Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models

Machine learning techniques are now integral to the advancement of intelligent urban services, playing a crucial role in elevating the efficiency, sustainability, and livability of urban environments. The recent emergence of foundation models such as ChatGPT marks a revolutionary shift in the fields of machine learning and artificial intelligence. Their unparalleled capabilities in contextual understanding, problem solving, and adaptability across a wide range of tasks suggest that integrating these models into urban domains could have a transformative impact on the development of smart cities. Despite growing interest in Urban Foundation Models~(UFMs), this burgeoning field faces challenges such as a lack of clear definitions, systematic reviews, and universalizable solutions. To this end, this paper first introduces the concept of UFM and discusses the unique challenges involved in building them. We then propose a data-centric taxonomy that categorizes current UFM-related works, based on urban data modalities and types. Furthermore, to foster advancement in this field, we present a promising framework aimed at the prospective realization of UFMs, designed to overcome the identified challenges. Additionally, we explore the application landscape of UFMs, detailing their potential impact in various urban contexts. Relevant papers and open-source resources have been collated and are continuously updated at https://github.com/usail-hkust/Awesome-Urban-Foundation-Models

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The Potential Application of BAs for a Gas Sensor for Detecting SO2 Gas Molecule: a DFT Study

Abstract Different atmospheric gas molecules (e.g., N2, O2, CO2, H2O, CO, NO, NO2, NH3, and SO2) are absorbed on the pristine hexagonal boron arsenide (BAs) through density functional theory calculations. For each gas molecules, various adsorption positions were considered. The most stable adsorption depended on position, adsorption energy, charge transfer, and work function. SO2 gas molecules had the best adsorption energy, the shortest distance for BAs surface in the atmospheric gas molecule, and a certain amount of charge transfer. The calculation of work function was important for exploring the possibilities of adjusting the electronic and optical properties. Our results presented BAs materials can be the potential gas sensor of SO2 with high sensitivity and selectivity

Adiponectin,leptin: focus on low-protein diet supplemented with keto acids in chronic glomerulonephritis with hbv patients

Leptin and adiponectin come from adipose tissue, which can reflect patients' inflammation and status of lipid metabolism. Our study is aim to evaluate the effects of short-term restriction of dietary protein intake (DPI) supplemented with keto acids on nutrition and lipid metabolic disturbance in chronic glomeruloneph-ritis with HBV patients. 17 patients were randomized to either low DPI with keto acid-supplemented (sLP) or low DPI (LP) group for 12 weeks. Low-protein diet (LPD) wasindividualized with protein intake of 0.6–0.8 g/kg/day and keto acids were supplied in 0.1 g/kg/day. Nutritional index other clinical index were measured to evaluate the effect and safey respectively. Serum levels of adiponectin, leptin were determined by ELISA assay.The urine protein excretion level was significantly decreased after 12 weeks in the sLP group compared to the basal value and the LP group (baseline:4.52±1.74,4 weeks:3.19±1.52 g,8 weeks: 2.19±1.1 g,12 weeks:1.64±0.77 g, P<0.05).No difference was observed in serume creatinine, eGFR. Nutritional index was significantly improved at week 12 in the sLP group. 4 week later, Serum leptin of sLP decreased signficangly compared with baseline.[baseline: 4.99 (1.66, 11.44) ng/ml, 4 weeks: 2.29 (1.22,10.2) ng/ml;8 weeks: 1.8(1.18,5.07) ng/ml; 12 weeks: 1.38(0.88,2.55) ng/ml, P<0.05]. The level of serum adiponectin in sLP raised after 8 week compared with the baseline and LP (baselin: 21.60±4.78 pg/ml, 4 weeks: 22.30±4.98 pg/ml, 8 weeks: 24.44±4.43 pg/ml, 12 weeks: 25.11±4.25 pg/ml, P<0.05). In conclusion: Short-term restriction of DPI 0.6–0.8 g of protein/ kg IBW/day is safe, when combined with keto acids, is associated with decreased of urinary protein and improvement of lipid metabolis

