Effective Area Research Articles

Dividing active and passive particles in nonuniform nutrient environments

To explore the coupling between a growing population of microorganisms such as E. coli and a nonuniform nutrient distribution, we formulate a minimalistic model. It consists of active Brownian particles that divide and grow at a nutrient-dependent rate following the Monod equation. The nutrient concentration obeys a diffusion equation with a consumption term and a point source. In this setting the heterogeneity in the nutrient distribution can be tuned by the diffusion coefficient. In particle-based simulations, we demonstrate that passive and weakly active particles form proliferation-induced clusters when the nutrient is localized, without relying on further mechanisms such as chemotaxis or adhesion. In contrast, strongly active particles disperse in the whole system during their lifetime and no clustering is present. The steady population is unaffected by activity or nonuniform nutrient distribution and only determined by the ratio of nutrient influx and bacterial death. However, the transient dynamics strongly depends on the nutrient distribution and activity. Passive particles in almost uniform nutrient profiles display a strong population overshoot, with clusters forming all over the system. In contrast, when slowly diffusing nutrients remain centred around the source, the bacterial population quickly approaches the steady state due to its strong coupling to the nutrient. Conversely, the population overshoot of highly active particles becomes stronger when the nutrient localisation increases. We successfully map the transient population dynamics onto a uniform model where the effect of the nonuniform nutrient and bacterial distributions are rationalized by two effective areas.

Machine learning-assisted prediction and optimization of solid oxide electrolysis cell for green hydrogen production

The solid oxide electrolysis cell (SOEC) holds great promise to efficiently convert renewable energy into hydrogen. However, traditional modeling methods are limited to a specific or reported SOEC system. Therefore, four machine learning models are developed to predict the performance of SOEC processes of various types, operating parameters, and feed conditions. The impact of these features on the SOEC's outputs is explained by the Shapley additive explanations and partial dependency plot analyses. The preferred model is integrated with a genetic algorithm to determine the optimal values of each input feature. Results show the improved extreme gradient enhanced regression (XGBoost) algorithm is the core of the machine learning model of the process since it has the highest R2 (> 0.95) in the three outputs. The electrolytic cell descriptors have a greater impact on the system performance, contributing up to 54.5%. The effective area, voltage, and temperature are the three most influential factors in the SOEC system, contributing 21.6%, 16.6%, and 13.0% to its performance. High temperature, high pressure, and low effective area are the most favorable conditions for H2 production rate. After conducting multi-objective optimization, the optimal current intensity and hydrogen production rate were determined to be 1.61 A/cm2 and 1.174 L/(h·cm2).

The study of input power of an underwater free-damping ribbed plate in statistical energy analysis

To study the vibration characteristics of the free-damping ribbed plate with fluid load under point force excitation in statistical energy analysis (SEA), the theoretical model of input power calculation was established in this research. The simulational results from SEA commercial software validated the correctness of the proposed theoretical model. As inferred from the theoretical model, the added damping layer and ribs significantly affect the effective bending stiffness and area density, and the added fluid load only affects the effective area density. These effective parameters will affect the input power of the fluid-loaded free-damping ribbed plate, resulting in increased input power as a function frequency. The research in this paper could provide theoretical guidance on the vibroacoustic analysis of underwater complex ship structures.

Transforming into a Learning Health System: A Quality Improvement Initiative.

