Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly variable basking shark (Cetorhinus maximus) diving behavior in the lower Bay of Fundy, Canada

Diving behavior in basking sharks, the largest obligate ram filter feeding planktivore, is highly dependent on their location. In the Bay of Fundy, where basking sharks congregate in the boreal summer and autumn, the sharks’ copepod prey are located deep in the water column, below 100 m, in dense but scattered patches. We used time-depth recorders to examine how the vertical movements of basking sharks adapt to such a prey field and captured 4,138 hours of diving behavior from 42 sharks in the boreal summer from 2008 to 2020. Using finite mixture models, we split the time series into surface and subsurface movement blocks and used dynamic time-warping to cluster subsurface movements into seven modes based on their shapes and lengths, with mostly V-shaped subsurface movements (85%) and a minority that were U-shaped (14%). Across sharks, five overall strategies of vertical movement behavior were identified. The strategies split broadly by the ratio of V-shaped movements to U-shaped movements in a deployment and whether the majority of subsurface movements were above or below 100 m. A majority of basking sharks (64%) were reverse diel vertical migrators but none altered their time-allocation across tidal periods. During more thermal stratification, sharks dove deeper, longer, and less frequently while during less thermal stratification sharks dove shallower, shorter, and more frequently. Overall, we show that basking sharks exhibit considerable inter- and intra-individual variability in their diving behavior, and therefore presumably also in foraging modes. Some of this variability relates to time of year and tidal phase, unsurprising in this highly tidally-driven system; however, the majority of the variability remains unexplained without more information on the distribution, composition, and abundance of the copepod prey field. The technique presented is extendable to other species and, unlike many dive classification techniques, requires few subjective delineations of diving behavior.
The development of the Chinese version of the Sports Emotional Intelligence Scale

Objective To revise and test the Chinese version of the Sports Emotional Intelligence Scale (SEIS) in sports situations. Materials and methods After pretesting 112 college students, 832 college students were formally tested, and item analysis, validity test, internal consistency reliability analysis, and calibration validity and equivalence test of the Chinese version of the SEIS were performed. The Chinese version of the SEIS had 14 items with four dimensions (evaluation of others’ emotions, self-emotional management, emotion use, and social skills), with a cumulative variance contribution of 57.812 percent; the four-factor measurement model fit well (χ2/df = 3.743, NFI = 0.917, GFI = 0.945, AFGI = 0.913, CFI = 0.926, and RMSEA = 0.062). The internal consistency coefficients (Cronbach’s α) of the Chinese version of the SEIS ranged from 0.824 to 0. 905, and the split-half reliability ranged from 0.807 to 0.891; the correlations between the total SEIS score and its dimensional scores and the calibration variables were significantly correlated (p < 0.05), ranging from 0.255 to 0.603. The gender measure equivalence test was valid, and the mean difference of potential variables across gender groups was not significant in the potential mean analysis. Conclusion The Chinese version of the SEIS has good reliability and validity, and it is appropriate for assessing emotional intelligence in sports situations.
Learning generalizable behaviors from demonstration

Generalizing prior experiences to complete new tasks is a challenging and unsolved problem in robotics. In this work, we explore a novel framework for control of complex systems called Primitive Imitation for Control (PICO). The approach combines ideas from imitation learning, task decomposition, and novel task sequencing to generalize from demonstrations to new behaviors. Demonstrations are automatically decomposed into existing or missing sub-behaviors which allows the framework to identify novel behaviors while not duplicating existing behaviors. Generalization to new tasks is achieved through dynamic blending of behavior primitives. We evaluated the approach using demonstrations from two different robotic platforms. The experimental results show that PICO is able to detect the presence of a novel behavior primitive and build the missing control policy.
Dynamic changes in metabolites of the kynurenine pathway in Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease: A systematic Review and meta-analysis

