Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Assessment of Industrial Classification Systems for Modeling Freight Production and Freight Trip Production

Freight demand models typically employ a priori classification systems for dividing establishments into hypothetically complementary groups with homogeneous patterns in freight production (FP) and freight trip production (FTP). Although an attractive and popular notion, the assumption of homogeneity within these a priori industrial classes is reductive in nature and is not yet tested in literature. This research examines this hypothesis and explores the possibility of a data-driven segmentation by examining the relationships between FP/FTP patterns and prevalent a priori classes; subsequently, it creates homogeneous ensembles of a posteriori segments through aggregation. This research labels, explains, and interprets these novel segments using commodity value density of industrial classes. The alternate segmentation schemes are compared in their ability to predict FP and FTP and it is found that: (i) industrial classification systems (NAICS, ISIC) perform significantly better than product classification systems (ASICC); (ii) a considerable portion of variability in FTP does not depend on employment predictor due to the underlying influence of shipment size; (iii) an a posteriori segmentation scheme considering shipment size may represent an effective middle ground for developing both FP and FTP models in freight demand model systems. Adoption of these novel segments of the freight travel market has the potential to reduce the sample size requirements of freight demand model systems and minimize the financial necessities for future freight surveys.
Statistical graphs in the training of teachers

The responses to four multiple-choice questions taken from delMas, Garfield and Ooms (2005) by 190 future Spanish teachers and 345 American college students are compared and then complemented with a qualitative analysis of the justifications given by a subsample of 44 Spanish teachers. Some conclusions for the training of teachers are presented.
Early-Summer Deficit Irrigation Increases the Dry-Matter Content and Enhances the Quality of Ambrosia™ Apples At- and Post-Harvest

Ambrosia™ is an apple that naturally has limited post-harvest quality retention, which is accompanied by relatively low dry-matter content (DMC). This trial was proposed to improve the DMC of this apple by scheduling deficit irrigation (DI) conducted in a semi-arid orchard in the Similkameen Valley (British Columbia, Canada) in 2018 and 2019. Two irrigation regimes were implemented in the orchard: commercial irrigation (CI) and DI, which was defined as irrigation for 2/5 of the timespan of CI. Five irrigation treatments were conducted: 1—adequate irrigation (AI), which used CI for the whole season; 2—early-summer DI (ED), which used DI from 20 June to 20 July; 3—middle-summer DI (MD), which used DI from 20 July to 20 August; 4—late-summer DI (LD), which used DI from 20 August to 10 days before harvest; and 5—double-period DI (DD), which covered the interval of MD and LD. The DI treatments resulted in a significant decrease from AI −1.0 to −1.5 MPa in stem water potential (SWP), followed by subsequent recovery. Conversely, SWP did not recover, and instead reached a critical low of −2.5 MPa under continued deficit conditions (DD). This, in turn, correlated with significant differences in the DMC among the treatments. Specifically, ED resulted in a rapid and sustained increase in DMC throughout the summer. At the time of harvest, ED resulted in a five-fold increase in the proportion of fruit, with greater than 16% DMC and 15% DMC in 2018 and 2019, respectively, compared to AI. DD resulted in similar levels of DMC elevation compared to ED, but also caused irregular maturation and the increased incidence of soft scald disorder in the post-harvest period. MD and LD had variable effects on DMC, and also increased the incidence of soft scald disorder. Consequently, fruit collected from the ED resulted in the best blush color attributes, higher soluble solid content, and a significant improvement in the post-harvest retention of both fruit firmness and acidity. The ED irrigation model would be recommended as a practical way for Ambrosia™ growers in semi-arid regions to decrease water usage, and to ensure high fruit quality for superior marketing and sustainable production.
Modulation of 1-ÃŸ-D-Arabinofuranosylcytosine Metabolism and Cytotoxicity in L1210 Cells by Fluoropyrimidine Pretreatment1

