Introduction: Differentiated service delivery (DSD) models for antiretroviral treatment (ART) for HIV are being scaled up in the expectation that they will improve the quality and efficiency of treatment delivery and reduce costs while maintaining at least equivalent clinical outcomes. Even this minimum requirement of equivalent clinical outcomes is poorly documented for most models and settings, however. We reviewed the recent literature on DSD models to describe what is known about clinical outcomes. Methods: We conducted a rapid systematic review of peer-reviewed publications in PubMed, Embase, and the Web of Science and major international conference abstracts that reported outcomes of DSD models for the provision of ART in sub-Saharan Africa from January 1, 2016 to September 12, 2019. Sources reporting standard clinical HIV treatment metrics, primarily retention in care and viral load suppression, were reviewed and categorized by DSD model and source quality assessed. Results and Discussion: Twenty-nine papers and abstracts describing 37 DSD models and reporting 52 discrete outcomes met search inclusion criteria. Of the 37 models, 7 (19%) were facility-based individual models, 12 (32%) out-of-facility based individual models, 5 (14%) client-led groups, and 13 (35%) healthcare worker-led groups. Retention was reported for 73% of the models and viral suppression for 57%. Where a comparison with conventional care was provided, retention in most DSD models was within 5% of that for conventional care; where no comparison was provided, retention generally exceeded 80%. For viral suppression, all those with a comparison to conventional care reported a small increase in suppression in the DSD model; reported suppression exceeded 90% in 11/21 models. Analysis was limited by the extensive heterogeneity of study designs, outcomes, models, and populations. Most sources did not provide comparisons with conventional care, and metrics for assessing outcomes varied widely and were in many cases poorly defined. Conclusion: Existing evidence on the clinical outcomes of DSD models for HIV treatment in sub-Saharan Africa is limited in both quantity and quality but suggests that retention in care and viral suppression are roughly equivalent to those in conventional models of care.

FRAP technique have been used for decades to measure movements of molecules in 2D. Data obtained by FRAP experiments in cell plasma membranes are assumed to be described through means of two parameters, a diffusion coefficient D (as defined in a pure Brownian model) and a mobile fraction M. Nevertheless, it has also been shown that recoveries can be nicely fit using anomalous sub-diffusion. FRAP at variable radii has been developed using the Brownian diffusion model to access geometrical characteristics of the surrounding landscape of the molecule. Here we performed numerical simulations of continuous time random walk (CTRW) anomalous subdiffusion and interpreted them in the context of variable radii FRAP. These simulations were compared to experimental data obtained at variable radii on living cells using the PH domain of the membrane binding protein EFA6 (exchange factor for ARF6, a small G protein). This protein domain is an excellent candidate to explore the structure of the interface between cytosol and plasma membrane in cells. By direct comparison of our numerical simulations to the experiments, we show that this protein does not exhibit anomalous diffusion in BHK cells. The non Brownian PH-EFA6 dynamics observed here is more related to spatial heterogeneities such as cytoskeleton fences effects.

Objective: The study aimed to characterize the changing landscape of circulating SARS-CoV-2 lineages in the local community of Hong Kong throughout 2022. We examined how adjustments to quarantine arrangements influenced the transmission pattern of Omicron variants in a city with relatively rigorous social distancing measures at that time. Methods: In 2022, a total of 4,684 local SARS-CoV-2 genomes were sequenced using the Oxford Nanopore GridION sequencer. SARS-CoV-2 consensus genomes were generated by MAFFT, and the maximum likelihood phylogeny of these genomes were determined using IQ-TREE. The dynamic changes in lineages were depicted in a time tree created by Nextstrain. Statistical analysis was conducted to assess the correlation between changes in the number of lineages and adjustments to quarantine arrangements. Results: By the end of 2022, a total of 83 SARS-CoV-2 lineages were identified in the community. The increase in the number of new lineages was significantly associated with the relaxation of quarantine arrangements (One-way ANOVA, F(5,47)=18.233, p<0.001)). Over time, Omicron BA.5 sub-lineages replaced BA.2.2 and became the predominant Omicron variants in Hong Kong. The influx of new lineages reshaped the dynamics of Omicron variants in the community without fluctuating the death rate and hospitalization rate (One-way ANOVA, F(5,47)=2.037, p=0.091). Conclusion: The study revealed that even with an extended mandatory quarantine period for incoming travelers, it may not be feasible to completely prevent the introduction and subsequent community spread of highly contagious Omicron variants. Ongoing molecular surveillance of COVID-19 remains essential to monitor the emergence of new recombinant variants.

In this paper we investigate in different scenarios the feasibility of using massive multiple-input multiple-output (mMIMO) with Reconfigurable Intelligent Surfaces (RISs) to boost the throughput and coverage performances with high energy efficiency, considering sub-6 GHz, mmWave and THz bands. With that objective, a centralized radio access network (C-RAN) suitable for beyond fifth generation (B5G) systems is considered, where we integrate the base stations (BSs) with multiple RISs and devices or user equipment. RISs with a large number of quasi-passive reflecting elements constitute a low-cost approach capable of shaping the radio wave propagation and improve wireless connectivity. We consider a scenario where multiple RISs are combined with mMIMO in the uplink in order to provide connectivity to Smart City (thousands of active low power devices) wirelessly, in the 3.6GHz and 28GHz bands. We also address a scenario where RISs are adopted with mMIMO in the downlink so as to offer connectivity to a Stadium with Pitch, (thousands of active user equipment) in the 28GHz band. Finally, we have also studied the connectivity at 100GHz of a Factory where several RIS panels replacing most of the BSs equipped with mMIMO assure improved throughput and coverage. We concluded that RISs are capable of improving the performance in any of these analyzed scenarios at the different frequency bands, justifying that they are a key enabling technology for 6G.

Background and Objectives: Proper use of oral anticoagulants is crucial in the management of non-valvular atrial fibrillation (AF) patients. Left atrial appendage closure (LAAC) may be considered for stroke prevention in patients with AF and contraindications for long-term anticoagulant treatment. We aimed to assess the anticoagulation status and LAAC indications in patients with AF from HECMOS (Hellenic Cardiorenal Morbidity Snapshot) survey. Materials and Methods: HECMOS was a nationwide snapshot survey of cardiorenal morbidity in hospitalized cardiology patients. HECMOS used an electronic platform to collect demographic and clinically relevant information from all patients hospitalized on March 3, 2022, in 55 different cardiology departments. In this substudy, we included patients with known AF without mechanical prosthetic valves and moderate to severe mitral valve stenosis. Patients with prior stroke, previous major bleeding, poor adherence to anticoagulants, and end-stage renal disease were considered candidates for LAAC. Results: Two hundred fifty-six patients (mean age 76.6±11.7, 148 males) were included in our analysis. Most of them (n=159; 62%) suffered from persistent AF. Mean CHA2DS2-VASc score was 4.28±1.7, while mean HAS-BLED score was 1.47±0.9. Three out of 3 patients with a CHA2DS2-VASc 0 or 1 (female) received improperly anticoagulants. Sixteen out of 18 patients with a CHA2DS2-VASc 1 or 2 (female) received anticoagulants. Thirty-three out of 235 patients with a CHA2DS2-VASc > 1 or 2 (for female) did not receive improperly anticoagulants. Among 221 under anticoagulant therapy, 191 (86.4%) received non-vitamin K antagonist oral anticoagulants (NOACs) and 30 (13.6%) received vitamin K antagonists. Relative indications for LAAC were present in 64 patients with NVAF (60 had only one risk factor and 2 had two concurrent risk factors). In detail, 36 had a prior stroke, 17 patients had a history of major bleeding, 15 patients reported poor or no adherence to the anticoagulant therapy and 5 had eGFR< 15 ml/min/1.73m2. Moreover, 33 had a HAS-BLED score ≥3. No LAAC treatment was recorded. Conclusions: Anticoagulation status was nearly optimal in a high thromboembolic risk population of cardiology patients, mainly treated with NOACs. One out of four AF patients should be screened for LAAC.

Background/Purpose: In recent times, Sub-Sahara Africa (SSA) had been rated by the World Health Organization, (WHO), as the most malaria endemic region in the world. Evidence synthesis of the risk factors associated with malaria among children aged under-five in SSA is urgently needed. This would help to inform decisions that policy makers and executors in the region need to make for the effective distribution of scare palliative resources to curb the spread of the illness. This scoping review is aimed to identify studies that have used multivariate classical regression analysis to determine risk factors associated with malaria among children under-five years old in SSA. Methods/Design: The search terms followed PICOTS, (Population, Intervention, Comparator, Outcome, Timing, Setting), and were used in searching through the following databases: PubMed, MEDLINE, Web of Science, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Scopus, and MeasureDHS. The databases were searched for published articles from January 1990 to December 2020. Results: Among the 1154 studies identified, only thirteen (13) studies met the study’s inclusion/exclusion criteria. Narrative syntheses were performed on the selected papers to synchronise the various risk factors identified. Factors ranging from child-related, (age, birth order and use of bed net), parental/household-related, (maternal age and education status, household wealth index) and community-related variables, (community wealth status, free bed net distribution), were some of the identified significant risk factors. Conclusion: It is timely to have a synthesis of risk factors that influence the malaria status of children under-five in SSA. The outcome of the review will increase the knowledge of the epidemiology of morbidity that will form the basis for designing efficient and cost-effective distribution of palliatives and controls of malaria in SSA.

An important aspect of the new sustainable development goals (SDGs) is a greater emphasis on reducing the health impacts of urban ambient air pollution (AAP) in developing countries. Meanwhile, the burden of disease attributable to AAP in sub-Saharan Africa (SSA) is growing, yet estimates of its impact in the region are likely underestimated due to a lack of air quality monitoring, the paucity of epidemiological studies, and important population vulnerabilities in the region. The lack of studies in the SSA region also represents an important global health disparity and environmental justice issue because thousands of air pollution health effects studies have been conducted in Europe and North America rather than in some of the most polluted regions of the world, such as SSA. In this review, we synthesize all of the ambient air pollution epidemiological studies that have been conducted in SSA to date. We highlight the gaps in AAP epidemiological studies conducted in different sub-regions of SSA and provide methodological recommendations for future environmental epidemiology studies addressing AAP in the SSA region.

The accumulation of high levels of lead or lead ions in a human body is harmful, particularly to children. Its neurotoxic effect is profound, damaging the central and peripheral nervous systems, resulting in stunted growth, behavioral problems and learning disabilities. The major source of lead or lead ions comes from the drinking water and tap water. The assessment of the water quality, including lead or lead ion content, is usually completed by a regional water department professional. This assessment is time-consuming and requires expensive instruments and skilled operators. Therefore, there is a need to produce a simple-use and relatively inexpensive method to detect lead or lead ions in water samples. This research has developed a simple-use, cost effective sensor system for the detection of lead ions in tap water. An under-potential deposited bismuth sub-layer on a thin gold film based electrochemical sensor was designed, manufactured and evaluated. Differential pulse voltammetry (DPV) measurement technique was employed in this detection. Tap water from the Cleveland, Ohio, USA regional water district was the test medium. Concentrations of lead ion in the range of 8 X 10^-8 M to 8 x 10^-4 M were evaluated. This DPV detection system required 3 -6 minutes to complete the detection measurement. A longer measurement time of 6 minutes was used for the lower lead ion concentration. The selectivity of this lead ion sensor was very good, and Fe III, Cu II, Ni II and Mg II at a concentration level of 5×10^-4 M did not interfere with the lead ion measurement.

It is known that complexes based on natural polysaccharides are able to eliminate bone defects. Prolonged hyperglycemia means low bone regeneration and a chronic inflammatory response. The purpose of the study was to increase the efficiency of early bone formation in a cavity of critical size in diabetes mellitus in the experiment. The polyelectrolyte complex contains high molecular ascorbate of chitosan, chondroitin sulfate, sodium hyaluronate, heparin, adgelon serum growth factor, sodium alginate and amorphous nanohydroxyapatite (CH-SA-HA). Studies were conducted on 5 groups of white female Wistar rats: group 1 - regeneration of a bone defect in healthy animals under a blood clot; group 2 - regeneration of a bone defect under a blood clot in animals with diabetes mellitus; group 3 - bone regeneration in animals with diabetes mellitus after filling the bone cavity with a collagen sponge; group 4 - filling of a bone defect with a CH-SA-HA construct in healthy animals; Group 5 - filling of a bone defect CH-SA-HA in animals with diabetes mellitus. Implantation of the CH-SA-HA construct into bone cavities in type I diabetic rats can accelerate the rate of bone tissue repair. The inclusion of modifying polysaccharides and apatite agents in the construction may be a prospect for further improvement of the properties of implants.

The ongoing emergence of SARS-CoV-2 virus variants remains a source of concern because it is accompanied by the potential for increased virulence as well as evasion of immunity. Here we show that, although having an almost identical spike gene sequence as another Omicron variant (BA.5.2.1), a BA.4 isolate lacked all the typical disease characteristics of other isolates seen in the Golden Syrian hamster model despite replicating almost as effectively. Animals infected with BA.4 had similar viral shedding profiles to that seen with BA.5.2.1 (up to day 6 post infection) but they all failed to lose weight or present with any other significant clinical signs. We hypothesize that this lack of detectable signs of disease during infection with BA.4 was due to a small (nine nucleotide) deletion (∆686-694) in the viral genome (ORF1ab) responsible for production of non-structural protein 1 which resulted in the loss of three amino acids (aa 141-143).

