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Defects can induce drastic changes of the electronic properties of two-dimensional transition metal dichalcogenides and influence their applications. It is still a great challenge to characterize small defects and correlate their structures with properties. Here, we show that tip-enhanced Raman spectroscopy (TERS) can obtain distinctly different Raman features of edge defects in atomically thin MoS 2 , which allows us to probe their unique electronic properties and identify defect types (e.g., armchair and zigzag edges) in ambient. We observed an edge-induced Raman peak (396 cm −1 ) activated by the double resonance Raman scattering (DRRS) process and revealed electron–phonon interaction in edges. We further visualize the edge-induced band bending region by using this DRRS peak and electronic transition region using the electron density-sensitive Raman peak at 406 cm −1 . The power of TERS demonstrated in MoS 2 can also be extended to other 2D materials, which may guide the defect engineering for desired properties. Probing inevitable defects in two- dimensional materials is challenging. Here, the authors tackle this issue by using tip-enhanced Raman spectroscopy (TERS) to obtain distinctly different Raman features of edge defects in atomically thin MoS 2 , and further probe their unique electronic properties as well as identify the armchair and zigzag edges.

Surface plasmons (SPs) of metals enable the tight focusing and strong absorption of light to realize an efficient utilization of photons at nanoscale. In particular, the SP-generated hot carriers have emerged as a promising way to efficiently drive photochemical and photoelectric processes under moderate conditions. In situ measuring of the transport process and spatial distribution of hot carriers in real space is crucial to efficiently capture the hot carriers. Here, we use electrochemical tip-enhanced Raman spectroscopy (EC-TERS) to in situ monitor an SP-driven decarboxylation and resolve the spatial distribution of hot carriers with a nanometer spatial resolution. The transport distance of about 20 nm for the reactive hot carriers is obtained from the TERS imaging result. The hot carriers with a higher energy have a shorter transport distance. These conclusions can be guides for the design and arrangement of reactants and devices to efficiently make use of plasmonic hot carriers. Revealing the spatial distribution of hot carriers in real space is crucial to their efficient utilization. Here, the authors show that in-situ electrochemical tip-enhanced Raman spectroscopy is able to resolve the spatial distribution of reactive hot carriers with a nanometer spatial resolution.

For daily syndromic surveillance to be effective, an efficient and sensible algorithm would be expected to detect aberrations in influenza illness, and alert public health workers prior to any impending epidemic. This detection or alert surely contains uncertainty, and thus should be evaluated with a proper probabilistic measure. However, traditional monitoring mechanisms simply provide a binary alert, failing to adequately address this uncertainty. Based on the Bayesian posterior probability of influenza-like illness (ILI) visits, the intensity of outbreak can be directly assessed. The numbers of daily emergency room ILI visits at five community hospitals in Taipei City during 2006-2007 were collected and fitted with a Bayesian hierarchical model containing meteorological factors such as temperature and vapor pressure, spatial interaction with conditional autoregressive structure, weekend and holiday effects, seasonality factors, and previous ILI visits. The proposed algorithm recommends an alert for action if the posterior probability is larger than 70%. External data from January to February of 2008 were retained for validation. The decision rule detects successfully the peak in the validation period. When comparing the posterior probability evaluation with the modified Cusum method, results show that the proposed method is able to detect the signals 1-2 days prior to the rise of ILI visits. This Bayesian hierarchical model not only constitutes a dynamic surveillance system but also constructs a stochastic evaluation of the need to call for alert. The monitoring mechanism provides earlier detection as well as a complementary tool for current surveillance programs.

Radiotherapy is a leading treatment intervention for cancer and has been shown to improve the prognosis of patients with malignant tumors. However, there are several side effects associated with radiotherapy that require attention. The present case study describes the case of a patient who underwent breast-conserving surgery after receiving a diagnosis of right-sided breast cancer, following which they received conventional radiation therapy. A skin nodule was found on the right side of the breast 3 years later, which was pathologically confirmed to be a highly differentiated skin squamous cell carcinoma after surgical local excision. The patient presented with poor skin healing 2 months after the operation, and a myocutaneous flap of the descending branches of the thoracodorsal vessels was used to repair the defect and improve the breast shape. Although skin cancer induced by radiotherapy is relatively rare, physicians should remain cautious when treating skin injuries after radiotherapy, and recovery should be closely monitored. For patients with skin nodules after radiotherapy, a biopsy should be performed as early as possible to clarify the diagnosis and to develop appropriate treatment programs. For such skin cancer patients who have received radiotherapy in the past, it is necessary to consider the potential radiotherapy-related skin injuries they may have suffered after previous radiotherapy, the skin flap should be comprehensively evaluated before the operation and an appropriate surgical method should be selected to reduce the necessity of a second operation.