The effect of pretreatment with the fluoropyrimidines 5-fluo- rouracil (FUra), 5-fluorouridine (FUrd), 5-fluoro-2'-deoxyuri-dine (FdUrd), and 5'-deoxy-5-fluorouridine (5'-dFUrd) on the intracellular metabolism and in vitro cytotoxicity of 1-/S-D-ara-binofuranosylcytosine (ara-C) was explored in L1210 cells. A 4-hr exposure to 100 JUMFUra, FUrd, or FdUrd produced greater than 3-fold increments in the intracellular accumulation of [3H]deoxycytidine, and 2-fold increments in the intracellular accumulation of [3H]ara-C were produced over a 1-hr exposure. Intracellular 1-yS-o-arabinofuranosylcytosine S'-triphosphate levels in cells exposed to these 3 agents were also increased over 2-fold. L1210 cells exposed sequentially to 1 /Â¿MFUra, FUrd, or FdUrd followed by 5 U.Mara-C for 1 hr resulted in synergistic cell killing measured by soft-agar cloning. Although intracellular 2'-deoxycytidine 5'-triphosphate levels were re duced in cells treated for 4 hr with FUra and FUrd, this was not associated directly with the maximum accumulation of ara-C. treatment was as effective as FUra and FUrd at enhanc ing ara-C accumulation and 1-/J-o-arabinofuranosylcytosine 5'-triphosphate formation and producing synergistic cytotoxicity; however, the 2'-deoxycytidine 5'-triphosphate pools were min imally affected. 5'-Deoxy-5-fluorouridine did not increase intra cellular ara-C accumulation, reduce intracellular 2'-deoxycyti-dine S'-triphosphate levels, or enhance ara-C cytotoxicity. This sequential drug interaction is similar to that which we have observed when methotrexate precedes ara-C and provides a rational basis from which further in vivo studies can be de signed.
Morality extracted under crowding impairs face identification

We investigated whether morality associated with faces is perceptible even under less optimal visual conditions such as crowding. A facial image was paired with a sentence describing an immoral act or a neutral act. Participants imagined the person performing the actions described in the sentence during the learning phase. Then, in the crowding phase, the target face was briefly presented in the left or right peripheral visual fields. Participants were required to judge the gender or morality of the target face in Experiment 1 and to choose the target face from two faces in Experiment 2. In both experiments, flankers were presented around the target face in the flanker condition, whereas no flankers were presented in the no-flanker condition. Experiment 1 indicated that the accuracy of judgments about the morality of a crowded face was higher for immoral faces than for neutral faces. This demonstrates that morality is preferentially extracted even when conscious access to facial representations is limited. Experiment 2 showed that the accuracy of selecting the flanked face from two faces was higher for neutral faces than for immoral faces. These indicated that the morality processed under the crowding impaired the discrimination of the facial identity.
Adversarial-Network Regularized Inverse Design of Frequency-Selective Surface with Frequency-Temporal Deep Learning

In contrast to designing electromagnetic (EM) structures by tuning computationally expensive forward models, recent advancements in data-driven inverse-design approaches have potentials to transform the designs to more effective and intelligent ways. However, the fundamental challenges of the non-uniqueness in mapping from the demand space to geometry space and the difficulty in incorporation of fabrication constraints severely hinder the practical applications of these data-driven methods. To alleviate both challenges, we propose an adversarial-network regularized inverse design scheme with frequency-temporal deep learning method (AR-FTDL). A key feature of the proposed AR-FTDL is that it initially generates data distributions from the demand functional characteristics regularized by a generative adversarial network (GAN). Further, the inversion network utilizes both frequency and time a prior information of data space, which is followed by a pseudo-twin network to constrain geometry space satisfying fabrication requirements. The proposed method is numerically and experimentally verified by inversely designing passive/active EM absorbers with absorption-transmission-absorption functions. We believe that the proposed data-driven scheme can extend and improve the capabilities of the traditional intuition-driven or intense computation-driven design method.
Chronic Uptake of A Probiotic Nutritional Supplement (AB001) Inhibits Absorption of Ethylalcohol in the Intestine Tract – Results from a Randomized Double-blind Crossover Study

