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Optofluidic paper-based analytical device for discriminative detection of organic substances via digital color coding
Developing a portable yet affordable method for the discrimination of chemical substances with good sensitivity and selectivity is essential for on-site visual detection of unknown substances. Herein, we propose an optofluidic paper-based analytical device (PAD) that consists of a macromolecule-driven flow (MDF) gate and photonic crystal (PhC) coding units, enabling portable and scalable detection and discrimination of various organic chemical, mimicking the olfactory system. The MDF gate is designed for precise flow control of liquid analytes, which depends on intermolecular interactions between the polymer at the MDF gate and the liquid analytes. Subsequently, the PhC coding unit allows for visualizing the result obtained from the MDF gate and generating differential optical patterns. We fabricate an optofluidic PAD by integrating two coding units into a three-dimensional (3D) microfluidic paper within a 3D-printed cartridge. The optofluidic PADs clearly distinguish 11 organic chemicals with digital readout of pattern recognition from colorimetric signals. We believe that our optofluidic coding strategy mimicking the olfactory system opens up a wide range of potential applications in colorimetric monitoring of chemicals observed in environment.
Efficiently preparing chiral states via fermionic cooling on bosonic quantum hardware
Simulating many-body systems is one of the most promising applications of near-term quantum computers. An important open question is how to efficiently prepare the ground states of arbitrary fermionic Hamiltonians, especially those with nontrivial topology. Here, we propose an efficient protocol for preparing low-energy states of fermionic Hamiltonians on a noisy bosonic quantum simulator by adiabatic cooling using a simulated bath. We arrange the couplings such that the simulated system and bath together obtain a local fermionic description in which fermionic excitations can be extracted individually, via coherent hopping to the bath, rather than in pairs as would otherwise be required by fermion parity conservation. This approach thus achieves a linear (rather than quadratic) scaling of the cooling rate vs. excitation density at low densities. We show that certain topological phases such as the chiral (non-Abelian) phase of the Kitaev honeycomb model can be prepared efficiently using our protocol. Our protocol performs favorably in the presence of noise, making it suitable for execution on near-term quantum devices.
Toward change in the uneven geographies of urban knowledge production
More than four-fifths of the global urban population live in the Global South and East. Most urban theories, however, originate in the Global North. Building on recent efforts to address this mismatch, this paper examines the geographies of urban knowledge production. It analyzes the institutional affiliations of contributions in 25 leading Anglophone journals (n = 14,582) and nine urban handbooks (n = 252). We show that 42% of the journal articles and 17% of the handbook chapters were authored outside the Global North. However, only 15% of the editor positions (handbooks: 10%) were held by scholars based outside the Global North. This indicates that Global Northern institutions still dominate knowledge gatekeeping, whereas authors are more diverse. Additionally, more empirical journals and those with fewer Northern board members tend to publish more non-Northern authors. Our findings underscore the need for greater epistemic diversity in gatekeeping positions and broader understandings of what counts as theory to better incorporate diverse urban knowledge.
Optical sorting: past, present and future
Optical sorting combines optical tweezers with diverse techniques, including optical spectrum, artificial intelligence (AI) and immunoassay, to endow unprecedented capabilities in particle sorting. In comparison to other methods such as microfluidics, acoustics and electrophoresis, optical sorting offers appreciable advantages in nanoscale precision, high resolution, non-invasiveness, and is becoming increasingly indispensable in fields of biophysics, chemistry, and materials science. This review aims to offer a comprehensive overview of the history, development, and perspectives of various optical sorting techniques, categorised as passive and active sorting methods. To begin, we elucidate the fundamental physics and attributes of both conventional and exotic optical forces. We then explore sorting capabilities of active optical sorting, which fuses optical tweezers with a diversity of techniques, including Raman spectroscopy and machine learning. Afterwards, we reveal the essential roles played by deterministic light fields, configured with lens systems or metasurfaces, in the passive sorting of particles based on their varying sizes and shapes, sorting resolutions and speeds. We conclude with our vision of the most promising and futuristic directions, including AI-facilitated ultrafast and bio-morphology-selective sorting. It can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.
When the customers comes to you: mobile apps and corporate investment efficiency
Firms are increasingly shifting towards digital channels, yet the implications of this shift remain underexplored. Using a unique database of customer behaviors extracted from the top 2000 mobile apps developed by companies in China, this study investigates the impact of mobile apps on inefficient corporate investments. The results indicate that metrics such as active user count, usage duration, and app launch frequency can mitigate inefficient investments, notably by curtailing overinvestment. These findings survive a series of robustness checks such as altering the measures of inefficient investment, extending the analysis to include the top five apps, incorporating H-share listed firms, and employing instrumental variables regression. Moreover, the mechanism analysis indicates that mobile apps help reduce inefficient investments by lowering agency costs and relaxing financial constraints. Further analysis examines the business models of these apps (paid vs. free) as well as their reputation mechanisms, revealing that the pricing strategies of apps and the reputation of corporate brands also play a role in how the adoption of mobile apps affects inefficient investment.
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