Understanding the interactive effects of temperature and diet on insect life cycles is crucial for effective pest management. Here, the influence of different temperatures and diets on the life cycle of Conogethes punctiferalis was investigated using the age-stage, two-sex life table analysis. The results support the hypothesis that temperature and diets (maize, apple, and artificial diet) significantly influence the entire life cycle performance of C. punctiferalis. The duration of larval development was significantly prolonged, whereas adult lifespan was shortened and showed lower reproductive capacity on apple and artificial diet than maize. The total pre-oviposition period was longer on apples than on maize and artificial diet at both temperatures (20, 26°C). The highest r (0.113 d−1), λ (1.128 d−1), R0 (57.213), and GRR (75.54) of C. punctiferalis were found on maize at 26°C, while the highest T (45.062) was found on apples. Similar results were obtained in the age-specific survival curves (sxj), fecundity (mx), maternity (lxmx), and reproductive value (vxj) of YPM on different host plants when exposed to 20°C. These findings highlight the need for further research into the complex interactions between temperature, diet, and insect life history traits to develop effective pest management strategies and enhance our understanding of insect ecology in agroecosystems.

Graphical models have received an increasing amount of attention in network psychometrics as a promising probabilistic approach to study the conditional relations among variables using graph theory. Despite recent advances, existing methods on graphical models usually assume a homogeneous population and focus on binary or continuous variables. However, ordinal variables are very popular in many areas of psychological science, and the population often consists of several different groups based on the heterogeneity in ordinal data. Driven by these needs, we introduce the finite mixture of ordinal graphical models to effectively study the heterogeneous conditional dependence relationships of ordinal data. We develop a penalized likelihood approach for model estimation, and design a generalized expectation-maximization (EM) algorithm to solve the significant computational challenges. We examine the performance of the proposed method and algorithm in simulation studies. Moreover, we demonstrate the potential usefulness of the proposed method in psychological science through a real application concerning the interests and attitudes related to fan avidity for students in a large public university in the United States.

We propose a two-way Bayesian vector spatial procedure incorporating dimension reparameterization with a variable selection option to determine the dimensionality and simultaneously identify the significant covariates that help interpret the derived dimensions in the joint space map. We discuss how we solve identifiability problems in a Bayesian context that are associated with the two-way vector spatial model, and demonstrate through a simulation study how our proposed model outperforms a popular benchmark model. In addition, an empirical application dealing with consumers’ ratings of large sport utility vehicles is presented to illustrate the proposed methodology. We are able to obtain interpretable and managerially insightful results from our proposed model with variable selection in comparison with the benchmark model.

A new Bayesian multinomial probit model is proposed for the analysis of panel choice data. Using a parameter expansion technique, we are able to devise a Markov Chain Monte Carlo algorithm to compute our Bayesian estimates efficiently. We also show that the proposed procedure enables the estimation of individual level coefficients for the single-period multinomial probit model even when the available prior information is vague. We apply our new procedure to consumer purchase data and reanalyze a well-known scanner panel dataset that reveals new substantive insights. In addition, we delineate a number of advantageous features of our proposed procedure over several benchmark models. Finally, through a simulation analysis employing a fractional factorial design, we demonstrate that the results from our proposed model are quite robust with respect to differing factors across various conditions.

We study household fuel choice in rural China through the lens of social interactions, deploying a structural discrete choice interaction model to explain peer-dependence in household fuel choice. The data comes from the China Family Panel Studies 2010–2020, and we use multiple strategies to examine the robustness of the social interaction effects. We find a significant endogenous social effect, meaning that whether a household chooses non-solid clean fuel for cooking is directly affected by the choice in cooking fuel made by its neighbors in the village. Households with lower non-farm income are more sensitive to the choices of others, and the fuel choices of households with a higher education and/or a higher income attracts more attention from others. Modern communication technologies facilitate information exchange among rural residents, thereby strengthening the endogenous social effect. We suggest that public policies can accelerate rural energy transition by stimulating positive social spillovers.

The wheeled-legged robot combines the advantages of wheeled and legged robots, making it easier to assist people in completing repetitive and time-consuming tasks in their daily lives. This paper presents a study on the kinematic and dynamic modeling, as well as the controller design, of a wheeled biped robot with a parallel five-bar linkage mechanism as its leg module. During the motion of the robot, the robot relies on the tilt angle of the inverted pendulum, and this angle often results in the tilting of the chassis of the robot, presenting challenges for the installation of upper-body payloads and sensor systems. The controller proposed in this paper, which is developed by decoupling the primary motions of the robot and designing a multi-objective, multilevel controller, addresses this issue. This controller employs the pendulum pitch angle of the equivalent inverted pendulum model as the control variable and compensates for the chassis tilt angle (CTA). This control method can effectively reduce the CTA of such robots and eliminate the need for additional counterweights. It also provides a more spacious structural design for accommodating upper-body devices. The effectiveness of this control framework is verified through variable height control, walking on flat ground, and carrying loads over rough terrain and slopes.