Background: Regular alcohol consumption, e.g. by social drinking, is a potential source of consecutive health problems in many countries worldwide. A probiotic nutritional supplement (AB001) has been developed to reduce alcohol absorption from the intestine tract and to mitigate potential health care risks. Methods: This randomized placebo-controlled double-blind crossover study was conducted with 24 healthy subjects (13 male, 11 female, age: 25.4 ± 7.7 years, BMI: 23.6 ± 2.5 kg/m²). The subjects were randomized to take 2 capsules/day of AB001 or placebo for 1 week prior to an alcohol exposure experiment. On the experimental day, they ingested a light breakfast and drank a moderate glass of spirit (0.3 g/kg body weight). Breath alcohol tests and blood draws for determination of blood alcohol levels were performed for up to 6 hours. After crossover, the experiment was repeated in the following week. Areas under the curves were calculated to determine alcohol absorption rates. Results: A significant reduction of blood alcohol levels by 70.3% (P < 0.005 vs. placebo) was seen with AB001, (breath test: −30.7%; P < 0.005 vs. placebo). No difference was seen in a cognitive function test performed 60 minutes after alcohol ingestion (22.4 ± 7.7 seconds vs. 22.7 ± 5.6 seconds, n.s.). There were no adverse events or serious adverse events reported in this study Conclusions: One week of supplementation with AB001 resulted in a substantially reduced absorption of alcohol into the body. Regular uptake of AB001 may help to prevent liver and other organ damage, and may reduce the negative medical and economical impact of social drinking on the individual and the society.
Optimization of Patient Flow and Process for a Primary Care Clinic During the COVID-19 Pandemic

Many patient throughput inefficiencies result from poor communication practices, inadequate understanding of optimizing healthcare systems to maximize efficiency, and longterm complications caused by the COVID-19 pandemic. The challenges precipitated by the pandemic, combined with the need to provide safe, high-quality care to patients, have further exacerbated existing patient flow and throughput issues. The overarching goal of this project is to improve the patient experience in primary care clinics and reduce the stress placed on providers, nurses, and staff. The authors implemented a two-phased approach that combined qualitative observations with quantitative data analysis, developed a robust methodology for understanding the University Physicians of Charlottesville (UPC) Clinic's processes, and produced structured insights for stakeholders. We established what components comprised a typical patient's journey through system intake through qualitative clinic observations: pre-registration, check-in, and rooming. In contrast to the qualitative observations, the quantitative analysis encompassed the complete patient experience, outs coping to include appointment durations and check-out. All quantitative analyses relied on data from the University of Virginia (UVA) Health's electronic medical record (EMR) system, Epic. In addition to the qualitative analyses, the authors utilized Cadence reports and appointment scheduling data to understand patient flow through the UPC Clinic. Primarily, the data are utilized to understand the distributions between the different patient flow milestones of registration, clinic check-in, rooming, and check-out and what factors, if any, were statistically significant. This approach enabled us to model the distribution of patient arrival times, wait times between arrival and rooming, and other relevant bottlenecks in the flow process.
Examining the Role of Perceived Classroom Goal Structures and Parents’ Goals in ESL/EFL Learners’ Achievement Goals, Engagement and Achievement

ABSTRACT This study examined the role of perceived classroom goal structures and parent’s goals in predicting students’ achievement goals, engagement and achievement. Mastery goals were predicted by both classroom and parents’ mastery goals. Both performance-approach goals and performance-avoidance goals were predicted by both classroom and parents’ performance goals. Mastery goals had positive impacts on academic engagement and achievement, but performance-avoidance goals had negative impacts. The impacts of performance-approach goals were not significant. Classroom and parents’ mastery goals had indirect positive effects on academic engagement and achievement through mastery goals. Parents’ performance goals had indirect negative effects through performance-avoidance goals.
Unveiling Chemical Cues of Insect-Tree and Insect-Insect Interactions for the Eucalyptus Weevil and Its Egg Parasitoid by Multidimensional Gas Chromatographic Methods

