Miracle-dz/UniFAR-FTUs huggingface dataset:
Overdensities of submillimetre-bright sources around candidate protocluster cores selected from the South Pole Telescope survey

We present APEX-LABOCA 870-μm observations of the fields surrounding the nine brightest, high-redshift, unlensed objects discovered in the South Pole Telescope’s (SPT) 2500 deg2 survey. Initially seen as point sources by SPT’s 1-arcmin beam, the 19-arcsec resolution of our new data enables us to deblend these objects and search for submillimetre (submm) sources in the surrounding fields. We find a total of 98 sources above a threshold of 3. 7σ in the observed area of 1300 arcmin2, where the bright central cores resolve into multiple components. After applying a radial cut to our LABOCA sources to achieve uniform sensitivity and angular size across each of the nine fields, we compute the cumulative and differential number counts and compare them to estimates of the background, finding a significant overdensity of δ ≈ 10 at S870 = 14 mJy. The large overdensities of bright submm sources surrounding these fields suggest that they could be candidate protoclusters undergoing massive star-formation events. Photometric and spectroscopic redshifts of the unlensed central objects range from z = 3 to 7, implying a volume density of star-forming protoclusters of approximately 0.1 Gpc−3. If the surrounding submm sources in these fields are at the same redshifts as the central objects, then the total star-formation rates of these candidate protoclusters reach 10,000 M⊙ yr−1, making them much more active at these redshifts than seen so far in either simulations or observations.
From Language Games to Drawing Games

We attempt to automate various artistic processes by inventing a set of drawing games, analogous to the approach taken by emergent language research in inventing communication games. A critical difference is that drawing games demand much less effort from the receiver than do language games. Artists must work with pre-trained viewers who spend little time learning artist specific representational conventions, but who instead have a pre-trained visual system optimized for behaviour in the world by understanding to varying extents the environment's visual affordances. After considering various kinds of drawing game we present some preliminary experiments which have generated images by closing the generative-critical loop.
Structure and kinematics of shocked gas in Sgr B2: further evidence of a cloud–cloud collision from SiO emission maps

We present SiO J=2-1 maps of the Sgr B2 molecular cloud, which show shocked gas with a turbulent substructure comprising at least three cavities at velocities of [10,40] km s$^{-1}$ and an arc at velocities of [-20,10] km s$^{-1}$. The spatial anti-correlation of shocked gas at low and high velocities, and the presence of bridging features in position-velocity diagrams suggest that these structures formed in a cloud-cloud collision. Some of the known compact HII regions spatially overlap with sites of strong SiO emission at velocities of [40,85] km s$^{-1}$, and are between or along the edges of SiO gas features at [100,120] km s$^{-1}$, suggesting that the stars responsible for ionizing the compact HII regions formed in compressed gas due to this collision. We find gas densities and kinetic temperatures of the order of $n_{\rm H_2}\sim 10^5\rm cm^{-3}$ and $\sim$30 K, respectively, towards three positions of Sgr B2. The average values of the SiO relative abundances, integrated line intensities, and line widths are $\sim$10$^{-9}$, $\sim$11 K km s$^{-1}$, and $\sim$31 km s$^{-1}$, respectively. These values agree with those obtained with chemical models that mimic grain sputtering by C-type shocks. A comparison of our observations with hydrodynamical simulations shows that a cloud-cloud collision that took place $\lesssim$ 0.5 Myr ago can explain the density distribution with a mean column density of $\bar{N}_{\rm H_2}\gtrsim 5\times10^{22}$ cm$^{-2}$, and the morphology and kinematics of shocked gas in different velocity channels. Colliding clouds are efficient at producing internal shocks with velocities $\sim$5-50 km $s^{-1}$. High-velocity shocks are produced during the early stages of the collision and can readily ignite star formation, while moderate- and low-velocity shocks are important over longer timescales and can explain the widespread SiO emission in Sgr B2.
Randomized Value Functions via Posterior State-Abstraction Sampling

