Selectivity Filter Research Articles

Learning filter selection policies for interpretable image denoising in parametrised action space

AbstractThe denoising of images is an important research direction in computer vision. We consider the image denoising task as an estimation problem of the filtering policy related to image features, which is different from end‐to‐end image mapping. Commonly used simple filters such as gaussian filtering and bilateral filtering have fixed global denoising policies. However, the denoising policies of different filters can only adapt to limited image features. To solve this problem, we propose a method that applies different filters to different spatial ranges and adjusts the parameters of these filters simultaneously. Since not all filters can be easily transformed into differentiable forms and it is difficult to obtain paired datasets of filter action areas, we use reinforcement learning (RL) methods to estimate the spatial domain action range and adjustable parameters of filters, respectively. Furthermore, for removing higher intensity noise, simple filters can iteratively approximate higher‐order denoising policies and obtain more accurate and stable denoising results with the increase of iteration steps. Experimental results show that our proposed method can not only generate intuitive and interpretable denoising policies but also achieve comparable or better visual effects and computational efficiency than baseline methods.

Selection of a Particulate Filter for a Gasoline-Powered Vehicle Engine in Static and Dynamic Conditions

Current challenges in terms of exhaust emission limits are related to the reduction of the particle numbers in spark ignition direct injection engines. The article concerns the analysis of the thermodynamic parameters of engine operation, allowing the selection of the particulate filter configuration and its technical parameters. The designed system consisting of an internal combustion engine and an exhaust system with an exhaust gas treatment system should be sufficient to meet ecological requirements in the form of reducing particulate matter emissions. The analysis of particulate matter emissions for the system without a filter and with a filter installed in the engine exhaust system was carried out for the mass, number and dimensional distribution of particulate matter. The result was an assessment of filtration efficiency for the entire spectrum of particulate diameters in the identified engine operating ranges. As a result, it was found that the particulate filter used in the engine exhaust system effectively reduces the particle number due to the greater filtration efficiency of large particles. The summary of the work related to the analysis of the ecological parameters of a spark ignition engine with direct fuel injection was a simulation of road tests of a vehicle with the proposed modified vehicle exhaust system equipped with a particulate filter. For this configuration, the analysis of particulate number emissions in the parameterized engine operating areas showed that it is possible to meet the particulate number emission limits, and the obtained road emission results are fully acceptable in terms of the obtained absolute values.

Understanding adsorption behavior of Polysorbate-20 to sterile filters in therapeutic proteins final filtration process.

Surfactants are commonly used in the therapeutic protein manufacturing process as stabilizer. Polysorbate-20 (PS-20) is one of the most commonly used surfactants to mitigate protein aggregation in the therapeutic protein formulation. It has been observed that polysorbate can be adsorbed by sterile filters during the final filtration process, which poses risk of uneven distribution and potentially reduced polysorbate concentration in final products. In this study, we evaluated the PS-20 adsorption behavior using commonly used sterilizing-grade microfiltration (MF) membranes via a customized filtration set-up. The effect of membrane properties, including the membrane materials, modification, and layer configuration were studied. In addition, the effect of PS-20 concentration was evaluated and the PS-20 adsorption amount by each type of membranes was determined quantitatively and showed good agreement with the in-process adsorption results. Finally, the selection of sterile filters and strategy of pre-flush are discussed for ensuring accurate PS-20 content in the final therapeutic protein drug product.

A new filter-based gene selection approach in the DNA microarray domain

The high dimensionality of data hinders the learning ability of machine learning algorithms. Feature selection techniques can be used to reduce dimensionality, which is an important step for processing high-dimensional data. Feature selection solves this problem by removing irrelevant and redundant information, which can improve learning models, reduce calculation time, and improve learning accuracy. In this paper, a novel filter in mixed-attribute datasets for feature selection is proposed. The independent attributes are mixed or heterogeneous in the sense that both numerical and categorical attribute types may appear together in the same dataset. Based on the preordonnances theory, we use a new concept to quantify the relevance and redundancy of features even if there are heterogeneous (mixed-type) data. The technique for order preference by similarity to the ideal solution is one of the well-known multicriteria decision-making methods; it is utilized as a weighting and informative feature selection filter. To assess the effectiveness of the proposed method, several experiments, both simulated and real, are performed, including a comparison to other well-known filter methods. The experimental results show that, in most cases, the method yielded competitive results in comparison to other methods.

