The coalescence time of bubbles in a liquid depends on the nature of the liquid, which determines both its surface thermodynamics and the molecular interactions between the gas/liquid interfaces, and on the geometry, prescribed by the curvature of the bubbles. Coalescence is well described in pure liquids that have the same composition in bulk and at interfaces and in which the interactions are attractive. In contrast, the mechanisms are poorly understood in more complex liquids in which coalescence times are orders of magnitudes larger than in pure liquids and are unpredictable. To provide insight on these mechanisms, we use model systems: binary mixtures of miscible oils. In these liquids, interfaces have purely attractive molecular interactions and the surface thermodynamics can simply be described using a well-determined Gibbs elastic modulus, which is controlled by the composition of the mixture. We measure the coalescence rate by forming periodic trains of bubbles in millifluidic tubes whose radius varies over 1.5 decade. We report coalescence times spanning more than three decades and, for a given composition, varying according to a power law with curvature, with an exponent larger than that reported in pure liquids and independent of Gibbs elasticity. The experimental behavior is in excellent agreement with a numerical solution of the coupled thermodynamical and hydrodynamical equations, performed in the simple geometry of a suspended liquid film. Our results clearly reveal how geometry and surface thermodynamics modify the coalescence process of bubbles in the limit of small Gibbs elasticity.
Our aim was to assess the knowledge, awareness, and confidence of US primary care providers (PCPs) in assessing multiple myeloma (MM) and related plasma cell disorders. A survey with quantitative and qualitative questions was conducted from October to December 2024. A total of 560 respondents met the criteria of a representative US PCP cohort, but only 300 respondents were invited to continue the rest of the survey. These respondents had ordered serum protein electrophoresis (SPEP) in the past 12 months and believed that SPEP should be ordered for plasma cell disorder diagnosis. Nearly half of the representative US PCP cohort (46%) do not order tests for plasma cell disorders. Among the 300 who do, there is generally good awareness of symptoms and high-risk characteristics, but only 28% follow guideline-recommended paired testing of SPEP and serum free light chains. The majority (80%) lack confidence in appropriate test selection and interpretation, often relying on peers and hematologists for guidance. Additionally, only 15% of the US PCPs have access to and use myeloma diagnostic ordering sets and panels, while 54% express interest in utilizing such tools. The PCPs identified barriers like insufficient education, collaboration, and specialist support to patient care and outcomes. The study reveals significant gaps in the understanding and practice of MM diagnostic testing in primary care. Results indicate insufficient knowledge and inadequate utilization of testing guidelines, including low confidence in test ordering and interpretation. The survey suggests a lack of comprehensive, guideline-adherent MM diagnostic panels offered by US laboratories.
Rapid sequence intubation (RSI) with neuromuscular blocking agents (NMBAs) can result in awareness with paralysis (AWP) if sedation is inadequate. This is of particular concern with rocuronium due to its prolonged half-life. This study evaluated sedation practices before and after the implementation of an RSI clinical decision support (CDS) update with sedation guidance linked to rocuronium orders. This retrospective, multicenter, observational, before-after study included adult patients who received rocuronium for RSI. The preimplementation cohort spanned the period July 1, 2022, to January 1, 2023; the postimplementation cohort spanned the period January 1 to July 1, 2024. Coprimary outcomes were sedative selection and initial sedative dose within 1 hour after rocuronium administration. Secondary outcomes included time to sedative initiation, time to adequate sedation, and incidence of hypotension requiring vasopressors. Groups were compared using a t test or Mann-Whitney U test for continuous variables and χ2 or Fisher's exact test for categorical variables. A total of 713 patients were included (308 in the preimplementation and 405 in the postimplementation cohort). After CDS implementation, propofol use increased (56.8% vs 73.1%, P < 0.0001), and initial dosing increased (median, 5 µg/kg/min vs 20 µg/kg/min; P < 0.0001). Midazolam use decreased (from 32.1% to 19.3%, P < 0.0001). The median (interquartile range [IQR]) time to sedation initiation decreased (from 14 [10-22] minutes to 12 [12-15] minutes; P = 0.001), as did median time to adequate sedation (from 32 [15.3-51.4] minutes to 14 [12-25] minutes; P < 0.0001). The incidence of new-onset hypotension was similar between groups (25.0% vs 25.2%, P = 0.95). A CDS update linking sedation guidance to rocuronium orders resulted in faster initiation of higher doses of sedation after paralysis without increasing hemodynamic instability, supporting the use of CDS strategies in the peri-intubation period.
