Miracle-dz/UniFAR-FTUs huggingface dataset:
Valorization o f Algerian Semi - Soft Date a nd Tradition al Preparation o f Date Syrup: Physicochemical a nd Biochemical Properties

— In Algeria, the production of dates occupies a large part of Saharan agricultural production. The wilaya of Bechar is one of the most productive regions for dates, where more than half of their production is considered as a second quality dates which are sold by barter or used as animal feed. Families in these regions use this type of date to prepare by-products, namely; date syrup locally called " Robb ". The preparation of this type of product is limited and confined to the individual scale. The aim of this study is to highlight the physicochemical and the biochemical quality of this home-prepared artisanal product by comparing it to two others marketed in the wilaya of Bechar and of El-Bayadh (Algeria). The physicochemical and the biochemical results of the three analyzed samples showed an acidic pH value ranged from 4,26 to 4,7, a degree of acidity ranging from 8,2 to 12%, a soluble solids content of 64 to 75%, a total sugars and reducing sugar content of 51 to 63,6 and 40 to 52% respectively. While the water content is relatively high ranging from 28 to 37%, and a significant potassium ions content compared to sodium ions varies from 195 to 555 and from 5,8 to 137mg/L respectively. These characteristics are not only considered as a high added value to the product which enhances the value of the second-quality low marketing dates but also contributes to increasing their shelf life, constituting an economic priority for the oasis’ inhabitants of the Southern Algeria region.
Random Sharpness-Aware Minimization

Currently, Sharpness-Aware Minimization (SAM) is proposed to seek the parameters that lie in a flat region to improve the generalization when training neural networks. In particular, a minimax optimization objective is defined to find the maximum loss value centered on the weight, out of the purpose of simultaneously minimizing loss value and loss sharpness. For the sake of simplicity, SAM applies one-step gradient ascent to approximate the solution of the inner maximization. However, one-step gradient ascent may not be sufficient and multi-step gradient ascents will cause additional training costs. Based on this observation, we propose a novel random smoothing based SAM (R-SAM) algorithm. To be specific, R-SAM essentially smooths the loss landscape, based on which we are able to apply the one-step gradient ascent on the smoothed weights to improve the approximation of the inner maximization. Further, we evaluate our proposed R-SAM on CIFAR and ImageNet datasets. The experimental results illustrate that R-SAM can consistently improve the performance on ResNet and Vision Transformer (ViT) training.
The Effect of Neuroticism on Trust Perception of Time Series Visualizations

Trust is one of the most important factors when it comes to deciding whether the information displayed in a visualization is going to be acquired as knowledge and used by the users. There are many factors in a visualization that can affect perceived trust, such as design factors, the display of uncertainties, or even individual characteristics such as personality. However, nowadays most visualizations are still designed using a one-size-ﬁts-all approach. Our work proposes a study to evaluate whether the neuroticism trait has an effect on data trust perception in the context of information visualization of time-oriented data. In particular, we want to evaluate whether time granularity has an impact on perceived trust. This work acknowledges that granularity may be a relevant feature in the design of time-based visualizations, since people trust more in a line chart with a larger number of data points and interact more with a line chart that they trust less. Contrarily, we did not ﬁnd any relation between neuroticism and perceived trust. However a deeper analysis concerning the facets of neuroticism and other traits from the Five Factor Model (FFM) suggests that personality characteristics might inﬂuence perceived trust and user interaction with a visualization.
Comprehensive comparison of industrial cannabinoid extraction techniques: Evaluation of the most relevant patents and studies at pilot scale

