bluuebunny/crossref_metadata_2025 huggingface dataset:
Covering young avocado ‘Hass’ trees with high-density shading nets during the winter mitigates frost damage and improves tree performance
Authors: Lahak Michal , Alon Eitan , Chen Assaf , Rubinovich Lior
Published: February 2024

Key message

Covering young ‘Hass’ trees with Silver 60% shading nets during cold winters mitigates frost damage and improves tree performance, apparently through a mechanism other than increasing nighttime air temperature.

Avocado is a commercially important subtropical evergreen fruit tree. Severe frost may damage foliage, floral buds, flowers and fruit, thereby reducing avocado crop yield and restricting its geographical distribution and expansion. Shading nets are frequently used to protect agricultural crops from climate-related damage. To determine their ability to mitigate frost damage, Silver 60% shading nets were deployed over young ‘Hass’ trees during two consecutive winters and uncovered trees served as controls. Freezing and chilling temperatures occurred in the experimental orchard during the winter of each year, from December to March, reaching − 2.49 ℃ in January 2022. In the control, 93% of the examined floral buds were severely damaged compared to 4% in the Silver 60% trees. Damage to young vegetative shoots was assessed at 4.35 out of 5 in the control compared to 0.5 out of 5 in the Silver 60% trees. In both years, minimum air temperatures under the Silver 60% shading nets were similar to those of the control. Leaf-level photosynthetic photon flux density was ~ 60% lower under the shading nets. In most measurements, CO2-assimilation rate, stomatal conductance, ratio of variable to maximum fluorescence (Fv/Fm) and chlorophyll concentration in the leaves of the Silver 60% trees were higher than, or similar to the controls. Trunk diameter and flowering intensity of the Silver 60% trees were higher than for the control. These results indicate that covering young ‘Hass’ trees with Silver 60% shading nets during cold winters can mitigate frost damage and improve tree performance.
Effects of cancer severity on the relationship between emotional intelligence, perceived social support, and psychological distress in Italian women
Authors: Bruno Francesco , Lau Chloe , Tagliaferro Carlotta , Marunic Georgia , Quilty Lena C. , Liuzza Marco Tullio , Chiesi Francesca
Published: February 2024

Purpose

This study aims to understand the association between emotional intelligence, perceived social support, and psychological distress (i.e., anxiety, depression, stress) in women with cancer at different stages. Specifically, the aims of this study were to investigate: i) the links between emotional intelligence and psychological distress (i.e., symptoms of anxiety, stress and depression); ii) the mediating role of perceived social support provided by family members, friends, and significant others in the relationship between emotional intelligence and psychological distress; iii) the impact of cancer type and cancer stage (I-II vs III-IV) in moderating these relationships, among Italian women.

Methods

The research sample consisted of 206 Italian women (mean age = 49.30 ± 10.98 years; 55% breast cancer patients) who were administered a questionnaire to assess emotional intelligence, perceived social support, and psychological distress. Structural equation model (SEM) analysis was carried out to confirm the hypothetical-theoretical model.

Results

Emotional intelligence had a positive association with perceived social support, which in turn prevented psychological distress only in women with early-stages cancers. The type of cancer has no effect on these relationships.

Conclusions

The findings of this study indicate a pressing need to screen and recognize women with lower emotional intelligence and perceived social support, as they may be more prone to experiencing psychological distress. For such individuals, our results recommend the implementation of psychological interventions aimed at enhancing emotional intelligence and fortifying their social support networks, with consideration for the stage of cancer they are facing.
Investigation of encapsulated water wire within self-assembled hydrophilic nanochannels, in a modified γ4-amino acid crystals: Tracking thermally induced changes of intermolecular interactions within a crystalline hydrate
Authors: Basuroy Krishnayan , de Jesus Velazquez-Garcia Jose , Techert Simone
Published: February 2024

Nanostructures formed by the self-assembly of modified/unmodified amino acids have the potential to be useful in several biological/nonbiological applications. In that regard, the greater conformational space provided by γ-amino acids, owing to their additional backbone torsional degrees of freedom and enhanced proteolytic stability, compared to their α-counterparts, should be explored. Though, modified single amino acid-based nanomaterials such as nanobelts or hydrogels are developed by utilizing the monosubstituted γ-amino acids derived from the backbone homologation of phenylalanine (Phe). Examples of a single γ-amino acid-based porous nanostructure capable of accommodating solvent molecules are not really known. The crystal structures of a modified γ4(R)Phe residue, Boc-γ4(R)Phe-OH, at different temperatures, showed that hydrogen-bonded water molecules are forming a wire inside hydrophilic nanochannels. The dynamics of intermolecular interactions between the water wire and the inner wall of the channel with relation to the temperature change was investigated by analyzing the natural bonding orbital (NBO) calculation results performed with the single crystal structures obtained at different temperature points. The NBO results showed that from 325 K onward, the strength of water–water interactions in the water wire are getting weaker, whereas, for the water–inner wall interactions, it getting stronger, suggesting a favorable change in the orientation of water molecules with temperatures, for the latter.
Role of women empowerment on mental health problems and care-seeking behavior among married women in Nepal: secondary analysis of nationally representative data
Authors: Shawon Md Shajedur Rahman , Hossain Fariha Binte , Ahmed Robin , Poly Isfar Jahan , Hasan Moushumi , Rahman Mohammad Rifat
Published: February 2024

