Carbon nanotube/polymer nanocomposite plate- and shell-like structures will be the next generation lightweight structures in advanced applications due to the superior multifunctional properties combined with lightness. Here material optimization of carbon nanotube/polymer nanocomposite beams and shells is tackled via ad hoc nonlinear finite element schemes so as to control the loss of stability and overall nonlinear response. Three types of optimizations are considered: variable through-the-thickness volume fraction of random carbon nanotubes (CNTs) distributions, variable volume fraction of randomly oriented CNTs within the mid-surface, aligned CNTs with variable orientation with respect to the mid-surface. The collapse load, which includes both limit points and deformation thresholds, is chosen as the objective/cost function. An efficient computation of the cost function is carried out using the Koiter reduced order model obtained starting from an isogeometric solid-shell model to accurately describe the point-wise material distribution. The sensitivity to geometrical imperfections is also investigated. The optimization is carried out making use of the Global Convergent Method of Moving Asymptotes. The extensive numerical analyses show that varying the volume fraction distribution as well as the CNTs orientation can lead to significantly enhanced performances towards the loss of elastic stability making these lightweight structures more stable. The most striking result is that for curved shells, the unstable postbuckling response of the baseline material can be turned into a globally stable response maintaining the same amount of nanostructural reinforcement but simply tailoring strategically its distribution. Thin-walled, lightweight composite structures are commonly used in a wide range of engineering applications, particularly in aerospace engineering, where they are often employed as primary structural components. Due to the high strength-to-weight ratio, the mechanical response is dominated by buckling and turns out to be mainly influenced by two factors: the geometry and the elastic properties. While the former is often imposed by the structural functionality and only little variations are possible, the spatial distribution of the material properties  can be easily tailored in composite shells. Consequently, an efficient optimization process of the material distribution is required to obtain the desired structural response, usually defined in terms of deflections and load-carrying capacity. Many manufacturing options are also available to fine-tune the stiffness and the onset of buckling: grid stiffeners , multi-lA promising direction in the context of material optimization is that offered by nanostructured materials which can exhibit multifunctional properties and are thus prone to more advanced multi-objective optimizations. In this field, nanocomposite materials made of thermosetting or thermoplastic polymers integrated with carbon nanotubes (CNTs) are currently subject to intense developments due to their superior mechanical/electrical/thermal performance, electromagnetic shielding or energy storage capacity ,5,6,7. AMoreover, as known, optimal properties in composites are usually sought also by controlling the orientation of the fibers in each layer, since the fiber orientation significantly affects the stiffness distribution, hence, the load-carrying capability or the elastic limits states . AloThe Riks arc-length strategy ,17 is a In the optimization strategy presented in , the colMore recently, a solution algorithm based on Koiter’s theory implemented within a Finite Element environment was proposed in ,27. It aDespite the difficulties associated with the prediction of the nonlinear behavior, another challenge is the solution to the optimization problem. This is always expressed as a nonlinear, nonconvex mathematical programming problem whose solution is generally computationally expensive and extremely difficult because of the likely presence of multiple local minima. This is indeed the most penalizing aspect of the analysis. Among others, frequently employed solution strategies are the random search methods , geneticThis work addresses the optimization problem of nanocomposite shell-like structures with variable CNTs distributions. Three types of optimizations are tackled: (a) through-the-thickness CNT distribution in terms of volume fractions, (b) randomly oriented CNT distributions across the mid-surface in terms of volume fraction, (c) distribution of aligned CNTs across the mid-surface in terms of orientation. The collapse load, including limit points and deformation limits, is taken as the objective function. Its efficient estimate is carried out using a reduced order model (Koiter’s method) obtained starting from an isogeometric solid-shell model capable of accurately modeling the variable material distribution. The sensitivity to geometrical imperfections is also addressed as in . The optThe paper is organized as follows: This section describes the main equations of the solid-shell FE formulation (see ) used toh the shell thickness. The position vector Convective curvilinear shell coordinates i-th component of Note that while Assuming a linear through-the-thickness interpolation, the position vector is expressed asζ)=x0ζ1,ζ+2ζ3hxnqWeights, as well as control points of the initial geometry, are provided by the CAD model while suitable algorithms exist for the refinement required to approximate the unknown solution . The geoIsogeometric interpolation. In this subsection, the discrete isogeometric model used within the optimization strategy is summarized. The geometry is described by NURBS interpolation functions asal NURBS  functionBy following the isogeometric concept, the displacement field is interpolated using the same shape functions of the geometryThe Green–Lagrange strains in Equation , upon cofound in .Stored energy and equilibrium path. The stored energy of the shell can be evaluated using a numerical integration ase denotes the FE, g indicates the integration point and cts, see ,36).The system of discrete equilibrium equations is then obtained through enforcement of the stationarity of the total potential energy according tor=∂ΦOur aim is to tailor the nanostructured material distribution within the shell that leads to the optimization of a certain property of the nonlinear equilibrium path obtained  by solving the equilibrium problem later expressed by Equation . Before A compact expression of the effective elastic tensor for the constitutive law of the 3D continuum is given