Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Space Imaging of the Ordered Small Molecule Orientations in Porous Frameworks by Electron Microscopy

The real-space imaging of small molecules is always challenging under the electron microscopes, but highly demanded for investigating various nanoscale interactions, such as hydrogen bond and van der Waals (vdW) force. Especially, identifying the host-guest interactions in porous materials directly at the molecular level will bring a deeper insight into the behaviors of guest molecules during the sorption, catalysis, gas separation and energy storage. In this work, we directly resolved the ordered configurations of p-xylenes (PXs) adsorbed in ZSM-5 frameworks by the scanning transmission electron microscopy (STEM) with the integrated differential phase contrast (iDPC) technique to identify the host-guest vdW interactions. Based on these observations, we revealed that the PXs in one straight channel modified the channel geometry with a coherent orientation. And the adjacent straight channels were deformed up to 8.8% along the different directions corresponding to three dominant PX configurations, resulting a negligible overall expansion of ZSM-5 lattices. Then, we could also image the disorder and desorption of PXs in ZSM-5 channels during the in situ heating. This work not only helped us to study the host-guest vdW interactions and the sorption behaviors of PXs in ZSM-5, but also provided an efficient tool for further imaging and studying other single-molecule behaviors under STEMs.
Hermes: A Fast, Fault-Tolerant and Linearizable Replication Protocol

Today's datacenter applications are underpinned by datastores that are responsible for providing availability, consistency, and performance. For high availability in the presence of failures, these datastores replicate data across several nodes. This is accomplished with the help of a reliable replication protocol that is responsible for maintaining the replicas strongly-consistent even when faults occur. Strong consistency is preferred to weaker consistency models that cannot guarantee an intuitive behavior for the clients. Furthermore, to accommodate high demand at real-time latencies, datastores must deliver high throughput and low latency. This work introduces Hermes, a broadcast-based reliable replication protocol for in-memory datastores that provides both high throughput and low latency by enabling local reads and fully-concurrent fast writes at all replicas. Hermes couples logical timestamps with cache-coherence-inspired invalidations to guarantee linearizability, avoid write serialization at a centralized ordering point, resolve write conflicts locally at each replica (hence ensuring that writes never abort) and provide fault-tolerance via replayable writes. Our implementation of Hermes over an RDMA-enabled reliable datastore with five replicas shows that Hermes consistently achieves higher throughput than state-of-the-art RDMA-based reliable protocols (ZAB and CRAQ) across all write ratios while also significantly reducing tail latency. At 5% writes, the tail latency of Hermes is 3.6X lower than that of CRAQ and ZAB.
The Effects of Gender Signals and Performance in Online Product Reviews

This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are prominently displayed next to products. Differences in reviews, perceived—consciously or unconsciously—with respect to gender signals, can lead to crucial biases in determining what content and perspectives are represented among top reviews. To investigate this, we extract signals of author gender from user names to select reviews where the author’s likely gender can be inferred. Using reviews authored by these gender-signaling authors, we train a deep learning classifier to quantify the gendered writing style (i.e., gendered performance) of reviews written by authors who do not send clear gender signals via their user name. We contrast the effects of gender signaling and performance on the review helpfulness ratings using matching experiments. This is aimed at understanding if an advantage is to be gained by (not) signaling one’s gender when posting reviews. While we find no general trend that gendered signals or performances influence overall review success, we find strong context-specific effects. For example, reviews in product categories such as Electronics or Computers are perceived as less helpful when authors signal that they are likely woman, but are received as more helpful in categories such as Beauty or Clothing. In addition to these interesting findings, we believe this general chain of tools could be deployed across various social media platforms.
The Energy Sources of Double-peaked Superluminous Supernova PS1-12cil and Luminous Supernova SN 2012aa

