Navigating the new normal: Examining coattendance in a hybrid work environment.

The recent rise of hybrid work poses novel challenges for synchronizing in-office work schedules. Using anonymized building access data, we quantified coattendance patterns among ~43k employees at a large global technology company. We used two-way fixed effects regression models to investigate the association between an employee's presence in the office and that of their manager and teammates. Our analysis shows that employee in-person attendance was 29% higher when their manager was present. Moreover, a 1-SD increase in the share of teammates who were present yielded a 16% increase in the individual employee's attendance. We also observed greater coattendance among employees who were recently hired, have a Corporate or Operations role, or work in shared office spaces. Thus, we find evidence of some voluntary alignment of work schedules. Companies could bolster such organic coordination by leveraging digital scheduling tools or providing guidance specifically aimed at increasing coattendance.

Climate mitigation potentials of teleworking are sensitive to changes in lifestyle and workplace rather than ICT usage.

The growth in remote and hybrid work catalyzed by the COVID-19 pandemic could have significant environmental implications. We assess the greenhouse gas emissions of this transition, considering factors including information and communication technology, commuting, noncommute travel, and office and residential energy use. We find that, in the United States, switching from working onsite to working from home can reduce up to 58% of work's carbon footprint, and the impacts of IT usage are negligible, while office energy use and noncommute travel impacts are important. Our study also suggests that achieving the environmental benefits of remote work requires proper setup of people's lifestyle, including their vehicle choice, travel behavior, and the configuration of home and work environment.

Highly dispersed Co/Co9S8 nanoparticles encapsulated in S, N co-doped longan shell-derived hierarchical porous carbon for corrosion-resistant, waterproof high-performance microwave absorption.

It is highly desirable, but challenging to develop multifunctional electromagnetic wave (EMW) absorbing material for practical applications in some harsh environments. Herein, we successfully embedded highly dispersed Co/Co9S8 nanoparticles into a three-dimensional (3D) honeycomb porous carbon skeleton (the carbon skeleton is derived from longan shell-derived S, N co-doped porous carbon) as a multifunctional material with outstanding EMW absorption properties, hydrophobicity and corrosion resistance. Its superior versatility is attributed to synergistic effects of the S and N dopants, large specific surface area, abundant carbon defects, and 3D porous characteristics. Minimal reflection loss (RLmin) and efficient absorption bandwidth (EAB) of the optimized material as EMW absorbers can achieve -59.9 dB and 6.8 GHz at a thickness of 2.7 mm, respectively, which are superior to most of the reported carbon-based absorbents. Meanwhile, theoretical simulations of the radar scattering cross section (RCS) further confirm that this multifunctional material has outstanding EMW attenuation performance and actual application potential. In addition, the material possesses strong hydrophobicity (124°) and anti-corrosion properties, expanding the scope of potential applications of microwave absorbers. Therefore, this work provides an effective development strategy for the design of anti-corrosion, super-hydrophobic, and high-performance EMW absorbing materials.

Optimizing the Nonlinear Optical Performance of an A-N-M-Q (A: Alkali Metal; N: d10 Metal; M: Main Group Metal; Q: Chalcogen) System.

Exploring new infrared nonlinear optical (IR NLO) materials with superior overall properties is scientifically and technically important. However, large second-order harmonic generation (SHG) efficiencies and high laser-induced damage thresholds (LIDT) are incompatible, which makes realizing this goal a challenge. The IR NLO performance of an A-NIIB-MIIIA-Q (Q: chalcogen) system was optimized by simultaneously modulating A/(M + N) and M/N ratios (A: alkali metal; N, M: tetra-coordinated metals), and SHG-LIDT balance was achieved. Three new sulfides, KCd3Ga5S11 (1), RbCd4Ga3S9 (2), and Cs2Cd2Ga8S15 (3), containing the same CdS4 and GaS4 but with different A/(Ga + Cd) and Ga/Cd ratios were obtained. Among these compounds, compound 3 exhibits both the largest SHG efficiency (0.5 × AgGaS2) and LIDT (35 × AgGaS2), which can be ascribed to the Ga/Cd modulation for enhancing the NLO functional motif distortions and SHG efficiency as well as the A/(Ga + Cd) modulation for enlarging the band gap and LIDT. Remarkably, compound 3 is the first phase-matchable IR NLO material in the A-NIIB-MIIIA-Q family. This article proposes a novel avenue to explore infrared nonlinear materials with superior comprehensive properties by modulating the A/(M + N) and M/N ratios.

The effects of remote work on collaboration among information workers.

The coronavirus disease 2019 (COVID-19) pandemic caused a rapid shift to full-time remote work for many information workers. Viewing this shift as a natural experiment in which some workers were already working remotely before the pandemic enables us to separate the effects of firm-wide remote work from other pandemic-related confounding factors. Here, we use rich data on the emails, calendars, instant messages, video/audio calls and workweek hours of 61,182 US Microsoft employees over the first six months of 2020 to estimate the causal effects of firm-wide remote work on collaboration and communication. Our results show that firm-wide remote work caused the collaboration network of workers to become more static and siloed, with fewer bridges between disparate parts. Furthermore, there was a decrease in synchronous communication and an increase in asynchronous communication. Together, these effects may make it harder for employees to acquire and share new information across the network.

Balanced infrared nonlinear optical performance achieved by modulating the covalency and ionicity distributions in the electron localization function map.

