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Pd(II)-Catalyzed Asymmetric [4 + 1] Annulation via Ligand Relay-Enabled Carbenylative Insertion/E1cB-Type Heck Cascade
Floating population diversity as a leading indicator of business turnover imbalance in commercial districts: A spatial panel analysis in Seoul
This study develops a quantitative indicator for the early diagnosis of commercial instability in business openings and closures and proposes a new analytical framework for assessing the stability of commercial districts. To address the limitations of prior research that relied on static measures such as sales or store counts, two complementary approaches were introduced. First, we propose the Commercial Instability Index (CII), a direction-agnostic metric of turnover instability computed from the standardized relative deviation between openings and closures, where larger values indicate greater instability. Second, entropy-based floating population diversity indicators were applied to capture the distribution of visitors by age, time of day, and day of week, as well as their temporal changes. These indicators were tested on quarterly panel data from 1,650 commercial districts in Seoul between the first quarter of 2019 and the fourth quarter of 2024 using panel regression and spatial panel regression models, specifically the spatial autoregressive (SAR) and spatial error model (SEM). The results showed that higher day-of-week diversity consistently reduced the CII, whereas a greater balance in age diversity provided partial mitigation effects. Moreover, the CII revealed significant spatial dependence, indicating that instability in one district could spread to its neighbors. By focusing on the magnitude of instability rather than its direction, and by integrating floating population diversity with spatial dependence, this study advances beyond static approaches. These findings expand the theoretical scope of commercial district research and offer a practical basis for early warning systems and area-based management strategies, thereby contributing to the development of urban policies for resilience and stability of commercial districts.
Controlling Reductive Elimination Pathways in Ti(IV) Pincer Complexes: Concerted versus Radical Mechanisms via Ligand Design
Circuit explained: How does a transformer perform compositional generalization
Compositional generalization—the systematic combination of known components into novel structures—is fundamental to flexible human cognition, yet the mechanisms that enable it in neural networks remain poorly understood in both machine learning and cognitive science. [1] showed that a compact encoder-decoder transformer can achieve simple forms of compositional generalization in a sequence arithmetic task. In this work, we identify and mechanistically interpret the circuit responsible for this behavior in such a model. Using causal ablations, we isolate the circuit and show that this understanding enables precise activation edits to steer the model’s outputs predictably. We find that the circuit performs function composition without encoding the specific semantics of any given function—instead, it leverages a disentangled representation of token position and identity to apply a general token remapping rule across an entire family of functions. Although the circuit mechanism was identified in a limited number of small scale models with a synthetic task, it sheds light to how symbolic compositionality can emerge in transformers and offer testable hypotheses for similar mechanisms in large-scale models. Code for model and analysis is publicly available .
Atlantic ocean currents defied the ice age
Proteome-Mining and Chemical Activation of Hidden Bioactive Fragments as Antimicrobial Assemblies
Effect of morphology on the biomechanics of contusion models of non-human primate spinal cord injury: a finite element study in a digital population
Traumatic spinal cord injuries (SCIs) stem from mechanical events that translate external forces through the spinal column, damaging the spinal cord. Since tissue damage is related to the strain/stress it experiences, finite element models are being increasingly used to supplement pre-clinical models of animal SCI. Simulations; however, are often conducted in a single geometry, while morphological variability has been highlighted as having an important influence on biomechanical outcomes. We developed tissue scale finite element models of non-human primate spinal cord injury with different morphologies (N = 40) to assess the effect of morphology on biomechanical outcomes. Applying the same displacement to different digital subjects generated different peak forces, and the magnitude of these forces was related to subject morphology, specifically the area of cerebrospinal fluid (CSF) and the occlusion of the spinal canal by the spinal cord (SCO/SC), particularly in the mediolateral direction (SCOW/SCW). Despite the same loading (0.75 N preload and 4-mm displacement at 500 mm/s), different subjects experienced a wide range of impact forces (13–33 N) due to morphological differences. In pre-clinical experiments, this variability could lead to drastically different outcomes, ranging from no functional deficits at the lower end (13 N) to unintended contralateral contusions at the higher end (33 N), despite the intent to induce unilateral injury. Peak forces were statistically correlated with white matter sparing, which affects observed functional outcomes. We showed that both tissue-level and impact biomechanics are significantly affected by morphology, emphasizing the need to include diversity and morphological variability into computational models of spinal cord injury. This highlights that either impact parameters need to be adjusted for morphological variability or that animals should be pre-screened for cord/column morphology, which can be prohibitively expensive. Future work is needed to determine how to scale these impact parameters for different morphologies.
