A Quantitative Review on Language Model Efficiency Research

Language models (LMs) are being scaled and becoming powerful. Improving their efficiency is one of the core research topics in neural information processing systems. Tay et al. (2022) provided a comprehensive overview of efficient Transformers that have become an indispensable staple in the field of NLP. However, in the section of "On Evaluation", they left an open question "which fundamental efficient Transformer one should consider," answered by "still a mystery" because "many research papers select their own benchmarks." Unfortunately, there was not quantitative analysis about the performances of Transformers on any benchmarks. Moreover, state space models (SSMs) have demonstrated their abilities of modeling long-range sequences with non-attention mechanisms, which were not discussed in the prior review. This article makes a meta analysis on the results from a set of papers on efficient Transformers as well as those on SSMs. It provides a quantitative review on LM efficiency research and gives suggestions for future research.Comment: 29 pages, 24 table

Bayesian reinforcement learning reliability analysis

A Bayesian reinforcement learning reliability method that combines Bayesian inference for the failure probability estimation and reinforcement learning-guided sequential experimental design is proposed. The reliability-oriented sequential experimental design is framed as a finite-horizon Markov decision process (MDP), with the associated utility function defined by a measure of epistemic uncertainty about Kriging-estimated failure probability, referred to as integrated probability of misclassification (IPM). On this basis, a one-step Bayes optimal learning function termed integrated probability of misclassification reduction (IPMR), along with a compatible convergence criterion, is defined. Three effective strategies are implemented to accelerate IPMR-informed sequential experimental design: (i) Analytical derivation of the inner expectation in IPMR, simplifying it to a single expectation. (ii) Substitution of IPMR with its upper bound IPMRU to avoid element-wise computation of its integrand. (iii) Rational pruning of both quadrature set and candidate pool in IPMRU to alleviate computer memory constraint. The efficacy of the proposed approach is demonstrated on two benchmark examples and two numerical examples. Results indicate that IPMRU facilitates a much more rapid reduction of IPM compared to other existing learning functions, while requiring much less computational time than IPMR itself. Therefore, the proposed reliability method offers a substantial advantage in both computational efficiency and accuracy, especially in complex dynamic reliability problems

Cryo-EM Studies of TMEM16F Calcium-Activated Ion Channel Suggest Features Important for Lipid Scrambling.

As a Ca2+-activated lipid scramblase and ion channel that mediates Ca2+ influx, TMEM16F relies on both functions to facilitate extracellular vesicle generation, blood coagulation, and bone formation. How a bona fide ion channel scrambles lipids remains elusive. Our structural analyses revealed the coexistence of an intact channel pore and PIP2-dependent protein conformation changes leading to membrane distortion. Correlated to the extent of membrane distortion, many tightly bound lipids are slanted. Structure-based mutagenesis studies further reveal that neutralization of some lipid-binding residues or those near membrane distortion specifically alters the onset of lipid scrambling, but not Ca2+ influx, thus identifying features outside of channel pore that are important for lipid scrambling. Together, our studies demonstrate that membrane distortion does not require open hydrophilic grooves facing the membrane interior and provide further evidence to suggest separate pathways for lipid scrambling and ion permeation

A Unified Quantum NOT Gate

We study the feasibility of implementing a quantum NOT gate (approximate) when the quantum state lies between two latitudes on the Bloch's sphere and present an analytical formula for the optimized 1-to-$M$ quantum NOT gate. Our result generalizes previous results concerning quantum NOT gate for a quantum state distributed uniformly on the whole Bloch sphere as well as the phase covariant quantum state. We have also shown that such 1-to-$M$ optimized NOT gate can be implemented using a sequential generation scheme via matrix product states (MPS)

