Continually Updating Generative Retrieval on Dynamic Corpora

Generative retrieval has recently been gaining a lot of attention from the research community for its simplicity, high performance, and the ability to fully leverage the power of deep autoregressive models. However, prior work on generative retrieval has mostly investigated on static benchmarks, while realistic retrieval applications often involve dynamic environments where knowledge is temporal and accumulated over time. In this paper, we introduce a new benchmark called STREAMINGIR, dedicated to quantifying the generalizability of retrieval methods to dynamically changing corpora derived from StreamingQA, that simulates realistic retrieval use cases. On this benchmark, we conduct an in-depth comparative evaluation of bi-encoder and generative retrieval in terms of performance as well as efficiency under varying degree of supervision. Our results suggest that generative retrieval shows (1) detrimental performance when only supervised data is used for fine-tuning, (2) superior performance over bi-encoders when only unsupervised data is available, and (3) lower performance to bi-encoders when both unsupervised and supervised data is used due to catastrophic forgetting; nevertheless, we show that parameter-efficient measures can effectively mitigate the issue and result in competitive performance and efficiency with respect to the bi-encoder baseline. Our results open up a new potential for generative retrieval in practical dynamic environments. Our work will be open-sourced.Comment: Work in progres

Cardiometabolic Disease Risk in Normal Weight Obesity and Exercise Interventions for Proactive Prevention

PURPOSE Normal weight obesity (NWO) is characterized by a normal body mass index but a high body fat mass percentage and low skeletal muscle mass, thereby increasing the risk of cardiometabolic dysfunction and morbidity. However, the effects of exercise intervention in reducing the risk of cardiometabolic disease in NWO have not been fully elucidated. Therefore, this review aimed to summarize the potential cardiometabolic disease risk and to provide implications of exercise interventions for the proactive prevention of cardiometabolic disease risk in NWO. METHODS We searched and summarized the literature on the cardiometabolic risk factors in NWO. In addition, we summarized literature investigating the effects of exercise intervention on the cardiometabolic risk factors in NWO. We performed the literature search using PubMed, Web of Science, and Google Scholar databases. RESULTS NWO was associated with increased visceral fat, ectopic fat, oxidative stress, inflammatory cytokines, insulin resistance, dyslipidemia, and subclinical atherosclerosis compared with normal weight lean. NWO requires exercise interventions that induce alterations in body composition, such as decreased body fat percentage and increased muscle mass. Resistance exercise (RE) and high-intensity interval exercise (HIIE) can improve lipid components and alter body composition in NWO. In addition, low-intensity blood flow restriction resistance exercise (BFR-RE) may enhance muscular strength and anaerobic power in NWO. CONCLUSIONS The cardiometabolic disease risk is increased in NWO. We suggest that exercise interventions (RE, HIIE, and BFR-RE) may effectively prevent cardiometabolic disease risk and alter body composition in NWO. As this has potential implications for exercise interventions in NWO, further investigations are needed to find the optimal exercise for proactive prevention of cardiometabolic risk in NWO

Enhanced Electrochemical Performances of Hollow-Structured N-Doped Carbon Derived from a Zeolitic Imidazole Framework (ZIF-8) Coated by Polydopamine as an Anode for Lithium-Ion Batteries

Doping heteroatoms such as nitrogen (N) and boron (B) into the framework of carbon materials is one of the most efficient methods to improve the electrical performance of carbon-based electrodes. In this study, N-doped carbon has been facilely synthesized using a ZIF-8/polydopamine precursor. The polyhedral structure of ZIF-8 and the effective surface-coating capability of dopamine enabled the formation of N-doped carbon with a hollow structure. The ZIF-8 polyhedron served as a sacrificial template for hollow structures, and dopamine participated as a donor of the nitrogen element. When compared to ZIF-8-derived carbon, the HSNC electrode showed an improved reversible capacity of approximately 1398 mAh·g−1 after 100 cycles, with excellent cycling retention at a voltage range of 0.01 to 3.0 V using a current density of 0.1 A·g−1

How Well Do Large Language Models Truly Ground?

