Search Results (325)

In the ecosystem, birds are important indicators that can sensitively reflect changes in the ecological environment and its health. However, bird monitoring has challenges due to species diversity, variable behaviors, and distinct morphological characteristics. Therefore, we propose a parallel dual-branch hybrid CNN–Transformer architecture for feature extraction that simultaneously captures local and global image features to address the “local feature similarity” issue in dual tasks of bird species and behaviors. The dual-task framework comprises three main components: the Token Re-segmentation Module (TRM), the Multi-scale Adaptive Module (MAM), and the Feature Interleaving Structure (FIS). The designed MAM fuses hybrid attention to address the problem of different-scale birds. MAM models the interdependencies between spatial and channel dimensions of features from different scales. It enables the model to adaptively choose scale-specific feature representations, accommodating inputs of different scales. In addition, we designed an efficient feature-sharing mechanism, called FIS, between parallel CNN branches. FIS interleaving delivers and fuses CNN feature maps across parallel layers, combining them with the features of the corresponding Transformer layer to share local and global information at different depths and promote deep feature fusion across parallel networks. Finally, we designed the TRM to address the challenge of visually similar but distinct bird species and of similar poses with distinct behaviors. TRM adopts a two-step approach: first, it locates discriminative regions, and then performs fine segmentation on them. This module enables the network to allocate relatively more attention to key areas while merging non-essential information and reducing interference from irrelevant details. Experiments on the self-made dataset demonstrate that, compared with state-of-the-art classification networks, the proposed network achieves the best performance, achieving 79.70% accuracy in bird species recognition, 76.21% in behavior recognition, and the best performance in dual-task recognition. Full article

In today’s increasingly serious environmental problems, a growing number of enterprises are upgrading remanufacturing as an important corporate strategy. This paper compares two third-party remanufacturing models: the entrusting and Authorizing Models, and introduces two different levels of consumer low-carbon preferences: medium and high. By establishing game equations, we find the equilibrium solution of each model. The results reveal that in the basic model, OEM tends to choose the Authorizing Model when consumers have a pronounced quality bias against remanufactured products. Contrary to intuition, TRM always prefers the Entrusting Model. In scenarios where consumers possess medium low-carbon preferences, OEM tends to choose the Authorizing Model when consumers have a high bias against the quality of the remanufactured products or a low bias against the carbon emissions of the new products. Conversely, OEM tends to choose the entrusting remanufacturing model under the opposite conditions. In scenarios where consumers express high low-carbon preferences, the situation becomes the complete opposite. When consumers exhibit a low bias against remanufactured products’ quality or a high bias against carbon emissions from new products, OEM tends to choose the Authorizing Model. Conversely, OEM prefers the Entrusting Model when consumers’ biases differ. In addition, the consumer surplus and social welfare of the Entrusting Model are higher than those of the Authorizing Model, regardless of the research scenario. Full article

This study focuses on the key challenges in detecting and estimating motion parameters of ground maneuvering targets for airborne radar sensors. The complex unknown motion states of the ground maneuvering target, including velocity, acceleration, and jerk, result in range migrations (RMs) and Doppler frequency migrations (DFMs). These effects severely degrade the long-time coherent accumulation performance of the airborne radar, thereby limiting the reliable detection and precise parameter estimation of maneuvering targets. To address this issue, a new detection and motion parameter estimation method based on the range frequency reversal transform (RFRT) and searching Lv’s distribution (SLVD), i.e., RFRT-SLVD, is proposed. Specifically, the third-order RM (TRM) and quadratic DFM (QDFM) are considered. The proposed method operates as follows: First, RMs are eliminated simultaneously via the RFRT operation, which multiplies the echo by its reversed data in the range frequency and slow-time domains, leveraging the symmetric equal-interval sampling property of the range frequency. Subsequently, a phase compensation function (PCF) related to the jerk is constructed to compensate the QDFM. Finally, the LVD is performed to remove residual DFMs and achieve effective signal energy accumulation. Additionally, the case of a fast-moving target with Doppler ambiguity is analyzed, and a method for estimating three motion parameters is provided. A key advantage of the proposed technique is its ability to directly compensate the RMs without requiring prior knowledge of the maneuvering target, while also avoiding the blind speed sidelobe (BSSL) effect. In comparison with existing algorithms, RFRT-SLVD achieves a balanced trade-off between parameter estimation performance and computational efficiency. Numerical analyses and experiments are conducted to validate the method, assessing its detection capability for ground maneuvering targets, Doppler ambiguity resolution in parameter estimation, computational complexity, and method applicability in multi-target scenarios. Full article