Biosequence use cases in mobios sql

The sequencing and annotation of entire genomes has enriched the content of biological sequence databases such that new methods of sequence analysis, comparison and retrieval are being invented and rerun on an increasingly regular basis, generating new and more complete biological information. Examples include full genome comparisons and phylogenetic footprinting. Simple identification of homologous sequences based on BLAST searches is now just one option for querying the contents of a sequence database. These developments underscore the need for more general methods of sequence data management and concomitant programming models that simplify biological discovery. MoBIoS, the Molecular Biological Information System, with mSQL, its set of SQL extensions, is such a system. MoBIoS supports two views of sequence data. Sequences are identified and stored based on long functional units (e.g. genes, proteins and chromosomes). Matching and analysis of sequences exploits distance-based methods comparing short-overlapping substrings. We show that a number of sequence analysis problems can thus be succinctly expressed as mSQL queries.

Analysis of a urinary biomarker panel for obstructive nephropathy and clinical outcomes.

To follow up renal function changes in patients with obstructive nephropathy and to evaluate the predictive value of biomarker panel in renal prognosis.A total of 108 patients with obstructive nephropathy were enrolled in the study; 90 patients completed the follow-up. At multiple time points before and after obstruction resolution, urinary samples were prospectively collected in patients with obstructive nephropathy; the levels of urinary kidney injury molecule-1 (uKIM-1), liver-type fatty acid-binding protein (uL-FABP), and neutrophil gelatinase associated lipocalin (uNGAL) were determined by enzyme-linked immunosorbent assay (ELISA). After 1 year of follow-up, the predictive values of biomarker panel for determining the prognosis of obstructive nephropathy were evaluated.uKIM-1 (r = 0.823), uL-FABP (r = 0.670), and uNGAL (r = 0.720) levels were positively correlated with the serum creatinine level (all P<0.01). The levels of uKIM-1, uL-FABP, and uNGAL were higher in the renal function deterioration group than in the renal function stable group. Cox regression analysis revealed that the 72-h postoperative uKIM-1 level and the preoperative and 72-h postoperative uL-FABP levels were all risk factors for renal function deterioration (all P<0.01). The area under the curve of Receiver Operating Characteristic(ROC-AUCs) of 72-h postoperative uKIM-1, preoperative uL-FABP, and 72-h postoperative uL-FABP were 0.786, 0.911, and 0.875, respectively. When the combined preoperative uKIM-1, uL-FABP, and uNGAL levels or combined 72-h postoperative uKIM-1, uL-FABP, and uNGAL levels were considered, the accuracy of prediction for renal prognosis was markedly increased, with an ROC-AUC of 0.967 or 0.964, respectively. Kaplan-Meier survival curve analysis demonstrated that a 72-h postoperative uKIM-1>96.69 pg/mg creatinine (Cr), a preoperative uL-FABP>154.62 ng/mg Cr, and a 72-h postoperative uL-FABP>99.86 ng/mg Cr were all positively correlated with poor prognosis (all P<0.01).Biomarker panel may be used as a marker for early screening of patients with obstructive nephropathy and for determining poor prognosis

Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices

Abstract In recent years, the increasing penetration level of renewable generation and combined heat and power (CHP) technology in power systems is leading to significant changes in energy production and consumption patterns. As a result, the integrated planning and optimal operation of a multi-carrier energy (MCE) system have aroused widespread concern for reasonable utilization of multiple energy resources and efficient accommodation of renewable energy sources. In this context, an integrated demand response (IDR) scheme is designed to coordinate the operation of power to gas (P2G) devices, heat pumps, diversified storage devices and flexible loads within an extended modeling framework of energy hubs. Subsequently, the optimal dispatch of interconnected electricity, natural gas and heat systems is implemented considering the interactions among multiple energy carriers by utilizing the bi-level optimization method. Finally, the proposed method is demonstrated with a 4-bus multi-energy system and a larger test case comprised of a revised IEEE 118-bus power system and a 20-bus Belgian natural gas system