Purpose

This study investigates the associations between women empowerment and the prevalence of mental health symptoms and care-seeking behavior among ever-married Nepalese women aged 15–49 years.

Methods

We utilized 2022 Nepal Demographic and Health Survey data to measure women empowerment, employing the Survey-Based Women’s Empowerment (SWPER) index. The index focuses on the domains of social independence, decision-making, and attitudes towards violence. Symptoms of anxiety and depression were measured using the Generalized Anxiety Disorder-7 scale (GAD-7) and the Patient Health Questionnaire (PHQ-9), respectively. Multiple logistic regression was performed to estimate adjusted odds ratio (aOR) for associations of women empowerment domains and mental health problems and care-seeking behavior.

Results

Among 5556 women, the prevalence of symptoms of anxiety and depression was 23.1% and 6.1%, respectively. Among those with any symptoms of anxiety or depression, 18.3% sought care. Compared to women with low level of empowerment in the “social independence” domain, those with high level of empowerment were less likely to suffer from symptoms of anxiety (aOR = 0.68; 95%CI, 0.57–0.82) and depression (aOR = 0.69; 95%CI, 0.50–0.94). However, high empowerment in “decision-making” domain was associated with higher likelihood of anxiety (aOR = 1.67; 95%CI, 1.33–2.10) and depression (aOR = 1.80; 95%CI, 1.26–2.58). There was evidence of positive association between high empowerment in “decision-making” and care-seeking (aOR = 1.28; 95%CI, 0.96–1.71).

Conclusions

This study underscores important roles of women empowerment on mental health symptoms and care-seeking behavior, suggesting the need to integrate empowerment initiatives into strategies to promote mental health among women in Nepal and similar low- and middle-income settings.
The impact of folate pathway variants on the outcome of methotrexate therapy in rheumatoid arthritis patients
Authors: Nomair Azhar M. , Abdelati Abeer , Dwedar Fatma I. , Elnemr Rehab , Kamel Yasmine N. , Nomeir Hanan M.
Published: February 2024

Background

There are currently no validated criteria that entirely explain or predict response to methotrexate (MTX) treatment in rheumatoid arthritis (RA). We tried to identify the connection between three variants (RFC1 G80A (rs1051266), TYMS 2R/3R (rs34743033), and ATIC C347G (rs2372536)) in the folate pathway of MTX metabolism and the response to MTX monotherapy in a cohort of RA cases.

Methods

A prospective study on 100 RA patients on MTX monotherapy was performed. Disease activity was measured at the start of treatment and 6 months after treatment with MTX. The patients were then split into two groups: those who responded to the treatment and those who did not. The molecular genetic study for the RFC1 (G80A) variant was employed via the PCR-restriction fragment length polymorphism (PCR–RFLP) technique, the ATIC (C347G) variant was performed using TaqMan allelic discrimination real-time PCR, and the tandem repeat sequences of TYMS (2R/3R) were amplified by conventional PCR and detected by agarose gel electrophoresis.

Results

The genotype distribution of RFC-1 (G80A) showed significant variations among non-responders and responders in the recessive genetic model. A significant difference was found in TYMS (2R/3R) in the dominant and heterozygous genetic models. However, ATIC (C347G) genotype frequency did not exhibit substantial link with drug response in all genetic models. Furthermore, the genotype and allele rates of the analyzed variants did not show any significant association with adverse events in all genetic models.

Conclusion

The 80AA genotype of RFC-1 G80A and the 2R/3R or 3R/3R genotypes of TYMS 2R/3R are more vulnerable to the good consequences of MTX therapy.

