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The best crystal identification (CI) algorithms proposed so far for phoswich detectors are based on adaptive filtering and pulse shape discrimination (PSD). However, these techniques require free running analog to digital converters, which is no longer possible with the ever increasing pixelization of new detectors. We propose to explore the dual-threshold time-over-threshold (ToT) technique, used to measure events energy and time of occurence, as a more robust solution for crystal identification with broad energy windows in phoswich detectors. In this study, phoswich assemblies made of various combinations of LGSO and LYSO scintillators with decay times in the range 30 to 65 ns were investigated for the LabPET II detection front-end. The electronic readout is based on a 4 × 8 APD array where pixels are individually coupled to charge sensitive preamplifiers followed by first order CR-RC shapers with 75 ns peaking time. Crystal identification data were sorted out based on the measurements of likeliness between acquired signals and a time domain model of the analog front-end. Results demonstrate that crystal identification can be successfully performed using a dual-threshold ToT scheme with a discrimination accuracy of 99.1% for LGSO (30 ns)/LGSO (45 ns), 98.1% for LGSO (65 ns)/LYSO (40 ns) and 92.1% for LYSO (32 ns)/LYSO (47 ns), for an energy window of [350–650] keV. Moreover, the method shows a discrimination accuracy >97% for the two first pairs and ~90% for the last one when using a wide energy window of [250–650] keV.

This study aims to see the effect of the application of discovery learning models with blended learning strategies assisted by Crossword Puzzle media on the ability to understand students' physics concepts by choosing. This study used a pre-experimental method with a one-shot case study design consisting of 1 experimental class as a sample class which was carried out at SMP Negeri 1 Botupingge. The data obtained were in the form of understanding students' physics concepts on the material of vibration, waves, and sound which were netted using a multiple-choice test sheet as many as 20 items. The overall research results show that the application of discovery learning models with blended learning strategies assisted by Crossword Puzzle media has a significant effect on students' ability to understand physics concepts which is shown by proving the hypothesis test that the value of t table> t count which states that the lowest student learning outcomes are 75, where from the total sample of 69 respondents, 82.61% or 57 respondents scored above 75.

Pemantapan Mutu internal merupakan kegiatan pencegahan dan pengawasan yang dilaksanakan oleh masing-masing laboratorium secara rutin agar tidak terjadi atau mengurangi error/penyimpangan sehingga diperoleh hasil pemeriksaan yang tepat dengan tingkat akurasi dan presisi yang tinggi. Penelitian ini menggunakan desain penelitian kuantitatif dengan menggunakan rancangan cross sectional. Hasil penelitian dengan jumlah responden sebanyak 15 orang dan jumlah sampel urin sebanyak 40 sampel, didapatkan nilai rata-rata dari masing-masing kriteria pemantapan mutu internal, pada kriteria Sumber Daya Manusia dengan skor 97,91 yang berarti sangat baik. Kriteria kedua terhadap quality control dengan skor 60,6 yang berarti kurang baik, yang ketiga kriteria terhadap fasilitas sarana dan prasarana dengan skor 100 yang berarti sangat baik, dan yang terakhir kriteria SOP dengan skor 58,3 yang berarti kurang baik.

Background and Purpose: Mechanical thrombectomy (MT) in ischemic stroke patients with poor prestroke conditions remains controversial. We aimed to analyze the frequency of previously disabled patients treated with MT in clinical practice, the safety and clinical response to MT of patients with preexisting disability, and the disabled patient characteristics associated with a better response to MT. Methods: We studied all consecutive patients with anterior circulation occlusion treated with MT from January 2017 to December 2019 included in the Codi Ictus Catalunya registry—a government-mandated, prospective, hospital-based data set. Prestroke disability was defined as modified Rankin Scale score 2 or 3. Functional outcome at 90 days was centrally assessed by a blinded evaluator of the Catalan Stroke Program. Favorable outcome (to return at least to prestroke modified Rankin Scale at 90 days) and safety and secondary outcomes were compared with patients without previous disability. Logistic regression analysis was used to assess the association between prestroke disability and outcomes and to identify a disabled patient profile with favorable outcome after MT. Results: Of 2487 patients included in the study, 409 (17.1%) had prestroke disability (313 modified Rankin Scale score 2 and 96 modified Rankin Scale score 3). After adjustment for covariates, prestroke disability was not associated with a lower chance of achieving favorable outcome at 90 days (24% versus 30%; odds ratio, 0.79 [0.57–1.08]), whereas it was independently associated with a higher risk of symptomatic intracranial hemorrhage (5% versus 3%; odds ratio, 2.04 [1.11–3.72]) and long-term mortality (31% versus 18%; odds ratio, 1.74 [1.27–2.39]) compared with patients without disability. Prestroke disabled patients without diabetes, Alberta Stroke Program Early CT Score >8 and National Institutes of Health Stroke Scale score Conclusions: Despite a higher mortality and risk of symptomatic intracranial hemorrhage, prestroke-disabled patients return as often as independent patients to their prestroke level of function, especially those nondiabetic patients with favorable early ischemic signs profile. These data support a potential benefit of MT in patients with previous mild or moderate disability after large anterior vessel occlusion stroke.

Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum’s epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (R2 0.358 and 0.378, respectively). In conclusion, our results support the influence of these factors on Age-A; although, they were not enough to explain most of its variability.

Objective To find new biomarkers of early stroke recurrence (SR) by using lipidomic strategies on patients who suffered a transient ischemic attack. Methods Untargeted lipidomic analysis was performed in plasma samples of 460 consecutive TIA patients. Recruited

Background: Several studies have reported that an increase in blood glucose in patients with diabetes mellitus (DM) can cause complications to death that occur due to oxidative stress conditions due to excessive ROS production. Red spinach extract was found to be rich in antioxidant compounds. However, there has been no further research on the ability of red spinach to lower blood glucose levels and prevent oxidative stress, which can be seen from the levels of malondialdehyde (MDA; a marker of oxidative stress) in the DM body.Objective: This study aims to determine whether there is a change in blood glucose levels and MDA levels in DM animal models between the groups that were given red spinach extract and not.Methods: This study used white rats (Rattus norvegicus) which were divided into 5 groups: K(-) group in which the rats were not induced by diabetogenic agent and were not treated; K(+) group, the rats were made DM induced by multiple low dose streptozotocin (MLD-STZ); and T1, T2, and T3 groups were exposed to MLD-STZ and treated with red spinach extract (Amaranthus tricolor L.) at a dose of 200 mg/kgBW, 300 mg/kgBW and 400 mg/kgBW, respectively. Blood sugar levels were checked before and after treatment with extract using glucometer digital. Meanwhile, MDA levels were measured by TBA test using protein isolates from the pancreas of each rat.Results: The results showed that the average MDA levels in the K-, K+, T1, T2, and T3 groups were 1.759±0.08, 2.280±0.15, 2.303±0.11, 1.927±0.06, and 1.801±0.04. While the average blood sugar levels in the K-, K+, T1, T2, and T3 groups were 114.4±8.82, 464±72.78, 421.2±37.60, 140.6±20.19, and 176±13.06.Conclusion: It can be concluded that the administration of red spinach extract therapy in DM model rats was able to reduce both glucose levels and MDA levels. By lowering the levels of MDA compounds, it is also believed to be able to prevent oxidative stress in cells which causes tissue damage.

Une enseignant��e universitaire qui souhaite r��guler ses pratiques professionnelles pour r��pondre aux besoins des apprenant��e��s est parfois en d��ficit d���informations pour identifier les actions �� entreprendre. Afin de permettre de d��passer son ressenti et ses propres impressions, deux Hautes ��coles p��dagogiques de Suisse romande ont d��velopp�� un outil num��rique nomm�� OURA, qui a pour but de soutenir la r��gulation des activit��s d���enseignement/apprentissage au niveau universitaire. Cet article expose les fondements th��oriques qui ��tayent son d��veloppement: d���abord les d��marches de data-based decision-making et d���analytique de l���enseignement, puis les fondements th��oriques des diff��rents domaines et dimensions pris en comptedans l���outil. (DIPF/Orig.), A university teacher who wishes to regulate his or her professional practices to meet the needs of learners is sometimes lacking information to identify the actions to be taken. In order to enable him or her to go beyond his or her own feelings and impressions, two Universities of Teacher Education in the French-speaking part of Switzerland have developed a digital tool called OURA, which aims to support the regulation of teaching/learning activities at the university level. This article explains the theoretical foundations that underpin its development: firstly, the data-based decision-making and the teaching analytics, and secondly, the theoretical foundations of the various fields and dimensions taken into account in the tool. (DIPF/Orig.)

