Malaria is a long-standing disease and one of the top life-threatening diseases, yet its treatment has not changed, while the world has already embraced the Fourth Industrial Revolution (4IR). A wave of research on digitizing monitoring mechanisms of such a deadly disease has surfaced. Automated malaria screening is one of the detection processes which are gaining popularity in the research domain. However, the process needs to be coupled with other processes aiming a nationally or regionally contextualised malaria monitoring system. This paper proposes a digital malaria monitoring system in the context of an African country or region. One advantage of such a digital system is that is enables a novel disease spread forecasting model based on the dynamics of different malaria types. The architecture of the diagnosis system is described, and the disease spread model is mathematically modelled in terms of a SPITR (Susceptible- Protected- Infected-Treated- Recovered) epidemic model which is further analysed. The forecasting model is expressed and analysed whereas experiments are conducted using a Monte Carlo simulation method. The design of the monitoring system has inspired how predictions can be made in the complex cases such as mixed infections. Results show that reinforcing the model parameter makes a significant improvement on the disease prediction.

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made on complex multicellular organisms, and then modified to fit a DNA-centric view. In this article, I argue that, based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that: i) natural selection plays a dominant role in evolution, and ii) the probability of mutations is independent of the generated phenotype. I will show that the adaptation of a phenotype to an environment does not correspond to organism fitness but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome, and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype, the phenotype ensuring the stability of the genotype in a cellular and environment physicochemical parameter-depending manner.

The physics–biology continuum relies on the fact that life emerged from prebiotic molecules. Here, I argue that life emerged from the physical coupling between the synthesis of nucleic acids and the synthesis of amino acid polymers. Owing to this physical coupling, amino acid polymers (or proto-phenotypes) maintained the physicochemical parameter equilibria (proto-homeostasis) in the immediate environment of their encoding nucleic acids (or proto-genomes). This protected the proto-genome physicochemical integrity (i.e., atomic composition) from environmental physicochemical stresses, and therefore increased the probability of reproducing the proto-genome without variation. From there, genomes evolved depending on the biological activities they generated in response to environmental fluctuations. Thus, a genome generating an internal environment whose physicochemical parameters guarantee homeostasis and genome integrity has a higher probability to be reproduced without variation and therefore to reproduce the same phenotype in offspring. Otherwise, the genome is modified by the imbalances of the internal physicochemical parameters it generates, until new emerging biological activities maintain homeostasis. In sum, evolution depends on feedforward and feedback loops between genome and phenotype, since the internal physicochemical conditions that a genome generates in response to environmental fluctuations in turn either guarantee the stability or direct the variation of the genome.

Although information theory resolves inconsistencies (known under the form of famous enigmas) of the traditional approach of thermostatistics, its place in the corresponding literature is not what it deserves. This is interpreted as being mainly due to epistemological rather than scientific reasons: the subjectivity introduced into physics is perceived as a problem. This paper attempts to expose and clarify where exactly this subjectivity lies: in the representation of the reality and in probabilistic inference. Two aspects which have been integrated into the practice of science for a long time and which should no longer frighten anyone, but which become explicit with information theory.

Landauer’s principle states that the logical irreversibility of an operation, such as erasing one bit, whatever its physical implementation, necessarily implies its thermodynamical irreversibility. In this paper, a very simple counterexample of physical implementation (that uses a two-to-one relation between logic and thermodynamic states) is given that allows to erase one bit in a thermodynamical quasistatic manner (i.e. that may tend to be reversible if slowed down enough).

This study inscribes itself in the global discussion on the nurturing of pro-environmental behaviors among young people for a sustainable future. Here we focus on students' interest in Ecosystem Services and Sustainability to explain their awareness and optimism about the environmental issues of air pollution, water shortage and green gas emission in 50 countries around the world. To this end, we use the cross-sectional survey data of the OECD's Program for International Student Assessment (PISA) 2015, along with seemingly unrelated bi-variate weighted ordered Probit modeling with country specific effects. The results show that in addition to factors such as age, gender, immigration status, and economic, social and cultural status, interest in the biosphere is a significant determinant of students' environmental awareness and optimism. In fact, a one level increase in students' interest in ecosystem services and sustainability raises on average their awareness level by 15.3% for the issue of air pollution, 15.7% for the issue of water shortage, and 24.6% for the issue of green gas emission. Although students' interest in the biosphere seems to not have a significant effect on their expectations about the issue of green gas emission, it does however raise their level of optimism by 0.8% for the issue of air pollution, and 0.2% for the issue of water shortage. Furthermore, every one level increase in students' environmental awareness leads to 17.3% more optimism about the issue of air pollution, 15.8% more optimism about the issue of water shortage, and 17.4% more optimism about the issue of green gas emission. Therefore, relying on the Theory of Planned Behavior (TPB), our results imply that governments and policy makers can successfully leverage young people interests in the biosphere to effectively achieve their goals for sustainability.

Computer vision models of salient object detection attempt to mimic the ability of the human visual system to select relevant objects in images. To this end, the development of deep neural networks on high-end computers has recently made it possible to achieve high performance. However, it remains a challenge to develop deep neural network models of the same performance for devices with much more limited resources. In this work, we propose a new approach for a lightweight salient object detection neural network model, inspired by the cone and spatial opponent processes of the primary visual cortex (V1), that inextricably link color and shape in human color perception. Our proposed model, namely CoSOV1net, is trained from scratch, without using backbones from image classification or other tasks. Experiments, on the most widely used and challenging datasets for salient object detection, show that CoSOV1Net achieves competitive performance (i.e. Fβ=0.931 on the ECSSD dataset) with state-of-the-art salient object detection models, while having low number of parameters (1.14M), low FLOPS (1.4G) and high FPS (211.2) on GPU (nvidia Geforce RTX 3090 TI) compared to the state-of-the-art in the salient object detection or lightweight salient object detection task. Thus, CoSOV1net turns out to be a lightweight salient object detection that can be adapted to mobile environments and resource-constrained devices.

There is an increasing need for quantitative rockfall hazard and risk assessment that requires a precise definition of the terms and concepts used for this particular type of landslide. This paper suggests to use terms that appear to be the more logic and explicit as possible, and describes methods to derive some of the main hazard and risk descriptors. The terms and concepts presented concern the rockfall process (failure, propagation, fragmentation, modelling) and the hazard and risk descriptors, distinguishing the cases of localized hazards and diffused hazards. For a localized hazard, the failure probability of the considered rock compartment in a given period of time has to be assessed and the probability for a given element at risk to be impacted with a given energy must be derived combining the failure probability, the propagation probability and the exposure of the element. For a diffuse hazard that is characterized by a failure frequency, the number of rockfalls reaching the element at risk per unit of time and with a given energy (reach frequency) can be derived. However, when the element at risk is not replaced or repaired, the probability that it is impacted by at least one rockfall must be considered.

Prionace glauca, blue shark is a cosmopolitan species. Together with Carcharhinus falciformis, it co-dominated the landings of carcharhinidae sharks at the Artisanal Fishing Port of Cotonou. The objective of this study is to determine the demographic parameters of the blue shark in Gulf of Guinea marine waters. The different routines of the FISAT II v 1.2 software associated with the empirical equations of Froese and Nohland, allowed the evaluation of the different demographic parameters of the blue shark in Benin's marine waters. From August to December 2015, 244 individuals shark sizes; ranging from 175cm to 325cm were sampled. The total asymptotic length obtained was 341.25cm with a growth rate of 0.35/year, which indicates that the species is growing rapidly and the optimal total length of the species is 232.01cm. The age of first maturity of the species is 3 years with a longevity of 10 years. The exploitation rate is E= 0.74 with total mortality being 2.4; natural mortality is 0.6 and fishing mortality is 1.8. The sex ratio remains in favour of males throughout the study period. Monitoring programme were suggested with effective management measures established and executed for sustainability of the blue shark’s stock in the Gulf of Guinea.

In this paper, we present the idea of Self Supervised learning on the Shape Completion and Classification of point clouds. Most 3D shape completion pipelines utilize autoencoders to extract features from point clouds used in downstream tasks such as Classification, Segmentation, Detection, and other related applications. Our idea is to add Contrastive Learning into Auto-Encoders to learn both global and local feature representations of point clouds. We use a combination of Triplet Loss and Chamfer distance to learn global and local feature representations. To evaluate the performance of embeddings for Classification, we utilize the PointNet classifier. We also extend the number of classes to evaluate our model from 4 to 10 to show the generalization ability of learned features. Based on our results, embedding generated from the Contrastive autoencoder enhances Shape Completion and Classification performance from 84.2% to 84.9% of point clouds achieving the state-of-the-art results with 10 classes.

The misuse of antibiotics during the last decades led to the emergence of multidrug resistant pathogenic bacteria. This phenomenon constitutes a major public health issue. Consequently, the discovery of new antibacterials in the short term is crucial. Colicins, due to their antibacterial properties, thus constitute good candidates. These toxin proteins, produced by E. coli to kill enteric relative competitors, exhibit cytotoxicity through ionophoric activity or essential macromolecule degradation. Among the 25-colicin types known to date, colicin M (ColM) is the only one colicin interfering with peptidoglycan biosynthesis. Accordingly, ColM develops its lethal activity in E. coli periplasm by hydrolyzing the last peptidoglycan precursor, lipid II, into two dead-end products, thereby leading to cell lysis. Since the discovery of its unusual mode of action, several ColM orthologs have also been identified based on sequence alignments; all of the characterized ColM-like proteins display the same enzymatic activity of lipid II degradation and narrow antibacterial spectra. This publication aims at being an exhaustive review about what is currently known on this new family of antibacterial enzymes as well as on their potential use of food preservatives or therapeutic agents.

