Changes In Distribution Research Articles

Changes in cancer diagnoses and stage distribution during the second year of the COVID-19 pandemic in the US.

130 Background: During 2020, the first year of the COVID-19 pandemic, cancer diagnoses decreased, especially early-stage disease, with largest decreases in medically underserved populations. It is unknown whether this pattern continued during 2021, the second year of the COVID-19 pandemic. With newly released cancer surveillance data, this study examined nationwide changes in adult cancer diagnoses and stage distribution from 2019 to 2021 in the US. Methods: Adults aged ≥18 years who were newly diagnosed with first primary malignant cancers between 2019 and 2021 from 50 US states and the District of Colombia were identified from the National Cancer Database. We calculated monthly cases, stage distribution, and adjusted odds ratios (aOR) of stage I vs. stage II–IV cancer and stage IV vs. stage I–III cancer diagnoses in 2021 compared with 2019, controlling for sociodemographic and clinical factors and stratified by cancer type. Results: We identified 864,430 individuals diagnosed in 2019, 780,478 diagnosed in 2020, and 819,791 diagnosed in 2021. The proportion of diagnoses at stage I decreased from 39.6% in 2019 to 31.1% in April 2020, and were 39.2% overall in 2021. The decrease in stage I diagnoses was mirrored by an increase in stage IV diagnoses. The pattern was most prominent for female breast, lung, colorectal, and prostate cancers, and melanoma. Overall, compared to 2019, we found a 5.98% decrease in stage I diagnoses and a 4.55% decrease in stage IV diagnoses in 2021 (Table). Lower odds of diagnosis at stage I were most prominent among individuals who were male, aged 18-44, Hispanic, from Mid-Atlantic region, and for the cancers of melanoma, non-Hodgkin lymphoma, prostate, esophagus, and cervical cancer. Higher odds of diagnosis at stage IV in 2021 vs. 2019 were most prominent among individuals who were Hispanic, diagnosed with cancers of prostate, thyroid, liver, esophagus and cervix. Conclusions: Decreases in cancer diagnoses and proportion of early-stage diagnoses continued in 2021 in the US. The proportion of late-stage diagnoses were lower in 2021 than 2020 but have not returned to pre-pandemic levels. Changes in stage I distribution among major cancer sites 2021 vs. 2019. 2019 2021 2021 vs. 2019 Cases Cases Percent Change AdjustedOR* (95%CI) All Cancers 341971 321514 -5.98% 0.978 (0.972-0.985) Female breast 116828 116780 -0.04% 1.023 (1.007-1.038) Prostate 26323 21012 -20.18% 0.826 (0.809-0.843) Lung cancer and bronchus 28258 25966 -8.11% 1.033 (1.012-1.053) Colon and rectum 14258 12992 -8.88% 0.942 (0.918-0.968) Melanoma 21005 19542 -6.97% 0.936 (0.907-0.966) Data source: National Cancer Database 2019-2021. *Stage I vs. II-IV, models adjusted for age group, sex, race/ethnicity, zip-code level social deprivation index, comorbidity score, state-level COVID-19 age adjusted mortality rate, MSA, state, insurance status.

Impact of elevated loading rates on the shape of the Master Curve (ASTM E1921) for a German RPV steel

The Master Curve Methodology (ASTM E1921) experimentally assesses a materials temperature-dependent fracture toughness, predominantly for quasi-static testing conditions. The treatment of elevated loading rates is described by the annex A1 of ASTM E1921 and A14 of ASTM E1820. This paper presents results of the evaluation of a large and standard-conforming database in order to verify the procedures recommended by the standard for elevated loading rates. Testing involved C(T)- and SEN(B)-specimens of the RPV-steel 22NiMoCr3-7 (A508 Grade 2) for loading rates of 100 MPa√m/s ≤ K̇ ≤ 104 MPa√m/s in the ductile to brittle transition region. While valid T0-values were found, single-temperature T0-values were observed to differ more than expected from multi-temperature T0-values, which cannot be explained by the Master Curve uncertainty. The shape and underlying distribution of the Master Curve show deviations with increased loading rate. The shape factor p is optimized with respect to the individual data, and it increases with K̇, but deviations are not completely overcome. This can be linked to a change in distribution, which was demonstrated by an optimization of minimum fracture toughness Kmin, which increases with temperature. It is argued that the cause for the observations is linked to both heating processes and local crack arrest that severely influence macroscopic fracture behavior. Also, an individual adjustment of p or Kmin is not helpful due to the material-dependency in practice. It is recommended that fracture mechanics testing at elevated loading rates is performed close to or below T0 in order to minimize the influence of dynamic loading conditions on the assessment.