Cannabinoids are gaining attention in many sectors, including the pharmaceutical, nutraceutical, and cosmetic sectors. To date, several conventional and alternative techniques have been applied for Cannabis sativa L (C. sativa L.) extraction at the industrial scale. The conventional methods are liquid solvent extraction, including polar and non-polar solvents such as ethanol, hexane, petroleum ether, and other solvent extraction. Pressurized gas extraction is another conventional method and comprises gaseous hydrocarbon extraction such as n-butane and n-propane, supercritical or subcritical carbon dioxide extraction, and extraction using a refrigerant gas such as 1,1,1,2-tetrafluoroethane (HFC 134a). Alternative extraction methods include microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), hydrodynamic cavitation, and pulsed electric fields (PEF). This review thoroughly analyzes and compares the main extraction techniques and technologies at the industrial scale found in the patent literature. In addition, several aspects of the pretreatment of cannabis plant material and its influence on extraction are also discussed.
Barriers and facilitators for the sustainability of digital health interventions in low and middle-income countries: A systematic review

Background Digital health interventions (DHIs) have increased exponentially all over the world. Furthermore, the interest in the sustainability of digital health interventions is growing significantly. However, a systematic synthesis of digital health intervention sustainability challenges is lacking. This systematic review aimed to identify the barriers and facilitators for the sustainability of digital health intervention in low and middle-income countries. Methods Three electronic databases (PubMed, Embase and Web of Science) were searched. Two independent reviewers selected eligible publications based on inclusion and exclusion criteria. Data were extracted and quality assessed by four team members. Qualitative, quantitative or mixed studies conducted in low and middle-income countries and published from January 2000 to May 2022 were included. Results The sustainability of digital health interventions is very complex and multidimensional. Successful sustainability of digital health interventions depends on interdependent complex factors that influence the implementation and scale-up level in the short, middle and long term. Barriers identified among others are associated with infrastructure, equipment, internet, electricity and the DHIs. As for the facilitators, they are more focused on the strong commitment and involvement of relevant stakeholders: Government, institutional, sectoral, stakeholders' support, collaborative networks with implementing partners, improved satisfaction, convenience, privacy, confidentiality and trust in clients, experience and confidence in using the system, motivation and competence of staff. All stakeholders play an essential role in the process of sustainability. Digital technology can have long term impacts on health workers, patients, and the health system, by improving data management for decision-making, the standard of healthcare service delivery and boosting attendance at health facilities and using services. Therefore, management changes with effective monitoring and evaluation before, during, and after DHIs are essential. Conclusion The sustainability of digital health interventions is crucial to maintain good quality healthcare, especially in low and middle-income countries. Considering potential barriers and facilitators for the sustainability of digital health interventions should inform all stakeholders, from their planning until their scaling up. Besides, it would be appropriate at the health facilities level to consolidate facilitators and efficiently manage barriers with the participation of all stakeholders.
Auxin biosynthesis by Microbacterium testaceum Y411 associated with orchid aerial roots and their efficacy in micropropagation

Root-associated bacteria strongly affect plant growth and development by synthesizing growth regulators and stress-relieving metabolites. The present study is mainly focused on assessing aerial root-associated bacteria of Rhynchostylis retusa (L.) Blume is an endemic epiphytic orchid responsible for auxin production and influencing plant growth. A bacterial isolate, Microbacterium testaceum Y411, was found to be the most active producer of indole-3-acetic acid (IAA). The maximum IAA production (170µg/mL) was recorded with the bacterium at optimum process parameters such as pH 7, temperature 30°C, and tryptophan 1000 µg/mL in a culture medium for 48 h. The extracted auxin was purified and analyzed by FT-IR, HPLC, and HR-MS, indicating bacterial auxin has a similar mass value to 4-chloroindole-3-acetic acid auxin. Furthermore, the bacterial auxin was tested on in vitro propagation of orchid, Cymbidium aloifolium, and 90% seed germination was recorded in Murashige and Skoog’s medium supplemented with bacterial auxin. The novel results obtained in this study are used for agricultural applications and the Microbacterium testaceum Y411 is a valuable biotechnological resource for a natural auxin.
Therapist reactions to patient personality: A pilot study of clinicians’ emotional and neural responses using three clinical vignettes from in treatment series

