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The extensive accumulation of coal-derived solid wastes in China has become a significant environmental challenge. Utilizing these wastes as resources is considered an effective approach. This study investigated activation systems for coal gangue to determine the optimal dosage for incorporation into cementitious materials. The effects of types and dosages of admixtures on the mechanical properties were examined. The results showed that augmenting the coal gangue content within a certain range enhanced the compressive strength of the composite cementitious materials. However, exceeding 20 wt.% led to a decline in compressive strength. The addition of coal gangue led to an increase in porosity. Furthermore, the addition of 4% lime and 4% gypsum resulted in enhanced properties. The performance of the resultant optimal cementitious material surpasses that of P·O 32.5 cement, making it a viable replacement in construction sector and contributing to the realization of resource recycling and ecological civilization construction goals.

Multimodal artificial intelligence models using digital histopathology slides outperform clinical and pathological variables for prognostic prediction of distant metastasis and prostate cancer–specific mortality, and can be incorporated in clinical practice for personalized risk stratification.

Artificial rockfill (AR) instead of natural rockfill can be used in rock-filled concrete (RFC) to increase the utilization ratio of solid waste. However, research on the placement style of ARs in RFC is still lacking. Artificial rockfill ratio (ARR) and exposed surface ratio (ESR) are taken into account when designing the placement style of ARs. The placement style with the row and column alignment is recommended for single-layer AR placement. The ARR and ESR of ARs with various sizes as influenced by placement styles without/with cushion blocks are compared. The ARR of the two styles both increases as rockfill size increases. The ARR of RFC without cushion blocks is greater than that of cushion blocks for each rockfill size. The ESR of RFC without cushion blocks decreases as rockfill size increases, whereas the ESR of RFC with cushion blocks increases. Placement style with cushion blocks is highly recommended when the particle size of ARs exceeds 300 mm. ARs with solid waste produced with the pressure forming method and self-compacting concrete (SCC) designed using the paste rheological threshold theory are used to produce scaled solid waste RFC specimens. Cracks tend to appear at the interfaces of the ARs and the SCC due to insufficient bonding force. Furthermore, wide cracks appear near the outer layer of the specimen's side wall. The ARR approaches 53.6% by ignoring the formwork sidewall effect and results in a higher solid waste content of 70.2%.

This study investigated the effect of powder materials and superplasticizer type on the optimal proportion of pastes and self-compacting concrete (SCC). Nine groups of power materials containing cement, fly ash (FA), limestone powder (LP), granulated blast furnace slag (GBFS), and modified phosphogypsum (MPG) were designed. The powder materials differed in their characteristics including specific surface area, zeta potential and density. Self-compacting paste zone (SCP zone) and the optimal proportion were obtained based on the paste rheological threshold theory. Quantitative relationships between the optimal proportion and powder characteristics were obtained by the linear regression method, which can help in the optimizing process of SCC. A new powder combination was designed to validate the relationships. The optimal water‒powder ratio by volume (VW/VP) and the optimal superplasticizer dosage by mass (SP%) could be calculated considering the physical and chemical properties of the powder combination. According to the optimal mix, the search area was narrowed and the SCP zone was obtained where a good SCC was obtained, which validated the effectiveness of the powder effect model. Finally, an improved powder effect model applicable to different superplasticizer types was proposed based on a good linear relationship between the optimal VW/VPand the basic VW/VP.

[Display omitted] • Our new designs on composition and two-step annealing produce almost the best tensile property among reported DP steels. • Deformable martensite is found responsible for the excellent ductility of dual-phase microstructure. • We propose a new martensitic phase transformation mode that enhances the plasticity of martensite. • A thermo-kinetic modulation strategy, higher ∆G and higher Q condition to initiate phase transformations, is proposed. A good combination of ultimate tensile strength (UTS) up to 1365 MPa and total strain to failure (StF) to 15.5 % has been achieved due to deformable martensite in the invented vanadium-microalloyed dual-phase (DP) steel, which was manufactured by two-stage annealing of cold rolled steel strip. The employed extensive characterizations revealed that the ductile martensitic phase in this DP steel differentiated from ordinarily low-carbon martensitic lath in both morphology and lattice structure. Complex coherent orientation relationships between ferrite, reverse austenite, martensitic phase and vanadium carbide (VC) do exist, leading to a new martensitic transformation mechanism and resultant dual-phase microstructure. Besides, a detailed characterization including essential phase transformation analysis in combination with in situ TEM observation, shows that, all the essential processing including recrystallization, reverse austenitic and martensitic transformation, in debt to the particular effects of VC, can be recognized as phase transformations with higher thermodynamic driving force and higher kinetic energy barrier as compared to previously common processing, which actually changes the microstructure and, indirectly leads to higher strength and higher ductility. This synergy of thermodynamics and kinetics can be generalized to improve mechanical properties of present steels. [ABSTRACT FROM AUTHOR]