The human microbiota plays a pivotal role in health, with widespread alterations implicated in conditions ranging from inflammatory disorders to cancer. While correlation-based network analyses have illuminated ecological interactions within these communities, the host environment uniquely mediates microbial relationships, demanding new methods to capture dynamic, condition-dependent modules of species interactions. Here, we present a statistical framework termed differential co-occurrence analysis, which identifies blocks of taxa whose collective presence is strengthened or weakened under distinct host states. By leveraging recent advances in metagenomics that enable detailed taxonomic profiling and higher-order interaction discovery, our method transcends traditional pairwise correlation constraints. Conceptually akin to associative rule mining, it diverges through the integration of robust statistical modeling, directly extracting interactions that differ significantly between conditions. This approach offers a refined lens to dissect microbiota ecology and could pave the way for new insights into microbiome-associated disease mechanisms. The research on the role of the intestinal microbiota in the onset of cancer and as a modulator of anticancer treatments, including chemotherapeutics and immune checkpoint inhibitors, is helping medicine to identify novel strategies for cancer prevention, for the delivery of more effective treatments, and in reducing treatment side effects and complications. Within this context, it is of crucial importance to approach the analysis of clinical microbiome data with an ecology-oriented perspective and to develop bioinformatics tools able to identify functional interactions in bacterial communities of patients from observational cohort studies. Clinical microbiome datasets are typically high dimensional, comprising numerous taxa measured across relatively few samples. This imbalance increases the risk of statistical overfitting and undermines the robustness of analytical findings. However, recent advances in metagenomic bioinformatics pipelines and reference databases have enabled the comprehensive extraction of genetic information from microbiome samples, facilitating the precise characterization of bacterial species presence and absence. In our manuscript, we describe a statistical computational method that we named differential co-occurrence analysis, which focuses on the analysis of the co-presence of microbiota taxa across samples associated with different host conditions. The proposed method can reveal modules of interacting taxa that are strengthened or weakened when the host condition changes (e.g., when passing from a healthy state to a disease state). The method is general and applicable to a broad range of ecological datasets featuring presence/absence data structures. Furthermore, the method accommodates the analysis of higher-order co-occurrence patterns beyond pairwise co-occurrence, thereby enabling the investigation of higher-order interactions, whose detection and identification are a major challenge in ecological network analysis.
Rational design of transition metal complexes with desired optical properties is a major challenge due to high computational costs of quantum-chemical methods that can deliver quantitatively reliable results. We present a machine learning framework for predicting absorption and emission maxima in both transition metal coordination compounds and organic chromophores using joint training on a combined experimental data set. Our featurization strategy integrates ligand environment fingerprints (Morgan), metal center features (Coulomb matrices), and topological descriptors from persistent homology analysis. The combined training data set comprises 19,733 absorption and 2675 emission measurements for 17,359 metal complexes (with focus on Ir, Rh, Pt, and Ru systems) and 17,294 absorption and 18,141 emission measurements for 7065 organic molecules across 365 solvents. Among several architectures evaluated, multilayer perceptrons provide the best absorption predictions (RMSE = 33.5 nm, R2 = 0.83, Pearson r = 0.92 for metal-organic compounds), while gated recurrent units are optimal for emission (RMSE = 41.7 nm, R2 = 0.83, Pearson r = 0.90). Models trained jointly on both data sets show good universal applicability with moderate accuracy trade-offs: RMSE increases by approximately 7-19 nm for organic compounds compared to specialized models, and for metal-organic compounds, RMSE increases by 1-2 nm. In contrast, models trained on organic data alone fail catastrophically when applied to metal complexes (R2 = 0.01). For a test set of 35 metal complexes including metal centers beyond the main training distribution (V, W, Cu, and Os in addition to Ir, Rh, Pt, and Ru), our best models achieve an RMSE of ∼28 nm for absorption maxima, comparable to TDDFT-O3LYP predictions but at substantially lower computational costs. SHAP analysis reveals that Coulomb matrix descriptors are most important for metal complex predictions, while Morgan fingerprints prevail for purely organic compounds. The presented approach enables efficient screening of candidate compounds for various photophysical applications orders of magnitude faster than TDDFT calculations.
