Universal University

Cells can adapt to various environments by changing their biomolecular profiles while maintaining physiological homeostasis. What organizational principles in cells enable the simultaneous realization of adaptability and homeostasis? To address this question, we measure Raman scattering light from Escherichia coli cells under diverse conditions, whose spectral patterns convey their comprehensive molecular composition. We reveal that dimension-reduced Raman spectra can predict condition-dependent proteome profiles. Quantitative analysis of the Raman-proteome correspondence characterizes a low-dimensional hierarchical stoichiometry-conserving proteome structure. The network centrality of each gene in the stoichiometry conservation relations correlates with its essentiality and evolutionary conservation, and these correlations are preserved from bacteria to human cells. Furthermore, stoichiometry-conserving core components obey growth law and ensure homeostasis across conditions, whereas peripheral stoichiometry-conserving components enable adaptation to specific conditions. Mathematical analysis reveals that the stoichiometrically constrained architecture is reflected in major changes in Raman spectral patterns. These results uncover coordination of global stoichiometric balance in cells and demonstrate that vibrational spectroscopy can decipher such biological constraints beyond statistical or machine-learning inference of cellular states.

The rapid development of generative Artificial Intelligence (AI) technology offers significant efficiency opportunities across various sectors; however, empirical research within the local Indonesian context, particularly in Batam City, remains scarce. This exploratory study aims to analyze the influence of positive perception, negative perception, and AI regulation understanding on technology adoption trends, as well as productivity and product innovation opportunities among creative industry players. The creative industry is a focal point due to the inherent tension between technological efficiency and the preservation of human originality in the creative process. This research employs a quantitative causal approach, utilizing a sample of 30 respondents reached through snowball sampling techniques. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. The findings reveal that only positive perception has a significant direct impact on product innovation (p=0.004), while AI regulation and technical adoption do not show significant effects. This suggests that a positive technology mindset is a more decisive factor for innovation than technical mastery or current regulatory compliance. These results underscore the urgent need for local government socialization of AI policies and enhanced digital literacy for Batam's creative practitioners to transform them from mere users into strategic AI-driven innovators.

Artikel ini bertujuan untuk menganalisis pengaruh Work-Life Balance (WLB) terhadap Produktivitas Karyawan Generasi Z di Kota Bandung. Masalah difokuskan pada apakah keseimbangan antara kehidupan kerja dan personal dapat bertindak sebagai pendorong kinerja yang signifikan bagi angkatan kerja muda ini. Guna mendekati masalah ini dipergunakan acuan teori dari Social Exchange Theory yang mendukung adanya hubungan timbal balik antara dukungan organisasi dan output karyawan. Data-data dikumpulkan melalui kuesioner terstruktur yang disebarkan kepada 100 responden Gen Z di sektor industri kreatif Kota Bandung dan dianalisis secara kuantitatif dengan menggunakan Regresi Linier Sederhana. Hasil menunjukkan bahwa tingkat WLB karyawan Gen Z cenderung berada pada kategori sedang hingga tinggi, yang sejalan dengan tingkat produktivitas mereka yang juga tinggi. Kajian ini menyimpulkan bahwa Work-Life Balance berpengaruh positif dan signifikan terhadap Produktivitas Karyawan Gen Z. Koefisien Determinasi (R2) menunjukkan bahwa WLB mampu menjelaskan 62,3% variasi produktivitas. Temuan ini menegaskan WLB sebagai variabel krusial dan investasi langsung dalam peningkatan kinerja, bukan hanya sebagai faktor kesejahteraan semata.

Explore the article titled How Friends Influence Purchases Among Youth: An Analytical Study of Peer Dynamics and Consumer Decision-Making from IJIRT Volume 12, Issue 8. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.

