Non-exhaustive double effort test is reliable and estimates the firs ventilatory threshold intensity in running exercise

Purpose: The present study aimed to investigate the reliability of the non-exhaustive double effort(NEDE) test in running exercise and its associations with the ventilatory thresholds(VT_1 and VT_2) and the maximal lactate steady state(MLSS).Methods: Ten healthy male adults(age: 23 ± 4 years, height: 176.6 ± 6.4 cm, body mass: 76.6 ± 10.7 kg) performed 4 procedures:(1) a ramp test for VT_1 and VT_2 determinations measured by ratio of expired ventilation to O_2 uptake(VE/VO_2) and expired ventilation to CO_2 output(VE/VCO_2) equivalents, respectively;(2) the NEDE test measured by blood lactate concentration(NEDE_(LAC)) and heart rate responses(NEDE_(HR));(3) a retest of NEDE for reliability analysis; and(4) continuous efforts to determine the MLSS intensity. The NEDE test consisted of4 sessions at different running intensities. Each session was characterized by double efforts at the same running velocity(E1 and E2, 180 s), separated by a passive recovery period(90 s rest). LAC and HR values after E1 and E2(in 4 sessions) were used to estimate the intensity equivalent to"null delta" by linear fit. This parameter represents, theoretically, the intensity equivalent to maximal aerobic capacity.Results: The intraclass correlation coefficient indicated significant reliability for NEDE_(LAC)(0.93) and NEDE_(HR)(0.79)(both p < 0.05). There were significant correlations, no differences, and strong agreement with the intensities predicted by NEDE_(LAC)(10.1 ± 1.9 km/h) and NEDE_(HR)(9.8 ± 2.0 km/h) to VT_1(10.2 ± 1.1 km/h). In addition, despite significantly lower MLSS intensity(12.2 ± 1.2 km/h), NEDE_(LAC) and NEDE_(HR) intensities were highly correlated with this parameter(0.90 and 0.88, respectively).Conclusion: The NEDE test applied to running exercise is reliable and estimates the VT_1 intensity. Additionally, NEDE intensities were lower but still correlated with VT_2 and MLSS.

CLUSTERING PATENTS USING NON-EXHAUSTIVE OVERLAPS

Patent documents are unique external sources of information that reveal the core technology underlying new inventions. Patents also serve as a strategic data source that can be mined to discover state-of-the-art technical development and subsequently help guide R＆D investments. This research incorporates an ontology schema to extract and represent patent concepts. A clustering algorithm with non-exhaustive overlaps is proposed to overcome deficiencies with exhaustive clustering methods used in patent mining and technology discovery. The non-exhaustive clustering approach allows for the clustering of patent documents with overlapping technical findings and claims, a feature that enables the grouping of patents that define related key innovations. Legal advisors can use this approach to study potential cases of patent infringement or devise strategies to avoid litigation. The case study demonstrates the use of non-exhaustive overlaps algorithm by clustering US and Japan radio frequency identification （RFID） patents and by analyzing the legal implications of automated discovery of patent infringement.

Identify the contribution of vehicle non-exhaust emissions:a single particle aerosol mass spectrometer test case at typical road environment

A single particle aerosol mass spectrometer(SPAMS)was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment.The PM_(2.5),black carbon,meteorological parameters and traffic flow were recorded during the test period.The daily trend for traffic flow and speed on TEDA Street showed obvious“M”and“W”characteristics.6.3 million particles were captured via the SPAMS,including 1.3 million particles with positive and negative spectral map information.Heavy Metal,High molecular Organic Carbon,Organic Carbon,Mixed Carbon,Elemental Carbon,Rich Potassium,Levo-rotation Glucose,Rich Na,SiO_(3) and other categories were analyzed.The particle number concentration measured by SPAMS showed a good linear correlation with the mass concentrations of PM_(2.5) and BC,which indicates that the particulate matter captured by the SPAMS reflects the pollution level of fine particulate matter.EC,ECOC,OC,HM and crustal dust components were found to show high values from 7:00–9:00 AM,showing that these chemical components are directly or indirectly related to vehicle emissions.Based on the PMF model,7 major factors are resolved.The relative contributions of each factor were determined:vehicle exhaust emission(44.8%),coal-fired source(14.5%),biomass combustion(12.2%),crustal dust(9.4%),ship emission(9.0%),tires wear(6.6%)and brake pads wear(3.5%).The results show that the contribution of vehicle non-exhaust to particulate matter at roadside environment is approximately 10.1%.Vehicle non-exhaust emissions are the focus of future research in the vehicle pollutant emission control field.

