Robust construction of CeNi quantum dots/Ni-MOL nanosheets for superior photocatalytic CO2 reduction.

Since the intensification of global environmental pollution and energy shortages, photocatalytic CO2 reduction reaction (CO2RR) has emerged as a promising strategy to convert solar energy into clean chemical energy. Herein, we construct a robust and efficient heterojunction construction photocatalyst for CO2RR, composed of the highly reactive CeNi quantum dots (CeNi QDs) and nickel metal-organic layer (Ni-MOL) ultrathin nanosheets. This design facilitates the rapid separation of photogenerated charge carriers, as confirmed by X-ray photoelectron spectroscopy (XPS), photoluminescence spectroscopy (PL) and other characterizations. Mechanistic studies with in situ diffuse reflectance Fourier transform infrared spectroscopy (in situ DRIFTS) and the d-band center calculation indicate that the propensity of photocatalyst for CO2 absorption and CO desorption, leading to high performance and selectivity. The optimized loading amount of CeNi quantum dots and modified structure result in a CO yield of 30.53 mmol·g-1 within 6 h under irradiation. This work not only paves a new and convenient way for developing high-activity quantum dot materials for CO2RR but also exploits novel avenues to fabricate more heterojunction composites for solar energy conversion.

Smoke and NOx emission characteristics of in-use construction machinery base on substantial field measurement: A case study in Beijing, China.

To understand the smoke level and NOx emission characteristics of in-use construction machinery in Beijing, we selected 905 construction machines in Beijing from August 2022 to April 2023 to monitor the emission level of smoke and NOx. The exhaust smoke level and excessive emission situation of different machinery types were identified, and their NOx emission levels were monitored according to the free acceleration method. We investigated the correlation of NOx and smoke emission, and proposed suggestions for controlling pollution discharge from construction machinery in the future. The results show that the exhaust smoke level was 0-2.62 m-1, followed a log-normal distribution (µ = -1.73, δ = 1.09, R2 = 0.99), with a 5.64% exceedance rate. Differences were observed among machinery types, with low-power engine forklifts showing higher smoke levels. The NOx emission range was 71-1516 ppm, followed a normal distribution (µ = 565.54, δ = 309.51, R2 = 0.83). Differences among machinery types were relatively small. Engine rated net power had the most significant impact on NOx emissions. Thus, NOx emissions from construction machinery need further attention. Furthermore, we found a weak negative correlation (p < 0.05) between the emission level of smoke and NOx, that is the synergic emission reduction effect is poor, emphasizing the need for NOx emission limits. In the future, the oversight in Beijing should prioritize phasing out China Ⅰ and China Ⅱ machinery, and monitor emissions from high-power engine China Ⅲ machinery.

Measurements of dust and respirable crystalline silica during indoor demolition and renovation.

Increased focus on renovating and maintaining the existing building stock is an integral part of the circular economy, however this might pose challenges to workers health. The aim of this study was to assess the renovation workers' exposure to inhalable dust, thoracic dust, respirable dust, and respirable crystalline silica (RCS). Personal aerosol samples were collected as full shift samples from 92 workers to a total of 407 samples. Fourteen locations around Oslo, Norway was visited for multiple days with repeated measurements of the same individual. Particulate matter from 3 aerosol fractions, respirable, thoracic, and inhalable, were analyzed gravimetrically, and the respirable fraction was analyzed for RCS by NIOSH 7500 method for X-ray diffraction (XRD) with low temperature plasma ashing sample preparation. The total measured concentrations of respirable dust (n = 192) had a geometric mean (GM) of 0.88 mg/m3, RCS concentrations (n = 182) had a GM of 0.040 mg/m3, thoracic dust (n = 131) had GM 2.4 mg/m3, and inhalable dust (n = 84) had a GM of 8.5 mg/m3. The maximum measured concentrations were 29 mg/m3, 3.2 mg/m3, 65 mg/m3, and 163 mg/m3, respectively. Workdays involving tasks such as mechanical demolition and clearing out demolished materials led to the highest exposure levels of both dust and RCS. However, other workers at the renovation sites were indirectly exposed to a considerable amount of RCS. This study revealed substantial exposure to both RCS and dust during renovation, and protective measures are warranted to reduce exposure levels in the industry.