Key Points

• Current recommendations support the gold standard role of MTX as a first-line monotherapy for RA patients. However, up to 40% of RA patients do not respond or exhibit partial response to MTX.• Persistent disease activity due to treatment unresponsiveness will affect the long-term outcomes in RA patients.• We aimed, through molecular genetic study, to identify the connection between three variants in the folate pathway of MTX metabolism and the response to methotrexate monotherapy in a cohort of RA patients.
Designing tractable piecewise affine policies for multi-stage adjustable robust optimization
Authors: Thomä Simon , Walther Grit , Schiffer Maximilian
Published: February 2024

We study piecewise affine policies for multi-stage adjustable robust optimization (ARO) problems with non-negative right-hand side uncertainty. First, we construct new dominating uncertainty sets and show how a multi-stage ARO problem can be solved efficiently with a linear program when uncertainty is replaced by these new sets. We then demonstrate how solutions for this alternative problem can be transformed into solutions for the original problem. By carefully choosing the dominating sets, we prove strong approximation bounds for our policies and extend many previously best-known bounds for the two-staged problem variant to its multi-stage counterpart. Moreover, the new bounds are—to the best of our knowledge—the first bounds shown for the general multi-stage ARO problem considered. We extensively compare our policies to other policies from the literature and prove relative performance guarantees. In two numerical experiments, we identify beneficial and disadvantageous properties for different policies and present effective adjustments to tackle the most critical disadvantages of our policies. Overall, the experiments show that our piecewise affine policies can be computed by orders of magnitude faster than affine policies, while often yielding comparable or even better results.
To choose or not to choose? Effects of choice in authentic context-based learning environments
Authors: Güth Fabien , van Vorst Helena
Published: February 2024

Context-based learning (CBL) environments are widely used in science education to create authentic learning opportunities. Contexts can be authentic through their relation to everyday life, to uncommon scientific phenomena, or to the chemical laboratory. Previous research revealed that students choose contexts that are authentic in different ways depending on their individual characteristics. Self-determination theory and psychological research indicate that it is not the choice itself that is beneficial for learning, but rather the congruence between the characteristics of the participants and the task. The extent to which these results are transferable to CBL in chemistry education and the effects on cognitive load have not yet been analyzed. The focus of the present study was to investigate whether the choice of a contextualized task or the congruence between context and student are causal for beneficial effects in situational interest, cognitive load, and task-related satisfaction. We conducted an experimental study with 217 third-year chemistry students comparing three treatments while learning in a CBL environment. In the first group, students could choose a contextual task that was varied in terms of authenticity. Students in the second group were assigned a contextual task by an artificial neural network that matched their individual characteristics. Students in the third group were assigned a contextualized task by the neural network that did not match their individual characteristics. Multilevel analyses show that whether the context is chosen or not is irrelevant for situational interest and task-related satisfaction if the context fits the individual characteristics of the students.
Revisiting the leeway of shipping containers: a case study of the M/V Zim Kingston incident
Authors: Sutherland Graig , Chang Kuo-Hsien , Pestieau Paul
Published: February 2024

On 22 October 2021, 109 shipping containers fell overboard from the M/V Zim Kingston in rough seas off the coast of Vancouver Island, British Columbia, Canada. While afloat, these shipping containers pose a significant risk to marine traffic in addition to being a source of marine pollution. Out of the 109 shipping containers, 4 were discovered on the beaches of northwest Vancouver Island 5 days later. Drift simulations were made using the standard leeway tables for shipping containers that vary with the immersion fraction of the shipping container. These leeway values over the expected range of immersion levels underestimated the travelled distance of the shipping containers relative to the observed grounding locations. An increase in the leeway of 1.5% of the wind speed improves the agreement between the simulations and observations, which is consistent with the addition of the Stokes drift to the leeway of the shipping container. It is argued that the leeway measured using the direct method, which was used to calculate the leeway of shipping containers, does not implicitly include the Stokes drift as previously suggested. This result suggests that the Stokes drift should be added to the leeway calculated with the direct method. While the error is small over timescales of 24 to 48 h, it accumulates in time and is appreciable for drift prediction greater than 48 h.
Differential control of sympathetic outflow to muscle and skin during physical and cognitive stressors
Authors: McCarthy Brendan , Datta Sudipta , Sesa-Ashton Gianni , Wong Rebecca , Dawood Tye , Macefield Vaughan G.
Published: February 2024

Purpose

Sympathetic nerve activity towards muscle (MSNA) and skin (SSNA) regulates various physiological parameters. MSNA primarily functions in blood pressure and flow, while SSNA operates in thermoregulation. Physical and cognitive stressors have been shown to have effects on both types of sympathetic activity, but there are inconsistencies as to what these effects are. This article aims to address the discrepancies in the literature and compare MSNA and SSNA responses.

Methods

Microelectrode recordings were taken from the common peroneal nerve in 29 participants: MSNA (n = 21), SSNA (n = 16) and both MSNA and SSNA (n = 8). Participants were subjected to four different 2-min stressors: two physical (isometric handgrip task, cold pressor test) and two cognitive (mental arithmetic task, Stroop colour–word conflict test), the latter of which saw participants separated into responders and non-responders to the stressors. It was hypothesised that the physical stressors would have a greater effect on MSNA than SSNA, while the cognitive stressors would operate conversely.

