Recently, spam emails have become a significant problem with the expanding usage of the Internet. It is to some extend obvious to filter emails. A spam filter is a system that detects undesired and malicious emails and blocks them from getting into the users' inboxes. Spam filters check emails for something "suspicious" in terms of text, email address, header, attachments, and language. However, we have used different features such as word2vec, word n-grams, character n-grams, and a combination of variable length n-grams for comparative analysis in our proposed approach. Different machine learning models such as support vector machine (SVM), decision tree (DT), logistic regression (LR), and multinomial naïve bayes (MNB) are applied to train the extracted features. We use different evaluation metrics such as precision, recall, f1-score, and accuracy to evaluate the experimental results. Among them, SVM provides 97.6 \% of accuracy, 98.8\% of precision, and 94.9\% of f1-score using a combination of n-gram features.

Clove (Syzygium aromaticum L. Myrtaceae) is an aromatic plant widely cultivated in tropical and subtropical countries, rich in volatile compounds and antioxidants such as eugenol, β-caryophyllene, and α-humulene. Clove essential oil has received considerable interest due to its wide application in the perfumery, cosmetic, health, medical, flavoring, and food industries. Clove essential oil has relevant biological activities to human health, including antimicrobial, antioxidant, and insecticide. This review describes the effect of the extraction method (hydrodistillation, steam distillation, ultrasound-assisted extraction, microwave-assisted extraction, cold pressing, and supercritical fluid extraction) on the chemical composition of essential oil and its correlation with their biological activities. Likewise, are summarized the main compounds and their reported biological activities. Furthermore, the main applications in clove essential oil in the food industry are presented. Finally, this review presents the new biological activities such as anti-inflammatory, analgesic, anesthetic, antinociceptive and anticancer, which are beneficial for human health. This review aims to compile the effect of different methods of extracting clove essential oil on chemical composition, food applications, as well as a current description of biological activities of interest to human health. Biological activities have increased interest in research into this essential oil and its future applications in the food or pharmaceutical industry.

The pandemic respiratory disease COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan in December 2019 and then spread throughout the world; Italy was the most affected European country. Despite the close pet-human contact, little is known about the predisposition of pets to SARS-CoV-2. Among these, felines are the most susceptible. In this study, a domestic cat with clear symptoms of pneumonia, confirmed by Rx imaging, was found to be infected by SARS-CoV-2 using quantitative RT–qPCR from a nasal swab. This is the first Italian study reporting on the request of the scientific community to focus attention on the possible role of pets as a SARS-CoV-2 reservoir. An important question remains unanswered: did the cat die from SARS-CoV-2 infection?

Cannabis is a flowering plant that has long been used for medicinal, therapeutic, and recreational purposes. Cannabis contains more than 500 different compounds, including a unique class of terpeno-phenolic compounds known as cannabinoids; Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) are the most prevalent cannabinoids and have been associated with the therapeutic and medicinal properties of the cannabis plant. In this paper, continuous flow microwave assisted extraction (MAE) is presented and compared with other methods for commercial cannabis extraction. The practical issues of each extraction method are discussed. The main advantages of MAE are: continuous-flow method which allows for higher volumes of biomass to be processed in less time than existing extraction methods, improved extraction efficiency leading to increased final product yields, improved extract consistency and quality because the process does not require stopping and restarting material flows, and ease of scale-up to industrial scale without the use of pressurised batch vessels. Moreover, due to the flexibility of changing the operation conditions, MAE eliminates additional steps required in most extraction methods, such as biomass decarboxylation, winterisation, which typically adds at least a half day to the extraction process. Another factor that sets MAE apart is the ability to achieve high extraction efficiency even at the industrial scale. Whereas the typical recovery of active compounds using supercritical CO¬2 remains around 70-80%, via MAE up to 95% of the active compounds from cannabis biomass can be recovered at the industrial scale.

Significant progress has made in pattern recognition technology. However, one obstacle that has not yet overcome is the recognition of words in the Brahmi script, specifically the recognition of characters, compound characters, and word because of complex structure. For this kind of complex pattern recognition problem, it is always difficult to decide which feature extraction and classifier would be the best choice. Moreover, it is also true that different feature extraction and classifiers offer complementary information about the patterns to be classified. Therefore, combining feature extraction and classifiers, in an intelligent way, can be beneficial compared to using any single feature extraction. This study proposed the combination of HOG +zonal density with SVM to recognize the Brahmi words. Keeping these facts in mind, in this paper, information provided by structural and statistical based features are combined using SVM classifier for script recognition (word-level) purpose from the Brahmi words images. Brahmi word dataset contains 6,475 and 536 images of Brahmi words of 170 classes for the training and testing, respectively, and the database is made freely available. The word samples from the mentioned database are classified based on the confidence scores provided by support vector machine (SVM) classifier while HOG and zonal density use to extract the features of Brahmi words. Maximum accuracy suggested by system is 95.17% which is better than previously suggested studies.

A partial extraction procedure was used to study the distribution of uranium in the mineral phases of rocks of an aquifer of sandy-clay deposits of the Vendian in the northwest of Russia. This work is a part of a research project to develop a method for combined radiocarbon and uranium-isotope dating of groundwater. Representative aliquots of each core sample were subjected to five "partial" extractions by treatment with: distilled water, low mineralized fresh natural groundwater, minopolycarboxylic acid chelating agent (0.05M EDTA), 0.5M HCl, 15M HNO₃, and a total digestion, with U isotopes reported in this study for each procedure. The following mineral phases of core samples: adsorbed material, carbonate minerals, amorphous iron oxides, aluminosilicates partial digestion and a crystalline iron oxides, aluminosilicates total digestion and a clay/quartz resistate were characterized. Red-colored siltstones depleted in uranium in relatively readily soluble mineral phases. The concentration of adsorbed uranium was established in the amount of 15.8±2.1 - 30.5±3.9 μg/kg. Carbonate minerals contain even less of this element. In iron hydroxides and the most readily soluble aluminosilicates, its concentrations are in the range 168±24 - 212±28 μg/kg. The most insoluble fraction contains 1.65±0.21 - 4.32±0.45 mg/kg of uranium. In green-colored siltstones, the concentration of adsorbed uranium is much higher: 106±14 - 364±43 μg/kg. Carbonate minerals and amorphous iron oxides contain 1.91±0.21 - 2.34±0.26 mg/kg of uranium. In aluminosilicates and a clay/quartz resistate, uranium concentrations are 5.6±0.5 - 16.8±1.4 mg/kg. Elevated values of ²³⁴U:²³⁸U activity ratio prevail in the adsorbed material and iron hydroxides. In aluminosilicates and clay/quartz resistate, the values decrease. This indicates the replacement of primary sedimentogenic uranium by secondary hydrogenic uranium adsorbed on the surface of minerals and coprecipitated with iron hydroxides. The results obtained made it possible to carry out preliminary quantitative estimates of the retardation factor and recoil loss factor of uranium in the groundwater of siltstones of the studied Vendian aquifer.

Semen Allii Fistulosi is the seed of Allium fistulosum L. of the Liliaceae family. The purpose of this study was to extract, characterize, and evaluate the antioxidant activity in vitro of proteins from Semen Allii Fistulosi (PSAF). Using single factor and orthogonal design, the optimum conditions of extraction were determined to be as follows: extraction time 150 min, pH 8.5, temperature 60℃, and ratio (v/w, mL/g) of extraction solvent to raw material 35. The isoelectric point of the pH was determined to be about 4.4 and 10.2, by measuring the protein content of PSAF solutions at different pH. The amino acid composition of PSAF was determined by high performance liquid chromatography (HPLC), and the results suggested that the species of amino acids contained in the PSAF was complete. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS–PAGE) analysis showed the molecular weight was mainly between 40 and 55 kDa, and Fourier-transform infrared spectroscopy (FTIR) characterized prevalent protein absorption peaks. PSAF exhibited potent scavenging activities against DPPH assays, via targeting of hydroxyl and superoxide radicals, while chelating Fe2+ activity, and demonstrating weak reducing power. This work revealed that PSAF possessed potential antioxidant activity in vitro, suggesting potential for use of PSAF as a natural antioxidant.

A study has been carried out on Ta and Nb recovery by liquid-liquid extraction process using 4-methylacetophenone (4-MAcPh) as organic phase. The 4-MAcPh was compared to methylisobutylketone (MIBK) with respect to extraction efficiencies (kD values) at different concentrations of H2SO4 in the aqueous phase. The results showed a similar extraction of Nb for both solvents. However, for Ta extraction efficiency is increased by a factor of 1.3 for 4-MAcPh. In addition, the MIBK solubilized completely after 6 mol L-1 of H2SO4 against only a loss of 0.14 to 4% for 4-MAcPh between 6 and 9 mol L-1 of H2SO4. The potential of 4-MAcPh has also been studied to selectively recover Ta from a model capacitor waste solution. The results showed a selectivity for Ta in the presence of impurities such as Fe, Ni, Mn. The 4-MAcPh also presents the advantage of having physicochemical properties adapted to its use in liquid-liquid extraction technologies such as mixer-settlers.

Azadirachta indica A. Juss (neem) extracts have been used in pharmaceutical applications as antitumor agents, due to their terpenes and phenolic compounds. To obtain extracts from neem leaves with potential antiproliferative effect, a sequential process of pressurized liquid extraction was carried out in a fixed bed extractor at 25 ºC and 100 bar, using hexane (SH), ethyl acetate (SEA) and then ethanol (SE) as solvents. An extraction using only ethanol (EE) was also conducted to compare the characteristics of the fractionated extracts. The results obtained by liquid chromatography-electrospray ionization mass spectrometry suggested the highest concentration of terpenes for SEA extract in comparison to SH, SE and EE extracts. Therefore, antiproliferative activity showed SEA extracts were the most efficient inhibitors to human tumor cells MCF-7, NCI-H460, HeLa, and HepG2 between all other extracts studied. However, hepatocellular normal cells were more resistant to SH, SEA, SE, and EE compared to malignant cells of breast, lung, hepatocellular, and cervical. Neem fractioned extracts obtained in the present study seem to be more selective for malignant cells compared to the normal cells.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Large-span post-tensioned (PT) beams play a crucial role in maximizing the benefits of post-tensioning techniques. Bonded and unbonded systems are prevalent, with the latter being more widespread in the United States. While bonded systems are advantageous for creating long spans when multiple tendons are grouped in ducts, limited literature exists on their demolition. In a case study, this paper addresses the unique challenge of demolishing large-span bonded post-tensioned beams due to a building's functional change. Emphasizing insights for engineers, it explores the use of cutting and dismantling methods, considering the presence of prestressed cables. The demolition process is distinctive due to the presence of numerous pre-stressed cables along the beams, necessitating a specialized and cautious cutting approach. This is accomplished through the use of a drilling technique that selectively distresses the tendons, ensuring they are not all affected simultaneously. An intriguing observation discussed in this paper pertains to the occurrence of horizontal cracks accompanied by loud sounds following the drilling process, offering insights from the design perspective of PT systems. The paper details an innovative method for safely demolishing large-span bonded PT beams, using ground-penetrating radar and computer models to navigate structural complexities and ensure nearby structures' safety.

The pandemic was an enormous experience all over the world. The type of living, working and study were changed irreversibly. Facing the opportunity to establish old frames of education in universities is impossible. The adoption of new ways of teaching and assessments reveal their convenience and in the same way their weak points. In response to that stage, on 14 December 2022, the EU parliament accepted the "Digital Decade Policy Programme 2030", for the establishment of a digital transformation community (EU 2022). Trakia University had an online assessment system, quizzes for self-training, and final exams, developed in 2008 on Moodle virtual learning environment. During the pandemic, online exams and lectures were conducted using platforms like BigBlueButton in Moodle or Google Meets. The article gives the results of online exams before, during, and after the pandemic. The outcome, without doubt, displays the lowering knowledge level or performance during the social isolation due to COVID-19, and after, and the reasons are discussed. During the second year of the pandemic was mentioned also a high dropout of students. Now the situation is returning to the previous levels, before the pandemic, but the quality of education is not yet reached. The article values the grades results of session exams and has the intention to clarify the influence of the pandemic period on the excellence of high institution education.

The study aimed to evaluate the after-effects of the COVID-19 pandemic on the sleep quality and patterns of women across different cultural settings within Iraq, spanning the period of 2022. A cross-sectional survey was administered to a diverse cohort of women from multiple provinces in Iraq. The survey measured various parameters, including sleep duration, onset latency, and disturbances. The post-pandemic period has seen a notable decline in sleep quality among the female population. Contributing factors include psychological stress, lifestyle changes due to the pandemic, and ongoing socio-economic challenges. The impact on sleep quality exhibited variation across different cultural groups, indicating a significant cultural influence on the pandemic's psychological aftermath. The study concludes that the post-pandemic phase has adversely affected the sleep health of women in Iraq, with cultural factors playing a critical role in these changes. There is a pressing need for culturally sensitive public health strategies to address sleep disturbances and mitigate their long-term effects on women's health. Public health initiatives should be tailored to address the specific cultural contexts within Iraq to improve sleep health among women. Further research is warranted to explore the long-term consequences of disturbed sleep patterns and the effectiveness of different intervention strategies.

