Aiming at the difficult problem of broadband oscillation localization in power systems, the intel-ligent localization method of oscillation source based on the digital twin is proposed and the os-cillation source localization system based on the digital twin is constructed. Firstly, a digital twin-based oscillation source localization method and system architecture are proposed. Fur-thermore, an intelligent positioning method of oscillation source based on data-driven and mechanism fusion is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the su-per-resolution technique is used to realize the super-resolution measurement of broadband os-cillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, the branch potential energy is used as input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

The use of visual signals in horticulture has attracted significant attention and encompassed a wide range of data types such as 2D images, videos, hyperspectral images, and 3D point clouds. These visual signals have proven to be valuable in developing cutting-edge computer vision systems for various applications in horticulture, enabling plant growth monitoring, pest and disease detection, quality and yield estimation, and automated harvesting. However, unlike other sectors, developing deep learning computer vision systems for horticulture encounters unique challenges due to the limited availability of high-quality training and evaluation datasets necessary for deep learning models. This paper investigates the current status of vision systems and available data in order to identify the high-quality data requirements specific to horticultural applications. We analyse the impact of the quality of visual signals on the information content and features that can be extracted from these signals. To address the identified data quality requirements, we explore the usage of a deep learning-based super-resolution model for generative quality enhancement of visual signals. Furthermore, we discuss how these can be applied to meet the growing requirements around data quality for learning-based vision systems. We also present a detailed analysis of the competitive quality generated by the proposed solution compared to cost-intensive hardware-based alternatives. This work aims to guide the development of efficient computer vision models in horticulture by overcoming existing data challenges and paving a pathway forward for contemporary data acquisition.

Spatial biology is a rapidly growing research field which focuses on the transcriptomic or proteomic profiling of single cells within tissues with preserved spatial information. Imaging-based spatial transcriptomics uses epifluorescence microscopy, which has shown remarkable results for identification of multiple targets in situ. Nonetheless, the number of genes that can be reliably visualized is limited by the diffraction of light. Here, we investigate the effect of structured illumination (SIM), a super-resolution microscopy approach, over the performance of single gene transcript detection in spatial transcriptomics experiments. We performed direct mRNA-targeted hybridization in situ sequencing for multiple genes in mouse coronal brain tissue sections. We evaluated spot detection performance in widefield and confocal images versus those with SIM in combination with 20X, 25X and 60X objectives. In general, SIM increases the detection efficiency of gene transcripts spots compared to widefield and confocal modes. For each case, the specific fold increase in localizations is dependent on gene transcripts density and the numerical aperture of the objective used, which showed to play an important role especially for densely clustered spots. Taken together, our results suggest that SIM has the capacity to improve spot detection and overall data quality in spatial transcriptomics.

With the development of deep learning technology, various structures and research methods for super-resolution restoration of natural images and document images have been introduced. In particular, a number of recent studies have been conducted and developed in image restoration using generative adversarial network. Super-resolution restoration is ill-posed problem because of some complex restraints such as a lot of high-resolution images being restored for the same low-resolution image and also difficulty in restoring noises like edges, light smudging, and blurring. In this study, we utilized the spatially adaptive de-normalization (SPADE) structure for document image restoration to solve previous problems such as edge unclearness, hardness to catch features of texts, and the image color transition. Consequently, it can be confirmed that the edge of the character and the ambiguous stroke are restored more clearly when contrasting with the other previously suggested methods. Also, the proposed method’s PSNR and SSIM scores are geting 8% and 15% higher, respectively, compared to the previous methods.

Laser shock peening as an innovative surface treatment technology can effectively improve the fatigue life, sur-face hardness, corrosion resistance, and residual compressive stress. Compared with the laser shock peening, the warm laser shock peening (WLSP) is a new surface treatment technology to improve materials’ surface performances, which takes advantage of thermal mechanical effects on stress strengthening and micro-structure strengthening, results in more stable distribution of the residual compressive stress under heating and cyclic loading process. In this paper, the microstructure of GH4169 nickel super-alloy processed by WLSP technology with differ-ent laser parameters were investigated. The proliferation and tangling of dislocations in GH4169 were observed and the dislocation density increased after WLSP treatment. The influences of different treatment by LSP and WLSP on the microhardness distribution of the surface and along cross-sectional depth were investi-gated. The microstructure evolution of the GH4169 alloy being shocked with WLSP were studied by TEM. The effect of temperature on the stability of high temperature microstructure and properties of GH4169 alloy WLP was investigated.

With our long experience in the field of unification of gravity and quantum mechanics, we understood that, when mass of any elementary is extremely small/negligible compared to macroscopic bodies, highly curved microscopic space-time can be addressed with large gravitational constants and magnitude of elementary gravitational constant seems to increase with decreasing mass and increasing interaction range. In our earlier publications, we proposed that, 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions; 2) There exists a strong interaction elementary charge in such a way that, it's squared ratio with normal elementary charge is close to inverse of the strong coupling constant; and 3) Considering a fermion-boson mass ratio of 2.27, quarks can be split into quark fermions and quark bosons. Further, we noticed that, electroweak field seems to be operated by a primordial massive fermion of rest energy 584.725 GeV and hadron masses seem to be generated by a new hadronic fermion of rest energy 103.4 GeV. In this context, starting from lepton rest masses to stellar masses, we have developed many interesting and workable relations. With further study, a workable model of final unification can be developed.

A phenomenological constitutive model is developed to describe the uniaxial transformation ratcheting behaviors of super–elastic shape memory alloy (SMA) by employing a cosine–type phase transformation equation with the initial martensite evolution coefficient that can capture the feature of the predictive residual martensite accumulation evolution and the nonlinear hysteresis loop on a finite element (FE) analysis framework. The effect of the applied loading level on transformation ratcheting are considered in the proposed model. The evolutions of transformation ratcheting and transformation stresses are constructed as the function of the accumulated residual martensite volume fraction. The FE implementation of the proposed model is carried out for the numerical analysis of transformation ratcheting of the SMA bar element. The integration algorithm and the expression of consistent tangent modulus are deduced in a new form for the forward and reverse transformation. The numerical results are compared with those of existing model and the experimental results to show the validity of the proposed model and its FE implementation in transformation ratcheting. Finally, a FE modeling is established for a repeated preload analysis of SMA bolted joint

To develop green super rice varieties with high and stable yields under the rainfed conditions and improved nutrient use efficiency (NuUE), a modified backcross (BC) breeding approach was adopted using a high yielding and widely adaptable Xian variety, WTR1, as the recipient and a Geng variety, HAN, as the donor. Starting from the BC1F2 generation, the BC population had gone through one generation of selection under the IG, LI and RF conditions, followed by consecutive four generations of screening and selection for high GY under six different nutrient conditions, leading to the development of 230 BC1F6 introgression lines (ILs). The final evaluation of the 230 ILs under the six nutrient conditions identified many ILs with improved yields under various combinations of nutrient deficient conditions, including 12 promising lines that had significantly improved NuUE under two or more nutrient deficiency conditions. Our results demonstrated an efficient inter-subspecific BC breeding procedure with first round selection under the rainfed-drought condition followed by four generations of progeny testing for yield performances under six different nutrient conditions. The promising ILs were studied under replicated yield trials under 75N and -NPK conditions for developing high yield rice varieties with improved NuUE. Our results indicated that NuUE in rice was controlled by complex genetic and physiological mechanisms and the developed ILs provided useful materials for genetic and molecular dissection of NuUE in rice.

Background: Ankle fractures, comprising about 10% of musculoskeletal injuries, pose a significant healthcare burden with an increasing incidence, particularly among an aging population. This study focuses on isolated Danis-Weber type B fractures. Recent trends lean towards surgical intervention for anatomical restoration, quicker recovery, albeit with associated complications. This report aims to assess the safety and efficacy of NewClip narrow locking plate system with early weight bearing in treating isolated fibular fractures. Methods: The study includes patients with Danis-Weber type B fractures surgically treated with NewClip narrow locking plate system. Exclusions involved nondisplaced fractures, open fractures, or those requiring additional fixation.Results: Fifteen patients were enrolled in this study. Minor complications, including wound swelling, were observed in two cases. The Visual Analogue Scale (VAS) for pain exhibited a steady decline postoperatively, with almost complete resolution by the third month. At three months, the FAOS demonstrated excellent results, and final follow-up at twelve months revealed complete osseous healing without complications.Conclusions: The use of this type of plates in treating isolated fibular fractures with early weight bearing shows promising results in terms of fracture healing, pain resolution, and functional outcomes warranting further investigation with larger cohorts.

Introduction: Physiotherapy exercises administered to preterm infants in the NICU can enhance motor skills and expedite the discharge process for infants born before 30 weeks of gestational age. The research delves into the influence of physiotherapy programs on these preterm infants' activity and participation levels. Methods: The intervention group received a one-month physiotherapy program including massage around the mouth, mobilization and weight-bearing exercises, and massage therapy for the extremities, while the control group did not. The motor skills were evaluated by the Test of Infant Motor Performance (TIMP), Dubowitz Neurological examination, and Preterm Oral Feeding Readiness Scales (POFRAS). Results: There was a significant difference in The TIMP, Dubowitz Optimal Score, Type of Non-Invasive Ventilation, TIMP Range, and POFRAS scores in the physiotherapy group rather than the control group (p<0.05). There were no differences in the length of stay in the NICU, respiration rate, heart rate, body temperature, oxygen saturation, body weight on the evaluation day, body weight at discharge, head circumference at discharge between the groups (p>0.05) Discussion: We conclude that physiotherapy in NICU improves the motor outcomes, activity and participation in preterm infants rather than the body functions and structure like vital signs and infants’ body weight.

Lung cancer remains the leading cause of cancer-related mortality worldwide. The main issue is the absence of a screening test available in clinical practice; the identification of non-invasive biomarkers is thus an urgent clinical necessity. Currently, low-dose computed tomography (LD-CT) demonstrates a 20% reduction of lung cancer mortality. However, it is not particularly suitable for clinical practice because of the costs, radiation, and the false positive rate. Several studies have therefore focused on research into biomarkers in body fluids. Despite the power of certain molecules to distinguish lung cancer patients from healthy subjects, no biomarker has yet been shown to significantly and reliably influence clinical decisions or to be translated from the laboratory to clinical practice. We performed an overview of the peer-reviewed biomedical literature published in the last 10 years on the research regarding biomarkers for the early diagnosis of lung cancer via a comprehensive analysis of the reviews published this past year. Our main aim was to bring to light the limitations and strengths of the research already conducted. Furthermore, future prospectives have been explored, bearing in mind the management of clinical trials and their integration into clinical practice.

Multi-cancer early detection (MCED) tests are being developed, but little is known about patient receptivity to their use for cancer screening. The current study assessed patient interest in such testing. Our team conducted a prospective, observational study among primary care patients in a large, urban health system. They were asked to complete a telephone survey that briefly described a new blood test in development to identify multiple types of cancer, but was not currently recommended or covered by insurance. The survey included items to assess respondent background characteristics, perceptions about MCED testing, and interest in having such an MCED test. We also used multivariable analyses to identify factors associated with patient interest in test use. In 2023, we surveyed 159 (32%) of 500 identified patients. Among respondents, 125 (79%) reported a high level of interest in having an MCED test. Interest was not associated with personal background characteristics, but was positively associated with the following expectations: testing would be recommended for cancer screening, be convenient, and be effective in finding early-stage disease (OR=11.70, 95% CI: 4.02, 34.04, p < 0.001). Research is needed to assess patient interest and actual uptake when detailed information on testing is presented in routine care.

