Probing light dark sector at future lepton colliders via (dark) Higgs invisible decays

A renormalizable UV model for Axion-Like Particles (ALPs) or hidden photons, that may explain the dark matter usually involves a dark Higgs field which is a singlet under the standard model (SM) gauge group. The dark sector can couple to the SM particles via the portal coupling between the SM-like Higgs and dark Higgs fields. Through this coupling, the dark sector particles can be produced in either the early universe or the collider experiments. Interestingly, not only the SM-like Higgs boson can decay into the light dark bosons, but also a light dark Higgs boson may be produced and decay into the dark bosons in a collider. In this paper, we perform the first collider search for invisible decays by taking both the Higgs bosons into account. We use a multivariate technique to best discriminate the signal from the background. We find that a large parameter region can be probed at the International Linear Collider (ILC) operating at the center-of-mass energy of 250 GeV. In particular, even when the SM-like Higgs invisible decay is a few orders of magnitude below the planned sensitivity reach of the ILC, the scenario can be probed by the invisible decay of the dark Higgs boson produced via a similar diagram. Measuring the dark Higgs boson decay into the dark sector will be a smoking gun signal of the light dark sector. A similar search of the dark sector would be expected in, e.g., Cool Copper Collider (C$^3$), Circular Electron Positron Collider (CEPC), Compact Linear Collider (CLIC) and Future Circular electron-positron Collider (FCC-ee).Comment: 40 pages, 8 figure

Targeting SARS-CoV2 Spike Protein Receptor Binding Domain by Therapeutic Antibodies

The Authors As the number of people infected with the newly identified 2019 novel coronavirus (SARS-CoV2) is continuously increasing every day, development of potential therapeutic platforms is vital. Based on the comparatively high similarity of receptor-binding domain (RBD) in SARS-CoV2 and SARS-CoV, it seems crucial to assay the cross-reactivity of anti-SARS-CoV monoclonal antibodies (mAbs) with SARS-CoV2 spike (S)-protein. Indeed, developing mAbs targeting SARS-CoV2 S-protein RBD could show novel applications for rapid and sensitive development of potential epitope-specific vaccines (ESV). Herein, we present an overview on the discovery of new CoV followed by some explanation on the SARS-CoV2 S-protein RBD site. Furthermore, we surveyed the novel therapeutic mAbs for targeting S-protein RBD such as S230, 80R, F26G18, F26G19, CR3014, CR3022, M396, and S230.15. Afterwards, the mechanism of interaction of RBD and different mAbs were explained and it was suggested that one of the SARS-CoV-specific human mAbs, namely CR3022, could show the highest binding affinity with SARS-CoV2 S-protein RBD. Finally, some ongoing challenges and future prospects for rapid and sensitive advancement of therapeutic mAbs targeting S-protein RBD were discussed. In conclusion, it may be proposed that this review may pave the way for recognition of RBD and different mAbs to develop potential therapeutic ESV

Core–shell inorganic NP@MOF nanostructures for targeted drug delivery and multimodal imaging-guided combination tumor treatment

It is well known that metal–organic framework (MOF) nanostructures have unique characteristics such as high porosity, large surface areas and adjustable functionalities, so they are ideal candidates for developing drug delivery systems (DDSs) as well as theranostic platforms in cancer treatment. Despite the large number of MOF nanostructures that have been discovered, conventional MOF-derived nanosystems only have a single biofunctional MOF source with poor colloidal stability. Accordingly, developing core–shell MOF nanostructures with good colloidal stability is a useful method for generating efficient drug delivery, multimodal imaging and synergistic therapeutic systems. The preparation of core–shell MOF nanostructures has been done with a variety of materials, but inorganic nanoparticles (NPs) are highly effective for drug delivery and imaging-guided tumor treatment. Herein, we aimed to overview the synthesis of core–shell inorganic NP@MOF nanostructures followed by the application of core–shell MOFs derived from magnetic, quantum dots (QDs), gold (Au), and gadolinium (Gd) NPs in drug delivery and imaging-guided tumor treatment. Afterward, we surveyed different factors affecting prolonged drug delivery and cancer therapy, cellular uptake, biocompatibility, biodegradability, and enhanced permeation and retention (EPR) effect of core–shell MOFs. Last but not least, we discussed the challenges and the prospects of the field. We envision this article may hold great promise in providing valuable insights regarding the application of hybrid nanostructures as promising and potential candidates for multimodal imaging-guided combination cancer therapy.</p

