Movie Recommender System on Twitter Using Weighted Hybrid Filtering and GRU

The development of the industry in the film sector has experienced rapid growth, marked by the emergence of film streaming platforms such as Netflix and Disney+. With the abundance of available films, users face difficulty in choosing films that suit their preferences. Recommender systems can be a solution to this problem for users. Recommender systems rely on user reviews, making Twitter a platform that can be used to collect user reviews of a film. This study will develop a recommender system that has the potential to provide item recommendations to users using the weighted hybrid filtering and GRU methods. The weighted hybrid filtering used is a combination of collaborative filtering and content-based filtering methods. The dataset used in this study was obtained by crawling tweets relevant to the feedback of specific accounts regarding a film. The dataset resulting from the data crawling consists of a total of 854 films, 45 users and 34,086 tweets consisting of film reviews from Twitter users. The GRU model classification is performed on the results of weighted hybrid filtering with model optimization involving testing various test size scenarios and optimizer methods. The test sizes used are 40%, 30%, and 20%. The optimizer methods used include Adam, Nadam, Adamax, Adadelta, Adagrad, and SGD. The research results show that the optimal outcome is obtained using the Nadam optimization method. The performance evaluation yielded 85.74% precision, 88.63% recall, 88.63% accuracy, and 86.30% F1-score

DISCOVERY OF A GALAXY CLUSTER WITH A VIOLENTLY STARBURSTING CORE AT z=2.506

We report the discovery of a remarkable concentration of massive galaxies with extended X-ray emission at z(spec) = 2.506, which contains 11 massive (M-* greater than or similar to 10(11) M-circle dot) galaxies in the central 80 kpc region (11.6 sigma overdensity). We have spectroscopically confirmed 17 member galaxies with 11 from CO and the remaining ones from Ha. The X-ray luminosity, stellar mass content, and velocity dispersion all point to a collapsed, cluster-sized dark matter halo with mass M-200c = 10(13.9 +/- 0.2) M-circle dot, making it the most distant X-ray-detected cluster known to date. Unlike other clusters discovered so far, this structure is dominated by star-forming galaxies (SFGs) in the core with only 2 out of the 11 massive galaxies classified as quiescent. The star formation rate (SFR) in the 80 kpc core reaches similar to 3400 M-circle dot yr(-1) with a. gas depletion time of similar to 200 Myr, suggesting that we caught this cluster in rapid build-up of a dense core. The high SFR is driven by both a high abundance of SFGs and a higher starburst fraction (similar to 25%, compared to 3%-5% in the field). The presence of both a collapsed, cluster-sized halo and a predominant population of massive SFGs suggests that this structure could represent an important transition phase between protoclusters and mature clusters. It provides evidence that the main phase of massive galaxy passivization will take place after galaxies accrete onto the cluster, providing new insights into massive cluster formation at early epochs. The large integrated stellar mass at such high redshift challenges our understanding of massive cluster formation.Peer reviewe

Test of machine learning at the CERN LINAC4

The CERN H− linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared before- hand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed.peer-reviewe

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Joint contractures in the absence of inflammation may indicate mucopolysaccharidosis

<p>Abstract</p> <p>Background</p> <p>Undiagnosed patients with the attenuated form of mucopolysaccharidosis (MPS) type I often have joint symptoms in childhood that prompt referral to a rheumatologist. A survey conducted by Genzyme Corporation of 60 European and Canadian rheumatologists and pediatric rheumatologists demonstrated that < 20% recognized signs and symptoms of MPS I or could identify appropriate diagnosis tests. These results prompted formation of an international working group of rheumatologists, pediatric rheumatologists, and experts on MPS I to formulate a rheumatology-based diagnostic algorithm. The resulting algorithm applies to all MPS disorders with musculoskeletal manifestations.</p> <p>Bone and joint manifestations are prominent among most patients with MPS disorders. These life-threatening lysosomal storage diseases are caused by deficient activity of specific enzymes involved in the degradation of glycosaminoglycans. Patients with attenuated MPS disease often experience diagnostic delays. Enzyme replacement therapy is now commercially available for MPS I (laronidase), MPS II (idursulfase), and MPS VI (galsulfase).</p> <p>Presentation of the hypothesis</p> <p>Evolving joint pain and joint contractures in the absence of inflammation should always raise the suspicion of an MPS disorder. All such patients should undergo urinary glycosaminoglycan (uGAG) analysis (not spot tests for screening) in a reputable laboratory. Elevated uGAG levels and/or an abnormal uGAG pattern confirms an MPS disorder and specific enzyme testing will determine the MPS type. If uGAG analysis is unavailable and the patient exhibits any other common sign or symptom of an MPS disorder, such as corneal clouding, history of hernia surgery, frequent respiratory and/or ear, nose and throat infections; carpal tunnel syndrome, or heart murmur, proceed directly to enzymatic testing. Refer patients with confirmed MPS to a geneticist or metabolic specialist for further evaluation and treatment.</p> <p>Testing of the hypothesis</p> <p>We propose that rheumatologists, pediatric rheumatologists, and orthopedists consider our diagnostic algorithm when evaluating patients with joint pain and joint contractures.</p> <p>Implications of the hypothesis</p> <p>Children and young adults can suffer for years and sometimes even decades with unrecognized MPS. Rheumatologists may facilitate early diagnosis of MPS based on the presenting signs and symptoms, followed by appropriate testing. Early diagnosis helps ensure prompt and appropriate treatment for these progressive and debilitating diseases.</p

