Miracle-dz/UniFAR-FTUs huggingface dataset:
Summit: Benchmarking Machine Learning Methods for Reaction Optimisation

In the fine chemicals industry, reaction screening and optimisation are essential to development of new products. However, this screening can be extremely time and labor intensive, especially when intuition is used. Machine learning offers a solution through iterative suggestions of new experiments based on past experimental data, but knowing which machine learning strategy to apply in a particular case is still difficult. Here, we develop chemically-motivated virtual benchmarks for reaction optimisation and compare several strategies on these benchmarks. The benchmarks and strategies are encompassed in an open source framework named Summit. The results of our tests show that Bayesian optimisation strategies perform very well across the types of problems faced in chemical reaction optimisation, while many strategies commonly used in reaction optimisation fail to find optimal solutions.
Local and remote response of ozone to Arctic stratospheric circulation extremes

Abstract. Intense natural circulation variability associated with stratospheric sudden warmings, vortex intensifications, and final warmings is a typical feature of the winter Arctic stratosphere. The attendant changes in transport, mixing, and temperature create pronounced perturbations in stratospheric ozone. Understanding these perturbations is important because of their potential feedbacks with the circulation and because ozone is a key trace gas of the stratosphere. Here, we use Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), reanalysis to contrast the typical spatiotemporal structure of ozone during sudden warming and vortex intensification events. We examine the changes of ozone in both the Arctic and the tropics, document the underlying dynamical mechanisms for the observed changes, and analyze the entire life cycle of the stratospheric events – from the event onset in midwinter to the final warming in early spring. Over the Arctic and during sudden warmings, ozone undergoes a rapid and long-lasting increase of up to ∼ 50 DU, which only gradually decays to climatology before the final warming. In contrast, vortex intensifications are passive events, associated with gradual decreases in Arctic ozone that reach ∼ 40 DU during late winter and decay thereafter. The persistent loss in Arctic ozone during vortex intensifications is dramatically compensated by sudden warming-like increases after the final warming. In the tropics, the changes in ozone from Arctic circulation events are obscured by the influences from the quasi-biennial oscillation. After controlling for this effect, small but coherent reductions in tropical ozone can be seen during the onset of sudden warmings (∼ 2.5 DU) and also during the final warmings that follow vortex intensifications (∼ 2 DU). Our results demonstrate that Arctic circulation extremes have significant local and remote influences on the distribution of stratospheric ozone.
"Health Insurance Coverage: Early Release of Estimates From the National Health Interview Survey, January–June 2020

• From January through March 2011, 46.5 million persons of all ages (15.3%) were uninsured at the time of interview, 60.5 million (19.8%) had been uninsured for at least part of the year prior to interview, and 34.2 million (11.2%) had been uninsured for more than a year at the time of interview. • From January through March 2011, the percentage of children under age 18 years who were uninsured at the time of interview was 6.9%. • Among adults aged 19–25, the percentage uninsured at the time of interview decreased from 33.9% (10 million) in 2010 to 30.4% (9.1 million) in the first 3 months of 2011. • Private coverage decreased among near poor adults aged 18–64, from 52.6% in 1997 to 36.1% in the first 3 months of 2011. The uninsured rate (40.2%) was higher than the private coverage rate (36.1%) for this population. • From January through March 2011, 29.1% of persons under age 65 with private health insurance at the time of interview were enrolled in a high deductible health plan (HDHP), including 8.8% who were enrolled in a consumer-directed health plan (CDHP). More than 50% of persons with a private plan obtained by means other than through employment were enrolled in an HDHP. An estimated 20.7% of persons with private health insurance were in a family with a flexible spending account (FSA) for medical expenses.
Bangla language textual image description by hybrid neural network model

Automatic image captioning task in different language is a challenging task which has not been well investigated yet due to the lack of dataset and effective models. It also requires good understanding of scene and contextual embedding for robust semantic interpretation of images for natural language image descriptor. To generate image descriptor in Bangla, we created a new Bangla dataset of images paired with target language label, named as Bangla Natural Language Image to Text (BNLIT) dataset. To deal with the image understanding, we propose a hybrid encoder-decoder model based on encoder-decoder architecture and the model is evaluated on our newly created dataset. This proposed approach achieves significance performance improvement on task of semantic retrieval of images. Our hybrid model uses the Convolutional NeuralNetwork as an encoder whereas the Bidirectional Long Short Term Memory is used for the sentence representation that decreases the computational complexities without trading off the exactness of the descriptor. The model yielded benchmark accuracy in recovering Bangla natural language and we also conducted a thorough numerical analysis of the model performance on the BNLIT dataset.
A new characterization of simple $K_3$-groups using same-order type