Indoor air quality and health in schools: a critical review for developing the roadmap for the future school environment

Several research studies have ranked indoor pollution among the top environmental risks to public health in recent years. Good indoor air quality is an essential component of a healthy indoor environment and significantly affects human health and well-being. Poor air quality in such environments may cause respiratory disease for millions of pupils around the globe and, in the current pandemic-dominated era, require ever more urgent actions to tackle the burden of its impacts. The poor indoor quality in such environments could result from poor management, operation, maintenance, and cleaning. Pupils are a different segment of the population from adults in many ways, and they are more exposed to the poor indoor environment: They breathe in more air per unit weight and are more sensitive to heat/cold and moisture. Thus, their vulnerability is higher than adults, and poor conditions may affect proper development. However, a healthy learning environment can reduce the absence rate, improves test scores, and enhances pupil/teacher learning/teaching productivity. In this article, we analyzed recent literature on indoor air quality and health in schools, with the primary focus on ventilation, thermal comfort, productivity, and exposure risk. This study conducts a comprehensive review to summarizes the existing knowledge to highlight the latest research and solutions and proposes a roadmap for the future school environment. In conclusion, we summarize the critical limitations of the existing studies, reveal insights for future research directions, and propose a roadmap for further improvements in school air quality. More parameters and specific data should be obtained from in-site measurements to get a more in-depth understanding at contaminant characteristics. Meanwhile, site-specific strategies for different school locations, such as proximity to transportation routes and industrial areas, should be developed to suit the characteristics of schools in different regions. The socio-economic consequences of health and performance effects on children in classrooms should be considered. There is a great need for more comprehensive studies with larger sample sizes to study on environmental health exposure, student performance, and indoor satisfaction. More complex mitigation measures should be evaluated by considering energy efficiency, IAQ and health effects

Exploring the interaction of quercetin-3-O-sophoroside with SARS-CoV-2 main proteins by theoretical studies: A probable prelude to control some variants of coronavirus including Delta

The aim of this study was to investigate the mechanism of interaction between quercetin-3-O-sophoroside and different SARS-CoV-2’s proteins which can bring some useful details about the control of different variants of coronavirus including the recent case, Delta. The chemical structure of the quercetin-3-O-sophoroside was first optimized. Docking studies were performed by CoV disease-2019 (COVID-19) Docking Server. Afterwards, the molecular dynamic study was done using High Throughput Molecular Dynamics (HTMD) tool. The results showed a remarkable stability of the quercetin-3-O-sophoroside based on the calculated parameters. Docking outcomes revealed that the highest affinity of quercetin-3-O-sophoroside was related to the RdRp with RNA. Molecular dynamic studies showed that the target E protein tends to be destabilized in the presence of quercetin-3-O-sophoroside. Based on these results, quercetin-3-O-sophoroside can show promising inhibitory effects on the binding site of the different receptors and may be considered as effective inhibitor of the entry and proliferation of the SARS-CoV-2 and its different variants. Finally, it should be noted, although this paper does not directly deal with the exploring the interaction of main proteins of SARS-CoV-2 Delta variant with quercetin-3-O-sophoroside, at the time of writing, no direct theoretical investigation was reported on the interaction of ligands with the main proteins of Delta variant. Therefore, the present data may provide useful information for designing some theoretical studies in the future for studying the control of SARS-CoV-2 variants due to possible structural similarity between proteins of different variants

Search for lepton-flavor-violating ALPs at a future muon collider and utilization of polarization-induced effects