Table detection is a preliminary step in extracting reliable information from tables in scanned document images. We present CasTabDetectoRS, a novel end-to-end trainable table detection framework that operates on Cascade Mask R-CNN, including Recursive Feature Pyramid network and Switchable Atrous Convolution in the existing backbone architecture. By utilizing a comparatively lightweight backbone of ResNet-50, this paper demonstrates that superior results are attainable without relying on pre and post-processing methods, heavier backbone networks (ResNet-101, ResNeXt-152), and memory-intensive deformable convolutions. We evaluate the proposed approach on five different publicly available table detection datasets. Our CasTabDetectoRS outperforms the previous state-of-the-art results on four datasets (ICDAR-19, TableBank, UNLV, and Marmot) and accomplishes comparable results on ICDAR-17 POD. Upon comparing with previous state-of-the-art results, we obtain a significant relative error reduction of 56.36%, 20%, 4.5%, and 3.5% on the datasets of ICDAR-19, TableBank, UNLV, and Marmot, respectively. Furthermore, this paper sets a new benchmark by performing exhaustive cross-datasets evaluations to exhibit the generalization capabilities of the proposed method.

Malassezia is lipid-dependent commensal yeast of the human skin. The different culture media and skin sampling methods used to grow these fastidious yeasts are a source of heterogeneity in culture-based epidemiological study results. This study aimed to compare the performances of three methods of skin sampling, and two culture media for the detection of Malassezia yeasts by culture from the human skin. Three skin sampling methods, namely sterile gauze, dry swab and TranswabTM with transport medium, were applied on 10 healthy volunteers. Each sample was further inoculated onto either the novel FastFung medium or the reference Dixon agar for the detection of Malassezia spp. by culture. At least one colony of Malassezia spp. grew on 93/300 (31%) of the cultures, corresponding to 150 samplings. The positive culture rate was 67%, 18%, and 15% (P < 10-3), for samples collected with sterile gauze, TranswabTM, and dry swab, respectively. The positive culture rate was 62% and 38% (P < 0.003) by using the FastFung and the Dixon media, respectively. Our results showed that sterile gauze rubbing skin sampling followed by inoculation on FastFung medium should be implemented in the routine clinical laboratory procedure for Malassezia spp. cultivation.

Background: The aim of this study was to compare energy expenditure (EE) predicted by accelerometery (EEAcc) with indirect calorimetry (EEMETA) in individuals with hemiparesis. Methods: Twenty-four participants (12 with stroke and 12 healthy controls) performed a six-minute walk test (6MWT) during which EEMETA was measured using a portable indirect calorimetry system and EEACC was calculated using Bouten’s equation (1993) with data from a 3-axis accelerometer positioned between L3 and L4. Results: Median EEMETA was 9.85 [8.18;11.89] W·kg-1 in the stroke group, and 5.0 [4.56;5.46] W·kg-1 in the control group. Median EEACC was 8.57 [7.86;11.24] W·kg-1 in the control group and 8.2 [7.05;9.56] W·kg-1 in the stroke group. EEACC and EEMETA were not significantly correlated in either the control (p=0.8) or the stroke groups (p=0.06). The Bland-Altman method showed a mean difference of 1.77±3.65 W·kg-1 between EEACC and EEMETA in the stroke group and -2.08±1.59 W·kg-1 in the controls. Conclusions: The accuracy of the predicted EE, based on the accelerometer and the equations proposed by Bouten et al, is low in individuals with hemiparesis and impaired gait. This combination (sensor and Bouten's equation) is not yet suitable for use as a stand-alone measure in clinical practice for the evaluation of hemiparetic patients.

Hyperacusis, i.e., an increased sensitivity to sounds, is described in several neurodevelopmental disorders (NDDs), including Fragile X Syndrome (FXS). The mechanisms underlying hyperacusis in FXS are still largely unknown and effective therapies are lacking. Big conductance calci-um-activated potassium (BKCa) channels have been proposed as a therapeutic target to treat several behavioral disturbances in FXS preclinical models, but their role in mediating their au-ditory alterations has not been specifically addressed. Furthermore, studies on the acoustic phe-notypes of FXS animal models have mostly focused on central rather than peripheral auditory pathways. Here we provided an extensive characterization of the peripheral auditory phenotype of the Fmr1-knockout (KO) mouse model of FXS at adulthood. We also assessed whether the acute administration of Chlorzoxazone, a BKCa agonist, could rescue the auditory abnormalities of mutant mice. Fmr1-KO mice both at 3 and 6 months showed a hyperacusis-like startle pheno-type with paradoxically reduced auditory brainstem responses associated with a loss of ribbon synapses in the inner hair cells (IHCs). BKCa expression was markedly reduced in the IHCs of KO mice, but only at 6 months, when Chlorzoxazone rescued mutant auditory dysfunction. Our findings highlight the age-dependent and progressive contribution of peripheral mechanisms and BKCa channels to hyperacusis in FXS, suggesting a novel therapeutic target to treat auditory dysfunction in NDDs.

The aim of this paper is to apply all the existing pyranometric method, to estimate the sunshine duration from the global solar irradiation, in order to find in their original form the most suitable method for a tropical site. Then, in a second step, one of these methods will be optimized to well fit tropical sites. Five methods in the literature (Step Algorithm, Carpentras Algorithm, Slob & Monna Algorithm, Slob & Monna 2 Algorithm, and Linear Algorithm) were applied with eleven years of global and diffuse solar radiation data. As a result, in their original form, the Step Algorithm is on the first rank. But in the second step, after improving its main coefficients, the Carpentras Algorithm was found to be the best algorithm for tropical site in the southern hemisphere.

The present work describes the synthesis, characterization and photomineralization activity of synthesized Ce1-xZnxO2-x solid solution catalysts allowing the degradation of Diclofenac as a model of anti-inflammatory medicines in water. Oxygen deficient photocatalysts Ce1-xZnxO2-x (CeZnx), produced with mixing ZnO and CeO2 have been characterized for their crystallographic parameters, specific surface area and morphology. Photomineralization activity determinations using TOC analysis have shown efficient diclofenac photooxidation under sunlight. Moreover, results indicate that coexistence of Zn2+, Ce4+ and oxygen vacancies rate in CeZnx solid solution are key factors for strong drug mineralization. Finally, CeZn0.1 which is one of the photocatalysts synthesized in the present work represents a cheap and efficient reagent for organic matter photomineralization in wastewater.

In any document, graphical elements like tables, figures, and formulas contain essential information. The processing and interpretation of such information require specialized algorithms. Off-the-shelf OCR components cannot process this information reliably. Therefore, an essential step in document analysis pipelines is to detect these graphical components. It leads to a high-level conceptual understanding of the documents that makes digitization of documents viable. Since the advent of deep learning, the performance of deep learning-based object detection has improved many folds. In this work, we outline and summarize the deep learning approaches for detecting graphical page objects in the document images. Therefore, we discuss the most relevant deep learning-based approaches and state-of-the-art graphical page object detection in document images. This work provides a comprehensive understanding of the current state-of-the-art and related challenges. Furthermore, we discuss leading datasets along with the quantitative evaluation. Moreover, it discusses briefly the promising directions that can be utilized for further improvements.

Recent progress in deep learning has led to accurate and efficient generic object detection networks. Training of highly reliable models depends on large datasets with highly textured and rich images. However, in real-world scenarios, the performance of the generic object detection system decreases when (i) occlusions hide the objects, (ii) objects are present in low-light images, or (iii) they are merged with background information. In this paper, we refer to all these situations as challenging environments. With the recent rapid development in generic object detection algorithms, notable progress has been observed in the field of object detection in challenging environments. However, there is no consolidated reference to cover state-of-the-art in this domain. To the best of our knowledge, this paper presents the first comprehensive overview, covering recent approaches that have tackled the problem of object detection in challenging environments. Furthermore, we present the quantitative and qualitative performance analysis of these approaches and discuss the currently available challenging datasets. Moreover, this paper investigates the performance of current state-of-the-art generic object detection algorithms by benchmarking results on the three well-known challenging datasets. Finally, we highlight several current shortcomings and outline future directions.

The cytoskeleton is a master organizer of cell cortex, organelles positioning and membrane trafficking. Therefore, playing a decisive role in establishment of apico-basal polarity. Septins are critical cytoskeleton components which function in apico-basal polarity remain weakly investigated. Here, using 3D culture system, we demonstrate that septin9 localizes at basolateral membrane (BM). Its depletion induces an inverted polarity phenotype, decreasing -catenin at BM and increasing the expression of the transforming growth factor (TGF) and the epithelial-to-mesenchymal transition (EMT) markers. Similar effects were observed upon deleting its two polybasic domains, and the mutant become cytoplasmic and apical. The cysts with an inverted polarity phenotype display an invasive phenotype, with src and cortactin accumulating at the peripheric membrane. Inhibition of TGF-receptor and RhoA rescues the polarized phenotype. Although the cysts from overexpressed-septin 9, overgrowth and present a filled lumen. Both phenotypes correspond to tumor features. This suggests that septin 9 expression and assembly through the two PB domains are essential for establishing and maintaining apico-basal polarity against tumor development through a mechanism involving TGF-dependent EMT and RhoA activity.

