bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetics of hereditary forms of primary hyperparathyroidism
Authors: English Katherine A. , Lines Kate E. , Thakker Rajesh V.
Published: December 2023

Primary hyperparathyroidism (PHPT), a relatively common disorder characterized by hypercalcemia with raised or inappropriately normal serum parathyroid hormone (PTH) concentrations, may occur as part of a hereditary syndromic disorder or as a non-syndromic disease. The associated syndromic disorders include multiple endocrine neoplasia types 1–5 (MEN1-5) and hyperparathyroidism with jaw tumor (HPT-JT) syndromes, and the non-syndromic forms include familial hypocalciuric hypercalcemia types 1–3 (FHH1-3), familial isolated hyperparathyroidism (FIHP), and neonatal severe hyperparathyroidism (NS-HPT). Such hereditary forms may occur in > 10% of patients with PHPT, and their recognition is important for implementation of gene-specific screening protocols and investigations for other associated tumors. Syndromic PHPT tends to be multifocal and multiglandular with most patients requiring parathyroidectomy with the aim of limiting end-organ damage associated with hypercalcemia, particularly osteoporosis, nephrolithiasis, and renal failure. Some patients with non-syndromic PHPT may have mutations of the MEN1 gene or the calcium-sensing receptor (CASR), whose loss of function mutations usually cause FHH1, a disorder associated with mild hypercalcemia and may follow a benign clinical course. Measurement of the urinary calcium-to-creatinine ratio clearance (UCCR) may help to distinguish patients with FHH from those with PHPT, as the majority of FHH patients have low urinary calcium excretion (UCCR < 0.01). Once genetic testing confirms a hereditary cause of PHPT, further genetic testing can be offered to the patients’ relatives and subsequent screening can be carried out in these affected family members, which prevents inappropriate testing in normal individuals.
The Justice Factory
Authors: Clements Richard
Published: December 2023

Spend time at the International Criminal Court, and you will hear the familiar language of anti-impunity. Spend longer, and you will encounter the less familiar language of management – efficiency, risk, and performance, and tools of strategic planning, audit, and performance appraisal. How have these two languages fused within the primary institution of global justice? This book explores that question through an historical and conceptually layered account of management's effects on the ICC's global justice project. It historicises management, forcing international lawyers to look at the sites of struggle – from the plantation to the United Nations – that have shaped the court's managerial present. It traces the court's macro, micro and meso scales of management, showing how such practices have fashioned a vision of global justice at organisational, professional, and argumentative levels. And it asks how those who care about global justice might engage with managerial justice at an institution animated by forms, reforms, and the promise of optimisation.
Deception aversion, communal norm violation and consumer responses to prosocial initiatives
Authors: Alempaki Despoina , Isoni Andrea , Read Daniel
Published: December 2023

Companies face increasing pressure to adopt social responsibility initiatives while simultaneously providing shareholder value. However, consumers may respond negatively to ‘win-win’ initiatives that benefit society while bringing financial gain to the corporation, producing a backlash effect. Previous researchers have attributed this backlash effect to the violation of a communal relationship norm that companies trigger in consumers when communicating their win-win initiatives. We propose the alternative hypothesis that the backlash derives from people's deception aversion. We find evidence supporting deception aversion in three preregistered studies showing that companies are evaluated negatively when their actions differ from those implied by their stated prosocial policy and not, as predicted by the communal norm violation hypothesis, when they merely earn a profit. Our results suggest that companies should not fear that earning a profit from prosocial activities will carry reputational risk, so long as they are transparent.
Shaping the future of tunneling with data and emerging technologies
Authors: Apoji Dayu , Sheil Brian , Soga Kenichi
Published: November 2023

The increase in global population and urbanization is presenting significant challenges to society: space is becoming increasingly scarce, demand is exceeding capacity for deteriorating infrastructure, transportation is fraught with congestion, and environmental impacts are accelerating. Underground space, and particularly tunnels, has a key role to play in tackling these challenges. However, the cost, risk, uncertainty, and complexity of the tunneling process have impeded its growth. In this paper, we envision several technological advancements that can potentially innovate and transform the mechanized tunneling industry, including artificial intelligence (AI), autonomous, and bio-inspired systems. The proliferation of AI may assist human engineers and operators in making informed decisions systematically and quantitatively based on massive real-time data during tunneling. Autonomous tunneling systems may enable precise and predictable tunneling operations with minimal human intervention and facilitate the construction of massive and large-scale underground infrastructure projects that were previously challenging or unfeasible using conventional methods. Bio-inspired systems may provide valuable references and strategies for more efficient tunneling design and construction concepts. While these technological advancements can offer great promise, they also face considerable challenges, such as improving accessibility to and shareability of tunneling data, developing robust, reliable, and explainable machine learning systems, as well as scaling the mechanics and ensuring the applicability of bio-inspired systems from the prototype level to real-world applications. Addressing these challenges is imperative to ensure the successful implementation of these innovations for future tunneling.
Make it or draw it? Investigating the communicative trade-offs between sketches and prototypes
Authors: Krishnakumar Sandeep , Letting Cynthia , Johnson Erin , Soria Zurita Nicolas F. , Menold Jessica
Published: December 2023