Diabetic retinopathy (DR) and cataracts (CA) have an early onset in diabetes mellitus (DM) due to the redox imbalance and inflammation triggered by hyperglycemia. Plant-based therapies are characterized by low bioavailability in ocular tissues. The study aimed to investigate the effect of gold nanoparticles phytoreduced with Rutin (AuNPsR), as a possible solution. Insulin, Rutin, and AuNPsR, were administered to an early, six-week rat model of DR and CA. Oxidative stress (MDA, CAT, SOD) was assessed in serum and eye homogenates, and inflammatory cytokines (IL-1 beta, IL-6, TNF alpha) were quantified in ocular tissues. Fundus of retinal arterioles, retina histopathology and lens transmission electron microscopy (TEM), were also performed. DM was linked to constricted retinal arterioles, reduced endogen antioxidants, and eye inflammation. Histologically, retinal wall thickness decreased. TEM showed increased lens opacity and fiber disorganization. Rutin improved retinal arteriolar diameter, while reducing oxidative stress and inflammation. Retinas were moderately edematous. Lens structure was preserved on TEM. Insulin restored retinal arteriolar diameter, while increasing MDA, and amplifying TEM lens opacity. The best outcomes were obtained for AuNPsR, as it improved fundus appearance of retinal arterioles, decreased MDA formation and increased antioxidant capacity. Retinal edema and disorganization in lens fibers were still present.

Purpose: This study evaluates the performance of the Early Intervention Physiotherapist Framework (EIPF) for injured workers. This study provides a proper follow-up period (3 years) to examine the impacts of the EIPF program on injury outcomes such as return to work (RTW) and time to RTW. This study also identifies the factors influencing the outcomes. Methods: The study was conducted on data collected from compensation claims of people who were injured at work in Victoria, Australia. Injured workers who commenced their compensation claims after the first of January 2010 and had their initial physiotherapy consultation after the first of August 2014 are included. To conduct the comparison, we divided the injured workers into two groups: physiotherapy services provided by EIPF-trained physiotherapists (EP) and regular physiotherapists (RP) over the three-year intervention period. We used three different statistical analysis methods to evaluate the performance of the EIPF program. We used descriptive statistics to compare two groups based on physiotherapy services and injury outcomes. We also completed survival analysis using Kaplan-Meier curves in terms of time to RTW. We developed univariate and multivariate regression models to investigate whether the difference in outcomes achieved after adjusting for significantly associated variables. Results: The results showed that physiotherapists in the EP group on average dealt with more claims (over twice as many) than those in the RP group. Time to RTW for the injured workers treated by the EP group was significantly lower than for those who were treated by the RP group, indicated by descriptive, survival and regression analyses. Earlier intervention by physiotherapists led to earlier RTW. Conclusion: This evaluation showed that the EIPF program achieved successful injury outcomes three years after implementation. Motivating physiotherapists to intervene earlier in the recovery process of injured workers by initial consultation helps to improve injury outcomes.

Preoperative angiography in glioblastoma (GBM) often shows arteriovenous shunts and early venous filling (EVF). Here, we investigated the clinical implications of EVF in GBM as a prognostic and vascular mimicry biomarker. In this retrospective multicenter study, we consecutively enrolled patients who underwent angiography with a GBM diagnosis between April 1, 2013, and March 31, 2021. The primary and secondary endpoints were the differences in overall survival (OS) and progression-free survival (PFS), respectively, between cases with and without EVF. Of 133 initially enrolled patients, 91 newly diagnosed with GBM underwent preoperative angi-ography and became the study population. The 6-year OS and PFS were significantly worse in the EVF than in the non-EVF group. Moreover, 20 GBM cases (10 with EVF and 10 without EVF) were randomly selected and evaluated for histological vascular mimicry. Except for two cases that were difficult to evaluate, the EVF group had a significantly higher frequency of vascular mimicry than the non-EVF group (0/8 vs. 5/10, P = 0.04). EVF on preoperative angiography is a robust prognostic biomarker for GBM and may help detect cases with a high frequency of histological vascular mimicry.

It has been suggested that primordial planets could have formed in the early Universe and the missing baryons in the Universe could be explained by primordial free-floating planets of solid hydrogen. Many such planets were recently discovered around the old and metal poor stars and such planets could have formed at early epochs. Another possibility for missing baryons in the Universe could be that these baryons are admixed with DM particles inside the primordial planets. Here we discuss the possibility of admixture of baryons to the DM primordial planets discussed earlier. We consider gravitationally bound DM objects with the DM particles constituting them varying in mass from 20 to100GeV. Different fractions of DM particles mixed with baryonic matter in forming the primordial planets are discussed. For the different mass range of DM particles forming DM planets, we have estimated the radius and density of these planets with different fractions of DM and baryonic particles. It is found that for heavier mass DM particles with the admixture of certain fractions of baryonic particles, the mass of the planet increases and can reach or even substantially exceed Jupiter-mass. The energy released during the process of merger of such primordial planets is discussed. Also the energy required for the tidal breakup of such an object in the vicinity of a black hole is also discussed.

Epigenetic alterations are heritable and enduring modifications in gene expression that play a pivotal role in immune evasion. These include alterations to noncoding RNA, DNA methylation, and histone modifications. DNA methylation plays a crucial role in normal cell growth and development but alterations in methylation patterns such as hypermethylation or hypomethylation can enable tumor and viral cells to evade host immune responses. Histone modifications can also inhibit immune responses by promoting the expression of genes involved in suppressing normal immune function. In the case of T-cell lymphoma, adult T-cell Lymphomas (ALT) also undergo immune evasion through the exceptional function of its accessory and regulatory genes. Epigenetic therapies are emerging as a promising adjunct to traditional immunotherapy and chemotherapy regimens. Clinical trials are currently investigating the use of epigenetic therapies in combination with immunotherapies and chemotherapies for more effective treatment of ATL and other cancers. This review highlights epigenetic alterations that are widely found in T cell malignancies.

Antibiotic therapy is a cornerstone of modern medicine, yet the development of antibiotic re-sistance threatens to render these therapies ineffective. The gut microbiota, a complex ecosystem of microorganisms residing in the gastrointestinal tract, plays a critical role in modulating anti-biotic efficacy and resistance. This review delves into the intricate relationship between gut mi-crobiota, antibiotic therapy, and resistance, and discusses the potential applications of gut mi-crobiota research in guiding personalized antibiotic therapy and resistance mitigation strategies. Recent advancements in metagenomics, metatranscriptomics, and metabolomics have demon-strated the potential for tailored antibiotic regimens that minimize collateral damage to com-mensal bacteria and reduce the risk of resistance. Adjuvant therapies such as probiotics, prebi-otics, and synbiotics have shown promise in restoring gut microbial balance and mitigating the adverse effects of antibiotic therapy. We address the challenges associated with this emerging field including the need for standardized methodologies, ethical considerations, and interdisci-plinary collaboration. With continued interdisciplinary collaboration and the implementation of standardized methodologies, gut microbiota research can contribute to the global fight against antibiotic resistance and improve patient outcomes.

The application of movement-detection sensors is crucial for understanding surface movement and tectonic activities. The development of modern sensors has been instrumental in earthquake monitoring, prediction, early warning, emergency commanding and communication, search and rescue, and life detection. There are numerous sensors currently being utilized in earthquake engineering and science. It is essential to review their mechanisms and working principles thoroughly. Hence, we have attempted to review the development and application of these sensors by classifying them based on the timeline of earthquakes, physical or chemical mechanisms of sensors, and location of sensor platforms. In this study, we analyzed all available sensor platforms that have been widely used in recent years, with satellites and UAVs being among the most used. The findings of our study will be useful for future earthquake response and relief efforts, as well as research aimed at reducing earthquake disaster risks.

Background: Implant surface topography is a key element in achieving osseointegration. Nanostructured surfaces have shown promising results in accelerating and improving bone healing around dental implants. The main objective of the present clinical and histological study is to compare, at 4 and 6 weeks, (w) bone-to-implant contact in implants having either machined surface (MAC), SLA medium roughness surface or a Nanostructured Calcium-Incorporated sur-face (XPEED®). Methods: 35 mini-implants with 3 different surface treatments (XPEED® (n=16) – SLA (n=13) – Machined (n=6), were placed in the posterior maxilla of 11 patients then, retrieved at either 4 or 6w in a randomized split-mouth study design. Results: The BIC rate measured at 4 and 6w respectively, was: 16.8 % (±5.0) and 29.0 % (±3.1) for MAC surface; 18.5 % (±2.3) and 33.7 % (±3.3) for SLA surface; 22.4 % (±1.3) and 38.6 % (±3.2) for XPEED® surface. In all types of in-vestigated surfaces, the time factor appeared to significantly increase the BIC rate (p < .05). XPEED® surface showed a significantly higher values when compared to both SLA and MAC values at 4w (p < .05). Also, at 6w, both roughened surfaces (SLA and XPEED® ) showed signifi-cantly higher values (p < .05) than turned surface (MAC). Conclusion: Nanostructured Calcium titanate coating is able to enhance bone deposition around implants at early healing stages.

Early diagnosis of malaria and treatment seeking behavior play key role in controlling and preventing further complication related to malaria disease. Aim of this study was to determine the responses on early malaria diagnosis and treatment seeking behavior among outpatient clients attending at Sekou toure regional referral hospital in Mwanza, Tanzania. Methods: A cross-sectional study was conducted among outpatient client at Sekou-Touré regional referral hospital, convenient simple random sampling used and self-administered questionnaire were used to collect data and data was entered into Microsoft excel and then exported to SPSS version 25.0 for further analysis and presented on the percentages and table. The analysis of strength of relationships between categorical variables was conducted using the Chi-square test. A p-value of ≤ 0.05 was considered to be statistically significant. Results: A total of 192 respondents completed the study with a response rate of 97.6%. The study revealed that Most of the respondents about 90.6% stated they would seek treatment from health facility when symptoms appear. However, only 6.3% seek treatment within 24 hours of onset of illness (p= 0.017). Half of respondents (50.5%) experienced malaria symptoms in the past six months and only 30% seek for treatment at health facility. Preference of health facility, (51%) respondents were going direct to pharmacy to buy medicine for self-treatment. Overall, cost of service, time consumed and distance of health facility especially health center shows significant with such delay. Conclusion: A low proportion of malaria-suspected patients sought treatment within 24 h of fever onset compared to the national target. Distance from the health facility, cost of service and time consumed were found to be predictors of early treatment-seeking behavior for malaria. Strengthening strategies tailored to increasing awareness for communities about malaria, importance of going hospital and early treatment-seeking behavior is essential.

The incidence and prevalence of food allergy (FA) are increasing. While several studies have established the safety and efficacy of early introduction of single allergens in infants for the prevention of FA, the exact dose, frequency, and number of allergens that can be safely introduced to infants particularly in those at high or low risk of atopy are still unclear. This 1-year study evaluated the safety of early introduction of single foods (milk, egg, or peanut), vs. two foods (milk/egg, egg/peanut, milk/peanut), vs. multiple foods (milk/egg/peanut/cashew/almond/shrimp/walnut/wheat/fish/soy at low, medium, or high doses) vs no early introduction in infants between 4-6 months of age. At the end of the study, they were evaluated for plasma biomarkers associated with food reactivity with standardized blood tests. Two to four years after the start of the study, participants were evaluated by standardized food challenges. The serving sizes for the single, double, and low dose mixtures were 300 mg total protein per day. The serving sizes for the medium and high dose mixture was 900 mg and 3000 mg total protein, respectively. Equal parts of each protein were used for double or mixture foods. All infants were breastfed until at least 6 months of age. Results demonstrate that infants at either high or low risk for atopy were able to tolerate early introduction of multiple allergenic foods with no increases in any safety issues, including eczema, FA, or food protein induced enterocolitis. The mixtures of foods at either low, medium, or high doses demonstrated trends for improvement in food challenge reactivity and plasma biomarkers compared to single and double food introductions. The results of this study suggest that early introduction of foods, particularly simultaneous mixtures of many allergenic foods is efficacious for preventing FA and can occur safely.

Flood Early Warning Systems (FEWSs) using Machine Learning (ML) has gained worldwide popularity. However, determining the most efficient ML technique is still a bottleneck. We assessed FEWSs with three river states, No-alert, Pre-alert, and Alert for flooding, for lead times between 1 to 12 hours using the most common ML techniques, such as Multi-Layer Perceptron (MLP), Logistic Regression (LR), K-Nearest Neighbors (KNN), Naive Bayes (NB), and Random Forest (RF). The Tomebamba catchment in the tropical Andes of Ecuador was selected as case study. For all lead times, MLP models achieve the highest performance followed by LR, with f1-macro (log-loss) scores of 0.82 (0.09) and 0.46 (0.20) for the 1- and 12-hour cases, respectively. The ranking was highly variable for the remaining ML techniques. According to the g-mean, LR models correctly forecast and show more stability at all states, while the MLP models perform better in the Pre-alert and Alert states. Future efforts are recommended to enhance the input data representation and develop communication applications to boost the awareness of the society for floods.