Air-conditioning systems are vital for indoor environmental quality. However, noise can offset its benefits, making acoustic monitoring important. Recent research revealed that sound quality perceptions can be described by three psychological dimensions: Evaluation, Potency, and Activity (EPA). This is the first study to develop psychoacoustic heatmap machine learning models (PHMLM) for predicting sound quality and the negative noise impacts (O1: Discomfortable, O2: Annoying, O3: Stressful, and O4: Unacceptable) of air conditioning sounds using a 227 × 227-pixel psychoacoustic heatmap as input for machine learning. A total of 1208 jury listening tests were conducted with 101 participants on 30 s soundtracks from air-conditioned environments. Psychoacoustic heatmaps were generated by converting time-varying psychoacoustic metrics (N, S, R, and FS) into intensity maps containing 51,529 pixels of multidimensional acoustic information. The PHMLMs achieved predictive performance with correlation coefficients of 0.79, 0.80, and 0.62 for E-, P-, and A-scores, respectively. Compared to traditional regression models (TRM), PHMLM-EPA demonstrated significantly better performance with 31% lower mean absolute error (4.4 vs. 6.4) and higher regression slope (0.798 vs. 0.587). Moreover, PHMLM-EPA demonstrated a higher goodness-of-fit than TRM (+55% to +95%) and traditional acoustic metric L_Aeq (+87% to +95%). The approach offers an advanced acoustic monitoring method for sustainable building designs. Full article

Streptococcus suis is an important zoonotic pathogen responsible for severe infections in pigs and humans. Its capacity to survive within phagocytic cells is considered a key virulence mechanism that contributes to dissemination and persistence in host tissues. This study employed comparative proteomic profiling to investigate intracellular adaptation of S. suis serotypes 2 (SS2) and 14 (SS14) during infection of human U937 macrophages. Five isolates originating from humans and pigs were analyzed using gel electrophoresis with liquid chromatography–tandem mass spectrometry (GeLC–MS/MS), revealing 118 differentially expressed proteins grouped into 11 functional categories. Translation-related proteins represented the largest group (48%), including upregulated ribosomal subunits (30S: S2, S5, S7, S8, S12, S15; 50S: L1, L5, L18, L22, L24, L33, L35) and translation factors such as GidA/TrmFO and RimP. Enrichment of carbohydrate metabolism and DNA replication proteins, including phosphoenolpyruvate carboxylase (PEP), UDP-N-acetylglucosamine pyrophosphorylase (GlmU), and ATP-dependent DNA helicase RuvB, indicated metabolic reprogramming and stress adaptation under intracellular conditions. Stress-response proteins such as molecular chaperone DnaK were also induced, supporting their multifunctional, “moonlighting” roles in virulence and host interaction. Comparative analysis showed that SS2 expressed a broader range of adaptive proteins than SS14, consistent with its higher virulence potential. These findings reveal conserved intracellular responses centered on translation, energy metabolism, and stress tolerance, which enable S. suis to survive within human macrophages. Integration of these intracellular proteomic signatures with previous exoproteomic, peptidomic, and network-based studies highlights translational and metabolic proteins—particularly DnaK, enolase, elongation factor EF-Tu, and GlmU—as multifunctional candidates linking survival and immunogenicity. This work establishes a comparative proteomic foundation for understanding S. suis intracellular adaptation and highlights potential targets for future vaccine or therapeutic development against this zoonotic pathogen. Full article

Tissue-resident memory T (T_RM) cells persist long-term in non-lymphoid tissues and provide rapid local immune protection, yet emerging evidence shows they also act as key drivers of chronic inflammation and relapse in rheumatoid immune diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), and primary Sjögren’s syndrome (pSS). A systematic search of PubMed, Web of Science, and Google Scholar (through October 2025) identified studies on T_RM cell biology, pathogenic roles, and therapeutic modulation in autoimmune diseases. This review summarizes the fundamental features of T_RM cells, including their TGF-β and IL-15 dependent development, tissue-specific heterogeneity, and unique metabolic programs. It highlights disease-specific pathogenic mechanisms: promotion of osteoclastogenesis and chronic synovial inflammation via Granulocyte-macrophage colony stimulating factor (GM-CSF) and the IL-23/IL-17 axis in RA; amplification of type I interferon responses and autoantibody production in SLE; potential contribution to fibrosis through TGF-β secretion in SSc; and mediation of glandular injury through cytotoxicity in pSS. Therapeutic strategies targeting T_RM cells—such as JAK inhibitors, IL-17/IL-23 blockade, disruption of residency signals, metabolic interventions, and microenvironmental remodeling via nanotechnology—are critically evaluated. Challenges remain in achieving tissue-specific targeting without compromising systemic immune memory. Future directions include spatial transcriptomics, organoid models, and artificial intelligence to support precision medicine. Targeting T_RM cells presents a promising novel avenue for achieving long-term remission and potentially even a cure for rheumatoid immune diseases. Full article

