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Job satisfaction and its associated factors among health care workers in Saint Paul’s Hospital Millennium Medical College, Ethiopia

Background Job satisfaction, a positive emotional state from evaluating work experiences, has a global prevalence of 46.68% among healthcare workers, often lower than other public servants due to challenging conditions. Improving job satisfaction is vital for better healthcare services. However, information on the level of job satisfaction among health professionals in Ethiopia remains scarce. This study sought to assess job satisfaction and its associated factors among health professionals at Saint Paul’s Hospital Millennium Medical College in Addis Ababa, Ethiopia. Methods An institution-based cross-sectional study was conducted from April 03/2023 to May 10/2023, involving 439 randomly selected healthcare workers. Data collection utilized the interviewer-administered Minnesota Satisfaction Questionnaire. Ordinal logistic regression was applied to identify factors associated with job satisfaction. Statistical significance was determined by a p-value of less than 0.05 or a 95% confidence interval for the adjusted odds ratio excluding one. Results All 439 healthcare workers participated, achieving a 100% response rate. Job satisfaction levels were categorized as very dissatisfied (27.1%), dissatisfied (26.2%), satisfied (24.8%), and very satisfied (21.9%). Factors associated with decreased job satisfaction included a monthly salary below 8,000 ETB (AOR = 0.377, CI: 0.174–0.814), salary of 8,000–10,000 ETB (AOR = 0.249, CI: 0.117–0.571), history of headaches (AOR = 0.607, CI: 0.406–0.908), working in emergency (AOR = 0.205, CI: 0.084–0.502), inpatient (AOR = 0.391, CI: 0.167–0.916), or radiology environments (AOR = 0.081, CI: 0.013–0.489). Increased job satisfaction was linked to nursing (AOR = 1.679, CI: 1.011–2.787) and radiology professions (AOR = 35.21, CI: 4.14–299.39). Conclusion Factors such as low salary and high-stress work environments reduce job satisfaction, necessitating strategies to improve workplace conditions and revise salary structures to foster greater satisfaction among healthcare workers. The hospital should address high-stress environments like emergency and inpatient settings and offer support to healthcare workers with headaches. Moreover, the Ministry of Health should revise salary structures and assess work environments to enhance healthcare workers’ job satisfaction.

Influence of nitrogen addition on soil respiration and soil properties in urban forests in Hefei city in China

With the continuous development of urbanization, nitrogen deposition has affected the regeneration capacity of urban forest soil. This study focused on Quercus acutissima Carruth forest in a southern city Hefei in China. The effects of different nitrogen addition rates on both the soil respiration rate and the soil properties of urban forests were studied. In addition, the effects of seasonal changes on soil respiration were also analyzed. The experimental results showed that low nitrogen addition rate (5 g·m-2·yr-1) increased soil respiration rate by about 11% in summer, but decreased it by about 6% in winter, with a range of 5% to 20%. High nitrogen addition (15 g·m-2·yr-1) significantly increased soil temperature by about 12% in summer (p < 0.05), and significantly decreased soil temperature by about 13% in winter (p < 0.05), indicating the seasonal regulation effect of nitrogen addition on soil temperature. As a result, the soil respiration rate was 3.26 ± 0.45 μmol m-2·s-1 in summer and 0.51 ± 0.07 μmol m-2·s-1 in winter. The results indicated that the high nitrogen addition had a significant effect on soil respiration rate, which increased in summer and decreased in winter. Soil moisture content and temperature had significant effects on soil respiration rate, especially in the suburban test site. Nitrogen addition significantly increased soil total nitrogen and nitrate nitrogen contents (p < 0.05), but had no significant effect on soil pH value. Structural equation modeling analysis showed that nitrogen addition promoted soil microbial activity, releases heat, and thus increases soil temperature. Meanwhile, this method affected soil respiration rate, soil moisture, soil total nitrogen, and nitrate nitrogen content, directly or indirectly regulating soil heterotrophic respiration and autotrophic respiration. In conclusion, this study revealed the significant effects of nitrogen addition on urban forest soil respiration and its components, which provided data support and theoretical reference for understanding the dynamic changes of urban ecosystem carbon cycle, and was of great significance for guiding future urban greening and ecological protection work.