by(i)randomly orientated CNTs(ii)CNTs alignment along where Tensor orted in . Subsequgiven in . Two cas−0)  through-the-thickness optimization of the aligned CNTs volume fraction; (2) optimization of randomly orientated CNTs volume fraction; (3) optimization of the in-plane CNTs orientation. We will discuss each of these problems next.In the first case, the optimal distribution of CNTs parameters is obtained by changing the through-the-thickness CNTs distribution across the shell mid-surface.The volume fraction of CNTs is assumed to be distributed asBy simply increasing the polynomial order, more complex material distributions can be obtained. Considering a certain feature The optimal distribution of CNTs in this instance is obtained by changing the volume fraction As in the previous case, the CNTs volume faction distribution at a point of the domain can be obtained using Bernstein polynomials throughout the whole shell. The constitutive matrix The minimization problem is cast in the formThe CNTs are assumed to be aligned along a direction parallel to the shell mid-surface at an angle The optimization problem readsThe objective function. The optimization process is aimed at maximizing the collapse load of the nanocomposite shells. In buckling problems, the collapse load can be defined as the lower bound between the critical limit load The evaluation h method ,35. In th method ,27, in oh method . For thih method . Hence, h method  of the pKoiter’s method. The structure is first discretized using the isogeometric environment described in ariables (25)Φe=∑As shown in , this isg, Koiter’s method is based on the following reduced order model:ith of the n buckling modes, By collecting in vector found in ,36.According to this choice and after a few asymptotic expansions, it is possible to obtain the following nonlinear algebraic reduced system of equilibrium equations where the unknowns are The coefficients found in ,36.A remarkable advantage afforded by Koiter’s method is the possibility of performing computationally efficient and robust imperfection sensitivity analysis of elastic structures. Once Equation  has beenEquation  becomesThis means that all coefficients of  coincideEquation . In thisFor the evaluation of proposed . A firstproposed  and, by The Global Convergent Method of Moving Asymptotes. The optimal design problem is solved using a gradient-based optimizer, i.e., the Global Convergent Method of Moving Asymptotes (GCMMA) [ (GCMMA) ,38,39,40i-th component of the gradient is evaluated according to a forward finite difference scheme asd is a conveniently small finite difference and ith component is 1 while the others are zero.Constructing the gradient of the objective function with respect to the design parameters is not a simple task and is thus computed numerically. The Although the task of evaluating the objective function is extremely time-consuming when using the full discrete model, the efficiency of Koiter’s method allows its computational cost to be reduced to within an acceptable level. Moreover, since GCMMA generally converges with relatively few iterations, the number of gradient evaluations is small and the overall computational cost of the optimization is sustainable.-OPT1: through-the-thickness optimization, i.e., variable through-the-thickness distribution of aligned CNTs across the shell mid-surface with assigned mid-surface value;-OPT2: optimization across the mid-surface, i.e., the volume fraction of randomly oriented CNTs is kept constant through the thickness but can vary within the shell mid-surface with a constraint on the overall CNTs volume;-OPT3: optimization of the orientation, i.e., the CNTs volume is assigned, the orientation of the CNTs can vary across the shell mid-surface but is constant through the thickness.In this section, the CNTs distribution is optimized in order to improve the nonlinear response under buckling. The three types of optimizations discussed in Three applications are considered. The first samples are an Euler beam and a simply supported plate in compression exhibiting a stable post-buckling behavior. In this case, the optimizations are expected to provide a higher buckling load and a less compliant post-buckling response. The last test regards a curved panel, whose post-buckling behavior can be either stable or unstable depending on the material distribution. This is a more significant test to show the formidable potential of a variable CNTs distribution in the design of thin nanocomposite structures.We consider shells made of an isotropic polymeric matrix with Young modulus Two material descriptions over the mid-surface are considered: polynomials of order 4 and 9. Due to the problem symmetry, only the control points of a quarter of the structure are considered as independent variables, leading to For the OPT2 problem, the volume fraction bounds are set to It is worth noting that the effective CNTs volume fraction decreases by increasing rding to  as shownThis test consists of a simply supported Euler beam under compression on two opposite ends as shown in h. The deformation limit is set to v the mean value of the flexural displacement.This simple test is considered to show the correctness of the proposed numerical approach. A single linearized buckling mode is used to construct the ROM of the Koiter method and the geometrical imperfection. The imperfection shape is scaled such that the maximum deviation Optimization of the CNT volume fraction for random orientations. The optimization problem OPT2 only is considered because OPT1 and OPT3 do not yield any improvement for this specific problem. The results of OPT2 are compared with the performance of a uniform distribution of This test deals with a simply supported square plate under compression on two opposite sides as shown in The thickness was set to 5 mm while the span is 508 mm, and the uniform compression load was h being the shell thickness. The deformation limit is set to v being the mean value of the out-of-plane displacement. Due to the symmetry of the test, OPT1 does not provide any improvement compared to a uniform volume fraction distribution and is omitted. Instead, the focus is on OPT2 and OPT3, respectively.A single linearized buckling mode is used to construct the ROM of the Koiter method and the geometrical imperfection. The imperfection shape is scaled such that the maximum deviation Optimization of the CNTs volume fraction for random orientations. The optimization problem OPT2 is discussed here, making use of a comparison with the solution obtained for the uniform distribution of Optimization of