Let $G$ be a group, define an equivalence relation $\sim$ as below: $$\forall \ g, h \in G, \ g \sim h \Longleftrightarrow |g| = |h|$$ the set of sizes of equivalence classes with respect to this relation is called the same-order type of $G$ and denoted by $\alpha(G)$. And $G$ is said a $\alpha_n$-group if $|\alpha(G)|=n$. Let $\pi(G)$ be the set of prime divisors of the order of $G$. A simple group of $G$ is called a simple $K_n$-group if $|\pi(G)|=n$. We give a new characterization of simple $K_3$-groups using same-order type. Indeed we prove that a nonabelian simple group $G$ has same-order type \{r, m, n, k, l\} if and only if $G \cong PSL(2,q)$, with $q=7, 8$ or $9$. This result generalizes the main results in \cite{KKA}, \cite{Sh} and \cite{TZ1}. Motived by the main result in \cite{TZ1} L. J. Taghvasani and M. Zarrin put the following Conjecture 2.10: \textit{Let $S$ be a nonabelian simple $\alpha_n$-group and $G$ a $\alpha_n$-group such that $|S|=|G|$. Then $S \cong G$}. In this paper with a counterexample we give a negative answer to this question.
Possible adaptive growth responses of Chromolaena odorata during heavy metal remediation

The changes in morphological and crude protein content of Chromolaena odorata to heavy metal-induced stress were investigated. This was with a view to providing information on the test plant adaptation potential during remediation of contaminated with . Stems of C. odorata were planted in soils treated with Cd (as CdCl) and Pb (as PbCl) at different concentrations of 6.67, 33.3 and 100 mg/kg respectively, singly and in combinations (Cd+Pb). After the exposure of C. odorata to heavy metals for 3 months, results showed that residual Pb concentration in soil was 4.31 mg/kg in the 6.66mg (Pb)/kg-polluted soil, compared to the control (0.7 mg/kg). Residual concentration of Cd in soil was 0.22 mg/kg in the soil originally polluted with 6.66 mg (Cd)/kg, compared to a residual concentration of 5.94 mg/kg in the 100 mg (Cd)/kg-polluted soil. Residual metal concentration after plant exposure was lower for Cd in Cd-polluted soil than for Pb in Pb-polluted soils suggesting better plant-assisted remediation of Cd than Pb. Total crude protein content of plants exposed to metals increased with increase in metal concentration in soil. The presence of metal in soil reduced plant height from 127 cm in the control to a range of vales from 93 – 117 cm in the plants exposed to metal contamination. However, at lower concentrations of the Cd in soil, plants showed improved root branching (117.00±11.31), compared to the control (62.35±5.63). Results of the study further show the capability of C. odorata for metal remediations and also possible morphological adaptation mechanisms of survival in metal-impacted soils. Keywords : Heavy metals, bioremediation, crude protein, adaptation, Chromolaena odorata
FACMAC: Factored Multi-Agent Centralised Policy Gradients

We propose FACtored Multi-Agent Centralised policy gradients (FACMAC), a new method for cooperative multi-agent reinforcement learning in both discrete and continuous action spaces. Like MADDPG, a popular multi-agent actor-critic method, our approach uses deep deterministic policy gradients to learn policies. However, FACMAC learns a centralised but factored critic, which combines per-agent utilities into the joint action-value function via a non-linear monotonic function, as in QMIX, a popular multi-agent Q-learning algorithm. However, unlike QMIX, there are no inherent constraints on factoring the critic. We thus also employ a nonmonotonic factorisation and empirically demonstrate that its increased representational capacity allows it to solve some tasks that cannot be solved with monolithic, or monotonically factored critics. In addition, FACMAC uses a centralised policy gradient estimator that optimises over the entire joint action space, rather than optimising over each agent's action space separately as in MADDPG. This allows for more coordinated policy changes and fully reaps the benefits of a centralised critic. We evaluate FACMAC on variants of the multi-agent particle environments, a novel multi-agent MuJoCo benchmark, and a challenging set of StarCraft II micromanagement tasks. Empirical results demonstrate FACMAC's superior performance over MADDPG and other baselines on all three domains.
PROBLEMS RELATED TO SURGERY AND PATHOLOGY IN LIP CANCER PATIENTS AND THEIR MANAGEMENT