Climate change undermines seafood micronutrient supply from wild-capture fisheries in Southeast Asia and Pacific Island countries

Marine ecosystem functions are affected by climate change impacts such as ocean warming, deoxygenation and acidification. These impacts drive changes in distributions and body size of fish species and directly affect fisheries. Wild-capture fisheries are crucial for providing nutrients, livelihoods, and employment in tropical Southeast Asia and Pacific Island countries, where coastal communities are highly vulnerable to climate change. We examined the impacts of climate change on fish stocks and nutrient availability of seven key micronutrients (calcium, Omega-3 fatty acids, iodine, iron, vitamin A, vitamin B12 and zinc) in Southeast Asia, Pacific Islands, and Oceania (Australia and New Zealand). We combined micronutrient demands by local human populations with Sea Around Us reconstructed catch time series and catch projections from a dynamic bioclimate envelope model for the 21st century. The model predicted a decline in the Maximum Catch Potential (MCP) within Exclusive Economic Zones for Oceania, Pacific Islands, and Southeast Asian countries. Under the ‘strong mitigation’ scenario, catch potential reductions ranged from a decline of 54–66 % in Oceania, 58–92 % in Pacific Islands, and 65–86 % in Southeast Asia by the mid to the end of the 21st century relative to the historical period, respectively. Under the ‘no-mitigation’ climate scenario, reductions were more severe, with a decline of 55–70 % in Oceania, 66–92 % in Pacific Islands, and 70–86 % in Southeast Asia for the same time periods. Our findings indicate that Australia and New Zealand are unlikely to meet the recommended nutrient intake demand for most micronutrients through their fisheries (not considering trade or aquaculture production), except for iodine and vitamin B12. Pacific Island countries will likely follow the same pattern while Southeast Asia is expected to face worsening deficits, except for iodine and vitamin B12. This study highlights the importance of incorporating nutritional considerations of seafood into national food, trade and economic policies.

Impacts of climate change and human activities on three Glires pests of the Qinghai-Tibet Plateau.

The range of Glires is influenced by human activities and climate change. However, the extent to which human activities and environmental changes have contributed to this relationship remains unclear. We examined alterations in the distribution changes and driving factors of the Himalayan marmot, plateau pika, and plateau zokor on the Qinghai-Tibet Plateau (QTP) using the maximum entropy (MaxEnt) model and a geographical detector (Geodetector). The MaxEnt model showed that the contribution rates of the human footprint index (HFI) to the distribution patterns of the three types of Glires were 46.70%, 58.70%, and 59.50%, respectively. The Geodetector results showed that the distribution pattern of the Himalayan marmot on the QTP was influenced by altitude and the normalized difference vegetation index (NDVI). The distribution patterns for plateau pikas and plateau zokors were driven by HFI and NDVI. Climate has played a substantial role in shaping suitable habitats for these three Glires on the QTP. Their suitable area is expected to decrease over the next 30-50 years, along with their niche breadth and overlap. Future suitable habitats for the three Glires tended to shift toward higher latitudes on the QTP. These findings underscore the impacts of environmental and human factors on the distribution of the three Glires on the QTP. They have enhanced our understanding of the intricate relationships between Glires niches and environments. This can aid in identifying necessary interventions for developing effective early warning systems and prevention strategies to mitigate Glires infestations and plague epidemics on the QTP. © 2024 Society of Chemical Industry.

Investigating spatial-temporal trend of snow cover over the three provinces of Northeast China based on a cloud-free MODIS snow cover product