the CNTs orientation within the mid-surface. The optimization problem OPT3 is investigated next. It consists in optimizing the orientation of the CNTs in the plate plane, while keeping the volume fraction constant. The results of OPT3 are compared with those corresponding to all CNTs uniformly aligned with the load direction (UD). The linearized buckling loads are reported in The last test in The optimizations seek the material distributions that maximize the collapse load considering as deformation limit the axial displacement of the loaded section Through-the-thickness optimization of aligned CNTs volume fraction. We start with the through-the-thickness optimization problem referred to as OPT1. The CNTs are aligned along the load direction. The results are compared with those obtained for a uniform through-the-thickness distribution (UD). First, Optimization of CNTs volume fraction for random orientations. The optimization problem OPT2 is considered next. The results are compared with the performance of a uniform distribution of randomly oriented CNTs (UD). First, we compare the linearized buckling loads reported in Optimization of CNTs orientation. The optimization problem OPT3 is finally discussed here. It consists of optimizing the CNTs orientation within the shell mid-surface, while keeping constant the volume fraction at each point of the structure. The results of OPT3 are compared with those obtained for uniformly aligned CNTs collinear with the load direction (UD). The linearized buckling loads are reported in This work tackled the new challenging problem of finding optimal distributions of the nanostructural reinforcement phase  within polymeric composite panels subject to buckling and snap-through.A numerical strategy for the optimization of the buckling and postbuckling response of nanocomposite shells with variable CNTs distribution was proposed and investigated. The method is based on an integrated isogeometric framework that employs NURBS functions to describe the geometry and displacements while the optimization variables deal with the CNT distributions within the polymer hosting matrix.Various CNTs distributions were investigated either through the thickness or within the mid-surface for both aligned CNTs, aligned but varying within the surface or randomly oriented. The obtained through-the thickness distributions can be practically realized in multilayer nanocomposite structures since a continuous law can be reasonably approximated by piece-wise functions when the multilayers are considered sufficiently thin.The outcomes of extensive numerical tests have proved that the limit load can be largely improved for optimal CNTs distributions in the sense of strategically deploying the nanofibers where the maximum elastic stiffness fighting against the negative stiffness can be attained.Most importantly, it has been shown that shallow shells, which are dangerously prone to snap-through, can become globally stable if the CNTs are optimally distributed. This is a remarkable result on the global stability of nanocomposite shallow shells which, when properly designed, do not show any snap-through and thus can be safely employed in engineering applications. Mention must be made of the fact that these nanocomposite panels also show the additional advantage of exhibiting enhanced damping capability thanks to the CNT/polymer interfacial dissipation which makes these structures generally more stable against dynamic loads.This work has shown the potential of optimizing nonlinear structural behaviors using the unprecedented flexibility afforded by the CNTs nanoreinforcement which not only acts to shift the elastic loss of stability towards higher stresses, but can also either suppress snap-through or make the response less compliant in the postbuckling range. The next step of the research will be the optimal design of high-performance and lightweight vehicles, aerostructures and devices.


Understanding the genetic structure of adaptation and productivity in challenging environments is necessary for designing breeding programs that suit such conditions. Crossbred dairy cattle in East Africa resulting from over 60 years of crossing exotic dairy breeds with indigenous cattle plus inter se matings form a highly variable admixed population. This population has been subject to natural selection in response to environmental stresses, such as harsh climate, low-quality feeds, poor management, and strong disease challenge. Here, we combine two complementary sets of analyses, genome-wide association (GWA) and signatures of selection (SoS), to identify genomic regions that contribute to variation in milk yield and/or contribute to adaptation in admixed dairy cattle of Kenya. Our GWA separates SNP effects due to ancestral origin of alleles from effects due to within-population linkage disequilibrium. The results indicate that many genomic regions contributed to the high milk production potential of modern dairy breeds with no region having an exceptional effect. For SoS, we used two haplotype-based tests to compare haplotype length variation within admixed and between admixed and East African Shorthorn Zebu cattle populations. The integrated haplotype score (iHS) analysis identified 16 candidate regions for positive selection in the admixed cattle while the between population Rsb test detected 24 divergently selected regions in the admixed cattle compared to East African Shorthorn Zebu. We compare the results from GWA and SoS in an attempt to validate the most significant SoS results. Only four candidate regions for SoS intersect with GWA regions using a low stringency test. The identified SoS candidate regions harbored genes in several enriched annotation clusters and overlapped with previously found QTLs and associations for different traits in cattle. If validated, the GWA and SoS results indicate potential for SNP-based genomic selection for genetic improvement of smallholder crossbred cattle. Exotic dairy breeds have been extensively imported to Kenya since the 1950s for use in crossbreeding aimed to improve the productivity of indigenous cattle by combining the environmental adaptation features of the latter with the high milk yield potential of the former. This has resulted in a large population of admixed cattle that, for several decades, have been subject to natural selection in response to different environmental stresses, such as harsh climate, low-quality feeds, poor management, and strong disease challenge. Smallholder farmers retain the admixed cattle typically in herds of size one to five cows and breed them