MET）扩增是表皮生长因子受体（epidermal growth factor receptor, EGFR）阳性非小细胞肺癌（non-small cell lung cancer, NSCLC）耐药的重要驱动因素，MET-酪氨酸激酶抑制剂（tyrosine kinase inhibitors, TKIs）联合EGFR-TKIs的治疗策略可以克服MET介导的获得性耐药。研究表明，MET扩增也是间变性淋巴瘤激酶（anaplastic lymphoma kinase, ALK）、RET、ROS1等驱动基因阳性NSCLC患者接受TKIs类药物治疗后耐药的驱动因素。本文综述了近年来关于MET扩增作为驱动基因阳性NSCLC靶向治疗耐药驱动因素的研究进展，并总结了克服这种耐药机制的治疗策略。间质-上皮细胞转化因子（mesenchymal-epithelial transition factor,  MET）扩增是表皮生长因子受体（epidermal growth factor receptor, EGFR）等驱动基因阳性非小细胞肺癌（non-small cell lung cancer, NSCLC）患者接受TKIs类药物治疗后获得性耐药的一致性分子机制，双靶联合治疗策略有望可以克服MET扩增介导的获得性耐药。本文就MET基因及其信号通路、MET扩增的检测、获得性耐药现状及其联合治疗策略进行了综述。如今，针对驱动基因变异的靶向治疗药物已经为恶性肿瘤患者带来了长期获益和生存，近年来靶向治疗因其独特的作用机制、突破性的疗效和较少的不良反应也一直是肿瘤药物研发的方向，然而，随之而来的便是靶向治疗耐药的问题，解决酪氨酸激酶抑制剂（tyrosine kinase inhibitors, TKIs）类药物的耐药问题是精准医学时代的关键挑战。一些证据表明，间质-上皮细胞转化因子（mesenchymal-epithelial transition factor, 1MET基因，位于人类7号染色体长臂（7q21-31）上，全长约125 kb，由21个外显子和20个内含子组成，其编码分子量约150 kDa的c-MET蛋白前体，经局部糖基化后生成一个190 kDa的糖蛋白，该糖蛋白进一步剪切为α亚基（50 kDa）和β亚基（140 kDa），两者以二硫键连接形成一个异源二聚体-酪氨酸激酶受体，即为c-MET蛋白，也被称为肝细胞生长因子受体（hepatocyte growth factor receptor, HGFR）。。在生理状态下，HGF/MET信号通路的激活，负责调控多种生物学过程，包括细胞发育、增殖等，这对于多细胞生物体的完整性至关重要。在胚胎发育过程中，MET-HGF结合可以促进肌肉生长和神经系统的形成。在成年生物体内，它具有促进伤口愈合、组织修复及阻碍器官纤维化的生物学功能。而HGF/MET信号通路的失调不仅可以诱导肿瘤的发生，而且还会导致肿瘤的侵袭、增殖、血管生成和转移扩散等。c-MET通路的异常激活主要包括三种类型：MET外显子14跳跃突变、MET扩增和MET蛋白过表达。HGF是目前发现的c-MET的唯一配体，是间质细胞在发育过程中产生和分泌的旁分泌信号分子。成熟的活性HGF是由α链和β链通过二硫键形成的二聚体。只有当c-Met和HGF的α链完全结合时，才能完全诱导HGF/MET信号通路的激活22.1MET扩增可以通过多倍体和局部扩增两种方式来实现。携带MET基因的7号染色体出现全基因组异常复制时就会形成多倍体，多倍体除了会导致MET基因拷贝数（gene copy number, GCN）增加，也会使得位于7号染色体上其他基因（如EGFR等）的拷贝数平行增加，而局部扩增则不会因为整条染色体的复制使得其他基因的拷贝数增加。2.2MET扩增的检测方法有很多，包括荧光原位杂交（fluorescence in situ hybridization, FISH）、二代测序（next-generation sequencing, NGS）、实时定量聚合酶链反应（quantitative real time polymerase chain reaction, qRT-PCR）和免疫组织化学（immunohistochemistry, IHC）等。然而，上述的检测方法界定MET扩增的阈值均没有明确标准。目前，对于2.2.1MET扩增。其一依赖于测定MET GCN，现有临床研究多采用Cappuzzo标准（MET GCN≥5）来界定MET扩增, 9，也有其他学者建议MET GCN≥6个甚至是15个才能定义为MET扩增，此法不足之处是无法区分多倍体和局部扩增。其二通过计算MET位点数目与7号染色体探针（chromosome 7 probe, CEP7）的比值作为评估MET扩增的依据（MET/CEP7≥2.0），这也是目前最广为接受的标准。FISH法主要通过两种方式来定义2.2.2MET和其他基因的拷贝数变异。然而使用NGS检测扩增时不仅需要考虑一些技术层面的问题，且NGS有时会出现难以解释的结果，目前尚无研究证实FISH法和NGS法的一致性，因此FISH法迄今为止被认为是相对更可靠的技术。目前基于NGS的检测方法主要有两种：扩增法和杂交捕获法，两种方法各有利弊，相较于扩增法，杂交捕获法覆盖的基因组区域更加广泛，可识别和剔除重复序列，能够更准确地评估2.2.3MET扩增的另一种方法，有临床研究对阳性的定义是评分为200或更高，此外qRT-PCR也是一种检测MET扩增的方法，但是与FISH法、NGS方法相比，IHC、PCR法优势并不显著。IHC作为检测33.1MET扩增是目前已经明确的EGFR-TKIs治疗获得性耐药的重要机制之一，属于旁路激活途径。5%-20%接受第一/二代TKIs治疗的患者会发生MET扩增介导的耐药, 14。接受第三代TKIs奥希替尼治疗的患者，无论是一线还是后线治疗，发生MET扩增的比例大致相同，占10%-24%。对于EGFR-TKIs耐药后MET扩增的患者，传统化疗、MET抑制剂单药疗法、免疫抑制剂疗法等效果均有限。而EGFR-TKIs联合MET-TKIs的双通路抑制已经在多项临床研究, 19, 20中显示出不错的疗效获益。，70例接受过EGFR-TKIs治疗进展后出现MET扩增的晚期NSCLC患者，接受了三种治疗方案：EGFR-TKIs联合克唑替尼（DT组，n=38）、克唑替尼单药治疗（ST组，n=10）、含铂双药化疗（CH组，n=22）。结果显示：DT组的客观缓解率（objective response rate, ORR）和疾病控制率（disease control rate, DCR）显著优于CH组（ORR: 48.6% vs 18.2%, P=0.026; DCR: 82.9% vs 50.0%, P=0.016），而与ST组相比，却无显著统计学差异（ORR: 48.6% vs 40.0%, P=0.73; DCR: 82.9% vs 70.0%, P=0.39）。生存分析结果显示：DT组的无进展生存期（progression-free survival, PFS）较ST组（5.0个月vs 2.3个月，P=0.004）及CH组（5.0个月vs 2.9个月，P=0.036）显著延长，然而，三组的总生存期（overall survival, OS）无显著差异（10.0个月vs 4.1个月vs 8.5个月，P=0.088）。此外，该研究还发现合并TP53突变及EGFR扩增的分子特征均不会影响EGFR-TKIs联合克唑替尼的疗效。2021年美国临床肿瘤学会（American Society of Clinical Oncology, ASCO）年会上公布了由我国研究者开展的一项真实世界研究是第一项比较替泊替尼联合吉非替尼和标准化疗用于MET过表达和MET扩增晚期NSCLC的多中心随机临床研究。研究结果显示，在接受替泊替尼和吉非替尼联合治疗的MET扩增患者中，近67%的患者在该研究的IB期和II期均取得了客观缓解，同时联合用药也是安全和可耐受的，联合治疗组及化疗组的中位PFS分别为16.6个月、4.2个月（HR=0.13），中位OS分别为37.3个月、13.1个月（HR=0.08），该研究还强调了替泊替尼联合吉非替尼对MET高水平扩增患者的疗效更加显著。INSIGHT研究的部分结果，该研究入组既往接受EGFR-TKIs治疗后出现MET扩增的局部晚期或转移性NSCLC患者。扩展队列的结果表明奥希替尼联合赛沃替尼安全性良好，同时对于既往未经过三代EGFR-TKI治疗耐药后出现MET驱动突变的NSCLC患者疗效确切，其中对于伴有T790M阳性的患者，疗效最为显著（PFS：11.1个月，ORR=67%）。此外，该研究中B1部分显示，既往经过三代EGFR-TKI治疗的患者使用联合方案疗效并不显著（PFS：5.5个月，ORR=33%），可能与既往接受多线治疗及较重的疾病转移负担有关。2021年世界肺癌大会（World Congress of Lung Cancer, WCLC）上，发布了国际多中心TATTON研究A组部分（MET基因变异组）疗效数据，入组的20例患者均接受奥希替尼联合赛沃替尼的治疗方案，17例可评估疗效，其中7例患者经研究者评估达到了客观缓解，其ORR达到了41%（95%CI: 25%-59%），体现了初步的抗肿瘤活性，同样并未发现新的安全性事件。2021年欧洲肿瘤内科学会年会（European Society for Medical Oncology, ESMO）公布了II期ORCHARD研究Science Translational Medicine上发表了一项临床前研究，与我们传统认知相悖，表明部分同时存在EGFR突变和MET扩增的肺癌患者，可能仅依赖于MET的激活，对于这部分人群，仅需要使用单药MET-TKIs治疗，而并非目前所认可的EGFR-TKIs联合MET-TKIs的治疗方案。研究进一步发现对MET-TKIs单药治疗敏感的细胞相较于对EGFR-TKIs敏感的细胞以及EGFR-TKIs和MET-TKIs联合处理敏感的细胞，其EGFR: MET mRNA的比率更低，临床中似乎可以通过评估EGFR: MET mRNA的比率来预测其对MET-TKIs单药治疗的敏感性。因其仅是一项临床前研究，结论尚需在未来更多的前瞻性临床试验中来验证。3.2ALK融合是NSCLC中又一种常见的分子亚型，目前，ALK抑制剂已经发展到第三代，与EGFR-TKIs类似，克唑替尼等ALK抑制剂虽疗效显著，但同样面临着耐药的问题，研究, 24发现约50%的NSCLC患者对ALK-TKIs的耐药是通过非ALK依赖途径实现的，其中最常见的原因是旁路信号途径的激活，包括MET、EGFR、SRC和IGF-1R等。建立了对ALK抑制剂耐药的晚期肺腺癌来源的人源性肿瘤组织异种移植（patient-derived xenograft, PDX）模型，全外显子测序证实，在PDX模型中，MET扩增是阿来替尼的独立耐药机制，ALK抑制剂联合MET抑制剂的双通路抑制在PDX模型克服耐药中十分有效。Ji等报道了1例ALK阳性肺腺癌患者，一线接受阿来替尼治疗6个月后疾病进展，肾上腺转移灶活检组织NGS检测提示：MET高水平扩增，未发现ALK突变，给予克唑替尼治疗10个月后再次进展，二次肾上腺活检行MET FISH检测示：MET/CEP7=9.6，同时循环肿瘤DNA（circulating tumor DNA, ctDNA）NGS检测提示：EML4-ALK阳性，且未发现其他耐药突变。随后给予阿来替尼联合克唑替尼的联合治疗策略，2周后随访行正电子发射计算机断层显像（positron emission tomography-computed tomography, PET-CT）检查示：肾上腺、纵隔及胸膜的转移性病灶较前显著改善，直到4个月后患者出现颅内转移性病灶。Dagogo-Jack等分析了来自136例ALK阳性NSCLC患者ALK-TKIs治疗后的207个组织（n=101）和血浆（n=106）样本，采取FISH检测或NGS检测来评估MET扩增的基因改变。结果显示，11例（13%）患者的活检组织样本检测出MET扩增，相较于克唑替尼耐药后二线接受第二/三代ALK抑制剂的患者，一线接受第二/三代ALK-TKIs治疗的患者更容易出现MET扩增的基因改变（33% vs 9%, P=0.019）。该研究进一步在临床前模型中证实了MET-TKIs卡马替尼或赛沃替尼可部分抑制细胞增殖，而劳拉替尼和卡马替尼或赛沃替尼的联合使用抑制细胞增殖的效力更强，表明ALK/MET的双重阻断可强效抑制ALK及其下游的信号通路。基于上述结果，本研究中2例因MET改变而发生获得性耐药的患者，接受劳拉替尼联合克唑替尼的治疗方案后迅速获益，进一步验证了双靶联合方案在ALK抑制剂耐药后出现MET改变患者中的治疗潜力，但最佳联合方案仍需在更多的前瞻性临床试验中进行评估。Shi等3.3ROS1重排占NSCLC的1%-2%，已逐渐成为NSCLC的重要致癌驱动基因以及治疗靶点之一, 29。随着研究的深入，越来越多的ROS1抑制剂已被获批用于临床。目前关于ROS1重排NSCLC对TKIs耐药机制的研究中，已发现了ROS1激酶结构域外显子的继发突变。而随着恩曲替尼和劳拉替尼在美国和日本的上市，其耐药模式又有了新的发现。对晚期ROS1融合阳性NSCLC患者接受克唑替尼或劳拉替尼治疗进展后的组织或血浆样本进行了重复基因检测，以探索其耐药机制，结果表示在部分未发现ROS1激酶结构域耐药突变的患者中，可能存在ROS1非依赖性耐药机制，2例患者的组织NGS检测结果提示出现了MET扩增，1例为治疗前胸水FISH检测提示未见MET扩增（FISH: MET/CEP7=1），接受劳拉替尼治疗耐药后的脑转移灶组织NGS检测结果提示：MET扩增（FISH: MET/CEP7=6.3），另一例患者的肾上腺转移灶组织NGS检测同样出现了MET扩增（FISH: MET/CEP7 > 25），提示MET扩增可能为ROS1非依赖性耐药机制。Yang等报道了1例ROS1重排转移性肺腺癌患者，一线接受克唑替尼治疗19个月后，脑转移灶迅速进展（期间给予劳拉替尼治疗，脑转移相关症状较前加重），随后进行了紧急的脑转移灶手术，术后病理标本NGS检测回报提示：高水平MET扩增（GCN: 32），为进一步验证MET扩增为TKIs治疗后出现，研究者们又对肺部原发灶再次进行了FISH检测，结果并未检测出MET扩增。该研究同样提示MET扩增可能为ROS1-TKIs的潜在耐药机制，而遗憾的是，该患者最终死于严重脑水肿和脑疝，未尝试ROS1-TKIs联合MET-TKIs的联合治疗策略。目前尚无公开的研究数据表明ROS1抑制剂耐药后MET扩增的患者中双靶联合治疗策略的可行性与安全性，未来有必要继续探索ROS1非依赖的耐药机制及应对策略。Lin等3.4RET基因融合的发生率占1.4%-2.5%。塞尔帕替尼（Selpercatinib）和普拉替尼（Pralsetinib）是特异性RET抑制剂，已被美国食品药物监督管理局（Food and Drug Administration, FDA）批准用于转移性RET融合阳性的NSCLC成人患者。根据NSCLC靶向治疗的经验，耐药的发生是不可避免的，目前RET抑制剂耐药相关的分子机制尚不完全清楚。我国NSCLC患者中对一组RET融合阳性NSCLC患者接受塞尔帕替尼和普拉替尼治疗耐药后的肿瘤组织和血浆进行了详细分析，其中3例（15%）耐药患者检测出MET扩增，2例（10%）检测出RET耐药突变（为已知的RET G810S和G810C突变），1例检测出KRAS扩增。由此可见，MET扩增可能是这些新型RET抑制剂的潜在耐药机制。Rosen等的一项研究进一步在体外模型中表明，MET扩增是塞尔帕替尼获得性耐药的潜在机制，且塞尔帕替尼和克唑替尼的联合治疗可以克服其耐药性。同样该研究中4例接受塞尔帕替尼耐药的NSCLC患者，二次组织NGS检测提示MET扩增，鉴于联合使用EGFR和MET抑制剂可以有效克服MET驱动的耐药性已被大家所熟知，研究者们随后采取了尝试塞尔帕替尼联合克唑替尼的双靶抑制策略，结果也证实了这种联合治疗的有效性，其中1例患者的治疗缓解时间更是达到了10个月。遗憾的是，该研究的病例数（n=4）太少。然而Meng等报道了1例RET融合阳性（KIF5B-RET, FOXD1-RET）IV期肺腺癌患者，一线接受贝伐珠单抗联合培美曲塞和卡铂治疗14个月后进展，二线接受塞尔帕替尼靶向治疗9个月后再次进展，二次基因检测提示MET扩增，随后接受了塞尔帕替尼联合克唑替尼的双靶治疗方案，然而患者的一般状况迅速恶化，4个月后死于癌症。因此，这更加凸显了未来进行更大规模前瞻性研究的重要性，以探索RET抑制剂联合MET抑制剂的疗效及安全性，为我们带来更加准确的循证医学证据。Lin等3.5KRAS是一种癌症常见突变基因，2021年5月，FDA批准Sotorasib（AMG 510）用于治疗先前已经接受过至少一种系统疗法、经FDA批准的检测方法证实存在KRASG12C突变、局部晚期或转移性NSCLC成人患者。其临床研究CodeBreak（NCT03600883）在后线治疗中ORR达到了36%，中位PFS为6.8个月，中位OS为12.5个月。同样，探索耐药突变谱至关重要，但CodeBreak研究中尚未报道连续活检数据和连续ctDNA数据。的研究中，10例被评估为疾病进展的KRASG12C突变NSCLC患者中，2例（20%）患者中发现了MET扩增。同样另一项研究发现，在23例对KRASG12C抑制剂Adagrasib产生耐药的NSCLC患者中，2例患者检测出MET扩增，并未发现其他可能的耐药机制，包括KRAS继发性突变等。Suzuki等在构建的耐Sotorasib的KRASG12CNSCLC细胞株中检测到了MET扩增的亚克隆进化，深入探索发现MET扩增既可以促使RAS由非活性状态向活性状态转换，通过激活RAS-RAF-MEK-ERK途径来实现对Sotorasib的耐药，还可以通过RAS非依赖性途径激活AKT来诱导对KRASG12C抑制剂的耐药性。且在细胞株模型中，MET抑制剂克唑替尼可通过抑制Ras-MEK-ERK和AKT信号通路来恢复对Sotorasib的敏感性；在耐Sotorasib的异种移植肿瘤小鼠模型中，MET抑制剂及KRASG12C抑制剂的联合治疗可使移植瘤缩小，且并未发现毒性作用。因此，MET扩增作为选择性小分子KRASG12C抑制剂耐药可能的驱动因素，双通路阻断同样有希望成为克服MET扩增所介导KRASG12C突变NSCLC耐药性的一种有前景的治疗选择。在Awad等3.6NTRK基因融合作为NSCLC的一个独特分子亚型，与获批药物数量众多的EGFR等靶点相比，患者生存情况并不乐观。原肌球蛋白受体激酶（tropomyosin receptor kinase, TRK）抑制剂作为针对NTRK基因融合的靶向治疗药物，为无法使用常规靶向治疗药物的患者提供了新的选择。有研究表明，对TRK抑制剂的耐药性是由丝裂原活化蛋白激酶（mitogen-activated protein kinase, MAPK）通路的基因组改变所介导的，而MET扩增已被确定为耐药的关键。目前，关于NTRK融合阳性肺癌患者TKIs治疗后耐药的研究报道相对较少，Cocco等报道了1例NTRK融合阳性的胆管癌患者，一代TRK抑制剂耐药后检测出MET扩增，且对NTRK的测序并未发现激酶结构域点突变。4MET扩增是目前已经明确的EGFR阳性NSCLC获得性耐药的机制之一，而近年来，越来越多的研究发现，MET扩增不仅存在于EGFR阳性患者中，而且在ALK、RET、ROS1等驱动基因阳性NSCLC患者的获得性耐药机制中同样发挥着关键作用。目前，在EGFR阳性NSCLC患者中，EGFR和MET的双通路抑制在国内外几项大型临床研究中均取得了不错的疗效和安全性数据；在ALK、RET、ROS1等驱动基因阳性NSCLC患者中，通过前文所述不难发现，双靶联合治疗策略也有望成为克服MET扩增所介导获得性耐药的最佳治疗选择之一。因此，未来期待有更多的前瞻性临床试验来继续验证该双靶联合治疗策略的疗效和安全性。精准治疗时代下，随着MET抑制剂的不断推陈出新，相信在不久的将来，不同的药物组合可以最大化发挥其疗效。


Thus, the current findings demonstrated that RHA can be used in the concrete industry as a possible revenue source for developing sustainable concretes with high performance.The incorporation of waste materials generated in many industries has been actively advocated for in the construction industry, since they have the capacity to lessen the pollution on dumpsites, mitigate environmental resource consumption, and establish a sustainable environment. This research has been conducted to determine the influence of different rice husk ash (RHA) concentrations on the fresh and mechanical properties of high-strength concrete. RHA was employed to partially replace the cement at 5%, 10%, 15%, and 20% by weight. Fresh properties, such as slump, compacting factor, density, and surface absorption, were determined. In contrast, its mechanical properties, such as compressive strength, splitting tensile strength and flexural strength, were assessed after 7, 28, and 60 days. In addition, the microstructural evaluation, initial surface absorption test, = environmental impact, and cost–benefit analysis were evaluated. The results show that the incorporation of RHA reduces the workability of fresh mixes, while enhancing their compressive, splitting, and flexural strength up to 7.16%, 7.03%, and 3.82%, respectively. Moreover, incorporating 10% of RHA provides the highest compressive strength, splitting tensile, and flexural strength, with an improved initial surface absorption and microstructural evaluation and greater eco-strength efficiencies. Finally, a relatively lower CO Concrete production requires a lot of raw materials, which leads to a significant amount of energy consumption and pollution of nature . Cement ioration ,4. FurthThe concept has prompted concrete science and engineering researchers to look into and explore supplemental waste components that could be employed as alternatives for different elements in concrete manufacturing ,7,8,9. WRice is a