in amniotic fluid supernatant was used to detect genes/organ systems which may be significant in the pathophysiology of Turner’s syndrome. The cell-free RNA from the amniotic fluid of five mid-trimester Turner’s syndrome fetuses and five euploid female fetuses matched for age of gestation were extracted, amplified and hybridized onto Affymetrix U33 Plus 2.0. array. The paired t-test was used to identify the significantly differentially regulated genes. Biological interpretation was conducted using ingenuity pathway analysis and BioGPS gene expression atlas. Of the genes, XIST was especially downregulated and SHOX was not expressed differentially. One of the most highly represented organ systems was the hematologic/immune system, differentiating the transcriptome of Turner’s syndrome from other chromosomal aneuploidies that are discussed in this area of science. The differences in the transcriptome of the Turner’s syndrome are due to genome-wide dysregulation. The hematologic/immune system differences are significant in early-onset autoimmune dysfunction. There are other genes which have been identified that are associated with the cardiovascular and the skeletal system, as these are often seen to be affected in the female patients with turner’s syndrome. Hopefully, such knowledge gained from this study will help us to understand the deeper mechanisms of this disorder and the possible treatments of this disease.

Resonance inductive coupling is widely used for wireless power transfer (WPT) in medical applications. In this paper, we analyze the LCL-compensated WPT structure and propose a novel constant voltage transmission system based on gain estimation, without any extra feedback from the receiver. The system is capable for implant neural stimulation where the load impedance and the coupling coefficient are both variable. Compared to existing methods for constant voltage transmission, our approach offers advantages in compact size and the compatibility with the industrial, scientific and medical (ISM) band. We validate the load-independent resonant characteristic and the feasibility of constant voltage transmission using an experimental prototype working at 6.78MHz. Finally, we discuss the structure of the implant stimulator and methods of applying the proposed WPT system.

The growing interest in Kv7.2/7.3 agonists originates from the involvement of these channels in several brain hyperexcitability disorders. In particular, Kv7.2/7.3 mutants have been clearly associated with epileptic encephalopathies (DEE) as well as with a spectrum of focal epilepsy disorders, often associated with developmental plateauing or regression. Nevertheless, there is a lack of available therapeutic options, considering that retigabine, the only molecule used in clinic as broad-spectrum Kv7 agonist, has been withdrawn from the market in the late 2016. This is why several efforts have been made both by both academia and industry in the search for suitable chemotypes acting as Kv7.2/7.3 agonists. In this context, in silico methods have played a major role, since the precise structures of different Kv7 homotetramers have been only recently disclosed. In the present review the computational methods used for the design of Kv.7.2/7.3 small molecule agonists and the underlying medicinal chemistry are discussed in the context of their biological and structure-function properties.

We reduplicate the Book “Dark Energy” by M. Li, X-D. Li, and Y. Wang, given zero-point energy calculation with an unexpected “length’ added to the ‘width’ of a graviton wave just prior to specifying the creation of ‘gravitons’, while using Karen Freeze’s criteria as to the breakup of primordial black holes to give radiation era contributions to GW generation. The GW generation will be when there is sufficient early universe density so as to break apart Relic Black holes of the order of Planck mass (10^15 grams) which isabout when the mass of relic black holes is created, 10^-27 or so seconds after expansion starts. Need to state a key result will be in the initial potential V calculated, in terms of other input variables

This work presents emission line flux and kinematic structure mapping based on IFU data of the planetary nebulae Abell 30 (A30). The IFU has a field of view (FoV) of 16" x 12.3" and was used to partially cover knots J1 and J2, and completely cover knots J3 and J4 of A30. Our emission line flux map shows recombination species C II, C III, He I, O II as well as forbidden line species [O III], [Ne III] and [Ne IV] of high excitation level are all distributed in different parts of the knots. The kinematic structure shows considerable variation in both the velocities and spatial locations of these knots with positive and negative velocity excursions from the systematic value. Forbidden line species [O III], [Ne III] are distributed in both knots J3 and J4 but they are travelling at different speeds in opposite directions. Despite variation in distribution of the species, the velocities of [Ne IV] and [O III] are similar and travelling in the same direction while the other species [Ne III], He I, and O II share similar velocity of 200kms−1 up in the opposite direction. The complexity of distribution and kinematic structure of the knots revealed in this work indicates a strong tendency towards the hypothesis of multiple triggering events in the past history of A30.

For the first time to optimize the creation of new neuroprotective agents based on bioflavonoids, we applied information technologies - docking analysis to calculate the binding of candidate molecules to the pharmacological target protein transthyretin, as well as the program of virtual screening of NO scavengers. As a result of this approach, the substance catechin was isolated from candidate molecules - quercetin, catechin, Epicatechin gallate, Epicatechin, Procyanidin B1, Procyanidin B2, Procyanidin B3, Catechin-3-gallate according to docking analysis. As a result of virtual screening, catechin was identified as a potential NO scavenger (55.15% prediction). The results of the prediction were confirmed by in vitro experiments. Course administration of catechin to animals with experimental multiple sclerosis (MS) against the background of methylprednisolone administration completely eliminated lethal cases, reduced the number of diseased animals by 20%, as well as prevented the development of severe neurological symptoms by 20% (compared to the methylprednisolone group) and by 60% compared to the control group. Course administration of catechin with methylprednisolone leads to decrease of neurodegradation markers in the cytosol of rats with EAE: NSE by 37%, and S-100 - by 54.8%. The combined administration of methylprednisolone significantly exceeds the combination of methylprednisolone with the reference drug mexidol by the degree of NSE reduction. The obtained results indicate a significant neuroprotective effect of ocular combinations of methylprednisolone and catechin. The above-mentioned confirms the correctness of bioflavonoid selection with the help of virtual screening program.

As argued by ‘Declaration of Concrete Environment (2010)’ of Korea and ‘Declaration of Asian Concrete Environment (2011)’ of six Asian countries, concrete as a single material has lately shown extremely large impact on environmental issues such as climate change. Assessment of environmental impact from concrete material and production has considerable importance. Concrete is a major material used in the construction industry that emits a large amount of substances with environmental impacts during its life cycle. Accordingly, technologies for the reduction in and assessment of the environmental impact of concrete from the perspective of Life Cycle Assessment must be developed. At present, the studies in relation to greenhouse gas emission from concrete are being carried out globally as a countermeasure against climate change. In this study, a sustainable concrete mix design algorithm was designed using correlation analyses, and its carbon emission and cost reduction performances were assessed. Using correlation analyses, the concrete strength, w/b and s/a ratios, and CO₂ emissions were identified as major variables of concrete mix design that influenced other variables. Also, this study aims to evaluate the CO₂ emission reduction performance of the algorithm-deduced sustainable concrete mix design, and therefore, the CO₂ emissions of the sustainable concrete mix design are compared with those of the actual concrete mix design applied to the construction of the office building A in South Korea.

Background: Cell-free DNA (cfDNA) analysis has become a promising tool for diagnosis, prognosis and monitoring of lymphoma cases. Until now, research in this area has mainly focused in aggressive lymphomas with scanty information from other lymphoma subtypes. Methods: We selected 256 patients diagnosed with lymphomas including a large variety of B-cell and T-cell non-Hodgkin and Hodgkin lymphomas and quantified cfDNA from plasma at the time of diagnosis. We further selected 49 large B cell lymphomas (LBCL) and analyzed cfDNA levels at diagnosis (pre-therapy) and after therapy. In addition, we performed NGS in cfDNA and tissue in this cohort of LBCL. Results: Lymphoma patients showed a statistically significant higher cfDNA concentration than healthy controls (mean 53.0 ng/mL vs 5.6 ng/mL, p <0.001). The cfDNA concentration correlated with lymphoma subtype, lactate dehydrogenase, International Prognostic Index (IPI) score, Ann Arbor (AA) and B-symptoms. In 49 LBCL cases, the cfDNA concentration decreased after therapy in cases who achieved complete response (CR), and increased in non-responders. The median cfDNA at diagnosis of patients who achieved CR and later relapsed was higher (81.5 ng/mL) compared with levels of those who did not (38.6 ng/mL). A concordance of 84% was observed between NGS results in tumor and cfDNA samples. Higher VAF in cfDNA correlated with advanced stage and bulky disease. Conclusions: cfDNA analysis can be easily performed in almost all lymphoma cases. The cfDNA concentration correlated with the characteristics of aggressiveness of the lymphomas and in LBCL with the response achieved after therapy. These results support the utility of cfDNA analysis as a complementary tool in the management of lymphoma patients.

This study explores religious diversity in Romania and how the trends of indices of religious fractionalization and polarization manifest at the county level in the post-communist period. The county is selected as the relevant level for analysis due to its spatial confessional dynamics being more clearly visible. Recent studies have revealed that erosion of diversity represents an important aspect for any country and needs to be considered as an important aspect of democracy. This paper highlights that religious polarization and fractionalization in Romania has been generally maintained, although the regions of Transylvania, Banat, Dobrogea and Western Moldova remain areas where there are different confessions. Besides the general aspect of religion diversity depending the ethnic trends, there is a rise of Pentecostals and Baptists at the county level. This aspect can inform policymakers to create new institutions for dialogue between majority Orthodox communities and Protestants so that potential conflicts do not appear between the Orthodox and emerging religious communities, but also to ensure objective, cultural, religious coherence.

Certain configurations of liquefied natural gas refueling stations exhibit a deficiency in managing boil-off gas. Furthermore, the ill-conceived linkage between the submersible pump and the gas storage tank pipeline leads to impeded natural gas transmission. This study employs Computational Fluid Dynamics (CFD) methodology to scrutinize the hydrodynamic attributes of T-type tee and dovetail tee configurations implemented in the pipeline design connecting the submersible pump and storage tank in an LNG filling station across diverse operational scenarios. The T-type tee induces detachment of the primary flow from the inner wall due to inertial forces, resulting in vortex formation and heightened resistance, accompanied by increased energy dissipation. Conversely, the dovetail tee, with its circular wall transition, mitigates vortex generation, reducing the separation zone and consequently minimizing resistance and energy loss. The maximum static differential pressure between the inlet and outlet of the dovetail tee is diminished by 52.52% when compared to that of the T-type tee. In the most noteworthy scenarios, the local resistance coefficient of the dovetail tee is even less than 1/10 of that of the T-type tee. In practical engineering applications, the incorporation of dovetail tees leads to a 17.58% reduction in the required elevation difference. This results in a more uniform flow field and enhanced stability in both flow rate and pressure. Such improvements contribute to heightened engineering efficiency and environmental sustainability, particularly evident in the design of LNG filling stations.