This paper presents the design and implementation of SNAFH-R1, a low-cost four-degree-of-freedom (4-DOF) glambot camera arm intended for indoor photobooth applications. The system integrates a Python-based image processing module on a laptop with an Arduino Uno R3 controller that drives three high-torque RDS3225MG servos and one MG995 servo via a PCA9685 PWM driver. A USB camera (Logitech C270) is used to capture video frames that are processed in real time using grayscale conversion, illumination enhancement, noise reduction, and human detection based on a cascade classifier. The centroid of the detected region of interest is then converted into position offsets and mapped to target joint angles, which are applied to the servos using clamped and interpolated commands to produce smooth camera motion. A BH1750 light sensor and relay-controlled LED lamp are employed to automatically stabilize local illumination around the subject. Experimental observations in an indoor photobooth scenario show that SNAFH-R1 can maintain the subject’s head and upper body within the camera frame at short to medium distances, while producing reasonably smooth camera trajectories and operating stably during short test sessions. These results indicate that the proposed system is a feasible low-cost alternative for automated glambot-style camera movements in small to medium-scale events and as a teaching platform for robotics and computer vision.

Dermatoscopy image-based skin lesion classification is a challenge in dermatology due to the high visual variation between lesion types and the imbalanced class distribution in the dataset. In this study, a Hybrid Vision Transformer–ConvNeXt architecture is proposed, combining the global attention capability of Vision Transformer (ViT) and the spatial feature representation of ConvNeXt, to improve the classification performance of skin lesion images on the HAM10000 dataset. This study also applies Multi-Task Focal Loss, auxiliary classifier, and Weighted Random Sampler to effectively address the class imbalance. In addition, the Medical Test-Time Augmentation (TTA) approach is used in the inference stage to improve the stability of predictions. The model is trained using a two-stage strategy (head training and full fine-tuning), as well as optimization based on AdamW and Cosine Annealing Warm Restarts. The test results show that the proposed model successfully achieves a validation F1-Score of 0.8723, and after TTA it increases to 0.90, surpassing the baseline of ViT and single ConvNeXt. These findings indicate that the integration of ViT–ConvNeXt with loss strategy and medical TTA is able to significantly improve the performance of skin lesion classification, and has the potential to be applied as a clinical diagnosis support system.

Explore the article titled Retention Challenges in the Oil & Petroleum Sector: Examining Workforce Stability in High-Risk Producer Countries from IJIRT Volume 12, Issue 6. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.

Esti trabayu ta basáu nos datos publicaos nel Estudiu llingüísticu nel centru-occidente asturianu (ELCOA). Pequeñu atles dialectográficu (Rodríguez Monteavaro 2023), un atles llingüísticu dialectal centráu nel área centro-occidental d’Asturies (nel norte de la Península Ibérica). Los 361 ítems llingüísticos investigaos en caún de los 18 puntos d’encuesta del ELCOA fueron trataos dialectométricamente (Rodríguez Monteavaro 2025) col fin d’atopar estructures dialectales superiores a les que la dialectoloxía tradicional proponía y equí, agora, relaciónense esos resultaos de los análisis dialectométricos con dellos aspectos característicos físicos, poblacionales y sociollingüísticos del área d’estudiu. L’oxetivu principal d’esti capítulu ye amostrar delles conclusiones a partir de los análisis realizaos nuna frontera llingüística interna del asturllionés, que fuera trazada polos investigadores Menéndez Pidal (1906ab); Rodríguez-Castellano (1954); Catalán (1956, 1957) y García Arias (2003), pero que necesitaba ser revisada con ferramientes informátiques matemático-estadístiques pa llegar a un mayor grau de precisión.

Abstract The continuous increase of the global human population living in cities has significantly impacted various aspects of nature and climate worldwide, affecting the local green space and its biodiversity. One initiative to promote urban biodiversity and its flora and fauna is the application of green roofs. However, the optimal design of these green roofs is currently uncertain, as it strongly depends on local environmental conditions. This research investigates the effect of water- and nutrient availability on the success of green roofs in the Netherlands, utilizing an adapted, experimental design of a green roof. Mineral wool was used as a water retention layer and compost was used to increase nutrient availability. The results indicate that adding mineral wool significantly affects the number of flowers, seeds and the total number of plant species. This applies to the planted species, as well as spontaneously growing species. The addition of compost, to increase nutrient availability, did not significantly affect these parameters of plant growth. This research shows that this adapted design aiming to improve soil moisture is crucial in stimulating the urban green space and its biodiversity in environments in the Netherlands. Besides, this research evaluates the results for the current state of green roofs (management) in urban areas and future possibilities and research recommendations.