mainly through natural mating to local bulls. A small proportion of matings (~10%) are made by AI to imported and locally produced purebred dairy bulls. There is no record of pedigree or performance of smallholder cattle and no current genetic improvement program for crossbred cattle. Genomic technologies can aid smallholder dairy farmers to develop genetically improved animals when the genetic improvement by traditional breeding schemes is impossible  if alleles in the admixed population can be correctly assigned to their ancestral origin. The latter can be done through methods that infer the ancestry of haplotypes, such as LAMP-LD  difference in milk production potential.With high-density SNP markers, it is possible to identify genomic regions that may be useful in future selection. This can be done through genome-wide association (GWA) analysis, which relies on linkage disequilibrium (LD) between SNPs and causal variants and requires phenotype plus genotype data, and by detection of signatures of selection, which only requires genotypic information. In admixed populations, the LD between SNP markers and causal variants can arise from the LD that existed in the parental populations that contributed to the admixed population and from When a beneficial allele increases in frequency by natural or artificial selection, the allele frequencies of neighboring loci in LD are also altered, and this creates extended blocks of haplotypes with increased LD and reduced variation. The changes in allele frequencies, LD, and genetic variation accumulate over time and generate unique patterns at specific regions of genome, which are referred to as signatures of selection  a GWA analysis that separates breed origin SNP effects from effects due to within-population LD to find SNPs associated with milk yield and (2) a signature of selection (SoS) analysis to detect signals of post-admixture selection. The GWA and SoS analyses are complementary because in relatively young populations, SoS are not expected to have led to fixation of alleles, and therefore, the results from one can be used as partial validation of the other.Bos indicus animals (IND) from 12 Indian breeds were obtained by stratified sampling of the larger data set analyzed by Strucken et al. (n = 24) and (ii) European taurine (EUT) ancestors of admixed cattle: Holstein , Jersey , Guernsey , British Friesian , and Ayrshire . All genotypes except BF and AY, which were provided by the Scottish Rural University College (SRUC) and Canadian Dairy Network (CDN), respectively, were obtained from the Bovine HapMap Consortium (http://bovinegenome.org). These genotypes were obtained post-quality control, so only the common SNPs between them and African and Indian genotypes were extracted. We sampled an equal number of 21 animals from each EUT breed and considered the five EUT breeds as recent ancestors of Kenyan admixed dairy cattle. SNPs with a MAF less than 0.01 across the whole sample were excluded. Animals were also required to have genotypes for more than 90% of SNPs. These controls resulted to 521,362 SNPs on 1,475 admixed, 19 EASZ, 105 IND, 24 AFT, and 105 EUT animals distributed over 29 autosomes based on the UMD3.1 bovine reference genome. Details of the cattle populations in this study are presented in The genotypic data included 1,475 admixed and 19 East African Shorthorn Zebu (EASZ) cattle sampled in Kenya between 2010 and 2014 and genotyped for 777,962 SNP markers using Illumina BovineHD BeadChip . More information on collection of samples can be found in Aliloo et al. . We retan et al. . ReferenMilk yield deviations (MYD) were obtained for the individual test-days of 1,034  Kenyan admixed cows in smallholder farms from the analyses of Brown et al. . In theiG) constructed using the VanRaden  based on all SNP genotypes after quality control  was implemented. The PCA was applied to a (co)variance matrix between all animals' genotypes  frequency of crossovers in haplotypes with lowest number of crossovers was used to rank the admixed animals.y is the vector of MYD of size n, 1n is a vector of ones, μ is the population mean term, β is a 2 × 1 vector containing the ancestral origin of allele effect and residual SNP effect, u contains polygenic effects assumed to be distributed as G being the genomic relationship matrix based on all SNP genotypes except the SNPs on the chromosome of the marker for which the association is tested  simultaneously estimated the effect of the ancestral origin (exotic vs. indigenous) of the SNP and the residual effects of SNP alleles after accounting for the ancestral origin. The local ancestry inferences obtained above were used to assign the ancestral origin of SNP alleles with ancestral origin coded as 0, 1, and 2 for no copies, one copy, or two copies coming from the EUT ancestor, respectively. The GWA model was as follows:p-values were supplied to the q-value package  and FDR thresholds.The above model was fitted by WOMBAT Meyer, . The SNPWe used two complementary haplotype-based methods to scan the genome of the admixed cattle for candidate regions under selection. The integrated haplotype score (iHS) is an intra-population measure of the extent of haplotype homozygosity  and the derived (iHHd) alleles, and then, the iHS was calculated as Kas,t is the number of distinct haplotypes from the core SNP s to SNP t carrying the core allele as, nk is the number of times the kth haplotype is observed, and nas is the total number of haplotypes carrying as and is calculated as p-values of “no selection” hypothesis according to Gautier and Naves  and derived (as = 2) alleles, and Kas,t is the number of distinct haplotypes from the core SNP s to SNP t carrying the core allele as. The iES was defined as the area under the EHHS curve at a core allele within a chromosome using a homozygosity decay threshold of 0.05. The Rsb score between admixed and EASZ cattle populations was defined as medRsb and σRsb are the median and standard deviation of Rsb across all SNPs within genome. The p-values for Rsb(s) were calculated according to Gautier and Naves (Rsb(s)) represents the Gaussian cumulative distribution function of Rsb(s) values. The qvalue package  by generating the corresponding q-values and FDR thresholds.The Rsb values between admixed and EASZ cattle populations were calculated within each chromosome according to Tang et al.  using thnd Naves :pRsb(s)We calculated measures of selection signatures in two scenarios. In the first scenario, all the admixed samples were used to obtain estimates of iHS. In the second scenario, admixed cattle with less than