Results

Peristimulus time histogram (PSTH) analysis showed the mental arithmetic task to significantly increase both MSNA and SSNA; the isometric handgrip task and cold pressor test to increase MSNA, but not SSNA; and Stroop test to have no significant effects on changing MSNA or SSNA from baseline. Additionally, stress responses did not differ between MSNA and SSNA in participants who had both sets of data recorded.

Conclusions

This study has provided evidence to support the literature which claims cognitive stressors increase sympathetic activity, and provides much needed SSNA data in response to stressors.
Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments’ carbon reduction policies
Authors: Ezenkwu Chinedu Pascal , Cannon San , Ibeke Ebuka
Published: February 2024

Across the globe, governments are developing policies and strategies to reduce carbon emissions to address climate change. Monitoring the impact of governments’ carbon reduction policies can significantly enhance our ability to combat climate change and meet emissions reduction targets. One promising area in this regard is the role of artificial intelligence (AI) in carbon reduction policy and strategy monitoring. While researchers have explored applications of AI on data from various sources, including sensors, satellites, and social media, to identify areas for carbon emissions reduction, AI applications in tracking the effect of governments’ carbon reduction plans have been limited. This study presents an AI framework based on long short-term memory (LSTM) and statistical process control (SPC) for the monitoring of variations in carbon emissions, using UK annual CO2 emission (per capita) data, covering a period between 1750 and 2021. This paper used LSTM to develop a surrogate model for the UK’s carbon emissions characteristics and behaviours. As observed in our experiments, LSTM has better predictive abilities than ARIMA, Exponential Smoothing and feedforward artificial neural networks (ANN) in predicting CO2 emissions on a yearly prediction horizon. Using the deviation of the recorded emission data from the surrogate process, the variations and trends in these behaviours are then analysed using SPC, specifically Shewhart individual/moving range control charts. The result shows several assignable variations between the mid-1990s and 2021, which correlate with some notable UK government commitments to lower carbon emissions within this period. The framework presented in this paper can help identify periods of significant deviations from a country’s normal CO2 emissions, which can potentially result from the government’s carbon reduction policies or activities that can alter the amount of CO2 emissions.
European highways and the geographic diffusion of economic activities from agglomerations to less urbanised areas
Authors: Ignatov Augustin
Published: February 2024

This paper analyses the impact of highways on the distribution of economic activities between urban agglomerations and peripheral regions in the European Union. In doing so, I use an empirical strategy based on the land use theory employing disaggregated economic and infrastructure data. To address endogeneity, I apply an IV strategy exploiting non-local highway construction as a source of exogenous variation. I find that highways contribute to the diffusion of urban economic activities into surrounding areas, reducing the income gap between European agglomerations and peripheries. Reduced-form estimations suggest that the gap would have been nearly 3% higher in 2020 if the highway networks of European countries had remained at the level of 1990. The study concludes that transportation infrastructure policies can alleviate regional income disparities, increasing economic convergence between urbanised and less urbanised areas.
Ethics of generative AI and manipulation: a design-oriented research agenda
Authors: Klenk Michael
Published: February 2024

Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending and curbing manipulation risks. By highlighting these questions, the article underscores the necessity of an appropriate conceptualisation of manipulation to ensure the responsible development of Generative AI technologies.
Fusion of Time-of-Flight Based Sensors with Monocular Cameras for a Robotic Person Follower
Authors: Sarmento José , Neves dos Santos Filipe , Silva Aguiar André , Filipe Vítor , Valente António
Published: February 2024

Human-robot collaboration (HRC) is becoming increasingly important in advanced production systems, such as those used in industries and agriculture. This type of collaboration can contribute to productivity increase by reducing physical strain on humans, which can lead to reduced injuries and improved morale. One crucial aspect of HRC is the ability of the robot to follow a specific human operator safely. To address this challenge, a novel methodology is proposed that employs monocular vision and ultra-wideband (UWB) transceivers to determine the relative position of a human target with respect to the robot. UWB transceivers are capable of tracking humans with UWB transceivers but exhibit a significant angular error. To reduce this error, monocular cameras with Deep Learning object detection are used to detect humans. The reduction in angular error is achieved through sensor fusion, combining the outputs of both sensors using a histogram-based filter. This filter projects and intersects the measurements from both sources onto a 2D grid. By combining UWB and monocular vision, a remarkable 66.67% reduction in angular error compared to UWB localization alone is achieved. This approach demonstrates an average processing time of 0.0183s and an average localization error of 0.14 meters when tracking a person walking at an average speed of 0.21 m/s. This novel algorithm holds promise for enabling efficient and safe human-robot collaboration, providing a valuable contribution to the field of robotics.
Stability of the bulk gap for frustration-free topologically ordered quantum lattice systems
Authors: Nachtergaele Bruno , Sims Robert , Young Amanda
Published: February 2024