Selective Chemical Filters for VOF3: Tailoring MgF2 Filter Selectivity through Surface Chemistry

In order to synthesize chemical filters for the selective removal of volatile fluorides, commercial magnesium fluoride MgF2 with high specific surface area (HSA) was investigated. The amount of -OH groups substituting fluorine is not negligible, partly due to the high surface area, but also due to the synthesis route. These hydroxyl groups induce a Lewis basicity on the surface of metal fluorides. The amount of these Lewis basic sites has been tailored using fluorination with F2 gas. The sorption of VOF3, used as model gas, onto these fluorides was investigated. The versatility of surface chemistry as a function of a number of Lewis basic sites opens the way to filter selectivity mixture of volatile fluorides depending on their Lewis acidity. HSA MgF2 acts as a stable matrix towards the gas to be purified, and the selectivity may be achieved by a higher Lewis acidity of the gaseous impurity.

Analysis of Carica papaya Informs Lineage-Specific Evolution of the Aquaporin (AQP) Family in Brassicales.

Aquaporins (AQPs), a type of intrinsic membrane proteins that transport water and small solutes across biological membranes, play crucial roles in plant growth and development. This study presents a first genome-wide identification and comparative analysis of the AQP gene family in papaya (Carica papaya L.), an economically and nutritionally important fruit tree of tropical and subtropical regions. A total of 29 CpAQP genes were identified, which represent five subfamilies, i.e., nine plasma intrinsic membrane proteins (PIPs), eight tonoplast intrinsic proteins (TIPs), seven NOD26-like intrinsic proteins (NIPs), two X intrinsic proteins (XIPs), and three small basic intrinsic proteins (SIPs). Although the family is smaller than the 35 members reported in Arabidopsis, it is highly diverse, and the presence of CpXIP genes as well as orthologs in Moringa oleifera and Bretschneidera sinensis implies that the complete loss of the XIP subfamily in Arabidopsis is lineage-specific, sometime after its split with papaya but before Brassicaceae-Cleomaceae divergence. Reciprocal best hit-based sequence comparison of 530 AQPs and synteny analyses revealed that CpAQP genes belong to 29 out of 61 identified orthogroups, and lineage-specific evolution was frequently observed in Brassicales. Significantly, the well-characterized NIP3 group was completely lost; lineage-specific loss of the NIP8 group in Brassicaceae occurred sometime before the divergence with Cleomaceae, and lineage-specific loss of NIP2 and SIP3 groups in Brassicaceae occurred sometime after the split with Cleomaceae. In contrast to a predominant role of recent whole-genome duplications (WGDs) on the family expansion in B. sinensis, Tarenaya hassleriana, and Brassicaceae plants, no recent AQP repeats were identified in papaya, and ancient WGD repeats are mainly confined to the PIP subfamily. Subfamily even group-specific evolution was uncovered via comparing exon-intron structures, conserved motifs, the aromatic/arginine selectivity filter, and gene expression profiles. Moreover, down-regulation during fruit ripening and expression divergence of duplicated CpAQP genes were frequently observed in papaya. These findings will not only improve our knowledge on lineage-specific family evolution in Brassicales, but also provide valuable information for further studies of AQP genes in papaya and species beyond.

A Novel Hybrid Technique Combining Improved Cepstrum Pre-Whitening and High-Pass Filtering for Effective Bearing Fault Diagnosis Using Vibration Data.

Rolling element bearings (REBs) are an essential part of rotating machinery. A localised defect in a REB typically results in periodic impulses in vibration signals at bearing characteristic frequencies (BCFs), and these are widely used for bearing fault detection and diagnosis. One of the most powerful methods for BCF detection in noisy signals is envelope analysis. However, the selection of an effective band-pass filtering region presents significant challenges in moving towards automated bearing fault diagnosis due to the variable nature of the resonant frequencies present in bearing systems and rotating machinery. Cepstrum Pre-Whitening (CPW) is a technique that can effectively eliminate discrete frequency components in the signal whilst detecting the impulsive features related to the bearing defect(s). Nevertheless, CPW is ineffective for detecting incipient bearing defects with weak signatures. In this study, a novel hybrid method based on an improved CPW (ICPW) and high-pass filtering (ICPW-HPF) is developed that shows improved detection of BCFs under a wide range of conditions when compared with existing BCF detection methods, such as Fast Kurtogram (FK). Combined with machine learning techniques, this novel hybrid method provides the capability for automated bearing defect detection and diagnosis without the need for manual selection of the resonant frequencies. The results from this novel hybrid method are compared with a number of established BCF detection methods, including Fast Kurtogram (FK), on vibration signals collected from the project I2BS (An EU Clean Sky 2 project 'Integrated Intelligent Bearing Systems' collaboration between Schaeffler Technologies and the University of Southampton. Safran Aero Engines was the topic manager for this project) and those from three databases available in the public domain-Case Western Reserve University (CWRU), Intelligent Maintenance Systems (IMS) datasets, and Safran jet engine data-all of which have been widely used in studies of this kind. By calculating the Signal-to-Noise Ratio (SNR) of each case, the new method is shown to be effective for a much lower SNR (with an average of 30.21) compared with that achieved using the FK method (average of 14.4) and thus is much more effective in detecting incipient bearing faults. The results also show that it is effective in detecting a combination of several bearing faults that occur simultaneously under a wide range of bearing configurations and test conditions and without the requirement of further human intervention such as extra screening or manual selection of filters.

