Miracle-dz/UniFAR-FTUs huggingface dataset:
Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines

Continuously learning new tasks using high-level ideas or knowledge is a key capability of humans. In this paper, we propose Lifelong reinforcement learning with Sequential linear temporal logic formulas and Reward Machines (LSRM), which enables an agent to leverage previously learned knowledge to fasten learning of logically specified tasks. For the sake of more flexible specification of tasks, we first introduce Sequential Linear Temporal Logic (SLTL), which is a supplement to the existing Linear Temporal Logic (LTL) formal language. We then utilize Reward Machines (RM) to exploit structural reward functions for tasks encoded with high-level events, and propose automatic extension of RM and efficient knowledge transfer over tasks for continuous learning in lifetime. Experimental results show that LSRM outperforms the methods that learn the target tasks from scratch by taking advantage of the task decomposition using SLTL and knowledge transfer over RM during the lifelong learning process.
Reconciling the FOPT and CIPT Predictions for the Hadronic Tau Decay Rate

In a recent work it was suggested that the discrepancy observed in the perturbation series behavior of the $\tau$ hadronic decay rate determined in the FOPT and CIPT approaches can be explained from a different infrared sensitivity inherent to both methods, assuming that the major source of the discrepancy is the asymptotic behavior of the series related to the gluon condensate renormalon. This implies that the predictions of both methods may be reconciled in infrared subtracted perturbation theory. In this talk we explore this implication concretely in the large-$\beta_0$ approximation, where the perturbation series is known to all orders, using a renormalon-free scheme for the gluon condensate.
Recent infections among individuals with a new HIV diagnosis in Rwanda, 2018–2020

Background Despite Rwanda’s progress toward HIV epidemic control, 16.2% of HIV-positive individuals are unaware of their HIV positive status. Tailoring the public health strategy could help reach these individuals with new HIV infection and achieve epidemic control. Recency testing is primarily for surveillance, monitoring, and evaluation but it’s not for diagnostic purposes. However, it’s important to know what proportion of the newly diagnosed are recent infections so that HIV prevention can be tailored to the profile of people who are recently infected. We therefore used available national data to characterize individuals with recent HIV infection in Rwanda to inform the epidemic response. Methods We included all national-level data for recency testing reported from October 2018 to June 2020. Eligible participants were adults (aged ≥15 years) who had a new HIV diagnosis, who self-reported being antiretroviral therapy (ART) naïve, and who had consented to recency testing. Numbers and proportions of recent HIV infections were estimated, and precision around these estimates was calculated with 95% confidence intervals (CI). Logistic regression was used to assess factors associated with being recently (within 12 months) infected with HIV. Results Of 7,785 eligible individuals with a new HIV-positive diagnosis, 475 (6.1%) met the criteria for RITA recent infection. The proportion of RITA recent infections among individuals with newly identified HIV was high among those aged 15–24 years (9.6%) and in men aged ≥65 years (10.3%) compared to other age groups; and were higher among women (6.7%) than men (5.1%). Of all recent cases, 68.8% were women, and 72.2% were aged 15–34 years. The Northern province had the fewest individuals with newly diagnosed HIV but had the highest proportion of recent infections (10.0%) compared to other provinces. Recent infections decreased by 19.6% per unit change in time (measured in months). Patients aged ≥25 years were less likely to have recent infection than those aged 15–24 years with those aged 35–49 years being the least likely to have recent infection compared to those aged 15–24 years (adjusted odds ratio [aOR], 0.415 [95% CI: 0.316–0.544]). Conclusion Public health surveillance targeting the areas and the identified groups with high risk of recent infection could help improve outcomes.
Synthesizing Stellar Populations in South Pole Telescope Galaxy Clusters. I. Ages of Quiescent Member Galaxies at 0.3 < z < 1.4