three crossovers were removed prior to iHS and Rsb analyses because they were deemed to be recently admixed individuals in which selection has not had enough time to leave a signature on their genome.q value < 0.1 and then searching within the 500-Kbp interval downstream and upstream (1 Mbp window) of the identified SNP for SNPs with q value < 0.5 and q value < 0.25 for iHS and Rsb analyses, respectively. We extended the detected region (with a 500-Kbp step size) until there was no SNP with a q value less than the suggestive thresholds within the 500-Kbp interval from the last identified SNP. The boundaries of the candidate region were determined based on the base pair positions of the last-identified SNP in each direction. The same procedure was used for iHS and Rsb analyses. Where GWA results were used for partial validation of SoS analyses (see below), we used a suggestive p-value threshold of 10−3 to define the candidate regions from GWA, and to define the boundaries of each candidate region, we searched the 500-Kbp upstream and downstream intervals for SNPs whose p-values were smaller than 10−3 and extended the region until there was no SNP p-value less than our suggestive threshold. The candidate regions designated by iHS and Rsb analyses were then annotated using the Ensemble Biomart 94 based on the UMD v3.1 bovine genome assembly for the underlying genes, and the biological functions of the discovered genes were evaluated and compared to the existing literature. We also calculated the ancestral allele dosages for the identified candidate regions in order to track the candidate regions under selection to each of the ancestral populations described above. In an attempt to validate SoS regions in the admixed cattle, we looked for overlap between the candidate regions identified in each of the SoS analyses, i.e., iHS or Rsb, and those identified by GWA.A candidate region detected by the SoS analyses was defined by first identifying SNPs with a https://www.animalgenome.org/cgi-bin/QTLdb/BT/index) on July 8, 2019, and was used to compare the results of the present study with the reported QTL regions in the literature. We compared the genes within our identified candidate regions for selection from iHS and Rsb analyses to the whole bovine genome background using functional annotation clustering by DAVID online bioinformatics resource v 6.8  were used to infer the local ancestries of the admixed cattle at the individual loci level. The majority of haplotypes in the admixed cattle were found to be originated from EUT ancestor (≈0.73), and IND and AFT ancestral populations contributed smaller proportions of admixed haplotypes . The genome-wide average ancestries of the three ancestral populations for each crossbred animal are shown in The distribution of number of recent crossovers on haplotypes with the lowest number of crossovers in different chromosomes is shown in The distribution patterns for the average local ancestries of admixed cattle with three or more recent crossovers per Morgan in haplotypes carrying the lowest number of crossovers are shown in The Manhattan plots of SNP allele effects and ancestral origin effects for MYD are presented in p-values for genome-wide iHS scores calculated using all samples of admixed cattle as well as when using only the admixed cattle with three or more crossovers per Morgan on the chromosomes with lowest frequency of crossovers are given in The Manhattan plots of p-values from Rsb analysis between the admixed cattle with a minimum number of three crossovers on the haplotype carrying the lowest number of crossovers across their genome and the EASZ population is shown in q value and highest peak in the Manhattan plot of The distribution of Because the SoS showed lower FDR than the results from the GWA analysis, for the purpose of investigating possible candidate genes, we chose to cross-validate the SoS that passed FDR < 0.1 with the GWA results. We used only the estimates of SNP allele effects because the confidence intervals for ancestral origin effects were very large. Four candidate regions from GWA, on BTAs 1, 7, and 20, overlapped with four candidate regions for selection obtained from iHS and Rsb analyses  appeared to work very well, yielding similar levels of indigenous vs. exotic admixture to previous Admixture analyses  are real effects. The distribution of ancestral origin effects  showed tThe distribution of estimated SNP effects  shows thWork is currently underway to phenotype and genotype much larger populations of crossbred dairy cows in East Africa. This will provide a future opportunity to validate the GWA results presented here. If some of these results are validated, it will be possible to identify groups of SNPs that track genomic region effects due either to within-population LD with causal variants or to ancestral genomic effects. In the latter case, SNPs can be chosen to provide a high accuracy of assigning ancestral haplotype allocation to the relatively large confidence regions encompassed by the ancestral QTL effects.When mapping signatures of selection, the null hypothesis of “no selection” typically implies a lack of statistical significance in situations where there is no disturbance from common demographic factors. Therefore, the ability to clearly distinguish positive selection from neutral effects is a challenge given the high sensitivity of the test statistics for detection of selection  productivity and (2) adaptation, recognizing that some regions might have pleiotropic effects in both categories. In the following, we characterize the functions of our identified regions in more detail.Several candidate regions from iHS and Rsb analyses intersected with previously reported QTLs and associations for milk and meat production traits in the literature. Milk and milk composition encompassed the highest number of overlaps among all traits for both methods. Given that there is no genetic improvement program for milk yield in the population of smallholder cows analyzed here, this might be due to phenotypic selection by farmers who preferentially keep progeny from their best yielding cows. However, it should be noted that the milk production under these poor-quality environments relies on other factors, such as the ability of cows to achieve acceptable growth and reproductive performance with restricted feed and in the presence of disease pathogens.GHR) gene that has been proved to play a central role in variation of milk production in dairy cattle , regulation of lipid metabolism (THEM5), and cell cycle progression and differentiation (S100A10) where