Background Tryptophan (TRP) is an essential amino acid that must be provided in the diet. The kynurenine pathway (KP) is the main route of TRP catabolism into nicotinamide adenosine dinucleotide (NAD+), and metabolites of this pathway may have protective or degenerative effects on the nervous system. Thus, the KP may be involved in neurodegenerative diseases. Objectives The purpose of this systematic review and meta-analysis is to assess the changes in KP metabolites such as TRP, kynurenine (KYN), kynurenic acid (KYNA), Anthranilic acid (AA), 3-hydroxykynurenine (3-HK), 5-Hydroxyindoleacetic acid (5-HIAA), and 3-Hydroxyanthranilic acid (3-HANA) in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD) patients compared to the control group. Methods We conducted a literature search using PubMed/Medline, Scopus, Google Scholar, Web of Science, and EMBASE electronic databases to find articles published up to 2022. Studies measuring TRP, KYN, KYNA, AA, 3-HK, 5-HIAA, 3-HANA in AD, PD, or HD patients and controls were identified. Standardized mean differences (SMDs) were used to determine the differences in the levels of the KP metabolites between the two groups. Results A total of 30 studies compromising 689 patients and 774 controls were included in our meta-analysis. Our results showed that the blood levels of TRP was significantly lower in the AD (SMD=-0.68, 95% CI=-0.97 to -0.40, p=0.000, I2 = 41.8%, k=8, n=382), PD (SMD=-0.77, 95% CI=-1.24 to -0.30, p=0.001, I2 = 74.9%, k=4, n=352), and HD (SMD=-0.90, 95% CI=-1.71 to -0.10, p=0.028, I2 = 91.0%, k=5, n=369) patients compared to the controls. Moreover, the CSF levels of 3-HK in AD patients (p=0.020) and the blood levels of KYN in HD patients (p=0.020) were lower compared with controls. Conclusion Overall, the findings of this meta-analysis support the hypothesis that the alterations in the KP may be involved in the pathogenesis of AD, PD, and HD. However, additional research is needed to show whether other KP metabolites also vary in AD, PD, and HD patients. So, the metabolites of KP can be used for better diagnosing these diseases.
Integrating machine learning to construct aberrant alternative splicing event related classifiers to predict prognosis and immunotherapy response in patients with hepatocellular carcinoma

Introduction: In hepatocellular carcinoma (HCC), alternative splicing (AS) is related to tumor invasion and progression. Methods: We used HCC data from a public database to identify AS subtypes by unsupervised clustering. Through feature analysis of different splicing subtypes and acquisition of the differential alternative splicing events (DASEs) combined with enrichment analysis, the differences in several subtypes were explored, cell function studies have also demonstrated that it plays an important role in HCC. Results: Finally, in keeping with the differences between these subtypes, DASEs identified survival-related AS times, and were used to construct risk proportional regression models. AS was found to be useful for the classification of HCC subtypes, which changed the activity of tumor-related pathways through differential splicing effects, affected the tumor microenvironment, and participated in immune reprogramming. Conclusion: In this study, we described the clinical and molecular characteristics providing a new approach for the personalized treatment of HCC patients.
Off-label and investigational drugs in the treatment of alcohol use disorder: A critical review

Compounds known to be successful in the treatment of alcohol use disorder include the aversive agent, Disulfiram, the glutamatergic NMDA receptor antagonist, Acamprosate, and the opioid receptor antagonists, Naltrexone and Nalmefene. Although all four are effective in maintaining abstinence or reduction of alcohol consumption, only a small percentage of patients receive pharmacological treatment. In addition, many other medications have been investigated for their therapeutic potential in the treatment of alcohol use disorder. In this review we summarize and compare Baclofen, Gabapentin, Topiramate, Ondansetron, Varenicline, Aripiprazole, Quetiapine, Clozapine, Antidepressants, Lithium, Neuropeptide Y, Neuropeptide S, Corticotropin-releasing factor antagonists, Oxytocin, PF-05190457, Memantine, Ifenprodil, Samidorphan, Ondelopran, ABT-436, SSR149415, Mifepristone, Ibudilast, Citicoline, Rimonabant, Surinabant, AM4113 and Gamma-hydroxybutyrate While some have shown promising results in the treatment of alcohol use disorder, others have disappointed and should be excluded from further investigation. Here we discuss the most promising results and highlight medications that deserve further preclinical or clinical study. Effective, patient-tailored treatment will require greater understanding provided by many more preclinical and clinical studies.
Functional characterization of a cell wall invertase inhibitor StInvInh1 revealed its involvement in potato microtuber size in vitro

Cell wall invertase (CWI) is as an essential coordinator in carbohydrate partitioning and sink strength determination, thereby playing key roles in plant development. Emerging evidence revealed that the subtle regulation of CWI activity considerably depends on the post-translational mechanism by their inhibitors (INHs). In our previous research, two putative INHs (StInvInh1 and StInvInh3) were expected as targets of CWI in potato (Solanum tubersum), a model species of tuberous plants. Here, transcript analysis revealed that StInvInh1 showed an overall higher expression than StInhInh3 in all tested organs. Then, StInvInh1 was further selected to study. In accordance with this, the activity of StInvInh1 promoter increased with the development of leaves in plantlets but decreased with the development of microtubers in vitro and mainly appeared in vascular bundle. The recombinant protein StInvInh1 displayed inhibitory activities on the extracted CWI in vitro and StInvInh1 interacted with a CWI StcwINV2 in vivo by bimolecular fluorescence complementation. Furthermore, silencing StInvInh1 in potato dramatically increased the CWI activity without changing activities of vacuolar and cytoplasmic invertase, indicating that StInvInh1 functions as a typical INH of CWI. Releasing CWI activity in StInvInh1 RNA interference transgenic potato led to improvements in potato microtuber size in coordination with higher accumulations of dry matter in vitro. Taken together, these findings demonstrate that StInvInh1 encodes an INH of CWI and regulates the microtuber development process through fine-tuning apoplastic sucrose metabolism, which may provide new insights into tuber development.
The potential of functionalized dressing releasing flavonoids facilitates scar-free healing