Coppicing has been neglected in recent decades leaving gaps in knowledge on silvicultural interventions, especially the long-term effects on coppices of South-East Europe. Thus, our work aims to define the long-term effects of thinning in sessile oak (Quercus petraea (Matt.) Liebl.) and European beech (Fagus sylvatica L.) sub-mountainous thermophilic low coppices in the Croatian Dinarides. The experiment includes two localities with thinning plots and control plots. Thinning was done in 2002 with 17.71% of wood volume removed in the European beech coppice and 26.09% in the sessile oak coppice. 1276 trees were marked, measured (DBH, tree height, number of stems per stump) and assessed for vitality, origin and six silvicultural features revealing tree quality. Descriptive statistics for all variables, RMANOVA for DBH and height and for continuous variables mean+-+ standard deviation for categorical frequency and relative frequency variables were carried out. The results show a statistically significant positive long-term effect of thinning on tree growth, stem and crown features and support findings that thinning, by increasing growth and quality, is a necessary intervention in European beech and sessile oak low coppices. The recent economic crisis, the sudden increase in energy prices, and the increased demand for assorted wood products have initiated higher interest in coppices in Croatia.

Satellite altimetry is successfully developing during the past three decades for the sea level, ocean dynamics, coastal oceanography, planetary waves, ocean tides, wind and wave, ice cover, Earth’s gravity field, and climatology research. We propose a new essential add-on of satellite altimetry related to the peculiarities of the orbits of the Topex/Poseidon and Jasons’ satellite missions which were not mentioned before in the scientific publications. Derived subsets of “self-crossover” and “inter-crossover” points in sub-polar latitudes are discussed in detail in the context of water exchange, and wind-wave dynamics, and potential challenges to be solved. The relatively short time lags between measurements at these crossovers provide additional information on anomalies of magnitudes and directions of ocean currents, and characteristics of wind-driven waves. Resulting data snapshots with constant space and time intervals can be regarded as time series of virtual buoys, an analog of continuous buoy measurements of the sea level, wind speed, and wave height. Areas of the World Ocean where these specific crossovers occur are described in the context of water exchange, wind wave studies, and potential challenges to be solved. The value of these special crossovers for studies and monitoring of the sub-polar seas is illustrated by a case study.

Forests, as a form of natural resource, play a significant role in the social, ecological, and economic aspects of community life. One of the communities that live in the forest and dependent on the forest is Orang Rimba in Jambi. The objectives of this research are to investigate changes in ownership and access systems of natural resources within the Orang Rimba community, the factors driving these changes, and the impacts of changes in access and control over natural resources on the socio-cultural conditions of the Orang Rimba community. This research was conducted using a qualitative approach. The result of this research shows that the Orang Rimba community has experienced changes in access and control of forest resources. Many factors contribute to these changes, mainly from the Government and market forces. Moreover, these changes bring about some fundamental changes in Orang Rimba’s livelihood and even their live in general.

In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia's semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia-Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36.0% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers' climate adaptation. Semi-arid agro-region policymakers could utilize this information to adjust local seed systems and extension strategies.

China’s Grassland Eco-Subsidy Program has been implemented since 2011 to protect and sustain grassland resources and improve the economic situation of herders. In this case study, we evaluated the policy from the perspective of pastoral differentiations and their willingness to accept (WTA) the eco-subsidy. Using the contingent valuation method (CVM), we interviewed 410 herder households in the grass-livestock balance sub-policy zones across Inner Mongolia, and examined how their horizontal and vertical differentiation affected their WTA and compensation expectations in a sorted Logistic model and a Tobit model, respectively. Our findings suggest that horizontal differentiation of herders (variations of income sources and employments) promoted the WTA for eco-subsidy and inhibited the increase of compensation expectations. A large vertical differentiation extent (income disparity) lowered the WTA but raised expectations for payment levels. Besides, factors such as operating pasture area, precipitation, and supervision intensity had significant impacts. Grazing income remained the primary income source for most herder households, reflecting the characteristics of "the rational economic man." Our results suggest a need for policy improvements to guide herders towards becoming "rational ecological men.” By considering this differentiation, policymakers can better tailor the program to meet the needs and expectations of diverse herder households.

The ongoing evolution of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has resulted in the recent emergence of a highly divergent variant of concern (VOC) defined as Omicron or B.1.1.529. This VOC is of particular concern because it has the potential to evade most therapeutic antibodies and has undergone a sustained genetic evolution, resulting in the emergence of five distinct sub-lineages. However, the evolutionary dynamics of initially identified Omicron BA.1 and BA.2 sub-lineages remain poorly understood. Herein, we combined Bayesian phylogenetic analysis, mutational profiling, and selection pressure analysis to track virus genetic changes that drive the early evolutionary dynamics of the Omicron. Based on the Omicron dataset chosen for the improved temporal signals and sampled globally between November 2021 and January 2022, most recent common ancestor (tMRCA) and substitution rates for BA.1 were estimated to be 18 September 2021 (95% highest posterior density (HPD) 04 August – 22 October 2021) and 1.435×10-3 (95% HPD = 1.021×10-3 – 1.869×10-3) substitution/site/year, respectively, whereas 03 November 2021 (95% highest posterior density (HPD) 26 September – 28 November 2021) and 1.074×10-3 (95% HPD = 6.444×10-4 – 1.586×10-3) substitution/site/year for BA.2 sub-lineage. The findings of this study suggest that the Omicron BA.1 and BA.2 sub-lineages originated independently and evolved over time. Furthermore, we identified multiple sites in spike protein undergoing continued diversifying selection that may alter the neutralization profile of BA.1. This study shed light on the ongoing global genomic surveillance and Bayesian molecular dating analyses to better understand the evolutionary dynamics the virus and, as a result, mitigate the impact of emerging variants on public health.

Studies shows that, normal to high serum 25(OH)D status appears to have some beneficial influence on the incidence and severity of some, though not all, types of infections. However, studies with vitamin D supplementation on young children produced conflicting results with respect to the level of vitamin D deficiency among common medical illnesses among children. Method: A systematic review of literatures from PubMed, CINAHL, Web of science, global health and Google scholar electronic databases was conducted to assess the pooled prevalence of vitamin D deficiency among healthy and sick children in sub-Saharan Africa. The data was extracted by two authors independently using standard data extraction format and STATA Version 14 was used for analysis. The heterogeneity of the studies was assessed by using I2 test. A random-effects model was used to estimate the pooled prevalence among both healthy and sick children. Presence of publication bias was checked using Funnel plot and Egger's test. Result: A total of 1212 articles were identified by the total search of utilized data bases of which 13 papers fulfilled the inclusion criteria and accessible with full document. The meta-analysis revealed that the pooled prevalence of vitamin D deficiency among healthy children in this study was 50.06% (95%CI 33.46%, 66.67%) with mean serum vitamin D level of 41.06 nm/L (CI range from 23.82nm/L to 58.31nm/L). The pooled prevalence among the sick children was 39.36% (CI 20.57%, 57.96%) with 66.96nm/L (95% CI 54.81nm/L, 79.11nm/L) mean concentration of vitamin D. Comparing the two level of the pooled prevalence, the prevalence among the healthy children was significantly higher compared to those who have common medical illnesses and the pooled mean concentration among the sick was much higher than the mean concentration among healthy children. Conclusion: The level of pooled prevalence among both group of population was significantly of public health concern and the prevalence among the healthy children was much higher among the sick children implying the need for reconsideration of available recommendations for the prevention of vitamin D deficiency

Bacteria’s ability to withstand the detrimental effects of antimicrobials may take the form of resistance or tolerance with the minimum inhibitory concentration (MIC), the mutant prevention concentration (MPC), and the mutant selection window as salient concepts. Isolates exposed for 30 days to different concentrations of selected antibiotics, biocides, and heavy metals, singly and in combination, were additionally exposed to very high (15 × MIC) concentrations of ampicillin., and their tolerance was calculated the time to kill 99.9% of the isolate population (MDK99.9). These values were increased by 30 to 50% in test isolates compared to the untreated control. BAC 10-exposed isolates had the highest tolerance increase, and the tolerance appeared to originate from two sources, i.e., stochastic persistence and genetic-induced persistence, involving multiple genes using diverse mechanisms. The mutant selection window of the isolates to ampicillin, amoxicillin, and oxytetracycline also slightly increased compared to the control, indicating the amplification of persister cells during the 30-day exposure. These findings indicate that bacterial exposure to sub-inhibitory concentrations of environmental chemical stressors may not always result in the development of antimicrobial resistance but could initiate this process by selecting for persisters that could evolve into resistant isolates.

Understanding neck pain is an important societal issue. Kinematic data from sensors may help to gain insight on the pathophysiological mechanisms associated with neck pain through a quantitative sensorimotor assessment of one patient. The objective of this study was to evaluate the potential usefulness of artificial intelligence with several Machine Learning (ML) algorithms in assessing neck sensorimotor performance. Angular velocity and acceleration measured by an inertial sensor placed on the forehead during the DidRen laser test in thirty-eight acute and subacute non-specific neck pain (ANSP) patients were compared to forty-two healthy control participants (HCP). Seven supervised ML algorithms were chosen for the predictions. The most informative kinematic features were computed using Sequential Feature Selection methods. The best performing algorithm is the Linear Support Vector Machine with an accuracy of 82% and Area Under Curve of 84%. The best discriminative kinematic feature between ANSP patients and HCP is the first quartile of head pitch angular velocity. This study has shown that supervised ML algorithms could be used to classify ANSP patients and identify discriminatory kinematic features potentially useful for the clinicians in the assessment and monitoring of the neck sensorimotor performance in ANSP patients.

Background: Several studies recently confirmed the emergence of resistance to antimalarial drugs in sub-Saharan Africa. Multiple first-line treatment (MFT) is one of the measures envisaged to respond to the emergence and spread of this resistance. The aim of this study was to identify perceived advantages and disadvantages of several MFT deployment strategies and to better understand potential implementation drivers and barriers. Methods: A qualitative survey was conducted in seven sub-Saharan countries amongst key opinion-leaders, national decision-makers, and end users. A total of 200 individual interviews were conducted and findings were analyzed following a thematic inductive approach. Results: From a policy perspective, the new MFT intervention would require endorsement at the global, national, and regional levels to ensure its inclusion in guidelines. Funding of the MFT intervention could be a bottleneck due to costs associated with additional training of healthcare workers, adaptation of drug delivery mechanisms, and higher costs of drugs. Concerning the MFT deployment strategies, a slight preference for the segmentation strategy was expressed over the rotation and geographic approaches, due to the perception that a segmentation approach is already in place at country level. Conclusions: The findings highlighted the need for a collective approach to MFT deployment through the engagement of stakeholders at all levels of malaria management.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in humans in Wuhan City at the end of December 2019. Since then, it has spread to all the countries. Therefore, global interest has been focused on discovering treatments and developing successful vaccines. This study sequenced the complete genome of the SARS-COV-2 Omicron Omicron (BA.1) and sub-variants (BA.1.1, BA.2), which were isolated from 40 individuals in Duhok, Iraq. Ninety-five different mutations were identified when the complete genome of the SARS-COV-2 virus discovered in Wuhan, China (accession number: NC 045512.2) was matched to the virus sequence using sequencing technology (Illumina, USA). Sequence analysis revealed 38 mutations in spike glycoprotein (S), 30 of which were found in ORF1a. Additionally, 11 mutations were found in ORF1b, and 7,3,2,1 mutations were found in Nucleocapsid (N), membrane protein (M), Open Reading Frames 6 (ORF6), Open Reading Frames 9 (ORF9), and Envelope (E) genes, respectively. Phylogenetic analysis and transmission further confirmed that the isolates found in Iraq had distinct infection origins and were closely related to those from other countries and states. According to the findings of this study, a new vaccine can be developed based on identifying new Omicron variant mutations and sub-variants such as BA.2, which were identified for the first time in Iraq.

The purpose of this work is to analyze heat-treated ash wood at temperature of 185 ºC, in order to analyze its dimensional stability. For comparison, native ash/ not thermally treated wood, was be used. In order to analyze heat-treated ash wood, some main properties such as water absorption, swelling in thickness, roughness, Brinell hardness, modulus of rupture and elasticity, color change toward black with CIELab space, and many others properties were determined and processed. The results obtained after processing the experimental data have showed that heat-treated ash wood had good physical properties as absorption and swelling in thickness, and the slight increase in elasticity offers new fields of use. As a general conclusion of the work, it was established that the ash wood can be properly thermally treated, the dimensional stability characteristics being very good, and the decrease in bending resistance being almost imperceptible.