We prove that uniformly small short-range perturbations do not close the bulk gap above the ground state of frustration-free quantum spin systems that satisfy a standard local topological quantum order condition. In contrast with earlier results, we do not require a positive lower bound for finite-system spectral gaps uniform in the system size. To obtain this result, we extend the Bravyi–Hastings–Michalakis strategy so it can be applied to perturbations of the GNS Hamiltonian of the infinite-system ground state.
Modelling the impact of opinion flexibility on the vaccination choices during epidemics
Authors: Della Marca Rossella , Menale Marco
Published: February 2024

Spontaneous behavioural responses of individuals to epidemics are a relevant factor in the understanding of infection dynamics. In this work, we consider a vaccine–preventable infectious disease spreading within a population, where vaccination is on a voluntary basis and individuals can conform to either the pro–vaccine or the anti–vaccine group. A switch of vaccinating attitude may occur following an imitation game dynamics. In particular, we incorporate the role of individuals’ opinion flexibility, that is a measure of the personal propensity to change opinion, in the switch of vaccinating attitude. We consider a disease dynamics of Susceptible–Infected–Removed type. Then, we use the tools of kinetic theory to describe the overall system at microscopic, mesoscopic and macroscopic scale. Finally, the role of flexibility of opinion on the vaccination choice during an epidemic is shown by providing some numerical simulations.
Analyzing third-party data leaks on online pharmacy websites
Authors: Rauti Sampsa , Carlsson Robin , Mickelsson Sini , Mäkilä Tuomas , Heino Timi , Pirjatanniemi Elina , Leppänen Ville
Published: February 2024

Purpose

With digitalization, using essential digital services such as online services has become increasingly common. These services process sensitive health related data, such as customers’ prescription medicine orders, which makes ensuring stringent data privacy crucial. The current study examines third parties such as analytics services on Finnish pharmacy websites and investigates the nature and contents of data leaks on these websites.

Methods

We perform an extensive network traffic analysis to reveal data leaks among 163 Finnish online pharmacies. We also study a set of privacy policies of these online pharmacies, and provide a legal analysis regarding the interpretation of the concept of data concerning health in the context of online pharmacies.

Results

Our findings reveal serious data leaks among Finnish online pharmacies. We found 145 pharmacies had third-party services on their websites and only 18 did not. Out of all 163 online pharmacies, 57 (35.0 %) leaked a specific prescription medicine name connected with identifying personal data on the customer. We argue that the information concerning purchases on the prescription medicines should be interpreted as data concerning health to ensure efficient protection of customers’ right to data protection and privacy.

Conclusions

We hope that these concerning results will serve as a wake-up call for the developers and maintainers of online pharmacies and other web services processing sensitive data. Any third-party services incorporated into websites processing sensitive personal data should be closely inspected in terms of data leaks, or preferably not used at all.
Reducing echocardiographic examination time through routine use of fully automated software: a comparative study of measurement and report creation time
Authors: Hirata Yukina , Nomura Yuka , Saijo Yoshihito , Sata Masataka , Kusunose Kenya
Published: February 2024

Background

Manual interpretation of echocardiographic data is time-consuming and operator-dependent. With the advent of artificial intelligence (AI), there is a growing interest in its potential to streamline echocardiographic interpretation and reduce variability. This study aimed to compare the time taken for measurements by AI to that by human experts after converting the acquired dynamic images into DICOM data.

Methods

Twenty-three consecutive patients were examined by a single operator, with varying image quality and different medical conditions. Echocardiographic parameters were independently evaluated by human expert using the manual method and the fully automated US2.ai software. The automated processes facilitated by the US2.ai software encompass real-time processing of 2D and Doppler data, measurement of clinically important variables (such as LV function and geometry), automated parameter assessment, and report generation with findings and comments aligned with guidelines. We assessed the duration required for echocardiographic measurements and report creation.

Results

The AI significantly reduced the measurement time compared to the manual method (159 ± 66 vs. 325 ± 94 s, p < 0.01). In the report creation step, AI was also significantly faster compared to the manual method (71 ± 39 vs. 429 ± 128 s, p < 0.01). The incorporation of AI into echocardiographic analysis led to a 70% reduction in measurement and report creation time compared to manual methods. In cases with fair or poor image quality, AI required more corrections and extended measurement time than in cases of good image quality. Report creation time was longer in cases with increased report complexity due to human confirmation of AI-generated findings.

