MedEdit: Model Editing for Medical Question Answering with External Knowledge Bases

Large Language Models (LLMs), although powerful in general domains, often perform poorly on domain-specific tasks like medical question answering (QA). Moreover, they tend to function as "black-boxes," making it challenging to modify their behavior. Addressing this, our study delves into model editing utilizing in-context learning, aiming to improve LLM responses without the need for fine-tuning or retraining. Specifically, we propose a comprehensive retrieval strategy to extract medical facts from an external knowledge base, and then we incorporate them into the query prompt for the LLM. Focusing on medical QA using the MedQA-SMILE dataset, we evaluate the impact of different retrieval models and the number of facts provided to the LLM. Notably, our edited Vicuna model exhibited an accuracy improvement from 44.46% to 48.54%. This work underscores the potential of model editing to enhance LLM performance, offering a practical approach to mitigate the challenges of black-box LLMs.Comment: 6 page

Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model

With the rapid growth in model size, fine-tuning the large pre-trained language model has become increasingly difficult due to its extensive memory usage. Previous works usually focus on reducing the number of trainable parameters in the network. While the model parameters do contribute to memory usage, the primary memory bottleneck during training arises from storing feature maps, also known as activations, as they are crucial for gradient calculation. Notably, neural networks are usually trained using stochastic gradient descent. We argue that in stochastic optimization, models can handle noisy gradients as long as the gradient estimator is unbiased with reasonable variance. Following this motivation, we propose a new family of unbiased estimators called WTA-CRS, for matrix production with reduced variance, which only requires storing the sub-sampled activations for calculating the gradient. Our work provides both theoretical and experimental evidence that, in the context of tuning transformers, our proposed estimators exhibit lower variance compared to existing ones. By replacing the linear operation with our approximated one in transformers, we can achieve up to 2.7$\times$ peak memory reduction with almost no accuracy drop and enables up to $6.4\times$ larger batch size. Under the same hardware, WTA-CRS enables better down-streaming task performance by applying larger models and/or faster training speed with larger batch sizes

Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy

DeePMD-kit v2: A software package for Deep Potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments.Comment: 51 pages, 2 figure

The Germ Cell Nuclear Proteins hnRNP G-T and RBMY Activate a Testis-Specific Exon

The human testis has almost as high a frequency of alternative splicing events as brain. While not as extensively studied as brain, a few candidate testis-specific splicing regulator proteins have been identified, including the nuclear RNA binding proteins RBMY and hnRNP G-T, which are germ cell-specific versions of the somatically expressed hnRNP G protein and are highly conserved in mammals. The splicing activator protein Tra2β is also highly expressed in the testis and physically interacts with these hnRNP G family proteins. In this study, we identified a novel testis-specific cassette exon TLE4-T within intron 6 of the human transducing-like enhancer of split 4 (TLE4) gene which makes a more transcriptionally repressive TLE4 protein isoform. TLE4-T splicing is normally repressed in somatic cells because of a weak 5′ splice site and surrounding splicing-repressive intronic regions. TLE4-T RNA pulls down Tra2β and hnRNP G proteins which activate its inclusion. The germ cell-specific RBMY and hnRNP G-T proteins were more efficient in stimulating TLE4-T incorporation than somatically expressed hnRNP G protein. Tra2b bound moderately to TLE4-T RNA, but more strongly to upstream sites to potently activate an alternative 3′ splice site normally weakly selected in the testis. Co-expression of Tra2β with either hnRNP G-T or RBMY re-established the normal testis physiological splicing pattern of this exon. Although they can directly bind pre-mRNA sequences around the TLE4-T exon, RBMY and hnRNP G-T function as efficient germ cell-specific splicing co-activators of TLE4-T. Our study indicates a delicate balance between the activity of positive and negative splicing regulators combinatorially controls physiological splicing inclusion of exon TLE4-T and leads to modulation of signalling pathways in the testis. In addition, we identified a high-affinity binding site for hnRNP G-T protein, showing it is also a sequence-specific RNA binding protein

Measuring the Psychological Behavior of Tourism Service Providers in Low-Income Regions: Implementing Effective Service Marketing and Performances Strategies

An effective marketing strategy is a critical contribution in any business including the tourism sector. Understanding marketing strategies increases business performance. The purpose of this study is to determine how service marketing strategies impact small town tourism business owners. Using an econometric model, the implementation of the 4P mixed strategy on the profitability and potential of service providers in Molise is investigated. Revenue, cost, and profit are the three areas analyzed. Results showed that service operators have to place emphasis on research and development, reflecting cultural identities and the adoption of modern media. Operators should emphasize marketing and sales promotions through websites and social media. Creating a quality brand and setting reasonable prices without exploiting consumers are essential strategies. In conclusion, strategies that emphasize knowledge management and team building should be put into practice. This study could help tourism businesses in small regions to be more sustainable. It is the first research study where Stan Shih’s innovation smiling curve has been used in an Italian region