Wave buoy measurements were carried out near the north-eastern Black Sea coast at the natural reserve Utrish in 2020-2021. In total, about 11 months of data records were collected during two stages of the experiment at 600 and 1500 meters offshore and depths of 18 and 42 meters. The measured waves propagate almost exclusively from the seaward directions. Generally, the waves do not follow the local wind directions, thus, implying a mixed sea state. Nevertheless, dimensionless wave heights and periods appears to be quite close to the previously established empirical laws for the wind-driven seas. The results of the wave turbulence theory are applied for estimates of spectral energy fluxes and their correspondence to the energy flux from the turbulent wind pulsations. These estimates are consistent with today's understanding of wind-wave interaction. It is shown that the main fraction of the wind energy flux goes to the direct Kolmogorov-Zakharov cascade to high wave frequencies and then to dissipation in small scales. Less than 1% of the wind energy flux is directed to low frequency band (the so-called inverse Kolmogorov-Zakharov cascade), thus, providing wave energy growth.

Issues related to safe and abundant energy production have been prominent in recent years. This is particularly tr ue when society considers how to increase the quality of life by providing low-cost energy to citizens. A significant concern of the Gulf Cooperation Council (GCC) relates to the environmental effects of energy production and energy use associated with climate change. Efforts to reduce fossil fuel use and increase the use of renewable energy, together with the price volatility of fossil fuels, have seriously impacted the economics of many of the oil-producing countries, particularly the Gulf States, which has led to efforts to make their economies more diverse and less dependent on oil production.

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model’s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

Artisanal goldminers in Ghana are exposed to various levels and forms of health, safety and environmental threats. Without the required legislation and regulations, artisanal miners are responsible for their own health and safety at work. Consequently, understanding the probabilities of self-protection at work by artisanal goldminers is crucial. A cross-sectional survey of 500 artisanal goldminers was conducted to examine the probabilities of personal protective equipment use among artisanal goldminers in Ghana. The data was subjected to both descriptive and inferential statistics. Initial findings showed that personal protective equipment use among artisanal miners was 77.4%. Overall, higher probabilities of personal protective equipment use was observed among artisanal goldminers who work in good health and safety conditions as compared to artisanal miners who work in poor health and safety conditions. Also, personal protective equipment use was more probable among the highly educated artisanal goldminers, miners who regularly go for medical screening and the most experienced miners. Additionally, personal protective equipment use was more probable among artisanal miners who work in non-production departments and miners who work in the medium scale subsector. Inversely, personal protective equipment use was less probable among female artisanal miners and miners who earn more monthly income ($174 and above). To increase self-care and safety consciousness in artisanal mining, there is the need for a national occupational health and safety legislation in Ghana. Also, interventions and health promotion campaigns for better occupational conditions in artisanal mining should target and revise the health and safety related workplace programs and conditions

The COVID-19 appears as a catastrophic health risk with psychological, emotional, social and relational implications. From the early stages of the virus spread, the elderly population was identified as the most vulnerable and the health authorities have rightly focused on such frailest population. Conversely, less attention was paid to emotional and psychological dimension of children and adolescents. Actually, they were less at risk quoad vitam or quoad valetudinem, nevertheless they had to face a reality of anxiety, fears and uncertainties. The current study investigated state anxiety and emotion awareness in a healthy sample of older adolescents, 84 females and 64 males, aged 17 to 19, during the pandemic lockdown, using Self-rating Anxiety Scale and the Italian Emotion Awareness Questionnaire. An unexpected anxious phenomenology, impacting the anxiety ideo-affective domain, was found, while the somatic symptomatology appeared to be less severe. The highest anxiety symptom were the breathing difficulties. These findings supported the hypothesis that the COVID-19 pandemic may be a risk condition for an increased state anxiety in older adolescents and suggest the need to provide 1. an effective, empathic communication system with the direct participation of older adolescents, 2. a psychological counseling service for stress management of adolescents.

The amount of outdoor particles that indoor environments receive depends on the particle infiltration factors (Fin), peculiar of each environment, and on the outdoor aerosol concentrations and size distributions. The respiratory doses received, while residing indoor, will change accordingly. This study aims to ascertain to what extent such doses are affected by the vertical distance from the traffic sources. Particle number size distributions have been simultaneously measured at street level and at about 20 m height in a street canyon in downtown Rome. The same Fin have been adopted to estimate indoor aerosol concentrations, due to the infiltration of outdoor particles and then the relevant daily respiratory doses. Aerosol concentrations at ground floor were more than double than at 20 m height and richer in ultrafine particles. Thus, although aerosol infiltration efficiency was on average higher at 20 m height than at ground floor, particles more abundantly infiltrated at ground level. On a daily basis, this involved a 2.5-fold higher dose at ground level than at 20 m height. At both levels, such doses were greater than those estimated over the period of activity of some indoor aerosol sources, therefore they represent an important contribution to the total daily dose.

The creep behaviors of TA2 and R60702 at low and intermediate temperature were presented and discussed in this paper. Experimental results indicated that an apparent threshold stress exhibited in the creep deformation of R60702. Meanwhile, the primary creep phase was found as the main pattern in the room temperature creep behavior of TA2. Compared with exponential law, the power law has been proved to be a proper constitutive model in the description of primary creep phase. It also showed that θ projection method had its significant advantage in the evaluation of accelerated creep stage. Thus, a composite model which combined power law with θ projection method was applied in the creep curves evaluation at low and intermediate temperature. Based on the multiaxial creep deformation results, the model was modified and discussed. A linear relationship existed between composite model parameters and applied load. Finally, the creep life could be accurately predicted and the composite model method is suitable for application in low and intermediate temperature creep life analysis.

Banks have enormous potential in supporting the achievement of sustainable development goals (SDGs) in accordance with their function as financial intermediaries through sustainable lending. However, the average national financing growth for the sustainable business activity category over the past four years is still 12%. The aim of this research is to identify the conditions of sustainable lending at state-owned conventional banks and analyze the influence of the value chain, economic performance and ESG performance on sustainable lending. The research was conducted at state-owned commercial banks in Indonesia. The research utilized a Structural Equation Modeling (SEM). The SEM results of this study describe value chain, ESG performance (environmental, social and governance) and economic performance have direct and positive influences on sustainable lending, of which ESG performance has the biggest influence. As per individual aspect, social orientation gives the biggest contribution toward sustainable lending.

Currently, health tourists primarily rely on independent facilitators to manage and book their medical appointments and vacation plans. There is a notable absence of dedicated booking applications for health tourism packages. This paper proposes HealthTourismHub, an application designed to provide personalized packages that include medical appointments, accommodation options and recommended tourism activities. It also serves as a platform for medical experts and accommodation providers, allowing health tourists to discover and connect with them. To incorporate personalization, HealthTourismHub uses an ontology that organizes medical and tourism data, along with a reasoner that generates new knowledge. This approach enables the application to offer customized packages and identify the most suitable providers for each user. Providers are strategically paired and located in close proximity, with the package also including personalized tourism recommendations. A survey was conducted to assess the usability of the application and general perspectives towards health tourism, including motivations, concerns, and preferences. The results revealed an above-average SUS score, indicating that users found the application user-friendly and effective. Some areas for improvement were identified, such as error handling and additional functionalities. Nonetheless, HealthTourismHub shows great potential as a pioneer in the field of health tourism applications.

One of the most important defining characteristics of groundwater quality is pH as it fundamentally controls the amount and chemical form of many organic and inorganic solutes in groundwater. Groundwater data are frequently characterized by a wide degree of variability of the factors which possibly influence pH distribution. For this reason, it is challenging to link the spatio-temporal dynamics of pH to a single environmental factor by the ordinary least squares regression technique of the conditional mean. In this study, quantile regression was used to estimate the response of pH to nine environmental factors (As, Cd, Fe, Mn, Pb, turbidity, electrical conductivity, total dissolved solids and nitrates). Results of 25%, 50%, 75% quantile regression and ordinary least squares (OLS) regression were compared. The standard regression of the conditional means (OLS) underestimated the rates of change of pH due to the selected factors in comparison with the regression quantiles. The effect of arsenic increased for sampling locations with higher pH values (higher quantiles) likewise the influence of Pb and Mn. However, the effects of Cd and Fe decreased for sampling locations in higher quantiles. It can be concluded that these detected heterogeneities would be missed if this study had focused exclusively on the conditional means of the pH values. Consequently, quantile regression provides a more comprehensive account of possible spatio-temporal relationships between environmental covariates in groundwater. This study is one of the first to apply this technique on groundwater systems in sub-Saharan Africa. The approach is useful and interesting and has broad application for other mining environments especially tropical low-income countries where climatic conditions can drive rapid cycling or transformations of pollutants. It is also pertinent to geopolitical contexts where regulatory; monitoring and management capacities are weak and where mining pollution of groundwater largely occur.

Introduction: The objective of this study was: compare the continuous infusion of cefepime with the intermittent infusion in patients with sepsis caused by Gram negative bacilli (GNB). Methods: Randomized 1:1 multicenter double-blinded placebo-controlled study with allocation concealment. Multicenter study in Intensive Care Units of Colombia. Patients with sepsis, severe sepsis or septic shock and GNB suspected bacteraemia. Cefepime was administered for 7 to 14 days over 30 m intermittently every 8 h over 24 h plus continuous saline solution (0.9%) (G1) or 3 g administered continuously plus saline solution every 8 h (0.9%) (G2). Percentage of clinical response at 3, 7, 14 days, relapse at 28 days and mortality at discharge were measured. Results: The recruitment was stopped by suggestion of the Institutional Review Board (IRB), following an FDA alert about cefepime. Thirty-two patients were randomized, 25 received the intervention and GNB bacteremia was confirmed in 16 (9 G1 and 7 G 2). Favourable clinical response in days 3,7,14 was 88.8%, 88.8%, 77.8 % (G 1) and was similar for G 2 (85.7%). There were not relapses and deaths in G2 while in G1 one relapse and 2 deaths were observed. Conclusions: The results of this study support the use of cefepime for the treatment of Gram-negative infections in critically ill patients but we could not demonstrate differences between continuous or intermittent administration, because of the small sample size, given the early suspension of the study.

