Explore the vast range of titles available.

The objective of this paper is to study the effect of travel time information on day-to-day driver route choice behavior. A real-world experimental study is designed to have participants repeatedly choose between two alternative routes for five origin-destination pairs over multiple days after providing them with dynamically updated travel time information (average travel time and travel time variability). The results demonstrate that historical travel time information enhances behavioral rationality by 10% on average and reduces inertial tendencies to increase risk seeking in the gain domain. Furthermore, expected travel time information is demonstrated to be more effective than travel time variability information in enhancing rational behavior when drivers have limited experiences. After drivers gain sufficient knowledge of routes, however, the difference in behavior associated with the two information types becomes insignificant. The results also demonstrate that, when drivers lack experience, the faster less reliable route is more attractive than the slower more reliable route. However, with cumulative experiences, drivers become more willing to take the more reliable route given that they are reluctant to become risk seekers once experience is gained. Furthermore, the effect of information on driver behavior differs significantly by participant and trip, which is, to a large extent, dependent on personal traits and trip characteristics.

ObjectivesDepression and depressive symptoms are common mental disorders that have a considerable effect on patients’ health-related quality of life and satisfaction with medical care, but the prevalence of these conditions varies substantially between published studies. The aim of this study is to conduct a systematic review and meta-analysis to provide a precise estimate of the prevalence of depression or depressive symptoms among outpatients in different clinical specialties.DesignSystematic review and meta-analysis.Data sources and eligibility criteriaThe PubMed and PsycINFO, EMBASE and Cochrane Library databases were searched to identify observational studies that contained information on the prevalence of depression and depressive symptoms in outpatients. All studies included were published before January 2016. Data characteristics were extracted independently by two investigators. The point prevalence of depression or depressive symptoms was measured using validated self-report questionnaires or structured interviews. Assessments were pooled using a random-effects model. Differences in study-level characteristics were estimated by meta-regression analysis. Heterogeneity was assessed using standard χ2 tests and the I2 statistic. The study protocol has been registered with PROSPERO under number CRD42017054738.ResultsEighty-three cross-sectional studies involving 41 344 individuals were included in this study. The overall pooled prevalence of depression or depressive symptoms was 27.0% (10 943/41 344 individuals; 95% CI 24.0% to 29.0%), with significant heterogeneity between studies (p<0.0001, τ2=0.3742, I2=96.7%). Notably, a significantly higher prevalence of depression and depressive symptoms was observed in outpatients than in the healthy controls (OR 3.16, 95% CI 2.66 to 3.76, I2=72.0%, χ 2 =25.33). The highest depression/depressive symptom prevalence estimates occurred in studies of outpatients from otolaryngology clinics (53.0%), followed by dermatology clinics (39.0%) and neurology clinics (35.0%). Subgroup analyses showed that the prevalence of depression and depressive symptoms in different specialties varied from 17.0% to 53.0%. The prevalence of depression and depressive symptoms was higher among outpatients in developing countries than in outpatients from developed countries. Moreover, the prevalence of depression and depressive symptoms in outpatients slightly decreased from 1996 to 2010. Regarding screening instruments, the Beck Depression Inventory led to a higher estimate of the prevalence of depression and depressive symptoms (1316/4702, 36.0%, 95% CI 29.0% to 44.0%, I2=94.8%) than the Hospital Anxiety and Depression Scale (1003/2025, 22.0%, 95% CI 12.0% to 35.0%, I2=96.6%).ConclusionOur study provides evidence that a significant proportion of outpatients experience depression or depressive symptoms, highlighting the importance of developing effective management strategies for the early identification and treatment of these conditions among outpatients in clinical practice. The substantial heterogeneity between studies was not fully explained by the variables examined.

ObjectiveTo characterise the contributing factors that affect medical students’ subspecialty choice and to estimate the extent of influence of individual factors on the students’ decision-making process.DesignSystematic review and meta-analysis.MethodsA systematic search of the Cochrane Library, ERIC, Web of Science, CNKI and PubMed databases was conducted for studies published between January 1977 and June 2018. Information concerning study characteristics, influential factors and the extent of their influence (EOI) was extracted independently by two trained investigators. EOI is the percentage level that describes how much each of the factors influenced students’ choice of subspecialty. The recruited medical students include students in medical school, internship, residency training and fellowship, who are about to or have just made a specialty choice. The estimates were pooled using a random-effects meta-analysis model due to the between-study heterogeneity.ResultsData were extracted from 75 studies (882 209 individuals). Overall, the factors influencing medical students’ choice of subspecialty training mainly included academic interests (75.29%), competencies (55.15%), controllable lifestyles or flexible work schedules (53.00%), patient service orientation (50.04%), medical teachers or mentors (46.93%), career opportunities (44.00%), workload or working hours (37.99%), income (34.70%), length of training (32.30%), prestige (31.17%), advice from others (28.24%) and student debt (15.33%), with significant between-study heterogeneity (p<0.0001). Subgroup analyses revealed that the EOI of academic interests was higher in developed countries than that in developing countries (79.66% [95% CI 70.73% to 86.39%] vs 60.41% [95% CI 43.44% to 75.19%]; Q=3.51, p=0.02). The EOI value of prestige was lower in developed countries than that in developing countries (23.96% [95% CI 19.20% to 29.47%] vs 47.65% [95% CI 34.41% to 61.24%]; Q=4.71, p=0.01).ConclusionsThis systematic review and meta-analysis provided a quantitative evaluation of the top 12 influencing factors associated with medical students’ choice of subspecialty. Our findings provide the basis for the development of specific, effective strategies to optimise the distribution of physicians among different departments by modifying these influencing factors.