Scars are pathological marks left after an injury heals that inflict physical and psychological harm, especially the great threat to development and aesthetics posed by oral and maxillofacial scars. The differential expression of genes such as transforming growth factor-β, local adherent plaque kinase, and yes-related transcriptional regulators at infancy or the oral mucosa is thought to be the reason of scarless regenerative capacity after tissue defects. Currently, tissue engineering products for defect repair frequently overlook the management of postoperative scars, and inhibitors of important genes alone have negative consequences for the organism. Natural flavonoids have hemostatic, anti-inflammatory, antioxidant, and antibacterial properties, which promote wound healing and have anti-scar properties by interfering with the transmission of key signaling pathways involved in scar formation. The combination of flavonoid-rich drug dressings provides a platform for clinical translation of compounds that aid in drug disintegration, prolonged release, and targeted delivery. Therefore, we present a review of the mechanisms and effects of flavonoids in promoting scar-free regeneration and the application of flavonoid-laden dressings.
The role of product cues and regulatory focus in the consumers’ response to green products: The mediation effects of green attitudes

By applying the cue-diagnosticity theory, this study explores the influence mechanism of consumption response to low-involvement products and high-involvement products, respectively. Specifically, the purpose of this study is to investigate how product clues (brand strength and retailer reputation) affect consumption responses to green products with different involvement and to examine regulatory focus as a moderator and green attitude as a mediator. The results of study 1 reveal that for low-involvement green products, the effect of the retailer reputation rather than brand strength on consumption response is mediated by a green attitude, and the regulatory focus plays a moderating role in this process. The results of study 2 show that for high-involvement green products, the effect of the brand strength rather than retailer reputation on consumption response is mediated by a green attitude; however, the regulatory focus does not play a moderating role in this process. Finally, the data aggregation verifies that people’s consumption response to green products strongly depends on the retailer reputation, brand strength, and green attitude, and there is a moderated mediation effect of regulatory focus on the indirect effect of retailer reputation (rather than brand strength) on consumption response via green attitude. As behavioral antecedents differ across the analyzed product types in forming consumer response, it is very important for policymakers and marketers to take note of the differences when designing marketing activities for green products.
Total marrow irradiation (TMI): Addressing an unmet need in hematopoietic cell transplantation - a single institution experience review

Purpose TMI utilizes IMRT to deliver organ sparing targeted radiotherapy in patients undergoing hematopoietic cell transplantation (HCT). TMI addresses an unmet need, specifically patients with refractory or relapsed (R/R) hematologic malignancies who have poor outcomes with standard HCT regimens and where attempts to improve outcomes by adding or dose escalating TBI are not possible due to increased toxicities. Over 500 patients have received TMI at this center. This review summarizes this experience including planning and delivery, clinical results, and future directions. Methods Patients were treated on prospective allogeneic HCT trials using helical tomographic or VMAT IMRT delivery. Target structures included the bone/marrow only (TMI), or the addition of lymph nodes, and spleen (total marrow and lymphoid irradiation, TMLI). Total dose ranged from 12 to 20 Gy at 1.5-2.0 Gy fractions twice daily. Results Trials demonstrate engraftment in all patients and a low incidence of radiation related toxicities and extramedullary relapses. In R/R acute leukemia TMLI 20 Gy, etoposide, and cyclophosphamide (Cy) results in a 1-year non-relapse mortality (NRM) rate of 6% and 2-year overall survival (OS) of 48%; TMLI 12 Gy added to fludarabine (flu) and melphalan (mel) in older patients (≥ 60 years old) results in a NRM rate of 33% comparable to flu/mel alone, and 5-year OS of 42%; and TMLI 20 Gy/flu/Cy and post-transplant Cy (PTCy) in haplo-identical HCT results in a 2-year NRM rate of 13% and 1-year OS of 83%. In AML in complete remission, TMLI 20 Gy and PTCy results in 2-year NRM, OS, and GVHD free/relapse-free survival (GRFS) rates of 0%, 86·7%, and 59.3%, respectively. Conclusion TMI/TMLI shows significant promise, low NRM rates, the ability to offer myeloablative radiation containing regimens to older patients, the ability to dose escalate, and response and survival rates that compare favorably to published results. Collaboration between radiation oncology and hematology is key to successful implementation. TMI/TMLI represents a paradigm shift from TBI towards novel strategies to integrate a safer and more effective target-specific radiation therapy into HCT conditioning beyond what is possible with TBI and will help expand and redefine the role of radiotherapy in HCT.
Open Domain Response Generation Guided by Retrieved Conversations