the latter gene has also been reported as a candidate gene for residual feed intake in Angus . MSTN, also known as growth and differentiation factor-8 (GDF-8), has an important role in muscle development in cattle  and 21 (CSPG4). A candidate region on BTA 7 with a dominant IND ancestry extends from 41.40 to 42 Mbp and harbors the NLRP3 gene. This gene encodes a protein that is involved in regulation of inflammation, immune response, and apoptosis. It is also a candidate gene for Crohn's disease  that are involved in spermatogenesis and early embryonic development in humans  and regulate some important functions for reproduction. These findings suggest an advantage for inheriting genes of IND origin for fertility under heat stress conditions.Heat stress can have adverse effects on reproductive performance of cattle  are advantageous in different regions of the genome. If confirmed, it may be possible to use beneficial haplotypes in genetic improvement of crossbred performance.http://data.ilri.org/portal/dataset/dgea1-data-used-in-aliloo-et-al-2020. The reference genotypes used in this study can be accessed through direct requests to the respective data owners as indicated in the acknowledgments section.The phenotypic and genotypic data for the study population were collected by the Dairy Genetics East Africa (DGEA) project. The genetic data were collected under host country agreements that anticipated Article 5 of Nagoya Protocol of the United Nations Convention on Biodiversity (CBD). The data underlying this study is archived at the International Livestock Research Institute (ILRI) and request to access the data set can be made to Ethical review and approval was not required for the animal study because in the current study we accessed to already produced genotypes and no live animals were used.AO and JG designed the data collection program, including the phenotypes used for GWA. HA and JG conceived and designed the current analyses. RM undertook the initial analyses and produced the corrected data used for GWA. HA conducted all other analyses and drafted the manuscript. JG assisted with the interpretation of results and edited the manuscript. All authors read and approved the manuscript before submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Shadow-play, is an assistance solution for Table Tennis training, develops novice players' strokes and performing skills, and helps the players' brain to train in terms of the correct positioning and how the proper stroke technique feels. Most currently proposed training assistance systems are rarely used in actual applications, as they are expensive and their setup is complex. Thus, there is a need for a practical and low-cost intelligent system training assistance solution, as well as the possibility of using this solution comfortably to assist players. This paper specifies Forehand shadow play strokes movement and orientation sensory dataset for Table Tennis using a miniaturized low-powered, inexpensive and non- intrusive Inertial Measurement Unit (IMU) BNO055. We mounted the IMU on the center of a standard Table Tennis racket's surface. Eight novices, eight professional players, and three high ranked Table Tennis coaches participated in this research voluntarily. The Racket enabled us to collect players' strokes' time-series data responsively and sensitively. Collected sensory time-series data contains 1570 samples for the Basic, Topspin, and Push Forehand strokes of the players. Besides, all performed strokes were manually labeled and scored by the coaches simultaneously. The sensory dataset contains data from one 9-axis IMU  and Euler angles , mounted on the Racket. Based on the nature of the Forehand movements, the center of the surface was empirically determined to be the appropriate sensor placement in this experiment. We accomplished the collection of all samples under conditions that have been set by the coaches. The authors expect that the collected dataset can be used in a digital shadow-play coaching system to automatically send feedback to novice players when they practice shadow-play Table Tennis strokes individually. It was conducted to validate object sensors measurements in motion detection and quality evaluation of Table Tennis Forehand strokes. The developed Racket used during the data acquisition phase is as shown in ID.csv file is structured in 14 columns with various rows. Every single ID.CSV file contains the raw values of the racket movements and orientation released from the mounted IMU. Each AEliminating incomplete samplesThe Processed named folder consists of five subfolders, namely "Basic", "Topspin", "Push", "Clean-Players-Level" and "Clean-Sample-Scores". The name of the first three subfolders indicates the label of strokes and contains the captured strokes samples corresponding to the title of the strokes. Like the Raw folder, the other two subfolders are about the level of the players and the quality score of the stroke, respectively. We created the Processed folder contents after completion of the pre-processed phase. The pre-processing stage includes two main sections: 1) eliminate incomplete samples 2) splitting the time series data into fixed and equal segmentation BThe time-series signals segmentationWe collected 1,728 samples of the participants' Forehand shadow-play strokes. However, 158 of the samples were excluded from this research because the sensor did not capture the signals completely. Thus, 1570 samples are used as raw time-series signals in this paper. Therefore, we excluded the records of incomplete samples from the "Players-Level.csv" and "Scores.csv" files.CThe Experiment participantsAll acquired signals were passed through the Kalman Filter, and the values of the Euler angles were computed by fusing the sensory data of the IMU. Generally, the primary step in motion recognition tasks based on time series signals involves splitting signals into a fixed and equal length of segmentation by utilizing the sliding window technique 1Professional PlayersThe data set has been collected by the members of three groups: 1) Professional Table Tennis players 2) Novice Table Tennis Players, and 3) Table Tennis professional Coaches. A group of 16 participants comprising players of both genders participated in the creation of the self-collected dataset. The participants constituted two groups, namely Novice and Professional.2Novice PlayersThe professional players' group consisted of eight professional players who are experts in Table Tennis and have a national ranking. I.R. Iran Table Tennis Federation (TTF) in East Azerbaijan