Electrical Tuning of Neutral and Charged Excitons with 1-nm Gate

Electrical control of individual spins and photons in solids is key for quantum technologies, but scaling down to small, static systems remains challenging. Here, we demonstrate nanoscale electrical tuning of neutral and charged excitons in monolayer WSe2 using 1-nm carbon nanotube gates. Electrostatic simulations reveal a confinement radius below 15 nm, reaching the exciton Bohr radius limit for few-layer dielectric spacing. In situ photoluminescence spectroscopy shows gate-controlled conversion between neutral excitons, negatively charged trions, and biexcitons at 4 K. Important for quantum information processing applications, our measurements indicate gating of a local 2D electron gas in the WSe2 layer, coupled to photons via trion transitions with binding energies exceeding 20 meV. The ability to deterministically tune and address quantum emitters using nanoscale gates provides a pathway towards large-scale quantum optoelectronic circuits and spin-photon interfaces for quantum networking.Comment: 21 pages, 11 figure

Capacity Management in Agricultural Commodity Processing and Application in the Palm Industry

This paper examines the capacity investment decisions of a processor that uses a commodity input to produce both a commodity output and a by-product in the context of agricultural industries. We employ a multiperiod model to study the optimal one-time processing and (output) storage capacity investment decisions—in addition to the periodic processing and inventory decisions—when both input and output spot prices as well as production yield are uncertain. We characterize the optimal decisions and perform sensitivity analysis to investigate how spot price uncertainty affects the processor’s optimal capacity and profitability. Using a calibration based on the palm industry, we study (both numerically and analytically) the performance of a variety of heuristic capacity investment policies that can be used in practice. We find that if the yield uncertainty is ignored in capacity planning, then basing those plans on the average yield is preferable to basing them (as often occurs in practice) on the maximum yield. However, planning based on the average yield performs well only when the relative (processing-to-storage) capacity investment cost is high; otherwise, it leads to a significant loss of profit. We also find that ignoring spot price uncertainty in capacity planning results in a relatively small profit loss. In contrast, ignoring by-product revenue—which constitutes a small portion of total revenues—during capacity planning substantially reduces the processor’s profit. The online appendix is available at https://doi.org/10.1287/msom.2017.0624 . </jats:p

Dairy Value Chain In Vietnam: Evidences from Bavi Area

Dairy farming, in Vietnam, existed in the early twentieth century thanks to the favorable natural advantage. During many difficult periods, the Vietnam’s dairy industry has developed constantly and contributed significantly to the food needs ensuring. However, Vietnam’s dairy industry still could not satisfy the domestic milk demand. Retail milk prices in Vietnam are very high, whereas the price of milk sold by the dairy farmers is very low. The cause stems from the control of dairy companies in the quantity and quality of milk. Moreover, that control caused an imbalance in the profits and benefits of each actor in the dairy value chain. This study, hence, finds out the distribution of benefits, costs, value-added among the actors, and problems in the practical management in dairy milk value chain with specific focus on Bavi as the case study

Optimization of Total Flavonoid Extraction From the Helicteres hirsuta Lour. Roots by Bath Ultrasound Assisted method and cytotoxic activities of these Flavonoids

This study was carried out to optimize the various approaches to analyze the effects of various variables on the total flavonoid content extraction from the roots of Helicteres hirsuta L. The existence of various compounds in the methanol fraction was accessed by using LC-MS/MS analysis. The results of the study identified the ideal parameters such as times (30 minutes); methanol solvent concentration (50%); ultrasonic frequency (12 Hz); and material/solvent ratio [1:30 (w/v)] for extracting the highest total flavonoids from the roots of H. Hirsuta. The study's results suggested that the total flavonoid value was 3.52684 (mg Catechin/g extract). The verified experiment obtained an actual value of 5.205 (mg Catechin/g extract). Further, the results of the study suggested the presence of 20 compounds of a flavonoid nature (66.667%) appearing in the purified methanol fractional extract. These compounds can inhibit DPPH free radicals at 50%, with an IC50 value of 536.760 g/mL, and they also have inhibitory activity on the growth of cancer cell lines with IC50 values ranging from 115.81 and 219.17g/mL. The human leukemia cell line (HL-60) exhibits the most significant cytotoxic response to a methanol extract from H. hirsuta root with an IC50 value of 115.81 g/mL