Cross sectional analysis of clinical trials search results for cancer patients using a navigator-assisted clinical trials search using five different search engines

Background Clinical trials play a critical role in providing patients with access to novel treatments and therapies. However, limitations in clinical trial search engines impede healthcare professionals and patients from accessing the most suitable clinical trials. This study aimed to address this issue by conducting a critical analysis of several prominent clinical trial search websites, including ClinicalTrials.gov, Canadian Cancer Trials, Clinical Trials Ontario, Canadian Cancer Clinical Trials Network, and Q-CROC. Methods To identify areas for improvement, three skilled clinical trials navigators independently curated clinical trial searches for 18 cancer patients over a 2-month period. After verifying patients’ eligibility for enrollment in clinical trials, the navigators documented their search outcomes and identified several limitations in the current search engines. Results Careful curation of clinical trials for 18 patients revealed 247 trials. However, 140 eligible trials out of 247 (57% with 95% binomial confidence interval [50%, 63%]) were found only on alternative websites yet not discoverable on the initial ClinicalTrials.gov searches, even though they were listed on ClinicalTrials.gov. Our study revealed multiple deficiencies in available clinical trials search engines. Lack of reliability was repeatedly identified in all search engines. Discussion This study highlights that the current clinical trial search system needs improvement to enhance patient outcomes. It needs to be highlighted that these searches were performed by trained and dedicated clinical trials navigators. The challenges facing patients and health care professionals in navigating would be much greater. The findings from this study can serve as a foundation for the development of enhanced search engines with improved functionality, which will enable healthcare professionals and patients to find and access the most suitable clinical trials with greater ease and accuracy.

Analysis of the deterioration process of DC XLPE cable with protrusion defect based on the development of partial discharge

High-voltage direct current (HVDC) cables are essential for long-distance power transmission, particularly in renewable energy applications. Cross-linked polyethylene (XLPE) insulation is commonly used in these cables, but protrusion defects that occur during manufacturing can distort the electric field and initiate partial discharge (PD), accelerating insulation degradation. In this study, partial discharge experiments were conducted at 50 °C and 80 kV to investigate the behavior of internal semi-conductive protrusion defects in insulation, following methodologies aligned with relevant industry standards IEC 60270 for partial discharge measurements. This voltage condition is obtained from the previous pre-test using the same model, and can ensure that the cable can generate partial discharge under the conditions of 50°C and 80kV, but there will be no rapid deterioration of the cable leading to breakdown, which meets the needs of this experiment. The discharge process is divided into stages, and the relationship between discharge frequency, quantity, and cumulative discharge is explored. The results reveal a clear increase in discharge activity, especially in the fourth stage, which corresponds to the accelerated development of the discharge channel and impending insulation breakdown. These findings provide valuable insights into the defect’s progression and highlight the risks of protrusion defects in HVDC cable insulation. This research contributes to the understanding of insulation degradation mechanisms and offers important data for improving the design, manufacturing, and maintenance of HVDC cables.

Research on group type theory and its functorial semantic models in category logic

This paper explores the introduction of group structures within type theory, drawing from the algebraic theory proposed by Roy L. Crole. We define types with group structures and demonstrate that models of these types in categories with finite products can be interpreted as group objects. Each equation within the context of group theory types corresponds to a commutative diagram, representing the axioms of groups, inspired by Lawvere’s functorial semantics. Moreover, we clarify the role of control equations associated with fundamental properties of groups, such as operations and identities. By formalizing a type referred to as “Group Type," which involves integrating group operations and the equations they satisfy into an algebraic type, we incorporate the algebraic structure of a specific group into this type. This Group Type represents a concrete algebraic structure. In practical applications, the introduction of group structures into types is anticipated to optimize algorithms and data structures, leveraging the algebraic properties of groups to enhance computational efficiency. Furthermore, our exploration is not limited to mathematical conversions; it is also envisioned to extend to the application in various type systems, providing support for future research in formal verification and program analysis in computer science.