Conclusions

This fully automated software has the potential to serve as an efficient tool for echocardiographic analysis, offering results that enhance clinical workflow by providing rapid, zero-click reports, thereby adding significant value.
Design and Parameter Optimization of Zero Position Code Considering Diffraction Based on Deep Learning Generative Adversarial Networks
Authors: Wang Shengtong , Luo Linbin , Li Xinghui
Published: February 2024

Absolute measurement has consistently been the primary focus in the development of precision linear and angular displacement measurements. The scheme design of binary zero position codes is an important factor for absolute measurement. Designing and optimizing high-bit zero position codes with over 100 bits face considerable challenges. Simultaneously, the working parameters of zero position codes [unit code width (b), distance (d), and yaw angle (α)] remarkably affect their post-installation performance, particularly in absolute positioning and limit code application in multi-degree-of-freedom measurement schemes. This study addresses these challenges by proposing a design method for zero position codes that considers diffraction based on generative adversarial networks and aims to explore a design with increased efficiency and accuracy as well as optimization for high-bit zero position codes. Additionally, the tolerance range of zero positioning performance for each working parameter is examined. By leveraging the adversarial network structure, this study generates the optimization of a 150-bit code and processes the tests of the zero position code by using simulation results. The following working parameter ranges for code design are recommended on the basis of theoretical and experimental results: b greater than 10 μm, d and α within 1000 μm and 3490 μrad, and avoidance of intervals with sharp changes in the full width at half maximum. The proposed code design and parameter optimization lay a solid foundation for research and engineering applications in absolute measurement field and have considerable potential for generalization and wide applicability.
How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method
Authors: Ganasegeran Kurubaran , Abdul Manaf Mohd Rizal , Safian Nazarudin , Waller Lance A. , Mustapha Feisul Idzwan , Abdul Maulud Khairul Nizam , Mohd Rizal Muhammad Faid
Published: February 2024

Accurate assessments of epidemiological associations between health outcomes and routinely observed proximal and distal determinants of health are fundamental for the execution of effective public health interventions and policies. Methods to couple big public health data with modern statistical techniques offer greater granularity for describing and understanding data quality, disease distributions, and potential predictive connections between population-level indicators with areal-based health outcomes. This study applied clustering techniques to explore patterns of diabetes burden correlated with local socio-economic inequalities in Malaysia, with a goal of better understanding the factors influencing the collation of these clusters. Through multi-modal secondary data sources, district-wise diabetes crude rates from 271,553 individuals with diabetes sampled from 914 primary care clinics throughout Malaysia were computed. Unsupervised machine learning methods using hierarchical clustering to a set of 144 administrative districts was applied. Differences in characteristics of the areas were evaluated using multivariate non-parametric test statistics. Five statistically significant clusters were identified, each reflecting different levels of diabetes burden at the local level, each with contrasting patterns observed under the influence of population-level characteristics. The hierarchical clustering analysis that grouped local diabetes areas with varying socio-economic, demographic, and geographic characteristics offer opportunities to local public health to implement targeted interventions in an attempt to control the local diabetes burden.
Assessment on natural ventilation and pollutant dispersion around sunken squares by transient simulation
Authors: Hu Mengjuan , Zhong Jiading , Chu Yujie , Liu Jianlin
Published: February 2024

Sunken square is a semi-open public space that has been gaining popularity in urban planning and designs. Its semi-open design is beneficial to ventilation of the connected underground spaces, but it is also subject to potential exposure to ground-level traffic pollutants. To evaluate the semi-open design’s influence on the balance between underground ventilation efficiency and the pollutant exposure, this study uses large eddy simulation (LES) to simulate turbulent wind flow characteristics and pollutant dispersion in a typical sunken square. The sunken square is connected to two indoor spaces with single-sided opening, and the design features of staircase and arcade are further tested for their influences on the wind flow field. The air change rate per hour (ACH, h−1) is adopted to quantify the ventilation efficiency of the two connected indoor spaces. Results show that the staircases amplify wind velocities for the indoor spaces but also bring higher pollutant concentrations inside together. Moreover, the design of the arcade at the opening prompts the vortex to shift towards the entrance, leading to a heightened concentration of pollutants. Meanwhile, the effective ACH is mostly contributed by the turbulent diffusion (ACHt), while the mean flow (ACHm) has much less effect on the ventilation of the indoor spaces. These findings of this study provide references for sunken square design.
Virasoro Constraints for Toric Bundles
Authors: Coates Tom , Givental Alexander , Tseng Hsian-Hua
Published: February 2024

We show that the Virasoro conjecture in Gromov–Witten theory holds for the the total space of a toric bundle

$E \to B$

if and only if it holds for the base B. The main steps are: (i) We establish a localization formula that expresses Gromov–Witten invariants of E, equivariant with respect to the fiberwise torus action in terms of genus-zero invariants of the toric fiber and all-genus invariants of B, and (ii) we pass to the nonequivariant limit in this formula, using Brown’s mirror theorem for toric bundles.
The many swords of Shivaji: Searching for a weapon, finding a nation
Authors: Halladay Andrew
Published: February 2024

