Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the Relation between Structural and Spectral Properties of Light-Harvesting Complex II

Light-harvesting complex II (LHCII) is a pigment–protein complex present in higher plants and green algae. LHCII represents the main site of light absorption, and its role is to transfer the excitation energy toward the photosynthetic reaction centers, where primary energy conversion reactions take place. The optical properties of LHCII are known to depend on protein conformation. However, the relation between the structural and spectroscopic properties of the pigments is not fully understood yet. In this respect, previous classical molecular dynamics simulations of LHCII in a model membrane [Sci. Rep.2015, 5, 1–10] have shown that the configuration and excitonic coupling of a chlorophyll (Chl) dimer functioning as the main terminal emitter of the complex are particularly sensitive to conformational changes. Here, we use quantum chemistry calculations to investigate in greater detail the effect of pigment–pigment interactions on the excited-state landscape. While most previous studies have used a local picture in which electrons are localized on single pigments, here we achieve a more accurate description of the Chl dimer by adopting a supramolecular picture where time-dependent density functional theory is applied to the whole system at once. Our results show that specific dimer configurations characterized by shorter inter-pigment distances can result in a sizable intensity decrease (up to 36%) of the Chl absorption bands in the visible spectral region. Such a decrease can be predicted only when accounting for Chl–Chl charge-transfer excitations, which is possible using the above-mentioned supramolecular approach. The charge-transfer character of the excitations is quantified by two types of analyses: one focusing on the composition of the excitations and the other directly on the observable total absorption intensities.
The Mechanism of Macular Sparing.

Patients with homonymous hemianopia sometimes show preservation of the central visual fields, ranging up to 10°. This phenomenon, known as macular sparing, has sparked perpetual controversy. Two main theories have been offered to explain it. The first theory proposes a dual representation of the macula in each hemisphere. After loss of one occipital lobe, the back-up representation in the remaining occipital lobe is postulated to sustain ipsilateral central vision in the blind hemifield. This theory is supported by studies showing that some midline retinal ganglion cells project to the wrong hemisphere, presumably driving neurons in striate cortex that have ipsilateral receptive fields. However, more recent electrophysiological recordings and neuroimaging studies have cast doubt on this theory by showing only a minuscule ipsilateral field representation in early visual cortical areas. The second theory holds that macular sparing arises because the occipital pole, where the macula is represented, remains perfused after occlusion of the posterior cerebral artery because it receives collateral flow from the middle cerebral artery. An objection to this theory is that it cannot account for reports of macular sparing in patients after loss of an entire occipital lobe. On close scrutiny, such reports turn out to be erroneous, arising from inadequate control of fixation during visual field testing. Patients seem able to detect test stimuli on their blind side within the macula or along the vertical meridian because they make surveillance saccades. A purported treatment for hemianopia, called vision restoration therapy, is based on this error. The dual perfusion theory is supported by anatomical studies showing that the middle cerebral artery perfuses the occipital pole in many individuals. In patients with hemianopia from stroke, neuroimaging shows preservation of the occipital pole when macular sparing is present. The frontier dividing the infarcted territory of the posterior cerebral artery and the preserved territory of the middle cerebral artery is variable, but always falls within the representation of the macula, because the macula is so highly magnified. For physicians, macular sparing was an important neurological sign in acute hemianopia because it signified a posterior cerebral artery occlusion. Modern neuroimaging has supplanted the importance of that clinical sign but at the same time confirmed its validity. For patients, macular sparing remains important because it mitigates the impact of hemianopia and preserves the ability to read fluently. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Microwave Extract for Naphtha in Fruit of Cuminum cyminum

Objective:To extract and determine naphtha in fruit of Cuminum cyminum . Methods:To apply microwave extraction to determinating content of naphtha in fruit of Cuminum cyminum . Results:Reaction shortened 15 times, Naphtha content was 4.866 5%. Conclusion:Microwave technology was applied to extracting naphtha of Cuminum cyminum for the first time with more rapid reaction.
Gene‐disruption of the entomopathogenic fungus Beauveria bassiana incubated with dsRNA

The species of Beauveria bassiana is widely used for the management of agricultural insect pests. In this study, we integrated egfp‐double‐stranded RNA (dsRNA) to a previously generated egfp‐expressing B. bassiana transformant (Bb‐egfp#3) using a protoplast integration method. The Bb‐egfp#3 protoplast was mixed with the dsRNA under PEG/CaCl2 conditions and liquid‐cultured in Sabouraud dextrose broth for 5 days. A control culture followed the same procedure without dsRNA. Bb‐egfp#3/egfp‐dsRNA cultures showed very low fungal growth (OD630 = 0.2) compared to the control culture, Bb‐egfp#3 only (OD630 = 1.1). Screening of possible transformants on Sabouraud dextrose agar revealed a transformant T3, without egfp signal. T3 was confirmed as B. bassiana through sequencing of conserved genes and insect bioassays. Interestingly, the genomic egfp fragment of T3 was disrupted, and the egfp signal was not detected over four subcultures, which was also confirmed by RNA‐seq of Bb‐egfp#3 and T3. This study provides an interesting observation that protoplast integration with dsRNA could possibly generate significantly reduced gene expression in B. bassiana and it is stable across several generations.
Use of a Design of Experiments (DoE) Approach to Optimize Large-Scale Freeze-Thaw Process of Biologics

