Search Results (2,895)

Phosphogypsum (PG) is the main by-product of wet-process phosphoric acid production. Its annual global production reaches about 200 million tons, yet its utilization rate remains low. Consequently, long-term stockpiling of large PG volumes poses immense pressure to the ecological environment. To mitigate negative environmental impacts, the utilization of PG is imperative. Despite progress in PG utilization and 3D-printing technology, there is still a significant lack of understanding about the synergistic activation mechanisms in multi-solid-waste systems. In particular, the composition design, microstructure evolution, and structure–property relationships of 3D-printed PG-based composites are not well-studied, which limits their high-value engineering applications. Three-dimensional-printed phosphogypsum concrete (3DPPGC) is proposed here, promoting PG resource utilization by leveraging the expanding applications of 3D-printed concrete (3DPC). However, the strength of 3DPPGC needs to be enhanced to meet engineering requirements. This study designed the mix proportion of 3DPPGC and fabricated the corresponding test specimens. The optimal Cement Replacement Ratio (CRR) was determined through experimental testing, and the mechanism behind the strength enhancement of the 3DPPGC was elucidated. The results indicated that the 3DPPGC’s mechanical properties peaked at the 70% CRR. Compared with cast specimens, 3DPPGC exhibited a 1.52% increase in 28-day flexural strength in the y-direction, reaching 4.69 MPa. The early-age compressive strength, flexural strength, and later-age compressive strength of 3DPPGC were significantly enhanced when PG, blast-furnace slag (BS), fly ash (FA), and silica fume (SF) were used to partially replace cement. This study provides a theoretical and experimental basis for the large-scale, high-value application of PG in intelligent construction. Full article

The Failure Assessment Diagram (FAD), as a significant method for evaluating the suitability of defective metallic structures, has been subject to considerable debate regarding its applicability in assessing ring welded joints for high-grade steel and large-diameter pipelines. To address this issue, this study first designed and conducted two sets of full-scale pressure-tension tests on large-diameter X80 pipeline ring welded joints, considering factors such as different welding processes, joint configurations, defect dimensions, and locations. Subsequently, three widely adopted failure assessment diagram methodologies—BS 7910, API 579, and API 1104—were selected. Corresponding assessment curves were established based on material performance parameters obtained from the ring weld tests. Finally, predictive outcomes from each assessment method were compared against experimental data to investigate the applicability of failure assessment diagrams for evaluating high-strength, large-diameter, thick-walled ring welds. The research findings indicate that, under the specific material and defect assessment conditions employed in this study, the API 1104 assessment results exhibited significant conservatism (two sets matched). Conversely, the BS 7910 and API 579 assessment results showed a high degree of agreement with the experimental data (eight sets matched), with the BS 7910 assessment providing a relatively higher safety margin compared to API 579. The data from this study provides valuable experimental reference for selecting assessment methods under specific conditions, such as similar materials, defects, and loading patterns. Full article

Biosurfactants produced by halophilic bacteria are gaining attention as eco-friendly and biocompatible alternatives to synthetic surfactants due to their high surface activity, stability under extreme conditions, and intrinsic antimicrobial properties. These amphiphilic biomolecules hold great promise for bioremediation, biomedical, and pharmaceutical applications. In this study, moderately halophilic bacteria capable of biosurfactant production were isolated from saline mud collected at the Burgas solar salterns (Bulgaria). The halophilic microbiota was enriched in Bushnell–Haas (BH) medium containing 10% NaCl amended with different carbon sources. Primary screening in BH liquid medium evaluated the isolates’ ability to degrade n-hexadecane while at the same time producing biosurfactants. Thirty halophilic bacterial strains were isolated on BH agar plates supplemented with 2% n-hexadecane, 2% olive oil, or 2% glycerol. Four isolates—BS7OL, BS8OL, BS9GL, and BS10HD—with strong emulsifying activity (E₂₄ = 56%) and reduced surface tension in the range of 27.3–45 mN/m were derived after 7 days of batch fermentation. Strain BS10HD was chosen as the most potent biosurfactant producer. Its phylogenetic affiliation was determined by 16S rRNA gene sequence analysis; according to the nucleotide sequence, it was assigned to Halomonas ventosae. The extract material was analysed by thin-layer chromatography (TLC) and Fourier transform infrared spectroscopy (FTIR). Upon spraying the TLC plate with ninhydrin reagent, the appearance of a pink spot indicated the presence of amine functional groups. FTIR analysis showed characteristic peaks for both lipid and peptide functional groups. Based on the observed physicochemical properties and analytical data, it can be suggested that the biosurfactant produced by Halomonas ventosae BS10HD is a lipopeptide compound. Full article