The nonlinear optical (NLO) efficiency (dij) and laser-induced damage threshold (LIDT) of a material are mainly determined by their covalency and ionicity, respectively, the incompatibility between which makes balancing the dij and LIDT challenging in an IR NLO material. The topological feature (fractal dimension) of the electron localization function (ELF) map (distribution of covalency and ionicity) was evaluated for a series of NLO materials, and, phenomenologically, the fine mixing of covalency and ionicity will benefit a balanced dij and LIDT. Chemical bonds with different interaction strengths were introduced simultaneously to mix the covalency and iconicity finely, and three new IR NLO sulfides, A2Ba3Li6Ga28S49 (A = K, 1; Rb, 2; Cs, 3), were obtained. They exhibit a strong NLO efficiency (1.9-2.1 × AgGaS2 at 1064 nm and 0.5-0.6 × AgGaS2 at 1910 nm) and high LIDTs (16.7-18.0 × AgGaS2), which fulfill the criteria of being promising IR NLO candidates. This study provides a new method for designing high-performance IR NLO materials based on the topological features of the ELF.

Vertically Grown Few-Layer MoS2 Nanosheets on Hierarchical Carbon Nanocages for Pseudocapacitive Lithium Storage with Ultrahigh-Rate Capability and Long-Term Recyclability.

Molybdenum disulfide (MoS2 ) is an intensively studied anode material for lithium-ion batteries (LIBs) owing to its high theoretical capacity, but it is still confronted by severe challenges of unsatisfactory rate capability and cycle life. Herein, few-layer MoS2 nanosheets, vertically grown on hierarchical carbon nanocages (hCNC) by a facile hydrothermal method, introduce pseudocapacitive lithium storage owing to the highly exposed MoS2 basal planes, enhanced conductivity, and facilitated electrolyte access arising from good hybridization with hCNC. Thus, the optimized MoS2 /hCNC exhibits reversible capacities of 1670 mAh g-1 at 0.1 A g-1 after 50 cycles, 621 mAh g-1 at 5.0 A g-1 after 500 cycles, and 196 mAh g-1 at 50 A g-1 after 2500 cycles, which are among the best for MoS2 -based anode materials. The specific power and specific energy, which can reach 16.1 kW kg electrode - 1 and 252.8 Wh kg electrode - 1 after 3000 cycles, respectively, indicate great potential in high-power and long-life LIBs. These findings suggest a promising strategy for exploring advanced anode materials with high reversible capacity, high-rate capability, and long-term recyclability.

Yum-Me: A Personalized Nutrient-Based Meal Recommender System.

Nutrient-based meal recommendations have the potential to help individuals prevent or manage conditions such as diabetes and obesity. However, learning people's food preferences and making recommendations that simultaneously appeal to their palate and satisfy nutritional expectations are challenging. Existing approaches either only learn high-level preferences or require a prolonged learning period. We propose Yum-me, a personalized nutrient-based meal recommender system designed to meet individuals' nutritional expectations, dietary restrictions, and fine-grained food preferences. Yum-me enables a simple and accurate food preference profiling procedure via a visual quiz-based user interface and projects the learned profile into the domain of nutritionally appropriate food options to find ones that will appeal to the user. We present the design and implementation of Yum-me and further describe and evaluate two innovative contributions. The first contriution is an open source state-of-the-art food image analysis model, named FoodDist. We demonstrate FoodDist's superior performance through careful benchmarking and discuss its applicability across a wide array of dietary applications. The second contribution is a novel online learning framework that learns food preference from itemwise and pairwise image comparisons. We evaluate the framework in a field study of 227 anonymous users and demonstrate that it outperforms other baselines by a significant margin. We further conducted an end-to-end validation of the feasibility and effectiveness of Yum-me through a 60-person user study, in which Yum-me improves the recommendation acceptance rate by 42.63%.

Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain.

Active and passive mobile sensing has garnered much attention in recent years. In this paper, we focus on chronic pain measurement and management as a case application to exemplify the state of the art. We present a consolidated discussion on the leveraging of various sensing modalities along with modular server-side and on-device architectures required for this task. Modalities included are: activity monitoring from accelerometry and location sensing, audio analysis of speech, image processing for facial expressions as well as modern methods for effective patient self-reporting. We review examples that deliver actionable information to clinicians and patients while addressing privacy, usability, and computational constraints. We also discuss open challenges in the higher level inferencing of patient state and effective feedback with potential directions to address them. The methods and challenges presented here are also generalizable and relevant to a broad range of other applications in mobile sensing.

[Comparative study on characteristics of urban rainfall runoff from two urban lawn catchments in Macau and Xiamen].

A comparative study on characteristics of stormwater runoff from two urban lawn catchments in Macau (ELH) and Xiamen (PGH) with separated sewer system were conducted. The result obtained shows that COD, TP and NO3- -N are the major pollutants with mean EMC of 165.77-60.48 mg/L, 0.96-0.44 mg/L and 7.16-1.18 mg/L, respectively, and the mean values of pollutants loads of COD, TP and NO3- -N from study lawn catchments are 6.53-0.63 kg/hm2, 0.0375-0.0047 kg/hm2 and 0.0122-0.0128 kg/hm2, respectively. Peak values of major pollutant concentrations usually precede the flow peak. First flush effect of rainfall runoff from two study catchments is no obvious, which can be reflected by the low mean value of FF30 of TSS, COD, TP and NO3- -N, with 36.26%, 26.13%, 28.13% and 39.03%, respectively. Based on multivariate statistical analysis, first flush effect from urban lawn rainfall runoff is greatly influenced by total rainfall amount (Tr) and total runoff volume (V).