Background Posttraumatic stress disorder (PTSD) is a complex condition that represents a significant burden in terms of individual disability and societal costs. Despite decades of research investigating treatment options, PTSD remains a major cause of quality-of-life impairment. We hypothesized that patients with PTSD might benefit from peripheral somatosensory stimulation (PSS) therapy. Methods Six adult patients with clinically diagnosed PTSD were enrolled to undergo daily PSS therapy over a 4-week period. Patients completed two surveys evaluating satisfaction with treatment and overall well-being (Survey 1) and severity of PTSD symptoms (Survey 2). Survey 1 was completed weekly during the course of the study. Survey 2 was based on the 9-question National Stressful Events Survey PTSD Short Scale (NSESSS) and was completed as a baseline prior to initiation of therapy and then at the conclusion of the trial. All data were analyzed by an independent statistician. Results Six male patients were enrolled in the study; all completed the trial. All patients demonstrated a decrease in symptoms within one week of initiation of therapy. This benefit was sustained and appeared to further improve over the course of the trial. For Survey 1, the overall median scores demonstrated a significant time-dependent improvement across measurement times (p < 0.001). For Survey 2, patients had statistically significant improvements from baseline regarding feelings of being emotionally upset and being overly alert. Results from a cumulative link mixed model demonstrated that treatment yielded a 38.2-fold higher likelihood of transitioning from a higher PTSD score at baseline to a lower (improved) score at week 4. No adverse events were described by the patients. Conclusions PSS stimulation appeared to improve symptoms in all six patients with PTSD symptoms in this trial. Patients had unanimous and clinically meaningful improvement in overall PTSD symptoms with treatment. By week 4, all patients responded that they enjoyed the treatment and would like to keep their device. We suggest that further investigation into the potential usefulness of PSS therapy in patients with PTSD is warranted.

Post-traumatic stress disorder (PTSD) is a debilitating mental health disorder that causes significant dysfunction in individuals. Currently, there are many approved Pharmacotherapy and Psychotherapy treatment options for PTSD, but unfortunately, half of the patients do not respond to traditional therapies. In this article, we reviewed clinical trials and research on 3,4-methylenedioxymethamphetamine (MDMA) assisted Psychotherapy in PTSD patients, its pharmacokinetics and current treatment guidelines for PTSD. Based on the results of the efficacy of MDMA assisted Psychotherapy from six phases II Randomized controlled trials. MDMA-assisted Psychotherapy for PTSD has received the “Breakthrough Therapy” designation from the FDA. MDMA can potentially reduce PTSD symptoms even in treatment-resistant cases by increasing certain neurohormones, i.e. dopamine, serotonin, norepinephrine and oxytocin. It also modulates activities in the brain regions involved in fear and anxiety. Future research is needed to show whether the advantages outweigh the disadvantages and whether its use can be integrated into available treatment options for PTSD.

Aims: The aims of this meta-analysis were to assess: the prevalence of Post-Acute COVID-19 sequalae in HIV positive patients; average time of diagnosis; and meta-regress for possible moderators of PACS.Methods: A standard search strategy was used in PubMed, and then later modified according to each specific database to get the best relevant results. These included Medline indexed journals; PubMed Central; NCBI Bookshelf and publishers' Web sites in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “long COVID-19 or post-acute COVID-19 syndrome/sequalae”, “persons living with HIV or HIV. The criteria for inclusion were published clinical articles reporting HIV in association with long COVID-19, further, the average time to an event of post-acute COVID-19 sequelae among primary infected patients with COVID-19. Random-effects model was used. Rank Correlation and Egger's tests were used to ascertain publication bias. Sub-group, sensitivity and meta-regression analysis were conducted. A 95% confidence intervals were presented and a p-value < 0.05 was considered statistically significant. Review Manager 5.4 and comprehensive meta-analysis version 4 (CMA V4) were used for the analysis. The review/trial was PROSPERO registered (CRD42022328509).Results: A total of 43 studies reported post-acute COVID-19 syndrome. Of those, five reported post-acute COVID-19 sequalae in PLHIV. Prevalence of post-acute COVID-19 sequalae was 43.1% (95% CI 20.5% to 68.9%) in persons living with HIV (PLWH). The average time to PACS diagnosis was 4 months at 64% [0.64 (95% CI 0.230, 0.913) (P < 0.0000), I²= 93%] and at one year to PACS diagnosis was at 70 %, however with non-significant correlation (P > 0.05). On comorbidities, asthenia was associated with PACS at 17.6 % [0.176 (95% CI 0.067, 0.385) (P = 0.008), I²= 86%] while fatigue at 82%, however not related with PACS event incidence (P < 0.05). Americas, Asian and European regions showed PACS events rates of 82%, 43% and 19 % respectively (P<0.05) relative to HIV infection. Conclusion: PACS prevalence in PLWH was 43% occurring at an average time of 4 months at 64% and 70 % at 12 months however non-significant with PACS. Asthenia was significantly associated with PACS at 17.6 % while fatigue at 82%, however not related with PACS event incidence. Americas recorded the highest PACS event rates in PLWH.

In this review we extensively describe the main post-translational modifications that give rise to the multiple proteoforms characterized to date in the human salivary proteome and their potential role. Most of the data reported were obtained by our group in over twenty-five years of research carried out on human saliva mainly by applying a top-down strategy. At the beginning we describe the products generated by proteolytic cleavages, which can occur before and after secretion. In this section the most relevant families of salivary proteins are also described. Next, we report the current information concerning the human salivary phospho-proteome and the limited news available on sulfo-proteome. Three sections are dedicated to the description of the glycation and enzymatic glycosylation. Citrullination and N- and C- terminal PTMs and a miscellaneous of other modifications are described in the last two sections. Results highlighting the variation in the level of some proteoforms in local or systemic pathologies are also reviewed along the sections of manuscript to underline the impact and relevance of this information for the development of new diagnostic biomarkers useful in clinical practice.

Abstract Congenital rubella syndrome is a constellation of birth defects that can have devastating consequences, impacting approximately 100,000 births worldwide each year. The incidence is much lower in countries that routinely vaccinate their population. In the US, postnatal immunization of susceptible women is an important epidemiological strategy for the prevention of rubella. However, concerns that co-administration of Rubella vaccine with other immunoglobins (i.e., Rhogam) could comprise vaccine efficacy has produced warnings that can delay the administration of Rubella vaccination postpartum, leaving women susceptible in a subsequent pregnancy. We aimed to address whether co-administration of Rubella vaccine and Rhogam decreased antibody responses as compared to those receiving only Rubella vaccination. This retrospective cohort study utilized clinical data from 80 subjects who received Rubella vaccine and Rhogam after delivery and 43 subjects received Rubella vaccine alone. Maternal demographics, pregnancy complications and rubella status at the start of a subsequent pregnancy were recorded for analysis. Overall, the two cohorts had similar baseline characteristics; however, lower parity was noted in the participants having both Rubella vaccination and Rhogam. Based on maternal antibody IgG index for rubella during the next pregnancy, we observed that 88% of the Rhogam + Rubella vaccine group had positive titers, which was not significantly different than the 81% in the Rubella vaccine only cohort (p=0.36). In conclusion, no differences in the rubella immunity status in a subsequent pregnancy were observed in those mothers administered both Rubella vaccine and Rhogam concurrently. Given these findings, warnings against co-administration of Rubella vaccine in combination with other immunoglobulins should be discontinued.

(1) Background: High-grade cervical dysplasia is primarily caused by human papillomavirus (HPV) infection. Conservative surgery is the preferred treatment approach for this condition. The most commonly employed technique is the loop electrosurgical excision procedure (LEEP), which involves removing the affected portion of the cervix. Excisional treatments are often curative, and complications are typically rare and minor; (2) Methods: The loop electrosurgical excision procedure (LEEP) is the standard method used for conservative surgery in high-grade cervical dysplasia. It entails the excision of the specific area of the cervix where the abnormal cells are present. The procedure employs a wire loop carrying an electrical current to remove the affected tissue; (3) Results: Excisional treatments, such as LEEP, have shown to be effective in treating high-grade cervical dysplasia. They have a high success rate in eliminating abnormal cells and reducing the risk of cervical cancer. Complications associated with LEEP are infrequent and usually minor. Short-term complications may include bleeding, which can be managed easily. Long-term complications may involve cervical canal stenosis, which can impact fertility; (4) Conclusions: Conservative surgery, particularly the loop electrosurgical excision procedure (LEEP), is the preferred and effective treatment for high-grade cervical dysplasia caused by HPV infection. It offers a high cure rate with rare and minor complications. While short-term bleeding is a common occurrence, it is manageable. Long-term complications such as cervical canal stenosis may impact fertility. However, an extremely rare and possibly unique complication described in this case is the development of a vaginorectal fistula. This complication is likely due to indirect thermal injury resulting from compromised tissue. Further research is needed to better understand and prevent such complications.

Abstract: Gastroesophageal reflux disease (GERD), the inflammatory bowel disease (IBD), and mental health issues are significant public health concerns in globally. Although rising peaks observed post-COVID-19, there is a sever paucity in high quality data. Using descriptive analysis, we identified the frequency and associations of age- and gender, sport, genetic, and psychiatric consequences in the coexistence of GERD and IBD in 2067 participants 18 to &gt;60 years with mean age of 26.8 ± 12.9 years. Most were 18 -29 years old (66%, n=1364) of which majority were young Saudi females (72.4%, n=1496). Estimated 1099 (53.2%) were students, 428 (20.7%) were unemployed, and 540 (26.1%) were. The majority were Saudis (94.7%, n= 1957). Psychological syndromes anxiety (60.7%), stress (60.7%), and depression (60.6%) were most frequent; whereas, IBD (48.7%) and GERD (36.3%), respectively were the second and third. In 51 % respondents depression, anxiety, and stress occurred first while in 33.9%, and 24.3% IBD and GERD, respectively, were the first signs. In most respondents (59.2%, n=1178), these signs first appeared recently and 33.6% (n=669) reported occurrence during adult life, and only in 7.2% (n=144) the signs noticed during childhood (7.2%, n=144)). Aggravating factors were 32.9% (n=681) genetic and other factors of which 476 (69.9%) inherited IBD while 215(31.6%) and 175 ((25.7), respectively, inherited psychological (depression, anxiety, and stress) and GERD. However, only 18.3% sought treatment (n=378) and only 66 (3.2%) had colectomy or a colostomy bag. Little over half of the studied population (58.1%, n=1201) were active in outdoor. GERD or IBS and psychological factors (anxiety, depression, and stress), were significantly associated with age (P value =.001).; GERD with old age, IBD with mid-age 40-49 years, and psychological disorders among younger ages. Thus, while mental health issues predispose young millennial women to neurogastroenterological disorders, the IBD and GERD initiate psychological problems in old and mid-ages, respectively. Intriguingly, despite the significantly mosaic global genetic population structures, their lifestyles, and nutritional habits, the pattern of these disorders remains similar. Thus, this is potentially consistent with notion that the gut nerve cells are conserved and that the changes in gut dysbiosis of gut microbiome signatures are responsible. These findings have significant clinical implications in the patient treatment strategies and tailored educational and awareness programs in lifestyle medicine. Future microbiome studies would reveal more insight into the mechanisms of disorders.

The rapid development of quantum computing devices promises powerful machines with capabilities that solve a wide range of problems that traditional computers cannot. Therefore, quantum computers generate new threats at unprecedented speed and scale and specifically pose an enormous threat to encryption. Lattice-based cryptography is considered to be the rival to a quantum computer attack and the future of post-quantum cryptography. So, cryptographic protocols based on lattices have a variety of benefits, like security, efficiency, lower energy consumption, and speed. In this work, we study the most well-known lattice-based cryptosystems while a systematic evaluation and comparison is presented also, and focuses on their strengths and weaknesses.

Temperature is a critical factor that influences the proliferation of pathogens in hosts. The impact of temperature on pathogens is commonly explored in controlled and constant temperatures. Experiments under varying environmental temperature are becoming more frequent, however, testing every temperature scenario à la carte is unachievable. One example of this is the human pathogen Vibrio parahaemolyticus (Vp) in oysters. Here, a predictive model was developed for predicting the growth of Vp in oysters under varying ambient temperature. The model was fitted and evaluated against data from experiments studying growth and inactivation of Vp in oysters at eight constant temperatures. Once evaluated, Vp dynamics in oysters were estimated at different post-harvest varying temperature scenarios affected by water and air temperature, and different ice treatment timing. The model performed adequately under varying temperature, reflecting that (i) increasing temperature, particularly in hot summers, favors a rapid Vp growth in oysters, resulting in a very high risk of gastroenteritis in humans after consumption of a serving of raw oysters, (ii) pathogen inactivation due to day/night oscillations, and more evidently, due to ice treatments, (iii) ice treatment is much more effective limiting risk of illness when applied immediately onboard compared to dockside. The model results to be a promising tool for improving the understanding of the Vp-oyster system and support studies on public health impact of pathogenic Vp associated with raw oyster consumption. Although robust validation of the model predictions is needed, initial results and evaluation show the potential of the model to be easily modified to match similar systems where the temperature is a critical factor shaping the proliferation of pathogens in hosts.