To address the challenge of low nitrogen removal efficiency, particularly the difficulty in meeting total nitrogen (TN) discharge standards during low-temperature seasons and intermittent emission modes in conventional aquaculture wastewater treatment, this study proposed the novel application of bioretention systems. Biochar and sponge iron were used as fillers to construct three bioretention systems: biochar-based (B-BS), sponge iron-based (SI-BS), and a composite system (SIB-BS), for evaluating their nitrogen removal performance for aquaculture wastewater treatment. Experimental results demonstrated that under intermittent flooding conditions at 8.0–13.0 °C and increasing TN loading (9.48 mg/L–31.13 mg/L), SIB-BS maintained stable TN removal (79.7–86.7%), outperforming B-BS and SI-BS (p < 0.05). Under continuous inflow (influent TN = 8.4 ± 0.5 mg/L) at 8.0–13.0 °C, SIB-BS achieved significantly lower effluent TN (2.57 ± 1.5 mg/L) than B-BS (5.6 ± 1.6 mg/L) and SI-BS (5.0 ± 1.5 mg/L) (p < 0.05). Meanwhile, when the temperature ranged from 8.0 to 26.3 °C, SIB-BS exhibited a more stable and efficient denitrification ability. Mechanistic investigations revealed that coupling biochar with sponge iron promoted denitrifying microbial activity and enhanced the functional potential for nitrogen transformation (p < 0.05). Specifically, biochar provided porous attachment sites and improved mass transfer, while sponge iron supplied readily available Fe²⁺ as an electron donor; their combination buffered iron oxidation and facilitated Fe²⁺-mediated electron transfer. At low temperature, SIB-BS further stimulated extracellular polymeric substances (EPS) secretion, strengthened biofilm stability without causing blockage, and improved the protective interactions between fillers, thereby increasing metabolic efficiency and sustaining TN removal under variable loading. This study provided a technical reference for the efficient denitrification of aquaculture wastewater. Full article

Massive MIMO systems can substantially enhance spectral efficiency, but such gains rely on the availability of accurate channel state information (CSI). However, the increase in the number of antennas leads to a significant growth in feedback overhead, while conventional deep-learning-based CSI feedback methods also impose a substantial computational burden on the user equipment (UE). To address these challenges, this paper proposes LLM4FB, a one-sided CSI feedback framework that leverages a pre-trained large language model (LLM). In this framework, the UE performs only low-complexity linear projections to compress CSI. In contrast, the BS leverages a pre-trained LLM to accurately reconstruct and predict CSI. By utilizing the powerful modeling capabilities of the pre-trained LLM, only a small portion of the parameters needs to be fine-tuned to improve CSI recovery accuracy with low training cost. Furthermore, a multiobjective loss function is designed to simultaneously optimize normalized mean square error (NMSE) and spectral efficiency (SE). Simulation results show that LLM4FB outperforms existing methods across various compression ratios and mobility levels, achieving high-precision CSI feedback with minimal computational capability from terminal devices. Therefore, LLM4FB presents a highly promising solution for next-generation wireless sensor networks and industrial IoT applications, where terminal devices are often strictly constrained by energy and hardware resources. Full article

The objective of this research was to optimize a technological package for the biosorption of heavy metals in water, using agricultural waste activated with lemon juice, as a sustainable development alternative. Heavy metals such as lead, cadmium, copper, and chromium were characterized in two stages (field and laboratory conditions) using the American Public Health Association (APHA) method, and morphological characterization was performed using electron scanning techniques. Cocoa pod husk (CPH) and banana stem (BS) waste was collected with the informed consent of the native communities to obtain charcoal activated with lemon juice (LJ). In addition, a portable filter was designed that could be adapted to the native communities. The efficiency and validation of the filter were also calculated in the field. Statistical analysis was performed using Student’s t-test and Pearson’s correlation. The results show a significant reduction in lead from 0.209 mg/L to 0.02 mg/L. With regard to morphological characterization, more compact structures were observed after activation with BS, favoring the absorption of heavy metals. The correlations were positive for copper and lead (1.000), evidently due to the alteration of anthropic factors. The efficiency of the cocoa filter reached 87.48% and that of the banana stem reached 88.77%. For the cadmium, copper, and chromium parameters, the values obtained were within the maximum permissible limit (LMP). The validation of the filters showed that 80% of the population agrees with using the filters and hopes for their large-scale implementation. These findings represent a new alternative for native communities and a solution to the problem of heavy metals in drinking water. Full article

