Background: The Norwegian Mother, Father, and Child Cohort Study (MoBa) is a population-based pregnancy cohort, which includes approximately 114,500 children, 95,200 mothers, and 75,200 fathers. Genotyping of MoBa has been conducted through multiple research projects, spanning several years; using varying selection criteria, genotyping arrays, and genotyping centres. MoBa contains numerous interrelated families, which necessitated the implementation of a family-based quality control (QC) pipeline that verifies and accounts for diverse types of relatedness. Methods: The MoBaPsychGen pipeline, comprising pre-imputation QC, phasing, imputation, and post-imputation QC, was developed based on current best-practice protocols and implemented to account for the complex structure of the MoBa genotype data. The pipeline includes QC on both single nucleotide polymorphism (SNP) and individual level. Phasing and imputation were performed using the publicly available Haplotype Reference Consortium release 1.1 panel as a reference. Information from the Medical Birth Registry of Norway and MoBa questionnaires were used to identify biological sex, year of birth, reported parent-offspring (PO) relationships, and multiple births (only available in the offspring generation). Results: In total, 207,569 unique individuals (90% of the unique individuals included in the study) and 6,981,748 SNPs passed the MoBaPsychGen pipeline. The relatedness checks performed throughout the pipeline allowed identification of within-generation and across-generation first-degree, second-degree, and third-degree relatives. The individuals passing post-imputation QC comprised 64,471 families ranging in size from singletons to 84 unique individuals (singletons are included as families as other family members may not have been genotyped, imputed, or passed post-imputation QC). The relationships identified include 287 monozygotic twin pairs, 22,884 full siblings, 117,004 PO pairs, 23,299 second-degree relative pairs, and 10,828 third-degree relative pairs. Discussion: MoBa contains a highly complex relatedness structure, with a variety of family structures including singletons, PO duos, full (mother, father, child) PO trios, nuclear families, blended families, and extended families. The availability of robustly quality-controlled genetic data for such a large cohort with a unique extended family structure will allow many novel research questions to be addressed. Furthermore, the MoBaPsychGen pipeline has potential utility in similar cohorts.

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To communicate at the nanoscale, researchers have proposed molecular communication as an energy-efficient solution. The drawback to this solution is that the histogram of the molecules' hitting times, which constitute the molecular signal at the receiver, has a heavy tail. Reducing the effects of this heavy tail, inter-symbol interference (ISI), has been the focus of most prior research. In this paper, a novel way of decreasing the ISI by defining a counting region on the spherical receiver's surface facing towards the transmitter node is proposed. The beneficial effect comes from the fact that the molecules received from the back lobe of the receiver are more likely to be coming through longer paths that contribute to ISI. In order to justify this idea, the joint distribution of the arrival molecules with respect to angle and time is derived. Using this distribution, the channel model function is approximated for the proposed system, i.e., the partially counting absorbing spherical receiver. After validating the channel model function, the characteristics of the molecular signal are investigated and improved performance is presented. Moreover, the optimal counting region in terms of bit error rate is found analytically.

A basic property of any diffusion-based molecular communication system is the geometry of the enclosing container. In particular, the geometry influences the system's behavior near the boundary and in all existing modulation schemes governs receiver design. However, it is not always straightforward to characterize the geometry of the system. This is particularly the case when the molecular communication system operates in scenarios where the geometry may be complex or dynamic. In this paper, we propose a new scheme-called equilibrium signaling-which is robust to uncertainties in the geometry of the fluid boundary. In particular, receiver design only depends on the relative volumes of the transmitter or receiver, and the entire container. Our scheme relies on reversible reactions in the transmitter and the receiver, which ensure the existence of an equilibrium state into which information is encoded. In this case, we derive near optimal detection rules and develop a simple and effective estimation method to obtain the container volume. We also show that equilibrium signaling can outperform classical modulation schemes, such as concentration shift keying, under practical sampling constraints imposed by biological oscillators.

One promising technique for communicating at the nanoscale is molecular communication (MC). In a molecular-communication-via-diffusion-scenario, the memory component of the channel is very high. This gives rise to what is known as inter-symbol interference. Traditional channel coding schemes cannot be utilized in MC due to the high memory. In this paper, a novel low complexity channel coding method is proposed for the molecular communication domain. The design of the proposed channel code takes into account the capability of a nano-device and the characteristics of the molecular communication channel. Simulation results confirm that the proposed method provides a significant improvement in terms of bit error rate. Moreover, a proof-of-concept implementation of the proposed coding scheme is done on a macro-scale testbed. The reliability of the communication link is shown to be significantly increased. INDEX TERMS Molecular communications, nanonetworking, diffusion channel, channel coding. ALI E. PUSANE (Senior Member, IEEE) received the B.Sc. and M.Sc. degrees in electronics and communications engineering from Istanbul Technical University, Istanbul, Turkey, in 1999 and 2002, respectively, and the M.Sc. degree in electrical engineering, the M.Sc. degree in applied mathematics, and the Ph.D. degree in electrical engineering from the