The Institute of Medicine introduced the Learning Healthcare System concept in 2006. The system emphasizes quality, safety, and value to improve patient outcomes. The Bellevue Clinic and Surgical Center is an ambulatory surgical center that embraces continuous quality improvement to provide exceptional patient-centered care to the pediatric surgical population. We used statistical process control charts to study the hospital's electronic health record data. Over the past 7 years, we have focused on the following areas: efficiency (surgical block time use), effectiveness (providing adequate analgesia after transitioning to an opioid-sparing protocol), efficacy (creating a pediatric enhanced recovery program), equity (evaluating for racial disparities in surgical readmission rates), and finally, environmental safety (tracking and reducing our facility's greenhouse gas emissions from inhaled anesthetics). We have seen improvement in urology surgery efficiency, resulting in a 37% increase in monthly surgical volume, continued adaptation to our opioid-sparing protocol to further reduce postanesthesia care unit opioid administration for tonsillectomy and adenoidectomy cases, successful implementation of an enhanced recovery program, continued work to ensure equitable healthcare for our patients, and more than 85% reduction in our facility's greenhouse gas emissions from inhaled anesthetics. The Bellevue Clinic and Surgical Center facility is a living example of a learning health system, which has evolved over the years through continued patient-centered QI work. Our areas of emphasis, including efficiency, effectiveness, efficacy, equity, and environmental safety, will continue to impact the community we serve positively.

Prosthesis-patient mismatch in transcatheter and surgical aortic valve replacement.

Prosthesis-patient mismatch (PPM) occurs when the effective orifice area (EOA) of a normally functioning prosthetic valve is too small in relation to the patient's body size. The effect of PPM on outcomes and valve durability have gained credibility, making this an important possibly preventable risk factor. Transcatheter aortic valve replacement (TAVR) generally has a lower incidence of PPM than surgical aortic valve replacement (SAVR). Current surgical literature and randomized trials show an association between severe PPM and mortality in patients with SAVR but there is less evidence for an association with TAVR. Differences in the incidence of PPM may be related to the methods and cutoffs for measuring mismatch. This review will discuss the current state of field and propose standardization of measurement methods which may more accurately risk stratify patients.

A mesoporous magnetothermal nanopomegranate with acid-tolerant hierarchical structure for remote controlled drug delivery

Developing acid-tolerant magnetothermal nanoplatform with robust drug loading capacity for remote controlled drug release is challenging in the harsh acid environment of stomach. Herein, a nanopomegranate-type magnetothermal controllable drug release platform (FeCo@G@MSN), consisted of magnetothermal convertor (graphene-isolated FeCo nanocrystal core, FeCo@G) and drug reservoir (mesoporous silica, MSN), with acid-tolerant hierarchical structure was developed. Benefiting from the acid tolerance of graphene and MSN, FeCo@G@MSN was stable in 1 M hydrochloric acid for more than 12 h. The nanopomegranate-type hierarchical structure endowed FeCo@G@MSN with high saturation magnetization (114.9 emu/g) to generate a magnetothermal effect and large specific surface area (293.7 m2/g) to provide ample space for drug loading. As a proof of concept, a heat-triggered nitric oxide (NO) precursor was loaded, and NO were controlled released by breaking of S-NO bonds through localized heat derived from magnetothermal effect of FeCo@G, resulting in an inhibition effect towards Helicobacter pylori. A chemotherapeutic drug (doxorubicin, DOX) was also loaded and controlled released by breaking of hydrogen bonds between silica and DOX under remote an alternating magnetic field, thus exhibiting an inhibition effect towards gastric cancer cells. This work provides an efficient strategy to exploit magnetothermal controlled drug release platform and offers inspiration for the treatment of gastric diseases.

Development of BaMnO3 nanoparticles embedded on rGO nanosheets via facile hydrothermal route to improve water oxidation

In light of environmental problems such as the depletion of hydrocarbon resources and global warming, the use of environment-friendly power production has become crucial nowadays. Hydrogen can serve as a globally friendly energy source because the byproduct of hydrogen combustion is only water. By a hydrothermal approach, we synthesized barium manganese oxide (BaMnO3) embedded on reduced graphene oxide (rGO) as a competent electrocatalyst for OER. We utilized X-ray diffraction (XRD), scanning electron microscope (SEM), energy dispersive x-rays (EDX), Brunauer Emmette Teller (BET) and Raman to determine the crystal structure, morphology, elemental composition, surface area and lattice phenomena of the fabricated rGO/BaMnO3 nanocomposite. The BaMnO3 agglomerated nanoparticles were incorporated into the mesoporous hollow carbon nanosheets to form amorphous textured embedded rGO/BaMnO3. This enhanced the intrinsic reactivity of rGO/BaMnO3 nanocomposite for the oxygen evolution reaction (OER) in addition to increasing the effective surface area of the electrolyte. The electrochemical outcomes demonstrate that synthesized nanocomposite exhibited an impressive Tafel slope (36 mV dec−1), lowest overpotential (202 mV) and remarkable stability over 35 h. Therefore, the fabricated nanocomposite displayed exceptional efficiency in OER process as well as for numerous other future applications.