Microbial community composition and co-occurrence network analysis of the rhizosphere soil of the main constructive tree species in Helan Mountain of Northwest China.

To understand the microbial diversity and community composition within the main constructive tree species, Picea crassifolia, Betula platyphylla, and Pinus tabuliformis, in Helan Mountain and their response to changes in soil physicochemical factors, a high throughput sequencing technology was used to analyze the bacterial and fungal diversity and community structure. RDA (Redundancy Analysis) and Pearson correlation analysis were used to explore the influence of soil physicochemical factors on microbial community construction, and co-occurrence network analysis was conducted on the microbial communities. The results showed that the fungal and bacterial diversity was highest in B. platyphylla, and lowest in P. crassifolia. Additionally, the fungal/bacterial richness was greatest in the rhizosphere soils of P. tabuliformis and B. platyphylla. RDA and Pearson correlation analysis revealed that NN (nitrate nitrogen) and AP (available phosphorus) were the main determining factors of the bacterial community, while NN and SOC (soil water content) were the main determining factors of the fungal community. Pearson correlation analysis between soil physicochemical factors and the alpha diversity of the microbial communities revealed a significant positive correlation between pH and the bacterial and fungal diversity, while SOC, TN (total nitrogen), AP, and AN (available nitrogen) were significantly negatively correlated with the bacterial and fungal diversity. Co-occurrence network analysis revealed that the soil bacterial communities exhibit richer network nodes, edges, greater diversity, and greater network connectivity. Indicating that bacterial communities exhibit more complex and stable interaction patterns in soil. This study reveals the complex interactive relationship between microbial communities and soil physicochemical factors in forest ecosystems. By analyzing the response of rhizosphere microbial communities of major tree species in Helan Mountain to nutrient dynamics and pH changes, we can deepen our understanding of the role of microorganisms in regulating ecosystem functions and provide theoretical basis for soil improvement and ecological restoration strategies.

A survey of keys for the identification of newly described insect genera: recommendations for authors, reviewers, editors, and publishers.

Large numbers of new taxa are described annually and while there is a great need to make them identifiable, there seems little consistency in how this might be facilitated. 427 papers published in 2021 and 2022 were surveyed, which described 587 new insect genera. Only 136 of these papers included keys, and these allowed the identification of 233 of the new genera (31.9% of papers and 39.7% of the new genera). The proportion of papers that included a key varied significantly among insect orders but not among the handful of journals wherein the bulk of the new genera were described. Overall, for 17 key-related variables assessed in a binary fashion (optimal vs suboptimal), the average key had almost six criteria that were scored as being suboptimal. For example, less than one-fifth facilitated retracing and less than 12% had illustrated keys where the images were conveniently located close to the relevant key couplets. Progress towards confirming a putative identification was possible in all papers, through the inclusion of a diagnosis, habitus images, or both. Based upon this analysis, and expanding on previous suggestions for key construction, 23 recommendations are made on how to make an identification key maximally useful for users and I indicate the relative ease with which each could be adhered to. Identification keys should accompany all new taxon descriptions, guidelines for effective key construction should be added to journals' instructions to authors, editors and reviewers should check keys carefully, and publishers should be attentive to the needs of users through, for example, permitting duplication of images to make keys easier to use. Recommendations are likely relevant to all levels in the taxonomic hierarchy for all organisms, despite the data being derived from generic-level keys for insects.

Three-dimensional evaluation of a giant torus in the maxilla and mandible that affected pronunciation: a case report.