Several studies have suggested that pre and/or postdiagnosis physical activity can reduce the risk of recurrence in breast cancer patients, however its effect according to follow-up time has not yet been investigated. We analyzed recurrence and mortality dynamics in randomized clinical trials (RCTs) from Australia and Canada. The combined Australian RCTs evaluated, at median follow-up of 8.3 years, an 8-month pragmatic exercise intervention in 337 women with newly diagnosed breast cancer, while the Canadian RCT evaluated, at median follow-up of 7.4 years, supervised aerobic or resistance exercise during chemotherapy in 242 patients. For each RCT, the control arm consisted of patients undergoing usual care. We estimated the event dynamics by the discrete hazard function, through flexible regression of yearly conditional event probabilities with generalized additive models. In the considered RCTs, the recurrence and mortality risk of patients enrolled in the physical activity arm was stably reduced at medium/long term after five year of follow-up. In the Australian RCTs where patients were recruited by urban versus rural area, the latter group did not display benefit from physical activity. Estimated Odds Ratios (95% Confidence Intervals) for Disease Free Survival (DFS) in urban women were 0.63 (0.22-1.85); 0.27 (0.079-0.90); 0.11 (0.013-0.96) at the 3rd, 5th and 7th year of follow-up, respectively. For rural women, DFS patterns were overlapping with ORs approximating 1 at the different years of follow-up. Although not reaching statistical evidence, the estimates in the Canadian trial were in line with the results from the Australian urban women with ORs (95% CI) forDFS of 0.70 (0.33-1.50); 0.47 (0.19-1.18); 0.32 (0.077-1.29) at 3rd, 5th, 7th follow-up year, respectively. While we acknowledge that the analyzed RCTs were not designed for investigating disease recurrence over time, these results support the evidence that physical activity reduces the risk of developing medium/long-term metastases. Additional translational research is needed to clarify the mechanisms underlying these observations.

Background: Early-stage interventions in a potential pandemic are important tounderstand as they can make the difference between runaway exponential growththat is hard to turn back and stopping the spread before it gets that far. COVID-19 is an interesting case study because there have been very different outcomesin different localities. These variations are best studied after the fact if precisionis the goal; while a pandemic is still unfolding less precise analysis is of value inattempting to guide localities in the early stages to learn lessons of those that pre-ceded them. Methods: I examine three factors that could differentiate strategy: asymptomaticspread, differences in use of the Bacillus Calmette-Guerin (BCG) tuberculosis vac-cine and cloth face masks.Results:Differences in disease progression as well as the possibility of alternativestrategies to prevent COVID-19 from entering the runaway phase or damping itdown later can be elucidated by a study of asymptomatic infection. A study todemonstrate not only what fraction are asymptomatic but how contagious they arewill also inform policy on universal mask wearing. Conclusions: While a COVID-19 outbreak is at a level that makes accurate trace-and test possible, investigation of asymptomatic transmission is viable and shouldbe attempted to enhance understanding of spread and variability in the disease aswell as policy options for slowing the spread.

With reference to Planck scale Hubble parameter, super luminal expansion speeds, super luminal rotation speeds, Mach’s principle and Holographic principle, we review the current cosmological observations with eight simple assumptions. By understanding Yuri N. Obukhov and V.A. Korotky proposed cosmic rotational effects of polarization of radiation due to massive bodies, to some extent cosmic rotation can be deep-rooted in an observational approach and the ratio of current angular velocity and Hubble parameter can be estimated. It is possible to show that, at H₀ =70 km/sec/Mpc, current cosmic temperature, age, radius, mass, mass density are 2.721 K, 4.41x10¹⁷ sec, 90 billion light years, 1.14654x10⁵⁴ kg, 0.0482 times the current critical density respectively. Clearly speaking, current universe seems to constitute 267 Hubble spheres. Important point to be noted is that, current rotational kinetic energy is 0.6667 times the current critical energy. Based on the estimated current mass density and current rotational kinetic energy, current cosmic dark matter density can be shown to be 0.2851 times the current critical density. These numerical coincidences cast serious doubt on the on the real existence of currently believed ‘dark energy’. Initial and current expansion speeds are 3x10⁸ m/sec and 3.56x10⁹ m/sec respectively. With increasing cosmic age and increasing cosmic expansion speed, current universe is expanding with a speed of 11.885c. By knowing the time to time future cosmic temperatures, future Hubble parameters and corresponding future cosmic expansion speeds can be estimated and thus future expansion speed can be understood. Starting from ‘speed of light’, our model assumes a continuous increase in expansion speed and attains a current radius of 90 billion light years (without inflationary concepts) and casts a serious doubt on the actuality of currently believed ‘inflation’.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Imaging of the ocular vasculature can provide new insights into the pathophysiology of ocular diseases. This study proposes a novel high-frequency super-resolution ultrasound localization microscopy (SRULM) technique and evaluates its ability to measure in vivo perfusion changes in the rat eye at elevated intraocular pressure (IOP). A 38.4 MHz center frequency linear array transducer on a VisualSonics Vevo F2 imaging platform was used to collect high frame rate (1 kHz) radiofrequency data of the posterior rat eye following systemic microbubble contrast injection. Following clutter and spatiotemporal non-local means filtering, individual microbubbles were localized and tracked. The microbubble tracks were accumulated over 10,000 frames to generate vascular images quantifying perfusion velocity and direction. Experiments were performed using physiologic relevant controlled flow states for algorithm validation and subsequently performed in vivo on the rat eye at 10 mm Hg IOP increments from 10 to 60 mm Hg. The posterior vasculature of the rat eye, including the ophthalmic artery, long posterior ciliary arteries and their branches, central retinal artery and retinal arterioles and venules were successfully visualized, and velocities quantified at each IOP level. Significant reductions in arterial flow were measured as IOP was elevated. High-frequency SRULM can be used to visualize and quantify perfusion velocity of the rat eye in both the retrobulbar and intraocular vasculature simultaneously. The ability to detect ocular perfusion changes throughout the depth of the eye may help elucidate the role ischemia has in the pathophysiology of ocular diseases such as glaucoma.

This paper demonstrates an on-off keying (OOK) super-regenerative quenching transmitter operating in 402- 405MHz MICs band applications. To reduce power consumption, the transmitter is controlled by a novel digital quenching signal controller that generates a digital control signal to start transmitter operation when a baseband signal is input to the transmitter. The digital signal controller consists of an envelope detector, a comparator, and a quench timer designed using a state machine to synchronize the operation between the digital controller and the input baseband signal. The transmitter consists of a Colpitts oscillator operating in double operating frequency followed by a frequency divider by 2, this configuration reduces system area and improves phase noise and signal spectrum. The proposed transmitter is implemented using UMC 130nm CMOS technology, and a 1.2V supply. Simulation shows that the proposed transmitter can meet MICS band mask specifications with data rates up to 1Mbps and total power dissipation of 537uW.

The dynamic effects observed in collisions represent a specific area of high-energy interaction located at the boundary of mechanics, hydrodynamics, shock wave physics, and alternating high-pressure regions. The paper shows that in the volume of a solid metal body, as a result of dynamic alloying by a high-speed stream of powder particles in the super-deep penetration mode (SDP), fibre structures of altering material arise, forming the framework of the composite material. The stream of powder particles in the metal obstacle following the path of least resistance and the impact of shock waves on particles results in a volumetric framework from the products of interaction between the injected and matrix materials. When using SDP, defective structural elements (channelled) - germs of reinforcing fibres arise. At the subsequent heat treatment, there is an intensive diffusion. The growth process of reinforcing fibres shifts to higher temperatures (as compared to the standard mode), leading to an increase in the bending strength of the fibre material up to 13 times for high-speed tool W6Mo5Cr4V2 steel. As a result of the completion of the growth of reinforcing fibres in the volume of the W6Mo5Cr4V2 steel, the material's bending strength in 1.2 times is realised. Simultaneously, it provides an increase of wear resistance 1.7-1.8 times.

Corona viruses cause extensive SARS epidemics via super spread events (SSE). Due to variation in infection risk and heterogeneity of reproduction numbers specific distinction between SSE’s and typical case events is essential. SARS transmissions unveil a complex scenario in which SSE’s are shaped by multiple factors. Specific screening strategies for infection emergence within potential super spreading groups will help to efficiently control the SARS-2 pandemic and alleviate the partially effective general restriction measures.

We derive time evolution equations, namely the Schrodinger-like equations and the Klein-Gordon equations for coherent fields and the Kadanoff-Baym (KB) equations for quantum fluctuations, in Quantum Electrodynamics (QED) with electric dipoles in 2 + 1 dimensions. Next we introduce a kinetic entropy current based on the KB equations in the 1st order of the gradient expansion. We show the H-theorem for the Leading-Order self-energy in the coupling expansion (the Hartree-Fock approximation). We show a conserved energy in the spatially homogeneous systems in the time evolution. We derive aspects of the super-radiance and the equilibration in our single Lagrangian. Our analysis can be applied to Quantum Brain Dynamics, that is QED with water electric dipoles. The total energy consumption to maintain super-radiant states in microtubules seems to be within the energy consumption to maintain the ordered systems in a brain.

Different severe energy crises episodes occurred in the world in the last five decades. Energy crises lead to deterioration of international relations, economic crises, changes in monetary systems and social problems in countries. This paper aims to show the essential determinants of energy crises by developing a binary logit model which estimates the predictive ability of thirteen indicators in a sample that covers the period from January 1973 to December 2022. The empirical results show that the energy crises are mainly due to energy supply-demand imbalances (petroleum stocks, fossil energy production-consumption imbalance and changes in energy imports by country groups), energy investments (oil and natural gas drilling activities), economic and financial disruptions (inflation, dollar index, index of global real economic activity) and geopolitical risks. Additionally, the model is capable of accurately predicting the world energy crisis event months with 99% probability.

Food allergy (FA) affects approximately 6–8% of children worldwide causing a significant impact on the quality of life of children and their families. In the years, the possible role of weaning in the development of FA has been studied. According to recent studies, the role of weaning in its development is still controversial and influenced by several factors, such as the type of food, the age at food introduction and family history. In this narrative review, we aimed to collected the most recent evidence about weaning and its role in FA development, organizing the gathered data based on both the type of study and the food.

At the beginning of 2023 the Italian former prime minister, the former health minister and 17 others including the current president of Lombardy region, were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government’s response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse pandemic data of Italy and Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers.

Aim: This analytical cross-sectional study aimed to examine whether there is a correlation between tumor differentiation and certain biomarkers in patients with hepatocellular carcinoma (HCC). Methods: Poorly differentiated (n=443), moderately differentiated (n=379), and well-differentiated (n=272) tumors were separated from the research population, along with a control group (n=364). Biopsies were used to establish the presence of HCC, and biomarker levels were analyzed using chemiluminescence immunoassays in both infected and uninfected individuals. Results: The correlation between age and tumor size was shown to be statistically significant (p0.05) across all subgroups using both descriptive and inferential statistics. Patients with hepatitis C virus and non-A, non-B hepatitis had more advanced tumors than those with other types of poorly differentiated liver cancer. Similarly, individuals with HBsAg and moderate differentiation had bigger tumors, although there was no correlation between hepatitis C and non-A, non-B. Patients with HBsAg or hepatitis C had bigger tumors in the well-differentiated group, albeit the hepatitis C connection was not statistically significant. In addition, the study stressed that tumor size increases with age and that farmers were the most commonly diagnosed profession category. Conclusions: It is clear that early detection in infected populations is crucial for improving HCC outcomes and that chemiluminescence immunoassay has the potential to be a helpful platform for biomarker research. However, the study is limited by its small sample size and its emphasis on only three tumor markers, indicating that more biomarker research is required to improve the accuracy of HCC diagnosis and prognosis.