Underappreciated microplastic galaxy biases the filter-based quantification

Long-term environmental loading of microplastics (MPs) causes alarming exposure risks for a variety of species worldwide, considered a planetary threat to the well-being of ecosystems. Robust quantitative estimates of MP extents and featured diversity are the basis for comprehending their environmental implications precisely, and of these methods, membrane-based characterizations predominate with respect to MP inspections. However, though crucial to filter-based MP quantification, aggregation statuses of retained MPs on these substrates remain poorly understood, leaving us a “blind box” that exaggerates uncertainty in quantitive strategies of preselected areas without knowing overview loading structure. To clarify this uncertainty and estimate their impacts on MP counting, using MP imaging data assembled from peer-reviewed studies through a systematic review, here we analyze the particle-specific profiles of MPs retained on various substrates according to their centre of mass with a fast-random forests algorithm. We visualize the formation of distinct galaxy-like MP aggregation—similar to the solar system and Milky Way System comprised of countless stars—across the pristine and environmental samples by leveraging two spatial parameters developed in this study. This unique pattern greatly challenges the homogeneously or randomly distributed MP presumption adopted extensively for simplified membrane-based quantification purposes and selective ROI (region of interest) estimates for smaller-sized plastics down to the nano-range, as well as the compatibility theory using pristine MPs as the standard to quantify the presence of environmental MPs. Furthermore, our evaluation with exemplified numeration cases confirms these location-specific and area-dependent biases in many imaging analyses of a selective filter area, ascribed to the minimum possibility of reaching an ideal turnover point for the selective quantitive strategies. Consequently, disproportionate MP schemes on loading substrates yield great uncertainty in their quantification processing, highlighting the prompt need to include pattern-resolved calibration prior to quantification. Our findings substantially advance our understanding of the structure, behavior, and formation of these MP aggregating statuses on filtering substrates, addressing a fundamental question puzzling scientists as to why reproducible MP quantification is barely achievable even for subsamples. This study inspires the following studies to reconsider the impacts of aggregating patterns on the effective counting protocols and target-specific removal of retained MP aggregates through membrane separation techniques.

Pruning Networks With Cross-Layer Ranking & k-Reciprocal Nearest Filters.

This article focuses on filter-level network pruning. A novel pruning method, termed CLR-RNF, is proposed. We first reveal a "long-tail" pruning problem in magnitude-based weight pruning methods and then propose a computation-aware measurement for individual weight importance, followed by a cross-layer ranking (CLR) of weights to identify and remove the bottom-ranked weights. Consequently, the per-layer sparsity makes up the pruned network structure in our filter pruning. Then, we introduce a recommendation-based filter selection scheme where each filter recommends a group of its closest filters. To pick the preserved filters from these recommended groups, we further devise a k -reciprocal nearest filter (RNF) selection scheme where the selected filters fall into the intersection of these recommended groups. Both our pruned network structure and the filter selection are nonlearning processes, which, thus, significantly reduces the pruning complexity and differentiates our method from existing works. We conduct image classification on CIFAR-10 and ImageNet to demonstrate the superiority of our CLR-RNF over the state-of-the-arts. For example, on CIFAR-10, CLR-RNF removes 74.1% FLOPs and 95.0% parameters from VGGNet-16 with even 0.3% accuracy improvements. On ImageNet, it removes 70.2% FLOPs and 64.8% parameters from ResNet-50 with only 1.7% top-five accuracy drops. Our project is available at https://github.com/lmbxmu/CLR-RNF.

