Derived equivalences between generalized matrix algebras

summary:We construct derived equivalences between generalized matrix algebras. We record several corollaries. In particular, we show that the $n$-replicated algebras of two derived equivalent, finite-dimensional algebras are also derived equivalent

Data and the Development of Research Methods in the Science of Human Emotional Expression from Darwin to Klineberg

The science of emotional expression was opened up by Charles Darwin in The Expression of the Emotions in Man and Animals (1872). It proposes three principles to explain the mechanisms of expressive behaviours through six research methods. This thesis offers the first detailed examination of three of the new methods of data collection that Darwin introduced in the book, and uses that examination to explore the relations between Darwin’s theories and data as well as the afterlives of his methods in American psychology in the first half of the twentieth century. The three methods are the questionnaire, the recognition experiments on photographed expressions and the newly discovered literary approach. The original data of the questionnaire avails the first discussion of Darwin’s publication bias, finding that in order to produce the conclusion on racial unity, Darwin had silently dropped one of the questions from the original questionnaire and hidden a significant body of data about racial distinctions. Apart from this pursuit of racial universality, another ultimate conclusion & presumed hypothesis in the book is discovered: the evolution of expression from animals to human, concerned with the recognition experiments. With the last method, we find that when there lacked observational evidence for some expressions, Darwin often quoted works of fiction as supplementary data. The use of these Darwinian methods in the field of psychology is then historically tracked. Two American psychologists – Antoinette Feleky and Otto Klineberg – are cited as the prominent users of recognition experiments and the literary approach respectively. With historical and sometimes quantitative analysis of their original data, the research uncovers reasons for the prosperity of the recognition experiments and the decline of the literary approach in that period; and demonstrates the ideological transition in the expressional science: from physiological doctrine to the purely psychological approach with more cultural concerns

Grounding Language Model with Chunking-Free In-Context Retrieval

This paper presents a novel Chunking-Free In-Context (CFIC) retrieval approach, specifically tailored for Retrieval-Augmented Generation (RAG) systems. Traditional RAG systems often struggle with grounding responses using precise evidence text due to the challenges of processing lengthy documents and filtering out irrelevant content. Commonly employed solutions, such as document chunking and adapting language models to handle longer contexts, have their limitations. These methods either disrupt the semantic coherence of the text or fail to effectively address the issues of noise and inaccuracy in evidence retrieval. CFIC addresses these challenges by circumventing the conventional chunking process. It utilizes the encoded hidden states of documents for in-context retrieval, employing auto-aggressive decoding to accurately identify the specific evidence text required for user queries, eliminating the need for chunking. CFIC is further enhanced by incorporating two decoding strategies, namely Constrained Sentence Prefix Decoding and Skip Decoding. These strategies not only improve the efficiency of the retrieval process but also ensure that the fidelity of the generated grounding text evidence is maintained. Our evaluations of CFIC on a range of open QA datasets demonstrate its superiority in retrieving relevant and accurate evidence, offering a significant improvement over traditional methods. By doing away with the need for document chunking, CFIC presents a more streamlined, effective, and efficient retrieval solution, making it a valuable advancement in the field of RAG systems

Targeting cancer-related inflammation with non-steroidal anti-inflammatory drugs: Perspectives in pharmacogenomics

Inflammatory processes are essential for innate immunity and contribute to carcinogenesis in various malignancies, such as colorectal cancer, esophageal cancer and lung cancer. Pharmacotherapies targeting inflammation have the potential to reduce the risk of carcinogenesis and improve therapeutic efficacy of existing anti-cancer treatment. Non-steroidal anti-inflammatory drugs (NSAIDs), comprising a variety of structurally different chemicals that can inhibit cyclooxygenase (COX) enzymes and other COX-independent pathways, are originally used to treat inflammatory diseases, but their preventive and therapeutic potential for cancers have also attracted researchers’ attention. Pharmacogenomic variability, including distinct genetic characteristics among different patients, can significantly affect pharmacokinetics and effectiveness of NSAIDs, which might determine the preventive or therapeutic success for cancer patients. Hence, a more comprehensive understanding in pharmacogenomic characteristics of NSAIDs and cancer-related inflammation would provide new insights into this appealing strategy. In this review, the up-to-date advances in clinical and experimental researches targeting cancer-related inflammation with NSAIDs are presented, and the potential of pharmacogenomics are discussed as well