Design representations play a crucial role in facilitating communication between individuals in design. Sketches and physical prototypes are frequently used to communicate design concepts in early-stage design. However, we lack an understanding of the communicative benefits each representation provides and how these benefits relate to the effort and resources required to create each representation. A mixed-methods study was conducted with 44 participants to identify whether sketches and physical prototypes led to different levels of cognitive load perceived by a communicator and listener and the characteristics that shape their cognitive load during communication. Results showed that listeners perceived higher levels of mental and physical demands when understanding ideas as low-fidelity physical prototypes, as compared to sketches. No significant differences were found in the cognitive load levels of communicators between the two conditions. Qualitative analyses of post-task semi-structured interviews identified five themes relating to verbal explanations and visual representations that shape designers’ cognitive load when understanding and communicating ideas through design representations. Results indicate that designers should be aware of the specific objectives they seek to accomplish when selecting the design representation used to communicate. This work contributes to the knowledge base needed for designers to use design representations more effectively as tools for communication.
Archives of Military Courts in Colonial Congo: New Sources for the History of Violence and Agency in Central Africa
Authors: Henriet Benoît , Lauro Amandine , Juste Renaud
Published: November 2023

This article offers an overview of the recently rediscovered archives of the Conseils de Guerre—the military court—of colonial Congo (1885–1960). As a long-considered lost collection of court records encompassing seventy years of testimonies of colonial military crimes, these archives offer unparalleled insights on the complex relation between law, impunity, and armed violence in colonial Central Africa. The article first sheds light on the history of those records and on their ongoing digitization in the context of debates about the contested heritage of Belgian “displaced” colonial public archives. It then sketches out several promising avenues for academic research and public history projects that they could help document, notably on the controversial history of violence in the Belgian empire and on the multifaceted nature of African agency under colonial rule.
Guiding-centre orbit-following simulations of charge exchange loss of NBI ions with the finite Larmor radius effect
Authors: Xu Yingfeng , Wang Fuqiong , Li Yongliang , Zhong Fangchuan
Published: November 2023

Guiding-centre orbit-following simulations of the charge exchange (CX) loss of neutral beam injection (NBI) ions are presented. The finite Larmor radius (FLR) effect in the fast ion–neutral collision can be included in guiding-centre orbit-following simulations by using the gyroaverage method. It is proved that the neutralization probability of fast ions computed by using the gyroaverage method in the guiding-centre orbit simulation is roughly the same as that computed in the full-orbit simulation when the time step in the guiding-centre simulation is the order of the gyroperiod. The CX losses of NBI fast ions for two NBIs in the EAST tokamak have been simulated by the guiding-centre orbit-following code GYCAVA, and the FLR effect in the fast ion–neutral collision on CX losses has been numerically studied. The CX effect of the fast ion–neutral collision can significantly enhance NBI ion losses on EAST. The FLR effect in the fast ion–neutral collision can enhance the CX loss. Vertical asymmetry of localized heat loads induced by CX losses is found, which is related to the FLR effect of fast ions and the strong radial gradient of the neutral density near the plasma edge. Heat loads induced by CX losses are localized in the regions near the poloidal angle

$\theta =-60^\circ$

, because the likelihood of exchanging charge is the largest at gyrophase

$\xi ={\rm \pi}$

, and this leads to fast downwards moving neutrals. Fast ion loss fractions induced by CX increase with the neutral density increasing.
Environmental distribution of Echinococcus- and Taenia spp.-contaminated dog feces in Kyrgyzstan
Authors: Abdykerimov Kubanychbek K. , Kronenberg Philipp A. , Isaev Myktybek , Paternoster Giulia , Deplazes Peter , Torgerson Paul R.
Published: November 2023