Optimizing Ion Optical Design for Laser Ablation Source in Mass Spectrometry

The study focuses on optimizing a Laser Ablation Source (LAS) for use in mass spectrometry, particularly aiming to enhance transmission of ions and and determination of isotopic compositions in diverse matrices at TRIUMF’s Ion Trap for Atomic and Nuclear Science (TITAN). Critical variables affecting mass spectrometer resolution, such as ion kinetic energy distribution and ion transport are optimized through LAS. The paper explores the importance of consistent initial conditions, ion transport efficiency, and ion capture for accurate and reproducible measurements. Using SIMION software, we optimized ion optical design to tackle challenges like collimating ions travelling off-axis and mass filtering. A significant part of the study is dedicated to ion optic design to enable low abundance measurement of ions of interest (e.g., 10 ions of interest out of 1014 total ions). Techniques like high voltage switching and beam shaping were explored, and the final design aims for high transport efficiency and a 4 mm effective target scan area with maximum transport efficiency. The integration of LAS with a Multiple-Reflection Time-Of-Flight Mass Spectrometer (MR-TOF-MS) is expected to yield an analytical tool with high spatial resolution and transport efficiency for isotope abundance measurement.

DCT Transcriptional and Structural Remodeling: Impacts on Magnesium Handling

Loss of activity of the NaCl Cotransporter (NCC) in Gitelman syndrome and with chronic thiazide treatment results in hypomagnesemia but the underlying mechanism remains unresolved. The prevailing hypothesis is that it results indirectly from distal convoluted tubule (DCT) atrophy lowering magnesium (Mg)-reabsorbing capacity by this segment. We tested the hypothesis that NCC inhibition directly disrupts a cellular mechanism related to Mg handling independent of DCT atrophy. We used the NCC-Cre+−/−- INTACT+/- mouse line to allow enrichment of DCT nuclei via Cre-dependent GFP expression in DCT nuclei. Eight- to 10-week-old male mice were given 50 mg/kg/day metolazone (MTZ) orally in food for 4 days; littermate controls receiving only vehicle. After nuclei isolation, GFP+ events (DCT nuclei) were sorted by fluorescence assisted nuclei sorting. Purified DCT nuclei were sequenced using 10X Chromium controller. Reads were then analyzed using a standard transcriptomic bioinformatics pipeline with Seurat. Tubule morphometrics using optical tissue clearing was performed on kidneys from animals receiving the same treatment. MTZ-treated mice had lower plasma Mg compared to controls recapitulating thiazide-induced hypomagnesemia. Our snRNAseq dataset containing 45,953 cells from 3 MTZ-treated and 3 control mice showed clear separation into early DCT (DCT1) and late DCT (DCT2) based on canonical segment markers. Gene expression analysis showed the DCT1 contained a magnesium cassette consisting of known magnesiotropic genes Trpm6, Trpm7, Egf, Umod, Prox1, Fxyd2, Cnnm2, and Slc41a3 so we focused subsequent analyses on DCT1. NCC inhibition caused DCT1 degeneration as indicated by lower mean DCT1 score of DCT1 cells and a greater proportion of DCT1 cells with low differentiation state in the MTZ group. Similarly, MTZ-treated samples had lower DCT1/DCT2 cell proportion in our snRNAseq dataset and morphometrics revelead significantly shorter DCT1 tubules implying that the degeneration process eventually leads to DCT1 atrophy. Using the aggregate expression of the magnesium cassette genes, we computationally defined a Mg score as a surrogate marker for Mg reabsorption capacity for each individual cells. The average Mg score was lower in the MTZ-treated group compared to the controls. Our data supports the long-standing hypothesis that hypomagnesemia is a secondary consequence of the loss of effective surface area for Mg reabsorption. Additionally, we uncovered that even at the single cell level, the Mg handling capacity of the cell decreases as a result of NCC inhibition implying that a disruption in sodium reabsorption disrupts expression of the Mg reabsorption machinery. NIH DK51496, NIH DK054983, NIDDK DK132066, VA 1I01BX002228, LeDucq Foundation, DOST-PCHRD-ASTHRDP. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

