Miracle-dz/UniFAR-FTUs huggingface dataset:
An optimal scheme for differentiating a variety of fruits for real-time prediction using Convolutional Neural Network by comparing with Decision Tree to increase the Accuracy, Precision and Sensitivity

Aim: The objective of this study is to implement deep learning technique based on innovative classification using convolutional neural networks algorithm to improve the detection of disease in fresh fruit compared with the Decision Tree algorithm to increase accuracy, precision, and sensitivity. Materials and Methods: A total of 2500 samples were collected from kaggle’s various fruit images. A training dataset of 1750 (70%) and a test dataset of 750 (30%) were generated from these samples. To measure the efficiency of the Convolutional neural network algorithm, accuracy, precision, and sensitivity values were measured. For each sample, 10 samples were collected for analysis. The significance p<0.005 mean accuracy, precision, and sensitivity shows the performance of fruit quality detection. The study parameters are found as alpha = 0.02 and G power = 0.8. Results: On the two classes under consideration, an independent samples T-test was performed. CNN has achieved accuracy, precision, and sensitivity of 97.5%, 95.1% and 99.4% respectively compared to 87.7%, 90.8%, and 91.2% by the Decision Tree algorithm. Conclusion: In this study it was found that the CNN algorithm appears to be significantly better than the Decision Tree algorithm in fruit quality detection whether it was healthy or diseased of the datasets considered.
LuckyChirp: Opportunistic Respiration Sensing Using Cascaded Sonar on Commodity Devices

We present LuckyChirp, a contactless, passive, opportunistic respiratory tracking solution for commodity device using cascaded sonar modeling. Compared to conventional sonar methods that only solve the respiratory estimation problem (“what is the respiratory rate”), LuckyChirp also solves the additional respiratory detection problem (“is the human present and static enough for respiration sensing”). LuckyChirp uses a custom neural network on pulsed sonar’s wavelet transformed features to detect respiration. The classifier is then cascaded with a respiratory rate estimator. Such holistic design eliminates user friction of manually activating the system and enables passive respiration monitoring for all-day natural use. With Google Nest Hub and Pixel 4 as experimental devices, LuckyChirp achieves a mean absolute error of 0.48±0.98 and 1.07±1.67 breaths/min, respectively, for 20 users participating in a whole-night study. Compared to direct respiratory estimation without respiration classification, this is a ×6 (Nest Hub) and ×4 (Pixel) reduction in error.
Symmetric Contrastive Loss for Out-of-Distribution Skin Lesion Detection

Detecting out-of-distribution (OOD) data has been a challenging task for deep learning models trained with real-life datasets. This work studies OOD detection in medical images where inter-class difference (e.g., variations in visual appearance across separate diseases) outweighs intra-class difference (e.g., same disease but on different locations or people). To improve OOD detection performance, we propose a self-supervised learning approach that can better capture inter-/intra-class variance using a novel symmetric contrastive loss. Two large-scale, publicly-available skin lesion datasets, HAM10000 and DermNet, are adopted in our study. Comprehensive experiments, including three different distributional shifts, disease-specific OOD detection, as well as an adversarial attack, are conducted to validate the effectiveness of our approach.
Kinematic analysis of automobile wishbone independent suspension

By applying the principles of coordinate transfer and introducing Euler parameters, the constraint equations of key points are formulated, and the law that parameters such as caster, camber, toe in and wheel base vary with the wheel moving up and down is deduced. A new method of analyzing the motion of wishbone independent suspension is put forward. To different types of automobile, the kinematics simulation was implemented by using the code developed . The simulation results agree with the experimental data quite well.
An Accurate Solution of the Furthest Right Point of the Pro-cut Line of Taper & Column

The article makes a correction to a prevalent fault in engineering drawing science at present.Where taper and column pro-cuts,it usually utilizes characteristic of gather in side elevation to seek the cut line in the furthest right point,passing the top of taper to make cut line of gather circularity,finding out the cutting point in shadow of V side,which was thought that the point should be the furthest right.However,it is not correct.The article gives an accurate solution of finding the cut line in the furthest right point,and makes an analysis by analytics.
Dissection of the microRNA Network Regulating Hedgehog Signaling in Drosophila