significant agricultural commodity in Asia ,23. Its 2, making it ideal for usage as a pozzolan material [Rice husk contains a high concentration of SiOmaterial . Pozzolamaterial . Rice humaterial  which camaterial ,23. Thismaterial ,34,35 anmaterial ,37, with2 during the hydration phase of concrete led to the formation of additional C-S-H gel, which considerably increases the strength and durability characteristics. Ge et al. [2 for generating a specific type of C-S-H gel  at a temperature of about 40 °C, with the contact of moisture. According to Bouzoubaâ and Fournier [The favorable benefits of RHA on concrete’s mechanical performance and longevity have been extensively studied ,38,39,40e et al.  considere et al.  observedFournier , substitFournier  calculatFournier , and wasFournier . GiaccioFournier  found thThe investigation was directed to reinforce a link between the two research topics, namely the incorporation of waste products in concrete and the demonstration of their relevance. Furthermore, RHA is not frequently employed throughout the Malaysian building industry. The fundamental goal of the study is to evaluate the behavior and performance of high-strength concrete incorporating RHA at various proportions ranging from 0% to 20%, as well as to promote the utilization of waste materials for a sustainable future. Various fresh properties including slump, compacting factor, density, compressive strength, splitting tensile strength, and flexural strength were all evaluated, and the strength properties were compared with conventional HSC. Furthermore, an environmental impact assessment of the produced HSC was investigated.With growing environmental consciousness at all levels of society, the pollution and health hazards specifically associated with the concrete, cement, and clay brick industries are coming under intense scrutiny from environmentalists and governments. A significant amount of RHA is generated in Malaysia, which imposes tremendous environmental challenge. Even worse, the high population growth and shortage of waste-disposal sites in Malaysia pose a challenge to deal with this kind of toxic waste. They pose environmental problems such as air pollution and the leaching of hazardous and toxic chemicals , cobalt, lead, manganese, mercury, molybdenum, selenium, strontium, thallium, and vanadium, along with dioxins, polycyclic aromatic hydrocarbon compounds, etc.) when dumped in landfills, quarries, rivers, and oceans. Consequently, air and water pollution have been inextricably linked to environmental problems and climate change. This study was conducted to maximize the application of RHA, which may help to reduce the environmental challenge, and to find a cost-effective sustainable solution for producing high-strength concrete.Ordinary Portland cement (OPC) was collected from local vendors and considered the prime binder material for the concrete mixes that corresponded to the standard BS EN 196-1:2016 . The cemThis study’s experimental procedure includes the evaluation of fresh properties, mechanical properties, microstructural properties, environmental impact, and cost–benefit assessment. So, the sequential works are represented in this study, as shown in Rice husk was gathered from a mill located in Kuala Selangor, Malaysia, and incinerated inside a ferrocement furnace at the University of Malaya to generate RHA. After about an hour of keeping the flame beneath the furnace, the husk began to smolder itself for around 24 h. Then, the ash was kept for settling within the furnace for the next 24 h, before being extracted and pulverized with a Los Angeles machine. The specimen of rice husk ash utilized in this research is illustrated in Physical properties also can be understood by the particle-size distribution curve. The distribution curve of RHA is shown in This investigation used crushed aggregates from the quarry as coarse aggregate (CA), collected from local suppliers with a nominal size of 20 mm, complying with BS 812-103.1:1985 . The finThis experimental investigation was done for five concrete mixes prepared by altering the water–binder ratio and superplasticizer concentrations. The water–binder ratio and the superplasticizer remained constant at 0.35 for all concrete mixes, which are about 0.5% of the cement on a weight basis. Five mixtures of the concrete were generated in the laboratory to conduct this research. The initial mix was termed the reference (control) mix, as it was prepared with a conventional mix design and without any RHA, and was designated as RHA0 for this investigation. The remaining four mixes had the cement substituted by 5%, 10%, 15%, and 20% RHA and were termed RHA5, RHA10, RHA15, and RHA20, respectively. The concrete mixtures with various rice husk ash percentages are demonstrated in All concrete mixes were designed with a water–binder ratio of 0.275. A 0.5% weight-based addition of superplasticizer was made to the cement. According to ASTM C685M-17 , the conThe compressive strength tests were carried out on a cube specimen of 100 mm × 100 mm × 100 mm, whereas the splitting tensile strength tests were performed on a cylindrical specimen, with a diameter of 100 mm and a height of 200 mm. The flexural strength was determined utilizing 100 mm × 100 mm × 500 mm prisms prepared in the lab. The concrete in the molds was temped in three stages, while casting to achieve optimal compaction and void elimination. Before demolding, all samples were allowed to stand for 24 h to ensure they were sufficiently hardened. The samples were removed from the molds and labeled for accurate recordkeeping after 24 h. Then, all the specimens emerged in curing tanks completely at 27 ± 2 °C ambient temperatures for 7, 28, and 56 days.The slump test was performed for the reference and other mixtures employing the ASTM C-143  standardThe compacting factor test of concrete mixture, equivalent to the slump test, exhibits a downward tendency when the proportion of RHA increases, as shown in 3, with associated slump ranging from 56 to 30.5 mm. The density of the control sample was about 2638.125 kg/m3, whereas the 5%, 10%, 15%, and 20% RHA concrete mixes had densities of 2600.63 kg/m3, 2565 kg/m3, 2509.38 kg/m3, and 2466.875 kg/m3, respectively, exhibiting 1.42%, 2.77%, 4.88%, and 6.49% reduction compared to the RHA0 mix. These findings are consistent with the investigation of Dong et al. [3. The reason behind the reduction is the reduced specific gravity of RHA. It is substantially lower than cement, leading to a decrease in mass per unit volume of the concrete mixes.The relation between the density and slump value of the concrete mixtures is depicted in g et al.  and EphrSeveral researchers have suggested that the increase in compressive strength could be due to various factors, such as RHA’s microfilling ability and pozzolanic activity. Moreover, RHA is highly reactive; it reacts with calcium hydroxide (a byproduct of cement hydration) and produces additional C-S-H. The additional C-S-H reduces the porosity of concrete by filling the capillary pores, thus improving the concrete microstructure in the bulk paste matrix and transition zone, leading to increased compressive strength. A decrease in compressive strength was observed with mixes containing more than 10% of RHA. Various researchers also reported such a trend in strength. Kannan et al.  reportedCompared with the reference concrete, RHA20 possessed a splitting tensile strength of 4.19, 6.19, and 6.37 MPa at 7, 28, and 56 days, respectively, which is comparable to the findings of earlier researchers ,41,66,71The flexural strength for RHA-incorporated concrete mixes regarding mean flexural strength, coefficient of variation (COV), standard deviation, standard error, and 95% confidence interval within 7, 28, and 56 days are depicted in The obtained flexural strength for all the concrete mixes with the varying RHA concentrations at 7, 28, and 56 days is illustrated in 2 s, which then reduced to 0.19 mL/m2 s after 30 min of measuring. Surface absorption for 10%-RHA replacement fell to 0.16 mL/m2 s at the 10 min mark, then steadily climbed to 0.26 and 0.29 mL/m2 s for concrete with 15% and 20% RHA . The original microstructure and morphology of the hydrate mixes were visible on the crushed sample surfaces. Gold-coated crushed samples were placed on the brass stubs using carbon adhesives. frf = flexural strength (MPa), cf = compressive strength (MPa).The interrelationship between the compressive and flexural strength of the concrete incorporating various proportions of RHA for 7, 28, and 56 days is illustrated in 2) demonstrate a good linear correlation between the compressive and flexural strengths for various durations at 7, 28, and 56 days. The preferred formula for representing the relation between the compressive and flexural strength is as follows:According to the relationship graph, the ACI 363R formula and the CEB-FIP formula are probably the best predictors of flexural strength among the other codes of standardized formulas for RHA-based concrete. Contrarily, AS 3600 showed the most significant deviation from the experimentally anticipated flexural strengths and significantly undervalued the flexural strength. The 0.96 coefficients of determination (Rfst = splitting tensile strength (MPa) and f’c = compressive strength (MPa).Likewise, 2 = 0.99, indicating that 99% of the average tensile strength can be clarified through that linear correlation, while the residual 1% remains unexplained. In this investigation, the following formula can be advised for expressing the relationship between the splitting tensile and compressive strengths of RHA-incorporated concrete.It can be seen that amongst all the standards, the estimated values of ACI 363R showed the nearest value compared to the experimental ones, whereas AS 3600 showed the most prominent variation within the experimental results. A strong correlation was determined between compressive and splitting tensile strengths, with the coefficient of determination R2 emissions [2 emissions [2-eq/kg material) has enabled the development of alternative binders to reduce concrete’s reliance on OPC as its primary binder.Cement production accounts for around 10% of worldwide COmissions ,81,82. D2 emissions of concrete, the embodied CO2 emissions of different waste materials will vary. Regarding the present investigation, RHA was partially utilized as a binder to replace OPC. To highlight the impact of RHA on the overall embedded