Sepsis is a life-threatening condition with high hospital mortality. Elevated mortality has also been observed in patients after hospital discharge due to post-sepsis syndrome (PSS). The etiology of PSS is still not entirely known, but it involves inflammation. Plasma extracellular vesicles (EVs) are recognized as a unique mechanism of intercellular communication in inflammatory processes. It has been reported that EV microRNA (miRNA) production during the acute sepsis phase may persist until after disease resolution and is associated with PSS. We employed mass spectrometry and qPCR analysis to determine the protein and miRNA composition of plasma-derived EVs of 36 patients during sepsis-related hospitalization, immediately after ICU discharge (post-sepsis), and three, six, twelve, and up to 36 months post-sepsis. We determined that patients’ immune system cells were the primary EV source. Fifteen differentially expressed EV miRNAs (DEmiRs) were identified in samples from septic patients compared to the control group. Predictive analyses revealed that these DEmiRs could influence inflammation by modulating pathways mediated by NF-κB, STAT3, and TLR4 signaling activation. Thirteen miRNAs (-15b-5p,-16-5p,-20a-5p,-25-3p,-27a-3p,-29a-3p,-30d-5p,-93-5p,-146a-5p,-148a-3p,-191-5p,-195-5p,-223-3p) were downregulated in the death group compared to the survivor group, making them candidate prognostic markers of ICU survival. One year after ICU discharge, the expression of miR-21-5p and miR-195-5p were decreased in the survivor group. The miRNAs identified in the present study represent potential biomarkers for the survival prognosis of post-sepsis patients.

This study is a cross-sectional survey involving physicians around Indonesia aimed to explore physician hesitancy to treat COVID-19 patients after experiencing COVID-19 infection coupled with associated occupational risk factors. The questionnaire was distributed via contact information from the Indonesian Physician Association database. Out of 383 participants, 25.6% suffered from moderate symptoms of COVID-19 and 2.9% were admitted for critical care. Hesitancy to treat suspected, probable, or confirmed COVID-19 patients was found in 20.3% of physicians. A higher hesitancy rate was found in older physicians and those with less experience in treating COVID-19 patients. Specialist trainees and those who work in public hospitals were physicians with the lowest hesitancy in treating COVID-19 patients. There is a significant hesitancy in treating COVID-19 patients among physicians who have suffered from COVID-19 which calls for further action by management and policy makers.

Plastid gene expression involves many post-transcriptional maturation steps resulting in a complex transcriptome composed of multiple isoforms. Although short read RNA-seq has considerably improved our understanding of the molecular mechanisms controlling these processes, it is unable to sequence full-length transcripts. This information is however crucial when it comes to understand the interplay between the various steps of plastid gene expression. Here, the study of the Arabidopsis leaf plastid transcriptome using Nanopore sequencing showed that many splicing and editing events were not independent but co-occurring. For a given transcript, maturation events also appeared to be chronologically ordered with splicing happening after most sites are edited.

Background: Percutaneous coronary intervention (PCI) is known as a very rare possible trigger of pericarditis. Most frequently it develops after a latent period or early in case of periprocedural complications. In this report, we present an atypical early onset of pericarditis after the uncomplicated PCI. Case Summary: A 58-year-old man was admitted to the hospital for the PCI of the chronic total occlusion of left anterior descending (LAD) artery. An initial electrocardiogram (ECG) was unremarkable. PCI attempt was unsuccessful. There were no procedure related complications observed at the end of PCI attempt and patient was symptom free. Six hours after interventional procedure the patient complained of severe chest pain. The ECG demonstrated ST-segment elevation in anterior and lateral leads. Troponin I was mildly elevated but coronary angiogram did not reveal impairment of collateral blood flow to the LAD territory. Because of pericarditic chest pain, typical ECG findings and pericardial effusion with elevated C-reactive protein, the diagnosis of acute pericarditis was established, and a course of nonsteroidal anti-inflammatory drugs (NSAIDs) was initiated. Chest pain was relieved and ST-segment elevation almost completely returned to baseline after three days of treatment. The patient was discharged in stable condition without chest pain on the fourth day after symptom onset. Conclusions: Acute pericarditis is a rare complication of PCI. Despite the lack of specific clinical manifestation, post-traumatic pericarditis should be considered in patients with symptoms and signs of pericarditis and a prior history of iatrogenic injury or thoracic trauma.

The influence of post-processing conditions on the magnetic properties of amorphous and nanocrystalline microwires have been thoroughly analyzed, paying attention on the influence of magnetoelastic, induced and magnetocrystalline anisotropies on the hysteresis loops of Fe-, Ni- and Co-rich microwires. We showed that magnetic properties of glass-coated microwires can be tuned by the selection of appropriate chemical composition and geometry in as-prepared state or further considerably modified by appropriate post-processing, which consists of either annealing or glass-coated removal. Furthermore, stress-annealing or Joule heating can further effectively modify the magnetic properties of amorphous magnetic microwires owing to induced magnetic anisotropy. Devitrification of microwires can be useful for either magnetic softening or magnetic hardening of the microwires. Depending on the chemical composition of the metallic nucleus and on structural features (grain size, precipitating phases) nanocrystalline microwires can exhibit either soft magnetic properties or semi-hard magnetic properties. We demonstrated that the microwires with coercivities from 1 A/m to 40 kA/m can be prepared.

Blackberry is a fruit that has high nutritional value, a factor that has expanded its consumption worldwide. However, due to the fragility of the fruits and the high incidence of postharvest diseases, the fruits have a short shelf life. Thus, the objective of this study was to evaluate whether the application of coatings based on microfibrillated cellulose (NC) and lemongrass essential oil (EO) nanoparticles can prolong the shelf life of blackberry fruits after harvest. EO-coated blackberry fruits at nanocellulose concentrations were analyzed as follows: 0; 0.2; 0.4; 0.6 and 0.8%, in addition to the control treatment of which neither essential oil nor nanocellulose was used, for each treatment five repetitions were used. The fruits were analyzed soon after the application of the cover and at three and six days after storage. Fruit quality was assessed by soluble solids (SS), titratable acidity (TA), pH, fresh weight loss (FWL) and colorimetric parameters such as luminosity, hue angle and fruit peel chroma. Coating on EO (1000 ppm) blackberries combined with NC at concentrations of 0.2, 0.4 and 0.6% is promising in preserving blackberry fruits and reducing the process color reversal, up to six days of storage. The 0.4% NC + 1000 ppm EO conjugated coating showed no SS changes in blackberry fruits during the six days of storage.

Background and Objectives: Due to huge demand and availability of Banana, innovative cost effective method is necessary to promote and smoothen the banana production among farmers commercially mitigating the demand. Method and Materials: In this study, we feed cow dung mixture along with Urea, TSP, MoP, water to the distal part of rachis after cutting down male bud as soon as the female flowers matured into fruits (T1). The effect of this method was then compared with two control groups; one with the same strategy except fertilizer applied on root following ring method (C1, Positive control) and another was male flower untouched without applying fertilizer on rachis or root (C2, Negative control). Results and Conclusion: T1 showed more than double increase in length than controls. In the same way, in case of shape (diameter), T1 (0.46 cm) showed twice as better growth in the C1 (0.22 cm) and C2 (0.18 cm). Trend analysis showed the test group T1 curve is much steeper than the control groups suggesting faster growth rate than the other two. Finally, the cost of fertilizers for T1 per plant was estimated 0.091 USD while for positive control C1 it was 2.9 USD. This study shows an approach to be effective and economic comparing to traditional method of fertilizer application, which can be adapted as a new method of banana production.

Synergistic effects between reactions, reagents and catalysts can lead to minor heats of reaction and occur as an inherent result of multi-component reactions (MCRs) and their extensions. They enable syntheses to be performed at a low energy level and the number of synthesis steps to be drastically reduced in comparison with ‘classical’ two-component reactions. The very high potential for variability, diversity and complexity of MCRs additionally generates an extremely diverse range of products, thus bringing us closer to the aim of being able to produce tailor-made and extremely low-priced materials, drugs and libraries.

The objective of this work was to investigate the deacidification of bio-oils (BOs) from triglyceride-based biomass through the application of liquid-liquid extraction (LLE) in a simple stage, using methanol and water as a binary solvent and feed/solvent ratio of 1/1. For this, the effects of process parameters such as the water content present in the solvent, the content of carboxylic acids present in the bio-oil, and the extraction temperature on the deacidification process through the efficiency and distribution coefficient were evaluated, as well as the effects of such parameters on the quality of deacidified bio-oils through physical-chemical analyzes and GC-MS analysis. The results show that such process parameters significantly affect the quality of deacidified bio-oils. The ideal condition to have the highest acid removal, i.e., the highest deacidification efficiency (72.65%), is the one in which the deacidification process is performed with aqueous methanol (5% water) at 35 °C and for BOs that have a total acid number (TAN) equal to 24.38 mg KOH/g. Therefore, the process of deacidification by LLE using aqueous methanol is a promising alternative for removing carboxylic acids and other oxygenated compounds, contributing significantly to the upgrading or improving biofuels produced by catalytic thermal cracking.

Emerging pollutants (EPs) encompass natural or synthetic substances in the environment that pose potential risks but have only recently been recognized or monitored. EPs consist of various categories including pesticides, pharmaceuticals, hormones, mycotoxins, and endocrine disrupting chemicals (EDCs). Through several pathways, EPs can access food, potentially leading to health impacts when their safe concentrations are exceeded. Milk, being a highly nutritious and a heavily consumed food product by many consumers of different ages, is a crucial food matrix where EPs should be regularly monitored. In literature, large number of studies was dedicated for the determination of different EPs in dairy milk, employing different analytical techniques. Chromatographic based techniques were the most prevalent means for analysis of EPs in milk, which demonstrated significant efficiency, sensitivity and accuracy for this specific purpose. Prior to chromatographic analysis, extraction of EPs from a complex matrix like milk, is essential. This review comprehensively covers relevant research papers on extraction and subsequent detection and determination of EPs in milk by chromatographic methods from 2018 and until 2023.

RNA extraction from human cumulus cells (CCs) is considered challenging due to low cell’s pop-ulation and small cell. The successful gene expression analysis from cumulus cells ultimately de-pends on an excellent concentration of Ribonucleic acid (RNA) yield by an appropriate technique. Our study aims to consolidate appropriate cumulus cell collection method, preparation and ex-traction techniques to ensure a good yield of RNA for better gene expression analysis. From the results obtained, the optimal strategy found involved mechanical denudation without an enzy-matic process, followed by the use of RNA stabilizer prior to RNA extraction. Subsequently, uti-lizing a smaller homogenizer, preferably manual pressure control with filter (Bio-Masher III®) is paramount for a pure and homogenize sample. Subsequently, during RNA extraction, the use of RNeasy micro kit and RNA carriers is recommended. These sample collection, preparation, and extraction techniques yielded an excellent-quality RNA concentration and successful gene expres-sion analysis. We also conducted a systematic review to consolidate our findings with current evidence of RNA extraction technique. Our results added a value as a current strategy for opti-mizing RNA extraction in CCs for experimental studies. Thus, our findings can contribute to for-mulating a better strategy for optimizing the RNA extraction in CCs for transcriptomic studies.

The solvent extraction of gold(III) by undiluted 2-ethylhexanol or dissolved in toluene from HCl solution has been investigated. The numerical analysis of gold distribution data suggests the formation of HAuCl4·L and HAuCl4·2L (L= 2-ethylhexanol) species in the organic phase with formation constants K11= 38 and K12= 309, respectively. The results derived from gold(III) distribution have been implemented in a solid-supported liquid membrane system. The influence of several variables on gold transport was considered: feed and receiving phases stirring speeds, HCl and gold concentrations in the feed phase and carrier concentration in the membrane phase as well as the presence of base metals (Fe,Cu,Ni) and PGMs in the feed phase. Also, diffusional resistances to mass transfer are estimated. Gold is recovered as zero valent nanoparticles.

This study focuses on the reasoning of symptoms of TCM internal diseases. Taking cough as an example, the BERT-BiLSTM-CRF model is used for entity recognition. Experiments show that the model has the best entity recognition effect on three types of texts, including teaching cases, clinical cases and literature data, and the F1 value is up to 0.967. It can effectively identify symptoms, course of disease, tongue condition and pulse condition in TCM diagnosis and treatment texts, which lays a solid foundation for intelligent assisted syndrome differentiation and treatment of TCM. By constructing four types of entity corpora and using three mainstream entity recognition models for experiments, it is found that the BERT-BiLSTM-CRF model has a good entity recognition effect in three types of data: teaching cases, clinical cases and literature data. Experimental results show that the F1 values of the BERT-bilSTM-CRF model in teaching cases, clinical cases and literature data are 0.967, 0.82 and 0.91, respectively, which provides an effective method for information extraction in the field of TCM syndrome differentiation diagnosis and treatment, and lays a foundation for further research on knowledge reasoning.

Despite UAV multi-target detection exhibits considerable developmental potential worldwide, it suffers distinct challenges compared with traditional tasks in this field. These challenges include insufficient feature extraction capabilities for small targets, limited capabilities for multi-dimensional feature fusion, as well as constraints on hardware computation parameters. Especially in mission scenarios such as disaster detection, these challenges will be further amplified. Consequently, this paper introduces SSE-YOLO, an innovative YOLO framework algorithm specially designed to address these challenges. To enhance the model's feature extraction capability, we employ the SPDConv module to replace the original Conv in the backbone section, utilizing depth-separable convolution instead of traditional convolution pooling. Concurrently, we eliminate the SPPF module at the bottom and address a new Separate Kernel Attention Pyramid Pooling (SKAPP) module, substantially enhancing the feature fusion capability at the model's core. Moreover, to address the challenge of multi-dimensional feature fusion, we replace the Concat module of the neck and head with E-BiFPN, transmitting feature information from the backbone to the lower network through four CBS blocks, which effectively resolves the issue of lost contextual information in the model. Meanwhile, SSE-YOLO undergoes ablation experiments on the VisDrone2019 dataset to evaluate its effectiveness against alternative methods, and experimental results illustrate the model's exceptional precision in detecting UAV targets. In comparison to models with comparable experimental accuracy, SSE-YOLO requires remarkably fewer parameters. On the VisDrone2019-DET-test-dev dataset, SSE-YOLO enhances mAP by 17.3%, with a 42.5% reduction in the parameter amounts. Therefore, the proposed method effectively tackles the challenge of reconciling low parameters and high accuracy, presenting a novel pathway for deep learning-based UAV multi-target detection.