Bladder cancer (BC) is one of the most lethal genitourinary malignancies owing to its propensity for recurrence and poor survival. The biochemical pathway, signal transducer and activator of transcription 3 (STAT3), has gained significance as a molecular pathway that promotes proliferation, invasion, and chemoresistance. In this study, we explored the targeting of STAT3 with TTI-101 and SH5-07 in bladder cancer (BCa) and elucidated the mechanisms in three-dimensional (3D) spheroid and tumoroid models. We optimized the growth of spheroids from human, rat, and mouse BCa cell lines (J82, NBT-II, and MB49, respectively), and tumoroids from BBN (N-butyl-N-(4-hydroxybutyl)-nitrosamine) induced rat bladder tumors. Cell viability was assessed using MTT and trypan blue assays. ATP production, ROS production, and calcium AM (CA)/EtBr staining were used to measure the spheroid and organoid inhibition and mitochondrial function. Western blot analysis was performed to evaluate the pharmacodynamic markers involved in cell proliferation, apoptosis, cancer stem cells (CSCs), and STAT3 signaling in BCa. We found that targeting STAT3 (using TTI-101 and SH5-07) significantly reduced the proliferation of BCa spheroids, and tumoroids, which was accompanied by decreased expression of pSTAT3, Cyclin D1, and PCNA. Our data also demonstrated that treatment with STAT3 inhibitors induced ROS production and cell death in BCa spheroids and organoids. STAT3 inhibition induced cell death was associated with the activation of caspase 3/7 and PARP cleavage. Moreover, TTI-101 and SH5-07 targets cancer stem cells by downregulating the expression of CD44 and CD133 in 3D models. This study provides the first evidence for the prevention of bladder cancer with small-molecule inhibitors TTI101 and SH5-07 via suppression of CSCs and STAT3 signaling.

Recently, the concept of participatory democracy developed in the early 1970s has come back into fashion to revitalize the public involvement in political decision-making processes. Public par-ticipation in forest policy has been fully conceptualized by the scientific community in the late 1990s and early 2000s, but in many contexts the practical application remains unfulfilled. The aim of this study is to identify and analyze the participatory techniques used in literature to increase knowledge and facilitate its transferability into forest policies and strategies. A literature review was carried out to offer an overview of the participatory techniques adopted in the deci-sion-making process. At the end of literature review, 25 participatory techniques were identified based on over 2,000 publications. Afterwards, the participatory techniques were assessed using seven indicators (degree of participation, type and number of participants, time scale, cost, po-tential influence on policy). The results showed that the type of actors involved in the participa-tory technique is a key variable for the complexity and usefulness of the process, while the number of participants influences how information is disseminated. The Principal Component Analysis highlighted that the participatory techniques can be divided in three groups: the first group includes those techniques with a high degree of participation and a contextual high po-tential influence on policies, the second one includes techniques with a costs in terms of re-sources, while the third one consists of those with a large number of participants and reduced time requirements.

Amid the array of challenges prompted by the COVID-19 pandemic, the policy response of governments proved vital. The U.S. states pursued varied policy approaches that demonstrated distinct divergences in impact. Particularly, contrasting state contexts produced markedly assorted frameworks for the delivery of public health services, which indicate potential effects for COVID-19 policy implementation. Using the rates of COVID-19 vaccinations as a measure of policy execution, the purpose of this study is to examine the political and administrative influences contributing to differences in COVID-19 public health policy outcomes among the U.S. states. Ordinary least squares (OLS) regression models included data sources of nationally representative information pertaining to state public health attributes of politics and administration during the height of the pandemic and vaccine campaign. The findings suggest that state political and fiscal orientations display significant associations with COVID-19 vaccination disparities, while other administrative indicators did not. The results signal important policy implications for the politics-administration dynamic within the COVID-19 pandemic and offer further understanding toward the roles of federalism and governance in future public health emergencies.

More than 700 anthocyanins are described so far, and many different sources are rich in these natural pigments. During the last few years, researchers have been focusing of strategies to recover and purify anthocyanins, from simple liquid-liquid extractions to more advanced supercritical CO2 extractions, however, with such a huge number of different sources, it’s extremely hard to get a simple and fast methodology that fits several sources, not only by the structural nature of the anthocyanins but also by the presence of specific groups of natural compounds. Using simple methodologies like solid-phase extraction resins represents a powerful economical and efficiency strategy. In this work, we tested several sources of structurally distinct anthocyanins, including purple basil, purple cabbage, purple sweet potato, butterfly pea flower, cornflower and wild pansy, in different resins to assess their efficiency in the obtention of anthocyanin-pure extracts. The results showed us that the combination of oasis HLB® resin followed by a cation-exchange SPE with DSC-MCAX® resulted in high-purity anthocyanin extracts for all the cases.

Ballistic helmets are individual armor equipment designed to protect a soldier's head from projectiles and fragments. Although very common, these helmets are responsible for several causalities due to their low ballistic resistance and large back face deformation to stop the projectile. Therefore, to enhance helmet performance, studies have focused on the development of new materials and new ballistic protection solutions. The purpose of this study was to develop and evaluate a new ballistic solution using thermoplastic-based matrices. The first matrix was based on high-density polyethylene (HDPE). The second matrix was based on HDPE modified with ex-foliated montmorillonite (MMT). The main manufacturing processes of a thermoplastic-based ballistic helmet are presented, along with its ballistic performance, according to the National Institute of Justice (NIJ) standard 0106.01 and an investigation of its failure mechanisms via a non-destructive technique. All the helmets resulted in level III-A ballistic protection. The postimpact helmets were scanned to evaluate the back face deformation dimensions, which revealed that the global cone deformation was deeper in the HDPE than in the HDPE/MMT. The failure analysis revealed an overall larger deformation area in the HDPE and HDPE/MMT helmet delamination zones in regions with a large radius of curvature than in zones with the lowest radius, which is in accordance with previous simulations from the literature.

This article provides a literature review on tubal carcinoma to offer an updated insight into its preventative strategies, diagnosis, treatment, and oncological surveillance. In addition to the search string utilized, the authors' focus extended to key scientific studies, consensus statements, guidelines, and relevant case reports essential for the proper clinical management of the disease, providing a methodologically well-structured literature review combined with the practical expertise in the oncological field. The article also includes two emblematic clinical cases that emphasize the importance of understanding the physiopathology and the current state of the art in the anatomopathological advancements of tubal/ovarian/peritoneal carcinoma, often assimilated into a single clinical entity.

The present work titled QRGB consists of the development of a Python application for generating QR codes using the additive color generation method (RGB). This innovative method increases the information density stored in QR codes by using three color layers (red, green, and blue), each representing a different data set. QRGB offers an efficient and secure solution for storing and transmitting large amounts of information in limited spaces, significantly improving the capabilities of traditional black-and-white QR codes.By using three color layers (red, green, and blue), QRGB codes can store up to three times more information in the same space. This technique not only increases storage capacity but also enhances information security, making it more difficult to counterfeit or manipulate the code. The superposition of multiple data layers allows for redundancy implementation, increasing the code's robustness against damage or reading errors.QRGB codes are especially useful in applications that require the transmission of large amounts of data in limited spaces, such as in the packaging industry, digital business cards, and interactive advertising. Additionally, they have great potential in areas such as document and ticket security, where the authenticity and integrity of information are crucial.These points provide a solid foundation for understanding the innovation and advantages of colored QR codes (QRGB) compared to traditional QR codes, highlighting their applicability and potential in various sectors.The Python application developed for QRGB utilizes advanced color image processing techniques, applying models and methods to generate and decode QR codes using the RGB color system, thus enhancing information density and security through the innovative use of additive color layers.

The Internet of Things (IoT) signifies a revolutionary technological advancement, enhancing various applications through device interconnectivity while introducing significant challenges due to these devices' limited hardware and communication capabilities. To navigate these complexities, the Internet Engineering Task Force (IETF) has tailored the Routing Protocol for Low-Power and Lossy Networks (RPL) to meet the unique demands of IoT environments. However, RPL struggles with traffic congestion and load distribution issues, negatively impacting network performance and reliability. This paper presents a novel enhancement to RPL by integrating learning automata designed to optimize network traffic distribution. This enhanced protocol, the Learning Automata-based Load-Aware RPL (LALARPL), dynamically adjusts routing decisions based on real-time network conditions, achieving more effective load balancing and significantly reducing network congestion. Extensive simulations reveal that this approach outperforms existing methodologies, leading to notable improvements in packet delivery rates, end-to-end delay, and energy efficiency. The findings highlight the potential of our approach to enhance IoT network operations and extend the lifespan of network components. The effectiveness of learning automata in refining routing processes within RPL offers valuable insights that may drive future advancements in IoT networking, aiming for more robust, efficient, and sustainable network architectures.

Antimicrobial resistance (AMR) is a growing concern in healthcare, and the misuse of antibiotics is contributing to the problem. Antimicrobial Stewardship Programs (ASPs) have been proven to help reduce antibiotic consumption, promote appropriate use, and decrease the incidence of AMR and related side effects. In this study, we aimed to evaluate the impact of ASPs on antibiotics consumption and AMR spread in a Southern Italy. Most of the APSs consisted of applying infection control guidelines and WHO recommendations on antibiotic consumption. The results of the study showed that during the study period, the number of hospitalizations increased by 24%, while the total amount of antibiotics administered decreased from 52.1 to 38.6 defined daily doses (DDD) per 100 bed-days. There was also a significant increase in the number of rectal swabs taken to detect carbapenem-resistant Enterobacteriaceae (CRE) and methicillin-resistant Staphylococcus aureus (MRSA), while the positivity rate of these infections decreased significantly. Moreover, the hospital recorded a decrease in the incidence of several infections, including CRPsA, MRSA, PDR, and VanA infections. This study provides further evidence that ASPs can be effective in reducing antibiotic consumption and preventing the spread of AMR. By promoting the appropriate use of antibiotics and implementing infection control measures, we can help preserve the effectiveness of these life-saving drugs and promote better patient outcomes. However, more efforts are needed to improve healthcare practices and reduce related costs. In conclusion, we urge healthcare providers to implement ASPs in their institutions and help combat the growing threat of AMR. By doing so, we can ensure that antibiotics remain effective for future generations.

Background: Chronic Heart failure (CHF)constitutes a major health problem, representing the leading cause of hospitalization in people over 65 years old. Several studies have associated the Mediterranean diet with a cardioprotective function, improving prognosis in patients with high cardiovascular risk. Our main objective is to determine whether greater adherence to the Mediterranean diet is associated with a lower severity of CHF, depending on the number of heart failure decompensations and complications of the disease. Methods: The study was a single-center restrospective cohort study conducted at the Virgen del Rocío Hospital (Seville). Adherence to a Mediterranean diet was determined by the Mediterranean Diet Adherence Screener (MEDAS) in patients with chronic heart failure in a state of clinical stability, and their cardiac and analytical profiles were evaluated. Results: Seventy-two patients were included (35 with high adherence to the Mediterranean diet and 37 with low adherence). The average age was 81.29 ± 0.86 years. A trend towards fewer cardiac decompensations (1,49 ± 0,14 vs 1,92 ± 0,17), p= 0,054) and lower NT-proBNP values 2897,02 ± 617,16 vs 5227,96 ± 1047,12; p = 0,088) was observed in patients with high adherence compared to those with low adherence to the Mediterranean diet. Conclusions: Our results suggest that patients with CHF and high adherence to the Mediterranean diet have a tendency towards improved cardiac profile, indicated by fewer decompensations and lower NT-proBNP levels. Future clinical trials are needed to substantiate these hypotheses.

(1) Background: The aim of this investigation is to determine the effect of archwires’ deflection on the temperature transitions driving the austenite to martensite transformation (and vice versa) and the force released by NiTi and CuNiTi orthodontic wires. (2) Methods: Round cross-section archwires have been investigated. The calorimetric approach has been used for measuring transition temperatures occurring in the unstressed (e.g. undeflected) state of the wires. Static Thermo-mechanical analysis in a temperature controlled wet environment has been performed in the range of temperature between 5°C and 55°C for measuring temperature transitions occurring in highly deflected archwires in conjunction with the force released by these wires. (3) Results: Plateau forces investigated in Part I and those reported in the literature describes the wire’s behaviour only at deflection levels close to the end point of the force plateau extension detected at 37°C. Upon heating or cooling, the austenite finish (Af) transition temperature and the martensite start (Ms) temperature largely depends on the deflection level for both NiTi and CuNiTi. (4) Conclusions: The plateau force levels at 37°C, broadly reported in the literature, only represent the lower boundary force that a superelastic wire releases at 37°C above its elastic limit. For both NiTi and CuNiTi, plateau force levels at 37°C can be predicted by the static TMA profile matching the end point of the force plateau extension. Transition temperatures in largely deflected wires are significantly higher than those determined through the calorimetric approach.

Half-metallic semi-Heusler compounds are currently at the forefront of scientific research due to their potential applications in spintronic devices. Unlike other semi-Heuslers, the p0(d0)-d compounds do not appear to crystallize in the typical variant of the C1b structure. We investigate this phenomenon in the p0-d Heusler compounds LiYGa and LiYGe, where Y varies between Ca and Zn, using first-principles ab-initio electronic band structure calculations. We examine the electronic and magnetic properties of these compounds in relation to the three possible C1b structures. Notably, LiVGa, LiVGe, LiMnGa, and LiCrGe are half-metallic ferromagnets across all three variations of the C1b lattice structure. Our findings will serve as a foundation for future experimental studies on these compounds.

Life is a field of senses and the experience of feeling, thinking, acting, and building relationships with everything around us. These senses and experiences are also consumed in travel destinations to pursue the traveler's escapism and happiness. However, while the field of tourism studies has recognized the importance of experience and focused on the relationship between various travel experiences and happiness, research on the variables that mediate and strengthen these relationships is lacking. Therefore, this study aims to apply the five strategic experiential models proposed by Schmitt [1]— sense, feel, think, act, and relate — to investigate the mediating effect of escapism on travelers' well-being. Data were collected from travelers visiting three major heritage sites in Gyeongju (Bulguksa Temple, Seokguram Grotto, and Bunhwangsa Temple), and 509 responses were used for analysis. The analysis was conducted using statistical package programs SPSS and AMOS employing frequency analysis, reliability analysis, confirmatory factor analysis, and structural equation modeling. The results indicated significant positive effects between variables such as cultural heritage travel experience, escapism, and well-being. In the analysis of the mediating effect of escapism, escapism showed a significant mediating effect on the relationship between travel experience and well-being. This study confirmed that, during cultural heritage travels, individuals’ well-being can be enhanced through a holistic experience encompassing sensory, emotional, cognitive, behavioral, and relational aspects rather than an isolated experience centered on escapism. This finding provides important implications for the design and planning of travel programs and products.