Axion-Like Particles (ALPs) are pseudo Nambu-Goldstone bosons associated with spontaneously broken global $U(1)$ symmetries. Such particles can have lepton-flavor-violating (LFV) couplings to the SM charged leptons. LFV ALPs provide the possibility to address some of the SM long-lasting problems. We investigate the sensitivity of a future muon collider suggested by the Muon Accelerator Program (MAP) to the production of LFV ALPs in the ALP mass range $m_a\leq1$ MeV. ALPs are assumed to be produced through the LFV decay \tau\ra\ell a ($\ell=e,\mu$) of one of the tau leptons produced in the muon-anti muon annihilation. Performing a realistic detector simulation and deploying a multivariate technique, we constrain the LFV couplings $c_{\tau e}$ and $c_{\tau \mu}$ for both the cases of unpolarized and polarized muon beams. Three different chiral structures are considered for the LFV ALP coupling and the muon collider is assumed to operate at the center-of-mass energies of 126, 350 and 1500 GeV. We present a procedure to search for LFV ALPs at colliders which takes advantage of tau polarization-induced effects. Polarized tau leptons which produce such effects can be produced when the initial muon beams are polarized. Utilizing the properties of polarized tau decays, the main SM background which overwhelms the ALP production in the case of unpolarized muon beams can be significantly suppressed. We present 95$\%$ CL expected limits on the LFV couplings and show that the present analysis can improve current experimental limits on the ALP LFV couplings by roughly one order of magnitude.Comment: 31 pages, 11 figure

Modeling of ternary mixture of VOCs in photocatalytic oxidation reactor for indoor air quality application

Photocatalytic oxidation (PCO) is an innovative method of removing volatile organic compounds (VOCs) from indoor air. PCO technology employs a semiconductor (such as TiO2) and ultraviolet light to decompose VOCs via successive oxidation processes and creates CO2 and H2O as the ultimate products of complete mineralization. The greatest drawback of this technology is, however, the production of hazardous by-products. The possible health risk posed by hazardous by-products inhibits the commercial adoption of PCO-based air purifiers in the indoor environment. Modeling is a powerful tool to address the chemical interaction and mass transfer phenomenon in the PCO reactor. This study presents the modeling of a ternary mixture of VOCs and generated by-products using a proposed degradation reaction pathway. A one-dimensional mathematical model by considering the axially dispersed plug flow and Langmuir-Hinshelwood (L-H) based reaction rate as well as linear source spherical emission model (LSSE) for the irradiation distribution on the media surface were used for modeling of VOCs and by-products. Three VOCs from different chemical groups (aldehyde, ketone, aromatic groups) were chosen as challenge compounds, and a commercial PCO filter (TiO2 coated on silica fiber felts) was considered as a photocatalyst. The model prediction was performed at different levels of concentration (0.1–1 ppm), relative humidity (15–70%), air velocity (0.016–0.1 m/s), and light intensity (7–23W/m2). Among generated by-products, aldehydes were the major by-products of VOCs in the PCO reactor. It was revealed that increasing concentration and irradiation, as well as decreasing relative humidity and velocity, increases by-product generation

Modeling and Evaluating the Scalability of Instruction Fetching in Superscalar Processors

Scalability is important in superscalar processors design. A superscalar processor is said to be linearly scalable if with linear increase in load or demand, performance remains constant relative to linear increase in resources. In this paper, for evaluating the instruction fetching scalability, an analytical model of a superscalar processor is proposed by defining the fetch unit as the “producer ” of instructions and the execution unit as the “consumer.” The scalability of the fetch unit relative to its branch predictor – the Bi-Mode Predictor – is then evaluated using SPEC2000 suite of benchmarks. Our simulation results strongly suggest that reducing branch misprediction penalty is a better alternative solution – compared with increasing prediction accuracy – for improving instruction fetch scalability. 1. Summary and future work In this paper, we composed an analytical model for evaluating instruction fetching scalability relative to branch prediction accuracy. For this purpose, we decoupled the fetch and execution engines using the model proposed in [1] and assumed the instruction cache to be totally perfect and based the fetch engine performance only on branch prediction accuracy. We defined the performance of the fetch unit as the number of instructions it produces in each cycle based on the prediction it makes for control instructions. However, this performance is dependent on the execution unit which informs the fetch unit of the resolved outcomes of branch instructions and keeps it on the correct execution path. To assess the scalability of the fetch unit, we proposed an analytical fetching model and developed formulas for measuring the fetch performance. Our formulas dictated two factors are necessary for evaluating the fetch engine performance