Snow serves as a pivotal water resource in the three provinces of Northeast China (TPNC), the investigation of spatial and temporal distribution changes of snow cover is essential for the region’s efficient water resource management. The Moderate Resolution Spectroradiometer (MODIS) snow cover product has proven effective in providing detailed spatial–temporal distribution and identification of snow cover. However, its accuracy and reliability are significantly hampered by cloud obscuration. To address this issue, we have developed a novel four-step cloud removal approach, which includes Terra and Aqua combination, 5-day temporal combination, snowline method (IMS) as well as 8-pixel and 24-pixel adjacent pixel method. Results indicate that the proposed approach successfully eliminates all cloud cover, yielding a highly accurate cloud-free snow cover product with validation accuracies of 92% and 97% when using in situ snow depth measurements and cloud masking method, respectively. We investigated the spatial and temporal variations of snow cover for the TPNC during 2003–2018 with snow coverage and snow cover days (SCD) and analyzed the correlation between snow cover and climate factors. The results showed that the annual basin-averaged snow coverage increased at a rate of 1.27% yr−1 before 2009 and decreased at a rate of 1.80% yr−1 after 2009. The Mann-Kendall tests indicated that about 72% of the total area showed an increasing trend of annual SCD during 2003–2018. Conversely, 94% of the total area exhibited a decreasing trend of annual SCD for the period of 2009–2018 due to the increasing trend of temperature and decreasing trend of precipitation. Our approach shows a promising application of generating accurate cloud-free products and its potential to examine spatial–temporal variations of snow cover under climate change for other snow-covered regions globally.

Effects of heat input on microstructure evolution and corrosion resistance of underwater laser cladding high-strength low-alloy steel coating

The effects of heat input on the microstructure evolution and corrosion resistance of the high-strength low-alloy (HSLA) steel coating obtained by wire-feed underwater laser cladding were studied. Optical digital microscope, scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), transmission electron microscope (TEM), electron back-scattered diffraction (EBSD), electrochemical tests, laser microscope and other characterization methods were used. As the heat input increased, the smoothness of the underwater cladding coating improved, with little changes in elemental distribution and phase composition. However, the content of acicular ferrite increased, while the amounts of lath bainite, lath martensite, and granular bainite decreased. As the heat input increased from 0.4 to 0.55 kJ/mm, the grain size increased from 25.3 to 55.9 μm, the proportion of low-angle grain boundaries rose from 61.3 % to 69.1 %, and the texture intensity of the (110) crystal plane increased from 16.22 to 23.83. Meanwhile, the dislocation density decreased from 4.9 × 1014 to 4.1 × 1014 m−2. These changes enhanced the corrosion resistance of underwater coating. As the heat input increased from 0.4 to 0.55 kJ/mm, the corrosion current density decreased from 2.13 × 10−5 to 3.35 × 10−6 A/cm2, and the corrosion potential increased from −0.823 to −0.529 V. Additionally, the depth-to-width ratio of the corrosion pits decreased from 0.255 to 0.053. This study laid the foundation for high-quality in-situ underwater repairs of ships and submarines made of high-strength steel.

Unveiling the structural and physico-chemical properties of glutenin macropolymer under frozen storage: Studies on experiments and molecular dynamics simulation

Glutenin macropolymer (GMP) plays an important role in wheat gluten fractions, and extensively presents in the frozen dough. However, the effects of freezing treatment on GMP remain not abundantly understood. In this study, we investigated the structure and physico-chemical properties of GMP under frozen storage through experimental methods and bioinformatics algorithms. Results revealed that freezing treatment weakened the structure and properties of GMP to varying degrees, and GMP might have tolerance to short-term freezing storage. During frozen storage, portions of α-helix in GMP were converted into β-turn and random coil, slight changes in the tertiary structure, and its surface hydrophobicity increased by 4.8 %. SDS-PAGE profiles indicated that the depolymerization behavior mainly occurred above the Mw of 70.0 kDa. Slight changes were observed in the content of free thiol groups and disulfide bonds during frozen storage. Combination of fluorescence spectroscopy and intermolecular interactions suggested that hydrogen bonds and hydrophobic interactions were probably important indicators for evaluating the deterioration of GMP. Frozen storage resulted in an unfolded and open protein network. Moreover, freezing treatment led to a main conversion from strongly bond water to weakly bond water. However, no significant changes in water distribution were observed during the first 7 days of frozen storage. The viscoelastic loss of GMP primarily occurred in the first fourteen days, but tan δ did not significantly increased, indicating that protein has not been seriously deteriorated. Molecular dynamics simulation further supplemented and validated these experimental results from molecular level through analysis of root mean square deviation, root mean square fluctuation, solvent-accessible surface area, radius of gyration and the number of hydrogen bonds.

Quantifying intra-annual changes in abundance and distribution to identify the magnitude and scale of potential mortality events.

