Truck-Platooning Impacts on Flexible Pavements: Experimental and Mechanistic Approaches

Truck platoons are expected to improve safety and reduce fuel consumption. However, their use is projected to accelerate pavement damage due to channelized-load application (lack of wander) and potentially reduced duration between truck-loading applications (reduced rest period). The effect of wander on pavement damage is well documented, while relatively few studies are available on the effect of rest period on pavement permanent deformation. Therefore, the main objective of this study was to quantify the impact of rest period theoretically, using a numerical method, and experimentally, using laboratory testing. A 3-D finite-element (FE) pavement model was developed and run to quantify the effect of rest period. Strain recovery and accumulation were predicted by fitting Gaussian mixture models to the strain values computed from the FE model. The effect of rest period was found to be insignificant for truck spacing greater than 10 ft. An experimental program was conducted, and several asphalt concrete (AC) mixes were considered at various stress levels, temperatures, and rest periods. Test results showed that AC deformation increased with rest period, irrespective of AC-mix type, stress level, and/or temperature. This observation was attributed to a well-documented hardening–relaxation mechanism, which occurs during AC plastic deformation. Hence, experimental and FE-model results are conflicting due to modeling AC as a viscoelastic and the difference in the loading mechanism. A shift model was developed by extending the time–temperature superposition concept to incorporate rest period, using the experimental data. The shift factors were used to compute the equivalent number of cycles for various platoon scenarios (truck spacings or rest period). The shift model was implemented in AASHTOware pavement mechanic–empirical design (PMED) guidelines for the calculation of rutting using equivalent number of cycles.

Probabilitas Modal Shift Model A Probabilitas Modal Shift Model Angkutan Umum Di Bandara Adi Soemarmo Solo

Mulai 1 Desember 2019 Kereta Api Bandara Adi Soemarmo Solo beroperasi dengan rute Stasiun Solo Balapan-Bandara Adi Soemarmo, dengan jarak sejauh 12,9 kilometer, dan rata-rata waktu tempuh selama 20 menit. Mobilitas pergerakan dapat menyebabkan proses pemilihan moda. Pemilihan moda merupakan salah satu model yang digunakan dalam perencanaan transportasi angkutan umum. Hasil perhitungan probability perpindahan untuk variabel usia dan pekerjaan responden merupakan variabel yang berpengaruh secara signifikan. Setelah dilakukan analisis akhir dengan pengkategorian untuk tiap variabel usia dan pekerjaan, maka didapatkan kategori tiap Usia (2) yaitu usia 21-30 tahun dan usia (3) yaitu usia 31-40 tahun. Untuk kategori tiap variabel pekerjaan yang signifikan yaitu pekerjaan 1 pelajar/mahasiswa, pekerjaan 3 BUMN, dan pekerjaan 4 pegawai swasta. Hasil perhitungan probabilitas menunjukan semakin bertambah usia responden maka probabilitasnya mengalami mengalami penurunan dengan semakin bertambahnya umur seseorang maka akan cenderung lebih memilih menggunakan kendaraan pribadi karena lebih mudah mobilitasnya, lebih aman, dan lebih cepat dibandingkan dengan mereka yang usia muda akan lebih banyak memilih menggunakan angkutan umum untuk mobilitasnya karena lebih terjangkau serta lebih murah. Begitupula dengan pekerjaan, para pelajar/mahasiswa probabilitasnya lebih tinggi dibandingkan Pegawai swasta maupun BUMN karena intensitas mobilitas nya tidak sesering Pegawai swasta maupun BUMN.

Virulence shift in a sexual clade of Type X Toxoplasma infecting Southern Sea Otters

