ECONOMIC MODEL FOR VEHICLE OWNERSHIP QUOTA POLICY ANALYSIS

Over the years, traffic congestion has become an ever more serious issue in many mega-regions worldwide, and has caused huge economic and environmental loss. Having witnessed big increase in the sales of passenger cars, some authorities have turned to vehicle ownership quota policy, which is a direct tool to control the number of vehicles on the road. Two of the most typical ownership quota policies, are the vehicle plate lottery system and vehicle plate auction system. This thesis developed an analytical framework that utilized the joint vehicle ownership and usage decision model to quantitatively measure the impacts of the two quota policies, in terms of compensating variation. It is shown that implementation of vehicle plate lottery system will invite more households who have lower preference of owning a vehicle, and will result in a decrease in net social impact. The thesis then proposed an alternative policy that restricts the lottery to only previous car owners, and shows that it will give a higher net social impact. A numerical example is then conducted to determine the optimal quota ratio for each of the policies, and to compare their social benefits. Various policy implications and future research directions are also discussed

Modification of Maxwell model for conductivity prediction of carbon nanotubes-filled polymer composites with tunneling effect

Carbon nanotubes (CNTs) have garnered great attention in recent years due to their outstanding electrical, thermal, and mechanical properties. The incorporation of small amounts of CNTs in polymers can substantially improve the sensitivity of the polymer’s electrical conductivity. This paper presents a modified Maxwell model to evaluate the electrical conductivity of CNTs-filled polymer composites by introducing a transition zone to account for the tunneling effect. In this modified Maxwell model, the CNTs-filled polymer composite is modeled as a three-phase composite, consisting of a matrix (polymer), inclusions (CNTs), and a transition zone (tunneling zone). The effective electrical conductivity (EEC) of the composite is calculated based on the volume fractions and electrical conductivities of the matrix, inclusions, and transition zone. The model’s validity is confirmed through the use of available test data, which demonstrates its capability to accurately capture the nonlinear conductivity behavior observed in CNTs-polymer composites. This study offers valuable insights into the design of high-performance conductive polymer nanocomposites, and enhances the understanding of electrical conduction mechanisms in CNT-dispersed polymer composites

Mesoscale Modeling for Predicting Effective Properties and Damage Behavior of Geopolymer Concrete

Geopolymer concrete is a sustainable construction material and is considered as a promising alternative to traditional Portland cement concrete. However, there is still not much research on the effective properties and damage behavior of geopolymer concrete with consideration of its heterogeneous characteristics by means of mesoscale models combined with the regularized microplane damage model. Here, in this research, an easy and simpler approach for generating concrete mesoscale models and characterizing the angular characteristics of aggregate particles is presented. After the proposed mesoscale modeling was validated by numerical, experimental and theoretical models, it was employed further to predict the effective properties and damage behavior of geopolymer concrete. The obtained results show that the effective elastic modulus and compressive strength of geopolymer concrete were greatly affected by the volume fractions of aggregate, while no significant influence on Poisson’s ratio was found. The evolution of damage and coalescence of cracks were affected by the volume fractions and spatial distribution of aggregate particles, which resulted in the different failure patterns in the mesoscale model of geopolymer concrete manufactured by different volume ratios of aggregate

Effects of the Zebra Mussel on Nitrogen Dynamics and the Microbial Community at the Sediment-Water Interface

A flow-through experiment was conducted on intact cores of sediments from Saginaw Bay, Lake Huron, to examine how trophic interactions between filter-feeding bivalve mussels and microbial populations could affect nitrogen dynamics at the sediment-water interface. The zebra mussels used in this experiment removed a large proportion of protozoa and phytoplankton from the overlying water, particularly heterotrophic nanoplankton (up to 82%), while bacterial populations showed less change. A 3-fold decrease in the protozoan to bacterial carbon ratio corresponded to a 2.5-fold increase in relative ammonium removal rates as estimated from the dark loss of N-15-ammonium. Excretion by the bivalves also increased net ammonium flux to the water, thus elevating the total calculated areal ammonium removal rates to about B-fold over rates observed in the control treatment. These data suggest that filter-feeding bivalves may significantly affect nitrogen transformation rates near the sediment-water interface by excreting ammonium and altering the microbial food web structure at the sediment-water interface