خوارزمية فصيلة ميركات المعدلة لتعدين القواعد الرابطة

تشكل قواعد جمعيات التعدين (ARM) إحدى تقنيات التنقيب عن البيانات المهمة. أصبحت الأساليب الكلاسيكية التي عمل عليها الباحثون سابقًا غير فعالة للتعامل مع النمو المطرد لقواعد البيانات ، مما دفعنا إلى استخدام عملية التعدين لقواعد الارتباط القائمة على ميتاهيورستك، وفي عملنا سنستخرج جميع القواعد الصحيحة ، و التعدين لا يقتصر على القواعد عالية الجودة. ذكاء السرب يعتبر إحدى هذه الأساليب المعتمدة. في هذه الورقة، تم اقتراح تعديل فصيلة ميركات لتعدين قواعد الجمعية (MCC-ARM). تعتمد الخوارزمية المقترحة بشكل أساسي على خوارزمية فصيلة ميركات (MCA). أكبر فائدة هي تنوع الحلول المرشحة في MCA. سنقوم في عملنا بتمثيل القاعدة باستخدام طريقتين مستعارتين من الخوارزمية الجينية، في المجموعة الأولى، تشير كل مجموعة من القواعد إلى كائن في المجتمع و التي تدعى طريقة بيتسبرغ، بينما تشير القاعدة الثانية إلى كائن في المجتمع و التي تدعى طريقة ميشيغان. تهدف الخوارزمية المقترحة إلى فحص أكبر عدد ممكن من قواعد الارتباط الصحيحة. ما يسمى بخوارزمية تتبع نهج تحديد منطقة البحث الفعالة، والتي تعتمد على آلية عشوائية رئيسية لقيادة الخوارزمية في استخراج القواعد البديلة وتجنب الحلول الكلية من الاسترشاد بنفس القاعدة، وهذا أدى إلى قدر كبير من التنوع. بالإضافة إلى ذلك، يستخدم MCC-ARM طريقة التكثيف في عملية البحث المتجاورة لمنع الخوارزمية من الوقوع في الوضع المحلي. لإثبات كفاءتها، سنطبقها في أربع مجموعات بيانات موثوقة (مثل حديقة الحيوان، والائتمان الألماني، والورم الأساسي والشطرنج). لقد حصل التحسين الذي أحدثته الخوارزمية المقترحة على عاملين حاسمين ، وهما عدد القواعد الصحيحة وقيمة لياقة الجودة.

Impacts of Land use Land cover dynamics on Ecosystem services in maze national park and its environs, southwestern Ethiopia