The evolutionarily conserved Hedgehog (Hh) signaling plays a critical role in embryogenesis and adult tissue homeostasis. Aberrant Hh signaling often leads to various forms of developmental anomalies and cancer. Since altered microRNA (miRNA) expression is associated with developmental defects and tumorigenesis, it is not surprising that several miRNAs have been found to regulate Hh signaling. However, these miRNAs are mainly identified through small-scale in vivo screening or in vitro assays. As miRNAs preferentially reduce target gene expression via the 3′ untranslated region, we analyzed the effect of reduced expression of core components of the Hh signaling cascade on downstream signaling activity, and generated a transgenic Drosophila toolbox of in vivo miRNA sensors for core components of Hh signaling, including hh, patched (ptc), smoothened (smo), costal 2 (cos2), fused (fu), Suppressor of fused (Su(fu)), and cubitus interruptus (ci). With these tools in hand, we performed a genome-wide in vivo miRNA overexpression screen in the developing Drosophila wing imaginal disc. Of the twelve miRNAs identified, seven were not previously reported in the in vivo Hh regulatory network. Moreover, these miRNAs may act as general regulators of Hh signaling, as their overexpression disrupts Hh signaling-mediated cyst stem cell maintenance during spermatogenesis. To identify direct targets of these newly discovered miRNAs, we used the miRNA sensor toolbox to show that miR-10 and miR-958 directly target fu and smo, respectively, while the other five miRNAs act through yet-to-be-identified targets other than the seven core components of Hh signaling described above. Importantly, through loss-of-function analysis, we found that endogenous miR-10 and miR-958 target fu and smo, respectively, whereas deletion of the other five miRNAs leads to altered expression of Hh signaling components, suggesting that these seven newly discovered miRNAs regulate Hh signaling in vivo. Given the powerful effects of these miRNAs on Hh signaling, we believe that identifying their bona fide targets of the other five miRNAs will help reveal important new players in the Hh regulatory network.
Adaptive Deformation Control for Elastic Linear Objects

This paper addresses the general problem of deformable linear object manipulation. The main application we consider is in the field of agriculture, for plant grasping, but may have interests in other tasks such as human daily activities and industrial production. We specifically consider an elastic linear object where one of its endpoints is fixed, and another point can be grasped by a robotic arm. To deal with the mentioned problem, we propose a model-free method to control the state of an arbitrary point that can be at any place along the object’s length. Our approach allows the robot to manipulate the object without knowing any model parameters or offline information of the object’s deformation. An adaptive control strategy is proposed for regulating the state of any point automatically deforming the object into the desired location. A control law is developed to regulate the object’s shape thanks to the adaptive estimation of the system parameters and its states. This method can track a desired manipulation trajectory to reach the target point, which leads to a smooth deformation without drastic changes. A Lyapunov-based argument is presented for the asymptotic convergence of the system that shows the process’s stability and convergence to desired state values. To validate the controller, numerical simulations involving two different deformation models are conducted, and performances of the proposed algorithm are investigated through full-scale experiments.
The U-Curve of Happiness Revisited: Correlations and Differences in Life Satisfaction Over the Span of Life—An Empirical Evaluation Based on Data From 1,597 Individuals Aged 12–94 in Germany

Background Subjective wellbeing (SWB) is a research topic of growing interest for different disciplines. Based on a cross-sectional survey with 1,597 participants aged 12–94, this study investigated life satisfaction and momentary happiness, two important dimensions of SWB. We examined their relationship, shape, and correlates across individuals of different ages and interpreted the results in the light of a neurobiological model of motivation systems. Methods Statistical analyses were performed using multiple linear regression. First, we examined how life satisfaction is associated with selected socio-demographic variables across four age groups. Second, we analyzed the association between life satisfaction and age, and lastly, we examined the extent to which happiness is a prerequisite for life satisfaction in each age group. Results Our analyses show that life satisfaction correlates negatively with poor health and financial worries, and positively with partnership, grandchildren, and religiosity. However, the inverse relationship with poor health is stronger in younger than in older individuals, while the inverse association with financial worries is strongest in late midlife (50–69 years). We identified gender-specific differences concerning the relationship between life satisfaction and age, with males displaying a U-shape trend with its lowest point between the ages of 30 and 49, whereas females’ life satisfaction increases stepwise with age. Although momentary happiness correlates strongly with life satisfaction, this relationship decreases with age. Conclusion The results suggest that individuals adjust or even grow beyond their perceptions of a “good life” over time. Neurobiological processes of adaptation and personal growth could play an important role in these developments.
Assessment of the Endophytic Fungal Composition of Lactobacillus plantarum and Enterococcus faecalis-Fermented Astragalus membranaceus Using Single-Molecule, Real-Time Sequencing Technology

Endophytic fungus represents microorganisms existing within the healthy plant organs, which can significantly influence metabolic product production in plants, a process with great research value and broad prospects for development. To investigate the effect of fermentation with probiotic cultures on the endophytic fungal diversity and composition of Astragalus membranaceus, we used single-molecular, real-time sequencing (Pacific Biosciences) for 18S ribosomal RNA (rRNA) sequencing. The results showed that the endophytic fungi of A. membranaceus mainly belonged to Aspergillus, Penicillium, Cystofilobasidium, Candida, Guehomyces, and Wallemia. Furthermore, the endophytic fungal diversity and abundance of A. membranaceus were more variable after fermentation with Enterococcus faecium and/or Lactobacillus plantarum. Our data lays a solid and comprehensive foundation for further exploration of endophytic fungi from A. membranaceus as potential sources of functional compounds.
Integrated Family Approach in Mental Health Care by Professionals From Adult and Child Mental Health Services: A Qualitative Study