Introduction and importance: Tori in the maxilla and mandible are often clinically asymptomatic, but can often lead to issues such as obstruction of denture attachment and dysarthria. The authors describe a case involving a substantial torus in the maxilla and mandible that significantly affected speech articulation. Case presentation: A 72-year-old woman presented with a pronounced torus in the maxilla and mandible. Surgical resection of the lesion resulted in improved tongue movement. Through both pre and postoperative assessments, the authors evaluated pronunciation, generated a three-dimensional (3D) computed tomography (CT)-based image, and quantified the extent of bone removal. A 6-month follow-up demonstrated no recurrence of the condition. Clinical discussion: Surgical intervention leads to improvements in soft palate sounds. The surgical intervention proved effective in ameliorating speech articulation difficulties, and the application of 3D-CT image construction was valuable. Conclusion: To summarize, the authors successfully managed and treated a giant torus in the maxilla and mandible, a condition scarcely been reported in the literature. This report is the first to detail the application of 3D analysis for the evaluation a torus.

Transition in action: toward a social theory of the governance of transitions.

This article explores how a re-interpretation of the socio-technical, socio-ecological and transition design approaches to transition from the point of view of Niklas Luhmann's general systems theory of society. The need to understand and promote changes that include a technological and ecological dimension has led to different approaches, such as socio-technical or socio-environmental approaches, to incorporate links with society. While these approaches often include sociological insights, they rarely offer a general understanding of how these are embedded into society. We need a new environmental sociology that helps catalyze change processes with a collectively reorganized society, empowering more radically transformative actions to change the current structures and processes that have led us to where we are today. The article offers a cross-sectional look at the socio-ecological and socio-technical systems literature, specifically for what concerns their understanding of the 'systems' in transition and how they can be governed, and re-interpret it from the theoretical lens of the deep sociological knowledge, which refers to the profound understanding of social systems and their dynamics, embedded in Luhmann's theory of social systems. From here, we suggest the second-order coupling for a sociologically grounded understanding of the interactions that comprise socio-ecological and socio-technical systems, heterogeneous and almost self-organizing assemblies of social, technical, and natural elements and processes. At the same time, third-order couplings are analyzed, focused on governance, relationships between operations, and structures mediated by a deliberate attempt to ensure coherence and coordination against the autonomy and heterogeneity of socio-techno-ecological systems. Therefore, this manuscript offers a deeper conceptual and methodological understanding of socio-techno-ecological couplings and systems in the context of sustainability transformation and gives insights into its governance.

Updating a diesel engine exhaust job-exposure matrix with published measurement data.

A job-exposure matrix (JEM) is a tool that can estimate diesel engine exhaust (DEE) exposures. JEMs based on expert judgment or measurement data are limited by the information available at the time of development. Over time, more information about hazardous exposures is understood through additional measurements and peer-reviewed publications. This study presents a systematic approach to updating an existing DEE JEM using published data to better reflect current scientific knowledge. The literature was searched for occupational exposure studies that measured DEE as elemental carbon (EC) between January 2010 and May 2022. Four-digit North American Industry Classification System (NAICS) 2002 and National Occupational Classification-Statistics (NOC-S) 2006 codes were assigned to each identified subgroup within the studies. EC exposures were categorized as low (0-10 µg/m3), moderate (10-20 µg/m3), or high (>20 µg/m3). Weighted arithmetic means were calculated for each industry-occupation intersection (IOI) identified in the literature. These means were used to adjust, or retain, the existing exposure level within the JEM cells using a decision tree based on the number of studies, workplace locations, and pooled sample size of the weighted mean. Concordance was measured between the updated JEM (Diesel Exhaust in Canada JEM (DEC-JEM)), the previous (existing) JEM, and the Canadian Job-Exposure Matrix (CANJEM). Thirty-seven studies were identified from the published literature reporting on 53 unique IOIs (20 NAICS and 34 NOC-S codes), including occupations in the mining, construction, and transportation industries. Exposure levels for 66% of identified IOIs increased, most in construction and mining. After the decision tree's results were expanded to the full DEC-JEM, the exposure level of 486 IOIs (12.5% of DEC-JEM) and 286,710 workers (15.8% of DEE-exposed workers) increased. There was a significant correlation between qualitative exposure levels in the updated DEC-JEM and CANJEM (Kendall's τ = 0.364, p < 0.001). This study describes a systematic approach to updating an existing JEM to incorporate new scientific knowledge. The updated DEC-JEM better reflects existing exposure knowledge in several industries, particularly construction. Future analyses include investigating its use as an exposure assessment tool in disease surveillance.