Introduction Therapists’ responses to patients play a crucial role in psychotherapy and are considered a key component of the patient–clinician relationship, which promotes successful treatment outcomes. To date, no empirical research has ever investigated therapist response patterns to patients with different personality disorders from a neuroscience perspective. Methods In the present study, psychodynamic therapists (N = 14) were asked to complete a battery of instruments (including the Therapist Response Questionnaire) after watching three videos showing clinical interactions between a therapist and three patients with narcissistic, histrionic/borderline, and depressive personality disorders, respectively. Subsequently, participants’ high-density electroencephalography (hdEEG) was recorded as they passively viewed pictures of the patients’ faces, which were selected from the still images of the previously shown videos. Supervised machine learning (ML) was used to evaluate whether: (1) therapists’ responses predicted which patient they observed during the EEG task and whether specific clinician reactions were involved in distinguishing between patients with different personality disorders (using pairwise comparisons); and (2) therapists’ event-related potentials (ERPs) predicted which patient they observed during the laboratory experiment and whether distinct ERP components allowed this forecast. Results The results indicated that therapists showed distinct patterns of criticized/devalued and sexualized reactions to visual depictions of patients with different personality disorders, at statistically systematic and clinically meaningful levels. Moreover, therapists’ late positive potentials (LPPs) in the hippocampus were able to determine which patient they observed during the EEG task, with high accuracy. Discussion These results, albeit preliminary, shed light on the role played by therapists’ memory processes in psychotherapy. Clinical and neuroscience implications of the empirical investigation of therapist responses are discussed.
Diverse mechanisms associated with cyhalofop-butyl resistance in Chinese sprangletop (Leptochloa chinensis (L.) Nees): Characterization of target-site mutations and metabolic resistance-related genes in two resistant populations

Resistance of Chinese sprangletop (Leptochloa chinensis (L.) Nees) to the herbicide cyhalofop-butyl has recently become a severe problem in rice cultivation. However, the molecular mechanisms of target-site resistance (TSR) in cyhalofop-butyl-resistant L. chinensis as well as the underlying non-target-site resistance (NTSR) have not yet been well-characterized. This study aimed to investigate cyhalofop-butyl resistance mechanisms using one susceptible population (LC-S) and two resistant populations (LC-1701 and LC-1704) of L. chinensis. We analyzed two gene copies encoding the entire carboxyltransferase (CT) domain of chloroplastic acetyl-CoA carboxylase (ACCase) from each population. Two non-synonymous substitutions were detected in the resistant L. chinensis populations (Trp2027-Cys in the ACCase1 of LC-1701 and Leu1818-Phe in the ACCase2 of LC-1704), which were absent in LC-S. As Trp2027-Cys confers resistance to ACCase-inhibiting herbicides, the potential relationship between the novel Leu1818-Phe mutation and cyhalofop-butyl resistance in LC-1704 was further explored by single-nucleotide polymorphism (SNP) detection. Metabolic inhibition assays indicated that cytochrome P450 monooxygenases (P450s) and glutathione S-transferases (GSTs) contributed to cyhalofop-butyl resistance in specific resistant populations. RNA sequencing showed that the P450 genes CYP71Z18, CYP71C4, CYP71C1, CYP81Q32, and CYP76B6 and the GST genes GSTF11, GSTF1, and GSTU6 were upregulated in at least one resistant population, which indicated their putative roles in cyhalofop-butyl resistance of L. chinensis. Correlation analyses revealed that the constitutive or inducible expression patterns of CYP71C4, CYP71C1, GSTF1, and GSTU6 in L. chinensis were strongly associated with the resistant phenotype. For this reason, attention should be directed towards these genes to elucidate metabolic resistance to cyhalofop-butyl in L. chinensis. The findings of this study improve the understanding of mechanisms responsible for resistance to ACCase-inhibiting herbicides in grass-weed species at the molecular level, thus aiding in the development of weed management strategies that delay the emergence of resistance to this class of pest control products.
Identification and validation of a prognostic risk-scoring model based on sphingolipid metabolism-associated cluster in colon adenocarcinoma