Multiple imputation by chained equations (MICE) is a popular and well-researched statistical approach to account for missing data in empirical research. However, applying the technique requires researchers to set dozens of smaller and larger parameters to build an adequate imputation model before estimating the analytical model of interest. It is somewhat unclear how severely small and potentially arbitrary decisions influence the quality of the produced findings. The current study tests this empirically using a simulation approach with datasets with low and high shares of missing data points that are missing at random (MAR). For each of the two specifications, 4,200 simulations are conducted where multiple parameters are randomly varied to create a diverse range of potential imputation models. The results demonstrate that even random imputation models can significantly reduce bias compared to listwise deletion since more than 90% of all simulations give less biased results. All minor decisions taken together explain between 11% and 21% of the variation in the statistics of interest. The most substantial influence on this variation is due to the selection of the imputation algorithm within MICE. These findings demonstrate that almost any imputation model, even those built with little care, will often result in a higher quality than applying listwise deletion, as long as critical assumptions, such as MAR and the avoidance of severe misspecifications, hold.

The goal of the project was to understand how topography/bathymetry is imported and used in GeoFlood with an aim towards improving efficiency and computational cost of bathymetry handling in GeoFlood.GeoFlood is a software to simulate overland flooding basing on shallow water equations.Numerical methods and programming were used for this study.The GeoFlood was ran on a given data set (Malpasset data) and it was found out that indeed topography handling during simulations has to be improved to minimise the computational time and also improve the efficiency.Through this research, we also looked at the the shallow water equations, and the numerical techniques used to solve the equations

Regression models are highly popular in empirical research and come in many different forms to fit virtually any distribution, variable, or research question. Usually, these models also compute how much variation in the outcome variable can be explained by all predictors, which is relevant to understanding whether the predictors are, in sum, able to explain the outcome or whether other potentially unobserved factors are more relevant. This aspect is crucial for interventions and policy as even statistically significant regression coefficients can be meaningless if they have little influence on the outcome overall. Besides having a measurement to judge the overall goodness of fit, ranking predictors by their relative importance is also relevant. For such analyses, it is necessary to decompose the total explanatory power of a model and partition it so that each explanatory variable is assigned a share. This enables the computation of a predictor variable's absolute and relative influence. Dominance analysis is a statistical approach to achieve this goal.

The working environment of mining electric locomotives is wet and muddy coal mine 1 roadway. There may be idling or slipping between the wheels and rails of mining electric locomotives 2 due to low friction between the wheel and rail and insufficient utilization of creep rate. Therefore, it 3 is necessary to control the creep rate within a reasonable range. In this paper, the autonomous control 4 algorithm for mining electric locomotives based on improved ε-greedy is theoretically proven to be 5 convergent and effective firstly. Secondly, after analyzing the contact state between the wheel and rail 6 under wet and slippery road conditions, it was concluded that the value of creep rate is an important 7 factor affecting the autonomous driving of mining electric locomotives. Therefore, the autonomous 8 control method for mining electric locomotives based on creep control is proposed in this paper. 9 Finally, the effectiveness of the proposed method was verified through simulation. The problem of 10 wheel slipping and idling caused by insufficient friction of mining electric locomotives in coal mining 11 environments is effectively suppressed. Autonomous operation of vehicles with optimal driving 12 efficiency can be achieved through quantitative control and utilization of the creep rate between 13 wheels and rails

In recent years, the utilization of machine learning algorithms and advancements in Unmanned Aerial Vehicle (UAV) technology have marked significant shifts in remote sensing practices. In particular, the integration of machine learning with physical models and their application in UAV-satellite data fusion have emerged as two prominent approaches for estimating vegetation biochemistry. This study evaluates the performance of five machine learning regression algorithms (MLRAs) for mapping crop canopy chlorophyll at the Kellogg Biological Station (KBS) in Michigan, USA, across three scenarios: (1) application to Landsat 7, RapidEye, and PlanetScope satellite images; (2) application to UAV-satellite data fusion; and (3) integration with the PROSAIL radiative transfer model (hybrid methods PROSAIL + MLRAs). The results indicate that the majority of the five MLRAs utilized in UAV-satellite data fusion perform better than the five PROSAIL + MLRAs. The general trend suggests that the integration of satellite data with UAV-derived information, including the normalized difference red-edge index (NDRE), canopy height model, and leaf area index (LAI), significantly enhances the performance of MLRAs. The UAV-RapidEye dataset exhibits the highest coefficient of determination (R2) and the lowest root-mean-square errors (RMSE) when employing kernel ridge regression (KRR) and Gaussian processes regression (GPR) (R2 = 0.89 and 0.89 and RMSE = 8.99 µg/cm2 and 9.65 µg/cm2, respectively). Similar performance is closely observed for the UAV-Landsat and UAV-PlanetScope datasets (R2 = 0.86 and 0.87 for KRR, respectively). For the hybrid models, maximum performance is attained with Landsat data using KRR and GPR (R2 = 0.77 and 0.51 and RMSE = 33.10 µg/cm2 and 42.91 µg/cm2, respectively), followed by R2 = 0.75 and RMSE = 39.78 µg/cm2 for PlanetScope data upon integrating partial least squares regression (PLSR) into the hybrid model. Across all hybrid models, RapidEye data yielded the most stable performance, with R2 ranging from 0.45 to 0.71 and RMSE ranging from 19.16 µg/cm2 to 33.07 µg/cm2. The study highlights the importance of synergizing UAV and satellite data which enables effective monitoring of canopy chlorophyll in small agricultural lands.

Fires in houses are inevitable and they cause loss of life and major repair costs for the damage structure and contents. There is a clear need to prevent its ignition and spread to adjacent areas. This article presents the steps taken, namely: contacts, data collection, tests, analysis and conclusions regarding the accident resulting from the outbreak and spread of a fire, on December 25, 2020, in a traditional Portuguese house in Arganil, Portugal. The owners and the court requested to carry out an expert opinion by a person with specialized technical-scientific knowledge, which led to this work as an expert. the work consists of carrying out observations and data analysis. Then, the observed and analysed data were laboratory tested in order to consistently identify characteristics that lead to the ignition and propagation of the fire. This work identified construction problems, materials used and heat sources that are responsible for the accident. The conclusions may be used to avoid future incidents or accidents with houses of same construction type.

With the fintech industry growing at an unprecedented rate, it is critical to protect cybersecurity and ensure data privacy. The research presented here offers a thorough examination of the challenges faced by financial technology companies, highlighting the growing risks posed by malware, phishing, and network vulnerabilities. As essential components of a proactive defense plan, the report promotes strong cybersecurity measures like frequent security assessments, encryption, and stringent access controls. The findings highlight how important it is for fintech companies to give cybersecurity equal importance with open and honest data privacy policies in order to win over customers. In order to protect the industry from cybersecurity risks regulatory compliance, intrusion detection systems, and collaborative information sharing are considered essential components. The article advises businesses to include cybersecurity and data privacy into their core business operations and customer relations, highlighting the critical role these factors play in sustaining success in the rapidly evolving fintech industry.

(1) Introduction: The COVID-19 pandemic presented unique challenges for patients and healthcare providers, especially for those working with obesity and related health problems. E-health has emerged as a crucial tool for the follow-up of users undergoing bariatric surgery during this period, allowing remote monitoring of users' health status and providing access to virtual consultation with health professionals. This study aims to analyze the impact of the use of telemedicine during the COVID-19 pandemic on the results of bariatric surgery and user satisfac-tion with this follow-up. (2) Method: Observational study with retrospective data collection. The variables were divided into several groups: health data, associated comorbidities, quality of life, quality of sleep and satisfaction with telemedicine monitoring. (3) Results: Surgery significantly affected weight loss, in general more than 75% loss of excess weight. Comorbidities, like the qual-ity of life, were reversed over time, with 50% of subjects maintaining excellent levels. Although most users were satisfied with the monitoring, the variables had no relationship. (4) Conclusions: The follow-up assured by telemedicine did not alter the results of bariatric surgery, which may allow us to infer that it may be an option to consider for regular monitoring of the post-bariatric surgery process.

A new trend in cow's milk has emerged in the market called type A1 and A2 milk. These products have piqued the interest of both consumers and researchers. Recent studies suggest that A2 milk may have potential health benefits, which is why researchers are investigating this product further. It is interesting to note that the A1 and A2 milk types have area-specific characteristics compared to breed-specific characteristics. Extensive research has focused on milk derivatives obtained from cow’s milk, primarily through in vitro and animal studies. However, few clinical studies have been conducted in humans, and the results have been unsatisfactory. New molecular techniques for identifying A1 and A2 milk may help researchers to develop new studies that can clarify certain controversies surrounding A1 milk. It is essential to exercise extreme caution when interpreting the updated literature. It has the potential to spread panic worldwide and have negative economic implications. Therefore, this study aims to investigate the new aspects of A1 and A2 milk in different research areas and clarify some aspects regarding these two types of milk.

In the paper, the authors view some ordinary differential equations and their solutions from the angle of (the generalized) derivative polynomials and simplify some known identities for the Bernoulli numbers and polynomials, the Frobenius-Euler polynomials, the Euler numbers and polynomials, in terms of the Stirling numbers of the first and second kinds.

The dynamics of surface and sub-surface water events can lead to slope instability resulting in anomalies such as slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We have implemented a supervised Mahalanobis distance classification algorithm for the detection of slough slides on levees using complex polarimetric Synthetic Aperture Radar (polSAR) data. The classifier output was followed by a spatial majority filter post-processing step which improved the accuracy. The effectiveness of the algorithm is demonstrated using fully quad-polarimetric L-band Synthetic Aperture Radar (SAR) imagery from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the southern USA. Slide detection accuracy of up to 98 percent was achieved, although the number of available slides examples was small.