Quantifying intra-annual changes in abundance and distribution to identify the magnitude and scale of potential mortality events.

Multiscale study of interfacial properties of carbon fiber reinforced polyphthalazine ether sulfone ketone resin matrix composites

In view of the limitations of traditional research tools on interfacial failure mechanisms in fiber/PPESK composites, this work proposes a multiscale research tool to carry out an in-depth study of the interfacial behavior between fibers and matrix. Based on microdroplet debonding tests, at the mesoscopic scale, the influence of residual thermal stress on the interface damage mode is explored through finite element (FEM) simulations. The evolution mechanism of composite material interfaces in spatial and temporal dimensions is examined based on changes in interfacial stress distribution, energy dissipation, and damage morphology during the debonding process, which can be summarized as follows: accompanied by elastic-plastic deformation and friction effects, the progressive process from localized to complete failure presents a dominant Type II damage mode at the interface. To further explore the interface failure mechanism at the molecular level, an interface model of CF/PPESK composite materials was established using molecular dynamics (MD) method. By monitoring the atom movement trend, the "fiber-matrix displacement synergistic effect" in the interfacial shear damage process was revealed, thereby establishing a multiscale mapping relationship of composite material interface. Based on this, the combination of FEM and MD was utilized to investigate the interface damage process of composite materials under different service conditions and to reasonably predict the initiation and expansion of microcracks. This study provides a pioneering perspective on interface damage research in composite materials with a "top-down" multiscale approach.

Estimates of life-history and growth parameters of exploited fish species in lakes Edward and George: Implications on exploitation status, population dynamics, management, and conservation of native species.

Adequate knowledge is essential for responsible inland fisheries. However, many inland fisheries lack monitoring, and therefore, decision-making for fisheries management is not reliable. In this paper, we used data from surveys and literature to estimate the life-history and growth parameters of 16 exploited fish stocks in the Ugandan part of Lake Edward and Lake George (East Africa). The estimated parameters are pivotal indicators of fish stock status, particularly in data-poor fisheries. The estimated parameters included maximum length (Lmax) and mean length (Lmean) as indicators of size structure in experimental and commercial catches, coefficients of length-weight relationships, length at 50% maturity (Lm50), fecundity, von Bertalanffy parameters, total mortality (Z), and natural mortality (M). These parameters were estimated using empirical formulae, statistical methods, and analyses of length frequencies. Only two stocks of semutundu Bagrus docmak exhibited significant and increasing trends in Lmax (Lake Edward) and Lmean (Lake George). The estimates for the remaining parameters were consistent with those in FishBase and other literature resources, either for the same species or related species. This consistency indicates their reliability for application in decision-making and further assessments. Some parameters showed evidence of unsustainable fishing. For example, estimates of Lm50 for four of the assessed stocks belonging to two species (Nile tilapia Oreochromis niloticus and marbled lungfish Protopterus aethiopicus) were lower than baseline estimates in the studied waterbodies. Furthermore, the Lmean in catches for all the stocks were less than the optimum lengths (Lopt), which maximize catches with a minimal impact on biomass and size structure. No significant changes in Lmean, length-frequency distributions, and size at maturity could be attributed to the management changes implemented in 2018, probably because it is too early to observe changes in these parameters. However, there are positive signs attributable to the changes in management as shown by a high proportion of mature individuals in commercial catches for most of the stocks for which the proportion was calculated, and an increase in Lmean and Lmax for some stocks, such as B. docmak, in commercial or experimental catches. New estimates from this study will enhance decision-making and further assessments of fisheries. Routine monitoring is recommended to update and improve the estimates.

The Impact of Wildfire Smoke on Asthma Control in California: A Microsimulation Approach.

Wildfire smoke exposure leads to poorer health among those with pre-existing conditions such as asthma. Particulate matter in wildfire smoke can worsen asthma control, cause acute exacerbations, and increase health resource utilization (HRU) and costs. Research to date has been retrospective with few opportunities to project changes in underlying asthma control and HRU given exposure to wildfire smoke. Using a microsimulation of 5,000 Californians with asthma, we calculated changes in asthma control distribution, risk of exacerbation, and HRU and cost outcomes in the 16weeks during and after a wildfire. The model was calibrated against empirical values on asthma control distribution and increased HRU after exposure to wildfire smoke. Without smoke exposure, 48% of the cohort exhibited complete or well control of asthma, and 8% required acute healthcare per cycle. Following two consecutive weeks of wildfire smoke, complete or well control of asthma fell to 27%, with an additional 4% HRU. This corresponds to total additional $601,250 in all-cause medical costs and eight fewer quality-adjusted life years over 16weeks of model time. Our model found increased asthma health and cost burden due to wildfire smoke that were aligned with empirical evidence from a historic wildfire event. This study establishes a framework for a more nuanced understanding of asthma impacts from wildfire smoke that can help inform the development of public health policies to mitigate harm and promote resilience among asthma patients in the face of climate change.