In this paper, we present the study of the energy reservoir powering the light curves (LCs) of PS1-12cil and SN 2012aa, which are superluminous and luminous supernovae (SNe), respectively. The multiband and bolometric LCs of these two SNe show unusual secondary bumps after the main peaks. The two-peaked LCs cannot be explained by any simple energy-source models (e.g., the 56Ni cascade decay model, the magnetar spindown model, or the ejecta-circumstellar medium interaction model). Therefore, we employ the 56Ni plus ejecta-circumstellar medium (CSM) interaction (CSI) model, the magnetar plus CSI model, and the double CSI model to fit their bolometric LCs, and find that both these two SNe can be explained by the double CSI model and the magnetar plus CSI model. Based on the modeling, we calculate the the time when the shells were expelled by the progenitors: provided that they were powered by double ejecta-shell CSI, the inner and outer shells might be expelled ∼0.2–3.6 and ∼2–25 yr before the explosions of the SNe, respectively; the shells were expelled ∼2–20 yr before the explosions of the SNe if they were powered by magnetars plus CSI.
Nonlinear Fourier Spectrum Characterization of Time-Limited Signals

Addressing the optical communication systems employing the nonlinear Fourier transform (NFT) for the data modulation/demodulation, we provide an explicit proof for the properties of the signals emerging in the so-called <inline-formula> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula>-modulation method, the nonlinear signal modulation technique that provides explicit control over the signal extent. We present details of the procedure and related rigorous mathematical proofs addressing the case where the time-domain profile corresponding to the <inline-formula> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula>-modulated data has a limited duration, and when the bound states corresponding to specifically chosen discrete solitonic eigenvalues and norming constants, are also present. We also prove that the number of solitary modes that we can embed without violating the exact localisation of the time-domain profile, is actually infinite. Our theoretical findings are illustrated with numerical examples, where simple example waveforms are used for the <inline-formula> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula>-coefficient, demonstrating the validity of the developed approach. We also demonstrate the influence of the bound states on the noise tolerance of the b-modulated system.
Herbicidal Properties of the Commercial Formulation of Methyl Cinnamate, a Natural Compound in the Invasive Silver Wattle (Acacia dealbata)

Abstract Plants that release molecules affecting other plants are a source of potential bioherbicides. Silver wattle (Acacia dealbata Link), considered invasive worldwide, was found to be phytotoxic to various other plant species. Combining the search for alternative bioherbicides while reducing the spread of this invader by preventing seed formation is a good potential strategy to solve both agricultural and environmental problems. This study aimed to identify nonvolatile compounds from A. dealbata flowers and explore their phytotoxicity on the germination process and seedling and plant growth of lettuce (Lactuca sativa L.), wheat (Triticum aestivum L.), and rigid ryegrass (Lolium rigidum Gaudin). We identified methyl cinnamate and methyl anisate as potential phytotoxins in the extracts, but we used pure commercial molecules to conduct bioassays. Methyl cinnamate showed higher phytotoxicity than methyl anisate and was selected for further bioassays. Methyl cinnamate reduced guaiacol peroxidase activity by 57% and 85% in L. rigidum and lettuce, respectively, and α-amylase by 6% in L. rigidum. This compound also inhibited early stem and radicle growth of dicotyledonous lettuce (60% and 89%, respectively) and monocotyledonous L. rigidum (76% and 87%, respectively), both species having small seeds. However, wheat with a larger seed size was not affected by the phytotoxin. The results obtained indicate a potential bioherbicidal effect for methyl cinnamate, and its application might be useful in wheat crops infested by L. rigidum. We suggest that collecting A. dealbata flowers would prevent Acacia seed formation and thus play a role in invasive pest management, as well as serving as a source of potential herbicides to other species.
Multiple Resistance to PPO and ALS Inhibitors in Redroot Pigweed (Amaranthus retroflexus)