CO2 emissions of HSC, this study estimates the total CO2 emissions, by considering the equivalent CO2 releases for each material. These numbers were extracted from relevant research studies and are presented in Although using SCMs will undoubtedly lower the overall embodied CO2 of each material and then adding the results. As seen in 2 content compared to other materials. OPC is responsible for roughly 89.10% of the total CO2 emissions for the control mix (RHA0). This was significantly reduced by substituting 20% OPC with RHA (RHA20). For the RHA20 mix, the CO2 contribution of OPC input decreased from 492 to 393.6 kg-CO2/m3. In addition, RHA5, RHA10, RHA15, and RHA20 reduced 4.31%, 8.63%, 12.95%, and 17.27% of the CO2 emissions, respectively.The embodied GWP for each mixture was calculated by multiplying the weight of each ingredient required to manufacture one cubic meter of concrete by the embodied CO2 intensity, which can be defined as the quantity of CO2 emissions produced per unit of performance. It was determined using Formula (11)iC represents the eco-strength efficiency, which is the intensity of CO2, CO2 represents the embodied carbon dioxide emissions released by the concrete mixes as determined using sC represents the compressive strength.The eco-strength efficiency of concrete is another metric that may be applied to the environmental impact assessment for evaluation. Alnahhal et al.  used the2 intensity is represented by the line along the secondary axis. The CO2 intensity allows for the evaluation of both the performance and contribution of concrete mixes to Global Warming Potential per their unit strength, which makes it a good predictor of the impact of concrete use  [2 rises when there is a greater amount of Portland cement in the concrete mixture. Substituting cement with RHA, CO2 intensity can be reduced for a given strength, particularly at later ages. For instance, lowering the percentage of Portland cement from 100% (RHA0) to 20% (RHA20) resulted in a decrease in the CO2 intensity from 11.89 MPa/kgCO2-eq.m−3 to 8.1 MPa/kgCO2-eq.m−3.The eco-strength efficiency of the various mixes is compared with their compressive strength to facilitate an organized and consistent comparison of the mixes.  et al.) . In most3 of concrete. The OPC and the superplasticizer are the primary factors that determine the pricing. The RHA20 mix has the lowest overall cost, costing USD 149.02 per m3 of concrete produced. Compared to the control mix, this is approximately 9.28% less expensive.Before adopting any newer or mixed concrete, the construction industry considers the environmental impact assessment and the cost–benefit analysis as two of the most critical factors. The cost–benefit analysis of concrete, which was the subject of this study, was computed for each mix, based on the costs of the individual materials in the area. As observed in The concrete mixture containing RHA exhibited poor overall workability due to a low water-to-cement ratio, a constant concentration of SP, and the cellular structure of RHA, which absorbed moisture.As the concentration of RHA was increased, the density of the hardened concrete mixtures decreased; similarly, the ISAT results indicated that the permeability of the concrete decreased as the concentration of RHA increased.The optimum compressive strength was achieved with RHA10, which was the 10% RHA supplementation by the weight of the cement. The reason could be due to the pozzolanic activity and pore refinement of the RHA particles.The addition of 10% RHA to concrete enhanced the splitting tensile strength compared to RHA0 (reference concrete), and the percentage of the splitting tensile strength enhancement ranged from approximately 2.0% to 7.5%. However, a decrease in the tensile strength was observed after 10% RHA incorporation.The flexural strength results were identical to the compressive and tensile strength tests. According to these determinations, concrete incorporating 10% RHA possessed maximum results of 5.3250, 8.1500, and 9.4517 MPa at 7, 28, and 56 days, respectively.The relationship between splitting tensile strength and flexural strength showed a good linear connection with the enhancement of compressive strength. The estimated values of ACI 363R and CEB-FIP were the closest among all standards for both flexural and splitting tensile strength, whereas AS 3600 possessed the highest fluctuation.Microstructural investigation of the specimens presented a mostly irregular and agglomerated state of the concrete. Chemical reactions and micrographs of the RHA-incorporated concrete depicted the microfiller effect. Based on the flakiness of the dense microstructure combination, RHA may achieve the strength in an incremental style up to 10% utilization, demonstrating the optimal consideration.2-eq/kg material, with a 17.27% reduction than the control mix, whereas the RHA10 mix represented an 8.63% GWP reduction, while achieving 3.28% better compressive strength than the control mix, demonstrating a significant eco-strength efficiency.RHA20 depicted the lowest GWP of 452.45 kgCOIn terms of cost–benefit analysis, the RHA20 mix had the lowest overall cost, projected to be approximately 9.28% less expensive than the control mix. Although the RHA10 mix showed little cost reduction (only 4.64% than the control mix), it depicted the lowest cost index value of 2.27 USD/MPa, which is almost 11% cheaper than the RHA0 mix.Among all the mix proportions, the 10%-RHA-incorporated concrete produced overall satisfactory performance for its fresh and mechanical characteristics as well as in its environmental impact analysis and cost–benefit analysis. It is feasible to generate high-strength concrete (grade 60) by employing RHA as an additional cementing element, which leads to waste-product mitigation and a sustainable alternative for the construction field.The awareness of waste management and environmental issues has led to considerable breakthroughs in using waste materials such as rice husk ash. The fundamental purpose is to assess the fresh and mechanical properties of concrete, including RHA as a cement substitute, to determine their feasibility for construction and attempt to preserve natural resources, recycle trash, and make long-lasting concrete. Based on the experimental outcomes, the following significant observations and conclusions can be reached:


In order to evaluate the influence of freeze–thaw action on the durability of concrete structures, this paper presented an experimental study to investigate the effects of freezing–thawing cycles and concrete strength on the bond behavior between steel bars and concrete confined with stirrups. Through freeze–thaw cycles and center pullout tests, the failure mode of pullout specimen, concrete strength, mass loss, dynamic elastic modulus, and bond–slip curves were analyzed. At last, the bond–slip constitutive model was proposed for specimens with stirrup confinement under freeze–thaw action. Main test results indicate that the failure mode and shape of bond–slip curves are affected by stirrups. The bond strength hasa certain increase after 100 freeze–thaw cycles owing to the constraining force from stirrups, whereas the splitting tensile strength significantly declines. After 100 freeze–thaw cycles, the splitting tensile strength of C20 and C40 decreased by 40.8% and 46.5%, respectively. The formula was provided to calculate the bond strength of constrained concrete after freeze–thaw cycles, and the damage coefficient and other related parameters in the formula were suggested. The predicted bond–slip curves are close to the experimental results, which could provide reference for the related research of bond performance after freeze–thaw action. Concrete has the advantages of high compressive strength, convenience in construction, relatively low cost, and so on, which has been used as the main building material worldwide. However, there exista large amount of tiny pores in concrete, and it is easy to crack. Therefore, water and aggressive ions would penetrate into concrete, decreasing the durability of concrete structures ,2. FreezBond performance is a key factor for steel bars and concrete working together, which allows longitudinal forces to transfer from steel bars to the surrounding concrete. Bond failure should be avoided in the design or repair of reinforced concrete structures ,19,20. IAt present, some studies ,27,28,29In addition, studies of the effects of stirrups on bond behavior between different types of bars and concrete were conducted by researchers ,39. The In this paper, the effect of freeze–thaw cycles on the bond behavior between steel bars and concrete confined with stirrups was experimentally investigated. The failure mode of pullout specimens, bond–slip curves, and concrete strengths were analyzed. Furthermore, the bond strength of steel bars in concrete confined with stirrups under freeze–thaw action was predicted based on the damage coefficient of the concrete. Finally, the bond–slip constitutive model was developed. The present research could be beneficial for the residual structural capacity and repair of reinforced concrete structure in severe cold regions.In this study, a total of ten group pullout specimens were prepared to investigate the bond properties considering the effects of concrete compressive strengths and freeze–thaw cycles. Every group consists of three specimens; thus, thirty pullout specimens were prepared. The details of the pullout specimens are shown in One HRB500 steel bar with a diameter of 12 mm was used as the main reinforcement in the center, and two HPB300 stirrups with a diameter of 6 mm were arranged to consider the influence of the stirrup constraint. The bonding length was set as four times of the diameter of the main reinforcement, and a PVC tube was embedded in the loading end to reduce the influence of the local stress on the bond. In addition, a total of sixty cubic specimens (100 mm × 100 mm × 100 mm) were cast to measure the compressive strength and splitting tensile strength, and six prism specimens (100 mm × 100 mm × 400 mm) were cast to measure the mass loss and relative dynamic elastic modulus .Two kinds of concrete with different concrete strength were adopted in this experiment. The mix proportions are shown in The mechanical properties of the two steel bars used in the specimen are shown in The specimens of the freeze–thaw test were cured at a temperature of 20 °C and 95% relative humidity. Then