Aiming at solving difficulties related to aero-engine classification and identification, the infrared spectra of aero-engine hot jets are measured by telemetry Fourier transform infrared spectrometer, and a six types aero-engine hot jet spectrum data set is generated. The spectrum data set were randomly sampled at a ratio of 8:1:1 to generate training set, validation set and prediction set. In this paper, a Peak Finding Siamese Convolutional Neural Network (PF-SCNN) is designed to match and classify spectrum data. In the first place, the matching pairs of training set and validation set are made independently with the labels of positive and negative samples creating. The spectrum feature extraction and distance similarity calculation are carried out by the Siamese convolutional neural network (SCNN). When entering the prediction phase, the prediction set and training set are integrated to predict in the trained model. The prediction set labels are ultimately determined by matching them with the training set labels having the highest similarities to ensure accurate predictions. To improve the operation efficiency of the SCNN, a peak finding method is introduced to extract the spectrum peaks. Peak positions of high frequency are counted, while the peak data are extracted. The peak data are used to take the place of the original data for training and prediction. The performance measures are defined as Accuracy, Precision, Recall, Confusion matrix and F1-score, and the prediction accuracy was up to 99%. The experimental results indicate that the proposed PF-SCNN is suitable for our spectral dataset and can complete the task of infrared spectrum classification of aero-engine hot jets.

The characteristics of tight sandstone, such as small pores, complex pore structures, low permeability, and low porosity, make it difficult to accurately characterize its pore structure. This represents a major challenge in the exploration and development of tight sandstone oil and gas reservoirs. This article conducts a simulation study on the impact of characteristic parameters such as pore size, coordination number, pore-throat ratio, and wettability on microscopic remaining oil after polymer flooding, thereby quantifying the types of remaining oil.

This study provides a methodology for optimizing oil production and CO2 sequestration using an integrated asset model of the Farnsworth Unit field, incorporating extensive geological, geophysical, and engineering data. Sensitivity analysis identified critical parameters impacting oil recovery and CO2 storage, leading to the construction of a proxy model using polynomial regression and radial basis function neural networks, with the latter proving more effective for "What-if" analysis. The sensitivity analysis indicated that the Corey parameters impact cumulative oil produced the most. Comprehensive history matching validated the model against historical production data, ensuring reliability for forecasting and optimization. Two scenarios, "Do-Nothing" and development strategy, were forecasted over 15 years (2020-2035). The "Do-Nothing" scenario resulted in 9.57 MMSTB of oil recovery and 2,822.70 MMlbs of CO2 storage. The development strategy case improved outcomes with 13.95 MMSTB of oil recovery and 5,061.68 MMlbs of CO2 stored, and was selected for optimization using particle swarm optimization. The optimized strategy achieved 14,043,372 STB of cumulative oil and 4,832.18 MMlbs of CO2 stored, and increased the field NPV by 25.84% to $114,871,730. This study underscores the significance of integrated asset modeling in enhancing oil recovery and optimizing CO2-EOR processes, providing valuable insights into operational conditions and constraints.

Here, we present a general framework for computing the infrared anharmonic vibrational spectra of polyatomic molecules using the Born-Oppenheimer molecular dynamics (BOMD) with the software PyRAMD. To account for the nuclear quantum effects, we suggest using the simplified Wigner sampling (SWS) approach [\textit{Phys. Chem. Chem. Phys.}, 2023, \textbf{25}, 18406-18423] simultaneously coupled with the Andersen and Berendsen thermostats. We propose a new criterion for selecting the parameter of the SWS based on the molecules' harmonic vibrational frequencies and usage of the large-time-step blue shift correction, allowing for a decrease in computational expenses. For the Fourier transform of the dipole moment autocorrelation function, we propose to use the regularized least-squares analysis, which allows us to obtain higher frequency resolution than the direct application of fast Fourier transform. Finally, we suggest the usage of the pre-parameterized scaling factors for the IR spectra from BOMD, also providing the scaling factors for the spectra at the BLYP-D3(BJ)/6-31G, PBE-D3(BJ)/6-31G, and PBEh-3c levels of theory.

The conservation of the main protease in viral genomes, combined with the absence of a homologous protease in humans, makes this enzyme family an ideal target for developing broad-spectrum antiviral drugs with minimal host toxicity. GC-376, a peptidomimetic 3CL protease inhibitor, has shown significant efficacy against coronaviruses. Recently, a GC-376-based PROTAC was developed to target and induce the proteosome-mediated degradation of the dimeric SARS-CoV-2 3CLPro protein. Extending this approach, the current study investigates the application of the GC-376 PROTAC to the 3CPro protease of Enteroviruses, specifically characterizing its interaction with CVB3 3CPro through X-ray crystallography, NMR and biophysical techniques. The present structural data show that there are some changes between the binding of CVB3 3CPro and SARS-CoV-2 3CLPro, but the overall similarity is strong. The most notable variation is the orientation of the phenylmethyl ester of GC-376 with the S4 subsite of the proteases. This is linked to the flexibility of the protein structure around the region of the catalytic triad shown by our NMR data. Other structural variations include distinct ligand interactions in subsites S1 and S2, influenced by the presence of Glu71 in CVB3 3CPro. Despite these differences, the GC-376 PROTAC fits well within the binding sites of both proteases, demonstrating its potential as a broad-spectrum antiviral agent.

Disaster issue consultation is crucial for effective emergency management, requiring timely and accurate information to support decision-making processes. This paper explores the integration of large language models (LLMs) with advanced prompt engineering to enhance the performance of AI systems in disaster management. We propose a novel multi-round prompt engineering approach that guides LLMs to iteratively refine their responses based on evolving disaster scenarios. Our method leverages diverse disaster-related datasets and employs a combination of accuracy metrics and a customized GPT-4 scoring system for evaluation. We conduct comprehensive experiments across multiple LLM platforms, including Qwen2, ChatGPT, Claude, and GPT-4, comparing our approach with baseline models and the Tree of Thoughts (ToT) method. The results demonstrate significant improvements in both accuracy and response quality, highlighting the effectiveness of our method in providing contextually relevant and actionable insights. Additional analysis confirms the robustness and generalizability of our approach across various disaster scenarios, establishing it as a valuable tool for enhancing disaster management practices.

AI advances integrate generative design tools in architecture, providing architects with sophisticated design options. It enables the creation of intricate, high-performing projects by exploring diverse design possibilities with AI and algorithms. Generative AI and generative design empower architects to create better-performing, sustainable, and efficient design solutions and explore diverse design possibilities. This paper leverages multimodal generative AI to enhance design creativity by combining textual and visual inputs. Blockchain technology converts design metadata into NFTs, ensuring secure, authentic, and traceable data storage. The framework addresses data ownership, legal adherence, and client-architect collaboration and is entirely scalable for digital design authentication. This research exemplifies the pragmatic fusion of Generative AI and blockchain technology applied in architectural design for more transparent, secure, and effective results. This study provides a strategy that uses generative AI technologies to achieve an efficient and creative workflow in the early stages of architectural design.

In the foodservice industry, clients judge not only the product standard but also the service quality they receive during their restaurant experience. Therefore, when the importance of the dining experience is strongly regarded by consumers in terms of intellectual and motivational attributes, they are happier to suggest the establishment to others. The main objective of this research is to study the influence of different service quality factors in restaurants and their impact on customer satisfaction. This research is also undertaken to evaluate the identification of important factors for the restaurant industry and the levels of service quality among customers satisfaction with the services offered by restaurants in India. As factor analysis, correlation, and regression research, this study was conducted using a modified IBM SPSS Statistics 24 and AMOS instrument among the 630 randomly selected customers. A weighted mean was used to describe the levels of service quality and customer satisfaction. Multiple regressions were used to determine the predictors of customer satisfaction. The results reveal the main 12 service quality factors, which are: 1. Process-related factors: system for take-away orders, order tracking system, and time for food preparation 2. People-related factors: focus on customers' special requests, peer group influence, and making you feel special. 3. Physical Environment: Walking Space, Architecture of the Restaurant, and Signals for Direction 4. Performance-related factors: food served at an appropriate temperature; food presentation; portion size of food in the restaurant. The researchers have developed one model on service quality factors that is described in the research paper.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. Validated through extensive offline experiments and online deployments, the model significantly outperforms existing optimal benchmark methods on real datasets, improving the location deviation squared metrics and the top-three location prediction accuracy metrics. These research results provide important support to further promote the intelligent development of the logistics industry.

This paper presents a demonstration of a linearly-polarized transmit-arrays antenna with high-efficiency and wideband operating in X-band. The topology of the unit cell consists of two identical patch antennas loaded by C-loop slot and interconnected by a metalized via through a ground plane sandwiched between two identical substrates [18]. A waveguide measurement system WGMS has been used for single cell characterization (reflection/transmission coefficients). Good results have been demonstrated in terms of matching performances; the reflection coefficient S11 is under 10-dB in the 9.4-10.4 GHz band (i.e. 10.1% around 9.9 GHz) and with only 0.35 dB-insertion loss at 10 GHz. The transmit-arrays prototype permitted to achieve 22.4 dBi of directivity and 20.1 dBi of gain. The aperture and radiation efficiencies are about 28.2% and 58.3%, respectively. With a focal ratio (F/D) of 1/2 the spill-over loss is less than 2 dB. Beam-scanning up to ± 35° has been achieved with the same phase quantization (passive) and less than 3 dB of gain losses.

The surface thermodynamic properties of polymers and copolymers modified by supramolecular structures are very used in several industrial processes, such as selective adsorption, paints, coatings, colloids, and adhesion applications. Background: Inverse gas chromatography at infinite dilution was proved to be the best technique to determine the surface properties of solid surfaces by studying the adsorption of some model polar and non-polar organic molecules adsorbed on solid surfaces by varying the temperature. Methods: The retention volume of adsorbed solvents is a precious parameter to obtain the London dispersive and polar free energies and the London dispersive surface energy of styrene–divinylbenzene copolymer modified by supramolecular structure of melamine using the Hamieh thermal model and our new methodology consisting in the separation of the two polar and dispersive free energy of interaction. This led to the determination of the polar acid and base surface energy, and the Lewis’s acid-base constants of the various solid materials. Results: all surface energetic properties of styrene–divinylbenzene copolymer modified by melamine at different percentages were determined as a function of temperature, following our new methodology. Conclusions: It was observed that the styrene–divinylbenzene copolymer exhibited the highest London dispersive surface energy which decreased when the melamine percentage increased. All materials presented higher Lewis’s basicity and this Lewis’s basicity increased with the percentage of melamine.

A high-gain broadband circularly polarized crossed dipole antenna is designed. This antenna utilizes two pairs of cross dipoles and a pair of phase delay lines to form circularly polarized radiation. Open-circuit stubs are loaded on the four arms of these two pairs of cross dipoles to introduce new circularly polarized resonating frequency. A rectangular ring patch is introduced directly below the cross dipoles to form the third circularly polarized resonating frequency, thereby broadening the axial ratio bandwidth of the antenna. In addition, metal posts are loaded at the four right angles of the rectangular ring patch to increase the antenna gain. Measurement results show that the antenna achieves a 3dB axial ratio bandwidth of 29.2% (1.9 GHz-2.55 GHz) and maintains a gain of 7.5 dB within the passband, exhibiting good circularly polarized radiation performance.

Nicotiana benthamiana plants infected with a potato virus Y isolate (PVYO) under ambient conditions of 25 °C and ~405 parts-per-million (ppm) ambient CO2 display symptoms of chlorosis, leaf curling, and stunting. However, under elevated temperature and CO2 levels (30 °C, 970 ppm), systemic viral titers decrease several-fold, and plants appear asymptomatic. Under the latter conditions we have studied how infection, drought, or both combined affect infection, drought-driven loss of leaf turgor, plant water content, stomatal conductance, metabolome, and hormone (ABA, SA, and JA) levels. We found that drought did not affect viral titers. As expected, drought decreased plant water content and stomatal conductance. Under drought conditions, infection did not alter significantly final water content or loss of leaf turgor progression, but it increased the levels of some sugars and other osmo-protectants. Infection and drought altered the levels of many components of the metabolome. Some components altered by infection were not altered by drought, but most of those altered by drought were also altered by infection. Drought increased the levels of ABA, infection increased the levels of ABA, SA, and JA, and altered their relative balance. The effects of drought and of infection on hormone levels were cumulative when combined. Thus, under ambient conditions that turn a severe infection into an asymptomatic one both, plant physiology parameters and the interplay with drought are affected.