Marine sentinels using eDNA to track Physalia sp. in the Gulf of Thailand

Physalia sp. is among the world’s most hazardous marine species, posing a significant threat to public safety and Thailand’s tourism sector. Traditional survey methods such as trawling and netting are time-consuming, potentially disruptive to marine ecosystems, and often lack the precision needed for effective monitoring. This study employed environmental DNA (eDNA) analysis to investigate the distribution of Physalia sp. across 45 sampling sites in eight provinces along the Gulf of Thailand. Using species-specific primers and probes targeting the COI region, we successfully detected Physalia sp. eDNA in four provinces: Chonburi, Rayong, Chumphon, and Songkhla. Notably, high eDNA concentrations were observed in Songkhla province, correlating with direct beach observations and public health warnings. The detection in Chumphon province represents a previously undocumented distribution area for this species in Thailand. Bayesian occupancy modeling revealed moderate true-positive detection rates for field samples (θ11 = 0.627) and high rates for qPCR replicates (p11 = 0.9), with notably low false-positive probabilities (θ10 = 0.008, p10 = 0.01), demonstrating the reliability of our eDNA-based approach. These findings demonstrate the utility of eDNA technology as a non-invasive, sensitive tool for monitoring hazardous marine species, with important implications for public safety and marine ecosystem management.

Isolated human lens interferometric surface radius of curvatures: Implications for the mechanism of accommodation

Accurate central surface radius of curvature (RoC) measurements of isolated human lenses are essential for understanding the zonular forces required to modify human lens shape to focus at near; i.e., accommodate. The human lens can be described as an encapsulated oblate spheroid, with its minor axis aligned with its optical axis. The lens is suspended by zonular fibers that originate from the epithelium of the ciliary body and insert into the equatorial region of the lens capsule. According to Helmholtz’s theory of accommodation when the eye views a distant object (the unaccommodated state), the ciliary muscle is fully relaxed and the zonules are under maximal tension. This tension flattens both the central and peripheral lens surfaces resulting in minimal central optical power (COP). During near focus (accommodation), contraction of the ciliary muscle reduces zonular tension, allowing the elastic capsule to restore the lens to a more rounded shape. This increases the curvature of the lens surfaces, central thickness, and COP. Consequently, isolated lenses without zonular tension from young donors (20–30 years old) would be expected to exhibit maximum COP. However, the companion independent profilometric equation fitting study found that, within central optical zones ≤ 3 mm, 10 fresh isolated lenses from donors in this age range actually had minimal COP. The present study utilizes a white light scanning interferometer (WLSI) with a 10x objective that was validated by measuring RoCs of glass and porcine lenses. Fourteen transparent human lenses were obtained from both eyes of seven donors aged 20–30 years of whom 2 were female and 5 were male. One lens of each donor was placed in preservative media and the contralateral lens in culture media within 11:26 ± 5:15 (range: 4:47–21:54) of the donor’s death. Two of the lenses stored in the culture media had torn capsules and were excluded from the study. Central thickness and WLSI surface vertex RoCs of 12 lenses were measured within 16:27 ± 5:22 (range: 10:11–25:33) of the donor’s death. Mean central thickness, anterior and posterior vertex RoCs and COP were 3.54 ± 0.07 mm, 10.2 ± 0.9 mm, 6.8 ± 1.0 mm, and 20.7 ± 2.1 diopters, respectively. These results confirm the companion study that isolated human lenses have low COP consistent with the unaccommodated state of lenses in vivo. Therefore, relaxation of all the zonules does not increase COP and cannot be the basis for the mechanism of accommodation. These results have implications for the development and treatment of myopia, presbyopia, glaucoma, cortical cataracts and design of accommodative intraocular lenses.