Perovskite single crystals (PSCs) are highly promising direct X-ray detection materials, whereas the mechanical brittleness and thermal instability easily bring about stress cracking and structural decomposition under a conventional bonding process, hindering integrated applications. In this work, we developed a photopolymerization-induced heterogeneous bonding technology based on 4-acryloylmorpholine (ACMO) for monolithic PSC integration, which enables effective bonding within seconds via a liquid film transfer method. The interfacial coordination effect between ACMO and PSCs simultaneously achieves defect passivation for the buried surface of PSCs and robust mechanical bonding with tensile and shear strengths of up to 1.81 and 1.50 MPa, respectively. Furthermore, polymerized ACMO has a high resistivity of 7.72 × 1012 Ω·cm that effectively suppresses dark current in the integrated devices. Compared with the control crystal, the dark current of the integrated device is reduced by 2 orders of magnitude, while the limit of detection (LOD) for X-ray detection improves 20-fold. The 5.6% relative standard deviation of dark currents among 6 × 6 pixels and 96% performance retention after 30 days of storage confirm the reliable uniformity and stability. This work provides a novel technical solution for the heterogeneous bonding of PSCs, facilitating the further development of high-performance PSC-integrated optoelectronic devices.
Computing molecular thermodynamic properties is instrumental in multiple scientific disciplines, such as statistical physics, N-body simulations, and molecular docking. However, exact thermodynamic calculations are almost always not feasible. In this work, we introduce a versatile algorithm designed to rapidly compute the two-body partition function, its related thermodynamic properties, and the second virial coefficient for anisotropic nanoparticles and proteins under the rigid-body approximation. Our method involves constructing a quasi-regular grid in the 5D angular space between pairs of arbitrary objects and efficiently scanning the radial-angular space between the rigid molecules. Where available, we find excellent agreement with light and X-ray scattering experiments, as well as with Monte Carlo simulations. Our results suggest a correction to current coarse-grained protein force fields, and we further discover a new, counterintuitive effect of temperature on virial coefficients, caused by a population shift in angular space due to the dielectric response of water. Finally, the grid can serve as an interpolation table for N-body simulations, increasing their performance by orders of magnitude.
Beta-blockers are commonly prescribed for chronic cardiovascular diseases. Despite potential benefits in septic shock, beta-blockers are often held at hospital admission for patients with suspected infection and possible sepsis. We compared the effects of chronic beta-blocker continuation vs. discontinuation on 90-day all-cause mortality among patients admitted from the emergency department with suspected infection. Retrospective cohort study using the target trial emulation framework. We used Cox regression to compare 90-day mortality between treatment groups, with inverse probability of treatment weights to account for baseline differences in sex, race, ethnicity, age, body mass index, presence of a "do not resuscitate" order, comorbidities, and acute illness severity. A single large, academic, tertiary care emergency department in the Midwest United States. Patients 18 years or older on beta-blockers prior to admission hospitalized for suspected infection (defined by orders for blood cultures and broad-spectrum antibiotics). Patients with shock, heart rates less than 40 or greater than 120, or who required an IV beta- or calcium channel blocker at a clinician's discretion were excluded. Continuation of oral beta-blockers within 48 hours of admission vs. no continuation. Of 4635 eligible patients, 1172 (25.3%) received an oral beta-blocker, whereas 3463 (74.7%) did not receive an oral beta-blocker. Beta-blocker continuation was associated with a reduced risk of all-cause mortality within 90 days of hospital admission (hazard ratio 0.77; 95% CI, 0.61-0.98; p = 0.03) and shorter hospital stay (incidence rate ratio 0.39; 95% CI, 0.38-0.41; p < 0.001). There was no significant association between beta-blocker continuation and in-hospital mortality (odds ratio 0.60; 95% CI, 0.30-1.20; p = 0.15). Continuation of chronic beta-blockers in a broad population of patients admitted with suspected infection was associated with improved clinical outcomes. Our findings support the need for controlled experimental studies evaluating the role of chronic beta-blocker continuation among patients hospitalized with possible sepsis.