Reliance on the inherent knowledge of Large Language Models (LLMs) can cause issues such as hallucinations, lack of control, and difficulties in integrating variable knowledge. To mitigate this, LLMs can be probed to generate responses by grounding on external context, often given as input (knowledge-augmented models). Yet, previous research is often confined to a narrow view of the term "grounding", often only focusing on whether the response contains the correct answer or not, which does not ensure the reliability of the entire response. To address this limitation, we introduce a strict definition of grounding: a model is considered truly grounded when its responses (1) fully utilize necessary knowledge from the provided context, and (2) don't exceed the knowledge within the contexts. We introduce a new dataset and a grounding metric to assess this new definition and perform experiments across 13 LLMs of different sizes and training methods to provide insights into the factors that influence grounding performance. Our findings contribute to a better understanding of how to improve grounding capabilities and suggest an area of improvement toward more reliable and controllable LLM applications

Dual-Channel P-Type Ternary Dntt-Graphene Barristor

P-type ternary switch devices are crucial elements for the practical implementation of complementary ternary circuits. This report demonstrates a p-type ternary device showing three distinct electrical output states with controllable threshold voltage values using a dual-channel dinaphtho[2,3-b:2\u27,3\u27-f]thieno[3,2-b]-thiophene-graphene barristor structure. to obtain transfer characteristics with distinctively separated ternary states, novel structures called contact-resistive and contact-doping layers were developed. The feasibility of a complementary standard ternary inverter design around 1 V was demonstrated using the experimentally calibrated ternary device model

Detection of EGFR Mutations Using Bronchial Washing-Derived Extracellular Vesicles in Patients with Non-Small-Cell Lung Carcinoma

The detection of epidermal growth factor receptor (EGFR) mutation, based on tissue biopsy samples, provides a valuable guideline for the prognosis and precision medicine in patients with lung cancer. In this study, we aimed to examine minimally invasive bronchial washing (BW)-derived extracellular vesicles (EVs) for EGFR mutation analysis in patients with lung cancer. A lab-on-a-disc equipped with a filter with 20-nm pore diameter, Exo-Disc, was used to enrich EVs in BW samples. The overall detection sensitivity of EGFR mutations in 55 BW-derived samples was 89.7% and 31.0% for EV-derived DNA (EV-DNA) and EV-excluded cell free-DNA (EV-X-cfDNA), respectively, with 100% specificity. The detection rate of T790M in 13 matched samples was 61.5%, 10.0%, and 30.8% from BW-derived EV-DNA, plasma-derived cfDNA, and tissue samples, respectively. The acquisition of T790M resistance mutation was detected earlier in BW-derived EVs than plasma or tissue samples. The longitudinal analysis of BW-derived EVs showed excellent correlation with the disease progression measured by CT images. The EGFR mutations can be readily detected in BW-derived EVs, which demonstrates their clinical potential as a liquid-biopsy sample that may aid precise management, including assessment of the treatment response and drug resistance in patients with lung cancer

A pathogen-derived metabolite induces microglial activation via odorant receptors

Microglia (MG), the principal neuroimmune sentinels in the brain, continuously sense changes in their environment and respond to invading pathogens, toxins, and cellular debris, thereby affecting neuroinflammation. Microbial pathogens produce small metabolites that influence neuroinflammation, but the molecular mechanisms that determine whether pathogen-derived small metabolites affect microglial activation of neuroinflammation remain to be elucidated. We hypothesized that odorant receptors (ORs), the largest subfamily of G protein-coupled receptors, are involved in microglial activation by pathogen-derived small metabolites. We found that MG express high levels of two mouse ORs, Olfr110 and Olfr111, which recognize a pathogenic metabolite, 2-pentylfuran, secreted by Streptococcus pneumoniae. These interactions activate MG to engage in chemotaxis, cytokine production, phagocytosis, and reactive oxygen species generation. These effects were mediated through the G(alpha s)-cyclic adenosine monophosphate-protein kinase A-extracellular signal-regulated kinase and G(beta gamma)-phospholipase C-Ca2+ pathways. Taken together, our results reveal a novel interplay between the pathogen-derived metabolite and ORs, which has major implications for our understanding of microglial activation by pathogen recognition. Database Model data are available in the PMDB database under the accession number PM0082389.N

The Nordics underdeveloped e-commerce food sector : how can e-commerce strategies be enhanced?