The recent crisis of Covid-19, including its long-term nature and the new working practices it has generated, has highlighted the importance of internal communication in line with the needs of the internal publics in organizations and thus prompted us to question the evolution of the role and practices of internal communication professionals. We propose to address these issues in the light of the events observed in our quantitative and qualitative surveys about the employees��� experiences of internal communication during the first wave of the Covid-19 pandemic in Belgium. The results of our survey led to a particular segmentation of internal publics in organizations based on their working reality and their perception of different risks. The issue of segmentation of internal publics has been little explored by researchers, yet it appears crucial in helping communication professionals understand the specificities of their publics and adapting their strategies to the needs of these publics. Another key finding of our research concerns the growing importance of managerial communication. In this respect, the role of communication professionals in supporting managers deserves to be questioned.

Background: The aim of the study was to determine the association between previous stroke and mortality after coronavirus disease 2019 (COVID-19) according to sex, age groups, and stroke subtypes. Methods: Prospective population-based cohort study including all COVID-19 positive cases between February 1 and July 31, 2020. Comorbidities and mortality were extracted using linked health administration databases. Previous stroke included transient ischemic attack, ischemic stroke, hemorrhagic stroke, spontaneous subarachnoid hemorrhage, and combined stroke for cases with more than one category. Other comorbidities were obesity, diabetes, hypertension, ischemic heart disease, atrial fibrillation, heart failure, chronic obstructive pulmonary disease, chronic kidney disease, cirrhosis, dementia, individual socioeconomic index, and deprivation index. Cases were followed up until December 31, 2020. Primary outcome was mortality of any cause after COVID-19 positivity. Cox proportional regression analysis adjusted for comorbidities was used. Stratified analyses were performed for sex and age ( Results: There were 91 629 COVID-19 cases. Previous strokes were 5752 (6.27%), of which 3887 (67.57%) were ischemic, 1237 (21.50%) transient ischemic attack, 255 (4.43%) combined, 203 (3.53%) hemorrhagic, and 170 (2.96%) subarachnoid hemorrhage. There were 9512 deaths (10.38%). Mortality was associated with previous stroke (hazard ratio [HR]=1.12 [95% CI, 1.06–1.18]; P P =0.001; women=1.09 [1.01–1.18]; P =0.023), in people P P P =0.437). Ischemic (HR=1.11 [1.05–1.18]; P =0.001), hemorrhagic (HR=1.53 [1.20–1.96]; P =0.001) and combined (HR=1.31 [1.05–1.63]; P =0.016) strokes were associated but not transient ischemic attack. Subarachnoid hemorrhage was associated only in people P =0.003). Conclusions: Previous stroke was associated with a higher mortality in people younger than 80 years. The association occurred for both ischemic and hemorrhagic stroke but not for transient ischemic attack. These data might help healthcare authorities to establish prioritization strategies for COVID-19 vaccination.

Gagal Ginjal Kronis (GGK) merupakan kerusakan fungsi ginjal yang terjadi selama lebih dari 3 bulan, dan dapat ditegakkan jila nilai Laju Filtrasi Glomerulus (LFG) kurang dari 60 ml/menit/1,73m2 . Pemeriksaan Laboratorium untuk mendeteksi adanya gangguan fungsi ginjal yaitu dengan melihat hasil kadar hemoglobin dan kadar kreatinin. Tujuan penelitian adalah untuk mengetahui hubungan antara kadar hemoglobin dengan kadar kreatinin pada pasien hemodialisa. Penelitian ini menggunakan metode kuantitatif dengan pendekatan Cross Sectional data primer di Rumah Sakit Umum Zahirah Jagakarsa. Hasil penelitian ini menunjukan adanya hubungan antara kadar hemoglobin dengan kadar kreatinin dengan nilai p=0,000 (p=

Objectives The COVID-19 vaccination in autoimmune diseases (COVAD) study aimed to assess short-term COVID-19 vaccination-related adverse events (AEs) in RA patients. Methods An online self-reported questionnaire (March–December 2021) was used to capture data related to COVID-19 vaccination-related AEs in RA, other autoimmune rheumatic diseases (AIRDs) (excluding RA and inflammatory myositis), non-rheumatic autoimmune diseases (nrAIDs) and healthy controls (HCs). Descriptive and multivariable regression analyses were performed. Results Of the 9462 complete respondents, 14.2% (n = 1347) had been diagnosed with RA; they had a mean (s.d.) age of 50.7 (13.7) years, 74.2% were women and 49.3% were Caucasian. In total, 76.9% and 4.2% of patients with RA reported minor and major AEs, respectively. Patients with active and inactive RA had similar AE and hospitalization frequencies. Overall, AEs were reported more frequently by BNT162b2 and mRNA-1273 recipients and less frequently by BBV152 recipients compared with the rest. Major AE and hospitalization frequencies were similar across recipients of different vaccines. Patients receiving methotrexate and hydroxychloroquine reported fewer minor AEs than those patients not on them. Compared with HCs and patients with other AIRDs, patients with RA reported similar total AEs, overall minor AEs, and hospitalizations. Compared with nrAIDs, patients with RA reported lower frequencies of overall AEs, minor AEs (both odds ratio [OR] = 0.7; 95% CI: 0.5, 0.9), and injection site pain (OR = 0.6; 95% CI: 0.5, 0.8) with similar major AE and hospitalization frequencies. Conclusion Despite the differences in AE frequency across different COVID-19 vaccines, all were well tolerated in patients with RA and were comparable to HCs, providing reassurance as to the safety of COVID-19 vaccination.