The burden of vulvovaginal atrophy on women's daily living: implications on quality of life from a face-to-face real-life survey

Objective: This subanalysis of the European Vulvovaginal Epidemiology Survey study aimed to assess the correlation of vulvovaginal atrophy (VVA) symptoms and severity, when confirmed by objective gynecologic examination, with the quality of life of postmenopausal women. Methods: Women aged 45 to 75 years with confirmation of last menstrual period more than 12 months before, who attended menopause or gynecology centers, were included. Those women had at least one VVA symptom filled in a group of questionnaires, including EuroQol-EQ-5D-3L and Day-to-Day Impact of Vaginal Aging (DIVA). To confirm the VVA diagnosis, an objective gynecologic examination was also performed. Results: Of a total of 2,160 evaluable women, 66.3%, 30.5%, and 11.2% suffered from severe vaginal, vulvar, and urinary symptoms, respectively. VVA was confirmed in more than 90% of the participants. Mean (±SD) EQ-5D-3L score was 0.892 ± 0.144 and mean (±SD) score on the associated visual analog scale was 71.7 ± 16.0. Mean (±SD) DIVA score was 0.922 ± 0.653. For both EQ-5D-3L and DIVA, the overall scores and most of the dimensions/components were statistically significantly worse for women with severe VVA symptoms (vulvar and urinary) compared with women not affected by severe symptoms. Quality of life questionnaires showed worse scores in women where the diagnosis of VVA was confirmed by gynecologic examination. Conclusions: Severe VVA symptoms showed a direct association with worse quality of life in postmenopausal women. This important effect on the quality of life of many women should be recognized as equivalent to those from other conditions and pathologies of which there is greater awareness

Test of Machine Learning at the CERN LINAC4

The CERN H$^-$ linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared beforehand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed

Targeting transdifferentiated hepatic stellate cells and monitoring the hepatic fibrogenic process by means of IGF2R-specific peptides designed <i>in silico</i>

In silico designed peptides showed high binding affinity towards activated human hepatic stellate cells, offering new strategies to target insulin-like growth factor 2 receptor in fibrotic liver and suggesting a potential for noninvasive diagnosis.</p

Targeting transdifferentiated hepatic stellate cells and monitoring the hepatic fibrogenic process by means of IGF2R-specific peptides designed in silico

The lack of accurate and easily applicable methods for the diagnosis of liver fibrosis, a disease characterized by an accumulation of the extracellular matrix released by activated hepatic stellate cells (HSCs), has been a major limitation for the clinical management of liver diseases. The identification of biomarkers specific to liver microstructure alterations, combined with a non-invasive optical imaging modality, could guide clinicians towards a therapeutic strategy. In this study, structural information of the insulin-like growth factor 2 receptor (IGF2R), an overexpressed protein on activated HSCs, was used for in silico screening of novel IGF2R-specific peptide ligands. Molecular dynamics simulations, followed by computational alanine scanning of the IGF2R/IGF2 complex, led to the identification of a putative peptide sequence containing the most relevant amino acids for the receptor–ligand interaction (IGF2 E12-C21). The Residue Scan tool, implemented in the MOE software, was then used to optimize the binding affinity of this sequence by amino acid mutations. The designed peptides and their associated scrambled sequences were fluorescently labelled and their binding affinity to LX-2 cells (model for activated human HSCs) was tested using flow cytometry and confocal microscopy. In vitro binding was verified for all sequences (KD ≤ 13.2 μM). With respect to the putative binding sequence, most mutations led to an increased affinity. All sequences have shown superior binding compared to their associated scrambled sequences. Using HPLC, all peptides were tested in vitro for their proteolytic resistance and showed a stability of ≥60% intact after 24 h at 37 °C in 50% v/v FBS. In view of their prospective diagnostic application, a comparison of binding affinity was performed in perpetuated and quiescent-like LX-2 cells. Furthermore, the IGF2R expression for different cell phenotypes was analysed by a quantitative mass spectrometric approach. Our peptides showed increased binding to the perpetuated cell state, indicating their good selectivity for the diagnostically relevant phenotype. In summary, the increased binding affinity of our peptides towards perpetuated LX-2 cells, as well as the satisfactory proteolytic stability, proves that the in silico designed sequences offer a new potential strategy for the targeting of hepatic fibrosis.ISSN:2050-7518ISSN:2050-750