Objective A multiple case-study in which each case was evaluated by adult and child mental health professionals who used an integrated family approach in their treatments. In this approach, treatment focuses on the mental disorders of the parents as well as on the development of the young child and family relationships. This study evaluated the experiences of professionals from adult and child mental health services using this approach. The aim of the study is identifying key elements of this approach, processes involved in treatment, and barriers to its success, with the aim of contributing to the development of practice based integrated mental health care for the whole family. Background Parental mental disorders have an impact on parenting and child development. To stop detrimental cascade effects and prevent parent and child from being caught up in the intergenerational transmission of psychopathology, an integrated family approach in mental health care is needed. Methods: A qualitative case study design using a grounded theory approach. Data were collected through 19 group interviews of professionals (N = 37) from adult and infant mental health teams who worked together in the treatment of a family. Results Professionals from the two services were comfortable coping with complexity and felt supported to perform their treatments by staying in touch with each other in multi-disciplinary consultations. They indicated that by attuning the treatment components to each other and tailoring them to the capabilities of the family, their treatments had more impact. A flexible attitude of all involved professionals and commitment to the interest of all family members was essential. Conclusion According to professionals, treatment with an integrated family approach in mental health care is of value for families by addressing the distinct roles, positions and relationships, by implementing a flexible complementary treatment plan, and by empowering professionals by multi-disciplinary consultations.
How Does Green Credit Promote Carbon Reduction? A Mediated Model

Using China’s provincial panel data from 2006 to 2016, this paper develops a dynamic panel data model to investigate the impact and mechanism of green credit on carbon emissions at the national and regional levels. According to the findings, green credit significantly reduces carbon emissions, with the eastern region having the greatest reduction effect. Green credit, with the exception of the western region, has a strong positive impact on disruptive low-carbon innovation. When green credit is combined with disruptive low-carbon innovation, both can significantly reduce carbon emissions; however, the green credit impact diminishes. It can be concluded that disruptive low-carbon innovation has a mediation effect on green credit’s contribution to carbon emission reduction. As a result, China should broaden the scope of green credit, concentrate on providing high-quality low-carbon patented technology to science and technology enterprises, and alleviate their financing constraints. Furthermore, these enterprises should increase their output of disruptive low-carbon innovation while lowering carbon emissions through technological innovation.
Digital Innovation and Firm Environmental Performance: The Mediating Role of Supply Chain Management Capabilities

Given the omnipresence and profoundness of the ongoing pandemic from the Coronavirus disease 2019, its potential spread can be minimized through social distancing. However, this practice causes increasing difficulties and undesirability of traditional transactions or interactions. Accordingly, various manufacturing firms around the world have become more committed not only to accelerating the development of digital technologies, but also to integrating them with existing processes. In this study, we address an important issue of how manufacturing firms can adapt to the ever-changing volatility and unpredictable global business environment, and achieve sustainable growth by developing a strong supply chain management capability. Two specific interrelated research questions are considered: (1) How do supply chain management capabilities contribute to firm environmental performance; and (2) What are the sources of such capabilities? In so doing, we integrate various forms of digital innovation into a supply chain management capability logic to explore their antecedents and consequences. By using survey data from 272 manufacturing firms in China, we examine the relationship between three key forms of digital innovation (i.e., product, platform, and service) and firm environmental performance. Results show that digital product, platform, and service innovations all have positive contributions to supply chain management capability. In turn, supply chain management capabilities have a partial mediating effect between digital product innovation and firm environmental performance, but a full mediating effect between digital platform and service innovations and firm environmental performance.
Defining the Roles of Cardiokines in Human Aging and Age-Associated Diseases

In recent years an expanding collection of heart-secreted signaling proteins have been discovered that play cellular communication roles in diverse pathophysiological processes. This minireview briefly discusses current evidence for the roles of cardiokines in systemic regulation of aging and age-associated diseases. An analysis of human transcriptome and secretome data suggests the possibility that many other cardiokines remain to be discovered that may function in long-range physiological regulations. We discuss the ongoing challenges and emerging technologies for elucidating the identity and function of cardiokines in endocrine regulations.
A Cell-free Expression Pipeline for the Generation and Functional Characterization of Nanobodies