State abstraction has been an essential tool for dramatically improving the sample efficiency of reinforcement-learning algorithms. Indeed, by exposing and accentuating various types of latent structure within the environment, different classes of state abstraction have enabled improved theoretical guarantees and empirical performance. When dealing with state abstractions that capture structure in the value function, however, a standard assumption is that the true abstraction has been supplied or unrealistically computed a priori, leaving open the question of how to efficiently uncover such latent structure while jointly seeking out optimal behavior. Taking inspiration from the bandit literature, we propose that an agent seeking out latent task structure must explicitly represent and maintain its uncertainty over that structure as part of its overall uncertainty about the environment. We introduce a practical algorithm for doing this using two posterior distributions over state abstractions and abstract-state values. In empirically validating our approach, we find that substantial performance gains lie in the multi-task setting where tasks share a common, low-dimensional representation.
“I Trust in Staff's Creativity”—The Impact of COVID-19 Lockdowns on Physical Activity Promotion in Nursing Homes Through the Lenses of Organizational Sociology

Objectives: The health-enhancing benefits or regular physical activity (PA) reach into old age. With the emergence of the coronavirus disease of 2019 (COVID-19) pandemic and the associated national lockdowns and restrictions, nursing home residents were restrained from being physically active. In our study, we aimed to assess the impact of the COVID-19-related restrictions on PA promotion in nursing homes from an organizational-sociological lens. Methods: We collected data in eight nursing homes in Germany. Data collection included (i) semistructured interviews focusing on COVID-19-related restrictions and their effects on nursing homes from the home administrators' perspectives; (ii) open-ended surveys with nursing home staff and relatives focusing on daily routines and contact restrictions; and (iii) collection of documents such as care concepts, mission statements, and weekly activity plans. We analyzed all data with a reflexive thematic analysis approach. Results: We identified three stages of COVID-19-related changes in nursing homes that impacted PA promotion, as follows: (1) external closure and search for emergency control, (2) organizational adaptations to create a livable daily life in the internal environment, and (3) slow reintegration of interactions with the external organizational environment. Document analysis revealed that PA promotion was not part of decision programs or internal staff work descriptions. Rather, PA promotion was delegated to external service providers. The assignment of PA promotion to external providers was not structurally anchored in decision programs, which makes PA promotion not sustainable, particularly during unforeseen events that limit access to the organization. During the pandemic, executive staff believed in internal staff to buffer competencies with regard to PA promotion. Thus, executive staff often considered PA promotion relevant, even during the pandemic, but thought that PA promotion is a task that can be fulfilled by unqualified but motivated internal staff. Conclusion: While our study participants showed a high level of coping-capacity belief, it remains unclear which long-term impacts of COVID-19 on PA promotion in nursing homes are to be expected. At the practice level, executive staff in nursing homes that aim to promote PA within their organization should become aware that PA promotion needs to be incorporated into organizational structures to be implemented and continued in challenging times such as in a pandemic.
If Beam Search Is the Answer, What Was the Question?

Quite surprisingly, exact maximum a posteriori (MAP) decoding of neural language generators frequently leads to low-quality results. Rather, most state-of-the-art results on language generation tasks are attained using beam search despite its overwhelmingly high search error rate. This implies that the MAP objective alone does not express the properties we desire in text, which merits the question: if beam search is the answer, what was the question? We frame beam search as the exact solution to a different decoding objective in order to gain insights into why high probability under a model alone may not indicate adequacy. We find that beam search enforces uniform information density in text, a property motivated by cognitive science. We suggest a set of decoding objectives that explicitly enforce this property and find that exact decoding with these objectives alleviates the problems encountered when decoding poorly calibrated language generation models. Additionally, we analyze the text produced using various decoding strategies and see that, in our neural machine translation experiments, the extent to which this property is adhered to strongly correlates with BLEU.
Embedding Words in Non-Vector Space with Unsupervised Graph Learning

It has become a de-facto standard to represent words as elements of a vector space (word2vec, GloVe). While this approach is convenient, it is unnatural for language: words form a graph with a latent hierarchical structure, and this structure has to be revealed and encoded by word embeddings. We introduce GraphGlove: unsupervised graph word representations which are learned end-to-end. In our setting, each word is a node in a weighted graph and the distance between words is the shortest path distance between the corresponding nodes. We adopt a recent method learning a representation of data in the form of a differentiable weighted graph and use it to modify the GloVe training algorithm. We show that our graph-based representations substantially outperform vector-based methods on word similarity and analogy tasks. Our analysis reveals that the structure of the learned graphs is hierarchical and similar to that of WordNet, the geometry is highly non-trivial and contains subgraphs with different local topology.
Iterative Domain-Repaired Back-Translation