Giris: Dudak kanserleri bas boyun bolgesinde ikinci siklikta gorulen kanserlerdir. Fonksiyonel ve estetik sonuclari ve agresif seyri sebebiyle cerrahi eksizyon sinirlari, boyun diseksiyonu tipi ve rekonstruksiyon secenekleri gibi klinik yaklasim tipleri dudak kanseri hakkinda tartisilan konulardir. Calismada cerrahi oncesi yapilan degerlendirmelerin guvenilirligi, rekurrens ve metastaz icin risk faktorleri, cerrahiye bagli morbiditeler ve tedavileri arastirildi. Method: Klinigimizde tedavi edilen bazal hucreli karsinom ve squamoz hucreli karsinom tanili hastalarin verileri retrospektif olarak tarandi. Hastalarin demografik verileri degerlendirildi, punch biyopsi ve radyolojik goruntulemelerin guvenilirligi tartisildi ve patolojik ozelliklerin rekurrens ve metastaz risk uzerine etkileri arastirildi. Cerrahi sonrasi morbiditeler degerlendirilerek tum bu problemler ve cozum yollari literatur esligide tartisildi. Sonuc: Bu calismada punch biyopsi guvenilir bulunmadi. Rekurrensler ileri evre ve perinoral invazyon ile, servikal metastazlar ise cikartilan lezyon boyutu ve cerrahi sinir ile iliskili bulundu. Lokal fleplerde donor alan morbiditeleri daha yuksekti. Genis eksizyon, boyun diseksiyonu ve serbest flep ile rekonstruksiyon yapilan hasta grubunda rekurrens veya metastaz gozlenmedi. Tartisma: Erken tani ve fonksiyonel-estetik onarim dudak kanseri prognozunda en onemli faktorlerdir. Yapilan ilk cerrahi prognozu belirlediginden cok onemlidir. Evre ilerledikce cerrahi komplekslesir fakat iyi bir klinik yaklasim ile erken evreler kadar iyi bir prognoz saglanabilir.
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification

For future learning systems, incremental learning is desirable because it allows for: efficient resource usage by eliminating the need to retrain from scratch at the arrival of new data; reduced memory usage by preventing or limiting the amount of data required to be stored – also important when privacy limitations are imposed; and learning that more closely resembles human learning. The main challenge for incremental learning is catastrophic forgetting, which refers to the precipitous drop in performance on previously learned tasks after learning a new one. Incremental learning of deep neural networks has seen explosive growth in recent years. Initial work focused on task-incremental learning, where a task-ID is provided at inference time. Recently, we have seen a shift towards class-incremental learning where the learner must discriminate at inference time between all classes seen in previous tasks without recourse to a task-ID. In this paper, we provide a complete survey of existing class-incremental learning methods for image classification, and in particular, we perform an extensive experimental evaluation on thirteen class-incremental methods. We consider several new experimental scenarios, including a comparison of class-incremental methods on multiple large-scale image classification datasets, an investigation into small and large domain shifts, and a comparison of various network architectures.
Physical activity promotion is lacking in local treatment protocols for patients hospitalized with myocardial infarction: A cross-sectional study