The concept and policies of multiple early cancer detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control researches or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumor, and addressing cancer-related information such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarkers detection, MCED AIs training/validation, and the clinical application. The review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

The first 1000 days of life is a critical period that contributes significantly to the programming of an individual's future health. Among the many changes that occur during this period, there is growing evidence that the establishment of a healthy gut microbiota early in life plays an important role in the prevention of both short- and long-term health problems. Numerous publications suggest that the quality of gut microbiota colonization depends on several dietary factors, including breastfeeding. In this respect, a relationship between breastfeeding and the risk of inflammatory bowel disease (IBD) has been suggested. IBD are chronic intestinal diseases in which perinatal factors may be partly responsible for its onset. We propose to review the existence of links between breastfeeding and IBD, based on experimental and clinical studies. Overall, despite encouraging experimental data in rodents, the association between breastfeeding and the development of IBD remains controversial in humans, partly due to considerable heterogeneity between clinical studies. The duration of exclusive breastfeeding is probably decisive for its lasting effect on IBD. Thus, specific improvements in our knowledge could support dietary interventions targeting the gut microbiome, such as the early use of prebiotics, probiotics or postbiotics in order to prevent the disease.

Canistel (Pouteria campechiana (Kunth) Baehni) (yellow sapote, canistel). Originally from Mexico, the fruit is edible, and the tree is used as an ornamental and medicinal plant. Descriptive studies were carried out with the objective of morphologically characterizing the fruits and leaves of trees located in different regions of Mexico to select outstanding specimens and propose their massive reproduction. The trees were selected in three zones. In zone 2 from flower anthesis to harvest 11 months, fruits with 3 seeds, greater weight (180 to 330 g) and quantity of pulp (198.88 g), subglobose shape, total soluble solids 33 %. The fruits of zone 1 at harvest 8 months and zone 3 took 9 months to be harvested, in the rest of the characteristics evaluated were exceeded by the fruits of zone 2. To characterize the canistel (P. campechiana) leaf and identify accessions or cultivars, the three main variables, according to the principal component analysis were: leaf area, perimeter, and minor diameter. The three zones where canistel fruits and leaves were characterized are important and can be recommended for propagation in zones with favorable climatic conditions for fruiting in tropical and subtropical regions of Mexico.

(1) Background: Endoscopic submucosal dissection (ESD) has been widely accepted as the standard method for treating early-stage cancer or precancerous lesions in the upper gastrointestinal tract, however it may be difficult in patients with liver cirrhosis due to coagulation dysfunction or presence of gastroesophageal varices. We aimed to demonstrate the safety and efficacy of ESD in these population. (2) Methods: We retrospectively collected the clinical data and analyzed. Patients inclusion criteria: 1) patients with liver cirrhosis; 2) patients who underwent ESD; 3) patients diagnosed of early-stage cancer or precancerous lesions in the upper gastrointestinal tract. (3) Results: Eight patients were enrolled from April 2019 to April 2023, of whom 3 were male and 5 female, with age ranging from 43 to 70 years old. Seven lesions were located in the stomach, and the other one lesion in the esophagus. ESD was performed successfully in all patients, and the resected lesion size ranged from 2 to 6 cm. Only one patient encountered postoperative complication, chest pain and fever. No recurrence of noticed during a follow-up of 6 to 36 months. (4) Conclusions: ESD is safe and effective for treating upper gastrointestinal early-stage cancer or precancerous lesions in patients with liver cirrhosis.

Aim: To improve risk stratification in early-stage endometrial cancer (EC), we performed mo-lecular classification, and L1CAM immunohistochemistry (IHC) for additional risk assessment. Method: We analyzed archival tumor tissue from 247 early-stage EC patients. POLE mutations were detected using a Droplet digital polymerase chain reaction assay and Sanger sequencing, while the mismatch repair (MMR) status was determined by MMR protein IHC and MSI test. Additionally, we conducted IHC of p53 and L1CAM. Results: The 247 ECs were categorized into four subgroups: POLE-mutated (13.0%), MMR-deficient (27.9%), p53-abnormal (8.5%), and non-specific molecular profile (NSMP, 50.6%). We further subcategorized NSMP subgroup into NSMP-L1CAMneg (44.9%) and NSMP-L1CAMpos (5.7%), which we refer to as the molecu-lar-L1CAM classification. The molecular-L1CAM classification was an independent prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (p <0.001, each). Similarly, the simplified L1CAM-p53 categorization, for practical use, remained an independent prognostic factor for RFS and OS (p <0.001, p =0.003, respectively). Conclusion: Integrating the molecu-lar-L1CAM classification or the simplified L1CAM/p53 categorization can enhance risk stratifi-cation in early-stage EC, providing valuable prognostic information to guide treatment deci-sions and improve patient outcomes.

BACKGROUND: The National Lung Screening Trial (ILST) and the NELSON study showed that lung cancer-specific mortality can be reduced by 20-24% using low-dose computed tomography (LDCT) screening in high-risk populations, due to an increase in early-stage diagnoses. RESEARCH QUESTION: How much lung cancer-related direct costs may be reduced using a LDCT screening programme based on the ILST protocol in a public healthcare system?STUDY DESIGN AND METHODS: Cost analysis of lung cancer screening (LCS) vs. usual care in the framework of the retail price of the Catalan public healthcare system. The LCS group included costs of screening (ILST protocol), treatment cost according to weighted average distribution of TNM staging in the NLST and NELSON trials, lung cancer detection rate (CDR) and smoking cessation intervention. The usual care group included treatment costs based on distribution of TNM staging registered in the Spanish index hospital. RESULTS: In the usual care group, treatment costs were €91,959. In the 5-year duration of the LCS programme, the average expected costs per subject were €1,342 (range €1,054-1,832 depending on malignancy in detected nodules) for screening and €32,431 for treatment, with an expected reduction of €952 based on an average CDR of 1.6%. The decrease in cost resulting from stage shift offsets 70.6% of the costs of the screening programme. INTERPRETATION: Baseline 5-year LCS costs are low according to the ILST protocol. In the Catalan public healthcare system, the expense reduction from the stage shift due to the LCS programme compensates a substantial part of its costs.

Breast cancer prevention is very important for a woman's health worldwide. We have demonstrated a correlation between mammography and ultrasound with diagnoses using passive microwave radiometry (MWR) and a miRNA oncopanel. While mammography screening dynamics could be completed in 3-6 months, MWR will provide us with a prediction in a matter of weeks or even days with the potential for complementary miRNA diagnostics. An early breast cancer diagnosis may be accomplished using either one of these novel techniques alone or in conjunction with more established techniques

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions could change across the health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 heat wave definitions associated with HRI emergency department visits over five summer seasons (2011-2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the heat wave definitions to identify an optimal heat wave definition. In the Coastal region, heat wave definition based on daily maximum temperature with a threshold >90^th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, heat wave definition based on the daily minimum temperature with a threshold value >90^th percentile for two or more consecutive days was optimal. Additionally, we observed that the optimal heat wave definitions from this study captured moderate and frequent heat episodes than the national weather service (NWS) heat products that worked best for extreme heat episodes. This study compared the HRI morbidity risk associated with epidemiologic-based heat wave definitions and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Exploring the contribution of proximal family risk factors on SLC6A4 DNA methylation in children with a history of maltreatment

The estimation of the Hubble constant in the past few decades has increasingly become more accurate with the advance of new techniques. But its value seems to depend on the epoch at which the measurements are made. The Planck estimate of the Hubble constant from the observations of the CMBR in the early Universe is about 67.

Introduction: People with schizophrenia have poor cardiometabolic health, with elevated 10-year cardiovascular disease risk (CVD-R) scores and poor quality of life (QOL). There is lack of understanding of these issues in early psychosis. Aims: To quantify CVD-R in people with early psychosis and profile their obesity prevalence, lifestyle behaviours and QOL. Secondary aim was to explore associations between lifestyle behaviours/treatment characteristics and CVD-R/QOL. Method:Baseline data from 81 RCT participants were used to profile cardiometabolic health risks (QRISK®3, BMI and waist circumference). Participants self-reported lifestyle behaviours and QOL. Relationships between modifiable treatment/lifestyle factors and QOL/CVD-R were explored using bivariate analyses. Results: Participants’ relative risk for CVD over 10 years was 1.93 times higher than healthy counterparts; 39% also had an obese BMI and physical QOL was poor. No significant associations were observed between CVD-R or QOL with treatment characteristics and lifestyle factors. Discussion: Despite positive lifestyle behaviours, participants had elevated CVD-R scores and poor physical health related QOL. Quantifying CVD-R with QRISK®3 may highlight the need for health promotion interventions. Implications for practice: Mental health professionals should be alert to elevated cardiometabolic health risks in early psychosis, particularly as these can occur in the context of relatively healthy lifestyle behaviours.

Digital Educational Recourses (DER) have undergone a rapid evolution and integration into the educational contexts. Teachers play a fundamental role in incorporating technology into their classrooms, so it is important to identify the value that teachers on DER and reflect on the implications for their practice. Through the qualitative methodology the necessary data is obtained with open-response inter-views with teachers. This dataset was analysed and categorised using AQUAD. The results suggest that teachers acknowledge the importance of integrating digital re-sources into their classrooms, although there was no consensus regarding the appropriate level at which to do so. Further the inter-views revealed that younger teachers tend to use more self-elaborated or selected resources. Teachers noted the benefits of using technology, especially in regard to maintaining student motivation, how-ever they also highlighted a number of extrinsic challenges and limitations. The results indicate there is a relationship between teachers’ perceptions and their practice, although this could be improved.

Increasing evidence suggests that prenatal exposure to opioids can adversely influence brain development, yet, limited data exists on the effects of opioid-exposure on preschool language development. Our study aimed to characterize the nature and prevalence of language problems in children prenatally exposed to opioids, and the factors that support or hinder language acquisition. A sample of 100 children born to pregnant women in methadone maintenance treatment and 110 randomly identified non-exposed children were studied from birth to age 4.5 years. At 4.5 years, 89 opioid-exposed and 103 non-exposed children completed the preschool version of the Clinical Evaluation of Language Fundamentals (CELF-P) as part of a comprehensive neurodevelopmental assessment. Children prenatally exposed to opioid had poorer receptive and expressive language outcomes at age 4.5 years compared to non-exposed children. After adjustment for child sex, maternal education, other pregnancy substance use, maternal pregnancy nutrition and prenatal depression, opioid exposure remained a significant independent predictor of children’s total CELF-P language score. Examination of a range of potential intervening factors showed that a composite measure of the quality of parenting and home environment at 18 months and early childhood education participation at 4.5 years were important positive mediators.

Climate information can help vulnerable populations anticipate disasters before they happen and enable communities prepare for and cope with them. A complementary log-log regression model based on quantitative study in coastal communities in Tanzania was used to assess the likelihood of the rural poor, rural non poor, urban poor, and urban non poor to receive early warning information about flood, drought and other disasters. Individuals in the urban poor category were 35% less likely to receive early warning information about flood, drought and other disasters whereas urban non-poor residents were 49% more likely to receive same. This disadvantage to the urban poor persists even when adaptive capacity, geographical location and socio-environmental factors are accounted. Nuclear households consisting of a male head and female partner who have children or not had higher likelihood of receiving early warning information on flood, drought and other disasters (OR = 1.47, p < 0.001) compared with their counterparts in female-centred households (no husband or male partner). Residents with tertiary education were more likely (OR = 1.91, p < 0.001) to report that they had received early warning information about flood, drought and other disasters compared with their counterparts without any formal education. This zero-order relationship was completed mediated by geographical location and socio-environmental factors in the multivariate model. The results underline the key role access to climate- and disaster-related information play in enhancing adaptive capacity to reduce vulnerability to natural hazards, as well as the importance of targeting the most vulnerable households in policy interventions to improve resilience in the face of a changing climate.

The aim of this article is to analyze the evidence against the effectiveness of intervention programs based on the participation of parents of children with autism. To obtain the data, a systematic search was carried out in four databases (ProQuest-PsychArticles, ProQuest-ERIC, ProQuest-PubMed, and Scopus). These documents were refined under the inclusion/exclusion criteria and a total of 51 empirical studies were selected. They were classified, first, according to the function of the intervention objective and, later, by the methodology applied (19 studies based on comprehensive interventions, 11 focused on the nuclear symptoms of ASD, 12 focused on the promotion of positive parenting and 9 interactions focused on children play). Once all the documents have been analyzed, the evidence indicates scientific efficacy in most studies, mainly in those based on child development and the application of behavioral analysis principles. Also, the positive influence of parent participation in such programs was demonstrated.