The Philippines has the highest HIV incidence rate in the Asia-Pacific region. Previous studies identified multilevel factors contributing to this phenomenon. This scoping review describes the extent of the literature on HIV contributory factors and identifies gaps to guide directions for HIV prevention research. The keywords HIV incidence, individual, sociocultural, environmental factors, and Philippines, were used to search for evidence on Google Scholar, PubMed, Scopus, and Web of Science databases. A total of 1,017 peer-reviewed articles published in the English language from 2014 to 2024 were reviewed using the Joanna Briggs Institute Scoping Review protocol. Thirty articles were included in this review. The majority of the available evidence was quantitative studies published between 2020 and 2024. Individual, sociocultural, economic, educational, political, and environmental factors shaped the Philippines’ HIV epidemic. Low levels of HIV knowledge, low testing rates, high-risk sex behaviors, stigma, lifestyle, location, lack of HIV education in schools, conservative society, and restrictive policies are HIV contributing factors. The Philippine HIV epidemic is multifactorial. Identifying the contributory factors is crucial in developing targeted interventions for high-risk populations. A dedicated HIV research program is needed to provide evidence-based information to guide the development of HIV preventive programs and research.

Originally developed as a chemotherapeutic agent, miltefosine (hexadecylphosphocholine) is an inhibitor of phosphatidylcholine synthesis with proven antiparasitic effects. It is the only oral drug approved for the treatment of Leishmaniasis and American Trypanosomiasis (Chagas Disease). Although its precise mechanisms are not yet fully understood, miltefosine exhibits broad-spectrum anti-parasitic effects primarily by disrupting the intracellular Ca2+ homeostasis of the parasites while sparing the human hosts. In addition to its inhibitory effects on phosphatidylcholine synthesis and cytochrome c oxidase, miltefosine has been found to affect the unique giant mitochondria and the acidocalcisomes of parasites. Both of these crucial organelles are involved in Ca2+ regulation. Furthermore, miltefosine has the ability to activate a specific parasite Ca2+ channel that responds to sphingosine, that is different to its L-type VGCC human ortholog. Here, we aimed to provide an overview of recent advancements of the anti-parasitic mechanisms of miltefosine. We also explored its multiple molecular targets and investigated how its pleiotropic effects translate into a rational therapeutic approach for patients afflicted by Leishmaniasis and American Trypanosomiasis. Notably, miltefosine's therapeutic effect extends beyond its impact on the parasite to also affect positively the host's immune system. These findings enhance our understanding on its multi targeted mechanism of action. Overall, this review sheds light on the intricate molecular actions of miltefosine highlighting its potential as a promising therapeutic option against these debilitating parasitic diseases.

The physical and mechanical properties of rocks will change significantly after being subjected to high temperatures, which poses safety hazards to underground projects such as coal underground gasification. In order to investigate the effect of temperature on the macroscopic and microscopic properties of rocks, this paper has taken sandstone as the research object and conducted uniaxial compression tests on sandstone specimens at different temperatures (20-1000 ℃) and different heating rates (5-30 ℃/min) at 1200 ℃. At the same time, the acoustic emission (AE) test system was used to observe the acoustic emission characteristics of the rock damage process, and the microstructural changes after high temperature were analyzed with the help of a scanning electron microscope (SEM). The test results show that the effect of temperature on sandstone is mainly divided into three stages: Ⅰ (20-500 ℃) stage is the strengthening zone, the evaporation of water and the contraction of primary fissures, sandstone densification is enhanced. Specifically, the compressive strength and elastic modulus increase, the macroscopic damage mode is dominated by shear damage, and the fracture micro-morphology is mainly brittle fracture. Stage II (500-600°C) is the transition zone, 500°C is the threshold temperature for compressive strength and modulus of elasticity, and the damage mode changes from shear to cleavage damage, and the sandstone undergoes brittle-ductile transition in this temperature interval. Stage III is the physicochemical deterioration stage. The changes in physical and chemical properties make the sandstone compressive strength and modulus of elasticity continue to decline, the macroscopic damage mode is mainly dominated by cleavage damage, and the fracture microscopic morphology is more toughness fracture. The effect of different heating rates on the mechanical properties of sandstone was further studied, and it was found that the mechanical properties of the rock were more deteriorated under higher heating rates.

Supply chain disruptions, a pandemic, and war in Ukraine have exposed faultlines in a globalised food system that depends on a few staple crops grown in a few exporting regions and transported to consumers around the world. In the UK, just three crops, (wheat, barley, and oilseed rape), account for 75 per cent of the UK’s 4.5 million hectares of arable land whilst the country imports around half its food - nearly 40 per cent from just four EU countries (the Netherlands, Ireland, Germany, and France). Poor diets contribute to one in seven deaths in the UK, 63 per cent of the population is overweight or obese and health inequality is increasing between the poorest and most affluent regions. The food security and health of the UK population is therefore dependent on a small number of locally grown crops, vulnerable supply chains, and an unhealthy, obesogenic diet. The UK food system must diversify if it is to become food and nutritionally secure, meet its climate and biodiversity goals and have a healthy and active population. Climate resilient and nutritious underutilised crops can help diversify the UK agrifood system but, research and investment in them is sporadic, piecemeal, and unfocused. In this paper we compare two approaches to identifying potentially suitable underutilised crops for the UK. The first, based on Defra Project CH0224 was delivered through literature and database searches and expertise of growers, advisers, breeders, seed suppliers, processors, traders, and researchers. The second, used the CropBASE digital knowledge base for underutilised crops described in Jahanshiri et. al. (2023). The two approaches produced no single crop that was common to both shortlists. We propose that the analytical and predictive tools derived from CropBASE could be combined with local knowledge and expertise from the Defra project to provide a common framework for the identification of underutilised crops that are best suited to local UK circumstances now and in climates of the future.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

A novel five-surface phosphor-in-glass (FS-PiG) for high illumination and excellent color uniformity in larger-scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680°C to form a phosphor wafer. A sophisticated laser engraving was employed on the phosphor wafer to form a saddle-shaped large-scale FS-PiG LEDs. The performance of the FS-PiG LEDs exhibited the illumination of 401lm, average color temperature (CCT) of 5488K±110K, and color coordinates (CIE) of (0.3179±0.003, 0.3352±0.003). In contrast to convention single-surface phosphor-in-glass (SS-PiG) LEDs, the performance exhibited the illumination of 380lm, average CCT of 5830K±758K, and CIE of (0.3083±0.07, 0.3172±0.07). These indicated that the performance of the FS-PiG LEDs was higher than the SS-PiG LEDs for illumination, CCT, and CIE of 1.7, 7, and 23 times, respectively. Furthermore, the FS-PiG LEDs demonstrate lower lumen loss of 2% and less chromaticity shift of 5.4x10-3 under accelerated aging at 350°C for 1008 hours, owing to the high ceramic melting temperature of up to 510°C. In this study, the proposed FS-PiG larger-scale LEDs having excellent optical performance and high reliability may be the promising candidates to replace the convention phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications.

This research presents the creation of a Virtual Reality experience for the Balzi Rossi museum, commemorating the centenary of Prince Albert I Grimaldi's archaeological work at the site. The project, a collaboration between the University of Genoa's 3D Lab Factory, Eurodrone, and the Balzi Rossi archaeological museum, aims to preserve and convey the site's heritage through advanced VR technology. Initially employing Unreal Engine 4, the team used photogrammetry for 3D reconstruction of the "Caviglione" and "Florestano" caves, notable for their ancient rock engravings. This first VR model, despite hardware limitations, provided an interactive exploration of the site. The subsequent development phase utilized Unreal Engine 5, incorporating Nanite technology for enhanced visual fidelity. This advancement resulted in a more detailed and immersive VR experience, presenting the Balzi Rossi cliff across different historical periods, including the Würm glaciation. Key to this phase was optimizing the VR experience for performance, focusing on stable frame rates and minimizing motion sickness, and integrating a multi-lingual interface for broader accessibility. Since November 2023, the VR setup at the Balzi Rossi Museum has been an educational and interactive feature, enabling visitors to explore the site's history virtually. This research demonstrates the potential of VR in cultural heritage preservation and education, providing a foundation for future technological improvements in the field.

The Cobb angle is critical in assessing adolescent idiopathic scoliosis (AIS) patients. This study aimed to evaluate the error in selecting the cranial and caudal limit vertebrae on AIS digital X-rays of experienced and novice observers and its correlation with the error in measuring the Cobb angle and determining the length of the scoliotic curves. Using the TraumaMeter v.873 software, eight raters (four experienced and four novices) independently evaluated 68 scoliotic curves on 42 AIS X-rays across three sessions one month apart according to Hopkins’ criteria of absolute reliability. Two spine specialist experts using the Cobb method established the gold standard measurements. The percentage of error in the selection of the cranial vertebrae (the most-tilted vertebra above the apex) is higher than in the caudal vertebrae (the most-tilted vertebrae below the apex) (44.7%, CI95% 41.05-48.3 compared to 35%, CI95% 29.7-40.4). The error in the choice of the most tilted vertebrae, in number of vertebrae per scoliotic curve, was MBE (mean bias error) =0.45, CI95% 0.38-0.52 in the cranial and MBE=0.35, CI% 0.69-0.91 in the caudal. The percentage of errors in the choice of boundary vertebrae is lower for the experienced than for the novices, both in cranial and caudal. The experienced chose at least one boundary vertebrae incorrectly in 52% of the meas-urements and the novices in 65.1%. The error in the Cobb angle did not depend on the number of boundary vertebrae chosen incorrectly (r=0.198, p=0.111). Of the 50% of Cobb angle measurements closest to the actual value, 55.4% (454) were obtained by incorrectly selecting at least one boundary vertebra. There was a positive correlation (r=0.673, p=0.000) between the error in selecting the boundary vertebrae and the error in determining the length of the scoliotic curves. The error in quantifying the length of scoliotic curves was MBE=0.43, CI95% 0.35-0.51 vertebrae per curve. We can conclude that errors in selecting boundary vertebrae are common among experienced and novice observers, with a greater frequency of error in the cranial vertebrae. There is no correlation between the error in selecting the boundary vertebrae and the error in measuring the Cobb angle. Contrary to the consensus, the accuracy of determining the length of the scoliotic curve is limited by the Cobb method’s reliance on the correct selection of boundary vertebrae. Inappropriate choice of boundary vertebrae leads to an estimated error in determining the length of the scoliotic curves of 0.805 vertebrae for each boundary vertebra chosen incorrectly.