We propose a novel approach to quantum theory construction that involves solving a maximization problem on the Shannon entropy of all possible measurements of a system, relative to its initial preparation. This maximization problem is additionally constrained by a phase condition that vanishes under measurements. Specifically, enforcing a vanishing U(1)-valued phase constraint leads to standard quantum mechanics, while a vanishing Spin^c(3,1)-valued phase constraint extends the theory to relativistic quantum mechanics and to quantum gravity. The latter scenario derives the metric tensor as an operator via a double-copy mechanism applied to the Dirac current. Significantly, this solution is consistent exclusively in 3+1-dimensions as all other dimensional configurations lead to fundamental obstructions. Finally, the solution uniquely incorporates the SU(3)xSU(2)xU(1) symmetries of the Standard Model. This framework seamlessly integrates fundamental concepts from quantum mechanics, relativistic quantum mechanics, quantum gravity, the dimensional specificity of spacetime, and particle physics gauge symmetries as the solution to a simple entropy optimization problem.

In vitro cancer cell cytotoxicity (IC50 values) of (E)-3-(4’-methylbenzylidene)-4-chromanone (IIIb) showed >50.0 decreases in comparison to those of the respective tetralone derivative (IIIc). On the other hand, such a decrease was not observed in the analogous 4-OCH3 (IIc and IIIc) derivatives. Since the compounds can be considered cyclic chalcone analogs, kinetics and diastereoselectivity of non-enzyme catalyzed reactions with reduced glutathione (GSH) and N-acetylcysteine (NAC) of IIIb and IIIc were investigated to assess the possible role of thiol-reactivity in the increased cytotoxicity of IIIb. Reactivity of the compounds and stereochemical outcome of the reactions were evaluated using high-pressure liquid chromatography-mass spectrometry (HPLC-MS). Molecular modeling calculations were performed to rationalize the observed differences in the thiol-reactivities of the chromanones (III) and the previously investigated tetralones (II). The results indicated possible role of spontaneous thiol-reactivity of compounds III in their recorded biological effects.

Preeclampsia is a complex pregnancy-related hypertensive disorder which poses significant risks for both maternal and fetal health. Preeclampsia affects 5-8% of the pregnancies in the United States, causing a significant public health and economic burden. Despite extensive research, the etiology and pathogenesis of preeclampsia remain elusive, but have been correlated with maternal conditions such as obesity. In the past decades, the incidence of preeclampsia increased along with the prevalence of obesity among women of reproductive age. Maternal obesity has been shown to negatively affect pregnancy in almost all aspects. However, the precise mechanisms by which obesity influences preeclampsia are unclear. Ankyrin repeat and SOCS Box Containing protein 4 (ASB4) is an E3 ubiquitin ligase that can promote the degradation of a wide range of target proteins. ASB4-null mice display a full spectrum of preeclampsia-like phenotypes during pregnancy including hypertension, proteinuria, and decreased litter size. Furthermore, maternal obesity induced by a high fat diet aggravates preeclampsia-like phenotypes in pregnant mice lacking ASB4. Variants in the ASB4 gene have been associated with obesity in humans, and a functional connection between the ASB4 gene and obesity has been established in mice. This review discusses the connections between preeclampsia, obesity, and ASB4.

Exosomes are small extracellular vesicles produced by almost all cell types in the human body and exosomal microRNAs (miRNAs) are small non-coding RNA molecules that are known to serve as important biomarkers for diseases such as cancer. Given that the upregulation of miR-106b is closely associated with several types of malignancies, the sensitive and accurate detection of miR-106b is important but difficult. In this study, a surface acoustic wave (SAW) biosensor was developed to detect miR-106b isolated from the cancer cells based on immunoaffinity separation technique using our unique paddle screw device. Our novel SAW biosensor could detect a miR-106b concentration as low as 0.024 pM in a linear range from 0.1 pM to 1.0 μM with a correlation coefficient of 0.9939. Additionally, we were able to successfully detect miR-106b in total RNA extracted from the exosomes isolated from the MCF-7 cancer cell line, a model system for human breast cancer, with performance comparable to commercial RT-qPCR methods. Therefore, the exosome isolation by paddle screw method and the miRNA detection using the SAW biosensor has the potential to be used in basic biological research and clinical diagnosis as an alternative to RT-qPCR.

Colloidal quantum dots (CQDs) are valuable for their potential applications in optoelectronic devices. However, they are susceptible to thermal degradation during processing and while in use. Mitigating thermally induced sintering, which leads to absorption spectrum broadening and undesirable changes to thin film electrical properties, is necessary for the reliable design and manufacture of CQD-based optoelectronics. Here, low temperature metal-oxide atomic layer deposition (ALD) was investigated as a method for mitigating sintering while preserving the optoelectronic properties of mercury telluride (HgTe) CQD films. ALD-coated films are subjected to temperatures up to 160oC for up to 5 hours and alumina (Al2O3) is found to be most effective at preserving the optical properties, demonstrating the feasibility of metal-oxide infilling to protect against sintering. HgTe CQD film electrical properties were investigated before and after alumina ALD in-filling, which was found to increase the p-type doping and hole mobility of the films. The magnitude of these effects depended on the conditions used to prepare the HgTe CQDs. With further investigation into the interaction effects of CQD and ALD process factors, these results may be used to guide the design of CQD-ALD materials for their practical integration into useful optoelectronic devices.

In vertical coordinates, (x,y,z), the gradient Richardson number Ri=N^2⁄S^2 is the square of the ratio between buoyancy frequency N and vertical-shear amplitude S, where N^2=-(g⁄ρ) ∂ρ⁄∂z and S^2=(∂u⁄∂z)^2+ (∂v⁄∂z)^2, with ρ potential density, (u,v) the horizontal velocity components and g gravity acceleration, so that a decrease in stratification brings a decrease in dynamic stability and vice versa. In the isopycnic coordinate system, (x,y,ρ), however, Ri=M^2⁄〖S_ρ〗^2 , is the ratio between 〖M^2≡N〗^(-2) and the squared diapycnal shear 〖S_ρ〗^2=(ρ⁄g)^2 [(∂u⁄∂ρ)^2+ (∂v⁄∂ρ)^2 ], so a decrease in stratification leads to an increase in dynamic stability and vice versa. The apparently different role of stratification arises because S and S_ρ are related through the stratification itself, S_ρ=S⁄N^2 or, equivalently, τ=〖t_o〗^2⁄t_d , which is interpreted as a natural oscillation time τ≡S_ρ that equals the buoyancy or oscillation time t_o=N^(-1) normalized by the ratio t_o⁄t_d , where the deformation time is t_d=S^(-1). Here we follow simple arguments and use field data from three different situations (island shelf-break, Gulf Stream and Mediterranean outflow) to endorse the usefulness of the isopycnal approach. In particular, we define the reduced squared vertical σ^2= S^2-N^2 and reduced squared diapycnal shear 〖σ_ρ〗^2= 〖S_ρ〗^2-M^2, which are positive for unstable conditions and negative for stable conditions. It turns out that Ri and σ^2 remain highly variable for all stratification conditions; in contrast, the mean 〖σ_ρ〗^2 values display a univocal tendency, its magnitude decreasing with stratification. We propose 〖σ_ρ〗^2 and 〖S_ρ〗^2 to be good indexes for the occurrence of effective mixing under high stratification conditions.

Glioblastoma is a highly aggressive brain tumor and is considered to be the most common primary one. Recurrence after treatment is a major problem. The recurrence of GBM is related to different cellular mechanisms and molecular signaling. Therapies to prolong survival are not completely effective. Epigenetics and non-coding genetic elements play a crucial role in gliomagenesis. Non-coding RNAs are novel regulatory RNAs that play key roles in different physiological processes such as gene regulation, cell differentiation, and proliferation. Interestingly, some LncRNAs have a tumor suppressor role while others are oncogenic. In this review article, we are going to illustrate the role of a well-known lncRNA HOX transcript antisense intergenic RNA (HOTAIR) in glioma and highlight the possible functions in glioma in both pre-clinical and clinically evident studies.

High consequence pathogens such as Ebola, Marburg and Lassa viruses are handled in maximum containment Biosafety Level 4 (BSL-4) laboratories. Genetic material is often isolated from such viruses and subsequently removed from BSL-4 for a multitude of downstream analyses using readily accessible technologies and equipment available at lower biosafety level laboratories. However, it is essential to ensure that these materials are free of viable viruses before removal from BSL-4 to guarantee sample safety. This study details the in-house procedure used for validating the inactivation of Ebola, Marburg and Lassa virus cultures after incubation with AVL lysis buffer (Qiagen) and ethanol. This study’s findings showed no viable virus was detectable when high-titer cultures of Ebola, Marburg, and Lassa viruses were incubated with AVL lysis buffer for 10 minutes, followed by an equal volume of 95% ethanol for 3 minutes, using a method with a sensitivity of ≤0.8 log10 TCID50 as the limit of detection.

The iron roughneck is an automated equipment utilized for the connection and removal of drilling tools. This paper presents the design of an integrated iron roughneck, providing a detailed introduction to its clamp body structure, along with an analysis of its structural characteristics and performance requirements. The study delves into the integration mode and working characteristics of the clamping mechanism and spin buckle mechanism for the integrated upper clamp body structure of the iron roughneck. Additionally, this paper conducts an in-depth theoretical study on the spin buckle mechanism. Firstly, it analyzes the actual working condition of the spin buckle roller from two perspectives: contact theory and rolling friction theory, determining the structural form of the spin buckle roller. Secondly, it investigates the relative displacement between the spin buckle mechanism and the drilling tool, proposing a design method for the floating device mounted on the spin buckle roller and establishing the kinematic equation of the spin buckle roller under the influence of the floating device. Furthermore, the kinematic equations of the spin buckle roller under the influence of the floating device are established. Finally, a dynamics simulation experiment is performed to simulate the working process of the spin buckle mechanism under actual working conditions, analyzing the dynamics and kinematics of the spin buckle mechanism and obtaining the relevant parameter curves of the spin buckle mechanism and drilling tools. Through data comparison and analysis, the correctness of the theoretical analysis results and the rationality of the performance and structure of the spin buckle mechanism are verified.

The emergence of antibiotic-resistant Campylobacter jejuni, a leading cause of gastroenteritis worldwide, presents a significant public health challenge requiring vigilant surveillance and disease control. This study aimed to characterize C. jejuni strains isolated in Romania from 2017-2020, focusing on genetic diversity, virulence, and antibiotic resistance determinants. The isolates underwent phenotypical testing, PCR, and antibiotic resistance assessment using Disc Diffusion Kirby–Bauer for ciprofloxacin, nalidixic acid, erythromycin, and tetracycline. Genetic analysis identified resistance and virulence genes, point mutations, and performed sequence typing (7-gene MLST) to determine genetic relatedness. Results indicated substitutions at position 86 in the amino acid sequence or position 257 in the nucleotide sequence of the gyrA gene in 47 fluoroquinolone-resistant isolates. Additionally, mutations in the rRNA23S gene at positions 2074 and 2075, associated with macrolide resistance, were found in 12 of the 66 isolates. Allelic profiles generated 38 sequence types (STs), including three new STs not present in the reference database. The sequence data analysis revealed a genetically diverse C. jejuni population with a weak clonal structure. This study provides crucial insights into the genetic diversity and antibiotic resistance of C. jejuni strains in Romania, highlighting the need for ongoing surveillance and control measures.

Idiopathic pulmonary fibrosis [IPF] is a chronic progressive disease characterised by the accumulation of scar tissue in the lung parenchyma. It primarily occurs in middle-aged and elderly adults and results in significant morbidity and mortality worldwide. The disease occurs due to repetitive lung epithelial injury, subsequent fibroblast activation and myofibroblast differentiation, resulting in excessive extracellular matrix deposition. This leads to scar formation and subsequent loss of lung function. Current treatment options for patients with IPF include the two anti-fibrotic drugs, pirfenidone and nintedanib, which can slow disease progression; however, there are currently no known cures for the disease. As such, novel methods and drug targets are warranted. In this review, we provide an up-to-date account of the importance of specific cytokines and the potential role of regulatory immune cells. We discuss their role in the pathogenesis of IPF and address some of the key gaps in knowledge.

Wicked problems, such as climate change, systemic poverty, and healthcare inequalities, rep- resent the most pressing and intractable challenges facing society today. We propose a novel approach that leverages complex systems theory as a comprehensive framework for understanding and tackling these challenges. By applying concepts such as state space analysis, attractors, and nonlinear dynamics, we offer a sophisticated toolkit for mapping the intricate web of interactions defining wicked problems and exploring potential interventions. Our approach moves beyond tradi- tional reductionist methods, embracing the inherent complexity and dynamism of these issues. We demonstrate how this framework can lead to more nuanced, adaptive, and effective strategies for addressing persistent societal problems. Despite the prevalence of wicked problems and the avail- ability of complex systems theory, practical applications of this approach remain uncommon. This paper aims to bridge this gap, illustrating the potential of complex systems theory to transform our engagement with intractable problems and pave the way for more robust, holistic solutions. By synthesizing insights from mathematics, physics, and social sciences, we present a transdisci- plinary approach that promises to revolutionize how we conceptualize and address society’s most challenging issues.

An efficacious treatment of H. pylori infection is cornerstone for the global control of the diseases caused by this bacterium. Continuous epidemiologic surveillance of susceptibility of H. pylori to the antibiotics recommended for its eradication is highly recommended. This study aimed to determine the antimicrobial susceptibility pattern of 651 isolates from five different collections isolated between 1996 to 2008 in México City. The susceptibility profile of H. pylori isolates was determined by the E-test strips for each antibiotic (amoxicillin, clarithromycin, metronidazole, and tetracycline). Antimicrobial susceptibility testing showed a very high proportion of H pylori strains susceptible to amoxicillin, clarithromycin, and tetracycline (94.5%, 95%, and 99.5 %, respectively). In contrast, a high proportion (95%) of isolates was resistant to metronidazole. Notably, the proportion of susceptible/resistant strains to the 4 antibiotics over 5 consecutive time periods remained stable over time. Despite a wide use of amoxicillin and clarithromycin in the general population, the H pylori high susceptibility to these 2 antibiotics has been preserved during more than a decade. The high prevalence of resistance to metronidazole in H. pylori strains in our population compromises its use in the empirical treatment of H. pylori infection.