Using stellar population synthesis models to infer star formation histories (SFHs), we analyze photometry and spectroscopy of a large sample of quiescent galaxies that are members of Sunyaev–Zel’dovich (SZ)-selected galaxy clusters across a wide range of redshifts. We calculate stellar masses and mass-weighted ages for 837 quiescent cluster members at 0.3 < z < 1.4 using rest-frame optical spectra and the Python-based Prospector framework, from 61 clusters in the SPT-GMOS Spectroscopic Survey (0.3 < z < 0.9) and three clusters in the SPT Hi-z cluster sample (1.25 < z < 1.4). We analyze spectra of subpopulations divided into bins of redshift, stellar mass, cluster mass, and velocity-radius phase-space location, as well as by creating composite spectra of quiescent member galaxies. We find that quiescent galaxies in our data set sample a diversity of SFHs, with a median formation redshift (corresponding to the lookback time from the redshift of observation to when a galaxy forms 50% of its mass, t 50) of z = 2.8 ± 0.5, which is similar to or marginally higher than that of massive quiescent field and cluster galaxy studies. We also report median age–stellar mass relations for the full sample (age of the universe at t 50 (Gyr) = 2.52 (±0.04)–1.66 (±0.12) log10(M/1011 M ⊙)) and recover downsizing trends across stellar mass; we find that massive galaxies in our cluster sample form on aggregate ∼0.75 Gyr earlier than lower-mass galaxies. We also find marginally steeper age–mass relations at high redshifts, and report a bigger difference in formation redshifts across stellar mass for fixed environment, relative to formation redshifts across environment for fixed stellar mass.
Measurements of Moisture Suction and Diffusion Coefficient in Hot-Mix Asphalt and Their Relationships to Moisture Damage

A procedure for measuring the total suction in hot-mix asphalt (HMA) mixes was developed in this study. Suction measurements were related to physical and chemical properties of HMA that influence moisture damage. This procedure was achieved in two phases. In the first phase, the total suction was measured in HMA specimens with different types of aggregates and with different air void distributions and aggregate gradations. The results showed that the drying test using a 60°C temperature-controlled room was the most appropriate setup for measuring the total suction in HMA with thermocouple psychrometers. The characteristics of suction–moisture content curves were found to be related to the air void distribution in HMA and to the resistance of the mixtures to moisture damage. In the second phase, total suction was measured in sand asphalt specimens. These specimens had different combinations of aggregates and binders that exhibited different field resistances to moisture damage. The suction measurements were used to calculate the moisture diffusion coefficient. The results revealed that mixes with a higher diffusion coefficient are those that had poor resistance to moisture damage.
Clinical Antiviral Drug Arbidol Inhibits Infection by SARS-CoV-2 and Variants through Direct Binding to the Spike Protein

Arbidol (ARB) is a broad-spectrum antiviral drug approved in Russia and China for the treatment of influenza. ARB was tested in patients as a drug candidate for the treatment at the early onset of COVID-19 caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite promising clinical results and multiple ongoing trials, preclinical data are lacking and the molecular mechanism of action of ARB against SARS-CoV-2 remains unknown. Here, we demonstrate that ARB binds to the spike viral fusion glycoprotein of the SARS-CoV-2 Wuhan strain as well as its more virulent variants from the United Kingdom (strain B.1.1.7) and South Africa (strain B.1.351). We pinpoint the ARB binding site on the S protein to the S2 membrane fusion domain and use an infection assay with Moloney murine leukemia virus (MLV) pseudoviruses (PVs) pseudotyped with the S proteins of the Wuhan strain and the new variants to show that this interaction is sufficient for the viral cell entry inhibition by ARB. Finally, our experiments reveal that the ARB interaction leads to a significant destabilization and eventual lysosomal degradation of the S protein in cells. Collectively, our results identify ARB as the first clinically approved small molecule drug binder of the SARS-CoV-2 S protein and place ARB among the more promising drug candidates for COVID-19.
Models for assessing net CO2 emissions applied on district heating technologies