With the rapid transition toward a low-carbon power system, the temporal intermittency and spatial unevenness of renewable generation have imposed emerging challenges to the supply–demand balance of electricity. To enhance the secure utilization of inter-regional transmission capacity under uncertainties, this paper proposes a correlation-aware Gaussian mixture model (GMM) for probabilistic assessment of the transmission reliability margin (TRM) of interconnectors. The proposed method explicitly captures multi-source uncertainties, including renewable generation, load, and power contract execution deviation. The internal correlations among uncertain factors are embedded in the GMM to avoid the misestimation associated with independent-distribution assumptions. Simulation results on a four-region system demonstrate that the proposed method outperforms existing methods in higher accuracy and computational efficiency, which enables reliable and economic cross-regional power trading under uncertainty. Full article

This study aimed to evaluate the combined effects of two probiotic strains, Lactobacillus salivarius TRM58163 and Lactobacillus johnsonii TRM59525—originally isolated from human infant feces (aged 0–6 months)—on growth performance, antioxidant capacity, liver function, intestinal morphology, and cecal microbiota in 100-day-old Baicheng You chickens fed a low-protein diet. Ten strains isolated from infant feces were initially screened, and eight were assessed in vitro for safety, gastrointestinal tolerance, and antimicrobial activity. TRM58163 and TRM59525 showed the best probiotic potential. A total of 240 Baicheng You chickens (100 days old) were randomly assigned to two groups: The control group was fed a low-protein diet (CLD), while the experimental group had Lactobacillus salivarius TRM58163 and Lactobacillus johnsoni TRM59525 added to the low-protein diet (LLD, ≥1 × 10⁹ CFU/g feed). Each treatment included four replicates of 30 chickens over 42 days. Probiotic supplementation significantly improved average daily feed intake (ADFI), average daily gain (ADG), and feed conversion ratio (FCR) (p < 0.05). It also enhanced antioxidant status, with increased plasma superoxide dismutase activity and reduced malondialdehyde levels. Lower total bilirubin levels indicated improved liver function. The LLD group showed increased ileal villus height and villus-to-crypt ratio. 16S rRNA gene sequencing revealed greater microbial diversity, increased beneficial genera (e.g., Akkermansia, Bacteroides), and decreased harmful taxa (e.g., Sutterella). These microbial shifts were associated with improved growth and metabolic profiles. In conclusion, L. salivarius TRM58163 and L. johnsonii TRM59525 supplementation improved performance, gut health, and microbial composition, supporting their use as functional probiotics in low-protein poultry diets. Full article

Objectives: Vaccination by a nonmucosal route to elicit CD8⁺ T cell-mediated mucosal immunity against respiratory infections presents a great challenge for the development of an effective vaccine or immunization strategy. This study aimed to explore a new strategy to address the challenge. Methods: To test this strategy, s.c. vaccinated mice were administered i.p. with tanshinone I (TSN1), a main bioactive compound found in the root of Salvia miltiorrhiza, and CD8⁺ T cell responses were analyzed using flow cytometry. The differentiating effects of TSN1 on CD8⁺ T cells from naïve mice were also evaluated in an in vitro setting. Results: Nonmucosal vaccination and administration of TSN1 induce pulmonary-resident vaccine-specific memory CD8⁺ T cells through increased lung-specific recruitment and retention. The improved memory response appears to result from the impact of TSN1 introduced during the primary immunization phase. Given a specific range of varying concentrations of this natural compound, it exhibits a differential effect on the memory differentiation of CD8⁺ T cells in the process of being activated. Effector memory T cells expand robustly relative to central memory T cells, and both memory subsets have additionally increased expression of CD44 and CD69. With more potent cytolytic activity, CD8⁺ Trm expressing CD69 particularly predominate the population lacking the CD69 expression in the lungs of TSN1-treated mice. Conclusions: Our study suggests that TSN1 as an important natural compound may hold great promise for novel approaches to the design and development of a more practical and efficient vaccination strategy to generate effective respiratory mucosal immunity. Full article