The diel variations of viruses (< 0.2 μm), picoplankton (0.2—2 μm; heterotrophic bacteria, Syn-echococcus spp., Prochlorococcus spp. and picoeukaryotes) and nanoplankton (2—20 μm; hetero-trophic nanoflagellates and pigmented nanoflagellates) were investigated for 2 days with about 4 hours of temporal sampling in spring 2024 in coastal surface waters of the subtropical western Pacific. A period of wind change associated with rain and increased turbulence, disrupted diel patterns of the overall microbial communities during the second cycle. The abundance of bacteria did not follow a consistent diel pattern, while viral abundance positively correlated with bacterial abundance. Synechococcus spp. and Prochlorococcus spp. grew during the light period and with peak abundance at night, exhibited marked diel variability, however, opposite patterns were observed in picoeukaryotes. According to Synechococcus spp. and Prochlorococcus spp. diel changes, nano-flagellate grazing could control their abundances and may explain temporally varying picocyanobacteria abundances. As we observed in the culture experiments, the results showed a significant increase in picoeukaryotic abundance from noon to nighttime, and a decrease in bacterial abundance during nighttime, to show the prey-predator cycle. Our study suggests picoeukaryotes could serve as bacteria predators by being mixotrophs. Future studies aiming to understand the interactions between prokaryotes and picoeukaryotes within marine microbial communities should take these differences into account.

The Hyper-Torus Universe Model (HTUM) proposes a novel framework to unify quantum mechanics, cosmology, and consciousness. This paper introduces HTUM's core concept: a higher-dimensional hyper-torus encompassing all possible states of existence. HTUM suggests that the universe functions as a quantum system where all outcomes are inherently connected, with consciousness playing a significant role in actualizing reality. The model introduces several key innovations, including the universe's 4-dimensional toroidal structure (4DTS), providing a new geometric interpretation of spacetime. HTUM presents dark matter and dark energy as nonlinear probabilistic phenomena within this toroidal framework, offering a unique perspective on their nature and interactions. The model proposes a mechanism for wave function collapse through universal self-observation, bridging quantum mechanics and gravity. It introduces a Topological Vacuum Energy Modulator (TVEM) function, offering a potential resolution to the cosmological constant problem. Furthermore, HTUM integrates consciousness as a fundamental aspect of the universe, influencing quantum state actualization and potentially resolving the hard problem of consciousness. The model explores the implications of a timeless singularity and the emergence of time as a product of causal relationships within the toroidal structure. This framework addresses critical challenges in modern physics, including the nature of quantum entanglement, the origin and fate of the universe, and the relationship between mind and matter. The paper discusses the mathematical formulation of HTUM, its implications for quantum mechanics and cosmology, and its potential to bridge the gap between science and philosophy. We present detailed predictions for the cosmic microwave background (CMB) power spectrum, gravitational wave signatures, and large-scale structure formation, demonstrating how HTUM differs from the standard ΛCDM model. Our analysis reveals distinctive oscillatory patterns in the relative difference between HTUM and ΛCDM predictions, with deviations reaching up to ±20% at certain scales. The paper also explores the unification of fundamental forces within the HTUM framework, proposing novel approaches to particle physics and quantum field theory. It introduces the concept of unified mathematical operations, suggesting a more holistic approach to mathematical thinking that aligns with the model's interconnected view of the universe. Additional testable predictions and proposed experimental approaches are discussed, including advanced space-based tests and laboratory experiments probing quantum gravity effects. These specific, quantifiable predictions offer multiple avenues for empirical validation, highlighting HTUM's potential to be distinguished from ΛCDM and other alternative cosmological models. HTUM represents a significant new perspective in our understanding of the universe, inviting further research and exploration into the nature of reality, consciousness, and the fundamental structure of the cosmos. By providing a comprehensive framework that unifies various aspects of physics, cosmology, and consciousness studies, HTUM offers a promising path toward a more complete understanding of our universe.

With the continuous advancement of digital transformation, digital payments are playing an increasingly important role in the financial industry. This study aims to utilize machine learning models to predict and analyze digital payment behavior. Initially, the background and significance of digital payments in the financial sector are introduced. Subsequently, the current status and trends of traditional digital payment distribution are reviewed, alongside related work on digital payment behavior prediction. Methodologically, principles and applications of machine learning models such as logistic regression, decision trees, and random forests are elaborated, along with experimental design and data preprocessing methods. The experimental results and discussion section illustrates the performance of each model in digital payment prediction and explores their impact on credit decisions. This exploration equips financial institutions with more effective user behavior analysis and risk management tools, thereby fostering future development and application of digital payment technologies.

The purpose of this narrative review is to provide an overview of the latest literature on bariatric and metabolic surgery for diabetes mellitus type II and obesity (diabesity) and to discuss its implications for future research and clinical practice.

Plant activators have emerged as promising alternatives to conventional pesticides for crop disease manage-ment due to their unique mode of action. By priming the plant's innate immune system, these compounds can induce systemic acquired resistance against a broad spectrum of pathogens without directly inhibiting their proliferation. Key advantages of plant activators include prolonged defense activity, lower effective dosages, and negligible risk of developing pathogen resistance. Among the various defensive pathways tar-geted, the salicylic acid (SA) signaling cascade has been extensively explored, leading to the successful devel-opment of commercial activators like benzothiadiazole for widespread application in crop protection. While the action sites of many SA-targeting activators have been preliminarily mapped to different steps along the pathway, a comprehensive understanding of their precise mechanisms remains elusive. This review provides a historical perspective on plant activator development and outlines diverse screening strategies employed across multiple levels, from whole-plant bioassays to molecular and transgenic approaches. We expound on the intricate components, biological relevance, and regulatory circuits governing the SA pathway, while criti-cally examining the structural features, bioactivities, and proposed modes of action of classical activators such as benzothiadiazole derivatives, salicylic acid analogs, and other small molecules. Insights from field trials as-sessing their practical applicability are also discussed. Furthermore, we highlight the current status, challenges, and future prospects in the realm of SA-targeting activator development globally, with a focus on recent en-deavors in China. Collectively, this comprehensive review aims to synthesize existing knowledge and provide a roadmap for future research toward developing more potent and mechanistically understood plant activa-tors that fortify crop immunity against disease.

In recent years, urbanization and industrialization have significantly increased the levels of outdoor noise pollution, affecting the quality of life in residential areas. In Uzbekistan, rapid development in urban centers has led to heightened concerns about the impact of noise on residents' health and well-being. Noise pollution can result from various sources, including traffic, construction, and industrial activities, causing disturbances and potential health issues such as stress, sleep disorders, and cardiovascular problems. Addressing this issue is crucial for creating a healthier living environment. This article explores effective strategies for mitigating the impact of outdoor noise on residential buildings in Uzbekistan.

At the end of the dry season in early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass burnings period, smoke aerosols blanket the whole regions and were transported and dispersed by predominant westerly and south westerly winds to southern China, Taiwan and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperature making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burnings period to the exposed population and their health impact. The Weather Research Forecast- Chemistry (WRF-Chem) model was used to predict the PM2.5 concentration over the simulating domain and health impacts are then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia and Vietnam. Using the health impact based on log-linear concentration response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 314 deaths respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact and associated economic cost of agricultural waste burnings in Southeast Asia at the end of the dry season. And hence policy makers should take these into account to design measures to reduce the negative impact of widespread burnings on exposed population in the region.

The enzyme acetylcholinesterase (AChE) plays a crucial role in the termination of nerve impulses by hydrolyzing the neurotransmitter acetylcholine (ACh). The inhibition of AChE has emerged as a promising therapeutic approach for the management of neurological disorders such as Lewy body dementia and Alzheimer's disease. The potential of various compounds as AChE inhibitors has been investigated. In this study, we evaluated the impact of natural compounds of interest on the intrinsic deformability of human AChE using computational biophysical analysis. Our approach incorporates classical dynamics, elastic networks, statistical potentials, energy frustration, and volumetric cavity analyses. The results revealed that cyanidin induced significant changes in the flexibility and rigidity of AChE, especially in the distribution and volume of internal cavities, compared to model inhibitors such as TZ2PA6, and through a distinct biophysical-molecular mechanism from the other inhibitors considered. These findings suggest that cyanidin could offer potential mechanistic pathways for future research and applications in the development of new treatments for neurodegenerative diseases.

Obstructive sleep apnea (OSA) often goes unrecognized despite common symptoms such as excessive daytime sleepiness, fatigue, and impaired quality of life (QoL). CPAP is the gold standard treatment for OSA, but optimal daily usage and time needed for observable effects remain unclear. This study aimed to investigate the short-term effects of CPAP on daytime sleepiness and QoL in patients with severe OSA. Medical records were collected from 87 patients with severe OSA who initiated CPAP therapy. Also, validated questionnaires were used before and after one month of CPAP to analyze QoL - the Calgary Sleep Apnea Quality of Life Index (SAQLI), the Cues to CPAP Use Questionnaire (CCUQ), and daytime sleepiness - the Epworth Sleepiness Scale (ESS). Multiple regression analysis was conducted to identify predictors of CPAP usage. Of the total participants aged 55.6±12.5, 77% were males, and 62% were CPAP adherent. Reductions in daytime sleepiness (ESS) were noted, as well as improvements in both overall QoL (SAQLI) and specifically in the domains of daily functioning, social interactions, emotional well-being, and symptom perception. Important cues for CPAP usage recognized by patients were physicians’ instructions and physicians’ worry regarding patients' condition. Furthermore, multiple regression revealed higher SAQLI scores and lower ESS scores as positive predictors of CPAP usage, along with lower AHI after one month of CPAP being associated with sufficient adherence.

The signs and symptoms of Long COVID can be explained by a shortage of blood in the body and a resulting deficient blood flow through nearly all organs. This shortage arose during the acute phase of COVID19 by an increased breakdown of haematocytes, to which the liver responds by reducing the production of plasma. In order to prevent a too large decrease in haematocrit. In order to ensure the perfusion of organs that are directly necessary for survival, the body takes the emergency measure of diverting blood from other organs and tissues. The perfusion of the blood-producing organs is also affected by this distribution measure, which hinders the smooth recovery of the total blood volume. The body is stuck in this vicious circle: a shortage of circulating blood hinders the recovery of blood production. This explains the long duration of Long COVID. My proposed treatment of Long COVID focuses on the recovery of the correct volume of blood in the body of the right composition by the intravenous administration of donor blood products, starting with albumin concentrate. A trial treatment can be performed in any hospital without much additional preparations, and has a lower associated risk for the patient than analysing the total blood. A diagnosis ex juvantibus, by therapeutic response, is therefore preferable. I suspect that we will find a haematocrit value at the high extreme of the reference range, and an albumin value at the low extreme of the reference range in most Long COVID patients before the start of the treatment, because the liver can not keep up with the recovery of the red bone marrow.

Substance abuse is a significant public health issue both globally and nationally. Substance abuse involves the detrimental or risky consumption of psychoactive substances, posing a significant global issue, particularly among the youth. In India, cannabis abuse is a major concern. Cannabis is consumed legally in many states as Bhang, also known as marijuana or weed, while Charas and Ganja are illegal under both international drug conventions and the Indian NDPS Act of 1985. The Cannabis users are at great risk of developing Cannabis use disorder which is a pattern of problematic cannabis use leading to clinically significant impairment or distress. It is the most widely used illegal substance worldwide, showing a high prevalence in India.

Conclusions: CGP do not substantially differ between initial tumor vs tumor recurrence and recurrent thymomas vs non-recurrent thymomas. Cell-cycle control genes alterations are associated with an early recurrence after thymectomy. Multiple target therapies are potentially available by performing a comprehensive CGP, suggesting that a precision medicine approach on these patients could be further explored.

Background: Low back pain (LBP) is a major cause of disability globally, and the diagnosis of LBP is challenging for clinicians. Objective: This study aimed to assess the accuracy level of arti-ficial intelligence as a Clinical Decision Support System (CDSS) called Therapa compared to MRI in predicting lumbar disc herniated patients. Methods: One hundred low back pain patients aged ≥18 years old were included in the study. The study was conducted in 3 stages, at first, a case se-ries was conducted by matching MRI and Therapha diagnosis for 10 patients. Subsequently, Delphi methodology was employed to establish a clinical consensus. Lastly, to determine the ac-curacy of the newly developed software, a cross-sectional study was undertaken, involving 100 patients. Results: The software showed a significant diagnostic accuracy with the area under the curve in the ROC analysis determined as 0.84 with a sensitivity of 88% and a specificity of 80%. Conclusion: The study’s findings revealed that CDSS using Therapha has a reasonable level of ef-ficacy, and this can be utilized clinically to acquire faster and more accurate screening of patients with lumbar disc herniation.

