Identifying the shortest log trucking routes and optimizing those constrained by low-weight bridges in Mississippi

Timber haulage in Mississippi incurs the greatest portion of logging expenses because of a myriad of closed and posted (restricted) bridges. This study utilized Dijkstra\u27s algorithm method in ArcGIS Pro to derive 129 feasible shortest optimal trucking routes between 46 harvest sites and 32 softwood sawmills in Mississippi. Among these routes, 30 of them had restricted bridges along the way; however, only 13 viable alternative routes were identified due to distance and weight restrictions. The additional trucking distance for alternative routes ranged between 1.5 to 12.9 miles, whose effect on transportation cost was determined using a Mixed Integer Linear Programming optimization model incorporating weight limits of the restricted bridges. Restricted bridges along optimal routes resulted in an additional transportation cost of $4.09 million, representing a 4.07% increase in total transportation cost or 0.34 per ton of softwood sawlogs transported. All these cost increases were exclusive to softwood sawlogs

Specific parameters for some isotopes of copernicium and flerovium

Super heavy elements (SHE) in the periodic table are generally transuranic and transactinide elements having Z > 92. Here, some of the properties of two super heavy elements viz. Copernicium (Cn) and Flerovium (Fl) are discussed. The half life time, transition probability, Gamow’s factor, disintegration constant are calculated for these super heavy elements and compared with other values

Ethnic/Racial, Religious, and Demographic Predictors of Organ Donor Registration Status Among Young Adults in the Southwestern United States.

Context and Setting: New Mexico (NM) is a minority-majority state. Despite its unique cultural characteristics and documented ethnic/racial disparities in deceased organ donation (DOD), past studies did not explore predictors of organ donor registration status (ODRS) in this state. OBJECTIVES: This study aimed at identifying demographic, cultural, and religious predictors of ODRS among a diverse sample of young adults in NM. DESIGN: This study focused on recruitment of American Indian, Hispanic, and Asian American participants through online social network sites and university listservs. Participants (N = 602) answered an online survey. The largest racial/ethnic group included American Indians (n = 200). Main outcome measures included ODRS, demographics, religious affiliation, and open-ended question on reasons for objections to DOD. RESULTS: Race/ethnicity, religion, and educational attainment were significant predictors of ODRS. Non-Hispanic whites (NHWs) were most likely to be registered as donors, with no significant difference between NHWs and Asians or Pacific Islanders. Non-Catholic Christians were most likely to be registered donors, followed by Catholics, practitioners of American Indian/Native American traditional religions, and Hindus, with Buddhists the least likely to register. This pattern was consistent with the propensity of individuals from these religious groups to cite religious objections to DOD. Finally, respondents who had graduated from high schools in NM were 2.3 times less likely to be registered as organ donors compared to those who had graduated in other states. CONCLUSION: This study provides evidence for the need for culturally tailored interventions targeting diverse communities in NM

A Pan-Cancer Census of Dominant Tumor Immune Archetypes

SUMMARY Cancers display significant heterogeneity with respect to tissue of origin, driver mutations and other features of the surrounding tissue. It is likely that persistent tumors differentially engage inherent patterns–here ‘Archetypes’–of the immune system, to both benefit from a tumor immune microenvironment (TIME) and to disengage tumor-targeting. To discover dominant immune system archetypes, the Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub compartments uncovered archetypes that exist across indications. These Immune composition-based archetypes differentiate tumors based upon unique immune and tumor gene-expression patterns. Archetypes discovered this way also tie closely to well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune infiltration and provides a rational path forward to learn how to modulate these patterns to improve therapy