Recently, there have been epidemics of human cystic echinococcosis (CE) and alveolar echinococcosis (AE) in Kyrgyzstan. This study investigated 2 districts for the presence of Echinococcus granulosus s.l. and Echinococcus multilocularis eggs; species identity was confirmed by polymerase chain reaction in dog feces and the level of environmental contamination with parasite eggs in 2017–2018 was also investigated. In the Alay district 5 villages with a high reported annual incidence of AE of 162 cases per 100 000 and 5 villages in the Kochkor district which had a much lower incidence of 21 cases per 100 000 were investigated. However, the proportion of dog feces containing E. granulosus s.l. eggs was ~4.2 and ~3.5% in Alay and Kochkor respectively. For E. multilocularis, the corresponding proportions were 2.8 and 3.2%. Environmental contamination of Echinococcus spp. eggs was estimated using the McMaster technique for fecal egg counts, weight and density of canine feces. The level of environmental contamination with E. multilocularis eggs was similar at 4.4 and 5.0 eggs per m2 in Alay and Kochkor respectively. The corresponding values for E. granulosus s.l. were 8.3 and 7.5 eggs per m2. There was no association between village or district level incidence of human AE or CE and the proportion of dog feces containing eggs of Echinococcus spp. or the level of environmental contamination. Increased contamination of taeniid eggs occured in the autumn, after the return of farmers with dogs from summer mountain pastures.
Childhood abuse v. neglect and risk for major psychiatric disorders
Authors: Alkema Anne , Marchi Mattia , van der Zaag Jeroen A. J. , van der Sluis Daniëlle , Warrier Varun ,   Genetic Risk and Outcome of Psychosis (GROUP) Investigators, Ophoff Roel A. , Kahn René S. , Cahn Wiepke , Hovens Jacqueline G. F. M. , Riese Harriëtte , Scheepers Floortje , Penninx Brenda W. J. H. , Cecil Charlotte , Oldehinkel Albertine J. , Vinkers Christiaan H. , Boks Marco P. M.
Published: November 2023

Background

Childhood maltreatment (CM) is a strong risk factor for psychiatric disorders but serves in its current definitions as an umbrella for various fundamentally different childhood experiences. As first step toward a more refined analysis of the impact of CM, our objective is to revisit the relation of abuse and neglect, major subtypes of CM, with symptoms across disorders.

Methods

Three longitudinal studies of major depressive disorder (MDD, N = 1240), bipolar disorder (BD, N = 1339), and schizophrenia (SCZ, N = 577), each including controls (N = 881), were analyzed. Multivariate regression models were used to examine the relation between exposure to abuse, neglect, or their combination to the odds for MDD, BD, SCZ, and symptoms across disorders. Bidirectional Mendelian randomization (MR) was used to probe causality, using genetic instruments of abuse and neglect derived from UK Biobank data (N = 143 473).

Results

Abuse was the stronger risk factor for SCZ (OR 3.51, 95% CI 2.17–5.67) and neglect for BD (OR 2.69, 95% CI 2.09–3.46). Combined CM was related to increased risk exceeding additive effects of abuse and neglect for MDD (RERI = 1.4) and BD (RERI = 1.1). Across disorders, abuse was associated with hallucinations (OR 2.16, 95% CI 1.55–3.01) and suicide attempts (OR 2.16, 95% CI 1.55–3.01) whereas neglect was associated with agitation (OR 1.24, 95% CI 1.02–1.51) and reduced need for sleep (OR 1.64, 95% CI 1.08–2.48). MR analyses were consistent with a bidirectional causal effect of abuse with SCZ (IVWforward = 0.13, 95% CI 0.01–0.24).

Conclusions

Childhood abuse and neglect are associated with different risks to psychiatric symptoms and disorders. Unraveling the origin of these differences may advance understanding of disease etiology and ultimately facilitate development of improved personalized treatment strategies.
Childhood maltreatment and internalizing/externalizing disorders in trauma-exposed adolescents: Does posttraumatic stress disorder (PTSD) severity have a mediating role?
Authors: van den Heuvel Leigh Luella , Assim Ayesha , Koning Milo , Nöthling Jani , Seedat Soraya
Published: November 2023

Childhood maltreatment is associated with wide-ranging psychopathology at all stages of life. In the current study, we investigated whether posttraumatic stress disorder (PTSD) severity mediated the association between childhood maltreatment and internalizing and externalizing disorders among 262 South African trauma-exposed adolescents (aged 12–18 years). Childhood maltreatment and PTSD symptom severity were assessed using the Childhood Trauma Questionnaire and the Child PTSD Checklist, respectively. Psychiatric disorders were assessed utilizing the Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime version and were grouped into internalizing or externalizing disorders. Hierarchal logistic regression was used to assess the association of childhood maltreatment subtype with internalizing and externalizing disorders, controlling for age and gender, with PTSD symptom severity added to the final model. We found that sexual abuse was significantly associated with internalizing disorders, although this effect was no longer significant when PTSD was added to the model demonstrating that PTSD mediated the association between sexual abuse and internalizing disorders. Physical abuse, but not PTSD, was associated with externalizing disorders. Physical abuse, emotional neglect, and PTSD were associated with comorbid internalizing and externalizing disorders. These findings have implications for intervention and prevention strategies targeted at trauma-exposed adolescents with a history of childhood maltreatment.
Conceptual Dissonance in Peacebuilding Research: Lessons from a Somali Diaspora
Authors: Carver Stephanie , Zech Steven T. , Tohow Ahmed
Published: November 2023