Cell-free systems are well-established platforms for the rapid synthesis, screening, engineering and modification of all kinds of recombinant proteins ranging from membrane proteins to soluble proteins, enzymes and even toxins. Also within the antibody field the cell-free technology has gained considerable attention with respect to the clinical research pipeline including antibody discovery and production. Besides the classical full-length monoclonal antibodies (mAbs), so-called “nanobodies” (Nbs) have come into focus. A Nb is the smallest naturally-derived functional antibody fragment known and represents the variable domain (VHH, ∼15 kDa) of a camelid heavy-chain-only antibody (HCAb). Based on their nanoscale and their special structure, Nbs display striking advantages concerning their production, but also their characteristics as binders, such as high stability, diversity, improved tissue penetration and reaching of cavity-like epitopes. The classical way to produce Nbs depends on the use of living cells as production host. Though cell-based production is well-established, it is still time-consuming, laborious and hardly amenable for high-throughput applications. Here, we present for the first time to our knowledge the synthesis of functional Nbs in a standardized mammalian cell-free system based on Chinese hamster ovary (CHO) cell lysates. Cell-free reactions were shown to be time-efficient and easy-to-handle allowing for the “on demand” synthesis of Nbs. Taken together, we complement available methods and demonstrate a promising new system for Nb selection and validation.
Engineering Light-Control in Biology

Unraveling the transformative power of optogenetics in biology requires sophisticated engineering for the creation and optimization of light-regulatable proteins. In addition, diverse strategies have been used for the tuning of these light-sensitive regulators. This review highlights different protein engineering and synthetic biology approaches, which might aid in the development and optimization of novel optogenetic proteins (Opto-proteins). Focusing on non-neuronal optogenetics, chromophore availability, general strategies for creating light-controllable functions, modification of the photosensitive domains and their fusion to effector domains, as well as tuning concepts for Opto-proteins are discussed. Thus, this review shall not serve as an encyclopedic summary of light-sensitive regulators but aims at discussing important aspects for the engineering of light-controllable proteins through selected examples.
Lateral Mesoderm-Derived Mesenchymal Stem Cells With Robust Osteochondrogenic Potential and Hematopoiesis-Supporting Ability

Mesenchymal stem cells (MSCs) are among the most promising cell sources for the treatment of various diseases. Nonetheless, the therapeutic efficacy in clinical trials has been inconsistent due to the heterogeneity of MSCs, which may be partially attributed to their undefined developmental origins. The lateral mesoderm is also a developmental source of MSCs that constitute appendicular skeletal elements in the developing vertebrate embryo. However, it is difficult to isolate homogeneous lateral mesoderm (LM)-derived MSCs from bone tissues or bone marrow due to the lack of understanding of their characteristics. Herein, we successfully established an efficient differentiation protocol for the derivation of MSCs with a LM origin from human pluripotent stem cells (hPSCs) under specific conditions. LM-MSCs resembled bone marrow-derived MSCs (BMSCs) with regard to cell surface markers, global gene profiles, and immunoregulatory activity and showed a homeodomain transcription factor (HOX) gene expression pattern typical of skeletal MSCs in long bones. Moreover, we demonstrated that LM-MSCs had an increased osteogenic/chondrogenic differentiation capacity and hematopoietic support potential compared to BMSCs. These homogeneous LM-MSCs may serve as a powerful tool for elucidating their precise role in bone formation and hematopoiesis and could be a potentially ideal cell source for therapeutic applications.
Monocyte Count on Admission Is Predictive of Shunt-Dependent Hydrocephalus After Aneurysmal Subarachnoid Hemorrhage

The authors sought to evaluate whether immunologic counts on admission were associated with shunt-dependent hydrocephalus following aneurysmal subarachnoid hemorrhage. A retrospective analysis of 143 consecutive patients with aneurysmal subarachnoid hemorrhage over a 9-year period was performed. A stepwise algorithm was followed for external ventricular drain weaning and determining the necessity of shunt placement. Data were compared between patients with and without shunt-dependent hydrocephalus. Overall, 11.19% of the cohort developed shunt-dependent hydrocephalus. On multivariate logistic regression analysis, acute hydrocephalus (OR: 61.027, 95% CI: 3.890–957.327; p = 0.003) and monocyte count on admission (OR: 3.362, 95% CI: 1.024–11.037; p = 0.046) were found to be independent predictors for shunt dependence. Receiver operating characteristic curve analysis for the prediction of shunt-dependent hydrocephalus confirmed that monocyte count exhibited an acceptable area under the curve (AUC = 0.737, 95% CI: 0.601–0.872; p < 0.001). The best predictive cutoff value to discriminate between successful external ventricular drain weaning and shunt-dependent hydrocephalus was identified as a monocyte count ≥0.80 × 103/uL at initial presentation. These preliminary data demonstrate that a monocyte count ≥0.80 × 103/uL at admission predicts shunt-dependent hydrocephalus in patients with aneurysmal subarachnoid hemorrhage; however, further large-scale prospective trials and validation are necessary to confirm these findings.