these specimens were immersed in water for 4 days before the freeze–thaw tests. A quick-freeze method was used according to the standard for test methods of long-term performance and durability of ordinary concrete (GB/T 50082-2009 ), as shoThe temperatures measured in the center of the concrete prism specimen (100 mm × 100 mm × 400 mm) ranged from −20 °C to 7 °C, and each freeze–thaw cycle took 3 h.Central pullout tests were carried out on bond specimens after the freeze–thaw test. Three displacement sensors were arranged at the free end to measure the displacement of concrete and main reinforcement, and a load sensor was arranged at the loading end to measure the bond force, as shown in F is the pullout force, d represents the diameter of the main reinforcement, and la is the anchorage length or the bonding length of the main reinforcement.The pullout tests were conducted by loading and displacement control. Before reaching the maximum bond force, the loading was controlled at a rate of 7.5 kN/min. When reaching the maximum bond force, the loading rate was controlled at a rate of 0.2 mm/min until the slip reached 15 mm. During the loading process, the load and displacement data were automatically collected and stored by a data acquisition system. The bond stress can be calculated as follows:The surface morphology of the specimen significantly changed after the freeze–thaw test, as shown in Pullout tests were conducted on bond specimens. It was found that the main reinforcements were pulled out for all specimens due to the confinement of stirrups located in concrete, and cracks were not found on the surface of concrete. The pullout failure mode is shown in Concrete compressive strength and splitting tensile strength after different freeze–thaw cycles are shown in N cycles of freeze–thaw damage could be expressed as follows:ft,0 is the splitting tensile strength before freeze–thaw, MPa; ft,N is the splitting tensile strength after N cycles of freeze–thaw, MPa; and k1 represents the coefficient of strength reduction, with k1 = 0.452 for C20 series and k1 = 0.426 for C40 series obtained by regression of the test data.Based on the linear regression of experimental data, the splitting tensile strength after The variation of bond strength with freeze–thaw cycles is shown in Previous studies ,59 have WN, is expressed as follows [W0 is the mass of specimens before the freeze–thaw test, WN is the mass of specimens after the N freeze–thaw test. The mass loss results are summarized in Mass loss and dynamic elastic modulus are important parameters to evaluate the damage level of concrete subjected to freeze–thaw cycles. The mass loss of concrete, Δ follows :(3)ΔWN=WThere will be a certain degree of damage in concrete under the action of freeze–thaw cycles, thus resulting in the changes of the dynamic elastic modulus . Figure DN, expressed by the relative dynamic elastic modulus [P0 is the dynamic elastic modulus before freeze–thaw cycles, GPa; and PN is the dynamic elastic modulus after N freeze–thaw cycles, GPa.On the basis of concrete damage mechanics, the damage coefficient,  modulus  was adopDN and N was established as follows:N is the number of freeze–thaw cycles; α and β are influence parameters, in which the value of α is 0.01 for two series of specimens, and the values of β for C20 and C40 concrete are 0.39 and 0.20, respectively.Based on the regression analysis of the experimental data, the relationship between For concrete specimens without stirrups, the bond strength decreased with freeze–thaw cycles. The bond strength after freeze–thaw action could be calculated by the splitting tensile strength or compressive strength of concrete ,19,20,21k is a constant and its value is 0.9; c is the concrete cover of the main steel bar; KsvN is the restraint enhancement factor of stirrups after freeze–thaw cycles; Asv is the section area of stirrups; and ssv is the spacing of transverse stirrups.Based on the existing bond strength calculation formula of ribbed steel bars in concrete confined with stirrups , the folKsvN is affected by the number of freeze–thaw cycles, but it is essentially related to the concrete damage induced by freeze–thaw action. The relationship between coefficient KsvN and DN was obtained by the analysis of experimental data, as shown in The restraint enhancement factor of stirrups The fitting function in this study is shown in Formula (7), with the correlation coefficient of 0.878.KsvN is equal to 20 when DN = 0, which is the same asthe coefficient value of ordinary concrete without freeze–thaw cycles. According to Formula (7), the bond strength after different freeze–thaw cycles can be calculated. Additionally, the calculated results and experimental bond strengths are listed in It can be found that Two series of bond–slip curves of specimens with different concrete strength are shown in s is the slip between reinforcement and concrete; su is the slip corresponding to the peak bond strength; and A and B are the parameters determined by test results. The value of parameter A could be obtained by nonlinear curve fitting; A = 0.4 was adopted in this study for all groups of specimens considering the suggested value of other literature [sr. The expressions of To analyze the mechanical properties of reinforced concrete structures under a freeze–thaw environment, it is necessary to use the bond–slip constitutive model between reinforcement and concrete. A two-stage model (including ascending stage and descending stage) was adopted, and the bond–slip relationship can be expressed by the following equations ,62:(8)y=terature ,64.Param010-2010 :(10)τr=τBased on the regression analysis of the test results, the value of B for C20 and C40 series was obtained as 0.58 and 0.22, respectively. The bond–slip constitutive model was established, and the predicted results are shown in Reinforced concrete structures in cold regions are usually subjected to freeze–thaw action, which leads to the deterioration of concrete and the decrease in concrete strength. Since bond performance is the basis for steel bars and concrete working together, the variation of the bond between steel bars and concrete under freeze–thaw action deserves attention. Previous research mainly focused on the bond performance of specimens without stirrups, and the influence of stirrups was not considered. Considering the restraint effect of stirrups on concrete during the process of concrete freeze–thaw damage and its influences on the bond strength and bond–slip curve, this paper has carried out relevant research work.Through the experimental phenomena of this paper, it was found that the pullout failure occurred for the bond specimens due to the restraint effect of stirrups. This failure mode is different from other studies in which splitting failure or splitting–pullout failure occurs for specimens without stirrups or with small concrete cover ,63. In tDN, as shown in Equation (4), is used as a variable to determine the restraint enhancement factor of stirrups KsvN expressed as Equation (7). Then the ultimate bond strength is determined using Formula (6). This formula can be used to evaluate the bond strength between ribbed bars and concrete with or without stirrups subject to freeze–thaw cycles. It is found from the present study that the constraint effect of stirrups mainly affects the descending stage of the bond–slip curve, which is significantly different from the steeper descending stage of the curve of the specimen without stirrups [The relative dynamic elastic modulus could reflect the damage degree of concrete subject to freeze–thaw action; therefore, the damage coefficient stirrups . Based oThis study has certain reference value for the evaluation of the mechanical performance of reinforced concrete structures under freeze–thaw action and also can help researchers to select the relevant parameters in the bond–slip constitutive model. There are several factors affecting the bond performance between steel bars and concrete, such as the steel bar diameter, bond strength, concrete cover, and stirrup ratio. Due to the limitation of the present study, only part of the research was carried out, and the maximum number of freeze–thaw cycles is set to 100. Therefore, further research should be carried out to investigate the influence of these factors on the bond performance, and the number of freeze–thaw cycles should be increased to obtain more comprehensive rules.(1)Due to the confinement effect of transverse stirrups, the generation of cracks was effectively prevented, and steel bar pullout failure was observed for all bond specimens in this study. This is different from the splitting–pullout failure mode of specimens without stirrups. The shape of the bond–slip curve was affected by stirrups in concrete and exhibited better ductility.(2)The internal pore structure of concrete was destroyed by freeze–thaw damage, which made the compressive strength and splitting tensile strength decrease to some extent. In this experiment, the compressive strength of C20 and C40 concrete after 100 freeze–thaw cycles decreased by 22.2% and 13.1%, respectively. Furthermore, the splitting tensile strength decreased by 46.5% and 40.8%, respectively. Freeze–thaw action had greater influence on the splitting tensile strength than compressive strength of concrete.(3)Transverse stirrups could effectively improve the bond performance between steel bars and concrete. Under the action of 100 freeze–thaw cycles, the bond strength did not decrease compared with that of nonfreeze–thaw specimens. However, the bond strength had a descending trend based on the experimental data analysis.(4)On the basis of the existing bond strength model for unfrozen concrete, the formula expressed by the damage coefficient was given for calculating the bond strength after freeze–thaw cycles considering the effects of concrete strength and stirrup confinement. The comparison between calculation and experiment shows that the formula used in this paper can effectively predict the bond strength confined with stirrups subject to freeze–thaw cycles.(5)The bond–slip constitutive model was developed for deformed steel bars. This model is applicable for specimens with or without stirrups under freeze–thaw action. The relevant parameter values were suggested by fitting the test curves. It was found that the model had good accuracy and could provide references for the calculation of reinforced concrete structures in cold regions.


