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1. Examining recycling behaviors at Semizbugu P1 (2022), Kazakhstan

   https://doi.org/10.52967/akz2022.3.17.103.114  

   Coco, Emily; Mamirov, Talgat (September 2022, Археология Казахстана)

   This article presents the preliminary results of a new project aimed at investigating the behavioural aspects of stone tool reutilisation at the Semizbugu Palaeolithic complex. Monuments with surface artifacts are ideal sites for recycling, as artifacts are easy to locate and reuse on the day surface in such environments. As part of this project, artifacts were analysed at a new site, designated P1 (2022) of the Semizbugu settlement complex, with a focus on the identification of recycled objects, mainly by the presence of double patina. The results presented here describe the nature of the secondary use of the artifacts. The relevance of the work carried out is associated primarily with the fact that this is a completely new approach in the study of Paleolithic monuments of Kazakhstan, represented by numerous sites of the so-called "open type". On the example of the Semizbugu P1 monument (2022) it is possible to extrapolate the received conclusions with other similar monuments of the region for understanding of character of principles of reutilization and behavioral aspects in the past. Direct field studies at the Semizbugu complex were preceded by laboratory work on materials collected in the 1960s by A.G. Medoev. 

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2. New Insights into the Structure and Assembly of Bacteriophage P1

   https://doi.org/10.3390/v14040678  

   Gonzales, Miguel F.; Piya, Denish K.; Koehler, Brian; Zhang, Kailun; Yu, Zihao; Zeng, Lanying; Gill, Jason J. (April 2022, Viruses)

   Bacteriophage P1 is the premier transducing phage of E. coli. Despite its prominence in advancing E. coli genetics, modern molecular techniques have not been applied to thoroughly understand P1 structure. Here, we report the proteome of the P1 virion as determined by liquid chromatography tandem mass-spectrometry. Additionally, a library of single-gene knockouts identified the following five previously unknown essential genes: pmgA, pmgB, pmgC, pmgG, and pmgR. In addition, proteolytic processing of the major capsid protein is a known feature of P1 morphogenesis, and we identified the processing site by N-terminal sequencing to be between E120 and S121, producing a 448-residue, 49.3 kDa mature peptide. Furthermore, the P1 defense against restriction (Dar) system consists of six known proteins that are incorporated into the virion during morphogenesis. The largest of these, DarB, is a 250 kDa protein that is believed to translocate into the cell during infection. DarB deletions indicated the presence of an N-terminal packaging signal, and the N-terminal 30 residues of DarB are shown to be sufficient for directing a heterologous reporter protein to the capsid. Taken together, the data expand on essential structural P1 proteins as well as introduces P1 as a nanomachine for cellular delivery. 

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3. P1 Center Electron Spin Clusters Are Prevalent in Type Ib Diamonds

   https://doi.org/10.1021/jacs.3c06705  

   Bussandri, Santiago; Shimon, Daphna; Equbal, Asif; Ren, Yuhang; Takahashi, Susumu; Ramanathan, Chandrasekhar; Han, Songi (February 2024, Journal of the American Chemical Society)

   Understanding the spatial distribution of the P1 centers is crucial for diamond-based sensors and quantum devices. P1 centers serve as polarization sources for dynamic nuclear polarization (DNP) quantum sensing and play a significant role in the relaxation of nitrogen vacancy (NV) centers. Additionally, the distribution of NV centers correlates with the distribution of P1 centers, as NV centers are formed through the conversion of P1 centers. We utilized DNP and pulsed electron paramagnetic resonance (EPR) techniques that revealed strong clustering of a significant population of P1 centers that exhibit exchange coupling and produce asymmetric line shapes. The 13C DNP frequency profile at a high magnetic field revealed a pattern that requires an asymmetric EPR line shape of the P1 clusters with electron–electron (e–e) coupling strengths exceeding the 13C nuclear Larmor frequency. EPR and DNP characterization at high magnetic fields was necessary to resolve energy contributions from different e–e couplings. We employed a two-frequency pump–probe pulsed electron double resonance technique to show cross-talk between the isolated and clustered P1 centers. This finding implies that the clustered P1 centers affect all of the P1 populations. Direct observation of clustered P1 centers and their asymmetric line shape offers a novel and crucial insight into understanding magnetic noise sources for quantum information applications of diamonds and for designing diamond-based polarizing agents with optimized DNP efficiency for 13C and other nuclear spins of analytes. We propose that room temperature 13C DNP at a high field, achievable through straightforward modifications to existing solution-state NMR systems, is a potent tool for evaluating and controlling diamond defects. 

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4. Nuclease P1 Digestion for Bottom-Up RNA Sequencing of Modified siRNA Therapeutics

   https://doi.org/10.1021/acs.analchem.2c04902  

   Jones, Joshua D.; Grassmyer, Kathleen T.; Kennedy, Robert T.; Koutmou, Kristin S.; Maloney, Todd D. (March 2023, Analytical Chemistry)
5. p1-FP: Extraction, Classification, and Prediction of Website Fingerprints with Deep Learning

   https://doi.org/10.2478/popets-2019-0043  

   Oh, Se Eun; Sunkam, Saikrishna; Hopper, Nicholas (July 2019, Proceedings on Privacy Enhancing Technologies)

   Abstract Recent advances in Deep Neural Network (DNN) architectures have received a great deal of attention due to their ability to outperform state-of-the-art machine learning techniques across a wide range of application, as well as automating the feature engineering process. In this paper, we broadly study the applicability of deep learning to website fingerprinting. First, we show that unsupervised DNNs can generate lowdimensional informative features that improve the performance of state-of-the-art website fingerprinting attacks. Second, when used as classifiers, we show that they can exceed performance of existing attacks across a range of application scenarios, including fingerprinting Tor website traces, fingerprinting search engine queries over Tor, defeating fingerprinting defenses, and fingerprinting TLS-encrypted websites. Finally, we investigate which site-level features of a website influence its fingerprintability by DNNs. 

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