The industry demand oriented construction of intelligence medicine specialty in traditional Chinese medicine university: teachers' perspective.

BACKGROUND: The aim of this study was to explore the relationships between teaching competence, career development, industrial orientation, and specialty construction in the case of intelligent medicine specialties in universities of traditional Chinese medicine, as well as the influencing factors of specialty construction. METHODS: Two-stage sampling with unequal probability was conducted to distribute self-administered questionnaires in the fieldwork. A structural equation model was built to investigate the influencing factors of specialty construction. Forty-two teachers were recruited and completed the questionnaire. RESULTS: The study found that teaching competence, career development, and industrial orientation positively affect specialty construction at a significant level. Career development and industrial orientation play chain mediating roles in the effect of teaching competence on specialty construction. CONCLUSIONS: In the construction of intelligent medicine specialties, a professional curriculum system should be built that caters to industrial demand and is combined with industrial development, the traditional mode of teaching should be transformed, and the transformation of theoretical knowledge into practical ability should be promoted. Innovations in teaching modes should be achieved by introducing information technology, and the teacher evaluation system should be optimized.

Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network.

This study aims to address the challenges of capturing design changes, supply chain fluctuations, and labor cost variations to improve the accuracy and real-time nature of intelligent building construction cost predictions. It seeks to accurately forecast and optimize project costs. The study innovatively constructs an intelligent building construction cost prediction model based on Building Information Modeling (BIM) and Elman neural networks (ENNs), denoted as the BIM-ENN model. The BIM-ENN model first introduces BIM technology to digitize and visualize information related to building structures, electromechanical systems, and pipelines. The digitized data obtained through BIM technology is then used as input data for the ENN, which optimizes the neural network parameters to predict and optimize intelligent building construction costs. Finally, the BIM-ENN model is experimentally evaluated. The results demonstrate that the prediction value of the construction cost of the intelligent building by this model closely matches the original information price, with a prediction accuracy of 95.83 %. Compared with the single ENN, the root mean squared error of the BIM-ENN model is less than 75, and the determination coefficient is above 0.95. This indicates that this model can explain more than 95 % of the construction cost prediction results, making it a feasible solution for actual prediction problems and achieving satisfactory results. The intelligent building construction cost prediction model reported here exhibits high accuracy and reliability. It can successfully forecast construction costs, providing robust decision support for the digitalization and intelligent development of construction enterprises. The practical significance of this study lies in providing the construction industry with an accurate cost management tool that helps enterprises optimize budget control and resource allocation, enhancing risk assessment and management capabilities. Moreover, the potential impact of the BIM-ENN model is its ability to elevate prediction standards within the construction industry, promote technological integration and innovation, enhance enterprise competitiveness, and drive the industry's transition towards digitalization and intelligent sustainable development.

Evaluation of Personal Protective Equipment Usage Among Construction Workers in Erbil City, Iraq.

Background and aim The construction industry is a high-risk environment where the use of personal protective equipment (PPE) is essential for worker safety. Despite the clear benefits of PPE, compliance rates among construction workers are often suboptimal. In response to these concerns, this study aimed to assess the knowledge and attitudes regarding PPE usage among construction workers in Erbil City, Iraq. Methods This cross-sectional study was conducted from December 15, 2022, to June 15, 2023, among construction workers in Erbil. Convenience sampling was used to collect data through a self-structured questionnaire. The questionnaire collected demographic information, as well as responses to a 15-item Knowledge Questionnaire and an 8-item Attitude Questionnaire. Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 28 (Released 2021; IBM Corp., Armonk, New York). Frequency and percentage were used to describe qualitative variables, while mean and standard deviation were calculated for quantitative variables. Parametric tests such as the independent sample t-test and ANOVA were used, along with multinomial logistic regression, to assess the relationships between knowledge, attitude, and various demographic factors. Results A total of 280 workers participated in the study. The mean knowledge score was 13.56 ± 1.17, indicating a good level of knowledge, while the mean attitude score was 6.86 ± 1.11, reflecting a fair attitude toward PPE usage. A significant majority of the participants, 97.9% (274), were categorized as having good knowledge, while 68.2% (191) exhibited a fair attitude towards PPE usage. The analysis showed that demographic factors such as age, marital status, working hours, work experience, and employment type did not significantly affect knowledge or attitude, with all odds ratios (ORs) near 1 and P-values above 0.05. Conclusion The findings indicate that construction workers in Erbil generally have good knowledge but only a fair attitude toward PPE usage. These results suggest that healthcare providers and policymakers should implement targeted educational interventions to improve workers' attitudes toward PPE, aiming to boost compliance and enhance workplace safety. Additionally, these interventions should address practical barriers to PPE usage, such as discomfort or lack of accessibility. By fostering more positive attitudes and ensuring the availability of necessary resources, overall safety in the construction industry can be significantly improved.