Poboljšana adaptivna pretvorba ostataka prilikom H.264/AVC video kodiranja bez gubitka kvalitete

The H.264/AVC was designed mainly for lossy video coding, the lossless coding of H.264 use bypass mode for DCT and quantization. Although sample-by-sample DPCM improves performance of coding, the benefit is limited in intra. In this paper, a new adaptive transform is proposed based on the character of 4x block residual coefficient\u27s distribution, which can be used both in intra and inter coding. The greatest strength of the proposed transform is the decorrelation without inflation versus dynamic range of input matrix. Due to the random distribution of residual coefficients, a specific transform is hard to play a positive impact on them. Therefore, several transforms of different directions will be implemented simultaneously, and the most efficient one will be determined by a proposed mechanism. Then, by means of statistic method, a new scan order is designed for CAVLC entropy encoder, cooperating with corresponding transform. The simulation results show that based on the fast algorithm of proposed method, the bit saving achieves about 7.41% bit saving in intra coding and 10.47% in inter, compared with H.264-LS.H.264/AVC je napravljen prvenstveno za kodiranje videa uz gubitak kvalitete, dok kodiranje H.264 bez gubitka kvalitete koristi zaobilazni mod za DCT i kvantizaciju. Iako uzorak-po-uzorak (DPCM) kvantizacija poboljšava performanse kodiranja, dobitak je ograničen. U ovom radu predlaže se nova adaptivna transformacija koja se zasniva na znakovima od 4x4 blokova distribucije ostataka koeficijenata, koja može koristiti i unutarnje i među kodiranje. Najveća snaga predložene transformacije je u nekoreliranosti bez inflacije protiv dinamičke veličine ulazne matrice. Radi slučajne distribucije ostataka koeficijenata, teško je postići da određena transformacija ima pozitivan učinak na njih. Iz tog razloga istovremeno je implementirano nekoliko transformacija različitih pristupa, te je korištenjem predloženog mehanizma odabrana najefikasnija. Zatim je, korištenjem statističke metode, dizajniran novi poredak snimanja za CAVLC entropijski enkoder, koji surađuje s odgovarajućom transformacijom. Rezultati simulacija pokazuju da korištenjem brzog algoritma predložene metode dolazi do smanjenja korištenih bitova od 7.41% kod među kodiranja i 10.47% prilikom unutarnjeg kodiranja u usporedbi s H.264-LS

Analysis of heavy metals in the conversion of lake sediment and restaurant waste by black soldier fly (Hermetia illucens)

The risk posed by heavy metals makes it difficult to dispose of sediment contaminants from dredging lakes in China. Black soldier fly (Hermetia illucens) can convert organic waste, such as restaurant waste and lake sediment, to high-value-added protein feed and fertilizer. Experimental groups were formed in this study to explore the conversion of heavy metals present in the mixture of restaurant waste and lake sediment by black soldier fly larvae (BSFL). The results demonstrated that BSFL could survive in pure sediment with an 84.76% survival rate. Relative to the substrate, BSFL could accumulate 70-90% zinc (Zn), chromium (Cr), copper (Cu), and 20-40% cadmium (Cd) and lead (Pb). The experimental group 2:3, with 40% lake sediment and 60% restaurant waste, was the best group after conversion for 15 days, which showed a 95.24% survival rate of BFSL, 82.20 mg average weight of BFSL, 8.92 mm average length of BFSL, with varying content of heavy metals such as Cu (43.22 mg/kg), Zn (193.31 mg/kg), Cd (1.58 mg/kg), Cr (25.30 mg/kg) Cr, and Pb (38.59 mg/kg) in BSFL. Furthermore, the conversion residue conforms to the relevant standards of organic fertilizer in China and can be used as organic fertilizer. Overall, the present study shows that black soldier flies can improve the resource utilization of lake sediment, especially by reducing the effect of heavy metals