AI could transform research assessment — and some academics are worried
Unraveling the mechanistic links between blood pressure regulation and calcium-magnesium homeostasis: Insights into hypertension, hyperparathyroidism, and mineral disorders
The systems regulating blood pressure and calcium-magnesium (Ca 2+ -Mg 2+ ) homeostasis are increasingly recognized to have clinically relevant interactions, where alterations in one can lead to significant changes in the other. In this study, we developed a computational model integrating blood pressure regulation and Ca 2+ -Mg 2+ homeostasis in a male rat. We simulated various conditions, including hypertension, Ca 2+ , Mg 2+ , and vitamin D 3 deficiencies, and primary hyperparathyroidism. Simulations of hypertension, induced by various stimuli like increased renin or aldosterone secretion, demonstrated significant effects on parathyroid hormone (PTH), calcitriol, renal Ca 2+ /Mg 2+ handling, and bone resorption. Dietary Ca 2+ , Mg 2+ , and vitamin D 3 deficiencies was predicted to elevate mean arterial pressure, with Mg 2+ deficiency having a stronger effect. Furthermore, the model predicted that primary hyperparathyroidism elevates PTH, Ca 2+ , and calcitriol, leading to increased mean arterial pressure and bone loss. Overall, this model provides valuable insights into the mechanistic links between blood pressure regulation and Ca 2+ -Mg 2+ homeostasis, offering insights into clinical conditions like hypertension and hyperparathyroidism.
Optimizing toward Discovery: AI-Driven Exploration of Lewis Acid–Base Catalysts for PET Glycolysis
Field evaluation of drone and AI assisted larval source management in Ghana
Background Malaria remains a major public health burden in sub-Saharan Africa. In Ghana, in particular, larval source management (LSM) is increasingly recognized as a complementary vector control strategy. This study evaluates a field-adapted LSM approach that integrates drone-based mapping and artificial intelligence (AI)–driven site prioritization to enhance operational efficiency and reduce resource use. Methods The intervention replaces conventional manual scouting with aerial mapping conducted one day prior to larvicide application. An AI model analyzes geospatial and morphological features of water bodies to identify high-risk larval habitats. Site coordinates are transmitted to field teams via mobile devices for targeted treatment. A comparative field trial was conducted in eight administrative sub-districts within Ghana’s Eastern Region. Four sub-districts implemented the drone- and AI-assisted approach, while four served as controls using standard LSM procedures. A mixed-methods evaluation was employed, incorporating quantitative metrics and qualitative field insights. Results Drone-assisted mapping led to more than a threefold increase in the number of identified breeding sites. AI-based targeting reduced larvicide consumption by over 60%. The combined technologies lowered worker requirements by approximately 50%. Despite these reductions, malaria case trends in the intervention sub-districts remained comparable to those in the control sub-districts. The study’s limitations include its restriction to the dry season and below-average rainfall, which may have influenced mosquito abundance and transmission. Conclusions Drone- and AI-assisted LSM demonstrated substantial resource savings without compromising vector control outcomes. Further longitudinal evaluation across transmission seasons is warranted to assess sustained effectiveness and inform national policy.
Direct B–H Activation of Carborane Clusters via Synergistic LMCT and HAT Photocatalysis
Knowledge, perception and attitude toward fibromyalgia among physical therapists in the United Arab Emirates: A cross-sectional study
Background Fibromyalgia (FM) is a chronic condition classified by widespread pain, fatigue, and associated symptoms. Patients with FM are frequently referred to physical therapists, whose knowledge of assessment criteria and management strategies is critical for timely recognition and effective care. Early diagnosis has been shown to improve outcomes, whereas delayed recognition often leads to prolonged suffering and increased healthcare costs. Aim The objective of this study was to examine the knowledge, perceptions, and attitudes of physical therapists in the United Arab Emirates (UAE) with respect to the diagnosis and management of FM. Methods A cross-sectional self-reported survey was distributed electronically to practicing physical therapists across the UAE. The survey collected demographic data, as well as information on confidence in determining and managing FM, awareness of international guidelines, perceptions of other healthcare providers roles, and knowledge of the risk factors. Results A total of 300 physical therapists were invited, and 240 completed the survey and met the inclusion criteria (response rate of 80%). The results revealed a predominantly female workforce, with 73.8% of participants identifying as female. The age of most respondents ranged between 23 and 42 years. Almost half of the participants had less than five years of experience. Nearly two-thirds of participants expressed confidence in diagnosing and managing FM cases. Most participants were unaware of any of the international FM practice guidelines (1990 ACR, 2010 ACR, 2012 Canadian). Conclusion The findings of this study underscore a concern for a lack of confidence and awareness among physical therapists in the UAE regarding the diagnosis and management of FM cases. Despite a significant proportion of participants reporting experience in managing FM cases, the majority were not familiar with recent FM practice guidelines, indicating potential gaps in knowledge and practice. This study highlights the importance of improving curricular integration of FM content, and greater dissemination of evidence-based guidelines. Addressing these gaps will be essential for promoting earlier diagnosis, reducing delays in management, and improving patient outcomes in the UAE.