Visualization experiment of solid-liquid two-phase flow transportation in a jet pump

Abstract Due to its lack of internal moving components, the jet pump offers widespread application possibilities in solid-liquid two-phase flow transportation. Utilizing high-speed photography, this research established a visual experimental platform for jet pumps, allowing for a detailed study and analysis of the dynamics of solid particles entering, mixing, and being conveyed through the jet pump. The following results were obtained. The introduction of solid phase particles into the jet pump results in decreased pressure ratio and efficiency, yet the general trajectory of change within the pump system remains constant. With decreasing particle size, particles become increasingly susceptible to being entrained and propelled into the jet pump by the high-velocity jet flow. The proportion of particle distribution in the mixing chamber rises as the flow ratio goes up. However, when the flow ratio falls below 0.6, the changes in particle distribution beneath the jet zone of the mixing chamber become insignificant, primarily due to the impact of particle deposition within the suction chamber. A reflux zone is observed in the throat, which gradually shrinks in length as the flow ratio increases.

Reduction of the Downward Energy Flux of Nonthermal Electrons in the Solar Flare Corona due to Cospatial Return-current Losses

High-energy electrons carry much of a solar flare’s energy. Therefore, understanding changes in electron beam distributions during their propagation is crucial. A key focus of this paper is how the cospatial return current reduces the energy flux carried by these accelerated electrons. We systematically compute this reduction for various beam and plasma parameters relevant to solar flares. Our 1D model accounts for collisions between beam and plasma electrons, return-current electric-field deceleration, thermalization in a warm target approximation, and runaway electron contributions. The results focus on the classical (Spitzer) regime, offering a valuable benchmark for energy flux reduction and its extent. Return-current losses are only negligible for the lowest nonthermal fluxes. We calculate the conditions for return-current losses to become significant and estimate the extent of the modification to the beam’s energy flux density. We also calculate two additional conditions that occur for higher injected fluxes: (1) where runaway electrons become significant, and (2) where current-driven instabilities might become significant, requiring a model that self-consistently accounts for them. Condition 2 is relaxed and the energy flux losses are reduced in the presence of runaway electrons. All results are dependent on beam and cospatial plasma parameters. We also examine the importance of the reflection of beam electrons by the return-current electric field. We show that the interpretation of a number of flares needs to be reviewed to account for the effects of return currents.

Sub‐Milankovitch Signals in the Northern Polar Layered Deposits of Mars

AbstractOur understanding of the paleoclimate of Mars and the dominant forcing functions that drive large‐scale changes largely remains a mystery. However, the Martian Polar Layered Deposits (PLD) offer a promising avenue for unraveling the planet's recent paleoclimate history. Despite recent progress to detect a climate signal in the PLD, definitive evidence of a correlation between the stratigraphic record and Mars' recent orbital history remains elusive. We utilized new and updated techniques, including high‐resolution stratigraphic reconstruction from High Resolution Imagine Science Experiment stereo imagery and digital terrain models, combined with a technique of variable dip correction to account for three dimensional bedding orientations. Signal processing methods, such as wavelet and Fourier analysis, were applied to perform detailed time‐series analysis. These analyses revealed a quasi‐periodic signal indicative of fine bedding at a scale of approximately 2 m. Based on previously proposed deposition rates, these fine layers appear to correspond to timescales centering around 4,000 years. This suggests that the meter‐scale layers may not be the result of orbital forcing and hint at an unknown sub‐Milankovitch climate forcing mechanism. We discuss potential exogenic causal mechanisms, such as cyclic variations in solar activity, and endogenic factors, including large‐scale changes in dust distribution. Understanding the formation processes of these fine layers may significantly enhance our knowledge of Martian climate history and its driving forces.

Spatial distribution of poultry farms using point pattern modelling: A method to address livestock environmental impacts and disease transmission risks.