Characterizing pituitary adenomas in clinical notes: Corpus construction and its application in LLMs.

Objective: Faced with the challenges of differential diagnosis caused by the complex clinical manifestations and high pathological heterogeneity of pituitary adenomas, this study aims to construct a high-quality annotated corpus to characterize pituitary adenomas in clinical notes containing rich diagnosis and treatment information. Methods: A dataset from a pituitary adenomas neurosurgery treatment center of a tertiary first-class hospital in China was retrospectively collected. A semi-automatic corpus construction framework was designed. A total of 2000 documents containing 9430 sentences and 524,232 words were annotated, and the text corpus of pituitary adenomas (TCPA) was constructed and analyzed. Its potential application in large language models (LLMs) was explored through fine-tuning and prompting experiments. Results: TCPA had 4782 medical entities and 28,998 tokens, achieving good quality with the inter-annotator agreement value of 0.862-0.986. The LLMs experiments showed that TCPA can be used to automatically identify clinical information from free texts, and introducing instances with clinical characteristics can effectively reduce the need for training data, thereby reducing labor costs. Conclusion: This study characterized pituitary adenomas in clinical notes, and the proposed method were able to serve as references for relevant research in medical natural language scenarios with highly specialized language structure and terminology.

Effect of metakaolin and lime addition on geopolymerization of construction and demolition waste.

Construction and demolition waste generates the largest amount of waste by volume, which threatens sustainable development and adversely affects the environment. These wastes contain a significant amount of aluminosilicates that have the potential to be used as building materials for value-added applications applicable to alternative construction materials. This study aims to synthesize geopolymers from brick powder using metakaolin/lime as additives and compare their physico-mechanical properties. The compressive strengths of the geopolymer products GP-1, GP-2, and GP-3 developed at 28 days from brick powder and metakaolin/lime with the activator solution were found to be 8.35, 21.30, and 25.0 MPa respectively, 2.55 and 2.99 times higher when metakaolin and lime were added. FTIR spectra and SEM-EDX micrographs of the reaction products showed structural changes and formation of aluminosilicate hydrate and calcium silicate hydrate gel with Al2O3/Na2O ratios of 0.75, 1.67, and 1.98 respectively. The reaction products containing SiO2/(SiO2 + Al2O3 + Fe2O3) ratios of 0.70 and 0.76 were found to be desirable. The geopolymer product GP-3 was found to have a higher bulk density and mechanical strength than those of GP-1 and GP-2. These products are found to be very hard, with potential applications in construction industries to conserve the environment.

Specific and shared cognitive predictors of drawing and block building in typically developing children.

Introduction: Spatial construction is a complex ability involving attention, global/local visual processing, mental representation, visuo-motor coordination and, to varying extent, working memory and executive functions, and verbal abilities. In developmental neuropsychology, little attention has been paid to comprehend whether and to what extent the above cognitive processes are involved in two main spatial construction tasks, that is drawing and block building. Method: We used path analysis to test shared and specific effects of verbal and spatial working memory, spatial attention, inhibition, verbal abilities (vocabulary and naming), figure disembedding, mental rotation, and visual-motor coordination, as well as of demographics (sex, age and socio-economic status), on two classical drawing (Rey-Osterrieth Complex Figure; ROCF) and block building (Block design; BD) tasks in a sample of 195 typically developing children (age range: 7-11 years). Results: Figure disembedding and visuo-motor coordination were the only shared predictors of both spatial construction tasks. Moreover, ROCF score was directly related with spatial attention and inhibition, while BD score was directly related with sex, vocabulary, mental rotation and backward spatial working memory. Discussion: These findings distinguish between abilities involved in spatial construction regardless of the type of task and those specifically related to ROCF or Block Design, thus providing clues relevant to neuropsychological assessment and intervention in children with spatial construction disorders.

