Data-driven aggregate thermal dynamic model for buildings: a regression approach

The thermal inertia of buildings brings considerable flexibility to the building heating and cooling loads, which is believed to be a promising demand response resource in energy systems. However, it is challenging to utilize the thermal inertia of buildings in the operation of energy systems because of the complicated thermal dynamics and high computational cost. This paper proposes a data-driven aggregate thermal dynamic model (ATDM) for the multi-zone building and building cluster, respectively, which offers an equivalent and low-complexity building model for the operation and control of energy systems. The ATDM consists of the aggregation equation and the state equation. The former projects the detailed real states of buildings into the characteristic state (i.e., aggregate state) using an affine function, and the latter describes the thermal dynamics of buildings using the aggregate state. The ATDM is formulated for two practical load control strategies for the building cluster, including direct load control and indirect load control. Then, the constrained nonlinear regression model is proposed to estimate the model parameters and occupant behavior, for which an efficient algorithm based on the block coordinate descent method is developed by exploiting the decomposable structure of the regression model. Simulation results based on real-world data show that the root mean square error and mean absolute percentage error for the multi-zone building (or building cluster) are below 0.72 °C and 1.44% (or 0.32°C and 1.39%), respectively, verifying the effectiveness of the proposed methods

All-optical controllable electromagnetically induced transparency in coupled silica microbottle cavities

An all-optical control scheme of electromagnetically induced transparency (EIT) based on two coupled silica microbottle cavities coated with iron oxide nanoparticles is proposed and experimentally demonstrated. The specially designed and fabricated silica microbottle cavity with a short and spherical end, which is coated with iron oxide nanoparticles, possesses a quality (Q) factor of 1.39×108 and large all-optical tunability in a range of 282.32 GHz (2.25 nm) arising from the strong photothermal effect of the nanoparticles. Based on two coupled silica microbottle cavities, we achieve the EIT spectrum with a transparency window bandwidth of 2.3 MHz. The transparency window can be flexibly controlled by tuning the resonant frequency of the higher-Q microcavity. Besides, by tuning the resonant frequencies of the two microcavities separately, the whole EIT spectrum can be shifted with a range of 71.52 GHz, to the best of our knowledge, for the first time. Based on this scheme, we have realized all-optical and independent control of the transparency window and the whole EIT spectrum. We believe this work has great potential in applications such as light storage, optical sensing, and quantum optics

Backscattering-Induced Chiral Absorption in Optical Microresonators

Chirality in micro- and nanophotonic structures is crucial for both fundamental research and applied technology. Here, we experimentally demonstrate chiral absorption via backscattering in a single whispering-gallery microresonator under simultaneous excitation from both ports. Remarkably, this scheme does not rely on any nonlinear effects or the breaking of parity or time-reversal symmetry. These intriguing phenomena occur due to the interference between the clockwise- and counterclockwise-propagating light fields induced by the backscattering. Furthermore, we also achieve the chiral optical states in a coupled-microresonator system, which can be utilized to manipulate the electromagnetically induced transparency or absorption effect. Our work proposes a linear and all-optical scheme to realize chiral optical states, which can help control the light flow in photonic systems with a high operation rate

Self‐Healable Multifunctional Fibers via Thermal Drawing

Abstract The development of soft electronics and soft fiber devices has significantly advanced flexible and wearable technology. However, they still face the risk of damage when exposed to sharp objects in real‐life applications. Taking inspiration from nature, self‐healable materials that can restore their physical properties after external damage offer a solution to this problem. Nevertheless, large‐scale production of self‐healable fibers is currently constrained. To address this limitation, this study leverages the thermal drawing technique to create elastic and stretchable self‐healable thermoplastic polyurethane (STPU) fibers, enabling cost‐effective mass production of such functional fibers. Furthermore, despite substantial research into the mechanisms of self‐healable materials, quantifying their healing speed and time poses a persistent challenge. Thus, transmission spectra are employed as a monitoring tool to observe the real‐time self‐healing process, facilitating an in‐depth investigation into the healing kinetics and efficiency. The versatility of the fabricated self‐healable fiber extends to its ability to be doped with a wide range of functional materials, including dye molecules and magnetic microparticles, which enables modular assembly to develop distributed strain sensors and soft actuators. These achievements highlight the potential applications of self‐healable fibers that seamlessly integrate with daily lives and open up new possibilities in various industries

Phytotoxic Compounds Isolated from Leaves of the Invasive Weed <i>Xanthium spinosum</i>