Alginate, a biopolymer promising in food, biomedical, pharmaceutical, and electronic materials industries, is characterized by its biodegradability, biocompatibility, low toxicity, and gel-forming properties. It is most abundantly found in brown algae. However, conventional dilute acid and alkali extraction methods face limitations in commercialization due to their long processing time, low throughput, and high solvent requirements. In this study, a microwave-assisted extraction (MAE) process for sodium alginate was designed to improve extraction efficiency. Solid/liquid ratio, extraction temperature, and extraction solvent concentration were major variables affecting sodium alginate extraction from Undaria pinnatifida(sea mustard). They were then statistically optimized using response surface methodology. Under optimal conditions (13.27 g/L, 91.86 ℃, 2.51 %(w/v), and 15 min), the yield was 38.41 %, which was 93.43 % of the theoretical content of sodium alginate in Undaria pinnatifida. Our work has confirmed the productivity and industrial feasibility of efficient extraction of sodium alginate from marine biomass, and we hope that it will serve as an encouraging case for the application of biopolymers as one of the desirable options for alternative petrochemicals to construct a sustainable society.

Accurate weight measurement is pivotal for monitoring the growth and well-being of cattle. However, the conventional weighing process, which involves physically placing cattle on scales, is labor-intensive and distressing for the animals. Hence, the development of automated cattle weight prediction techniques assumes critical significance. This study proposes a weight prediction approach for Korean cattle using 3D segmentation-based feature extraction and regression machine learning techniques from incomplete 3D shapes acquired from real farm environments. In the initial phase, we generated mesh data of 3D Korean cattle shapes using a multiple-camera system. Subsequently, deep learning-based 3D segmentation with the PointNet network model was employed to segment two dominant parts of the cattle. From these segmented parts, three crucial dimensions of Korean cattle were extracted. Finally, we implemented five regression machine learning models (CatBoost regression, LightGBM, Polynomial regression, Random Forest regression, and XGBoost regression) for weight prediction. To validate our approach, we captured 270 Korean cattle in various poses, totaling 1190 poses of 270 cattle. The best result was achieved with mean absolute error (MAE) of 25.2 kg and mean absolute percent error (MAPE) of 5.81% using the random forest regression model.

Cambodian spices Amomum kravanh, Citrus hystrix and Piper nigrum 'Kampot' have long history of seasoning of food products. In this study, essential oils (EOs) and supercritical CO2 extracts from all three species have been analyzed using GC-MS with two columns of different polarity, whereas EO and CO2 extract from P. nigrum fruits and CO2 extract from the peel of C. hystrix have been isolated and analyzed for the first time. The results showed that A. kravanh EO contained mostly eucalyptol (78.8/ 72.6 %), while CO2 extract was rich in oleic acid (29.26 %) and tricosane (14.74 %). C. hystrix EO was rich in β-pinene (29.95/29.45 %), followed by D-limonene (24.54/23.24 %) and sabinene (9.94/10.23 %). β-pinene (30.2/28.9 %), D-limonene (23.99/23.74 %) and sabinene (13.36/19.55 %) were also predominant in the CO2 extracts. β-Caryophyllene was the main constituent of both EO and CO2 extract from P. nigrum 'Kampot' with contents ranging from 37.84 to 55.84 %, followed by 3-carene (from 7.18 to 18.72 %). Such findings suggest that supercritical CO2 can potentially be used for extraction of all three Cambodian spices. Nevertheless, further research determining the most efficient extraction parameters will be needed before its application in the spice processing practice.

The residue of chestnut processing generates a large amount of waste material, a resource not adequately exploited. The phenolic composition of water extracts from discarded pericarp of four (MURG, LOCG, ILDP and COEV) chestnut accessions and one marron variety belonging to the Sardinian biodiversity was studied. The antioxidant capacity of cold and hot water extracts was determined by DPPH, ABTS and cyclic voltammetry tests. The antiproliferative effect on normal cells (fibroblasts), and colon (RKO and SW48), breast (MCF7) and melanoma (B16F10) cancer cells, was evaluated by biological assays. MTT test demonstrated that temperature and different extraction times significantly influenced the growth of cells, both normal and tumor. The fibroblast viability was significantly reduced by moderate doses of cold extracts, but only by doses greater than 250 µg/ml of hot extracts, regardless of the accession or cultivar. An even more marked effect was observed when RKO and SW48 were treated with cold extracts, while treatments on B16F10 melanoma cells resulted less effective. Differently, the cold extracts of all accessions induced a significant increase in MCF7 cell viability starting from moderate doses (50 µg/ml), whereas hot extracts had a similar, but less evident, effect compared to reference fibroblasts.

Nuts are a staple food consumed throughout the world, and their purity is essential to maintaining human health. However, fungal mycotoxins pose one of the real challenges in keeping nuts clean for human consumption. The high cost of equipment, reagents used, standard samples, as well as increased requirements for personnel qualifications limit the use of chromatographic methods in testing laboratories, both manufacturing enterprises and organizations monitoring food safety. The present study aimed to test a new method for extracting aflatoxin B1 using sodium chloride and citric acid instead of methanol present in imported nuts obtained from local markets in Astana (Kazakhstan). The proposed method for extracting aflatoxin B1 from nuts is chemically safe, since the substances used belong to hazard class 3 of the international classification and do not require separate premises in food safety laboratories of the Astana markets and special training of specialists. The technical objective of the method is to replace the reagent (methanol) during the sample preparation process when conducting cocuret enzyme-linked immunosorbent assay. Aflatoxin B1 levels varied depending on the type of nut. Aflatoxin contamination was observed in 35.8% of samples analyzed. These levels of mycotoxin contamination are alarming and raise serious questions about the purity of imported nuts to ensure food safety.

Context: Despite the effort put into developing standards for structuring construction cost, and the strong interest into the field. Most construction companies still perform the process of data gathering and processing manually. That provokes inconsistencies, different criteria when classifying, misclassifications, and the process becomes very time-consuming, particularly on big projects. Additionally, the lack of standardization makes very difficult the cost estimation and comparison tasks. Objective: To create a method to extract and organize construction cost and quantity data into a consistent format and structure, to enable rapid and reliable digital comparison of the content. Method: The approach consists of a two-step method: Firstly, the system implements data mining to review the input document and determine how it is structured based on the position, format, sequence, and content of descriptive and quantitative data. Secondly, the extracted data is processed and classified with a combination of data science and experts’ knowledge to fit a common format. Results: A big variety of information coming from real historical projects has been successfully extracted and processed into a common format with 97.5% of accuracy, using a subset of 5770 assets located on 18 different files, building a solid base for analysis and comparison. Conclusion: A robust and accurate method was developed for extracting hierarchical project cost data to a common machine-readable format to enable rapid and reliable comparison and benchmarking.

The production of polyurethane films from bark-derived polyols requires the complete solubility of all components in the polyurethane synthesis media. In this study, a comprehensive investigation was conducted to achieve the copolymerization of black alder bark water extract-derived polyol with isocyanate for polyurethane film synthesis in THF solution. A fractionation approach using tetrahydrofuran (THF) as a solvent was employed to dissolve the extract, followed by filtration and removal of the solvent. The resulting THF-soluble fraction comprised 62±1% of the dry weight of the alder bark extract, mainly consisting of the xyloside form of the diarylheptanoid compound oregonin, along with oligomeric flavonoids and carbohydrates. The THF-insoluble fraction was the most enriched with carbohydrate compounds, followed by the crude extract and THF-soluble fraction. Another approach was aimed at obtaining bark extractives based liquid polyols suitable for producing rigid PU foams. For this purpose, oven-dried crude black alder bark water extract was liquefied with polyethylene glycol (PEG 400). The liquefaction of black alder bark and pine bark extractives was studied under different conditions, including varying temperature ranges (130-170⁰C), catalyst concentrations (0-1,5%), and bark extract content in the mixture (15-30%). The results showed that the use of sulphuric acid as a catalyst (1-1.5%) significantly improved the solubility of both extractives, enabling the attainment of extract concentrations up to 25% at 170⁰C. However, increasing the extract content beyond a certain threshold led to incomplete solubility. It was shown that the PEG-insoluble fractions consist mainly of carbohydrate components. To increase the content of biomass in liquid polyols, the effect of glycerol additions into the liquefaction agent is under study. The findings provide insights into tailoring bark-sourced polyols for polyurethane foam production through appropriate liquefaction conditions.

Extracting railway tracks is crucial for creating electronic railway maps. Traditional methods require significant manual labor and resources, while existing neural networks have limitations in efficiency and precision. To address these challenges, a railway track extraction method using an improved DeepLabV3+ model is proposed, which incorporates several key enhancements. Firstly, the encoder part of the method utilizes the lightweight network MobileNetV3 as the backbone extraction network for DeepLabV3+. Secondly, the decoder part adopts the lightweight universal upsampling operator CARAFE for upsampling. Lastly, to address any potential extraction errors, morphological algorithms are applied to optimize the extraction results. Additionally, a dedicated railway track segmentation dataset is created to train and evaluate the proposed method. The experimental results demonstrate that the model achieves impressive performance on the railway track segmentation dataset and DeepGlobe dataset. The MIoU scores are 88.93% and 84.72%, with Recall values of 89.02% and 86.96%. Moreover, the overall accuracy stands at 97.69% and 94.84%. The algorithm's operation time is about 5% lower in comparison to the original network. Furthermore, the morphological algorithm effectively eliminates errors like holes and spots. These findings indicate the model's accuracy, efficiency, and the enhancement brought by the morphological algorithm in error elimination.

In this study, we had investigated the use of high-pressure homogenization (HPH) as a novel pretreatment method for the extraction of sodium alginate (SA) from Laminaria japonica. Our results demonstrated that under optimal condition of 100 MPa HPH pressure, 4 cycles, pH 6.0, and 0.5% ethylene diaminetetra acetic acid tetrasodium salt (EDTA) concentration (w/v) for 3.0 hours, the extraction yield of HPH reached 34%, which was higher than that achieved by previous methods such as complex enzyme hydrolysis (CE), ultrasonic-assisted extraction (UAE), and complex enzyme-ultrasonic combined method (CE-UC). To further characterize the extracted SA, we conducted a comprehensive analysis using SEM, FTIR, MRS, NMR, XRD, TGA, and T-AOC assay. Our findings revealed the following: 1) HPH treatment significantly disrupted the structure of L. japonica cells and reduced their crystallinity to 76.27%, the lowest among all pretreatment samples; 2) the extracted SA had a greater tendency to form elastic gels; and 3) the antioxidant activity of HPH-extracted SA reached 0.02942 mgVceq∙mg-1, which was the highest among all tested methods. Based on these results, we concluded that HPH extraction not only increased the yield of SA but also enhanced its antioxidant activity.

The focus of this study was to evaluate the effectiveness of incorporation of phenolic compounds from blueberry juice into pear slices using a combination of ohmic heating (OH) and vacuum impregnation (VI), followed by air- or freeze-drying. The results showed that OH is a valuable technique to increase the content of bioactive compounds and antioxidant capacity of blueberry juice. The optimal OH treatment is heating the juice at 50 °C for 20 min under an electric field of 13 V/cm. Furthermore, the combination of VI and OH showed the efficiency of enriching pear slices with bioactive compounds from blueberry juice. The best treatment is to immerse the slices for 90 min at 50 °C and an electric field of 7.8 V/cm. The presence of anthocyanin pigments from blueberry juice affects the color parameters of pear slices by increasing the a* parameter and decreasing the b* and L* parameters. However, both freeze-drying and air-drying (at temperatures of 40, 50, and 60 °C) negatively affected the phenolic content and antioxidant capacity. Notably, air-drying at 60 °C highest levels of phenolic compounds and antioxidant potential for both impregnated and non-impregnated pear slices among the drying processes applied.

With the proliferation and development of social media platforms, social media data has become an important source for acquiring spatio-temporal information on various urban events. Providing accurate spatio-temporal information for events contributes to enhancing the capabilities of urban management and emergency response. However, existing research on mining spatio-temporal information of events often focuses solely on textual content, neglecting data from other modalities such as images and videos. Therefore, this study proposes an innovative spatio-temporal information extraction method for multi-modal social media data (MIST-SMMD), which extracts the spatio-temporal information of events from multi-modal data on Weibo at coarse and fine-grained hierarchical levels, serving as a beneficial supplement to existing urban event monitoring methods. This paper takes the "July 20th Zhengzhou Heavy Rainfall" incident as an example, to evaluate and analyze the effectiveness of the proposed method. The results indicate that in the coarse-grained spatial information extraction using only textual data, our method achieves a Spatial Precision of 87.54% within a 60m range, and reaches 100% Spatial Precision for ranges beyond 200m. For fine-grained spatial information extraction, the introduction of other modal data such as images and videos results in a significant improvement in Spatial Error. These results demonstrate the ability of the MIST-SMMD method to extract spatio-temporal information from urban events at both coarse and fine levels, and confirms the significant advantages of multi-modal data in enhancing the precision of spatial information extraction.