Abstract A redroot pigweed (Amaranthus retroflexus L.) population (HN-02) collected from Nenjiang County, Heilongjiang Province, exhibited multiple resistance to fomesafen and nicosulfuron. The purposes of this study were to characterize the herbicide resistance status of an HN-02 population for both acetolactate synthase (ALS) and protoporphyrinogen oxidase (PPO) inhibitors and the response to other herbicides and to investigate the target site-based mechanism governing fomesafen and nicosulfuron resistance. Three mutations, Ala-205-Val and Trp-574-Leu mutations in the ALS gene and an Arg-128-Gly mutation in the PPX2 gene, were identified in individual resistant plants. An HN-02F1-1 subpopulation homozygous for the Ala-205-Val and Arg-128-Gly mutations was generated, and whole-plant experiments confirmed multiple resistance to PPO inhibitors (fomesafen, fluoroglycofen-ethyl, and acifluorfen) and ALS inhibitors (imidazolinones [IMI], sulfonylureas [SU], and triazolopyrimidines [TP]) in the HN-02F1-1 plants, which presented resistance index values ranging from 8.3 to 110; however, these plants were sensitive to flumioxazin, fluroxypyr-meptyl, and 2,4-D butylate. In vitro ALS enzyme activity assays revealed that, compared with ALS from susceptible plants, ALS from the HN-02F1-1 plants was 15-, 28- and 320-fold resistant to flumetsulam, nicosulfuron, and imazethapyr, respectively. This study confirms the first case of multiple resistance to PPO and ALS inhibitors in A. retroflexus and determines that the target-site resistance mechanism was produced by Ala-205-Val and Arg-128-Gly mutations in the ALS gene and PPX2 gene, respectively. In particular, the Ala-205-Val mutation was found to endow resistance to three classes of ALS inhibitors: TP, SU, and IMI.
Research Priorities for Achieving Healthy Marine Ecosystems and Human Communities in a Changing Climate

The health of coastal human communities and marine ecosystems are at risk from a host of anthropogenic stressors, in particular, climate change. Because ecological health and human well-being are inextricably connected, effective and positive responses to current risks require multidisciplinary solutions. Yet, the complexity of coupled social–ecological systems has left many potential solutions unidentified or insufficiently explored. The urgent need to achieve positive social and ecological outcomes across local and global scales necessitates rapid and targeted multidisciplinary research to identify solutions that have the greatest chance of promoting benefits for both people and nature. To address these challenges, we conducted a forecasting exercise with a diverse, multidisciplinary team to identify priority research questions needed to promote sustainable and just marine social–ecological systems now and into the future, within the context of climate change and population growth. In contrast to the traditional reactive cycle of science and management, we aimed to generate questions that focus on what we need to know, before we need to know it. Participants were presented with the question, “If we were managing oceans in 2050 and looking back, what research, primary or synthetic, would wish we had invested in today? ” We first identified major social and ecological events over the past 60 years that shaped current human relationships with coasts and oceans. We then used a modified Delphi approach to identify nine priority research areas and 46 questions focused on increasing sustainability and well-being in marine social–ecological systems. The research areas we identified include relationships between ecological and human health, access to resources, equity, governance, economics, resilience, and technology. Most questions require increased collaboration across traditionally distinct disciplines and sectors for successful study and implementation. By identifying these questions, we hope to facilitate the discourse, research, and policies needed to rapidly promote healthy marine ecosystems and the human communities that depend upon them.
Age-Related Alterations of White Matter Integrity in Adolescents and Young Adults With Bipolar Disorder