The biomechanical performance of bileaflet transcatheter mitral valves (TMVs) depends on complex interactions between leaflet material behavior and stent design. However, the contributions of leaflet materials and constitutive models, stent materials, and stent geometry to valve function and durability remain poorly understood. A parametric finite element study was conducted using a CAD model of a bileaflet TMV subjected to physiological pressure loading. Five leaflet material models were evaluated: 3 glutaraldehyde-fixed tissues-bovine pericardium (BP; FBP1, FBP2) and porcine pericardium (PP; FPP)-and 2 unfixed tissues-bovine (UBP) and porcine pericardium (UPP). BP was modeled as a linear elastic (FBP1) and Ogden (FBP2). Each was paired with 2 stent materials, cobalt chromium (CoCr) and nitinol, and 3 stent cell densities (low, medium, high), yielding 30 configurations. Von Mises stresses and relative leaflet opening were quantified. UPP achieved the largest opening (30-32%) with the lowest leaflet 99th percentile stresses (0.048-0.050 MPa), while FBP1 produced the smallest opening (8-9%) and highest leaflet stresses (0.077-0.078 MPa). Leaflet 99th percentile stress was strongly inversely correlated with valve opening (Spearman r=-0.9, p<0.01). Stent material had a negligible effect on valve opening but affected stent stress notably, with nitinol exhibiting about 2-3 orders of magnitude lower stresses compared to CoCr. Increasing stent cell density improved stress distribution with only a modest reduction in opening. Leaflet material model was the primary determinant of bileaflet TMV biomechanical performance, whereas stent material and cell density exerted secondary but meaningful effects. These findings offer insights that may guide the design of more optimized TMV replacement devices.
Self-consistent field theory simulations of rod-coil diblock copolymers in slit confinement present significant numerical challenges due to sharp density gradients near hard walls. To rigorously resolve these systems utilizing the Gaussian and wormlike chain models, a hybrid spectral-compact finite difference scheme is developed on a non-uniform Chebyshev-Gauss-Lobatto grid. Shen's Chebyshev spectral method is employed for the flexible blocks. For the semiflexible blocks, a second-order upwind compact scheme together with an L-stable TR-BDF2 contour-stepping algorithm is adopted. This hybrid framework effectively suppresses spurious numerical oscillations. This unconditionally stable formulation strictly preserves propagator non-negativity and achieves up to a two-orders-of-magnitude speedup over uniform-grid implementations while maintaining linear spatial scaling. Simulations utilizing this advanced framework under neutral wall conditions reveal that the confining walls naturally induce preferential wetting of the semiflexible blocks at the impenetrable boundaries. As the incompressibility penalty increases, the compressible system progressively approaches the incompressible limit. For the selected physical parameters, decreasing the slit width induces a sequence of structural transitions from a smectic-C morphology with three internal periods (SC3) to morphologies with two and one internal periods (SC2 and SC1), and ultimately to a highly compressed smectic-P morphology (SP1). The equilibrium thickness of these confined structures deviates from exact integer multiples of the bulk spatial period. This deviation arises from the volume compensation associated with boundary depletion layers, together with adjustments in the molecular tilt angle and the degree of molecular interdigitation.