This study investigated the impacts of LULC changes on selected ecosystem services in Maze National Park (MzNP) and its environs in southwestern Ethiopia. Landsat images from 1985, 2005, and 2020 were used to examine land use land cover (LULC) changes. Images were classified using the Random Forest (RF) classifier, and their accuracy was computed in QGIS. Ecosystem service values (ESVs) were then estimated using the benefit transfer method employing Ecosystem Service Valuation Database (ESVD) coefficients. Additionally, socioeconomic survey was conducted to understand the local community's perceptions regarding the dynamics of ecosystem services. The findings revealed a significant increase in croplands (103.7 %) and built-up areas (31.32 %), while riverine forests, water bodies, and wooded grasslands declined. The overall ESVs decreased by 20 %, from 2038.42 million USD in 1985 to 1628.72 million USD in 2020, mainly driven by reductions in riverine forests and wooded grasslands. As for the individual ESVs for the period 1985 to 2020, only food production increased by 0.7 million USD, while water supply, climate regulation, raw materials, and recreation and tourism declined by 180.35, 2.67, 45.72, and 481.62 million USD, respectively. The coefficient of sensitivity ranged from 0.01 to 0.94, <1, revealed that our estimates are relatively robust. Ecosystem services such as grazing, recreation, wild food, and firewood are highly valued by local residents, but they are declining over time due to environmental degradation and restrictions on access to the park. Thus, understanding LULC changes and their impacts on ESVs can help decision-makers design effective protected area management plans and reduce potential conflicts over resource uses. Further investigations are suggested to more accurately quantify ESVs using high resolution satellite imageries and different valuation methods.

Evaluation of effective cross-area of reinforced concrete wall considering chloride diffusion using ANN

Reinforced concrete structures are subject to exposure to chloride ions in the air, leading to chloride penetration, and carbonation attacks resulting from exposure to carbon dioxide. This chemical degradation process induces corrosion of reinforcing bars within concrete, significantly impacting durability. Structures situated in coastal areas, such as nuclear power plants, are particularly susceptible to rapid chloride penetration due to the high chloride concentration in the air. This study utilizes existing experimental data to forecast the chloride diffusion coefficient employing artificial neural network (ANN technology). The total number of experimental data was 535 gathered from 18 papers. Through analysis of the chloride coefficient and predicted degradation depth, the effective cross-sectional area of concrete is examined, and the deterioration of wall performance is forecasted.

ПРОФЕСІЙНА ПІДГОТОВКА ВЧИТЕЛЯ ПОЧАТКОВИХ КЛАСІВ ДО ВИХОВНОЇ РОБОТИ В НОВІЙ УКРАЇНСЬКІЙ ШКОЛИ

The article based on a holistic analysis of the theory and practice of professional education, describes the theoretical and methodological principles of training perspective primary school teachers to manage and implement educational work with primary school pupils in the New Ukrainian School. It has been established that in the context of the modernisation of the system of higher pedagogical education in Ukraine, there are significant shifts in the directions, content, and essence of primary school teacher training. The author proves that in the process of studying professional disciplines by future primary school teachers in a higher pedagogical education institution, there is an effective formation and development of their educational competence (professional thinking, emotional intelligence, creative potential, assimilation of educational values and value orientations, experience of social adaptation and socialisation of a growing personality to the challenges and threats of modern Ukrainian society). The elements of such competence are as follows: the knowledge, skills, and practical abilities, experience in designing effective areas of childhood education, communication skills, and abilities to implement, analyse and predict the effectiveness of pedagogical interaction of all participants in the educational process in primary school based on child-centredness, cooperation, co-creation, formed autonomy and responsibility by developing pedagogical thinking, creative activity, and independent improvement of the level of organisation of the educational process in primary school. The article defines and describes the current leading principles of organising and conducting professional training of perspective primary school teachers in the implementation of the strategy of creating an educational process in primary school. There has been highlighted and defined the essence of the basic requirements concerning the content of professional training of perspective primary school teachers for the organisation of educational work in the New Ukrainian School.

Development of a low-pressure Multi-Mesh THGEM detector for fission experiments at FRIB

A small-area imaging detector prototype for position measurement of fission fragments produced in low energy heavy-ion reactions is presented in this study. The detector readout is equipped with a 2-dimensional, position-sensitive gaseous avalanche readout based on the novel Multi-Mesh Thick-GEM (MM-THGEM), and is coupled to a delay-line board for particle localization. The prototype has an effective area of 10 × 10 cm2 and is operated in isobutane at low pressure (7–10 Torr). We present and discuss a series of systematic evaluation tests performed by irradiating the detector with α-particles and fission fragments emitted by small-rate sources (241Am, 249Cf and 252Cf). Position and time resolutions of about 0.42 mm and 1 ns were achieved, respectively. This work serves as a benchmark for the development of a large-scale array of detectors for experiments with fission and fission-like reaction products at the Facility for Rare Isotope Beams (FRIB).