Structural basis for human Cav1.2 inhibition by multiple drugs and the neurotoxin calciseptine

Cav1.2 channels play crucial roles in various neuronal and physiological processes. Here, we present cryo-EM structures of human Cav1.2, both in its apo form and in complex with several drugs, as well as the peptide neurotoxin calciseptine. Most structures, apo or bound to calciseptine, amlodipine, or a combination of amiodarone and sofosbuvir, exhibit a consistent inactivated conformation with a sealed gate, three up voltage-sensing domains (VSDs), and a down VSDII. Calciseptine sits on the shoulder of the pore domain, away from the permeation path. In contrast, when pinaverium bromide, an antispasmodic drug, is inserted into a cavity reminiscent of the IFM-binding site in Nav channels, a series of structural changes occur, including upward movement of VSDII coupled with dilation of the selectivity filter and its surrounding segments in repeat III. Meanwhile, S4-5III merges with S5III to become a single helix, resulting in a widened but still non-conductive intracellular gate.

Thermal management of tungsten by spectrally selective thin film optical filters under laser illumination

Surface temperature management of refractory metals, such as Tungsten, is crucial for their use in high-temperature applications like aerospace, defense, and laser instruments. In this study, distributed Bragg reflectors (DBR) were utilized to reduce the temperature caused by intense laser illumination. To address this problem, we developed a coupled optical and thermal model and investigated multiple factors, including material composition, morphology, architecture, and source-related parameters, such as wavelength. Our results indicate that our DBR coating designs can significantly decrease the temperature of the Tungsten.

A study on the implementation of nonlinear Kalman filter applying MMG model

Many technologies need to be established to realize autonomous ships. In particular, accurate state estimation in real time is one of the most important technologies. In the ship and ocean engineering fields, there have been many studies on state estimation using nonlinear Kalman filters. Several methods have been proposed for nonlinear Kalman filters. However, there is insufficient verification on the selection of which filter should be applied among them. Therefore, this study aims to validate the filter selection to provide a guideline for filter selection. The effects of modeling error, observation noise, and type of maneuvers on the estimation accuracy of the unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF) used in this study were investigated. In addition, it was verified whether filtering could be performed in real time. The results show that modeling error significantly impacts the estimation accuracy of the UKF and EnKF. However, the observation noise and types of maneuvers did not have an impact like the modeling error. Thus, we obtained the guideline that UKF and EnKF should be used differently depending on the required computation time. We also obtained that keeping the modeling error sufficiently small is essential to improving the estimation accuracy.

A novel TWIK2 channel inhibitor binds at the bottom of the selectivity filter and protects against LPS-induced experimental endotoxemia in vivo

TWIK2 channel plays a critical role in NLRP3 inflammasome activation and mice deficient in TWIK2 channel are protected from sepsis and inflammatory lung injury. However, inhibitors of TWIK2 channel are currently in an early stage of development, and the molecular determinants underlying the chemical modulation of TWIK2 channel remain unexplored. In this study, we identified NPBA and the synthesized derivative NPBA-4 potently and selectively inhibited TWIK2 channel by using whole-cell patch clamp techniques. Furthermore, the mutation of the last residues of the selectivity filter in both P1 and P2 (i.e., T106A, T214A) of TWIK2 channel substantially abolished the effect of NPBA on TWIK2 channel. Our data suggest that NPBA blocked TWIK2 channel through binding at the bottom of the selectivity filter, which was also supported by molecular docking prediction. Moreover, we found that NPBA significantly suppressed NLRP3 inflammasome activation in macrophages and alleviated LPS-induced endotoxemia and organ injury in vivo. Notably, the protective effects of NPBA against LPS-induced endotoxemia were abolished in Kcnk6-/- mice. In summary, our study has uncovered a series of novel inhibitors of TWIK2 channel and revealed their distinct molecular determinants interacting TWIK2 channel. These findings provide new insights into the mechanisms of pharmacological action on TWIK2 channel and opportunities for the development of selective TWIK2 channel modulators to treat related inflammatory diseases.

