Synthetic routes to trifluoromethylphenyl diazirine photolabeling reagents containing an alkyne substituent (TPDYNE) for chemical biology applications

The trifluoromethylphenyl diazirine (TPD) group is widely used in photoaffinity labeling studies. The TPDYNE group (TPD with an additional alkyne substituent on the phenyl ring) enables the use of click chemistry in conjunction with photoaffinity labeling and expands the utility of the TPD group. New methods for preparing previously known as well as new TPDYNE reagents are reported. Additional methods for preparation of a TPDYNE precursor from which the TPDYNE group can be generated once the precursor is attached to the molecule of interest are also described. Procedures for attaching the TPDYNE or TPDYNE precursor to carboxyl, amino, hydroxyl and alkyne groups are demonstrated using steroids as examples

Enhancing Quantised End-to-End ASR Models via Personalisation

Recent end-to-end automatic speech recognition (ASR) models have become increasingly larger, making them particularly challenging to be deployed on resource-constrained devices. Model quantisation is an effective solution that sometimes causes the word error rate (WER) to increase. In this paper, a novel strategy of personalisation for a quantised model (PQM) is proposed, which combines speaker adaptive training (SAT) with model quantisation to improve the performance of heavily compressed models. Specifically, PQM uses a 4-bit NormalFloat Quantisation (NF4) approach for model quantisation and low-rank adaptation (LoRA) for SAT. Experiments have been performed on the LibriSpeech and the TED-LIUM 3 corpora. Remarkably, with a 7x reduction in model size and 1% additional speaker-specific parameters, 15.1% and 23.3% relative WER reductions were achieved on quantised Whisper and Conformer-based attention-based encoder-decoder ASR models respectively, comparing to the original full precision models.Comment: 5 pages, submitted to ICASSP 202

Reducing Carbon Footprint Inequality of Household Consumption in Rural Areas:Analysis from Five Representative Provinces in China

Household consumption carbon footprint and inequality reductions are vital for a sustainable society, especially for rural areas. This study, focusing on rural China, one of the fastest growing economies with a massive population, explored the carbon footprint and inequality of household consumption using the latest micro household survey data of 2018 linked to environmental extended input–-output analysis. The results show that in 2018 in rural China, the average household carbon footprint is 2.46 tons CO2-eq per capita, which is around one-third of China’s average footprint, indicating the large potential for further growth. Housing (45.32%), transportation (20.45%), and food (19.62%) are the dominant contributors to the carbon footprint. Meanwhile, great inequality, with a Gini coefficient of 0.488, among rural households is observed, which is largely due to differences in type of house built or purchased (explaining 24.44% of the variation), heating (18.10%), car purchase (12.44%), and petrol consumption (12.44%). Provinces, average education, and nonfarm income are among the important factors influencing the inequality. In the process of urbanization and rural revitalization, there is a high possibility that the household carbon footprint continues to increase, maintaining high levels of inequality. The current energy transition toward less carbon-intensive fuels in rural China is likely to dampen the growth rates of carbon footprints and potentially decrease inequality. Carbon intensity decrease could significantly reduce carbon footprints, but increase inequality. More comprehensive measures to reduce carbon footprint and inequality are needed, including transitioning to clean energy, poverty alleviation, reduction of income inequality, and better health care coverage

Revisit Two Memoryless State-Recovery Cryptanalysis Methods on A5/1

At ASIACRYPT 2019, Zhang proposed a near collision attack on A5/1 claiming to recover the 64-bit A5/1 state with a time complexity around $2^{32}$ cipher ticks with negligible memory requirements. Soon after its proposal, Zhang\u27s near collision attack was severely challenged by Derbez \etal who claimed that Zhang\u27s attack cannot have a time complexity lower than Golic\u27s memoryless guess-and-determine attack dating back to EUROCRYPT 1997. In this paper, we study both the guess-and-determine and the near collision attacks for recovering A5/1 states with negligible memory complexities. Firstly, we propose a new guessing technique called the \emph{move guessing technique} that can construct linear equation filters in a more efficient manner. Such a technique can be applied to both guess-and-determine and collision attacks for efficiency improvements. Secondly, we take the filtering strength of the linear equation systems into account for complexity analysis. Such filtering strength are evaluated with practical experiments making the complexities more convincing. Based on such new techniques, we are able to give 2 new guess-and-determine attacks on A5/1: the 1st attack recovers the internal state $\vec{s}^0$ with time complexity $2^{43.92}$; the 2nd one recovers a different state $\vec{s}^1$ with complexity $2^{43.25}$. We also revisit Golic\u27s guess-and-determine attack and Zhang\u27s near collision attacks. According to our detailed analysis, the complexity of Golic\u27s $\vec{s}^1$ recovery attack is no lower than $2^{46.04}$, higher than the previously believed $2^{43}$. On the other hand, Zhang\u27s near collision attack recovers $\vec{s}^0$ with the time complexity $2^{53.19}$: such a complexity can be further lowered to $2^{50.78}$ with our move guessing technique