The effect of experimental warming on reproductive performance and parental care in the burying beetle Nicrophorus nepalensis.

Rising temperatures can adversely affect parental care and reproductive performance across a range of taxa. However, the warming impact is contingent upon understanding how temperature affects the spectrum of parental behaviours and their interplay. Here, we assessed how temperature affects parental care and reproductive success in the burying beetle, Nicrophorus nepalensis, which exhibits complex parental care behaviours. We exposed breeding pairs of N. nepalensis, to three temperature regimes (18°C, 20°C and 22°C) and assessed changes in parental care, and the subsequent development and growth of their offspring. Our findings show that 22°C disrupts carcass nest building by the parents and results in smaller clutches. Moreover, no eggs successfully hatched in the 22°C treatment. A milder increase to 20°C did not affect the hatching rate but resulted in smaller broods and lighter offspring, even when considering brood size, suggesting a change in post-hatching care quality. Our research suggests that warming may weakly affect parental care but has strong detrimental effects on offspring performance. These findings highlight the necessity of investigating the effect of ambient temperature across a diversity of traits and behaviours and across a range of life-history stages to fully assess species vulnerability in the face of future climate change.

Development of a center for automated equipment processing to transform the research enterprise configuration.

The strategy of centralizing equipment sanitation and processing was developed by a top-tier public university to address the growing physical infrastructure and human resource challenges of its expanding in-vivo research enterprise. Subsequently, a center for automated equipment processing physically separate from all animal research facilities was developed and has operated consistently since 2016. The facility incorporates systems such as process automation to sanitize and sterilize equipment as efficiently as possible. Analysis of the differences between the new centralized and old distributed research enterprise configurations shows a total estimated fiscal benefit of almost US$54 m to date projected out to US$124 m through 2028. Utility consumption of operations over nine years in the new configuration was estimated to be decreased by over 125 million gallons of water, 14 million gallons of chilled water, 121 million pounds of steam, and almost 3.6 million kilowatts of electricity, with consumption savings significantly increased projected out to 2028. Additional operational and organizational benefits as well as direct research benefits were identified. The new configuration has functioned for nine years without detectable cross contamination within the research enterprise thus providing evidence that the location of equipment processing can be less of a "microbial" risk factor than previously attributed.

Effects of a back-assist exosuit in lab-based approximations of construction tasks performed by novices and experienced construction workers.

Passive back-assist exosuits may be beneficial for construction workers, but few evaluations have been conducted with actual workers and construction-relevant tasks. This paper presents a laboratory study of the HeroWear Apex exosuit with 35 participants: 15 with significant construction experience and 20 without it. Participants completed several approximations of brief construction tasks (lifting, carrying, raising boards) and three 3-min tasks (hunched standing, kneeling, hunched walking with a nail gun) with and without the exosuit. During brief tasks, erector spinae electromyograms were reduced in all tasks (Cohen's d up to -0.58), kinematics suggested load shifting from the back to the legs, and the exosuit was perceived as helpful. During 3-min tasks, the exosuit was perceived as helpful in all tasks, but only reduced erector spinae electromyograms during kneeling. Thus, the exosuit may benefit workers during several construction-related tasks, though objective benefits could not be shown in 3-min standing or walking.

This study explored how a passive back-assist exosuit affects back muscle activity and kinematics in lab-based approximations of construction tasks performed by both novices and experienced construction workers. Quantitative and qualitative results indicated potential benefits in several brief load lifting and carrying tasks, but not during 3-min standing or walking.

A hybrid MCDM approach based on combined weighting method, cloud model and COPRAS for assessing road construction workers' safety climate.