IgG4-related disease and granulomatosis with polyangiitis share several features as well as the presence of ANCA antibodies and serum IgG4 immunoglobulins. It is often difficult to distinguish between two entities. We hereby report the case of a patient portraying the clinical conundrum with clinical and biological features of the two diseases. Granulomatosis with polyangiitis (GPA), previously known as Wegener's granulomatosis is an ANCA-associated vasculitis mainly involving the lungs and kidneys , 2. ThisIgG4-related disease (IgG4-RD) is an immune-mediated inflammatory disorder affecting several organs with a wide spectrum of clinical manifestations. The affected organs share several clinical and biological characteristics such as tumor-swelling like of organs, lymphoproliferative infiltration, and a certain extent of fibrosis described as “storiform fibrosis.” The pathological hallmark of IgG4-RD is lymphoplasmacytic infiltrates containing IgG4+ plasma cells of the affected tissues , 6. SeruBecause of several similar clinical signs and the presence of ANCA antibodies and serum IgG4 immunoglobulins, differentiating IgG4-RD from GPA is not always easy. Furthermore, increased serum concentration of IgG4 has been observed in GPA as well as the presence of infiltration of IgG4 positive cells in tissues in patients with GPA. Currently, the existence of an overlap between the two diseases is not clearly certified –12. We hN < 1.350). The abdominal CT image did not show retroperitoneal fibrosis despite the presence of bilateral uretero-hydronephrosis without objectified obstacle. A possible diagnosis of IgG4-related disease (IgG4-RD) was then carried out, but GPA diagnosis was not completely excluded. The patient was treated by intravenous methylprednisolone and rituximab with a good clinical and biological evolution. Three years later, he developed another relapse with distal digital ischemia of the foot, multiplex mononeuritis, and external popliteal sciatica deficit, rather in favour of GPA with a BVAS score of 6 (Birmingham Vasculitis Activity Score). Afterwards, the patient was treated only with mycophenolate mofetil (2 g/day) without any relapse.A 60-year-old patient was admitted to our hospital because of inflammatory syndrome, polyarthralgia, and weight loss. A physical examination showed only pain in the heels and the first metatarsophalangeal joint as well as hypoesthesia of the left foot. The significant biological results showed nonidentified c-ANCA (non-PR3 and non-MPO) with a titer of 1 : 2560 as well as a C-reactive protein of 99 mg/L, and an erythrocyte sedimentation rate of 67 mm/h. The renal function was in the normal range values. The thoracic computed tomography (CT) scan showed several bilateral nonspecific micronodules , and theGPA and IgG4-RD are today two better known diseases. GPA is an ANCA-associated vasculitis that can be defined by the 1990 ACR criteria and the 2012 Chapel Hill Consensus Conference. Recently, an Iranian team proposed a new algorithm called 2017 ACR/EMA Revised Criteria for Very Early Diagnosis of GPA .IgG4-RD diagnosis can be based on the CDC according to the presence of organ involvement, the presence of IgG4/IgG ratio >40% abd the presence of high power fieds immunostaining for IgG4 more than 10. The diagnosis can be established as either possible, probable or definite . RecentlCurrently, the existence of an overlap between the two diseases is not clearly certified. Some authors believe that this association is possible and represent as such a particular phenotype. Organ involvement occurring in AAV patients could be related to IgG4-RD rather than to refractory granulomatous lesions, especially in GPA patients . In thisOn the other hand, there is even a case report of GPA mimicking IgG4-RD . It is iT follicular helper cells that have increased in both diseases [The association of GPA and IgG4-RD as a potential overlap syndrome with common pathophysiological mechanisms responsible for clinical and biological manifestations is therefore probable. However, both diseases have complex and still yet undeciphered pathological pathways. The link between the pathological role of ANCA and IgG4 in purporting damage in both diseases is still unknown. Certain lines of evidence underscore the role of diseases .Our patient illustrates the difficulty to differentiate between these two diseases. In fact, the patient presented the characteristics of the two diseases. The presence of c-ANCA with pulmonary micronodules, pansinusitis, multiplex mononeuritis, and a decrease in ANCA with treatment is in favour of GPA. In 2009, the diagnosis was made following the consensus methodology for the classification of ANCA-associated vasculitis despite the presence of nonidentified c-ANCA . HoweverThis case illustrates well the possible coexistence of characteristics of ANCA vasculitis and IgG4-RD, as well as the difficulty to differentiate between the two diseases and above all, to affirm the presence of an overlap syndrome.


The objective of this paper is to provide a comprehensive study about the performance of concrete using mixed coarse recycled aggregate (MCRA) as an alternative for natural aggregate (NA) at replacement levels of 0, 30, 60, and 100%, which can greatly reduce the environmental pollution by incorporating the construction and demolition wastes in the reproduction of concrete. The focus of this study was to use the raw MCRA that was directly obtained from a recycling plant and not further processed. Initially, MCRA was studied to ascertain if its property meets the recommended Indian standards for natural aggregates. Using the slump test, the workability of freshly prepared concrete with a characteristic strength of 30 MPa was assessed. Additionally, the mechanical performance of concrete was assessed on the specimens prepared in the different forms: cubes, cylinders, and beams. Moreover, Scanning Electron Microscopy (SEM) with EDAX, XRD, and FTIR were used to study the microstructural behavior of selected optimum and control mixes at 7 and 28 days of curing. The studies revealed that a higher MCRA content improved the workability of concrete and 30% replacement of MCRA improved the compressive strength by 11.01, 6.98, 6.19, and 14.24% at 7, 28, 56, and 90 days respectively. At the same time, the 30% replacement of the MCRA mix showed an improved split tensile and flexural strength by 2.92 and 6.26%, respectively. The microstructural analysis showed that the optimum mixture had a more condensed microstructure. Therefore, 30% replacement of MCRA can be incorporated in the characteristic strength of concrete of 30 MPa. In particular, MCRA incorporation had a positive influence similar to conventional concrete on the physical, mechanical, and microstructural properties, which can increase the utilization of all kinds of directly obtained construction and demolition wastes to increase the circular economy in the construction sector. Concrete is a human-made substance that is the most widely used material on the planet. At the same time, unfortunately, it represents a source of concern when it comes to environmental degradation. It is of maximum importance to investigate the materials used to manufacture concrete, as well as their broader environmental impact. It is expected that global annual construction waste could reach 2.2 billion tons by 2025 as reported by transparency market research. Based on the report of the building materials and technology promotion council , India pThe crushed C&DW particles are mainly composed of concrete, mortar, bricks, glass, and wood pieces and can be used as mixed coarse recycled aggregate (MCRA) ,8,9. The2 curing [The inclusion of MCRA at 25 and 50% replacement causes no consequential changes in the 28-day strength with respect to the standard mix. The tensile strength of concrete with 25 and 50% substitution of MCRA diminishes with 3 and 10%, progressively, in succession to the control mix . This en2 curing , carbona2 curing , acid tr2 curing , heating2 curing , heating2 curing , and the2 curing ,28,29,302 curing .The main objective of this research is to advance the adaptation of new types of aggregate in the form of a mixed coarse recycled aggregate fraction of building and demolition debris. Advancing research on recycled aggregate concrete, recycled aggregate collected from the C&DW recycling facility is used to produce recycled aggregate that has resulted in demolition waste utilization more broadly in the construction sector. However, examination of such recycled aggregate from the C&DW reprocessing plants is still required for the mechanical characteristics and microstructural behavior of concrete. The previous study’s hindrance has been overcome using mixed recycled aggregate, and the mechanical properties and microstructural characterization have been investigated deeply at a curing period of 7 and 28 days.The experimental study incorporated concrete with a varied percentage of recycled aggregates at 0, 30, 60, and 100 to determine the effect of recycled aggregate concrete at low, moderate, and high volumes. In this research, the mechanical properties of mixed recycled aggregate concrete such as compressive, flexure, and split tensile strength were investigated. Furthermore, nondestructive parameters of selected concrete series were evaluated in terms of the ultrasonic pulse velocity and rebound hammer. The morphology and cement hydration products of the optimum and control mix were studied using Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (SEM-EDAX), X-ray Diffraction (XRD), and Fourier Transform Infrared Radiation (FT-IR).In this current research, mixed coarse recycled aggregate was used as an alternative to conventional aggregate, which can increase the incorporation of all kinds of construction and demolition waste in concrete production. The natural aggregates utilized locally from Chennai, India and mixed recycled aggregates were sourced from the C&DW Recycling Plant at Jeedimetla in Telangana, India. The manufactured sand with a size less than 4.75 mm that belongs to Zone I as per IS383:2016 was used in this research. During the production of the reprocessed aggregates, the unsettled substances were discarded first from C&DWs and, thereafter, the construction waste was crushed by a jaw crusher and separated according to their sizes. The recycled aggregates involved in this study contained all forms of construction and demolition wastes except steel and floating materials. The coarse mixed recycled aggregates of 20 mm and 12 mm were mixed at a percentage of 60% and 40%, respectively, to enhance the properties of recycled aggregate concrete with better packing. Ordinary portland cement (53 grade) manufactured by Zuari, meeting IS 12269:2013 requirements, along with tap water was used for the experimental process. The superplasticizer (SP) with trading name AURAMIX 200 was used with a solid content of 30–35% having a specific gravity 1.08, which has a 20% water reduction rate. The amount of SP was found on the basis of workability requirements. The coarse recycled material used in this study is shown in The physical properties of the aggregates obtained from the construction and demolition recycling plant at Jeedimetla were studied and the results are shown in The particle size distributions of aggregates were determined using a sieve analysis test as per IS 383:2016. 