Minimally invasive approaches to detect residual disease after surgery are needed to identify patients with cancer who are at risk for metastatic relapse. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease and relapse1. We evaluated outcomes in 581 patients who had undergone surgery and were evaluable for ctDNA from a randomized phase III trial of adjuvant atezolizumab versus observation in operable urothelial cancer. This trial did not reach its efficacy end point in the intention-to-treat population. Here we show that ctDNA testing at the start of therapy (cycle 1 day 1) identified 214 (37%) patients who were positive for ctDNA and who had poor prognosis (observation arm hazard ratio = 6.3 (95% confidence interval: 4.45–8.92); P< 0.0001). Notably, patients who were positive for ctDNA had improved disease-free survival and overall survival in the atezolizumab arm versus the observation arm (disease-free survival hazard ratio = 0.58 (95% confidence interval: 0.43–0.79); P= 0.0024, overall survival hazard ratio = 0.59 (95% confidence interval: 0.41–0.86)). No difference in disease-free survival or overall survival between treatment arms was noted for patients who were negative for ctDNA. The rate of ctDNA clearance at week 6 was higher in the atezolizumab arm (18%) than in the observation arm (4%) (P= 0.0204). Transcriptomic analysis of tumours from patients who were positive for ctDNA revealed higher expression levels of cell-cycle and keratin genes. For patients who were positive for ctDNA and who were treated with atezolizumab, non-relapse was associated with immune response signatures and basal–squamous gene features, whereas relapse was associated with angiogenesis and fibroblast TGFβ signatures. These data suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in patients who are positive for ctDNA and who are at a high risk of relapse. These findings, if validated in other settings, would shift approaches to postoperative cancer care.

Background: Prostate cancer exhibits biological and clinical heterogeneity even within established clinico-pathologic risk groups. The Decipher genomic classifier (GC) is a validated method to further risk-stratify disease in patients with prostate cancer, but its performance solely within National Comprehensive Cancer Network (NCCN) high-risk disease has not been undertaken to date. Methods: A multi-institutional retrospective study of 405 men with high-risk prostate cancer who underwent primary treatment with ?radical prostatectomy (RP) or radiation therapy (RT) with androgen-deprivation therapy (ADT) at 11 centers from 1995 to 2005 was performed. Cox proportional hazards models were used to determine the hazard ratios (HR) for the development of metastatic disease based on clinico-pathologic variables, risk groups, and GC score. The area under the receiver operating characteristic curve (AUC) was determined for regression models without and with the GC score. Results: Over a median follow-up of 82 months, 104 patients (26%) developed metastatic disease. On univariable analysis, increasing GC score was significantly associated with metastatic disease ([HR]: 1.34 per 0.1 unit increase, 95% confidence interval [CI]: 1.19–1.50, p?&lt;?0.001), while age, serum PSA, biopsy GG, and clinical T-stage were not (all p?>?0.05). On multivariable analysis, GC score (HR: 1.33 per 0.1 unit increase, 95% CI: 1.19–1.48, p?&lt;?0.001) and GC high-risk (vs low-risk, HR: 2.95, 95% CI: 1.79–4.87, p?&lt;?0.001) were significantly associated with metastasis. The addition of GC score to regression models based on NCCN risk group improved model AUC from 0.46 to 0.67, and CAPRA from 0.59 to 0.71. Conclusions: Among men with high-risk prostate cancer, conventional clinico-pathologic data had poor discrimination to risk stratify development of metastatic disease. GC score was a significant and independent predictor of metastasis and may help identify men best suited for treatment intensification/de-escalation.

Background: The Decipher 22-gene genomic classifier (GC) may help in post-radical prostatectomy (RP) decision making given its superior prognostic performance over clinicopathologic variables alone. However, most studies evaluating the GC have had a modest representation of African-American men (AAM). We evaluated the GC within a large Veteran Affairs cohort and compared its performance to CAPRA-S for predicting outcomes in AAM and non-AAM after RP. Methods: GC scores were generated for 548 prostate cancer (PC) patients, who underwent RP at the Durham Veteran Affairs Medical Center between 1989 and 2016. This was a clinically high-risk cohort and was selected to have either pT3a, positive margins, seminal vesicle invasion, or received post-RP radiotherapy. Multivariable Cox models and survival C-indices were used to compare the performance of GC and CAPRA-S for predicting the risk of metastasis and PC-specific mortality (PCSM). Results: Median follow-up was 9 years, during which 37 developed metastasis and 20 died from PC. Overall, 55% (n= 301) of patients were AAM. In multivariable analyses, GC (high vs. intermediate and intermediate vs. low) was a significant predictor of metastasis in all men (all p&lt; 0.001). Consistent with prior studies, relative to CAPRA-S, GC had a higher C-index for 5-year metastasis (0.78 vs. 0.72) and 10-year PCSM (0.85 vs. 0.81). There was a suggestion GC was a stronger predictor in AAM than non-AAM. Specifically, the 5-year metastasis risk C-index was 0.86 in AAM vs. 0.69 in non-AAM and the 10-year PCSM risk C-index was 0.91 in AAM vs. 0.78 in non-AAM. However, the test for interaction of race and the performance of the GC in the Cox model was not significant for either metastasis or PCSM (both p≥ 0.3). Conclusions: GC was a very strong predictor of poor outcome and performed well in both AAM and non-AAM. Our data support the use of GC for risk stratification in AAM post-RP. While our data suggest that GC may actually work better in AAM, given the limited number of events, further validation is needed.