Methodologies to assess the effects of energy projects on global carbon dioxide emissions will be an important feature of a future international carbon dioxide trading system. In this paper, we present and discuss four different models for assessing the net carbon dioxide emissions resulting from a certain energy project. These models are applied to different district heating technologies. To judge the mitigation performance of a project, the amount of carbon dioxide released in kilograms is expressed per megawatt‐hour of useful district heating produced. All the models consider the marginal change caused by the project on the electric power system. The different model perspectives are discussed, and it is shown that the choice of model is very critical for assessing the net carbon dioxide emissions from an energy project. Copyright © 2003 John Wiley & Sons, Ltd.
Diagnostic performance of radiomics using machine learning algorithms to predict MGMT promoter methylation status in glioma patients: a meta-analysis.

PURPOSE We aimed to assess the diagnostic performance of radiomics using machine learning algorithms to predict the methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter in glioma patients. METHODS A comprehensive literature search of PubMed, EMBASE, and Web of Science until 27 July 2021 was performed to identify eligible studies. Stata SE 15.0 and Meta-Disc 1.4 were used for data analysis. RESULTS A total of fifteen studies with 1663 patients were included: five studies with training and validation cohorts and ten with only training cohorts. The pooled sensitivity and specificity of machine learning for predicting MGMT promoter methylation in gliomas were 85% (95% CI 79%-90%) and 84% (95% CI 78%-88%) in the training cohort (n=15) and 84% (95% CI 70%-92%) and 78% (95% CI 63%-88%) in the validation cohort (n=5). The AUC was 0.91 (95% CI 0.88-0.93) in the training cohort and 0.88 (95% CI 0.85-0.91) in the validation cohort. The meta-regression demonstrated that magnetic resonance imaging sequences were related to heterogeneity. The sensitivity analysis showed that heterogeneity was reduced by excluding one study with the lowest diagnostic performance. CONCLUSION This meta-analysis demonstrated that machine learning is a promising, reliable and repeatable candidate method for predicting MGMT promoter methylation status in glioma and showed a higher performance than non-machine learning methods.
Domestic Ethnic Conflict and Ethnic Nepotism: A Comparative Analysis

Ethnic conflict seems to be common in all countries of the world where people are divided into separate ethnic groups, that may have a racial, national, linguistic, tribal, religious or caste basis. In this article it is proposed that a significant part of the universality of ethnic conflict can be explained by our evolved predisposition to ethnic nepotism, which can be regarded as an extended form of nepotism. Evolutionary theories of inclusive fitness and kin selection explain the origin and universality of nepotism. The members of an ethnic group tend to favour their group members over non-members because they are more related to their group members than to outsiders. This disposition to favour kin over non-kin becomes important in social life and politics when people and groups of people have to compete for scarce resources. Two hypotheses on political consequences of ethnic nepotism are presented: (1) significant ethnic division tends to lead to ethnic interest conflict in all societies and (2) the more a society is ethnically divided, the more political and other interest conflict tend to become channelled into ethnic lines. These two hypotheses are tested by empirical evidence for 183 contemporary states. The hypothetical concepts `ethnic division' and `ethnic conflict' are operationalized into empirical variables. The results support the two hypotheses. Deviating cases underline the importance of other relevant factors behind ethnic conflict and violence.
Finite element beam propagation method for three-dimensional optical waveguide structures

A beam propagation method (BPM) based on the finite element method (FEM) is described for longitudinally varying three-dimensional (3-D) optical waveguides. In order to avoid nonphysical reflections from the computational window edges, the transparent boundary condition is introduced. The present algorithm using the Pade approximation is, to our knowledge, the first wide-angle finite element beam propagation method for 3-D waveguide structures. To show the validity and usefulness of this approach, numerical results are shown for Gaussian-beam excitation of a straight rib waveguide and guided-mode propagation in a Y-branching rib waveguide.
DEFECTS GENERATION IN SIO 2 /HFO 2 STUDIED WITH VARIABLE T CHARGE - TDISCHARGE CHARGE PUMPING (VT 2 CP).