Migrant workers are a vulnerable population for hepatitis B virus (HBV) infection. The present study aimed to assess HBV prevalence and identify associated risk factors among migrant workers at a construction site in Qingdao, in order to inform prevention strategies. A random sampling method was used to select 169 migrant workers from a construction site in Qingdao in 2022. Data were collected through questionnaire surveys, and venous blood samples were obtained for serological testing. The electrochemiluminescence method was employed for serological testing to determine the positivity rate of Hepatitis B surface antigen (HBsAg), surface antibody (HBsAb), and core antibody (HBcAb), as well as the overall infection rate of HBV. Multivariate logistic regression analysis was conducted to identify factors associated with HBV infection. Among the 169 participants, the positivity rates of HBsAg, HBsAb, and HBcAb were 4.73%, 52.07%, and 43.20%, respectively, and the HBV infection rate was 46.75%. Multivariate logistic regression analysis revealed that being male, aged 41 years and above, having 2-5 years of working experience at construction sites, and residing in rural areas were risk factors for HBV infection, while a history of hepatitis B vaccination was a protective factor for HBV infection. The positivity rate of HBsAg was higher among migrant workers at a construction site in Qingdao. Several risk factors were identified in relation to HBV infection. Strengthening health education and promoting hepatitis B vaccination are recommended to reduce the infection and prevalence of hepatitis B.
The emergence of multiferroic order in perovskite thin films is governed by symmetry-broken coupling between polar domains and magnetic order parameters; however, currently prevailing theoretical frameworks, due to a constraint of reduced-dimensional approximations, fail to capture the inherent three-dimensional (3D) complexity of domain-mediated cross-correlations. Here, performing atomic-resolution HAADF/iDPC-STEM on BiFeO3 (BFO), we discover a "pseudo-ferroelectric domain wall" bridging (11¯4¯)h/(1¯1¯0)h planes of BFO, in which two-dimensional (2D) projection indicates a domain-wall angle of 54.37°, but the actual 3D orientation remains 70.17°. When the (11¯4¯)h plane is rotated 90° about the [22¯1]h axis, it reveals the atomic arrangement of the (1¯1¯0)h plane, with polarization along [001¯]. These noncanonical 3D walls arise from oxygen-rearrangement-induced structural deviations and asymmetric Fe-O lattice coupling, which generate chiral polarization stabilized by a potent tripartite interaction between ferroelectric, shear, and spin degrees of freedom. This work provides a design principle for reconfigurable domain wall nanoelectronics.
Identifying novel drug-disease associations (DDAs) is critical for advancing drug discovery. While AI-driven approaches have shown promise, most still struggle to maintain semantic consistency between learned high-order representations and the original feature space. Additionally, they often neglect the varying importance of different views and fail to model the semantic gaps between heterogeneous drug and disease features, hindering cross-modal alignment. To overcome these challenges, we propose a novel diffusion-enhanced fine-grained cross-semantic fusion framework for DDA prediction, namely DFCDDA. First, a conditional diffusion-based decoder is leveraged to ensure semantic consistency between the high-order features learned by the model and the original features. Second, an attention-guided fine-grained graph convolutional network dynamically generates soft adjacency matrices from multi-view structural data, enabling precise feature aggregation. Third, a bidirectional cross-attention module aligns heterogeneous drug and disease features and captures their complementary interactions. These three modules work collaboratively to improve the learning of robust drug and disease embeddings. Experiments on three real-world datasets show that DFCDDA consistently outperforms existing approaches in DDA prediction. Case studies further demonstrate its effectiveness in uncovering plausible drug-disease associations.