Scholars recognize the important role that diasporas play in conflict dynamics, including efforts to build peace in conflict-affected communities. Broader academic research emphasizes a focus on local conditions and actors, as well as site-specific understandings of peace and peacebuilding practices. This focus on specific communities and contexts often draws on qualitative, narrative-driven data, predominantly collected through interviewing. This article identifies some of the core challenges related to data collection encountered during semi-structured interviews in a study of Somali diaspora members in Melbourne, Australia. We emphasize how issues associated with cross-cultural and gendered understandings of concepts related to peacebuilding can affect each stage of a research project, from the preliminary collection of data to the analysis and discussion of research implications. Specifically, we address challenges related to instances of conceptual dissonance that occur when researchers employ cross-cultural and gendered concepts—in this case, peace, peacebuilding, and leadership. The findings will benefit conflict researchers who work with socially distant groups and ethnically divided populations more broadly, along with those who employ interpretivist methodologies that focus on how meaning making might ultimately influence peacebuilding practices and outcomes.
Nocebo Hypothesis Cognitive Behavioural Therapy (NH-CBT) for non-epileptic seizures: a consecutive case series
Authors: Richardson Matt , Cathro Michael , Kleinstäuber Maria
Published: November 2023

Background:

Research has demonstrated that implementation of Nocebo Hypothesis Cognitive Behavioural Therapy (NH-CBT) achieved full symptom remission in 93% of people with Functional Neurological Symptoms Disorder (FNSD), most of them exhibiting motor symptoms. The basis for NH-CBT is consistent with a predictive coding aetiological model of FNSD. This idea is transparently shared with people with FNSD in the form of telling them that their symptoms are caused by a nocebo effect, usually followed by some physical activity that aims to change the person’s belief about their body.

Aims:

To demonstrate that a version of NH-CBT can also be effective in eliminating or reducing non-epileptic seizures (assumed to be a sub-type of FNSD).

Method:

A consecutive case series design was employed. Participants were treated with NH-CBT over a 12-week period. The primary outcome measure was seizure frequency. Numerous secondary measures were employed, as well as a brief qualitative interview to explore participants’ subjective experience of treatment.

Results:

Seven out of the 10 participants became seizure free at least 2 weeks before their post-treatment assessment, and all stayed seizure-free for at least 5 months. Six of those seven remained seizure free at 6-month follow-up. There were large positive effect sizes for the majority of secondary measures assessed.

Conclusions:

This case series provides evidence of feasibility and likely utility of NH-CBT in reducing the frequency of non-epileptic seizures.
Mass, Iteration, and Pejoration: On the Evolution of Iterative Adverbs from Indefinite Quantifiers in German Varieties
Authors: Ellsäßer Sophie
Published: November 2023

This article deals with the formal and functional development of aspectual adverbs from indefinite quantifiers in German. More specifically, it focuses on the functions of adverbs that prompted their development into different iterative markers. Through a corpus analysis of spoken language data, insights were gained into the semantic spectrum of the nonstandard adverb als ‘always’. This adverb can be classified as an iterative and, in certain contexts, as a habitual marker, which has undergone a similar development to the standard language adverb viel ‘much’. The article shows that lexical markers of iterativity and—to some extent—habituality may suggest new avenues for variation and change research. It traces the development of the habitual function of als and offers new perspectives for in-depth analyses of the evolution of lexical aspectuality marking.*
Prospective Aspect and Current Relevance: A Case Study of the German Prospective Stehen vor NP Light Verb Construction
Authors: Fleischhauer Jens
Published: November 2023

The paper presents a detailed corpus-based analysis of the German prospective stehen vor NP light verb construction. The starting point of the analysis is the claim that the construction is restricted to change-of-state nouns in the NP-internal position (Fleischhauer & Gamerschlag 2019, Fleischhauer et al. 2019). Based on corpus data, I demonstrate that although the construction shows a strong preference for such nouns, other semantic types of nouns (such as state nouns or process nouns) occur in the construction as well. I argue that process nouns in particular require contextual support to be licensed within the construction. In the paper, I present an analysis of the prospective light verb construction in terms of current relevance. This analysis accounts for the observed preference for change-of-state NP-internal nouns as well as for the need to provide contextual support for process nouns. The notion current relevance is frequently employed in the analysis of the perfect aspect; the current paper represents the first attempt to extend this notion to the prospective aspect.*
Cogs in Collective Action: The 2022 Skytte Lecture
Authors: Goodin Robert E.
Published: December 2023

Collective action can be motivated in many different ways. Here I point to a new and perhaps surprising one: by, in effect, telling people that the group is powerful and likely to achieve its goal, precisely because each of them is an inessential, interchangeable part in it. Given people’s desire to be part (even if a superfluous part) of a winning group, that can be a powerful motivator for people to join in a collective action.
Natural and Anthropogenic Climate Variability Signals in a 237‐Year‐Long Coral Record From the Philippines
Authors: Inoue M. , Fukushima A. , Chihara M. , Genda A. , Ikehara M. , Okai T. , Kawahata H. , Siringan F. P. , Suzuki A.
Published: November 2023