In the case that ship operators may not be aware of the potential risks of environmental factors in situation of high causation probability during the initial stage of the geometric probability analysis process, it is likely that higher-grade collision accident measures will not be taken. However, if any risks is told to the ship operators, more effective and intentional measures can be taken in time. Moreover, if the causation probability corresponding to environmental factors is no less than the risk early warning critical value calculated based on historical collision accident data, there would be a high-risk level that a collision may occur. A new method is put forward based on quantitative analysis of environmental factors and previous collision statistics to provide early warning of any accident risk, and a risk early-warning critical value (REWCV) can be obtained based on this simple but highly operational and practical method. A case study of Three Gorges Reservoir in China indicates that the range of environmental factors where the probability of collision accident grows rapidly is consistent with environmental limits defined by Chinese maritime standards. In addition, the relationship between the risk early-warning critical value and the number of previous collision accident is also clarified.

Chronic myelogenous leukemia (CML) was the first malignancy for which clinical outcome was drastically improved by kinase inhibitor therapy. Kinase inhibitors targeting other well-known oncogenes have been introduced into clinical practice, but none have shown the same magnitude of clinical benefit as ABL1 inhibition in CML. We argue that early detection is an underappreciated, but critically important factor in success of ABL1 inhibitors in treatment of CML. We show that CML provides a window into how many types of cancer may look and behave at an early stage, prior to diagnosis and the development of additional genomic alterations. The remarkable clinical benefits of ABL1 inhibition is likely due to early detection of CML at a stage in which the tumor is driven by single oncogenic alteration which can be successfully controlled by the inhibitor. Thinking of CML as a prototype for effective systemic treatment based on early cancer detection may help to develop strategies for improving treatment for other types of cancer.

Malnutrition and dental caries in early childhood remain persistent and intertwined global health challenges, particularly for indigenous and geographically-remote populations. To examine the prevalence and associations between early childhood dental caries, parent-reported mouth pain and malnutrition in the Amazonian region of Ecuador, we conducted a cross-sectional study of the oral health and nutrition status of 1,407 children from birth through age 6 in the “Alli Kiru” program (2011-2013). We used multivariate regression analysis to examine relationships between severe caries, parent-reported mouth pain measures, and nutritional status. The prevalence of dental caries was 65.4%, with 44.7% of children having deep or severe caries, and 33.8% reporting mouth pain. The number of decayed, missing and filled teeth dmft) increased dramatically with age. Malnutrition was prevalent, with 35.9% of children stunted, 1.1% wasted, 7.4% underweight, and 6.8% overweight. As mouth pain increased in frequency, odds for severe caries increased. For each unit increase in mouth pain frequency interfering with sleeping, children had increased odds for underweight (AOR: 1.27; 95% CI: 1.02 – 1.54) and decreased odds for overweight (AOR: 0.76; 95% CI: 0.58 – 0.97). This relationship was most pronounced among 3-6 year-olds. Early childhood caries, mouth pain and malnutrition were prevalent in this sample of young children. Parent-reported mouth pain was associated with severe caries, and mouth pain interfering with sleeping was predictive of poor nutritional status. We demonstrate the utility of a parsimonious parent-reported measure of mouth pain to predict young children’s risk for severe early childhood caries and malnutrition, which has implications for community health interventions.

The assessment of welfare and disease progression in animal models is critical. Most tools rely on evaluating individual subjects, whereas social behaviors, also sensitive to acute illness, chronic diseases, or mental health, are scarcely monitored because of their complexity, are invasive, and time-consuming. We propose the evaluation of social nesting, a species-typical behavior naturally occurring in standard housing conditions, for such behavioral monitoring. We provide an example of its use to evaluate social deficits and the long-term effects of neonatal sensorial stimulation in male and female adult 3xTg-AD mice for Alzheimer's disease compared to sex- and age-matched NTg counterparts with normal aging. Social nesting was sensitive to genotype (worse in 3xTg-AD mice), sex (worse in males), profile, and treatment (distinct temporal patterns, time to observe the maximum score and incidence of the perfect nest). Since social nesting can be easily included in housing routines, this neuroethological approach can be useful for animal's welfare, monitoring the disease's progress, and evaluating potential risk factors and effects of preventive/therapeutical strategies. Finally, the non-invasive, painless, simple, short time and low-cost features of this home-cage monitoring are advantages that make social nesting feasible to be successfully implemented in most animal department settings.

In Kenya, millions of children have limited access to nurturing care. With the COVID-19 pandemic, it is anticipated that vulnerable children will bear the biggest brunt of the direct and indirect impacts of the pandemic. This review aimed to deepen understanding of the effects of COVID-19 on nurturing care from conception to four years of age, a period where the care of children is often delivered through caregivers or other informal platforms. The review has drawn upon the empirical evidence from previous pandemics and epidemics, and anecdotal and emerging evidence from the ongoing COVID-19 crisis. Multifactorial impacts fall into five key domains: direct health; health and nutrition systems, economic, social and child protection, and child development and early learning. The review proposes program and policy strategies to guide the re-orientation of nurturing care, prevent the detrimental effects associated with deteriorating nurturing care environments, and support the optimal development of the youngest and most vulnerable children. These include the provision of cash transfers and essential supplies for vulnerable households, and strengthening of community-based platforms for nurturing care. Further research on COVID-19 and the ability of children’s ecology to provide nurturing care is needed, as is further testing of new ideas.

We will apply Pascal’s hydrostatic pressure law to black holes and also to the Hubble sphere. Haug has recently demonstrated how hydrostatic pressure in water can be utilized to determine the Planck length. One can conceptualize the energy in the Hubble sphere as a type of superfluid, and if this is correct, then Blaise Pascal’s hydrostatic pressure formula may also be applicable to such a superfluid, even within the Hubble sphere. By employing the same method on the Hubble sphere and considering it as a Schwarzschild black hole with the critical Friedmann mass, we can estimate the Planck length based on its hypothetical hydrostatic pressure.

Multiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real- time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

A super-porous hybrid platform can offer significantly increased number of reaction sites for the analytes and thus can offer advantages in the biosensor applications. In this work, a significantly improved sensitivity and selectivity of hydrogen peroxide (H2O2) cancer sensor is demonstrated by a super-porous hybrid CuO/Pt NP platform. The super-porous hybrid platform is fabricated by a physiochemical approach combining the physical vapor deposition of Pt NPs and electrochemical deposition of super-porous CuO structures by adopting a dynamic hydrogen bubble technique. Under an optimized condition, the hybrid CuO/Pt biosensor demonstrates a very high sensitivity of 2,205 µA/mM∙cm2 and a low limit of detection (LOD) of 140 nM with a wide range of H2O2 detection. This is meaningfully improved performance as compared to the CuO-based H2O2 sensors as well as to the previously reported metal oxide based H2O2 sensors. The hybrid CuO/Pt platform exhibits excellent selectivity against other interfering molecules such as glucose, fructose, dopamine, and ascorbic acid. Due to the synergetic effect of highly porous CuO structures and underlying Pt NPs, the CuO/Pt architecture offers extremely abundant active sites for the H2O2 reduction and electron transfer pathways.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

Exploiting the existing optical fiber network’s terrestrial infrastructure offers unexpected solutions to global challenges. We aim to expand the current network by incorporating a streaming telemetry system to integrate earthquake early detection. The purpose is to analyze and interpret alteration of light’s polarization induced by seismic events, particularly Primary earthquake waves that precede destructive Surface waves. This analysis facilitates the development of an early warning system and implementation of earthquakes countermeasures to mitigate humanitarian and economic impact. Consequently, we have developed a Python-based Waveplate Model designed to monitor light’s polarization changes within optical fibers buried underground. The model incorporates real ground displacement data from a 4.9 magnitude earthquake that struck in Marradi region, central Italy. We propose a novel approach of a smart sensing grid of optical network empowered by machine learning, trained on a large number of polarization evolution extracted from two distinct sensing fibers to identify the pattern of polarization change occurring during Marradi earthquake. Test Results demonstrate that this method can detect Primary waves within one second time-frame, achieving an accuracy rate of 99.5%. This system therefore affords nearby regions 52 seconds to take emergency response, and an extended margin of 62 seconds in more distant areas.

Triclopyr is an auxin-like herbicide extensively employed to manage weeds in food crops and pastures. Triclopyr has been detected in environmental matrices, with a notable presence within aquatic ecosystems. Given the limited understanding of its fate in the environment, potential implications for environmental and human health, and the lack of adequate monitoring in various environmental compartments, triclopyr is now considered a contaminant of emerging concern (CEC). The present study was undertaken to investigate the impact of triclopyr on zebrafish development, with a specific focus on assessing its embryotoxic, behavioral, and neurotoxic effects at environmentally realistic concentrations ranging from 0.5 to 50 µM on zebrafish embryos. Our results revealed that triclopyr caused sublethal effects on zebrafish embryos, such as delayed hatchability at 50 µM, yolk sac retention at 0.5, 1, 5, and 10 µM, and uninflated swim bladder at 50 µM concentration of triclopyr. Moreover, a subtle alteration in the swimming activity of larvae was observed in the 10 µM triclopyr after 144 hours of exposure. However, the activity of acetylcholinesterase, remained unchanged after triclopyr exposure. Taken together, these comprehensive findings suggest that triclopyr can induce adverse effects on the early development of zebrafish, even at concentrations detected in aquatic environments.

IIt is important that Master’s Degree students in psychology, regardless of their future specialisa-tion, know about Attention Deficit Hyperactivity Disorder (ADHD). The aim is evaluate and an-alyse the ADHD-related knowledge held by students of Early Childhood Education and Primary Education. The findings that were obtained in this study (on the chronicity of the disorder, changes in manifestations throughout the life cycle, and the importance of early and multidisci-plinary intervention) have clear implications in relation to the specific training in ADHD for fu-ture teachers. It is essential to broaden the specific training in relation to ADHD in studies for the Master’s Degrees in Early Childhood Education and Primary Education and through contin-uous training.

It is essential to consider the factors that affect early childhood development because doing so can help identify potential risks and window of opportunity for intervention to improve outcomes for children. However, identifying risk and protective factors in early childhood requires careful consideration of several challenges and an integrated approach that recognises the complex and dynamic nature of development. The purpose of this study was to identify and describe the prevalent psychosocial risk and protective factors in the early childhood development phase, using an ecological perspective. The study employed a quantitative cross-sectional study using a random sampling technique. The final sample consisted of 505 caregivers of children aged 5 years old and younger. This study revealed that the most prevalent protective factors include child self-regulation, parent-child warmth, family management and collective efficacy but more importantly social support. While risk factors may exist this is mitigated by social support as it moderates and buffers against the effects of risk factors, as indicated by the various research studies cited.

Malaria remains a primary public health challenge in Africa, and there is growing interest in leveraging artificial intelligence (AI) to raise malaria interventions. This research examines the possible influence, challenges, and recommendations for implementing AI-based personalized malaria interventions in Africa. AI offers several opportunities in malaria management, including early detection and prediction of outbreaks, improved diagnosis, personalized interventions, optimal treatment recommendations, surveillance and response, resource optimization, and research innovation. However, the implementation of AI in malaria interventions faces various challenges. These include data availability and quality, infrastructure and resource constraints, contextual relevance and generalizability, ethical and privacy considerations, integration into healthcare workflows, and the need to build trust and acceptance among stakeholders. To address these challenges, it is recommended to strengthen data infrastructure, build local capacity in AI technologies, contextualize AI models to local settings, address ethical considerations, establish monitoring and evaluation frameworks, promote collaboration and knowledge sharing, and secure sustainable funding and long-term commitment. By considering these recommendations, stakeholders can work towards implementing AI-based personalized malaria interventions in Africa that can contribute to improving malaria control outcomes, reducing the weight of the disease, and advancing public health in the region.