The purpose of this study was to explore ways to enhance the Nordic region's underdeveloped e-commerce food sector strategies to gain a sustainable competitive advantage. The study conducted a literature review covering topics such as e-commerce, business models, food e-tailing strategies, consumer adoption models, and consumer behavior and food consumption in the Nordic region. The study primarily focused on identifying strategies that could enhance the Nordic food market. This study applied a qualitative research method to provide a comprehensive view of the question. The study employed a case analysis through exploratory research. Secondary data was gathered from the case company's annual reports, statistics, news media, and press releases. The study's key findings indicate that case companies mainly focus on the consumer- centric approach and cost leadership strategies. The study identified strategies that can be implemented in the Nordic region to succeed with the direct-to-consumer model and reduce steps and intermediaries in between, including automation, data analytics, artificial intelligence, cashier less stores, and scan and go technology. These approaches can help to reduce costs, increase profitability, and gain sustainable competitive advantage. By implementing the strategies discussed before, retail can move closer to the consumer directly and tackle the challenges in the online grocery retail sector

Epitaxial growth and piezoelectric properties of lithium niobate thin films

With the increasing volume of wireless communication globally, the demand for more sophisticated acoustic filter technologies to prevent signal interference has risen exponentially. A key component of acoustic filters is the piezoelectric film layer, and high-quality films are critical for high filter performance. This report studies the relevant parameters involved in the thin film deposition of a piezoelectric material, LiNbO3. The ideal conditions for the synthesis of a ceramic target are reported to include 3.5% of K2O in the solid-state synthesis process, while a sintering temperature of 900℃ yielded the highest ceramic density. This ceramic target was used to produce thin film samples, among which films deposited on LiTaO3 substrates yielded the highest uniformity. Ultimately, SAW devices were constructed onto the thin film samples and their resonance behavior was compared with SAW devices on bulk LiNbO3 crystals to observe their potential for applications in acoustic filter devices.Bachelor of Engineering (Materials Engineering

Acute effect of exercise intensity on circulating FGF-21, FSTL-1, cathepsin B, and BDNF in young men

Background/objectives: Exercise intensity is potentially an important regulator of various exerkines secretion, but the optimal exercise intensity to increase and sustain exerkines levels, including FGF-21, FSTL-1, cathepsin B, and BDNF in humans, has not yet been fully elucidated. This study aimed to examine the circulating levels of FGF-21, FSTL-1, cathepsin B, and BDNF according to the exercise intensity. Methods: Nine young men (24.0 ± 0.4 years old) performed 4 different experimental sessions at 1-week intervals: 1) a control session (CTRL; no exercise); 2) moderate-intensity continuous exercise (MICE, 55% HRR); 3) vigorous-intensity continuous exercise (VICE, 85% HRR); and 4) high-intensity interval exercise (HIIE, 4 repetitions of a 30-s of “all out” cycling workout followed by a 4-min recovery). Blood samples were collected at 4 different time points (pre-exercise, immediately post-exercise, 30 min post-exercise, and 90 min post-exercise). Results: Serum FGF-21, FSTL-1, cathepsin B, and BDNF were higher in HIIE than in CTRL immediately post-exercise, and FSTL-1, cathepsin B, and BDNF were higher in HIIE than in MICE immediately post-exercise (P < 0.05). The AUC for FGF-21, FSTL-1, and BDNF was higher in HIIE than in CTRL, and the AUC for FGF-21 and BDNF was higher in HIIE than in MICE (P < 0.05). Furthermore, the change in blood lactate was positively correlated with the changes in all exerkines. Conclusions: This study demonstrates that acute HIIE effectively increases serum FGF-21, FSTL-1, cathepsin B, and BDNF compared to MICE. Therefore, the secretion of exerkines, including FGF-21, FSTL-1, cathepsin B, and BDNF may be exercise intensity-dependent