Compared with conventional solid-solution alloy nanoparticles with disordered atomic structures, platinum (Pt)-based intermetallic compounds (IMCs) are recognized as highly promising electrocatalysts for practical fuel cell applications, on account of their long-range periodically ordered atomic arrangements. Nevertheless, the rational development of Pt-based catalysts featuring both high intrinsic activity and long-term durability remains a key challenge in this field. In this work, by simultaneously introducing manganese (Mn) with low-electronegativity into both the active component and the support, we report an efficient electrocatalyst toward the oxygen reduction reaction (ORR), composed of L12-ordered Pt3Mn nanoparticles on Mn single-atom nitrogen-doped carbon support (L12-Pt3Mn@Mn-N-C). The incorporation of Mn, the strong anchoring effect arising from the hierarchically porous structure of the support, and the directional interfacial electron transfer between L12-Pt3Mn and Mn-N-C synergistically mitigate the adsorption strength of key oxygen intermediates and suppress the dissolution of surface Pt sites. Superior catalytic performance and durability are validated in proton exchange membrane fuel cells (PEMFCs), achieving a peak power density of 1.15 W cm-2 under H2/air conditions. After 30 000 square-wave cycles, the voltage loss at 0.8 A cm-2 is only 19 mV, ranking it among the top-performing Pt-based cathode catalysts reported to date.
In this paper, we address the characterization of the structure of condensed materials, periodic and non-periodic. Carrying out an extensive study of over 7000 different ground-state structures of a 2D lattice model of binary packing, we find a predominance of non-periodic structures (over 96%) that extend across the entire range of possible diversities. These non-periodic structures are resolved by establishing whether a structure will accommodate or reject additional local structures. This property, structural selectivity, is treated as a signature of an underlying ordering principle. The major result of this paper is the determination that roughly 35% of the non-periodic structures are selective and, hence, ordered in some way. This selectivity extends up to a diversity of ∼9, well beyond the upper threshold for diversity in periodically ordered states.
Chemotherapy-induced peripheral neuropathy (CIPN) affects approximately 50% of patients who receive chemotherapy. CIPN often results in dose reductions, therapy discontinuation, and long-term neurological impairment. Despite existing studies, identifying high-risk populations remains challenging, particularly in patients with diabetes, diabetic neuropathy, and those undergoing corticosteroid therapy. We sought to evaluate the key risk factors associated with CIPN by analyzing patient demographics, comorbidities, and chemotherapy regimens, with a specific focus on diabetes-related variables in order to inform early identification and prevention strategies. Retrospective, single-center, observational cohort study. Academic tertiary care cancer center. Adult patients who received chemotherapy between January 2016 and December 2023 were identified through electronic medical records. Patients with CIPN were defined by the International Classification of Disease, Tenth Revision G62.0 diagnosis code (drug-induced polyneuropathy) and an associated diagnosis of "painful peripheral neuropathy." Extracted data included demographics (age, body mass index [kg/m2], race/ethnicity), clinical variables (alcohol use, corticosteroid use, diabetes-related factors), and chemotherapy regimen details. Descriptive statistics, Wilcoxon rank sum, c2/Fisher's exact tests, and multivariable logistic regression were performed. Institutional review board (IRB) approval was obtained (IRB exemption #2024-0139). Among 36,949 patients, significant CIPN risk factors included older age (40-80 years, P < 0.0001), women (odds ratio [OR] 1.89; P < 0.0001), non-Hispanic/non-Latino ethnicity (OR 1.29; P < 0.0001), and corticosteroid use (OR 2.01; P < 0.0001). African American patients had lower odds of CIPN than White patients (OR 0.78; P < 0.0001). Diabetic neuropathy was strongly associated with increased CIPN risk (OR 5.35; P < 0.0001). Alcohol use was inversely associated with CIPN (OR 0.75; P < 0.0001). Several chemotherapy agents also showed significant associations. Our study is limited by its retrospective design, potential misclassification bias in CIPN diagnosis, and reliance on electronic medical records. Alcohol use data were frequently missing or unspecified, limiting interpretation. Key CIPN risk factors include age, race/ethnicity, corticosteroid use, and diabetic neuropathy. Alcohol use appeared inversely associated with CIPN, though causality remains unclear. Individualized patient assessments and proactive management strategies may help reduce CIPN incidence and improve outcomes in patients with cancer who are receiving chemotherapy.
