Artificial Intelligence, CEO Turnover, and Directional Change in Firm Innovation

We examine the role of artificial intelligence (AI) in facilitating a change in innovation directions after a leadership change. Using patent data for firms that have gone through a CEO turnover, we find that firms with greater AI investment are more successful in changing their innovation directions. The effect of AI is driven principally by the continued development of innovation in areas that are modestly different from the past. Further analyses show that this effect is likely due to firms with AI investment that can enable strategic change in cultivating culture of exploring frontiers in innovation and managing R&D. A new CEO can direct more resources to the acquisition of employees with greater technological capabilities such as AI skills to facilitate the innovation change. Overall, our study sheds light on the value of AI in fostering the change in innovation directions during uncertain and turbulent times

Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing

Large language models (LLMs) have made impressive progress in natural language processing. These models rely on proper human instructions (or prompts) to generate suitable responses. However, the potential of LLMs are not fully harnessed by commonly-used prompting methods: many human-in-the-loop algorithms employ ad-hoc procedures for prompt selection; while auto prompt generation approaches are essentially searching all possible prompts randomly and inefficiently. We propose Evoke, an automatic prompt refinement framework. In Evoke, there are two instances of a same LLM: one as a reviewer (LLM-Reviewer), it scores the current prompt; the other as an author (LLM-Author), it edits the prompt by considering the edit history and the reviewer's feedback. Such an author-reviewer feedback loop ensures that the prompt is refined in each iteration. We further aggregate a data selection approach to Evoke, where only the hard samples are exposed to the LLM. The hard samples are more important because the LLM can develop deeper understanding of the tasks out of them, while the model may already know how to solve the easier cases. Experimental results show that Evoke significantly outperforms existing methods. For instance, in the challenging task of logical fallacy detection, Evoke scores above 80, while all other baseline methods struggle to reach 20

Should Steroid Therapy Be Necessarily Needed for Autoimmune Pancreatitis Patients with Lesion Resected due to Misdiagnosed or Suspected Malignancy?

To explore whether steroid therapy should be needed for autoimmune pancreatitis patients after operation, eight AIP patients receiving operation were enrolled in this study from January 2007 to July 2013. All patients underwent liver function, CA19-9, and contrast-enhanced CT and/or MRI. Tests of IgG and IgG4 were performed in some patients. Tests of serum TB/DB, γ-GT, and γ-globulin were undergone during the perioperative period. Six cases receiving resection were pathologically confirmed as AIP patients and two were confirmed by intraoperative biopsy. For seven patients, TB/DB level was transiently elevated 1 day or 4 days after operation but dropped below preoperative levels or to normal levels 7 days after operation, and serum γ-GT level presented a downward trend. Serum γ-globulin level exhibited a downward trend among six AIP patients after resection, while an upward trend was found in another two AIP patients receiving internal drainage. Steroid therapy was not given to all six AIP patients until two of them showed new lines of evidence of residual or extrapancreatic AIP lesion after operation, while another two cases without resection received steroid medication. Steroid therapy might not be recommended unless there are new lines of evidence of residual extrapancreatic AIP lesions after resection

Observation of oscillatory relaxation in the Sn-terminated surface of epitaxial rock-salt SnSe {111}\{111\} topological crystalline insulator

Topological crystalline insulators have been recently predicted and observed in rock-salt structure SnSe $\{111\}$ thin films. Previous studies have suggested that the Se-terminated surface of this thin film with hydrogen passivation, has a reduced surface energy and is thus a preferred configuration. In this paper, synchrotron-based angle-resolved photoemission spectroscopy, along with density functional theory calculations, are used to demonstrate conclusively that a rock-salt SnSe $\{111\}$ thin film epitaxially-grown on \ce{Bi2Se3} has a stable Sn-terminated surface. These observations are supported by low energy electron diffraction (LEED) intensity-voltage measurements and dynamical LEED calculations, which further show that the Sn-terminated SnSe $\{111\}$ thin film has undergone a surface structural relaxation of the interlayer spacing between the Sn and Se atomic planes. In sharp contrast to the Se-terminated counterpart, the observed Dirac surface state in the Sn-terminated SnSe $\{111\}$ thin film is shown to yield a high Fermi velocity, $0.50\times10^6$m/s, which suggests a potential mechanism of engineering the Dirac surface state of topological materials by tuning the surface configuration.Comment: 12 pages, 13 figures, supplementary materials include

The Influence of Action Video Gaming Experience on the Perception of Emotional Faces and Emotional Word Meaning