During the last few years, several approaches have been proposed to improve early warning systems for reducing rock-fall risk. In this regard, this paper introduces a Deep learning-and (IoT) based Framework for Rock-fall Early Warning, devoted to reducing the rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused the prediction model-based deep learning with a detection model-based Internet of Things. In order to determine the framework’s performance, this study adopted parameters, namely overall prediction performance measures, based on a confusion matrix and the ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, a framework reduced the risk probability from (1.51 ×10-3) to (8.57 ×10-9). Our results indicate the framework’s high prediction accuracy; it also provides a robust decision-making process for delivering early warning and lowering the rock-fall risk probability.

Blood-based circulating cell free DNA(cfDNA) detection offers a non-invasive and easily accessible way for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to develop the clinical biomarkers. For example, cfDNA with genetic alterations often compose a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from health population will be important for the cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in small amount of cfDNA-based cancer test. We hypothesize that, the combination of diverse types of cancer studies on cfDNA can provide us a new insight to identify low-frequency genetic variant across cancer types for early clinical detection of cancers. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritize 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting to membrane, some of which are tumor suppressor, oncogene and related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as the common biomarkers in early cancer diagnosis.

Digital wellbeing concerns the balance and health we may experience in digital use, and the existing studies have focused on adolescents and adults. However, young children are more vulnerable to digital overuse and addiction than adults; thus, their digital wellbeing deserves empirical exploration. This scoping review synthesized and evaluated 35 collected studies on young children’s digital use and their wellbeing that were published until October of 2022 to understand the definitions, measurements, contributors, and interventions. The synthesis of evidence revealed that: (1) there was no consensus about its definition; (2) there were no effective measurements of young children’s digital wellbeing; (3) both child factors (duration and place of digital use, child demographic characteristics) and parent factors (digital use, parental perception, and mediation) contribute to young children’s wellbeing; and (4) there were some effective applications and interventions. This review contributes to the theoretical development by mapping the existing work on young children's digital wellbeing, proposing a model, and identifying the research gaps for future studies.

This study examined the relationship among the three domains of executive function (EF; cognitive shifting, inhibitory control, and working memory) to test the applicability of the unity-diversity model in preschoolers using both behavioral and fNIRS approaches. Altogether 58 Chinese preschoolers (34 boys, 24 girls, Mage = 5.86 years, SD = 0.53, Age range = 4.83-6.67 years) were administered the Dimensional Card Change Sort (DCCS), go/no-go, and missing scan task. Their brain activations in the prefrontal cortex during the tasks were examined using fNIRS. First, the behavioral results indicated that the missing scan task scores (working memory) correlated with the DCCS (cognitive shifting) and go/no-go tasks (inhibitory control). But the latter two did not correlate with each other. Second, the fNIRS results demonstrated that the prefrontal activations during the working memory task correlated with those in the same regions during the cognitive shifting and inhibitory control tasks. Still, the latter two did not correlate. The behavioral and neuroimaging evidence jointly indicates that the unity-diversity model of EF does apply to Chinese preschoolers.

Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires’ fast spread in the early stage. NOAA’s geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection. However, advanced processing algorithms are needed to provide timely and reliable detection of wildfires. In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series data. GRU model maintains good performance on temporal modelling while keep a simple architecture, makes it suitable to efficiently process time-series data. 36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The detection times based on GOES-R are compared with VIIRS active fire products at 375m resolution in NASA’s Fire Information for Resource Management System (FIRMS). The results show that GRU-based GOES-R detections of the wildfires are earlier than that of the VIIRS active fire products in most of the study areas. Also, results from proposed method offer more precise location on the active fire at early stage than GOES-R Active Fire Product in mid-latitude and low-latitude regions.

Groundwater degradation is a global problem linked to irrigation agriculture and aggravated by climate change. In drylands, where aquifer recharge is low, irrigation has emerged as an engine of economic growth. This problem falls under the paradigm of desertification, as it fits the definition of this complex problem in that the degradation of drylands is due to climatic variations and inappropriate human activities. Land Degradation Neutrality (LDN), the response of the United Nations Convention to Combat Desertification to the lack of progress in tackling desertification, is integrated into Sustainable Development Goal 15.3 and provides the adequate framework for implementing effective solutions. LDN prioritizes prevention strategies, and early warning systems coupled to integrated simulation models is a sound approach. We analyze the dynamics of a coastal aquifer in southern Spain, a “desertification landscape” according to the Spanish National Action Plan to Combat Desertification. For this purpose, we have (i) adapted a generic desertification model that considers socio-ecological systems as a particular case of predator-prey systems; and (ii) coupled to this model a risk analysis to calculate the probabilities of groundwater salinization under the current scenario of water resources use, driven by the expansion of greenhouse agriculture supported by external water transfer. The risk of desertification is close to 100%: groundwater salinity is 40 dS m-1 (well above tomato tolerance, 3.5 dS m-1), and 2.4 Mm3 yr–1 water transfer is needed to support the 631 ha of greenhouses. This worrying result suggests that complimentary solutions should be promoted to deactivate the ongoing process of desertification. Among them, we propose reclaimed water, diversifying the economy, or promoting crops adapted to aridity. This simulation framework shows how to explore the future of a socio-ecosystem under current scenarios and others that consider climate change, the energy crisis, or the impact of alternative solutions.

Crop-type mapping is an important intermediate step for cost-effective crop management at the field level, as an overview of all fields with a particular crop type can be used for monitoring or yield forecasting, for instance. Our study used a data set with 2400 fields and corresponding satellite observations from the federal state of Bavaria, Germany. The study classified corn, winter wheat, winter barley, sugar beet, potato, and winter rapeseed as the main crops grown in Upper Bavaria. We additionally experimented with a rejection class "Other", which summarised further crop types. Corresponding Sentinel-2 data included the normalised difference vegetation index (NDVI) and raw bands from 2016 to 2018 for each selected field. The influence of raw bands compared to NDVI was analysed and the classification algorithms, i.e. support vector machine (SVM) and random forest (RF), were compared. The study showed that the use of an index should be critically questioned and that raw bands provided a wider spectral bandwidth, which significantly improved the mapping of crop types. The results underline the use of RF with raw bands and achieved overall accuracies (OA) of up to 92%. We also predicted crop types in an unknown year with significantly different weather conditions and several months before the end of the growing season. Thus, the influence of climate anomalies and the accuracy depending on the time of prediction were assessed. The crop types of a test site and year without labels could be determined with an OA of up to 86%. The results demonstrate the usefulness of the proof-of-concept and its readiness for use in real applications.

The movement direction of propagating convective systems originating from both inland and offshore over the north coast of West Java in Indonesia is determined primarily by the prevailing wind. However, the role of a land-sea contrast and a rugged topography over southern West Java is also expected to affect propagating convective systems by increasing land-sea breezes and enhancing upward motion. These hypotheses are tested using a weather prediction model incorporating convection (up to 3 km height) to simulate the heavy rainfall event during 26–29 January associated with the 2002 Jakarta flood. First, we addressed the influence of land-sea contrast and topography on the local circulation, particularly in the area surrounding Jakarta, by replacing the inland topography over western Indonesia (96°–119°E, 17°S–0°) with a water body with an altitude of 0 m. We then compared the results of model simulations with and without topography. The results show that the main role of the topography here is enhancing the upward motion and generating a deep convective cloud in response to the land-based convective system during 26–27 January 2002, which then continuously and rapidly propagates offshore due to the cold pool mechanism. Furthermore, the land-sea contrast has a significant role in increasing sea breeze under the rapidness of the landward propagation system during 28–29 January 2002, which was strengthened by the gravity waves and resulted in early morning convection over coastal regions.

The evolutionary origin of the genome remains elusive. Here, I hypothesize that its first iteration, the protogenome, was a multi-ribozyme RNA. It evolved, likely within liposomes (the protocells) forming in dry-wet cycling environments, through the random fusion of ribozymes by a ligase and was amplified by a polymerase. The protogenome thereby linked, in one molecule, the information required to seed the protometabolism (a combination of RNA-based autocatalytic sets) in newly forming protocells. If this combination of autocatalytic sets was evolutionarily advantageous, the protogenome would have amplified in a population of multiplying protocells. It likely was a quasispecies with redundant information, e.g., multiple copies of one ribozyme. As such, new functionalities could evolve, including a genetic code. Once one or more components of the protometabolism were templated by the protogenome (e.g., when a ribozyme was replaced by a protein enzyme), and/or addiction modules evolved, the protometabolism became dependent on the protogenome. Along with increasing fidelity of the RNA polymerase, the protogenome could grow, e.g., by incorporating additional ribozyme domains. Finally, the protogenome could have evolved into a DNA genome with increased stability and storage capacity. I will provide suggestions for experiments to test some aspects of this hypothesis.

The effect of aqueous extracts of the biomass of the adult Ulomoides dermestoides beetle on the delayed effects of the defoliant paraquat causing parkinsonism in experimental mice was evaluated. The motor activity of the animals was analyzed in behavioral tests using a rotarod and a vertical pole. The number of tyrosine hydroxylase-immunopositive neurons in the ventral part of the substantia nigra of the midbrains of experimental and control mice was studied by immunohistochemistry. In the model in vitro system with SH-SY5Y human neuroblastoma, the effect of the extracts on cell proliferation was examined in the absence and presence of the neurotoxin MPP⁺. The isolation of biologically active substances from raw biomass using cavitation effects made it possible to obtain extracts with protective properties in the model of an early stage of Parkinson's disease used in this study.

Timely diagnosis of Alzheimer's diseases(AD) is crucial to obtain more practical treatments. In this paper, a novel approach Based on Multi-Level Fuzzy Neural Networks (MLFNN) for early detection of AD is proposed. The focus of study was on the problem of diagnosing AD and MCI patients from healthy people using MLFNN and selecting the best feature(s) and most compatible classification algorithm. In this way, we achieve an excellent performance using only a single feature i.e. MMSE score, by fitting the optimum algorithm to the best area using optimum possible feature(s) namely one feature for a real life problem. It can be said, the proposed method is a discovery that help patients and healthy people get rid of painful and time consuming experiments. Experiments shows the effectiveness of proposed method in current research for diagnosis of AD with one of the highest performance (accuracy rates of 96.6%), ever reported in the literature.

Recent analyses of cosmic microwave background (CMB) maps have been interpreted as demonstrating that the Universe was born without an initial rotation. However, these analyses are based on unrealistic models and do not contain essential ingredients such as quantum effects, the strong, weak and gravitational interactions between the components, their intrinsic spins and magnetic moments, as well as primordial black holes. If the Universe was born spinning these effects would distribute the initial spin angular momentum among its components long before the CMB forms at recombination. A primordial spin would now appear as a nonzero total angular momentum of its components along the direction of the original spin, and a primordial large-scale rotation would no longer be apparent. The existence of a special axis or direction would break a fundamental symmetry assumed in general relativity, cosmic isotropy, and a net angular momentum implies a cosmic parity violation.