Purpose: The purpose of this paper is to propose a novel approach to assess the safety climate level of different groups of workers in a construction company and predict safety performance and implement targeted improvement measures. Design/methodology/approach: This paper utilizes the BP neural network and random forest algorithm to establish a weight learning mechanism for calculating the weights of safety climate evaluation criteria. The cloud model is employed to construct the decision matrix for different groups under the evaluation criteria. Meanwhile, the paper utilizes the COPRAS method to compare the safety climate of different groups. Findings: The findings show the accuracy of the CM-COPRAS model is assessed by comparing it with the other methods. The three models are almost consistent in assessing the safety climate for working age groups, accident experience groups, and work type groups, with slight differences in the evaluation results for the education groups. The consistency of the computational results of the CM-COPRAS model with the results of the existing research, i.e., that the education level is positively proportional to the safety climate supports the reasonableness and validity of the CM-COPRAS model. Originality: The paper proposes a hybrid MCDM method that integrates the Combined weighting method, Cloud model, and COPRAS for safety climate level evaluation in different construction worker groups. A case study is presented to demonstrate the applicability of the proposed method and to compare it with other methods to validate the effectiveness of the present method.

Influence of construction works on urban streamflow water quality variations.

Construction activities can have long-lasting impacts on receiving water bodies, especially when they receive polluted urban runoff. Therefore, it is essential to minimize these impacts on water quality and consider the long-term environmental effects of development activities. This study aims to provide insights into the assessment, temporal variations, and key variables associated with the impact of construction works on streamflow water quality. However, current assessment methods relating to construction works and streamflow water quality may lead to spurious correlations. A spurious correlation refers to a connection between two variables that appears to be causal but is not. This study proposes a novel approach to avoid spurious correlations between construction work signatures and water quality, ensuring causality and correlation between water quality parameters. The approach was applied to a developing urban catchment in Hong Kong. Compared to existing assessment models, the proposed approach advances in ensuring true correlations between construction works and streamflow water quality. It is also the first to develop a new indicator to represent the key variable of construction works. In this study, salinity, turbidity, and suspended solids were used as substitutes for construction activity parameters, such as the number of construction works, to correlate with water quality parameters. Additionally, principal component analysis and the construction work signature index were both adopted to calculate the key variables of water quality on behalf of construction works. Results demonstrate that the new approach has significantly improved causality by 45 % compared to previous assessment methods. However, the method has limitations as it does not consider the impact of rainfall on construction works.

Multicenter Validation of the English Version of the Dépistage Cognitif de Québec: a Cognitive Screening Tool for Atypical Dementias.

BACKGROUND: Early detection of atypical dementia remains difficult partly because of the absence of specific cognitive screening tools. This creates undue delays in diagnosis and management. The Dépistage Cognitif de Québec (DCQ; dcqtest.org) was developed in French and later validated in participants with atypical syndromes. We report the validation of the English version. METHODS: This multicentre prospective validation study was conducted in 10 centers across Canada and the United States on 260 English-speaking participants aged over 50. We translated and modified the original French DCQ to add targeted stimuli to the Visusopatial Index and social cognition vignettes to the Behavioral Index. A backward translation was performed and equivalence between languages was assessed by administering both tests to 30 bilingual participants. RESULTS: Mean DCQ total score (out of 100) was 95.0 (SD = 3.6). Spearman's correlation coefficient showed a strong and significant correlation (r = 0.49, p < .001) with the Montreal Cognitive Assessment. Test-retest reliability was good (Spearman's coefficient = 0.72, p < .001) and interrater reliability, excellent (intraclass correlation = 0.97, p < .001). Normative data shown in percentiles were stratified by age and education for a population-based sample of 260 English-speaking controls aged between 50 and 87 years old. CONCLUSIONS: Similar to the French version, the English DCQ proved to be a valid cognitive screening test. The original version was very sensitive to detect atypical dementias such as primary progressive aphasias, Alzheimer's disease' variants and syndromes along the frontotemporolobar degeneration spectrum. This 20-min test can be administered à la carte and offers an alternative to detailed comprehensive neuropsychological evaluations.