Many current approaches for image classification concentrate solely on the most prominent features within an image, but in fine-grained image recognition, even subtle features can play a significant role in model classification. In addition, the large variations in the same class and small differences between different categories that are unique to fine-grained image recognition pose a great challenge for the model to extract discriminative features between different categories. Therefore, we aim to present two lightweight modules to help the network discover more detailed information in this paper. (1) Patches Hidden Integrator (PHI) module randomly selects patches from images and replaces them with patches from other images of the same class. It allows the network to glean diverse discriminative region information and prevent over-reliance on a single feature, which can lead to misclassification. Additionally, it does not increase the training time. (2) Consistency Feature Learning (CFL) aggregates patch tokens from the last layer, mining local feature information and fusing it with the class token for classification. CFL also utilizes inconsistency loss to force the network to learn common features in both tokens, thereby guiding the network to focus on salient regions. We conducted experiments on three datasets, CUB-200-2011, Stanford Dogs, and Oxford 102 Flowers. We achieved experimental results of 91.6%, 92.7%, and 99.5%, respectively, achieving a competitive performance compared to other works.

Immunotherapy using immune checkpoint inhibitors (ICIs) has become a prominent strategy for cancer treatment over the past ten years. However, the efficacy of ICIs remains limited, with certain cancers exhibiting resistance to these therapeutic approaches. Consequently, several immune checkpoint proteins are presently being thoroughly screened and assessed in both preclinical and clinical studies. Among these candidates, T cell immunoglobulin and mucin-domain containing-3 (TIM-3) is considered a promising target. TIM-3 exhibits multiple immunosuppressive effects on various types of immune cells. Given its differential expression levels at distinct stages of T cell dysfunction in the tumor microenvironment (TME), TIM-3, along with programmed cell death protein 1 (PD-1), serves as indicators of T cell exhaustion. Moreover, it is crucial to carefully evaluate the impact of TIM-3 and PD-1 expression in cancer cells on the efficacy of immunotherapy. To increase the effectiveness of anti-TIM-3 and anti-PD-1 therapies, it is proposed to combine the inhibition of TIM-3, PD-1, and programmed death-ligand 1 (PD-L1). The efficacy of TIM-3 inhibition in conjunction with PD-1/PD-L1 inhibitors is being evaluated in a number of ongoing clinical trials for patients with various cancers. This study systematically investigates the fundamental biology of TIM-3 and PD-1, as well as the detailed mechanisms through which TIM-3 and PD-1/PD-L1 axis contribute to cancer immune evasion. Additionally, this article provides a thorough analysis of ongoing clinical trials evaluating the synergistic effects of combining PD-1/PD-L1 and TIM-3 inhibitors in anti-cancer treatment, along with an overview of the current status of TIM-3 and PD-1 antibodies.

Freeway incidents block road lanes and result in increasing travel time delays. The intense lane changes of upstream vehicles may also lead to capacity drop and more congestion. Connected vehicles (CVs) offer a viable solution to minimize the impact of such incidents via monitoring the status of the incidents and providing real-time driving guidance. This paper evaluates the performance of an existing CV-enabled incident management system, which minimizes travel time by effectively leading CVs to bypass incident spots. This study comprehensively quantifies the effects of system parameters (speed weight and lane-changing inertia), control segment length, and road information-updating intervals. This analysis identifies the optimal settings for the incident management system to minimize vehicle travel time delays. Additionally, this paper evaluates the influence of CV market penetration rates (MPRs), network volume-to-capacity ratios, and incident settings to understand the system benefits under varying connected environments and traffic conditions. The results reveal that with the control of the proposed system, overall travel delays can be reduced by up to 45% and that road congestion caused by incidents can be mitigated quickly.