This research paper is mainly aimed to elaborate the initial risk management and measures which government of Pakistan took towards Novel Corona Virus (COVID-2019). This initial response and planning was devised after the early outbreak of COVID-2019 in Wuhan, China in early time of January 2020. Pakistan devised a comprehensive plan that not to evacuate their student from Wuhan, China. The government of Pakistan in compliance with the National Institute of Health (NIH) devised and documented comprehensive plans such as the flight operations postponed related to Umerah pilgrims, which were intended to go to sacred places of KSA (The Kingdom of Saudi Arabia). The process of visa, immigration policy totally changed and the government of Pakistan notified it officially that, no new visas of visit, student, and business would be issued in due course of uncertainty due to COVID-2019. The government of Pakistan also announced medical emergency and notified through the country’s provinces the process of testing and treatment of COVID-2019. The government of Pakistan also allocated funds for medical supplies and named out the particular country’s best laboratories. The government of Pakistan also locked down all the cities with the emergency announcement that people should stay inside the home in quarantine or self-isolation. NIH (The National Institute of Health) played a vital role in executing the planning to cope with COVID – 2019). The National Institute of Health responded as “The Centre for Disease Control”. In aid to the government, the national army of Pakistan responded in a proactive manner towards planed execution. The medical corps of Pakistan army dedicated themselves to treat the suspected patients of COVID – 2019. Due to plans, policies being documented, implemented in such a way productive way that from February 28, 2020 to till date there is not much critical situation and issues are not present. There are much productive results as there is not much boom in a rise of COVID-2019 patients. This lockdown under the authority of the provinces resulted in fruitful outcomes. Background: On January 02, 2020, authorities of the People Republic of China elaborated that they have encountered with a novel type of infectious viral disease 2019. Later on January 12, the authorities from China elaborated the related sequence of Corona Virus diseases 2019 names as COVID – 2019. When COVID-2019 being identified in Wuhan, Hubei China, as an early response the Government of Pakistan in support of the National Institute of Health (Field Epidemiology & Disease Surveillance Division) published a health advisory about novel coronavirus. Methods: According to Global Health Security Index, Pakistan is ranked as 105th country among 195 countries in GHS index. Overall Score of Pakistan is 35.5. The score of Early Detection and Reporting for Epidemics of Potential International Concern is 41.7. A Graphical depiction of the COVID-19 cases placed until April 10, 2020 as well as a graph trend line of recovered as well as death rate is also depicted. According to the graphical facts of Government of Pakistan and World meters, the recovery rate of COVID-19 is about 98 percent and 2.1 percent death rate is reported against the total cases. Trend analysis with line graph was drawn based on available data from official dashboard web portal of the government of Pakistan and worldometers.info. Data figures were incorporated from March to August 18, 2020 in MS Excel and then subsequently deployed to draw trend analysis from managing risk to recovery. Results: The line graph showed a slowdown in the COVID-19 cases and high rate of recoveries from COVID-19 in Pakistan. On March 11, 2020, there were 20 confirmed cases of coronavirus reported in Pakistan. No death was recorded in very first seven days, on March 18, 2020 only two deaths were reported. On August 18, 2020, there were 272128 recoveries, 6201 deaths, total confirmed cases 290445, and total test were 2340072 in Pakistan. As a results, we can report that due to early measures taken by government of Pakistan no mass scale destruction in terms of death and cases been recorded in Pakistan. Conclusions: To till date, the government of Pakistan tried its level best to minimize the coronavirus cases as much as they can. However, the ending of the potential attack of an outbreak would depend upon the well organized and coordinated approach at all levels such as true directed decisions, fully preparedness, as well implementation and evaluation of continuous decisions. As the recovery rate of the cases is 98 percent and merely death rate is 2.1 percent, concluded that in future it would be a good sign to stop the potential outbreak. Also, lock down as well as precautionary measurement taken by the provincial governments resulted a decline number of COVID-19 cases in the country. Another good sign is that merely 4 percent population of Pakistan is of more than 60 years of old it can be concluded that there are less chances of mass death due to outbreak of COVID-19.

Young women with breast cancer represent 15% of cancer cases in Latin America. Genomic studies have found that early-onset breast-cancer cases exhibit a higher genetic susceptibility and a specific genomic signature as compared to their older counterparts. The aim of this study was to describe clinically relevant germline mutations in a cohort of young women with breast cancer. To achieve this, we analyzed hereditary-cancer genes from whole-exome sequencing data in 108 unrelated women with an extreme phenotype of breast cancer (≤40 years of age), diagnosed and treated at the National Cancer Institute of Mexico; 11% of the patients carried a pathogenic variant. BRCA2 comprised 46% of the mutations, followed by BRCA1 with 23%; PALB2 with 15%; and TP53 and RAD51C with 8 % each. This article describes a novel pathogenic mutation in RAD51C c.519dupT. The median age at diagnosis was 35 years overall; however, it was six years younger in patients with mutations. Age at diagnosis (OR=0.82, CI 95% 0.71-0.94; P= 0.008) and first-degree family history of cancer (OR=8.26, CI95% 1.35-50; P= 0.022) were the only epidemiological variables associated with mutational status. We found no differences in disease-free survival (p=0.403) or overall survival (p=0.735) among mutational status subgroups.

Changes in curricula, publication policy and information technology, notably in China have led to concentrations in the role of STEM (science, technology, engineering and mathematics) education in early childhood and applauded to proliferations of imported up-to-date reading materials and mobile apps in English. This paper proposes a longitude study of a Chinese toddler learning STEM by reading picture books and playing with tablet and suggests new horizons in parenting and in STEM education during children's early years. The present study carried out from 2016, when the participant reached one year old, eligible to learn to speak and to concentrate on the picture books read by parents who had filled a language background questionnaire with information on themselves and the participant. Tablet playing brought about for the two-year-old toddler and collections of STEM books in English was added for the second year. Data collection lasted for two years with an iLab video camera, capturing utterances and motions for five minutes per week transcribed by VoiceScript software. Tests were given quarterly at private home by tapping in mobile app "Bilingual Child Learning" which consists of 20 basic STEM themes before scores were collected. Findings indicate that (1) it is accessible for children of very early years to be engaged in English STEM resources, (2) kids' limited English dominance does not impede learning STEM, (3) and to think in English in early STEM contributes to children's English.

The purpose of interdisciplinary communication during the early architectural design stage is to achieve the early integration of knowledge in different professional fields, which can help architects to choose correct design development strategies during the early architectural design stage. However, because there is too little information at the early design stage, and design solutions are still rapidly changing and developing, the uncertainties at this stage make it difficult for consultants in other disciplines to provide their views and analysis. In spite of this situation, the emergence of generative modeling is changing design procedures and methods of communication and cooperation for architectural teams, and has brought about a shift in the way architects transmit design information from "what" (declarative information) to "how" (procedural information). Generative modeling is like an aircraft's dashboard: It can provide a basis for interdisciplinary communication, provide interdisciplinary knowledge packages, and bring about a shift in interdisciplinary communication that will reduce the architectural team's communication needs and cost. This study uses a real design case to show the feasibility of generative modeling. Employing generative modeling as a basis, architects can enhance the efficiency of design change and multi-disciplinary communication during the early design stage, integrate specialized knowledge in relevant fields, use this knowledge to formulate design criteria for the next stage, and effectively transmit design decisions. As a consequence, the changes to the cost structure of design revisions and communication between different disciplines has initiated a paradigm shift toward multi-disciplinary communication in architectural design.

To help reduce the impact of geohazards, an innovative landslide early-warning technology based on an energy demodulation-based fiber optic sensing (FOS-LW for short) technology, is introduced in this paper. FOS-LW measures the energy change in a sensing fiber at the segment of micro-bending, which can be caused by landslide movements, and automatically raises an alarm as soon as the measured signal intensity in the fiber reaches a pre-set threshold. Based on the sensing of micro-bending losses in the fiber optics, a two-event sensing algorithm has been developed for the landslide early-warning. The feasibility of the FOS-LW technology is verified through laboratory simulation and field tests. The result shows that FOS-LW has some unique features such as the graded alarm, real-time responses, remote monitoring, low cost and passive optical network, and can be applied in the early-warning of landslides.

In the recent concrete industry, high fluidity concrete is being widely used for the pouring of dense reinforced concrete. Normally, in the case of high fluidity concrete, it includes high binder contents, so it is necessary to replace part of the cement through admixtures such as fly ash to procure economic feasibility and durability. This study shows the mechanical properties and field applicability of high fluidity concrete that using mass of fly ash as alternative materials of cement. The high fluidity concrete mixed with 50% fly ash was measured to manufacture concrete that applies low water/binder ratio to measure the mechanical characteristics as compressive strength and elastic modulus. Also, in order to evaluate the field applicability, high fluidity concrete containing high volume fly ash was evaluated that fluidity, compressive strength, heat of hydration and drying shrinkage of concrete.

Accurate climate data at fine spatial resolution are essential for scientific research and the development and planning of crucial social systems, such as energy and agriculture. Among them, sea surface temperature plays a critical role as the associated El Niño-Southern Oscillation (ENSO) is considered a significant signal of global interannual climate system. In this paper, we propose an implicit neural representation-based interpolation method with temporal information (T_INRI) to reconstruct climate data of high spatial resolution, with sea surface temperature as the research object. Traditional deep learning models for generating high-resolution climate data are only applicable to fixed resolution enhancement scales. In contrast, the proposed T_INRI method is not limited to the enhancement scale provided during the training process and its results indicate that it can enhance low-resolution input by arbitrary scale. Additionally, we discuss the impact of temporal information on the generation of high-resolution climate data, specifically, which month the low-resolution sea surface temperature data is from. Our experimental results indicate that T_INRI is advantageous over traditional interpolation methods under different enhancement scales, and the temporal information can improve T_INRI performance for a different calendar month. We also examined the potential capability of T_INRI in recovering missing grid value. These results demonstrate that the proposed T_INRI is a promising method for generating high-resolution climate data and has significant implications for climate research and related applications.

Super duplex stainless steel (SDSS) is used for manufacturing large valves and pipes in offshore plants because of its excellent strength and corrosion resistance. Large valves and pipes are manufactured by forging after casting, and the outside and inside microstructures are different owing to the difference in the cooling rate caused by the thermal conductivity. This microstructural variation causes cracks during solution annealing, which breaks the materials. To study toe corrosion resistance of the SDSS forged material, the microstructure was conducted based on the difference in the cooling rate between the inside and outside of the cast SDSS. To analyze the effects of the secondary phase fraction before solution annealing on the solution and corrosion resistance, the corrosion resistance with and without solution annealing was measured using the potentiodynamic polarization test and critical temperature test after the precipitation of the secondary phase. In the potentiodynamic polarization test, the secondary phase decreased the activation polarization and increased the corrosion rate. The critical pitting temperature exhibited the effect of the secondary phase.

In our recently published papers, considering Planck mass based light speed growing black hole universe and scaled Hawking’s black hole temperature formula, we have developed a simple procedure for estimating the current Hubble parameter and current cosmic mass. In addition to that, without considering galactic dark matter, starting from 10 km/sec to 500 km/sec, we have tried to fit the observed galactic flat rotation speeds with a concept of super gravity of galactic baryonic mass. To estimate the equivalent mass of currently hypothecated galactic dark matter, we have introduced a timely increasing cosmological reference mass unit. Its current magnitude seems to be around 200 million solar masses. In this paper, considering 200 million solar masses as a characteristic representation of cosmic weak interaction mass unit, we have developed a simple formula for its estimation. We would like to appeal that, weak interaction boosts the gravity of galaxies in proportion with their virtual dark mass as (galactic baryonic mass)^3/2 / (200 million solar masses)^1/2. With further study- dark matter existence and physical properties can be understood in a theoretical approach.

Green innovation has become an important combination of high-quality economic growth and sustainable development of ecological environment. In this paper, the super-efficiency network SBM model is used to measure the two-stage green innovation efficiency of industrial science and technology R&amp;D and achievement transformation in 30 provinces and cities from 2009 to 2019, and exploratory Data Analysis (ESDA) and spatial econometric model are used to investigate the spatial-temporal evolution characteristics and influencing factors of green innovation efficiency. The results show that: firstly, the overall efficiency of industrial green innovation is low, and the efficiency of scientific research and development and achievement transformation has experienced three stages of "upward-declining-revitalized period". The low efficiency of achievement transformation is an important factor hiding the improvement of the efficiency of industrial green innovation. Secondly, The industrial green innovation efficiency gradually increases from northwest to southeast, forming a centralized "line" and "block" distribution. The high efficiency area is still concentrated in the eastern coastal region, and the balanced development trend is obvious in the central and western regions. Finally, openness has a positive impact on the two-stage green innovation efficiency; Industrial structure and government investment in science and technology have a positive impact on the efficiency of science and technology research and development, but have no significant effect on the efficiency of achievement transformation. Enterprise size has a positive effect on achievement transformation efficiency, but has no significant effect on R&amp;D efficiency. Environmental regulation has a positive impact on R&amp;D efficiency and a negative impact on achievement transformation efficiency.