introduced these players as experienced and highly ranked. Moreover, most of the players also have national and international coaching certificates. All professional players performed Forehand strokes at least 60 times in the limited conditions.3Coach groupThe novice players group consisted of eight voluntary male/female first-year physical education and sport science undergraduate students attending the University of Tabriz Physical Education and Sport Science faculty during the fall semester of the 2019-2020 academic year. The students taking the Table Tennis course for the first time had reached the 4th session of the course. They had already learned about standard positioning and how to grip the Racket. Each novice player performed Forehand strokes at least 30 times in the given situation. It was tried to equalize the gender of the dataset in the selection of the volunteer players . Weights and heights' attributes of the players do not have a severe effect on the research's validation. Thus, we did not consider this biometric information.Three high-level ranked coaches who were introduced by I.R. Iran TTF acted as supervisors. They scored and labeled each performed stroke individually. Besides, the coaches contributed to the supervision of the data collection phase as well. The coach supervised each player's stroke performing speed, positioning, the racket gripping style and direction, and the posture of the Forehand strokes.As seen in 2AThe Experiment Hardware SetupBThe Experiment Data collection protocolsAs seen in All participants performed Forehand strokes at least 81 times. Players waited five seconds between each repetition. By utilizing the developed Racket, each captured sample contains 12 different values, where each value represents one of the tri-axis of the IMUs' sensors data separately. Discrete-time series data were collected from participants while they were performing a set of Forehands, namely Basic Forehand, Topspin Forehand, and Push Forehand. All data were collected in the I.R. Iran TTF approved sports hall. The two limiting conditions of the research are, 1) the limit on the speed of the strokes and, 2) the prior need for Forehands training . The waiting times were the only interruptions during the data collection phase. Players performed the strokes using their skills under the coaches' supervision. Table Tennis racket's movements and orientations while performing any type of stroke are complicated, mainly when focusing on Forehand techniques.In the case of Forehand strokes, evaluation variables may represent a comparatively high risk of bias. Thus, to avoid personal errors of judgment and obtain approximately more accurate evaluations, three coaches' points of view  were used in this paper. The coaches were placed around the Table Tennis table to observe each player's performance and the assigned scores of performed stroke qualities separately. The places were determined based on the coaches' best-observing conditions and eliminating blind spots associated with the players' arm. 3AData collection softwareBLabeling samplesThe BNO055 Sensor fusion software (BSX) is used for the recording of the fusion measurements from a 3- axis accelerometer, a 3-axis gyroscope, and a 3-axis magnetometer sensor. Moreover, the software provides the orientation measurements, so-called Euler angles as well.CScoring samplesWhat is more, beyond supervising the initial condition and pause time between two shadow-play executions, the coaches assigned the label of the strokes to every performed sample. The initial state for Forehands training is the positioning, the accurate racket direction (IMU side on top), and the way of gripping the Racket and posture of the Forehand strokes. The coaches noted all collected samples as one of the Forehand strokes type, namely Basic Forehand (B), Topspin (T), and Push (P).Five primary evaluation and scoring Forehand training metrics were adapted among the standard Table Tennis training parameters ,7 in thiThe placed coach group members around the table see  scored tWe used the method of performance scoring of some sports such as Gymnastic and Ice-skating. The following approach was used for each criterion. We used the average of the coaches' scores for each stroke of an individual player. The practical and close cooperation among all the paper parties  in the design and data collection phases of the current research overcomes the challenge mentioned in the recent Rajšp and Fister study The I.R. Iran TTF in Tabriz Ethics Committee approved the current paper, and all participants delivered their written agreement in advance.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Progressive non-syndromic sensorineural hearing loss (PNSHL) is the most common cause of sensory impairment, affecting more than a third of individuals over the age of 65. PNSHL includes noise-induced hearing loss (NIHL) and inherited forms of deafness, among which is delayed-onset autosomal dominant hearing loss (AD PNSHL). PNSHL is a prime candidate for genetic therapies due to the fact that PNSHL has been studied extensively, and there is a potentially wide window between identification of the disorder and the onset of hearing loss. Several gene therapy strategies exist that show potential for targeting PNSHL, including viral and non-viral approaches, and gene editing versus gene-modulating approaches. To fully explore the potential of these therapy strategies, a faithful in vitro model of the human inner ear is needed. Such models may come from induced pluripotent stem cells (iPSCs). The development of new treatment modalities by combining iPSC modeling with novel and innovative gene therapy approaches will pave the way for future applications leading to improved quality of life for many affected individuals and their families. In particular, progressive, late-onset, non-syndromic, sensorineural HL (PNSHL), including age-related HL , noise-induced hearing loss (NIHL), drug ototoxicity, and autosomal dominant (AD) HL, constitutes the most common causes of hearing impairment (Liu and Xu Hearing loss (HL) is the most frequent inherited sensory deficit in humans. The number of hearing-impaired individuals dramatically increases with aging. According to the World Health Organization’s estimate . Vibrations of this membrane then move the ossicles of the middle ear which in turn push on the oval window of the cochlea, generating a fluid wave in the spiral-shaped structure. This fluid wave causes the mechanosensitive hair cells of the cochlea to bend and initiate an action potential that is propagated to the brain stem.The pathophysiology of PNSHL is directly related to hair cell death and dysfunction; however, there are no regenerative of preventative interventions for individuals known to have genetic or environmental predispositions. Gene therapy is emerging as promising treatment strategy for PNSHL. The ear is particularly amenable to local administration of therapeutic agents: there are surgical approaches to the cochlea including intratympanic injection, allowing diffusion across the round window membrane, round window membrane injection, stapedotomy with oval window injection, and cochleostomy or canalostomy with injection Fig.  