Objectives: To describe the content and methodological quality of local physiotherapy and nursing treatment protocols specifically regarding physical activity promotion in patients hospitalised with myocardial infarction. Design: Cross-sectional study comprising the analysis of 18 physiotherapy and 14 nursing protocols. Setting: Protocols from twenty Dutch hospitals were used. Main outcome measures: Data were extracted from protocols for patients hospitalised with myocardial infarction according to a standardized data-extraction procedure. Descriptive statistics were used to describe the content of protocols, in specific, treatment goals, interventions, clinimetrics and discharge criteria. Methodological quality of the protocols was examined using the AGREE-II tool. Results: Therapeutic goals concerning physical activity were described in 83% of the physiotherapy protocols and in 7% of the nursing protocols. Therapeutic interventions concerning physical activity were described in 100% of the physiotherapy protocols and in 57% of the nursing protocols. Two (14%) of the fourteen interventions described in the physiotherapy protocols and none in the nursing protocols, were interpreted as physical activity promotion. All protocols were rated as having low methodological quality, mainly due to a lack of supporting scientific evidence. The overall quality was rated with an average score of 3 out of 7 (range: 1-5). Conclusions: Physiotherapy and nursing protocols for hospitalized patients with myocardial infarction are primarily aimed at physical activity under supervision, rather than physical activity promotion. Our work provides physiotherapists and nurses insights in how to further improve the content and methodological quality of their local treatment protocols for patients hospitalised with myocardial infarction.
The 2175 Å Dust Feature in Star-forming Galaxies at 1.3 ≤ z ≤ 1.8: The Dependence on Stellar Mass and Specific Star Formation Rate

We present direct spectroscopic measurements of the broad 2175 Å absorption feature in 505 star-forming main-sequence galaxies at 1.3 ≤ z ≤ 1.8 using individual and stacked spectra from the zCOSMOS-deep survey. Significant 2175 Å excess absorption features of moderate strength are measured, especially in the composite spectra. The excess absorption is well described by a Drude profile. The bump amplitude expressed in units of k(λ) = A(λ)/E(B − V), relative to the featureless Calzetti et al. law, has a range B k ≈ 0.2–0.8. The bump amplitude decreases with the specific star formation rate (sSFR), while it increases moderately with the stellar mass. However, a comparison with local “starburst” galaxies shows that the high-redshift main-sequence galaxies have stronger bump features, despite having a higher sSFR than the local sample. Plotting the bump strength against the ΔlogsSFR≡logSFR/SFRMS relative to the main sequence, however, brings the two samples into much better concordance. This may indicate that it is the recent star formation history of the galaxies that determines the bump strength through the destruction of small carbonaceous grains by supernovae and intense radiation fields coupled with the time delay of ∼1 Gyr in the appearance of carbon-rich asymptotic giant branch stars.
The infrared-radio correlation of star-forming galaxies is stronglyM⋆-dependent but nearly redshift-invariant sincez∼ 4

Over the past decade, several works have used the ratio between total (rest 8−1000μm) infrared and radio (rest 1.4 GHz) luminosity in star-forming galaxies (qIR), often referred to as the infrared-radio correlation (IRRC), to calibrate the radio emission as a star formation rate (SFR) indicator. Previous studies constrained the evolution ofqIRwith redshift, finding a mild but significant decline that is yet to be understood. Here, for the first time, we calibrateqIRas a function ofbothstellar mass (M⋆) and redshift, starting from anM⋆-selected sample of > 400 000 star-forming galaxies in the COSMOS field, identified via (NUV − r)/(r − J) colours, at redshifts of 0.1 < z < 4.5. Within each (M⋆,z) bin, we stacked the deepest available infrared/sub-mm and radio images. We fit the stacked IR spectral energy distributions with typical star-forming galaxy and IR-AGN templates. We then carefully removed the radio AGN candidates via a recursive approach. We find that the IRRC evolves primarily withM⋆, with more massive galaxies displaying a systematically lowerqIR. A secondary, weaker dependence on redshift is also observed. The best-fit analytical expression is the following:qIR(M⋆, z) = (2.646 ± 0.024) × (1 + z)( − 0.023 ± 0.008)–(0.148 ± 0.013) × (log M⋆/M⊙ − 10). Adding the UV dust-uncorrected contribution to the IR as a proxy for the total SFR would further steepen theqIRdependence onM⋆. We interpret the apparent redshift decline reported in previous works as due to low-M⋆galaxies being progressively under-represented at high redshift, as a consequence of binning only in redshift and using either infrared or radio-detected samples. The lower IR/radio ratios seen in more massive galaxies are well described by their higher observed SFR surface densities. Our findings highlight the fact that using radio-synchrotron emission as a proxy for SFR requires novelM⋆-dependent recipes that will enable us to convert detections from future ultra-deep radio surveys into accurate SFR measurements down to low-M⋆galaxies with low SFR.
A giant X-ray dust scattering ring discovered with SRG/eROSITA around the black hole transient MAXI J1348–630