Open domain response generation is the task of creating a response given a user query in any topics/domain. Limited by context and reference information, responses generated by current systems are often “bland” or generic. In this paper, we combine a response generation model with a retrieval system that searches for relevant utterances and responses. The generation model has two main components: a keyword extraction module and a two-stage transformer. The keyword extraction module aims to extract two types of keywords in an unsupervised fashion from the retrieved results: (1) keywords in the query not found in the retrieved utterances (DiffKey), and (2) overlapping keywords among the retrieved responses (SimKey). Given these keywords, the two-stage transformer first decides where to insert the keywords in the response, and the second generates the full response given the location of the keywords. The keyword extraction module and the two-stage transformer are connected in a single network, and so our system is trained end-to-end. Experimental results on Cornell Movie-Dialog corpus, Douban and Weibo demonstrate that our model outperforms state-of-the-art systems in terms of ROUGE, relevance scores and human evaluation.
Tissue and Tumor Epithelium Classification using Fine-tuned Deep CNN Models

The field of Digital Pathology (DP) has become more interested in automated tissue phenotyping in recent years. Tissue phenotyping may be used to identify colorectal cancer (CRC) and distinguish various cancer types. The information needed to construct automated tissue phenotyping systems has been made available by the introduction of Whole Slide Images (WSIs). One of the typical pathological diagnosis duties for pathologists is the histopathological categorization of epithelial tumors. Artificial intelligence (AI) based computational pathology approaches would be extremely helpful in reducing the pathologists ever-increasing workloads, particularly in areas where access to pathological diagnosis services is limited. Investigating several deep learning models for categorizing the images of tumor epithelium from histology is the initial goal. The varying accuracy ratings that were achieved for the deep learning models on the same database demonstrated that additional elements like pre-processing, data augmentation, and transfer learning techniques might affect the models' capacity to attain better accuracy. The second goal of this publication is to reduce the time taken to classify the tissue and tumor Epithelium. The final goal is to examine and fine-tune the most recent models that have received little to no attention in earlier research. These models were checked by the histology Kather CRC image database's nine classifications (CRC-VAL-HE-7K, NCT-CRC-HE-100K). To identify and recommend the most cutting-edge models for each categorization, these models were contrasted with those from earlier research. The performance and the achievements of the proposed preprocessing workflow and fine-tuned Deep CNN models (Alexnet, GoogLeNet and Inceptionv3) are greater compared to the prevalent methods. Keywords—Colorectal cancer; deep learning; CNN; tumor epithelium; Alexnet; GoogLeNet; Inceptionv3
Mixed ab initio quantum mechanical and Monte Carlo calculations of secondary emission from SiO 2 nanoclusters

A mixed quantum mechanical and Monte Carlo method for calculating Auger spectra from nanoclusters is presented. The approach, based on a cluster method, consists of two steps. Ab initio quantum mechanical calculations are first performed to obtain accurate energy and probability distributions of the generated Auger electrons. In a second step, using the calculated line shape as electron source, the Monte Carlo method is used to simulate the effect of inelastic losses on the original Auger line shape. The resulting spectrum can be directly compared to 'as-acquired' experimental spectra, thus avoiding background subtraction or deconvolution procedures. As a case study, the O K-LL spectrum from solid SiO2 is considered. Spectra computed before or after the electron has traveled through the solid, i.e., unaffected or affected by extrinsic energy losses, are compared to the pertinent experimental spectra measured within our group. Both transition energies and relative intensities are well reproduced.
Title: Genomic demography of world’s ethnic groups and individual genomic 1 identity

: Categorizing extant humankinds based on common characteristics is a useful concept 18 in many fields for correlating the category or demography to the variety of biological, societal, 19 cultural, economic and other issues, but has many problems primarily because of the difficulties 20 of defining the common characteristics objectively and quantitatively . All current 21 categorizations, such as ethnicity, ancestry and race, are based on various selections and 22 combinations of subjectively- and/or qualitatively -defined characteristics, such as ancestral 23 lineage/location, cultural/societal norm, language, skin color and other phenotypes and traits 24 perceived by the members within or from outside of the categorized group. Yet, such 25 categorization has been broadly used in many fields, including the fields of human genetics, health sciences and medical practices (e.g., 1,2,3 ), where the observed health characteristics are 27 objectively- and quantitatively-definable, but the population categorization is not. Here we 28 present a whole genome-based categorization that is objectively definable and quantitatively 29 measurable. We observe that: (a) the world’s ethnic populations form about 14 “genomic groups (b) each GG consists of multiple ethnic groups (EGs); and (c) at an individual level, approximately 99.8%, on average, of the whole genome contents are identical between any two individuals regardless of their GGs or EGs.