This paper presents a Cartesian model of sustainability by a novel integration of Circular Economy principles and ESG (Environmental, Social, and Governance) criteria to explicitly establish a clear path for closing the loops of negative social and environmental externalities. As global sustainability transformations accelerate, they bring both opportunities and inherent financial risks and social uncertainties. Historically, economic development has often been achieved at the expense of environmental balance. The contemporary challenge is to attain a dynamic equilibrium between natural and socio-economic systems. We introduce an integrated, multidisciplinary, and dynamic framework for studying and managing sustainability transitions. Our innovative 4-quadrant framework utilizes a Cartesian coordinate system to map the impacts of various business models on natural and socio-economic systems, spanning from linear open-loop to circular closed-loop ESG models. The framework is data-driven, employing normalized coordinates (-1 to 1) to facilitate empirical analysis and the establishment of temporal Key Performance Indicators. By integrating the Human Development Index within ecological limits, our model targets regenerative development that harmonizes human progress with planetary boundaries. This versatile and robust framework serves as a practical tool for businesses, households, organizations, and policymakers to navigate the complexities of sustainable development, promoting innovation and fostering a just transition towards regenerative practices. Our approach provides a comprehensive roadmap for achieving high human development within the planet's ecological limits, contributing significantly to the broader discourse on sustainability science and management.

While there are millions of reptile images available online, they are not well organized and not easily findable, accessible, interoperable, or reproducible (FAIR). More importantly, they are not standardized and thus hardly comparable. Here we present a reference database of more than 14,000 standardized images of 1,045 reptile species (969 lizard and 76 snake species), that are based on preserved specimens in 20 different collections, including 533 type species of genera and type specimens of 72 species. All images were taken with standardized views, including dorsal and ventral body shots as well as dorsal, ventral, and lateral views of the heads and other body parts. Although only 11 out of the 20 collections are cross-referenced in Vertnet, some others are indexed in GBIF, and this fraction will certainly grow in the near future. The utility of this and similar image collections will further grow with additional material and further cross-referencing, e.g., to DNA sequence databases or citizen science projects. The images are searchable and freely available on Morphobank.org (Project 5121) and on Figshare.com.

This article raise a topic of critical examination of polypropylene, a key polymeric material, and its extensive application within the automotive industry, particularly focusing on the manufacturing of brake fluid reservoirs. The study aims to enhance the understanding of polypropylene's behavior under mechanical stresses through a series of laboratory destruction tests and numerical simulations, emphasizing the Finite Element Method (FEM). A novel aspect of this research is the introduction of the PEAK parameter, a groundbreaking approach designed to assess the material's resilience against varying states of strain, known as triaxiality. This parameter facilitates the identification of critical areas prone to crack initiation, thereby enabling the optimization of component design with a minimized safety margin, which is crucial for cost-effective production. The methodology involves conducting burst tests to locate crack initiation sites, followed by FEM simulations to determine the PEAK threshold value for the Sabic 83MF10 polypropylene material. The study successfully validates the predictive capability of the PEAK parameter, demonstrating a high correlation between simulated results and actual laboratory tests. This validation underscores the potential of the PEAK parameter as a predictive tool for enhancing the reliability and safety of polypropylene automotive components. The research presented in this article contributes significantly to the field of material science and engineering by providing a deeper insight into the mechanical behavior of polypropylene and introducing an effective tool for predicting crack initiation in automotive components. The findings hold promise for advancing the design and manufacturing processes in the automotive industry, with potential applications extending to other sectors.

The Ethnographic Museum in Dubrovnik holds an extensive textile collection that includes a range of dress and costume from Croatia and neighbouring countries. Until recently, the costumes were displayed on mannequins created by the academic artist Zvonimir Lončarić (1927–2004). His sculptures are expressive forms constructed from terracotta, fibreglass, wood, metal, acrylic paint and other materials selected for their visual appeal. Due to their importance, the museum considered the mannequins as protected artworks in the permanent exhibition, however, they had a harmful effect on the costumes displayed. In 2018, after completing a series of conservation-restoration projects within the collection, it was decided to replace the existing mounts with new, museum–quality mannequins. Two project–based learning workshops were organised, led by a team of textile conservators from the University of Dubrovnik and the Croatian Conservation Institute, in cooperation with the curator of the Ethnographic Museum. This case study highlights the challenges of exhibiting ethnographic costumes by discussing past presentation methods and how new solutions have been implemented conforming with the modern conservation-restoration profession. The new solutions consider ethics, decision–making processes, and the understanding of contemporary materials and methodology.

Laser Powder Bed Fusion (L-PBF)-based manufacturing is a growing area of research, with a particular focus on evaluating constraints in printed products. This research emphasises the importance of considering various factors—including mechanical properties and support structures—that influence the final product during the design phase. Specifically, the design of microchannel heat exchangers is highlighted, where all constraints are critical. This article will present a method for analysing channel pressure limitations and report findings about mechanical properties loss from examining tube porosity. This includes a summary of results and the establishment of an experimental device system.

Hyperspectral imaging data holds great potential for various stages of the mining life cycle in active and abandoned mines. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite im-agery yields high spectral resolution, high signal-to-noise ratio (SNR), and global availability with breakthrough satellite sys-tems like EnMAP, EMIT, and PRISMA, limited spatial resolution poses challenges for mining sectors, which require decimeter- to centimeter-scale spatial resolution for applications such as reconciliation, ore/waste estimates, geotechnical assessments, and en-vironmental monitoring. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the pit/ mine scale, with the capability for frequent, user-defined re-visit times. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers to detect different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we review of applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging in or appropriate to the mining sector, especially for hyperspectral VNIR-SWIR UASs. If directly applicable, draw on previous insights derived from airborne, satellite, and ground-based imaging systems. We also discuss common practices for UAS survey planning and sampling considerations for interpretation.

Complicated grief (CG) predicts decreased mental health over time. Furthermore, feeling connected to nature (CN) is positively associated with beneficial mental health outcomes, such as psychological wellbeing and perceived psychological resilience. Thus, we hypothesized that CN moderates the association between general grief or CG and negative mental health for bereaved people. Further, we hypothesized that one’s physical exposure to nature—that is, estimated time spent in nature and greenness (i.e., vegetation) surrounding one’s residential area—might moderate the association between general grief or CG and negative mental health for bereaved people. To test these hypotheses, we sampled 153 participants who experienced the death of a close other by COVID-19 infection. Participants reported CG, general grief, anxiety symptoms, depression symptoms, CN, estimated time spent in nature, and residential area postal code via a single online survey. We estimated greenness surrounding participants’ residential areas using their self-reported 5-digit U.S. postal code. Cross-sectional analyses indicated that, as predicted, CN attenuated the association between CG and depression, but only trended toward moderating the association between CG and anxiety and did not moderate the associations between general grief and depression or anxiety. Other variables related to the experience of nature—the estimated time an individual spends in nature and the greenness surrounding one’s residential area—did not moderate the association between general grief or CG and depression or anxiety. We thus conclude that a sense of feeling connected to nature—not simply spending more time in nature or being surrounded by nature—may serve an important role in the mental health status of people experiencing complicated grief, perhaps because CN replenishes general belonging when someone significant has passed away.

Background/Objectives: Encouraging results reported of Platelet-Rich Plasma (PRP) treatment for knee osteoarthritis (KOA). The present retrospective study reports the efficacy and safety of a high dose of neutrophile and red blood cell-depleted PRP to treat 212 patients with KOA. Methods: 212 consecutive patients diagnosed with Kellgren-Lawrence (KL) grading 1-3 KOA chronic knee pain for at least 1 year were treated with 3 injections at 15-day intervals with a high dose of neutrophil-depleted PRP (4 billion platelets). Clinical outcomes were retrospectively recorded as a percentage of responders at 3,6, and 12-month follow-up, following the OMERACT-OARSI criteria. Pain through VAS score and WOMAC score have also been recorded. Results: 4ml of PRP containing 4X109 platelets were obtained by single spin centrifugation and injected intra-articular into each patient with no pre-activation. The overall responder rate of patients responding to OMERACT-OARSI criteria at 3,6,12 months was 68.9%, 72,7% and 70,6%. There was a significant improvement in VAS and WOMAC scores at 3-, 6- and 12-month follow-up compared to the pre-treatment value (p&lt; 0.01). The lowest VAS score was observed at 6 months overall and in all three-grade KL groups. KL2 groups showed the best results regarding pain reduction and WOMAC score at 6 months (p&lt; 0.01). Conclusions: a high dose of neutrophil-depleted PRP is an effective treatment for KL1-3 KOA. It provides symptomatic relief, can potentially reduce disease progression, and has sustained effects for up to 12 months.

Both, in developed and developing countries, atmospheric pollution with particulate matter (PM) remains an important issue. Despite the health effects of poor air quality, studies on air pollution are often limited by the high costs of continuous monitoring and the need of extensive sampling. Furthermore, these particles are often enriched in potentially toxic trace elements and organics pollutants. This study evaluates both, the composition of atmospheric dust accumulated during a certain time-span on leaves of Hedera helix and Senecio cineraria, as well as the potential to use them as bio-monitors. The test plants were positioned nearby automatic air quality monitoring stations at four different sites with respectively high, moderate and low traffic intensity. Gravimetric deposition of PM10 and PM2.5 on leaves was consistent with data recorded by the monitoring stations and related to the weather conditions reported by Argentina´s National Meteorological service. To determine the presence of trace elements enriching the PM deposited on leaves, two analytical techniques were applied, XRF (not destructive) and ICP (destructive). The results indicated that only in the unpaved street location (site 2), PM10 and PM2.5 concentrations in the air exceeded WHO guidelines. However, several trace elements were found enriching PM deposited on leaves from all sites. Predominantly, increased concentrations of Cd, Cu, Ti, Mn, Zn and Fe were found, which were associated to construction, traffic and unpaved street sources. Furthermore, based on its high capability to sequester PM and trace elements Senecio cineraria can be take into consideration to be adopted as a bio-monitor or even for PM mitigation.

In recent decades, there has been a rising demand for anti-aging interventions aimed at postponing or potentially reversing indicators of skin aging. The use of collagen-based nutraceutical supplements has gained popularity as they have shown promise in enhancing skin health and reducing signs of aging. The aim of this randomized, placebo-controlled, blinded study was to investigate the effects of 2.5 g COLLinstant® LMW, a novel cosmeceutical containing low molecular weight (≤ 1000 Da) collagen peptides, on skin aging and health. The trial was conducted in 80 healthy women aged 30 years and older. They received a daily oral dose of either the food supplement (n = 40) or placebo (n = 40) for six weeks. Skin assessment was performed based on validated objective methods, such as Visioface 1000D (skin wrinkling), cutometry (elasticity and fatigue) and corneometry (skin hydration) at baseline (T0), and at week 6 (T6). After 6 weeks, participants that received collagen had significant improvements in biometric skin wrinkle parameters from baseline, with a reduction in volume by 46%, in area by 44%, and in depth by 9%, along with a greater increase in skin moisturization (by 34%) than those in the placebo group (p &lt; 0.001). The food supplement did not significantly modify skin firmness or fatigue and had only slight beneficial effects on skin elasticity. The investigational product was well tolerated. The observed effects aligned closely with the subjective assessments reported by study participants. The study provides substantiated evidence supporting the efficacy of low molecular weight collagen peptides in restoring altered skin biometric parameters, as objectively assessed. Thus, regular supplementation with this nutraceutical may contribute to achieving smoother and more radiant skin.

This paper presents the development of an analytical model of Microelectromechanical Systems (MEMS) internal vibrating ring gyroscope. The internal ring structure consists of eight semicircular beams that are attached to the externally placed anchors. The research work analyses the vibrating ring gyroscope inplane displacement behavior and the resulting elliptical vibrational modes. The elliptical vibrational modes appear as pairs with the same resonance frequency due to the symmetric structure of the design. The analysis commences by conceptualizing the ring as a geometric structure with a circular shape, possessing specific dimensions such as thickness, height, and radius. We construct a linear model that characterizes the vibrational dynamics of the internal vibrating ring. The analysis develops a comprehensive mathematical formulation for the radial and tangential displacements in local polar coordinates, considering the inextensional displacement of the ring structure. By utilizing the derived motion equations, we highlight the underlying relationships driving the vibrational characteristics of the MEMS vibrating ring gyroscope. These dynamic vibrational relationships are essential in enabling the vibrating ring gyroscope's future utilization in accurate navigation and motion sensing technologies.

This study aimed to develop a carbon yield model for a Makino bamboo plantation and addressed a monoculture Makino bamboo plantation in central Taiwan. We established a long-term trial to monitor the stand dynamic following thinning. A total of 16 plots were installed based on four thinning treatments, each sharing four plots. After thinning, data were collected from two investigations, resulting in 32 records. We calculated the number of culms (N), mean diameter at breast height (MDBH), and basal area (BA) for each record. An allometric function developed by previous research was used to predict aboveground biomass and to obtain aboveground carbon storage (AGCS). The model used the N, MDBH, and BA with various types (reciprocal and natural logarithm types) as independent variables to predict ln(AGCS) by the stepwise method. According to the Radj2 value, the best predictive models were: ln(ABCS) = -0.004 + 0.820 ln(MDBH) + 1.008 ln(BA), and ln(ABCS) = 7.550 - 0.820 ln(N) + 1.828 ln(BA). From these two models, we found the factors, either BA and MDBH or BA and N, can effectively predict AGCS. It indicated that stand density was critical in affecting AGCS, especially the variable BA.