Resveratrol (RSV), a naturally occurring phytoalexin, is the most important stilbenoid synthesized by plants, as a defense mechanism, in response to microbial aggression, toxins or ultraviolet radiation. RSV came to the attention of researchers both as a potential chemopreventive agent and a possible explanation for the low incidence of cardiovascular disease (CVD) in French people with a high-fat diet. RSV is mainly administered as a food supplement, its properties being evaluated in vitro or in vivo, on various experimental models. RSV modulates signaling pathways that limit the spread of tumor cells, protects nerve cells from damage, is useful in the prevention of diabetes, and generally acts as an anti-aging natural compound. It was highlighted that RSV could ameliorate the consequences of an unhealthy lifestyle caused by an exaggerated caloric intake. This paper reviews the evidence supporting the beneficial effect of RSV for various pathological conditions, e.g., neoplastic diseases, neurodegeneration, metabolic syndrome, diabetes, obesity, CVDs, immune diseases, bacterial, viral, and fungal infections. The study also focused on the chromatographic analysis of trans-RSV (tRSV) in Romanian wine samples, providing a comprehensive overview of tRSV content across different types of wine.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

The physiological process of iodine uptake in the thyroid is used for 131I treatment of thyroid diseases. Children are more sensitive to radiation compared to adults and may react differently to 131I exposure. The aims of this study were to evaluate the effects on thyroid protein expression in young and adult rats one year after 131I injection, and identify potential biomarkers related to 131I exposure, absorbed dose, and age. Twelve Sprague Dawley Rats (young and adults) were i.v. injected with 50 kBq or 500 kBq 131I and were killed twelve months later. Twelve untreated rats were used as age-matched controls. Quantitative proteomics, statistical analysis and evaluation of biological effects was performed. The effects of irradiation were most prominent in young rats. Protein biomarker candidates were proposed related to age, absorbed dose, thyroid function and cancer and a panel was proposed for 131I exposure. In conclusion, the proteome of rat thyroid was differentially regulated twelve months after low-intermediate dose exposure to 131I in both young and adult rats. Several biomarker candidates are proposed for 131I exposure, age, and many of them are known to be related to thyroid function or thyroid cancer. Further research on human samples are needed for validation.

A paper recently published by eLife on forebrain cortical synaptic plasticity reports that retinoic acid (RA) alters synaptopodin-dependent metaplasticity in mouse dentate granule cells (Lenz et al., 2021). RA is the active form of vitamin A that functions as a ligand for nuclear RA receptors that directly bind genomic control regions to regulate gene expression (Chambon, 1996; Ghyselinck and Duester, 2019). However, some studies have suggested that RA may have nongenomic effects outside of the nucleus, particularly with regard to synaptic plasticity (Aoto et al., 2008; Zhang et al., 2018). The current results reported by Lenz et al. demonstrate that treatment with pharmacological levels of RA can alter synaptic plasticity which may be useful to treat neurological diseases (Lenz et al., 2021). However, the results reported here and those reported by others have not shown that endogenous RA is normally required for synaptic plasticity (or any other nongenomic effect) as there are no reports of genetic loss-of-function studies that remove endogenous RA in adult brain. The implication is that pharmacological levels of RA result in nongenomic effects, some of which may be helpful to treat certain diseases but in other cases this may cause unwanted side-effects.

In the present work report, the MgAl₂O₄and the Ag/MgAl₂O₄ samples were successfully synthesized by the modified hydrothermal and the isovolumetric impregnation methods, respectively. The structural properties of the prepared samples were systematically characterized by XRD, SEM, TEM, DRS, XPS and et al techniques. The photocatalytic degradation of methylene blue by the Ag/MgAl₂O₄ and MgAl₂O₄ samples was comparatively studied under UV lamp irradiation. The results revealed that the prepared Ag/MgAl₂O₄ (pH=6) samples were the most active among the samples in photocatalytic of methylene blue. Under UV lamp irradiation, the Ag/MgAl₂O₄ (pH=6) photodegradation of methylene blue reached to 89.6% within 120 min. And the Ag/MgAl₂O₄ (pH=6) complex photocatalysts displayed a high photochemical stability under repeated irradiation. Repeated irradiate the Ag/MgAl₂O₄ (pH=6) compound, which indicated it had a high photochemical stability.

The three-armed cluster-randomized trial ARena (Sustainable reduction of antibiotic-induced antimicrobial resistance) aimed to foster appropriate antibiotic use and reduce overprescribing in German ambulatory care to counter antibiotic resistance. Multi-faceted interventions targeted primary care physicians, teams and patients. This study examined effectiveness of the implementation program. ARena was conducted in 14 primary care networks with 196 practices. All arms received data-based feedback on antibiotics prescribing and quality circles. Arms II and III received different add-on components each. Primary outcome examined is the prescribing rate for systemic antibiotics for cases with non-complicated acute infections (upper respiratory tract, bronchitis, sinusitis, tonsillitis, otitis media). Secondary outcomes refer to prescribing of quinolones and guideline-recommended antibiotics. Based on pseudonymized quarterly claims data, mixed logistic regression models examined pre-post intervention antibiotic prescribing rate changes and compared to matched standard care. A significant rate reduction (arm I 11.7%; arm II 9.9%; arm III 12.7%) and significantly lower prescribing rates were observed for all arms (20.1%, 18.9% and 23.6%) compared to matched standard care (29.4%). Fluoroquinolone prescribing was reduced in all intervention arms and rates for recommended substances generally increased. No significant post-interventional difference between intervention arms was detected. Findings indicate implementation program impact compared to standard care. Trial registration: ISRCTN, ISRCTN58150046

We study how abstract representations emerge in a Deep Belief Network (DBN) trained on benchmark datasets. Our analysis targets the principles of learning in the early stages of information processing, starting from the “primordial soup" of the under-sampling regime. As the data is processed by deeper and deeper layers, features are detected and removed, transferring more and more “context-invariant” information to deeper layers. We show that the representation approaches an universal model – the Hierarchical Feature Model (HFM) – determined by the principle of maximal relevance. Relevance quantifies the uncertainty on the model of the data, thus suggesting that “meaning" – i.e. syntactic information – is that part of the data which is not yet captured by a model. Our analysis shows that shallow layers are well described by pairwise Ising models, which provide a representation of the data in terms of generic, low order features. We also show that plasticity increases with depth, in a similar way as it does in the brain. These findings suggest that DBNs are capable of extracting a hierarchy of features from the data which is consistent with the principle of maximal relevance.

This paper presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g. a laser diode is affixed to a movable axis and projects a random geometric shape on an image sensor (CMOS or CCD). The software in the downstream microcontroller identifies the geometric shape’s center, distortion and size, then calculates X, Y, and Z coordinates. These coordinates can then be processed in attached devices. The 3-axis sensor is characterized by its very high resolution, precise reproducibility and plausibility of the coordinates produced. In addition, optical processing of the signal provides a high level of safety against electromagnetic and radio frequency interference. The sensor presented here is adaptive and can be adjusted to fit a user’s range of motion (stroke and force). This recommendation aims to optimize sensor systems such as joysticks in medical devices in terms of safety, ease of use, and adaptability.

Voice spoofing attempts to break into a specific automatic speaker verification (ASV) system by forging the user’s voice, and can be used through methods, such as text-to-speech (TTS), voice conversion (VC), and replay attacks. Recently, deep learning-based voice spoofing countermeasures have been developed. however, the problem with replay is that it is difficult to construct a large number of datasets because it requires a physical recording process. To overcome these problems, this study proposes a pre-training framework based on multi-order acoustic simulation for replay voice spoofing detection. Multi-order acoustic simulation utilizes existing clean signal and room impulse response (RIR) datasets to generate audios, which simulate the various acoustic configurations of the original and replayed audios. The acoustic configuration refers to factors, such as the microphone type, reverberation, time delay, and noise that may occur between a speaker and microphone during the recording process. We assume that a deep learning model trained on an audio that simulates the various acoustic configurations of the original and replayed audios can classify the acoustic configurations of the original and replay audios well. To validate this, we performed pre-training to classify the audio generated by the multi-order acoustic simulation into 3 classes: clean signal, audio simulating the acoustic configuration of the original audio, and audio simulating the acoustic configuration of the replay audio. We also set the weights of the pre-training model to the initial weights of the replay voice spoofing detection model using the existing replay voice spoofing dataset and then performed fine-tuning. To validate the effectiveness of the proposed method, we evaluated the performance of the conventional method without pre-training and proposed method using an objective metric, i.e., the accuracy. As a result, the conventional method achieved 92.94% accuracy and proposed method achieved 98.16% accuracy.

Electrical impedance tomography (EIT) can monitor the real-time hemodynamic state of a conscious and spontaneously breathing patient noninvasively. However, cardiac volume signal (CVS) extracted from EIT images has a small amplitude and is sensitive to motion artifacts (MAs). This study aimed to develop a new algorithm to reduce MAs from the CVS for more accurate heart rate (HR) and cardiac output (CO) monitoring in patients undergoing hemodialysis based on the source consistency between the electrocardiogram (ECG) and the CVS of heartbeats. Two signals were measured at different locations on the body through independent instruments and electrodes, but the frequency and phase were matched when no MAs. As the number of motions per hour (MI) increased over 30, the proposed algorithm had a correlation of 0.83 and a precision of 1.65 beats per minute (BPM) compared to the conventional statical algorithm of a correlation of 0.56 and a precision of 4.04 BPM. For CO monitoring, the precision and upper limit of the mean ∆CO were 3.41 and 2.82 liters per minute (LPM), respectively, compared to 4.05 and 3.82 LPM of the statistical algorithm. The developed algorithm could reduce MAs and improve HR/CO monitoring accuracy and reliability, particularly in high-motion environments.