Myocarditis has been recognized as a possible rare complication of COVID-19 mRNA vaccination. It concerns between one and five vaccinated people per 100,000 in the general population, with increased incidence in adolescent and young adult men. Most often, cases of myocarditis have been reported in the days following the second dose of vaccine mainly in younger male patients. This rare complication of vaccination usually resolves within days or weeks. However, the pathophysiological events responsible for the increase in frequency of myocarditis after COVID-19 vaccination remain unclear. Several recent reports have highlighted that free spike proteins circulating in the blood of patients at high levels appear to play a major role in myocarditis. Here, we review the most relevant data that partly lift the veil on the molecular mechanisms of the induction of myocarditis following mRNA-based COVID-19 vaccination. We hypothesize that a mechanism of molecular mimicry of the viral spike triggers transient dysregulation of angiotensin-converting enzyme 2, leading to increased soluble angiotensin II binding to the transmembrane receptor angiotensin II type I receptor, similar to what is observed during SARS-CoV-2 infection. We suggest to standardize management of suspected cases of mRNA-based COVID-19 vaccine-induced myocarditis, including angiotensin II and spike antigenemia monitoring.

The aim of this publication is to analyze the topic of high-frequency jet ventilation (HFJV), namely the catheter HFJV (C-HFJV) from a mathematical-physical as well as a clinical point of view. There are known issues with applying anesthesia and artificial lung ventilation (ALV) during surgical procedures in the upper airways, e.g. during bronchoscopy or tracheostomy. The principles, advantages, and disadvantages of HFJV are discussed in context with basic physical principles to clarify the proper use of this method. The basic technical principles of catheter construction, as well as its functional properties from a biophysical point of view, are introduced. Also, the placement of the catheter in the airways, the set-up of the HFJV ventilator, and the indications as well as the risks and contraindications of the use of C-HFJV are analyzed. This leads to the explanation of potentially optimal techniques for C-HFJV applications. In this article, we present the positive effects of C-HFJV even with complications such as bacterial or viral pneumonia, including COVID-19. In conclusion, we offer recommendations for clinical practice obtained from a literature review as well as from our own rich clinical experience.

This study presents the utilization of the Microwave InfraRed Thermography (MIRT) technique to identify and analyze the defects in the carbon-fiber-reinforced polymer (CFRP) composite rein-forcement of concrete specimens. At first, a set of the numerical models was created, comprising of the broadband pyramidal horn antenna and the analyzed specimen. The utilization the system operating at a power of 1000W in a continuous mode, operating at frequency of 2.45 GHz was analyzed. The specimen under examination comprised a compact concrete slab that was covered with an adhesive layer, thereafter, topped with a layer of CFRP. An air gap represented a defect at the interface between the concrete and CFRP within the adhesive layer. In the modelling stage the study investigated three separate scenarios: a sample with no defects, a sample with a defect located at the center, and a sample with a numerous additional random defects located at the rim of the CFRP matte, to analyze the effect of the natural reinforcement degradation in this area. The next phase of the study involved conducting experiments to confirm the results obtained from nu-merical modeling. In the experiments the concrete sample aged for 10 years with the defect in the center and naturally developed defects at the CFRP rim was used. The study employed numerical modeling to explore the phenomenon of microwave heating in complex structures. The aim was to assess the chosen antenna design and identify the most effective experimental setup. These con-clusions were subsequently confirmed through experimentation. The observations made during the heating process were particularly remarkable, since they deviated from earlier studies that solely conducted measurements of the sample post-heating phase. The findings demonstrate that MIRT has the capacity to be employed as a technique for detecting flaws in concrete structures reinforced with CFRP.

In recent years, due to the advancement of machine learning, object detection has become a mainstream task in the computer vision domain. The first phase of object detection is to find the regions where objects can exist. With the improvement of deep learning, traditional approaches such as sliding windows and manual feature selection techniques have been replaced with deep learning techniques. However, object detection algorithms face a problem when performing in low light, challenging weather, and crowded scenes like any other task. Such an environment is termed a challenging environment. This paper exploits pixel-level information to improve detection under challenging situations. To this end, we exploit the recently proposed hybrid task cascade network. This network works collaboratively with detection and segmentation heads at different cascade levels. We evaluate the proposed methods on three complex datasets of ExDark, CURE-TSD, and RESIDE and achieve an mAP of 0.71, 0.52, and 0.43, respectively. Our experimental results assert the efficacy of the proposed approach.

This work presents an approach for detecting mathematical formulas in scanned document images. The proposed approach is end-to-end trainable. Since many OCR engines cannot reliably work with the formulas, it is essential to isolate them to obtain the clean text for information extraction from the document. Our proposed pipeline comprises a hybrid task cascade network with deformable convolutions and a Resnext101 backbone. Both of these modifications help in better detection. We evaluate the proposed approaches on the ICDAR-2017 POD and Marmot datasets and achieve an overall accuracy of 96% for the ICDAR-2017 POD dataset. We achieve an overall reduction of error of 13%. Furthermore, the results on Marmot datasets are improved for the isolated and embedded formulas. We achieved an accuracy of 98.78% for the isolated formula and 90.21% overall accuracy for embedded formulas. Consequently, it results in an error reduction rate of 43% for isolated and 17.9% for embedded formulas.

This paper presents a novel architecture for detecting mathematical formulas in document images, which is an important step for reliable information extraction in several domains. Recently, Cascade Mask R-CNN networks have been introduced to solve object detection in computer vision. In this paper, we suggest a couple of modifications to the existing Cascade Mask R-CNN architecture: First, the proposed network uses deformable convolutions instead of conventional convolutions in the backbone network to spot areas of interest better. Second, it uses a dual backbone of ResNeXt-101, having composite connections at the parallel stages. Finally, our proposed network is end-to-end trainable. We evaluate the proposed approach on the ICDAR-2017 POD and Marmot datasets. The proposed approach demonstrates state-of-the-art performance on ICDAR-2017 POD at a higher IoU threshold with an f1-score of 0.917, reducing the relative error by 7.8%. Moreover, we accomplished correct detection accuracy of 81.3% on embedded formulas on the Marmot dataset, which results in a relative error reduction of 30%.

The growing amount of data demands methods that can gradually learn from new samples. However, it is not trivial to continually train a network. Retraining a network with new data usually results in a known phenomenon, called “catastrophic forgetting.” In a nutshell, the performance of the model drops on the previous data by learning from the new instances. This paper explores this issue in the table detection problem. While there are multiple datasets and sophisticated methods for table detection, the utilization of continual learning techniques in this domain was not studied. We employed an effective technique called experience replay and performed extensive experiments on several datasets to investigate the effects of catastrophic forgetting. Results show that our proposed approach mitigates the performance drop by 15 percent. To the best of our knowledge, this is the first time that continual learning techniques are adopted for table detection, and we hope this stands as a baseline for future research.

In this paper, we propose a novel approach to utilize silicon nanowires as high-sensitivity pH sensors. Our approach works based on fixing the current bias of silicon nanowires Ion Sensitive Field Effect Transistors (ISFETs) and monitor the resulting drain voltage as the sensing signal. By fine tuning the injected current levels, we can optimize the sensing conditions according to different sensor requirements. This method proves to be highly suitable for real-time and continuous measurements of biomarkers in human biofluids. To validate our approach, we conducted experiments, with real human sera samples to simulate the composition of human interstitial fluid (ISF), using both the conventional top-gate approach and the optimized constant current method . We successfully demonstrated pH sensing within the physiopathological range of 6.5 to 8, achieving an exceptional level of accuracy in this complex matrix. Specifically, we obtained a maximum error as low as 0.92\% (equivalent to 0.07 pH unit) using the constant-current method at the optimal current levels (1.71\% for top-gate). Moreover, by utilizing different pools of human sera with varying total protein content, we demonstrated that the protein content among patients does not impact the sensors' performance in pH sensing. Furthermore, we tested real-human ISF samples collected from volunteers. The obtained accuracy in this scenario was also outstanding, with an error as low as 0.015 pH unit using the constant-current method and 0.178 pH unit in traditional top-gate configuration.

In France, veterinarians are allowed to both prescribe and deliver drugs, a questioned situation from the perspective of antimicrobial use (AMU) reduction in order to ovoid AM resistance (AMR). This situation places veterinarians in direct commercial relationships with the pharmaceutical industry. The present study aims to describe contracts between pharmaceutical companies and veterinarians during the period 2008-2014. 382 contracts related to 47 drugs belonging to the 8 main pharmaceutical firms (2,320 observations) in France were collected. The price per unit after rebate (PUR) was calculated for each drug and contract. The descriptive analysis demonstrated a high disparity between the content of contracts and the way in which they are presented. A linear regression was then used to explain the PUR with the explanatory variables, which were the yearly purchase objective, the year, the type of drug and type of rebate. The decrease in PUR for each extra €1,000 objective per drug category was established to be €0.061 per 100 kg body weight (BW) for anticoccidiosis treatments, €0.029 per 100 kg BW for anti-inflammatories, €0.0125 per 100 kg BW, €0.0845 per animal for antiparasitics, and €0.031 per animal for intramammary antimicrobials. Applying agency theory shows that veterinarians can be considered the agents in case of monopolistic or oligopolistic situations of pharmaceutical firms, they are considered the principals otherwise. Policies that focus on maintaining veterinarians as principals may help reach the better societal benefit since this helps them maintain access to veterinary services throughout the region at low public cost while being liable for AMU.