Plasmon-enhanced Raman spectroscopy (PERS), including surface-enhanced Raman spectroscopy, shell-isolated nanoparticle-enhanced Raman spectroscopy and tip-enhanced Raman spectroscopy, has witnessed substantial development over the past 20 years. These techniques can provide fingerprint information on target materials with sensitivities down to the single-molecule level and with sufficient spatial resolution to observe individual vibrational modes. PERS has thus found applications in diverse areas, ranging from bioanalysis to materials characterization. In this Technical Review, we survey the fundamental principles, advantages and limitations of using localized surface plasmon resonance to enhance the Raman signal in PERS. We discuss the issues that influence the sensitivity and interpretation of PERS results and provide an overview of state-of-the-art PERS applications in materials characterization, bioanalysis and the study of surfaces and interfaces. We also troubleshoot common experimental issues, largely based on our own experience. Finally, we conclude by examining future directions and issues to be addressed for the further development of PERS techniques.Plasmon-enhanced Raman spectroscopy (PERS) is a highly sensitive technique that can provide molecular fingerprint information. This Technical Review discusses the fundamental principles, advantages and limitations of PERS, key issues in using PERS and interpreting results, and state-of-the-art applications in materials characterization, bioanalysis and the study of surfaces.

After over 15 years of development, tip-enhanced Raman spectroscopy (TERS) is now facing a very important stage in its history. TERS offers high detection sensitivity down to single molecules and a high spatial resolution down to sub-nanometers, which make it an unprecedented nanoscale analytical technique offering molecular fingerprint information. The tip is the core element in TERS, as it is the only source through which to support the enhancement effect and provide the high spatial resolution. However, TERS suffers and will continue to suffer from the limited availability of TERS tips with a high enhancement, good stability, and high reproducibility. This review focuses on the tip-related issues in TERS. We first discuss the parameters that influence the enhancement and spatial resolution of TERS and the possibility to optimize the performance of a TERS system via an in-depth understanding of the enhancement mechanism. We then analyze the methods that have been developed for producing TERS tips, including vacuum-based deposition, electrochemical etching, electrodeposition, electroless deposition, and microfabrication, with discussion on the advantages and weaknesses of some important methods. We also tackle the issue of lifetime and protection protocols of TERS tips which are very important for the stability of a tip. Last, some fundamental problems and challenges are proposed, which should be addressed before this promising nanoscale characterization tool can exert its full potential. Graphical Abstract ᅟ

Defects can induce drastic changes of the electronic properties of two-dimensional transition metal dichalcogenides and influence their applications. It is still a great challenge to characterize small defects and correlate their structures with properties. Here, we show that tip-enhanced Raman spectroscopy (TERS) can obtain distinctly different Raman features of edge defects in atomically thin MoS , which allows us to probe their unique electronic properties and identify defect types (e.g., armchair and zigzag edges) in ambient. We observed an edge-induced Raman peak (396 cm ) activated by the double resonance Raman scattering (DRRS) process and revealed electron-phonon interaction in edges. We further visualize the edge-induced band bending region by using this DRRS peak and electronic transition region using the electron density-sensitive Raman peak at 406 cm . The power of TERS demonstrated in MoS can also be extended to other 2D materials, which may guide the defect engineering for desired properties.

For daily syndromic surveillance to be effective, an efficient and sensible algorithm would be expected to detect aberrations in influenza illness, and alert public health workers prior to any impending epidemic. This detection or alert surely contains uncertainty, and thus should be evaluated with a proper probabilistic measure. However, traditional monitoring mechanisms simply provide a binary alert, failing to adequately address this uncertainty. Based on the Bayesian posterior probability of influenza-like illness (ILI) visits, the intensity of outbreak can be directly assessed. The numbers of daily emergency room ILI visits at five community hospitals in Taipei City during 2006-2007 were collected and fitted with a Bayesian hierarchical model containing meteorological factors such as temperature and vapor pressure, spatial interaction with conditional autoregressive structure, weekend and holiday effects, seasonality factors, and previous ILI visits. The proposed algorithm recommends an alert for action if the posterior probability is larger than 70%. External data from January to February of 2008 were retained for validation. The decision rule detects successfully the peak in the validation period. When comparing the posterior probability evaluation with the modified Cusum method, results show that the proposed method is able to detect the signals 1-2 days prior to the rise of ILI visits. This Bayesian hierarchical model not only constitutes a dynamic surveillance system but also constructs a stochastic evaluation of the need to call for alert. The monitoring mechanism provides earlier detection as well as a complementary tool for current surveillance programs.

For daily syndromic surveillance to be effective, an efficient and sensible algorithm would be expected to detect aberrations in influenza illness, and alert public health workers prior to any impending epidemic. This detection or alert surely contains uncertainty, and thus should be evaluated with a proper probabilistic measure. However, traditional monitoring mechanisms simply provide a binary alert, failing to adequately address this uncertainty. Based on the Bayesian posterior probability of influenza-like illness (ILI) visits, the intensity of outbreak can be directly assessed. The numbers of daily emergency room ILI visits at five community hospitals in Taipei City during 2006-2007 were collected and fitted with a Bayesian hierarchical model containing meteorological factors such as temperature and vapor pressure, spatial interaction with conditional autoregressive structure, weekend and holiday effects, seasonality factors, and previous ILI visits. The proposed algorithm recommends an alert for action if the posterior probability is larger than 70%. External data from January to February of 2008 were retained for validation. The decision rule detects successfully the peak in the validation period. When comparing the posterior probability evaluation with the modified Cusum method, results show that the proposed method is able to detect the signals 1-2 days prior to the rise of ILI visits. This Bayesian hierarchical model not only constitutes a dynamic surveillance system but also constructs a stochastic evaluation of the need to call for alert. The monitoring mechanism provides earlier detection as well as a complementary tool for current surveillance programs.