3 and a water–cement ratio of 0.42 as per IS 456:2000. The mixes studied were prepared using a 45 L capacity laboratory vertical shaft mixer. All the dry ingredients were loaded one by one and dry-mixed for a duration of 120 s, and then water was added while the mixer was running; simultaneously, the superplasticizers were added to improve the workability. The total mixing time was 240 s, which satisfied the minimum requirement as per IS 456:2000. Finally, the samples were produced and cured by following IS 456:2000.Four mixes were composed to explain the concrete in the fresh state, the hardened properties, and the microstructural behavior of concrete. The specimens were prepared in the different combinations: control mix with 100% NA; concrete with 30% MCRA (M1); concrete with 60% MCRA (M2); concrete with 100% MCRA (M3). The proportion of the mixes was designed using IS 10262:2019 shown in 3 for concrete that has different replacements of RA. This finding denotes that the tiles, mosaic, granite, and other components present in RA do not compromise the density of freshly prepared concrete. A similar study reported that the compressive strength of 25 MPa concrete showed a fresh density of 2416 and 2331.01 kg/m3 for ordinary concrete and 50% replacement of mixed recycled aggregate concrete (MRAC), respectively. The previous studies [3 for conventional and 2.28 Mg/m3 for 100% replacement of MRAC. Thus, it was found that the fresh concrete replaced with recycled aggregate has suitable properties for application of concrete.Fresh concrete properties, namely slump and density, were determined as specified in IS 456:2000. All the mixes were planned to have a retention slump value of one hour by fixing the dosage of superplasticizer (SP) ARAMIX 200 at 0.4% in the amount of binder. The variation in slump is shown in 3 for the mix having NA and MRAC. In comparison with the control mix, the dry density of 30, 60, and 100% replacements of recycled aggregates decreases by 2.83, 2.78, and 1.6% respectively. This decrease in density is closer to the previous study by [3 for the control and 50% replaced MRAC, respectively. This indicates that there was a 3.5% reduction in apparent dry density of MRAC while comparing with conventional concrete. The results of the current study show that the decrease in dry density of MRAC is less than the results obtained in previous studies.The hardened density values shown in study by , which r2/min. The differences in strength compared to the control mix are shown in The bending and split tensile strength tests were carried out without applying any shock, and the load was gradually increased at a nominal rate between 1.2 and 2.4 N/mmIn the present study, nondestructive testing of concrete was assessed as per IS 516 (part 5): 2018. The morphological characteristics of concrete mixtures were determined on the powder sample of a broken cube for both 7 and 28 days of curing. The TESCAN VEGA3 instrument manufactured from Brno, Czech Republic is used for scanning electron microscopy testing. All the absorbed water in the specimen was removed by hydration stoppage using the oven-drying method at 100 °C for a duration of 10 min. From The interfacial zone B, which The energy-dispersive X-ray spectroscopy shows the high content of major peaks of Ca, Si, and O, which indicates the presence of calcium silicate hydrates (CSH) in hardened concrete. The high calcium content shown in The diffractogram was obtained using CuKα radiation (30 mA and 45 kV), scanning between 10.0100 and 89.1500 (°2Th.), as shown in 2 (Q)—PDF Number: 46-1045; Ca(OH)2 (P)—PDF Number: 44-1481; CaCO3 (Ca)—PDF Number: 83-0577), as shown in 3, Ca(OH)2, and Al2O3·3H2O are observed at 26.7163°, 28.0422°, 34.1573°, and 18.1007°, respectively, in the optimum mix. Similarly, the amount of CSH, CaCO3, Ca (OH)2, and Al2O3·3H2O are observed at 26.6157°, 27.9707°, 34.0779°, and 18.0160°, respectively, in the control mix. Likewise, similar results were found by [3, and Ca(OH)2 compounds at 29.406°, 27.233°, and 34.102°, respectively. The higher counts of CSH in the optimum mix indicates that the strength improvement is higher than that of the control mix, as shown in The concrete specimen’s X-ray Diffraction (XRD) patterns after seven days of curing are displayed in found by  with the2 is observed at 18° and 34°, which is similar to the observation reported by [The optimum and control mix’s XRD patterns after 28 days of curing are shown in orted by . It is aorted by . The peaorted by . Overall−1. The replacement of 30% MCRA shifts the Si-O-Si absorption peak toward a higher wavenumber of 978 cm−1 in comparison to the control mix. This shift in wavenumber indicates that the silicon phase in the recycled aggregate changes the Ca:Si ratio in CSH. This could be the reason for the increased compressive strength with the addition of 30% MCRA. The peak at 3643 cm−1 for both mixtures indicates the presence of portlandite (Ca(OH)2), which is revealed by FT-IR spectroscopy. This peak is likely to subside during the period of the exposure, as shown in −1 and 3407 cm−1 for the optimum mix indicate that the O-H group is contributed by CSH, but in the control mix, the O-H group is contributed only at 1739 cm−1. The strong vibration bands at 977 cm−1 and 963 cm−1 for the optimum and control mix, respectively, signify the antisymmetric stretching associated with the Si-O group provided by CSH. The bands at 1379 cm−1 in the control mix and 1400 cm−1 in the optimum mix correspond to the antisymmetric stretching of CO32−. The peak at 1157 and 1206 cm−1 associated with SO42− is detected in the control and optimum mix, respectively, which corresponds to the findings by previous research [−1 of wavelength because of the v3 vibration in SO42−. In the current study, there is no sign of AlO6 at 850 cm−1, which further reduces the chances of the deterioration of concrete.The peaks of bands in the FTIR spectrum at 7 days were identified based on the observation by . The banresearch  where th−1 for the optimum and control mix, respectively, where it was observed between 900 and 1100 cm−1 in the study conducted by previous researchers. Most likely, the small peaks between 600 and 800 cm−1 are brought on by Si-O-Si bonds that come from the original features of the MCRA. It is observed that the intense band at 970 cm−1 is due to the Si-O asymmetric stretching vibration of the CSH. The vibration bands obtained at 1649 cm−1 and 3432 cm−1 for the control mix and 1683 cm−1 and 3436 cm−1 for the optimum mix represent the antisymmetric stretching associated with the OH- group generated by portlandites. The bands of carbonates (CO32−), CSH, and free silica (O-Si-O) are found to be less than the wavelength of 2000 cm−1. The presence of the CO32− band at 1365 cm−1 for the control mix and 1372 cm−1 for the optimum mix are found to be approximately similar to each other. The existence of absorption bands between 2960 and 2850 cm−1 that increases the compressive strength of concrete is a sign that stearic acid is present [The peaks of bands in the FTIR spectrum for both the optimum and control mix at 28 days of hydration are shown in  present . The conBased on the research findings, the mixed coarse recycled aggregates at 30% replacement can be utilized as an alternative to conventional aggregate to produce recycled aggregate concrete for structural applications. This research can increase the waste utilization in the form of coarse recycled aggregates. Further, the methods for enhancing the mechanical properties can be achieved by the addition of supplementary cementitious materials or various treatment methods, thus contributing to better performance and greater sustainability in construction. This will facilitate the wider use of mixed coarse recycled aggregate in the production of structural concrete as follows.Coarse recycled aggregate satisfied the physical parameters specified in IS 383:2016 for the production of concrete.The incorporation of coarse recycled aggregates in concrete showed a slump value around 75 ± 20 mm.The fresh concrete properties of density with 100% recycled aggregate concrete slightly decreased at a percentage of 2.33%. This behavior was the same for the concrete in fresh and hardened stages.The concrete with 30% replacement of MCRA showed increases of 11.01, 6.98, 6.19, and 14.23% at 7, 28, 56, and 90 days, respectively, in comparison with the control mix. Similarly, concrete with 30% replacement of MCRA showed improved split tensile and flexural strengths by about 2.92 and 6.26%, respectively.The ultrasonic pulse velocity (UPV) was observed as 4495 m/s for 30% of MCRA, which is recommended as excellent by IS 516 (Part 5/sec1): 2018.At 28 days, concrete with 30% incorporation of MCRA and the control mix had rebound numbers of 32 and 36, respectively.Scanning Electron Microscopy (SEM) investigations revealed a denser microstructure of recycled aggregate concrete at 30% replacement.The mineralogical characterization by X-ray diffraction revealed that the phases found in the recycled aggregates were calcium silicate hydrate, quartz, portlandite, and calcite in the required intensity.−1 changed to a higher frequency 970 cm−1 for the optimum mix as hydration advanced.Due to silicate polymerization and the development of calcium silicate hydrate gel, the primary peak at 817 cm


Wireless sensing-based human-vehicle recognition (WiHVR) methods have become a hot spot for research due to its non-invasiveness and cost-effective advantages. However, existing WiHVR methods shows limited performance and slow execution time on human-vehicle classification task. To address this issue, a lightweight wireless sensing attention-based deep learning model (LW-WADL) is proposed, which consists of a CBAM module and several depthwise separable convolution blocks in series. LW-WADL takes raw channel state information (CSI) as input, and extracts the advanced features of CSI by jointly using depthwise separable convolution and convolutional block attention mechanism (CBAM). Experimental results show that the proposed model achieves 96.26% accuracy on the constructed CSI-based dataset, and the model size is only 5.89% of the state of the art (SOTA) model. The results demonstrate that the proposed model achieves better performance on WiHVR tasks while reducing the model size compared to SOTA model. INTELLIGENT Traffic Systems (ITS) is an important part of smart city , providiWith the rapid development of artificial intelligence and deep learning techniques, image-based HVR methods  have beeGenerally, the purpose of wireless sensing-based HVR (WiHVR) methods is to extract the energy information of surrounding wireless signals for target recognition. Since the propagation of wireless signals has no directionality, the WiHVR method does not have the problem with the above-mentioned viewing angle . In recevia empirical mode decomposition. They decomposed CSI signals into intrinsic mode functions (IMF) and extracted the time domain and frequency domain features from IMF components.However, the above-mentioned WiHVR methods based on extracted RSS or CSI signatures from 2.4 GHz wireless transceivers like Bluetooth, ZigBee, and WiFi have the following drawbacks:1)RSS is a coarse-grained signal, which leads to limited accuracy of HVR tasks based on RSS signals.2)The effects of CSI or RSS on the performance of WiHVR in different application scenarios are not explored.Recently, deep learning techniques  consistiTo address the above-mentioned issues, this paper presents a novel WiHVR method based on the designed lightweight wireless sensing attention-based deep learning model (LW-WADL). Inspired by the recent-emerged convolutional block attention mechanism  (CBAM) aTo summarize, the main contributions of this paper are as follows:1)This paper proposes a CSI data enhancement method, which preprocess the change trend of CSI data to one direction, thereby enhancing CSI data.2)This paper provides a subcarrier selection method, which selects several subcarriers with large signal-to-noise ratios (SNR) as benchmarks and integrates them into a new CSI data.3)This paper has proposed a lightweight wireless sensing attention-based deep learning model, and attempts to explore the effects of CSI on the performance of WiHVR in different application scenarios.The remainder of this paper is organized as follows. Section “2. Preliminaries” introduces the CSI extraction and the theoretical analysis of WiHVR. Section “3. Proposed method” elaborates the proposed LW-WADL for WiHVR. Section “4. Experiment study” shows experimental results and analysis. Section “5. Conclusion and future work” gives the conclusions and future work.This paper aims to establish a lightweight and efficient WiHVR method to explore the effects of CSI on the performance of WiHVR in different application scenarios. The system architecture of the proposed WiHVR method is shown in From This paper uses the designed WTP to extract CSI data related to road users. CSI represents the fine-grained channel features of wireless communication links between transmitters and receivers based on orthogonal frequency division multiplexing (OFDM) technology. Besides, CSI describes the changes of phase and amplitude caused by multipath effect and transmission loss in wireless signal transmission. The CSI channel gain matrix is expressed as:hmn represents the different subcarriers. m and nrepresent the transmitting and receiving antennas, respectively. Each sub-element hmn represents:where hmn|| is the amplitude of the sub-carrier hmn, and jeηmn represent the phase of hmn. From Eqs 1, 2, it can be known that CSI is not a supersession of all subcarrier signals, it describes a multipath signal with more characteristics. In this case, the CSI extracted by WTP contains multiple subcarrier information. These subcarriers have different sensitivities to road users, so it is necessary to filter out the subcarriers with lower sensitivity. The specific method will be elaborated in Section “3. Proposed method.”where ||The specific process of CSI signal extraction is shown in d, is given by the Friis free space equation,The idea of WiHVR is based on the