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available.

The association of Medicaid expansion and parathyroidectomy for benign disease: Insurance status remains an important factor in access to high-volume centers

BackgroundMedicaid expansion has been associated with improved access to surgical care at high-volume centers. Its impact on parathyroidectomy, however, is unclear. We evaluated the association between Medicaid expansion and parathyroidectomy at high- and low-volume centers. MethodsThe Vizient Clinical Data Base was queried for parathyroidectomies. Patients were grouped by insurance status and pre- and post-Medicaid expansion periods. Hospitals were stratified into tertiles (T1-T3) by operative volume (T1 = highest-volume centers). Odds of parathyroidectomy and a difference-in-differences analysis were conducted. ResultsIn total, 31,983 patients were identified. Patients were predominantly privately insured (49.9%). Uninsured and Medicaid patients had increasing odds of operation at lower-tertile centers (odds ratio: T1 = ref; uninsured: T2 = 10.0, T3 = 15.8; Medicaid: T2 = 6.2, T3 = 13.5; P < .001). Medicare patients, however, were less likely to undergo operation at lower-volume centers (odds ratio: T2 = 0.89, P < .001; T3 = 0.92, P = .002). Privately insured patients were the least likely to receive care at low-volume centers (odds ratio: T3 = 0.7, P < .001).Medicaid patients in nonexpansion states had 12–16 times higher odds of parathyroidectomy at lower-volume hospitals than their counterparts in expansion states (expansion/nonexpansion states: pre-expansion T3 = 2.3/28.0; postexpansion T3 = 1.3/21.4). Expansion was associated with an increase in the proportion of parathyroidectomy for Medicaid patients, with larger gains seen at higher-volume centers (T1 = 5.0%, P = .01; T2 = 3.1%, P = .001; T3 = 2.7%, P = .03). Expansion was not associated with changes in payor distribution for uninsured, Medicare, or privately insured patients. ConclusionsMedicaid expansion was associated with an increase in parathyroidectomy for Medicaid patients at high-volume centers. However, in nonexpansion states, access to surgical treatment at high-volume centers remains limited for uninsured and underinsured patients.

Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical studies

Phytogeography, the study of the geographic distribution of plants, is important for understanding ecosystem dynamics, biodiversity, and ecological processes. Over the past few years, advances in technology, especially artificial intelligence (AI), have revolutionized various scientific fields, including ecology and environmental science. In recent years, AI techniques have been increasingly applied in phytogeography, providing new opportunities to increase our understanding of plant distribution patterns and improve conservation efforts. The study of the role of artificial intelligence in phytogeography focuses on how AI techniques such as machine learning, remote sensing, and spatial analysis are being used to analyse large-scale plant distribution data. By leveraging AI, researchers can gain valuable insights from vast and complex datasets, identify patterns and predict future changes in plant distributions with greater accuracy. Furthermore, AI-driven approaches have the potential to address important challenges in phytogeography, such as species distribution modelling, habitat mapping, and biodiversity conservation. By integrating AI with traditional ecological methods, more effective strategies can be developed to manage and conserve plant species and their habitats. AI-driven phytogeography research, provides an overview of recent progress, discusses potential applications of AI techniques in ecological studies, and the opportunities and challenges associated with the use of AI in understanding and conserving plant biodiversity. Ultimately, the integration of AI with phytogeography has the potential to revolutionize our understanding of plant distributions and inform more sustainable conservation practices in the face of global environmental change.

Study of correlation between arches of foot and lower back pain in Eastern India

Background: Low back pain is one of the most common disorders of the musculoskeletal system, leading to impaired function and decreased quality of life in many patients. Foot arch alterations may lead to structural changes and/or affect its load distribution. It should be noted that even slight elevations of the foot’s medial longitudinal arch above the norm may lead to changes in load and pressure distribution. Hence, it becomes important to find the relationship between low back pain and altered foot arch indices leading to improper body balance. Aims and Objectives: The aims and objectives of the study are to find any correlation between lower back pain and an altered foot arch index in the Eastern Indian population. Materials and Methods: A total of 60 subjects aged 20–40 years with varying degrees of low back pain were selected. Low back pain scores of the subjects were found using modified oswestry low back pain disability questionnaire. Footprints in standing position using ink were taken on graph paper and the foot arch indices were calculated. Results: 54.16% of the male and 36.11% of female participants had low arched feet, 20.83% of male and 52.78% of female participants had normal arched feet, and 25% of male and 11.11% of female participants had high arched feet with varying degrees of low back pain. 77.42% of the participants with minimal disability due to low back pain were having normal arched feet, 71.43% of the participants with moderate disability due to low back pain were having low arched feet, and 100% of the participants with severe disability due to low back pain were having either high or low arched feet. Conclusion: This study showed that people having either low or high arched feet are at an increased risk of developing acute or chronic low back pain at some stage in their lives. Knowledge of this risk factor might even help people to choose appropriate occupations in the future.