Managing blood cholesterol levels is important for the treatment and prevention of diabetes, cardiovascular disease, and obesity. An easy-to-use, portable cholesterol blood test will accelerate more frequent testing by patients and at-risk populations. We aim to evaluate the performance of smartphone-based point-of-care cholesterol blood tests as compared to that of hospital-grade laboratory tests. We used smartphone systems that are already familiar to many people. Because smartphone systems can be carried around everywhere, blood can be measured easily and frequently. We compared the results of cholesterol tests with those of existing clinical diagnostic laboratory methods. We found that smartphone-based point-of-care lipid blood tests are as accurate as hospital-grade laboratory tests (N=116, R>0.97, P<0.001 for all 3 cholesterol blood tests: total cholesterol, high density lipoprotein, and triglyceride). Our system will be useful for those who need to manage blood cholesterol levels to motivate them to track and control their behavior.

This paper presents a non-perturbative method for solving eigenproblems. This method applies to almost all potentials and provides non-perturbative approximations for any energy level. The method converts an eigenproblem into a perturbation problem, obtains perturbation solutions through standard perturbation theory, and then analytically continues the perturbative solution into a non-perturbative solution.

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

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

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

The incidence of hepatocellular carcinoma (HCC) is increasing and 40% of patients are diagnosed at advanced stages. Over the past 5 years, the number of clinical available treatments have dramatically increased for HCC, making patient management particularly complex. Immune checkpoint inhibitors (ICIs) have improved the overall survival of patients showing a durable treatment benefit over time, and a different response pattern with respect to tyrosine kinase inhibitors (TKIs). Although improved survival in responder cases, a sizeable group of patients are primary progressors or are ineligible for immunotherapy. Indeed, patients with non-viral etiologies, such non-alcoholic steatohepatitis (NASH), and alterations in specific driver genes might be less responsive to immunotherapy. Therefore, improving the comprehension of mechanisms of drug resistance and identifying biomarkers informative of the best treatment approach are required actions to improve patient survival. Numerous evidence indicated non-coding RNAs (ncRNAs) as pivotal players in cancer. Molecular mechanisms through which ncRNAs exert their effects in cancer progression and drug resistance have been widely investigated. Nevertheless, there are no studies summarizing the synergistic effect between ncRNA-based strategies and TKIs or ICIs in the preclinical setting. This review aims to provide up-to-date information regarding the possible use of ncRNAs as therapeutic targets in association with molecular targeted agents and immunotherapies and as predictive tools for the selection of optimized treatment options in advanced HCCs.

The service sector, whose value has started to increase in recent years, has gained momentum with the acceleration of economic developments especially after the 2000s in Turkey. In a world where competition is increasing and social purchase perception is changing, companies started to differentiate in the service sector to create a competitive advantage. Companies that would like to grow in the industry and aspire to a greater proportion need credit to extend. There are many factors to consider in order to allocate the credit. Banks make financial and non-financial analysis to make credit decisions. This study has been prepared to assess the effect of financial and non-financial features of middle segment companies that need credit in the service sector on the credit decision to be allocated by banks. The group of variables that explain the credit decision at the highest level in these companies are non-financial variables.

Enterococci are commonly found in the environment and humans as a part of the normal micro-biota Among these, Enterococcus faecalis and Enterococcus faecium can convert into opportunistic pathogens, making them a major cause of nosocomial infections. The rapid diffusion of vanco-mycin-resistant strains and their impact on nosocomial settings is of considerable concern. Ap-proximately one-third of the E. faecium infections in Italy are caused by vancomycin-resistant strains. This study explored the hypothesis that the oral cavity could represent a silent reservoir of virulent enterococci. A sample of 862 oral flora specimens collected from healthy human volun-teers in Central Italy was investigated by real-time PCR to detect E. faecalis and E. faecium, as well as the genetic elements that most frequently determine vancomycin resistance. The prevalence of E. faecalis was 19%, a value that was not associated with alcohol consumption, tobacco smoking, or age of the subjects. Less frequently detected, with an overall prevalence of 0.7%, the E. faecium was more common among people older than 49 years of age. The genes conferring vancomycin resistance were detected in only one sample. Results indicate that the oral cavity can be considered a reservoir of clinically relevant enterococci; however, our data suggest that healthy individuals rarely carry vancomycin-resistant strains.

Background: Routine childhood vaccination, e.g., for diphtheria-tetanus-pertussis (DTP), might provide an additional protection towards SARS-CoV-2 infection. This concept of heterologous immunity was explored in healthy children receiving both DTP and inactivated SARS-CoV-2 vaccines. Methods: A cross-sectional study was performed on 154 healthy children aged 6–8 years old in Jakarta, Indonesia. Their vaccination status of DTP (including diphtheria-tetanus booster vaccine at 5 years old) and CoronaVac (from 6 years old) were recorded. Peripheral blood samples were collected from all participants, in which anti-diphtheria toxoid IgG, anti-SARS-CoV-2 S-RBD antibodies and T cell-derived IFN-g were measured. Results: Study participants with complete DTP vaccination had significantly higher titer of anti-diphtheria toxoid IgG than the ones without (median=0.9349 versus 0.2113 IU/mL; p<0.0001). Upon stratification based on DTP and CoronaVac vaccination statuses, participants with complete DTP and CoronaVac vaccinations had the highest titer of anti-SARS-CoV-2 S-RBD antibodies (median=1,196 U/mL) and the highest concentration of SARS-CoV-2-specific T cell-derived IFN-g (median=560.9 mIU/mL) among all groups. Conclusion: Healthy children aged 6-8 years old with complete DTP and CoronaVac vaccinations exhibited higher SARS-CoV-2-specific adaptive immune responses, particularly on their T-cell response. This suggests an additional benefit of routine childhood vaccination to generate protection against novel pathogens, presumably via heterologous immunity.

The Sulfur Dioxide (SO2) compound is a primary environmental pollutant worldwide, whereas elemental Sulfur (S) is a global commodity possessing a variety of industrial as well as commercial functions. The chemical relationship between poisonous SO2 and commercially viable elemental S has motivated this investigation using Density Functional Theory calculation of the relative transition state barriers for the 2-step Dehydro-sulfurization oxidation-reduction reaction. Additionally, doubly-charged nanoscale platelet Molybdenum Disulfide (MoS2), Armchair (6,6) Carbon Nanotube, 28-atom Graphene nanoflake (GR-28), and Fullerene C-60 are utilized as catalysts. The optimal heterogeneous and homogeneous catalysis pathways of the 2-step oxidation-reduction from SO2 to elemental S are further inspired by the biomimicry of the honeybee species multi-step bio-catalysis of pollen conversion to organic honey. Potential applications include environmental depollution, the mining of elemental sulfur, and the functionalization of novel technologies such as the recently patented aerial and amphibious Lynchpin TM drones.

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics, and thermodynamic parameters of peanut shell using TGA under atmospheric air. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1. Pre-exponential factors using FWO range from 2.19×106 to 8.06×107 s–1, and for KAS range from9.72×105 to 2.25×107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤ ±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

Background: During the stay in the neonatal intensive care unit, parents play a crucial role in the care of their infants. Recent studies reported a decrease in parental participation due to Coronavirus Disease (COVID-19) pandemic that determined restricted access policies in hospitals. The aim of this study is to describe the barriers to a good parents’ participation during the stay in the neonatal intensive care unit in the COVID-19 era. Methods: A quantitative observational study was carried out. Results: 270 parents participated in this study. Mothers’ participation in care seems to be higher as compared to fathers (p = 0.017). Parents who lived the birth of their first child reported a better level of participation in care when compared to those who lived the birth of their second born (p = 0.005). Parents of extremely preterm neonates reported a lower interaction with their infant if compared to parents of term newborns (p &lt; 0.001). Conclusions: Some more disadvantaged categories have reported lower scores: cultural and linguistic minorities, parents of multiple children and fathers. COVID-19 pandemic made several Family Centred Care activities not possible with a higher impact on those who benefited the most of these facilities. This study was prospectively registered by the IRB-CRRM of the University “G. d’Annunzio” Chieti-Pescara on the 23/01/2024 with registration number CRRM;2023_12_07_01.

Savannas and adjacent vegetation types like gallery forests are highly valuable ecosystems contributing to several ecosystem services including carbon budgeting. Financial mechanisms such as REDD+ have provided an opportunity for developing countries to alleviate poverty through conservation of its forestry resources. For availing this opportunity carbon stock assessments are essential. Therefore, a research study at two protected areas i.e. Nazinga Game Ranch and Bontioli Nature Reserve, in Burkina Faso was conducted with the objective of assessing carbon Mg C ha-1 in aboveground biomass (AGB)dry of trees in different formations of the south-sudanian savanna in Burkina Faso, West Africa. Similarly analysis of various vegetation parameters was also conducted to understand the overall vegetation structure of these two protected areas. For estimating AGBdry, existing allometric equation for dry tropical woody vegetation types was used. The Importance Value Index (IVI) and Family Importance Value (FIV) were estimated through standard procedures. Various linear and non-linear regression analyses were conducted to test the relationships between carbon and other parameters such as DBH, height and basal area (BA). The results showed that both sites collectively contain mean carbon of 3.41 ± 4.98 Mg C ha-1. Amongst different vegetation types, gallery forests recorded the highest mean carbon of 9.38 ± 6.90 Mg C ha-1. The highest IVI of 115.56 at Nazinga Game Ranch was recorded for Anogeissus leiocarpa. Similarly, highest IVI of 98.59 was recorded for Mitragyna inermis at Bontioli Nature Reserve. The highest FIV was recorded for Combretaceae for both of the sites. To our knowledge, this was the first study conducted to assess the carbon stocks at the two protected areas in southern Burkina Faso. The study therefore was an attempt for addressing the knowledge gap particularly on carbon stocks of protected savannas. It could serve as a baseline for carbon stocks for future initiatives such as payment for environmental services and REDD+ at these areas.

Retroviruses perpetuate their survival by incorporating a copy of their genome into the host cell, a critical step catalyzed by the virally encoded integrase. The viral capsid plays an important role during the viral life-cycle, including nuclear importation in case of lentiviruses and integration targeting events, hence, targeting the integrase and the viral capsid is a favorable therapeutic strategy. While integrase strand transfer inhibitors (INSTIs) are recommended as first-line regimens given their high efficacy and tolerability, lenacapavir is the first capsid inhibitor and the newest addition to the HIV treatment arsenal. These inhibitors are however designed for treatment of HIV-1 infection, and their efficacy against HIV-2 remains widely understudied and inconclusive, supported only by few limited phenotypic susceptibility studies. We therefore carried out inhibition profiling of a panel of second-generation INSTIs and lenacapavir against HIV-2 in cell culture, utilizing pseudovirion inhibition profiling assays. Our results show that the tested INSTIs and lenacapavir exerted excellent efficacy against ROD-based HIV-2 integrase, and interestingly, raltegravir also showed modest antiviral activity against the SARS-CoV-2 Omicron variant in antiviral assays carried out in Vero E6 cells.