Background: Genomic classifiers (GC) have been shown to improve risk stratification post prostatectomy. However, their clinical benefit has not been prospectively demonstrated. We sought to determine the impact of GC testing on postoperative management in men with prostate cancer post prostatectomy. Methods: Two prospective registries of prostate cancer patients treated between 2014 and 2019 were included. All men underwent Decipher tumor testing for adverse features post prostatectomy (Decipher Biosciences, San Diego, CA). The clinical utility cohort, which measured the change in treatment decision-making, captured pre- and postgenomic treatment recommendations from urologists across diverse practice settings (n= 3455). The clinical benefit cohort, which examined the difference in outcome, was from a single academic institution whose tumor board predefined “best practices” based on GC results (n= 135). Results: In the clinical utility cohort, providers’ recommendations pregenomic testing were primarily observation (69%). GC testing changed recommendations for 39% of patients, translating to a number needed to test of 3 to change one treatment decision. In the clinical benefit cohort, 61% of patients had genomic high-risk tumors; those who received the recommended adjuvant radiation therapy (ART) had 2-year PSA recurrence of 3 vs. 25% for those who did not (HR 0.1 [95% CI 0.0–0.6], p= 0.013). For the genomic low/intermediate-risk patients, 93% followed recommendations for observation, with similar 2-year PSA recurrence rates compared with those who received ART (p= 0.93). Conclusions: The use of GC substantially altered treatment decision-making, with a number needed to test of only 3. Implementing best practices to routinely recommend ART for genomic-high patients led to larger than expected improvements in early biochemical endpoints, without jeopardizing outcomes for genomic-low/intermediate-risk patients.

The effect of a low concentration of salt and sugar on the quality and microbial succession in blunt snout bream (Megalobrama amblycephala) fillets was assessed by sensory analysis, total volatile basic nitrogen, biogenic amines, Kvalue, total viable counts, 16S rRNA gene analysis, and Illumina MiSeq PE300 high-throughput sequencing. Fish samples were left untreated (control), treated with 1.8% salt (T1), or treated with 1.8% salt plus 0.9% sugar (T2). Consequently, salted and sugar-salted treatments extended the shelf life of bream fillets by 2 days, which retarded the increase of total volatile basic nitrogen, putrescine, cadaverine, and total viable counts. The putrescine and cadaverine concentrations of T2 were significantly (P< 0.05) higher than T1 after day 10. Brachybacteriumwas the major initial microbiota of bream fillets. As storage time progressed, Pseudomonasand Shewanellawere major genera in the spoiled control group. Pseudomonas, Shewanella,and Pseudoalteromonasbecame the main spoilers in the T1 and T2 groups.

Localization for outdoor wireless sensor networks has been a challenge for real applications. Although many solutions have been proposed, few of them can be used in real applications because of their high cost, low accuracy or infeasibility due to practical issues. In this paper, we propose a practical acoustic localization scheme called Thunder. Thunder employs an asymmetric architecture and shifts most of the complexities and hardware requirements from each node to a single powerful centralized device. The solution is efficient, and requires virtually zero cost in terms of extra per node hardware and innetwork communication. This paper also presents an efficient scheduling algorithm called Equilateral Triangle Scheduling to schedule Thunder for very large sensor networks and a resilient algorithm called Adaptive Fuzzy Clustering to provide robust localization without sacrificing efficiency in the presence of a high percentage of large ranging errors. To validate and evaluate Thunder, we built an experimental localization system based on the Mica2 platform, which achieved localization errors of about 1 meter in medium scale localization experiments.

We developed a new method for lidar calibration using lidar horizontal measurements of the atmosphere, combined with measurements of the aerosol refractive index and its size distribution.

We have investigated the temperature, $T$, dependence of a highly sensitive far-infrared (FIR) photodetector fabricated on a two-dimensional electron gas system in GaAs/AlGaAs heterostructures. The photoinduced resistance change, $\Delta R_{xx}$, observed in different integer quantum Hall (QH) regimes shows different $T$ dependences. At high $T$, $\Delta R_{xx}$ is limited by the vanishing of rising electronic temperature $\Delta T_{\text{e}}$. For $T < 5$ K, $\Delta R_{xx}$ can either rapidly increase with lower $T$ or slowly diminish, determined by the interplay between the magnetic field dependence of $\Delta T_{\text{e}}$ and the $T$ dependence of QH states.