Application of heat pump combined two-stage desiccant wheel fresh air system of residential buildings in mixed climate zone

The building requires dehumidification for a long period of time in mixed climate zone of China. As a conventional method for dehumidification, vapor compression systems remove the water vapor by cooling the process air below dew point. This system consumes a lot of energy for reheating the air to meet the requirement of supply air temperature. A heat pump combined with two-stage desiccant wheel (TSDW&HP) is proposed as an air conditioning and dehumidification system in this study. The operation performance of proposed system applied in a hypothetical residence with 3 residents was investigated and simulated by using TRNSYS software. The operation modes of the system are discussed for different scenarios of season and outdoor air humidity ratio. In dehumidification season, fresh air deals with all of the latent load. In air conditioning season, fresh air deals with all of the moisture load with part of the cooling load. When evaporation temperature of HP is reduced and more moisture load is processed by evaporator in air conditioning season, there is a balance point between the performance of DWs and heat pump. The energy consumption of TSDW&HP fresh air system was compared with a conventional fresh air conditioner during dehumidification season and air conditioning season. It was found that the energy-saving potential of this system is 27.3% compared with conventional air conditioner

The System of the Calibration for Visibility Measurement Instrument Under the Atmospheric Aerosol Simulation Environment

Visibility is one of the most important parameters for meteorological observation and numerical weather prediction (NWP).It is also an important factor in everyday life, mainly for surface and air traffic especially in the Aeronautical Meteorology. The visibility decides the taking off and landing of aircraft. If the airport visibility is lower than requirement for aircraft taking off stipulated by International Civil Aviation Administration, then the aircraft must be parked at the airport. So the accurate measurement of visibility is very important. Nowadays, many devices can be measured the visibility or meteorological optical range (MOR) such as Scatterometers, Transmissometers and visibility lidar. But there is not effective way to verify the accuracy of these devices expect the artificial visual method. We have developed a visibility testing system that can be calibration and verification these devices. The system consists of laser transmitter, optical chopper, phase-locking amplifier, the moving optic receiving system, signal detection and data acquisition system, atmospheric aerosol simulation chamber. All of them were placed in the atmosphere aerosol simulation chamber with uniform aerosol concentration. The Continuous wave laser, wavelength 550nm, has been transmitted into the collimation system then the laser beam expanded into 40mm diameter for compressing the laser divergence angle before modulated by optical chopper. The expanding beam transmitting in the atmosphere aerosol cabin received by the optic receiving system moving in the 50m length precision guide with 100mm optical aperture. The data of laser signal has been acquired by phase-locking amplifier every 5 meter range. So the 10 data points can be detected in the 50 meters guide once. The slope of the fitting curve can be obtained by linear fitting these data using the least square method. The laser extinction coefficient was calculated from the slope using the Koschmieder formula, then it been divided by 3 is MOR. The aerosol concentration in chamber can be changed by adjusting aerosol generator that producing variety of visibility atmospherical environment. The experiment has been carried out and the measurement accuracy of atmospheric transmittance is 0.3‰ Corresponding to the accuracy of MOR 4.9% at the 2km visibility environment. So this system can be calibrated and validated the other visibility measuring devices

Study on the Dynamics of Microflora during Natural Fermentation of Different Blueberry Wines

Microflora play an important role in the fermentation of blueberry wine, influencing the flavor and nutrient formation. Commercial yeasts give blueberry wines an average flavor profile that does not highlight the specific aroma and origin of the blueberry. In the present study, ITS1-ITS2 region sequencing analysis was performed using Illumina MiSeq high-throughput technology to sequence fermented blueberry wine samples of three Vaccinium ashei varieties, Gardenblue, Powderblue, and Britewell, from the Majiang appellation in Guizhou province to analyze the trends of fungal communities and the diversity of compositional structures in different periods of blueberry wine fermentation. The study’s results revealed that 114 genera from seven phyla were detected in nine samples from different fermentation periods of blueberry wine. The main fungal phyla were Ascomycota, Basidiomycota, Kickxellomycota, Chytridiomycota, and Olpidiomycota. The main fungal genera were Hanseniaspora, Saccharomyces, unidentified, Aureobasidium, Penicillium, Mortierella, Colletotrichum, etc. Hanseniaspora was dominant in the pre-fermentation stage of blueberry wine, accounting for more than 82%; Saccharomyces was the dominant genera in the middle and late fermentation stages of blueberry wine, with Saccharomyces accounting for more than 72% in the middle of fermentation and 93% in the late fermentation stage. This study screened indigenous flora for the natural fermentation of blueberry wine in the Majiang production area of Guizhou, improved the flavor substances of the blueberry wine, highlighted the characteristics of the production area, and made the blueberry wine have the characteristic flavor of the production area