Aim: This study aimed to characterize and compare the composition of central (TCM), effector (TEM), tissue-resident (TRM), and terminally differentiated (TEMRA) memory T cells in mid-luteal endometrium during the window of implantation (WOI) in women with and without a previous miscarriage. Methods: Stromal lymphocytes from endometrial samples (P + 5) were analyzed by multicolor flow cytometry to quantify total, CD4⁺ and CD8⁺ TCM (CD45RA⁻CCR7⁺), TEM (CD45RA⁻CCR7⁻), TRM (CD69⁺), and TEMRA (CD45RA⁺CCR7⁻) subsets. Participants were grouped as having no previous miscarriage (n = 38) or ≥1 previous miscarriage (n = 33), and the relative distribution of these memory subsets was compared between groups. Correlations, PCA and logistic regression were used to assess global memory network organization. Results: Women with prior miscarriage exhibited higher TCM proportions among total and CD8⁺ lymphocytes (p < 0.01), alongside lower CD8⁺ TEM (p = 0.02) and higher CD4⁺ TEM (p = 0.01). TRM showed a mild, non-significant increase (p = 0.18), while TEMRA remained stable. TRM correlated positively with both TCM (r = 0.51) and CD4⁺ TEM (r = 0.40), indicating coordinated organization among memory subsets. Multivariate analyses (PCA and logistic regression) confirmed these trends and identified the TCM/TEM ratio as the most discriminative parameter. Conclusions: Endometrial memory T-cell composition during the WOI differs in women with miscarriage history, characterized by central memory expansion and reduced effector memory proportions, with parallel increases in tissue-resident cells. These changes suggest persistent remodeling of the local immune memory network toward a long-lived, less differentiated phenotype that may influence implantation readiness in subsequent cycles. Full article

A total of 304 bacterial strains were isolated from the Taklamakan Desert. Through screening, strain TRM82367 exhibited potent insecticidal activity against cotton aphids (Aphis gossypii) and was identified as Bacillus velezensis. To explore the primary insecticidal active components of this strain, lipopeptide substances in the fermentation broth were extracted via hydrochloric acid precipitation. The main active components were analyzed using activity-guided fractionation combined with liquid chromatography–mass spectrometry (LC-MS). Our results demonstrated that Bacillus velezensis TRM82367 possessed strong lethal activity against cotton aphids. The crude extract obtained by means of hydrochloric acid precipitation and methanol dissolution showed high insecticidal efficacy. At concentrations of 100, 150, 200, 250, 300, 400, and 500 mg/L, the 48 h corrected mortality rates of cotton aphids were 25.14%, 38.05%, 50.09%, 53.03%, 57.96%, 74.68%, and 88.67%, respectively. The toxicity regression equation was Y = 2.47X − 5.72, with a median lethal concentration (LC₅₀) of 207.616 mg/L and a 95% lethal concentration (LC₉₅) of 1004.673 mg/L. After separation by an ODS chromatographic column and identification by means of mass spectrometry, the main active components were confirmed to be C₁₂–C₁₆ surfactin homologs. Full article

This paper presents FRESCO (Fiber REinforced Strengthening COmposite Database), a comprehensive open-source database designed to systematically organize experimental data on infilled RC frame systems that can be strengthened with advanced composite materials, such as Fiber-Reinforced Polymers (FRP), Textile-Reinforced Mortars (TRM), and other fiber-based solutions. The database employs open source practices while providing high-quality output that is fully compatible with leading commercial software packages such as ANSYS 2022R2. It uses Python3 as the main programming language and FreeCAD v1.0 as the model generation engine, with a systematic 13-section structure that ensures complete documentation of all parameters necessary for numerical modeling and validation of analytical methods. Two types of databases are provided: in comma-separated format (.csv) for common everyday interaction and in JSON format (.json) for easy programmatic access. The database features automated 3D modeling capabilities, converting experimental data into detailed finite element models with solid RC frame geometry, reinforcement details, and infill configurations. Validation through three comprehensive examples demonstrates that numerical models generated from the database closely match experimental results, with response curves that closely match the initial stiffness, the peak loading and the post-peak stiffness degradation phase across different loading conditions. The database focuses on RC frame systems with unreinforced brick infill. Reflecting the term FRESCO, which in Greek (φρέσκο) means “fresh”, the database is designed as a dynamic, evolving resource, with future versions planned to include RC walls and full buildings. Full article

