HUBUNGAN ANTARA DYADIC STRESS DENGAN KEPUASAN PERNIKAHAN PADA REMAJA PUTRI YANG MENIKAH DI ACEH SELATAN

ABSTRAKPernikahan tidak hanya terjadi pada usia dewasa, namun pernikahan pada usia remaja juga masih terjadi termasuk di Aceh Selatan. Pernikahan pada usia remaja dapat melemahkan kepuasan pernikahan. Salah satu hal yang dapat menyebabkan terjadi redahnya kepuasan pernikahan adalah stres yang dialami individu didalam pernikahannya (dyadic stress). Tujuan penelitian ini untuk melihat hubungan antara dyadic stress dengan kepuasan pernikahan pada remaja putri yang menikah di Aceh Selatan. Data dikumpulkan melalui Multidimensional Stress Questionnaire for Couples (MDS-Q) dan ENRICH (Evaluation and Nurturing Relationship Issues, Communication and Happiness) Marital Satisfaction (EMS) Scale melalui teknik purposive sampling. Sebanyak 60 remaja putri terlibat dalam penelitian ini (x ?=19.75). Analisis data menggunakan teknik korelasi Spearman menunjukkan nilai r= -0.777, p= 0.000 (p < 0.05), sehingga dapat diartikan bahwa terdapat hubungan negatif dan signifikan antara dyadic stress dengan kepuasan pernikahan pada remaja putri yang menikah di Aceh Selatan. Hal ini mengindikasikan semakin tinggi dyadic stress maka semakin rendah kepuasan pernikahan, demikian juga sebaliknya. Kata kunci : Dyadic Stres, Kepuasan Pernikahan, Remaja Putri, Menikah

Disguise without Disruption: Utility-Preserving Face De-Identification

With the rise of cameras and smart sensors, humanity generates an exponential amount of data. This valuable information, including underrepresented cases like AI in medical settings, can fuel new deep-learning tools. However, data scientists must prioritize ensuring privacy for individuals in these untapped datasets, especially for images or videos with faces, which are prime targets for identification methods. Proposed solutions to de-identify such images often compromise non-identifying facial attributes relevant to downstream tasks. In this paper, we introduce Disguise, a novel algorithm that seamlessly de-identifies facial images while ensuring the usability of the modified data. Unlike previous approaches, our solution is firmly grounded in the domains of differential privacy and ensemble-learning research. Our method involves extracting and substituting depicted identities with synthetic ones, generated using variational mechanisms to maximize obfuscation and non-invertibility. Additionally, we leverage supervision from a mixture-of-experts to disentangle and preserve other utility attributes. We extensively evaluate our method using multiple datasets, demonstrating a higher de-identification rate and superior consistency compared to prior approaches in various downstream tasks.Comment: Accepted at AAAI 2024. Paper + supplementary materia

Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press

The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects

Local atomic stacking and symmetry in twisted graphene trilayers

Moir\'e superlattices formed from twisting trilayers of graphene are an ideal model for studying electronic correlation, and offer several advantages over bilayer analogues, including more robust and tunable superconductivity and a wide range of twist angles associated with flat band formation. Atomic reconstruction, which strongly impacts the electronic structure of twisted graphene structures, has been suggested to play a major role in the relative versatility of superconductivity in trilayers. Here, we exploit an inteferometric 4D-STEM approach to image a wide range of trilayer graphene structures. Our results unveil a considerably different model for moir\'e lattice relaxation in trilayers than that proposed from previous measurements, informing a thorough understanding of how reconstruction modulates the atomic stacking symmetries crucial for establishing superconductivity and other correlated phases in twisted graphene trilayers.Comment: 18 pages, 5 figure

LYVE-1+ macrophages form a collaborative CCR5-dependent perivascular niche that influences chemotherapy responses in murine breast cancer

Tumor-associated macrophages (TAMs) are a heterogeneous population of cells that facilitate cancer progression. However, our knowledge of the niches of individual TAM subsets and their development and function remain incomplete. Here, we describe a population of lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1)-expressing TAMs, which form coordinated multi-cellular “nest” structures that are heterogeneously distributed proximal to vasculature in tumors of a spontaneous murine model of breast cancer. We demonstrate that LYVE-1+ TAMs develop in response to IL-6, which induces their expression of the immune-suppressive enzyme heme oxygenase-1 and promotes a CCR5-dependent signaling axis, which guides their nest formation. Blocking the development of LYVE-1+ TAMs or their nest structures, using gene-targeted mice, results in an increase in CD8+ T cell recruitment to the tumor and enhanced response to chemotherapy. This study highlights an unappreciated collaboration of a TAM subset to form a coordinated niche linked to immune exclusion and resistance to anti-cancer therapy

Microfluidic affinity selection of active SARS-CoV-2 virus particles

We report a microfluidic assay to select active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral particles (VPs), which were defined as intact particles with an accessible angiotensin-converting enzyme 2 receptor binding domain (RBD) on the spike (S) protein, from clinical samples. Affinity selection of SARS-CoV-2 particles was carried out using injection molded microfluidic chips, which allow for high-scale production to accommodate large-scale screening. The microfluidic contained a surface-bound aptamer directed against the virus’s S protein RBD to affinity select SARS-CoV-2 VPs. Following selection (~94% recovery), the VPs were released from the chip’s surface using a blue light light-emitting diode (89% efficiency). Selected SARS-CoV-2 VP enumeration was carried out using reverse transcription quantitative polymerase chain reaction. The VP selection assay successfully identified healthy donors (clinical specificity = 100%) and 19 of 20 patients with coronavirus disease 2019 (COVID-19) (95% sensitivity). In 15 patients with COVID-19, the presence of active SARS-CoV-2 VPs was found. The chip can be reprogrammed for any VP or exosomes by simply changing the affinity agent

THEMIS: A Parameter Estimation Framework for the Event Horizon Telescope

The Event Horizon Telescope (EHT) provides the unprecedented ability to directly resolve the structure and dynamics of black hole emission regions on scales smaller than their horizons. This has the potential to critically probe the mechanisms by which black holes accrete and launch outflows, and the structure of supermassive black hole spacetimes. However, accessing this information is a formidable analysis challenge for two reasons. First, the EHT natively produces a variety of data types that encode information about the image structure in nontrivial ways; these are subject to a variety of systematic effects associated with very long baseline interferometry and are supplemented by a wide variety of auxiliary data on the primary EHT targets from decades of other observations. Second, models of the emission regions and their interaction with the black hole are complex, highly uncertain, and computationally expensive to construct. As a result, the scientific utilization of EHT observations requires a flexible, extensible, and powerful analysis framework. We present such a framework, Themis, which defines a set of interfaces between models, data, and sampling algorithms that facilitates future development. We describe the design and currently existing components of Themis, how Themis has been validated thus far, and present additional analyses made possible by Themis that illustrate its capabilities. Importantly, we demonstrate that Themis is able to reproduce prior EHT analyses, extend these, and do so in a computationally efficient manner that can efficiently exploit modern high-performance computing facilities. Themis has already been used extensively in the scientific analysis and interpretation of the first EHT observations of M87