What are memories made of? A survey of neuroscientists on the structural basis of long-term memory

Despite the last decade’s development of optogenetic methods for artificially manipulating engrams, and subsequent claims that there is a consensus that memories are stored in ensembles of synaptic connections, it remains unclear to what degree there truly is unanimity within the neuroscientific community about the neurophysiological basis of long-term memory. We surveyed 312 neuroscientists, comprising one cohort of experts on engram research and another of general neuroscientists, to assess this community’s views on how memories are stored. While 70.5% of participants agreed that long-term memories are primarily maintained by neuronal connectivity patterns and synaptic strengths, there was no clear consensus on which specific neurophysiological features or scales are critical for memory storage. Despite this, the median probability estimate that any long-term memories could potentially be extracted from a static snapshot of brain structure was around 40%, which was also the estimate for whether a successful whole brain emulation could theoretically be created from the structure of a preserved brain. When predicting the future feasibility of whole brain emulation, the median participant estimated this would be achieved for C. elegans around 2045, mice around 2065, and humans around 2125. Notably, neither research background nor expertise level significantly influenced views on whether memories could be extracted from brain structure alone. Our findings suggest that while most neuroscientists believe memories are stored in structural features of the brain, fundamental questions about the precise physical basis of memory storage remain unresolved. These findings have important implications for both theoretical neuroscience and the development of technologies aimed at preserving or extracting memory-related information.

Reply to Musculus et al.: A case of offside in scientific discourse?

Why “decoding the elite soccer player’s psychological profile” fails to score

Structure of the virulence-associated <i>Neisseria meningitidis</i> filamentous bacteriophage MDAΦ

Neisseria meningitidis is a human commensal bacterium that can opportunistically invade the bloodstream and cross the blood–brain barrier, where it can cause septicemia and meningitis. These diseases, if left untreated, can be lethal within hours. Hyperinvasive N. meningitidis strains often express a genomically encoded filamentous bacteriophage called MDAΦ, which promotes colonization of mucosal host surfaces to facilitate bacterial invasion. How this phage is organized and how it promotes biofilm formation and infection at the molecular level is unclear. Here, we present an electron cryomicroscopy structure of the MDA phage, showing that MDAΦ is a class I filamentous inovirus, with the major capsid protein (MCP) arranged within the phage as a highly curved and densely packed α-helix. Comparison with other filamentous bacteriophages offers clues about inoviral genome encapsidation mechanisms, providing a framework for understanding the evolutionary diversity of inoviruses. A disordered, N-terminal segment in the MCP presents hydrophobic patches on the surface of assembled phage particles, which, together with electron cryotomography data of phage bundles, furnishes a structural rationale for phage–phage interactions that were seen previously in an epithelium adhesion infection model of N. meningitidis . Taken together, our results shed light on the structure, organization, and higher-order assembly of a biomedically relevant phage encoded in the genome of a human pathogen. Molecular insights gleaned from this study increase our understanding of phage evolution, phage-mediated bacterial adhesion, and pathogenicity.

Participation bias in the estimation of heritability and genetic correlation

It is increasingly recognized that participation bias can pose problems for genetic studies. Recently, to overcome the challenge that genetic information of nonparticipants is unavailable, it is shown that by comparing the IBD (identity by descent) shared and not-shared segments between participating relative pairs, one can estimate the genetic component underlying participation. That, however, does not directly address how to adjust estimates of heritability and genetic correlation for phenotypes correlated with participation. Here, we demonstrate a way to do so by adopting a statistical framework that separates the genetic and nongenetic correlations between participation and these phenotypes. Crucially, our method avoids making the assumption that the effect of the genetic component underlying participation is manifested entirely through these other phenotypes. Applying the method to 12 UK Biobank phenotypes, we found eight that have significant genetic correlations with participation, including body mass index, educational attainment, and smoking status. For most of these phenotypes, without adjustments, estimates of heritability and the absolute value of genetic correlation would have underestimation biases.