In this paper, we focus on the domain-specific translation with low resources, where in-domain parallel corpora are scarce or nonexistent. One common and effective strategy for this case is exploiting in-domain monolingual data with the back-translation method. However, the synthetic parallel data is very noisy because they are generated by imperfect out-of-domain systems, resulting in the poor performance of domain adaptation. To address this issue, we propose a novel iterative domain-repaired back-translation framework, which introduces the Domain-Repair (DR) model to refine translations in synthetic bilingual data. To this end, we construct corresponding data for the DR model training by round-trip translating the monolingual sentences, and then design the unified training framework to optimize paired DR and NMT models jointly. Experiments on adapting NMT models between specific domains and from the general domain to specific domains demonstrate the effectiveness of our proposed approach, achieving 15.79 and 4.47 BLEU improvements on average over unadapted models and back-translation.
HIF-1α-Mediated, NADPH Oxidase-Derived ROS Contributes to Laryngeal Airway Hyperreactivity Induced by Intermittent Hypoxia in Rats

Obstructive sleep apnea, similar to intermittent hypoxia (IH) during sleep, is associated with laryngeal airway hyperreactivity (LAH). IH-induced laryngeal oxidative stress may contribute to LAH, but the underlying mechanism remains unknown. Conscious rats were subjected to repetitive 75 s cycles of IH for 7 or 14 consecutive days. Reflex apneic responses to laryngeal provocations with chemical stimulants were measured to reflect laryngeal reflex reactivity. Compared with control rats, rats exposed to IH for 14 days, but not for 7 days, displayed enhanced apneic response to laryngeal chemical stimulants. The apneic response to chemical stimulants, but not to mechanical stimulation, was totally abolished by perineural capsaicin treatment of superior laryngeal nerves (SLNs) or by the sectioning of the SLNs, suggesting that the reflex was mediated through capsaicin-sensitive SLNs. Daily intraperitoneal administration of N-acetyl-L-cysteine [NAC, a reactive oxygen species (ROS) scavenger], apocynin (an inhibitor of NADPH oxidase) or YC-1 (an inhibitor of HIF-1α), but not their vehicles, largely attenuated this augmented apneic response in 14 days IH rats. Laryngeal lipid peroxidation (an index of oxidative stress) was elevated in 7 days IH rats and 14 days IH rats, and was abolished by any of these three pharmacologic interventions. The protein expression of HIF-1α (an index of HIF-1 activation) and p47phox subunit in the membrane fraction (an index of NADPH oxidase activation) in the laryngeal tissues increased in 14 days IH rats; the former was reduced by NAC, whereas the latter was inhibited by YC-1. These results suggest that 14 days of IH exposure may sensitize capsaicin-sensitive SLNs and result in exaggerated apneic reflex response to laryngeal chemical stimulants. This phenomenon depends on the action of HIF-1α-mediated, NADPH oxidase-derived ROS.
Contact-Tracing-Apps als unterstützende Maßnahme bei der Kontaktpersonennachverfolgung von COVID-19

Zusammenfassung Die Kontaktpersonennachverfolgung ist derzeit eine der wirksamsten Maßnahmen zur Eindämmung der COVID-19 Pandemie. Digitales Contact Tracing mittels Smartphones scheint eine sinnvolle zusätzliche Maßnahme zur manuellen Kontaktpersonennachverfolgung zu sein, um Personen zu identifizieren, die nicht bekannt oder nicht erinnerlich sind und um den zeitlichen Verzug beim Melden eines Infektionsfalles und beim Benachrichtigen von Kontaktpersonen so gering wie möglich zu halten. Obwohl erste Modellierungsstudien eine positive Wirkung in Bezug auf eine zeitnahe Kontaktpersonennachverfolgung nahelegen, gibt es bislang keine empirisch belastbaren Daten, weder zum bevölkerungsweiten Nutzen noch zum potenziellen Schaden von Contact-Tracing-Apps. Die Beurteilung der Zweckerfüllung und eine wissenschaftliche interdisziplinäre Begleitforschung sowohl zur Wirksamkeit, Risiken und Nebenwirkungen als auch zu Implementierungsprozessen (z. B. Planung und Einbezug verschiedener Beteiligter) sind wesentliche Bestandteile einer Nutzen-Risiko Bewertung. Dieser Beitrag betrachtet daher den möglichen Public-Health-Nutzen sowie technische, soziale, rechtliche und ethische Aspekte einer Contact-Tracing-App zur Kontaktpersonennachverfolgung im Rahmen der COVID-19-Pandemie. Weiterhin werden Bedingungen für eine möglichst breite Nutzung der App aufgezeigt.
A Compact Patch-Based Representation for Technical Mesh Models