3D reconstruction from a single 2D input is a classic problem in the field of computer vision. With the advancements in deep learning, the performance of 3D reconstruction has also significantly improved. The reconstruction task is more difficult for objects with no textures or complex deformations. This paper serves as a review of recent literature on 3D reconstruction from a single view, with a focus on deep learning methods from 2018 to 2021. Due to lack of standard datasets or 3D shape representation methods, it is hard make direct comparisons between all reviewed methods. However, this paper reviews different approaches for reconstructing 3d shape as depth maps, surface normals, point clouds and meshes; along with various loss functions and evaluation metrics used to train and evaluate these methods.

The goal of this article was to evaluate the antioxidant and anti-inflammatory like activities of three species from genus Primula L. growing in Georgia: Primula macrocalyx, Primula woronowii and Primula saguramica . First, fractions containing shoot and root parts were air-dried, grinded and extracted by 80% ethanol followed by condensation and freeze-drying. Second, further chromatographic separations were done on Diaion HP-20 with the following solvents: H2O, methanol (50% and 100 %) and ethylacetate 100% to obtain the expected fractions.

Open-cell metallic foams used as catalyst supports exhibit excellent transport properties. In this work, a unique application of metallic foam, as pelletized catalyst in a packed bed reactor, is examined. By using a wall-segment Computational Fluid Dynamics (CFD) setup, parametric analyses are carried out to investigate the influence of foam morphologies (cell size ϕ=0.45-3 mm and porosity ε=0.55-0.95) and intrinsic conductivity on flow and heat transport characteristics in a slender packed bed (N=Ddp=6.78) made of cylindrical metallic foam pellets. The transport processes have been modeled using an extended version of conventional particle-resolved CFD, i.e., flow and energy in inter-particle spaces are fully resolved, whereas porous-media model is used for the effective transport processes inside highly-porous foam pellets. Simulation inputs include the processing parameters relevant to Steam Methane Reforming (SMR), analyzed for low (Rep~100) and high (Rep~5000) flow regimes. The effect of foam morphologies on packed beds has shown that the desired requirements contradict each other, i.e., increase in cell size and porosity favor the reduction in pressure drop, however lowering the heat transfer efficiency. A design study is also conducted to find the optimum foam morphology of a cylindrical foam pellet at higher Rep~5000, which yields ϕ = 0.45, ε = 0.8. Suitable correlations to predict the friction factor and the overall heat transfer coefficient in a foam packed bed have been presented, which considers the effect of different foam morphologies over a range of particle Reynolds number, 100≤Rep≤5000.

Tables in the document image are one of the most important entities since they contain crucial information. Therefore, accurate table detection can significantly improve information extraction from tables. In this work, we present a novel end-to-end trainable pipeline, HybridTabNet, for table detection in scanned document images. Our two-stage table detector uses the ResNeXt-101 backbone for feature extraction and Hybrid Task Cascade (HTC) to localize the tables in scanned document images. Moreover, we replace conventional convolutions with deformable convolutions in the backbone network. This enables our network to detect tables of arbitrary layouts precisely. We evaluate our approach comprehensively on ICDAR-13, ICDAR-17 POD, ICDAR-19, TableBank, Marmot, and UNLV. Apart from the ICDAR-17 POD dataset, our proposed HybridTabNet outperforms earlier state-of-the-art results without depending on pre and post-processing steps. Furthermore, to investigate how the proposed method generalizes unseen data, we conduct an exhaustive leave-one-out-evaluation. In comparison to prior state-of-the-art results, our method reduces the relative error by 27.57% on ICDAR-2019-TrackA-Modern, 42.64% on TableBank (Latex), 41.33% on TableBank (Word), 55.73% on TableBank (Latex + Word), 10% on Marmot, and 9.67% on UNLV dataset. The achieved results reflect the superior performance of the proposed method.

In the present, the growth of digitization and worldwide communications make OCR systems of exotic languages a very important task. In this paper, we attempt to develop an OCR system for one of these exotic languages with a unique script, Amharic. Motivated by the recent success of the Attention mechanism in Neural Machine Translation (NMT), we extend the attention mechanism for Amharic text-image recognition. The proposed model consists of CNNs and attention embedded recurrent encoder-decoder networks that are integrated following the configuration of the seq2seq framework. The attention network parameters are trained in an end-to-end fashion and the context vector is injected, with the previously predicted output, at each time steps of decoding. Unlike the existing OCR model that minimizes the CTC objective function, the new model minimizes the categorical cross-entropy loss. The performance of the proposed attention-based model is evaluated against the test dataset from the ADOCR database which consists of both printed and synthetically generated Amharic text-line images and achieved promising results with a CER of 1.54% and 1.17% respectively.

Biomimetic compounds are an alternative for to the limited action and fragile nature of enzymes. This work deals with the synthesis, characterization and evaluation of catalytic activity of two new biomimetic models for the active centers of ascorbate oxidase and catalase. [Cu3(S,S(+)cpse)3(H2O)3][Cu3(R,R(-)cpse)3(H2O)3]·17H2O (model for ascorbate oxidase, 1), and [Mn2(S,S(+)Hcpse)4(NaClO4)2(NaOH)(CH4O)]n·[(C2H6O)2]n·[(CH4O)2]n (model for catalase, 2) were prepared through the synchronic method (yields > 78%). The compound 1 has electronic and optical characteristics for racemic compound. The magnetic properties and electrochemical behavior evidence electronic transfer between metal centers. Meanwhile, the compound 2 showed polymeric properties in solid state and dimeric behavior in solution. Compound 1 was able to effectively catalyze the oxidation of ascorbic acid to dehydroascorbic acid (65.6% and 78.24% for racemic and enantiomeric pure compounds) showing structural and functional similarity to the natural enzyme. Besides, Compound 2 catalyzed the decomposition of hydrogen peroxide toward oxygen and water molecules (45%), evidencing that the prepared complex mimics the action of catalases. These two biomimetic models are relationship between them for the structural ligands, the coordination form to metal center and the catalytic activity as oxidase. This research shows the relationship with the design, evaluation, and comprehension of fundamentals aspects for the biomimetic models of active center of metalloenzymes that have importance for biological and industrial processes.

Document classification is one of the most critical steps in the document analysis pipeline. There are two types of approaches for document classification, known as image-based and multimodal approaches. The image-based document classification approaches are solely based on the inherent visual cues of the document images. In contrast, the multimodal approach co-learns the visual and textual features, and it has proved to be more effective. Nonetheless, these approaches require a huge amount of data. This paper presents a novel approach for document classification that works with a small amount of data and outperforms other approaches. The proposed approach incorporates a hierarchical attention network(HAN) for the textual stream and the EfficientNet-B0 for the image stream. The hierarchical attention network in the textual stream uses the dynamic word embedding through fine-tuned BERT. HAN incorporates both the word level and sentence level features. While the earlier approaches rely on training on a large corpus (RVL-CDIP), we show that our approach works with a small amount of data (Tobacco-3482). To this end, we trained the neural network at Tobacco-3428 from scratch. Thereby, we outperform state-of-the-art by obtaining an accuracy of 90.3%. This results in a relative error reduction rate of 7.9%.

Research has been growing on object detection using semi-supervised methods in past few years. We examine the intersection of these two areas for floor-plan objects to promote the research objective of detecting more accurate objects with less labelled data. The floor-plan objects include different furniture items with multiple types of the same class, and this high inter-class similarity impacts the performance of prior methods. In this paper, we present Mask R-CNN based semi-supervised approach that provides pixel-to-pixel alignment to generate individual annotation masks for each class to mine the inter-class similarity. The semi-supervised approach has a student-teacher network that pulls information from the teacher network and feeds it to the student network. The teacher network uses unlabeled data to form pseudo-boxes, and the student network uses both unlabeled data with the pseudo boxes and labelled data as ground truth for training. It learns representations of furniture items by combining labelled and unlabeled data. On the Mask R-CNN detector with ResNet-101 backbone network, the proposed approach achieves mAP of 98.8%, 99.7%, and 99.8% with only 1%, 5% and 10% labelled data, respectively. Our experiment affirms the efficiency of the proposed approach as it outperforms the fully supervised counterpart using only 10% of the labels.

Object detection is one of the most critical tasks in the field of Computer vision. This task comprises identifying and localizing an object in the image. Architectural floor plans represent the layout of buildings and apartments. The floor plans consist of walls, windows, stairs, and other furniture objects. While recognizing floor plan objects is straightforward for humans, automatically processing floor plans and recognizing objects is a challenging problem. In this work, we investigate the performance of the recently introduced Cascade Mask R-CNN network to solve object detection in floor plan images. Furthermore, we experimentally establish that deformable convolution works better than conventional convolutions in the proposed framework. Identifying objects in floor plan images is also challenging due to the variety of floor plans and different objects. We faced a problem in training our network because of the lack of publicly available datasets. Currently, available public datasets do not have enough images to train deep neural networks efficiently. We introduce SFPI, a novel synthetic floor plan dataset consisting of 10000 images to address this issue. Our proposed method conveniently surpasses the previous state-of-the-art results on the SESYD dataset and sets impressive baseline results on the proposed SFPI dataset. The dataset can be downloaded from SFPI Dataset Link. We believe that the novel dataset enables the researcher to enhance the research in this domain further.