Topological magnons are emergent quantum spin excitations featured by magnon bands crossing linearly at the points dubbed nodes, analogous to fermions in topological electronic systems. Experimental realisation of topological magnons in three dimensions has not been reported so far. Here, by measuring spin excitations (magnons) of a three-dimensional antiferromagnet Cu 3 TeO 6 with inelastic neutron scattering, we provide direct spectroscopic evidence for the coexistence of symmetry-protected Dirac and triply degenerate nodes, the latter involving three-component magnons beyond the Dirac–Weyl framework. Our theoretical calculations show that the observed topological magnon band structure can be well described by the linear-spin-wave theory based on a Hamiltonian dominated by the nearest-neighbour exchange interaction J 1 . As such, we showcase Cu 3 TeO 6 as an example system where Dirac and triply degenerate magnonic nodal excitations coexist, demonstrate an exotic topological state of matter, and provide a fresh ground to explore the topological properties in quantum materials. Topological magnonic materials display exotic properties which may enable high-efficiency and low-cost spintronic devices. Here the authors demonstrate a three-dimensional antiferromagnet Cu 3 TeO 6 that hosts symmetry-protected Dirac and triply degenerate magnons.

Soybean meal (SBM) is a high-quality vegetable protein, whose application is greatly limited due to its high molecular weight and anti-nutritional properties. The aim of this study was to modify the protein of soybean meal via solid-state fermentation of Bacillus subtilis. The fermentation conditions were optimized as, finally, the best process parameters were obtained, namely fermentation temperature of 37 °C, inoculum amount of 12%, time of 47 h, and material-liquid ratio of 1:0.58, which improved the content of acid-soluble protein. To explore the utilization of modified SBM as a food ingredient, the protein structure and properties were investigated. Compared to SBM, the protein secondary structure of fermented soybean meal (FSBM) from the optimal process decreased by 8.3% for α-helix content, increased by 3.08% for β-sheet, increased by 2.71% for β-turn, and increased by 2.51% for random coil. SDS-PAGE patterns showed that its 25–250 KDa bands appeared to be significantly attenuated, with multiple newborn peptide bands smaller than 25 KDa. The analysis of particle size and zeta potential showed that fermentation reduced the average particle size and increased the absolute value of zeta potential. It was visualized by SEM and CLSM maps that the macromolecular proteins in FSBM were broken down into fragmented pieces with a folded and porous surface structure. Fermentation increased the solubility, decreased the hydrophobicity, increased the free sulfhydryl content, decreased the antigenicity, improved the protein properties of SBM, and promoted further processing and production of FSBM as a food ingredient.

Broken symmetries play a fundamental role in superconductivity and influence many of its properties in a profound way. Understanding these symmetry breaking states is essential to elucidate the various exotic quantum behaviors in non-trivial superconductors. Here, we report an experimental observation of spontaneous rotational symmetry breaking of superconductivity at the heterointerface of amorphous (a)-YAlO 3 /KTaO 3 (111) with a superconducting transition temperature of 1.86 K. Both the magnetoresistance and superconducting critical field in an in-plane field manifest striking twofold symmetric oscillations deep inside the superconducting state, whereas the anisotropy vanishes in the normal state, demonstrating that it is an intrinsic property of the superconducting phase. We attribute this behavior to the mixed-parity superconducting state, which is an admixture of s -wave and p -wave pairing components induced by strong spin-orbit coupling inherent to inversion symmetry breaking at the heterointerface of a-YAlO 3 /KTaO 3 . Our work suggests an unconventional nature of the underlying pairing interaction in the KTaO 3 heterointerface superconductors, and brings a new broad of perspective on understanding non-trivial superconducting properties at the artificial heterointerfaces. Superconducting interfaces involving KTaO3 have recently attracted attention due to their relatively high transition temperature. Here, the authors study amorphous-YAlO 3 /KTaO 3 interfaces and find two-fold symmetry in the superconducting regime, possibly due to a mixed-parity superconducting state.

There is currently no reliable and easily applicable diagnostic marker for Parkinson’s disease (PD). The aims of the present study were to compare the expression profiles of the microRNA29 family (miR-29s) in blood serum from patients with PD with healthy controls and to clarify whether the expression of miR-29s is correlated with disease severity, duration or L-dopa therapy and whether expression depends on the gender and age of patients. The levels of blood serum miR-29s in 80 patients with PD and 80 unaffected controls were assessed by reverse transcription-quantitative real-time PCR. The PCR products were confirmed by cloning and sequencing. Additionally, the expression of miR-7 in the blood serum from PD patients and control subjects was assessed. Serum miR-29 levels were significantly downregulated in PD patients compared to healthy controls. The serum miR-29 levels in female PD patients were markedly higher than in male PD patients. The expression of serum miR-29a and miR-29c expression tended to decrease with disease severity. Moreover, we found that serum miR-7 levels did not differ between PD patients and control subjects. Therefore, the reduction of serum miR-29 levels, particularly miR-29a and miR-29c, warrants further investigation of its potential serving as biomarkers for PD.