Since at least the nineteenth century, the Maratha warrior-king Shivaji (r. 1674–80) has served as a central symbol in Indian politics. This article interrogates his legacy through the lens of his famous sword, the Bhavani Talvar. At least three swords have been identified as this weapon since the nineteenth century; by analysing each of these claims in turn, I consider how the discourse around Shivaji’s sword(s) traces the evolving legacy of Shivaji himself. Interested less in the historical merits of these claims than in the socio-political work they perform, I seek to uncover why the last of these three, now in London, has become essentially synonymous with the Bhavani Talvar in the popular sphere. Ultimately, I attribute this preference to the object’s political resonance: supposedly given to the Prince of Wales by a descendant of Shivaji in 1875, the object has been a rallying cry for Indian politicians of diverse ideological persuasions, who, in demanding its return, have sought to position themselves as the heirs to Shivaji and the healers of a nation still ailing from colonial wounds.
POVERTY, AGENCY, AND DEVELOPMENT
Authors: Rahman Tauhidur
Published: February 2024

This essay provides an account of four interrelated ideas. First, a person who is not poor by the standard conception of poverty can still be functionally poor. Second, poverty is a relationship between the poor and their environment (community, local markets, and local institutions). Third, poverty is a determinant of agency and impedes its exercise. Fourth, promoting agency promotes development. I conclude that agency is central to understanding both poverty and development.
USING BEHAVIORAL ECONOMICS TO REDUCE POVERTY AND OPPRESSION
Authors: Hoff Karla , Demeritt Allison
Published: February 2024

Until recently, economics conceived of poverty solely as a lack of material resources. This view likely captures the reality of poverty experienced by many people around the globe. However, two waves of behavioral economics demonstrate that the narrowing of people’s external environments may change people themselves: poverty lowers the quality of decision-making and poverty and oppression may depress the capacity to aspire. Poverty and a history of oppression also change how individuals are perceived. To overcome these effects may require helping people acquire new mental models. This essay discusses key findings from behavioral economics, the implications for agency, and some interventions with promising outcomes. We hope to inspire scholars and policymakers to think more deeply about the nature of poverty and oppression and to consider policies that target the psychological and sociological factors that create cycles of poverty.
The National Health Service urgent cancer referral pathway for suspected urological cancers: early economic evaluation of a risk prediction test
Authors: Cocco Paola , Smith Alison Florence , Neal Richard D. , Shinkins Bethany
Published: February 2024

Objectives

In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test – the PinPoint test – to triage and prioritize patients urgently referred with suspected urological cancers.

Methods

Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained.

Results

Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain.

Conclusions

Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.
Role of SST in Seasonal Western North Pacific Anomalous Anticyclone: Insights From AMIP Simulations in CMIP6
Authors: Wu Shuyan , Lin Wenshi , Dong Lu , Song Fengfei , Yang Song , Lu Zhiyuan , Hu Xiaoming
Published: February 2024

The western North Pacific anticyclone (WNPAC) significantly influences the East Asian climate and is modulated by tropical sea surface temperature (SST). This study uses 142 AMIP simulations from 33 Coupled Model Intercomparison Project (CMIP6) models to quantify the contributions of SST to the interannual variability of the WNPAC. SST forcing accounts for 66%, 77%, and 49% of the WNPAC variance in winter, spring, and summer, respectively. The persistence of the WNPAC depends on the relaying effects of SST in three tropical oceans. CMIP6 models exhibit excessive precipitation response to the Pacific SST, leading to an overestimated (underestimated) Pacific (Indian Ocean) effect in modulating the summer WNPAC. Sensitivity experiments with an atmospheric model confirm the crucial role of the Pacific in regulating the WNPAC interannual variation and the contribution from the tropical North Atlantic in spring. The tropical Indian Ocean only exerts a minor impact on the WNPAC when excluding the interactions with other oceans.
Increasing Racial and Ethnic Diversity in Physical Geography
Authors: Shepherd James , Bendix Jacob , Urban Michael
Published: February 2024

Geography, a discipline combining geosciences and social sciences, is becoming more demographically diverse overall. But physical geography is lagging behind and needs to catch up.
Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI
Authors: Sun Quan , Rowland Bryce T. , Chen Jiawen , Mikhaylova Anna V. , Avery Christy , Peters Ulrike , Lundin Jessica , Matise Tara , Buyske Steve , Tao Ran , Mathias Rasika A. , Reiner Alexander P. , Auer Paul L. , Cox Nancy J. , Kooperberg Charles , Thornton Timothy A. , Raffield Laura M. , Li Yun
Published: February 2024

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women’s Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
C2-methyladenosine in tRNA promotes protein translation by facilitating the decoding of tandem m2A-tRNA-dependent codons
Authors: Duan Hong-Chao , Zhang Chi , Song Peizhe , Yang Junbo , Wang Ye , Jia Guifang
Published: February 2024