Polyethylene terephthalate (PET) is nowadays one of the most used polymers for packaging applications. Modifications induced by service conditions and the optimal mean to recycle this matter several times have to be perfectly understood to allow a reuse for similar application (from bottle to bottle for example). The present study aims to compare physico-chemical properties, crystalline organization, and mechanical behaviour of virgin (vPET) and recycled PET (rPET). Using different combined experimental methods (Calorimetry, Small Angle X-ray Scattering, Atomic Force Microscopy, DMA, and uni-axial tensile test), it has been proven that even if there is no change in the crystallinity of PET, the crystallisation process shows some differences (size and number of spherulites). The potential impact of these differences on local mechanical characterization, at the lamella scale, is explored and tends to demonstrate the development of homogeneous microstructure, leading to well-controlled and relevant local mechanical properties. This approach increases the understanding of crystallisation of PET and recycled PET during forming processes such as thermoforming or injection stretch blow moulding (ISBM) where elongation at break can depend on the microstructure conditioned by the crystallisation process.

Background: Sickle cell disease (SCD) is a public health problem in the Democratic Republic of Congo. While reference sickle cell centers have been implemented in capital cities of African countries and have proven to be beneficial for SCD patients, they have never been set up in rural areas for families with very low sources of income. Method: A cohort of 143 children with SCD aged 10 years old (IQR (interquartile range): 6–15 years) (sex ratio male/female = 1.3) were clinically followed for 12 months without any specific intervention aside from the management of acute events, and then for 12 months with a monthly medical visit, biological follow-up, and regular prophylaxis. Results: The median age of patients at the diagnosis of SCD was 2 years (IQR: 1–5). The implementation of standardized and regular follow-ups in a new sickle cell referral center in a remote city showed an increase in the annual mean hemoglobin level from 50 to 70 g/L (p = 0.001), and a decrease in the lymphocyte count and spleen size (p < 0.001). A significant decrease (p < 0.001) in the average annual number of hospitalizations and episodes of vaso-occlusive crises, blood transfusions, infections, and acute chest syndromes were also observed. Conclusions: Creation of a sickle cell referral center and the regular follow-up of children with SCD are possible and applicable in the context of a remote city of an African country and represent simple and accessible measures that can reduce the morbimortality of children with sickle cell disease.

Environmental policy involving citizen science (CS) is of growing interest. In support of this open data stream, validation or quality assessment of the CS data and their appropriate usage for evidence-based policy making, needs a flexible and easily adaptable data curation process ensuring transparency. Addressing these needs, this paper describes an approach for automatic quality assurance as proposed by the Citizen OBservatory WEB (COBWEB) FP7 project. This approach is based upon a workflow composition that combines different quality controls, each belonging to seven categories or ‘pillars’. Each pillar focuses on a specific dimension in the types of reasoning algorithms for CS data qualification. These pillars attribute values to a range of quality elements belonging to three complementary quality models. Additional data from various sources, such as Earth Observation (EO) data, are often included as part of the inputs of quality controls within the pillars. However, qualified CS data can also contribute to the validation of EO data. Therefore, the question of validation can be considered as ‘two sides of the same coin’. Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper discusses the flexibility and usefulness of qualifying CS data, either when using an EO data for the validation within the quality assurance process, or validating an EO data product that describes the risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality assurance for validation, due to the quality of secondary data used within the automatic workflow, are described, e.g. error propagation, paving the route to improvements in the approach.

The probability of the evolution of a character depends on two factors: the probability of moving from one character state to another character state and the probability of the new character state fixation. More the evolution of a character is probable more convergent evolution will be witnessed, consequently, convergent evolution could mean that the convergent character evolution result as a combination of these two factors. We investigate this phenomenon by studying the convergent evolution of biochemical functions. We use for the investigation the case of β-lactamases. β-lactamases hydrolyzes β-lactams which are antimicrobials able to block the DD-peptidases involved in bacterial cell wall synthesis. β-lactamase activity is present in two different superfamilies: the metallo-β-lactamase and the serine β-lactamase superfamily. The mechanism used to hydrolyze the β-lactam is different for the two superfamilies. We named this kind of evolution an allo-convergent evolution. We further show that the β-lactamase activity evolved several times within each superfamily, a convergent evolution type that we named iso-convergent evolution. Both types of convergent evolution can be explained by the two evolutionary mechanisms discussed above. The probability of moving from one state to another is explaining the promiscuous β-lactamase activity present in the ancestral sequences of each superfamily, while the probability of fixation is explained in part, by positive selection as the organisms having β-lactamase activity allows them to resist to organism secreting β-lactams. Indeed a mutation increasing the β-lactamases activity will be selected as the organisms having this activity will have an advantage over the others.

Pediculus humanus capitis, the head louse, is an obligate blood-sucking ectoparasite that occurs in six divergent mitochondrial haplogroups (A, D, B, F, C and E), each exhibiting a particular geographic distribution. A few years ago, several studies reported the presence of different pathogenic agents in head lice specimens from different clades collected worldwide. These findings suggest that head louse could be a vector for dangerous diseases and therefore a serious public health problem. Herein, we aimed to study the mitochondrial genetic diversity, the PHUM540560 gene polymorphisms profile of head lice collected in Guinea, as well as to screen for the pathogens present in these lice. In 2018, a total of 155 head lice were collected from 49 individuals at the Medicals Centers of rural (Maférinyah village) and urban (Kindia city) areas, in Guinea. All head lice were subjected to genetic analysis and screened for the presence of several pathogens using molecular tools. The results showed that all head lice belonged to the haplogroups C/E using the duplex qPCR which detects both clades. Standard PCR and sequencing revealed that all specimens belonged to the haplogroup E, including 8 haplotypes, whither 6 new identified for the first time in this study. The study of the PHUM540560 gene polymorphisms in our Guinean head lice revealed that 7/40 (17.5%) of our tested samples exhibit three different polymorphism profiles compared to the clade A-head lice PHUM540560 gene profile, while the remaining specimens 33/40 (82,5%) showed the same PHUM540560 gene polymorphism profile as the previously reported clade A-body lice. Molecular investigations of the targeted pathogens revealed only the presence of Acinetobacter species in 9% of our samples using real time PCR. Sequencing results identified highlighted the presence of several Acinetobacter species, including Acinetobacter baumannii (14.3%), Acinetobacter nosocomialis (14.3%), Acinetobacter variabilis (14.3%), Acinetobacter haemolyticus (7.2%), Acinetobacter towneri (7.2%). Furthermore, a candidate new species of Acinetobacter sp. (7.2%) was detected. Positive specimens were collected from 24,5% individuals in Maférinyah. We also investigated in our study the carbapenem’s-resistant profile of A. baumannii, none of our specimens were positive for the following resistance genes blaOXA-21, blaOXA-24 and blaOXA-58. To the best of our knowledge, our study is the first to report the existence of the Guinean haplogroup E, the PHUM540560 gene polymorphism profile as well as the presence of Acinetobacter species in head lice collected from Guinea.

Gastric mixing relies both on enzymatic reactions and mechanical solicitations through antral contraction waves (ACWs). This work aims at discussing the influence of ACWs frequency and digesta viscosity on human gastric mixing efficiency by comparison with that of a soft elastic reactor (SER), that induces mixing by vibration of its wall in a similar way as ACWs promote stomach motility. The SER mixing curve was considered in order to determine the flow regime reached during gastric mixing. The number of contractions required to achieve homogenization was found to depend on the viscosity of the stomach content and the ACWs amplitude. Moreover, it was deduced from the same range of SER and ACWs operating points that the mechanical solicitation provided by human peristalsis was low and that gastric mixing was confined in laminar regime. Further efforts are needed to investigate the role of other physiological processes such as gastric secretions and emptying in overall gastric mixing performance.

Depth maps produced by LiDAR based approaches are sparse. Even high-end LiDAR sensors produce highly sparse depth maps, which are also noisy around the object boundaries. Depth completion is the task of generating a dense depth map from a sparse depth map. While the traditional approaches focus on directly completing this sparsity from the sparse depth maps, modern techniques use RGB images as a guidance tool to resolve this problem. Whilst many others rely on affinity matrices for depth completion. Based on these approaches, we have sub-divided the literature into two major categories; traditional approaches and backbone-based approaches. The latter is further sub-divided into two-branch, and spatial propagation approaches. The two-branch approaches still have a sub-category named guided-kernel approaches. In this paper, for the first time ever we present a comprehensive survey of depth completion methods. We present a novel taxonomy of depth completion approaches, review and detail different state-of-the art techniques within each category for depth completion of LiDAR data, and provide quantitative results for the approaches on KITTI and NYUv2 depth completion benchmark datasets.

COVID-19 is a novel severe acute respiratory syndrome coronavirus. Presently, there is no effective treatment for COVID-19. As part of the worldwide efforts to find efficient therapies and preventions, it has been reported the crystalline structure of the SARS-CoV-2 main protease Mpro (also called 3CL^pro) bound to a synthetic inhibitor which represents a major druggable target. The druggability of Mpro could be used for discovering drugs to treat coronavirus disease 2019. It was carried out a multi-level computational study to evaluate the potential anti-viral properties of the components of the medicinal herb Uncaria tomentosa (Cat´s claw) focusing on the inhibition of M^pro. The in-silico approach starts with protein-ligand docking of 26 Cat’s claw key components followed by ligand pathway calculations, molecular dynamics simulations and MM-GBSA calculation of the free energy of binding for the best docked candidates. The structural bioinformatics approaches led to the identification of three bioactive compounds of Uncaria tomentosa (Speciophylline, Cadambine and Proanthocyanidin B2) with potential therapeutic effects by strong interaction with 3CLpro. Additionally, in silico drug-likeness indices for these components were calculated and show good predicted therapeutic profiles of these phytochemicals. Our findings suggest the potential effectiveness of Cat's claw as complementary and/or alternative medicine for COVID-19 treatment.