Large volumes of protein solutions are commonly stored in a frozen state before further drug product fill and finish. This study aimed to establish a design space to perform large-scale freeze-thaw (F/T) processes of biotherapeutics without inducing protein destabilization. A response surface model was designed to evaluate the following main factors and interactions: fill volume of the protein solution in 1-L containers, distance among nine containers during both F/T, freezer set temperature, and a novel forced air flow methodology during thawing. The analysis from 46 experimental runs indicated over 4-fold increase in the freezing rate by lowering the freezing temperature from −20 to −80°C, and the forced air flow at 98 fpm doubled the thawing rate. Furthermore, multivariate linear regression modeling revealed the significant impact of all main factors investigated on lactate dehydrogenase (LDH) quality attributes. The factor that most strongly affected the retention of LDH activity was the loading distance: ≥ 5 cm among containers positively affected the LDH activity response in 50.6%. The factor that most strongly retained the LDH tetramers was the set freezer temperature towards the lower range of −80°C (2.2% higher tetramer retention compared to −20°C freezing, due to faster freezing rate). In summary, this DoE-based systematic analysis increased F/T process understanding at large scale, identified critical F/T process parameters, and confirmed the feasibility of applying faster freezing and forced air thawing procedures to maintain the stability of LDH solutions subject to large-scale F/T.
Synergizing Functional Nanomaterials with Aptamers Based on Electrochemical Strategies for Pesticide Detection: Current Status and Perspectives

Abstract Owing to the high toxicity and large-scale use of pesticides, it is imperative to develop selective, sensitive, portable, and convenient sensors for rapid monitoring of pesticide. Therefore, the electrochemical detection platform offers a promising analytical approach since it is easy to operate, economical, efficient, and user-friendly. Meanwhile, with advances in functional nanomaterials and aptamer selection technologies, numerous sensitivity-enhancement techniques alongside a widespread range of smart nanomaterials have been merged to construct novel aptamer probes to use in the biosensing field. Hence, this study intends to highlight recent development and promising applications on the functional nanomaterials with aptamers for pesticides detection based on electrochemical strategies. We also reviewed the current novel aptamer-functionalized microdevices for the portability of pesticides sensors. Furthermore, the major challenges and future prospects in this field are also discussed to provide ideas for further research. Graphical Abstract
Geo-spatial-based Emotions: A Mechanism for Event Detection in Microblogs

The use of emotions in microblogs to trace the occurrence of certain events and determine their locations is an open challenge for sentiment analysis. This study investigated the potential of detecting the geographical location of events based on existing linkages between the types of emotion embedded in tweets (degree of polarity) and the source location of those tweets. The extracted tweets were clustered using K-means algorithm and a predictive model was developed using Naïve Bayes algorithm. Then, a time series forecasting technique was applied using linear regression analysis. This method was used to predict the amount of emotions in association with the event of interest. Latitude and longitude were used to evaluate the results of the linear regression model on a real-time world map. Results showed that happy emotion tends to be a reliable source for detecting the geographical location of an event. This study revealed the feasibility of using the time series forecasting approach in investigating the degree of emotions in twitter messages.
Laser-induced transient magnons in Sr3Ir2O7 throughout the Brillouin zone

Significance Ultrafast manipulation of magnetic states holds great promise for progress in our understanding of new quantum states and technical applications, but our current knowledge of transient magnetism is very limited. Our work elucidates the nature of transient magnetism in gapped antiferromagnets using Sr3Ir2O7 as a model material. We find that transient magnetic fluctuations are trapped throughout the entire Brillouin zone while remaining present beyond the time that is required to restore the original spin network. The results are interpreted in the context of a spin-bottleneck effect, in which the existence of an explicit magnetic decay channel allows for an efficient thermalization of transient spin waves. Although ultrafast manipulation of magnetism holds great promise for new physical phenomena and applications, targeting specific states is held back by our limited understanding of how magnetic correlations evolve on ultrafast timescales. Using ultrafast resonant inelastic X-ray scattering we demonstrate that femtosecond laser pulses can excite transient magnons at large wavevectors in gapped antiferromagnets and that they persist for several picoseconds, which is opposite to what is observed in nearly gapless magnets. Our work suggests that materials with isotropic magnetic interactions are preferred to achieve rapid manipulation of magnetism.
Switching Transferable Gradient Directions for Query-Efficient Black-Box Adversarial Attacks