Background: Treosulfan combined with fludarabine (FluTreo) has emerged as a reduced-toxicity alternative to conventional myeloablative conditioning in allogeneic hematopoietic cell transplantation (allo-HCT) for acute myeloid leukemia (AML) and related myeloid malignancies. Purpose: This study evaluates the safety, engraftment kinetics, and long-term outcomes of the FluTreo FT14 regimen in a real-world adult cohort. Materials and Methods: We conducted a prospective cohort study of 186 consecutive adults (18–70 years) undergoing allo-HCT between January 2015 and December 2024. Eligible diagnoses included de novo or secondary AML, myelodysplastic syndrome, and myelofibrosis. All received peripheral blood stem cells from matched or mismatched unrelated donors, HLA-matched siblings, or haploidentical relatives. The FT14 protocol comprised fludarabine 150 mg/m² over five days and treosulfan 42 g/m² over three days, with rabbit antithymocyte globulin (5 mg/kg) for unrelated grafts. Primary endpoints were neutrophil and platelet engraftment, donor chimerism, incidence of acute and chronic graft-versus-host disease (GVHD), overall survival (OS), disease-free survival (DFS), relapse, and treatment-related mortality (TRM). Kaplan–Meier, Cox regression, and Fine and Gray models were applied. Results: Median age was 59 years; diagnoses included de novo AML (43%), secondary AML (16%), MDS (25%), and MF (16%). Neutrophil and platelet engraftment medians were 10 and 12 days, respectively. Full donor chimerism (≥99%) was achieved by day 31. Grade III conditioning-related toxicity occurred in 3.2% of cases. Five-year cumulative incidences of grade II–IV acute GVHD and moderate/severe chronic GVHD were 37.6% and 30.6%. Median follow-up was 16.3 months; relapse occurred in 25.3%. Five-year OS and DFS were 71% and 49% overall (75.8% and 59% in CR1), with TRM of 15.3%. Disease relapse and acute GVHD independently predicted inferior OS, and acute GVHD predicted TRM. Conclusions: The FluTreo FT14 regimen achieves rapid engraftment, universal high donor chimerism, low severe toxicity, and durable survival, supporting its use as a myeloablative, reduced-toxicity conditioning option in myeloid malignancies. Full article

This article presents a diagnostic method for transmit–receive modules (TRMs) in an airborne active phased array antenna (APAA). Given the spatial constraints of airborne radar systems, the diagnostic functionality was implemented using the peripheral probe method. To minimize the space, cost, and time required for modifications to the existing APAA, the side-lobe blanking (SLB) channel was employed as the probe. To prevent TRM saturation and to determine the fault detection threshold, an APAA-level test was performed using a movable anechoic chamber. The coupling level between the SLB antenna and TRM was maintained between −70 dB and −20 dB. With the result of the APAA-level test, a budget analysis on the signal path was performed, and the input attenuation level was determined. The received signal power was estimated at −40 dBm to −20 dBm. Based on the estimation, the detection threshold was determined as −50 dBm. For the operation of the diagnostic function, simple detection logic and associated control timing is implemented in the radar processor. The effectiveness of the proposed diagnostic method was validated by several test activities, including an anechoic chamber, a rooflab facility, and an actual fighter. The test result shows good agreement with the expectations. Full article

Cryptocurrencies are rapidly transforming digital finance and entrepreneurship, yet their adoption by entrepreneurs remains rather poorly understood. Drawing on the Threat-Rigidity Model (TRM) and the opportunity recognition literature, this study examines how entrepreneurial experience, financial literacy, perceived opportunities, and perceived threats influence entrepreneurial intention to use cryptocurrencies. We tested a moderated mediation model in which the association between financial literacy and experience, on the one hand, and intention to use cryptocurrencies, on the other, was mediated by perceived opportunities. In this model, perceived threats served as a moderator on the relationship between financial literacy and intention, as well as between perceived opportunities and adoption intention. Data were collected from a sample of 133 Romanian entrepreneurs across diverse industries. The results supported the mediating role of perceived opportunities in the relationship between financial literacy and intention to use cryptocurrencies in business and showed that the positive association between financial literacy and intention was attenuated by perceived threats. Entrepreneurial experience did not significantly influence perceived opportunities, while women entrepreneurs reported lower intention to adopt cryptocurrencies in business. This study is among the first to use the TRM to explore how the interplay of perceived opportunities and threats shapes cryptocurrency adoption in entrepreneurship. Other implications, limitations, and directions for future research are also discussed. Full article