We present a compact and intuitive geometry representation for technical models initially given as triangle meshes. For CAD-like models the deﬁning features often coincide with the intersection between smooth surface patches. Our algorithm therefore ﬁrst segments the input model into patches of constant curvature. The intersections between these patches are encoded through Bézier curves of adaptive degree, the patches enclosed by them are encoded by their (constant) mean and Gaussian curvatures. This sparse geometry representation enables intuitive understanding and editing by manipulating either the patches’ curvature values and/or the feature curves. During decoding/reconstruction we exploit remeshing and hence are independent of the underlying triangulation, such that besides the feature curve topology no additional connectivity information has to be stored. We also enforce discrete developability for patches with vanishing Gaussian curvature in order to obtain straight ruling lines.
Effects of incidental physical activity on morphosyntactic processing in aging

Older adults have difficulties in sentence comprehension when working memory (WM) load increases (e.g., multiple embedded clauses). Structured physical activity has been related to improvements in cognition; however, incidental physical activity (PA, i.e., unstructured daily physical activities), particularly incidental vigorous activity has been poorly studied in relation to its effects on behavior. Furthermore, no positive effect on language has been reported in either form of physical activity. The aim of this study was to evaluate how two levels of PA (high or low) affect WM processing and how this, in turn, may affect morphosyntactic processing in older adults. Individuals with high PA (n = 18) had a higher WM load effect than those with low PA (n = 18), both behaviorally (greater differences between high and low WM loads in correct responses) and in terms of event-related potentials (only subjects with high PA showed LAN and P600b amplitude differences between high and low WM loads). These findings suggest that PA promotes cognitive strategies to face WM loads and morphosyntactic processing.
Myocardin-Related Transcription Factor A (MRTF-A) Regulates the Balance between Adipogenesis and Osteogenesis of Human Adipose Stem Cells

Previous studies have demonstrated that myocardin-related transcription factor A (MRTF-A) generates a link between the dynamics of the actin cytoskeleton and gene expression with its coregulator, serum response factor (SRF). MRTF-A has also been suggested as a regulator of stem cell differentiation. However, the role of MRTF-A in human mesenchymal stem cell differentiation remains understudied. We aimed to elucidate whether MRTF-A is a potential regulator of human adipose stem cell (hASC) differentiation towards adipogenic and osteogenic lineages. To study the role of MRTF-A activity in the differentiation process, hASCs were cultured in adipogenic and osteogenic media supplemented with inhibitor molecules CCG-1423 or CCG-100602 that have been shown to block the expression of MRTF-A/SRF-activated genes. Our results of image-based quantification of Oil Red O stained lipid droplets and perilipin 1 staining denote that MRTF-A inhibition enhanced the adipogenic differentiation. On the contrary, MRTF-A inhibition led to diminished activity of an early osteogenic marker alkaline phosphatase, and export of extracellular matrix (ECM) proteins collagen type I and osteopontin. Also, quantitative Alizarin Red staining representing ECM mineralization was significantly decreased under MRTF-A inhibition. Image-based analysis of Phalloidin staining revealed that MRTF-A inhibition reduced the F-actin formation and parallel orientation of the actin filaments. Additionally, MRTF-A inhibition affected the protein amounts of α-smooth muscle actin (α-SMA), myosin light chain (MLC), and phosphorylated MLC suggesting that MRTF-A would regulate differentiation through SRF activity. Our results strongly indicate that MRTF-A is an important regulator of the balance between osteogenesis and adipogenesis of hASCs through its role in mediating the cytoskeletal dynamics. These results provide MRTF-A as a new interesting target for guiding the stem cell differentiation in tissue engineering applications for regenerative medicine.
Evaluation of Wearable Sensor Devices in Parkinson's Disease: A Review of Current Status and Future Prospects