Design, Synthesis, and Preclinical Evaluation of a High-Affinity 18F-Labeled Radioligand for Myocardial Growth Hormone Secretagogue Receptor Before and After Myocardial Infarction.

The peptide hormone ghrelin is produced in cardiomyocytes and acts through the myocardial growth hormone secretagogue receptor (GHSR) to promote cardiomyocyte survival. Administration of ghrelin may have therapeutic effects on post-myocardial infarction (MI) outcomes. Therefore, there is a need to develop molecular imaging probes that can track the dynamics of GHSR in health and disease to better predict the effectiveness of ghrelin-based therapeutics. We designed a high-affinity GHSR ligand labeled with 18F for imaging by PET and characterized its invivo properties in a canine model of MI. Methods: We rationally designed and radiolabeled with 18F a quinazolinone derivative ([18F]LCE470) with subnanomolar binding affinity to GHSR. We determined the sensitivity and invivo and ex vivo specificity of [18F]LCE470 in a canine model of surgically induced MI using PET/MRI, which allowed for anatomic localization of tracer uptake and simultaneous determination of global cardiac function. Uptake of [18F]LCE470 was determined by time-activity curve and SUV analysis in 3 regions of the left ventricle-area of infarct, territory served by the left circumflex coronary artery, and remote myocardium-over a period of 1.5 y. Changes in cardiac perfusion were tracked by [13N]NH3 PET. Results: The receptor binding affinity of LCE470 was measured at 0.33 nM, the highest known receptor binding affinity for a radiolabeled GHSR ligand. In vivo blocking studies in healthy hounds and ex vivo blocking studies in myocardial tissue showed the specificity of [18F]LCE470, and sensitivity was demonstrated by a positive correlation between tracer uptake and GHSR abundance. Post-MI changes in [18F]LCE470 uptake occurred independently of perfusion tracer distributions and changes in global cardiac function. We found that the regional distribution of [18F]LCE470 within the left ventricle diverged significantly within 1 d after MI and remained that way throughout the 1.5-y duration of the study. Conclusion: [18F]LCE470 is a high-affinity PET tracer that can detect changes in the regional distribution of myocardial GHSR after MI. In vivo PET molecular imaging of the global dynamics of GHSR may lead to improved GHSR-based therapeutics in the treatment of post-MI remodeling.

Through-Window Home Aerial Delivery System with In-Flight Parcel Load and Handover: Design and Validation in Indoor Scenario

Abstract This paper presents the design, development, and validation in indoor scenario of an aerial delivery system intended to conduct the delivery of light parcels directly to the user through the window of his/her home, motivated by the convenience of facilitating the access to medicines to people with reduced mobility.The system consists of a fully-actuated multi-rotor (FAMR) equipped with a front basket where the parcel to be delivered is loaded by a lightweight and compliant anthropomorphic dual arm system (LiCAS) located at the supply point, using one of the arms to drop the parcel in the basket while the other arm holds its base to support the sudden moment exerted at the FAMR. The paper analyses four types of physical interactions raised during the operation on flight: (1) sudden changes in the mass distribution of the FAMR during the load/unload phase, affecting the multi-rotor position-attitude controllers, (2) impact and impulsive forces exerted by the human on the FAMR to demonstrate the reliability and robustness of conventional cascade controllers, (3) passive accommodation of the LiCAS while holding the FAMR during the parcel load, relying on the mechanical joint compliance, and (4) compliant human–FAMR interaction, interpreting the multi-rotor pose control error as a Cartesian/angular deflection to implement an admittance controller that allows the user guiding the platform. Experimental results allow the identification and characterization of these effects for different payload masses. The execution of the complete operation, involving the parcel load with the LiCAS and handover by the user through a window, is validated in a representative indoor scenario. Graphical Abstract