Sacheli. A curreA wealth of information on the inner ear pathophysiology of a large number of disease forms has been accrued, raising the possibility for targeted therapies. In this context, the delayed-onset and progressive nature of hearing impairment offers a suitable time window between genetic diagnosis and symptom manifestation, making PNSHL more amenable to preventative and protective therapeutic interventions. Development of gene- and cell-based therapies shows great potential to address PNSHL under a variety of conditions. Here, we focus on recent progress using induced pluripotent stem cells, iPSCs, to model inner ear-related deficits and the developments of gene therapy approaches to potentially treat the molecular mechanisms that underlie the loss of hearing.Stem cells are one promising avenue for developing a robust model of the human inner ear in vitro. Stem cells are defined by their capacity for self-renewal  and pluripotency . The potential of differentiation in to any cell type makes stem cells attractive for therapeutic development and research approaches Hans .There are multiple types of stem cells defined by their origin and their potency. The first stem cells to be described and used in research settings were embryonic stem cells (ESCs). These are collected from the inner cell mass of the 5-day-old, pre-implantation blastocyst. ESCs have the potential to differentiate into any cell of the body and so have played an important role in understanding the nature of stem cells as well as in disease modeling and potential therapeutics. However, the widespread use of ESCs may not be feasible due to the limitations in harvesting, as well as ethical concerns over the destruction of embryos for research purposes  which can be found throughout the body. Their function is to replace damaged cells and accelerate tissue healing (Davanger and Evensen A very promising avenue of work is the innovative application of induced pluripotent stem cell (iPSC) technology. This new line of research was first described by Yamanaka in 2006 when his group was able to reprogram mouse fibroblasts into stem cells through the transgenic expression of a limited cocktail of transcription factors whose normal expression is restricted to stem and progenitor cells  and even miRNAs  have been used to successfully reprogram somatic cells to iPSCs  separated by sequences that correspond to viral DNA (spacers). The CRISPR-associated proteins (Cas) are endonucleases that can recognize viral DNA and are able to degrade the foreign invader . The targeted region corresponds to the first 20 bp of the sgRNA. This region in the genome must be flanked by a protospacer adjacent motif (PAM). Each Cas enzyme requires a different PAM sequence, and this must be considered when designing a CRISPR protocol. Specifically, the PAM sequence for Cas9 is NGG . AAVs, unlike lentiviruses, do not incorporate the foreign DNA into the host genome, mitigating the risk of gene disruption and off-target effects , increasing efforts have been focused on hearing loss treatment strategies using AAVs. Several studies using AAVs have shown success in delivery of gene products to the inner ear in animal models  has been shown to efficiently transduce cells of the inner ear. It was generated by inserting three, cell-penetrating peptides into the VP1 capsid of AAV-DJ. The newly generated AAV-ie was found to have a particular tropism for the supporting cells of the inner ear, transducing up to 77% of supporting cells in vivo when delivered by round window injection to mice. The authors then used AAV-ie to deliver the Tmc1, fondly known as the Beethoven mouse, a single injection of a viral vector carrying an siRNA led to significant restoration of hearing  is a transcription factor important in human hair cell differentiation and has shown therapeutic benefit in mammalian models of NIHL and ototoxicity  may pave the way for other viral gene therapy trials.Another clinical trial NCT03996824 is also exploring AAV transduction of hair cells collected from patients undergoing non-conservative surgery for vestibular schwannomas. The study aims to show the efficacy and safety of viral transduction in vitro. Successful transduction will be assessed by immunofluorescence, and if shown to be safe, these studies  can be used to achieve the knockdown of deleterious gene products or in the case of dominant mutations. ASOs backbone structure is modified to evade degradation by DNAses and allow sustained therapeutic effects. After binding to the target mRNA, they can induce degradation of the transcript by endonuclease digestion, prevent translation by inhibiting ribosome recruitment, or prevent pre-mRNA splicing Holmlund . Lentz eBdnf  thresholds (Chen et al. In a recent study, iPSC-derived otic epithelial progenitor cells, expressing GFP, were transplanted into the Slc26a4-null mice. After 4 weeks of transplantation, GFP expression was found in MYO7A-positive cells at the site where inner hair cells were absent. In addition, fibers of spiral ganglion neurons that were in the vicinity of hair cell-like cells expressed synaptophysin strongly suggesting synaptic formation with transplant-derived hair cells (Chen et al. PNSHL is a prime target for the development of gene therapeutics. Current and future studies will pave the way for human trials to determine the efficacy of gene delivery and genome editing in treating hearing loss. The focus of gene therapy research recently has been on utilization of patient-derived iPSCs as a model and therapeutic tool in the treatment of genetically caused hearing loss. In addition, the efficiency of CRISPR/Cas9 genome editing in correction of mutant alleles has led to major advances in treatment of hearing loss in multiple animal models. The current state of research has demonstrated that the combination of iPSC modeling and CRISPR/Cas9 genome editing shows great potential of stem cell gene therapy in the cochlea Fig. . There i