Parkinson's disease (PD) decreases the quality of life of the affected individuals. The incidence of PD is expected to increase given the growing aging population. Motor symptoms associated with PD render the patients unable to self-care and function properly. Given that several drugs have been developed to control motor symptoms, highly sensitive scales for clinical evaluation of drug efficacy are needed. Among such scales, the objective and continuous evaluation of wearable devices is increasingly utilized by clinicians and patients. Several electronic technologies have revolutionized the clinical monitoring of PD development, especially its motor symptoms. Here, we review and discuss the recent advances in the development of wearable devices for bradykinesia, tremor, gait, and myotonia. Our aim is to capture the experiences of patients and clinicians, as well as expand our understanding on the application of wearable technology. In so-doing, we lay the foundation for further research into the use of wearable technology in the management of PD.
Metagenomic analysis reveals distinct patterns of gut lactobacillus prevalence, abundance, and geographical variation in health and disease

ABSTRACT Lactobacilli are exploited extensively for food fermentation and biotechnology. Some food and gut isolates have been developed as probiotics, for which species that may be commensal to the human host are considered desirable. However, the robustness of defining original niches for lactobacilli – food, environment, the gut – is questionable, and culture-independent analyses of prevalence in different human populations is lacking. Here we analyzed the abundance of lactobacilli in 6,154 subjects from a database of highly curated fecal shotgun metagenomics data spanning 25 nationalities, with ages ranging from infancy to 102 years. Twenty-five species were detected, which we assigned into low, medium, and high prevalence groups. The microbiome of apparently healthy individuals could be categorized into 6 clusters or Lactobacillotypes (LbTypes), with three of the Lbtypes being dominated by L. delbrueckii, L. ruminis, L. casei, and the other three comprising a combination of different species. These Lactobacillus clusters exhibit distinct global abundance patterns. The cluster prevalences also display distinct age-specific trends influenced by geography, with overall lactobacillus prevalence increasing significantly with age in North America and Europe but declining with age in non-Westernized societies. Regression analysis stratified by regional location identified distinct associations of the Lactobacillotypes with age, BMI, and gender. Cirrhosis, fatty-liver, , IBD and T2D were characterized by net gain of lactobacilli, whereas hypertension patients harbored depleted lactobacillus levels. Collectively these data indicate that the species abundance of gut lactobacilli is moderated by geography, diet, and interaction with the whole microbiome, and has strong interactions with diseases associated with a western lifestyle.
PCR-based detection and serovar identification of Salmonella in retail meat collected from wet markets in Metro Manila, Philippines

This study aimed to detect Salmonella from retail meat collected from nine wet markets in Metro Manila, and identify the subtypes of Salmonella isolates using molecular serotyping assays from previously developed primers. Of the 720 collected meat samples, 57.64% were found to be Salmonella-contaminated. The most predominant serogroup was Salmonella O:3, and Salmonella serogroups O:4, O:6,7, O:8, O:9, and undetermined serogroups were also found. Most frequently detected isolates in bovine meat were S. 3:e,h:1,6 (putative identity: S. Anatum) and S: 4:e,h:1,2 (putative identity: S. Saintpaul), in porcine meat was S. 3:e,h:1,6 (putative identity: S. Anatum), and S. 8:i:z6 (putative identity: S. Kentucky) was common in poultry products. This study also demonstrated retail meat samples were contaminated with multiple Salmonella serogroups and serovars. This is the first Philippine study that utilized PCR-based assays to characterize Salmonella isolates down to a serovar level and provides baseline information regarding Salmonella prevalence and serovar distribution in retail meat. Molecular serotyping performed in this study can be used as an alternative approach to traditional serotyping in surveillance of Salmonella in the Philippines since the latter is expensive, time-consuming, and requires skilled technicians.