Colon adenocarcinoma (COAD) is the primary factor responsible for cancer-related mortalities in western countries, and its development and progression are affected by altered sphingolipid metabolism. The current study aimed at investigating the effects of sphingolipid metabolism-related (SLP) genes on multiple human cancers, especially on COAD. We obtained 1287 SLP genes from the GeneCard and MsigDb databases along with the public transcriptome data and the related clinical information. The univariate Cox regression analysis suggested that 26 SLP genes were substantially related to the prognosis of COAD, and a majority of SLP genes served as the risk genes for the tumor, insinuating a potential pathogenic effect of SLP in COAD development. Pan-cancer characterization of SLP genes summarized their expression traits, mutation traits, and methylation levels. Subsequently, we focused on the thorough research of COAD. With the help of unsupervised clustering, 1008 COAD patients were successfully divided into two distinct subtypes (C1 and C2). C1 subtype is characterized by a poor prognosis, activation of SLP pathways, high expression of SLP genes, disordered carcinogenic pathways, and immune microenvironment. Based on the clusters of SLP, we developed and validated a novel prognostic model, consisting of ANO1, C2CD4A, EEF1A2, GRP, HEYL, IGF1, LAMA2, LSAMP, RBP1, and TCEAL2, to quantitatively evaluate the clinical outcomes of COAD. The Kaplain-Meier survival curves and ROC curves highlighted the accuracy of our SLP model in both internal and external cohorts. Compared to normal colon tissues, expression of C2CD4A was detected to be significantly higher in COAD; whereas, expression levels of EEF1A2, IGF1, and TCEAL2 were detected to be significantly lower in COAD. Overall, our research emphasized the pathogenic role of SLP in COAD and found that targeting SLP might help improve the clinical outcomes of COAD. The risk model based on SLP metabolism provided a new horizon for prognosis assessment and customized patient intervention.
Analysis of subgingival micro-organisms based on multi-omics and Treg/Th17 balance in type 2 diabetes with/without periodontitis

Type 2 diabetes mellitus (T2DM) and periodontitis are common and interrelated diseases, resulting in altered host response microbiota. The subgingival micro-organisms play a key role in periodontitis pathogenesis. To assess the shift of subgingival microbiome and metabolome in T2DM, we performed an analysis of the subgingival microbiome in patients with T2DM (n = 20) compared with non-diabetes (ND) subjects (n = 21). Furthermore, patients were subdivided into 10 T2DM with periodontitis (DP), 10 T2DM without periodontitis (DNP), 10 periodontitis (P), and 11 healthy control (H) groups. 16SrRNA gene sequencing combined with ultra high-performance liquid chromatography-mass spectrometry (UHPLC–MS) based metabolomics was performed in all participants. T lymphocyte immunity was analyzed by flow cytometry. Furthermore, the network relationship among subgingival micro-organisms, metabolites, blood glucose level, and T lymphocyte immunity were analyzed. The results showed that the difference of the subgingival microbiome from healthy to periodontitis status was less prominent in T2DM compared with ND, though the clinical signs of disease were similar. The bacteria Eubacterium nodatum group, Filifactor, Fretibacterium, Peptostreptococcus, and Desulfovibrio, amongst others, may be important in the pathopoiesia of periodontitis in the T2DM state. In addition, some dominant bacteria showed network relationships. The Treg/Th17 ratio was lower in the DP and DNP groups than in the P and H groups—though that of P was lower than for H. The percentage of CD4+/CD8+ PD1 and CD8+ PDL1 was higher in the DP and DNP groups than in the H group; the percentage of CD8+ PDL1 was higher in the DP than P groups. Subgingival micro-organisms in periodontitis had a significant metabolic shift in terms of their signature metabolites. Butyrate metabolism and phenylalanine metabolism may play a role in the pathogenesis of periodontitis with/without T2DM. Specifically, biphenyl degradation, tryptophan metabolism, and the two-component system may play important roles in periodontitis with T2DM. Lastly, the network relationship among subgingival micro-organisms, metabolites, blood glucose level, and T lymphocyte immunity were unbalanced. This study identified the changes in the subgingival microbiome associated with periodontitis in T2DM, as well as the associated network between bacterial flora, metabolism dysbiosis, and immune regulation.
Family interactions in toddlerhood influence social competence in preschool age: Accounting for genetic and prenatal influences