Covid-19 is a lung disease caused by a Coronavirus family virus. Due to its extraordinary prevalence and death rates, it has spread quickly to every country in the world. Thus, achieving peaks and outlines and curing different types of relapses is extremely important. Given the worldwide prevalence of Coronavirus and the participation of physicians in all countries, Information has been gathered regarding the properties of the virus, its diverse types, and the means of analyzing it. Numerous approaches have been used to identify this evolving virus. It is generally considered the most accurate and acceptable method of examining the patient's lungs and chest through a CT scan. As part of the feature extraction process, a method known as fractional Fourier transform (FrFT) has been applied as one of the time-frequency domain transformations. The proposed method was applied to a database consisting of 2481 CT images. Following the transformation of all images into equal sizes and the removal of non-lung areas, multiple combination windows are used to reduce the number of features extracted from the images. In this paper, the results obtained for KNN and SVM classification have been obtained with accuracy values of 99.84% and 99.90%, respectively.

Phytochemicals are gaining popularity due to their antioxidant effects and potential protection against inflammation, cardiovascular disease, and certain types of cancer. The retention of these phytochemicals during extraction must be maximized. This research focused on extracting bioactive compounds from Psidium guajava Linn leaves using solvent extraction (SE), microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE) with distilled water (DW) or 60% (v/v) ethanol/water (ET). Phytochemical screening demonstrated that all of the screening showed positive results in all extraction methods, except glycoside. There were no significant (p&gt;0.05) differences in total phenolic (TPC) and flavonoid content (TFC) during MAE, SE, and UAE in case of ET. However, SE shows better (p&lt;0.05) extraction of TPC and TFC than UAE and MAE in case of DW. ET shows better (p&lt;0.05) extraction of TPC and TFC than DW. Antioxidant analysis shows the same trend though both DPPH and FRAP values were higher in MAE and SE for ET and DW, respectively. MAE/ET showed the highest inhibitory activity and dose-dependent response using SW480 cell via MTT assay. HPLC and TLC analysis reveal the fingerprint of morin, might function as an anticancer agent. In conclusion, MAE/ET is the most efficient among the extraction techniques in terms of anticancer activity.

The wheat aleurone layer is, according to millers, the main bran fraction. It is a source of nutritionally valuable compounds, such as dietary fibres, proteins, minerals and vitamins, that may exhibit health benefits. Despite these advantages, the aleurone layer is scarce on the market, probably due to issues related to its extraction. Many processes exist with some patents, but a choice must be made between the quality and quantity of the resulting product. Nonetheless, its potential has been studied mainly in bread and pasta. While the nutritional benefits of aleurone-rich flour addition to bread agree, opposite results have been obtained concerning its effects on end-product characteristics (namely loaf volume and sensory characteristics), thus ensuing different acceptability responses from consumers. However, the observed negative effects of aleurone-rich flour on bread dough could be reduced by subjecting it to pre- or post-extracting treatments meant to either reduce the particle size of the aleurone’s fibres or to change the conformation of its components.

Hexane is a solvent used extensively in the food industry for the extraction of various products such as vegetable oils, fats, flavours, fragrances, colour additives or other bioactive ingredients. As it is classified as a "processing aid", it does not have to be declared on the label under current legislation. Therefore, although traces of hexane may be found in final products, especially in processed products, its presence is not known to consumers. However, hexane, and in particular the n-hexane isomer, has been shown to be neurotoxic to humans and has even been listed as a cause of occupational diseases in several European countries since the 1970s. In order to support the European strategy for a toxic-free environment (and toxic-free food), it seemed important to collect scientific information on this substance by reviewing the available literature. This review contains valuable information on the nature and origin of the solvent hexane, its applications in the food industry, its toxicological evaluation and possible alternatives for the extraction of natural products. Numerous publications have investigated the toxicity of hexane, and several studies have demonstrated the presence of its toxic metabolite 2,5-hexanedione (2,5-HD) in the urine of the general, non-occupationally exposed population. Surprisingly, a tolerable daily intake (TDI) has apparently never been established by any food safety authority. Since hexane residues are undoubtedly found in various foods, it seems more than necessary to clearly assess the risks associated with this hidden exposure. A clear indication on food packaging and better information on the toxicity of hexane could encourage industry to switch towards one of the numerous other alternative extraction methods already developed.

Biorefining by enzymatic hydrolysis (EH) of lignocellulosic waste material due to low costs and affordability has received enormous interest amongst scientists as a potential strategy suitable for the production of bioactive ingredients and chemicals. In the present study, a sustainable and eco-friendly approach to the extraction of bound ferulic acid (FA) has been demonstrated using a single-step EH by a mixture of lignocellulose-degrading enzymes. For comparative purposes of the efficiency of EH, an online SFE-SFC-MS extraction and analysis approach was applied. The experimental results demonstrated up to 369.3 mg 100 g−1 FA released from rye bran after 48 h EH with Viscozyme L. The EH of wheat and oat bran with Viscoferm for 48 h resulted in 255.1 and 33.5 mg 100 g−1 of FA, respectively. The extraction of FA from bran matrix using the SFE-CO2-EtOH delivered up to 464.3 mg 100 g−1 of FA, though the extractability varied depending on the parameters used. The 10-fold and 30-fold scale-up experiments confirmed the applicability of EH as a bioprocessing method valid for industrial-scale. The highest yield of FA in both scale-up experiments was obtained from rye bran after 48 h of EH with Viscozyme L. In purified extracts, the absence of xylose, arabinose, and glucose as final degradation products of lignocellulose was proven by a HPLC-RID system. Up to 94.0% purity of FA was achieved by SPE using the polymeric reversed-phase Strata X column and 50% EtOH as eluent.

A major problem in the post-inversion geophysical interpretation is the extraction of geological information from inverted physical property models, which do not necessarily represent all underlying geological features. No matter how accurate the inversions are, each inverted physical property model is sensitive to limited aspects of subsurface geology and is insensitive to other geological features that are otherwise detectable with complementary physical property models. Therefore, specific parts of the geological model can be reconstructed from different physical property models. To show how this reconstruction works, we simulated a complex geological system that comprises an original layered earth model that has passed several geological deformations and alteration overprints. Linear combination of complex geological features comprised three physical property distributions: Electrical resistivity, induced polarization chargeability, and magnetic susceptibility models. This study proposes a multivariate feature extraction approach to extract information about the underlying geological features comprising the bulk physical properties. We evaluated our method in numerical simulations and compared three feature extraction algorithms to see the tolerance of each method to the geological artifacts and noises. We show that the fast-independent component analysis (fast-ICA) algorithm by negentropy maximization is a robust method in the geological feature extraction that can handle the added unknown geological noises. The post-inversion physical properties are also used to reconstruct the underlying geological sources. We show that the sharpness of the inverted images is an important constraint on the feature extraction process. Our method successfully separates geological features in multiple 3D physical property models. This methodology is reproducible for any number of lithologies and physical property combinations and can recover the latent geological features, including the background geological patterns from overprints of chemical alteration.

Existing methods for building extraction from remotely sensed images strongly rely on aerial or satellite-based images with very high resolution, which are usually limited by spatiotemporally accessibility and cost. In contrast, relatively low-resolution images have better spatial and temporal availability but cannot directly contribute to fine- and/or high-resolution building extraction. In this paper, based on image super-resolution and segmentation techniques, we propose a two-stage framework (SRBuildingSeg) for achieving super-resolution (SR) building extraction using relatively low-resolution remotely sensed images. SRBuildingSeg can fully utilize inherent information from the given low-resolution images to achieve high-resolution building extraction. In contrast to the existing building extraction methods, we first utilize an internal pairs generation module (IPG) to obtain SR training datasets from the given low-resolution images and an edge-aware super-resolution module (EASR) to improve the perceptional features, following the dual-encoder building segmentation module (DES). Both qualitative and quantitative experimental results demonstrate that our proposed approach is capable of achieving high-resolution (e.g. 0.5 m) building extraction results at 2×, 4× and 8× SR. Our approach outperforms 8 other methods with respect to the extraction result of mean Intersection over Union (mIoU) values by a ratio of 9.38%, 8.20% and 7.89% with SR ratio factors of 2, 4, and 8, respectively. The results indicate that the edges and borders reconstructed in super-resolved images serve a pivotal role in subsequent building extraction and reveal the potential of the proposed approach to achieve super-resolution building extraction. Our code is available at https://github.com/xian1234/SRBuildSeg.

Atlantic salmon (Salmo Salar) is one of the fish species that rich in omega-3 fatty acids. Consumption of omega-3 fatty acids can lower down the risk of cardiovascular disease and coronary heart disease. The extraction of omega-3 fish oil from Atlantic salmon by using hexane and isopropanol was conducted in this research. Response Surface Methodology (RSM) was used to study the impact of parameters which were temperature (50-90°C), centrifuge speed (1000-3000rpm) and solvent ratio of hexane to isopropanol (0.5-1.5) to the percentage of oil yield. The results obtained shows that 15.23%± 0.61 of oil yield from Atlantic salmon under an optimum condition of 70°C, 3000 rpm and solvent ratio of hexane to isopropanol of 1.5. The acid value, peroxide value and p-anisidine value of the fish oil obtained were 7.48 mg KOH/g, 1.94 meq/kg and 5.56 respectively which were all within the acceptable limit which stipulated by Global Organization for EPA and DHA (GOED) and Food and Agricultural Organization of the United Nations (FAO). The FTIR analysis proved the presence of alkane and carboxylic acid in the fish oil. Furthermore, GC-MS analysis showed that the fish oil contains higher monounsaturated fatty acids (MUFA) contents followed by polyunsaturated fatty acids (PUFA) and 4.5525% of total omega-3 fatty acids.

Although rRT-PCR is the gold standard method for SARS-CoV-2 detection, some factors, such as amplification inhibitors presence, lead to false-negative results. Here we describe differences between rRT-PCR results for SARS-CoV-2 infection in normal and diluted samples, simulating the need for dilution due to amplification inhibitors presence. Viral RNA extraction of nasopharyngeal swabs samples from 20 patients previously detected as 'Negative' and 21 patients detected as 'Positive' for SARS-CoV-2 was realized with the EasyExtract DNA-RNA (Interprise®). rRT-PCR was realized with OneStep/COVID-19 (IBMP) kit with normal and diluted (80µl of H₂O RNAse free) samples, totaling 82 tests. The results indicate that there is an average variation (ɑ < 0.05) delaying Cq between the amplification results of internal control (IC), N Gene (NG), and ORF-1ab (OF) of 1.811 Cq, 3.840 Cq, and 3.842 Cq, respectively. The extraction kit does not completely purify the inhibitor compounds, therefore non-amplification by inhibitors may occur. In this study, we obtained a 19.04% false-negative diagnosis after sample dilution, and this process reduces the efficiency of rRT-PCR to 29.80% for detecting SARS-CoV-2. Knowing the rRT-PCR standards of diluted samples can help in the identification of false-negative cases, and consequently avoid a wrong diagnosis.

Many classic visual monocular SLAM systems have been developed over the past decades, however, most of them will fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments based on ORB-SLAM. The article mainly concentrates on two aspects. Firstly, DLRSAC is proposed to extract static features from the dynamic scene based on awareness of nature difference between motion and static, which is integrated into initialization of DM-SLAM. Secondly, we design candidate map points selection mechanism based on neighborhood mutual exclusion to balance the accuracy of tracking camera pose and system robustness in motion scenes. Finally, we conduct experiments in the public dataset and compare DM-SLAM with ORB-SLAM. The experiments verify the superiority of the DM-SLAM.

Many corner detector techniques have already been used in extracting information from UAV images to perform various photogrammetric and mapping activities. Among these techniques is the Feature from Accelerated Segment Test (FAST) and the Harris corner detector. It is widely agreed that the evaluation of detectors is of great importance because it evaluates and enhances the accuracy of the detected features. This research evaluates the performance of FAST-9 and FAST-12 as well as the Harris detector in terms of the repeatability rate, completeness, and correctness under different threshold values. Each method is evaluated in terms of its ability for detection UAV objects (crowd and cars features). Then the common detected features between both FAST versions and the Harris detector are extracted. This is to determine which method performs best under different image conditions (e.g., illumination variations, camera position and orientation, and image noise). The results show that the size of the threshold plays a crucial role in determining the number of detected feature points. An increase in the threshold value leads to a decrease in the number of detected points and vice versa. Thus, the correctness decreases whereas the completeness increases as a function of the threshold values. Furthermore, the relationship between the FAST-9 and the Harris detector is slightly better than those between the FAST-12 and the Harris detector. This is because the number of common features between the FAST-9 and the Harris detector are relatively higher than those between the FAST-12 and the Harris detector.

The objective to fast-track the mapping and registration of large numbers of unrecorded land rights globally, leads to the experimental application of Artificial Intelligence (AI) in the domain of land administration, and specifically the application of automated visual cognition techniques for cadastral mapping tasks. In this research, we applied and compared the ability of rule-based systems within Object Based Image Analysis (OBIA), as opposed to human analysis, to extract visible cadastral boundaries from Very high resolution (VHR) World View-2 image, in both rural and urban settings. From our experiments, machine-based techniques were able to automatically delineate a good proportion of rural parcels with explicit polygons where the correctness of the automatically extracted boundaries was 47.4% against 74.24% for humans and the completeness of 45% for machine, as against 70.4% for humans. On the contrary, in the urban area, automatic results were counterintuitive: even though urban plots and buildings are clearly marked with visible features such as fences, roads and tacitly perceptible to eyes, automation resulted in geometrically and topologically poorly structured data, that could neither be geometrically compared with human digitised, nor actual cadastral data from the field. These results provide an updated snapshot with regards to the performance of contemporary machine-drive feature extraction techniques compared to conventional manual digitising.