The holy grail of Artificial Intelligence (AI) has been to mimic human intelligence using computing machines. Autopoiesis which refers to a system with well-defined identity and is capable of re-producing and maintaining itself and cognition which is the ability to process information, apply knowledge, and change the circumstance are associated with resilience and intelligence. While classical computer science (CCS) with symbolic and sub-symbolic computing has given us tools to decipher the mysteries of physical, chemical and biological systems in nature and allowed us to model, analyze various observations and use information to optimize our interactions with each other and with our environment, it falls short in reproducing even the basic behaviors of living organisms. We present the foundational shortcomings of CCS and discuss the science of infor-mation processing structures (SIPS) that allows us to fill the gaps. SIPS allows us to model su-per-symbolic computations and infuse autopoietic and cognitive behaviors into digital machines. They use common knowledge representation from the information gained using both symbolic and sub-symbolic computations in the form of system-wide knowledge networks consisting of knowledge nodes and information sharing channels with other knowledge nodes. The knowledge nodes wired together fire together to exhibit autopoietic and cognitive behaviors.

This paper combines the Good Regulator Theorem with the Law of Requisite Variety and seven other requisites that are necessary and sufficient for a cybernetic regulator to be effective and ethical. The resulting Ethical Regulator Theorem provides a basis for systematically evaluating and improving the adequacy of existing or proposed designs for systems that make decisions that can have ethical consequences; regardless of whether the regulators are human, machines, cyberanthropic hybrids, organizations, corporations, or government institutions. The theorem is then used to define an ethical design process that has potentially far-reaching implications for society. A six-level framework is proposed for classifying cybernetic and superintelligent systems, which highlights the existence of a possibility-space bifurcation in our future time-line. The implementation of “super-ethical” systems is identified as an urgent imperative for humanity to avoid the danger that superintelligent machines might lead to a technological dystopia. Third-order cybernetics is defined as the cybernetics of ethical systems. Concrete actions, a grand challenge, and a vision of a super-ethical society are proposed to help steer the future of the human race and our wonderful planet towards a realistically achievable minimum viable cyberanthropic utopia.

Here, using the theory of electrical-quantum modelling of the neutron and proton as a three-phase alternating current electrical generator, we will analyse the proton decay and the inverse neutron decay and determine the following subatomic particles, Dproton, Protoniu, Dneutron and Neutroniumd.

Early-life adversity can profoundly impact individual development, yet some demonstrate resilience. Longitudinal studies tracking individuals over extended periods have aided our understanding of resilience and growth following adverse childhood experiences. This paper reviews insights from influential studies like the Kauai Longitudinal Study, the Adverse Childhood Experiences (ACE) Study, and the Dunedin Study. It explores key findings on risk and protective factors, adaptation trajectories, and long-term outcomes associated with resilience. Theoretical frameworks and methodological considerations are discussed. The paper examines how this research informs interventions, policies, and support systems for fostering resilience. It highlights the need for diverse samples, integrating biological and environmental factors, and investigating intergenerational impacts. By synthesizing longitudinal research, this paper elucidates complex pathways to resilience and positive development despite early adversity, offering insights for research and supporting vulnerable populations.

Maternal unbalanced diets cause adverse metabolic programming and affect the offspring's liver microRNA profile. The liver is a site of β-carotene (BC) metabolism and a target of BC action. We studied the interaction of maternal Western diet (WD) and early-life BC supplementation on the epigenetic remodeling of offspring’s liver microRNAs. Mouse offspring of WD-fed mothers were given daily a placebo (controls) or BC during suckling. The liver miRNAome was analyzed in recently weaned animals by microarray hybridization. BC impacted the liver miRNAome differently in male and female offspring, with no overlap in differentially expressed (DE) miRNAs between sexes and more impact in females. Bioinformatic analysis of DE miRNA predicted target genes revealed enrichment in biological processes/pathways related to metabolic processes, regulation of developmental growth and circadian rhythm, liver homeostasis and metabolism, insulin resistance, and neurodegeneration, among others, with differences between sexes. Fifty five percent of the overlapping target genes in both sexes identified were targeted by DE miRNAs changed in opposite directions in males and females. The results identify sex-dependent responses of the liver miRNA expression profile to BC supplementation during suckling and may sustain further investigations regarding the long-term impact of early postnatal life BC supplementation on top of an unbalanced maternal diet.

High seismic activity in the Himalayas and the increasing urbanization of its surrounding areas in the northern Indian region pose significant threats to both lives and properties. To mitigate the risk of seismic events, an earthquake early warning system can be used in the region. This system would be particularly beneficial to cities and towns in the mountainous and foothill regions that are located near earthquake sources. The government and the science and engineering community have re-sponded to this call by establishing the Uttarakhand State Earthquake Early Warning System (UEEWS). The system became fully operational on August 4, 2021, after being launched by the government of Uttarakhand. The UEEWS includes 170 accelerometers in the seismogenic part of the Uttarakhand region of the Himalayas. Ground motion data is transmitted to a central server through a dedicated private telecommunication network 24 hours a day, seven days a week.The system is designed to issue warnings for moderate to high-magnitude earthquakes via a mobile application installed on users' devices and sirens installed in government-owned public buildings. The UEEWS has successfully issued alerts for light earthquakes that occurred in the instrumented region and warnings for moderate earthquakes that occurred in the vicinity of the instrumented area. This paper provides an overview of the design of the UEEWS, details of the instrumentation, adaptation of attributes and their relation to earthquake parameters, the operational flow of the system, and information about the dissemination of warnings

Keywords: early childhood; education; quality; measurement; monitoring; majority world; Item Response Theory; psychometrics

The Standard Model (SM) of particle physics successfully describes electromagnetic, weak, and strong forces but omits gravity. We introduce the Kinematrix Field Theory (KFT), integrating gravity into this fundamental force framework through a novel particle, the kinematon. This gauge boson, existing in both massless and massive forms, advances the SM's scope to address enigmas like dark matter and neutrino masses. We detail the mathematical structure of the KFT and establish Feynman rules for kinematon interactions with fermions and gauge bosons. The KFT, synergizing with the Higgs mechanism and general relativity, aspires to a unified quantum theory of gravity. We explore the kinematon's phenomenological implications and potential experimental signatures, forecasting significant advancements in fundamental physics and setting a course for future explorations in the SM.

Over recent years, the swine industry has witnessed the withdrawal of antibiotics and continuous regulation of zinc and copper oxides in the early-life nutrition of piglets. Due to this development, alternative ingredients or additives from plant sources have been tremendously explored. Therefore, this study's objective was to evaluate the effect of dietary supplementation with tannins on weaned piglets’ growth performance, serum antioxidant capacity, and immune status using a meta-analysis approach. With only the inclusion of non-challenged weaned piglets, a total of 16 studies with parameters of interest were deemed eligible after a two-step screening process following a comprehensive literature search in the scientific databases of Web of Science, Scopus, ScienceDirect, PubMed, and Google Scholar. Two main categories of data, including the study’s characteristics and response variables (growth performance, serum antioxidant, and immune indices), were extracted. Applying the random-effects models, Hedges’ g effect size of supplementation with tannins was calculated using the R software to determine the standardized mean difference (SMD) at a 95% confidence interval. Sub-group analysis and meta-regression further explored heterogeneity (PSMD 0.05, I2 50%, n ≥10). Supplementation with tannin reduced average daily gain (p = 0.20) and feed conversion ratio (p 0.01); however, it increased average daily feed intake (p = 0.07) and final body weight (p 0.01). Meta-regression models indicated that tannin dosage and supplementation duration were directly associated with tannins' effectiveness on productive performance. In the serum, the concentration of glutathione peroxidase, superoxide dismutase, and total antioxidant capacity were elevated (p 0.01) in response to tannins supplementation, while malondialdehydes was reduced (p 0.01). Likewise, decreased immunoglobin A (p = 0.47) and increased immunoglobin M and G levels (p 0.01) were detected. In conclusion, dietary supplementation with tannins, particularly with chestnut and grape seed proanthocyanidins, increases the productivity of weaned piglets. At the same time, it is a possible nutritional strategy to mitigate oxidative stress and stimulate gut health. Thus, supplementing chestnut and grape seed proanthocyanidin tannins in the early phase of swine production could be used to alleviate the incidence of diarrhea.

Background: Neonatal sepsis associated with severe morbidity and mortality defines the systemic condition arising from the bacterial, viral, fungal origin associated with hemodynamic and clinical alterations. Symptomatology can be different, from subclinical to severe, focal or systemic disease. The causal agent comes from maternal flora or can be of community/hospital origin. Material and method: Our retrospective study evaluated 121 newborns (both preterm and term), divided into three groups: early onset sepsis (35), late onset sepsis (39), and control group (47), from 0 to 28 days old. Blood samples and cultures were collected at admission, after 24 hours, and 72 hours. Results: The two-sample Wilcoxon signed rank test revealed a statistically significant difference between the initial and final measures of lactate dehydrogenase (LDH) and ferritin within the early onset sepsis (EOS) and late onset sepsis (LOS) groups. No significant differences were observed for those two variables within the control group. There were significant differences for first and last measurements of C-Reactive Protein (CRP) (p = 0.029), leukocyte count (p = 0.002), and platelets (TR) (p = 0.00001). Conclusions: Ferritin is a potential biomarker that can be associated with systemic response and sepsis in both cases of early and late onset sepsis.

This study develops a 7-layer Long Short-Term Memory (LSTM) model to enhance early diabetes detection in Oman, aligning with the theme of 'Artificial Intelligence in Healthcare'. The model focuses on addressing the increasing prevalence of Type 2 diabetes, projected to impact 23.8% of Oman's population by 2050. It employs LSTM neural networks to manage factors contributing to this rise, including obesity and genetic predispositions, and aims to bridge the gap in public health awareness and prevention. The model's performance is evaluated through various metrics. It achieves an accuracy of 99.40%, specificity and sensitivity of 100% for positive cases, a recall of 99.34% for negative cases, an F1 score of 96.24%, and an AUC score of 94.51%. These metrics indicate the model's capability in diabetes detection. The implementation of this LSTM model in Oman's healthcare system is proposed to enhance early detection and prevention of diabetes. This approach reflects an application of AI in addressing a significant health concern, with potential implications for similar healthcare challenges globally.st diagnostic capabilities, representing a significant leap forward in healthcare technology in Oman.

(1) Background: Neonatal early-onset sepsis (EOS) is associated with important mortality and morbidity. The aims of this study were to evaluate the association between serum biomarkers with early onset neonatal sepsis in a cohort of patients with prolonged rupture of membranes (PROM), and to calculate their diagnostic accuracy. (2) Methods: A retrospective cohort study was conducted on 1355 newborns with PROM admitted between January 2017 and March 2020, who were divided in two groups: group A, with PROM ≥ 18 hours and group B, with PROM < 18 hours. Both groups were further split into subgroups: proven sepsis, probable sepsis and no sepsis. Descriptive statistics, ANOVA analysis, and a Random Effects Generalized Least Squares (GLS) regression were used to evaluate the data. (3) Results: The statistically significant predictors of neonatal sepsis were the high white blood cells count from the first (p = 0.005) and third day (p = 0.028), and high CRP values from the first day (p = 0.004). Procalcitonin (area under the curve - AUC = 0.78) and CRP (AUC = 0.76) measured on the first day had the best predictive performance for early onset neonatal sepsis. (4) Conclusions: Further studies are needed to explore other bi-omarkers of sepsis in both pregnant women and newborns to better predict EOS.

Correlations between the Neoproterozoic belts surrounding the West African Craton and northern Brazilian cratons have long been a subject of interest and controversies. Due to the splitting of African and South American continents by the Atlantic oceanic domains, no direct links are preserved, requiring relying on various geological or geophysical characteristics to propose such correlations. In addition to the opening of the Atlantic oceanic domains, another difficulty arises from the covering of northern Brazilian belts by upper Paleozoic and Mesozoic basins, making these correlations speculative. Recently, four orogens have been evidenced in the Neoproterozoic belts of the western margin of the West Africa Craton, while the belts on the eastern side underwent only one orogeny. Similarities with the Pan-African I (900-650 Ma) and with the Pan-African II (650-480 Ma) orogenic events have been evidence in the western Brazilian belts (Araguay and Paraguay). The two first orogens on the western margin (Pan-African I and Pan-African II) can thus be extended to the western Brazilian belts and can be considered as parts of a single geodynamic system running from the Mauritania to the Paraguay including the “Gurupi rift” as an aulacogen connected to the NNW-SSE Panafrican I and II oceanic domains. Consequently, the eastern Brazilian belt should rather be linked the Eastern Trans-Saharan belts.