The focus of our study was the changes in the composition of semi-natural dry grasslands in Hungary. Since these valuable habitats were created with the help of humans, their preservation also requires regular treatment. Our mowing experiment aimed to investigate the suppression of the native Calamagrostis epigejos L. Roth. In Hungary, in the Cserhát Mountains, eight permanent plots were mowed twice a year. The vegetation was sampled annually between 2001 and 2011. The effects of mowing were investigated with repeated measures analysis of variance (ANOVA). After 10 years, the C. epigejos cover of the mowed plots decreased significantly, from the initial average of 62.38 to 7.50%. Surprisingly, we also experienced a similar decrease in the control plots. Regular treatment also had a positive effect on the number of species and diversity. Species richness increased continuously in both treatment types, which indicates the combined effect of vegetation succession and treatment. The biomass growth of other Poaceae and Fabaceae species, which are important from a grassland management perspective, was also facilitated by mowing. Our results suggest that long-term in situ experiments and continuous botanical studies are needed to establish a reliable utilization of grasslands.

This review delves into the growing field of flexible and stretchable strain sensors utilized in human gait analysis, focusing on determining knee bending angle and muscle activities when a human subject walks. Recent advancements have enabled these sensors to accurately capture biomechanical parameters while accommodating the body's natural movements. We examine the principles underlying these sensors' design and fabrication techniques, emphasizing their flexibility, stretchability, and biocompatibility for seamless integration into wearable systems. Through critical evaluation of existing methodologies, we assess the reliability and validity of these sensors in quantifying gait parameters. Furthermore, we discuss this technology's clinical and research implications, highlighting its potential in personalized rehabilitation and sports performance optimization. We provide an overview of flexible strain sensors and their application for analyzing human walking gait, especially for observing walking gait in rehabilitation programs. First, we present the basic working principles of various flexible strain sensors. Second, by the application of flexible strain sensors as walking gait monitoring. Finally, current challenges and future opportunities in this research area are discussed. By synthesizing current knowledge and outlining future directions, this review aims to provide insights for researchers and practitioners seeking to leverage flexible and stretchable strain sensors for comprehensive human gait analysis.

Nuclear waste is one of the most important environmental problems of nuclear power plants. A novel renewable distillation method has been proposed for an on-site recycling of the spent nuclear fuel and separation of its valuable components from the fissile isotopes, which is especially applicable for reactors using liquid fuels.

Wound healing involves physical, chemical and immunological processes. Transient receptor potential (TRP) and other ion channels are implicated in epidermal re-epithelization. Ion movement across ion channels can induce transmembrane potential that leads to transepithelial potential (TEP) changes. TEP present in epidermis surrounding the lesion decreases and induces an endogenous direct current generating an epithelial electric field (EF) that could be implicated in wound re-epithelialization. TRP channels are involved in the activation of immune cells during the inflammatory phase of wound healing. The aim of the study was to review the mechanisms of ion channel involvement in wound healing in in vivo experiments in rodents (mice, rats, rabbits) and how can this process be influenced. This review used the latest results published in scientific journals over the last year and this year to date (1 January 2023–31 December 3000) in order to include the in-press articles. Some types of TRP channels, such as TRPV1, TRPV3, and TRPA1, are expressed in immune cells and can be activated by inflammatory mediators. The most beneficial effects in wound healing are produced using agonists of TRPV1, TRPV4 and TRPA1 channels or by inhibiting with antagonists, antisense oligonucleotides or knocking down TRPV3 and TRPM8 channels.

On a global scale, food safety and security aspects entail to be considered throughout the farm to fork continuum considering food’s supply chain. Generally, the agri-food system is a multiplex network of interconnected features and processes, with a hard predictive rate, where maintaining the food’s safety is an indispensable element and is part of the Sustainable Development Goals (SDGs). It has led the scientific community to develop advanced applied analytical methods, such as Machine learning (ML) and Deep Learning (DL) techniques applied for assessing foodborne diseases. The main objective of this paper is to contribute to the development of the consensus version of ongoing research about the application of artificial intelligence tools in the domain of food-crops safety from an analytical point of view. Writing a comprehensive review for a more specific topic can also be challenging, especially when searching within the literature. To our knowledge, this review is the first to address this issue. This work consisted of conducting a unique and exhaustive study of the literature, using our TriScope Keywords-based Synthesis methodology. All available literature related to our topic was investigated according to our criteria of Inclusion and Exclusion. The final count of data papers was subject to deep reading and analysis to extract the necessary information to answer our research questions. Although many studies have been conducted, limited attention has been paid to outlining the applications of AI tools combined with analytical strategies for crop-based food safety specifically.

Perovskite solar cells have shown significant progress, but their commercialization remains hindered by lead-based toxicity. Many nontoxic perovskite-based solar cells have demonstrated potential such as Cs2AgBi0.75Sb0.25Br6, but their power-conversion efficiency is inadequate. To address this issue, some researchers are focusing on emerging acceptor-donor-acceptor'-donor-acceptor (A-DA'D-A) type non-fullerene acceptors (NFAs) for Cs2AgBi0.75Sb0.25Br6 to find effective electron transport layers for high-performance photovoltaic responses with low voltage drops. In this comparative study, four novel A-DA'D-A types NFAs such as BT-LIC, BT-BIC, BT-L4F, and were used as an electron transport layer (ETL) for the proposed devices, FTO/PEDOT: PSS/ Cs2AgBi0.75Sb0.25Br6/ETL/Au. Comprehensive simulations were conducted to optimize the devices. The simulations showed that all optimized devices exhibit photovoltaic responses, with the BT-BIC device having the highest power conversion efficiency (13.2%) and the BT-LIC device having the lowest (6.8%). The BT-BIC as ETL provides fewer interfacial traps and better band alignment, enabling greater open-circuit voltage for efficient photovoltaic responses.

Aquaporins (AQPs) are water channels widely distributed in living organisms and involved in many pathophysiologies as well as in cell volume regulations (CVR). In the present study, based on the structural homology existing between mineralocorticoids receptors (MR), glucocorticoids receptors (GR), cholesterol consensus motif (CCM) and the extra-cellular vestibules of AQPs, we investigated the binding of corticosteroids on AQP family through in silico molecular dynamics simulations of AQP2 interactions with cortisol. We propose for the first time a putative AQPs corticosteroids binding site (ACBS) and discussed its conservation through structural alignment. Corticosteroids can mediate non-genomic effects, nonetheless, the transduction pathways involved are still misunderstood. Moreover, a growing body of evidence is pointing out toward the existence of a novel membrane receptor mediating part of these rapid corticosteroids effects. Our results suggest that the naturally produced glucocorticoid cortisol inhibits channel water permeability. Based on these results, we propose a detailed description of a putative underlying molecular mechanism. In this process, we also bring new insights on the regulatory function of AQPs extra-cellular loops and on the role of ions in tuning the water permeability. Altogether, this work brings new insights into corticosteroids non-genomic effects through the proposition of AQPs as membrane receptor of this family of regulatory molecules. This original result is the starting point for future investigations to define more in depth and in vivo the validity of this functional model.

The underlying physical concept of computing out-of-time-ordered correlation (OTOC) is a significant new tool within the framework of quantum field theory, which now-a-days is treated as a measure of random fluctuations. In this paper, by following the canonical quantization technique we demonstrate a computational method to quantify the two different types of Cosmological auto-correlated OTO functions during the epoch when the non-equilibrium features dominates in Primordial Cosmology. In this formulation, two distinct dynamical time scales are involved to define the quantum mechanical operators arising from cosmological perturbation scenario. We have provided detailed explanation regarding the necessity of this new formalism to quantify any random events generated from quantum fluctuations in Primordial Cosmology. We have performed an elaborative computation for the two types of two-point and four-point auto-correlated OTO functions in terms of the cosmological perturbation field variables and its canonically conjugate momenta to quantify random auto-correlations in the non-equilibrium regime. For both the cases we found significantly distinguishable non-chaotic, but random behaviour in the OTO auto-correlations, which was not pointed before in this type of studies. Finally, we have also demonstrated the classical limiting behaviour of the mentioned two types of auto-correlated OTOC functions from the thermally weighted phase space averaged Poisson Brackets, which we found exactly matches with the large time limiting behaviour of the auto-correlations in the super-horizon regime of the cosmological scalar mode fluctuation.

Exportin-1, the ubiquitous nuclear protein transporter, is widely confirmed as an active chemotherapeutic target in non-small cell lung cancer condition while Juglans mandshurica is a well-studied anticancer plant in some lung cancer cell lines. We intend to find novel exportin-1 inhibitor from Juglans mandshurica with better potential tolerability and pharmaco-dynamo-kinetic properties than the current selective inhibitors of nuclear export in non-small cell lung cancer treatment. Osiris property explorer DataWarrior, Glide standard precision docking, quantum mechanics polarized ligand docking, MMGBSA binding free energy calculations, Jaguar density functional theory analysis, and the online web-based SwissADME were employed respectively in this study to filter the retrieved compounds based on tolerability, toxicity, and Lipinsky’s rule of five violation potential, determine their druggability, establish relative stability of the lead compound in water solvation model, and evaluates druglikeness, lead-likeness, as well as synthetic accessibility of the lead compound. This study reveals eriodictyol as having higher binding free energy (-40 kcal/mol) than that of standard (-39.56 kcal/mol) in exportin-1 active site, better synthetic accessibility score (3.15 versus 3.29), high GI absorption, non-blood brain barrier permeant, lacks Brenk and PAINS alert, obeying Lipinski’s, Ghose’s, Veber’s, Egan’s, and Muegge’s rule of druglikeness and lead-likeness as well as non-cytotoxic to HepG2 cells. We therefore found eriodictyol as a lead-like, non-toxic exportin-1 inhibitor with good predictive stability and pharmacokinetic potential and thus provided data for further validation of eriodictyol as a candidate exportin-1 inhibitor in both preclinical and clinical studies involving lung cancer therapy.