Shark vertebrae and their centra (vertebral bodies) are high-performance structures able to survive millions of cycles of high amplitude strain despite lacking a repair mechanism for accumulating damage. Shark centra consist of mineralized cartilage, a biocomposite of bioapatite (bAp), and collagen, and the nanocrystalline bAp's contribution to functionality remains largely uninvestigated. Using the multiple detector energy-dispersive diffraction (EDD) system at 6-BM-B, the Advanced Photon Source, and 3D tomographic sampling, the 3D functionality of entire centra were probed. Immersion in ethanol vs phosphate-buffered saline produces only small changes in bAp d-spacing within a great hammerhead centrum. EDD mapping under in situ loading was performed an entire blue shark centrum, and 3D maps of bAp strain showed the two structural zones of the centrum, the corpus calcareum and intermedialia, contained opposite-signed strains approaching 0.5%, and application of ~8% nominal strain did not alter these strain magnitudes and their spatial distribution.

Empirical reaction progress diagrams showing the trends of major element oxide concentrations (in g/cm3) as functions of bulk density for a diabase saprolite reveal discontinuities in the trends of Al2O3, MgO, H2O+, and nonextractable Fe2O3. The discontinuities coincide with discontinuities in the trends of (1) the kaolinite-smectite 001 peak-intensity ratio, (2) the smectite 002-001 peak intensity ratio, and (3) the smectite basal spacing as functions of bulk density. The discontinuities are apparently related to redox conditions in the weathering profile because they occur at a depth where siderite veins first appear in the saprolite. Oxidizing conditions in the upper part of the profile appear to have favored the formation of Ferich smectite over kaolinite, whereas reducing conditions deeper in the profile favored the formation of kaolinite over Al-rich smectite. These results indicate that where geochemical conditions favor retention of Fe over Al, smectites can form in preference to kaolinite or gibbsite even under conditions of strong leaching.

Background: Cerebral venous thrombosis (CVT) is a rare cause of stroke, with 10–15% of patients experiencing dependence or death. The role of endovascular therapy (EVT) in the management of CVT remains controversial and practice patterns are not well-known. Methods: We distributed a comprehensive 53-question survey to neurologists, neuro-interventionalists, neurosurgeons and other relevant clinicians globally from May 2023 to October 2023. The survey asked about practice patterns and perspectives on EVT for CVT and assessed opinions regarding future clinical trials. Results: The overall response rate was 31% (863 respondents from 2744 invited participants) across 61 countries. A majority (74%) supported use of EVT for certain CVT cases. Key considerations for EVT included worsening level of consciousness (86%) and other clinical deficits (76%). Mechanical thrombectomy with aspiration (22%) and stent retriever (19%) were the most utilized techniques, with regional variations. Post-procedurally, low molecular weight heparin was the predominant anticoagulant administered (40%), although North American respondents favored unfractionated heparin. Most respondents supported future trials of EVT (90%). Conclusions: Our survey reveals significant heterogeneity in approaches to EVT for CVT, highlighting the necessity for adequately powered clinical trials to guide standard-of-care practices.

Background: Primary central nervous system lymphoma (PCNSL) is highly sensitive to corticosteroid induced cell arrest, apoptosis and shrinkage. However, the precise impact of preoperative corticosteroid on accuracy of PCNSL diagnosis using tissue obtained from open or stereotactic biopsies remains debated. Methods: We conducted a systematic review and meta-analysis to determine the effect of preoperative corticosteroids on non-diagnostic biopsy rates for PCNSL in immunocompetent adults. Subgroup analyses explored whether non-diagnostic rates varied based on biopsy type. Results: Nineteen studies, comprising 1226 patients (55% male; mean age: 60.3 years), of which 679 (55.4%) received corticosteroids prior to biopsy were included. Overall, patients pretreated with corticosteroids were two times more likely to have a non-diagnostic biopsy compared to patients that were corticosteroid-naïve prior to biopsy (RR = 2.1 [95% CI: 1.1-4.1]). In the subgroup analysis limited to stereotactic biopsies, patient pretreated with corticosteroids were three times more likely to have a non-diagnostic biopsy (RR = 3.0 [95% CI: 1.2-7.5]). Whereas, in the open biopsy subgroup, there was no significant difference in non-diagnostic rates. Conclusions: Corticosteroids should be withheld, if clinically safe, prior to stereotactic biopsies in cases of suspected PCNSL. If corticosteroids are administered preoperatively, an open biopsy should be considered instead of stereotactic biopsy.

Background: For treatment of high-grade gliomas (HGGs), subtotal resection (STR) may be preferred to minimize injury to eloquent areas. We aimed to characterize neurologic deficits developed in STR patients within the first month post-operatively and to establish a potential threshold for a safe volume of residual tumor to avoid neurological worsening. Methods: This is a single institution retrospective chart review, with 146 charts reviewed and 78 patients deemed eligible. Preoperative deficits and postoperative neurological deficits presenting prior to 1 month after surgery were captured. Imaging features such as tumour volume, edema, and other pertinent imaging characteristics were collected from preoperative and postoperative imaging. Results: Most patients that developed a postoperative deficit presented with motor deficits (55.1%), while only 1.3% of patients developed new or worsening tremor after surgery. On average, in patients with a new deficit, 26.5% of tumor was resected, and all patients had more than 19% of residual tumor. Conclusions: Postoperative neurologic deficits may develop after a subtotal resection when an average of 73.5% of tumor remains. The proposed threshold for tumor resection is greater than 26.5% to minimize the potential of neurologic worsening 1 month postoperatively.