Background Alterations of white matter integrity during adolescence/young adulthood may contribute to the neurodevelopmental pathophysiology of bipolar disorder (BD), but it remains unknown how white matter integrity changes in BD patients during this critical period of brain development. In the present study, we aimed to identify possible age-associated alterations of white matter integrity in adolescents and young adults with BD across the age range of 13–30 years. Methods We divided the participants into two groups by age as follows: adolescent group involving individuals of 13–21 years old (39 patients with BD and 39 healthy controls) and young adult group involving individuals of 22–30 years old (47 patients with BD and 47 healthy controls). Diffusion tensor imaging (DTI) was performed in all participants to assess white matter integrity. Results In the adolescent group, compared to those of healthy controls, fractional anisotropy (FA) values were significantly lower in BD patients in the left inferior longitudinal fasciculus, splenium of the corpus callosum and posterior thalamic radiation. In the young adult group, BD patients showed significantly decreased FA values in the bilateral uncinate fasciculus, genu of the corpus callosum, right anterior limb of internal capsule and fornix compared to healthy controls. White matter impairments changed from the posterior brain to the anterior brain representing a back-to-front spatiotemporal directionality in an age-related pattern. Conclusions Our findings provide neuroimaging evidence supporting a back-to-front spatiotemporal directionality of the altered development of white matter integrity associated with age in BD patients during adolescence/young adulthood.
Capsule Networks Showed Excellent Performance in the Classification of hERG Blockers/Nonblockers

Capsule networks (CapsNets), a new class of deep neural network architectures proposed recently by Hinton et al., have shown a great performance in many fields, particularly in image recognition and natural language processing. However, CapsNets have not yet been applied to drug discovery-related studies. As the first attempt, we in this investigation adopted CapsNets to develop classification models of hERG blockers/nonblockers; drugs with hERG blockade activity are thought to have a potential risk of cardiotoxicity. Two capsule network architectures were established: convolution-capsule network (Conv-CapsNet) and restricted Boltzmann machine-capsule networks (RBM-CapsNet), in which convolution and a restricted Boltzmann machine (RBM) were used as feature extractors, respectively. Two prediction models of hERG blockers/nonblockers were then developed by Conv-CapsNet and RBM-CapsNet with the Doddareddy's training set composed of 2,389 compounds. The established models showed excellent performance in an independent test set comprising 255 compounds, with prediction accuracies of 91.8 and 92.2% for Conv-CapsNet and RBM-CapsNet models, respectively. Various comparisons were also made between our models and those developed by other machine learning methods including deep belief network (DBN), convolutional neural network (CNN), multilayer perceptron (MLP), support vector machine (SVM), k-nearest neighbors (kNN), logistic regression (LR), and LightGBM, and with different training sets. All the results showed that the models by Conv-CapsNet and RBM-CapsNet are among the best classification models. Overall, the excellent performance of capsule networks achieved in this investigation highlights their potential in drug discovery-related studies.
The Measurement of Eye Movements in Mild Traumatic Brain Injury: A Structured Review of an Emerging Area

Mild traumatic brain injury (mTBI), or concussion, occurs following a direct or indirect force to the head that causes a change in brain function. Many neurological signs and symptoms of mTBI can be subtle and transient, and some can persist beyond the usual recovery timeframe, such as balance, cognitive or sensory disturbance that may pre-dispose to further injury in the future. There is currently no accepted definition or diagnostic criteria for mTBI and therefore no single assessment has been developed or accepted as being able to identify those with an mTBI. Eye-movement assessment may be useful, as specific eye-movements and their metrics can be attributed to specific brain regions or functions, and eye-movement involves a multitude of brain regions. Recently, research has focused on quantitative eye-movement assessments using eye-tracking technology for diagnosis and monitoring symptoms of an mTBI. However, the approaches taken to objectively measure eye-movements varies with respect to instrumentation, protocols and recognition of factors that may influence results, such as cognitive function or basic visual function. This review aimed to examine previous work that has measured eye-movements within those with mTBI to inform the development of robust or standardized testing protocols. Medline/PubMed, CINAHL, PsychInfo and Scopus databases were searched. Twenty-two articles met inclusion/exclusion criteria and were reviewed, which examined saccades, smooth pursuits, fixations and nystagmus in mTBI compared to controls. Current methodologies for data collection, analysis and interpretation from eye-tracking technology in individuals following an mTBI are discussed. In brief, a wide range of eye-movement instruments and outcome measures were reported, but validity and reliability of devices and metrics were insufficiently reported across studies. Interpretation of outcomes was complicated by poor study reporting of demographics, mTBI-related features (e.g., time since injury), and few studies considered the influence that cognitive or visual functions may have on eye-movements. The reviewed evidence suggests that eye-movements are impaired in mTBI, but future research is required to accurately and robustly establish findings. Standardization and reporting of eye-movement instruments, data collection procedures, processing algorithms and analysis methods are required. Recommendations also include comprehensive reporting of demographics, mTBI-related features, and confounding variables.
An Active Data Representation of Videos for Automatic Scoring of Oral Presentation Delivery Skills and Feedback Generation