Both proxy and model studies conducted to understand anthropogenic warming have revealed historical variations in sea‐surface temperature (SST) since the industrial revolution. However, because of discrepancies between observations and models in the late nineteenth century, the timing and degree of anthropogenic warming remain unclear. In this study, we reconstructed a 237‐year‐long record of SST and salinity using a coral core collected from Bicol, southern Luzon, Philippines, which is located at the northern edge of the western Pacific warm pool. The SST record showed volcanic cooling after several volcanic eruptions, including the 1815 Tambora eruption, but the pattern of change differed. Decadal SST variations at Bicol are connected to Pacific Decadal Variability (PDV). Therefore, it is suggested that the PDV conditions at the time of the eruption may have influenced marine conditions, such as the degree and duration of cooling and/or salinity, after the eruptions. Although there were discrepancies in SST variations among the modeled, observed, and proxy SST data from the late nineteenth to early twentieth centuries, SST data from the late twentieth century showed globally coherent anthropogenic warming, especially after 1976. In particular, summer SST in the northwestern Pacific has become more sensitive to anthropogenic forcing since 1976.
A Novel Method to Determine Probabilistic Tsunami Hazard Using a Physics‐Based Synthetic Earthquake Catalog: A New Zealand Case Study
Authors: Hughes Laura , Power William , Lane Emily M. , Savage Martha K. , Arnold Richard , Howell Andrew , Shaw Bruce , Fry Bill , Nicol Andrew
Published: November 2023

Tsunamis can have devastating consequences for coastal communities. Yet hazards from future tsunamis are difficult to quantify due to their rarity in the instrumental record. Statistical earthquake catalogs have previously been used to quantify tsunami hazards. For the first time, we use a physics‐based synthetic earthquake catalog to assess probabilistic tsunami hazard in a local region. We analyze a 30,000‐year catalog to capture a wide range of the source complexity evident in tsunamigenic earthquakes. We produce models of land‐surface displacements and subsequent tsunamis from 2,585 earthquakes with magnitude > MW 7.0. Modeled slip of the Hikurangi and Tonga‐Kermadec subduction thrusts generated maximum wave heights at the coast of up to 28 m and these earthquakes pose the greatest tsunami hazard along New Zealand's coastline. The results provide a “proof of concept” for using earthquake simulators for probabilistic tsunami hazard models. They further present a platform upon which next‐generation probabilistic tsunami inundation models may be constructed.
Associative pyridinium electrolytes for air-tolerant redox flow batteries
Authors: Carrington Mark E. , Sokołowski Kamil , Jónsson Erlendur , Zhao Evan Wenbo , Graf Anton M. , Temprano Israel , McCune Jade A. , Grey Clare P. , Scherman Oren A.
Published: November 2023

Pyridinium electrolytes are promising candidates for flow-battery-based energy storage1–4. However, the mechanisms underlying both their charge–discharge processes and overall cycling stability remain poorly understood. Here we probe the redox behaviour of pyridinium electrolytes under representative flow battery conditions, offering insights into air tolerance of batteries containing these electrolytes while providing a universal physico-chemical descriptor of their reversibility. Leveraging a synthetic library of extended bispyridinium compounds, we track their performance over a wide range of potentials and identify the singlet–triplet free energy gap as a descriptor that successfully predicts the onset of previously unidentified capacity fade mechanisms. Using coupled operando nuclear magnetic resonance and electron paramagnetic resonance spectroscopies5,6, we explain the redox behaviour of these electrolytes and determine the presence of two distinct regimes (narrow and wide energy gaps) of electrochemical performance. In both regimes, we tie capacity fade to the formation of free radical species, and further show that π-dimerization plays a decisive role in suppressing reactivity between these radicals and trace impurities such as dissolved oxygen. Our findings stand in direct contrast to prevailing views surrounding the role of π-dimers in redox flow batteries1,4,7–11 and enable us to efficiently mitigate capacity fade from oxygen even on prolonged (days) exposure to air. These insights pave the way to new electrolyte systems, in which reactivity of reduced species is controlled by their propensity for intra- and intermolecular pairing of free radicals, enabling operation in air.
Scaling deep learning for materials discovery
Authors: Merchant Amil , Batzner Simon , Schoenholz Samuel S. , Aykol Muratahan , Cheon Gowoon , Cubuk Ekin Dogus
Published: November 2023

Novel functional materials enable fundamental breakthroughs across technological applications from clean energy to information processing1–11. From microchips to batteries and photovoltaics, discovery of inorganic crystals has been bottlenecked by expensive trial-and-error approaches. Concurrently, deep-learning models for language, vision and biology have showcased emergent predictive capabilities with increasing data and computation12–14. Here we show that graph networks trained at scale can reach unprecedented levels of generalization, improving the efficiency of materials discovery by an order of magnitude. Building on 48,000 stable crystals identified in continuing studies15–17, improved efficiency enables the discovery of 2.2 million structures below the current convex hull, many of which escaped previous human chemical intuition. Our work represents an order-of-magnitude expansion in stable materials known to humanity. Stable discoveries that are on the final convex hull will be made available to screen for technological applications, as we demonstrate for layered materials and solid-electrolyte candidates. Of the stable structures, 736 have already been independently experimentally realized. The scale and diversity of hundreds of millions of first-principles calculations also unlock modelling capabilities for downstream applications, leading in particular to highly accurate and robust learned interatomic potentials that can be used in condensed-phase molecular-dynamics simulations and high-fidelity zero-shot prediction of ionic conductivity.
Human mobility networks reveal increased segregation in large cities
Authors: Nilforoshan Hamed , Looi Wenli , Pierson Emma , Villanueva Blanca , Fishman Nic , Chen Yiling , Sholar John , Redbird Beth , Grusky David , Leskovec Jure
Published: November 2023

