CODIS STR loci data from 41 sample populations

Allele distributions for 12 or 13 CODIS core tetrameric short tandem repeat (STR) loci CSFIPO, D3S1358, D5S818, D7S820, D8S1179, D13S317, D16S539, D18S51, D21S11, FGA, TH01, TPOX, and vWA were determined in 41 population data sets. The major population groups comprise African Americans, U.S. Caucasians, Hispanics, Far East Asians, and Native Americans. There was little evidence for departures from Hardy-Weinberg expectations (HWE) in any of the populations. The FST estimates over all thirteen STR loci are 0.0006 for African Americans, -0.0005 for Caucasians, 0.0021 for Hispanics, 0.0039 for Asians, and 0.0282 for Native Americans.     

Agriculture in the western Himalayas – an asset turning into a liability

Agriculture in the Himalayas has witnessed dynamic shifts and acute crises over the last decade. This viewpoint identifies and discusses the factors leading to de-agrarianisation and land abandonment in the western Himalayas. Data on farming preferences and bottlenecks for agricultural production were also gathered through a short survey with farmers. Escalating male out-migration, land fragmentation and heightened exposure to uncertain environmental conditions have transformed agriculture into a liability for the farmers. The viewpoint suggests that effective implementation of land consolidation reforms in the region would enhance agricultural production, curtail mass migration, and potentially insulate farmers from the ongoing agrarian crisis.     

Who Buys Foreclosed Homes? How Neighborhood Characteristics Influence Real Estate-Owned Home Sales to Investors and Households

Abstract

This study examines the trajectory of real estate-owned (REO) sales in the Chicago metropolitan statistical area from 2009 to 2013, roughly the first few years of the housing market recovery. Using a data set of property transactions, it tracks property sales to investors and owner-occupiers, and examines the neighborhood characteristics that contribute to an investor’s decision to purchase an REO property. Neighborhood characteristics include social and physical variables as well as housing and transportation affordability variables. Findings are consistent with previous studies in that investor activity is high in neighborhoods with higher proportions of African American and older residents. In addition, investors are more likely to purchase homes in neighborhoods that offer more affordable transportation options. Our findings can help planners identify areas where they may need to target programs that help reduce barriers to REO sales, particularly to owner-occupiers. By understanding the neighborhood-level determinants of REO dispositions, planners can help promote an equitable recovery and affordable homeownership for low- and moderate-income families.     

Impact of trade and investment on income surge in Bangladesh: Evidence from trade liberalization regime

Trade and investment are crucial drivers of economic growth. Successful execution of trade and investment policy can elevate a developing country to a sustained growth path and make it self-reliant. Bangladesh implemented a trade liberalization policy in the 1980s, deviating much from its conservative trade policy. This article assesses the impacts of trade, investment in physical as well as human capital, and a few trade policy variables on income surge for the liberalized regime. The econometric analysis finds that export, import, and domestic investment stimulate income. The impact of foreign investment is not conducive. Public spending on education also contributes to the income surge. Among the policy variables, trade openness and currency depreciation produce a beneficial impact. Population growth retards economic growth. The baseline results hold in the estimations involving several specifications of variables and testified as robust. The article views that a comprehensive approach to trade and investment policy would ensure the comparative advantage of trade and the well-being of Bangladesh.     

Population studies on three Native Alaska population groups using STR loci

Allele distributions for 13 short tandem repeat (STR) loci D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317, D7S820, TH01, TPOX, CSF1PO and D16S539 were determined for three Native Alaskan population groups-Athabaskans, Inupiats, and Yupiks. Although genetic diversity is lower in the Native Alaskan populations compared with Caucasians and Africans, almost all loci are highly polymorphic in all three Native Alaskan groups. There was little evidence for departures from Hardy-Weinberg expectations (HWE) in any of the populations. Only two examples of detectable departures from HWE out of 39 locus-population tests performed were observed based on the exact test (Yupik, D8S1179, P=0.030; Yupik, D5S818, P=0.016). The F(ST) estimate overall 13 STR loci is 0.0309 for the Native Alaskan populations. Based on a genetic distance measure, Athabaskans are more closely related to Apaches and Navajos (all of the same linguistic group) than the other Native Alaskan groups. The F(ST) estimate for Athabaskans, Apaches and Navajos is 0.0180 and for Inupiats and Yupiks is 0.0167. The allele frequency data can be used for estimating DNA profile frequencies for Native Americans residing in Alaska.     