We propose a simple and highly query-efficient black-box adversarial attack named SWITCH, which has a state-of-the-art performance in the score-based setting. SWITCH features a highly efficient and effective utilization of the gradient of a surrogate model $\hat{\mathbf{g}}$ w.r. t. the input image, i.e., the transferable gradient. In each iteration, SWITCH first tries to update the current sample along the direction of $\hat{\mathbf{g}}$, but considers switching to its opposite direction $-\hat{\mathbf{g}}$ if our algorithm detects that it does not increase the value of the attack objective function. We justify the choice of switching to the opposite direction by a local approximate linearity assumption. In SWITCH, only one or two queries are needed per iteration, but it is still effective due to the rich information provided by the transferable gradient, thereby resulting in unprecedented query efficiency. To improve the robustness of SWITCH, we further propose SWITCH$_\text{RGF}$ in which the update follows the direction of a random gradient-free (RGF) estimate when neither $\hat{\mathbf{g}}$ nor its opposite direction can increase the objective, while maintaining the advantage of SWITCH in terms of query efficiency. Experimental results conducted on CIFAR-10, CIFAR-100 and TinyImageNet show that compared with other methods, SWITCH achieves a satisfactory attack success rate using much fewer queries, and SWITCH$_\text{RGF}$ achieves the state-of-the-art attack success rate with fewer queries overall. Our approach can serve as a strong baseline for future black-box attacks because of its simplicity. The PyTorch source code is released on https://github.com/machanic/SWITCH.
Retrieval-Augmented Generation for Code Summarization via Hybrid GNN

Source code summarization aims to generate natural language summaries from structured code snippets for better understanding code functionalities. However, automatic code summarization is challenging due to the complexity of the source code and the language gap between the source code and natural language summaries. Most previous approaches either rely on retrieval-based (which can take advantage of similar examples seen from the retrieval database, but have low generalization performance) or generation-based methods (which have better generalization performance, but cannot take advantage of similar examples). This paper proposes a novel retrieval-augmented mechanism to combine the benefits of both worlds. Furthermore, to mitigate the limitation of Graph Neural Networks (GNNs) on capturing global graph structure information of source code, we propose a novel attention-based dynamic graph to complement the static graph representation of the source code, and design a hybrid message passing GNN for capturing both the local and global structural information. To evaluate the proposed approach, we release a new challenging benchmark, crawled from diversified large-scale open-source C projects (total 95k+ unique functions in the dataset). Our method achieves the state-of-the-art performance, improving existing methods by 1.42, 2.44 and 1.29 in terms of BLEU-4, ROUGE-L and METEOR.
Data Sharing Attitudes and Practices in the Plant Sciences: Results from a Mixed Method Study

ABSTRACT Data sharing attitudes and practices of the faculty of the plant sciences departments at the University of Minnesota-Twin Cities were explored in a mixed method study consisting of an online survey and semi-structured in-depth interviews. Results show the majority of participating faculty responded positively regarding data sharing and practice it in some form. However, several challenges exist, such as the time needed to prepare metadata, long-term storage and preservation, collaboration and communication with fellow researchers, and gaps in coding skill. Librarians are uniquely suited to help researchers face these challenges and support increased data sharing.
A Brief Dietary Screening and Counseling Tool for Health Educators

ABSTRACT Background: Diet quality assessment in community health settings is critical to reduce the incidence and improve management of diet-related chronic disease. Unfortunately, understandable and actionable brief dietary screening tools that empower individuals are nearly absent. Purpose: The purpose of this article is to describe two rigorous methodological approaches to validate and assess suitability of the Rapid Diet Quality Screener (RDQS). Methods: The first phase consisted of the content validation of a food consumption frequency questionnaire based on the Alternative Healthy Eating Index (AHEI). The second phase involved evaluating the design of the RDQS using the Suitability Assessment of Materials (SAM). Results: The RDQS and its food/beverage consumption frequency questions met established validity criteria consistent with the AHEI dietary metric components. The SAM evaluation was superior, thus elevating the RDQS from a one-way process of users assessing their diet quality to a two-way process allowing users to engage in behavior change that positively supports health and well-being. Translation to Health Education Practice: The RDQS enables health educators to quickly screen an individual’s diet quality to determine risk, guide brief counseling, and monitor progress with the populations they engage.
Assessing Use of Caloric Information on Restaurant Menus and Resulting Meal Selection in Saudi Arabia: Application of the Theory of Planned Behavior