Patients with Relapsed/Refractory Diffuse Large B-cell Lymphoma (R/R DLBCL) harbor a poor prognosis. Novel therapies, such as bispecific antibodies (BsAbs), provide an effective therapeutic option for such patients. BsAbs are studied both as monotherapy and combination therapy for patients with R/R DLBCL with promising results. Unlike cellular therapies, such as autologous stem cell transplant (ASCT) or chimeric antigen receptor therapy (CAR-T), BsAbs are more amenable to administration in a community setting, given the lower incidence and severity of key toxicities, such as cytokine release syndrome (CRS) and immune effector cell-associated neurologic syndrome (ICANS). Deployment of BsAbs in the community setting requires operational considerations and a multidisciplinary team approach. This review will discuss the currently approved BsAb treatment regimens and our community institution’s experience in implementing BsAbs. Full article

Objectives: Investigating and comparing the micro-tensile bond strength (µTBS) of etch-and-rinse (ER) or self-etch (SE) adhesives on sound (s) and eroded (e) human (H) and bovine (B) dentin. Methods: Twenty-four human and bovine teeth were divided into eight groups (n = 6) and coronally ground down, exposing their dentin. Two groups of human (HeER + HeSE) and bovine teeth (BeER + BeSE) were subjected to erosive challenges (citric acid (pH 2.7), 10 × 2 min per day for five days, and stored in artificial saliva). Groups HsER + HeER and BsER + BeER were treated with an etch-and-rinse adhesive (OptiBond FL), and groups HsSE + HeSE and BsSE + BeSE were treated with a self-etch adhesive (OptiBond All-in-One), followed by buildups with a composite restorative material. After seven days of storage in tap water, µTBS was determined and failure type analysis was performed. Data were evaluated using two-way ANOVA and Tukey’s post hoc tests at a level of significance of α = 0.05. Results: Using etch-and-rinse adhesive, sound human dentin (HsER) showed the significantly highest µTBS (p < 0.05) compared to eroded human (HeER) and sound and eroded bovine dentin (BsER + BeER). For sound human and bovine specimens (HsSE + BsSE), there was no significant difference (p ≥ 0.05) in µTBS when self-etch adhesive was applied, as well as in the eroded specimens (HeSE + BeSE). Conclusions: Within the limitations of this study, it can be concluded that for the etch-and-rinse approach, it is not recommended to substitute human dentin with bovine dentin. When using the specific self-etch adhesive used in the present study, bovine dentin can be used to substitute human dentin, as they showed comparable µTBS. Full article

Modern 5G+grade low power wide area network (LPWAN) technologies such as Narrowband Internet-of-Things (NB-IoT) operate utilizing a multi-channel slotted ALOHA algorithm at the random access phase. As a result, the random access phase in such systems is characterized by relatively low throughput and is highly sensitive to traffic fluctuations that could lead the system outside of its stable operational regime. Although theoretical results specifying the optimal transmission probability that maximizes the successful preamble transmission probability are well known, the lack of knowledge about the current offered traffic load at the BS makes the problem of maintaining the optimal throughput a challenging task. In this paper, we propose and analyze a new reactive access-barring scheme for NB+IoT systems based on machine learning (ML) techniques. Specifically, we first demonstrate that knowing the number of user equipments (UE) experiencing a collision at the BS is sufficient to make conclusions about the current offered traffic load. Then, we show that through utilizing ML-based techniques, one can safely differentiate between events in the Physical Random Access Channel (PRACH) at the base station (BS) side based on only the signal-to-noise ratio (SNR). Finally, we mathematically characterize the delay experienced under the proposed reactive access-barring technique. In our numerical results, we show that by utilizing modern neural network approaches, such as the XGBoost classifier, one can precisely differentiate between events on the PRACH channel with accuracy reaching 0.98 and then associate it with the number of user equipment (UE) competing at the random access phase. Our simulation results show that the proposed approach can keep the successful preamble transmission probability constant at approximately 0.3 in overloaded conditions, when for conventional NB-IoT access, this value is less than 0.05. The proposed scheme achieves near-optimal throughput in multi-channel ALOHA by employing dynamic traffic awareness to adjust the non-unit transmission probability. This proactive congestion control ensures a controlled and bounded delay, preventing latency from exceeding the system’s maximum load capacity. Full article