Multidimensional gas chromatography is, presently, an established and powerful analytical tool, due to higher resolving power than the classical 1D chromatographic approaches. Applied to multiple areas, it allows to isolate, detect and identify a larger number of compounds present in complex matrices, even in trace amounts. Research was conducted to determine which compounds, emitted by host plants of the eucalyptus weevil, Gonipterus platensis, might mediate host selection behavior. The identification of a pheromone blend of G. platensis is presented, revealing to be more attractive to weevils of both sexes, than the individual compounds. The volatile organic compounds (VOCs) were collected by headspace solid phase microextraction (HS-SPME), MonoTrapTM disks, and simultaneous distillation-extraction (SDE). Combining one dimensional (1D) and two-dimensional (2D) chromatographic systems—comprehensive and heart-cut two-dimensional gas chromatography (GC×GC and H/C-MD-GC, respectively) with mass spectrometry (MS) and electroantennographic (EAD) detection, enabled the selection and identification of pertinent semiochemicals which were detected by the insect antennal olfactory system. The behavioral effect of a selected blend of compounds was assessed in a two-arm olfactometer with ten parallel walking chambers, coupled to video tracking and data analysis software. An active blend, composed by cis and trans-verbenol, verbenene, myrtenol and trans-pinocarveol was achieved.
Liposomes Bearing Non-Bilayer Phospholipid Arrangements Induce Specific IgG Anti-Lipid Antibodies by Activating NK1.1+, CD4+ T Cells in Mice

Liposomes are artificial models of cellular membranes that are used as delivery systems for genes, drugs and protein antigens. We have previously used them to study the antigenic properties of their phospholipids. Here, we used them to induce the production of IgG anti-non-bilayer phospholipid arrangements (NPAs) antibodies in mice; these antibodies cause cell lysis and trigger a lupus-like disease in mice. We studied the mechanisms that lead to the production of these antibodies, and provide evidence that NK1.1+, CD4+ T cells respond to NPA-bearing liposomes and deliver the help required for specific B cell activation and antibody class-switching to IgG. We found increased numbers of IL-4-producing NK1.1+, CD4+ T cells in the secondary lymphoid organs of mice administered with NPAs, and these cells also expressed CD40L, which is required for B cell activation. Additionally, we isolated and purified NK1.1+, CD4+ T cells from spleens and determined that they over-expressed 40 genes, which are key players in inflammatory processes and B cell stimulation and have TRAF6 and UNC39B1 as key nodes in their network. These results show that liposomes are membrane models that can be used to analyze the immunogenicity of lipids.
Contextualizing social networks: The role of person–organization fit in the network–job performance relationship

While scholars have attended to the performance implications of employee embeddedness in social networks within the workplace, less research accounts for the interface of employee and organizational values in enabling employees to leverage these networks. Network perspectives on employee performance acknowledge that certain informal network positions create resources that are beneficial for performance while simultaneously creating demands that may diminish or erode these benefits. Leveraging a Job Demands-Resources (JD-R) perspective, we suggest that person – organization (PO) fit — the perceived congruence between individual and organizational values — will play a crucial role in shaping the performance effects of demands and resources inherently generated by workplace relationships. Results suggest that PO fit moderates relationships between network positions and individual job performance. Specifically, we find that having many friendships or being heavily sought out for advice enhances performance for those with higher levels of PO fit. Supplemental analyses highlight that incoming friendships or advice ties that are cross-functional are still beneficial for those among the highest in PO fit, but also that these same network positions can be detrimental for employees who are among the lowest in PO fit. These results contribute to a more nuanced understanding of the demands and resources generated by informal networks and how the translation of these features into performance is contingent upon the extent to which an employee identifies with organizational values.
Humoral Response to mRNA-1273 SARS-CoV-2 Vaccine in Peritoneal Dialysis Patients: Is Boostering After Six Months Adequate?