Electron-Rich Subnanometer Cu Clusters Facilitate CO–CO Coupling in CO <sub>2</sub> Electroreduction
Assessment of antidiabetic, hepatoprotective, and analgesic effects of quinazolinone derivative, (E)-1-Benzoyl-3-((4- (Dimethylamino) Benzylidene) Amino)-2-(4-(Dimethylamino) Phenyl)-2,3 dihydroquinazoline-4(1h)-one, in diabetes induced mice model
Diabetes can cause serious complications such as liver damage and nerve pain. Unfortunately, existing treatment options for these problems often have limited effectiveness and unwanted side effects. To find better therapeutic alternatives with good efficacy and safety profile this study tested a novel quinazolinone derivative, (E)-1-benzoyl-3-((4(dimethylamino)benzylidene)amino)-2-(4-(dimethylamino)phenyl)-2,3 dihydroquinazoline-4(1H)-one , in diabetic mice’s experiencing liver damage and neuropathic pain. Diabetes was induced in mice using alloxan (150 mg/kg). For possible antidiabetic effect, test compound was given in doses of 10 mg/kg and 20 mg/kg. The standard drugs used for comparison was Glibenclamide (5 mg/kg), Tramadol (50 mg/kg) and Diclofenac sodium (50 mg/kg) for pain relief, and Gabapentin (75 mg/kg) for nerve pain. Pain relieving effect was assessed using various test models (e.g., hot plate, writhing, allodynia, and hyperalgesia). Liver function was studied through blood tests and tissue examination. The test compound (at test dose of 20 mg/kg) led to a significant reduction in blood glucose even greater than the reduction seen with glibenclamide (5 mg/kg). Similarly, the test compound significantly reduced pain and showed protective effects on the liver. This new quinazolinone compound was found to be safe and effective in reducing diabetic nerve pain and liver damage in mice. It may offer a better alternative to currently available treatments like gabapentin and glibenclamide.
Solution and Active Site Speciation Drive Selectivity for Electrocatalytic Reactive Carbon Capture in Diethanolamine over Ni–N–C Catalysts
Defining frailty using a modified Fried’s Frailty Phenotype in a Southern African context
Introduction Frailty leads to disability, morbidity, and mortality in older persons. The Fried’s Frailty Phenotype (FFP), derived in the American Cardiovascular Health Study (CHS), is widely used around the world to define frailty, but lacks adaptation in African populations. Objective To derive a modified FFP definition which best identifies frailty in a Southern African context. Methods A population-based cross-sectional study of adults aged ≥40 years collected data from questionnaires and physical assessments. Original CHS, population-dependent, European Working Group on Sarcopenia in Older People2 (EWGSOP2) and Sarcopenia Definitions and Outcomes Consortium (SDOC) and independent thresholds were all applied to the five FFP criteria (weight loss, exhaustion, low physical activity [PA], low grip strength [GS] and slow walking speed [WS]) to assess non-differentiality, internal consistency, and plausibility. Results The 919 participants had a median age of 59 years [IQR 50–70], 53.3% were female. Self-reported exhaustion was reported by 37.5%nd self-reported weight loss by 34.9%. Using the lowest quintile of body mass index (BMI), missed 15.2% of overweight and obese participants who reported weight loss. Using CHS thresholds, low PA was present in 36.7%. Grip strength correlated better with age (r = −0.45) than BMI (r = −0.19). Therefore, the sex-specific tenth percentile of the 40–49-years-age band of the study population was used rather than the CHS approach. The modified SDOC threshold identified slow WS in almost all (85.8%) and was therefore non-differential. The EWGSOP2 and CHS thresholds identified slow WS in 52.9% and 22.9%, respectively, compared to 34.5% using the study population’s lowest quintile. Conclusion Culture and language sensitive questions for self-reported exhaustion and weight loss, CHS thresholds for low PA, and population dependent thresholds for GS and WS were the most suitable modifications in a Southern African setting, highlighting the need for region-specific adaptations when diagnosing frailty.