A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1–6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city’s hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.
Cellular development and evolution of the mammalian cerebellum
Authors: Sepp Mari , Leiss Kevin , Murat Florent , Okonechnikov Konstantin , Joshi Piyush , Leushkin Evgeny , Spänig Lisa , Mbengue Noe , Schneider Céline , Schmidt Julia , Trost Nils , Schauer Maria , Khaitovich Philipp , Lisgo Steven , Palkovits Miklós , Giere Peter , Kutscher Lena M. , Anders Simon , Cardoso-Moreira Margarida , Sarropoulos Ioannis , Pfister Stefan M. , Kaessmann Henrik
Published: November 2023

The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programmes underlying the development of the cerebellum in mammals. In this study we generated single-nucleus RNA-sequencing data for around 400,000 cells to trace the development of the cerebellum from early neurogenesis to adulthood in human, mouse and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell-type generation, except for Purkinje cells, for which we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell-state markers and gene-expression trajectories across neuronal differentiation show that cerebellar cell-type-defining programmes have been overall preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell-type level. In sum, our study unveils shared and lineage-specific gene-expression programmes governing the development of cerebellar cells and expands our understanding of mammalian brain evolution.
A megastudy on the predictability of personal information from facial images: Disentangling demographic and non-demographic signals
Authors: Tkachenko Yegor , Jedidi Kamel
Published: November 2023

While prior research has shown that facial images signal personal information, publications in this field tend to assess the predictability of a single variable or a small set of variables at a time, which is problematic. Reported prediction quality is hard to compare and generalize across studies due to different study conditions. Another issue is selection bias: researchers may choose to study variables intuitively expected to be predictable and underreport unpredictable variables (the ‘file drawer’ problem). Policy makers thus have an incomplete picture for a risk-benefit analysis of facial analysis technology. To address these limitations, we perform a megastudy—a survey-based study that reports the predictability of numerous personal attributes (349 binary variables) from 2646 distinct facial images of 969 individuals. Using deep learning, we find 82/349 personal attributes (23%) are predictable better than random from facial image pixels. Adding facial images substantially boosts prediction quality versus demographics-only benchmark model. Our unexpected finding of strong predictability of iPhone versus Galaxy preference variable shows how testing many hypotheses simultaneously can facilitate knowledge discovery. Our proposed L1-regularized image decomposition method and other techniques point to smartphone camera artifacts, BMI, skin properties, and facial hair as top candidate non-demographic signals in facial images.
Streamlining pipeline efficiency: a novel model-agnostic technique for accelerating conditional generative and virtual screening pipelines
Authors: Viswanathan Karthik , Goel Manan , Laghuvarapu Siddhartha , Varma Girish , Priyakumar U. Deva
Published: November 2023

The discovery of potential therapeutic agents for life-threatening diseases has become a significant problem. There is a requirement for fast and accurate methods to identify drug-like molecules that can be used as potential candidates for novel targets. Existing techniques like high-throughput screening and virtual screening are time-consuming and inefficient. Traditional molecule generation pipelines are more efficient than virtual screening but use time-consuming docking software. Such docking functions can be emulated using Machine Learning models with comparable accuracy and faster execution times. However, we find that when pre-trained machine learning models are employed in generative pipelines as oracles, they suffer from model degradation in areas where data is scarce. In this study, we propose an active learning-based model that can be added as a supplement to enhanced molecule generation architectures. The proposed method uses uncertainty sampling on the molecules created by the generator model and dynamically learns as the generator samples molecules from different regions of the chemical space. The proposed framework can generate molecules with high binding affinity with $$\sim$$
∼
a 70% improvement in runtime compared to the baseline model by labeling only $$\sim$$
∼
30% of molecules compared to the baseline oracle.
Harnessing deep learning to forecast local microclimate using global climate data
Authors: Zanchi Marco , Zapperi Stefano , La Porta Caterina A. M.
Published: November 2023