: Foodshed approaches allow the assessment of the theoretical food self-sufficiency capacity of a specific region based on biophysical conditions. Recent analyses show that the focus needs to be shifted from foodshed size portrayed as an isotropic circle to a commodity-group-specific spatial configuration of the foodshed that takes into account the socio-economic and biophysical conditions essential to the development of local food supply chains. We focus on a specific animal product (beef) and use an innovative modeling approach based on spatial analysis to detect the areas of the foodshed dedicated to beef feeding (forage, pasture, and grassland), considering the foodshed as a complex of complementary areas called an archipelago. We use available statistical data including a census to address the city-region of Avignon (France) covering a 100 km radius. Our results show that the factors driving the use of short supply chains for beef feeding areas are the foodshed archipelago’s number of patches, the connectivity between them, and the rugosity of the boundaries. In addition, our beef self-sufficiency assessment results differ depending on geographical context. For instance, being located within the perimeters of a nature park seems to help orient beef production towards short supply chains. We discuss possible leverage for public action to reconnect beef production areas to consumption areas (the city) via short supply chains (e.g. green, home-grown school food programs) so as to increase local food security through increased local food self-sufficiency.

This study presents a methodology to fabricate Ti6Al4V cylindrical compacts with a highly porous core and dense shell with the purpose to mimic the bone microstructure. Compacts with different core diameters were obtained by conventionally press and sintering. Large pores were created with the aid of pore formers. Sintering kinetics was determined by dilatometry, whereas characterization was performed by X-ray computed tomography. Also, permeability was evaluated on the 3D microstructure and the mechanical strength was evaluated by compression tests. Results indicated that sintering is constraint by the different densification rates of the porous and dense layers. Nonetheless, defectless compacts were obtained due to neck bonding between Ti6Al4V particles. Large pores were located in the designed core with similar pore size distribution. Permeability increased following a power law as a function of the pore volume fraction. Stiffness of bilayer components was driven by the porous core, meanwhile, the strength resulted from the combination of both layers. Bilayer materials obtained showed a permeability and mechanical properties, as well as admissible strain (σy /E) similar to those of human bones.

Blood and/or urine levels of 27 heavy metals were determined by ICPMS in 41 patients with dilated cardiomyopathy (DCM) and 29 presumably healthy subjects from the Katanga Copperbelt (KC), in the Democratic Republic of Congo (DRC). After adjusting for age, gender, education level, and renal function, DCM probability was almost maximal for blood concentrations above 0.75 and 150 µg/dl for arsenic and copper, respectively. Urinary concentrations above 1 for chromium, 20 for copper, 600 for zinc, 30 for selenium, 2 for cadmium, 0.2 for antimony, 0.5 for thallium and 0.05 for uranium, all in μg/g of creatinine, were also associated with increased DCM probability. Concurrent and multiple exposures to heavy metals, well beyond permissible levels, are associated with increased probability for DCM. Study findings warrant screening for metal toxicity in case of DCM and prompt public health measures to reduce exposures in the KC, DRC.

Abstract: Turmeric is a plant with multiple medicinal attributes. One of them being its analgesic effect. In this project the analgesic effect of the plant was evaluated with an inflammatory pain model: the 5% formalin model. Turmeric was administered to 250 g male Wistar rats (6 ± 2) provided by the Health Science department’s vivarium. The dose-response curve of the plant was per-formed observing the analgesic effect. Once the dose was selected, they were administrated within different turmeric protocols. 400 mg orally every 24 h for two weeks, another group with turmeric ad libitum for two weeks, the control group with 0.9% saline solution for two weeks, and a group with administration of metamizole prior to evaluation with 5% formalin. Subsequently, each rat was evaluated by 5% formalin intraplantarly and the number of rat paw twitches per 1 h was observed. The analysis of the data generated through the obtained results was carried out. The dose of 400 mg of oral turmeric was administered for two weeks without observing any collateral effects. An excellent analgesic effect was found in this protocol, as well as, in the ad libitum administration for two weeks compared to the control group. Likewise, turmeric presents a milder effect than metamizole, a well-known analgesic.

This article presents a decentralized phase-shedding technique for multiphase converters. The usual central digital controller is replaced by identical local controllers forming a daisy-chain structure. Phase-shedding decisions are taken locally based on a local inductor current monitoring and threshold crossing management. This control strategy allows to implement as many phases as desired in a modular manner. In order to handle specific events such as load current inrush or a start-up sequence and to guarantee optimal transient responses, additional functions are included into each local controllers. The inter-cell communication protocol is described, along with necessary design considerations of threshold and timing values. Finally, functional simulations are carried out on a 5-leg 12V/1.2V 60W multiphase converter, which validate the proposed decentralized phase-shedding strategy for a microcontroller power supply implementation.

We assessed the use of Evidence-Based Practice (EBP) among pharmacists working in community pharmacies in France, and the factors linked to this practice. During 3 months in 2018 an online survey was sent to over 7,000 active pharmacists, and posted on pharmacist social media sites. The 40-item questionnaire described four clinical cases reflecting typical situations (conventional med-icine and Complementary and Alternative Medicine) encountered daily by community pharma-cists. Multiple-choice responses were proposed and scored according to whether they reflected EBP. A high total score indicated behavior in line with EBP. Univariate and multivariate analyses were used to evaluate factors that might explain adherence to EPB (pharmacy’s characteristics, the pharmacist’s status, mode of continuing education and sources of information). 595 pharmacists completed the questionnaire. The majority relied on pharmaceutical industry and other biased and/or non-evidence-based sources, particularly concerning information on homeopathic products. The consultation of independent reviews, health agency recommendations, and peer-reviewed scientific journals, was associated with evidence-based decisions. In contrast, reliance on phar-maceutical industry documents, personal experience and informal handbooks was linked to lower EBP scores. The level of EBP use by French community pharmacists needs to be improved to ensure that good quality scientifically-based advice is given to customers.

Background : The quantification of electromyographic activity using surface electrodes is inval-uable for understanding gait disorders in patients with central nervous system lesions. We propose to evaluate a commercially available low-cost system compared to a reference system in partic-ipants with stroke-related movement disorders in functional situations. Methods : Three hemiparetic participants performed three functional tasks: two treadmill walks at different speeds and a sit-to-stand test. The vastus lateralis and gastrocnemius medialis muscles were equipped with two EMG sensors. The comparison between the two EMG systems was based on 883 identified cycles. Spearman’s correlation coefficients (SC), linear correlation coefficients (LCC), and cross-correlation coefficients (CCC) were calculated. Results : The main results indicate good to very good similarity of the EMG signals collected from the two tested sEMG systems. In the comfortable walking condition, an SC of 0.894±0.091 and an LCC of 0.909±0.094 were noted. In the fast walking condition, an SC of 0.918±0.064 and an LCC of 0.935±0.056 were observed. For the 1-minute sit-to-stand test an SC of 0.880±0.058 and an LCC of 0.881±0.065 were noted. Conclusions : This study demonstrates good to very good similarity between the two sEMG systems, enabling the analysis of muscle activity during functional tasks.

The aim of this study is to evaluate the efficacy of taking a daily supplement based on active compounds (AUDISTIM® Day Night: A D/N) in alleviating tinnitus-related disability, as suggested by previous real-life studies. This double-blind randomized placebo-controlled study was conducted in adult with mild to severe tinnitus receiving a 3 month-supplementation. Tinnitus-related handicap (THI), psychological stress (MSP-9) and sleep quality (PSQI) were assessed at baseline and during intervention, perceived impression of tinnitus improvement at the end of the follow-up. The full set analysis included 114 patients (59 A D/N, 55 placebo) aged 53.8±11.4 years, 58% women, with fluctuating (45%) or permanent (55%) tinnitus from 9.3±9.4 years. A D/N supplementation led to greater changes in THI (-13.2±16.0 vs -6.2±14.4, p=0.0158, Cohen’s d=0.44) at 3 months, especially with continuous tinnitus (-15.0±16.3 vs -4.6±12.8, p=0.0065), and, to a lesser extent, at 1 month (-9.8±13.1 for A vs -4.3±12.1, p=0.0213). PSQI significantly improved over time in both groups, MSP-9 only with A D/N. In lines with previous observational studies, both clinical (THI score &gt; 7 pts) and statistical (vs. placebo) improvement, more pronounced in permanent tinnitus, demonstrate the effectiveness of the combination of active compounds and support its use in the management of mild to severe tinnitus.

Treatment with calcitriol, the hormonal form of vitamin D, has shown beneficial effects in ex-perimental models of acute lung injury. In this study we aimed to analyze the associations be-tween calcitriol supplementation and the risk of SARS-CoV2 infection or COVID-19 mortality. Individuals ≥18 years old living in Catalonia and supplemented with calcitriol from April 2019 to February 2020 were compared with propensity score matched controls. Outcome variables were SARS-CoV2 infection, severe COVID-19 and COVID-19 mortality. Associations between calcitriol supplementation and outcome variables were analyzed using multivariable Cox proportional regression. A total of 8076 patients were identified as being on calcitriol treatment. Advanced chronic kidney disease and hypoparathyroidism were the most frequent reasons for calcitriol supplementation in our population. Calcitriol use was associated with reduced risk of SARS-CoV2 infection (HR 0.78 [CI 95% 0.64-0.94], p=0.010), reduced risk of severe COVID-19 and reduced COVID-19 mortality (HR 0.57 (CI 95% 0.41-0.80), p=0.001) in patients with advanced chronic kidney disease. In addition, an inverse association between mean daily calcitriol dose and COVID-19 severity or mortality was observed in treated patients, independently of renal function. Our findings point out that patients with advanced chronic kidney disease could benefit from calcitriol supplementation during the COVID-19 pandemic.