Two-dimensional quantum droplets in binary quadrupolar condensates

We study the stability and characteristics of two-dimensional (2D) quasi-isotropic quantum droplets (QDs) of fundamental and vortex types, formed by binary Bose–Einstein condensate with magnetic quadrupole–quadrupole interactions (MQQIs). The magnetic quadrupoles are built as pairs of dipoles and antidipoles polarized along the x-axis. The MQQIs are induced by applying an external magnetic field that varies along the x-axis. The system is modeled by the Gross–Pitaevskii equations including the MQQIs and Lee-Huang-Yang correction to the mean-field approximation. Stable 2D fundamental QDs and quasi-isotropic vortex QDs with topological charges S⩽4 are produced by means of the imaginary-time-integration method for configurations with the quadrupoles polarized parallel to the system’s two-dimensional plane. Effects of the norm and MQQI strength on the QDs are studied in detail. Some results, including an accurate prediction of the effective area, chemical potential, and peak density of QDs, are obtained in an analytical form by means of the Thomas-Fermi approximation. Collisions between moving QDs are studied by means of systematic simulations.

A3COSMOS and A3GOODSS: Continuum source catalogues and multi-band number counts

Context. Galaxy submillimetre number counts are a fundamental measurement in our understanding of galaxy evolution models. Most early measurements are obtained via single-dish telescopes with substantial source confusion, whereas recent interferometric observations are limited to small areas. Aims. We used a large database of ALMA continuum observations to accurately measure galaxy number counts in multiple (sub)millimetre bands, thus bridging the flux density range between single-dish surveys and deep interferometric studies. Methods. We continued the Automated Mining of the ALMA Archive in the COSMOS Field project (A3COSMOS) and extended it with observations from the GOODS-South field (A3GOODSS). The database consists of ∼4000 pipeline-processed continuum images from the public ALMA archive, yielding 2050 unique detected sources, including sources with and without a known optical counterpart. To infer galaxy number counts, we constructed a method to reduce the observational bias inherent to targeted pointings that dominate the database. This method comprises a combination of image selection, masking, and source weighting. The effective area was calculated by accounting for inhomogeneous wavelengths, sensitivities, and resolutions and for the spatial overlap between images. We tested and calibrated our method with simulations. Results. We derived the number counts in a consistent and homogeneous way in four different ALMA bands covering a relatively large area. The results are consistent with number counts retrieved from the literature within the uncertainties. In Band 7, at the depth of the inferred number counts, ∼40% of the cosmic infrared background is resolved into discrete sources. This fraction, however, decreases with increasing wavelength, reaching ∼4% in Band 3. Finally, we used the number counts to test models of dusty galaxy evolution, and find a good agreement within the uncertainties. Conclusions. By continuing the A3COSMOS and A3GOODSS archival effort, we obtained the deepest archive-based (sub)millimetre number counts measured to date over such a wide area. This database proves to be a valuable resource that, thanks to its substantial size, can be used for statistical analyses after having applied certain conservative restrictions.

Sublimation and oxidation measurements of graphite and carbon black at high temperatures in a shock tube using absorption imaging and thermal emission

Surface mass loss rates due to sublimation and oxidation at temperatures of 3000–7000 K have been measured in a shock tube for graphite and carbon black (CB) particles. Diagnostics are presented for measuring surface mass loss rates by diffuse backlit illumination extinction imaging and thermal emission. The surface mass loss rate is found by regression fitting extinction and emission signals with an independent spherical primary particle assumption. Measured graphite sublimation and oxidation rates are reported to be an order of magnitude greater than CB sublimation and oxidation rates. It is speculated that the difference between CB and graphite surface mass loss rates is largely due to the primary particle assumption of the presented technique which misrepresents the effective surface area of an aggregate particle where primary particles overlap and shield inner particles. Measured sublimation rates are compared to sublimation models in the literature, and it is seen graphite shows fair agreement with the models while CB underestimates, likely a result of the particle shielding affect not being considered in the sublimation model.