Action video gaming (AVG) experience has been found related to sensorimotor and attentional development. However, the influence of AVG experience on the development of emotional perception skills is still unclear. Using behavioral and ERP measures, this study examined the relationship between AVG experience and the ability to decode emotional faces and emotional word meanings. AVG experts and amateurs completed an emotional word-face Stroop task prior to (the pregaming phase) and after (the postgaming phase) a 1 h AVG session. Within-group comparisons showed that after the 1 h AVG session, a more negative N400 was observed in both groups of participants, and a more negative N170 was observed in the experts. Between-group comparisons showed that the experts had a greater change of N170 and N400 amplitudes across phases than the amateurs. The results suggest that both the 1 h and long-term AVG experiences may be related to an increased difficulty of emotional perception. Furthermore, certain behavioral and ERP measures showed neither within- nor between-group differences, suggesting that the relationship between AVG experience and emotional perception skills still needs further research

Dual protective role of velutin against articular cartilage degeneration and subchondral bone loss via the p38 signaling pathway in murine osteoarthritis

Osteoarthritis (OA) is a common degenerative joint condition associated with inflammation and characterized by progressive degradation of the articular cartilage and subchondral bone loss in the early stages. Inflammation is closely associated with these two major pathophysiological changes in OA. Velutin, a flavonoid family member, reportedly exerts anti-inflammatory effects. However, the therapeutic effects of velutin in OA have not yet been characterized. In this study, we explore the effects of velutin in an OA mouse model. Histological staining and micro-CT revealed that velutin had a protective effect against cartilage degradation and subchondral bone loss in an OA mouse model generated by surgical destabilization of the medial meniscus (DMM). Additionally, velutin rescued IL-1β-induced inflammation in chondrocytes and inhibited RANKL-induced osteoclast formation and bone resorption in vitro. Mechanistically, the p38 signaling pathway was found to be implicated in the inhibitory effects of velutin. Our study reveals the dual protective effects of velutin against cartilage degradation and subchondral bone loss by inhibiting the p38 signaling pathway, thereby highlighting velutin as an alternative treatment for OA

Induction of protective and therapeutic anti-pancreatic cancer immunity using a reconstructed MUC1 DNA vaccine

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer is a common, highly lethal disease with a rising incidence. MUC1 is a tumor-associated antigen that is over-expressed in pancreatic adenocarcinoma. Active immunotherapy that targets MUC1 could have great treatment value. Here we investigated the preventive and therapeutic effect of a MUC1 DNA vaccine on the pancreatic cancer.</p> <p>Methods</p> <p>MUC1-various tandem repeat units(VNTR) DNA vaccine was produced by cloning one repeat of VNTR and inserting the cloned gene into the pcDNA3.1. In the preventive group, female C57BL/6 mice were immunized with the vaccine, pcDNA3.1 or PBS; and challenged with panc02-MUC1 or panc02 cell. In the therapeutic group the mice were challenged with panc02-MUC1 or panc02 cell, and then immunized with the vaccine, pcDNA3.1 or PBS. The tumor size and the survival time of the animals were compared between these groups.</p> <p>Results</p> <p>The DNA vaccine pcDNA3.1-VNTR could raise cytotoxic T lymphocyte (CTL) activity specific for MUC1. In the preventive experiment, the mice survival time was significantly longer in the vaccine group than in the control groups (<it>P </it>< 0.05). In the therapeutic experiment, the DNA vaccine prolonged the survival time of the panc02-MUC1-bearing mice (<it>P </it>< 0.05). In both the preventive and therapeutic experiments, the tumor size was significantly less in the vaccine group than in the control groups (<it>P </it>< 0.05). This pcDNA3.1-VNTR vaccine, however, could not prevent the mice attacked by panc02 cells and had no therapeutic effect on the mice attacked by panc02 cells.</p> <p>Conclusion</p> <p>The MUC1 DNA vaccine pcDNA3.1-VNTR could induce a significant MUC1-specific CTL response; and had both prophylactic and therapeutic effect on panc02-MUC1 tumors. This vaccine might be used as a new adjuvant strategy against pancreatic cancer.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

When and How Much Did the Green Line LRT Increase Single-Family Housing Values in St. Paul, Minnesota?

Studies quantifying value added of transit often cannot differentiate whether the premiums are transit effects or location effects. Limited studies have examined the timing of value added. Using before and after data, this study explores the impact of the Green Line LRT on housing sales prices. Compared to the studied period before its funding announcement, its announcement increased housing values by $9.2/sq ft and its commencement increased sales prices by$13.7/sq ft. Further analyses show that housing value appreciation actually occurred after the announcement but before the commencement. Thus, using the right timing of value added is critical for value capture programs and benefit–cost analysis

A 64-Line Lidar-Based Road Obstacle Sensing Algorithm for Intelligent Vehicles

Based on the 64-line lidar sensor, an object detection and classification algorithm with both effectiveness and real time is proposed. Firstly, a multifeature and multilayer lidar points map is used to separate the road, obstacle, and suspension object. Then, obstacle grids are clustered by a grid-clustering algorithm with dynamic distance threshold. After that, by combining the motion state information of two adjacent frames, the clustering results are corrected. Finally, the SVM classifier is used to classify obstacles with clustered object position and attitude features. The good accuracy and real-time performance of the algorithm are proved by experiments, and it can meet the real-time requirements of the intelligent vehicles