We construct a family of two-step optimal fourth order iterative methods for finding single root of non-linear equations. We generalize these methods to simultaneous iterative methods for determining all the distinct as well as multiple roots of single variable non-linear equations. Convergence analysis is present for both cases to show that the order of convergence is four in case of single root finding method and is twelve for simultaneous determination of all roots of non-linear equation. The computational cost, Basin of attraction, efficiency, log of residual and numerical test examples shows, the newly constructed methods are more efficient as compared to the existing methods in literature.

Dynamic analyses and seismic assessments of multi-storey buildings at urban level require large-scale simulations and computational procedures based on simplified but accurate numerical models. At this aim the present paper propos-es an equivalent non-uniform beam-like model, suitable for the dynamic analysis of buildings with asymmetric plan and non-uniform vertical distribution of mass and stiffness. The equations of motion of this beam-like model, which pre-sents only shear and torsional deformability, are derived through the application of Hamilton’s principle. The linear dy-namic behaviour is evaluated by discretizing the continuous non-uniform model according to a Rayleigh-Ritz approach based on a suitable number of modal shapes of the uniform shear-torsional beam. In spite of its simplicity, the model is able to reproduce the dynamic behaviour of low- and mid-rise buildings with a significant reduction of the computa-tional burden with respect to that required by more general models. The efficacy of the proposed approach has been tested, by means of comparisons with linear FEM simulations, on three multi-storey buildings characterized by different irregularities. The satisfactory agreement, in terms of natural frequencies, modes of vibration and seismic response, proves the capability of the proposed approach to reproduce the dynamic response of complex spatial multi storey frames.

The upsurge of Generative Adversarial Networks (GANs) in the previous five years has led to advancements in unsupervised data manipulation, sourced feature translation, and precise input-output synthesis through a competitive optimization of the discriminator and generator networks. More specifically, the recent rise of cycle-consistent GANs enables style transfers from a discrete source (input A) to target domain (input B) by preprocessing object features for a multi-discriminative adversarial network. Traditionally, cyclical adversarial networks have been exploited for unpaired image-to-image translation and domain adaptation by determining mapped relationships between an input A graphic and an input B graphic. However, this integral mechanism of domain adaptation can be applied to the complex acoustical features of human speech. Although well-established datasets, such as the 2018 Voice Conversion Challenge repository, paved way for female-male voice transformation, cycle-GANs have rarely been re-engineered for voices outside the datasets. More critically, cycle-GANs have massive potential to extract surface-level and hidden feature to distort an input A source into a texturally unrelated target voice. By preprocessing, compressing, and packaging unique acoustical voice properties, CycleGANs can learn to decompose speech signals and implement new translation models while preserving emotion, the intent of words, rhythm, and accents. Due to the potential of CycleGAN’s autoencoder in realistic unsupervised voice-voice conversion/feature adaptation, the researchers raise the ethical implications of controlling source input A to manipulate target voice B, particularly in cases of defamation and sabotage of target B’s words. This paper analyzes the potential of cycle-consistent GANs in deceptive voice-voice conversion by manipulating interview excerpts of political candidates.

Non-destructive testing of metallic objects that may contain embedded defects of different sizes is an important application in many industrial branches for quality control. Most of these techniques allow defect detection and its approximate localization, but very few give enough information for its 3D reconstruction. Here we present a hybrid laser – transducer system that combines remote laser-generated ultrasound excitation and non-contact ultrasonic transducer detection. This fully non-contact method gives access to separating scan areas on different object’s faces and defect details from different angles/perspectives can be analysed. This hybrid system can analyse the whole object’s volume data and allow a 3D reconstruction image of the embedded defects. As a novelty for the signal processing improvement, we use a 2D apodization window filtering technique, applied along with the synthetic aperture focusing algorithm in order to remove the undesired effects of side lobes and wide-angle reflections of propagating ultrasound waves, thus, enhancing the resulting 3D image of the defect. We provide both qualitative and quantitative volumetric results with high accuracy and resolution compared with conventional techniques.

The rapid development of algorithms for skeleton detection with relatively inexpensive contactless systems and cameras opens the possibility of virtual exercise therapy for patients with different complications. However, evaluation and confirmation of posture classifications is still needed. The purpose of this study was therefore to find the most accurate algorithm for automatic classification of human exercise movement. A Kinect V2 with 25 joints identification was used to record movements for data analysis. A total of 10 subjects volunteered for this study. Four algorithms were tested for the classification of different postures in Matlab. These were based on: total error of vector lengths, total error of angles, multiplication of these two parameters and simultaneous analysis of the first and second parameters. A base of 13 exercises was then created to test the recognition of postures by the algorithm, and to analyse subject performance. The best results for posture classification was shown by the second algorithm with an accuracy of 94.9%. The average correctness of exercises among the 10 participants was 94.2% (SD1.8%). The algorithms tested in this study therefore proved to be effective and could potentially form the basis for developing a system for remote monitoring of rehabilitation involving exercise.

Considering characteristics of high river density, special underlying surface in plain river network region, and municipal drainage system function, river network drainage unit model is proposed, which is defined as a region surrounded by main river or embankment. Flood storage variety and control projects regulation of small rivers in each unit is simulated. With drainage catchment as an object, according to its drainage capacity, simplified municipal drainage model was developed. Coupling river network drainage unit model, simplified municipal drainage model and 2D flood routing model, urban flood analysis model for plain tidal river network region was developed, which could be applied to analyzing flood from upstream river, storm surge and local rainfall. Demonstration research was carried out in Puxi flood protected area in Shanghai.

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, the drill bit condition monitoring techniques have been developed based on the wavelet analysis and artificial neural network (ANN) as 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 changed. The Data Acquisition system (DAQ) with Lab VIEW software is used to capture the vibration signals for drill bit with different wear conditions. 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 results show the effectiveness of the combed WT and ANN for automatic classification of tool wear conditions with high success rate.

The effective Supervisory Control and Data Acquisition (SCADA) system can improve the reliability, safety and economic benefits of microgrid operation. In this research, the lower central controller and upper WEB monitoring system are connected by the SCADA system which is as the hub of microgrid intelligent monitoring platform. This system contains a set of specific functions programmed by Java as a middleware which can provide control and communication between the central controller and the upper monitoring system. The system realizes the real-time data acquisition and storage, the control instructions parsing and transmitting, the microgrid security and stability, the load balancing and resource recovery of the microgrid. All that functions have been tested and verified in the actual operation.

Until recently, no disease-specific health-related quality of life (HRQoL) instrument existed for pediatric traumatic brain injury (TBI). In this revalidation study, the psychometric properties and the validity of the final German version of the 35-item QOLIBRI-KID/ADO questionnaire were examined in 300 children and adolescents. It is the first self-reported TBI-specific instrument for measuring pediatric HRQoL in individuals aged 8–17 years. The six-factor model fits the data adequately. Internal consistencies were excellent for the total score and satisfactory to excellent for the scale scores. Intraclass correlations indicated good test-retest reliability. Construct validity was supported by overlaps between the QOLBRI-KID/ADO and the PedsQL, which measures generic HRQoL. Discriminant validity indicated that HRQoL was significantly lower in older children and girls, and in those with anxiety, depression, and post-concussion symptoms than in comparison groups, replicating the results of the questionnaire’s first development study. Our results suggest that the QOLIBRI-KID/ADO is a valid and reliable multidimensional instrument for assessing disease-specific HRQoL after pediatric TBI in clinical and research settings, which can additionally be used across the lifespan in combination with the adult version. This may help to improve care, treatment, daily functioning and HRQoL after TBI.

Robot-assisted rehabilitation has emerged as a promising approach for enhancing motor function in stroke survivors. However, the feasibility and effectiveness of home-based robotic training in this population are underexplored, especially in low/middle-income countries. This feasibility study aimed to address this gap by examining the feasibility and effectiveness of independent home-based training using PLUTO, a robotic device for hand training. A total of 7 chronic stroke survivors were recruited, with 5 completing the study. The results revealed high engagement and adherence to the home-based training program, with participants averaging 1659.8 minutes of training over 24.8 days. The PLUTO system demonstrated excellent usability and elicited positive user perceptions. Significant improvements were observed in functional outcomes, as evidenced by a noteworthy increase in Fugl-Meyer Assessment scores (mean increase of 6.2 points, exceeding the minimal clinically important difference (MCID) of 5.35 points). Furthermore, participants showed improvements in the ABILHAND measure (mean improvement of 1.24 logits, surpassing the MCID of 0.2 logits) and the Barthel Index (mean increase of 8.8 points). These findings demonstrate the feasibility and effectiveness of home-based robotic rehabilitation for chronic stroke survivors. This has implications for expanding access to rehabilitation services in low- and middle-income countries, enhancing patient engagement and adherence, and improving functional outcomes. Larger controlled studies are warranted to evaluate the effectiveness of home-based robotic rehabilitation programs.

The ocean’s mixed layer depth (MLD) plays an important role in understanding climate dynamics, especially during extreme weather occurrences like hurricanes. This study investigates the effects of Hurricane Katrina (2005) on the MLD in the Gulf of Mexico, using the Delft3D modeling system. By integrating hydrodynamics and wave dynamics modules, we simulate the ocean’s response to extreme weather, focusing on temperature, salinity and MLD variations. Our analysis reveals significant cooling and mixing induced by Katrina, resulting in spatial and temporal fluctuations in temperature (~± 4°C) and salinity (~± 2.5 ppt). The MLD is estimated using a simple threshold method, revealing a substantial deepening to ~120 m on August 29th-30th during Hurricane Katrina in the middle of northern Gulf of Mexico, compared to an average MLD of ~20-40 m during pre-storm conditions. It took about 18-days to recover to ~84% of the pre-storm level after Katrina. Compared to the stand-alone FLOW model, the coupled FLOW+WAVE model yields a deeper MLD of ~5%. The MLD recovery and wave effect on the MLD provide insights from various scientific, environmental and operational perspectives, offering a valuable basis for ocean management, planning and applications, particularly during extreme weather events.