Public speaking is an important skill, the acquisition of which requires dedicated and time consuming training. In recent years, researchers have started to investigate automatic methods to support public speaking skills training. These methods include assessment of the trainee's oral presentation delivery skills which may be accomplished through automatic understanding and processing of social and behavioral cues displayed by the presenter. In this study, we propose an automatic scoring system for presentation delivery skills using a novel active data representation method to automatically rate segments of a full video presentation. While most approaches have employed a two step strategy consisting of detecting multiple events followed by classification, which involve the annotation of data for building the different event detectors and generating a data representation based on their output for classification, our method does not require event detectors. The proposed data representation is generated unsupervised using low-level audiovisual descriptors and self-organizing mapping and used for video classification. This representation is also used to analyse video segments within a full video presentation in terms of several characteristics of the presenter's performance. The audio representation provides the best prediction results for self-confidence and enthusiasm, posture and body language, structure and connection of ideas, and overall presentation delivery. The video data representation provides the best results for presentation of relevant information with good pronunciation, usage of language according to audience, and maintenance of adequate voice volume for the audience. The fusion of audio and video data provides the best results for eye contact. Applications of the method to provision of feedback to teachers and trainees are discussed.
Ultrastructural Changes Associated With the Enhanced Permeability of the Round Window Membrane Mediated by Ultrasound Microbubbles

The round window membrane (RWM) is the most common entryway for local drug and gene delivery into the inner ear, but its permeability can change the treatment outcome. We previously demonstrated a feasible and highly efficient approach using ultrasound-aided microbubble (USMB) cavitation to enhance the permeability of the RWM. Here, we investigated the safety of USMB exposure and the association between temporal changes in RWM permeability and ultrastructure. Experimental guinea pigs were divided into two treatment groups: a control group receiving round window soaking (RWS) with MBs and treatment (USM) groups undergoing 3 (USM-3) or 5 (USM-5) consecutive USMB exposures (1 min/exposure) at an acoustic intensity of 3 W/cm2 and 1 MHz frequency. The trans-RWM delivery efficiency of biotin-fluorescein isothiocyanate conjugates, used as permeability tracers, revealed a greater than 7-fold higher delivery efficiency for the USM groups immediately after 3 or 5 exposures than for the RWS group. After 24 h, the delivery efficiency was 2.4-fold higher for the USM-3 group but was 6.6-fold higher for the USM-5 group (and 3.7-fold higher after 48 h), when compared to the RWS group. Scanning electron microscopy images of the RWM ultrastructure revealed USMB-induced sonoporation effects that could include the formation of heterogeneous pore-like openings with perforation diameters from 100 nm to several micrometers, disruption of the continuity of the outer epithelial surface layer, and loss of microvilli. These ultrastructural features were associated with differential permeability changes that depended on the USMB exposure course. Fourteen days after treatment, the pore-like openings had significantly decreased in number and the epithelial defects were healed either by cell expansion or by repair by newly migrated epithelial cells. The auditory brainstem response recordings of the animals following the 5-exposure USMB treatment indicated no deterioration in the hearing thresholds at a 2-month follow-up and no significant hair cell damage or apoptosis, based on scanning electron microscopy, surface preparations, and TUNEL assays. USMBs therefore appear to be safe and effective for inner ear drug delivery. The mechanism of enhanced permeability may involve a disruption of the continuity of the outer RWM epithelial layer, which controls transmembrane transport of various substances.