Insight study of rare earth elements in PM_(2.5)during five years in a Chinese inland city:Composition

The booming development of rare earth industry and the extensive utilization of its products accompanied by urban development have led to the accelerated accumulation of rare earth elements(REEs)as emerging pollutants in atmospheric environment.In this study,the variation of REEs in PM_(2.5)with urban(a non-mining city)transformation was investigated through five consecutive years of sample collection.The compositional variability and provenance contribution of REEs in PM_(2.5)were characterized,and the REEs exposure risks of children and adults via inhalation,ingestion and dermal absorption were also evaluated.The results showed an increase in the total REEs concentration from 46.46±35.16 mg/kg(2017)to 81.22±38.98 mg/kg(2021)over the five-year period,with Ce and La making the largest contribution.The actual increment of industrial and traffic emission source among the three pollution sources was 1.34 ng/m^(3).Coal combustion source displayed a downward trend.Ingestion was the main exposure pathway for REEs in PM_(2.5)for both children and adults.Ce contributed the most to the total intake of REEs in PM_(2.5)among the population,followed by La and Nd.The exposure risks of REEs in PM_(2.5)in the region were relatively low,but the trend of change was of great concern.It was strongly recommended to strengthen the concern about traffic-related non-exhaust emissions of particulate matter.

Brake wear-derived particles:Single-particle mass spectral signatures and real-world emissions

Brake wear is an important but unregulated vehicle-related source of atmospheric particulate matter(PM).The single-particle spectral fingerprints of brake wear particles(BWPs)provide essential information for understanding their formation mechanism and atmospheric contributions.Herein,we obtained the single-particle mass spectra of BWPs by combining a brake dynamometer with an online single particle aerosol mass spectrometer and quantified real-world BWP emissions through a tunnel observation in Tianjin,China.The pure BWPs mainly include three distinct types of particles,namely,Bacontaining particles,mineral particles,and carbon-containing particles,accounting for 44.2%,43.4%,and 10.3%of the total BWP number concentration,respectively.The diversified mass spectra indicate complex BWP formation pathways,such as mechanical,phase transition,and chemical processes.Notably,the mass spectra of Ba-containing particles are unique,which allows them to serve as an excellent indicator for estimating ambient BWP concentrations.By evaluating this indicator,we find that approximately 4.0%of the PM in the tunnel could be attributable to brake wear;the real-world fleet-average emission factor of 0.28 mg km
1 veh
1 is consistent with the estimation obtained using the receptor model.The results presented herein can be used to inform assessments of the environmental and health impacts of BWPs to formulate effective emissions control policies.

Instrumental and bio-monitoring of heavy metal and nanoparticle emissions from diesel engine exhaust in controlled environment

In the present article we characterized the emissions at the exhaust of a Common Rail （CR） diesel engine, representative of lightduty class, equipped with a catalyzed diesel particulate filter （CDPF） in controlled environment. The downstream exhausts were directly analyzed （for PM, CO, CO/, Oz, HCs, NOx） by infrared and electrochemical sensors, and SEM-EDS microscope; heavy metals were chemically analyzed using mosses and lichens in bags, and glass-fibre filters all exposed at the engine exhausts. The highest particle emission value was in the 7-54 nm size range; the peak concentration rose until one order of magnitude for the highest load and speed. Particle composition was mainly carbonaceous, associated to noticeable amounts of Fe and silica fibres. Moreover, the content of Cu, Fe, Na, Ni and Zn in both moss and lichen, and of A1 and Cr in moss, was significantly increased. Glass-fibre filters were significantly enriched in A1, B, Ba, Cu, Fe, Na, and Zn. The role of diesel engines as source of carbonaceous nanoparticles has been confirmed, while further investigations in controlled environment are needed to test the catalytic muffler as a possible source of silica fibres considered very hazardous for human health.

Customer Joining Behavior and Regulation Strategy in Visible Multi-Server Queues with Synchronous Vacations of Partial Servers

This paper studies customer joining behavior and system regulation strategy in nonexhaustive visible M/M/m queues with synchronous vacations of a part of the servers.Once this part of the servers are idle,they take multiple vacations simultaneously(vacation period).Until there are customers waiting in the queue,they are reactivated and all servers are busy or idle(busy period).The authors call this part of the servers as“partial servers”.In view of the fully visible queue and the almost visible queue,the authors obtain customers’equilibrium joining threshold strategies and their socially optimal joining threshold strategies,respectively,and observe that customer joining behavior in equilibrium generally makes the system overcrowded,which makes the equilibrium social welfare lower than the optimal social welfare.After regulation,interestingly,for optimizing social welfare,the system manager hopes not only customers arriving in vacation period pay attention to the number of partial servers,but also customers arriving in busy period should care about it rather than ignore.Moreover,arranging more servers for vacation does not necessarily lead to the decrease of social welfare on condition that the number of partial servers is close to m.As for the information advantage of the fully visible case,it is not obvious for increasing social welfare and even unfavorable to servers’profit unless the number of partial servers is big enough.Furthermore,given the different composition of social welfare,there exists the optimal number of partial servers and the optimal arrival rate of customers for maximizing social welfare.