Diffusion-limited settling of highly porous particles in density-stratified fluids

The vertical transport of solid material in a stratified medium is fundamental to a number of environmental applications, with implications for the carbon cycle and nutrient transport in marine ecosystems. In this work, we study the diffusion-limited settling of highly porous particles in a density-stratified fluid through a combination of experiment, analysis, and numerical simulation. By delineating and appealing to the diffusion-limited regime wherein buoyancy effects due to mass adaptation dominate hydrodynamic drag, we derive a simple expression for the steady settling velocity of a sphere as a function of the density, size, and diffusivity of the solid, as well as the density gradient of the background fluid. In this regime, smaller particles settle faster, in contrast with most conventional hydrodynamic drag mechanisms. Furthermore, we outline a general mathematical framework for computing the steady settling speed of a body of arbitrary shape in this regime and compute exact results for the case of general ellipsoids. Using hydrogels as a highly porous model system, we validate the predictions with laboratory experiments in linear stratification for a wide range of parameters. Last, we show how the predictions can be applied to arbitrary slowly varying background density profiles and demonstrate how a measured particle position over time can be used to reconstruct the background density profile.

Synergetic hydrogen-bond network of functionalized graphene and cations for enhanced atmospheric water capture

Water molecules at the solid–liquid interface display intricate behaviors sensitive to small changes. The presence of different interfacial components, such as cations or functional groups, shapes the physical and chemical properties of the hydrogen-bond network. Understanding such interfacial hydrogen-bond networks is essential for a large range of applications and scientific questions. To probe the interfacial hydrogen-bond network, atmospheric water capture is a powerful tool. Here, we experimentally observe that a calcium ion on a calcium-intercalated graphene oxide aerogel (Ca-GOA) surface captures 3.2 times more water molecules than in its freestanding state. From experimental Van’t Hoff estimation and density functional theory (DFT) calculations, we uncover the synergistically enhanced hydrogen-bond network of the calcium ion–epoxide complex due to significantly larger polarizations and hydrogen bond enthalpies. This study reveals valuable insights into the interfacial water hydrogen-bond network on functionalized carbon–cation complexed surfaces and potential pathways for future atmospheric water generation technologies.

Gut microbiome and host TOR pathway interact to regulate predator-induced aversive memory in <i>Drosophila melanogaster</i>

The gut microbiome has emerged as a key factor influencing a wide range of host physiological processes and behaviors, though the mechanisms behind these effects remain only partially understood. In this study, we explored the role of the gut microbiome in memory regulation using a parasitoid wasp-induced oviposition depression paradigm in Drosophila melanogaster . Our findings show that flies with depleted gut microbiota, either through axenic culture or antibiotic treatment, exhibited significant memory impairments. However, reintroducing the commensal bacterium Lactobacillus plantarum alone was sufficient to restore memory, while coinoculation with Acetobacter pomorum further enhanced memory performance. Hemolymph metabolomic analyses revealed reduced amino acid levels in antibiotic-treated flies, which were linked to impaired Drosophila target of rapamycin (dTOR) signaling. Additionally, genetic manipulation of dTOR or dietary supplementation with branched-chain amino acids either mimicked or rescued the memory deficits caused by antibiotic treatments. These results suggest that the gut microbiome is essential for regulating memory function by maintaining amino acid homeostasis and proper dTOR signaling, with profound implications for advancing knowledge of cognitive regulation.