Remote sensing object detection is a critical task in Earth observation. Despite the remarkable progress made in general object detection, existing detectors struggle with remote sensing scenarios due to the prevalence of numerous small objects with limited discriminative cues. Cutting-edge studies have shown that incorporating contextual information effectively enhances the detection performance for small objects. Meanwhile, recent research has revealed that convolution in the frequency domain is capable of capturing long-range spatial dependencies with high efficiency. Inspired by this, we propose a Frequency-aware Feature Pyramid Framework (FFPF) for remote sensing object detection, which consists of a novel Frequency-aware ResNet (F-ResNet) and a Bilateral Spectral-aware Feature Pyramid Network (BS-FPN). Specifically, the F-ResNet is proposed to extract the spectral context information by plugging the frequency domain convolution into each stage of the backbone, thereby enriching features of small objects. In addition, the BS-FPN employs a bilateral sampling strategy and skipping connection to model the association of object features at different scales, enabling the contextual information extracted by the F-ResNet to be fully leveraged. Extensive experiments are conducted for object detection in the public remote sensing image dataset and natural image dataset. The experimental results demonstrate the excellent performance of the FFPF, achieving 73.8% mAP on the DIOR dataset without using any additional training tricks. Full article

The two-parameter Birnbaum–Saunders (B-S) distribution is widely applied across various fields due to its favorable statistical properties. This study aims to enhance the efficiency of modified moment estimators for the B-S distribution by systematically incorporating auxiliary non-sample information. To this end, we developed and analyzed a suite of estimation strategies, including restricted estimators, preliminary test estimators, and Stein-type shrinkage estimators. A pretest procedure was formulated to guide the decision on whether to integrate the non-sample information. The relative performance of these estimators was rigorously evaluated through an asymptotic distributional analysis, comparing their asymptotic distributional bias and risk under a sequence of local alternatives. The finite-sample properties were assessed via Monte Carlo simulation studies. The practical utility of the proposed methods is demonstrated through applications to two real-world datasets: failure times for mechanical valves and bone mineral density measurements. Both numerical results and theoretical analysis confirm that the proposed shrinkage-based techniques deliver substantial efficiency gains over conventional estimators. Full article

Scutellaria baicalensis is an important medicinal plant, and the diversity of its rhizosphere microbiota may influence its growth, development, and yield. Numerous studies have reported that warming associated with global climate change significantly altered plant-associated soil microbial diversity. To reveal the effects of night-time warming on the rhizosphere microbial community of S. baicalensis, soil microbial diversity in the rhizosphere (RS) and bulk soil (BS) of S. baicalensis were analyzed by employing bacterial 16S rRNA and fungal ITS sequencing technology. Warming significantly altered both bacterial and fungal communities in the rhizosphere and bulk soils of S. baicalensis, with pronounced changes in OTU composition, relative abundances at both phylum and species levels. The analysis of alpha and beta diversity showed that warming significantly altered the fungal community structure in the rhizosphere soil (R² = 0.423, p < 0.05) and significantly reduced the species richness in the bulk soil of S. baicalensis (Shannon and Simpson index, p < 0.05). LEfSe and functional prediction analyses revealed that warming altered the taxonomic composition of both bacterial (35 taxa, LDA > 3) and fungal (24 taxa, LDA > 4) communities in rhizosphere and bulk soils of S. baicalensis, with multiple bacterial and fungal taxa serving as treatment-specific biomarkers. Functional predictions indicated that fungal functional groups, including saprotrophic and mycorrhizal guilds, were more strongly affected by warming than bacteria. Overall, warming has a significantly stronger impact on fungal communities in the rhizosphere and bulk soils of S. baicalensis than on bacteria, and has a significantly greater effect on the diversity of microbial communities in bulk soils than that in rhizosphere soils. This study provides important data for understanding the impact of global climate change on the rhizosphere microbial communities of cultivated plants. Full article

To address the problems of complex composition, significant property variations, and difficult and costly harmless treatment of oil-contaminated sludge in oil and gas field development, its good compatibility with the formation is leveraged to formulate it with oilfield water into an oil–water profile control agent. This reduces the cost of harmless treatment and enables resource utilization of hazardous waste. The properties of oil-contaminated sludge were evaluated experimentally. Suspending agents and stabilizers were selected according to the oil–water profile control agent preparation process, the corresponding agents were prepared, and the system was experimentally tested. The experimental results show that the suspending agent carboxymethyl cellulose (CMC) and partially hydrolyzed polyacrylamide (HPAM), and the dispersant Dodecyl dimethyl betaine (BS-12) are used to prepare oil–water profile control agent based on the selected sulfonated mud oily sludge and ground system oily sludge. The optimal formulation of profile control agent is as follows: (1) 50% ground system oily sludge +50% oilfield produced water + 0.2% CMC + 1.0% BS-12; (2) 50% sulfonated mud system oily sludge +50% oilfield produced water + 0.1% HPAM + 1.0% BS-12. The preparation of a profile control agent from oily sludge is a viable low-cost resource treatment strategy for oily sludge, which is of great significance for the environmentally friendly treatment of oil and gas field development. Full article