How virulent protozoal pathogens capable of causing overt disease are maintained in nature is an important paradigm of eukaryotic pathogenesis. Here we used population genetics and molecular methods to study the evolution and emergence of a marine invasion of new genetic variants of Toxoplasma gondii, referred collectively as Type X (HG12). 53 Toxoplasma isolates were obtained from mustelids that stranded between 1998-2004 with toxoplasmosis (ranging from chronic infection to fatal encephalitis). Over 74% of the sea otters collected throughout their geographic range were infected with Type X as determined by multi-locus PCR-DNA sequencing. Depending on the locus investigated, Type X strains possessed one of three allelic types that had independently assorted across the strains examined; either genetically distinct alleles, referred to as “γ” or “δ”, or a Type II allele. Phylogenetic incongruence among locus-specific trees, genome-wide CGH array and WGS analyses confirmed that Type X is a sexual clade of natural recombinants that resemble F1 progeny from a genetic cross between Type II and a mosaic of two distinct “γ” or “δ” ancestries. A single Type X genotype (19/53; 36%) had expanded in sea otters largely as subclinical chronic infections, but it was highly pathogenic to mice (LD100= 1 parasite). To determine whether murine virulence genes could be mapped within this naturally occurring population, we performed a genome scan and identified four QTLs with LOD scores greater than 4.0. Targeted disruption of ROP33, the strongest candidate from among 16 genes within the highest QTL on Chromosome VIIa established ROP33 as a murine virulence locus. The ability of this highly pathogenic clone to expand and cause the majority of sea otter infections supports a virulence shift model whereby generalist pathogens like Toxoplasma utilize their sexual cycles to produce new strains with an expanded biological potential. Such a trait enables pathogens to extend their host range or be naturally selected within their vast intermediate host range to maximize their transmission. Our work thus establishes a rationale for how virulent strains can be maintained cryptically in nature across a pathogen’s broad host range, and act as reservoirs for epidemic disease.ImportanceWaterborne outbreaks of protozoal parasites are increasingly causing fatal disease in a wide range of animals, including humans. Population expansion of felids near marine estuarine environments has led to increased exposure of marine wildlife to highly infectious Toxoplasma gondii oocysts shed in the feces of cats that are dispersed by storm events. In North America Toxoplasma is thought to possess a highly clonal population structure dominated by 4 clonal lineages (I, II, III, and X). Population genetic analysis of 53 Toxoplasma isolates collected longitudinally from mustelids infected with Toxoplasma that stranded between 1998-2004 identified a majority of otters (74%) to be infected with Type X Toxoplasma, and that Type X is not a clonal lineage, but rather a recombinant clade of strains consistent with a recent genetic cross that produced at least 12 distinct haplotypes. Importantly, one Type X haplotype expanded in 36% of otters across their geographic range and caused relatively benign infections, however it was highly pathogenic to mice. A genome scan was performed to identify a new virulence locus, a secreted serine threonine kinase (ROP33), that is pathogenic in mice, but not sea otters. Our data support a virulence shift model whereby generalist pathogens like Toxoplasma utilize their sexual cycles to produce virulent strains that are maintained cryptically in nature, according to their differential capacity to cause disease within the pathogen’s broad intermediate host range. This type of “zoonotic selection” has important public health implications. Strains capable of causing fatal infections can persist in nature by circulating as chronic infections in intermediate host species that act as reservoirs for epidemic disease.

Modelling the Long-Term Effects of Covid-19 Cancer Services Disruption on Patient Outcome in Scotland

BackgroundModelling the long-term effects of disruption of cancer services and minimising any excess cancer mortality due to the Covid-19 pandemic is of great importance. Here we adapted a stage-shift model to inform service planning decisions within NHS Scotland for the ‘‘Detect Cancer Early’ tumours, breast, colorectal and lung cancer which represent 46% of all cancers diagnosed in Scotland.Methods & DataLung, colorectal and breast cancer incidence data for years 2017-18 were obtained from Public Health Scotland Cancer Quality Performance Indicators (QPI), to define a baseline scenario. The most current stage-specific 5-year survival data came from 2009-2014 national cancer registry and South East Scotland Cancer Network (SCAN) QPI audit datasets. The Degeling et al., inverse stage-shift model was adapted to estimate changes in stage at diagnosis, excess mortality and life-years lost from delays to diagnosis and treatment due to Covid-19-related health services disruption. Three and 6-month periods of disruption were simulated to demonstrate the model predictions.ResultsApproximately, 1-9% reductions in stage I/II presentations leading up to 2-10% increases in stage III/IV presentations are estimated across the three cancer types. A 6-month period of service disruption is predicted to lead to excess deaths at 5 years of 32.5 (31.1, 33.9) per 1000 cases for lung cancer, 16.5 (7.9, 24.3) for colorectal cancer and 31.6 (28.5, 34.4) for breast cancer.ConclusionsDisruption of cancer diagnostic services can lead to significant excess deaths in following years. Increasing diagnostic and capacity for cancer services to deal with the backlog of care are needed. Real time monitoring of incidence and referral patterns over the disruption and post-disruption period to reduce excess deaths including more rapid incidence data by stage and other key tumour/clinical characteristics at presentation for key cancer cases (on a quarterly basis). Real time monitoring in cancer care and referral patterns should help inform what type of interventions are needed to reduce excess mortality and whether different population subgroups require public health messaging campaigns. Specific mitigation measures can be the subject of additional modelling analysis to assess the benefits and inform service planning decision making.