Large language models show amplified cognitive biases in moral decision-making

As large language models (LLMs) become more widely used, people increasingly rely on them to make or advise on moral decisions. Some researchers even propose using LLMs as participants in psychology experiments. It is, therefore, important to understand how well LLMs make moral decisions and how they compare to humans. We investigated these questions by asking a range of LLMs to emulate or advise on people’s decisions in realistic moral dilemmas. In Study 1, we compared LLM responses to those of a representative U.S. sample ( N = 285) for 22 dilemmas, including both collective action problems that pitted self-interest against the greater good, and moral dilemmas that pitted utilitarian cost–benefit reasoning against deontological rules. In collective action problems, LLMs were more altruistic than participants. In moral dilemmas, LLMs exhibited stronger omission bias than participants: They usually endorsed inaction over action. In Study 2 ( N = 474, preregistered), we replicated this omission bias and documented an additional bias: Unlike humans, most LLMs were biased toward answering “no” in moral dilemmas, thus flipping their decision/advice depending on how the question is worded. In Study 3 ( N = 491, preregistered), we replicated these biases in LLMs using everyday moral dilemmas adapted from forum posts on Reddit. In Study 4, we investigated the sources of these biases by comparing models with and without fine-tuning, showing that they likely arise from fine-tuning models for chatbot applications. Our findings suggest that uncritical reliance on LLMs’ moral decisions and advice could amplify human biases and introduce potentially problematic biases.

AI assessment changes human behavior

AI is increasingly replacing human decision-makers across domains. AI-based tools have become particularly common in assessment decisions, such as when recruiting employees or admitting students. Calls for transparency and new legislation require organizations to disclose the use of AI assessment tools, thus making people under assessment aware of its use. We investigate whether this shift from human to AI assessment affects people’s behavior during the assessment. We propose that people emphasize their analytical characteristics and downplay their intuitive and emotional ones under AI (vs. human) assessment, a phenomenon we label “the AI assessment effect.” Twelve studies (eight in text and four in the Supporting Information; N = 13,342) document the AI assessment effect and its underlying mechanism: the lay belief that AI prioritizes analytical characteristics in its assessment. Whereas prior work has studied perceptions of AI assessment tools and their productivity gains, the current research demonstrates systematic behavioral changes because of AI assessment. The findings offer theoretical contributions to the psychology of AI and practical insights for organizations using AI assessment.

A norm about harvest division is maintained by a desire to follow tradition, not by social policing

Determining how people behave in contexts governed by social norms can clarify both how norms influence human behavior and how norms evolve. We examined cooperative farming harvest division among the Derung, a Tibeto-Burman-speaking horticultural society in southwestern China. In the village of Dizhengdang, the norm dictates that cofarming harvests should be divided equally among participating households. This contrasts with an alternative norm followed in some other Derung villages that holds that harvests should be divided equally among participating laborers. Rational choice theory and evolutionary models of norm-based cooperation assume that individuals weigh the material and social payoffs of different actions and follow norms because doing so maximizes their payoff. However, the behavior of the Derung in Dizhengdang is not consistent with payoff maximization. Using interviews on co-farming behaviors and attitudes, along with an ultimatum game experiment framed as co-farming harvest division, we found that most respondents preferred divisions based on labor contribution. They also accurately guessed that others shared this preference and would approve of such divisions. Nonetheless, they still followed the prevailing norm of dividing by household. Their self-reported explanation for this behavior was that they desired to follow their traditional practices. Such a normative decision-making algorithm can allow individually consequential norms to persist without costly policing by other group members.

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal–melt interface structure.

Beyond additive genetic effects: Explaining family resemblance in school performance across millions of pairs of Norwegian relatives

We investigate the hypothesis that family resemblance on school performance can be fully explained by additive genetic effects and assortative mating. Our sample consists of all schoolchildren who took Norwegian national standardized tests between 2007 and 2019 (N = 936,708). These tests measure aptitude in math and reading comprehension, and are taken the years children turn 10, 13, and 14 y old. We identify millions of pairs of relatives within our sample (82 different kinds, in total), including not only conventional biological relatives such as siblings and cousins, but also relatives-in-law, relatives through adoption, twins, and relatives connected through twins. When fitting models which assume that family resemblance arises solely from additive genetic effects and assortative mating, we find that they describe much of our data well, but that they systematically underestimate the similarity of close relatives (particularly monozygotic twins), maternal relatives, relatives-in-law, and relatives through adoption. We discuss potential explanations for these deviations, including shared-environmental effects, nonadditive genetic effects, and gene–environment interplay.