We report the discovery of a giant dust scattering ring around the Black Hole transient MAXI J1348−630 with SRG/eROSITA during its first X-ray all-sky survey. During the discovery observation in February 2020, the ring had an outer diameter of 1.3 deg, growing to 1.6 deg by the time of the second all-sky survey scan in August 2020. This makes the new dust ring by far the largest X-ray scattering ring observed so far. Dust scattering halos, in particular the rings found around transient sources, provide an opportunity to make precise distance measurements towards the original X-ray sources. We combine data from SRG/eROSITA, XMM-Newton, MAXI, and Gaia to measure the geometrical distance of MAXI J1348−630. The Gaia data place the scattering dust at a distance of 2050 pc. Based on the measured time lags and the geometry of the ring we find MAXI J1348−630 at a distance of 3390 pc with a statistical uncertainty of only 1.1% and a systematic uncertainty of 10% caused mainly by the parallax offset of Gaia. This result makes MAXI J1348−630 one of the black hole transients with the most accurately determined distances. The new distance leads to a revised mass estimate for the black hole of 11 ± 2 M⊙. The transition to the soft state during the outburst occurred when the bolometric luminosity of MAXI J1348−630 reached 1.7% of its Eddington luminosity.
Complex networks with tuneable spectral dimension as a universality playground

The authors study a complex network model whose spectral dimension can be continuously tuned in the range ${d}_{s}\ensuremath{\in}[1,+\mathrm{\ensuremath{\infty}}]$. The disorder contribution to this dimension mirrors the dependence of the anomalous dimension of the Ising model in fractional dimensions.
Understanding of the Extremely Low Thermal Conductivity in High‐Performance Polycrystalline SnSe through Potassium Doping

P‐type polycrystalline SnSe and K0.01Sn0. 99Se are prepared by combining mechanical alloying (MA) and spark plasma sintering (SPS). The highest ZT of ≈0.65 is obtained at 773 K for undoped SnSe by optimizing the MA time. To enhance the electrical transport properties of SnSe, K is selected as an effective dopant. It is found that the maximal power factor can be enhanced significantly from ≈280 μW m−1 K−2 for undoped SnSe to ≈350 μW m−1 K−2 for K‐doped SnSe. It is also observed that the thermal conductivity of polycrystalline SnSe can be enhanced if the SnSe powders are slightly oxidized. Surprisingly, after K doping, the absence of Sn oxides at grain boundaries and the presence of coherent nanoprecipitates in the SnSe matrix contribute to an impressively low lattice thermal conductivity of ≈0.20 W m−1 K−1 at 773 K along the sample section perpendicular to pressing direction of SPS. This extremely low lattice thermal conductivity coupled with the enhanced power factor results in a record high ZT of ≈1.1 at 773 K along this direction in polycrystalline SnSe.
Assessment of Regression Models With Discrete Outcomes Using Quasi-Empirical Residual Distribution Functions

Abstract Making informed decisions about model adequacy has been an outstanding issue for regression models with discrete outcomes. Standard assessment tools for such outcomes (e.g., deviance residuals) often show a large discrepancy from the hypothesized pattern even under the true model and are not informative, especially when data are highly discrete (e.g., binary). To fill this gap, we propose a quasi-empirical residual distribution function for general discrete (e.g., ordinal and count) outcomes that serves as an alternative to the empirical distribution function of Cox–Snell residuals. The assessment tool we propose is a principled approach and does not require injecting noise into the data. When at least one continuous covariate is available, we show asymptotically that the proposed function converges uniformly to the identity function under the correctly specified model, even with highly discrete outcomes. Through simulation studies, we demonstrate empirically that the proposed quasi-empirical residual distribution function outperforms commonly used residuals for various model assessment tasks, since it is close to the hypothesized pattern under the true model and significantly departs from this pattern under model misspecification, and is thus an effective assessment tool. Supplementary materials for this article are available online.