Religious Filter Bubbles on Digital Public Sphere

The aim of the study is to present the online processes related to religious phenomena appearing on digital platforms, primarily the practice of content filtering (gatekeeping, echo chamber, filter bubble), and a critical review of the scientific literature on the field. At the same time, the goal is to create a theoretical introduction to the special issue and a comprehensive examination of the scientific context. For the first time, the study shows that, in terms of media content, filtering can appear from two directions. One is the selections from different events by professional journalists during content creation. The media theoretical literature refers to this aspect as the phenomenon of gatekeeping. Filtering in the other direction takes place on the part of the receivers, who choose from among the available media contents. This phenomenon has already been described by several media scholars, with the concept of selective exposure (Klapper), Daily Me (Negroponte), echo chamber (Sunstein) or filter bubble (Pariser). Focusing on the phenomenon of the filter bubble, the study presents this theory, its criticism and its relevance to religious content and religious communities. The second part of the study focuses on religious filter bubbles and presents the related investigations so far. It analyses in detail the document published by the Catholic Church on 28 May 2023, entitled Towards Full Presence, Pastoral Reflection on Engagement with Social Media. During the detailed analytical presentation of the text, the study covers how the opportunities and dangers of network communication and the use of social media appear (including the filter bubble) and what solutions the Catholic Church proposes in this regard.

A filter-based feature selection approach in multilabel classification

Multi-label classification is a fast-growing field of machine learning. Recent developments have shown several applications, including social media, healthcare, bio-molecular analysis, scene, and music classification associated with the multilabel classification. In classification problems, multiple labels (multilabel or more than one class label) are assigned to an unseen record instead of a single-label class assignment. Feature selection is a preprocessing phase used to identify the most relevant features that could improve the accuracy of the multilabel classifiers. The focus of this study is the feature selection method in multilabel classification. The study used a feature selection filter method involving the Fisher score, analysis of variance test, mutual information, Chi-Square, and ensembles of these statistical methods. An extensive range of machine learning algorithms is applied in the modelling phase of a multilabel classification model that includes binary relevance, classifier chain, label powerset, binary relevance KNN, multi-label twin support vector machine, multi-label KNN. Besides, label space partitioning and majority voting of ensemble methods are used and Random Forest is the base learner. The experiments are carried out over five different multilabel benchmarking datasets. The evaluation of the classification model is measured using accuracy, precision, recall, F1 score, and hamming loss. The study demonstrated that the filter methods (i.e. mutual information) having top weighted to features provided significant outcomes.

Intracellular Plasmodium aquaporin 2 is important for sporozoite production in the mosquito vector and malaria transmission.

Malaria remains a devastating disease and, with current measures failing to control its transmission, there is a need for novel interventions. A family of proteins that have long been pursued as potential intervention targets are aquaporins, which are channels facilitating the movement of water and other solutes across membranes. We identify an aquaporin in malaria parasites and demonstrate that it is important for completion of Plasmodium development in the mosquito vector. Disruption of AQP2 in the human parasite Plasmodium falciparum and the rodent parasite Plasmodium berghei blocks sporozoite production inside oocysts established on mosquito midguts, greatly limiting parasite infection of salivary glands and transmission to a new host. In vivo epitope tagging of AQP2 in P. berghei, combined with immunofluorescence assays, reveals that the protein is localized in vesicle-like organelles found in the cytoplasm of gametocytes, ookinetes, and sporozoites. The number of these organelles varies between individual parasites and lifecycle stages suggesting that they are likely part of a dynamic endomembrane system. Phylogenetic analysis confirms that AQP2 is unique to malaria and closely related parasites and most closely resembles intracellular aquaporins. Structure prediction analyses identify several unusual features, including a large accessory extracellular loop and an arginine-to-phenylalanine substitution in the selectivity filter principally determining pore function, a unique feature among known aquaporins. This in conjunction with the importance of AQP2 for malaria transmission suggests that AQP2 may be a fruitful target of antimalarial interventions.

Design and analysis of highly selective ultrawide stopband lowpass filter using lumped and distributed equivalent circuit models

AbstractAn ultrawide stopband lowpass filter is reported using three stepped impedance resonators with high selectivity. The filter extends the stopband frequency range and attenuation, and two quarter‐wave open stubs and three circular ground slots are introduced. The lumped and distributed equivalent models are derived and analyzed. The corresponding results are validated experimentally in a fabricated prototype. The prototype lowpass filter has a 3 dB cutoff frequency (fc) of 2.9 GHz, and the stopband is extended up to 35 GHz (12.07fc), with an attenuation level better than 20 dB throughout. The passband‐to‐stopband transition (3 dB–20 dB) bandwidth is 0.18 GHz, and the roll‐off factor is 135 dB/GHz at 30 dB. The insertion loss is 0.3 dB at 1.6 GHz. The normalized circuit size of the proposed filter with respect to the guided wavelength is 0.04.