Effects of Volatile Substances from Trichoderma erinaceum M6-5 on the Cell Membrane and Wall of Alternaria alternata, a Postharvest Pathogen of Korla Fragrant Pear

In this study, the effects of volatile substances from Trichoderma erinaceum M6-5 on the cell membrane and wall of Alternaria alternata were investigated. To evaluate the antifungal effect, the culture medium inoculated with T. erinaceum and cultured for 5 days was covered with the culture medium containing A. alternata and cultured at 30 ℃ for 3, 5 and 7 days. The mycelia of A. alternata in the treatment and control groups were observed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) and were collected to observe the integrity of the cell membrane by propidiumiodide (PI) staining, and cell membrane-related indexes such as electrical conductivity were measured. The morphological changes of apical growth cells were detected by calcofluor white (CFW) staining, and alkaline phosphatase (AKP) activity and N-acetylglucosamine concentration were determined. The results showed that during the culture period, the volatile substances produced by T. erinaceum had good antifungal effects on A. alternata. SEM and TEM images showed that the mycelia of A. alternata appeared shriveled, swollen and broken partially after the treatment. A greater reduction in cytoplasmic matrix was noted when compared with the control group, which was accompanied by local plasmolysis. For the control group, the mycelium growth was normal, the spore structure was complete, the cross-section structure was clear, the cytoplasm was uniform, and the cell wall and membrane structures were normal. After the treatment, the electrical conductivity, malondialdehyde (MDA) level, protein and nucleic acid leakage significantly increased relative to the control group. PI staining showed that the mycelia of the treated group emitted red fluorescence, indicating that the volatile substances of T. erinaceum damaged the integrity of the cell membrane, thus resulting in the leakage of cellular contents and marked disruption of the normal function of the cell membrane. CFW staining showed no significant differences between the treated and control groups with respect to the fluorescence intensity of mycelia, AKP activity or n-acetylglucosamine concentration indicating that the volatile substances of T. erinaceum did not damage the cell wall of A.alternata, and their major targets were not the cell wall. In conclusion, the antifungal target of volatile substances from T. erinaceum M6-5 is the cell membrane of A. alternata

Deciphering the impact of intra-tumoral bacterial infiltration on multi-omics profiles in low-grade gliomas

BackgroundLow-grade gliomas (LGGs) exhibit diverse bacterial infiltrations. This study delves into the intricate relationship between microbial infiltration in glioma samples and tumor multi-omics characteristics, aiming to elucidate its impact on tumor behavior and patient prognosis.MethodsWe included low-grade glioma (LGG) samples from The Cancer Genome Atlas (TCGA) as analysis cohort and used LGG tumor samples from patients who underwent surgical treatment as validation cohort. For the TCGA samples, utilizing advanced machine learning algorithms, this study identified distinct patterns of bacterial infiltration within the LGG population and constructed a prognostically relevant intra-tumoral bacteria risk model (PRIBR Index). For the clinically derived samples, we performed 16S rRNA sequencing, bulk RNA sequencing, and proteomics analysis. Subsequently, the samples were stratified into high-risk and low-risk groups. We then explored clinical information, tumor microenvironment, methylation status, and sensitivity to targeted therapies between these groups to elucidate the impact of varying bacterial infiltration levels on glioma behavior.ResultsA total of 32 common differentially expressed genes were identified between the TCGA-LGG samples and the clinical samples when comparing the high-risk and low-risk groups. The high-risk group demonstrated elevated bacterial infiltration levels, which were associated with increased infiltration of inflammatory factors. Patients in this group exhibited shorter survival periods, potentially attributable to the heightened expression of negative immune checkpoints. Predictive analysis for targeted drugs indicated that certain agents might achieve a lower half maximal inhibitory concentration (IC50) in the low-risk group compared to the high-risk group. Furthermore, while no significant differences were observed in tumor mutation burden or copy number variation between the two groups, the high-risk group showed increased methylation levels across multiple pathways.ConclusionThese findings offer new insights into the biological characteristics of gliomas and provide novel avenues for exploring new therapeutic approaches, bringing fresh perspectives to the field of intra-tumoral bacteria