RNA modification C2-methyladenosine (m2A) exists in both rRNA and tRNA of Escherichia coli (E. coli), installed by the methyltransferase RlmN using a radical-S-adenosylmethionine (SAM) mechanism. However, the precise function of m2A in tRNA and its ubiquity in plants have remained unclear. Here we discover the presence of m2A in chloroplast rRNA and tRNA, as well as cytosolic tRNA, in multiple plant species. We identify six m2A-modified chloroplast tRNAs and two m2A-modified cytosolic tRNAs across different plants. Furthermore, we characterize three Arabidopsis m2A methyltransferases—RLMNL1, RLMNL2, and RLMNL3—which methylate chloroplast rRNA, chloroplast tRNA, and cytosolic tRNA, respectively. Our findings demonstrate that m2A37 promotes a relaxed conformation of tRNA, enhancing translation efficiency in chloroplast and cytosol by facilitating decoding of tandem m2A-tRNA-dependent codons. This study provides insights into the molecular function and biological significance of m2A, uncovering a layer of translation regulation in plants.
The impacts of active and self-supervised learning on efficient annotation of single-cell expression data
Authors: Geuenich Michael J. , Gong Dae-won , Campbell Kieran R.
Published: February 2024

A crucial step in the analysis of single-cell data is annotating cells to cell types and states. While a myriad of approaches has been proposed, manual labeling of cells to create training datasets remains tedious and time-consuming. In the field of machine learning, active and self-supervised learning methods have been proposed to improve the performance of a classifier while reducing both annotation time and label budget. However, the benefits of such strategies for single-cell annotation have yet to be evaluated in realistic settings. Here, we perform a comprehensive benchmarking of active and self-supervised labeling strategies across a range of single-cell technologies and cell type annotation algorithms. We quantify the benefits of active learning and self-supervised strategies in the presence of cell type imbalance and variable similarity. We introduce adaptive reweighting, a heuristic procedure tailored to single-cell data—including a marker-aware version—that shows competitive performance with existing approaches. In addition, we demonstrate that having prior knowledge of cell type markers improves annotation accuracy. Finally, we summarize our findings into a set of recommendations for those implementing cell type annotation procedures or platforms. An R package implementing the heuristic approaches introduced in this work may be found at https://github.com/camlab-bioml/leader.
Rapid synthesis of phosphor-glass composites in seconds based on particle self-stabilization
Authors: Sun Yongsheng , Wang Yuzhen , Chen Weibin , Jiang Qingquan , Chen Dongdan , Dong Guoping , Xia Zhiguo
Published: February 2024

Phosphor-glass composites (PGC) are excellent candidates for highly efficient and stable photonic converters; however, their synthesis generally requires harsh procedures and long time, resulting in additional performance loss and energy consumption. Here we develop a rapid synthetic route to PGC within about 10 seconds, which enables uniform dispersion of Y3Al5O12:Ce3+ (YAG:Ce) phosphor particles through a particle self-stabilization model in molten tellurite glass. Thanks for good wettability between YAG:Ce micro-particles and tellurite glass melt, it creates an energy barrier of 6.94 × 105 zJ to prevent atomic-scale contact and sintering of particles in the melt. This in turn allows the generation of YAG:Ce-based PGC as attractive emitters with high quantum efficiency (98.4%) and absorption coefficient (86.8%) that can produce bright white light with luminous flux of 1227 lm and luminous efficiency of 276 lm W−1 under blue laser driving. This work shows a generalizable synthetic strategy for the development of functional glass composites.
Acoustic-driven magnetic skyrmion motion
Authors: Yang Yang , Zhao Le , Yi Di , Xu Teng , Chai Yahong , Zhang Chenye , Jiang Dingsong , Ji Yahui , Hou Dazhi , Jiang Wanjun , Tang Jianshi , Yu Pu , Wu Huaqiang , Nan Tianxiang
Published: February 2024

Magnetic skyrmions have great potential for developing novel spintronic devices. The electrical manipulation of skyrmions has mainly relied on current-induced spin-orbit torques. Recently, it was suggested that the skyrmions could be more efficiently manipulated by surface acoustic waves (SAWs), an elastic wave that can couple with magnetic moment via the magnetoelastic effect. Here, by designing on-chip piezoelectric transducers that produce propagating SAW pulses, we experimentally demonstrate the directional motion of Néel-type skyrmions in Ta/CoFeB/MgO/Ta multilayers. We find that the shear horizontal wave effectively drives the motion of skyrmions, whereas the elastic wave with longitudinal and shear vertical displacements (Rayleigh wave) cannot produce the motion of skyrmions. A longitudinal motion along the SAW propagation direction and a transverse motion due to topological charge are simultaneously observed and further confirmed by our micromagnetic simulations. This work demonstrates that acoustic waves could be another promising approach for manipulating skyrmions, which could offer new opportunities for ultra-low power skyrmionics.