Association between dynamic fluctuations in triiodothyronine levels and prognosis among critically ill patients within comprehensive intensive care units

ObjectiveDecrease in free thyroid hormone T3 (FT3) can be used as an independent prognostic indicator for the risk of death in ICUs. However, FT3 as a predictive marker is hindered by its accuracy. The study introduces the concept of dynamic FT3 data as a means to bolster the value of FT3 as a prognostic tool. Therefore, the aim of this study is to investigate the prognostic value of dynamic FT3 evolution in a comprehensive ICU setting, analyze the consistency between dynamic FT3 changes and variations in disease severity, and explore the feasibility of FT3 as an objective indicator for real-time clinical treatment feedback.MethodsEmploying a single-center prospective observational study, FT3 measurements were taken on multiple days following enrollment, corresponding clinical data were collected. To investigated the pattern of dynamic changes of FT3,its prognostic significance in forecasting the risk of 28-day mortality, the alignment between dynamic FT3 changes and variations in the Sequential Organ Failure Assessment (SOFA) score.ResultsThe survival group exhibited higher last FT3 levels compared to the lowest point (p<0.05), while the death group did not show statistically significant differences (p>0.05). The study also identifies the optimal correlation between FT3 and SOFA score at day 5 (optimal correlation coefficient -0.546).The ROC curve for FT3 at day 5 yielded an optimal AUC of 0.88, outperforming the SOFA score. The study categorizes FT3 curve patterns,Kaplan-Meier survival analysis of these patterns highlighted that the descending-type curve was significantly associated with increased risk of death (P<0.001). Additionally, the research explores the consistency between changes in FT3 and SOFA scores. While overall consistency rates were modest, subgroup analyses unveiled that greater disease severity led to higher consistency rates.ConclusionsThis study introduces the concept of dynamic FT3 changes to augment its prognostic utility in comprehensive ICU settings. The research identifies day 5 as the optimal time point for predictive efficacy, the descending FT3 curve as indicative of poor prognosis. While overall consistency with SOFA scores is modest, the correlation strengthens with greater disease severity

Improved Weighted Covariance Based Detector for Spectrum Sensing in Rayleigh Fading Channel

In this letter, we propose an improved weighted covariance based detector (IWCD) for spatially correlated time-varying Rayleigh fading channel. The proposed method uses adaptive weights that are tailored to the dynamic nature of the channels. These weights can be chosen manually to meet practical requirements or derived theoretically by optimizing some performance index, such that the IWCD outperforms traditional weighted covariance-based detectors (WCDs), which rely heavily on data-aided weights determined by the sample covariance matrix (SCM). Performance merits in terms of the probabilities of false alarm and detection are analyzed in the low signal-to-noise-ratio (SNR) regime. Besides, the optimal weights are derived via maximizing the modified deflection coefficient (MDC). A reasonable estimator of the optimal weights is also constructed armed with the available samples at hand. Theoretical analyses and experimental results demonstrate the superiority of our proposed method over existing works in various scenarios

Droplets as Carriers for Flexible Electronic Devices

Coupling soft bodies and dynamic motions with multifunctional flexible electronics is challenging, but is essential in satisfying the urgent and soaring demands of fully soft and comprehensive robotic systems that can perform tasks in spite of rigorous spatial constraints. Here, the mobility and adaptability of liquid droplets with the functionality of flexible electronics, and techniques to use droplets as carriers for flexible devices are combined. The resulting active droplets (ADs) with volumes ranging from 150 to 600 µL can conduct programmable functions, such as sensing, actuation, and energy harvesting defined by the carried flexible devices and move under the excitation of gravitational force or magnetic force. They work in both dry and wet environments, and adapt to the surrounding environment through reversible shape shifting. These ADs can achieve controllable motions at a maximum velocity of 226 cm min−1 on a dry surface and 32 cm min-1 in a liquid environment. The conceptual system may eventually lead to individually addressable ADs that offer sophisticated functions for high-throughput molecule analysis, drug assessment, chemical synthesis, and information collection