Bauxite residue is the voluminous by-product of alumina production after Bayer process. Its high alkalinity causes disposal problems and harmful environmental impacts. However, the residue contains significant amounts of valuable elements such as rare earth elements including scandium. Greek bauxite residue contains a high amount of scandium close to its main resources. Taking into account scandium limited availability coupled with its high demand in modern technology, bauxite residue could be considered as a potential resource for scandium recovery. In this study, the optimization of scandium extraction from bauxite residue with sulfuric acid is investigated using Taguchi methodology. Based on previous studies acid molarity, leaching time, solid/liquid ratio and reaction temperature were selected as control parameters for the selective Sc recovery. Method optimization targeted the highest concentration of scandium combined with the lowest concentration of iron without taking into account applications constraints. The predicted values resulted by Taguchi methodology were affirmed by a confirmation experiment conducted at optimal conditions. Regression analysis provided the respective equations to be applied on several conditions depending on different applications.

Introduction: Novel robotic surgery systems (da Vinci Xi) are superior to classical open and laparoscopic techniques with its clear and three-dimensional view. We aimed to present the first case low anterior resection of rectal cancer and vaginal specimen extraction with Da Vinci Xi.Case: A 75-year-old female patient with rectum adenocarcinoma was undergone robotic-assisted low anterior resection (LAR) of the rectum, vaginal removal of the specimen, colorectal anastomosis and loop ileostomy. The operation time was 190 minutes. There were no postoperative complications. Pathological tumor stage was stage pT1N0 with negative proximal, distal and radial resection margins. The patient was discharged on the third postoperative day.Conclusion: Robot-assisted LAR, total mesorectal excision, vaginal removal of the specimen, colorectal anastomosis, and loop ileostomy can be performed easily and safely with Da Vinci Xi at early stage rectal cancer. And the vaginal extraction of the specimen avoids us from a traditional abdominal incision.

Numerous protocols have been published for extracting DNA from phlebotomines. Nevertheless, their small size is generally an issue in terms of yield, efficiency, and purity, for large-scale individual sand fly DNA extractions when using traditional methods. Even though this can be circumvented with commercial kits, these are generally cost-prohibitive for developing countries. We encountered these limitations when analysing parasite infection in Lutzomyia spp. by PCR [1] and, for this reason, we evaluated various modifications on a previously published protocol ([2] and Acardi personal communication). The most significant variation was the use of a different lysis buffer [3] to which added Ca2+ (buffer TESCa), because this ion protects proteinase K against autolysis, increases its thermal stability, and could have a regulatory function for its substrate-binding site [4]. Individual sand fly DNA extraction success was confirmed by amplification reactions using internal control primers that amplify a fragment of the cacophony gene [5,6]. To the best of our knowledge, this is the first time a lysis buffer containing Ca2+ has been reported for the extraction of DNA from sand flies.

The aim of this paper is to develop an intelligent event-driven Electrocardiogram (ECG) processing module in order to achieve an efficient solution for diagnosis of the cardiac diseases. The suggested method acquires the signal with an event-driven A/D converter (EDADC). The output of EDADC is passed through the activity selection and interpolation blocks. It allows focusing only on the important signal parts and resampling it uniformly. Later on, the signal is de-noised. The autoregressive (AR) method is used to extract the classifiable features of the de-noised signal. Afterwards, the output is classified by employing different robust classification techniques such as support vector machines (SVMs), K- Nearest Neighbor (KNN) and Artificial Neural Network (ANN). The event-driven feature enables to adapt the system processing load according to the signal temporal variations. This interesting feature of the devised system aptitudes a drastic reduction in its processing activity and therefore in the power consumption as compared to the traditional ones. A comparison of the performance of different classifiers is also made in terms of accuracy. Results show that the proposed system is a potential candidate for an automatic diagnosis of the cardiac diseases.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

Saliency detection in synthetic aperture radar (SAR) image is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR image. Firstly, we extract four features of SAR image as the input of the MSD model, which include the intensity, orientation, uniqueness and global contrast. Then, the saliency map is generated by the multitask sparsity pursuit (MTSP) which integrates the multiple features collaboratively. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps of the source images, an image fusion method is proposed for the SAR and color optical image fusion. The experimental results of real data show the proposed image fusion method is superior to the presenting methods in terms of several universal quality evaluation indexes, as well as in the visual quality. The salient areas in the SAR image can be highlighted and the spatial and spectral details of color optical image can also be preserved in the fusion result.

Beaches are among the habitats most frequented by migratory birds for breeding and/or wintering. However, threats such as human pressure and sea level rise can reduce the availability of these habitats for different species. The presence of alternative areas, such as salt pans and brackish habitats, is essential for many migratory shorebird populations. This study addresses the post-breeding dispersal of the Kentish plover (Charadrius alexandrinus) in the Iberian Peninsula by analysing C and N isotopes in feathers. The study was conducted at six locations along the Iberian coast, which were categorized in three areas: NW Atlantic coast, the Atlantic coast of Andalusia and the Mediterranean coast. Although linear mixed models did not reveal any significant effects of sex or coastal area on isotopic levels, the variability in the data suggests different habitat-use strategies in the post-reproductive period. Birds from the northwest of the Iberian Peninsula exhibit greater fidelity to a single habitat type, i.e. coastal beaches, while populations from the Mediterranean coast and the Atlantic coast of Andalusia show different individual dispersal strategies, occupying coastal habitats and freshwater wetlands. The lack of alternative habitats for the northwest Iberian population, the reduction in available habitat due to rising sea levels and human pressure together pose a serious threat to the survival of this species, already with an unfavourable conservation status.

Background: Traumatic events adversely affect the clinical course of obsessive-compulsive disorder (OCD). Our investigation explores the correlation between prolonged interpersonal trauma and the severity of symptoms related to obsessive-compulsive and anxiety disorders. Methods: The study follows a cross-sectional and observational design, employing the International Trauma Questionnaire (ITQ) to examine areas linked to interpersonal trauma, the Hamilton Anxiety Rating Scale (HAM-A), and the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) to assess anxious and obsessive-compulsive symptoms, respectively. Descriptive analysis, analysis of variance (ANOVA), and logistic regression analyses were conducted. Results: We recruited 107 OCD-diagnosed patients, categorizing them into subgroups based on the presence or absence of complex post-traumatic stress disorder (cPTSD). The ANOVA revealed statistically significant differences between the two groups in the onset age of OCD (p=0.083), psychiatric familial history (p=0.023), HAM-A, and Y-BOCS (p=0.000). Logistic regression indicated a statistically significant association between the presence of cPTSD and Y-BOCS scores (p=0.000). Conclusion: The coexistence of cPTSD in OCD exacerbates obsessive-compulsive symptoms and increases the burden of anxiety. Further advancements in this field are crucial for mitigating the impact of early trauma on the trajectory of OCD and associated anxious symptoms.

Background and aims: For many surgical procedures, spinal anesthesia is a reliable and efficient anesthetic approach. Numerous drugs have been reported to be administered to intrathecal local anesthetics as adjuvants to increase the efficacy of spinal anesthesia. There is little evidence of the effect of intrathecal dexmedetomidine on pain scores and the consumption of analgesia postoperatively. Methods: After obtaining ethical approval, demographical and clinical data of patients who underwent surgical procedures under spinal anesthesia with intrathecal dexmedetomidine or fentanyl was collected and analyzed. Results: In this study with 96 patients, intrathecal dexmedetomidine (group D) resulted in significantly lower post-operative pain scores compared to intrathecal fentanyl (group F) (p=0.000). Across various surgical types, including Orthopedic, General, Urology, and Obs/Gyne procedures, group D consistently displayed reduced pain scores (p&lt;0.001). The number of patients who needed post-operative analgesia was significantly higher in group (F) than in group (D) (40 vs 23, p=0.002). Conclusion: Compared to fentanyl, intrathecal dexmedetomidine as an adjuvant to local anesthesia was found to lower post-operative pain scores and decrease the need for post-operative analgesia.

ICT and digital technology adoption, sustainable development, community empowerment and local wisdom and destinations uniqueness are keywords that will be further explored in the de-velopment of tourism villages in Kenderan as the most importance of tourism destinations de-velopment from the village level. Therefor this research is aimed at developing suitable model for post smart or wise tourism village through proposing Culture and Tradition Festival and the application of a circular economy. Circular economy development in tourism villages focuses on the application of sustainable production principles in the tourism value chain, namely in creating tourism experiences together with tourists (co-creation of experience) and integrated in a tourism system that supports environmental sustainability. This research is applied research conducted with a sequential mixed method research by conducting qualitative research through expert judgment and quantitative research by circulating questionnaire to tourists visiting Kenderan village, while the collected data is analyzed by Structural Equation Modelling to see the rela-tionship between variables. The results of this research show that creative event as the locality aspects of tourist village, digital competence, and sustainability practice are the building blocks of post smart tourism village, while digital competence and sustainable practice have significant mediating effect of locality on post smart tourism village. To make tourism village possesses sustainable competitive advantages, the village must explore and promote its locality aspects to differentiate its tourist village by identifying the valuable, rare, inimitable and non-substitutable tourism resources. The implication of this research is that to develop smart tourism destination wiser and distinctive, tourist village should explore their local values and resources, embed them into its tourism basic components and core resources, and co create, distribute, deliver and promote it to global market through technology adoption and global sustainability value.

Objective: To assess the recovery of voice in patients with unilateral vocal cord paralysis after thyroid surgery following treatment with nursing intervention combined with voice training. Methods: Thirty patients with unilateral vocal cord paralysis and hoarseness for 6-12 months post-thyroid surgery were selected. They first underwent two weeks of psychological and cognitive intervention, followed by a psychological resilience assessment, and then proceeded with 12 weeks of voice training. This training primarily included muscle relaxation exercises, breathing training, and phonation exercises. A comparative analysis was conducted on the patients' voice parameters before and after the training, including jitter, shimmer, maximum phonation time (MPT), noise to harmonic ratio (NHR), and the Voice Handicap Index (VHI) scores. Results: After psychological and cognitive intervention, scores for optimism, resilience, and self-strength among the 30 patients increased. Post-voice training, reductions were observed in jitter, shimmer, NHR, and VHI scores, the Maximum Phonation Time (MPT) increased compared to pre-training, with the difference being statistically significant (P<0.05). Conclusion: Nursing intervention combined with voice training can effectively improve voice quality in patients with unilateral vocal cord paralysis after thyroid surgery.

Background: Chronic post-surgical pain is a condition persisting at least three months after surgery. It is estimated that 25-60% of patients who underwent breast cancer removal surgery suffer from post-mastectomy pain syndrome and occurred anxiety, depression, sleep disturbance and catastrophizing. Physical activity can reduce the risk of chronic diseases and has a good impact on mood and cognitive function. Aim of this study was to evaluate the effects of physical activity on the intensity of pain, depression and anxiety in women underwent mastectomy for breast cancer removal. Methods: A prospective observational unicentric cohort study was performed. Patients were female underwent unilateral or bilateral mastectomy. Numerical Rating Scale (NRS), was used to assess pain intensity, Beck’s Depression Inventory (BDI) for depression and Generalized Anxiety Disorders-7 (GAD-7), for anxiety evaluation. Physical activity was assessed by International Physical activity questionnaire (IPAQ). Interleukin (IL)-17, IL-1β, cortisol, adrenocorticotropic hormone (ACTH) and brain-derived neurotrophic factor (BDNF) were also evaluated in the blood of patients. All the evaluation was assessed 3 and 6 months after the surgery. Results: Adequate physical activity reduced intensity of pain, depression and anxiety symptoms in women affected by post-mastectomy pain syndrome. Moreover, adequate active women, showed a reduction of biomarkers of inflammation, cortisol, ACTH and an increase of BDNF. Conclusions: Our results suggest that physical activity can improve quality of life, reducing intensity of pain, inflammatory markers and it can be useful in the reduction of associated anxiety and depression.

Keywords: Post-Stroke; Hyperbaric oxygen therapy; Sequelae; Feasibility; Out-patient.

Considering the importance of assessing the impacts resulting from a sport career, this study aimed at developing and validating a semi-structure interview guide suitable for quantifying the socio-demographic and epidemiological profile of former professional football players. Based on the theoretical frameworks and several methodological procedures, an interview guide was de-veloped, consisting of 3 areas of conceptual organization (A1. Biographical data; A2. Career data; and A3. Post-Career Transition data) and 8 data collection categories (C1. Personal data; C2. Pro-fessional data; C3. Socio-demographic pathway in the post-career; epidemiological pathway; C4. Epidemiological pathway; C5. Moment of leaving the career; C6. Socio-demographic pathway in post-career; C7. Epidemiological pathway in the post-career; and C8. Perceptions on post-career planning). The construction and validation of the interview guide following 4 steps: Ad hoc con-struction of the interview guide (step 1); Review of the interview guide by a panel of experts (step 2); Definition of procedures and protocol for the application of the interview (step 3); Application of the pilot study for face validation of the interview guide (step 4). Thus, in procedural terms, four stages were considered for the construction and validation of the interview guide, namely the Ad hoc construction of the interview guide (i), the review of the in-terview guide by a panel of experts (ii), definition of procedures and protocol for the application of the interview (iii), and the application of the pilot study for the face validation of the interview guide (iv). The results showed that the interview guide for the study of the impacts of the sports careers on the quality of life of Portuguese former football players shows reliability for the collec-tion of qualitative and quantitative information from the respective content analysis. The use of the interview guide characterizes the path of former player, providing information and knowledge on the socio-demographic and epidemiological impact factors resulting from their post-career (sports retirement).