The family Capitellidae performs critical roles in bioturbation and sediment remediation within global marine benthic ecosystems. However, they are a taxonomically challenging group due to their simple morphology and a ‘morphological mosaic’, where traditional classificatory traits, such as thoracic chaetiger counts, appear convergently across genera. Previous multi-locus studies (using 18S, 28S, H3, and COI) first highlighted this conflict, revealing the polyphyly of major genera like Notomastus and even Leiochrides itself (based on unidentified specimens). More recently, mitogenomic studies uncovered massive gene order rearrangements and a conflicting topology but did not include Leiochrides. Critically, with no complete mitogenome reported for a formally identified Leiochrides species, its true phylogenetic position and the validity of its polyphyly remain unresolved. To address this critical gap, we sequenced and characterized the first complete mitochondrial genome from a formally identified species, Leiochrides yokjidoensis, recently described from Korean waters. The complete mitogenome was 17,933 bp in length and included the typical 13 protein-coding genes (PCGs), 2 ribosomal RNAs (rRNAs), and 22 transfer RNAs (tRNAs). Gene order (GO) analysis revealed the occurrence of gene rearrangements in Capitellidae and in its sister clade, Opheliidae. A phylogenomic analysis using the amino acid sequences of 13 PCGs from 30 species established the first robust systematic position for the genus Leiochrides (based on this formally identified species). Phylogenetic results recovered Leiochrides as a sister group to the clade comprising Mediomastus, Barantolla, Heteromastus, and Notomastus hemipodus (BS 99%). This distinct placement confirms that Leiochrides represents an independent evolutionary lineage, phylogenetically separate from the polyphyletic Notomastus complex, despite their morphological similarities. Furthermore, our analysis confirmed the polyphyly of Notomastus, with N. hemipodus clustering distinctly from other Notomastus species. Additionally, signatures of positive selection were detected in ND4, and ND5 genes, suggesting potential adaptive evolution to the subtidal environment. This placement provides a critical, high-confidence anchor point for the genus Leiochrides. It provides a reliable reference to investigate the unresolved polyphyly suggested by previous multi-locus studies and provides compelling evidence for the hypothesis that thoracic chaetiger counts are of limited value for inferring phylogenetic relationships. This study provides the foundational genomic cornerstone for Leiochrides, representing an essential first step toward resolving the systematics of this taxonomically challenging family. Full article

To address the challenge of treating refractory organic dyes in textile wastewater, this study synthesized a novel copper-based composite material (designated MEL-Cu-6HNA) via a supramolecular self-assembly–pyrolysis pathway. Its core component consists of CuO/Cu₂O(SO₄), which was applied to efficiently degrade the Reactive Red 3BS dye within a sodium bicarbonate-activated hydrogen peroxide (BAP) system. This material was applied to degrade the Reactive Red 3BS dye using a sodium bicarbonate-activated hydrogen peroxide system. The morphology, crystal structure, and surface chemistry of the material were systematically characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Electron paramagnetic resonance (EPR) was employed to identify reactive species generated during the reaction. The effects of dye concentration, H₂O₂ concentration, MEL-Cu-6HNA dosage, and coexisting substances in water on degradation efficiency were systematically investigated, with active species identified via EPR. This study marks the first application of the supramolecular self-assembled CuO/Cu₂O(SO₄)₂ composite material MEL-Cu-6HNA, prepared via pyrolysis, in a sodium bicarbonate-activated hydrogen peroxide system. It achieved rapid and efficient decolorization of the recalcitrant Reactive Red 3BS dye. The three-dimensional sulfate framework and dual Cu²⁺ sites of the material significantly enhanced the degradation efficiency. MEL-Cu-6HNA achieved rapid and efficient decolorization of the recalcitrant Reactive Red 3BS in a sodium bicarbonate-activated hydrogen peroxide system. The material’s three-dimensional sulfate framework and dual Cu²⁺ sites significantly enhanced interfacial electron transfer and Cu²⁺/Cu⁺ cycling activation capacity. ·OH served as the primary reactive oxygen species (ROS), with SO₄²⁻, ¹O₂, and ·O₂⁻ contributing to sustained radical generation. This system achieved 95% decolorization within 30 min, demonstrating outstanding green treatment potential and providing a reliable theoretical basis and practical pathway for efficient, low-energy treatment of dyeing wastewater. Full article