Helicases are proteins that use the energy of ATP to unwind nucleic acids and to remodel protein-nucleic acid complexes. They are involved in almost every aspect of the DNA and RNA metabolisms and participate in numerous repair mechanisms that maintain cellular integrity. Helicases are classified into 6 superfamilies (SF1-6). The archaeal Lhr-type proteins are SF2 helicases that are mostly uncharacterized. They have been proposed to be a DNA helicase that acts in DNA recombination and repair processes in Sulfolobales and Methanothermobacter. In parallel, a protein annotated as an Lhr2 protein was also found in the network of proteins involved in RNA metabolism in Thermococcales. To this respect, we performed in-depth phylogenomic analyses to report the classification and taxonomic distribution of Lhr-type proteins in Archaea, and to better understand their relationship with bacterial Lhr. Furthermore, with the goal of envisioning the role(s) of aLhr2 in archaeal cells, we deciphered the enzymatic activities of aLhr2 from Thermococcus barophilus (Tbar). We showed that Tbar-aLhr2 is a DNA/RNA helicase acting on DNA:RNA and RNA:RNA duplexes and proposed that aLhr2 helicases are involved in processes dependent of DNA and RNA transactions.

Enteroviruses (EVs) are viruses of the family Picornaviridae that cause mild to severe infections in humans and in several animal species, including nonhuman primates (NHPs). We conducted a survey and characterization of enteroviruses circulating between humans and great apes in the Congo. Fecal samples (N=24) of gorillas and chimpanzees living close to or distant from humans in three Congolese parks were collected, as well as from healthy humans (N=38) living around and within these parks. Enterovirus were detected in 29.4% gorilla and 13.15% human feces, including wild and human-habituated gorillas, local humans and eco-guards. Two identical strains were isolated from two humans come from two remote regions. Their genomes were similar and all genes showed their close similarity to Coxsackieviruses except for 3C, 3D and 5’UTR region where they were most similar to poliovirus 1 and 2, suggesting recombination. Recombination events were found between these strains, poliovirus 1 and 2 and EV-C99. The same EV- C species detected in both humans and apes in different regions suggest a clonal distribution of the virus in Congo.

Parametric cyclonic wind fields are widely used worldwide for insurance risk underwriting, coastal planning, or storm surge forecasts. They support high-stakes financial, development, and emergency decisions. Yet, there is still no consensus on the best parametric approach, or relevant guidance to choose among the great variety of published models. The aim of this paper is first and foremost to demonstrate that recent progresses on estimating extreme surface wind speeds from satellite remote sensing now makes it possible to select the best option with greater objectivity. In particular, we show that the Cyclone Global Navigation Satellite System (CYGNSS) mission of NASA is able to capture a substantial part of the tropical cyclones structure, and allows identifying systematic biases in a number of parametric models. Our results also suggest that none of the traditional empirical approaches can be considered as the best option in all cases. Rather, the choice of a parametric model depends on several criteria such as cyclone intensity and/or availability of wind radii information. The benefit of using satellite remote sensing data to better select a parametric model for a specific case study is tested here by simulating hurricane Maria (2017). The significant wave heights computed by a wave-current hydrodynamic coupled model are found to be in good accordance with the predictions given by the remote sensing data in terms of bias. The results and approach presented in this study should shed new light on how to handle parametric cyclonic wind models, and help the scientific community to conduct better wind, waves and surge analysis for tropical cyclones.

Accurate and timely rainfall prediction enhances productivity and can aid proper planning in sectors such as agriculture, health, transport and water resources. This study is aimed at improving rainfall prediction using ensemble methods. It first assesses the performance of six convective schemes (Kain–Fritsch (KF); Betts–Miller–Janji´c (BMJ); Grell–Fretas (GF); Grell 3D ensemble (G3); New–Tiedke (NT) and Grell–Devenyi (GD)) using the root mean square error (RMSE) and mean error (ME) focusing on the March–May 2013 rainfall period over Uganda. 18 ensemble members are generated from the three best performing convective schemes (i.e. KF, GF & G3). The performance of three ensemble methods (i.e. ensemble mean (EM); ensemble mean analogue (EMA) and multi–member analogue ensemble (MAEM)) is also analyzed using the RMSE and ME. The EM presented a smaller RMSE compared to individual schemes (EM:10.02; KF:23.96; BMJ:26.04; GF:25.85; G3:24.07; NT:29.13 & GD:26.27) and a better bias (EM:-1.28; KF:-1.62; BMJ:-4.04; GF:-3.90; G3:-3.62; NT:-5.41 & GD:-4.07). The EMA and MAEM presented 13 out of 21 stations & 17 out of 21 stations respectively with smaller RMSE compared to EM thus demonstrating additional improvement in predictive performance. The MAEM is a new approach proposed and described in the study.

Eukaryotic enteric pathogens (EEP) are a public health issue in tropical areas. Yet, their interactions with the gut mycobiota remain poorly understood. We conducted a cross-sectional study in Malian children to analyze the impact of EEP on the gut fungal community. EEP were assessed by qPCR and the gut mycobiota was characterized by ITS1-2 metabarcoding in stool samples collected from 296 children. The 100 controls, in whom no EEP was detected, were compared to: a) 196 children with ≥1 EEP; b) 91 with only Blastocystis; c) 35 with only Giardia intestinalis; and d) 12 with another (&lt;1% each) EPP. The gut fungal community structure was homogenous in each children’s group. Linear size-effect discriminant analysis highlighted five relatively more abundant species, including Fusarium longipes and Penicillium caseifulvum, in children with ≥1 EEP, whereas 28, including Aspergillus sydowii and Microdochium colombiense were more abundant in controls. Fusarium, Pyxidiophora, and Stereum abundance was higher in Blastocystis-infected children, whereas Ogataea and Allocryptovalsa were more abundant in controls. Sordariales and Mortierellales abundance was higher in Giardia intestinalis-infected children, whereas Agaricales and Capnodiales abundance was higher in controls. In conclusion, EEP do not significantly alter the gut fungal community structure, and further studies are warranted to confirm our findings that particular taxa are associated with susceptibility or resistance to specific EEP.

Diseases caused by arboviruses are on the increase worldwide. In addition to arthropod bites, most arboviruses can be transmitted via accessory routes. Products of human origin (labile blood products, solid organs, hematopoietic stem cells, tissues) present a risk of contamination for the recipient if the donation is made when the donor is viremic. This narrative review describes the risks of acquiring certain arboviral diseases from human products, mainly solid organs and hematopoietic stem cells, in the French context. Mainland France and its overseas territories are exposed to a complex array of imported and endemic arboviruses, which differ according to their respective location. The main risks considered in this study are infections by West Nile virus, dengue virus and tick-borne encephalitis virus. The ancillary risks represented by Usutu virus infection, chikungunya and Zika are also addressed more briefly. For each disease, the guidelines issued by the French High Council of Public Health, which is responsible for issuing guidelines to mitigate the risks associated with products of human origin and for supporting public health policy decisions, are briefly outlined. The aim of this review is also to contribute to the standardization of recommendations at international level in areas with the same viral epidemiology.

Background: In France, no previous studies had addressed the acquisition of multidrug resistant (MDR) bacteria and colistin resistance genes by medical students when undertaking internships abroad. Methods: Nasopharyngeal, rectal, and vaginal swabs samples were collected from 382 French medical students before and after travel to investigate the acquisition of MDR bacteria. The bacterial diversity in the samples was assessed by culture on selective media. We also genetically characterised the isolates of MDR bacteria including Extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E), methicillin-resistant Staphylococcus aureus (MRSA), and Carbapenemase-producing Enterobacteriacae (CPE) using the real-time polymerase chain reaction method. The samples were collected from 293 students and were investigated for mcr colistin-resistance genes using RT-PCR directly on the samples, followed by conventional PCR and sequencing. Results: A proportion of 29.3% of the participants had acquired ESBL-E and 2.6% had acquired CPE. The most common species and ESBL-E encoding gene were Escherichia coli (98.4%) and bla_CTX-M-A (95.3%), respectively. A proportion of 6.8% of the participants had acquired mcr-1 genes, followed by mcr-3 (0.3%) and mcr-8 (0.3%). We found that taking part in humanitarian missions to orphanages, being in contact with children during travel, the primary destination of travel being Vietnam and north India, using antibiotics during travel, and studying in 2017 were associated with the acquisition of ESBL-E. When the primary destination of travel was Vietnam and the year of study was 2018, this was associated with acquisition of colistin resistance genes. Conclusion: Medical students are at a potential risk of acquiring ESBL-E, CPE and colistin resistance genes. A number of risk factors have been identified, which may be used to develop targeted preventive measures.