This study intricately explores the evolving tapestry of Christmas celebrations in a post-pandemic era, where tradition delicately intertwines with technology. The literature review presents a global panorama of Christmas observances, delving into varied religious perspectives. Within this exploration, a Southeast Asian country discreetly initiates its festivities as early as September—a nuanced response to the profound significance of Christmas. Navigating the digital age, the paper dissects the impact of virtual gatherings, the surge in e-commerce, and digital church services on festive traditions. Employing diverse research methods, including thematic analysis, nuanced insights are synthesized from extensive literature reviews, interviews, and observations. Scrutinizing challenges posed by the digital divide, the erosion of personal connections in virtual gatherings, and sustainability concerns in online celebrations, the qualitative research methodology reveals the interplay between tradition and technology. The paper contemplates the future of Christmas in this transformative era, offering implications for future celebrations, technology developers, policymakers, and beyond. This endeavor invites contemplation on the dynamic interplay shaping the festive landscape and prompting reflection on future celebrations.

In conclusion, this qualitative exploration has unveiled the profound and essential impact of music on psychological well-being, especially in the post-pandemic world. Through in-depth literature reviews, informal interviews, and observations with thirty CAS participants from SMC, the researcher uncovered ten salient themes that collectively illustrate music's multifaceted role as a potent remedy. These findings showcase how music serves as an emotional outlet, a cognitive enhancer, and a source of inspiration. The emotional depth and spiritual resonance participants associate with music underscore its capacity to address diverse human needs, making it an indispensable tool in navigating the complexities of our post-pandemic reality. Moreover, the cognitive benefits observed, such as improved concentration and focus, are particularly pertinent in the context of remote work and education, highlighting music's necessity in our daily lives. Additionally, this study emphasizes the vital role of virtual music communities in fostering social connections, even amidst physical isolation, further underscoring the enduring relevance of music in these challenging times. This research contributes to the expanding knowledge of music's impact on well-being, offering a holistic perspective encompassing spiritual, emotional, social, and cognitive dimensions. It enriches existing music psychology theories and invites further exploration into the mechanisms underpinning music's diverse effects. These insights have practical implications for fields such as mental health, education, and remote work, where music can be utilized as an essential tool for stress reduction and emotional regulation. This is highlighted further in the Suggested songs that can help sought the mind, body, spirit and soul. Looking ahead, future research could delve deeper into the long-term impact of music engagement on well-being and explore the universality of music's benefits through cross-cultural studies. Overall, music, as illuminated by this study, stands as a timeless and indispensable companion, offering solace, inspiration, vitality, and connection in the face of any contemporary challenges.

ACE2 impact on the severity of COVID-19 is widely discussed but still controversial. To estimate its role in aspects of the main risk factors and comorbidities, we involved post-COVID-19 patients in Ternopil region (Ukraine). Recruitment period was July 2020 to December 2021. Medical records, treatment modalities and outcomes were recorded and analyzed. Serum human ACE2 protein was measured with Cusabio ELISA kits (Houston, TX, USA). Statistical analysis was performed with SPSS21.0 software (SPSS Inc., Chicago, IL, USA). The level of ACE2 serum protein was significantly higher (p < 0.001) in patients with mild symptoms compared to more severe course of disease, and inversely had changed from 1 to 90 days after recovery. In patients with mild COVID-19, ACE2 level significantly decreased over time, while among critical patients, it increased by 34.1percent. Such results could be explained by ACE2 shedding from tissues into circulation. Loss of the membrane-bound form of the enzyme decreases the virus entry into cells. Our studies did not identify any sex-related ACE2 serum levels correlation. The most common comorbidities were hypertension, cardiovascular diseases, respiratory diseases and diabetes mellitus. All comorbidities except respiratory diseases contribute to the severity of disease and correlate with ACE2 blood serum level.

The long-term laboratory aspects of the effects of COVID-19 on liver function are still not well understood. Therefore, this study aimed to evaluate the hepatic clinical-laboratory profile of patients with up to 20 months of long-term COVID-19. A total of 243 patients of both sexes aged 18 years or older hospitalised in the acute phase of COVID-19 were included in this study. Liver function analysis was performed. Changes were identified in the mean levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), gamma-glutamyl transferase (GGT), and ferritin. Inflammatory markers such as ferritin > 300 U/L were observed in the group that presented more changes in liver function markers (ALT, AST, and GGT). Age ≥ 60 years, male sex, AST > 25 U/L, and GGT ≥ 50 or 32 U/L were associated with ALT > 29 U/L. There was a correlation between ALT and AST, LDH, GGT, and ferritin. Our findings suggest that ALT and AST levels may be elevated in patients with long-term COVID, especially in those hospitalised in the acute phase. In addition, ALT > 29 U/L was associated with other markers of liver injury, such as LDH, GGT, and ferritin.

In the Valpolicella area (Verona - Italy) Vitis vinifera cv. Corvina is the main grape variety used to produce Amarone wine. Before starting the winemaking process, the Corvina grapes are stored in a withering (i.e., dehydrating) warehouse until about 30% of the berry weight is lost (WL). This practice is followed to have the chemical metabolites concentrate in the berry and enrich the Amarone wine in aroma and antioxidant compounds. In compliance with the guidelines and strict Amarone protocol set by the Consorzio of Amarone-Valpolicella, withering must be carried out by setting the grapes in a suitable environment, either under controlled relative air humidity (RH) conditions and wind speed (WS) – no temperature modification is to be applied – or, following the traditional methods, in open-air natural environmental conditions. In general, the two processes have different dehydration kinetics due to the different conditions in terms of temperature, RH, and WS, which affect the accumulation of sugars and organic acids and the biosynthesis of sec-ondary metabolites such as stilbenes and glycoside aroma precursors. For this study, the two grape-withering processes were carried out under controlled (C) and not-controlled (NC) condi-tions and the final compositions of the Corvina dried grapes were compared also to evaluate the effects on the organoleptic characteristics of Amarone wine. The findings highlighted differences between the two processes mainly in terms of the secondary metabolites of the dried grapes, which affect the organoleptic characteristics of Amarone wine.

Post-Shoah Christology is embedded in the unique relationship of Jews and Christians, especially Jesus’ Jewishness and the Jewish roots of Christianity, as well as Christian moral failures towards Jews before and during the Shoah. Essential for contemporary Christianity, a vibrant post-Shoah Christology confronts three main challenges, each demanding a different response. The first challenge is the reality that soon there will be no more first-generation witnesses to the Final Solution. Such is an inevitable challenge that has to be faced and prepared for. Religious pluralism is the second challenge, and includes a number of related threads, yet should ultimately be embraced. The third challenge is the (inevitable?) loss of memory, passion, and urgency, a willful forgetfulness by Christians towards the importance of the Jewish-Christian relationship, and especially, Christian failure in the Shoah. This challenge demands robust refutation and ongoing struggle. Before addressing these challenges, I will first further define and highlight the need for a post-Shoah Christology and will conclude this article with three general and three concrete hopes for a viable post-Shoah Christology.

Two ligands, 1, 3-bis(4-carboxyphenyl)imidazolium chloride and 4, 4՛-bipyridine, were employed to prepare nickel and zinc azolium based MOFs, 1 and 2 by the mixed ligand solvothermal approach. The positively charged azolium moieties in the imidazolium linker resulted in a charged environment in the as-synthesized frameworks. As a result, 1 and 2 demonstrated preferential adsorption of CO2 over methane molecules in the gas phase adsorption due to the higher quadruple moment of CO2, which interacts more with the positively charged frameworks. Besides, in aqueous media, 1 and 2 exhibited incredible adsorption efficiency for anionic dyes. In the following, MOF 1 was metallated at the carbene site of the azolium linker to generate the novel heterogeneous catalyst 1-Pd, which was successfully applied for Sonogashira and Suzuki-Miyaura coupling reactions without losing its activity after three cycles.

Post-mortem cardiac magnetic resonance (PMCMR) is an emerging tool supporting forensic medicine for the identification of the causes of cardiac death, as hypertrophic cardiomyopathy (HCM). We proposed a new method of PMCMR to diagnose HCM despite myocardial rigor mortis. Methods: we performed CMR in 49 HCM patients, 30 non-HCM hypertrophy and 32 healthy controls. In cine images, rigor mortis was simulated by the analysis of the cardiac phase corresponding to the 25% of diastole. Left ventricular mass, mean and standard deviation (SD) of WT, maximal WT, minimal WT and their difference, were compared for the identification of HCM. These parameters were validated at PMCMR, evaluating 8 hearts with HCM, 10 with coronary artery disease and 10 with non-cardiac death. Results: The SD of WT with a cut-off of > 2.4 had the highest accuracy to identify HCM (AUC 0.95, 95%CI 0.89-0.98). This was particularly evident in female population of HCM (AUC=0.998), with 100% specificity (95%CI 85-100%) and 96% sensitivity (95%CI 79-99%). Using this parameter, at PMCMR all the 8 patients with HCM were correctly identified with no false positive. Conclusions: PMCMR allows to identify HCM as cause of sudden death using the SD of WT >2.4 as diagnostic parameter.

n our previous paper, we showed that the so-called quantum entanglement also exists in classical mechanics. The inability to measure this classical entanglement was rationalized with the definition of a classical observer which collapses all entanglement into distinguishable states. It was shown that evidence for this primary coherence is Newton’s third law. However, in reformulating a "classical entanglement theory" we assumed the existence of Newton’s second law as an operator form where a force operator was introduced through a Hilbert space of force states. In this paper, we derive all related physical quantities and laws from basic quantum principles. We not only define a force operator but also derive the classical mechanic's laws and prove the necessity of entanglement to obtain Newton’s third law.

Data on pathologic changes of the 2019 novel coronavirus disease (COVID-19) are scarce. To gain knowledge about the pathology that may contribute to disease progression and fatality, we performed post-mortem needle core biopsies of lung, liver, and heart in four patients who died of COVID-19 pneumonia. The patients’ ages ranged from 59 to 81, including 3 males and 1 female. Each patient had at least one underlying disease, including immunocompromised status (chronic lymphocytic leukemia and renal transplantation) or other conditions (cirrhosis, hypertension, and diabetes). Time from disease onset to death ranged from 15 to 52 days. All patients had elevated white blood cell counts, with significant rise toward the end, and all had lymphocytopenia except for the patient with leukemia. Histologically, the main findings are in the lungs, including injury to the alveolar epithelial cells, hyaline membrane formation, and hyperplasia of type II pneumocytes, all components of diffuse alveolar damage. Consolidation by fibroblastic proliferation with extracellular matrix and fibrin forming clusters in airspaces is evident. In one patient, the consolidation consists of abundant intra-alveolar neutrophilic infiltration, consistent with superimposed bacterial bronchopneumonia. The liver exhibits mild lobular infiltration by small lymphocytes, and centrilobular sinusoidal dilation. Patchy necrosis is also seen. The heart shows only focal mild fibrosis and mild myocardial hypertrophy, changes likely related to the underlying conditions. In conclusion, the post-mortem examinations show advanced diffuse alveolar damage, as well as superimposed bacterial pneumonia in some patients. Changes in the liver and heart are likely secondary or related to the underlying diseases.

In 2010, Parties to the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 to address the loss and degradation of nature. Subsequently, most biodiversity indicators continued to decline. Nevertheless, conservation actions can make a positive difference for biodiversity. The emerging Post-2020 Global Biodiversity Framework has potential to catalyze efforts to ‘bend the curve’ of biodiversity loss. Thus, the inclusion of a goal on species, articulated as Goal B in the Zero Draft of the Post-2020 Framework, is essential. However, as currently formulated, this goal is inadequate for preventing extinctions, and reversing population declines; both of which are required to achieve the CBD’s 2030 mission. We contend it is unacceptable that Goal B could be met while most threatened species deteriorated in status and many avoidable species extinctions occurred. We examine the limitations of the current wording and propose an articulation with robust scientific basis. A goal for species that strives to end extinctions and recover populations of all species that have experienced population declines, and especially those at risk of extinction, would help to align actors towards the transformative actions and interventions needed for humans to live in harmony with nature.

We aimed to evaluate the safety of maternal Tdap we assessed health events by examining the difference in birth and hospital-related outcomes of infants with and without fetal exposure to Tdap. This was a retrospective cohort study using linked administrative datasets. The study population were all live-born infants in New Zealand (NZ) weighing at least 400 grams at delivery and born to women who were eligible for the government funded, national-level vaccination program in 2013. Infants were followed from birth up to one year of age. There were a total of 69,389 eligible infants in the cohort. Of these, 8,299 infants were born to 8,178 mothers exposed to Tdap (12%), primarily between 28-38 weeks gestation as per the national schedule. Among the outcomes, we found a reduced risk for moderate to late preterm birth, low birth weight, small for gestational age, large for gestational age, respiratory distress syndrome, transient tachypnea of newborn, tachycardia or bradycardia, haemolytic diseases, other neonatal jaundice, anaemia, syndrome of infant of mother with gestational diabetes, and hypoglycemia in infants born to vaccinated mothers. There was no association between maternal Tdap and stillbirth, infant Apgar score at 5 minutes after birth, microcephaly, asphyxia, sepsis or infection, or hypoxic ischemic encephalopathy. Infant exposure to Tdap during pregnancy was associated with a higher mean birthweight (not clinically significant) and higher odds for ankyloglossia and neonatal erythema toxicum diagnoses. There were insufficient observations to allow examination of the effect of Tdap on extreme preterm and very preterm birth, and infant death. Overall, we found no outcomes of concern associated with the administration of Tdap during pregnancy.