Lemur: Harmonizing Natural Language and Code for Language Agents

We introduce Lemur and Lemur-Chat, openly accessible language models optimized for both natural language and coding capabilities to serve as the backbone of versatile language agents. The evolution from language chat models to functional language agents demands that models not only master human interaction, reasoning, and planning but also ensure grounding in the relevant environments. This calls for a harmonious blend of language and coding capabilities in the models. Lemur and Lemur-Chat are proposed to address this necessity, demonstrating balanced proficiencies in both domains, unlike existing open-source models that tend to specialize in either. Through meticulous pre-training using a code-intensive corpus and instruction fine-tuning on text and code data, our models achieve state-of-the-art averaged performance across diverse text and coding benchmarks among open-source models. Comprehensive experiments demonstrate Lemur's superiority over existing open-source models and its proficiency across various agent tasks involving human communication, tool usage, and interaction under fully- and partially- observable environments. The harmonization between natural and programming languages enables Lemur-Chat to significantly narrow the gap with proprietary models on agent abilities, providing key insights into developing advanced open-source agents adept at reasoning, planning, and operating seamlessly across environments. https://github.com/OpenLemur/Lemu

Effect of different binders on the electrochemical performance of metal oxide anode for lithium-ion batteries

When testing the electrochemical performance of metal oxide anode for lithium-ion batteries (LIBs), binder played important role on the electrochemical performance. Which binder was more suitable for preparing transition metal oxides anodes of LIBs has not been systematically researched. Herein, five different binders such as polyvinylidene fluoride (PVDF) HSV900, PVDF 301F, PVDF Solvay5130, the mixture of styrene butadiene rubber and sodium carboxymethyl cellulose (SBR+CMC), and polyacrylonitrile (LA133) were studied to make anode electrodes (compared to the full battery). The electrochemical tests show that using SBR+CMC and LA133 binder which use water as solution were significantly better than PVDF. The SBR+CMC binder remarkably improve the bonding capacity, cycle stability, and rate performance of battery anode, and the capacity retention was about 87% after 50th cycle relative to the second cycle. SBR+CMC binder was more suitable for making transition metal oxides anodes of LIBs

Adverse Events Associated With Anti-IL-23 Agents: Clinical Evidence and Possible Mechanisms

BackgroundAnti-interleukin (IL)-23 agents are widely used for autoimmune disease treatment; however, the safety and risks of specific symptoms have not been systematically assessed.ObjectivesThe aim of this study was to summarize the characteristics and mechanisms of occurrence of five immunological and non-immunological adverse events caused by different anti-IL-23 agents.MethodsThe Cochrane Library, EMBASE, PubMed, and Web of Science databases were searched for eligible randomized clinical trials published from inception through May 1, 2020. Randomized clinical trials that reported at least one type of adverse event after treatment were included, regardless of sex, age, ethnicity, and diagnosis. Two investigators independently screened and extracted the characteristics of the studies, participants, drugs, and adverse event types. The Cochrane Handbook was used to assess the methodological quality of the included randomized clinical trials. Heterogeneity was assessed using the I2 statistic. Meta-regression was applied to determine the sources of heterogeneity, and subgroup analysis was used to identify the factors contributing to adverse events.ResultsForty-eight studies were included in the meta-analysis, comprising 25,624 patients treated with anti-IL-23 agents. Serious immunological or non-immunological adverse events were rare. Anti-IL-12/23-p40 agents appeared to cause adverse events more easily than anti-IL-23-p19 agents. The incidence of cancer did not appear to be related to anti-IL-23 agent treatment, and long-term medication could lead to mental diseases. The prevention of complications should be carefully monitored when administered for over approximately 40 weeks to avoid further adverse reactions, and the incidence of infection was the highest among general immunological adverse events.ConclusionsThe application of anti-IL-23 agents induced a series of immunological and non-immunological adverse events, but these agents tend to be well-tolerated with good safety profiles

Implementation of a multi-agent based power market simulator

published_or_final_versionElectrical and Electronic EngineeringMasterMaster of Philosoph