Mental ill-health is common after stroke. Stroke survivors with aphasia are at higher risk of depression and anxiety, but communication impairment makes identification challenging. This study investigates if, how, and by whom mental health is assessed in Swedish stroke care, and whether resources to assess mental health in stroke patients with aphasia are available. A survey was distributed to healthcare professionals (HCP) in stroke care and rehabilitation across Sweden. 981 complete responses were included. HCP perceive mental ill-health as more common among patients with aphasia than among other stroke patients, but that their mental health is assessed less frequently. Assessment procedures are inconsistent. Physicians, psychologists, and social workers are viewed as responsible, but these professions are lacking in many rehabilitation settings and do not always work with patients with aphasia. HCPs attempt to adapt assessment procedures but report lacking aphasia-friendly material and competence in communication strategies. According to HCP, mental health is not assessed adequately, especially in patients with aphasia. More mental health professionals, greater competence in communication strategies, improved collaboration between professions, and access to aphasia-friendly assessment materials are important to improve mental health care for stroke patients with and without aphasia. Standardised procedures for assessing mental health in all stroke patients, including those with aphasia, could improve early identification.Aphasia-friendly materials for mental health assessment are needed, and should be used alongside other strategies that support communication.All healthcare professionals involved in stroke rehabilitation require adequate skills in communicating with individuals with aphasia, in order to enable conversations about mental ill-health.Additional mental health professionals are needed within stroke rehabilitation, as well as increased collaboration between mental health professionals and speech-language pathologists regarding mental ill-health in patients with aphasia.
The belief in the power of the imagination of parents, and especially of the mother, to influence the features of the foetus has been widespread since ancient times. The first reference is in Genesis 30:25-43. It tells the story of how Jacob showed his father-in-law's ewes and goats coloured branches (stripped branches) during the mating season in order to produce spotted offspring. The theory refers not only to animals, but also to human beings, as various sources testify. The power of female imagination could extend from the moment of coitus through to the entire pregnancy, giving rise to congenital features in the foetus. Starting from the widespread idea of the female imagination as a disruptive factor in the entire process of the formation of the future individual, the aim of this article is to focus on one specific aspect of the question: namely, the origin and development of the belief that 'bastard' children resemble their putative fathers rather than their real fathers. To this end, the most significant medical and philosophical sources will be considered, from the origin of this belief, in the late Middle Ages through to the early modern period.
When a molecule or sub-molecular entity is ordered on a surface in a manner that can be described by a tilt- and azimuthal-angle distribution, the projection of the molecular hyperpolarizability into the laboratory frame can be described using spherical harmonics. We illustrate that this lends itself to the construction of ten achiral order parameters associated with vibrational sum-frequency generation. We describe how these order parameters can be extracted from spectral data, first ignoring and then including the dispersion of the local electric fields. We then use these order parameters to determine the most probable orientation distribution without any assumptions about the surface alignment and in the absence of any other type of experimental data. This constitutes a flexible framework for describing a wide array of surface orientation distributions.
With increasing petroleum transport through coastal waters of the northeastern Pacific, understanding the ecological hazards of these mixtures is essential, yet the sublethal impacts on benthic filter feeders remain poorly characterized. The sub-chronic (7-d exposure) effects of crude oil (CO), marine diesel (MD), and diluted bitumen (DB) water-accommodated fractions (WAFs) on the scope for growth (oxygen consumption, food absorption efficiency, and clearance rate), as well as gonadal and digestive gland histopathology in Pacific oysters (Crassostrea gigas) were examined. Initial total polycyclic aromatic compound (TPAC) concentrations in WAFs were ranked CO > MD > DB, which also accumulated within oyster tissues in the same order. Sub-chronic exposures to different WAF dilutions of three petroleum products did not alter any measured endpoints in Pacific oysters. PACs accumulated in oyster tissues had a rapid depuration after the exposure period due to the potential biotransformation of parent hydrocarbons, which could elucidate the lack of significant adverse effects. These results indicate that adult C. gigas maintained physiological and tissue-level integrity under transient, declining petroleum exposure conditions, providing context for interpreting potential impacts of short-term nearshore spill scenarios.