The aim of this study was to identify bioactive compounds from leaves of the invasive plant Xanthium spinosum and assess their phytotoxic activity. Activity-guided fractionation led to the isolation of 6 bioactive compounds: xanthatin (1), 1&#945;,5&#945;-epoxyxanthatin (2), 4-epiisoxanthanol (3), 4-epixanthanol (4), loliolide (5) and dehydrovomifoliol (6). Of them, compounds 2&#8315;6 were isolated from the X. spinosum for the first time. The structures of 1&#8315;6 were elucidated on the basis of extensive NMR studies and ESI-MS measurements as well as comparison with literature data. All of compounds were evaluated for their phytotoxic activity. Among them, compounds 1&#8315;4 exhibited stronger activity on 2 receiver plants compared with the other 2 compounds, with xanthatin (1) being the most potent compound, which suppressed root growth of the dicot plant Amaranthus retroflexus by 32.5%, 39.4%, 84.7% when treated xanthatin (1) at 5, 20, and 100 &#181;g/mL, while for the monocot plant, root growth was inhibited by 14.7%, 28.0%, and 40.0%, respectively. Seedling growth was nearly completely inhibited when the concentration of xanthanolides increased to 500 &#181;g/mL, whereas there was still some seedling growth when loliolide (5) and dehydrovomifoliol (6) were applied at the same concentration. Dehydrovomifoliol (6) did not negatively affect seedling growth of P. annua at all tested concentrations, and root length was still 42.0% of the control when the highest concentration 500 &#181;g/mL was used. This is the first report of the phytotoxicity of 1&#945;,5&#945;-epoxyxanthatin (2), 4-epiisxanthanol (3) and 4-epixanthanol (4). These compounds have the potential to be utilized as natural herbicides, especially 4-epiisoxanthanol (3), which exhibited significant selective activity between the dicot and monocot plants. On the other hand, whether these bioactive substances serve as allelochemicals to facilitate the invasion success of X. spinosum needs to be further studied

A novel cardiovirus in wild rats

Abstract Background Cardioviruses cause severe illnesses in rodents and humans. In recent years, novel cardioviruses have been frequently found, which promoted further studies of the genetic diversity of cardioviruses. Using viral metagenomics, we genetically characterized a novel cardiovirus (named SX1) from wild rat feces. The genomic structure of SX1 shared similar features with those of the Theiler’s murine encephalomyelitis viruses, including a leader protein, four structural proteins and seven non-structural proteins. Phylogenetic analysis based on both structural proteins and non-structural proteins coding regions showed that SX1 was formed into a separate branch, being located between the branches of Theiler’s murine encephalomyelitis viruses and Thera viruses. Variable resides presented in the Ser/Thr rich domain of L protein, VP1 loops, and VP2 puffs distinguished SX1 from Theiler’s murine encephalomyelitis viruses, suggesting the different antigenicity and pathogenicity of SX1

Interlocking-governed ultra-strong and highly conductive MXene fibers through fluidics-assisted thermal drawing

High-performance MXene fibers are always of significant interest for flexible textile-based devices. However, achieving high mechanical property and electrical conductivity remains challenging due to the uncontrolled loose microstructures of MXene (Ti3 C2 Tx and Ti3 CNTx ) nanosheets. Herein, high-performance MXene fibers directly obtained through fluidics-assisted thermal drawing are demonstrated. Tablet interlocks are formed at the interface layer between the outer cyclic olefin copolymer and inner MXene nanosheets due to the thermal drawing induced stresses, resulting in thousands of meters long macroscopic compact MXene fibers with ultra-high tensile strength, toughness, and outstanding electrical conductivity. Further, large-scale woven textiles constructed by these fibers offer exceptional electromagnetic interference shielding performance with excellent durability and stability. Such an effective and sustainable approach can be applied to produce functional fibers for applications in both daily life and aerospace.Agency for Science, Technology and Research (A*STAR)Ministry of Education (MOE)Nanyang Technological UniversityThis work was supported by the Singapore Ministry of Education Academic Research Fund Tier 2 (MOE2019-T2-2-127 and MOE-T2EP50120-0002), the Singapore Ministry of Education Academic Research Fund Tier1 (RG62/22), A*STAR under AME IRG (A2083c0062), and A*STAR under IAF-ICP Programme I2001E0067 and the Schaeffler Hub for Advanced Research at NTU. This work was supported by the IDMxS (Institute for Digital Molecular Analytics and Science) by the Singapore Ministry of Education under the Research Centres of Excellence scheme. This work was also supported by the NTU-PSL Joint Lab collaboration. This work was partly supported by the National Science Fund for Distinguished Young Scholars (52125302), the National Key Research and Development Program of China (2021YFA0715703), the National Natural Science Foundation of China (NSFC) (52203078, 22075009), the National Postdoctoral Program for Innovative Talents (BX2021025), and the Postdoctoral Science Foun-dation (2021M690005)