Evolving profiles of financial risk management in the era of digitization: The tomorrow that began in the past

The initial phases of digitization have automatized the front‐end of banks and financial institutions (FIs). This paper documents the automation of the back‐end in the current wave of digitization. In particular, it highlights the use of technology in streamlining risk management and its potential to provide competitive advantage to the FIs embracing digitization. For instance, automated “big data” credit scoring tools built on predictive analytics and machine learning algorithms are employed to examine several credit propositions. This can accurately construct the credit worthiness and risk profile of public, even without any credit history. These developments can widen the access of credit and other financial services to the society. However, on a cautionary note, this study emphasizes that although digitization of back‐end financial transactions carries substantive advantages, the FIs must be guarded against cyber, outsourcing, financial exclusion, and macrofinance risks that can manifest with this automation. In this backdrop, the need for robust yet agile regulations and supervisory counsel to control and exploit the digitization towards optimal benefits for banks and FIs and society at large, acquires salience. Furthermore, regulators and supervisory authorities can mitigate the digitization risks and prevent any public fallout by leveraging the use of digitization itself.     

Comparisons of familial DNA database searching strategies

The current familial searching strategies are generally based on either Identity-By-State (IBS) (i.e., number of shared alleles) or likelihood ratio (i.e., kinship index [KI]) assessments. In this study, the expected IBS match probabilities given relationships and the logic of the likelihood ratio method were addressed. Further, the false-positive and false-negative rates of the strategies were compared analytically or by simulations using Caucasian population data of the 13 CODIS Short Tandem Repeat (STR). IBS ≥ 15, IBS ≥ 16, KI ≥ 1000, or KI ≥ 10,000 were found to be good thresholds for balancing false-positive and false-negative rates. IBS ≥ 17 and/or KI ≥ 1,000,000 can exclude the majority of candidate profiles in the database, either related or not, and may be an initial screening option if a small candidate list is desired. Polices combining both IBS and KI can provide higher accuracy. Typing additional STRs can provide better searching performance, and lineage markers can be extremely useful for reducing false rates.     

关于法庭科学DNA数据库若干问题的探讨

本文论述常染色体STR基因座的选取和数量对数据库直接匹配、亲缘关系检索、失踪人员检索等数据库检索应用可能带来的影响,指出大容量DNA数据库在应用中可能出现的问题,并讨论应用数据库时需要考虑的群体和群体内差异,以及Y染色体和线粒体DNA对数据库检索的辅助作用。旨在为今后建设和完善具有中国特色的大容量DNA数据库提供参考和帮助。     

World population data for the HLA-DQA1, PM and D1S80 loci with least and most common profile frequencies for combinations of loci estimated following NRC II guidelines

All published and unpublished gene frequency data for the PCR-based loci HLA-DQA1, LDLR, GYPA, HBGG, D7S8, GC, and D1S80 that could be located are presented in summary tables. These gene frequencies provide the data necessary for estimating probabilities of chance match according to NRC II guidelines for any DNA profile that includes any combination of these loci for any of the populations. To illustrate the range of polymorphism for combined locus profiles, least and most common profile frequencies were estimated following NRC II guidelines for: the PM loci for all populations for which PM data were available; and for combinations of HLA-DQA1/PM, HLA-DQA1/D1S80, PM/D1S80, and HLA-DQA1/ PM/D1S80 for populations for which data were available for the relevant combinations. The profile frequencies were calculated at theta values of zero and 0.01. Minimum allele frequencies (MAF) were calculated, and are shown, for each data set for which the MAF was greater than the lowest observed allele frequency. Least common profile frequencies were calculated using MAF in those cases to illustrate a conservative estimate. The effect of using MAF versus lowest observed allele frequency in estimating least common profile frequencies is briefly illustrated as well. We finally show that aggregate U.S. gene frequency data for the classical MN and GC polymorphisms for both Caucasian and African-American populations is fully in accord with the DNA-based gene frequency data obtained from PM reverse dot-blot strips for GYPA and GC, respectively.