Microclimate is a complex non-linear phenomenon influenced by both global and local processes. Its understanding holds a pivotal role in the management of natural resources and the optimization of agricultural procedures. This phenomenon can be effectively monitored in local areas by employing models that integrate physical laws and data-driven algorithms relying on climate data and terrain conformation. Climate data can be acquired from nearby meteorological stations when available, but in their absence, global climate datasets describing 10 km-scale areas are often utilized. The present research introduces an innovative microclimate model that combines physical laws and deep learning to reproduce temperature and relative humidity variations at the meter-scale within a study area located in the Lombardian foothills. The model is exploited to perform a comparative study investigating whether employing the global climate dataset ERA5 as input reduces model’s accuracy in reproducing the microclimate variations compared to using data collected by the Lombardy Regional Environment Protection Agency (ARPA) from a nearby meteorological station. The comparative analysis shows that using local meteorological data as inputs provides more accurate results for microclimate modeling. However, in situations where local data is not available, the use of global climate data remains a viable and reliable approach.
The online language of work-personal conflict
Authors: Liou Gloria , Mittal Juhi , Sehgal Neil K. R. , Tay Louis , Ungar Lyle , Guntuku Sharath Chandra
Published: November 2023

With the blurring of boundaries in this digital age, there is increasing concern around work-personal conflict. Assessing and tracking work-personal conflict is critical as it not only affects individual workers but is also a vital measure among broader well-being and economic indices. This inductive study examines the extent to which work-personal conflict corresponds to individuals’ language use on social media. We apply an open-vocabulary analysis to the posts of 2810 Facebook users who also completed a survey for an established work-personal conflict scale. It was found that the language-based model can predict personal-to-work conflict (r = 0.23) and work-to-personal conflict (r = 0.15) and provide important insights into such conflicts. Specifically, we found that high personal-to-work conflict was associated with netspeak and swearing, while low personal-to-work conflict was associated with language about work and positivity. We found that high work-to-personal conflict was associated with negative emotion and negative tone, while low work-to-personal conflict was associated with positive emotion and language about birthdays.
Quantum optical tomography based on time-resolved and mode-selective single-photon detection by femtosecond up-conversion
Authors: Namekata Naoto , Kobayashi Nobuaki , Nomura Kenya , Sako Tokuei , Takata Norio , Inoue Shuichiro
Published: November 2023

We developed an optical time-of-flight measurement system using a time-resolved and mode-selective up-conversion single-photon detector for acquiring tomographic images of a mouse brain. The probe and pump pulses were spectrally carved from a 100-femtosecond mode-locked fiber laser at 1556 nm using 4f systems, so that their center wavelengths were situated at either side of the phase matching band separated by 30 nm. We demonstrated a sensitivity of 111 dB which is comparable to that of shot-noise-limited optical coherence tomography and an axial resolution of 57 μm (a refractive index of 1.37) with 380 femtosecond probe and pump pulses whose average powers were 1.5 mW and 30 μW, respectively. The proposed technique will open a new way of non-contact and non-invasive three-dimensional structural imaging of biological specimens with ultraweak optical irradiation.
Synthesis of MWCNTs by chemical vapor deposition of methane using FeMo/MgO catalyst: role of hydrogen and kinetic study
Authors: Chotmunkhongsin Chawalkul , Ratchahat Sakhon , Chaiwat Weerawut , Charinpanitkul Tawatchai , Soottitantawat Apinan
Published: November 2023

This study aims to investigate the role of hydrogen on CNTs synthesis and kinetics of CNTs formation. The CNTs were synthesized by catalytic chemical vapor deposition of methane over FeMo/MgO catalyst. The experimental results revealed that hydrogen plays an important role in the structural changes of catalyst during the pre-reduction process. The catalyst structure fully transformed into metallic FeMo phases, resulting in an increased yield of 5 folds higher than those of the non-reduced catalyst. However, the slightly larger diameter and lower crystallinity ratio of CNTs was obtained. The hydrogen co-feeding during the synthesis can slightly increase the CNTs yield. After achieving the optimum amount of hydrogen addition, further increase in hydrogen would inhibit the methane decomposition, resulting in lower product yield. The hydrogenation of carbon to methane was proceeded in hydrogen co-feed process. However, the hydrogenation was non-selective to allotropes of carbon. Therefore, the addition of hydrogen would not benefit neither maintaining the catalyst stability nor improving the crystallinity of the CNT products. The kinetic model of CNTs formation, derived from the two types of active site of dissociative adsorption of methane, corresponded well to the experimental results. The rate of CNTs formation greatly increases with the partial pressure of methane but decreases when saturation is exceeded. The activation energy was found to be 13.22 kJ mol−1, showing the rate controlling step to be in the process of mass transfer.
Advancing diabetes prediction with a progressive self-transfer learning framework for discrete time series data
Authors: Lim Heeryung , Kim Gihyeon , Choi Jang-Hwan
Published: November 2023