Wildfires have short- and long-term impacts on the geoenvironment, including the changes to biogeochemical and mechanical properties of soils, landfill stability, surface- and groundwater, air pollution, and vegetation. Climate change has increased the extent and severity of wildfires across the world. Simultaneously, anthropogenic activities—through the expansion of urban areas into wildlands, abandonment of rural practices, and accidental or intentional fire-inception activities—are also responsible for a majority of fires. This paper provides an overall review and critical appraisal of existing knowledge about processes induced by wildfires and their impact on the geoenvironment. Burning of vegetation leads to loss of root reinforcement and changes in soil hydromechanical properties. Also, depending on the fire temperature, soil can be rendered hydrophobic or hydrophilic and compromise soil nutrition levels, hinder revegetation, and, in turn, increase post-fire erosion and debris flow susceptibility of hillslopes. In addition to direct hazards, wildfires pollute air and soil with smoke and fire suppression agents releasing toxic, persistent, and relatively mobile contaminants into the geoenvironment. Nevertheless, the mitigation of wildfires’ geoenvironmental impacts does not fit within the scope of this paper. In the end, in no exhaustive way, some areas of future need for research are highlighted.

Background : Drug treatments for gait disorders in post-stroke patients aim to reduce muscular hyperactivity. Analysis of muscle activity is essential to help clinicians understand these disorders. The aim of this study was to quantify changes in muscle synergies before (PRE) and after (POST) rectus femoris nerve block. Methods : Gait analysis of 8 post-stroke patients before and immediately after nerve block. Muscle synergies were quantified from electromyographic signals. We have selected: the account for variance indicating the robustness of the synergies, the recruitment selectivity index indicating the degree of multiplexing of the synergies, and the recruitment consistency index indicating the variability of the synergies. Results : A decrease in VAF is observed, suggesting a reduction in gait pattern robustness. We also note that spatial and temporal primitives are slightly different (IRC, IRS) in PRE vs. POST, and that their activation is more nested in POST than in PRE. Conclusions : The motor nerve block has not created new muscle synergies of the paretic limb during gait, but indicates that there is flexibility in motor organization. This method of quanti-fication may enable clinicians to assess the motor adaptation potential of their post-stroke patient.

Ciguatera fish poisoning (CFP) is one of the most common causes worldwide of marine poisoning associated with fish consumption from tropical areas. Its incidence is underreported. CFP cases seem to increase with grouped cases reported during summer. Exposure to ciguatoxin, the toxin responsible for CFP with sodium-channel agonistic, cholinergic, and adrenergic activities, may result in a large spectrum of manifestations. We aimed to describe the clinical characteristics, management, and outcome of CFP in Martinique, French West Indies. We conducted an observational retrospective single-center study for six years (October 2012 to September 2018) including all CFP patients managed by the prehospital medical services, admitted to the university hospital emergency department, or declared to the regional health agency. One hundred and forty-nine CFP patients (81females/63males; median age, 46 years [interquartile range, 34-61]) were included. Acute features consisted of general (91%; mainly, myalgia pruritus, and asthenia), gastrointestinal (90%; mainly diarrhea, abdominal pain, and nausea), neurological (72%; mainly, paresthesia, dysgeusia, and impairment of hot/cold feeling), and cardiovascular manifestations (22%; bradycardia, hypotension, and heart conduction disorders). Management was supportive. No patient died but symptoms persisted in 40% of the 77 patients with follow-up on day 15. CFP was mainly attributed to the ingestion of trevallies (59%), snappers (13%), and king mackerels (8%) with collective contaminations (71%). Unusual fish (tuna, salmon, and spider conchs) were suspected in rare cases. Ingestion of trevallies was associated with significantly higher persistent symptoms (odds ratio, 3.00; 95% confidence interval, [1.20-8.00]; p=0.03). CFP incidence was 0.67 cases per 10,000 patient-years in Martinique over the study period. To conclude, CFP represents an increasing public health issue in Martinique like in other Caribbean islands. Patients present usual but possibly life-threatening features. The outcome is excellent despite frequently prolonged manifestations.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

Oligosaccharides derived from λ-carrageenan (λ-COs) are gaining interest in the cancer field. They have been recently reported to regulate heparanase (HPSE) activity, a protumor enzyme involved in cancer cell migration and invasion, making them very promising molecules for new therapeutic applications. However, one of the specific features of commercial λ-carrageenan (λ-CARs) is that they are in fact heterogeneous mixtures of different CARs families, and are named according to the thickening purpose of the product which does not reflect the real com-position. Consequently, this can limit their use in a clinical grade. To address this issue, six commercial λ-CARs were compared for which differences in their physiochemical properties were shown. Then, a H2O2-assissed radical depolymerization was applied to each commercial source and the number and weight averaged molar masses (Mn and Mw) and sulfation degree (DS) of the λ-COs produced over time were determined. By adjusting the depolymerization time for each product, almost comparable λ-CO formulations could be obtained in term of molar masses and DS, that ranged within previously reported values suitable for anti-tumor proper-ties. However, when the anti-HPSE activity of these new λ-COs was screened, small changes that could not be attributed only to their small length or DS changes between them were found, suggesting a role of other features such as differences in the initial mixture composition. Further structural MS and NMR analysis revealed indeed qualitative and semi-quantitative differences between the molecular species, especially in the proportion of the anti-HPSE λ-type, other CARs types and adjuvants, but also showed that H2O2-based hydrolysis induced sugar degradation. Finally, when the effects of λ-COs were assessed in an in vitro migration cell-based model, they seemed more related to the proportion of other CAR types in the formulation than to their λ-type-dependent anti-HPSE activity.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

The ongoing emergence of SARS-CoV-2 virus variants remains a source of concern because it is accompanied by the potential for increased virulence as well as evasion of immunity. Here we show that, although having an almost identical spike gene sequence as another Omicron variant (BA.5.2.1), a BA.4 isolate lacked all the typical disease characteristics of other isolates seen in the Golden Syrian hamster model despite replicating almost as effectively. Animals infected with BA.4 had similar viral shedding profiles to that seen with BA.5.2.1 (up to day 6 post infection) but they all failed to lose weight or present with any other significant clinical signs. We hypothesize that this lack of detectable signs of disease during infection with BA.4 was due to a small (nine nucleotide) deletion (∆686-694) in the viral genome (ORF1ab) responsible for production of non-structural protein 1 which resulted in the loss of three amino acids (aa 141-143).

The gut microbiota has recently been associated with susceptibility/resistance to malaria in animal models and humans, yet the impact of the gut microbiota on the risk of a malaria attack remains to be assessed. This study aims at assessing the influence of the gut microbiota on malaria attacks and Plasmodium parasitæmia in children living in a malaria-endemic area in Mali. Three hundred healthy children were included in a 16-months cohort study in Bandiagara. Their gut bacteria and fungi community structures were characterised via 16S and ITS metabarcoding from stool samples collected at inclusion. Clinician team monitored the occurrence of malaria attacks. Asymptomatic carriage of Plasmodium was assessed by qPCR. Over the 16-month period, 107 (36%) children experienced at least one occurrence of malaria attacks, and 82 (27%) at least one asymptomatic Plasmodium parasitæmia episode. A higher gut bacteria richness was independently associated with susceptibility to asymptomatic parasitæmia episodes and malaria attacks; while the Shannon H diversity and Chao-1 richness index of gut fungi community structure was relatively homogeneous in children who were and were not infected with P. falciparum. Using a linear discriminant effect size analysis of operational taxonomic units assigned to the species level, 17 bacteria, including Clostridiaceae, Eubacteriaceae, Senegalimassilia sp., Atopobiaceae and Lachnosipraceae, and seven fungi, including Dioszegia fristigensis, Ogataea polymorpha and Cutaneotrichosporon cyanovorans, were associated with susceptibility; whereas eight bacteria, including, Bifidobacterium spp., Weissela confusa and Peptostreptococcacea, and 3 fungi, Malassezia sp., Niesslia exosporoides, and Didymocrea leucaenae, were associated with resistance to malaria. Moreover, 15 bacteria, including Coproccus eutactus, Terrisporobacter petrolearius, Klebsiella pneumoniae and Ruminococcaceae, and 13 fungi, including Wallemia mellicola, were associated with susceptibility, whereas 19 bacteria, including Bifidobacterium spp., Bacteroides fragilis, Peptostreptococcacea, and Lactobacillus ruminis, and three fungi, including Cryptococcus neoformans, were associated with resistance to asymptomatic Plasmodium parasitæmia episodes. Further studies are needed to confirm these findings that point the way towards strategies aiming to reduce the risk of malaria by modulating gut microbiota components in at-risk populations.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by &gt;6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

Cocoa (Theobroma Cacao, L.) represents an important market that gained relevance and became an esteemed commodity thanks to cocoa powder, chocolate, and other related products. This work has analyzed 59 cocoa powder samples from the European market. Three distinct subgroups were identified: organic or conventional, alkalized or not alkalized, and raw or roasted processing. The impact of the technological process was evaluated on the pH, color, and compositional traits, as content of biogenic amines and salsolinol. The phenolic fraction was also investigated trough both common and emerging methods. Results depict that the influence of the agronomical practices (organic/conventional) did not affect significatively (p&lt;0.05) the composition of cocoa powders; similarly, the roasting process was not discriminative for the compounds traced. On the other hand, the alkalinization process greatly impacted on color, and pH, no matter of cocoa provenience, obtention, or other processes, also resulting reducing the phenolic fraction of treated samples. Principal components analysis confirmed that the alkali process acts on pH, color, and phenolic composition, but not on other bioactives molecules (BAs and salsolinol). All samples resulted safe while alkalized powders have a great reduction in beneficial biocompounds. A novel strategy could be to emphasize non-alkalized powders in the label, to meet the demand for more beneficial products.