Identification of early promotive and risk factors for social competence is important for fostering children’s successful social development; particularly given social competence is essential for children’s later academic and psychological well-being. While research suggests that the early parent–child relationship, genetics, and prenatal influences are associated with social competence, there is less research considering how these factors may operate together to shape children’s social competence in early childhood. Using a genetically informed sample from the Early Growth and Development Study (N = 561), we examined multiple levels of influence (i.e., genetic, prenatal, parenting, and child characteristics) on children’s social competence at 4.5 years old. Results from structural equation models showed adoptive mother overreactivity at 18 months was positively associated with child dysregulation at 27 months, which, in turn, was associated with lower levels of social competence at 4.5 years. Also, child reactivity at 18 months was independently associated with higher levels of adoptive mother overreactivity at 27 months, which, in turn, was associated with lower levels of social competence at 4.5 years. Finally, we found an evocative effect on adoptive fathers’ overreactivity at 18 months such that prenatal birth mother distress was negatively associated with adoptive fathers’ overreactivity at 18 months. Overall, this study found evidence for genetic influences, and bidirectional associations between parent and child in toddlerhood that are related to lower levels of social competence when children were 4.5 years old. We also found that the prenatal environment was associated with parenting, but not with child behavior directly. This study’s ability to simultaneously examine multiple domains of influence helps provide a more comprehensive picture of important mechanisms and developmental periods for children’s early social competence.
Genome−wide identification and analysis of LEA_2 gene family in alfalfa (Medicago sativa L.) under aluminum stress

Late embryonic development abundant proteins (LEAs) are a large family of proteins commonly existing in plants. LEA_2 is the largest subfamily in the LEA, it plays an important role in plant resistance to abiotic stress. In order to explore the characteristics of LEA_2 gene family members in alfalfa (Medicago sativa L.), 155 members of LEA_2 (MsLEA_2) family were identified from alfalfa genome. Bioinformatics analysis was conducted from the aspects of phylogenetic relationship, chromosome distribution, chromosome colinearity, physical and chemical properties, motif composition, exon-intron structure, cis-element and so on. Expression profiles of MsLEA_2 gene were obtained based on Real-time fluorescent quantitative PCR (qRT-PCR) analysis and previous RNA-seq data under aluminum (Al) stress. Bioinformatics results were shown that the MsLEA_2 genes are distributed on all 32 chromosomes. Among them, 85 genes were present in the gene clusters, accounting for 54.83%, and chromosome Chr7.3 carries the largest number of MsLEA_2 (19 LEA_2 genes on Chr7.3). Chr7.3 has a unique structure of MsLEA_2 distribution, which reveals a possible special role of Chr7.3 in ensuring the function of MsLEA_2. Transcriptional structure analysis revealed that the number of exons in each gene varies from 1 to 3, and introns varies from 0 to 2. Cis-element analysis identified that the promoter region of MsLEA_2 is rich in ABRE, MBS, LTR, and MeJARE, indicating MsLEA_2 has stress resistance potential under abiotic stress. RNA-seq data and qRT-PCR analyses showed that most of the MsLEA_2 members were up-regulated when alfalfa exposed to Al stress. This study revealed that phylogenetic relationship and possible function of LEA_ 2 gene in alfalfa, which were helpful for the functional analysis of LEA_ 2 proteins in the future and provided a new theoretical basis for improving Al tolerance of alfalfa.