In dialysis patients the humoral response to anti-SARS-CoV-2 vaccines is attenuated and rapidly declines over time. However, data on the persistence of the immune response in peritoneal dialysis (PD) patients are scarce, particularly after a third (booster) dose with mRNA-1273 vaccine. In this prospective cohort study, we report anti-SARS-CoV-2 antibody levels in PD patients before and after the third dose of mRNA-1273 vaccine. Six months after the second dose, anti-SARS-CoV-2 antibodies were detected in all patients (n = 34). However, within this time period antibodies substantially declined in 31 of 34 patients (4.5-fold, median = 192 BAU/mL, p = 1.27 × 10–9) and increased in three patients. In accordance with government regulations, a third dose of mRNA-1273 vaccine (50 μg) was given to 27 PD patients 6 months after the second dose which induced a significant increase of anti-SARS-CoV-2 antibody titers (58.6-fold, median = 19405 BAU/mL, p = 1.24 × 10–29). A mixed model analysis showed that a lower Davies Comorbidity Score and a higher GFR were associated with higher antibody titers (p = 0.03 and p = 0.02). The most common adverse events after the third dose were pain at the injection site (77.8%) and fatigue (51.9%). No hospitalizations were reported. In conclusion, 6 months after the second dose of mRNA-1273 vaccine, anti-SARS-CoV-2 antibodies substantially decreased in PD patients, whereas a well-tolerated third dose induced a robust humoral response. Our data suggest that the administration of a booster dose within a shorter interval than 6 months should be considered in PD patients in order to maintain high anti-SARS-CoV-2 antibody levels and assure protection from severe COVID-19 disease.
Transcriptome Analysis of Retinoic Acid-Inducible Gene I Overexpression Reveals the Potential Genes for Autophagy-Related Negative Regulation

Retinoic acid-inducible gene I (RIG-I) serves as an essential viral RNA sensor for innate immune. The activation of the RIG-I-like receptors (RLRs) pathway triggers many regulations for the outcome of type I interferon, including ubiquitination, dephosphorylation, ISGylation, and autophagy. However, the autophagy-related regulation of RIG-I is still not fully understood. To investigate the potentially unknown genes related to autophagy-related regulation of RIG-I, we firstly confirm the induction of autophagy derived by overexpression of RIG-I. Furthermore, the autophagy inducer and inhibitor drugs were used in different assays. The results showed autophagy could control the activation of RLRs pathway and expression of exogenous RIG-I. In addition, we carried out the transcriptome analysis of overexpression of RIG-I in vitro. Differentially expressed genes (DEGs) in GO and KEGG signaling pathways enrichment provided a newly complex network. Finally, the validation of qPCR indicated that the DEGs PTPN22, PRKN, OTUD7B, and SIRT2 were correlated to the negative regulation of excessive expression of RIG-I. Taken together, our study contributed new insights into a more comprehensive understanding of the regulation of excessive expression of RIG-I. It provided the potential candidate genes for autophagy-related negative regulation for further investigation.
Learning via Linear Operators: Maximum Margin Regression; Multiclass and Multiview Learning at One-class Complexity

We introduce a maximum margin framework realizing a regression type learning in an arbitrary Hilbert space whilst the corresponding dual problem preserving the structure and, therefore, the complexity that of the binary Support Vector Machine(SVM). We demonstrate via some examples this learning framework is broadly applicable in several seemingly diﬀerent problems. One example is the multiclass classiﬁcation problem which, in this way, can be implemented with the complexity of a binary SVM. The reduction of the complexity does not involve diminishing performance but, in some cases this approach can improve the classiﬁcation accuracy. The multiclass classiﬁcation is realized where the output labels are vector valued. Other examples implement multiview learning problems.
Complete chloroplast genome of Holboellia grandiflora Réaubourg (Lardizabalaceae), a plant with an edible fruit

Abstract Holboellia grandiflora Réaubourg (Lardizabalaceae) is an evergreen twining perennial woody vine. To our knowledge, this is the first report on the complete chloroplast genome sequence of H. grandiflora. The complete chloroplast genome sequence was 157,811 bp in length and contained a large single-copy region of 86,554 bp and a small single-copy region of 18,975 bp. A pair of inverted repeats of 26,141 bp were included. It contained 130 genes, comprising 37 transfer RNA genes, and eight ribosomal RNA genes, as well as 85 coding sequences (CDSs). The GC content of the complete chloroplast genome sequence was 38.7%. The phylogenetic tree showed a close relationship among the three species of Holboellia (H. grandiflora, H. angustifolia, and H. latifolia). These findings provide a reference for phylogenetic relationships and assessment of the genetic structure of the Lardizabalaceae family.