fact that road users of existence and movement affect the wireless propagation paths. To understand the relation of road users movement with received CSI, the wireless propagation model should be first studied. In a typical wireless environment, there is one main path line-of-sight (LOS) and several reflected paths by the surroundings. As shown in Pr and Pt are the receiving and transmitting power, respectively. Gr and Gt are the receiving and transmitting antenna gains, respectively. λ is the wavelength in meters. d is the distance between the transmitter and receiver in meters, that is, the propagation path length. When a road user exists in the wireless environment, several scattered paths are produced by road user. Those scattered power should also be added in the final received power.where Pr is almost stable. However, along with the move of a road user, the scattered paths change in a fast speed, resulting in the variance in received signal power.where δ is a brief representation of path length caused by road user. If a road user is static in the environment, According to Eq. 4, the differences in size and speed of road users lead to different attenuation of wireless signals. Hence, the CSI readings measured by the WTP prototype are various.According to the above analysis, since the differences in the size and speed of humans or vehicles moving on the road, the attributes of energy attenuation caused by two targets are various. In this case, it is feasible to design a WiHVR method. To this end, a deep learning-based WiHVR method is proposed in purpose of analyzing the effects of CSI on the performance of WiHVR in different application scenarios.C-class vector (C is the number of categories) is output through the Softmax function.The overview of the proposed WiHVR based on a lightweight wireless sensing attention-based deep learning model (LW-WADL) is shown in As shown in x[n](n > 0) represents the n-th CSI reading. xstatic[n] is the average of CSI readings when there are no road users in the wireless environment, namely, CSI baseline. Tobject is the decision threshold to determine whether there is a road user (dBm). Here, Tobject is set to 4 dBm in this work. W is the size of the judgment window, and is set to 50 when the sampling rate is 50 Hz. Xectiondet is the object detection result. “Detected” indicates that there are road users in the range of interest, and otherwise “Static” denotes no road users.where xstatic. Thus, to improve the performance of the above-mentioned fluctuation detection algorithm, an adaptive baseline adjustment method is proposed, which can be calculated by:Moreover, the environmental factors such as rain, fog, temperature, etc., can affect the CSI baseline β is a correction factor with a value of 0.96 in this paper. It can be seen from Eq. 6 that the CSI baseline will be updated as long as there are no road users in the wireless environment, otherwise it will not be updated. Hence, the problem of CSI baseline drift caused by environmental factors can be solved efficiently, as well as the robustness of the fluctuation detection algorithm can be improved.where Finally, the CSI data extracted by WTP contains 52 subcarriers, and each subcarrier contains amplitude and phase information. In order to improve execution efficiency of LW-WADL, this paper converts the raw two-dimensional CSI data containing amplitude information into one-dimensional data. Then, one-dimensional CSI data containing road user behavior information will be sent to the second stage for data preprocessing.The CSI preprocessing module includes the following four steps: CSI filtering, CSI augmentation, CSI subcarriers selection, and CSI segmentation.To guarantee the robustness of road users recognition, smoothing filtering is used to remove noise from the raw CSI data, as defined by:Xfilter(n) is the average processed data and then the filter shift window size used is N, where is set to five. The raw CSI waveform vs. filtered waveform is shown in where Xbase of a set of CSI data needs to be calculated, which can be expressed as:Channel state information augmentation aims to find a way to enhance the CSI features without changing the raw CSI features. According to the characteristics of the raw CSI signal waveform, this paper proposes a novel CSI data enhancement method. This method first calculates the average value of a set of CSI amplitude, and then takes the absolute value of the CSI amplitude which is smaller than the average value. In this way, the decay of the CSI amplitude is amplified, thereby enhancing CSI features. First, the baseline i represents the i-th CSI subcarrier, n represents the n-th sampling point of the i-th subcarrier. I represents the number of CSI subcarriers, which is 52 in this paper. T is the number of sampling points of a group of CSI data. The enhanced CSI dataXcsi_aug can be obtained according to the CSI baseline Xcsi_base :where where | | denotes the absolute value operation. According to the Eqs 8, 9, the enhanced CSI data can be obtained.Although CSI augmentation have enhanced CSI features related to road users. In practical applications, different subcarriers of CSI have different sensitivities to road users, e.g., some subcarriers fluctuate greatly when encountering road users, while other subcarriers fluctuate less. Therefore, to further enhance CSI data, we design a raw CSI subcarrier selection method to remove subcarriers with low sensitivity in CSI data. In order to evaluate the sensitivity of CSI subcarriers, this paper calculates the SNR of the CSI data amplitude, as expressed by:xpeak is the peak value of CSI with respect to a road user. xstatic is the average of CSI readings when there are no road users within a wireless environment. nnoise is the peak value of noise. According to Eq. 10, the SNR Xcsi_SNR(n) of all subcarriers in a set of CSI data is obtained:where xSNR(m) represents the SNR value of the m-th subcarrier. For the convenience of calculation, it is assumed that xSNR(n)has been arranged in descending order of SNR, that is, {xSNR(1) > xSNR(2) > … > xSNR(m) > … > xSNR(n)}. According to Eq. 11, “m” subcarriers with larger SNR are selected, where “m” is defined as the CSI factor. The selection of the CSI factor “m” is discussed in detail in Section “4. Experiment study.” The mean of “m” subcarriers is calculated, which can be expressed as:where To demonstrate the validity of Eq. 12, we compare our proposed method with k-subcarriers weight fusion  and averxd[i] represents the i-th decision point, xd[i] can be calculated as:The selected CSI data xd[i] is the minimize value within the value range of L is the number of decision points. w is the size of sliding window, and is set to 50, s is the step size of the window, and is set to 200. Additionally, the index of decision points in Pi . According to Eq. 13 and Pi, L segments. i-th segment, which can be defined as:where c0 is the slicing factor, and is set to 100. In this case, a new CSI dataset is developed. About 500 samples of four categories are included in the dataset: pedestrian, bicycle, motorcycle, and car.where According to the features of CSI signals containing time series features, as shown in The overall network structure of the proposed LW-WADL is presented in The attention mechanism makes the model tend to pay attention to some information about the auxiliary classification in the feature map, while suppressing other useless information, thereby improving the classification ability of the model. The CBAM module consists of a channel attention module and a spatial attention module. The detailed structure is shown in The channel attention module first performs maxpooling and average pooling based on the height and width of the DSCB_1 feature map to obtain two one-dimensional vectors. Then, it is input into the shared multi-layer perceptron (Shared MLP), and the corresponding elements of the output features of the MLP are summed point by point. The result is input into the Sigmoid activation function, and then the inner product operation is performed with the initial input feature map. The final output feature map is used as the input of the spatial attention module.The spatial attention module performs maxpooling and average pooling based on the channel, and then uses the convolution (abbreviated as Conv) operation to merge the output features on the channel dimension. The merged features are input into a sigmoid activation function, then an inner product operation is performed on the obtained output features and the input of the spatial attention module. Finally, the output of the inner product operation is combined with the output of the DSCB_1 module to form the input features of the DSCB_2 module.WiHVR is fundamentally a multi-classification task, so we choose the Softmax function to produce final classification results. Through the Softmax function, the output values of classifier can be converted into a probability distribution in the range .The cross-entropy loss function is implemented as the training objective function for LW-WADL:i, otherwise yi represents the output of the LW-WADL model, the probability that the class is i. Lloss is a loss measure of the difference between two probability distributions.where As can be seen from The performance of the designed LW-WADL is evaluated by three typical metrics such as “Accuracy,” “Recall,” and “Precision.” For the computational complexity analysis of deep learning methods, two well-known computational indicators, the network parameters (abbreviated as param.) and floating-point operations (FLOPs) are employed. Specifically, “Accuracy” is the ratio of all correct predictions to the whole number of predictions. “Precision” is the ratio of correct predictions with positive values to total predictions with positive values. “Recall” is the ratio of predicted positives to the total number of actual positives. They are defined as:TP denotes the number of true positive samples classified as positive. FP denotes the number of true negative samples classified as positive. FN denotes the number of true positive samples classified as negative. TN denotes the number of true negative samples classified as negative.where To verify the effectiveness of our LW-WADL for WiHVR, we adopt the developed CSI four-category dataset, so as to compare the performance of various deep learning models on WiHVRs tasks. From A set of experiments are designed to investigate the effect of CSI factor “m” on the accuracy of WiHVR. As shown in To verify the performance of the proposed CSI subcarrier selection method, we conduct comparative experiments on the CSI four-category dataset. Recently-merged CSI subcarrier selection methods such as k-subcarrier weight fusion  and averAs shown in To explore the performance of CSI signals on different classification tasks, three groups of experiments are set up, namely two-classification tasks, three-classification tasks, and four-classification tasks. Each group of experiments selects four methods to test, FCN, DeepWiTraffic, ResNet, and our LW-WADL, respectively, so that the results are more credible. The experimental results are shown in The results of To further display the recognition accuracy for each class of road users, This paper has proposed a lightweight wireless sensing attention-based deep learning model (LW-WADL). In order to evaluate the classification ability of LW-WADL, three CSI-based datasets are established, namely two-category dataset, three-category dataset. and four-category dataset. The experimental results on the developed dataset show that the classification accuracy of LW-WADL decreases with the increase of road user categories, but it is higher than 96%. In addition, this paper provides a novel CSI subcarrier selection method, which calculates the SNR of all subcarriers and selects the first four subcarriers with larger SNR for fusion. Besides, a new CSI data enhancement method is exploited to preprocess the change trend of CSI data to one direction, thereby enhancing CSI data.In future, the performance of other advanced deep learning-based WiHVR methods will be investigated. It is also significant to explore the human-vehicle recognition task based on multiple sets of WTPs. Additionally, it is meaningful to explore the applications of the proposed methods in real scenarios such as multi-lane roads.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.MS was responsible for the writing of the manuscript and some experiments. RZ was responsible for some experiments of the manuscript. XC was responsible for the data collection and processing of the manuscript. CZ was responsible for the revision of the manuscript. LL provided the fund support for this project. All authors contributed to the article and approved the submitted version.