Although diabetes mellitus is a complex and pervasive disease, most studies to date have focused on individual features, rather than considering the complexities of multivariate, multi-instance, and time-series data. In this study, we developed a novel diabetes prediction model that incorporates these complex data types. We applied advanced techniques of data imputation (bidirectional recurrent imputation for time series; BRITS) and feature selection (the least absolute shrinkage and selection operator; LASSO). Additionally, we utilized self-supervised algorithms and transfer learning to address the common issues with medical datasets, such as irregular data collection and sparsity. We also proposed a novel approach for discrete time-series data preprocessing, utilizing both shifting and rolling time windows and modifying time resolution. Our study evaluated the performance of a progressive self-transfer network for predicting diabetes, which demonstrated a significant improvement in metrics compared to non-progressive and single self-transfer prediction tasks, particularly in AUC, recall, and F1 score. These findings suggest that the proposed approach can mitigate accumulated errors and reflect temporal information, making it an effective tool for accurate diagnosis and disease management. In summary, our study highlights the importance of considering the complexities of multivariate, multi-instance, and time-series data in diabetes prediction.
Multi-domain and complex protein structure prediction using inter-domain interactions from deep learning
Authors: Xia Yuhao , Zhao Kailong , Liu Dong , Zhou Xiaogen , Zhang Guijun
Published: December 2023

Accurately capturing domain-domain interactions is key to understanding protein function and designing structure-based drugs. Although AlphaFold2 has made a breakthrough on single domain, it should be noted that the structure modeling for multi-domain protein and complex remains a challenge. In this study, we developed a multi-domain and complex structure assembly protocol, named DeepAssembly, based on domain segmentation and single domain modeling algorithms. Firstly, DeepAssembly uses a population-based evolutionary algorithm to assemble multi-domain proteins by inter-domain interactions inferred from a developed deep learning network. Secondly, protein complexes are assembled by means of domains rather than chains using DeepAssembly. Experimental results show that on 219 multi-domain proteins, the average inter-domain distance precision by DeepAssembly is 22.7% higher than that of AlphaFold2. Moreover, DeepAssembly improves accuracy by 13.1% for 164 multi-domain structures with low confidence deposited in AlphaFold database. We apply DeepAssembly for the prediction of 247 heterodimers. We find that DeepAssembly successfully predicts the interface (DockQ ≥ 0.23) for 32.4% of the dimers, suggesting a lighter way to assemble complex structures by treating domains as assembly units and using inter-domain interactions learned from monomer structures.
The expansion of land plants during the Late Devonian contributed to the marine mass extinction
Authors: Smart Matthew S. , Filippelli Gabriel , Gilhooly William P. , Ozaki Kazumi , Reinhard Christopher T. , Marshall John E. A. , Whiteside Jessica H.
Published: November 2023

The evolution and expansion of land plants brought about one of the most dramatic shifts in the history of the Earth system — the birth of modern soils — and likely stimulated massive changes in marine biogeochemistry and climate. Multiple marine extinctions characterized by widespread anoxia, including the Late Devonian mass extinction around 372 million years ago, may have been linked to terrestrial release of the nutrient phosphorus driven by newly-rooted landscapes. Here we use recently published Devonian lake records as variable inputs in an Earth system model of the coupled carbon-nitrogen-phosphorus-oxygen-sulfur biogeochemical cycles to evaluate whether recorded changes to phosphorus fluxes could sustain Devonian marine anoxia sufficient to drive mass extinction. Results show that globally scaled increases in riverine phosphorus export during the Late Devonian mass extinction could have generated widespread marine anoxia, as modeled perturbations in carbon isotope, temperature, oxygen, and carbon dioxide data are generally consistent with the geologic record. Similar results for large scale volcanism suggest the Late Devonian mass extinction was likely multifaceted with both land plants and volcanism as contributing factors.
A ratiometric fluorescence assay for the detection of DNA methylation based on an alkaline phosphatase triggered in situ fluorogenic reaction
Authors: Zhang Hongding , Su Yinhui , Zhao Jiamiao , Song Huixi , Zhou Xiaohong
Published: November 2023

An ALP triggered in situ fluorogenic reaction as a ratiometric fluorescent probe for the sensitive and accurate detection of DNA methylation.
Utilising the intrinsic fluorescence of pomalidomide for imaging applications
Authors: Brownsey Duncan K. , Gafuik Christopher J. , Kim Dae-Sun , O’Sullivan Leonie , Gorobets Evgueni , Krukowski Samuel , Turk Madison , Jenne Craig N. , Mahoney Douglas J. , Derksen Darren J.
Published: November 2023

The fluorescent properties of pomalidomide derivatives have been utilised to develop a high-throughput imaging method suitable for rapid screening of protein degrader candidates.
Covalent PROTAC design method based on a sulfonyl pyridone probe
Authors: Luo Qinhong , Wang Yaqi , Hou Zhanfeng , Liang Huiting , Tu Licheng , Xing Yun , Wan Chuan , Liu Jianbo , Wang Rui , Zhu Lizhi , Han Wei , Wu Jianlong , Lu Fei , Yin Feng , Li Zigang
Published: November 2023

Covalent proteolysis-targeting chimeras (PROTACs) offer enhanced selectivity, prolonged action, and increased efficacy against challenging target proteins.