Background: Whilst lack of concentration is a known symptom of anaemia, its association with post-stroke dementia is unclear. Methods: We used data from a UK regional stroke register. To be eligible, patient must have survived to discharge and had anaemia by WHO criteria. Dementia status and other prevalent co-morbidities were assessed using ICD-10 codes. Patients were followed till May 2015 (mean follow-up 3.7 years, total person years = 27,769). Hazard Ratio for incident dementia was calculated using Cox-proportional hazards model controlling for potential confounders. Fine and Gray model was additionally constructed using mortality as the competing risk. Results: A total of 7,454 stroke patients were included with mean age (SD) of 75.9(12.3) years (50.2% men). Those with anaemia were older, has higher disability and co-morbidity burden prior to stroke. We observed a large amount of variation in the dementia incidence rates over time and that the hazard ratio increased every year. The significant association between anaemia and dementia incidence was lost after controlling for pre-stroke Modified Rankin score (HR1.17(0.97,1.40)). With every 20g/dL increase in Hb was associated with a significant reduction in the risk of dementia after adjustment for age, sex, stroke factors and disability but lost significance after adjustment for vascular risk factors. Competing risk analyses showed similar results. Conclusion: Whilst we found no evidence of anaemia as a risk factor for post-stroke dementia, the findings may be limited by potential under recognition of post stroke dementia.

Soccer is the most played sport worldwide, with over 265 million participants. It is an incredibly demanding sport, with many different technical skills and physical loads placed on the body. This makes post-match recovery strategies amongst high level soccer players of great importance. The aim of this review is to summarize the existing literature on stretching for post-match recovery, examining its relation to injury prevention, Delayed Onset Muscle Soreness (DOMS), and performance. Scientific evidence of the highest quality and relevance was extracted and reviewed. Despite its common practice, evidence does not support static stretching as a modality to improve recovery post-match amongst soccer players. Larger trials with important outcome measures are needed to determine if a post-match stretching regimen to facilitate recovery exists.

The current urban environment is faced with the potential threat of frequent natural disasters, and the sustainable development of post-disaster community has become a global issue. As an intrinsic motivation influencing the social interaction and capital operation of community, social network is an important mechanism promoting such sustainable development. However, the difference in social network caused by different member structure, spatial arrangement and management mechanism of post-disaster communities in different reconstruction modes has influenced such sustainable development process. Therefore, reasonable selection of reconstruction mode is crucial. This paper applied analytic hierarchy process to comprehensively measure and compare the social network strength in post-disaster communities in the four reconstruction modes adopted by the government of China, i.e. unified planning and unified construction, unified planning and independent construction, in situ reconstruction and relocation resettlement, with communities after the 2008 Sichuan earthquake in Chengdu, China as study objects from the perspective of three social relations (the relations between residents and residents, residents and managers, and residents and servers). The results showed that strong connections are generally presented in the social network of post-disaster communities in unified planning modes, that the strength is significantly higher than that of those in non-unified planning modes, and that the strength of UPIC communities is the highest. Meanwhile, government intervention, residents’ free participation and market operation are positively correlated to government trust, community interaction and community service respectively. The positive impact of government intervention is the most significant, but it has a peak value. No government management and excessive government intervention will exert negative impacts. The coordination of government, society and market is the key contents of post-disaster community reconstruction. The reconstruction modes based on “government leadership, resident participation and market operation” may become a feasible path for such sustainable development.

Connexins are tetraspan transmembrane proteins that form gap junctions and facilitate direct intercellular communication, a critical feature for the development, function and homeostasis of tissues and organs. In addition, a growing number of gap junction-independent functions are being ascribed to these proteins. The connexin gene family is under extensive regulation at the transcriptional and post-transcriptional level, and undergoes numerous modifications at the protein level, including phosphorylation, which ultimately affects their trafficking, stability and function. Here, we summarize these key regulatory events, with emphasis on how these affect their multi-functionality in health and disease.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

Lavander distillation leads to huge quantities of solid waste produced yearly. This waste is usually discarded resulting in serious environmental issues. However, it still contains residual essential oil and other bioactive compounds. This research reports on the development and comparison of optimized solid-liquid separation methods, i.e. microwave (MAE) and ultrasound assisted extraction (UAE) of phenolic compounds from lavender distillation waste. Optimal pretreatment conditions, such as waste moisture content and particle size were also determined. The extracts were spray or freeze-dried and the resulting powders were characterized for their physicochemical properties. The majority of the original phenolic compounds in lavender were found in the leachate fraction after distillation (61%), while 43% in the solid waste. Drying of the solid waste before extraction affected the process efficiency. UAE led to higher phenolic content and antioxidant properties compared to MAE. Drying (spray or freeze) the extracts did not significantly affect their phenolic content, while the use of maltodextrin as a drying agent improved the drying process yield especially in the freeze-drying method. It is concluded that valorization of lavender distillation wastes can be achieved via an integrated process consisting of a green extraction method and a consequent drying process that result in a stable bioactive powder.

German chamomile galenic preparations are used to treat mild skin diseases, inflammation and spasms, and they have also reported to have anxiolytic and sedative effects. The medicinal use of chamomile is well-known in ethnomedicine. Since chamomile has shown to have some adverse effects, there is a need to develop new formulations, such as dry extracts, for the present herb. The aims of this study were (1) to develop a novel method for preparing essential oils and dry extracts from German chamomile flowers, (2) to reveal the phytochemical composition of such extracts, and (3) to verify the analgesic and soporific activity of extracts in vivo with a rodent animal model. Furthermore, our study aims to gain knowledge of the ethnomedical status of chamomile in the past and presence. Essential oils and dry extracts were successfully prepared from the tincture and aqueous extracts obtained after hydrodistillation and from a tincture powder. Total 22 phenolic compounds (7 hydroxycinnamic acids, 13 flavonoids and 2 phenolic acids), were found in the dry extracts by using UPLC-MS/MS. Total 9 main terpenoids were identified in the chamomile oil, and these terpenoids represent the chemotype rich in bisabolol oxides A and B. In the highest yield, the ratio of phenolic compounds and extract was in the range of 1:14-1:16 and triple extraction was performed. In in-vivo studies with mice and rats, the extracts showed analgesic activity and improvements in sleep. The highest sedative effect in rodents was found with the extract prepared by using a 70% aqueous ethanol solution for extraction. The administration of such extract at the dose of 50 mg/kg significantly prolonged the sleeping time in rats.

Biomass as a whole offers a more diverse potential for valorisation than any other renew-able energy source. As one of the stages in the separation of bio-oil involves the liquid mixture of acetol and acetic acid, and as both components are particularly well suited for valorisation, a hybrid method has been developed for their separation with a high purity level through an approach combining liquid-liquid extraction and rectification. In order to design and simulate the flowsheet, the ChemCAD 7.0 simulation software has been used. Sensitive analyses have been carried out to investigate the influence of the different pa-rameters in the rectification columns such as the reflux ratio, the feed stage location, and the vapour/bottom molar flow ratio. The effect of different extractants and of their excess on the separation process as well as the possibility of regenerating the extractant has also been studied. Tri-n-octylamine has accordingly been selected as a separating agent which has been fully recycled. The end result for separating an initial 48/52 wt% ace-tol/acetic-acid liquid mixture has been acetol with a purity of 99.4 wt% and acetic acid with a purity of 100 wt%.

Fire outbreaks continue to cause damage despite the improvements in fire-detection tools and algorithms. It is still challenging to implement a well performing and optimized approach, which is sufficiently accurate, and has tractable complexity and low false alarming rate. Small amount of fire and identification of fire from a long distance is also a challenge in previously proposed techniques. In this study, we propose a novel hybrid model based on Convolutional Neural Networks (CNN) to detect and analyze fire intensity. 21 convolutional layers, 24 Rectified Linear Unit (ReLU) layers, 6 pooling layers, 3 fully connected layers, 2 dropout layers, and a softmax layer are included in the proposed 57-layer CNN model. Our proposed model performs instance segmentation in order to distinguish between fire and non-fire events. To reduce the intricacy of the proposed model, we also propose a key-frame extraction algorithm. The proposed model uses Internet of Things (IoT) devices to alert the relevant person by calculating the severity of fire. Our proposed model is tested on a publicly available dataset having fire and normal videos. The achievement of 95.25 % classification accuracy, 0.09% False Positive Rate (FPR), 0.65 percent False Negative Rate (FNR), and a prediction time of 0.08 seconds validates the proposed system.

Machinery degradation assessment can offer meaningful prognosis and health management in-formation. Although numerous machine prediction models based on artificial intelligence have emerged in recent years, they still face a series of challenges: (1) Many models continue to rely on manual feature extraction. (2) Deep learning models still struggle with long sequence prediction tasks. (3) Health indicators are inefficient for remaining useful life (RUL) prediction with cross-operational environments when dealing with high-dimensional datasets as inputs. This research proposes a health indicator construction methodology based on a transformer self-attention transfer network (TSTN). This methodology can directly deal with the high-dimensional raw dataset and keep all the information without missing when the signals are taken as the input of the diagnosis and prognosis model. First, we design an encoder with a long-term and short-term self-attention mechanism to capture crucial time-varying information from a high-dimensional dataset. Second, we propose an estimator that can map the embedding from the encoder output to the estimated degradation trends. Then, we present a domain dis-criminator to extract invariant features from different machine operating conditions. The case studies with the FEMTO-ST bearing dataset and the Monte Carlo method for RUL prediction during the degradation process are conducted. The experiment results fully exhibited the signif-icant advantages of the proposed method compared to other state-of-the-art techniques.

Human Action Recognition is widely used in multiple fields to recognize activities and extract spatial and temporal information. This paper focuses on analyzing various methods as well as provides extensive knowledge of the foundational concepts of the HAR. A dataset is also very crucial for any research study so we discussed the popular dataset and its features in this paper.

To address the deficiency of existing relation extraction models in effectively extracting relational triplets pertaining to railway traffic knowledge in Tibet, this paper constructs a Tibet Railway Traffic text dataset and provides an enhanced relation extraction model. The proposed model incorporates subject feature enhancement and relational attention mechanisms. It leverages a pre-trained model as the embedding layer to obtain vector representations of text. Subsequently, the subject is extracted and its semantic information is augmented using an LSTM neural network. Furthermore, during object extraction, the multi-head attention mechanism enables the model to prioritize relations associated with the aforementioned features. Finally, objects are extracted based on the subjects and relations. The proposed method has been comprehensively evaluated on multiple datasets, including the Tibet Railway Traffic text dataset and two public datasets. The results on the Tibet dataset achieves an F1-score of 93.3\%, surpassing the baseline model CasRel by 0.8\%, indicating a superior applicability of the proposed model. On the other hand, the model achieves F1-scores of 91.1\% and 92.6\% on two public datasets, NYT and WebNLG, respectively, outperforming the baseline CasRel by 1.5\% and 0.8\%, which highlights the good generalization ability of the proposed model.

The reagents and raw materials used, as well as the products obtained (bio-oil, reaction condensates, polyols and sugar phases) were characterized by elemental analysis, infrared spectroscopy, thermogravimetry and high performance liquid chromatography with mass spectrometry. The heating value of the bio-oils is higher than that of the original biomass (higher heating value of Eucalyptus sawdust bio-oil 29 MJ/kg versus 19.5 MJ/kg of the original Eucalyptus sawdust). The analyses of the bio-oils allowed to identify the presence of high added-value compounds, such as levulinic acid and furfural. Finally, a study of the accelerated aging of the liquefied biomass showed that the biofuel density increases with the storage time due to the occurrence of repolymerization reactions.

Deep convolutional neural networks (CNN) are favored methods widely used in medical image processing due to their assured shown performance. Recently, the emergence of new lung diseases and the possibility of early detection of their symptoms has attracted many researchers to classify diseases by training deep CNNs on lung CT images. The trained networks are expected to distinguish between lung indications in different diseases, especially at the early stages of them. With the hope of achieving this purpose, we proposed an efficient deep CNN called AFEX-Net with adaptive feature extraction layers that successfully extract distinguishing features and classify chest CT images. The efficiency of the proposed network has two aspects: it is a lightweight network with low number of parameters and fast training and it has adaptive pooling layers and adaptive activation functions to increase its level of compatibility to the input data. The proposed network has been evaluated on a dataset with more than 10K chest CT slices, while an efficient pre-processing method is developed to remove any bias from the images. Additionally, we evaluated the performance of the proposed model on the public COVID-CTset dataset to prove the generalisability of our model. The obtained results confirm the competence of the proposed network in confronting medical images, where prompt and accurate learning is required.

Proso millet starch (PMS) as an unconventional and underutilized cereal starch is becoming increasingly popular worldwide due to its health-promoting properties. This review summarizes research progress in the isolation, characterization, modification, and applications of PMS. PMS can be isolated from proso millet grains by acidic, alkaline, or enzymatic extraction. PMS exhibits typical A-type polymorphic diffraction patterns and shows polygonal and spherical granular structures with a granule size of 0.3-17 µm. PMS is modified by chemical, physical, and biological methods. The native and modified PMS are analyzed for swelling power, solubility, pasting properties, thermal properties, retrogradation, freeze-thaw stability, and in vitro digestibility. The improved physicochemical, structural, and functional properties and digestibility of modified PMS are discussed in terms of their suitability for specific applications. The potential applications of native and modified PMS in food and non-food products are presented. Future prospects for research and commercial use of PMS in the food industry are also highlighted.