A Variable Tcharge-Tdischarge Charge Pumping (VT 2 CP) is used to investigate the creation of traps in the SiO2 and HfO2 separately in an ALD SiO2/HfO2 metal gate stack. It is shown that by independently controlling the pulse low timing “discharging time” and high level timing “charging time”, we are able to separate the traps in the interfacial SiO2 from the traps in the HfO2 and observe the creation of new traps in both constituent layers. During degradation the increase of traps, both in the SiO2 as well as in the HfO2, follows a power law behavior as a function of time with an exponent ~0.32 and ~0.34 respectively independent of stress voltage. The voltage acceleration of creation of HfO2 traps (-30) found using VT 2 CP is nearly identical of the TDDB (-27) confirming the earlier published model that TDDB occurs when the density of traps in the HfO2 reaches a critical value. VT 2 CP can accurately detect degradation down to a much lower voltage than the dielectric breakdown measurement range and only one stress experiment combined with VT 2 CP is sufficient to determine the degradation at a given voltage, while a TDDB test requires many measurements in order to construct an accurate distribution of failure times.
Phthalates and alternative plasticizers differentially affect phenotypic parameters in gonadal somatic and germ cell lines

Abstract The developmental and reproductive toxicity associated with exposure to phthalates has motivated a search for alternatives. However, there is limited knowledge regarding the adverse effects of some of these chemicals. We used high-content imaging to compare the effects of mono (2-ethylhexyl) phthalate (MEHP) with six alternative plasticizers: di-2-ethylhexyl terephthalate (DEHTP); diisononyl-phthalate (DINP); diisononylcyclohexane-1,2-dicarboxylate (DINCH); 2-ethylhexyl adipate (DEHA); 2,2,4-trimethyl 1,3-pentanediol diisobutyrate (TXIB) and di-isodecyl-adipate (DIDA). A male germ spermatogonial cell line (C18–4), a Sertoli cell line (TM4) and two steroidogenic cell lines (MA-10 Leydig and KGN granulosa) were exposed for 48 h to each chemical (0.001–100 µM). Cell images were analyzed to assess cytotoxicity and effects on phenotypic endpoints. Only MEHP (100 µM) was cytotoxic and only in C18–4 cells. However, several plasticizers had distinct phenotypic effects in all four cell lines. DINP increased Calcein intensity in C18–4 cells, whereas DIDA induced oxidative stress. In TM4 cells, MEHP, and DINCH affected lipid droplet numbers, while DEHTP and DINCH increased oxidative stress. In MA-10 cells, MEHP increased lipid droplet areas and oxidative stress; DINP decreased the number of lysosomes, while DINP, DEHA, and DIDA altered mitochondrial activity. In KGN cells, MEHP, DINP and DINCH increased the number of lipid droplets, whereas DINP decreased the number of lysosomes, increased oxidative stress and affected mitochondria. The Toxicological Priority Index (ToxPi) provided a visual illustration of the cell line specificity of the effects on phenotypic parameters. The lowest administered equivalent doses were observed for MEHP. We propose that this approach may assist in screening alternative plasticizers. Summary Sentence WhileMEHP was the only chemical displaying cytotoxicity, alternative plasticizers caused cell type-specific phenotypic changes in somatic and germ cell lines. Graphical Abstract
A novel single-phase active-clamped ZVT-PWM PFC converter

A novel single-phase active-clamped power factor correction converter is proposed. Based on the constant frequency and the resonant active-clamped techniques. This circuit realizes ZVT of the main switch and ZCS of the auxiliary switch. In the full range of loads, it can be operated at constant frequency soft-switching mode. Finally, the PSPICE simulation and experiment results of a 3 kW 100 kHz PFC converter are presented, whose efficiency is as high as 97%.
Safety and immediate humoral response of COVID-19 vaccines in chronic kidney disease patients: the SENCOVAC study