Streptococcaceae, Enterobacteriaceae and Enterococcaceae families in antibiotic users increased almost 50%, 70% and 200%, respectively, while yogurt consumption also increased relative abundances of Streptococcaceae and Enterococcaceae, but not Enterobacteriaceae. Alpha diversity analyses suggested that the microbiome of the antibiotic usage and yogurt consumption groups exhibited an alpha diversity lower than that of the control. LEfSe analysis showed that, at the family level, the number of biomarkers in the yogurt consumption and antibiotic usage group were respectively 5 and 7, lower than that of the control (13). This study demonstrated the importance in considering the potential assistance of yogurt consumption on ARG gene transfer from commensal bacteria to pathogens in the human gut, which may pose a risk for human health. Antibiotic usage and yogurt consumption share more identical changes on healthy human gut flora than disparities. Therefore, in order to understand the potential risks of antibiotic usage and yogurt consumption on antibiotic resistance transmission in human gut microbiota, further research needs to be undertaken.Antibiotic usage and yogurt consumption are the major interventions for gut microbiota, yet their shared characteristics and disparities in healthy human gut microbiome remain unclear. This study aimed to decipher the composition changes among healthy humans, comparing antibiotic usage and yogurt consumption. The relative bacterial abundances of 1113 fecal samples were collected from an ongoing, population-based longitudinal cohort study in China that covered lifestyle, diet, disease status and physical measurements, and biological indicators of participants were obtained by the sequencing of 16S rRNA. The samples were divided into three groups, which were antibiotic users (122), yogurt consumers (497) and controls (494), where data visualization, alpha diversity, beta diversity and LEfSe analysis were conducted. At the family level, the relative abundances of  Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota [Bacteroides, Clostridium, Faecalibacterium, Eubacterium, Ruminococcus, Peptococcus, Peptostreptococcus, and Bifidobacterium are the dominant genera that are found to inhabit the human gut [The human gut microbiota comprises the microorganisms that live in the human gut, including bacteria, archaea, fungi, and viruses, from which bacteria are dominant . The funmonadota . Bacterouman gut . The comuman gut . It has uman gut ,6.Lactobacillus species might help prevent antibiotic-associated diarrhea [Antibiotic resistance is a global concern. Some bacteria in the gut are naturally resistant to certain antibiotics, while other commensal bacteria may acquire resistance genes from fellow resistant bacteria through horizontal gene transfer (HGT), including conjugation, transduction and transformation . The humdiarrhea .Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus bacteria, yogurt consumption is gradually increasing around the world. However, although yogurt consumption is good for human health, as reported [Diet may influence gut resistome in healthy humans. Researchers found that subjects with a diverse, fiber-rich diet had a lower abundance of ARGs in their gut, through changing the composition of gut microbiota to harbor more antibiotic resistance genes . As a foreported , does thThe average age of the three groups ranged from 48.0 to 54.7 years, with a slightly higher proportion of women than men. The yogurt group had higher levels of education and lower rates of smoking than the other two groups. Other basic characteristics, such as body mass index (BMI), waist circumference (WC), physical activity (PA), and total energy were presented as means in Bacteroidetes phyla in feces from the antibiotic usage and yogurt group were both lower than those of the control group, with the yogurt group being the lowest among them. The relative abundances of Actinobacteria and Proteobacteria phyla showed opposite results while comparing with the control group, with Actinobacteria higher in the yogurt group, Proteobacteria higher in the antibiotic group, and control in the middle. At the order level, the relative abundances of Bacillales order in the antibiotic usage group increased notably. Both antibiotic and yogurt brought about observable increases in Lactobacillales order . Principal coordinates analysis (PCoA) was performed to visualize the beta diversity based on the PERMANOVA statistic method in the microbial community structure, where antibiotic usage and yogurt consumption groups were shown in the Bray–Curtis Index analysis .After operational taxonomic units (OTUs) were obtained and analyzed using QIIME 2 work flow, alpha and beta diversity analyses were carried out. Chao1, Shannon, Simpson and observed indexes were calculated to evaluate the alpha diversity in the human gut microbiome. The microbiomes of the antibiotic usage and yogurt consumption groups exhibited a lower alpha diversity than that of the control A. There Proteobacteria was the biomarker of the antibiotic usage group, and Actinobacteria the yogurt consumption group, where they were all four times higher than those in the control group. At Order level, Enterobacteriales, Lactobacillales, and Actinomycetales in the antibiotic usage group were three times higher than those in the control group. At family level, the number of biomarkers in the yogurt consumption and antibiotic usage group were respectively 5 and 7, lower than that of the control (13), as shown in In this study, we carried out the linear discriminant analysis (LDA) effect size  to investigate the differences in different taxa levels between groups using the Microbiome Analyst online platform ,17. At pSelf-use of antibiotics in healthy humans is becoming a health concern, especially in low-income groups of people. Although clinical use of antibiotics has been proved to reduce diversity in the gut microbiome , the sitBoth the antibiotic usage and yogurt consumption groups exhibited a decrease in the richness and evenness of diversity compared with the control group. The insignificant result of the Simpson index showed that the dominance indices of gut flora remained stable in a large scale of healthy human gut microbiome. Alpha analysis indicated that antibiotic usage and yogurt consumption were making significant changes in healthy human gut microbiome. However, the overall diversity of the microbiome among these groups was not obvious enough, possibly due to attenuation of the potential effects on the physiology of the host organisms. This may also possibly be due to the limitation of the sample sets, and the deviation caused by other variables such as age, smoking state, and the evolutionary outcomes that keep getting the human gut microbiome back to a stable state should also be considered.Lactobacillus delbrueckii subspecies bulgaricus and Streptococcus salivarius subspecies thermophiles, Lactobacilli or Bifidobacteria [Bacteroidetes phyla in feces from the antibiotic usage and yogurt groups were both lower than those of the control group, with the yogurt group being the lowest among them. It is consistent with Odamaki’s reports that the consumption of yogurt containing Bifidobacterium longum BB536 significantly decreases enterotoxigenic Bacteroides fragilis in the gut microbiota [Yogurt is produced by adding a combination of probiotics to ferment milk, which are mostly bacteria . The lacbacteria ,20. In ocrobiota .Bifidobacterium lactis and other probiotics are considered to help maintain gut flora by providing organisms that are usually inhabited in the human gut [Streptococcaceae, Enterobacteriaceae and Enterococcaceae, which are closely correlated with AMR, increased almost 50%, 70% and 200% in the antibiotic usage group, as expected. It has been suggested that probiotic supplementation may decrease the total load of ARGs within the gut [Streptococcaceae and Enterococcaceae family, the same as antibiotic usage group. Therefore, it is not negligible that we should consider the potentiality of yogurt consumption on bacterial ecosystems that will potentially increase the stress and/or selection pressure and, therefore, could induce an intensification of ARG gene transfer processes from commensal bacteria to pathogens in the human gut, posing a possible risk for human health.Yogurt consumption was reported to be good for human health, and is especially deemed beneficial to the human gut . Yogurtsuman gut . Howeveruman gut . However the gut ,25. HoweThrough LEfSe analysis, we can see that the number of biomarkers in the yogurt consumption and antibiotic usage group was much lower than that of control. This probably means that the yogurt consumption and antibiotic usage decreased gut micobiome diversity in healthy human. Antibiotic usage was more influential than yogurt consumption on healthy human gut microbiome. However, antibiotic usage and yogurt consumption do share more identical changes in healthy human gut microbiome than disparities. Therefore, in order to reduce the health and AMR transmitting risk, functional research based on an in-depth study from a meta-interactomics perspective and the use of advanced computing equipment under different metabolic states needs to be carried out to decipher the correlation between antibiotic usage and yogurt consumption on human gut microbiota.The present study was based on data from the China Health and Nutrition Survey (CHNS), an ongoing, population-based longitudinal cohort in China that covers lifestyle, diet and disease status, physical measurements and biological indicators. A total of 15 provinces/megacities in China participated. An overview of the CHNS study design has been published previously . During Adult participants collected stool samples themselves after receiving adequate instruction for the collection process during a home visit prior to collection, and samples were frozed immediately at −20 °C. Stool samples were transported within 48 h by cold chain to the central laboratory and stored at −20 °C to ensure proper processing.The methods for DNA extraction, amplification and sequencing have been described previously . A bead-The V3-V4 region of 16s rRNA gene with a 6-bp barcode unique to each sample was amplified with primers 515F/806R (5′-GTGCCAGCMGCCGCGGTAA-3′/5′-GGACTACHVGGGTWTCTAAT-3′) to characterize the taxonomic profile of gut microbiota. In an equimolar ratio, PCR products were combined. An Illumina HiSeq PE-250 platform was used to sequence the libraries, constructed with TruSeq DNA PCR-Free Library Preparation Kit . p-value was assessed as significant when <0.05. The comparisons between groups were analyzed using parametric  or non-parametric tests ; a An analysis of the 16S rRNA gene sequences was performed using the QIIME 2 bioinformatics pipeline . The filStreptococcaceae, Enterococcaceae and so on) in healthy human gut microbiomes in this study. Antibiotic usage and yogurt consumption shared more identical changes in healthy human gut microbiome than disparities, especially ARG gene related bacteria groups that could induce an intensification of ARG gene transfer processes from commensal bacteria to pathogens in human gut. However, in order to understand the potential risks of antibiotic usage and yogurt consumption on antibiotic resistance transmission in human gut microbiota, further researches need to be carried out.Antibiotic usage and yogurt consumption demonstrated significant changes in specific bacterial groups (