ABSTRACT Background: Beginning in 2019, the Saudi Government required restaurants to post caloric information on menus to facilitate informed meal choices by Saudi consumers. Purpose: To assess the impact on consumer food choices, leveraging TPB, related to caloric information on menus among restaurants in Saudi Arabia. Methods: A cross-sectional study among adult Saudi consumers was conducted. Theoretically based on TPB, data were gathered on the use of caloric information on menus in restaurants across Riyadh. Results: Only 24.4% of participants utilized caloric information on menus to make a meal decision. Attitude (r = 0.65), and perceived behavioral control (r = 0.62) significantly correlated with intention. Multiple regression analysis showed that attitude (R 2 = 0.47, P = .05), and perceived behavioral control (R 2 = 0.11, P = .03) were significant predictors of using caloric information on menus for meal selection. Discussion: Among Saudi participants, the use of caloric information on menus was low in their meal decision. Interestingly, attitude was found to be a significant predictor of utilizing caloric information in making a meal decision. Translation to Health Education Practice: Consumer education should consider constructs of the TPB in intervention development and evaluation strategies to influence attitudes toward healthy eating behaviors and enhance the use of caloric information on restaurant menus in making informed meal decisions.
Who are the people? Using fandom research to study populist supporters

ABSTRACT This article suggests considering a social facet of populism, focusing on the supporters, to grasp how they use media to engage with the populist message and their understanding of it. The article proposes that a fan studies approach can be useful to examine how populist supporters’ identification with the imagined community of pure people can help them address specific social-psychological needs. A study applying this approach to the Spanish populist far-right provides evidence that a fan studies framework can help understand populist supporters’ community-building processes and benefits. Then, the article explains the implications for research on populism using this approach, offering a guide for future research. This work is relevant to multiple areas including political communication and cultural studies.
Sensorimotor Enhanced Neural Network for Metaphor Detection

Detecting metaphors is challenging due to the subtle ontological differences between metaphorical and non-metaphorical expressions. Neural networks have been widely adopted in metaphor detection and become the main stream technology. However, linguistic insights have been less utilized. This work proposes a linguistically enhanced model for metaphor detection extending one published work (WAN et al., 2020) by incorporating the modality norms into attention-based Bi-LSTM. Results show that the current model outperforms most recent works by 0.5%- 11% F1, indicating the effectiveness of us-ing modality norms for metaphor detection. This work provides a new perspective to detect token-level metaphoricity by leveraging the modality mismatch between words.
Enhancing Quality of Corpus Annotation: Construction of the Multi-Layer Corpus Annotation and Simplified Validation of the Corpus Annotation

In this paper, we construct simultaneously multi-layer corpus annotation of 7 linguistic layers as a gold set. And we design the validation procedure using the gold set and report the results of a validation procedure for other large-scale corpus annotation of 7 linguistic layers. Furthermore, we present a sim-pliﬁed validation method without a gold set using annotation models learned by the gold set. Based on the validation results, the tendency of annotation across the entire corpus is observed macroscopically, and the corpus annotation validation results are analyzed micro-scopically to verify the validation methodology to address the case study.
A Parallel Corpus-driven Approach to Bilingual Oenology Term Banks: How Culture Differences Influence Wine Tasting Terms

This paper describes the construction of an English-Chinese Parallel Corpus of wine reviews and elaborates on one of its applications – i.e. an E-C bilingual oenology term bank of wine tasting terms. The corpus is sourced from Decanter China, containing 1211 aligned wine reviews in both English and Chinese with 149,463 Chinese characters and 66,909 English words. It serves as a dataset for investigating crosslingual and cross-cultural differences in describing the sensory properties of wines. Our log-likelihood tests revealed good candidates for the Chinese translations of the English words in wine reviews. One of the most challenging features of this domain-specific bilingual term bank is the dominant many-to-many nature of term mapping. We focused on the one-to-many English-Chinese mapping relations of two major types: (a) the words without a single precise translation (e.g. “palate”) and (b) the words that are underspecified and involve ‘place-holder’ translation (e.g. “aroma”). Our study differs from previous bilingual CompuTerm studies by focusing on an area where cultural and sensory experiences favour many-to-many mappings instead of the default one-to-one mapping preferred in scientific and jurisprudential areas. This necessity for many-to-many mappings in turn challenges the basic design feature of many state-of-the-art automatic bilingual term-extraction approaches.
Understanding Transformers for Information Extraction with Limited Data

Transformers have recently achieved promising results in many natural language processing tasks; however, the understanding of transformers for information extraction in business scenarios is still an open question. This paper bridges the gap by introducing an investigation to understand the behavior of transformers in extracting information from domainspecific business documents. To do that, we employ transformers for taking advantage of these architectures trained on a huge amount of general data and fine-tune transformers to our down-stream IE task by using transfer learning. Experimental results on three Japanese datasets show that there are small margins among transformers in terms of Fscores but some models can achieve high accuracy with a small number of training data.