Abstract Background Chronic kidney disease (CKD) patients are at high-risk for severe Covid-19. The multicentric, observational and prospective SENCOVAC study aims to describe the humoral response and safety of SARS-CoV-2 vaccines in CKD patients. Safety and immediate humoral response results are reported here. Methods Four cohorts of patients were included: kidney transplant (KT) recipients, haemodialysis (HD), peritoneal dialysis (PD) and non-dialysis CKD patients from 50 Spanish centres. Adverse events after vaccine doses were recorded. At baseline and on day 28 after the last vaccine dose, anti-Spike antibodies were measured and compared between cohorts. Factors associated with development of anti-Spike antibodies were analyzed. Results 1746 participants were recruited: 1116 HD, 171 PD, 176 non-dialysis CKD patients and 283 KT recipients. Most patients (98%) received mRNA vaccines. At least one vaccine reaction developed after the first dose in 763 (53.5%) and after the second dose in 741 (54.5%) of patients. Anti-Spike antibodies were measured in the first 301 patients. At 28 days, 95% of patients had developed antibodies: 79% of KT, 98% of HD, 99% of PD and 100% of non-dialysis CKD patients (p<0.001). In a multivariate adjusted analysis, absence of an antibody response was independently associated to KT (OR 20.56, p = 0.001) and to BNT162b2 vaccine (OR 6.03, p = 0.023). Conclusion The rate of anti-Spike antibody development after vaccination in KT patients was low but in other CKD patients it approached 100%; suggesting that KT patients require persistent isolation measures and booster doses of a Covid-19 vaccine. Potential differences between Covid-19 vaccines should be explored in prospective controlled studies.
Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model

Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of comedicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A, leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and human liver microsomes (HLM) to predict clinically relevant drug-drug interactions was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate, and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were preincubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition was detected in HLM for four moderate/strong inhibitors, suggesting that some optimization of incubation conditions (i.e., lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters maximal rate of enzyme inactivation (min−1) (kinact) and concentration of inhibitor resulting in 50% of the maximum enzyme inactivation (KI) into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models, which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within twofold of the observed value. SIGNIFICANCE STATEMENT Coupling time-dependent inactivation parameters derived from pooled human hepatocytes and human liver microsomes (HLM) with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical drug-drug interaction risk from in vitro data. Optimization is needed to evaluate time-dependent inhibition (TDI) for weak and moderate inhibitors using HLM. Recommendations are made with respect to input parameters for in vitro to in vivo extrapolation (IVIVE) of TDI with non-CYP3A enzymes using available data from HLM and human hepatocytes.
Crime prevention through environmental design: what works and what does not? - Reflections from a Nigerian city

In many cities, residents engage in grassroots efforts to reclaim space and participate in shaping engaged and safe communities. They hold weekend barbecues in newly greened lots, transform overgrown areas into community gardens, and help neighbors replace broken windows and old porch lights. City and nonprofit groups also spearhead initiatives to change spaces by altering the flow of foot and vehicle traffic and investing in greening projects and supporting resident initiatives.
Entrapment and escape: Exploring the relationship between suicide and emigration in a post-communist country

Background: Suicide rate in Hungary was nearly the highest in the world in the decades preceding the transition of the social system. Shortly after the transition in 1989, a radical decrease in fatal suicides occurred, parallel with a marked increase in emigration. Methods: We analyzed the data published by the Hungarian Central Statistical Office to detect if there was an association between the remarkable drop in suicide rates and the changes in emigration rates from 1995 to 2019. Results: The results of a brief statistical analysis on the correlation between suicide rate and emigration confirmed a strong negative relationship (r = −.855, p = .00). For more precise results, we applied linear regression analysis, which showed that the emigration rate predicted 73.2% of suicide rate variances with a high predictive value (β = −.983). Conclusion: The study provides a possible explanation through a phenomenological analysis on major life transformations. Relating the arrested flight/cry of pain theory, the theory of rites of passage and double-bind communication resulted a comprehensive and coherent, but not exhaustive explanation on the relationship between suicide and emigration.