Nanocone-substrated BiVO4-Mo/MOFs photoanodes for highly efficient photoelectrochemical water splitting

Photoelectrochemical (PEC) performance of photoanode is limited by the cascade-dynamic processes, mainly including light absorption, charge separation, and surface reaction. This work adopted a strategy of nanocones modification on FTO substrate (FTO-NC) to enhance light utilization and photoelectrons collection for improved PEC water splitting. Comparative studies showed that FTO-NC enhanced the light scattering, promoting the conversion process of photon to electron/hole and enlarging the effective surface area of BiVO4 for surface reaction. Meanwhile, cooperative Mo-doping and Co-MOF decoration improved the bulk electron transportation in BiVO4, hole migration towards the electrode surface, and accelerated the water oxidation reaction of photogenerated holes. The photocurrent density of FTO-NC/BiVO4-Mo/MOFs reached 3.56 mA cm−2, 6.14 times that of pristine BiVO4. The IPCE of FTO-NC/BiVO4-Mo/MOFs photoanode achieve 60% at 1.23 V vs. RHE, demonstrating a significantly enhanced light utilization performance. This work presents new insight into boosting cascade-dynamic processes through collaborative strategies for highly efficient PEC water-splitting.

Comparison of infiltration of different particle sizes and influencing parameters

The size fractional distribution of indoor and outdoor particles was investigated to understand how particle size, air change rate, building airtightness, and meteorological parameters affect particle infiltration behavior. The experiments were performed for two apartments, one without airtightness intervention and the other after sealing the window gaps. Although the correlation analysis showed that the indoor PM trend was highly dependent on outdoor conditions, different penetration behavior for different particle sizes was noticed. Despite the absence of indoor sources, the size fractional distribution of particles in the indoor and outdoor environment did not follow the same pattern. Moreover, airtightness somehow reduced the envelope effective leakage area and slightly decreased the indoor/outdoor ratio and infiltration factor for all particle sizes; however, it did not affect the relative infiltrability. The highest penetration rates were observed in the size range of 0.3–1.0 μm and the lowest rates were in the 2.5–10 μm range. Although with particles greater than 0.3 μm, the infiltration of fine particles was higher than that of coarse particles, the infiltrability of PM < 0.3 was slightly lower than PM0.3-1.0, probably due to the penetration dominated by the concentration gradient. Particle size, envelope airtightness, and outdoor source were the main factors that governed fractional particle infiltration, overshadowing the effect of meteorological parameters. Furthermore, window airtightness decreased the indoor-outdoor PM correlation, especially for coarser particles. It caused approximately a 1-h lag-time between the indoor and outdoor PM trend, a positive point in case of accidental increase of outdoor levels.

Course Evaluation and Improvement Based on Association Rule Mining in English Online Teaching and Learning

Association rule mining in English online teaching and learning involves the analysis of patterns and relationships within large sets of data to uncover meaningful insights that can enhance the teaching and learning experience. By examining student interactions, performance data, and usage patterns on online learning platforms, educators can identify correlations between different learning activities, student characteristics, and learning outcomes. This paper explores the application of the Frequent Pattern System Modelling Association Rule (FPSMAR) in the realm of online English teaching and learning. FPSMAR offers a data-driven approach to analyzing student interaction data, uncovering meaningful patterns and associations between different elements of the online learning environment and student outcomes. Through the analysis of association rules and frequent patterns, educators gain valuable insights into effective instructional strategies, learning patterns, and areas for improvement. The study presents association rules indicating relationships such as the correlation between multimedia resource usage and high language proficiency or active online discussion participation and enhanced speaking ability. The study reveals association rules indicating strong relationships, such as a correlation coefficient of 0.80 between multimedia resource usage and high language proficiency, or a confidence level of 0.85 indicating enhanced speaking ability through active online discussion participation.