Vibration signals measured on rotating machinery typically exhibit cyclostationarity due to the inherent nature of real-world rotating vibration sources. Hence, the development of signal processing tools devoted to investigating or exploiting this cyclostationarity for condition monitoring purposes of gears and bearings has seen a significant increase in research interest. One of the main approaches to analyze a vibration signal’s cyclostationary behavior is the cyclic spectral correlation and its normalized derivative the cyclic spectral coherence. Even though these two methods are closely related, they do offer different statistical insights which may influence the fault detection and trending capabilities of these tools. The aim of this work is to investigate the performance of these two methods with regard to the accuracy of tracking mechanical degradation over time. The normalization of the spectral coherence which makes it independent of the signal power spectrum improves the interpretability of the resulting coherence spectrum but it may lead to suppress or equalize fault-related frequency bands relative to other frequency bands and it may skew the coherence spectrum amplitudes of fault harmonics in different operating regimes for complex machinery. Tracking the evolution of a second-order cyclostationary component over time might thus be hindered by this normalization which can lead to issues when combining such a tool with a data-driven machine learning technique that employs the operating conditions for making the cyclostationary indicators operating condition independent. Instead, using the cyclic spectral correlation which is not normalized, may provide a more accurate depiction of the degradation process. This paper investigates whether there is any significant benefit to using the cyclic spectral correlation over the cyclic spectral coherence for monitoring complex rotating machinery and if so, when does it make sense to prefer one over the other. To answer these questions, both simulated and experimental vibration data is examined in order to highlight the differences between the two concepts.

Viruses represent an important cause of cancer in humans: infections are estimated to account for close to one cancer case out of five.With the ongoing discovery of new infectious agents, this number should be raising in the near future. In 2006, the discovery of a new _-retrovirus in prostate cancer biopsies launched an intense research activity: could this new xenotropic MLV-related virus (XMRV) be the cause of prostate cancer? Five years later, the initial enthusiasm of retrovirologists has dramatically diminished. One by one, arguments favouring the hypothesis of human infection with XMRV are being refuted. The aim of this review article is to present the discovery of XMRV and to analyze recent data arguing against its existence in humans. A synthetic interpretation of XMRV literature will then be suggested.

The increasing share of renewables in the electricity generation mix comes along with an increasing uncertainty in power supply. In the recent years, distributionally robust optimization has gained significant interest due to its ability to make informed decisions under uncertainty, which are robust to misrepresentations of the distributional information (e.g., from probabilistic forecasts). This is achieved by introducing an ambiguity set that describes the potential deviations from an empirical distribution of all uncertain parameters. However, this set typically overlooks the inherent dependencies of uncertainty, e.g., spatial dependencies of weather-dependent energy sources. This paper goes beyond the state of the art by embedding such dependencies within the definition of the ambiguity set. In particular, we propose a copula-based ambiguity set which is tailored to capture any type of dependencies. We develop a conic reformulation which is kept generic such that it can be applied to any decision-making problem under uncertainty in power systems. As an example, we illustrate the performance of our proposed distributionally robust model applied to an optimal power flow problem in a power system with a high share of renewables.&nbsp

The increasing share of natural gas-fired power plants in the electricity generation mix has tightened the existing link between power and gas systems. This may bring technical and economical risks, e.g., congestions and peak prices, which mainly stem from the non-coordinated operation of both systems and the failure to properly anticipate the multivariate and correlated demand uncertainty. In this paper, we propose a Wasserstein metric-based distributionally robust optimization framework for the joint power and gas dispatch to mitigate these risks. The distributionally robust decision-making approach strives to ensure risk-hedging dispatch solutions, by considering a set of potential distributions, the so-called ambiguity set. We go beyond the state of the art by considering a realistic dependence structure among the power and gas demands uncertainty. We show the benefits of the proposed approach via a numerical study based on the Belgian networks.