Since the beginning of the internet era, there has been an explosion of growth in structured data (such as numbers, symbols, and labels) as well as unstructured data (including images, videos, and text). Efficient and accurate mixed query of these two types of data is a key technology to achieve high-quality information retrieval, and it is also a major challenge that needs to be solved urgently in the industry. In this study, we employ an advanced Transformer model that combines strategies and fine-tuning techniques for multi-task learning. Specifically, the model is first pre-trained on a large-scale, general-purpose dataset to learn different types of data representations and basic language comprehension skills. After that, we fine-tuned the parameters of the model to better suit these specific data processing tasks for specific application scenarios, such as image annotation, video content analysis, and structured data query. At the heart of the model is the self-attention mechanism, which allows the model to automatically emphasize the important parts and ignore irrelevant information when processing the input data. In addition, we have introduced task-specific adaptation layers that are designed to add additional processing power to the original Transformer architecture, such as a semantic analysis layer for unstructured text data and a relational extraction layer for structured data. This combination of general pre-training and task-specific fine-tuning allows the model to flexibly process and integrate information from different data sources, improving processing efficiency and accuracy. Experimental results show that the model performs well in a variety of data processing tasks, significantly improves the accuracy and efficiency of information retrieval, and verifies the strong potential and adaptability of large language models in processing mixed data types.

This study delves into the dynamics of 'Variations' and 'Claims' within construction projects, specifically under the FIDIC-Red Book 1999 framework. The study aims to identify, categorize, and devise mitigation strategies for key types of variations and claims aligning with the FIDIC conditions of contract. The research is drawing on inputs from construction industry professionals including contract administrators and project managers, focusing on the MENA region. This choice is driven by the region's extensive adoption of FIDIC standards and its rapidly growing construction sector. Data collection encompassed a questionnaire distributed to 80 industry experts predominantly through interviews that focused on countries like Saudi Arabia, UAE, Kuwait, and Egypt. These locations were chosen to reflect diverse construction practices and the involvement of international firms. Utilizing SPSS-V.25 for statistical analysis, the study uncovers the most prevalent and impactful causes of variations and claims, highlighting the critical need for managerial intervention. A key feature is the integration of scientometric analysis for a quantitative finding. A significant addition to the methodology is the implementation of a k-means clustering analysis. The survey had high internal consistency with a Cronbach's alpha of 0.97, and respondents reported frequent and significant claims like delayed drawings, ambiguous documents, and client changes. The results showed that effective claims management requires clear communication and balanced contracts, while poor design and contract documentation cause variations and claims. Spearman's correlation showed strong positive relationships between certain claim types and causes, emphasizing the importance of dealing with these factors to reduce claims. Most respondents said the survey could predict and reduce claims.

International cooperation and food diplomacy play a pivotal role in addressing global challenges to food security. This study explores the effectiveness of Indonesia's international partnerships and diplomatic strategies in bolstering its food security amidst global uncertainties. The research employs a mixed-methods approach, combining qualitative analysis of policy documents and interviews with key stakeholders, alongside quantitative data on food production and trade. Our findings indicate that Indonesia has benefited significantly from technical and financial assistance through collaboration with organizations such as FAO, ASEAN, and bilateral agreements with countries like Japan and China. These partnerships have facilitated the adoption of advanced agricultural technologies, improved infrastructure, and enhanced human resource capacities. However, challenges remain, including bureaucratic inefficiencies and dependency on food imports, which pose risks to sustainable food security. The study concludes that while international cooperation has provided critical support, Indonesia must further streamline its policy implementation processes and reduce its reliance on imports by fostering local production. Strengthening research and development collaborations and actively participating in global forums are also recommended to ensure long-term resilience and food sovereignty. This research provides valuable insights for policymakers and stakeholders aiming to develop effective strategies to navigate the complexities of global food diplomacy and cooperation.

Advanced persistent threat (APT) attacks are sophisticated and organized attacks commonly motivated by political, financial, and strategic objectives. In order to comprehend their tactics, techniques, and procedures (TTP) and indicators, APT reports are valuable sources. While blue teams typically rely on server logs, firewall rules and user authorizations managed in database tables, attackers have a graph-based mindset. In this work, we propose a framework for discovering and evaluating APTs using graph-based algorithms. Cyber threat intelligence (CTI) was extracted from 40,358 pages of APT reports and transformed into a graph. Centrality, community, and similarity analyses were executed on the graph. As a result, critical and influential APT groups and indicators of compromise (IoC) were discovered. Similar attacks and APT groups were revealed. Analysis results were interpreted to create new strategic CTI that can be utilized in future security operations.

With the widespread use of the Internet of Things, underwater control and monitoring systems for purposes such as ocean data sampling, natural disaster prevention, underwater surveillance, submarine exploration, and the like have become a popular and challenging topic in computers. So far, various topology control and routing solutions have been proposed for these networks. However, as technology expands and applications grow, so does the need for a stable underwater communication platform. On the other hand, underwater communication is associated with challenges such as node mobility, long propagation delays, low bandwidth, limited resources, and high error rates. In this research, for the first time, a topology control platform based on the RPL tree is modelled by applying its structural changes underwater. The proposed RPLUW methods in the case of RPLUWM fixed nodes are introduced to support the mobility of nodes underwater. Flexible objective functions, utilisation of decision-making systems, and application of control schedules in these methods have increased network life, reduced overhead, and increased node efficiency. The simulation results of the proposed method, in comparison with recent methods in this field, show an increase in network efficiency.

The issue of antibiotic resistance represents a significant threat that extends beyond human health, encompassing animal welfare and the sustainability of the natural environment. The inappropriate use of antibiotics, poor sanitation and inadequate control measures, have contributed to the emergence of drug-resistant bacteria, which can spread at the human-animal-environment interface. The documented presence of antimicrobials in agriculture, veterinary medicine and human medicine has convinced all stakeholders of the need to contribute to the development of a "One Health" approach, which recognises the interrelationships between animals, humans and their environment and the need to adopt a common strategy encompassing these sectors to limit the spread of antimicrobial resistance (AMR). Although a number of countries have implemented integrated surveillance systems to monitor antibiotic use and antimicrobial resistance, available data suggest that the use of antibiotics in humans, animals and the environment is increasing worldwide. Consequently, the emergence of antibiotic-resistant pathogens is becoming a recurring concern. This review provides a comprehensive overview of the measures that are necessary to be taken and implemented in order to guarantee global health security.

This study explores the potential of digital technologies for preserving cultural heritage through the case study of the Raya Gopura, an incomplete monument in Melukote, India. Employing a combination of terrestrial photogrammetry, drone-based photogrammetry and terrestrial laser scanning, the research team captured highly detailed 3D models of the structure. This non-destructive approach offers a comprehensive digital record for future research and preservation. Furthermore, for the conjecture for the Raya Gopura two possible purposes: an entrance to a planned fort or a gateway to the temple are perceived through the collective intelligence (CI) approach. These insights inform a conjectural architectural drawing of the potentially completed monument. The 3D models hold significant potential for various applications, including tourism, education, and architectural research, with the potential for immersive experiences through VR and AR technologies. The study demonstrated the effectiveness of digital tools in heritage preservation, not only safeguarding the Raya Gopura but also offering valuable in-sights for future research and public engagements.

In a trip planning service, travelers first set a starting point, a destination, and a sequential list of specific points of interest types (e.g., museums, restaurants, and parks). Based on this information, the service searches the spatial database to customize the best travel itinerary for the tourist. However, in previous studies, planners only considered the time factor when designing the optimal route, and failed to fully consider the quality of each point of interest. In this study, we specifically leveraged the capabilities of large language model to parse and respond to complex travel-related user queries. To apply large language model to route planning, we fine-tuned the model to understand geotagging and user travel preferences. We have introduced a novel graph search algorithm combined with large language model output, which optimizes the route search process to provide optimal travel recommendations by taking into account various factors such as distance length, budget constraints, and popularity of tourist attractions. In addition, we have integrated real-time traffic data and historical travel data to further improve the prediction accuracy and application usefulness of the model. In the experimental validation phase, we designed a series of benchmarks to compare the performance of the system with traditional algorithms and other machine learning-based route planning methods. Experimental results show that our model has a significant improvement compared with traditional methods in improving the speed and accuracy of path selection.

The study examines the risk and protective factors in childhood for boys and girls who engage in unlawful behavior, through the lens of developmental criminology. This field explores the elements contributing to the emergence of antisocial and prosocial behaviors in childhood, which are linked to the increase or desistance of delinquency in later years. To enhance understanding in this domain, the study analyzes risk and protective factors associated with criminality in children across various levels: individual, family, and community. Utilizing a systematic review grounded in the PRISMA method, the study identifies and categorizes a range of factors, including conduct problems, socio-emotional competencies, biological determinants, social exclusion, interpersonal relationships, institutional governance, family adversity, caregiver characteristics, and family composition. This review underscores the significance of recognizing risk and protective factors in child development to design interventions at multiple levels, aiming to prevent antisocial behavior proactively.

Purpose To compare and adjust activated clotting time (ACT) between two systems and to optimize ACT during atrial fibrillation (AF) ablation. Methods Electromagnetic detection using a rotation tube (EM system; Hemochron Response, Soma Tech Intl, Bloomfield, CT, USA) and photo-optical detection using a cartridge immersed in blood (PO system; ACT CA-300TM, APEL) were compared. Results The EM system showed an ACT of 320 ± 44 s (average ± 1 standard deviation), with a range of 156–487 s, from 3363 measurements in 1161 patients during uncomplicated procedures. An ACT >400 s was observed in 3.7% (124/3364) of patients. The pre-ablation ACT measured by the EM method was 143 ± 28 s. Cardiac tamponade was observed in 4/2085 ablations (0.19%) over 5 years. The ACT associated with cardiac tamponade ranged from 330 to 391 in the EM system. The regression equation was ACT-EM system = 1.19 × ACT-PO system + 9.03 (p

Due to the adverse effect of prolonged drought stress on plants, accurate detection is essential for water use efficiency and maintaining productivity. Hyperspectral imaging is frequently used for non-invasive plant phenotyping, allowing for the long-term monitoring of crop health due to its sensitivity to subtle changes in leaf constituents. The broad spectrum of hyperspectral data enables the development of multiple vegetation indices (Vis) derived from the different spectral regions to estimate plant biophysical and biochemical traits. However, the known VIs often do not generalize well and perform poorly for multiple plant stresses. This study proposes new VIs combined with machine learning models to identify drought stress in wheat species under different nitrogen (N) levels. A wheat experiment was set up in the glasshouse with four treatments: well-watered high-N (WWHN), well-watered low-N (WWLN), drought-stress high N and drought-stress low-N. In addition to ensuring that plants were watered according to the experiment design, photosynthetic rate (Pn) and stomatal conductance (gs) were taken regularly, serving as the ground truth data for this study. Sensitive spectral features were selected using a custom-designed ensemble modelling technique. New drought VIs are proposed using different combinations of the selected features. Three classification models (support vector machines, random forest and deep neural network) were developed and trained using four sets of data: known VIs, proposed VIs, combined VIs (from the known and proposed VIs) and PCA-transformed features (over the whole spectral data). From the results, the proposed VIs outperformed the known VIs, yielding &gt; 0.94 accuracies for all three models, and the performance improved when they were trained with the combined VIs. The combined VIs were used to train three regression models to predict the stomatal conductances and photosynthetic rates of plants. The random forest regression model performed best, suggesting that it could be used as a stand-alone tool to forecast gs and Pn and track drought stress in wheat.

It is well-known that the canonical quantization of $\varphi^4_4$ fails. Here is how to fix it along with many other problems.

The impact of COVID-19’s unexpected outbreak forced the scientific world to thoroughly seek alternative ways of treatment in order to overcome the hindrance of traditional medicine in alleviating the symptoms of this virus and possibly be an option for a potential cure in the near future. The antibiotic erythromycin, which was introduced in 1952, has been reported to pose an effective substitute medication for various ailments such as skin, respiratory, bone, female reproductive conditions, and cancer, as well as the newly added COVID-19’s aftermath. Countries, World Health Organization and the health industry have recruited and cooperated with numerous universities and institutions, so as to tackle the demand for efficient antibiotics, with USA and China leading this effort. Consequently, the catalytic mechanism of erythromycin’s synthesis and industrial production was discussed and analyzed further in order to gain a better understanding and extrapolate innovative and environmentally friendly methods of producing this antibiotic. Therefore, the demand for an increase and improvement in the production of erythromycin should be globally promoted, in order to deliver more effective results against infectious diseases such as COVID – 19.

Preoperative assessment is crucial in surgical care, traditionally relying on physical examinations and paper-based questionnaires. The emergence of digital tools like Pathpoint® ePOA represents a significant advancement, aiming to enhance the efficiency, accuracy, and standardisation of preoperative evaluations. Pathpoint® ePOA is a cloud-based platform designed to integrate seamlessly with Electronic Health Records (EHRs), providing a comprehensive, data-driven approach to preoperative assessments. It supports improved risk stratification, optimised resource allocation, and enhanced patient engagement through features such as customisable templates and real-time data integration.Current research highlights that digital preoperative tools like ePOA offer notable advantages, including increased clinical capacity, better complexity stratification, and improved patient follow-up. Despite these benefits, gaps remain in comparative studies, detailed clinical outcomes, and patient engagement strategies, indicating areas for further exploration. Pathpoint® ePOA adheres to rigorous safety standards and risk management protocols, ensuring reliability and data security while contributing to improved surgical outcomes. The benefit-risk ratio for ePOA is favourable, underscoring its potential to advance preoperative care by optimising clinical workflows and enhancing patient safety.