Role of Hydrophobic Amino-Acid Side-Chains in the Narrow Selectivity Filter of the CFTR Chloride Channel Pore in Conductance and Selectivity.

Cystic fibrosis is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) anion channel. Structural analysis of CFTR has identified a narrow, hydrophobic region close to the extracellular end of the open channel pore that may function as a selectivity filter. The present study combines comprehensive mutagenesis of hydrophobic amino-acid side-chains within the selectivity filter with functional evaluation of channel Cl- conductance and anion selectivity. Among these hydrophobic amino-acids, one (F337) appears to play a dominant role in determining both conductance and selectivity. Anion selectivity appears to depend on both side-chain size and hydrophobicity at this position. In contrast, conductance is disrupted by all F337 mutations, suggesting that unique interactions between permeating Cl- ions and the native phenylalanine side-chain are important for conductance. Surprisingly, a positively charged lysine side-chain can be substituted for several hydrophobic residues within the selectivity filter (including F337) with only minor changes in pore function, arguing against a crucial role for overall hydrophobicity. These results suggest that localized interactions between permeating anions and amino-acid side-chains within the selectivity filter may be more important in determining pore functional properties than are global features such as overall hydrophobicity.

Multi-wavelength fiber laser via evanescent field confinement with Al2O3 nanolaminate-coated thinned fiber

We present the fabrication and analysis of an Erbium-doped optical fiber laser emitting at multiple wavelengths. This is accomplished via a filter constructed from a fiber taper coated with alumina (Al2O3). The taper is created using the flame brushing induction technique with a combination of Butane (25 %) and Oxygen (75 %). The diameter is reduced to a 20 µm waist and 2 mm burner displacement. The thin film of Al2O3 was deposited via atomic layer deposition (ALD), resulting in a 15 nm layer. The coated fiber taper was then inserted into a ring fiber laser cavity functioning as a selector filter. This fiber laser produced an output comprising six simultaneous wavelengths: 1531.14, 1531.79, 1532.45, 1541.85, 1544.45, and 1562.22 nm. Laser signal stability tests were performed for one hour at 25 °C at the six emission wavelengths, resulting in a maximum optical power fluctuation of 0.15 to 0.33 dB, a wavelength shift variation of 0.02 nm, and a signal-to-noise ratio of 31.79 dB in average. The laser lines emitted have an average spectral width of 0.06 nm. Our results show that the typical performance of the fiber laser configuration based on an optical fiber taper was improved by the addition of the Al2O3 layer and can be further improved. Our findings demonstrate that the standard operation of the fiber laser setup, which utilizes an optical fiber taper, was enhanced through the incorporation of an Al2O3 layer and has the potential for further development.

Ethnicity-Related Partner Selection Experiences Among Young Adults from Christian Armenian Families: A Qualitative Study in Turkey

ABSTRACT In this qualitative study partner selection experiences of young Armenian adults were examined using Ecological Systems Theory and Filter Theory as a theoretical basis. The literature review of partner selection was reviewed in three subtitles as theoretical foundations of partner selection, partner selection studies in Turkey, and intermarriage and intramarriage in Armenians. The study was conducted with 10 participants and data analysis was undertaken through thematic analysis using MAXQDA. This approach emerged nine themes and eight subthemes across four levels. Individuals’ Filters and Preferences about Partner Selection Level themes were as follows: 1. Choosing an Armenian partner is a priority, 2. Importance of the Partner’s Ethnic Identity is Highlighted for Long-Term Relationships, 3. Implementing other selection filters than ethnic identity, 4. Advising Armenian Partner to Children without Rigid Restrictions. Impact of Immediate Social Environment level emerged as Theme 5: Community disapproves and judges out-group marriages, 6. Friends tend to select Armenian partners w/out isolating others, and 7. Families implement and contain partner restriction, Social Connection Level theme revealed: 8. Strength of ties to Armenian Culture/Community promote deeper interiorizing of ingroup partner selection, Attitudes and Ideologies of the Culture Level emerged as 9. Concerns about sustaining culture/population promote in group partner selection. Themes and Subthemes were elaborated upon and discussed in the results and discussion sections providing comprehensive insight into the partner selection experiences of young Armenian Adults. Thematic analysis of the interviews exhibited the interaction of the larger social systems during the partner selection process of Armenian young adults. Thus, this study introduced an extended framework illuminating partner selection experiences among ethnic minorities in the Turkish context